Association of reproductive and gender-related characteristics with cardiovascular risk factors of women in India: an analysis of nationally representative data

Association of reproductive and gender-related characteristics with cardiovascular risk factors of women in India: an analysis of nationally representative data | medRxiv /* */ /* */ <!-- <!-- /*! * yepnope1.5.4 * (c) WTFPL, GPLv2 */ (function(a,b,c){function d(a){return"[object Function]"==o.call(a)}function e(a){return"string"==typeof a}function f(){}function g(a){return!a||"loaded"==a||"complete"==a||"uninitialized"==a}function h(){var a=p.shift();q=1,a?a.t?m(function(){("c"==a.t?B.injectCss:B.injectJs)(a.s,0,a.a,a.x,a.e,1)},0):(a(),h()):q=0}function i(a,c,d,e,f,i,j){function k(b){if(!o&&g(l.readyState)&&(u.r=o=1,!q&&h(),l.onload=l.onreadystatechange=null,b)){"img"!=a&&m(function(){t.removeChild(l)},50);for(var d in y[c])y[c].hasOwnProperty(d)&&y[c][d].onload()}}var j=j||B.errorTimeout,l=b.createElement(a),o=0,r=0,u={t:d,s:c,e:f,a:i,x:j};1===y[c]&&(r=1,y[c]=[]),"object"==a?l.data=c:(l.src=c,l.type=a),l.width=l.height="0",l.onerror=l.onload=l.onreadystatechange=function(){k.call(this,r)},p.splice(e,0,u),"img"!=a&&(r||2===y[c]?(t.insertBefore(l,s?null:n),m(k,j)):y[c].push(l))}function j(a,b,c,d,f){return q=0,b=b||"j",e(a)?i("c"==b?v:u,a,b,this.i++,c,d,f):(p.splice(this.i++,0,a),1==p.length&&h()),this}function k(){var a=B;return a.loader={load:j,i:0},a}var l=b.documentElement,m=a.setTimeout,n=b.getElementsByTagName("script")[0],o={}.toString,p=[],q=0,r="MozAppearance"in l.style,s=r&&!!b.createRange().compareNode,t=s?l:n.parentNode,l=a.opera&&"[object Opera]"==o.call(a.opera),l=!!b.attachEvent&&!l,u=r?"object":l?"script":"img",v=l?"script":u,w=Array.isArray||function(a){return"[object Array]"==o.call(a)},x=[],y={},z={timeout:function(a,b){return b.length&&(a.timeout=b[0]),a}},A,B;B=function(a){function b(a){var a=a.split("!"),b=x.length,c=a.pop(),d=a.length,c={url:c,origUrl:c,prefixes:a},e,f,g;for(f=0;f<d;f++)g=a[f].split("="),(e=z[g.shift()])&&(c=e(c,g));for(f=0;f<b;f++)c=x[f](c);return c}function g(a,e,f,g,h){var i=b(a),j=i.autoCallback;i.url.split(".").pop().split("?").shift(),i.bypass||(e&&(e=d(e)?e:e[a]||e[g]||e[a.split("/").pop().split("?")[0]]),i.instead?i.instead(a,e,f,g,h):(y[i.url]?i.noexec=!0:y[i.url]=1,f.load(i.url,i.forceCSS||!i.forceJS&&"css"==i.url.split(".").pop().split("?").shift()?"c":c,i.noexec,i.attrs,i.timeout),(d(e)||d(j))&&f.load(function(){k(),e&&e(i.origUrl,h,g),j&&j(i.origUrl,h,g),y[i.url]=2})))}function h(a,b){function c(a,c){if(a){if(e(a))c||(j=function(){var a=[].slice.call(arguments);k.apply(this,a),l()}),g(a,j,b,0,h);else if(Object(a)===a)for(n in m=function(){var b=0,c;for(c in a)a.hasOwnProperty(c)&&b++;return b}(),a)a.hasOwnProperty(n)&&(!c&&!--m&&(d(j)?j=function(){var a=[].slice.call(arguments);k.apply(this,a),l()}:j[n]=function(a){return function(){var b=[].slice.call(arguments);a&&a.apply(this,b),l()}}(k[n])),g(a[n],j,b,n,h))}else!c&&l()}var h=!!a.test,i=a.load||a.both,j=a.callback||f,k=j,l=a.complete||f,m,n;c(h?a.yep:a.nope,!!i),i&&c(i)}var i,j,l=this.yepnope.loader;if(e(a))g(a,0,l,0);else if(w(a))for(i=0;i (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];var j=d.createElement(s);var dl=l!='dataLayer'?'&l='+l:'';j.src='//www.googletagmanager.com/gtm.js?id='+i+dl;j.type='text/javascript';j.async=true;f.parentNode.insertBefore(j,f);})(window,document,'script','dataLayer','GTM-P4HH5NV'); Skip to main content Home About Submit ALERTS / RSS Search for this keyword Advanced Search Association of reproductive and gender-related characteristics with cardiovascular risk factors of women in India: an analysis of nationally representative data View ORCID Profile Vinita Subramanya , View ORCID Profile Shakira Suglia , View ORCID Profile K.M. Venkat Narayan , View ORCID Profile Suryakant Yadav , View ORCID Profile Robin A. Richardson , View ORCID Profile Alvaro Alonso , View ORCID Profile Shivani A. Patel doi: https://doi.org/10.1101/2025.05.02.25326891 Vinita Subramanya 1 Department of Epidemiology, Rollins School of Public Health, Emory University , Atlanta, GA MBBS, MPH, PhD Find this author on Google Scholar Find this author on PubMed Search for this author on this site ORCID record for Vinita Subramanya For correspondence: vinitasubramanya{at}gmail.com Shakira Suglia 1 Department of Epidemiology, Rollins School of Public Health, Emory University , Atlanta, GA ScD Find this author on Google Scholar Find this author on PubMed Search for this author on this site ORCID record for Shakira Suglia K.M. Venkat Narayan 2 Hubert Department of Global Health, Rollins School of Public Health, Emory University , Atlanta, GA 3 Emory Global Diabetes Research Center, Woodruff Health Sciences Center and Emory University , Atlanta, USA MD, MSc, MBA Find this author on Google Scholar Find this author on PubMed Search for this author on this site ORCID record for K.M. Venkat Narayan Suryakant Yadav 4 International Institute for Population Sciences , Mumbai, India MSc, MPS, PhD Find this author on Google Scholar Find this author on PubMed Search for this author on this site ORCID record for Suryakant Yadav Robin A. Richardson 1 Department of Epidemiology, Rollins School of Public Health, Emory University , Atlanta, GA MPH, PhD Find this author on Google Scholar Find this author on PubMed Search for this author on this site ORCID record for Robin A. Richardson Alvaro Alonso 1 Department of Epidemiology, Rollins School of Public Health, Emory University , Atlanta, GA MD, PhD Find this author on Google Scholar Find this author on PubMed Search for this author on this site ORCID record for Alvaro Alonso Shivani A. Patel 2 Hubert Department of Global Health, Rollins School of Public Health, Emory University , Atlanta, GA 3 Emory Global Diabetes Research Center, Woodruff Health Sciences Center and Emory University , Atlanta, USA MPH, PhD Find this author on Google Scholar Find this author on PubMed Search for this author on this site ORCID record for Shivani A. Patel Abstract Full Text Info/History Metrics Supplementary material Data/Code Preview PDF Abstract Introduction Women have unique characteristics based on their biological sex and gender that could contribute to their cardiovascular risk. This paper investigates the association between reproductive and gender-related characteristics on cardiovascular risk factors (CVRF) among women in India. Methods This cross-sectional analysis included 54,200 women aged 18-49 years from the National Family Health Survey-5, restricted to participants interviewed for the state or domestic violence module. Associations of reproductive characteristics (age at first birth, use of contraception, the total number of children born, pregnancy loss) and gender-related characteristics (age at first union, access to financial resources, owning property, currently working, experience of intimate partner violence) with CVRF (diabetes, hypertension, overweight or obesity) were estimated with Poisson regression. Analyses stratified by socioeconomic status, measured by education, were also performed. Results Women who had their first childbirth before the age of 20 years had a higher prevalence of all assessed CVRF across socioeconomic groups. Pregnancy loss was associated with a higher prevalence of being overweight or obese [prevalence ratio (PR) (95% CI): 1.16 (1.09, 1.23)], while an early age at first union (< 20 years) was linked to a greater prevalence of hypertension [PR (95% CI): 1.09 (1.02, 1.17)] that persisted across socioeconomic groups. Intimate partner violence was associated with a higher prevalence of hypertension in women with a primary school education or lower [PR (95% CI): 1.15 (1.05, 1.25)]. Conclusion The association of reproductive and gender-related characteristics with CVRF across the socioeconomic spectrum underscores the importance of integrated consideration of biological and social determinants to evaluate cardiovascular risk in women. Introduction Although cardiovascular disease is the leading cause of death in women, women remain underrepresented in cardiovascular research. Moreover, health research among women has primarily focused on issues related to pregnancy and the postpartum period. Cardiovascular disease in women of reproductive age is uniquely shaped by both biological sex and gender-related factors. Sex—a biological construct determined by reproductive characteristics— influences the distribution of cardiovascular risk factors (CVRF) such as hypertension, diabetes, and obesity as well as cardiovascular outcomes.( 1 , 2 , 3 , 4 , 5 , 6 , 7 , 8 ) Gender—a multidimensional social construct shaped by an individual’s body, identity, and self-expression within a societal framework—( 9 ) has been less well studied in relation to cardiovascular disease (CVD). While sex and gender are distinct concepts, they overlap because the societal construction of gender roles often incorporates biological sex characteristics.( 6 , 10 , 11 , 12 ) Understanding cardiovascular risk in women requires examining biological and social factors and their intersection. With respect to reproductive characteristics unique to women, sex hormones such as estrogen and progesterone play a major role. While these hormones are typically cardioprotective and integral to reproduction, they can increase cardiovascular risk when present at non- physiological levels.( 13 , 14 , 15 ) During reproduction, pregnancy-induced hemodynamic changes and hormonal fluctuations( 16 , 17 ) can contribute to this increased risk. Reproductive characteristics, such as age at menarche and menopause, parity, short birth intervals, and pregnancy outcomes, also influence the development of CVD in women.( 18 , 19 , 20 , 21 , 22 , 23 , 24 , 25 ) With respect to gender, multiple direct and indirect influences on cardiovascular risk are supported by the literature.( 6 ) Gender roles, a set of culturally and socially determined traits, influence health and lifestyle choices.( 26 , 27 , 28 , 29 , 30 , 31 ) Women often engage in sedentary behavior and experience unique stressors related to caregiving, work-family life, gender discrimination, finances, and experiences of violence and abuse, contributing to chronic stress.( 6 ) Prolonged stress and inflammation can increase cardiovascular disease risk through multiple pathways, including elevated blood pressure, lipids, and blood glucose.( 6 ) Patriarchal power dynamics favor men’s access to opportunities and resources, limiting women’s financial access, asset ownership, decision-making, and autonomy, which have a detrimental effect on health and act as a barrier to healthcare access and utilization.( 26 , 27 , 28 , 29 , 32 , 33 ) India is a particularly rich setting to investigate the intersection of sex and gender in relation to CVD. Reproductive histories in India differ from those observed in high-income country settings, and strong social structures influence gender norms regarding health behaviors.( 34 ) Disparities in socioeconomic development have further complicated the relationship between gender, social structures, and cardiovascular health. Prior work in India indicates higher CVRF prevalence among the socioeconomically advantaged but higher mortality among the disadvantaged.( 35 , 36 , 37 ) Women disproportionately face health disparities driven by high inequality and poverty.( 38 , 39 ) This, along with shifting gender roles and related changes in lifestyles and health behaviors may impact CVD risk but have not yet been studied.( 40 , 41 ) Focusing on a single aspect of the biological or social components of women’s unique risks constrains our understanding of health inequalities arising from multiple intersecting processes. Therefore, this study adopted a woman-focused conceptual framework to clarify the role of reproductive and gender-related characteristics on CVRFs across educational attainment. The objectives were to evaluate the cross-sectional associations between reproductive and gender- related characteristics with CVRFs and ii) examine whether observed associations between reproductive and gender-related factors differed by educational attainment. Methods Data sources and study population The National Family Health Survey (NFHS), conducted by the International Institute for Population Sciences under the aegis of the Ministry of Health and Family Welfare, is a nationally representative, comprehensive, multi-round cross-sectional survey of households.( 42 ) NFHS-5 (2019–21), the fifth and most recent round, included data from 724,115 women from 636,699 households recruited through a stratified two-stage sampling approach.( 42 ) The sampling methodology has been described previously.( 42 ) An additional state or domestic violence module with information on gender-related and socioeconomic characteristics was administered in a random sub-sample of 15% of participants, where one woman per eligible household was included.( 42 ) This study was restricted to married women aged 18-49 years from the domestic violence module (N=72,320). The analytic sample ( Figure 1 ) comprised 54,200 ever-married women with complete information for study covariates. Download figure Open in new tab Figure 1: Sampling strategy used in National Family Health Survey-5 Download figure Open in new tab Figure 2: Participant flow diagram Study measures The study utilized information from three instruments: a household survey collecting sociodemographic and socioeconomic details; a women’s survey assessing reproductive, marital, and sexual history, women’s empowerment, and domestic violence; and a biomarker assessment measuring anthropometry, blood pressure, and random blood glucose. 1. Cardiovascular risk factors Diabetes was defined by the presence of any of the following: self-reported diabetes, use of glucose-lowering medication, a diagnosis of high blood glucose levels on at least two separate occasions, or a random blood glucose level exceeding 200 mg/dL. Hypertension was defined as a systolic blood pressure (SBP) of ≥140 mm Hg or a diastolic blood pressure (DBP) of ≥90 mm Hg or using blood pressure lowering medication or a diagnosis of high blood pressure on two separate occasions. These cut-offs were based on the Indian Guidelines for Hypertension- IV.( 43 ) Height and weight were used to calculate the body mass index. Overweight and obese status were defined using a body mass index cutoff of >25 kg/m 2 . 2. Reproductive characteristics Reproductive characteristics were self-reported and included use of contraception, the total number of children born, age at first birth (among those reporting any birth), and pregnancy loss. Contraceptive usage was categorized as ( 1 ) not using any method, ( 2 ) use of a modern method (sterilization, injectables, intrauterine devices, oral contraceptive pills, implants, barrier methods such as condoms and diaphragm, foam/jelly, standard days method, lactational amenorrhea method, and emergency contraceptive pills), and ( 3 ) use of a traditional method (including rhythm, withdrawal, and other traditional methods).( 42 ) Pregnancy loss or having ever had a pregnancy not resulting in a live birth included information on spontaneous abortions, medical termination of pregnancy, and stillbirth.( 42 ) 3. Gender-related characteristics Gender-related indicators included those suggestive of a woman’s autonomy over their life choices for the improvement of their social, political, economic, and health status, such as age at first union (restricted to those ever reporting a union), access to financial resources such as owning and operating a bank account, owning property as well as, the experience of intimate partner violence (IPV). Information on IPV included any experience of physical, sexual, or emotional IPV and compared to having no experience of violence.( 42 , 44 ) 4. Socioeconomic and demographic variables Socioeconomic status refers to an individual’s position within a stratified social structure, commonly determined by income, wealth, education, and occupation.( 45 , 46 ) In this study, educational attainment—a key indicator of socioeconomic status—was categorized into three levels: primary education or less, completed secondary education, and education beyond the secondary level. The current age of participants was analyzed as a continuous variable. Religion was categorized as Hindu, Muslim, and ‘Others’ due to sparse categories. Social caste was self-reported as belonging to a scheduled caste or tribe or other backward class. Place of residence was classified as urban or rural. Statistical analysis Data was described using mean (standard deviation) or percentage for continuous and categorical variables, as appropriate. In the primary analysis, associations of reproductive and gender-related characteristics with CVRFs were evaluated using Poisson regression models with robust variance estimation to directly estimate prevalence ratios.( 47 ) Models were adjusted for sociodemographics and state of residence. For analyses evaluating reproductive characteristics, we stratified the sample by parity, as parous women who have experienced childbirth differ in their risk profile compared to nulliparous women who have not experienced childbirth. We estimated models with multiplicative interactions between the primary exposures of interest (reproductive and gender-related characteristics) and educational attainment to evaluate whether associations differed by educational attainment. Analyses applied state module survey weights and were conducted using Stata SE (version 18). Results Distribution of socioeconomic, reproductive, and gender-related characteristics Less than 10% of the study population comprised nulliparous women (N=4,542). Among parous women, the mean (SD) age of the women in the study was 35.0 (8.1) years ( Table 1 ). About 70% of participants lived in rural parts of India. About 12% of women had completed secondary or higher education, and 37% were employed. Forty-four percent of parous women had their first childbirth between 15-19 years of age. Examination of gender-related characteristics showed that over 95% of all women were married for the first time by age 30 ( Table 1 ), and 30% experienced some form of intimate partner violence. The overall prevalence of hypertension was 23%, diabetes was 6%, and overweight or obesity was 29%. Nulliparous women were younger, with a mean (SD) age of 26.2 (8.0). About 30% of them had completed secondary school or higher. The prevalence of CVRFs was lower in nulliparous women as compared to parous women. View this table: View inline View popup Table 1: Characteristics of women (18-49 years) in the National Family Health Survey-5* Association between reproductive characteristics and cardiovascular risk factors Associations between reproductive characteristics and CVD risk factors among women who have ever given birth are shown in Table 2 . A higher prevalence of hypertension was observed among women with age at first birth younger than 20 years (ref: 20-29 years) [PR (95% CI): 1.11 (1.04, 1.19)] after adjusting for sociodemographics. As with hypertension, a higher prevalence of diabetes was seen among women with age at first birth younger than 20 years [PR (95% CI): 1.17 (1.00, 1.37)] in fully adjusted models. In contrast, a lower prevalence of diabetes was observed with the use of modern methods of contraception (ref: no contraceptive use) [PR (95% CI): 0.81 (0.69, 0.95)] after adjusting for sociodemographics. In fully adjusted models, a higher prevalence of being overweight or obese was observed among women with two children (ref: one child) [PR (95%CI): 1.15 (1.07, 1.24)], among women with age at first birth younger than 20 years [PR (95% CI): 1.06 (1.00, 1.12)], and among those who experienced a pregnancy loss (ref: no pregnancy loss) [PR (95% CI): 1.16 (1.09, 1.23)]. View this table: View inline View popup Table 2: Cross-sectional associations between reproductive characteristics and prevalence of cardiovascular risk factors among parous women (18-49 years), in the NFHS-5 (N=49,658) Association between gender-related characteristics and cardiovascular risk factors Associations between gender-related characteristics and CVD risk factors among parous women are shown in Table 3 . A greater prevalence of hypertension was observed among women with age at first union younger than 20 years (ref: 20-29 years) [PR (95% CI): 1.09 (1.02, 1.17)] in fully adjusted models. A lower prevalence of diabetes was associated with being currently unemployed (ref: employed) [PR (95% CI): 0.76 (0.58, 1.00)] whereas owning a bank account was associated with a higher prevalence of diabetes [PR (95% CI): 1.22 (1.01, 1.46)]. There were no significant associations between gender-related characteristics and being overweight/obese. View this table: View inline View popup Table 3: Cross-sectional associations between gender-related characteristics and prevalence of cardiovascular risk factors among women (18-49 years) in the NFHS-5 (N= 54,200) Associations by educational attainment In the education-stratified analysis for reproductive characteristics, there were no meaningful interactions in parous women ( Table 4 ). A younger age at first birth was generally associated with all evaluated CVRF. However, these associations were not always statistically significant. The association between other reproductive characteristics and CVRF across subgroups of educational attainment was similar to the primary analysis. Similarly, the association between gender-related characteristics and CVRF was similar to the primary analysis ( Table 5 ). Among women with the lowest educational attainment, there was a statistically significant (p-value for interaction=0.01) greater prevalence of hypertension as compared to other educational attainment groups [PR (95% CI): 1.15 (1.05, 1.25)]. Conversely, there was a statistically significant (p-value for interaction = 0.05) association among women with the highest level of educational attainment, associated with a higher prevalence of diabetes as compared to other subgroups [PR (95% CI): 1.88 (1.16, 3.06)]. View this table: View inline View popup Table 4: Associations between reproductive characteristics and prevalent cardiovascular risk factors stratified by educational attainment among parous women (18-49 years) in the NFHS-5 View this table: View inline View popup Table 5: Cross-sectional associations between gender-related characteristics and prevalence of cardiovascular risk factors among women (18-49 years) in the NFHS-5, stratified by educational attainment Discussion In a large nationally representative sample of Indian women, we found that reproductive and gender-related characteristics were associated with prevalent hypertension, diabetes, and obesity. With respect to reproductive history, women who had their first childbirth before the age of 20 years had a higher prevalence of all assessed CVRFs. Experiencing pregnancy loss was consistently associated with a greater prevalence of being overweight or obese, while the use of modern contraceptives was linked to a lower prevalence of diabetes. On examining gender- related characteristics, an earlier age at first union was positively associated with hypertension. Associations were broadly consistent in direction across socioeconomic subgroups. These findings underscore the importance of considering reproductive life events and gender-related experiences in the evaluation of cardiovascular health across the socioeconomic spectrum in India. Our study revealed that first childbirth during teenage years was associated with a higher prevalence of CVRF. This adds to prior NFHS-4 findings, which also linked adolescent childbirth to a higher prevalence of hypertension.( 48 ) While prior research suggests a U-shaped relationship between age at first birth and CVD risk, i.e., an increased risk at both younger and older ages, this association has been inconsistent across studies.( 17 , 49 , 50 , 51 ) As demonstrated in high-income countries, the link between reproductive factors and CVD has a strong biological basis.( 16 , 17 ) Cardiovascular risk due to a younger age at first birth, however, is thought to have a biological, social, and behavioral basis.( 17 ) Physiologically, adolescent pregnancy triggers unique changes in the body due to the ongoing growth of the adolescent mother, leading to higher weight gain and retention (ref: mothers with older age at first birth), which can increase CVD risk.( 17 ) Their exposure to physiological changes of pregnancy also occurs earlier in life and may irreversibly change their trajectory of cardiovascular risk as compared to women who have childbirth later in life. Socially and behaviorally, adolescent pregnancy can lead to adverse life circumstances, including an incomplete education, reduced economic opportunities, social isolation, and even exposure to violence.( 17 ) These factors contribute to cumulative adversity and increase CVD risk by limiting access to resources and social support while also perpetuating stress and unhealthy living conditions. Together, these interconnected factors suggest that giving birth prior to reaching 20 years of age may negatively impact cardiovascular health through multiple compounding pathways. We observed conflicting associations between parity and CVD risk factors. While we observed a higher prevalence of being overweight or obese in women with two children (ref: one child), there were no associations between higher parity and diabetes or hypertension. Higher parity is expected to increase CVD risk through repeated physiological changes during pregnancy and the associated metabolic changes.( 52 ) Indeed, several studies in the United States and Britain have demonstrated a J-shaped association between parity and CVD risk (Atherosclerosis Risk in Communities and British Regional Heart Study).( 53 , 54 ) Findings from India, however, contrast from these studies and have been inconsistent. In an earlier study using NFHS-4 data, each additional childbirth was associated with significantly lower systolic and diastolic blood pressure, sustained up to 10 years post-childbirth.( 55 ) While sociocultural factors may account for some of the differences, we did not find any meaningful differences in subgroups of educational attainment and occupation status. Additionally, some of our findings could be explained by the cardioprotective effects of breastfeeding, which were unaccounted for,( 53 ) or higher parity in earlier birth cohorts that were less exposed to obesogenic environments. The role of parity in CVD risk warrants further investigation in prospective studies. In our study, contraceptive use was categorized into traditional and modern methods, with the latter including hormonal methods (e.g.: oral contraceptives) and non-hormonal methods (e.g.: barrier methods, sterilization). Modern contraceptive methods were linked to a lower prevalence of diabetes among parous women, though this association was not always statistically significant. Supplemental analyses (data not shown) showed there were no associations between oral contraceptive pill use and CVRFs, which may be due to the relatively low usage of oral contraception (around 5%) among women in India. Oral contraceptive pills (OCP) increase cardiovascular risk through the atherogenic effects of estrogen exerted through blood pressure and lipid level elevations.( 56 , 57 ) Earlier formulations with higher estrogen content were linked to elevated blood pressure, even among normotensive women, with an increase in thromboembolic events.( 58 , 59 ) However, more recent analyses challenge these views, suggesting that OCP use might be associated with no or lower risk of cardiovascular events, with prolonged use further reducing these risks.( 60 , 61 ) The underlying mechanism contributing to the protective associations observed in our paper is unclear as we could not cleanly parse out the hormonal from the non-hormonal effects. In this study, pregnancy loss captured stillbirths, spontaneous abortions, and medically terminated pregnancies. Stillbirths and spontaneous abortions, via genetic and immunological pathways, lead to endothelial dysfunction and inflammation, thereby increasing the risk for atherosclerosis, diabetes, and hypertension.( 62 ) In medically terminated pregnancies secondary to maternal health conditions, the increased CVD risk is presumed to be due to the underlying medical issue.( 63 ) Further, increased CVD risk occurs with recurrent pregnancy losses, especially with short intervals.( 63 , 64 , 65 , 66 , 67 ) In our analysis, we observed that both parous and nulliparous women who experienced a pregnancy loss were more likely to be overweight or obese. However, we were unable to determine the direction of causality and if there were underlying conditions, such as polycystic ovarian disease, that drove this association. Gender-related characteristics related to CVRFs have not been studied in the same detail as reproductive characteristics. Conceptually, gender-related characteristics may relate to CVRFs through biological, social, and behavioral pathways. We found that a younger age at first union was associated with a higher prevalence of hypertension. A prior analysis from the India Human Development Survey linked early marriage to a range of health issues in women, including greater functional limitations, poorer self-rated health, and a higher prevalence of diabetes, hypertension, and cardiovascular disease in mid-life.( 68 ) Our study aligns with some of these findings, demonstrating an association between younger age at first marriage and the prevalence of hypertension. The greater prevalence of CVRFs seen with an early age at first marriage could, in part, be attributed to alterations in cardiovascular risk profiles related to pregnancy. Beyond these direct health implications, early marriage adversely impacts educational attainment, correlates with lower empowerment and agency, and is associated with a higher prevalence of intimate partner violence. ( 69 , 70 , 71 ) Intimate partner violence is a significant factor impacting a woman’s well-being, although the specific mechanisms linking violence with physical health are still under investigation.( 72 ) In our study, women who experienced IPV had a lower prevalence of being overweight or obese. However, this association did not persist when accounting for sociodemographics. Prior research indicates that early-life abuse—be it physical, sexual, or emotional—increases the risk of developing cardiovascular disease in later life.( 73 , 74 ) In adults, physical or sexual IPV is linked to increased abdominal obesity, reduced high-density lipoprotein cholesterol, elevated triglycerides, and greater long-term requirement for anti-hypertensive medication.( 75 ) Notably, one study extended these findings to include both victims and perpetrators of IPV, observing an increased cardiovascular risk in both groups.( 76 ) A comprehensive understanding of the mechanistic pathways linking IPV to CVD risk is needed, particularly its impact at various life stages and its long-term sequelae in later life. Financial stress negatively impacts health. Our study focused on financial inclusion, measured through the ownership and operation of a bank account and property ownership, individually or jointly. Contrary to our hypothesis that financial inclusion would correlate with better cardiovascular health, we did not find any consistent associations between bank account ownership and/or owning property with CVRFs. Financial inclusion influences health through greater healthcare utilization.( 77 ) Along with property rights, it is pivotal in fostering sustainable livelihoods for women, offering economic security, enhancing their bargaining power, and elevating their status in the community.( 78 ) Our analysis could not assess utilization indicators relevant to cardiovascular disease, such as hospital visits, hospitalization rates, prescription drug use, mortality rates, and patient self-management indicators or medication use, a consideration for future research. The results of this study should be interpreted considering its strengths and limitations. The study addressed a significant gap in existing research by focusing on gender, reproductive health, and cardiovascular risk in a low- to middle-income country setting. This is particularly important as most existing literature centers on high-income countries, and this study offers insights specific to a different socioeconomic and cultural context. We used a large, comprehensive, nationally representative sample of women in India between 18 and 49 years of age. Given the younger age profile of the study’s participants, there may have been insufficient time for CVRFs to develop within the lifecourse. While the cross-sectional design limits the ability to establish causality, it offers a valuable snapshot of associations between variables in a real-world setting. The study offers insights and directions for subsequent research efforts. Although the study adjusts for a range of sociodemographic variables, there remains the possibility of residual confounding by behavioral and clinical factors that are known to influence cardiovascular risk. The reliance on self-reported data for several variables, including reproductive history and experiences of intimate partner violence, may introduce reporting biases in the absence of medical records to corroborate the same. Experiences of intimate partner violence are known to be underreported, and it is possible that this was the case in the NFHS as well, which could have resulted in an underestimation of its impact on CVRFs. Another limitation of this study was the separation of sex and gender-related characteristics, which does not accurately reflect their interrelated nature, such as parity and the preference for sons. This is an opportunity for future research to explore how sex and gender influence cardiovascular risk in a more integrated manner. The findings of this study have both clinical and research implications. Given the high prevalence of early marriage and childbearing among girls and women and the associated health ramifications, healthcare professionals need to identify at-risk individuals for screening and follow-up. Shifting fertility preferences and childbearing patterns in India necessitate an in- depth exploration of the relationship between nulliparity and cardiovascular risk. This exploration should distinguish between women who choose not to have children and those unable to do so for medical reasons. Mechanistic studies that link early age at first marriage and childbirth, pregnancy loss, contraceptive use, and IPV to cardiovascular risk are needed. Lifecourse studies are needed to examine the cumulative effects of adverse social exposures on cardiovascular risk. Given the pervasiveness of IPV, the development of integrated screening protocols in healthcare settings to identify women experiencing IPV and implement interventions to alleviate the associated health and safety risks. Incorporating sex- and gender-specific factors into cardiovascular risk assessment tools and using gender-related and intersectional analyses in research will help better understand health inequities and improve risk evaluation for women. Data Availability The dataset (name: IAIR7ADT) used in the current analysis was obtained through a request to the Demographic and Health Surveys. List of abbreviations CVRF Cardiovascular risk factor CVD Cardiovascular disease NFHS National Family Health Survey SBP Systolic blood pressure DBP Diastolic blood pressure IPV Intimate partner violence SD Standard deviation PR Prevalence ratio CI Confidence interval Declarations Ethics approval and consent to participate This study was reviewed and approved by the Emory Institutional Review Board under 45 CFR 46.110 and/or 21 CFR 56.110. Consent for publication Not applicable Availability of data and materials The dataset (name: IAIR7ADT) used in the current analysis was obtained through a request to the Demographic and Health Surveys. Competing interests The authors declare that they have no competing interests. Funding The authors acknowledge funding from the American Heart Association Pre-Doctoral Fellowship (Award ID 0000060880, PI: Vinita Subramanya) that supported this work. Authors’ contributions VS conceptualized the study, performed the analysis, and prepared the manuscript. 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