Spousal age difference and risk of hypertension in women: evidence from India

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However, most of the extant evidence is based on population from the developed countries. Using nationally representative data from India, this cross-sectional study explores whether spousal age gap is associated with risk of hypertension in married women aged 20 to 49 years. Based on the age difference with their husbands, women were grouped into four categories: husband was – i) of similar age, ii) 3–5 years older, iii) 6–9 years older, and iv) 10 + years older. Compared to women whose husbands were of similar age, the odds of having hypertension for the other categories were assessed by estimating multivariable logistic regression models. While the hypertension prevalence in our sample was 18.9%, it was 2.2%-points lower among women whose husbands were of similar age, and 3.3%-points higher among women whose husbands were 10 + years older. The adjusted odds of having hypertension for women with 10 + years of spousal age difference were 1.18 (95% CI: 1.13–1.24) times that of their counterparts who were of similar age to their husbands. These results were persistent in both younger (age 20–34) and older (age 35–49) women and robust across age at marriage, years in marriage, and various socioeconomic sub-groups including women’s educational attainment, husband’s educational level, household wealth, urban/rural residence, and geographic regions. The relationship also persisted after adjusting for husband’s hypertension status. Our findings thus highlight spousal age difference as a biopsychosocial factor influencing the risk of hypertension in women. Health sciences/Risk factors Health sciences/Health care/Disease prevention/Preventive medicine Figures Figure 1 Summary Table What is known about topic Spousal age gap is associated with male dominance in decision making and intimate partner violence. Perceived spouse dominance can influence cardiovascular reactivity. What this study adds Spousal age gap is potentially a biopsychosocial risk factor of hypertension in women. Women who were younger than their husbands by 10+ years, had a higher risk of hypertension compared to women who were of similar age to their husbands. Background Common risk factors for hypertension include an unhealthy diet, physical inactivity, tobacco- and alcohol- consumption, and being overweight or obese [ 1 ]. These modifiable risk factors are further influenced by age, sex, race and ethnicity, and other elements of an individual’s life such as geographical location and socioeconomic status conditions [ 2 ]. While the role of socioeconomic status and environmental conditions on hypertension outcome are commonly explored [ 3 , 4 , 5 , 6 ], there is a dearth of evidence on the potential influence of psychosocial factors, which, under the social ecological model of health, can act as important determinants of health outcomes [ 7 ]. As such, these factors can play a role in the development and progression of cardiometabolic conditions such as hypertension [ 8 , 9 ]. For example, the spousal concordance of hypertension is a commonly observed phenomenon, which is presumably connected with similar socioeconomic and environmental exposures among a husband and wife within a household [ 10 ]. However, the role of certain spousal characteristics, such as spousal age differences, or the spousal age gap, on hypertension risk, especially in the low-and-middle income countries (LMICs) has not yet been explored. The literature on the health impact of spousal age gap has largely revolved around intimate partner violence (IPV) and contraceptive use [ 11 , 12 ]. Findings of these studies suggest that women who are considerably younger than their husbands (e.g., by 10 + years) were more likely to experience violence and less likely to use contraception compared to their peers. Experiencing IPV and decision on contraceptive-use are also influenced by husband’s controlling behaviors among these women [ 13 , 14 ]. Given the risk of cardiovascular reactivity associated with perceived spouse dominance [ 15 ], spousal age difference can be regarded as a biopsychosocial factor influencing the risk of hypertension in women. While some recent studies explored related areas, such as the role of child marriage, early childbearing, and marital disruption in developing hypertension [ 16 , 17 ], the risk of hypertension specifically in relation to spousal age gaps has rarely been studied. In this study, we explored the potential role of spousal age difference in hypertension risk among married women in India, where age hypergamous marriages (i.e., wife younger than husband) are quite prominent [ 18 ]. India also has a high burden of hypertension with age standardized prevalence rate of 25.4% among adult women [ 19 ]. More concerning, over half of the hypertensive women in India remain unaware of their condition [ 19 ]. As such, recognizing psychosocial risk factors of hypertension, beyond the traditional risks, could facilitate better management of hypertension in India. Against this backdrop, the aim of this cross-sectional analysis was to assess whether higher spousal age gap was associated with greater risks of hypertension in a nationally representative sample of adult reproductive-aged (i.e., 20 to 49 years) women in India. Methods Data This observational study used data from the 2019-21 India National Family Health Survey (NFHS-5). Our sample comprised of 355 486 currently married women, aged 20 to 49 years, who were in marriage for at least 5 years and were not in multiple unions (i.e., not married more than once). The NFHS-5 utilized a stratified two-stage sampling framework to collect nationally representative data on various population health topics in India. The survey was administered under technical assistance from the USAID’s Demographic and Health Surveys (DHS) Program. The survey protocol was approved by the institutional review boards of the International Institute of Population Studies (IIPS) and the ICF [ 20 ]. We used publicly available anonymized data for analyses, which met the exempt human subject research definition (Exemption 4) of the National Institutes of Health (NIH). Ethical approval for this study, therefore, was not required. Measures Our outcome variable was a binary variable indicating whether a woman was hypertensive or not. Hypertension status was defined by average systolic blood pressure (SBP) ≥ 140 mmHg or average diastolic blood pressure (DBP) ≥ 90 mmHg or taking anti-hypertensive medication at the time of the survey [ 20 ]. Our exposure variable was a categorical variable denoting the age difference between husband and wife. Women were categorized in four categories: husband was – i) of similar age (i.e., age difference is ± 2 years), ii) 3–5 years older, iii) 6–9 years older, and iv) 10 + years older. Of note, 1.05% (N = 3,781) women were married to men who were 3 + years younger than their wives. These women were excluded from analysis since they constituted only a tiny fraction of the sample and thereby lacked statistical power to be analyzed as a separate category. We, however, checked that our results (for the four categories) would have remained unaffected if a fifth category, containing women who were older than their husbands by 3 + years, was included. Statistical analysis We estimated binomial logistic regressions to assess the odds of being hypertensive by spousal age difference categories, compared to that of women whose husband were of similar age. To address potential heterogeneity in the study population, we estimated the models for sub-groups by age (20–34 years and 35–49 years), by age at marriage (≤ 17 years, 18–21 years, and ≥ 22 years), and by years in marriage (5–9 years, 10–19 years, and ≥ 20 years). We estimated both unadjusted and adjusted forms of regressions. In the multivariable specification, we accounted for various sociodemographic and socioeconomic attributes along with common risk factors for hypertension. Sociodemographic characteristics included women’s age, religion, caste, urban/rural residence, and whether husband had multiple wives. Socioeconomic attributes included educational attainment, husband’s level of education, household wealth index quintiles. Hypertension risk factors included body mass index (BMI) categories, parity (i.e., number of children born), age at first marriage, tobacco use, alcohol use, menopausal status, pregnancy status, and lactation status. Further, geographic-region fixed effects were included in the model to account for regional differences in societal norms and health outcomes. While age and parity were continuous variables, all other covariates were binary or categorical variables. A complete list of categories of respective covariates is provided in Table 1. We also estimated a multivariable specification accounting for husband’s hypertension status along with other covariates. Next, we estimated models by sub-groups of husband’s hypertension status (i.e., husband did or did not have hypertension). Of note, husband’s hypertension status was not available for 10.4% (N = 36,909) of the sample. Lastly, motivated by the multi-level social ecological model [ 7 ], we estimated the models by sub-groups of geographic regions, household wealth index quintiles, and women’s and their husbands’ educational attainment as further robustness check. Statistical analyses were performed in Stata 18.0 software using the complex sampling design of the NFHS-5. Results Around one in every three women (N = 135 012) in the study sample were married to men who were older by 3 to 5 years. Around 12.5% (N = 44 511) and 22.9% (N = 81 509) had husbands who were older by 10 + years and 6 to 9 years, respectively. The remaining 24.0% (N = 94 454) were married to men of similar age. Table 1 presents the characteristics of study population by spousal age difference categories. Average age of women in our sample was 36 years, which was quite similar across the four categories. Percentages of residing in the rural areas, being in the poorest households, belonging to a scheduled tribe, and from the Central region were higher among women whose husbands were of similar age or 3–5 years older, compared to those of women whose husbands were older by 6–9 or 10 + years. In contrast, percentages of having secondary or higher educational attainment, being married before the age of 18 years, and from the South region were higher among women with higher spousal age difference (i.e., 6–9 or 10 + years), compared to those of women with smaller spousal age difference (i.e., similar or 3–5 years). The overall hypertension prevalence in the study population was 18.9%. The prevalence was 11.9% among women aged 20 to 34 years and 24.3% among women aged 35 to 49 years. While the prevalence was 16.7% among women whose husbands were of similar age, the prevalence rates were 3.1 percentage points (pp) and 5.4 pp higher among women whose husbands were older by 6–9 years and 10 + years, respectively. In both younger (i.e., age 20 to 34 years) and older (i.e., age 35 to 49 years) age groups, the higher was the age difference with husband, the higher was prevalence of hypertension (Fig. 1 ). The odds ratios of having hypertension for spousal age differences categories for the full sample, and for sub-samples of age groups and age at marriage are presented in Table 2. The adjusted odds of hypertension for women whose husbands were 10 + years older were 1.18 (95% CI: 1.13–1.24) times that of women who were of similar age to their husbands. The adjusted odds for women with 3–5 years and 6–9 years age difference were 1.07 (95% CI: 1.04–1.10) and 1.11 (95% CI: 1.07–1.15) times, respectively, compared to that of women whose husbands were of similar aged. The odds were similar and robust across the younger and older age sub-groups as well as across age at marriage sub-groups. When husband’s hypertension status was accounted for, the adjusted odds for spousal age difference categories remained statistically significant in the full sample but became relatively smaller. For example, after controlling for whether husband had hypertension, women whose husbands were 10 + years older were 1.13 (95% CI: 1.08–1.19) times more likely to have hypertension. With adjustment for husband’s hypertension, the adjusted odds for 10 + years of age gap were greater than one but not statistically significant for the younger age group and for women who were married at or after the age of 22 years. The husband’s hypertension status, on the other hand, was strongly associated with women’s likelihood of being hypertensive across all groups. The likelihood of having hypertension among women whose husband had hypertension was around 50% higher than that of women whose husbands were not hypertensive. The results were also persistent across years in marriage sub-groups (Table 3). Irrespective of how long a woman was in marriage (i.e., 5–9 years, or 10–19 years, or 20 + years), spousal age difference of 10 + years was associated with 13 to 15% higher odds of having hypertension. The adjusted odds for an age difference of 6–9 years, however, were not statistically significant for women who were 5–9 years in marriage. Further, with accounting for husband’s hypertension status, the adjusted odds of being hypertensive for 10 + years of spousal age difference were not statistically significant for women who were in marriage for less than 20 years. Table 4 presents the result for the husband’s hypertension status sub-groups. In both groups, i.e., women whose husband did or did not have hypertension, higher spousal age difference was associated with higher odds of having hypertension. Women who were younger than their husbands by 10 + years were 9.4 to 15.1% more likely to have hypertension across the sub-groups. Further, in the non-hypertensive husband sub-group, women who had a spousal age difference of 6–9 years were 10.6% more likely to have hypertension compared to those who were of similar age to their husbands. The results were generally robust across sub-groups of geographic regions (Table 5) and household wealth index quintiles (Table 6). While the unadjusted odds of having hypertension for 10 + years of age difference were higher (ranging from 17–48%) in all geographic regions, the adjusted odds were statistically significant for East, West, and South only. The adjusted odds in North, Central, and Northeast were greater than one but not statistically significant. The higher adjusted odds of being hypertensive for spousal age difference of 10 + years were evident in all wealth levels (ranging from 13–31%). While women who were younger than their husbands by 10 + years had higher risk of hypertension across all rural wealth quintiles, the adjusted higher risks were statistically significant for the third and fourth urban wealth quintiles only. Lastly, across all sub-groups of husband’s educational levels, women whose husbands were older by 10 + years were 12 to 17% more likely to have hypertension (Table 7). Apart from women with higher than secondary education, spousal age gap of 10 + years was significantly associated with greater risk of hypertension among all other women. Discussion This study contributes to the growing literature on novel psychosocial risk factors of hypertension. We examined whether a spousal age gap was associated with hypertension status among married women in India. We found that women who were younger than their husbands, specifically by 10 + years, were more likely to have hypertension compared to women who were of similar age to their husbands. This finding was robust for both younger (age 20–34 years) and older (age 35–49 years) women, for different ages at the time of marriage, and for different lengths of marriage. Further, the results were persistent across sociodemographic sub-groups and for women whose husbands did or did not have hypertension. The existing evidence suggests that psychosocial factors such as racial and ethnic discrimination, social support and social relationships, occupational stress, housing instability, etc. could contribute to the onset and progression of hypertension [ 8 , 9 ]. We expanded the evidence base by assessing the role of spousal age gap as a potential psychosocial risk factor of hypertension in women. Further, while hypertension in relation to marriage has been studied primarily in the contexts of marital status and spousal concordance [ 21 , 22 ], our analyses shed light on the psychosocial aspects within a marriage that could influence hypertension outcomes in women. The findings, however, should be interpreted cautiously. First and foremost, culture and societal norms play a critical role in shaping psychosocial determinants of health. As such, the study findings may not be generalizable across different cultural settings. Further research is warranted to assess the generalizability of this association across countries and continents. Second, hypertension status was not clinically diagnosed and was based on average blood pressure measure during a single visit. Third, we did not know the timing of the onset of hypertension. Neither did we know any family history of hypertension that we could have accounted for in the model. These prevented us from inferring any causal relationship. On the other hand, our analyses have some notable strengths. First, our measure of hypertension status was based on actual blood pressure measures and not self-reported status. These measures came from a large nationally representative data and were commonly used to assess hypertension prevalence and care management in India [ 23 , 24 ]. Second, our results were robust across different groups of women who had differential risks of hypertension. For example, age is a natural risk factor for hypertension in women [ 25 ]. In our study population, hypertension prevalence was 11.9% and 24.3% among women aged 20–34 years and 35–49 years, respectively. Despite differences in hypertension prevalence across age groups, we found that higher spousal age difference was associated with higher likelihood of having hypertension in women in both age groups. Child marriage or marriage before the age of 18 years is a biopsychosocial risk factor for hypertension [ 16 ]. Women who were married in childhood had a higher risk of having hypertension in later life. Also, the spousal age gap is generally larger if women are married before reaching adulthood [ 26 ]. To mitigate the confounding influence of early marriage, we not only controlled for age at marriage groups (i.e., ≤ 17 years, 18–21 years, and ≥ 22 years) in the regression models, but also assessed the relationship between hypertension and spousal age gap across sub-groups of age at marriage categories. Similarly, to account for the potential influence of spousal concordance in hypertension outcome [ 22 ], we adjusted for husband’s hypertension status in the model, and also estimated models for sub-groups of women whose husbands did or did not have hypertension. The relationship between larger spousal age difference and risk of hypertension persisted in both specifications. Our results were also robust across socioeconomic status conditions manifested by household wealth, urban and rural residence, and educational attainment of both wife and husband. Thus, despite differences in hypertension prevalence across socio-demographic groups in India [ 27 ], the role of spousal age difference in hypertension outcome of women was evident in all groups. India is diverse in culture, values, and societal norms, which vary across geographic regions. The socio-spatial differences have critical influence on women’s empowerment and autonomy [ 28 ], and gendered cultural practices in India [ 29 ]. To account for these varying geo-spatial influences, we controlled for geographic region fixed effects in the models and additionally, conducted sub-sample analyses by geographic regions. The general direction of the positive association between larger spousal age difference and hypertension risk was evident across all regional sub-groups. All together the robustness of the results across different sub-groups, addressing a range of confounding relationships, had been a notable strength of the paper. Although we were unable to explore mechanistic pathways with available NFHS-5 data, one potential mechanism through which spousal age difference may influence hypertension in women is stressful life events [ 9 ] tied with women’s typical subordinate position in the relationship within a marriage [ 30 ]. In the LMIC context, a larger spousal age gap is often associated with higher likelihood of male dominance within a household [ 31 ]. Spousal age difference is also associated with risk of IPV [ 11 ], which along with male dominance can exacerbate the level of stress [ 32 ], influencing the onset of hypertension in women [ 33 ]. Future research should explore mechanistic roles to better understand of the effects of spousal age gap on the development and progression of hypertension in women. Despite mounting research on hypertension, much remains to be understood on the unique psychosocial factors shaping risk differentials among women in LMICs. This study is the first to explore the role of spousal age differences as a determinant of hypertension in India. Our results provide early support for documentation of spousal age gap as a screening item during hypertension risk and diagnostic assessments, especially in societies where age hypergamous marriages tend to create an environment of male dominance. However, there is a need for longitudinal data to facilitate in-depth understanding of how spousal age gaps may contribute towards hypertension risk. Declarations Ethical Approval The study used anonymized data from publicly available sources, which met the definition of exempt human subject research. Ethics committee approval, therefore, was not required. Participation in the original survey was voluntary and informed consent was obtained prior to each interview. The survey protocols were reviewed and approved by the institutional review boards of the ICF and the International Institute for Population Sciences. Details of the ethical review of the NFHS-5 are available at: https://dhsprogram.com/Methodology/Protecting-the-Privacy-of-DHS-Survey-Respondents.cfm . The methods were carried out in accordance with the “U.S. Department of Health and Human Services regulations for the protection of human subjects” and relevant national guidelines. Competing Interest The authors declare no competing interest. Funding This research did not receive any specific grant from funding agencies in the public, commercial, or not-for-profit sectors. Author Contributions BKD designed the study and performed empirical analysis. AT and MJ critically reviewed the results and developed the discussion points. NT and SA contributed to conceptualization of the study and drafting the background section. All authors read and approved the final manuscript. 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Supplementary Files Table1.xlsx Table 1 Table2.xlsx Table 2 Table3.xlsx Table 3 Table4.xlsx Table 4 Table5.xlsx Table 5 Table6.xlsx Table 6 Table7.xlsx Table 7 Cite Share Download PDF Status: Published Journal Publication published 21 Sep, 2024 Read the published version in Journal of Human Hypertension → Version 1 posted Editorial decision: revise 10 Jul, 2024 Review # 2 received at journal 09 Jul, 2024 Reviewer # 2 agreed at journal 01 Jul, 2024 Review # 1 received at journal 30 Jun, 2024 Reviewer # 1 agreed at journal 15 Jun, 2024 Reviewers invited by journal 09 Jun, 2024 Editor assigned by journal 07 Jun, 2024 Submission checks completed at journal 23 May, 2024 First submitted to journal 22 May, 2024 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. 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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-4462823","acceptedTermsAndConditions":true,"allowDirectSubmit":false,"archivedVersions":[],"articleType":"Article","associatedPublications":[],"authors":[{"id":312314554,"identity":"8a23db2d-f345-4e6a-b6a0-477da2199e1b","order_by":0,"name":"Biplab Datta","email":"data:image/png;base64,iVBORw0KGgoAAAANSUhEUgAAAZAAAAAyAQMAAABI0h/eAAAABlBMVEX///8AAABVwtN+AAAACXBIWXMAAA7EAAAOxAGVKw4bAAAA1UlEQVRIiWNgGAWjYBACA4YEEGWDJHSAsBbGhgMMaUiqidRymAQt5uzJzx9/qDkvb3B+jfHnDzUMcnw3EvBrsex5Zthw4Nhtww033phJHDjGYCxJSIvBjQSgFrbbjBtunDFjOMDGkLiBsJb0jw0H/p2zB2ox/nDgH0M9EVpyDBsOth1I3HC+x0DiYBtDggFhv7wpnHG2Lzl55g22MomzfRKGM888wK/FnD19w4eKb3a2fecPbwYybOT5jhOwBQEkwColiFUOAvwHSFE9CkbBKBgFIwkAAPuSVhkBb/1GAAAAAElFTkSuQmCC","orcid":"https://orcid.org/0000-0002-2559-850X","institution":"Augusta University","correspondingAuthor":true,"prefix":"","firstName":"Biplab","middleName":"","lastName":"Datta","suffix":""},{"id":312314555,"identity":"af85429a-a637-47eb-9278-f9c349f3cd2e","order_by":1,"name":"Ashwini Tiwari","email":"","orcid":"","institution":"Augusta University","correspondingAuthor":false,"prefix":"","firstName":"Ashwini","middleName":"","lastName":"Tiwari","suffix":""},{"id":312314556,"identity":"7fd6fa02-fc5d-4c17-a24d-1d3312772d49","order_by":2,"name":"Murshed Jahan","email":"","orcid":"https://orcid.org/0000-0002-3953-9324","institution":"Valdosta State University","correspondingAuthor":false,"prefix":"","firstName":"Murshed","middleName":"","lastName":"Jahan","suffix":""},{"id":312314557,"identity":"e5bbf2cb-efd4-4e05-9da8-ce92edf1a6f8","order_by":3,"name":"Natalia Torres","email":"","orcid":"","institution":"Rollins College","correspondingAuthor":false,"prefix":"","firstName":"Natalia","middleName":"","lastName":"Torres","suffix":""},{"id":312314558,"identity":"1a7f8277-fd99-49c1-a9fe-581afa92364c","order_by":4,"name":"Sara Attari","email":"","orcid":"","institution":"Augusta University","correspondingAuthor":false,"prefix":"","firstName":"Sara","middleName":"","lastName":"Attari","suffix":""}],"badges":[],"createdAt":"2024-05-22 19:35:15","currentVersionCode":1,"declarations":"","doi":"10.21203/rs.3.rs-4462823/v1","doiUrl":"https://doi.org/10.21203/rs.3.rs-4462823/v1","draftVersion":[],"editorialEvents":[{"content":"https://doi.org/10.1038/s41371-024-00959-6","type":"published","date":"2024-09-21T04:00:00+00:00"}],"editorialNote":"","failedWorkflow":false,"files":[{"id":58932935,"identity":"a7bd9c4f-0f5f-4ccd-8deb-f9f1245ece7c","added_by":"auto","created_at":"2024-06-24 09:24:45","extension":"png","order_by":1,"title":"Figure 1","display":"","copyAsset":false,"role":"figure","size":171691,"visible":true,"origin":"","legend":"\u003cp\u003eHypertension prevalence by age and spousal age differences.\u003c/p\u003e","description":"","filename":"Fig1.png","url":"https://assets-eu.researchsquare.com/files/rs-4462823/v1/eee354d641b9f4b35678db2c.png"},{"id":65431721,"identity":"ebfbf86a-55ce-4dcd-a99c-0455c3d6d736","added_by":"auto","created_at":"2024-09-27 11:59:16","extension":"pdf","order_by":0,"title":"","display":"","copyAsset":false,"role":"manuscript-pdf","size":419066,"visible":true,"origin":"","legend":"","description":"","filename":"manuscript.pdf","url":"https://assets-eu.researchsquare.com/files/rs-4462823/v1/ed04bf1b-0ae1-4a93-8161-816ec1d77e9b.pdf"},{"id":58932930,"identity":"d2d1f963-e11f-4ddf-9fbf-8d384d685d00","added_by":"auto","created_at":"2024-06-24 09:24:45","extension":"xlsx","order_by":1,"title":"","display":"","copyAsset":false,"role":"supplement","size":12428,"visible":true,"origin":"","legend":"Table 1","description":"","filename":"Table1.xlsx","url":"https://assets-eu.researchsquare.com/files/rs-4462823/v1/c2834a7a552d671efb53a53c.xlsx"},{"id":58932929,"identity":"ea0f4fa4-af3b-4d4a-9028-1dde8ec52349","added_by":"auto","created_at":"2024-06-24 09:24:45","extension":"xlsx","order_by":2,"title":"","display":"","copyAsset":false,"role":"supplement","size":12318,"visible":true,"origin":"","legend":"Table 2","description":"","filename":"Table2.xlsx","url":"https://assets-eu.researchsquare.com/files/rs-4462823/v1/75399df83b9a62df5e3eb188.xlsx"},{"id":58934002,"identity":"362dcba9-ff7d-409f-9de1-1d204b539177","added_by":"auto","created_at":"2024-06-24 09:40:45","extension":"xlsx","order_by":3,"title":"","display":"","copyAsset":false,"role":"supplement","size":11244,"visible":true,"origin":"","legend":"Table 3","description":"","filename":"Table3.xlsx","url":"https://assets-eu.researchsquare.com/files/rs-4462823/v1/34927b817907374256b62f93.xlsx"},{"id":58933519,"identity":"f256409c-07ab-4a4b-ad7d-c5e7a276ebb4","added_by":"auto","created_at":"2024-06-24 09:32:45","extension":"xlsx","order_by":4,"title":"","display":"","copyAsset":false,"role":"supplement","size":10499,"visible":true,"origin":"","legend":"\u003cp\u003eTable 4\u003c/p\u003e","description":"","filename":"Table4.xlsx","url":"https://assets-eu.researchsquare.com/files/rs-4462823/v1/b5225058b67d137f0b42b0a2.xlsx"},{"id":58932928,"identity":"9b20987a-5196-4c5f-bdc1-81e59c916cc3","added_by":"auto","created_at":"2024-06-24 09:24:45","extension":"xlsx","order_by":5,"title":"","display":"","copyAsset":false,"role":"supplement","size":11197,"visible":true,"origin":"","legend":"\u003cp\u003eTable 5\u003c/p\u003e","description":"","filename":"Table5.xlsx","url":"https://assets-eu.researchsquare.com/files/rs-4462823/v1/46bf40c96f2df2a5d874f273.xlsx"},{"id":58932932,"identity":"009ed6bb-4722-40bd-a915-8a2cef555ccb","added_by":"auto","created_at":"2024-06-24 09:24:45","extension":"xlsx","order_by":6,"title":"","display":"","copyAsset":false,"role":"supplement","size":11709,"visible":true,"origin":"","legend":"\u003cp\u003eTable 6\u003c/p\u003e","description":"","filename":"Table6.xlsx","url":"https://assets-eu.researchsquare.com/files/rs-4462823/v1/78861ef6a794d952eed21f2f.xlsx"},{"id":58934003,"identity":"1c66aecb-1c42-4bc5-a120-a49d6d6898d6","added_by":"auto","created_at":"2024-06-24 09:40:45","extension":"xlsx","order_by":7,"title":"","display":"","copyAsset":false,"role":"supplement","size":10815,"visible":true,"origin":"","legend":"\u003cp\u003eTable 7\u003c/p\u003e","description":"","filename":"Table7.xlsx","url":"https://assets-eu.researchsquare.com/files/rs-4462823/v1/0afa59f5ac8fc47b78ec56f3.xlsx"}],"financialInterests":"There is \u003cb\u003eNO\u003c/b\u003e conflict of interest to disclose.","formattedTitle":"Spousal age difference and risk of hypertension in women: evidence from India","fulltext":[{"header":"Summary Table","content":"\u003cp\u003e\u003cstrong\u003eWhat is known about topic\u003c/strong\u003e\u003c/p\u003e\n\u003cul\u003e\n \u003cli\u003eSpousal age gap is associated with male dominance in decision making and intimate partner violence.\u0026nbsp;\u003c/li\u003e\n \u003cli\u003ePerceived spouse dominance can influence cardiovascular reactivity.\u0026nbsp;\u003c/li\u003e\n\u003c/ul\u003e\n\u003cp\u003e\u003cstrong\u003eWhat this study adds\u003c/strong\u003e\u003c/p\u003e\n\u003cul\u003e\n \u003cli\u003eSpousal age gap is potentially a biopsychosocial risk factor of hypertension in women.\u003c/li\u003e\n \u003cli\u003eWomen who were younger than their husbands by 10+ years, had a higher risk of hypertension compared to women who were of similar age to their husbands.\u003c/li\u003e\n\u003c/ul\u003e"},{"header":"Background","content":"\u003cp\u003eCommon risk factors for hypertension include an unhealthy diet, physical inactivity, tobacco- and alcohol- consumption, and being overweight or obese [\u003cspan citationid=\"CR1\" class=\"CitationRef\"\u003e1\u003c/span\u003e]. These modifiable risk factors are further influenced by age, sex, race and ethnicity, and other elements of an individual\u0026rsquo;s life such as geographical location and socioeconomic status conditions [\u003cspan citationid=\"CR2\" class=\"CitationRef\"\u003e2\u003c/span\u003e]. While the role of socioeconomic status and environmental conditions on hypertension outcome are commonly explored [\u003cspan citationid=\"CR3\" class=\"CitationRef\"\u003e3\u003c/span\u003e, \u003cspan citationid=\"CR4\" class=\"CitationRef\"\u003e4\u003c/span\u003e, \u003cspan citationid=\"CR5\" class=\"CitationRef\"\u003e5\u003c/span\u003e, \u003cspan citationid=\"CR6\" class=\"CitationRef\"\u003e6\u003c/span\u003e], there is a dearth of evidence on the potential influence of psychosocial factors, which, under the social ecological model of health, can act as important determinants of health outcomes [\u003cspan citationid=\"CR7\" class=\"CitationRef\"\u003e7\u003c/span\u003e]. As such, these factors can play a role in the development and progression of cardiometabolic conditions such as hypertension [\u003cspan citationid=\"CR8\" class=\"CitationRef\"\u003e8\u003c/span\u003e, \u003cspan citationid=\"CR9\" class=\"CitationRef\"\u003e9\u003c/span\u003e]. For example, the spousal concordance of hypertension is a commonly observed phenomenon, which is presumably connected with similar socioeconomic and environmental exposures among a husband and wife within a household [\u003cspan citationid=\"CR10\" class=\"CitationRef\"\u003e10\u003c/span\u003e]. However, the role of certain spousal characteristics, such as spousal age differences, or the spousal age gap, on hypertension risk, especially in the low-and-middle income countries (LMICs) has not yet been explored.\u003c/p\u003e \u003cp\u003eThe literature on the health impact of spousal age gap has largely revolved around intimate partner violence (IPV) and contraceptive use [\u003cspan citationid=\"CR11\" class=\"CitationRef\"\u003e11\u003c/span\u003e, \u003cspan citationid=\"CR12\" class=\"CitationRef\"\u003e12\u003c/span\u003e]. Findings of these studies suggest that women who are considerably younger than their husbands (e.g., by 10\u0026thinsp;+\u0026thinsp;years) were more likely to experience violence and less likely to use contraception compared to their peers. Experiencing IPV and decision on contraceptive-use are also influenced by husband\u0026rsquo;s controlling behaviors among these women [\u003cspan citationid=\"CR13\" class=\"CitationRef\"\u003e13\u003c/span\u003e, \u003cspan citationid=\"CR14\" class=\"CitationRef\"\u003e14\u003c/span\u003e]. Given the risk of cardiovascular reactivity associated with perceived spouse dominance [\u003cspan citationid=\"CR15\" class=\"CitationRef\"\u003e15\u003c/span\u003e], spousal age difference can be regarded as a biopsychosocial factor influencing the risk of hypertension in women. While some recent studies explored related areas, such as the role of child marriage, early childbearing, and marital disruption in developing hypertension [\u003cspan citationid=\"CR16\" class=\"CitationRef\"\u003e16\u003c/span\u003e, \u003cspan citationid=\"CR17\" class=\"CitationRef\"\u003e17\u003c/span\u003e], the risk of hypertension specifically in relation to spousal age gaps has rarely been studied.\u003c/p\u003e \u003cp\u003eIn this study, we explored the potential role of spousal age difference in hypertension risk among married women in India, where age hypergamous marriages (i.e., wife younger than husband) are quite prominent [\u003cspan citationid=\"CR18\" class=\"CitationRef\"\u003e18\u003c/span\u003e]. India also has a high burden of hypertension with age standardized prevalence rate of 25.4% among adult women [\u003cspan citationid=\"CR19\" class=\"CitationRef\"\u003e19\u003c/span\u003e]. More concerning, over half of the hypertensive women in India remain unaware of their condition [\u003cspan citationid=\"CR19\" class=\"CitationRef\"\u003e19\u003c/span\u003e]. As such, recognizing psychosocial risk factors of hypertension, beyond the traditional risks, could facilitate better management of hypertension in India. Against this backdrop, the aim of this cross-sectional analysis was to assess whether higher spousal age gap was associated with greater risks of hypertension in a nationally representative sample of adult reproductive-aged (i.e., 20 to 49 years) women in India.\u003c/p\u003e"},{"header":"Methods","content":"\u003cp\u003eData\u003c/p\u003e \u003cp\u003eThis observational study used data from the 2019-21 India National Family Health Survey (NFHS-5). Our sample comprised of 355 486 currently married women, aged 20 to 49 years, who were in marriage for at least 5 years and were not in multiple unions (i.e., not married more than once).\u003c/p\u003e \u003cp\u003eThe NFHS-5 utilized a stratified two-stage sampling framework to collect nationally representative data on various population health topics in India. The survey was administered under technical assistance from the USAID\u0026rsquo;s Demographic and Health Surveys (DHS) Program. The survey protocol was approved by the institutional review boards of the International Institute of Population Studies (IIPS) and the ICF [\u003cspan citationid=\"CR20\" class=\"CitationRef\"\u003e20\u003c/span\u003e]. We used publicly available anonymized data for analyses, which met the exempt human subject research definition (Exemption 4) of the National Institutes of Health (NIH). Ethical approval for this study, therefore, was not required.\u003c/p\u003e \u003cp\u003eMeasures\u003c/p\u003e \u003cp\u003eOur outcome variable was a binary variable indicating whether a woman was hypertensive or not. Hypertension status was defined by average systolic blood pressure (SBP)\u0026thinsp;\u0026ge;\u0026thinsp;140 mmHg or average diastolic blood pressure (DBP)\u0026thinsp;\u0026ge;\u0026thinsp;90 mmHg or taking anti-hypertensive medication at the time of the survey [\u003cspan citationid=\"CR20\" class=\"CitationRef\"\u003e20\u003c/span\u003e].\u003c/p\u003e \u003cp\u003eOur exposure variable was a categorical variable denoting the age difference between husband and wife. Women were categorized in four categories: husband was \u0026ndash; i) of similar age (i.e., age difference is \u0026plusmn;\u0026thinsp;2 years), ii) 3\u0026ndash;5 years older, iii) 6\u0026ndash;9 years older, and iv) 10\u0026thinsp;+\u0026thinsp;years older. Of note, 1.05% (N\u0026thinsp;=\u0026thinsp;3,781) women were married to men who were 3\u0026thinsp;+\u0026thinsp;years younger than their wives. These women were excluded from analysis since they constituted only a tiny fraction of the sample and thereby lacked statistical power to be analyzed as a separate category. We, however, checked that our results (for the four categories) would have remained unaffected if a fifth category, containing women who were older than their husbands by 3\u0026thinsp;+\u0026thinsp;years, was included.\u003c/p\u003e \u003cdiv id=\"Sec3\" class=\"Section2\"\u003e \u003ch2\u003eStatistical analysis\u003c/h2\u003e \u003cp\u003eWe estimated binomial logistic regressions to assess the odds of being hypertensive by spousal age difference categories, compared to that of women whose husband were of similar age. To address potential heterogeneity in the study population, we estimated the models for sub-groups by age (20\u0026ndash;34 years and 35\u0026ndash;49 years), by age at marriage (\u0026le;\u0026thinsp;17 years, 18\u0026ndash;21 years, and \u0026ge;\u0026thinsp;22 years), and by years in marriage (5\u0026ndash;9 years, 10\u0026ndash;19 years, and \u0026ge;\u0026thinsp;20 years).\u003c/p\u003e \u003cp\u003eWe estimated both unadjusted and adjusted forms of regressions. In the multivariable specification, we accounted for various sociodemographic and socioeconomic attributes along with common risk factors for hypertension. Sociodemographic characteristics included women\u0026rsquo;s age, religion, caste, urban/rural residence, and whether husband had multiple wives. Socioeconomic attributes included educational attainment, husband\u0026rsquo;s level of education, household wealth index quintiles. Hypertension risk factors included body mass index (BMI) categories, parity (i.e., number of children born), age at first marriage, tobacco use, alcohol use, menopausal status, pregnancy status, and lactation status. Further, geographic-region fixed effects were included in the model to account for regional differences in societal norms and health outcomes. While age and parity were continuous variables, all other covariates were binary or categorical variables. A complete list of categories of respective covariates is provided in Table\u0026nbsp;1.\u003c/p\u003e \u003cp\u003eWe also estimated a multivariable specification accounting for husband\u0026rsquo;s hypertension status along with other covariates. Next, we estimated models by sub-groups of husband\u0026rsquo;s hypertension status (i.e., husband did or did not have hypertension). Of note, husband\u0026rsquo;s hypertension status was not available for 10.4% (N\u0026thinsp;=\u0026thinsp;36,909) of the sample. Lastly, motivated by the multi-level social ecological model [\u003cspan citationid=\"CR7\" class=\"CitationRef\"\u003e7\u003c/span\u003e], we estimated the models by sub-groups of geographic regions, household wealth index quintiles, and women\u0026rsquo;s and their husbands\u0026rsquo; educational attainment as further robustness check. Statistical analyses were performed in Stata 18.0 software using the complex sampling design of the NFHS-5.\u003c/p\u003e \u003c/div\u003e"},{"header":"Results","content":"\u003cp\u003eAround one in every three women (N\u0026thinsp;=\u0026thinsp;135 012) in the study sample were married to men who were older by 3 to 5 years. Around 12.5% (N\u0026thinsp;=\u0026thinsp;44 511) and 22.9% (N\u0026thinsp;=\u0026thinsp;81 509) had husbands who were older by 10\u0026thinsp;+\u0026thinsp;years and 6 to 9 years, respectively. The remaining 24.0% (N\u0026thinsp;=\u0026thinsp;94 454) were married to men of similar age.\u003c/p\u003e \u003cp\u003eTable\u0026nbsp;1 presents the characteristics of study population by spousal age difference categories. Average age of women in our sample was 36 years, which was quite similar across the four categories. Percentages of residing in the rural areas, being in the poorest households, belonging to a scheduled tribe, and from the Central region were higher among women whose husbands were of similar age or 3\u0026ndash;5 years older, compared to those of women whose husbands were older by 6\u0026ndash;9 or 10\u0026thinsp;+\u0026thinsp;years. In contrast, percentages of having secondary or higher educational attainment, being married before the age of 18 years, and from the South region were higher among women with higher spousal age difference (i.e., 6\u0026ndash;9 or 10\u0026thinsp;+\u0026thinsp;years), compared to those of women with smaller spousal age difference (i.e., similar or 3\u0026ndash;5 years).\u003c/p\u003e \u003cp\u003eThe overall hypertension prevalence in the study population was 18.9%. The prevalence was 11.9% among women aged 20 to 34 years and 24.3% among women aged 35 to 49 years. While the prevalence was 16.7% among women whose husbands were of similar age, the prevalence rates were 3.1 percentage points (pp) and 5.4 pp higher among women whose husbands were older by 6\u0026ndash;9 years and 10\u0026thinsp;+\u0026thinsp;years, respectively. In both younger (i.e., age 20 to 34 years) and older (i.e., age 35 to 49 years) age groups, the higher was the age difference with husband, the higher was prevalence of hypertension (Fig.\u0026nbsp;\u003cspan refid=\"Fig1\" class=\"InternalRef\"\u003e1\u003c/span\u003e).\u003c/p\u003e \u003cp\u003e \u003c/p\u003e \u003cp\u003eThe odds ratios of having hypertension for spousal age differences categories for the full sample, and for sub-samples of age groups and age at marriage are presented in Table\u0026nbsp;2. The adjusted odds of hypertension for women whose husbands were 10\u0026thinsp;+\u0026thinsp;years older were 1.18 (95% CI: 1.13\u0026ndash;1.24) times that of women who were of similar age to their husbands. The adjusted odds for women with 3\u0026ndash;5 years and 6\u0026ndash;9 years age difference were 1.07 (95% CI: 1.04\u0026ndash;1.10) and 1.11 (95% CI: 1.07\u0026ndash;1.15) times, respectively, compared to that of women whose husbands were of similar aged. The odds were similar and robust across the younger and older age sub-groups as well as across age at marriage sub-groups.\u003c/p\u003e \u003cp\u003eWhen husband\u0026rsquo;s hypertension status was accounted for, the adjusted odds for spousal age difference categories remained statistically significant in the full sample but became relatively smaller. For example, after controlling for whether husband had hypertension, women whose husbands were 10\u0026thinsp;+\u0026thinsp;years older were 1.13 (95% CI: 1.08\u0026ndash;1.19) times more likely to have hypertension. With adjustment for husband\u0026rsquo;s hypertension, the adjusted odds for 10\u0026thinsp;+\u0026thinsp;years of age gap were greater than one but not statistically significant for the younger age group and for women who were married at or after the age of 22 years. The husband\u0026rsquo;s hypertension status, on the other hand, was strongly associated with women\u0026rsquo;s likelihood of being hypertensive across all groups. The likelihood of having hypertension among women whose husband had hypertension was around 50% higher than that of women whose husbands were not hypertensive.\u003c/p\u003e \u003cp\u003eThe results were also persistent across years in marriage sub-groups (Table\u0026nbsp;3). Irrespective of how long a woman was in marriage (i.e., 5\u0026ndash;9 years, or 10\u0026ndash;19 years, or 20\u0026thinsp;+\u0026thinsp;years), spousal age difference of 10\u0026thinsp;+\u0026thinsp;years was associated with 13 to 15% higher odds of having hypertension. The adjusted odds for an age difference of 6\u0026ndash;9 years, however, were not statistically significant for women who were 5\u0026ndash;9 years in marriage. Further, with accounting for husband\u0026rsquo;s hypertension status, the adjusted odds of being hypertensive for 10\u0026thinsp;+\u0026thinsp;years of spousal age difference were not statistically significant for women who were in marriage for less than 20 years.\u003c/p\u003e \u003cp\u003eTable\u0026nbsp;4 presents the result for the husband\u0026rsquo;s hypertension status sub-groups. In both groups, i.e., women whose husband did or did not have hypertension, higher spousal age difference was associated with higher odds of having hypertension. Women who were younger than their husbands by 10\u0026thinsp;+\u0026thinsp;years were 9.4 to 15.1% more likely to have hypertension across the sub-groups. Further, in the non-hypertensive husband sub-group, women who had a spousal age difference of 6\u0026ndash;9 years were 10.6% more likely to have hypertension compared to those who were of similar age to their husbands.\u003c/p\u003e \u003cp\u003eThe results were generally robust across sub-groups of geographic regions (Table\u0026nbsp;5) and household wealth index quintiles (Table\u0026nbsp;6). While the unadjusted odds of having hypertension for 10\u0026thinsp;+\u0026thinsp;years of age difference were higher (ranging from 17\u0026ndash;48%) in all geographic regions, the adjusted odds were statistically significant for East, West, and South only. The adjusted odds in North, Central, and Northeast were greater than one but not statistically significant.\u003c/p\u003e \u003cp\u003eThe higher adjusted odds of being hypertensive for spousal age difference of 10\u0026thinsp;+\u0026thinsp;years were evident in all wealth levels (ranging from 13\u0026ndash;31%). While women who were younger than their husbands by 10\u0026thinsp;+\u0026thinsp;years had higher risk of hypertension across all rural wealth quintiles, the adjusted higher risks were statistically significant for the third and fourth urban wealth quintiles only.\u003c/p\u003e \u003cp\u003eLastly, across all sub-groups of husband\u0026rsquo;s educational levels, women whose husbands were older by 10\u0026thinsp;+\u0026thinsp;years were 12 to 17% more likely to have hypertension (Table\u0026nbsp;7). Apart from women with higher than secondary education, spousal age gap of 10\u0026thinsp;+\u0026thinsp;years was significantly associated with greater risk of hypertension among all other women.\u003c/p\u003e"},{"header":"Discussion","content":"\u003cp\u003eThis study contributes to the growing literature on novel psychosocial risk factors of hypertension. We examined whether a spousal age gap was associated with hypertension status among married women in India. We found that women who were younger than their husbands, specifically by 10\u0026thinsp;+\u0026thinsp;years, were more likely to have hypertension compared to women who were of similar age to their husbands. This finding was robust for both younger (age 20\u0026ndash;34 years) and older (age 35\u0026ndash;49 years) women, for different ages at the time of marriage, and for different lengths of marriage. Further, the results were persistent across sociodemographic sub-groups and for women whose husbands did or did not have hypertension.\u003c/p\u003e \u003cp\u003eThe existing evidence suggests that psychosocial factors such as racial and ethnic discrimination, social support and social relationships, occupational stress, housing instability, etc. could contribute to the onset and progression of hypertension [\u003cspan citationid=\"CR8\" class=\"CitationRef\"\u003e8\u003c/span\u003e, \u003cspan citationid=\"CR9\" class=\"CitationRef\"\u003e9\u003c/span\u003e]. We expanded the evidence base by assessing the role of spousal age gap as a potential psychosocial risk factor of hypertension in women. Further, while hypertension in relation to marriage has been studied primarily in the contexts of marital status and spousal concordance [\u003cspan citationid=\"CR21\" class=\"CitationRef\"\u003e21\u003c/span\u003e, \u003cspan citationid=\"CR22\" class=\"CitationRef\"\u003e22\u003c/span\u003e], our analyses shed light on the psychosocial aspects within a marriage that could influence hypertension outcomes in women.\u003c/p\u003e \u003cp\u003eThe findings, however, should be interpreted cautiously. First and foremost, culture and societal norms play a critical role in shaping psychosocial determinants of health. As such, the study findings may not be generalizable across different cultural settings. Further research is warranted to assess the generalizability of this association across countries and continents. Second, hypertension status was not clinically diagnosed and was based on average blood pressure measure during a single visit. Third, we did not know the timing of the onset of hypertension. Neither did we know any family history of hypertension that we could have accounted for in the model. These prevented us from inferring any causal relationship.\u003c/p\u003e \u003cp\u003eOn the other hand, our analyses have some notable strengths. First, our measure of hypertension status was based on actual blood pressure measures and not self-reported status. These measures came from a large nationally representative data and were commonly used to assess hypertension prevalence and care management in India [\u003cspan citationid=\"CR23\" class=\"CitationRef\"\u003e23\u003c/span\u003e, \u003cspan citationid=\"CR24\" class=\"CitationRef\"\u003e24\u003c/span\u003e]. Second, our results were robust across different groups of women who had differential risks of hypertension. For example, age is a natural risk factor for hypertension in women [\u003cspan citationid=\"CR25\" class=\"CitationRef\"\u003e25\u003c/span\u003e]. In our study population, hypertension prevalence was 11.9% and 24.3% among women aged 20\u0026ndash;34 years and 35\u0026ndash;49 years, respectively. Despite differences in hypertension prevalence across age groups, we found that higher spousal age difference was associated with higher likelihood of having hypertension in women in both age groups.\u003c/p\u003e \u003cp\u003eChild marriage or marriage before the age of 18 years is a biopsychosocial risk factor for hypertension [\u003cspan citationid=\"CR16\" class=\"CitationRef\"\u003e16\u003c/span\u003e]. Women who were married in childhood had a higher risk of having hypertension in later life. Also, the spousal age gap is generally larger if women are married before reaching adulthood [\u003cspan citationid=\"CR26\" class=\"CitationRef\"\u003e26\u003c/span\u003e]. To mitigate the confounding influence of early marriage, we not only controlled for age at marriage groups (i.e., \u0026le; 17 years, 18\u0026ndash;21 years, and \u0026ge;\u0026thinsp;22 years) in the regression models, but also assessed the relationship between hypertension and spousal age gap across sub-groups of age at marriage categories.\u003c/p\u003e \u003cp\u003eSimilarly, to account for the potential influence of spousal concordance in hypertension outcome [\u003cspan citationid=\"CR22\" class=\"CitationRef\"\u003e22\u003c/span\u003e], we adjusted for husband\u0026rsquo;s hypertension status in the model, and also estimated models for sub-groups of women whose husbands did or did not have hypertension. The relationship between larger spousal age difference and risk of hypertension persisted in both specifications. Our results were also robust across socioeconomic status conditions manifested by household wealth, urban and rural residence, and educational attainment of both wife and husband. Thus, despite differences in hypertension prevalence across socio-demographic groups in India [\u003cspan citationid=\"CR27\" class=\"CitationRef\"\u003e27\u003c/span\u003e], the role of spousal age difference in hypertension outcome of women was evident in all groups.\u003c/p\u003e \u003cp\u003eIndia is diverse in culture, values, and societal norms, which vary across geographic regions. The socio-spatial differences have critical influence on women\u0026rsquo;s empowerment and autonomy [\u003cspan citationid=\"CR28\" class=\"CitationRef\"\u003e28\u003c/span\u003e], and gendered cultural practices in India [\u003cspan citationid=\"CR29\" class=\"CitationRef\"\u003e29\u003c/span\u003e]. To account for these varying geo-spatial influences, we controlled for geographic region fixed effects in the models and additionally, conducted sub-sample analyses by geographic regions. The general direction of the positive association between larger spousal age difference and hypertension risk was evident across all regional sub-groups. All together the robustness of the results across different sub-groups, addressing a range of confounding relationships, had been a notable strength of the paper.\u003c/p\u003e \u003cp\u003eAlthough we were unable to explore mechanistic pathways with available NFHS-5 data, one potential mechanism through which spousal age difference may influence hypertension in women is stressful life events [\u003cspan citationid=\"CR9\" class=\"CitationRef\"\u003e9\u003c/span\u003e] tied with women\u0026rsquo;s typical subordinate position in the relationship within a marriage [\u003cspan citationid=\"CR30\" class=\"CitationRef\"\u003e30\u003c/span\u003e]. In the LMIC context, a larger spousal age gap is often associated with higher likelihood of male dominance within a household [\u003cspan citationid=\"CR31\" class=\"CitationRef\"\u003e31\u003c/span\u003e]. Spousal age difference is also associated with risk of IPV [\u003cspan citationid=\"CR11\" class=\"CitationRef\"\u003e11\u003c/span\u003e], which along with male dominance can exacerbate the level of stress [\u003cspan citationid=\"CR32\" class=\"CitationRef\"\u003e32\u003c/span\u003e], influencing the onset of hypertension in women [\u003cspan citationid=\"CR33\" class=\"CitationRef\"\u003e33\u003c/span\u003e]. Future research should explore mechanistic roles to better understand of the effects of spousal age gap on the development and progression of hypertension in women.\u003c/p\u003e \u003cp\u003eDespite mounting research on hypertension, much remains to be understood on the unique psychosocial factors shaping risk differentials among women in LMICs. This study is the first to explore the role of spousal age differences as a determinant of hypertension in India. Our results provide early support for documentation of spousal age gap as a screening item during hypertension risk and diagnostic assessments, especially in societies where age hypergamous marriages tend to create an environment of male dominance. However, there is a need for longitudinal data to facilitate in-depth understanding of how spousal age gaps may contribute towards hypertension risk.\u003c/p\u003e"},{"header":"Declarations","content":"\u003cp\u003e \u003ch2\u003eEthical Approval\u003c/h2\u003e \u003cp\u003eThe study used anonymized data from publicly available sources, which met the definition of exempt human subject research. Ethics committee approval, therefore, was not required. Participation in the original survey was voluntary and informed consent was obtained prior to each interview. The survey protocols were reviewed and approved by the institutional review boards of the ICF and the International Institute for Population Sciences. Details of the ethical review of the NFHS-5 are available at: \u003cspan class=\"ExternalRef\"\u003e\u003cspan class=\"RefSource\"\u003ehttps://dhsprogram.com/Methodology/Protecting-the-Privacy-of-DHS-Survey-Respondents.cfm\u003c/span\u003e\u003cspan address=\"https://dhsprogram.com/Methodology/Protecting-the-Privacy-of-DHS-Survey-Respondents.cfm\" targettype=\"URL\" class=\"RefTarget\"\u003e\u003c/span\u003e\u003c/span\u003e. The methods were carried out in accordance with the \u0026ldquo;U.S. Department of Health and Human Services regulations for the protection of human subjects\u0026rdquo; and relevant national guidelines.\u003c/p\u003e \u003c/p\u003e \u003cp\u003e \u003cstrong\u003eCompeting Interest\u003c/strong\u003e \u003cp\u003eThe authors declare no competing interest.\u003c/p\u003e \u003c/p\u003e\u003ch2\u003eFunding\u003c/h2\u003e \u003cp\u003eThis research did not receive any specific grant from funding agencies in the public, commercial, or not-for-profit sectors.\u003c/p\u003e\u003ch2\u003eAuthor Contributions\u003c/h2\u003e \u003cp\u003eBKD designed the study and performed empirical analysis. AT and MJ critically reviewed the results and developed the discussion points. NT and SA contributed to conceptualization of the study and drafting the background section. All authors read and approved the final manuscript.\u003c/p\u003e\u003ch2\u003eAcknowledgements\u003c/h2\u003e \u003cp\u003eN/A.\u003c/p\u003e\n\u003ch3\u003eData Availability Statement\u003c/h3\u003e\n\u003cp\u003eData used in this analysis is publicly available from the USAID\u0026rsquo;s DHS Program website: \u003cspan class=\"ExternalRef\"\u003e\u003cspan class=\"RefSource\"\u003ehttps://dhsprogram.com/Data/\u003c/span\u003e\u003cspan address=\"https://dhsprogram.com/Data/\" targettype=\"URL\" class=\"RefTarget\"\u003e\u003c/span\u003e\u003c/span\u003e.\u003c/p\u003e"},{"header":"References","content":"\u003col\u003e\u003cli\u003e\u003cspan\u003eWang W, Lee ET, Fabsitz RR, Devereux R, Best L, Welty TK, Howard BV. A longitudinal study of hypertension risk factors and their relation to cardiovascular disease: the Strong Heart Study. 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Spousal age differences and violence against women in Nigeria and Tanzania. Health Care for Women International. 2018;39(8):872\u0026ndash;87.\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eKitila SB, Terfa YB, Akuma AO, Olika AK, Olika AK. Spousal age difference and its effect on contraceptive use among sexually active couples in Ethiopia: evidence from the 2016 Ethiopia demographic and health survey. Contraception and Reproductive Medicine. 2020;5:1\u0026ndash;9.\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eTun T, Ostergren PO. Spousal violence against women and its association with sociodemographic factors and husbands\u0026rsquo; controlling behaviour: the findings of Myanmar Demographic and Health Survey (2015\u0026ndash;2016). Global health action. 2020;13(1):1844975.\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003ePaul P, Mondal D. Association between intimate partner violence and contraceptive use in India: Exploring the moderating role of husband\u0026rsquo;s controlling behaviors. Journal of interpersonal violence. 2022;37(17\u0026ndash;18):NP15405-33.\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eBrown PC, Smith TW, Benjamin LS. Perceptions of spouse dominance predict blood pressure reactivity during marital interactions. Annals of Behavioral Medicine. 1998;20(4):286\u0026ndash;93.\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eDatta BK, Haider MR, Tiwari A, Jahan M. The risk of hypertension among child brides and adolescent mothers at age 20 s, 30 s, and 40 s: Evidence from India. Journal of Human Hypertension. 2023;37(7):568\u0026ndash;75.\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eTiwari A, Datta BK, Haider MR, Jahan M. The role of child marriage and marital disruptions on hypertension in women-A nationally representative study from India. SSM-Population Health. 2023;22:101409.\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eDommaraju P. Age gap between spouses in south and southeast Asia. Journal of Family Issues. 2024;45(5):1242\u0026ndash;60.\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eVarghese JS, Venkateshmurthy NS, Sudharsanan N, Jeemon P, Patel SA, Thirumurthy H, Roy A, Tandon N, Narayan KV, Prabhakaran D, Ali MK. Hypertension diagnosis, treatment, and control in India. JAMA Network Open. 2023;6(10):e2339098-.\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eInternational Institute for Population Sciences (IIPS) and ICF. National Family Health Survey (NFHS-5), 2019-21: India. Mumbai: IIPS. 2021 Mar.\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eManfredini R, De Giorgi A, Tiseo R, Boari B, Cappadona R, Salmi R, Gallerani M, Signani F, Manfredini F, Mikhailidis DP, Fabbian F. Marital status, cardiovascular diseases, and cardiovascular risk factors: a review of the evidence. Journal of Women's Health. 2017;26(6):624\u0026ndash;32.\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eWang Z, Ji W, Song Y, Li J, Shen Y, Zheng H, Ding Y. Spousal concordance for hypertension: a meta-analysis of observational studies. The Journal of Clinical Hypertension. 2017;19(11):1088\u0026ndash;95.\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eGupta R, Gaur K, S. Ram CV. Emerging trends in hypertension epidemiology in India. Journal of human hypertension. 2019;33(8):575\u0026ndash;87.\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eGuthi VR, Kumar DS, Kumar S, Kondagunta N, Raj S, Goel S, Ojah P. Hypertension treatment cascade among men and women of reproductive age group in India: analysis of National Family Health Survey-5 (2019\u0026ndash;2021). The Lancet Regional Health-Southeast Asia. 2024;23.\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eRosenthal T, Oparil S. Hypertension in women. Journal of human hypertension. 2000;14(10):691\u0026ndash;704.\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eNasrullah M, Zakar R, Zakar MZ. Child marriage and its associations with controlling behaviors and spousal violence against adolescent and young women in Pakistan. Journal of Adolescent Health. 2014;55(6):804\u0026ndash;9.\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eGeldsetzer P, Manne-Goehler J, Theilmann M, Davies JI, Awasthi A, Vollmer S. Diabetes and hypertension in India: a nationally representative study of 1.3 million adults. JAMA Intern Med. 2018; 178 (3): 363\u0026ndash;72.\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eGupta K, Yesudian PP. Evidence of women\u0026rsquo;s empowerment in India: A study of socio-spatial disparities. GeoJournal. 2006;65:365\u0026ndash;80.\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eDatta A. Gender, space and agency in India: exploring regional genderscapes. InGender, Space and Agency in India 2020 Aug 31 (pp. 1\u0026ndash;14). Routledge India.\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eWanic R, Kulik J. Toward an understanding of gender differences in the impact of marital conflict on health. Sex roles. 2011;65:297\u0026ndash;312.\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eAkhter S, Hossain MF, Mazumder MA. Examining the association between spousal age difference and household male dominance: does wives\u0026rsquo; gender ideology matter?. SN Social Sciences. 2023;3(6):92.\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eAl-Modallal H. Psychological partner violence and women's vulnerability to depression, stress, and anxiety. International journal of mental health nursing. 2012;21(6):560\u0026ndash;6.\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eLarkin KT. Stress and hypertension: Examining the relation between psychological stress and high blood pressure. Yale university press; 2008 Oct 1.\u003c/span\u003e\u003c/li\u003e\u003c/ol\u003e"},{"header":"Tables","content":"\u003cp\u003eTables 1-7 are available in the Supplementary Files section.\u003c/p\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":"journal-of-human-hypertension","isNatureJournal":false,"hasQc":false,"allowDirectSubmit":false,"externalIdentity":"jhh","sideBox":"Learn more about [Journal of Human Hypertension](http://www.nature.com/jhh/)","snPcode":"41371","submissionUrl":"https://mts-jhh.nature.com/cgi-bin/main.plex","title":"Journal of Human Hypertension","twitterHandle":"@jhhypertension","acdcEnabled":true,"dfaEnabled":true,"editorialSystem":"ejp","reportingPortfolio":"Nature AJ","inReviewEnabled":true,"inReviewRevisionsEnabled":false},"keywords":"","lastPublishedDoi":"10.21203/rs.3.rs-4462823/v1","lastPublishedDoiUrl":"https://doi.org/10.21203/rs.3.rs-4462823/v1","license":{"name":"CC BY 4.0","url":"https://creativecommons.org/licenses/by/4.0/"},"manuscriptAbstract":"\u003cp\u003eThere has been steady progress in documenting the psychosocial risk factors of hypertension. However, most of the extant evidence is based on population from the developed countries. Using nationally representative data from India, this cross-sectional study explores whether spousal age gap is associated with risk of hypertension in married women aged 20 to 49 years. Based on the age difference with their husbands, women were grouped into four categories: husband was \u0026ndash; i) of similar age, ii) 3\u0026ndash;5 years older, iii) 6\u0026ndash;9 years older, and iv) 10\u0026thinsp;+\u0026thinsp;years older. Compared to women whose husbands were of similar age, the odds of having hypertension for the other categories were assessed by estimating multivariable logistic regression models. While the hypertension prevalence in our sample was 18.9%, it was 2.2%-points lower among women whose husbands were of similar age, and 3.3%-points higher among women whose husbands were 10\u0026thinsp;+\u0026thinsp;years older. The adjusted odds of having hypertension for women with 10\u0026thinsp;+\u0026thinsp;years of spousal age difference were 1.18 (95% CI: 1.13\u0026ndash;1.24) times that of their counterparts who were of similar age to their husbands. These results were persistent in both younger (age 20\u0026ndash;34) and older (age 35\u0026ndash;49) women and robust across age at marriage, years in marriage, and various socioeconomic sub-groups including women\u0026rsquo;s educational attainment, husband\u0026rsquo;s educational level, household wealth, urban/rural residence, and geographic regions. The relationship also persisted after adjusting for husband\u0026rsquo;s hypertension status. Our findings thus highlight spousal age difference as a biopsychosocial factor influencing the risk of hypertension in women.\u003c/p\u003e","manuscriptTitle":"Spousal age difference and risk of hypertension in women: evidence from India","msid":"","msnumber":"","nonDraftVersions":[{"code":1,"date":"2024-06-24 09:24:40","doi":"10.21203/rs.3.rs-4462823/v1","editorialEvents":[{"type":"communityComments","content":0},{"type":"decision","content":"revise","date":"2024-07-10T15:46:42+00:00","index":"","fulltext":""},{"type":"editorInvitedReview","content":"This content is not available.","date":"2024-07-09T16:06:55+00:00","index":2,"fulltext":"This content is not available."},{"type":"reviewerAgreed","content":"This content is not available.","date":"2024-07-01T08:56:25+00:00","index":2,"fulltext":"This content is not available."},{"type":"editorInvitedReview","content":"This content is not available.","date":"2024-06-30T13:43:44+00:00","index":1,"fulltext":"This content is not available."},{"type":"reviewerAgreed","content":"This content is not available.","date":"2024-06-15T19:04:31+00:00","index":1,"fulltext":"This content is not available."},{"type":"reviewersInvited","content":"","date":"2024-06-09T15:58:06+00:00","index":"","fulltext":""},{"type":"editorAssigned","content":"","date":"2024-06-07T04:30:13+00:00","index":"","fulltext":""},{"type":"checksComplete","content":"","date":"2024-05-23T10:52:09+00:00","index":"","fulltext":""},{"type":"submitted","content":"Journal of Human Hypertension","date":"2024-05-22T19:34:12+00:00","index":"","fulltext":""}],"status":"published","journal":{"display":true,"email":"[email protected]","identity":"journal-of-human-hypertension","isNatureJournal":false,"hasQc":false,"allowDirectSubmit":false,"externalIdentity":"jhh","sideBox":"Learn more about [Journal of Human Hypertension](http://www.nature.com/jhh/)","snPcode":"41371","submissionUrl":"https://mts-jhh.nature.com/cgi-bin/main.plex","title":"Journal of Human Hypertension","twitterHandle":"@jhhypertension","acdcEnabled":true,"dfaEnabled":true,"editorialSystem":"ejp","reportingPortfolio":"Nature AJ","inReviewEnabled":true,"inReviewRevisionsEnabled":false}}],"origin":"","ownerIdentity":"1fd927c2-d84d-4367-87fe-95f8fe85ec58","owner":[],"postedDate":"June 24th, 2024","published":true,"recentEditorialEvents":[],"rejectedJournal":[],"revision":"","amendment":"","status":"published-in-journal","subjectAreas":[{"id":33010620,"name":"Health sciences/Risk factors"},{"id":33010621,"name":"Health sciences/Health care/Disease prevention/Preventive medicine"}],"tags":[],"updatedAt":"2024-09-27T10:47:09+00:00","versionOfRecord":{"articleIdentity":"rs-4462823","link":"https://doi.org/10.1038/s41371-024-00959-6","journal":{"identity":"journal-of-human-hypertension","isVorOnly":false,"title":"Journal of Human Hypertension"},"publishedOn":"2024-09-21 04:00:00","publishedOnDateReadable":"September 21st, 2024"},"versionCreatedAt":"2024-06-24 09:24:40","video":"","vorDoi":"10.1038/s41371-024-00959-6","vorDoiUrl":"https://doi.org/10.1038/s41371-024-00959-6","workflowStages":[]},"version":"v1","identity":"rs-4462823","journalConfig":"researchsquare"},"__N_SSP":true},"page":"/article/[identity]/[[...version]]","query":{"redirect":"/article/rs-4462823","identity":"rs-4462823","version":["v1"]},"buildId":"qtupq5eGEP_6zYnWcrvyt","isFallback":false,"isExperimentalCompile":false,"dynamicIds":[84888],"gssp":true,"scriptLoader":[]}