Artigos

Introduction

Given the increasing impact of cardiovascular diseases on mortality and disability-adjusted life years (DALYs), measuring cardiovascular health (CVH) has gained increased attention in recent years. In 2020, the American Heart Association (AHA) established metrics for population CVH monitoring, known as the “Life's Essential 8 – LE8”1, replacing their previous 2010 publication, the “Life's Simple 7 – LS7”2. It defined objective metrics for monitoring 8 health behaviors and health factors in the population: diet, physical activity (PA), nicotine exposure, sleep health, body mass index (BMI), blood lipid levels, plasma glucose, and blood pressure (BP). The final assessment classifies individual CVH profiles as high, moderate, or low according to average scores.
Subclinical hypothyroidism (SCH) is defined when TSH (thyroid-stimulating hormone) levels are elevated above reference values, while serum FT4 levels are within the reference range. There is evidence suggesting that SCH may be associated with comorbidities related to cardiovascular diseases (CVD), such as subclinical atherosclerosis3, dyslipidemia4, coronary artery disease5, insulin resistance6 and metabolic syndrome6.
Data from recent studies have been controversial regarding the association between SCH and higher mortality, and the extent to which this association (if existent) is driven by poorer cardiovascular health. Inoue et al.7, through causal mediation analysis, found increased risk of all-cause mortality among people with SCH mediated by cardiovascular diseases; and a meta-analysis 8 found an association of SCH and increased CVD risk and all-cause mortality, particularly in participants with high CVD risk. On the other hand, Zhang et al.9 also found an increased risk of mortality in patients with SCH after adjusting for age and sex. However, significance disappeared after further adjustment for body mass index (BMI), hypertension, diabetes and dyslipidemia. Other meta-analysis10 did not find an association of higher TSH levels and increased risk of cardiovascular-related mortality in adults with SCH and age higher than 60 years.
The use of LE8 scores offers advantages over the isolated analysis of individual risk factors. Evaluating these factors through the LE8 is superior from a predictive standpoint, as it captures cumulative effects and outperforms models based on single variables; moreover, from a primary prevention perspective, it intentionally excludes non-modifiable factors such as age, prioritizing feasible actions, and it is precisely the interventions aimed at improving cardiovascular health (and thus the LE8 score) that reduce the incidence of adverse outcomes. Cohort analyses demonstrate that higher LE8 scores reduce the risk of cardiovascular events by up to 53% (Hazard-ratio – HR - 0.47) and cardiovascular mortality by 63% (HR 0.37).11
A recent study12 found a negative association between LE8 score and higher TSH levels. However, to the best of our knowledge, no studies have applied the latest AHA's risk score in patients with SCH compared to euthyroid individuals. Here, we compared the LE8 CVH scores in euthyroid individuals and those with SCH in a cross-sectional analysis of the Brazilian Longitudinal Study of Adult Health (ELSA-Brasil) baseline.
Methods

Study design and population

ELSA-Brasil is a prospective cohort study including 15,105 women and men aged 35 to 74 years, who were retired or active civil servants from six educational and research institutions across three regions of Brazil. The primary objective of ELSA-Brasil is to investigate the epidemiological, clinical, and molecular aspects of non-communicable chronic diseases, with a particular emphasis on type 2 diabetes and cardiovascular diseases13. Data collection protocol involved interviews, measurements, examinations, and the storage of biological samples14. Annually, participants are contacted via telephone, and every four to five years, they are invited to undergo additional interviews, measurements, and examinations in face-to-face encounters for health status tracking and outcome monitoring. The first wave (baseline) of data collection occurred between 2008 and 2010.
The ELSA-Brasil inclusion criteria comprised active or retired civil servants with 35-74 years at baseline (2008-2010)15. Exclusion criteria were (i) intention to leave the institution in the incoming years, (ii) current pregnancy or recent pregnancy less than 4 months before participating in the study, (iii) severe cognitive or communication disability, and (iv) residency outside the center of investigation metropolitan area15.
In this cross-sectional study, we analyzed data from baseline, except for the sleep health metric. Sleep information was first collected in the second ELSA-Brasil onsite assessment (Wave 2, 2012-2014). Therefore, data about sleep health in these analyses considers information from Wave 2 (2012-2014). Of the 15,105 individuals included in Wave 1, 10,780 were eligible for this analysis. We excluded 2,784 participants who had thyroid status other than normal or SCH or missing information about thyroid function, 224 who were using medications that altered thyroid function (amiodarone, carbamazepine, carbidopa, furosemide, haloperidol, heparin, levodopa, lithium, metoclopramide, phenytoin, propranolol, primidone, rifampicin, steroids, and valproic acid) and 1,317 who presented missing data for LE8 analysis (Supplementary Figure 1).

Ethical aspects
The project was approved in the Ethics Research Committee as nº 6.509.981 (CAAE nº 75639423.2.0000.0076). All participants provided signed informed consents.

Thyroid function assessment

Venous blood samples were collected between 6:30 a.m. and 9:00 a.m., after an overnight fast. Thyroid-stimulating hormone (TSH, normal range: 0.4–4.0 mIU/L) and free thyroxine (FT4, 0.93–1.7 ng/dL) levels were determined using a third-generation enzymatic method with Roche kits. The analysis included euthyroid participants (TSH levels 0.4–4.0 mIU/L and no use of levothyroxine/antithyroid drugs) and participants with SCH (TSH >4.0 mIU/L with fT4 0.93–1.7 ng/dL).

LE8 assessment

Several previous analyses of ELSA-Brasil reported the association of cardiovascular health and coronary artery calcium6; psychiatric comorbidity16; and cognitive decline17. LE8 metrics were evaluated following the American Heart Association's criteria1. It includes four health behaviors (physical activity, diet, nicotine exposure and sleep) and four health factors (BMI, blood lipids, plasma glucose and blood pressure). Each metric ranged from 0 to 100 and the overall LE8 score was calculated as the unweighted average of all metrics, therefore also ranging from 0 to 100. Higher score values represented better health behavior/factor profiles. Low nicotine exposure, BMI, blood lipids, plasma glucose, and blood pressure yield higher LE8 scores. Conversely, for Mediterranean Eating Pattern for Americans (MEPA) diet score and physical activity, higher levels result in higher LE8 scores. Sleep health is ideal (100 points) if sleep duration is between 7-9h/day, and lower LE8 scores are assigned outside this range (Supplementary Table 1).
All health behavioral variables were assessed through face-to-face interviews at the ELSA-Brasil research centers. Information about diet was based on a Food Frequency Questionnaire (FFQ) asking about the frequency of consumption of 114 typical Brazilian foods, including fresh, regional, processed, and alcoholic beverages18. The LE8 information about diet was based on the DASH- and Mediterranean-style eating patterns.1 ELSA-Brasil questionnaire has all the information included in DASH diet and Mediterranean Style Eating Pattern (MEPA), thus permitting to classify diet according to LE8 criteria. Cutoffs from the LE8 for MEPA were then applied, to generate a continuous (0 to 100) diet score.
Physical activity was evaluated at leisure and transportation-related physical activity assessed using the long version of the International Physical Activity Questionnaire (IPAQ). The IPAQ, proposed by the World Health Organization (WHO) in 1998, measures physical activity levels with international applicability19. Participants reported how much time per week they engaged in moderate or vigorous physical activities during leisure and daily transportation. Nicotine exposure was self-reported. Participants were asked if they were current or former smokers, if they had smoked at least 100 cigarettes in their lifetime, at what age they initiated smoking, the quantity, frequency, and duration of current or previous cigarette use, and if they were exposed to secondhand smoke. Sleep duration was assessed by the self-reported question ‘‘How many hours do you usually sleep at night?’’. Participants were classified into short sleep duration (?6 h), adequate sleep duration (6-8h), and long sleep duration (?8 h). Three questions examined subjective insomnia complaints: ‘‘In the past four weeks regarding your sleep at home at night, how often have you had difficulty falling asleep?’’, ‘‘How often have you woken up and had difficulty falling asleep again?’’,and ‘‘How often have you woken up before the desired time and not managed to fall asleep again?’’. Participants answered using the following Likert-type scale: always, almost always, sometimes, rarely, and never. A frequent insomnia complaint was considered when participants answered ‘‘always’’ or ‘‘almost always’’ to at least one question. The collected data were then adapted to the LE8 by calculating the weighted weekly average sleep duration. This average was then categorized according to LE8 criteria2, with decreasing scores for very short sleep (<7h) or very long sleep (>9h).
All anthropometric measurements were performed using standardized techniques.20 Body Mass Index (BMI) was calculated as weight (kg) divided by squared height (m2). Blood lipids such as total cholesterol, high-density lipoprotein (HDL)-cholesterol, and triglycerides (glycerol phosphate peroxidase) were measured by enzymatic colorimetric assay (Siemens, Deerfield, USA); LDL-cholesterol was calculated using Friedewald equation, except if triglycerides >400 mg/dL, when an enzymatic colorimetric assay (ADVIA 1200; Siemens) was used. Plasma glucose levels were measured using the hexokinase method, using ADVIA 1200 Siemens® analyzer. Blood pressure was measured using an automated sphygmomanometer (Omron HEM 750 CP INT) after a five-minute rest period, with the patient seated in a temperature-controlled room (20-24 degrees Celsius). Three measurements were taken at one-minute intervals, and the mean of the last two measurements was considered.

Sociodemographic variables

The ELSA-Brasil questionnaires included information about sociodemographic risk factors, such as age, gender, educational level, average monthly income, and ethnicity. Educational level was recorded as i) less than high school, ii) high school and some college iii) complete college or more. Net family income was recorded as i) less than US$1245, ii) between US$1246-3319, or iii) greater than US$3320. Race/ethnicity was self-declared and recorded as black, brown, white, Asian, or native.

Statistical analysis
Categorical variables were expressed as proportions and were compared using Chi-squared tests. Continuous variables were expressed as means (standard deviation) and compared using Wilcoxon rank-sum tests for two independent samples. Adjusted means of each LE8 factors and scores were determined and compared between samples using linear regression and their respective p-values calculated with Tukey test. Logistic regression models unadjusted and adjusted by age, sex, educational attainment, and race/ethnicity were built using LE8 metrics as the independent variable and SCH as the dependent variable, reporting odds ratios (OR) and 95% confidence interval (95% CI). Significance level was set at 0.05. All analyses were performed using RStudio 2023.09.0 Build 463 (Posit, 2024).
The authors are solely responsible for the design and conduct of this study, all study analyses, the drafting and editing of the manuscript, and its final contents.
Results

From 10,780 participants included in this analysis, 987 (9.2%) presented with SCH. Table 1 shows general characteristics of participants according to thyroid function profile. Statistically significant differences were observed for age, with a median that was on average 3 years higher in those with SCH compared to euthyroid individuals (p<0.001); self-reported race, with SCH presenting mostly individuals that self-reported as White (59.6% versus 51.1%, p<0.001); and smoking, which was lower among those with SCH (8.4% versus 13.4%, p<0.001). We did not find differences regarding the following LE8 cardiovascular health factors: BMI, dyslipidemia, diabetes and hypertension according to thyroid function. However, individuals with SCH showed higher scores for nicotine exposure (p=0.0177), diet (p=0.0023) and LE8 health behaviors (p=0.0120).
After adjustment for age, sex, educational attainment, and race (Table 2), a higher LE8 health factors score was found in euthyroid individuals (70.5 vs. 70.0) compared to individuals with subclinical hypothyroidism. After the same adjustment (Table 2), a higher LE8 health behavior score was found in individuals with SCH compared to euthyroid ones (56.8 vs 55.4; p=0.0142). Among individual LE8 metrics, differences in nicotine exposure (77.1 vs 72.4; p<0.001) and diet (45.9 vs 45.0; p=0.0373) may explain the better health behavior profile in individuals with SCH. Additionally, blood glucose adjusted means also pointed to a small but statistically significant better CVH in individuals with SCH (73.5 vs 72.0; p=0.0388).
Furthermore, logistic regression models adjusted by age, sex, educational attainment and race (Figure 1) confirmed the tendency of increased OR for the association between SCH and higher LE8 health behaviors strata (OR = 1.18, CI 1.01 – 1.37) for moderate CVH score and OR = 1.25, CI 1.02 – 1.53 for high CVH score) and also showed a significant LE8 health factors score strata (OR = 0.80, CI 0.65 – 0.99 for moderate CVH score and OR=0.77, CI 0.62-0.97 for high CVH score), using those in the low CVH score range as the reference group.

Fig1

Discussion
Our findings showed that after adjustment of age, sex, educational attainment, and race there was no difference of total LE8 score comparing euthyroid individuals and people with subclinical hypothyroidism (SCH). In adjusted logistic models we found similar findings with no association between total LE8 between individuals with subclinical hypothyroidism compared to euthyroid ones.
Our findings are in disagreement with the findings of the analysis of Fang et al., that showed an inverse association of LE8 with low thyroid function 12. Low thyroid function in their analysis was defined TSH> 2.5 mIU/L, a continuous variable, while we considered SCH a categorical variable using the cutoff of TSH> 4.0mIU/L and FT4 in the reference range. Therefore, the strategy of analysis was different between both studies. In addition, differences in study populations may also influence the differences between the two studies. The association between cardiovascular diseases and subclinical thyroid disease has been previously studied. There is some evidence that SCH contributes to pathological processes occurring over the natural history of cardiovascular disease, e.g., hypercholesterolemia 4, coronary artery calcification 24 and increased carotid intima-media thickness3,25. However, conflicting evidence exists. A systematic review with 555,287 participants 5 found an increased risk of cardiovascular events and deaths only when TSH levels were between 10 and 19.9 mIU/L, but not when TSH elevation was below 10 mIU/L. The RR for CHD mortality was 1.42 (95% CI, 1.03-1.95) for TSH values 7-9.9 mIU/L and 1.58 (95% CI, 1.10-2.27) for TSH values between 10 and 19.9 mIU/L. Similarly, Gencer et al.26 found that there is an increased risk of heart failure in people whose TSH is over 10 mIU/L, but not on those with TSH between 4.50 and 6.99 mIU/L.
Health behaviors were found to have a direct relation with SCH, meaning that a healthier, higher health behaviors LE8 score could be associated with SCH through lower nicotine exposure and better diet. Individuals with SCH had higher adjusted mean nicotine-related LE8 scores (lower exposure to nicotine), a characteristic previously described in individuals with SCH in other samples. Taylor et al.21, Asvold et al.22 and Cho et al. 23 found an inverse relation between current smoking and SCH. Therefore, the high score of LE8 health behaviors may be explained by the lower prevalence of current smoking in people with SCH and not with a real better CVD health profile.
One possible mechanism for the association of SCH and cardiovascular disease is the presence of poorer CVH profile compared to euthyroid individuals. In our study, we reported a better health LE8 score because of a lower frequency of smoking in individuals with SCH, which is consistent with previous findings of previous thyroid studies. (Taylor et al.21, Asvold et al.22, Cho et al. 23, Strider27, Belin28). A 2018 review on the epidemiology of thyroid dysfunctions 21, based on the cross-sectional studies from Strieder et al.27, Belin et al.28 and Asvold et al.22, summarized that, compared to non-smokers, current smokers were 50% less likely to have SCH and 40% less likely to have overt hypothyroidism 21,22. In the context of our study, the higher health LE8 score may be understood as a proxy of smoking. The association of SCH with less smoking may be explained by the suppressive effect of nicotine exposure on autoimmunity. Research has shown that smokers have a 30–45% lower likelihood of testing positive for thyroid peroxidase antibodies (anti-TPO)22. Hashimoto's thyroiditis, the leading cause of hypothyroidism in iodine-sufficient regions, is characterized by the presence of anti-TPO antibodies. Furthermore, it has been suggested that nicotine and anatabine, both alkaloids found in tobacco, may modulate the autoimmune response by shifting it away from Th1 and Th17 pathways through the activation of nicotine receptors on immune cells29. However, smoking is a risk factor for Grave's hyperthyroidism30, which is also an autoimmune disease. In this regard, the relation between tobacco exposure and autoimmunity needs to be clarified in further studies. Another important point is that Brazilian prevalence of current smoking is around 9%, lower than the world prevalence of 19%31. This lower prevalence of smoking in Brazil may likely impact our findings.
The association of healthy diet with SCH was of significance after adjustment for age, sex, educational attainment, and race (p=0.0373, Table 2). A recently published study32 found an inverse association between a Western-pattern diet (i.e., high on solid fats, processed meats and added sugar) and overt hypothyroidism. The main reason raised was the high contents of iron, zinc and selenium, necessary elements for the synthesis of thyroid hormones, in meat products. This could potentially also be seen in our sample, considering that Brazil has one of the largest meat intake in the world33. However, the Mediterranean Eating Pattern for Americans (MEPA) scoring system does not explore these micronutrients in detail, and further research is necessary in order to understand the role of each separate food on explaining how a Dietary Approaches to Stop Hypertension (DASH) inspired, low-fat, lean meat and whole grain diet could be associated with higher TSH levels.
We have not found an association between SCH and factors such as BMI, hypertension, diabetes, and dyslipidemia. Our divergent results from previous studies that linked SCH to cardiovascular risk factors may rely partially on heterogeneous SCH definitions. Most associations were found using a TSH level cutoff at 10 mIU/L. In our sample, only 1.9% of people with SCH had TSH above 10mIU/L, hence our decision to not analyze this subgroup separately. Additionally, studies regarding association between SCH and risk factors often find significant results in specific population risk groups. For obesity, a meta-analysis34 found a prevalence of 14.6% in 19,996 patients with obesity but acknowledged that the female to male ratio of 4:1 could induce bias. A cross-sectional survey of 2,505 subjects found that presence of SCH was higher in those who had positive thyroid autoantibodies and were obese35. As for hypertension, another meta-analysis36 found SCH associated with an increased incidence of hypertension in middle-aged women but not in women above 65 years. On the other hand, hyperlipidemia appears to have the strongest link to SCH, but even this association has not been consensual due to heterogeneity of studies37.
Although higher LE8 blood glucose score was found statistically significant, the slight difference on the adjusted means cannot be considered clinically significant. Also, in our population there was no association between SCH and people with overt diabetes. Our findings converge with other studies regarding diabetes: in a meta-analysis involving data from 61,178 individuals38, after excluding people with diabetes and overt thyroid dysfunction at baseline, SCH was not linked to incident diabetes.
The main strength of our study is the utilization of data from the large, multicenter ELSA-Brasil cohort, which provided a high-quality database for our analyses with all the necessary information to fulfill the LE8. One of the most important limitations of the study is that the sleep variable was only collected in Wave 2. We used the information about sleep from Wave 2 in the calculation of LE8 in this study. However, it is important to note that there were similar findings for sleeping in Waves 2 and 3, suggesting that sleep patterns did not change substantially over time39. TSH and FT4 values were measured only one time and some kind of misclassification is possible. However, this is a common limitation of large epidemiologic studies evaluating thyroid function. In addition, the number of participants with high TSH levels is very small, which can contribute to the absence of association of SCH with cardiovascular risk factors.
Our findings showed that after adjustment for age, sex, education attainment and race there was no difference in LE8 total score comparing euthyroid individuals and individuals with SCH. In the context of our analysis the higher health LE8 score may be interpreted as a proxy of smoking in the sample, but not with a real better CVD health profile.
Funding
The ELSA-Brasil baseline study and the 4-year follow-up was supported by the Brazilian Ministry of Health (Science and Technology Department) and the Brazilian Ministry of Science and Technology (Financiadora de Estudos e Projetos and CNPq National Research Council) (grants of baseline 01 06 0010.00 RS, 01 06 0212.00 BA, 01 06 0300.00 ES, 01 06 0278.00 MG, 01 06 0115.00 SP, 01 06 0071.00 RJ; grants of 4-year follow-up 01 10 0643-03 RS, 01 10 0742-00 BA, 01 12 0284-00 ES, 01 10 0746-00 MG, 01 10 0773-00 SP, 01 11 0093-01 RJ); (grants follow-up 01 10 0643-03 RS; 01 10 0742-00 BA; 01 11 0093- 01 RJ; 01 12 0284-00 ES; 01 10 0746-00 MG; 01 10 0773- 00 SP). FAPESP – Fundação de Amparo à Pesquisa do Estado de São Paulo – 2015/17213-2. The study was also supported by Fundação de Amparo à Pesquisa under grant no. 2023/16565-9.
Disclosure of interest
The authors report there are no competing interests to declare.
Data Availability Statement
Raw data were generated at Centro de Pesquisa Clínica e Epidemiológica (CPCE), Hospital Universitário, Universidade de Sao Paulo, Sao Paulo, Brazil. Derived data supporting the findings of this study are available from the corresponding author Isabela M. Bensenor on request.
The Supplementary Figure 1 and Supplementary Table 1 are available in the SciELO Data repository on the Ciência & Saúde Coletiva Dataverse at the link: https://doi.org/10.48331/SCIELODATA.A3FGP9.40



References
1.Lloyd-Jones DM, Allen NB, Anderson CAM, et al. Life's Essential 8: updating and enhancing the American Heart Association's construct of cardiovascular health: a Presidential Advisory from the American Heart Association. Circulation 2022;146(5):e18-e43
2.Lloyd-Jones DM, Hong Y, Labarthe D, et al. Defining and setting national goals for cardiovascular health promotion and disease reduction: the American Heart Association's strategic Impact Goal through 2020 and beyond. Circulation 2010;121(4):586-613
3.Gao N, Zhang W, Zhang YZ, Yang Q, Chen SH. Carotid intima-media thickness in patients with subclinical hypothyroidism: a meta-analysis. Atherosclerosis 2013;227(1):18-25
4.Liu J, Chen Y, Ren B, et al. Alteration of lipid profile between subclinical hypothyroidism and well-matched controls: a meta-analysis. Horm Metab Res 2023;55(7):479-486
5.Rodondi N, den Elzen WP, Bauer DC, et al. Subclinical hypothyroidism and the risk of coronary heart disease and mortality. JAMA 2010;304(12):1365-1374
6.Bensenor IM, Goulart AC, Santos IS, et al. Association between a healthy cardiovascular risk factor profile and coronary artery calcium score: results from the Brazilian Longitudinal Study of Adult Health (ELSA-Brasil). Am Heart J 2016;174:51-59
7.Inoue K, Ritz B, Brent GA, Ebrahimi R, Rhee CM, Leung AM. Association of subclinical hypothyroidism and cardiovascular disease with mortality. JAMA Netw Open 2020;3(2):e1920745
8.Moon S, Kim MJ, Yu JM, Yoo HJ, Park YJ. Subclinical hypothyroidism and the risk of cardiovascular disease and all-cause mortality: a meta-analysis of prospective cohort studies. Thyroid 2018;28(9):1101-1110
9.Zhang X, Wang Y, Wang H, Zhang X. Trends in prevalence of thyroid dysfunction and its associations with mortality among US participants, 1988-2012. J Clin Endocrinol Metab 2024;109(2):e657-e666
10.Zhong J, Mu D, Zou Y, Li L, Cheng X, Qiu L. High thyrotropin levels and risk of mortality in the elderly with subclinical hypothyroidism: a systematic review and meta-analysis. Endocr Pract 2023;29(3):206-213
11.Sebastian SA, Shah Y, Paul H, Arsene C. Life's Essential 8 and the risk of cardiovascular disease: a systematic review and meta-analysis. Eur J Prev Cardiol 2025;32(5):358-373
12.Fang X, Hu R, Fei S, Ding Z, Zhao J, Shang J. Associations between cardiovascular health and low thyroid function among US adults: a population-based study. Front Endocrinol (Lausanne) 2024;15:1437386
13.Aquino EM, Barreto SM, Bensenor IM, et al. Brazilian Longitudinal Study of Adult Health (ELSA-Brasil): objectives and design. Am J Epidemiol 2012;175(4):315-324
14.Bensenor IM, Griep RH, Pinto KA, et al. Rotinas de organização de exames e entrevistas no centro de investigação ELSA-Brasil. Rev Saude Publica 2013;47 Supl 2:37-47
15.Schmidt MI, Duncan BB, Mill JG, et al. Cohort Profile: Longitudinal Study of Adult Health (ELSA-Brasil). Int J Epidemiol 2015;44(1):68-75
16.Szlejf C, Suemoto CK, Santos IS, et al. Poorer cardiovascular health is associated with psychiatric comorbidity: results from the ELSA-Brasil Study. Int J Cardiol 2019;274:358-365
17.Ferreira NV, Gonçalves NG, Szlejf C, et al. Optimal cardiovascular health is associated with slower cognitive decline. Eur J Neurol 2024;31(2):e16139
18.Molina Mdel C, Benseñor IM, Cardoso Lde O, et al. Reprodutibilidade e validade relativa do Questionário de Frequência Alimentar do ELSA-Brasil. Cad Saude Publica 2013;29(2):379-389
19.Matsudo S, Araújo T, Matsudo V, et al. Questionário Internacional de Atividade Física (IPAQ): estudo de validade e reprodutibilidade no Brasil. Rev Bras Ativ Fis Saude 2001;6(2):5-18
20.Lohman TG, Roche AF, Martorell R. Anthropometric standardization reference manual. Champaign, IL: Human Kinetics; 1991. p.90
21.Taylor PN, Albrecht D, Scholz A, et al. Global epidemiology of hyperthyroidism and hypothyroidism. Nat Rev Endocrinol 2018;14(5):301-316
22.Asvold BO, Bjøro T, Nilsen TI, Vatten LJ. Tobacco smoking and thyroid function: a population-based study. Arch Intern Med 2007;167(13):1428-1432
23.Cho NH, Choi HS, Kim KW, et al. Interaction between cigarette smoking and iodine intake and their impact on thyroid function. Clin Endocrinol (Oxf) 2010;73(2):264-270
24.Zhang Y, Kim BK, Chang Y, et al. Thyroid hormones and coronary artery calcification in euthyroid men and women. Arterioscler Thromb Vasc Biol 2014;34(9):2128-2134
25.Peixoto de Miranda ÉJ, Bittencourt MS, Pereira AC, et al. Subclinical hypothyroidism is associated with higher carotid intima-media thickness in cross-sectional analysis of the Brazilian Longitudinal Study of Adult Health (ELSA-Brasil). Nutr Metab Cardiovasc Dis 2016;26(10):915-921
26.Gencer B, Collet TH, Virgini V, et al. Subclinical thyroid dysfunction and the risk of heart failure events: an individual participant data analysis from 6 prospective cohorts. Circulation 2012;126(9):1040-1049
27.Strieder TG, Prummel MF, Tijssen JG, Endert E, Wiersinga WM. Risk factors for and prevalence of thyroid disorders in a cross-sectional study among healthy female relatives of patients with autoimmune thyroid disease. Clin Endocrinol (Oxf) 2003;59(3):396-401
28.Belin RM, Astor BC, Powe NR, Ladenson PW. Smoke exposure is associated with a lower prevalence of serum thyroid autoantibodies and thyrotropin concentration elevation and a higher prevalence of mild thyrotropin concentration suppression in the third National Health and Nutrition Examination Survey (NHANES III). J Clin Endocrinol Metab 2004;89(12):6077-6086
29.Wiersinga WM. Smoking and thyroid. Clin Endocrinol (Oxf) 2013;79(2):145-151
30.Prummel MF, Wiersinga WM. Smoking and risk of Graves' disease. JAMA 1993;269(4):479-482
31.World Health Organization. WHO report on the global tobacco epidemic 2025. Geneva: World Health Organization; 2025
32.Alkhatib D, Shi Z, Ganji V. Dietary patterns and hypothyroidism in U.S. adult population. Nutrients 2024;16(3):382
33.OECD Data Explorer. [Internet]. 2024 [cited 2026 Jan 22]. Available from: https://data-explorer.oecd.org/
34.van Hulsteijn LT, Pasquali R, Casanueva F, et al. Prevalence of endocrine disorders in obese patients: systematic review and meta-analysis. Eur J Endocrinol 2020;182(1):11-21
35.Yan Y, Xu M, Wu M, et al. Obesity is associated with subclinical hypothyroidism in the presence of thyroid autoantibodies: a cross-sectional study. BMC Endocr Disord 2022;22(1):94
36.Kim J, Prasitlumkum N, Randhawa S, Banerjee D. Association between subclinical hypothyroidism and incident hypertension in women: a systematic review and meta-analysis. J Clin Med 2021;10(15):3318
37.Liu XL, He S, Zhang SF, et al. Alteration of lipid profile in subclinical hypothyroidism: a meta-analysis. Med Sci Monit 2014;20:1432-1441
38.Alwan H, Villoz F, Feller M, et al. Subclinical thyroid dysfunction and incident diabetes: a systematic review and an individual participant data analysis of prospective cohort studies. Eur J Endocrinol 2022;187(5):S35-S46
39.Ferreira NV, Gonçalves NG, Szlejf C, et al. Optimal cardiovascular health is associated with slower cognitive decline. Eur J Neurol 2024;31(2):e16139
40.Stelati, Adriana. 2026. “Data for: Life's Essential 8 in Patients with Subclinical Hypothyroidism: Results of the Brazilian Longitudinal Study of Adult Health (ELSA-Brasil).” SciELO Data. https://doi.org/10.48331/SCIELODATA.A3FGP9.