We used a dataset series of four nationally representative PDHS (1990–91, 2006–07, 2012–13 and 2017–18). These surveys are conducted in order to gain information on mother and child health, fertility, family planning, reproductive health, and nutritional and immunisation status. So far, four standard PDHS have been conducted and data from all these surveys has been included in this research. The response rates of each PDHS of ever-married women were 6,611 (95 %) in 1990–91, 10,023 (95 %) in 2006–07, 13,558 (93 %) in 2012–13 and 15,509 (96 %) in 2017–18. The surveys used a multistage sampling procedure: at the first stage, strata were built on an urban and rural basis; from each strata, households were selected by using a simple random sampling method. Our study focused on the personal, socio-cultural, community-level and supply-side factors dealing with the use of contraceptives. Women who had given birth in the previous five years and participated in the family planning module were selected to obtain the sample for this study. The selection of women as respondents was made on the basis that almost all of the family planning programs in Pakistan have remained women-focused and they are considered the main clients for any family planning interventions. The sample from each data set is as follows: 4,092 women in 1990–91, 5,742 women in 2006–07, 7,461 women in 2012–13 and 8,219 in 2017–18 [28–31].
Instrumentation and data classification
The current use of contraceptive methods was defined as the dependent variable, including traditional (periodic abstinence [rhythm], withdrawal and abstinence) and modern methods (pill, intrauterine devices, injections, diaphragm, condom, female or male sterilisation, implants, female condom, foam/jelly and lactational amenorrhea). The reason behind combining both types of methods was that the focus of the study was to see the use and non-use of contraceptive measures rather than the types of methods being used.
Women’s socio-demographic, and demand- and supply-side factors were considered as independent variables. Women’s socio-demographic factors were: age, type of residence (urban vs. rural), region, ethnicity, education (no education, primary, secondary, higher), women’s occupation/employment status (not working, unskilled employment [sales, household domestic, unskilled manual], skilled employment [self-employed, agricultural employees, skilled manual, clerical] and professional [professional/technical/managerial services]). The wealth index of women was calculated through quintiles. Afterwards, the quintiles were categorised into three main categories (poor, middle, rich) to make it more clear and vivid for this analysis.
Among the demand-side factors, questions regarding media exposure, desire for children, number of sons living, number of daughters living, history of intimate partner violence, decisional autonomy, permission to attend medical or health facilities from male members of the family specifically husbands, as well as unwillingness to go alone and concerns about going to female health providers were included. Exposure to any source of information (TV, radio, newspaper) was computed and recoded as overall media exposure including print and electronic media, and response categories generated were “No” and “Yes”. Desire for more children was categorised into two categories: either “No” (wanted no more children, sterilised [respondent or partner]) or “Yes” (wanted within or after the next two years, unsure about timing, undecided). Intimate partner violence was part of PDHS 2012–13, in which emotional, physical and sexual violence were included. Women were asked if they had ever faced any humiliating attitude from their husband, physical violence (such as being beaten, having their arms twisted, hair pulled) or threatened with a harmful weapon (such as a knife or gun), or sexual violence from their husbands, which includes forced sex. All forms of violence were coded as binary categories and, thereafter, combined as overall violence by intimate partners as “Yes” if faced with any type of violence and “No” if not faced with violence. However, data for this variable was not available for the previous PDHS 1990–91 and 2006–07. Women’s independent or joint control of income, purchases, healthcare decisions and visits to relatives were included women’s decisional autonomy. Each variable was first coded into two categories: “Yes” if the respondent contributed to any type of decision either individually or jointly, and “No” if she did not participate in any decision-making. All types were then combined into overall autonomy as women who have any type of autonomy as “Yes” and those who do not have any autonomy as “No”. The responses to questions regarding permission to attend medical or health facilities were divided into two categories (“Big problem” and “Not a big problem”). Similarly, going alone to get medical treatment was divided into the same two categories. The number of sons living has also been taken as a variable to determine whether use of contraceptives is contingent upon son preference. It has been coded as “No living son”, “1–3”, “4–6” and “7–10”.
Among supply-side factors, the facilitation and provision of governmental and non-governmental family planning services was measured through questions about the distance to health facilities, transport availability, visits by lady health workers (LHWs), unmet needs and the availability of contraceptives through different sources. The distance to health facilities and transport availability were categorised as either “Big problem” or “Not a big problem”. The sources of family planning were first categorised into public (government hospitals, family planning clinics and LHWs), private (private hospitals, pharmacies and clinics) and others (such as shops, friends or relatives and traditional practitioners). Unmet needs included those for the spacing and limiting of births. Per definition, unmet needs relate to women who do not use any contraceptive methods, although they wish to stop or limit childbearing. From 2012–13 onwards, a revised definition has been used that includes unwanted pregnancy (in the next two years), being not sure and having postpartum amenorrhea for up to two years following an unwanted birth.
Data was analysed using SPSS version 24. Absolute numbers and weighted percentages were obtained through descriptive analysis. The purpose of weighting was to balance the data to reflect the population more accurately that can project the result of the large universe of this study. The relationship between demographic characteristics, and demand- and supply-side factors, along with current use and non-use of contraceptives was assessed through the Chi square test (X2) on categorical variables. A p-value of < 0.05 was considered statistically significant. Associations between demand- and supply-side indicators of non-use of contraceptives were measured using binary logistic regression models to present odds ratios (OR). Multivariable analysis was conducted by assessing adjusted ORs (AORs) through controlling the demographic variables (age, education, income, wealth, residence). Data on ethnicity is missing in PDHS 1990–91 and 2017–18, so it was not included in the analysis. Furthermore, several variables relating to demand-side factors (media exposure, intimate partner violence, decisional autonomy, permission to attend medical or health facilities, not wanting to go alone for medical help) and supply-side factors (distance to the health facility, transport availability, visit by a family planning worker during the previous 12 months) were not included in the questionnaire in 1990–91 or 2006–07 and, therefore, were not included in the analysis for these years.