Socio-demographic determinants of sexual inactivity among reproductive married women in Bangladesh: Evidence of BDHS data 2022

Socio-demographic determinants of sexual inactivity among reproductive married women in Bangladesh: Evidence of BDHS data 2022 | Research Square window.SnipcartSettings = { analytics: { enabled: false } }; (function() { var accessVector = localStorage.getItem('access_vector') || ''; window.dataLayer = window.dataLayer || []; if (accessVector) { window.dataLayer.push({ user: { profile: { profileInfo: { snid: accessVector } } } }); } })(); (function(w,d,s,l,i){w[l]=w[l]||[];w[l].push({'gtm.start':new Date().getTime(),event:'gtm.js'});var f=d.getElementsByTagName(s)[0],j=d.createElement(s),dl=l!='dataLayer'?'&l='+l:'';j.async=true;j.src='https://www.googletagmanager.com/gtm.js?id='+i+dl;f.parentNode.insertBefore(j,f);})(window,document,'script','dataLayer','GTM-K279D39R'); Browse Preprints In Review Journals COVID-19 Preprints AJE Video Bytes Research Tools Research Promotion AJE Professional Editing AJE Rubriq About Preprint Platform In Review Editorial Policies Our Team Advisory Board Help Center Sign In Submit a Preprint Cite Share Download PDF Research Article Socio-demographic determinants of sexual inactivity among reproductive married women in Bangladesh: Evidence of BDHS data 2022 Md. Aslam Hossain, A. M. Mujahidul Islam, Md. Zahidul Islam, Md. Shariful Islam, and 2 more This is a preprint; it has not been peer reviewed by a journal. https://doi.org/ 10.21203/rs.3.rs-5823750/v1 This work is licensed under a CC BY 4.0 License Status: Published Journal Publication published 10 Mar, 2026 Read the published version in Reproductive Health → Version 1 posted 10 You are reading this latest preprint version Abstract Background: Sexual intercourse is integral part of physical well-being health especially in married couple's life. Unhappiness and life dissatisfaction can be positively influenced by sexual inactivity. Sexual inactivity has recently been subject to increased scrutiny from public health perspectives. This project targeted to examine the socio-demographic determinants of sexual inactivity in Bangladeshi women of childbearing age. Method: Data from the most recent Bangladesh Health and Demographic Survey (BDHS) conducted in 2022 was utilized. Our study was considered a two-stage stratified sampling technique and cross-sectional design. Sexual inactivity was defined as no sexual frequency among reproductive women in the last month. The analysis included 14650 reproductive women aged 15–49 years. The associations between sexual inactivity and exposure variables were evaluated using the Pearson's Chi-square test, and the prediction model considered the multivariable logistic regression. Results: The prevalence of sexual inactivity among reproductive women in Bangladesh was 6.72% (95% CI: 0.93-0.94). The likelihood of sexual inactivity was more pointedly among married women who live in the Dhaka region, Khulna region, and Sylhet region [p<0.05] compared to the Chittagong region. Women who had household heads [p<0.001] were significantly less likely to report sexual inactive than those who had no household heads. The odds of sexual inactivity were lower among women who had the age of ≥40 years [p<0.001] compared to their counterparts. Women whose height below <164cm were [p<0.001] had significantly higher chances of sexual inactivity. Sexually inactive significantly higher odds of being women who had a husband/partner are age of 30- 40 years [p=0.036]. Unemployment husband/partner's (p=0.014) were less likely to be sexually inactive. Conclusion: Demographic factors such as women's age significantly affect sexual inactivity (SI) among the women in their reproductive age in Bangladesh. To overcome SI problem government and nongovernmental organization must take effective measures to improve women education level, reproductive health-care service, including sexual health of childbearing age. Sexual intercourse health Sexual inactivity reproductive women age husband Figures Figure 1 Figure 2 Background Sexuality, governed by the neurological, vascular, and endocrine systems, is crucial for well-being[ 1 ]. Despite its connection to general satisfaction and increased longevity, many individuals worldwide find themselves grappling with sexual inactivity or dysfunctions impacting their quality of life [ 2 ]. Marital satisfaction depends on the couple's sexuality. Inevitably, any marriage can face sexual activity problems. The problem of sexuality causes conflicts of marital satisfaction which ultimately lead to divorce ([ 3 ],[ 4 ]). Participation in sexual activity manifests potential health merits, encompassing the reduction of heart rate and blood pressure, along with stress alleviation through the release of oxytocin ([ 5 ], [ 6 ]). Sexual inactivity may be caused by diminished sexual desire to the absence of arousal, lubrication, orgasm, and overall satisfaction among reproductive-aged women [ 3 ]. Conversely, sexual activity contributes to pain reduction, enhanced function of the immune system, and sleep improvement [ 7 ]. Lubrication insufficiency, dyspareunia, vaginismus, and anorgasmia are the causes of women's sexual dysfunction [ 8 ]. It's notable that there's a general decrease in both the frequency and functionality of sexual activity, especially among individuals after the age of 45 years in men and after the age of 35 years in women, with women being more affected [ 9 ]. The landscape of sexual activity is shaped by a range of factors, including socio-demographic, medical, behavioral, psychological, religious, and lifestyle elements ( [ 10 ],[ 11 ], [ 12 ], [ 13 ]). In married couples, sociocultural beliefs, physical health duration of the marriage, and mental well-being are influenced by the intricate fabric of the marital life which determines the frequency of sexual activity [ 14 ]. Sexual inactivity among women is associated with several influential factors including obesity, physical inactivity, tobacco smoking [ 2 ], depression, and the presence of chronic diseases [ 3 ], older age, lowest education, younger menarche, [ 10 ] less favorable socioeconomic conditions, and underweight [ 15 ]. In Bangladesh, despite decades of progress in public health, deeply entrenched cultural stigma and taboos surrounding sexual health continue to constrain help-seeking behaviors and hinder research efforts in this domain ([ 16 ], [ 17 ]). While previous studies have explored sexual dysfunction in specific groups, such as post-menopausal women and those with type II diabetes mellitus ([ 18 ], [ 19 ]) a broader understanding is lacking. One study focused on the frequency of sexual intercourse among residents of Bangladesh [ 14 ], and another delved into the knowledge, attitudes, and reproductive health performance practices among older teenage girls [ 20 ]. However, none of these studies covered the entire nation or investigated the factors influencing sexual inactivity among women of reproductive age. Despite the growing recognition of sexual health's importance, there's still a lack of comprehensive studies on why some women in Bangladesh are sexually inactive. This national survey aims to fill this gap, offering a detailed understanding of the social and demographic factors affecting sexual inactivity patterns among reproductive Bangladeshi married women. Methods Data source Our investigation adopts secondary data of cross-sectional design sourced from the Bangladesh Demography and Health Survey (BDHS) of 2022. This survey, conducted nationwide, encompasses the total populace dwelling within the borders of Bangladesh [ 21 ]. The BDHS employs a sampling technique employing a two-phase approach, stratified by clusters, with enumeration areas (EAs) forming the primary units of selection, followed by household (HH) sampling within chosen clusters. In the first stage, EAs are chosen, followed by the selection of HHs from each EA in the second stage, as per the criteria established by the DHS team. It is anticipated that around 30078 interviews will be completed with females between the ages of 15 and 49. Our study utilizes the women's data file from the survey, which provides comprehensive information on the sampling design, encompassing both the sample framework and its structure and implementation details [ 22 ]. Exclusion criteria Among the 30078 reproductive women, a total of 15428 women were omitted from the analysis, which included the following criteria: 12061 missing data; 2000 currently not staying with husband; 946 pregnancy case; 421 exclusive breastfeeding mothers. After excluding, a total of 14650 reproductive married women sample were considered for the final phase of the analysis Outcome variable In BDHS 2022 survey, the frequency of sexual intercourse was asked among the married women in their reproductive age, which appeared as "About how times did you have sex during the last month?" Based on the frequency of sexual activity, the outcome variable “Sexual Inactivity” was measured. Sexual inactivity (SI) was classified two classes such as (i) Yes (no sexual activity during the last month, coded as "0") and (ii) No (at least one or more sexual activity during the defined period, coded as "1"). Exposure variable Based on the literatures, and cultural contexts, the following variables were included from the dataset that were hypothesized to be linked to the sexual inactivity: including geographical region (Barisal, Chittagong, Dhaka, Khulna, Mymensingh, Rajshahi, Rangpur, Sylhet), place of residence (urban, rural), religion (Muslim, Non-Muslim), sex of household head (male, female), watching television (no, yes), usage of internet last 12 month (no, yes), wealth status (poorest, poorer, middle, richer, richest), women current age (years) (below 30, 30–40, above 40), women’s education level (less than high school, high school, more than high school), women’s height (< 164 cm, ≥ 164 cm), women’s age at first intercourse (years) (< 15, 15–17, ≥ 18), women’s occupation (homemakers, service holder, others), women continue studies after marriage (no, yes), husband's age (years) (below 30, 30–40, above 40), husband's education level (no education, primary, secondary, higher), husband's occupation (unemployed, farmer/labour, business, service holder). Most of the above covariates have been acknowledged from the prior studies([ 2 ], [ 5 ] and [ 23 ]). Statistical analysis All investigations were performed by using Stata v14.2 (StataCorp, CollegeStation, TX, USA). We acknowledged the implementation of the 'Svy' command for adapting the cluster sampling design and weights. Before the formal data analysis, we cleaned the dataset by eliminating instances with missing data and redefining variables as necessary. Descriptive statistics were executed to assess the rate of sexual inactivity among females between the ages of 15 and 49. Either Pearson's chi-square test was conducted for comparative analysis of the prevalence of sexual inactivity among categorical variables. The value of test-statistic was: $$\:\left[{\:\chi\:}^{2}=\sum\:_{i=1}^{r}\sum\:_{j=1}^{c}\frac{{({O}_{i,j}-{E}_{i,j})}^{2}}{{E}_{i,j}}\right]$$ where, \(\:{\chi\:}^{2}\) =Pearson's cumulative test statistic, which asymptotically approaches a \(\:{\chi\:}^{2}\) distribution, \(\:{O}_{i,j}\) =an observed frequency, \(\:\:{E}_{i,j}\) =an expected (theoretical) frequency, asserted by the null hypothesis, n = the number of cells in the table. Fitting the model of "independence" reduces the number of degrees of freedom by p=r+c-1. Where r is the number of levels for one categorical variable, and c is the number of levels for the other categorical variable. Besides, we assessed the associated baseline factors of sexual inactivity. The underlying multiple logistic regression model was: $$\:Log\left(\frac{P}{1-P}\right)={\beta\:}_{0}+{\beta\:}_{1}{X}_{1}+{\beta\:}_{2}{X}_{2}+{\beta\:}_{3}{X}_{3}+{\beta\:}_{4}{X}_{4}+{\beta\:}_{5}{X}_{5}+{\beta\:}_{6}{X}_{6}+{\beta\:}_{7}{X}_{7}+{\beta\:}_{8}{X}_{8}+{\beta\:}_{9}{X}_{9}+{\beta\:}_{10}{X}_{10}$$ Finally, the logistic regression model was used to calculate the unadjusted and adjusted odds ratio (OR) with 95% confidence intervals and determine the association between the study variable and sexual inactivity. The final model underwent testing for collinearity. Statistical tests were considered two-sided, and significance was inferred at a p-value < 0.05. Results During the survey period in Bangladesh, the incidence of being sexually inactive married women of childbearing age was 6.72%. Figure 1 shows the frequency of sexual inactivity among reproductive married women in Bangladesh by their age group. It was noted that the highest number (21.3%) of sexually inactive women was in 45–49 years followed by 40–44 years (16.7%), 35–39 years (15.6%), 30–34 years (13.2%) and 25–29 years (10.6%). Figure 2 shows the weighted prevalence of sexual inactivity among reproductive married women per household wealth index. Approximately one-quarter 7.33% (95% CI: 6.42–8.37) of reproductive married women in the lowest wealth quintile had been sexually inactive, compared to 6.1% (95% CI: 5.26–7.02) of those in the richest quintile. The graph also indicates that the rate of SI gradually decreases as wealth status improves from the middle to the richest quintile. Prevalence of sexual inactivity The highest prevalence of sexual inactivity was identified in households primarily headed by females, with a striking figure of 19.51%. Notably, a significant prevalence was observed among women whose husbands were unemployed (10.22%) or aged over 40 (8.87%). Additionally, a higher prevalence of sexual inactivity was recorded among reproductive married women aged over 40 (10.17%), those have less than high school education (7.22%), residents of the Barisal region (9.02%), those who initiated sexual activity before the age of 15 (7.83%), individuals watching television (6.29%) or usage of the internet last 12 Months (5.52%), and those women height below average (6.16%) [Table 1 ]. Table 1 shows that factors such as geographical region, sex of household head, women's age, women's level of education, current age of husband's, and husband's occupation are significantly (p < 0.001) associated with sexual inactivity among reproductive married women. Additionally, the likelihood of sexual inactivity is significantly (p < 0.05) higher among reproductive married women who have been watching television, using the internet for the last 12 Months, women's education level, women's height, and women's age at first intercourse. Table 1 Prevalence of sexual inactivity by individual and household level of socio-demographic characteristics among reproductive married women in Bangladesh Study variables N (%) Sexual Inactivity χ 2 -values ( p-values) Weighted Prevalence (95% CI) Yes (%) No (%) Geographical region 37.54 (< 0.001) Barisal 1496 (10.21) 135 (9.02) 1361 (90.98) 9.74 (8.00–12.00) Chittagong 1894 (12.93) 144 (7.60) 1750 (92.40) 7.81 (6.79–8.97) Dhaka 2200 (15.02) 123 (5.59) 2077 (94.41) 5.56 (4.87–6.35) Khulna 1998 (13.64) 108 (5.41) 1890 (94.59) 5.96 (4.26–6.30) Mymensingh 1643 (11.22) 99 (6.03) 1544 (93.97) 5.96 (4.73–7.48) Rajshahi 2038 (13.91) 127 (6.23) 1911 (93.77) 6.42 (5.45–7.56) Rangpur 1923 (13.13) 162 (8.42) 1761 (91.58) 8.73 (7.52–10.12) Sylhet 1458 (9.95) 86 (5.90) 1372 (94.10) 5.91 (4.45–7.8) Place of Residence 1.79 (0.180) Urban 5308 (36.23) 647 (6.93) 8695 (93.07) 6.1 (5.43–6.86) Rural 9342 (63.77) 337 (6.35) 4971 (93.65) 6.94 (6.46–7.44) Religion 0.16 (0.684) Muslim 12952 (88.41) 866 (6.69) 12086 (93.31) 6.56 (6.14-7.00) Non-Muslim 1698(11.59) 118 (6.95) 1580 (93.05) 7.78 (6.56–9.22) Sex of household head 188.14 (< 0.001) Male 13963 (95.31) 850 (6.09) 13113 (95.95) 6.09 (5.70–6.5) Female 687 (4.69) 134 (19.51) 553 (80.49) 19.1 (16.24–22.15) Watching television 5.72 (0.017) No 6226 (42.50) 454 (7.29) 5772 (92.71) 7.22 (6.60–7.89) Yes 8424 (57.50) 530 (6.29) 7894 (93.71) 6.29 (5.79–6.83) Usage of the internet last 12 Months 9.98 (0.002) No 11281 (77.00) 798 (7.07) 10483 (92.93) 7.11 (6.65–7.61) Yes 3369 (23.00) 186 (5.52) 3183 (94.48) 5.29 (4.59–6.1) Wealth status 3.88 (0.423) Poorest 2754 (18.80) 198 (7.19) 2556 (92.81) 7.33 (6.42–8.37) Poorer 2885 (19.69) 197 (6.83) 2688 (93.17) 6.83 (5.98–7.8) Middle 2920 (19.93) 207 (7.09) 2713 (92.91) 7.10 (6.24–8.08) Richer 2981 (20.35) 192 (6.44) 2789 (93.56) 6.13 (5.33–7.05) Richest 3110 (21.23) 190 (6.11) 2920 (93.89) 6.08 (5.26–7.02) Women's current age (years) 79.13 (< 0.000) Median (IQR) 33.0 (26.0–40.0) 35.0 (25.0–43.0) 33.0 (26.0–40.0) Below 30 5530 (37.75) 326 (5.90) 5204 (94.10) 6.01 (5.42–6.66) 30–40 5895 (40.24) 330 (5.6) 5565 (94.40) 5.63 (5.07–6.26) above 40 3225 (22.01) 328 (10.17) 2897 (89.83) 9.83 (8.84–10.92) Women education level 9.53 (0.009) Less than high school 4100 (32.76) 296 (7.22) 3804 (92.78) 6.86 (6.12–7.67) High school 6410 (51.22) 398 (6.21) 6012 (93.79) 6.41 (5.84–7.03) More than high school 2005 (16.02) 105 (5.24) 1900 (94.76) 4.97 (4.06–6.07) Women height 6.60 (0.010) Median (IQR) 151.5 (147.9-155.3) 151.2 (147.4-154.6 151.6 (148.0-155.3) Below average (< 164 cm) 6951 (47.45) 428 (6.16) 6523 (93.84) 6.02 (5.48–6.61) Average/above (≥ 164 cm) 7699 (52.55) 556 (7.22) 7143 (92.78) 7.29 (6.73–7.89) Women age at first intercourse (years) 10.95 (0.004) Median (IQR) 16.0 (14.0–18.0) 16.0 (14.0–18.0) 16.0 (14.0–18.0) < 15 3970 (27.10) 311 (7.83) 3659 (92.17) 7.53 (6.76–8.39) 15–17 5965 (40.72) 380 (6.37) 5585 (93.63) 6.58 (5.98–7.23) ≥ 18 4715 (32.18) 293 (6.21) 4422 (93.79) 6.08 (5.41–6.81) Women occupation 7.29 (0.063) Homemakers 12285 (83.86) 847 (6.89) 11438 (93.11) 6.92 (6.48–7.39) Business 1001 (6.83) 54 (5.39) 947 (94.61) 5.12 (3.92–6.66) Service Holder 326 (2.23) 13 (3.99) 313 (96.01) 3.22 (1.74–5.88) Others 1037 (7.08) 70 (6.75) 967 (93.25) 6.56 (5.23–8.21) Women continue studies after marriage 0.06 (0.805) No 7687 (82.12) 504 (6.56) 7183 (93.44) 6.64 (6.10–7.21) Yes 1674 (17.88) 107 (6.39) 1567 (93.61) 6.19 (5.10–7.49) Husband's current age (years) 102.69 (< 0.000) Median (IQR) 40.0 (33.0–49.0) 45.0 (34.0–54.0) 40.0 (33.0–48.0) Below 30 2220 ( 15.15) 136 (6.13) 2084 (93.87) 6.07 (5.16–7.16) 30–40 5610 (38.29) 243 (4.33) 5367 (95.67) 4.41 (3.90–4.98) above 40 6820 (46.55) 605 (8.87) 6215 (91.13) 8.81 (8.15–9.51) Husband's education level 3.49 (0.321) No education 3384 (23.29) 215 (6.35) 3169 (93.65) 6.39 (5.62–7.26) Primary 4206 (28.95) 259 (6.16) 3947 (93.84) 6.19 (5.5–6.95) Secondary 4371 (30.09) 268 (6.13) 4103 (93.87) 6.13 (5.46–6.88) Higher 2566 (17.66) 135 (5.26) 2431 (94.74) 5.08 (4.27–6.03) Husband's occupation 22.06 (< 0.001) Unemployed 499 (3.44) 51 (10.22) 448 (89.78) 9.36 (7.07–12.3) Farmer/Labour 7470 (51.45) 467 (6.25) 7003 (93.75) 6.20 (5.69–6.77) Business 5493 (37.84) 311 (5.66) 5182 (94.34) 5.82 (5.22–6.49) Service Holder 1056 (7.27) 47 (4.45) 1009 (95.55) 4.21 (3.13–5.64) Notes: ‘N, total’; ‘%, percentages’ Socio-demographic factors influencing sexual inactivity Table 2 highlighted the significant socio-demographic determinants related with sexual inactivity among Bangladeshi married women of childbearing age. Notably, geographical region, sex of the household head, women's age, women height, husband's age, and husband's occupation were significantly connected with sexual inactivity. The likelihood of sexual inactivity was significantly elevated among reproductive married women who residing in the Dhaka region (AOR = 1.47, 95% CI = 1.09–1.97, p < 0.011) or Khulna region (AOR = 1.59, 95% CI = 1.17–2.16, p < 0.003) or Sylhet region to compared of the Chittagong region residents (AOR = 1.46, 95% CI = 1.04–2.04, p < 0.028). Conversely, female-headed households exhibited markedly reduced odds of sexual inactivity (AOR = 0.37, 95% CI = 0.28–0.48, p < 0.001). Additionally, women aged above 40 displayed significantly lower odds of sexual inactivity compared to women below 30 (AOR = 0.57, 95% CI = 0.42–0.78, p < 0.001). Reproductive married women whose height < 164 cm had significantly higher odds of sexual inactivity (AOR = 1.33, 95% CI = 1.14–1.56, p < 0.001). Moreover, husband's aged 30–40 years showed significantly increased odds of sexual inactivity in comparison to those who were below 30 years (AOR = 1.30, 95% CI = 1.02–1.67, p = 0.036). Likewise, unemployed husbands had substantially lower odds of sexual inactivity (AOR = 0.56, 95% CI = 0.35–0.89, p < 0.014) [Table 2 ]. Table 2 The impact of socio-demographic factors on sexual inactivity among married women of childbearing age in Bangladesh. Study variables Unadjusted Adjusted UOR (95% CI) p-values AOR (95% CI) p-values Geographical region Barisal 0.83 (0.65–1.06) 0.135 0.84 (0.63–1.11) 0.211 Chittagong Reference Reference Dhaka 1.38 (1.08–1.78) 0.010 1.47 (1.09–1.97) 0.011 Khulna 1.44 (1.11–1.86) 0.006 1.59 (1.17–2.16) 0.003 Mymensingh 1.28 (0.98–1.67) 0.065 1.38 (0.99–1.90) 0.051 Rajshahi 1.24 (0.97–1.58) 0.090 1.24 (0.92–1.67) 0.148 Rangpur 0.89 (0.71–1.13) 0.350 0.88 (0.67–1.17) 0.392 Sylhet 1.31 (0.99–1.73) 0.054 1.46 (1.04–2.04) 0.028 Sex of household head Male Reference Reference Female 0.27 (0.22–0.33) < 0.001 0.37 (0.28–0.48) < 0.001 Watching television No Reference Reference Yes 1.17 (1.03–1.33) 0.017 1.14 (0.97–1.34) 0.107 Usage of internet last 12 months No Reference Reference Yes 1.30 (1.10–1.53) 0.002 1.11 (0.91–1.37) 0.302 Women current age (years) Below 30 Reference Reference 30–40 1.06 (0.90–1.24) 0.495 1.04 (0.81–1.33) 0.744 above 40 0.55 (0.47–0.65) < 0.001 0.57 (0.42–0.78) < 0.001 Women education level Less than high school Reference Reference High school 1.17 (1.01–1.37) 0.042 0.99 (0.83–1.19) 0.970 More than high school 1.41 (1.12–1.77) 0.003 1.16 (0.85–1.58) 0.337 Women height Below average (< 164 cm) 1.19 (1.04–1.35) 0.010 1.33 (1.14–1.56) < 0.001 Average or above (≥ 164 cm) Reference Reference Women age at first intercourse (years) < 15 0.78 (0.66–0.92) 0.003 0.87 (0.69–1.08) 0.213 15–17 0.97 (0.83–1.14) 0.741 1.05 (0.86–1.28) 0.610 ≥ 18 Reference Reference Husband's current age (years) Below 30 Reference Reference 30–40 1.44 (1.16–1.79) 0.001 1.30 (1.02–1.67) 0.036 above 40 0.67 (0.55–0.81) < 0.001 1.03 (0.74–1.42) 0.874 Husband's occupation Unemployed 0.41 (0.27–0.62) < 0.001 0.56 (0.35–0.89) 0.014 Farmer/Labour 0.69 (0.51–0.95) 0.022 0.81 (0.57–1.14) 0.224 Business 0.78 (0.57–1.06) 0.114 0.84 (0.59–1.19) 0.336 Service Holder Reference Reference Notes: ‘UOR, unadjusted odd ratios’; ‘CI, confidence interval’; ‘AOR, adjusted odd ratios’ Discussion A nationwide survey of BDHS data from 2022 was used for this research. We are assessed 6.72% of reproductive married women sexually inactive in the past month. Arafat et al. study revealed that sexual inactivity among married couples of Bangladesh is 5.6%. However, our study depicted that sexual inactivity among married women in Bangladesh is increasing comparing the prior study of Bangladesh. Several high-income countries such as Finland, [ 24 ] Australia, [ 25 ] and United States[ 5 ] are increased the sexual inactivity among married women. Ascorbic acid develops vascular function and raises oxytocin release. Besides, ascorbic acid declines stress reactivity and approaches anxiety and prolactin release. These relevant procedures are increased the frequency of women sexual intercourse [ 26 ]. The fundamental part of life is a Sexual task. A robust positive relationship exists between sexual behavior and the excellence of life [ 27 ]. In a British cohort study reported that married women lessen the intercourse for declined the quality of sex life [ 28 ]. The local build of environmental characteristics significantly influences the health outcomes [ 29 ]. Our analysis shows the geographical region was significantly related with sexually inactive. Women who live in Dhaka region or Khulna region or Sylhet region were more prone to sexual inactive comparing Chittagong region residents. Women who live in urban areas were significantly related to higher sexual intercourse frequency compared to rural women [ 30 ]. Besides, an Egyptian study reported that the purpose of intercourse among urban women was to have pleasure for themselves and their husbands and more initiation of coitus [ 31 ]. A household head female designates a woman in charge of handling the family. As a result, she gets the power of separation, immigration, and divorce [ 32 ]. intensely in developing countries had increased the number of female-headed households [ 33 ]. Low-income and physical disorders and mental, neurological, etc. problems faced by female-headed households [ 34 ]. Female-headed households involve many risk factors upsetting their sexual life [ 35 ]. Women-headed households face the challenge of intra-family tension [ 36 ]. Where, women in the high-stress group had lower levels of genital sexual arousal [ 37 ]. Our research depicted that households' female-headed are more chance of sexually inactive than male-headed households. Our investigation is consistent with a qualitative study in Iran [ 35 ]. Partner balanced intimacy relationship can promote mental and physical health [ 38 ]. Consistently, both men and women in sexual activity decrease with age's [ 39 ]. The incidence of sexual activity among women is lower than among men [ 40 ]. Testosterone starts to slowly decrease with age. The traditional advantage of testosterone leads to sexual behavior. It effects on bone density, obesity, insulin resistance, prostate disease, and aggression etc. [ 41 ]. Approximately, our study shows one in fifteen women were sexually inactive between ages 15 and 49 years. Additionally, our study revealed reproductive married women aged above 40 years are significantly associated with sexual inactivity. Our simple regression analysis revealed that women whose husbands aged above 40 years are less likely to be sexually inactive. Our result is contradictory to the Iranian analysis. Additionally, Iranian analysis showed that female sexual dysfunction was significantly more likely to be those who had husbands aged 40 years or older [ 42 ].Besides, above 40 years men and women around one in eleven and one in ten are reported being sexually inactive. These findings clarified the higher likelihood sexual inactivity of women who are living partner's current age 30–40 years. For incidence of sexual inactivity, our study is consistent with previous studies ([ 23 ], [ 40 ]). The serum concentrations of testosterone are increased by boron supplementation [ 43 ]. The maximum amounts of boron contained in fruits, tubers, coffee, milk, dried and cooked beans, potatoes, legumes, etc. [ 44 ]. Body shape for women is a contributing factor to sexual attraction [ 45 ]. Additionally, height plays a significant role in human companion preferences [ 46 ]. Mid-range women's leg-to-body ratios were observed as extremely attractive [ 47 ]. Besides, women's height has been proven to be an element of reproductive accomplishment [ 48 ]. Our study depicted that reproductive married women were significantly more likely to be sexually inactive whose height was shorter than average. Our investigation is consistent with a cross-sectional probability sample survey data study in Britain [ 40 ]. Body figure and stature can also reflect overall fitness that may be related to poor sexual function [ 49 ]. Women who have higher body appreciation positively predicted better sexual function [ 50 ]. The advent of first sex is essential course of good health life [ 51 ]. Early first sex is associated with higher rates of current mental distress and smoking among adult women ([ 52 ], [ 53 ]). The problem of depression and marriage-related difficulties are faced the later of life who initiation of sexual intercourse during adolescence [ 54 ]. Besides, Senn et. al study depicted that sexual abuse is a strong forecaster of early sexual initiation [ 55 ]. Our unadjusted odds ratio showed that women more likely to sexual inactive who complete first intercourse at early age. The public programs and family life education should concentration on sexual health elevation considering the physical and psychosocial changes that can prevent perilous sexual behaviors among adolescent girls [ 56 ]. Experiential research shows that the condition of unemployment has negative effects on health [ 57 ]. Unemployed young men who live with their parents are less feasible in dating markets and less equipped for sensitive intimacy, the logic follows that they will be less able to obtain healthy loving and sexual relations with participants of the opposite sex ([ 58 ][ 59 ]). Many studies depict that unemployment men are more distressed [ 60 ]. But, an energetic sex life is positively associated with mental and bodily health [ 6 ]. Pitta et.al study showed that depressive symptoms are strongly associated with erectile dysfunction [ 61 ]. The present study finds substantiation that unemployed husbands/partners have more chance to be sexually inactive compared to employed husbands/partners. Several realistic studies show consistently that unemployed men are more likely to abstain from sexual intercourse ([ 5 ], [ 62 ]). So, unemployed men can do physical exercise which has a positive impact on sexual function in men and promotes sexual health [ 63 ]. Policy Implications The results of this study hold noteworthy policy implications for public health efforts in Bangladesh. Policymakers should prioritize sexual health education and awareness campaigns that address the socio-cultural taboos surrounding discussions on sexual health. Efforts should be made to promote open communication between couples and encourage help-seeking behaviors for sexual health issues. Furthermore, policies aimed at improving access to education, particularly for women, may empower people to make knowledgeable decisions about their sexual and reproductive well-being. Additionally, policies targeting poverty alleviation and employment generation, especially in rural areas, may indirectly contribute to reducing sexual inactivity by addressing socio-economic disparities. Strengths and limitations A key strength of this study was the use of a nationally representative sample with women as participants. Utilizing nationally adopted and internationally validated surveys such as the BDHS enhanced the robustness of our findings. Our study emphasized the significance of making valid statistical inferences for continuous variables. Although this study offers valuable visions, it is important to recognize numerous limitations. The study's cross-sectional design hinders drawing causal conclusions, emphasizing the need for longitudinal studies to determine the temporal connections between socio-demographic factors and sexual inactivity. Secondly, the dependence on data reported by individuals themselves may engender remember bias or social allure bias, thereby potentially compromising the veracity of responses concerning sexual activity. Additionally, the omission of specific cohorts, for example unmarried or divorced women, limits the extendibility or applicability of the conclusions to the broader populace. Moreover, the study's focus on socio-demographic factors may fail to notice other latent contributors to sexual inactivity's, such as psychological or relational factors. Recommendations In light of the discoveries gleaned from this investigation, it is advisable that interventions and programs designed at addressing sexual inactivity among Bangladeshi women must consider the socio-demographic factors identified as significant determinants. Specifically, efforts should focus on regions with higher prevalence rates of sexual inactivity, such as the Sylhet region. Strategies to empower women, particularly those in female-headed households, may help mitigate sexual inactivity. Additionally, targeted interventions should be designed to support women who marry at younger ages, as they are at increased risk of sexual inactivity. Furthermore, initiatives to promote economic opportunities for men, particularly those aimed at reducing unemployment, may contribute to reducing sexual inactivity among married couples. Conclusion In conclusion, this nationwide survey offers valuable visions into the socio-demographic determinants of sexual inactivity among reproductive Bangladeshi married women. The results highlight the imperative for comprehensive strategies in tackling sexual health concerns, acknowledging the intricate interplay of socio-demographic elements. Efforts to empower women, enhance economic opportunities, and promote open communication within marital relationships are crucial for mitigating sexual inactivity and improving the overall well-being of women in Bangladesh. Future research should explore additional factors influencing sexual activity patterns and evaluate the effectiveness of targeted interventions in addressing sexual health disparities. Declarations Author Contributions MAH conceptualized the study design. MAH had all access to the data and validation of the statistical analysis. MAH and MSI did the formal analysis. MAH, MZI and AMMI drafting the original manuscript. MAH, MZI, AMMI, MSI, MA and MAR critically reviewed the manuscript. MAH supervised the whole study. Funding: We don’t have any funding from specific grant agencies in the public or commercial sectors. Data Availability Statement: The recent survey datasets were constructed for analysis of this study. Data are open-access sources available online and accessible to the public: https://dhsprogram.com/data/dataset/Bangladesh_Standard-DHS_2022.cfm?flag=0 Acknowledgments: The writers are grateful for accessing data from the Demographic and Health Surveys (DHS) Program and the Ministry of Health and Family Welfare, Dhaka, Bangladesh. Conflicts of Interest: There is no conflict of interest. Ethics approval: BDHS for 2022 is a cross-sectional secondary publicly accessible data approved by the Ministry of Health and Family Welfare. Consequently, the current study was released from ethics support. References A. Avasthi, S. Grover, and T. S. S. Rao, “Clinical practice guidelines for management of sexual dysfunction,” Indian J. Psychiatry , vol. 59, no. Suppl 1, pp. S91–S115, 2017. B. S. Christensen, M. Grønbæk, B. V Pedersen, C. Graugaard, and M. Frisch, “Associations of unhealthy lifestyle factors with sexual inactivity and sexual dysfunctions in Denmark,” J. Sex. 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Cite Share Download PDF Status: Published Journal Publication published 10 Mar, 2026 Read the published version in Reproductive Health → Version 1 posted Editorial decision: Revision requested 14 Apr, 2025 Reviews received at journal 13 Apr, 2025 Reviews received at journal 07 Apr, 2025 Reviewers agreed at journal 07 Apr, 2025 Reviewers agreed at journal 02 Apr, 2025 Reviews received at journal 29 Mar, 2025 Reviewers agreed at journal 26 Mar, 2025 Reviewers invited by journal 26 Mar, 2025 Submission checks completed at journal 25 Mar, 2025 First submitted to journal 24 Mar, 2025 You are reading this latest preprint version Research Square lets you share your work early, gain feedback from the community, and start making changes to your manuscript prior to peer review in a journal. As a division of Research Square Company, we’re committed to making research communication faster, fairer, and more useful. We do this by developing innovative software and high quality services for the global research community. Our growing team is made up of researchers and industry professionals working together to solve the most critical problems facing scientific publishing. Also discoverable on Platform About Our Team In Review Editorial Policies Advisory Board Help Center Resources Author Services Accessibility API Access RSS feed Manage Cookie Preferences © Research Square 2026 | ISSN 2693-5015 (online) Privacy Policy Terms of Service Do Not Sell My Personal Information {"props":{"pageProps":{"initialData":{"identity":"rs-5823750","acceptedTermsAndConditions":true,"allowDirectSubmit":false,"archivedVersions":[],"articleType":"Research Article","associatedPublications":[],"authors":[{"id":434439951,"identity":"7c31a1fc-ed93-4522-9734-dd7c95dfb886","order_by":0,"name":"Md. 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Despite its connection to general satisfaction and increased longevity, many individuals worldwide find themselves grappling with sexual inactivity or dysfunctions impacting their quality of life [\u003cspan citationid=\"CR2\" class=\"CitationRef\"\u003e2\u003c/span\u003e]. Marital satisfaction depends on the couple's sexuality. Inevitably, any marriage can face sexual activity problems. The problem of sexuality causes conflicts of marital satisfaction which ultimately lead to divorce ([\u003cspan citationid=\"CR3\" class=\"CitationRef\"\u003e3\u003c/span\u003e],[\u003cspan citationid=\"CR4\" class=\"CitationRef\"\u003e4\u003c/span\u003e]). Participation in sexual activity manifests potential health merits, encompassing the reduction of heart rate and blood pressure, along with stress alleviation through the release of oxytocin ([\u003cspan citationid=\"CR5\" class=\"CitationRef\"\u003e5\u003c/span\u003e], [\u003cspan citationid=\"CR6\" class=\"CitationRef\"\u003e6\u003c/span\u003e]). Sexual inactivity may be caused by diminished sexual desire to the absence of arousal, lubrication, orgasm, and overall satisfaction among reproductive-aged women [\u003cspan citationid=\"CR3\" class=\"CitationRef\"\u003e3\u003c/span\u003e]. Conversely, sexual activity contributes to pain reduction, enhanced function of the immune system, and sleep improvement [\u003cspan citationid=\"CR7\" class=\"CitationRef\"\u003e7\u003c/span\u003e].\u003c/p\u003e \u003cp\u003eLubrication insufficiency, dyspareunia, vaginismus, and anorgasmia are the causes of women's sexual dysfunction [\u003cspan citationid=\"CR8\" class=\"CitationRef\"\u003e8\u003c/span\u003e]. It's notable that there's a general decrease in both the frequency and functionality of sexual activity, especially among individuals after the age of 45 years in men and after the age of 35 years in women, with women being more affected [\u003cspan citationid=\"CR9\" class=\"CitationRef\"\u003e9\u003c/span\u003e]. The landscape of sexual activity is shaped by a range of factors, including socio-demographic, medical, behavioral, psychological, religious, and lifestyle elements ( [\u003cspan citationid=\"CR10\" class=\"CitationRef\"\u003e10\u003c/span\u003e],[\u003cspan citationid=\"CR11\" class=\"CitationRef\"\u003e11\u003c/span\u003e], [\u003cspan citationid=\"CR12\" class=\"CitationRef\"\u003e12\u003c/span\u003e], [\u003cspan citationid=\"CR13\" class=\"CitationRef\"\u003e13\u003c/span\u003e]).\u003c/p\u003e \u003cp\u003eIn married couples, sociocultural beliefs, physical health duration of the marriage, and mental well-being are influenced by the intricate fabric of the marital life which determines the frequency of sexual activity [\u003cspan citationid=\"CR14\" class=\"CitationRef\"\u003e14\u003c/span\u003e]. Sexual inactivity among women is associated with several influential factors including obesity, physical inactivity, tobacco smoking [\u003cspan citationid=\"CR2\" class=\"CitationRef\"\u003e2\u003c/span\u003e], depression, and the presence of chronic diseases [\u003cspan citationid=\"CR3\" class=\"CitationRef\"\u003e3\u003c/span\u003e], older age, lowest education, younger menarche, [\u003cspan citationid=\"CR10\" class=\"CitationRef\"\u003e10\u003c/span\u003e] less favorable socioeconomic conditions, and underweight [\u003cspan citationid=\"CR15\" class=\"CitationRef\"\u003e15\u003c/span\u003e].\u003c/p\u003e \u003cp\u003eIn Bangladesh, despite decades of progress in public health, deeply entrenched cultural stigma and taboos surrounding sexual health continue to constrain help-seeking behaviors and hinder research efforts in this domain ([\u003cspan citationid=\"CR16\" class=\"CitationRef\"\u003e16\u003c/span\u003e], [\u003cspan citationid=\"CR17\" class=\"CitationRef\"\u003e17\u003c/span\u003e]). While previous studies have explored sexual dysfunction in specific groups, such as post-menopausal women and those with type II diabetes mellitus ([\u003cspan citationid=\"CR18\" class=\"CitationRef\"\u003e18\u003c/span\u003e], [\u003cspan citationid=\"CR19\" class=\"CitationRef\"\u003e19\u003c/span\u003e]) a broader understanding is lacking. One study focused on the frequency of sexual intercourse among residents of Bangladesh [\u003cspan citationid=\"CR14\" class=\"CitationRef\"\u003e14\u003c/span\u003e], and another delved into the knowledge, attitudes, and reproductive health performance practices among older teenage girls [\u003cspan citationid=\"CR20\" class=\"CitationRef\"\u003e20\u003c/span\u003e]. However, none of these studies covered the entire nation or investigated the factors influencing sexual inactivity among women of reproductive age. Despite the growing recognition of sexual health's importance, there's still a lack of comprehensive studies on why some women in Bangladesh are sexually inactive. This national survey aims to fill this gap, offering a detailed understanding of the social and demographic factors affecting sexual inactivity patterns among reproductive Bangladeshi married women.\u003c/p\u003e"},{"header":"Methods","content":"\u003cdiv id=\"Sec3\" class=\"Section2\"\u003e\n \u003ch2\u003eData source\u003c/h2\u003e\n \u003cp\u003eOur investigation adopts secondary data of cross-sectional design sourced from the Bangladesh Demography and Health Survey (BDHS) of 2022. This survey, conducted nationwide, encompasses the total populace dwelling within the borders of Bangladesh [\u003cspan class=\"CitationRef\"\u003e21\u003c/span\u003e]. The BDHS employs a sampling technique employing a two-phase approach, stratified by clusters, with enumeration areas (EAs) forming the primary units of selection, followed by household (HH) sampling within chosen clusters. In the first stage, EAs are chosen, followed by the selection of HHs from each EA in the second stage, as per the criteria established by the DHS team. It is anticipated that around 30078 interviews will be completed with females between the ages of 15 and 49. Our study utilizes the women\u0026apos;s data file from the survey, which provides comprehensive information on the sampling design, encompassing both the sample framework and its structure and implementation details [\u003cspan class=\"CitationRef\"\u003e22\u003c/span\u003e].\u003c/p\u003e\n\u003c/div\u003e\n\u003ch3\u003eExclusion criteria\u003c/h3\u003e\n\u003cp\u003eAmong the 30078 reproductive women, a total of 15428 women were omitted from the analysis, which included the following criteria: 12061 missing data; 2000 currently not staying with husband; 946 pregnancy case; 421 exclusive breastfeeding mothers. After excluding, a total of 14650 reproductive married women sample were considered for the final phase of the analysis\u003c/p\u003e\n\u003ch3\u003eOutcome variable\u003c/h3\u003e\n\u003cp\u003eIn BDHS 2022 survey, the frequency of sexual intercourse was asked among the married women in their reproductive age, which appeared as \u0026quot;About how times did you have sex during the last month?\u0026quot; Based on the frequency of sexual activity, the outcome variable \u0026ldquo;Sexual Inactivity\u0026rdquo; was measured. Sexual inactivity (SI) was classified two classes such as (i) Yes (no sexual activity during the last month, coded as \u0026quot;0\u0026quot;) and (ii) No (at least one or more sexual activity during the defined period, coded as \u0026quot;1\u0026quot;).\u003c/p\u003e\n\u003ch3\u003eExposure variable\u003c/h3\u003e\n\u003cp\u003eBased on the literatures, and cultural contexts, the following variables were included from the dataset that were hypothesized to be linked to the sexual inactivity: including geographical region (Barisal, Chittagong, Dhaka, Khulna, Mymensingh, Rajshahi, Rangpur, Sylhet), place of residence (urban, rural), religion (Muslim, Non-Muslim), sex of household head (male, female), watching television (no, yes), usage of internet last 12 month (no, yes), wealth status (poorest, poorer, middle, richer, richest), women current age (years) (below 30, 30\u0026ndash;40, above 40), women\u0026rsquo;s education level (less than high school, high school, more than high school), women\u0026rsquo;s height (\u0026lt;\u0026thinsp;164 cm, \u0026ge;\u0026thinsp;164 cm), women\u0026rsquo;s age at first intercourse (years) (\u0026lt;\u0026thinsp;15, 15\u0026ndash;17, \u0026ge;\u0026thinsp;18), women\u0026rsquo;s occupation (homemakers, service holder, others), women continue studies after marriage (no, yes), husband\u0026apos;s age (years) (below 30, 30\u0026ndash;40, above 40), husband\u0026apos;s education level (no education, primary, secondary, higher), husband\u0026apos;s occupation (unemployed, farmer/labour, business, service holder). Most of the above covariates have been acknowledged from the prior studies([\u003cspan class=\"CitationRef\"\u003e2\u003c/span\u003e], [\u003cspan class=\"CitationRef\"\u003e5\u003c/span\u003e] and [\u003cspan class=\"CitationRef\"\u003e23\u003c/span\u003e]).\u003c/p\u003e\n\u003cdiv id=\"Sec7\" class=\"Section2\"\u003e\n \u003ch2\u003eStatistical analysis\u003c/h2\u003e\n \u003cp\u003eAll investigations were performed by using Stata v14.2 (StataCorp, CollegeStation, TX, USA). We acknowledged the implementation of the \u0026apos;Svy\u0026apos; command for adapting the cluster sampling design and weights. Before the formal data analysis, we cleaned the dataset by eliminating instances with missing data and redefining variables as necessary. Descriptive statistics were executed to assess the rate of sexual inactivity among females between the ages of 15 and 49. Either Pearson\u0026apos;s chi-square test was conducted for comparative analysis of the prevalence of sexual inactivity among categorical variables. The value of test-statistic was:\u003c/p\u003e\n \u003cdiv id=\"Equa\" class=\"Equation\"\u003e\n \u003cdiv class=\"mathdisplay\" id=\"FileID_Equa\" name=\"EquationSource\"\u003e$$\\:\\left[{\\:\\chi\\:}^{2}=\\sum\\:_{i=1}^{r}\\sum\\:_{j=1}^{c}\\frac{{({O}_{i,j}-{E}_{i,j})}^{2}}{{E}_{i,j}}\\right]$$\u003c/div\u003e\n \u003c/div\u003e\n \u003cp\u003ewhere,\u003c/p\u003e\n \u003cp\u003e\u003cspan class=\"InlineEquation\"\u003e\u0026nbsp;\u003cspan class=\"mathinline\"\u003e\\(\\:{\\chi\\:}^{2}\\)\u003c/span\u003e\u0026nbsp;\u003c/span\u003e=Pearson\u0026apos;s cumulative test statistic, which asymptotically approaches a \u003cspan class=\"InlineEquation\"\u003e\u003cspan class=\"mathinline\"\u003e\\(\\:{\\chi\\:}^{2}\\)\u003c/span\u003e\u003c/span\u003e distribution,\u003c/p\u003e\n \u003cp\u003e\u003cspan class=\"InlineEquation\"\u003e\u0026nbsp;\u003cspan class=\"mathinline\"\u003e\\(\\:{O}_{i,j}\\)\u003c/span\u003e\u0026nbsp;\u003c/span\u003e=an observed frequency,\u003cspan class=\"InlineEquation\"\u003e\u003cspan class=\"mathinline\"\u003e\\(\\:\\:{E}_{i,j}\\)\u003c/span\u003e\u003c/span\u003e=an expected (theoretical) frequency, asserted by the null hypothesis, n\u0026thinsp;=\u0026thinsp;the number of cells in the table. Fitting the model of \u0026quot;independence\u0026quot; reduces the number of degrees of freedom by p=r+c-1. Where r is the number of levels for one categorical variable, and c is the number of levels for the other categorical variable. Besides, we assessed the associated baseline factors of sexual inactivity. The underlying multiple logistic regression model was:\u003c/p\u003e\n \u003cdiv id=\"Equb\" class=\"Equation\"\u003e\n \u003cdiv class=\"mathdisplay\" id=\"FileID_Equb\" name=\"EquationSource\"\u003e$$\\:Log\\left(\\frac{P}{1-P}\\right)={\\beta\\:}_{0}+{\\beta\\:}_{1}{X}_{1}+{\\beta\\:}_{2}{X}_{2}+{\\beta\\:}_{3}{X}_{3}+{\\beta\\:}_{4}{X}_{4}+{\\beta\\:}_{5}{X}_{5}+{\\beta\\:}_{6}{X}_{6}+{\\beta\\:}_{7}{X}_{7}+{\\beta\\:}_{8}{X}_{8}+{\\beta\\:}_{9}{X}_{9}+{\\beta\\:}_{10}{X}_{10}$$\u003c/div\u003e\n \u003c/div\u003e\n \u003cp\u003e\u003cimg 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\" style=\"width: 886px;\" width=\"886\" height=\"262\"\u003e\u003cbr\u003e\u003c/p\u003e\n \u003cp\u003eFinally, the logistic regression model was used to calculate the unadjusted and adjusted odds ratio (OR) with 95% confidence intervals and determine the association between the study variable and sexual inactivity. The final model underwent testing for collinearity. Statistical tests were considered two-sided, and significance was inferred at a p-value\u0026thinsp;\u0026lt;\u0026thinsp;0.05.\u003c/p\u003e\n\u003c/div\u003e"},{"header":"Results","content":"\u003cp\u003eDuring the survey period in Bangladesh, the incidence of being sexually inactive married women of childbearing age was 6.72%. Figure\u0026nbsp;\u003cspan refid=\"Fig1\" class=\"InternalRef\"\u003e1\u003c/span\u003e shows the frequency of sexual inactivity among reproductive married women in Bangladesh by their age group. It was noted that the highest number (21.3%) of sexually inactive women was in 45\u0026ndash;49 years followed by 40\u0026ndash;44 years (16.7%), 35\u0026ndash;39 years (15.6%), 30\u0026ndash;34 years (13.2%) and 25\u0026ndash;29 years (10.6%).\u003c/p\u003e \u003cp\u003e \u003c/p\u003e \u003cp\u003eFigure \u003cspan refid=\"Fig2\" class=\"InternalRef\"\u003e2\u003c/span\u003e shows the weighted prevalence of sexual inactivity among reproductive married women per household wealth index. Approximately one-quarter 7.33% (95% CI: 6.42\u0026ndash;8.37) of reproductive married women in the lowest wealth quintile had been sexually inactive, compared to 6.1% (95% CI: 5.26\u0026ndash;7.02) of those in the richest quintile. The graph also indicates that the rate of SI gradually decreases as wealth status improves from the middle to the richest quintile.\u003c/p\u003e \u003cp\u003e \u003c/p\u003e\n\u003ch3\u003ePrevalence of sexual inactivity\u003c/h3\u003e\n\u003cp\u003eThe highest prevalence of sexual inactivity was identified in households primarily headed by females, with a striking figure of 19.51%. Notably, a significant prevalence was observed among women whose husbands were unemployed (10.22%) or aged over 40 (8.87%). Additionally, a higher prevalence of sexual inactivity was recorded among reproductive married women aged over 40 (10.17%), those have less than high school education (7.22%), residents of the Barisal region (9.02%), those who initiated sexual activity before the age of 15 (7.83%), individuals watching television (6.29%) or usage of the internet last 12 Months (5.52%), and those women height below average (6.16%) [Table\u0026nbsp;\u003cspan refid=\"Tab1\" class=\"InternalRef\"\u003e1\u003c/span\u003e].\u003c/p\u003e \u003cp\u003eTable\u0026nbsp;\u003cspan refid=\"Tab1\" class=\"InternalRef\"\u003e1\u003c/span\u003e shows that factors such as geographical region, sex of household head, women's age, women's level of education, current age of husband's, and husband's occupation are significantly (p\u0026thinsp;\u0026lt;\u0026thinsp;0.001) associated with sexual inactivity among reproductive married women. Additionally, the likelihood of sexual inactivity is significantly (p\u0026thinsp;\u0026lt;\u0026thinsp;0.05) higher among reproductive married women who have been watching television, using the internet for the last 12 Months, women's education level, women's height, and women's age at first intercourse.\u003c/p\u003e \u003cp\u003e \u003cdiv class=\"gridtable\"\u003e\u003ctable float=\"Yes\" id=\"Tab1\" border=\"1\"\u003e \u003ccaption language=\"En\"\u003e \u003cdiv class=\"CaptionNumber\"\u003eTable 1\u003c/div\u003e \u003cdiv class=\"CaptionContent\"\u003e \u003cp\u003ePrevalence of sexual inactivity by individual and household level of socio-demographic characteristics among reproductive married women in Bangladesh\u003c/p\u003e \u003c/div\u003e \u003c/caption\u003e \u003ccolgroup cols=\"6\"\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c1\" colnum=\"1\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c2\" colnum=\"2\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c3\" colnum=\"3\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c4\" colnum=\"4\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c5\" colnum=\"5\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c6\" colnum=\"6\"\u003e\u003c/div\u003e \u003cthead\u003e \u003ctr\u003e \u003cth align=\"left\" colname=\"c1\" morerows=\"1\" rowspan=\"2\"\u003e \u003cp\u003eStudy variables\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c2\" morerows=\"1\" rowspan=\"2\"\u003e \u003cp\u003eN (%)\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colspan=\"2\" nameend=\"c4\" namest=\"c3\"\u003e \u003cp\u003eSexual Inactivity\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c5\" morerows=\"1\" rowspan=\"2\"\u003e \u003cp\u003eχ\u003csup\u003e2\u003c/sup\u003e-values\u003c/p\u003e \u003cp\u003e(\u003cem\u003ep-values)\u003c/em\u003e\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c6\" morerows=\"1\" rowspan=\"2\"\u003e \u003cp\u003eWeighted Prevalence (95% CI)\u003c/p\u003e \u003c/th\u003e \u003c/tr\u003e \u003ctr\u003e \u003cth align=\"left\" colname=\"c3\"\u003e \u003cp\u003eYes (%)\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c4\"\u003e \u003cp\u003eNo (%)\u003c/p\u003e \u003c/th\u003e \u003c/tr\u003e \u003ctr\u003e \u003cth align=\"left\" colspan=\"4\" nameend=\"c4\" namest=\"c1\"\u003e \u003cp\u003eGeographical region\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c5\"\u003e \u003cp\u003e37.54 (\u0026lt;\u0026thinsp;0.001)\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c6\"\u003e\u0026nbsp;\u003c/th\u003e \u003c/tr\u003e \u003c/thead\u003e \u003ctbody\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eBarisal\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e1496 (10.21)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e135 (9.02)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e1361 (90.98)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e9.74 (8.00\u0026ndash;12.00)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eChittagong\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e1894 (12.93)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e144 (7.60)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e1750 (92.40)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e7.81 (6.79\u0026ndash;8.97)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eDhaka\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e2200 (15.02)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e123 (5.59)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e2077 (94.41)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e5.56 (4.87\u0026ndash;6.35)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eKhulna\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e1998 (13.64)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e108 (5.41)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e1890 (94.59)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e5.96 (4.26\u0026ndash;6.30)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eMymensingh\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e1643 (11.22)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e99 (6.03)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e1544 (93.97)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e5.96 (4.73\u0026ndash;7.48)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eRajshahi\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e2038 (13.91)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e127 (6.23)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e1911 (93.77)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e6.42 (5.45\u0026ndash;7.56)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eRangpur\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e1923 (13.13)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e162 (8.42)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e1761 (91.58)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e8.73 (7.52\u0026ndash;10.12)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eSylhet\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e1458 (9.95)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e86 (5.90)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e1372 (94.10)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e5.91 (4.45\u0026ndash;7.8)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colspan=\"4\" nameend=\"c4\" namest=\"c1\"\u003e \u003cp\u003e\u003cb\u003ePlace of Residence\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e\u003cb\u003e1.79 (0.180)\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eUrban\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e5308 (36.23)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e647 (6.93)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e8695 (93.07)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e6.1 (5.43\u0026ndash;6.86)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eRural\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e9342 (63.77)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e337 (6.35)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e4971 (93.65)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e6.94 (6.46\u0026ndash;7.44)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colspan=\"4\" nameend=\"c4\" namest=\"c1\"\u003e \u003cp\u003e\u003cb\u003eReligion\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e\u003cb\u003e0.16 (0.684)\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eMuslim\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e12952 (88.41)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e866 (6.69)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e12086 (93.31)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e6.56 (6.14-7.00)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eNon-Muslim\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e1698(11.59)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e118 (6.95)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e1580 (93.05)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e7.78 (6.56\u0026ndash;9.22)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colspan=\"4\" nameend=\"c4\" namest=\"c1\"\u003e \u003cp\u003e\u003cb\u003eSex of household head\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e\u003cb\u003e188.14 (\u0026lt;\u0026thinsp;0.001)\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eMale\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e13963 (95.31)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e850 (6.09)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e13113 (95.95)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e6.09 (5.70\u0026ndash;6.5)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eFemale\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e687 (4.69)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e134 (19.51)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e553 (80.49)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e19.1 (16.24\u0026ndash;22.15)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colspan=\"4\" nameend=\"c4\" namest=\"c1\"\u003e \u003cp\u003e\u003cb\u003eWatching television\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e\u003cb\u003e5.72 (0.017)\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eNo\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e6226 (42.50)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e454 (7.29)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e5772 (92.71)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e7.22 (6.60\u0026ndash;7.89)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eYes\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e8424 (57.50)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e530 (6.29)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e7894 (93.71)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e6.29 (5.79\u0026ndash;6.83)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colspan=\"4\" nameend=\"c4\" namest=\"c1\"\u003e \u003cp\u003e\u003cb\u003eUsage of the internet last 12 Months\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e\u003cb\u003e9.98 (0.002)\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eNo\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e11281 (77.00)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e798 (7.07)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e10483 (92.93)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e7.11 (6.65\u0026ndash;7.61)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eYes\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e3369 (23.00)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e186 (5.52)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e3183 (94.48)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e5.29 (4.59\u0026ndash;6.1)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colspan=\"4\" nameend=\"c4\" namest=\"c1\"\u003e \u003cp\u003e\u003cb\u003eWealth status\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e\u003cb\u003e3.88 (0.423)\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003ePoorest\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e2754 (18.80)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e198 (7.19)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e2556 (92.81)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e7.33 (6.42\u0026ndash;8.37)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003ePoorer\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e2885 (19.69)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e197 (6.83)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e2688 (93.17)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e6.83 (5.98\u0026ndash;7.8)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eMiddle\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e2920 (19.93)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e207 (7.09)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e2713 (92.91)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e7.10 (6.24\u0026ndash;8.08)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eRicher\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e2981 (20.35)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e192 (6.44)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e2789 (93.56)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e6.13 (5.33\u0026ndash;7.05)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eRichest\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e3110 (21.23)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e190 (6.11)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e2920 (93.89)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e6.08 (5.26\u0026ndash;7.02)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colspan=\"4\" nameend=\"c4\" namest=\"c1\"\u003e \u003cp\u003e\u003cb\u003eWomen's current age (years)\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e\u003cb\u003e79.13 (\u0026lt;\u0026thinsp;0.000)\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eMedian\u003c/p\u003e \u003cp\u003e(IQR)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e\u003cb\u003e33.0\u003c/b\u003e\u003c/p\u003e \u003cp\u003e\u003cb\u003e(26.0\u0026ndash;40.0)\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e\u003cb\u003e35.0\u003c/b\u003e\u003c/p\u003e \u003cp\u003e\u003cb\u003e(25.0\u0026ndash;43.0)\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e\u003cb\u003e33.0\u003c/b\u003e\u003c/p\u003e \u003cp\u003e\u003cb\u003e(26.0\u0026ndash;40.0)\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eBelow 30\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e5530 (37.75)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e326 (5.90)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e5204 (94.10)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e6.01 (5.42\u0026ndash;6.66)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e30\u0026ndash;40\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e5895 (40.24)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e330 (5.6)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e5565 (94.40)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e5.63 (5.07\u0026ndash;6.26)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eabove 40\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e3225 (22.01)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e328 (10.17)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e2897 (89.83)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e9.83 (8.84\u0026ndash;10.92)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colspan=\"4\" nameend=\"c4\" namest=\"c1\"\u003e \u003cp\u003e\u003cb\u003eWomen education level\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e\u003cb\u003e9.53 (0.009)\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eLess than high school\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e4100 (32.76)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e296 (7.22)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e3804 (92.78)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e6.86 (6.12\u0026ndash;7.67)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eHigh school\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e6410 (51.22)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e398 (6.21)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e6012 (93.79)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e6.41 (5.84\u0026ndash;7.03)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eMore than high school\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e2005 (16.02)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e105 (5.24)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e1900 (94.76)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e4.97 (4.06\u0026ndash;6.07)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colspan=\"4\" nameend=\"c4\" namest=\"c1\"\u003e \u003cp\u003e\u003cb\u003eWomen height\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e\u003cb\u003e6.60 (0.010)\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eMedian\u003c/p\u003e \u003cp\u003e(IQR)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e\u003cb\u003e151.5\u003c/b\u003e\u003c/p\u003e \u003cp\u003e\u003cb\u003e(147.9-155.3)\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e\u003cb\u003e151.2\u003c/b\u003e\u003c/p\u003e \u003cp\u003e\u003cb\u003e(147.4-154.6\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e\u003cb\u003e151.6\u003c/b\u003e\u003c/p\u003e \u003cp\u003e\u003cb\u003e(148.0-155.3)\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eBelow average (\u0026lt;\u0026thinsp;164 cm)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e6951 (47.45)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e428 (6.16)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e6523 (93.84)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e6.02 (5.48\u0026ndash;6.61)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eAverage/above (\u0026ge;\u0026thinsp;164 cm)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e7699 (52.55)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e556 (7.22)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e7143 (92.78)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e7.29 (6.73\u0026ndash;7.89)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colspan=\"4\" nameend=\"c4\" namest=\"c1\"\u003e \u003cp\u003e\u003cb\u003eWomen age at first intercourse (years)\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e\u003cb\u003e10.95 (0.004)\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eMedian\u003c/p\u003e \u003cp\u003e(IQR)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e\u003cb\u003e16.0\u003c/b\u003e\u003c/p\u003e \u003cp\u003e\u003cb\u003e(14.0\u0026ndash;18.0)\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e\u003cb\u003e16.0\u003c/b\u003e\u003c/p\u003e \u003cp\u003e\u003cb\u003e(14.0\u0026ndash;18.0)\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e\u003cb\u003e16.0\u003c/b\u003e\u003c/p\u003e \u003cp\u003e\u003cb\u003e(14.0\u0026ndash;18.0)\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e\u0026lt;\u0026thinsp;15\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e3970 (27.10)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e311 (7.83)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e3659 (92.17)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e7.53 (6.76\u0026ndash;8.39)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e15\u0026ndash;17\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e5965 (40.72)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e380 (6.37)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e5585 (93.63)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e6.58 (5.98\u0026ndash;7.23)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e\u0026ge;\u0026thinsp;18\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e4715 (32.18)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e293 (6.21)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e4422 (93.79)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e6.08 (5.41\u0026ndash;6.81)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colspan=\"4\" nameend=\"c4\" namest=\"c1\"\u003e \u003cp\u003e\u003cb\u003eWomen occupation\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e\u003cb\u003e7.29 (0.063)\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eHomemakers\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e12285 (83.86)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e847 (6.89)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e11438 (93.11)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e6.92 (6.48\u0026ndash;7.39)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eBusiness\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e1001 (6.83)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e54 (5.39)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e947 (94.61)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e5.12 (3.92\u0026ndash;6.66)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eService Holder\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e326 (2.23)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e13 (3.99)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e313 (96.01)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e3.22 (1.74\u0026ndash;5.88)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eOthers\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e1037 (7.08)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e70 (6.75)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e967 (93.25)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e6.56 (5.23\u0026ndash;8.21)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colspan=\"4\" nameend=\"c4\" namest=\"c1\"\u003e \u003cp\u003e\u003cb\u003eWomen continue studies after marriage\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e\u003cb\u003e0.06 (0.805)\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eNo\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e7687 (82.12)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e504 (6.56)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e7183 (93.44)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e6.64 (6.10\u0026ndash;7.21)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eYes\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e1674 (17.88)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e107 (6.39)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e1567 (93.61)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e6.19 (5.10\u0026ndash;7.49)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colspan=\"4\" nameend=\"c4\" namest=\"c1\"\u003e \u003cp\u003e\u003cb\u003eHusband's current age (years)\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e\u003cb\u003e102.69 (\u0026lt;\u0026thinsp;0.000)\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eMedian\u003c/p\u003e \u003cp\u003e(IQR)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e\u003cb\u003e40.0\u003c/b\u003e\u003c/p\u003e \u003cp\u003e\u003cb\u003e(33.0\u0026ndash;49.0)\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e\u003cb\u003e45.0\u003c/b\u003e\u003c/p\u003e \u003cp\u003e\u003cb\u003e(34.0\u0026ndash;54.0)\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e\u003cb\u003e40.0\u003c/b\u003e\u003c/p\u003e \u003cp\u003e\u003cb\u003e(33.0\u0026ndash;48.0)\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eBelow 30\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e2220 ( 15.15)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e136 (6.13)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e2084 (93.87)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e6.07 (5.16\u0026ndash;7.16)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e30\u0026ndash;40\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e5610 (38.29)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e243 (4.33)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e5367 (95.67)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e4.41 (3.90\u0026ndash;4.98)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eabove 40\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e6820 (46.55)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e605 (8.87)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e6215 (91.13)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e8.81 (8.15\u0026ndash;9.51)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colspan=\"4\" nameend=\"c4\" namest=\"c1\"\u003e \u003cp\u003e\u003cb\u003eHusband's education level\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e\u003cb\u003e3.49 (0.321)\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eNo education\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e3384 (23.29)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e215 (6.35)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e3169 (93.65)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e6.39 (5.62\u0026ndash;7.26)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003ePrimary\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e4206 (28.95)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e259 (6.16)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e3947 (93.84)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e6.19 (5.5\u0026ndash;6.95)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eSecondary\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e4371 (30.09)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e268 (6.13)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e4103 (93.87)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e6.13 (5.46\u0026ndash;6.88)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eHigher\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e2566 (17.66)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e135 (5.26)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e2431 (94.74)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e5.08 (4.27\u0026ndash;6.03)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colspan=\"4\" nameend=\"c4\" namest=\"c1\"\u003e \u003cp\u003e\u003cb\u003eHusband's occupation\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e\u003cb\u003e22.06 (\u0026lt;\u0026thinsp;0.001)\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eUnemployed\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e499 (3.44)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e51 (10.22)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e448 (89.78)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e9.36 (7.07\u0026ndash;12.3)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eFarmer/Labour\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e7470 (51.45)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e467 (6.25)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e7003 (93.75)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e6.20 (5.69\u0026ndash;6.77)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eBusiness\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e5493 (37.84)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e311 (5.66)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e5182 (94.34)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e5.82 (5.22\u0026ndash;6.49)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eService Holder\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e1056 (7.27)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e47 (4.45)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e1009 (95.55)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e4.21 (3.13\u0026ndash;5.64)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colspan=\"6\" nameend=\"c6\" namest=\"c1\"\u003e \u003cp\u003e\u003cem\u003eNotes: \u0026lsquo;N, total\u0026rsquo;; \u0026lsquo;%, percentages\u0026rsquo;\u003c/em\u003e\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003c/tbody\u003e \u003c/colgroup\u003e \u003c/table\u003e\u003c/div\u003e \u003c/p\u003e\n\u003ch3\u003eSocio-demographic factors influencing sexual inactivity\u003c/h3\u003e\n\u003cp\u003eTable\u0026nbsp;\u003cspan refid=\"Tab2\" class=\"InternalRef\"\u003e2\u003c/span\u003e highlighted the significant socio-demographic determinants related with sexual inactivity among Bangladeshi married women of childbearing age. Notably, geographical region, sex of the household head, women's age, women height, husband's age, and husband's occupation were significantly connected with sexual inactivity.\u003c/p\u003e \u003cp\u003eThe likelihood of sexual inactivity was significantly elevated among reproductive married women who residing in the Dhaka region (AOR\u0026thinsp;=\u0026thinsp;1.47, 95% CI\u0026thinsp;=\u0026thinsp;1.09\u0026ndash;1.97, p\u0026thinsp;\u0026lt;\u0026thinsp;0.011) or Khulna region (AOR\u0026thinsp;=\u0026thinsp;1.59, 95% CI\u0026thinsp;=\u0026thinsp;1.17\u0026ndash;2.16, p\u0026thinsp;\u0026lt;\u0026thinsp;0.003) or Sylhet region to compared of the Chittagong region residents (AOR\u0026thinsp;=\u0026thinsp;1.46, 95% CI\u0026thinsp;=\u0026thinsp;1.04\u0026ndash;2.04, p\u0026thinsp;\u0026lt;\u0026thinsp;0.028). Conversely, female-headed households exhibited markedly reduced odds of sexual inactivity (AOR\u0026thinsp;=\u0026thinsp;0.37, 95% CI\u0026thinsp;=\u0026thinsp;0.28\u0026ndash;0.48, p\u0026thinsp;\u0026lt;\u0026thinsp;0.001). Additionally, women aged above 40 displayed significantly lower odds of sexual inactivity compared to women below 30 (AOR\u0026thinsp;=\u0026thinsp;0.57, 95% CI\u0026thinsp;=\u0026thinsp;0.42\u0026ndash;0.78, p\u0026thinsp;\u0026lt;\u0026thinsp;0.001). Reproductive married women whose height\u0026thinsp;\u0026lt;\u0026thinsp;164 cm had significantly higher odds of sexual inactivity (AOR\u0026thinsp;=\u0026thinsp;1.33, 95% CI\u0026thinsp;=\u0026thinsp;1.14\u0026ndash;1.56, p\u0026thinsp;\u0026lt;\u0026thinsp;0.001). Moreover, husband's aged 30\u0026ndash;40 years showed significantly increased odds of sexual inactivity in comparison to those who were below 30 years (AOR\u0026thinsp;=\u0026thinsp;1.30, 95% CI\u0026thinsp;=\u0026thinsp;1.02\u0026ndash;1.67, p\u0026thinsp;=\u0026thinsp;0.036). Likewise, unemployed husbands had substantially lower odds of sexual inactivity (AOR\u0026thinsp;=\u0026thinsp;0.56, 95% CI\u0026thinsp;=\u0026thinsp;0.35\u0026ndash;0.89, p\u0026thinsp;\u0026lt;\u0026thinsp;0.014) [Table\u0026nbsp;\u003cspan refid=\"Tab2\" class=\"InternalRef\"\u003e2\u003c/span\u003e].\u003c/p\u003e \u003cp\u003e \u003cdiv class=\"gridtable\"\u003e\u003ctable float=\"Yes\" id=\"Tab2\" border=\"1\"\u003e \u003ccaption language=\"En\"\u003e \u003cdiv class=\"CaptionNumber\"\u003eTable 2\u003c/div\u003e \u003cdiv class=\"CaptionContent\"\u003e \u003cp\u003eThe impact of socio-demographic factors on sexual inactivity among married women of childbearing age in Bangladesh.\u003c/p\u003e \u003c/div\u003e \u003c/caption\u003e \u003ccolgroup cols=\"5\"\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c1\" colnum=\"1\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c2\" colnum=\"2\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c3\" colnum=\"3\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c4\" colnum=\"4\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c5\" colnum=\"5\"\u003e\u003c/div\u003e \u003cthead\u003e \u003ctr\u003e \u003cth align=\"left\" colname=\"c1\" morerows=\"1\" rowspan=\"2\"\u003e \u003cp\u003eStudy variables\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colspan=\"2\" nameend=\"c3\" namest=\"c2\"\u003e \u003cp\u003eUnadjusted\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colspan=\"2\" nameend=\"c5\" namest=\"c4\"\u003e \u003cp\u003eAdjusted\u003c/p\u003e \u003c/th\u003e \u003c/tr\u003e \u003ctr\u003e \u003cth align=\"left\" colname=\"c2\"\u003e \u003cp\u003eUOR (95% CI)\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c3\"\u003e \u003cp\u003e\u003cem\u003ep-values\u003c/em\u003e\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c4\"\u003e \u003cp\u003eAOR (95% CI)\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c5\"\u003e \u003cp\u003e\u003cem\u003ep-values\u003c/em\u003e\u003c/p\u003e \u003c/th\u003e \u003c/tr\u003e \u003ctr\u003e \u003cth align=\"left\" colspan=\"5\" nameend=\"c5\" namest=\"c1\"\u003e \u003cp\u003eGeographical region\u003c/p\u003e \u003c/th\u003e \u003c/tr\u003e \u003c/thead\u003e \u003ctbody\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eBarisal\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e0.83 (0.65\u0026ndash;1.06)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e0.135\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e0.84 (0.63\u0026ndash;1.11)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e0.211\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eChittagong\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e\u003cb\u003eReference\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e\u003cb\u003eReference\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eDhaka\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e1.38 (1.08\u0026ndash;1.78)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e0.010\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e1.47 (1.09\u0026ndash;1.97)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e0.011\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eKhulna\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e1.44 (1.11\u0026ndash;1.86)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e0.006\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e1.59 (1.17\u0026ndash;2.16)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e0.003\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eMymensingh\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e1.28 (0.98\u0026ndash;1.67)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e0.065\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e1.38 (0.99\u0026ndash;1.90)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e0.051\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eRajshahi\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e1.24 (0.97\u0026ndash;1.58)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e0.090\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e1.24 (0.92\u0026ndash;1.67)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e0.148\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eRangpur\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e0.89 (0.71\u0026ndash;1.13)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e0.350\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e0.88 (0.67\u0026ndash;1.17)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e0.392\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eSylhet\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e1.31 (0.99\u0026ndash;1.73)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e0.054\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e1.46 (1.04\u0026ndash;2.04)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e0.028\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colspan=\"5\" nameend=\"c5\" namest=\"c1\"\u003e \u003cp\u003e\u003cb\u003eSex of household head\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eMale\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e\u003cb\u003eReference\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e\u003cb\u003eReference\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eFemale\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e0.27 (0.22\u0026ndash;0.33)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e\u0026lt;\u0026thinsp;0.001\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e0.37 (0.28\u0026ndash;0.48)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e\u0026lt;\u0026thinsp;0.001\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colspan=\"5\" nameend=\"c5\" namest=\"c1\"\u003e \u003cp\u003e\u003cb\u003eWatching television\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eNo\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e\u003cb\u003eReference\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e\u003cb\u003eReference\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eYes\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e1.17 (1.03\u0026ndash;1.33)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e0.017\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e1.14 (0.97\u0026ndash;1.34)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e0.107\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colspan=\"5\" nameend=\"c5\" namest=\"c1\"\u003e \u003cp\u003e\u003cb\u003eUsage of internet last 12 months\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eNo\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e\u003cb\u003eReference\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e\u003cb\u003eReference\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eYes\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e1.30 (1.10\u0026ndash;1.53)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e0.002\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e1.11 (0.91\u0026ndash;1.37)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e0.302\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colspan=\"5\" nameend=\"c5\" namest=\"c1\"\u003e \u003cp\u003e\u003cb\u003eWomen current age (years)\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eBelow 30\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e\u003cb\u003eReference\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e\u003cb\u003eReference\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e30\u0026ndash;40\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e1.06 (0.90\u0026ndash;1.24)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e0.495\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e1.04 (0.81\u0026ndash;1.33)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e0.744\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eabove 40\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e0.55 (0.47\u0026ndash;0.65)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e\u0026lt;\u0026thinsp;0.001\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e0.57 (0.42\u0026ndash;0.78)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e\u0026lt;\u0026thinsp;0.001\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colspan=\"5\" nameend=\"c5\" namest=\"c1\"\u003e \u003cp\u003e\u003cb\u003eWomen education level\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eLess than high school\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e\u003cb\u003eReference\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e\u003cb\u003eReference\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eHigh school\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e1.17 (1.01\u0026ndash;1.37)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e0.042\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e0.99 (0.83\u0026ndash;1.19)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e0.970\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eMore than high school\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e1.41 (1.12\u0026ndash;1.77)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e0.003\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e1.16 (0.85\u0026ndash;1.58)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e0.337\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e\u003cb\u003eWomen height\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eBelow average (\u0026lt;\u0026thinsp;164 cm)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e1.19 (1.04\u0026ndash;1.35)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e0.010\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e1.33 (1.14\u0026ndash;1.56)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e\u0026lt;\u0026thinsp;0.001\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eAverage or above (\u0026ge;\u0026thinsp;164 cm)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e\u003cb\u003eReference\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e\u003cb\u003eReference\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colspan=\"5\" nameend=\"c5\" namest=\"c1\"\u003e \u003cp\u003e\u003cb\u003eWomen age at first intercourse (years)\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e\u0026lt;\u0026thinsp;15\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e0.78 (0.66\u0026ndash;0.92)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e0.003\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e0.87 (0.69\u0026ndash;1.08)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e0.213\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e15\u0026ndash;17\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e0.97 (0.83\u0026ndash;1.14)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e0.741\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e1.05 (0.86\u0026ndash;1.28)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e0.610\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e\u0026ge;\u0026thinsp;18\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e\u003cb\u003eReference\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e\u003cb\u003eReference\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colspan=\"5\" nameend=\"c5\" namest=\"c1\"\u003e \u003cp\u003e\u003cb\u003eHusband's current age (years)\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eBelow 30\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e\u003cb\u003eReference\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e\u003cb\u003eReference\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e30\u0026ndash;40\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e1.44 (1.16\u0026ndash;1.79)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e0.001\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e1.30 (1.02\u0026ndash;1.67)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e0.036\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eabove 40\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e0.67 (0.55\u0026ndash;0.81)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e\u0026lt;\u0026thinsp;0.001\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e1.03 (0.74\u0026ndash;1.42)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e0.874\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colspan=\"5\" nameend=\"c5\" namest=\"c1\"\u003e \u003cp\u003e\u003cb\u003eHusband's occupation\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eUnemployed\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e0.41 (0.27\u0026ndash;0.62)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e\u0026lt;\u0026thinsp;0.001\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e0.56 (0.35\u0026ndash;0.89)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e0.014\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eFarmer/Labour\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e0.69 (0.51\u0026ndash;0.95)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e0.022\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e0.81 (0.57\u0026ndash;1.14)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e0.224\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eBusiness\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e0.78 (0.57\u0026ndash;1.06)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e0.114\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e0.84 (0.59\u0026ndash;1.19)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e0.336\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eService Holder\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e\u003cb\u003eReference\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e\u003cb\u003eReference\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colspan=\"5\" nameend=\"c5\" namest=\"c1\"\u003e \u003cp\u003e\u003cem\u003eNotes: \u0026lsquo;UOR, unadjusted odd ratios\u0026rsquo;; \u0026lsquo;CI, confidence interval\u0026rsquo;; \u0026lsquo;AOR, adjusted odd ratios\u0026rsquo;\u003c/em\u003e\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003c/tbody\u003e \u003c/colgroup\u003e \u003c/table\u003e\u003c/div\u003e \u003c/p\u003e"},{"header":"Discussion","content":"\u003cp\u003eA nationwide survey of BDHS data from 2022 was used for this research. We are assessed 6.72% of reproductive married women sexually inactive in the past month. Arafat et al. study revealed that sexual inactivity among married couples of Bangladesh is 5.6%. However, our study depicted that sexual inactivity among married women in Bangladesh is increasing comparing the prior study of Bangladesh. Several high-income countries such as Finland, [\u003cspan citationid=\"CR24\" class=\"CitationRef\"\u003e24\u003c/span\u003e] Australia, [\u003cspan citationid=\"CR25\" class=\"CitationRef\"\u003e25\u003c/span\u003e] and United States[\u003cspan citationid=\"CR5\" class=\"CitationRef\"\u003e5\u003c/span\u003e] are increased the sexual inactivity among married women. Ascorbic acid develops vascular function and raises oxytocin release. Besides, ascorbic acid declines stress reactivity and approaches anxiety and prolactin release. These relevant procedures are increased the frequency of women sexual intercourse [\u003cspan citationid=\"CR26\" class=\"CitationRef\"\u003e26\u003c/span\u003e].\u003c/p\u003e \u003cp\u003eThe fundamental part of life is a Sexual task. A robust positive relationship exists between sexual behavior and the excellence of life [\u003cspan citationid=\"CR27\" class=\"CitationRef\"\u003e27\u003c/span\u003e]. In a British cohort study reported that married women lessen the intercourse for declined the quality of sex life [\u003cspan citationid=\"CR28\" class=\"CitationRef\"\u003e28\u003c/span\u003e]. The local build of environmental characteristics significantly influences the health outcomes [\u003cspan citationid=\"CR29\" class=\"CitationRef\"\u003e29\u003c/span\u003e]. Our analysis shows the geographical region was significantly related with sexually inactive. Women who live in Dhaka region or Khulna region or Sylhet region were more prone to sexual inactive comparing Chittagong region residents. Women who live in urban areas were significantly related to higher sexual intercourse frequency compared to rural women [\u003cspan citationid=\"CR30\" class=\"CitationRef\"\u003e30\u003c/span\u003e]. Besides, an Egyptian study reported that the purpose of intercourse among urban women was to have pleasure for themselves and their husbands and more initiation of coitus [\u003cspan citationid=\"CR31\" class=\"CitationRef\"\u003e31\u003c/span\u003e].\u003c/p\u003e \u003cp\u003eA household head female designates a woman in charge of handling the family. As a result, she gets the power of separation, immigration, and divorce [\u003cspan citationid=\"CR32\" class=\"CitationRef\"\u003e32\u003c/span\u003e]. intensely in developing countries had increased the number of female-headed households [\u003cspan citationid=\"CR33\" class=\"CitationRef\"\u003e33\u003c/span\u003e]. Low-income and physical disorders and mental, neurological, etc. problems faced by female-headed households [\u003cspan citationid=\"CR34\" class=\"CitationRef\"\u003e34\u003c/span\u003e]. Female-headed households involve many risk factors upsetting their sexual life [\u003cspan citationid=\"CR35\" class=\"CitationRef\"\u003e35\u003c/span\u003e]. Women-headed households face the challenge of intra-family tension [\u003cspan citationid=\"CR36\" class=\"CitationRef\"\u003e36\u003c/span\u003e]. Where, women in the high-stress group had lower levels of genital sexual arousal [\u003cspan citationid=\"CR37\" class=\"CitationRef\"\u003e37\u003c/span\u003e]. Our research depicted that households' female-headed are more chance of sexually inactive than male-headed households. Our investigation is consistent with a qualitative study in Iran [\u003cspan citationid=\"CR35\" class=\"CitationRef\"\u003e35\u003c/span\u003e]. Partner balanced intimacy relationship can promote mental and physical health [\u003cspan citationid=\"CR38\" class=\"CitationRef\"\u003e38\u003c/span\u003e].\u003c/p\u003e \u003cp\u003eConsistently, both men and women in sexual activity decrease with age's [\u003cspan citationid=\"CR39\" class=\"CitationRef\"\u003e39\u003c/span\u003e]. The incidence of sexual activity among women is lower than among men [\u003cspan citationid=\"CR40\" class=\"CitationRef\"\u003e40\u003c/span\u003e]. Testosterone starts to slowly decrease with age. The traditional advantage of testosterone leads to sexual behavior. It effects on bone density, obesity, insulin resistance, prostate disease, and aggression etc. [\u003cspan citationid=\"CR41\" class=\"CitationRef\"\u003e41\u003c/span\u003e]. Approximately, our study shows one in fifteen women were sexually inactive between ages 15 and 49 years. Additionally, our study revealed reproductive married women aged above 40 years are significantly associated with sexual inactivity. Our simple regression analysis revealed that women whose husbands aged above 40 years are less likely to be sexually inactive. Our result is contradictory to the Iranian analysis. Additionally, Iranian analysis showed that female sexual dysfunction was significantly more likely to be those who had husbands aged 40 years or older [\u003cspan citationid=\"CR42\" class=\"CitationRef\"\u003e42\u003c/span\u003e].Besides, above 40 years men and women around one in eleven and one in ten are reported being sexually inactive. These findings clarified the higher likelihood sexual inactivity of women who are living partner's current age 30\u0026ndash;40 years. For incidence of sexual inactivity, our study is consistent with previous studies ([\u003cspan citationid=\"CR23\" class=\"CitationRef\"\u003e23\u003c/span\u003e], [\u003cspan citationid=\"CR40\" class=\"CitationRef\"\u003e40\u003c/span\u003e]). The serum concentrations of testosterone are increased by boron supplementation [\u003cspan citationid=\"CR43\" class=\"CitationRef\"\u003e43\u003c/span\u003e]. The maximum amounts of boron contained in fruits, tubers, coffee, milk, dried and cooked beans, potatoes, legumes, etc. [\u003cspan citationid=\"CR44\" class=\"CitationRef\"\u003e44\u003c/span\u003e].\u003c/p\u003e \u003cp\u003eBody shape for women is a contributing factor to sexual attraction [\u003cspan citationid=\"CR45\" class=\"CitationRef\"\u003e45\u003c/span\u003e]. Additionally, height plays a significant role in human companion preferences [\u003cspan citationid=\"CR46\" class=\"CitationRef\"\u003e46\u003c/span\u003e]. Mid-range women's leg-to-body ratios were observed as extremely attractive [\u003cspan citationid=\"CR47\" class=\"CitationRef\"\u003e47\u003c/span\u003e]. Besides, women's height has been proven to be an element of reproductive accomplishment [\u003cspan citationid=\"CR48\" class=\"CitationRef\"\u003e48\u003c/span\u003e]. Our study depicted that reproductive married women were significantly more likely to be sexually inactive whose height was shorter than average. Our investigation is consistent with a cross-sectional probability sample survey data study in Britain [\u003cspan citationid=\"CR40\" class=\"CitationRef\"\u003e40\u003c/span\u003e]. Body figure and stature can also reflect overall fitness that may be related to poor sexual function [\u003cspan citationid=\"CR49\" class=\"CitationRef\"\u003e49\u003c/span\u003e]. Women who have higher body appreciation positively predicted better sexual function [\u003cspan citationid=\"CR50\" class=\"CitationRef\"\u003e50\u003c/span\u003e].\u003c/p\u003e \u003cp\u003eThe advent of first sex is essential course of good health life [\u003cspan citationid=\"CR51\" class=\"CitationRef\"\u003e51\u003c/span\u003e]. Early first sex is associated with higher rates of current mental distress and smoking among adult women ([\u003cspan citationid=\"CR52\" class=\"CitationRef\"\u003e52\u003c/span\u003e], [\u003cspan citationid=\"CR53\" class=\"CitationRef\"\u003e53\u003c/span\u003e]). The problem of depression and marriage-related difficulties are faced the later of life who initiation of sexual intercourse during adolescence [\u003cspan citationid=\"CR54\" class=\"CitationRef\"\u003e54\u003c/span\u003e]. Besides, Senn et. al study depicted that sexual abuse is a strong forecaster of early sexual initiation [\u003cspan citationid=\"CR55\" class=\"CitationRef\"\u003e55\u003c/span\u003e]. Our unadjusted odds ratio showed that women more likely to sexual inactive who complete first intercourse at early age. The public programs and family life education should concentration on sexual health elevation considering the physical and psychosocial changes that can prevent perilous sexual behaviors among adolescent girls [\u003cspan citationid=\"CR56\" class=\"CitationRef\"\u003e56\u003c/span\u003e].\u003c/p\u003e \u003cp\u003eExperiential research shows that the condition of unemployment has negative effects on health [\u003cspan citationid=\"CR57\" class=\"CitationRef\"\u003e57\u003c/span\u003e]. Unemployed young men who live with their parents are less feasible in dating markets and less equipped for sensitive intimacy, the logic follows that they will be less able to obtain healthy loving and sexual relations with participants of the opposite sex ([\u003cspan citationid=\"CR58\" class=\"CitationRef\"\u003e58\u003c/span\u003e][\u003cspan citationid=\"CR59\" class=\"CitationRef\"\u003e59\u003c/span\u003e]). Many studies depict that unemployment men are more distressed [\u003cspan citationid=\"CR60\" class=\"CitationRef\"\u003e60\u003c/span\u003e]. But, an energetic sex life is positively associated with mental and bodily health [\u003cspan citationid=\"CR6\" class=\"CitationRef\"\u003e6\u003c/span\u003e]. Pitta et.al study showed that depressive symptoms are strongly associated with erectile dysfunction [\u003cspan citationid=\"CR61\" class=\"CitationRef\"\u003e61\u003c/span\u003e]. The present study finds substantiation that unemployed husbands/partners have more chance to be sexually inactive compared to employed husbands/partners. Several realistic studies show consistently that unemployed men are more likely to abstain from sexual intercourse ([\u003cspan citationid=\"CR5\" class=\"CitationRef\"\u003e5\u003c/span\u003e], [\u003cspan citationid=\"CR62\" class=\"CitationRef\"\u003e62\u003c/span\u003e]). So, unemployed men can do physical exercise which has a positive impact on sexual function in men and promotes sexual health [\u003cspan citationid=\"CR63\" class=\"CitationRef\"\u003e63\u003c/span\u003e].\u003c/p\u003e \u003cdiv id=\"Sec12\" class=\"Section2\"\u003e \u003ch2\u003ePolicy Implications\u003c/h2\u003e \u003cp\u003eThe results of this study hold noteworthy policy implications for public health efforts in Bangladesh. Policymakers should prioritize sexual health education and awareness campaigns that address the socio-cultural taboos surrounding discussions on sexual health. Efforts should be made to promote open communication between couples and encourage help-seeking behaviors for sexual health issues. Furthermore, policies aimed at improving access to education, particularly for women, may empower people to make knowledgeable decisions about their sexual and reproductive well-being. Additionally, policies targeting poverty alleviation and employment generation, especially in rural areas, may indirectly contribute to reducing sexual inactivity by addressing socio-economic disparities.\u003c/p\u003e \u003c/div\u003e \u003cdiv id=\"Sec13\" class=\"Section2\"\u003e \u003ch2\u003eStrengths and limitations\u003c/h2\u003e \u003cp\u003eA key strength of this study was the use of a nationally representative sample with women as participants. Utilizing nationally adopted and internationally validated surveys such as the BDHS enhanced the robustness of our findings. Our study emphasized the significance of making valid statistical inferences for continuous variables. Although this study offers valuable visions, it is important to recognize numerous limitations. The study's cross-sectional design hinders drawing causal conclusions, emphasizing the need for longitudinal studies to determine the temporal connections between socio-demographic factors and sexual inactivity. Secondly, the dependence on data reported by individuals themselves may engender remember bias or social allure bias, thereby potentially compromising the veracity of responses concerning sexual activity. Additionally, the omission of specific cohorts, for example unmarried or divorced women, limits the extendibility or applicability of the conclusions to the broader populace. Moreover, the study's focus on socio-demographic factors may fail to notice other latent contributors to sexual inactivity's, such as psychological or relational factors.\u003c/p\u003e \u003c/div\u003e \u003cdiv id=\"Sec14\" class=\"Section2\"\u003e \u003ch2\u003eRecommendations\u003c/h2\u003e \u003cp\u003eIn light of the discoveries gleaned from this investigation, it is advisable that interventions and programs designed at addressing sexual inactivity among Bangladeshi women must consider the socio-demographic factors identified as significant determinants. Specifically, efforts should focus on regions with higher prevalence rates of sexual inactivity, such as the Sylhet region. Strategies to empower women, particularly those in female-headed households, may help mitigate sexual inactivity. Additionally, targeted interventions should be designed to support women who marry at younger ages, as they are at increased risk of sexual inactivity. Furthermore, initiatives to promote economic opportunities for men, particularly those aimed at reducing unemployment, may contribute to reducing sexual inactivity among married couples.\u003c/p\u003e \u003c/div\u003e"},{"header":"Conclusion","content":"\u003cp\u003eIn conclusion, this nationwide survey offers valuable visions into the socio-demographic determinants of sexual inactivity among reproductive Bangladeshi married women. The results highlight the imperative for comprehensive strategies in tackling sexual health concerns, acknowledging the intricate interplay of socio-demographic elements. Efforts to empower women, enhance economic opportunities, and promote open communication within marital relationships are crucial for mitigating sexual inactivity and improving the overall well-being of women in Bangladesh. Future research should explore additional factors influencing sexual activity patterns and evaluate the effectiveness of targeted interventions in addressing sexual health disparities.\u003c/p\u003e"},{"header":"Declarations","content":"\u003cp\u003e\u003cstrong\u003eAuthor Contributions\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eMAH conceptualized the study design. MAH had all access to the data and validation of the statistical analysis. MAH and MSI did the formal analysis. MAH, MZI and AMMI drafting the original manuscript. MAH, MZI, AMMI, MSI, MA and MAR critically reviewed the manuscript. MAH \u0026nbsp;supervised the whole study.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eFunding:\u003c/strong\u003e We don\u0026rsquo;t have any funding from specific grant agencies in the public or commercial sectors.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eData Availability Statement:\u003c/strong\u003e The recent survey datasets were constructed for analysis of this study. Data are open-access sources available online and accessible to the public:\u003c/p\u003e\n\u003cp\u003ehttps://dhsprogram.com/data/dataset/Bangladesh_Standard-DHS_2022.cfm?flag=0\u0026nbsp;\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eAcknowledgments:\u003c/strong\u003e The writers are grateful for accessing data from the Demographic and Health Surveys (DHS) Program and the Ministry of Health and Family Welfare, Dhaka, Bangladesh.\u0026nbsp;\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eConflicts of Interest:\u003c/strong\u003e There is no conflict of interest.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eEthics approval:\u003c/strong\u003e BDHS for 2022 is a cross-sectional secondary publicly accessible data approved by the Ministry of Health and Family Welfare. Consequently, the current study was released from ethics support.\u003c/p\u003e"},{"header":"References","content":"\u003col\u003e\n\u003cli\u003eA. Avasthi, S. Grover, and T. S. S. 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Health Promot.\u003c/em\u003e, vol. 7, no. 1, p. 57, 2018.\u003c/li\u003e\n\u003c/ol\u003e"}],"fulltextSource":"","fullText":"","funders":[],"hasAdminPriorityOnWorkflow":false,"hasManuscriptDocX":true,"hasOptedInToPreprint":true,"hasPassedJournalQc":"","hasAnyPriority":false,"hideJournal":false,"highlight":"","institution":"","isAcceptedByJournal":true,"isAuthorSuppliedPdf":false,"isDeskRejected":"","isHiddenFromSearch":false,"isInQc":false,"isInWorkflow":false,"isPdf":false,"isPdfUpToDate":true,"isWithdrawnOrRetracted":false,"journal":{"display":true,"email":"[email protected]","identity":"reproductive-health","isNatureJournal":false,"hasQc":true,"allowDirectSubmit":false,"externalIdentity":"reph","sideBox":"Learn more about [Reproductive Health](http://reproductive-health-journal.biomedcentral.com)","snPcode":"12978","submissionUrl":"https://submission.nature.com/new-submission/12978/3","title":"Reproductive Health","twitterHandle":"@Reprod_Health","acdcEnabled":true,"dfaEnabled":true,"editorialSystem":"em","reportingPortfolio":"BMC/SO AJ","inReviewEnabled":true,"inReviewRevisionsEnabled":true},"keywords":"Sexual intercourse, health, Sexual inactivity, reproductive, women, age, husband","lastPublishedDoi":"10.21203/rs.3.rs-5823750/v1","lastPublishedDoiUrl":"https://doi.org/10.21203/rs.3.rs-5823750/v1","license":{"name":"CC BY 4.0","url":"https://creativecommons.org/licenses/by/4.0/"},"manuscriptAbstract":"\u003cp\u003e\u003cstrong\u003eBackground:\u003c/strong\u003e Sexual intercourse is integral part of physical well-being health especially in married couple's life. Unhappiness and life dissatisfaction can be positively influenced by sexual inactivity. Sexual inactivity has recently been subject to increased scrutiny from public health perspectives. This project targeted to examine the socio-demographic determinants of sexual inactivity in Bangladeshi women of childbearing age.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eMethod:\u003c/strong\u003e Data from the most recent Bangladesh Health and Demographic Survey (BDHS) conducted in 2022 was utilized. Our study was considered a two-stage stratified sampling technique and cross-sectional design. Sexual inactivity was defined as no sexual frequency among reproductive women in the last month. The analysis included 14650 reproductive women aged 15–49 years. The associations between sexual inactivity and exposure variables were evaluated using the Pearson's Chi-square test, and the prediction model considered the multivariable logistic regression.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eResults:\u003c/strong\u003e The prevalence of sexual inactivity among reproductive women in Bangladesh was 6.72% (95% CI: 0.93-0.94). The likelihood of sexual inactivity was more pointedly among married women who live in the Dhaka region, Khulna region, and Sylhet region [p\u0026lt;0.05] compared to the Chittagong region. Women who had household heads [p\u0026lt;0.001] were significantly less likely to report sexual inactive than those who had no household heads. The odds of sexual inactivity were lower among women who had the age of ≥40 years [p\u0026lt;0.001] compared to their counterparts. Women whose height below \u0026lt;164cm were [p\u0026lt;0.001] had significantly higher chances of sexual inactivity. Sexually inactive significantly higher odds of being women who had\u003cstrong\u003e \u003c/strong\u003ea husband/partner are age of\u003cstrong\u003e \u003c/strong\u003e30- 40 years [p=0.036]. Unemployment husband/partner's (p=0.014) were less likely to be sexually inactive.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eConclusion:\u003c/strong\u003e Demographic factors such as women's age significantly affect sexual inactivity (SI) among the women in their reproductive age in Bangladesh. To overcome SI problem government and nongovernmental organization must take effective measures to improve women education level, reproductive health-care service, including sexual health of childbearing age.\u003c/p\u003e","manuscriptTitle":"Socio-demographic determinants of sexual inactivity among reproductive married women in Bangladesh: Evidence of BDHS data 2022","msid":"","msnumber":"","nonDraftVersions":[{"code":1,"date":"2025-03-27 09:36:41","doi":"10.21203/rs.3.rs-5823750/v1","editorialEvents":[{"type":"communityComments","content":0},{"type":"decision","content":"Revision requested","date":"2025-04-14T19:40:08+00:00","index":"","fulltext":""},{"type":"editorInvitedReview","content":"","date":"2025-04-13T20:59:59+00:00","index":"hide","fulltext":""},{"type":"editorInvitedReview","content":"","date":"2025-04-07T15:06:35+00:00","index":"hide","fulltext":""},{"type":"reviewerAgreed","content":"20258754157512716343832041825058996647","date":"2025-04-07T14:12:47+00:00","index":"hide","fulltext":""},{"type":"reviewerAgreed","content":"271018883141215111086254081568577632412","date":"2025-04-02T20:03:23+00:00","index":"hide","fulltext":""},{"type":"editorInvitedReview","content":"","date":"2025-03-30T00:47:08+00:00","index":"hide","fulltext":""},{"type":"reviewerAgreed","content":"154394202372037578647976477411878727000","date":"2025-03-26T16:59:48+00:00","index":"hide","fulltext":""},{"type":"reviewersInvited","content":"","date":"2025-03-26T15:39:26+00:00","index":"","fulltext":""},{"type":"checksComplete","content":"","date":"2025-03-26T00:37:47+00:00","index":"","fulltext":""},{"type":"submitted","content":"Reproductive Health","date":"2025-03-25T02:36:25+00:00","index":"","fulltext":""}],"status":"published","journal":{"display":true,"email":"[email protected]","identity":"reproductive-health","isNatureJournal":false,"hasQc":true,"allowDirectSubmit":false,"externalIdentity":"reph","sideBox":"Learn more about [Reproductive Health](http://reproductive-health-journal.biomedcentral.com)","snPcode":"12978","submissionUrl":"https://submission.nature.com/new-submission/12978/3","title":"Reproductive Health","twitterHandle":"@Reprod_Health","acdcEnabled":true,"dfaEnabled":true,"editorialSystem":"em","reportingPortfolio":"BMC/SO AJ","inReviewEnabled":true,"inReviewRevisionsEnabled":true}}],"origin":"","ownerIdentity":"e5120aad-096f-4e16-af3f-f1e76ee9e3b8","owner":[],"postedDate":"March 27th, 2025","published":true,"recentEditorialEvents":[],"rejectedJournal":[],"revision":"","amendment":"","status":"published-in-journal","subjectAreas":[],"tags":[],"updatedAt":"2026-03-16T16:03:04+00:00","versionOfRecord":{"articleIdentity":"rs-5823750","link":"https://doi.org/10.1186/s12978-025-02099-7","journal":{"identity":"reproductive-health","isVorOnly":false,"title":"Reproductive Health"},"publishedOn":"2026-03-10 15:59:33","publishedOnDateReadable":"March 10th, 2026"},"versionCreatedAt":"2025-03-27 09:36:41","video":"","vorDoi":"10.1186/s12978-025-02099-7","vorDoiUrl":"https://doi.org/10.1186/s12978-025-02099-7","workflowStages":[]},"version":"v1","identity":"rs-5823750","journalConfig":"researchsquare"},"__N_SSP":true},"page":"/article/[identity]/[[...version]]","query":{"redirect":"/article/rs-5823750","identity":"rs-5823750","version":["v1"]},"buildId":"XKTyCvWXoU3ODBz1xrDgd","isFallback":false,"isExperimentalCompile":false,"dynamicIds":[84888],"gssp":true,"scriptLoader":[]}