Gender discrimination in healthcare spending at the household
level and women’s access to resources : Perspective of
Bangladesh

Khandaker, Mu. Mizanur Rahman
GraSPP, University of Tokyo,
Student ID: 51-118218

1

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Definitions of some terminologies,
Research motivation,
Research objectives,
Research question,
Data and research methodology,
Econometrics Results,
Causes of gender discrimination, andRecommendations.

2Some terminologies
Sex:
Sex refers to the biological differences between men and women,boys and girls. It is defined as the property by which organisms areclassified as males or females based on reproductive organs andfunctions (www.thefreedictionary.com).
Biological and physiological differences between males andfemales are represented by sex such as reproductive organs,chromosomes and hormones etc. distinguish men and women, boys andgirls (WHO, 2010).
• Gender :Gender describes socially constructed differences between men andwomen, boys and girls etc. Gender is defined on the basis of social
norms, behaviors, activities, relationship, responsibilities which areassigned by the society as appropriate for male and female (WHO,2010).
Understanding of gender varies in different races, nations, castes,ethnic groups, religions.
3

Some terminologies
Gender equality :The gender equality means that both men and women, as
human being, have equal rights and opportunities irrespective ofgender. It also refers that all people (men and women) must have equal
right to develop their personal abilities and free to make personal
choices.
World Bank (2012), “Gender refers to the social, behavioral, and cultural
attributes, expectations and norms that distinguish men and women.
Gender equality refers to the extent to which men’s and women’s
opportunities and outcomes are constrained—or enhanced—solely on
the basis of their gender”.
More specifically, gender equality emphasis that natural or biologicaldifference between men and women will not lead to difference in status
and rights in all sphere of life between men and women(www. http://global.finland.fi)
4Background issues
Gender Issue : A common goal for the International community.
Reasons :(i) A tremendous constraint towards the development process ;(ii) A causal factor of violence against women ;(iii) To create a more just and equal world for both men and women.
International recognition:
Gender issue(i) had been set out in the preamble to the Charter of the United
Nations (UN) in 1945;(ii) included in the Universal Declaration of Human Rights in 1948;(iii) the Convention on elimination of all forms of discrimination against
women (CEDAW) was adopted by General Assembly of United
Nations in 1979 .
5

Background issues
Importance of CEDAW: A key international document on the rights of women; A legal and moral pressure on the UN member countries for taking
necessary steps in order to ensure equal rights for women;
 Focus the civil rights, legal rights of women, reproductive roles and rights,
impact of cultural factors on gender relations and barriers on advancementof women .
Beijing Platform for Action
In the Beijing Platform for action adopted at the Fourth World
Conference on Women in 1995, Governments committed themselves to taking
a number of measures in order to promote women’s economic rights andeliminate discrimination against women.
Millennium Development Goals (MDGs)
 MDGs which were adopted in the Millennium Summit of the United
Nations in 2000 and endorsed by 189 United Nations member states alsoemphasize on gender issue;
 The third goal of MDGs is “Promote gender equality and empower
6
women”.

Background issues
Various approaches or strategies in promoting the advancementof women :Period : Until late 1960s.
Strategies :Overall economic development and modernization process in thedeveloping world would improve the status of women by benefiting both maleand female with equal pace.
Target areas:
Women’s reproductive health, especially women’s access to food,contraceptives, nutrition and health care.

7

Background issues
WID vs GAD
Gender Mainstreaming
Period : During 1970s and 1980s
WID : 1970s
Women in Development (WID) aims to include women in development
projects in order to make them more efficient.
WID paradigm had three phases (i) “Equity approach”, (ii) “Anti-poverty” phase,and (iii) “Efficiency” phase.
GAD : Mid 1980s
Gender and Development (GAD) aims to address inequalities between women's
and men's social roles in relation to development.

Gender Mainstreaming : The most recent approach endorsed by 189 countries; Gender Mainstreaming emphasizes on the full participation of women for
the attainment of sustainable development.
8

Background issues
Approaches of Gender Mainstreaming are :(i)

It considers men and women as a complementary forces andnot as opposing forces,(ii) It is an umbrella approach targets gender equality policies,(iii) It has a wide scope to address all kinds of development
settings from poverty alleviation to environmental
protection,(iv) It aims at institutional restructuring for sustainable
development on gender equality,(v) It tries to determine the root causes of gender discriminationand institutional reform to achieve sustainable development
in all spheres of the nation
9

Motivation

 Promotion of gender discrimination directly
contributes to Poverty reduction strategies
and MDGs;
 Government emphasis on gender issues andcommitted to bring the gender issue in policy
formulation;
 Motivated to conduct a research on thefollowing topic , with a view to contributing tonational sustainable development programs.
10Research Objectives
Objectives:To estimate gender biasness in healthcare spending
for the children (age upto 10) within the household;To find the determinants that cause gender
gap in the household as well as in the society; andTo recommend some policy implications.

Research question:(i) Is there any gender biasness in healthcare spending forthe children within the household in Bangladesh ?
(ii) Does socio-cultural norms influence gender gap
against women in the society ?
11Data and Methodology

Data :
a. HIES-2010 from Bangladesh;b. Information from national and international journals,
publications and books on existing laws in Bangladesh.
Methodology :(i) Quantitative methodology;

12

Data and Methodology• Model specifications:
Ln_healthcare_costi = β0 + β 1 Genderi + β 2 Agei + β 3Rurali+What_Classi + β 5 Immunization i+ β 6Hhsizei+ β 7 Parent_edui + β 8 Highest_passed+
β 9 Hhwealthi + β 10 Regioni + εi….(i)Where, i = 1, 2, …, 10422.
• Dependent variable :Yearly healthcare spending for children in thehousehold;13

Hypothesis• Objective:
The prime objective of the research is to examine whether
there is gender discrimination in healthcare spending for thechildren at household level in Bangladesh or not.

• Variable of interest: Gender• Controlling variables :Healthcare spending is mainly influenced by three major
factors such as (i) Personal chacerteristics, (ii) Family
background and (iii) Locality .
Thus we are interested to measure the variation in healthcare
spending by regressing it on the independent variables including
gender where some influential factors of healthcare spending
would be controlled.
14Independent variables (Regressors)
Independent variables (Regressors)
Personal chacerteristics :Gender , Age , Chronic_dis , Immu_bcg, Immu_dpt_1,
Immu_dpt_2 , Immu_dpt_3, Immu_ polio_1 ,Immu_polio_2, Highest_passed, What_class.
Family background:
Fathereducation, Mothereducation, Landasset,
Non_landasset , Hhsize .
Region: (i) Locality (Rural/urban)(ii) Geographical location of 7 Administrative Regions
such as Borisal, Chittagong, Dhaka, Khulna,
Rajshahi, Rangpur, Sylhet.
15

Summary Statistics of some variables
Table: I

Summary statistics of some variables:
Variable

Obs

Mean

Min

Max

Healthcare_cost

2491

384.5548

3

70000

Gender2491

0.4628663

0

1

Age

2491

4.695303010Highest_passed

2491

0.4347652

0

19

Attending_school

2491

0.5917302

02

What_class2491

0.9642714

019Chronic_dis

2491

1.956644

1

2

Immu_bcg

2491

0.5584103

02

Immu_dpt_1

2491

0.5620233

02

Immu_polio_1

2491

0.5688479

02

Immu_measles

2491

0.6174227

02

Immu_hepatites

2491

0.6471297

0

2

Rural

2491

0.6932959

01

Hhsize2491

5.1240473

15

Landasset

2491

53.61582

1

1179

Non_landasset

2491

362998.5

0

1.72E+07

Father’s educeducation

2491

3.758731

013Mother’s education

2491

3.744279

0

13

16

Table_III

Average yearly spending on healthcare for male and female children within household(in BD. Taka)t-statistics
Male
Femaledifference
1.7164238.0983
118.9199
119.1784**
1.7282101.4083
69.69743
85.93774**
1.288865.32046
51.93122
13.38925*
0.916781.930760.30818
21.62252

Age group
0-2
3-5
6-8
9-10

***
**
*

indicates statistical significant at 1% level of significanceindicates statistical significant at 5% level of significanceindicates statistical significant at 10% level of significance

Average yearly spending on healthcare for children within household(in BD. Taka)

300
250
B
D
200
.
150
T
A 100
K
A 50

Male
Female00 to 23 to 5

6 t0 89 to 10

Children of age group17

Linear regression
Number of obs = 2491, F( 17, 2473) = 10.49, Prob > F = 0.0000, R-squared= 0.0741. Root MSE = 1.2074
Robust[95% Conf. Interval]

ln_healthc~t

Coef.

Std. Err.

T

P>tgender-.1612105.0488496

-3.30

0.001

-.2570008-.0654202

age-.0751649.0175641

-4.28

0.000

-.1096067-.040723

highest_pa~d.0214915.0226507

0.95

0.343

-.0229247.0659078

attending_~l -.0275559.0548917

-0.50

0.616

-.1351943.0800825

what_class.009556.014857

0.64

0.520

-.0195774.0386894

chronic_dis.904233.1251333

7.23

0.000

.6588561

1.14961

immu_bcg.3308168.450063

0.74

0.462

-.5517223

1.213356

immu_dpt_1-.3352627.4231331

-0.79

0.428

-1.164994.4944689

immu_polio_1-.0111534.2386223

-0.05

0.963

-.4790736.4567668

immu_measles-.090539.1321828

-0.68

0.493

-.3497394.1686615

immu_hepat~s-.1034924.0998741

-1.04

0.300

-.2993379.0923532

rural-.0677506

-1.21

0.225

-.1773001.041799

hhsize-.0136573.0154434

-0.88

0.377

-.0439406.0166259

landasset.0001686.0002031

0.83

0.407

-.0002296.0005668

non_landas~t

6.89e-08

3.52e-08

1.96

0.050

-1.33e-11

1.38e-07

fathereduc~n.0245534.0077053

3.19

0.001

.009444.0396628

mothereduc~n.0161504.0084208

1.92

0.055

-.0003622.032663_cons

5.425217.1521455

35.66

0.000

5.126871

5.723563.0558663

18

reg ln_healthcare_cost gender age highest_passed attending_school what_class chronic_dis immu_bcg immu_dpt_1
immu_polio_1 immu_measles immu_hepatitis rural hhsize landasset non_landasset fathereducation mothereducation Borisal
chittagong Dhaka Khulna Rajshahi Rangpur ,rLinear regression
Number of obs = 2491 , F( 23, 2467) = 13.75, Prob > F = 0.0000, R-squared = 0.1173, Root MSE = 1.1803
Ln_healthc~tgenderage
highest_pa~dattending_~l
what_classchronic_dis
immu_bcg
immu_dpt_1
immu_polio_1
immu_measles
immu_hepat~s
rural
hhsizelandasset
non_landas~tfathereduc~nmothereduc~nBorisalChittagong
Dhaka
KhulnaRajshahi
Rangpur
_cons

Coef.
-.1539197-.0691072.0363511-.0205795.0031137.8652634.4612107-.4137023-.0655113-.0826457-.0707316-.0666589-.0542592.0002653
4.82e-08.0249245.0176718.1448831.2749807-.1821765-.432475-.2478177-.4881127
5.707212

Std. Err.
.0476923.0175169.0231088.0536078.0149163.1242231.4198373.3964264.2340423.1329731.1024355.0553083.0157826.0001956
3.50e-08.0075314.0082169.1318588.1009418.1013691.1155427.1117995.1070083.1860525

T
-3.23
-3.95
1.57
-0.38
0.21
6.97
1.10
-1.04
-0.28
-0.62
-0.69
-1.21
-3.44
1.36
1.38
3.31
2.15
1.10
2.72
-1.80
-3.74
-2.22
-4.56
30.68

p>t
0.001
0.000
0.116
0.701
0.835
0.000
0.272
0.297
0.780
0.534
0.490
0.228
0.001
0.175
0.168
0.001
0.032
0.272
0.006
0.072
0.000
0.027
0.000
0.000

[95% Conf.
-.2474408-.1034565-.0089635-.1257003-.0261362.621671-.3620592-1.191065-.5244509-.3433961-.2716-.1751145-.0852077-.0001182-2.04e-08.010156.0015591-.1136822.0770412-.3809538-.6590458-.4670482-.697948
5.342377

Interval]-.0603986-.0347579.0816658.0845414.0323635
1.108856
1.284481.3636606.3934282.1781047.1301369.0417967-.0233107.0006489
1.17e-07.0396929.0337846.4034484.4729202.0166009-.2059043-.0285872-.2782774
6.07204719

reg ln_healthcare_cost gender age age2 highest_passed attending_school what_class chronic_dis immu_bcg immu_dpt_1
immu_polio_1 immu_measles immu_hepatitis rural hhsize landasset non_landasset fathereducation mothereducation Borisal
chittagong Dhaka Khulna Rajshahi Rangpur ,rLinear regression
Number of obs = 2491 , F( 23, 2467) = 13.75, Prob > F
ln_healthc~t
Coef.
Std. Err.

= 0.0000, R-squared = 0.1201,
tP>tgenderage
age2
highest_pa~dattending_~l
what_classchronic_dis
immu_bcg
immu_dpt_1
immu_polio_1
immu_measles
immu_hepat~s
rural
hhsizeLandasset
non_landas~tfathereduc~nmothereduc~nBorisalchittagong
Dhaka
KhulnaRajshahi
Rangpur
_cons

-3.18
-4.58
2.81
1.08
0.40
-0.17
-7.01
-1.44
0.79
0.74
-0.61
0.64
-1.27
-3.55
1.38
1.36
3.42
2.19
1.02
2.70
-1.91
-3.83
-2.37
-4.63
23.92

-.1516623-.1606736.0091043.0232387.0216903-.0024591.8696365-.605774.3131535.1715658-.08198.0655852-.0701613-.0561661.0002686
4.71e-08.0256265.0179319.13409.2726721-.1942268-.4435682-.2662189-.4967287
7.580218.0476552.0351102.0032432.0215305.0544804.0146907.1240558.4205283.3963497.232756.134559.1029664.0551733.0158057.0001947
3.48e-08.0075015.0081993.1311509.1010077.1015637.1159108.1123392.1072219.3169641

0.001
0.000
0.005
0.281
0.691
0.867
0.000
0.150
0.430
0.461
0.542
0.524
0.204
0.000
0.168
0.175
0.001
0.029
0.307
0.007
0.056
0.000
0.018
0.000
0.000

Root MSE= 1.1803[95% Conf. Interval]-.2451106 -.058214-.2295222 -.0918251.0027446 .0154639-.0189811 .0654585-.0851418 .1285225-.0312665 .0263483-1.112901 -.6263721-1.430399 .2188511-.4640592 1.090366-.2848515 .6279832-.3458402 .1818802-.1363243 .2674947-.1783521 .0380295-.0871599 -.0251724-.0001133 .0006504-2.10e-08 1.15e-07.0109165 .0403364.0018537 .0340101-.1230873 .3912674.0746035 .4707408-.3933858 .0049322-.6708607 -.2162757-.4865078 -.04593-.7069829 -.2864744
6.958674 8.201761
20Linear regression
Number of obs = 2491 ,F( 30, 2460) = 10.80, Prob > F

ln_healthc~t
Coef.
Gender-.2671133
Age.0922843
highest_pa~d .0361001
attending_~l -.0208188
what_class.0036142
chronic_dis.8683253
immu_bcg.4803952
immu_dpt_1 -.4175006
immu_polio_1 -.0777547
immu_measles -.0870377
immu_hepat~s -.0698431
Rural-.0696968
Hhsize-.0644059
Landasset.0005092
non_landas~t -1.34e-07
fathereduc~n .0320322
mothereduc~n .0239801
Borisal.1618192
Chittagong.2843803
Dhaka-.1703866
Khulna-.4208839
Rajshahi-.2404288
Rangpur-.4718024age_gender.0157436
rural_gender .0042471
hhsize_gen~r .0066113
landasset_~r -.0001721
non_landas~r 1.39e-07
fathereduc~r -.0054505
mothereduc~r -.0045486_cons
5.748123

Std. Err.
.2020776.0302416.0230339.0536681.0148954.1246235.4200882.3954472.2364047.1324159.1024878.1713922.046263.0006125
1.01e-07.0235379.0259273.132473.1013724.1016607.1159214.1124208.1075363.0163484.1104312.0297762.0003837
6.82e-08.0149591.0163191.2062349

t
-1.32
-3.05
1.57
-0.39
0.24
6.97
1.14
-1.06
-0.33
-0.66
-0.68
-0.41
-1.39
0.83
-1.33
1.36
0.92
1.22
2.81
-1.68
-3.63
-2.14
-4.39
0.96
0.04
0.22
-0.45
2.03
-0.36
-0.28
27.87

= 0.0000, R-squared

P>t
0.186
0.002
0.117
0.698
0.808
0.000
0.253
0.291
0.742
0.511
0.496
0.684
0.164
0.406
0.184
0.174
0.355
0.222
0.005
0.094
0.000
0.033
0.000
0.336
0.969
0.824
0.654
0.042
0.716
0.780
0.000

= 0.1197, Root MSE[95% Conf.
-.663373-.151586-.0090677-.1260581-.0255946.6239475-.3433678-1.192944-.5413275-.3466958-.2708143-.4057847-.1551243-.0006919-3.31e-07-.014124-.0268615-.0979508.0855962-.369736-.6481974-.4608779-.6826734-.0163145-.2123006-.0517777-.0009245
4.85e-09-.0347841-.0365493
5.343711= 1.1804

Interval].1291465-.0329826.0812679.0844205.032823
1.112703
1.304158.3579432.385818.1726205.1311282.266391.0263124.0017102
6.35e-08.0781885.0748216.4215893.4831645.0289628-.1935703-.0199796-.2609314.0478017.2207949.0650004.0005804
2.72e-07.0238832.0274521
6.152535

21

reg ln_healthcare_cost gender age highest_passed attending_school what_class chronic_dis immu_bcg immu_dpt_1 immu_polio_1
immu_measles immu_hepatitis rural hhsize landasset non_landasset fathereducation mothereducation Borisal chittagong Dhaka Khulna
Rajshahi Rangpur,clu(uniqueid)
Linear regression
Number of obs = 2491, F( 23, 1956) = 11.42, Prob > F= 0.0000, R-squared= 0.1173, Root MSE

Robustln_healthc~t Coef.

Std. Err.

t

P>t[95% Conf.

Interval]

Gender-.1539197
Age-.0691072
highest_pa~d .0363511
attending_~l -.0205795
what_class .0031137
chronic_dis .8652634
immu_bcg.4612107
immu_dpt_1 -.4137023
immu_polio_1-.0655113
immu_measles-.0826457
immu_hepat~s-.0707316
rural-.0666589
hhsize-.0542592
landasset.0002653
non_landas~t 4.82e-08
fathereduc~n .0249245
mothereduc~n .0176718
Borisal.1448831
chittagong.2749807
Dhaka-.1821765
Khulna-.432475
Rajshahi-.2478177
Rangpur-.4881127_cons
5.707212.049308.0174076.023462.0548579.0152212.1318333.4198527.3968911.2343504.1350123.1076436.0609029.0208313.0002056
3.90e-08.0084696.0093197.152657.1221381.1219875.1360693.1281137.1245776.2037503

-3.12
-3.97
1.55
-0.38
0.20
6.56
1.10
-1.04
-0.28
-0.61
-0.66
-1.09
-2.60
1.29
1.24
2.94
1.90
0.95
2.25
-1.49
-3.18
-1.93
-3.92
28.01

0.002
0.000
0.121
0.708
0.838
0.000
0.272
0.297
0.780
0.541
0.511
0.274
0.009
0.197
0.217
0.003
0.058
0.343
0.024
0.135
0.002
0.053
0.000
0.000

-.2506215-.1032466-.009662-.1281655-.0267378.6067148-.362195-1.192076-.5251141-.3474287-.2818397-.1861002-.095113-.000138-2.83e-08.0083141-.0006058-.1545044.0354462-.4214156-.6993312-.4990715-.7324316
5.307621-.0572179-.0349679.0823643.0870065.0329652
1.123812
1.284616.3646716.3940914.1821374.1403765.0527824-.0134054.0006686
1.25e-07.0415348.0359494.4442706.5145152.0570626-.1656189.0034361-.2437938
6.106802= 1.1803

22

Summary of Findings
Econometric Results : Health care spending for female children in the household is significantly
lower than that of male children holding all other things constant; Age, chronic_dis, hhsize, nonland_asset, fathereducation, andmothereducation are very important variables in determining the healthcare spending for the children irrespective of gender; An in crease in age of the children is associated with decrease in healthcare spending of the children holding other variables constant; The health care spending for the children who have been suffering fromchronic diseases is higher than that of children who have not been
suffering from this kind of diseases keep all other variables unchanged.
Major causes of Gender discrimination:(i) Hierarchical family settings , (ii) Learning at the childhood, (iii) Negligenceof girls since birth, (iv) Women’s access to education and gender gap, (v)Women and poverty, (vi) Religious influence on women lives, (vii) Inheritanceand property rights of women (legal aspect), (viii) Labor force participation ,(ix) Health situation of women.
23

Recommendations
 To ease the health care budget of the household and everybody
should have some specific health insurance policy;
 To promote advocacy and comprehensive gender analysis on
health financing and health insurance proposal in order toaddress women’s health and family planning needs effectively;
 To ensure equal and easy access to gender responsive health andeducation services more widely; Law and order enforcing agencies along with both marriage
registrars and birth registrars should be more efficient; Women need to have easy access to education, particularly tothe higher study and comprehensive social awareness programs
need to be undertaken by the government in collaboration with
NGOs of national and international level;24

Recommendations cont.
 Mass media like electronic media, print media even social media
like facebook, YouTube, twitter etc. should come forward inorder to build mass awareness against dowry, early marriage,
son preference, and violence against women.
 Women should be given priority for human resources
development programs in order to enhance women’s skills andcapability ; Local government institutions, NGOs and community leaders
jointly can organize counseling parents on importance ofmaternal health, women’s education, bad effect of earlymarriage and dowry system;
 Documentaries, short film or commercial film based on positive
image of women can play a vital role in changing the mind set ofcommon people.
25References
Shahnaj Parveen (2007), Gender Awareness of Rural Women in Bangladesh, Journal ofInternational Women’s Studies Vol. 9 #1 November 2007
Gender Equality in Sector Wide Approaches : A Reference Guide (June 2002), Development
Assistance Committee, OECD ,World Bank, (2012), Toward Gender Equality in East Asia and the Pacific: A Companion to theWorld Development Report—Conference Edition.
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Thank you all
Questions?

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