Abstract
Background
Previous studies have yielded inconsistent findings regarding the association between age at menopause and bone health, with limited exploration of potential mediating factors, particularly in the less-developed muti-ethnic regions of China. Our objective was to analyze the association between age at menopause and bone health among postmenopausal women in southwest China, while also examining the mediating effect of body mass index (BMI) and the moderating effect of years since menopause on this association.
Methods and results
The analysis included a total of 15,352 naturally postmenopausal women obtained from the baseline data of the China Multi-Ethnic Cohort (CMEC) Study. Multiple linear regression was used for multivariate analysis. Mediation analysis was conducted to examine the mediating role of BMI in the association between age at menopause and bone health. A significant positive association was observed between age at menopause and bone health index (Quantitative ultrasound index, QUI). Specifically, with each year’s delay in age at menopause, there was an increase of 0.260 (95% confidence interval (CI): 0.152–0.368) in QUI. Notably, women with later menopause (menopausal age ≥ 53 years) exhibited a higher QUI (β: 2.684, 95%CI: 1.503–3.865). Additionally, BMI partially mediated the relationship between age at menopause and QUI, accounting for 9.0% of the total effect, with an indirect effect coefficient β(95%CI) was 0.023(0.014, 0.032). Besides, it is worth mentioning that years since menopause moderated the association between age at menopause and bone health as well as the mediating effect of BMI.
Conclusion
Naturally postmenopausal women with a later age at menopause demonstrate enhanced bone health. Maintaining a moderately high BMI, without progressing to overweight or obesity, may provide health benefits for postmenopausal women, especially for those with a longer duration since menopause.
Supplementary Information
The online version contains supplementary material available at 10.1186/s12889-024-20628-0.
Keywords: Age at menopause, Bone health, Body mass index, Mediating effect, Naturally postmenopausal women in Southwest China
Introduction
The skeletal system, one of the largest systems in the human body, performs vital functions including facilitating movement, providing structure support and protection, as well as serving as a mineral reservoir. Osteoporosis, the most prevalent bone disease in humans, is characterized by low bone mass, deterioration of bone tissue structure, resulting in decreased bone strength and heightened susceptibility to low-energy fractures (commonly known as fragility fractures), significantly compromising overall bone health [1]. Researchers have found that women face a significantly higher risk of developing bone-related issues in comparison to men [2–4]. According to a British cohort study, it is estimated that approximately half of the female population may experience an osteoporotic fracture later in life [2]. The incidence of osteoporotic fractures among women aged 50 years and above in the European Union was nearly four times higher than that among men in the same age group [3]. Similarly, from 2008 to 2018, the incidence of fractures and osteoporosis among women in China was estimated to be more than three times higher than that among men [4]. Meanwhile, the age-standardized prevalence of osteoporosis in individuals over the age of 50 was 6.46% for men and 29.13% for women [5]. Multiple studies indicated that this disparity might be attributed to the distinct physiological characteristics and hormone exposure experienced by women through their life cycle [6]. Women undergo menarche, fertility, breastfeeding, all of which cause complex hormonal changes, and menopause in particular may exacerbate bone changes and loss [7].
Menopause, marking the end of female reproductive life and the cessation of ovarian endogenous female sex hormone secretion, is a critical event intricately related to physiological changes and adverse health outcomes in women’s later life [8, 9]. Studies have found that decreased estrogen levels and attenuated ovarian function after menopause are associated with an increased risk of bone loss, osteoporosis, and fractures [6, 10]. However, the age at menopause varies greatly among individuals. Researches on the relationship between the age at menopause and bone health have been limited, mostly focusing on Western populations, and findings have been inconsistent. Earlier menopause might be associated with lower bone mineral density (BMD) [11, 12] and is a risk factor for osteoporosis and fractures [13, 14]. The Women’s Health Initiative Observational cohort reported that early age at menopause (<40 years) might contributed to decreased BMD and increased fracture risk [15], a meta-analysis showed that early menopause (<45 years) was relevant to the higher risk of fracture [16]. While later age at menopause was associated with a lower risk of low BMD [17, 18], and that late menopause (> 55 years) was a protective factor for bone health [19]. Meanwhile, some studies suggested that age at menopause had no significant effect on osteoporosis and fracture risk [20, 21]. There was no association between age at menopause and bone health indicators (Broadband ultrasound attenuation (BUA) and Quantitative ultrasound speed of sound (SOS) of calcaneus) [22]. Limited research has been conducted on this topic in China. The China Kadoorie Biobank (CKB) study followed 125,336 women who experienced natural menopause for 10 years and found that women who experienced menopause at a later age (≥53 years) were confronted with the lower risk of hip fracture [23]. Study from Hong Kong suggested that age at menopause predicted bone loss and agreed with that postmenopausal women with early menopause have lower bone density [24]. Nevertheless, to the best of the authors’ knowledge, there are few efforts in the multi-ethnic regions of western China, where the distribution of menopausal age may deviate from other areas in China. Moreover, the association between menopausal age and bone health might differ due to distinct genetic, socioeconomic, and lifestyle characteristics.
In addition, body mass index (BMI) is supposed to be a key determinant factor of BMD in postmenopausal women [25]. A recent Chinese cross-sectional study found a positive relationship between BMI and BMD among postmenopausal women [26], and a previous study showed that BMI > 32 kg/m2 had a significant protective effect against osteoporosis in women with natural menopause [27]. Several studies indicated that age at menopause was also implicated in adiposity [28–30]. The CKB study conducted in 128,259 Chinese postmenopausal women demonstrated that a 1-year delay in age at menopause was associated with a 0.05 kg/m2 increase in BMI [30]. Thus, BMI may potentially mediate the relationship between menopausal age and bone health. However, there is limited research on this topic. At the same time, women who experienced earlier menopause have a longer duration since menopause compared to those of the same age but with later menopause, reflecting prolonged exposure to low estrogen levels, which also play significant roles in overall bone health [21, 31]. It remains unclear whether the years since menopause moderates the mediation effect of BMI on the association between age at menopause and bone health.
To address these gaps, this study analyzed the relationship between age at menopause and bone health using the baseline survey data from a population of 15,352 naturally postmenopausal women in Southwest China, which represented a less developed multi-ethnic community. Additionally, we explored the mediating role of BMI and further examined whether years since menopause moderated this possible association and mediation. This study aimed to provide novel insights into the underlying mechanism linking age at menopause with bone health by examining whether BMI mediates the relationship between the two variables. The goal was to establish a scientific foundation for targeted interventions aimed at preventing bone health issues among postmenopausal women.
Materials and methods
Study design
The data of this study was derived from the baseline survey of the China Multi-Ethnic Cohort (CMEC) conducted in five provinces (Sichuan, Chongqing, Yunnan, Guizhou and Tibet), a population-based cohort study. Details of the study design and recruitment of subjects for this cohort have been described in detail in previous literature [32]. In brief, the project was sampled using a multi-stage stratified cluster sampling method from May 2018 to September 2019, taking full account of ethnic characteristics and population size. A total of 99,556 adults aged 30 to 79 years (few of the Tibetan participants were younger than 30 years) were recruited from five provinces in Southwest China. The data collection process involved conducting face-to-face interviews using electronic questionnaires, as well as performing medical examinations and clinical laboratory tests to assess on non-communicable diseases (NCDs) such as hypertension, diabetes, and stroke along with their related factors. The electronic questionnaire encompassed demographic characteristics, socioeconomic status, health behaviors (e.g. diet, physical activity, smoking status, and alcohol consumption), reproductive history, and other health-related factors. Medical examinations were primarily conducted using the available resources and personnel at local clinical centers, including physical examination, bone densitometry assessments, as well as collection of biological samples. All the doctors, nurses, and investigators involved in the study received epidemiologic training in professional measuring methods and questionnaire administration skills before the survey began.
Study participants
In this study, a total of 99,556 multi-ethnic adult participants aged 30 to79 years were analyzed and the study population was excluded according to the following criteria: (1) Individuals outside of the age of 30 to 79 years; (2) Male; (3) Pre-menopausal women; (4) Women with surgical menopause (hysterectomy and/or ovariectomy women); (5) Women with a history of diseases that may affect the outcome of the study, such as fractures, rheumatoid arthritis, rheumatoid arthritis, diabetes, chronic hepatitis, cirrhosis, etc.; (6) Women with unknown age at menopause; (7) Women with menopause occurring before the age of 40, possibly due to other pathological factors; (8) Women without variables related to bone health; (9) Due to the fact that Tibetans primarily inhabit plateau areas and possess distinct diet, exercise and living habits compared to those residing in plain areas, as well as their exposure to high altitude and hypoxic conditions which significantly impact residents’ BMI and bone metabolism [33, 34], Tibetan women living in plateau areas were excluded from the main findings of this study. A total of 15,352 naturally postmenopausal women were included in the study. Figure 1 shows details of the inclusions and exclusions in this study.
Fig. 1.
A schematic overview of the procedures for selecting and excluding study population
Assessment of bone health
Quantitative ultrasound (QUS) was used to measure calcaneal bone with OSTEOKJ3000 (Nanjing Kejin Industrial Co., LTD., China) in the CMEC [35]. The calcaneus is the most common site for QUS measurement due to its two lateral surfaces and relatively thin soft tissue covering, which facilitates ultrasound conduction [36]. QUS is a non-ionizing radiation technique that provides fast and economical information about bone structure, organization, and bone mass [37]. Its high reproducibility (accuracy error of about 2–3%) makes it comparable to dual-energy X-ray absorptiometry in predicting fracture risk [38, 39]. QUS technique has been extensively evaluated and applied in a large number of studies, marking it suitable for evaluating fracture risk in older women and large-scale epidemiological studies [37, 40, 41].
The QUS evaluation method measures the broadband ultrasound attenuation (BUA) of calcaneal bone, which reflects the frequency dependence of ultrasonic attenuation [42], as well as the quantitative ultrasound speed of sound (SOS) that reflects the elastic modulus of bone [43]. In this study, quantitative ultrasound index (QUI), an index reflecting bone strength derived from the combination of the above variables, was used as the outcome variable for analysis. A higher QUI means a higher bone strength, and its calculation method is as follows [44, 45]:
 |
Assessment of age at menopause
The age at menopause was defined as the age of a postmenopausal woman at the onset of menopause, which was obtained through an open-ended question [46]. Menopause was defined as the cessation of menstruation in a woman lasting longer than 12 months. The age at menopause was directly used as a continuous variable in the analysis to evaluate the effect of each year’s delay in age at menopause on bone health. Alternatively, it was classified as a categorical variable according to the P10th and P90th of age at menopause within this population (early menopause: 40–43 years; normal menopause: 44–52 years; and late menopause: ≥ 53 years) [21] to compare the differences of bone health in the three menopausal age groups.
Assessment of body mass index
Body mass index (BMI, kg/m2) at the time of the survey was used for the analysis. Participants’ height and weight were measured at the survey site by trained medical workers using a unified and calibrated medical height and weight meter.
Assessment of covariates
This study considered several covariates including female reproductive factors such as age at menarche, parity, number of abortions (including natural abortion, drug abortion, artificial surgical abortion), age of first birth (women who went through childbirth), oral contraceptive (OC) use (yes, or no). It also examined basic sociodemographic characteristics and financial situation: age at enrollment, ethnicity (Han, Dong, Bouyei, Yi, Miao, and Bai), education level (illiteracy, primary, middle school, and high school or above), occupation (agriculture and related, factory worker, professionals, clerk, self-employed, unemployed, and other), marital status (unaccompanied, accompanied), and annual family income (<12,000, 12,000–19,999, 20,000–59,999, 60,000–99,999, and ≥100,000). Furthermore, health-related behaviors variables were taken into account: smoking status (never, former, and current), alcohol consumption (never, occasionally, and often), diet (Mediterranean diet score, calculated with reference to the study of Trichopoulou, et al. [47]. The Mediterranean diet pattern, a simple, light and nutrient-rich healthy diet, has been found to be associated with increased survival among older adults [47] and the higher the score, the healthier the diet [48]), physical activity (assessed according to the metabolic equivalent value per unit of physical activity performed by the respondents in four areas of household, work, transportation, and leisure multiplied by the total metabolic equivalent calculated by the number of hours per day of such physical activity (METs/ day) [49], and divided into three categories according to quantile for analysis), severe food shortages experience (yes, or no), calcium supplements intake (yes, or no), vitamin D intake (yes, or no).
Assessment of moderator
Years since menopause was obtained by subtracting age at menopause from age at enrollment.
Statistical analysis
The data was collated and analyzed using R 4.1.0 software. All tests were 2- sided, and P values < 0.05 indicated statistical significance. Mean ± standard deviation (SD) was used to describe the continuous variables, the categorical variables were statistically described by frequency and percentage (N(%)). Analysis of variance and Chi-square analysis were used for the comparison of data in difference age groups at menopause. Multiple linear regression was conducted to analyze the association between age at menopause and bone health. β(95%CI) represented the association coefficient between independent variable and dependent variable, along with its 95% confidence interval (CI). In order to gradually reduce confounding and explore the effect of BMI, four models were established. Model 1 is a crude model without any adjustment for confounding factors. Model 2 adjusted the age at enrollment on the basis of model 1; Model 3, based on model 2, factors such as ethnicity, occupation, marital status, education level, annual family income, severe food shortage experience, smoking status, alcohol consumption, total physical activity, calcium supplements intake, vitamin D intake, Mediterranean diet score, oral contraceptives use, parity, number of abortions, age at menarche, age of first birth were included to be adjusted; Model 4 has additionally adjusted BMI based on model 3. In order to explore the relationship between age at menopause and bone health in women with different characteristics, model 3 was used as the main model in this study. Subgroup analyses of associations between age at menopause and bone health were performed according to participants’ age, ethnic group, education level, oral contraceptive use, smoking status, alcohol consumption, total physical activity level, leisure physical activity frequency, occupational physical activity intensity, household physical activity level, transportation physical activity level, experiencing severe food shortage, Mediterranean diet score, and parity. The P value (interaction P) between the groups was obtained by the likelihood ratio test. All P for trend values in the analysis are the P-values of the variables obtained by converting the value of categorical variables into ordered numerical variables and including them in the regression equation, representing the linear trend [50]. Then, the mediation role of BMI was analyzed based on model 4 with the package “mediation” in R software version 4.1.0. Finally, the year since menopause was divided into <9 years and ≥9 years based on the median value. In each group, the relationship between age at menopause and bone health as well as the mediating effect of BMI were analyzed to investigate the moderating effect of years since menopause.
Sensitivity analysis
To verify the robustness of the findings, a series of sensitivity analyses were conducted in this study: (1) The association between age at menopause and bone health was studied in all naturally postmenopausal women, including Tibetan women; (2) The association analysis between age at menopause and bone health was conducted in postmenopausal women who were not overweight and obese, so as to verify the association between age at menopause and bone health on the basis of controlling BMI.
Results
Baseline characteristics
Finally, 15,352 naturally postmenopausal women from Southwest China were included in this study, with a mean age of 59.87±7.71 years. Among them, the Han, Dong, Bai, Bouyei, Miao, and Yi ethnic groups accounted for 54.5%, 11.6%, 10.5%, 9.9%, 7.6%, and 5.9%, respectively. The mean age at menopause was 48.76±3.78 years, the mean BMI was 23.74±3.47 kg/m2, the mean QUI was 65.39±25.76, the mean SOS was 1522.57±43.47 m/s, and the mean BUA was 29.60±45.58 dB/MHz. The distributions of age at menopause, years since menopause, BMI and bone health indexes among postmenopausal women in different ages and ethnic groups are presented in Supplement 1 of Supplementary Material 2, Figure S1-S6.
A descriptive analysis based on age groups at menopause showed that individuals who experienced menopause later tended to be older, more likely to be Han ethnicity and less likely to consume alcohol. They were also less likely to have companionship, had later age at menarche and first birth, had lower overall physical activity levels, but engaged in more leisure physical activity. Furthermore, they participated in less occupational and transportation-related physical activity, had higher BMI values, a higher percentage of experiencing severe food shortages and calcium supplements intake, and higher Mediterranean diet scores. Women who experienced menopause earlier were more likely to be employed in agriculture sector and related occupations, had a higher rate of illiteracy, lower annual family income, more parities, and longer years since menopause. There were no significant differences in smoking status, oral contraceptive use, housework physical activity level, and vitamin D intake ratio. For details, see Table 1.
Table 1.
Characteristics of the study participants by age at menopause
| Total | Age at menopause (years) | P | ||||
|---|---|---|---|---|---|---|
| 40–43 | 44–52 | ≥53 | ||||
| N | 15,352 | 1454 | 11,786 | 2112 | ||
| Age (SD), years | 59.87(7.71) | 60.46(9.32) | 59.40(7.69) | 62.09(6.00) | < 0.001 | |
| Ethnicity (%) | < 0.001 | |||||
| Han | 8364(54.5) | 658(45.3) | 6497(55.1) | 1209(57.2) | ||
| Dong | 1782(11.6) | 267(18.4) | 1338(11.4) | 177(8.4) | ||
| Bouyei | 1514(9.9) | 182(12.5) | 1135(9.6) | 197(9.3) | ||
| Yi | 913(5.9) | 81(5.6) | 673(5.7) | 159(7.5) | ||
| Miao | 1166(7.6) | 134(9.2) | 885(7.5) | 147(7.0) | ||
| Bai | 1613(10.5) | 132(9.1) | 1258(10.7) | 223(10.6) | ||
| Occupation (%) | < 0.001 | |||||
| Agriculture and related | 6943(45.2) | 713(49.0) | 5267(44.7) | 963(45.6) | ||
| Clerk | 479(3.1) | 59(4.1) | 375(3.2) | 45(2.1) | ||
| Factory worker | 360(2.3) | 40(2.8) | 278(2.4) | 42(2.0) | ||
| Professionals | 245(1.6) | 26(1.8) | 203(1.7) | 16(0.8) | ||
| Self-employed | 328(2.1) | 30(2.1) | 261(2.2) | 37(1.8) | ||
| Other | 447(2.9) | 50(3.4) | 344(2.9) | 53(2.5) | ||
| Unemployed | 6548(42.7) | 536(36.9) | 5056(42.9) | 956(45.3) | ||
| Marital status: accompanied (%) | 12,561(81.8) | 1166(80.2) | 9703(82.3) | 1692(80.1) | 0.013 | |
| Education level (%) | < 0.001 | |||||
| Illiteracy | 7061(46.0) | 841(57.8) | 5198(44.1) | 1022(48.4) | ||
| Primary | 3799(24.7) | 340(23.4) | 2971(25.2) | 488(23.1) | ||
| Middle school | 2771(18.1) | 181(12.4) | 2235(19.0) | 355(16.8) | ||
| High school or above | 1720(11.2) | 92(6.3) | 1381(11.7) | 247(11.7) | ||
| Annual family income, yuan (%) | < 0.001 | |||||
| < 12,000 | 3788(24.7) | 450(31.0) | 2855(24.2) | 483(22.9) | ||
| 12,000–19,999 | 3107(20.3) | 330(22.7) | 2357(20.0) | 420(19.9) | ||
| 20,000–59,999 | 5266(34.3) | 468(32.2) | 4029(34.2) | 769(36.4) | ||
| 60,000–99,999 | 1933(12.6) | 123(8.5) | 1543(13.1) | 267(12.6) | ||
| ≥10,0000 | 1248(8.1) | 82(5.6) | 993(8.4) | 173(8.2) | ||
| Smoking status (%) | 0.116 | |||||
| Never | 15,219(99.1) | 1434(98.6) | 11,687(99.2) | 2098(99.3) | ||
| Quit | 26(0.2) | 3(0.2) | 22(0.2) | 1(0.1) | ||
| Current | 107(0.7) | 17(1.2) | 77(0.6) | 13(0.6) | ||
| Alcohol consumption (%) | 0.003 | |||||
| Never | 11,869(77.3) | 1145(78.7) | 9107(77.3) | 1617(76.6) | ||
| Occasionally | 2965(19.3) | 253(17.4) | 2313(19.6) | 399(18.9) | ||
| Often | 518(3.4) | 56(3.9) | 366(3.1) | 96(4.5) | ||
| Total physical activity (%) | 0.037 | |||||
| Low | 3657(23.9) | 335(23.2) | 2786(23.8) | 536(25.5) | ||
| Moderate | 7692(50.4) | 700(48.4) | 5930(50.6) | 1062(50.5) | ||
| High | 3921(25.7) | 411(28.4) | 3004(25.6) | 506(24.0) | ||
| Leisure physical activity (%) | < 0.001 | |||||
| Never | 8849(58.0) | 958(66.3) | 6739(57.5) | 1152(54.8) | ||
| Low | 1381(9.0) | 110(7.6) | 1078(9.2) | 193(9.2) | ||
| High | 5040(33.0) | 378(26.1) | 3903(33.3) | 759(36.1) | ||
| Occupational physical activity (%) | < 0.001 | |||||
| Never | 6656(43.6) | 554(38.3) | 5097(43.5) | 1005(47.8) | ||
| Low | 3413(22.4) | 325(22.5) | 2641(22.5) | 447(21.2) | ||
| High | 5201(34.1) | 567(39.2) | 3982(34.0) | 652(31.0) | ||
| Housework physical activity (%) | 0.946 | |||||
| Low | 4229(27.7) | 407(28.1) | 3249(27.7) | 573(27.2) | ||
| Moderate | 4384(28.7) | 420(29.0) | 3351(28.6) | 613(29.1) | ||
| High | 6657(43.6) | 619(42.8) | 5120(43.7) | 918(43.6) | ||
| Transportation physical activity (%) | < 0.001 | |||||
| Never | 7488(49.0) | 633(43.8) | 5739(49.0) | 1116(53.0) | ||
| Low | 1792(11.7) | 169(11.7) | 1386(11.8) | 237(11.3) | ||
| high | 5990(39.2) | 644(44.5) | 4595(39.2) | 751(35.7) | ||
| Body mass index (BMI, kg/m2) (SD) | 23.74(3.47) | 23.57(3.54) | 23.69(3.45) | 24.15(3.50) | < 0.001 | |
| Severe food shortages experience: no (%) | 10,873(70.9) | 972(66.9) | 8493(72.1) | 1408(66.8) | < 0.001 | |
| Calcium supplement intake (%) | 3016(19.7) | 243(16.7) | 2310(19.6) | 463(22.0) | 0.001 | |
| Vitamin D intake (%) | 305(2.0) | 22(1.5) | 235(2.0) | 48(2.3) | 0.276 | |
| Mediterranean diet score (SD) | 24.79(4.38) | 24.03(4.34) | 24.87(4.36) | 24.92(4.49) | < 0.001 | |
| Number of abortion (SD) | 0.96(1.29) | 0.86(1.36) | 0.97(1.27) | 0.98(1.34) | 0.006 | |
| Oral contraceptive use (%) | 1405(9.2) | 121(8.3) | 1106(9.4) | 178(8.4) | 0.192 | |
| Age at menarche, years (SD) | 15.50(2.27) | 15.53(2.45) | 15.43(2.24) | 15.86(2.29) | < 0.001 | |
| Age of first birth, years (SD) | 23.31(2.92) | 23.14(3.04) | 23.32(2.89) | 23.38(2.97) | 0.038 | |
| Parity (SD) | 2.25(1.18) | 2.53(1.29) | 2.21(1.17) | 2.30(1.15) | < 0.001 | |
| Years since menopause (SD) | 11.11(8.29) | 19.11(9.69) | 10.77(7.88) | 7.48(5.54) | < 0.001 | |
Multiple linear regression between age at menopause and QUI in postmenopausal women
As shown in Table 2, this study found that there was a positive association between the age at menopause and QUI. After adjusting for all potential covariates in the main model (Model 3), a significant positive association was observed between delayed age at menopause and an increase in QUI by 0.260(0.152, 0.368). Furthermore, compared to women who experienced menopause between the age of 44 and 52, those with the later menopause (at age ≥53 years) had higher QUI levels. The β(95%CI) of QUI in women aged 40–43 and ≥53 years was − 0.225(-1.621, 1.172) and 2.684(1.503, 3.865), respectively, with a significant P value for trend of <0.001(Table 2, Model 3).
Table 2.
Multiple linear regression results of age at menopause and QUI in postmenopausal women (β(95%CI))
| Age at menopause (years) | P trend | 1-year delay of age at menopause | |||
|---|---|---|---|---|---|
| 40–43 | 44–52 | ≥ 53 | |||
| Model 1 | -0.568(-1.972, 0.835) | Ref. | 1.224(0.031, 2.417) | 0.105 | 0.132(0.025, 0.240) |
| Model 2 | -0.039(-1.428, 1.350) | Ref. | 2.571(1.382, 3.759) | <0.001 | 0.220(0.113, 0.327) |
| Model 3 | -0.225(-1.621, 1.172) | Ref. | 2.684(1.503, 3.865) | <0.001 | 0.260(0.152, 0.368) |
| Model 4 | -0.207(-1.612, 1.198) | Ref. | 2.517(1.325, 3.709) | <0.001 | 0.243(0.134, 0.352) |
Model 1: crude model, without any adjustment
Model 2: Model 1 + adjusted age
Model 3: Model 2 + adjusted for ethnicity, occupation, marital status, education level, annual family income, experience of severe food shortages, smoking status, alcohol consumption status, total physical activity, calcium supplement intake, vitamin D intake, Mediterranean diet score, OC use, parity, number of abortions, age at menarche, age of first birth
Model 4: Model 3 + Adjusted BMI
Model 4 made additional adjustments to BMI on the basis of model 3 and found that age at menopause had a reduced protective effect on QUI. The increase of QUI changed to 0.243(0.134, 0.352) for each year delay of menopausal age.
Besides, we also examined the association of age at menopause and QUI in women with different years since menopause, details see Supplement 2 of Supplementary Material 2, Table S1.
Subgroup Analysis of the association between age at menopause and QUI
The results of subgroup analysis were consistent and indicated a statistically significant association between age at menopause and QUI. Age, ethnicity, education level, alcohol consumption, transportation physical activity may also serve as important moderators of the association between menopausal age and bone health (interactive P < 0.05). All significant results consistently demonstrated that age at menopause was positively associated with QUI, as shown in Fig. 2.
Fig. 2.
Association of age at menopause and QUI in different subgroups. Note: To test the stability of the analysis results, subgroup analysis of important covariates was performed based on Model 3, adjusting for occupation, marital status, annual family income, calcium supplement intake, vitamin D intake, number of abortions, age at menarche, and age of first birth. Age, ethnicity, education level, OC use, smoking status, alcohol consumption, total physical activity level, experience of severe food shortages, Mediterranean diet score, and parity were adjusted for each other in the regression equation. When occupational physical activity, leisure physical activity, housework physical activity and transportation physical activity were stratified, the four variables adjusted each other, and the total physical activity level was not adjusted
The mediation effect of BMI between age at menopause and QUI
As the basis of BMI as a mediator, the association between age at menopause and BMI as well as BMI and QUI were shown in Supplement 3 of Supplementary Material 2, Figure S7-S8.
In the study population, it was observed that BMI partially mediated the relationship between age at menopause and QUI. The direct effect β(95%CI) of age at menopause on QUI was 0.223(0.115, 0.331). Age at menopause was positively associated with BMI, with an effect value β(95%CI) was 0.052(0.037, 0.066). Additionally, BMI demonstrated a positive association with QUI, with an influence β(95%CI) of 0.439(0.320, 0.558). The indirect effect β(95%CI), mediated by BMI in the relationship, was estimated to be 0.023(0.014, 0.032), accounting for 9.0% of the total effect, as depicted in Fig. 3.
Fig. 3.
The mediating effect of BMI between age at menopause and QUI. Note: Adjusted for age, ethnicity, occupation, marital status, education level, experience of severe food shortages, annual family income, smoking status, alcohol consumption, total physical activity, calcium supplements intake, vitamin D intake, Mediterranean diet score, OC use, parity, age at menarche, number of abortions, age of first birth
The mediating role of BMI in women with different years since menopause
In order to investigate the moderating effect of years since menopause on the mediating effect of BMI on age at menopause and QUI, years since menopause were divided into 2 categories according to the median (9 years), and the mediating effect of BMI was analyzed within the two groups, as shown in Fig. 4.
Fig. 4.
The mediating effect of BMI in women with different years since menopause. Note: A: in women with less than 9 years since menopause; B: in women with 9 or more years since menopause. Adjusted for age, ethnicity, occupation, marital status, education level, experience of severe food shortages, annual family income, smoking status, alcohol consumption, total physical activity, calcium supplements intake, vitamin D intake, Mediterranean diet score, OC use, parity, age at menarche, number of abortions, age of first birth
In women with less than 9 years since menopause, BMI partially mediated the association between age at menopause and QUI. The direct effect β(95%CI) of menopausal age on QUI was 0.803(0.509, 1.106), while the indirect effect β(95%CI) mediated by BMI was 0.022(0.007, 0.041), accounting for 2.7% of the total effect, as shown in Fig. 4, A.
In women with 9 or more years since menopause, the direct impact of age at menopause on QUI was no longer significant, while the indirect effect on QUI through BMI remained statistically significant. The β(95%CI) for the direct effect of age at menopause on QUI was 0.077(-0.071, 0.240), and the β(95%CI) for the indirect effect of BMI was 0.025(0.013, 0.040), accounting for 20.5% of the total effect, as illustrated in Fig. 4, B.
Sensitivity analysis
In addition to the main analyses, a series of sensitivity analyses were carried out in this study. As shown in Supplement 4 of Supplementary Material 2, Table S2-S3, all analytical results consistently indicated that the robustness of this study’s results and confirmed the existence of an association between age at menopause and bone health.
Discussion
This study represents the first comprehensive epidemiological investigation into the association between age at menopause and bone health among women residing in multi-ethnic regions of southwest China. The findings demonstrated a positive association between age at menopause and bone health, highlighting late menopausal onset (≥ 53 years) as a protective factor for maintaining optimal bone health. Moreover, BMI emerged as a significant mediator in the relationship between age at menopause and bone health. Additionally, the study revealed that the years since menopause played a moderating role in both the total effect of menopausal age on bone health, and the indirect influence mediated by BMI.
Our results regarding the association between age at menopause and bone health are generally consistent with some previous studies. Researchers found that women with later menopause were supposed to have better bone health compared to those of similar age due to a self-limiting bone loss associated with menopause [51] and the rapid decline in BMD that initiates about one year prior to the final menstrual period [52]. This phenomenon could potentially be attributed to the timing of decline in endogenous hormone exposure caused by menopausal age, as late-menopausal women have a longer duration of exposure to the beneficial effects of estrogen [53, 54]. A Japanese study involving 1,035 women who experienced natural menopause concluded that women who experienced a late menopause had a reduced risk of low bone density and potentially lower susceptibility to osteoporosis [17]. Similar results were found in studies on postmenopausal women in Thailand and South Korea, in which later age at menopause was identified as a protective factor against osteoporosis and fracture [18, 19]. However, the findings of this study diverged from some previous studies. A Dutch study involving women aged 55 to 93 years found no association between women’s age at menopause and SOS or BUA values, despite a significant age-related decline in BUA and SOS, with women experiencing a decline rate about three times higher than men [22]. Some studies have proposed that the impact of age at menopause on BMD and fractures is limited or insignificant [20, 55]. Besides, some previous studies have reported that an early age at menopause has detrimental effects on bone health [15, 16, 56], but we found no association between early age at menopause and bone health. These inconsistent results may be attributed to variations in sampling methods, geographical location, living conditions, basic characteristics, age grouping at menopause, and other aspects of the study population.
Notably, this study revealed that BMI served as a mediator in the positive association between age at menopause and QUI, demonstrating an increase in BMI with higher age at menopause, subsequently leading to elevated levels of QUI. Previous studies have not investigated the mediating role of BMI between age at menopause and bone health, but there are many studies examining the association between age at menopause and BMI as well as BMI and bone health. A cross-sectional study in Korean indicated that late menopause was associated with obesity and being overweight [57]. The CKB study [30] found that BMI was positively associated with age at menopause, with each one-year increase in age at menopause resulting in a 0.05 kg/m2 rise in BMI, which aligned with our findings. The obesity with higher BMI during menopause might be attributed to the decrease of estrogen and the increase of androgen-related free testosterone [58]. Furthermore, it is worth noting that higher BMI was closely related to bone mass [59], serving as a determining factor for postmenopausal women’s BMD [25]. Lower BMI was associated with an increased risk of hip fracture [60], while a BMI above 32 kg/m2 appeared to protect against postmenopausal osteoporosis [27]. In postmenopausal women, adipocyte was a significant source of estrogen production, which was known to inhibit bone resorption by inducing osteoclast apoptosis and led to the higher bone mass [61]. In conclusion, age at menopause may influence changes in BMI which subsequently impacts overall bone health; thus BMI, is presumed to play a significant mediating role in the relationship between age at menopause and bone health in response to changes in sex hormones or other unknown mechanisms. The findings of this study validate this hypothesis, but further investigation is required.
Furthermore, this study found that the direct impact of age at menopause on QUI disappeared in mediation analysis of women with ≥ 9 years since menopause, the influence of age at menopause on QUI was primarily indirect through its effect on BMI. A Chinese study involving 775 women aged 35 to 75 years demonstrated a significant influence of age at menopause on bone loss, particularly among younger postmenopausal women (<10 years after menopause) [62]. An Italian study comprising 2,204 postmenopausal women found that women under 60 years of age who experienced early menopause had lower peripheral bone mass and an increased risk of fracture, but not observed in women over 60 years [63]. Vertebral BMD was significantly lower in women with early menopause within the age group of 50 to 54 years, but no significant difference was found among women over 55 years [64]. The differences led by variation in age distribution might be related to different durations since menopause. The SWAN study followed pre-menopausal or early menopausal women and discovered that the femoral neck strength began declining one to two years before their last menstrual period and continued to decline for ten years after reaching menopause [65]. Women with shorter years since their last menstrual period were more likely to be affected by this decline. For women who experienced longer years since menopause, the main issue was the cumulative effect of sex hormone deficiency, while the influence of age at menopause on bone health diminished or even disappeared over time. However, age at menopause still significantly affected BMI, suggesting that it might indirectly influence bone health through its impact on BMI. The relationship between age at menopause and bone health may involve additional mediating factors or mechanisms, which warrant further investigation.
Strengths and limitations
In this study, a large and diverse population was selected through multi-stage sampling from various provinces and ethnicities in Southwest China, ensuring the representativeness of the sample and the validity of the results. A series of sensitivity analyses were conducted, yielding robust findings. This study introduced several innovations: (1) It is the first to examine the mediating role of BMI between age at menopause and bone health, providing novel insights into the mechanism underlying the impact of menopausal age on bone health; (2) It initially investigated the moderating impact of years since menopause on the relationship between age at menopause and bone health, as well as examine the moderating effect on the indirect relationship mediated by BMI.
However, there were some limitations in this study: (1) Although the subjects had experienced menopause prior to the investigation, both BMI and QUI were obtained through field surveys, which essentially won’t lead to causal inversion. However, the cross-sectional data limited the causal inferences; (2) Variables such as diet, physical activity, reproductive histories, and particularly age at menopause, were self-reported based on recall, which might introduce recall bias. Nevertheless, studies have indicated that factors like reproductive history are closely related to their true values [66, 67], and recall bias for recent events such as age at menopause might be smaller. (3) BMI was used as an indicator of obesity in this study, but it only reflects the overall body shape and doesn’t provide information on the distribution of body fat and skeletal muscle [68], further research is needed to explore whether body fat or skeletal muscle play a mediating role on the association between menopausal age and bone health. (4) Due to challenges in conducting large-scale population studies involving measurement techniques, QUS measurement were used instead of other methods, which might affect the precision of bone health assessment. Nonetheless, studies have shown that QUS possesses similar predictive capabilities for osteoporotic fractures compared to bone density, and serves as an independent risk factor [37, 69, 70].
Conclusion
In conclusion, there exists a positive association between age at menopause and bone health, whereby women experiencing later menopause exhibit higher levels of bone strength. It is plausible that delayed menopause may contribute to improved bone health through an elevated BMI, thus forming a significant mediating pathway. Furthermore, the duration since menopause moderates these associations. Our findings can serve as a new reference for the protection of bone health in postmenopausal women.
Electronic supplementary material
Below is the link to the electronic supplementary material.
Acknowledgements
We thank all the team members and participants involved in the China Multi-Ethnic Cohort (CMEC). We are grateful to Prof. Xiaosong Li at Sichuan University for his leadership and fundamental contribution to the establishment of the CMEC. Li has passed away in 2019 and his contribution is worth bearing in mind forever.
Author contributions
Q.L. and X.Z. proposed the Conceptualization; J.C., X.L., Y.W., D., Y.Z., and L.C. were responsible for Data curation; J.C. and X.L. completed the Formal analysis; Q.L. and X.Z. provided the Funding acquisition; Y.W. and D., Y.Z., and L.C. conducted the Investigation; J.C. and X.L. explored the Methodology; X.L. and X.Z. were involved in Project administration; J.C. and Y.W. were in charge of Software application; J.C. and X. L. completed the Writing—original draft; Q.L., Y.W., D., Y.Z., and L.C. reviewed and edited the original manuscript; All authors have read and approved the final manuscript.
Funding
This work was supported by the National Key R&D Program of China (Grant No: 2017YFC0907300). This work was also supported by the “Unveiling-list, Assuming-leadership” Project of Zigong Academy of Medical Sciences in 2023 (Grant NO: ZGYKY23JB001).
Data availability
The datasets generated and analyzed during the current study are not publicly available due to protect the privacy of study participants in this project which involved a large range of population data, but are available from the corresponding author on reasonable request.
Declarations
Ethics approval and consent to participate
The project was approved by the Medical Ethics Review Committee of Sichuan University (K2016038, K2020022). And all subjects signed informed consent before participating in the investigation.
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.
Jiayi Chen and Xian Liang have contributed equally to this work and share the first authorship.
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Associated Data
This section collects any data citations, data availability statements, or supplementary materials included in this article.
Supplementary Materials
Data Availability Statement
The datasets generated and analyzed during the current study are not publicly available due to protect the privacy of study participants in this project which involved a large range of population data, but are available from the corresponding author on reasonable request.