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Prevalence of and risk factors for fatty liver in a general population of Shanghai, China
Journal of Hepatology 43 (2005) 508–514 www.elsevier.com/locate/jhep
Prevalence of and risk factors for fatty liver in a general population of Shanghai, China Jian-Gao Fan1,*, Jun Zhu1, Xing-Jian Li2, Lan Chen1, Lui Li2, Fei Dai3, Feng Li1, Shi-Yao Chen4 1 Center for Fatty Liver, Shanghai First People’s Hospital, JiaoTong University, Shanghai, China Department of Chronic Disease, Shanghai Center for Disease Control and Prevention, Shanghai, China 3 School of Public Health, Shanghai Second Medical University, Shanghai, China 4 Clinical Epidemiology Resource and Training Center, Zhongshan Hospital, Fudan University, Shanghai, China 2
Background/Aims: To determine the prevalence and risk factors of fatty liver (FL) among Shanghai adults. Methods: A cross-sectional ultrasonographic survey with randomized multistage stratified cluster sampling was used. Results: The study included 3175 subjects (1218 men) with a mean age of 52 years. FL was found in 661 (20.82%) subjects. After adjustment by age and sex, FL prevalence was found to be 17.29%, and the prevalences of alcoholic, suspected alcoholic and nonalcoholic FL were determined to be 0.79, 1.15 and 15.35%, respectively. Generally, age, body mass index (BMI), waist circumference, blood pressure, and the prevalences of obesity, diabetes, hypertension and dyslipidemia were all significantly higher in FL patients than in controls; In contrast, the levels of high-density-lipoprotein cholesterol (HDL-C), education and physical activity were markedly lower. Multiple regression analyses showed that only nine factors (male, educational level, waist circumference, BMI, HDL-C, triglyceride, fasting plasma glucose, diabetes and hypertension) were closely related to FL. In excessive drinkers, obesity increased the risk for FL by 4.8-fold, but excessive drinking was associated with only a 1.5-fold increased risk in obese subjects. Conclusions: FL in Shanghai is highly prevalent and mainly related to multiple metabolic disorders. q 2005 European Association for the Study of the Liver. Published by Elsevier B.V. All rights reserved. Keywords: Fatty liver (FL); Obesity; Alcohol; Epidemiology; Ultrasound 1. Introduction Fatty liver (FL) is a disease with genetic, environmental, metabolic and stress-related components; the prevalence of FL has consistently increased with changes of lifestyle. FL can be either alcoholic or nonalcoholic, and both conditions are associated with a potential risk for progression to cirrhosis, hepatocarcinoma and liver failure [1–4]. Therefore, epidemiological studies of FL have drawn wide attention [5–7]. However, there is a paucity of populationbased survey from China [8]. Therefore, we conducted
Received 2 September 2004; received in revised form 28 January 2005; accepted 2 February 2005; available online 12 May 2005 * Corresponding author. Address: 85 Wujin Road, Shanghai, 200080, China. Tel.: C86 21 63240090; fax: C86 21 63240825. E-mail address: [email protected] (J.-G. Fan).
a cross-sectional general population study to determine the prevalence of FL and its risk factors among Shanghaineses.
2. Materials and methods 2.1. Survey design and study sample We assigned a number to each of the 16 urban districts of Shanghai, and randomly selected two districts (Yangpu District and Pudong New District). Of 11 residential districts within Yangpu and Pudong, we randomly selected the Pingliang and Shanggang residential districts, which contained 30 and 26 neighborhood communities, respectively. From these, we selected eight neighborhood communities in total. Resident groups were randomly selected from each sample neighborhood community. From October 2002 to April 2003, investigations were conducted in every adult over the age of 16 in the selected resident groups at home, with 500 participants initially enrolled in each group. This program was approved by the Research Ethics Committee of the Shanghai Health Bureau, and all participants provided written informed consent. Physical examinations, laboratory assessments and ultrasound liver scans were carried out on each
0168-8278/$30.00 q 2005 European Association for the Study of the Liver. Published by Elsevier B.V. All rights reserved. doi:10.1016/j.jhep.2005.02.042
J.-G. Fan et al. / Journal of Hepatology 43 (2005) 508–514 study subject at a mobile examination center following an overnight fast of at least 12 h.
2.2. Data collection 2.2.1. Interview Selected individuals were interviewed in their homes using a questionnaire that gathered information on demographic characteristics, medical history and health-related habits. Information on age and education was categorized according to the design suggested by the United States National Center for Health Statistics [9]. A poverty–income ratio was calculated for each person based on self-reported family income in relation to the poverty threshold, family size, and calendar year. Individuals were classified as being below the poverty level (poor) if their poverty to income ratio was !1.0 [10]. Participants were classified as non-smoker, exsmoker, and current smoker at three levels (1–19, 20–39, and O40 cigarettes/day). Use of alcohol was ascertained from a series of questions including whether the respondent had consumed 12 drinks (one drink Z 10 g alcohol) in his/her lifetime. If so, respondents were asked to quantify the number of days they had consumed alcohol over the past 5 years and the number of drinks per day on drinking days. From these data, we calculated an average daily intake of alcohol [11]. Exercise was ascertained by asking participants how often in the previous month they had engaged in any number of different activities, including walking, jogging, biking and swimming. A total physical score was calculated for each person based on the frequency and type (intensity) of his/her physical activity. The participants were grouped into two broad categories based on their total score: inactive (including occasional exercise) and active (including light, moderately vigorous, and vigorous exercise) [12].
2.2.2. Physical examination Body measurements including weight, standing height, waist and hip circumference were measured in a standardized fashion by a trained examiner. Body mass index (BMI, kg/m2) and the waist-to-hip ratio (WHR) were calculated from these values. Three blood pressure readings were obtained at 1-min intervals; the second and third systolic and diastolic pressure readings were averaged and used in the analyses.
2.2.3. Laboratory assessments Venous blood samples were collected at 0 and 120 min following 75-g oral glucose challenge for non-diabetics or 100-g steamed bread for diabetics. Samples were immediately centrifuged, and specimens were frozen and shipped to a central laboratory at the Shanghai Center for Disease Control and Prevention, where they were sequentially stored at K20 and K708C. Serum glucose was determined using a modified hexokinase method. Fasting serum total cholesterol and triglyceride concentrations were measured enzymatically with color absorptiometry based on a peroxidase-catalyzed reaction. High-density lipoprotein cholesterol (HDL-C) was measured after precipitation of other lipoproteins with a polyanion/divalent cation mixture. Low-density lipoprotein cholesterol (LDL-C) was calculated according to the formula: LDLZ (total cholesterol)K(HDL)K(triglycerides/5). LDL was not calculated if the triglyceride level was O4.52 mM/L. All serum biochemistries were performed with a Bayer model 1650 automated bio-analyzer (Bayer Diagnostic, Basingstoke, UK).
2.2.4. Ultrasonographic examination Hepatic ultrasonographic examination was performed by an experienced ultrasonographist using a Simens Sonoline-SI450 unit with a 3.5 MHz probe.
2.3. Quality control All researchers were given systematic training before investigation. For further quality control, 5% of the questionnaires, blood samples and ultrasonographic results were sampled for reexamination; kappa analysis of these samples showed good consistency in the results of the diagnostic tests (data not shown).
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2.4. Definitions Obesity and abdominal obesity were categorized according to the new BMI criteria for Asians put forth by the WHO regional office for the Western Pacific region [13]. Hypertension was defined as published in the Seventh Report of the Joint National Committee on Prevention, Detection, Evaluation, and Treatment of High Blood Pressure (JNC7) [14]. Dyslipidemia (including hypertriglyceridemia and low HDL-C) was diagnosed according to the Third Report of the National Cholesterol Education Program Expert Panel on Detection, Evaluation, and Treatment of High Blood Cholesterol in Adults (NCEP-ATPIII) [15]. The diagnoses of impaired fasting glucose, impaired glucose tolerance and diabetes mellitus (DM) were based on the WHO 1999 criteria [16]. We counted participants who reported current use of antihypertension or antidiabetic medications as having hypertension or diabetes, respectively. Diagnosis of FL was based on the presence of an ultrasonographic pattern consistent with ‘bright liver’ (brightness and posterior attenuation) with stronger echoes in the hepatic parenchyma than in the renal parenchyma, vessel blurring, and narrowing of the lumen of the hepatic veins in the absence of findings suggestive of other chronic liver disease [17,18]. The determination of the etiology of FL was based on the Chinese Liver Disease Association 2002 criteria [19,20], in which FL was divided into three subtypes: AFL (alcohol consumption more than 210 g/wk for more than 5 years), NAFL (non-drinkers or alcohol consumption less than 40 g/wk for more than 1 year), and suspected AFL (alcohol consumption and duration intermediate between the two other subtypes).
2.5. Statistical analysis All data were analyzed using SPSS 11.0 software (SPSS, Inc.). Unpaired t test, c2 contingency test, and Fisher’s exact test were used where appropriate. Nonparametric methods were also used for non-normally distributed values. Logistic regression analyses (univariate and multivariate) were used to calculate the risk for FL and various parameters. Some analyses were adjusted for age and sex. Kappa analysis was performed for blood biochemical data and as a quality control for ultrasonography. All provided P-values represent the results of two-sided tests. P-values !0.05 were considered statistically significant.
3. Results 3.1. Sampling status and general data We used a stratified multistage probability cluster sampling design to obtain a representative sample of the noninstitutionalized population in Shanghai. The investigated neighborhoods contained 4205 residents aged 16 years or more; persons reporting clinical diagnosis of chronic viral hepatitis, cirrhosis or other severe diseases, or pregnant, or long-term using of estrogens, tamoxifen, or corticosteroids were excluded (nZ237). Physical examination and laboratory data were obtained for 3834 individuals, of these, only 3175 individuals (82.81%) with complete data and ultrasonographic examinations were accepted; this study population corresponded to approximately 2.26/10,000 of the Shanghaineses, according to the Shanghai Census Count (2000). The study population included 1218 males and 1957 females, with a mean age of 52.4G15.1 years (16–88 years), and no significant difference was noted between males and females. Anthropometric, clinical, laboratory data, and prevalence rates of metabolic disorders of the 3175 participants were shown in Tables 1 and 2. In comparison
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Table 1 Anthropometric, clinical, and laboratory data of 3175 participants Characteristics
All cases (nZ3175)
Men (nZ1218)
Women (nZ1957)
P-value
Age (years) BMI (kg/m2) Waist circumference (cm) WHR Triglyceride (mmol/L) Total cholesterol (mmol/L) HDL-C (mmol/L) LDL-C (mmol/L) Systolic pressure (mmHg) Diastolic pressure (mmHg) Fasting glucose (mmol/L) 120-m glucose (mmol/L)
52.4G15.1 24.52G5.50 80.28G10.09 0.836G0.069 1.34G0.99 5.01G0.97 1.53G0.41 2.91G0.84 129.5G19.5 82.0G12.3 5.76G1.54 6.29G3.31
52.3G16.4 24.48G3.52 83.79G9.70 0.867G0.064 1.46G1.10 4.84G0.95 1.37G0.37 2.84G0.83 131.7G18.8 84.0G12.0 5.78G1.56 6.27G3.51
52.4G14.3 24.60G6.44 78.06G9.69 0.817G0.061 1.26G0.91 5.11G0.97 1.62G0.40 2.96G0.84 128.1G19.8 80.8G12.2 5.74G1.53 6.31G3.19
0.865 0.483 !0.001 !0.001 !0.001 !0.001 !0.001 !0.001 !0.001 !0.001 0.497 0.754
Table 2 Prevalence of metabolic syndrome features among 3175 participants Characteristics
All cases (nZ3175)
Men (nZ1218)
Women (nZ1957)
P-value
Obesity (%) Abdominal obesity (%) Dyslipidemia (%) Hypertension (%) Impaired fasting glucose (%) Impaired glucose tolerance (%) Diabetes mellitus (%)
1331 (41.9) 1136 (36.0) 1466 (46.2) 1511 (47.59) 261 (8.22) 128 (4.03) 512 (16.1)
545 (44.7) 333 (27.3) 526 (43.2) 647 (53.12) 109 (8.95) 53 (4.35) 220 (18.1)
786 (40.1) 803 (41.0) 940 (48.0) 864 (44.15) 152 (7.77) 75 (3.83) 292 (14.9)
0.011 !0.001 0.007 !0.001 0.238 0.470 0.019
*P-value for comparison between sexes.
with the sex and age composition obtained in the Shanghai Census Count (2000), the study population contained higher percentages of elderly and women (both P!0.001). Therefore, some of the results were adjusted by age and sex in order to better represent the real situation in Shanghai. 3.2. Prevalence of FL and the influence of age and sex Of the 3175 enrolled subjects, 661 (20.82%) were diagnosed as having FL. There was no significant sexual difference in the prevalence of FL (21.18 vs. 20.59%, PZ0.6908). The total prevalence of FL increased with age (in trend analysis, PZ0.00000), and the peak prevalence (28.44%) was reached between the ages of
60–69 years (Table 3). After stratification by sex, the prevalence of FL increased with age in both males and females (in trend analysis, PZ0.00011 and 0.00000, respectively). The peak prevalence in males was reached between the ages of 40–49 years, whereas in females between the ages of 60–69 years. The prevalence of FL was significantly higher in males than in females before age 50 years (c2-valueZ13.934, PZ0.0002), but was significantly higher in females than in males after age 50 years (c2Z4.146, PZ0.0417). After adjustment by age and sex, the overall prevalence of FL among Shanghai adults was found to be 17.29%, with the prevalence of FL being significantly higher in males than in females (19.30 vs. 15.08%, PZ0.0019).
Table 3 Prevalence of fatty liver in the study population Age (years)
Fatty liver in total (%)
Fatty liver in men (%)
Fatty liver in women (%)
P-value
16–19 20–29 30–39 40–49 50–59 60–69 R70
2/185 8/123 17/130 142/750 196/920 186/655 110/412
2/98 6/49 9/49 67/242 68/340 61/249 45/191
0/87 2/74 8/81 75/508 128/580 125/406 65/221
0.1815 0.0364 0.1657 !0.0001 0.4597 0.0833 0.1811
(1.08) (6.50) (13.08) (18.93) (21.13) (28.40) (26.70)
*P-value for comparison between sexes.
(2.04) (12.25) (18.37) (27.69) (20.00) (24.50) (23.56)
(0.00) (2.70) (9.88) (14.76) (22.07) (30.79) (29.41)
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Table 4 Baseline characteristics of 3175 participants according to the presence of the fatty liver Characteristics
With fatty liver (nZ661)
Without fatty liver (nZ2514)
T-value
P-value
Age (years) BMI (kg/m2) WHR Waist circumference (cm) Fasting glucose (mmol/L) 120-m glucose (mmol/L) Triglyceride (mmol/L) Total cholesterol (mmol/L) HDL-C (mmol/L) LDL-C (mmol/L) Systolic pressure (mmHg) Diastolic pressure (mmHg)
57.6G11.0 27.45G3.38 0.876G0.066 88.38G9.30 6.51G2.09 7.84G2.89 1.90G0.48 5.271G0.949 1.35G0.35 3.14G0.83 138.0G19.1 87.1G11.3
51.0G15.8 23.76G5.69 0.826G0.064 78.15G9.17 5.56G1.29 5.89G1.62 1.19G0.34 4.941G0.964 1.57G0.41 2.85G0.83 127.2G19.0 80.7G12.1
12.234 15.946 17.430 25.423 11.247 13.865 13.518 7.789 14.062 7.875 13.019 12.329
0.000 0.000 0.000 0.000 0.000 0.000 0.000 0.000 0.000 0.000 0.000 0.000
3.3. Analysis of risk factors for FL The 3175 subjects were divided into FL group (661) and non-FL group (2514). Univariate analysis showed that age, BMI, WHR, waist circumference, plasma glucose, triglyceride, total cholesterol, LDL-C and blood pressure were all significantly higher in the FL group than in the non-FL group, whereas HDL-C was otherwise (Table 4). The prevalences of obesity, abdominal obesity, abnormal glucose metabolism, dyslipidemia and hypertension were all significantly higher in the FL group than in the non-FL group (P!0.001) (Table 5). Of the 3175 enrolled subjects, 242 had habitual alcohol consumption (7.62%), with a much higher alcohol consumption rate in males versus females (17.73 vs. 1.33%, P!0.0001). Habitual alcohol consumption was seen in 61 (9.23%) subjects with FL and 181 (7.2%) subjects without FL (PO0.05). Low educational level and physical inactivity
was significantly higher in the FL group than in the non-FL (both P!0.05), but there were no differences in total family economic income or current cigarette smoking rates between the two groups (Table 6). Stepwise regression analysis was performed on the 28 features using the dichotomous variable logistic regression model. Our results showed that nine features were closely related to FL, including male gender, HDLC, triglyceride, educational level, DM, fasting glucose level, hypertension, waist circumference and BMI (Table 7). 3.4. Etiological constituent ratios of FL and their mutual influences Among the 661 FL patients, 611 (92.43%) were NAFL, 23 (3.48%) were AFL and 27 (4.08%) were suspected AFL. After age-and sex-adjustment, 88.78% were NAFL, 4.53%
Table 5 Prevalence of metabolic syndrome features in groups with and without fatty liver Characteristics
With fatty liver (nZ661)
Without fatty liver (nZ2514)
c2-value
P-value
Obesity Abdominal obesity Impaired fasting glucose Impaired glucose tolerance Diabetes mellitus Dyslipidemia Hypertension
522 (78.97) 474 (71.71) 81 (12.25) 25 (3.78) 215 (32.53) 467 (57.19) 464 (70.20)
809 (32.18) 662 (26.33) 190 (7.56) 25 (0.99) 297 (11.81) 999 (39.74) 1071 (42.60)
562.887 468.867 14.783 26.233 165.960 48.751 159.547
!0.0001 !0.0001 !0.001 !0.0001 !0.0001 !0.0001 !0.0001
Table 6 Other characteristics (%) in groups with and without fatty liver Characteristics
With fatty liver (nZ661)
Without fatty liver (nZ2514)
c2-value
P-value
Less than high school education Poverty-to-income ratio!1 Physical inactivity Current cigarette smoking Current habitual drinking
306 (46.29%) 49 (7.41%) 471 (71.26%) 87 (13.16%) 61 (9.23%)
825 (32.82%) 245 (9.75%) 1472 (58.55%) 276 (10.98%) 181 (7.20%)
41.441 3.388 35.558 2.463 3.058
!0.0001 0.0657 !0.0001 0.1165 0.0803
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Table 7 Results of logistic multivariant regression analysis of fatty liver and the tested variables Variable
Coefficient of regression (b)
Standard error (SE)
Wald c2
P
OR
95%CI
Male sex HDL cholesterol Triglyceride Educational level Diabetes mellitus Fasting glucose Hypertension Waist circumference BMI
0.994 K0.768 0.330 0.187 0.165 0.120 0.105 0.103 0.046
0.131 0.172 0.054 0.051 0.056 0.039 0.030 0.009 0.022
57.221 20.047 36.991 13.308 8.682 9.564 12.026 121.920 4.651
0.000 0.000 0.000 0.000 0.003 0.002 0.001 0.000 0.031
2.702 0.464 1.391 1.205 1.179 1.127 1.111 1.108 1.048
2.088–3.495 0.332–0.649 1.251–1.547 1.090–1.332 1.057–1.316 1.045–1.216 1.047–1.179 1.088–1.129 1.004–1.093
AFL, and 6.69% suspected AFL, the prevalence rates of nonalcoholic, alcoholic and suspected alcoholic FL in Shanghai adults were thus 15.35, 0.79 and 1.15%, respectively. Based on BMI and daily mean alcohol consumption, among the 3175 enrolled subjects, 1049 subjects were in the control group (BMI!23 kg/m2, alcohol consumption! 10 g/d and accumulative consumption!100 kg), 25 were in the excessive drinking group (BMI!23 kg/m2 and alcohol consumptionR30 g/d and/or accumulative consumptionR100 kg), 1252 were in the obese group (BMIR25 kg/m 2, alcohol consumption!10 g/d and accumulative consumption!100 kg), and 35 in the obese excessive drinking group (BMIR25 kg/m2 and alcohol consumptionR30 g/d and/or accumulative consumptionR100 kg). The prevalence rates of FL in the control, excessive drinking, obese and obese excessive drinking groups were 3.34, 8.00, 38.66 and 57.14%, respectively. Compared to the control group, the odds-ratio (95%CI) for FL for the other groups was 3.6 (1.1–11.7), 11.6 (8.2–16.5) and 17.1 (9.1–32.4), respectively. In excessive drinkers, obesity increased the risk for FL by 4.8-fold (1.4–16.6), but excessive drinking was associated with only a 1.5-fold (0.9–2.6) increased risk in obese subjects, whereas the risk of FL in obese subjects without excessive drinking was 3.2-fold (1.03– 10.1) higher than that in excessive drinkers without obesity.
4. Discussion FL is a heterogeneous disorder. In Western Europe, Japan, Australia, and the USA, population-based ultrasound surveys have indicated that almost one quarter of the adults has FL [1,5,6,8,17,21]. According to a sampling survey conducted among 257 northern Italian adults by Bellentani et al. [22], FL was more strongly associated with obesity than with heavy drinking. Several recent studies have shown that NAFL is the main cause of chronic liver disease in these parts of the world [1,5,6,8,17]. In China, epidemiological ultrasound surveys on FL were first published in the mid 1990s [8], but these studies were relatively limited in their specific populations, and the obtained FL prevalence rates varied widely due to differences in careers, age, gender
and regions studied [8,23,24]. To date, little is known about the population-based prevalence of FL in China. Our investigations demonstrated that approximately 20.82% of Shanghai adults (17.29% after age and sex adjustment) had FL, and most of these were cases of NAFL, consistent with the low alcohol consumption rate (7.62%) in the investigated subjects. Although studies published before 1990 emphasized that NAFL occurred mostly in women, whereas more recent studies have shown that NAFL and steatosis on CT occurs with equal frequency in both sexes [1,6]. In this study, the age-adjusted prevalence of FL was significantly higher in men than women, and logistic regression analysis showed that male gender was closely related to FL. Thus, our results suggest that female gender is not a risk factor for steatosis in Shanghai adults. FL has been reported in all age groups, including children, with a highest prevalence in those between 40 and 49 years of age [1]. In this study, the prevalence of FL increased with age in both sexes, with prevalence peaking in women 60–69 years of age, and in men 40–49 years of age. Interestingly, the prevalence was higher in males than females under the age of 50, but was lower in males than females among people older than 50 years. This phenomenon has been noted in our previous study [23], possibly related to differences in estrogen levels between pre- and post-menopausal women. It is supposed that the prevalence of AFL in China is lower than in many Western countries [8]. In this study, the age- and sex-adjusted prevalence of AFL was found to be only 0.79%, which was similar to the prevalence (0.94%) of AFL determined by an epidemiological survey of 18,237 residents in Zhejiang Province, China [25]. However, the etiological constituent ratio of FL should be further studied in North China, where there are more habitual and heavy drinkers than South China [26]. Compared with the controls, the risk for FL was 3.6-fold higher in heavy drinkers, 11.6fold higher in obese persons, and 17.1-fold higher in obese heavy drinkers. Indeed, in heavy drinkers, obesity increased the risk for FL by 4.8-fold, although heavy drinking did not significantly increase the risk for FL in obese persons. These findings are consistent with those of Bellentani et al. [22]. Because Asians generally have a lower BMI, and FL can occur in Asian subjects at levels of adiposity much lower than traditionally defined Western standards, regional
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guidelines for obesity were used in this study [13,27]. Our data demonstrated that FL was mainly associated with obesity, hyperglycemia, dyslipidemia and hypertension. These are the main features of the recently characterized metabolic syndrome, and people with the metabolic syndrome are at increased risk for developing DM and cardiovascular disease [1–4,7,28]. FL may be considered an additional feature of metabolic syndrome, and subjects with abdominal obesity are more prone to develop diabetes, hypertension and FL [1–4,7,28]. With epidemics of obesity and DM in Shanghai [8,23,28], FL has become an important emerging public health issue. Our univariate and multivariate regression analyses showed that FL was closely correlated with educational level. This could possibly be attributed to a lack of knowledge regarding prevention of multiple metabolic disorders, such as obesity and diabetes, in the population with lower educational levels. Univariate analysis showed that physical activity was a protective factor for FL, but this was not confirmed by the results of multivariate analysis. Moreover, we did not observe any significant relationship between FL and smoking or total economic income. Although there are inherent difficulties in quantitating and grading these ordinal data, a stringent effort was made to maintain the integrity of data collection and analysis throughout this work. FL has been associated with the use of various drugs or occupational exposure to specific chemicals, the prevalence of such exposures and their impact on the epidemiology of FL are unknown. In this study, we did not observe any significant correlation between drug use and FL. Ultrasonography is the modern diagnostic test of choice for FL epidemiological surveys because it is noninvasive, safe, widely available, portable, sensitive (up to 89%) and specific (up to 93%) in detecting steatosis [1,17,18].Our diagnoses of FL were based on ultrasonographic examinations, in which false-negative and false-positive errors are inevitable in comparison to liver biopsy, which is the gold standard for diagnosis of FL [1,28]. Therefore, strict quality controls were utilized in this study; the consistency tests showed that the ultrasonography used in this epidemiological field investigation produced good reliability. Despite the meticulous design and randomized sampling methods, some biases were still present, specifically via the inclusion of a larger proportion of the elderly and females in the study subjects, and complete data collection from only 82.81% of participants. Thus, the representative nature and scientific validity of this survey were likely influenced to some extent. However, this study offers a unique opportunity to study the evolution of previously described ‘first’ world diseases. Future studies should continue to focus both on the similar ties and highlight differences in the regional presentation of FL, and public health initiatives are imperative to halt or reverse FL epidemic.
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Acknowledgements We acknowledge Tian-shu Liu, M.D., for her assistance with statistical analysis, and Prof. Yong-de Peng and Xie-ning Wu for their assistances with critical revision of the manuscript.
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[18] Joseph AE, Saverymuttu SH, al-Sam S, Cook MG, Maxwell JD. Comparison of liver histology with ultrasonography in assessing diffuse parenchymal liver disease. Clin Radiol 1991;43:26–31. [19] Fatty Liver and Alcoholic Liver Disease Study Group of Chinese Liver Disease Association. Diagnostic criteria of nonalcoholic fatty liver disease. Zhonghua Gan Zang Bing Za Zhi 2003;11:71. [20] Fatty Liver and Alcoholic Liver Disease Study Group, Chinese Liver Disease Association. Diagnostic criteria of alcoholic liver disease. Zhonghua Gan Zang Bing Za Zhi 2003;11:72. [21] Omagari K, Kadokawa Y, Masuda J, Egawa I, Sawa T, Hazama H, et al. Fatty liver in non-alcoholic non-overweight Japanese adults: incidence and clinical characteristics. J Gastroenterol Hepatol 2002; 17:1098–1105. [22] Bellentani S, Saccoccio G, Masutti F, Croce LS, Brandi G, Sasso F, et al. Prevalence of and risk factors for hepatic steatosis in Northern Italy. Ann Intern Med 2000;132:112–117. [23] Shen L, Fan JG, Shao Y, Zeng MD, Wang JR, Luo GH, et al. Prevalence of nonalcoholic fatty liver among administrative officers
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Prevalence of and risk factors for fatty liver in a general population of Shanghai, China Jian-Gao Fan1,*, Jun Zhu1, Xing-Jian Li2, Lan Chen1, Lui Li2, Fei Dai3, Feng Li1, Shi-Yao Chen4 1 Center for Fatty Liver, Shanghai First People’s Hospital, JiaoTong University, Shanghai, China Department of Chronic Disease, Shanghai Center for Disease Control and Prevention, Shanghai, China 3 School of Public Health, Shanghai Second Medical University, Shanghai, China 4 Clinical Epidemiology Resource and Training Center, Zhongshan Hospital, Fudan University, Shanghai, China 2
Background/Aims: To determine the prevalence and risk factors of fatty liver (FL) among Shanghai adults. Methods: A cross-sectional ultrasonographic survey with randomized multistage stratified cluster sampling was used. Results: The study included 3175 subjects (1218 men) with a mean age of 52 years. FL was found in 661 (20.82%) subjects. After adjustment by age and sex, FL prevalence was found to be 17.29%, and the prevalences of alcoholic, suspected alcoholic and nonalcoholic FL were determined to be 0.79, 1.15 and 15.35%, respectively. Generally, age, body mass index (BMI), waist circumference, blood pressure, and the prevalences of obesity, diabetes, hypertension and dyslipidemia were all significantly higher in FL patients than in controls; In contrast, the levels of high-density-lipoprotein cholesterol (HDL-C), education and physical activity were markedly lower. Multiple regression analyses showed that only nine factors (male, educational level, waist circumference, BMI, HDL-C, triglyceride, fasting plasma glucose, diabetes and hypertension) were closely related to FL. In excessive drinkers, obesity increased the risk for FL by 4.8-fold, but excessive drinking was associated with only a 1.5-fold increased risk in obese subjects. Conclusions: FL in Shanghai is highly prevalent and mainly related to multiple metabolic disorders. q 2005 European Association for the Study of the Liver. Published by Elsevier B.V. All rights reserved. Keywords: Fatty liver (FL); Obesity; Alcohol; Epidemiology; Ultrasound 1. Introduction Fatty liver (FL) is a disease with genetic, environmental, metabolic and stress-related components; the prevalence of FL has consistently increased with changes of lifestyle. FL can be either alcoholic or nonalcoholic, and both conditions are associated with a potential risk for progression to cirrhosis, hepatocarcinoma and liver failure [1–4]. Therefore, epidemiological studies of FL have drawn wide attention [5–7]. However, there is a paucity of populationbased survey from China [8]. Therefore, we conducted
Received 2 September 2004; received in revised form 28 January 2005; accepted 2 February 2005; available online 12 May 2005 * Corresponding author. Address: 85 Wujin Road, Shanghai, 200080, China. Tel.: C86 21 63240090; fax: C86 21 63240825. E-mail address: [email protected] (J.-G. Fan).
a cross-sectional general population study to determine the prevalence of FL and its risk factors among Shanghaineses.
2. Materials and methods 2.1. Survey design and study sample We assigned a number to each of the 16 urban districts of Shanghai, and randomly selected two districts (Yangpu District and Pudong New District). Of 11 residential districts within Yangpu and Pudong, we randomly selected the Pingliang and Shanggang residential districts, which contained 30 and 26 neighborhood communities, respectively. From these, we selected eight neighborhood communities in total. Resident groups were randomly selected from each sample neighborhood community. From October 2002 to April 2003, investigations were conducted in every adult over the age of 16 in the selected resident groups at home, with 500 participants initially enrolled in each group. This program was approved by the Research Ethics Committee of the Shanghai Health Bureau, and all participants provided written informed consent. Physical examinations, laboratory assessments and ultrasound liver scans were carried out on each
0168-8278/$30.00 q 2005 European Association for the Study of the Liver. Published by Elsevier B.V. All rights reserved. doi:10.1016/j.jhep.2005.02.042
J.-G. Fan et al. / Journal of Hepatology 43 (2005) 508–514 study subject at a mobile examination center following an overnight fast of at least 12 h.
2.2. Data collection 2.2.1. Interview Selected individuals were interviewed in their homes using a questionnaire that gathered information on demographic characteristics, medical history and health-related habits. Information on age and education was categorized according to the design suggested by the United States National Center for Health Statistics [9]. A poverty–income ratio was calculated for each person based on self-reported family income in relation to the poverty threshold, family size, and calendar year. Individuals were classified as being below the poverty level (poor) if their poverty to income ratio was !1.0 [10]. Participants were classified as non-smoker, exsmoker, and current smoker at three levels (1–19, 20–39, and O40 cigarettes/day). Use of alcohol was ascertained from a series of questions including whether the respondent had consumed 12 drinks (one drink Z 10 g alcohol) in his/her lifetime. If so, respondents were asked to quantify the number of days they had consumed alcohol over the past 5 years and the number of drinks per day on drinking days. From these data, we calculated an average daily intake of alcohol [11]. Exercise was ascertained by asking participants how often in the previous month they had engaged in any number of different activities, including walking, jogging, biking and swimming. A total physical score was calculated for each person based on the frequency and type (intensity) of his/her physical activity. The participants were grouped into two broad categories based on their total score: inactive (including occasional exercise) and active (including light, moderately vigorous, and vigorous exercise) [12].
2.2.2. Physical examination Body measurements including weight, standing height, waist and hip circumference were measured in a standardized fashion by a trained examiner. Body mass index (BMI, kg/m2) and the waist-to-hip ratio (WHR) were calculated from these values. Three blood pressure readings were obtained at 1-min intervals; the second and third systolic and diastolic pressure readings were averaged and used in the analyses.
2.2.3. Laboratory assessments Venous blood samples were collected at 0 and 120 min following 75-g oral glucose challenge for non-diabetics or 100-g steamed bread for diabetics. Samples were immediately centrifuged, and specimens were frozen and shipped to a central laboratory at the Shanghai Center for Disease Control and Prevention, where they were sequentially stored at K20 and K708C. Serum glucose was determined using a modified hexokinase method. Fasting serum total cholesterol and triglyceride concentrations were measured enzymatically with color absorptiometry based on a peroxidase-catalyzed reaction. High-density lipoprotein cholesterol (HDL-C) was measured after precipitation of other lipoproteins with a polyanion/divalent cation mixture. Low-density lipoprotein cholesterol (LDL-C) was calculated according to the formula: LDLZ (total cholesterol)K(HDL)K(triglycerides/5). LDL was not calculated if the triglyceride level was O4.52 mM/L. All serum biochemistries were performed with a Bayer model 1650 automated bio-analyzer (Bayer Diagnostic, Basingstoke, UK).
2.2.4. Ultrasonographic examination Hepatic ultrasonographic examination was performed by an experienced ultrasonographist using a Simens Sonoline-SI450 unit with a 3.5 MHz probe.
2.3. Quality control All researchers were given systematic training before investigation. For further quality control, 5% of the questionnaires, blood samples and ultrasonographic results were sampled for reexamination; kappa analysis of these samples showed good consistency in the results of the diagnostic tests (data not shown).
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2.4. Definitions Obesity and abdominal obesity were categorized according to the new BMI criteria for Asians put forth by the WHO regional office for the Western Pacific region [13]. Hypertension was defined as published in the Seventh Report of the Joint National Committee on Prevention, Detection, Evaluation, and Treatment of High Blood Pressure (JNC7) [14]. Dyslipidemia (including hypertriglyceridemia and low HDL-C) was diagnosed according to the Third Report of the National Cholesterol Education Program Expert Panel on Detection, Evaluation, and Treatment of High Blood Cholesterol in Adults (NCEP-ATPIII) [15]. The diagnoses of impaired fasting glucose, impaired glucose tolerance and diabetes mellitus (DM) were based on the WHO 1999 criteria [16]. We counted participants who reported current use of antihypertension or antidiabetic medications as having hypertension or diabetes, respectively. Diagnosis of FL was based on the presence of an ultrasonographic pattern consistent with ‘bright liver’ (brightness and posterior attenuation) with stronger echoes in the hepatic parenchyma than in the renal parenchyma, vessel blurring, and narrowing of the lumen of the hepatic veins in the absence of findings suggestive of other chronic liver disease [17,18]. The determination of the etiology of FL was based on the Chinese Liver Disease Association 2002 criteria [19,20], in which FL was divided into three subtypes: AFL (alcohol consumption more than 210 g/wk for more than 5 years), NAFL (non-drinkers or alcohol consumption less than 40 g/wk for more than 1 year), and suspected AFL (alcohol consumption and duration intermediate between the two other subtypes).
2.5. Statistical analysis All data were analyzed using SPSS 11.0 software (SPSS, Inc.). Unpaired t test, c2 contingency test, and Fisher’s exact test were used where appropriate. Nonparametric methods were also used for non-normally distributed values. Logistic regression analyses (univariate and multivariate) were used to calculate the risk for FL and various parameters. Some analyses were adjusted for age and sex. Kappa analysis was performed for blood biochemical data and as a quality control for ultrasonography. All provided P-values represent the results of two-sided tests. P-values !0.05 were considered statistically significant.
3. Results 3.1. Sampling status and general data We used a stratified multistage probability cluster sampling design to obtain a representative sample of the noninstitutionalized population in Shanghai. The investigated neighborhoods contained 4205 residents aged 16 years or more; persons reporting clinical diagnosis of chronic viral hepatitis, cirrhosis or other severe diseases, or pregnant, or long-term using of estrogens, tamoxifen, or corticosteroids were excluded (nZ237). Physical examination and laboratory data were obtained for 3834 individuals, of these, only 3175 individuals (82.81%) with complete data and ultrasonographic examinations were accepted; this study population corresponded to approximately 2.26/10,000 of the Shanghaineses, according to the Shanghai Census Count (2000). The study population included 1218 males and 1957 females, with a mean age of 52.4G15.1 years (16–88 years), and no significant difference was noted between males and females. Anthropometric, clinical, laboratory data, and prevalence rates of metabolic disorders of the 3175 participants were shown in Tables 1 and 2. In comparison
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Table 1 Anthropometric, clinical, and laboratory data of 3175 participants Characteristics
All cases (nZ3175)
Men (nZ1218)
Women (nZ1957)
P-value
Age (years) BMI (kg/m2) Waist circumference (cm) WHR Triglyceride (mmol/L) Total cholesterol (mmol/L) HDL-C (mmol/L) LDL-C (mmol/L) Systolic pressure (mmHg) Diastolic pressure (mmHg) Fasting glucose (mmol/L) 120-m glucose (mmol/L)
52.4G15.1 24.52G5.50 80.28G10.09 0.836G0.069 1.34G0.99 5.01G0.97 1.53G0.41 2.91G0.84 129.5G19.5 82.0G12.3 5.76G1.54 6.29G3.31
52.3G16.4 24.48G3.52 83.79G9.70 0.867G0.064 1.46G1.10 4.84G0.95 1.37G0.37 2.84G0.83 131.7G18.8 84.0G12.0 5.78G1.56 6.27G3.51
52.4G14.3 24.60G6.44 78.06G9.69 0.817G0.061 1.26G0.91 5.11G0.97 1.62G0.40 2.96G0.84 128.1G19.8 80.8G12.2 5.74G1.53 6.31G3.19
0.865 0.483 !0.001 !0.001 !0.001 !0.001 !0.001 !0.001 !0.001 !0.001 0.497 0.754
Table 2 Prevalence of metabolic syndrome features among 3175 participants Characteristics
All cases (nZ3175)
Men (nZ1218)
Women (nZ1957)
P-value
Obesity (%) Abdominal obesity (%) Dyslipidemia (%) Hypertension (%) Impaired fasting glucose (%) Impaired glucose tolerance (%) Diabetes mellitus (%)
1331 (41.9) 1136 (36.0) 1466 (46.2) 1511 (47.59) 261 (8.22) 128 (4.03) 512 (16.1)
545 (44.7) 333 (27.3) 526 (43.2) 647 (53.12) 109 (8.95) 53 (4.35) 220 (18.1)
786 (40.1) 803 (41.0) 940 (48.0) 864 (44.15) 152 (7.77) 75 (3.83) 292 (14.9)
0.011 !0.001 0.007 !0.001 0.238 0.470 0.019
*P-value for comparison between sexes.
with the sex and age composition obtained in the Shanghai Census Count (2000), the study population contained higher percentages of elderly and women (both P!0.001). Therefore, some of the results were adjusted by age and sex in order to better represent the real situation in Shanghai. 3.2. Prevalence of FL and the influence of age and sex Of the 3175 enrolled subjects, 661 (20.82%) were diagnosed as having FL. There was no significant sexual difference in the prevalence of FL (21.18 vs. 20.59%, PZ0.6908). The total prevalence of FL increased with age (in trend analysis, PZ0.00000), and the peak prevalence (28.44%) was reached between the ages of
60–69 years (Table 3). After stratification by sex, the prevalence of FL increased with age in both males and females (in trend analysis, PZ0.00011 and 0.00000, respectively). The peak prevalence in males was reached between the ages of 40–49 years, whereas in females between the ages of 60–69 years. The prevalence of FL was significantly higher in males than in females before age 50 years (c2-valueZ13.934, PZ0.0002), but was significantly higher in females than in males after age 50 years (c2Z4.146, PZ0.0417). After adjustment by age and sex, the overall prevalence of FL among Shanghai adults was found to be 17.29%, with the prevalence of FL being significantly higher in males than in females (19.30 vs. 15.08%, PZ0.0019).
Table 3 Prevalence of fatty liver in the study population Age (years)
Fatty liver in total (%)
Fatty liver in men (%)
Fatty liver in women (%)
P-value
16–19 20–29 30–39 40–49 50–59 60–69 R70
2/185 8/123 17/130 142/750 196/920 186/655 110/412
2/98 6/49 9/49 67/242 68/340 61/249 45/191
0/87 2/74 8/81 75/508 128/580 125/406 65/221
0.1815 0.0364 0.1657 !0.0001 0.4597 0.0833 0.1811
(1.08) (6.50) (13.08) (18.93) (21.13) (28.40) (26.70)
*P-value for comparison between sexes.
(2.04) (12.25) (18.37) (27.69) (20.00) (24.50) (23.56)
(0.00) (2.70) (9.88) (14.76) (22.07) (30.79) (29.41)
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Table 4 Baseline characteristics of 3175 participants according to the presence of the fatty liver Characteristics
With fatty liver (nZ661)
Without fatty liver (nZ2514)
T-value
P-value
Age (years) BMI (kg/m2) WHR Waist circumference (cm) Fasting glucose (mmol/L) 120-m glucose (mmol/L) Triglyceride (mmol/L) Total cholesterol (mmol/L) HDL-C (mmol/L) LDL-C (mmol/L) Systolic pressure (mmHg) Diastolic pressure (mmHg)
57.6G11.0 27.45G3.38 0.876G0.066 88.38G9.30 6.51G2.09 7.84G2.89 1.90G0.48 5.271G0.949 1.35G0.35 3.14G0.83 138.0G19.1 87.1G11.3
51.0G15.8 23.76G5.69 0.826G0.064 78.15G9.17 5.56G1.29 5.89G1.62 1.19G0.34 4.941G0.964 1.57G0.41 2.85G0.83 127.2G19.0 80.7G12.1
12.234 15.946 17.430 25.423 11.247 13.865 13.518 7.789 14.062 7.875 13.019 12.329
0.000 0.000 0.000 0.000 0.000 0.000 0.000 0.000 0.000 0.000 0.000 0.000
3.3. Analysis of risk factors for FL The 3175 subjects were divided into FL group (661) and non-FL group (2514). Univariate analysis showed that age, BMI, WHR, waist circumference, plasma glucose, triglyceride, total cholesterol, LDL-C and blood pressure were all significantly higher in the FL group than in the non-FL group, whereas HDL-C was otherwise (Table 4). The prevalences of obesity, abdominal obesity, abnormal glucose metabolism, dyslipidemia and hypertension were all significantly higher in the FL group than in the non-FL group (P!0.001) (Table 5). Of the 3175 enrolled subjects, 242 had habitual alcohol consumption (7.62%), with a much higher alcohol consumption rate in males versus females (17.73 vs. 1.33%, P!0.0001). Habitual alcohol consumption was seen in 61 (9.23%) subjects with FL and 181 (7.2%) subjects without FL (PO0.05). Low educational level and physical inactivity
was significantly higher in the FL group than in the non-FL (both P!0.05), but there were no differences in total family economic income or current cigarette smoking rates between the two groups (Table 6). Stepwise regression analysis was performed on the 28 features using the dichotomous variable logistic regression model. Our results showed that nine features were closely related to FL, including male gender, HDLC, triglyceride, educational level, DM, fasting glucose level, hypertension, waist circumference and BMI (Table 7). 3.4. Etiological constituent ratios of FL and their mutual influences Among the 661 FL patients, 611 (92.43%) were NAFL, 23 (3.48%) were AFL and 27 (4.08%) were suspected AFL. After age-and sex-adjustment, 88.78% were NAFL, 4.53%
Table 5 Prevalence of metabolic syndrome features in groups with and without fatty liver Characteristics
With fatty liver (nZ661)
Without fatty liver (nZ2514)
c2-value
P-value
Obesity Abdominal obesity Impaired fasting glucose Impaired glucose tolerance Diabetes mellitus Dyslipidemia Hypertension
522 (78.97) 474 (71.71) 81 (12.25) 25 (3.78) 215 (32.53) 467 (57.19) 464 (70.20)
809 (32.18) 662 (26.33) 190 (7.56) 25 (0.99) 297 (11.81) 999 (39.74) 1071 (42.60)
562.887 468.867 14.783 26.233 165.960 48.751 159.547
!0.0001 !0.0001 !0.001 !0.0001 !0.0001 !0.0001 !0.0001
Table 6 Other characteristics (%) in groups with and without fatty liver Characteristics
With fatty liver (nZ661)
Without fatty liver (nZ2514)
c2-value
P-value
Less than high school education Poverty-to-income ratio!1 Physical inactivity Current cigarette smoking Current habitual drinking
306 (46.29%) 49 (7.41%) 471 (71.26%) 87 (13.16%) 61 (9.23%)
825 (32.82%) 245 (9.75%) 1472 (58.55%) 276 (10.98%) 181 (7.20%)
41.441 3.388 35.558 2.463 3.058
!0.0001 0.0657 !0.0001 0.1165 0.0803
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Table 7 Results of logistic multivariant regression analysis of fatty liver and the tested variables Variable
Coefficient of regression (b)
Standard error (SE)
Wald c2
P
OR
95%CI
Male sex HDL cholesterol Triglyceride Educational level Diabetes mellitus Fasting glucose Hypertension Waist circumference BMI
0.994 K0.768 0.330 0.187 0.165 0.120 0.105 0.103 0.046
0.131 0.172 0.054 0.051 0.056 0.039 0.030 0.009 0.022
57.221 20.047 36.991 13.308 8.682 9.564 12.026 121.920 4.651
0.000 0.000 0.000 0.000 0.003 0.002 0.001 0.000 0.031
2.702 0.464 1.391 1.205 1.179 1.127 1.111 1.108 1.048
2.088–3.495 0.332–0.649 1.251–1.547 1.090–1.332 1.057–1.316 1.045–1.216 1.047–1.179 1.088–1.129 1.004–1.093
AFL, and 6.69% suspected AFL, the prevalence rates of nonalcoholic, alcoholic and suspected alcoholic FL in Shanghai adults were thus 15.35, 0.79 and 1.15%, respectively. Based on BMI and daily mean alcohol consumption, among the 3175 enrolled subjects, 1049 subjects were in the control group (BMI!23 kg/m2, alcohol consumption! 10 g/d and accumulative consumption!100 kg), 25 were in the excessive drinking group (BMI!23 kg/m2 and alcohol consumptionR30 g/d and/or accumulative consumptionR100 kg), 1252 were in the obese group (BMIR25 kg/m 2, alcohol consumption!10 g/d and accumulative consumption!100 kg), and 35 in the obese excessive drinking group (BMIR25 kg/m2 and alcohol consumptionR30 g/d and/or accumulative consumptionR100 kg). The prevalence rates of FL in the control, excessive drinking, obese and obese excessive drinking groups were 3.34, 8.00, 38.66 and 57.14%, respectively. Compared to the control group, the odds-ratio (95%CI) for FL for the other groups was 3.6 (1.1–11.7), 11.6 (8.2–16.5) and 17.1 (9.1–32.4), respectively. In excessive drinkers, obesity increased the risk for FL by 4.8-fold (1.4–16.6), but excessive drinking was associated with only a 1.5-fold (0.9–2.6) increased risk in obese subjects, whereas the risk of FL in obese subjects without excessive drinking was 3.2-fold (1.03– 10.1) higher than that in excessive drinkers without obesity.
4. Discussion FL is a heterogeneous disorder. In Western Europe, Japan, Australia, and the USA, population-based ultrasound surveys have indicated that almost one quarter of the adults has FL [1,5,6,8,17,21]. According to a sampling survey conducted among 257 northern Italian adults by Bellentani et al. [22], FL was more strongly associated with obesity than with heavy drinking. Several recent studies have shown that NAFL is the main cause of chronic liver disease in these parts of the world [1,5,6,8,17]. In China, epidemiological ultrasound surveys on FL were first published in the mid 1990s [8], but these studies were relatively limited in their specific populations, and the obtained FL prevalence rates varied widely due to differences in careers, age, gender
and regions studied [8,23,24]. To date, little is known about the population-based prevalence of FL in China. Our investigations demonstrated that approximately 20.82% of Shanghai adults (17.29% after age and sex adjustment) had FL, and most of these were cases of NAFL, consistent with the low alcohol consumption rate (7.62%) in the investigated subjects. Although studies published before 1990 emphasized that NAFL occurred mostly in women, whereas more recent studies have shown that NAFL and steatosis on CT occurs with equal frequency in both sexes [1,6]. In this study, the age-adjusted prevalence of FL was significantly higher in men than women, and logistic regression analysis showed that male gender was closely related to FL. Thus, our results suggest that female gender is not a risk factor for steatosis in Shanghai adults. FL has been reported in all age groups, including children, with a highest prevalence in those between 40 and 49 years of age [1]. In this study, the prevalence of FL increased with age in both sexes, with prevalence peaking in women 60–69 years of age, and in men 40–49 years of age. Interestingly, the prevalence was higher in males than females under the age of 50, but was lower in males than females among people older than 50 years. This phenomenon has been noted in our previous study [23], possibly related to differences in estrogen levels between pre- and post-menopausal women. It is supposed that the prevalence of AFL in China is lower than in many Western countries [8]. In this study, the age- and sex-adjusted prevalence of AFL was found to be only 0.79%, which was similar to the prevalence (0.94%) of AFL determined by an epidemiological survey of 18,237 residents in Zhejiang Province, China [25]. However, the etiological constituent ratio of FL should be further studied in North China, where there are more habitual and heavy drinkers than South China [26]. Compared with the controls, the risk for FL was 3.6-fold higher in heavy drinkers, 11.6fold higher in obese persons, and 17.1-fold higher in obese heavy drinkers. Indeed, in heavy drinkers, obesity increased the risk for FL by 4.8-fold, although heavy drinking did not significantly increase the risk for FL in obese persons. These findings are consistent with those of Bellentani et al. [22]. Because Asians generally have a lower BMI, and FL can occur in Asian subjects at levels of adiposity much lower than traditionally defined Western standards, regional
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guidelines for obesity were used in this study [13,27]. Our data demonstrated that FL was mainly associated with obesity, hyperglycemia, dyslipidemia and hypertension. These are the main features of the recently characterized metabolic syndrome, and people with the metabolic syndrome are at increased risk for developing DM and cardiovascular disease [1–4,7,28]. FL may be considered an additional feature of metabolic syndrome, and subjects with abdominal obesity are more prone to develop diabetes, hypertension and FL [1–4,7,28]. With epidemics of obesity and DM in Shanghai [8,23,28], FL has become an important emerging public health issue. Our univariate and multivariate regression analyses showed that FL was closely correlated with educational level. This could possibly be attributed to a lack of knowledge regarding prevention of multiple metabolic disorders, such as obesity and diabetes, in the population with lower educational levels. Univariate analysis showed that physical activity was a protective factor for FL, but this was not confirmed by the results of multivariate analysis. Moreover, we did not observe any significant relationship between FL and smoking or total economic income. Although there are inherent difficulties in quantitating and grading these ordinal data, a stringent effort was made to maintain the integrity of data collection and analysis throughout this work. FL has been associated with the use of various drugs or occupational exposure to specific chemicals, the prevalence of such exposures and their impact on the epidemiology of FL are unknown. In this study, we did not observe any significant correlation between drug use and FL. Ultrasonography is the modern diagnostic test of choice for FL epidemiological surveys because it is noninvasive, safe, widely available, portable, sensitive (up to 89%) and specific (up to 93%) in detecting steatosis [1,17,18].Our diagnoses of FL were based on ultrasonographic examinations, in which false-negative and false-positive errors are inevitable in comparison to liver biopsy, which is the gold standard for diagnosis of FL [1,28]. Therefore, strict quality controls were utilized in this study; the consistency tests showed that the ultrasonography used in this epidemiological field investigation produced good reliability. Despite the meticulous design and randomized sampling methods, some biases were still present, specifically via the inclusion of a larger proportion of the elderly and females in the study subjects, and complete data collection from only 82.81% of participants. Thus, the representative nature and scientific validity of this survey were likely influenced to some extent. However, this study offers a unique opportunity to study the evolution of previously described ‘first’ world diseases. Future studies should continue to focus both on the similar ties and highlight differences in the regional presentation of FL, and public health initiatives are imperative to halt or reverse FL epidemic.
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Acknowledgements We acknowledge Tian-shu Liu, M.D., for her assistance with statistical analysis, and Prof. Yong-de Peng and Xie-ning Wu for their assistances with critical revision of the manuscript.
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