Source document: https://docs-lawep.s3.us-east-2.amazonaws.com/1697647718015.pdf (Bahamas)
83340_00i-xxiv 3/31/05 8:33 PM Page i Bahamas Living Conditions Survey 2001 Department of Statistics 2004 Nassau, The Bahamas 83340_00i-xxiv 3/31/05 8:33 PM Page ii © 2004 Department of Statistics Clarence Bain Building Thompson Boulevard Nassau, The Bahamas All rights reserved Produced by the Department of Statistics Cover photos (clockwise from left): The Bahamas Tourist Office—Curious faces (Hope Town, Abaco), Typical picket-fenced house (Harbour Island, Eleuthera), Fernandez Bay (Cat Island), Androsia, a type of batik, hung out to dry (Andros); Ministry of Education—Students at lunch vendor, H.O.
Nash Junior High School (Nassau, New Providence).

Map: Design Unit, Inter-American Development Bank, Washington, D.C., USA Printing and cover design: Automated Graphics Systems, Inc., White Plains, Maryland, USA ISBN: 976-95136-0-1 83340_00i-xxiv 3/31/05 8:33 PM Page iii This report is dedicated to the memory of Portia E. Johnson, whose untimely death in 2003 represents an irreparable loss for the Department of Statistics and the Commonwealth of The Bahamas.
Portia’s statistical research and analytical skills, proven leadership, creativity, and tireless dedication to her country’s people were critical in launching this first-ever Bahamas Living Conditions Survey.

Her colleagues and friends pay her homage.

83340_00i-xxiv 3/31/05 8:33 PM Page iv 83340_00i-xxiv 3/31/05 8:33 PM Page v Contents Foreword .

.

.

.

.

.

.

.

.

.

.

.

.

.

.

.

.

.

.

.

.

.

.

.

.

.

.

.

.

.

.

.

.

.

.

.

.

.

.

.

.

.

.

.

.

.

.

.

.

.

.

.

.

.

.


xiii Preface .

.

.

.

.

.

.

.

.

.

.

.

.

.

.

.

.

.

.

.

.

.

.

.

.

.

.

.

.

.

.

.

.

.

.

.

.

.

.

.

.

.

.

.

.

.

.

.

.

.

.

.

.

.

.

.

.

.

.

.

.

.

.

.

.

.

.

.

.

.

.

.

.

.

.

.

.

.

.

.

.

.

.

xv Acknowledgments .

.

.

.

.

.

.

.

.

.

.

.

.

.

.

.

.

.

.

.

.

.

.

.

.

.

.

.

.

.

.

.

.

.


.

.

.

.

.

.

.

.

.

.

.

.

.

.

.

.

.

.

.

.

.

.

.

xvii Abbreviations and Acronyms .

.

.

.

.

.

.

.

.

.

.

.

.

.

.

.

.

.

.

.

.

.

.

.

.

.

.

.

.

.

.

.

.

.

.

.

.

.

.

.

.

.

.

.

.

.

.

.

.

.

.

.

.

.

.

.

.

.

.

.

.

.

.

.

.

.

xix Key Numerical Codes .

.

.

.

.

.

.

.

.

.

.

.

.

.

.

.

.

.

.

.

.

.

.

.

.

.

.

.

.


.

.

.

.

.

.

.

.

.

.

.

.

.

.

.

.

.

.

.

.

.

.

.

.

.

.

.

.

.

.

xix Notes to the Tables .

.

.

.

.

.

.

.

.

.

.

.

.

.

.

.

.

.

.

.

.

.

.

.

.

.

.

.

.

.

.

.

.

.

.

.

.

.

.

.

.

.

.

.

.

.

.

.

.

.

.

.

.

.

.

.

.

.

.

.

.

.

.

.

.

.

.

.

.

.

.

.

.

.xix Who are the poor in The Bahamas?

.

.

.

.

.

.

.

.

.

.

.

.

.

.

.

.

.

.


.

.

.

.

.

.

.

.

.

.

.

.

.

.

.

.

.

.

.

.

.

.

.

.

.

.

.

xx Executive Summary .

.

.

.

.

.

.

.

.

.

.

.

.

.

.

.

.

.

.

.

.

.

.

.

.

.

.

.

.

.

.

.

.

.

.

.

.

.

.

.

.

.

.

.

.

.

.

.

.

.

.

.

.

.

.

.

.

.

xxi Chapter 1.

Population Patterns: Regional Distribution and Migration .

.

.

.

.

.

.

.

.

.

.

.

.

.

.

.

.

.

.

.

1 Underlying Patterns .

.

.

.

.

.

.

.

.


.

.

.

.

.

.

.

.

.

.

.

.

.

.

.

.

.

.

.

.

.

.

.

.

.

.

.

.

.

.

.

.

.

.

.

.

.

.

.

.

.

.

.

.

.

.

.

.

.

.

.

.

.

.

.

.

1 Regional Population Distribution .

.

.

.

.

.

.

.

.

.

.

.

.

.

.

.

.

.

.

.

.

.

.

.

.

.

.

.

.

.

.

.

.

.

.

.

.

.

.

.

.

.

.

.

.

.

.

.

.

.

.

.

.

.

1 Age and Sex Distribution .

.

.

.

.

.

.

.

.

.

.

.

.

.

.

.

.

.

.

.

.

.

.


.

.

.

.

.

.

.

.

.

.

.

.

.

.

.

.

.

.

.

.

.

.

.

.

.

.

.

.

.

.

.

.

2 Nationality .

.

.

.

.

.

.

.

.

.

.

.

.

.

.

.

.

.

.

.

.

.

.

.

.

.

.

.

.

.

.

.

.

.

.

.

.

.

.

.

.

.

.

.

.

.

.

.

.

.

.

.

.

.

.

.

.

.

.

.

.

.

.

.

.

.

.

.

.

.

.

.

4 Distribution by Household Characteristics .

.

.

.

.

.

.

.

.

.

.

.

.

.

.

.

.

.

.

.

.

.

.

.

.


.

.

.

.

.

.

.

.

.

.

.

.

.

.

4 Migration Overview .

.

.

.

.

.

.

.

.

.

.

.

.

.

.

.

.

.

.

.

.

.

.

.

.

.

.

.

.

.

.

.

.

.

.

.

.

.

.

.

.

.

.

.

.

.

.

.

.

.

.

.

.

.

.

.

.

.

.

.

.

.

.

.

.

8 Direction for Policy and Research .

.

.

.

.

.

.

.

.

.

.

.

.

.

.

.

.

.

.

.

.

.

.

.

.

.

.

.

.

.

.

.

.

.

.

.

.

.

.

.

.

.

.

.

.

.

.

.


11 References .

.

.

.

.

.

.

.

.

.

.

.

.

.

.

.

.

.

.

.

.

.

.

.

.

.

.

.

.

.

.

.

.

.

.

.

.

.

.

.

.

.

.

.

.

.

.

.

.

.

.

.

.

.

.

.

.

.

.

.

.

.

.

.

.

.

.

.

.

.

.

12 For Further Reading .

.

.

.

.

.

.

.

.

.

.

.

.

.

.

.

.

.

.

.

.

.

.

.

.

.

.

.

.

.

.

.

.

.

.

.

.

.

.

.

.

.

.

.

.

.

.

.

.

.

.

.

.

.

.

.

.

.

.

.

.

.

.


12 Chapter 2.

Poverty Estimates and Policy Issues .

.

.

.

.

.

.

.

.

.

.

.

.

.

.

.

.

.

.

.

.

.

.

.

.

.

.

.

.

.

.

.

.

.

.

.

.

13 Welfare Measure and Poverty Line .

.

.

.

.

.

.

.

.

.

.

.

.

.

.

.

.

.

.

.

.

.

.

.

.

.

.

.

.

.

.

.

.

.

.

.

.

.

.

.

.

.

.

.

.

.

.

.

.

.

.

.

.

13 Estimates and Indicators .

.

.

.

.

.

.

.

.

.

.

.

.

.

.

.

.

.

.

.

.

.

.

.

.

.


.

.

.

.

.

.

.

.

.

.

.

.

.

.

.

.

.

.

.

.

.

.

.

.

.

14 Poverty Profile: Household Characteristics .

.

.

.

.

.

.

.

.

.

.

.

.

.

.

.

.

.

.

.

.

.

.

.

.

.

.

.

.

.

.

.

.

.

.

.

.

.

.

.

.

.

.

.

.

.

.

14 Characteristics of Household Head .

.

.

.

.

.

.

.

.

.

.

.

.

.

.

.

.

.

.

.

.

.

.

.

.

.

.

.

.

.

.

.

.

.

.

.

.

.

.

.

.

.

.

.

.


18 Expenditure Level and Composition .

.

.

.

.

.

.

.

.

.

.

.

.

.

.

.

.

.

.

.

.

.

.

.

.

.

.

.

.

.

.

.

.

.

.

.

.

.

.

.

.

.

.

.

.

.

.

.

.

.

.

20 Access to Social Programmes .

.

.

.

.

.

.

.

.

.

.

.

.

.

.

.

.

.

.

.

.

.

.

.

.

.

.

.

.

.

.

.

.

.

.

.

.

.

.

.

.

.

.

.

.

.

.

.

.

.

.

.

.

.

.

.

.

22 Children’s Health and Schooling .

.

.

.

.


.

.

.

.

.

.

.

.

.

.

.

.

.

.

.

.

.

.

.

.

.

.

.

.

.

.

.

.

.

.

.

.

.

.

.

.

.

.

.

.

.

.

.

.

.

.

.

.

.

23 Adult Education and Training for Non-heads .

.

.

.

.

.

.

.

.

.

.

.

.

.

.

.

.

.

.

.

.

.

.

.

.

.

.

.

.

.

.

.

.

.

.

.

.

.

.

.

.

.

.

.

25 Housing Characteristics .

.

.

.

.

.

.

.

.

.

.

.

.

.

.

.

.

.

.

.

.

.

.

.

.

.

.

.

.

.

.

.

.

.

.

.

.


.

.

.

.

26 Key Results and Policy Implications .

.

.

.

.

.

.

.

.

.

.

.

.

.

.

.

.

.

.

.

.

.

.

.

.

.

.

.

.

.

.

.

.

.

.

.

.

.

.

.

.

.

.

.

.

.

.

.

.

.

.

.

28 Appendix: Method for Calculating the Poverty Line .

.

.

.

.

.

.

.

.

.

.

.

.

.

.

.

.

.

.

.

.

.

.

.

.

.

.

.

.

.

.

.

.

.

.

.

.

.

.

31 Chapter 3.


Household Expenditure Data: Patterns for Analysis .

.

.

.

.

.

.

.

.

.

.

.

.

.

.

.

.

.

.

.

.

.

.

.

35 Issues for Data Interpretation .

.

.

.

.

.

.

.

.

.

.

.

.

.

.

.

.

.

.

.

.

.

.

.

.

.

.

.

.

.

.

.

.

.

.

.

.

.

.

.

.

.

.

.

.

.

.

.

.

.

.

.

.

.

.

.

.

35 Data-collection Methods and Categories .

.

.

.

.

.

.

.

.

.

.

.

.

.

.

.

.

.

.

.

.

.

.

.

.

.

.

.

.

.

.


.

.

.

36 Findings: Food Expenditure Patterns .

.

.

.

.

.

.

.

.

.

.

.

.

.

.

.

.

.

.

.

.

.

.

.

.

.

.

.

.

.

.

.

.

.

.

.

.

.

.

.

.

.

.

.

.

.

.

.

.

.

.

37 Findings: Non-food Expenditures .

.

.

.

.

.

.

.

.

.

.

.

.

.

.

.

.

.

.

.

.

.

.

.

.

.

.

.

.

.

.

.

.

.

.

.

.

.

.

.

.

.

.

.

.

.

.

.

.

.

.

.

.


39 Findings: Food and Non-food Expenditures .

.

.

.

.

.

.

.

.

.

.

.

.

.

.

.

.

.

.

.

.

.

.

.

.

.

.

.

.

.

.

.

.

.

.

.

.

.

.

.

.

.

.

.

.

49 Conclusions .

.

.

.

.

.

.

.

.

.

.

.

.

.

.

.

.

.

.

.

.

.

.

.

.

.

.

.

.

.

.

.

.

.

.

.

.

.

.

.

.

.

.

.

.

.

.

.

.

.

.

.

.

.

.

.

.

.

.

.

.

.

.

.

.

.

.

.

.

.

52 Looking Ahead: Conditions for Data Application .

.

.
.

.

.

.

.

.

.

.

.

.

.

.

.

.

.

.

.

.

.

.

.

.

.

.

.

.

.

.

.

.

.

.

.

.

.

.

.

.

.

.

53 Appendix .

.

.

.

.

.

.

.

.

.

.

.

.

.

.

.

.

.

.

.

.

.

.

.

.

.

.

.

.

.

.

.

.

.

.

.

.

.

.

.

.

.

.

.

.

.

.

.

.

.

.

.

.

.

.

.

.

.

.

.

.

.

.

.

.

.

.

.

.

.

.

.

54 Chapter 4.

Health Status: Socioeconomic Analysis .

.

.

.

.

.

.

.

.

.

.

.

.

.

.

.

.

.

.

.

.

.

.

.

.

.

.

.

.

.

.

.

.

.


61 Self-reported Health Status .

.

.

.

.

.

.

.

.

.

.

.

.

.

.

.

.

.

.

.

.

.

.

.

.

.

.

.

.

.

.

.

.

.

.

.

.

.

.

.

.

.

.

.

.

.

.

.

.

.

.

.

.

.

.

.

.

.

61 Child Health .

.

.

.

.

.

.

.

.

.

.

.

.

.

.

.

.

.

.

.

.

.

.

.

.

.

.

.

.

.

.

.

.

.

.

.

.

.

.

.

.

.

.

.

.

.

.

.

.

.

.

.

.

.

.

.

.

.

.

.

.

.

.

.

.

.

.

.

.


65 Nutritional Status of Children .

.

.

.

.

.

.

.

.

.

.

.

.

.

.

.

.

.

.

.

.

.

.

.

.

.

.

.

.

.

.

.

.

.

.

.

.

.

.

.

.

.

.

.

.

.

.

.

.

.

.

.

.

.

.

.

68 v 83340_00i-xxiv 3/31/05 8:33 PM Page vi vi | Nutritional Status of Adolescents .

.

.

.

.

.

.

.

.

.

.

.

.

.

.

.

.

.

.

.

.

.

.

.

.

.

.

.

.

.

.

.

.

.

.

.

.

.

.

.

.

.

.

.

.

.

.

.

.

.

.

.

.

.


70 Nutritional Status of Adults .

.

.

.

.

.

.

.

.

.

.

.

.

.

.

.

.

.

.

.

.

.

.

.

.

.

.

.

.

.

.

.

.

.

.

.

.

.

.

.

.

.

.

.

.

.

.

.

.

.

.

.

.

.

.

.

.

.

71 Breastfeeding .

.

.

.

.

.

.

.

.

.

.

.

.

.

.

.

.

.

.

.

.

.

.

.

.

.

.

.

.

.

.

.

.

.

.

.

.

.

.

.

.

.

.

.

.

.

.

.

.

.

.

.

.

.

.

.

.

.

.

.

.

.

.

.

.

.

.

.

.
73 Female Reproductive Health .

.

.

.

.

.

.

.

.

.

.

.

.

.

.

.

.

.

.

.

.

.

.

.

.

.

.

.

.

.

.

.

.

.

.

.

.

.

.

.

.

.

.

.

.

.

.

.

.

.

.

.

.

.

.

.

.

74 Health-services Use and Expenditure .

.

.

.

.

.

.

.

.

.

.

.

.

.

.

.

.

.

.

.

.

.

.

.

.

.

.

.

.

.

.

.

.

.

.

.

.

.

.

.

.

.

.

.

.

.

.

.

.

.

.

76 Health Insurance Coverage .

.

.

.

.

.

.

.

.

.

.

.

.


.

.

.

.

.

.

.

.

.

.

.

.

.

.

.

.

.

.

.

.

.

.

.

.

.

.

.

.

.

.

.

.

.

.

.

.

.

.

.

.

.

.

.

.

81 Conclusions and Policy Recommendations .

.

.

.

.

.

.

.

.

.

.

.

.

.

.

.

.

.

.

.

.

.

.

.

.

.

.

.

.

.

.

.

.

.

.

.

.

.

.

.

.

.

.

.

.

.

82 References .

.

.

.

.

.

.

.

.

.

.

.

.

.

.

.

.

.

.

.

.

.

.

.

.

.

.

.

.

.

.

.

.

.

.

.

.

.

.

.

.

.

.

.

.

.

.

.

.


85 For Further Reading .

.

.

.

.

.

.

.

.

.

.

.

.

.

.

.

.

.

.

.

.

.

.

.

.

.

.

.

.

.

.

.

.

.

.

.

.

.

.

.

.

.

.

.

.

.

.

.

.

.

.

.

.

.

.

.

.

.

.

.

.

.

.

85 Chapter 5.

Educational System: Achievements and Challenges .

.

.

.

.

.

.

.

.

.

.

.

.

.

.

.

.

.

.

.

.

.

.

.

.


87 Government Initiatives and Their Implementation .

.

.

.

.

.

.

.

.

.

.

.

.

.

.

.

.

.

.

.

.

.

.

.

.

.

.

.

.

.

.

.

.

.

.

.

.

.

.

.

87 Survey Context .

.

.

.

.

.

.

.

.

.

.

.

.

.

.

.

.

.

.

.

.

.

.

.

.

.

.

.

.

.

.

.

.

.

.

.

.

.

.

.

.

.

.

.

.

.

.

.

.

.

.

.

.

.

.

.

.

.

.

.

.

.

.

.

.

.

.

88 Enrolment .

.

.

.

.

.

.

.

.

.

.

.

.

.

.

.

.

.

.

.


.

.

.

.

.

.

.

.

.

.

.

.

.

.

.

.

.

.

.

.

.

.

.

.

.

.

.

.

.

.

.

.

.

.

.

.

.

.

.

.

.

.

.

.

.

.

.

.

89 Distance Traveled .

.

.

.

.

.

.

.

.

.

.

.

.

.

.

.

.

.

.

.

.

.

.

.

.

.

.

.

.

.

.

.

.

.

.

.

.

.

.

.

.

.

.

.

.

.

.

.

.

.

.

.

.

.

.

.

.

.

.

.

.

.

.

.

.

92 Mode of Transport .

.

.

.

.

.

.

.

.

.

.

.

.

.

.

.

.

.

.

.

.

.

.

.


.

.

.

.

.

.

.

.

.

.

.

.

.

.

.

.

.

.

.

.

.

.

.

.

.

.

.

.

.

.

.

.

.

94 School Attendance in Last Five Days .

.

.

.

.

.

.

.

.

.

.

.

.

.

.

.

.

.

.

.

.

.

.

.

.

.

.

.

.

.

.

.

.

.

.

.

.

.

.

.

.

.

.

.

.

.

.

.

.

.

.

96 Grade Repetition .

.

.

.

.

.

.

.

.

.

.

.

.

.

.

.

.

.

.

.

.

.

.

.

.

.

.

.

.

.

.

.

.

.

.

.

.

.

.

.

.

.

.


98 Selected Outcomes by Schooling of Mother .

.

.

.

.

.

.

.

.

.

.

.

.

.

.

.

.

.

.

.

.

.

.

.

.

.

.

.

.

.

.

.

.

.

.

.

.

.

.

.

.

.

.

.

.

.

98 Unenrolled Youth .

.

.

.

.

.

.

.

.

.

.

.

.

.

.

.

.

.

.

.

.

.

.

.

.

.

.

.

.

.

.

.

.

.

.

.

.

.

.

.

.

.

.

.

.

.

.

.

.

.

.

.

.

.

.

.

.

.

.

.

.

.

.

.


100 National Educational Expenditure .

.

.

.

.

.

.

.

.

.

.

.

.

.

.

.

.

.

.

.

.

.

.

.

.

.

.

.

.

.

.

.

.

.

.

.

.

.

.

.

.

.

.

.

.

.

.

.

.

.

.

.

102 Financial Assistance .

.

.

.

.

.

.

.

.

.

.

.

.

.

.

.

.

.

.

.

.

.

.

.

.

.

.

.

.

.

.

.

.

.

.

.

.

.

.

.

.

.

.

.

.

.

.

.

.

.

.

.

.

.

.

.

.

.

.

.

.

.

.

105 Conclusions .

.

.

.

.

.

.

.

.

.

.

.

.


.

.

.

.

.

.

.

.

.

.

.

.

.

.

.

.

.

.

.

.

.

.

.

.

.

.

.

.

.

.

.

.

.

.

.

.

.

.

.

.

.

.

.

.

.

.

.

.

.

.

.

.

.

.

.

107 Meeting the Challenge: Policy and Research Recommendations .

.

.

.

.

.

.

.

.

.

.

.

.

.

.

.

.

.

.

.

.

.

.

.

.

.

.

.

.

107 For Further Reading .

.

.

.

.

.

.

.

.

.

.

.

.

.

.

.

.

.

.

.

.

.

.

.

.

.

.

.

.

.

.

.

.

.

.

.

.

.

.

.

.

.

.

.

.


108 Chapter 6.

Employment Data Analysis: Toward Equitable Planning .

.

.

.

.

.

.

.

.

.

.

.

.

.

.

.

.

.

.

109 Target Population .

.

.

.

.

.

.

.

.

.

.

.

.

.

.

.

.

.

.

.

.

.

.

.

.

.

.

.

.

.

.

.

.

.

.

.

.

.

.

.

.

.

.

.

.

.

.

.

.

.

.

.

.

.

.

.

.

.

.

.

.

.

.

.

109 Unattached Youths .

.

.

.

.

.

.

.

.

.

.

.

.

.

.

.

.


.

.

.

.

.

.

.

.

.

.

.

.

.

.

.

.

.

.

.

.

.

.

.

.

.

.

.

.

.

.

.

.

.

.

.

.

.

.

.

.

.

.

.

.

.

112 Children 10–14 Years of Age .

.

.

.

.

.

.

.

.

.

.

.

.

.

.

.

.

.

.

.

.

.

.

.

.

.

.

.

.

.

.

.

.

.

.

.

.

.

.

.

.

.

.

.

.

.

.

.

.

.

.

.

.

.

.

.

114 Employment Characteristics .

.

.

.

.

.

.

.

.

.

.

.

.

.

.

.

.

.

.

.

.

.

.

.

.

.

.

.

.

.

.

.


.

.

.

.

.

.

.

.

.

115 Employment Status .

.

.

.

.

.

.

.

.

.

.

.

.

.

.

.

.

.

.

.

.

.

.

.

.

.

.

.

.

.

.

.

.

.

.

.

.

.

.

.

.

.

.

.

.

.

.

.

.

.

.

.

.

.

.

.

.

.

.

.

.

.

.

120 Employed Persons by Industry .

.

.

.

.

.

.

.

.

.

.

.

.

.

.

.

.

.

.

.

.

.

.

.

.

.

.

.

.

.

.

.

.

.

.

.

.

.

.

.

.

.

.

.

.

.

.

.

.


120 Employed Persons by Occupation .

.

.

.

.

.

.

.

.

.

.

.

.

.

.

.

.

.

.

.

.

.

.

.

.

.

.

.

.

.

.

.

.

.

.

.

.

.

.

.

.

.

.

.

.

.

.

.

.

.

.

.

123 Mode of Transport .

.

.

.

.

.

.

.

.

.

.

.

.

.

.

.

.

.

.

.

.

.

.

.

.

.

.

.

.

.

.

.

.

.

.

.

.

.

.

.

.

.

.

.

.

.

.

.

.

.

.

.

.

.

.

.

.

.

.

.

.

.

.

126 Time Spent En Route .

.

.

.

.

.


.

.

.

.

.

.

.

.

.

.

.

.

.

.

.

.

.

.

.

.

.

.

.

.

.

.

.

.

.

.

.

.

.

.

.

.

.

.

.

.

.

.

.

.

.

.

.

.

.

.

.

.

.

.

.

126 Hours Worked .

.

.

.

.

.

.

.

.

.

.

.

.

.

.

.

.

.

.

.

.

.

.

.

.

.

.

.

.

.

.

.

.

.

.

.

.

.

.

.

.

.

.

.

.

.

.

.

.

.

.

.

.

.

.

.

.

.

.

.

.

.

.

.

.

.

.

127 Conclusions and Policy Implications .

.

.

.

.

.

.

.

.

.

.

.

.


.

.

.

.

.

.

.

.

.

.

.

.

.

.

.

.

.

.

.

.

.

.

.

.

.

.

.

.

.

.

.

.

.

.

.

.

127 References .

.

.

.

.

.

.

.

.

.

.

.

.

.

.

.

.

.

.

.

.

.

.

.

.

.

.

.

.

.

.

.

.

.

.

.

.

.

.

.

.

.

.

.

.

.

.

.

.

.

.

.

.

.

.

.

.

.

.

.

.

.

.

.

.

.

.

.

.

.

129 For Further Reading .

.

.

.

.

.

.

.

.

.

.

.

.

.

.

.

.

.

.

.

.

.

.

.

.

.

.

.

.

.

.

.

.

.

.

.

.

.

.


.

129 Chapter 7.

Community Services and Social Programmes: Accessibility Analysis .

.

.

.

.

.

.

.

.

.

.

131 Access To Community Services .

.

.

.

.

.

.

.

.

.

.

.

.

.

.

.

.

.

.

.

.

.

.

.

.

.

.

.

.

.

.

.

.

.

.

.

.

.

.

.

.

.

.

.

.

.

.

.

.

.

.

.

.

.

131 Access to Social Programmes .

.

.

.

.

.

.

.

.

.

.

.

.

.

.

.

.


.

.

.

.

.

.

.

.

.

.

.

.

.

.

.

.

.

.

.

.

.

.

.

.

.

.

.

.

.

.

.

.

.

.

.

.

.

.

137 Appendix .

.

.

.

.

.

.

.

.

.

.

.

.

.

.

.

.

.

.

.

.

.

.

.

.

.

.

.

.

.

.

.

.

.

.

.

.

.

.

.

.

.

.

.

.

.

.

.

.

.

.

.

.

.

.

.

.

.

.

.

.

.

.

.

.

.

.

.

.

.

.

141 83340_00i-xxiv 3/31/05 8:33 PM Page vii vii | Chapter 8.

Housing Variables for Policy Formulation .

.

.

.

.

.
.

.

.

.

.

.

.

.

.

.

.

.

.

.

.

.

.

.

.

.

.

.

.

.

.

.

.

.

.

.

155 Dwelling Type .

.

.

.

.

.

.

.

.

.

.

.

.

.

.

.

.

.

.

.

.

.

.

.

.

.

.

.

.

.

.

.

.

.

.

.

.

.

.

.

.

.

.

.

.

.

.

.

.

.

.

.

.

.

.

.

.

.

.

.

.

.

.

.

.

.

.

155 Construction Materials .

.

.

.

.

.

.

.

.

.

.

.

.

.

.

.

.

.

.

.

.

.

.

.

.

.

.

.

.

.

.

.

.

.

.

.

.

.

.

.

.

.

.

.

.

.

.

.

.

.

.

.

.

.

.

.

.

.

.


156 Tenure Type .

.

.

.

.

.

.

.

.

.

.

.

.

.

.

.

.

.

.

.

.

.

.

.

.

.

.

.

.

.

.

.

.

.

.

.

.

.

.

.

.

.

.

.

.

.

.

.

.

.

.

.

.

.

.

.

.

.

.

.

.

.

.

.

.

.

.

.

158 Water Supply .

.

.

.

.

.

.

.

.

.

.

.

.

.

.

.

.

.

.

.

.

.

.

.

.

.

.

.

.

.

.

.

.

.

.

.

.

.

.

.

.

.

.

.

.

.

.

.

.

.

.

.

.

.

.

.

.

.

.

.

.

.

.

.

.

.

.

.


158 Sanitary Facilities .

.

.

.

.

.

.

.

.

.

.

.

.

.

.

.

.

.

.

.

.

.

.

.

.

.

.

.

.

.

.

.

.

.

.

.

.

.

.

.

.

.

.

.

.

.

.

.

.

.

.

.

.

.

.

.

.

.

.

.

.

.

.

.

.

162 Lighting and Cooking Fuels .

.

.

.

.

.

.

.

.

.

.

.

.

.

.

.

.

.

.

.

.

.

.

.

.

.

.

.

.

.

.

.

.

.

.

.

.

.

.

.

.

.

.

.

.

.

.

.

.

.

.

.

.

.

.

.

.

163 Telephone Service .

.

.

.

.

.


.

.

.

.

.

.

.

.

.

.

.

.

.

.

.

.

.

.

.

.

.

.

.

.

.

.

.

.

.

.

.

.

.

.

.

.

.

.

.

.

.

.

.

.

.

.

.

.

.

.

.

.

.

.

.

.

.

.

163 Garbage Disposal .

.

.

.

.

.

.

.

.

.

.

.

.

.

.

.

.

.

.

.

.

.

.

.

.

.

.

.

.

.

.

.

.

.

.

.

.

.

.

.

.

.

.

.

.

.

.

.

.

.

.

.

.

.

.

.

.

.

.

.

.

.

.

.

.

164 Household Expenditure on Utilities and Services .

.

.

.

.

.
.

.

.

.

.

.

.

.

.

.

.

.

.

.

.

.

.

.

.

.

.

.

.

.

.

.

.

.

.

.

.

.

.

.

.

.

.

.

.

.

165 Selected Indicators .

.

.

.

.

.

.

.

.

.

.

.

.

.

.

.

.

.

.

.

.

.

.

.

.

.

.

.

.

.

.

.

.

.

.

.

.

.

.

.

.

.

.

.

.

.

.

.

.

.

.

.

.

.

.

.

.

.

.

.

.

.

.

.

169 Summary of Findings .

.

.

.

.

.

.

.

.

.

.

.

.

.

.

.

.

.

.

.

.

.

.

.

.

.

.

.

.

.

.

.

.

.

.

.

.

.

.

.

.

.

.

.

.

.

.

.

.

.

.


172 The Challenges Ahead .

.

.

.

.

.

.

.

.

.

.

.

.

.

.

.

.

.

.

.

.

.

.

.

.

.

.

.

.

.

.

.

.

.

.

.

.

.

.

.

.

.

.

.

.

.

.

.

.

.

.

.

.

.

.

.

.

.

.

.

.

173 References .

.

.

.

.

.

.

.

.

.

.

.

.

.

.

.

.

.

.

.

.

.

.

.

.

.

.

.

.

.

.

.

.

.

.

.

.

.

.

.

.

.

.

.

.

.

.

.

.

.

.

.

.

.

.

.

.

.

.

.

.

.

.

.

.

.

.

.

.


173 Technical Appendix .

.

.

.

.

.

.

.

.

.

.

.

.

.

.

.

.

.

.

.

.

.

.

.

.

.

.

.

.

.

.

.

.

.

.

.

.

.

.

.

.

.

.

.

.

.

.

.

.

.

.

.

.

.

.

.

.

175 A.

Survey Design and Methodology .

.

.

.

.

.

.

.

.

.

.

.

.

.

.

.

.

.

.

.

.

.

.

.

.

.

.

.

.

.

.

.

.

.

.

.

.

.

.

.

.

.

.

.

.

.

.

.

.

.

.

175 B.

Other Technical Considerations .

.

.

.

.

.

.

.

.

.

.

.


.

.

.

.

.

.

.

.

.

.

.

.

.

.

.

.

.

.

.

.

.

.

.

.

.

.

.

.

.

.

.

.

.

.

.

.

.

.

179 For Further Reading .

.

.

.

.

.

.

.

.

.

.

.

.

.

.

.

.

.

.

.

.

.

.

.

.

.

.

.

.

.

.

.

.

.

.

.

.

.

.

.

.

.

.

.

.

.

.

.

.

.

.

.

.

.

.

.

.

.

.

.

.

.

188 About the Authors .

.

.

.

.

.

.

.

.

.

.

.

.

.

.

.

.

.

.

.

.

.

.

.

.

.

.

.

.

.

.

.

.

.

.

.

.

.

.

.

.

.

.

.


189 Map .

.

.

.

.

.

.

.

.

.

.

.

.

.

.

.

.

.

.

.

.

.

.

.

.

.

.

.

.

.

.

.

.

.

.

.

.

.

.

.

.

.

.

.

.

.

.

.

.

.

.

.

.

.

.

.

.

.

.

.

.

.

.

.

.

.

.

.

.193 83340_00i-xxiv 3/31/05 8:33 PM Page viii viii | Tables 1-1.

Population Distribution, by Region and Quintile .

.

.

.

.

.

.

.

.

.

.

.

.

.

.

.

.

.

.

.

.

.

.

.

.

.

.

.

.

.

.


2 1-2.

Population Distribution, Showing Within-region Quintile Distribution .

.

.

.

.

.

.

.

.

.

.

.

.

.

.

.

.

.

3 1-3.

Population Distribution; by Age, Sex, and Region .

.

.

.

.

.

.

.

.

.

.

.

.

.

.

.

.

.

.

.

.

.

.

.

.

.

.

.

.

.

.

.

.

.

.

3 1-4.

Sex Ratios, by Age Group and Region .

.

.

.

.

.

.

.

.

.

.

.

.

.

.

.

.

.

.

.

.

.

.

.

.

.

.

.

.

.

.

.

.

.

.

.

.


4 Population; by Nationality, Region, and Quintile .

.

.

.

.

.

.

.

.

.

.

.

.

.

.

.

.

.

.

.

.

.

.

.

.

.

.

.

.

.

.

.

.

.

.

.

4 1-5.

1-6.

Household Size; by Sex of Head, Region, and Quintile .

.

.

.

.

.

.

.

.

.

.

.

.

.

.

.

.

.

.

.

.

.

.

.

.

.

.

.

.

.

.

5 1-7.

Characteristics of Heads of One-person Households .

.

.

.

.

.

.

.

.

.

.

.

.

.

.

.

.

.

.

.

.


.

.

.

.

.

.

.

.

.

5 1-8.

Mean Household Composition; by Age, Sex of Head, and Region .

.

.

.

.

.

.

.

.

.

.

.

.

.

.

.

.

.

.

.

.

.

.

6 Selected Characteristics of Household Heads, by Region and Quintile .

.

.

.

.

.

.

.

.

.

.

.

.

.

.

.

.

.

.

.

7 1-9.

1-10.

Household Characteristics, by Sex of Head .

.

.

.

.

.

.

.

.

.

.

.

.

.

.

.

.

.

.

.

.

.

.

.

.

.

.

.

.

.

.

.

.


8 1-11.

Recent Immigrants, by Place of Birth and Sex .

.

.

.

.

.

.

.

.

.

.

.

.

.

.

.

.

.

.

.

.

.

.

.

.

.

.

.

.

.

.

.

.

.

.

.

.

.

9 1-12.

Recent Immigrants, by Place of Birth and Region of First Entry .

.

.

.

.

.

.

.

.

.

.

.

.

.

.

.

.

.

.

.

.

.

.

.

.

9 1-13.

Distribution of Recent Immigrants, by Age and Sex .

.

.

.

.

.

.

.

.

.

.

.

.

.

.

.

.

.

.

.

.


.

.

.

.

.

.

.

.

.

9 1-14.

Reasons for Immigration (%), by Place of Birth and Quintile .

.

.

.

.

.

.

.

.

.

.

.

.

.

.

.

.

.

.

.

.

.

.

.

.

.

10 1-15.

Recent Immigrants, by Place of Birth and Quintile .

.

.

.

.

.

.

.

.

.

.

.

.

.

.

.

.

.

.

.

.

.

.

.

.

.

.

.

.

.

.

.

.

.

10 1-16.

Recent Immigrants, by Place of Birth and Quintile Distribution within Immigrant Group .

.

.

.

.

.
.

.

.

.

.

.

.

.

.

.

.

.

.

.

.

.

.

.

.

.

.

.

.

.

.

.

.

.

.

.

.

.

.

.

.

.

.

.

.

.

.

.

.

.

.

.

.

.

.

.

.

.

10 1-17.

Age Group of Recent Internal Migrants, by Sex .

.

.

.

.

.

.

.

.

.

.

.

.

.

.

.

.

.

.

.

.

.

.

.

.

.

.

.

.

.

.

.

.

.

.

.

11 1-18.

Quintile of Recent Internal Migrants, by Sex .

.

.

.

.

.

.

.

.

.

.

.

.

.

.

.

.

.

.

.

.

.

.

.

.

.

.

.

.

.

.

.

.

.

.

.

.

.

11 1-19.


Reasons for Internal Migration, by Quintile .

.

.

.

.

.

.

.

.

.

.

.

.

.

.

.

.

.

.

.

.

.

.

.

.

.

.

.

.

.

.

.

.

.

.

.

.

.

.

11 1-20.

Current Region of Residence of Recent Internal Migrants, by Sex .

.

.

.

.

.

.

.

.

.

.

.

.

.

.

.

.

.

.

.

.

.

11 2-1.

National and Regional Poverty Indicators, by Population Characteristic (%) .

.

.

.

.

.

.

.

.

.

.

.

.

.

15 2-2.


Poverty Rates, by Household Characteristic (%) .

.

.

.

.

.

.

.

.

.

.

.

.

.

.

.

.

.

.

.

.

.

.

.

.

.

.

.

.

.

.

.

.

.

.

.

16 2-3.

Household-level Poverty Rates .

.

.

.

.

.

.

.

.

.

.

.

.

.

.

.

.

.

.

.

.

.

.

.

.

.

.

.

.

.

.

.

.

.

.

.

.

.

.

.

.

.

.

.

.

.

.

.

.

17 2-4.

Dependency Ratios, by Poverty Status .

.

.

.

.

.

.

.

.

.

.

.

.

.

.

.

.

.

.

.

.

.

.

.

.

.


.

.

.

.

.

.

.

.

17 2-5.

Economic Activity, by Poverty Status .

.

.

.

.

.

.

.

.

.

.

.

.

.

.

.

.

.

.

.

.

.

.

.

.

.

.

.

.

.

.

.

.

.

.

.

.

.

.

.

.

.

.

.

18 2-6A.

Poverty Rates, by Household Head Schooling .

.

.

.

.

.

.

.

.

.

.

.

.

.

.

.

.

.

.

.

.

.

.

.

.

.

.

.

.

.

.

.

.

.

.

.

.

19 2-6B.

Poverty Rates, by Household Head Gender .

.

.

.

.

.
.

.

.

.

.

.

.

.

.

.

.

.

.

.

.

.

.

.

.

.

.

.

.

.

.

.

.

.

.

.

.

.

.

.

.

.

.

.

19 2-7.

Economic Activity of Household Heads, by Poverty Status .

.

.

.

.

.

.

.

.

.

.

.

.

.

.

.

.

.

.

.

.

.

.

.

.

.

.

20 2-8.

Mean and Distribution of Per-capita Household Expenditure .

.

.

.

.

.

.

.

.

.

.

.

.

.

.

.

.

.

.

.

.

.

.

.

.

21 2-9.

Expenditure and Budget Shares, by Poverty Status .

.

.

.

.

.

.

.

.

.

.

.

.

.

.

.

.

.


.

.

.

.

.

.

.

.

.

.

.

.

.

.

.

21 Food Expenditure and Shares, by Poverty Status .

.

.

.

.

.

.

.

.

.

.

.

.

.

.

.

.

.

.

.

.

.

.

.

.

.

.

.

.

.

.

.

.

.

.

.

22 2-10.

2-11.

Access to Social Programmes, by Poverty Status .

.

.

.

.

.

.

.

.

.

.

.

.

.

.

.

.

.

.

.

.

.

.

.

.

.

.

.

.

.

.

.

.

.

.

.

22 2-12.

Participation in National School Lunch Programme .

.

.

.

.

.

.

.


.

.

.

.

.

.

.

.

.

.

.

.

.

.

.

.

.

.

.

.

.

.

.

.

23 2-13.

School Outcomes for Children Ages 0–18 .

.

.

.

.

.

.

.

.

.

.

.

.

.

.

.

.

.

.

.

.

.

.

.

.

.

.

.

.

.

.

.

.

.

.

.

.

.

.

.

23 2-14.

Health Outcomes for Pre-school Children .

.

.

.

.

.

.

.

.

.

.

.

.

.

.

.

.

.

.

.

.

.

.

.

.

.

.

.

.

.

.

.

.

.

.

.

.

.

.

.

24 2-15.

Education and Training of Non-head Adults, Ages 25–65 .

.

.

.

.
.

.

.

.

.

.

.

.

.

.

.

.

.

.

.

.

.

.

.

.

.

.

.

.

.

.

.

25 2-16.

Education and Training of Young Adults, Ages 19–24 .

.

.

.

.

.

.

.

.

.

.

.

.

.

.

.

.

.

.

.

.

.

.

.

.

.

.

.

.

.

.

26 2-17.

Housing Characteristics, by Poverty Status .

.

.

.

.

.

.

.

.

.

.

.

.

.

.

.

.

.

.

.

.

.

.

.

.

.

.

.

.

.

.

.

.

.

.

.

.

.

.

.

27 2-18.

Leakage Rates for Various Beneficiary Selection Mechanisms (%) .

.

.

.

.

.

.

.

.

.

.


.

.

.

.

.

.

.

.

.

.

.

30 2-A1.

Caloric and Cost Distribution of Low-cost Food Basket, by Major Food Group .

.

.

.

.

.

.

.

.

.

.

31 2-A2.

Items in Low-cost Food Basket .

.

.

.

.

.

.

.

.

.

.

.

.

.

.

.

.

.

.

.

.

.

.

.

.

.

.

.

.

.

.

.

.

.

.

.

.

.

.

.

.

.

.

.

.

.

.

.

.

32 2-A3.

Diet of Composition of Low-cost Food Basket .

.

.

.

.

.

.

.

.

.

.

.

.

.

.

.

.

.

.

.

.

.

.

.

.

.

.

.

.


33 2-A4.

Poverty Lines and Rates for Selected LAC Countries and U.S. .

.

.

.

.

.

.

.

.

.

.

.

.

.

.

.

.

.

.

.

.

.

.

.

.

33 83340_00i-xxiv 3/31/05 8:33 PM Page ix ix | 3-1.

Average Household Food Expenditures, Share in Total, and Household Consumption .

.

.

.

.

.

.

.

.

.

.

.

.

.

.

.

.

.

.

.

.

.

.

.

.

.

.

.

.

.

.

.

.

.

.

.

.

.

.

.

.

.

.

.

.

.

.

.

.

.

37 3-2.


Mean Individual Expenditures on Food Eaten Away from Home .

.

.

.

.

.

.

.

.

.

.

.

.

.

.

.

.

.

.

.

.

.

.

39 3-3A.

Mean Shares of Food Groups in Total Food Expenditure, by Various Factors .

.

.

.

.

.

.

.

.

.

.

.

.

40 3-3B.

Mean (Nominal) Expenditure on Types of Food, by Various Factors .

.

.

.

.

.

.

.

.

.

.

.

.

.

.

.

.

.

.

.

42 3-4.


Average Household Non-food Expenditures, Share in Total, and Household Consumption .

.

.

.

.

.

.

.

.

.

.

.

.

.

.

.

.

.

.

.

.

.

.

.

.

.

.

.

.

.

.

.

.

.

.

.

.

.

.

.

.

.

.

.

.

.

.

.

.

44 3-5A.

Mean Share of Non-food Groups in Total Non-food Expenditure .

.

.

.

.

.

.

.

.

.

.

.

.

.

.

.

.

.

.

.

.

.

45 3-5B.

Mean Annual Expenditure (B$) on Non-food Items .

.

.

.

.

.

.

.

.

.

.

.

.


.

.

.

.

.

.

.

.

.

.

.

.

.

.

.

.

.

.

.

47 3-6A.

Shares of Food and Non-food Items in Total Expenditures .

.

.

.

.

.

.

.

.

.

.

.

.

.

.

.

.

.

.

.

.

.

.

.

.

.

.

50 3-6B.

Total Annual (Nominal) Expenditures .

.

.

.

.

.

.

.

.

.

.

.

.

.

.

.

.

.

.

.

.

.

.

.

.

.

.

.

.

.

.

.

.

.

.

.

.

.

.

.

.

.

.

51 3-A1.

Average Household Food Expenditures, Share in Total, and Household Consumption .

.
.

.

.

.

.

.

.

.

.

.

.

.

.

.

.

.

.

.

.

.

.

.

.

.

.

.

.

.

.

.

.

.

.

.

.

.

.

.

.

.

.

.

.

.

.

.

.

.

.

54 3-A2.

Average Household Non-food Expenditures, Share in Total, 4-1.

4-2.

4-3.

4-4. and Household Consumption .

.

.

.

.

.

.

.

.

.

.

.

.

.

.

.

.

.

.

.

.

.

.

.

.

.

.

.

.

.

.

.

.

.

.

.

.

.

.

.

.

.

.

.

.

.

.

.

.

.

57 Ill Residents Who Sought Care (%), by Population Characteristic .

.

.

.

.

.

.

.

.

.

.


.

.

.

.

.

.

.

.

.

.

62 Proportion of Respondents with a Disability or Injury in Past 12 Months .

.

.

.

.

.

.

.

.

.

.

.

.

.

.

.

63 Self-reported Diabetes and Hypertension and Proportion Treated .

.

.

.

.

.

.

.

.

.

.

.

.

.

.

.

.

.

.

.

.

.

64 Proportion of Children Five Years and Younger with Common Illnesses in Past Four Weeks .

.

.

.

.

.

.

.

.

.

.

.

.

.

.

.

.

.

.

.

.

.

.

.

.

.

.

.

.

.

.

.

.

.

.


.

.

.

.

.

.

.

66 4-5.

Immunization Coverage Amongst Children 0–71 Months .

.

.

.

.

.

.

.

.

.

.

.

.

.

.

.

.

.

.

.

.

.

.

.

.

.

.

.

67 4-6A.

National Immunization Coverage Levels, 1997–2000 .

.

.

.

.

.

.

.

.

.

.

.

.

.

.

.

.

.

.

.

.

.

.

.

.

.

.

.

.

.

.

68 4-6B.

Vaccine-preventable Cases Reported, 1997–2000 .

.

.

.

.

.

.

.

.

.

.

.


.

.

.

.

.

.

.

.

.

.

.

.

.

.

.

.

.

.

.

.

.

.

68 Low and High Z-scores for Children 2–10 Years of Age .

.

.

.

.

.

.

.

.

.

.

.

.

.

.

.

.

.

.

.

.

.

.

.

.

.

.

.

.

.

69 4-7.

Body Mass Indices for Adolescents, Ages 11–20 Years .

.

.

.

.

.

.

.

.

.

.

.

.

.

.

.

.

.

.

.

.

.

.

.

.

.

.

.

.

.

.

70 4-8.

4-9.

Body Mass Indices for All Persons, Ages 21–60 Years .

.

.

.

.

.

.

.

.

.

.

.

.

.

.


.

.

.

.

.

.

.

.

.

.

.

.

.

.

.

.

72 4-10.

Body Mass Indices of Males, Ages 21–60 Years .

.

.

.

.

.

.

.

.

.

.

.

.

.

.

.

.

.

.

.

.

.

.

.

.

.

.

.

.

.

.

.

.

.

.

.

.

72 4-11.

Body Mass Indices of Females, Ages 21–60 Years .

.

.

.

.

.

.

.

.

.

.

.

.

.

.

.

.

.

.

.

.

.

.

.

.

.

.

.

.

.

.

.

.

.

.

73 4-12.

Breastfeeding Incidence and Median Months of Exclusive Breastfeeding .

.

.

.
.

.

.

.

.

.

.

.

.

.

.

.

.

.

.

.

74 4-13.

Percentage of Females, 10–49 Years of Age, Who Have Ever Been Pregnant .

.

.

.

.

.

.

.

.

.

.

.

.

.

75 4-14.

Outpatients (during Past Four Weeks) and Inpatients (during Past 12 Months) .

.

.

.

.

.

.

.

.

.

.

.

76 4-15.

Outpatient Visits to Health Facilities in Past Four Weeks, by Facility and Sector .

.

.

.

.

.

.

.

.

.

.

77 4-16A.

Average Expenditure on Outpatient and Inpatient Care .

.

.

.

.

.

.

.

.

.


.

.

.

.

.

.

.

.

.

.

.

.

.

.

.

.

.

.

.

78 4-16B.

Average Annual Health Expenditure and Percentage Distribution, by Expenditure Type .

.

.

.

.

.

.

.

.

.

.

.

.

.

.

.

.

.

.

.

.

.

.

.

.

.

.

.

.

.

.

.

.

.

.

.

.

.

.

.

.

.

.

.

.

.

.

.

.

.

.

.

.

.

.

.

79 4-17.

Proportion of Respondents with Medical and Dental Coverage .

.

.

.

.

.

.

.

.

.

.

.

.

.

.

.

.

.

.

.

.

.

.

.

81 4-18.


Average Medical Insurance Payments .

.

.

.

.

.

.

.

.

.

.

.

.

.

.

.

.

.

.

.

.

.

.

.

.

.

.

.

.

.

.

.

.

.

.

.

.

.

.

.

.

.

.

.

82 Characteristics of Individuals 0–24 Years of Age .

.

.

.

.

.

.

.

.

.

.

.

.

.

.

.

.

.

.

.

.

.

.

.

.

.

.

.

.

.

.

.

.

.

.

.

89 5-1.

Enrolment Rates for Individuals 0–24 Years of Age .

.

.

.

.

.

.

.

.

.

.

.

.

.

.

.

.

.

.

.

.

.

.

.

.


90 5-2.

Type of School, by Age (Those Currently Enrolled) .

.

.

.

.

.

.

.

.

.

.

.

.

.

.

.

.

.

.

.

.

.

.

.

.

.

.

.

.

.

.

.

.

91 5-3.

5-4.

Current Public-school Enrolment, by Type and Level (Ages 0–24) .

.

.

.

.

.

.

.

.

.

.

.

.

.

.

.

.

.

.

.

.

.

92 5-5.

Distance (Miles) to School, by Level .

.

.

.

.

.

.

.

.

.

.

.

.

.

.

.

.

.

.

.

.

.

.

.

.

.

.

.

.

.


.

.

93 5-6.

Mode of Transport to School, by Level of Schooling .

.

.

.

.

.

.

.

.

.

.

.

.

.

.

.

.

.

.

.

.

.

.

.

.

.

.

.

.

.

.

.

95 Attendance in Last Five Days, by Level of Schooling .

.

.

.

.

.

.

.

.

.

.

.

.

.

.

.

.

.

.

.

.

.

.

.

.

.

.

.

.

.

.

.

96 5-7.

5-8.

Percentage Who Did Not Attend All Five Days, by Level and Reason .

.

.

.

.

.

.

.

.

.


.

.

.

.

.

.

.

.

97 5-9.

Grade Repetition (%) (Currently Enrolled Students) .

.

.

.

.

.

.

.

.

.

.

.

.

.

.

.

.

.

.

.

.

.

.

.

.

.

.

.

.

.

.

.

99 83340_00i-xxiv 3/31/05 8:33 PM Page x x | 5-10.

Selected Schooling Outcomes, by Schooling of Mother .

.

.

.

.

.

.

.

.

.

.

.

.

.

.

.

.

.

.

.

.

.

.

.

.

.

.

.

.

.

99 5-11.

Reported Reasons for Unenrolment (ages 5–16 years) .

.

.

.

.

.

.

.

.

.

.

.

.

.

.

.


.

.

.

.

.

.

.

.

.

.

.

.

.

100 5-12.

Education of Youth Not in School (ages 16–24) .

.

.

.

.

.

.

.

.

.

.

.

.

.

.

.

.

.

.

.

.

.

.

.

.

.

.

.

.

.

.

.

.

.

.

100 5-13.

Qualifications of Youth Not in School (ages 16–24) .

.

.

.

.

.

.

.

.

.

.

.

.

.

.

.

.

.

.

.

.

.

.

.

.

.

.

.

.

.

.

.

101 5-14.

Educational Expenses of Those Enrolled (Ages 0–21), by Level .

.

.

.

.

.

.

.

.

.

.


.

.

.

.

.

.

.

.

.

.

.

103 5-15.

Net Expenditures for Enrolled Children (Ages 0–21) .

.

.

.

.

.

.

.

.

.

.

.

.

.

.

.

.

.

.

.

.

.

.

.

.

.

.

.

.

.

.

106 5-16.

Financial Aid Received (Enrolled Children, Ages 0–21) .

.

.

.

.

.

.

.

.

.

.

.

.

.

.

.

.

.

.

.

.

.

.

.

.

.

.

.

.

106 Population Profile: Individuals 15 Years and Older .

.

.

.

.

.

.

.

.

.

.

.

.

.

.

.

.

.

.

.

.

.

.

.

.

.

.

.


110 6-1.

Labour-force Participation of Persons 15 Years and Older, by Selected Variables .

.

.

.

.

.

.

.

.

.

111 6-2.

Labour-force Characteristics, Persons 15 Years and Older .

.

.

.

.

.

.

.

.

.

.

.

.

.

.

.

.

.

.

.

.

.

.

.

.

.

.

.

111 6-3.

Labour-force Participation of Persons 15 Years and Older, by Age Group and Region .

.

.

.

.

.

112 6-4.

Status of Youths 16–24 Years Old .

.

.

.

.

.

.

.


.

.

.

.

.

.

.

.

.

.

.

.

.

.

.

.

.

.

.

.

.

.

.

.

.

.

.

.

.

.

.

.

.

.

.

.

113 6-5.

Educational Status of Total and Unattached Youths, 16–24 Years of Age .

.

.

.

.

.

.

.

.

.

.

.

.

.

.

.

113 6-6.

Labour-force Profile, Persons 10–14 Years of Age .

.

.

.

.

.

.

.

.

.

.

.

.

.

.

.

.

.

.

.

.

.

.

.

.

.

.

.

.

.

.

.

.

.

114 6-7.

Unemployed Persons 15 Years and Older, by Selected Variables .

.

.

.

.

.

.
.

.

.

.

.

.

.

.

.

.

.

.

.

.

.

.

.

.

.

.

.

.

114 6-8 Characteristics of Unemployed Persons, Ages 15 Years and Older .

.

.

.

.

.

.

.

.

.

.

.

.

.

.

.

.

.

.

.

.

115 6-9 6-10.

Percentage Distribution of Labour Force of Persons 15 Years and Older .

.

.

.

.

.

.

.

.

.

.

.

.

.

.

.

115 6-11.

Quintile Distribution of Employed Persons, by Region .

.

.

.

.

.

.

.

.

.

.

.

.

.

.

.

.

.

.

.

.

.

.

.

.

.

.

.

.

116 6-12.


Regional Distribution of Employed Persons 15 Years and Older, by Nationality and Sex .

.

.

.

.

.

.

.

.

.

.

.

.

.

.

.

.

.

.

.

.

.

.

.

.

.

.

.

.

.

.

.

.

.

.

.

.

.

.

.

.

.

.

.

.

.

.

.

.

.

.

.

.

.

117 6-13.

Quintile Distribution of Employed Persons 15 Years and Older, by Nationality .

.

.

.

.

.

.

.

.

.

.

117 Educational Status of Employed Persons 15 Years and Older, by Sex .

.

.

.

.

.

.

.


.

.

.

.

.

.

.

.

.

.

117 6-14.

Educational Status of Employed Persons, by Sex Within Regions .

.

.

.

.

.

.

.

.

.

.

.

.

.

.

.

.

.

.

.

.

.

118 6-15.

Educational Status of Employed Persons, by Sex Within Quintiles .

.

.

.

.

.

.

.

.

.

.

.

.

.

.

.

.

.

.

.

.

119 6-16.

Educational Status of Employed Persons, by Sex Across Quintiles .

.

.

.

.

.

.

.

.

.

.

.

.

.

.

.

.

.

.

.

.

119 6-17.


Primary Employment Status of Employed Persons, by Sex within 6-18.

Regions and Quintiles .

.

.

.

.

.

.

.

.

.

.

.

.

.

.

.

.

.

.

.

.

.

.

.

.

.

.

.

.

.

.

.

.

.

.

.

.

.

.

.

.

.

.

.

.

.

.

.

.

.

.

.

.

.

.

121 6-19.

Occupational Distribution of Self-employed Persons, by Region and Sex within Quintile .

.

.

.

.

.

.

.

.

.

.

.

.

.

.

.

.

.

.

.

.

.

.

.

.

.

.

.

.

.

.

.

.

.

.

.

.


122 Primary Industry of Employed Persons, by Sex .

.

.

.

.

.

.

.

.

.

.

.

.

.

.

.

.

.

.

.

.

.

.

.

.

.

.

.

.

.

.

.

.

.

.

.

123 6-20.

Primary Industry of Employed Persons, within Region and Quintile .

.

.

.

.

.

.

.

.

.

.

.

.

.

.

.

.

.

.

124 6-21.

Primary Occupation of Employed Persons, by Sex .

.

.

.

.

.

.

.

.

.

.

.

.

.

.

.

.

.

.

.

.

.

.

.

.

.

.

.


124 6-22.

Primary Occupation of Employed Persons, by Region and Quintile .

.

.

.

.

.

.

.

.

.

.

.

.

.

.

.

.

.

.

.

125 6-23.

Primary Occupation of Employed Persons, Across Regions and Quintiles .

.

.

.

.

.

.

.

.

.

.

.

.

.

.

125 6-24.

6-25.

Transport Method and Time for Employed Persons 15 Years and Older .

.

.

.

.

.

.

.

.

.

.

.

.

.

.

.

126 6-26.


Mean Weekly Hours in Primary Activity, by Selected Demographic Characteristics .

.

.

.

.

.

.

.

.

.

.

.

.

.

.

.

.

.

.

.

.

.

.

.

.

.

.

.

.

.

.

.

.

.

.

.

.

.

.

.

.

.

.

.

.

.

.

.

.

127 6-27.

Mean Weekly Hours in Primary Occupation and Industry, by Sex .

.

.

.

.

.

.

.

.

.

.

.

.

.

.

.

.

.

.

.

.

128 7-1.

Median Household Distance to Facilities, by Region .

.

.

.

.

.

.

.

.

.

.

.

.

.


.

.

.

.

.

.

.

.

.

.

.

.

.

.

.

.

132 7-2.

Median Distance to Facilities, by Quintile .

.

.

.

.

.

.

.

.

.

.

.

.

.

.

.

.

.

.

.

.

.

.

.

.

.

.

.

.

.

.

.

.

.

.

.

.

.

.

133 7-3.

Household Ownership of Cars, by Region and Quintile .

.

.

.

.

.

.

.

.

.

.

.

.

.

.

.

.

.

.

.

.

.

.

.

.

.

.

.

.

133 7-4A.

Households’ Mode of Transport (%) To Access Facilities, by Region .

.

.

.

.

.

.

.

.


.

.

.

.

.

.

.

.

.

134 7-4B.

Households’ Mode of Transport (%) To Access Facilities, by Quintile .

.

.

.

.

.

.

.

.

.

.

.

.

.

.

.

.

.

134 Summary of Travel Costs to Access Selected Facilities, by Region .

.

.

.

.

.

.

.

.

.

.

.

.

.

.

.

.

.

.

.

.

.

135 7-5.

7-6.

Summary of Median Distances and Time Required To Access Facilities, by Region .

.

.

.

.

.

.

.

136 7-7.

Median Time to Access Facilities, by Quintile .

.

.

.

.

.
.

.

.

.

.

.

.

.

.

.

.

.

.

.

.

.

.

.

.

.

.

.

.

.

.

.

.

.

.

.

.

.

.

.

.

136 83340_00i-xxiv 3/31/05 8:33 PM Page xi xi | 7-A1.

Distance to Nearest Health Facility, by Region and Quintile .

.

.

.

.

.

.

.

.

.

.

.

.

.

.

.

.

.

.

.

.

.

.

.

.

141 7-A2.

Means of Transportation to Nearest Health Facility, by Region and Quintile .

.

.

.

.

.

.

.

.

.

.

.

.

141 7-A3.

Average Cost of Travel to Health Facility .

.

.

.

.

.

.

.

.

.

.

.

.


.

.

.

.

.

.

.

.

.

.

.

.

.

.

.

.

.

.

.

.

.

.

.

.

.

.

142 7-A4.

Travel Time to Nearest Health Facility, by Region and Quintile .

.

.

.

.

.

.

.

.

.

.

.

.

.

.

.

.

.

.

.

.

.

142 7-A5.

Distance to Nearest School, by Region and Quintile .

.

.

.

.

.

.

.

.

.

.

.

.

.

.

.

.

.

.

.

.

.

.

.

.

.

.

.

.

.

.

143 7-A6.

Means of Transportation to Nearest School .

.

.

.

.

.

.

.

.

.

.

.

.

.

.

.


.

.

.

.

.

.

.

.

.

.

.

.

.

.

.

.

.

.

.

.

.

143 7-A7.

Average Cost of Travel to School .

.

.

.

.

.

.

.

.

.

.

.

.

.

.

.

.

.

.

.

.

.

.

.

.

.

.

.

.

.

.

.

.

.

.

.

.

.

.

.

.

.

.

.

.

.

144 7-A8.

Travel Time to Nearest School .

.

.

.

.

.

.

.

.

.

.

.

.

.

.

.

.

.

.

.

.

.

.

.

.

.

.

.

.

.

.

.

.

.

.

.

.

.

.

.

.

.

.

.

.

.

.

.

144 7-A9.


Distance to Nearest Post Office or Police Station .

.

.

.

.

.

.

.

.

.

.

.

.

.

.

.

.

.

.

.

.

.

.

.

.

.

.

.

.

.

.

.

.

.

145 7-A10.

Means of Transportation to Nearest Post Office or Police Station .

.

.

.

.

.

.

.

.

.

.

.

.

.

.

.

.

.

.

.

.

145 7-A11.

Average Cost of Travel to Post Office or Police Station .

.

.

.

.

.

.

.

.

.

.

.

.

.

.

.

.

.

.

.

.

.

.

.

.

.

.

.

.

.

146 7-A12.


Travel Time to Nearest Post Office or Police Station .

.

.

.

.

.

.

.

.

.

.

.

.

.

.

.

.

.

.

.

.

.

.

.

.

.

.

.

.

.

.

146 7-A13.

Distance to Nearest Mail Boat or Government Complex .

.

.

.

.

.

.

.

.

.

.

.

.

.

.

.

.

.

.

.

.

.

.

.

.

.

.

.

147 7-A14.

Means of Transportation to Nearest Mail Boat or Government Complex .

.

.

.

.

.

.

.

.

.

.

.

.

.

.

.

147 7-A15.


Average Cost of Travel to Mail Boat or Government Complex .

.

.

.

.

.

.

.

.

.

.

.

.

.

.

.

.

.

.

.

.

.

.

.

148 7-A16.

Travel Time to Nearest Mail Boat or Government Complex .

.

.

.

.

.

.

.

.

.

.

.

.

.

.

.

.

.

.

.

.

.

.

.

.

148 7-A17.

Distance to Nearest Grocery Store or Banking Facility .

.

.

.

.

.

.

.

.

.

.

.

.

.

.

.

.

.

.

.

.

.

.

.

.

.

.

.

.

.

149 7-A18.


Means of Transportation to Nearest Grocery Store or Banking Facility .

.

.

.

.

.

.

.

.

.

.

.

.

.

.

.

.

149 7-A19.

Average Cost of Travel to Facility .

.

.

.

.

.

.

.

.

.

.

.

.

.

.

.

.

.

.

.

.

.

.

.

.

.

.

.

.

.

.

.

.

.

.

.

.

.

.

.

.

.

.

.

.

.

150 7-A20.

Travel Time to Nearest Grocery Store or Banking Facility .

.

.

.

.

.

.

.

.

.

.

.

.

.

.

.

.

.

.

.

.

.

.

.

.

.

.


150 7-A21.

Responses to Survey Question: “Ever Heard of Social Program?” .

.

.

.

.

.

.

.

.

.

.

.

.

.

.

.

.

.

.

.

.

.

151 7-A22.

Receipt of Social Benefits .

.

.

.

.

.

.

.

.

.

.

.

.

.

.

.

.

.

.

.

.

.

.

.

.

.

.

.

.

.

.

.

.

.

.

.

.

.

.

.

.

.

.

.

.

.

.

.

.

.

.

.

151 7-A23.

Beneficiary Characteristics for All Social Programs .

.

.

.

.

.

.

.

.

.

.

.

.

.

.

.

.

.

.

.

.


.

.

.

.

.

.

.

.

152 7-A24.

Participation in National School Lunch Programme, by Selected Variables .

.

.

.

.

.

.

.

.

.

.

.

.

.

153 7-A25.

Participation of Children Ages 5–16 in National School Lunch Programme .

.

.

.

.

.

.

.

.

.

.

.

.

.

154 7-A26.

Responses to Question: “What Does Child Usually Have for Lunch?” .

.

.

.

.

.

.

.

.

.

.

.

.

.

.

.

.

.


154 Percentage Distribution of Dwelling Type .

.

.

.

.

.

.

.

.

.

.

.

.

.

.

.

.

.

.

.

.

.

.

.

.

.

.

.

.

.

.

.

.

.

.

.

.

.

.

156 8-1.

Percentage Distribution of Outer-wall Construction Materials .

.

.

.

.

.

.

.

.

.

.

.

.

.

.

.

.

.

.

.

.

.

.

.

156 8-2.

Percentage Distribution of Roofing Materials .

.

.

.

.

.

.

.

.

.

.

.

.

.

.

.

.

.

.

.

.

.

.

.

.

.

.

.

.

.

.

.

.

.


157 8-3.

Percentage Distribution of Flooring Materials .

.

.

.

.

.

.

.

.

.

.

.

.

.

.

.

.

.

.

.

.

.

.

.

.

.

.

.

.

.

.

.

.

.

.

.

157 8-4.

Percentage Distribution, by Tenure Type .

.

.

.

.

.

.

.

.

.

.

.

.

.

.

.

.

.

.

.

.

.

.

.

.

.

.

.

.

.

.

.

.

.

.

.

.

.

.

.

158 8-5.

Percentage Distribution of Type of Dwelling, by Tenure Type .

.

.

.

.

.

.

.

.

.

.

.

.

.

.

.


.

.

.

.

.

.

.

159 8-6.

Percentage Distribution of Bathing Water Source, by Region and Quintile .

.

.

.

.

.

.

.

.

.

.

.

.

.

161 8-7.

Percentage Distribution of Source of Drinking Water, by Region and Quintile .

.

.

.

.

.

.

.

.

.

.

161 8-8.

8-9.

Percentage Distribution of Sanitary Facility Types .

.

.

.

.

.

.

.

.

.

.

.

.

.

.

.

.

.

.

.

.

.

.

.

.

.

.

.

.

.

.

.

.

162 8-10.


Comparison of Indoor and Outdoor Toilet Facilities, by Region and Quintile (%) .

.

.

.

.

.

.

.

162 Percentage Distribution of Lighting Source, by Region and Quintile .

.

.

.

.

.

.

.

.

.

.

.

.

.

.

.

.

.

.

163 8-11.

Percentage Distribution of Cooking Fuel Use, by Region and Quintile .

.

.

.

.

.

.

.

.

.

.

.

.

.

.

.

.

163 8-12.

Percentage Distribution of Household Telephone Access, by Region and Quintile .

.

.

.
.

.

.

.

.

.

.

.

164 8-13.

8-14.

Percentage Distribution of Household Disposal Type, by Region and Quintile .

.

.

.

.

.

.

.

.

.

.

164 8-15.

Mean Monthly Expenditure on Utilities and Services (B$) .

.

.

.

.

.

.

.

.

.

.

.

.

.

.

.

.

.

.

.

.

.

.

.

.

.

.

165 8-16A.

Mean Monthly Expenditure on Shelter Costs and Real Property Tax (B$) .

.

.

.

.

.

.

.

.

.

.

.

.

.

.

166 8-16B.


Expenditure on Shelter Costs and Real Property Tax (% Total Monthly Expenditure) .

.

.

.

.

.

166 8-17.

Mean Monthly Expenditure on Other Household Operational Expenses .

.

.

.

.

.

.

.

.

.

.

.

.

.

.

.

167 Percentage Distribution of Durable Goods Ownership, by Region and Quintile .

.

.

.

.

.

.

.

.

.

169 8-18.

Percentage Distribution of Consumer Durables Ownership .

.

.

.

.

.

.

.

.

.

.

.

.

.

.

.

.

.

.

.

.


.

170 8-19.

83340_00i-xxiv 3/31/05 8:33 PM Page xii xii | Figures Boxes 8-20.

Ranking of the 10 Most Commonly Owned Durable Goods, by Region and Quintile .

.

.

.

.

.

170 8-21.

Housing Quality Index, by Region .

.

.

.

.

.

.

.

.

.

.

.

.

.

.

.

.

.

.

.

.

.

.

.

.

.

.

.

.

.

.

.

.

.

.

.

.

.

.

.

.

.

.

.

.

171 8-22.

Housing Quality Index, by Quintile .

.

.

.

.

.

.

.

.

.

.

.

.

.

.

.

.


.

.

.

.

.

.

.

.

.

.

.

.

.

.

.

.

.

.

.

.

.

.

.

.

.

.

171 Percentage Distribution of Crowding, by Region and Quintile .

.

.

.

.

.

.

.

.

.

.

.

.

.

.

.

.

.

.

.

.

.

.

.

172 8-23.

A-A1.

Systematic Selection of Enumeration Districts .

.

.

.

.

.

.

.

.

.

.

.

.

.

.

.

.

.

.

.

.

.

.

.

.

.

.

.

.

.

.

.

.

.

.

.

177 A-A2.

Non-response Distribution .

.

.

.

.

.

.

.

.

.

.

.

.


.

.

.

.

.

.

.

.

.

.

.

.

.

.

.

.

.

.

.

.

.

.

.

.

.

.

.

.

.

.

.

.

.

.

.

.

.

178 Island Deflators Used, BLCS 21751 .

.

.

.

.

.

.

.

.

.

.

.

.

.

.

.

.

.

.

.

.

.

.

.

.

.

.

.

.

.

.

.

.

.

.

.

.

.

.

.

.

.

.

.

179 A-B1.

A-B2.

Items Included in Commodity Groups and Subgroups, BLCS 21771 .

.

.

.

.

.

.

.

.

.

.

.

.

.

.

.

.

.

180 A-B3.

Contents of Dataset AGGREGATES.dta, BLCS 21781 .


.

.

.

.

.

.

.

.

.

.

.

.

.

.

.

.

.

.

.

.

.

.

.

.

.

.

.

.

181 A-B4.

Data Sets, BLCS 2001 .

.

.

.

.

.

.

.

.

.

.

.

.

.

.

.

.

.

.

.

.

.

.

.

.

.

.

.

.

.

.

.

.

.

.

.

.

.

.

.

.

.

.

.

.

.

.

.

.

.

.

.

.

.

182 A-B5.

Variables Used To Construct Consumption Expenditure Aggregates, BLCS 2001 .

.

.

.

.

.

.

.

.

183 A-B6.

Estimation of Consumption Expenditure Aggregates, BLCS 2001 .
.

.

.

.

.

.

.

.

.

.

.

.

.

.

.

.

.

.

.

.

185 A-B7.

Definition of Quintiles and Deciles, Showing Per-capita Expenditure Ranges .

.

.

.

.

.

.

.

.

.

.

.

186 A-B8.

Number in Sample, Mean, and Standard Error of Estimates of Per-capita Consumption .

.

.

.

.

.

.

.

.

.

.

.

.

.

.

.

.

.

.

.

.

.

.

.

.

.

.

.

.

.

.

.

.

.

.

.

.

.

.

.

.

.

.

.

.

.

.

.

.

.

.

.

.

186 A-B9.


Mean and Standard Error of Household Size and Adult Males, Adult Females, and Children .

.

.

.

.

.

.

.

.

.

.

.

.

.

.

.

.

.

.

.

.

.

.

.

.

.

.

.

.

.

.

.

.

.

.

.

.

.

.

.

.

.

.

.

.

.

.

.

.

186 A-B10.

Results of Tests of Significance, by Region, BLCS 2001 (mean per-capita consumption) .

.

.

.

.

.

.

.

.

.

.

.

.

.

.

.

.

.

.

.

.

.

.

.

.

.

.

.

.

.

.

.

.

.

.

.

.

.

.

.

.

.

.

.


187 1-1.

Population (%) in Selected Age Groups, by Region .

.

.

.

.

.

.

.

.

.

.

.

.

.

.

.

.

.

.

.

.

.

.

.

.

.

.

.

.

.

.

.

.

.

.

.

.

3 1-2.

Household Distribution, by Size and Selected Quintiles .

.

.

.

.

.

.

.

.

.

.

.

.

.

.

.

.

.

.

.

.

.

.

.

.

.

.

.

.

.

.

.

.

6 3-1.

Food Groups as Share of Total Food Expenditure .

.

.

.

.

.

.

.

.

.

.

.

.

.

.

.

.

.

.

.

.

.


.

.

.

.

.

.

.

.

.

.

38 3-2.

Shares of Non-food Items in Total Non-food Expenditure .

.

.

.

.

.

.

.

.

.

.

.

.

.

.

.

.

.

.

.

.

.

.

.

.

.

.

.

.

.

44 3-3.

Shares of Food and Non-food Items in Total Annual (Nominal) Expenditures .

.

.

.

.

.

.

.

.

.

.

.

.

.

.

49 4-1.

Prevalence of Disability, by Type and Age Group .

.

.

.

.

.

.

.

.

.

.

.

.

.

.

.

.

.

.

.

.

.

.

.

.

.


.

.

63 4-2.

Distribution of Injuries, by Type (%) .

.

.

.

.

.

.

.

.

.

.

.

.

.

.

.

.

.

.

.

.

.

.

.

.

.

.

.

.

.

.

.

.

.

.

.

.

.

.

.

.

.

.

.

.

.

63 4-3.

Vaccination Coverage Amongst Children 0-71 Months, by Vaccine .

.

.

.

.

.

.

.

.

.

.

.

.

.

.

.

.

.

.

.

.

.

.

66 4-4.

Children 0–71 Months Not Vaccinated or Behind Schedule (%) .

.

.

.

.

.

.

.

.

.

.

.


.

.

.

.

.

.

.

.

.

.

.

.

67 4-5.

Common Contraceptive Methods Women Used, by Age and Type .

.

.

.

.

.

.

.

.

.

.

.

.

.

.

.

.

.

.

.

.

.

.

.

75 4-6.

Medical Insurance Payers .

.

.

.

.

.

.

.

.

.

.

.

.

.

.

.

.

.

.

.

.

.

.

.

.

.

.

.

.

.

.

.

.

.

.

.

.

.

.

.

.

.

.

.

.

.

.

.

.

.

.

.

.

.

.

.

82 6-1.

Labour-force Participation, by Age Group and Sex .

.

.

.

.

.

.

.

.

.

.

.

.

.


.

.

.

.

.

.

.

.

.

.

.

.

.

.

.

.

.

.

.

.

111 6-2.

Rate of Labour-force Participation, by Quintile .

.

.

.

.

.

.

.

.

.

.

.

.

.

.

.

.

.

.

.

.

.

.

.

.

.

.

.

.

.

.

.

.

.

.

.

.

.

112 6-3.

Employed Persons, by Region and Poorest and Wealthiest Quintiles .

.

.

.

.

.

.

.

.

.

.

.

.

.

.

.

.

.

.

.

.

.

115 8-1.

Distribution of Outer-wall Construction Material, by Consumption Quintile .

.

.

.

.
.

.

.

.

.

.

.

.

.

.

.

.

.

158 1-1.

Distribution Disparities of the Bahamian Population .

.

.

.

.

.

.

.

.

.

.

.

.

.

.

.

.

.

.

.

.

.

.

.

.

.

.

.

.

.

.

.

.

.

.

2 3-1.

Key Terms and Definitions .

.

.

.

.

.

.

.

.

.

.

.

.

.

.

.

.

.

.

.

.

.

.

.

.

.

.

.

.

.

.

.

.

.

.

.

.

.

.

.

.

.

.

.

.

.

.

.

.

.

.

.

.

.

36 5-1.

Evolution of Bahamian Education .

.

.

.

.

.

.

.

.

.

.

.

.

.

.

.

.

.

.

.

.

.

.


.

.

.

.

.

.

.

.

.

.

.

.

.

.

.

.

.

.

.

.

88 7-1.

Making the Case for Equitable Access: Hospital Facilities .

.

.

.

.

.

.

.

.

.

.

.

.

.

.

.

.

.

.

.

.

.

.

.

.

.

.

.

.

.

132 7-2.

National Lunch Programme Targets Neediest Schoolchildren .

.

.

.

.

.

.

.

.

.

.

.

.

.

.

.

.

.

.

.

.

.

.

.

.

.

.


138 83340_00i-xxiv 3/31/05 8:33 PM Page xiii Foreword In response to the Government of the Commonwealth of The Bahamas’ directive to measure poverty, the Depart- ment of Statistics, along with the Ministry of Health, con- ducted the first-ever Bahamas Living Conditions Survey (BLCS).

Carried out in late 2001, the BLCS—a multi- topic household survey—builds on the experience of sim- ilar surveys conducted throughout the world over the past 20 years.
Although such surveys are often expensive and time-consuming, requiring a high level of technical capac- ity, the data they provide are indispensable tools in the analysis of a country’s socioeconomic conditions and the formulation and assessment of policy initiatives.

The BLCS instruments, based on a wide body of global research, have been carefully tested in the Bahamian con- text.
The amassed data reveal the social landscape of the country—from shifting population patterns and house- hold expenditures; to health and education; to employ- ment, community and social services, and housing access.

The data patterns that emerge are rich in content and can provide a quantitative benchmark useful to researchers and policymakers both within the country and across the region.
Considerable effort was made to seek advice from local subject-matter experts, regional and international counter- parts, and international organizations, in researching this project.

This resulted in the hiring of a team of expert con- sultants in survey execution, sample design, questionnaire design, software development, and report editing.
It is hoped that the BLCS findings and recommenda- tions will help policy planners, researchers, and other pub- lic- and private-sector organizations to make better- informed decisions that will result in the implementation of initiatives that improve quality of life for all Bahamians, especially the country’s poorest citizens.
—Charles Stuart Director of Statistics Department of Statistics Ministry of Finance Nassau xiii 83340_00i-xxiv 3/31/05 8:33 PM Page xiv 83340_00i-xxiv 3/31/05 8:33 PM Page xv Preface This report is the product of the first-ever Bahamas Liv- ing Conditions Survey (BLCS), which was conducted in late 2001.
This type of comprehensive household survey has become an indispensable tool for understanding de- velopment and providing the necessary data for imple- menting, monitoring, and assessing socioeconomic pro- grammes and policies.

Such surveys—more commonly identified with developing countries—provide a com- pendium of reliable socioeconomic data on the living conditions of a populace.

They also assist in identifying the poor and providing a wealth of information on their characteristics.
In short, living conditions surveys offer comprehensive, reliable, and timely information critical to effective planning.

Such surveys are relatively new to the Caribbean re- gion.

Jamaica—indisputably the region’s leader in this re- gard—has conducted living conditions surveys annually since l988.

The Jamaican government has used the survey findings to initiate and monitor programmes aimed at im- proving the living standards of its people and to develop and assess poverty eradication strategies.
Belize has com- pleted its second such survey, while other countries, including The Turks & Caicos Islands, have recently completed their first.

Still others have yet to initiate the exercise.

Aware of the critical data that a living conditions survey can provide, the Government of The Bahamas determined the absolute necessity of conducting one immediately following the 2000 Census.
Thus, in late 2000, the Department of Statistics, the agency charged with chief responsibility for the BLCS, began the groundwork.

From the outset, the Department recognized the need for an in- tersectoral approach, given the diverse yet interconnected body of information that had to be collected.

The Min- istries of Health, Education, and Social Services were con- sidered major stakeholders and thus played an integral role in shaping the study.
The Department of Statistics collab- orated closely with the Ministry of Health in the Survey’s planning and execution.

This report reflects the culmination of all these efforts.

Along with an accompanying Executive Summary and Technical Appendix, each of the eight chapters includes an introduction to its respective topic; in-depth data analysis, incorporating tables and charts; and a concluding section that outlines policy implications and recommendations for further research.
In all chapters, the data are analysed by region and quintile.

Chapter 1 sets the tone by providing background in- formation on population distribution—both across and within regions—and composition, including age, sex, marital status, and nationality.

Households are also exam- ined in the light of their composition and characteristics of household head.

Finally a brief profile of immigrants and internal migrants is provided.
The centerpiece of the report, chapter 2, constitutes the driving force behind the study—namely, poverty.

It presents the poverty line and proportion of individuals and households falling below it.

It further examines the poverty gap, Gini coefficient, and population characteris- tics.

In addition, it thoroughly examines individual and household characteristics of the poor.

A supporting ap- pendix details the method for calculating the poverty line.

Chapter 3 examines expenditure data.


The information is not restricted to out-of-pocket expenditures but also in- cludes the estimated value of household-owned goods and services, household production, and gifts received.

As the chapter unfolds, a comprehensive analysis of food expen- diture patterns (both at and away from home), as well as non-food expenditure patterns, is provided.

Chapter 4 focuses on health, providing data on both medically diagnosed and self-reported illnesses.
The major topics covered include child immunization, nutritional status of children and adults, and female reproductive health.

Health insurance coverage, expenditure on health, and use of health facilities are also presented.

Education is the focus of chapter 5.

An overview of school attendance and completion is presented, followed by an examination of school absenteeism, grade repetition, and the time and distance involved in traveling to school.

School expenses are also analysed in detail.


Chapter 6 explores the employment status of the Ba- hamian population.

An overview of those 15 years of age and older is presented, focusing on individuals engaged in the labour force, particularly the employed; for this segment of the population, detailed data is provided on educational achievement, occupation, industry, number of hours worked, and mode of transport to work.
Chapter 7 then examines the population’s access to community services and social programmes.

Individual xv 83340_00i-xxiv 3/31/05 8:33 PM Page xvi xvi xvi | | and household access to such facilities as hospitals, schools, banks, and police stations are examined in terms of both distance and the cost involved.

Public awareness of social programmes is explored, and an analysis of pro- gramme beneficiaries is presented.

Finally, chapter 8 focuses on housing.


Dwelling type, number of rooms, construction material used, toilet facil- ities, and other basic indicators of living standards are ex- amined.

Shelter costs, including mortgages and rents, and utilities are also analysed.
83340_00i-xxiv 3/31/05 8:33 PM Page xvii Acknowledgments The Bahamas Living Conditions Survey (BLCS), the first survey of this type conducted in the Commonwealth of The Bahamas, is the most ambitious project ever at- tempted by the Department of Statistics.

Its success is the result of the committed involvement and cooperation of a broad cross-section of individuals and agencies.

The De- partment is truly grateful to all who have participated in one form or another.
Our sincerest gratitude is conveyed to those individuals and institutions whose support, encouragement, and tech- nical expertise were provided throughout the project.

First and foremost, we thank the Inter-American Development Bank (IDB) and its officers, whose valuable contribution spanned all aspects of the study.

The Department espe- cially thanks Oscar Spencer, Jorge Torres, Dougal Martin, Jose Antonio Mejia, Andres Montes, and Sud- hanshu (Ashu) Handa.
To the latter, Ashu, a mentor par excellent, we convey our deepest thanks for the dynamic role he played, including the writing of chapter 2.

We ex- tend our thanks to the IDB mapping design unit, particu- larly Eduardo Ramirez, for preparing the country map in- cluded in this book.

Our deepest gratitude goes to Jakishan Desai, lead con- sultant for the BLCS project, whose assistance spanned all areas, including data cleaning and the writing of chapter 3.
We also express thanks to Juan Muñoz, poverty expert, who provided solid input and guidelines.

We are indebted to Rodrigo Muñoz of Sistemas Integrales, who produced the software programme and trained the data-entry operators.

Sincere gratitude is expressed to Fritzroy Henry, Beverley Laurence, and the staff of the Caribbean Food and Nutrition Institute (CFNI), Jamaica, who allowed two of our officers to understudy them and provided use- ful guidelines on production of the nutritional basket.
We are also grateful to the staff of the Planning Institute of Jamaica (PIOJ) for their valuable assistance.

We truly appreciate the contributions of Norma Adams, who painstakingly edited the various chapters to produce a well-written report of high quality and coordi- nated production of the document for publication.

Sin- cerest gratitude goes to Desmond Hunt, who produced the survey design and methodology presented in the Tech- nical Appendix.
To Cypreanna Winters and Kijana Rolle, who assisted him, we convey our thanks.

To the chapter authors, most of whom were also peer readers who provided invaluable assistance in other areas, we extend our deepest thanks.

They are Arneta D. Clarke, Brenda Y. Coakley, Sandra C. Adderley-Coleby, Camille S. Deleveaux, Jaikishan Desai, Kelsie Dorsett, William J.

Fielding, Carmen Gomez, Sudhanshu (Ashu) Handa, Jessica Minnis, Adelma L. Penn, Susan J. Plumridge, and Melissa Underwood.
We express our thanks to members of the Advisory Committee.

We also wish to convey our gratitude to Alpheaus Forbes of the former Ministry of Economic De- velopment, who expedited our numerous requests for sup- plies and funds.

Additionally, we express thanks to the Comptroller and staff of Customs House and the Director and staff of National Insurance for use of their premises for training sessions.
Similarly, we thank the Department of Local Government for providing training facilities and of- fice space in the various islands.

Thanks are also extended to the Permanent Secretary and staff of the Ministry of Education and Director and staff of the Department of Education for their input into the questionnaire and for use of their facilities for both training and field-office sup- port.

We wish to especially thank two officers from this Ministry: Brenda Y. Coakley and Marcellus Taylor.
The Department of Social Services must be recognized for its input into the questionnaire and for allowing two of its officers to be seconded to work as a part of the roving team, which expedited work in the various islands.

In this respect, special thanks are conveyed to Phillipa Ferguson, Ellery Rolle, and Agnes McKenzie.
To our partner in the BLCS exercise, Ministry of Health, we express our sincerest gratitude to the Perma- nent Secretary, Chief Medical Officer, and staff of the Health Information Unit, The Nutrition Unit, and Pub- lic Health Department, particularly the numerous nurses who worked as special enumerators throughout the coun- try.
We especially thank Camille S. Deleveaux, Terrance Fountain, Adelma L. Penn, Melissa Underwood, Sandra C. Adderley-Coleby, Arneta D. Clarke, Deborah Fox, Evaneth McPhee, Mortimer Moxey, Ann Rolle, Brenda Armbrister, Nanika Brathwaite, and Valarie Minus.

Sincerest thanks are extended to the staff of the Department of Statistics, both the Nassau and Freeport offices.
We posthumously commend the tremendous ef- fort expended by Portia E. Johnson, the chief technocrat xvii 83340_00i-xxiv 3/31/05 8:33 PM Page xviii xviii xviii | | responsible for the project—she made it happen!

We es- pecially thank Carmen Dawkins and Evangeline Bowleg, who headed the roving teams.

To all members of the rov- ing teams, as well as the field staff, we express our deepest gratitude.

We are indebted to Geraldine Ingraham and Clara Lowe, who spearheaded the work in Freeport.
Spe- cial mention must be made of Leona Wilson, who was re- sponsible for all aspects of the data-processing operations and wrote the Technical Appendix.

We commend the ef- forts of Kelsie Dorsett, coordinator of the project, who wore many hats and was intimately involved in all aspects of the exercise.

We greatly appreciate the input, support, and effort expended by our Director, Charles Stuart, and Senior Deputy Director, Carmen Gomez.
We thank the Counsellors, Ltd., major newspapers, ra- dio stations, and ZNS TV 13 for their coverage of the pro- ject.

We also thank the various business establishments and Government agencies that allowed us to display our posters.

To the many enumerators in New Providence, Grand Bahama, Abaco, and Eleuthera and the roving teams that worked the Other Islands, we express our deepest grati- tude for bearing the brunt of the work.
To the supervisors responsible for overseeing their work and editing their forms, we convey our thanks.

Likewise, we thank the data- entry clerks who served in the field, as well as in the office.

We cannot possibly complete this exercise without conveying our deepest and sincerest gratitude to the hun- dreds of householders who graciously subjected them- selves to at least two lengthy visits by the enumerators and nurses.

Your patience and cooperation was greatly appre- ciated; thank you so very much!
Finally, to any individual or organization who may have been inadvertently overlooked, please forgive us and be assured that we are grateful for whatever role you played in this important exercise.
—Kelsie Dorsett Deputy Director and Division Head Social Statistics Division Department of Statistics —Leona Wilson Assistant Director and Division Head Economic Statistics Division Department of Statistics 83340_00i-xxiv 3/31/05 8:33 PM Page xix Abbreviations and Acronyms BGCSE The Bahamas General Certificate of BLCS BMI CHP COB CPI FAO Secondary Education Bahamas Living Conditions Survey Body Mass Index Child Health Passport College of The Bahamas Consumer Price Index Food and Agriculture Organization of the United Nations Female Headed Household General Certificate of Education Gross Domestic Product FHH GCE GDP GOBH Government of the Commonwealth of HAZ HQI LAC The Bahamas Height for Age Housing Quality Index Latin America and the Caribbean Key Numerical Codes Geographical Regions 1 New Providence and Grand Bahama 2 Abaco, Andros, and Eleuthera 3 Exuma and Long Island 4 Other Family Islands xix | Liquefied Petroleum Gas LPG MHH Male Headed Household MOE Ministry of Education MOF Ministry of Finance MOH Ministry of Health NHNS National Health and Nutrition Survey NSLP PG SES SLC SPG THE UNDP United Nations Development Programme WAZ Weight for Age WHO World Health Organization WHZ Weight for Height National School Lunch Programme Poverty Gap Socioeconomic Status School Leaving Certificate Squared Poverty Gap Total Health Expenditure Consumption Quintiles 1 lowest (poorest) 2 next to lowest (or poorest) 3 middle 4 next to highest (or wealthiest) 5
 highest (wealthiest) Expenditure Ranges (per capita) $0.00–3,967.99 $3,968.00–5,947.99 $5,948.00–8,523.99 $8,524.00–13,446.99 $13,447.00–infinity Notes to the Tables Throughout the chapter tables, the abbreviation N equals number of observations.
Unless otherwise indicated, the num- bers in the body of the tables represent percentages of N. xix 83340_00i-xxiv 3/31/05 8:33 PM Page xx xx xx | | BAHAMAS LIVING CONDITIONS SURVEY 2001 Who are the poor in The Bahamas?

The face of Bahamian poverty is largely masked by the country’s low poverty rate of about 9%; indeed, only some 5% of households fall below the annual poverty line of $2,863 per person.

Distribution and rates of poverty vary dramatically throughout the archipelago.
While most poor people—nearly 76%—live in the densely populated, urban areas of New Providence and Grand Bahama, the poverty rate there is less than the national rate.

By contrast, in the sparsely populated region known as Other Family Islands, where less than 6% of the poor live, the poverty rate is nearly 21%.

Moreover, poor ru- ral residents struggle harder than the urban poor to meet basic human needs (see chapter 2).
FACTS ON BAHAMIAN POVERTY ➢ Nearly 75% of all poor Bahamian households have five or more members.

➢ Households headed by widows, females, Haitian nationals, and those in common-law relationships have poverty rates above the national average.

➢ Households headed by single female parents comprise 45% of all poor households.

➢ Poor people are more likely to be employed in private enterprise or the informal sector.

➢ About 42% of poor household heads have completed some secondary schooling.
➢ Older, retired household heads on a pension or who receive remittances from non-residents are vulnerable to poverty.

➢ About 34% of poor youth, ages 19–24, are out of school and unemployed.

➢ More than 50% of the country’s poor are children 14 years of age or younger.

Poor children are.

.

.

➢ Less likely to have an early childhood education.

➢ More likely to repeat a grade in primary school.

➢ Less likely to attend college or university.


Housing conditions ➢ 58% of poor families rent, rather than own, their homes.

➢ 54% has no piped water.

➢ 33% lacks access to a flush toilet.

➢ 50% crowds more than three people into each bedroom.

83340_00i-xxiv 3/31/05 8:33 PM Page xxi Executive Summary OVERVIEW Quality of life in The Bahamas is an intricate balance of social, economic, cultural, and geopolitical factors.
The dynamic interplay of demographic, health, and educa- tional characteristics influences access to the country’s community and social services, housing, and employment opportunities.

Participation in these sectors, in turn, af- fects expenditure and living standards, thereby determin- ing households’ relative wealth or poverty and societal co- hesiveness.
To better understand how the interplay of socioeco- nomic forces affects residents’ well-being and to bring about improvements for the country’s poor, The Govern- ment of the Commonwealth of the Bahamas (GOBH) undertook the first-ever Bahamas Living Conditions Sur- vey (BLCS).

Conducted in 2001 by the Department of Statistics and Ministry of Health, the Survey analysed both monetary and non-monetary factors that determine overall household well-being.
Taken together, the find- ings that emerge from these analyses provide an overall picture of the state of living conditions in The Bahamas.

Utilizing the results of the 2000 Census as the bases for a sample frame,1 The BLCS aimed at slightly more than 2,000 households, randomly selected throughout the country, representing about 2% of total households.

The islands of the archipelago were grouped, by population size, into four regions.
Per-capita expenditure was catego- rized into quintiles and deciles (see Technical Appendix).

The quintiles were utilized in the analysis presented in this report.

The Survey focused on eight interrelated issues: demography and migration, poverty, household expendi- tures, health, education, employment, access to commu- nity services and social programmes, and housing.
HIGHLIGHTS OF THE FINDINGS Demography and Migration As discussed in chapter 1, The Bahamas is characterized by extreme regional disparities in population distribution, which mirror large regional disparities in living standards.

EXECUTIVE SUMMARY xxi | Residents of New Providence and Grand Bahama (Region 1), who enjoy the highest standard of living, comprise 85% of the country’s population of just over 300,000.

Sixty-nine percent of the population live in New Provi- dence alone.
Of those in the wealthiest expenditure quin- tile, some 91% live in Region 1, compared to 7% in Re- gion 2 (Abaco, Andros, Eleuthera) and only 1% each in Regions 3 (Exuma and Long Island) and 4 (Other Family Islands).

Whilst 77% of persons in the poorest quintile— those whose per-capita expenditure is less than $3,968— live in Region 1, their proportion is lower than that of the overall population (85%).
Conversely, in the other three regions, the proportion of persons in the poorest quintile is higher than their share of the overall population.

For all regions except Region 1, at least 50% of the population— more than 59% in Region 4—have a per-capita expendi- ture of less than $5,948.

Standard of living varies greatly amongst nationalities.

Bahamians, who represent 89% of the population, com- prise nearly 88% of those in the wealthiest quintile and just over 84% in the poorest quintile.
Haitians, who rep- resent only slightly more than 6% of the total population, account for more than 14% of those in the poorest quin- tile and only about 1% of those in the wealthiest (i.e., those whose per-capita expenditure is $13,447 or higher).

Within recent immigrant groups, nearly 84% of Haitians have a per-capita expenditure of less than $8,524, whilst 91% of those from the UK, U.S., or Canada and 56% of those from other Caribbean countries have a per-capita ex- penditure of $8,524 or higher.
Forty-five percent of households in the poorest quintile have six or more members, compared to slightly more than 1% of those in quintile 5.

Female headed households (FHHs) account for a greater proportion of households with six or more members than do male headed house- holds (MHHs).

Moreover, the share of FHHs is highest in the poorest quintile (50%) and lowest in the wealthiest (33%).
As mentioned in chapter 2, female heads require higher levels of schooling than their male counterparts to reduce the risk of poverty.

83340_00i-xxiv 3/31/05 8:33 PM Page xxii xxii xxii | | BAHAMAS LIVING CONDITIONS SURVEY 2001 Poverty The poverty line represents the minimum expenditure nec- essary for an individual to satisfy basic needs over a specific reference period (e.g., per day).

This cost is estimated in two stages.


In the first stage, the minimum expenditure needed to purchase a nutritionally adequate diet is calculated.

This amount is often referred to as the food poverty line.

In the second stage, the minimum required cost of non-food items, such as clothing and shelter, is estimated.

The sum of these two estimates equals the poverty line.
In chapter 2, the minimum amount of money necessary to purchase an ade- quate low-cost diet with allowances for non-food needs was estimated at $7.84 per person per day, which translates into an annual poverty line of $2,863 per person.

On this basis, the national poverty rate for The Ba- hamas is 9.3%, which is lower than Barbados (13.9%) and the United States (12%).
The rate is slightly lower in Re- gion 1 (8.3%), but significantly higher in the other re- gions, with the highest rate found in Region 4 (21%).

Notwithstanding this finding, given the distribution of the population, 76% of all poor people live in Region 1.

Nearly 75% of all poor households have five or more members, and 45% of all poor households are headed by single female parents.

Moreover, 50% of the country’s poor are children, 14 years of age or younger.
Household Expenditure As discussed in chapter 3, the average per-capita food ex- penditure is about $8.41 per day, of which 34% is spent on food eaten away from home.

Food expenditures vary with living standards in predictable ways—that is, the share of total expenditure on food items declines as living standards rise.

Rent (actual or imputed) represents the largest non-food expenditure and is uniformly above 32% for households across the spectrum of economic well-being.
Housing Chapter 8 highlights that households in the lowest quin- tile, whose average monthly housing expenditure is $1,374, have a housing quality index (HQI) of only 69; by contrast, those in the highest quintile, with an average monthly expenditure of $4,393, have an HQI of 86.

Households in the two poorest quintiles have significant levels of overcrowding.

In terms of construction materials, the wealthiest and poorest quintiles differ significantly.
In quintile 5, 81% of dwellings are made of concrete block or slab, compared to only 43% of those in quintile 1, which are more likely made of wood or stucco.

Ninety-six per- cent of households in the wealthiest quintile live in dwellings with running water, compared to only 62% of those in the poorest quintile.

Shelter costs (mortgage and rent), along with real prop- erty tax, account for the highest percentage of expenditure on household operations across all regions and quintiles.
Shelter costs represent more than 61% of household oper- ating expenses and more than 24% of total consumption expenditure.

Households in the poorest quintile spend nearly 67% of household operating costs on shelter, whilst those in the wealthiest quintile spend more than 60%.

Households in quintile 1 have an average mortgage expense of about $474, compared to nearly $1,440 for those in quintile 5.
Households in the poorest quintile spend more than 26 cents out of every consumption dollar on mortgage or rent, a higher proportion than for any other quintile.

Health With regard to chronic and non-communicable diseases, The Bahamas has characteristics similar to those of indus- trialized countries.
As discussed in chapter 4, the preva- lence of self-reported diabetes outside Region 1 is of special concern and may be related to elevated levels of adult obesity and low consumption of complex carbohy- drates.

Nearly 1 out of every 10 persons has a self-reported history of hypertension.

The proportion of self-reporting increases by quintile—from 6% in the lowest to 13% in the highest—which may reflect a tendency of wealthier individuals to seek health care.
The Survey found that 14% of children 2–10 years of age are overweight and 6% are underweight.

As mentioned in chapter 2, the policy response to this phenomenon de- pends on its underlying causal mechanism.

Adolescents (individuals 11–20 years of age) living in households with overweight adults are four times more likely to be over- weight or at risk of becoming overweight than those not liv- ing in such households.

Overweight and obesity problems worsened progressively with age.
Amongst adults 21–60 years, 34% are overweight and a further 32% obese.

Over- weight prevalence is higher amongst males (37%) than fe- males (32%).

Conversely, obesity is more prevalent amongst females (37%) than males (24%).

83340_00i-xxiv 3/31/05 8:33 PM Page xxiii As wealth increases, the proportion of visits to public- health facilities decreases, whilst visits to local private prac- titioners or those abroad increase, indicating that private providers are the preferred choice.
In terms of health insurance, about 51% of respondents report having cover- age; only 20% of those in the poorest quintile have cover- age, compared to 75% of those in the wealthiest quintile.

Education The developed region of New Providence and Grand Ba- hama is the seat of tertiary education, as well as the major- ity of the country’s pre-schools.

As chapter 5 highlights, stu- dents from outside Region 1 depend almost entirely on Government-operated schools for their education.
They are typified by lower attendance records and higher repetition rates, particularly in Regions 2 and 4.

As discussed in chap- ter 2, high rates of repetition represent a significant cost to both society and individuals.

Students from the poorest quintile have considerably lower representation in pre- school, are less likely to attend tertiary schools, and are more likely to exit the educational system without qualifications.
For enrolled children between the ages of 0 and 21 years, uniforms represent less than 8% of total educational expen- diture for those in the wealthiest quintile, compared to more than 34% for those in the poorest.

Uniforms are a substan- tial burden for households in Regions 3 and 4, where they account for more than 41% of total educational expendi- ture, compared to about 22% for the country overall.

Employment The Bahamas is a country of extreme worker inequality, both across and within regions.
As discussed in chapter 6, the socioeconomic status of Region 1 workers outstrips that of all other regions.

Not surprisingly, Region 1 work- ers’ educational level and academic qualifications also sur- pass those of the other regions.

With regard to overall liv- ing standard, low levels of academic achievement typify workers in the two lowest quintiles.

Workers in quintiles 4 and 5 have the lowest unemployment rates, whilst their level and nature of participation in the labour force are higher.
Employment opportunities outside Region 1 are more limited, with a significant proportion of self-em- ployment in Regions 2, 3 and 4 at the subsistence level.

Education at the tertiary level is needed to allow people from lower quintiles to move into the highest quintile, suggesting that action is required to ensure that tertiary- level education is made accessible and affordable to all.
EXECUTIVE SUMMARY | xxiii Access to Services and Programmes As discussed in chapter 7, the archipelagic nature of The Bahamas makes it difficult to develop community services and social programmes that serve everyone equally.

Un- even distribution of population and transportation— within and between islands—exacerbates the difficulty.
To reach a hospital—located only on the two islands in Region 1—more than twice as many lower-expenditure residents (26%) as higher-expenditure ones (12%) must travel over water.

Whilst children from the lower-expenditure groups and households outside of Region 1 participate in the Na- tional School Lunch Programme (NSLP), coverage is low.

As mentioned in chapter 2, at its present coverage level, the NSLP is unlikely to have a major impact on the poor.
LOOKING AHEAD The BLCS 2001 findings chart the difficulty of servicing all of the Commonwealth’s residents evenly, given the archipelago’s highly uneven distribution of population.

In- deed, concentrated population patterns affect the cost-ef- fectiveness of social policies.
Given that 76% of all poor people live in Region 1, for example, serious efforts aimed at alleviating or reducing poverty must focus there; the data also reveal, however, that the proportion and depth of poverty are greater in more sparsely populated, rural areas.

Thus, the challenge for policy planners is to avoid marginal- izing any particular group while ensuring that the neediest are provided a social safety net.
The mean gap or shortfall of a poor person from the poverty line is approximately $873 annually, meaning that $24 million will be required to lift all poor people to the line and eliminate poverty.

Across health, education, and housing sectors, similar data patterns emerge; that is, as household-expenditure quintiles rise, residents tend to shift from public to private or foreign health care and from Government-funded to private schools; they also tend to own, rather than rent, their homes.
That the socioeconomic status of Region 1 workers far surpasses that of all other regions underlines the need to improve accessibility and affordability of services and programmes.

Moreover, grappling with the social causes of low coverage rates for well-targeted programmes, such as the NSLP, call for further research.

Finally, many successful programmes, such as the National Breastfeeding Campaign, have failed to influence the social behavior of citizens outside Region 1 on a large scale.
83340_00i-xxiv 3/31/05 8:33 PM Page xxiv xxiv | xxiv | BAHAMAS LIVING CONDITIONS SURVEY 2001 Clearly, to empower more citizens to assume greater re- sponsibility for their health, the BLCS data imply that promotional campaigns must be targeted more evenly across all four regions.

Similarly, the educational findings imply that new, more flexible ways of expanding educa- tion and training opportunities outside of Region 1 should be emphasized.
Distance learning and adjusting academic calendars to enable rural children to participate in their families’ seasonal businesses are two such examples.

Effective follow-on research and policy solutions will require forging appropriate linkages across and within sec- tors.

For example, national occupational health-safety ini- tiatives must include labour, education, and other social agencies and should require linkages to the workplace and school environment.
Similarly, developing appropriate training programmes or other interventions oriented to the labour market will require coordinated research on the quality and relevance of secondary education.

Finally, how welfare policy addresses the issue of affordable housing is critical to how the country addresses poverty and equity.
The in-depth analysis of the social safety net called for in chapter 2 requires building on this study and conducting intersectoral analyses to assess the suitability of current programs, target populations, criteria, and benefit levels.

83340_001-012 3/31/05 8:36 PM Page 1 CHAPTER 1 Population Patterns: Regional Distribution and Migration Kelsie Dorsett P opulation size, composition, and distribu- tion are vital to a country’s policymakers, planners, and researchers.
Moreover, such information is integral to any survey of a country’s living conditions.

The Bahamas Living Condi- tions Survey (BLCS) baseline data focused on an array of population variables: age and sex distribu- tion, nationality, household composition, and basic migration patterns.

This chapter presents the results of Survey analyses, by both region and quintile, highlighting findings that merit further investigation and implications for policymakers.
UNDERLYING PATTERNS This analysis has revealed major demographic features involving 1) the ongoing pull of outlying rural populations to the more developed urban areas and 2) immigration.

Individuals from the Family Islands continue to move into the urban region, apparently because of better employment opportunities and lack of economies of scale in the other three regions.
In recent decades, Haitian migrants, who tend to enter the country en masse, have outnumbered all other immigrant groups.1 This large influx of immigrants—both documented and undocumented—presents major challenges to the country’s social and economic fibre, as it diverts precious resources toward detaining, maintaining, and repatriating such individuals.2 REGIONAL POPULATION DISTRIBUTION The Bahamas is characterized by extreme regional disparities in population distribution (Box 1-1).
As Table 1-1 illustrates, these differences reflect extreme regional disparities in standard of living, clearly showing that residents of Region 1 (New 1 Except for a short period during the early l990s, The Ba- hamas has had relatively large inflows of migrants from North America, Great Britain, and the Caribbean.
2 The International Organization for Migration (IOM) has initiated a study, still in its preliminary stages, on the dimension and impact of Haitian migration in The Bahamas; the study will collect and analyse existing data and conduct surveys of migrant households.
1 83340_001-012 3/31/05 8:36 PM Page 2 2 | BAHAMAS LIVING CONDITIONS SURVEY 2001 Distribution BOX 1-1 Disparities of the Bahamian Population The Bahamian population, counted at 303,611 in the 2000 Census (DOS 2002), is widely and unevenly dispersed amongst the island groups.
The overwhelm- ing majority live in Region 1 (New Providence and Grand Bahama), whilst only 10% reside in Region 2 (Abaco, Andros, and Eleuthera) and a mere 5% in Re- gions 3 and 4 combined (Exuma and Long Island and Other Family Islands, respectively).

Sixty-nine percent of the population live on the island of New Providence alone—with 2,635 per- sons per square mile (sq.

mi.

)—even though the island accounts for only 1.5% of total land mass.
By stark contrast, Andros, the country’s largest island, representing 43% of its land mass, boasts only 3% of its population—with 3 persons per sq.

mi.

Consecu- tive censuses have shown that New Providence, together with Grand Bahama, the country’s second largest population centre, continues to increase its population share at the expense of the other islands.

Providence and Grand Bahama) enjoy a standard of living far surpassing that of the other three regions.
Whilst Region 1’s share of total population was small- est in the poorest quintile (77%), this share increased as living standards rose, reaching a high of nearly 91% in the wealthiest quintile.

What stands out is that, in quintiles 1 and 2, the proportion of persons from Region 1 (77% and 84%, respectively) was lower than their overall share of the population (85%); however, in quintiles 3–5, their pro- portions were higher.
In the other three regions, the situa- tion was virtually reversed, as they were over-represented in the poorest quintile; this was further exaggerated by their consistent decline in population share as living stan- dards rose.

Regional differences in well-being are further illus- trated in Table 1-2, which shows that, in New Providence and Grand Bahama, unlike the other three regions, the quintiles were fairly evenly distributed.
For example, in Other Family Islands (Region 4), 35% of the population represented the poorest quintile, whilst less than 10% were in the wealthiest.

For all regions except Region 1, at least 50% of the population were in the two poorest quintiles.

AGE AND SEX DISTRIBUTION The Bahamian population is predominantly young, with nearly one-third of its citizens under 15 years of age.
Survey results showed little regional variation, except for Exuma and Long Island, where the proportion of those under age 15 was 27%.

Persons 65 years or older comprise 5% of the country’s population.
Within all Family Island regions, the Survey showed that the proportion of senior TABLE 1-1 Population Distribution, by Region and Quintile Data source Region BLCS 2000 Census 1 2 3 4 N 85.1 10.4 2.1 2.5 6,330 84.9 10.5 2.2 2.4 1 77.0 15.4 3.2 4.3 2 84.4 10.6 2.0 3.0 1,560 1,325 Quintile 3 86.3 9.6 2.1 2.1 1,248 4 87.0 9.3 1.9 1.8 5 90.7 6.9 1.2 1.2 1,177 1,020 83340_001-012 3/31/05 8:36 PM Page 3 POPULATION PATTERNS: REGIONAL DISTRIBUTION AND MIGRATION | 3 TABLE 1-2 Population Distribution, Showing Within-region Quintile Distribution FIGURE 1-1 Population (%) in Selected Age Groups, by Region Quintile Region N All Bahamas t n e c r e P 35 30 25 20 15 10 5 0 31.5 31.6 31.7 32.5 27.3 5.0 All 4.3 1 7.9 2 Region 13.6 10.7 3 4 Under 15 65 and over citizens was noticeably higher than in New Providence and Grand Bahama.3 Census data have shown that most Family Islands have experienced declining populations, resulting largely from migration to either New Providence or Grand Bahama.
The majority of migrators are young adults, with young children and the elderly left behind.

Exuma and Long Is- land (Region 3) stands out as having the largest proportion of older persons (13.6%), more than three times that of New Providence and Grand Bahama (4.3%) (Figure 1-1).

3 These findings confirm results of the last three national censuses.

For example, in l980, the proportion of elderly in New Providence and Grand Bahama was 3.3%, compared to 7.9% in the Family Islands.
In 2000, the proportions were 4.6% and 8.7%, respectively.

TABLE 1-3 Population Distribution; by Age, Sex, and Region Sex differentials were more extreme amongst the el- derly.

For every 1,000 females, there were only 708 males—not a surprising finding, given that life expectancy is higher for females.

As of 2001, life expectancy for fe- males was 76 years, compared to 70 for males (DOS 2004).

With the exception of Region 2, males outnum- bered females amongst persons under 15 years of age.
Na- tionwide, there were 1,128 males for every 1,000 females in this age group.

Overall, for every 1,000 females in the country, there were 952 males (Tables 1-3 and 1-4).

Nearly two-thirds of the population was between the ages of 15 and 64—the potentially economically active population.
Distribution of persons in this age group was Data source Sex Region Age factor & sex ratio BLCS 2000 Census Male Female 1 2 3 4 Age group 0–14 15–64 65 and over Age dependency ratio (per 1,000 population)* Median age Proportion of male Sex ratio (males per 1,000 females) N 31.5 63.3 5.0 620.8 26.0 48.8 952.4 29.4 65.3 5.2 530.4 28.0 48.6 947.4 6,414 303,611 34.3 61.2 4.2 648.3 24.0 - - 3,152 28.9 65.2 5.7 595.0 28.0 - - * Ratio of population 0–14 and 65 and older to population 15–64 years of age.
83340_001-012 3/31/05 8:36 PM Page 4 4 | BAHAMAS LIVING CONDITIONS SURVEY 2001 TABLE 1-4 Sex Ratios, by Age Group and Region Age group 0–14 15–64 65 and over N BLCS ratio 1,128.1 894.0 707.8 6,413 1 1,162.4 877.0 630.6 3,405 * This ratio varies from that of the 2000 Census.

highest (64%) in the more developed region of New Prov- idence and Grand Bahama and lowest (57%) in the least developed region of Other Family Islands.
The age dependency ratio,4 estimated at 621, is an in- dicator of the degree to which younger and older persons depend economically on the working-age population.

In New Providence and Grand Bahama, this dependency was significantly lower (563) than for all the other regions (the highest ratio of 764 was found in Other Family Islands).

NATIONALITY The Bahamian share of population was 89%, far out- weighing that of any other nationality group.

A distant second was Haitian, representing 6%.


These figures com- pare favourably with those of the 2000 Census (DOS 2002), which showed shares of 87% Bahamian and 7% Haitian.

Bahamians were proportionally lowest (83%) in 4 Age dependency ratio is defined as the ratio of population under 15 and over 64 years of age per 1,000 persons between 15 and 64 years of age.
TABLE 1-5 Population; by Nationality, Region, and Quintile Region 2 890.6 978.0 913.3 1,780 3 1,024.3 998.4 1,048.3* 621 4 1,175.2 1,143.2 966.0 607 Region 2, where both Haitians and North Americans had their highest share.

Standard of living varied greatly amongst nationali- ties.

Most striking was the status of Haitians, who were disproportionately represented in the poorest quintile, accounting for more than double their share of the total population.
Their numbers progressively decreased as living standards increased, diminishing to 1.4% in the wealthiest group.

As Table 1-5 shows, North Americans and other nationalities were more heavily concentrated in the wealthiest groups.

DISTRIBUTION BY HOUSEHOLD CHARACTERISTICS Household Size Distribution Survey results show that All Family Island regions had smaller households than did New Providence and Grand Bahama.

Region 3 claimed the smallest households, with a mean of 3.1 persons.
One-person households were more prevalent in Regions 3 and 4, accounting for 26% and 30% of households, respectively (Table 1-6).
Nationality Total 1 Bahamian Haitian Other Caribbean North American (U.S. & Canadian) Other N 89.0 6.2 1.9 1.9 1.0 89.5 5.8 2.0 1.8 1.0 Region Quintile 3 91.6 5.1 2.6 0.6 0.2 4 91.4 2.7 2.9 1.9 1.1 1,177 5 87.6 1.4 2.4 5.7 3.0 1,020 6,425 3,413 1,784 621 607 1,560 1,325 1,248 83340_001-012 3/31/05 8:36 PM Page 5 POPULATION PATTERNS: REGIONAL DISTRIBUTION AND MIGRATION | 5 TABLE 1-6 Household Size; by Sex of Head, Region, and Quintile Data source Sex of head Region Quintile Size factor BLCS 2000 Census M Mean 3.5 3.4 3.5 No.
members or more N 20.0 19.2 16.2 17.2 12.9 14.4 21.0 20.0 16.8 15.8 11.3 15.2 19.6 19.0 16.0 19.0 13.2 13.2 1,878 87,742 1,238 640 F Nationwide, one-person households comprised 20% of all households, a finding consistent with that of the 2000 Census.
As Table 1-7 indicates, slightly more than 30% of the heads of one-person households in Regions 3 and 4 were 65 years of age or older.
Because of the limited num- TABLE 1-7 Characteristics of Heads of One-person Households Region Head characteristic Overall 1 2 3 & 4 Male Marital status Married/common law Divorced/separated Widowed Never married Age group 20–44 45–64 65 and older Median age Quintile 1 & 2 3 4 5 N ber of observations, further analysis could not be made to determine whether these elderly persons were poor or vul- nerable.
(These findings suggest the need for further re- search in this area.)

Examined by household size and quintile, the data re- vealed no surprises.

Mean household size—largest (5.8 per- sons) in the poorest quintile—declined as wealth increased, reaching a low of 2.1 persons in the wealthiest quintile (Table 1-6).

Most striking is that 45% of households in the poorest quintile had six or more members, compared to 1% of those in the wealthiest quintile (Figure 1-2).
Although mean household size (3.5 persons) did not vary by sex of head, female headed households (FHHs) ac- counted for a greater proportion of larger households (6 or more members) than did male headed households (MHHs) (16.3% versus 13.2%).

The data further indicate that FHHs had a greater proportion of dependents than did MHHs.

The dependency ratio for FHHs was 328, compared to a considerably lower MHH ratio of 282 (Table 1-8).5 The underlying pattern that emerges from this analysis is sex disparities.
Females headed approximately 38% of all households, a proportion that varied noticeably by region 5 The BLCS, like other household surveys conducted by the Depart- ment of Statistics (DOS), defines household head as that person who is acknowledged as such by the other household members.

The house- hold head is usually the person who bears greatest responsibility for economic maintenance of the household.
83340_001-012 3/31/05 8:36 PM Page 6 6 | BAHAMAS LIVING CONDITIONS SURVEY 2001 FIGURE 1-2 Household Distribution, by Size and Selected Quintiles Poorest Quintile 4% 7% Wealthiest Quintile Household Size 3% 1% 11% 45% 12% 11% 21% 6+ 15% 43% 27% and quintile.

In Regions 2, 3, and 4, share of FHHs varied little, peaking at 29% in Region 3.

However, this propor- tion was 10 percentage points lower than that of Region 1 (Table 1-9).
Household inequalities based on sex of head are evi- dent in that the share of FHHs was highest in the poorest quintiles.

In quintiles 1-3, their share was larger than their overall share of total households (Table 1-9).

In the poor- est quintile, female headship was about equivalent to that of males; however, in contrast to MHHs, FHHs declined as living standards rose, reaching their lowest share in the wealthiest quintile (33%).
In short, one half of the house- holds in the poorest quintile were headed by females, com- pared to one third of those in the wealthiest quintile.

Approximately 43% of household heads were mar- ried, with an additional 25% never having married.

Regional extremes were evident amongst married, never- married single, and widowed heads.
With respect to the TABLE 1-8 Mean Household Composition; by Age, Sex of Head, and Region Age factor Age group 0–4 5–14 15–19 20–34 35–54 55–64 65 and older Dependency ratio* (per 1,000 population) N BLCS mean 0.35 0.75 0.27 0.86 0.90 0.18 0.18 299 1,878 Sex of head Region Male Female * Proportion of household members 0–14 years of age and 65 and older to the total population.
83340_001-012 3/31/05 8:36 PM Page 7 POPULATION PATTERNS: REGIONAL DISTRIBUTION AND MIGRATION | 7 TABLE 1-9 Selected Characteristics of Household Heads, by Region and Quintile Head characteristic All Bahamas Female Nationality Bahamian Haitian Other Marital status Married Common law Divorced Separated Widowed Never married Age group 20–34 35–44 45–54 55–64 65 and older Median age N 37.7 84.0 8.1 7.9 43.4 8.5 7.3 6.8 9.8 24.2 22.2 30.0 23.9 12.7 11.2 44 1,881 Region Quintile latter, Region 3 had the largest proportion of widowed persons (16%), well above the national average of 10%, and also the greatest proportion of household heads over 64 years of age.
The median age of the household head in Region 3 was 52, six years older than the national aver- age (Table 1-9).

With regard to household living standard, according to the marital status of household heads, those headed by in- dividuals in a common-law relationship were worse off than all others (Table 1-9).

Perhaps the reason is that a sig- nificant proportion of male partners in common-law rela- tionships in The Bahamas tend to have families elsewhere; thus, their resources are spread more widely.
Female part- ners are, in many cases, single individuals whose children have been fathered by their partners and largely depend on them for their well-being.

In the poorest quintile, house- holds headed by individuals in a common-law relationship accounted for 20% of households; this share declined to 5% in the wealthiest quintile.

Households headed by mar- ried or divorced persons were better off than those in other groups.
Regarding marital status of household head by sex of head, the most striking finding was that 74% of MHHs had a partner, compared to only 15% of FHHs (Table 1- 10).

MHHs were more likely to have partners because men, more so than women, tend to remarry after being di- vorced or widowed, and they tend to die earlier than women.

In the case of The Bahamas, what is most striking is the vast difference between the two: FHHs with no part- ner totaled more than three times the number of MHHs with no partner.
Similarly, 43% of female heads were never-married sin- gle heads, compared to only 13% of male heads.

Given these results, it is not surprising that the female share of households was highest in the poorest quintiles (Table 1- 9).
Data provided in Table 1-10 show that, of the total households, 12% were in the poorest quintile; however, for FHHs, a larger proportion fell into this quintile (16%), 83340_001-012 3/31/05 8:36 PM Page 8 8 | BAHAMAS LIVING CONDITIONS SURVEY 2001 TABLE 1-10 Household Characteristics, by Sex of Head Characteristic Total Male Female Mean household size Dependency ratio (per 1,000 population) Marital status Married Common law Divorced Separated Widowed Never married Partner lives in household Age group 20–34 35–44 45–54 55–64 65 and older Region 1 2 3 4 Quintile N compared to (12%) for MHHs.
In the wealthiest quintile, the situation was reversed; that is, FHHs were over- represented in the poorest quintile and under-represented in the wealthiest.

In light of the above discussion, it is clear that FHHs are vulnerable, a situation that must concern policymak- ers.

These households tend not to have a male spouse, are larger, have a larger proportion of children and/or depen- dents, and are poorer.

all other non-Bahamian nationalities combined.


Region 2 stands out as the region in which Bahamian headship was at its lowest (78%), whilst that of both Haitians and “Other” nationalities were at their highest (Table 1-9).

When living standards of household heads were exam- ined by nationality, it was found that, within the poorest quintile, Haitian-headed households accounted for 22%, a share that declined with rising living standards, reaching a low of 2% in the wealthiest quintile.
The reverse was true for other nationalities, whose share of households in- creased with a rise in living standards, from 3% in the poorest quintile to 14% in the wealthiest.

In short, Haitian-headed households were, by a wide margin, less affluent than all others.
MIGRATION OVERVIEW Throughout most of the twentieth century, The Bahamas experienced a net inflow of migrants.6 The age, sex, and socioeconomic status of immigrants are vital information that planners need in order to determine how immigration affects their country.

For this reason, the BLCS included a brief section on recent immigration.

It should be empha- sized that BLCS data and subsequent analysis be used cau- tiously, owing to the small number of immigrants covered (167 observations).
When these observations are further disaggregated (e.g., by place of birth, sex, or age), the num- bers within cells become even smaller, which affects data reliability.

This analysis, therefore, aims to present a gen- eral overview of Bahamian immigrants—their status and overall well-being—to provide planners a much needed immigrant profile.
Recent Immigrants During the five-year period prior to the BLCS, Haitians comprised the single largest immigrant group, account- ing for about 33% of recent immigrants.7 For all recent immigrants, Region 1 (New Providence and Grand Ba- hama) was the overwhelming region of choice.
This is no surprise, given that work-related reasons are major motives for migration; thus, Region 1, being the most Nationality of Household Head Predictably, the overwhelming proportion of households was headed by Bahamians (84%).

Of the balance, Haitians accounted for 8%, a percentage equal to that of 6 Whilst the 1990 Census showed that slightly more people were leav- ing than entering the country (DOS 1996), the 2000 Census again recorded a net inflow (DOS 2002).
7 Recent immigrants are defined as those persons who immigrated to The Bahamas within five years prior to the 2001 BLCS.
83340_001-012 3/31/05 8:36 PM Page 9 POPULATION PATTERNS: REGIONAL DISTRIBUTION AND MIGRATION | 9 TABLE 1-11 Recent Immigrants, by Place of Birth and Sex TABLE 1-12 Recent Immigrants, by Place of Birth and Region of First Entry Country or region of birth All immigrants Male Female Haiti UK, U.S., or Canada Other Caribbean Other N 33.1 18.4 26.2 22.3 167 40.0 28.4 18.4 13.2 82 26.2 8.6 33.9 31.2 85 Region of first entry Place of birth All immigrants Haiti UK, U.S., or Canada Other Caribbean Other 1 85.7 85.3 91.5 87.8 79.2 2 11.9 13.9 4.4 7.5 20.2 3 1.6 0.4 2.6 3.7 0.0 4 0.8 0.4 1.4 1.0 0.6 N 164 63 29 43 29 developed, is more likely to meet this demand (Tables 1- 11 and 1-12).
Amongst immigrants, both sexes were equally repre- sented; however, variations were apparent amongst migrant groups.

For example, 75% of immigrants from “UK, U.S., or Canada” were male, as were 60% of Haitian immigrants.

By sharp contrast, migrants from “Other Caribbean” and “Other” country categories were predom- inantly female (Table 1-13).

About 67% of immigrants were 25–54 years of age, the prime working age.
As Table 1-14 indicates, slightly more than half of all immigrants entered the country for work- ing purposes.

The median age of immigrants was 33, seven years older than the median age for the general population.

Amongst migration groups, age structure varied widely— ranging from the Haitian median age of only 28 to the UK, U.S., and Canadian median of 47 (Table 1-13).

Survey data substantiates and underscores information already known to policymakers (Table 1-14).
More than two-thirds of Haitian immigrants, in stark contrast to their counterparts from other places of birth, entered the country not to start a new job; rather, they fled a difficult geopolitical situation to look for work.

For each of the other nationalities, less than 8% entered the country for this reason.

More than half of the persons from “Other Caribbean” countries migrated because a job awaited them.
Most of these migrants were female, who for some years, on an on- going basis, have been recruited by Bahamians as teachers or domestic help.

Immigrants’ standard of living varied greatly.

Within the three poorest quintiles, some 64% of immigrants were Haitian, whilst only 7% were from “Other” countries.
The latter group comprised 36% of those in the two TABLE 1-13 Distribution of Recent Immigrants, by Age and Sex Place of birth Age or sex factor All immigrants Haiti UK, U.S., or Canada Other Caribbean Other Age group 0–14 15–24 25–44 45–54 55 and older Proportion male Median age N 83340_001-012 3/31/05 8:36 PM Page 10 10 | BAHAMAS LIVING CONDITIONS SURVEY 2001 TABLE 1-14 Reasons for Immigration (%), by Place of Birth and Quintile Reason Parents moved/ marriage School/schooling completed Start new job Look for work Other N All immigrants 28.7 2.0 28.6 24.8 15.9 166 Haiti 14.8 0.6 0.0 67.4 17.2 62 Place of birth Quintile UK, U.S., or Canada Other Caribbean Other 1, 2, & 3 4 & wealthiest quintiles, in contrast to the former, which accounted for only 10%.
Immigrants from “Other Caribbean” countries were about equally represented in these two quintile groups (Table 1-15).

When living standard was examined within specific mi- grant groups, it was found that 84% of all Haitians were within the three poorest quintiles (Table 1-16).

Only 9% of “UK, U.S., or Canada” immigrants and 13% of those from “Other” countries were part of the three poorest groups.
That Haitians comprise the largest group of immi- grants and are known to enter the country—either doc- umented or not—en masse, poses a pressing policy issue.

Regardless of documentation status, most are poor, young males in search of work.

This phenomenon has far-reaching implications for a small developing country with a predominantly young population and limited resources.
Internal Migrants Individuals who migrated within the islands during the five years prior to the BLCS were young persons—about half of both male and female migrants were under 25 years of age.

Males comprised 54% of internal migrants (Table 1-17).

As Table 1-18 shows, male migrants were richer than their female counterparts; 14% of males were in the poorest quintile, whilst 28% were in the wealthiest.

For fe- males, proportions were higher in the lowest quintile (18%) and lower in the wealthiest (20%).
Nearly half of internal migrants were from the two wealthiest quintiles (Table 1-18).

These persons indicated that the main reason for their move was to fill a job posi- tion (47%).

An additional 20% moved for other reasons, which included retirement (Table 1-19).
By contrast, migrants from the poorest quintiles, who comprised 15% of all internal migrants, moved either be- cause of marriage or relocation of parents (27%) or search TABLE 1-15 Recent Immigrants, by Place of Birth and Quintile TABLE 1-16 Recent Immigrants, by Place of Birth and Quintile Distribution within Immigrant Group Place of birth Haiti UK, U.S., or Canada Other Caribbean Other N All immigrants 34.3 16.5 26.2 23.1 163 Quintile Quintile 1, 2 & 3 4 & 5 Place of birth 1, 2 & 3 4 & 5 64.4 33 25.8 6.5 79 10.1 27.1 26.5 36.4 84 All immigrants Haiti UK, U.S., or Canada Other Caribbean Other 44.6 83.7 8.9 43.9 12.5 55.4 16.3 91.1 56.1 87.5 N 163 63 28 43 29 83340_001-012 3/31/05 8:36 PM Page 11 POPULATION PATTERNS: REGIONAL DISTRIBUTION AND MIGRATION | 11 TABLE 1-17 Age group 0–24 25–44 45–64 65 and older N Age Group of Recent Internal Migrants, by Sex TABLE 1-19 Reasons for Internal Migration, by Quintile All 47.4 38.6 11.7 2.4 314 Male 47.8 36.8 12.6 2.8 169 Female 46.8 40.6 10.7 1.9 145 Reason Parents moved/marriage School/schooling completed Start new job Look for work Other N All 20.5 14.1 31.6 12.0 21.7 315 Quintile 1 2 & 3 4 & 5 26.6 16.8 10.4 25.9 20.2 81 27.2 17.1 18.6 10.8 26.2 105 13.3 11.8 46.7 8.6 19.6 120 for work (26%).
Overall, nearly one-third moved to start a new job.

That the largest proportion moved for job-re- lated purposes correlates with data presented in Table 1- 20, which shows that, for more than 61% of internal mi- grants, the industrialized region of New Providence and Grand Bahama—where jobs and educational opportuni- ties are more abundant—was their destination.

The present migration pattern, if allowed to continue unchecked, could create serious socioeconomic problems for all of the regions affected.
Thus, the lure of residents from the other regions to New Providence and Grand Ba- hama is a major policy issue.

DIRECTION FOR POLICY AND RESEARCH This demographic overview conveys the picture of a small archipelago in which two major industrialized centres, New Providence and Grand Bahama (Region 1), are vital to the life stream of the country.
Region 1—where resi- dents enjoy the highest standard of living and comprise the overwhelming majority of the country’s population— is also a major destination for both immigrants and inter- nal migrants.

This sustained migration pattern has affected the size, composition, and regional distribution of the Bahamian population.
As the BLCS findings show, All Family Is- lands, particularly Regions 3 and 4, had a larger propor- tion of the very young (14 years and under) and the elderly (65 years and over), and therefore significantly higher de- pendency ratios; moreover, these regions were poorer than Region 1.

Concentrated population patterns affect the cost- effectiveness of social policy.
Due to its population size, Region 1 has the largest number of persons in all quintiles, however, proportionally it has the smallest share of per- sons in the poorest quintiles; by contrast, in the more sparsely populated, difficult-to-reach areas of the country, the proportion of persons in the poorest quintiles is larger.
This finding is identical to that of Chapter 2, which TABLE 1-18 Quintile of Recent Internal Migrants, by Sex Quintile N All 15.4 16.9 17.1 26.4 24.2 306 Male 13.5 17.2 16.3 25.3 27.6 169 Female 17.8 16.4 18.0 27.8 20.0 137 TABLE 1-20 Current Region of Residence of Recent Internal Migrants, by Sex Current region of residence All internal migrants 1 2 3 4 N 61.1 23.9 8.4 6.5 316 Sex Female 61.3 23.9 10.2 4.5 146 Male 61.0 24.0 6.9 8.1 170 83340_001-012 3/31/05 8:36 PM Page 12 12 | BAHAMAS LIVING CONDITIONS SURVEY 2001 focuses on the poor—the lowest of the poorest quintiles.
Wealthier residents tend to live in the more densely popu- lated, urban region, where the potential for overcrowding and its accompanying social ills, stemming from unchecked growth, could have costly repercussions.

In re- sponse, planners must decide on the optimum type of de- velopment policy to foster.8 A second major policy concern involves the vulnerabil- ity of FHHs.
Intervention in some form is necessary, given that such households—which tend to be large, poor, and have more dependents—account for about one-third of all Bahamian households.

Finally, immigration data leads one to conclude that the country has two distinct migratory patterns: a poorer group in search of work and a wealthier middle-aged group taking up a job post (most likely on contract).

Both types affect the country in unique ways.


Poorer migrants tend to make demands on the country’s social services, including Government health facilities and schools (see chapters 4 and 5, respectively); whilst wealthier migrants tend to use private facilities, but also make demands on such public resources as electric utilities and the telephone system.

In addition, their presence suggests that they oc- cupy positions for which Bahamians are either unqualified or insufficient in number to fill.
Further research on the effects of both types of migrant groups is called for, including identification of manpower gaps within the country’s current educational and training system.

REFERENCES DOS.

1996.

Report of the 1990 Census of Population and Hous- ing.

Nassau: Department of Statistics, Ministry of Economic Development.

_______.

2002.

Report of the 2000 Census of Population and Housing.

Nassau: Department of Statistics, Ministry of Economic Development.

_______.

2004.
_______.

2004.

Life Tables Report 1999–2001.

Nassau: Depart- ment of Statistics, Ministry of Finance.

FOR FURTHER READING Abdulah, Norma.

1988.

The Bahamas and Its People: A Demographic Analysis.

St. Augustine, Trinidad: The University of The West Indies.

DOS.

1996.

National Census Report: The Bahamas.

Nassau: Department of Statistics, Ministry of Economic Development.

Mills, Frank L. 1997.

Intraregional and Extraregional Mobility: The New Caribbean Migration.

Regional Monograph.
Regional Monograph.

Georgetown: CARICOM Secretariat.

Schaefer, Richard, Richard Floyd, and Bonnie Haaland.

2003.

Sociology: A Brief Introduction.

Toronto: McGraw-Hill Ryerson, Ltd. Singh, Jyoti Shankar.

1998.

Creating a New Consensus on Population.

London: Earthscan Publications, Ltd. UNFPA.

1996.

Programme of Action Adopted at the International Conference on Population and Development.

New York: United Nations Population Fund.


8 For example, a poverty map could provide useful input into the coun- try’s urban renewal programme.

_______.

1998.

The State of World Population: The New Gener- ations.

New York: United Nations Population Fund.

83340_013-034 3/31/05 8:39 PM Page 13 CHAPTER 2 Poverty Estimates and Policy Issues Sudhanshu Handa tion expenditure is the preferred approach to measuring welfare.
The poverty line used in this study is an abso- lute poverty line in that it represents the mini- mum amount of money necessary to purchase an adequate low-cost diet, with allowances for non- food needs.1 Based on a minimum daily require- ment of 2,400 kilocalories (kcal) for an adult, the least-cost food basket that delivers Bahamians a nutritionally adequate diet requires $2.64 per day.
Including allowances for the purchase of non-food necessities, the total absolute poverty line is $7.84 per day.2 This translates into an an- nual poverty line of $2,863 per person, slightly higher than the recent estimate of $2,752 for Barbados and significantly lower than the U.S. estimate of $4,525.
Since expenditures are collected at the house- hold level, each individual is assigned the per- capita expenditure of the household in which 1 See Appendix for details on the procedure used to estimate the poverty line for The Bahamas.

2 New Providence prices.


13 A ny estimate of poverty requires two es- sential ingredients: a welfare measure used to rank households and a poverty line to distinguish between “poor” and “non- poor.” The Bahamas Living Conditions Survey (BLCS) poverty assessment uses per-capita, household-consumption expenditure as its wel- fare measure.
WELFARE MEASURE AND POVERTY LINE Theoretically, expenditure is a better measure of welfare than income because it directly measures the attained consumption of an individual or household.

Conversely, income measures only potential consumption or welfare.

Expenditure is also preferable from a practical perspective be- cause households are more likely to understate income.

Thus, income measurement may be problematic where unearned income, such as re- mittances, is significant.
Finally, expenditures fluctuate less than income (i.e., savings during prosperous times and lack of savings or losses in difficult periods).

For these reasons, consump- 83340_013-034 3/31/05 8:39 PM Page 14 14 | BAHAMAS LIVING CONDITIONS SURVEY 2001 s/he lives (it is assumed that resources are equally dis- tributed within the household).

It is understood that over- all well-being includes access to such basic needs as clean water, good health, quality education, and freedom of speech and movement.
However, this chapter focuses on monetary welfare, which complements the analyses of non-monetary well-being detailed in other chapters of this report.

Taken together, these chapters offer an overall pic- ture of the state of living conditions in the country.

ESTIMATES AND INDICATORS National and Regional Rates The national poverty rate for The Bahamas overall is 9.3% (Table 2-1).
The rate is one percentage point lower for New Providence and Grand Bahama, but significantly higher for the other three regions, with the highest rate (nearly 21%) found in Other Family Islands.

However, as Table 2-1 shows, nearly 76% of all poor people live in New Providence and Grand Bahama, whilst less than 6% live in Other Family Islands.

Thus, any serious effort to re- duce poverty must focus heavily on the two major islands.
Poverty Gap, Gini Coefficient, and Population Characteristics BLCS results show that both the poverty gap (PG)3 and squared poverty gap (SPG)4 are larger in the Other Fam- ily Islands and Exuma and Long Island (Table 2-1).

For example, in the Other Family Islands, the PG is close to 6.4%, compared to 2.8% for the entire country; whilst the SPG is 3.0%, compared to 1.3% for the country as a whole.
Hence, not only are poverty rates highest in the Other Family Islands; the poor in this region are poorer, on average, than the poor in other regions.

Using the concept of the PG, it is possible to estimate the mean gap or shortfall of a poor person from the poverty line—approximately $873 per year.
By multiply- ing this average figure by the total number of poor, one can estimate the total amount required annually to lift all poor people up to the poverty line and thus out of poverty; this is $24 million.
When similar calculations are per- formed using the food poverty line—commonly referred to as the “line of indigency”—the mean gap is $963 and the total gap is $475,000 per year (although only 1% of the population falls below this line).5 The Gini coefficient, a commonly used indicator of in- equality, can range from 0 to 1, with higher values indi- cating greater inequality.

The Gini coefficient for The Ba- hamas is estimated at 0.57, which is equal to that of Brazil (Table 2-1).
However, the Brazilian Gini is based on in- come distribution, which tends to be more unequal be- cause of savings and seasonality, whilst the Bahamian fig- ure is based on expenditures.

This implies that true inequality is likely to be significantly higher in The Ba- hamas and thus probably the highest in the Caribbean.

Within the region, consumption-based inequality figures are available for Jamaica (0.35), Suriname (0.46), and Guyana (0.45).
Even the income-based estimates for Bar- bados (0.38) and Trinidad & Tobago (0.40) are signifi- cantly lower than the consumption-based estimate for The Bahamas.6 Estimating Bahamian poverty using the indicators of gender, nationality, and age group reveals two key points (Table 2-1).

Haitian nationals (25%) is higher than the national average; however, given the population distribu- tion of the country, 83% of the poor are Bahamian whilst only 17% are Haitian.
Second, poverty rates are higher amongst younger age groups; when this factor is combined with population distribution, one sees that slightly more than 50% of the Bahamian poor are children ages 14 and under.

In addition, both the PG and SPG are higher amongst children, compared to other age groups and the national average.7 POVERTY PROFILE: HOUSEHOLD CHARACTERISTICS Only 5.1% of Bahamian households are poor—less than the national poverty rate of 9.3% (Table 2-2).
Because 3 Poverty gap is an indicator sensitive to the distance of the poor from the poverty line; a larger number indicates that the mean distance from the poverty line for the poor in that region is higher.

4 Squared poverty gap, calculated using the square of the distance of the poor from the poverty line, gives more weight to observations that are farther away from the line.
Thus, this indicator is distributionally sen- sitive, and tends to be larger when even a few observations are far from the poverty line (i.e., extremely poor).

5 See Appendix for the method used to calculate the food poverty line.

6 It should be noted that the subregional inequality estimates for The Bahamas are significantly lower than the national estimate (around 0.39 each).
This means that, within each region, welfare distribution is more equal; thus, the high overall Gini coefficient stems from large dif- ferences in welfare between regions.

7 The policy implication is that poverty-reduction efforts should focus strongly on children and families with young children.
83340_013-034 3/31/05 8:39 PM Page 15 POVERTY ESTIMATES AND POLICY ISSUES 15 | Gini coefficient 0.5745 0.3859 0.3944 TABLE 2-1 National and Regional Poverty Indicators, by Population Characteristic (%) Population characteristic Poverty rate All Bahamas Region 1 (New Providence & Grand Bahama) 2 (Abaco, Eleuthera, & Andros) 3 (Exuma & Long Island) 4 (Other Family Islands) Region 1 Regions 2–4 Gender Male Female Nationality Bahamian Haitian U.S., UK, or Canadian Other Age group (years) 0–4 5–14 15–19 20–34 35–54 55–64 65 and older 9.33 8.33 13.19 16.64 20.96 9.05 9.60 8.67 24.90 1.69 0.35 16.61 13.90 9.05 9.01 4.90 3.48 6.26 Proportion of population Distribution of poor PG 2.84 2.58 3.73 5.00 6.35 2.79 2.90 2.56 8.89 0.10 0.09 5.99 4.32 2.06 2.85 1.26 0.96 1.59 SPG 1.32 1.21 1.56 2.55 3.00 1.28 1.35 1.20 3.87 0.01 0.03 3.04 1.97 0.88 1.37 0.51 0.34 0.61 Note: The PG measures the average shortfall of those persons below the poverty line relative to the line; it is a measure of the depth of poverty.
For example, the poor in Region 1 are closer to the poverty line (PG .0259) than those in Region 4 (PG 0.0635).

The SPG is a similar measure, except that deviations from the poverty line are squared, which gives more weight to the poorest of the poor (i.e., those farthest from the poverty line).
poor households tend to be larger than non-poor ones, when household poverty is translated into individual poverty via family size, poor households receive more weight, thereby increasing the proportion of individuals that fall below the poverty line.
As Table 2-2 demon- strates, poverty rates are above the national (household) average amongst female headed households (FHHs) (7%); homes in which the household head is in a common-law relationship (13%), widowed (8%), or a Haitian national (16%); households that have five or more residents; and households in which the head is age 65 or older (7%).
The degree of usefulness of these characteristics for de- signing interventions or selecting beneficiaries depends on how important each type of household is within the pop- ulation.8 For example, FHHs represent 38% of house- holds in the country, and because their subgroup poverty rate is higher than the national average, FHHs represent 55% of all poor households.
On the other hand, house- hold heads in a common-law or divorced marital status are more likely to live in poverty; however, they represent less than 40% of all poor households because the proportion of these types of households is relatively small (Table 2-2).

Therefore, targeting according to these last two criteria 8 From an operational perspective, it is also important that targeting criteria be relatively easy to verify and not fungible by the household.
83340_013-034 3/31/05 8:39 PM Page 16 16 | BAHAMAS LIVING CONDITIONS SURVEY 2001 TABLE 2-2 Poverty Rates, by Household Characteristic (%) Household characteristic Poverty rate All Bahamas Gender of head Male Female Marital status of head Married Common-law Divorced/separated Widowed Never married Nationality of head Bahamian Haitian U.S., UK, or Canadian Other Household size (no.
members) or more Age of head (years) 20–34 35–44 45–54 55–64 65 and older 5.10 3.70 7.37 2.79 13.31 2.79 8.32 6.26 4.45 16.02 0.00 0.72 1.09 2.05 2.87 1.81 7.05 13.67 23.78 5.44 5.44 4.65 3.28 6.73 Distribution of households Distribution of poor PG 1.49 0.98 2.32 0.75 3.95 0.68 2.53 1.95 1.20 5.70 0.00 0.18 0.27 0.69 0.99 0.50 1.87 2.89 7.69 2.18 1.28 1.31 0.93 1.71 SPG 0.66 0.37 1.12 0.27 1.72 0.30 1.07 1.00 0.53 2.50 0.00 0.06 0.11 0.31 0.41 0.20 0.76 0.98 3.82 1.18 0.48 0.57 0.32 0.66 would not be an accurate method to select beneficiaries for poverty-alleviation programmes.
Although household size is one of the most accurate predictors of poverty—nearly 75% of all poor households have five or more members—it is difficult to verify.

With regard to age of household head, poverty rates for house- holds headed by those aged 20–54 are close to the national average; given the distribution of these households, they represent 75% of all poor households in the country.
If one observes the PG and SPG for each household subgroup, one sees that both are highest amongst the largest households (7 or more members), those in which the household head is a Haitian national, and those headed by widows and FHHs (Table 2-2).

All of these groups have above-average poverty rates.

The high PG and SPG statistics indicate that these households are the poor- est of the poor.
Additional analyses of the relationship between demo- graphic structure and household poverty highlight the precarious situation of FHHs with children, who com- prise 23% of all Bahamian households and 45% of all poor ones (Tables 2-3 and 2-4).
Households without 83340_013-034 3/31/05 8:39 PM Page 17 POVERTY ESTIMATES AND POLICY ISSUES 17 | TABLE 2-3 Household-level Poverty Rates Household level Poverty rate All households Single-parent Female-headed Male-headed Two-parent No parent 5.10 9.36 10.01 4.89 5.14 2.10 PG 0.0155 0.0288 0.0315 0.0105 0.0140 0.0077 SPG 0.0071 0.0139 0.0155 0.0027 0.0055 0.0039 Distribution of households Distribution of poor 100 25.97 22.57 3.39 36.98 37.05 100 47.87 44.69 3.18 36.71 15.41 children have a poverty rate of only 2.1%, compared to overall household poverty of 5.1%.
For single-parent households, the poverty rate is 9.4%, significantly higher than that for two-parent households (5.1%).

Finally, within single-parent households, FHHs have an even higher poverty rate (10%).
Both the age dependency and youth dependency ratios are significantly higher amongst FHHs than male headed households (MMHs), whilst the old-age dependency ratio is slightly higher amongst MHHs.9 This indicates that FHHs have more young household members, and each prime-age, economically active resident in a FHH must support more dependants relative to MHHs.

This is prob- ably one reason why FHHs are poorer than MHHs.
As Table 2-4 illustrates, dependency ratios by poverty status are higher amongst poor households relative to non-poor ones; the total age dependency ratio is highest amongst poor FHHs, where each prime-age adult lives with 1.8 non prime-age household residents.

It should be noted, however, that the old-age dependency ratio is highest amongst poor MHHs.

In The Bahamas, as in most coun- tries, FHHs tend to be single heads whilst male heads tend to have a partner.
This fact alone reduces the overall age dependency burden amongst MHHs; the higher old-age dependency ratio amongst MHHs indicates that older parents are more likely to move in with a partnered son or daughter rather than a single one.

9 Age dependency ratio is defined as the number of household members below age 15 and above age 64, divided by the number of members be- tween ages 14 and 65.
Youth and old-age dependency use only mem- bers ages 14 and under and 65 and over, respectively, in the numera- tor, and the same denominator as the age dependency ratio.

Amongst persons 15 years and older, 75% are em- ployed, 4% are unemployed, and the remainder are out- side the labour force (Table 2-5).
Amongst the poor, how- ever, the proportion of employed is significantly lower (58%), whilst the percentage of those unemployed (12%) and outside the labour force (30%) is significantly higher.10 Moreover, amongst those employed, the type of 10 Additional analysis was conducted on the characteristics of the un- employed, by poverty status.

Poor, unemployed people are more likely to be female (73%) and less likely to be household heads, compared to the non-poor.
However, distribution of schooling amongst the poor and non-poor is remarkably similar; 70% of the unemployed have higher secondary education, although a greater percentage of the non- poor have completed some tertiary education (11% versus 5%).

Be- cause of the small sample sizes, the tables in this chapter do not present these results.
TABLE 2-4 Dependency Ratios, by Poverty Status Dependency ratio All households MHHs FHHs All Bahamas Age Youth Old age Poor Age Youth Old age Non-poor Age Youth Old age 0.6244 0.5073 0.0773 1.4831 1.3727 0.1118 0.5703 0.4578 0.0730 0.5717 0.4441 0.0791 1.0998 0.9198 0.1539 0.5410 0.4241 0.0725 0.7116 0.6135 0.0741 1.7959 1.7205 0.0795 0.6199 0.5159 0.0740 83340_013-034 3/31/05 8:39 PM Page 18 18 | BAHAMAS LIVING CONDITIONS SURVEY 2001 TABLE 2-5 Economic Activity, by Poverty Status Employment factor % N % N % N Poor Non-poor All 236 39 142 58.14 11.53 30.34 Employment status (15 years and older) Employed Unemployed Outside labour force Primary employer (15 years and older) 41 Government/Government corporation 109 Private enterprise 49 Private individual Own account 39 Ratio of non-working to working household members (10 years and older) 129 All households 69 MHHs 60 FHHs primary employer differs slightly between the poor and non-poor.
The poor are more likely to work in private en- terprise (58% versus 53%) or as private individuals (15% versus 9%), whilst the non-poor are more likely to work as own-account workers.

This pattern is reversed for house- hold heads.

Amongst all households, the work dependency ratio is around 0.5;11 this means that each worker supports half a non-worker, with the ratio slightly lower amongst MHHs and higher amongst FHHs.
Dependency burdens amongst poor households (0.88) are more than 50% higher than the national average; amongst FHHs, this ra- tio rises to 0.98, implying that, amongst poor FHHs, each worker supports about one non-worker.

Clearly, this is an important causal factor in the higher poverty rates amongst FHHs.
CHARACTERISTICS OF HOUSEHOLD HEAD Because a household head is usually the most economi- cally important person in a household, his or her charac- teristics are critical determinants of overall household wel- 11 Work dependency is defined as the number of non-workers age 15 and older, divided by the number of workers age 15 and older.

fare.

Tables 2-6a and b present poverty rates by the house- hold head’s schooling and gender distribution, respec- tively.
By selecting only household heads, the analysis is done at the household level, and, as mentioned above, the proportion of poor households is lower than the popula- tion poverty rate because of the larger size of poor house- holds.

There is a strong positive relationship between school- ing of household head and probability of escaping poverty.
As Table 2-6A shows, the poverty rate amongst household heads with kindergarten or less schooling is 15.4%, whilst only 2.8% for heads with higher secondary schooling.

Of course, few household heads have only kindergarten schooling; when population distribution of heads is con- sidered, one observes that 47% of poor heads have com- pleted primary schooling.
Given the country’s current eco- nomic structure, merely attaining literacy and other basic skills through primary schooling is not enough to succeed economically.

In fact, 40% of poor households have com- pleted some secondary schooling, implying either a low quality of education or a mismatch between subjects taught in secondary schools and labour-market demands.
Across the Caribbean region, vulnerability of FHHs is a concern to policymakers because of women’s less secure status in the labour force and because FHHs have more 83340_013-034 3/31/05 8:39 PM Page 19 POVERTY ESTIMATES AND POLICY ISSUES 19 | TABLE 2-6A Poverty Rates, by Household Head Schooling Schooling level completed Poverty rate All Bahamas Highest level completed None/kindergarten Primary Lower secondary Higher secondary College/university Technical/vocational 5.10 15.41 12.88 5.98 2.82 0.51 0 PG 1.49 5.17 3.68 1.65 0.84 0.27 0.00 SPG 0.66 2.23 1.49 0.70 0.45 0.15 0.00 Distribution of households Distribution of poor 100 3.18 18.34 17.59 37.36 18.82 4.71 100 9.64 46.98 20.96 20.53 1.88 0 children and dependents than other family structures.12 Amongst FHHs, the overall poverty rate is 7.4%, com- pared to only 3.7% for MHHs (Table 2-6B).
For both groups, poverty rates decline as schooling levels increase.

For women, these rates decline significantly between lower (11.4%) and higher (4.4%) secondary schooling; for men, the critical schooling occurs earlier, between primary and lower-secondary levels.
Therefore, female household heads need slightly higher levels of schooling than male heads to 12 The definition of household head provided by the BLCS interviewer to household respondents is “that person who is acknowledged as such by the other members, and usually the person who bears chief respon- sibility for economic maintenance of the household.” break out of poverty.
This hypothesis is borne out by the Survey results, which show that nearly 60% of poor male heads have completed only primary schooling, whilst nearly 50% of poor female heads have completed some secondary education.

This finding supports the hypothe- sis that women require more schooling than men to reduce the risk of poverty.
Alternatively, the relationship between schooling and poverty amongst female heads may occur because female heads choose lower paying, but more flex- ible, jobs or because of career interruptions to have and raise children.
In terms of distribution of economic activity by poverty status, only 64% of poor household heads are em- ployed, whilst a full 25% are outside the labour force TABLE 2-6B Poverty Rates, by Household Head Gender Female Male Distribution of poor Schooling level completed Poverty rate PG Poverty rate PG Female Male All Bahamas Highest level completed None/kindergarten Primary Lower secondary Higher secondary College/university Technical/vocational 83340_013-034 3/31/05 8:39 PM Page 20 20 | BAHAMAS LIVING CONDITIONS SURVEY 2001 TABLE 2-7 Economic Activity of Household Heads, by Poverty Status Employment factor Distribution of poor Distribution of non-poor Proportion of population Employment status* Employed Unemployed Outside labour force Primary employer Government/Government corporation Private enterprise Private individual Own account 63.70 11.56 24.74 27.57 34.58 24.15 13.71 * Based on last 7 days (not on last 12 months).
85.03 1.75 13.22 20.03 43.09 7.90 28.97 83.87 2.23 13.90 20.36 42.54 8.46 28.65 (Table 2-7).

Conversely, 85% of non-poor household heads are employed.

The large percentage of poor heads out of the labour force is an interesting statistic, driven by predominantly older, retired household heads who receive a pension or remittances from non-residents.
Although both poor and non-poor household heads are more likely to work in private enterprise—where most economic activity in The Bahamas occurs—employment status of poor and non-poor heads differs significantly.

Non-poor heads are concentrated in private enterprise (43%) and own account (29%), whilst poor heads are con- centrated in private enterprise (35%), public sector (28%), and private individuals (24%) (Table 2-7).
The difference between own account and private individual may be blurred; however, the former indicates a more for- mal and established activity, whilst the latter implies a more informal, variable type of activity.

This employment pattern is the opposite of what was discovered for all labour force participants (Table 2-5).
EXPENDITURE LEVEL AND COMPOSITION The mean per-capita expenditure in The Bahamas is $10,111, with mean expenditures significantly lower out- side New Providence and Grand Bahama (Table 2-8).

Since distribution of expenditures is typically skewed be- cause of a few large observations, a better measure is the median, which is substantially lower ($6,989).
Another approach is to calculate the mean after dropping or trim- ming the top and bottom 1% of the distribution; this cal- culation yields $9,463, which is closer to the full sample mean than to the median.

Table 2-8 shows shares of total expenditure enjoyed by each decile, which are used to calculate the Gini coeffi- cient.
The top-expenditure decile (decile 10) accounts for more than 34% of total expenditure in The Bahamas, whilst the top two deciles (deciles 9 and 10) account for about half of all expenditure in the country.

This unequal share of consumption is precisely what leads to the large calculated Gini coefficient for the country.

Another ap- proach to understanding consumption distribution is to compare the expenditure share of the top 20% to the share of the bottom 20%.
As Table 2-8 illustrates, the top 20% consumes about 50% of the total, whilst the bottom 20% consumes about 5%, resulting in a high ratio (approxi- mately 10:1).

In terms of household-expenditure composition by poverty status, 40% of the budget is spent on housing and 27% on food; thus, 67% of the budget is dedicated to these two basic needs (Table 2-9).

For poor households, this proportion is higher (76%), largely because a higher proportion of the budget (37%) is spent on food.
By re- gional standards, the food ratio amongst poor Bahamian households is extremely low.

In most middle-income countries, the food share amongst poor households is about 50%; for low-income countries in sub-Saharan Africa and South Asia, it approaches 70%.13 The low food 13 In Argentina, Paraguay, and Chile, the food ratio is 50%.

In Peru, the ratio is slightly higher, at 53%.
83340_013-034 3/31/05 8:39 PM Page 21 POVERTY ESTIMATES AND POLICY ISSUES 21 | TABLE 2-8 Mean and Distribution of Per-capita Household Expenditure Mean or share Overall mean Median Trimmed mean Share (%), by decile Gini coefficient All $10,110.87 $6,989.06 $9,463.27 2.08 3.48 4.40 5.54 6.31 7.75 9.37 11.54 15.51 34.02 0.5745 New Providence and Grand Bahama $10,517.03 $7,184.79 $9,773.09 1.77 3.08 4.13 5.39 6.32 7.37 8.88 11.73 15.61 35.71 0.3859 Other islands $7,814.43 $5,729.90 $7,686.90 4.40 6.54 6.47 6.71 6.22 10.62 13.10 10.06 14.74 21.13 0.3944 ratio in The Bahamas reflects the country’s high standard of living, relative to other countries in the region.
In terms of composition of non-food budget items, the only significant difference between poor and non-poor households is the share of spending on recreation (2.5% versus 5.5%) and durable goods (1.9% versus 3.7%).

One interesting observation is that poor households’ share spent on education is slightly higher than non-poor house- holds (4.5% versus 3.4%).

With regard to overall food distribution, the single most important food group is animal products (36%) (Table 2-10).
This finding reflects the country’s high stan- TABLE 2-9 Expenditure and Budget Shares, by Poverty Status Share per capita Mean per-capita annual household expenditure Trimmed mean Median Expenditure Shares Food Housing Durable goods Health Clothing & footwear Education Transportation Recreation Other Poor $1,990.26 $2,159.32 $2,013.45 37.09 39.22 1.87 6.44 4.87 4.51 2.86 2.46 0.67 N 129 116 129 129 129 129 129 129 129 129 129 129 Non-poor $10,946.65 $10,088.29 $7,571.14 26.16 40.04 3.81 7.33 4.74 3.33 4.71 5.69 4.20 N 1,700 1,671 1,700 1,700 1,700 1,700 1,700 1,700 1,700 1,700 1,700 1,700 All $10,110.87 $9,463.27 $6,989.06 26.71 40.00 3.71 7.28 4.75 3.39 4.61 5.53 4.02 N 1,829 1,815 1,829 1,829 1,829 1,829 1,829 1,829 1,829 1,829 1,829 1,829 83340_013-034 3/31/05 8:39 PM Page 22 22 | BAHAMAS LIVING CONDITIONS SURVEY 2001 TABLE 2-10 Food Expenditure and Shares, by Poverty Status Share per capita Mean per-capita household food Expenditure (all) At home Away from home Total Food Shares (%) Cereals Starches Sugars Legumes Vegetables Fruits Animal products Fats and oils Other foods Poor $755.09 $502.92 $252.05 17.14 9.56 8.83 1.51 8.16 9.61 35.46 4.80 4.49 N 129 129 129 129 129 129 129 129 129 129 129 129 Non-poor N All $2,548.22 $1,474.22 $1,020.42 12.47 6.92 10.34 1.50 10.03 12.47 35.56 3.82 6.66 1,700 1,699 1,699 1,669 1,668 1,668 1,668 1,668 1,669 1,669 1,669 1,665 $2,380.89 $1,383.52 $948.59 12.71 7.06 10.27 1.50 9.93 12.33 35.56 3.87 6.55 N 1,829 1,828 1,828 1,798 1,797 1,797 1,797 1,797 1,798 1,798 1,798
 1,794 dard of living since meat and chicken are typically consid- ered luxury goods, whose consumption increases with in- come.
A major cause for concern in the Bahamian diet is the large proportion of the budget (10%) devoted to sug- ars; in most countries, this percentage is typically about 5% or less.

The main food-expenditure difference between poor and non-poor households is proportion of the budget de- voted to starches and cereals, which typically are a cheaper source of calories and thus tend to play a more important role in the budget of poorer households.
In The Bahamas, poor households spend approximately 8 percentage points more on these two groups, relative to the non-poor (27% versus 19%); this means that poorer households spend less on other foods, fruits, vegetables, and—to a lesser extent—sugars.

Interestingly, both poor and non-poor households spend the same proportion on animal products—clearly the staple food for all Ba- hamian households.
ACCESS TO SOCIAL PROGRAMMES In terms of awareness of the Ministry of Social Services’ 10 major programmes, 59% of non-poor households, com- pared to 51% of poor ones, had heard of any of them (Table 2-11).

However, in terms of programme participa- tion, poor households, compared to non-poor ones, were significantly more likely to have received benefits (14% versus 4%) or to be receiving them (17% versus 3%).
De- spite the programmes being relatively well-targeted, over- all coverage rates are extremely low and are thus unlikely to ameliorate poverty amongst the target population.

TABLE 2-11 Access to Social Programmes, by Poverty Status Survey question Heard of any of the 10 programmes?

Anybody ever received benefits?

Currently receive benefits?

Ever applied for assistance?
Poor 51.18 14.13 16.67 8.9 N 129 129 129 129 Non-poor 58.95 4.23 2.8 2.25 N 1,700 1,700 1,700 1,700 All 58.34 4.63 3.42 2.52 N 1,879 1,879 1,879 1,879 83340_013-034 3/31/05 8:39 PM Page 23 POVERTY ESTIMATES AND POLICY ISSUES 23 | TABLE 2-12 Participation in National School Lunch Programme Participation factor Awareness of NSLP School participation in the NSLP Children (ages 3–10) Children (ages 11–18) Children that have received lunch (ever) Ages 3–10 Ages 11–18 Children that receive lunch (currently) Ages 3–10 Ages 11–18 Note: Children currently in school.
Poor 56.89 27.27 29.82 23.16 17.15 22.85 7.95 12.02 15.58 6.28 N 92 285 175 110 285 175 110 285 175 110 Non-poor 47.09 14.66 14.48 14.88 1.36 1.51 1.17 0.62 0.63 0.61 N 798 1553 850 703 1553 850 703 1553 850 703 All 47.74 16.38 16.54 16.16 3.22 4.29 1.83 1.98 2.61 1.17 N 915 1,894 1,051 843 1,894 1,051 843 1,894 1,051 843 Similar main conclusions can be drawn from analysis of the National School Lunch Programme (NSLP) (Table 2- 12).
Poor households are 10% more likely than non-poor ones to be aware of the NSLP (57% versus 47%).

Chil- dren from poor households are 12% points more likely than those from non-poor ones to attend a school that of- fers the NSLP (27% versus 15%), indicating that the Pro- gramme is targeting schools appropriately.

However, NSLP participation is low.

For example, only 17% of poor children have ever received a lunch, and only 12% cur- rently receive an NSLP-provided lunch.
Whilst take-up rates are slightly higher amongst younger children (ages 3–10), relative to secondary-age children, coverage rates are so low that the overall effect of the NSLP on poor chil- dren may require careful evaluation (see chapters 5 and 7).

CHILDREN’S HEALTH AND SCHOOLING As Table 2-13 shows, national school enrolment is univer- sal amongst children 5–16 years of age, whether poor or non-poor.

However, national enrolment for children ages 0–2 is only 26%, and just 14% for poor children.
A simi- TABLE 2-13 School Outcomes for Children Ages 0–18 Enrolment or attendance factor Current enrolment (age group) 0–2 3–4 5–10 11–13 14–16 17–18 Attendance factor Public school (ages 5–13) Public school (ages 14–16) Attendance in last 5 days (ages 5–13) Attendance in last 5 days (ages 14–16) Repeated a primary grade Repeated a secondary grade Poor 13.68 51.21 95.73 96 99.06 10.52 98.42 96.96 83.98 86.91 21.93 2.32 N 65 47 157 50 58 20 207 58 207 58 263 110 Non-poor 28.71 91.17 99.92 100 96.73 49.88 67.01 71.58 87.4 85.72 11.18 2.72 N 309 190 687 323 308 163 1,010 308 1,010 308 1,359 677 All 26.06 84.53 99.34 99.59 96.73 49.13 70.73 74.49 87.06 86.4 12.27 2.84 N 374 237 844 373 366 183 1,217 366 1,217 366 1,673 815 83340_013-034 3/31/05 8:39 PM Page 24 24 | BAHAMAS LIVING CONDITIONS SURVEY 2001 lar pattern can be observed at the pre-school level (ages 3–4), where national enrolment is an impressive 85%, but only 51% amongst the poor, versus 91% amongst the non-poor.
Early childhood education is now recognized as an essential ingredient for preparing children for school; participation in such programmes has been linked to later performance on literacy and numeracy tests in primary school.

To the extent that poor children may lack a stim- ulating family environment that encourages activities lead- ing to school readiness, interventions to increase poor chil- dren’s participation in early childhood and pre-school programmes could be a priority item on the policy agenda.
For children 17–18 years of age, universal enrolment drops off dramatically from those aged 14–16 years (from 97% to only 49% nationally, and from 99% to only 11% for poor youth) (Table 2-13).

Enrolment at this level is de- termined by both supply-side (limited seats) and demand- side (opportunity costs, fees, and performance) factors.
Poor families with tighter budget constraints may lack ac- cess at this level; however, limited supply of seats also means that competition is stiff in terms of performance.

If family income buys access to the best schools, as it does in most countries throughout the Caribbean, then public policy clearly has a role to play.

This topic requires more analysis to clarify the market failure and public policy mo- tivation.
TABLE 2-14 Health Outcomes for Pre-school Children At both the primary and secondary levels of schooling, nearly 75% of children attend public school; however, public-school enrolment for poor children is virtually uni- versal at these levels, no doubt, because of monetary con- straints (Table 2-13).

Interestingly, full attendance at both primary and secondary levels is about 86% nationally, re- gardless of poverty status.
On the other hand, school per- formance, as measured by grade repetition, is significantly lower amongst poor children.

For example, 22% of chil- dren from poor families have failed a primary grade, com- pared to only 11% from wealthy families.

This pattern is consistent with the earlier observation that less access to early childhood programmes amongst poor children may reduce their chances at succeeding in primary school.
De- terminants of this relatively high failure rate and the role of family background, school quality, and access to early childhood development are important topics for future re- search (see chapter 5).

In terms of health, 46% of all pre-school children have had an illness within the past 30 days, compared to only 38% of poor pre-school children (Table 2-14).
These dif- ferences commonly occur with self-reported health surveys in developing countries because the definition of being sick is subjective and highly correlated with socioeco- nomic status; that is, poorer individuals may have a higher threshold for illness.

Compared to non-poor households, Outcome item Questions (0–5 year olds) Ill in last 4 weeks?

Diarrhoea in last 4 weeks?

If so, treated?

Has vaccination card?

Vaccinations on schedule?
Anthropometry (2–5 year olds) Weight for height (proportion) Severely wasted Moderately wasted Severely overweight Moderately overweight Height for age (proportion) Severely stunted Moderately stunted Poor 38.13 4.73 100.00 85.12 84.81 0.00 3.37 3.37 13.42 5.65 5.30 N 37 7 7 97 87 0 1 1 7 4 3 Non-poor 47.82 6.66 80.02 88.14 87.12 0.09 1.5 4.91 8.76 9.23 5.38 N 234 34 30 450 414 1 4 19 16 24 20 All 46.29 6.22 82.66 87.81 86.36 0.07 1.68 5.30 9.03 9.08 5.29 N 277 41 38 561 511 1 5 22 25 29 24 83340_013-034 3/31/05 8:39 PM Page 25 POVERTY ESTIMATES AND POLICY ISSUES 25 | TABLE 2-15 Education and Training of Non-head Adults, Ages 25–65 Education or training factor Poor Highest level completed None/kindergarten Primary Lower secondary Higher secondary College/university Technical/vocational Highest academic exam passed None SLC BJC or CXC basic O level/CXC general A level/other degree Skill or trade?
8.18 17.81 26.89 46.8 0.32 0 80.22 6.77 12 0.67 0.34 19.27 N 8 32 30 59 1 0 94 11 15 2 1 130 Non-poor 2.66 11.25 15.11 49.21 17.46 4.31 31.53 9.69 20.42 16.96 21.4 45.98 N 34 192 212 573 192 48 454 114 277 200 239 1252 All 2.95 11.61 15.61 49.29 16.54 3.99 34.13 9.7 19.87 16.14 20.16 43.85 N 42 224 242 632 193 48 548 125 292 202 240 1,382 poor families reported slightly lower incidence of diar- rhoea; however, the small sample size may mean that re- sults are unreliable (see chapter 4).
Nationwide, about 87% of children have a vaccination card and 86% have had the full schedule of vaccinations, given their age and Ministry of Health protocols (Table 2- 14).

These rates are a few percentage points lower amongst poor children, indicating serious differences by poverty status.

In a country like The Bahamas, the overall coverage rate should be virtually universal.
Table 2-14 also provides anthropometric outcomes for children ages 2–5.14 Because sample sizes are small, little confidence can be placed in the results.

The main area of concern is the rate of moderately overweight poor children (13.4%), which is significantly higher than the national average (9.0%) (see chapter 4).
ADULT EDUCATION AND TRAINING FOR NON-HEADS Whilst the adult head is arguably the most important household member, other adult members clearly help de- 14 “Severely” wasted or stunted is defined as less than, or equal to, 3 z-scores, whilst “moderately” wasted or stunted is between 3 and 2 z-scores.

Similarly, “severely” overweight is defined as greater than, or equal to, 3 z-scores, whilst “moderately” overweight is between 2 and 3 z-scores.

termine overall household welfare.


As Table 2-15 shows, non-head adults (ages 25–65) from poor households are more likely to have lower levels of schooling than those from non-poor ones.

For example, more than 50% of poor, non-head adults, compared to only 28% of their non-poor counterparts, have only completed lower sec- ondary schooling or below.
At the other end of the spec- trum, more than 20% of non-head adults from non-poor households have completed some tertiary education, com- pared to less than 1% of their poor counterparts.

With regard to distribution of qualifications, as mea- sured by examinations passed, one observes an enormous quality difference between non-head adults from poor and non-poor households.

In poor households, 80% of non- head adults have passed no exams, compared to 32% of those from non-poor households.
Even if one considers an alternative qualification path—attainment of a specific skill or trade—non-head adults from non-poor house- holds have a higher attainment rate (46%), relative to those from poor households (19%).

In terms of education and training of young adults (ages 19–24), 34% of poor youth, compared to only 22% of non-poor youth, do not attend a training insti- tution and are not gainfully employed (Table 2-16).
Dis- tribution of completed education amongst poor and non-poor youths differs somewhat, but not as much as between the non-head adults (ages 25–65) described in 83340_013-034 3/31/05 8:39 PM Page 26 26 | BAHAMAS LIVING CONDITIONS SURVEY 2001 TABLE 2-16 Education and Training of Young Adults, Ages 19–24 Factor Educational Status Student only Employed only Student and working Unattached If not currently in school, highest level completed None/kindergarten Primary Lower secondary Higher secondary College/university Technical/vocational Poor 0 63.25 2.85 33.89 0 0.81 29.71 61.13 2.34 6.01 N 0 42 1 25 0 2 23 38 1 2 Non-poor 6.78 64.19 7.47 21.57 1.24 3.5 18.65 66.97 7.71 1.93 N 21 251 22 94 4 17 69 226 22 7 All 5.72 63.51 7.92 22.85 1.04 3.05 19.82 66.84 6.78 2.47 N 21 293 23 119 4 19 92 264 23 9 Table 2-15.
For example, the rate of tertiary training is about 8% amongst both sets of youth, although youth from poor households are more likely to have attained technical or vocational training (6%) whilst non-poor youth are more likely to have attained a college or uni- versity degree (8%).
In sum, non-head adults from poor and non-poor households differ significantly in terms of schooling levels and educational qualifications, which clearly has implica- tions for their labour-market potential and ability to con- tribute to household welfare.

Amongst youth (ages 19–24), schooling outcomes do not differ as much, indi- cating a degree of convergence in educational attainment over time.
Nevertheless, the unattachment rate is signifi- cantly higher amongst poor youth, which increases the de- pendency burden, thereby affecting overall household welfare.

HOUSING CHARACTERISTICS Housing tenure differs markedly between poor and non- poor Bahamian residents.

Non-poor households are more likely to own their home (58%); whilst poor families are more likely to rent (41%), live rent free (10%), or rent a Government home (6%) (Table 2-17).
About 95% of non-poor households either own or rent their homes pri- vately, compared to only 82% of poor households, for whom other forms of tenure are more important.

In addition, housing quality differs significantly be- tween poor and non-poor families.

In terms of outer-wall material, for example, 73% of non-poor families have con- crete slabs or blocks, compared to only 42% of poor fam- ilies, who are more likely to live in wood or stucco homes (54%).
Similarly, 90% of non-poor households have bathing water piped into their dwellings; amongst poor households, only 46% have piped water and more than 50% use non-piped water.

With regard to access to toilet facilities, 95% of non-poor households use a flush toilet, whilst only 67% of poor households have access; 25% of poor households use a pit latrine, and 7% have no toilet (see chapter 8).
Nationwide, about 70% of households have fewer than two people per bedroom, and 90% have fewer than three people per bedroom.

By contrast, only 22% of poor households have fewer than two people per bedroom, and 50% have more than three people per bedroom.

It is well known that crowded conditions affect hygiene and overall sanitary conditions, leading to easier transmission of dis- ease and other forms of illness.
Significantly more crowded living conditions amongst the poor, especially in light of their lower housing quality and limited access to water and toilets, is a major policy concern.
83340_013-034 3/31/05 8:39 PM Page 27 POVERTY ESTIMATES AND POLICY ISSUES 27 | TABLE 2-17 Housing Characteristics, by Poverty Status Characteristic % N % N % N All Bahamas Poor Non-poor Tenure type Owned Private rented Government rented Rent free Other Main materials of outer walls Wood/stucco Concrete blocks/slabs Wood/concrete Stone/brick Other Main source of water for bathing and cleaning Public, piped into dwelling Public, not piped into dwelling Private, piped Private, not piped Other Main source of drinking water Public, piped into dwelling Private, piped Public/private, not piped Purchased bottled water Other Toilet facility type Flush toilet, linked into public sewerage system Flush toilet, with cesspit of septic tank Pit latrine Other None Level of crowding (persons per bedroom) Fewer than 1.0 1.0–1.9 2.0–2.9 3.0–3.9 4 or more 24
83340_013-034 3/31/05 8:39 PM Page 28 28 | BAHAMAS LIVING CONDITIONS SURVEY 2001 KEY RESULTS AND POLICY IMPLICATIONS The analysis presented in this chapter, though descriptive and bivariate, nonetheless highlights key results that de- serve further analysis and policy attention.
Before turning to them, however, it should be emphasized that, compared to the Latin America and the Caribbean (LAC) region, and even the world, The Bahamas has an overall low rate of poverty.

For example, poverty in The Bahamas is nearly 5% less than in Barbados (13.9%), which has a compara- ble level of gross domestic product (GDP) and almost 3% less than in the United States (12%), which has a signifi- cantly higher level of GDP.

• Poverty rates versus composition of the poor.


There is an underlying tension between specific risk fac- tors associated with poverty and the proportion of the population that exhibits these factors.

For ex- ample, residents living in regions other than New Providence and Grand Bahama, a widowed house- hold head, an individual in a common-law relation- ship, or a Haitian immigrant are all important predictors of poverty.
Yet, these specific groups rep- resent only a small portion of the population, not a large proportion of the actual poor.

Although poverty rates are much higher outside of New Prov- idence and Grand Bahama, 75% of the country’s poor live on these two islands.

This can lead to con- flict over allocating resources for poverty pro- grammes.
The overall poverty situation outside of New Providence and Grand Bahama indicates the need for more effort and resources directed to those regions; however, any overall reduction in poverty or improvement in living conditions will come only from changes in New Providence and Grand Bahama.

At the same time, from a basic-needs per- spective, the situation in other regions is more crit- ical; poor residents on Other Family Islands are much worse off, as indicated by larger PG and SPG values.
Thus, if the Government’s strategy is to en- sure a minimum level of basic needs for all Ba- hamians, then resources allocated to the poor on these islands should be a top priority.

• Inequality.

The Bahamas is one of the world’s most unequal societies, although it has a low level of absolute poverty, distinguishing it from most other highly unequal societies, such as Brazil, where high inequality coexists with high rates of poverty.
In The Bahamian context, it is unclear whether inequality should be a pressing policy issue, given the low rate of poverty; indeed, in- equality is probably a direct consequence of one of the country’s key development strategies: provid- ing a tax haven for wealthy expatriates.

Neverthe- less, a highly unequal society is less cohesive, which has direct implications for financing of public goods and willingness to share the burden during times of crises.
Highly unequal societies may also be more prone to crime, with direct eco- nomic consequences for investment and business confidence.

Whilst inequality has not presented an economic burden to date, extreme inequality could lead to social unrest, which could negatively affect the country’s economy.

This issue clearly deserves further intellectual attention.

• Poverty, employment, and education.

Poor house- holds have significantly less education than non- poor households.
This is true for both household heads and non-head adults and youth.

In addition, and perhaps as a consequence, employment rates are much lower amongst poor household heads and non-head adults in poor households, compared to non-poor households.

Thus, the overall economic dependency ratio is three times as high in poor households as in non-poor households.
These results indicate that there may be scope for training or other interventions oriented to the labour market to raise poor households’ long-term earning capacity (see chapter 6).

In terms of education, the results show that the majority of poor household heads have at least a pri- mary education, and 20% have completed higher secondary schooling.

This raises the question of qual- ity and relevance of secondary schooling, which deserves further research (see chapter 5).

• Female headed households.


As is common in the En- glish-speaking Caribbean, FHHs represent a significant portion of all Bahamian households, and their poverty rates are double those of MHHs.

FHHs are larger, have more children, and have higher economic dependency burdens than MHHs.

However, poor female heads are better educated than poor male heads.

The analysis reflected in Table 2-6b indicates that female heads require higher levels of schooling than male heads to reduce the risk of poverty.
The reasons for this may range from labour- market discrimination to compensating wages for 83340_013-034 3/31/05 8:39 PM Page 29 jobs that are more flexible or compatible with family responsibilities (see chapter 6).

• Vulnerability of children.

Poor households are larger and have more children; thus, it is not surprising that more than 50% of the poor are children age 14 and under.

Poverty alleviation programmes must con- sider how to reach these children and what services to provide them.
• Youth unemployment and school-to-work transition.

In poor households, 33% of youths (ages 19–24) are “unattached,” meaning that they neither work nor train; even amongst non-poor households, the unattachment rate for this age group is more than 20%.

Unattachment can quickly lead to disillusion- ment with the system and pursuit of alternative, usu- ally illegal, outlets for productive activity.
Often resulting from difficulty in making the school-to- work transition, youth unattachment is a major pol- icy issue throughout the region; many interventions focus specifically on easing this transition, especially for poor youth.

• Intergenerational transmission of poverty.

Breaking the vicious cycle of poverty across generations is of- ten viewed as one of the most important public-pol- icy issues facing any state.
In The Bahamas, poor children suffer, relative to non-poor children, in four key areas: 1) Access to early childhood education.

Early childhood is the most rapid period of human development; events that occur during this period have an enor- mous effect on future health, cognitive develop- ment, socialization, and adult productivity.
Access to early childhood education is extremely low amongst poor children (ages 3–4), which is likely to negatively affect their readiness for school and even- tual achievement (see chapter 5).

2) Primary-grade repetition.

Whilst grade repetition may be directly linked to issues of school readiness and early childhood development, high rates of repetition represent a significant cost to both soci- ety and the individual.

The individual cost is borne disproportionately by poor families.
3) Low rates of tertiary school enrolment, relative to the non-poor.

This issue deserves further analysis to en- sure that market failures and equity issues are ade- quately addressed by suitable interventions.

4) Underweight and overweight children.

Nearly 50% of poor children (ages 2–5) are either POVERTY ESTIMATES AND POLICY ISSUES 29 | underweight or overweight, a significantly higher percentage than for non-poor children of the same age.
The precise policy response to this phenomenon depends on the causal mechanism underlying this outcome and clearly deserves fur- ther research (see chapter 4).

• Coverage and targeting of social programmes.

Whilst the existing menu of social programmes, including the NSLP, appears reasonably well targeted, coverage rates are extremely low.

As a result, it is highly un- likely that these programmes can, at their present coverage levels, have a major impact on the poor.
An in-depth analysis of the social safety net is needed, using the information presented in this chapter, to assess the suitability of the current menu of pro- grammes, target populations and criteria, and bene- fit levels.

With regard to targeting, the criteria used to select ben- eficiaries for poverty programmes are more challenging the fewer potentially eligible individuals there are.
Thus, in The Bahamas, beneficiary identification and selection are difficult because of the country’s low poverty rate.

Under these circumstances, simple methods, such as geographical targeting, must be replaced by more sophisticated tech- niques, such as proxy means tests or selection on a combi- nation of characteristics.
To illustrate the challenge, simu- lations have been conducted to assess the targeting efficiency of selecting beneficiaries based on characteristics associated with poverty, as indicated by the results of this chapter.

As Table 2-18 shows, if the selection criterion were fe- male headship only, then 86% of qualified applicants would not be poor, which represents leakage of pro- gramme benefits to the non-poor.
Leakage rates are extremely high, even when combined with geographical targeting (within New Providence and Grand Bahama or within Other Family Islands).

However, when fe- male headship is combined with a housing-quality indi- cator (e.g., whether a family has a toilet), leakage rates decline dramatically.
In fact, if the selection criteria were female headship with no toilet and at least one child un- der age 5, the leakage rate drops to an extremely efficient 6% nationally and 4% in New Providence and Grand Bahama.

Of course, this criterion carries a substantial cost be- cause it entails a visit to verify housing conditions.
83340_013-034 3/31/05 8:39 PM Page 30 30 | BAHAMAS LIVING CONDITIONS SURVEY 2001 TABLE 2-18 Leakage Rates for Various Beneficiary Selection Mechanisms (%) Selection criterion National New Providence/ Grand Bahama Other Family Islands FHH only FHH, with child 0–4 FHH, with child 0–14 FHH, no toilet FHH, no toilet and child 0–4 FHH, no toilet and child 0–14 86 76 83 26 6 14 87 77 84 28 4 15 78 64 73 22 10 12 Note: Leakage indicates the proportion of individuals who would qualify for the programme, based on the selection criteria, but who are non-poor.
Nevertheless, in a country with a low poverty rate, such as The Bahamas, some level of verification is usually necessary to avoid large rates of leakage.

It should be noted that female headship is not a straightforward targeting criterion since households may alter their com- position to gain programme eligibility.
In general, per- manent characteristics that cannot be easily manipulated are the most appropriate for selecting beneficiaries; in practice, however, such characteristics may not be easily identified.

83340_013-034 3/31/05 8:39 PM Page 31 APPENDIX: METHOD FOR CALCULATING THE POVERTY LINE CONSTRUCTING THE POVERTY LINE The poverty line represents the minimum expenditure necessary for an individual to satisfy basic needs over a spe- cific reference period (e.g.

per day).
per day).

This cost is estimated in two stages.

In the first stage, the minimum expenditure necessary to purchase a nutritionally adequate diet is cal- culated.

This amount is often referred to as the food poverty line.

In the second stage, the minimum required cost of non-food items, such as clothing and shelter, is estimated.

The sum of these two estimates equals the poverty line.
Al- though estimations vary by country—because of data availability and other country-specific factors—the methodological approach is fairly standard.

The specific technique used for The Bahamas is identical to that used for Jamaica and several other LAC countries.

FOOD POVERTY LINE POVERTY ESTIMATES AND POLICY ISSUES 31 | would be consistent with the observed empirical distribu- tion of the food budget amongst households in the BLCS.
Within each broad food group, specific commodities were selected based not only on their price, but also on their popularity, as measured by frequency of purchase, based on BLCS data.

In some cases, this involved a trade- off because a frequently purchased item (as observed from the BLCS) was not one of the two-to-three cheapest sources of calories in a particular food group.
In these few cases, the cheaper source of calories was selected to main- tain consistency with the fundamental idea behind the ex- ercise.

Table 2-A2 lists the 31 commodities comprising the food basket, by food group.

Prices per unit quantity were collected from New Prov- idence for the items in the food basket, and standard calorie-quantity conversion tables were used to calculate the cost per calorie for each item.
Within each food group, calories were assumed to come from specific commodities in equal proportion.

The cost of calories for each food group was then summed across all food groups to obtain the total cost of the food basket.

This cost, in New Provi- dence prices, is $2.64 per day (Table 2-A3).

The food poverty line is derived by costing out a low-cost basket of food that satisfies acceptable nutritional require- ments.
Following recommendations of the World Health Organization (WHO), the chosen basket of goods provides 2,400 kcal per day.

These 2,400 kcal are derived from the eight broad food groups listed in Table 2-A1.

The distribu- tion of calories amongst these eight groups was selected so that the implied cost share of each group in the final basket NON-FOOD COMPONENT The non-food component of the poverty line was estimated from the observed expenditure patterns of households in the BLCS.
Specifically, the cost of basic food-basket needs was divided by the average food-ratio for households in deciles 2, 3, and 4 of the welfare distribution to derive the full poverty line.

The mean food ratio for these three deciles is TABLE 2-A1 Caloric and Cost Distribution of Low-cost Food Basket, by Major Food Group Food group Energy (%) No.
items in final diet Total cost ($) Cost share (%) Cereals Starchy fruits, roots, and tubers Sugar and syrups Legumes Vegetables Fruits Animal-derived foods Fats and oils Total 35.0 10.0 5.0 5.0 4.0 6.0 25.0 10.0 100 5 3 1 3 4 3 8 3 30 0.57 0.33 0.02 0.14 0.33 0.45 0.77 0.03 $2.64 20 14 1 5 13 18 29 1 83340_013-034 3/31/05 8:39 PM Page 32 32 | BAHAMAS LIVING CONDITIONS SURVEY 2001 0.328, and the resulting daily poverty line is $8.05, imply- ing an annual poverty line of $2,941.
This poverty line is close to that recently calculated for Barbados, and is signif- icantly higher than poverty lines for LAC countries with much lower overall levels of development, such as Jamaica, Guyana, and Honduras (Table 2-A4).

In The Bahamas, the food budget share is extremely low, especially for the poorer quintiles; in other LAC countries, the food share is close to 0.5 and sometimes even higher.
The low food share in The Bahamas, an indicator of the country’s relatively high standard of living, leads to a higher poverty line (Table 2-A4).

TABLE 2-A2 Items in Low-cost Food Basket Item Amount (oz.)
Amount (gram) Energy (kcal) Cereals Wheat flour (all purpose, enriched) Rice (parboiled) Grits Bread (white, enriched) Spaghetti, macaroni (enriched, ckd) Starches Potato (sweet, fresh); tuber (raw) Potato (Irish, fresh); tuber (raw) Cassava (fresh root, raw) Sugars and cereals Sugar (white, refined, granulated) Legumes Lima beans (whole seed, dry, raw) Peanut butter (added fat, sweet) Pigeon pea (whole seed, dry) Vegetables Corn (canned, solid and liquid) Cabbage (common, raw) Carrot (fresh, raw) Mixed vegetables (canned, drained) Fruits Peaches (canned, in syrup) Bananas Oranges (all varieties) Animal-derived foods Mackerel (canned, solid and liquid) Beef (canned, medium fat) Ham (picnic) Mutton (whole, lean and fat, choice ckd) Bologna Cheese (hard, cheddar) Sardines (canned, in oil) Turkey (dark meat, raw) Fats and oils Vegetable shortening Margarine (regular, hard, vegetable fat, oil) Oil (pure, all kinds, blend) Total 83340_013-034 3/31/05 8:39 PM Page 33 POVERTY ESTIMATES AND POLICY ISSUES 33 | TABLE 2-A3 Diet of Composition of Low-cost Food Basket Item Water (g) Energy (kcal) Protein (g) Fat (g) Saturated fat (g)
 Cholesterol (mg) Carbohydrate (g) Fibre (g) Calcium (mg) Iron (mg) Potassium (mg) Sodium (mg) Zinc (mg) Vitamin A (R.E.)
Thiamin (mg) Riboflavin (mg) Niacin (mg) Folacin (ug) Cyano cobalamin (ug) Vitamin C (mg) Total amount (lb) Total amount (kg) Total cost ($) Amount 726.7 2,400.1 89.4 81.8 23.0 180.3 331.6 23.6 762.2 20.8 3,371.8 2,211.4 9.7 3,973.0 2.9 1.50 24.9 242.3 11.7 159.7 3.19 1.45 2.64 TABLE 2-A4 Poverty Lines and Rates for Selected LAC Countries and U.S. Country Poverty line (US$) Poverty rate (%) GDP per capita (US$) Bahamas Barbados Brazil Guyana Honduras Jamaica Mexico United States 2,863 2,752 749 510 762 980 1,545 4,525* 9.10 13.9 37.5 36.3 79.1 16.0 41.1 11.7 Note: Poverty lines are for an individual per year.
* Calculated by converting the poverty line for a family of 4 to that per person.

15,997 8,212 4,690 901 790 2,604 4,100 34,000 Year 2001 1997 1999 1999 1999 1998 2000 2001 83340_013-034 3/31/05 8:39 PM Page 34 83340_035-060 3/31/05 8:54 PM Page 35 CHAPTER 3 Household Expenditure Data: Patterns for Analysis Jaikishan Desai I t is now commonly accepted that expen- ditures on food and various non-food items provide a better measure of an in- dividual’s standard of living than does income.
Although the process of collecting data on ex- penditures is more time-consuming, measure- ment errors are fewer, respondents are less likely to misrepresent information, and a closer con- nection is made with economic well-being (Box 3-1) (see chapter 2).

Independent of its role in measuring living standards, expenditure data provides a wealth of information that can be used for making policy and planning decisions.
This chapter examines the expenditure data collected for the Bahamas Living Conditions Survey (BLCS).

ISSUES FOR DATA INTERPRETATION Obtaining accurate data on household expendi- tures requires various methods and reference (recall) periods since such expenditures differ by household member and in frequency.

For exam- ple, it is easier to identify food eaten outside the home by individual household members than food prepared and eaten at home, which is more likely to be eaten by members collectively.
Thus, it is better to collect data on food eaten outside the home from individuals and data on food eaten within the home from the household mem- ber who makes the purchases or does the cook- ing.

Moreover, certain expenditures (e.g., food, rent, utilities, transport, and personal care) occur more regularly whilst others (e.g., furniture, ap- pliances, overnight stay in hospitals and clinics) occur less often.
Collecting accurate data requires choosing a recall period appropriate to the type of expenditure.

For more frequently purchased items, such as food, the recall period is shorter (monthly); however, for such items as clothing and hospital stays, the recall period is yearly.

Ul- timately, all expenditures must be standardized to one recall period—in this case, a year.

This necessarily requires extrapolation, which can in- troduce a degree of error into the measurement of total expenditures.
35 83340_035-060 3/31/05 8:54 PM Page 36 36 | BAHAMAS LIVING CONDITIONS SURVEY 2001 BOX 3-1 Key Terms and Definitions Economic well-being.

Usually defined in terms of the value of all goods and services consumed over a well- defined time period, economic well-being or standard of living is a major criterion used to define the range of goods and services included in estimating house- hold expenditures.

Double-counting.
Double-counting.

Avoidance of double-counting is a second criterion that drives the selection of expendi- ture items.

Double-counting can occur for two rea- sons.

First, the survey instrument’s definitions of expenditure can overlap, especially when data is col- lected in various survey sections.
Second, expendi- tures of one household may be receipts for another; thus, it is necessary to ensure that both expenditures and gifts are not included when, as with sample sur- veys, each selected household represents several oth- ers.

For example, The BLCS measure of expenditures included the value of food and non-food gifts received by each household.
If it also included remittance and gift expenditures to other households, this could lead to double-counting if the receiving households were located within the same enumeration area.

Unless the survey instrument clearly identifies the origin and des- tination of each type of gift and remittance, thus per- mitting exclusion within the enumeration area, it is advisable to exclude gifts and remittances for all households Expenditure.
As used in this chapter, expenditure im- plies the value of all goods and services contributing to well-being consumed over a specified period.

Within this context, household expenditures are not restricted to out-of-pocket expenditures, but also include the es- timated value of household-owned goods and services, household production, and gifts received.
DATA-COLLECTION METHODS AND CATEGORIES The BLCS, unlike a typical income-expenditure survey, collected expenditure data in a variety of ways that corre- sponded to incidence and relevance to the topics covered by the survey instrument.

The data-collection methods chosen sought to strike a balance between accuracy (of re- call) and practicality (of obtaining information).
For ex- ample, data on food eaten at home, frequent (and some less frequent) non-food expenditures, housing, and con- sumer durables were collected for the entire household, largely because most of these items were collectively con- sumed by all household members.

On the other hand, ex- penditure data on food eaten away from home, health, and education were collected for each household member be- cause these items were more clearly correlated with specific individuals.
Similarly, whilst certain expenditure informa- tion referred to the month preceding the interview, other data covered a longer recall period (e.g., year); the choice was based on respondents’ recall ability.

Food-expenditure data were collected separately for food consumed at and away from home.
The Survey team obtained data on food consumed at home by soliciting de- tailed information on household purchases, value of home production (consumed by the household), and gifts re- ceived for 98 food items over a 12-month period.
Data on food consumed away from home, disaggregated by meal type (breakfast, lunch, dinner, and snack), was collected for the month preceding the interview for each household member, as the amount spent was expected to be substan- tial (the data collected validated this assumption) and a shorter recall period was deemed appropriate.
Non-food expenditure data were collected for the en- tire household over the 12-month period prior to the in- terview.1 Data on such consumer durables as motor vehi- cles and appliances were collected by item for the entire household; this information—obtained on current value, acquisition price, and acquisition date—was used to esti- mate a “use value” for one year.2 1 Non-food expenditures encompass a wide range of items, from fre- quently purchased fuel, toiletries, personal-care items, and transport to less frequently purchased clothing, footwear, and small household items.
2 It should be noted that data were not collected on furniture, based on the assumption that respondents would be unable to provide accurate information on the current value of these items.

83340_035-060 3/31/05 8:54 PM Page 37 HOUSEHOLD EXPENDITURE DATA: PATTERNS FOR ANALYSIS 37 | Data on health and education expenditures were collected for each relevant household member.
For health, information was collected on outpatient-visit ex- penditures over a four-week period, inpatient visits over a 12-month period, and insurance premiums for one year.

For education, information was collected on school tu- ition and fees, uniforms, and books for each household member who attended school during the 12 months pre- ceding the interview.

Finally, housing-expenditure data were collected for the entire household.
Data on such utility expenditures as water, electricity, telephone, and garbage disposal were based on the most recent bill and months covered.

For dwelling use, actual household rents were used for rented homes; in the case of owner-occupied, rent-free, and squatter-occupied dwellings, respondents were asked how much they were prepared to pay each month.

This “per- ceived” rental value was used to determine the value that the household derived from use of the dwelling.
consumption varies widely across households, particularly in terms of standard of living.

Amongst the poorest 20% of the population, daily per-capita expenditure is only about $2.91, whilst the wealthiest 20% consume a per- capita equivalent of B$14.19 per day (see chapter 2).
The most striking finding was that the largest share of total food expenditures is food eaten away from home (in- cluding out-of-pocket expenditures and food eaten at other households and social events).3 For the average Ba- hamian household, food eaten away from home consti- tutes 34% of total annual food expenditures (Figure 3-1).
The largest component of this category is lunch, typically consumed at the workplace, for which mean annual ex- penditures total more than B$1,779 per household or about B$1,535 per capita (Table 3-1).

As Table 3-2 shows, men spend about B$500 more per year than women on food eaten away from home.

FINDINGS: FOOD EXPENDITURE PATTERNS The average Bahamian household consumes nearly B$8,164 of food each year (Table 3-1), which translates into a daily per-capita expenditure of B$8.41.
However, 3 To the extent that food was eaten at other households—including the homes of friends and relatives—double-counting of food expenditures may have occurred because food eaten at home is based on purchases, home production, and gifts received.

The survey instrument does not break down the value of food eaten away from home into purchased and non-purchased components.
TABLE 3-1 Average Household Food Expenditures, Share in Total, and Household Consumption Food group* Staples (cereals, roots, and tubers) Fruits & vegetables Meats & dairy products Fish & seafood Sugar and sugar products Fats, oils, nuts, & beans Beverages Other foods Foods consumed away from home Breakfast Lunch Dinner Snacks Total food expenditure Mean annual expenditure Share of total food expenditure % Households that consumed over past 12 months * See Table 3-A1 for data on the items within each food group.
83340_035-060 3/31/05 8:54 PM Page 38 38 | BAHAMAS LIVING CONDITIONS SURVEY 2001 FIGURE 3-1 Food Groups as Share of Total Food Expenditure Staples 8.9% Fruits & vegetables 12.3% Food away from home 34.3% Other foods 7.2% Beverages 8.7% Fats, oils, nuts, & beans 2.8% Meats & dairy products 16.5% Fish & seafood 6.7% Sugar & sweets 2.6% Amongst working-age individuals (19–64 years old), those who worked in the 12 months prior to the BLCS spent nearly B$800 more than those who did not; most of this difference was due to higher spending of those who oper- ated their own businesses.
Amongst school-age children (6–18 years), those enrolled at the time of the survey spent about B$350 less than non-enrolled children, largely because the latter group was employed and thus spent more on meals consumed away from home.

Meats and dairy products comprise the second largest share of total food expenditures.

Within this food group, average household expenditures on chicken are substan- tially higher, amounting to nearly B$20 per month.
The third largest share of food expenditures is fruits and veg- etables.

Whilst no single fruit or vegetable accounts for more than 1% of total food expenditure, together they ac- count for about 12% of the total.
Staples (cereals, roots, and tubers) and beverages (alcoholic and non-alcoholic) each comprise about 9% of total food expenditure; of the items that comprise each of these food groups, bottled wa- ter (2.7%), fruit juices (2.2%), soft drinks (2.0%), bread (1.8%), and cold breakfast cereal (1.6%) are the main ones.

Fish and seafood expenditures, about B$540 per year, comprise nearly 7% of the total, with fresh and frozen fish accounting for nearly 3% of the total.
Variations across Households Household spending on staple foods is inversely related to standard of living (Table 3-3a).

Predictably, wealthier households spend a smaller share of their total food bud- get on staples.

Whilst households in the poorest quintile spend 12.5% of their food budget on staples, those in the wealthiest quintile spend only 7%.
Similarly, share of to- tal food expenditure on meat and dairy products is lower amongst those who are better off, although differences between quintiles are small.

The largest differences be- tween quintiles involve food expenditures away from home.

The wealthiest 20% of households spends about B$4,139 on food away from home, whilst the poorest spends 80% less.
Household food-expenditure differences are also related to the age and gender of the household head, as well as household composition (Tables 3-3A and B).

Households headed by older individuals spend progressively less on food eaten away from home and more on all food items con- sumed at home.

Male-headed households spend about 4% more on food eaten away from home.
Variations in house- hold size and composition do not translate into large differ- ences in spending patterns, although they clearly affect the amounts spent on specific foods.

One exception is the large difference in expenditures on food eaten away from home between households with and without at least one member 15–64 years old.
Households with no members in this age group spend an average of only 12.7% of their total food ex- penditure on food away from home, whilst households with one or more members in this age group spend between 34.6–38.4% on food away from home.

Variations across Island Groups Another striking difference in food expenditure patterns occurs between island groups.

Distinct from the other re- gions, New Providence and Grand Bahama (Region 1) largely follow the patterns of the fourth expenditure quintile.
Households on these two islands spend a smaller share on staples and nearly every other food group, but spend more on food away from home.

To a certain degree, island-wise differences reflect differences in living standards; however, they also persist within ex- penditure quintile groups.

Thus, Region 1 households in the poorest quintile (quintile 1) spend more on food away from home than do the poorest quintile households on other islands.
83340_035-060 3/31/05 8:54 PM Page 39 HOUSEHOLD EXPENDITURE DATA: PATTERNS FOR ANALYSIS 39 | TABLE 3-2 Mean Individual Expenditures on Food Eaten Away from Home Factor Breakfasts Lunches Dinners Snacks All meals Age (in years) 5 or younger 6–14 15–18 19–24 25–64 65 or older Gender Male Female Total (annually, per person) Work status (individuals, 19–64 years old) Worked for wages (past 12 months) Yes No Worked on own farm (past 12 months) Yes No Worked in own business (past 12 months) Yes No Worked (past 12 months) Yes No Total Currently enrolled in school (6–18 years old) Yes No Total FINDINGS: NON-FOOD EXPENDITURES Rent, averaging about B$8,799, comprises the largest share—35.5%—of total non-food expenditure (Table 3-4).4 Overall, about 57% of Bahamian households own their dwellings.
This largely reflects the home-ownership status of New Providence and Grand Bahama, where much of the population lives.

By contrast, on the Family 4 For rental units, the tenant’s rent is the expenditure incurred by the household; for owner-occupied dwellings and rent-free dwellings, the respondent’s estimate of rental value is the implicit expenditure on use of the dwelling.

Islands, more than 70% of households own their dwellings.
The rental market is largely private; although, on the Family Islands, about 4% of all households live in Government-rented housing.

The imputed rent for homeowners is nearly 2.8 times the rent that tenants actu- ally pay.

This finding may indicate that homeowners over- estimated rental values.

Annual rent averages about 9% of house value, which is somewhat higher than such countries as the U.S., where the average is 6–7% (see chapter 8).
The second largest non-food expenditure item is elec- tricity (7%), followed by health and dental insurance 83340_035-060 3/31/05 8:54 PM Page 40 40 | BAHAMAS LIVING CONDITIONS SURVEY 2001 , s l i o , s t a F & , s t u n s n a e b & r a g u S r a g u s s t c u d o r p & h s i F d o o f a e s & s t a e M y r i a d s t c u d o r p & s t i u r F s e l b a t e g e v s e l p a t S .

9 7 2 .

9 0 3 9 .

1 3 .

7 5 3 .

6 8 3 .

0 6 3 .


7 5 2 .

9 4 2 .

9 5 2 5 .

1 5 .

0 0 4 .

9 6 3 3 .

4 3 .

5 5 2 1 .

4 2 .

8 5 3 .

0 2 3 .

5 5 3 0 .

1 3 .

4 4 3 .

7 5 3 .

2 6 3 0 9 .

7 7 .

8 7 .

3 .

7 8 5 .

1 .

7 2 7 .

6 7 .

7 7 .

.

7 6 .

5 7 8 7 .

.

5 6 0 7 .

.

7 6 0 7 .

4 7 .

7 5 .

.

4 6 6 7 .

3 .

8 .

2 8 0 8 .

.

7 8 8 8 .

.

5 8 1 .

9 .

6 8 .

4 9 8 9 .

.

7 9 6 6 .

3 .

8 8 8 .

8 8 .

.

2 9 .

2 9 8 8 .

.

6 8 .

4 0 1 .

4 9 .

4 8 8 7 .

8 6 .

4 .

3 1 .


3 8 2 .

.

7 2 .

5 2 6 2 .

7 .

3 7 .

3 1 .

3 7 .

1 3 .

2 .

5 2 9 2 .

6 .

3 5 .

3 6 2 .

1 .

3 9 2 .

0 .

3 .

7 2 .

5 2 6 2 .

1 .

3 6 2 .

0 .

3 6 2 .

3 .

2 .

5 2 3 .

3 0 .

3 3 .

3 .

5 2 .

7 2 .

7 2 4 2 .

6 2 .

9 2 .

.

5 2 .

7 2 .

5 2 .

5 2 .

7 2 .

5 2 2 .

3 .

4 6 0 6 .

9 6 .

6 6 .

2 7 .

3 .

6 1 .

8 3 .

0 1 .

6 0 1 5 .

3 0 6 .

9 5 .

6 7 .

8 7 .

9 7 .

0 7 .

3 .

6 9 6 .

7 7 .

.

5 6 0 6 .

6 6 .

3 .

8 1 .


9 7 1 .

5 6 1 .

2 6 1 3 .

5 1 .

2 6 1 .

0 8 1 3 .

7 1 .

6 6 1 .

6 2 1 3 .

4 1 1 .

6 1 .

2 6 1 1 .

9 1 3 .

9 1 .

0 6 1 3 .

7 1 3 .

5 1 3 .

7 1 .

6 6 1 .

7 6 1 .

0 6 1 3 .

1 1 3 .

2 1 .

8 2 1 .

2 2 1 3 .

2 1 .

0 2 1 7 .

3 1 1 .

3 1 .

4 2 1 8 7 .

3 .

0 1 0 .

1 1 0 .

3 1 1 .

5 1 3 .

5 1 8 .

1 1 1 .

3 1 .

8 2 1 8 .

3 1 .

2 2 1 .

9 0 1 .

6 0 1 .

5 2 1 .

9 0 1 6 9 .

.

2 8 9 6 .

.

6 8 .

9 0 1 3 .

0 1 .

7 0 1 0 7 .

.


5 8 .

5 8 3 .

8 .

2 0 1 1 .

1 1 .

5 8 6 9 .

0 8 .

0 9 .

.

9 8 .

5 9 8 9 .

i e l i t n u q e r u t i d n e p x E ) % 0 2 t s e w o l ( 1 r o t c a F ) % 0 2 t s e h g i h ( – 5 2 4 4 – 5 3 4 5 – 5 4 4 6 – ) s r e b m e m .
o n ( e z i s d l o h e s u o H e r o m r o 7 4 – 3 6 – 5 1 2 s r o t c a F s u o i r a V y b , - 3 E L B A T 83340_035-060 3/31/05 8:54 PM Page 41 HOUSEHOLD EXPENDITURE DATA: PATTERNS FOR ANALYSIS 41 | .

4 4 3 .

2 5 3 2 .

1 3 .

0 4 3 .

9 5 3 3 .

3 3 1 .

4 3 .

7 2 1 .

8 4 3 .

6 4 3 .

4 5 3 .

4 8 3 .

8 5 3 3 .

6 2 6 .

3 2 3 .

4 3 0 6 .

.

0 0 1 2 .

1 1 .

7 6 8 7 .

8 7 .

0 8 .

6 6 .

6 6 .

.


5 7 2 7 .

4 7 .

3 .

7 .

7 6 .

2 6 2 7 .

0 9 .

0 8 .

.

2 8 .

2 9 0 8 .

8 8 .

4 7 .

.

6 0 1 .

0 0 1 .

6 8 .

2 8 9 6 .

.

7 8 .

9 8 8 8 .

.

7 8 8 2 .

.

5 2 9 2 .

9 2 .

.

5 2 .

7 2 .

7 2 .

2 4 9 2 .

.

7 2 .

7 2 .

5 2 .

7 2 4 .

3 4 .

3 8 2 .

.

5 2 8 2 .

4 .

3 4 2 .

.

7 2 .

7 2 3 .

3 3 .

3 .

7 2 6 2 .

.

5 2 .

5 2 6 2 .

8 2 .

9 2 .

6 2 .

9 6 .

.

2 6 0 7 .

9 6 .

.

5 6 8 6 .

8 5 .

3 .

9 .

5 6 2 7 .

1 .


6 1 .

6 .

5 6 3 .

8 9 6 .

.

7 6 .

8 6 1 .

6 5 1 .

6 5 1 .

5 6 1 .

0 6 1 .

5 6 1 .

4 7 1 3 .

2 2 .

7 5 1 .

0 6 1 .

2 7 1 3 .

6 1 .

0 6 1 .

8 8 1 .

9 0 2 .

5 6 1 .

7 2 1 .

9 0 1 .

8 0 1 .

7 2 1 8 .

1 1 9 .

1 1 .

7 0 1 .

5 8 1 .

5 2 1 1 .

2 1 8 .

1 1 .

6 0 1 9 .

1 1 1 .

4 1 .

8 5 1 .

2 2 1 8 8 .

0 9 .

.

7 9 .

7 8 .

7 8 .

4 9 .

6 0 1 .

6 2 1 3 .

8 .

7 8 0 9 .

3 .

9 .

6 8 .

7 0 1 4 .

1 1 .

9 8 ) .
o n ( s r e b m e m d l o h e s u o h f o s e g A s r a e y 4 – 0 0 1 e r o m r o 2 s r a e y 4 1 – 5 0 1 2 s r a e y 4 6 – 83340_035-060 3/31/05 8:54 PM Page 42 42 | BAHAMAS LIVING CONDITIONS SURVEY 2001 1 5 1 , 2 6 8 8 2 , 3 8 0 , 3 7 3 2 , 3 9 3 1 , 4 7 2 4 , 3 9 4 7 2 , 4 1 8 2 , 7 3 9 2 , 6 7 2 4 , 9 2 6 , 3 7 2 7 , 3 1 1 6 , 3 0 8 2 2 , 7 3 1 , 2 4 3 6 , 3 8 1 8 2 , 0 9 4 2 , 3 7 5 2 , 8 5 3 , 3 9 1 2 4 , 0 3 9 4 , , 1 7 7 2 , 1 0 2 1 , 1 6 0 3 , 1 0 0 2 , 1 8 5 2 , 1 9 5 0 , 1 8 3 1 , 1 2 2 9 9 3 0 , 1 7 9 2 , 1 0 0 3 , 1 1 0 2 , 1 3 9 0 , 1 2 4 2 , 1 4 3 1 , 1 1 6 7 2 9 9 6 6 2 , 1 1 7 4 , 1 4 7 8 , , 1 y a
6 0 9 8 2 8 2 0 6 9 9 7 9 3 9 8 8 9 5 1 2 , , s l i o , s t a F & , s t u n s n a e b & r a g u S r a g u s s t c u d o r p & h s i F d o o f a e s & s t a e M y r i a d s t c u d o r p & , ) l a n m o N ( n a e M B 3 - 3 E L B A T i e
8 i ) l a n m o N ( n a e M B 3 - 3 E L B A T i e l i t n u q e r u t i d n e p x E ) % 0 2 t s e w o l ( 1 r o t c a F ) % 0 2 t s e h g i h ( – 5 2 4 4 – 5 3 4 5 – 5 4 4 6 – ) s r e b m e m .
o n ( e z i s d l o h e s u o H 4 – 3 6 – 5 1 2 0 9 0 , 1 e r o m r o 7 83340_035-060 3/31/05 8:54 PM Page 43 HOUSEHOLD EXPENDITURE DATA: PATTERNS FOR ANALYSIS 43 | 8 8 1 , 3 5 6 6 , 3 0 2 8 , 3 0 1 8 2 , 8 0 9 , 3 0 5 8 , 3 9 8 5 4 , 1 8 6 6 3 5 2 , 6 6 3 , 3 0 5 8 , 3 5 4 8 4 , 6 6 4 , 3 0 2 5 2 , 3 0 3 , 2 5 2 3 , , 1 9 5 3 , 1 2 4 3 , 1 4 9 9 5 1 4 , 1 6 8 4 , 1 8 6 6 , 1 3 8 8 0 3 8 3 8 1 , 1 6 5 4 , 1 5 0 7 , 1 4 0 2 , 1 1 3 1 , 1 0 4 3 , 1 1 0 2 , 1 8 4 8 1 7 9 6 0 9 5 6 7 1 1 0 , 1 3 5 0 , 1 7 4 0 , 1 1 0 7 8 4 6 5 9 8 3 0 0 , 1 1 4 1 , ) .
o n ( s r e b m e m d l o h e s u o h f o s e g A s r a e y 4 – 0 0 1 e r o m r o 2 s r a e y 4 1 – 5 0 1 2 s r a e y 4 6 – 83340_035-060 3/31/05 8:54 PM Page 44 44 | BAHAMAS LIVING CONDITIONS SURVEY 2001 TABLE 3-4 Average Household Non-food Expenditures, Share in Total, and Household Consumption Non-food expenditure group* Mean annual expenditure Share in total non-food expenditures % Households that consumed over past 12 months Rent Utilities Clothing, footwear, & personal care Clothing & footwear Personal care Household operation Consumer durables (excluding furniture) Household maintenance Cooking fuel Small household items Other non-food items Health Entertainment Transport & communication Education Total non-food expenditures 8,799.2 2,838.5 1,914.6 630.4 1,448.8 545.7 195.1 163.1 3,268.6 2,138.4 2,247.2 1,234.9 1,331.8 26,756.2 *See Table 3-A2 for data on the items within each non-food group.
(4.5%) and education (4.5%), excursions and holidays (3.8%), telephone (3.7%), gasoline (3.4%), and the use value of cars or trucks (3.2%).

The individual expenditure items listed in Table 3-A2 are further grouped into a smaller set of nine non-food groups (Tables 3-5a and b).
FIGURE 3-2 Shares of Non-food Items in Total Non-food Expenditure Household operation 9.1% Education 4.4% Rent 35.5% Health 7.3% Other non-food 9.3% Entertainment 7.3% Transport & communication 4.8% Utilities 11.8% Clothing, footwear, personal care As Figure 3-2 illustrates, utilities comprise 12% of total non-food expenditures, whilst health and education com- bined account for only 11%.
Expenditure Variations by Quintile, Region, and Household Non-food expenditures vary by quintile, region, and household characteristics (including size, composition, and household head) (Tables 3-5A and B).

As Table 3-5B shows, households in the lowest expenditure quintile (quintile 1) pay an average of B$3,718 for rent, whilst those in the highest (quintile 5) pay nearly four times as much.
However, viewed as a share of total non-food ex- penditures, the rent difference between the poorest and wealthiest quintiles is less than 2% (Table 3-5A).

Con- versely, most other types of non-food expenditures are more closely related to living standard.

For example, utili- ties; clothing, footwear, and personal care; household op- eration; and education comprise a smaller share of non- food expenditures for wealthier households.
Variations across Households Rent, as a share of total non-food spending, is positively related to age of household head and household size; 83340_035-060 3/31/05 8:54 PM Page 45 45 | ) s e u tin n o c ( HOUSEHOLD EXPENDITURE DATA: PATTERNS FOR ANALYSIS .

0 0 1 .

4 9 8 9 .

.

9 8 .

5 8 1 .

9 .

7 9 3 .

9 .

2 8 .

2 8 .

7 8 .

5 9 .

4 9 .

9 8 .

6 8 .

4 9 .

7 8 1 .

8 3 .

9 3 .

9 6 9 .

.

2 9 1 .

7 6 4 .

5 5 .

8 4 .

6 2 .

8 4 .

.

7 2 0 2 .

1 .

2 1 .

3 1 .

5 8 5 .

.

2 4 .


7 2 4 2 .

0 4 .

0 5 .

.

2 0 0 2 .

2 5 .

3 .

7 .

5 0 1 5 5 .

.

7 6 6 7 .

6 7 .

0 8 .

3 .

7 .

5 7 8 5 .

.

5 7 3 .

6 .

7 6 2 7 .

4 7 .

.

7 8 .

5 7 4 7 .

2 7 .

5 5 .

.

6 8 .

5 7 9 7 .

8 6 .

0 4 .

6 6 .

8 8 .

.

0 0 1 3 .

2 1 .

0 0 1 .

4 6 1 .

5 1 .

5 .

5 0 1 .

0 0 1 6 9 .

0 9 .

.

2 0 1 1 .

7 .

7 9 8 8 .

.

7 9 9 9 .

8 9 .

.

2 8 7 7 .

6 4 .

3 .

5 2 7 .

0 8 .

8 8 .

3 .

7 2 7 .

6 6 .

1 .

9 1 .

8 7 7 .


6 7 .

0 7 .

8 7 .

9 5 .

1 .

7 6 7 .

9 7 .

3 .

7 .

5 7 0 7 .

8 5 .

6 .

3 9 4 .

3 .

5 6 5 .

4 4 .

9 4 .

8 .

3 2 5 .

3 .

4 .

5 4 4 5 .

.

7 4 1 .

5 .

7 4 6 .

3 4 5 .

8 .

3 1 .

4 9 4 .

1 .

5 0 5 .

.

5 4 4 .

3 1 9 .

1 1 .

4 0 1 9 9 .

0 9 .

3 .

0 1 .

7 0 1 .

8 0 1 9 .

1 1 .

5 4 1 1 .

3 1 .

5 0 1 .

4 0 1 0 8 .

4 7 .

.

5 0 1 .

4 0 1 3 .

9 6 9 .

.

2 0 1 8 .

1 1 .

9 2 1 .

0 4 1 0 .

3 1 .

6 2 1 1 .

1 1 .


4 0 1 5 .

1 1 3 .

3 1 6 .

1 1 1 .

3 1 9 9 .

9 9 .

6 .

1 1 7 .

1 1 2 .

3 1 .

2 4 1 1 .

1 1 .

9 2 1 1 .

1 1 7 .

1 1 4 .

1 1 1 .

2 1 1 .

4 1 .

8 7 3 .

7 7 3 .

8 2 3 1 .

4 3 .

0 6 3 .

8 4 3 .

7 8 3 6 .

3 4 .

9 8 3 .

9 4 3 3 .

3 3 5 .

3 3 .

8 5 3 .

8 5 3 2 .

3 4 .

5 5 3 .

5 5 3 .

0 4 4 .

6 6 3 1 .

4 3 .

9 0 3 .


 – 5 2 4 4 – 5 3 4 5 – 5 4 4 6 – ) s r e b m e m .
o n ( e z i s d l o h e s u o H e r o m r o 7 4 – 3 6 – 5 1 2 n o i g e R 1 2 3 4 ) % 0 2 t s e i h t l a e w ( 2 3 4 5 ) % 0 2 t s e r o o p ( 1 e l i t n u Q i , s e l b a r u d r e m u s n o C d l o h e s u o h , e c n a n e t n i a m & , & t r o p s n a r T , e r a c l a n o s r e P & , - n o N l a t o T n i s p u o r G d o o f - n o N f o e r a h S n a e M A 5 - 3 E L B A T 83340_035-060 3/31/05 8:54 PM Page 46 46 | BAHAMAS LIVING CONDITIONS SURVEY 2001 , s e l b a r u d r e m u s n o C d l o h e s u o h , e c n a n e t n i a m & , & t r o p s n a r T , e r a c l a n o s r e P & , .
o N s r a e y 4 – 0 1 .

9 3 .

9 .

7 8 1 .

9 3 .

9 .

9 8 1 .

9 6 7 .

.

5 8 .

2 9 .

5 9 .

0 0 1 .

2 9 .

5 8 6 9 .

1 .

9 2 .

3 2 7 .

.

0 0 1 8 .

1 6 6 .

.

6 8 .

6 0 1 3 .

0 7 .

1 9 4 .

0 6 .

3 .

7 .

7 4 8 2 .

4 2 .

4 4 .

4 7 .

.

5 7 3 .

6 2 7 .

0 8 .

0 7 .

3 .

7 9 5 .

.

5 6 6 7 .

0 8 .

6 7 .

3 .

7 2 7 .

1 .

8 3 .

7 9 9 .

1 .

8 3 .

7 6 9 .

6 9 .

3 .

9 1 .

7 6 6 .

0 9 .

.

7 9 .

7 9 3 .

9 .

7 9 4 7 .

9 6 .

3 .

9 4 7 .

0 7 .

8 6 .

3 .

7 4 7 .


8 7 .

.

4 6 3 .

4 .

2 8 7 7 .

8 6 .

.

2 6 .

5 7 0 6 .

6 5 .

3 .

7 8 4 .

1 .

5 .

5 4 8 4 .

1 .

5 0 5 .

0 4 .

6 2 .

3 .

4 0 5 .

5 5 .

0 5 .

0 5 .

1 .

3 0 6 .

8 4 .

.

7 9 3 .

2 1 .

9 2 1 .

7 9 5 .

1 1 .

4 0 1 .

7 2 1 6 5 .

8 9 .

.

9 0 1 .

5 0 1 9 .

1 1 .

9 0 1 8 7 .

.

7 6 .

4 0 1 7 .

1 1 7 .

1 1 .

5 2 1 7 .

1 1 5 .

1 1 6 .

1 1 0 .

3 1 .

5 4 1 2 .

1 1 .

9 0 1 3 .

2 1 5 .

3 1 3 .

1 1 .

0 5 1 5 .

3 1 8 .


1 1 .

9 6 3 9 .

1 3 1 .

1 3 .

9 8 3 1 .

1 3 4 .

1 3 .

6 9 2 .

7 2 5 .

8 0 4 .

0 4 3 8 .

1 3 .

2 9 2 .

4 4 3 3 .

2 4 4 .

1 4 .
5 5 3 e r o m r o 2 s r a e y 4 1 – 5 0 1 0 1 2 s r a e y 4 6 – ) d e u tin n o C ( A 5 - 3 E L B A T 83340_035-060 3/31/05 8:54 PM Page 47 HOUSEHOLD EXPENDITURE DATA: PATTERNS FOR ANALYSIS 47 | 3 4 0 , 1 2 4 4 , 1 7 5 1 , 2 4 7 2 2 , 6 0 4 , 3 2 6 4 2 , 6 3 9 , 1 1 1 6 , 1 7 1 3 , 1 3 2 8 , 1 7 9 8 , 1 0 3 4 2 , 3 1 7 2 , 7 5 6 2 , 6 0 0 2 , 2 8 5 2 , 7 7 9 , 1 ) s e u tin n o c ( , s e l b a r u d r e m u s n o C d l o h e s u o h , e c n a n e t n i a m & , & t r o p s n a r T , e r a c l a n o s r e P & , - n o N n o ) $ B ( e r u t i d n e p x E l a u n n A n a e M B 5 - 3 E L B A T 2 7 8 7 0 9 5 0 4 , 1 4 4 5 , 1 9 1 5 , 1 5 8 4 , 1 0 9 5 7 0 4 2 2 4 0 5 6 6 2 1 , 1 9 3 7 , 1 7 3 5 , 1 2 5 9 3 1 8 9 6 4 , 1 7 0 1 , 1 1 4 5 7 5 2 , 1 6 0 8 , 1 5 8 0 2 , 6 3 3 , 3 7 9 1 , 2 5 7 9 , 1 2 2 2 , 1 8 7 7 , 1 2 9 7 , 1 8 4 6 , 1 0 5 1 , 2 8 7 4 2 , 6 0 6 2 , 0 6 8 , 1 6 5 3 , 2 2 8 7 , 1 2 9 4 1 0 5 , 1 4 7 1 , 2 7 0 8 2 , 8 6 9 5 , 7 6 5 , 3 2 9 8 , 1 7 3 4 , 1 3 3 2 , 1 6 8 4 2 , 2 7 8 2 , 4 6 1 , 3 1 6 5 , 3 2 9 8 4 , 4 8 0 2 , 1 8 4 , 3 1 2 9 2 , 3 3 5 9 4 8 7 2 6 , 1 5 2 2 2 , 4 5 8 , 3 8 5 3 , 2 1 2 7 , 1 0 2 4 , 1 1 7 6 , 1 6 0 0 2 , 8 7 8 , 1 8 6 2 2 , 3 5 6 2 , 9 8 7 2 ,
 8 8 4 , 1 1 2 3 , 2 7 2 1 , 2 0 9 3 2 0 8 3 2 2 , 1 4 7 4 , 1 2 9 5 , 1 6 9 2 , 1 3 2 9 6 9 9 9 0 8 3 5 8 7 6 1 , 1 6 7 2 , 1 3 3 3 , 1 7 5 3 , 1 3 0 0 , 1 1 2 4 , 1 0 3 9 7 7 3 , 1 0 1 8 , 1 3 5 2 2 , 4 0 6 2 , 3 2 4 , 3 9 4 6 2 , 6 9 9 , 1 9 5 0 2 , 3 8 9 , 1 0 0 3 , 3 6 4 6 2 , 3 7 5 2 , 2 7 9 2 , 1 9 0 2 , 3 4 7 , 1 4 3 6 2 , 0 0 4 2 , 3 8 6 , 1 3 2 1 , 2 2 3 6 2 , 8 5 7 2 , 3 5 7 , 3 0 8 8 2 , 8 4 8 2 , 9 1 0 2 , 7 2 2 2 , 3 0 1 , 2 1 9 0 2 , 8 0 9 2 , 6 4 2 , 3 9 9 3 , 3 6 2 6 2 , 1 8 9 2 , 5 0 6 2 ,
 8 1 7 , 3 8 6 3 , 5 6 0 6 6 , 2 8 0 8 , 2 4 8 , 3 1 7 9 9 8 , 4 5 4 8 , 3 0 0 7 , 3 9 6 5 , 9 7 5 6 , 4 4 5 6 , 4 3 3 , 8 2 3 1 , 1 1 4 4 9 9 , 7 2 2 8 , 5 2 8 9 , 1 2 1 , 7 d a e h d l o h e s u o h f o e g A 5 2 r e d n U 4 3 – 5 2 4 4 – 5 3 4 5 – 5 4 4 6 – ) % 0 2 t s e i h t l a e w ( 2 3 4 5 ) % 0 2 t s e r o o p ( 1 e l i t n u Q i 83340_035-060 3/31/05 8:54 PM Page 48 48 | BAHAMAS LIVING CONDITIONS SURVEY 2001 , s e l b a r u d r e m u s n o C d l o h e s u o h , e c n a n e t n i a m & , & t r o p s n a r T , e r a c l a n o s r e P & , g n i h t o l c r a e w t o o f 4 7 5 , 1 2 9 2 2 , 3 3 6 2 , 8 6 6 2 , 3 2 5 2 , 4 3 3 , 2 7 1 5 2 , 2 8 0 2 , 2 3 1 , 2 8 8 7 2 , 6 0 5 2 , 8 1 5 2 , 8 5 1 , 1 0 3 7 , 1 3 7 4 2 , 0 9 8 2 , 0 6 8 2 , 1 0 4 2 , 6 1 9 , 1 3 0 5 2 , 3 5 3 , 2 0 3 3 8 4 9 4 7 , 1 8 4 3 , 2 0 8 4 2 , 4 8 0 , 1 8 9 9 , 1 9 8 0 2 , 9 1 5 6 7 1 , 2 4 4 5 2 , 2 2 0 , 3 7 4 7 3 3 3 1 5 , 1 2 9 0 2 , 9 9 0 2 , 7 0 4 , 1 0 5 8 5 4 9 2 3 3 , 1 9 4 1 , 1 4 5 3 , 2 9 8 4 2 , 0 1 4 2 , 3 7 9 , 1 1 7 1 , 2 2 7 1 , 2 3 8 6 , 1 6 2 9 , 1 7 8 5 2 , 7 1 3 , 2 8 7 1 , 2 9 9 1 , 1 6 5 4 , 1 8 3 3 , 2 5 6 6 2 , 3 7 4 2 , 1 6 1 , 2 6 8 8 , 1 8 5 3 , 2 8 3 1 , 2 5 1 0 , 3 7 3 0 , 3 2 6 7 , 3 5 5 1 , 3 3 2 7 2 , 0 1 4 , 3 9 1 0
 , 3 3 6 4 2 , 2 8 0 , 3 7 3 7 , 3 7 9 5 , 3 0 9 8 2 , 0 3 6 , 1 7 1 7 2 , 6 2 4 , 3 1 7 9 , 3 8 6 4 , 3 4 6 4 , 3 4 7 0 2 , 3 1 1 , 2 9 6 2 , 3 4 2 0 2 , 6 2 0 2 , 7 3 5 2 , 3 0 4 2 , 7 9 7 , 1 9 5 2 2 , 1 0 3 , 2 9 5 9 , 1 5 4 0 2 , 0 2 6 2 , 6 6 5 2 , 5 2 2 2 , 3 9 7 8 0 1 , 2 2 4 3 , 2 1 5 7 2 , 3 5 0 2 , 5 6 3 , 2 1 7 5 , 1 3 0 4 , 1 7 4 2 2 , 2 5 7 3 9 0 , 1 2 0 5 , 1 5 7 3 , 1 1 4 3 , 1 3 9 1 , 1 3 6 4 , 1 1 3 0 , 1 4 0 1 , 1 4 1 5 , 1 8 5 4 , 1 3 0 1 , 1 4 4 5 4 2 8 9 1 3 , 1 9 3 5 , 1 4 9 5 , 1 6
 4 8 9 6 2 , 1 0 0 6 , 1 5 3 2 , 1 2 1 6 , 1 6 4 2 2 , 3 8 6 2 , 0 3 2 , 3 1 7 3 , 3 8 8 2 2 , 8 7 3 , 3 3 1 9 2 , 1 0 1 , 2 9 0 3 , 3 3 1 8 2 , 3 1 2 , 3 2 8 6 3 0 8 , 1 1 7 6 2 , 5 1 2 , 3 1 0 3 , 3 9 6 6 2 , 6 6 8 , 1 5 5 5 , 1 5 4 5 2 , ) s r e b m e m .
o n ( e z i s d l o h e s u o H 0 2 1 , 2 8 0 7 2 , 9 0 1 , 3 2 7 9 2 , 6 8 4 , 3 4 9 7 2 , 5 0 0 , 3 9 3 8 2 , 9 3 6 2 , 4 0 2 , 3 1 3 0 , 3 5 8 9 2 , 7 5 1 , 2 3 8 2 2 , 8 8 7 2 , 7 0 3 , 3 6 0 6 , 3 2 3 8 2 , 5 9 7 2 , 5 3 1 , 3 9 3 8 2 , 4 2 8 8 , 0 4 8 8 , 3 2 6 9 , 1 8 1 , 8 4 7 7 6 , 9 4 1 , 9 1 6 0 8 , 3 5 1 , 7 5 8 8 8 , 0 0 7 9 , 1 5 0 8 , 6 0 9 6 , 3 4 1 , 8 3 2 4 8 , 0 1 1 , 9 9 4 2 9 , 3 7 2 8 , 9 8 8 8 , 4 1 9 7 , 0 2 3 , 9 9 9 7 8 , s r e b m e m d l o h e s u o h .
o N e r o m r o 7 s r a e y 4 – 0 4 – 3 6 – 5 1 2 e r o m r o 2 s r a e y 4 1 – 5 0 1 0 1 2 s r a e y 4 6 – ) d e u tin n o C ( B 5 - 3 E L B A T 83340_035-060 3/31/05 8:54 PM Page 49 HOUSEHOLD EXPENDITURE DATA: PATTERNS FOR ANALYSIS 49 | however, there is no clear relationship in absolute amounts.
Spending on clothing, footwear, and personal care comprises a larger share of non-food spending in households with younger heads and in larger households (especially those with more young children).

The other categories of non-food expenditures display no relation- ship with household size and composition.
FINDINGS: FOOD AND NON-FOOD EXPENDITURES To analyse the BLCS findings in terms of all household ex- penditures—both food and non-food—all food items were combined into a single category, whilst non-food items were combined into four groups: housing (rent and utilities); health and education; clothing, footwear, per- sonal care, and entertainment; and other non-food items (Tables 3-6A and B).5 For the typical Bahamian household, housing expenses (rent and utilities) amount to B$11,638, comprising 35% of total expenditures (Figure 3-3 and Table 3-6A).
Food expenditures average B$8,164 per household, accounting for 27% of total expenditures (Table 3-6B).

Clothing, footwear, personal care, and entertainment average B$4,792 (13% of total expenses); whilst health and edu- 5 Expenditure items were grouped in order to examine expenditure variations in terms of household characteristics.

Whilst the grouping of non-food items may appear somewhat arbitrary, it follows a general pri- oritization of expenses in terms of human needs.
FIGURE 3-3 Shares of Food and Non-food Items in Total Annual (Nominal) Expenditures Other non-food items 17.1% Food 26.7% Personal care, clothing, footwear, and entertainment 12.6% Health & education 8.8% cation average B$3,470 (9%).

Expenditures on other non- food items amount to B$6,856 (17%), bringing total nominal expenditures to B$29,489;6 this amount corre- sponds to a median, nominal per-capita expenditure of B$9,754 per year.
Variations across Groups As Tables 3-6A and B illustrate, the share of food in to- tal expenditures declines with a rise in living standard.
Households in quintile 1 spend 36% of total expendi- tures on food, whilst those in quintile 5 spend only 21%.7 Greater concentration of the wealthiest quintile in New Providence and Grand Bahama means that share of food expenditures is lowest on these two islands even though, in absolute terms, the amount spent on food is similar to that of other island regions (Table 3-6A).
Clearly, households with more children below 14 years of age spend more—in absolute terms and as a percentage of total expenditure—on food.

Whilst households headed by younger adults do not spend more on food; food expenditures account for a higher percentage of their total spending.

These variations by household com- position and age of household head do not merely reflect differences in living standards.
Indeed, a regression anal- ysis of the determinants of food share (not reported here) demonstrates that these factors are significant, even after controlling for living standards.

Housing expenses are clearly higher in better-off house- holds and in New Providence and Grand Bahama; however, as a share of total expenditure, they do not exhibit system- atic variation across the living standard or regional spec- trum.
The relatively constant expenditure in households of varying sizes suggests that economies of scale are consider- able with respect to these expenditures.

Health and education expenditures generally increase with household living standard, but the relationship is not perfectly linear.

The bottom 40% of the population spend about 8% of their total expenditure on health and educa- tion.
Amongst the next 40% of the population, spending on health and education is about 2% higher, but then amongst the top 20% it is somewhat lower at 8.5%.

These differences (in expenditure shares) are relatively small, but Housing (rent & utilities) 34.8% 6 The relevant time period for this estimate is October 2000 to De- cember 2001 (the 12 months preceding the survey period).

7 Food share is often used as an indicator of well-being; thus, this pat- tern is not surprising.
83340_035-060 3/31/05 8:54 PM Page 50 TABLE 3-6A Shares of Food and Non-food Items in Total Expenditures Expenditure factor Food Housing (rent & utilities) Health & education Personal care, clothing, footwear, & entertainment Other non-food items Quintile 1 (poorest 20%) 2 3 4 5 (wealthiest 20%) Region 1 2 3 4 Age of household head Under 25 25–34 35–44 45–54 55–64 65 or older Gender of household head Male Female Household size (no.

members) 1 2 3–4 5–6 7 or more No.
household members 0–4 years 0 1 2 or more 5–14 years 0 1 2 3 or more 15–64 years 0 1 2 3 4 or more 65 years or older 0 1 2 or more All Bahamas 83340_035-060 3/31/05 8:54 PM Page 51 TABLE 3-6B Total Annual (Nominal) Expenditures Expenditure factor Quintile 1 (poorest 20%) 2 3 4 5 (wealthiest 20%) Region 1 2 3 4 Age of household head Under 25 25–34 35–44 45–54 55–64 65 or older Gender of household head Male Female Household size (no.
members) 1 2 3–4 5–6 7 or more No.
household members 0–4 years 0 1 2 or more 5–14 years 0 1 2 3 or more 15–64 years 0 1 2 3 4 or more 65 years or over 0 1 2 or more All Bahamas Food Housing (rent & utilities) Health & education Personal care, clothing, footwear, & entertainment Other non-food items 83340_035-060 3/31/05 8:54 PM Page 52 52 | BAHAMAS LIVING CONDITIONS SURVEY 2001 as Table 3-6B
 shows, in absolute amounts, the differences are large: the wealthiest 20% (quintile 5) spend 3.4 times the amount spent by the poorest 20% (quintile 1).
Region 1 households spend considerably more than the other three regions on health and education—as a share of total expenditures and in absolute amounts.

These expen- ditures vary by age of household head, number of young children, and household size.

Such patterns are also ap- parent in expenditure shares (Table 6A); however, the dif- ferences are less striking.
Expenditures on clothing, footwear, personal care, and entertainment increase—in terms of absolute amounts and expenditure share—as living standards rise and de- cline as household heads grow older; however, the differ- ences are small.

Variation in expenditures on other non- food items is more pronounced; however, with the exception of differences between expenditure quintiles, no patterns are easily discernable.

CONCLUSIONS The BLCS examination of household expenditures reveals interesting patterns.
Based on the findings, the average per-capita food expenditure is about $8.41 per day, of which $2.85 is spent on food eaten away from home.
Us- ing the detailed Survey data on food-expenditure patterns, it should be possible to determine, in general, the nutri- tional adequacy represented by this level of spending.8 Survey results demonstrate clearly that food expendi- tures vary with living standards in predictable ways; that is, share of total expenditure devoted to food items declines with an increase in living standard.
In such large samples as the BLCS—involving several interviewers, several hundred respondents, and a lengthy interview process—this result is 8 Although this research is outside the scope of this chapter, the general approach is straightforward.

Using the BLCS data collected on market prices, it is possible to calculate average quantities consumed by house- holds.
Along with information from widely-used food composition ta- bles, it should be possible to determine the nutritional adequacy of the diets across Bahamian groups.

Obviously, this would not be the same as carefully collecting dietary histories and food consumption data, and thus should not be used for individual counseling; however, in being representative of the entire country, it would highlight the nutritional health of the population.
One limitation of this exercise would be the inability to determine the nutritional composition of food eaten away from home.

reassuring, as it points to a reasonable degree of internal consistency in the data collected.

Interestingly, amongst the poorest quintile—even within the poorest decile—food share amounts to only about 37% of total expenditure.

As mentioned above, the largest component of food expenditure is food eaten away from home, which ac- counts for 34% of the total spent on food.
Had the Survey instrument been designed to collect information on the types of foods that comprise this expenditure, this data could have been used for nutritional analysis.

Even if it had been, however, it would still have been limited by the difficulty in translating expenditures incurred away from home into quantities and quality of food consumed by in- dividuals.
Nevertheless, given the primacy of expenditures on food eaten away from home, it is imperative that future surveys attempt to collect more detailed information on these types of expenditures.

That rent (actual or imputed) represents the largest component of non-food expenditures—and is uniformly above 34% for households across the economic well-being spectrum—has critical implications for welfare policy.
As housing values increase—with economic development and, at times, in a speculative market—the poorest of the poor are increasingly likely to face conditions in which housing is unaffordable.9 How welfare policy addresses the issue of affordable housing is likely crucial to how the country addresses poverty and equity (see chapter 8).
Health and education, the critical avenues for ensuring a reasonable degree of equity and opportunity in a market economy, together represent less than 10% of the average Bahamian household’s annual expenditures (see chapters 4 and 5, respectively).

As a share of total expenditure there is relatively little variation across households from different economic strata, but in absolute amounts there is large variation since the poorest 20% spend 25–33% of what the wealthiest 20% spend.
Whether these differences in private household expenditures reflect differences in the quality of schooling received by children from different economic backgrounds—and the extent to which they hide differences in public subsidies—requires careful anal- ysis, as this issue is often a matter of policy debate in mar- ket economies.

9 Assuming that the location of housing is reasonably convenient to work and basic amenities.
83340_035-060 3/31/05 8:54 PM Page 53 HOUSEHOLD EXPENDITURE DATA: PATTERNS FOR ANALYSIS 53 | LOOKING AHEAD: CONDITIONS FOR DATA APPLICATION The patterns revealed by the BLCS household-expendi- ture data are rich in content and can be put to worthy use for public policy and market analysis.

However, any such use must carefully consider the instruments and methods used to collect this data, a point sometimes forgotten in the rush to use a new data set.
The BLCS instruments are based on a wide body of research that spans the entire globe, and they have been painstakingly tested in the Ba- hamian context.

A capable set of interviewers administered these instruments; they used methods—those that inter- national and statistical organizations, including the World Bank, have applied around the world for more than 20 years—to digitize, check, and organize the data.
Thus, the data are internally consistent and provide a reasonably good snapshot of spending patterns in the country.
83340_035-060 3/31/05 8:54 PM Page 54 54 | BAHAMAS LIVING CONDITIONS SURVEY 2001 APPENDIX TABLE 3-A1 Average Household Food Expenditures, Share in Total, and Household Consumption; by Food Group/Item Food group/item Mean annual expenditure Share in total food expenditures % Households that consumed over past 12 months Staples (cereals, roots, and tubers) Bread Breakfast cereal (cold) Rice Pasta Breakfast cereal (hot) Potatoes (w & s) Plantains Grits Flour Root crops Prepared flour mixes Fruits & vegetables Banana Grapes & berries Limes, lemons, & big sours Apple Other citrus fruit Tomato (fresh) Other fresh fruit Canned vegetable Frozen vegetable Onion Other fresh vegetable Lettuce Tomato paste & sauce Other fresh local fruit Sweet pepper Carrot Cabbage Canned fruit & fruit filling Avocado Tomato (canned) Cucumber Frozen fruit Meats & dairy products Chicken (fresh & frozen) Beef Fresh milk 83340_035-060 3/31/05 8:54 PM Page 55 HOUSEHOLD EXPENDITURE DATA: PATTERNS FOR
 ANALYSIS 55 | TABLE 3-A1 (Continued) Food group/item Mean annual expenditure Share in total food expenditures % Households that consumed over past 12 months Pork Deli-meat Turkey Canned milk Hot dogs & other Cheese Tinned meat Eggs Ice cream & related products Lamb-mutton Ham Other poultry Bacon Other milk product Organ meat (liver, kidney, etc) Fish & seafood Fish (fresh & frozen) Conch Tinned fish & seafood Crawfish Crab Other marine products Sugar and sugar products Cakes & pastries Sugar Candy,
 chocolate, & chewing gum Jams & jellies Honey & artificial sweeteners Other confectioneries Fats, oils, nuts, & beans Peas & beans Cooking oil, shortening, & lard Butter, margarine, & vegetable spreads Nuts & dried fruit Peanut butter Creamers & non-dairy substitutes Other fats & oils Bottled water Fruit juice Soft drink Beer, wine, & other alcoholic beverages Other non-alcoholic drinks (continues) 83340_035-060 3/31/05 8:54 PM Page 56 56 | BAHAMAS LIVING CONDITIONS SURVEY 2001 TABLE 3-A1 (Continued) Food group/item Mean annual expenditure Share in total food expenditures % Households that consumed over past 12 months Other foods Snacks Canned & packaged soup Seasoning, salt, spices, olives, etc.
Coffee, tea, & cocoa Baby food & juice Baby milk/formula Tomato ketchup, mustard, & hot sauce Mayonnaise Miscellaneous foods Salad dressing Frozen prepared food Rising agents Other condiments 83340_035-060 3/31/05 8:54 PM Page 57 HOUSEHOLD EXPENDITURE DATA: PATTERNS FOR ANALYSIS 57 | TABLE 3-A2 Average Household Non-food Expenditures, Share in Total, and Household Consumption; by Non-food Group/Item Non-food group/item Mean annual expenditure Share in total food expenditures % Households that consumed over past 12 months Rent Utilities Electricity Telephone (includes mobile) Water Garbage collection fees Sewage Clothing, footwear, & personal care Clothing & footwear Women’s clothing Men’s clothing Children’s clothing (excluding uniforms) Laundry & dry cleaning Women’s footwear Jewelry & accessories Men’s footwear Cloth & sewing supplies Tailoring expenses Shoe repair & cleaning services Personal care Personal services Personal-care items Infant personal-care items Medical supplies/equipment Cosmetics Household operation Consumer durables (excluding furniture) Car or truck Boat Personal computer Television Refrigerator Stove Air conditioner (wall unit) Washing machine Tape player/CD player Camera/video camera Freezer Video player/DVD player Microwave oven Vacuum cleaner Fan 8,799.21 2,838.51 1,633.53 923.25 247.06 21.60
(continues) Staples (cereals, roots, and tubers) 631.7 8.9 98.8 83340_035-060 3/31/05 8:54 PM Page 58 58 | BAHAMAS LIVING CONDITIONS SURVEY 2001 TABLE 3-A2 (Continued) Non-food group/item Mean annual expenditure Share in total food expenditures % Households that consumed over past 12 months Water heater Clothes dryer Bicycle Video games Motorcycle/scooter Lawnmower Sewing/knitting machine Household maintenance Cleaning articles Toilet supplies (paper, cleanser, etc.)
Kitchen supplies Item repair & maintenance Electrical items (light bulbs, cords, plugs, & batteries) Cooking fuel LPG Condo assoc.

& property maintenance fees Charcoal Kerosene Small household items Linens (sheets, blankets, towels) Dishes (crockery, cutlery, glassware, etc.)

Utensils (pots, pans, buckets, tools, etc.)

Small electrical items (radio, walkman, watch, clock) Small kitchen appliances (blender, mixer, etc.)
Household tools Other non-food items Life insurance premiums Insurance (auto & property) Contributions to Ague’s, Christmas clubs, etc.
Domestic staff (maids, gardeners, chauffeurs) Legal or notary services Funeral expenses Membership fees (clubs & associations) 83340_035-060 3/31/05 8:54 PM Page 59 HOUSEHOLD EXPENDITURE DATA: PATTERNS FOR ANALYSIS 59 | TABLE 3-A2 (Continued) Non-food group/item Mean annual expenditure Share in total food expenditures % Households that consumed over past 12 months Health Health & dental insurance premium Outpatient care Inpatient care Entertainment Excursion, holiday Cable TV & satellite services; Internet & beeper fees Pet supplies & services Newspapers & magazines Cinema; cultural & sporting events Toys CDs & cassettes Books (excluding textbooks) & stationery Cigarettes, cigars, & tobacco Gambling (lottery, etc.)
Photography supplies & services Sports & hobby equipment Musical instruments Transport & communication Gasoline Parking fees & motor-vehicle licenses Transportation costs Postal expenses, telegrams, & pre-paid phone cards Diesel fuel Education School tuition, fees, books, uniforms, & meals 83340_035-060 3/31/05 8:54 PM Page 60 83340_061-086 3/31/05 9:20 PM Page 61 CHAPTER 4 Health Status: Socioeconomic Analysis Camille S. Deleveaux, Arneta D. Clarke, Sandra C. Adderley-Coleby, Adelma L. Penn, and Melissa Underwood T he health of any country’s population is affected by the socioeconomic status (SES) of its citizens.
The Bahamas Living Conditions Survey (BLCS) provided an opportu- nity to evaluate the causal link between SES and health in the Bahamian context.

In addition, the Survey provided a baseline for selected health in- dicators, while allowing for a comparison with the findings of earlier investigations.
It examined the following health-related areas: self-reported health status; child health; nutritional status of children, adolescents, and adults; female-repro- ductive health; health-services use and expendi- ture; and health-insurance coverage.

SELF-REPORTED HEALTH STATUS Whilst self-reporting reveals much about a pop- ulation’s health, it is subject to biases that lead to underreporting; thus, a population’s true health status may be clouded by survey respondents’ perception and level of well-being.
If feasible, health measures that use physical evaluations are preferable and more accurate.

Ideally, both mea- sures can be used to enhance understanding of a population’s health status.

Inferences drawn from findings based on self-reporting should be considered in light of these limitations.

BLCS respondents were asked to report on several aspects of their health status: recent ill- ness, injury or accident, and disability.
They were also asked whether they had previously been diagnosed with chronic diabetes and hyper- tension.

Approximately 1 in 10 respondents (13.4%) reported having had an illness or injury during the four-week period preceding the sur- vey (Table 4-1); of these, slightly more than half (53.6%) subsequently visited a health practi- tioner to treat their condition.
The majority of those who did not seek treatment either found it unnecessary (57%) or chose to self-medicate at home (41%).1 The average length of illness was eight days.

1 With initial symptoms of illness, self-medication is a com- mon tendency in The Bahamas, where over-the-counter drugs are readily available and “bush” medicine is com- monly practiced.
61 83340_061-086 3/31/05 9:20 PM Page 62 62 | BAHAMAS LIVING CONDITIONS SURVEY 2001 TABLE 4-1 Ill Residents Who Sought Care (%), by Population Characteristic Population characteristic Gender Male Female Age group (years) 0–4 5–14 15–19 20–34 35–54 55–64 65 and older Region 1 2 3 4 Quintile Total Ill residents (%) 11.8 14.9 23.1 12.2 7.6 11.0 13.4 12.6 20.3 13.4 15.1 10.6 9.2 10.7 10.5 14.9 15.0 15.7 13.4 N 3,152 3,262 625 1,394 503 1,435 1,623 389 446 3,413 1,775 621 605 1,560 1,325 1,247 1,173 1,024 6,414 Ill residents who sought care (%) 49.2 56.8 69.4 51.8 39.1 43.7 52.8 41.6 66.2 53.0 56.4 61.6 56.4 49.5 63.1 51.7 52.0 49.9 53.6 N 382 465 142 172 33 152 217 47 84 457 267 67 56 161 147 178 189 164 847 In terms of gender, fewer males (11.8%) than females (14.9%) reported an illness.
Vulnerable or immuno- compromised groups—children under 5 years (23.1%) and adults 65 years and older (20.3%)—were more likely to report an illness during the reference period.

Reporting of illness was also higher amongst persons from the better- off households; for example, 15.7% of those from the wealthiest quintile (of per-capita consumption expendi- ture) reported being ill, compared to only 10.8% from the poorest quintile.
Higher reporting of illness amongst better-off households is consistent with similar surveys conducted around the world, and is often viewed as repre- sentative of reporting bias rather than poorer health status.

Geographically, more residents (15.1%) of the Family Islands of Region 2 (Abaco, Andros, and Eleuthera)— where about 10% of Bahamians live—reported an illness than persons residing in the other three regions (Table 4-1).
Disabilities and Injuries The Survey sought to determine the prevalence of both physical and mental disabilities in the population (Table 4-2).

Approximately 6% of the sample population re- ported having a physical or mental disability.

Of those who had a disability, 68.5% of reported disabilities were related to sight, hearing, or speech; 18.2% to limbs; and 13.3% to mental disabilities.

Males and females were equally likely (6%) to report having a disability.
Regardless of the type of physical or mental disability, it generally increased with age.

For ex- ample, whilst only 3.7% of children under 5 years of age had a disability, 17.6% of the elderly were disabled—a nearly fivefold increase.

Mental disabilities were also more common amongst the elderly (2.3%) (Figure 4-1).
These findings support conclusions drawn from institu- tional data, which show that aging is associated with 83340_061-086 3/31/05 9:20 PM Page 63 TABLE 4-2 Proportion of Respondents with a Disability or Injury in Past 12 Months FIGURE 4-1 Prevalence of Disability, by Type and Age Group HEALTH STATUS: SOCIOECONOMIC ANALYSIS 63 | Population characteristic Physical or mental disability (%) Injury (%) N Gender Male Female Age group (years) 0–4 5–14 15–19 20–34 35–54 55–64 65 and older Region 1 2 3 4 Quintile Total disability, which further affects quality of life and may be linked to poverty.
That residents in quintile 4 had the highest proportion of disability (8.5%) requires further investigation.

Lowest reporting of disabilities was found in quintiles 3 (3.3%) and 5 (4.6%).

Lack of a systematic pattern suggests that living standards bear little relationship to incidence of dis- ability in the population or that the effect is heavily out- weighed by other factors, such as age.
Residents of Region 3 (Exuma and Long Island) had the greatest proportion (9.5%) of persons with disabilities overall—both physical (7%) and mental (2.5%)—whilst the lowest proportion was found in Region 2 (Abaco, An- dros, and Eleuthera) (4.0%), where the elderly population comprises about 7%.
Respondents were asked whether they had experienced any injury due to an accident at their workplace, gunshot, t n e c r e P 16 14 12 10 8 6 4 2 0 8.9 15.2 2.3 3.7 4.0 3.1 5.2 4.5 0.0 < 5 0.1 5–14 0.7 0.5 0.8 0.8 15–19 20–34 35–54 55–64 65+ Age Group (Years) Physical Mental stabbing, or other external cause during the past 12 months (Table 4-2).

Approximately 4% of the popula- tion—4.7% of males and 4.1% of females—reported an injury over the reference period.
Most incidents occurred at work or school (63%) (Figure 4-2).

The proportion of reported injuries was highest amongst the elderly (5.9%), who are more likely to experience falls, and amongst work- ing-age individuals in age groups 20–34 years (5.7%) and 35–54 years (5.1%).
FIGURE 4-2 Distribution of Injuries, by Type (%) Occupational/ School 63% Motor Vehicle Accident 12% Gunshot/Stab 10% Other 15% (n = 246) 83340_061-086 3/31/05 9:20 PM Page 64 64 | BAHAMAS LIVING CONDITIONS SURVEY 2001 The highest and lowest occurrences of injuries were found in quintiles 4 (6.7%) and 3 (2.1%), respectively.
In terms of region of residence, Bahamians on the most de- veloped islands of New Providence and Grand Bahama (Region 1), as well as Exuma and Long Island (Region 3), had the most injuries.

Diabetes and Hypertension To estimate the prevalence of diabetes and hypertension, BLCS respondents were asked whether they had a history of those conditions or whether a doctor or nurse had ever told them they had these chronic diseases.
Notably, it is well documented that reported history of diabetes and hy- pertension is significantly lower than what actually occurs in a population.

As Table 4-3 shows, prevalence of diabetes was 3.3%, with knowledge of the condition more prevalent amongst females (3.8%) than males (2.7%), a significant difference, proven by chi-square testing (p 0.000).
Amongst males, prevalence increased from nearly 1% for those 20–34 years of age to about 17% for those 55–64 years old, and remained at the same level amongst elderly men 65 years and older.

Amongst females, preva- lence increased from less than 1% (0.1%) for girls un- der 20 years old, peaking at 19.1% for women 55–64 years old, and then declining to 15.7% amongst elderly women.
National Health and Nutrition Survey (NHNS) (1988–1989) respondents were asked: “Has a doctor ever told you that you have diabetes?” Answers showed that prevalence of self-reported diabetes was 3.3% in the 15- to-64 age group, and 14% in the elderly group.

Corre- sponding BLCS rates were 3.8% and 16.4%, respectively.
Higher rates may have resulted from changing lifestyle TABLE 4-3 Self-reported Diabetes and Hypertension and Proportion Treated Diabetes Hypertension Population characteristic Self-reported diagnosis (%) Gender Male Female Age group (years) 0–4 5–14 15–19 20–34 35–54 55–64 65 and over Region 1 2 3 4 Quintile Total 2.7 3.8 0.0 0.1 0.0 1.3 4.4 18.2 16.4 3.0 5.1 5.3 5.0 2.2 3.1 3.9 3.1 4.2 3.3 Received treatment (%) 88.6 90.1 0.0 100.0 0.0 78.3 83.2 95.5 95.1 90.0 87.8 88.4 87.3 95.7 92.7 86.1 96.3 81.8 89.5 N 3,152 3,262 625 1,394 503 1,435 1,623 389 446 3,413 1,775 621 605 1,560 1,325 1,247 1,173 1,024 6,414 N 94 160 0 1 0 18 83 74 78 101 89 33 31 48 61 48 46 48 254 Self-reported diagnosis (%) 6.1 12.3 0.3 0.2 0.1 3.8 15.8 36.0 44.0 8.3 15.1 14.0 13.3 6.4 7.3 9.8 9.9 13.1 9.3 Received treatment (%) 85.2 92.4 11.1 47.6 0.0 78.3 88.5 90.8 99.5 90.2 89.4 94.4 86.8 95.8 92.4 89.8 91.6 84.6 90.1 N 3,252 3,262 625 1,394 503 1,435 1,623 389 446 3,413 1,775 621 605 1,560 1,325 1,247 1,173 1,024 6,414 N 242 479 2 2 1 69 295 158 194 289 263 88 81 137 129 148 142 155 721 83340_061-086 3/31/05 9:20 PM Page 65 practices and increased obesity—a risk factor for diabetes—in addition to a growing elderly population.
In the BLCS, prevalence of diabetes based on reported history increased as levels of consumption rose between the first (2.3%) and third (3.9%) quintiles, but fluctuated thereafter; a statistical association was not found between the proportion of persons with diabetes and quintile levels.

These results may reflect differences in obesity levels across consumption groups.
The highest prevalence of diabetes (about 5%) was found in the Family Islands (Regions 2, 3, and 4), as com- pared to 3% in the urban areas of Region 1 (New Provi- dence and Grand Bahama).

One contributing factor may have been the elevated levels of obesity amongst adults in these regions, as first reported in the NHNS and observed in the present BLCS.
In addition, low consumption of complex carbohydrates—including fresh fruits and veg- etables, root crops, and legumes—persists.2 Nearly 1 out every 10 persons (9.3%) had a self- reported history of hypertension, with rates for females about twice that of males (12.3% versus 6.2%).

Like dia- betes, reported hypertension increased with age, from about 4% in adults aged 20–34 years, to 44% in the el- derly.
The proportion of females with a history of hyper- tension increased from less than 1% (0.2%) in girls under 20 years old to 50.9% in elderly women; that is, 1 out of every 2 women 65 years or older had a reported history of hypertension.

Self-reported hypertension amongst males ranged from less than 1% in boys under 20 years old to about 34.5% in elderly men.
NHNS blood-pressure measurements showed that prevalence of hypertension amongst adults aged 15–64 years was 13%,3 compared to BLCS self-reported results of 11% for the same age group.

In addition, the NHNS classified 37.9% of those 65 years or older as hypertensive by blood-pressure measurement, compared to 53.1% who reported hypertension.

In the BLCS, 44% of the el- derly reported a history of hypertension.
In the NHNS, self-reporting was determined by responses to a question similar to that asked in the BLCS: “Did a doctor ever tell you that you had hypertension?” 2 This problem is evidenced in the most recent Food and Agriculture Organization (FAO) data on food availability data, as well as in NHNS observations.

3 NHNS classification for hypertension was systolic 160 and/or dias- tolic 95.
HEALTH STATUS: SOCIOECONOMIC ANALYSIS 65 | Analysis by quintiles of consumption groups showed the proportion of self-reported hypertension to increase by quintile, rising from 6.4% in the lowest, to 13.1% in the highest.

This may reflect a tendency of better-off individ- uals to seek health care, thus having a greater opportunity for diagnosis.
The highest prevalence of hypertension by reported history was 15.1%, found in Region 2 (Abaco, Andros, and Eleuthera), whilst the lowest was 8.4%, found in Re- gion 1 (New Providence and Grand Bahama).

About 9 out of every 10 persons with a history of dia- betes or hypertension subsequently received treatment, and a greater proportion of these persons was 55 years or older.

Those most likely to seek treatment lived on islands with greater access to health care (New Providence and Grand Bahama) (90.5%).
A greater percentage from Re- gion 3 (Exuma and Long Island) was treated for hyperten- sion (94.4%).

Whilst the proportion of treated persons was high, the extent of compliance with prescribed medications to con- trol the conditions is not known.
Consequently, in addi- tion to the need to reduce the percentage of untreated per- sons, particularly adults 54 years and younger, an aggressive approach is needed to create awareness of the signs and symptoms of diabetes and related complications to improve compliance.

These findings on diabetes and hypertension ade- quately reflect the current reality in the population.
Both diseases present a public-health problem of alarming pro- portion, which, if ignored, could result in a deficit of hu- man capital and reduced quality of life.

CHILD HEALTH In terms of childhood illness, BLCS results showed that, in children ages 5 years and younger, respiratory illness is a major concern.
During the four weeks prior to the Sur- vey, amongst children in this age group, coughs, colds, and runny noses were the most common illnesses (41.6%), followed by diarrhoea (6.6%) and asthma (2.4%).

A greater percentage of girls than boys was re- ported as having each illness; however, no significant sta- tistical association was found by gender (Table 4-4).
Incidence of diarrhoea amongst children five years of age and younger was 7.8%; only 3 out of every 10 (28.6%) who suffered with the condition were given oral rehydra- tion therapy, the course of treatment recommended by the 83340_061-086 3/31/05 9:20 PM Page 66 66 | BAHAMAS LIVING CONDITIONS SURVEY 2001 TABLE 4-4 Proportion of Children Five Years and Younger with Common Illnesses in Past Four Weeks Cough, cold, or runny nose 42.1 44.7 46.9 46.4 36.8 43.8 41.6 41.0 34.8 41.4 45.1 45.1 39.5 47.9 41.6 Population characteristic Gender Male Female Age group (years) 0–1 2–3 4–5 Region 1 2 3 4 Quintile Total Asthma Diarrhoea N World Health Organization (WHO).
Most of the chil- dren affected were in the lowest consumption quintile.

Re- gion 4 (Other Family Islands) had the highest incidence (16.5%), whilst Region 3 (Exuma and Long Island) had the lowest (2.2%).

As part of the Expanded Program on Immunization (EPI), children in The Bahamas are immunized against Diphtheria, Pertussis, and Tetanus (DPT), Poliomyelitis (Polio), Haemophilus Influenza Type B (HIB) and Hep- atitis B (Hep B) within the first year of life; and Measles, Mumps, and Rubella (MMR) at age 1.
DPT and HIB boosters are given at 15 months, whilst Paediatric Diph- theria Tetanus (Paed DT), Polio, and MMR boosters are given at ages 4–5 years.

In accordance with the national immunization sched- ule, coverage levels for infants and children ages 0–71 months who had received the required three doses of vac- cines on schedule were: DPT (88.8%); Polio (87.2%); HIB (71.9%); and Hep B (32.1%).4 Coverage amongst children 12–71 months who received their first dose of MMR on schedule was 69.1% (Figure 4-3).
Amongst infants 6–11 months, the coverage level was 74% for DPT, Polio, and HIB; and, amongst children 12–23 months, MMR coverage was 74%.

Less than 3% of the children surveyed were not immu- nized against DPT and Polio.

Higher proportions were not immunized for HIB (12.6%), Hep B (48%), and MMR (7.7%) (Figure 4-4).
Immunization coverage (for DPT, Polio, and HIB) was generally higher amongst children from progressively better-off households, but sample sizes were smaller in the upper two quintiles (Table 4-5).

Amongst the four regions, Exuma and Long Island had the highest reported coverage levels for DPT (93%) and Polio (97.5%).
Both Exuma and Long Island and Other Family Islands had the highest coverage for MMR (76%), whilst New Providence and Grand Bahama had the high- est for HIB (74.9%) and Hep B (35.7%) (Table 4-5).

The immunization or vaccination card, used to verify a child’s immunization status, is a requirement for school enrolment.
The Child Health Passport (CHP), currently used in place of the original immunization card, was 4 The Hep B vaccine, as part of the pentavalent vaccine, was introduced to the public sector in July 2001, which explains its low coverage level at the time of the BLCS.
FIGURE 4-3 Vaccination Coverage Amongst Children 0–71 Months, by Vaccine t n e c r e P 100 80 60 40 20 0 88.8 87.2 71.9 69.1 32.1 DPT3 Polio Hep B MMR HIB Vaccine 83340_061-086 3/31/05 9:20 PM Page 67 FIGURE 4-4 Children 0–71 Months Not Vaccinated or Behind Schedule t n e c r e P 60 50 40 30 20 10 0 47.7 8.2 8.4 1.6 1.5 2.7 1.7 DPT Polio 12.6 12.2 3.3 HIB Vaccine 15.3 5 19.9 7.7 3.3 Hep B MMR Not Vaccinated Behind Schedule Not Known* *While most of these children were vaccinated, a card was not pro- duced to verify dosage.
HEALTH STATUS: SOCIOECONOMIC ANALYSIS 67 | presented for about 88% of children who participated in the BLCS.

Nurse enumerators then reviewed the card and determined coverage levels.

The CHP may have presented some limitations during data collection, as it was not designed to capture new vaccines added to the national immunization schedule.
In evaluating the immunization status of infants and children 0–5 years, coverage levels reported for children under 1 year were slightly lower than national figures (Table 4-6A).

However, through defaulter tracing and im- munization outreach, coverage levels usually increased by age 2, as reflected in Survey findings.

Potential factors contributing to low coverage levels included small or non- representative sample sizes for children under 2 years.
In addition, CHPs may not have been up to date; moreover, children may not have been due their third dose at the TABLE 4-5 Immunization Coverage Amongst Children 0–71 Months Population characteristic DPT (%) N Polio (%) N HIB (%) N Hep B (%) N MMR1 (%) N Gender Male Female Age (months) 0–5 6–11 12–23 24–71 Region 1 2 3 4 Quintile Total n.a.
n.a.

73.62 69.6 62.6 75.5 76.5 66.1 71.8 67.5 71.5 71.4 69.1 259 248 n.a.

n.a.

90 2 284 144 37 42 161 109 109 84 44 507 1 Children ages 12–71 months.

2 MMR age groups differed for older children: 24–47 mo.

coverage 93.0% (n 196); 48–71 mo.

coverage 44.4% (n 221).

n.a.

 not applicable.


83340_061-086 3/31/05 9:20 PM Page 68 68 | BAHAMAS LIVING CONDITIONS SURVEY 2001 TABLE 4-6A National Immunization Coverage Levels, 1997–2000 coverage was reported at 99% for DPT; 92% for Polio and HIB; and 94% for MMR (Tables 4-6A and B).

Coverage level NUTRITIONAL STATUS OF CHILDREN Vaccine type 1997 1998 1999 2000 DPT Polio HIB Hep B MMR 87 86 n.a n.a 94 89 88 n.a n.a 92 84 84 77 n.a 87 99 92 92 n.a.

94 n.a.

 not applicable.


time of the Survey because of defaulting.

Additional con- tributing factors were the recent introduction of HIB and Hep B into the national immunization schedule.5 National figures for the 1997–2000 period show that, amongst vaccine-preventable diseases, there were no re- ported cases of DPT, whooping cough, polio, tetanus neonatorum, or mumps.

In 1997 and 1998, respectively, one case of measles and four cases of congenital rubella were reported.
Since introduction of the HIB vaccination in 1999, the number of reported cases declined from six that year to none in 2000.

In 2000, national vaccination 5 HIB was introduced into the schedule in 1999, and Hep B was in- cluded in 2001; however, at the time the BLCS was conducted, the third dose of Hep B was not administered routinely to infants under age 1 by all private doctors.
TABLE 4-6B Vaccine-preventable Cases Reported, 1997–2000 Disease 1997 1998 1999 2000 Diphtheria Whooping cough Poliomyelitis Tetanus neonatorum Measles Mumps Congenital rubella syndrome Rubella (German measles) Hep B HIB The nutritional status of children 2–10 years was assessed, using the anthropometric measurements of weight and height compared with WHO reference standards (Z- scores).
The three indices examined were Weight for Age (WAZ), Height for Age (HAZ), and Weight for Height (WHZ).

WAZ compares a child’s weight with the WHO reference standard weight for a child of the same age.

WAZ is the easiest indicator to measure, and therefore the most common measure of nutritional well-being.

HAZ compares a child’s height with the WHO refer- ence standard height for a child of the same age.
In chil- dren older than 3 years, HAZ is a proxy for the cumulative environmental conditions—past influences—of the pe- riod of earlier growth, principal amongst which is the ef- fect of poor nutrition (a clear indicator of stunted growth).

In children younger than 3 years, HAZ is a proxy for past and current influences on nutritional status, as well as fu- ture growth failure and resulting associated risk; it is also a stronger predictor of mortality in children of this age.
WHZ compares a child’s weight with the WHO reference standard weight for a child of the same height.

It is used to assess wasting, is the most sensitive measure of the three used, and is a proxy for current nutritional status.

Across a population, it is generally expected that 2.3% of children will be undernourished (Z-score of 2.00), whilst 2.3% will be overnourished (Z-score of 2.00).
Prevalence of Undernutrition As shown in Table 4-7, 11% of Bahamian children had low HAZ, whilst 6% had low WHZ.

The indicators stunt- ing (low HAZ) and wasting (low WHZ) were at least three times greater than what is normally expected, with Region 1 indicating the highest prevalence.

These levels suggest the population may have pockets of endemic undernutri- tion.

This extreme situation is difficult to assess in this type of survey and requires surveillance and clinic-based data.
The proportion of children with low weight for age (WAZ) (3.3%) was within normal levels (Table 4-7).

Stunting is slightly more prevalent amongst boys (11%) than girls (10% ), and both percentages are unacceptably high.
Using the other two indicators—WHZ and WAZ— percentages were significantly lower, with 8% of boys and 83340_061-086 3/31/05 9:20 PM Page 69 HEALTH STATUS: SOCIOECONOMIC ANALYSIS 69 | TABLE 4-7 Low and High Z-scores for Children 2–10 Years of Age* Population characteristic 2.0 2.0 2.0 2.0 2.0 2.0 HAZ-score (%) WAZ-score (%) WHZ-score (%) Gender Male Female Region 1 2 3 4 Quintile Total N 492 332 437 212 87 88 273 181 175 130 65 824 * Low Z-scores 2.0; high Z-scores 2.0.
4% of girls having low WHZ; 4% of boys had low WAZ, whilst the percentage of girls with low WAZ (2%) was in keeping with the expected proportion (Table 4-7).

The highest rate of stunting was found amongst the youngest population, with proportions declining as chil- dren grew older.

The HAZ-score indicated that 15% of children 2–4 years of age were at significant risk of stunt- ing; that proportion was more than halved (7%) in chil- dren 7–10 years of age.
These results show a reverse of the pattern usually found in populations with a certain level of food deprivation; they may suggest an error in either data collection or measurement or reflect a current or emerging economic situation that is acutely depressed.

In any event, these results warrant further investigation by the social agencies of the various ministries and the local, national, and international institutions involved.
The overall trend of low WHZ-scores (wasting), which reflect current nutritional status, showed that the potential for undernourishment increased as children grew older.

This was evident in the increase from 4% in children 2–4 years to 8% in children 7–10 years, a proportion triple that of what is expected by global standards.

This pattern deviates from what is typically found in other surveys.
In the BLCS, the higher prevalence of wasting amongst older children reflects similar results from two previous surveys, and may indicate that, within households, the nutritional status of younger children is a priority.

Both WHZ- and HAZ-scores showed the highest prevalence of undernutrition on the urbanized islands of Region 1 (New Providence and Grand Bahama) and the lowest on the less developed Family Islands of Region 4 (Other Family Islands).
In both developing and developed countries, this pattern suggests that, for individual house- holds, the economic and social safety net (e.g., land for farming or extended family) is less secure in urban areas during periods of economic stress.

Prevalence of Overweight Children The WHZ-score, the indicator used to determine under- weight children, was also used to assess the extent of overweight children.
Overall, 14% of the total sample of 2–10 year-olds was overweight, indicating the emergence of chronic overnutrition.

As Table 4-7 shows, the pro- portion of children considered clinically obese was six times more than what was expected.

The likelihood that these children will become overweight adults has daunt- ing consequences for the long-term public health of the country.
83340_061-086 3/31/05 9:20 PM Page 70 70 | BAHAMAS LIVING CONDITIONS SURVEY 2001 As observed in the wider population, more girls than boys (16% versus 13%) were overweight; amongst all chil- dren, weight increased with age.

Of those in age group 2–4 years, 11% registered above normal weight, compared to the 2.3% referenced as normal; the prevalence of excessive weight for height further increased to 16% amongst chil- dren 7–10 years.

Overall, 14% of children 2–10 years were overweight and 6% underweight.
Both scenarios underscore the need to identify environmental risk factors—household food insecurity and poor nutritional practices—in this subgroup to determine the causal relation (which is be- yond the scope of this study).

According to WHO stan- dards, only 5% of a sample should be outside normal ranges.

For the most part, WHZ increased with higher per- capita, household-consumption expenditure.
Regions 2 (Abaco, Andros, and Eleuthera) and 4 (Other Family Is- lands) had the lowest prevalence of overweight children (10.4% and 13.3%, respectively), whilst Region 3 (Exuma and Long Island) reported the highest, with 20%.

NUTRITIONAL STATUS OF ADOLESCENTS Adolescence, a period characterized by rapid physical growth and social adjustment, makes the adolescent child susceptible to environmental factors, particularly those re- lated to food and nutrition.
Amidst the concern of sexual maturation and the milieu of social development and ad- justment problems is the disorder of obesity, which is common in adolescents generally.

The Body Mass Index (BMI) is a simple and reliable index of weight for height commonly used to classify underweight, overweight, and obesity; the BMI provides useful, crude data on the afore- mentioned measurements within the population.
The BMI for age and gender was determined for ado- lescents 11–20 years of age, using reference standards from the Centers for Disease Control.

BMI categories used were: underweight (5th percentile); normal weight; at risk of overweight (85th percentile); and overweight (95th per- centile).
As shown in Table 4-8, of all youth measured, 59% were reported to have normal weight, 14% were at risk of becoming overweight, and approximately 9% were TABLE 4-8 Body Mass Indices for Adolescents, Ages 11–20 Years Population characteristic Underweight Normal BMI (%) At risk for overweight Overweight Total N Mean BMI Gender Male Female Age group (years) 11–15 16–20 Region 1 2 3 4 Quintile Total 83340_061-086 3/31/05 9:20 PM Page 71 overweight for their age.
Notably, 18% of these adoles- cents were underweight at the time of the Survey.

Age group and gender trends revealed more overweight females than males, specifically amongst those 16–20 years (13%).

Young people living on more urbanized islands were more likely to have normal weight than those resid- ing in less developed regions.
With regard to the relationship between BMI and so- cioeconomic status, more children and teenagers who were underweight for their age and gender were from higher-consumption households (quintiles 4 and 5), which contradicts results found in similar surveys.

How- ever, this finding could reflect concern for physical ap- pearance, a common phenomenon in populations of wealth and affluence.

More boys than girls were classified as underweight.
Overall, the highest prevalence of underweight youth was observed in the less developed islands of Region 4 (Other Family Islands) (Table 4-8).

NUTRITIONAL STATUS OF ADULTS Evidence is convincing that mortality rates increase as ex- cessive weight increases, as measured by the BMI.

More- over, as the BMI increases, the proportion of people with one or more co-morbid conditions also increases.
In this regard, assessing the nutritional status of the adult popula- tion is particularly important to understanding its relationship to disease and death, health effects, and the human development index.

The nutritional status of adults 21–60 years of age was assessed based on weights and heights taken during the BLCS.

General BMI rankings are:6 normal weight for height, underweight for height, and overweight for height.

The latter is further subdivided into three classes of obe- sity.
WHO-accepted cutoffs for BMI are: 18.5 (under- weight), 18.5–24.9 (normal), 25–29.9 (pre-obesity or overweight), 30–34.9 (obesity class I), 35–39.9 (obesity class II), and 40 (obesity class III).

As Table 4-9 indicates, the mean BMI was 28 for adults; 34.4% of adults were overweight, a further 30.9% 6 BMI, the international standard for determining weight range, is cal- culated by weight in kilograms (kg), divided by height in meters (m) squared (kg/m2).
HEALTH STATUS: SOCIOECONOMIC ANALYSIS 71 | were obese, and about 2% were underweight.

When the figures were combined, the percentage of overweight or obese adults was 65%, approximately two-thirds of this population.

The 1988–1989 NHNS showed that, in adults 15–64 years of age, this prevalence was 49%.

It can reasonably be concluded that The Bahamas, like many other high-income countries, is experiencing an obesity epidemic.
Within the adult population, females had a significantly higher prevalence of obesity (37%) than did males (24%) (Table 4-9).

Female obesity was highest in Region 4 (Other Family Islands), the most un- derdeveloped area; there, overweight (35%) and obese (49%) females comprised 84% of the Region’s female population, a grave revelation (Tables 4-10 and 4-11).

As shown in Table 4-10, the youngest group of males was the healthiest group in terms of weight.
On average, one out of every two men 21–30 years of age (49.5%) was of normal weight.

About 62% of men were too heavy for their height, whilst 69% of women had a BMI of 25 or more (Table 4-11).

These results clearly show that a high proportion of Bahamian adults is at risk for developing one or more co-morbidities of the chronic, non-commu- nicable diseases.

Amongst all persons, the combination of being over- weight and obese increased with age.
Obesity was most notable in the age groups between 31–50 years (about 35%), as well as in the 51–60 age group (33%), whilst young adults in the 21–30 age group were predominantly the healthiest in terms of weight (Table 4-9).

As an indirect measure of socioeconomic status, obe- sity is more common amongst middle-aged women in low-income countries.
In high-income countries, it is more prevalent amongst middle-aged people, as well as younger adults and children, and tends to be associ- ated with lower socioeconomic status.

The highest preva- lence of overweight persons was found in quintile 5 (38%) and decreased steadily in lower-consumption households.
With regard to obesity, however, the wealth- iest households had the smallest proportion of obese persons (27%), whilst quintile 2 had the highest (35%), an expected result for high-income populations (Table 4-9).

Overall, the highest prevalence of overweight and obese persons was found in Region 3 (Exuma and Long Island).
Gender differences, noted in Table 4-10, show that those two islands have the highest percentage of obese men 83340_061-086 3/31/05 9:20 PM Page 72 TABLE 4-9 Body Mass Indices for All Persons, Ages 21–60 Years BMI (%) Population characteristic Underweight (18.5) Normal weight (18.5–24.9) Overweight (25.0–29.9) Obese (30) Total N Mean BMI Age group (years) 21–30 31–40 41–50 51–60 Region 1 2 3 4 Quintile Total TABLE 4-10 Body Mass Indices of Males, Ages 21–60 Years BMI (%) Population characteristic Underweight (18.5) Normal Overweight (18.5–24.9) Obese (25.0–29.9) Total (30) N Mean BMI Age group (years) 21–30 31–40 41–50 51–60 Region 1 2 3 4 Quintile Total 100.0
83340_061-086 3/31/05 9:20 PM Page 73 HEALTH STATUS: SOCIOECONOMIC ANALYSIS 73 | TABLE 4-11 Body Mass Indices of Females, Ages 21–60 Years BMI (%) Population characteristic Underweight (18.5) Normal (18.5–24.9) Overweight (25.0–29.9) Obese (30) Total N Mean BMI Age group (years) 21–30 31–40 41–50 51–60 Region 1 2 3 4 Quintile Total 2.6 1.7 0.8 0.0 1.6
3 4 Quintile Total (28%).
The greatest proportion of obese women was found on Other Family Islands (Region 4), where 47% had a BMI of 30 or more (Table 4-11).

Overall, New Providence and Grand Bahama had the lowest prevalence of obesity amongst island regions (Table 4-9).

It follows that overweight persons and obesity present a significant public-health problem, especially in the less developed Family Islands (Region 4) and poorest segments of the population.
BREASTFEEDING Results on breastfeeding show that approximately 74% of all children 24 months and younger had been breastfed (Table 4-12).7 More boys (79%) than girls (69.6%) had been breastfed.

The lowest prevalence of recorded breast- feeding was for infants 7–12 months (69.1%), which was 7 Children’s ages were classified as 0–6 months, 7–12 months, and 13–24 months.

lower than that for children 13–24 months (74.6%).


This unexpected finding may be a factor of memory and the ac- curacy of recall by mothers of older children.

As expected, the highest prevalence of breastfeeding (76%) was amongst children 0–6 months of age.

The highest prevalence of breastfeeding (94%) was found in the median quintile, whilst the lowest was found in quintile 4 (63%).
Mothers residing in the more devel- oped islands of Region 1 (New Providence and Grand Ba- hama) and 2 (Abaco, Andros, and Eleuthera) were most likely to breastfeed their infants.

Amongst those house- holds, approximately 74% of children were breastfed.

These results show that breastfeeding is more prevalent in urban areas than rural ones, which is not typically found.

However, this result can be attributed to the National Breastfeeding Campaign.
Initiated eight years prior to the BLCS, the Campaign has influenced Regions 1 and 2 more than 3 and 4 because of the way in which resources have been concentrated.
According to lactation management research, the opti- mal length of time recommended for exclusive breastfeed- 83340_061-086 3/31/05 9:20 PM Page 74 74 | BAHAMAS LIVING CONDITIONS SURVEY 2001 TABLE 4-12 Breastfeeding Incidence and Median Months of Exclusive Breastfeeding* Population characteristic % breastfed Gender Male Female Age (months) 0–6 7–12 13–24 Mother’s education completed Secondary school College/university Region 1 2 3 4 Quintile Total 79.0 69.6 76.3 69.1 74.6 70.2 82.2 74.2 72.6 57.3 62.6 68.3 70.7 93.6 62.5 72.5 73.7 N 86 115 50 51 100 150 28 126 49 7 18 62 50 41 29 19 201 Median months of exclusive breastfeeding 2 2 1 1 3 2 3 2 3 3 3 2 2 2 1 3 2 N 57 68 35 31 59 91 20 81 29 4 10 32 30 33 19 11 125 * Note: Breastfeeding sample was for children 24 months or younger; exclusive breastfeeding was for those 6 months or younger.
ing is six months.

This is important to prevent incidence of diarrhoeal diseases, which can increase infant morbidity and mortality.

A pertinent indicator of the benefits of breastfeeding is the duration of exclusive breastfeeding.8 Infants 6 months of age and younger were exclusively breastfed for a median of 2 months.

For the purpose of comparison with the NHNS of 1988–1989, the level of breastfeeding of children 12 months of age and younger was assessed.
BLCS results showed that 7% of children were exclusively breastfed for 4 months, compared to 2% of children in the NHNS, a marked improvement in prevalence rate for exclusive breastfeeding.

8 The term exclusive breastfeeding is defined as an infant being solely breastfed or fed expressed breast milk via the spoon-and-cup method; and given no bottle (even if it contains expressed breast milk), water, formula, or baby food.
With regard to exclusive breastfeeding by region, Re- gion 1 mothers exclusively breastfed their babies for an av- erage of 2 months.

Sample sizes for the other regions were too small to make comparisons.

FEMALE REPRODUCTIVE HEALTH Approximately 61.9% of females 10–49 years of age reported being pregnant at least once, with a propor- tional range from 6% in adolescent girls 10–19 years of age to 91.8% in women 40–49 years.
The average number of reported pregnancies increased from less than one for girls 10–19 years to three for women 40–49 years.

In each age group, those least able to afford it became pregnant, as the highest proportion of women who were ever pregnant was found in the lowest quintile.
Amongst 83340_061-086 3/31/05 9:20 PM Page 75 HEALTH STATUS: SOCIOECONOMIC ANALYSIS 75 | TABLE 4-13 Percentage of Females, 10–49 Years of Age, Who Have Ever Been Pregnant Population characteristic Education Primary or lower 1–3 grades of higher secondary 4–5 grades of higher secondary Higher secondary or technical/vocational Jr. college, community college, or college/univ.

Region 1 2 3 4 Quintile Total 10–19 yrs.

20–29 yrs.

30–39 yrs.

40–49 yrs.
% 5.1 1.6 5.0 19.3 0.0 5.6 8.4 8.2 4.9 9.2 8.8 3.5 5.2 0.0 6.0 N 85 153 113 84 % 100 76.7 79.9 73.8 N 10 19 54 240 % 95.4 95.7 93.2 87.1 N 27 32 53 231 % N 62 26 32 143 188 83 42 30 55 65 71 75 78 344 age groups, a greater proportion residing in Family Is- lands reported pregnancies (Table 4-13).
About 67% of all females had had at least one gynae- cological examination.

Amongst women 20–49 years of age, more than 80% across all quintile levels had been examined.

Level of contraceptive use to avoid pregnancy was 5.6% for girls 10–19 years of age, 57% for women 30–39 years, declining to 33% for women 40 years and older (some of whom may have no longer needed contraception because of hysterectomies or menopause).
Women who had had at least one live birth were more likely to use con- traceptive methods than those who had had no deliveries.

The birth control pill was the most popular contra- ceptive method used amongst all females (47%), fol- lowed by female sterilization (19.7%), which was used primarily by older women.
Other methods included in- jectables (16.1%), condoms (9.1%), and other modern FIGURE 4-5 Common Contraceptive Methods Women Used, by Age and Type t n e c r e P 80 60 40 20 0 69.9 58.3 51.4 43.4 20.6 22.1 22.7 14.6 27.5 4.0 0 10-19 10.4 3.5 7.6 10.8 5.7 20–29 30–39 40–49 Age Group Pill Injectable Sterilization Condom 83340_061-086 3/31/05 9:20 PM Page 76 76 | BAHAMAS LIVING CONDITIONS SURVEY 2001 methods (6.5%) (Figure 4-5).

This pattern was compara- ble by quintile.


HEALTH-SERVICES USE AND EXPENDITURE The Government attempts to make health-care services available to all residents of the Bahamas by subsidizing costs for certain population groups, and deferring or waiv- ing costs in cases of demonstrated lack of ability to pay.
Because of this policy, infants, children under 19 years (students only), civil servants, pregnant women, the phys- ically disabled, the elderly (pensioners), and holders of the social-services medical card are exempt from facility fees, including medicines.

Over the past five years, health services accounted for about 15% of the national budget.
In fiscal year (FY) 2001–2002, about 69% of the health budget was appor- tioned to the delivery of health care, with institutions re- ceiving the majority of the share.

Given the Government’s mandate to ensure the availability of accessible and afford- able health care for all persons living in The Bahamas, the BLCS sought to determine whether inequities existed in the level of facility use.
Outpatient Visits In the four-week period immediately preceding the Sur- vey, approximately 1 in 10 persons (12.9%) visited a health practitioner for outpatient care.

More females (15.3%) than males (10.4%) made visits.

This finding is not surprising, as pregnant females are more likely to re- port illness and visit health facilities.

The very young (18.7%) and the elderly (24.6%) represented the highest proportion of visits (Table 4-14).
The percentage of persons seeking outpatient care rose with consumption levels, from 8% in the lowest quintile to about 20% in the highest (Table 4-14).
TABLE 4-14 Outpatients (during Past Four Weeks) and Inpatients (during Past 12 Months) Population characteristic Outpatient visits Total Average length of stay Inpatient admissions Gender Male Female Age group (years) 0–4 5–14 15–19 20–34 35–54 55–64 65 Region 1 2 3 4 Quintile Total N 3,152 3,262 625 1,394 503 1,435 1,623 389 446 3,413 1,725 621 605 1,560 1,325 1,247 1,173 1,024 6,414 83340_061-086 3/31/05 9:20 PM Page 77 HEALTH STATUS: SOCIOECONOMIC ANALYSIS 77 | TABLE 4-15 Outpatient Visits to Health Facilities in Past Four Weeks, by Facility and Sector Public Private Characteristic Total Hospital Clinic Total Hospital Clinic Professional Foreign medical N Gender Males Females Age group 0–4 5–14 15–19 20–34 35–54 55–64 65 Region 1 2 3 4 Quintile Total 30.3
Table 4-15 shows that as consumption quintiles in- creased, visits to public health facilities decreased while those to private practitioners increased.
About 62% was made to public-health facilities, 36.2% to private practi- tioners, and 2.3% to health facilities abroad.

On most islands outside of New Providence and Grand Bahama (Region 1), health care is largely limited to Government clinics.

The data shows greater usage on Family Islands (Regions 2, 3, and 4), where 70–87% of medical visits were made to public-health facilities, especially clinics.
Residents in Region 1 used public-health facilities the least and made the highest proportion of visits to private practitioners (47.9%).

This finding is predictable, given that most private-health facilities are found on New Prov- idence and Grand Bahama.

Despite comparatively lim- ited availability of private-health facilities on the Family Islands, about 10–27% of those residents chose private facilities for outpatient care, either locally or on other is- lands.
The proportion of outpatient visits to foreign med- ical facilities was modest in most areas.

Medicine As Table 4-16A illustrates, respondents who were outpa- tients tended to buy their medicine from both public and private facilities,9 although they spent more at the latter over the reference period (past four weeks).
When expen- diture at public- and private-health facilities was com- bined, results showed that, on average, about $4 was spent on medicine, with females spending more than males ($4.61 versus $3.91).

9 Expenditure on medicine is at an individual level, inclusive of those who did not pay, including Government-subsidized groups.
83340_061-086 3/31/05 9:20 PM Page 78 78 | BAHAMAS LIVING CONDITIONS SURVEY 2001 TABLE 4-16A Average Expenditure on Outpatient and Inpatient Care Outpatient ($) Population characteristic Public Private Foreign Public Medicine private Both Inpatient (all sectors) (B$) Gender Male Female Age group (years) 0–4 5–14 15–19 20–34 35–54 55–64 65 or older Region 1 2 3 4 Quintile Gini coefficient Total N 3,061 3,175 611 1,350 489 1,403 1,573 380 431 3,306 1,721 616 594 1,553 1,316 1,220 1,144 1,004 6,236 6,236 In terms of age group, adults aged 55–64 years incurred the highest average cost for medicine ($13.78), most of which was spent at private facilities.
Persons under 35 years had the lowest cost (less than $3.00).

Low expenditure amongst infants and children reflect, in part, the Government’s policy to subsidize their health-care costs in the public sector.

Average spending increased by quintile when expendi- tures at public and private facilities were combined.

On average, individuals in the highest quintile paid 13 times more for medicines to treat various health conditions ($11.39) than those in the lowest quintile ($0.86).
This may be related to the tendency of better-off persons to buy medicines at private, rather than public, facilities.

Medicinal expenditure ranged from about $3.00 to $6.00 in the island regions, with residents of Region 2 (Abaco, Andros and Eleuthera) paying the most for medicines ($5.52), as compared to persons in the remaining Family Islands of Regions 3 and 4, who spent about $3.00.
Expenditure As Table 4-16A shows, the average expenditure for out- patient care (during the four-week period preceding the survey) at public, private, and foreign facilities was $1.43, $9.06, and $0.57, respectively.

Expenses were averaged for all costs associated with outpatient visits—excluding medicines, transportation, and insurance-reimbursed costs.

Per-capita spending on overall outpatient care was 83340_061-086 3/31/05 9:20 PM Page 79 $11.07, averaging $12.78 for females and $9.26 for males.
On average, males spent more on outpatient care at public health facilities and overseas, whilst females spent more at local private facilities.

The average health-care cost at public facilities was $2.14 for males and $0.77 for fe- males.

At private facilities, average expenditure was $6.30 for males and $11.67 for females.

Amongst those who sought outpatient care in the pub- lic sector, expenditures decreased with age amongst adults in the 35 years and older age groups.
Average expenses de- creased from $3.58 (for adults aged 35–54 years) to $1.33 (those 65 years or older).

For children and young adults, the average cost of public-health care was less than $1.00.

For private costs, average expenses increased from $2.92 for children aged 5–14 years to $11.19 for adults aged HEALTH STATUS: SOCIOECONOMIC ANALYSIS 79 | 35–54 years.

Overall, the highest average, private-care cost was found amongst the elderly ($25.84), whilst the lowest was amongst children 5–14 years.
Amongst residents who traveled abroad for outpatient care, the elderly incurred the highest average cost ($4.43).

Across all sectors, health expenditure increased as quintiles rose.

Results using the Gini coefficient to mea- sure inequality showed statistical differences by con- sumption quintile (the measure was greater than 0.95 in each sector).

Mean expenditure on public-health care, by region, was about $2 or less.
Residents of Region 1 (New Provi- dence and Grand Bahama), where most private health- care facilities are found, had the highest private health-care expenditure ($9.54).
Persons living in Region 4 (Other Family Islands), who had to travel longer distances for TABLE 4-16B Average Annual Health Expenditure and Percentage Distribution, by Expenditure Type Population characteristic Average annual expenditure (B$) Public Private Foreign Medicine Total Inpatient (all sectors) Distribution (%) Outpatient Gender Male Female Age Group (years) 0–4 5–14 15–19 20–34 35–54 55–64 65 or older Region 1 2 3 4 Quintile Total N 3,156 3,269 626 1,396 503 1,436 1,625 391 448 3,367 1,745 620 599 1,560 1,325 1,248 1,177 1,021 6,425 83340_061-086 3/31/05 9:20 PM Page 80 80 | BAHAMAS LIVING CONDITIONS SURVEY 2001 hospital services, had the highest average expenditure for outpatient care abroad ($7.44).
Table 4-16B shows that the share of Total Health Ex- penditure (THE) increased between the lowest and middle consumption quintiles (78.8% and 90.4%, respectively) and fluctuated in the highest ones.

Share of public-sector expenditure decreased as consumption levels increased (from 11% in the lowest consumption quintile to about 5% in the upper quintiles).

This finding corresponds with the earlier observation that visits to the public-health sec- tor decrease with increased levels of well-being.
Conversely, the share of private-sector (and foreign facility) expenditure increased as consumption levels rose (from 7.9% in the lowest quintile to 34.2% in the highest); this represented a fourfold increase, indicating that, with higher levels of af- fluence, a greater portion of THE is spent on private care.

The expenditure share on medicines was highest amongst persons in the lowest consumption quintile and decreased between the middle and highest quintiles.
Inpatient Admissions and Expenditure During the 12 months preceding the BLCS, 5.5% of all respondents were admitted to a health facility for inpatient care: 4% at public facilities and 1.5% at local private or foreign ones.

In all facilities combined, female admissions were nearly twice as high as that of males (7.1% compared to 3.8%).

Adults 65 years and older (11.5%), followed by those 20–34 years (7.7%), were more likely than other groups to be admitted for medical care (Table 4-15).
The difference between consumption quintiles was only 3% (4–7%) and only 1% (5–6%) across the island regions.

Average Length of Stay Whilst some Government-owned clinics have accommoda- tions for overnight medical stay, most persons requiring ex- tended medical care are retained in a hospital.

As shown in Table 4-14, the average length of stay in health-care institu- tions over the reference period (last 12 months) was 7 nights.
Even though fewer males than females were admit- ted to health-care facilities, they were retained longer (9 ver- sus 7 nights).

The reasons may be that males are more likely to suffer from externally caused, acute illnesses and be diag- nosed at a more advanced stage of illness.

The elderly and children 5–14 years had the longest average periods of stay (16 nights and 13 nights, respectively), whilst children un- der 5 years were retained for the shortest period of time (4 nights).
Generally, as quintiles increased, the average number of nights spent in a health facility decreased.

Whilst respon- dents in the lower two quintiles spent an average of about 8 nights, this decreased to about 6 nights in the higher quintiles.
Whilst it is possible that persons in a lower so- cioeconomic level may have more severe illness, resulting from deprivation of certain services, it is also possible that these results may reflect who is paying the bills (i.e., Gov- ernment, persons paying out of pocket, or a third party).

On average, respondents from the more remote islands of Region 4 (Other Family Islands) had the longest stay (11 nights), followed by those from Region 2 (Abaco, Andros, and Eleuthera) (9 nights).
In Regions 1 and 3, respondents were retained for an average of about 7 nights.

This finding may reflect the need for more diagnostic ser- vices for persons referred to hospitals in New Providence or Grand Bahama from the other islands, or simply that only the more serious cases are referred.
Expenditure Table 4-16A, which summarizes the average expenditure amongst those admitted to a health facility over the 12-month period prior to the Survey, shows expenditure, which covered all payments associated with inpatient vis- its (including medicines), but excluded transportation, room and board, and insurance-reimbursed costs.

Combined per-capita expenditure for inpatient care (public, private, and foreign) was $28.41.
Average expen- diture on inpatient health care was lower amongst males than females ($23.00 versus $33.56).

By age group, the el- derly incurred the highest average cost ($49.15), whilst children 5–14 years had the lowest ($12.52).

Average cost increased with age between the 5–14 and 35–54 age groups.
Expenses for adults 55–64 were lower ($41.27) but rose again for those 65 and older.10 Average expenditure on health care over the past 12 months increased steadily by quintile, from $5.47 at the lowest quintile to $72.04 at the highest—roughly a thirteen-fold increase.

This finding most likely reflects the preference for private services as socioeconomic status (SES) increases.
However, as shown in Table 4-16B, the share of THE on inpatient care (including medicine) dif- 10 These results are interesting, considering that the Government heav- ily subsidizes care to the elderly.

83340_061-086 3/31/05 9:20 PM Page 81 fered by quintile.

It was highest in the lowest quintile (21.2%), which was about twice that of the middle and highest quintiles.
This latter finding clearly indicates the SES/health cycle: How poor health can negatively affect SES and how poverty can lead to poor health.

Amongst island regions, average expenditure was high- est on Family Islands, where average cost ranged between $40 and $49 for inpatient care.

It was lowest for Region 1 residents, who spent an average of $25.89 (Table 4-16A).
Whilst expenditure rose by quintile, the share of THE on outpatient care was lowest amongst children and the el- derly, both subsidized by Government.

The poor allocated the greatest proportion of their THE share to inpatient care.

Medicines comprised the greatest share of THE.

Overall, the average annual expenditure on health care per person was $309.20 ($252.40 amongst males and $363.20 amongst females).

Generally, expenses increased with age (with the exception of adults 55 to 64 years).
By consumption quintile, persons in the lowest quintile spent an average of $25.50 annually, compared to $747.80 for those in the highest quintile.

Regional comparisons showed that Region 3 (Exuma and Long Island) had the lowest annual cost ($164.20), whilst Region 4 (Other Family Islands) had the highest ($249.60) (Table 4-16B).

HEALTH INSURANCE COVERAGE The principal avenues by which health care is financed are: • Government.

Approximately 15% of the nation’s budget is allocated to health (MOF 2004).
• Private health insurance.

About $102 million was spent in 2001.

• User fees at both public and private facilities.

Total out-of-pocket expenditure was $309 per capita over the last 12 months.

• Social health insurance.

Through the National Insurance Board (industrial injury component).

• External sources.

Such sources are limited because of the country’s economic profile (MOH 2004, p. 77).
Survey results revealed that 51.4% of respondents re- ported having some form of health insurance, leaving oth- ers to cover health-care expenses out of pocket or with Gov- ernment assistance.
In terms of gender, coverage levels did not differ significantly between males (50.7%) and females HEALTH STATUS: SOCIOECONOMIC ANALYSIS 81 | TABLE 4-17 Population characteristic Gender Male Female Age group (years) 0–4 5–14 15–19 20–34 35–54 55–64 65 Region 1 2 3 4 Quintile Total Proportion of Respondents with Medical and Dental Coverage Medical (%) Dental (%) N (52.2%).
The age groups with the least coverage were those most likely to seek care: the elderly (34.7%) and children under 5 years (42.8%).

Both groups are more vulnerable to illness than others, and additionally, the cost of insurance for the elderly is prohibitive.

Coverage for employable per- sons (ages 20–64) ranged from 50%–59%.

Individuals from better-off households (higher con- sumption quintiles) had higher levels of coverage.
For ex- ample, only 20.1% of those in the poorest quintile had coverage, compared to 76% in the wealthiest quintile.

In addition to differences in level of insurance coverage, scope of coverage differed.

Higher-income persons were more likely to have comprehensive health-insurance packages, whilst lower-income persons, who purchased lower-priced premiums, faced higher deductibles (MOH 2003).
83340_061-086 3/31/05 9:20 PM Page 82 82 | BAHAMAS LIVING CONDITIONS SURVEY 2001 FIGURE 4-6 Medical Insurance Payers TABLE 4-18 Average Medical Insurance Payments 50 40 t n e c r e P 30 20 10 0 Self Family Employer 1 39.2 44.6 15.2 2 44.6 42.1 13.5 4 37.5 40.8 23.4 3 38.0 46.0 19.7 Quintile 5 39.8 33.6 31.6 Results also showed that family members were the pri- mary sources of obtaining both medical (40.8%) and den- tal (44.2%) insurance coverage.
However, as consumption quintiles increased, the level of coverage by employers in- creased, whilst coverage by family members decreased (Figure 4-6).

Residents of the most developed islands of New Provi- dence and Grand Bahama (Region 1) had the highest cov- erage level (54%), whilst residents of Exuma and Long Island (Region 3) had the lowest (30.8%).
Further analysis revealed that a much greater propor- tion of respondents had medical (50%), as opposed to dental (5%), insurance, possibly because of the lower pri- ority given to oral health care and the more affordable, out-of-pocket cost of dental care.

Males and females had comparable levels of medical ( 50%) and dental (5%) cov- erage.

On a monthly basis, respondents paid an average of nearly three times as much for medical insurance ($61.1) as for dental coverage ($21.20).
Table 4-18 provides de- tails on medical insurance payments (dental-insurance payments are excluded because of small sample sizes in most subgroups).

Predictably, payments increased with levels of consumption.
Residents of Region 2 (Abaco, Andros, and Eleuthera) had the highest average cost for Population characteristic Medical insurance ($) N Gender Male Female Age group 0–4 5–14 15–19 20–34 35–54 55–64 65 and older Region 1 2 3 4 Quintile Total medical insurance ($74), whilst the Family Islands of Region 3 (Exuma and Long Island) had the lowest ($57).
Total outpatient expenditure on visits to health facili- ties (over the past four weeks) was estimated at about $2 million amongst persons with private insurance and about $1 million amongst those without coverage.

Total inpa- tient expenditure was higher, at about $6 million amongst those insured and $3 million for the uninsured (MOH 2003).
This finding raises the question: Do those with - insurance make more use of the service or are pricing and billing differences based on whether an individual has coverage?

CONCLUSIONS AND POLICY RECOMMENDATIONS The Survey findings described above reveal the need for comprehensive, intersectoral interventions to improve the 83340_061-086 3/31/05 9:20 PM Page 83 overall health status of Bahamians of all ages.

Various ini- tiatives are recommended for consideration at the policy or program level.
Some of the more critical ones are sum- marized below.

Self-reported Health Status Accidents and Workplace Injuries The proportion of injuries due to violence and preventable accidents is of increasing concern to health-care practi- tioners and the general public.

(About 20% of reported ac- cidents and workplace injuries resulted from gunshots or stabbing and motor vehicle accidents.)
As reflected in both national morbidity and mortality statistics, such injuries affect productivity levels and result in temporary or per- manent disability, or even death.

Given that the leading causes of mortality are external, it is important to under- stand and prevent the occurrence of such events through evidence-based interventions.

In the BLCS, most injuries reported occurred at the workplace or school.
This highlights the need to strengthen and implement national occupational health- safety initiatives that are intersectoral—including labour, education, and other social agencies.

Appropriate linkages must be forged to ensure that safety measures are in place in the workplace and school environments.
Chronic Non-Communicable Disease With regard to chronic non-communicable diseases—the chief contributors to morbidity and mortality in the pop- ulation—The Bahamas has characteristics similar to those of industrialized countries.

Its profile of hypertension and diabetes, particularly the greater prevalence of the latter in the Family Islands, is of concern, and efforts to control these diseases must be strengthened.
A related factor may be food availability,11 which, ac- cording to FAO data, has increased in recent years.

For ex- ample, the WHO-recommended, daily-caloric availability per capita is 2,250 for a population the size of the Ba- hamas.

In 2001, 2,777 total calories were available in the population, compared with 2,500 in 1999 and 2,498 in 1992.
Another contributing factor is the shift in quality of dietary intake toward increasingly higher percentages of 11 In The Bahamas, food availability is a proxy for consumption, as no portion of imported foods is exported, but is consumed by the popula- tion and its visitors.

HEALTH STATUS: SOCIOECONOMIC ANALYSIS 83 | refined carbohydrates and high-fat foods.
Combined with a sedentary lifestyle, this factor exacerbates the problem of obesity—a risk factor for diabetes, hypertension, and other chronic diseases.

These realities require a comprehensive response in- volving all levels of Bahamian society—national, commu- nity, and individual—so that people will be empowered to take greater responsibility for their health.

To this end, the following recommendations are proposed: • Adoption of the National Food and Nutrition Pol- icy.
This Policy defines the direction of such initia- tives as national dietary guidelines, food standards, regulatory measures, education, promotion of best nutrition practices, and institutional strengthening for the prevention of obesity and chronic non-com- municable diseases.

• Increased health education and promotion and com- munity awareness-raising of associated risk factors.

• Targeted research on the relationship between non- communicable diseases and socioeconomic status and region of residence.
Child Health Immunization The current instrument used to record vaccinations is inadequate, and should be revised to address such limita- tions as the inclusion of new vaccines.

Moreover, an im- munization database should be established to capture vac- cination information on each child.

This would allow for detection of defaulters and early follow-up, and would improve coverage rates.
Respiratory Illness In view of the high incidence of upper-respiratory ill- nesses, compared to that of asthma and diarrhoea (Table 4-4), it is recommended that further research be con- ducted to determine contributing factors so that preven- tive measures can be taken.
Nutrition Children: Ages 2–10 Years Although prevalence of undernutrition in this age group is low by World Health Classification standards (less than 20%), the low HAZ-score in this Survey for children 2–4 years of age (15%) is cause for concern.

This is especially true for children 3 years and younger, as this measurement 83340_061-086 3/31/05 9:20 PM Page 84 84 | BAHAMAS LIVING CONDITIONS SURVEY 2001 is a most sensitive predictor of mortality in this age group.
Further investigation should be conducted to determine the extent to which this problem exists so that appropriate intervention strategies may be implemented, if and where necessary, to prevent exacerbating the problem.

Although wasting is not a significant public-health problem, targeted health- and social-sector programs are needed for children 7–10 years of age (the group with the highest prevalence rate).
The health sector should monitor this group closely to ensure intervention response and con- trol of the condition.

Survey results indicate that, for this age group, be- ing overweight is a nutritional problem of sufficient public-health magnitude to warrant immediate action to abate a future crisis.

Response to the current situation must be multifaceted and multisectoral.

Prevention should be the primary focus of targeted interventions.
Adolescents: Ages 11–20 Years As with younger children, prevention, containment, and reduction are a top priority.

Survey results showed that children living in households with overweight adults were four times more likely to be overweight, or at risk of be- coming overweight than those not living with overweight adults.

This shows that obesity is a familial problem re- lated to household consumption patterns, as well as ge- netic traits.
Thus, it is recommended that: • Prevention programs be family-oriented.

• Targeted programs meet the needs and expectations of adolescents.

In addition, underweight adolescents (18%) should be followed closely, and contributing environmental factors should be identified as an early warning of household food insecurity (espe- cially in the urban areas, taking note of the implica- tion of nationality).
Adults: Ages 21–60 Years Every avenue must be explored to empower adults to take better care of their health.

This includes making healthy food choices, increasing physical exercise and limiting lifestyle practices that negatively affect health and well-being.

Adults 21–60 years of age comprise the majority of human capital in the Bahamian workforce.

This group is critical to the country’s economic and social development, underscoring the need for it to main- tain good health.
The prevention approach to the over- weight and obesity issue is needed amongst younger adults to delay the onset of chronic non-communicable diseases.

It is recommended that: • Partnerships and linkages be forged with all segments of society to enable a synergistic effect and minimize the burden in terms of human and financial capital expenditure, as proposed in the National Food and Nutrition Policy.
• Gender-specific programs and components on chronic non-communicable disease be strengthened and integrated into all other health programs.

Na- tionwide health education and promotion strategies must continue to be developed to empower individ- uals to take greater responsibility for their health care.
Breastfeeding Populations with a high prevalence of breastfeeding are characterized by reduced incidence of childhood disease, particularly diarrhoea and upper-respiratory infections; subsequently, such a reduction lowers morbidity and mor- tality rates of children under 2 years.

Since inception of the National Breastfeeding Campaign more than a decade ago, incidences of childhood diseases, including gastroen- teritis, have been significantly reduced and, by extension, infant mortality rates have declined.
The Campaign has also succeeded in increasing breastfeeding prevalence amongst lactating women, particularly in Regions 1 and 2, where Campaign efforts were more concentrated.

The same effect on breastfeeding was not observed in Regions 3 and 4.

These factors indicate the need to target health- promotion efforts evenly across all regions.
Additionally, there is a need for the Government to approve the Na- tional Breastfeeding Policy, (currently in draft form), which will mobilize all necessary resources to create a baby-friendly environment.

Female Reproductive Health Based on the Survey results, it is recommended that pro- motion of health education be increased throughout The Bahamas to raise awareness of the importance of family planning.
Health Services Use, Expenditure, and Insurance Survey results showed that, as wealth increased, a shift oc- curred in the use of health-care facilities.

With increasing 83340_061-086-R1 4/7/05 10:28 PM Page 85 consumption levels, the proportion of visits to public- health facilities decreased, whilst those to private facilities increased, indicating that private providers were the pre- ferred choice.
Clearly, public-health care is affordable; however, users tend to choose other alternatives as their socioeconomic capacity—and thus their health-care options—increases.

Given the rising costs of private coverage and many persons not being able to afford private coverage, the Blue Ribbon Commission was formed to investigate the feasi- bility of forming a national health insurance system to ensure equity of access to all.
The Commission recom- mended that a compulsory social health insurance be in- troduced as the principal method of financing health care for The Bahamas (MOH 2004, p. ix).

REFERENCES HEALTH STATUS: SOCIOECONOMIC ANALYSIS 85 | MOH.

2003.

“Blue Ribbon Commission on National Insur- ance.” 2003 Private Health Insurance Company Sur- vey.

Nassau: Commonwealth of The Bahamas, Min- istry of Health.

Unpublished data.

_______.

2004.

Report of the Blue Ribbon Commission.


Nassau: Commonwealth of The Bahamas, Ministry of Health.

FOR FURTHER READING MOH.

2000.

Commonwealth of The Bahamas National Health Services Strategic Plan, 2000–2004.

Nassau: Com- monwealth of The Bahamas, Ministry of Health.

_______.

2002.

Annual Report of the Chief Medical Officer.

Nas- sau: Commonwealth of The Bahamas, Ministry of Health.

MOF.

2004.

Draft Estimates of Revenue and Expenditure (Recur- rent and Capital).
Nassau: Commonwealth of The Ba- hamas, Ministry of Finance.

PAHO.

2002.

Health in the Americas, 2002 edition.

2 vols.

Washington, D.C.: Pan American Health Organiza- tion.

Also available in Spanish.


83340_061-086 3/31/05 9:20 PM Page 86 83340_087-108 3/31/05 9:22 PM Page 87 CHAPTER 5 Educational System: Achievements and Challenges Brenda Y. Coakley T he Bahamian Government regards edu- cation as a fundamental human right—a key to sustainable development and an indispensable means by which its people can par- ticipate effectively in the national and global economy.
Today, education is viewed as a pow- erful determinant of labour-force participation, career choice, and ultimately earning capacity; in short, education both affects and is affected by individuals’ well-being (Box 5-1).
GOVERNMENT INITIATIVES AND THEIR IMPLEMENTATION To ensure equitable access to the country’s schools,1 The Government has initiated a range 1 Educational access in The Bahamas is universal; moreover, under the Education Act of 1996, education is mandatory for children 5–16 years of age (see chapter 36, Bahamas Is- lands Statute Law, rev.

eds.

1987 and 1996, Nassau).


The country has a 633 structure of schooling; that is, 6 years of primary school, 3 years of junior-secondary school, and 3 years of senior-high school of initiatives and programmes that focus on: • Academic success; • Student support; and • Family life, character-building, and reform.
Initiatives that aim to further academic suc- cess include Let’s Read Bahamas, Virtual School Mathematics, the 3Rs Enrichment, massive computerization of schools (including labs), Early Childhood thrust (including appending pre-school units to existing primary schools in all four geographical regions), and scholarships ear- marked for students in the southeastern part of the country who wish to pursue technical studies in any region.
The massive Curriculum Initiative of 1997 improved curriculum relevance and effective- ness.

Primary and secondary curricula were expanded to include Family Life and Health Ed- ucation (FLHE), Social Studies, and Tourism; and Spanish became the country’s second language.

87 83340_087-108 3/31/05 9:22 PM Page 88 88 | BAHAMAS LIVING CONDITIONS SURVEY 2001 BOX 5-1 Evolution of Bahamian Education When The Bahamas gained internal self-rule in 1964, the country’s educational system underwent a dra- matic shift.
A new Ministerial System replaced the Board System, which had existed since 1835.

The ed- ucational frontier expanded as the Government un- dertook a massive school-construction programme at both primary and secondary levels.

Central secondary schools were established on the Family Islands, the first of which was on Crooked Island; this development, in turn, extended secondary education throughout the country.
In addition, provisions were made for post- secondary institutions and teacher training both lo- cally and abroad.

Tertiary education 1974—the year after The Bahamas gained indepen- dence from Great Britain—marked another water- shed for education, with establishment of the College of The Bahamas (COB).

The COB provided for academic success and helped students overcome defi- ciencies through preparatory courses.
Current challenges Today, both international and local educational insti- tutions offer services in The Bahamas.

While most are located in New Providence, others have made inroads into the Family Islands.

In 1997, the Government undertook massive cur- riculum reform in response to national and interna- tional demands; by 2000, new curriculum guidelines and support materials were available across the island chain.
The country now faces the challenge of deliv- ering an equitable educational system to students throughout the archipelago, including remote islands and cays.

Roving teachers and distance education are helping to meet teacher shortages in critical subject areas, and computerization of schools is under way; however, much work remains.

A variety of programs and institutions have been estab- lished to support at-risk students.
For many years, Provid- ing Access for Continuing Education (PACE) has equipped pregnant students for re-entry into school or the workforce.

The Ministry of Health provides PACE stu- dents pre-natal care (see chapter 4), and The Bahamas Technical and Vocational Institute (BTVI) provides post- natal educational opportunities, as well as nursery facili- ties.

Another program, Success Ultimately Reassures Ev- eryone (SURE), targets male students challenged by the traditional school curriculum.
The National School Lunch Programme (NSLP), introduced by the Govern- ment in 1981, was extended to Special Schools the fol- lowing year so that children of unemployed parents or guardians or from indigent families could be guaranteed one nutritious meal daily (see chapter 7).

Both PACE and SURE participants are NSLP recipients.

Two reformatory schools, The Williemae Pratt School for Girls and Simp- son Penn School for boys, were established to build stu- dents’ character and instill moral values.
SURVEY CONTEXT When the BLCS was conducted in 2001, the country had 147 Government and 42 private schools.2 The 147 Gov- ernment schools included primary, all-age, junior-high, secondary and senior-high schools, and special schools (the latter numbering 11); 48,478 students were enrolled in Government schools (24,880 males and 23,598 fe- 2 The Bahamian school system comprises Government and private/in- dependent schools.
Various governing bodies control the indepen- dent—mainly church-administered—private schools; however, these schools function within the ambit of the Education Act (1996), and many receive annual Government subventions.

While private-school students must pay tuition and related costs, the Government under- writes the costs of public education.

Structural financial assistance for public education is achieved through International Educational Loans and local self-help projects.
All of the country’s private schools and col- leges must register with the Ministry of Education; the Education Act sets out the regulations under which the public schools operate.

83340_087-108 3/31/05 9:22 PM Page 89 EDUCATIONAL SYSTEM: ACHIEVEMENTS AND CHALLENGES 89 | males).

In the 42 private schools, the student population numbered 16,752 (8,025 males and 8,727 females).

Spe- cial schools had 690 enrolled students (376 males and 314 females).
The total number enrolled in Bahamian educa- tional institutions was 65,920.

Staff members in Government schools numbered 3,132, while 1,572 worked in private schools.

In 2000–2001, the average pupil-teacher ratio across the country was 16:1 for Government schools and 11:1 for private schools.
This chapter provides an overview of the Bahamian ed- ucational system with respect to student enrolment and at- tendance rates, age and gender, type and level of school attended, method of transport used to reach school and distance traveled, and school-related expenses.

Unenrolled youths are also briefly discussed.


ENROLMENT Characteristics The BLCS found that persons under 25 years of age were most likely to be enrolled in some type of educational in- stitution, whether a day-care facility, high school, or uni- versity.

As Table 5-1 shows, 52% of all persons in this age group were males.

Similarly, males accounted for 52% of those not enrolled.

By age, 28% were 5–10 years of age, 19% were 19–24, and 13% were younger than 3 years old.
This distribution compares favourably with that of the 2000 Population Census.3 More than 75% of this en- rolled population were 5–16 years of age (the compulsory age for school attendance).

Of those not enrolled, 52.2% were 19–24 years of age, while an additional 30% were younger than 3 years old.

In keeping with the overall pat- tern of population distribution, 86% of these youths resided in New Providence and Grand Bahama.
Rates Given that public primary and secondary education is free and universal throughout the country, and that school at- tendance is compulsory for children 5–16 years of age, it is expected that enrolment rates would be exceptionally high in these age groups.
Indeed, this assumption is supported TABLE 5-1 Characteristics of Individuals 0–24 Years of Age Characteristic All individuals Currently enrolled Not enrolled Age (years) 0–2 3–4 5–10 11–13 14–16 17–18 19–24 Region 1 2 3 4 Gender Boys Girls Quintile N by the data, which shows an enrolment rate of 96.7% for youth 14–16 years of age and an even higher rate of 99.2% for children 5–10 years of age (Table 5-2).
All regions and quintiles enjoyed such high enrolment rates.

Beyond the age of 16, a dramatic drop in enrolment to 48.8% occurred among 17–18 year olds; the rate fell fur- ther to 14% for persons over 18 years of age.

It can be as- sumed that individuals falling between these two age groups had completed secondary school and that a fair pro- portion would likely be working.
It should also be noted that, across all age groups, the enrolment rate for females was higher than that for males, with differences more pro- nounced amongst persons 17–18 years old (Table 5-2).

3 See Commonwealth of The Bahamas: Report of the 2000 Census of Pop- ulation and Housing.

Department of Statistics, Ministry of Economic Development, Nassau, 2002.
Regional Comparisons For young people 11–13 years of age, full enrolment was recorded in all regions, except Region 1 (New Providence 83340_087-108 3/31/05 9:22 PM Page 90 90 | BAHAMAS LIVING CONDITIONS SURVEY 2001 TABLE 5-2 Enrolment Rates for Individuals 0–24 Years of Age Characteristic All Bahamas Gender Male Female Region 1 2 3 4 Quintile 0–2 26.0 24.8 27.0 28.0 11.4 10.1 18.7 18.6 21.2 35.6 31.6 36.0 3–4 84.5 83.6 85.7 85.9 72.8 89.4 79.5 65.8 88.4 88.0 99.5 100.0 Age group 11–3 97.9 97.5 98.2 97.4 100.0 100.0 100.0 93.0 100.0 98.0 100.0 100.0 5–10 99.2 99.0 99.4 99.1 99.2 99.0 100.0 97.4 100.0 99.9 99.7 100.0 14–16 17–18 19– N 2,965 1,528 1,437 1,630 812 253 270 928 663 599 478 255 and Grand Bahama).
The latter had the highest enrolment rates amongst infants and toddlers (0–2 years of age) and the eldest youth group (19–24).

These findings are not surprising, as New Providence has an abundance of day- care centers catering to working parents.

Such facilities are not as prevalent in other regions, where the economic structure depends highly on self-employment and infor- mal activities, which more easily accommodate the pres- ence of young children in the workplace (often the home).
In the case of those 19–24 years old, most (if not all) post- secondary institutions are based on the two islands of Region 1.

Surprisingly, Exuma and Long Island (Region 3) had the highest enrolment rates for persons 17–18 years old (60.5%) (Table 5-2).
Closer examination of this phe- nomenon indicates that, unlike their counterparts in New Providence and Grand Bahama, who were either enrolled in tertiary schools or working, all of these individuals were still in high school because a significant number had had to repeat one or more grades (Table 5-9).

BLCS data indi- cate that grade repetition in secondary school was consid- erably higher in Region 3 (18.5%) compared to the other three regions.

This situation requires further investigation and action.
Quintile Comparisons Although enrolment rates were high across all quintiles, those in the wealthiest quintile were more likely part of the school system, particularly in the non-compulsory age cat- egories.

As Table 5-2 indicates, the enrolment rate for chil- dren 3–4 years old was 100% in quintile 5, compared to 65.8% in quintile 1.
If allowed to continue unchecked, such a situation would give persons in the wealthier quin- tiles a jump start in the educational process—an advantage they would likely maintain throughout their lives, accord- ing to various sociological studies on the benefits of early childhood education.

Cognizant of this issue, policymakers have instituted initiatives to correct this potential imbal- ance.
One such initiative is the development of a pre- school curriculum and attachment of pre-schools to pri- mary schools, the effects of which are yet to be determined.

Persons 19–24 years old in the wealthiest quintile had an enrolment rate approximately 10 times higher than that of persons in the poorest quintile (30.9% versus 3.5%).

Stated simply, richer persons were more likely than poorer ones to have a tertiary level of education.
This suggests that incentives and initiatives directed toward encouraging participation in tertiary education should be intensified and/or redirected.
83340_087-108 3/31/05 9:22 PM Page 91 EDUCATIONAL SYSTEM: ACHIEVEMENTS AND CHALLENGES 91 | TABLE 5-3 Type of School, by Age (Those Currently Enrolled) Age group (years) School type Total 0–2 3–4 5–10 11–13 14–16 17–18 19–24 All Bahamas Pre-school/day care Primary High school Technical/vocational College/university N Region 1 Pre-school/day care Primary High school Technical/vocational College/university N Region 2 Pre-school/day care Primary High school Technical/vocational College/university N Region 3 & 4 Pre-school/day care Primary High school Technical/vocational College/university N Quintiles 1, 2, & 3 Pre-school/day care Primary High school Technical/vocational College/university N Quintiles 4 & 5 Pre-school/day care Primary High school Technical/vocational College/university N 0.0
83340_087-108 3/31/05 9:22 PM Page 92 92 | BAHAMAS LIVING CONDITIONS SURVEY 2001 School Type and Level Two-thirds of the nation’s children were enrolled in pub- lic schools, ranging from 54% in New Providence and Grand Bahama (Region 1) to 90% in Exuma and Long Is- land (Region 3) (Table 5-4).
For the overwhelming ma- jority of children in the two poorest quintiles—86% and 78%, respectively—public schools were their vehicle for obtaining an education.

In contrast, slightly less than half (46%) of the students in quintile 4 and a quarter of those in quintile 5 attended Government schools.

For children in the public school system, 57% were in primary school, an additional 43% were in secondary school, and less than 2% were in pre-school.

No significant variation was found by region.


The pro- portion of students in primary school was highest in quintiles 1 (66%) and 5 (60%).

Within the wealthiest quintile, no children were enrolled in public pre-schools.

This finding could indicate that persons in this quintile prefer private pre-schools or home-schooling and can exercise this choice.
However, it could also indicate the effectiveness of Government policy as it relates to pre- schools; that is, it gives priority to providing for those with the greatest need and therefore the neediest students, who would otherwise lack access to pre-school (Table 5-4).

DISTANCE TRAVELED Differences by Level of Schooling Nationwide, slightly more than one-third of students at- tended a school within a mile of their homes, while nearly one-quarter had to travel more than five miles (Table 5-5).
The Government’s effort to ensure that primary schools are located in most settlements and communities is reflected by the data, which show that 46% of all primary school stu- dents attended a school within a mile of their homes—a proportion noticeably higher than their counterparts at- tending pre-schools or secondary schools.

On average, these students traveled 2.7 miles to school, a shorter dis- tance than any other category of students.
High-school stu- dents traveled the farthest, with an average of 4.4 miles.

Regional Differences On average, students in Abaco, Andros, and Eleuthera (Region 2) had to travel longer distances to school than did their counterparts in other regions.

For example, they traveled 6 miles, compared to 4.8 miles for students in Exuma and Long Island (Region 3), who had the second longest distance to travel.
High-school students in these two regions traveled considerably farther than did those in the other two regions.
In Region 3, nearly 63% of students had to travel more that 5 miles, compared to nearly 51% TABLE 5-4 Current Public-school Enrolment, by Type and Level (Ages 0–24) Level of schooling School type Characteristic Pre-school Primary High school All Bahamas Region 1 2 3 4 Quintile N 1,353 595 429 170 159 512 349 261 169 43 Public school Private school N 83340_087-108 3/31/05 9:22 PM Page 93 TABLE 5-5 Distance (Miles) to School, by Level Level All Bahamas Pre-school/day care Primary High school All schools Region 1 Pre-school/day care Primary High school All schools Region 2 Pre-school/day care Primary High school All schools Region 3 Pre-school/day care Primary High school All schools Region 4 Pre-school/day care Primary High school All schools Quintile 1 Pre-school/day care Primary High school All schools Quintile 2 Pre-school/day care Primary High school All schools Quintile 3 Pre-school/day care Primary High school All schools Quintile 4 Pre-school/day care Primary High school All schools Quintile 5 Pre-school/day care Primary High school All schools Miles traveled (%) Avg.
distance N 83340_087-108 3/31/05 9:22 PM Page 94 94 | BAHAMAS LIVING CONDITIONS SURVEY 2001 in Region 2.
The distances traveled by these students re- flect the fact that most communities in these regions lack high schools, which are few in number and located only in specific areas.

Region 3, which comprises two separate is- lands, has only three high schools.
The major reason for so few schools is that the population base does not support establishing additional schools.4 Because schools—particularly high schools—in such areas are difficult to access due to the distance involved, the Government, via contracts, provides a busing system for students in these areas to ensure that distance is not a deterrent to school attendance.
Government-operated bus service provided transportation for 59.8% of high-school students in Region 2 (Abaco, Andros, and Eleuthera) and 72.6% of those in Region 3 (Exuma and Long Island).

Likewise, more than 20% of primary-school students in the three regions outside of New Providence and Grand Bahama used the school bus.

Quintile Comparisons As Table 5-5 suggests, the higher the consumption- expenditure quintile, the farther the distance traveled to school.
Persons in the wealthiest quintile traveled an aver- age of 4.2 miles, compared to 2.7 miles for those in the poorest quintile.

Some 48% of students in the wealthiest quintile traveled approximately 5 miles to reach primary school.

This percentage compares to 7.4% and 12%, re- spectively, of students in the two poorest quintiles.

This finding reflects the fact that students in the wealthiest quintile can exercise choice of school, which for most is private school.
Moreover, these students were three times more likely than the poorest ones to be driven to school in private vehicles (87% versus 27%) (Table 5-6).

MODE OF TRANSPORT Differences by Level of Schooling Slightly more than half (52.3%) of the nation’s students traveled to school in a private vehicle; an additional 22% walked; and the balance relied on school bus (13.8%), jit- ney (8%), or another means (3.5%).
Private car was the most common mode of transport for students at all levels; however, the proportion of pre-school children who used this means was significantly higher than other groups.

Some 30% of primary-school students walked, while 21% of high-school students took the bus and an additional 15% used the jitney.

Regional Differences Region 1 (New Providence and Grand Bahama) was the only region in which more than half (57%) of students traveled to school by private vehicle.
In Regions 2 (Abaco, Andros, and Eleuthera) and 4 (Other Family Islands), most students took the school bus or walked.

In Exuma and Long Island (Region 3), they took the school bus or were driven in a private car (Table 5-6).

The school bus plays a striking role outside of New Providence and Grand Bahama.

The Survey showed that, in the other three re- gions, more than one-third of students used this system; overwhelmingly, it was the major mode of transport for high-school students.
This data confirms the critical need for a busing system in these regions and further indicates the need for decision makers to ensure its continuance and potential improvement.

Quintile Comparisons Nearly all students in the wealthiest quintile (87%) took a private car to school, compared to 27% of those in the poorest quintile.

In the latter group, 43% walked to school, compared to only 3% in the former group.
Heavy reliance on the school bus and jitney, particularly for high- school students, is obvious amongst students in the two poorest quintiles.

In quintile 1, an almost equal propor- tion of high-school students used the jitney (27.8%) and school bus (24.4%).

In quintile 5, these respective per- centages were 5.3% and 3.6%.

These findings indicate the demand for school-bus ser- vice.

Of concern, however, is the relatively large propor- tion of poorer students who use the jitney.
Whether this results from the school not catering to the area in which they live, an administrative loophole, or the students’ fail- ure to use the service is unknown.

Whatever the reason, further investigation is needed.
Some of the surveyed stu- dents who said they were jitney users may have indeed par- ticipated in the school-bus system.5 Several jitney opera- tors are contracted to bus children to school; perhaps because these students physically rode in a jitney, they an- swered the question accordingly, not indicating that they had a school voucher to ride the jitney.

4 It should be noted that, in certain areas, some students must travel by both car and bus in order to attend high school.
5 Jitney services are available only in New Providence and Grand Ba- hama (Region 1).
83340_087-108 3/31/05 9:22 PM Page 95 EDUCATIONAL SYSTEM: ACHIEVEMENTS AND CHALLENGES 95 | TABLE 5-6 Mode of Transport to School, by Level of Schooling Transport mode Level Walk Private car School bus Jitney Other N All Bahamas Pre-school/day care Primary High school All schools Region 1 Pre-school/day care Primary High school All schools Region 2 Pre-school/day care Primary High school All schools Region 3 Pre-school/day care Primary High school All schools Region 4 Pre-school/day care Primary High school All schools Quintile 1 Pre-school/day care Primary High school All schools Quintile 2 Pre-school/day care Primary High school All schools Quintile 3 Pre-school/day care Primary High school All schools Quintile 4 Pre-school/day care 1,033
(continues) 83340_087-108 3/31/05 9:22 PM Page 96 96 | BAHAMAS LIVING CONDITIONS SURVEY 2001 TABLE 5-6 (Continued) Transport mode Level Walk Private car School bus Jitney Other Primary High school All schools Quintile 5 Pre-school/day care Primary High school All schools N 137 135 329 25 71 51 147 SCHOOL ATTENDANCE IN LAST FIVE DAYS Comparisons by Schooling Level Attendance is one among many variables used to assess students’ overall participation in the school system.
Table 5-7 shows that, at both the primary and secondary levels, the proportion of students who attended school the full week prior to the interview exceeded 85%.

At both levels, students in private schools had a better attendance record than those in Government schools.

Likewise, the atten- dance record for girls was better than that for boys.

During the week surveyed, 4% of the nation’s primary school students and 3% of its high-school students were absent the entire week.
TABLE 5-7 Attendance in Last Five Days, by Level of Schooling Primary school (days) High school (days) Characteristic All Bahamas School Type Government Private Gender Boys Girls Region 1 2 3 4 Quintile 87.2 86.2 89.6 85.1 89.8 89.3 73.0 76.6 84.4 86.2 89.6 86.1 87.4 86.2 1– N 949 199 750 499 450 491 262 99 97 327 213 189 137 71 5 86.0 85.0 88.6 85.0 87.0 87.2 76.8 83.2 92.5 84.3 87.8 86.0 84.6 88.3 1– N 724 138 586 367 357 355 225 73 71 195 178 153 135 50 83340_087-108 3/31/05 9:22 PM Page 97 EDUCATIONAL SYSTEM: ACHIEVEMENTS AND CHALLENGES 97 | The survey found that girls were more likely than boys to miss school for reasons other than illness, especially at the high-school level.
This was the case for 81% of girls and 70% of boys.

Government-school students at the primary level were more likely to be absent due to illness than their private-school counterparts (26% versus 18%).

At the high-school level, the situation was greatly reversed; illness was the reason for absences amongst 18% of Government-school children and 46% of private-school students (Table 5-8).
In short, children in Government schools are far more likely to be absent for non-health reasons than those in private schools, probably because parents of private-school children view education as an investment and make extra efforts to ensure that their children attend regularly.

It could also stem from the fact that private schools enforce their attendance rules more strictly.
Regional Comparisons Region 1 (New Providence and Grand Bahama) was the only region in which high-school attendance was lower than primary attendance.

Region 2 (Abaco, Andros, and Eleuthera) had the lowest attendance rate at both levels; however, at the high-school level, attendance was consid- erably lower than in the other three regions.

Additionally, at both levels, the proportion of Region 2 students who were absent the entire week was significantly higher than in other regions.
The survey found that high-school students were more likely to be absent due to illness than those in primary school (Table 5-8).

For 55.5% of high-school students in Region 4 (Other Family Islands), illness accounted for their absence.

However, this finding is based on only a small number of observations (5); moreover, absenteeism was not a serious problem in Region 4 as no students were absent for the entire one-week period, and some 93% attended all five days (Table 5-7).
One striking finding is that, in Region 2 (Abaco, Andros, and Eleuthera), some 85.5% of high-school students indicated they were absent for non-health reasons (Table 5-8).

This percentage was considerably higher than the second highest figure (73.3%) recorded in Region 1 (New Providence and Grand Bahama) and nearly twice that found in Region 4 (Other Family Islands).
On the TABLE 5-8 Percentage Who Did Not Attend All Five Days, by Level and Reason Primary school High school Characteristic Illness Other All Bahamas School type Government Private Gender Boys Girls Region 1 2 3 4 Quintile N 155 135 20 88 67 46 72 24 13 57 33 25 26 11 Illness Other 24.7 18.1 46.2 29.8 19.2 26.7 14.5 31.3 55.5 14.7 19.0 14.8 26.2 75.5 75.3 81.9 53.8 70.2 80.8 73.3 85.5 68.7 44.5 85.3 81.0 85.2 73.8 24.5 N 114 97 17 60 54 43 53 13 5 44 25 21 17 5 83340_087-108 3/31/05 9:22 PM Page 98 98 | BAHAMAS LIVING CONDITIONS SURVEY 2001 Survey form, the “other reasons” category was to be speci- fied; however, in many instances, it was not.
When it was, the reasons given were so varied and the observations so few that further analysis was precluded.6 The lower attendance rate of Region 2 and the under- lying causes are not new to decision makers.
For example, in June 1993, the National Task Force on Education con- cluded that absenteeism in Region 2 was linked to craw- fishing and crabbing seasons.7 Because crawfishing is the backbone of many families’ monetary gains for the year, their children absent themselves from school in an effort to participate in such family activities.

Thus, these eco- nomic realities challenge educators to develop solutions.
Suggestions put forth have included introducing a flexible, district-based school calendar and developing a compre- hensive, practical training and/or job-release programme.

Quintile Comparisons When the data were examined by living standards, no appreciable differences were found in attendance.

How- ever, differences were noted in reasons for non-attendance.
At both the primary and high-school levels, children in the poorest quintile were more likely to be absent for non- health reasons than those in all other quintiles (with the exception of primary-school children in quintile 3).

Amongst high-school students, 85.3% of those in the poor- est quintile were absent for non-heath reasons, compared to 24.5% of their counterparts in the wealthiest quintile.
When the reasons for absences were examined by quin- tile, observations were too small to allow for reliable analy- sis; however, they did indicate that the major reasons students in the poorest quintile gave for their absence were “no lunch,” “no transportation,” and “did not want to go.” GRADE REPETITION Differences by Schooling Level The Survey data show that 14% of primary-school students repeated a grade, whilst 10% of those in secondary school repeated a grade when they were in primary school.
Of these students, 3% repeated one or more grades whilst in 6 One of the other reasons given was “hurricane.” Indeed, Hurricane Mitchell threatened the country, particularly Region 2 (Abaco, Andros, and Eleuthera) during the early stage of fieldwork.

7 See National Task Force on Education, Ministry of Education, Nassau, 1994. secondary school.
In each instance, repetition was higher for boys than for girls, with differences more pronounced amongst secondary students who had repeated grades in primary school.

The proportion of boys repeating grades was twice that of girls (14% versus 7%).

Students in Government schools had a higher repetition rate than those in private schools.

Within the secondary school, no signif- icant difference was found between Government and private schools with regard to repeating a class.
However, at the primary-school level, a noticeably larger percentage of Government students repeated classes.

Regional Differences At the primary level, Regions 1 and 3 had significantly lower repetition rates than Regions 2 and 4.

However, at the sec- ondary level, Region 3 had the highest repetition rate, whilst Region 1 had the lowest.

Particularly disturbing was the rel- atively high proportion of secondary students in all regions except Region 1 who had repeated grades while in primary school.
Of further concern is the large proportion of sec- ondary-school repeaters in Regions 3 (18%) and 4 (13%).

Quintile Comparisons Somewhat unexpectedly, no distinct relationship was found between grade repetition and students’ living standards.

Between the wealthiest and the poorest quin- tiles, a slight difference was observed at the primary level; however, rates in these groups were higher than those of the other three quintiles.
Even more surprising was that, at the secondary level, rates for these two quintiles were about equal and were higher than for students in all other groups, except quintile 3 (Table 5-9).
SELECTED OUTCOMES BY SCHOOLING OF MOTHER In sociological circles, it is generally thought that parents’ educational background has a significant effect on the schooling of their children and that student performance is linked to the educational level of the parent; thus, students who perform better are likely to have parents with a higher educational background than that of other stu- dents.

As Table 5-10 shows, mothers with higher levels of education had fewer children who repeated a grade.
For instance, 19.4% of children whose mothers had a primary- school education repeated a grade; however, only 8% of children whose mothers had a tertiary-level education did so.
The attendance record for children whose mothers had 83340_087-108 3/31/05 9:22 PM Page 99 EDUCATIONAL SYSTEM: ACHIEVEMENTS AND CHALLENGES 99 | TABLE 5-9 Grade Repetition (%) (Currently Enrolled Students) Primary students Secondary students Characteristic Primary repeated All Bahamas School type Government Private Gender Boys Girls Region 1 2 3 4 Quintile 13.9 14.9 11.5 14.3 13.4 12.9 20.7 11.9 20.9 17.0 13.9 10.8 11.9 14.2 N 949 750 199 499 450 491 262 99 97 327 213 189 137 71 Primary repeated Secondary repeated 10.4 11.7 7.1 13.8 7.0 9.3 15.5 16.2 16.6 16.1 8.9 4.0 11.5 16.7 3.3 3.4 3.0 3.9 2.6 2.2 5.3 18.5 13.4 3.7 3.2 3.8 2.5 3.5 N 725 587 138 368 357 356 225 73 71 195 179 153 135 50 TABLE 5-10 Selected Schooling Outcomes, by Schooling of Mother Mother’s educational level Outcome (children 5–24) Less than primary Primary Secondary Tertiary Not known Current enrolment status Yes No N If “yes,” then Ever repeat grade Yes No Full attendance Yes No Enrolled in Government school Yes No N 83340_087-108 3/31/05 9:22 PM Page 100 100 | BAHAMAS LIVING CONDITIONS SURVEY 2001 TABLE 5-11 Reported Reasons for Unenrolment (ages 5–16 years) Reason given Total Boys Girls Need to work Does not want Pregnancy Chronic illness Completed Other Too young or hasn’t started N 0.0 43.8 2.0
 11.3 12.2 17.3 13.3 18 0.0 46.5 0.0 0.0 16.0 22.7 14.8 13 0.0 35.4 8.5 47.6 0.0 0.0 8.5 5 a primary-level education was slightly lower (86%) than those whose mothers had a tertiary-level education (88%).
The data also indicate that educational background of the mother influences whether her children attend Govern- ment or private schools.

For students whose mothers had a primary-school education, 84% were enrolled in Gov- ernment schools; for those whose mothers had a tertiary- level education, the proportion in Government schools was considerably less (41%).
UNENROLLED YOUTH Since The Bahamas has a compulsory school age, knowing the proportion of persons within this group (5–16 year olds) who are not enrolled and the underlying reasons offer educators useful data.

The BLCS attempted to cap- ture this information (Table 5-11); however, the number of observations was too few (18) to allow for meaningful, reliable analyses.

However, as a basic guideline, the data indicated that 44% of unenrolled youth in this age group simply did not want to be in school.
This was the main reason for boys and the second major reason for girls.

Educational Status of 16–24 Year Olds Tables 5-12 and 5-13 show that 68% of those between the ages of 16 and 24 had completed high school, while 32% had no form of academic qualification.

That girls contin- ued on through the system more than did boys is evident from the data; only 3.8% of girls with 1–3 years of high school terminated their education at this point, compared to 11% of boys.
A greater proportion of girls than boys completed high school, and 7.4% of girls, compared to 4.4% of boys, completed college.
Girls also surpassed boys in qualifications; considerably fewer girls than boys had no TABLE 5-12 Education of Youth Not in School (ages 16–24) Highest level completed Characteristic Primary or lower High school 1–3 High school 4–5 High school 6 College 1–2 College 3 Technical/ vocational All Gender Boys Girls Region 1 2 3 4 Quintile N 572 303 269 337 146 43 46 173 136 109 87 62 83340_087-108 3/31/05 9:22 PM Page 101 EDUCATIONAL SYSTEM: ACHIEVEMENTS AND CHALLENGES 101 | TABLE 5-13 Qualifications of Youth Not in School (ages 16–24) School-leaving certif./High-school diploma BJC; Pitman/ RSA stage 1; CXC basic; CSE; Cambridge Jr. School Certif.
GCE ‘O’ levels; BGCSE; Cambridge School Certif.

; CXC gen. prof.; Pitman stage 2 & 3/ RSA stage 2 Post-secondary qualification Characteristic No.
qualifications All Gender Boys Girls Region 1 2 3 4 Quintile N 569 303 266 336 144 43 46 174 135 106 87 qualifications (23.5% versus 40.1%).
Beyond this level, the proportion of girls with various levels of qualifications was greater than that of their male counterparts.

Regional and Quintile Comparisons In all regions except Region 3 (Exuma and Long Island), about 67% of youths completed high school.
In Region 3, only 48.6% of youths completed high school; however, this region had the highest proportion of youths with The Bahamas General Certificate of Secondary Education (BGCSE) or its equivalent (30.3%), and had the second lowest proportion of youths without any qualifications.8 Region 2 (Abaco, Andros, and Eleuthera) had the largest proportion of youths with only a primary-level education and the smallest proportion of youths who had completed college.
Youths in this region were also less qualified than those in other regions; they had the largest proportion of 8 The BGCSE, initiated in 1993, is an exit examination for students completing Grade 12; The Bahamas Junior Certificate (BJC), reintro- duced the same year, evaluates students completing Grade 9. persons without qualifications and the smallest proportion with either BGCSE or post-secondary qualifications.
The two poorest quintiles accounted for 56% of youths not in school, while the two wealthiest quintiles accounted for 26%.

Within all quintiles, the proportion of youths who had completed high school was more than 50%, with the smallest proportion in the poorest and wealthiest quintiles (59% and 60%, respectively).

Within the wealthiest quintile, approximately 20% of youths had completed college, compared to 3% of those in the poor- est quintile.
Likewise, youths in the wealthiest quintile were far better qualified than those in the other quintiles; 24% of them had post-secondary qualifications, compared to 12% in quintile 4 and 2% in quintile 1.

More than half (53%) of the youths in the poorest quintile had no academic qualifications, compared to 9% of those in the wealthiest quintile.
The above data clearly show that youths from the poorer quintiles exited the educational system earlier and with fewer qualifications than did youths from wealthier quintiles.

Youths from the poorer quintiles, therefore, are 83340_087-108 3/31/05 9:22 PM Page 102 102 | BAHAMAS LIVING CONDITIONS SURVEY 2001 disadvantaged.
Because they are less equipped to enter the job market, they are more likely to end up with lower- paying jobs, which, in turn, will seal their position in the lower quintiles, thereby repeating the cycle experienced by their parents.

NATIONAL EDUCATIONAL EXPENDITURE BLCS data on educational expenditure show that the average household expenditure on education amounted to $1,470 in 2001.

This represented approximately 4% of total annual household expenditure.
This figure compares with an estimated 5.3%, as calculated by the Consumer Price Index (CPI).
Educational expenditure included that for “school tuition and fees,” “extra classes (outside school),” “transportation,” “lunch and snacks at school,” “uniforms,” “books,” and “other supplies.” By contrast, the CPI, based on the 1993 Household Budgetary Survey, included “school tuition and fees,” “books,” and “other supplies.” According to Table 5-14, “lunch and snacks at school” represented the largest item of household expenditure on education, accounting for 31.3% of educational expenses.
This was followed by “school tuition and fees” (28.6%), “uniforms” (22.4%), “books” (10.3%), and other cate- gories (ranging from 1% to 4%).

Regional Comparisons Across all regions, major expenditure items, in varying or- der, were: “school tuition and fees,” “lunch and snacks at school,” “uniforms,” “books,” and “other supplies.” To- gether, these five categories accounted for 96.02–99.27% of educational expenditure.
Urban households in Region 1 spent considerably more on education than did Family Island households.

According to Table 5-14, the former group spent $1,583 per year on education; Region 2 households spent 56.1% of this amount, whilst those in Regions 3 and 4 spent 43.4% and 34.2%, respectively.

Region 1 households spent the largest proportion of educational expenditure on tuition and fees (31.1%).
Those in Region 2 spent the most on “lunch and snacks at school,” whilst those in Regions 3 and 4 spent the largest proportion (41.5% and 41%, respectively) on “uniforms.” Across all regions except Region 4 (Other Family Islands) expenditure on “lunch and snacks at school” accounted for one-third or more of annual educational expenditure.

It was the highest expenditure (37.6%) for Region 3, 30.7% for Region 1, and only 28.1% for Region 4.
For Family Island households, “uniforms” represented a substantial burden—more than 41% of total educational expenditure in two of the regions and nearly 29% in an- other.

On the other hand, households in New Providence and Grand Bahama spent more on “school tuition and fees,” presumably because of the preponderance of private educational institutions available on those two islands.
Quintile Comparisons Households in the wealthiest quintile spent five times as much on education as those in the poorest and almost one-third more than the next wealthiest quintile.

Accord- ing to Table 5-14, the average household expenditure in the wealthiest quintile ($3,388) was more than twice that of the national average and accounted for about 6.4% of total consumption expenditure for those households.
The data reveal a direct relationship between welfare status and household expenditure on education, highlighting a significant expenditure difference between the wealthiest and poorest groups.

Survey results showed a distinct difference between the educational-expenditure priorities of households in the poorest and wealthiest consumer quintiles.
While house- holds in the poorest quintile spent the largest proportion on “uniforms,” those in the wealthiest spent it on “school tuition and fees.” The second and third poorest quintiles spent more on “lunch and snacks at school” than any other item, while the second wealthiest spent it on “school tuition and fees.” In the wealthiest quintile, the proportion spent on “school tuition and fees” was more than twice what was spent on any other item.
Households in this consumer class were the only ones that spent less than one-third of their educational output on “lunch and snacks at school” and less than 10% on “uniforms.” For households in the poorest consumption quintile, like Family Island householders, “uniforms” presented a substantial burden.

While most households in quintile 1 reside in Region 1, the issue affects all regions.
Although expenditure on transportation was only 2.5% nationally, it accounted for nearly 5% of household expenditure in the poorest quintile and 2% in the next poorest.

In all other quintiles, it represented less than 2% of expenditure and accounted for the lowest proportion.
83340_087-108 3/31/05 9:22 PM Page 103 EDUCATIONAL SYSTEM: ACHIEVEMENTS AND CHALLENGES 103 | , ) 1 2 – 0 s e g A ( - , 3 $ 3 4 0 2 $ , 8 8 2 , 1 $ 5 3 9 $ 5 7 6 $ 1 4 5 $ 6 8 6 $ 7 8 8 $ 3 8 5 , 1 $ 0 7 4 , 1 $ e r u t i d n e p x e l a t o t e g a r e v A 1 6 .

3 9 0 .

1 8 2 .

3 5 6 8 .


3 2 8 9 7 .

3 3 .

7 5 8 2 .

0 0 0 .

2 6 9 3 .

9 6 .

1 1 5 .

1 9 8 .

1 3 5 0 .

3 1 3 8 8 .

1 4 .

3 0 0 0 .

6 8 0 .

2 7 .

1 .

3 4 0 3 1 0 .

3 3 2 7 9 1 .

4 1 .

0 1 3 1 .

4 0 0 0 .

6 9 6 1 .

8 5 0 .

0 1 .

2 1 8 .

3 3 0 1 .

0 3 0 0 2 1 .

5 4 4 .

0 0 0 .

0 3 .

3 1 3 1 .

0 0 7 4 .

2 6 .

1 3 6 0 4 3 .

9 8 .

1 1 3 1 .

4 7 1 .

0 .

3 5 0 1 4 8 0 .

2 5 0 .

0 1 .

8 2 7 0 .

1 4 4 6 .

1 1 0 3 .

7 0 0 0 .

7 9 5 .

6 5 0 .

6 1 .

0 1 9 .

1 3 8 4 .


1 4 2 9 .

1 1 9 9 7 .

0 0 0 .

1 2 5 1 .

4 2 0 .

0 2 .

1 2 6 7 3 .

.

6 7 8 2 0 5 .

1 1 7 4 5 .

0 0 0 .

9 0 .

1 3 6 2 .

1 9 6 2 .

6 6 0 3 .

.

3 7 0 2 5 0 0 1 .

9 4 .

3 5 0 0 .

8 6 1 4 4 3 6 2 4 8 4 4 2 0 6 2 9 1 7 8 1 7 4 5 6 8 0 , 1 0 6 7 2 $ , 2 7 0 2 $ , 3 5 2 , 1 $ 9 8 2 , 1 $ 9 1 2 , 1 $ 8 6 7 $ 7 3 0 , 1 $ 4 6 0 , 1 $ 6 1 7 , 1 $ .

1 8 2 7 6 8 .

1 9 7 0 .

1 2 5 1 .

6 4 5 .

7 5 2 .

0 3 .

1 0 0 0 .

5 2 .

5 2 9 6 8 6 0 .

3 2 0 .


9 8 9 1 .

0 0 6 .

8 4 2 .

6 4 .

1 0 0 0 .

7 5 8 5 .

1 7 6 2 0 .

0 1 .

1 6 7 6 1 .

5 3 .

7 1 6 .

1 4 3 .

1 0 0 0 .

1 7 6 3 .

7 6 7 8 0 .

0 3 .

1 0 0 6 1 .

1 7 .

1 1 4 4 .

1 2 3 .

1 0 0 0 .

9 4 8 8 .

1 6 0 0 0 .

4 5 0 .

0 5 6 1 .

9 3 .

7 1 7 1 .

3 1 5 0 .

0 0 0 .

3 7 .

1 5 0 6 0 0 0 .

7 9 .

3 .

1 9 0 2 5 4 2 1 .

6 0 2 .

0 1 .

0 0 0 0 .

4 2 9 6 5 4 .

0 0 0 .

0 0 0 .

.

3 7 4 2 1 3 .

1 2 4 9 6 .

2 3 .

1 0 0 0 .

4 1 .


5 8 7 6 0 0 0 .

9 4 2 .

4 0 5 1 .

4 5 0 1 .

2 0 2 .

7 0 2 .

0 0 0 .

8 5 .

3 2 9 6 9 6 0 .

6 5 0 .

6 8 6 1 .

7 3 .

9 9 1 .

2 2 1 .

1 0 0 0 .

0 8 1 6 7 2 4 1 .

1 5 4 2 .

.

7 5 8 2 1 3 .

1 3 8 3 .

2 2 6 2 0 1 .

6 8 .

3 4 0 0 .

2 1 0 2 , 8 4 6 , 1 $ .

5 7 8 6 2 6 0 .

4 7 0 .

9 8 6 1 .

2 6 9 .

2 2 2 .

6 1 .

1 0 0 0 . )
l o o h c s e d i s t u o ( - E R P / E R A C Y A D t n e p s e r a h S ) l o o h c s e d i s t u o ( ) s e u tin n o c ( 6 9 .
1 5 8 7 4 .

9 1 .

0 9 2 .

3 2 0 7 9 .

9 7 .

1 3 1 3 .

1 1 3 .

0 0 5 .

3 3 9 0 8 1 .

4 1 .

1 .

1 5 2 2 0 7 0 .

0 8 .

1 3 .

7 4 6 2 1 0 2 1 .

2 7 0 .

5 2 .

1 .

6 7 0 3 4 4 5 3 .

0 1 .

4 1 1 .

0 3 0 4 .

6 3 .

2 3 .

8 8 0 4 9 3 .

4 0 1 .

0 0 0 0 .

5 3 .

8 2 3 1 .

4 4 9 3 .

3 0 2 0 .

0 3 .

0 5 1 .

5 3 .

3 7 0 4 9 3 .

8 9 2 0 .

5 3 .

1 .

3 7 4 3 2 3 .

5 3 7 1 .

2 2 9 3 .

1 8 7 .

1 .

1 5 0 3 3 8 7 2 .

1 2 .

1 6 6 .

1 6 8 9 1 .

0 0 .

1 3 1 3 .


9 2 ) l o o h c s e d i s t u o ( , 3 $ 7 6 7 , 1 $ 7 3 0 , 1 $ 8 8 7 $ 8 2 5 $ 2 6 5 $ 5 2 6 $ 4 8 6 $ 5 0 3 , 1 $ 4 0 2 , 1 $ e r u t i d n e p x e l a t o t e g a r e v A 83340_087-108 3/31/05 9:22 PM Page 104 104 | BAHAMAS LIVING CONDITIONS SURVEY 2001 2 3 .

7 6 7 2 .

0 0 0 .
7 6 7 2 .

0 0 0 .

1 7 5 0 5 0 1 .

0 5 4 .

0 0 0 .

7 3 1 4 e l i t n i u Q 2 9 .

1 1 7 4 5 .

0 0 0 .

9 8 1 3 8 2 5 1 .

4 5 4 .

0 0 0 .

3 1 2 2 7 9 5 4 .

3 9 2 .

7 8 0 .

.

7 5 8 2 6 7 9 .

4 7 7 .

5 1 .

4 0 0 0 .

1 5 7 8 2 .

3 1 .

3 .

1 9 7 2 8 6 8 3 .

1 8 .

3 1 4 9 9 .

7 6 .

3 0 0 0 .

5 3 1 6 9 8 1 .

8 8 0 .

1 6 2 .

0 6 4 4 .

8 3 .

8 1 7 8 0 1 .

9 6 .

3 0 0 0 .

4 5 1 6 2 5 .

3 1 .

0 5 4 .

3 6 5 .

3 4 1 5 .

1 3 0 4 .

1 1 8 6 4 .

0 0 0 .


9 7 1 7 9 8 , 3 $ 3 0 3 , 2 $ 0 0 6 , 1 $ 9 7 9 $ 7 2 2 , 3 $ 0 2 0 2 $ , 2 9 4 , 1 $ 0 7 2 , 1 $ 4 4 2 5 .

3 8 .

1 4 5 4 .

2 8 4 2 .

2 9 .

1 2 2 2 1 .

3 2 2 .

0 0 0 .

1 2 0 5 .

1 6 0 0 0 .

5 5 2 .

7 1 .

0 2 2 8 0 .

9 2 .

3 1 7 6 .

1 0 0 0 .

5 1 0 0 0 .

7 4 9 .

.

3 6 9 4 0 3 .

0 1 9 3 .

0 4 3 .

4 2 7 8 5 .

0 0 0 .

2 1 5 6 5 3 .

6 1 .

3 3 5 .

1 6 9 .

1 5 2 .

1 3 9 3 .

2 1 6 0 4 1 .

0 0 0 .

7 5 0 .

3 1 6 1 .

5 0 3 .


0 1 9 2 3 5 8 6 $ 9 5 4 .

3 2 0 .

0 3 .

8 4 5 9 3 .

0 1 .

0 3 5 1 .

3 1 9 0 4 .

0 0 0 .

7 9 1 5 1 9 $ .

3 0 0 6 0 0 0 .

0 0 0 .

9 6 .

3 0 0 0 .

0 0 0 .

0 0 0 .

8 2 6 3 .

3 5 8 8 .

0 0 0 .

8 1 .

4 1 7 9 4 9 4 0 1 .

4 7 9 .

0 0 0 .

9 9 3 n o i g e R 0 4 .

3 1 1 5 6 .

0 0 0 .

2 6 2 2 1 0 2 1 .

1 2 4 .

0 1 .

0 1 9 4 9 6 4 .

9 0 0 .

7 1 .

2 1 9 4 9 8 0 .

1 4 1 .

2 0 0 0 .

0 3 .

0 3 7 0 7 4 .

3 6 .

1 1 7 7 7 .

0 0 0 .

1 7 0 $ 0 0 0 .


0 0 0 .

0 0 0 .

0 0 0 .

0 0 0 .

0 0 0 .

0 0 0 .

0 0 0 .

0 4 2 0 .

8 1 .

1 0 0 0 .

0 4 9 2 .

.

5 2 7 4 0 0 5 1 .

2 9 6 .

0 0 0 .

3 7 .

1 2 4 8 0 0 0 .

0 0 0 .

0 0 0 .

0 0 0 .

6 2 5 .

0 0 0 .

.

3 5 0 1 1 0 5 9 $ 1 0 9 .

5 2 0 .

1 5 0 .

8 1 .

7 4 9 0 6 2 .

9 7 .

1 1 8 1 .

5 0 0 0 .

5 2 2 6 3 5 $ 0 0 0 .

4 4 2 .

0 0 0 .

0 0 0 .

3 1 .

8 0 0 0 .

0 0 0 .

2 .

3 4 9 8 .

1 2 0 2 1 3 .

1 9 7 4 .

9 7 9 3 .

3 7 9 1 .

.


3 5 0 1 5 6 .

3 0 0 0 .

6 5 3 5 9 7 1 .

0 2 .

1 6 0 4 .

.

1 2 0 4 7 7 .

1 2 .

1 8 0 1 1 0 4 .

0 0 0 .

5 2 7 6 5 1 , 2 $ 0 4 1 , 2 $ 9 0 .

1 9 9 .

3 9 1 .

4 5 4 0 0 2 .

4 2 .

1 7 5 5 1 .

8 8 .

3 0 0 0 .

9 5 9 3 .

4 5 9 0 .

1 8 9 .

3 2 9 9 1 .

3 2 .

1 2 5 5 1 .

8 8 .

3 0 0 0 .
2 6 7 3 4 $ 7 0 7 $ 7 7 0 , 1 $ 7 0 8 , 1 $ 5 5 6 , 1 $ ) l o o h c s e d i s t u o ( - ) l o o h c s e d i s t u o ( ) d e u tin n o C ( 4 1 - 5 E L B A T 83340_087-108 3/31/05 9:22 PM Page 105 EDUCATIONAL SYSTEM: ACHIEVEMENTS AND CHALLENGES 105 | To reiterate, transportation represents a significant bur- den for households in this welfare class.
When this fact is correlated to the data presented in Table 5-6, the distinction is further amplified; that is, while 14.1% of children in the poorest quintile used the jitney (for which there is a charge), only 1.2% of those in the wealthiest quin- tile did so.

Conversely, 87% of children in the wealthiest quintile were transported to school in a private vehicle, compared to only 26.7% of those in the poorest quintile.
Expenditure by School Type Households spent more annually on post-secondary education than on any other level of education.

The low- est expenditure was for children at the primary level, which had the largest enrolment rate—45.17%—of any level (Table 5-3).

Bahamian households spent an average of $1,648 on pre-school education (Table 5-14).

Region 1 households spent an average of $1,716, while those in Region 4 spent less than 50% of that amount.
When examined by quintile, expenditure at this level ranged from $1,220 for the poor- est quintile to $2,760 for the wealthiest.

At the pre-school level, the largest proportion expended was on “school tu- ition and fees;” this was so for all regions and quintiles.
The next major item of expenditure was “lunch and snacks at school,” followed by “uniforms.” Region 3 households spent the least amount (45.7%) on “school tuition and fees” and the most (24.7%) on “lunch and snacks at school;” whilst households in the poorest quintile spent the least on “school tuition and fees” (61.9%) and the most on “uniforms” (17.4%).

According to Table 5-14, Bahamian households spent an average of $1,204 on items related to primary educa- tion.
At this level, the largest expenditure items were “lunch and snacks at school” for Region 1 households and “uniforms” for households in the other three regions.

For the two lowest consumer quintiles, the largest expenditure was “uniforms;” for the next two quintiles, it was “lunch and snacks at school;” and, for the highest, it was “school tuition and fees.” Households in the wealthiest quintile spent more than six times as much as those in the poorest quintile on primary education.
Interestingly, at the secondary level, households in the poorest quintile spent a higher proportion of their educa- tion dollars on “transportation” than they did on “school tuition and fees.” In the wealthiest quintile, the largest proportion was spent on “school tuition and fees,” while “transportation” accounted for less than 1% of total ex- penditure on secondary education.

Regions 3 and 4 had no significant transportation ex- penditures.
In these regions, the overwhelming majority of students attended Government school, for which the bus- ing system was available at no charge.

Bahamian house- holds spent an average of $1,655 on secondary education, with Region 1 households spending the most ($1,807) and Region4 households spending the least ($437).

Simi- larly, the wealthiest households spent more than five times that of the poorest ones.
At the post-secondary level, households across all regions and quintiles spent the largest proportion of their education dollars on “school tuition and fees.” For all households, this item was followed by either “books” or “lunch and snacks at school.” Households spent more on this level of education than on any other.

Region 4 households reported no expenditure at this level, presumably because no institutions offered post-secondary education on those islands.
Table 5-4 helps to explain differences between the wealthiest household quintiles and the other four at all lev- els of education.

While two-thirds of the school population is enrolled in Government-operated, public schools, only 24.6% of children from the wealthiest household quintiles participate in the public-school system.

Table 5-14 displays variations in spending levels amongst the five quintiles.
As Table 5-15 shows, the average net expenditure across the country was $1,357, which Region 1 exceeded by $96; other regions were significantly below the national average—from $870 in Region 2 to $532 in Region 4.

The wealthiest quintile expended four times as much as the poorest on their children’s education ($2,926 versus $663).

For those receiving financial aid only, the average expenditure nationwide was $753.
Again, Region 1 exceeded this amount, while the other three regions were significantly lower (Table 5-15) (however, sample sizes for Regions 3 and 4 were small).

Only the poorest and wealth- iest quintiles exceeded the national average ($1,475 and 1,206, respectively), while the other three were signifi- cantly lower, with quintile 4 expending only $161.

FINANCIAL ASSISTANCE Many Bahamian households received assistance with educational expenses.
As Table 5-16 shows, 7.6% of house- holds with currently enrolled children 0–21 years of age re- ceived a certain amount of assistance.

This was generally 83340_087-108 3/31/05 9:22 PM Page 106 106 | BAHAMAS LIVING CONDITIONS SURVEY 2001 TABLE 5-15 Net Expenditures for Enrolled Children (Ages 0–21) Region Quintile Expenditure average All Bahamas 1 2 3 4 Avg.

(All Bahamas) N Avg.


(those receiving aid only) N $1,357 2,017 $753 119 $1,453 1,089 $784 83 $870 548 $449 29 $680 188 $665 5 $532 192 $438 2 $663 599 $1,475 18 $895 448 $895 19 $1,235 425 $741 27 $1,876 345 $161 32 $2,926 169 $1,206 22 Note: Net expenditure equals expenditures, minus assistance received.

provided by non-household family members (55.2%), private companies (24.4%), private schools (9.4%), Gov- ernment (3.7%), and other sources (7.3%).
Households re- ceived an average of $1,579 to assist with educational expenses.

The average amount of assistance received ac- counted for about 55.5% of annual household expenditure on education.

Regional Comparisons Regions 3 and 4 were conspicuous in terms of the paucity of financial assistance reported.

In all regions except Other Family Islands, assistance with household educational ex- penses was secured mainly from family members who resided elsewhere.
Non-household family members ac- counted for 52.4% of assistance in Region 1, 89.7% in Re- gion 2, and 74.2% in Region 3.

In New Providence and Grand Bahama, a significant amount of assistance was ten- dered by private companies (26.4%) and private schools (10.3%).

Family Islands had little of this type of assistance (Region 2 had only 3.5%).
Government assistance was re- ported only for Region 1.9 Quintile Comparisons Households in the poorest consumer quintile received most of their financial assistance (55.6%) from private schools, while those in the wealthiest received the most (41.1%) from private companies.
9 This finding reflects how the BLCS recorded data; for example, a Family Island student who received educational assistance and at- tended an educational institution in Region 1 would therefore be recorded as a resident of that region.

TABLE 5-16 Financial Aid Received (Enrolled Children, Ages 0–21) Region Quintile Survey question All Bahamas 1 2 3 4 7.6 8.2 5.8 2.6 $1,579 $1,695 $329 $230 1.1 $850 1 2.7 2 3 4 5 5.2 8.7 10.6 15.5 $419 $888 $725 $1,583 $2,975 Received help?

Avg.
Avg.

help received Share, by source Gov’t.

Private school Private co.

Nonprofit org.
Non-household family member Other N 83340_087-108 3/31/05 9:22 PM Page 107 EDUCATIONAL SYSTEM: ACHIEVEMENTS AND CHALLENGES 107 | CONCLUSIONS The above analysis reveals interesting and pertinent information about the Bahamian educational system.
Despite a range of efforts to bring about equity in access to education—attachment of pre-schools to Government- operated schools, provision of primary schools in nearly every community, availability of a free bus system, and standardized curricula and exit examinations— inequalities persist.

Disparities are apparent both across and within regions.
The developed region of New Provi- dence and Grand Bahama is the seat of tertiary education; the COB is situated in New Providence, automatically placing Region 1 students at an advantage.

Region 1 also has the majority of the country’s pre-schools.10 Taken together, these factors mean that Region 1 students exit the educational system with better academic qualifications than students from other islands.
Students from outside New Providence and Grand Bahama had limited access to tertiary institutions and depended almost entirely on Government-operated schools for their education.

They were typified by lower attendance records and higher repetition rates (particu- larly in Regions 2 and 4).

Secondary-school students in these regions traveled greater distances to school than did their Region 1 counterparts, and most relied on bus trans- portation.
Because most attended Government schools, their expenditure on school tuition and fees, as a propor- tion of total educational expenditure, was miniscule; however, this low outlay was offset by substantially high expenditure on uniforms and lunch and snacks at school.

The analyses clearly indicate that students from the wealthier quintiles had a more productive educational ex- perience than did others.
Their enrolment rates were higher, and they were more likely to attend pre-schools and tertiary schools, as well as private schools.

Their school absences were mainly due to illness rather than extraneous reasons.

They completed school with higher academic qualifications than did their counterparts in the poorer quintiles.

Conversely, students from the poorest quintile got a slower start at school.
Their propor- tions in pre-school were considerably lower, they were less likely to attend tertiary schools (no students from quintile 10 Region 1 had the highest household expenditure on education because of the preponderance of private pre-schools and tertiary institutions.

2 were on record for college), and were more likely to exit the educational system without qualifications.

Their expenditure on education was burdened by the cost of uni- forms, lunch and snacks at school, and transportation.
Finally, throughout the analyses, it was noted that, al- though males outnumbered females in the school system, the participation of females was more meaningful.

Their at- tendance and enrolment rates were higher, particularly at the tertiary level.

They exited the school system with higher levels of education and qualifications.

It must be empha- sized, however, that too large a proportion of youths has left and is leaving secondary schools without qualifications.
MEETING THE CHALLENGE: POLICY AND RESEARCH RECOMMENDATIONS As the above results show, educators face many challenges.

The Bahamian educational system needs improving at all levels to ensure that, when students exit the system, they do so with acceptable academic qualifications.

To this end, the necessary infrastructure and resources must be put in place to enforce merit-based promotion, thereby eradicat- ing social promotion completely.
In addition, educators need to address the issue of high repetition rates, particu- larly in Region 3.

Further study is needed with regard to the relevance and practicality of curricula, with specific focus on the Family Islands.

Special emphasis should be given to expanding educational and training opportunities outside Region 1 through distance education and other related initiatives.
To this end, more work is needed to under- stand the precise incentives needed to encourage greater academic participation in these regions, as well as among males in general, whose involvement in higher education is considerably lower than that of females.
In situations where 19–24 year olds are still in high school or where 17–18 year olds do not aspire to attend college, technical and vocational studies should be introduced so that these students can acquire the skills needed to make the transition to the labour force.

More civic clubs should be invited to start programmes to de- velop students’ entrepreneurial ethos and spirit.

In this way, students—especially unskilled youths over 19 years of age—can learn to create jobs and earn money.
On islands where crabbing, fishing, and harvesting of crops are major economic activities for students’ families (especially in Region 2), a shift system of schooling should 83340_087-108 3/31/05 9:22 PM Page 108 108 | BAHAMAS LIVING CONDITIONS SURVEY 2001 be introduced so that critical school hours will not be missed.

Bahama, perhaps using a voucher system for those who frequently take the bus to school.
Efforts must be made to ensure accessibility and affordability of education at all levels, particularly at the pre-school and tertiary levels.

These issues are especially important at the pre-school level, when young children are at the critical stage of cognitive development.

Thus, efforts to incorporate pre-schools into most Government- operated schools should be intensified to ensure accessibil- ity by those unable to pay for this vital service.
Failing that, designated pre-schools may need to be subsidized through agreements allowing for the attendance of “sponsored” children.

That a large proportion of poorer students spent sub- stantial amounts on lunch and snacks at school reinforces the need to revitalize and expand the NSLP.

Although the NSLP appears to be reaching its targeted population, a large proportion of qualifying students and parents are un- aware of the Programme.
Thus, efforts must be created and strengthened to heighten NSLP awareness.

Similarly, the Survey data clearly reveal the financial burden that uniforms place on students in the lower quintiles and a sig- nificant proportion of Family Island students, suggesting the need to subsidize their cost.

The data show that the Government-supported busing system has proven beneficial, especially to students in the Family Islands.
However, it also suggests that the system may need to be expanded in New Providence and Grand Finally, the data infer that students in private schools perform better than those in Government-operated schools.

These results are in line with those of national examinations, which have consistently shown better grades for private-school students.

For example, 2001 BGCSE re- sults indicate that 51% of private-school students received passes of A-C, compared to only 27% of those in Govern- ment schools.
It is often said that the teachers in Government schools are more highly qualified than those in private schools.

If this is indeed the case, then other factors—school environment, availability of supplies, and preparedness of the students themselves, among other variables—must contribute to the greater success of private-school students.

This phenomenon must be studied rigorously to determine the precise, underlying causes for the differ- ences in performance.
Answers to this question could provide a catalyst to effect overall improvement in the Bahamian educational system.

FOR FURTHER READING The Bahamas Union of Teachers.

1974.

The Black Paper on Education.

Nassau: The Bahamas Union of Teachers.

MOE.

1974.

Educational Development in an Archipelagic Nation.

The Maraj Report.

Nassau: Ministry of Education.


83340_109-130 3/31/05 9:25 PM Page 109 CHAPTER 6 Employment Data Analysis: Toward Equitable Planning Kelsie Dorsett T he labour force is that segment of a coun- try’s population economically engaged, or willing and able to be engaged, in the production of goods and services.

It is composed of those persons with jobs—the employed—and those without jobs who seek economic activity— the unemployed.
The Bahamas Living Condi- tions Survey (BLCS) analysed the population of individuals 15 years of age and older.1 However, in order to thoroughly examine how individuals live and the major factors contributing to their well-being, the Survey relaxed this group’s age limits to include persons 10 years of age and older; in this way, it could investigate the extent of child labour and its effects on the well-being of Bahamian households.
Accordingly, this analysis includes a brief section focused only on persons 10–14 years of age.

Reliable labour-force data is vital to formulat- ing, implementing, and monitoring a country’s 1 The age group targeted by the Department of Statistics in its annual labour-force surveys; see DOS (annual).

socioeconomic-development plans and pro- grammes.


Labour-force participation is inextrica- bly linked with socioeconomic status and is a widely asserted determinant of individuals’ well- being and standard of living; hence its inclusion in this chapter.

This overview focuses mainly on employment variables—ranging from employment status and occupational and industrial characteristics to transport to work and hours worked.

In most cases, these variables are analysed by sex, region, and quintile.
Finally, policy implications of this analysis are discussed.

TARGET POPULATION BLCS data show that persons 15 years of age and older had the following characteristics: 44% were household heads, 52% were female, the average age was 38 years, and 85% resided in the more de- veloped areas of New Providence and Grand Ba- hama (Region 1).
Distribution by quintile indi- cates that the largest proportion of this group was 109 83340_109-130 3/31/05 9:25 PM Page 110 110 | BAHAMAS LIVING CONDITIONS SURVEY 2001 in the wealthiest quintile (25%), whilst 15% were in the poorest.

Perhaps predictably, most were Bahamians (87%), with Haitians representing the second largest nationality (7%).
Finally, schooling-level data showed that the major- ity (66%) had a high-school education, 16% were educated to the college level, and 2% had no schooling (Table 6-1).

Labour-force Participants Of the targeted population, 78% actively participated in the labour force.
As Figure 6-1 clearly shows, across all age groups, males participated at a much higher level than did females; differences were more pronounced amongst per- sons 65 years of age or older, where the level of male par- ticipation was more than twice that of females.

As expected, the 25–44 year age group, considered the core of the labour force, had the highest level of participation (91%), accounting for more than half (57%) of the total force (Tables 6-2 and 6-3).
By nationality, Survey data showed that Haitians had a 75% participation rate, which was slightly lower than TABLE 6-1 Population Profile: Individuals 15 Years and Older Population characteristics Total Employed Unemployed Not in labour force Male Household head Region 1 2 3 4 Quintile Nationality Bahamian Haitian Other Caribbean U.S. and Canada Other Education completed No schooling Primary school High school College/university Technical/vocational Age Mean years 15–24 25–44 45–64 65 and older N Percent 83340_109-130 3/31/05 9:25 PM Page 111 EMPLOYMENT DATA ANALYSIS: TOWARD EQUITABLE PLANNING | 111 FIGURE 6-1 Labour-force Participation, by Age Group and Sex TABLE 6-3 Labour-force Characteristics, Persons 15 Years and Older t n e c r e P 100 80 60 40 20 0 96.0 87.1 91.5 73.1 63.3 56.7 43.1 19.9 15–24 25–44 45–64 65 & older Age Group Male Female TABLE 6-2 Labour-force Participation of Persons 15 Years and Older, by Selected Variables Characteristic Total Male Female All Bahamas Age Group
 15–24 25–44 45–64 65 and older Nationality Bahamian Haitian Other Region 1 2 3 4 Quintile N Characteristic Labour force (%) Male Household head Region 1 2 3 4 Quintile Education completed No schooling Primary school High school College/university Technical-vocational Age Mean years 15–24 25–44 45–64 65 and older N 51.8 48.9 86.0 9.7 1.9 2.4 13.8 17.8 19.0 21.7 27.7 1.6 7.8 67.8 18.2 4.6 37.2 16.8 56.7 23.9 2.6 3,677 that of other nationalities; however, the rate for Haitian males was significantly higher than that for the next highest group (93% versus 84%).
Conversely, Haitian females had a rate of 45%, well below that of others (Table 6-2).

Regional Differences New Providence and Grand Bahama (Region 1), where 85% of the total population resides, accounted for an al- most equal share of the labour force (86%).

Not surpris- ingly, participation in Region 1—the primary site for job search and procurement—was higher than in the other three regions.

Indeed, the BLCS data showed that Region 1 participation was 79%, compared to 67% in Region 3.
Interestingly, Region 4—the least developed of the four regions—had the second highest participation rate 83340_109-130 3/31/05 9:25 PM Page 112 112 | BAHAMAS LIVING CONDITIONS SURVEY 2001 TABLE 6-4 Labour-force Participation of Persons 15 Years and Older, by Age Group and Region Age group 15–24 25–44 45–64 65 and older N All Bahamas 60.0 91.4 81.8 29.7 4,875 1 61.3 91.9 83.1 30.0 2,544 Region 2 51.3 87.6 71.8 29.7 1,362 3 47.4 86.7 83.1 20.2 510 4 55.2 92.6 80.7 35.6 459 (Table 6-2).
This is perhaps related to the fact that, in the absence of a corporate/industrial sector, the individuals themselves generate economic activity through informal activities: subsistence farming and fishing and operation of local ‘petty’ stores.

Many do not consider such activities as work, but rather as a way of life, especially in the elderly age group.

As Table 6-4 shows, in Region 4, participation of persons 65 years and older was noticeably higher than in the other three regions.
Quintile Differences The Survey data indicated a direct relationship between labour-force participation and living standard; that is, the higher the consumption quintile, the higher the level of labour-force participation (Figure 6-2).
The poorest con- FIGURE 6-2 Rate of Labour-force Participation, by Quintile 100 n o i t a p i c i t r a P t n e c r e P 80 60 40 20 0 1 2 3 Quintile 4 5 sumption group (quintile 1) had the lowest participation rate (70%); the rate increased with each quintile, peaking at 85% in the wealthiest group (quintile 5).

This pattern did not differ by sex.


Non-participants Selected Characteristics Of those individuals not participating in the labour force, 65% were female, 25% were household heads, and 58% had some high-school education (Table 6-1).

Forty per- cent of the non-participants were youths between 15 and 24 years of age.

It is expected that a large proportion of this group would be in school, given that the average age at which young persons in The Bahamas exit the secondary school system is 17.
It follows, therefore, that the majority of youths between 15 and 17 years of age would be in school, bearing in mind that attendance at school is com- pulsory up to age 16.

The section below focuses on youths between 16 and 24 years of age who neither attend school nor work.

A critical issue facing policymakers across the Caribbean region is unemployed/unattached youths; that is, persons 16–24 years of age who are neither working nor attending school.
Given the importance of an educated youth to any country’s future, the BLCS conducted a brief analysis re- lated to this phenomenon in The Bahamas.

Survey results showed that 20% of all persons 16–24 years of age were unattached.

Region 1, by virtue of its size, accounted for the majority (60%).
However, this re- gion accounted for about 87% of total youths, meaning that the other regions had more than their share of 77.3 79.7 85.1 UNATTACHED YOUTHS 70.1 74.1 83340_109-130 3/31/05 9:25 PM Page 113 EMPLOYMENT DATA ANALYSIS: TOWARD EQUITABLE PLANNING | 113 TABLE 6-5 Status of Youths 16–24 Years Old Status Student only Employed only Student and working Unattached N All Bahamas 22.8 48.9 8.4 19.9 822 Sex Quintile Region M 21.5 54.6 6.9 17.0 424 F unattached youths.
Table 6-5, which provides more detailed information on these youths, shows that, within regions, the largest proportion of unattached youths was in Region 2 (28%).

It is no surprise that unattached youths were more evident in the poorest quintile (35%) than they were in the wealthiest (12%).

Lack of academic qualifications was likely a major factor contributing to detachment of these youths.
As Table 6-6 shows, 19.4% of all youth had tertiary-level (college/university or technical/vocational) education, compared to only 4% of unattached youths.

Higher rep- resentation of all youths at this level, vis-à-vis that of unattached youths, accounted, in part, for their high- school proportion being lower than that of unattached youths (79% versus 90%).

Although 90% of unattached youths completed high school, 53% had only a School Leaving Certificate (SLC) or no qualification.
Similarly, of the 79% of youths overall who completed high school, 36% had the maximum of an SLC.

The data also highlighted a characteristic well known to policymakers: the educational level and qualification of female youths has surpassed that of male youths.

This was the case for both population sets (total and unattached youths).
These findings point to a key problem in the educa- tional system: Too many of the country’s young people are TABLE 6-6 Educational Status of Total and Unattached Youths, 16–24 Years of Age Status Total Male Female Total Male Female Total youths Unattached youths Education completed No schooling Primary school High school College/university Technical/vocational Educational qualifications SLC or less BJC, CXC Basic 0 Level, CXC General, A level Degree Other N 83340_109-130 3/31/05 9:25 PM Page 114 114 | BAHAMAS LIVING CONDITIONS SURVEY 2001 exiting the system without any qualifications and are thus ill-equipped to participate meaningfully in the workforce (see chapter 5).2 CHILDREN 10–14 YEARS OF AGE In an effort to comply with United Nations Conventions pertaining to the rights and protection of children, the fo- cus on child labour has increased both regionally and in- ternationally (ILO 1973, 1999).3 Recently, The Bahamas participated in a regional child-labour study mounted by the International Labour Office (ILO) in Trinidad.
Such activities led to the decision to collect economic-activity data on children beginning at age 10 to examine the extent of child labour and its potential effect on household well- being.4 The data presented in Table 6-7 suggest that child labour was not widespread in The Bahamas; that is, only 2.4% of children were economically active.

These young- sters accounted for less than 1% of the total labour force.

All of them were employed, and most were from the poor- est quintile.
The Unemployed Quintile and Regional Comparisons Mirroring worldwide patterns, unemployment was high- est amongst females (5.4%), youths (12%), and the poor (11.6% in quintile 1).

Amongst nationalities, Haitians had the highest unemployment rate (8%), compared to 2 Apparently, this is the basic problem for unattached youths; however, other underlying factors are likely at play; hence, the need for further study.
3 The Bahamas, based on its ratification of the ILO Convention on child labour, considers child labour work that is harmful to children’s physical and moral health or development and that prevents them from attending and participating effectively in school and vocational train- ing programmes.

ILO Convention no.
182 (ratified by The Bahamas) lists four cate- gories of the worst forms of child labour: 1) all forms of slavery or prac- tices similar to slavery, such as the sale and trafficking of children, debt bondage and serfdom or forced labour, or compulsory recruitment of children for use in armed conflict; 2) use, procurement, or offering of a child for prostitution or pornography; 3) use or procurement of a child for illicit activities; and 4) work, which by its nature or the cir- cumstances by which it is carried out, is likely to harm the health, safety, and morals of children.
4 The data presented in Table 6-7 should be considered only as a gen- eral outline of the employment status of children 10–14 years of age, as the small numbers captured in the BLCS (18 observations) precluded meaningful analysis.

TABLE 6-7 Labour-force Profile, Persons 10–14 Years of Age Characteristic Total labour force (%) Participation rate Region 1 2, 3, & 4 Quintile 1 2, 3, 4, & 5 N % 0.4 2.4 79.0 21.0 53.0 47.0 18 the national average of 4.6%.
By region, the rate was high- est (6.7%) in Region 2 (Table 6-8).5 Data profiling of the unemployed showed that almost one-quarter were heads of households, 57% were females, and slightly more than one-third were in the poorest quintile (Table 6-9).

5 It should be noted that the unemployment rate was calculated using the labour-force population, not persons 15 years of age and older, as a base.
TABLE 6-8 Unemployment of Persons 15 Years and Older, by Selected Variables Characteristic Total Male Female All Bahamas Age group 15–24 25–64 65 and over Nationality Bahamian Haitian Other Region 1 2 3 & 4 Quintile 1 2 3 4 & 83340_109-130 3/31/05 9:25 PM Page 115 EMPLOYMENT DATA ANALYSIS: TOWARD EQUITABLE PLANNING | 115 TABLE 6-9 Characteristics of Unemployed Persons, Ages 15 Years and Older FIGURE 6-3 Employed Persons, by Region and Poorest and Wealthiest Quintiles Characteristic % unemployed Total no.
Household head Sex Male Female Age group 15–24 25–44 45 and older Region 1 2 3 & 4 Quintile 1 2 3 4 & 5 23.8 43.2 56.8 44.2 45.1 10.7 84.1 14.3 1.6 34.6 29.1 17.3 19.0 N 173 48 82 91 68 84 21 94 67 12 69 46 30 28 EMPLOYMENT CHARACTERISTICS The BLCS showed that 95% of labour-force participants were employed, compared to 93%, recorded in the labour- force survey conducted earlier in 2001.
In terms of quin- t n e c r e P 35 30 25 20 15 10 5 0 30.03 11.37 21.92 19.85 19.99 18.16 28.25 15.48 1 2 3 4 Region Q1 Q5 tiles, persons in the two poorest quintiles had the lowest levels of employment (88% and 92%, respectively).

In the two wealthiest quintiles, the rates were 97% and 99%, re- spectively (Table 6-10).

Region 1 workers enjoyed a more affluent lifestyle than those in other regions (Figure 6-3).
In this region, 11% of workers fell into the poorest quintile, whilst 30% were in the wealthiest.
By contrast, 28% of Region 4 workers were TABLE 6-10 Percentage Distribution of Labour Force of Persons 15 Years and Older, by Selected Variables Employed Unemployed Variable Total Male Female Total Male Female All Bahamas Region 1 2 3 4 Quintile N N Male 1,969 1,022 557 189 201 322 360 368 413 480 — Total 3,677 2,018 973 343 343 633 681 691 767 855 — Female 1,708 996 416 154 142 311 321 323 354 375 — 83340_109-130 3/31/05 9:25 PM Page 116 116 | BAHAMAS LIVING CONDITIONS SURVEY 2001 in the poorest quintile, with a considerably smaller pro- portion (15%) in the wealthiest.
Figure 6-3 clearly illus- trates that disparities amongst employed persons were greatest within these two regions.

In Region 1, the wealth- iest quintile had the larger proportion of employed per- sons; whilst in Region 4, the poorest quintile accounted for the larger share of workers.

The two poorest Region 4 groups represented 50% of workers; this finding con- trasted sharply with Region 1, where the two wealthiest groups accounted for 52% of workers.
Further disparities were noted when one examined the regions’ share of total employed persons by quintile (Table 6-11).

Within the two poorest quintiles, the proportion of Region 1 workers was lower (77% and 85%, respectively) than their share of total workers (86%).

Within the re- maining quintiles, their share of workers was larger than their share of population, peaking at 90% in the wealthi- est quintile.

As living standards increased, so did the share of Region 1 workers.
This was not the case for workers in the other regions; as living standard increased, their pro- portions decreased.

Within the two poorest quintiles, the proportion of workers from Regions 2, 3, and 4 were higher than their share of the total working population; that is, these regions were over-represented in the poorer quintiles.
In addition to substantial disparities in welfare status of employed persons amongst regions, within-region dispar- ities were pronounced in Region 1; however, workers in this region enjoyed a more affluent life style than their counterparts in other regions.

The problem of the work- ing poor outside of Region 1, which were linked to the employment structure in those regions, is a major policy concern.
The sections that follow analyze causes for these disparities, particularly as they relate to education and occupation.

Nationality Bahamians, not surprisingly, comprised 88% of workers nationwide.

Haitians accounted for an additional 6%, equivalent to the percentage for all other nationalities combined.

The Bahamian share of workers was highest in Regions 3 (92%) and 4 (93%), less developed areas gener- ally unattractive to migrants.
Haitians were more visible in Region 2, where they accounted for 10% of employed per- sons (Table 6-12).

As Table 6-13 shows, Bahamians accounted for more than 80% of workers across all quintiles—from 82% in quintile 1, peaking at 90% in quintile 3, and declining slightly to 88% in quintile 5.

“Other” nationalities ap- peared more affluent than either Bahamians or Haitians, as their share of workers increased from 2% in the lowest quintile to 10% in the highest.
Clearly, Haitians were more disadvantaged than other groups, as their propor- tions declined with each rising quintile, from 16% in the lowest to 2% in the highest.

Education Sixty-four percent (64%) of employed persons had a high- school education, 22% had attained a college degree, whilst slightly less than 2% had no schooling.

Despite this relatively high level of attainment, some 30% of employed persons had no form of qualification.
Data clearly indicate that female workers were better educated than their male counterparts; 28% had some college education, compared to 16% for male workers.

Females also surpassed males in academic qualifications; for example, 22% had a General Certificate of Education (GCE), The Bahamas General Certificate of Secondary Education (BGCSE), or similar qualifications; and 17% had a degree.

Proportions for males were 19% and 12%, respectively.
Females enjoyed this advantage in all regions (Tables 6-14 and 6-15).
TABLE 6-11 Quintile Distribution of Employed Persons, by Region Region 1 2 3 4 Total 86.2 9.3 2.0 2.5 1 76.8 14.5 3.1 5.6 2 84.9 9.7 2.2 3.2 Quintile 3 86.8 9.0 1.9 2.2 4 86.8 9.1 2.1 2.0 5 90.3 7.1 1.3 1.3 83340_109-130 3/31/05 9:25 PM Page 117 EMPLOYMENT DATA ANALYSIS: TOWARD EQUITABLE PLANNING | 117 TABLE 6-12 Regional Distribution of Employed Persons 15 Years and Older, by Nationality and Sex Region All Bahamas Total Male Female Region 1 Total Male Female Region 2 Total Male Female Region 3* Total Region 4* Total Bahamian Nationality Haitian 87.8 84.5 91.4 87.9 84.5 91.6 84.3 81.5 88.1 92.2 92.9 6.3 9.9 2.3 6.1 9.9 2.0 9.9 12.7 6.2 3.8 2.7 Other 5.9 5.6 6.3 6.0 5.6 6.4 5.8 5.8 5.7 4.0 4.4 N 3,504 1,887 1,617 1,924 983 941 906 518 388 335 339 * For Regions 3 and 4, observations by sex were too few for meaningful analysis.
Regional Differences Tables 6-15, 6-16, and 6-17 clearly indicate disparities by region and quintile in the educational level of the working population; these were more pronounced at the primary and tertiary levels.

By region, the proportion of workers with education to the primary level was lowest in Region 1 (7%) and highest in Region 2 (21%).
The reverse was observed at the tertiary level, where 28% of Region 1 workers had education to this level, doubling the propor- TABLE 6-13 Quintile Distribution of Employed Persons 15 Years and Older, by Nationality Nationality Quintile Bahamian Haitian Other 81.9 86.8 90.1 89.2 88.4 16.5 10.6 5.5 4.3 1.6 1.7 2.6 4.4 6.5 10.0 N 564 635 661 751 843 TABLE 6-14 Educational Status of Employed Persons 15 Years and Older, by Sex Sex Status Total Male Female Education completed No schooling Primary school High school College/university Technical/vocational N Qualification None SLC BJC, CXC Basic 0 Level, CXC General, A level Degree Other N 83340_109-130 3/31/05 9:25 PM Page 118 118 | BAHAMAS LIVING CONDITIONS SURVEY 2001 TABLE 6-15 Educational Status of Employed Persons, by Sex Within Regions Region 1 Region 2 Region 3 Region 4 Status Total M F Total M F Total M F Total M F Education completed No schooling/primary school High school College/university Technical/vocational N Qualification SLC or less BJC, CXC Basic 0 Level, CXC General, A level Degree/other N 19.4
tion noted in Region 4 (14%).
In all regions, more than 60% of employed persons had a high-school education, the proportion ranging from 60% in Region 2 to 71% in Region 4 (Table 6-15).

Region 1 workers were better qualified than their counterparts in all other regions; 22% had a GCE or its equivalent, and 21% had a degree or other tertiary-level certification.

Region 3 followed, with 15% and 18%, re- spectively.
Workers with either no academic qualification or an SLC were significantly fewer in Region 1 (38%) than in the other regions, peaking at 54% in Region 4 (Table 6-15).

Quintile Comparisons It is well understood that education exerts a powerful in- fluence on labour-force participation, career choice, and ultimately earning capacity.

Data provided in Table 6-16 clearly show that wealthier workers had higher levels of ed- ucation and academic qualifications than poorer ones.
Within the wealthiest quintile, the proportion of workers with a college education was at least 5 times that of persons in quintile 2 and nearly 10 times that of workers in quin- tile 1.

In the latter group, 5% of workers had a college ed- ucation, compared to 48% in the wealthiest group.

At the opposite end of the educational spectrum, workers with ei- ther no schooling or a primary education accounted for l4% in the richest quintile but 17% in the poorest.
Disparities in academic qualifications of employed persons were stark.

A mere 3% of workers in the poorest quintile had a degree or some form of tertiary-level certi- fication, compared to 40% of those in the wealthiest quintile.
Whilst the proportion of persons with tertiary- level degrees or certificates increased with each quintile, the proportion with no academic qualification, including an SLC, decreased with each quintile (from 71% of workers in the poorest quintile to 22% of those in the wealthiest).
The analyses above not only underline the disparities in education amongst the regions and quintiles; they also suggest that too many persons are completing school without any form of qualification, indicating a serious im- balance in the educational system.

The strength of any country’s economy is largely based on the educational prowess of its workforce.

A solid edu- cational background benefits both the individual and his or her country.
Social theory asserts that education is a ma- jor vehicle of social mobility and therefore a major deter- minant of an individual’s well-being.

As a basic guideline, the data in Table 6-17 suggest that, in terms of schooling, an individual needs tertiary-level education in order to move into quintile 5; with regard to qualifications, a de- gree is needed to advance to quintile 5.

These findings point to the need for serious upgrading of the Bahamian educational system.
83340_109-130 3/31/05 9:25 PM Page 119 EMPLOYMENT DATA ANALYSIS: TOWARD EQUITABLE PLANNING | 119 , - 6 E L B A T 3 .

4 5 .

3 4 .

2 2 5 6 .

3 .

4 2 5 9 .

3 4 0 4 .

3 .

8 4 .


8 7 4 7 5 .

3 .

4 5 .

0 0 4 6 7 .

.

7 9 6 .

7 2 2 .

7 6 3 .

2 6 0 .

1 3 6 6 .

.

8 8 6 .

6 4 2 1 .

9 .

2 5 7 .

6 5 1 9 7 .

.

0 2 7 1 .

0 2 .

4 0 1 .

5 7 7 1 .

2 1 .

2 7 1 .

9 6 7 9 5 .

.

0 4 1 .

2 7 7 8 8 .

1 .

5 1 .

2 8 7 .

7 6 .

4 8 1 .

6 8 7 0 .

3 .

8 6 1 .

4 8 7 8 4 .

 .

4 7 1 .

8 6 1 1 .

5 2 .

7 0 4 .

5 6 2 .

8 4 1 .

0 0 2 .


7 8 3 .

2 2 2 .

7 5 1 .

4 2 2 .

7 9 3 .

2 7 2 .

0 2 2 6 .

1 2 .

2 9 2 4 .

3 4 3 .

1 2 .

2 9 1 1 .

6 1 .

6 5 3 6 .

1 2 .

4 0 2 .

4 2 2 5 .

3 3 .

4 0 3 .

2 4 2 8 .

1 1 2 .

3 4 1 .

9 1 3 .

4 2 4 .

3 1 .

5 8 3 .

7 4 2 3 .

4 2 .

6 2 1 .

4 5 4 3 .

3 2 .

2 5 2 1 .

 .

3 6 1 .

8 1 .

9 4 1 2 .

3 5 1 3 .

0 5 5 .

6 0 2 .

8 9 1 6 4 .

.

4 7 6 .

2 9 1 6 9 .

8 .

3 3 .

5 7 .


0 2 1 6 .

1 1 1 .

1 3 .

1 7 .

6 5 1 .

6 0 1 .


5 2 9 9 5 8 5 2 1 7 2 9 2 5 l o o h c s y r a m i r p / g n i l o o h c s o N l a n o i t a c o v / l a c i n h c e t / y t i s r e v i n u / , C J B N l e v e l A , l a r e n e G C X C , l e v e L 0 r e h t o / .
2 6 1 .

9 6 1 .

4 7 1 9 .

3 2 .

5 5 2 8 4 2 1 .

1 1 .

6 7 1 3 .

7 1 0 .

1 3 0 .

3 2 5 2 4 2 .

3 1 3 .

7 1 .

4 7 1 1 .

8 2 1 .

4 2 d e t e l p m o c n o i t a c u d E / , - 6 E L B A T 6 5 9 8 3 3 .

6 9 1 .

4 7 4 .

7 9 1 .

6 9 2 .

2 2 2 .

8 4 1 .

0 2 2 7 5 .

.

5 6 1 6 2 .

5 2 2 1 9 2 3 .

9 2 2 3 .

9 5 .

8 2 2 5 .

1 2 .

5 0 2 .

8 2 1 .

8 9 1 6 4 .


.

0 4 1 8 .

1 1 8 1 , 2 7 6 6 4 .

1 2 1 .

3 5 4 .

1 2 .

7 5 2 2 .

1 2 8 .

3 1 2 5 .

.

8 0 2 1 .

5 1 2 2 .

1 9 5 9 3 3 0 1 3 1 0 3 .

6 4 1 6 .

1 2 .

2 2 3 .

7 2 5 .

0 8 1 .

5 2 2 9 .

1 2 .

9 9 2 .

5 9 1 1 .

7 2 5 .

1 2 .

6 0 1 3 .

2 2 .

5 7 1 .

9 8 1 6 4 .

.

6 5 2 2 .

1 1 5 5 .

2 2 .

1 8 8 0 3 3 5 7 2 8 8 2 .

4 7 1 .

4 5 2 7 .

1 3 .

8 2 6 4 .

1 2 .

6 7 2 0 .

3 2 .

6 9 1 .

2 8 1 1 .

1 2 .

7 4 2 9 .

3 1 7 .

3 2 .


8 7 1 4 .

3 1 0 .

3 3 .

9 1 1 .

8 2 7 .

.

7 0 2 7 4 , 1 9 6 6 5 8 5 9 8 5 .

2 6 1 4 .

3 2 .

0 2 3 .

5 7 5 .

0 0 2 .

8 4 2 .

4 2 2 .

0 5 2 .

7 8 1 .

4 4 2 0 .

3 2 1 .

2 1 1 .

3 2 .

6 7 1 3 .

6 1 8 .

3 9 .

1 2 8 9 .

3 .

6 5 .


1 l a n o i t a c o v / l a c i n h c e t / y t i s r e v i n u / , C J B l e v e l A , l a r e n e g C X C , l e v e l 0 r e h t o / e e r g e D l o o h c s y r a m i r P 83340_109-130 3/31/05 9:25 PM Page 120 120 | BAHAMAS LIVING CONDITIONS SURVEY 2001 EMPLOYMENT STATUS Nearly 62% of the workforce were engaged in the private sector, 21% in Government, and 17% were self-em- ployed.
Almost equal proportions of males (61%) and fe- males (63%) were employed in the private sector.

About 24% of females depended on the Government for their employment, whilst 12% were self-employed.

In the case of males, 22% were self-employed, whilst 17% were em- ployed by the Government (Tables 6-18 and 6-19).

Regional Differences As Table 6-18 highlights, type of employment varied by region.
In the urbanized, developed area of New Provi- dence and Grand Bahama (Region 1), 64% of workers were private employees.

In the less developed regions of Exuma and Long Island (Region 3) and Other Family Is- lands (Region 4), the percentage of private employees, though the largest group, was substantially smaller (less than 50%).

In these regions, self-employed persons ac- counted for nearly 33% of workers; a larger share than that of Government employees.
Interestingly, the combination of self-employed persons and Government employees out- numbered private employees.

This finding reflects the ab- sence of a corporate sector, which is heavily concentrated in Region 1.

As mentioned earlier, self-employment in Re- gions 3 and 4 tends to consist of small-scale businesses and other informal-sector activities.

Moreover, in Regions 2, 3, and 4, females relied on Government employment far more than did males.
This phenomenon was most pronounced in Region 4, where 39% of female workers versus 18% of male workers, were Government employees.

Quintile Comparisons Workers in the lowest quintiles (1 and 2) depended more heavily on private-sector employment than those in the higher quintiles; this dependency ranged from 71% in quintile 1 to 53% in quintile 5.
Persons in the latter quin- tile were more equally distributed throughout the employ- ment groups; 53% were private employees, and an almost equal share were self-employed (24%) or Government- employed (22%).
When self-employment was examined more closely it was noted that the proportion of persons varied little within the three lowest quintiles; however above quintile 3, the proportion jumped by 4 percentage points and again by 7 percentage points to quintile 5, suggesting two distinct groups of self-employed persons: a poorer group (quintiles 1, 2, and 3) and a wealthier group (quintiles 4 and 5).
One possible explanation is that poor self-employed persons were likely engaged in informal-sector activities, whilst the work of wealthier self-employed persons was more formal- ized.

Data in Table 6-19 lends support to this suggestion; for example, within the poorer quintiles, the majority of self-employed persons were craft workers (29%), service and sales workers (27%), and agricultural workers (14%).
In the two wealthier quintiles, they were craft workers (26%), managers (21%), and professionals (16%).

When a sex perspective is added to the analysis of self- employment, the Survey found that self-employed males enjoyed a standard of living that far exceeded that of their female counterparts (Table 6-18).

Within the poorest quintile, self-employed females, as a proportion of total female workers, accounted for 12%; in the wealthiest quintile, the proportion was slightly higher, at 15%.
The proportion of self-employed males was 11% in the poor- est quintile; however, their share in the wealthiest quintile was substantially higher, at 32%.

Females accounted for approximately 34% of the total self-employed persons, however they represented 39% of the self-employed in the three poorer quintiles and only 29% in the two two wealthier quintiles.

The data further showed that 45% of poorer, self-employed females were service and sales work- ers (Table 2-19).
EMPLOYED PERSONS BY INDUSTRY Some 30% of employed persons were engaged in commu- nity, social, and personal services.

This group not only comprised the largest industrial group; it was also the largest employer of women (40%).

For men, the largest proportion (28%) worked in construction, the second largest industry, which accounted for 15% of all workers (Table 6-20).
Regional Differences Across all regions, a minimum of 25% of workers was en- gaged in “community, social, and personal services.” Vari- ation in industrial distribution across regions was largely confined to two industries: 1) “agriculture, hunting, forestry, and fishing” and 2) “financing, insurance, real es- tate, and other business services.” Predictably, a signifi- cantly larger proportion of workers in Region 1—the 83340_109-130 3/31/05 9:25 PM Page 121 , - 6 E L B A T EMPLOYMENT DATA ANALYSIS: TOWARD EQUITABLE PLANNING | 121 .
9 5 3 4 .

3 2 5 .

1 9 3 1 F .

6 5 2 .

4 7 5 .

5 4 1 4 2 .

7 6 3 F M l a t o T F .

2 9 3 .

4 8 1 .

9 6 2 2 .

1 3 1 .

3 4 .

6 8 3 0 0 .

9 9 1 1 .

0 4 .

4 2 3 .

6 0 8 3 3 1 .

7 4 .

4 0 2 4 .

1 3 4 1 M 3 .

2 1 .

0 8 4 .

6 7 3 2 2 .

5 8 1 l a t o T F .

6 0 2 .

8 4 2 .

6 7 4 1 .

0 3 8 .

1 8 2 3 3 .

1 5 .

0 2 2 9 .

1 0 8 3 M 4 .

3 1 3 .

2 5 3 .

3 3 0 2 .

2 1 5 l a t o T F M l a t o T .

2 8 1 9 .

3 2 .

8 7 1 .

8 0 2 9 .

1 5 .

5 8 2 4 .

1 .

9 4 6 .

2 0 1 0 .

1 0 .

3 6 .


2 9 1 0 0 .

9 .

3 6 .

8 4 1 .

5 0 .

4 4 2 .

8 2 6 7 .

1 1 1 .

1 F .

2 7 1 0 .

1 6 6 .

1 2 1 .

0 .

7 0 2 9 .

1 6 .

8 6 1 .

6 0 / .

t v o G - e e y o l p m E .

p r o c .


t v o G e t a v i r p - e e y o l p m E d e y o l p m e - , 1 0 0 6 , 1 6 6 8 , 1 6 6 4 , .

5 9 1 .

2 8 4 1 .

2 3 .

2 0 1 7 4 l a t o T F M l a t o T F M l a t o T F .

4 2 2 .

2 6 2 .

6 9 1 .

8 2 2 .

6 7 2 .

6 8 1 .

5 2 5 8 .

3 2 3 .

1 8 3 8 0 .

3 6 1 .

0 1 .


7 0 1 4 3 .

5 6 5 8 .

3 2 1 .

0 .

6 9 5 3 .

7 1 .

4 0 5 0 4 6 4 7 .

2 0 6 1 .

2 1 1 .

0 0 1 3 .

4 6 6 .

8 4 1 .

2 0 5 4 3 1 .

3 2 3 .

3 6 5 .

3 1 1 .

0 .

4 7 1 4 .

3 7 3 .

8 .

9 0 5 5 6 5 9 2 M .

0 2 1 0 .

1 7 .

9 6 1 1 .

0 1 3 3 .

6 4 1 1 .

2 7 .

8 2 1 .

5 0 l a t o T .

7 2 2 .

6 4 6 3 .

2 1 .

4 0 F .

0 2 1 .

5 7 7 .

5 0 1 0 0 .

.

2 7 1 2 .

1 7 4 .

1 1 .

2 0 / .

t v o G - e e y o l p m E .

p r o c .


t v o G e t a v i r p - e e y o l p m E d e y o l p m e - 83340_109-130 3/31/05 9:25 PM Page 122 122 | BAHAMAS LIVING CONDITIONS SURVEY 2001 e l a m e F .

5 5 2 .

5 9 1 .

4 0 .

9 5 3 3 .

1 0 9 .

9 2 .

5 5 .

6 9 5 & 4 e l a M .

5 9 1 .

0 4 1 .

7 0 9 6 .

.

4 8 7 .

3 3 .

0 2 1 8 4 .


1 3 2 e l i t n i u Q 3 & , 2 , 1 n o i g e R l a t o T e l a m e F e l a M l a t o T 4 & 3 3 .

1 2 .

6 5 1 .

6 0 .

4 5 1 3 .

6 .

5 6 2 3 .

9 0 5 .

7 2 3 .

9 2 1 3 .

3 1 3 .

0 .

6 4 4 8 .

1 .

7 5 1 0 .

3 .

4 8 5 0 1 3 .

5 6 5 .

0 0 .

0 .

3 1 0 .

3 2 .

7 8 3 .

5 4 9 9 .

2 6 1 .

6 8 0 9 .

1 .

0 .

8 6 2 8 .

3 1 .

6 8 2 8 .

3 3 .

9 7 6 2 4 .

1 1 8 2 .

2 .

1 .

6 9 1 .

7 7 2 .

8 6 2 8 2 .

7 7 .

7 6 1 2 .

7 9 1 8 6 .

.


5 0 9 .

3 1 .

9 7 2 .

0 0 2 0 6 .

3 .

5 8 9 1 1 .

6 6 1 .

5 5 1 .

4 0 .

6 0 2 5 .

3 .

5 8 2 3 .

8 .

7 6 4 3 2 l a t o T n o i t a p u c c o y r a m i r P .

6 6 1 2 .

3 1 .

4 0 .

5 9 1 1 .

9 1 .

7 2 .

5 7 6 6 .
9 9 5 l a n o i s s e f o r p e t a i c o s s a & s r e g a n a m & , s l a i c i f f o , s n a i c i n h c e t , s a n o i s s e f o r P i r o n e s , & & & N & & , s n o s r e P d e y o l p m e - - 6 E L B A T 83340_109-130 3/31/05 9:25 PM Page 123 EMPLOYMENT DATA ANALYSIS: TOWARD EQUITABLE PLANNING | 123 TABLE 6-20 Primary Industry of Employed Persons, by Sex Primary industry Total Male Female Male Female Sex Sex distribution Agriculture, hunting, forestry, & fishing Mining, quarrying, electricity, gas & water Manufacturing Construction Wholesale & retail Hotels & restaurants Transport, storage & communication Financing, insurance, real estate & other business services Community, social & personal services N — 12.4 16.1 43.6 5.7 55.9 62.7 30.0 60.0 63.2 — N 252 26 138 564 496 525 213 270 1,006 — country’s major business centre—was engaged in “financ- ing, insurance, real estate, and
 other business services” (12%), a sharp contrast to less than 2% of Region 4 work- ers so engaged.
With regard to “agriculture, hunting, forestry, and fishing,” significantly larger employed shares were found in the other regions.

For example, this indus- try category accounted for only 2% of employed persons in Region 1, compared to 15% of those employed in Re- gion 2 (Table 6-21).

EMPLOYED PERSONS BY OCCUPATION About 20% of all workers were “service workers & shop and market sales workers;” this was the main occupational group for women (26%) and the second largest for men (15%).
“Elementary occupations” (e.g., maids or labour- ers) was the third largest occupational group and was also third for both males and females.

Indeed, it was the only group in which males and females were almost equally rep- resented (Table 6-22).

Quintile Comparisons Industrial grouping was not significant as a determinant of economic differences, as the pattern was similar for most consumption quintiles.
This is an expected finding, given that industries usually engage a wide spectrum of occupations; these, not the industry itself, affect the well- being of workers.

Nonetheless, slight differences were found.

For example, 16% of persons in the highest quin- tile worked in “financing and business” compared to 5% in the lowest quintile; while 19% of those in the lowest quintile worked in “construction,” compared to 13% of those in the highest.
Regional Differences “Skilled agricultural & fishery workers” was the smallest occupational group; however, in this group, differences between Region 1 and the other three regions were appar- ent.

In Region 1, only 2% of workers performed in this ca- pacity, whilst at least 12% did so in all other regions (Table 6-23).
In Region 2–by far the country’s most agrarian region–13% of employed persons worked in the “skilled agricultural & fishery workers” category; additionally, Re- gion 2 accounted for 35% of total workers in this category.
Thus, this category was over-represented in Region 2, where 83340_109-130 3/31/05 9:25 PM Page 124 124 | BAHAMAS LIVING CONDITIONS SURVEY 2001 TABLE 6-21 Primary Industry of Employed Persons, within Region and Quintile Primary industry Total 1 Region Quintile Agriculture, hunting, forestry, & fishing Mining, quarrying, electricity, gas, & water Manufacturing Construction Wholesale & retail Hotels & restaurants Transport, storage, & communication Financing, insurance, real estate, & other business services Community, social, & personal services 30.2 30.7 28.2 24.6 25.8 29.4 28.0 33.9 32.0 27.7 N 3,490 1,918 901 332 339 559 634 659 749 841 TABLE 6-22 Primary Occupation of Employed Persons, by Sex Primary occupation Total Male Female Male Female Sex distribution Legislators, senior officials, & managers Professionals Technicians & associated professionals Clerks Service workers & shop and market sales workers Skilled agricultural and fishery workers Craft & related trade workers Plant & machine operators & assemblers Elementary occupations N 8.6 9.6 11.3 10.9 20.3 3.5 16.6 4.9 14.4 3,485 9.6 7.9 8.3 2.7 14.8 6.2 28.5 8.4 13.6 1,878 7.4 11.4 14.6 19.9
 26.3 0.5 3.6 1.0 15.2 1,607 58.7 42.9 38.2 12.7 38.1 93.6 89.5 89.7 49.5 — 41.3 57.1 61.8 87.3 61.9 6.4 10.5 10.3 50.5 — N 282 278 316 358 676 232 593 169 581 — 83340_109-130 3/31/05 9:25 PM Page 125 EMPLOYMENT DATA ANALYSIS: TOWARD EQUITABLE PLANNING | 125 TABLE 6-23 Primary Occupation of Employed Persons, by Region and Quintile Primary occupation Total Legislators, senior officials, & managers Professionals Technicians & associate professionals Clerks Service workers & shop and market sales workers Skilled
 agricultural & fishery workers Craft & related trade workers Plant & machine operators & assemblers Elementary occupations N 8.6 9.6 11.3 10.9 20.3 3.5 16.6 4.9 14.4 3,485 1 8.6 10.1 12.3 11.2 20.8 2.0 16.5 4.9 13.6 1,916 Region Quintile the total number of employed persons accounted for only 9% of the nation’s workers.
By contrast, Region 1, embrac- ing 86% of total workers, accounted for only 49% of the “skilled agricultural & fishery workers” category.

However, Region 1 clearly dominated in occupations associated with more developed, urban centres; for example, “technicians & associated professionals” accounted for 93% of total work- ers in this group.

Within this region, the proportion of workers who fell into this category was twice that of any of the other regions (Tables 6-23 and 6-24).
TABLE 6-24 Primary Occupation of Employed Persons, Across Regions and Quintiles Region Quintile Primary occupation 1 2 Legislators, senior officials, & managers Professionals Technicians & associate professionals Clerks Service workers & shop and market sales workers Skilled agricultural & fishery workers Craft & related trade workers Plant & machine operators & assemblers Elementary occupations N N 282 278 316 358 676 232 593 169 581 83340_109-130 3/31/05 9:25 PM Page 126 126 | BAHAMAS LIVING CONDITIONS SURVEY 2001 Quintile Comparisons As Tables 6-23 and 6-24 suggest, stark occupational dis- parities by quintile were found.
Persons from the poorest quintile were more likely to be employed as “elementary workers” (36%) or “service workers & shop and market sales workers” (21%).

Few worked as “legislators, senior officials, & managers” (3%) or “professionals” (1%)— occupations associated with lucrative financial opportuni- ties and more affluent life styles.

By contrast, a significant proportion of persons from the wealthiest quintile were “legislators, senior officials, & managers” (19%) or “pro- fessionals” (18%).
They were less likely to be “elementary workers” (7%), although a fair proportion was “service workers & shop and market sales workers” (16%).

These disparities are further crystallized, upon further examina- tion of the data, which shows that employed persons in the highest quintile accounted for 63% of all “legislators, senior officials, & managers” (Table 6-24).
The propor- tion of this category in quintile 5 far exceeded that of any other consumption quintile (it tripled the proportion in quintile 4 and eclipsed the 4% found in quintile 1).

MODE OF TRANSPORT Most workers (73%) traveled to their respective jobs in private vehicles (Table 6-25).

Substantial disparities by re- gion and quintile were found in the mode of transport used to commute to work.
Use of a private vehicle was far more prevalent in the more developed area of New Providence and Grand Bahama (74%).

In the more rural Region 4, the proportion using private vehicles was considerably less (49%).

The share of workers who cycled or walked was significantly larger in Region 4 (29%)— nearly six times that of Region 1 (5%) (see chapter 7).

The second most common method of worker transport was the jitney.

This bus system, confined mainly to Re- gion 1, was used by 11% of workers in that area.
With regard to consumption expenditure quintile, use of private vehicles to commute to work was well above the national average in the two wealthiest groups (82% in each group).

The proportion was substantially lower in the poorest quintile (49%), which relied more heavily on the jitney (23%).

Only 5% of workers in the wealthiest quin- tile used the jitney.

TIME SPENT EN ROUTE The vast majority of Bahamian workers (85%) reached their workplace within half an hour.
For workers that re- quired more than half an hour, the proportion was high- est in Region 1 (15%) and lowest in Region 4 (6%).
Re- gion 1 was heavily weighted by the small island of New TABLE 6-25 Transport Method and Time for Employed Persons 15 Years and Older, by Region and Quintile Transport method or time traveled All Bahamas Region Quintile 1 2 3 4 Mode of transport Walk/bicycle Private vehicle Jitney Taxi/private bus Boat/ferry None needed N Minutes traveled to activity 0–10 11–30 31–60 61 or more N 83340_109-130 3/31/05 9:25 PM Page 127 EMPLOYMENT DATA ANALYSIS: TOWARD EQUITABLE PLANNING | 127 Providence, where the amount of time taken to reach work was more likely associated with traffic congestion than dis- tance.
The situation was likely reversed outside Region 1 (Table 6-25).

TABLE 6-26 Mean Weekly Hours in Primary Activity, by Selected Demographic Characteristics Characteristic Total Male Female HOURS WORKED Employed persons worked an average of 43 hours per week.

Across all regions and quintiles, males worked longer days than did females, with averages of 46 and 41 hours, respectively.
Younger persons (15–24 year-olds) and the elderly (persons 65 years and older) worked fewer hours than did all other age groups.

In Region 3, more than any other region, employees worked longer days (47); whilst the shortest work days (41) were found in Region 4.

The average hours worked was directly related to the well-being of individuals; per- sons in the poorest quintile worked an average of 40 hours, whilst those in the wealthiest quintile worked 45.
Those engaged in “elementary occupations,” associated with the poorest quintile, worked 39 hours; by contrast, those em- ployed as “legislators, senior officials, & managers,” asso- ciated with the highest quintile, worked an average of 52 hours per week (Tables 6-26 and 6-27).

CONCLUSIONS AND POLICY IMPLICATIONS The picture that emerges from this analysis is a country of extreme worker inequalities, both across and within re- gions.
Because of Region 1’s economic structure, the so- cioeconomic status of its workers outstripped that of all other regions.

Clearly, Region 1 workers’ level of educa- tion and academic qualifications require improvement; nonetheless, they still surpassed those of the other regions.

The level and type of labour-force participation of Region 1 workers also surpassed those of the other regions.
This resulted directly from the large economies of scale enjoyed in Region 1: banking, industrial centre, and seat of Government.

Ironically, although Region 1 workers were generally better off than those in the other regions, in- equalities within the Region were more extreme.

The other three regions, characterized by small economies of scale, were more rural.

Self-employment fea- tured prominently amongst most workers in the lower consumption quintiles.
Many were engaged in informal activities, including subsistence farming and fishing.

A sig- nificant proportion had a high-school education but lacked academic qualification or training.
Many others All individuals Household head Region 1 2 3 4 Quintile Age group 15–24 25–44 45–64 65 and older Education completed No schooling Primary school High school College/university Technical/vocational were engaged in various “elementary occupations,” which accounted for as much as 24% of employment (Region 4).
With regard to overall living standard, low levels of aca- demic achievement typified workers in the two lowest quintiles.

In general, they were unskilled workers engaged as “elementary workers” or “service workers”.

Their rate of participation was lower than workers in the other quin- tiles; however, their unemployment rate was higher.

A sig- nificant proportion walked to work or used the jitney.
To safeguard the jobs of poorer workers and to continue to service others in the community, policymakers must en- sure that a well-organized, accessible transportation system is provided and maintained.

Thus, these workers’ heavy reliance on the jitney is an issue that planners must seri- ously address.

Workers in quintiles 4 and 5 had the lowest unem- ployment rates, whilst their level and nature of participa- tion in the labour force were higher.
These quintiles had the majority of “legislators, senior officials, & managers,” 83340_109-130 3/31/05 9:25 PM Page 128 128 | BAHAMAS LIVING CONDITIONS SURVEY 2001 TABLE 6-27 Mean Weekly Hours in Primary Occupation and Industry, by Sex Occupation or industry Total Male Female Primary Occupation Legislator, senior officials, & managers Professionals Technicians & associate professionals Clerks Service workers & shop and market sales workers Skilled agricultural & fishery workers Craft & related trade workers Plant & machine operators & assemblers Elementary occupations Primary Industry Agriculture, hunting, forestry, & fishing Mining, quarrying, & electricity, gas, & water Manufacturing Construction Wholesale & retail Hotels & restaurants Transport, storage, & communication Financing, insurance, real estate, & other business services Community, social, & personal services N as well as “professionals.” By a wide margin, they were bet- ter educated than workers in the other groups.
They worked longer hours, and the vast majority traveled to work in private vehicles.

Quintile 3, the middle group, to varying degrees, exhibited characteristics found in the higher and lower quintiles.
The underlying thrust of the Employment Act 2001 was that workers throughout the country were entitled to equal employment opportunity and treatment.6 As BLCS data indicate, this goal remains far from being realized; it will be difficult, if not impossible, to accomplish in the ab- sence of sustainable economic growth and investment, particularly in areas outside Region 1.
As Survey results show, employment opportunities in Regions 2, 3, and 4 are more limited; hence, the pressing need to equip workers to capitalize on existing opportuni- 6 The Employment Act 2001 established standardized provisions for employees, including minimum number of working hours, wages, and child employment (DOL 2001).

ties and prepare for future ones.


Self-employment in these regions is largely subsistence level; thus, capacities must be strengthened, and workers must be equipped to create employment.

Small-scale farmers, fishermen, and en- trepreneurs, with special emphasis on females, require in- creased technical and financial support to improve their productivity.

A range of initiatives—ongoing training, marketing strategies, and greater accessibility to credit— must be intensified.
The major thrust of all initiatives must be improving workers’ educational level, as education is perhaps the ma- jor vehicle for empowerment.

The BLCS demonstrates the serious imbalance in the Bahamian educational system; to reiterate, too many people are completing school without any qualification.
BLCS data convincingly show that edu- cational attainment of the working population has not yet reached acceptable levels; the data further illustrate that education to the tertiary level is needed to move into the highest quintile.

Therefore, actions should be directed to- ward ensuring that tertiary-level education is accessible 83340_109-130 3/31/05 9:25 PM Page 129 EMPLOYMENT DATA ANALYSIS: TOWARD EQUITABLE PLANNING | 129 and affordable to all.
Special emphasis must be placed on expanding educational and training opportunities outside Region 1 through distance education and related initia- tives (see chapter 5).

In this process, consideration should be given to tailoring the educational programme to meet- ing the unique needs of these communities.

There is a def- inite need for further research in this area.
Finally, the above-cited initiatives are likely to affect unattached youths, who represent 20% of all youths; of this percentage, 26% are from the poorest quintile.

Clearly, these statistics have implications for urgent policy action; nonetheless, the phenomenon of unattached youths must also be treated as a special project requiring further study.

REFERENCES DOL.

2001.

The Employment Act 2001.

Nassau: Department of Labour.

_______.

annual.

Labour Force and Household Income Report.


Nassau: Department of Statistics, Ministry of Finance.

ILO.

1973.

Convention no.

138.

Minimum Age for Admission to Employment.

Geneva: International Labour Orga- nization.

_______.

1999.

Convention no.

182.

Elements of the Worst Form of Child Labour.

Geneva: International Labour Organization.

FOR FURTHER READING DOS.

1996.

Commonwealth of the Bahamas: Report of the 1990 Census of Population and Housing.
Nassau: Department of Statistics, Ministry of Economic Development.

ECLAC.

1992.

Education and Knowledge: Basic Pillars of Chang- ing Production Patterns with Social Equity.

Santiago: Economic Commission for Latin America and the Caribbean.

DOS.

2002.

Commonwealth of the Bahamas: Report of the 2000 Census of Population and Housing.

Nassau: Department of Statistics, Ministry of Economic Development.

ILO.

1990.
ILO.

1990.

Surveys of Economically Active Population, Employ- ment, Unemployment, and Underemployment: An ILO Manual on Concepts and Methods.

Geneva: Interna- tional Labour Organization, Bureau of Statistics.

83340_109-130 3/31/05 9:25 PM Page 130 83340_131-154 3/31/05 9:28 PM Page 131 CHAPTER 7 Community Services and Social Programmes: Accessibility Analysis William J.
Fielding, Jessica Minnis, and Susan J. Plumridge B ecause The Bahamas is an archipelago, it is difficult to develop community ser- vices and social programmes to serve ev- eryone.

Uneven distribution of population and transportation—within and between islands— exacerbates the difficulty.

Across the four re- gions, average population density varies from 423 persons per square mile (sq.

mi.)
mi.)

in New Providence and Grand Bahama; to 22.3 in Ex- uma and Long island; to 9.1 in Abaco, Andros, and Eleuthera;1 to only 7.8 in other Family Is- lands.

Ragged Island’s population of 72 is only about .034% that of New Providence, whose population numbers 210,832.2 In terms of trans- portation infrastructure, Andros has only 0.034 miles (mi.)

of main road per sq.

mi., compared to 8.75 for New Providence.


Despite such disparities, residents of all islands have similar expectations with regard to access to 1 Excluding Andros, Abaco and Eleuthera have an average population density of 24.9 persons per sq.

mi.

(Andros has an average of only 3.3).

2 2000 estimate.

community services and social programmes.


Thus, the challenge for policymakers is this: How can the Commonwealth’s resources be used most equitably and efficiently to ensure broadest access by communities and avoid marginalizing any par- ticular ones.

This chapter seeks to answer this question by analysing accessibility–defined in terms of both availability and affordability of ser- vices and programmes—by households in each consumption group and region.
ACCESS TO COMMUNITY SERVICES Given the distance between the Family Islands and the two most developed and populated centres—New Providence and Grand Bahama— it is reasonable to expect that families who live in sparsely populated areas, particularly on the smaller Family Islands, will pay more to access community services.3 The high cost of travel to community services centres puts Family 3 For example, Inagua is about 350 mi.

from New Providence.


131 83340_131-154 3/31/05 9:28 PM Page 132 132 | BAHAMAS LIVING CONDITIONS SURVEY 2001 BOX 7-1 Making the Case for Equitable Access: Hospital Facilities Islanders at a disadvantage and means that poorer house- holds may be deprived access to services (Box 7-1).

To date, The Government of the Bahamas has built hospitals on only the two most populated islands—New Providence and Grand Bahama— and clinics on other islands.
Whilst such a strategy permits the most cost-effective expenditure of public money, it adds to the financial burden of Family Island residents, who must use more ex- pensive air or sea transport to access hospital care.

In emergency cases, it may even prevent access to timely care.

Notably, more than twice as many lower-expenditure residents (26%) as higher- expenditure ones (12%) must travel over water to reach a hospital.
However, since Family Island populations have declined in recent years, provid- ing facilities on those islands may be difficult to justify.

Household Access: Distance to Nearest Facility Survey data collected on access to community services re- ferred to the facility nearest the household, not necessarily the facility a household elected to use.
Some households might have been considered disadvantaged if they had to use the nearest—but not what they perceived as the best— facility and thus had less choice than other households (see Appendix; Tables 7-A1, 7-A5, 7-A9, 7-A13, and 7-A17).

The study found that, overall, more than 80% of households were located within two miles of food mar- ket/grocery stores, Government administration com- plexes, health clinics/doctors’ offices, police stations, post offices, and primary schools.
This proximity reflects 1) the small size of the islands and 2) that clinics and other facil- ities are spread throughout the islands.

Only with regard to access to banking facilities, hospitals, and secondary schools were there consistent regional differences.

Exuma and Long Island residents generally had farther to travel to reach many facilities (Table 7-1).

Few clear differences are associated with household ex- penditures.
That the highest-expenditure households must TABLE 7-1 Median Household Distance to Facilities, by Region Facility type Bank/banking services facility Food market/grocery store Govt.

admin.

complex Health clinic/doctor’s office Hospital Mail boat3 Police station Post office Primary school Secondary school Bahamas overall 1.6 0.8 4.8 1.0 6.7 6.8 1.4 1.6 1.0 1.6 1 1.6 0.8 6.01 1.0 5.7 6.9 1.4 1.6 1.0 1.5 1 Refers to Grand Bahama only.

2 On another island.


3 Provides freight and passenger service throughout the archipelago.

Median distance (mi.)

Region 2 1.7 0.6 1.5 0.9 OAI2 4.3 1.5 1.0 1.0 4.5 3 7.1 0.9 7.8 1.3 OAI2 9.8 5.1 1.9 1.5 6.8 4 5.8 0.7 1.4 1.5 OAI2 3.8 1.2 1.2 1.0 1.4 83340_131-154 3/31/05 9:28 PM Page 133 COMMUNITY SERVICES AND SOCIAL PROGRAMMES: ACCESSIBILITY ANALYSIS 133 | TABLE 7-2 Median Distance to Facilities, by Quintile Median distance (mi.)
Quintile Facility type Bank/banking services Food market/grocery store Govt.

admin.
Complex Health clinic/Doctor’s office Hospital Mail boat* Police station Post office Primary school Secondary school * See definition in Table 7-1. travel the farthest median distance to access Government administration complexes probably reflects the choice of higher-expenditure New Providence and Grand Bahama residents to live on the outskirts of town (Table 7-2).
Overall, 95% of households were within 10 miles of a secondary school.

Of the four regions, only Region 2 (Abaco, Andros, and Eleuthera) had access to a school on another island (3.4% of households).

Moreover, students in poorer households were more likely than wealthier stu- dents to travel more than 10 miles to school.
Similarly, 95% of households were within 10 miles of a banking facility.4 In Exuma and Long Island (Region 3) and Other Family Islands (Region 4), formal banking fa- cilities were limited but not completely inaccessible, even if bank buildings were lacking; in Region 3, 38% of house- holds had to travel more than 10 miles to reach a banking facility.

Transport to Nearest Facility The car was the most popular mode of transport and own- ership was widespread.
Nearly 73% of all Bahamian households owned motor vehicles, ranging from more 4 The term banking facility can refer to a physical bank that offers a full range of services or places that allow money to be deposited and with- drawn from accounts or cheques cashed.

than 39% of the lowest-expenditure households to more than 84% of the highest-expenditure ones (Table 7-3).
Outside New Providence and Grand Bahama (Region 1), where public transport was less available, transport poverty may have been higher (see Appendix; Tables 7-A2, 7A6, 7-A10, 7-A14, and 7-A18).

General bus services were limited to New Providence and Grand Bahama (except for school buses), whilst taxis were available across all islands.
Thus, use of public trans- port was greater in New Providence and Grand Bahama, except for accessing hospitals—overall, 66% of house- holds used a car to access hospital facilities; however, marked inter-island differences resulted from location of facilities limited to New Providence and Grand Bahama.

On other islands, walking was more prevalent, which may have reflected lower levels of car ownership and lack of public transport.
Tables 7-4A and B, respectively, show the percentage of households who walked or used public transport to ac- cess facilities, by region and quintile.

Walking and bus travel were more common in low-expenditure groups (high-expenditure households, who had the highest levels of car ownership, used cars the most; low-expenditure households used them the least).

Taxis were little used, but slightly more by lower-expenditure groups.
Households from all groups used public transport to access hospitals; this resulted from the need for residents from islands other than New Providence and Grand Bahama to travel over water to reach hospitals on these two islands.
TABLE 7-3 Household Ownership of Cars, by Region and Quintile Region or quintile % households Region 1 2 3 4 All Bahamas Quintile 74.94 59.33 61.58 52.94 72.55 39.45 61.21 72.73 79.83 84.27 83340_131-154 3/31/05 9:28 PM Page 134 134 | BAHAMAS LIVING CONDITIONS SURVEY 2001 TABLE 7-4A Households’ Mode of Transport (%) To Access Facilities, by Region Facility type Bank/bank services facility Food market/grocery store Gov’t.

admin.
admin.

complex Health clinic/doctor’s office Hospital Mail boat3 Police station Post office Primary school Secondary school All Bahamas 12 22 12 15 4 4 12 11 20 13 Walking Region Public transport1 Region All Bahamas 10 6 10 10 30 17 10 13 7 12 1 Includes jitney/bus; taxi; and boat, airplane, and other.
2 Refers to Grand Bahama only.

3 See definition in Table 7-1.

TABLE 7-4B Households’ Mode of Transport (%) To Access Facilities, by Quintile Facility type Bank/bank services facility Food market/grocery store Gov’t.

admin.
admin.

complex2 Health clinic/doctor’s office Hospital Primary school Police station Post office Primary school Secondary school 1 32 51 29 37 7 48 27 23 48 28 Walking Quintile 3 11 23 15 17 3 23 15 13 23 15 2 15 38 17 25 6 34 20 17 34 24 Public transport1 Quintile Includes jitney/bus; taxi; and boat, airplane, and other.
2 Excludes New Providence.

4 1 1 2 6 100 5 1 1 3 6 5 5 3 8 4 17 4 4 5 4 6 83340_131-154 3/31/05 9:28 PM Page 135 COMMUNITY SERVICES AND SOCIAL PROGRAMMES: ACCESSIBILITY ANALYSIS 135 | Cost of Travel to Facility Data on cost of travel were collected only for those house- holds that did not own the mode of transport (usually car or motorcycle) used; thus, these costs referred only to the use of public transport or immediate, out-of-pocket travel expenses.
Table 7-5 reflects access to private transport (generally motor vehicles) and the lack of bus services out- side of New Providence and Grand Bahama.

Further, in those islands without buses, more expensive public trans- port modes must be used.

The net effect of these factors was that households outside of New Providence and Grand Bahama needed to spend more to access facilities than did households on New Providence and Grand Ba- hama.
This, combined with the lower household expendi- ture groups on Family Islands, made travel proportion- ately more expensive for these households.

Overall, transport costs in Exuma and Long Island were probably the most expensive in The Bahamas (see Appendix; Tables 7A-3, 7A-7, 7A-11, 7A-15, and 7A-19).

Notably, two recurring activities—grocery shopping and going to primary school—were relatively expensive journeys.
These costs probably reflected the use of public transport, instead of private (car) or pedestrian modes of transport, for the bulk of the population, which resided in New Providence and Grand Bahama.

The cost of travel to primary schools was greater in Region 1 than in the other regions, which made greater use of public transport.

Conversely, travel to secondary schools in Regions 3 and 4 was up to six times more expensive than in Region 1 (Table 7-5).
Cost of travel to a hospital was some 24 times more ex- pensive for the Other Family Islands, compared with New Providence and Grand Bahama.

Thus, in some cases, lack of a facility on an island added greatly to household ex- penditure.

Cost of travel to health clinics/doctors’ offices was more expensive outside New Providence and Grand Bahama and as much as 15 times more expensive in Abaco, Andros, and Eleuthera.
Travel Time to Nearest Facility Travel time depends on distance travelled, speed, and mode of transport.

However, in more heavily populated areas, such as New Providence, travel time in relation to distance increases, especially at peak travel times— morning and evening rush hour—because of traffic con- gestion and speed limits.

Thus, speed is a function of traf- fic congestion and speed limits.
These factors undermine the assumed relationship between distance, speed, and mode of transport (see Appendix; Tables 7-A4, 7-A8, 7- A12, 7-A16, and 7-A20).

It should be noted that travel time data provided by survey respondents did not always include the time needed to complete the journey (e.g., from leaving home to arriv- ing at the hospital).

For example, some households only stated the flying time, which drastically reduced the over- all time of the journey.
Consequently, the study team re- TABLE 7-5 Summary of Travel Costs to Access Selected Facilities, by Region Facility type Bank/banking services facility Food market/grocery store Govt.

admin.

complex Health clinic/doctor’s office Hospital Mail boat* Police station Post office Primary school Secondary school * See definition in Table 7-1.
1 1.41 4.48 1.52 1.47 3.25 2.57 2.85 2.30 3.98 1.21 Region Average cost ($) 2.03 4.64 3.24 2.29 36.11 3.40 3.03 2.50 3.56 1.62 83340_131-154 3/31/05 9:28 PM Page 136 136 | BAHAMAS LIVING CONDITIONS SURVEY 2001 TABLE 7-6 Summary of Median Distances and Time Required To Access Facilities, by Region Median time (min.)
Region Facility type Bank/banking services facility Food market/grocery store Govt.

admin.

complex Health clinic/doctor’s office Hospital Mail boat2 Police station Post office Primary school Secondary school 1 Refers to Grand Bahama only.
2 See definition in Table 7-1. evaluated the amount of time associated with modes of transport, which is reflected in Table 7-6.

Only access to hospitals and mail boats involved jour- neys of more than 15 minutes for many people.

Residents trying to reach a hospital from islands other than New Providence and Grand Bahama would have a travel time of more than one hour (Table 7-6).
This finding raises a concern that, in emergency situations, such residents may not have sufficient time to access effective treatment.

Whilst differences in travel time were negligible across ex- penditure groups for accessing most facilities, travel time to access hospital care was a clear exception: highest-ex- penditure groups’ travel time was nearly 10 minutes less than that of lowest-expenditure groups (Table 7-7).

Dis- TABLE 7-7 Median Time to Access Facilities, by Quintile Median time (min.)
Quintile Facility type Bank/banking services facility Food market/grocery store Govt.

admin.

Complex Health clinic/doctor’s office Hospital Mail boat* Police station Post office Primary school Secondary school * See definition in Table 7-1.
83340_131-154 3/31/05 9:28 PM Page 137 COMMUNITY SERVICES AND SOCIAL PROGRAMMES: ACCESSIBILITY ANALYSIS 137 | tances to mail boats, which probably reflected the geogra- phy of the islands, varied; however, median travel time did not vary by more than about 12 minutes (Table 7-6).

Discussion: Cost of Access and Regional Geography Not surprisingly, higher-expenditure households accessed facilities by car to a greater extent than did lower-expendi- ture ones.
Despite the convenience that the car offered users, the median time to arrive at facilities was virtually the same across quintiles.

Although higher-expenditure house- holds typically lived on the outskirts of urban areas, the small size of the islands resulted in little difference in median distance to a particular facility across expenditure groups.
As Box 7-1 illustrates, access to hospital care presented the highest travel cost to residents living outside New Providence and Grand Bahama, which likely creates a fi- nancial burden for lower-expenditure groups.

Access to food markets/grocery stores involved the second highest travel cost, which likely represents an important item in the budget of lower-expenditure households.
Likewise, ac- cessing health clinics/doctors’ offices and schools involved significant expenses; in the case of primary schools, for ex- ample, daily household expenditures might need to cover several children.

As Table 7-4b shows, use of walking and public transport as modes of accessing facilities was high- est for low-expenditure household groups and lowest for high-expenditure groups.
Given the geography of the islands, it is clear that most facilities are well distributed throughout the Common- wealth.

However, the cost of accessing facilities varies con- siderably.

To reiterate, the most striking cost variation was in accessing hospitals on New Providence and Grand Ba- hama.

Clearly, transport cost to a frequently used facility, such as schools and grocery stores, is a key component of the household budget.
Except in Other Family Islands, secondary-school chil- dren were less inclined to walk to school than their pri- mary-school counterparts.

Greater use of public transport in New Providence and Grand Bahama reflected the avail- ability of public buses.

Elsewhere, however, walking was used more often than public transport.

This could reflect 1) willingness to make short trips by foot, 2) unavailabil- ity of public transport on the desired route, or 3) a deci- sion to use the cheapest method of transport.
In Other Family Islands, extensive use of public transport to reach a banking facility resulted from the limited number of full- service banks on those islands.

The figures in Table 7-4a demonstrate the high level of private transport used for all purposes on all islands.
For example, in New Providence and Grand Bahama, 18% of residents walked and 6% used public transport to reach a food market/grocery store; it can be assumed that the remaining 76% used an alter- nate means of transport, like a private motor vehicle.

Overall, Family Islanders face higher direct-transport costs than do households in New Providence and Grand Bahama.
This fact, combined with their lower expenditure levels, indicates that the travel cost to access community services presents a greater burden for households living outside New Providence and Grand Bahama.

ACCESS TO SOCIAL PROGRAMMES Like other governments, the Government of the Com- monwealth of The Bahamas (GOBH) recognizes that cer- tain members of society will always require assistance to enable them to provide for themselves and their depen- dents, particularly in terms of food and education.
To this end, various social programmes are available to assist households in need.

Programme assistance includes:5 • Burial.

Burial assistance of $550 is provided to per- sons with little or no expenditure.

• Disability.

Medically certified disabled persons awaiting approval from the National Insurance Board (or those who do not qualify) can claim a dis- ability allowance as a short-term cash allowance.

Sin- gle applicants can claim $100 per month.


Applicants with one-to-three dependents can claim $130 per month, whilst those with four or more dependents can claim $140.

• Financial.

Financial assistance is limited to persons with little or no expenditure.

Applicants can receive allowances for clothing, footwear, school supplies, basic household items, and travel (boat or airplane).

• Food.
• Food.

The Food Assistance Programme provides long-term, monthly food coupons to eligible pen- sioners and invalids and short-term, monthly coupons to others.

Single applicants receive $50.

Ap- plicants with dependents receive $60, $70, or $80, respectively, with one or two, three, or four or more 5 Complete descriptions of these programmes are available from the Ministry of Social Services and Community Development.
83340_131-154 3/31/05 9:28 PM Page 138 138 | BAHAMAS LIVING CONDITIONS SURVEY 2001 dependents.

To qualify, applicants must be either unemployed or classified as “low expenditure.”6 • Housing repair.

Indigent senior citizens or invalids may receive a housing repair allowance of $1,000–2,000 (amounts cover minor repairs and in- clude labour and materials).

• Med card.

Med-card service is provided to persons seeking medical attention who are unable to pay for some or all services.
Claimants usually have disabili- ties or chronic medical conditions.

Cards are usually issued for 6–12 months.

Patients with chronic psy- chiatric conditions or terminal illnesses (including full-blown AIDS) can receive five-year cards.
One- day cards can be issued to persons experiencing fi- 6 As a general rule, persons earning less than $150 a week (about $7,800 per year) are classified as “low expenditure” and are thus eligi- ble to apply for assistance; about 11% of Bahamian households may be eligible for these programmes.

nancial hardship.

Cards do not cover services costing more than $300.

• Rent.

Rental assistance of $300 per year is available to applicants with little or no expenditure who are in arrears on their rent.
This amount is paid directly to the landlord.

• School lunches.

The National School Lunch Pro- gramme (NSLP) is open to children 1) identified as undernourished and recommended by medical au- thorities, school administrators, or social workers; 2) whose parents (or other breadwinners) are unem- ployed; and 3) whose family earnings are less than the minimum wage or whose household expenditure is insufficient (Box 7-2).

• School uniforms.
• School uniforms.

The School Uniform Assistance Programme aims to ensure regular school attendance by children from lower-expenditure households.

Available annually to single parents, two-parent fam- ilies, and other caregivers experiencing economic BOX 7-2 National Lunch Programme Targets Neediest Schoolchildren The National School Lunch Programme (NSLP), un- like other social programmes, is delivered directly to beneficiaries—that is, schoolchildren.
Overall, about 45% of the households surveyed were aware of the Programme.

In the lowest-expenditure households, 55% knew about it, compared to 31% in the highest- expenditure ones.

Overall, 20% of households re- ported that their school participated in the Pro- gramme when children were 5–10 years old and 16% when children reached 11–16 years of age.
The per- centage of households in the highest expenditure group that reported school participation (for either child age group) was more than 10 times less than that reported by households in the lowest expenditure group (see Tables 7-A24 and 7-A25).

Survey results showed that younger schoolchildren were more likely than older ones to receive school lunches.

No children from higher-expenditure house- holds received them.
At the time of the survey, 13% of lowest-expenditure households with children aged 3–10 received them, whilst 5% with children aged 11–18 did.

A slightly higher percentage of boys than girls received the meals.

A smaller percentage of chil- dren in both age groups in New Providence and Grand Bahama received them, compared with chil- dren in the other islands.
When schoolchildren aged 5–16 were considered, it was found that no child in the two highest- expenditure households received school lunches, and less than 1% of those in the middle-expenditure group received them.

Across all islands and quintiles, 54% of schoolchildren received a snack/meal from the school canteen or vendor.
In New Providence and Grand Bahama, children were more likely not to eat lunch, as were children in the highest-expenditure group, suggesting that, for these children, “skipping” lunch may have a psychological cause (Table 7-A26).

For the most part, children from the lower- expenditure groups and households outside New Providence and Grand Bahama participated, suggest- ing that the Programme has succeeded in its overall targeting.

Nonetheless, data suggest that coverage may be low.
This may reflect children’s reluctance to be seen by their peers participating in the Programme, as this would indicate they came from lower- expenditure households (see chapter 5).

83340_131-154 3/31/05 9:28 PM Page 139 COMMUNITY SERVICES AND SOCIAL PROGRAMMES: ACCESSIBILITY ANALYSIS 139 | hardship, the Programme provides schoolchildren uniforms and footwear.

• Unemployment.
• Unemployment.

Since the survey was conducted, op- eration of the Unemployment Assistance Programme, as initially designed, has been discontinued.

Individu- als may now receive assistance with rent arrears and/or utility payments, and a limited number of persons may receive cash grants.

When it was fully operational, the programme was available to Bahamian citizens who were unemployed but seeking gainful employ- ment or citizens suffering genuine hardship.
The monthly allowances were $104 for a single applicant.

Applicants with dependents received $150, $196, $246, and $300, respectively, for one, two, three, or four or more dependents.

• Work.

The Work Assistance Programme provides temporary relief for unemployed persons.

Participa- tion is for not more than six months, but this limita- tion is not fixed.

Employable out-of-work persons are paid temporarily to work in charitable organiza- tions.

Workers receive payment of $190 per week and $350 monthly.
Public Awareness of Programmes Awareness of these social programmes was greatest in New Providence and Grand Bahama (Region 1), followed by Abaco, Andros, and Eleuthera (Region 2); Exuma and Long Island (Region 3); and finally Other Family Islands (Region 4).

This suggests that awareness amongst house- hold heads was greatest in the most densely populated is- lands, decreasing as populations became sparser (see Ap- pendix, Table 7-A21).
The Food Assistance Programme was the most com- monly known programme.

Overall, 45% of the house- holds surveyed had heard of it, compared to only 34% of respondents on Other Family Islands.

Overall, about 33% of respondents knew of the Unemployment Assistance Programme and Disability Allowance; whilst the least known programmes were Burial and Rent Assistance.
The programmes about which respondents displayed greatest variation in knowledge were Med Card, Work Assistance, Rent Assistance, and Burial Assistance.

Beneficiaries Overall, 8.5% of respondents received medical benefits and 6% received Food Assistance.

At the time of the sur- vey, no respondents received Burial or Rent Assistance.

Food Assistance was the most common benefit ever re- ceived, and some respondents had received all benefits at certain times.
Less than 3% of respondents had ever ap- plied for any specific benefit (see Appendix, Table 7-A22).

Beneficiaries of social programmes were predominantly female (71%).

Fifty-one percent were heads of households, 13% were children, and 12% spouses.

Nearly all recipients (98%) were Bahamian nationals.

Sixty-nine percent were aged 35 or older, and 21% were teenagers or younger.

While up to 3% of children received school lunches, only 1% received a school-uniform allowance (see chapter 5).
As Table 7-A23 shows, the average monthly value of all social benefits received by a household was about $105; of this amount, $61 was for Food Assistance.

However, the me- dian monthly value of all assistance per household was the same as the mean monthly amount received for Food Assis- tance ($50); that is, the monthly benefit was nearly always equivalent to the food allowance.

This finding clearly sug- gests that Food Assistance is the most important allowance.
Discussion Females were more likely than males to claim social-pro- gramme benefits (males comprise 49% of the population, yet receive 29% of the benefits).

Likewise, Bahamian na- tionals were more likely than other nationals to benefit (Bahamians constitute 87% of the population and 98% of beneficiaries).

Older people were more likely than younger people to benefit.
Those over 55 years of age comprise 11% of the population, but represent 39% of beneficia- ries; whilst 0–14 year-olds represent 30% of the popula- tion and only 11% of beneficiaries.

This finding may sug- gest that hardship is age-related and that older people may have inadequate income (due to limited pensions) and thus be in greater need of state aid.

These observations suggest that this issue requires further research.
Given the eligibility criteria for social programmes, it is clear that only a subset of the population can claim assis- tance.

Of the 10% of households that included persons with disabilities, 2.5% claimed the disability allowance, which suggests that more households with disabled mem- bers might be eligible to utilize the programme.

Similarly, of the 12% of households with diabetic persons and 32% with hypertensive persons, the medical-card benefit could be claimed by more than 8% of households.
The monthly value of benefits is slightly more than $100 per household.

As the most commonly received al- lowance is Food Assistance (varying from $50 to $80) and the average monthly amount received per household is 83340_131-154 3/31/05 9:28 PM Page 140 140 | BAHAMAS LIVING CONDITIONS SURVEY 2001 $50, Food Assistance is likely the most important al- lowance.

Given that the household food-poverty line is $280 per month, the Food Assistance contribution repre- sents about 18% of essential food expenditure.
This may suggest that an increase in the food allowance currently of- fered would be beneficial.

Implications for Further Research The above findings raise important issues with regard to providing the neediest Bahamians a social safety net.

This study collected relatively little information on this group; the limited extent of the data is evidenced by the fact that regional and quintile breakdowns are not always given.
As a result, a reliable, detailed analysis is not yet available to benefit policymakers.

However, the chapter findings sug- gest that the topic of social programmes and their delivery would benefit from further research.

Specific areas that need clarification include low rates of programme partici- pation and, if confirmed, reasons for lack of programme utilization.
83340_131-154 3/31/05 9:28 PM Page 141 COMMUNITY SERVICES AND SOCIAL PROGRAMMES: ACCESSIBILITY ANALYSIS 141 | APPENDIX TABLE 7-A1 Distance to Nearest Health Facility, by Region and Quintile Distance (mi.)
Health clinic/doctor’s office Less than 1 1–2 3–10 11–20 21 or more On another island N Hospital Less than 1 1–2 3–10 11–20 21 or more On another island N All Bahamas Region Quintile TABLE 7-A2 Means of Transportation to Nearest Health Facility, by Region and Quintile Means of transportation All Bahamas Region Quintile 1 2 3 4 Health clinic/doctor’s office Walk Bicycle/motorcycle Private car Jitney/bus Taxi Boat/airplane/other N Hospital Walk Bicycle/motorcycle Private car Jitney/bus Taxi Boat/airplane/other N 0.0
83340_131-154 3/31/05 9:28 PM Page 142 142 | BAHAMAS LIVING CONDITIONS SURVEY 2001 TABLE 7-A3 Average Cost of Travel to Health Facility* Region of facility location Health clinic/ doctor ($) Hospital ($) All Bahamas 1 2 3 4 N Primary means of transport Jitney/bus Taxi Boat/airplane/other N 2.3 1.5 22.9 15.8 6.9 153 1.2 7.6 — 142 36.1 3.2 67.9 72.2 78.0 1,073 2.6 6.4 70.1 1,066 * Data were collected only for households that did not use their own means of transportation.
TABLE 7-A4 Travel Time to Nearest Health Facility, by Region and Quintile* Travel time (min.)

Health clinic/doctor’s office 0–15 16–30 31–60 More than 60 N Hospital 0–15 16–30 31–60 More than 60 N All Bahamas 88.5 9.6 1.1 0.8 1,873 38.9 36.8 18.5 5.8 * Based on reported means of transportation.
Region Quintile 83340_131-154 3/31/05 9:28 PM Page 143 COMMUNITY SERVICES AND SOCIAL PROGRAMMES: ACCESSIBILITY ANALYSIS 143 | TABLE 7-A5 Distance to Nearest School, by Region and Quintile Region Quintile 1 2 3 4 Distance (mi.)
Primary school Less than 1 1–2 3–10 11–20 21 or more On another island N Secondary school Less than 1 1–2 3–10 11–20 21 or more On another island N All Bahamas TABLE 7-A6 Means of Transportation to Nearest School Means of transportation All Bahamas 1 2 3 4 Region Quintile Primary school Walk Bicycle/motorcycle Private car Jitney/bus Taxi Boat/airplane/other N Secondary school Walk Bicycle/motorcycle Private car Jitney/bus Taxi Boat/airplane/other N 5.3
83340_131-154 3/31/05 9:28 PM Page 144 144 | BAHAMAS LIVING CONDITIONS SURVEY 2001 TABLE 7-A7 Average Cost of Travel to School* Region of facility location Primary school ($) Secondary school ($) All Bahamas 1 2 3 4 N Primary means of transport Jitney/bus Taxi Boat/airplane/other N 3.6 4.0 0.8 3.1 0.6 133 3.8 2.8 — 122 1.6 1.2 2.3 8.1 6.8 253 1.0 6.9 5.6 253 * Data collected only for households that did not use own means of transportation.
TABLE 7-A8 Travel Time to Nearest School* Travel time (min.)
Primary school 0–15 16–30 31–60 More than 60 N Secondary school 0–15 16–30 31–60 More than 60 N All Bahamas 91.3 7.5 1.0 0.2 1,873 80.3 16.0 3.3 0.4 1,873 Region Quintile * Based on reported means of transportation.
83340_131-154 3/31/05 9:28 PM Page 145 COMMUNITY SERVICES AND SOCIAL PROGRAMMES: ACCESSIBILITY ANALYSIS 145 | TABLE 7-A9 Distance to Nearest Post Office or Police Station Distance to facility (mi.)
All Bahamas Region Quintile 1 2 3 4 Post office Less than 1 1–2 3–10 11–20 21 or more On another island N Police station Less than 1 1–2 3–10 11–20 21 or more On another island N TABLE 7-A10 Means of Transportation to Nearest Post Office or Police Station Means of transportation All Bahamas Region Quintile 1 2 3 4 Post office Walk Bicycle/ motorcycle Private car Jitney/bus Taxi Boat/airplane/other N Police station Walk Bicycle/ motorcycle Private car Jitney/bus Taxi Boat/airplane/other N 81.0
83340_131-154 3/31/05 9:28 PM Page 146 146 | BAHAMAS LIVING CONDITIONS SURVEY 2001 1 TABLE 7-A11 Average Cost of Travel to Post Office or Police Station* Region of facility location Post office ($) Police station ($) All Bahamas 1 2 3 4 N Primary means of transport Jitney/bus Taxi Boat/airplane/other N 2.5 2.3 10.8 11.5 3.0 171 2.2 6.9 0.0 162 3.0 2.8 5.2 17.1 4.5 151 2.7 5.5 0.0 139 * Data collected only for households that did not use own means of transportation.
TABLE 7-A12 Travel Time to Nearest Post Office or Police Station* Travel time (min.)
All Bahamas Region Quintile 1 2 3 4 Post office 0–15 16–30 31–60 More than 60 N Police station 0–15 16–30 31–60 More than 60 N * Based on reported means of transportation.
83340_131-154 3/31/05 9:28 PM Page 147 COMMUNITY SERVICES AND SOCIAL PROGRAMMES: ACCESSIBILITY ANALYSIS 147 | TABLE 7-A13 Distance to Nearest Mail Boat or Government Complex Distance to facility (mi.)
All Bahamas Region Quintile 1 2 3 4 Mail boat Less than 1 1–2 3–10 11–20 21 or more On another island N Government complex Less than 1 1–2 3–10 11–20 21 or more On another island N TABLE 7-A14 Means of Transportation to Nearest Mail Boat or Government Complex Means of transportation All Bahamas Region Quintile 1 2 3 4 Mail boat Walk Bicycle/motorcycle Private car Jitney/bus Taxi Boat/airplane/other N Government complex Walk Bicycle/motorcycle Private car Jitney/bus Taxi Boat/airplane/other N 21.6
83340_131-154 3/31/05 9:28 PM Page 148 148 | BAHAMAS LIVING CONDITIONS SURVEY 2001 TABLE 7-A15 Average Cost of Travel to Mail Boat or Government Complex Region of facility location All Bahamas 1 2 3 4 N Primary Means of Transport Jitney/bus Taxi Boat/airplane/other N Mail boat ($) Government complex ($) 3.4 2.6 19.0 22.0 7.9 230 1.2 13.1 — 214 3.2 1.5 13.2 14.8 6.2 66 1.2 8.1 — 61 TABLE 7-A16 Travel Time to Nearest Mail Boat or Government Complex* Travel time (min.)
All Bahamas Region Quintile 1 2 3 4 Mail boat 0–15 16–30 31–60 More than 60 N Government Complex 0–15 16–30 31–60 More than 60 N * Based on reported means of transportation.
83340_131-154 3/31/05 9:28 PM Page 149 TABLE 7-A17 Distance to Nearest Grocery Store or Banking Facility Distance to facility (mi.)
All Bahamas Region Quintile 1 2 3 4 Grocery store Less than 1 1–2 3–10 11–20 21 or more On another island N Banking facility* Less than 1 1–2 3–10 11–20 21 or more On another island N * Banking facility included availability of financial transactions at the Post Office in the Government Administrative Complex; for about 45% of households in Region 4, this was the only type of banking facility available.
TABLE 7-A18 Means of Transportation to Nearest Grocery Store or Banking Facility Means of transportation All Bahamas Region Quintile 1 2 3 4 Grocery store Walk Bicycle/motorcycle Private car Jitney/bus Taxi Boat/airplane/other No.
observations Banking facility* Walk Bicycle/motorcycle Private car Jitney/bus Taxi Boat/airplane/other N * Banking facility included availability of financial transactions at the Post Office in the Government Administrative Complex; for about 45% of households in Region 4, this was the only type of banking facility available.
83340_131-154 3/31/05 9:28 PM Page 150 150 | BAHAMAS LIVING CONDITIONS SURVEY 2001 TABLE 7-A19 Average Cost of Travel to Facility1 Region of facility location Grocery store ($) Banking facility ($)2 All Bahamas 1 2 3 4 Primary Means of Transport N Jitney/bus Taxi Boat/airplane/other N 4.6 4.5 8.5 10.5 10.0 81 5.0 4.2 — 75 2.0 1.4 11.9 16.4 5.4 207 1.2 8.8 0.0 201 1 Data were collected only for households that did not use their own means of transportation.
2 Banking facility included availability of financial transactions at the Post Office in the Government Administrative Com- plex; for about 45% of households in Region 4, this was the only type of banking facility available.

TABLE 7-A20 Travel Time to Nearest Grocery Store or Banking Facility1 Travel time (min.)
All Bahamas Region Quintile 1 2 3 4 Grocery store 0–15 16–30 31–60 More than 60 N Banking facility2 0–15 16–30 31–60 More than 60 N Based on reported means of transportation.
2 Banking facility included availability of financial transactions at the Post Office in the Government Administrative Complex; for about 45% of households in Region 4, this was the only type of banking facility available.
83340_131-154 3/31/05 9:28 PM Page 151 COMMUNITY SERVICES AND SOCIAL PROGRAMMES: ACCESSIBILITY ANALYSIS 151 | TABLE 7-A21 Responses to Survey Question: “Ever Heard of Social Program?” Social program All Bahamas Unemployment Food assistance Financial assistance Disability allowance Housing repair allowance Burial assistance Rent assistance Work programme School uniform Medical card 31.0 45.1 22.4 30.9 16.1 15.1 14.5 19.2 19.4 23.7 1 33.2 45.3 23.7 33.0 15.9 16.3 16.0 21.1 19.9 25.8 Region TABLE 7-A22 Receipt of Social Benefits* Social benefit Currently received No.
observations Ever received Unemployment Food assistance Financial assistance Disability allowance Housing repair allowance Burial assistance Rent assistance Work Programme School uniform Medical card Any social programme N 492 752 357 483 298 229 207 276 332 323 996 Ever applied 2.6 2.4 0.9 0.9 0.7 0.0 1.1 1.4 0.6 0.6 4.5 * The number of responses was insufficient to allow for analysis by region and quintile.
N 1,874 1,876 1,876 1,876 1,876 1,876 1,876 1,875 1,875 1,876 N 484 703 352 481 292 227 206 275 328 319 968 83340_131-154 3/31/05 9:28 PM Page 152 152 | BAHAMAS LIVING CONDITIONS SURVEY 2001 TABLE 7-A23 Beneficiary Characteristics for All Social Programs Characteristic Currently received Ever received Currently or ever received Male Relationship to head Head Spouse Child Other Bahamian national Age 0–14 15–19 20–34 35–54 55 or older $ received per month Average Median Average, Food Assistance for household Median, Food Assistance for household Average, Food Assistance per capita Median, Food Assistance per capita N Per-capita food poverty line (monthly) Average household size Household food poverty line (monthly) 83340_131-154 3/31/05 9:28 PM Page 153 COMMUNITY SERVICES AND SOCIAL PROGRAMMES: ACCESSIBILITY ANALYSIS 153 | TABLE 7-A24 Participation in National School Lunch Programme (NSLP), by Selected Variables Participation factor All Bahamas Region 1 Regions 2–4 Boys Girls Quintile 1 Quintile 5 Awareness of the NSLP N Child’s school participation in the NSLP Children (ages 3–10) No.
observations Children (ages 11–18) N Child who has ever received lunch Children (ages 3–10) N Children (ages 11–18) N Child who currently receives lunch Children (ages 3–10) N Children (ages 11–18) N 83340_131-154 3/31/05 9:28 PM Page 154 154 | BAHAMAS LIVING CONDITIONS SURVEY 2001 TABLE 7-A25 Participation of Children Ages 5–16 (Currently Attending) in National School Lunch Programme (NSLP) Participation factor All Bahamas Awareness of the NSLP N Child’s school participation in the NSLP Children (ages 5–10) N Children (ages 11–16) N Child who has ever received lunch Children (ages 5–10) N Children (ages 11–16) N Child who currently receives lunch Children (ages 5–10) N Children (ages 11–16) N 49.8 1,581 19.7 849 15.8 731 5.4 849 2.0 731 3.3 849 1.3 731 1 59.0 500 32.2 292 26.7 208 16.1 292 4.7 208 9.0 292 4.0 208 Quintile TABLE 7-A26 Responses to Question: “What Does Child
 Usually Have for Lunch?,” by Selected Variables Response All Bahamas Region 1 Regions 2–4 Boys Girls Quintile 1 Quintile 5 Snack/meal from school canteen vendor Snack/meal from home Other Nothing N 83340_155-174 3/31/05 9:30 PM Page 155 CHAPTER 8 Housing Variables for Policy Formulation Carmen Gomez DWELLING TYPE The BCLS found that 63.4% of dwellings in The Bahamas were separate detached houses (Table 8-1).
These units occupied a parcel of land in a freestanding capacity and did not share walls, roofs, or floors with any other dwelling units.

The second most significant type of dwelling was the apartment or flat, which accounted for 18.3% of units.

Apartments or flats were usually found in blocks, generally stacked atop each other.

They shared not only walls, but also floors and ceilings; (that is, one household’s floor was another’s ceil- ing).
Occasionally, apartments or flats were found above commercial structures.

Finally, 17.3% of dwellings were single attached houses.

They were usually duplexes or other multi-dwelling struc- tures that shared walls, from ground to roof.

Distribution by Region In Region 1, which includes the country’s two major centres of habitation—New Providence 155 H ousing policy is inextricably linked to so- cioeconomic and political considera- tions.
Availability of reliable data on the housing variables that characterize a country’s living standards is critical to policy planners, who seek to base their decisions upon objective crite- ria.

To describe the national housing stock of The Bahamas, the Bahamas Living Conditions Survey (BLCS) used a range of variables—from dwelling type, construction materials, and tenure type to water supply, utilities, and waste-disposal facilities and services.
The household expendi- tures analysed included water, an array of utilities and services, shelter costs, and real property tax.

Expenses were examined in terms of the mean value of household payments, as well as in rela- tion to other expenditures.

Several indicators— durable-goods ownership, housing quality index (HQI), and overcrowding—were considered to determine housing conditions.

All variables were examined at both national and regional levels and by consumer quintile.
83340_155-174 3/31/05 9:30 PM Page 156 156 | BAHAMAS LIVING CONDITIONS SURVEY 2001 TABLE 8-1 Percentage Distribution of Dwelling Type Dwelling type Separate detached house Single attached house Apartment/flat Other All Bahamas 63.4 17.3 18.3 1.1 Region Quintile and Grand Bahama—distribution of dwelling types con- forms closely to national percentages.
The percentage of apartments/flats was slightly higher than the national average, at 20.5%, whilst the percentage of single detached dwellings was slightly lower, at 60.7%.

Across the coun- try’s other three regions, the single detached dwelling was more widely represented, with 74.9% in Region 2, 87.1% in Region 3, and 79.2% in Region 4.

Single attached dwellings accounted for 15.6% of units in Region 2 and less than 10% in Regions 3 and 4.
In Region 4, the apart- ment/flat accounted for 10.5% of units and less than 10% in the other two regions (Table 8-1).

Distribution by Quintile Across all consumption quintiles, the single detached dwelling unit was the predominant type, ranging from 71.3% in quintile 1 to 55% in quintile 5.

More house- holds in the highest quintile inhabited apartments/flats and attached houses than in the other four quintiles.
The Survey data did not show any significant differences in the choice of dwelling unit between the four lower quintiles, except that the lowest percentage (9.9%) was apart- ments/flats in the middle quintile (3).

CONSTRUCTION MATERIALS The most widely used construction material for the outer walls of Bahamian dwellings was concrete block or slab.

As Table 8-2 shows, 71.4% of units were made of concrete.
The second most frequently used material was wood, with or without stucco, which accounted for 21% of units.

Other types of materials combined accounted for less than 10% of dwellings.

Nationwide, 80.8% of roofs were covered predomi- nantly with asphalt shingles (Table 8-3).

Wooden shingles were used for 8.6% of roofs, corrugated metal sheet was used for 3.8%, tile was used for 3.4%, and concrete for 2.4%.

Less than 1% used some other type of roofing material.
Distribution by Region Outer Walls In New Providence and Grand Bahama (Region 1), 73.6% of dwellings’ outer walls were made of concrete, compared to 19.0% made of wood, with or without stucco, and 5.7% made of stone.

In Region 4 (Other Family Islands), houses made of wood were more heavily represented.
In Region 2 (Abaco, Andros, and Eleuthera), 33.3% of dwellings were TABLE 8-2 Percentage Distribution of Outer-wall Construction Materials Construction material Wood/stucco Concrete Block/slab Wood & concrete Stone/brick Other All Bahamas 21.0 71.4 2.1 5.4 0.2 Region Quintile 83340_155-174 3/31/05 9:30 PM Page 157 HOUSING VARIABLES FOR POLICY FORMULATION | 157 TABLE 8-3 Percentage Distribution of Roofing Materials Roofing material Asphalt shingle Wood shingle Corrugated metal sheet Concrete Tile Other All Bahamas 80.8 8.6 3.8 2.4 3.4 1.0 Region Quintile made of wood and 59.9% of concrete.
Distribution in the other two regions was similar.

In Exuma and Long Island (Region 3), 26.5% of dwellings were made of wood, whilst 58.1% were made of concrete.

In Other Family Islands (Region 4), 25.6% of houses were made of wood, and 62% were made of concrete block or slab.

All four regions had some stone houses, with Region 3 having the highest per- centage (8.5%), followed by Region 4 (7%).

In Region 2, only 2.1% of dwellings were made of stone.
Roofing In all four regions, roofs were made mainly of either as- phalt or wooden shingles.

In New Providence and Grand Bahama, about 4.3% of roofs were corrugated metal sheet; whilst only 1.4% of dwellings in Region 2 and less than 1% in Regions 3 and 4 used this material (Table 8-3).

The data for roofing tile was similar.

In Region 4, 4.8% of roofs were made of other types of material not used signif- icantly in the other three regions.
Flooring Across all regions, concrete was the material of choice for floors, accounting for more than 80%.

These floors could TABLE 8-4 Percentage Distribution of Flooring Materials be subsequently covered by tile (marble, ceramic, or vinyl), rug, or mat; however, the base material was poured concrete.

Table 8-4 shows that Region 2 had the highest percentage of wooden floors (16.8%), followed by Region 1 (16.4%).
Distribution by Quintile Outer Walls In quintile 1, 48.8% of dwellings had wooden outer walls, with or without stucco, compared to 10.6% in quintile 5.

As Table 8-2 shows, there is an inverse relationship be- tween material used for outer walls and living standards, as typified by consumption quintiles.

As consumption status increased, so did the use of concrete; the reverse was the case for wood, whose use increased as consumption status declined (Figure 8-1).
Roofing The roofing-materials variable was not significant as a de- terminant of economic differences, as the distribution pat- tern was similar for all consumer quintiles.

More than 70% of households across all quintiles used asphalt shin- gles.
As Table 8-3 shows, 9.3% of dwellings in quintile Flooring material Wood Concrete Other All Bahamas 16.2 83.4 0.4 Region 1 16.4 83.1 0.4 2 16.8 83.0 0.2 3 10.9 87.0 2.1 4 11.5 88.0 0.6 1 35.6 63.0 1.4 2 20.5 78.8 0.7 Quintile 3 17.4 82.6 0.1 4 13.1 86.8 0.1 5 9.0 90.6 0.4 83340_155-174 3/31/05 9:30 PM Page 158 158 | BAHAMAS LIVING CONDITIONS SURVEY 2001 FIGURE 8-1 Distribution of Outer-wall Construction Material, by Consumption Quintile t n e c r e P 90 80 70 60 50 40 30 20 10 0 Q-1 Q-2 Q-3 Quintile Q-4 Q-5 Wood/Stucco Concrete Wood/Concrete Stone/Brick Other 1 used corrugated metal sheet, compared to only 1.5% in quintile 5.
Roofing tile was used almost exclusively by the highest quintile.

Whilst all quintiles used wooden shin- gles, rates were highest in the poorest two quintiles and lowest in the wealthiest quintile.

TENURE TYPE Owner-occupied dwellings accounted for nearly 58% of dwellings in The Bahamas, whilst renter households ac- counted for 36.8% (Table 8-5).

In addition to private renters, another 1.1% had their units rented for them by the Government (presumably, their employer).
Interest- ingly, some 3.5% of the households occupied their units rent-free.

TABLE 8-5 Percentage Distribution, by Tenure Type Separate detached dwellings tended to be owner-occu- pied (86.3%), whilst single attached dwellings and apart- ments/flats were more likely to be rented (68.3% and 82.2%, respectively) (Table 8-6).

For Region 1, this dis- tinction was particularly true; it was not as marked in Region 4, where private rental units accounted for a much lower percentage of occupied dwellings.
Across all five consumption quintiles, renters overwhelmingly occupied apartments/flats and, to a lesser extent, single attached units.

Distribution by Region In Region 4, nearly 75% of households lived in owner- occupied dwellings.

This was in stark contrast to 55% in Region 1.

On the other hand, private renters accounted for more than 40% of Region 1 dwellings, compared to only 15–16% in Region 4.
Households occupying Gov- ernment-rented units and rent-free units were also higher in Region 4 than in Region 1.

Distribution by Quintile In the poorest quintile, 46.4% of households occupied dwellings owned by a member of the household, and 41.8% of dwellings were rented units.
Although no mea- surable relationship was found between wealth and tenure, Table 8-5 shows that the poorest quintile had the lowest percentage (46.4%) of owner-occupied dwellings and the highest percentages of rent- free (7.7%) and Government- rented (2.5) dwellings.

WATER SUPPLY Any country must have a readily available supply of water to support life and its activities.

On average, each person Tenure type Owned Private rented Gov’t.
rented Rent free Other All Bahamas 57.8 36.8 1.1 3.5 0.8 Region Quintile 83340_155-174 3/31/05 9:30 PM Page 159 HOUSING VARIABLES FOR POLICY FORMULATION | 159 TABLE 8-6 Percentage Distribution of Type of Dwelling, by Tenure Type Dwelling type All Bahamas Separate detached house Single attached house Apartment/flat Other N Region Region 1 Separate detached house Single attached house Apartment/flat Other N Region 2 Separate detached house Single attached house Apartment/flat Other N Region 3 Separate detached house Single attached house Apartment/flat Other N Region 4 Separate detached house Single attached house Apartment/flat Other N Quintile Quintile 1 Separate detached house Single attached house Apartment/flat Other N Total Owned Private rented Gov’t.
rented Rent free Other Tenure type (continues) 83340_155-174 3/31/05 9:30 PM Page 160 160 | BAHAMAS LIVING CONDITIONS SURVEY 2001 TABLE 8-6 (Continued) Dwelling type Total Owned Private rented Gov’t.
rented Rent free Other Tenure type Quintile 2 Separate detached house Single attached house Apartment/flat Other N Quintile 3 Separate detached house Single attached house Apartment/flat Other N Quintile 4 Separate detached house Single attached house Apartment/flat Other N Quintile 5 Separate Detached House Single Attached House Apartment/Flat Other N requires more than 50 litres of water daily to meet personal and household needs (Gleick 1996).
In The Bahamas, most of the water used comes from underground; the amount of fresh water available varies according to each is- land’s shape, rock formation, and rainfall distribution.

Thus, water collection and distribution to households is a costly undertaking.

As Table 8-7 shows, nearly 52% of Bahamian house- holds enjoyed public water piped into their dwellings, whilst almost 35% had a private source of water piped into their homes.
Nearly 6% of units had water piped into their yard, either from a public or private source.

About 4.1% of households relied on a public standpipe, whilst another 1.3% used a public well or tank.

Distribution by Region Households that had public water piped into their dwellings were unevenly distributed across the four re- gions.

In Region 1, such households accounted for 51.7% of units, compared to 64.7% in Region 2, 43.7% in Re- gion 3, and only 12.6% in Region 4.
Because the country’s public-water system was balanced by a private system, the percentage of households that en- joyed water piped into their dwellings was raised consider- ably.

In Region 4, for example, 64.4% of dwellings had a private piped supply; added to the 12.6% public supply, the percentage for those islands rose to 77%.
Amongst households that relied on a public well or standpipe for their supply (5.4%), Region 1 households 83340_155-174 3/31/05 9:30 PM Page 161 HOUSING VARIABLES FOR POLICY FORMULATION | 161 TABLE 8-7 Percentage Distribution of Bathing Water Source, by Region and Quintile Water source for bathing Public piped into dwelling Public piped into yard Private piped into dwelling Private not piped Public stand pipe Public well or tank Rain water system (piped) Rain water system (not piped) Other All Bahamas 51.9 2.3 34.8 3.3 4.1 1.3 1.3 0.2 0.8 Region Quintile mainly used standpipes, whilst Region 4 households tended to used a public well or tank.
Distribution by Consumer Quintile BLCS results showed that access to water piped into dwellings increased with wealth.

In quintile 1, 61.5% of households had water piped into their dwelling units, compared to 96.1% in quintile 5.

Less than 2% of house- holds in the wealthiest quintile obtained their water from a public well or standpipe, compared to 21.5% in the poorest quintile.

In all but the poorest quintile, more than one-third of households had a private source piped into their dwellings.
Drinking Water Despite high percentages of households with running wa- ter, only 11.1% of all households drank from the same source used for bathing and cleaning (Table 8-8).
This TABLE 8-8 Percentage Distribution of Source of Drinking Water, by Region and Quintile Drinking water source Public piped into dwelling Public piped into yard Private piped into dwelling Private not piped Public stand pipe Public well or tank Rain water system (piped) Rain water system (not piped) Purchased bottled water Other Same water source for bathing and drinking Yes No All Bahamas 5.8 0.6 3.8 0.7 0.8 0.3 0.8 0.4 86.3 0.4 11.1 88.9 Region Quintile 83340_155-174 3/31/05 9:30 PM Page 162 162 | BAHAMAS LIVING CONDITIONS SURVEY 2001 TABLE 8-9 Percentage Distribution of Sanitary Facility Types Toilet facilities Flush toilet linked into a public sewerage system Flush toilet with cesspit of septic tank Pit latrine Other None Exclusive use of flush toilet Yes No All Bahamas 12.7 81.3 4.5 0.3 1.1 89.5 10.5 Region 2 2.0 3 0.0 1 14.9 Quintile 0.6
0.0 2.6 80.1 19.9 18.5 1.0 4.0 71.0 29.0 4.9 0.6 2.1 88.6 11.4 4.2 0.6 0.7 90.8 9.2 2.2 0.0 0.8 91.8 8.2 1.2 0.0 0.0 94.7 5.3 percentage was lowest in Region 1 (9.6%) and highest in Region 2 (19.2%).
In the poorest quintile, 19.7% of households drank from the same source used for bathing and cleaning, compared to 11.2% in the wealthiest.

More than 86% of all Bahamian households purchased bottled drinking water; whilst Region 1 had the highest use percentage (88.3%), that in the other three regions ranged from 75.2% to 78.8%.

In the poorest consump- tion quintile, 77.8% of households purchased bottled drinking water.
In the higher four quintiles, percentages ranged from 85.7% in the wealthiest quintile to 89.4% in quintile 4.

SANITARY FACILITIES Together with access to safe and adequate water supply, sanitary facilities for disposal of human waste are consid- ered important indicators of housing conditions.

Across The Bahamas, most dwelling units had flush toilets, either linked to a public sewerage system (12.7%) or attached to a cesspit or septic tank (81.3%) (Table 8-9).
Some 4.5% of households still used a pit latrine, whilst 1.1% reported having no toilet facilities attached to their dwelling unit.

According to Table 8-9, 89.5% of households had ex- clusive use of toilet facilities, although this figure declined to 71% in the lowest consumer quintile.

Only 10.5% of households shared toilet facilities; this percentage fell to 10.0% in Region 1 and rose to 19.9% in Region 4.
In the poorest quintile, 29.1% of households shared toilet facili- ties, compared to 5.3% in the wealthiest quintile.

Slightly more than 10% of households went outside their dwelling unit to use their toilet facility (Table 8-10).

This percentage was highest in Region 4 (17%), followed by Region 3 (15.2%).
In quintile 1, the percentage of TABLE 8-10 Comparison of Indoor and Outdoor Toilet Facilities, by Region and Quintile (%) Had to use outdoor toilet All Bahamas Yes No 10.3 89.7 Region 1 10.1 89.9 2 9.1 90.9 3 15.2 84.8 4 16.9 83.1 1 28.3 71.7 2 10.7 89.3 Quintile 3 8.4 91.6 4 8.2 91.8 5 6.1 93.9 83340_155-174 3/31/05 9:30 PM Page 163 HOUSING VARIABLES FOR POLICY FORMULATION | 163 TABLE 8-11 Percentage Distribution of Lighting Source, by Region and Quintile Lighting source Electricity Other All Bahamas 96.1 3.9 Region 1 96.6 3.4 2 92.2 7.8 3 94.6 5.4 4 95.4 4.6 1 84.8 15.2 2 94.4 5.6 Quintile 3 96.0 4.0 4 98.0 2.0 5 99.4 0.6 households that had outdoor toilet facilities was 28.3%; compared to 10.7% in quintile 2 and 6.1% in quintile 5.
Distribution by Region Only Regions 1 and 2 had households that were linked to a public sewerage system.

The percentage was highest in Region 1 (14.9%), compared to only 2% in Region 2.

Pit- latrine use was highest in Region 4 (13.8%) and lowest in Region 1 (4.5%).

In Region 1, 10% of households shared toilet facilities, whilst less than 1% reported having no toilet facility.
More households (2.6%) in Region 4 than in any other re- gion reported having no facilities; 19.9% of Region 4 households shared toilet facilities with other households.

Distribution by Consumer Quintile Whilst 98.8% of households in the wealthiest quintile re- ported having flush toilets linked either to a public sewer or cesspit, the rate fell to 75.4% in the poorest quintile.

Conversely, 18.5 % of households in the poorest quintile had a pit latrine, as opposed to 1.2% in the wealthiest quintile.
Likewise, 29.0% of households in the lowest quintile shared toilet facilities with another household, compared to 5.3% in the highest.

LIGHTING AND COOKING FUELS Lighting More than 96% of Bahamian households used electricity for lighting.

Region 2 had the highest percentage (7.8%) of households that used other lighting sources.

Even in the lowest consumer quintile, nearly 85% of Bahamian house- holds had electric lighting (Table 8-11).
Cooking Fuels For most Bahamian households, gas was the preferred cooking fuel.

Only 21.4% used electricity for cooking.

As Table 8-12 shows, 9.9% of households in the lowest quin- tile used electricity for cooking, although households in this quintile comprised the highest percentage (82.2%) of those who used gas as a cooking fuel.

TELEPHONE SERVICE In an archipelagic country like The Bahamas, where the population is scattered, telecommunications services are essential.
As Table 8-13 shows, 80.3% of the country’s dwellings were equipped with telephone service.
For some 6.2% of the population, the nearest telephone was within TABLE 8-12 Percentage Distribution of Cooking Fuel Use, by Region and Quintile Cooking fuel most often used All Bahamas Gas Electricity Other 75.6 21.4 3.0 Region 1 75.1 22.4 2.6 2 76.9 19.0 4.1 3 85.0 10.5 4.5 4 79.5 11.3 9.2 1 82.2 9.9 7.9 2 81.2 15.3 3.5 Quintile 3 78.2 18.7 3.1 4 77.8 20.1 2.1 5 67.6 31.2 1.2 83340_155-174 3/31/05 9:30 PM Page 164 164 | BAHAMAS LIVING CONDITIONS SURVEY 2001 TABLE 8-13 Percentage Distribution of Household Telephone Access, by Region and Quintile Nearest telephone Own home Neighbour’s house Public place within 5 minutes walk of unit Public place more than 5 minutes walk of unit Other No access All Bahamas 80.3 9.5 6.2 2.8 1.2 0.1 Region Quintile a five-minute walk of their dwelling, with only 2.8% hav- ing to walk farther to use a public telephone.
Only 0.1% of households had no access to a telephone.

25% of quintile 1 households used a public telephone; of these, 30% had to walk more than five minutes to reach that phone.

Distribution by Region In Region 1, telephone access was universal.

Region 3, which also had universal access, boasted the highest percentage (82.8%) of in-home telephone service.

More households in Regions 2 (14.6%) and 4 (13.1%) used a neighbour’s telephone than in Regions 1 and 3.
Less than 1% (.2%) of Region 4 households had no telephone access.

Distribution by Consumer Quintile Only 48.9% of households in quintile 1 had a telephone in their dwelling, compared to 91.1% in quintile 5.

More than 99% of quintile 1 households had telephone access, compared to 100% in the quintile 5.
Slightly more than GARBAGE DISPOSAL More than 95% of Bahamian households had their garbage collected for disposal in sanitary landfills, nearly 80% used a free Government-provided service, and more than 16% used private sources.1 As Table 8-14 shows, 4.3% of households either burned or dumped their garbage.
In terms of disposal by 1 In the mid-nineteenth century, following a series of epidemics that demonstrated the link between unsanitary waste disposal and diseases carried by insects and rodents, the relationship between proper waste disposal and public health was firmly established.

TABLE 8-14 Percentage Distribution of Household Disposal Type, by Region and Quintile Disposal type Collected by truck (Gov’t.
service) Collected by truck (Private service) Burned Dumped Buried All Bahamas 79.6 16.1 2.1 2.2 0.0 Region Quintile 83340_155-174 3/31/05 9:30 PM Page 165 dumping, 11.2% of Region 2, 7.6% of Region 4, and 6.0% of Region 3 households used this method; compared to less than 1% of Region 1 households.
Burning was most prevalent amongst Region 3 households (9.4%).

HOUSEHOLD EXPENDITURE ON UTILITIES AND SERVICES Government policymakers require household data on util- ities and services spending in order to monitor the effects of public policies on household well-being and to deter- mine the best ways to direct such policies.
The BLCS used the following variables to measure household operating ex- penses: water, electricity, telephone service, sewerage and garbage collection, mortgage and rent (shelter costs), and real property tax.

Composition of Bahamian household ex- penditure on utilities and services, shelter costs and real property tax, and other operational expenses are presented in Tables 8-15, 8-16A and B, and 8-17; respectively.
Nationwide, households spent 40 cents out of every consumption dollar on household operating expenses; in Region 1, 39.6 cents was expended, compared to 37.9 cents in Region 4 (Table 8-17).

Regions 2 and 3 house- holds spent somewhat more (about 43 cents out of every dollar).

Households in the lowest quintile spent 39.1 cents per dollar on household operations, compared to 42.4 cents for those in the highest quintile.
HOUSING VARIABLES FOR POLICY FORMULATION | 165 Analysis of the data reveals that, for utilities (water, electricity, and telephone), households in the poorest quintile spent significantly more, as a share of expenditure, than those in the wealthiest quintile.

For example, for quintile 1 households, electricity accounted for a hefty 7.3% of monthly household operational expenses, com- pared to only 4.3% for quintile 5 households.
Water Bahamian households spent 0.8% of their mean monthly consumption expenditure on water (Table 8-17).

The pro- portion was as high as 10% in Region 2 and as low as 0.2% in Region 4.

Households in the lowest consumer quintile spent an average of 1.3% of their mean monthly outlay on water, as compared to 0.5 % in the highest quintile.

As Table 8-15 shows, households’ mean monthly out- lay on water was considerably lower in Region 4 (B$3.87) than in any other region.
It was about one-third of the out- lay in Region 3 and less than one-fifth that spent in Re- gions 1 and 2.

The highest consumer quintiles spent more than did the lowest.

Electricity Electricity accounted for 5.3% of mean monthly expendi- ture.

In Region 3, the percentage was 4.1%, compared to 5.7% for Region 4.
Households in the lowest consumer quintile spent 7.3 cents out of every consumption dollar TABLE 8-15 Mean Monthly Expenditure on Utilities and Services (B$) Region or quintile All Bahamas Region 1 2 3 4 Quintile Utility Service Water Electricity Telephone Sewerage Garbage collection 83340_155-174 3/31/05 9:30 PM Page 166 166 | BAHAMAS LIVING CONDITIONS SURVEY 2001 TABLE 8-16A Mean Monthly Expenditure on Shelter Costs and Real Property Tax (B$) Tenure type Mortgage type Region or quintile All Bahamas Region 1 2 3 4 Quintile Rent 498.58 507.82 391.74 468.00 337.63 284.81 394.30 454.19 473.22 688.81 Both types 938.83 950.09 789.52 700.04 658.86 473.55 553.76 612.00 688.12 1,439.94 Private mortgage Gov’t.-guaranteed mortgage Property tax Mean monthly exp.
TABLE 8-16B Expenditure on Shelter Costs and Real Property Tax as Percentage of Total Monthly Expenditure Region or quintile All Bahamas Region 1 2 3 4 Quintile Rent 23.55 23.86 20.43 20.44 18.32 25.03 25.33 23.53 22.69 22.42 Both types 25.14 25.27 23.55 23.16 20.28 31.86 24.77 20.72 22.71 28.44 Tenure type Mortgage type Private mortgage Gov’t.-guaranteed mortgage Property tax 83340_155-174 3/31/05 9:30 PM Page 167 HOUSING VARIABLES FOR POLICY FORMULATION | 167 r e h t O 2 0 6 .
5 6 5 .

6 4 9 .

9 0 6 .

.

1 9 0 1 6 0 0 .

3 4 .

3 2 4 5 .

7 2 7 .

2 6 8 .

l a e R y t r e p o r p x a t 6 1 .

0 0 2 0 .

3 0 0 .

0 0 0 .

0 0 0 .

0 0 0 .

2 0 0 .

3 0 0 .

3 1 .

0 5 3 .

 ) $ ( .
.

o m l a t o T .

7 2 4 2 .

1 4 4 2 .

3 5 2 2 8 5 2 2 .

6 5 .

1 2 3 1 .

6 2 0 2 5 2 .

1 3 .

2 2 4 7 2 2 .

8 1 .

5 2 5 0 0 .

5 0 0 .

6 0 0 .

2 0 0 .

1 0 0 .

3 0 0 .

6 0 0 .

6 0 0 .

6 0 0 .

5 0 0 .

7 0 0 .

8 0 0 .

0 0 0 .

0 0 0 .

3 0 0 .

6 0 0 .

4 1 .

0 6 0 0 .

9 0 0 .

3 0 0 .

5 3 .

3 9 1 .


3 9 1 .

4 7 3 .

4 8 2 4 .

3 2 4 .

3 7 .

3 6 8 2 .

1 2 .

3 5 3 .

3 5 2 5 .

3 2 5 .

3 5 5 .

9 0 4 .

0 7 5 .

9 2 7 .

7 5 5 .

7 0 6 .

6 8 4 .

2 3 .

4 3 8 0 .

8 2 .

3 3 0 0 0 4 .

.

1 7 6 2 3 8 0 .

6 9 0 .

5 6 0 .

1 2 0 .

6 2 .

1 3 0 .

1 3 9 0 .

9 7 0 .

4 5 0 .

8 3 .

4 3 .

1 5 7 2 .

5 9 6 2 .

5 2 8 2 .

6 5 4 2 4 6 7 2 .

9 3 .

4 3 1 3 .

6 3 .

2 5 6 3 4 6 9 3 .

6 7 2 4 .

2 6 2 4 .

8 8 7 3 .

6 0 9 3 .

8 1 .


9 3 4 7 7 3 .

5 1 .

9 3 4 4 2 4 .

8 9 5 2 .

.

3 7 9 2 .

3 4 0 3 7 8 .

3 3 8 3 .

6 3 8 1 .

3 3 7 8 7 2 .

.

4 5 4 2 3 0 .

1 2 .

1 0 8 6 9 2 , .

0 4 7 6 0 , 3 .

4 6 0 6 5 2 , .

5 8 4 5 3 , 2 .

1 5 9 8 0 2 , 6 1 .

4 7 3 , 1 6 1 .

8 2 9 , 1 .

1 4 4 8 4 2 , .

1 4 8 9 7 2 , .


2 9 2 9 3 , - 8 E L B A T 83340_155-174 3/31/05 9:30 PM Page 168 168 | BAHAMAS LIVING CONDITIONS SURVEY 2001 on electricity, whilst those in the wealthiest quintile spent 4 cents for every dollar.
Table 8-15 indicates that Region 2 households spent more on electricity than those in the other three regions.

Region 3 had the lowest mean monthly outlay for elec- tricity, B$90.14, compared to B$144.3 in Region 2.

Households in quintile 5 spent significantly more on elec- tricity (B$175.3) than did any other quintile; household in the two lowest quintiles spent about 60% of what those in the highest quintiles spent.
Telephone Service The mean monthly expenditure on telephone service was B$96.55 (3.4 cents for every consumer dollar spent by Ba- hamian households).

Data from Tables 8-15 and 8-17 in- dicate that Region 2 households spent more (B$109.06 per month) on telephone service than did households in any other region.

This amount, however, represented 4.2% of their total monthly expenditure.

In Region 4, households spent B$90.32 (about 4.3% of their monthly expenditure) on telephone service.
Region 4 households spent 4.2–4.4 cents out of every consumption dollar on telephone service, compared to 3.2 cents for Region 1 households.

Households in the highest quintile spent the most (B$126.36), about 3.4% of total consumption expendi- ture.

On the other hand, households in the lowest quintile had a mean monthly expenditure of B$64.79, which was equivalent to 4.2% of these households’ monthly outlay.
Sewerage and Garbage Collection Across all regions and quintiles, waste disposal cost house- holds less than 1 cent per dollar of mean monthly expen- diture.

This finding is not surprising, given that 79.6% of households had their garbage collected free of charge by the Government, and only 16.2% used a private collection service.

Similarly, only 12.7% of households were linked to a sewerage system, thereby incurring a sewerage cost.
Since, in most cases, the sewerage bill was included with the water bill, it is likely that many households overlooked the distinction and reported the entire bill as water.

Con- sequently, expenditure on sewerage services was negligible for all households.

According to Table 8-17, shelter costs accounted for 61.1% of household operating expenditure and 24.3% of total consumption expenditure.

Region 1 households spent a higher proportion on shelter costs than did house- holds in any other region.
Households in the lowest quin- tile spent 66.9% of household operating costs for shelter (26.1% of total consumption expenditure), whilst house- holds in the highest quintile spent 60.2% (25.2% of total consumption expenditure).

Table 8-16A shows that, across The Bahamas, the mean expenditure paid by renters was B$498.58.

House- holds in the highest quintile spent more than twice what those in the lowest quintile spent on rent (B$688.81 ver- sus B$284.81).
The mean mortgage expenditure for households was B$938.83; this amount varied between B$950.09 and B$658.86 across the four regions.

Region 1 households spend 20% more than the next highest region.

House- holds in the lowest quintile had a mean mortgage expense of B$473.55, compared to B$1,439.94 for those in the wealthiest quintile.

Tables 8-16A and B illustrate, home owners had access to both private and Government-guaranteed mortgages.
Owners with private mortgages spent nearly twice as much as those with Government-guaranteed mortgages (B$1,032.15 versus B$544.02 per month).

The gap be- tween the two groups was slightly narrower (about 1.4 times) in Regions 2 and 3.

In the poorest quintile, owners with Government-guaranteed mortgages paid more than those with private mortgages.

However, this finding may have resulted from the small number of observations in the sample.
Table 8-16A also shows that the amount of Gov- ernment-guaranteed mortgages varied little between re- gions or quintiles.

This could reflect the cap on the amount of these loans.

Bahamian households spent 24.3 cents out of every consumption dollar on mortgage or rent (Table 8-17).

Re- gion 1 households spent the highest proportion (24 cents per consumption dollar).
In addition, households in the poorest quintile spent a higher proportion of their con- sumption dollars on mortgage or rent (26.13 cents per dollar) than did any other quintile.

Shelter Costs: Mortgage and Rent Along with real property tax, shelter costs—mortgage and rent—accounted for the highest percentage of expenditure on household operations across all regions and quintiles.

Real Property Tax Expenditure on property tax, as a percentage of total household consumption, was less than 1% (Table 8-17).
Households in the highest quintile had a mean monthly 83340_155-174 3/31/05 9:30 PM Page 169 tax of B$23.26 (0.35% of expenditure); those in the low- est quintile paid none.

This is the result of exemptions based on property values, income qualifications, and level of compliance with tax regulations.2 SELECTED INDICATORS Durable Goods Ownership To analyse differences between households, it is useful to describe the availability of certain assets to households.
Consequently, the BLCS examined household ownership 2 See Real Property Tax Act, Sections 3 and 39.

HOUSING VARIABLES FOR POLICY FORMULATION | 169 of 22 consumer durable goods (Table 8-18).

Survey results showed that ownership of durable goods was largely a func- tion of tenure type and how common certain goods were, rather than wealth (Table 8-19).

Of the 22 items examined, 11 were consistently amongst the 10 most commonly owned (Table 8-20).
Only two items, freezer and water heater, were not common to the top 10 for all regions and quintiles.

Television ranked first across all regions and quin- tiles, except for Region 3 and the lowest quintile, where it ranked third and second, consecutively.

In the poorest quin- tile and in Region 3, the stove ranked first.

The fan enjoyed a high degree of ownership in all regions and quintiles.
More than 52% of households in quintile 5 owned a per- TABLE 8-18 Percentage Distribution of Durable Goods Ownership, by Region and Quintile Item Television Fan Stove Refrigerator Car or truck Microwave oven Tape player/ CD player Video player/ DVD player Washing machine Water heater Air conditioner Personal computer Vacuum cleaner Freezer Camera/ Video camera Bicycle Lawnmower Video game (Sony, Nintendo) Clothing dryer Sewing/knitting machine Boat Motorcycle/scooter All Bahamas Region Quintile 57.4
94.0 78.8 72.7 75.5 84.3 74.2 65.6 59.0 54.3 57.4 41.8 52.5 47.9 30.8 38.2 23.7 28.0 17.7 33.3 20.8 11.2 1.5 83340_155-174 3/31/05 9:30 PM Page 170 170 | BAHAMAS LIVING CONDITIONS SURVEY 2001 TABLE 8-19 Percentage Distribution of Consumer Durables Ownership Consumer status None owned One or more owned Characteristic All Bahamas Region 1 2 3 4 Quintile Tenure Type Owned Private rented Gov’t.
rented Rent-free Squatted Other sonal computer, compared to only 3.6% in quintile 1.

Wealthier households were more likely to own cars or trucks than poorer ones; these durable goods ranked second in the highest quintile and seventh in the poorest.

Ranking of the washing machine was probably affected by wide accessibil- ity of laundromats in most urban areas; this item ranked tenth overall, and tenth in Region 1 in the highest and two lowest quintiles.
Ownership of durable goods was not an ideal indicator of level of well-being since many households, even in the higher quintiles, occupied rented quarters where durables were included in the rent.

When classified by type of tenure (Table 8-19), it was found that 1.1% of owner-occupied households and 12.7% of renter households owned no consumer durables.

A further 19.8% of households who claimed to be squatters and another 4.8% of households with undetermined tenure owned no durable goods.
Housing Quality Index The variables used to measure housing stock (type of dwelling, construction material of outer walls, toilet facil- ities, water supply, lighting, kitchens, and tenure type), combined in a simple summary HQI, provided a useful tool for comparing housing conditions across regions and quintiles.
The HQI, a simple average of the percentage of households meeting stated standards, included living in TABLE 8-20 Ranking of the 10 Most Commonly Owned Durable Goods, by Region and Quintile Item Television Fan Stove Refrigerator Car or truck Microwave oven Tape player/CD player Video player/DVD player Water heater Washing machine Freezer Bahamas overall — 1 1 2 4 3 — Region Quintile 2 1 4 2 3 6 7 5 10 8 9 3 3 4 1 2 5 8 6 10 — 9 7 4 1 2 3 4 8 6 5 10 — 9 7 1 2 3 1 4 7 5 6 8 — 10 9 2 — 10 9 3 1 2 3 4 6 5 7 9 10 8 — 4 1 2 4 3 5 6 7 10 8 8 — 5 1 3 6 4 2 5 7 8 9 10 — 83340_155-174 3/31/05 9:30 PM Page 171 HOUSING VARIABLES FOR POLICY FORMULATION | 171 TABLE 8-21 Housing Quality Index, by Region Indicator Detached units Walls of concrete block/slab Exclusive use of flush toilets Indoor running water Electricity for lighting Exclusive room as kitchen Level of crowding Ownership of dwelling unit Garbage collection Total HQI Bahamas overall 63.4 71.4 89.5 88.0 96.0 92.4 90.0 57.8 95.7 744.2 82.7 1 60.7 73.6 90.0 89.2 96.6 93.0 89.6 55.0 97.5 745.2 82.8 Region detached units, dwellings with walls made of concrete, ownership of dwellings, access to indoor running water, access to electricity, exclusive use of flush toilet inside the dwelling, level of crowding, exclusive use of kitchens, and garbage
 collection (Tables 8-21 and 8-22).
Nationwide, households scored relatively high, with in- dices for all regions above 80% and only those households in the two lowest quintiles scoring below 80% (68.8% and 78.7%, respectively).

Individual components of the HQI varied somewhat.

Such items as “Ownership of Dwelling Unit” and “Detached Unit” had indices of 57.8% and 63.3%, respectively; whilst “Electricity for Lighting,” “Exclusive Room as Kitchen,” “Garbage Collection,” and “Level of Crowding” all had indices above 90%.
The sin- gle detached dwelling (index of 63.3) will likely continue to decline in percentage share, as successive censuses have shown that the townhouse or condominium continues to gain in popularity.
TABLE 8-22 Housing Quality Index, by Quintile Indicator Detached unit Walls of concrete block/slab Exclusive use of flush toilets Indoor running water Electricity for lighting Exclusive room as kitchen Level of crowding Ownership of dwelling unit Garbage collection Total HQI 1 71.3 42.6 71.0 61.5 84.8 88.1 61.4 46.4 91.7 618.9 68.8 2 66.3 57.6 88.6 82.4 94.4 92.0 82.2 50.6 94.6 708.6 78.7 Quintile 83340_155-174 3/31/05 9:30 PM Page 172 172 | BAHAMAS LIVING CONDITIONS SURVEY 2001 TABLE 8-23 Percentage Distribution of Crowding, by Region and Quintile Persons per bedroom Fewer than 1.0 1.0–1.9 2.0–2.9 3.0–3.9 4 or more All Bahamas 22.9 47.6 19.6 6.0 4.0 Region Quintile Housing conditions are closely related to a group’s pur- chasing power; households in the lowest quintile, whose average monthly expenditure on housing costs was B$1,374, had a HQI of only 69; whilst those in the high- est quintile, with an average monthly expenditure of B$4,393, had an HQI of 86.
Several variables contributed to the lower index in the poorest quintile.

“Indoor Running Water” measured only 62 in the poorest quintile and was almost 21 points below the next lowest quintile; “Level of Crowding” also measured more than 20 points lower than the index for the next quintile.
The poorest quintile also scored lowest on “Walls of Concrete Block/Slab” and “Ownership of Dwelling Unit.” Overcrowding According to the BLCS, overcrowding,3 another indicator of housing needs, was present in 10% of dwelling units.

Whilst only 0.5% in the highest quintile, it was 38.6% in the lowest.
As Table 8-23 shows, 22.9% of households na- tionwide had fewer than one person per bedroom, 70.5% accommodated fewer than two persons per bedroom, and 90% accommodated fewer than three persons per bed- room.

Overcrowding was more prevalent in Region 1, where 10.4% of households had three or more persons per bedroom (the range of overcrowding for the other three regions was 5.9–8.3%).

Level of crowding by quintile provides a more mean- ingful description of the overcrowding problem.
House- holds in the poorest quintile experienced significantly 3 Overcrowding is defined as having three or more persons per bedroom more crowding (a level of 38.6%) than those in any other group.

Households in the second poorest quintile also re- ported significant levels of overcrowding, with a mean of 17.8%.

By contrast, the wealthiest and second wealthiest quintiles had crowding levels of less than 1% and 4.1%, respectively.
SUMMARY OF FINDINGS The BLCS found that most Bahamian households occu- pied separate detached houses; however, in the two major population centres of Region 1, apartment dwellers com- prised a significant percentage of households.

Overall, dis- tinct variations in housing types were observed between Region 1 and the other three regions.
Structural variations were related to standard of living, as dwelling types occu- pied by households in the wealthiest quintile differed markedly from those in the other four quintiles.

The propensity to occupy a single detached unit decreased as level of wealth increased.

With regard to the types of materials used to construct outer walls, the wealthiest and poorest quintiles differed significantly.
In quintile 5, 81% of dwelling units were made of concrete block or slab, compared to only 43% in quintile 1, which were more likely made of wood or stucco.

In terms of tenure type, households in the poorest quintile had the lowest percentage of owner-occupied dwellings and the highest percentage of rented and rent- free dwellings.

Substandard housing generally lacks one or more of the following: piped water, private flush toilet, and private shower or bath.
Survey data showed that slightly more 83340_155-174 3/31/05 9:30 PM Page 173 than 12% of dwellings lacked piped water, whilst 10.5% lacked exclusive use of a flush toilet.

Amongst quintiles, more than 96% of households in the wealthiest quintile lived in dwelling units with run- ning water, compared to only 62% of those in the poorest quintile.
With regard to the HQI, quintile 1 households had an HQI of 61.52 for indoor running water, compared to 96 for quintile 5 households and 87.98 for the nation overall.

Similarly, whilst more than 98% of households in the wealthiest quintile used a flush toilet, only 76% of those in the poorest quintile did; a further 19% used a pit latrine and as many as 2% had no facility.

These data raise the question of how best to expand water supply and san- itary services to households in this group.
The Survey found that quintile 1 households spent pro- portionately more consumption dollars on water, electric- ity, and telephone services than did quintile 5 households.

Whilst the total mean monthly expenditure for wealthy households was B$4,393, poor households spent less than one-third of that amount; however, they spent more than 7% of consumption dollars on electricity and 4% on tele- phone services, compared to 4% and 3%, respectively, spent by wealthy households.
Finally, households in the wealthiest quintile had more than 42% of consumer dol- lars available to spend on such amenities as health, educa- tion, transportation, and entertainment; compared to only 27% of those in the poorest quintile (see chapter 3).

HOUSING VARIABLES FOR POLICY FORMULATION | 173 THE CHALLENGES AHEAD As the above findings show, action is urgently needed to achieve universal coverage for water supply and sanitary services.
In addition, research is needed to determine the condition of housing stock to ensure its acceptability for occupancy (the Survey found that an average of 15% of housing units—and nearly 33% in some areas— were more than 30 years old).
Moreover, given the Government’s stated aim to ensure that many more Bahamians can afford to buy their own homes, policies must be implemented to reduce mortgage-loan rates and borrowing costs.4 In this regard, efforts must also be made to keep the price of construction materials and housing amenities at affordable levels.

Finally, the biggest challenge is ensuring that the country’s housing programmes adequately meet the population’s changing needs.

REFERENCES Gleick, P.H.

1996.


“Basic Water Requirements for Human Ac- tivities: Meeting Basic Needs.” Water International 21: 83–92.

4 See Our Plan 2002, p. 47.

83340_155-174 3/31/05 9:30 PM Page 174 83340_175-188 3/31/05 9:36 PM Page 175 Technical Appendix Leona Wilson A.

SURVEY DESIGN AND METHODOLOGY The Bahamas Living Conditions Survey (BLCS) 2001 aimed at obtaining information on house- holds throughout the country.
These included household expenditure on food and non-food items, use of health facilities and social pro- grammes, and general characteristics of the pop- ulation.

It is expected that the data gathered will provide a general picture of the conditions under which Bahamians live.

In particular, it will pro- duce a poverty line with which to estimate that proportion of the population or households un- able to afford the basic necessities for living.
The Survey aimed at just over 2000 house- holds, randomly selected throughout the country.

Selected households were interviewed by specially trained interviewers over a month-long period.

Survey Design The frame for the survey design was based on data from the 2000 Census,1 which provided in- 1 See Commonwealth of the Bahamas: Report of the 2000 Census of Population and Housing.
Department of Statistics, Ministry of Economic Development, Nassau, 2002. formation on the number of households in the country at Enumeration District (ED) level, conditions of the dwelling units, and basic pop- ulation characteristics (e.g., age, sex, education, and economic activity).

The ED was the smallest area used in the collection of Census data and formed an integral part of the survey design.
Certain areas (mainly cays) were excluded from the survey frame: EDs 01, 09, 14, and 15 (South Abaco); EDs 01, 02, and 03 (Exuma); and Berry Island and Ragged Island.

Addition- ally, EDs 01, 02, and 03 (Shirlea) and EDs 01 and 02 (Delaporte), both located in New Provi- dence, were excluded.
Sample Size and Methodology The islands were first grouped by size: Group 1 (New Providence and Grand Bahama), Group 2 (Abaco, Andros, and Eleuthera [including Har- bour Island and Spanish Wells]), Group 3 (Ex- uma and Long Island), and Group 4 (remaining or Other Family Islands).

Household groups or clusters were to be interviewed in the various EDs selected from each of the four groups.
175 83340_175-188 3/31/05 9:36 PM Page 176 176 | BAHAMAS LIVING CONDITIONS SURVEY 2001 Because of cost constraints and other difficulties associ- ated with data collection, particularly in the Family Is- lands, it was agreed that large, workable cluster sizes of 20–25 households would be more effective in reducing the number of primary sampling units or EDs to be visited.

In addition, it was necessary to keep the cluster sizes as close as possible to reduce the sampling error.
Two-stage Design The design consisted of two stages of selection: 1) Primary Sampling Unit (PSU) and 2) Ultimate Sampling Unit (USU) or the cluster of households to be interviewed.

The PSUs (EDs) were selected with probability proportional to size; that is, the number of households in the ED at the time of the Census.

The design also took into account the need to make statements about the groups and the larger islands amongst the first two groups.
Therefore, each of these was given at least 220 households, including 10% for non-response.

This means that the sampling fraction var- ied by group.

An estimate of the number of households to be sur- veyed was assigned to each group of islands, taking into consideration the criterion mentioned above.

Initially, Group 1 was assigned approximately 1,100 households; Group 2, 660; Group 3, 220; and Group 4, 220.

How- ever, at the completion of the design, these figures had changed slightly.
The proportion of persons 15 years and older, with four years of high-school education or higher, was used to arrange the EDs within supervisory districts in each of the islands.

The EDs were arranged in descending order of these proportions.
Each group was allocated a number of clusters deter- mined by the number of households in the group, the sampling fraction to be used, and an initial approximate cluster size in order that the desired number of households in the survey for each group, as indicated above, could be achieved.

EDs were assigned clusters based on their size or the number of households in the ED.
To allocate the cluster assigned to a group among the EDs, the number of households in each ED was divided by the average cluster size for the group.

This number was rounded up or down to the nearest whole number.

These, when summed, had to equal the total number of clusters assigned to the group.

For example, Group 4 (Other Fam- ily Islands) had 1,979 households.

A sample of 1 in 9 would yield 220 households.


The total of 1,979 house- holds would result in 81 clusters, with an average size of 24.4 households.

Assignment of Clusters and Sampling Fractions Group 1: Total number of clusters, 3,660.

A sampling fraction of 1/60 will yield 61 clusters, with an average size of 20.0 households or approximately 1,220 households.

Group 2: Total number of clusters, 312.


A sampling frac- tion of 1/13 will yield 24 clusters, with an average size of 27.6 households or approximately 662 households.

Group 3: Total number of clusters, 72.

A sampling frac- tion of 1/8 will yield 9 clusters, with an average size of 25.0 households or approximately 225 households.

Group 4: Total number of clusters, 81.

A sampling frac- tion of 1/9 will yield 9 clusters, with an average size of 24.4 households or approximately 226 households.
Thus, the total number of households expected to be interviewed for the BLCS was about 2,334.

This number may have varied because of changes that occurred in EDs between the time of the Census and the Survey (e.g., in- crease or decrease in households) and because the sam- pling interval was fixed.

Before selecting the households for the sample, EDs were systematically selected within each group.
This was done by accumulating the number of clusters in the EDs and placing the cumulated number next to the ED (Table A-A1).

A random number was selected between 1 and the inverse of the sampling fraction of the group that was be- tween 1 and 60, 1 and 13, 1 and 8, and 1 and 9 for the re- spective groups.

The inverse of the sampling fraction was the sampling interval.
The sampling interval was added to the randomly selected number; the process was repeated until the number of clusters for the group was reached (but not exceeded).

In the case of Group 1, the random number selected was 27.

With an interval of 60, this meant that clusters 27, 87, 147, 207, etc.

were selected.

The EDs within which these clusters fell became a selected ED.
For example, in Group 1 (New Providence and Grand Bahama), EDs with # were selected EDs because clusters 27, 87, 147, 207, and 267 fell within these EDs.

During the second stage of the design (selection of the USU [households to be interviewed]), the same procedure was used to select households within EDs, with the interval 83340_175-188 3/31/05 9:36 PM Page 177 TABLE A-A1 Systematic Selection of Enumeration Districts Group ED no.

% 15 pop.

with 4 years high school No.

HHs No.
clusters assigned Cumulated clusters EDs selected RS 27 New Providence Yamacraw Malcolm Creek # # # # # 83340_175-188 3/31/05 9:36 PM Page 178 178 | BAHAMAS LIVING CONDITIONS SURVEY 2001 being the number of clusters assigned to the ED.
For ex- ample, in ED 10601 of Yamacraw, the number of clusters assigned was 6 because there were 111 households (Table A-A1).

The randomly selected number between 1 and 6 was 4, therefore households 4, 10, 16, 22, 28, 34, 40, 46, 52, 58, 64, 70, 76, 82, 88, 94, 100 and 106 were selected.

(It should be noted that, if 6 were added to 106, then household 112 would have become eligible for interview- ing; however, that would exceed 111—that is, there was no household 112.
If the listing of the ED were done as re- quired while the survey was being carried out, and there were now 115 households, then household 112 would have become eligible for being selected and interviewed.)

Sampling Errors The BLCS sampling design is self-weighting.

This means that the probability of a household being selected is the same for all households in the population, which, in effect, means a fixed sampling interval for all strata.

The sampling fraction differs for each strata (group).
At the time of the design, preliminary Census data were available and the undercount adjustment was taken into consideration.

In hindsight, the undercount adjustment was not necessary in several areas of Group 1 (New Provi- dence and Grand Bahama); hence, the discrepancies were between what the design said should be found and what was actually found on the ground.

Adjustments had to be made prior to adjustments for legitimate non-response.
Of the total planned questionnaires, 1,881 were ana- lyzed, indicating a non-response rate of 15.4% from dwellings identified from the listing exercise and 18.6% required by the design.

An analysis of the reasons for non- response showed that the majority of cases resulted from vacant/demolished dwellings (36.5%).

Other factors were refusals (33.3%) and rejects at the data-cleaning stage TABLE A-A2 Non-response Distribution (3.5%).

Table A-A2 shows the distribution of non- response.
To preserve the self-weighting nature of the sample, ad- justment factors were applied at the ED level for non- responses.

The adjustment factor is the total number assigned under the self-weighting design, divided by the number of dwellings for which data are finally accepted for analysis (the underlying assumption of this method is that both the non-responding and responding households have similar features): Adjustment factor Sampling fraction for each stra- tum X (no.
assigned dwellings no.

dwellings accepted for analysis).

Estimation Procedures The formulae for estimating the sample mean and its vari- ance are described below.
Estimator of Total The estimator of a given total Y for a given subpopulation A is YA h i jA w hijyhij where: sample PSU, 1 nh unit of analysis or element, 1 - A estimated total for variable Y in subpopulation A YA h substratum within the estimation domain: 1 4 i j A subset of elements possessing a given attribute; that is, belonging to a given subpopulation A (e.g., persons within a given age group) yhij w hij observed value of the variable “y” for the j-th element of the i-th sample PSU in substratum h final (adjusted) sampling weight for the element, including all stages of selection Stratum Design planned Identified in listing Vacant, closed, or demolished Refusal Other Rejected during data cleaning I II III IV Total Total 174 114 26 28 342 83340_175-188 3/31/05 9:36 PM Page 179 Estimator of Variance for Total Under the ultimate clusters approach, the variance of an estimator of total for a given subpopulation A, within any domain of estimation is estimated by (YA) YAhi n h 1 nh 2 Y A n h where: YAhi YAh jA w i jA w hijyhij hijyhij Other notation is as previously defined.
Estimator for a Proportion (p) For a proportion (e.g., households with a given character- istic, such as poverty), Ph whph where: ph proportion of households with the given character- istics (i.e., in stratum # (group) h wh fh Fh F*h F*hnh / F*hnh sampling fraction for stratum (group) h 1/ fh Fh adjusted for non-response Fh number of households selected number of households interviewed nh number of elements (households) TABLE A-B1 Island Deflators Used, BLCS 2001 TECHNICAL APPENDIX 179 | Variance of Proportion Variance of a proportion is expressed as: Var (Ph) wh ( h) p 1 2(1 fh) .
Ph (n ) 1 h B.

OTHER TECHNICAL CONSIDERATIONS Construction of an Annualized Consumption Data Set Household Expenditures were collected in Sections 4, 7, 8, and 11.

Section 4 relates to Housing and Utilities, Section 7 to Health Expenditures, Section 8 to Education Expenditures, and Section 11 to Food and Non-food Expenditures and Consumer Durables.
To calculate the total consumption expenditure figure, the consumption data (for those sections not already quoted by the householders on an annual basis) were an- nualized and the parts were summed.

Deflators The expenditure aggregates were calculated at the prices faced by the household.

To allow for comparisons across households, island deflators (New Providence 100) were compiled (Table A-B1).

The annual household consumption was grouped un- der nine commodity groups and two food subgroups.
Island Water bill Electricity bill Telephone bill All other items Item group New Providence Grand Bahama Abaco Acklins Andros Bimini Cat Island Eleuthera Spanish Wells Harbour Island Exuma Inagua Long Island San Salvador 83340_175-188 3/31/05 9:36 PM Page 180 180 | BAHAMAS LIVING CONDITIONS SURVEY 2001 Table A-B2 shows the items included in each commodity group and subgroup.
Annualized Expenditure Data Set The annualized expenditure data is given in the STATA dataset AGGREGATES.dta.

Table A-B3 lists and briefly describes the variables.
Identification Variables The identification variables were edno, hhid, stra- tum, quintile, decile, and factor in the STATA file “aggregates.” STATA Data Sets One STATA data set was usually created for each page of the questionnaire, except for Consumption: Food Ex- penses at Home (Section 11B) and Consumption: Non- Food Expenses (Section 11C), where one data set was created for the entire section (because the same questions were asked for all items in the section).
The two questions for the Other Income Sources (Section 10) were on one page; however, question 1 was a household- level question and question 2 was an individual- level question.

Therefore, Section 10 has two data sets (Table A-B4).

TABLE A-B2 Items Included in Commodity Groups and Subgroups, BLCS 2001 Group/subgroup Commodity Groups 1.

Food and beverages 1a.

Food at home 1b.

Food away from home 2.

Housing 2a.

Rent-imputed rent 2b.


Utilities, household fuels, repairs and maintenance to house, yard 2c.

Household linens and supplies 3.

Durable goods 4.

Health and personal care 5.

Clothing and footwear 6.

Education 7.

Transportation 8.

Recreation 9.

Other consumption Subgroups (under food at home) 1.

Cereals 2.

Starchy fruits/roots/tubers 3.

Sugars and syrups 4.

Legumes 5.

Vegetables 6.

Fruits 7.

Food from animals 8.

Fats and oils 9.


Other food at home Section and item codes Section 11B: See below for items Section 11A Section 4 Section 4, Section 11C: Items 201–203, 249, 268 Section 11C: Items 214–216, 226, 236–239, 241–244 Section 11D Sections 7B, 7C, Section 11C: Items 209, 211–213, 271 Section 11C: Items 217–219, 221–225, 227–228 Section 8C Section 11C: Items 204–207, 234, 248 (trans.

related to health care) (trans.
related to education) Section 11C: Items 208, 229, 231–233, 235, 245–247, 253–254, 257, 267, 269 Section 11C: Items 261, 265–266 Section 11B Items 11–19 Items 67, 74, 76, 91–93, 98 Items 81–87, 89, 102, 104–106 Items 64, 83 Items 61, 63, 65–66, 68–69, 71–73, 75, 77, 81–82, 95 Items 54–59, 62, 78–79, 101 Items 21–29, 31–39, 47–49, 51–53, 99 Items 41–46, 88 Items 94, 96–97, 103, 107 83340_175-188 3/31/05 9:36 PM Page 181 TABLE A-B3 Contents of Dataset AGGREGATES.dta, BLCS 2001 Variable Description Variable Description 1. edno 2. weight 3.
Hhid 4. stratum 5. island 6.

Fgrp1 7.

Fgrp2 8.

Fgrp3 9.

Fgrp4 10.

Fgrp5 11.

Fgrp6 12.

Fgrp7 13.

Fgrp8 14.

Fgrp9 15.

Age 16.

Fhh 17. marital 18. national 19.

Noo_4 20. no5_14 21. no15_19 22. no20_34 23. no35_54 24. no55_64 25. no65ov 26. no0_14 27. no15_64 28. agedep 29. totdep 30. hhsize 31.

Shh 32.
Fact_per 33. grp01_1 34. grp01_2 35. grp02a_1 36. grp02a_2 37. grp02b_1 38. grp02b_2 39. grp02b_3 40. grp02b_4 41. grp02b_5 42. grp02b_6 Enumeration District Number Household Weight Household Identification Number Region Island Cereals Starchy fruits/roots/tubers Sugars and syrups Legumes Vegetables Fruits Food from animals Fats and oils Other food at home Age of head Female headed household Head’s marital status Head’s nationality Number of persons aged 0–4 Number of persons aged 5–14 Number of persons aged 15–19 Number of persons aged 20–34 Number of persons aged 35–54 Number of persons aged 55–64 Number of persons aged 65 and over Number of persons aged 0–14 Number of persons aged 15–64 Age dependency ratio: (no0_14no65ov)/no15_64 Total dependency ratio: (no0_14no65ov)/hhsize Household Size Single Person Household factor*hhsize Annual Food at Home Expenditure Annual Food Away From Home Expendiure Annual Rent Expenditure Annual Imputed Rent Expenditure Annual Garbage Collection Expenditure Annual Water Bill Annual Sewerage Bill Annual Electricity Bill Annual Telephone Bill Annual Repair & Maintenance to House and Yard Expenditure 43. grp02c_1 Annual Household Operation Expenditure 44. grp02c_2 45. grp03_1 46. grp03_2 47. grp04_1 48. grp04_2 49. grp04_3 50. grp04_4 51. g01 52. g02a 53. g02b Annual Household Linen and Supplies Expenditure Annual Durable Goods Current Consumption Expenditure (if purchased 12 months or more ago) Annual Durable Goods Current Consumption Expenditure (if purchased
 less than 12 months ago) Annual Personal Care Expenditure Annual Outpatient Health Expenditure Annual Inpatient Health Expenditure Annual Health Insurance Expenditure Annual Food Expenditure (grp01_1 grp01_2) Annual Rent-Imputed Rent Expenditure (grp02a_1 grp02a_2) Annual Utilities Bill (grp02b_1grp02b_2grp02b_3 grp02b_4grp02b_5grp02b_6) 54. g02c Annual Household Operation, 55. g02 56. g03 57. g04 58. g05 59. g06 60. g07 61. g08 62. g09 63. consumption
 64. con_pc 65. deflator 66. pwat_index 67. pele_index 68. ptel_index 69. rcon_pc 70. decile 71. quintile 72. tcon_pc 73. rtcon_pc Linens and Supplies Expenditure (grp02c_1grp02c_2) Annual Housing Expenditure (g02ag02bg02c) Annual Durable Goods Current Expenditure (grp03_1grp03_2) Annual Health Expenditure (grp04_1grp04_2grp04_3grp04_4) Annual Clothing and Footwear Expenditure Annual Education Expenditure Annual Transportation Expenditure Annual Recreation Expenditure Other Consumption Expenditure Total Annual Consumption Expenditure Annual Per Capita Consumption Expenditure Regional Price Deflator Regional Price Index for Water Bill Regional Price Index for Electricity Bill Regional Price Index for Telephone Bill Real Annual Per Capita Consumption Expenditure Per Capita Population Decile Per Capita Population Quintile Annual Per Capita Consumption Trimmed by Top and Bottom 1% Real Annual Per Capita Consumption Trimmed by Top and Bottom 1% 83340_175-188 3/31/05 9:36 PM Page 182 TABLE A-B4 Data Sets, BLCS 2001 Data set Description AGGREGATES.DTA CONSUMPTION.DTA DEFLATOR.DTA DEMO.DTA HEADS.DTA POVERTY.DTA QUINTILES.DTA S00.DTA S01A1.DTA S01A2.DTA S01B.DTA S02.DTA S03.DTA S04.DTA S041.DTA S042.DTA S043.DTA S05.DTA S06.DTA S07.DTA S07A.DTA S07B1.DTA S07B2.DTA S07C.DTA S08A.DTA S08A1.DTA S08A2.DTA S08A3.DTA S08B.DTA S08C.DTA S08C1.DTA S08C2.DTA S09A.DTA S09A.DTA S09B.DTA S09C.DTA S09D.DTA S101.DTA S102.DTA S11A.DTA
 S11B.DTA S11C.DTA S11D.DTA SNU00.DTA SNU12.DTA SNU13.DTA SNU14.DTA Annualized Consumption Data Annualized Consumption Data Island Deflator Household Characteristics Head of Household Characteristics Poverty Characteristics (by household) Quintiles (by household) Cover Data: Household Questionnaire I Section 1A: Respondents ID Code Section 1A: Listing of Individuals Who Might Be Household Members Section 1B: Household Roster Section 2: Parents of Household Members Section 3: Migration Section 4: Housing
 (S041, S042, S043 combined) Section 4: Housing (Part 1) Section 4: Housing (Part 2) Section 4: Housing (Part 3) Section 5: Access to Community Facilities Section 6: Access to Social Programmes Section 7: Health (S07A, S07B, S07C combined) Section 7A: Health: Self Reported Health Status Section 7B: Health: Health Care Utilization Expenditures (Part 1) Section 7B: Health: Health Care Utilization Expenditures (Part 2) Section 7C: Health: Insurance Coverage Section 8A: Education: School Attendance and Completion (S08A1, S08A2, S08A3 combined) Section 8A: Education: School Attendance and Completion (Part 1) Section 8A: Education: School Attendance and Completion (Part 2) Section 8A: Education: School Attendance and Completion (Part 3) Section 8B: Education: School Expenses Section 8C: Education: National School Lunch Programme (S08C1, S08C2 combined) Section 8C: Education: National School Lunch Programme (Part 1) Section 8C: Education: National School Lunch Programme (Part 2) Section 9A: Employment and Income: Labour Force Participation Section 9A: Employment and Income: Labour Force Participation Section 9B: Employment and Income: Employment in the Past 12 Months Section 9C: Employment and Income: Wage Employment Earnings Section 9D: Employment and Income: Self-Employment Earnings Section 10: Other Income Sources (question 1) Section 10: Other Income Sources (question 2) Section 11A: Consumption: Meals Away From Home Section 11B: Consumption: Food Expenses At Home
 Section 11C: Consumption: Non-Food Expenses Section 11D: Consumption: Durable Goods Cover Data: Household Questionnaire II Section 12: Child Health Section 13: Reproductive Health Section 14: Anthropometry 83340_175-188 3/31/05 9:36 PM Page 183 TECHNICAL APPENDIX 183 | Tabulation Programme STATA tabulation programmes (do files) were created to produce tables for each of the chapters in the report.
Estimation of Consumption Expenditure Aggregates The estimation of aggregates using BLCS data were straightforward and followed established procedures for consumption expenditure aggregation.

Table A-B5 lists the variables used in the construction of the consumption aggregates, while Table A-B6 shows how each aggregate was estimated.

Quintiles and Deciles The quintiles and deciles were formed from the sample household members after arranging them in ascending or- der of per-capita household expenditure.
Dividing the to- tal household expenditure by the number of household members results in the per-capita expenditure.

All mem- bers of the household were assumed to have the same per- capita expenditure.
The decile classification of households TABLE A-B5 Variables Used To Construct Consumption Expenditure Aggregates, BLCS 2001 Section 4 7B 7C Variable s04213 s04214 s04219 s04220 s04222 s04223 s04227 s04228 s04339 s04341a s04341b s04345a s04345b s07b113a2 s07b113b2 s07b113c2 s07b113d2 s07b113e2 s07b113f2 s07b113g2 s07b114 s07b116a s07b116b s07b220 s07b223 s07b226 s07b229 s07b230 s07c34 s07c34 Description Amount of last water bill Months covered by last water bill Amount of last sewerage bill Months covered by last sewerage bill Amount of last electricity bill Months covered by last electricity bill Amount of last telephone bill Months covered by last telephone bill Estimate rent paid for the dwelling (if not rented) Amount paid for rent Time period for rent paid Amount paid for garbage collection Time period for garbage collection Amount paid for outpatient visits (public hospital) Amount paid for outpatient visits (public clinic) Amount paid for outpatient visits (private hospital) Amount paid for outpatient visits (private doctor, clinic) Amount paid for outpatient visits (private allied health professional) Amount paid for outpatient visits (foreign) Amount paid for outpatient visits (traditional medicine) Transportation related to outpatient visits Amount paid for medicines (public facility) Amount paid for medicines (private facility) Amount paid for inpatient visits (public hospital) Amount paid for inpatient visits (public clinic) Amount paid for inpatient visits (private hospital) Amount paid for
 inpatient visits (foreign) Transportation related to inpatient visits Amount paid per month for medical insurance Amount paid per month for dental insurance (continues) 83340_175-188 3/31/05 9:36 PM Page 184 184 | BAHAMAS LIVING CONDITIONS SURVEY 2001 TABLE A-B5 (Continued) Section 8B 11A 11B 11C 11D Variable Description s08b20a s08b20b s08b20c s08b20e s08b20f s08b20g s08b20h s08b22a s08b22b s08b22c s08b22e s11a02 s11a04 s11a06 s11a06 s11b04 s11b05 s11b06 s11b07 s11b06 s11c04 s11c06 s11d02a s11d02b s11d06 Amount
 paid for school expenses (tuition) Amount paid for school expenses (extra classes) Amount paid for school expenses (transportation) Amount paid for school expenses (uniforms) Amount paid for school expenses (books) Amount paid for school expenses (other supplies) Amount paid for school expenses (room and board) Amount received for school tuition and fees (government) Amount received for school tuition and fees (private school) Amount received for school tuition and fees (private company) Amount received for school tuition and fees (non-profit organization) Value of breakfasts outside the home Value of lunches outside the home Value of dinners outside the home Value of beverages and snacks outside the home Number of months in past 12 months that purchase food item How spent in typical month on food item Number of months in past 12 months that consumed home produced food item Value of consumption in typical month of home produced food Value of food gifts in past 12 months Amount spent on item in past 12 months Value of item received as gift (12 months) Number of years had durable good Number of months had durable good (if less than 3 years) Estimated current market value of durable good is shown in the STATA data set with label “aggregates.” Each quintile comprises two deciles (e.g., quintile 1 com- prises deciles 1 and 2) (Table A-B7).
The quintiles and deciles are comprised of an equal number of household members, not an equal number of households.

Twenty-three households were ignored in the analysis of variables according to quintiles or deciles be- cause they either had too much expenditure data missing or abnormally high, health-outpatient expenditure.

The standard errors were compiled for the mean per- capita consumption estimates at Region 1 (New Provi- dence and Grand Bahama) prices.
Mean Household Composition Table A-B9 presents the standard errors of the estimates of mean household size; and number of adult males, adult fe- males, and children.

Standard Errors Estimates of Mean Per-capita Consumption The mean per-capita consumption expenditure and its stan- dard error were compiled for the four regions (Table A-B8).

Tests Of Significance Difference in Means in Two Regions The broad principles in testing the means obtained from two samples (regions) are described below.
83340_175-188 3/31/05 9:36 PM Page 185 TECHNICAL APPENDIX 185 | TABLE A-B6 Estimation of Consumption Expenditure Aggregates, BLCS 2001 Aggregate Estimation Annual Food at Home Expenditure Annual Food Away From Home Expenditure Annual Rent Expenditure Annual Imputed Rent Expenditure Annual Garbage Collection Expenditure Annual Water Bill Annual Sewerage Bill Annual Electricity Bill Annual Telephone Bill Annual Repair & Maintenance to House and Yard Expenditure Annual Household Operation Expenditure Annual Household Linen and Supplies Expenditure Annual Durable Goods Current Consumption Expenditure (if purchased 12 months or more ago) Annual Durable Goods Current Consumption Expenditure (if purchased less than 12 months ago) Annual Personal Care Expenditure Annual Outpatient Health Expenditure Annual Inpatient Health Expenditure Annual Health Insurance Expenditure Annual Food Expenditure Annual Rent-Imputed Rent Expenditure Annual Utilities Bill Annual Household Operation, Linens and Supplies Expenditure Annual Housing Expenditure Annual Durable Goods Current Expenditure Annual Health Expenditure Annual Clothing and Footwear Expenditure Annual Education Expenditure Annual Transportation Expenditure Annual Recreation Expenditure Other Consumption Expenditure For each item in Section 11B calculate:{[(s11b04 s11b05) 9s01b06 s01b07)] 12} s11b08, then aggregate over the items From each individual in household calculate: (s11a02 s11a04 s11a06 s11a08)
 12, then aggregate over individuals Question s04341 annualized Question s04339 annualized Question s04344 annualized Question s04213 annualized Question s04219 annualized Question s04222 annualized Question s04227 annualized Question s11c04 for items 201– 203, 268, 249 Question s11c04 for items 214–216, 226, 236, 252 Question s11c04 for items 237–239, 241–244 For each item in Section 11D calculate: s11d06 (discount rate inflation rate depreciation rate) then aggregate over
 items For each item in Section 11D calculate: [s11d06 (discount rate inflation rate depreciation rate)]/ 12 s11d02b, then aggregate over items Question s11c04 for items 209, 211–213, 271 For each individual and item, annualize and aggregate For each individual: (s07b220 s07b223 s07b227 s07b229), then aggregate over individuals For each individual and item, annualize and aggregate (grp01_1 grp01_2) (grp02a_1 grp02a_2) (grp02b_1grp02b_2grp02b_3grp02b_4grp02b_5grp02b_6) (grp02c_1grp02c_2) (g02ag02bg02c) (grp03_1grp03_2) (grp04_1grp04_2grp04_3grp04_4) Question s11c04 for items 217–219, 221–225, 227–228 For each individual, calculate (s08b20a s0b20b s08b20e s08b20f s08b20g s08b20h s0s0b22a s08b22b s08b22c s08b22d), then aggregate over individuals Question s11c04 for items 204–207,234, 248, plus for the household aggregate individual [(s07b114 x13) s07b230 s08b20c] Question s11c04 for items 208, 229, 231–233, 235, 245–247, 253–254, 257, 267, 269 Question s11c04 for items 261, 265–266 83340_175-188 3/31/05 9:36 PM Page 186 186 | BAHAMAS LIVING CONDITIONS SURVEY 2001 TABLE A-B7 Definition of Quintiles and Deciles, Showing Per-capita Expenditure Ranges TABLE A-B9 Per-capita expenditure ($) Mean and Standard
 Error of Household Size and No.
of Adult Males, Adult Females, and Children, BLCS 2001 Quintile Decile From To Variable Mean infinity Sample Size 1,881 Household size Adult males Adult females Total adults Number of children 3.49 1.12 1.27 2.39 1.10 Standard error Standard error (%) 0.10 0.03 0.03 0.05 0.06 2.89 2.89 2.67 2.28 5.28 Hypothesis The hypothesis in testing for significance is that there is no difference in the means of the populations from which the two samples were selected.
If it is known that the standard deviations of the two populations are equal, it will test whether these two samples came from the same population.

This hypothesis, also called the “null” hypothesis, states that the difference in the population means is zero, although there is some observed difference in the sample means.

Assumptions The assumptions involved in the test were that 1) the two samples are independent and 2) the population distribu- tions are approximately normal.
Results of the tests of significance are shown in Table A-B10.

Data Cleaning The previous section described the expenditure compo- nents at aggregate level, which were estimated for the BLCS.

However, calculation of these components was complex.

In general, expenditure variables were collected at a highly disaggregated level, mainly to facilitate more accurate estimates of expenditure.

Prior to estimating the expenditure aggregates, three issues had to be taken into account.
First, because the variables collected in the questionnaire related to various reference periods, stan- dardization (i.e., expressing all variables on a consistent annual basis) was needed.

Second, outliers had to be identified and re-estimated across the sample.

Third, missing values of the variables had to be re-estimated, where appropriate.

TABLE A-B8 Number in Sample, Mean, and Standard Error of Estimates of Per-capita Consumption, by Region; BLCS 2001 Region Sample HHs (no.)

Mean cons.
Mean cons.

($) Standard error (%) 1 (New Providence and Grand Bahama) 2 (Abaco, Andros, and Eleuthera) 3 (Exuma and Long Island) 4 (Other Family Islands) All Bahamas 929 515 198 187 1,829 14,999.59 11,033.89 10,416.56 9,069.69 14,292.74 4.2 4.1 6.9 5.6 2.9 83340_175-188 3/31/05 9:36 PM Page 187 TECHNICAL APPENDIX 187 | TABLE A-B10 Results of Tests of Significance, by Region, BLCS 2001 (mean per-capita consumption) Region Sample size (N) Mean cons.
($) Standard error % 9.2 7.3 9.2 15.4 9.2 10.4 7.3 15.4 7.3 10.4 15.4 10.4 ($) 1,374.80 924.60 1,374.80 1,893.24 1,374.80 1,127.19 924.60 1,893.24 924.60 1,127.19 1,893.24 1,127.19 Diff.

in means ($) Standard error of diff.


($) t-statistic P  t  2,256.77 1,656.79 2,591.78 2,339.75 4,124.07 1,777.81 335.01 2,106.95 1,867.30 1,457.89 1,532.29 2,203.39 1.36 1.11 2.32 0.16 1.28 0.70 0.1760 0.2710 0.0220 0.8740 0.2030 0.4880 Standardization For many variables, the standardization process was trivial because they had already been quoted by respondents on an annual basis.
For example, all the education expenses were collected for “the last 12 months.” In other cases, the reference period was less than a year; therefore, responses had to be converted into an annual basis (e.g., expenditure on meals away from home, where expenditure was quoted for the “past 30 days”).

While most of the annualization calculations were straightforward, the annual flow of ser- vices (use values) from consumer durables was calculated on the basis of estimated depreciation rates.
The deprecia- tion rates were estimated with straight-line deprecation for the 90th percentile year of acquisition for the item.

Treatment of Outliers After the variables had been standardized, they could then be compared across households.

This meant that it was now possible to search for any outliers that may have been present amongst these standardized variables.

Outliers were deemed as those observations lying more than three standard deviations above or below the mean value.
The search for outliers was made at either the ED level (e.g., rents paid), or item level (e.g., food at home items).

Fur- thermore, for expenditure variables considered likely to depend on household size (such as food at home and non- food items), the search for outliers was based on per- capita, rather than household, level of the variables.

Any outliers were replaced with the mean, median, or pre- dicted value, depending on which was deemed the typical value.
Treatment of Zero and Missing Observations The stages of the calculations discussed earlier relate ex- clusively to situations in which respondents reported a value for a variable.

However, two types of non-response to questions may occur, which generally appear in the data sets as missing observations.

The first type of non-response arises when a respondent is either unable or unwilling to answer a particular question or when the data-entry oper- ator fails to enter the data for a particular question.
This may be interpreted as a genuine missing value.

The second type of non-response occurs when a question is not appli- cable and, given the skip pattern of the questionnaire, is not posed.

In the case of monetary variables, this is best in- terpreted as a zero value.

It is highly desirable that genuine missing values be re- estimated to enable all aggregates to be estimated (includ- ing zero values) for all households.
The re-estimate used was the mean, median, or predicted value of the standardized 83340_175-188 3/31/05 9:36 PM Page 188 188 | BAHAMAS LIVING CONDITIONS SURVEY 2001 variable in the ED in question, these typical values being calculated at the commodity level where considered appro- priate.

As with outliers, for those expenditures deemed likely to depend on household size, the re-estimate used was the mean, median, or predicted per-capita value, multiplied by the size of the household in question.
FOR FURTHER READING _______.

2000b.

How To Plan a Survey.

ASA Series.

Alexandria, VA: American Statistical Association.

_______.

2000c.

What Is a Survey?

ASA Series.

Alexandria, VA: American Statistical Association.

Freund, R., and W. Wilson.

2002.

Statistical Methods.

2nd ed.

San Diego: Academic Press.

Scheaffer, R., W. Mendenhall, and L. Ott.

1995.

Elementary Survey Sampling.

Pacific Grove, CA: Duxbury Press.

ASA.

2000a.

How To Collect Survey Data.

ASA Series.


Alexan- dria, VA: American Statistical Association.

Yates, Frank.

1987.

Sampling Methods for Censuses and Surveys.

3rd ed.

New York: Oxford University Press.

83340_189-192 3/31/05 9:41 PM Page 189 ABOUT THE AUTHORS Arneta D. Clarke is maternal and child health/family planning coordinator with the Commonwealth of The Bahamas’ Ministry of Health.
During her 27-year tenure as a nurse with the Ministry, she has also served as supervi- sor of public health community clinics.

Her re- search has focused on establishing a women’s health centre in The Bahamas.

She received a master’s degree in health administration from Western Connecticut State University in 2000.
Brenda Y. Coakley is senior planner with the Commonwealth of The Bahamas’ Ministry of Education, where she serves as researcher, inter- national representative, and liaison with interna- tional organizations.

During her 30-year tenure with the Ministry, she has held key leadership positions in secondary-school supervision and administration and teacher training throughout The Bahamas.
Her current research centers on decentralization of Government-maintained schools, education and technology, and gender and equity.

She received a doctorate in educa- tional theory and policy from The Pennsylvania State University in 1997.

Sandra C. Adderley-Coleby is senior nursing of- ficer in the Department of Public Health within the Commonwealth of The Bahamas’ Ministry of Health.

Since 2000, she has been responsible for nursing administration of all public health clinics in New Providence.
Previously, she super- vised Family Island clinics.

Her research has centered on the effects of frequent travel on the children of informal commercial importers, hy- pertension, and satisfaction of clinic customers.

She received a master’s degree in business ad- ministration from the University of Miami in 1995.

Camille S. Deleveaux is epidemiologist in the Commonwealth of The Bahamas’ Ministry of Health, where she has been employed since 1989.
Prior to her current posting, she served as statistician within the Ministry.

In her current position, she is responsible for technical and 189 83340_189-192 3/31/05 9:41 PM Page 190 190 | BAHAMAS LIVING CONDITIONS SURVEY 2001 editorial support for various research activities, compila- tion of health statistics, data analysis and management, and report writing.

She received her master’s degree in epi- demiology from the University of Texas in 2000.
Jaikishan Desai is senior associate with Family Health In- ternational, a nonprofit research organization based in North Carolina.

His current research centers on youth and women’s health.

In 2001–2004, he was lead consultant for the first-ever survey of living conditions in The Bahamas.

For two years, he served as poverty advisor to the Ministry of Planning and Finance, Government of Mozambique.

In addition, he has consulted for the World Bank, FAO, UNDP, and the Government of Nigeria.
He received his doctorate in economics from the University of North Car- olina at Chapel Hill in 1992.

Kelsie Dorsett is deputy director of the Department of Statistics within the Commonwealth of The Bahamas’ Ministry of Finance, where she also heads the Social Statis- tics Division.

During her tenure at the Department, she has served as census officer, census coordinator, and su- pervisor of the Household Survey Section.
She received her master’s degree in sociology, with specialization in de- mography, from the University of Western Ontario, Canada.

She co-authored National Census Report: The Bahamas, a monograph of The Bahamas 1990 Census.

She will soon embark on a study of The Bahamas’ elderly population.

William J.

Fielding is director of planning in the Office of Research, Planning, and Development at The College of The Bahamas in Nassau.
Prior to joining The College in 2001, he was biometric advisor at Pakhribas Agricultural Centre in Nepal.

He has 18 years of research experience in the Caribbean region.

He holds a master’s of philosophy in statistics and is a charted statistician.

His publications include Potcake or Dog Welfare in The Bahamas, to be published by Purdue University Press in 2004.
Carmen Gomez is senior deputy director of statistics in the Department of Statistics within the Commonwealth of The Bahamas’ Ministry of Finance.

Her principal du- ties center on the management of national census-taking and administration.

She is the co-author of National Census Report: The Bahamas 1990–1991 Population and Housing Census of the Caribbean (CARICOM), as well as several unpublished analytical reports.

She received her bachelor’s degree in economics from the University of the West Indies.
Sudhanshu Handa is associate professor in the Depart- ment of Public Policy at the University of North Carolina at Chapel Hill.

Previously, he served as social development specialist at the Inter-American Development Bank (2000–2003) and lecturer in economics at the University of the West Indies (1993–1997).

His current research fo- cuses on the optimal design of poverty alleviation pro- grams and the performance of alternative techniques for evaluating program impacts.
He received his doctorate in economics from the University of Toronto in 1993.

Portia E. Johnson (deceased) was statistician in the De- partment of Statistics within the Commonwealth of The Bahamas’ Ministry of Finance.

She had primary responsi- bility for conducting the first-ever survey of living condi- tions in The Bahamas.

Previously, she worked for the Central Bank of The Bahamas and The Ministry of Tourism.
She held a bachelor’s degree in business admin- istration from Bryant College in Smithfield, Rhode Island.

Jessica Minnis is senior lecturer in sociology and chairper- son of the School of Social Sciences at The College of The Bahamas in Nassau, where she has been employed for the past 24 years.

She obtained ADB status in sociology from York University, Canada and a master’s degree from the University of Northern Colorado.
Her current research centers on human responses to marine protected areas as a function of pre-existing sociocultural conditions.

Adelma L. Penn is director of food and nutrition in the Department of Public Health of the Commonwealth of The Bahamas’ Ministry of Health, where she has been em- ployed for the past 25 years.

Her current research focuses on evaluation of the National School Lunch Programme, promotion of dietary guidelines, and dietary management of chronic non-communicable disease.
She holds a mas- ter’s degree in public health nutrition from the University of Tennessee, Knoxville, and has extensive postgraduate training.

In 2002, she received the Health Hero Award from the Pan American Health Organization.

Susan J. Plumridge is psychology lecturer at The College of The Bahamas in Nassau.
Prior to joining the College in 83340_189-192 3/31/05 9:41 PM Page 191 ABOUT THE AUTHORS 191 | 1999, she served as professor at Lakehead University and psychometrist at The Lakehead Regional Family Centre.

She holds a master’s degree in clinical psychology.

Recent publications include Reactions of American Tourists to Roaming Dogs in New Providence, The Bahamas, published by Anthrozoös in 2003.
Melissa Underwood is nutritionist in the Department of Public Health of the Commonwealth of The Bahamas’ Ministry of Health.

In this capacity, she helped to re- search, develop, and promote the first national dietary guidelines, launched in 2002.

Her research includes school health, child obesity, and nutrition counseling and - intervention.

Previously, she taught nutrition in Trinidad and Tobago.
In 1999, she completed graduate coursework in nutrition science from Florida International University, where earned a bachelor’s of science degree in 1997.

Leona Wilson is assistant director and division head of the Economic Statistics Division within the Department of Statistics of the Commonwealth of The Bahamas’ Min- istry of Finance.
Before beginning her tenure with the De- partment, she obtained her bachelor’s degree in economics from the University of the West Indies, and subsequently earned a master’s of business administration from Nova Southeastern University.

83340_189-192 3/31/05 9:41 PM Page 192 83340_193-194 3/31/05 9:45 PM Page 193 83340_193-194 3/31/05 9:45 PM Page 194