# Meta-analysis: Early Age at Natural Menopause and Risk for All-Cause and Cardiovascular Mortality

Authors: Luyao Huan; Xiangling Deng; Mengyang He; Shunhong Chen; Wenquan Niu
Journal: BioMed Research International
 (2021)

---

## Abstract

Aims. The aim of this meta-analysis was to comprehensively evaluate the association of early age at natural menopause with the risk for all-cause and cardiovascular mortality. Methods. Literature retrieval was done on August 4, 2020. Article selection and data extraction were completed independently and in duplicate. Early age at natural menopause was grouped into premature menopause (<40 years), early menopause (40-44 years), and relatively early menopause (45-49 years). Effect-size estimates are summarized as hazard ratio (HR) or relative risk (RR) with 95% confidence interval (CI). Results. Sixteen articles involving 321,233 women were meta-analyzed. Overall analyses revealed a statistically significant association of early age at natural menopause with all-cause mortality risk (HRadjusted=1.08, 95% CI: 1.03 to 1.14, P=0.002; RRadjusted=1.05, 95% CI 1.01 to 1.08, P=0.005), but not with cardiovascular mortality risk. In dose-response analyses, the association with all-cause mortality was significant for premature menopause with (HRadjusted=1.10; 95% CI: 1.01 to 1.21; P=0.034) and without (RRadjusted=1.34; 95% CI: 1.08 to 1.66; P=0.007) considering follow-up intervals. As for cardiovascular mortality, marginal significance was noted for premature menopause after considering follow-up intervals (HR=1.09; 95% CI: 1.00-1.19; P=0.045). Subgroup analyses indicated that gender, country, and follow-up periods were possible causes of heterogeneity. There was an overall low probability of publication bias. Conclusions. Our findings indicate that premature menopause is a promising independent risk factor for both all-cause and cardiovascular mortality.


---

## Body

## 1. Introduction

Menopause is defined as the cessation of spontaneous menses for 12 months, marking the end of a woman’s reproductive life [1], and it typically occurs between the ages of 49 and 52 years [2]. An estimated 5% women experience early menopause (menopause onset within 40 to 45 years of age) [3], and 1% women experience premature menopause (menopause onset before 40 years of age) [4, 5]. It is well known that the onset age of menopause is an indicator of reproductive aging, general health, and somatic aging [6]. Evidence from epidemiologic and clinical studies has demonstrated that early age at natural menopause is associated with an enhanced risk for all-cause and cardiovascular mortality [7, 8]. In 2016, Gong and colleagues conducted a meta-analysis of 10 articles, by showing that women who experienced the earliest age natural menopause had a slightly increased all-cause mortality risk [8]. Another review by Muka and colleagues recorded an enhanced risk of cardiovascular mortality and overall mortality in women who had experienced premature or early-onset menopause [9]. Although the association between early age at natural menopause and mortality has been widely evaluated in current medical literature [9–12], there is no definite consensus on this association, possibly due to populations of different races or ethnicities, individually underpowered studies, and lack of adjusting for confounding factors. Given the accumulating data after the year 2016 [8, 9, 13], a more comprehensive evaluation of this association and exploration of possible reasons behind previously inconsistent reports are necessary.To fill this gap in knowledge and yield more information for future research, we conducted a comprehensive meta-analysis by synthesizing the results of prospective studies that have evaluated the association of early age at natural menopause with all-cause and cardiovascular mortality.


## 2. Materials and Methods

This meta-analysis was complied with the guidelines of the Preferred Reporting Items for Systematic Reviews and Meta-analyses (PRISMA) statement [14], and the PRISMA checklist is summarized in Supplementary Table 1.In this meta-analysis, as all data were extracted from previous published studies, ethical approval and informed consent are not required.


### 2.1. Search Strategy

We completed literature search as of August 4, 2020, by reviewing PubMed, HuGE Navigator, EMBASE (Excerpt Medica Database), and Web of Science databases. Only published articles written in the English language were considered in the current meta-analysis. The following medical subject heading terms were used: (premenopausal OR early menopause OR perimenopausal OR premature menopause OR menopause OR late menopause OR natural menopause OR postmenopause OR age at menopause OR menopausal age) [Title/Abstract] AND (cardiovascular risk OR coronary heart disease OR cardiovascular disease OR cardiovascular OR all-cause mortality OR cardiovascular mortality) [Title/Abstract]. The reference lists of retrieved articles were also hand searched for potential missing hits.Two investigators (L.H. and X.D.) independently reviewed all retrieved articles and carefully assessed preliminary eligibility based on the title and abstract, as well as full text when necessary.


### 2.2. Inclusion and Exclusion Criteria

We restricted our analysis to articles that fulfilled the following inclusion criteria: (i) natural menopause; (ii) without estrogen therapy; (iii) multivariate-adjusted hazard ratio (HR) or relative risk (RR) with 95% confidence interval (CI) for quantifying the association of age at natural menopause with cardiovascular or all-cause mortality; (iv) prospective design; (v) all-cause mortality verified by death certificates or medical records; (vi) study subjects free of major underlying diseases.Articles were excluded if they focused on treatment, survival, or surgical menopause, or lacked control groups, or if they were case report or case series, editorial, narrative review, letter to the editor or correspondence, and non-English articles.


### 2.3. Data Extraction

Two investigators (L.H. and X.D.) independently extracted data from each qualified article, which were typed into a standardized Excel spreadsheet, including the following items: name of first author, publication year, country where study was conducted, sample size, method for mortality ascertainment, baseline age, follow-up period, study design, study type, numbers of deaths, effect-size estimate, and other traditional risk factors, where available, including education, body mass index (BMI), and estrogen therapy. Any disagreement was resolved by a joint reevaluation of original article and, when necessary, was adjudicated by a third author (W. N.).


### 2.4. Quality Appraisal

The quality of the included cohort studies was appraised by means of the NOS (Newcastle-Ottawa Quality Assessment Scale) [15], which is calculated on the basis of three major components: selection of the groups of study (0-4 points), quality of the adjustment for confounding (0-2 points), and ascertainment of the exposure or outcome of interest in the case-control or cohorts, respectively (0-3 points). The maximum score is 9 points, which represents the highest methodological quality.


### 2.5. Statistical Analyses

We employed the STATA software (Stata Corp, College Station, TX, version 14.1 for Windows) for statistical analyses. The effect-size estimates for the association of early age at natural menopause with the risk for cardiovascular or all-cause mortality were summarized as HR or RR with 95% CI under the random-effects models.The inconsistency index (I2) was used to assess between-study heterogeneity, and it represents the per cent of observed diversity between studies that is a consequence of heterogeneity other than a chance observation. Significant heterogeneity is recorded if the I2 is over 50%, and a higher value denotes a higher degree of heterogeneity.As there are various sources of heterogeneity, a wide panel of subgroups analyses were conducted by region, follow-up period, and age at menopause, respectively. We quantified the probability of publication bias by means of the Begg’s funnel plots [16] and Egger regression asymmetry tests [17]. The trim-and-fill method was also used to estimate the number of potentially missing studies in the current meta-analysis. Significant publication bias is recorded if the probability of Egger’s tests is below 10%.


## 2.1. Search Strategy

We completed literature search as of August 4, 2020, by reviewing PubMed, HuGE Navigator, EMBASE (Excerpt Medica Database), and Web of Science databases. Only published articles written in the English language were considered in the current meta-analysis. The following medical subject heading terms were used: (premenopausal OR early menopause OR perimenopausal OR premature menopause OR menopause OR late menopause OR natural menopause OR postmenopause OR age at menopause OR menopausal age) [Title/Abstract] AND (cardiovascular risk OR coronary heart disease OR cardiovascular disease OR cardiovascular OR all-cause mortality OR cardiovascular mortality) [Title/Abstract]. The reference lists of retrieved articles were also hand searched for potential missing hits.Two investigators (L.H. and X.D.) independently reviewed all retrieved articles and carefully assessed preliminary eligibility based on the title and abstract, as well as full text when necessary.


## 2.2. Inclusion and Exclusion Criteria

We restricted our analysis to articles that fulfilled the following inclusion criteria: (i) natural menopause; (ii) without estrogen therapy; (iii) multivariate-adjusted hazard ratio (HR) or relative risk (RR) with 95% confidence interval (CI) for quantifying the association of age at natural menopause with cardiovascular or all-cause mortality; (iv) prospective design; (v) all-cause mortality verified by death certificates or medical records; (vi) study subjects free of major underlying diseases.Articles were excluded if they focused on treatment, survival, or surgical menopause, or lacked control groups, or if they were case report or case series, editorial, narrative review, letter to the editor or correspondence, and non-English articles.


## 2.3. Data Extraction

Two investigators (L.H. and X.D.) independently extracted data from each qualified article, which were typed into a standardized Excel spreadsheet, including the following items: name of first author, publication year, country where study was conducted, sample size, method for mortality ascertainment, baseline age, follow-up period, study design, study type, numbers of deaths, effect-size estimate, and other traditional risk factors, where available, including education, body mass index (BMI), and estrogen therapy. Any disagreement was resolved by a joint reevaluation of original article and, when necessary, was adjudicated by a third author (W. N.).


## 2.4. Quality Appraisal

The quality of the included cohort studies was appraised by means of the NOS (Newcastle-Ottawa Quality Assessment Scale) [15], which is calculated on the basis of three major components: selection of the groups of study (0-4 points), quality of the adjustment for confounding (0-2 points), and ascertainment of the exposure or outcome of interest in the case-control or cohorts, respectively (0-3 points). The maximum score is 9 points, which represents the highest methodological quality.


## 2.5. Statistical Analyses

We employed the STATA software (Stata Corp, College Station, TX, version 14.1 for Windows) for statistical analyses. The effect-size estimates for the association of early age at natural menopause with the risk for cardiovascular or all-cause mortality were summarized as HR or RR with 95% CI under the random-effects models.The inconsistency index (I2) was used to assess between-study heterogeneity, and it represents the per cent of observed diversity between studies that is a consequence of heterogeneity other than a chance observation. Significant heterogeneity is recorded if the I2 is over 50%, and a higher value denotes a higher degree of heterogeneity.As there are various sources of heterogeneity, a wide panel of subgroups analyses were conducted by region, follow-up period, and age at menopause, respectively. We quantified the probability of publication bias by means of the Begg’s funnel plots [16] and Egger regression asymmetry tests [17]. The trim-and-fill method was also used to estimate the number of potentially missing studies in the current meta-analysis. Significant publication bias is recorded if the probability of Egger’s tests is below 10%.


## 3. Results

### 3.1. Eligible Studies

After searching four public databases using predefined subject heading terms, we obtained a total of 4,472 articles, and 16 of them involving 321,233 women that assessed the association of early age at natural menopause with all-cause or cardiovascular mortality were eligible for inclusion in the current meta-analysis [12, 18–31].The detailed selection process is presented in Figure1.Figure 1
Flow chart of records retrieved, screened, and included in this meta-analysis.


### 3.2. Study Characteristics

Out of 16 eligible articles, only cardiovascular mortality was reported by 2 articles [25, 26], all-cause mortality by 7 articles [19, 23, 24, 27–29, 31], and both by 7 articles [10, 12, 18, 20–22, 30]. Ten studies [10, 18–23, 25, 26, 30] reported HR as effect-size estimates, and RR by 6 studies [12, 24, 27–29, 31], as shown in Table 1. According to statistical methods used, 14 articles [10, 12, 18–23, 25–27, 29–31] used Cox proportional hazards model, 1 article [24] used Poisson regression procedures, and 1 article [28] used logistic regression model (Table 2). The NOS scores ranged from 5 to 8 (Table 3).Table 1
The baseline characteristics of all involved studies in this meta-analysis.
YearFirst authorCountrySample sizeAge (years)Follow-up (years)Ascertainment of mortalityTotal deathsCVD deathsExposure (years)Ref (years)Effect estimateAdjustmentHR (95% CI) (all-cause)HR (95% CI) (CVD)2002KleijnNetherlands945035-6620.5Death certificates24391063>44 and ≤48≤44HRNo—0.78 (0.65-0.94)2002KleijnNetherlands945035-6620.5Death certificates24391063>44 and ≤48≤44HRYes—0.77 (0.64-0.93)2002KleijnNetherlands945035-6620.5Death certificates24391063>48 and ≤51≤44HRNo—0.92 (0.78-1.09)2002KleijnNetherlands945035-6620.5Death certificates24391063>48 and ≤51≤44HRYes—0.92 (0.78-1.09)2006AmagaiJapan468336-899.2Death certificates215—<4045-49HRNo2.75 (1.19-6.36)—2006AmagaiJapan468336-899.2Death certificates215—<4045-49HRYes2.77 (1.16-6.58)—2006AmagaiJapan468336-899.2Death certificates215—40-4445-49HRNo0.67 (0.34-1.30)—2006AmagaiJapan468336-899.2Death certificates215—40-4445-49HRYes0.53 (0.24-1.17)—2006CuiJapan3796540-7910International classification of disease—1010≤44≥51HRNo—1.07 (0.88-1.32)2006CuiJapan3796540-7910International classification of disease—1010≤44≥51HRYes—1.08 (0.88-1.34)2006CuiJapan3796540-7910International classification of disease—101045-46≥51HRNo—0.96 (0.77-1.19)2006CuiJapan3796540-7910International classification of disease—101045-46≥51HRYes—0.97 (0.78-1.21)2006CuiJapan3796540-7910International classification of disease—101047-48≥51HRNo—1.12 (0.93-1.34)2006CuiJapan3796540-7910International classification of disease—101047-48≥51HRYes—1.10 (0.92-1.32)2006CuiJapan3796540-7910International classification of disease—101049-50≥51HRNo—0.92 (0.78-1.09)2006CuiJapan3796540-7910International classification of disease—101049-50≥51HRYes—0.91 (0.77-1.97)2007HongKorea2658≥5515.8Statistics on the causes of death of Korea1193297<4045-49HRNo1.33 (1.07-1.65)—2007HongKorea2658≥5515.8Statistics on the causes of death of Korea1193297<4045-49HRYes1.32 (1.05-1.66)—2007HongKorea2658≥5515.8Statistics on the causes of death of Korea1193297<4045-49HRNo—1.58 (1.04-2.41)2007HongKorea2658≥5515.8Statistics on the causes of death of Korea1193297<4045-49HRYes—1.53 (1.01-2.39)2007HongKorea2658≥5515.8Statistics on the causes of death of Korea119329740-4445-49HRNo1.13 (0.97-1.32)—2007HongKorea2658≥5515.8Statistics on the causes of death of Korea119329740-4445-49HRYes1.13 (0.97-1.34)—2007HongKorea2658≥5515.8Statistics on the causes of death of Korea119329740-4445-49HRNo—1.17 (0.84-1.62)2007HongKorea2658≥5515.8Statistics on the causes of death of Korea119329740-4445-49HRYes—1.15 (0.82-1.60)2012TomUSA1684≥6524National death index14771231<4550-54HRNo0.89 (0.74-1.07)—2012TomUSA1684≥6524National death index14771231<4550-54HRYes0.88 (0.73-1.06)—2012TomUSA1684≥6524National death index14771231<4550-54HRNo—0.97 (0.76-1.24)2012TomUSA1684≥6524National death index14771231<4550-54HRYes—0.96 (0.75-1.23)2012TomUSA1684≥6524National death index1477123145-4950-54HRNo0.95 (0.82-1.10)—2012TomUSA1684≥6524National death index1477123145-4950-54HRYes0.96 (0.83-1.12)—2012TomUSA1684≥6524National death index1477123145-4950-54HRNo—0.93 (0.76-1.24)2012TomUSA1684≥6524National death index1477123145-4950-54HRYes—0.95 (0.77-1.16)2014WuChina3195540-7011.2Medical records31581001<46.6448.80-50.15HRNo1.17 (1.05-1.31)—2014WuChina3195540-7011.2Medical records31581001<46.6448.80-50.15HRYes1.16 (1.04-1.29)—2014WuChina3195540-7011.2Medical records31581001<46.6448.80-50.15HRNo—1.03 (0.85-1.24)2014WuChina3195540-7011.2Medical records31581001<46.6448.80-50.15HRYes—1.01 (0.83-1.22)2014WuChina3195540-7011.2Medical records3158100146.64-48.7948.80-50.15HRNo1.04 (0.93-1.17)—2014WuChina3195540-7011.2Medical records3158100146.64-48.7948.80-50.15HRYes1.03 (0.92-1.15)—2014WuChina3195540-7011.2Medical records3158100146.64-48.7948.80-50.15HRNo—0.92 (0.76-1.11)2014WuChina3195540-7011.2Medical records3158100146.64-48.7948.80-50.15HRYes—0.90 (0.74-1.09)2018LayBrazil868≥7016Death certificates444199≤4050-54HRNo1.27 (0.88-1.83)—2018LayBrazil868≥7016Death certificates444199≤4050-54HRYes1.18 (0.79-1.76)—2018LayBrazil868≥7016Death certificates444199≤4050-54HRNo—1.17 (0.65-2.09)2018LayBrazil868≥7016Death certificates444199≤4050-54HRYes—1.03 (0.57-1.86)2018LayBrazil868≥7016Death certificates44419941-4450-54HRNo1.38 (0.94-2.03)—2018LayBrazil868≥7016Death certificates44419941-4450-54HRYes1.48 (1.03-2.14)—2018LayBrazil868≥7016Death certificates44419941-4450-54HRNo—0.83 (0.38-1.78)2018LayBrazil868≥7016Death certificates44419941-4450-54HRYes—0.89 (0.41-1.93)2018LayBrazil868≥7016Death certificates44419945-4950-54HRNo1.17 (0.87-1.58)—2018LayBrazil868≥7016Death certificates44419945-4950-54HRYes1.11 (0.81-1.52)—2018LayBrazil868≥7016Death certificates44419945-4950-54HRNo—1.09 (0.72-1.66)2018LayBrazil868≥7016Death certificates44419945-4950-54HRYes—1.04 (0.67-1.60)2019MalekUSA11287≥457.1Social security death index and National Death Index1524—<45≥45HRNo1.17 (1.06-1.30)—2019MalekUSA11287≥457.1Social security death index and National Death Index1524—<45≥45HRYes1.03 (0.93-1.14)—2019ZhangUSA7535950-7813Death certificates78261584≤4445-54HRNo1.24 (1.18-1.30)—2019ZhangUSA7535950-7813Death certificates78261584≤4445-54HRYes1.12 (1.05-1.18)—2019ZhangUSA7535950-7813Death certificates78261584≤4445-54HRNo—1.32 (1.18-1.47)2019ZhangUSA7535950-7813Death certificates78261584≤4445-54HRYes—1.14 (1.01-1.30)2020ShenTaiwan3693161(mean)14.6National Death Index53161141<40-4450-54HRNo1.10 (1.00-1.21)—2020ShenTaiwan369316114.6National death index53161141<40-4450-54HRYes1.09 (0.99-1.20)—2020ShenTaiwan369316114.6National death index53161141<40-4450-54HRNo—1.06 (0.85-1.31)2020ShenTaiwan369316114.6National death index53161141<40-4450-54HRYes—1.05 (0.85-1.30)2020ShenTaiwan369316114.6National death index5316114145-4950-54HRNo1.08 (1.01-1.15)—2020ShenTaiwan369316114.6National death index5316114145-4950-54HRYes1.07 (1.01-1.14)—2020ShenTaiwan369316114.6National death index5316114145-4950-54HRNo—1.21 (1.06-1.39)2020ShenTaiwan369316114.6National death index5316114145-4950-54HRYes—1.22 (1.07-1.40)1998CooperUSA319150-864Death certificates345—<4045-49RRYes1.56 (1.07-2.27)—1998CooperUSA319150-864Death certificates345—40-4445-49RRYes1.10 (0.80-1.51)—1999JacobsenUSA5279≥2513Death certificates1831—35-4049-51RRYes1.30 (1.10-1.50)—1999JacobsenUSA5279≥2513Death certificates1831—41-4449-51RRYes0.90 (0.80-1.10)—1999JacobsenUSA5279≥2513Death certificates1831—45-4849-51RRYes0.99 (0.90-1.10)—2000CooperUSA82663-8155Death certificates108—28-45≥51RRYes1.39 (0.63-3.04)—2000CooperUSA82663-8155Death certificates108—46-50≥51RRYes1.38 (0.86-2.22)—2003JacobsenNorway1973132-7437Official personal registration18533—≤4050-52RRYes1.06 (0.99-1.14)—2003JacobsenNorway1973132-7437Official personal registration18533—41-4350-52RRYes1.02 (0.96-1.09)—2003JacobsenNorway1973132-7437Official personal registration18533—44-4650-52RRYes1.05 (1.01-1.09)—2003JacobsenNorway1973132-7437Official personal registration18533—47-4950-52RRYes1.01 (0.98-1.05)—2005MondulUSA68154≥3020Death certificates23067—40-4450-54RRNo1.05 (1.01-1.09)—2005MondulUSA68154≥3020Death certificates23067—40-4450-54RRYes1.04 (1.01-1.08)—2005MondulUSA68154≥3020Death certificates23067—45-4950-54RRNo1.02 (0.99-1.05)—2005MondulUSA68154≥3020Death certificates23067—45-4950-54RRYes1.02 (1.01-1.05)—2013LiUSA1121221-6913National death index and otification from next of kin and postal692199<4050-54RRYes1.97 (1.30-2.99)—2013LiUSA1121221-6913National death index and notification from next of kin and postal692199<4050-54RRYes—1.26 (0.56-2.86)2013LiUSA1121221-6913National death index and notification from next of kin and postal69219940-4450-54RRYes1.50 (1.08-2.06)—2013LiUSA1121221-6913National death index and notification from next of kin and postal69219940-4450-54RRYes—1.04 (0.54-1.99)2013LiUSA1121221-6913National death index and notification from next of kin and postal69219945-4950-54RRYes1.13 (0.88-1.44)—2013LiUSA1121221-6913National death index and notification from next of kin and postal69219945-4950-54RRYes—1.05 (0.67-1.63)Ref: reference; RR: relative risk; HR: hazard ratio; CVD: cardiovascular disease.Table 2
The statistical methods of all involved studies in this meta-analysis.
YearFirst authorCountrySample sizeStudy typeStatistical methodAdjustment for confoundersEffect estimate2002KleijnNetherlands9450Cohort studyCox proportional hazards modelAge, hormone replacement therapy use, hypertension, BMI, and social economic class.HR2006AmagaiJapan4683Cohort studyCox proportional hazard modelAge, SBP, TC, HDL-C, history of DB, BMI, smoking, alcohol, marital status, study area, and type of menopause.HR2006CuiJapan37965Cohort studyCox proportional hazard modelAge, smoking, alcohol, marital status, type of menopause, education, hypertension, and diabetes.HR2007HongKorea2658Cohort studyCox proportional hazards modelAge, alcohol consumption, education, age at first birth, self-cognitive health level, chronic disease, marital partner, parity, age at menarche, oral contraceptive use, and hypertension.HR2012TomUSA1684Cohort studyCox proportional hazards modelAge, education, pregnancy number, age at menarche, smoking, height, weight, and use of ET.HR2014WuChina31955Cohort studyCox proportional hazard modelAge at study enrollment, BMI, WHR, education, occupation, income, regular exercise, current smoking or alcohol, marital status, age at menarche, and number of live births.HR2018LayBrazil868Cohort studyCox regression modelSocial, year of birth, education, marital status, race, reproductive, parity, smoking, number of chronic diseases, and ET.HR2019MalekUSA11287Cohort studyCox proportional hazards modelAge, race, education, medical conditions, behavioral characteristics, and type of menopause.HR2019ZhangUSA75359Cohort studyCox proportional hazards modelBaseline age, race, BMI, smoking, alcohol, marital status, education level, physical exercise, hormone replacement therapy use, CVD history, number of live births, age at first birth, and type of menopause.HR2020ShenTaiwan36931Cohort studyCox proportional hazards modelBirth cohort, education, smoking status, body mass index, hypertension, diabetes, and high blood cholesterol.HR1998CooperUSA3191Cohort studyPoisson regression proceduresAge, education, race, smoking, use of estrogen therapy, and years of follow-up.RR1999JacobsenUSA5279Cohort studyProportional hazards modelDB, hypertension, parity, age at first birth, leisure PA, education, BMI, current use of estrogen, ever-smoking, vegetarian status, and dietary pattern.RR2000CooperUSA826Cohort studyLogistic regression modelAge, smoking, use of estrogen replacement therapy, and parity.RR2003JacobsenNorway19731Cohort studyCox proportional hazards modelAttained age, county, occupation, and birth cohort.RR2005MondulUSA68154Cohort studyCox proportional hazards modelAge, race, marital status, BMI, age at menarche, parity, education, alcohol, oral contraceptive use, and exercise.RR2013LiUSA11212Cohort studyCox proportional hazard modelAge and time period, education, marital status, BMI, smoking, alcohol, PE, dietary pattern, menarche age, parity or first birth, reproductive factors, contraceptive use, lactation duration, and unilateral oophorectomy.RRRR: relative risk; HR: hazard ratio; BMI: body mass index; SBP: systolic blood pressure; CVD: cardiovascular disease; HDL-C: high-density lipoprotein cholesterol; PE: physical education; TC: total cholesterol; DB: diabetes mellitus; WHR: waist-to hip ratio; PA: physical activity.Table 3
The Newcastle-Ottawa Scale (NOS) for assessing the quality of cohort studies.
First authorYearSelectionComparabilityOutcomeRepresentative of the exposed cohortSelection of the nonexposed cohortAscertainment of exposedDemonstration that outcome of interest was no present at start of studyControl for important cohortAdditional factorsAssessment of outcomeFollow-upAdequacy of follow-upScoreCooper19981101111006Jacobsen19990011111005Cooper20000011111106Kleijn20021101111118Jacobsen20031111111108Mondul20051111111108Amagai20061101111006Cui20061101111006Hong20071111110107Tom20121101111118Li20130011111106Wu20141111111007Lay20181111111108Malek20191111110006Zhang20191111111108Shen20201101110106According to age at menopause, we divided study subjects into four subgroups: (i) younger than 40 years (premature menopause); (ii) 40-44 years (early menopause); (iii) 45-49 years (relatively early menopause); (iv) 49-52 years (reference category). According to median follow-up periods (in years), we divided data into two subgroups: (i) less than 13.8 years (HR) [19, 22, 23, 25, 30], less than 16.5 years (RR) [12, 24, 29]; (ii) more than or equal to 13.8 years (HR) [10, 18, 20, 21, 26], more than or equal to 16.5 years (RR) [27, 28, 31]. In terms of location, we grouped studies into three groups: America [12, 19–22, 24, 27–29], Europe [26, 31], and Asian [10, 18, 23, 25, 30].


### 3.3. Overall Analyses

After pooling the results of all eligible articles together, we observed a statistically significant association of early age at natural menopause with an increased risk for all-cause mortality (unadjustedHR=1.12, 95% CI: 1.05 to 1.19, P<0.001; adjustedHR=1.08, 95% CI: 1.03 to 1.14, P=0.002; unadjustedRR=1.03, 95% CI: 1.00 to 1.06, P=0.026; adjustedRR=1.05, 95% CI: 1.01 to 1.08, P=0.005) (Table 4). By contrast, no statistical significance was observed for the association between early age at natural menopause and cardiovascular mortality (unadjustedHR=1.04, 95% CI: 1.00 to 1.13, P=0.385; adjustedHR=1.01, 95% CI: 0.95 to 1.09, P=0.682; adjustedRR=1.08, 95% CI: 0.77 to 1.51, P=0.652) (Table 4). For all-cause mortality, there was no heterogeneity with the I2 of 45.6% for HR, but there was significant heterogeneity with the I2 of 60.7% for RR. For cardiovascular mortality, there was no significant evidence of heterogeneity, with the I2 of 42.1% for HR and 0.0% for RR.Table 4
Overall and subgroup analyses of early age at natural menopause with all-cause and cardiovascular mortality.
GroupStudies (n)All-cause mortalityCardiovascular mortalityEffect-size estimateHR (95% CI);PI2HR (95% CI);PI2Overall analysesMortality (unadjusted)15/181.12 (1.05-1.19); <0.00165.3%1.04 (1.00-1.13); 0.38561.7%Mortality (adjusted)15/181.08 (1.03-1.14); 0.00245.6%1.01 (0.95-1.09); 0.68242.1%Subgroup analysesBy countryAmerica7/61.05 (0.96-1.15); 0.26851.5%1.06 (0.96-1.16); 0.2350.0%EuropeNA/2NANA0.85 (0.71-1.01); 0.06048.3%Asia8/101.11 (1.03-1.18); 0.00446.7%1.05 (0.97-1.14); 0.22837.1%By follow-up<13.8 years6/71.09 (1.00-1.18); 0.04757.7%1.02 (0.95-1.10); 0.56020.6%≥13.8 years9/111.08 (1.01-1.16); 0.03640.0%1.01 (0.90-1.14); 0.81154.0%Dose-response analysis<40 years7/61.10 (1.01-1.21); 0.03460.7%1.09 (1.00-1.19); 0.0450.0%40-44 years4/31.12 (0.96-1.31); 0.14549.2%1.07 (0.90-1.27); 0.4640.0%45-49 years4/91.05 (1.00-1.10); 0.0510.0%0.97 (0.88-1.07); 0.53960.8%Effect-size estimateRR (95% CI);PI2RR (95% CI);PI2Overall analysesMortality (unadjusted)2/NA1.03 (1.00-1.06); 0.02628.2%NANAMortality (adjusted)16/31.05 (1.01-1.08); 0.00560.7%1.08 (0.77-1.51); 0.6520.0%Subgroup analysesBy countryAmerica12/31.08 (1.02-1.15); 0.01068.8%1.08 (0.77-1.51); 0.6520.0%Europe4/NA1.03 (1.01-1.08); 0.0100.0%NANAAsiaNA/NANANANANABy follow-up<16.5 years8/81.21 (1.03-1.41); 0.02076.0%1.08 (0.77-1.51); 0.6520.0%≥16.5 years3/NA1.08 (0.77-1.51); 0.6520.0%NANADose-response analysis<40 years5/11.34 (1.08-1.66); 0.00775.3%1.26 (0.56-2.85); 0.579NA40-44 years5/11.03 (0.96-1.10); 0.37752.7%1.04 (0.54-2.00); 0.906NA45-49 years6/11.02 (1.01-1.04); 0.0040.0%1.05 (0.67-1.64); 0.830NAHR: hazard ratio; RR: relative risk; 95% CI: 95% confidence interval; NA: not available.


### 3.4. Publication Bias

The possibility of publication bias was illustrated using the Begg’s funnel plots for the association of early age at natural menopause with all-cause (Figure2) and cardiovascular (Supplementary Figure 1) mortality, respectively, and they seemed symmetric. As further revealed by the Egger’s tests, in studies reporting HR, there was no evidence of publication bias for all-cause mortality (P=0.746) and cardiovascular mortality (P=0.782). By contrast, in studies reporting RR, there was strong evidence of publication bias for all-cause mortality (P=0.010), yet no publication bias for cardiovascular mortality (P=0.456).Figure 2
The Begg’s and filled funnel plots on the association of early age at natural menopause with all-cause and cardiovascular mortality in studies reporting hazard ratio (HR) as effect-size estimates. (a) Begg’s funnel plot and (b) filled funnel plot: all-cause mortality (HR). (c) Begg’s funnel plot and (d) filled funnel plot: cardiovascular mortality (HR).
(a)(b)(c)(d)As reflected by the filled funnel plots, one and six additional studies were separately required for the relationship between all-cause mortality and early age at natural menopause in studies reporting HR and RR. For cardiovascular mortality, no study was missing for studies reporting HR and RR.After adjusting for potential missing studies, effect-size estimates were still statistically significant for all-cause mortality (HR=1.08, 95% CI: 1.03 to 1.14, P=0.002). On the contrary, even if the funnel plots were further filled to make the cardiovascular mortality plot symmetric, after adjustment for potential missing studies, effect-size estimates were not statistically significant for cardiovascular mortality (HR=1.01, 95% CI: 0.95 to 1.09, P=0.682; RR=1.08, 95% CI: 0.77 to 1.51, P=0.652).


### 3.5. Subgroup Analyses

We subsequently conducted a large panel of subgroup analyses, because theI2 suggested the possible existence of between-study heterogeneity (Table 4).By geographic location, in studies reporting HR, the association between early age at natural menopause and all-cause mortality was statistically significant in Asian countries (HR=1.11, 95% CI: 1.03 to 1.18, P=0.004), but not in American countries (HR=1.05, 95% CI: 0.96 to 1.15, P=0.268). In studies reporting RR, the association between early age at natural menopause and all-cause mortality was statistically significant in both American countries (RR=1.08, 95% CI: 1.02 to 1.15, P=0.010) and European countries (RR=1.03, 95% CI: 1.01 to 1.08, P=0.010) (Two-sample Z test P=0.088). However, the association between early age at natural menopause and cardiovascular mortality was not statistically significant in American (HR=1.06, 95% CI: 0.97 to 1.16, P=0.235; RR=1.08, 95% CI: 0.77 to 1.51, P=0.652), Europe (HR=0.85, 95% CI: 0.71 to 1.01, P=0.060), and Asian (HR=1.05, 95% CI: 0.97 to 1.14, P=0.228) countries.In studies reporting HR, by the median value (13.8 years) of follow-up intervals, the association of early age at natural menopause with all-cause mortality was significant in both short (<13.8 years) (HR=1.09, 95% CI: 1.00 to 1.18, P=0.047) and long (≥13.8 years) (HR=1.08, 95% CI: 1.01 to 1.16, P=0.036) follow-ups. By contrary, in studies reporting RR, by the median value (16.5 years) of follow-up intervals, the association of early age at natural menopause with all-cause mortality was significant in short (<16.5 years) (RR=1.21, 95% CI: 1.03 to 1.41, P=0.020), but not in long (≥16.5years) (RR=1.08, 95% CI: 0.77 to 1.51, P=0.652) follow-ups. The association of early age at natural menopause with cardiovascular mortality was not significant in long (≥13.8 years) (HR=1.01, 95% CI: 0.90 to 1.14, P=0.811) and short (<13.8 years) (HR=1.02, 95% CI: 0.95 to 1.10, P=0.560) follow-ups in studies reporting HR. Meanwhile, in studies reporting RR, the association of early age at natural menopause with cardiovascular mortality was not significant.


### 3.6. Dose-Response Analyses

In the dose-response analysis of all-cause mortality in studies reporting HR, the association of premature menopause with all-cause mortality was significant (HR=1.10, 95% CI: 1.01 to 1.21, P=0.034), but not for early (HR=1.12, 95% CI: 0.96 to 1.31, P=0.145) and relatively early menopause (HR=1.05, 95% CI: 1.00 to 1.10, P=0.051). In studies reporting RR, women with premature menopause (RR=1.34, 95% CI: 1.08 to 1.66, P=0.007) had a higher risk than women with relatively early menopause (RR=1.02, 95% CI: 1.01 to 1.04, P=0.004) (Two-sample Z test P=0.010) for all-cause mortality.In the dose-response analysis of cardiovascular mortality in studies reporting HR, the association was only significant for premature menopause (HR=1.09, 95% CI: 1.00 to 1.19, P=0.045). However, in studies reporting RR, no statistical significance was observed across age groups in cardiovascular mortality (<40 years: RR=1.26, 95% CI: 0.56 to 2.85, P=0.579; 40-44 years: RR=1.04, 95% CI: 0.54 to 2.00, P=0.906; 45-49 years: RR=1.05, 95% CI: 0.67 to 1.64, P=0.830).


## 3.1. Eligible Studies

After searching four public databases using predefined subject heading terms, we obtained a total of 4,472 articles, and 16 of them involving 321,233 women that assessed the association of early age at natural menopause with all-cause or cardiovascular mortality were eligible for inclusion in the current meta-analysis [12, 18–31].The detailed selection process is presented in Figure1.Figure 1
Flow chart of records retrieved, screened, and included in this meta-analysis.


## 3.2. Study Characteristics

Out of 16 eligible articles, only cardiovascular mortality was reported by 2 articles [25, 26], all-cause mortality by 7 articles [19, 23, 24, 27–29, 31], and both by 7 articles [10, 12, 18, 20–22, 30]. Ten studies [10, 18–23, 25, 26, 30] reported HR as effect-size estimates, and RR by 6 studies [12, 24, 27–29, 31], as shown in Table 1. According to statistical methods used, 14 articles [10, 12, 18–23, 25–27, 29–31] used Cox proportional hazards model, 1 article [24] used Poisson regression procedures, and 1 article [28] used logistic regression model (Table 2). The NOS scores ranged from 5 to 8 (Table 3).Table 1
The baseline characteristics of all involved studies in this meta-analysis.
YearFirst authorCountrySample sizeAge (years)Follow-up (years)Ascertainment of mortalityTotal deathsCVD deathsExposure (years)Ref (years)Effect estimateAdjustmentHR (95% CI) (all-cause)HR (95% CI) (CVD)2002KleijnNetherlands945035-6620.5Death certificates24391063>44 and ≤48≤44HRNo—0.78 (0.65-0.94)2002KleijnNetherlands945035-6620.5Death certificates24391063>44 and ≤48≤44HRYes—0.77 (0.64-0.93)2002KleijnNetherlands945035-6620.5Death certificates24391063>48 and ≤51≤44HRNo—0.92 (0.78-1.09)2002KleijnNetherlands945035-6620.5Death certificates24391063>48 and ≤51≤44HRYes—0.92 (0.78-1.09)2006AmagaiJapan468336-899.2Death certificates215—<4045-49HRNo2.75 (1.19-6.36)—2006AmagaiJapan468336-899.2Death certificates215—<4045-49HRYes2.77 (1.16-6.58)—2006AmagaiJapan468336-899.2Death certificates215—40-4445-49HRNo0.67 (0.34-1.30)—2006AmagaiJapan468336-899.2Death certificates215—40-4445-49HRYes0.53 (0.24-1.17)—2006CuiJapan3796540-7910International classification of disease—1010≤44≥51HRNo—1.07 (0.88-1.32)2006CuiJapan3796540-7910International classification of disease—1010≤44≥51HRYes—1.08 (0.88-1.34)2006CuiJapan3796540-7910International classification of disease—101045-46≥51HRNo—0.96 (0.77-1.19)2006CuiJapan3796540-7910International classification of disease—101045-46≥51HRYes—0.97 (0.78-1.21)2006CuiJapan3796540-7910International classification of disease—101047-48≥51HRNo—1.12 (0.93-1.34)2006CuiJapan3796540-7910International classification of disease—101047-48≥51HRYes—1.10 (0.92-1.32)2006CuiJapan3796540-7910International classification of disease—101049-50≥51HRNo—0.92 (0.78-1.09)2006CuiJapan3796540-7910International classification of disease—101049-50≥51HRYes—0.91 (0.77-1.97)2007HongKorea2658≥5515.8Statistics on the causes of death of Korea1193297<4045-49HRNo1.33 (1.07-1.65)—2007HongKorea2658≥5515.8Statistics on the causes of death of Korea1193297<4045-49HRYes1.32 (1.05-1.66)—2007HongKorea2658≥5515.8Statistics on the causes of death of Korea1193297<4045-49HRNo—1.58 (1.04-2.41)2007HongKorea2658≥5515.8Statistics on the causes of death of Korea1193297<4045-49HRYes—1.53 (1.01-2.39)2007HongKorea2658≥5515.8Statistics on the causes of death of Korea119329740-4445-49HRNo1.13 (0.97-1.32)—2007HongKorea2658≥5515.8Statistics on the causes of death of Korea119329740-4445-49HRYes1.13 (0.97-1.34)—2007HongKorea2658≥5515.8Statistics on the causes of death of Korea119329740-4445-49HRNo—1.17 (0.84-1.62)2007HongKorea2658≥5515.8Statistics on the causes of death of Korea119329740-4445-49HRYes—1.15 (0.82-1.60)2012TomUSA1684≥6524National death index14771231<4550-54HRNo0.89 (0.74-1.07)—2012TomUSA1684≥6524National death index14771231<4550-54HRYes0.88 (0.73-1.06)—2012TomUSA1684≥6524National death index14771231<4550-54HRNo—0.97 (0.76-1.24)2012TomUSA1684≥6524National death index14771231<4550-54HRYes—0.96 (0.75-1.23)2012TomUSA1684≥6524National death index1477123145-4950-54HRNo0.95 (0.82-1.10)—2012TomUSA1684≥6524National death index1477123145-4950-54HRYes0.96 (0.83-1.12)—2012TomUSA1684≥6524National death index1477123145-4950-54HRNo—0.93 (0.76-1.24)2012TomUSA1684≥6524National death index1477123145-4950-54HRYes—0.95 (0.77-1.16)2014WuChina3195540-7011.2Medical records31581001<46.6448.80-50.15HRNo1.17 (1.05-1.31)—2014WuChina3195540-7011.2Medical records31581001<46.6448.80-50.15HRYes1.16 (1.04-1.29)—2014WuChina3195540-7011.2Medical records31581001<46.6448.80-50.15HRNo—1.03 (0.85-1.24)2014WuChina3195540-7011.2Medical records31581001<46.6448.80-50.15HRYes—1.01 (0.83-1.22)2014WuChina3195540-7011.2Medical records3158100146.64-48.7948.80-50.15HRNo1.04 (0.93-1.17)—2014WuChina3195540-7011.2Medical records3158100146.64-48.7948.80-50.15HRYes1.03 (0.92-1.15)—2014WuChina3195540-7011.2Medical records3158100146.64-48.7948.80-50.15HRNo—0.92 (0.76-1.11)2014WuChina3195540-7011.2Medical records3158100146.64-48.7948.80-50.15HRYes—0.90 (0.74-1.09)2018LayBrazil868≥7016Death certificates444199≤4050-54HRNo1.27 (0.88-1.83)—2018LayBrazil868≥7016Death certificates444199≤4050-54HRYes1.18 (0.79-1.76)—2018LayBrazil868≥7016Death certificates444199≤4050-54HRNo—1.17 (0.65-2.09)2018LayBrazil868≥7016Death certificates444199≤4050-54HRYes—1.03 (0.57-1.86)2018LayBrazil868≥7016Death certificates44419941-4450-54HRNo1.38 (0.94-2.03)—2018LayBrazil868≥7016Death certificates44419941-4450-54HRYes1.48 (1.03-2.14)—2018LayBrazil868≥7016Death certificates44419941-4450-54HRNo—0.83 (0.38-1.78)2018LayBrazil868≥7016Death certificates44419941-4450-54HRYes—0.89 (0.41-1.93)2018LayBrazil868≥7016Death certificates44419945-4950-54HRNo1.17 (0.87-1.58)—2018LayBrazil868≥7016Death certificates44419945-4950-54HRYes1.11 (0.81-1.52)—2018LayBrazil868≥7016Death certificates44419945-4950-54HRNo—1.09 (0.72-1.66)2018LayBrazil868≥7016Death certificates44419945-4950-54HRYes—1.04 (0.67-1.60)2019MalekUSA11287≥457.1Social security death index and National Death Index1524—<45≥45HRNo1.17 (1.06-1.30)—2019MalekUSA11287≥457.1Social security death index and National Death Index1524—<45≥45HRYes1.03 (0.93-1.14)—2019ZhangUSA7535950-7813Death certificates78261584≤4445-54HRNo1.24 (1.18-1.30)—2019ZhangUSA7535950-7813Death certificates78261584≤4445-54HRYes1.12 (1.05-1.18)—2019ZhangUSA7535950-7813Death certificates78261584≤4445-54HRNo—1.32 (1.18-1.47)2019ZhangUSA7535950-7813Death certificates78261584≤4445-54HRYes—1.14 (1.01-1.30)2020ShenTaiwan3693161(mean)14.6National Death Index53161141<40-4450-54HRNo1.10 (1.00-1.21)—2020ShenTaiwan369316114.6National death index53161141<40-4450-54HRYes1.09 (0.99-1.20)—2020ShenTaiwan369316114.6National death index53161141<40-4450-54HRNo—1.06 (0.85-1.31)2020ShenTaiwan369316114.6National death index53161141<40-4450-54HRYes—1.05 (0.85-1.30)2020ShenTaiwan369316114.6National death index5316114145-4950-54HRNo1.08 (1.01-1.15)—2020ShenTaiwan369316114.6National death index5316114145-4950-54HRYes1.07 (1.01-1.14)—2020ShenTaiwan369316114.6National death index5316114145-4950-54HRNo—1.21 (1.06-1.39)2020ShenTaiwan369316114.6National death index5316114145-4950-54HRYes—1.22 (1.07-1.40)1998CooperUSA319150-864Death certificates345—<4045-49RRYes1.56 (1.07-2.27)—1998CooperUSA319150-864Death certificates345—40-4445-49RRYes1.10 (0.80-1.51)—1999JacobsenUSA5279≥2513Death certificates1831—35-4049-51RRYes1.30 (1.10-1.50)—1999JacobsenUSA5279≥2513Death certificates1831—41-4449-51RRYes0.90 (0.80-1.10)—1999JacobsenUSA5279≥2513Death certificates1831—45-4849-51RRYes0.99 (0.90-1.10)—2000CooperUSA82663-8155Death certificates108—28-45≥51RRYes1.39 (0.63-3.04)—2000CooperUSA82663-8155Death certificates108—46-50≥51RRYes1.38 (0.86-2.22)—2003JacobsenNorway1973132-7437Official personal registration18533—≤4050-52RRYes1.06 (0.99-1.14)—2003JacobsenNorway1973132-7437Official personal registration18533—41-4350-52RRYes1.02 (0.96-1.09)—2003JacobsenNorway1973132-7437Official personal registration18533—44-4650-52RRYes1.05 (1.01-1.09)—2003JacobsenNorway1973132-7437Official personal registration18533—47-4950-52RRYes1.01 (0.98-1.05)—2005MondulUSA68154≥3020Death certificates23067—40-4450-54RRNo1.05 (1.01-1.09)—2005MondulUSA68154≥3020Death certificates23067—40-4450-54RRYes1.04 (1.01-1.08)—2005MondulUSA68154≥3020Death certificates23067—45-4950-54RRNo1.02 (0.99-1.05)—2005MondulUSA68154≥3020Death certificates23067—45-4950-54RRYes1.02 (1.01-1.05)—2013LiUSA1121221-6913National death index and otification from next of kin and postal692199<4050-54RRYes1.97 (1.30-2.99)—2013LiUSA1121221-6913National death index and notification from next of kin and postal692199<4050-54RRYes—1.26 (0.56-2.86)2013LiUSA1121221-6913National death index and notification from next of kin and postal69219940-4450-54RRYes1.50 (1.08-2.06)—2013LiUSA1121221-6913National death index and notification from next of kin and postal69219940-4450-54RRYes—1.04 (0.54-1.99)2013LiUSA1121221-6913National death index and notification from next of kin and postal69219945-4950-54RRYes1.13 (0.88-1.44)—2013LiUSA1121221-6913National death index and notification from next of kin and postal69219945-4950-54RRYes—1.05 (0.67-1.63)Ref: reference; RR: relative risk; HR: hazard ratio; CVD: cardiovascular disease.Table 2
The statistical methods of all involved studies in this meta-analysis.
YearFirst authorCountrySample sizeStudy typeStatistical methodAdjustment for confoundersEffect estimate2002KleijnNetherlands9450Cohort studyCox proportional hazards modelAge, hormone replacement therapy use, hypertension, BMI, and social economic class.HR2006AmagaiJapan4683Cohort studyCox proportional hazard modelAge, SBP, TC, HDL-C, history of DB, BMI, smoking, alcohol, marital status, study area, and type of menopause.HR2006CuiJapan37965Cohort studyCox proportional hazard modelAge, smoking, alcohol, marital status, type of menopause, education, hypertension, and diabetes.HR2007HongKorea2658Cohort studyCox proportional hazards modelAge, alcohol consumption, education, age at first birth, self-cognitive health level, chronic disease, marital partner, parity, age at menarche, oral contraceptive use, and hypertension.HR2012TomUSA1684Cohort studyCox proportional hazards modelAge, education, pregnancy number, age at menarche, smoking, height, weight, and use of ET.HR2014WuChina31955Cohort studyCox proportional hazard modelAge at study enrollment, BMI, WHR, education, occupation, income, regular exercise, current smoking or alcohol, marital status, age at menarche, and number of live births.HR2018LayBrazil868Cohort studyCox regression modelSocial, year of birth, education, marital status, race, reproductive, parity, smoking, number of chronic diseases, and ET.HR2019MalekUSA11287Cohort studyCox proportional hazards modelAge, race, education, medical conditions, behavioral characteristics, and type of menopause.HR2019ZhangUSA75359Cohort studyCox proportional hazards modelBaseline age, race, BMI, smoking, alcohol, marital status, education level, physical exercise, hormone replacement therapy use, CVD history, number of live births, age at first birth, and type of menopause.HR2020ShenTaiwan36931Cohort studyCox proportional hazards modelBirth cohort, education, smoking status, body mass index, hypertension, diabetes, and high blood cholesterol.HR1998CooperUSA3191Cohort studyPoisson regression proceduresAge, education, race, smoking, use of estrogen therapy, and years of follow-up.RR1999JacobsenUSA5279Cohort studyProportional hazards modelDB, hypertension, parity, age at first birth, leisure PA, education, BMI, current use of estrogen, ever-smoking, vegetarian status, and dietary pattern.RR2000CooperUSA826Cohort studyLogistic regression modelAge, smoking, use of estrogen replacement therapy, and parity.RR2003JacobsenNorway19731Cohort studyCox proportional hazards modelAttained age, county, occupation, and birth cohort.RR2005MondulUSA68154Cohort studyCox proportional hazards modelAge, race, marital status, BMI, age at menarche, parity, education, alcohol, oral contraceptive use, and exercise.RR2013LiUSA11212Cohort studyCox proportional hazard modelAge and time period, education, marital status, BMI, smoking, alcohol, PE, dietary pattern, menarche age, parity or first birth, reproductive factors, contraceptive use, lactation duration, and unilateral oophorectomy.RRRR: relative risk; HR: hazard ratio; BMI: body mass index; SBP: systolic blood pressure; CVD: cardiovascular disease; HDL-C: high-density lipoprotein cholesterol; PE: physical education; TC: total cholesterol; DB: diabetes mellitus; WHR: waist-to hip ratio; PA: physical activity.Table 3
The Newcastle-Ottawa Scale (NOS) for assessing the quality of cohort studies.
First authorYearSelectionComparabilityOutcomeRepresentative of the exposed cohortSelection of the nonexposed cohortAscertainment of exposedDemonstration that outcome of interest was no present at start of studyControl for important cohortAdditional factorsAssessment of outcomeFollow-upAdequacy of follow-upScoreCooper19981101111006Jacobsen19990011111005Cooper20000011111106Kleijn20021101111118Jacobsen20031111111108Mondul20051111111108Amagai20061101111006Cui20061101111006Hong20071111110107Tom20121101111118Li20130011111106Wu20141111111007Lay20181111111108Malek20191111110006Zhang20191111111108Shen20201101110106According to age at menopause, we divided study subjects into four subgroups: (i) younger than 40 years (premature menopause); (ii) 40-44 years (early menopause); (iii) 45-49 years (relatively early menopause); (iv) 49-52 years (reference category). According to median follow-up periods (in years), we divided data into two subgroups: (i) less than 13.8 years (HR) [19, 22, 23, 25, 30], less than 16.5 years (RR) [12, 24, 29]; (ii) more than or equal to 13.8 years (HR) [10, 18, 20, 21, 26], more than or equal to 16.5 years (RR) [27, 28, 31]. In terms of location, we grouped studies into three groups: America [12, 19–22, 24, 27–29], Europe [26, 31], and Asian [10, 18, 23, 25, 30].


## 3.3. Overall Analyses

After pooling the results of all eligible articles together, we observed a statistically significant association of early age at natural menopause with an increased risk for all-cause mortality (unadjustedHR=1.12, 95% CI: 1.05 to 1.19, P<0.001; adjustedHR=1.08, 95% CI: 1.03 to 1.14, P=0.002; unadjustedRR=1.03, 95% CI: 1.00 to 1.06, P=0.026; adjustedRR=1.05, 95% CI: 1.01 to 1.08, P=0.005) (Table 4). By contrast, no statistical significance was observed for the association between early age at natural menopause and cardiovascular mortality (unadjustedHR=1.04, 95% CI: 1.00 to 1.13, P=0.385; adjustedHR=1.01, 95% CI: 0.95 to 1.09, P=0.682; adjustedRR=1.08, 95% CI: 0.77 to 1.51, P=0.652) (Table 4). For all-cause mortality, there was no heterogeneity with the I2 of 45.6% for HR, but there was significant heterogeneity with the I2 of 60.7% for RR. For cardiovascular mortality, there was no significant evidence of heterogeneity, with the I2 of 42.1% for HR and 0.0% for RR.Table 4
Overall and subgroup analyses of early age at natural menopause with all-cause and cardiovascular mortality.
GroupStudies (n)All-cause mortalityCardiovascular mortalityEffect-size estimateHR (95% CI);PI2HR (95% CI);PI2Overall analysesMortality (unadjusted)15/181.12 (1.05-1.19); <0.00165.3%1.04 (1.00-1.13); 0.38561.7%Mortality (adjusted)15/181.08 (1.03-1.14); 0.00245.6%1.01 (0.95-1.09); 0.68242.1%Subgroup analysesBy countryAmerica7/61.05 (0.96-1.15); 0.26851.5%1.06 (0.96-1.16); 0.2350.0%EuropeNA/2NANA0.85 (0.71-1.01); 0.06048.3%Asia8/101.11 (1.03-1.18); 0.00446.7%1.05 (0.97-1.14); 0.22837.1%By follow-up<13.8 years6/71.09 (1.00-1.18); 0.04757.7%1.02 (0.95-1.10); 0.56020.6%≥13.8 years9/111.08 (1.01-1.16); 0.03640.0%1.01 (0.90-1.14); 0.81154.0%Dose-response analysis<40 years7/61.10 (1.01-1.21); 0.03460.7%1.09 (1.00-1.19); 0.0450.0%40-44 years4/31.12 (0.96-1.31); 0.14549.2%1.07 (0.90-1.27); 0.4640.0%45-49 years4/91.05 (1.00-1.10); 0.0510.0%0.97 (0.88-1.07); 0.53960.8%Effect-size estimateRR (95% CI);PI2RR (95% CI);PI2Overall analysesMortality (unadjusted)2/NA1.03 (1.00-1.06); 0.02628.2%NANAMortality (adjusted)16/31.05 (1.01-1.08); 0.00560.7%1.08 (0.77-1.51); 0.6520.0%Subgroup analysesBy countryAmerica12/31.08 (1.02-1.15); 0.01068.8%1.08 (0.77-1.51); 0.6520.0%Europe4/NA1.03 (1.01-1.08); 0.0100.0%NANAAsiaNA/NANANANANABy follow-up<16.5 years8/81.21 (1.03-1.41); 0.02076.0%1.08 (0.77-1.51); 0.6520.0%≥16.5 years3/NA1.08 (0.77-1.51); 0.6520.0%NANADose-response analysis<40 years5/11.34 (1.08-1.66); 0.00775.3%1.26 (0.56-2.85); 0.579NA40-44 years5/11.03 (0.96-1.10); 0.37752.7%1.04 (0.54-2.00); 0.906NA45-49 years6/11.02 (1.01-1.04); 0.0040.0%1.05 (0.67-1.64); 0.830NAHR: hazard ratio; RR: relative risk; 95% CI: 95% confidence interval; NA: not available.


## 3.4. Publication Bias

The possibility of publication bias was illustrated using the Begg’s funnel plots for the association of early age at natural menopause with all-cause (Figure2) and cardiovascular (Supplementary Figure 1) mortality, respectively, and they seemed symmetric. As further revealed by the Egger’s tests, in studies reporting HR, there was no evidence of publication bias for all-cause mortality (P=0.746) and cardiovascular mortality (P=0.782). By contrast, in studies reporting RR, there was strong evidence of publication bias for all-cause mortality (P=0.010), yet no publication bias for cardiovascular mortality (P=0.456).Figure 2
The Begg’s and filled funnel plots on the association of early age at natural menopause with all-cause and cardiovascular mortality in studies reporting hazard ratio (HR) as effect-size estimates. (a) Begg’s funnel plot and (b) filled funnel plot: all-cause mortality (HR). (c) Begg’s funnel plot and (d) filled funnel plot: cardiovascular mortality (HR).
(a)(b)(c)(d)As reflected by the filled funnel plots, one and six additional studies were separately required for the relationship between all-cause mortality and early age at natural menopause in studies reporting HR and RR. For cardiovascular mortality, no study was missing for studies reporting HR and RR.After adjusting for potential missing studies, effect-size estimates were still statistically significant for all-cause mortality (HR=1.08, 95% CI: 1.03 to 1.14, P=0.002). On the contrary, even if the funnel plots were further filled to make the cardiovascular mortality plot symmetric, after adjustment for potential missing studies, effect-size estimates were not statistically significant for cardiovascular mortality (HR=1.01, 95% CI: 0.95 to 1.09, P=0.682; RR=1.08, 95% CI: 0.77 to 1.51, P=0.652).


## 3.5. Subgroup Analyses

We subsequently conducted a large panel of subgroup analyses, because theI2 suggested the possible existence of between-study heterogeneity (Table 4).By geographic location, in studies reporting HR, the association between early age at natural menopause and all-cause mortality was statistically significant in Asian countries (HR=1.11, 95% CI: 1.03 to 1.18, P=0.004), but not in American countries (HR=1.05, 95% CI: 0.96 to 1.15, P=0.268). In studies reporting RR, the association between early age at natural menopause and all-cause mortality was statistically significant in both American countries (RR=1.08, 95% CI: 1.02 to 1.15, P=0.010) and European countries (RR=1.03, 95% CI: 1.01 to 1.08, P=0.010) (Two-sample Z test P=0.088). However, the association between early age at natural menopause and cardiovascular mortality was not statistically significant in American (HR=1.06, 95% CI: 0.97 to 1.16, P=0.235; RR=1.08, 95% CI: 0.77 to 1.51, P=0.652), Europe (HR=0.85, 95% CI: 0.71 to 1.01, P=0.060), and Asian (HR=1.05, 95% CI: 0.97 to 1.14, P=0.228) countries.In studies reporting HR, by the median value (13.8 years) of follow-up intervals, the association of early age at natural menopause with all-cause mortality was significant in both short (<13.8 years) (HR=1.09, 95% CI: 1.00 to 1.18, P=0.047) and long (≥13.8 years) (HR=1.08, 95% CI: 1.01 to 1.16, P=0.036) follow-ups. By contrary, in studies reporting RR, by the median value (16.5 years) of follow-up intervals, the association of early age at natural menopause with all-cause mortality was significant in short (<16.5 years) (RR=1.21, 95% CI: 1.03 to 1.41, P=0.020), but not in long (≥16.5years) (RR=1.08, 95% CI: 0.77 to 1.51, P=0.652) follow-ups. The association of early age at natural menopause with cardiovascular mortality was not significant in long (≥13.8 years) (HR=1.01, 95% CI: 0.90 to 1.14, P=0.811) and short (<13.8 years) (HR=1.02, 95% CI: 0.95 to 1.10, P=0.560) follow-ups in studies reporting HR. Meanwhile, in studies reporting RR, the association of early age at natural menopause with cardiovascular mortality was not significant.


## 3.6. Dose-Response Analyses

In the dose-response analysis of all-cause mortality in studies reporting HR, the association of premature menopause with all-cause mortality was significant (HR=1.10, 95% CI: 1.01 to 1.21, P=0.034), but not for early (HR=1.12, 95% CI: 0.96 to 1.31, P=0.145) and relatively early menopause (HR=1.05, 95% CI: 1.00 to 1.10, P=0.051). In studies reporting RR, women with premature menopause (RR=1.34, 95% CI: 1.08 to 1.66, P=0.007) had a higher risk than women with relatively early menopause (RR=1.02, 95% CI: 1.01 to 1.04, P=0.004) (Two-sample Z test P=0.010) for all-cause mortality.In the dose-response analysis of cardiovascular mortality in studies reporting HR, the association was only significant for premature menopause (HR=1.09, 95% CI: 1.00 to 1.19, P=0.045). However, in studies reporting RR, no statistical significance was observed across age groups in cardiovascular mortality (<40 years: RR=1.26, 95% CI: 0.56 to 2.85, P=0.579; 40-44 years: RR=1.04, 95% CI: 0.54 to 2.00, P=0.906; 45-49 years: RR=1.05, 95% CI: 0.67 to 1.64, P=0.830).


## 4. Discussion

Via a comprehensive meta-analysis of 16 articles and 321,233 women, our findings indicate that premature menopause is a promising independent risk factor for both all-cause and cardiovascular mortality. Moreover, gender, country, and follow-up periods were identified as possible causes of between-study heterogeneity. To the best of our knowledge, this is the most comprehensive report that has meta-analyzed the prediction of early age at natural menopause for all-cause and cardiovascular mortality risk.In 2016, Gong and colleagues in a meta-analysis of 10 articles investigated the association of early age at natural menopause with all-cause and cardiovascular mortality risk, and they found that the earliest age at natural menopause (<40 years) was associated with a slightly increase in all-cause mortality, but not with cardiovascular and stroke-related mortality [8]. In addition, they also found that women with natural menopause before 40 years of age had an 18% greater risk of all-cause mortality, and this relationship was not statistically significant in women with natural menopause before age 46.7 years [8]. The findings of the current meta-analysis on 16 articles reinforced that of the meta-analysis by Gong and colleagues [8], by reinforcing that early age at natural menopause was associated with a slightly increased risk of all-cause mortality. However, by further subdividing age of early menopause into three groups and different reports of study results into HRs and RRs, our findings indicated that premature menopause was more strongly associated with all-cause mortality than early natural menopause and relatively early natural menopause. Extending the findings of the meta-analysis by Gong and colleagues [8], as expected, we reported that early age at natural menopause was not significantly associated with cardiovascular mortality. More importantly, using the relatively large number of eligible articles, we further explored possible causes of between-study heterogeneity by conducting a wide panel of subgroup analyses.Our finding on the association of natural menopause age before 40 years with increased all-cause mortality risk supports the hypothesis that premature natural menopause may serve as a marker of accelerated reproductive and somatic aging, as well as causing premature death [12]. Meantime, the timing of menopause reflects a complex interplay of genetic, epigenetic, socioeconomic, and lifestyle factors [32]. Several mechanisms have been proposed to interpret the association between earlier menopause and an increased risk of all-cause mortality, and the most promising reason may be lack of estrogen. Estrogens are potent vasoactive hormones that promote vascular remodeling and elasticity, and they can regulate reactive dilation and local inflammatory activity [33], as well as endothelial vasodilator dysfunction after estrogen deficiency [34, 35]. Estrogens also play a key role in the regulation of calcium homeostasis, and thus fine-tuning the normal process of cardiomyocyte contraction and relaxation [36]. Of course, it has also been suggested that this increased risk is associated with an increase in luteinizing hormone [37] or modulation of T cells [38].Epidemiological studies have shown that premature menopause before 40 years of age affects about 1% of women [4], and as demonstrated in the current meta-analysis, the risk for all-cause mortality was greatest for women with premature menopause. The possible reasons lie in that earlier loss of the ovarian function can lead to long-term activation of the renin-angiotensin-aldosterone system, endothelial dysfunction, inflammation and immune dysfunction, and further acceleration of the occurrence or progression of chronic diseases, ending with the predisposition to all-cause mortality [9, 39]. Furthermore, menopause marks the beginning of a biological mechanism caused by hormonal changes leading to tissue damage and organ dysfunction [40], and premature menopause is the earlier onset of this biological mechanism.There are several possible limitations for the current meta-analysis. Firstly, because only published articles were retrieved and the “grey” literature (articles in languages other than the English) was not incorporated, publication bias is possible. Additionally, as the number of studies reporting RR as effect-size estimates is less than 10 in this meta-analysis, the power to detect statistical significance is low [41]. Secondly, age at menopause was self-reported, and misclassification of the groups by age at menopause cannot be excluded. Thirdly, women in these studies were limited only to natural menopause, and we did not address the effect of surgical menopause or medical interventions that induced menopause-relevant mortality.


## 5. Conclusions

Our findings indicated that premature menopause is a promising independent risk factor for both all-cause and cardiovascular mortality. To date, the most effective treatment is still hormone replacement therapy, yet this method may increase the incidence of more serious concerns such as venous thromboembolism and cancer [42]. Therefore, investigations on the mechanisms and therapies between early age at menopause and all-cause mortality are also warranted.



---

*Source: 6636856-2021-03-16.xml*