Skip Navigation
Skip to contents

Diabetes Metab J : Diabetes & Metabolism Journal

Search
OPEN ACCESS

Articles

Page Path
HOME > Diabetes Metab J > Volume 41(2); 2017 > Article
Brief Report
Obesity and Metabolic Syndrome A Cutoff for Age at Menarche Predicting Metabolic Syndrome in Egyptian Overweight/Obese Premenopausal Women
Ibrahim Elsehely1orcid, Hala Abdel Hafez1, Mohammed Ghonem1, Ali Fathi2, Rasha Elzehery3
Diabetes & Metabolism Journal 2017;41(2):146-149.
DOI: https://doi.org/10.4093/dmj.2017.41.2.146
Published online: November 30, 2016
  • 3,198 Views
  • 29 Download
  • 7 Web of Science
  • 7 Crossref
  • 7 Scopus

1Department of Internal Medicine, Faculty of Medicine, Mansoura University, Mansoura, Egypt.

2Department of Internal Medicine, Demira Hospital, Ministry of Health, Dakhlia, Egypt.

3Department of Clinical Pathology, Faculty of Medicine, Mansoura University, Mansoura, Egypt.

Corresponding author: Ibrahim Elsehely. Department of Internal Medicine, Faculty of Medicine, Mansoura University, Gomheria St, Mansoura, Egypt. dr_hima_dm@yahoo.com
• Received: June 17, 2016   • Accepted: August 26, 2016

Copyright © 2017 Korean Diabetes Association

This is an Open Access article distributed under the terms of the Creative Commons Attribution Non-Commercial License (http://creativecommons.org/licenses/by-nc/4.0/) which permits unrestricted non-commercial use, distribution, and reproduction in any medium, provided the original work is properly cited.

  • Previous studies showed that early age at menarche is associated with increased risk of metabolic syndrome. However, the definition of early menarche at these studies was based on background data in the communities at which these studies was carried on. The aim of this work is to determine a cutoff for age at menarche discriminating presence or absence of metabolic syndrome in overweight/obese premenopausal women. This study included 204 overweight/obese women. Metabolic syndrome was defined according to NCEP-ATP III (National Cholesterol Education Program Adult Treatment Panel III) criteria. Of a total 204 participants, 82 (40.2%) had metabolic syndrome. By using receiver operating characteristic analysis, age at menarche ≤12.25 year discriminated individuals with from those without metabolic syndrome. The area under the curve was 0.76 (95% confidence interval, 0.70 to 0.83). Sensitivity, specificity, negative predictive value, and positive predictive value were 82%, 70%, 85%, and 64%, respectively. Age at menarche ≤12.25 years predicts the presence of metabolic syndrome in overweight/obese women.
Metabolic syndrome is a major health problem as it affects about 25% of the population worldwide [1]. The components of this syndrome are central obesity, high blood pressure, hyperglycemia, low levels of high density lipoprotein cholesterol (HDL-C) and hypertriglyceridemia [2].
Several studies showed a link between early age at menarche and increased risk of metabolic syndrome [3456]. However, the definition of early menarche at these studies either below 12 years [345] or below 12.5 years [6] was based on background data in their communities. The aim of this work is to determine a cutoff for age at menarche predicting metabolic syndrome in premenopausal overweight/obese women.
Participants
This is a cross-sectional study was conducted on 222 randomly selected premenopausal overweight/obese women (body mass index [BMI] ≥25 kg/m2) aged from 25 to 45 years attending Mansoura Specialized Medical Hospital outpatient obesity clinic. All study participants gave written informed consent and the study was approved by the Ethics Committee of the Mansoura Faculty of Medicine. Participants were asked about their age at which the first menstrual bleeding occurred in years and months. Women with lacking information about age at onset of menarche, those with menarche before 9 years or beyond 16 years were excluded. Women taking hypolipidemic or corticosteroid medications were also excluded. Finally, 204 subjects remained in this study.
Clinical evaluation
Assessment of anthropometric measurements was done while the participants wearing light clothes and no shoes. Height was measured to the nearest 0.5 cm and weight to the nearest 1 kg. BMI was estimated as weight (kg) divided by squared height (m2). Waist circumference was measured at the upper border of the iliac crest to the nearest 0.5 cm. Blood pressure was measured in the right arm in a sitting position to the nearest 2 mm Hg and the average of the two measurements was used in the analysis.
Sampling and biochemical measurements
After at least 12 hours fast, 5 mL venous blood was withdrawn from each subject under complete aseptic conditions. After serum separation, blood glucose and lipid profile were assayed immediately. Fasting blood glucose, serum total cholesterol, triglycerides, and HDL-C were measured by enzymatic methods. Low density lipoprotein cholesterol was calculated using Friedewald equation [7].
Definition of metabolic syndrome
The National Cholesterol Education Program-Adult Treatment Panel III guidelines [8] was used to define participants who have metabolic syndrome if three or more of the following five criteria are present: (1) waist circumference ≥88 cm; (2) blood pressure ≥130/85 mm Hg or treated for hypertension; (3) fasting blood glucose ≥100 mg/dL or treated for diabetes; (4) fasting triglycerides ≥150 mg/day; and (5) fasting HDL-C <50 mg/dL. All study participants were divided into two groups according to presence or absence of metabolic syndrome.
Statistical analysis
Data were expressed as mean±standard deviation for continuous variables and as number (%) for categorical variables. Student t-test and chi-square tests were used to compare continuous and categorical variables respectively. Receiver operating characteristic (ROC) curve analysis was done to evaluate the ability of age at menarche to discriminate between individuals with and those without metabolic syndrome. The optimal cutoff was determined by Youden index [9]. All statistical analysis were done using SPSS version 20 (IBM Co., Armonk, NY, USA). A two tailed P value less than 0.05 was considered significant.
Of a total 204 participants, 60 (29.4%) were overweight and 144 (70.6%) were obese. Prevalence of metabolic syndrome was 33.3%, 43.1%, and 40.2% in overweight, obese and all study participants respectively. Other characteristics of study population are summarized in Table 1. Age at menarche was significantly lower in individuals with metabolic syndrome when compared to those without metabolic syndrome (P<0.01).
ROC curve analysis for prediction of metabolic syndrome by age at menarche is presented in Table 2. Age at menarche significantly discriminated overweight/obese individuals with from those without metabolic syndrome (P value of AUC <0.01).
The presence of metabolic syndrome in overweight and obese individuals increases the risk of cardiovascular disease, type 2 diabetes mellitus, nonalcoholic fatty liver disease, obstructive sleep apnea, and polycystic ovarian syndrome [1]. In this study, prevalence of metabolic syndrome in overweight and obese women was 33.3% and 43.1% respectively which is slightly differ from what was reported by Park et al. [10] (28.1% and 50.0%, respectively).
In this study and by using of ROC curve analysis, age at menarche ≤12.25 years predicted presence of metabolic syndrome in overweight and obese women. This cutoff is about to be similar with that used for definition of early menarche in previous studies reporting its association with metabolic syndrome [3456]. To best of our knowledge, this is the first time to define a cutoff for age at menarche that predicts metabolic syndrome using ROC curve analysis.
A possible explanation for the inverse association between age at menarche and metabolic syndrome is that childhood obesity enhances early sexual maturation possibly due to high leptin levels [11]. In addition, childhood obesity was found to be associated development of metabolic syndrome in adulthood [12]. Therefore, childhood obesity may mediate the link between age at menarche and metabolic syndrome.
Previous studies showed that certain parameters can be used in screening of metabolic syndrome such as waist-to-height ratio [13], lipid accumulation product which is estimated from waist circumference and plasma triglyceride levels [14] and triglyceride/HDL-C ratio [15]. In females, especially if obese or overweight, age at menarche may be one of such parameters.
This study conducted on overweight/obese women to ensure that a higher proportion of this study participants would have metabolic syndrome since prevalence of metabolic in overweight/obese individuals is higher than those with normal body weight [10]. Moreover, it may be appropriate to differentiate obese individuals who are metabolically healthy obese form those who have metabolic syndrome [16]. So, knowing age at menarche in overweight/obese women may be helpful in this differentiation.
One of the limitations of this study is that it is not a population based one and this due to lack of financial support. A second limitation is that determination of age of menarche was done using recall. However, menarche is a major physiological event, and age of menarche is memorable for many years [17]. A third limitation is that childhood BMI and waist circumference were not adjusted in regression models due to lack of data about these two parameters.
In conclusion, age at menarche less than or equal to 12.25 years predicts the presence of metabolic syndrome in overweight/obese women and can be used in screening of metabolic syndrome in females.

CONFLICTS OF INTEREST: No potential conflict of interest relevant to this article was reported.

  • 1. Kaur J. A comprehensive review on metabolic syndrome. Cardiol Res Pract 2014;2014:943162ArticlePubMedPMCPDF
  • 2. Alberti KG, Eckel RH, Grundy SM, Zimmet PZ, Cleeman JI, Donato KA, Fruchart JC, James WP, Loria CM, Smith SC Jr. International Diabetes Federation Task Force on Epidemiology and Prevention. Hational Heart, Lung, and Blood Institute. American Heart Association. World Heart Federation. International Atherosclerosis Society. International Association for the Study of Obesity. Harmonizing the metabolic syndrome: a joint interim statement of the International Diabetes Federation Task Force on Epidemiology and Prevention; National Heart, Lung, and Blood Institute; American Heart Association; World Heart Federation; International Atherosclerosis Society; and International Association for the Study of Obesity. Circulation 2009;120:1640-1645. ArticlePubMed
  • 3. Akter S, Jesmin S, Islam M, Sultana SN, Okazaki O, Hiroe M, Moroi M, Mizutani T. Association of age at menarche with metabolic syndrome and its components in rural Bangladeshi women. Nutr Metab (Lond) 2012;9:99ArticlePubMedPMCPDF
  • 4. Stockl D, Meisinger C, Peters A, Thorand B, Huth C, Heier M, Rathmann W, Kowall B, Stockl H, Doring A. Age at menarche and its association with the metabolic syndrome and its components: results from the KORA F4 study. PLoS One 2011;6:e26076ArticlePubMedPMC
  • 5. Lim SW, Ahn JH, Lee JA, Kim DH, Seo JH, Lim JS. Early menarche is associated with metabolic syndrome and insulin resistance in premenopausal Korean women. Eur J Pediatr 2016;175:97-104. ArticlePubMedPDF
  • 6. Heys M, Schooling CM, Jiang C, Cowling BJ, Lao X, Zhang W, Cheng KK, Adab P, Thomas GN, Lam TH, Leung GM. Age of menarche and the metabolic syndrome in China. Epidemiology 2007;18:740-746. ArticlePubMed
  • 7. Friedewald WT, Levy RI, Fredrickson DS. Estimation of the concentration of low-density lipoprotein cholesterol in plasma, without use of the preparative ultracentrifuge. Clin Chem 1972;18:499-502. ArticlePubMedPDF
  • 8. Expert Panel on Detection, Evaluation, and Treatment of High Blood Cholesterol in Adults. Executive summary of the third report of the National Cholesterol Education Program (NCEP) Expert Panel on Detection, Evaluation, and Treatment of High Blood Cholesterol in Adults (Adult Treatment Panel III). JAMA 2001;285:2486-2497. ArticlePubMed
  • 9. Schisterman EF, Faraggi D, Reiser B, Hu J. Youden index and the optimal threshold for markers with mass at zero. Stat Med 2008;27:297-315. ArticlePubMedPMC
  • 10. Park YW, Zhu S, Palaniappan L, Heshka S, Carnethon MR, Heymsfield SB. The metabolic syndrome: prevalence and associated risk factor findings in the US population from the Third National Health and Nutrition Examination Survey, 1988-1994. Arch Intern Med 2003;163:427-436. ArticlePubMedPMC
  • 11. Shalitin S, Phillip M. Role of obesity and leptin in the pubertal process and pubertal growth: a review. Int J Obes Relat Metab Disord 2003;27:869-874. ArticlePubMedPDF
  • 12. Biro FM, Wien M. Childhood obesity and adult morbidities. Am J Clin Nutr 2010;91:1499S-1505S. ArticlePubMedPMC
  • 13. Cai L, Liu A, Zhang Y, Wang P. Waist-to-height ratio and cardiovascular risk factors among Chinese adults in Beijing. PLoS One 2013;8:e69298ArticlePubMedPMC
  • 14. Kahn HS. The “lipid accumulation product” performs better than the body mass index for recognizing cardiovascular risk: a population-based comparison. BMC Cardiovasc Disord 2005;5:26ArticlePubMedPMCPDF
  • 15. Chen BD, Yang YN, Ma YT, Pan S, He CH, Liu F, Ma X, Fu ZY, Li XM, Xie X, Zheng YY. Waist-to-height ratio and triglycerides/high-density lipoprotein cholesterol were the optimal predictors of metabolic syndrome in uighur men and women in Xinjiang, China. Metab Syndr Relat Disord 2015;13:214-220. ArticlePubMed
  • 16. Munoz-Garach A, Cornejo-Pareja I, Tinahones FJ. Does metabolically healthy obesity exist? Nutrients 2016;8:E320
  • 17. Must A, Phillips SM, Naumova EN, Blum M, Harris S, Dawson-Hughes B, Rand WM. Recall of early menstrual history and menarcheal body size: after 30 years, how well do women remember? Am J Epidemiol 2002;155:672-679. ArticlePubMed
Table 1

Characteristics of study population

dmj-41-146-i001.jpg
Characteristic Metabolic syndrome present (n=82)a Metabolic syndrome absent (n=122)a P value
Current age, yr 38.9±6.4 37.3±6.8 0.09
Age at menarche, yr 11.6±1.1 13.2±1.8 <0.01
BMI, kg/m2 33.6±4.2 32.5±4.6 0.08
Overweight/obese 0.20
 Overweight 20 (24.4) 40 (32.8)
 Obese 62 (75.6) 82 (67.2)
Parity 0.07
 0–2 47 (57.3) 85 (69.7)
 ≥3 35 (42.7) 37 (30.3)
Ever use of contraception (yes) 26 (31.7) 34 (27.9) 0.56
WC, cm 104.3±12.0 103.6±13.2 0.69
WC ≥88 cm 81 (98.8) 109 (89.3) 0.01
SBP, mm Hg 124.5±14.3 113.3±10.3 <0.01
SBP ≥130 mm Hg 41 (50.0) 9 (7.4) <0.01
DBP, mm Hg 78.0±9.1 71.5±7.5 <0.01
DBP ≥85 mm Hg 18 (22.0) 3 (2.5) <0.01
FBG, mg/dL 109.5±12.7 98.2±16.7 <0.01
FBG ≥100 mg/dL 69 (84.1) 46 (37.7) <0.01
HDL-C, mg/dL 49.3±11.5 54.7±9.6 <0.01
HDL-C <50 mg/dL 49 (59.8) 32 (26.2) <0.01
TG, mg/dL 134.1±34.9 100.8±23.7 <0.01
TG ≥150 mg/dL 39 (47.6) 6 (4.9) <0.01
LDL-C, mg/dL 132.2±31.5 126.0±30.6 0.16
TC, mg/dL 208.3±33.4 200.8±30.3 0.10

Values are presented as mean±standard deviation or number (%).

BMI, body mass index; WC, waist circumference; SBP, systolic blood pressure; DBP, diastolic blood pressure; FBG, fasting blood glucose; HDL-C, high density lipoprotein cholesterol; TG, triglyceride; LDL-C, low density lipoprotein cholesterol; TC, total cholesterol.

aDefined by the National Cholesterol Education Program-Adult Treatment Panel III [9].

Table 2

Prediction of metabolic syndrome by age at menarche using receiver operating characteristic curve analysis

dmj-41-146-i002.jpg
Age at menarche cutoff point, yr AUC (95% CI) P valuea Sensitivity, % Specificity, % NPV, % PPV, % Accuracy, %
≤12.25 0.76 (0.70–0.83) <0.01 82 70 85 64 75

AUC, area under the curve; CI, confidence interval; NPV, negative predictive value; PPV, positive predictive value.

aSignificance of AUC.

Figure & Data

References

    Citations

    Citations to this article as recorded by  
    • Prevalence of the metabolic syndrome in African populations: A systematic review and meta-analysis
      Arnol Bowo-Ngandji, Sebastien Kenmoe, Jean Thierry Ebogo-Belobo, Raoul Kenfack-Momo, Guy Roussel Takuissu, Cyprien Kengne-Ndé, Donatien Serge Mbaga, Serges Tchatchouang, Josiane Kenfack-Zanguim, Robertine Lontuo Fogang, Elisabeth Zeuko’o Menkem, Juliette
      PLOS ONE.2023; 18(7): e0289155.     CrossRef
    • Separate and combined effects of famine exposure and menarche age on metabolic syndrome among the elderly: a cross-sectional study in China
      Congzhi Wang, Jiazhi Wang, Rui Wan, Ting Yuan, Liu Yang, Dongmei Zhang, Xiaoping Li, Haiyang Liu, Lin Zhang
      BMC Women's Health.2023;[Epub]     CrossRef
    • Association between Age at Menarche and Metabolic Syndrome in Southwest Iran: A Population-Based Case-Control Study
      Zahra Rahimi, Nader Saki, Bahman Cheraghian, Sara Sarvandian, Seyed Jalal Hashemi, Jamileh Kaabi, Amal Saki Malehi, Arman Shahriari, Nahal Nasehi
      Journal of Research in Health Sciences.2022; 22(3): e00558.     CrossRef
    • The role of multiparity and maternal age at first pregnancy in the association between early menarche and metabolic syndrome among middle-aged and older women
      Tiago Novais Rocha, Pedro Rafael de Souza Macêdo, Afshin Vafaei, Dimitri Taurino Guedes, Ingrid Guerra Azevedo, Álvaro Campos Cavalcanti Maciel, Saionara Maria Aires da Câmara
      Menopause.2021; 28(9): 1004.     CrossRef
    • Association of Early Menarche with Adolescent Health in the Setting of Rapidly Decreasing Age at Menarche
      Eun Jeong Yu, Seung-Ah Choe, Jae-Won Yun, Mia Son
      Journal of Pediatric and Adolescent Gynecology.2020; 33(3): 264.     CrossRef
    • Relationship between age at menarche and chromosome numerical abnormalities in chorionic villus among missed abortions: A cross‐sectional study of 459 women in China
      Lu Zhao, Hua Yang, Guoyan Liu
      Journal of Obstetrics and Gynaecology Research.2020; 46(12): 2582.     CrossRef
    • Age at menarche and clinical outcomes following medically assisted reproduction (MAR): a cohort study
      Paraskevi Vogiatzi, Abraham Pouliakis, Stefano Bettocchi, George Daskalakis, Tereza Vrantza, Charalampos Siristatidis
      Gynecological Endocrinology.2019; 35(5): 448.     CrossRef

    • PubReader PubReader
    • Cite
      CITE
      export Copy
      Close
      Download Citation
      Download a citation file in RIS format that can be imported by all major citation management software, including EndNote, ProCite, RefWorks, and Reference Manager.

      Format:
      • RIS — For EndNote, ProCite, RefWorks, and most other reference management software
      • BibTeX — For JabRef, BibDesk, and other BibTeX-specific software
      Include:
      • Citation for the content below
      A Cutoff for Age at Menarche Predicting Metabolic Syndrome in Egyptian Overweight/Obese Premenopausal Women
      Diabetes Metab J. 2017;41(2):146-149.   Published online November 30, 2016
      Close
    • XML DownloadXML Download

    Diabetes Metab J : Diabetes & Metabolism Journal