Women Decision Making Autonomy as a Facilitating Factor for Contraceptive Use for Family Planning in Pakistan

Abstract

Pakistan is 5th most populous country in the world and striving to achieve population equilibrium. Unfortunately, one in five women in Pakistan has not been using contraceptives and thus bearing unwanted pregnancies. Female’s participation in their own matters and benefits from social, economic, and political spheres has remained very low. Gender inequality is often cited as a barrier to improving women’s sexual and reproductive health outcomes, including contraceptive use. Pakistan is ranked at 148th place out of the 149 countries in Global Gender Gap Report 2018, which indicates very high gender inequality. Keeping in view this fact, we investigated the impact of women’s decision-making autonomy on contraceptive use among married women age 15–49 years in Pakistan. Pakistan Demographic and Health Survey 2018 data has been used for analysis by using descriptive statistics, association tests, and multiple logistic regression. Women’s participation in making four household decisions: access to health care; large household purchases; what to do with the husband earning and freedom to visit family and relatives have been used as women’s decision-making autonomy. The results indicated that women’s decision-making autonomy has been positively associated with contraceptive use. Women’s age, province of residence, education level, household wealth status, number of children, time since last sex, and awareness about family planning services have also been found statistically significantly associated with contraceptive use. The current study suggests integrating the interventions for women's decision-making autonomy into family planning programs. For this purpose, the development of community-based awareness programs for women’s decision-making autonomy and contraceptive use could be useful interventions to achieve population equilibrium.

Full text

Vol.:(0123456789)
Social Indicators Research
https://doi.org/10.1007/s11205-021-02633-7
1 3
ORIGINAL RESEARCH
Women Decision Making Autonomy asaFacilitating Factor
forContraceptive Use forFamily Planning inPakistan
MuhammadNadeem1· MuhammadIrfanMalik2 · MumtazAnwar3·
SobiaKhurram4
Accepted: 1 February 2021
© The Author(s), under exclusive licence to Springer Nature B.V. part of Springer Nature 2021
Abstract
Pakistan is 5th most populous country in the world and striving to achieve population equi-
librium. Unfortunately, one in five women in Pakistan has not been using contraceptives
and thus bearing unwanted pregnancies. Female’s participation in their own matters and
benefits from social, economic, and political spheres has remained very low. Gender ine-
quality is often cited as a barrier to improving women’s sexual and reproductive health
outcomes, including contraceptive use. Pakistan is ranked at 148th place out of the 149
countries in Global Gender Gap Report 2018, which indicates very high gender inequality.
Keeping in view this fact, we investigated the impact of women’s decision-making auton-
omy on contraceptive use among married women age 15–49years in Pakistan. Pakistan
Demographic and Health Survey 2018 data has been used for analysis by using descrip-
tive statistics, association tests, and multiple logistic regression. Women’s participation in
making four household decisions: access to health care; large household purchases; what
to do with the husband earning and freedom to visit family and relatives have been used as
women’s decision-making autonomy. The results indicated that women’s decision-making
autonomy has been positively associated with contraceptive use. Women’s age, province of
residence, education level, household wealth status, number of children, time since last sex,
and awareness about family planning services have also been found statistically signifi-
cantly associated with contraceptive use. The current study suggests integrating the inter-
ventions for women’s decision-making autonomy into family planning programs. For this
purpose, the development of community-based awareness programs for women’s decision-
making autonomy and contraceptive use could be useful interventions to achieve popula-
tion equilibrium.
Keywords Women decision making autonomy· Contraceptive use· DHS· Pakistan
* Muhammad Irfan Malik
irfan.malik@ue.edu.pk
Extended author information available on the last page of the article

M.Nadeem et al.
1 3
1 Introduction
Family planning is considered as an important tool for achieving population equilibrium.
“Due to its huge socio-economic, environmental, and human rights implications, family
planning is considered an important development priority for many underdeveloped coun-
tries including Pakistan. Family planning contributes to achieving the Sustainable Devel-
opment Goals (SDGs) through healthier birth spacing and by reducing mortality and mor-
bidity associated with pregnancy”. Contraceptive use is a basic tool for family planning.
The utilization of various contraceptive methods is a key strategy to avoid complicated and
unwanted pregnancies. Among many interventions, contraceptive use to prevent unwanted
pregnancies is one of the most cost-effective ways of reducing maternal deaths (Bongaarts
and Sinding 2009).
According to the Population Reference Bureau (PRB) 2019 Family Planning Datasheet,
globally 62% of women aged 15–49 are using the contraceptive method for family planning
and 56% are using modern methods of contraception. Accordingly, these rates are high
(67% and 60% respectively) in rich countries compared to poor countries (34% and 29%
respectively) due to access, demand, and availability of family planning services. Limiting
family size in less developed countries is the urgent need of the hour as according to cur-
rent projections of world population prospects 2019 of United Nations, Least Developed
Countries (LDC’S) are growing at 2.3% annually since 2015. This growth rate is 2.5 times
faster than the rest of the world which is 1.08%.
Pakistan is 5th most populous country in the world with 207 million people and its pop-
ulation is growing at a rate of 2.4% (World Development Indicators 2018). Due to the high
population size, “Pakistan is facing a huge challenge on almost all development indicators,
particularly about maternal and child health. Failure to effectively manage the fertility rate
and rapid population growth had adverse effects on development indicators such as edu-
cation, poverty, and life expectancy, particularly for maternal and child health”. Pakistan
Demographic and Health Survey (PDHS) 2017–18 reported fertility rate per woman is 31%
higher than the desired rate. The survey reported that a woman bears an average of 3.6
children in her lifetime and the fertility rate is high that is 3.9 in rural areas as compared
to urban areas where it is 2.9. Furthermore only 34% women in Pakistan used contracep-
tion (urban = 43%, rural = 29%). The use of contraceptive methods has remained stagnant
over the past 5years (35% in PDHS, 2012–13, and 34% in PDHS 2017–18). To control the
population contraceptive use has to be increased.
Maternal autonomy in healthcare-seeking behavior is connected to women’s empower-
ment and helps to achieve desired health outcomes (Hameed etal. 2014). Moreover, “wom-
en’s health and access to reproductive resources, such as contraception, are a reflection
of women’s place in society and their ability to access social and health services, while
also reflecting disparities in economic development (WHO 2010; Eliason et al. 2014;
Fawole and Adeoye 2015). Women’s place in society is usually measured by indicators
of status and empowerment (Kabeer 1999; Malhotra etal. 2002). The health of women
and their children in many societies is adversely affected by women’s inferior social sta-
tus within households. This is mainly because of the culturally and socially determined
roles for women that pervade every aspect of their lives (Ali etal. 2010). Women in South
Asia sacrifice their desire to regulate their fertility because they are nurtured in such a way
that their family-group interest supersedes their personal desire (Ubaidur Rob 1990). An
increasing body of evidence demonstrates the ways unequal levels of power between men
and women in intimate relationships prevent women from making decisions regarding their

Women Decision Making Autonomy asaFacilitating Factor for…
1 3
sexual and reproductive health” (Senarath and Gunawardena 2009). Women empowerment
is one such characteristic that may influence a woman’s experience of pregnancy, delivery,
and postnatal care.
In Pakistan, “the patriarchal framework of society works at all levels to place women
in a more vulnerable position than men (Ali etal. 2010). Out of the 149 countries in the
World Economic Forum’s (WEF) “Global Gender Gap Report 2018”, “Pakistan only bet-
tered Yemen to be ranked at 148th place. The WEF’s report tracked disparities between
the sexes in 149 countries across four areas: education, health, economic opportunity, and
political empowerment. Pakistan ranked 146th in the economic participation and oppor-
tunity category, 139th in educational attainment, 145th in health and survival, and 97th in
political empowerment. So, to improve key maternal and reproductive-health indicators,
addressing the issue of Gender Gap” and empowering women is very much needed”. Cur-
rently, the literature on this issue is very scant (Fikree etal. 2001; Saleem and Bobak 2005;
Hameed etal. 2014), not updated and based on small and non-representative data sets. It is
now required to understand the factors affecting contraception usage in Pakistan in context
to women empowerment and other important factors based upon the most recent and coun-
try representative data set. Keeping in view this fact the current study has been an effort to
address this issue based upon the most recent and representative data set.
2 Material andMethod
This research examines the prevalence and determinants of contraceptive use in Pakistan.
“We utilized data of 11,766 married women of age 15–49years. The data was collected in
the PDHS 2017–18. The PDHS is a nationally representative household survey, undertaken
by the National Institute of Population Studies (NIPS) Pakistan,under the umbrella of the
Ministry of National Health Services, Regulations & Coordination (NHSR&C) Pakistan.
The dataset is publicly available from the NIPS website (www.nips.org.pk). Support for
the survey was also provided by the United Nations Population Fund (UNFPA), United
States Agency for International Development (USAID), ICF through DHS program, and
the Department for International Development (DFID). The details of questionnaires and
methodology have been given on the website and the key indicators report is publicly avail-
able on the NIPS website”.
The outcome variable for this study is “Contraceptive use” among currently married
women aged 15–49years, measured by women’s self-reporting response. The independent
variable of the model is women’s decision-making autonomy regarding access to health
care, large household purchase, visiting relatives and friends, use of husband earning. In
the first model, the role of the female in decision making about her health care has been
used, in the second model decision making about large household purchases, in the third
model decision making regarding visiting relatives, in the fourth model decision making
regarding what to do with the husband earning has been used and lastly, an additive index
has been used which has been generated from these four variables. The value of Cron-
bach alpha based upon these four items was 0.890. “Cronbach’s alpha is a measure used
to assess the reliability, or internal consistency, of a set of scale or test items. It ranges
from 0 to 1, If all of the scale items are entirely independent of one another then it will
be = 0; and, if all of the items have high covariance’s it approaches 1. The higher thecoef-
ficient, the more the items have shared covariance and probably measure the same underly-
ing concept. The control variables included in our model includes women’s age recorded

M.Nadeem et al.
1 3
into categories, the region” (province of residence), education level of female, household
wealth status, number of children, time since last sex, and awareness about family planning
services. These variables had been chosen from the existing literature on contraceptive use.
The definition and measurement of the variables used in this study have been provided
in Table1.
3 Statistical Analysis
This study, the use of contraceptives is an outcome variable. “The data were analyzed with
Stata14. First, data were analyzed using descriptive statistics to describe the characteris-
tics of the study participants and to report the prevalence of contraceptive use. Secondly,
the chi-square test was used to examine the individual association between the outcome
variable and the independent variables”. The variables that have a significant association
with the outcome variable were then included in the multiple logistic regression model. An
adjusted odds ratio (AOR), and p-value have been reported.
4 Descriptive Statistics
Table2 represents the distribution of the study participants concerning various socio-eco-
nomic characteristics. The age distribution of the respondents is such that the percentage of
respondents is low for the first age group. As the age moves to the higher age group the per-
centage of respondents increases, it reaches the maximum for the age group 25–29years,
later on, decreases as the age of the respondents move to a higher age group. It may be
said that age distribution is somewhat symmetric. There are around 6% of respondents
that belong to the age group 15–19years. The percentage of respondents in the age group
25–29years is around 21% which is highest, followed by the age group 30–34years hav-
ing around 19% share in the total number of respondents. In the age group of 45–49years,
there are around 10% of respondents. The second characteristic represents the region-wise
distribution of respondents. As Punjab is the most populous region so it has the highest
percentage of respondents which is around 27 percent, on similar grounds, Sindh has the
second largest percentage of respondents which is around 22 percent, followed by Khay-
bar Pakhtunkhwa (KP)with around 19 percent respondents, around 14 percent respondents
belongs to Baluchistan.
It is evident from the numbers that the majority (around 54%) of the married women
have no education at all. Around 14% of married women have a primary level of education,
which together with no education makes around 67% of the total respondents. The percent-
age of married women with a secondary level of education is around 19% of total respond-
ents. There are only around 14% of married women who have a higher level of education.
The next one is the distribution of respondents by household wealth status. Married women
aged 15 to 49years old are evenly distributed across the wealth index, with approximately
a fifth of women in each wealth status group. The percentage of married women who are
not currently using contraceptives is quite high which is around 68%. The next one is the
awareness level of females regarding family planning through T.V. It shows that around 80
percent of the respondents have no awareness regarding family planning.
The seventh characteristic represents the respondent’s health care decision mak-
ing autonomy. The level of married women’s autonomy is quite low as only around 9%

Women Decision Making Autonomy asaFacilitating Factor for…
1 3
Table 1 Variable description
Variable Definition and measurement
Contraceptive use Is the self-reporting response of currently married
women aged 15–49years about the use of contra-
ceptive (traditional or modern method). Which has
a ‘Yes/No’ response, and the value of ‘1 was given
if the respondent is currently using contraceptives
and the value of ‘0 was given if she is not using
Age Self-reported age of women at the time of the
survey, grouped into 15–19years; 20–24years;
25–29years; 30–34years; 35–39years;
40–44years and 45–49years
Region The provincial residence of the respondent at the time
of the survey: Punjab 1; Sindh 2; Khaybar Pakh-
tunkhwa, 3; Baluchistan 4; ICT a 5; FATA b 6
Education The highest level of education attained by the
respondent was collected as No Education, Primary,
Secondary, and Higher
Household wealth status A composite index of household possessions, assets,
and amenities, derived using principal component
analysis, grouped as Poorest; Poorer; Middle;
Richer and Richest
Number of children The total number of children ever born at the time of
the survey
Time since last sex Number of days from the date of the survey since the
respondent female has sexual activity
Job status The respondent self-reported response, if she is
currently on the paid job she is considered to be
employed and the variable takes the value 1, 0
otherwise
Awareness about family planning services The respondent self-reported response to whether she
heard about family planning services for the last
few months. If the response has been yes then this
variable is assigned the value = 1, in case of no it
has been assigned = 0
Decision-making autonomy about access to health
care
Women’s self-reported autonomy in decision making
regarding her health care measured from women’s
participation (alone or with husband) in deciding
to access the health care services. If she herself
decides or decides with the consultation of her
husband then this variable is assigned the value = 1,
on the other hand, if others (her husband alone,
someone else, and others) decide then this variable
is assigned the value = 0
Decision-making Autonomy about large household
purchases
Women’s self-reported autonomy in decision making
regarding large household purchases measured from
women’s participation (alone or with husband) in
deciding on purchases the large household items. If
she herself decides or decides with the consultation
of her husband then this variable is assigned the
value = 1, on the other hand, if this decision is made
by others (her husband alone, someone else, and
others) then this variable is assigned the value = 0

M.Nadeem et al.
1 3
of married women decide on their own regarding their health care, around 37% decides
about their health care in consultation with their husband. It indicates that around 44%
of married women are not part of decision making regarding their own health care. The
level of married women’s autonomy is even lower (around 5%) in case of deciding about
large household purchases. The percentage of married women who decide together with
their husband/partner about large household purchases is around 35%. Deciding alone and
together with her husband/partner cumulatively makes around 40%. It means that 60% per-
cent of married women are not involved at all in deciding about large household purchases.
Similar is the case for household decision making to visit the family and friend. The data
depicts that only around 9% of married women alone decide about visits to family or rela-
tives, while around 36% of married women decide together with her husband/partner about
visits to family or relatives. Deciding alone and together with her husband/partner cumu-
latively makes around 44%. It means that 56% of married women are not involved at all in
deciding visits to family or relatives. The married women’s decision-making autonomy is
further low in case of decision making in the household regarding what to do with husband
Table 1 (continued)
Variable Definition and measurement
Decision-making autonomy about visiting relatives
and friends
Women’s self-reported autonomy in decision making
regarding visiting the relatives and friends, meas-
ured from women’s participation (alone or with
husband) in deciding to visit relatives or friends. If
she herself decides or decides with the consultation
of her husband then this variable is assigned the
value = 1, on the other hand, if this decision is made
by others (her husband alone, someone else, and
others) then this variable is assigned the value = 0
Decision-making autonomy about use of husband
earnings
Women’s self-reported autonomy in decision making
regarding the use of husband earnings, measured
from women’s participation (alone or with husband)
in making the decision what to do with husband
earnings. If she herself decides or decides with
the consultation of her husband then this variable
is assigned the value = 1, on the other hand, if this
decision is made by others (her husband alone,
others, her husband have no earnings and her
family members) then this variable is assigned the
value = 0
Decision-making autonomy index A composite variable measured from women’s par-
ticipation (alone or with husband) in making four
household decisions (access to health care; large
household purchases; what to do with husband
earning and freedom to visit families and relatives).
It ranges from 0 to 4, o means no participation
at all, 1 indicates participation in one dimension,
2 indicates participation in two dimensions, 3
indicates participation in three dimensions and 4
indicates participation in all four dimensions. The
value of Cronbach alpha based on four dimensions
has been 0.890
a Islamabad Capital Territory;
b Federally Administrative Trible Areas

Women Decision Making Autonomy asaFacilitating Factor for…
1 3
Table 2 Descriptive statistics
Variable Classification /response Frequency Percentage
Age 15–19 649 6
20–24 1821 15
25–29 2517 21
30–34 2222 19
35–39 2090 18
40–44 1341 11
45–49 1126 10
Region Punjab 3174 27
Sindh 2600 22
Khaybar Pakhtunkhwa 2291 19
Baluchistan 1660 14
ICT 1059 9
FATA 982 8
Level of education No education 6322 54
Primary 1612 14
Secondary 2216 19
Higher 1616 14
Household wealth status Poorest 2291 19
Poorer 2306 20
Middle 2200 19
Richer 2324 20
Richest 2645 22
Contraceptive use Yes 3792 32
No 7974 68
Family planning awareness through TV Yes 2420 21
No 9346 79
The person who usually decides on the respondent’s health care Respondent alone 1009 9

M.Nadeem et al.
1 3
Table 2 (continued)
Variable Classification /response Frequency Percentage
Respondent and husband/partner 4393 37
Husband/partner alone 4900 42
Someone else 1131 10
Other 333 3
The person who usually decides on large household purchases Respondent alone 625 5
Respondent and husband/partner 4073 35
Husband/partner alone 4666 40
Someone else 1873 16
Other 529 5
The person who usually decides on visits to family or relatives Respondent alone 1026 9
Respondent and husband/partner 4179 36
Husband/partner alone 4558 39
Someone else 1610 14
Other 393 3
The person who usually decides what to do with money husband earns Respondent alone 701 6
Respondent and husband/partner 4150 35
Husband/partner alone 5272 45
Other 17 0
Husband/partner has no earnings 359 3
Family members 1267 11
Jobs status Yes 1511 13
No 10,255 87

Women Decision Making Autonomy asaFacilitating Factor for…
1 3
earnings. Only 6% of married women alone decide about what to do with husband earn-
ings, around 35% of married women decide together with their husband/partner about what
to do with husband earnings. Deciding alone and together with her husband/partner cumu-
latively makes around 41%. It means that around 59% of married women are not involved
at all in deciding about what to do with husband earnings. The last one represents the
job status of married women and it is evident from the table that around 87% of married
women are not on jobs.
The percentage of women in each category of decision-making autonomy index with
respect to each age group has been provided in Table3. It is important to note that these
categories are mutually exclusive. The results indicate that amongst married women of the
age group of 15–19years, 73 percent have autonomy in neither of the dimension, 9 percent
have autonomy only in one dimension, 5 percent have autonomy in two and three dimen-
sions, and 9 percent have autonomy in all four dimensions. Likewise, there is 56 percent
of women in the age group 20–24years that have autonomy in neither of the dimension,
14 percent of women of this age group have autonomy in only one dimension, 8 percent
of the women of this age group have autonomy in two dimensions, 6 percent have auton-
omy in three dimensions and 16 percent of women of this age group have autonomy in all
four dimensions. It is pertinent to note that overall autonomy increases with an increase
in the age of married women, for example, in the age group of 15–19years, 73% have no
autonomy at all whereas, only 26% of women in the age group of 45–49 has no autonomy
at all. On the other side, only 9 percent of the married women of age group 15–19years
have autonomy in all four dimensions and it increased to 43 percent for the age group
45–49years.
It may be due to the reason that at the early years of marriage, most of the couple lives
with their elders in the joint family system and most of the decision are taken by the elders.
The results of association tests are reported in Table4. It is observed that variable con-
traceptive use has a significant association with Age, Region, Education, Wealth Status,
Awareness of Family Planning, various dimensions of women empowerment, overall
women empowerment index, and Job-status of women. In further analysis, we analyze the
effect of these variables on our outcome variable i.e. contraceptive use.
Table 3 Decision-making
autonomy index and female age Age Decision-making autonomy index (%)
01234
15–19 73 9 5 5 9
20–24 56 14 8 6 16
25–29 47 12 7 8 25
30–34 38 12 8 11 30
35–39 34 11 10 11 33
40–44 29 10 11 13 37
45–49 26 10 9 13 43

M.Nadeem et al.
1 3
5 Regression Analysis
The dependent variable contraceptive use is categorical with two categories i.e. “yes (1)
or no (0). When the dependent variable is categorical and has two values then the suitable
technique for the estimation is Logistic regression.
Logistic regression analysis studies the association between a categorical dependent
variable and a set of independent (explanatory) variables.
Let
pi
is the probability of contraceptive use, the model can be written as
“The above model is a simple model with one independent variable. Here Pi is the prob-
ability of contraceptive use, and for example if we consider xi is a residence (rural/urban)
of the respondent. When xi = 1 (urban) β1 shows the log of odds of rural women being
using contraceptives. We can write the model in terms of odds as”:
pi=pr
(
y=
1
x=xi)
log 
p
1−pi 
=log it

pi

=𝛽0+𝛽ix
i
p
i
(
1−p
i)
=exp
(
𝛽0+𝛽ixi
)
Table 4 Association between
contraceptive use and
socioeconomic variables
Contraceptive use
Variable
𝜒2
−
value
P-Value
Age 581 0.000
Region 340 0.000
Education 282 0.000
Household wealth status 524 0.000
Awareness of family planning services 133 0.000
Job status 22 0.000
Time since last sex 425 0.000
Number of children ever born 1300 0.000
Empowerment regarding health care 126 0.000
Empowerment regarding household
purchases
171 0.000
Empowerment regarding the visit to
family
188 0.000
Empowerment regarding what to do
with the husband earning
159 0.000
Women empowerment overall index 227 0.000

Women Decision Making Autonomy asaFacilitating Factor for…
1 3
Or in terms of the probability of the outcome (e.g. being a user of contraceptive) occur-
ring as:
Conversely, the probability of the outcome not occurring (e.g. being not user) is
Notice that we have so far not included a residual term in the models and have instead
expressed the model in terms of population probabilities. But we could write it as:
It may be kept in mind that fi is not normally distributed, and it is assumed that it was
linear regression.
The results of the regression analysis are given in Table5. We estimated five models by
using different proxies of women’s decision-making autonomy. In the first model, the role
of married women in decision making about her health care has been used, in the second
model decision making about large household purchases, in the third model” decision mak-
ing regarding visiting the relatives, in the fourth model decision making regarding what to
do with the husband earning has been used, lastly, an index has been used which has been
generated from these variables. “Decisions on daily household purchases are indicative of
women’s influence over routine household activities, while decisions on large household
purchases are indicative of decision-making with a partner. Furthermore, visits to relatives
suggest influence over women’s social life. Finally, women’s participation in health care
decisions is the most likely indicator of women’s health care decision-making”.
The first model represents the result of married women’s decision-making autonomy
about her health care and contraceptive use. The base category of this variable is the deci-
sion about her health care is taken by others. The odds ratio associated with women’ deci-
sion making autonomy (when she decides or she decides in consultation with her husband)
is 1.15, it means that she is 1.15 times more likely to use contraceptive when she herself
decides or she decides in consultation with her husband regarding her health care as com-
pared to when others decide about her health care. So, if the women have decision making
autonomy about her health care, she is most likely to use contraceptives.
In the second model, the decision making about large household purchases has been
used. If she herself decides or in consultation with her husband decides about the large
household purchases then she is autonomous and if others decide it, then she is considered
not to be autonomous. The timing and number of times to get pregnant is a big household
decision. If she has autonomy for large household purchases it may indicate that she may
also have the autonomy to decide when to get pregnant and how many children, she wants
to have. The odds ratio associated with this variable is 1.21 and the base category for this
variable is married women have no autonomy (the decision is made by others). It indicates
that if a woman has autonomy, she is 1.21 times more likely to use a contraceptive. It is
consistent with the results of the previous model.
In the third model, the decision-making autonomy regarding visiting relatives and
friends has been used. If she herself decides or in consultation with her husband decides
about visiting relatives and friends then she is considered to be autonomous and if others
decide it, then she is considered not to be autonomous. The odds ratio associated with this
variable is 1.22 and the base category for this variable is women have no autonomy (the
p
i
=exp
(
𝛽
0
+𝛽
i
x
i)
∕
(
1+exp
(
𝛽
0
+𝛽
i
x
i))
1
−p
i
=1∕(1+exp
(
𝛽
0
+𝛽
i
x
i
)
)
Pi
=p
i
+f
i
=exp
(
𝛽
0
+𝛽
i
x
i)
∕
(
1+exp
(
𝛽
0
+𝛽
i
x
i))
+f
i

M.Nadeem et al.
1 3
Table 5 Regression results (Dependent variable = Contraceptive use)
Variable Model: 1 Model: 2 Model: 3 Model: 4 Model: 5
Decision-making autonomy about health care
Decided by other (Base category) 1.000
Herself or both 1.158***
(0.002)
Decision-making autonomy about household purchases
Decided by Other (Base category) 1.000
Herself or both 1.211***
(0.000)
Decision-making autonomy to visit relatives and friends
Decided by other (Base category) 1.000
Herself or both 1.229***
(0.000)
Decision-making autonomy about husband earning
Decided by other (Base category) 1.000
Herself or both 1.214***
(0.000)
Decision-making autonomy index
No autonomy at all (Base category) 1.000
Autonomy in one dimension 1.122
(0.130)
Autonomy in two dimensions 1.197**
(0.036)
Autonomy in three dimensions 1.277***
(0.002)
Autonomy in all four dimensions 1.307***
(0.000)
Age
15–19 (Base category) 1.000 1.000 1.000 1.000 1.000
20–24 1.646*** 1.647*** 1.637*** 1.652*** 1.631***
(0.002) (0.002) (0.000) 0.002 (0.002)
25–29 2.049*** 2.038*** 2.019*** 2.056*** 2.009***
(0.000) (0.000) (0.000) (0.000) (0.000)
30–34 2.402*** 2.372*** 2.346*** 2.404*** 2.327***
(0.000) (0.000) (0.000) (0.000) (0.000)
35–39 2.148*** 2.118*** 2.089*** 2.142*** 2.068***
(0.000) (0.000) (0.000) (0.000) (0.000)
40–44 1.959*** 1.919*** 1.899*** 1.954*** 1.871***
(0.000) (0.000) (0.000) (0.000) (0.000)
45–49 1.232 1.203 1.188*** 1.229*** 1.172
(0.240) (0.298) (0.000) (0.000) (0.371)
Region
Baluchistan (Base category) 1.000 1.000 1.00 1.000 1.000
Punjab 3.490*** 3.471*** 3.429*** 3.401*** 3.393***
(0.000) (0.000) (0.000) (0.000) (0.000)

Women Decision Making Autonomy asaFacilitating Factor for…
1 3
decision is made by others). It indicates that if a woman has autonomy, she is 1.22 times
more likely to use a contraceptive. It is consistent with the results of the previous model.
In the fourth model, the decision-making autonomy regarding what to do with the
earning of the husband has been used. If she decides or in consultation with her husband
Table 5 (continued)
Variable Model: 1 Model: 2 Model: 3 Model: 4 Model: 5
Sindh 2.804*** 2.777** 2.709*** 2.716*** 2.699***
(0.000) (0.000) (0.000) (0.000) (0.000)
Khaybar Pakhtunkhwa 2.797*** 2.80*** 2.767*** 2.769*** 2.802***
(0.000) (0.000) (0.000) (0.000) (0.000)
ICT 3.545*** 3.528*** 3.469*** 3.478*** 3.437***
(0.000) (0.000) (0.000) (0.000) (0.000)
FATA 2.297*** 2.320*** 2.313*** 2.272*** 2.351***
(0.000) (0.000) (0.000) (0.000) (0.000)
Education level
No education (Base category) 1.000 1.000 1.000 1.000 1.000
Primary 1.380*** 1.375*** 1.379*** 1.381*** 1.373***
(0.000) (0.000) (0.000) (0.000) (0.000)
Secondary 1.600*** 1.594*** 1.593*** 1.602*** 1.585***
(0.000) (0.000) (0.000) (0.000) (0.000)
Higher 1.726*** 1.714*** 1.717*** 1.729*** 1.701***
(0.000) (0.000) (0.000) (0.000) (0.000)
Householdwealth status
Poorest (Base category) 1.000 1.000 1.000 1.000 1.000
Poorer 2.114*** 2.103*** 2.110*** 2.108*** 2.099***
(0.000) 0.000 (0.000) (0.000) (0.000)
Middle 3.109*** 3.095*** 3.107*** 3.104*** 3.087***
(0.000) (0.000) (0.000) (0.000) (0.000)
Richer 3.538*** 3.531*** 3.539*** 3.533*** 3.52***
(0.000) (0.000) (0.000) (0.000) (0.000)
Richest 4.330*** 4.346*** 4.324*** 4.342*** 4.314***
(0.000) (0.000) (0.000) (0.000) (0.000)
Number of children 1.408*** 1.408*** 1.409*** 1.407*** 1.409***
(0.000) (0.000) (0.000) (0.000) (0.000)
Time since last sex 0.955*** 0.955*** 0.955*** 0.955*** 0.955***
(0.000) (0.000) (0.000) (0.000) (0.000)
FP awareness 1.116** 1.112* 1.111* 1.116** 1.106*
(0.050) (0.058) (0.060) (0.049) (0.072)
Job status 1.186** 1.178** 1.184** 1.177** 1.167**
(0.011) (0.015) (0.012) (0.015) (0.022)
Constant 0.012*** 0.012*** 0.012*** 0.012*** 0.012***
(0.000) (0.000) (0.000) (0.000) (0.000)
Pseudo r-squared 0.179 0.179 0.179 0.179 0.179
Number of observations 11,766 11,766 11,766 11,766 11,766
***p < 0.01,**p < 0.05,*p < 0.1; P-values are given in the parenthesis

M.Nadeem et al.
1 3
decides about what to do with the earning of her husband then she is autonomous and if
others decide it, then she is considered not to be autonomous. The odds ratio associated
with this variable is 1.21 and the base category for this variable is women who have no
autonomy (the decision is made by others). It indicates that if a woman has autonomy, she
is 1.21 times more likely to use a contraceptive. It is consistent with the results of the pre-
vious model.
In the final model women’s autonomy has been measured by the women’s autonomy
index which has been constructed from four variables that have been previously used
(decision about: health care, large household purchases, visiting relatives, what to do with
the husband earning). This index ranges from 0 to 4, 0 indicates no autonomy in all four
dimensions, 1 indicates autonomy only in one dimension and similarly, 4 indicates auton-
omy in all four dimensions. The results indicate that as the level of autonomy increases
from 1 to 4, the odds ratios associated with them also kept on increasing, the base category
is no autonomy at all (0). The odds ratio associated with 1 is 1.12but it is statistically insig-
nificant. The odds ratio associated with index value 2 is 1.20, it means that if a woman has
autonomy in two dimensions, she is 1.20 times more likely to use contraceptive as com-
pared to a female who has autonomy in neither of the dimension. The odds ratio associated
with index value 3 is 1.28, it means that if a woman has autonomy in three dimensions, she
is 1.28 times more likely to use contraceptive as compared to a female who has autonomy
in neither of the dimension. The odds ratio associated with index value 4 is 1.31, it means
that if a woman has autonomy in all four given dimensions, she is 1.31 times more likely to
use contraceptive as compared to a woman who is not autonomous in any dimension.
Decision-making autonomy has been found as one of the most facilitating factors for
contraception use. Women’s final say in decisions regarding day-to-day household matters
leads to women’s decision-making autonomy for wanting no more children, having a small
family size, and even using contraception. Many women with issues of health care chal-
lenges experience gendered power inequalities, especially in their intimate relationships,
that prevent them from achieving optimal sexual and reproductive health benefits and using
contraceptives. The finding of the study is consistent with the existing literature, see for
example (Fawole and Adeoye 2015; Woldemicael 2009; Senarath and Gunawardena 2009;
Robinson etal. 2017).
After women’s autonomy, the next variable is women’s age, which is given in age
groups of five-year intervals from 15 to 49. The base category of age used in logistic
regression analysis is the 15–19years group. The results of the first model indicate that the
odds ratio associated with the age group 20–24years is 1.64 and it is statistically signifi-
cant as well. It means that the married women of the age group 20–24years are 1.64 times
more likely to use contraceptives as compared to females of age group 15–19. Likewise,
married women of the age group 25–29years are 2 times more likely to use contraceptives
as compared to married women of age group 15–19. Similarly: the married women of age
group 30–34years are 2.4 times more likely to use contraceptives as compared to married
women of age group 15–19, the married women of age group 35–39years are 2.14 times
more likely to use contraceptives as compared to married women of age group 15–19, the
married women of age group 40–44 years are 1.95 times more likely to use contracep-
tives as compared to married women of age group 15–19, the married women of age group
45–49years are not statistically significant. The results of various age groups are as per
expectations, the contraceptive use keeps on rising till the age group 30–34years, after-
ward it decreases and becomes insignificant for the age group 45–49years. It is highest for
the age group 30–34years, it may be due to the reason that it is the age group where cou-
ples need contraceptive use for limiting or spacing as they are most likely to have children

Women Decision Making Autonomy asaFacilitating Factor for…
1 3
at this stage of life and at the age group 45–49years married women are very less fertile
and use of contraceptive does not matter significantly. This variable has quite a similar
magnitude and level of significance of odds ratios in the rest of the models. The findings of
the study are consistent with the existing literature which suggests that contraceptive use is
higher for women who are of more reproductive age. (Islam etal. 2016) found that women
in the age group 25–34years used contraceptives considerably more than that of younger
and older counterparts, likewise (Tehrani etal. 2001) found higher contraceptive use for
the age group 21–35years.
The next variable is the region, the base category for the region is Baluchistan. The
results of the first model indicate that the odds ratios of all regions are statistically sig-
nificant. The odds ratio associated with married women residing in the Punjab region is
3.49, which means that the married women of Punjab are 3.49 times more likely to use
contraceptives as compared to women in Baluchistan. The odds ratio associated with mar-
ried women residing in the Sindh region is 2.80, which means that the married women of
Sindh are 2.80 times more likely to use contraceptives as compared to married women in
Baluchistan. The odds ratio associated with married women residing in the KP region is
2.79, which means that the married women of KP are 2.79 times more likely to use con-
traceptives as compared to married women in Baluchistan. The odds ratio associated with
married women residing in the ICT region is 3.54, which means that the married women
of ICT are 3.54 times more likely to use contraceptives as compared to married women in
Baluchistan. The odds ratio associated with married women residing in the FATA region is
2.29, which means that the married women of FATA are 2.29 times more likely to use con-
traceptives as compared to married women in Baluchistan. This variable has quite a similar
magnitude and level of significance of odds ratios in the rest of the models. The regional
variation is as per the cultural and socio-economic conditions of the regions. The use of
contraceptives is higher in all regions as compared to Baluchistan, it may be due to the rea-
son that Baluchistan is the most deprived region and culturally women have no much say
in the society, whereas ICT is the most modern region and women are quite independent
in this region. The existing literature also suggests that there can be a regional variation in
contraceptive use based upon various socio-economic conditions for example see (Islam
etal. 2016).
The next variable is the education level of married women, the base category for edu-
cation is married women have no education at all. The results of the first model indicate
that the odds ratios of all education levels are statistically significant, and the odds ratio
increases as the level of education increases. The odds ratio associated with females having
education level up to primary is 1.38, it means that the married women with primary level
education are 1.38 times more likely to use contraceptives as compared to married women
with no education. The odds ratio associated with married women having education level
up to secondary is 1.60, it means that the married women with secondary level education
are 1.60 times more likely to use contraceptives as compared to married women with no
education. The odds ratio associated with married women having an education level up to
higher is 1.72, it means that the married women with higher-level education are 1.72 times
more likely to use contraceptives as compared to married women with no education. This
variable has quite a similar magnitude and level of significance of odds ratios in the rest of
the models. The results are consistent as per expectation due to the reason that as the level
of education increases it gives confidence and exposure to the women. Education helps
to make her self-sufficient and she can make decisions. Education leads to a feeling of
self-worth and self-confidence; such feelings are essential for changing health behavior and
opting for family planning services. Furthermore, education also increases the discussion

M.Nadeem et al.
1 3
between wife and husband, between women and health care providers thereby increasing
the chances of using family planning services. The findings of the study are consistent with
(Sado etal. 2014; Furuta and Salway 2006; Fayehun etal. 2011).
The next variable is the wealth status of the household; the base category is married
women belong to the poorest households. The results indicate that the odds ratios of all
levels of wealth status are statistically significant and the odds ratios increase as the level
of wealth status increases. The odds ratio associated with married women of the poorer
household is 2.11, which means that the married women of poorer households are 2.11
times more likely to use contraceptives as compared to married women of poorest house-
holds. The odds ratio associated with married women of the middle household depicts
that married women of middle households are 3.1 times more likely to use contraceptives
as compared to married women belongs to the base category. The odds ratio associated
with married women of the richer household is 3.53, it means that the married women of
richer households are 3.53 times more likely to use contraceptives as compared to mar-
ried women of poorest households. The odds ratio associated with married women of the
richest household shows that women from richest households are 4.33 times more likely to
use contraceptives as compared to women of poorest households. This variable has quite
a similar magnitude and level of significance of odds ratios in the rest of the models. The
household wealth status increases the use of contraceptives because the provision of con-
traceptives is not free of cost. Married women belonging to poor households may not be
able to avail of family planning services. This finding is consistent with the various exist-
ing studies available in the literature, for example (Haider and Sharma 2013; Woldemicael
and Beaujot 2011; Wulifan etal. 2017).
The next variable is the number of children and the odds ratio associated with this varia-
ble is 1.40. It means that, with an increase in the number of one child of a married woman,
she is 1.40 times more likely to use a contraceptive. Finding is consistent with (Islam etal.
2016). This variable has quite a similar magnitude and level of significance of odds ratios
in the rest of the models. The next variable is the time since the last sex, the odds ratio
associated with this variable is 0.95. It means that if there is an increase in the time since
the last sex, she is in less need of contraceptives. This variable has quite a similar magni-
tude and level of significance of odds ratios in the rest of the models. The next variable is
awareness about family planning and the odds ratio associated with this variable is 1.11,
which means that if a female is aware of family planning services, then she is 1.11 times
more likely to use a contraceptive. This finding is well-aligned with previous studies that
found that women who were exposed to family planning information in the media, such
as television, were more likely to be using contraception compared to those who were not
(Awusabo-Asare etal. 2004; Chima and Alawode 2019; Rutaremwa etal. 2015; Stephen-
son etal. 2007). Lastly, the job status of the female is also statistically significant, and the
odds ratio associated with this variable is 1.18, which means that if the female is on job
(working lady) then she is 1.18 times more likely to use a contraceptive. It may be due to
the reason that the opportunity cost of childbearing may be very high for employed mar-
ried women. This variable has quite a similar magnitude and level of significance of odds
ratios in the rest of the models.

Women Decision Making Autonomy asaFacilitating Factor for…
1 3
6 Conclusion
Pakistan is 5th most populous country in the world and striving to achieve population
equilibrium.
“Due to the high population size, Pakistan is facing a huge challenge on almost all
development indicators, particularly about maternal and child health. Failure to effectively
manage the fertility rate and rapid population growth had adverse effects on development
indicators such as education, poverty, and life expectancy, particularly for maternal and
child health. Unfortunately, one in five women in Pakistan are not using contraceptives
and thus bearing unwanted pregnancies. Pakistan Demographic Survey (PDHS) 2017–18
reported 3.8 fertility rates per woman that are 31% higher than the desired rate. Further-
more, only 34% of women in Pakistan used contraception. Female’s participation in their
own matters and benefits from social, economic, and political spheres is very low. Gender
inequality is often cited as a barrier to improving women’s sexual and reproductive health
outcomes, including contraceptive use. Pakistan is ranked at 148th place out of the 149
countries in Global Gender Gap Report 2018, which indicates very high gender inequality.
Keeping in view this fact, we investigated the impact of women’s decision-making auton-
omy on contraceptive use among married women in Pakistan.
Pakistan Demographic and Health Survey 2018 data has been used for analysis by using
descriptive statistics, association tests, and multiple logistic regression. Women’s participa-
tion in making four household decisions: access to health care; large household purchases;
what to do with the husband earning and freedom to visit family and relatives have been
used as women’s decision-making autonomy. Furthermore, a composite women decision-
making autonomy index has been developed from these four items, the value of Cronbach
alpha was 0.890. The results indicated that women’s involvement in household decision
making has been positively associated with contraceptive use. Control variables: women’s
age recorded into categories, the region” (province of residence), education level of female,
wealth status, number of children, time since last sex, and awareness about family planning
services were also statistically significantly associated with contraceptive use. It may be
concluded that to increase contraceptive use there is a need to improve married women’s
decision-making autonomy. To increase the married women’s decision-making autonomy,
there is a need to integrate the interventions for women’s decision-making autonomy into
family planning programs. For this purpose, the development of community-based aware-
ness programs for women’s decision-making autonomy and contraceptive use could be
useful interventions to achieve population equilibrium.
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Authors and Aliations
MuhammadNadeem1· MuhammadIrfanMalik2 · MumtazAnwar3·
SobiaKhurram4
Muhammad Nadeem
mnadeem.eco@gmail.com
Mumtaz Anwar
mumtaz.anwar@pu.edu.pk
Sobia Khurram
sobia.ias@pu.edu.pk
1 Planning andDevelopment Department, Punjab Economic Research Institute, Government
ofthePunjab Lahore, Lahore, Pakistan
2 Department ofEconomics andBusiness Administration, University ofEducation, Lahore
(Faisalabad Campus), Faisalabad, Pakistan
3 Department ofEconomics, University ofthePunjab, Lahore, Pakistan
4 Institute ofAdministrative Sciences, University ofthePunjab, Lahore, Pakistan