DHS METHODOLOGICAL 

REPORTS 25

Consistency of Reporting 

of Terminated Pr egnancies 

in DHS Calendars

SEPTEMBER 2018

This publication was produced for review by the United States Agency for International Development. It was prepared by 

Kerry L.D. MacQuarrie, William Winfrey, Jacqueline Meijer-Irons, and Anne Roback Morse.

DHS Methodological Reports No. 25 

Consistency of Reporting of Terminated Pregnancies 

in DHS Calendars 

Kerry L. D. MacQuarrie1,2

William Winfrey1

Jacqueline Meijer-Irons3

Anne Roback Morse4

ICF 

Rockville, Maryland, USA 

September 2018 

1

 Avenir Health 

2

 The DHS Program 

3

 Independent Consultant 

4

 Pennsylvania State University 

Corresponding author: Kerry L. D. MacQuarrie, ICF, 530 Gaither Road, Suite 500, Rockville, MD 

20850, USA; phone: +1 301-407-6500; fax: +1 301-407-6501; email: kerry.macquarrie@icf.com 
Acknowledgments: The authors gratefully acknowledge Thomas Pullum, ICF, and our numerous 

contemplative conversations that influenced this study’s analytic strategy. We also appreciate Kristin 

Bietsch, Avenir Health, for her thoughtful comments on an early draft.

Editor: Bryant Robey 

Document Production: Natalie Shattuck 

This study was carried out with support provided by the United States Agency for International 

Development (USAID) through The DHS Program (#AID-OAA-C-13-00095). The views expressed are 

those of the authors and do not necessarily reflect the views of USAID or the United States Government. 

The DHS Program assists countries worldwide in the collection and use of data to monitor and evaluate 

population, health, and nutrition programs. Additional information about The DHS Program can be obtained 

from ICF, 530 Gaither Road, Suite 500, Rockville, MD 20850 USA; telephone: +1 301-407-6500, fax: 

+1 301-407-6501, email: info@DHSprogram.com, internet: www.DHSprogram.com. 

Recommended citation: 

MacQuarrie, Kerry L. D., William Winfrey, Jacqueline Meijer-Irons, and Anne Morse. 2018. Consistency 

of Reporting of Terminated Pregnancies in DHS Calendars. DHS Methodological Reports No. 25. 

Rockville, Maryland, USA: ICF. 
iii 

CONTENTS 

TABLES ........................................................................................................................................................ v 

FIGURES .................................................................................................................................................... vii 

PREFACE .................................................................................................................................................... ix 

ABSTRACT.................................................................................................................................................. xi 

1 INTRODUCTION .............................................................................................................................. 1 

1.1 Background ......................................................................................................................... 1 

1.1.1 Recalling terminated pregnancies .......................................................................... 1 

1.1.2 Underreporting of terminated pregnancies ............................................................ 2 

1.1.4 Improving reporting through calendar methods ..................................................... 5 

1.2 DHS Calendar ..................................................................................................................... 6 

1.2.1 History of the DHS calendar .................................................................................. 6 

1.2.2 Collecting birth, termination, and pregnancy information in the DHS calendar ..... 7 

2 METHODS ..................................................................................................................................... 15 

2.1 Calendar Data and Survey Characteristics ....................................................................... 15 

2.2 Period of Observation ....................................................................................................... 19 

2.3 Measures .......................................................................................................................... 20 

2.3.1 Termination ratio .................................................................................................. 20 

2.3.2 Other measures ................................................................................................... 21 

2.4 Analytic Strategy ............................................................................................................... 21 

2.4.1 Within-survey consistency ................................................................................... 21 

2.4.2 Between-survey consistency ............................................................................... 21 

2.4.3 Classification by survey characteristics ............................................................... 22 

3 PATTERNS OF TERMINATION RATIOS IN SINGLE SURVEYS................................................ 23 

3.1 Observing Patterns of Termination Ratios in Single Surveys ........................................... 23 

3.1.1 Patterns of termination ratios in Asia ................................................................... 23 

3.1.2 Patterns of termination ratios in Africa ................................................................. 27 

3.1.3 Patterns of termination ratios in Latin America and the Caribbean ..................... 36 

3.1.4 Patterns of termination ratios in Other Countries ................................................. 41 

3.2 Testing Within-Survey Consistency .................................................................................. 46 

4 TRENDS IN TERMINATION RATIOS ACROSS MULTIPLE SURVEYS ..................................... 51 

4.1 Models of Between-Survey Consistency and Between-Survey Inconsistency ................. 51 

4.2 Pattern 1: Inconsistent Surveys with No Evidence of Secular Trend ............................... 53 

4.3 Pattern 2: Consistent Surveys with No Evidence of Secular Trend .................................. 61 

4.4 Pattern 3: Consistent Surveys with Evidence of Secular Trend ....................................... 62 

4.5 Pattern 4: Inconsistent Surveys with Evidence of Secular Trend ..................................... 64 

4.5.1 Increasing termination ratios over time ................................................................ 64 

4.5.2 Decreasing termination ratios over time .............................................................. 67 

4.6 Testing Between-Survey Consistency .............................................................................. 69 

5 COMPARING WITHIN-SURVEY AND BETWEEN-SURVEY CONSISTENCY ............................ 77 

 
iv 

6 CONSISTENCY OF THE REPRODUCTIVE CALENDAR BY SURVEY CHARACTERISTICS .. 83 

6.1 Classification of Survey Consistency ................................................................................ 83 

6.2 Consistency in Termination Ratios and Type of History ................................................... 85 

6.3 Consistency in Termination Ratios and Direction of History ............................................. 85 

6.4 Consistency in Termination Ratios and Questions Distinguishing Pregnancy 

Outcome ............................................................................................................................ 86 

6.5 Consistency in Termination Ratios and Mode of Data Collection ..................................... 86 

6.6 Consistency in Termination Ratios and Survey Length .................................................... 87 

6.7 Consistency in Termination Ratios and DHS Phase ........................................................ 87 

7 DISCUSSION AND CONCLUSIONS ............................................................................................ 89 

REFERENCES ............................................................................................................................................ 93 

APPENDICES ............................................................................................................................................. 99 
v 

TABLES 

Table 2.1 Survey characteristics of DHS surveys with reproductive calendars ................... 16 

Table 3.1 Measures of consistency within single surveys ................................................... 47 

Table 4.1 Measures of consistency between consecutive surveys ..................................... 70 

Table 5.1 Comparison of within-survey consistency and between-survey consistency 

measures ............................................................................................................. 77 

Table 5.2 Summary counts of within-survey, between-survey, and overall 

classification of consistency, by region ................................................................ 81 

Table 6.1 Consistency classification of surveys................................................................... 83 

Table 6.2 Consistency of surveys by type of history ............................................................ 85 

Table 6.3 Consistency of surveys by direction of reporting in the history ............................ 85 

Table 6.4 Consistency of surveys by questions distinguishing miscarriage and 

induced abortion................................................................................................... 86 

Table 6.5 Consistency of surveys by mode of data collection ............................................. 86 

Table 6.6 Consistency of surveys by length of survey ......................................................... 87 

Table 6.7 Consistency of surveys by DHS phase ................................................................ 88 

Appendix Table A.1 List of surveys by type of history and consistency classification ......................... 99 

Appendix Table A.2 List of surveys by direction of reporting in the history and consistency 

classification ....................................................................................................... 101 

Appendix Table A.3 List of surveys by questions that distinguish miscarriage and induced 

abortion and consistency classification .............................................................. 103 

Appendix Table A.4 List of surveys by mode of data collection and consistency classification......... 105 

Appendix Table A.5 List of surveys by length of survey and consistency classification .................... 107 

Appendix Table A.6 List of surveys by DHS phase and consistency classification ........................... 109 

vii 

FIGURES 

Figure 1.1 Sample birth history in the DHS-7 Model Questionnaire .............................................. 8 

Figure 1.2 Reproductive calendar in the DHS-7 Model Questionnaire ......................................... 9 

Figure 1.3 Sample questions on terminated pregnancies in the DHS-7 Model Questionnaire ... 11 

Figure 1.4 India 2015-16 DHS questionnaire and reproductive calendar with survey-specific 

questions distinguishing miscarriage, induced abortion, and stillbirth ....................... 13 

Figure 2.1 Study period of observation ........................................................................................ 20 

Figure 3.1 Ratios of terminated pregnancies to live births (per 100) in DHS calendars, Asia .... 24 

Figure 3.2 Ratios of terminated pregnancies to live births (per 100) in DHS calendars, Africa .. 28 

Figure 3.3 Ratios of terminated pregnancies to live births (per 100) in DHS calendars, 

Latin America and the Caribbean ............................................................................... 37 

Figure 3.4 Ratios of terminated pregnancies to live births (per 100) in DHS calendars, 

Other Countries .......................................................................................................... 42 

Figure 4.1 Model of consistent calendars with level ratios of terminations to live births 

over time (Country A) and increasing ratios of terminations to live births over 

time (Country B) ......................................................................................................... 51 

Figure 4.2 Model of inconsistent calendars with level ratios of terminations to live births 

over time (Country C) and increasing ratios of terminations to live births over 

time (Country D) ......................................................................................................... 52 

Figure 4.3 Ratios of terminated pregnancies to live births (per 100) in consecutive DHS 

calendars, Indonesia .................................................................................................. 53 

Figure 4.4 Ratios of terminated pregnancies to live births (per 100) in consecutive DHS 

calendars, Philippines ................................................................................................. 54 

Figure 4.5 Ratios of terminated pregnancies to live births (per 100) in consecutive DHS 

calendars, Burundi ...................................................................................................... 54 

Figure 4.6 Ratios of terminated pregnancies to live births (per 100) in consecutive DHS 

calendars, Ethiopia ..................................................................................................... 54 

Figure 4.7 Ratios of terminated pregnancies to live births (per 100) in consecutive DHS 

calendars, Kenya ........................................................................................................ 55 

Figure 4.8 Ratios of terminated pregnancies to live births (per 100) in consecutive DHS 

calendars, Madagascar .............................................................................................. 55 

Figure 4.9 Ratios of terminated pregnancies to live births (per 100) in consecutive DHS 

calendars, Malawi ....................................................................................................... 56 

Figure 4.10 Ratios of terminated pregnancies to live births (per 100) in consecutive DHS 

calendars, Mali ........................................................................................................... 56

Figure 4.11 Ratios of terminated pregnancies to live births (per 100) in consecutive DHS 

calendars, Nigeria ....................................................................................................... 57 

Figure 4.12 Ratios of terminated pregnancies to live births (per 100) in consecutive DHS 

calendars, Rwanda ..................................................................................................... 57 

Figure 4.13 Ratios of terminated pregnancies to live births (per 100) in consecutive DHS 

calendars, Senegal ..................................................................................................... 57 

Figure 4.14 Ratios of terminated pregnancies to live births (per 100) in consecutive DHS 

calendars, Sierra Leone ............................................................................................. 58 

Figure 4.15 Ratios of terminated pregnancies to live births (per 100) in consecutive DHS 

calendars, Tanzania ................................................................................................... 58 
viii 

Figure 4.16 Ratios of terminated pregnancies to live births (per 100) in consecutive DHS 

calendars, Uganda ..................................................................................................... 58 

Figure 4.17 Ratios of terminated pregnancies to live births (per 100) in consecutive DHS 

calendars, Zambia ...................................................................................................... 59 

Figure 4.18 Ratios of terminated pregnancies to live births (per 100) in consecutive DHS 

calendars, Zimbabwe ................................................................................................. 59 

Figure 4.19 Ratios of terminated pregnancies to live births (per 100) in consecutive DHS 

calendars, Dominican Republic .................................................................................. 60 

Figure 4.20 Ratios of terminated pregnancies to live births (per 100) in consecutive DHS 

calendars, Egypt ......................................................................................................... 60 

Figure 4.21 Ratios of terminated pregnancies to live births (per 100) in consecutive DHS 

calendars, Jordan ....................................................................................................... 61 

Figure 4.22 Ratios of terminated pregnancies to live births (per 100) in consecutive DHS 

calendars, Guatemala ................................................................................................ 61 

Figure 4.23 Ratios of terminated pregnancies to live births (per 100) in consecutive DHS 

calendars, Nicaragua .................................................................................................. 62 

Figure 4.24 Ratios of terminated pregnancies to live births (per 100) in consecutive DHS 

calendars, Cambodia .................................................................................................. 63 

Figure 4.25 Ratios of terminated pregnancies to live births (per 100) in consecutive DHS 

calendars, Nepal ......................................................................................................... 63 

Figure 4.26 Ratios of terminated pregnancies to live births (per 100) in consecutive DHS 

calendars, Vietnam ..................................................................................................... 64 

Figure 4.27 Ratios of terminated pregnancies to live births (per 100) in consecutive DHS 

calendars, Honduras .................................................................................................. 64 

Figure 4.28 Ratios of terminated pregnancies to live births (per 100) in consecutive DHS 

calendars, Bangladesh ............................................................................................... 65 

Figure 4.29 Ratios of terminated pregnancies to live births (per 100) in consecutive DHS 

calendars, Ghana ....................................................................................................... 65 

Figure 4.30 Ratios of terminated pregnancies to live births (per 100) in consecutive DHS 

calendars, Lesotho ..................................................................................................... 66 

Figure 4.31 Ratios of terminated pregnancies to live births (per 100) in consecutive DHS 

calendars, Bolivia ....................................................................................................... 66 

Figure 4.32 Ratios of terminated pregnancies to live births (per 100) in consecutive DHS 

calendars, Colombia ................................................................................................... 67 

Figure 4.33 Ratios of terminated pregnancies to live births (per 100) in consecutive DHS 

calendars, Peru .......................................................................................................... 67 

Figure 4.34 Ratios of terminated pregnancies to live births (per 100) in consecutive DHS 

calendars, Benin ......................................................................................................... 68 

Figure 4.35 Ratios of terminated pregnancies to live births (per 100) in consecutive DHS 

calendars, Armenia ..................................................................................................... 68 

Figure 4.36 Ratios of terminated pregnancies to live births (per 100) in consecutive DHS 

calendars, Turkey ....................................................................................................... 69 
ix 

PREFACE 

The Demographic and Health Surveys (DHS) Program is one of the principal sources of international data 

on fertility, family planning, maternal and child health, nutrition, mortality, environmental health, 

HIV/AIDS, malaria, and provision of health services. 

One of the objectives of The DHS Program is to continually assess and improve the methodology and 

procedures used to carry out national-level surveys as well as to offer additional tools for analysis. 

Improvements in methods used will enhance the accuracy and depth of information collected by The DHS 

Program and relied on by policymakers and program managers in low- and middle-income countries. 

While data quality is a main topic of the DHS Methodological Reports series, the reports also examine 

issues of sampling, questionnaire comparability, survey procedures, and methodological approaches. The 

topics explored in this series are selected by The DHS Program in consultation with the U.S. Agency for 

International Development. 

It is hoped that the DHS Methodological Reports will be useful to researchers, policymakers, and survey 

specialists, particularly those engaged in work in low- and middle-income countries, and will be used to 

enhance the quality and analysis of survey data. 

Sunita Kishor 

Director, The DHS Program 

xi 

ABSTRACT 

This study examines the consistency of reporting of terminated pregnancies in DHS reproductive calendars. 

We examine two measures of consistency: within-survey consistency and between-survey consistency. We 

find that 70-80% of surveys are inconsistent by either or both of these measures. Reporting of terminated 

pregnancies deteriorates in earlier periods of the calendar. Africa has a higher proportion of inconsistent 

surveys (78%), whereas in the other regions about two-thirds of surveys are classified as inconsistent. 

Consistency appears to vary with type of history (pregnancy or birth), direction of the history, and the 

inclusion of questions that distinguish between miscarriage and induced abortion. Survey length and mode 

of data collection appear unrelated to either consistency or inconsistency of reporting terminated 

pregnancies. While previous studies have assessed DHS calendar data related to contraception, perinatal 

mortality, age displacement, and birth intervals, this study is believed to be the first to undertake a focused 

assessment of reporting of terminated pregnancies. Our findings suggest the need for more experimentation 

with modifications to the calendar and modes of data collection. Such modifications should be randomly 

assigned within or across surveys and accompanied by rigorous assessment. 

KEY WORDS: data quality, reproductive calendar, contraceptive calendar, terminated pregnancies, 

termination ratio, birth history 

1 

1 INTRODUCTION 

Retrospective inquiry in household or population-based surveys is a common way of gathering data on 

women’s reproductive behavior and experiences, including terminated pregnancies. This is particularly the 

case for experiences that are not well captured through service statistics, sentinel surveillance, or vital 

registration statistics. For example, it is estimated that only 2% of stillbirths globally—just one type of 

terminated pregnancy—are counted through vital registration (Lawn et al. 2010). Primary among household 

surveys are the Demographic Health Surveys (DHS), which have collected population and health data in 

more than 400 surveys in over 90 countries since the mid-1980s. The DHS has employed a reproductive 

calendar since 1986 to collect data on births, pregnancies, and episodes of contraceptive use. Although 

numerous studies have evaluated such a calendar with regard to the quality and consistency of numerous 

types of data, this is believed to be the first study examining the consistency of calendar data on terminated 

pregnancies. 

1.1 Background 

This study encompasses three types of terminated pregnancies: miscarriages, induced abortions, and 

stillbirths. The International Classification of Diseases defines a fetal death as “death prior to the complete 

expulsion or extraction from its mother of a product of conception, irrespective of the duration of 

pregnancy; the death is indicated by the fact that after such separation the fetus does not breathe or show 

any other evidence of life, such as beating of the heart, pulsation of the umbilical cord, or definite movement 

of voluntary muscles.” Stillbirth refers to a fetus that dies before birth but at or after 28 weeks of gestation 

or of greater than 1000 gms (WHO 2016). Miscarriage1

 is fetal death that occurs spontaneously prior to the 

28th week of gestation. As a practical matter, stillbirths are frequently differentiated from miscarriages 

based on their occurrence at or after 7 months of pregnancy. Induced abortion, meanwhile, refers to any 

conceptus that does not result in a live birth as the result of direct action taken with the intent to terminate 

the pregnancy. This study addresses such terminated pregnancies without differentiating among types of 

termination. 

Household surveys remain a common method to collect data on terminated pregnancies (miscarriages, 

induced abortions, and stillbirths) and other reproductive events. Surveys relying on retrospective reporting 

from the respondent, however, face a variety of obstacles when trying to accurately estimate the incidence 

and prevalence of terminated pregnancies. These include difficulties associated with accurate recall and 

willingness to report not only the occurrence of termination events, but also their timing. Incorporation of 

data collection techniques such as a reproductive events calendar into traditional survey instruments is 

designed to overcome some of these challenges, though further analysis of the quality and consistency of 

such instruments is warranted. 

1.1.1 Recalling terminated pregnancies 

Women’s diverse experiences of pregnancy termination affect whether women will recognize them, 

remember them, and report them in a survey. Events that set off other events are more likely to be 

 

1

 Miscarriage is sometimes also referred to as “spontaneous abortion,” “spontaneous fetal death,” “spontaneous fetal 

loss,” or “fetal wastage.” The term “pregnancy loss” may refer to either miscarriage or stillbirth. 
2 

remembered (Berntsen and Rubin 2002), and a terminated pregnancy that triggers a divorce, social censure, 

or continual health problems is therefore more likely to be remembered than one that does not. The longer 

the duration of any event, the more likely it is to be remembered (Belli 1998). A termination that is 

prolonged or requires a hospital stay is more likely to be remembered than one that does not. Similarly, 

terminations that are physically painful or that occur late in gestation are distinctly vivid. Conversely, some 

terminated pregnancies can be more ephemeral; most miscarriages occur very early in pregnancy (Macklon, 

Geraedts, and Fauser 2002; Nepomnaschy et al. 2006; Wang et al. 2003; Wilcox et al. 1988; Zinaman et al. 

1996). Women therefore are often uncertain whether they were pregnant and are unable to confidently 

identify the occurrence of a miscarriage (Casterline 1989; Edmonds et al. 1982; James 1970). A study in 

the U.S. found that women are more likely to report miscarriages in a survey if the loss occurred after five 

weeks gestation (Jones and Kost 2007). In contexts where regular menstruation has cultural importance, 

induced abortions also serve the function of “menstrual regulation” and often occur without ever confirming 

a pregnancy (Johnston et al. 2010). 

In addition, social processes affect whether a terminated pregnancy will be remembered or not. Cultural 

perceptions about the nature and importance of terminations influence whether women remember them. 

Memories are embedded within cultural norms about the salience and importance of the event, as well as 

what that event means for that person’s life trajectory (Belli 1998). In rural Gambia, for example, repeated 

miscarriages may spur a divorce (Bledsoe, Banja, and Hill 1998). 

Cultural scripts about terminated pregnancies also influence whether and how often they are discussed. 

Memories that people discuss or mentally revisit after their occurrence are better recalled than those that 

have no thematic place within a cultural framework or that people try actively to forget ever occurred 

(Berntsen and Rubin 2004). In rural Tanzania, for example, pregnancy losses may be discussed if the fetus 

was “mature,” but losses early in gestation are kept private, or are supposed to be discussed only within a 

close confidence (Haws et al. 2010). In Ethiopia, Amhara women believe a stillbirth should only be 

mourned privately, but Oromiya women believe that it should be mourned “like the death of an adult” (Sisay 

et al. 2014). These different social processes following a terminated pregnancy suggest different likelihoods 

for women across different societies to report it in a survey. 

1.1.2 Underreporting of terminated pregnancies 

Social desirability bias and reporting terminated pregnancies 

Even when women correctly recall a terminated pregnancy, reporting error in a survey can result from 

deliberate omission. Tourangeau and Yan (2007) argue that deliberate misreporting can be the “main source 

of error” for sensitive questions—those that are intrusive (they are inappropriate topics for polite 

conversation, “regardless of what the correct answer is”), that are a threat if disclosed (there would be 

negative consequences if the true answer became known to a third party), or that have socially desirable 

answers (social desirability can be viewed as a subset of the threat of disclosure, wherein the negative effect 

is social censure) (Tourangeau and Yan 2007). Questions about terminated pregnancies—particularly 

questions about induced abortion—clearly fall into the sensitive category in most settings. 

Women frequently omit induced abortion in surveys. A U.S. study compared women’s medical records of 

induced abortion with their responses in a survey and found that a maximum of 80% of induced abortions 

identified in medical records were reported in the survey (Udry et al. 1996). From estimates derived from 
3 

abortion providers, Jones and Forrest (1992) estimated that only between 35% to 59% of women reported 

their induced abortions, depending on the survey and the year. 

This underreporting of induced abortion is likely deliberate due to social desirability bias, and may be 

exacerbated in settings where induced abortion is illegal, stigmatized, or carries severe social consequences 

for women. Women’s reports of induced abortion increase as techniques to affirm anonymity or conceal 

their response from the interviewer are incorporated into surveys compared with surveys that require 

directly responding in a face-to-face interview (Fu et al. 1998; Juarez, Cabigon, and Singh 2010). Surveys 

that use the random response technique—where the interviewer does not know which of several questions 

the respondent is answering—also record higher rates of induced abortion compared with face-to-face 

interviews (Chow and Rider 1972; Chow, Gruhn, and Chang 1979; Tezcan and Omran 1981). 

Social desirability bias leads to different patterns of underreporting for different social groups. In Estonia, 

women were more likely to omit reporting an induced abortion if they were over age 40 or were ethnic 

Estonians (Anderson et al. 1994). Studies in the U.S. have found that women are less likely to report an 

induced abortion if they are nonwhite, have incomes below 200% of the poverty level, are unmarried, are 

Catholic, or live in the South (Fu et al. 1998; Jones and Forrest 1992; Jones and Kost 2007; Udry et al. 

1996). 

Although social desirability bias clearly reduces reporting of induced abortion, it is less clear the extent to 

which reporting of miscarriage or stillbirth may also be affected by social desirability bias. In the U.S., 

Jones and Kost (2007) found that women reported more instances of miscarriages and stillbirths in selfadministered survey responses than in face-to-face interviews. This finding suggests that social desirability 

bias curbs women’s propensity to report spontaneous abortion and stillbirths in a similar manner as it does 

for reports of induced abortion. 

Several qualitative studies in sub-Saharan Africa suggest that social scripts determine the pattern of social 

pressure to conceal miscarriages and stillbirths. Miscarriage may be stigmatized if it is perceived to be an 

indicator of infertility, the consequence of previously having had an induced abortion, or caused by 

malevolent spirits (Bledsoe, Banja, and Hill 1998; Haws et al. 2010; Sisay et al. 2014; van der Sijpt 2010). 

However, miscarriage generates less stigma when perceived as proof that a woman can get pregnant, as 

described in a rural Gambian study: “simply getting pregnant periodically, even if some of these pregnancies 

eventually go wrong, is a key sign that a marriage is on track” (Bledsoe, Banja, and Hill 1998). Such events 

trigger less social censure when they are perceived to be the result of biological forces outside of the 

woman’s control (Sisay et al. 2014; van der Sijpt 2010). Although the study of reporting miscarriages and 

stillbirths has been underdeveloped compared with the study of induced abortions (van der Sijpt 2010), the 

existing literature suggest that social desirability bias likely contributes to underreporting of miscarriages 

and stillbirths in surveys as well as underreporting of induced abortion. 

Misclassification of terminated pregnancies 

When women misreport induced abortions in surveys, they can either omit the pregnancy altogether, or 

report their induced abortion as a miscarriage. Social desirability bias may influence women to recast their 

experience with a terminated pregnancy as being a type of termination that is less stigmatized. In a U.S. 

study by Fu et al. (1998), women were asked about induced abortion during a face-to-face interview and 

again in a self-administered response format. Between 2%-5% of women who had reported a miscarriage 
4 

or ectopic pregnancy during the face-to-face interview changed their response to an induced abortion during 

the self-administered portion of the survey. Another study estimated that in Turkey a third of abortions that 

were reported in surveys as miscarriages had likely been induced abortions, on the basis of factors such as 

length of gestation before the abortion, contraceptive use preceding the pregnancy, reason for discontinuing 

contraception, and the wantedness of the pregnancy (Magnani, Rutenberg, and McCann 1996). 

Misreporting of induced abortions as miscarriages leads to overestimating miscarriages and 

underestimating induced abortions (Casterline 1989). 

Misclassification of terminations can occur from miscommunication or misunderstanding. For example, 

researchers in Tanzania encountered difficulties when English classifications of terminations did not 

translate clearly into Swahili. They found that respondents might use a word meaning “miscarriage” but 

give a narrative account that described a termination that occurred after seven months of gestation—a 

stillbirth (Haws et al. 2010). Similarly, Gambians classified terminations by the woman’s experience of the 

pregnancy loss and the health implications to the woman, rather than fetal age (Bledsoe, Banja, and Hill 

1998). Moreover, a woman may recount to the interviewer what she believes to be a true description of the 

event, but may have received incorrect information or misunderstood information from a medical provider. 

A study in Australia found discrepancies between women’s reports and administrative datasets by some 

women “misreporting a late spontaneous miscarriage or medical termination as a stillbirth” (Hure et al. 

2015). Genuine confusion may also occur in borderline cases. Medical professionals might classify fetal 

deaths as late as 30 weeks gestation as miscarriages rather than as stillbirths, particularly in settings without 

neonatal intensive care (Blencowe et al. 2016). Anderson et al. (1994) also noted the possibility for women 

to confuse an induced abortion with a spontaneous abortion “if a troubled pregnancy or a medical 

recommendation led to the decision to abort the fetus.” 

1.1.3 Time and reporting of terminated pregnancies 

Time and social desirability 

Evidence on the effects of the passage of time on the misreporting of induced abortions is mixed; Udry et 

al. (1996) found that women were less likely to report an induced abortion as more time passed since the 

abortion, suggesting fading memories of the abortion with time. Fu et al. (1998), however, found that 

women were more likely to accurately report induced abortions that occurred further in the past compared 

with recent induced abortions—suggesting that time serves to create emotional distance from social 

pressures and allows for more objective reporting. The two could be operating simultaneously, with the net 

effect varying depending on social context. 

Recall of the timing and displacement of terminated pregnancies

Many women accurately recall their experience with pregnancy termination but inaccurately recall when 

the termination occurred. Accurate recall of timing may become more difficult as the memory of the event 

fades with time. A study in Bangladesh found that women were more likely to misremember the timing of 

a birth the further into the past the pregnancy occurred (Espeut and Becker 2015). The more frequently an 

event occurs, the greater the likelihood a respondent will confuse the correct date (Sudman and Bradburn 

(1973). The implications of this study could be that women who experience repeated pregnancy 

terminations may be less likely to accurately place the timing of each one. Another study in Bangladesh 
5 

found that the more reproductive events of any kind that a woman had, the less likely she could reliably 

recall the timing of any given event (Callahan and Becker 2012). 

Although vivid events are generally more likely to be remembered and nondescript ones forgotten, when a 

respondent remembers an event vividly, the respondent may incorrectly infer recency from the clarity of 

the memory, an effect called telescoping (Bradburn, Rips, and Shevell 1987; Sudman and Bradburn 1973). 

A study in Bangladesh, however, found that when women misreported the timing of births, they reported 

births farther back in time than actually occurred (Becker and Mahmud 1984). Even when women are 

willing to disclose their terminated pregnancies in a survey, difficulties with accurately recalling their 

timing may influence their reporting within the specific window of time captured by a reproductive 

calendar. 

1.1.4 Improving reporting through calendar methods 

Event history (or life history) calendar methods improve the reporting of the timing of events compared 

with direct questions in surveys by anchoring events around more memorable events. Anchors are easily 

recalled events (such as births) that help respondents place the timing of less memorable events in reference 

(Freedman et al. 1988). Commonly used anchors include births, birthdays, marriages, or public events (e.g., 

a presidency). Less memorable events are then nested in reference to the more accurately remembered 

events. For example, a survey on the purchase of major household goods might use an event history calendar 

that first asks a respondent to list the month and year of all births, marriages, moves, and job changes to 

make the task of remembering the date of a household purchase easier. Event history calendars facilitate 

accurate recall of events through incorporating the natural process of recall into the structure of the survey 

(Axinn, Pearce, and Ghimire 1999; Belli 1998; Belli et al. 2004).They improve recall of whether an event 

occurred by helping the respondent recall the chronology of events (Belli 1998). 

A study on intimate partner violence in the U.S. found that an event history calendar facilitated remembering 

events further in the past compared with standard questionnaires, and therefore produced higher lifetime 

estimates of intimate partner violence (Yoshihama et al. 2005). A study on contraceptive use found both 

more accurate estimates of when events occurred and higher reported incidence of whether contraceptive 

use occurred when measured with the DHS calendar compared with a standard questionnaire (Goldman, 

Moreno, and Westoff 1989a). 

Calendars also improve the recall of events compared with direct survey questionnaires by grouping events 

of a similar theme (e.g., a survey on reproductive behavior anchored around births, a survey on sexual 

behavior anchored around relationships) (Belli 1998). Event history calendars cue individuals with related 

anchors that “facilitate the remembrance of other thematic or temporally related events” from their own 

past (Belli, Shay, and Stafford 2001). By contrast, typical survey questionnaires “segment related aspects 

of autobiographical events from one another” (Belli 1998). A study in Costa Rica examined the results from 

an event history calendar that overlaid past work, pregnancy, contraception, and union events onto one 

calendar compared with the results from a standard questionnaire that segmented questions by topic. This 

study found that a higher percentage of women reported experiencing a miscarriage when interviewed with 

an event history calendar compared with the standard survey (6.7% versus 4.9%) (Becker and Sosa 1992). 

Calendars also improve completeness of reporting by facilitating a more natural flow to the survey 

compared with standard questionnaires. This more natural structure helps build rapport between the 
6 

interviewer and respondent and decreases misreporting due to social desirability bias (Belli et al. 2004). A 

study on sexual behavior in Kenya estimated higher incidence of abstinence for men and multiple sexual 

partners for women with an event history calendar than with a standard questionnaire, suggesting that the 

event history calendar elicited more accurate reporting of socially sensitive behaviors (Luke, Clark, and 

Zulu 2011). 

Calendars have received positive assessments for data collection in a number of areas, including dating 

relationships, employment, postpartum breastfeeding, amenorrhea, abstinence, intimate partner violence, 

contraceptive use, and birth intervals (Becker and Diop-Sidibé 2003; Callahan and Becker 2012; Freedman 

et al. 1988; Glasner and Van der Vaart 2009; Goldman, Moreno, and Westoff 1989a; Luke, Clark, and Zulu 

2011; Yoshihama et al. 2005). Nonetheless, event history calendar methods can be improved upon. A study 

in one Indian state that incorporated a narrative life story approach with a calendar-style survey instrument 

elicited a lifetime abortion rate nearly five times higher than similar estimates from the National Family 

and Health Survey-2 (NFHS-2), which adopted the DHS calendar (Edmeades et al. 2010). A specific focus 

on abortion (rather than a multipurpose health indicator survey), interviewer-respondent rapport, and 

narrative structure, and careful attention to anchors, memory cues, and probes, may have contributed to 

improved reporting of induced abortion (Edmeades et al. 2010). 

1.2 DHS Calendar 

1.2.1 History of the DHS calendar 

The DHS Program first developed the reproductive calendar2

 in an experimental study conducted in Peru 

and replicated in the Dominican Republic in 1986 (Goldman, Moreno, and Westoff 1989b; Westoff, 

Goldman, and Moreno 1990). In particular, these experiments tested “the potential of a 6-year calendar for 

the collection of monthly data on contraceptive practice, breastfeeding, amenorrhea, postpartum abstinence 

and exposure to risk; the comparative merits of a calendar approach vs. the standard format of collecting 

such information within each birth interval for estimates of fecundability, natural fertility, and contraceptive 

efficacy” (Goldman, Moreno, and Westoff 1989b p. 1). 

Analysis of the data collected in the Peru survey showed improved data collection from the calendar format 

in the experimental questionnaire compared with the previously used tabular format, particularly for data 

on contraceptive histories (Goldman, Moreno, and Westoff 1989b, 1989a; Moreno, Goldman, and Babako 

1991). 

Subsequently, the reproductive calendar became a standard part of the DHS Model A questionnaire in the 

second phase of DHS (DHS-2) starting in 1990. In phases DHS-2 through DHS-4 the calendar was included 

only in countries with high contraceptive prevalence. Beginning in DHS-5 the core questionnaire for all 

countries included a reproductive calendar that collected information on births, pregnancies, terminations, 

and episodes of contraceptive use. 

 

2

 This description of the DHS reproductive calendar borrows extensively from two sources: Bradley, S. E. K., W. 

Winfrey, and T. N. Croft. 2015. Contraceptive Use and Perinatal Mortality in the DHS: An Assessment of the Quality 

and Consistency of Calendars and Histories. DHS Methodological Reports No. 17. Rockville, Maryland, USA: ICF 

International; and Croft, T., S. E. K. Bradley, and C. Allen. 2018. DHS Contraceptive Calendar Tutorial. Rockville, 

MD: ICF. 
7 

The current DHS-7 standard questionnaire uses a two-column calendar collecting month-by-month data on 

births, pregnancies, and contraceptive use in column 1, and the reason for discontinuation of contraception 

in column 2. The DHS-6 standard questionnaire followed the same format as in DHS-7. The DHS-5 

standard questionnaire included only one column for births, pregnancies, and contraceptive use, and did not 

include the reason for discontinuation of contraception. Earlier rounds of the DHS questionnaire collected 

a variety of information in the calendar. 

1.2.2 Collecting birth, termination, and pregnancy information in the DHS calendar 

This report analyzes the consistency of terminated pregnancies across the reproductive history calendar. 

The reproductive history calendar is a month-by-month history of reproductive events for five or more 

completed calendar years up to and including the year of the survey. The reproductive events included are: 

live births, months of pregnancy preceding live births, months of current pregnancy, terminated 

pregnancies, completed months of pregnancy before termination, and months of contraceptive method use. 

This report will include a discussion only of the process of recording pregnancies, births, and terminations. 

Discussion of data collection on contraceptive episodes occurs elsewhere (e.g., Bradley, Winfrey, and Croft 

2015). 

The calendar survey asks women about the most recent 5 years up to and including the current survey year. 

The survey therefore includes a column with 72 boxes in six sections—one box for up to 6 years’ worth of 

months in which a woman can contribute information about reproductive events. 

The reproductive calendar follows a complete birth history.3

 That is, the interviewer elicits data from the 

respondent through direct questions in the questionnaire, but records them in calendar format. A study of 

192 surveys found DHS birth histories to be generally of excellent quality, with minimal evidence of 

omission or displacement of live births (Pullum and Becker 2014). Questions marked with a bold C indicate 

to the interviewer to transfer the response onto the calendar. In the birth history section of the questionnaire, 

the interviewer asks the respondent to list all her live births, usually from her first birth through her most 

recent birth.4

 The interviewer records characteristics of each live birth including the month and year of the 

birth. See Figure 1.1 as an example of the birth history from the DHS-7 Model Questionnaire. The 

interviewer then records any births that occurred in the past 5 years in the appropriate month in the 

reproductive calendar with a “B” for “birth.” This becomes the starting point for filling out the reproductive 

calendar and effectively anchors reproductive events around live births. 

 

3

 The majority of DHS questionnaires employ a birth history. However, some surveys instead employ a more complete 

pregnancy history in their questionnaires. 

4

 This is a forward reported birth history when births are recorded in this direction. A backward reported birth history, 

beginning with the most recent birth, is used in a smaller proportion of surveys. 
8 

Figure 1.1 Sample birth history in the DHS-7 Model Questionnaire 

The interviewer then proceeds to fill out the boxes in column 1 of the reproductive calendar, starting with 

the duration of each pregnancy preceding each live birth. Figure 1.2 displays the standard two-column 

calendar in the DHS-7 Model Questionnaire. (The second column records information on reasons for 

discontinuation of contraception, and is not germane this report.) Each month spent pregnant preceding a 

live birth is marked with a “P” for “pregnant.” The final month of the pregnancy is the month of birth, “B,” 

and the total months of pregnancy is therefore the sum of the number of P’s plus one. The interviewer then 

asks the woman whether she is currently pregnant. If so, the interviewer enters the current month and any 

preceding months spent pregnant into column 1 with a “P.” 
9 

Figure 1.2 Reproductive calendar in the DHS-7 Model Questionnaire 
10 

Once the interviewer has recorded data on all live births a woman has experienced, the interviewer then 

asks the woman about pregnancies that did not end in a live birth: 

• Have you ever had a pregnancy that miscarried, was aborted, or ended in a stillbirth? 

Note that this wording asks whether or not a woman ever had a pregnancy that did not end in a live birth, 

and does not ask the woman to state how the pregnancy ended. 

If the woman says “no,” the interviewer proceeds with the interview and collects information on 

contraceptive use to fill out the rest of the calendar. 

If the woman says “yes” to indicate that she has had a pregnancy that did not end in a live birth, the interview 

asks: 

• When did the last such pregnancy end? 

If the pregnancy ended in the last 5 years and is therefore eligible to be included in the calendar, the 

interviewer asks: 

• In what month and year did the preceding such pregnancy end? 

And enters a “T” for “terminated pregnancy” next to the appropriate month and year in the calendar. 

The interviewer then asks: 

• How many months pregnant were you when that pregnancy ended? 

And enters a “P” into the calendar for each month the woman was pregnant preceding the termination. As 

with pregnancies ending in a live birth, the final month of the pregnancy is the month of termination, “T,” 

and the total number of months of pregnancy is therefore the sum of the number of P’s plus one. Pregnancies 

that terminate in their first month are recorded with a T and no P’s in the preceding months. 

The interviewer then asks: 

• Since [the beginning month and year of the eligible calendar period], have you had any other 

pregnancies that did not result in a live birth? 

The interviewer repeats this process until the woman responds “no”—she has not had any (additional) 

pregnancies that did not result in a live birth. The interviewer then continues with the survey, including 

information on contraceptive use, which fills out the rest of the calendar. Note that in the standard DHS-7 

Model Questionnaire the interviewer never asks the woman to differentiate between whether the pregnancy 

ended in a miscarriage, abortion, or a stillbirth. Figure 1.3 shows the standard questions used in the DHS-7 

Model Questionnaire to collect data on terminated pregnancies. 

 
11 

Figure 1.3 Sample questions on terminated pregnancies in the DHS-7 Model Questionnaire 

There is a hierarchy to the data collected in the calendar and the priority certain events have, and this follows 

from the order in which the data are collected, as described in the previous section. DHS reproductive 

calendars prioritize live births and use them to anchor memories of other reproductive and contraceptive 

events. The priority order for recording events in each month is as follows: 
12 

1) Live births 

2) Completed months of pregnancy preceding live births 

3) Months of current pregnancy 

4) Terminated pregnancies 

5) Completed months of pregnancy before a terminated pregnancy 

6) Months of use of the current contraceptive method 

7) Discontinuation of a contraceptive method, and months of use preceding the discontinuation 

The calendar only permits a single code in each month, which necessitates adding the month in which B or 

T is recorded to the P’s to calculate the duration of the pregnancy. Additionally, if a delivery of a pregnancy 

with multiples results in a live birth and a stillbirth in the same month, then only the live birth is recorded 

in the calendar. This potentially results in a slight undercount of stillbirths. 

This section has described how the standard DHS questionnaire completes the reproductive calendar using 

a woman’s birth history. Countries can request deviations from the standard questionnaire. In certain 

surveys the terminated pregnancies are further classified as stillbirths, abortions, or miscarriages. These 

surveys typically use a pregnancy history rather than a birth history in the Women’s Questionnaire. 

For example, the 2015-16 India DHS survey (also referred to as the NFHS-4) included questions on induced 

abortion (see Figure 1.4). Like the standard DHS questionnaire, the India survey questionnaire asks, “Have 

you ever had a pregnancy that miscarried, was aborted, or ended in a stillbirth?” Like the core questionnaire, 

the interviewer asks when the pregnancy ended. Unlike the standard questionnaire, the India questionnaire 

includes a follow-up question asking the respondent how the pregnancy ended: 

• Did that pregnancy end in a miscarriage, an abortion, or a stillbirth? 

The interviewer then marks a “M,” “A,” or “S” in the corresponding month and year in the calendar to 

indicate whether the pregnancy ended in a miscarriage, abortion, or stillbirth.5

 These data on the types of 

terminations are usually recorded in a survey-specific calendar variable. The specific question wording for 

any questionnaire can be found in the appendix of the survey’s final report. 

 

5

 In DHS recode data files, “M,” “A,” or “S” codes are converted to a “T” code in the standard variable for the first 

column of the calendar (vcal_1) to maintain comparability across DHS data files. The “M,” “A,” or “S” code is retained 

in a survey-specific variable. 
13 

Figure 1.4 India 2015-16 DHS questionnaire and reproductive calendar with survey-specific questions 

distinguishing miscarriage, induced abortion, and stillbirth 

Continued 
14 

Figure 1.4—Continued
15 

2 METHODS 

2.1 Calendar Data and Survey Characteristics 

In this study, we analyze 162 standard DHS surveys from 62 countries that administered a reproductive 

calendar, as shown in Table 2.1. Of these, 30 surveys are in Asia, 67 in sub-Saharan Africa, 33 in Latin 

America and the Caribbean (LAC), and 32 in 13 countries of North Arica, the Middle East, West and Central 

Asia, and Eastern Europe (hereafter grouped as “Other Countries” in this study, for the purpose of analysis). 

The surveys were conducted between 1991 and 2017, with their data publicly available by June 2018. Data 

for all surveys can be obtained freely from The DHS Program at https://www.dhsprogram.com/data/, with 

the exception the Turkey 2008 DHS and Turkey 2013 DHS. These data can be obtained by request from 

the Institute of Population, Hacettepe University, at http://www.hips.hacettepe.edu.tr/tnsa/request.php. 

The number of columns typically included in the calendar has changed over different phases of The DHS 

Program. We make use of the first calendar column in which pregnancies, births, and terminations are 

recorded, regardless of the other columns recorded in the calendar. Specifically, we use events files created 

from the calendar string variables available in standard DHS recode data files. A method for preparing such 

events files is described in The DHS Contraceptive Calendar Tutorial6

 (Croft, Bradley, and Allen 2018). 

Although the calendar is generally standard in its implementation, there are some survey-to-survey 

differences in the way it is administered, as shown in Table 2.1. Most calendars are recorded from a 

complete birth history in which women are asked about every birth they have experienced, whether still 

living or not. However, in about 20 surveys the calendar is based on a pregnancy history in which women 

are asked about every pregnancy they have had, whether resulting in a live birth or not. All but a few surveys 

employ a forward reported history, which collects data beginning with the first birth/pregnancy and moves 

through each subsequent one until reaching the time of the survey. Just nine surveys use a backward reported 

history, which collects data beginning with the most recent birth/pregnancy and moves backward until the 

first birth/pregnancy. The majority of surveys, when inquiring about pregnancies that do not result in a live 

birth, do not distinguish between terminations that result from miscarriages versus induced abortion; 

however, 24 surveys in Asia and the Other Countries region do make this distinction. 

DHS surveys have changed in other ways over time. They are increasingly administered using computerassisted field editing (CAFÉ) or computer-assisted personal interview (CAPI) on tablets rather than with a 

pen-and-paper interview. Additionally, questionnaires have become longer over subsequent phases of The 

DHS Program. These survey characteristics may influence the consistency of reporting of terminated 

pregnancies in DHS calendars. 

 

6

 The DHS Contraceptive Calendar Tutorial and associated programs and resources are available on The DHS

Program website at www.dhsprogram.com/data/Calendar-Tutorial/index.cfm. 
16 

Table 2.1 Survey characteristics of DHS surveys with reproductive calendars 

Survey 

DHS 

phase 

Type of 

history 

[1] 

Direction of 

reporting [2] 

Questions 

distinguish 

miscarriage 

and induced 

abortion 

Mode of data 

collection [3] 

Survey 

length 

[4] 

# of 

questions 

Asia 

Afghanistan 2015 7 Birth Forward No PAPI Long 383 

Bangladesh 1993-94 3 Birth Forward No PAPI Short 253 

Bangladesh 1996-97 3 Birth Forward Yes PAPI Short 261 

Bangladesh 1999-00 3 Birth Forward No PAPI Short 270 

Bangladesh 2004 4 Birth Forward No PAPI Short 245 

Bangladesh 2007 5 Birth Forward No PAPI Short 256 

Bangladesh 2011 6 Birth Forward No PAPI Short 302 

Bangladesh 2014 6 Birth Forward No PAPI Short 273 

Cambodia 2010 5 Birth Forward No PAPI Short 352 

Cambodia 2014 6 Birth Forward No PAPI Long 375 

India 2005-06 5 Birth Forward No PAPI Long 433 

India 2015-16 6 Birth Forward Yes CAPI Long 493 

Indonesia 1991 2 Birth Forward No PAPI Short 226 

Indonesia 1994 3 Birth Forward No PAPI Short 255 

Indonesia 1997 3 Birth Forward Yes PAPI Short 215 

Indonesia 2002-03 4 Birth Forward No PAPI Short 294 

Indonesia 2007 5 Birth Forward No PAPI Short 297 

Indonesia 2012 6 Birth Forward Yes PAPI Long 446 

Maldives 2009 5 Birth Forward No CAPI Short 320 

Myanmar 2015-16 7 Birth Forward No CAFÉ Long 390 

Nepal 2006 5 Pregnancy Forward Yes PAPI Short 332 

Nepal 2011 6 Pregnancy Forward Yes CAPI Short 334 

Nepal 2016 7 Pregnancy Forward Yes CAPI Long 446 

Pakistan 2012-13 6 Pregnancy Forward Yes PAPI Short 319 

Philippines 1993 2 Pregnancy Forward No PAPI Short 312 

Philippines 1998 3 Pregnancy Forward No PAPI Short 280 

Philippines 2003 4 Pregnancy Forward No PAPI Short 284 

Timor-Leste 2009-10 5 Birth Forward No PAPI Long 419 

Vietnam 1997 3 Pregnancy Backward No PAPI Short 263 

Vietnam 2002 4 Pregnancy Backward No PAPI Short 263 

Africa 

Angola 2015-16 7 Birth Forward No CAPI Long 429 

Benin 2006 5 Birth Forward No PAPI Long 399 

Benin 2011-12 6 Birth Forward No CAPI Long 391 

Burkina Faso 2003 4 Birth Forward No PAPI Short 330 

Burkina Faso 2010 6 Birth Forward No PAPI Long 405 

Burundi 2010 6 Birth Forward No PAPI Short 350 

Burundi 2016-17 7 Birth Forward No CAPI Long 469 

Comoros 2012 6 Birth Forward No PAPI Long 391 

Ethiopia 2005 4 Birth Forward No PAPI Long 370 

Ethiopia 2011 6 Birth Forward No PAPI Short 349 

Ethiopia 2016 7 Birth Forward No CAPI Long 476 

Gambia 2013 6 Birth Forward No PAPI Long 390 

Ghana 2003 4 Birth Forward No PAPI Short 280 

Ghana 2008 5 Birth Forward No PAPI Long 444 

Ghana 2014 6 Birth Forward No CAFÉ Long 418 

Guinea 2005 4 Birth Forward No PAPI Long 390 

Kenya 1998 3 Birth Forward No PAPI Short 296 

Kenya 2003 4 Birth Forward No PAPI Short 316 

Continued 
17 

Table 2.1—Continued 

Survey 

DHS 

phase 

Type of 

history 

[1] 

Direction of 

reporting [2] 

Questions 

distinguish 

miscarriage 

and induced 

abortion 

Mode of data 

collection [3] 

Survey 

length 

[4] 

# of 

questions 

Africa cont’d 

Kenya 2008-09 5 Birth Forward No PAPI Long 445 

Kenya 2014 6 Birth Forward No PAPI Long 391 

Lesotho 2009 5 Birth Forward No CAPI Long 447 

Lesotho 2014 6 Birth Forward No CAPI Long 379 

Liberia 2013 6 Birth Forward No PAPI Short 350 

Madagascar 2003-04 4 Birth Forward No PAPI Long 403 

Madagascar 2008-09 5 Birth Forward No PAPI Long 422 

Malawi 2000 4 Birth Forward No PAPI Short 304 

Malawi 2004 4 Birth Forward No PAPI Short 343 

Malawi 2010 5 Birth Forward No PAPI Long 500 

Malawi 2015-16 7 Birth Forward No CAPI Long 450 

Mali 2001 4 Birth Forward No PAPI Short 322 

Mali 2006 5 Birth Forward No PAPI Long 444 

Mali 2012-13 6 Birth Forward No CAPI Long 407 

Mozambique 2003 4 Birth Forward No PAPI Short 297 

Mozambique 2011 6 Birth Forward No CAPI Long 381 

Namibia 2006-07 5 Birth Forward No PAPI Long 445 

Namibia 2013 6 Birth Forward No PAPI Long 400 

Niger 2006 5 Birth Forward No PAPI Long 408 

Niger 2012 6 Birth Forward No PAPI Long 404 

Nigeria 2008 5 Birth Forward No PAPI Long 491 

Nigeria 2013 6 Birth Forward No PAPI Long 396 

Rwanda 2000 4 Birth Forward No PAPI Short 315 

Rwanda 2005 4 Birth Forward No PAPI Long 411 

Rwanda 2010 6 Birth Forward No PAPI Long 366 

Rwanda 2014-15 6 Birth Forward No PAPI Long 378 

Senegal 2005 4 Birth Forward No PAPI Long 383 

Senegal 2010-11 6 Birth Forward No CAPI Short 328 

Senegal 2012-13 6 Birth Forward No CAPI Short 293 

Senegal 2014 6 Birth Forward No CAPI Short 344 

Senegal 2015 6 Birth Forward No CAPI Short 354 

Senegal 2016 6 Birth Forward No CAPI Short 353 

Sierra Leone 2008 5 Birth Forward No PAPI Long 444 

Sierra Leone 2013 6 Birth Forward No PAPI Long 409 

Swaziland 2006-07 5 Birth Forward No PAPI Long 414 

Tanzania 2004-05 4 Birth Forward No PAPI Long 369 

Tanzania 2010 5 Birth Forward No PAPI Long 466 

Tanzania 2015-16 7 Birth Forward No PAPI Long 412 

Uganda 2000-01 4 Birth Forward No PAPI Short 310 

Uganda 2006 5 Birth Forward No PAPI Long 467 

Uganda 2011 6 Birth Forward No PAPI Long 387 

Uganda 2016 7 Birth Forward No CAPI Long 387 

Zambia 2007 5 Birth Forward No PAPI Long 464 

Zambia 2013-14 6 Birth Forward No PAPI Long 382 

Zimbabwe 1994 3 Birth Forward No PAPI Short 339 

Zimbabwe 1999 4 Birth Forward No PAPI Short 286 

Zimbabwe 2005-06 5 Birth Forward No PAPI Long 485 

Zimbabwe 2010-11 6 Birth Forward No CAPI Long 384 

Zimbabwe 2015 7 Birth Forward No CAPI Long 432 

Continued 
18 

Table 2.1—Continued 

Survey 

DHS 

phase 

Type of 

history 

[1] 

Direction of 

reporting [2] 

Questions 

distinguish 

miscarriage 

and induced 

abortion 

Mode of data 

collection [3] 

Survey 

length 

[4] 

# of 

questions 

LAC 

Bolivia 1994 3 Birth Forward No PAPI Short 322 

Bolivia 2003 4 Birth Forward No PAPI Long 359 

Bolivia 2008 5 Birth Forward No PAPI Long 499 

Brazil NE 1991 2 Birth Forward No PAPI Short 297 

Brazil 1996 3 Birth Forward No PAPI Short 286 

Colombia 1990 2 Birth Forward No PAPI Short 252 

Colombia 1995 3 Birth Forward No PAPI Short 278 

Colombia 2000 4 Birth Forward No PAPI Short 342 

Colombia 2005 4 Birth Forward No CAPI Long 477 

Colombia 2010 5 Birth Forward No CAPI Long 582 

Colombia 2015 7 Birth Forward No CAPI Long 493 

Dominican Republic 1991 2 Birth Forward No PAPI Short 306 

Dominican Republic 1996 3 Birth Forward No PAPI Short 287 

Dominican Republic 1999 3 Birth Forward No PAPI Long 389 

Dominican Republic 2002 4 Birth Forward No PAPI Long 380 

Guatemala 1995 3 Birth Forward No PAPI Short 301 

Guatemala 1998-99 3 Birth Forward No [7] PAPI Short 275 

Guatemala 2014-15 6 Birth Forward No PAPI Long 420 

Guyana 2009 5 Birth Forward No PAPI Long 425 

Honduras 2005-06 5 Birth Forward No PAPI Long 459 

Honduras 2011-12 6 Birth Forward No PAPI Long 415 

Nicaragua 1998 3 Birth Forward No PAPI Short 334 

Nicaragua 2001 4 Birth Forward No PAPI Short 298 

Paraguay 1990 2 Birth Forward No PAPI Short 250 

Peru 1991-92 2 Birth Forward No PAPI Short 312 

Peru 1996 3 Birth Forward No PAPI Short 284 

Peru 2000 4 Birth Forward No PAPI Short 358 

Peru 2004-06 5 Birth Forward No CAPI Short 335 

Peru 2007-08 5 Birth Forward No CAPI Short 336 

Peru 2009 6 Birth Forward No CAPI Short 320 

Peru 2010 6 Birth Forward No CAPI Short 323 

Peru 2011 6 Birth Forward No CAPI Short 323 

Peru 2012 6 Birth Forward No CAPI Short 323 

Other Countries 

Albania 2008-09 5 Pregnancy [6] Forward Yes CAPI Long 426 

Armenia 2000 4 Pregnancy Backward Yes PAPI Long 384 

Armenia 2005 4 Pregnancy Backward Yes PAPI Long 377 

Armenia 2010 6 Pregnancy Backward Yes PAPI Long 364 

Armenia 2015-16 7 Pregnancy Forward Yes PAPI Long 445 

Azerbaijan 2006 5 Pregnancy Backward No PAPI Long 463 

Egypt 1992 2 Birth Forward No PAPI Short 343 

Egypt 1995 3 Birth Forward Yes PAPI Short 350 

Egypt 2000 4 Birth Forward Yes PAPI Short 324 

Egypt 2003 4 Birth Forward Yes PAPI Short 277 

Egypt 2005 4 Birth Forward Yes PAPI Long 378 

Egypt 2008 5 Birth Forward Yes PAPI Short 349 

Egypt 2014 6 Birth Forward Yes PAPI Short 349 

Jordan 1990 2 Birth Forward No PAPI Short 234 

Jordan 1997 3 Birth Forward No PAPI Short 266 

Continued 
19 

Table 2.1—Continued 

Survey 

DHS 

phase 

Type of 

history 

[1] 

Direction of 

reporting [2] 

Questions 

distinguish 

miscarriage 

and induced 

abortion 

Mode of data 

collection [3] 

Survey 

length 

[4] 

# of 

questions 

Other Countries cont’d 

Jordan 2002 4 Birth Forward No PAPI Short 274 

Jordan 2007 5 Birth Forward No PAPI Short 318 

Jordan 2009 5 Birth Forward No PAPI Short 183 

Jordan 2012 6 Birth Forward No PAPI Short 338 

Kazakhstan 1999 3 Pregnancy Backward Yes PAPI Short 353 

Kyrgyz Republic 2012 6 Pregnancy Forward No PAPI Long 420 

Moldova 2005 4 Pregnancy Backward No PAPI Long 410 

Morocco 1992 2 Birth Forward No PAPI Short 291 

Morocco 2003-04 4 Birth Forward No PAPI Short 313 

Tajikistan 2012 6 Pregnancy Forward No PAPI Long 393 

Turkey 1993 2 Birth Forward Yes PAPI Short 310 

Turkey 1998 3 Birth Forward No PAPI Short 328 

Turkey 2003 4 Birth Forward Yes PAPI Long 378 

Turkey 2008 [5] 5 Birth Forward Yes PAPI Short 287 

Turkey 2013 [5] 6 Birth Forward Yes PAPI Short 287 

Ukraine 2007 5 Pregnancy Backward No PAPI Long 400 

Yemen 2013 6 Birth Forward No PAPI Short 337 

Notes: 

[1] A birth history collects data on every live birth, whether still alive or not. A pregnancy history collects data on all pregnancies, including 

those that ended in a live birth, an induced abortion, a miscarriage, and a stillbirth. 

[2] A forward reported history collects data beginning with the first birth/pregnancy moving through each subsequent one until the most 

recent, whereas a backward reported history collects data beginning with the most recent birth/pregnancy moving backward until the first 

birth/pregnancy. 

[3] PAPI: pen and paper personal interview; CAFÉ: computer-assisted field editing; CAPI: computer-assisted personal interview.

[4] The survey is categorized as long if the number of questions exceeds the median number of questions across all surveys, and short if 

the number of questions is fewer than the median number of questions across all surveys. 

[5] The Turkey 2008 and 2013 surveys can be obtained from the Institute of Population, Hacettepe University, at http://www.hips. 

hacettepe.edu.tr/tnsa/request.php. All other surveys are available from The DHS Program at https://www.dhsprogram.com/data/. 

[6] The Albania 2008-09 DHS administers a birth history for all births, but a pregnancy history for the last 5 years. It is categorized as having 

a pregnancy history for the purposes of this study since that is the history type completing the period of time covered by the calendar. 

[7] The Guatemala 1998-99 DHS does not distinguish between miscarriage and induced abortion, but does differentiate between early 

neonatal death and stillbirth. 

2.2 Period of Observation 

Although DHS calendars collect monthly data for a total of more than 60 months, we restrict our period of 

observation to a 60-month period, as in Figure 2.1. Our 60-month period of observation does not begin with 

the month of the interview, however, as we do not use the 3 months preceding the date of the interview. 

There are several reasons: First, we discard the month of the interview because it is an incomplete month 

of observation for all but approximately 3% of women who happen to be interviewed on the last day of the 

month. Second, omitting the first 3 months of the calendar follows the convention for analysis of 

contraceptive discontinuation. Because many women may not recognize that they are pregnant in the first 

2 months of pregnancy, this exclusion avoids the potential for biased reporting of pregnancies, pregnancy 

outcomes, and pregnancies due to contraceptive failure in this period. Finally, this exclusion results in an 

even distribution of observations across the observation period. 

Each survey’s calendar varies in length depending on the months of the year in which data collection occurs. 

We also restrict our period of observation to 60 months so that we are examining a consistent period of time 
20 

across all surveys. There is also substantial attrition in the number of cases in the earliest months of the 

calendar. The exclusion of the earliest tail of the calendar results in an even distribution of observations in 

the same way that excluding the three months preceding the interview does. 

Figure 2.1 Study period of observation 

2.3 Measures 

2.3.1 Termination ratio 

Our primary measure is a termination ratio, which in any given month of the calendar is the ratio of 

terminated pregnancies to live births, expressed per 100 live births. As such, it is analogous to an abortion 

ratio or maternal mortality ratio. The termination ratio is simply 

൬

ݏ݁݃݊ܽ݊ܿ݅݁ݎ݌ ݁݀ݐ݉݅݊ܽݎ݁ݐ

100 × ൰ ݏhݐݎܾ݅ ݁ݒ݈݅

We aggregate monthly termination ratios into termination ratios for five 12-month intervals in two ways. 

The first is with regard to the woman’s month of interview. We calculate the termination ratio for each 12-

month interval (0-11 months, 12-23 months, 24-35 months, 36-47 months, and 48-59 months) from the 

month of interview during the observation period. The second is with regard to month and year in the 

calendar. Thus, for a survey’s calendar beginning in January 2010, and June 2015 being the most recent 

month in the observation period, we calculate the termination ratio for the following 12-month intervals: 

July 2014–June 2015, July 2013–June 2014, July 2012–June 2013, July 2011–June 2012, and July 2010–

June 2011. The period of January–June 2010 would form an incomplete sixth interval and falls outside of 

our observation period. 
21 

2.3.2 Other measures 

We classify survey calendars according to six survey characteristics, described in Table 2.1. These are: 

• whether the survey employs a birth history or a pregnancy; 

• whether the survey gathers forward reported or backward reported history; 

• whether the survey includes questions to differentiate types of termination, namely miscarriage 

and induced abortion; 

• whether data were collected through PAPI, CAFÉ, or CAPI; 

• whether the survey questionnaire was relatively long or short; and 

• phase of The DHS Program. 

A survey is classified as having a long questionnaire if the number of questions exceeds the median number 

of questions across all surveys, and as having a short questionnaire if the number of questions is less than 

or equal to the median number of questions across all surveys. 

2.4 Analytic Strategy 

2.4.1 Within-survey consistency 

In this study, we first examine within-survey consistency in the termination ratios, in two ways. First, for 

all 162 surveys, we generate plots to describe termination ratios over the course of the 60-month observation 

period into five 12-month intervals. Next, we apply a statistical test of the equivalence of termination ratios 

estimated at the most recent and earliest interval in the calendar. 

Ceteris paribus, we would expect that the termination ratio would be constant over the course of a 60-month 

calendar. Our null hypothesis implicitly assumes that 5 years is a sufficiently short period of time that 

changing fertility patterns resulting in real changes in the termination ratio would not be detectable. A Wald 

test of equivalence tests whether the relative odds of termination during the 0-11 months preceding the 

survey is equivalent to that in the 48-59 months preceding the survey. Thus, with a p-value of the Wald test 

of less than 0.05, we reject the null hypothesis that the termination ratios at the start and the end of the 

calendar are statistically equivalent and deem the survey “inconsistent.” 

2.4.2 Between-survey consistency 

Of the 62 countries that have at least one survey with a calendar, more than half—34 countries—have 

multiple calendars that are consecutive or overlap in time. For these surveys, we supplement the assessment 

of within-survey consistency by assessing between-survey consistency in termination ratios from one 

survey to the next. We allow up to a 1-year gap between surveys. This analysis comprises 121 calendars. 

For between-survey analysis, we first use graphical analysis to examine the continuity of termination ratios 

from one survey to the next. In particular, we examine the adjoining (or overlapping) moments of the 

surveys. The termination ratios calculated from two surveys at these adjoining (or overlapping) points 

should be similar, i.e., not statistically different. Between-survey inconsistency is evident if they are not 

similar. 
22 

We follow the graphical analysis with a formal test of between-survey consistency. With each pair of 

consecutive surveys, we calculate the absolute and relative difference in the termination ratios between the 

earliest observed interval of one survey and the most recent observed interval of the preceding survey. If 

the relative difference is greater than the absolute value of 20.6%, we reject the null hypothesis that there 

is no significant difference between the two termination ratios, meaning that between-survey inconsistency 

is evident. We use a cutoff of 20.6% as the threshold because it is the minimum difference for which a 

significant difference in termination ratios can be detected. 

Fertility patterns, public health status, and health care systems may change over time, influencing the real 

ratio of pregnancies that end in termination to those ending in live birth. Examining termination ratios over 

a longer stretch of time allows us to detect whether increasing or decreasing termination ratios reflect a 

secular trend, which may or may not be detectable in a single 5-year calendar. In the presence of a secular 

trend, the adjoining (or overlapping) points of the calendars should nonetheless be consistent if termination 

ratios are consistently reported. A survey that suggests within-survey inconsistency because of a 

significantly increasing (or decreasing) termination ratio may be revealed to have between-survey 

consistency if the change in the termination ratio is due to a secular trend. Nonetheless, there should be 

between-survey consistency, regardless of whether or not there is a secular trend or evidence of withinsurvey inconsistency. If between-survey inconsistency is indicated, we assume that the higher termination 

ratio is the more accurate ratio, and hypothesize that this will be recorded in the more recent interval of a 

preceding calendar rather than in the earlier interval of the following calendar. 

2.4.3 Classification by survey characteristics 

Based on the two tests of within-survey and between-survey consistency, we classify each survey as either 

“consistent” or “inconsistent.” A survey is classified as “inconsistent” if both the within-survey and 

between-survey tests indicate inconsistency, and it is classified as “consistent” if either the within-survey 

or between-survey test, or both, suggests consistency. If only one test is available, a survey is classified 

according to the results of the within-survey test. 

We then disaggregate consistent and inconsistent surveys according to the six survey characteristics to 

determine if we can identify any patterns. We selected these survey characteristics on the basis of their 

potential to be associated with the consistency or inconsistency of surveys’ termination ratios, but we make 

no specific hypotheses about any such associations. These data are descriptive; no statistical tests are 

conducted to conclude whether surveys with certain characteristics are significantly more or less likely to 

produce calendars with consistent reporting of termination ratios. 
23 

3 PATTERNS OF TERMINATION RATIOS IN SINGLE 

SURVEYS 

3.1 Observing Patterns of Termination Ratios in Single Surveys 

Figures 3.1 through 3.4 show the termination ratios in 12-month intervals for each of the 162 surveys in the 

study, organized by region. We expect that if the calendar demonstrates consistency, the reported 

termination ratios will be constant across all intervals in a survey’s calendar in the absence of changes in 

real-world conditions. With only a few exceptions, however, this is not the pattern we find. The dominant 

pattern in all four regions is one of higher termination ratios in the most recent interval, 0-11 months 

preceding the interview, and decreasing termination ratios in earlier intervals. 

3.1.1 Patterns of termination ratios in Asia 

Of the 30 surveys in Asia, Timor-Leste 2009-2010 most clearly shows a pattern of consistent termination 

ratios over the course of the calendar. Timor-Leste also shows the lowest termination ratios in the region, 

at about 3 terminated pregnancies per 100 live births in each interval of the calendar. 

Elsewhere in Asia, the majority of termination ratios are below 20, ranging from about 5 terminated 

pregnancies per 100 live births in the earliest interval preceding interview in the Indonesia 1991, 1994, and 

1997 surveys to about 19 terminated pregnancies per 100 live births in the most recent interval. However, 

several surveys (Cambodia 2010 and 2014, Vietnam 1997 and 2002, and Nepal 2016) show termination 

ratios beyond this range. The highest termination ratios in this region are observed in Vietnam 2002, at 49 

terminated pregnancies per 100 live births in the first interval. 

Regardless of the level of termination ratios, the surveys in Asia universally (with the exception of TimorLeste) show a pattern of decreasing termination ratios in intervals farther away from the time of interview. 

This pattern is most pronounced in the Cambodia, Vietnam, and Maldives surveys. There is variation, 

however, as to whether the termination ratios decrease steadily with each interval (e.g., Bangladesh 2014), 

decrease sharply in all intervals preceding the first interval (e.g., Indonesia 1994), or show the steepest 

decrease in the earliest intervals (e.g., Philippines 2003), or some combination of these (e.g., Maldives 2009 

and Vietnam 1997). 
24 

Figure 3.1 Ratios of terminated pregnancies to live births (per 100) in DHS calendars, Asia 

 

 

 

 

Continued 

12.4

13.6

10.4

8.8 8.7

0

5

10

15

20

48-59 36-47 24-35 12-23 0-11

Months of observed calendar preceding the survey

Afghanistan 2015

10.1 11.2

6.2 6.3 7.4

0

5

10

15

20

48-59 36-47 24-35 12-23 0-11

Months of observed calendar preceding the survey

Bangladesh 1993-94

14.3

11.7

8.9 9.6 9.9

0

5

10

15

20

48-59 36-47 24-35 12-23 0-11

Months of observed calendar preceding the survey

Bangladesh 1996-97

15.9

12.1

14.8

11.7 11.0

0

5

10

15

20

48-59 36-47 24-35 12-23 0-11

Months of observed calendar preceding the survey

Bangladesh 1999-00

19.3

15.7

13.5

16.4

13.3

0

5

10

15

20

48-59 36-47 24-35 12-23 0-11

Months of observed calendar preceding the survey

Bangladesh 2004

16.1

13.4 13.0

15.2

10.6

0

5

10

15

20

48-59 36-47 24-35 12-23 0-11

Months of observed calendar preceding the survey

Bangladesh 2007

18.9

17.6

14.2

11.6

13.0

0

5

10

15

20

48-59 36-47 24-35 12-23 0-11

Months of observed calendar preceding the survey

Bangladesh 2011

17.1

13.4

11.7 10.9 11.2

0

5

10

15

20

48-59 36-47 24-35 12-23 0-11

Months of observed calendar preceding the survey

Bangladesh 2014
25 

Figure 3.1—Continued

 

 

 

 

Continued 

29.2 30.0

24.2 22.1

16.6

0

5

10

15

20

25

30

35

40

48-59 36-47 24-35 12-23 0-11

Months of observed calendar preceding the survey

Cambodia 2010

38.9

32.5

27.2 29.2

25.2

0

5

10

15

20

25

30

35

40

48-59 36-47 24-35 12-23 0-11

Months of observed calendar preceding the survey

Cambodia 2014

17.0

13.1 12.4

11.0

8.3

0

5

10

15

20

48-59 36-47 24-35 12-23 0-11

Months of observed calendar preceding the survey

India 2005-06

15.6

12.1 11.1

9.3 9.5

0

5

10

15

20

48-59 36-47 24-35 12-23 0-11

Months of observed calendar preceding the survey

India 2015-16

7.6

6.0 5.7 4.8 4.7

0

5

10

15

20

48-59 36-47 24-35 12-23 0-11

Months of observed calendar preceding the survey

Indonesia 1991

9.3

6.3

7.6

6.0 5.4

0

5

10

15

20

48-59 36-47 24-35 12-23 0-11

Months of observed calendar preceding the survey

Indonesia 1994

8.7

7.2 8.0 7.2

4.6

0

5

10

15

20

48-59 36-47 24-35 12-23 0-11

Months of observed calendar preceding the survey

Indonesia 1997

9.5 8.7

7.1 8.0

6.4

0

5

10

15

20

48-59 36-47 24-35 12-23 0-11

Months of observed calendar preceding the survey

Indonesia 2002-03
26 

Figure 3.1—Continued

 

 

 

 

Continued 

13.0

10.9

7.3

9.1

6.4

0

5

10

15

20

48-59 36-47 24-35 12-23 0-11

Months of observed calendar preceding the survey

Indonesia 2007

13.3 12.2 12.5

8.2 8.9

0

5

10

15

20

48-59 36-47 24-35 12-23 0-11

Months of observed calendar preceding the survey

Indonesia 2012

19.3

14.3 14.0 14.4

11.1

0

5

10

15

20

48-59 36-47 24-35 12-23 0-11

Months of observed calendar preceding the survey

Maldives 2009

11.0

12.7

10.9

6.7 7.4

0

5

10

15

20

48-59 36-47 24-35 12-23 0-11

Months of observed calendar preceding the survey

Myanmar 2015-16

13.9

10.7 12.4 11.6 9.9

0

5

10

15

20

25

30

35

48-59 36-47 24-35 12-23 0-11

Months of observed calendar preceding the survey

Nepal 2006

20.8 19.2

14.9 15.5 15.5

0

5

10

15

20

25

30

35

48-59 36-47 24-35 12-23 0-11

Months of observed calendar preceding the survey

Nepal 2011

29.7

23.6 22.9 21.4

18.2

0

5

10

15

20

25

30

35

48-59 36-47 24-35 12-23 0-11

Months of observed calendar preceding the survey

Nepal 2016

20.8 19.3 19.5 20.6

17.4

0

5

10

15

20

25

48-59 36-47 24-35 12-23 0-11

Months of observed calendar preceding the survey

Pakistan 2012-13
27 

Figure 3.1—Continued

 

 

 

Note: While the scale for most surveys in this region extends from 0 to 20 terminated pregnancies per 100 live births, higher

termination ratios in Cambodia, Nepal, Pakistan, and Vietnam necessitate an extended scale. 

3.1.2 Patterns of termination ratios in Africa 

With the exception of several calendar intervals in the Ghana 2008 and 2014 surveys, observed termination 

ratios in Africa are less than 20 terminated pregnancies per 100 live births. Six surveys in Africa—Benin 

2006, Burkina Faso 2003 and 2010, Malawi 2004, Mali 2012-13, and Niger 2006—exhibit constant 

termination ratios over the course of the calendar, as shown in Figure 3.2. However, the vast majority of 

surveys in the region show higher termination ratios in more recent intervals of the calendar. The slope of 

the termination ratios across intervals may be quite modest, as in Benin 2011-12, or pronounced, as in 

Ghana 2014 and Uganda 2016. The most common pattern in Africa is a relatively steady increase in the 

termination ratio as intervals are closer to the date of interview. However, two other patterns are observed 

12.5

10.5 10.3 9.6

8.5

0

5

10

15

20

48-59 36-47 24-35 12-23 0-11

Months of observed calendar preceding the survey

Philippines 1993

13.9

11.2 12.2 11.9

9.9

0

5

10

15

20

48-59 36-47 24-35 12-23 0-11

Months of observed calendar preceding the survey

Philippines 1998

12.4 11.5 11.5 12.1

8.3

0

5

10

15

20

48-59 36-47 24-35 12-23 0-11

Months of observed calendar preceding the survey

Philippines 2003

3.2 2.5 3.4 2.9 3.0

0

5

10

15

20

48-59 36-47 24-35 12-23 0-11

Months of observed calendar preceding the survey

Timor-Leste 2009-10

37.9

26.1 26.4 27.6

20.0

0

5

10

15

20

25

30

35

40

45

50

48-59 36-47 24-35 12-23 0-11

Months of observed calendar preceding the survey

Vietnam 1997

48.8

43.1

35.7

43.9

35.7

0

5

10

15

20

25

30

35

40

45

50

48-59 36-47 24-35 12-23 0-11

Months of observed calendar preceding the survey

Vietnam 2002
28 

as well. For example, Senegal 2012-13 and Kenya 2008-09 show a marked decrease in all intervals 

compared with the most recent interval, whereas Liberia 2013 shows a marked decrease both following the 

first interval and again in the earliest interval. 

Figure 3.2 Ratios of terminated pregnancies to live births (per 100) in DHS calendars, Africa 

 

 

 

Continued 

 

9.3

7.2 6.4

4.6 4.2

0

5

10

15

20

48-59 36-47 24-35 12-23 0-11

Months of observed calendar preceding the survey

Angola 2015-16

8.9

7.6 8.0 6.8 7.5

0

5

10

15

20

48-59 36-47 24-35 12-23 0-11

Months of observed calendar preceding the survey

Benin 2006

4.9 4.4 3.5 2.6 2.9

0

5

10

15

20

48-59 36-47 24-35 12-23 0-11

Months of observed calendar preceding the survey

Benin 2011-12

6.5 6.5 6.2 6.0 6.0

0

5

10

15

20

48-59 36-47 24-35 12-23 0-11

Months of observed calendar preceding the survey

Burkina Faso 2003

6.3

4.7 5.2 5.6 5.0

0

5

10

15

20

48-59 36-47 24-35 12-23 0-11

Months of observed calendar preceding the survey

Burkina Faso 2010

10.3

6.0 7.1

8.5

6.7

0

5

10

15

20

48-59 36-47 24-35 12-23 0-11

Months of observed calendar preceding the survey

Burundi 2010
29 

Figure 3.2—Continued

 

 

 

 

Continued 

10.4

8.6 9.2

7.3

5.7

0

5

10

15

20

48-59 36-47 24-35 12-23 0-11

Months of observed calendar preceding the survey

Burundi 2016-2017

11.9

7.5

5.9 6.5 6.6

0

5

10

15

20

48-59 36-47 24-35 12-23 0-11

Months of observed calendar preceding the survey

Comoros 2012

4.6 5.0 4.3 3.5 2.7

0

5

10

15

20

48-59 36-47 24-35 12-23 0-11

Months of observed calendar preceding the survey

Ethiopia 2005

9.5

6.6

5.0

3.8 3.0

0

5

10

15

20

48-59 36-47 24-35 12-23 0-11

Months of observed calendar preceding the survey

Ethiopia 2011

6.6 5.8 4.8 4.7

3.1

0

5

10

15

20

48-59 36-47 24-35 12-23 0-11

Months of observed calendar preceding the survey

Ethiopia 2016

8.2

6.6

5.4 5.3 5.3

0

5

10

15

20

48-59 36-47 24-35 12-23 0-11

Months of observed calendar preceding the survey

Gambia 2013

17.8

11.4

8.6 10.0

7.6

0

5

10

15

20

25

30

48-59 36-47 24-35 12-23 0-11

Months of observed calendar preceding the survey

Ghana 2003

20.3

17.1 15.3 13.8

10.5

0

5

10

15

20

25

30

48-59 36-47 24-35 12-23 0-11

Months of observed calendar preceding the survey

Ghana 2008
30 

Figure 3.2—Continued

 

 

 

 

Continued 

28.5

23.2

19.8

17.9

12.6

0

5

10

15

20

25

30

48-59 36-47 24-35 12-23 0-11

Months of observed calendar preceding the survey

Ghana 2014

10.9

8.5 7.8

4.1

6.2

0

5

10

15

20

48-59 36-47 24-35 12-23 0-11

Months of observed calendar preceding the survey

Guinea 2005

8.0

6.3

4.4

3.0 4.0

0

5

10

15

20

48-59 36-47 24-35 12-23 0-11

Months of observed calendar preceding the survey

Kenya 1998

7.9

5.6 5.5 4.4 3.5

0

5

10

15

20

48-59 36-47 24-35 12-23 0-11

Months of observed calendar preceding the survey

Kenya 2003

8.7

5.0 5.3 4.8 4.7

0

5

10

15

20

48-59 36-47 24-35 12-23 0-11

Months of observed calendar preceding the survey

Kenya 2008-09

10.1

8.0 7.0

5.5 4.6

0

5

10

15

20

48-59 36-47 24-35 12-23 0-11

Months of observed calendar preceding the survey

Kenya 2014

5.0

7.0

4.9

7.0

5.6

0

5

10

15

20

48-59 36-47 24-35 12-23 0-11

Months of observed calendar preceding the survey

Lesotho 2009

8.2

11.5

8.7 7.5

9.2

0

5

10

15

20

48-59 36-47 24-35 12-23 0-11

Months of observed calendar preceding the survey

Lesotho 2014
31 

Figure 3.2—Continued

 

 

 

Continued 

19.8

11.5 10.9

12.1

6.3

0

5

10

15

20

48-59 36-47 24-35 12-23 0-11

Months of observed calendar preceding the survey

Liberia 2013

9.3 9.5

6.4 6.3 5.6

0

5

10

15

20

48-59 36-47 24-35 12-23 0-11

Months of observed calendar preceding the survey

Madagascar 2003-04

9.8

7.9 7.6

5.5 5.9

0

5

10

15

20

48-59 36-47 24-35 12-23 0-11

Months of observed calendar preceding the survey

Madagascar 2008-09

6.8

5.3 4.9 4.6 4.4

0

5

10

15

20

48-59 36-47 24-35 12-23 0-11

Months of observed calendar preceding the survey

Malawi 2000

5.5 5.3 5.6 4.5

5.7

0

5

10

15

20

48-59 36-47 24-35 12-23 0-11

Months of observed calendar preceding the survey

Malawi 2004

7.4

6.2

4.9 5.0 4.5

0

5

10

15

20

48-59 36-47 24-35 12-23 0-11

Months of observed calendar preceding the survey

Malawi 2010

8.1

5.8

4.5 4.8 4.0

0

5

10

15

20

48-59 36-47 24-35 12-23 0-11

Months of observed calendar preceding the survey

Malawi 2015-16

9.8 8.6

6.0 6.8 6.2

0

5

10

15

20

48-59 36-47 24-35 12-23 0-11

Months of observed calendar preceding the survey

Mali 2001
32 

Figure 3.2—Continued

 

 

 

 

Continued 

10.4

6.2

8.3 7.3 6.2

0

5

10

15

20

48-59 36-47 24-35 12-23 0-11

Months of observed calendar preceding the survey

Mali 2006

3.6

5.2 4.4

3.1 3.2

0

5

10

15

20

48-59 36-47 24-35 12-23 0-11

Months of observed calendar preceding the survey

Mali 2012-13

9.4 9.2

7.0

5.7

7.5

0

5

10

15

20

48-59 36-47 24-35 12-23 0-11

Months of observed calendar preceding the survey

Mozambique 2003

8.1 7.1

5.8

4.4 3.8

0

5

10

15

20

48-59 36-47 24-35 12-23 0-11

Months of observed calendar preceding the survey

Mozambique 2011

8.0

5.6

3.4 4.4

5.9

0

5

10

15

20

48-59 36-47 24-35 12-23 0-11

Months of observed calendar preceding the survey

Namibia 2006-07

10.0

5.7

7.8

5.9 5.6

0

5

10

15

20

48-59 36-47 24-35 12-23 0-11

Months of observed calendar preceding the survey

Namibia 2013

6.6

4.9 5.9 5.2 5.2

0

5

10

15

20

48-59 36-47 24-35 12-23 0-11

Months of observed calendar preceding the survey

Niger 2006

9.9

7.0 7.0

5.5 6.3

0

5

10

15

20

48-59 36-47 24-35 12-23 0-11

Months of observed calendar preceding the survey

Niger 2012
33 

Figure 3.2—Continued

 

 

 

 

Continued 

8.6 8.7

6.3 5.4 5.6

0

5

10

15

20

48-59 36-47 24-35 12-23 0-11

Months of observed calendar preceding the survey

Nigeria 2008

9.6

8.0 7.4 6.3

4.8

0

5

10

15

20

48-59 36-47 24-35 12-23 0-11

Months of observed calendar preceding the survey

Nigeria 2013

8.5

10.3

8.3

5.8 6.3

0

5

10

15

20

48-59 36-47 24-35 12-23 0-11

Months of observed calendar preceding the survey

Rwanda 2000

9.8

7.5 7.3 8.3

5.2

0

5

10

15

20

48-59 36-47 24-35 12-23 0-11

Months of observed calendar preceding the survey

Rwanda 2005

8.8 7.9 6.7 5.9 6.5

0

5

10

15

20

48-59 36-47 24-35 12-23 0-11

Months of observed calendar preceding the survey

Rwanda 2010

9.5 10.5

6.4 6.8

9.3

0

5

10

15

20

48-59 36-47 24-35 12-23 0-11

Months of observed calendar preceding the survey

Rwanda 2014-15

13.5

9.5 8.9 8.9

7.3

0

5

10

15

20

48-59 36-47 24-35 12-23 0-11

Months of observed calendar preceding the survey

Senegal 2005

11.5 10.7

8.2 8.6 7.8

0

5

10

15

20

48-59 36-47 24-35 12-23 0-11

Months of observed calendar preceding the survey

Senegal 2010-11
34 

Figure 3.2—Continued

 

 

 

 

Continued 

14.7

9.2 8.3 8.2 8.9

0

5

10

15

20

48-59 36-47 24-35 12-23 0-11

Months of observed calendar preceding the survey

Senegal 2012-13

14.2

8.7

6.7 7.8

4.9

0

5

10

15

20

48-59 36-47 24-35 12-23 0-11

Months of observed calendar preceding the survey

Senegal 2014

16.0

9.2

7.1

8.7 7.8

0

5

10

15

20

48-59 36-47 24-35 12-23 0-11

Months of observed calendar preceding the survey

Senegal 2016

9.3

6.2 6.5

4.7

6.0

0

5

10

15

20

48-59 36-47 24-35 12-23 0-11

Months of observed calendar preceding the survey

Sierra Leone 2008

7.5 7.5 6.7 6.3 5.2

0

5

10

15

20

48-59 36-47 24-35 12-23 0-11

Months of observed calendar preceding the survey

Sierra Leone 2013

7.3 6.8

3.0

4.3 3.2

0

5

10

15

20

48-59 36-47 24-35 12-23 0-11

Months of observed calendar preceding the survey

Swaziland 2006-07

11.9

9.5 8.9

7.2

9.3

0

5

10

15

20

48-59 36-47 24-35 12-23 0-11

Months of observed calendar preceding the survey

Tanzania 2004-05

12.7

8.9 7.8 6.8 6.6

0

5

10

15

20

48-59 36-47 24-35 12-23 0-11

Months of observed calendar preceding the survey

Tanzania 2010
35 

Figure 3.2—Continued

 

 

 

 

Continued 

12.4 11.5

8.9 8.5

7.1

0

5

10

15

20

48-59 36-47 24-35 12-23 0-11

Months of observed calendar preceding the survey

Tanzania 2015-16

9.6 8.8 9.1

7.4 6.4

0

5

10

15

20

48-59 36-47 24-35 12-23 0-11

Months of observed calendar preceding the survey

Uganda 2000-01

14.3

11.0

7.8 7.3 7.6

0

5

10

15

20

48-59 36-47 24-35 12-23 0-11

Months of observed calendar preceding the survey

Uganda 2006

13.3

10.9 9.9

8.3 8.0

0

5

10

15

20

48-59 36-47 24-35 12-23 0-11

Months of observed calendar preceding the survey

Uganda 2011

15.9

13.4

10.1

8.2

6.0

0

5

10

15

20

48-59 36-47 24-35 12-23 0-11

Months of observed calendar preceding the survey

Uganda 2016

8.6

6.2

4.8 5.5 5.3

0

5

10

15

20

48-59 36-47 24-35 12-23 0-11

Months of observed calendar preceding the survey

Zambia 2007

8.0

5.6 4.8 4.7 3.8

0

5

10

15

20

48-59 36-47 24-35 12-23 0-11

Months of observed calendar preceding the survey

Zambia 2013-14

12.1

8.8

6.7 5.8 6.4

0

5

10

15

20

48-59 36-47 24-35 12-23 0-11

Months of observed calendar preceding the survey

Zimbabwe 1994
36 

Figure 3.2—Continued

 

 

Note: While the scale for most surveys in this region extends from 0 to 20 terminated pregnancies per 100 live births, higher

termination ratios in Ghana necessitate an extended scale. 

3.1.3 Patterns of termination ratios in Latin America and the Caribbean 

In contrast to Asia and Africa, multiple surveys in Latin America and the Caribbean show termination ratios 

higher than 20 per 100 live births. Therefore, the scale in Figure 3.3 extends from 0-40 terminated 

pregnancies per 100 live births, rather than from 0-20. 

Compared with the other two regions discussed above, the Latin America and Caribbean region shows a 

greater share of surveys that suggest consistent termination ratios over the course of the calendars. We 

formally test these in the next section. Steady termination ratios appear to be observed in Bolivia 1994 and 

2003, Colombia 2015, Guatemala 1998-99 and 2014-15, Honduras 2005-06, and Nicaragua 1998 and 2001. 

Nonetheless, the majority of surveys in the region show higher termination ratios in the most recent intervals 

and lower termination ratios in earlier intervals. In many cases the increase in termination ratios 

approaching the date of interview is modest, as is evident in the Peru 1996 survey. However, this increase 

is pronounced in the Dominican Republic 1999 and Guyana 2009 surveys. About 25 points separate the 

termination ratios in the most recent interval (0-11 months preceding the date of interview) and the earliest 

interval (48-59 months preceding the date of the interview) in these two surveys. 

 

15.5

8.1

6.8 6.3 5.3

0

5

10

15

20

48-59 36-47 24-35 12-23 0-11

Months of observed calendar preceding the survey

Zimbabwe 1999

11.0

6.7

5.5 6.3

4.9

0

5

10

15

20

48-59 36-47 24-35 12-23 0-11

Months of observed calendar preceding the survey

Zimbabwe 2005-06

10.4

8.9

6.5 6.2 5.4

0

5

10

15

20

48-59 36-47 24-35 12-23 0-11

Months of observed calendar preceding the survey

Zimbabwe 2010-11

12.7

9.2

7.4 6.6 6.3

0

5

10

15

20

48-59 36-47 24-35 12-23 0-11

Months of observed calendar preceding the survey

Zimbabwe 2015
37 

Figure 3.3 Ratios of terminated pregnancies to live births (per 100) in DHS calendars, Latin America and the 

Caribbean 

 

 

 

 

Continued 

10.6 9.5 9.6 9.8

6.8

0

5

10

15

20

25

30

35

40

48-59 36-47 24-35 12-23 0-11

Months of observed calendar preceding the survey

Bolivia 1994

13.1 11.6 9.6 9.8 8.3

0

5

10

15

20

25

30

35

40

48-59 36-47 24-35 12-23 0-11

Months of observed calendar preceding the survey

Bolivia 2003

20.3

14.5 12.6 13.1 11.1

0

5

10

15

20

25

30

35

40

48-59 36-47 24-35 12-23 0-11

Months of observed calendar preceding the survey

Bolivia 2008

17.2 15.2 17.1

13.6 12.1

0

5

10

15

20

25

30

35

40

48-59 36-47 24-35 12-23 0-11

Months of observed calendar preceding the survey

Brazil (Northeast) 1991

17.1 15.3 16.3 15.1

11.2

0

5

10

15

20

25

30

35

40

48-59 36-47 24-35 12-23 0-11

Months of observed calendar preceding the survey

Brazil 1996

13.5 14.2 12.9

17.0

9.6

0

5

10

15

20

25

30

35

40

48-59 36-47 24-35 12-23 0-11

Months of observed calendar preceding the survey

Colombia 1990

15.7

12.7 11.7 10.5 10.0

0

5

10

15

20

25

30

35

40

48-59 36-47 24-35 12-23 0-11

Months of observed calendar preceding the survey

Colombia 1995

21.2 21.7

17.2 16.3

13.0

0

5

10

15

20

25

30

35

40

48-59 36-47 24-35 12-23 0-11

Months of observed calendar preceding the survey

Colombia 2000
38 

Figure 3.3—Continued

 

 

 

 

Continued 

 

26.1

21.1 20.2

17.2 16.3

0

5

10

15

20

25

30

35

40

48-59 36-47 24-35 12-23 0-11

Months of observed calendar preceding the survey

Colombia 2005

26.7

21.2 20.3 18.5 18.1

0

5

10

15

20

25

30

35

40

48-59 36-47 24-35 12-23 0-11

Months of observed calendar preceding the survey

Colombia 2010

19.5

16.7

19.3 20.0 18.5

0

5

10

15

20

25

30

35

40

48-59 36-47 24-35 12-23 0-11

Months of observed calendar preceding the survey

Colombia 2015

19.6

12.2

20.5

13.3 13.8

0

5

10

15

20

25

30

35

40

48-59 36-47 24-35 12-23 0-11

Months of observed calendar preceding the survey

Dominican Republic 1991

22.2 20.2 20.0

13.6 14.7

0

5

10

15

20

25

30

35

40

48-59 36-47 24-35 12-23 0-11

Months of observed calendar preceding the survey

Dominican Republic 1996

35.9

30.0

20.5

14.8 13.3

0

5

10

15

20

25

30

35

40

48-59 36-47 24-35 12-23 0-11

Months of observed calendar preceding the survey

Dominican Republic 1999

22.2

18.1 19.5

16.6

13.1

0

5

10

15

20

25

30

35

40

48-59 36-47 24-35 12-23 0-11

Months of observed calendar preceding the survey

Dominican Republic 2002

7.8 5.6 5.9 5.3 4.4

0

5

10

15

20

25

30

35

40

48-59 36-47 24-35 12-23 0-11

Months of observed calendar preceding the survey

Guatemala 1995
39 

Figure 3.3—Continued

 

 

 

 

Continued 

 

6.8 7.9

5.3 7.4 6.3

0

5

10

15

20

25

30

35

40

48-59 36-47 24-35 12-23 0-11

Months of observed calendar preceding the survey

Guatemala 1998-99

10.1 8.2 7.9 7.1 8.0

0

5

10

15

20

25

30

35

40

48-59 36-47 24-35 12-23 0-11

Months of observed calendar preceding the survey

Guatemala 2014-15

39.7

30.2

24.5

19.5

13.9

0

5

10

15

20

25

30

35

40

48-59 36-47 24-35 12-23 0-11

Months of observed calendar preceding the survey

Guyana 2009

10.3 10.9 9.6

6.8 8.1

0

5

10

15

20

25

30

35

40

48-59 36-47 24-35 12-23 0-11

Months of observed calendar preceding the survey

Honduras 2005-06

13.9 11.7 10.0 10.1 8.1

0

5

10

15

20

25

30

35

40

48-59 36-47 24-35 12-23 0-11

Months of observed calendar preceding the survey

Honduras 2011-12

9.9 7.8 8.8 7.2 7.5

0

5

10

15

20

25

30

35

40

48-59 36-47 24-35 12-23 0-11

Months of observed calendar preceding the survey

Nicaragua 1998

9.9

7.1 7.6 7.5 8.1

0

5

10

15

20

25

30

35

40

48-59 36-47 24-35 12-23 0-11

Months of observed calendar preceding the survey

Nicaragua 2001

13.4 13.5

10.5 9.5 10.3

0

5

10

15

20

25

30

35

40

48-59 36-47 24-35 12-23 0-11

Months of observed calendar preceding the survey

Paraguay 1990
40 

Figure 3.3—Continued

 

 

 

 

Continued 

 

12.9 12.5 10.1 8.5 9.6

0

5

10

15

20

25

30

35

40

48-59 36-47 24-35 12-23 0-11

Months of observed calendar preceding the survey

Peru 1991-92

13.3 11.4 10.1 8.5 8.7

0

5

10

15

20

25

30

35

40

48-59 36-47 24-35 12-23 0-11

Months of observed calendar preceding the survey

Peru 1996

12.5 11.9 10.9 9.8 8.7

0

5

10

15

20

25

30

35

40

48-59 36-47 24-35 12-23 0-11

Months of observed calendar preceding the survey

Peru 2000

17.0

11.1 12.5 10.6 9.3

0

5

10

15

20

25

30

35

40

48-59 36-47 24-35 12-23 0-11

Months of observed calendar preceding the survey

Peru 2004-06

20.3

16.7 14.5 13.6

8.9

0

5

10

15

20

25

30

35

40

48-59 36-47 24-35 12-23 0-11

Months of observed calendar preceding the survey

Peru 2007-08

16.7

19.5

14.8 13.8

11.0

0

5

10

15

20

25

30

35

40

48-59 36-47 24-35 12-23 0-11

Months of observed calendar preceding the survey

Peru 2009

25.2

17.0 18.2

12.7 11.9

0

5

10

15

20

25

30

35

40

48-59 36-47 24-35 12-23 0-11

Months of observed calendar preceding the survey

Peru 2010

20.5 19.9

14.9 16.0

12.7

0

5

10

15

20

25

30

35

40

48-59 36-47 24-35 12-23 0-11

Months of observed calendar preceding the survey

Peru 2011
41 

Figure 3.3—Continued

3.1.4 Patterns of termination ratios in Other Countries 

The Other Countries region is distinct in several ways compared with the other regions in the study. First, 

this region exhibits the highest termination ratios of all the surveys in this study, as shown in Figure 3.4. 

Four surveys7

 display termination ratios of about 100 per 100 live births or more, meaning more than 50% 

of pregnancies conclude with termination. In the 0-11 months preceding interview in the Armenia 2000 

survey, the observed termination ratio was 153 terminated pregnancies per 100 live births. Accordingly, the 

scale of the plots is extended to 0 to 175 for seven surveys with the highest termination ratios, 0 to 60 for 

six surveys with medium-high termination ratios, and from 0 to 40 for the remaining 19 surveys in the 

region. 

Of the 32 surveys in the Other Countries region, three surveys (Egypt 2005, Egypt 2014, and Morocco 

2003-04) suggest consistent observed termination ratios over the observation period of the calendars. Other 

surveys suggest some type of inconsistency in termination ratios over the observation period of the 

calendars. The most common pattern of inconsistency is similar to that observed in the other three regions: 

observed termination ratios are higher in the more recent intervals of the observation period compared with 

earlier intervals. This pattern is observed in 20 of the 32 surveys in the Other Countries region. 

The Other Countries region is also distinguished from the other three regions in that it is the only region 

where termination ratios decrease over the course of the calendar. In six surveys, the termination ratio in 

the most recent interval is lower than that observed in the earliest interval of the calendar. It is predominantly 

the surveys with the highest termination ratios that show this pattern of lower termination ratios closer to 

the date of interview. Kazakhstan 1999 is a counterexample, illustrating a pattern of very high termination 

ratios that are highest near the date of interview and lower in earlier intervals of the calendar. 

In two other surveys, Albania 2008-09 and Armenia 2000, higher termination ratios are observed in the 

middle of the observation period than in either the more recent or earlier interval. Finally, Jordan 2009 

exhibits inconsistency throughout the observation period, without a clear pattern of increasing or decreasing 

termination ratios. 

 

7

 Armenia 2000, Armenia 2005, Azerbaijan 2006, Kazakhstan 1999. 

20.2

16.4 17.8

14.8 14.7

0

5

10

15

20

25

30

35

40

48-59 36-47 24-35 12-23 0-11

Months of observed calendar preceding the survey

Peru 2012
42 

Figure 3.4 Ratios of terminated pregnancies to live births (per 100) in DHS calendars, Other Countries 

 

 

 

 

Continued 

18.1 20.0 20.3

17.0 15.3

0

5

10

15

20

25

30

35

40

48-59 36-47 24-35 12-23 0-11

Months of observed calendar preceding the survey

Albania 2008-09

152.5 162.5 170.3

146.3

134.2

0

20

40

60

80

100

120

140

160

180

48-59 36-47 24-35 12-23 0-11

Months of observed calendar preceding the survey

Armenia 2000

120.8

95.3

113.2 107.5

119.3

0

20

40

60

80

100

120

140

160

180

48-59 36-47 24-35 12-23 0-11

Months of observed calendar preceding the survey

Armenia 2005

55.3 50.8

62.3 71.2

85.9

0

20

40

60

80

100

120

140

160

180

48-59 36-47 24-35 12-23 0-11

Months of observed calendar preceding the survey

Armenia 2010

40.4 46.6 54.1

67.5

52.2

0

20

40

60

80

100

120

140

160

180

48-59 36-47 24-35 12-23 0-11

Months of observed calendar preceding the survey

Armenia 2015-16

128.3

102.4

122.2

79.5 82.1

0

20

40

60

80

100

120

140

160

180

48-59 36-47 24-35 12-23 0-11

Months of observed calendar preceding the survey

Azerbaijan 2006

17.9

14.2 16.0

11.0 10.1

0

5

10

15

20

25

30

35

40

48-59 36-47 24-35 12-23 0-11

Months of observed calendar preceding the survey

Egypt 1992

17.6 15.7 16.4

11.9 9.9

0

5

10

15

20

25

30

35

40

48-59 36-47 24-35 12-23 0-11

Months of observed calendar preceding the survey

Egypt 1995
43 

Figure 3.4—Continued

 

 

 

Continued 

15.1 16.0 14.2 13.3 11.5

0

5

10

15

20

25

30

35

40

48-59 36-47 24-35 12-23 0-11

Months of observed calendar preceding the survey

Egypt 2000

12.5 13.1 13.9

9.3 9.3

0

5

10

15

20

25

30

35

40

48-59 36-47 24-35 12-23 0-11

Months of observed calendar preceding the survey

Egypt 2003

16.3 15.3 14.0 12.2 13.8

0

5

10

15

20

25

30

35

40

48-59 36-47 24-35 12-23 0-11

Months of observed calendar preceding the survey

Egypt 2005

14.4 14.0 13.5

10.9 9.6

0

5

10

15

20

25

30

35

40

48-59 36-47 24-35 12-23 0-11

Months of observed calendar preceding the survey

Egypt 2008

14.3 14.3 14.4

11.4 13.0

0

5

10

15

20

25

30

35

40

48-59 36-47 24-35 12-23 0-11

Months of observed calendar preceding the survey

Egypt 2014

19.2

16.0 15.2 13.0 13.0

0

5

10

15

20

25

30

35

40

48-59 36-47 24-35 12-23 0-11

Months of observed calendar preceding the survey

Jordan 1990
44 

Figure 3.4—Continued

 

 

 

 

Continued 

23.8

21.4

17.6 15.5 14.3

0

5

10

15

20

25

30

35

40

48-59 36-47 24-35 12-23 0-11

Months of observed calendar preceding the survey

Jordan 1997

19.9 21.7 21.2

17.0 16.3

0

5

10

15

20

25

30

35

40

48-59 36-47 24-35 12-23 0-11

Months of observed calendar preceding the survey

Jordan 2002

24.2

19.2

13.5 13.6 12.5

0

5

10

15

20

25

30

35

40

48-59 36-47 24-35 12-23 0-11

Months of observed calendar preceding the survey

Jordan 2007

21.2 19.0 18.6

24.8

19.9

0

5

10

15

20

25

30

35

40

48-59 36-47 24-35 12-23 0-11

Months of observed calendar preceding the survey

Jordan 2009

27.1

31.4

20.9

17.8

15.2

0

5

10

15

20

25

30

35

40

48-59 36-47 24-35 12-23 0-11

Months of observed calendar preceding the survey

Jordan 2012

94.9

80.2 90.5 81.5 72.4

0

20

40

60

80

100

120

140

160

180

48-59 36-47 24-35 12-23 0-11

Months of observed calendar preceding the survey

Kazakhstan 1999

31.1 29.0 28.7

32.5 31.9

0

5

10

15

20

25

30

35

40

48-59 36-47 24-35 12-23 0-11

Months of observed calendar preceding the survey

Kyrgyz Republic 2012

90.5 79.9 74.8 78.6

98.4

0

20

40

60

80

100

120

140

160

180

48-59 36-47 24-35 12-23 0-11

Months of observed calendar preceding the survey

Moldova 2005
45 

Figure 3.4—Continued

 

 

 

 

Continued 

11.7

8.3 8.0 7.3 6.3

0

5

10

15

20

25

30

35

40

48-59 36-47 24-35 12-23 0-11

Months of observed calendar preceding the survey

Morocco 1992

14.4 14.3

11.1 11.6 12.5

0

5

10

15

20

25

30

35

40

48-59 36-47 24-35 12-23 0-11

Months of observed calendar preceding the survey

Morocco 2003-04

23.6

16.8 18.5 18.9 17.6

0

5

10

15

20

25

30

35

40

48-59 36-47 24-35 12-23 0-11

Months of observed calendar preceding the survey

Tajikistan 2012

43.3

37.6

50.6

35.9

25.0

0

10

20

30

40

50

60

48-59 36-47 24-35 12-23 0-11

Months of observed calendar preceding the survey

Turkey 1993

36.2 34.6 36.1

27.9 27.6

0

10

20

30

40

50

60

48-59 36-47 24-35 12-23 0-11

Months of observed calendar preceding the survey

Turkey 1998

34.6

28.9 26.6 28.2 25.6

0

10

20

30

40

50

60

48-59 36-47 24-35 12-23 0-11

Months of observed calendar preceding the survey

Turkey 2003

31.8

27.9 27.7 25.6 23.8

0

10

20

30

40

50

60

48-59 36-47 24-35 12-23 0-11

Months of observed calendar preceding the survey

Turkey 2008

24.4 25.3 26.4

22.9

18.5

0

10

20

30

40

50

60

48-59 36-47 24-35 12-23 0-11

Months of observed calendar preceding the survey

Turkey 2013
46 

Figure 3.4—Continued

 

Note: While the scale for most surveys in this region extends from 0 to 40 terminated pregnancies per 100 live births, higher

termination ratios are found in Armenia, Azerbaijan, Kazakhstan, Moldova, Turkey, and Ukraine, requiring an extended scale. 

3.2 Testing Within-Survey Consistency 

The previous section showed that termination ratios appear to be inconsistently reported within most 

surveys—termination ratios tend to be higher the closer to the date of interview. The graphical analysis of 

consistency is illustrative but hard to judge definitively. We complete our analysis of within-survey 

consistency with a more formal, statistical test of the difference between termination ratios observed in the 

first, most recent interval (0-11 months preceding the interview) and those observed in the fifth, earliest 

interval (48-59 months preceding the interview). Table 3.1 shows the termination ratios in the first and the 

fifth intervals of the observation period, their absolute and relative difference, and the level of statistical 

significance. 

The results of the statistical test indicate that a large majority of the surveys (128 of the 162) are marked by 

within-survey inconsistency. In about 20% of surveys (34) we fail to reject the null hypothesis and detect 

no significant difference between the observed termination ratios in the first and last intervals. These 

surveys can be considered to demonstrate within-survey consistency. 

A majority of surveys are found to be within-survey inconsistent in all regions. Within-survey consistency 

appears to be somewhat less common in Asia, at 26 of 30 surveys within-survey inconsistent, compared 

with the Other Countries region, where in Other Countries, 11 of the 32 surveys are found to be withinsurvey consistent while 21 of 32 are within-survey inconsistent. In Africa, 13 of 54 surveys are withinsurvey consistent, while 54 are within-survey inconsistent. In Latin America and the Caribbean, 6 of 33 

surveys are within-survey consistent and 27 of 33 surveys are within-survey inconsistent. 

In a few surveys the results of the statistical test contradict the apparent pattern shown in graphical analysis 

of the plots in Figures 3.1-3.4. In 10 surveys,8

 termination ratios appear to be higher in intervals closer to 

the date of interview, but there is no statistical difference between the first and the fifth intervals. This is 

also the case for three surveys in the Other Countries region,9

 where termination ratios appear to be lower 

 

8

 Nepal 2006, Vietnam 2002, Gambia 2013, Lesotho 2009 and 2014, Malawi 2004, Mozambique 2003, Namibia 2006-

07, Rwanda 2014-15, and Tanzania 2004-05. 

9

 Armenia 2015-16, Kyrgyz Republic 2012, and Moldova 2005. 

40.3

52.7

46.0

58.5 57.7

0

10

20

30

40

50

60

48-59 36-47 24-35 12-23 0-11

Months of observed calendar preceding the survey

Ukraine 2007

15.3 14.4 13.4 12.1 10.6

0

5

10

15

20

25

30

35

40

48-59 36-47 24-35 12-23 0-11

Months of observed calendar preceding the survey

Yemen 2013
47 

closer to the date of the interview. In the Other Countries region, the three surveys10 with apparent 

inconsistency without a clear increasing or decreasing pattern also show no significant difference between 

the endpoints of the observation period. These surveys are designated within-survey consistent. In three 

surveys in Latin America and the Caribbean—Bolivia 1994 and 2003 and Honduras 2005-06—termination 

ratios appeared to be consistent across the observation period in the graphical analysis, but the statistical 

test shows a significant difference between the first and last intervals; these surveys are designated withinsurvey inconsistent. 

Table 3.1 Measures of consistency within single surveys 

Survey 

Termination 

ratio in 

Interval 1 

(0-11 months) 

Termination 

ratio in 

Interval 5 

(46-59 months) 

Absolute 

difference 

Relative 

difference p-value [1] 

Asia 

Afghanistan 2015 12.4 8.8 3.5 29% * 

Bangladesh 1993-94 10.1 7.4 2.7 27% * 

Bangladesh 1996-97 14.3 9.6 4.6 32% ** 

Bangladesh 1999-00 15.9 11.0 4.9 31% ** 

Bangladesh 2004 19.3 13.3 6.1 31% ** 

Bangladesh 2007 16.1 10.6 5.5 34% ** 

Bangladesh 2011 18.9 13.0 5.9 31% *** 

Bangladesh 2014 17.1 11.2 5.9 34% *** 

Cambodia 2010 29.2 16.6 12.6 43% *** 

Cambodia 2014 38.9 25.2 13.7 35% *** 

India 2005-06 17.0 8.3 8.6 51% *** 

India 2015-16 15.6 9.3 6.3 40% *** 

Indonesia 1991 7.6 4.8 2.8 37% ** 

Indonesia 1994 9.3 5.4 3.9 42% *** 

Indonesia 1997 8.7 4.6 4.1 47% *** 

Indonesia 2002-03 9.5 6.4 3.1 33% * 

Indonesia 2007 13.0 6.4 6.6 51% *** 

Indonesia 2012 13.3 8.9 4.3 33% *** 

Maldives 2009 19.3 11.1 8.2 43% ** 

Myanmar 2015-16 11.0 7.4 3.6 33% * 

Nepal 2006 13.9 9.9 4.0 29% 

Nepal 2011 20.8 14.9 5.8 28% * 

Nepal 2016 29.7 18.2 11.5 39% *** 

Pakistan 2012-13 20.8 17.4 3.4 16% 

Philippines 1993 12.5 8.5 4.0 32% *** 

Philippines 1998 13.9 9.9 4.0 29% * 

Philippines 2003 12.4 8.3 4.0 33% ** 

Timor-Leste 2009-10 3.2 2.9 0.3 10% 

Vietnam 1997 37.9 20.0 17.9 47% *** 

Vietnam 2002 48.8 35.7 13.1 27% 

Continued 

 

 

10 Albania 2008-09, Armenia 2000, and Jordan 2009. 
48 

Table 3.1—Continued

Survey 

Termination 

ratio in 

Interval 1 

(0-11 months) 

Termination 

ratio in 

Interval 5 

(46-59 months) 

Absolute 

difference 

Relative 

difference p-value [1] 

Africa 

Angola 2015-16 9.3 4.2 5.1 55% *** 

Benin 2006 8.9 7.5 1.4 16% 

Benin 2011-12 4.9 2.6 2.4 48% *** 

Burkina Faso 2003 6.5 6.2 0.3 5% 

Burkina Faso 2010 6.3 5.0 1.2 20% 

Burundi 2010 10.4 5.7 4.7 45% ** 

Burundi 2016-17 10.3 6.7 3.5 34% *** 

Comoros 2012 11.9 6.5 5.4 45% * 

Ethiopia 2005 4.6 2.7 1.9 42% ** 

Ethiopia 2011 9.5 3.0 6.5 69% *** 

Ethiopia 2016 6.6 3.1 3.5 53% *** 

Gambia 2013 8.2 5.4 2.9 35% 

Ghana 2003 17.8 7.6 10.1 57% *** 

Ghana 2008 20.3 10.5 9.8 48% *** 

Ghana 2014 28.5 12.6 15.9 56% *** 

Guinea 2005 10.9 6.2 4.7 43% ** 

Kenya 1998 8.0 4.0 4.0 51% ** 

Kenya 2003 7.9 3.5 4.4 55% *** 

Kenya 2008-09 8.7 4.8 3.9 45% * 

Kenya 2014 10.1 4.6 5.5 55% *** 

Lesotho 2009 5.0 5.6 -0.6 -11% 

Lesotho 2014 8.2 9.2 -0.9 -11% 

Liberia 2013 19.8 6.3 13.5 68% *** 

Madagascar 2003-04 9.5 5.6 3.9 41% * 

Madagascar 2008-09 9.8 5.9 3.8 39% *** 

Malawi 2000 6.8 4.6 2.2 33% * 

Malawi 2004 5.6 5.7 -0.1 -2% 

Malawi 2010 7.4 4.5 2.9 39% *** 

Malawi 2015-16 8.1 4.0 4.2 51% *** 

Mali 2001 9.8 6.2 3.6 37% ** 

Mali 2006 10.4 6.2 4.2 41% ** 

Mali 2012-13 3.6 3.1 0.5 15% 

Mozambique 2003 9.2 7.5 1.6 18% 

Mozambique 2011 8.1 3.8 4.3 53% *** 

Namibia 2006-07 8.0 5.9 2.1 26% 

Namibia 2013 10.0 5.6 4.4 44% * 

Niger 2006 6.6 5.2 1.5 22% 

Niger 2012 9.9 6.3 3.6 37% ** 

Nigeria 2008 8.7 5.4 3.3 38% *** 

Nigeria 2013 9.6 4.8 4.8 50% *** 

Rwanda 2000 8.5 6.3 2.2 26% * 

Rwanda 2005 9.8 5.2 4.6 47% *** 

Rwanda 2010 8.8 6.5 2.3 26% * 

Rwanda 2014-15 9.5 9.3 0.2 3% 

Senegal 2005 13.5 7.3 6.2 46% *** 

Senegal 2010-11 11.5 7.8 3.7 32% *** 

Senegal 2012-13 14.7 8.9 5.7 39% ** 

Senegal 2014 14.2 4.9 9.2 65% *** 

Continued 
49 

Table 3.1—Continued

Survey 

Termination 

ratio in 

Interval 1 

(0-11 months) 

Termination 

ratio in 

Interval 5 

(46-59 months) 

Absolute 

difference 

Relative 

difference p-value [1] 

Africa cont’d 

Senegal 2015 13.4 6.5 6.9 51% *** 

Senegal 2016 16.0 7.8 8.3 52% ** 

Sierra Leone 2008 9.3 6.0 3.2 35% * 

Sierra Leone 2013 7.5 5.2 2.4 32% ** 

Swaziland 2006-07 7.3 3.2 4.1 56% ** 

Tanzania 2004-05 11.9 9.3 2.6 22% 

Tanzania 2010 12.7 6.8 5.9 46% *** 

Tanzania 2015-16 12.4 7.1 5.3 43% *** 

Uganda 2000-01 9.6 6.4 3.3 34% * 

Uganda 2006 14.3 7.6 6.6 47% *** 

Uganda 2011 13.3 8.0 5.3 40% *** 

Uganda 2016 15.9 6.0 9.8 62% *** 

Zambia 2007 8.6 5.5 3.1 36% * 

Zambia 2013-14 8.0 3.8 4.1 52% *** 

Zimbabwe 1994 12.1 6.4 5.7 47% *** 

Zimbabwe 1999 15.5 5.3 10.2 66% *** 

Zimbabwe 2005-06 11.0 4.9 6.1 55% *** 

Zimbabwe 2010-11 10.4 5.4 5.0 48% *** 

Zimbabwe 2015 12.7 6.3 6.5 51% *** 

LAC 

Bolivia 1994 10.6 6.8 3.8 36% ** 

Bolivia 2003 13.1 8.3 4.8 36% *** 

Bolivia 2008 20.3 11.1 9.2 45% *** 

Brazil NE 1991 17.2 12.1 5.1 30% * 

Brazil 1996 17.1 11.2 5.9 34% ** 

Colombia 1990 14.2 9.6 4.5 32% * 

Colombia 1995 15.7 10.5 5.2 33% ** 

Colombia 2000 21.7 13.0 8.7 40% *** 

Colombia 2005 26.1 16.3 9.8 38% *** 

Colombia 2010 26.7 18.5 8.3 31% *** 

Colombia 2015 19.5 18.5 1.0 5% 

Dominican Republic 1991 19.6 13.3 6.4 32% * 

Dominican Republic 1996 22.2 14.7 7.6 34% ** 

Dominican Republic 1999 35.9 13.3 22.6 63% ** 

Dominican Republic 2002 22.2 13.1 9.1 41% *** 

Guatemala 1995 7.8 4.4 3.4 43% ** 

Guatemala 1998-99 6.8 6.3 0.6 8% 

Guatemala 2014-15 10.1 8.0 2.1 21% 

Guyana 2009 39.7 13.9 25.8 65% *** 

Honduras 2005-06 10.9 8.1 2.8 25% * 

Honduras 2011-12 13.9 8.1 5.8 42% *** 

Nicaragua 1998 9.9 7.2 2.7 27% 

Nicaragua 2001 9.9 7.6 2.2 23% 

Paraguay 1990 13.5 10.3 3.3 24% 

Peru 1991-92 12.5 9.6 2.8 23% * 

Peru 1996 13.3 8.5 4.8 36% *** 

Peru 2000 11.9 8.7 3.2 27% ** 

Peru 2004-06 17.0 9.3 7.7 45% * 

Peru 2007-08 20.3 8.9 11.4 56% *** 

Continued 
50 

Table 3.1—Continued

Survey 

Termination 

ratio in 

Interval 1 

(0-11 months) 

Termination 

ratio in 

Interval 5 

(46-59 months) 

Absolute 

difference 

Relative 

difference p-value [1] 

LAC cont’d 

Peru 2009 16.7 11.0 5.7 34% *** 

Peru 2010 25.2 11.9 13.3 53% *** 

Peru 2011 19.9 12.7 7.2 36% ** 

Peru 2012 20.2 14.8 5.4 27% ** 

Other Countries 

Albania 2008-09 18.1 15.3 2.7 15% 

Armenia 2000 152.5 134.2 18.3 12% 

Armenia 2005 120.8 119.3 1.5 1% 

Armenia 2010 55.3 85.9 -30.6 -55% * 

Armenia 2015-16 40.4 52.2 -11.8 -29% 

Azerbaijan 2006 128.3 79.5 48.8 38% ** 

Egypt 1992 17.9 10.1 7.8 43% *** 

Egypt 1995 17.6 9.9 7.8 44% *** 

Egypt 2000 15.1 11.5 3.6 24% ** 

Egypt 2003 13.1 9.3 3.8 29% * 

Egypt 2005 16.3 13.8 2.5 15% 

Egypt 2008 14.4 9.6 4.8 33% *** 

Egypt 2014 14.4 13.0 1.4 10% 

Jordan 1990 19.2 13.0 6.2 32% *** 

Jordan 1997 23.8 14.3 9.5 40% *** 

Jordan 2002 19.9 16.3 3.6 18% 

Jordan 2007 24.2 12.5 11.7 48% *** 

Jordan 2009 21.2 19.9 1.3 6% 

Jordan 2012 27.1 15.2 11.9 44% *** 

Kazakhstan 1999 94.9 72.4 22.5 24% * 

Kyrgyz Republic 2012 31.1 32.5 -1.4 -4% 

Moldova 2005 90.5 98.4 -7.9 -9% 

Morocco 1992 11.7 6.3 5.5 47% *** 

Morocco 2003-04 14.3 12.5 1.8 13% 

Tajikistan 2012 23.6 17.6 6.0 25% * 

Turkey 1993 43.3 25.0 18.3 42% *** 

Turkey 1998 36.2 27.9 8.4 23% * 

Turkey 2003 34.6 25.6 9.0 26% * 

Turkey 2008 31.8 23.8 8.0 25% * 

Turkey 2013 25.3 18.5 6.8 27% * 

Ukraine 2007 40.3 58.5 -18.2 -45% * 

Yemen 2013 15.3 10.6 4.7 31% *** 

[1] Result of a Wald test of equivalence of the termination ratio in the first and fifth interval. 

* p≤0.05; ** p≤0.01; *** p≤0.001 
51 

4 TRENDS IN TERMINATION RATIOS ACROSS MULTIPLE 

SURVEYS 

4.1 Models of Between-Survey Consistency and Between-Survey 

Inconsistency 

So far, our study has examined only within-survey consistency. Of the 62 countries contributing surveys to 

the study, 34 countries have a total of 124 consecutive surveys whose calendars adjoin or overlap. These 

124 surveys can be used to examine between-survey consistency. 

Of particular focus for this analysis are the adjoining (or overlapping) moments in consecutive calendars. 

To this point, we have assumed that real and observed termination ratios should be constant over the course 

of a single calendar if the calendar manifests within-survey consistency. In this scenario, examination of 

the adjoining point of consecutive calendars should appear as a pattern over time like that shown for 

Country A in Figure 4.1. The observed termination ratios are similar at the adjoining moments and observed 

termination ratios are consistent over the course of each separate calendar. These surveys manifest both 

within-survey consistency and between-survey consistency. 

Figure 4.1 Model of consistent calendars with level ratios of terminations to live births over time (Country A) 

and increasing ratios of terminations to live births over time (Country B) 

 

However, analysis presented in the previous chapter has indicated that termination ratios are in fact seldom 

consistent within single surveys. Instead, termination ratios are typically higher the closer to the date of 

interview, and lower in the earliest periods of the calendar. This pattern could either result from an 

inconsistency in reporting of terminated pregnancies, or be due to a real secular trend in the underlying ratio 

of terminated pregnancies to live births. 

A secular trend could occur if a fertility regime changes in a way that increases the ratio of terminations to 

live births—for example, desire for fewer children, increasing contraceptive use, and changes in the 

contraceptive mix could result in fewer births in a population. If the level of contraceptive use does not 

keep pace with the demand, however, and the level of unmet need for family planning increases, and there 

are more unintended pregnancies, more women may avoid unintended pregnancies through induced 

abortion, resulting in an increased termination ratio. Termination ratios can also increase if there are changes 

Ratio of terminations to live births

Time

Country A

DHS 1 DHS 2 DHS 3

Ratio of terminations to live births

Time

Country B

DHS 1 DHS 2 DHS 3
52 

in the willingness to terminate an unintended pregnancy, if safe abortion services become more available, 

or if the legal status of abortion changes. 

On the other hand, we generally expect improvements in population health and health care systems over 

time. Such improvements may reduce the level of preventable miscarriages and stillbirths, which could 

result in modest declines in the termination ratio. 

The analysis of 124 consecutive surveys in 34 countries allows us to: 

• examine between-survey consistency at the adjoining moments for each of these pairs of surveys; 

• examine whether a real secular trend contributes to the within-survey inconsistency observed in 

many surveys in the previous section. 

If there is no trend and surveys are characterized by between-survey consistency, we would expect to see 

termination ratios like those depicted in Country A in Figure 4.1. If there is a real secular trend toward 

higher termination ratios over time, but surveys are nonetheless characterized by between-survey 

consistency, we would expect to see termination ratios like those depicted in Country B in Figure 4.1, which 

shows within-survey inconsistency but between-survey consistency, suggesting that the within-survey 

inconsistency can be attributed to a real secular trend. A similar trend could be observed in the opposing 

direction toward declining termination ratios over time. 

Between-survey inconsistency is evident in the models presented in Figure 4.2, as shown by the gap 

between two observed termination ratios at adjoining points in time of two pairs of surveys. Country C 

depicts a pattern of no secular trend in termination ratios over time. Within-survey inconsistency is 

accompanied by between-survey inconsistency. In contrast, Country D in Figure 4.2 depicts a pattern of an 

evident secular trend toward higher termination ratios over time. A portion of the observed within-survey 

inconsistency can be attributed to this secular trend, but not all of the within-survey inconsistency. Some 

degree of between-survey inconsistency persists. 

Figure 4.2 Model of inconsistent calendars with level ratios of terminations to live births over time (Country C) 

and increasing ratios of terminations to live births over time (Country D) 

 

The figures in the following sections depict the termination ratios from 123 consecutive surveys in 34 

countries. Graphical examination of these suggests the existence of all four distinct patterns: (1) inconsistent 

surveys with no evidence of a secular trend; (2) consistent surveys with no evidence of a secular trend; 

Ratio of terminations to live births

Time

Country C

DHS 1 DHS 2 DHS 3

Ratio of terminations to live births

Time

Country D

DHS 1 DHS 2 DHS 3
53 

(3) consistent surveys with evidence of a secular trend; (4) inconsistent surveys with evidence of a secular 

trend. 

4.2 Pattern 1: Inconsistent Surveys with No Evidence of Secular Trend 

The most common pattern observed is no evidence of a secular trend in termination ratios over time, but 

evidence of inconsistency both within and between surveys. In 18 countries some or all of the surveys 

exhibit this pattern, as illustrated for each country in Figures 4.3 through 4.21 respectively. This pattern is 

found in all four regions, comprising two countries in Asia, 14 countries in Africa, one country in Latin 

America and the Caribbean, and two countries in the Other Countries region. 

Indonesia offers a good illustrative example both because the pattern shown in Indonesia’s surveys typifies 

the pattern in this group, and because Indonesia has six DHS surveys over about 25 years between 1987 

and 2012. As Figure 4.3 shows, the earliest surveys are each marked by higher termination ratios at more 

recent (closer to the time of data collection) intervals and lower termination ratios in earlier intervals, 

without any indication of an increase in the termination ratio over the survey period. Each of the first four 

surveys suggests a similar minimum and maximum observed termination ratio, though the last two surveys 

suggest a greater range over the course of one survey than the earlier four surveys. Observation of the 

adjoining and overlapping moments indicates that the more recent period of a previous survey consistently 

shows higher termination ratios than in the subsequent survey. The two most recent Indonesia surveys may 

hint at a slight secular rise in the termination ratio in recent years, however the dominant pattern again is a 

discrepancy between the termination ratios at adjoining points that is large and perhaps increasing compared 

with that in earlier survey pairs. 

Figure 4.3 Ratios of terminated pregnancies to live births (per 100) in consecutive DHS calendars, 

Indonesia 

The three surveys in the Philippines (Figure 4.4) show a similar discrepancy between the adjoining points 

of the earliest two surveys, as in Indonesia, and between the most recent survey pair, though this does 

require extrapolating forward in time the termination ratios observed in the Philippines 1996 DHS. Each of 

the three surveys produces termination ratios of about 9 in their earliest periods and approaching 12-14 in 

their most recent intervals, without any sign of an increasing trend over time. 

0

5

10

15

20

25

1988 1990 1992 1994 1996 1998 2000 2002 2004 2006 2008 2010 2012

Indonesia 1991 Indonesia 1994 Indonesia 1997 Indonesia 2002-03 Indonesia 2007 Indonesia 2012
54 

Figure 4.4 Ratios of terminated pregnancies to live births (per 100) in consecutive DHS calendars, 

Philippines 

The two surveys in Burundi (Figure 4.5) also show initial termination ratios near 5, increasing to about 10 

over the course of each survey, but the gap between the two surveys when extrapolated from their terminal 

points shows discrepant observed ratios. In Ethiopia (Figure 4.6), the relatively steep increase in termination 

ratios observed over the course of the 2011 DHS is not corroborated by the termination ratios observed in 

either the preceding or successive survey. 

Figure 4.5 Ratios of terminated pregnancies to live births (per 100) in consecutive DHS calendars, Burundi 

Figure 4.6 Ratios of terminated pregnancies to live births (per 100) in consecutive DHS calendars, Ethiopia 

0

5

10

15

20

25

1989 1991 1993 1995 1997 1999 2001 2003

Philippines 1993 Philippines 1998 Philippines 2003

0

5

10

15

20

25

2006 2008 2010 2012 2014 2016

Burundi 2010 Burundi 2016-2017

0

5

10

15

20

25

2002 2004 2006 2008 2010 2012 2014 2016

Ethiopia 2005 Ethiopia 2011 Ethiopia 2016
55 

Likewise, the four surveys in Kenya (Figure 4.7) depict a marked increase in the termination ratios within 

each survey and sizable gaps between the adjoining moments of survey pairs. 

Figure 4.7 Ratios of terminated pregnancies to live births (per 100) in consecutive DHS calendars, Kenya 

The two surveys in Madagascar (Figure 4.8) depict a similar pattern as Kenya, with termination ratios 

falling in a similar range. The most recent interval produces nearly identical termination ratios at about 10, 

with a gap of about 5 points at their adjoining moment. 

Figure 4.8 Ratios of terminated pregnancies to live births (per 100) in consecutive DHS calendars, 

Madagascar 

Malawi’s two earliest surveys, in 2000 and 2004 (Figure 4.9), show variation within a narrow range, and 

the gap in the observed termination ratios from their adjoining moment in 2000 is not large. However, the 

level of within-survey inconsistency and the gap between the two most recent surveys are wider. 

0

5

10

15

20

25

1994 1996 1998 2000 2002 2004 2006 2008 2010 2012 2014

Kenya 1998 Kenya 2003 Kenya 2008-09 Kenya 2014

0

5

10

15

20

25

2001 2003 2005 2007 2009

Madagascar 2003-04 Madagascar 2008-09
56 

Figure 4.9 Ratios of terminated pregnancies to live births (per 100) in consecutive DHS calendars, Malawi 

Mali presents an interesting pattern (Figure 4.10). The three surveys indicate the within-survey and 

between-survey inconsistency that is typical of all surveys in this group. However, the termination ratios 

observed throughout the Mali 2012-13 DHS are consistently lower than those observed in either of the 

previous two surveys. Despite its lower termination ratios, the ratios at the most recent point of the calendar 

(2012) exceed those measured at its earliest points in 2008-09.

Figure 4.10 Ratios of terminated pregnancies to live births (per 100) in consecutive DHS calendars, Mali 

In Nigeria (Figure 4.11), the termination ratio in each of the two surveys, in 2008 and 2013, show a nearly 

monotonic, linear increase with time, with a disjuncture between them in 2008-2009, whereas in Rwanda 

(Figure 4.12), the disjunctures between the termination ratios in the country’s four surveys are accompanied 

by jagged inconsistency within each of the surveys. Additionally, the (nearly) adjoining moment between 

the two most recent surveys produces similar termination ratios. 

0

5

10

15

20

25

1997 1999 2001 2003 2005 2007 2009 2011 2013 2015

Malawi 2000 Malawi 2004 Malawi 2010 Malawi 2015-16

0

5

10

15

20

25

1998 2000 2002 2004 2006 2008 2010 2012

Mali 2001 Mali 2006 Mali 2012-13
57 

Figure 4.11 Ratios of terminated pregnancies to live births (per 100) in consecutive DHS calendars, Nigeria 

Figure 4.12 Ratios of terminated pregnancies to live births (per 100) in consecutive DHS calendars, Rwanda 

The first three surveys in Senegal (Figure 4.13) show discrepancies between them. The 2012-13 survey, 

which has a calendar that nearly perfectly overlaps in time with the 2014 survey, consistently produces 

higher observed termination ratios at every point it shares with the later survey. However, the concordance 

in observed termination ratios in the three most recent surveys—Senegal 2014, 2015, and 2016—stands in 

contrast to the earlier surveys. While the first three surveys align with the pattern in this category, the latter 

two may better fit Pattern 4: between-survey inconsistency accompanied by a (modest) increasing trend in 

termination ratios, as shown in Figure 4.2, Country D. The latter surveys are all part of the DHS Senegal 

Continuous Survey. 

Figure 4.13 Ratios of terminated pregnancies to live births (per 100) in consecutive DHS calendars, Senegal 

0

5

10

15

20

25

2005 2007 2009 2011 2013

Nigeria 2008 Nigeria 2013

0

5

10

15

20

25

1996 1998 2000 2002 2004 2006 2008 2010 2012 2014

Rwanda 2000 Rwanda 2005 Rwanda 2010 Rwanda 2014-15

0

5

10

15

20

25

2006 2008 2010 2012 2014 2016

Senegal 2010-11 Senegal 2012-13 Senegal 2014

Senegal 2015 Senegal 2016
58 

Sierra Leone also shows a disjuncture between the two surveys in 2008-09 (Figure 4.14). It also shows two 

patterns of within-survey inconsistency: a jagged, erratic pattern of observed termination ratios in the 2008 

survey and steadily increasing termination ratios in the 2013 survey. 

Figure 4.14 Ratios of terminated pregnancies to live births (per 100) in consecutive DHS calendars, Sierra 

Leone 

Figures 4.15 and 4.16 show a very similar pattern in the three surveys in Tanzania and four surveys in 

Uganda. Termination ratios begin near 5 terminated pregnancies per 100 live births in the earliest intervals 

of each calendar and increase erratically upward toward a ratio of 15 in the most recent intervals of the 

calendar, producing clear between-survey inconsistency at the adjoining points. 

Figure 4.15 Ratios of terminated pregnancies to live births (per 100) in consecutive DHS calendars, Tanzania 

Figure 4.16 Ratios of terminated pregnancies to live births (per 100) in consecutive DHS calendars, Uganda 

0

5

10

15

20

25

2005 2007 2009 2011 2013

Sierra Leone 2008 Sierra Leone 2013

0

5

10

15

20

25

2001 2003 2005 2007 2009 2011 2013 2015

Tanzania 2004-05 Tanzania 2010 Tanzania 2015-16

0

5

10

15

20

25

1996 1998 2000 2002 2004 2006 2008 2010 2012 2014 2016

Uganda 2000-01 Uganda 2006 Uganda 2011 Uganda 2016
59 

Both the Zambia 2007 and 2013-14 surveys (Figure 4.17) show termination ratios that are consistently low 

for the earliest three intervals of their calendars but that then increase steadily in the most recent two 

intervals, making an evident gap between the surveys. 

Figure 4.17 Ratios of terminated pregnancies to live births (per 100) in consecutive DHS calendars, Zambia 

The pattern exhibited by the surveys in Zimbabwe (Figure 4.18) closely resembles that in Kenya, Tanzania, 

and Uganda, with erratically increasing termination ratios within each survey accompanied by gaps of 5-

10 points between surveys. 

Figure 4.18 Ratios of terminated pregnancies to live births (per 100) in consecutive DHS calendars, 

Zimbabwe 

The Dominican Republic surveys (Figure 4.19) exhibit a pattern similar to those of several Eastern and 

Southern African countries. Note that higher termination ratios in the Dominican Republic necessitate an 

extended scale from 0 to 40. One feature of these surveys is that the steepest decline in termination ratios 

is evident in the most recent intervals (between first and second, or second and third) rather than in the 

earliest intervals of the calendar. Most striking, however, is the exceptionally large range of nearly 25 points 

in the observed termination ratios in the 1999 survey. Accordingly, there is a notable difference between 

the adjoining moment of this survey and the 2002 survey. Although by comparison the differences in 

termination ratios between the 1999 and 1996 surveys are not especially large in 1996, they are wider again 

in 1995. 

0

5

10

15

20

25

2003 2005 2007 2009 2011 2013

Zambia 2007 Zambia 2013-14

0

5

10

15

20

25

1991 1993 1995 1997 1999 2001 2003 2005 2007 2009 2011 2013 2015

Zimbabwe 1994 Zimbabwe 1999 Zimbabwe 2005-06 Zimbabwe 2010-11 Zimbabwe 2015
60 

Figure 4.19 Ratios of terminated pregnancies to live births (per 100) in consecutive DHS calendars, 

Dominican Republic 

The patterns in Egypt (Figure 4.20) and Jordan (Figure 4.21) are also similar to the several African surveys 

mentioned above and to the Dominican Republic, but each includes a survey pair that exhibits some degree 

of between-survey consistency. The Egypt 2005 and 2003 surveys produce nearly identical termination 

ratios at several overlapping points shared by the two surveys between 2001 and 2003. Likewise, the 

termination ratios in intervals shared by the Jordan 2012 and 2009 surveys in 2008 and 2009 are not far 

apart. While evidence from some countries in this category (e.g., Indonesia, the Philippines, Ethiopia, 

Malawi, and Mali) suggests that between-survey inconsistency widens with more recent surveys, Egypt and 

Jordan join Senegal in providing evidence potentially suggesting lower between-survey inconsistency over 

time. 

Figure 4.20 Ratios of terminated pregnancies to live births (per 100) in consecutive DHS calendars, Egypt 

Although it is typical for a preceding survey to produce observed termination ratios higher than those 

observed in the corresponding moments of their calendars, this is not the case with two of the Jordan 

surveys. The observed termination ratio in the preceding survey (2007) exceeds that in the subsequent 

survey (2009) at their intersection in 2007, but this relationship is reversed in earlier shared intervals: the 

termination ratio in 2006 and 2005 is lower in the 2007 survey than in the 2009 survey. Note that the higher 

termination ratios in Jordan necessitate a scale extended beyond that for the Egypt surveys. 

0

5

10

15

20

25

30

35

40

1988 1990 1992 1994 1996 1998 2000 2002

Dominican Republic 1991 Dominican Republic 1996

Dominican Republic 1999 Dominican Republic 2002

0

5

10

15

20

25

1988 1990 1992 1994 1996 1998 2000 2002 2004 2006 2008

Egypt 1992 Egypt 1995 Egypt 2000 Egypt 2003 Egypt 2005 Egypt 2008
61 

Figure 4.21 Ratios of terminated pregnancies to live births (per 100) in consecutive DHS calendars, Jordan 

4.3 Pattern 2: Consistent Surveys with No Evidence of Secular Trend 

Just two countries in Latin America—Guatemala and Nicaragua—typify the pattern of consistent surveys 

and no evidence of a secular trend in the termination ratio. Each country has two consecutive surveys, and 

the results of the statistical test (Table 3.1) showed both surveys in each country were within-survey 

consistent. The graphical analysis presented in Figures 4.22 and 4.23 indicated that observed ratios are 

stagnant over the combined observation periods that the two surveys cover—1991-1998 in Guatemala and 

1994-2001 in Nicaragua. Furthermore, the observed termination ratios are nearly identical in the intervals 

overlapped by the Guatemala surveys in 1994-95, and very similar in those overlapped by the Nicaragua 

surveys in 1997-98. Although there is some difference in the termination ratios for 1998 for Nicaragua, they 

are nearly identical in 1997. 

Figure 4.22 Ratios of terminated pregnancies to live births (per 100) in consecutive DHS calendars, 

Guatemala 

0

5

10

15

20

25

30

35

1986 1988 1990 1992 1994 1996 1998 2000 2002 2004 2006 2008 2010 2012

Jordan 1990 Jordan 1997 Jordan 2002 Jordan 2007 Jordan 2009 Jordan 2012

0

5

10

15

20

25

1992 1994 1996 1998

Guatemala 1995 Guatemala 1998-99
62 

Figure 4.23 Ratios of terminated pregnancies to live births (per 100) in consecutive DHS calendars, 

Nicaragua 

4.4 Pattern 3: Consistent Surveys with Evidence of Secular Trend 

The third pattern—consistent surveys with evidence of a secular trend in termination ratios over time—is 

only a marginally larger category than for Pattern 2. Pattern 3 comprises nine surveys in four countries—

Cambodia, Nepal, Vietnam, and Honduras. Recent surveys in Senegal, presented earlier, may join this 

category. Note that the scale varies for each of these countries to accommodate variation in the level of their 

termination ratios. With two exceptions11 among the nine surveys exhibiting Pattern 3, testing found 

statistically significant within-survey inconsistency (Table 3.1). However, when placed alongside 

consecutive surveys, a clear secular trend emerges, as presented in Figures 4.24 through 4.27. The secular 

trend shows increasing termination ratios over time in all four countries. Furthermore, focusing on the 

adjoining moments in consecutive calendars indicates relatively close correspondence between surveys. 

In Cambodia (Figure 4.24), the trend in the termination ratio is clearly rising across the 2010 and 2014 

surveys, with a similar overall slope in each survey. However, there is some jaggedness to the rate of 

increase in the termination ratio, and the termination ratios are similar at the adjoining moment of the two 

surveys, mainly due to a plateauing or slight decrease in the most recent 12 months of the Cambodia 2010 

survey (between 2009 and 2010). 

 

11 Nepal 2006 and Vietnam 2002. 

0

5

10

15

20

25

1995 1997 1999 2001

Nicaragua 1998 Nicaragua 2001
63 

Figure 4.24 Ratios of terminated pregnancies to live births (per 100) in consecutive DHS calendars, 

Cambodia 

Nepal (Figure 4.25) shows a trend that perhaps most closely aligns with the model of a consistent trend 

depicted in Country B of Figure 4.1. The slopes are noticeably consistent from survey to survey and the 

termination ratios at their adjoining moments are noticeably similar, although the termination ratios between 

the Nepal 2011 and 2016 surveys are somewhat separated in time.

Figure 4.25 Ratios of terminated pregnancies to live births (per 100) in consecutive DHS calendars, Nepal 

In contrast, in Vietnam (Figure 4.26) the surveys display a decidedly jagged path in their trend toward a 

termination ratio that quickly increases over time. The overall slope appears steep, rising from about 20 

terminated pregnancies per 100 live births in 1993 to about 50 in 2002. The termination ratios at their 

adjoining moment are nonetheless similar. 

0

5

10

15

20

25

30

35

40

2006 2008 2010 2012 2014

Cambodia 2010 Cambodia 2014

0

5

10

15

20

25

30

35

2004 2006 2008 2010 2012 2014 2016

Nepal 2006 Nepal 2011 Nepal 2016
64 

Figure 4.26 Ratios of terminated pregnancies to live births (per 100) in consecutive DHS calendars, Vietnam 

In Honduras (Figure 4.27) the termination ratios rise much more slowly than in Vietnam. The slow rise in 

termination ratios is accompanied by consistent observed termination ratios at the (nearly) adjoining 

moment between the two surveys. 

Figure 4.27 Ratios of terminated pregnancies to live births (per 100) in consecutive DHS calendars, 

Honduras 

4.5 Pattern 4: Inconsistent Surveys with Evidence of Secular Trend 

The fourth pattern is the second-largest category—inconsistent surveys alongside evidence of a secular 

trend. Surveys in nine countries exhibit this pattern, as illustrated in Figures 4.28 through 4.36. Like the 

pattern of inconsistent surveys with no secular trend, this pattern is found in all four study regions, 

comprising one country in Asia, three countries in Africa, three countries in Latin America and the 

Caribbean, and two countries in the Other Countries region. Pattern 4 presents with two main variants: 

(1) a secular trend suggestive of increasing termination ratios over time; and (2) a secular trend indicating 

decreasing termination ratios over time. 

4.5.1 Increasing termination ratios over time 

Within Pattern 4, six countries—Bangladesh, Ghana, Lesotho, Bolivia, Colombia, and Peru—exhibit a 

trend toward the first variant—increasing termination ratios. These are shown below in Figures 4.28 through 

4.33. Three Other Countries show the second variant—decreasing termination ratios—and are shown in 

section 4.5.2. 

0

5

10

15

20

25

30

35

40

45

50

1994 1996 1998 2000 2002

Vietnam 1997 Vietnam 2002

0

5

10

15

20

25

2002 2004 2006 2008 2010 2012

Honduras 2005-06 Honduras 2011-12
65 

Figure 4.28 Ratios of terminated pregnancies to live births (per 100) in consecutive DHS calendars, 

Bangladesh 

The trend exhibited by Bangladesh (Figure 4.28) is an amalgam of both trends in this variant of the pattern. 

For most of the surveys here, there is evidence of an increasing termination ratio between 1989 and 2004. 

The most recent three surveys, however, offer tentative evidence of a declining trend in termination ratios. 

The gaps at adjoining or overlapping moments between surveys are smaller between earlier surveys when 

the trend is increasing—coinciding at one point between the Bangladesh 1993-94 and 1996-97 surveys—

than they are at adjoining or overlapping points in later surveys when the trend is decreasing. 

The three surveys in Ghana (Figure 4.29) are a good illustration of inconsistent surveys with evidence of 

an increasing trend in termination ratios. The range in the termination ratios within a single survey increases 

with each successive survey, yet there are clear gaps between the surveys. 

Figure 4.29 Ratios of terminated pregnancies to live births (per 100) in consecutive DHS calendars, Ghana 

Lesotho offers an interesting variation on Pattern 4. Figure 4.30 makes clear that there is a discordance in 

the magnitude of the termination ratios estimated at the (nearly) adjoining points of the calendar of 

approximately 5 points, and evidence of increasing termination ratios over time. However, with some 

variation, the level of termination ratios is roughly steady throughout either of the two surveys. Indeed, the 

two Lesotho surveys indicate within-survey consistency (see Table 3.1) at the same time that they 

demonstrate between-survey inconsistency. 

0

5

10

15

20

25

1988 1990 1992 1994 1996 1998 2000 2002 2004 2006 2008 2010 2012 2014

Bangladesh 1993-94 Bangladesh 1996-97 Bangladesh 1999-00 Bangladesh 2004 Bangladesh 2007 Bangladesh 2011 Bangladesh 2014

0

5

10

15

20

25

30

35

2000 2002 2004 2006 2008 2010 2012 2014

Ghana 2003 Ghana 2008 Ghana 2014
66 

Figure 4.30 Ratios of terminated pregnancies to live births (per 100) in consecutive DHS calendars, Lesotho 

In Bolivia (Figure 4.31) the surveys in 2003 and 2008 indicate a steadily increasing termination ratio over 

time. Meanwhile, there is a difference of several points between the termination ratios in the surveys 

observed at their adjoining moments. 

Figure 4.31 Ratios of terminated pregnancies to live births (per 100) in consecutive DHS calendars, Bolivia 

The six surveys in Colombia (Figure 4.32) indicate an increasing termination ratio beginning in the early 

1990s, if not earlier. These termination ratios rise to the point of data collection in the Colombia 2010 

survey. As in Bangladesh and Ghana, the between-survey difference in observed termination ratios 

increases with increases in the pace of the rise of the termination ratios. The most recent survey, Colombia 

2015, exhibits a pattern contradictory to the other surveys in the country. It is unclear with just the one data 

point if this is a turning point in a trend to declining termination ratios, as in Bangladesh, or if this survey 

is an idiosyncrasy in a continuing increasing trend. 

0

5

10

15

20

25

2006 2008 2010 2012 2014

Lesotho 2009 Lesotho 2014

0

5

10

15

20

25

2000 2002 2004 2006 2008

Bolivia 2003 Bolivia 2008
67 

Figure 4.32 Ratios of terminated pregnancies to live births (per 100) in consecutive DHS calendars, Colombia 

In Peru (Figure 4.33), the first three surveys are perhaps a better fit with Pattern 1 than Pattern 4—

inconsistent surveys with no evidence of a secular trend. The adjoining points of these three surveys are 

characterized by a discrepancy in the termination ratios observed in each of the survey pairs and by withinsurvey inconsistency. However, a trend to increasing termination ratios emerges beginning in the early 

2000s. Although the latter six surveys in Peru are indicative of this increasing secular trend, there are still 

inconsistencies between them. There are moments within each calendar where the observed termination 

ratio is similar to that observed for the corresponding interval in the preceding or consecutive survey. 

However, with the exception of the Peru 2009 survey, the most recent interval (closest to the point of data 

collection) in each survey produces an observed termination ratio noticeably larger than the successive 

survey. 

Figure 4.33 Ratios of terminated pregnancies to live births (per 100) in consecutive DHS calendars, Peru 

4.5.2 Decreasing termination ratios over time 

As mentioned above, three countries within Pattern 4 (inconsistent surveys alongside evidence of a secular 

trend) exhibit the second variant of this pattern—decreasing termination ratios over time. These are Benin, 

Armenia, and Turkey, shown in Figures 4.34 through 4.36. 

In Benin (Figure 4.34), within each of the two surveys the observed termination ratios increase slightly 

(Benin 2011-12) or are relatively steady (Benin 2006). However, in the more recent survey the observed 

termination ratios are continuously lower than those in the preceding survey and there is a conspicuous 

0

5

10

15

20

25

30

35

1987 1989 1991 1993 1995 1997 1999 2001 2003 2005 2007 2009 2011 2013 2015

Colombia 1990 Colombia 1995 Colombia 2000 Colombia 2005 Colombia 2010 Colombia 2015

0

5

10

15

20

25

30

1988 1990 1992 1994 1996 1998 2000 2002 2004 2006 2008 2010 2012

Peru 1991-92 Peru 1996 Peru 2000 Peru 2004-06 Peru 2007-08 Peru 2009 Peru 2010 Peru 2011 Peru 2012
68 

inconsistency between the two surveys’ terminal points. To some degree, Benin’s pattern with a decreasing 

trend is analogous but in converse to Lesotho’s pattern with an increasing trend, shown in Figure 4.30. 

Figure 4.34 Ratios of terminated pregnancies to live births (per 100) in consecutive DHS calendars, Benin 

Figure 4.35 Ratios of terminated pregnancies to live births (per 100) in consecutive DHS calendars, Armenia 

In contrast to Benin, the secular downward trend in termination ratios exhibited by Armenia (Figure 4.35) 

and Turkey (Figure 4.36) are starker, with much higher termination ratios in the earliest surveys. The 

termination ratios remain considerably higher than Benin’s in the most recent surveys. Armenia’s highest 

0

5

10

15

20

25

2001 2003 2005 2007 2009 2011

Benin 2006 Benin 2011-12

0

5

10

15

20

25

30

35

40

45

50

55

60

65

70

75

80

85

90

95

100

105

110

115

120

125

130

135

140

145

150

155

160

165

170

175

1997 1999 2001 2003 2005 2007 2009 2011 2013 2015

Armenia 2000 Armenia 2005 Armenia 2010 Armenia 2015-16
69 

termination ratio is observed at about 170 terminated pregnancies to 100 live births in 1998, with a decline 

to about 40 in the most recent interval of the most recent survey. Turkey’s termination ratios have declined 

from about 50 to 20-25 terminated pregnancies per 100 live births over the six surveys. With one 

exception—the 2010-2011 period in Armenia—the most recent interval of the preceding survey produces 

a higher termination ratio than the interval nearest to the later survey. These termination ratios are not 

measurably different in 2010-2011 in Armenia. 

Figure 4.36 Ratios of terminated pregnancies to live births (per 100) in consecutive DHS calendars, Turkey 

The two largest categories of surveys are those that indicate inconsistencies between surveys, whether 

without any indication of a secular trend (Pattern 1) or with evidence of a secular trend (Pattern 4). Thus, 

the within-survey inconsistency observed in Chapter 3 cannot be explained by a secular trend in the 

underlying real termination ratio for the majority of surveys. Between-survey inconsistency persists. Where 

there is evidence of an increasing trend in the termination ratio, this trend may reduce but not eliminate the 

magnitude of the between-survey inconsistency, though it is difficult to quantify the share of the betweensurvey inconsistency attributable to the secular trend and the share that can be attributed to reporting 

inconsistency. Where there is evidence of a decreasing trend in the termination ratio, that trend serves to 

reinforce and magnify between-survey inconsistencies. 

4.6 Testing Between-Survey Consistency 

Table 4.1 presents the results of a formal test of between-survey consistency for the same consecutive 

surveys analyzed graphically in the preceding section. This analysis involves comparing the termination 

ratio of the first 12-month interval of a preceding survey for a given country with the termination ratio for 

the interval in a survey that aligns in time with the first 12-month interval of the preceding survey. This 

analysis aligns with Figures 4.3 to 4.36 in the previous section of this report. The reader is encouraged to 

refer to these figures for any country appearing with results in this table. 

0

5

10

15

20

25

30

35

40

45

50

55

60

1989 1991 1993 1995 1997 1999 2001 2003 2005 2007 2009 2011 2013

Turkey 1993 Turkey 1998 Turkey 2003 Turkey 2008 Turkey 2013
70 

Table 4.1 Measures of consistency between consecutive surveys 

Survey 

Termination ratio 

in Interval 1 

(0-11 months) of 

preceding survey 

Termination ratio 

in interval closest 

in time to Interval 1 

of preceding 

survey 

Absolute 

difference 

Relative 

difference 

Consistent or 

Inconsistent [1] 

Asia 

Afghanistan 2015 NA NA NA NA NA 

Bangladesh 1993-94 NA NA NA NA NA 

Bangladesh 1996-97 10.0 9.9 0.1 1% Consistent 

Bangladesh 1999-00 15.1 12.5 2.6 17% Consistent 

Bangladesh 2004 17.0 14.0 2.9 17% Consistent 

Bangladesh 2007 21.1 13.8 7.3 35% Inconsistent 

Bangladesh 2011 16.4 12.9 3.5 22% Inconsistent 

Bangladesh 2014 19.0 12.4 6.7 35% Inconsistent 

Cambodia 2010 NA NA NA NA NA 

Cambodia 2014 28.5 25.6 2.9 10% Consistent 

India 2005-06 NA NA NA NA NA 

India 2015-16 NA NA NA NA NA 

Indonesia 1991 NA NA NA NA NA 

Indonesia 1994 7.8 5.9 1.8 24% Inconsistent 

Indonesia 1997 9.5 6.8 2.7 28% Inconsistent 

Indonesia 2002-03 8.9 7.2 1.8 20% Consistent 

Indonesia 2007 10.5 7.2 3.3 32% Inconsistent 

Indonesia 2012 12.4 9.1 3.3 27% Inconsistent 

Maldives 2009 NA NA NA NA NA 

Myanmar 2015-16 NA NA NA NA NA 

Nepal 2006 NA NA NA NA NA 

Nepal 2011 13.8 15.9 -2.1 -15% Consistent 

Nepal 2016 20.2 18.6 1.6 8% Consistent 

Pakistan 2012-13 NA NA NA NA NA 

Philippines 1993 NA NA NA NA NA 

Philippines 1998 12.6 9.9 2.7 22% Consistent 

Philippines 2003 14.2 9.2 5.0 35% Inconsistent 

Timor-Leste 2009-10 NA NA NA NA NA 

Vietnam 1997 NA NA NA NA NA 

Vietnam 2002 37.2 37.4 -0.2 -1% Consistent 

Africa 

Angola 2015-16 NA NA NA NA NA 

Benin 2006 NA NA NA NA NA 

Benin 2011-12 9.3 2.5 6.8 74% Inconsistent 

Burkina Faso 2003 NA NA NA NA NA 

Burkina Faso 2010 NA NA NA NA NA 

Burundi 2010 NA NA NA NA NA 

Burundi 2016-17 NA NA NA NA NA 

Comoros 2012 NA NA NA NA NA 

Ethiopia 2005 NA NA NA NA NA 

Ethiopia 2011 4.7 3.0 1.7 37% Inconsistent 

Ethiopia 2016 9.2 3.8 5.3 58% Inconsistent 

Gambia 2013 NA NA NA NA NA 

Ghana 2003 NA NA NA NA NA 

Ghana 2008 19.0 10.6 8.4 44% Inconsistent 

Ghana 2014 NA NA NA NA NA 

Guinea 2005 NA NA NA NA NA 

Continued 

 
71 

Table 4.1—Continued 

Survey 

Termination ratio 

in Interval 1 

(0-11 months) of 

preceding survey 

Termination ratio 

in interval closest 

in time to Interval 1 

of preceding 

survey 

Absolute 

difference 

Relative 

difference 

Consistent or 

Inconsistent [1] 

Africa cont’d 

Kenya 1998 NA NA NA NA NA 

Kenya 2003 7.9 4.1 3.8 48% Inconsistent 

Kenya 2008-09 7.9 4.5 3.4 43% Inconsistent 

Kenya 2014 9.5 4.8 4.7 49% Inconsistent 

Lesotho 2009 NA NA NA NA NA 

Lesotho 2014 5.3 9.2 -3.9 -74% Inconsistent 

Liberia 2013 NA NA NA NA NA 

Madagascar 2003-04 NA NA NA NA NA 

Madagascar 2008-09 10.0 5.2 4.9 49% Inconsistent 

Malawi 2000 NA NA NA NA NA 

Malawi 2004 6.4 5.2 1.2 19% Consistent 

Malawi 2010 NA NA NA NA NA 

Malawi 2015-16 7.4 4.6 2.8 38% Inconsistent 

Mali 2001 NA NA NA NA NA 

Mali 2006 10.6 6.6 4.0 38% Inconsistent 

Mali 2012-13 NA NA NA NA NA 

Mozambique 2003 NA NA NA NA NA 

Mozambique 2011 NA NA NA NA NA 

Namibia 2006-07 NA NA NA NA NA 

Namibia 2013 NA NA NA NA NA 

Niger 2006 NA NA NA NA NA 

Niger 2012 NA NA NA NA NA 

Nigeria 2008 NA NA NA NA NA 

Nigeria 2013 8.9 4.9 4.0 45% Inconsistent 

Rwanda 2000 NA NA NA NA NA 

Rwanda 2005 8.5 5.4 3.1 36% Inconsistent 

Rwanda 2010 9.5 5.9 3.6 38% Inconsistent 

Rwanda 2014-15 9.1 9.1 0.0 0% Consistent 

Senegal 2005 NA NA NA NA NA 

Senegal 2010-11 NA NA NA NA NA 

Senegal 2012-13 12.5 8.2 4.3 34% Inconsistent 

Senegal 2014 16.8 11.1 5.7 34% Inconsistent 

Senegal 2015 12.7 11.9 0.9 7% Consistent 

Senegal 2016 11.2 12.0 -0.7 -7% Consistent 

Sierra Leone 2008 NA NA NA NA NA 

Sierra Leone 2013 9.8 5.9 3.8 39% Inconsistent 

Swaziland 2006-07 NA NA NA NA NA 

Tanzania 2004-05 NA NA NA NA NA 

Tanzania 2010 NA NA NA NA NA 

Tanzania 2015-16 14.0 6.7 7.3 52% Inconsistent 

Uganda 2000-01 NA NA NA NA NA 

Uganda 2006 NA NA NA NA NA 

Uganda 2011 13.8 7.6 6.1 44% Inconsistent 

Uganda 2016 11.9 7.0 4.9 41% Inconsistent 

Zambia 2007 NA NA NA NA NA 

Zambia 2013-14 NA NA NA NA NA 

Zimbabwe 1994 NA NA NA NA NA 

Zimbabwe 1999 11.7 5.7 6.0 51% Inconsistent 

Zimbabwe 2005-06 NA NA NA NA NA 

Continued 
72 

Table 4.1—Continued 

Survey 

Termination ratio 

in Interval 1 

(0-11 months) of 

preceding survey 

Termination ratio 

in interval closest 

in time to Interval 1 

of preceding 

survey 

Absolute 

difference 

Relative 

difference 

Consistent or 

Inconsistent [1] 

Africa cont’d 

Zimbabwe 2010-11 11.0 7.0 4.0 37% Inconsistent 

Zimbabwe 2015 10.0 6.0 4.0 40% Inconsistent 

LAC 

Bolivia 1994 NA NA NA NA NA 

Bolivia 2003 NA NA NA NA NA 

Bolivia 2008 13.3 10.7 2.5 19% Consistent 

Brazil NE 1991 NA NA NA NA NA 

Brazil 1996 NA NA NA NA NA 

Colombia 1990 NA NA NA NA NA 

Colombia 1995 14.5 10.1 4.4 30% Inconsistent 

Colombia 2000 16.3 12.9 3.4 21.0% Consistent 

Colombia 2005 22.1 16.0 6.1 28% Inconsistent 

Colombia 2010 26.7 18.2 8.5 32% Inconsistent 

Colombia 2015 28.7 20.6 8.1 28% Inconsistent 

Dominican Republic 1991 NA NA NA NA NA 

Dominican Republic 1996 17.8 13.1 4.7 26% Inconsistent 

Dominican Republic 1999 22.4 19.2 3.2 14% Consistent 

Dominican Republic 2002 33.9 17.8 16.1 47% Inconsistent 

Guatemala 1995 NA NA NA NA NA 

Guatemala 1998-99 6.7 7.0 -0.2 -3% Consistent 

Guatemala 2014-15 NA NA NA NA NA 

Guyana 2009 NA NA NA NA NA 

Honduras 2005-06 NA NA NA NA NA 

Honduras 2011-12 NA NA NA NA NA 

Nicaragua 1998 NA NA NA NA NA 

Nicaragua 2001 9.8 7.0 2.8 29% Inconsistent 

Paraguay 1990 NA NA NA NA NA 

Peru 1991-92 NA NA NA NA NA 

Peru 1996 12.0 8.2 3.8 31% Inconsistent 

Peru 2000 12.9 8.5 4.4 34% Inconsistent 

Peru 2004-06 NA NA NA NA NA 

Peru 2007-08 20.8 16.4 4.4 21.0% Consistent 

Peru 2009 22.7 17.8 4.9 22% Inconsistent 

Peru 2010 16.6 18.1 -1.5 -9% Consistent 

Peru 2011 26.9 18.6 8.3 31% Inconsistent 

Peru 2012 22.7 18.6 4.1 18% Consistent 

Other Countries 

Albania 2008-09 NA NA NA NA NA 

Armenia 2000 NA NA NA NA NA 

Armenia 2005 155.1 118.3 36.8 24% Inconsistent 

Armenia 2010 120.8 89.8 31.0 26% Inconsistent 

Armenia 2015-16 53.6 53.6 0.0 0% Consistent 

Azerbaijan 2006 NA NA NA NA NA 

Egypt 1992 NA NA NA NA NA 

Egypt 1995 18.5 12.9 5.6 30% Inconsistent 

Egypt 2000 18.6 11.9 6.8 36% Inconsistent 

Egypt 2003 14.9 9.6 5.3 35% Inconsistent 

Egypt 2005 13.1 13.5 -0.4 -3% Consistent 

Continued 

 
73 

Table 4.1—Continued 

Survey 

Termination ratio 

in Interval 1 

(0-11 months) of 

preceding survey 

Termination ratio 

in interval closest 

in time to Interval 1 

of preceding 

survey 

Absolute 

difference 

Relative 

difference 

Consistent or 

Inconsistent [1] 

Other Countries cont’d 

Egypt 2008 16.0 10.7 5.3 33% Inconsistent 

Egypt 2014 NA NA NA NA NA 

Jordan 1990 NA NA NA NA NA 

Jordan 1997 NA NA NA NA NA 

Jordan 2002 24.2 16.8 7.4 31% Inconsistent 

Jordan 2007 19.8 12.1 7.7 39% Inconsistent 

Jordan 2009 25.2 18.9 6.3 25% Inconsistent 

Jordan 2012 21.7 18.8 2.9 13% Consistent 

Kazakhstan 1999 NA NA NA NA NA 

Kyrgyz Republic 2012 NA NA NA NA NA 

Moldova 2005 NA NA NA NA NA 

Morocco 1992 NA NA NA NA NA 

Morocco 2003-04 NA NA NA NA NA 

Tajikistan 2012 NA NA NA NA NA 

Turkey 1993 NA NA NA NA NA 

Turkey 1998 43.5 28.9 14.6 34% Inconsistent 

Turkey 2003 37.4 26.9 10.5 28% Inconsistent 

Turkey 2008 33.2 23.5 9.7 29% Inconsistent 

Turkey 2013 31.8 18.2 13.5 43% Inconsistent 

Ukraine 2007 NA NA NA NA NA 

Yemen 2013 NA NA NA NA NA 

[1] Between-survey inconsistency is indicated if the relative difference in the termination ratio with the overlapping moment of the 

preceding survey exceeds the cutoff of 21.6% 

The second column in Table 4.1 is the value of the termination ratio for the first 12-month interval in the 

survey preceding the survey named in column 1. Looking at the row for Bangladesh 1996-97, the value of 

10.0 that appears in column 2 is the value of termination for the first interval in the survey Bangladesh 

1993-94. Column 3 shows the termination ratio for the interval in the Bangladesh 1996-97 survey that most 

closely aligns with the first interval in Bangladesh 1993-94. Referring to Figure 4.28 on page 65 (and 

replicated immediately below), it can be seen that this is the fourth interval looking back from the date of 

the survey and corresponds to 1993. The value is 9.9 for Bangladesh 1996-97. The graph shows that the 

two curves are almost touching. 

0

5

10

15

20

25

1988 1990 1992 1994 1996 1998 2000 2002 2004 2006 2008 2010 2012 2014

Bangladesh 1993-94 Bangladesh 1996-97 Bangladesh 1999-00 Bangladesh 2004 Bangladesh 2007 Bangladesh 2011 Bangladesh 2014
74 

Column 4 is the difference between the values in the preceding two columns, or 0.1 in the case of 

Bangladesh 1996-97. Column 5 is the relative difference presented as a percent; in the example we are 

following, this is 1%. Finally, consistency is established by whether or not the absolute value of the relative 

difference is less than 20.6%. In the example we are following, it is clearly consistent, as 1% is less than 

20.6%. 

This procedure can be followed for most surveys reported on in the table. However, there are many surveys 

that have notations of “NA.” There are three types of cases with NA. The first type includes surveys such 

as Afghanistan 2015, which are the only DHS surveys implemented with reproductive calendars for a given 

country. The second type includes DHS surveys that are the first in a series of two or more surveys with 

reproductive calendars. Bangladesh 1993-94 is an example. As there is no preceding survey, it is impossible 

to perform the analysis. The third type includes DHS surveys that are preceded by a survey 6 or more years 

earlier and for which the gap between calendars is greater than 1 year. Burundi 2016-17 is an example. For 

78 surveys, there is a preceding survey close enough in time to form a survey pair for the test of betweensurvey consistency presented in Table 4.1. 

Overall, of the 78 surveys pairs, 23 are found to be between-survey consistent by this test, while 55 are 

between-survey inconsistent. For these surveys the termination ratio at the earlier intervals of the calendar 

differs by more than 20.6% from the corresponding termination ratio in the more recent intervals of the 

preceding survey. Two surveys in Africa display the largest between-survey differences. In Benin 2011-12 

the relative difference between the overlapping termination ratios is 74%, indicating that the previous 

survey produces a substantially higher termination ratio. In Lesotho 2014, it is the reverse, with a relative 

difference of -74%. 

Africa is also the region with the greatest proportion of surveys indicating between-survey inconsistency—

only four surveys are found to be between-survey consistent compared with 23 inconsistent. In contrast, in 

Asia nine surveys are found to be between-survey consistent and eight inconsistent. The other two regions 

are similar to each another, with seven consistent surveys and 11 inconsistent surveys in Latin America and 

the Caribbean, and three consistent surveys and 13 inconsistent surveys in the Other Countries region. 

The case of Bangladesh is instructive. Looking first at the graph from right to left, we see that Bangladesh 

2014 and Bangladesh 2007 lie considerably below Bangladesh 2011 and Bangladesh 2004, respectively. 

Then referring to Table 4.1 we see that the relative difference is 35% in both cases and that both are clearly 

inconsistent by the standard we have chosen (above or below 20.6%). Next, Bangladesh 2011, Bangladesh 

2004, and Bangladesh 1999-00 are moderately below Bangladesh 2007, Bangladesh 1999-2000, and 

Bangladesh 1996-97, respectively. Looking at Table 4.2, we see that the relative differences are 22%, 17%, 

and 17%—each close to the cutoff of 20.6%. Then at the far right, Bangladesh 1996-97 looks almost like a 

continuation, albeit jagged, of Bangladesh 1993-94, with the two curves almost touching at the point of 

comparison for the relative difference. At least for the case of Bangladesh there is not an evident country 

pattern to survey consistency or inconsistency by the between-survey mode of analysis. In fact, overall, for 

11 of the 16 countries that have two or more pairs of overlapping surveys, there are differing assessments 

of consistency from survey pair to survey pair. 

Additionally, there are some surveys for which the formal test of between-survey consistency differs from 

the assessment based on graphical analysis. These include Indonesia 2002-03, Philippines 1998, the 
75 

Dominican Republic 1999, Bangladesh 2004, Bolivia 2008, and Colombia 2000, which produced graphical 

analysis suggestive of between-survey inconsistency but whose difference in termination ratios at adjoining 

moments was not sufficiently large to reject the null hypothesis. It also includes Nicaragua 2001, which 

was a graphical example of between-survey consistency. Although this survey and its preceding survey 

produced nearly identical termination ratios for the interval in 1997, the observed termination ratios in each 

for the adjoining interval in 1998 differ by 29%. 

In Chapter 6 of the report we will make reference to how a survey is implemented to see if any patterns 

emerge for explaining consistency or inconsistency. 

77 

5 COMPARING WITHIN-SURVEY AND BETWEEN-SURVEY 

CONSISTENCY 

Table 5.1 brings together the results from the within-survey analysis of Table 3.1 and the between-survey 

analysis of Table 4.1. The second column of Table 5.1 indicates within-survey consistency or inconsistency 

based on whether or not the Wald test reported in Table 3.1 is significant at p-value ≤ 0.05. Statistical 

significance in this case is indicative of inconsistency between the ratio of terminations to births in the first 

12-month interval preceding the interview date to the fifth 12-month interval preceding the interview date. 

The third column pulls the determination of between-survey consistency or inconsistency directly from the 

final column of Table 4.1 for differences between comparable calendar intervals across surveys with 

overlapping reproductive calendars. The fourth column provides a synthesis of the previous two columns. 

Table 5.1 Comparison of within-survey consistency and between-survey consistency measures 

Survey 

Within-survey 

consistency 

Between-survey 

consistency 

Overall consistency 

classification 

Asia 

Afghanistan 2015 ● NA ● 

Bangladesh 1993-94 ● NA ● 

Bangladesh 1996-97 ● ○ ○ 

Bangladesh 1999-00 ● ○ ○ 

Bangladesh 2004 ● ○ ○ 

Bangladesh 2007 ● ● ● 

Bangladesh 2011 ● ● ● 

Bangladesh 2014 ● ● ● 

Cambodia 2010 ● NA ● 

Cambodia 2014 ● ○ ○ 

India 2005-06 ● NA ● 

India 2015-16 ● NA ● 

Indonesia 1991 ● NA ● 

Indonesia 1994 ● ● ● 

Indonesia 1997 ● ● ● 

Indonesia 2002-03 ● ○ ○ 

Indonesia 2007 ● ● ● 

Indonesia 2012 ● ● ● 

Maldives 2009 ● NA ● 

Myanmar 2015-16 ● NA ● 

Nepal 2006 ○ NA ○ 

Nepal 2011 ● ○ ○ 

Nepal 2016 ● ○ ○ 

Pakistan 2012-13 ○ NA ○ 

Philippines 1993 ● NA ● 

Philippines 1998 ● ○ ○ 

Philippines 2003 ● ● ● 

Timor-Leste 2009-10 ○ NA ○ 

Vietnam 1997 ● NA ● 

Vietnam 2002 ○ ○ ○ 

Notes: ○ Consistent; ● Inconsistent 

Continued 

 
78 

Table 5.1—Continued 

Survey 

Within-survey 

consistency 

Between-survey 

consistency 

Overall consistency 

classification 

Africa 

Angola 2015-16 ● NA ● 

Benin 2006 ○ NA ○ 

Benin 2011-12 ● ● ● 

Burkina Faso 2003 ○ NA ○ 

Burkina Faso 2010 ○ NA ○ 

Burundi 2010 ● NA ● 

Burundi 2016-17 ● NA ● 

Comoros 2012 ● NA ● 

Ethiopia 2005 ● NA ● 

Ethiopia 2011 ● ● ● 

Ethiopia 2016 ● ● ● 

Gambia 2013 ○ NA ○ 

Ghana 2003 ● NA ● 

Ghana 2008 ● ● ● 

Ghana 2014 ● NA ● 

Guinea 2005 ● NA ● 

Kenya 1998 ● NA ● 

Kenya 2003 ● ● ● 

Kenya 2008-09 ● ● ● 

Kenya 2014 ● ● ● 

Lesotho 2009 ○ NA ○ 

Lesotho 2014 ○ ● ○ 

Liberia 2013 ● NA ● 

Madagascar 2003-04 ● NA ● 

Madagascar 2008-09 ● ● ● 

Malawi 2000 ● NA ● 

Malawi 2004 ○ ○ ○ 

Malawi 2010 ● NA ● 

Malawi 2015-16 ● ● ● 

Mali 2001 ● NA ● 

Mali 2006 ● ● ● 

Mali 2012-13 ○ NA ○ 

Mozambique 2003 ○ NA ○ 

Mozambique 2011 ● NA ● 

Namibia 2006-07 ○ NA ○ 

Namibia 2013 ● NA ● 

Niger 2006 ○ NA ○ 

Niger 2012 ● NA ● 

Nigeria 2008 ● NA ● 

Nigeria 2013 ● ● ● 

Rwanda 2000 ● NA ● 

Rwanda 2005 ● ● ● 

Rwanda 2010 ● ● ● 

Rwanda 2014-15 ○ ○ ○ 

Senegal 2005 ● NA ● 

Senegal 2010-11 ● NA ● 

Senegal 2012-13 ● ● ● 

Senegal 2014 ● ● ● 

Senegal 2015 ● ○ ○ 

Senegal 2016 ● ○ ○ 

Sierra Leone 2008 ● NA ● 

Notes: ○ Consistent; ● Inconsistent 

Continued 
79 

Table 5.1—Continued 

Survey 

Within-survey 

consistency 

Between-survey 

consistency 

Overall consistency 

classification 

Africa cont’d 

Sierra Leone 2013 ● ● ● 

Swaziland 2006-07 ● NA ● 

Tanzania 2004-05 ○ NA ○ 

Tanzania 2010 ● NA ● 

Tanzania 2015-16 ● ● ● 

Uganda 2000-01 ● NA ● 

Uganda 2006 ● NA ● 

Uganda 2011 ● ● ● 

Uganda 2016 ● ● ● 

Zambia 2007 ● NA ● 

Zambia 2013-14 ● NA ● 

Zimbabwe 1994 ● NA ● 

Zimbabwe 1999 ● ● ● 

Zimbabwe 2005-06 ● NA ● 

Zimbabwe 2010-11 ● ● ● 

Zimbabwe 2015 ● ● ● 

LAC 

Bolivia 1994 ● NA ● 

Bolivia 2003 ● NA ● 

Bolivia 2008 ● ○ ○ 

Brazil NE 1991 ● NA ● 

Brazil 1996 ● NA ● 

Colombia 1990 ● NA ● 

Colombia 1995 ● ● ● 

Colombia 2000 ● ○ ○ 

Colombia 2005 ● ● ● 

Colombia 2010 ● ● ● 

Colombia 2015 ○ ● ○ 

Dominican Republic 1991 ● NA ● 

Dominican Republic 1996 ● ● ● 

Dominican Republic 1999 ● ○ ○ 

Dominican Republic 2002 ● ● ● 

Guatemala 1995 ● NA ● 

Guatemala 1998-99 ○ ○ ○ 

Guatemala 2014-15 ○ NA ○ 

Guyana 2009 ● NA ● 

Honduras 2005-06 ● NA ● 

Honduras 2011-12 ● NA ● 

Nicaragua 1998 ○ NA ○ 

Nicaragua 2001 ○ ● ○ 

Paraguay 1990 ○ NA ○ 

Peru 1991-92 ● NA ● 

Peru 1996 ● ● ● 

Peru 2000 ● ● ● 

Peru 2004-06 ● NA ● 

Peru 2007-08 ● ○ ○ 

Peru 2009 ● ● ● 

Peru 2010 ● ○ ○ 

Peru 2011 ● ● ● 

Peru 2012 ● ○ ○ 

Notes: ○ Consistent; ● Inconsistent 

Continued 

 
80 

Table 5.1—Continued 

Survey 

Within-survey 

consistency 

Between-survey 

consistency 

Overall consistency 

classification 

Other Countries 

Albania 2008-09 ○ NA ○ 

Armenia 2000 ○ NA ○ 

Armenia 2005 ○ ● ○ 

Armenia 2010 ● ● ● 

Armenia 2015-16 ○ ○ ○ 

Azerbaijan 2006 ● NA ● 

Egypt 1992 ● NA ● 

Egypt 1995 ● ● ● 

Egypt 2000 ● ● ● 

Egypt 2003 ● ● ● 

Egypt 2005 ○ ○ ○ 

Egypt 2008 ● ● ● 

Egypt 2014 ○ NA ○ 

Jordan 1990 ● NA ● 

Jordan 1997 ● NA ● 

Jordan 2002 ○ ● ○ 

Jordan 2007 ● ● ● 

Jordan 2009 ○ ● ○ 

Jordan 2012 ● ○ ○ 

Kazakhstan 1999 ● NA ● 

Kyrgyz Republic 2012 ○ NA ○ 

Moldova 2005 ○ NA ○ 

Morocco 1992 ● NA ● 

Morocco 2003-04 ○ NA ○ 

Tajikistan 2012 ● NA ● 

Turkey 1993 ● NA ● 

Turkey 1998 ● ● ● 

Turkey 2003 ● ● ● 

Turkey 2008 ● ● ● 

Turkey 2013 ● ● ● 

Ukraine 2007 ● NA ● 

Yemen 2013 ● NA ● 

Notes: ○ Consistent; ● Inconsistent 

In the second column the statistical measure was relatively rigorous concerning whether or not the 

termination ratio for the first interval is different from the termination ratio for the fifth interval. The 

difference between intervals could be due to errors in reporting, or it could represent a true change in the 

termination ratio.12 The third column has the advantage of comparing the termination ratio in two different 

surveys for the same 12-month interval. With perfect sampling, recall, reporting, and recording, the values 

would be expected to be the same in both surveys. Any differences between the two values would be due 

to recall, reporting, or recording within statistical bounds. We compare percent difference relative to a cutoff 

point of 20.6%. 

 

12 Recall that the termination ratio can change over time due to many factors: changes in contraceptive use, changes 

in the propensity to terminate unwanted pregnancies, changes in the availability or social acceptance of induced 

abortion, etc.
81 

In combining the two measures of consistency, we adopt the following set of rules for an overall 

classification of consistency. 

• If assessments both within-survey and between-survey are made: 

− Both inconsistent: survey assessed to be inconsistent (e.g., Bangladesh 2007) 

− One or both are consistent: survey assessed to be consistent (e.g., Bangladesh 1996-97) 

• If only within-survey assessment is made: 

− Assessment of the within-survey test is taken as the overall assessment (e.g., Afghanistan 

2015) 

These results on whether the surveys are consistent or inconsistent in reporting of terminated pregnancies 

in the DHS calendar are noted in the fourth column of Table 5.1. 

Table 5.2 presents counts of surveys assessed as consistent or inconsistent based on our three criteria—

within-survey, between-survey, and overall classification. The counts for the within-survey and the 

between-survey tests indicate that the within-survey test is more likely to show inconsistency than the 

between-survey test. However, we note that the difference is not large and that both measures are more 

likely to show inconsistency than consistency. 

Table 5.2 Summary counts of within-survey, between-survey, and overall classification of consistency, by region 

Within-survey consistency Between-survey consistency Overall consistency classification 

Consistent 

n (%) 

Inconsistent 

n (%) Total 

Consistent 

n (%) 

Inconsistent 

n (%) Total 

Consistent 

n (%) 

Inconsistent 

n (%) Total 

Asia 4 (13%) 26 (87%) 30 9 (53%) 8 (47%) 17 12 (40%) 18 (60%) 30 

Africa 13 (19%) 54 (81%) 67 4 (15%) 23 (85%) 27 15 (22%) 52 (78%) 67 

LAC 6 (18%) 27 (82%) 33 7 (39%) 11 (61%) 18 12 (36%) 21 (64%) 33 

Other 

Countries 11 (34%) 21 (66%) 32 3 (19%) 13 (81%) 16 12 (38%) 20 (63%) 32 

Total 30 (21%) 128 (79%) 162 23 (29%) 55 (71%) 78 51 (31%) 111 (69%) 162 

On the other hand, the regional disaggregation shows some interesting patterns. For both measures in 

Africa, more than 8 in 10 surveys indicate inconsistency. For the surveys in Asia and in Latin America and 

the Caribbean, inconsistency is more likely to be indicated in the within-survey measure than the betweensurvey measure. The reverse is found for surveys in the region of Other Countries: the between-survey test 

is more likely to find inconsistency than the within-survey test. 

83 

6 CONSISTENCY OF THE REPRODUCTIVE CALENDAR BY 

SURVEY CHARACTERISTICS 

6.1 Classification of Survey Consistency 

Table 6.1 summarizes the overall classification of consistency used in this chapter to disaggregate the 162 

surveys by survey characteristics. Overall, about 70% of the surveys (111) are classified as inconsistent 

across all regions. Africa has higher counts of inconsistency, at 78% (52 surveys), whereas about two-thirds 

of surveys in Other Countries, Latin America and the Caribbean, and Asia are classified as inconsistent. 

Table 6.1 Consistency classification of surveys 

Survey Inconsistent Consistent 

Asia 

Afghanistan 2015 ● 

Bangladesh 1993-94 ● 

Bangladesh 1996-97 ● 

Bangladesh 1999-00 ● 

Bangladesh 2004 ● 

Bangladesh 2007 ● 

Bangladesh 2011 ● 

Bangladesh 2014 ● 

Cambodia 2010 ● 

Cambodia 2014 ● 

India 2005-06 ● 

India 2015-16 ● 

Indonesia 1991 ● 

Indonesia 1994 ● 

Indonesia 1997 ● 

Indonesia 2002-03 ● 

Survey Inconsistent Consistent 

 

Indonesia 2007 ● 

Indonesia 2012 ● 

Maldives 2009 ● 

Myanmar 2015-16 ● 

Nepal 2006 ● 

Nepal 2011 ● 

Nepal 2016 ● 

Pakistan 2012-13 ● 

Philippines 1993 ● 

Philippines 1998 ● 

Philippines 2003 ● 

Timor-Leste 2009-10 ● 

Vietnam 1997 ● 

Vietnam 2002 ● 

SUBTOTAL 18 12 

Africa 

Angola 2015-16 ● 

Benin 2006 ● 

Benin 2011-12 ● 

Burkina Faso 2003 ● 

Burkina Faso 2010 ● 

Burundi 2010 ● 

Burundi 2016-17 ● 

Comoros 2012 ● 

Ethiopia 2005 ● 

Ethiopia 2011 ● 

Ethiopia 2016 ● 

Gambia 2013 ● 

Ghana 2003 ● 

Ghana 2008 ● 

Ghana 2014 ● 

Guinea 2005 ● 

Kenya 1998 ● 

Kenya 2003 ● 

Kenya 2008-09 ● 

Kenya 2014 ● 

Lesotho 2009 ● 

 

Lesotho 2014 ● 

Liberia 2013 ● 

Madagascar 2003-04 ● 

Madagascar 2008-09 ● 

Malawi 2000 ● 

Malawi 2004 ● 

Malawi 2010 ● 

Malawi 2015-16 ● 

Mali 2001 ● 

Mali 2006 ● 

Mali 2012-13 ● 

Mozambique 2003 ● 

Mozambique 2011 ● 

Namibia 2006-07 ● 

Namibia 2013 ● 

Niger 2006 ● 

Niger 2012 ● 

Nigeria 2008 ● 

Nigeria 2013 ● 

Rwanda 2000 ● 

Rwanda 2005 ● 

Continued 
84 

Table 6.1—Continued 

Survey Inconsistent Consistent 

Africa cont’d 

Rwanda 2010 ●

Rwanda 2014-15 ● 

Senegal 2005 ●

Senegal 2010-11 ●

Senegal 2012-13 ●

Senegal 2014 ● 

Senegal 2015 ● 

Senegal 2016 ● 

Sierra Leone 2008 ● 

Sierra Leone 2013 ● 

Swaziland 2006-07 ● 

Tanzania 2004-05 ● 

Tanzania 2010 ● 

Survey Inconsistent Consistent 

Tanzania 2015-16 ●

Uganda 2000-01 ●

Uganda 2006 ●

Uganda 2011 ●

Uganda 2016 ● 

Zambia 2007 ● 

Zambia 2013-14 ● 

Zimbabwe 1994 ● 

Zimbabwe 1999 ● 

Zimbabwe 2005-06 ● 

Zimbabwe 2010-11 ● 

Zimbabwe 2015 ● 

SUBTOTAL 52 15 

 

LAC 

Bolivia 1994 ● 

Bolivia 2003 ● 

Bolivia 2008 ● 

Brazil NE 1991 ● 

Brazil 1996 ● 

Colombia 1990 ● 

Colombia 1995 ● 

Colombia 2000 ● 

Colombia 2005 ● 

Colombia 2010 ● 

Colombia 2015 ● 

Dominican Republic 1991 ● 

Dominican Republic 1996 ● 

Dominican Republic 1999 ● 

Guatemala 1995 ● 

Guatemala 1998-99 ● 

Guatemala 2014-15 ● 

 

Guyana 2009 ● 

Honduras 2005-06 ● 

Honduras 2011-12 ● 

Nicaragua 1998 ● 

Nicaragua 2001 ● 

Paraguay 1990 ● 

Peru 1991-92 ● 

Peru 1996 ● 

Peru 2000 ● 

Peru 2004-06 ● 

Peru 2007-08 ● 

Peru 2009 ● 

Peru 2010 ● 

Peru 2011 ● 

Peru 2012 ● 

SUBTOTAL 22 11 

Other Countries 

Albania 2008-09 ● 

Armenia 2000 ● 

Armenia 2005 ● 

Armenia 2010 ● 

Armenia 2015-16 ● 

Azerbaijan 2006 ● 

Egypt 1992 ● 

Egypt 1995 ● 

Egypt 2000 ● 

Egypt 2003 ● 

Egypt 2005 ● 

Egypt 2008 ● 

Egypt 2014 ● 

Jordan 1990 ● 

Jordan 1997 ● 

Jordan 2002 ● 

Jordan 2007 ● 

 

Jordan 2009 ● 

Jordan 2012 ● 

Kazakhstan 1999 ● 

Kyrgyz Republic 2012 ● 

Moldova 2005 ● 

Morocco 1992 ● 

Morocco 2003-04 ● 

Tajikistan 2012 ● 

Turkey 1993 ● 

Turkey 1998 ● 

Turkey 2003 ● 

Turkey 2008 ● 

Turkey 2013 ● 

Ukraine 2007 ● 

Yemen 2013 ● 

SUBTOTAL 20 12 

TOTAL 112 50 
85 

6.2 Consistency in Termination Ratios and Type of History 

The type of history accompanying the reproductive calendar in DHS surveys is disproportionately the birth 

history. The birth history is used in 142 of the study’s 162 surveys, and a pregnancy history in only 20 

surveys. Table 6.2 shows the summary of survey consistency by type of history. A detailed tabulation of all 

surveys by consistency and type of history can be found in Appendix Table A.1. 

Table 6.2 Consistency of surveys by type of history 

Birth history Pregnancy history 

Survey Inconsistent Consistent Inconsistent Consistent Total 

Asia 15 6 3 6 30 

Africa 52 15 0 0 67 

LAC 22 11 0 0 33 

Other Countries 15 6 5 6 32 

Total 104 38 8 12 162 

Note: A birth history collects data on every live birth, whether still alive or not. A pregnancy history 

collects data on all pregnancies, including those which ended in a live birth, an induced abortion, a 

miscarriage, and a stillbirth. 

The skewed distribution of history type makes it difficult to find patterns in survey consistency with 

confidence. However, some overall patterns are suggested. While most of surveys with a birth history are 

inconsistent—at more than 70%— the converse is true of surveys with a pregnancy history—about 60% 

are consistent. Regional patterns are even more difficult to discern, both because of the skewed distribution 

and because pregnancy histories are only applied in some surveys in two regions. They are not used in 

either Latin America and the Caribbean or Africa, the region with the greatest proportion of inconsistent 

surveys. The pattern in consistency by history type may be attributed to either the type of history or to the 

region and specific countries that use the pregnancy history. 

6.3 Consistency in Termination Ratios and Direction of History 

As with type of history, the direction of reporting is similarly skewed—153 of the 162 surveys employ a 

forward reported history and just 10 employ a backward reported history. No surveys in Africa or Latin 

America and the Caribbean employ a backward reported history. This skew makes apparent patterns 

inconclusive. Table 6.3 provides evidence tentatively suggesting that, while a large proportion of surveys 

with a forward reported history are inconsistent, those with a backward reported history are roughly equally 

likely to be inconsistent as consistent in reporting termination ratios in the reproductive calendar. 

Table 6.3 Consistency of surveys by direction of reporting in the history 

Forward reported Backward reported 

Survey Inconsistent Consistent Inconsistent Consistent Total 

Asia 17 11 1 1 30 

Africa 52 15 0 0 67 

LAC 22 11 0 0 33 

Other Countries 16 9 4 3 32 

Total 107 46 5 4 162 

Note: A forward reported history collects data beginning with the first birth/pregnancy moving 

through each subsequent one until the most recent, whereas a backward reported history collects 

data beginning with the most recent birth/pregnancy moving backward until the first birth/pregnancy. 
86 

Attribution is nearly impossible, however, as these differences may be associated with the region or the 

type of history, or may not be significant at all. A detailed tabulation of all surveys by consistency and 

reporting direction of history can be found in Appendix Table A.2. 

6.4 Consistency in Termination Ratios and Questions Distinguishing 

Pregnancy Outcome 

Table 6.4 presents a summary of survey consistency by whether the survey questionnaire includes questions 

that explicitly distinguish between types of terminations, namely between miscarriage and induced 

abortion. Among the DHS surveys in this study, 138 do not include such questions. Twenty-four surveys 

do, concentrated in Asia and Other Countries. A detailed list of surveys, their consistency classification, and 

inclusion of such questions can be found in Appendix Table A.3.

Table 6.4 Consistency of surveys by questions distinguishing miscarriage and induced abortion 

No questions distinguish 

miscarriage & 

induced abortion 

Questions distinguish 

miscarriage & 

induced abortion 

Survey Inconsistent Consistent Inconsistent Consistent Total 

Asia 15 7 3 5 30 

Africa 52 15 0 0 67 

LAC 22 11 0 0 33 

Other Countries 10 6 10 6 32 

Total 99 39 13 11 162 

The proportion of surveys that are inconsistent (about 70%) is higher among surveys that do not include 

questions that distinguish between miscarriage and induced abortion than among surveys that do make a 

distinction. However, this finding comes with the same caveats as the findings related to type of history and 

direction of reporting. 

6.5 Consistency in Termination Ratios and Mode of Data Collection 

Table 6.5 shows summary information related to survey consistency and mode of data collection, with a 

detailed list of survey presented in Appendix Table A.4. 

Table 6.5 Consistency of surveys by mode of data collection 

PAPI CAFÉ or CAPI 

Survey Inconsistent Consistent Inconsistent Consistent Total 

Asia 15 10 3 2 30 

Africa 39 10 11 7 67 

LAC 16 8 6 3 33 

Other Countries 20 11 0 1 32 

Total 90 39 20 13 162 

Notes: PAPI: pen and paper personal interview; CAFÉ: computer-assisted field editing; CAPI: 

computer assisted personal interview 

While the number of surveys that collect data via computer-assisted personal interview (CAPI) has 

increased rapidly over time, interviewing with pen and paper remains a popular option in DHS surveys. All 

of the surveys in the earliest DHS phases used PAPI, with the first CAPI surveys used in 2004 in Peru. Only 
87 

three surveys in this study used computer-assisted field editing (CAFÉ), which is grouped with CAPI in 

Table 6.5. 

The majority of study surveys (129) collected data using PAPI, and 43 surveys using CAPI or CAFÉ. 

Overall, a slightly higher proportion of surveys using PAPI (7 in 10) are classified as inconsistent compared 

with surveys using CAPI (6 in 10), though this difference is not likely to be significant. In no region are 

CAFÉ or CAPI surveys more likely to be consistent compared with PAPI surveys. 

6.6 Consistency in Termination Ratios and Survey Length 

Table 6.6 shows survey consistency disaggregated by length of survey. Details can be found in Appendix 

Table A.5. The likelihood of a survey being inconsistent in reporting termination ratios is equivalent (69%) 

between surveys with short or long questionnaire length. This pattern holds within Asia, Africa, and Latin 

America and the Caribbean. However, in the Other Countries region, some evidence suggests that a greater 

proportion of long surveys are consistent and a greater proportion of short surveys are inconsistent. 

Table 6.6 Consistency of surveys by length of survey 

Long Short 

Survey Inconsistent Consistent Inconsistent Consistent Total 

Asia 5 3 13 9 30 

Africa 37 10 15 5 67 

LAC 7 4 15 7 33 

Other Countries 5 7 15 5 32 

Total 54 24 58 26 162 

Note: The survey is categorized as long if the number of questions exceeds the median number of 

questions across all surveys, and short if the number of questions is fewer than the median number 

of questions across all surveys. 

6.7 Consistency in Termination Ratios and DHS Phase 

Table 6.7 shows survey consistency as it relates to DHS phase. Details are found in Appendix Table A.6. It 

appears that the consistency of termination ratios in DHS surveys improves with successive phases between 

DHS-2 and DHS-4. In phases DHS-5 through DHS-7, termination ratios vary between 64% and 75% 

inconsistent. The small numbers of surveys studied within each DHS phase prevent us from drawing any 

conclusions about patterns in consistency by region across DHS phases. 
88 

Table 6.7 Consistency of surveys by DHS phase 

Survey Asia Africa LAC 

Other 

Countries Total 

DHS-2 

Inconsistent 2 0 4 4 10 

Consistent 0 0 1 0 1 

DHS-3 

Inconsistent 4 2 6 4 16 

Consistent 3 0 3 0 6 

DHS-4 

Inconsistent 1 12 4 3 20 

Consistent 3 4 2 6 15 

DHS-5 

Inconsistent 5 12 5 6 28 

Consistent 2 4 1 2 9 

DHS-6 

Inconsistent 4 19 3 3 29 

Consistent 3 7 3 3 16 

DHS-7 

Inconsistent 2 7 0 0 9 

Consistent 1 0 1 1 3 

Total 30 67 33 32 162 
89 

7 DISCUSSION AND CONCLUSIONS 

This study examined the consistency of reporting of terminated pregnancies in DHS calendars, using two 

measures of consistency: within-survey consistency and between-survey consistency. We find that overall 

about 70% of surveys are classified as inconsistent by either or both of these measures. About 80% (128 of 

162 surveys) indicate within-survey inconsistency, while about 70% (55 of 78 surveys) indicate betweensurvey inconsistency. The largest group of surveys shows within-survey and between-survey inconsistency 

with no evidence of a change in the underlying termination ratio over time. Next in number are surveys 

showing within-survey and between-survey inconsistency accompanied by a change (usually an increase) 

in termination ratios over time. However, the magnitude of the trend is insufficient to fully explain the 

inconsistency observed in reported termination ratios. 

Africa has a higher proportion of inconsistent surveys (78%), whereas in each of the other three regions 

about two-thirds of surveys are classified as inconsistent. The proportion of surveys marked by betweensurvey inconsistency was substantially lower than that with within-survey inconsistency in Asia. The 

highest proportion of consistent surveys occurred during DHS-4. Consistency of reporting of terminated 

pregnancies in the DHS calendar appears to be somewhat more likely with pregnancy histories, backward 

reported histories, and the inclusion of questions that distinguish miscarriage and induced abortion, though 

the potential for confounding exists. Survey length and mode of data collection appear unrelated to the 

consistency or inconsistency of a survey in reporting pregnancy termination. 

Almost without exception, our graphical analysis of within-survey consistency indicates higher termination 

ratios reported closer to the date of interview. This finding reinforces the finding of a U.S.-based study that 

underreporting of induced abortion increases with each year that passes since the abortion occurred (Udry 

et al. 1996). It contradicts findings from the National Survey of Family Growth (NSFG) that reporting 

improves for such events farther in the past (Fu et al. 1998). Our study’s results regarding terminated 

pregnancies also parallel results related to contraceptive use in the DHS calendar that found higher 

prevalence of method use in the most recent periods of the calendar (Bradley, Winfrey, and Croft 2015). 

Similarly, this study also finds that inconsistency in reports of terminated pregnancies varies regionally, 

with inconsistency highest in Africa, where underreporting of contraceptive use is highest, and somewhat 

better elsewhere (Bradley, Winfrey, and Croft 2015). Whereas reporting of contraceptive use also appears 

to be problematic in Asia, our study finds the consistency of reporting of terminated pregnancies to be 

moderately better in Asia. 

As with an older study based on the World Fertility Survey in Bangladesh (Becker and Mahmud 1984), our 

study finds tentative evidence preferring a backward reported pregnancy history versus a forward reported 

history for consistent reporting of terminated pregnancies. A study of perinatal mortality also found that a 

pregnancy history results in more reports of stillbirths than does a birth history (Bradley, Winfrey, and Croft 

2015). However, further research is needed before making any strong recommendations. Unlike previous 

studies of contraceptive use and infant and child mortality, our study does not find evidence that survey 

length or mode of data collection adversely affects consistency of reporting terminated pregnancies 

(Bradley 2015; Bradley, Winfrey, and Croft 2015). 
90 

The present study has several limitations that deserve mention. First, it has no externally validated estimate 

of the true termination ratio. Therefore, we are unable to quantify the degree of underreporting of terminated 

pregnancies in either consistent or inconsistent surveys. Such underreporting may remain even in the 

surveys with high levels of within-survey consistency and between-survey consistency. 

Second, our statistical test of within-survey consistency assesses consistency at the two endpoints—the 

interval 0-11 months preceding the interview and the interval 48-59 months preceding the interview—rather 

than throughout the entire duration of the calendar. If the observed termination ratios vary over the course 

of the calendar but not in a clearly monotonic, linear fashion (e.g., Dominican Republic 1991), it is possible 

that the existing inconsistency could escape detection if the arbitrarily selected comparison points by chance 

produced similar termination ratios. We compared this test of within-survey consistency with alternate 

specifications testing the relationship of termination ratios to time measured (a) continuously and (b) in 

multiple intervals, and found discordance in the assessment of inconsistency in a few surveys. Overall, the 

test used in this study proved to be the more conservative test, producing slightly fewer surveys classified 

as inconsistent. We opted for this more conservative test along with the increased risk of type II error in 

order to reduce the risk of type I errors. 

We were able to assess all study surveys for within-survey consistency. For the assessment of betweensurvey consistency, however, 21 surveys were the only surveys conducted in the country, and another 32 

surveys in 20 countries were conducted too far apart to be assessed for between-survey consistency. For 

these surveys, we are unable to assess whether trends in the underlying termination ratios might explain 

some or all of the observed within-survey inconsistency. Overall, 78 survey pairs in 21 countries could be 

assessed for between-survey consistency. 

Additionally, our study assessed between-survey consistency at just two points rather than at all adjoining 

or overlapping points in the calendar between two surveys. This could impair the ability to detect (or reject) 

inconsistency between the two surveys. Finally, the graphical analysis of between-survey inconsistency 

permits us to infer trends in the underlying termination ratios reported in the calendar. However, where 

trends of a changing termination ratio are evident, we are unable to quantify the share of the observed 

inconsistency that can be attributed to the trend versus reporting error. 

This study has described the distribution of consistent and inconsistent surveys in relation to several survey 

characteristics. However, the analysis of survey characteristics is descriptive only. Our ability to make 

inferences with confidence about the patterns of consistency across survey characteristics is hampered by 

the small number of surveys in each category and the skewed distribution of some survey characteristics. 

It is further limited by potential confounding of characteristics. Surveys that adopt pregnancy histories, 

backward reported histories, and questions that differentiate types of terminations are tightly clustered in 

Asia and in the Other Countries region. Similarly, data collection using CAFÉ and longer surveys is 

associated with more recent surveys. It is not possible to disentangle which of these characteristics, if any, 

might help to increase consistency in the reporting of terminated pregnancies, or whether they might be 

related to an unobserved selection effect in the countries selecting such modifications to the standard 

application of the calendar. For example, in some Asian and Other Countries, the greater likelihood of 

surveys using a forward reported pregnancy history with survey-specific questions differentiating 

miscarriage and induced abortion Other Countries to be classified as “consistent” could be due to the 
91 

characteristics of these surveys, or could reflect greater social acceptability of discussing terminated 

pregnancies in the context of a survey in countries that select these modifications in their surveys. 

Should The DHS Program decide to promote experimentation in some of the survey modifications (e.g., 

type and direction of history, inclusion of questions distinguishing type of termination), these survey 

characteristics might become less skewed and less subject to potential selection bias. Furthermore, a quasiexperimental design could be adopted such that these or other modifications are randomly assigned to 

households or enumeration areas within a survey. A previous recommendation was made to test differences 

in data quality between PAPI and CAPI modes of data collection (Bradley, Winfrey, and Croft 2015). Such 

a study design would allow more rigorous analysis of the association between selected survey 

characteristics and consistency in reporting of terminated pregnancies. 

Our study was unable to consider all the survey-related factors that might influence the consistency of 

reporting of terminated pregnancies in the calendar. For example, we did not consider the language in which 

the interview was administered, although responses are known to be sensitive to the wording of questions 

on reproductive events (Haws et al. 2010). We also did not have available to us a measure on interviewer 

training, although presumably interviewer skill in administering probing questions and completing the 

calendar could improve the accuracy and completeness of reporting pregnancy termination. Finally, we did 

not assess fieldworker characteristics, although interviewers’ attributes and social distance between 

interviewer and respondent may exacerbate rapport and social desirability bias (Pullum et al. 2018). 

A final limitation of our study is that we examine only survey-related characteristics. We do not examine 

other contextual factors that could influence the underlying termination ratio. These include measurable 

factors such as the total fertility rate, prevalence of contraceptive use, or the level of unmet need for family 

planning, as well as other factors that are more difficult to measure—such as the distribution of terminations 

that are miscarriages, induced abortions, and stillbirths; the legality (and perceived legality) of induced 

abortion; and the degree to which induced abortion and pregnancy loss are stigmatized or taboo. Exploring 

the effect of these factors could be a rich area for further research. 

Previous assessment of the quality or consistency of DHS calendar data has related to contraception, 

perinatal mortality, age displacement, and births (Bradley, Winfrey, and Croft 2015; Goldman, Moreno, and 

Westoff 1989a; Pullum and Becker 2014; Westoff, Goldman, and Moreno 1990). The present study is the 

first known to the authors to undertake a focused assessment of reporting of terminated pregnancies in the 

DHS reproductive calendar. We find high levels of inconsistency in termination ratios within and between 

surveys, and evidence indicating that reporting of terminated pregnancies deteriorates in earlier periods of 

the calendar. We conclude that the DHS reproductive calendar remains a valuable source of data on 

terminated pregnancies. However, researchers should acknowledge the possibility of underreporting of 

terminated pregnancies, particularly in earlier periods of the calendar. Our findings, and the study’s 

limitations, suggest more experimentation with modifications to the calendar (including type and direction 

of histories, mode of data collection, and more), perhaps with survey characteristics being randomly 

assigned within or across surveys, and accompanied by rigorous assessment. 

93 

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99 

APPENDICES 

Appendix Table A.1 List of surveys by type of history and consistency classification 

Surveys with a birth history 

Survey Inconsistent Consistent 

Asia 

Afghanistan 2015 ● 

Bangladesh 1993-94 ● 

Bangladesh 1996-97 ● 

Bangladesh 1999-00 ● 

Bangladesh 2004 ● 

Bangladesh 2007 ● 

Bangladesh 2011 ● 

Bangladesh 2014 ● 

Cambodia 2010 ● 

Cambodia 2014 ● 

India 2005-06 ● 

Survey Inconsistent Consistent 

 

India 2015-16 ● 

Indonesia 1991 ● 

Indonesia 1994 ● 

Indonesia 1997 ● 

Indonesia 2002-03 ● 

Indonesia 2007 ● 

Indonesia 2012 ● 

Maldives 2009 ● 

Myanmar 2015-16 ● 

Timor-Leste 2009-10 ● 

India 2015-16 ● 

Africa 

Angola 2015-16 ● 

Benin 2006 ● 

Benin 2011-12 ● 

Burkina Faso 2003 ● 

Burkina Faso 2010 ● 

Burundi 2010 ● 

Burundi 2016-17 ● 

Comoros 2012 ● 

Ethiopia 2005 ● 

Ethiopia 2011 ● 

Ethiopia 2016 ● 

Gambia 2013 ● 

Ghana 2003 ● 

Ghana 2008 ● 

Ghana 2014 ● 

Guinea 2005 ● 

Kenya 1998 ● 

Kenya 2003 ● 

Kenya 2008-09 ● 

Kenya 2014 ● 

Lesotho 2009 ● 

Lesotho 2014 ● 

Liberia 2013 ● 

Madagascar 2003-04 ● 

Madagascar 2008-09 ● 

Malawi 2000 ● 

Malawi 2004 ● 

Malawi 2010 ● 

Malawi 2015-16 ● 

Mali 2001 ● 

Mali 2006 ● 

Mali 2012-13 ● 

Mozambique 2003 ● 

 

Mozambique 2011 ● 

Namibia 2006-07 ● 

Namibia 2013 ● 

Niger 2006 ● 

Niger 2012 ● 

Nigeria 2008 ● 

Nigeria 2013 ● 

Rwanda 2000 ● 

Rwanda 2005 ● 

Rwanda 2010 ● 

Rwanda 2014-15 ● 

Senegal 2005 ● 

Senegal 2012-13 ● 

Senegal 2014 ● 

Senegal 2015 ● 

Senegal 2016 ● 

Sierra Leone 2008 ● 

Sierra Leone 2013 ● 

Swaziland 2006-07 ● 

Tanzania 2004-05 ● 

Tanzania 2010 ● 

Tanzania 2015-16 ● 

Uganda 2000-01 ● 

Uganda 2006 ● 

Uganda 2011 ● 

Uganda 2016 ● 

Zambia 2007 ● 

Zambia 2013-14 ● 

Zimbabwe 1994 ● 

Zimbabwe 1999 ● 

Zimbabwe 2005-06 ● 

Zimbabwe 2010-11 ● 

Zimbabwe 2015 ● 

Continued 

 
100 

Appendix Table A.1—Continued 

Surveys with a birth history 

Survey Inconsistent Consistent

LAC 

Bolivia 1994 ● 

Bolivia 2003 ● 

Bolivia 2008 ● 

Brazil NE 1991 ● 

Brazil 1996 ● 

Colombia 1990 ● 

Colombia 1995 ● 

Colombia 2000 ● 

Colombia 2005 ● 

Colombia 2010 ● 

Colombia 2015 ● 

Dominican Republic 1991 ● 

Dominican Republic 1996 ● 

Dominican Republic 1999 ● 

Dominican Republic 2002 ● 

Guatemala 1995 ● 

Guatemala 1998-99 ● 

Survey Inconsistent Consistent

 

Guatemala 2014-15 ● 

Guyana 2009 ● 

Honduras 2005-06 ● 

Honduras 2011-12 ● 

Nicaragua 1998 ● 

Nicaragua 2001 ● 

Paraguay 1990 ● 

Peru 1991-92 ● 

Peru 1996 ● 

Peru 2000 ● 

Peru 2004-06 ● 

Peru 2007-08 ● 

Peru 2009 ● 

Peru 2010 ● 

Peru 2011 ● 

Peru 2012 ● 

Other Countries 

Egypt 1992 ● 

Egypt 1995 ● 

Egypt 2000 ● 

Egypt 2003 ● 

Egypt 2005 ● 

Egypt 2008 ● 

Egypt 2014 ● 

Jordan 1990 ● 

Jordan 1997 ● 

Jordan 2002 ● 

 

Jordan 2007 ● 

Jordan 2009 ● 

Jordan 2012 ● 

Morocco 1992 ● 

Morocco 2003-04 ● 

Turkey 1993 ● 

Turkey 1998 ● 

Turkey 2003 ● 

Turkey 2008 ● 

Turkey 2013 ● 

 

Surveys with a pregnancy history 

Survey Inconsistent Consistent 

Asia 

Nepal 2006 ● 

Nepal 2011 ● 

Nepal 2016 ● 

Pakistan 2012-13 ● 

Philippines 1993 ● 

Survey Inconsistent Consistent 

 

Philippines 1998 ● 

Philippines 2003 ● 

Timor-Leste 2009-10 

Vietnam 1997 ● 

Vietnam 2002 ● 

Other Countries 

Albania 2008-09 [1] ● 

Armenia 2000 ● 

Armenia 2005 ● 

Armenia 2010 ● 

Armenia 2015-16 ● 

Azerbaijan 2006 ● 

 

Kazakhstan 1999 ● 

Kyrgyz Republic 2012 ● 

Moldova 2005 ● 

Tajikistan 2012 ● 

Ukraine 2007 ● 

Notes: A birth history collects data on every live birth, whether still alive or not. A pregnancy history collects data on all pregnancies, 

including those which ended in a live birth, an induced abortion, a miscarriage, and a stillbirth. 

[1] The Albania 2008-09 DHS administers a birth history for all births, but a pregnancy history for the last 5 years. For the purposes 

of this study it is categorized as having a pregnancy history, since that is the history type completing the period of time covered by the 

calendar. 

 
101 

Appendix Table A.2 List of surveys by direction of reporting in the history and consistency classification 

Surveys with a forward reported history 

Survey Inconsistent Consistent 

Asia 

Afghanistan 2015 ● 

Bangladesh 1993-94 ● 

Bangladesh 1996-97 ● 

Bangladesh 1999-00 ● 

Bangladesh 2004 ● 

Bangladesh 2007 ● 

Bangladesh 2011 ● 

Bangladesh 2014 ● 

Cambodia 2010 ● 

Cambodia 2014 ● 

India 2005-06 ● 

India 2015-16 ● 

Indonesia 1991 ● 

Indonesia 1994 ● 

Survey Inconsistent Consistent 

 

Indonesia 1997 ● 

Indonesia 2002-03 ● 

Indonesia 2007 ● 

Indonesia 2012 ● 

Maldives 2009 ● 

Myanmar 2015-16 ● 

Nepal 2006 ● 

Nepal 2011 ● 

Nepal 2016 ● 

Pakistan 2012-13 ● 

Philippines 1993 ● 

Philippines 1998 ● 

Philippines 2003 ● 

Timor-Leste 2009-10 ● 

Africa 

Angola 2015-16 ● 

Benin 2006 ● 

Benin 2011-12 ● 

Burkina Faso 2003 ● 

Burkina Faso 2010 ● 

Burundi 2010 ● 

Burundi 2016-17 ● 

Comoros 2012 ● 

Ethiopia 2005 ● 

Ethiopia 2011 ● 

Ethiopia 2016 ● 

Gambia 2013 ● 

Ghana 2003 ● 

Ghana 2008 ● 

Ghana 2014 ● 

Guinea 2005 ● 

Kenya 1998 ● 

Kenya 2003 ● 

Kenya 2008-09 ● 

Kenya 2014 ● 

Lesotho 2009 ● 

Lesotho 2014 ● 

Liberia 2013 ● 

Madagascar 2003-04 ● 

Madagascar 2008-09 ● 

Malawi 2000 ● 

Malawi 2004 ● 

Malawi 2010 ● 

Malawi 2015-16 ● 

Mali 2001 ● 

Mali 2006 ● 

Mali 2012-13 ● 

Mozambique 2003 ● 

 

Mozambique 2011 ● 

Namibia 2006-07 ● 

Namibia 2013 ● 

Niger 2006 ● 

Niger 2012 ● 

Nigeria 2008 ● 

Nigeria 2013 ● 

Rwanda 2000 ● 

Rwanda 2005 ● 

Rwanda 2010 ● 

Rwanda 2014-15 ● 

Senegal 2005 ● 

Senegal 2010-11 ● 

Senegal 2012-13 ● 

Senegal 2014 ● 

Senegal 2015 ● 

Senegal 2016 ● 

Sierra Leone 2008 ● 

Sierra Leone 2013 ● 

Swaziland 2006-07 ● 

Tanzania 2004-05 ● 

Tanzania 2010 ● 

Tanzania 2015-16 ● 

Uganda 2000-01 ● 

Uganda 2006 ● 

Uganda 2011 ● 

Uganda 2016 ● 

Zambia 2007 ● 

Zambia 2013-14 ● 

Zimbabwe 1994 ● 

Zimbabwe 1999 ● 

Zimbabwe 2005-06 ● 

Zimbabwe 2010-11 ● 

Continued 

 
102 

Appendix Table A.2—Continued 

Surveys with a forward reported history 

Survey Inconsistent Consistent

LAC 

Bolivia 1994 ● 

Bolivia 2003 ● 

Bolivia 2008 ● 

Brazil NE 1991 ● 

Brazil 1996 ● 

Colombia 1990 ● 

Colombia 1995 ● 

Colombia 2000 ● 

Colombia 2005 ● 

Colombia 2010 ● 

Colombia 2015 ● 

Dominican Republic 1991 ● 

Dominican Republic 1996 ● 

Dominican Republic 1999 ● 

Dominican Republic 2002 ● 

Guatemala 1995 ● 

Guatemala 1998-99 ● 

Survey Inconsistent Consistent

 

Guatemala 2014-15 ● 

Guyana 2009 ● 

Honduras 2005-06 ● 

Honduras 2011-12 ● 

Nicaragua 1998 ● 

Nicaragua 2001 ● 

Paraguay 1990 ● 

Peru 1991-92 ● 

Peru 1996 ● 

Peru 2000 ● 

Peru 2004-06 ● 

Peru 2007-08 ● 

Peru 2009 ● 

Peru 2010 ● 

Peru 2011 ● 

Peru 2012 ● 

 

Other Countries 

Albania 2008-09 ● 

Armenia 2015-16 ● 

Egypt 1992 ● 

Egypt 1995 ● 

Egypt 2000 ● 

Egypt 2003 ● 

Egypt 2005 ● 

Egypt 2008 ● 

Egypt 2014 ● 

Jordan 1990 ● 

 

Jordan 1997 ● 

Jordan 2002 ● 

Jordan 2007 ● 

Jordan 2009 ● 

Jordan 2012 ● 

Kyrgyz Republic 2012 ● 

Morocco 1992 ● 

Morocco 2003-04 ● 

Tajikistan 2012 ● 

Turkey 1993 ● 

 

Surveys with a backward reported history 

Survey Inconsistent Consistent 

Asia 

Vietnam 1997 ● 

Survey Inconsistent Consistent 

 

Vietnam 2002 ● 

Other Countries 

Armenia 2000 ● 

Armenia 2005 ● 

Armenia 2010 ● 

Azerbaijan 2006 ● 

 

Kazakhstan 1999 ● 

Moldova 2005 ● 

Ukraine 2007 ● 

Note: A forward reported history collects data beginning with the first birth/pregnancy moving through each subsequent one until the

most recent, whereas a backward reported history collects data beginning with the most recent birth/pregnancy moving backward

until the first birth/pregnancy. 

 
103 

Appendix Table A.3 List of surveys by questions that distinguish miscarriage and induced abortion and 

consistency classification 

Surveys with no questions that distinguish miscarriage and induced abortion 

Survey Inconsistent Consistent 

Asia 

Afghanistan 2015 ● 

Bangladesh 1993-94 ● 

Bangladesh 1999-00 ● 

Bangladesh 2004 ● 

Bangladesh 2007 ● 

Bangladesh 2011 ● 

Bangladesh 2014 ● 

Cambodia 2010 ● 

Cambodia 2014 ● 

India 2005-06 ● 

Indonesia 1991 ● 

Survey Inconsistent Consistent 

 

Indonesia 1994 ● 

Indonesia 2002-03 ● 

Indonesia 2007 ● 

Maldives 2009 ● 

Myanmar 2015-16 ● 

Philippines 1993 ● 

Philippines 1998 ● 

Philippines 2003 ● 

Timor-Leste 2009-10 ● 

Vietnam 1997 ● 

Vietnam 2002 ● 

Africa 

Angola 2015-16 ● 

Benin 2006 ● 

Benin 2011-12 ● 

Burkina Faso 2003 ● 

Burkina Faso 2010 ● 

Burundi 2010 ● 

Burundi 2016-17 ● 

Comoros 2012 ● 

Ethiopia 2005 ● 

Ethiopia 2011 ● 

Ethiopia 2016 ● 

Gambia 2013 ● 

Ghana 2003 ● 

Ghana 2008 ● 

Ghana 2014 ● 

Guinea 2005 ● 

Kenya 1998 ● 

Kenya 2003 ● 

Kenya 2008-09 ● 

Kenya 2014 ● 

Lesotho 2009 ● 

Lesotho 2014 ● 

Liberia 2013 ● 

Madagascar 2003-04 ● 

Madagascar 2008-09 ● 

Malawi 2000 ● 

Malawi 2004 ● 

Malawi 2010 ● 

Malawi 2015-16 ● 

Mali 2001 ● 

Mali 2006 ● 

Mali 2012-13 ● 

Mozambique 2003 ● 

Mozambique 2011 ● 

 

Namibia 2006-07 ● 

Namibia 2013 ● 

Niger 2006 ● 

Niger 2012 ● 

Nigeria 2008 ● 

Nigeria 2013 ● 

Rwanda 2000 ● 

Rwanda 2005 ● 

Rwanda 2010 ● 

Rwanda 2014-15 ● 

Senegal 2005 ● 

Senegal 2010-11 ● 

Senegal 2012-13 ● 

Senegal 2014 ● 

Senegal 2015 ● 

Senegal 2016 ● 

Sierra Leone 2008 ● 

Sierra Leone 2013 ● 

Swaziland 2006-07 ● 

Tanzania 2004-05 ● 

Tanzania 2010 ● 

Tanzania 2015-16 ● 

Uganda 2000-01 ● 

Uganda 2006 ● 

Uganda 2011 ● 

Uganda 2016 ● 

Zambia 2007 ● 

Zambia 2013-14 ● 

Zimbabwe 1994 ● 

Zimbabwe 1999 ● 

Zimbabwe 2005-06 ● 

Zimbabwe 2010-11 ● 

Zimbabwe 2015 ● 

Continued 

 
104 

Appendix Table A.3—Continued 

Surveys with no questions that distinguish miscarriage and induced abortion 

Survey Inconsistent Consistent

LAC 

Bolivia 1994 ● 

Bolivia 2003 ● 

Bolivia 2008 ● 

Brazil NE 1991 ● 

Brazil 1996 ● 

Colombia 1990 ● 

Colombia 1995 ● 

Colombia 2000 ● 

Colombia 2005 ● 

Colombia 2010 ● 

Colombia 2015 ● 

Dominican Republic 1991 ● 

Dominican Republic 1996 ● 

Dominican Republic 1999 ● 

Dominican Republic 2002 ● 

Guatemala 1995 ● 

Guatemala 1998-99 [1] ● 

Survey Inconsistent Consistent

 

Guatemala 2014-15 ● 

Guyana 2009 ● 

Honduras 2005-06 ● 

Honduras 2011-12 ● 

Nicaragua 1998 ● 

Nicaragua 2001 ● 

Paraguay 1990 ● 

Peru 1991-92 ● 

Peru 1996 ● 

Peru 2000 ● 

Peru 2004-06 ● 

Peru 2007-08 ● 

Peru 2009 ● 

Peru 2010 ● 

Peru 2011 ● 

Peru 2012 ● 

 

Other Countries 

Azerbaijan 2006 ● 

Egypt 1992 ● 

Jordan 1990 ● 

Jordan 1997 ● 

Jordan 2002 ● 

Jordan 2007 ● 

Jordan 2009 ● 

Jordan 2012 ● 

 

Kyrgyz Republic 2012 ● 

Moldova 2005 ● 

Morocco 1992 ● 

Morocco 2003-04 ● 

Tajikistan 2012 ● 

Turkey 1998 ● 

Ukraine 2007 ● 

Yemen 2013 ● 

 

Surveys with questions that distinguish miscarriage and induced abortion 

Survey Inconsistent Consistent 

Asia 

Bangladesh 1996-97 ● 

India 2015-16 ● 

Indonesia 1997 ● 

Indonesia 2012 ● 

Survey Inconsistent Consistent 

 

Nepal 2006 ● 

Nepal 2011 ● 

Nepal 2016 ● 

Pakistan 2012-13 ● 

Other Countries 

Albania 2008-09 ● 

Armenia 2000 ● 

Armenia 2005 ● 

Armenia 2010 ● 

Armenia 2015-16 ● 

Egypt 1995 ● 

Egypt 2000 ● 

Egypt 2003 ● 

 

Egypt 2005 ● 

Egypt 2008 ● 

Egypt 2014 ● 

Kazakhstan 1999 ● 

Turkey 1993 ● 

Turkey 2003 ● 

Turkey 2008 ● 

Turkey 2013 ● 

[1] The Guatemala 1998-99 DHS does not distinguish between miscarriage and induced abortion, but does differentiate between early

neonatal death and stillbirth. 

 
105 

Appendix Table A.4 List of surveys by mode of data collection and consistency classification 

Surveys with data collected by PAPI 

Survey Inconsistent Consistent 

Asia 

Afghanistan 2015 ● 

Bangladesh 1993-94 ● 

Bangladesh 1996-97 ● 

Bangladesh 1999-00 ● 

Bangladesh 2004 ● 

Bangladesh 2007 ● 

Bangladesh 2011 ● 

Bangladesh 2014 ● 

Cambodia 2010 ● 

Cambodia 2014 ● 

India 2005-06 ● 

Indonesia 1991 ● 

Indonesia 1994 ● 

Survey Inconsistent Consistent 

 

Indonesia 1997 ● 

Indonesia 2002-03 ● 

Indonesia 2007 ● 

Indonesia 2012 ● 

Nepal 2006 ● 

Pakistan 2012-13 ● 

Philippines 1993 ● 

Philippines 1998 ● 

Philippines 2003 ● 

Timor-Leste 2009-10 ● 

Vietnam 1997 ● 

Vietnam 2002 ● 

Africa 

Benin 2006 ● 

Burkina Faso 2003 ● 

Burkina Faso 2010 ● 

Burundi 2010 ● 

Comoros 2012 ● 

Ethiopia 2005 ● 

Ethiopia 2011 ● 

Gambia 2013 ● 

Ghana 2003 ● 

Ghana 2008 ● 

Guinea 2005 ● 

Kenya 1998 ● 

Kenya 2003 ● 

Kenya 2008-09 ● 

Kenya 2014 ● 

Liberia 2013 ● 

Madagascar 2003-04 ● 

Madagascar 2008-09 ● 

Malawi 2000 ● 

Malawi 2004 ● 

Malawi 2010 ● 

Mali 2001 ● 

Mali 2006 ● 

Mozambique 2003 ● 

Namibia 2006-07 ● 

 

Namibia 2013 ● 

Niger 2006 ● 

Niger 2012 ● 

Nigeria 2008 ● 

Nigeria 2013 ● 

Rwanda 2000 ● 

Rwanda 2005 ● 

Rwanda 2010 ● 

Rwanda 2014-15 ● 

Senegal 2005 ● 

Sierra Leone 2008 ● 

Sierra Leone 2013 ● 

Swaziland 2006-07 ● 

Tanzania 2004-05 ● 

Tanzania 2010 ● 

Tanzania 2015-16 ● 

Uganda 2000-01 ● 

Uganda 2006 ● 

Uganda 2011 ● 

Zambia 2007 ● 

Zambia 2013-14 ● 

Zimbabwe 1994 ● 

Zimbabwe 1999 ● 

Zimbabwe 2005-06 ● 

 

LAC 

Bolivia 1994 ● 

Bolivia 2003 ● 

Bolivia 2008 ● 

Brazil NE 1991 ● 

Brazil 1996 ● 

Colombia 1990 ● 

Colombia 1995 ● 

Colombia 2000 ● 

Dominican Republic 1991 ● 

Dominican Republic 1996 ● 

Dominican Republic 1999 ● 

Dominican Republic 2002 ● 

 

Guatemala 1995 ● 

Guatemala 1998-99 ● 

Guatemala 2014-15 ● 

Guyana 2009 ● 

Honduras 2005-06 ● 

Honduras 2011-12 ● 

Nicaragua 1998 ● 

Nicaragua 2001 ● 

Paraguay 1990 ● 

Peru 1991-92 ● 

Peru 1996 ● 

Peru 2000 ● 

Continued 
106 

Appendix Table A.4—Continued 

Surveys with data collected by PAPI 

Survey Inconsistent Consistent

Other Countries 

Armenia 2000 ● 

Armenia 2005 ● 

Armenia 2010 ● 

Armenia 2015-16 ● 

Azerbaijan 2006 ● 

Egypt 1992 ● 

Egypt 1995 ● 

Egypt 2000 ● 

Egypt 2003 ● 

Egypt 2005 ● 

Egypt 2008 ● 

Egypt 2014 ● 

Jordan 1990 ● 

Jordan 1997 ● 

Jordan 2002 ● 

Jordan 2007 ● 

Survey Inconsistent Consistent

 

Jordan 2009 ● 

Jordan 2012 ● 

Kazakhstan 1999 ● 

Kyrgyz Republic 2012 ● 

Moldova 2005 ● 

Morocco 1992 ● 

Morocco 2003-04 ● 

Tajikistan 2012 ● 

Turkey 1993 ● 

Turkey 1998 ● 

Turkey 2003 ● 

Turkey 2008 ● 

Turkey 2013 ● 

Ukraine 2007 ● 

Yemen 2013 ● 

 

Surveys with data collected by CAFÉ or CAPI 

Survey Inconsistent Consistent 

Asia 

India 2015-16 ● 

Maldives 2009 ● 

Myanmar 2015-16 ● 

Survey Inconsistent Consistent 

 

Nepal 2011 ● 

Nepal 2016 ● 

Africa 

Angola 2015-16 ● 

Benin 2011-12 ● 

Burundi 2016-17 ● 

Ethiopia 2016 ● 

Ghana 2014 ● 

Lesotho 2009 ● 

Lesotho 2014 ● 

Malawi 2015-16 ● 

Mali 2012-13 ● 

 

Mozambique 2011 ● 

Senegal 2010-11 ● 

Senegal 2012-13 ● 

Senegal 2014 ● 

Senegal 2015 ● 

Senegal 2016 ● 

Uganda 2016 ● 

Zimbabwe 2010-11 ● 

Zimbabwe 2015 ● 

LAC 

Colombia 2005 ● 

Colombia 2010 ● 

Colombia 2015 ● 

Peru 2004-06 ● 

Peru 2007-08 ● 

 

Peru 2009 ● 

Peru 2010 ● 

Peru 2011 ● 

Peru 2012 ● 

Other Countries 

Albania 2008-09 ● 

 

● 

Notes: PAPI: pen and paper personal interview; CAFÉ: computer-assisted field editing; CAPI: computer-assisted personal interview 

 
107 

Appendix Table A.5 List of surveys by length of survey and consistency classification 

Long surveys Short surveys

Survey Inconsistent Consistent Survey Inconsistent Consistent

Asia Asia 

Afghanistan 2015 ● Bangladesh 1993-94 ● 

Cambodia 2014 ● Bangladesh 1996-97 ● 

India 2005-06 ● Bangladesh 1999-00 ● 

India 2015-16 ● Bangladesh 2004 ● 

Indonesia 2012 ● Bangladesh 2007 ● 

Myanmar 2015-16 ● Bangladesh 2011 ● 

Nepal 2016 ● Bangladesh 2014 ● 

Timor-Leste 2009-10 ● Cambodia 2010 ● 

Africa Indonesia 1991 ● 

Angola 2015-16 ● Indonesia 1994 ● 

Benin 2006 ● Indonesia 1997 ● 

Benin 2011-12 ● Indonesia 2002-03 ● 

Burkina Faso 2010 ● Indonesia 2007 ● 

Burundi 2016-17 ● Maldives 2009 ● 

Comoros 2012 ● Nepal 2006 ● 

Ethiopia 2005 ● Nepal 2011 ● 

Ethiopia 2016 ● Pakistan 2012-13 ● 

Gambia 2013 ● Philippines 1993 ● 

Ghana 2008 ● Philippines 1998 ● 

Ghana 2014 ● Philippines 2003 ● 

Guinea 2005 ● Vietnam 1997 ● 

Kenya 2008-09 ● Vietnam 2002 ● 

Kenya 2014 ● Africa 

Lesotho 2009 ● Burkina Faso 2003 ● 

Lesotho 2014 ● Burundi 2010 ● 

Madagascar 2003-04 ● Ethiopia 2011 ● 

Madagascar 2008-09 ● Ghana 2003 ● 

Malawi 2010 ● Kenya 1998 ● 

Malawi 2015-16 ● Kenya 2003 ● 

Mali 2006 ● Liberia 2013 ● 

Mali 2012-13 ● Malawi 2000 ● 

Mozambique 2011 ● Malawi 2004 ● 

Namibia 2006-07 ● Mali 2001 ● 

Namibia 2013 ● Mozambique 2003 ● 

Niger 2006 ● Rwanda 2000 ● 

Niger 2012 ● Senegal 2010-11 ● 

Nigeria 2008 ● Senegal 2012-13 ● 

Nigeria 2013 ● Senegal 2014 ● 

Rwanda 2005 ● Senegal 2015 ● 

Rwanda 2010 ● Senegal 2016 ● 

Rwanda 2014-15 ● Uganda 2000-01 ● 

Senegal 2005 ● Zimbabwe 1994 ● 

Sierra Leone 2008 ● Zimbabwe 1999 ● 

Sierra Leone 2013 ● LAC 

Swaziland 2006-07 ● Bolivia 1994 ● 

Tanzania 2004-05 ● Brazil NE 1991 ● 

Tanzania 2010 ● Brazil 1996 ● 

Tanzania 2015-16 ● Colombia 1990 ● 

Uganda 2006 ● Colombia 1995 ● 

Uganda 2011 ● Colombia 2000 ● 

Uganda 2016 ● Dominican Republic 1991 ● 

Zambia 2007 ● Dominican Republic 1996 ● 

Continued 
108 

Appendix Table A.5—Continued 

Long surveys Short surveys

Survey Inconsistent Consistent Survey Inconsistent Consistent

Africa cont’d LAC cont’d 

Zambia 2013-14 ● Guatemala 1995 ● 

Zimbabwe 2005-06 ● Guatemala 1998-99 ● 

Zimbabwe 2010-11 ● Nicaragua 1998 ● 

Zimbabwe 2015 ● Nicaragua 2001 ● 

LAC Paraguay 1990 ● 

Bolivia 2003 ● Peru 1991-92 ● 

Bolivia 2008 ● Peru 1996 ● 

Colombia 2005 ● Peru 2000 ● 

Colombia 2010 ● Peru 2004-06 ● 

Colombia 2015 ● Peru 2007-08 ● 

Dominican Republic 1999 ● Peru 2009 ● 

Dominican Republic 2002 ● Peru 2010 ● 

Guatemala 2014-15 ● Peru 2011 ● 

Guyana 2009 ● Peru 2012 ● 

Honduras 2005-06 ● Other Countries 

Honduras 2011-12 ● Egypt 1992 ● 

Other Countries Egypt 1995 ● 

Albania 2008-09 ● Egypt 2000 ● 

Armenia 2000 ● Egypt 2003 ● 

Armenia 2005 ● Egypt 2008 ● 

Armenia 2010 ● Egypt 2014 ● 

Armenia 2015-16 ● Jordan 1990 ● 

Azerbaijan 2006 ● Jordan 1997 ● 

Egypt 2005 ● Jordan 2002 ● 

Kyrgyz Republic 2012 ● Jordan 2007 ● 

Moldova 2005 ● Jordan 2009 ● 

Tajikistan 2012 ● Jordan 2012 ● 

Turkey 2003 ● Kazakhstan 1999 ● 

Ukraine 2007 ● Morocco 1992 ● 

 Morocco 2003-04 ● 

 Turkey 1993 ● 

 Turkey 1998 ● 

 Turkey 2008 ● 

Turkey 2013 ● 

Yemen 2013 ● 

Note: The survey is categorized as long if the number of questions exceeds the median number of questions across all surveys, and 

short if the number of questions is fewer than the median number of questions across all surveys. 

 
109 

Appendix Table A.6 List of surveys by DHS phase and consistency classification 

Survey Inconsistent Consistent 

DHS-2 

Asia 

Indonesia 1991 ● 

Philippines 1993 ● 

LAC 

Brazil NE 1991 ● 

Colombia 1990 ● 

Dominican Republic 1991 ● 

Paraguay 1990 ● 

Peru 1991-92 ● 

Other Countries 

Egypt 1992 ● 

Jordan 1990 ● 

Morocco 1992 ● 

Turkey 1993 ● 

DHS-3 

Asia 

Bangladesh 1993-94 ● 

Bangladesh 1996-97 ● 

Bangladesh 1999-00 ● 

Indonesia 1994 ● 

Indonesia 1997 ● 

Philippines 1998 ● 

Vietnam 1997 ● 

Africa 

Kenya 1998 ● 

Zimbabwe 1994 ● 

LAC 

Bolivia 1994 ● 

Brazil 1996 ● 

Colombia 1995 ● 

Dominican Republic 1996 ● 

Dominican Republic 1999 ● 

Guatemala 1995 ● 

Guatemala 1998-99 ● 

Nicaragua 1998 ● 

Peru 1996 ● 

Other Countries 

Egypt 1995 ● 

Jordan 1997 ● 

Kazakhstan 1999 ● 

Turkey 1998 ● 

DHS-4 

Asia 

Bangladesh 2004 ● 

Indonesia 2002-03 ● 

Philippines 2003 ● 

Vietnam 2002 ● 

Continued 

 
110 

Appendix Table A.6—Continued 

Survey Inconsistent Consistent 

DHS-4 cont’d 

Africa 

Burkina Faso 2003 ● 

Ethiopia 2005 ● 

Ghana 2003 ● 

Guinea 2005 ● 

Kenya 2003 ● 

Madagascar 2003-04 ● 

Malawi 2000 ● 

Malawi 2004 ● 

Mali 2001 ● 

Mozambique 2003 ● 

Rwanda 2000 ● 

Rwanda 2005 ● 

Senegal 2005 ● 

Tanzania 2004-05 ● 

Uganda 2000-01 ● 

Zimbabwe 1999 ● 

LAC 

Bolivia 2003 ● 

Colombia 2000 ● 

Colombia 2005 ● 

Dominican Republic 2002 ● 

Nicaragua 2001 ● 

Peru 2000 ● 

Other Countries 

Armenia 2000 ● 

Armenia 2005 ● 

Egypt 2000 ● 

Egypt 2003 ● 

Egypt 2005 ● 

Jordan 2002 ● 

Moldova 2005 ● 

Morocco 2003-04 ● 

Turkey 2003 ● 

DHS-5 

Asia 

Bangladesh 2007 ● 

Cambodia 2010 ● 

India 2005-06 ● 

Indonesia 2007 ● 

Maldives 2009 ● 

Nepal 2006 ● 

Timor-Leste 2009-10 ● 

Africa 

Benin 2006 ● 

Ghana 2008 ● 

Kenya 2008-09 ● 

Lesotho 2009 ● 

Madagascar 2008-09 ● 

Malawi 2010 ● 

Mali 2006 ● 

Continued 
111 

Appendix Table A.6—Continued 

Survey Inconsistent Consistent 

DHS-5, Africa cont’d 

Namibia 2006-07 ● 

Niger 2006 ● 

Nigeria 2008 ● 

Sierra Leone 2008 ● 

Swaziland 2006-07 ● 

Tanzania 2010 ● 

Uganda 2006 ● 

Zambia 2007 ● 

Zimbabwe 2005-06 ● 

LAC 

Bolivia 2008 ● 

Colombia 2010 ● 

Guyana 2009 ● 

Honduras 2005-06 ● 

Peru 2004-06 ● 

Peru 2007-08 ● 

Other Countries 

Albania 2008-09 ● 

Azerbaijan 2006 ● 

Egypt 2008 ● 

Jordan 2007 ● 

Jordan 2009 ● 

Turkey 2008 ● 

Ukraine 2007 ● 

DHS-6 

Asia 

Bangladesh 2011 ● 

Bangladesh 2014 ● 

Cambodia 2014 ● 

India 2015-16 ● 

Indonesia 2012 ● 

Nepal 2011 ● 

Pakistan 2012-13 ● 

Africa 

Benin 2011-12 ● 

Burkina Faso 2010 ● 

Burundi 2010 ● 

Comoros 2012 ● 

Ethiopia 2011 ● 

Gambia 2013 ● 

Ghana 2014 ● 

Kenya 2014 ● 

Lesotho 2014 ● 

Liberia 2013 ● 

Mali 2012-13 ● 

Mozambique 2011 ● 

Namibia 2013 ● 

Niger 2012 ● 

Nigeria 2013 ● 

Rwanda 2010 ● 

Rwanda 2014-15 ● 

Senegal 2010-11 ● 

Continued 
112 

Appendix Table A.6—Continued 

Survey Inconsistent Consistent 

DHS-6, Africa cont’d 

Senegal 2012-13 ● 

Senegal 2014 ● 

Senegal 2015 ● 

Senegal 2016 ● 

Sierra Leone 2013 ● 

Uganda 2011 ● 

Zambia 2013-14 ● 

Zimbabwe 2010-11 ● 

LAC 

Guatemala 2014-15 ● 

Honduras 2011-12 ● 

Peru 2009 ● 

Peru 2010 ● 

Peru 2011 ● 

Peru 2012 ● 

Other Countries 

Armenia 2010 ● 

Egypt 2014 ● 

Jordan 2012 ● 

Kyrgyz Republic 2012 ● 

Tajikistan 2012 ● 

Turkey 2013 ● 

Yemen 2013 ● 

DHS-7 

Asia 

Afghanistan 2015 ● 

Myanmar 2015-16 ● 

Nepal 2016 ● 

Africa 

Angola 2015-16 ● 

Burundi 2016-17 ● 

Ethiopia 2016 ● 

Malawi 2015-16 ● 

Tanzania 2015-16 ● 

Uganda 2016 ● 

Zimbabwe 2015 ● 

LAC 

Colombia 2015 ● 

Other Countries 

Armenia 2015-16 ●