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. Author manuscript; available in PMC: 2025 Sep 27.
Published in final edited form as: J Epidemiol Community Health. 2025 Oct 9;79(11):858–865. doi: 10.1136/jech-2025-223994

Reproductive history, menopause and cardiometabolic health in women: a multicountry analysis

Wilhemina Quarpong 1, Suchitra Chandrasekaran 2,3, K M Venkat Narayan 1,3,4, Usha Ramakrishnan 1,4, Nikhil Tandon 5, Shivani Anil Patel 1,3,4
PMCID: PMC12470442  NIHMSID: NIHMS2110388  PMID: 40784744

Abstract

Background:

We investigated the association of reproductive history with cardiometabolic health in ethnically diverse women across five continents.

Methods:

We pooled cross-sectional survey data on non-pregnant women aged 30–49 years from 15 countries. Multilevel models examined associations between menopausal status, age at first birth (≥20 vs. <20 years), parity (1, 2, 3, 4+ vs. 0 births), and cardiometabolic indicators: body mass index (BMI), systolic blood pressure (SBP), and fasting blood glucose (FBG), adjusting for age and socioeconomic status.

Results:

We included 413,802 women (median age 38 years; 14% postmenopausal). Being in a postmenopausal state was associated with lower BMI (−0.22, 95% CI: −0.27, −0.17 kg/m2) and higher SBP (0.35, 95% CI: 0.18, 0.52 mmHg). In parous premenopausal women (n=332,569), later age at first birth was associated with lower BMI (−0.33, 95% CI: −0.36, −0.30 kg/m2) and SBP (−0.59, 95% CI: −0.69, −0.48 mmHg); higher parity was associated with lower SBP (−0.77 to −2.04 mmHg for 1–4+ births) and higher BMI (0.11–0.14 kg/m2 for 1–3 births). Among parous postmenopausal women (n=55,788), later age at first birth was associated with lower BMI (−0.15, 95% CI: −0.23, −0.07 kg/m2) and SBP (−0.38, 95% CI: −0.67, −0.08 mmHg), and higher FBG (2.08, 95% CI: 0.08, 4.11 mg/dl), while higher parity was associated with lower SBP (−1.60 to −3.06 mmHg for 1–4+ births).

Conclusions:

Later age at first birth was associated with lower BMI and SBP regardless of menopausal status, while higher parity was linked to lower SBP. Reproductive history can be useful in identifying cardiometabolic risk in women across diverse settings.

Keywords: Cardiometabolic health, reproductive history, women’s health, ethnic diversity

INTRODUCTION

Cardiovascular disease is the leading cause of death in women worldwide.1 Dominant prevention and management paradigms do not consider female-specific reproductive histories that are implicated in cardiometabolic changes across the life course. Yet, mounting evidence2,3 links women’s reproductive history with cardiometabolic conditions such as hypertension and diabetes, which are established risk factors for cardiovascular disease. Most of the evidence comes from relatively homogenous populations in high-income countries,4–6 which limits its applicability to women in low- and middle-income countries (LMICs).

Reproductive history and menopause have been associated with physiological changes that may influence long-term cardiometabolic health.7 Early age at first birth has been linked to cardiovascular disease and mortality,4 with less evidence for intermediate cardiovascular risk factors, while findings for parity remain inconsistent.5,6 Menopause, defined as the permanent cessation of menstruation for 12 consecutive months,8,9 has been consistently shown to increase cardiometabolic risk.10 The evidence linking menopause with elevated blood pressure is strong,11 whereas findings related to overall body weight vary across populations10,11 and those for glucose metabolism—though investigated in fewer studies—also show some inconsistency.10,11 Women in LMICs tend to experience menopause earlier than those in high-income countries,12 and it is unclear whether and how this impacts cardiometabolic health profiles.

Given that menopause is preceded by hormonal shifts associated with adverse cardiometabolic changes,10,13 it is important to consider whether reproductive history impacts cardiometabolic outcomes differently before and after menopause. Previous studies have largely ignored menopausal status or focused on older postmenopausal women,4–6 making it difficult to disentangle the effects of chronological aging from reproductive aging. While premenopausal women generally have lower cardiometabolic risk due to ongoing hormone exposure, it is unclear whether reproductive events like earlier age at first birth or parity influence cardiometabolic risk during these years. Among postmenopausal women, age-related risk accumulation and estrogen decline may interact with earlier reproductive exposures, potentially amplifying their effects.7,14

To investigate the potential role of reproductive history and menopause in shaping cardiometabolic health globally, we conducted a cross-sectional analysis of 413,802 ethnically diverse women from 15 countries across five world regions. We described cardiometabolic profiles by menopausal status and investigated associations of age at first birth and parity with cardiometabolic risk factors separately for premenopausal and postmenopausal women. By including a range of reproductive factors in both groups, this study provides a comprehensive, global analysis of the association between reproductive history and cardiometabolic health in women.

METHODS

Study design, population, and data sources

We conducted an analysis of nationally representative survey data focusing on non-pregnant women aged 30–49 years from 15 countries spanning five world regions: Africa (Benin, Ghana, Lesotho, Namibia, South Africa), Asia (Bangladesh, India, Nepal, Kyrgyz Republic, Tajikistan), Europe (Albania), Latin America & the Caribbean (Haiti, Peru, Mexico), and North America (United States of America, US).

Data for 12 countries were obtained from the database of the Demographic and Health Surveys Program (DHS).15 After conducting a thorough search of surveys assessing at least one of body mass index, blood pressure, or fasting blood glucose between 2010 and 2023, we identified 20 DHS surveys from 13 countries (all included countries except Mexico and US), selecting the most recent standard survey available for each. Data for Peru (Peru Demographic and Family Health Survey – Spanish acronym ENDES) was accessed through the national statistics repository,16 as it was not available via the DHS website.

To enhance the diversity of the sample, we also included publicly available data from Mexico (Mexican National Health and Nutrition Survey, Spanish acronym ENSANUT)17 and the United States (National Health and Nutrition Examination Survey, NHANES),18 sourced from their respective national repositories.

We excluded women with missing information for any of the study measures.

Study measures

Cardiometabolic measures

The cardiometabolic measures considered as outcomes in this study were body mass index (BMI), systolic blood pressure (SBP), and fasting blood glucose (FBG).

BMI was calculated as weight in kilograms divided by height in meters squared (kg/m2). Height and weight were measured using standardized approaches. BMI values less than 10 kg/m2 or above 80 kg/m2 were considered implausible and set to missing.19

SBP measurements were taken using standardized instruments across all surveys, with two to three consecutive readings per participant. We calculated the average SBP from all available measurements, setting implausible values (SBP less than 70 mmHg or above 270 mmHg) to missing.20

Fasting (≥8 hours) blood glucose measures were available for a subsample of women from five countries: Bangladesh, India, Mexico, Namibia, and US. In the US and Mexico, blood glucose was measured using venous blood samples, while in the other countries, capillary blood from finger pricks was used. We excluded implausible FBG values—those less than 36 mg/dl or greater than 540 mg/dl21—by setting them to missing.

We identified and excluded women with extreme cardiometabolic values, defined as values more than 5 standard deviations above or below the mean.

Further details of the sampling and measurement procedures are available from the applicable survey program websites.15–18

Reproductive history

The following reproductive factors were considered as independent exposure measures: menopausal status, age at first birth, and parity. Women were classified as premenopausal or postmenopausal. Postmenopause was defined as the absence of menstruation for 12 months or more prior to the assessment of study measures, based on the 2011 Stages of Reproductive Aging Workshop criteria.8,9 Women who reported having undergone a hysterectomy or experiencing natural menopause were also classified as postmenopausal.8 Women who had menstruated within the 12 months preceding the survey or were postpartum amenorrheic were classified as premenopausal.8 Women who had never menstruated were excluded from the analysis of the association between menopausal status and the cardiometabolic measures. Age at first birth was analyzed as a binary outcome, dichotomized into <20 years or ≥20 years. Parity was categorized into 0, 1, 2, 3, and 4 or more births. All reproductive history was self-reported.

Sociodemographic covariates

Covariates were selected based on existing literature, their availability across surveys, and considerations of parsimony.

We considered the following sociodemographic factors as potential confounders: age, education (categorized as lower than secondary, secondary, and higher than secondary education), marital status (categorized as never married, currently married and together, and ever married but currently apart), and household wealth index (categorized into five quintiles). For all countries except Mexico and the US, wealth quintiles were pre-constructed by the DHS program using factor analysis. For Mexico, we constructed wealth quintiles based on household characteristics and assets, following the DHS approach.22,23 In the US data, information on household assets was not publicly available. Therefore, we generated wealth quintiles from the family monthly poverty level index, which is a ratio of monthly family income to the Department of Health and Human Services’ poverty guidelines, specific to family size.24

The primary models also considered country income category (based on 2024–2025 World Bank classification),25 as an additional covariate. Women from Benin, Ghana, Haiti, Lesotho, Bangladesh, India, Kyrgyz, Nepal, and Tajikistan were classified as from lower-middle income countries; those from Namibia, South Africa, Mexico, Peru, and Albania as from upper-middle-income countries; and those from the United States as from a high income country.

To account for potential birth cohort effects, we divided women by 10-year intervals of calendar year at birth (1960s, 1970s, 1980s, 1990s) when available (all DHS surveys), or by subtracting women’s ages at the time of each survey from the respective survey year (Mexico and US samples). For the Nepal sample, the year of birth, originally reported in the Nepali calendar, was converted to the Gregorian calendar by subtracting 56 years. In the US sample, where the exact year of birth and interview were not publicly available, we estimated membership in birth cohort using the average survey period (2017–2020) and reported age at survey.

Statistical Analyses

Participant characteristics

Characteristics of women eligible for the study were described using medians and interquartile ranges (IQRs) for continuous variables and frequencies with 95% confidence intervals (CIs) for categorical variables.

Multilevel modeling

We pooled individual-level data from the 15 countries to create an ethnically diverse sample, organized into a three-level hierarchical structure with women nested within birth cohorts, nested within countries. Due to a smaller sample size and limited representation across birth cohorts, fasting blood glucose models used a two-level structure, with women nested within countries. Multilevel linear regression analyses were conducted to explore the associations between reproductive characteristics and cardiometabolic measures. To address violations of the normality assumption, all cardiometabolic measures were log-transformed, and the corresponding measures of association from multilevel models were back-transformed. Models estimated fixed effects for reproductive factors and included random effects to account for potential variation across country and birth cohort.

The first set of models evaluated the association between menopausal status and cardiometabolic measures, restricted to women aged 40–49 years. Next, in separate sets of models of premenopausal and postmenopausal women (age 30–49 years), we estimated associations of age at first birth and parity with the cardiometabolic outcomes. We tested for statistical interactions between menopausal status and each reproductive exposure using likelihood ratio tests (LRTs) comparing models with and without interaction terms. Adjusted models included individual-level sociodemographic covariates as fixed effects.

To assess whether associations varied by broader contextual factors, we also tested for statistical interaction between reproductive exposures and country income category using LRTs. Stratified results are presented only where significant interactions were observed.

Data harmonization and statistical analyses were conducted using the SAS programming software, version 9.4.

Sensitivity analysis

We conducted a leave-one-country-out analysis by iteratively excluding data from each country in our pooled sample and re-running the mixed-effects models on the remaining data. This was to determine whether the observed associations were influenced disproportionately by data from any single country. Additional sensitivity analyses were conducted to account for potential confounding due to medication use in subsamples with data on anti-hypertensive or anti-hyperglycemic medications.

RESULTS

Sociodemographic and reproductive characteristics

We included 413,802 non-pregnant women aged 30–49 years from 15 national demographic and health surveys conducted between 2012 (Kyrgyzstan) and 2022 (Peru and Nepal).

The majority of the study population (92.7%) was from lower-middle income countries (Table 1). The median (IQR) age was 38.0 years (34.0, 44.0) overall, 38.0 years (33.0, 42.0) for women who had not reached menopause, and 45.0 years (42.0, 48.0) for women who had reached menopause. In the total sample, about 10% had higher than secondary education, 89% were married and living with their partners, and 18% were from the highest household wealth quintile. Fourteen percent of the women had either naturally or surgically reached menopause. The median (IQR) age at first birth was 21.0 years (18.0, 24.0) for premenopausal and 19.0 years (17.0, 22.0) for postmenopausal women. About 57% of the total sample had their first birth at or after age 20, with 62% of premenopausal women and 48% of postmenopausal women falling into this category. The median parity was 3.0 births (IQR: 2.0, 4.0) in both groups. Among premenopausal women, most (36.3%, 95% CI: 36.1, 36.4) had two births, while over one-third of postmenopausal women reported four or more births (37.2%, 95% CI: 36.8, 37.6). The overall current breastfeeding prevalence was 9%, with 11% of premenopausal women breastfeeding at the time of the surveys.

Table 1.

Sociodemographic and reproductive characteristics of women participating in national surveys across 15 countries

Characteristic Percentage (95% CI) or Median (IQR)
All women aged 30–49 years (n=413,802) Premenopausal women aged 30–49 years who have given birth (n=332,569) Postmenopausal women aged 30–49 years who have given birth (n=55,788)
Sociodemographic Age (years), median 38.0 (34.0, 44.0) 38.0 (33.0, 42.0) 45.0 (42.0, 48.0)
Higher than secondary education, % 10.3 (10.2, 10.4) 10.5 (10.4, 10.6) 3.8 (3.7, 4.0)
Currently married and together, % 89.1 (89.0, 89.2) 92.2 (92.1, 92.3) 87.1 (86.8, 87.4)
Highest household wealth quintile, % 18.0 (17.8, 18.1) 18.4 (18.2, 18.5) 15.0 (14.7, 15.3)
Lower-middle income country, % 92.7 (92.6, 92.8) 93.2 (93.1, 93.3) 95.9 (95.8, 96.1)
Upper-middle income country, % 7.1 (7.1, 7.2) 6.7 (6.6, 6.8) 4.0 (3.8, 4.2)
High income country, % 0.2 (0.2, 0.2) 0.2 (0.1, 0.2) 0.1 (0.0, 0.1)
Reproductive Surgical/natural menopause, % 14.2 (14.1, 14.3) 0.0 100.0
Age at first birth (years), median 20.0 (18.0, 23.0) 21.0 (18.0, 24.0) 19.0 (17.0, 22.0)
First birth at <20 years, % 38.1 (38.0, 38.3) 37.8 (37.7, 38.0) 51.8 (51.4, 52.3)
First birth at ≥20 years, % 56.9 (56.8, 57.1) 62.2 (62.0, 62.3) 48.2 (47.7, 48.6)
Parity, median 3.0 (2.0, 4.0) 3.0 (2.0, 4.0) 3.0 (2.0, 4.0)
Nulliparous, % 4.9 (4.8, 4.9) 0.0 0.0
1 birth, % 10.1 (10.1, 10.2) 11.1 (11.0, 11.2) 8.2 (8.0, 8.4)
2 births, % 33.2 (33.1, 33.4) 36.3 (36.1, 36.4) 27.9 (27.5, 28.3)
3 births, % 24.9 (24.7, 25.0) 26.0 (25.8, 26.1) 26.7 (26.3, 27.0)
≥ 4 births, % 26.9 (26.7, 27.0) 26.6 (26.5, 26.8) 37.2 (36.8, 37.6)
Breastfeeding, % 8.7 (8.6, 8.8) 10.7 (10.6, 10.8) 0.5 (0.4, 0.6)
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Study countries include Benin, Ghana, Haiti, Lesotho, Bangladesh, India, Kyrgyz, Nepal, Tajikistan [Lower-middle income]; Namibia, South Africa, Mexico, Peru, and Albania [Upper-middle income]; and United States [High income]

Detailed characteristics of the included women, by country are provided in Supplementary Table 1.

Overall associations between reproductive factors and cardiometabolic indicators

Table 2 shows differences in cardiometabolic measures between women aged 40–49 years who have and have not experienced menopause. Being in a postmenopausal state was negatively associated with BMI (−0.22, 95% CI: −0.27, −0.17 kg/m2) and positively associated with SBP (0.35, 95% CI: 0.18, 0.52 mmHg), but showed no significant association with FBG (0.45, 95% CI: −0.66, 1.57 mg/dl) overall.

Table 2.

Mean differences (95% CI) in cardiometabolic measures among women (age 40–49 years) participating in national surveys across 15 countries, by menopausal status

Body mass index, BMI (kg/m2)
 Systolic blood pressure, SBP (mmHg)
 Fasting blood glucose, FBG (mg/dl)
Marginal mean Mean difference Marginal mean Mean difference Marginal mean Mean difference
Age-adjusted estimates
Premenopausal (ref) 26.61 (25.46, 27.80) 0.00 119.32 (117.08, 121.61) 0.00 97.35 (93.40, 101.47) 0.00
Postmenopausal 26.12 (25.00, 27.29) −0.49 (−0.54, −0.43) 119.67 (117.42, 121.96) 0.34 (0.17, 0.52) 97.73 (93.69, 101.95) 0.38 (−0.75, 1.53)
Fully-adjusted estimates
Premenopausal (ref) 26.38 (25.23, 27.59) 0.00 119.57 (117.38, 121.79) 0.00 96.48 (91.58, 101.64) 0.00
Postmenopausal 26.16 (25.02, 27.36) −0.22 (−0.27, −0.17) 119.92 (117.72, 122.15) 0.35 (0.18, 0.52) 96.93 (91.95, 102.19) 0.45 (−0.66, 1.57)
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Sample = All women 40–49 years

BMI: n = 185,466 women from all 15 study countries; adjusted for age, education, marital status, household wealth quintile, and parity

SBP: n = 154,172 women from all 15 study countries; adjusted for age, education, marital status, household wealth quintile, and parity

FBG: n = 5,025 women from 5 study countries (Namibia, India, Bangladesh, Mexico, and US); adjusted for age, education, marital status, household wealth quintile, parity, BMI, and birth cohort

BMI and SBP models include random effects for birth cohort and country; FBG models include random effects for country

Differences with P<.05 are in bold

We observed statistically significant interaction (p-interaction <0.01) by menopausal status for the associations between age at first birth and both BMI and SBP, as well as between parity and both BMI and SPB, but not for FBG. For consistency, Table 3 reports associations between age at first birth and parity with cardiometabolic outcomes stratified by menopausal status among women aged 30–49 years. In premenopausal women, a later age at first birth (≥20 years) was associated with a lower BMI (mean difference of −0.33, 95% CI: −0.36, −0.30 kg/m2) and lower SBP (mean difference of −0.59, 95% CI −0.69, −0.48 mmHg) relative to birth before age 20. Parity was positively associated with BMI for women with 1–3 births compared to nulliparous women (mean differences ranging from 0.11 to 0.14 kg/m2), but no association was observed for 4 or more births (mean difference −0.05, 95% CI: −0.15, 0.05 kg/m2). No associations were found between age at first birth or parity and fasting blood glucose in premenopausal women overall.

Table 3.

Adjusted mean differences (95% CI) in cardiometabolic measures among women (age 30–49 years) participating in national surveys across 15 countries, by reproductive history

Body mass index, BMI (kg/m2)
 Systolic blood pressure, SBP (mmHg)
 Fasting blood glucose, FBG (mg/dl)
Marginal mean Mean difference Marginal mean Mean difference Marginal mean Mean difference
Premenopausal women
Age at first birth
  <20 years (ref) 25.92 (24.92, 26.96) 0.00 116.01 (113.93, 118.12) 0.00 95.43 (90.94, 100.13) 0.00
  ≥20 years 25.59 (24.61, 26.61) −0.33 (−0.36, −0.30) 115.42 (113.35, 117.53) −0.59 (−0.69, −0.48) 94.91 (90.49, 99.56) −0.51 (−1.30, 0.29)
Parity
Nulliparous (ref) 25.46 (24.43, 26.53) 0.00 116.52 (114.52, 118.56) 0.00 94.57 (89.65, 99.76) 0.00
  1 25.59 (24.56, 26.66) 0.13 (0.02, 0.23) 115.75 (113.77, 117.77) −0.77 (−1.11, −0.44) 94.18 (89.34, 99.28) −0.39 (−2.32, 1.58)
  2 25.60 (24.57, 26.68) 0.14 (0.05, 0.24) 115.10 (113.13, 117.11) −1.42 (−1.73, −1.11) 94.32 (89.52, 99.37) −0.25 (−1.99, 1.51)
  3 25.57 (24.54, 26.65) 0.11 (0.01, 0.21) 115.08 (113.11, 117.09) −1.44 (−1.76, −1.12) 94.55 (89.74, 99.62) −0.02 (−1.79, 1.79)
  4+ 25.41 (24.38, 26.47) −0.05 (−0.15, 0.05) 114.48 (112.52, 116.48) −2.04 (−2.36, −1.72) 93.62 (88.86, 98.63) −0.95 (−2.74, 0.87)
Postmenopausal women
Age at first birth
  <20 years (ref) 26.40 (25.13, 27.74) 0.00 120.20 (117.53, 122.92) 0.00 96.49 (88.14, 105.64) 0.00
  ≥20 years 26.25 (24.99, 27.58) −0.15 (−0.23, −0.07) 119.82 (117.17, 122.53) −0.38 (−0.67, −0.08) 98.57 (90.09, 107.85) 2.08 (0.08, 4.11)
Parity
Nulliparous (ref) 25.92 (24.65, 27.26) 0.00 122.23 (119.56, 124.95) 0.00 96.49 (88.77, 104.88) 0.00
  1 26.02 (24.75, 27.35) 0.09 (−0.20, 0.39) 120.63 (118.03, 123.29) −1.60 (−2.68, −0.51) 96.23 (88.83, 104.26) −0.26 (−6.13, 6.00)
  2 26.08 (24.81, 27.41) 0.15 (−0.11, 0.42) 119.62 (117.06, 122.23) −2.61 (−3.57, −1.63) 94.34 (87.43, 101.78) −2.15 (−7.17, 3.14)
  3 26.01 (24.74, 27.34) 0.09 (−0.18, 0.35) 119.37 (116.82, 121.97) −2.86 (−3.83, −1.89) 95.35 (88.39, 102.87) −1.14 (−6.20, 4.21)
  4+ 25.86 (24.60, 27.18) −0.06 (−0.33, 0.20) 119.17 (116.63, 121.76) −3.06 (−4.01, −2.09) 94.78 (87.93, 102.16) −1.71 (−6.68, 3.54)
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Exposure =Age at first birth

BMI: n = 327,238 premenopausal and 55,156 menopausal women from all study countries except Mexico; fully adjusted for age, education, household wealth quintile, parity, and current breastfeeding status

SBP: n = 279,735 premenopausal and 44,727 menopausal women from all study countries except Mexico; fully adjusted for age, education, household wealth quintile, parity, and current breastfeeding status

FBG: n = 6,588 premenopausal and 1,334 menopausal women from Namibia, India, Bangladesh, and the U.S.; fully adjusted for age, education, household wealth quintile, parity, current breastfeeding status, BMI, and birth cohort

Exposure =Parity

BMI: n = 349,219 premenopausal and 58,122 menopausal women from all study countries; fully adjusted for age, education, marital status, household wealth quintile, and current breastfeeding status

SBP: n = 298,687 premenopausal and 47,101 menopausal women from all study countries; fully adjusted for age, education, marital status, household wealth quintile, and current breastfeeding status

FBG: n = 9,341 premenopausal and 1,652 menopausal women from Namibia, India, Bangladesh, Mexico, and the U.S.; fully adjusted for age, education, marital status, household wealth quintile, breastfeeding status, ever experience of pregnancy loss, BMI, and birth cohort

BMI and SBP models include random effects for birth cohort and country; FBG models include random effects for country

Differences with P<.05 are in bold

Among postmenopausal women, a later age at first birth (≥20 years) was associated with a lower BMI (mean difference of −0.15, 95% CI: −0.23, −0.07 kg/m2), lower systolic blood pressure (mean difference of −0.38, 95% CI −0.67, −0.08 mmHg), and higher fasting blood glucose (2.08, 95% CI: 0.08, 4.11 mg/dl). Parity was associated with a lower systolic blood pressure (SBP −3.06; 95% CI: −4.01, −2.09 mmHg comparing women with 4+ births to no births), but not BMI or blood glucose.

Associations between reproductive factors and BMI by country income category

In analyses stratified by country income category (p-interaction <0.01), the negative association between postmenopausal status and BMI was observed among women from lower-middle income countries only – findings were not significant in other income categories (Figure 1 and Supplementary Table 2a).

Figure 1. Association between menopausal status and body mass index among women (age 40–49 years) participating in national surveys across 15 countries, by country income category.

Figure 1.

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Estimates represent mean differences and 95% CIs in BMI from multilevel models accounting for country-level and birth cohort differences. The model was restricted to women aged 40–49 y (reference = premenopausal women) and adjusted for age, education, marital status, household wealth quintile, and parity. Fifteen countries were included: Benin, Ghana, Haiti, Lesotho, Bangladesh, India, Kyrgyz, Nepal, Tajikistan [Lower-middle Income]; Namibia, South Africa, Mexico, Peru, Albania [Upper-middle Income]; and United States [High Income].

Among premenopausal women, the negative association between later age at first birth and BMI was consistent across income categories, and the positive association between parity and BMI was most evident among those from upper-middle income countries. Findings in postmenopausal women were generally not statistically significant when stratified by country income category (Figure 2 and Supplementary Table 2b).

Figure 2. Associations between reproductive history and body mass index among women (age 30–49 years) participating in national surveys across 15 countries, by menopausal status and country income category.

Figure 2.

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Estimates represent mean differences and 95% CIs from multilevel models accounting for country-level and birth cohort differences. For age at first birth (reference = 13–19 y), models were adjusted for age, education, household wealth quintile, parity, and current breastfeeding status (panel A). For parity (reference = nulliparous), models were adjusted for age, education, marital status, household wealth quintile, and current breastfeeding status (panel B). Fifteen countries were included: Benin, Ghana, Haiti, Lesotho, Bangladesh, India, Kyrgyz, Nepal, Tajikistan [Lower-middle Income]; Namibia, South Africa, Mexico, Peru, Albania [Upper-middle Income]; and United States [High Income].

Sensitivity analyses

Sensitivity analyses using a leave-one-country-out approach (Supplementary Tables 3–17) generally supported the main findings, with two exceptions among postmenopausal women: the association between age at first birth and SBP became non-significant when India was excluded (Supplementary Table 14) and the association with FBG became non-significant when Bangladesh was excluded (Supplementary Table 16).

In sub-samples with medication data, adjusting for medication use did not meaningfully alter results. In the menopausal status–SBP model, adjustment for antihypertensive medication use slightly attenuated the estimate, but the direction and statistical significance remained unchanged [0.34 (0.17, 0.52) vs. 0.29 (0.11, 0.47)] (Supplementary Table 18). A similar pattern was observed in the age at first birth–SBP model among postmenopausal women [−0.38 (−0.67, −0.09) vs. −0.33 (−0.63, −0.03)].

DISCUSSION

Our study examined the relationships between reproductive history and cardiometabolic indicators in a diverse global sample of women. We found timing of first birth, parity, and menopausal status to be associated with various cardiometabolic indicators, including BMI and blood pressure. Notably, this is the first study to explore these associations in a predominantly reproductive-age population (86% not having reached menopause) across multiple countries, providing unique insights into the interplay between reproductive history and cardiometabolic health in younger women.

Menopause is a significant transition involving hormonal and cardiometabolic changes in women.9,26 Departing from prior data showing that menopause increases cardiometabolic risks,11,27 our findings suggest that menopausal status may not be a major determinant of these changes in women under the age of 50. Interestingly, a negative association between menopause and BMI (primarily in women from lower-middle income countries), and a positive association between menopause and SBP were observed. Our study included younger postmenopausal women (median age 45), likely in early postmenopause (within 5–8 years),9 which contrasts with studies on older women and may explain our differing results. Additionally, our premenopausal group may have included women in the menopausal transition, potentially masking associations. Research suggests that cardiometabolic risks increase during the menopausal transition but may stabilize or decrease postmenopause, suggesting that age at menopause and time since menopause may be more important indicators of cardiometabolic health than menopause status itself.28 Nevertheless, our inclusion of a relatively young, comparable age group of premenopausal and postmenopausal women indicates that our findings may reflect the true association between menopause and cardiometabolic health, rather than the effects of aging as seen in other studies.

Age at first birth has been associated with better cardiometabolic health and lower cardiovascular events.4,29 Multiple potential mechanisms have been proposed, including fewer pregnancies, lower risk of pregnancy-related complications, better socioeconomic status, and greater control over lifestyle behaviors among women who have children later. Our analyses replicated the inverse association between age at first birth and cardiometabolic disease. Prior to menopause, women who had a first delivery at or after age 20, compared to those who gave birth earlier, showed lower BMI and systolic blood pressure, indicating potential protective effects of later childbearing. After menopause, the inverse association between age at first birth and BMI and blood pressure persisted, but an association with higher fasting blood glucose emerged. This suggests that the cardiometabolic benefits of later childbirth may diminish over time, potentially due to changes related to ovarian or chronological aging. Notably, this protective effect was consistent across country income categories, indicating that age at first birth is an important factor for cardiometabolic health across different populations.

Lower systolic blood pressure in multiparous women compared to nulliparous women may be attributed to a sustained drop in blood pressure during pregnancy and following childbirth, with successive pregnancies leading to further reductions over time.30 In our study, we found this association held true regardless of menopausal status. A Norwegian cohort study supports this observation, showing persistently lower blood pressure in parous women compared to nulliparous women, even at age 50.31 In contrast, other studies have reported no significant association,32 non-linear associations,33 or differential associations by age, with positive associations in older women.34

Among premenopausal women, higher parity was associated with higher BMI, particularly among women from upper-middle income countries, likely due to ongoing hormonal changes, postpartum weight retention, and lifestyle factors related to childbearing. In contrast, we found no significant association between parity and BMI in postmenopausal women, possibly due to hormonal stabilization, aging, and the time since last pregnancy, which may lessen parity’s impact on BMI. Other studies6,32,35 have found parity to be associated with higher BMI in both pre- and post-menopausal/older women, with some noting stronger associations in younger or premenopausal women.32

This study is one of the few to comprehensively examine the associations between reproductive factors and cardiometabolic health in a large, ethnically diverse sample of women across multiple countries. While our study offers valuable insights, it is not without limitations. First, pooling data from various population-based surveys may have introduced inconsistencies due to differing data collection methods across countries, though all surveys followed similar standardized protocols. Second, reproductive factors were self-reported, potentially introducing bias. Additionally, we lacked information on age at menopause and time since menopause, which have been shown to be relevant for women’s cardiometabolic health. Lastly, the cross-sectional nature of the data limits our ability to draw causal inferences—future longitudinal studies are needed to confirm these associations and explore the underlying mechanisms.

CONCLUSION

In this ethnically diverse multi-country population of women aged 30–49 years, we found complex relationships between reproductive history and cardiometabolic health. A later age at first birth appeared to be a protective factor, associated with lower body mass index and blood pressure, though its benefits seem to diminish postmenopause. Parity showed varied associations—higher parity was associated with lower blood pressure in all women but higher body mass index in premenopausal women. These findings suggest that reproductive history influences cardiometabolic health differently across the life course, emphasizing its importance in understanding women’s cardiometabolic health. Future longitudinal studies are needed to investigate these associations further.

Supplementary Material

Supp1

Supplementary data

Supplementary data are available at Journal of Epidemiology and Community Health online.

KEY MESSAGES.

  • What is already known: Emerging evidence suggests reproductive factors are linked to cardiometabolic outcomes, with data primarily from homogeneous populations in high-income countries.

  • What this study adds: This study uniquely addresses the evidence gap from LMICs and diverse populations by examining associations across ethnically diverse women from 15 countries spanning 5 continents. We found that having a first birth at age ≥20 years was associated with lower BMI and systolic blood pressure, regardless of menopausal status, while higher parity was associated with lower systolic blood pressure among all women, but higher BMI in premenopausal women.

  • How this study might affect research, practice, or policy: Our findings support the hypothesis that reproductive history—specifically the timing of first birth, parity, and menopausal status—may contribute to the cardiometabolic health of women across diverse global settings. Understanding this relationship has important implications for cardiovascular disease risk in women.

Funding

WQ was supported by the Laney Graduate School, Emory University, and the Emory Global Diabetes Research Center of the Woodruff Health Sciences Center at Emory University. KMVN and SAP receive funding from the National Heart, Lung and Blood Institute of the National Institutes of Health under grant number P01HL154996. The funding sources had no role in the conceptualization of the study, data analysis and interpretation, writing of the manuscript, or the decision to publish.

Footnotes

DECLARATIONS

Conflict of interest

None declared.

Ethics approval

Ethics approval was not required for this study since the data were supplied in an anonymized format for analysis.

Data availability

Data are publicly available from the following sources: the Demographic and Health Surveys Program (www.dhsprogram.com; available upon request); the Peru National Institute of Statistics and Informatics (Spanish acronym INEI, https://proyectos.inei.gob.pe/endes/); the Mexican National Institute of Public Health (Spanish acronym INSP, https://ensanut.insp.mx/index.php); and the U.S. National Center for Health Statistics (https://www.cdc.gov/nchs/nhanes/).

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Associated Data

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

Supplementary Materials

Supp1
NIHMS2110388-supplement-Supp1.docx (125.3KB, docx)

Data Availability Statement

Data are publicly available from the following sources: the Demographic and Health Surveys Program (www.dhsprogram.com; available upon request); the Peru National Institute of Statistics and Informatics (Spanish acronym INEI, https://proyectos.inei.gob.pe/endes/); the Mexican National Institute of Public Health (Spanish acronym INSP, https://ensanut.insp.mx/index.php); and the U.S. National Center for Health Statistics (https://www.cdc.gov/nchs/nhanes/).

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