- Email: [email protected]
Age at menarche and non-alcoholic fatty liver disease
Research Article
Age at menarche and non-alcoholic fatty liver disease Seungho Ryu1,2,⇑, , Yoosoo Chang1,2, , Yuni Choi2, Min-Jung Kwon2,3, Chan-Won Kim2, Kyung Eun Yun2, Hyun-Suk Jung2, Bo-Kyoung Kim2, Yoo Jin Kim2, Jiin Ahn2, Yong Kyun Cho4, Kye-Hyun Kim5, Eun Chul Chung2,6, Hocheol Shin7, Juhee Cho2,8 1
Department of Occupational and Environmental Medicine, Kangbuk Samsung Hospital, Sungkyunkwan University, School of Medicine, Seoul, South Korea; 2Center for Cohort Studies, Total Healthcare Center, Kangbuk Samsung Hospital, Sungkyunkwan University, School of Medicine, Seoul, South Korea; 3Department of Laboratory Medicine, Kangbuk Samsung Hospital, Sungkyunkwan University, School of Medicine, Seoul, South Korea; 4Division of Gastroenterology and Hepatology, Department of Internal Medicine, Kangbuk Samsung Hospital, Sungkyunkwan University, School of Medicine, Seoul, South Korea; 5Department of Obstetrics and Gynecology, Kangbuk Samsung Hospital, Sungkyunkwan University, School of Medicine, Seoul, South Korea; 6Department of Radiology, Kangbuk Samsung Hospital, Sungkyunkwan University, School of Medicine, Seoul, South Korea; 7Department of Family Medicine, Kangbuk Samsung Hospital, Sungkyunkwan University, School of Medicine, Seoul, South Korea; 8Department of Health Sciences and Technology, Samsung Advanced Institute for Health Sciences and Technology, Sungkyunkwan University, Seoul, South Korea
Background & Aims: The goal of this study was to examine the association between age at menarche and non-alcoholic fatty liver disease (NAFLD) in Korean women and to explore whether any observed associations were mediated by adult adiposity. Methods: A cross-sectional study was performed for 95,183 Korean women, aged 30 or older, who underwent a regular health screening examination between March 2011 and April 2013. Information regarding age at menarche was collected using standardized, self-administered questionnaires. The presence of fatty liver was determined using ultrasonographic findings. Poisson regression models with robust variance were used to evaluate the association between age at menarche and NAFLD. Results: Of the 76,415 women evaluated in this study, 9601 had NAFLD. Age at menarche was inversely associated with the prevalence of NAFLD. In a multivariable-adjusted model, the prevalence ratios (95% CIs) for NAFLD comparing menarche at <12, 12, 14, 15, and 16–18 years to menarche at 13 years were 1.31 (1.18–1.45), 1.05 (0.97–1.13), 0.93 (0.87–0.99), 0.87 (0.82–0.93), and 0.78 (0.73–0.84), respectively (p for trend <0.001). Adjusting for adult BMI or percent fat mass (%) substantially reduced these associations; however, they remained statistically significant. The association between age at menarche and NAFLD was modified by age.
Keywords: Age at menarche; NAFLD; Early menarche; Obesity. Received 9 September 2014; received in revised form 3 November 2014; accepted 26 November 2014; available online 11 December 2014 ⇑ Corresponding author. Address: Department of Occupational and Environmental Medicine, Kangbuk Samsung Hospital, Sungkyunkwan University, School of Medicine, Samsung Main Building B2, 250, Taepyung-ro 2ga, Jung-gu, Seoul 100-742, South Korea. Tel.: +82 2 2001 5137; fax: +82 2 757 0436. E-mail address: [email protected] (S. Ryu). These authors contributed equally to this work. Abbreviations: ALT, alanine aminotransferase; BMI, body mass index; CI, confidence interval; FLI, fatty liver index; HEPA, health-enhancing physically active; HOMA-IR, homeostasis model assessment of insulin resistance; HDL-C, high-density lipoprotein-cholesterol; LDL-C, low-density lipoprotein-cholesterol; NAFLD, non-alcoholic fatty liver disease.
Conclusions: We identified an inverse association between age at menarche and NAFLD in a large sample of middle-aged women. This association was partially mediated by adiposity. The findings of this study suggest that obesity prevention strategies are needed in women who undergo early menarche to reduce the risk of NAFLD. Ó 2014 European Association for the Study of the Liver. Published by Elsevier B.V. All rights reserved.
Introduction Menarche represents a significant event in the reproductive life of a woman. In the last several years, age at menarche has received a great deal of attention concerning its implications for women’s health [1]. Early menarche is considered an important medical and social problem, since it may result in increased morbidity and mortality in later life [2]. Indeed, a growing number of epidemiologic studies have suggested an association between early menarche and adverse outcomes including obesity, diabetes, insulin resistance, metabolic syndrome, cardiovascular disease, stroke, and mortality [1,3–8]. Non-alcoholic fatty liver disease (NAFLD) encompasses a broad spectrum of liver disease from simple steatosis to non-alcoholic steatohepatitis [9,10]. In addition to its potential to progress to cirrhosis or hepatocellular carcinoma [11], recent evidence from epidemiological studies have linked NAFLD to a substantial increase in risk for metabolic complications such as diabetes and cardiovascular disease [12–15]. These associations are supported by several reports that have described a close link between NAFLD and metabolic disorders such as obesity, insulin resistance, and metabolic syndrome [16,17], all of which are likely to develop in women who undergo early menarche. Therefore, it is hypothesized that the metabolic milieu in women who experience early menarche may trigger several pathophysiologic
Journal of Hepatology 2015 vol. 62 j 1164–1170
JOURNAL OF HEPATOLOGY processes associated with NAFLD. In addition, the association between early menarche and NAFLD has implications for public health and clinical research as the average age at menarche has declined in recent years, coinciding with an increasing prevalence of obesity and NAFLD [18–20]. The association between early menarche and NAFLD remains largely unexplored and only one study has reported an inverse association between age at menarche and NAFLD among both Caucasian white and black women [21,22]. It should be noted that insulin resistance and reproductive factors such as parity, menopausal stage and use of oral contraceptives, which could influence the association with NAFLD, were not considered in the study described above. Therefore, the goal of this study was to examine the association between age at menarche and NAFLD in a large sample of Korean women, and to explore whether any observed associations were caused by adult adiposity or insulin resistance.
Materials and methods
squared (kg/m2). We classified BMI according to the criteria proposed for Asian populations [30]. Measurements for serum biochemical parameters, including glucose, uric acid, hemoglobin A1c, insulin, total cholesterol, triglycerides, low-density lipoprotein-cholesterol (LDL-C), and high-density lipoprotein-cholesterol (HDL-C) are described in detail elsewhere [23,24]. The Laboratory Medicine Department at Kangbuk Samsung Hospital in Seoul (Korea) is accredited by the Korean Society of Laboratory Medicine (KSLM) and the Korean Association of Quality Assurance for Clinical Laboratories (KAQACL); the laboratory participates in the CAP (College of American Pathologists) Survey Proficiency Testing. Hypertension was defined as a systolic blood pressure P140 mmHg, diastolic blood pressure P90 mmHg, or current use of antihypertensive medication. Diabetes was defined as a fasting serum glucose P126 mg/dl, hemoglobin A1c P6.5%, or current use of insulin or antidiabetic medications. Abdominal ultrasounds were performed using a Logic Q700 MR 3.5-MHz transducer (GE, Milwaukee, WI, USA) by eleven experienced radiologists, all of whom were unaware of the aims of this study. Images were captured in a standard fashion with the patient in the supine position with the right arm raised above the head. An ultrasonographic diagnosis of fatty liver was defined as the presence of a diffuse increase of fine echoes in the liver parenchyma compared with the kidney or spleen parenchyma [31]. The inter-observer reliability and intra-observer reliability for fatty liver diagnosis were substantial (kappa statistic of 0.74) and excellent (kappa statistic of 0.94), respectively [23]. Statistical analyses
Study population The Kangbuk Samsung Health Study was a cohort study comprising Korean men and women who underwent a comprehensive annual or biennial examination at the Kangbuk Samsung Hospital Total Healthcare Center in Seoul and Suwon, South Korea [23,24]. The study population for the present study consisted of women, aged 30 or older, who underwent a comprehensive health examination at the Kangbuk Samsung Hospital Total Healthcare Center in Seoul and Suwon, South Korea from March 2011 to April 2013 (n = 95,183). We excluded 18,768 participants for various reasons, chiefly missing data for abdominal ultrasonography, alcohol intake, or age at menarche (n = 3785); a past history of a malignancy (n = 3870); alcohol intake of P20 g/day (n = 4730) [25]; known liver disease or use of medications for liver disease (n = 5037); positive serologic markers for hepatitis B or C virus (n = 3086); use of medications associated with NAFLD within the past year such as valproate, amiodarone, methotrexate, tamoxifen, or corticosteroids (n = 905) [25]; and a reported age at menarche greater than 18 years, which may reflect an underlying pathological issue (n = 4839). Because some individuals met more than one exclusion criterion, the total number of patients eligible for the study was 76,415. This study was approved by the Institutional Review Board of Kangbuk Samsung Hospital, and the requirement for informed consent was waived because we used non-identified retrospective data routinely collected during the health screening process. Measurements All examinations were conducted at Kangbuk Samsung Hospital Health Screening Center clinics in Seoul and Suwon. Information regarding reproductive factors was collected using standardized, self-administered questionnaires that asked about regularity and frequency of menstrual periods, menopausal status, and use of oral contraceptives and hormone replacement therapy. Age at menarche was defined as the age at the first menstrual period (in years). The question asked, ‘‘At what age did your menstrual periods begin?’’. Response categories were ‘‘10 or younger, 11, 12, 13, 14, 15, 16, 17, 18, 19, and 20 or older.’’ The normal physiological age range at menarche was considered to be less than 19 years. Early menarche was defined as onset of menstruation occurring before the age of 12 [26]. Parity was derived from the number of reported live births and stillbirths. Data on demographic characteristics, smoking status, alcohol consumption, regular exercise, education level, medical history, and medication use were also collected by standardized, self-administered questionnaires as previously described [23,24]. Physical activity levels were assessed using the Korea-validated version of the International Physical Activity Questionnaire (IPAQ) short form and were classified into three categories: inactive, minimally active, and health-enhancing physically active (HEPA) [27,28]. Recalled body weight was self-reported via questionnaire at recruitment. Height, weight, and body composition were measured by trained nurses with the participants wearing a lightweight hospital gown and no shoes. The percentage of body fat was estimated using a multi-frequency bioimpedance analyzer with eight point tactile electrodes (InBody 720, Biospace Co., Seoul Korea), which was validated with respect to reproducibility and accuracy for body composition [29]. Body mass index (BMI) was calculated as weight (kg) divided by height (m)
Characteristics of the study participants were explored according to age at menarche, which was categorized into the following groups: <12 (early menarche), 12, 13 (the reference category), 14, 15, and 16–18 years. To test for linear trends, category numbers were used as continuous variables in regression models. To evaluate the association of NAFLD across categories of ages at menarche, we used robust Poisson regression with robust variance to estimate prevalence ratios with 95% confidence intervals (CIs) for NAFLD. We used four models to progressively reduce confounding associations. We initially adjusted for age, and further adjusted for study center (Seoul, Suwon), year of screening exam, smoking (never, past, current, or unknown), alcohol intake (0, <10, P10 g/d, or unknown), physical activity level (inactive, minimally active, HEPA, or unknown) and educational level. We next included the following reproductive factors: parity (no child, one or two children, three or more children), menopausal status (pre-menopause, late menopausal transition, early post-menopause or late post-menopause) [32], use of the oral contraceptive (ever or never), and use of hormone replacement therapy. Finally, the analysis was further adjusted for body weight at age 20. To assess whether the association between age at menarche and the prevalence of NAFLD was mediated by BMI, percent fat mass (%) or HOMA-IR, we included these variables in multivariable models. We performed stratified analyses in pre-specified subgroups defined by menopause (yes vs. no), age (<50 vs. P50 years), parity (ever vs. never), smoking (never smoker vs. ex- or current smoker), alcohol intake (<10 vs. P10 g of alcohol per day) and physical activity (no HEPA vs. HEPA); interactions between subgroups were tested using likelihood ratio tests comparing models with and without multiplicative interaction terms. We also examined the association between age at menarche and fatty liver index (FLI) as a surrogate marker of NAFLD in a sensitivity analysis. The FLI was calculated according to the published formula: Fatty liver index = (e 0.953 ⁄ loge (triglycerides) + 0.139 ⁄ BMI + 0.718 ⁄ loge (ggt) + 0.053 ⁄ waist circumference 15.745 )/(1 + e 0.953 ⁄ loge (triglycerides) + 0.139 ⁄ BMI + 0.718 ⁄ loge (ggt) + 0.053 ⁄ waist circumference 15.745 ) 100 [33]. Subjects were divided into three groups: FLI <30, 306 FLI <60 and FLI P60 [33]. Lastly, we examined the association of age at menarche with NAFLD and its severity. In individuals with NAFLD, serum markers of fibrosis were used to assess severity. NFS was calculated according to the published formula: NFS = 1.675 + 0.037 age (years) + 0.094 BMI (kg/m2) + 1.13 impaired fasting glycemia or diabetes (yes = 1, no = 0) + 0.99 AST/ALT ratio 0.013 platelet (109/L) 0.66 albumin (g/dl) [34]. The AST/platelet ratio index (APRI) was calculated as AST/ULN (upper limit of normal)/Platelets 100 [35]. The AST/ALT ratio was calculated as ratio of AST to ALT values [36]. All p values were two-tailed, and values of p <0.05 were considered statistically significant. We used STATA version 13.0 (Stata Corp., College Station, TX, USA) for data analysis.
Results The baseline characteristics of subjects by categories of ages at menarche are presented in Table 1. The mean age and BMI of
Journal of Hepatology 2015 vol. 62 j 1164–1170
1165
Research Article Table 1. Baseline characteristics of study participants according to age at menarche.
Characteristics
Overall
Number of participants Age (years) Body mass index (kg/m2)d Fat mass percentage (%)d Weight at age 20 (kg) Current smoker (%) Alcohol intake (%)a HEPA (%) Education level (%)b Parity ever (%) Menopause (%) Use of HRT (%) Use of oral contraceptive (%) Diabetes (%) Hypertension (%) Systolic BP (mmHg)d Diastolic BP (mmHg)d Glucose (mg/dl)d Total cholesterol (mg/dl)d LDL-C (mg/dl)d HDL-C (mg/dl)d Triglycerides (mg/dl)e ALT (U/L)e hsCRP (mg/L)e HOMA-IRe, f
76,415 40.9 (8.5) 21.7 (2.9) 29.1 (5.8) 50.5 (5.3) 2.2 8.8 7.8 74.5 88.5 14.9 4.4 0.4 2.4 6.6 103.5 (12.3) 65.8 (8.7) 92.8 (12.2) 189.1 (33.2) 112.4 (30.1) 64.1 (14.4) 72 (55-99) 13 (11-18) 0.3 (0.2-0.7) 0.99 (0.66-1.44)
<12 3562 36.1 (5.0) 22.0 (3.0) 29.6 (5.7) 51.8 (5.8) 1.7 10.3 5.8 92.8 82.2 4.4 4.1 0.7 0.9 3.0 101.0 (10.8) 64.5 (8.0) 90.6 (8.8) 186.0 (31.3) 108.8 (27.7) 65.2 (14.4) 69 (54-92) 13 (10-16) 0.3 (0.2-0.7) 1.02 (0.67-1.49)
12 10,421 37.3 (5.7) 21.8 (2.9) 29.3 (5.7) 51.3 (5.5) 2.1 8.9 6.6 89.0 83.3 6.0 3.3 0.6 1.4 3.0 101.7 (11.3) 64.8 (8.2) 91.6 (11.3) 186.0 (32.1) 108.9 (28.4) 64.7 (14.5) 69 (54-93) 13 (10-17) 0.3 (0.2-0.7) 1.02 (0.68-1.49)
Age at menarche (years) 13 14 16,539 18,082 38.9 (6.6) 40.6 (7.5) 21.6 (2.9) 21.6 (2.9) 28.9 (5.7) 28.8 (5.8) 50.6 (5.3) 50.2 (5.1) 2.0 2.1 8.8 8.4 6.7 8.0 83.4 75.8 86.9 89.3 8.6 12.7 3.6 4.1 0.4 0.4 1.8 1.9 4.6 5.5 102.4 (11.6) 103.4 (12.2) 65.3 (8.5) 65.8 (8.6) 92.1 (11.6) 92.7 (11.4) 186.7 (31.6) 189.0 (33.4) 109.9 (28.5) 112.2 (30.4) 64.6 (14.3) 64.4 (14.4) 70 (55-96) 71 (55-97) 13 (10-17) 13 (11-17) 0.3 (0.2-0.6) 0.3 (0.2-0.6) 1.01 0.98 (0.67-1.47) (0.66-1.44)
15 16,655 42.2 (8.3) 21.7 (2.9) 28.9 (5.8) 50.1(5.2) 2.5 9.2 8.5 68.3 91.3 17.0 4.5 0.4 2.5 7.3 104.1 (12.6) 66.2 (8.8) 93.2 (12.8) 190.0 (33.4) 113.6 (30.4) 63.8 (14.3) 73 (56-100) 14 (11-18) 0.3 (0.2-0.6) 0.97 (0.65-1.40)
16-18 11,156 47.5 (11.0) 22.2 (3.0) 29.8 (6.1) 50.0 (5.4) 2.8 8.5 10.2 49.4 92.4 37.0 7.1 0.3 5.2 14.8 107.0 (13.8) 67.6 (9.2) 95.1 (14.6) 195.3 (35.2) 119.3 (32.7) 62.4 (14.6) 79 (58-111) 15 (11-20) 0.3 (0.2-0.7) 0.97 (0.65-1.44)
p value <0.001 <0.001 0.004 <0.001 <0.001 0.093 <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 <0.001 0.485 <0.001
Data are d mean (standard deviation), e median (interquartile range), or percentage. ALT, alanine aminotransferase; BMI, body mass index; BP, blood pressure; HDL-C, high-density lipoprotein-cholesterol; HEPA, health-enhancing physical activity; hsCRP, high sensitivity C-reactive protein; HOMA-IR, homeostasis model assessment of insulin resistance; HRT, hormone replacement therapy; LDL-C, low-density lipoproteincholesterol. a P0 g of ethanol per day. b PCollege graduate. f In non-diabetics only (n = 73,639).
Table 2. Prevalence ratiosa (95% CI) of NAFLD according to age at menarche.
<12 3562 404 (11.3) 1.26 (1.14-1.39)
12 10,421 1064 (10.2) 1.04 (0.97-1.12)
Age at menarche (years) 13 14 16,539 18,082 1833 (11.1) 2156 (11.9) 1.00 (ref.) 0.94 (0.89-1.00)
Number Cases of NAFLD (%) Age-adjusted PR Multivariate-adjusted PRa Model 1 1.28 (1.16-1.41) 1.06 (0.98-1.13) 1.00 (ref.) Model 2 1.30 (1.18-1.45) 1.08 (1.00-1.16) 1.00 (ref.) Model 3 1.31 (1.18-1.45) 1.05 (0.97-1.13) 1.00 (ref.)
15 16,655 2167 (13.0) 0.91 (0.86-0.97)
p value 16-18 11,156 1977 (17.7) 0.83 (0.78-0.89) <0.001
0.93 (0.88-0.98) 0.88 (0.83-0.93) 0.79 (0.74-0.84) <0.001 0.92 (0.87-0.98) 0.87 (0.82-0.93) 0.79 (0.74-0.84) <0.001 0.93 (0.87-0.99) 0.87 (0.82-0.93) 0.78 (0.73-0.84) <0.001
a
Estimated from Poisson regression with robust error. Multivariable model 1 was adjusted for age, center, year of screening exam, smoking status, alcohol intake, physical activity levels and educational level; model 2: model 1 plus adjustment for parity, use of hormone replacement therapy, use of oral contraceptives, menopausal status; model 3: model 2 plus adjustment for weight at age 20.
the 76,415 women were 40.9 years (SD: 8.5) and 21.7 kg/m2 (SD: 2.9; range: 12.5–44.3), respectively. The prevalence of current smoking, diabetes, hypertension, and obesity were 2.2%, 2.4%, 6.6%, and 12.6%, respectively. There were clear dose-response relationships among some of the variables and age at menarche. Specifically, individuals with a younger age at menarche were 1166
more likely to be younger at baseline, likely reflecting the secular decline in age at menarche. Compared to women with menarche at 13–14 years of age, those with early menarche or late menarche tended to have a higher BMI and fat mass percentage. Smoking, physical activity, parity, systolic and diastolic blood pressures, glucose, total cholesterol, triglycerides, LDL-C, and
Journal of Hepatology 2015 vol. 62 j 1164–1170
JOURNAL OF HEPATOLOGY Table 3. Mediation analysis of the association between age at menarche and NAFLD.
Model 1-PRa (95% CI) Model 2-PRa (95% CI) Model 3-PRa (95% CI)
<12 1.12 (1.01-1.25) 1.10 (1.00-1.22) 1.29 (1.16-1.44)
12 0.98 (0.90-1.06) 0.95 (0.88-1.02) 0.95 (0.88-1.03)
Age at menarche (years) 13 14 1.00 (ref.) 0.94 (0.87-1.02) 1.00 (ref.) 0.96 (0.90-1.02) 1.00 (ref.) 0.92 (0.87-0.98)
15 0.97 (0.91-1.05) 0.96 (0.90-1.02) 0.87 (0.81-0.92)
p value 16-18 0.91 (0.83-0.99) 0.006 0.89 (0.83-0.95) 0.002 0.79 (0.73-0.84) <0.001
a
Estimated from Poisson regression with robust error. Multivariable model 1 was adjusted for age, center, year of screening exam, smoking status, alcohol intake, physical activity levels, educational level, parity, use of hormone replacement therapy, use of oral contraceptives, menopausal status, weight at age 20 and BMI at recruitment; model 2: model 1 plus adjustment for fat percent instead of BMI at recruitment; model 3: model 1 plus adjustment for HOMA-IR instead of BMI at recruitment.
Table 4. Prevalence ratiosa (95% CI) of NAFLD according to age at menarche in clinically relevant subgroups.
Subgroup <12 Menopause No (N = 62,307) Yes (N = 10,875) Age <50 yr (N = 65,721) ≥50 yr (N = 10,693) Parity Never (N = 8530) Ever (N = 65,421) Smoking Never (N = 53,202) Ever smoker (N = 2905) Alcohol intake <10 g/day (N = 69,669) ≥10 g/day (N = 6746) HEPA No (N = 65,457) Yes (N = 5550)
12
Age at menarche (years) 13 14 15
16-18
p for trend
p for interaction 0.265
1.31 (1.17-1.47) 1.02 (0.94-1.11) ref. 1.17 (0.81-1.71) 1.25 (1.03-1.52) ref.
0.89 (0.83-0.96) 0.82 (0.76-0.88) 0.72 (0.66-0.79) <0.001 1.06 (0.92-1.21) 1.03 (0.90-1.18) 0.99 (0.87-1.13) 0.060
1.17 (1.05-1.31) 0.97 (0.89-1.05) ref. 1.50 (1.08-2.09) 1.26 (1.05-1.53) ref.
0.94 (0.88-1.01) 0.88 (0.82-0.95) 0.80 (0.73-0.88) <0.001 1.05 (0.92-1.20) 1.08 (0.96-1.22) 1.05 (0.93-1.19) 0.370
0.93 (0.64-1.35) 1.06 (0.83-1.35) ref. 1.37 (1.22-1.53) 1.06 (0.98-1.14) ref.
0.91 (0.71-1.17) 0.81 (0.62-1.06) 0.75 (0.55-1.04) 0.029 0.93 (0.88-1.00) 0.88 (0.83-0.95) 0.79 (0.73-0.85) <0.001
1.29 (1.14-1.46) 1.04 (0.95-1.13) ref. 1.26 (0.74-2.14) 1.26 (0.87-1.82) ref.
0.91 (0.84-0.98) 0.85 (0.79-0.92) 0.75 (0.69-0.82) <0.001 1.08 (0.78-1.52) 1.12 (0.80-1.57) 0.86 (0.58-1.28) 0.181
1.32 (1.18-1.48) 1.04 (0.96-1.13) ref.
0.93 (0.87-0.99) 0.87 (0.81-0.93) 0.78 (0.72-0.83) <0.001
1.18 (0.84-1.65) 1.09 (0.84-1.40) ref.
0.86 (0.68-1.07) 0.87 (0.69-1.08) 0.85 (0.67-1.09) 0.017
1.32 (1.18-1.48) 1.04 (0.96-1.12) ref. 1.19 (0.76-1.86) 0.97 (0.72-1.30) ref.
0.93 (0.87-0.99) 0.87 (0.81-0.93) 0.79 (0.73-0.85) <0.001 0.78 (0.61-0.98) 0.89 (0.71-1.12) 0.79 (0.62-1.00) 0.052
0.033
0.250
0.657
0.487
0.618
a
Estimated from Poisson regression with robust error. Multivariable model 1 was adjusted for age, center, year of screening exam, smoking status, alcohol intake, physical activity levels, educational level, parity, use of hormone replacement therapy, use of oral contraceptives, menopausal status, weight at age 20 and BMI at recruit.
ALT were positively associated with age at menarche. On the other hand, body weight at 20 years, education level, HDL-C and HOMA-IR were negatively associated with age at menarche. The proportions of individuals at menopause or who had diabetes, hypertension, or use of hormone replacement therapy were also increased across age at menarche categories. Table 2 shows the relationship between age at menarche and NAFLD. Of the 76,415 women included in this study, 9601 had NAFLD. Age at menarche was inversely associated with the prevalence of NAFLD. In an age-adjusted model, the prevalence ratios (95% CIs) for NAFLD comparing menarche at <12 (early menarche), 12, 14, 15, and 16–18 years with menarche at 13 years were: 1.26 (1.14–1.39), 1.04 (0.97–1.12), 0.94 (0.89–1.00), 0.91 (0.86–0.97), and 0.83 (0.78–0.89), respectively. After adjusting further for screening center, year of screening exam, smoking status, alcohol intake, physical activity, and educational level, age at menarche was still significantly associated with decreasing prevalence of NAFLD (p for trend <0.001). In addition, this association persisted after further adjustment for reproductive factors
and body weight at 20 years of age. The prevalence ratios (95% CIs) for NAFLD comparing menarche at <12, 12, 14, 15, and 16–18 years to menarche at 13 years were 1.31 (1.18–1.45), 1.05 (0.97–1.13), 0.93 (0.87–0.99), 0.87 (0.82–0.93), and 0.78 (0.73–0.84), respectively (p for trend <0.001). In order to explore if the association between age at menarche and NAFLD was mediated by adiposity and insulin resistance, we performed additional analyses adjusting for adult BMI, percent fat mass (%) and HOMA-IR. Our results did not change after further adjustments for HOMA-IR. Specifically, adjusting for adult BMI or percent fat mass (%) substantially reduced the identified associations but they remained statistically significant (Table 3). The association between age at menarche and NAFLD was next examined in subgroups of study participants (Table 4). First, the association between age at menarche and NAFLD was modified by age. The adverse effect of early menarche on NAFLD was stronger in older women (age P50) than in younger women (age <50), while the protective effect of late menarche on NAFLD was observed only in younger women. The association
Journal of Hepatology 2015 vol. 62 j 1164–1170
1167
Research Article between age at menarche and NAFLD was similar across participant subgroups with no significant interactions between menopause (no vs. yes), parity (never vs. ever), smoking status (never smoker vs. ex- or current smoker), alcohol intake (<10 vs. P10 g of alcohol per day), and physical activity (no HEPA vs. HEPA). In a sensitivity analysis, we examined the association of age at menarche with the FLI as a surrogate marker of NAFLD. The prevalence ratios for FLI 30–59.9 comparing menarche at <12, 12, 14, 15, and 16–18 years with menarche at 13 years were similar to those for NAFLD (Supplementary Table 1). We also examined the association of age at menarche with NAFLD and its severity. Age at menarche was inversely associated with NAFLD and its severity according to NFS. Using either AST/ALT ratio or APRI instead of NFS did not qualitatively alter these estimates (Supplementary Table 2). When we re-analyzed considering three categories: early, medium, and late, an inverse linear association between categories of age at menarche and prevalence of NAFLD was observed (Supplementary Table 3).
Discussion There are several novel findings in the present study of a large sample of middle-aged women. First, we observed an inverse linear association between age at menarche and prevalence of NAFLD. This association persisted even after multivariable adjustment for reproductive factors and body weight at age 20. Second, this inverse association was partially mediated by adult BMI or percent fat mass. Third, this association was modified by age. Specifically, the adverse effect of early menarche on NAFLD was stronger in older women aged P50 than in younger women aged <50, while the protective effect of late menarche on NAFLD was observed only in women aged <50. A growing number of epidemiologic studies have suggested an association between early menarche and adverse outcomes. Specifically, several cohort studies have shown that age at menarche is inversely associated with type 2 diabetes, and that this association is mediated by adult obesity [5,37,38]. In addition, many epidemiologic studies have reported that early menarche is associated with insulin resistance, metabolic syndrome, and cardiovascular disease [3–8]. Also, early menarche has long been associated with increased risk of breast cancer [39], uterine leiomyomata [40], and endometrial cancer [41]. Recently, results from a meta-analysis showed that early menarche is consistently associated with higher risk of death from all causes [1]. In this study, we observed an inverse linear association between age at menarche and the prevalence of NAFLD. This finding is consistent with an earlier study that reported an inverse association between age at menarche and NAFLD [21,22]. The mechanism by which age at menarche is inversely associated with the prevalence of NAFLD was not elucidated in this study. However, early menarche has been consistently associated with adult obesity [42,43]. Thus, because obesity is a major risk factor for NAFLD, adiposity may represent a possible mechanism linking early menarche with increased risk of NAFLD [44]. However, it is unclear whether childhood adiposity is an early-life trigger of age at menarche, or if menarche age is a proxy for the pace of sexual maturation, which itself leads to differences in adiposity during the pubertal period that persists into adult life [4,7,43]. In our study, the association between age at menarche and NAFLD did not change qualitatively after adjusting for body
1168
weight at age 20, which is more likely related to pre-menarcheal adiposity than adiposity assessed in later adulthood [5]. However, the association with NAFLD was substantially attenuated after adjusting for adult BMI or percent fat mass (%), even though it remained statistically significant. Mueller also reported an attenuation of the association between age at menarche and NAFLD after accounting for adult BMI [21]. This finding may suggest that excess adiposity in adulthood is more important in mediating the increased risk of NAFLD related to early menarche than BMI earlier in life, and furthermore that age at menarche may have some direct effects on NAFLD through biological pathways independent of adiposity. Insulin resistance syndrome may be another possible mechanism to explain the relationship between early menarche and NAFLD, as this condition is strongly associated with early menarche [6]. Indeed, NAFLD is now considered an hepatic manifestation of insulin resistance and a feature of metabolic syndrome [45,46]. In this study, however, the association between age at menarche and NAFLD was not attenuated after adjusting for HOMA-IR. The mechanism by which the association between early menarche and NAFLD was modified by age in the current study remains unclear. Broadly speaking, the effect of a given set of risk factors on the development of a disease is established both by the magnitude of the deviation of these factors from normal and by the duration of exposure [47]. Thus, age may be to a large extent a reflection of the length of exposure to risk factor burden [47]. In this study, long-term exposure of risk factors including obesity – as a result of early menarche – may have increased the risk for NAFLD in older women (age P50) than in younger women (age <50). Previous studies showed that duration of obesity is an independent risk factor for adverse health outcome [48,49]. A major strength of our study is the large sample size, which allowed us to examine associations among stratified subgroups. In addition, our findings were strengthened by a comprehensive use of potential confounding variables including reproductive factors. However, our study has some limitations that should be considered. First, histologic proof (i.e. biopsy) of NAFLD was not included, as it is not appropriate to perform invasive tests in a population-based epidemiological study [50]. However, since fat deposition in the liver may be satisfactorily diagnosed non-invasively by ultrasonography or other imaging tests, many population-based studies have relied on ultrasound examination to diagnose NAFLD [51,52]. Furthermore, we examined the association between age at menarche and FLI as a surrogate marker of NAFLD, and found that the results did not change qualitatively. Future studies should investigate whether there is a causal relationship between age at menarche and the development of NAFLD. Second, because age at menarche was retrospectively assessed by recall, misclassification was inevitable. However, it has been demonstrated that age at menarche is usually well-recalled into adulthood, with age at menarche assessed by recall during adulthood exhibiting a high correlation with prospectively assessed childhood data [53,54]. Third, we did not measure adiposity before menarche directly. Instead, we adjusted values based on women’s recalled body weight at 20 years of age. Because body weight at 20 years of age was retrospectively assessed by recall, some level of misclassification was inevitable. However, self-reporting by middle-aged men of weight in early adulthood has been shown to be moderately accurate (r = 0.80) [55]. Fourth, the cross-sectional design of our study limited our
Journal of Hepatology 2015 vol. 62 j 1164–1170
JOURNAL OF HEPATOLOGY ability to establish temporal relationships and infer causality. However, all examinations including ultrasound were performed after the participants had completed the questionnaires and physical exams, thus minimizing the risk of reverse causation. Finally, our study population consisted of approximately middle-aged women in Asia; thus, our results may not be generally applicable to other populations. In conclusion, this study demonstrated an inverse relationship between age at menarche and NAFLD in a large sample of middle-aged Korean women. The adverse effect of early menarche on NAFLD was partially mediated by adult adiposity. The findings of this study suggest that obesity prevention strategies are needed in women with early menarche to reduce the risk of NAFLD.
Conflict of interest The authors who have taken part in this study declared that they do not have anything to disclose regarding funding or conflict of interest with respect to this manuscript.
Authors’ contributions RS and CY planned and designed the study, and directed its implementation, including quality assurance and control. RS and CY analyzed the data and designed the study’s analytic strategy. CJ, JEC, CYK, KKH, and SH helped supervise the field activities. CY, KMJ, KCW, YKE, JHS, KBK, KYJ, and AJ helped conduct the literature review and prepare the Materials and Methods and the Discussion sections of the manuscript. RS drafted the manuscript. RS, CY, CY, KMJ, KCW, YKE, JHS, KBK, KYJ, AJ, CJ, JEC, CYK, KKH, and SH interpreted the results. All authors contributed to critical revision of the manuscript.
Supplementary data Supplementary data associated with this article can be found, in the online version, at http://dx.doi.org/10.1016/j.jhep.2014.11. 041.
References [1] Charalampopoulos D, McLoughlin A, Elks CE, Ong KK. Age at menarche and risks of all-cause and cardiovascular death: a systematic review and meta-analysis. Am J Epidemiol 2014;180:29–40. [2] Walvoord EC. The timing of puberty: is it changing? Does it matter? J Adolesc Health 2010;47:433–439. [3] Kivimaki M, Lawlor DA, Smith GD, Elovainio M, Jokela M, Keltikangas-Jarvinen L, et al. Association of age at menarche with cardiovascular risk factors, vascular structure, and function in adulthood: the Cardiovascular Risk in Young Finns study. Am J Clin Nutr 2008;87: 1876–1882. [4] Remsberg KE, Demerath EW, Schubert CM, Chumlea WC, Sun SS, Siervogel RM. Early menarche and the development of cardiovascular disease risk factors in adolescent girls: the Fels Longitudinal Study. J Clin Endocrinol Metab 2005;90:2718–2724. [5] Elks CE, Ong KK, Scott RA, van der Schouw YT, Brand JS, Wark PA, et al. Age at menarche and type 2 diabetes risk: the EPIC-InterAct study. Diabetes Care 2013;36:3526–3534.
[6] Heys M, Schooling CM, Jiang C, Cowling BJ, Lao X, Zhang W, et al. Age of menarche and the metabolic syndrome in China. Epidemiology 2007;18: 740–746. [7] Pierce MB, Leon DA. Age at menarche and adult BMI in the Aberdeen children of the 1950s cohort study. Am J Clin Nutr 2005;82:733–739. [8] Okamoto K, Horisawa R, Kawamura T, Asai A, Ogino M, Takagi T, et al. Menstrual and reproductive factors for subarachnoid hemorrhage risk in women: a case-control study in nagoya, Japan. Stroke 2001;32:2841–2844. [9] Adams LA, Sanderson S, Lindor KD, Angulo P. The histological course of nonalcoholic fatty liver disease: a longitudinal study of 103 patients with sequential liver biopsies. J Hepatol 2005;42:132–138. [10] Caldwell SH, Crespo DM. The spectrum expanded: cryptogenic cirrhosis and the natural history of non-alcoholic fatty liver disease. J Hepatol 2004;40: 578–584. [11] Ascha MS, Hanouneh IA, Lopez R, Tamimi TA, Feldstein AF, Zein NN. The incidence and risk factors of hepatocellular carcinoma in patients with nonalcoholic steatohepatitis. Hepatology 2010;51:1972–1978. [12] Adams LA, Waters OR, Knuiman MW, Elliott RR, Olynyk JK. NAFLD as a risk factor for the development of diabetes and the metabolic syndrome: an eleven-year follow-up study. Am J Gastroenterol 2009;104:861–867. [13] Targher G, Day CP, Bonora E. Risk of cardiovascular disease in patients with nonalcoholic fatty liver disease. N Engl J Med 2010;363:1341–1350. [14] Targher G, Bertolini L, Padovani R, Rodella S, Zoppini G, Pichiri I, et al. Prevalence of non-alcoholic fatty liver disease and its association with cardiovascular disease in patients with type 1 diabetes. J Hepatol 2010;53: 713–718. [15] Bhatia LS, Curzen NP, Calder PC, Byrne CD. Non-alcoholic fatty liver disease: a new and important cardiovascular risk factor? Eur Heart J 2012;33: 1190–1200. [16] Zelber-Sagi S, Lotan R, Shlomai A, Webb M, Harrari G, Buch A, et al. Predictors for incidence and remission of NAFLD in the general population during a seven-year prospective follow-up. J Hepatol 2012;56:1145–1151. [17] Kumashiro N, Erion DM, Zhang D, Kahn M, Beddow SA, Chu X, et al. Cellular mechanism of insulin resistance in nonalcoholic fatty liver disease. Proc Natl Acad Sci U S A 2011;108:16381–16385. [18] Demerath EW, Towne B, Chumlea WC, Sun SS, Czerwinski SA, Remsberg KE, et al. Recent decline in age at menarche: the Fels Longitudinal Study. Am J Hum Biol 2004;16:453–457. [19] Lazo M, Clark JM. The epidemiology of nonalcoholic fatty liver disease: a global perspective. Semin Liver Dis 2008;28:339–350. [20] Cho GJ, Park HT, Shin JH, Hur JY, Kim YT, Kim SH, et al. Age at menarche in a Korean population: secular trends and influencing factors. Eur J Pediatr 2010;169:89–94. [21] Mueller NT. Early puberty: adulthood metabolic consequences and childhood nutritional determinants [doctorate thesis]. Minneapolis: University of Minnesota; 2013. [22] Mueller NT, Pereira MA, Demerath EW, Dreyfus JG, MacLehose RF, Carr JJ, et al. Age at menarche is inversely associated with liver steatosis and abdominal fat depots: CARDIA Study. Circulation 2014;129:AMP68, [abstract]. [23] Kim CW, Yun KE, Jung HS, Chang Y, Choi ES, Kwon MJ, et al. Sleep duration and quality in relation to non-alcoholic fatty liver disease in middle-aged workers and their spouses. J Hepatol 2013;59:351–357. [24] Chang Y, Kim BK, Yun KE, Cho J, Zhang Y, Rampal S, et al. Metabolically-healthy obesity and coronary artery calcification. J Am Coll Cardiol 2014;63:2679–2686. [25] Chalasani N, Younossi Z, Lavine JE, Diehl AM, Brunt EM, Cusi K, et al. The diagnosis and management of non-alcoholic fatty liver disease: practice Guideline by the American Association for the Study of Liver Diseases, American College of Gastroenterology, and the American Gastroenterological Association. Hepatology 2012;55:2005–2023. [26] Gaudineau A, Ehlinger V, Vayssiere C, Jouret B, Arnaud C, Godeau E. Factors associated with early menarche: results from the French Health Behaviour in School-aged Children (HBSC) study. BMC Public Health 2010;10:175. [27] Craig CL, Marshall AL, Sjostrom M, Bauman AE, Booth ML, Ainsworth BE, et al. International physical activity questionnaire: 12-country reliability and validity. Med Sci Sports Exerc 2003;35:1381–1395. [28] Oh JY, Yang YJ, Kim BS, Kang JH. Validity and reliability of Korean version of International Physical Activity Questionnaire (IPAQ) short form. Korean J Fam Med 2007;28:532–541. [29] Malavolti M, Mussi C, Poli M, Fantuzzi AL, Salvioli G, Battistini N, et al. Cross-calibration of eight-polar bioelectrical impedance analysis versus dual-energy X-ray absorptiometry for the assessment of total and appendicular body composition in healthy subjects aged 21–82 years. Ann Hum Biol 2003;30:380–391.
Journal of Hepatology 2015 vol. 62 j 1164–1170
1169
Research Article [30] Wen CP, David Cheng TY, Tsai SP, Chan HT, Hsu HL, Hsu CC, et al. Are Asians at greater mortality risks for being overweight than Caucasians? Redefining obesity for Asians. Public Health Nutr 2009;12:497–506. [31] Mathiesen UL, Franzen LE, Aselius H, Resjo M, Jacobsson L, Foberg U, et al. Increased liver echogenicity at ultrasound examination reflects degree of steatosis but not of fibrosis in asymptomatic patients with mild/moderate abnormalities of liver transaminases. Dig Liver Dis 2002;34:516–522. [32] Harlow SD, Gass M, Hall JE, Lobo R, Maki P, Rebar RW, et al. Executive summary of the Stages of Reproductive Aging Workshop + 10: addressing the unfinished agenda of staging reproductive aging. J Clin Endocrinol Metab 2012;97:1159–1168. [33] Bedogni G, Bellentani S, Miglioli L, Masutti F, Passalacqua M, Castiglione A, et al. The Fatty Liver Index: a simple and accurate predictor of hepatic steatosis in the general population. BMC Gastroenterol 2006;6:33. [34] Angulo P, Hui JM, Marchesini G, Bugianesi E, George J, Farrell GC, et al. The NAFLD fibrosis score: a noninvasive system that identifies liver fibrosis in patients with NAFLD. Hepatology 2007;45:846–854. [35] Wai CT, Greenson JK, Fontana RJ, Kalbfleisch JD, Marrero JA, Conjeevaram HS, et al. A simple noninvasive index can predict both significant fibrosis and cirrhosis in patients with chronic hepatitis C. Hepatology 2003;38:518–526. [36] Giannini E, Risso D, Botta F, Chiarbonello B, Fasoli A, Malfatti F, et al. Validity and clinical utility of the aspartate aminotransferase-alanine aminotransferase ratio in assessing disease severity and prognosis in patients with hepatitis C virus-related chronic liver disease. Arch Intern Med 2003;163: 218–224. [37] He C, Zhang C, Hunter DJ, Hankinson SE, Buck Louis GM, Hediger ML, et al. Age at menarche and risk of type 2 diabetes: results from 2 large prospective cohort studies. Am J Epidemiol 2010;171:334–344. [38] Dreyfus JG, Lutsey PL, Huxley R, Pankow JS, Selvin E, Fernandez-Rhodes L, et al. Age at menarche and risk of type 2 diabetes among African-American and white women in the Atherosclerosis Risk in Communities (ARIC) study. Diabetologia 2012;55:2371–2380. [39] Velie EM, Nechuta S, Osuch JR. Lifetime reproductive and anthropometric risk factors for breast cancer in postmenopausal women. Breast Dis 2005;24:17–35. [40] Marshall LM, Spiegelman D, Goldman MB, Manson JE, Colditz GA, Barbieri RL, et al. A prospective study of reproductive factors and oral contraceptive use in relation to the risk of uterine leiomyomata. Fertil Steril 1998;70: 432–439.
1170
[41] McPherson CP, Sellers TA, Potter JD, Bostick RM, Folsom AR. Reproductive factors and risk of endometrial cancer. The Iowa Women’s Health Study. Am J Epidemiol 1996;143:1195–1202. [42] Prentice P, Viner RM. Pubertal timing and adult obesity and cardiometabolic risk in women and men: a systematic review and meta-analysis. Int J Obes 2013;37:1036–1043. [43] Feng Y, Hong X, Wilker E, Li Z, Zhang W, Jin D, et al. Effects of age at menarche, reproductive years, and menopause on metabolic risk factors for cardiovascular diseases. Atherosclerosis 2008;196:590–597. [44] Chang Y, Ryu S, Sung E, Woo HY, Cho SI, Yoo SH, et al. Weight gain within the normal weight range predicts ultrasonographically detected fatty liver in healthy Korean men. Gut 2009;58:1419–1425. [45] Marchesini G, Marzocchi R, Agostini F, Bugianesi E. Nonalcoholic fatty liver disease and the metabolic syndrome. Curr Opin Lipidol 2005;16:421–427. [46] Fan JG, Peng YD. Metabolic syndrome and non-alcoholic fatty liver disease: Asian definitions and Asian studies. Hepatobiliary Pancreat Dis Int 2007; 6:572–578. [47] Sniderman AD, Furberg CD. Age as a modifiable risk factor for cardiovascular disease. Lancet 2008;371:1547–1549. [48] Abdullah A, Wolfe R, Stoelwinder JU, de Courten M, Stevenson C, Walls HL, et al. The number of years lived with obesity and the risk of all-cause and cause-specific mortality. Int J Epidemiol 2011;40:985–996. [49] Abdullah A, Stoelwinder J, Shortreed S, Wolfe R, Stevenson C, Walls H, et al. The duration of obesity and the risk of type 2 diabetes. Public Health Nutr 2011;14:119–126. [50] Joy D, Thava VR, Scott BB. Diagnosis of fatty liver disease: is biopsy necessary? Eur J Gastroenterol Hepatol 2003;15:539–543. [51] Clark JM, Diehl AM. Defining nonalcoholic fatty liver disease: implications for epidemiologic studies. Gastroenterology 2003;124:248–250. [52] Bellentani S, Tiribelli C. The spectrum of liver disease in the general population: lesson from the Dionysos study. J Hepatol 2001;35:531–537. [53] Must A, Phillips SM, Naumova EN, Blum M, Harris S, Dawson-Hughes B, et al. Recall of early menstrual history and menarcheal body size: after 30 years, how well do women remember? Am J Epidemiol 2002;155:672–679. [54] Casey VA, Dwyer JT, Coleman KA, Krall EA, Gardner J, Valadian I. Accuracy of recall by middle-aged participants in a longitudinal study of their body size and indices of maturation earlier in life. Ann Hum Biol 1991;18:155–166. [55] Rhoads GG, Kagan A. The relation of coronary disease, stroke, and mortality to weight in youth and in middle age. Lancet 1983;1:492–495.
Journal of Hepatology 2015 vol. 62 j 1164–1170
Age at menarche and non-alcoholic fatty liver disease Seungho Ryu1,2,⇑, , Yoosoo Chang1,2, , Yuni Choi2, Min-Jung Kwon2,3, Chan-Won Kim2, Kyung Eun Yun2, Hyun-Suk Jung2, Bo-Kyoung Kim2, Yoo Jin Kim2, Jiin Ahn2, Yong Kyun Cho4, Kye-Hyun Kim5, Eun Chul Chung2,6, Hocheol Shin7, Juhee Cho2,8 1
Department of Occupational and Environmental Medicine, Kangbuk Samsung Hospital, Sungkyunkwan University, School of Medicine, Seoul, South Korea; 2Center for Cohort Studies, Total Healthcare Center, Kangbuk Samsung Hospital, Sungkyunkwan University, School of Medicine, Seoul, South Korea; 3Department of Laboratory Medicine, Kangbuk Samsung Hospital, Sungkyunkwan University, School of Medicine, Seoul, South Korea; 4Division of Gastroenterology and Hepatology, Department of Internal Medicine, Kangbuk Samsung Hospital, Sungkyunkwan University, School of Medicine, Seoul, South Korea; 5Department of Obstetrics and Gynecology, Kangbuk Samsung Hospital, Sungkyunkwan University, School of Medicine, Seoul, South Korea; 6Department of Radiology, Kangbuk Samsung Hospital, Sungkyunkwan University, School of Medicine, Seoul, South Korea; 7Department of Family Medicine, Kangbuk Samsung Hospital, Sungkyunkwan University, School of Medicine, Seoul, South Korea; 8Department of Health Sciences and Technology, Samsung Advanced Institute for Health Sciences and Technology, Sungkyunkwan University, Seoul, South Korea
Background & Aims: The goal of this study was to examine the association between age at menarche and non-alcoholic fatty liver disease (NAFLD) in Korean women and to explore whether any observed associations were mediated by adult adiposity. Methods: A cross-sectional study was performed for 95,183 Korean women, aged 30 or older, who underwent a regular health screening examination between March 2011 and April 2013. Information regarding age at menarche was collected using standardized, self-administered questionnaires. The presence of fatty liver was determined using ultrasonographic findings. Poisson regression models with robust variance were used to evaluate the association between age at menarche and NAFLD. Results: Of the 76,415 women evaluated in this study, 9601 had NAFLD. Age at menarche was inversely associated with the prevalence of NAFLD. In a multivariable-adjusted model, the prevalence ratios (95% CIs) for NAFLD comparing menarche at <12, 12, 14, 15, and 16–18 years to menarche at 13 years were 1.31 (1.18–1.45), 1.05 (0.97–1.13), 0.93 (0.87–0.99), 0.87 (0.82–0.93), and 0.78 (0.73–0.84), respectively (p for trend <0.001). Adjusting for adult BMI or percent fat mass (%) substantially reduced these associations; however, they remained statistically significant. The association between age at menarche and NAFLD was modified by age.
Keywords: Age at menarche; NAFLD; Early menarche; Obesity. Received 9 September 2014; received in revised form 3 November 2014; accepted 26 November 2014; available online 11 December 2014 ⇑ Corresponding author. Address: Department of Occupational and Environmental Medicine, Kangbuk Samsung Hospital, Sungkyunkwan University, School of Medicine, Samsung Main Building B2, 250, Taepyung-ro 2ga, Jung-gu, Seoul 100-742, South Korea. Tel.: +82 2 2001 5137; fax: +82 2 757 0436. E-mail address: [email protected] (S. Ryu). These authors contributed equally to this work. Abbreviations: ALT, alanine aminotransferase; BMI, body mass index; CI, confidence interval; FLI, fatty liver index; HEPA, health-enhancing physically active; HOMA-IR, homeostasis model assessment of insulin resistance; HDL-C, high-density lipoprotein-cholesterol; LDL-C, low-density lipoprotein-cholesterol; NAFLD, non-alcoholic fatty liver disease.
Conclusions: We identified an inverse association between age at menarche and NAFLD in a large sample of middle-aged women. This association was partially mediated by adiposity. The findings of this study suggest that obesity prevention strategies are needed in women who undergo early menarche to reduce the risk of NAFLD. Ó 2014 European Association for the Study of the Liver. Published by Elsevier B.V. All rights reserved.
Introduction Menarche represents a significant event in the reproductive life of a woman. In the last several years, age at menarche has received a great deal of attention concerning its implications for women’s health [1]. Early menarche is considered an important medical and social problem, since it may result in increased morbidity and mortality in later life [2]. Indeed, a growing number of epidemiologic studies have suggested an association between early menarche and adverse outcomes including obesity, diabetes, insulin resistance, metabolic syndrome, cardiovascular disease, stroke, and mortality [1,3–8]. Non-alcoholic fatty liver disease (NAFLD) encompasses a broad spectrum of liver disease from simple steatosis to non-alcoholic steatohepatitis [9,10]. In addition to its potential to progress to cirrhosis or hepatocellular carcinoma [11], recent evidence from epidemiological studies have linked NAFLD to a substantial increase in risk for metabolic complications such as diabetes and cardiovascular disease [12–15]. These associations are supported by several reports that have described a close link between NAFLD and metabolic disorders such as obesity, insulin resistance, and metabolic syndrome [16,17], all of which are likely to develop in women who undergo early menarche. Therefore, it is hypothesized that the metabolic milieu in women who experience early menarche may trigger several pathophysiologic
Journal of Hepatology 2015 vol. 62 j 1164–1170
JOURNAL OF HEPATOLOGY processes associated with NAFLD. In addition, the association between early menarche and NAFLD has implications for public health and clinical research as the average age at menarche has declined in recent years, coinciding with an increasing prevalence of obesity and NAFLD [18–20]. The association between early menarche and NAFLD remains largely unexplored and only one study has reported an inverse association between age at menarche and NAFLD among both Caucasian white and black women [21,22]. It should be noted that insulin resistance and reproductive factors such as parity, menopausal stage and use of oral contraceptives, which could influence the association with NAFLD, were not considered in the study described above. Therefore, the goal of this study was to examine the association between age at menarche and NAFLD in a large sample of Korean women, and to explore whether any observed associations were caused by adult adiposity or insulin resistance.
Materials and methods
squared (kg/m2). We classified BMI according to the criteria proposed for Asian populations [30]. Measurements for serum biochemical parameters, including glucose, uric acid, hemoglobin A1c, insulin, total cholesterol, triglycerides, low-density lipoprotein-cholesterol (LDL-C), and high-density lipoprotein-cholesterol (HDL-C) are described in detail elsewhere [23,24]. The Laboratory Medicine Department at Kangbuk Samsung Hospital in Seoul (Korea) is accredited by the Korean Society of Laboratory Medicine (KSLM) and the Korean Association of Quality Assurance for Clinical Laboratories (KAQACL); the laboratory participates in the CAP (College of American Pathologists) Survey Proficiency Testing. Hypertension was defined as a systolic blood pressure P140 mmHg, diastolic blood pressure P90 mmHg, or current use of antihypertensive medication. Diabetes was defined as a fasting serum glucose P126 mg/dl, hemoglobin A1c P6.5%, or current use of insulin or antidiabetic medications. Abdominal ultrasounds were performed using a Logic Q700 MR 3.5-MHz transducer (GE, Milwaukee, WI, USA) by eleven experienced radiologists, all of whom were unaware of the aims of this study. Images were captured in a standard fashion with the patient in the supine position with the right arm raised above the head. An ultrasonographic diagnosis of fatty liver was defined as the presence of a diffuse increase of fine echoes in the liver parenchyma compared with the kidney or spleen parenchyma [31]. The inter-observer reliability and intra-observer reliability for fatty liver diagnosis were substantial (kappa statistic of 0.74) and excellent (kappa statistic of 0.94), respectively [23]. Statistical analyses
Study population The Kangbuk Samsung Health Study was a cohort study comprising Korean men and women who underwent a comprehensive annual or biennial examination at the Kangbuk Samsung Hospital Total Healthcare Center in Seoul and Suwon, South Korea [23,24]. The study population for the present study consisted of women, aged 30 or older, who underwent a comprehensive health examination at the Kangbuk Samsung Hospital Total Healthcare Center in Seoul and Suwon, South Korea from March 2011 to April 2013 (n = 95,183). We excluded 18,768 participants for various reasons, chiefly missing data for abdominal ultrasonography, alcohol intake, or age at menarche (n = 3785); a past history of a malignancy (n = 3870); alcohol intake of P20 g/day (n = 4730) [25]; known liver disease or use of medications for liver disease (n = 5037); positive serologic markers for hepatitis B or C virus (n = 3086); use of medications associated with NAFLD within the past year such as valproate, amiodarone, methotrexate, tamoxifen, or corticosteroids (n = 905) [25]; and a reported age at menarche greater than 18 years, which may reflect an underlying pathological issue (n = 4839). Because some individuals met more than one exclusion criterion, the total number of patients eligible for the study was 76,415. This study was approved by the Institutional Review Board of Kangbuk Samsung Hospital, and the requirement for informed consent was waived because we used non-identified retrospective data routinely collected during the health screening process. Measurements All examinations were conducted at Kangbuk Samsung Hospital Health Screening Center clinics in Seoul and Suwon. Information regarding reproductive factors was collected using standardized, self-administered questionnaires that asked about regularity and frequency of menstrual periods, menopausal status, and use of oral contraceptives and hormone replacement therapy. Age at menarche was defined as the age at the first menstrual period (in years). The question asked, ‘‘At what age did your menstrual periods begin?’’. Response categories were ‘‘10 or younger, 11, 12, 13, 14, 15, 16, 17, 18, 19, and 20 or older.’’ The normal physiological age range at menarche was considered to be less than 19 years. Early menarche was defined as onset of menstruation occurring before the age of 12 [26]. Parity was derived from the number of reported live births and stillbirths. Data on demographic characteristics, smoking status, alcohol consumption, regular exercise, education level, medical history, and medication use were also collected by standardized, self-administered questionnaires as previously described [23,24]. Physical activity levels were assessed using the Korea-validated version of the International Physical Activity Questionnaire (IPAQ) short form and were classified into three categories: inactive, minimally active, and health-enhancing physically active (HEPA) [27,28]. Recalled body weight was self-reported via questionnaire at recruitment. Height, weight, and body composition were measured by trained nurses with the participants wearing a lightweight hospital gown and no shoes. The percentage of body fat was estimated using a multi-frequency bioimpedance analyzer with eight point tactile electrodes (InBody 720, Biospace Co., Seoul Korea), which was validated with respect to reproducibility and accuracy for body composition [29]. Body mass index (BMI) was calculated as weight (kg) divided by height (m)
Characteristics of the study participants were explored according to age at menarche, which was categorized into the following groups: <12 (early menarche), 12, 13 (the reference category), 14, 15, and 16–18 years. To test for linear trends, category numbers were used as continuous variables in regression models. To evaluate the association of NAFLD across categories of ages at menarche, we used robust Poisson regression with robust variance to estimate prevalence ratios with 95% confidence intervals (CIs) for NAFLD. We used four models to progressively reduce confounding associations. We initially adjusted for age, and further adjusted for study center (Seoul, Suwon), year of screening exam, smoking (never, past, current, or unknown), alcohol intake (0, <10, P10 g/d, or unknown), physical activity level (inactive, minimally active, HEPA, or unknown) and educational level. We next included the following reproductive factors: parity (no child, one or two children, three or more children), menopausal status (pre-menopause, late menopausal transition, early post-menopause or late post-menopause) [32], use of the oral contraceptive (ever or never), and use of hormone replacement therapy. Finally, the analysis was further adjusted for body weight at age 20. To assess whether the association between age at menarche and the prevalence of NAFLD was mediated by BMI, percent fat mass (%) or HOMA-IR, we included these variables in multivariable models. We performed stratified analyses in pre-specified subgroups defined by menopause (yes vs. no), age (<50 vs. P50 years), parity (ever vs. never), smoking (never smoker vs. ex- or current smoker), alcohol intake (<10 vs. P10 g of alcohol per day) and physical activity (no HEPA vs. HEPA); interactions between subgroups were tested using likelihood ratio tests comparing models with and without multiplicative interaction terms. We also examined the association between age at menarche and fatty liver index (FLI) as a surrogate marker of NAFLD in a sensitivity analysis. The FLI was calculated according to the published formula: Fatty liver index = (e 0.953 ⁄ loge (triglycerides) + 0.139 ⁄ BMI + 0.718 ⁄ loge (ggt) + 0.053 ⁄ waist circumference 15.745 )/(1 + e 0.953 ⁄ loge (triglycerides) + 0.139 ⁄ BMI + 0.718 ⁄ loge (ggt) + 0.053 ⁄ waist circumference 15.745 ) 100 [33]. Subjects were divided into three groups: FLI <30, 306 FLI <60 and FLI P60 [33]. Lastly, we examined the association of age at menarche with NAFLD and its severity. In individuals with NAFLD, serum markers of fibrosis were used to assess severity. NFS was calculated according to the published formula: NFS = 1.675 + 0.037 age (years) + 0.094 BMI (kg/m2) + 1.13 impaired fasting glycemia or diabetes (yes = 1, no = 0) + 0.99 AST/ALT ratio 0.013 platelet (109/L) 0.66 albumin (g/dl) [34]. The AST/platelet ratio index (APRI) was calculated as AST/ULN (upper limit of normal)/Platelets 100 [35]. The AST/ALT ratio was calculated as ratio of AST to ALT values [36]. All p values were two-tailed, and values of p <0.05 were considered statistically significant. We used STATA version 13.0 (Stata Corp., College Station, TX, USA) for data analysis.
Results The baseline characteristics of subjects by categories of ages at menarche are presented in Table 1. The mean age and BMI of
Journal of Hepatology 2015 vol. 62 j 1164–1170
1165
Research Article Table 1. Baseline characteristics of study participants according to age at menarche.
Characteristics
Overall
Number of participants Age (years) Body mass index (kg/m2)d Fat mass percentage (%)d Weight at age 20 (kg) Current smoker (%) Alcohol intake (%)a HEPA (%) Education level (%)b Parity ever (%) Menopause (%) Use of HRT (%) Use of oral contraceptive (%) Diabetes (%) Hypertension (%) Systolic BP (mmHg)d Diastolic BP (mmHg)d Glucose (mg/dl)d Total cholesterol (mg/dl)d LDL-C (mg/dl)d HDL-C (mg/dl)d Triglycerides (mg/dl)e ALT (U/L)e hsCRP (mg/L)e HOMA-IRe, f
76,415 40.9 (8.5) 21.7 (2.9) 29.1 (5.8) 50.5 (5.3) 2.2 8.8 7.8 74.5 88.5 14.9 4.4 0.4 2.4 6.6 103.5 (12.3) 65.8 (8.7) 92.8 (12.2) 189.1 (33.2) 112.4 (30.1) 64.1 (14.4) 72 (55-99) 13 (11-18) 0.3 (0.2-0.7) 0.99 (0.66-1.44)
<12 3562 36.1 (5.0) 22.0 (3.0) 29.6 (5.7) 51.8 (5.8) 1.7 10.3 5.8 92.8 82.2 4.4 4.1 0.7 0.9 3.0 101.0 (10.8) 64.5 (8.0) 90.6 (8.8) 186.0 (31.3) 108.8 (27.7) 65.2 (14.4) 69 (54-92) 13 (10-16) 0.3 (0.2-0.7) 1.02 (0.67-1.49)
12 10,421 37.3 (5.7) 21.8 (2.9) 29.3 (5.7) 51.3 (5.5) 2.1 8.9 6.6 89.0 83.3 6.0 3.3 0.6 1.4 3.0 101.7 (11.3) 64.8 (8.2) 91.6 (11.3) 186.0 (32.1) 108.9 (28.4) 64.7 (14.5) 69 (54-93) 13 (10-17) 0.3 (0.2-0.7) 1.02 (0.68-1.49)
Age at menarche (years) 13 14 16,539 18,082 38.9 (6.6) 40.6 (7.5) 21.6 (2.9) 21.6 (2.9) 28.9 (5.7) 28.8 (5.8) 50.6 (5.3) 50.2 (5.1) 2.0 2.1 8.8 8.4 6.7 8.0 83.4 75.8 86.9 89.3 8.6 12.7 3.6 4.1 0.4 0.4 1.8 1.9 4.6 5.5 102.4 (11.6) 103.4 (12.2) 65.3 (8.5) 65.8 (8.6) 92.1 (11.6) 92.7 (11.4) 186.7 (31.6) 189.0 (33.4) 109.9 (28.5) 112.2 (30.4) 64.6 (14.3) 64.4 (14.4) 70 (55-96) 71 (55-97) 13 (10-17) 13 (11-17) 0.3 (0.2-0.6) 0.3 (0.2-0.6) 1.01 0.98 (0.67-1.47) (0.66-1.44)
15 16,655 42.2 (8.3) 21.7 (2.9) 28.9 (5.8) 50.1(5.2) 2.5 9.2 8.5 68.3 91.3 17.0 4.5 0.4 2.5 7.3 104.1 (12.6) 66.2 (8.8) 93.2 (12.8) 190.0 (33.4) 113.6 (30.4) 63.8 (14.3) 73 (56-100) 14 (11-18) 0.3 (0.2-0.6) 0.97 (0.65-1.40)
16-18 11,156 47.5 (11.0) 22.2 (3.0) 29.8 (6.1) 50.0 (5.4) 2.8 8.5 10.2 49.4 92.4 37.0 7.1 0.3 5.2 14.8 107.0 (13.8) 67.6 (9.2) 95.1 (14.6) 195.3 (35.2) 119.3 (32.7) 62.4 (14.6) 79 (58-111) 15 (11-20) 0.3 (0.2-0.7) 0.97 (0.65-1.44)
p value <0.001 <0.001 0.004 <0.001 <0.001 0.093 <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 <0.001 0.485 <0.001
Data are d mean (standard deviation), e median (interquartile range), or percentage. ALT, alanine aminotransferase; BMI, body mass index; BP, blood pressure; HDL-C, high-density lipoprotein-cholesterol; HEPA, health-enhancing physical activity; hsCRP, high sensitivity C-reactive protein; HOMA-IR, homeostasis model assessment of insulin resistance; HRT, hormone replacement therapy; LDL-C, low-density lipoproteincholesterol. a P0 g of ethanol per day. b PCollege graduate. f In non-diabetics only (n = 73,639).
Table 2. Prevalence ratiosa (95% CI) of NAFLD according to age at menarche.
<12 3562 404 (11.3) 1.26 (1.14-1.39)
12 10,421 1064 (10.2) 1.04 (0.97-1.12)
Age at menarche (years) 13 14 16,539 18,082 1833 (11.1) 2156 (11.9) 1.00 (ref.) 0.94 (0.89-1.00)
Number Cases of NAFLD (%) Age-adjusted PR Multivariate-adjusted PRa Model 1 1.28 (1.16-1.41) 1.06 (0.98-1.13) 1.00 (ref.) Model 2 1.30 (1.18-1.45) 1.08 (1.00-1.16) 1.00 (ref.) Model 3 1.31 (1.18-1.45) 1.05 (0.97-1.13) 1.00 (ref.)
15 16,655 2167 (13.0) 0.91 (0.86-0.97)
p value 16-18 11,156 1977 (17.7) 0.83 (0.78-0.89) <0.001
0.93 (0.88-0.98) 0.88 (0.83-0.93) 0.79 (0.74-0.84) <0.001 0.92 (0.87-0.98) 0.87 (0.82-0.93) 0.79 (0.74-0.84) <0.001 0.93 (0.87-0.99) 0.87 (0.82-0.93) 0.78 (0.73-0.84) <0.001
a
Estimated from Poisson regression with robust error. Multivariable model 1 was adjusted for age, center, year of screening exam, smoking status, alcohol intake, physical activity levels and educational level; model 2: model 1 plus adjustment for parity, use of hormone replacement therapy, use of oral contraceptives, menopausal status; model 3: model 2 plus adjustment for weight at age 20.
the 76,415 women were 40.9 years (SD: 8.5) and 21.7 kg/m2 (SD: 2.9; range: 12.5–44.3), respectively. The prevalence of current smoking, diabetes, hypertension, and obesity were 2.2%, 2.4%, 6.6%, and 12.6%, respectively. There were clear dose-response relationships among some of the variables and age at menarche. Specifically, individuals with a younger age at menarche were 1166
more likely to be younger at baseline, likely reflecting the secular decline in age at menarche. Compared to women with menarche at 13–14 years of age, those with early menarche or late menarche tended to have a higher BMI and fat mass percentage. Smoking, physical activity, parity, systolic and diastolic blood pressures, glucose, total cholesterol, triglycerides, LDL-C, and
Journal of Hepatology 2015 vol. 62 j 1164–1170
JOURNAL OF HEPATOLOGY Table 3. Mediation analysis of the association between age at menarche and NAFLD.
Model 1-PRa (95% CI) Model 2-PRa (95% CI) Model 3-PRa (95% CI)
<12 1.12 (1.01-1.25) 1.10 (1.00-1.22) 1.29 (1.16-1.44)
12 0.98 (0.90-1.06) 0.95 (0.88-1.02) 0.95 (0.88-1.03)
Age at menarche (years) 13 14 1.00 (ref.) 0.94 (0.87-1.02) 1.00 (ref.) 0.96 (0.90-1.02) 1.00 (ref.) 0.92 (0.87-0.98)
15 0.97 (0.91-1.05) 0.96 (0.90-1.02) 0.87 (0.81-0.92)
p value 16-18 0.91 (0.83-0.99) 0.006 0.89 (0.83-0.95) 0.002 0.79 (0.73-0.84) <0.001
a
Estimated from Poisson regression with robust error. Multivariable model 1 was adjusted for age, center, year of screening exam, smoking status, alcohol intake, physical activity levels, educational level, parity, use of hormone replacement therapy, use of oral contraceptives, menopausal status, weight at age 20 and BMI at recruitment; model 2: model 1 plus adjustment for fat percent instead of BMI at recruitment; model 3: model 1 plus adjustment for HOMA-IR instead of BMI at recruitment.
Table 4. Prevalence ratiosa (95% CI) of NAFLD according to age at menarche in clinically relevant subgroups.
Subgroup <12 Menopause No (N = 62,307) Yes (N = 10,875) Age <50 yr (N = 65,721) ≥50 yr (N = 10,693) Parity Never (N = 8530) Ever (N = 65,421) Smoking Never (N = 53,202) Ever smoker (N = 2905) Alcohol intake <10 g/day (N = 69,669) ≥10 g/day (N = 6746) HEPA No (N = 65,457) Yes (N = 5550)
12
Age at menarche (years) 13 14 15
16-18
p for trend
p for interaction 0.265
1.31 (1.17-1.47) 1.02 (0.94-1.11) ref. 1.17 (0.81-1.71) 1.25 (1.03-1.52) ref.
0.89 (0.83-0.96) 0.82 (0.76-0.88) 0.72 (0.66-0.79) <0.001 1.06 (0.92-1.21) 1.03 (0.90-1.18) 0.99 (0.87-1.13) 0.060
1.17 (1.05-1.31) 0.97 (0.89-1.05) ref. 1.50 (1.08-2.09) 1.26 (1.05-1.53) ref.
0.94 (0.88-1.01) 0.88 (0.82-0.95) 0.80 (0.73-0.88) <0.001 1.05 (0.92-1.20) 1.08 (0.96-1.22) 1.05 (0.93-1.19) 0.370
0.93 (0.64-1.35) 1.06 (0.83-1.35) ref. 1.37 (1.22-1.53) 1.06 (0.98-1.14) ref.
0.91 (0.71-1.17) 0.81 (0.62-1.06) 0.75 (0.55-1.04) 0.029 0.93 (0.88-1.00) 0.88 (0.83-0.95) 0.79 (0.73-0.85) <0.001
1.29 (1.14-1.46) 1.04 (0.95-1.13) ref. 1.26 (0.74-2.14) 1.26 (0.87-1.82) ref.
0.91 (0.84-0.98) 0.85 (0.79-0.92) 0.75 (0.69-0.82) <0.001 1.08 (0.78-1.52) 1.12 (0.80-1.57) 0.86 (0.58-1.28) 0.181
1.32 (1.18-1.48) 1.04 (0.96-1.13) ref.
0.93 (0.87-0.99) 0.87 (0.81-0.93) 0.78 (0.72-0.83) <0.001
1.18 (0.84-1.65) 1.09 (0.84-1.40) ref.
0.86 (0.68-1.07) 0.87 (0.69-1.08) 0.85 (0.67-1.09) 0.017
1.32 (1.18-1.48) 1.04 (0.96-1.12) ref. 1.19 (0.76-1.86) 0.97 (0.72-1.30) ref.
0.93 (0.87-0.99) 0.87 (0.81-0.93) 0.79 (0.73-0.85) <0.001 0.78 (0.61-0.98) 0.89 (0.71-1.12) 0.79 (0.62-1.00) 0.052
0.033
0.250
0.657
0.487
0.618
a
Estimated from Poisson regression with robust error. Multivariable model 1 was adjusted for age, center, year of screening exam, smoking status, alcohol intake, physical activity levels, educational level, parity, use of hormone replacement therapy, use of oral contraceptives, menopausal status, weight at age 20 and BMI at recruit.
ALT were positively associated with age at menarche. On the other hand, body weight at 20 years, education level, HDL-C and HOMA-IR were negatively associated with age at menarche. The proportions of individuals at menopause or who had diabetes, hypertension, or use of hormone replacement therapy were also increased across age at menarche categories. Table 2 shows the relationship between age at menarche and NAFLD. Of the 76,415 women included in this study, 9601 had NAFLD. Age at menarche was inversely associated with the prevalence of NAFLD. In an age-adjusted model, the prevalence ratios (95% CIs) for NAFLD comparing menarche at <12 (early menarche), 12, 14, 15, and 16–18 years with menarche at 13 years were: 1.26 (1.14–1.39), 1.04 (0.97–1.12), 0.94 (0.89–1.00), 0.91 (0.86–0.97), and 0.83 (0.78–0.89), respectively. After adjusting further for screening center, year of screening exam, smoking status, alcohol intake, physical activity, and educational level, age at menarche was still significantly associated with decreasing prevalence of NAFLD (p for trend <0.001). In addition, this association persisted after further adjustment for reproductive factors
and body weight at 20 years of age. The prevalence ratios (95% CIs) for NAFLD comparing menarche at <12, 12, 14, 15, and 16–18 years to menarche at 13 years were 1.31 (1.18–1.45), 1.05 (0.97–1.13), 0.93 (0.87–0.99), 0.87 (0.82–0.93), and 0.78 (0.73–0.84), respectively (p for trend <0.001). In order to explore if the association between age at menarche and NAFLD was mediated by adiposity and insulin resistance, we performed additional analyses adjusting for adult BMI, percent fat mass (%) and HOMA-IR. Our results did not change after further adjustments for HOMA-IR. Specifically, adjusting for adult BMI or percent fat mass (%) substantially reduced the identified associations but they remained statistically significant (Table 3). The association between age at menarche and NAFLD was next examined in subgroups of study participants (Table 4). First, the association between age at menarche and NAFLD was modified by age. The adverse effect of early menarche on NAFLD was stronger in older women (age P50) than in younger women (age <50), while the protective effect of late menarche on NAFLD was observed only in younger women. The association
Journal of Hepatology 2015 vol. 62 j 1164–1170
1167
Research Article between age at menarche and NAFLD was similar across participant subgroups with no significant interactions between menopause (no vs. yes), parity (never vs. ever), smoking status (never smoker vs. ex- or current smoker), alcohol intake (<10 vs. P10 g of alcohol per day), and physical activity (no HEPA vs. HEPA). In a sensitivity analysis, we examined the association of age at menarche with the FLI as a surrogate marker of NAFLD. The prevalence ratios for FLI 30–59.9 comparing menarche at <12, 12, 14, 15, and 16–18 years with menarche at 13 years were similar to those for NAFLD (Supplementary Table 1). We also examined the association of age at menarche with NAFLD and its severity. Age at menarche was inversely associated with NAFLD and its severity according to NFS. Using either AST/ALT ratio or APRI instead of NFS did not qualitatively alter these estimates (Supplementary Table 2). When we re-analyzed considering three categories: early, medium, and late, an inverse linear association between categories of age at menarche and prevalence of NAFLD was observed (Supplementary Table 3).
Discussion There are several novel findings in the present study of a large sample of middle-aged women. First, we observed an inverse linear association between age at menarche and prevalence of NAFLD. This association persisted even after multivariable adjustment for reproductive factors and body weight at age 20. Second, this inverse association was partially mediated by adult BMI or percent fat mass. Third, this association was modified by age. Specifically, the adverse effect of early menarche on NAFLD was stronger in older women aged P50 than in younger women aged <50, while the protective effect of late menarche on NAFLD was observed only in women aged <50. A growing number of epidemiologic studies have suggested an association between early menarche and adverse outcomes. Specifically, several cohort studies have shown that age at menarche is inversely associated with type 2 diabetes, and that this association is mediated by adult obesity [5,37,38]. In addition, many epidemiologic studies have reported that early menarche is associated with insulin resistance, metabolic syndrome, and cardiovascular disease [3–8]. Also, early menarche has long been associated with increased risk of breast cancer [39], uterine leiomyomata [40], and endometrial cancer [41]. Recently, results from a meta-analysis showed that early menarche is consistently associated with higher risk of death from all causes [1]. In this study, we observed an inverse linear association between age at menarche and the prevalence of NAFLD. This finding is consistent with an earlier study that reported an inverse association between age at menarche and NAFLD [21,22]. The mechanism by which age at menarche is inversely associated with the prevalence of NAFLD was not elucidated in this study. However, early menarche has been consistently associated with adult obesity [42,43]. Thus, because obesity is a major risk factor for NAFLD, adiposity may represent a possible mechanism linking early menarche with increased risk of NAFLD [44]. However, it is unclear whether childhood adiposity is an early-life trigger of age at menarche, or if menarche age is a proxy for the pace of sexual maturation, which itself leads to differences in adiposity during the pubertal period that persists into adult life [4,7,43]. In our study, the association between age at menarche and NAFLD did not change qualitatively after adjusting for body
1168
weight at age 20, which is more likely related to pre-menarcheal adiposity than adiposity assessed in later adulthood [5]. However, the association with NAFLD was substantially attenuated after adjusting for adult BMI or percent fat mass (%), even though it remained statistically significant. Mueller also reported an attenuation of the association between age at menarche and NAFLD after accounting for adult BMI [21]. This finding may suggest that excess adiposity in adulthood is more important in mediating the increased risk of NAFLD related to early menarche than BMI earlier in life, and furthermore that age at menarche may have some direct effects on NAFLD through biological pathways independent of adiposity. Insulin resistance syndrome may be another possible mechanism to explain the relationship between early menarche and NAFLD, as this condition is strongly associated with early menarche [6]. Indeed, NAFLD is now considered an hepatic manifestation of insulin resistance and a feature of metabolic syndrome [45,46]. In this study, however, the association between age at menarche and NAFLD was not attenuated after adjusting for HOMA-IR. The mechanism by which the association between early menarche and NAFLD was modified by age in the current study remains unclear. Broadly speaking, the effect of a given set of risk factors on the development of a disease is established both by the magnitude of the deviation of these factors from normal and by the duration of exposure [47]. Thus, age may be to a large extent a reflection of the length of exposure to risk factor burden [47]. In this study, long-term exposure of risk factors including obesity – as a result of early menarche – may have increased the risk for NAFLD in older women (age P50) than in younger women (age <50). Previous studies showed that duration of obesity is an independent risk factor for adverse health outcome [48,49]. A major strength of our study is the large sample size, which allowed us to examine associations among stratified subgroups. In addition, our findings were strengthened by a comprehensive use of potential confounding variables including reproductive factors. However, our study has some limitations that should be considered. First, histologic proof (i.e. biopsy) of NAFLD was not included, as it is not appropriate to perform invasive tests in a population-based epidemiological study [50]. However, since fat deposition in the liver may be satisfactorily diagnosed non-invasively by ultrasonography or other imaging tests, many population-based studies have relied on ultrasound examination to diagnose NAFLD [51,52]. Furthermore, we examined the association between age at menarche and FLI as a surrogate marker of NAFLD, and found that the results did not change qualitatively. Future studies should investigate whether there is a causal relationship between age at menarche and the development of NAFLD. Second, because age at menarche was retrospectively assessed by recall, misclassification was inevitable. However, it has been demonstrated that age at menarche is usually well-recalled into adulthood, with age at menarche assessed by recall during adulthood exhibiting a high correlation with prospectively assessed childhood data [53,54]. Third, we did not measure adiposity before menarche directly. Instead, we adjusted values based on women’s recalled body weight at 20 years of age. Because body weight at 20 years of age was retrospectively assessed by recall, some level of misclassification was inevitable. However, self-reporting by middle-aged men of weight in early adulthood has been shown to be moderately accurate (r = 0.80) [55]. Fourth, the cross-sectional design of our study limited our
Journal of Hepatology 2015 vol. 62 j 1164–1170
JOURNAL OF HEPATOLOGY ability to establish temporal relationships and infer causality. However, all examinations including ultrasound were performed after the participants had completed the questionnaires and physical exams, thus minimizing the risk of reverse causation. Finally, our study population consisted of approximately middle-aged women in Asia; thus, our results may not be generally applicable to other populations. In conclusion, this study demonstrated an inverse relationship between age at menarche and NAFLD in a large sample of middle-aged Korean women. The adverse effect of early menarche on NAFLD was partially mediated by adult adiposity. The findings of this study suggest that obesity prevention strategies are needed in women with early menarche to reduce the risk of NAFLD.
Conflict of interest The authors who have taken part in this study declared that they do not have anything to disclose regarding funding or conflict of interest with respect to this manuscript.
Authors’ contributions RS and CY planned and designed the study, and directed its implementation, including quality assurance and control. RS and CY analyzed the data and designed the study’s analytic strategy. CJ, JEC, CYK, KKH, and SH helped supervise the field activities. CY, KMJ, KCW, YKE, JHS, KBK, KYJ, and AJ helped conduct the literature review and prepare the Materials and Methods and the Discussion sections of the manuscript. RS drafted the manuscript. RS, CY, CY, KMJ, KCW, YKE, JHS, KBK, KYJ, AJ, CJ, JEC, CYK, KKH, and SH interpreted the results. All authors contributed to critical revision of the manuscript.
Supplementary data Supplementary data associated with this article can be found, in the online version, at http://dx.doi.org/10.1016/j.jhep.2014.11. 041.
References [1] Charalampopoulos D, McLoughlin A, Elks CE, Ong KK. Age at menarche and risks of all-cause and cardiovascular death: a systematic review and meta-analysis. Am J Epidemiol 2014;180:29–40. [2] Walvoord EC. The timing of puberty: is it changing? Does it matter? J Adolesc Health 2010;47:433–439. [3] Kivimaki M, Lawlor DA, Smith GD, Elovainio M, Jokela M, Keltikangas-Jarvinen L, et al. Association of age at menarche with cardiovascular risk factors, vascular structure, and function in adulthood: the Cardiovascular Risk in Young Finns study. Am J Clin Nutr 2008;87: 1876–1882. [4] Remsberg KE, Demerath EW, Schubert CM, Chumlea WC, Sun SS, Siervogel RM. Early menarche and the development of cardiovascular disease risk factors in adolescent girls: the Fels Longitudinal Study. J Clin Endocrinol Metab 2005;90:2718–2724. [5] Elks CE, Ong KK, Scott RA, van der Schouw YT, Brand JS, Wark PA, et al. Age at menarche and type 2 diabetes risk: the EPIC-InterAct study. Diabetes Care 2013;36:3526–3534.
[6] Heys M, Schooling CM, Jiang C, Cowling BJ, Lao X, Zhang W, et al. Age of menarche and the metabolic syndrome in China. Epidemiology 2007;18: 740–746. [7] Pierce MB, Leon DA. Age at menarche and adult BMI in the Aberdeen children of the 1950s cohort study. Am J Clin Nutr 2005;82:733–739. [8] Okamoto K, Horisawa R, Kawamura T, Asai A, Ogino M, Takagi T, et al. Menstrual and reproductive factors for subarachnoid hemorrhage risk in women: a case-control study in nagoya, Japan. Stroke 2001;32:2841–2844. [9] Adams LA, Sanderson S, Lindor KD, Angulo P. The histological course of nonalcoholic fatty liver disease: a longitudinal study of 103 patients with sequential liver biopsies. J Hepatol 2005;42:132–138. [10] Caldwell SH, Crespo DM. The spectrum expanded: cryptogenic cirrhosis and the natural history of non-alcoholic fatty liver disease. J Hepatol 2004;40: 578–584. [11] Ascha MS, Hanouneh IA, Lopez R, Tamimi TA, Feldstein AF, Zein NN. The incidence and risk factors of hepatocellular carcinoma in patients with nonalcoholic steatohepatitis. Hepatology 2010;51:1972–1978. [12] Adams LA, Waters OR, Knuiman MW, Elliott RR, Olynyk JK. NAFLD as a risk factor for the development of diabetes and the metabolic syndrome: an eleven-year follow-up study. Am J Gastroenterol 2009;104:861–867. [13] Targher G, Day CP, Bonora E. Risk of cardiovascular disease in patients with nonalcoholic fatty liver disease. N Engl J Med 2010;363:1341–1350. [14] Targher G, Bertolini L, Padovani R, Rodella S, Zoppini G, Pichiri I, et al. Prevalence of non-alcoholic fatty liver disease and its association with cardiovascular disease in patients with type 1 diabetes. J Hepatol 2010;53: 713–718. [15] Bhatia LS, Curzen NP, Calder PC, Byrne CD. Non-alcoholic fatty liver disease: a new and important cardiovascular risk factor? Eur Heart J 2012;33: 1190–1200. [16] Zelber-Sagi S, Lotan R, Shlomai A, Webb M, Harrari G, Buch A, et al. Predictors for incidence and remission of NAFLD in the general population during a seven-year prospective follow-up. J Hepatol 2012;56:1145–1151. [17] Kumashiro N, Erion DM, Zhang D, Kahn M, Beddow SA, Chu X, et al. Cellular mechanism of insulin resistance in nonalcoholic fatty liver disease. Proc Natl Acad Sci U S A 2011;108:16381–16385. [18] Demerath EW, Towne B, Chumlea WC, Sun SS, Czerwinski SA, Remsberg KE, et al. Recent decline in age at menarche: the Fels Longitudinal Study. Am J Hum Biol 2004;16:453–457. [19] Lazo M, Clark JM. The epidemiology of nonalcoholic fatty liver disease: a global perspective. Semin Liver Dis 2008;28:339–350. [20] Cho GJ, Park HT, Shin JH, Hur JY, Kim YT, Kim SH, et al. Age at menarche in a Korean population: secular trends and influencing factors. Eur J Pediatr 2010;169:89–94. [21] Mueller NT. Early puberty: adulthood metabolic consequences and childhood nutritional determinants [doctorate thesis]. Minneapolis: University of Minnesota; 2013. [22] Mueller NT, Pereira MA, Demerath EW, Dreyfus JG, MacLehose RF, Carr JJ, et al. Age at menarche is inversely associated with liver steatosis and abdominal fat depots: CARDIA Study. Circulation 2014;129:AMP68, [abstract]. [23] Kim CW, Yun KE, Jung HS, Chang Y, Choi ES, Kwon MJ, et al. Sleep duration and quality in relation to non-alcoholic fatty liver disease in middle-aged workers and their spouses. J Hepatol 2013;59:351–357. [24] Chang Y, Kim BK, Yun KE, Cho J, Zhang Y, Rampal S, et al. Metabolically-healthy obesity and coronary artery calcification. J Am Coll Cardiol 2014;63:2679–2686. [25] Chalasani N, Younossi Z, Lavine JE, Diehl AM, Brunt EM, Cusi K, et al. The diagnosis and management of non-alcoholic fatty liver disease: practice Guideline by the American Association for the Study of Liver Diseases, American College of Gastroenterology, and the American Gastroenterological Association. Hepatology 2012;55:2005–2023. [26] Gaudineau A, Ehlinger V, Vayssiere C, Jouret B, Arnaud C, Godeau E. Factors associated with early menarche: results from the French Health Behaviour in School-aged Children (HBSC) study. BMC Public Health 2010;10:175. [27] Craig CL, Marshall AL, Sjostrom M, Bauman AE, Booth ML, Ainsworth BE, et al. International physical activity questionnaire: 12-country reliability and validity. Med Sci Sports Exerc 2003;35:1381–1395. [28] Oh JY, Yang YJ, Kim BS, Kang JH. Validity and reliability of Korean version of International Physical Activity Questionnaire (IPAQ) short form. Korean J Fam Med 2007;28:532–541. [29] Malavolti M, Mussi C, Poli M, Fantuzzi AL, Salvioli G, Battistini N, et al. Cross-calibration of eight-polar bioelectrical impedance analysis versus dual-energy X-ray absorptiometry for the assessment of total and appendicular body composition in healthy subjects aged 21–82 years. Ann Hum Biol 2003;30:380–391.
Journal of Hepatology 2015 vol. 62 j 1164–1170
1169
Research Article [30] Wen CP, David Cheng TY, Tsai SP, Chan HT, Hsu HL, Hsu CC, et al. Are Asians at greater mortality risks for being overweight than Caucasians? Redefining obesity for Asians. Public Health Nutr 2009;12:497–506. [31] Mathiesen UL, Franzen LE, Aselius H, Resjo M, Jacobsson L, Foberg U, et al. Increased liver echogenicity at ultrasound examination reflects degree of steatosis but not of fibrosis in asymptomatic patients with mild/moderate abnormalities of liver transaminases. Dig Liver Dis 2002;34:516–522. [32] Harlow SD, Gass M, Hall JE, Lobo R, Maki P, Rebar RW, et al. Executive summary of the Stages of Reproductive Aging Workshop + 10: addressing the unfinished agenda of staging reproductive aging. J Clin Endocrinol Metab 2012;97:1159–1168. [33] Bedogni G, Bellentani S, Miglioli L, Masutti F, Passalacqua M, Castiglione A, et al. The Fatty Liver Index: a simple and accurate predictor of hepatic steatosis in the general population. BMC Gastroenterol 2006;6:33. [34] Angulo P, Hui JM, Marchesini G, Bugianesi E, George J, Farrell GC, et al. The NAFLD fibrosis score: a noninvasive system that identifies liver fibrosis in patients with NAFLD. Hepatology 2007;45:846–854. [35] Wai CT, Greenson JK, Fontana RJ, Kalbfleisch JD, Marrero JA, Conjeevaram HS, et al. A simple noninvasive index can predict both significant fibrosis and cirrhosis in patients with chronic hepatitis C. Hepatology 2003;38:518–526. [36] Giannini E, Risso D, Botta F, Chiarbonello B, Fasoli A, Malfatti F, et al. Validity and clinical utility of the aspartate aminotransferase-alanine aminotransferase ratio in assessing disease severity and prognosis in patients with hepatitis C virus-related chronic liver disease. Arch Intern Med 2003;163: 218–224. [37] He C, Zhang C, Hunter DJ, Hankinson SE, Buck Louis GM, Hediger ML, et al. Age at menarche and risk of type 2 diabetes: results from 2 large prospective cohort studies. Am J Epidemiol 2010;171:334–344. [38] Dreyfus JG, Lutsey PL, Huxley R, Pankow JS, Selvin E, Fernandez-Rhodes L, et al. Age at menarche and risk of type 2 diabetes among African-American and white women in the Atherosclerosis Risk in Communities (ARIC) study. Diabetologia 2012;55:2371–2380. [39] Velie EM, Nechuta S, Osuch JR. Lifetime reproductive and anthropometric risk factors for breast cancer in postmenopausal women. Breast Dis 2005;24:17–35. [40] Marshall LM, Spiegelman D, Goldman MB, Manson JE, Colditz GA, Barbieri RL, et al. A prospective study of reproductive factors and oral contraceptive use in relation to the risk of uterine leiomyomata. Fertil Steril 1998;70: 432–439.
1170
[41] McPherson CP, Sellers TA, Potter JD, Bostick RM, Folsom AR. Reproductive factors and risk of endometrial cancer. The Iowa Women’s Health Study. Am J Epidemiol 1996;143:1195–1202. [42] Prentice P, Viner RM. Pubertal timing and adult obesity and cardiometabolic risk in women and men: a systematic review and meta-analysis. Int J Obes 2013;37:1036–1043. [43] Feng Y, Hong X, Wilker E, Li Z, Zhang W, Jin D, et al. Effects of age at menarche, reproductive years, and menopause on metabolic risk factors for cardiovascular diseases. Atherosclerosis 2008;196:590–597. [44] Chang Y, Ryu S, Sung E, Woo HY, Cho SI, Yoo SH, et al. Weight gain within the normal weight range predicts ultrasonographically detected fatty liver in healthy Korean men. Gut 2009;58:1419–1425. [45] Marchesini G, Marzocchi R, Agostini F, Bugianesi E. Nonalcoholic fatty liver disease and the metabolic syndrome. Curr Opin Lipidol 2005;16:421–427. [46] Fan JG, Peng YD. Metabolic syndrome and non-alcoholic fatty liver disease: Asian definitions and Asian studies. Hepatobiliary Pancreat Dis Int 2007; 6:572–578. [47] Sniderman AD, Furberg CD. Age as a modifiable risk factor for cardiovascular disease. Lancet 2008;371:1547–1549. [48] Abdullah A, Wolfe R, Stoelwinder JU, de Courten M, Stevenson C, Walls HL, et al. The number of years lived with obesity and the risk of all-cause and cause-specific mortality. Int J Epidemiol 2011;40:985–996. [49] Abdullah A, Stoelwinder J, Shortreed S, Wolfe R, Stevenson C, Walls H, et al. The duration of obesity and the risk of type 2 diabetes. Public Health Nutr 2011;14:119–126. [50] Joy D, Thava VR, Scott BB. Diagnosis of fatty liver disease: is biopsy necessary? Eur J Gastroenterol Hepatol 2003;15:539–543. [51] Clark JM, Diehl AM. Defining nonalcoholic fatty liver disease: implications for epidemiologic studies. Gastroenterology 2003;124:248–250. [52] Bellentani S, Tiribelli C. The spectrum of liver disease in the general population: lesson from the Dionysos study. J Hepatol 2001;35:531–537. [53] Must A, Phillips SM, Naumova EN, Blum M, Harris S, Dawson-Hughes B, et al. Recall of early menstrual history and menarcheal body size: after 30 years, how well do women remember? Am J Epidemiol 2002;155:672–679. [54] Casey VA, Dwyer JT, Coleman KA, Krall EA, Gardner J, Valadian I. Accuracy of recall by middle-aged participants in a longitudinal study of their body size and indices of maturation earlier in life. Ann Hum Biol 1991;18:155–166. [55] Rhoads GG, Kagan A. The relation of coronary disease, stroke, and mortality to weight in youth and in middle age. Lancet 1983;1:492–495.
Journal of Hepatology 2015 vol. 62 j 1164–1170