Early Marriage in Adolescence and Risk of High Blood Pressure and High Blood Glucose in Adulthood: Evidence from India
1
Institute of Public and Preventive Health, Augusta University, Augusta, GA 30912, USA
2
Department of Population Health Sciences, Medical College of Georgia, Augusta University, Augusta, GA 30912, USA
*
Author to whom correspondence should be addressed.
Women 2022, 2(3), 189-203; https://doi.org/10.3390/women2030020
Submission received: 7 June 2022
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Revised: 24 July 2022
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Accepted: 24 July 2022
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Published: 27 July 2022
Abstract
:Adolescence, the transition phase to adulthood, is a critical period for physical and psychological development. Disruptions during this period, such as getting married, could result in various adverse short- and long-term health outcomes. This study aimed to assess the differential risk of two common chronic conditions—high blood pressure and high blood glucose—in adult women (20–49 years) who were married during different stages of adolescence (10–19 years) compared to women who were married in their youth (20–24 years). Using the most recent nationally representative data from India, we separately assessed the odds in favor of having the two chronic conditions for women who were married during early (10–14 years), middle (15–17 years), and late (18–19 years) adolescence. We found that an earlier age at marriage during adolescence was associated with a higher risk of chronic conditions later in life. Women who were married during early adolescence were respectively 1.29 and 1.23 times more likely (p < 0.001) to have high blood pressure and high blood glucose compared to women who were married in their youth. These findings highlight the importance of preventing underage marriage among adolescent females to address the risk of downstream chronic health consequences as adults.
1. Introduction
Adolescence (age 10 to 19 years) is a critical period for physical and psychological development, which lays the foundation for good health [1]. During this transitional period, individuals go through many changes, including physical, social, emotional, cognitive, and sexual development. Environmental influences and stress exposure during this vulnerable time can have lasting effects on adolescents [2] and can lead to adverse health outcomes in later life [3,4]. However, little is known about the distinctive differences in the risk of poor health outcomes from adversity-based exposure during different phases of adolescence. Adolescence can be divided into early (10–14), middle (15–17), and late (18–19) adolescence, each marked by unique physical and psychological developmental markers [5]. Each phase can encompass a range of experiences that is unique to one’s emotional–social development trajectory. As such, exposure to stressors at different stages of adolescence could have a differential impact on health outcomes later in life.
This study focuses on the distinctive differences in health outcomes based on exposure to a potentially chronic disruption during adolescence, that is, early marriage, a harmful practice that has devastating socioeconomic and health consequences for women. Marriage during early and middle adolescent years (i.e., before age 18 years) is defined as child marriage [6]. Child brides in particular are disproportionately susceptible to experiencing family and marital disorganizations as well as suffering from physical, emotional, and sexual abuse and violence [7]. Child marriage among women is also associated with psychiatric disorders, emotional distress, and depression [8,9]. Further, child marriage forces a girl to perform adult roles, including sexual activity and childbearing, before reaching adulthood [10]. Research shows that earlier (before the age of 16 years) sexual experience and early-life exposure to sexual and physical abuse are linked to depression and anxiety over the life course [11,12]. Child marriage could therefore be considered a potential early-life stressor.
Globally, 650 million women and girls who are currently living were married as children [13]. In developing countries, approximately 40% of girls are married before reaching adulthood (age 18 years), and around 12% of these girls are married during early adolescence (before age 15 years) [6]. Child brides experience many socioeconomic disparities as well as various forms of physical and psychological abuse, which could have direct and indirect impacts on their later-life health outcomes. However, beyond reproductive outcomes, the long-term health of child brides is an area that often goes unnoticed and is less visited in literature [14]. Only three studies to date have begun to explore the risk of hypertension and other chronic conditions among child brides later in life [15,16,17]. To our knowledge, however, no studies have explored the differential risk of such outcomes in adult women in relation to different marital ages based on adolescent phases.
This study thus aimed to investigate whether exposure to child marriage during different stages of adolescence leads to a differential risk for two of the most common chronic conditions, high blood pressure and high blood glucose, during adulthood (age 20 to 49 years) among a nationally representative sample of women. We conducted this analysis using the most recent data from India, home to the largest adolescent population in the world [18]. India also has a markedly high prevalence of child marriage, with approximately 1.5 million adolescent girls married every year before their eighteenth birthday [18]. As such, this study bears relevance for designing effective hypertension and diabetes prevention and control policies and strategizing the provision of required healthcare services for women in low-resource settings, where the burden of child marriage remains high.
2. Materials and Methods
2.1. Data
We used data from the 2019–2021 wave of the India National Family Health Survey (NFHS-5). The NFHS-5 is a nationally representative survey that provides various sociodemographic and health indicators of women aged 15 to 49 years, with a 97% response rate [19]. Our analyses included data of 466,693 ever-married women aged 20 to 49 years for whom valid systolic and diastolic blood pressure and random blood glucose measures were reported. Participation in the NFHS-5 was voluntary, and informed consent was obtained from the respondents prior to each interview. The survey protocol was reviewed and approved by the Institutional Review Boards of the International Institute for Population Sciences and the ICF [19].
2.2. Measures
The NFHS-5 reports respondents’ age at first marriage. In line with the WHO adolescent phase classification [5], we categorized the study participants into four groups: (i) married during early adolescence (age 10 to 14 years), (ii) married during middle adolescence (age 15 to 17 years), (iii) married during late adolescence (age 18 to 19 years), and (iv) married during youth (age 20 to 24 years). Of note, the classification of “youth” in this study solely serves the purpose of distinguishing ages 20 to 24 years from the adolescent age range and does not refer to the UN definition of youth (age 15 to 24 years).
The first dependent variable, high blood pressure, was assessed using respondents’ systolic and diastolic blood pressure measurements. Blood pressure was measured three times during one visit with at least a five-minute interval between each measurement using the Omron Blood Pressure Monitor. Respondents were also asked if they were taking any anti-hypertensive medication. The average blood pressure measurements were recorded as follows: average of the second and third measures if both were available; the third measure if the second was missing; the second measure if the third was missing; and the first measure if both second and third measures were missing. Respondents were classified as having high blood pressure if the average systolic blood pressure (SBP) was greater than or equal to 140 mmHg, the diastolic blood pressure (DBP) was greater than or equal to 90 mmHg, or the respondent was taking anti-hypertensive medication at the time of the survey [19].
The second dependent variable, high blood glucose, was assessed using respondents’ random blood glucose levels, measured by Accu-Chek Performa Glucometer. A random blood glucose level ≥ 141 mg/dL was considered high blood glucose [19].
2.3. Statistical Analysis
We estimated separate logistic regressions to obtain the odds in favor of having high blood pressure and high blood glucose. Our dependent variables in the respective cases were dichotomous variables indicating whether the respondent had high blood pressure and high blood glucose or not. Our key explanatory variables were a set of binary variables indicating age at marriage—early adolescence (10–14 years), middle adolescence (15–17 years), and late adolescence (18–19 years). We compared the odds in favor of having the studied chronic conditions for different marital ages in adolescence with those in the reference category—marriage at youth (20–24 years).
Next, we estimated separate multivariable logistic specifications to obtain the adjusted odds in favor of having the respective chronic conditions. We controlled for various sociodemographic correlates as well as for several risk factors for high blood pressure and high blood glucose among women. Sociodemographic covariates included: age; educational attainment—no education (reference category), primary, secondary, and higher; marital status—married (reference category) and widowed/separated/divorced; household wealth index quintiles—poorest (reference category), poorer, middle, richer, and richest; religion—Hindu (reference category), Muslim, Christian, and other; caste—not socially or economically backward class (reference category), scheduled caste, scheduled tribe, and other backward class; and region of residence—rural (reference category) and urban. Risk factors included: women’s nutritional status measured by body mass index (BMI)—normal (BMI 18.5 to 24.9 kg/m2—reference group), thin (BMI < 18.5 kg/m2), overweight (BMI 25.0 to 29.9 kg/m2), and obese (BMI ≥ 30.0 kg/m2); parity or number of children born; tobacco use; alcohol use; current pregnancy status; and current breast-feeding status. Of note, the included covariates are commensurate with those used in the extant literature on hypertension and diabetes prevalence in India [20,21].
Importantly, covariates were included to assess whether the relationship between marriage at different phases of adolescence and the risk of having high blood pressure and high blood glucose persisted after accounting for certain sociodemographic and behavioral characteristics. As such, these correlates were not assessed as predictors of the chronic conditions in our analyses. To account for regional variations in marital practices and healthcare provision across different states of India, we also controlled for state fixed effects in the multivariable specifications. Since prevalence rates of high blood pressure and high blood glucose in women increase with age [19], we separately estimated the models for the full sample of women aged 20–49 years and for sub-samples of the younger cohort aged 20–34 years and the older cohort aged 35–49 years.
To check the robustness of our results, we estimated the multivariable models for urban and rural and poor (bottom-two quintiles of household wealth index) and non-poor (top-three quintiles of household wealth index) sub-samples. Lastly, to assess the role of potential mediators, we accounted for (i) age difference from the husband, (ii) age at first birth, and (iii) household environment in the multivariable specifications. The household environment was reflected by the following covariates: respondent’s relationship to the household head, household head’s sex, household head’s educational attainment, household size, and the presence of elderly (age 65+ years) in the household. All models were estimated using complex survey weights in Stata version 17.0 (StataCorp, College Station, TX, USA) software.
3. Results
In our sample of adult women aged 20–49 years, 12.8% were married during early adolescence, 31.8% were married during middle adolescence, and 24.6% were married during late adolescence. The prevalence rates of marriage during early and middle adolescence were higher in the older age cohort, in rural areas, and in poor households. Table 1 presents the background characteristics of the study participants by age at first marriage.
The prevalence of high blood pressure by marital age is presented in Figure 1. About 17.4% of the women in the sample had high blood pressure. The prevalence was 10.7% in the younger age cohort and 24.6% in the older age cohort. The prevalence was the highest among women who were married during early adolescence and gradually declined by marital age in both age cohorts. Compared to women married at the ages of 20–24 years, high blood pressure prevalence rates among women married during early and middle adolescence were respectively 6.3 and 2.9 percentage points higher (p < 0.001). However, no significant differences were observed in the prevalence rates between women married during late adolescence and during youth. Similar patterns were observed for both younger and older age cohorts.
Figure 2 illustrates the prevalence of high blood glucose by marital age. Like the prevalence of high blood pressure, the prevalence of high blood glucose gradually declined with marital age. The overall prevalence was 9.0%, while it was 5.3% in the younger age cohort and 13.2% in the older age cohort. The prevalence of high blood glucose was respectively 3.1 and 1.4 percentage points higher (p < 0.001) among women married during early and middle adolescence compared to their counterparts married during youth. The prevalence of women married during late adolescence was no different from that of women married during youth. These patterns were similar in both younger and older age cohorts.
Figure 3 presents the crude odds ratios in favor of having high blood pressure for the sociodemographic and other correlates included in the model. The risk of having high blood pressure increased with age and was higher among women who were widowed/divorced/separated. While the risk was lower among women with higher educational attainment, the risk was higher among women from wealthier households. Women in urban areas also had higher odds of having high blood pressure compared to women who resided in rural areas. Being overweight or obese was significantly associated with a higher risk of having high blood pressure. Tobacco use and alcohol consumption were also found to be risk factors for hypertension in the sample. These results are consistent with findings in the extant literature on hypertension in India [20].
The crude odds ratios in favor of having high blood glucose for the model covariates are presented in Figure 4. Like the odds of having high blood pressure, the odds of having high blood glucose were also significantly higher among overweight and obese women in the sample. Women residing in urban areas, from wealthier households, and with lower educational attainment had higher odds of having high blood glucose. The odds increased with age and were higher among women who experienced marital disruption. These estimates were also consistent with those in the extant literature on diabetes in India [21].
The unadjusted odds ratios (ORs) from the logistic regressions are presented in Table 2. The odds of having high blood pressure among women who were married during early adolescence were significantly greater (OR = 1.5) than those of their counterparts married during youth. Similarly, women married during middle adolescence were 1.2 times more likely to have high blood pressure compared to women who were married in their youth. The odds of having high blood pressure were no different for women married during late adolescence compared to those of women married at the ages of 20–24 years. The results were similar in both younger and older age cohorts. Women married during early and middle adolescence were 1.4 and 1.2 times, respectively, more likely to have high blood glucose compared to women married during youth. Higher odds of having high blood glucose among women married at the ages of 10–14 years and 15–17 years were evident in both younger and older age cohorts. Like the odds of high blood pressure, the odds of high blood glucose for women married at the ages of 18–19 years were no different from those of women married at the ages of 20–24 years in the full sample as well as in the younger and older age cohorts.
The adjusted odds ratios (AORs) from the multivariable specifications are reported in Table 3. The adjusted estimates for both high blood pressure and high blood glucose outcomes were similar to the crude estimates presented in Table 2. Women who were married during early adolescence were 1.3 and 1.2 times more likely to have high blood pressure and high blood glucose, respectively, compared to women who were married at the ages of 20–24 years. For women married during middle adolescence, the adjusted odds were respectively 1.2 and 1.1 times those of their counterparts married during youth. The adjusted odds were similar in both younger and older age cohorts for both chronic conditions.
The AORs in the urban/rural and poor/non-poor sub-samples were similar to those of the full sample (Figure 5 and Figure 6). Urban women who were married in early adolescence were 1.3 times more likely to have high blood pressure and high blood glucose compared to their counterparts married during youth. Women married during early adolescence in rural areas also had similar risks, as they were 1.3 and 1.2 times more likely to have high blood pressure and high blood glucose, respectively, compared to women married during youth. The risks were similar in women from both poor and non-poor households. We also performed the Chow test to examine whether the higher odds of having high blood pressure or high blood glucose for women married during early adolescence were statistically different across the urban/rural and poor/non-poor subgroups. The results of the Chow tests suggested no statistically significant differences in the odds across these sub-groups.
Lastly, results accounting for potential mediating factors are presented in Table 4. Compared to women married during youth, women married during early and middle adolescence were more likely to get married to older men and to give birth before their 18th birthday. After controlling for the age difference from the husband, age at first birth, and household environment, the AORs in favor of high blood pressure decreased from 1.288 to 1.139, and the AORs in favor of high blood glucose decreased from 1.227 to 1.104 for marriage during early adolescence. The AORs in favor of the respective chronic conditions for marriage during middle adolescence also decreased from 1.155 to 1.066 and 1.120 to 1.047. These results suggest that the association between early marriage and the subsequent risk of chronic conditions was partly mediated through factors such as early childbearing and getting married to older men.
4. Discussion
In this study, we assessed how exposure to stressors at different stages of adolescence is associated with differential health outcomes in women. Considering early marriage as a stressor, we examined whether women married at different stages of adolescence bear a differential risk of high blood pressure or high blood glucose later in life. We found that the risks of having high blood pressure and high blood glucose were significantly higher among women who were married during early (age 10–14 years) and middle (age 15–17 years) adolescence compared to women who were married during late adolescence (age 18–19 years) and youth (age 20–24 years). Our results further suggest that the earlier a girl is married, the higher her risk of having high blood pressure or high blood glucose later in life.
High blood pressure and high blood glucose are critical risk factors for cardiovascular diseases, which are the leading cause of premature mortality worldwide [22]. As such, understanding how marriage at different stages of adolescence is associated with the risk of having high blood pressure and high blood glucose during adulthood may provide new insights on how to modify the downstream risk of premature mortality in women in low- and middle-income countries (LMICs).
Our findings are comparable to those in the literature that examines the association between adverse early-life experiences with later-life behavioral and health outcomes. The association between exposure to adverse childhood experiences (ACEs) and subsequent health outcomes is established in the extant literature [23]. Another strand of literature finds that precocious and stressful transitions during adolescence are associated with cardiometabolic disease risk in later life [24]. Despite early marriage being a stressful event in adolescence, there is a dearth of evidence on its consequences on later-life health outcomes, let alone the differential impact of marriage at different stages of adolescence. To date, the preponderance of works on child marriage’s impact on health has examined the risk of reproductive health and sexually transmitted diseases (STDs), with a few exploring impacts on mental health [14]. This study adds to the evolving body of work that links child marriage to long-term health and behavioral outcomes beyond reproductive health and STDs [15,16,17,25].
Although the examination of underlying mechanisms for the relationship between early marriage and the risk of high blood pressure and high blood glucose during adulthood was beyond the scope of this paper, previous studies have found that early menarche is associated with the risk of elevated blood pressure and type 2 diabetes [26,27]. Studies have also reported an association between early menarche and early marriage in LMICs [28]. The association that we observed in this study, therefore, could be partly attributed to forced biological maturity among women married as children. Early marriage is also associated with early pregnancy and higher parity [29]. A recent study showed that adolescent childbearing is associated with a heightened risk of hypertension among reproductive-age women, and the earlier a woman gave birth during adolescence, the greater the risk [30]. Early childbearing, thus, could be another channel through which early marriage may impact chronic conditions in adult women.
Other potential mediating factors may include spousal age differences, intimate partner violence, and a child bride’s suppressed agency in decision making on healthcare and fertility control. Child marriage was found to be associated with high fertility, repeated childbirth, and multiple unwanted pregnancies [31]. Girls married as children have little control over choosing their partners [32], and being married to older men was found to be associated with lower contraceptive use in women [33]. Since fertility history is associated with allostatic load and long-term health outcomes [34], early marriage, through its impact on fertility, may impact chronic conditions in women. Child brides are also more likely to experience intimate partner violence [14], which has implications for both physical and mental health [35]. Future research exploring etiologies and mechanisms may further develop our understanding of this issue.
Like other cross-sectional studies, our analyses are subject to some limitations. First, due to the cross-sectional nature of the data, we were not able to identify a causal pathway for the observed relationship. Future research using longitudinal data may provide more insights on this. Second, the high blood pressure and high blood glucose conditions in the NFHS-5 were not clinically diagnosed; however, these estimates are considered the best approximation of population-level prevalence rates [36]. Third, no data were available on family history or genetic predisposition for high blood pressure or blood glucose, nor exercise patterns, which are identified as non-modifiable and modifiable risk factors, respectively, that may play an important role in driving associations [37,38,39]. Despite these limitations, we presented a very strong and robust association between marriage at early and middle adolescent age and the risk of high blood pressure and high blood glucose in adult women, which warrants the attention of public health practitioners and policy makers.
5. Conclusions
The findings of this study show that delaying marriage at adolescence could improve women’s long-term health. However, the deeply embedded cultural considerations of child marriage have continued to propagate the practice in recent decades. We call for policy actions to ban child marriage as well as to provide child brides with necessary healthcare services to mitigate their disproportionately higher risk of chronic conditions at adult age. Our findings suggest that secondary and tertiary prevention efforts are needed to improve chronic disease management among women who have already been married during early and middle adolescence. The results also suggest that early marriage poses a higher risk of high blood pressure and high blood glucose among women living in rural areas and from poor households, where the risk of early marriage is higher, as well as among women living in urban areas and from non-poor households, where the risk of early marriage is lower. As such, it is important to not only address driving social determinants such as culture, poverty, and geography for preventing child marriage but also promote health interventions targeting chronic disease outcomes such as hypertension and diabetes. The identification and understanding of the geographic distribution of programs should be explored to better guide where health practices may have the best impact on women married as children.
Author Contributions
Conceptualization, B.D. and A.T.; methodology, B.D.; software, B.D.; validation, B.D. and A.T.; formal analysis, B.D.; investigation, B.D.; resources, B.D.; data curation, B.D.; writing—original draft preparation, B.D.; writing—review and editing, A.T. All authors have read and agreed to the published version of the manuscript.
Funding
This research received no external funding.
Institutional Review Board Statement
Ethical review and approval were waived for this study due to the use of publicly available anonymized secondary data. The survey protocol was approved by the institutional review boards of the International Institute of Population Sciences and the ICF and further reviewed by the U.S. Centers for Disease Control and Prevention. 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.
Informed Consent Statement
Informed consent was obtained from all subjects involved in the study.
Data Availability Statement
The data used in this paper are freely available from the USAID’s Demographic and Health Surveys (DHS) Program website (https://www.dhsprogram.com/data/dataset_admin/login_main.cfm (accessed on 6 May 2022)) upon registering as a DHS data user and submitting a research proposal.
Acknowledgments
We thank Bethany Johnson and Jamani Garner for their research support and the participants in the Institute of Public and Preventive Health (IPPH) Monthly Brown Bag Seminar for constructive inputs and suggestions.
Conflicts of Interest
The authors declare no conflict of interest.
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Figure 1.
High blood pressure prevalence by age at marriage. Estimates were obtained using complex survey weights. The horizontal lines across the markers represent 95% confidence intervals. The vertical dashed lines represent the average high blood pressure prevalence rates in the respective age groups.
Figure 1.
High blood pressure prevalence by age at marriage. Estimates were obtained using complex survey weights. The horizontal lines across the markers represent 95% confidence intervals. The vertical dashed lines represent the average high blood pressure prevalence rates in the respective age groups.
Figure 2.
High blood glucose prevalence by age at marriage. Estimates were obtained using complex survey weights. The horizontal lines across the markers represent 95% confidence intervals. The vertical dashed lines represent the average high blood glucose prevalence rates in respective age groups.
Figure 2.
High blood glucose prevalence by age at marriage. Estimates were obtained using complex survey weights. The horizontal lines across the markers represent 95% confidence intervals. The vertical dashed lines represent the average high blood glucose prevalence rates in respective age groups.
Figure 3.
Crude odds ratios in favor of having high blood pressure for the covariates. Estimates were obtained using complex survey weights. The horizontal lines across the markers represent 95% confidence intervals. The base categories of each categorical variable are as follows: educational attainment—no education; marital status—married; religion—Hindu; caste—none; wealth index quintiles—Q1: poorest; residence—rural; and BMI—normal.
Figure 3.
Crude odds ratios in favor of having high blood pressure for the covariates. Estimates were obtained using complex survey weights. The horizontal lines across the markers represent 95% confidence intervals. The base categories of each categorical variable are as follows: educational attainment—no education; marital status—married; religion—Hindu; caste—none; wealth index quintiles—Q1: poorest; residence—rural; and BMI—normal.
Figure 4.
Crude odds ratios in favor of having high blood glucose for the covariates. Estimates were obtained using complex survey weights. The horizontal lines across the markers represent 95% confidence intervals. The base categories of each categorical variable are as follows: educational attainment—no education; marital status—married; religion—Hindu; caste—none; wealth index quintiles—Q1: poorest; residence—rural; and BMI—normal.
Figure 4.
Crude odds ratios in favor of having high blood glucose for the covariates. Estimates were obtained using complex survey weights. The horizontal lines across the markers represent 95% confidence intervals. The base categories of each categorical variable are as follows: educational attainment—no education; marital status—married; religion—Hindu; caste—none; wealth index quintiles—Q1: poorest; residence—rural; and BMI—normal.
Figure 5.
Adjusted odds ratios in favor of having high blood pressure for age at marriage in urban/rural and poor/non-poor sub-samples. Estimates were obtained using complex survey weights. The horizontal lines across the markers represent 95% confidence intervals. All regressions included the following covariates: age, educational attainment, marital status, religion, caste, wealth index quintiles (for urban/rural sub-samples only), urban/rural residence (for poor/non-poor sub-samples only), body mass index (BMI) categories, parity (i.e., number of children born), tobacco use, alcohol consumption, pregnancy status, lactation status, and state fixed effects.
Figure 5.
Adjusted odds ratios in favor of having high blood pressure for age at marriage in urban/rural and poor/non-poor sub-samples. Estimates were obtained using complex survey weights. The horizontal lines across the markers represent 95% confidence intervals. All regressions included the following covariates: age, educational attainment, marital status, religion, caste, wealth index quintiles (for urban/rural sub-samples only), urban/rural residence (for poor/non-poor sub-samples only), body mass index (BMI) categories, parity (i.e., number of children born), tobacco use, alcohol consumption, pregnancy status, lactation status, and state fixed effects.
Figure 6.
Adjusted odds ratios in favor of having high blood glucose by age at marriage by urban/rural and poor/non-poor sub-samples. Estimates were obtained using complex survey weights. The horizontal lines across the markers represent 95% confidence intervals. All regressions included the following covariates: age, educational attainment, marital status, religion, caste, wealth index quintiles (for urban/rural sub-samples only), urban/rural residence (for poor/non-poor sub-samples only), body mass index (BMI) categories, parity (i.e., number of children born), tobacco use, alcohol consumption, pregnancy status, lactation status, and state fixed effects.
Figure 6.
Adjusted odds ratios in favor of having high blood glucose by age at marriage by urban/rural and poor/non-poor sub-samples. Estimates were obtained using complex survey weights. The horizontal lines across the markers represent 95% confidence intervals. All regressions included the following covariates: age, educational attainment, marital status, religion, caste, wealth index quintiles (for urban/rural sub-samples only), urban/rural residence (for poor/non-poor sub-samples only), body mass index (BMI) categories, parity (i.e., number of children born), tobacco use, alcohol consumption, pregnancy status, lactation status, and state fixed effects.
Table 1.
Descriptive statistics by age at marriage.
| Ever Married | Married at Adolescence | Married at Youth: 20–24 | |||
|---|---|---|---|---|---|
| Early: 10–14 | Middle: 15–17 | Late: 18–19 | |||
| Percentage of women 1 | |||||
| Categorial covariates | |||||
| Education | |||||
| No education | 30.06 | 50.07 | 36.94 | 26.16 | 17.78 |
| (45.85) | (47.95) | (47.28) | (44.30) | (39.40) | |
| Primary | 14.90 | 21.1 | 17.93 | 14.27 | 9.69 |
| (35.61) | (39.13) | (37.58) | (35.26) | (30.49) | |
| Secondary | 44.86 | 27.75 | 42.51 | 51.71 | 48.91 |
| (49.73) | (42.94) | (48.43) | (50.37) | (51.52) | |
| Higher | 10.19 | 1.09 | 2.62 | 7.86 | 23.62 |
| (30.25) | (9.95) | (15.64) | (27.12) | (43.77) | |
| Marital status | |||||
| Married | 94.34 | 91.60 | 93.82 | 95.01 | 95.47 |
| (23.11) | (26.60) | (23.6) | (21.95) | (21.43) | |
| Widowed/divorced/separated | 5.66 | 8.40 | 6.18 | 4.99 | 4.53 |
| (23.11) | (26.60) | (23.60) | (21.95) | (21.43) | |
| Wealth index quintile | |||||
| 1st (Poorest) | 19.55 | 26.96 | 23.57 | 18.73 | 13.00 |
| (39.66) | (42.56) | (41.58) | (39.33) | (34.66) | |
| 2nd (Poorer) | 20.86 | 25.42 | 23.74 | 20.9 | 15.98 |
| (40.63) | (41.76) | (41.68) | (40.98) | (37.76) | |
| 3rd (Middle) | 21.12 | 22.35 | 22.06 | 21.79 | 19.10 |
| (40.81) | (39.95) | (40.62) | (41.61) | (40.51) | |
| 4th (Richer) | 20.67 | 16.79 | 18.72 | 21.31 | 23.79 |
| (40.50) | (35.84) | (38.21) | (41.28) | (43.89) | |
| 5th (Richest) | 17.79 | 8.48 | 11.92 | 17.27 | 28.13 |
| (38.24) | (26.71) | (31.74) | (38.1) | (46.34) | |
| Religion | |||||
| Hindu | 82.66 | 82.48 | 83.48 | 82.91 | 81.68 |
| (37.86) | (36.45) | (36.38) | (37.94) | (39.87) | |
| Muslim | 12.83 | 14.29 | 13.13 | 12.80 | 11.93 |
| (33.44) | (33.57) | (33.09) | (33.68) | (33.41) | |
| Christian | 2.01 | 1.74 | 1.49 | 1.80 | 2.82 |
| (14.03) | (12.54) | (11.86) | (13.41) | (17.06) | |
| Other | 2.50 | 1.48 | 1.90 | 2.48 | 3.57 |
| (15.63) | (11.58) | (13.37) | (15.68) | (19.13) | |
| Caste | |||||
| None | 25.07 | 23.14 | 23.48 | 23.98 | 28.36 |
| (43.34) | (40.45) | (41.53) | (43.03) | (46.46) | |
| Scheduled caste | 22.10 | 25.88 | 23.59 | 21.63 | 19.38 |
| (41.49) | (42.00) | (41.59) | (41.50) | (40.74) | |
| Scheduled tribe | 9.42 | 9.76 | 10.04 | 9.67 | 8.45 |
| (29.21) | (28.46) | (29.44) | (29.79) | (28.66) | |
| Other backward class | 43.41 | 41.22 | 42.89 | 44.72 | 43.81 |
| (49.56) | (47.21) | (48.49) | (50.12) | (51.13) | |
| Residence | |||||
| Rural | 70.26 | 77.21 | 74.87 | 70.88 | 62.15 |
| (45.71) | (40.23) | (42.5) | (45.79) | (49.99) | |
| Urban | 29.74 | 22.79 | 25.13 | 29.12 | 37.85 |
| (45.71) | (40.23) | (42.5) | (45.79) | (49.99) | |
| BMI group | |||||
| Normal (18.5–24.9) | 57.91 | 57.4 | 58.48 | 58.54 | 57.03 |
| (49.37) | (47.42) | (48.28) | (49.66) | (51.02) | |
| Thin (<18.5) | 13.40 | 13.89 | 13.85 | 14.27 | 12.05 |
| (34.07) | (33.17) | (33.84) | (35.25) | (33.56) | |
| Overweight (25.0–29.9) | 21.05 | 21.32 | 20.23 | 20.13 | 22.50 |
| (40.76) | (39.28) | (39.36) | (40.42) | (43.04) | |
| Obese (≥30.0) | 7.64 | 7.39 | 7.44 | 7.06 | 8.42 |
| (26.57) | (25.09) | (25.71) | (25.81) | (28.62) | |
| Tobacco use | 5.41 | 8.11 | 6.48 | 4.87 | 3.61 |
| (22.62) | (26.18) | (24.12) | (21.69) | (19.24) | |
| Alcohol consumption | 0.88 | 1.39 | 0.94 | 0.74 | 0.73 |
| (9.36) | (11.24) | (9.45) | (8.65) | (8.77) | |
| Pregnant | 4.31 | 1.43 | 3.01 | 5.05 | 6.27 |
| (20.31) | (11.4) | (16.73) | (22.06) | (24.98) | |
| Lactating | 18.56 | 8.66 | 16.03 | 22.45 | 22.18 |
| (38.88) | (26.97) | (35.95) | (42.06) | (8.30) | |
| Continuous covariates | |||||
| Years | |||||
| Age | 34.1 | 36.23 | 34.59 | 33.09 | 33.5 |
| (8.31) | (7.43) | (8.17) | (8.67) | (42.82) | |
| Number | |||||
| Parity | 2.43 | 3.12 | 2.77 | 2.32 | 1.89 |
| (1.46) | (1.50) | (1.43) | (1.39) | (1.32) | |
| Observations | 466,693 | 54,943 | 142,309 | 116,589 | 152,852 |
1 Estimates were obtained using complex survey weights. Standard deviations are in parentheses. Shares (for categorical covariates) add up to 100% across rows for education, marital status, wealth index quintiles, religion, caste, residence, and BMI group.
Table 2.
Crude odds ratios in favor of having high blood pressure and high blood glucose by age at marriage.
Table 2.
Crude odds ratios in favor of having high blood pressure and high blood glucose by age at marriage.
| High Blood Pressure 1 | High Blood Glucose | |||||
|---|---|---|---|---|---|---|
| All | Age 20–34 | Age 35–49 | All | Age 20–34 | Age 35–49 | |
| Age at marriage | ||||||
| Youth (20–24) | Ref. | Ref. | Ref. | Ref. | Ref. | Ref. |
| Early adolescence (10–14) | 1.521 *** | 1.446 *** | 1.262 *** | 1.432 *** | 1.393 *** | 1.184 *** |
| (1.466, 1.578) | (1.355, 1.543) | (1.208, 1.318) | (1.364, 1.504) | (1.274, 1.523) | (1.116, 1.255) | |
| Middle adolescence (15–17) | 1.229 *** | 1.129 *** | 1.142 *** | 1.192 *** | 1.101 ** | 1.101 *** |
| (1.194, 1.266) | (1.073, 1.188) | (1.101, 1.183) | (1.147, 1.238) | (1.031, 1.176) | (1.050, 1.155) | |
| Late adolescence (18–19) | 1.029 | 1.006 | 1.037 | 1.006 | 0.945 | 1.035 |
| (0.998, 1.061) | (0.959, 1.056) | (0.997, 1.079) | (0.966, 1.049) | (0.882, 1.013) | (0.981, 1.091) | |
| Observations | 466,693 | 242,201 | 224,492 | 459,816 | 239,711 | 220,105 |
1 Estimates were obtained using complex survey weights. 95% confidence intervals are in parentheses. *** p < 0.001, ** p < 0.01.
Table 3.
Adjusted odds ratios in favor of having high blood pressure and high blood glucose by age at marriage.
Table 3.
Adjusted odds ratios in favor of having high blood pressure and high blood glucose by age at marriage.
| High Blood Pressure 1 | High Blood Glucose | |||||
|---|---|---|---|---|---|---|
| All | Age 20–34 | Age 35–49 | All | Age 20–34 | Age 35–49 | |
| Age at marriage | ||||||
| Youth (20–24) | Ref. | Ref. | Ref. | Ref. | Ref. | Ref. |
| Early adolescence (10–14) | 1.288 *** | 1.249 *** | 1.292 *** | 1.227 *** | 1.224 *** | 1.233 *** |
| (1.239, 1.340) | (1.162, 1.343) | (1.233, 1.354) | (1.163, 1.295) | (1.108, 1.352) | (1.157, 1.314) | |
| Middle adolescence (15–17) | 1.155 *** | 1.085 ** | 1.178 *** | 1.120 *** | 1.078 * | 1.145 *** |
| (1.120, 1.192) | (1.027, 1.147) | (1.133, 1.224) | (1.075, 1.168) | (1.000, 1.161) | (1.089, 1.205) | |
| Late adolescence (18–19) | 1.063 *** | 1.049 | 1.058 ** | 1.042 | 1.013 | 1.063 * |
| (1.030, 1.097) | (0.997, 1.103) | (1.016, 1.102) | (0.998, 1.088) | (0.942, 1.089) | (1.007, 1.122) | |
| Observations | 465,575 | 241,687 | 223,888 | 458,777 | 239,229 | 219,548 |
1 Estimates were obtained using complex survey weights. 95% confidence intervals are in parentheses. *** p < 0.001, ** p < 0.01, * p < 0.05. All models accounted for the following covariates: covariates were controlled for: age, educational attainment, marital status, religion, caste, urban/rural residence, wealth index, body mass index (BMI) categories, parity (i.e., number of children born), tobacco use, alcohol consumption, pregnancy status, lactation status, and state fixed effects.
Table 4.
Adjusted odds ratios in favor of having high blood pressure and high blood glucose by age at marriage with controls for potential mediating factors.
Table 4.
Adjusted odds ratios in favor of having high blood pressure and high blood glucose by age at marriage with controls for potential mediating factors.
| High Blood Pressure 1 | High Blood Glucose | |||||
|---|---|---|---|---|---|---|
| All | Age 20–34 | Age 35–49 | All | Age 20–34 | Age 35–49 | |
| Age at marriage | ||||||
| Youth (20–24) | Ref. | Ref. | Ref. | Ref. | Ref. | Ref. |
| Early adolescence (10–14) | 1.139 *** | 1.163 ** | 1.125 *** | 1.104 * | 1.223 ** | 1.060 |
| (1.076, 1.205) | (1.050, 1.288) | (1.051, 1.204) | (1.022, 1.194) | (1.057, 1.415) | (0.967, 1.161) | |
| Middle adolescence (15–17) | 1.066 ** | 1.038 | 1.078 ** | 1.047 | 1.150 * | 1.008 |
| (1.020, 1.113) | (0.961, 1.120) | (1.022, 1.136) | (0.986, 1.111) | (1.031, 1.282) | (0.940, 1.082) | |
| Late adolescence (18–19) | 1.026 | 1.010 | 1.029 | 1.019 | 1.064 | 1.004 |
| (0.989, 1.064) | (0.953, 1.071) | (0.981, 1.079) | (0.968, 1.072) | (0.978, 1.158) | (0.943, 1.069) | |
| Observations | 379,447 | 195,879 | 183,568 | 374,133 | 194,008 | 180,125 |
1 Estimates were obtained using complex survey weights. 95% confidence intervals are in parentheses. *** p < 0.001, ** p < 0.01, * p < 0.05. All models accounted for the following covariates: covariates were controlled for: age, educational attainment, marital status, religion, caste, urban/rural residence, wealth index, body mass index (BMI) categories, parity (i.e., number of children born), tobacco use, alcohol consumption, pregnancy status, lactation status, and state fixed effects. In addition, the models accounted for the respondent’s relationships to the household head, household size, the presence of elderly (age 65+ years) in the household, the sex of the household head, educational attainment of the household head, age difference from the husband, and the respondent’s age at first birth.
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Datta, B.; Tiwari, A. Early Marriage in Adolescence and Risk of High Blood Pressure and High Blood Glucose in Adulthood: Evidence from India. Women 2022, 2, 189-203. https://doi.org/10.3390/women2030020
AMA Style
Datta B, Tiwari A. Early Marriage in Adolescence and Risk of High Blood Pressure and High Blood Glucose in Adulthood: Evidence from India. Women. 2022; 2(3):189-203. https://doi.org/10.3390/women2030020
Chicago/Turabian StyleDatta, Biplab, and Ashwini Tiwari. 2022. "Early Marriage in Adolescence and Risk of High Blood Pressure and High Blood Glucose in Adulthood: Evidence from India" Women 2, no. 3: 189-203. https://doi.org/10.3390/women2030020
