Abstract
Background
China has undergone a significant socioeconomic transformation over the past few decades due to the implementation of family planning policies. These societal changes have resulted in an increased susceptibility among females to developing cardiometabolic diseases (CMD). Unfortunately, studies investigating the correlation between family planning policies in China and the incidence of CMD remain scarce.
Methods
Data from 1,226 females, aged 30 years or older with ≥ 1 live birth, undergoing routine physical examinations between January 2018 and December 2021 were collected, and they were grouped by number of live births 1, 2, and ≥ 3. A binary logistic regression model was employed to examine the association between the number of live births with CMD. Furthermore, the subgroup analysis was performed to elucidate the impact of the implementation of family planning policies with CMD.
Results
Women with live births ≥ 3 tended to be older, had higher gravidities, a greater proportion of central obesity, general obesity, hypertension, and dyslipidemia (all P < 0.05). Across the three groups (live birth = 1, =2 and ≥ 3), the odds ratio (OR) with 95% CI for obesity were: 1.00, 3.32 (2.36–4.69), and 5.73 (3.79–8.68); for dyslipidemia were: 1.00, 1.75 (1.29–2.39), and 2.02 (1.38–2.94); and for CMD were: 1.00, 1.91 (1.44–2.54), and 2.15 (1.46–3.15), respectively (all P < 0.05). In addition, based on the different periods of the childbearing policy in China, a subgroup analysis (where age was divided into ≤ 45, 45–65, and ≥ 65 years old) found that each additional live birth increased the prevalence risk of obesity and CMD in the younger generations, while hypertension and dyslipidemia in the elder generation.
Conclusions
Higher live births are positively associated with the prevalence of CMD among women in Southwest China. Moreover, giving birth after the implementation of the one-child policy tends to have a higher risk of developing CMD.
Supplementary Information
The online version contains supplementary material available at 10.1186/s12902-024-01706-1.
Keywords: Live births, Cardiometabolic disease, Family planning policies, China
Introduction
Cardiovascular diseases (CVDs) are the leading cause of death worldwide, with no signs of decreasing [1]. Metabolic syndrome (MetS) is a cluster of metabolically related cardiovascular risk factors [2–4]. Effective management of MetS has been receiving much attention as it is associated with a decreased risk of developing cardiometabolic disease (CMD) as well as an overall decrease in mortality. [5–7]. From 1991 to 1995 to 2011–2021, the prevalence of MetS risk factors in China has been increasing, with a prevalence from 8.8 to 29.3%, higher in women (7.9–30.7%) than in men (9.4–27.2%) [8]. Furthermore, studies have shown that MetS and CMD are projected to keep increasing simultaneously [9, 10], thus, early detection and promptly managing them is of utmost importance.
Family structure, relationships, and lifestyle have significantly shifted in China over the last 50 years. The one-child policy was implemented in 1979 to alleviate population growth and improve the health and welfare of women and children [11]. Unfortunately, in 2000, China entered a phase of persistent low fertility levels [12] leading to an aging population, a shortage of labor, and an imbalance of the sex ratio at birth. Thus, in October 2015, a universal two-child policy was implemented [13]. However, China’s fertility rate continued to decline, dropping to as low as 6.77 births per 1,000 women of childbearing age, resulting in the implementation of the three-child policy in 2021 [14].
Since the implementation of such family planning policies, studies regarding the changes in family structure with the incidence of CMD remain scarce. Therefore, in this study, we aimed to evaluate the impact of the number of live births with CMD in Chinese women.
Methods
Study population
A retrospective analysis was performed on 1,364 females undergoing routine health examinations at the Health Management Center in the First Affiliated Hospital of Chongqing Medical University from January 2018 to December 2021 (refer to Fig. 1).
Fig. 1.
Flow chart of the study population selection
Considering that (1) Chinese women are expected to adhere to a high-calorie, high-protein diet during the perinatal or lactation period [15]; (2) The protective effect of estrogen levels on cardiovascular diseases in women results in lower incidence among young women without a history of pregnancy [16]; hence, to prevent those possible biases in this study, we only included women: (1) over 30 years old with a history of previous pregnancy; (2) able to provide medical histories with medical documents as evidence. A total of 138 females were excluded, due to CMD and its components secondary to other pathologies (n = 19), no live births (n = 57), pregnancy and/or breastfeeding within the past one year (n = 26), and incomplete biochemistry testing or missing data of live births (n = 36).
Informed consents were obtained from all participants. This study was also approved by the ethics committee of the First Affiliated Hospital of Chongqing Medical University.
Definition of terms
Low income refers to a per capita monthly income that is below 1,000 RMB. Being well-educated indicates an individual who has completed at least a high school education or possesses a higher level of educational attainment. The definition of “insufficient intake” pertained to the consumption of vegetables, fruit, meat, and eggs less than three times a week, and each time with the daily minimum dosage recommended by the Chinese dietary guidelines [17]. Physical inactivity denoted engaging in less than two hours of physical activity per week.
Live birth was defined as the number of biological live childbirths plus the number of stillbirths (the birth of a fetus that died in the mother’s uterus after 20 weeks of gestation). The loss of an embryo or fetus before the 20th week of pregnancy is defined as miscarriage [18].
Hypertension was defined as the presence of at least one of the following criteria: (1) previously diagnosed with hypertension in secondary or above medical institutions, on or free from anti-hypertensive drugs; (2) having systolic blood pressure (SBP) ≥ 140mmHg, (3) having diastolic blood pressure (DBP) ≥ 90mmHg [19].
Type 2 diabetes mellitus (T2DM) was defined as the presence of at least one of the following criteria: (1) Fasting plasma glucose (FPG) level of ≥ 7.0mmol/L, (2) a 2-hour plasma glucose value in a 75 g oral glucose tolerance test of ≥ 11.1mmol/L, (3) pharmacologically treated with glucose-lowering medications because of T2DM [20].
Obesity was defined as body mass index (BMI) ≥ 28.0 kg/m2 (general obesity) and/or waist circumference (WC) ≥ 80.0 cm (central obesity) [21].
Dyslipidemia was defined as the presence of at least one of the following criteria: (1) total cholesterol (TC) > 5.7 mmol/L; (2) triglycerides (TG) > 1.7 mmol/L; (3) low-density lipoprotein cholesterol (LDL-C) > 3.37 mmol/L; (4) pharmacologically treated with lipid-lowering medications [22].
Metabolic syndrome (Mets) was defined as the presence of any three of the following five risk factors [23]: (1) Elevated SBP of ≥ 130 mmHg and/or DBP of ≥ 85 mmHg, or previous medical history of antihypertensive drug treatment use; (2) Elevated waist circumference ≥ 80 cm for all ethnicities; (3) Elevated triglycerides (TG) of ≥ 1.7 mmol/L, or drug treatment for dyslipidemia; (4) Reduced high-density lipoprotein cholesterol (HDL-C) < 1.3mmol/L, or drug treatment for lipid abnormality; 5) Elevated fasting glucose ≥ 5.6 mmol/L, or drug treatment for elevated glucose.
Cardiometabolic disease (CMD) refers to any one of the following: MetS, obesity, hypertension, T2DM, stroke, and event of CVD [24].
Data collection
The demographic data, lifestyle habits, reproductive factors, pregnancy complications, and comorbidities were collected through face-to-face questionnaire surveys or by utilizing self-mobile phone scan code answer sheets. The physical examinations, laboratory tests, and echocardiography were conducted by proficient medical practitioners.
Blood pressure was measured at the right brachial artery in a calm seated position using an automatic sphygmomanometer, noted as the average of three or more measurements. Height and body weight were measured with the individual wearing light-weight clothes and no shoes. BMI was calculated by dividing weight (kg) by height (m2). Waist circumference was measured at the midway level between the iliac crest and costal margin.
Blood test: Blood samples were taken in the morning, after a fasting period of at least twelve hours, to determine FPG, total cholesterol (TC), TG, high-density lipoprotein cholesterol (HDL-C), and low-density lipoprotein cholesterol (LDL-C). The FPG and lipid profiles were analyzed by colorimetric enzymatic spectrophotometry using the Cobas E602 analyzer from Roche Diagnostics, Rotkreuz, Switzerland.
Echocardiographic data acquisition and analysis was performed using a GE 95 Echo system with an M5S transducer (GE Vingmed Ultrasound, Horten, Norway). Echocardiographic images were recorded by an experienced sonographer.
Outcomes
The primary outcome of this study was an association of the number of live births with CMD and its components.
Since studies regarding the changes in childbirth policy with cardiometabolic risk factors are limited, therefore, we did a subgroup analysis by dividing the study population into three groups based on the different time period of the various childbearing policy (age ≤ 45 years old: China entered a phase of persistently low fertility levels and enforcement of two or more child policy; age 45–65 years old: during the implementation of one-child policy; age ≥ 65 years old: multiparous was allowed) [25].
Statistical analysis
Continuous variables with normal distribution were expressed as mean ± standard deviation (SD), while skewed distribution were expressed as median and interquartile range (25 − 75%), and the differences between groups were compared using one-way analysis of variance (ANOVA) test if the variance was uniformed; otherwise the Kruskal-Wallis test was used. Categorical variables were expressed by a number of cases and percentages, and the differences between groups were compared by the Pearson χ² test. The Shapiro-Wilk test was applied to test the normal distribution of values.
The binary logistic regression model was employed to determine the relationship between live births and hypertension, T2DM, obesity, dyslipidemia, MetS, and CMD. These models were adjusted for disease-related variables, and each odds ratio (OR) value along with its 95% confidence interval (CI) was computed. We initially performed univariate analysis to identify factors influencing CMD in the baseline data (P < 0.05), and subsequently included them for multivariate regression analysis. Furthermore, considering the close association of CMD with age cohorts, the subgroup analysis was calculated based on the time of the implementation of the family planning policy.
Data were analyzed by using SPSS version 25.0 (IBM, Armonk, NY, USA), and GraphPad Prism 8.4.3 (GraphPad Software, Inc., San Diego, CA, USA) was applied for the figures. All the statistical tests were double-tailed, and the significance level was set at P < 0.05.
Results
From January 2018 to December 2021, a total of 1,226 female participants (ranging in age from 31 to 90 years, with a mean age of 52.77 ± 12.11 years) were enrolled in this study. The overall distribution of live births was illustrated in Fig. 2. In this study, the majority of live births were observed as two (38.1%), followed by one (35.1%) and three (14.0%). Women below the age of 45 and those between the ages of 45–65 predominantly had one or two live births, while women above the age of 65 mainly experienced three or more live births.
Fig. 2.
The distribution of live births among women in the overall population (a), and in the three generations (b)
The baseline characteristics and laboratory parameters were presented in Tables 1 and 2 respectively. Women with three or more live births tended to be older, had reduced sleep duration, were menopausal, and had higher gravidities. Additionally, they exhibited lower weight, shorter height, larger waist circumference, elevated SBP, and lower heart rate. In terms of laboratory parameters and echocardiography findings, they demonstrated higher levels of serum creatinine, TC, LDL-C, and glucose; as well as thicker intraventricular septum (all P < 0.05).
Table 1.
Baseline characteristics according to number of live births
| Baseline Characteristics | Overall (n = 1,226) |
Number of live births | P-value | ||
|---|---|---|---|---|---|
| 1 (n = 430) | 2 (n = 467) | ≥ 3 (n = 329) | |||
| Demographics | |||||
| Enrollment age (years) | 52.77 ± 12.11 | 47.45 ± 8.16 | 50.15 ± 9.93 | 63.45 ± 12.60 | < 0.001 |
| Minority ethnicity (n%) | 17 (1.4) | 4 (0.9) | 9 (1.9) | 4 (1.2) | 0.662 |
| Rural residents (n%) | 377 (30.8) | 134 (31.2) | 138 (29.6) | 105 (31.9) | 0.756 |
| Married (n%) | 1150 (93.8) | 424 (98.6) | 445 (95.3) | 281 (85.4) | < 0.001 |
| CVD family history (n%) | 242 (19.7) | 99 (23.0) | 87 (18.6) | 56 (17.0) | 0.034 |
| Low income (n%) | 342 (27.9) | 126 (29.3) | 114 (24.4) | 102 (31.0) | 0.090 |
| Well educated (n%) | 54 (4.4) | 34 (7.9) | 18 (3.9) | 2 (0.6) | < 0.001 |
| Lifestyle habits | |||||
| Smoking, n% | 53 (4.3) | 34 (7.9) | 10 (2.1) | 9 (2.7) | < 0.001 |
| Alcohol intake, n% | 67 (5.5) | 36 (8.4) | 14 (3.0) | 17 (5.2) | 0.030 |
| Insufficient vegetables intakea (n%) | 56 (5.1) | 21 (5.5) | 20 (4.8) | 15 (5.0) | 0.906 |
| Insufficient fruits intakea (n%) | 143 (13.1) | 53 (13.9) | 55 (13.3) | 35 (11.7) | 0.692 |
| Insufficient meat intakea (n%) | 52 (4.8) | 15 (3.9) | 21 (5.1) | 16 (5.4) | 0.640 |
| Insufficient eggs intakea (n%) | 131 (12.0) | 49 (12.9) | 45 (10.9) | 37 (12.4) | 0.666 |
| Milk intakea (n%) | 402 (36.8) | 124 (32.6) | 154 (37.3) | 124 (41.6) | 0.054 |
| Physical inactivitya (n%) | 37 (3.4) | 14 (3.7) | 13 (3.1) | 10 (3.4) | 0.916 |
| Daily sleep durationa (hours) | 7.41 ± 2.31 | 7.52 ± 2.06 | 7.60 ± 2.51 | 7.00 ± 2.29 | 0.001 |
| Reproductive factors | |||||
| Age of menarche (years) | 14.55 ± 2.08 | 13.75 ± 1.59 | 14.56 ± 1.98 | 15.60 ± 2.33 | < 0.001 |
| Number of gravidities | 3 (3–5) | 3 (2–4) | 3 (2–4) | 5 (4–6) | < 0.001 |
| OCT history (n%) | 78 (6.4) | 32 (7.4) | 32 (6.9) | 14 (4.3) | 0.084 |
| HRT history (n%) | 48 (3.9) | 24 (5.6) | 12 (2.6) | 12 (3.6) | 0.130 |
| Number of miscarriages | 1 (0–3) | 2 (1–3) | 1 (0–2) | 1 (0–2) | < 0.001 |
| Menopausal status (n%) | 590 (48.1) | 137 (31.9) | 199 (42.6) | 254 (77.2) | < 0.001 |
| Age of menopauseb (years) | 48.22 ± 4.09 | 48.47 ± 3.58 | 48.29 ± 3.84 | 48.03 ± 4.53 | 0.563 |
| Pregnancy complications | |||||
| Gestational hypertensionc (n%) | 60 (6.6) | 37 (9.5) | 21 (5.3) | 2 (1.7) | 0.004 |
| Gestational diabetesc (n%) | 81 (9.0) | 47 (12.0) | 29 (7.3) | 5 (4.2) | 0.011 |
| Preeclampsiac (n%) | 41 (4.5) | 25 (6.4) | 15 (3.8) | 1 (0.8) | 0.025 |
Abbreviations: CVD Cardiovascular disease, OCT Oral contraceptive therapy, HRT Hormone replacement therapy
a A data of 135 individuals were missing among those variables due to no response or inaccuracy data, with 70, 230, and 234 remaining in each group respectively
b A data of 636 individuals were missing due to non-menopausal status, with 137, 199, and 254 remaining in each group respectively
c The absence of perinatal examinations in previous pregnancies resulted in a data loss of 321 individuals among those variables, leaving 391, 395, and 119 remaining in each respective group
Table 2.
Physical examinations and tests grouped by number of live births
| Examinations and tests | Overall (n = 1,226) |
Number of live births | P-value | ||
|---|---|---|---|---|---|
| 1 (n = 430) | 2 (n = 467) | ≥ 3 (n = 329) | |||
| Physical examinations | |||||
| Weight (kg) | 56.95 ± 8.65 | 57.90 ± 7.86 | 57.77 ± 8.43 | 54.56 ± 9.50 | < 0.001 |
| Height (cm) | 153.73 ± 6.48 | 156.49 ± 5.57 | 153.74 ± 5.93 | 150.05 ± 6.52 | < 0.001 |
| WC (cm) | 77.43 ± 8.74 | 75.06 ± 6.73 | 78.23 ± 8.19 | 79.38 ± 10.92 | 0.001 |
| BMI (kg/m2) | 24.07 ± 3.18 | 23.64 ± 2.94 | 24.41 ± 3.12 | 24.17 ± 3.50 | 0.001 |
| Heart rate (bpm) | 84.18 ± 12.52 | 85.64 ± 12.81 | 83.69 ± 12.29 | 82.98 ± 12.35 | 0.008 |
| SBP (mmHg) | 128.72 ± 19.72 | 124.37 ± 17.63 | 126.87 ± 18.32 | 137.05 ± 21.66 | < 0.001 |
| DBP (mmHg) | 75.94 ± 11.21 | 75.53 ± 10.96 | 75.93 ± 11.04 | 76.48 ± 11.79 | 0.511 |
| Laboratory parameters | |||||
| Serum creatinine (mmol/L) | 62.90 ± 17.61 | 59.95 ± 17.54 | 62.40 ± 13.01 | 67.45 ± 21.97 | < 0.001 |
| CCR (ml/min) | 87.25 ± 28.73 | 97.60 ± 26.07 | 90.53 ± 27.09 | 69.09 ± 25.79 | < 0.001 |
| Triglycerides (mmol/L) | 1.18 ± 0.94 | 1.17 ± 0.96 | 1.15 ± 1.00 | 1.21 ± 0.82 | 0.654 |
| TC (mmol/L) | 4.96 ± 1.01 | 4.68 ± 0.68 | 5.00 ± 1.08 | 5.28 ± 1.15 | < 0.001 |
| HDL-C (mmol/L) | 1.59 ± 0.39 | 1.59 ± 0.31 | 1.59 ± 0.44 | 1.59 ± 0.42 | 0.958 |
| LDL-C (mmol/L) | 3.03 ± 0.80 | 2.83 ± 0.59 | 3.05 ± 0.79 | 3.25 ± 0.97 | < 0.001 |
| Glucose (mmol/L) | 5.67 ± 1.51 | 5.44 ± 1.24 | 5.56 ± 1.20 | 6.11 ± 2.05 | < 0.001 |
| Echocardiography | |||||
| Right atrium (mm) | 30.49 ± 3.11 | 30.55 ± 3.43 | 30.44 ± 2.84 | 30.51 ± 3.03 | 0.864 |
| Right ventricle (mm) | 18.21 ± 2.69 | 18.35 ± 2.22 | 18.23 ± 3.36 | 18.02 ± 2.12 | 0.237 |
| Left atrium (mm) | 27.32 ± 2.98 | 27.35 ± 2.59 | 27.13 ± 3.04 | 27.57 ± 3.34 | 0.121 |
| Left ventricle (mm) | 45.57 ± 3.34 | 45.65 ± 3.05 | 45.51 ± 3.14 | 45.57 ± 3.94 | 0.817 |
| IVS (mm) | 9.70 ± 0.97 | 9.59 ± 0.85 | 9.66 ± 0.93 | 9.91 ± 1.12 | < 0.001 |
| Ejection fraction (%) | 63.24 ± 5.26 | 62.71 ± 5.78 | 63.88 ± 5.12 | 63.02 ± 4.65 | 0.003 |
Abbreviations: WC Waist circumference, BMI Body mass index, SBP Systolic blood pressure, DBP Diastolic blood pressure, CCR Creatinine clearance, TC Total cholesterol, HDL-C High density lipoprotein cholesterol, LDL-C Low density lipoprotein cholesterol, IVS Intraventricular septum
Meanwhile, women with only one live birth were more likely to be married and well-educated, engage in smoking or alcohol consumption. They also had a higher likelihood of having a family history of CVD and experiencing miscarriages. These individuals experienced menarche at an earlier age. However, they reported slightly increased rates of pregnancy complications. Additionally, they presented with a lower BMI and higher creatinine clearance levels, yet a slightly reduced cardiac ejection fraction (all P < 0.05). However, the three groups did not exhibit any significant differences in terms of ethnicity, rural residency, income, diets, physical activity, as well as levels of DBP, triglycerides, HDL-C, or heart chamber sizes (all P > 0.05).
As shown in Table 3, among the three groups (live birth = 1, =2, ≥ 3), the higher the number of live births, the greater the proportion of women presented with hypertension (22.8% vs. 24.8% vs. 45.0%), general obesity (8.4% vs. 12.8% vs. 13.1%), central obesity (12.3% vs. 33.2% vs. 43.8%), dyslipidemia (21.6% vs. 35.3% vs. 49.2%), MetS (12.8% vs. 14.6% vs. 21.9%) and CMD (45.3% vs. 63.8% vs. 78.4%), but there was no difference in T2DM.
Table 3.
CMD and its components grouped by number of live births
| Risk Factors | Overall (n = 1,226) |
Number of live births | P-value | ||
|---|---|---|---|---|---|
| 1 (n = 430) | 2 (n = 467) | ≥ 3 (n = 329) | |||
| Hypertension (n%) | 362 (29.5) | 98 (22.8) | 116 (24.8) | 148 (45.0) | < 0.001 |
| T2DM (n%) | 95 (7.7) | 37 (8.6) | 29 (6.2) | 29 (8.8) | 0.981 |
| Obesity (n%) | 300 (24.5) | 75 (17.4) | 137 (29.3) | 88 (26.7) | < 0.001 |
| General Obesity (n%) | 139 (11.3) | 36 (8.4) | 60 (12.8) | 43 (13.1) | 0.031 |
| Central Obesity (n%) | 352 (28.7) | 53 (12.3) | 155 (33.2) | 144 (43.8) | < 0.001 |
| Dyslipidemia (n%) | 420 (34.3) | 93 (21.6) | 165 (35.3) | 162 (49.2) | < 0.001 |
| MetS (n%) | 195 (15.9) | 55 (12.8) | 68 (14.6) | 72 (21.9) | 0.001 |
| CMD (n%) | 751 (61.3) | 195 (45.3) | 298 (63.8) | 258 (78.4) | < 0.001 |
Abbreviations: T2DM Type 2 diabetes mellitus, MetS Metabolic syndrome, CMD Cardiometabolic disease
As depicted in Fig. 3, we performed a multivariate logistic regression analysis to confirm the relationship between the risk factors of this cohort study and the risk of developing CMD. The final analysis showed that live births, age, marital status, CVD family history, low income, educational level, smoking, number of miscarriages, and menopausal status were statistically significant (all P < 0.05). Following multivariate adjustments, as presented in Table 4, the binary logistic regression model revealed that women with live birth = 2 and live births ≥ 3 exhibited a significantly higher prevalence risk for obesity, dyslipidemia, and CMD when compared to those with live birth = 1. In detail, across the three groups, the OR with 95% CI for obesity were: 1.00 (reference), 3.32 (2.36–4.69), and 5.73 (3.79–8.68); for dyslipidemia were: 1.00 (reference), 1.75 (1.29–2.39), and 2.02 (1.38–2.94); and for CMD were: 1.00 (reference), 1.91 (1.44–2.54), and 2.15 (1.46–3.15), respectively (all P < 0.05). However, the risks were not significantly different in hypertension, T2DM, or MetS among the three groups.
Fig. 3.
Forest plot of multivariable binary logistic regression model between CMD and risk factors
Table 4.
The association between live births with CMD and its components
| Diseases | Crude | P-value | Model 1a | P-value | Model 2b | P-value |
|---|---|---|---|---|---|---|
| PR (95% CI) | PR (95% CI) | PR (95% CI) | ||||
| Hypertension | ||||||
| Live birth = 1 | 1.00 | 1.00 | 1.00 | 1.00 | ||
| Live birth = 2 | 1.12 (0.82–1.52) | 0.472 | 0.92 (0.66–1.26) | 0.593 | 0.91 (0.66–1.27) | 0.587 |
| Live birth ≥ 3 | 2.77 (2.03–3.79) | < 0.001 | 0.99 (0.67–1.46) | 0.957 | 1.04 (0.70–1.54) | 0.858 |
| Pfor trend | < 0.001 | 0.905 | 0.919 | |||
| T2DM | ||||||
| Live birth = 1 | 1.00 | 1.00 | 1.00 | 1.00 | 1.00 | |
| Live birth = 2 | 0.70 (0.43–1.17) | 0.172 | 0.56 (0.33–0.95) | 0.030c | 0.64 (0.38–1.10) | 0.105 |
| Live birth ≥ 3 | 1.03 (0.62–1.71) | 0.919 | 0.35 (0.18–0.68) | 0.002c | 0.48 (0.25–0.95) | 0.034c |
| Pfor trend | 0.981 | 0.001c | 0.028c | |||
| Obesity | ||||||
| Live birth = 1 | 1.00 | 1.00 | 1.00 | 1.00 | 1.00 | |
| Live birth = 2 | 3.34 (2.39–4.65) | < 0.001 | 3.43 (2.45–4.79) | < 0.001 | 3.32 (2.36–4.69) | < 0.001 |
| Live birth ≥ 3 | 4.80 (3.39–6.81) | < 0.001 | 5.59 (3.74–8.35) | < 0.001 | 5.73 (3.79–8.68) | < 0.001 |
| Pfor trend | < 0.001 | < 0.001 | < 0.001 | |||
| Dyslipidemia | ||||||
| Live birth = 1 | 1.00 | 1.00 | 1.00 | 1.00 | 1.00 | |
| Live birth = 2 | 1.98 (1.47–2.67) | < 0.001 | 1.81 (1.34–2.45) | < 0.001 | 1.75 (1.29–2.39) | < 0.001 |
| Live birth ≥ 3 | 3.52 (2.57–4.82) | < 0.001 | 2.04 (1.41–2.94) | < 0.001 | 2.02 (1.38–2.94) | < 0.001 |
| Pfor trend | < 0.001 | < 0.001 | < 0.001 | |||
| MetS | ||||||
| Live birth = 1 | 1.00 | 1.00 | 1.00 | 1.00 | 1.00 | |
| Live birth = 2 | 1.16 (0.79–1.70) | 0.442 | 0.99 (0.67–1.46) | 0.949 | 1.27 (0.83–1.95) | 0.267 |
| Live birth ≥ 3 | 1.91 (1.30–2.81) | 0.001 | 0.81 (0.50–1.30) | 0.386 | 1.64 (0.89–2.43) | 0.128 |
| Pfor trend | 0.001 | 0.410 | 0.124 | |||
| CMD | ||||||
| Live birth = 1 | 1.00 | 1.00 | 1.00 | 1.00 | 1.00 | |
| Live birth = 2 | 2.13 (1.63–2.78) | < 0.001 | 1.93 (1.47–2.54) | < 0.001 | 1.91 (1.44–2.54) | < 0.001 |
| Live birth ≥ 3 | 4.38 (3.17–6.06) | < 0.001 | 2.12 (1.47–3.06) | < 0.001 | 2.15 (1.46–3.15) | < 0.001 |
| Pfor trend | < 0.001 | < 0.001 | 0.001 |
Abbreviations: OR Odds ratio, CI Confidence interval, T2DM Type 2 diabetes mellitus, MetS Metabolic syndrome, CMD Cardiometabolic disease
Logistic regression analysis was utilized in those models
a Model 1 was adjusted by enrollment age (continuous variable)
b Model 2 was adjusted by Model 1 + minority ethnicity, married, CVD family history, lower income, smoking, alcohol intake, number of miscarriages (continuous variable), and menopausal status among baseline variables
c Likely exhibited over-adjustment, as the crude analysis failed to demonstrate statistical significance
As for subgroup analysis, after adjusting for multiple variables, women in the second generation (aged 45–65 years) and third generation (aged ≤ 45 years) were found to have a significantly increased risk of obesity and CMD (all P < 0.05, and Pfor interaction < 0.05); however, this association was not observed in the first (aged ≥ 65 years) generation. Moreover, women in the first and second generations showed a tendency towards a higher risk of dyslipidemia with an increasing number of live births. Furthermore, as the number of live births increased, an increased risk of hypertension was observed solely in the first-generation women, while a distinct trend towards an elevated risk of MetS was only seen in third-generation women (refer to Fig. 4 and Supplement Table 1).
Fig. 4.
The association between live births with CMD and its components by age sub-group analysis
Discussion
In the present study, our major finding was that women with higher live birth pregnancies were associated with a higher prevalence risk of obesity, dyslipidemia, and CMD. Moreover, subgroup analysis revealed that in comparison to having only one live birth, each additional live birth was associated with increased susceptibility to obesity and CMD among younger generations, while hypertension and dyslipidemia were more prevalent among the elder generation.
Incidence and prevalence of MetS and CMD in China
MetS and CMD are considered to be a worldwide epidemic. As their incidence continues to increase, causing a severe economic burden to society. In China, there has been a rising trend of cardiometabolic risk factors among adults in the past decades. For example: (1) Overweight and obesity significantly increased between 2004 and 2019, from 32.1% and 5.3–34.8% and 14.1%, respectively [26]. (2) The prevalence of diabetes in China has increased from 0.67% in 1980 to 12.4% in 2018 [27]. (3) Among adults aged ≥ 18 years, there was a clear increasing trend of prevalence of low HDL-C in women, from 8.8% in 1997 doubled to 17.5% in 2018 [28]. (4) The prevalence of hypertension has increased from 15.3% in 1991 to 24.7% in 2018 [29]. (5) Recent data indicated that from year 1991–1995 to 2011–2015, the prevalence of MetS rose rapidly from 8.8 to 29.3%, with a more significant rise in women than in men [8]; the aforementioned situations have caused China to face a CVD crisis and presented with significant higher cases of CVD and numbers of death attributed to CVD.
In the present study, we attempted to observe the correlation between live birth pregnancies with MetS and CMD. To date, several studies have been conducted to elucidate the association between live births and the prevalence of MetS and CMD. A recent study [30] by Xie et al. reported that the number of live birth pregnancies was correlated with an increased risk of MetS, with the prevalence of MetS increasing with the number of live birth pregnancies [30]. Furthermore, Bai et al. [31] explored the relationship between reproductive variables and the prevalence of MetS in Chinese women aged 40 years and older and found that multiparity and menopausal status might be associated with the development of MetS.
Several findings may explain the disparity with our study. Firstly, it is noteworthy that only 15.9% of the participants in our study had MetS, compared to 34.8% and 23.9% in the studies conducted by Xie et al. [30] and Bai et al. [31]. Secondly, the differences in the baseline characteristics between each study; for example, our study population (52.8 years old) was younger in age compared to studies by Xie et al. [30] (58.7 years old) and Bai et al. [31] (56.7 years old). Furthermore, the prevalence of MetS and CMD varies according to the definition, geographic location, and population examined [32, 33]. The present study population was females aged ≥ 30 years old residing in Chongqing, located in Southwest China, while Xie et al. [30] investigated MetS incidence in females aged 40 years or older in Luzhou city, and Bai et al. [31] conducted a cross-sectional study in women aged 40 years or older in Guangxi.
Possible mechanism behind the relationship between live births with MetS and CMD
The specific mechanisms of how the number of live birth pregnancies and menopausal status contributes to MetS and CMD remain unclear, with most studies agreeing that pregnancy played a significant role in the development of MetS and CMD [30, 34].
Several hypotheses have been proposed; firstly, pregnancy is an extremely dynamic phenomenon where reversible metabolic, biochemical, physiological, hematological, and immunological changes occur. These changes lead to a pro-inflammatory, prothrombotic, highly insulin resistant, weight gain, and hyperlipidemic state [35]. Although these adaptations are necessary for the fetus’s development, they also increase the susceptibility to develop MetS and CMD [36]. Secondly, estrogen levels start to decline after the onset of menopause and cause a weakening of estrogen protective effect, thus, increasing the susceptibility of postmenopausal women to develop MetS and CMD [37].
Thirdly, a recent study demonstrated increased live births associated with a higher risk of developing central obesity due to intra-abdominal adipose tissue accumulation [38, 39]. Our finding is consistent with findings from Blaudeau and colleagues [38], which higher live births tend to develop central obesity. Moreover, a positive correlation has been observed between serum cholesterol and central obesity [39, 40], and the present study population demonstrated that a high number of live birth pregnancies were associated with hyperlipidemia.
Fourthly, pregnancy can lead to significant lifestyle and socioeconomic changes, as mothers have to spend most of their time caring for their children. Our research study, in line with previous findings, revealed that women reported a decrease in moderate and vigorous physical activity during pregnancy at 6 months postpartum [41]. This decrease puts them at a higher risk of developing obesity and MetS [35, 42]. Additionally, mothers with more children were under higher economic pressure and had less leisure time, eventually leading to poor access to healthcare, an unhealthier diet, and other socioeconomic problems [43, 44]. These findings underscore the potential implications between parity and socioeconomic status.
China family planning policies with MetS and CMD
The one-child policy was one of the world’s largest and most dramatic population-control campaigns. The policy worked well in containing the fast-growing population and significantly changed China’s family structure [45]. Unfortunately, the economic boom and improved living standards brought by the one-child policy have caused children and adolescents in China to face a higher risk of MetS and CMD [46]. In addition, studies found that since the implementation of the one-child policy, the number of CVD cases started to skyrocket [47].
Previous studies mainly focused on the relationship between the one-child policy to the incidence of CVD and childhood obesity [46, 47], with insufficient investigations of such policy on maternal health. Therefore, in this study, we did a subgroup analysis to elucidate the impact of family planning policy on the incidence of MetS and CMD in Southwest China. Our study suggested that women of the younger generation with more live birth pregnancies had a higher risk of developing obesity and CMD, and the older generation with higher live birth pregnancies had an increased risk of hypertension and dyslipidemia.
Several explanations are needed to elucidate these findings. Firstly, in the present study, we only included women aged ≥ 30 years old who had a history of live birth at least once to prevent the live birth selection bias. Moreover, the implications of family planning policies in China have led to significant changes in one’s economic background, lifestyle, and socioeconomic status, therefore, we did a subgroup analysis by dividing the study population into three groups based on the year of implementation of the changes in policy.
The second explanation lies in the changes in family structure. It is well known that family size significantly impacts maternal health. The more children a woman has, the fewer resources would be allocated to the mother. Wu et al. [48] examined the impact of family size on maternal health outcomes by exploiting the tremendous change in family size under the one-child policy in China and found that mothers with fewer children had a higher calorie intake and a higher probability of being overweight. This finding was in agreement with ours, as we found that the younger generation had a higher risk of developing obesity compared to the older generation.
Thirdly, most Chinese were slim and had suffered from undernutrition and poverty long before the 1980s. Moreover, the impact of slow economic growth led many women to participate in heavy labor jobs. Thus, the older generation (multiparous women) tended to have a lower risk of obesity, MetS, and CMD. Last but not least, the rise of the agricultural sector in the 1980s and the industrial sector in the 1990s has become the main driver of economic growth for the Chinese economy. The economic transition has provoked extensive changes in lifestyle involving overconsumption of dietary fat, high-calorie foods, high-protein diets, and reduction in physical activity. In addition, the traditional concept in China is to overeat while pregnant and breastfeeding, believing it will prevent miscarriage and provide better quality of breast milk. Thus, resulting in the younger generation having an increased risk of developing obesity and CMD [49].
To conclude, we found that since the implementation of the one-child policy and later loosened, women between the ages of 30–65 years old in Southwest China are prone to associated with obesity, dyslipidemia, and CMD. Therefore, strategies should be carried out to improve maternal health, such as health education, screening, and comprehensive evaluation of women’s lifestyles and dietary habits. Especially during perinatal and lactational periods, would be beneficial in reducing the risk of CMD.
Limitations
This study has limitations. Firstly, the scope of the present study is limited to Chinese females residing in Southwest China, which restricts its generalizability. Secondly, due to a lack of prior perinatal examinations, particularly among women in the first and second generations, we encounter challenges in identifying and adjusting pregnancy-related complications for the general population. Furthermore, the absence of a valid quantitative observational method and a potential memory bias hampers our ability to ascertain certain socioeconomic data, such as lifestyle and dietary habits. Consequently, it becomes impractical to account for the potential influence of these factors. Thirdly, the sample size of this study is relatively small; therefore, cautious interpretation is necessary and further investigation with larger sample sizes is required to validate our findings.
Conclusions
In conclusion, after adjusting for potential confounding variables, higher live births are positively associated with the prevalence of CMD among women in Southwest China. Moreover, giving birth after the implementation of the one-child policy tends to have a higher risk of developing CMD.
Electronic supplementary material
Below is the link to the electronic supplementary material.
Acknowledgements
Not Applicable.
Author contributions
B.R.S and G.L designed and performed the experiments, derived the models, and analyzed the data. B.R.S and B.H contributed to the design of the study. G.L contributed for data extraction. B.R.S wrote the manuscript with support from G.L and S.X. L.S.G edited the manuscript. All authors read and approved the final manuscript.
Funding
This study is supported by the cultivation fund of the First Affiliated Hospital of Chongqing Medical University, No. PYJJ2019-25 and The First Affiliated Hospital of Chongqing Medical University, Doctoral program of The First Affiliated Hospital of Chongqing Medical University, No. CYYY-BSYJSCXXM-202325.
Data availability
The data that supports the findings of this study are available from the corresponding author upon reasonable request.
Declarations
Ethics approval and consent to participate
All methods were carried out in accordance with relevant guidelines and regulations. This study was conducted in accordance with the Declaration of Helsinki and approved by the ethics committee of the First Affiliated Hospital of Chongqing Medical University. All the participants were informed of the study content and signed informed consent.
Consent for publication
Not applicable.
Competing interests
The authors declare no competing interests.
Footnotes
Publisher’s note
Springer Nature remains neutral with regard to jurisdictional claims in published maps and institutional affiliations.
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Data Availability Statement
The data that supports the findings of this study are available from the corresponding author upon reasonable request.