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. 2023 Aug 9;23:418. doi: 10.1186/s12905-023-02587-7

Examining the influence of Mother-in-law on family planning use in South Asia: insights from Bangladesh, India, Nepal, and Pakistan

Manas Ranjan Pradhan 1, Sourav Mondal 1,✉
PMCID: PMC10410985  PMID: 37553598

Abstract

Background

Contraceptive use contributes to improved maternal and child health, education, empowerment of women, slow population growth, and economic development. The role of the family in influencing women’s health and health-seeking behavior is undergoing significant changes, owing to higher education, media exposure, and numerous government initiatives, in addition to women’s enhanced agency across South Asia. Against this backdrop, this study assesses the relationship between women’s living arrangements and contraceptive methods used in selected south Asian countries (India, Pakistan, Nepal, and Bangladesh).

Methods

Data of currently married women aged 15–49 from the recent round of Demographic and Health Survey (DHS) of four South Asian countries, i.e., Nepal (2016), Pakistan (2017–18), Bangladesh (2017–18), and India (2019–21) had been used. Bivariate and multinomial logistic regression was performed using Stata with a 5% significance level.

Results

Living arrangement of women had a significant association with contraceptive use in South Asia. The Mother-in-law (MIL) influenced the contraceptive method used by the Daughter-in-law (DIL), albeit a country-specific method choice. Modern limiting methods were significantly higher among women living with MIL in India. The use of the modern spacing method was considerably high among women co-residing with husband and/or unmarried child(ren) and MIL in Nepal and India. In Bangladesh, women living with husband and other family member including MIL were more likely to use modern spacing methods.. Women co-residing with the MIL had a higher likelihood of using any traditional contraceptive method in India.

Conclusions

The study suggests family planning program to cover MIL for enhancing their understanding on the benefits of contraceptive use and modifying norms around fertility. Strengthening the interaction between the grassroots level health workers and the MIL, enhancing social network of DIL may help informed choice and enhance the use of modern spacing methods. Women’s family planning demands met with modern contraception, and informed contraceptive choices, must also be achieved to reach the 2030 Agenda for Sustainable Development.

Keywords: Family planning, Mother-in-law, Daughter-in-law, Co-residence, South Asia

Background

Contraceptive use contributes to improved maternal and child health, education, empowerment of women, slow population growth, and economic development [1, 2]. Nevertheless, in South Asia, the use of modern contraception is still deficient, with an overall median contraceptive prevalence rate (CPR) of 37%. The unmet need for contraception is as high as 12% in the South Asian region [3]. Several dimensions of factors, i.e., individual characteristics (education, economic status, race, ethnicity, place of residence, religion, occupation), demographic factors (age, sex, parity), relationship characteristics (partnership types, communication, attitude), family or household characteristics (family structure, co-residence, household economy, division of labor), and community characteristics (cultural, social and political context) affect the sexual health of women including family planning [4]. Recent literature suggests that women’s age, education, place of residence, and region are the significant determinants of contraceptive use in Bangladesh, India, Nepal, and Pakistan [5–8]. Women’s occupation, body mass index, breastfeeding practice, husband’s education, wish for children, sexual activity in the past year, abstaining status, the number of children born in the last 5 years, and the total number of children ever died are significantly associated with contraceptive use in Bangladesh [5]. Social groups and the number of surviving sons are crucial factors of contraception use in India [8]. A strong positive impact of spousal communication on contraceptive use is found in Nepal [9]. The economic condition of women has been identified as a significant determinant of contraceptive use in India and Pakistan [6, 8].

Several studies have explored the individual determinants of contraceptive use, but very few have attempted to understand the relationship of contraceptive use with women’s living arrangements. The presence of a modern contraceptive user in the household positively influences the use of modern contraceptives among young married women [10]. The presence of mother-in-law (MIL) is found to be a significant influencer of contraceptive use of daughter-in-law (DIL) in South Asia [11]. Country-specific studies also indicate the contributory role of MIL in the reproductive health of the DIL, including contraception, such as in India [12–14], Pakistan [15, 16], Nepal [17] and Bangladesh [18]. In India, the MIL influences the modern-limiting method of contraception use of DIL but not of the modern spacing method of contraception use [13]. In Bangladesh, contraceptive use is high for a DIL with a MIL who supports contraceptive use [19].

The MIL influences DIL’s use of contraception sometimes directly, sometimes indirectly through her son [20] and sometimes by controlling the mobility [21] of DIL as well as restricting her from creating any peer group [12]. There again exist contradictory results in respect of modern contraceptive use of DIL by the presence or absence of MIL; some studies found the latter as a barrier [22] and some as a facilitator [13, 16, 23]. However, most of these past studies are (a) based on relatively smaller sample sizes, (b) do not represent the national scenario (c) focus only on modern methods without segregating limiting and spacing methods. South Asian societies are witnessing changes, as evident in the increased female education and work participation in secondary or tertiary sectors, the rise of youth culture that shapes the experience of new intimacies, amendments, and the enactment of new laws aimed at women empowerment [24]. Therefore, South Asia’s patriarchal family system is also compelled to adjust its norms and values. The role of the family in influencing women’s health and health-seeking behavior is, thus, undergoing significant changes, owing to higher education, media exposure, and numerous government initiatives, in addition to women’s enhanced agency across South Asia [24–26]. Against this backdrop, this study assesses the relationship between women’s living arrangements and contraceptive methods used in selected south Asian countries-India, Pakistan, Nepal, and Bangladesh.

Methods

Data

The most recent Demographic and Health Survey (DHS) data for four selected countries, i.e., Nepal (2016), Pakistan (2017–18), Bangladesh (2017–18), and India (2019–21), were used for the analysis. DHSs are nationally representative large-scale cross-sectional surveys that provide data on various health indicators, including contraceptive use. DHS sample designs are usually two-stage probability samples drawn from the most recent sample frame. The Indian DHS comprises two modules of questions, i.e., State and District modules. The sample of women covered in the state module is a subsample (15%) of the district module. Questions on husbands’ backgrounds and women’s work, women’s empowerment, HIV/AIDS, and domestic violence were administered to women in the state module only. However, DHS of remaining three countries contains only one module of questions representing the country. Informed consent procedures were followed in the DHSs, and only those who agreed voluntarily were interviewed. The surveys were approved by the Institutional Review Boards of the involved Institutes, and the datasets are freely available at https://www.dhsprogram.com. More details about DHS survey design, sampling, survey instruments, data collection procedure, and ethical considerations are present here [27]. The analysis was carried out for currently married women aged 15–49 in the selected countries, i.e., Bangladesh (n = 18,895), Nepal (9,897), Pakistan (11,902), and India (5,12,408).

Outcome variable

The outcome variable used in this study was ‘contraceptive method use’; classified as not using any method, modern spacing methods, modern limiting methods, and any traditional method. Modern spacing methods include Pill, IUD, injections, diaphragm, condom, foam or jelly, lactational amenorrhea, and standard days. Female and male sterilization was considered a modern limiting method. Rhythm/ periodic abstinence and withdrawal were regarded as the traditional contraceptive methods.

Predictor variables

The household living arrangement of the women was the primary predictor variable for this analysis. It was categorized as (1) Living with a husband and/or unmarried children: defined as households comprised of a married couple or a man or a woman living alone or with unmarried children with or without unrelated individuals; (2) Living with a husband and other family members except MIL: defined as households comprised of a married couple and other family members except MIL; (3) Living with husband and other family members including MIL: defined as household comprised of a married couple and other family members including the MIL, and (4), Living with a husband and/or unmarried children and MIL: defined as households comprised of a married couple or a man or a woman living alone or with unmarried children with or without unrelated individuals and with MIL.

To assess the adjusted effect of household living arrangements on contraceptive use, selected socioeconomic and demographic characteristics of the women such as current age (15–19, 20–24, 25–29, 30–34, 35–39, 40–44, 45–49), years of schooling (no schooling, less than 10 years, 10 and more years), desire for more children (no, yes, undecided), gender of living children (have only daughters, have at least one son), mass-media exposure (yes, no), wealth quintile (poorest, poorer, middle, richer, richest), religion (Hindu, Muslim, others-except for Pakistan), place of residence (rural, urban), geographical region were also included in the analysis.

Statistical analysis

Univariate analysis was carried out to understand the profile of the study sample. Bivariate analysis was conducted to understand the individual association between the predictors and outcome variables. Multinomial logistic regression was used to check the adjusted effects of the predictor variables on contraceptive method use. The regression model used “not using any method” as the reference category. The predictor variables included for regression analysis were finalized after checking multicollinearity through the Variance Inflation Factors (VIF) test. Weights were used to restore the sample’s representativeness. The analyses were done with Stata (version 16) with a 5% significance level.

Results

Sample characteristics

Tables 1 and 2 presents the socioeconomic and demographic profile of the currently married women aged 15–49 in Bangladesh, Pakistan, India, and Nepal. Of the total women covered in the study, a majority were living in households with a husband and/or unmarried child(ren) in India (49%), Bangladesh (56%), and Nepal (48%). In Pakistan, most (45%) women lived in households with husbands and other family members except MIL. Most women had no schooling in Nepal (41%) and Pakistan (49%). The majority of women had no more desire for children in all four countries, i.e., India (74%), Nepal (73%), Bangladesh (64%), and Pakistan (47%). Close to three-fourths of women in all four countries had at least one living son, i.e., India (74%), Nepal (73%), Pakistan (73%), and Bangladesh (70%). India (82%) and Nepal (87%) had a majority of women of the Hindu religion, whereas, in Bangladesh, most (90%) followed Islam. In all four countries, the majority of women lived in rural areas, i.e., Bangladesh (64%), India (74%), Pakistan (73%), and Nepal (73%). Two-thirds of the women of Bangladesh (66%) and Pakistan (66%) had mass-media exposure. The corresponding figures were 76% in India and 82% in Nepal.

Table 1.

Socioeconomic and demographic characteristics of currently married women aged 15–49, Bangladesh (2017–18) and Pakistan (2017–18)

Background characteristics Bangladesh Pakistan
Unweighted % Unweighted n Weighted % Weighted n Unweighted % Unweighted n Weighted % Weighted n
Household living arrangements of Women
 Living with husband and/or unmarried child(ren) 54.99 10,391 55.63 10,562 42.77 5090 42.77 5060
 Living with husband and other family member except MIL 31.37 5,928 31.47 5975 45.13 5,371 45.13 5339
 Living with husband and other family member including MIL 11.68 2207 11.02 2092 10.8 1,286 10.8 1278
 Living with husband and/or unmarried child(ren) and MIL 1.95 369 1.87 355 1.3 155 1.3 154
Age
 15–19 10.01 1,891 10.57 2006 5.01 596 5.01 592
 20–24 17.96 3,394 18.09 3435 15.68 1,866 15.68 1855
 25–29 18.16 3,431 18.14 3445 21.08 2,509 21.08 2494
 30–34 17.43 3,293 17.43 3308 19.81 2,358 19.81 2344
 35–39 14.56 2,751 14.22 2699 17.27 2,055 17.27 2043
 40–44 11.23 2,122 11.11 2108 11.19 1,331 11.19 1323
 45–49 10.65 2,013 10.44 1983 9.97 1,187 9.97 1180
Years of schooling
 No education 17.31 3271 18.08 3432 48.79 5,807 48.79 5773
 < 10 years of schooling 63.87 12,069 64.70 12,284 27.35 3,256 27.35 3236
 ≥ 10 years of schooling 18.81 3555 17.22 3268 23.85 2,839 23.85 2822
Desire for more childrena
 No 64.80 12,244 64.40 12,225 46.95 5582 46.95 5548
 Yes 32.98 6231 33.39 6339 43.68 5193 43.68 5161
 Undecided 2.22 420 2.21 420 9.37 1114 9.37 1107
Gender of living children
 Only have daughters 29.80 5,631 29.82 5661 27.36 3,256 27.36 3237
 At least have one son 70.2 13,264 70.18 13,323 72.64 8,646 72.64 8594
Mass media exposure
 No 34.50 6,519 33.81 6419 33.77 4,018 33.77 3993
 Yes 65.50 12,376 66.19 12,565 66.23 7,880 66.23 7831
Religion
 Hindu 9.31 1,760 8.64 1640
 Muslim 90.06 17,016 90.63 17,205
 Others 0.63 119 0.73 139
Wealth quintile
 Poorest 18.77 3,547 18.29 3473 18.22 2,168 18.22 2155
 Poorer 19.05 3,599 19.65 3730 19.42 2,311 19.42 2298
 Middle 19.34 3,654 20.26 3846 20.35 2,422 20.35 2407
 Richer 20.43 3,861 20.99 3985 20.92 2,490 20.92 2475
 Richest 22.41 4,234 20.81 3951 21.10 2,511 21.10 2496
Place of residence
 Urban 36.42 6,881 28.33 5378 36.77 4,376 36.77 4350
 Rural 63.58 12,014 71.67 13,606 63.23 7,526 63.23 7481
 Total 100 18,895 100 18,984 100 11,902 100 11,831
Region (Pakistan)
 Punjab 53.06 6,315 53.06 6277
 Sindh 23.24 2,766 23.24 2750
 KPK 15.60 1,856 15.60 1845
 Balochistan 5.30 630 5.30 627
 IT 0.87 104 0.87 103
 FATA 1.93 230 1.93 229
Region (Bangladesh)
 Barisal 10.65 2012 5.56 1056
 Chittagong 14.45 2731 17.98 3414
 Dhaka 14.94 2822 25.62 4864
 Khulna 13.13 2480 11.62 2205
 Mymensingh 10.87 2053 7.73 1468
 Rajshahi 12.84 2426 13.93 2645
 Rangpur 12.42 2346 11.84 2247
 Sylhet 10.72 2025 5.71 1085
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aTotal number of women is different due to missing cases

Table 2.

Socioeconomic and demographic characteristics of currently married women aged 15- 49, India (2019–21) and Nepal (2016)

Background characteristics India Nepal
Unweighted % Unweighted n Weighted % Weighted n Unweighted % Unweighted n Weighted % Weighted n
Household living arrangements of Women
 Living with husband and or unmarried child 50.02 256,308 49.14 256,168 48.01 4,752 48.34 4771
 Living with husband and other family member except MIL 39.00 199,840 39.39 205,344 43.77 4,332 43.08 4252
 Living with husband and other family member including MIL 8.82 45,170 9.27 48,341 6.8 673 7.08 699
 Living with husband and/or unmarried child(ren) and MIL 2.16 11,090 2.21 11,498 1.41 140 1.49 147
Age of women
 15–19 2.64 13,548 2.96 15,407 7.49 741 7.14 704
 20–24 13.27 68,009 13.73 71,584 17.51 1,733 17.05 1682
 25–29 19.61 100,506 19.61 102,257 19.62 1,942 19.83 1957
 30–34 18.27 93,596 18.02 93,946 17.28 1,710 17.46 1723
 35–39 17.74 90,897 17.39 90,684 15.29 1,513 15.29 1509
 40–44 14.29 73,238 14.14 73,706 12.46 1,233 12.99 1282
 45–49 14.17 72,614 14.15 73,767 10.36 1,025 10.24 1010
Years of schooling
 No education 28.84 147,753 27.57 143,754 41.86 4,143 41.53 4098
 < 10 years of schooling 38.53 197,439 37.64 196,214 39.85 3,944 39.63 3910
 ≥ 10 years of schooling 32.63 167,216 34.79 181,384 18.29 1,810 18.85 1860
Desire for more childrena
 No 72.13 362,966 73.71 377,038 73.44 7268 73.04 7208
 Yes 23.67 119,096 23.16 118,469 24.42 2417 24.64 2432
 Undecided 4.20 21,120 3.13 15,998 2.14 212 2.32 229
Gender of living children
 Only have daughters 25.13 128,776 25.87 134,890 25.88 2,561 26.45 2610
 At least have one son 74.87 383,632 74.13 386,461 74.12 7,336 73.55 7258
Mass Media Exposure
 No 25.93 132,875 24.40 127,223 17.61 1,743 18.20 1796
 Yes 74.07 379,533 75.60 394,129 82.39 8,154 81.80 8072
Religion
 Hindu 76.71 393,073 81.92 427,114 87.66 8,676 86.62 8547
 Muslim 12.07 61,829 13.16 68,630 4.59 454 5.12 505
 Others 11.22 57,506 4.91 25,607 7.75 767 8.27 816
Wealth Quintile
 Poorest 21.06 107,924 18.79 97,962 21.32 2,110 17.08 1685
 Poorer 22.02 112,848 19.97 104,135 21.07 2,085 19.71 1945
 Middle 20.74 106,285 20.43 106,487 20.79 2,058 21.14 2086
 Richer 19.18 98,260 20.76 108,247 19.80 1,960 21.35 2106
 Richest 17.00 87,091 20.05 104,520 17.02 1,684 20.73 2045
Place of residence
 Rural 76.18 390,362 68.66 357,957 63.24 6,259 61.06 6025
 Urban 23.82 122,046 31.34 163,394 36.76 3,638 38.94 3843
 Total 100 512,408 100 521,352 100 9,897 100 9868
Region (India)
 North 19.92 102,094 13.73 71,597
 Central 22.86 117,128 23.64 123,236
 East 17.12 87,731 23.83 124,256
 Northeast 13.78 70,596 3.67 19,144
 West 10.26 52,592 14.34 74,774
 South 16.05 82,267 20.78 108,344
Region (Nepal)
 Province 1 14.11 1,396 16.76 1654
 Province 2 17.72 1,754 21.96 2167
 Province 3 11.83 1,171 19.45 1920
 Province 4 12.27 1,214 9.62 949
 Province 5 16.01 1,585 17.70 1747
 Province 6 14.34 1,419 5.94 586
 Province 7 13.72 1,358 8.56 845
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aTotal number of women is different due to missing cases

Current contraceptives use by household living arrangements and socio-demographic factors

Tables 3 and 4 presents the current use of contraceptive methods among currently married women aged 15–49 in Bangladesh, Pakistan, India, and Nepal by living arrangements of women and other socio-demographic characteristics. In Bangladesh, the use of the contraceptive method was 66% among women living with husbands and/or unmarried children, 52% for women living with husbands and other family members excluding MIL, 67% for women living with husbands and other family members, including MIL, and 65% for women living with husbands and/or unmarried children and MIL. The corresponding figures were- 40%, 28%, 34%, and 41% in Pakistan; 71%, 61%, 69%, and 71% in India; and 58%, 45%, 60%, and 67% in Nepal.

Table 3.

Current use of the contraceptive method among currently married women aged 15–49 by socioeconomic and demographic characteristics, Bangladesh (2017–18) and Pakistan (2017–18)

Background characteristics Bangladesh Pakistan
Not using Modern Spacing method Modern Limiting method Any Traditional method No. of women (UW) No. of women (W) Not using Modern Spacing method Modern Limiting method Any Traditional method No. of women (UW) No. of women (W)
Household living arrangements of Women
 Living with husband and/or unmarried child(ren) 33.9 48.6 6.9 10.7 10,391 10,562 59.6 17.1 12.5 10.8 5090 5060
 Living with husband and other family member except MIL 47.9 38.3 4.7 9.2 5,928 5975 71.7 14.3 5.7 8.4 5,371 5339
 Living with husband and other family member including MIL 32.5 53.6 4.7 9.2 2,207 2092 66.8 18.9 7.3 7.0 1,286 1278
 Living with husband and/or unmarried child(ren) and MIL 34.6 54.6 4 6.8 369 355 58.5 30.8 8.1 2.6 155 154
Age
 15–19 51.1 43.6 0.1 5.2 1,891 2006 92.6 5.9 0 1.5 596 592
 20–24 44.4 50.4 0.5 4.7 3,394 3435 81.7 13.1 0.2 5 1,866 1855
 25–29 36.5 53.5 3.3 6.7 3,431 3445 71.6 17.5 3.4 7.5 2,509 2494
 30–34 29 55.2 7.4 8.3 3,293 3308 57.9 21.8 8.4 12 2,358 2344
 35–39 24.6 50.5 11 13.9 2,751 2699 55.9 19.8 12.8 11.4 2,055 2043
 40–44 33.8 34.9 11.1 20.2 2,122 2108 52.3 14.7 21.3 11.6 1,331 1323
 45–49 55.4 18.2 10.6 15.8 2,013 1983 63.4 7.8 18.1 10.8 1,187 1180
Years of schooling
 No education 37.2 37.1 11.9 13.8 3271 3432 71.4 12 9.6 7 5,807 5773
 < 10 years  of schooling 37.7 48.24 5.13 8.93 12,069 12,284 63.6 18 9 9.4 3,256 3236
 ≥ 10 years of schooling 40.8 46.96 2.5 9.74 3555 3268 57 22.8 7 13.2 2,839 2822
Desire for more childrena
 No 30.8 47.6 9.15 12.37 12,244 12,225 46.49 21.45 18.79 13.27 5582 5548
 Yes 51.23 43.29 0 5.48 6231 6339 83.32 11.18 0 5.50 5193 5161
 Undecided 53.02 40.03 0 6.95 420 420 81.03 13.29 0 5.69 1114 1107
Gender of living children
 Only have daughters 52.45 38.53 1.99 7.03 5,631 5661 89.86 6.85 0.36 2.93 3,256 3237
 At least have one son 32.07 49.18 7.55 11.19 13,264 13,323 56.77 19.73 12 11.5 8,646 8594
Mass media exposure
 No 39 44 5.9 11 6,519 6419 74.7 12 7.3 6 4,018 3993
 Yes 37.7 47 5.9 9.4 12,376 12,565 61.3 18.3 9.6 10.8 7,880 7831
Religion
 Hindu 28.06 50.57 8.76 12.6 1,760 1640
 Muslim 39.19 45.5 5.65 9.66 17,016 17,205
 Others 28.37 55.06 1.71 14.87 119 139
Wealth quintile
 Poorest 33.7 49.9 7.3 9.1 3,547 3473 79.9 9.9 7.2 3 2,168 2155
 Poorer 36.5 46.1 6.6 10.9 3,599 3730 71 13.4 9.2 6.4 2,311 2298
 Middle 40.8 44.3 5.9 8.9 3,654 3846 63.3 17.7 9.2 9.8 2,422 2407
 Richer 38.9 45.9 5.4 9.8 3,861 3985 61.6 18.5 9.1 10.8 2,490 2475
 Richest 40.2 44.3 4.5 11 4,234 3951 55.5 20.5 9.2 14.8 2,511 2496
Place of residence
 Urban 34.6 49.6 5.3 10.5 6,881 5378 57.5 19 9.8 13.7 4,376 4350
 Rural 39.6 44.6 6.1 9.7 12,014 13,606 70.6 14.6 8.2 6.5 7,526 7481
 Total 38.1 46 5.9 10 18,895 18,984 65.8 16.2 8.8 9.2 11,902 11,831
Region (Pakistan)
 Punjab 61.7 16.6 10.6 11.1 6,315 6277
 Sindh 69.1 14.5 10 6.5 2,766 2750
 KPK 69.1 19.1 4 7.7 1,856 1845
 Balochistan 80.2 11.7 2.4 5.8 630 627
 IT 54.3 25.2 9.5 11 104 103
 FATA 78.2 12.7 1 8.1 230 229
Region (Bangladesh)
 Barisal 38.4 47.9 3.1 10.7 2012 1056
 Chittagong 46.3 40.5 4.3 9 2731 3414
 Dhaka 37.8 46.7 5.9 9.5 2822 4864
 Khulna 35.4 46.1 6.1 12.5 2480 2205
 Mymensingh 36.6 50.4 4.7 8.2 2053 1468
 Rajshahi 35.3 47.9 7.2 9.6 2426 2645
 Rangpur 30.2 50.3 8.6 10.8 2346 2247
 Sylhet 44.6 38.9 5.9 10.6 2025 1085
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aTotal number of women is different due to missing cases, UW means ‘Unweighted’, W means ‘Weighted’

Table 4.

Current use of the contraceptive method among currently married women aged 15–49 by socioeconomic and demographic characteristics, India (2019–21) and Nepal (2016)

Background characteristics India Nepal
Not using Modern spacing method Modern limiting method Any traditional method No. of women (UW) No. of women (W) Not using Modern spacing method Modern limiting method Any traditional method No. of women (UW) No. of women (W)
Household living arrangements of Women
 Living with husband and or unmarried child 28.9 16.5 44.6 10 256,308 256,168 42.1 24.2 23.2 10.4 4,752 4771
 Living with husband and other family member except MIL 39.4 20.3 29.7 10.6 199,840 205,344 55.1 19.4 16.5 8.9 4,332 4252
 Living with husband and other family member including MIL 31.4 18.1 40.1 10.3 45,170 48,341 39.5 28.3 21.2 11 673 699
 Living with husband and/or unmarried child(ren) and MIL 29.2 20 39.8 11 11,090 11,498 32.7 33.6 23 10.6 140 147
Age of women
 15–19 71.9 18.4 0.4 9.4 13,548 15,407 76.9 14.5 0 8.6 741 704
 20–24 57.5 23.9 7.9 10.7 68,009 71,584 68 21.3 2.7 8.1 1,733 1682
 25–29 39.1 24.8 24.6 11.5 100,506 102,257 54.2 27.2 9.8 8.8 1,942 1957
 30–34 26.4 22.3 40 11.2 93,596 93,946 41.5 27.1 20.3 11.2 1,710 1723
 35–39 21.1 17.3 50.8 10.8 90,897 90,684 31.5 24.3 33.2 11.1 1,513 1509
 40–44 22.8 11.2 56.1 9.8 73,238 73,706 30.6 21.1 37.3 11 1,233 1282
 45–49 27.9 6.5 58.7 6.9 72,614 73,767 34.7 13.3 42.2 9.8 1,025 1010
Years of schooling
 No education 29.9 11.2 48.9 10 147,753 143,754 42 20 31.5 6.5 4,143 4098
 < 10 years of schooling 31.3 17.7 40.9 10.1 197,439 196,214 52.5 23.5 14.2 9.8 3,944 3910
 ≥ 10 years of schooling 38.2 24.3 26.9 10.6 167,216 181,384 48.5 26.5 7.9 17.1 1,810 1860
Desire for more childrena
 No 21.07 16.12 52.85 9.97 362,966 377,038 37.46 24.99 27.64 9.92 7268 7208
 Yes 63.35 25.06 0 11.6 119,096 118,469 75.09 15.27 0 9.63 2417 2432
 Undecided 57.58 28.65 0 13.77 21,120 15,998 66.06 25.17 0 8.77 212 229
Gender of living children
 Only have daughters 58.1 19.8 12.4 9.6 128,776 134,890 71.71 16.81 1.82 9.66 2,561 2610
 At least have one son 24.6 17.7 47.2 10.5 383,632 386,461 38.65 24.68 26.79 9.88 7,336 7258
Mass Media Exposure
 No 37.7 15.5 35.3 11.5 132,875 127,223 53.9 19.5 21 5.6 1,743 1796
 Yes 31.9 19.1 39.2 9.9 379,533 394,129 45.9 23.3 20 10.8 8,154 8072
Religion
 Hindu 32.1 17.1 40.9 9.9 393,073 427,114 45.95 22.36 21.54 10.15 8,676 8547
 Muslim 39.8 25.4 21.9 12.8 61,829 68,630 69.61 14.16 10.28 5.95 454 505
 Others 35.2 18.5 36.8 9.5 57,506 25,607 48.77 30.3 12.2 8.73 767 816
Wealth Quintile
 Poorest 37.8 15.9 34.8 11.5 107,924 97,962 50.9 28.1 13.7 7.3 2,110 1685
 Poorer 33.9 16.8 38.7 10.6 112,848 104,135 46.6 23.5 21.3 8.6 2,085 1945
 Middle 32.3 15.7 42.6 9.4 106,285 106,487 50.4 18.2 24.4 7 2,058 2086
 Richer 32.2 17.7 40.8 9.3 98,260 108,247 49.9 19.8 21.9 8.4 1,960 2106
 Richest 30.6 25 33.7 10.7 87,091 104,520 39.7 24.6 18.4 17.4 1,684 2045
Place of residence
 Rural 34.4 16.5 39 10 122,046 357,957 45.2 23.7 20.5 10.6 6,259 6025
 Urban 30.7 22 36.5 10.7 390,362 163,394 50.8 20.9 19.7 8.6 3,638 3843
 Total 33.3 18.2 38.2 10.3 512,408 521,352 47.4 22.6 20.2 9.8 9,897 9868
Region (India)
 North 28.8 25.4 33.5 12.4 102,094 71,597
 Central 34.8 22.6 28.7 13.9 117,128 123,236
 East 34 19.5 32.2 14.3 87,731 124,256
 Northeast 40.7 33.8 9.2 16.2 70,596 19,144
 West 34.1 15.5 44.9 5.5 52,592 74,774
 South 31.9 6.2 59.5 2.3 82,267 108,344
Region (Nepal)
 Province 1 44.9 27.2 12.9 15 1,396 1654
 Province 2 52.3 9.8 32.4 5.5 1,754 2167
 Province 3 39.4 30.4 18.8 11.4 1,171 1920
 Province 4 51.6 19.5 17.8 11.1 1,214 949
 Province 5 52 23.4 15.4 9.1 1,585 1747
 Province 6 48.9 27 17.5 6.6 1,419 586
 Province 7 48.9 27 17.5 6.6 1,358 845
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UW means ‘Unweighted’, W means ‘Weighted’

aTotal number of women is different due to missing cases

Modern spacing method use varied by household living arrangements of women across the four selected south Asian countries. The prevalence of modern spacing method use was higher among women from households with a MIL except other family members than those residing in other types of households in all countries except India. For example- in Bangladesh, 55% of those from households with a MIL except other family members were using any modern spacing method and 54% of those from households with a MIL and with other family members were using any modern spacing method, which was 38% among women from households without the MIL, 49% for women living in households comprising husbands and/or unmarried children. Across the countries, the use of modern limiting methods of contraception was the highest among women living in households comprising husbands and/or unmarried children only than their counterparts from households with/without MIL. Between the women from households with and without MIL, modern method use was considerably higher among those from households with MIL. The result is true, except for Bangladesh, where modern limiting method use was almost the same (4.6%-4.7%) for women from households with/without the MIL. No specific pattern emerged so far as the use of traditional contraception methods was concerned, ranging between 7–11% for women with different living arrangements in Bangladesh, India, and Nepal. In Pakistan, 3% of the women from households with a MIL except other family members and 7% of the women from households with a MIL including other family members were using any traditional contraceptive method, which was 11% for women living in households comprising husbands and/or unmarried children.

Across the countries, the use of modern limiting methods increased with the increasing age of women. However, a higher prevalence of modern spacing methods was noticed for women aged 20–34, after which it declined. In all four countries, the years of schooling of women were positively associated with the use of the modern spacing method and inversely with the use of the modern limiting method. Higher percentages of the women with at least one surviving son were using any modern limiting method than those with only surviving daughters. Higher percentages of the women with mass-media exposure were using any modern spacing and limiting method of contraception in all four countries compared to those without mass-media exposure. The only exception was the use of modern limiting methods in Nepal. With the increasing wealth status of women, the use of the modern spacing method of contraception increased in India and Pakistan. Again, except in Pakistan, the use of modern limiting methods decreased with increasing wealth status. Contraceptive use pattern further varied by geographic region in all four selected countries. A sizable percentage of the women not desiring more children were not using any contraceptive methods across the four countries.

Determinants of current use of contraceptive methods

Table 5 presents the adjusted odds ratio (AOR) of logistic regression of factors affecting the current use of contraceptive methods. In Nepal, the odds of using modern spacing methods of contraception were significantly higher among women living with husband and/or unmarried children and MIL (OR = 2.35, CI = 1.53–3.60) as well as those living with husband and other family members, including MIL (OR = 1.63, CI = 1.32–2.02) than those women living with only husband and/or unmarried children. Similarly, the women co-residing with husband and other family member including MIL had higher probability of using any modern spacing method than their counterparts co-residing with only husband and/or unmarried children in Bangladesh (OR = 1.17, CI = 1.05–1.31). The chances of using any modern spacing methods of contraception were significantly higher among the women living in households including husband and/or unmarried children and MIL (OR = 1.12, CI = 1.05–1.18) than their counterparts living in households with only a husband and/or unmarried child(ren) in India. The chances of using any modern limiting methods of contraception were significantly higher among the women living in households including husband and/or unmarried children and MIL (OR = 1.20, CI = 1.13–1.27) as well as households including husband and other family members including MIL (OR = 1.12, CI = 1.09–1.16) than their counterparts living in households with only a husband and/or unmarried child(ren) only in India. As against the women from households with husbands and/or unmarried children, those living in households with husband and/or unmarried children and MIL (OR = 1.13, CI = 1.06–1.21) as well as with husband and other members including MIL (OR = 1.07, CI = 1.03–1.11) had higher odds of using any traditional method of contraception in India.

Table 5.

Adjusted Odds Ratio (AOR) of predictors of the contraceptive method use in selected South Asian countries

Background characteristics Modern Spacing Method AOR (95% CI) Modern limiting Method AOR (95% CI) Any traditional Method AOR (95% CI)
Nepal Pakistan Bangladesh India Nepal Pakistan Bangladesh India Nepal Pakistan Bangladesh India
Household living arrangements of Women
 Living with husband and or unmarried childa
 Living with husband and other family member except MIL 0.79*** [0.70, 0.89] 0.83** [0.75, 0.93] 0.70*** [0.65, 0.76] 0.92*** [0.90, 0.93] 0.94 [0.82, 1.07] 0.95 [0.81, 1.12] 0.81** [0.69, 0.94] 0.87*** [0.85, 0.88] 0.85 [0.73, 1.00] 0.84 [0.73, 0.96] 0.82*** [0.73, 0.92] 0.92*** [0.90, 0.94]
 Living with husband and other family member including MIL 1.63*** [1.32, 2.02] 1.05 [0.90, 1.23] 1.17** [1.05, 1.31] 1 [0.97, 1.03] 1.33 [1.03, 1.72] 0.9 [0.69, 1.17] 0.99 [0.79, 1.25] 1.12*** [1.09, 1.16] 1.33 [0.99, 1.79] 0.83 [0.67, 1.03] 1.08 [0.90, 1.28] 1.07*** [1.03, 1.11]
 Living with husband and/or unmarried child(ren) and MIL 2.35*** [1.53, 3.60] 1.49 [1.04, 2.13] 1.13 [0.89, 1.43] 1.12*** [1.05, 1.18] 1.6 [0.92, 2.78] 0.92 [0.44, 1.93] 0.7 [0.38, 1.29] 1.20*** [1.13, 1.27] 1.63 [0.88, 3.03] 0.83 [0.47, 1.49] 0.93 [0.62, 1.41] 1.13*** [1.06, 1.21]
Age of women
 15–19 1.75*** [1.26, 2.43] 2.86*** [1.94, 4.21] 9.16*** [7.62, 11.02] 1.93*** [1.82, 2.05] 0 [0.00, .] 0 [0.00, .] 0.42 [0.10, 1.72] 0.03*** [0.02, 0.05] 0.77 [0.51, 1.17] 1.27 [0.75, 2.15] 0.93 [0.69, 1.26] 0.99 [0.92, 1.06]
 20–24 1.93*** [1.49, 2.51] 4.10*** [3.19, 5.28] 8.12*** [6.90, 9.55] 2.50*** [2.40, 2.60] 0.13*** [0.09, 0.19] 0.10*** [0.03, 0.32] 0.41*** [0.25, 0.69] 0.33*** [0.31, 0.34] 0.52*** [0.37, 0.72] 1.56** [1.16, 2.11] 0.78 [0.61, 0.98] 1.13*** [1.08, 1.18]
 25–29 2.02*** [1.59, 2.56] 4.38*** [3.50, 5.49] 7.39*** [6.33, 8.62] 3.07*** [2.96, 3.18] 0.29*** [0.23, 0.37] 0.66** [0.49, 0.90] 1.18 [0.90, 1.54] 0.71*** [0.69, 0.73] 0.54*** [0.40, 0.73] 1.68*** [1.31, 2.17] 0.97 [0.79, 1.19] 1.47*** [1.42, 1.53]
 30–34 2.20*** [1.73, 2.79] 4.53*** [3.64, 5.64] 7.67*** [6.58, 8.92] 3.66*** [3.53, 3.80] 0.60*** [0.48, 0.74] 1.11 [0.88, 1.41] 2.37*** [1.90, 2.95] 1.12*** [1.09, 1.15] 0.96 [0.72, 1.28] 2.17*** [1.72, 2.75] 1.26 [1.04, 1.52] 1.92*** [1.84, 1.99]
 35–39 2.38*** [1.86, 3.04] 3.68*** [2.96, 4.57] 7.05*** [6.03, 8.24] 3.53*** [3.40, 3.67] 1.09 [0.89, 1.33] 1.49*** [1.20, 1.84] 2.92*** [2.36, 3.62] 1.41*** [1.37, 1.45] 1.21 [0.90, 1.62] 1.90*** [1.51, 2.39] 2.32*** [1.94, 2.77] 2.16*** [2.07, 2.24]
 40–44 2.02*** [1.56, 2.62] 2.39*** [1.89, 3.02] 3.38*** [2.88, 3.97] 2.12*** [2.04, 2.21] 1.21 [0.98, 1.48] 1.49*** [1.20, 1.85] 2.04*** [1.65, 2.53] 1.27*** [1.24, 1.31] 1.33 [0.98, 1.81] 1.59*** [1.25, 2.02] 2.18*** [1.83, 2.60] 1.81*** [1.74, 1.89]
 45–49a
Years of schooling
 No educationa
 < 10 years of schooling 1.01 [0.88, 1.16] 1.28*** [1.12, 1.47] 1.12 [1.01, 1.25] 1.36*** [1.33, 1.40] 0.62*** [0.53, 0.73] 1.13 [0.93, 1.37] 0.77** [0.65, 0.90] 0.82*** [0.80, 0.84] 1.23 [1.01, 1.50] 1.16 [0.97, 1.38] 1.02 [0.88, 1.17] 1.21*** [1.17, 1.24]
 ≥ 10 years of schooling 1.21 [1.01, 1.45] 1.66*** [1.43, 1.92] 1.24** [1.09, 1.42] 1.40*** [1.36, 1.44] 0.43*** [0.33, 0.55] 0.92 [0.72, 1.17] 0.59*** [0.44, 0.78] 0.55*** [0.54, 0.57] 2.28*** [1.79, 2.90] 1.45*** [1.20, 1.75] 1.41*** [1.16, 1.72] 1.16*** [1.12, 1.19]
Desire for more children
 Noa
 Yes 0.48*** [0.40, 0.56] 0.32*** [0.28, 0.36] 0.48*** [0.43, 0.52] 0.65*** [0.64, 0.67] 0 [0.00, .] 0 [0.00, .] 0 [0.00, .] 0 [0.00, .] 0.76 [0.60, 0.95] 0.35*** [0.30, 0.42] 0.45*** [0.38, 0.54] 0.63*** [0.61, 0.65]
 Undecided 0.52*** [0.36, 0.75] 0.34*** [0.29, 0.41] 0.38*** [0.31, 0.48] 0.67*** [0.64, 0.69] 0 [0.00, .] 0 [0.00, .] 0 [0.00, .] 0 [0.00, .] 0.68 [0.41, 1.11] 0.31*** [0.24, 0.40] 0.57** [0.39, 0.84] 0.61*** [0.58, 0.63]
Gender of living children
 Only have daughtersa
 At least have one son 2.06*** [1.78, 2.38] 3.27*** [2.81, 3.80] 2.06*** [1.90, 2.23] 2.09*** [2.05, 2.14] 5.72*** [4.17, 7.85] 6.79*** [3.77, 12.23] 1.89*** [1.52, 2.34] 3.63*** [3.54, 3.72] 1.75*** [1.44, 2.14] 3.66*** [2.95, 4.54] 1.51*** [1.32, 1.74] 1.98*** [1.93, 2.03]
Mass Media Exposure
 Noa
 Yes 1.26** [1.09, 1.47] 1.34*** [1.18, 1.52] 1.16*** [1.06, 1.26] 1.23*** [1.21, 1.26] 1.56*** [1.32, 1.85] 1.41*** [1.16, 1.70] 1.51*** [1.28, 1.78] 1.41*** [1.38, 1.44] 1.56*** [1.22, 1.99] 1.28** [1.08, 1.51] 0.94 [0.83, 1.07] 1.18*** [1.15, 1.21]
Religion
 Hindua
 Muslim 0.61*** [0.45, 0.81] 0.62*** [0.55, 0.70] 1.11*** [1.08, 1.14] 0.17*** [0.12, 0.24] 0.58*** [0.47, 0.72] 0.34*** [0.33, 0.35] 0.46*** [0.29, 0.72] 0.62*** [0.52, 0.74] 0.91*** [0.89, 0.94]
 Others 1.08 [0.90, 1.30] 1.12 [0.72, 1.76] 0.95*** [0.92, 0.97] 0.59*** [0.45, 0.76] 0.36 [0.11, 1.21] 0.35*** [0.34, 0.36] 0.77 [0.58, 1.01] 1 [0.52, 1.90] 0.87*** [0.84, 0.90]
Wealth Quintile
 Pooresta
 Poorer 1.18 [1.00, 1.39] 1.51*** [1.27, 1.79] 0.94 [0.84, 1.05] 1.14*** [1.11, 1.17] 2.07*** [1.69, 2.54] 1.34 [1.03, 1.74] 0.84 [0.68, 1.03] 1.29*** [1.26, 1.32] 1.32 [1.03, 1.70] 1.92*** [1.47, 2.51] 1.14 [0.96, 1.36] 1.05** [1.02, 1.08]
 Middle 1.13 [0.95, 1.35] 1.89*** [1.57, 2.28] 0.82** [0.73, 0.92] 1.09*** [1.06, 1.12] 2.39*** [1.93, 2.96] 1.61*** [1.21, 2.13] 0.68*** [0.54, 0.86] 1.57*** [1.53, 1.62] 1.16 [0.89, 1.52] 2.94*** [2.23, 3.88] 0.87 [0.72, 1.05] 0.96 [0.93, 0.99]
 Richer 1.01 [0.84, 1.21] 1.88*** [1.53, 2.30] 0.84** [0.75, 0.96] 1.17*** [1.13, 1.20] 2.16*** [1.73, 2.70] 1.77*** [1.31, 2.40] 0.65*** [0.51, 0.83] 1.64*** [1.59, 1.69] 1.29 [0.99, 1.69] 3.40*** [2.54, 4.55] 1 [0.82, 1.21] 0.93*** [0.89, 0.96]
 Richest 1.18 [0.96, 1.45] 2.16*** [1.73, 2.69] 0.80** [0.69, 0.92] 1.69*** [1.63, 1.75] 2.56*** [1.99, 3.28] 1.78*** [1.28, 2.48] 0.62*** [0.47, 0.81] 1.38*** [1.33, 1.43] 2.21*** [1.67, 2.92] 4.02*** [2.94, 5.49] 0.99 [0.80, 1.23] 1.08*** [1.04, 1.13]
Place of residence
 Urbana
 Rural 0.92 [0.82, 1.04] 0.93 [0.83, 1.04] 0.72*** [0.66, 0.78] 0.95*** [0.93, 0.97] 0.83** [0.72, 0.95] 1.1 [0.93, 1.31] 0.76*** [0.65, 0.89] 1.17*** [1.15, 1.20] 1.13 [0.96, 1.34] 0.73*** [0.63, 0.84] 0.73*** [0.65, 0.83] 0.93*** [0.90, 0.95]
Modern Spacing Method AOR (95% CI) Modern limiting Method AOR (95% CI) Any traditional Method AOR (95% CI)
Region (India)
 Northa
 Central 1.42*** [1.37, 1.47] 1.05 [1.01, 1.08] 1.25*** [1.19, 1.31]
 East 0.97 [0.92, 1.02] 0.51*** [0.49, 0.54] 0.69*** [0.64, 0.74]
 Northeast 0.96** [0.93, 0.99] 0.89*** [0.86, 0.91] 1.30*** [1.25, 1.34]
 West 1.10*** [1.07, 1.13] 0.48*** [0.47, 0.50] 1.45*** [1.40, 1.50]
 South 1.04** [1.01, 1.07] 0.67*** [0.65, 0.69] 0.78*** [0.75, 0.81]
Region (Nepal)
 Province 1a
 Province 2 0.37*** [0.30, 0.46] 2.46*** [1.94, 3.13] 0.39*** [0.30, 0.52]
 Province 3 1.2 [0.99, 1.47] 1.47** [1.13, 1.91] 0.68** [0.53, 0.89]
 Province 4 0.60*** [0.49, 0.74] 1.04 [0.81, 1.35] 0.59*** [0.46, 0.76]
 Province 5 0.77** [0.64, 0.93] 0.97 [0.76, 1.24] 0.52*** [0.41, 0.66]
 Province 6 0.92 [0.76, 1.13] 1.58*** [1.22, 2.05] 0.50*** [0.38, 0.67]
 Province 7 0.94 [0.77, 1.14] 1.38 [1.08, 1.78] 0.67** [0.52, 0.87]
Region (Pakistan)
 Punjaba
 Sindh 0.94 [0.80,1.10] 1.27 [1.03,1.56] 0.63*** [0.51,0.77]
 KPK 1.30*** [1.12,1.52] 0.40*** [0.30,0.52] 0.9 [0.74,1.09]
 Balochistan 0.70*** [0.58,0.86] 0.35*** [0.24,0.49] 0.46*** [0.35,0.61]
 IT 1.16 [0.96,1.41] 0.78 [0.60,1.03] 0.73** [0.57,0.93]
 FATA 1.09 [0.86,1.39] 0.19*** [0.10,0.35] 1.48** [1.12,1.96]
Region (Bangladesh)
 Barisala
 Chittagong 0.66*** [0.57, 0.75] 1.09 [0.79, 1.50] 0.70*** [0.56, 0.86]
 Dhaka 0.95 [0.82, 1.09] 1.79*** [1.31, 2.45] 0.92 [0.74, 1.14]
 Khulna 1 [0.87, 1.15] 1.68** [1.23, 2.30] 1.22 [0.99, 1.50]
 Mymensingh 1.13 [0.98, 1.31] 1.4 [1.00, 1.96] 0.84 [0.66, 1.06]
 Rajshahi 1.1 [0.96, 1.27] 2.09*** [1.54, 2.84] 1.01 [0.81, 1.25]
 Rangpur 1.19 [1.03, 1.37] 2.54*** [1.87, 3.44] 1.26 [1.02, 1.56]
 Sylhet 0.62*** [0.54, 0.72] 1.45 [1.05, 2.01] 0.81 [0.65, 1.02]
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**< 0.01, ***< 0.001

aReference category

Compared to the women living in households comprising husband and/or unmarried child(ren), those from the households comprising husband and other household members excluding MIL had lower odds of using any modern limiting or spacing contraceptive method and any traditional method in all four countries. For example- the women living with a husband and other family members excluding MIL in Bangladesh, had a 30% (OR = 0.70, CI = 0.65–0.76) lesser chance of using any modern spacing method than those staying in households comprising a husband and/or unmarried children. The corresponding figures were 21% (OR = 0.79, CI = 0.70–0.89) for Nepal, 17% for Pakistan (OR = 0.83, CI = 0.75–0.93), and 8% (OR = 0.92, CI = 0.90–0.93) for India.

Similarly, the probability of modern limiting method use was significantly low among women living in households comprising husbands and other family members, excluding the MIL in Bangladesh (OR = 0.81, CI = 0.69–0.94), and India (OR = 0.87, CI = 0.85–0.88). Again, the odds of using any traditional method were significantly low among women living with husband and other family members excluding MIL than those living with husband and/or unmarried child (ren) in Bangladesh (OR = 0.82, CI = 0.73–0.92) and India (OR = 0.92, CI = 0.90–0.94).

Across the countries, the likelihood of using modern spacing and traditional method increased whereas chances of using modern limiting method decreased with increasing years of schooling. The probability of using modern spacing and any traditional contraceptive method was less among those who desire for additional child compared to their counterpart who desire for no more children in all studied countries. Compared to those who had only daughters, those with at least one son had higher likelihood of using any modern as well as traditional contraceptives. The chances to use of any modern as well as traditional contraceptives was higher among women with mass-media exposure than their counterpart with no mass-media exposure. Muslims had less likelihood of using any (except India in modern spacing use) contraceptive method than Hindus in other three countries. In Pakistan, with increasing wealth quintile, the chances of use of all types of contraceptive increases while it decreases in Bangladesh. In Nepal, with increasing wealth quintile, the chances of use of modern limiting method increases in Nepal but in India it leads to use of modern spacing method. Compared to urban women, the chances of contraceptive use among rural women were less except for modern limiting method use in India.

Discussion

The study found that the living arrangement of women has a significant association with contraceptive use in South Asia. The MIL continues to influence the contraceptive method used by the DIL, albeit country-specific method choice. Co-residence with MIL is associated with higher use of modern spacing method, modern limiting method and traditional method in India, and modern spacing method use in Nepal and Bangladesh. In Pakistan, women living in households without the MIL are less likely to use any contraceptive method.

In Bangladesh, the use of the modern spacing method is more in a household where women live with husbands and other family members, including MIL. There are contradictory findings that have been reported in previous small-scale studies on Bangladesh. A study based on 413 interviews in two areas with different family planning program found contraception use higher among DIL if MIL is supportive [19] while a qualitative explorative study found married adolescents are less likely to use contraception if MIL is against contraception use [28]. Another study based on 4053 currently married women in Matlab Sub district found no influence of the MIL on co-resident DIL’s use of modern contraceptives [29]. In the country, the community health worker network has worked as a backbone to spread the modern spacing method [19, 30] and motivate clients to use contraceptive methods [19, 31]. The results indicate that the community health workers could strengthen the supportive role of the MILs in DIL’s use of the spacing method by gaining trust of MIL through frequent home visits and intensive interactions about the advantages of use of modern spacing methods for birth spacing [19]. We found that any types of contraceptive use is significantly less among women residing in households without MIL, hence the community health worker should identify these households and make extra effort in order to increase the use of contraception among them.

In India, the use of modern limiting methods is more in households with husbands and other family members, including MIL and households with husband and/or unmarried child(ren) and MIL. The results conform to a past study based on data from an earlier round of Indian DHS [32]. Another study reveals that the MILs usually favor the modern limiting method of contraception, influence the timing of use of modern limiting method and oppose the modern spacing method in India [13]. MIL also often force their DIL to prove their fertility in the first year of their marriage, which also restrains the DIL from using any modern spacing method [11, 33]. Studies even indicate that the MIL restricts the mobility of their DIL to disconnect them from the outer world and to maintain their dominance over DIL’s reproductive choice [12, 21]. The use of modern spacing method is high in households with husband and/or unmarried child(ren) and MIL, which may be because the decision to use modern spacing method is majorly taken between husband and wife and thus, though MIL is not in favor of modern spacing method still its use is high. A past small scale qualitative study (Based on 60 MIL, 60 DIL and Sons from same family) conducted in Madhya Pradesh, India conforms this and found that DIL is not comfortable to discuss or disclose about contraceptive use with MIL but they only discuss with husband [13]. Another earlier study also reveal that husband’s decision regarding spacing method use is more important than MIL’s [34]. In the country, the use of any traditional method of contraception is also high among women co-residing with MIL. The result is also in line with a previous study, which reveals that MIL are in favor of traditional methods of contraception for spacing of births [20]. Moreover, the higher use of the traditional method of contraception may be due to less access and knowledge about the modern spacing method among less educated economically poor women or may also be among highly educated wealthy women for the wholesome side effects of the modern contraceptive methods [13, 35].

As women co-residing with MIL are more likely to use modern limiting method and traditional methods, family planning programs may be designed to enhance social networks to increase women’s access and uptake of modern spacing methods. An earlier study also highlights the beneficial role of social networks to increase women’s access and uptake of family planning methods [12]. Again, as MIL often acts as the gatekeeper, future programs may directly target them to inform her about the benefits of family planning [36]. Moreover, schemes like Saas-Bahu Sammelan (under Mission Parivar Vikas), a platform for mothers-in-law and their daughters-in-law, which attempts to influence attitudes and ideas about sexual and reproductive health through interactive games and by drawing on personal experiences, needs to be implemented throughout the country. At present this scheme is limited to only 146 high fertility districts (only for rural areas) [37]. A previous study also advocates the beneficial role of this scheme [10].

In Pakistan, contraceptive use is low among women co-residing with other family members without the MIL. Earlier studies from Pakistan also viewed that MIL significantly influences DIL’s contraception use behavior [15, 16]. Evidence further reveals that MIL have greater decision-making authority over young couples’ family planning than either member of the couple itself [38]. Nevertheless, as the overall contraception use is very low in Pakistan compared to other studied South Asian countries, there should be focus on promoting all types of modern contraceptives among women and sensitizing MIL about the benefits of contraceptives by the Lady Health Workers (LHWs) and Family Welfare Assistants (FWAs) placed under existing FP program.

In Nepal, the use of modern spacing is high in a household where women co-reside with MIL. This is in line with previous studies which found that spacing method use can be high through improved and positive spousal communication as well as MIL’s support in delaying childbearing to allow their daughter-in-law to mature, continue her education or earn wages; irrespective of societal pressure upon them [9, 39]. This contradicts to previous literature that reveal MIL as one of the barriers to contraceptive use as she pressurizes DIL to produce a child in the first year itself to prove her fertility, restricts the mobility of DIL, and decides contraceptive use for DIL [17]. Adolescent women are further more vulnerable to the MIL’s decisions on their contraceptive behavior. Nearly one-fifth of the women have unmet need for limiting [40], which has increased in recent times; which suggest the need for expanding the basket of choices in the program to address the need of the women. Additionally, promising interventions such as Sumadhur i.e., intervention for triads (wives, husbands, and mothers-in-law) including inequitable gender norms and practices, fertility planning and contraception, and couples and household relationship dynamics, which has been proved beneficial in improving fertility and family planning decision-making norms among newlyweds should be scaled up [41].

Our study found MIL enhances modern spacing method use in Bangladesh, Nepal and India (in set up with only husband and MIL), and influences higher use of modern limiting and traditional methods use in India. Though this study did not analyze whether the method used were informed choices, evidence suggests inadequate informed contraceptive choice in India [42], Bangladesh [43], Nepal [44], and Pakistan [45]. Using contraception without informed choice violates women’s reproductive rights [46]. The inadequately informed choice might lead to higher contraceptive discontinuation. High contraceptive discontinuation rates among women who discontinue use for reasons other than the desire to get pregnant lead to unintended pregnancies [47, 48]. Unintended pregnancies may lead to high maternal morbidity and mortality [49]. Contraceptive discontinuations are further linked with higher unmet needs and induced abortions [50, 51], negatively affecting women’s health.

The study found that irrespective of the studied countries, household living arrangements influence contraceptive method use- contraceptive acceptance is less among women from households with husband and other family members excluding MIL. Co-residence with MIL is associated with higher use of modern spacing method, modern limiting method, and traditional method in India, and modern spacing method use in Nepal and Bangladesh. The results suggest strengthening country-specific family planning programs to ensure informed contraceptive choices in an enabling household environment. Programs proved to improve contraceptive decision making and use among women by addressing concerns of MIL or engaging them in the program may be scaled up to enhance informed contraceptive use.. Irrespective of countries, the use of contraceptives is less among households with husbands and other family members excluding MIL. As an experienced aged female household member, MIL plays a crucial role in DIL contraceptive choice and utilizations, as contraceptives still consider a women’s subject in selected South Asian countries. So, the grassroots-level health workers should identify those households without MIL and give extra attention to them in respect of contraceptive use. This will improve the use of contraceptive use among those households.

The study has some methodological limitations. The study is based on cross-sectional data, thus, limiting any causal association between household living arrangements and contraceptive use. There is a possibility of socio-cultural and contextual factors influencing the contraceptive method use, which this study could not consider due to a lack of data. Despite these limitations, the study’s strengths are that the findings are based on large-scale, nationally representative samples chosen using a robust sampling design. Thus, the results are contemporary and relevant. The results contribute to the existing scanty evidence on the role of MIL in DIL’s contraceptive use in South Asia.

Conclusion

The study concludes that the living arrangement of the women, especially co-residence with MIL, is associated with the contraceptive method used in South Asia. The MIL continues to influence the contraceptive method used by the DIL, albeit country-specific method choice. The study suggests family planning program to cover MIL for enhancing their understanding on the benefits of contraceptive use and modifying norms around fertility. Strengthening the interaction between the grassroots level health workers and the MIL, enhancing social network of DIL may help informed choice and enhance the use of modern spacing methods. Women’s family planning demands met with modern contraception, and informed contraceptive choices, must also be achieved to reach the 2030 Agenda for Sustainable Development.

Acknowledgements

Not Applicable.

Authors’ contributions

Both authors read and approved the final manuscript. MRP: Conceptualization, Investigation; Methodology; Supervision; Validation; Visualization; Roles/Writing - original draft; Writing - review & editing; SM: Conceptualization, Data curation; Formal analysis; Software; Roles/Writing - original draft; Writing - review & editing. Both authors reviewed the manuscript.

Funding

The authors received no financial support from any funding agency, commercial entity, or not-for-profit organization for the research, authorship and/or publication of this article.

Availability of data and materials

The datasets generated and/or analyzed during the current study are available in the [Demographic and Health Surveys Repository] repository, (https://dhsprogram.com).

Declarations

Ethics approval and consent to participate

The study is based on the publicly available data source, and survey agencies that conducted the field survey for the data collection have also collected a prior consent from the respondent. The NFHS-5 was approved by the Institutional Review Board of the Institutions involved, and the datasets are available at https://www.dhsprogram.com for broader use in social research. The authors assert that all procedures contributing to this work comply with the ethical standards of the relevant national and institutional committees on human experimentation and with the Helsinki Declaration of 1975, as revised in 2008. They ruled that no formal ethical consent was required to conduct research from this data source.

Consent for publication

Not applicable.

Competing interests

The authors declare no competing interests.

Footnotes

Publisher’s Note

Springer Nature remains neutral with regard to jurisdictional claims in published maps and institutional affiliations.

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Associated Data

This section collects any data citations, data availability statements, or supplementary materials included in this article.

Data Availability Statement

The datasets generated and/or analyzed during the current study are available in the [Demographic and Health Surveys Repository] repository, (https://dhsprogram.com).

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