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Age at menarche and its association with the metabolic syndrome in Taiwan
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Obesity Research & Clinical Practice (2015) xxx, xxx—xxx
ORIGINAL ARTICLE
Age at menarche and its association with the metabolic syndrome in Taiwan Chia-Jung Chang a,c, Ming-May Lai a,c, Cheng-Chieh Lin a,c,d,f, Chiu-Shong Liu a,c,d, Tsai-Chung Li e, Chia-Ing Li b,c, Wen-Yuan Lin a,c,d,g,∗ a
Department of Family Medicine, China Medical University Hospital, Taichung, Taiwan Department of Medical Research, China Medical University Hospital, Taichung, Taiwan c School of Medicine, China Medical University, Taichung, Taiwan d Graduate Institute of Clinical Medical Science, China Medical University, Taichung, Taiwan e Graduate Institute of Biostatistics, China Medical University, Taichung, Taiwan f Institute of Health Care Administration, Asia University, Taichung, Taiwan g Department of Family Medicine, National Taiwan University Hospital, Taipei, Taiwan b
Received 21 June 2015 ; received in revised form 17 September 2015; accepted 7 October 2015
KEYWORDS Menarche; Metabolic syndrome; Taiwan
Summary Background: The average age at menarche in the Taiwanese population is falling. Contrarily, the prevalence of metabolic syndrome (MetS) showed a worldwide increase in the past two decades. The aim of this study was to examine the association between age at menarche and MetS. Materials and methods: A total of 3292 women aged 19—91 years old were enrolled in two databases from 2004 to 2008. MetS was defined according to American Heart Association’s criteria. Age at menarche was obtained from self-reported questionnaires. Multiple logistic regression analyses were used to estimate the association between age at menarche and MetS with adjustment for potential confounding variables. Results: The prevalence of MetS increased with age. After adjusting age, lifestyle status, and reproductive factors as variables, subjects who had menarche at a younger age showed significantly higher risk of MetS. The adjusted odds ratio of having MetS in <12 and 12—14 years old menarche age groups were 1.71 (1.07—2.71) and 1.22 (1.00—1.50), respectively. The significant increase in odds ratio for MetS in early age menarche also reveals a dose—response effect.
∗
Corresponding author at: Department of Family Medicine, China Medical University Hospital, 2, Yuh-Der Road, Taichung 404, Taiwan. Tel.: +886 4 22052121x4507; fax: +886 4 22361803. E-mail address: [email protected] (W.-Y. Lin). http://dx.doi.org/10.1016/j.orcp.2015.10.003 1871-403X/© 2015 Asia Oceania Association for the Study of Obesity. Published by Elsevier Ltd. All rights reserved.
Please cite this article in press as: Chang C-J, et al. Age at menarche and its association with the metabolic syndrome in Taiwan. Obes Res Clin Pract (2015), http://dx.doi.org/10.1016/j.orcp.2015.10.003
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C.-J. Chang et al. Conclusions: Early onset of menarche is an important risk factor of MetS and may help identify women at risk of MetS. © 2015 Asia Oceania Association for the Study of Obesity. Published by Elsevier Ltd. All rights reserved.
Introduction A rapid fall in the age of women at menarche has been reported in Taiwan and other developed countries [1]. According to a public investigation in 2005, girls in north Taiwan start menstruation from an average age of 12.1 years old. A downward shift of 0.37 year in the mean menarche age during the past decade was also reported [2]. A growing body of evidence in Europe, America, mainland China, Japan, and Korea also reported that the mean age at menarche is falling [3—6]. By contrast, the prevalence of metabolic syndrome (MetS) showed a worldwide increase in the past two decades [7,8]. MetS is a clustering of metabolic abnormalities that places patients at higher risk of developing diabetes mellitus (DM), cardiovascular disease (CVD), stroke, and overall mortality. Efforts to identify possible risk factors early in life are important in order to benefit from preventive interventions. Few studies were reported to clarify whether age at menarche affects the development of MetS [9—11]. Therefore, we examined the effect of different age groups at menarche on the prevalence of MetS and the relationship of such effect to MetS components.
database is a population-based study composed of residents aged 40 and above in 2004 in Taichung, Taiwan [8]. A total of 363,543 residents in this area were identified during the time of study, which represented about 4.09% of the national population of the same age. A total of 2359 subjects were recruited. Among these, 1212 female individuals who completed the laboratory measurements and questionnaires were selected. A total of 3292 female subjects were selected for further analyses. Ethics approval for patient recruitment and data analysis was obtained from the Institutional Review Board of China Medical University Hospital in Taiwan.
Anthropometric indices and biochemical determinations Trained staff measured height, waist circumference (WC), hip circumference (HC), weight, and blood pressure (BP) of the study subjects [8]. Body mass index (BMI) was calculated as weight (kg) divided by height squared (m2 ). Blood samples were drawn in the morning after a 12 h overnight fast and were sent for analysis within 4 h of collection. Biochemical markers were analysed with a biochemical autoanalyzer (Beckman Cou, Fullerton, CA, USA) at the Clinical Laboratory Department (China Medical University Hospital, Taichung, Taiwan).
Materials and methods Study population and sampling method
Reproductive factors, personal history and life style behaviours
Study subjects were enrolled from two databases. One was obtained from a health screening centre in a tertiary hospital in Taiwan from 1 January 2006 to 31 December 2008. As previously reported, subjects underwent a health check-up, completed a structured questionnaire, and signed an informed consent to participate in the study [12]. The study was restricted to 2702 female participants. We excluded subjects without complete information for age at menarche (n = 622). A total of 2080 female subjects were finally included. The second
Several factors, such as DM, hypertension, dyslipidemia, history of gestational diabetes (GDM), alcohol consumption, smoking history, number of pregnancies, educational level, and marital status, were self-reported. Personal history of using hormone replacement therapy (HRT), use of oral contraceptive pills (OCP), occurrence of menopause, and history of abdominal total hysterectomy (ATH)/bilateral salpingo-oophorectomy (BSO) were also reported. History of smoking and alcohol consumption was divided into three classes
Please cite this article in press as: Chang C-J, et al. Age at menarche and its association with the metabolic syndrome in Taiwan. Obes Res Clin Pract (2015), http://dx.doi.org/10.1016/j.orcp.2015.10.003
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Menarche and metabolic syndrome
Definition of hypertension, diabetes, dyslipidemia, and MetS Hypertension was defined as systolic (BP ≥ 140 mmHg), and/or diastolic (BP ≥ 90 mmHg), and/or hypertension history on anti-hypertensive drug treatment. DM was defined as fasting glucose (≥7 mmol/L) and/or diabetes history with oral hypoglycemic agents or insulin treatment [13]. Dyslipidemia was defined as subjects with high triglycerides (TG) level (fasting TG ≥ 1.7 mmol/L), and/or high total cholesterol (TCHOL) level (TCHOL ≥ 5.17 mmol/L), and/or low high-density lipoprotein cholesterol (HDL-C) level (HDLC < 1.03 mmol/L in men or <1.29 mmol/L in women) [14,15]. MetS was defined clinically by the presence of three or more of the following American Heart Association/National Heart, Lung, and Blood Institute (AHA/NHLBI) MetS criteria [14]: (1) central obesity (WC ≥ 90 cm in men and ≥80 cm in women), (2) high TG level (≥1.7 mmol/L or on drug treatment for elevated triglycerides), (3) low HDLC level (<1.03 mmol/L in men and <1.29 mmol/L in women or on drug treatment for reduced HDL-C), (4) high BP (systolic BP ≥ 130 mmHg or diastolic BP ≥ 85 mmHg or under anti-hypertensive drug treatment in patients with history of hypertension), and (5) high fasting plasma glucose (FPG) concentration (≥5.6 mmol/L or on drug treatment for elevated glucose).
Assessment of age at menarche Age at menarche was defined as age at first menstrual bleeding and was recorded in years. After analysis of our database, two turning points of the curve presented the prevalence of MetS in different age groups. We categorised age at menarche as <12 years, 12—14 years, and >14 years according to these two turning points as seen in Fig. 1.
Statistical analysis The data are presented as means and standard deviation (SD) unless indicated otherwise. Multivariable
40%
Metabolic Syndrome Prevalence
as follows: never, former, and current. Education level was divided into three classes, as follows: ≤9 years, 10—12 years, and ≥13 years. Marital status was divided into three classes, as follows: single, married, and widow/divorced/separated. The number of previous pregnancies was divided into three classes, as follows: no pregnancy, 1 or 2 pregnancies, and more than 2 pregnancies.
3
35% 30% 25% 20% 15% 10% 5% 0%
<12
12
13
14
15
16
>16
Age at Menarche
Figure 1 The prevalence of metabolic syndrome according to age at menarche.
logistic regression was used to assess the relation between age at menarche, which was considered as a three-level categorical variable (<12 years, 12—14 years, and >14 years), and the MetS and its components. Age at menarche >14 years was the reference category. Student’s t-test and analysis of variance (ANOVA) were used to compare mean values. Variables with significant deviation from normal distribution were log transformed and assessed using a Kolmogorov—Smirnov test before further analyses. The Pearson’s 2 test was used to compare differences in categorical variables (such as smoking, alcohol drinking, education level, marital status, pregnancy times, OCP use, GDM, and HRT use). Univariate and multivariate logistic and linear regression analyses were applied to evaluate the relationship between the age at menarche and occurrence of MetS. Potential confounders were considered and modified in the regression analyses. Lifestyle model variables included age (years), history of smoking (current, former, never), alcohol intake (current, former, never), marital status (single, married, divorced, separated, or widowed), and education (≤9, 10—12, and ≥13 years). On the other hand, reproductive model variables included number of pregnancies (no pregnancy, 1—2 pregnancies, and more than 2 pregnancies), GDM (yes/no), use of OCP (yes/no), and use of HRT (yes/no). Confounder adjustment was done as described for the linear regression models. Significance tests were two-tailed, and p-values less than 0.05 were considered statistically significant. These statistical analyses were performed using the PC version of SPSS statistical software (17th version, SPSS Inc., Chicago, IL, USA).
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Figure 2 The mean age at menarche of women with 95% confidence intervals (vertical bars) by age at time of survey.
Table 3 shows the odds ratio (OR) and 95% confidence interval (CI) for MetS according to age at menarche of the women in the three groups (<12 years, 12—14 years, and >14 years), using age at menarche >14 years as the reference category. Inverse association between age at menarche and prevalence of MetS was found after adjustment of potential confounders (Models 1—3 in Table 3). Age at menarche and MetS showed an inverse association after adjustments were made for lifestyle model, which includes smoking and alcohol intake, marital status, and education; reproductive model, which includes number of pregnancies, GDM, use of OCP, and use of HRT; and age. Compared with subjects with age at menarche >14 years, the OR (95% CI) for those under 12 years and 12—14 years old groups were 1.71 (1.07—2.71) and 1.22 (1.00—1.50), respectively (p values < 0.05). The significant increase in ORs for MetS in the early age at menarche also reveals a dose—response effect.
Results Discussion The mean age at menarche in our study was 13.9 ± 1.69 years old. The mean ages at menarche were also counted according to different age groups. The mean age at menarche showed a significant dose—response effect with age at the time of survey as seen in Fig. 2. Table 1 shows the baseline characteristics by categories of age at menarche. Women with earlier age at menarche had greater height, weight, and education levels than those with later age at menarche and were more likely to be single. Women whose age at menarche was between 12 and 14 years had the lowest BMI among the groups. Women with late onset of menarche (>14 years) had the greatest weight, WC, TCHOL, FPG, and BP. Furthermore, they were more likely to have DM, hypertension, multi-parity, and with greater likelihood of undergoing HRT. As age at onset of menarche increased, the prevalence of MetS also increased significantly (p value for trend <0.001). No clear association was found between age at menarche and HDL-C, TG, smoking, alcohol consumption, and OCP use. The characteristics of women with or without MetS are presented in Table 2. The prevalence of MetS is 26.1%. Women with MetS were older and had a greater mean BMI, weight, WC, WHR, BP, TCHOL, FPG levels, and average menarche age, but lower HDL-C levels than women without MetS. They were more likely to have history of alcohol consumption, DM, hypertension, dyslipidemia, multi-parity, GDM, HRT use, and are currently married.
In this study, we demonstrated that early age at menarche was associated with the prevalence of MetS in adult Taiwanese women. Because this is a cross-sectional study, causality is not clear. However, the significant increase in ORs for the prevalence of MetS in younger age at menarche group suggests a dose—response effect. Multiple linear regression analyses also found a significant inverse association between age at menarche and MetS after adjustment of potential confounders. The stronger effect of age and life style factors than age at menarche may lead to different direction of ORs for the prevalence of MetS in unadjusted and adjusted models. The association of lower age at menarche and higher risk of MetS concurs with a previous study on Caucasians and Chinese in Mainland China [10,11]. A 2007 study of 7349 Chinese women aged 50—92 years showed an OR of 1.49 for the MetS in women with age at menarche below 12.5 years [10]. In 2008, a study involving 9000 Chinese women aged 25—64 years old reported that age at menarche was inversely associated with the number of MetS components and prevalence of MetS [16]. The result of KORA F4 study in Germany in 2011, which included 1536 German women aged 32—81 years old showed that age at menarche was inversely associated with MetS after adjusting the age variable [11]. Another study in rural Bangladesh also revealed that early onset of menarche (<12 years old) was associated with a higher prevalence of MetS compared with
Please cite this article in press as: Chang C-J, et al. Age at menarche and its association with the metabolic syndrome in Taiwan. Obes Res Clin Pract (2015), http://dx.doi.org/10.1016/j.orcp.2015.10.003
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Menarche and metabolic syndrome Table 1
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Baseline characteristics by age at menarche.
Age at menarche Age (years)† Height (cm)† Weight (kg)* BMI* (kg/m2 )† WC (cm)† WHR† TCHOL (mg/dl)† HDL-C (mg/dl)* TG (mg/dl)† LDL (mg/dl)† FPG (mg/dl)† SBP (mmHg)† DBP (mmHg)† Smoking (%)‡ Current Former Never Alcohol consumption (%)‡ Current Former Never Diabetes (%)‡,a Hypertension (%)‡,b Dyslipidemia (%)‡,c MetS (%)‡,d Education (years) (%)‡ ≤9 years old 10—12 years old ≥13 years old Marital status (%)‡ Single Married Widow, divorced or separated Pregnancies (%)‡ 0 1—2 ≥3 GDM (%)‡,e HRT (%)‡ OCP use (%)‡ Menopause ATH BSO Exposure
<12 n = 180 42.0 ± 10.2 157.5 ± 5.1 58.4 ± 10.9 23.6 ± 4.4 75.4 ± 10.1 0.80 ± 0.07 196.0 ± 39.7 50.1 ± 14.8 94.7 ± 56.4 127.8 ± 35.0 91.6 ± 16.2 116.2 ± 16.1 82.1 ± 25.1
12—14 n = 2122 48.4 ± 10.4 157.1 ± 5.4 56.7 ± 8.7 23.0 ± 3.5 74.7 ± 8.5 0.80 ± 0.06 200.8 ± 39.7 50.8 ± 13.6 100.1 ± 70.6 125.3 ± 35.5 94.7 ± 22.5 120.7 ± 18.5 91.7 ± 29.9
>14 n = 990 56.2 ± 11.4 155.6 ± 5.5 56.9 ± 8.5 23.5 ± 3.4 77.1 ± 9.0 0.82 ± 0.06 206.3 ± 38.6 50.0 ± 12.9 107.0 ± 65.1 130.7 ± 35.4 99.8 ± 27.3 129.6 ± 23.3 104.6 ± 35.9
1.1% 6.1% 92.8%
1.1% 4.9% 94.0%
1.3% 3.3% 95.3%
1.7% 9.4% 88.9% 2.8% 25.0% 78.9% 19.4%
0.9% 11.8% 87.3% 6.2% 44.3% 79.9% 23.1%
1.0% 10.5% 88.5% 11.9% 62.7% 85.6% 33.6%
10.3% 44.8% 44.8%
23.6% 50.4% 26.0%
57.5% 33.3% 9.2%
28.3% 63.6% 8.1%
9.4% 79.3% 11.3%
3.4% 76.1% 20.5%
30.4% 49.1% 20.5% 3.4% 13.3% 22.8% 24.0% 5.1% 5.6% 28.7 ± 8.2
10.7% 71.0% 57.5% 2.0% 23.6% 21.7% 41.8% 8.8% 6.4% 29.6 ± 6.5
4.4% 31.5% 64.2% 0.5% 29.7% 19.4% 66.3% 13.0% 9.4% 29.4 ± 6.3
p-Value <0.001 <0.001 0.032 <0.001 <0.001 <0.001 <0.001 0.268 0.011 <0.001 <0.001 <0.001 <0.001 0.237
0.585
<0.001 <0.001 <0.001 <0.001 <0.001
<0.001
<0.001
<0.001 <0.001 0.301 <0.001 <0.001 0.009 0.232
Present with mean ± SD (range) in continuous variables and percentage in categorical variables. Abbreviations. SD: standard deviation; BMI: body mass index; WC: waist circumference; WHR: waist-to-height ratio; TCHOL: total cholesterol; HDL-C: high-density-lipoprotein cholesterol; TG: triglycerides; LDL-C: low-density-lipoprotein cholesterol; FPG: fasting plasma glucose; SBP: systolic blood pressure; DBP: diastolic blood pressure; MetS: metabolic syndrome; GDM: gestational diabetes; HRT: hormone replacement therapy; OCP: oral contraceptives; ATH: abdominal total hysterectomy; BSO: bilateral salpingo-oophorectomy. * ANOVA test was used for continuous variables. † Kruskal—Wallis test showed not normal distribution; statistics were tested using the log-transformed values. ‡ Pearson Chi-Square test for categorical data. a Diabetes was defined as fasting glucose of ≥7 mmol/L, and/or diabetes history and on oral hypoglycemic agents or insulin treatment. b Hypertension was defined as systolic BP of ≥140 mmHg, and/or diastolic BP of ≥90 mmHg, and/or hypertension history and on anti-hypertensive drug treatment. c Dyslipidemia was defined as subjects with high triglycerides (TG ≥ 1.7 mmol/L), and/or high total cholesterol (TCHOL ≥ 5.17 mmol/L), and/or low HDL-C (HDL-C of <1.03 mmol/L in men or <1.29 mmol/L in women). d MetS: metabolic syndrome was defined by the American Heart Association/National Heart, Lung, and Blood Institute criteria. e GDM: gestational diabetes, defined as any degree of glucose intolerance with onset or first recognition during pregnancy.
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C.-J. Chang et al. Table 2
Characteristics of the subjects with MetS vs. without MetS.
Variables Age (years)† Age at menarche (years)† Height (cm)† Weight (kg)† BMI(kg/m2 )† WC(cm)† WHR† T-Chol (mg/dl)† HDL-C (mg/dl)† TG (mg/dl)† LDL (mg/dl)† FPG (mg/dl)† SBP (mmHg)† DBP (mmHg)† Alcohol consumption (%)‡ Current Former Never Smoking (%)‡ Current Former Never DM (%)‡,a Hypertension (%)‡,b Dyslipidemia (%)‡,c Pregnancies‡ 0 1—2 ≥3 Education (years) (%)‡ ≤9 years 10—12 years ≥13 years Marital status (%)‡ Single Married Widow, divorced, or separated GDM (%)‡,e HRT (%)‡ OCT use (%)‡ Menopause ATH BSO Exposure
MetSd (n = 858) 57.5 ± 1.00 14.2 ± 1.86 155.3 ± 5.2 63.1 ± 9.7 26.1 ± 3.6 83.5 ± 8.5 0.85 ± 0.6 213.5 ± 41.5 42.2 ± 9.2 157.4 ± 87.6 136.9 ± 38.6 112.6 ± 35.8 139.0 ± 19.5 111.0 ± 36.7
Without MetSd (n = 2434) 48.0 ± 1.10 13.8 ± 1.6 157.1 ± 5.5 54.6 ± 7.2 22.1 ± 2.8 72.7 ± 7.1 0.79 ± 0.5 198.1 ± 37.9 53.4 ± 13.5 82.1 ± 45.7 123.3 ± 33.7 90.30 ± 14.2 118.0 ± 17.1 90.0 ± 30.0
1.6% 8.4% 90.0%
0.7% 12.3% 86.9%
3.50% 1.3% 95.3% 17.4% 41.3% 24.7%
4.80% 1.1% 94.1% 1.1% 8.2% 3.6%
3.1% 30.4% 66.5%
12.2% 45.8% 42.0%
53.3% 35.4% 11.3%
26.3% 48.2% 25.5%
3.1% 76.1% 20.8% 2.6% 30.0% 20.3% 39.6% 7.7% 5.8% 28.7 ± 6.6
10.6% 77.7% 11.7% 1.6% 23.1% 21.2% 73.9% 16.4% 11.5% 31.7 ± 5.8
p-Value <0.001 <0.001 <0.001 <0.001 <0.001 <0.001 <0.001 <0.001 <0.001 <0.001 <0.001 <0.001 <0.001 <0.001 0.001
0.239
<0.001 <0.001 <0.001 <0.001
<0.001
<0.001
<0.001 <0.001 0.566 <0.001 <0.001 <0.001 <0.001
Present with mean ± SD (range) in continuous variables and percentage in categorical variables. Abbreviations. SD: standard deviation; BMI: body mass index; WC: waist circumference; WHR: waist-to-height ratio; TCHOL: total cholesterol; HDL-C: high-density-lipoprotein cholesterol; TG: triglycerides; LDL-C: low-density-lipoprotein cholesterol; FPG: fasting plasma glucose; SBP: systolic blood pressure; DBP: diastolic blood pressure; MetS: metabolic syndrome; GDM: gestational diabetes; HRT: hormone replacement therapy; OCP: oral contraceptives; ATH: abdominal total hysterectomy; BSO: bilateral salpingo-oophorectomy. † Kolmogorov—Smirnov test showed not normal distribution; statistics were tested using the log-transformed values. ‡ Pearson Chi-Square test for categorical data. a Diabetes was defined as fasting glucose of ≥7 mmol/L, and/or diabetes history and on oral hypoglycemic agents or insulin treatment. b Hypertension was defined as systolic BP ≥ 140 mmHg, and/or diastolic BP ≥ 90 mmHg, and/or hypertension history and on anti-hypertensive drug treatment. c Dyslipidemia defined as subjects with high triglycerides (TG ≥ 1.7 mmol/L), and/or high total cholesterol (TCHOL ≥ 5.17 mmol/L), and/or low HDL-C (<1.03 mmol/L in men or <1.29 mmol/L in women). d MetS: metabolic syndrome was defined by the American Heart Association/National Heart, Lung, and Blood Institute criteria. e GDM: gestational diabetes, defined as any degree of glucose intolerance with onset or first recognition during pregnancy.
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Table 3 Odds ratios (95% confidence interval) for metabolic syndrome in different models derived from multiple logistic regression analysis using age at menarche groups as independent variables; odds ratios were adjusted for potential confounders. Age at menarche
Model 1 OR (95% CI)
Model 2 OR (95% CI)
Model 3 OR (95% CI)
Model 4 OR (95% CI)
<12 12—14 >14 (Ref.)
0.48 (0.32—0.71)* 0.59 (0.50—0.70)* 1.00 (Ref.)
1.71 (1.09—2.69)* 1.26 (1.03—1.54)* 1.00 (Ref.)
1.58 (1.01—2.45)* 1.10 (0.90—1.34) 1.00 (Ref.)
1.71 (1.07—2.71)* 1.22 (1.00—1.50)* 1.00 (Ref.)
Model 1: Unadjusted. Model 2: Adjusted Age + ‘‘Life-style model: smoking and alcohol intake, marital status, education’’. Model 3: Adjusted Age + ‘‘Reproductive model: number of pregnancies, gestational diabetes, ever use of oral contraceptives and ever use of hormone replacement therapy’’. Model 4: Adjusted Age + ‘‘Life-style model’’ + ‘‘Reproductive model’’. * p < 0.05.
late onset (>13 years old) [9]. Although our study result is similar to these studies, our sample size is large enough to adjust potential confounders, especially for reproductive history, which may minimise residual confounding. Age at which menarche occurs differs among individuals and even among varying populations of the world [17—19]. Downward shift in the mean menarche age has been observed worldwide in the past few decades, and appears to be decreasing from generation to generation. These could be assumed to be the consequences of improved sanitary, nutritional, and socioeconomic conditions. Economic gains in the mid-1980s in Taiwan and in other countries might have caused a lifestyle change, which may have resulted in early pubertal maturation. Recently, environment, hormone, chemical contamination, and food additives have reportedly been the focus of research because they could alter the time of puberty. The role of menarche in the development of the MetS is unclear. Identifying and understanding potential mechanisms linking early menarche and the development of MetS will benefit future treatment and prevention efforts. Some evidence showed that early menarche is a marker for childhood obesity, but whether it acts a risk factor remains a question [20—24]. Additionally, the associations were only partly mediated by adiposity. The effects of sex hormones and genetic factors may also contribute to MetS. The 2006 Guangzhou Biobank Cohort Study reported that childbearing is associated with higher incidence of MetS among women of reproductive age who take necessary measurements to control components of the MetS before pregnancy [25]. The 2009 Isfahan Healthy Heart Program also showed that multi-parity is a risk factor of MetS [26]. Early age at menarche was also reported to be related to higher BMI [24] and adiposity in childhood and
adulthood [20—23]. These may partially explain the findings in this study. However, previous studies also found that early age at menarche was associated with the increased risk of cardiovascular morbidity and mortality [27—32], as well as another issue of vascular event referred to as type 2 DM and insulin intolerance [33—37]. Such associations might have arisen because of the increased prevalence of MetS in women who had menarche at an early age. Although our results demonstrate a clear inverse association between age at menarche and MetS among adult Taiwanese women, there are some limitations in this study. First, the cross-sectional design does not clarify causality. Future longitudinal cohort studies are necessary to establish causative links. However, the significant increase in ORs for the prevalence of MetS in younger age at menarche group suggests a dose—response effect, thus supporting the possibility of a causal relationship. Secondly, our study population was drawn from a metropolitan city in Taiwan, and the observations may not be true for all rural areas in Taiwan or across other countries, races, or ethnic groups. External validation is needed to confirm the results among different populations. Third, the information on age at menarche can be obtained using questionnaires, thus the recall bias could not be avoided, especially for elderly participants. The accuracy of recalled age at menarche has shown contradictory results in previous studies [38,39]. However, the enrolled people in these two databases were relatively healthy, clear-minded, and able to remember their personal history than in-hospital patients. Finally, although we have attempted to minimize confounding by statistically adjusting the effects of several variables including age, smoking status, alcohol intake, marital status, education level, number of pregnancies,
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GDM, and use of OCP or HRT, we cannot exclude the possibility of residual confounding. For example, physical activities or diet are also vital confounding factors of metabolic syndrome, but were not considered in the original study questionnaires.
Conclusions Age at menarche is not only a symbol of physiologic maturity in girls but may also help identify women at risk of MetS. In this manuscript, we concluded that adult Taiwanese women who underwent menarche at a younger age have higher MetS prevalence after adjustment of potential confounders. The results are quite similar to previous studies among Chinese and European groups. Women who underwent early onset of menarche are more at risk of MetS. Early screening for MetS in these groups may be necessary.
Conflicts of interest None declared.
Funding This study is supported by grants from National Science Council of Taiwan (NSC93-2314-B-039-025, NSC 94-2314-B-039-024), from Taiwan Ministry of Health and Welfare Clinical Trial and Research Center of Excellence (MOHW103-TDU-B-212-113002), and from China Medical University Hospital (DMR101-058 and DMR-102-065).
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Obesity Research & Clinical Practice (2015) xxx, xxx—xxx
ORIGINAL ARTICLE
Age at menarche and its association with the metabolic syndrome in Taiwan Chia-Jung Chang a,c, Ming-May Lai a,c, Cheng-Chieh Lin a,c,d,f, Chiu-Shong Liu a,c,d, Tsai-Chung Li e, Chia-Ing Li b,c, Wen-Yuan Lin a,c,d,g,∗ a
Department of Family Medicine, China Medical University Hospital, Taichung, Taiwan Department of Medical Research, China Medical University Hospital, Taichung, Taiwan c School of Medicine, China Medical University, Taichung, Taiwan d Graduate Institute of Clinical Medical Science, China Medical University, Taichung, Taiwan e Graduate Institute of Biostatistics, China Medical University, Taichung, Taiwan f Institute of Health Care Administration, Asia University, Taichung, Taiwan g Department of Family Medicine, National Taiwan University Hospital, Taipei, Taiwan b
Received 21 June 2015 ; received in revised form 17 September 2015; accepted 7 October 2015
KEYWORDS Menarche; Metabolic syndrome; Taiwan
Summary Background: The average age at menarche in the Taiwanese population is falling. Contrarily, the prevalence of metabolic syndrome (MetS) showed a worldwide increase in the past two decades. The aim of this study was to examine the association between age at menarche and MetS. Materials and methods: A total of 3292 women aged 19—91 years old were enrolled in two databases from 2004 to 2008. MetS was defined according to American Heart Association’s criteria. Age at menarche was obtained from self-reported questionnaires. Multiple logistic regression analyses were used to estimate the association between age at menarche and MetS with adjustment for potential confounding variables. Results: The prevalence of MetS increased with age. After adjusting age, lifestyle status, and reproductive factors as variables, subjects who had menarche at a younger age showed significantly higher risk of MetS. The adjusted odds ratio of having MetS in <12 and 12—14 years old menarche age groups were 1.71 (1.07—2.71) and 1.22 (1.00—1.50), respectively. The significant increase in odds ratio for MetS in early age menarche also reveals a dose—response effect.
∗
Corresponding author at: Department of Family Medicine, China Medical University Hospital, 2, Yuh-Der Road, Taichung 404, Taiwan. Tel.: +886 4 22052121x4507; fax: +886 4 22361803. E-mail address: [email protected] (W.-Y. Lin). http://dx.doi.org/10.1016/j.orcp.2015.10.003 1871-403X/© 2015 Asia Oceania Association for the Study of Obesity. Published by Elsevier Ltd. All rights reserved.
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C.-J. Chang et al. Conclusions: Early onset of menarche is an important risk factor of MetS and may help identify women at risk of MetS. © 2015 Asia Oceania Association for the Study of Obesity. Published by Elsevier Ltd. All rights reserved.
Introduction A rapid fall in the age of women at menarche has been reported in Taiwan and other developed countries [1]. According to a public investigation in 2005, girls in north Taiwan start menstruation from an average age of 12.1 years old. A downward shift of 0.37 year in the mean menarche age during the past decade was also reported [2]. A growing body of evidence in Europe, America, mainland China, Japan, and Korea also reported that the mean age at menarche is falling [3—6]. By contrast, the prevalence of metabolic syndrome (MetS) showed a worldwide increase in the past two decades [7,8]. MetS is a clustering of metabolic abnormalities that places patients at higher risk of developing diabetes mellitus (DM), cardiovascular disease (CVD), stroke, and overall mortality. Efforts to identify possible risk factors early in life are important in order to benefit from preventive interventions. Few studies were reported to clarify whether age at menarche affects the development of MetS [9—11]. Therefore, we examined the effect of different age groups at menarche on the prevalence of MetS and the relationship of such effect to MetS components.
database is a population-based study composed of residents aged 40 and above in 2004 in Taichung, Taiwan [8]. A total of 363,543 residents in this area were identified during the time of study, which represented about 4.09% of the national population of the same age. A total of 2359 subjects were recruited. Among these, 1212 female individuals who completed the laboratory measurements and questionnaires were selected. A total of 3292 female subjects were selected for further analyses. Ethics approval for patient recruitment and data analysis was obtained from the Institutional Review Board of China Medical University Hospital in Taiwan.
Anthropometric indices and biochemical determinations Trained staff measured height, waist circumference (WC), hip circumference (HC), weight, and blood pressure (BP) of the study subjects [8]. Body mass index (BMI) was calculated as weight (kg) divided by height squared (m2 ). Blood samples were drawn in the morning after a 12 h overnight fast and were sent for analysis within 4 h of collection. Biochemical markers were analysed with a biochemical autoanalyzer (Beckman Cou, Fullerton, CA, USA) at the Clinical Laboratory Department (China Medical University Hospital, Taichung, Taiwan).
Materials and methods Study population and sampling method
Reproductive factors, personal history and life style behaviours
Study subjects were enrolled from two databases. One was obtained from a health screening centre in a tertiary hospital in Taiwan from 1 January 2006 to 31 December 2008. As previously reported, subjects underwent a health check-up, completed a structured questionnaire, and signed an informed consent to participate in the study [12]. The study was restricted to 2702 female participants. We excluded subjects without complete information for age at menarche (n = 622). A total of 2080 female subjects were finally included. The second
Several factors, such as DM, hypertension, dyslipidemia, history of gestational diabetes (GDM), alcohol consumption, smoking history, number of pregnancies, educational level, and marital status, were self-reported. Personal history of using hormone replacement therapy (HRT), use of oral contraceptive pills (OCP), occurrence of menopause, and history of abdominal total hysterectomy (ATH)/bilateral salpingo-oophorectomy (BSO) were also reported. History of smoking and alcohol consumption was divided into three classes
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Definition of hypertension, diabetes, dyslipidemia, and MetS Hypertension was defined as systolic (BP ≥ 140 mmHg), and/or diastolic (BP ≥ 90 mmHg), and/or hypertension history on anti-hypertensive drug treatment. DM was defined as fasting glucose (≥7 mmol/L) and/or diabetes history with oral hypoglycemic agents or insulin treatment [13]. Dyslipidemia was defined as subjects with high triglycerides (TG) level (fasting TG ≥ 1.7 mmol/L), and/or high total cholesterol (TCHOL) level (TCHOL ≥ 5.17 mmol/L), and/or low high-density lipoprotein cholesterol (HDL-C) level (HDLC < 1.03 mmol/L in men or <1.29 mmol/L in women) [14,15]. MetS was defined clinically by the presence of three or more of the following American Heart Association/National Heart, Lung, and Blood Institute (AHA/NHLBI) MetS criteria [14]: (1) central obesity (WC ≥ 90 cm in men and ≥80 cm in women), (2) high TG level (≥1.7 mmol/L or on drug treatment for elevated triglycerides), (3) low HDLC level (<1.03 mmol/L in men and <1.29 mmol/L in women or on drug treatment for reduced HDL-C), (4) high BP (systolic BP ≥ 130 mmHg or diastolic BP ≥ 85 mmHg or under anti-hypertensive drug treatment in patients with history of hypertension), and (5) high fasting plasma glucose (FPG) concentration (≥5.6 mmol/L or on drug treatment for elevated glucose).
Assessment of age at menarche Age at menarche was defined as age at first menstrual bleeding and was recorded in years. After analysis of our database, two turning points of the curve presented the prevalence of MetS in different age groups. We categorised age at menarche as <12 years, 12—14 years, and >14 years according to these two turning points as seen in Fig. 1.
Statistical analysis The data are presented as means and standard deviation (SD) unless indicated otherwise. Multivariable
40%
Metabolic Syndrome Prevalence
as follows: never, former, and current. Education level was divided into three classes, as follows: ≤9 years, 10—12 years, and ≥13 years. Marital status was divided into three classes, as follows: single, married, and widow/divorced/separated. The number of previous pregnancies was divided into three classes, as follows: no pregnancy, 1 or 2 pregnancies, and more than 2 pregnancies.
3
35% 30% 25% 20% 15% 10% 5% 0%
<12
12
13
14
15
16
>16
Age at Menarche
Figure 1 The prevalence of metabolic syndrome according to age at menarche.
logistic regression was used to assess the relation between age at menarche, which was considered as a three-level categorical variable (<12 years, 12—14 years, and >14 years), and the MetS and its components. Age at menarche >14 years was the reference category. Student’s t-test and analysis of variance (ANOVA) were used to compare mean values. Variables with significant deviation from normal distribution were log transformed and assessed using a Kolmogorov—Smirnov test before further analyses. The Pearson’s 2 test was used to compare differences in categorical variables (such as smoking, alcohol drinking, education level, marital status, pregnancy times, OCP use, GDM, and HRT use). Univariate and multivariate logistic and linear regression analyses were applied to evaluate the relationship between the age at menarche and occurrence of MetS. Potential confounders were considered and modified in the regression analyses. Lifestyle model variables included age (years), history of smoking (current, former, never), alcohol intake (current, former, never), marital status (single, married, divorced, separated, or widowed), and education (≤9, 10—12, and ≥13 years). On the other hand, reproductive model variables included number of pregnancies (no pregnancy, 1—2 pregnancies, and more than 2 pregnancies), GDM (yes/no), use of OCP (yes/no), and use of HRT (yes/no). Confounder adjustment was done as described for the linear regression models. Significance tests were two-tailed, and p-values less than 0.05 were considered statistically significant. These statistical analyses were performed using the PC version of SPSS statistical software (17th version, SPSS Inc., Chicago, IL, USA).
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Figure 2 The mean age at menarche of women with 95% confidence intervals (vertical bars) by age at time of survey.
Table 3 shows the odds ratio (OR) and 95% confidence interval (CI) for MetS according to age at menarche of the women in the three groups (<12 years, 12—14 years, and >14 years), using age at menarche >14 years as the reference category. Inverse association between age at menarche and prevalence of MetS was found after adjustment of potential confounders (Models 1—3 in Table 3). Age at menarche and MetS showed an inverse association after adjustments were made for lifestyle model, which includes smoking and alcohol intake, marital status, and education; reproductive model, which includes number of pregnancies, GDM, use of OCP, and use of HRT; and age. Compared with subjects with age at menarche >14 years, the OR (95% CI) for those under 12 years and 12—14 years old groups were 1.71 (1.07—2.71) and 1.22 (1.00—1.50), respectively (p values < 0.05). The significant increase in ORs for MetS in the early age at menarche also reveals a dose—response effect.
Results Discussion The mean age at menarche in our study was 13.9 ± 1.69 years old. The mean ages at menarche were also counted according to different age groups. The mean age at menarche showed a significant dose—response effect with age at the time of survey as seen in Fig. 2. Table 1 shows the baseline characteristics by categories of age at menarche. Women with earlier age at menarche had greater height, weight, and education levels than those with later age at menarche and were more likely to be single. Women whose age at menarche was between 12 and 14 years had the lowest BMI among the groups. Women with late onset of menarche (>14 years) had the greatest weight, WC, TCHOL, FPG, and BP. Furthermore, they were more likely to have DM, hypertension, multi-parity, and with greater likelihood of undergoing HRT. As age at onset of menarche increased, the prevalence of MetS also increased significantly (p value for trend <0.001). No clear association was found between age at menarche and HDL-C, TG, smoking, alcohol consumption, and OCP use. The characteristics of women with or without MetS are presented in Table 2. The prevalence of MetS is 26.1%. Women with MetS were older and had a greater mean BMI, weight, WC, WHR, BP, TCHOL, FPG levels, and average menarche age, but lower HDL-C levels than women without MetS. They were more likely to have history of alcohol consumption, DM, hypertension, dyslipidemia, multi-parity, GDM, HRT use, and are currently married.
In this study, we demonstrated that early age at menarche was associated with the prevalence of MetS in adult Taiwanese women. Because this is a cross-sectional study, causality is not clear. However, the significant increase in ORs for the prevalence of MetS in younger age at menarche group suggests a dose—response effect. Multiple linear regression analyses also found a significant inverse association between age at menarche and MetS after adjustment of potential confounders. The stronger effect of age and life style factors than age at menarche may lead to different direction of ORs for the prevalence of MetS in unadjusted and adjusted models. The association of lower age at menarche and higher risk of MetS concurs with a previous study on Caucasians and Chinese in Mainland China [10,11]. A 2007 study of 7349 Chinese women aged 50—92 years showed an OR of 1.49 for the MetS in women with age at menarche below 12.5 years [10]. In 2008, a study involving 9000 Chinese women aged 25—64 years old reported that age at menarche was inversely associated with the number of MetS components and prevalence of MetS [16]. The result of KORA F4 study in Germany in 2011, which included 1536 German women aged 32—81 years old showed that age at menarche was inversely associated with MetS after adjusting the age variable [11]. Another study in rural Bangladesh also revealed that early onset of menarche (<12 years old) was associated with a higher prevalence of MetS compared with
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Menarche and metabolic syndrome Table 1
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Baseline characteristics by age at menarche.
Age at menarche Age (years)† Height (cm)† Weight (kg)* BMI* (kg/m2 )† WC (cm)† WHR† TCHOL (mg/dl)† HDL-C (mg/dl)* TG (mg/dl)† LDL (mg/dl)† FPG (mg/dl)† SBP (mmHg)† DBP (mmHg)† Smoking (%)‡ Current Former Never Alcohol consumption (%)‡ Current Former Never Diabetes (%)‡,a Hypertension (%)‡,b Dyslipidemia (%)‡,c MetS (%)‡,d Education (years) (%)‡ ≤9 years old 10—12 years old ≥13 years old Marital status (%)‡ Single Married Widow, divorced or separated Pregnancies (%)‡ 0 1—2 ≥3 GDM (%)‡,e HRT (%)‡ OCP use (%)‡ Menopause ATH BSO Exposure
<12 n = 180 42.0 ± 10.2 157.5 ± 5.1 58.4 ± 10.9 23.6 ± 4.4 75.4 ± 10.1 0.80 ± 0.07 196.0 ± 39.7 50.1 ± 14.8 94.7 ± 56.4 127.8 ± 35.0 91.6 ± 16.2 116.2 ± 16.1 82.1 ± 25.1
12—14 n = 2122 48.4 ± 10.4 157.1 ± 5.4 56.7 ± 8.7 23.0 ± 3.5 74.7 ± 8.5 0.80 ± 0.06 200.8 ± 39.7 50.8 ± 13.6 100.1 ± 70.6 125.3 ± 35.5 94.7 ± 22.5 120.7 ± 18.5 91.7 ± 29.9
>14 n = 990 56.2 ± 11.4 155.6 ± 5.5 56.9 ± 8.5 23.5 ± 3.4 77.1 ± 9.0 0.82 ± 0.06 206.3 ± 38.6 50.0 ± 12.9 107.0 ± 65.1 130.7 ± 35.4 99.8 ± 27.3 129.6 ± 23.3 104.6 ± 35.9
1.1% 6.1% 92.8%
1.1% 4.9% 94.0%
1.3% 3.3% 95.3%
1.7% 9.4% 88.9% 2.8% 25.0% 78.9% 19.4%
0.9% 11.8% 87.3% 6.2% 44.3% 79.9% 23.1%
1.0% 10.5% 88.5% 11.9% 62.7% 85.6% 33.6%
10.3% 44.8% 44.8%
23.6% 50.4% 26.0%
57.5% 33.3% 9.2%
28.3% 63.6% 8.1%
9.4% 79.3% 11.3%
3.4% 76.1% 20.5%
30.4% 49.1% 20.5% 3.4% 13.3% 22.8% 24.0% 5.1% 5.6% 28.7 ± 8.2
10.7% 71.0% 57.5% 2.0% 23.6% 21.7% 41.8% 8.8% 6.4% 29.6 ± 6.5
4.4% 31.5% 64.2% 0.5% 29.7% 19.4% 66.3% 13.0% 9.4% 29.4 ± 6.3
p-Value <0.001 <0.001 0.032 <0.001 <0.001 <0.001 <0.001 0.268 0.011 <0.001 <0.001 <0.001 <0.001 0.237
0.585
<0.001 <0.001 <0.001 <0.001 <0.001
<0.001
<0.001
<0.001 <0.001 0.301 <0.001 <0.001 0.009 0.232
Present with mean ± SD (range) in continuous variables and percentage in categorical variables. Abbreviations. SD: standard deviation; BMI: body mass index; WC: waist circumference; WHR: waist-to-height ratio; TCHOL: total cholesterol; HDL-C: high-density-lipoprotein cholesterol; TG: triglycerides; LDL-C: low-density-lipoprotein cholesterol; FPG: fasting plasma glucose; SBP: systolic blood pressure; DBP: diastolic blood pressure; MetS: metabolic syndrome; GDM: gestational diabetes; HRT: hormone replacement therapy; OCP: oral contraceptives; ATH: abdominal total hysterectomy; BSO: bilateral salpingo-oophorectomy. * ANOVA test was used for continuous variables. † Kruskal—Wallis test showed not normal distribution; statistics were tested using the log-transformed values. ‡ Pearson Chi-Square test for categorical data. a Diabetes was defined as fasting glucose of ≥7 mmol/L, and/or diabetes history and on oral hypoglycemic agents or insulin treatment. b Hypertension was defined as systolic BP of ≥140 mmHg, and/or diastolic BP of ≥90 mmHg, and/or hypertension history and on anti-hypertensive drug treatment. c Dyslipidemia was defined as subjects with high triglycerides (TG ≥ 1.7 mmol/L), and/or high total cholesterol (TCHOL ≥ 5.17 mmol/L), and/or low HDL-C (HDL-C of <1.03 mmol/L in men or <1.29 mmol/L in women). d MetS: metabolic syndrome was defined by the American Heart Association/National Heart, Lung, and Blood Institute criteria. e GDM: gestational diabetes, defined as any degree of glucose intolerance with onset or first recognition during pregnancy.
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Characteristics of the subjects with MetS vs. without MetS.
Variables Age (years)† Age at menarche (years)† Height (cm)† Weight (kg)† BMI(kg/m2 )† WC(cm)† WHR† T-Chol (mg/dl)† HDL-C (mg/dl)† TG (mg/dl)† LDL (mg/dl)† FPG (mg/dl)† SBP (mmHg)† DBP (mmHg)† Alcohol consumption (%)‡ Current Former Never Smoking (%)‡ Current Former Never DM (%)‡,a Hypertension (%)‡,b Dyslipidemia (%)‡,c Pregnancies‡ 0 1—2 ≥3 Education (years) (%)‡ ≤9 years 10—12 years ≥13 years Marital status (%)‡ Single Married Widow, divorced, or separated GDM (%)‡,e HRT (%)‡ OCT use (%)‡ Menopause ATH BSO Exposure
MetSd (n = 858) 57.5 ± 1.00 14.2 ± 1.86 155.3 ± 5.2 63.1 ± 9.7 26.1 ± 3.6 83.5 ± 8.5 0.85 ± 0.6 213.5 ± 41.5 42.2 ± 9.2 157.4 ± 87.6 136.9 ± 38.6 112.6 ± 35.8 139.0 ± 19.5 111.0 ± 36.7
Without MetSd (n = 2434) 48.0 ± 1.10 13.8 ± 1.6 157.1 ± 5.5 54.6 ± 7.2 22.1 ± 2.8 72.7 ± 7.1 0.79 ± 0.5 198.1 ± 37.9 53.4 ± 13.5 82.1 ± 45.7 123.3 ± 33.7 90.30 ± 14.2 118.0 ± 17.1 90.0 ± 30.0
1.6% 8.4% 90.0%
0.7% 12.3% 86.9%
3.50% 1.3% 95.3% 17.4% 41.3% 24.7%
4.80% 1.1% 94.1% 1.1% 8.2% 3.6%
3.1% 30.4% 66.5%
12.2% 45.8% 42.0%
53.3% 35.4% 11.3%
26.3% 48.2% 25.5%
3.1% 76.1% 20.8% 2.6% 30.0% 20.3% 39.6% 7.7% 5.8% 28.7 ± 6.6
10.6% 77.7% 11.7% 1.6% 23.1% 21.2% 73.9% 16.4% 11.5% 31.7 ± 5.8
p-Value <0.001 <0.001 <0.001 <0.001 <0.001 <0.001 <0.001 <0.001 <0.001 <0.001 <0.001 <0.001 <0.001 <0.001 0.001
0.239
<0.001 <0.001 <0.001 <0.001
<0.001
<0.001
<0.001 <0.001 0.566 <0.001 <0.001 <0.001 <0.001
Present with mean ± SD (range) in continuous variables and percentage in categorical variables. Abbreviations. SD: standard deviation; BMI: body mass index; WC: waist circumference; WHR: waist-to-height ratio; TCHOL: total cholesterol; HDL-C: high-density-lipoprotein cholesterol; TG: triglycerides; LDL-C: low-density-lipoprotein cholesterol; FPG: fasting plasma glucose; SBP: systolic blood pressure; DBP: diastolic blood pressure; MetS: metabolic syndrome; GDM: gestational diabetes; HRT: hormone replacement therapy; OCP: oral contraceptives; ATH: abdominal total hysterectomy; BSO: bilateral salpingo-oophorectomy. † Kolmogorov—Smirnov test showed not normal distribution; statistics were tested using the log-transformed values. ‡ Pearson Chi-Square test for categorical data. a Diabetes was defined as fasting glucose of ≥7 mmol/L, and/or diabetes history and on oral hypoglycemic agents or insulin treatment. b Hypertension was defined as systolic BP ≥ 140 mmHg, and/or diastolic BP ≥ 90 mmHg, and/or hypertension history and on anti-hypertensive drug treatment. c Dyslipidemia defined as subjects with high triglycerides (TG ≥ 1.7 mmol/L), and/or high total cholesterol (TCHOL ≥ 5.17 mmol/L), and/or low HDL-C (<1.03 mmol/L in men or <1.29 mmol/L in women). d MetS: metabolic syndrome was defined by the American Heart Association/National Heart, Lung, and Blood Institute criteria. e GDM: gestational diabetes, defined as any degree of glucose intolerance with onset or first recognition during pregnancy.
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Table 3 Odds ratios (95% confidence interval) for metabolic syndrome in different models derived from multiple logistic regression analysis using age at menarche groups as independent variables; odds ratios were adjusted for potential confounders. Age at menarche
Model 1 OR (95% CI)
Model 2 OR (95% CI)
Model 3 OR (95% CI)
Model 4 OR (95% CI)
<12 12—14 >14 (Ref.)
0.48 (0.32—0.71)* 0.59 (0.50—0.70)* 1.00 (Ref.)
1.71 (1.09—2.69)* 1.26 (1.03—1.54)* 1.00 (Ref.)
1.58 (1.01—2.45)* 1.10 (0.90—1.34) 1.00 (Ref.)
1.71 (1.07—2.71)* 1.22 (1.00—1.50)* 1.00 (Ref.)
Model 1: Unadjusted. Model 2: Adjusted Age + ‘‘Life-style model: smoking and alcohol intake, marital status, education’’. Model 3: Adjusted Age + ‘‘Reproductive model: number of pregnancies, gestational diabetes, ever use of oral contraceptives and ever use of hormone replacement therapy’’. Model 4: Adjusted Age + ‘‘Life-style model’’ + ‘‘Reproductive model’’. * p < 0.05.
late onset (>13 years old) [9]. Although our study result is similar to these studies, our sample size is large enough to adjust potential confounders, especially for reproductive history, which may minimise residual confounding. Age at which menarche occurs differs among individuals and even among varying populations of the world [17—19]. Downward shift in the mean menarche age has been observed worldwide in the past few decades, and appears to be decreasing from generation to generation. These could be assumed to be the consequences of improved sanitary, nutritional, and socioeconomic conditions. Economic gains in the mid-1980s in Taiwan and in other countries might have caused a lifestyle change, which may have resulted in early pubertal maturation. Recently, environment, hormone, chemical contamination, and food additives have reportedly been the focus of research because they could alter the time of puberty. The role of menarche in the development of the MetS is unclear. Identifying and understanding potential mechanisms linking early menarche and the development of MetS will benefit future treatment and prevention efforts. Some evidence showed that early menarche is a marker for childhood obesity, but whether it acts a risk factor remains a question [20—24]. Additionally, the associations were only partly mediated by adiposity. The effects of sex hormones and genetic factors may also contribute to MetS. The 2006 Guangzhou Biobank Cohort Study reported that childbearing is associated with higher incidence of MetS among women of reproductive age who take necessary measurements to control components of the MetS before pregnancy [25]. The 2009 Isfahan Healthy Heart Program also showed that multi-parity is a risk factor of MetS [26]. Early age at menarche was also reported to be related to higher BMI [24] and adiposity in childhood and
adulthood [20—23]. These may partially explain the findings in this study. However, previous studies also found that early age at menarche was associated with the increased risk of cardiovascular morbidity and mortality [27—32], as well as another issue of vascular event referred to as type 2 DM and insulin intolerance [33—37]. Such associations might have arisen because of the increased prevalence of MetS in women who had menarche at an early age. Although our results demonstrate a clear inverse association between age at menarche and MetS among adult Taiwanese women, there are some limitations in this study. First, the cross-sectional design does not clarify causality. Future longitudinal cohort studies are necessary to establish causative links. However, the significant increase in ORs for the prevalence of MetS in younger age at menarche group suggests a dose—response effect, thus supporting the possibility of a causal relationship. Secondly, our study population was drawn from a metropolitan city in Taiwan, and the observations may not be true for all rural areas in Taiwan or across other countries, races, or ethnic groups. External validation is needed to confirm the results among different populations. Third, the information on age at menarche can be obtained using questionnaires, thus the recall bias could not be avoided, especially for elderly participants. The accuracy of recalled age at menarche has shown contradictory results in previous studies [38,39]. However, the enrolled people in these two databases were relatively healthy, clear-minded, and able to remember their personal history than in-hospital patients. Finally, although we have attempted to minimize confounding by statistically adjusting the effects of several variables including age, smoking status, alcohol intake, marital status, education level, number of pregnancies,
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C.-J. Chang et al.
GDM, and use of OCP or HRT, we cannot exclude the possibility of residual confounding. For example, physical activities or diet are also vital confounding factors of metabolic syndrome, but were not considered in the original study questionnaires.
Conclusions Age at menarche is not only a symbol of physiologic maturity in girls but may also help identify women at risk of MetS. In this manuscript, we concluded that adult Taiwanese women who underwent menarche at a younger age have higher MetS prevalence after adjustment of potential confounders. The results are quite similar to previous studies among Chinese and European groups. Women who underwent early onset of menarche are more at risk of MetS. Early screening for MetS in these groups may be necessary.
Conflicts of interest None declared.
Funding This study is supported by grants from National Science Council of Taiwan (NSC93-2314-B-039-025, NSC 94-2314-B-039-024), from Taiwan Ministry of Health and Welfare Clinical Trial and Research Center of Excellence (MOHW103-TDU-B-212-113002), and from China Medical University Hospital (DMR101-058 and DMR-102-065).
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