Abstracts

Introduction

Non-alcoholic fatty liver disease (NAFLD) has become the leading cause of chronic liver disease worldwide, affecting 17-46% of adults ¹1. Vernon G, Baranova A, Younossi ZM. Systematic review: the epidemiology and natural history of non-alcoholic fatty liver disease and non-alcoholic steatohepatitis in adults. Aliment Pharmacol Ther 2011; 34:274-85.. About 20% of people with NAFLD have non-alcoholic steatohepatitis (NASH), which is associated with fibrosis and can evolve to cirrhosis and hepatocellular carcinoma ²2. Serfaty L, Lemoine M. Definition and natural history of metabolic steatosis: clinical aspects of NAFLD, NASH and cirrhosis. Diabetes Metab 2008; 34(6 Pt 2):634-7..

Prevalence of type 2 diabetes increased over the last decades and is still increasing globally ³3. NCD Risk Factor Collaboration (NCD-RisC). Worldwide trends in diabetes since 1980: a pooled analysis of 751 population-based studies with 4·4 million participants. Lancet 2016; 387:1513-30.. Diabetes has been linked to a shorter life expectancy mainly because of its complications, including heart disease, stroke, and kidney failure ⁴4. Seshasai SRK, Kaptoge S, Thompson A, Di Angelantonio E, Gao P, Sarwar N, et al. Diabetes mellitus, fasting glucose, and risk of cause-specific death. N Engl J Med 2011; 364:829-41.. Lifestyle changes and medications - such as metformin - are shown to reduce diabetes incidence ⁵5. Knowler WC, Barrett-Connor E, Fowler SE, Hamman RF, Lachin JM, Walker EA, et al. Reduction in the incidence of type 2 diabetes with lifestyle intervention or metformin. N Engl J Med 2002; 346:393-403.. Brazil is experiencing a rapid nutritional transition, with marked increases in overweight and obesity across all social strata, particularly in the low socioeconomic stratum. Not surprisingly, diabetes prevalence and associated mortality increased in the last decades ⁶6. Schmidt MI, Duncan BB, Silva GA, Menezes AM, Monteiro CA, Barreto SM, et al. Chronic non-communicable diseases in Brazil: burden and current challenges. Lancet 2011; 377:1949-61.^,77. Victora CG, Barreto ML, Leal MC, Monteiro CA, Schmidt MI, Paim J, et al. Health conditions and health-policy innovations in Brazil: the way forward. Lancet 2011; 377:2042-53..

NAFLD and diabetes share many cardiometabolic risk factors and pathophysiological pathways. Moreover, increasing epidemiological evidence suggests a bidirectional relationship between NAFLD and diabetes, and that NAFLD may precede and/or promote the development of diabetes ⁸8. Anstee QM, Targher G, Day CP. Progression of NAFLD to diabetes mellitus, cardiovascular disease or cirrhosis. Nat Rev Gastroenterol Hepatol 2013; 10:330-44.^,99. Bril F, Cusi K. Management of nonalcoholic fatty liver disease in patients with type 2 diabetes: a call to action. Diabetes Care 2017; 40:419-30.^,1010. Byrne CD, Targher G. NAFLD: a multisystem disease. J Hepatol 2015; 62(1 Suppl):S47-64.^,1111. Targher G, Marchesini G, Byrne CD. Risk of type 2 diabetes in patients with non-alcoholic fatty liver disease: causal association or epiphenomenon? Diabetes Metab 2016; 42:142-56.. Early identification of individuals at high risk for diabetes would help prevent further complications. Ultrasonography-diagnosed NAFLD has been independently associated with diabetes development, mainly in Asian populations ¹²12. Adams LA, Anstee QM, Tilg H, Targher G. Nonalcoholic fatty liver disease and its relationship with cardiovascular disease and other extrahepatic diseases. Gut 2017; 66:1138-53.^,1313. Okamoto M, Takeda Y, Yoda Y, Kobayashi K, Fujino MA, Yamagata Z. The association of fatty liver and diabetes risk. J Epidemiol 2003; 13:15-21.^,1414. Shibata M, Kihara Y, Taguchi M, Tashiro M, Otsuki M. Nonalcoholic fatty liver disease is a risk fator for type 2 diabetes in middle-aged Japanese men. Diabetes Care 2007; 30:2940-4.^,1515. Kim CH, Park JY, Lee KU, Kim JH, Kim HK. Fatty liver is an independent risk factor for the development of type 2 diabetes in Korean adults. Diabet Med 2008; 25:476-81.^,1616. Bae JC, Rhee EJ, Lee WY, Park SE, Park CY, Oh KW, et al. Combined effect of nonalcoholic fatty liver disease and impaired fasting glucose on the development of type 2 diabetes: a 4-year retrospective longitudinal study. Diabetes Care 2011; 34:727-9.^,1717. Park SK, Seo MH, Shin HC, Ryoo JH. Clinical availability of nonalcoholic fatty liver disease as an early predictor of type 2 diabetes mellitus in Korean men: 5-year prospective cohort study. Hepatology 2013; 57:1378-83.^,1818. Sung KC, Jeong WS, Wild SH, Byrne CD. Combined influence of insulin resistance, overweight/obesity, and fatty liver as risk factors for type 2 diabetes. Diabetes Care 2012; 35:717-22.^,1919. Chang Y, Jung HS, Yun KE, Cho J, Cho YK, Ryu S. Cohort study of non-alcoholic fatty liver disease, NAFLD fibrosis score, and the risk of incident diabetes in a Korean population. Am J Gastroenterol 2013; 108:1861-8.^,2020. Choi JH, Rhee EJ, Bae JC, Park SE, Park CY, Cho YK, et al. Increased risk of type 2 diabetes in subjects with both elevated liver enzymes and ultrasonographically diagnosed nonalcoholic fatty liver disease: a 4-year longitudinal study. Arch Med Res 2013; 44:115-20.^,2121. Yamazaki H, Tsuboya T, Tsuji K, Dohke M, Maguchi H. Independent association between improvement of nonalcoholic fatty liver disease and reduced incidence of type 2 diabetes. Diabetes Care 2015; 38:1673-9.^,2222. Mantovani A, Byrne CD, Bonora E, Targher G. Nonalcoholic fatty liver disease and risk of incident type 2 diabetes: a meta-analysis. Diabetes Care 2018; 41:372-82.^,2323. Tilg H, Moschen AR, Roden M. NAFLD and diabetes mellitus. Nat Rev Gastroenterol Hepatol 2017; 14:32-42.. This study aimed to determine whether hepatic steatosis is associated with the incidence of diabetes in a Brazilian cohort study, the Brazilian Longitudinal Study of Adult Health (ELSA-Brasil).

Methods

Study design and analytic sample

The ELSA-Brasil is a prospective, occupational cohort study aimed at investigating the incidence and progression of diabetes, cardiovascular disease, and other chronic conditions over time. The cohort study was conducted from August 2008 to December 2010, in six capital cities of different Brazilian regions. In total, 15,105 active or retired civil servants of public universities or research institutions aged 35-74 years participated. A comprehensive set of questionnaires, clinical measurements, and laboratory tests were carried out at baseline visit (visit 1). From September 2012 to December 2014, the cohort study was recalled for a new set of interviews and examinations (visit 2), as previously described ²⁴24. Schmidt MI, Duncan BB, Mill JG, Lotufo PA, Chor D, Barreto SM, et al. Cohort profile: ongitudinal study of adult health (ELSA-Brasil). Int J Epidemiol 2015; 44:68-75.. ELSA-Brasil was approved by the Brazilian National Research Ethics Commission (CONEP; 976/2006) and by the research ethics committee of each institution: São Paulo University (USP; 669/06), Oswaldo Cruz Foundation (Fiocruz; 343/06), Espírito Santo Federal University (UFES; 041/06), Minas Gerais Federal University (UFMG; 186/06), Rio Grande do Sul Federal University (UFRGS; 194/06), and Bahia Federal University (UFBA; 027/06).

At visit 1, 6,250 participants were excluded: 1,811 participants who had diabetes (confirmed at visit 2), four without enough information to confirm diabetes status, 2,558 who did not undergo liver ultrasonography, 751 who reported excessive alcohol consumption (> 20g/day for women and > 30g/day for men), 275 with missing information on relevant covariates (i.e., daily or weekly alcohol consumption, self-identified race/skin color, weight and/or height, physical activity level), 841 with self-referred hepatitis or cirrhosis, and 10 who had values four times higher or equal to the upper limit of normality for alanine aminotransferase (ALT) and/or aspartate aminotransferase (AST), resulting in 8,855 participants at risk of developing diabetes. Of these, 689 did not attend to the scheduled visit 2 or provided insufficient information to confirm diabetes status or relevant covariates at visit 2. Thus, considering the overlap in exclusion criteria, our final sample totaled 8,166 participants (92.2% of those at risk of diabetes at baseline). Compared to the study participants, those who did not return to visit 2 were slightly older, had higher body mass index (BMI), were more frequently men and had lower schooling level; difference regarding race/skin color was not significant.

Procedures

Data collection included face-to-face interviews, clinical examinations, and laboratory tests conducted by trained certified professionals using standardized instruments during visits 1 and 2 ²⁴24. Schmidt MI, Duncan BB, Mill JG, Lotufo PA, Chor D, Barreto SM, et al. Cohort profile: ongitudinal study of adult health (ELSA-Brasil). Int J Epidemiol 2015; 44:68-75.. They recorded age (years), race/skin color (self-declared following the Brazilian census categories as being white, black, mixed-race [“pardo”], Asian, and indigenous), sex, schooling level (≥ 12 years [higher education]; 9-11 years [high school]; ≤ 8 years [elementary school]), and family history of diabetes in first degree relatives. Alcohol consumption was assessed by the semi-quantitative food frequency questionnaire (g/day); smoking status (never, former, and current smoker) and current leisure physical activity were also assessed by questionnaires. Prescribed and nonprescribed medication use was verified against medication blisters/boxes and/or medical prescriptions brought to the clinic. Weight and height, BMI (kg/m²), and waist circumference (WC, in cm) were objectively assessed following standard procedures ²⁴24. Schmidt MI, Duncan BB, Mill JG, Lotufo PA, Chor D, Barreto SM, et al. Cohort profile: ongitudinal study of adult health (ELSA-Brasil). Int J Epidemiol 2015; 44:68-75..

An overnight fasting blood sample by venipuncture was obtained soon after the participant’s arrival at the clinic and followed standardized procedures for a two-hour 75g oral glucose tolerance test (OGTT) ²⁵25. World Health Organization. Definition, diagnosis and classification of diabetes mellitus and its complications. https://apps.who.int/iris/bitstream/handle/10665/66040/WHO_NCD_NCS_99.2.pdf (accessed on 03/Jul/2020).
https://apps.who.int/iris/bitstream/hand... . Fasting plasma glucose (FPG) concentrations were measured with the hexokinase method, insulin concentrations with an immunoenzymatic assay (ADVIA, Siemens: https://www.siemens.com); triglyceride and total and high density lipoprotein cholesterol (HDL) concentrations with enzymatic methods (Siemens); glycated hemoglobin (HbA1c) with high pressure liquid chromatography (Bio-Rad: https://www.bio-rad.com); AST and ALT by Modified International Federation for Clinical Chemistry technique (enzymatic assay) (Siemens). Insulin resistance was assessed using the homeostasis model assessment-insulin resistance (HOMA-IR), estimated by the equation [FPG (mg/dL) ×0.0555×fasting insulin (mIU/L)]/22.5. Low-density lipoprotein cholesterol (LDL) levels were estimated by the Friedewald equation when triglyceride levels were ≤ 400mg/dL. Otherwise, LDL was measured using the homogeneous enzymatic colorimetric method, without precipitation (Siemens). Ultrasensitive C-reactive protein (CRP) was measured by immunochemistry using nephelometry (nephelometer BN II Siemens).

Hypertension was defined as systolic blood pressure ≥ 140mmHg or diastolic blood pressure ≥ 90mmHg (sum of two measures), and/or use of anti-hypertensive drugs during the previous two weeks.

Leisure time physical activity was assessed using the International Physical Activity Questionnaire (IPAQ), in the long-modified version. Participants were categorized into two groups: low and moderate/high activity according to the sum of the metabolic equivalents per week (combination of type of activity, frequency, and duration) ²⁶26. Hallal PC, Victora CG. Reliability and validity of the International Physical Activity Questionnaire (IPAQ). Med Sci Sports Exerc 2004; 36:556..

Hepatic ultrasound protocol and fatty liver assessment

Liver ultrasound examinations on the participants were performed by board-certified radiologists or by radiology technicians, after adequate training, using the same models of equipment: a high-resolution B-mode scanner (SSA-790A, Aplio XG, Toshiba Medical System: https://www.toshiba.com/tic/industries-served/medical) and a convex array transducer (model PVT-375BT), with a central frequency of 3.5MHz, and a fundamental frequency of 1.9-5.0MHz. After acquisition, the B-mode hepatic ultrasound images were read by board-certified radiologists at the ELSA-São Paulo research center, which was established as the ELSA-Brasil ultrasound reading center. A senior ultrasound radiologist verified the quality control protocol was verified by crosschecking the data. The liver ultrasound scanning protocol was set up in accordance with the following criteria, as previously validated ²⁷27. Goulart AC, Oliveira IRS, Alencar AP, Santos MSC, Santos IS, Martines BMR, et al. Diagnostic accuracy of a noninvasive hepatic ultrasound score for non-alcoholic fatty liver disease (NAFLD) in the Brazilian Longitudinal Study of Adult Health (ELSA-Brasil). Sao Paulo Med J 2015; 133:115-24..

Hepatic attenuation of the ultrasound beam: a standard B-mode ultrasound evaluation was conducted using a 4-point visual grading system based on the degree of diaphragm visible posterior to the right hepatic lobe. The hepatic attenuation was classified as normal (diaphragm completely visible) or abnormal as: mild (partial, i.e., diaphragm > 50% visible); moderate (partial, i.e., diaphragm < 50% visible); or severe (no visible diaphragm). Liver steatosis was defined by the presence of abnormal hepatic attenuation ²⁷27. Goulart AC, Oliveira IRS, Alencar AP, Santos MSC, Santos IS, Martines BMR, et al. Diagnostic accuracy of a noninvasive hepatic ultrasound score for non-alcoholic fatty liver disease (NAFLD) in the Brazilian Longitudinal Study of Adult Health (ELSA-Brasil). Sao Paulo Med J 2015; 133:115-24..

Confirmation of diabetes

Diabetes was confirmed based on laboratory measurements and self-reported information at visit 1. Participants were considered to have previously diagnosed diabetes when answering yes to either “Have you been previously told by a physician that you had/have diabetes (sugar in the blood)?” or “Have you used medication for diabetes in the previous two weeks?”. For women who reported having only gestational diabetes, they were not considered as having had previously diagnosed diabetes. Those without a previous diagnosis were assessed for undiagnosed diabetes based on their laboratory values and then confirmed as having newly diagnosed diabetes if they reached the thresholds for FPG ≥ 126mg/dL; 7.0mmol/L, OGTT ≥ 200mg/dL; 11.1mmol/L, or HbA1C ≥ 6.5%; 48mmol/mol ¹¹11. Targher G, Marchesini G, Byrne CD. Risk of type 2 diabetes in patients with non-alcoholic fatty liver disease: causal association or epiphenomenon? Diabetes Metab 2016; 42:142-56.^,2525. World Health Organization. Definition, diagnosis and classification of diabetes mellitus and its complications. https://apps.who.int/iris/bitstream/handle/10665/66040/WHO_NCD_NCS_99.2.pdf (accessed on 03/Jul/2020).
https://apps.who.int/iris/bitstream/hand... . Participants whose diagnosis of diabetes has not been confirmed at visit 2 were not considered cases of diabetes and were included at baseline. Type 1 diabetes was not recorded among incident cases but, given that participants were all aged at least 35 years, these participants were unlikely to have type 1 diabetes. After excluding those with diabetes at visit 1 that were confirmed at visit 2, incident diabetes was confirmed based on the same criteria at visit 2 (2012-2014) ²⁸28. Schmidt MI, Bracco PA, Yudkin JS, Bensenor IM, Griep RH, Barreto SM, et al. Intermediate hyperglycaemia to predict progression to type 2 diabetes (ELSA-Brasil): an occupational cohort study in Brazil. Lancet Diabetes Endocrinol 2019; 7:267-77..

Statistical analysis

Kolmogorov-Smirnov and Shapiro-Wilk tests were used to test normality of data. Continuous variables were presented as means and standard deviation or medians and ranges, and dichotomic variables were presented as absolute numbers and percentages. Group differences for continuous variables were analyzed using Student’s t-test or the Mann-Whitney U test and, for categorical variables, using the chi-square test. Univariate logistic regression was performed to assess the characteristics associated with liver steatosis at baseline. Variables with a p-value < 0.20 in the univariate analysis were included as independent variables into the regression model. Multivariate logistic regression was used to evaluate the association of independent factors (age, sex, race/skin color, schooling level, BMI or WC, physical activity level, hypertension, smoking status, fasting plasma glucose, HDL cholesterol, and triglyceride levels) with liver steatosis. Statistical significance was set at two-sided p-value less than 0.05.

Time to event (detection of diabetes) was estimated as the time elapsed from visit 1 to the reported date of diagnosis obtained during yearly telephone interviews or at visit 2. When this date was unavailable, time to event was defined as half of the time elapsed from visit 1 to the follow-up contact point at which diabetes was reported. For incident cases defined only by laboratory values at visit 2, the estimated time to event (assuming a linear increase of glycemia from baseline to follow-up) was interpolated as the first date in which one of the three measures of glycemia reached its diagnostic threshold. Cumulative incidence (risk) over the whole analysis period was estimated as the number of new cases of diabetes divided by the total number of participants without diabetes at baseline.

Cox regression models were used to estimate the adjusted hazard ratio (HR) for incident diabetes based on two models. In the first model, adjustments were made for baseline BMI, sex, age, race/skin color, schooling level, hypertension, smoking status, leisure physical activity, FPG, and familiar history of diabetes. In the second model, BMI was replaced by WC and maintained the same variables. A sensitivity analysis was conducted, including CRP at model 1. We excluded participants with CRP ≥ 20mg/dL, which could indicate acute inflammation, totalizing 7,879 individuals for the final sample (Supplementary Material: http://cadernos.ensp.fiocruz.br/static//arquivo/suppl-0905-22_9379.pdf).

Proportional hazards assumptions were guaranteed using the Schoenfeld residual analysis. Statistical analysis was performed with Stata, version 14.0 (https://www.stata.com).

Results

Among ELSA-Brasil participants, the prevalence of liver steatosis was 35.1% and it was higher in males with obesity and lower schooling and physical activity levels. The group with liver steatosis had higher baseline BMI, WC, aminotransferases, triglycerides, total and LDL cholesterol, FPG, and HOMA-IR levels. Table 1 shows the baseline characteristics of the 8,166 participants.

The factors independently associated with liver steatosis at baseline were BMI and WC, sex, race/skin color, hypertension, leisure physical activity, triglycerides, HDL cholesterol, and FPG (Table 2).

The cumulative incidence of diabetes was 5.25% in the whole sample, 7.83% and 3.88% in the groups with and without hepatic steatosis, respectively (p < 0.001).

In the multivariate model adjusted for sex, age, race/skin color, schooling level, BMI, hypertension, smoking status, leisure physical activity, FPG, subjects with liver steatosis had higher risk of diabetes incidence compared to the group without hepatic steatosis (HR = 1.31; 1.09-1.56). The association persisted in the model adjusted for WC instead of BMI (HR = 1.29; 1.08-1.54) (Table 3).

Sensitivity analysis including CRP did not change the association between steatosis and diabetes incidence (Supplementary Material: http://cadernos.ensp.fiocruz.br/static//arquivo/suppl-0905-22_9379.pdf).

Discussion

Of the 8,166 participants without diabetes at baseline in the ELSA-Brasil, a contemporary, occupational cohort study of people aged 35-74 years living in a middle-income country, 35.1% presented liver steatosis detected by liver ultrasound, and fatty liver was associated with diabetes incidence. Due to unhealthy lifestyles, both NAFLD and diabetes have shown an increasing prevalence in the past decade, which is expected to increase further in the near future. Previous studies have shown that diabetes and cardiovascular disease are the most common outcomes and causes of death in patients with NAFLD ¹⁰10. Byrne CD, Targher G. NAFLD: a multisystem disease. J Hepatol 2015; 62(1 Suppl):S47-64.^,2929. Bhala N, George J. The burden of non-alcoholic fatty liver disease (NAFLD) in the Asia Pacific region. Curr Hepatol Rep 2015; 14:77-86..

The factors independently associated with the presence of hepatic steatosis at baseline were components of the metabolic syndrome (MetS): BMI and WC, triglycerides and FPG levels, which is consistent with the concept of NAFLD as a hepatic manifestation of MetS ³⁰30. Kotronen A, Westerbacka J, Bergholm R, Pietiläinen KH, Yki-Järvinen H. Liver fat in the metabolic syndrome. J Clin Endocrinol Metab 2007; 92:3490-7..

This study, based on the ELSA-Brasil, showed that having hepatic steatosis at baseline increased the risk of diabetes development by 29-30% after adjustments. To our knowledge, this is the first prospective study that confirms fatty liver as a risk factor for diabetes development in a South American population.

A recent meta-analysis with 19 unique observational studies (17 from Asian countries and two from the United States) provided evidence of a significant association between image-diagnosed fatty liver and the long-term risk of incident diabetes ²²22. Mantovani A, Byrne CD, Bonora E, Targher G. Nonalcoholic fatty liver disease and risk of incident type 2 diabetes: a meta-analysis. Diabetes Care 2018; 41:372-82.. They found that the presence of NAFLD conferred a HR = 2.2 for incident diabetes, a risk that seemed to increase further with growing NAFLD “severity” (assessed in four observational studies using either the ultrasonographic or the NAFLD fibrosis score). The association between NAFLD and diabetes risk was stronger in studies with a follow-up longer than five years ²²22. Mantovani A, Byrne CD, Bonora E, Targher G. Nonalcoholic fatty liver disease and risk of incident type 2 diabetes: a meta-analysis. Diabetes Care 2018; 41:372-82.. This might explain why we found a lower HR for diabetes in our study, as our mean follow-up was about four years.

It remains uncertain whether NAFLD causally increases diabetes risk or if it is a marker of other shared risk factors. The association between NAFLD and the development of diabetes can be explained in several ways. NAFLD, especially NASH with varying levels of hepatic fibrosis, exacerbates hepatic insulin resistance and causes the release of proinflammatory mediators and pro-diabetogenic hepatokines that may promote the development of diabetes ²³23. Tilg H, Moschen AR, Roden M. NAFLD and diabetes mellitus. Nat Rev Gastroenterol Hepatol 2017; 14:32-42.^,3131. Shoelson SE, Lee J, Goldfine AB. Inflammation and insulin resistance. J Clin Invest 2006; 116:1793-801.^,3232. Arkan MC, Havener AL, Greten FR, Maeda S, Li ZW, Long JM, et al. IKK-beta links inflammation to obesity-induced insulin resistance. Nat Med 2005; 11:191-8.. Although CRP is a biomarker of inflammation for ELSA-Brasil, the sensitivity analysis including it did not modify the association between NAFLD and diabetes incidence. Intrahepatic fat accumulation also increases insulin resistance by stimulating inflammatory pathways regulated by nuclear factor-β ³¹31. Shoelson SE, Lee J, Goldfine AB. Inflammation and insulin resistance. J Clin Invest 2006; 116:1793-801.^,3232. Arkan MC, Havener AL, Greten FR, Maeda S, Li ZW, Long JM, et al. IKK-beta links inflammation to obesity-induced insulin resistance. Nat Med 2005; 11:191-8.^,3333. Boden G, She P, Mozzoli M, Cheung P, Gumireddy K, Reddy P, et al. Free fatty acids produce insulin resistance and activate the proinflammatory nuclear factor-kB pathway in rat liver. Diabetes 2005; 54:3458-65.. However, whether improvement or resolution of NAFLD could decrease the risk of incident diabetes remains uncertain.

This study has several strengths. Firstly, a standard protocol of investigation was designed and strictly followed by specially trained epidemiologists, doctors, and nurses. All questionnaires and physical examinations were carried out according to a standard procedure. Secondly, the strict criteria of diabetes incidence included FPG, OGTT, and HbA1c, meaning fewer missing cases. Thus, excluding 689 participants who could not be evaluated at visit 2, all the participants who developed diabetes could be found and robust estimates of HR were obtained. Finally, this study had a large sample size, which gave us enough power to build a stable Cox model to estimate HRs.

This study also has its limitations. Viral hepatitis B and C serologies and laboratory investigations to exclude other etiologies of chronic liver diseases were not routinely performed. Some chronic liver diseases can lead to hepatic steatosis, such as alcoholic liver disease, infection by genotype 3 of the hepatitis C virus, Wilson’s disease, among others. However, participants were excluded if they reported excessive alcohol consumption or referred hepatitis or cirrhosis.

In conclusion, this study showed that in the ELSA-Brasil, liver steatosis is associated with an increased risk of developing diabetes. Showing that fatty liver is an independent risk factor for incident diabetes is important to justify strengthened NAFLD prevention strategies and to increase physicians’ awareness on the need to implement adequate preventive measures to decrease future diabetes incidence and related disease burden in patients with NAFLD. Lifestyle changes and sustained weight loss are the most effective ways to prevent diabetes and treat NAFLD.

Acknowledgments

Funding: The ELSA-Brasil baseline study and the 4-year follow-up were funded by the Brazilian Ministry of Health (Science and Technology Department) and the Brazilian Ministry of Science and Technology (Brazilian Funding Authority for Studies and Projects - FINEP, and the Brazilian National Research Council - CNPq). Grants of baseline: Rio Grande do Sul State (01 06 0010.00), Bahia State (01 06 0212.00), Espírito Santo State (01 06 0300.00), Minas Gerais State (01 06 0278.00), São Paulo State (01 06 0115.00), and Rio de Janeiro State (01 06 0071.00); grants of 4-year follow-up: Rio Grande do Sul State (01 10 0643-03), Bahia State (01 10 0742-00), Espírito Santo State (01 12 0284-00), Minas Gerais State (01 10 0746-00), São Paulo State (01 10 0773-00), and Rio de Janeiro State (01 11 0093-01). S. M. Barreto, L. Giatti, M. I. Schmidt, and B. B. Duncan are fellow of the CNPq. S. M. Barreto is also supported by the Minas Gerais State Research Foundation (FAPEMIG).

References

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