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      Associations of thyroid feedback quantile-based index with diabetes in euthyroid adults in the United States and China

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          Abstract

          Background

          We aimed to investigate the associations between thyroid hormone sensitivity indices and diabetes in euthyroid adults in the United States and China.

          Methods

          2296 euthyroid adults from the NHANES in the United States and 8319 euthyroid adults from the SPEED-Shunde in China were involved. The thyroid sensitivity indices, namely TFQIFT4 and TFQIFT3, were calculated. Multivariable logistic regression, restricted cubic spline analysis, and general ordinal logit regression were utilized.

          Results

          In the NHANES, compared with participants in quartile 1st (Q1), those in Q4 of TFQI FT3 (OR 2.12, 95% CI (1.18, 3.81)) and those in Q3 of TFQI FT4 (OR 2.31, 95% CI (1.18, 4.53)) (both P for trend < 0.05) were associated with a greater prevalence of diabetes. In the SPEED-Shunde, compared with participants in Q1, those in Q4 of TFQI FT3 had a greater prevalence of diabetes (OR 1.36, 95% CI (1.11, 1.66) ( P for trend < 0.05), while no significant associations between TFQI FT4 and diabetes were found.

          Conclusions

          TFQI FT3 was associated with a higher prevalence of diabetes both in the United States and China. However, TFQI FT4 was only associated with a higher prevalence of diabetes in the United States, not in China. Further prospective cohort studies are necessary to validate these findings.

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          Most cited references49

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          Prevalence of diabetes recorded in mainland China using 2018 diagnostic criteria from the American Diabetes Association: national cross sectional study

          Abstract Objective To assess the prevalence of diabetes and its risk factors. Design Population based, cross sectional study. Setting 31 provinces in mainland China with nationally representative cross sectional data from 2015 to 2017. Participants 75 880 participants aged 18 and older—a nationally representative sample of the mainland Chinese population. Main outcome measures Prevalence of diabetes among adults living in China, and the prevalence by sex, regions, and ethnic groups, estimated by the 2018 American Diabetes Association (ADA) and the World Health Organization diagnostic criteria. Demographic characteristics, lifestyle, and history of disease were recorded by participants on a questionnaire. Anthropometric and clinical assessments were made of serum concentrations of fasting plasma glucose (one measurement), two hour plasma glucose, and glycated haemoglobin (HbA1c). Results The weighted prevalence of total diabetes (n=9772), self-reported diabetes (n=4464), newly diagnosed diabetes (n=5308), and prediabetes (n=27 230) diagnosed by the ADA criteria were 12.8% (95% confidence interval 12.0% to 13.6%), 6.0% (5.4% to 6.7%), 6.8% (6.1% to 7.4%), and 35.2% (33.5% to 37.0%), respectively, among adults living in China. The weighted prevalence of total diabetes was higher among adults aged 50 and older and among men. The prevalence of total diabetes in 31 provinces ranged from 6.2% in Guizhou to 19.9% in Inner Mongolia. Han ethnicity had the highest prevalence of diabetes (12.8%) and Hui ethnicity had the lowest (6.3%) among five investigated ethnicities. The weighted prevalence of total diabetes (n=8385) using the WHO criteria was 11.2% (95% confidence interval 10.5% to 11.9%). Conclusion The prevalence of diabetes has increased slightly from 2007 to 2017 among adults living in China. The findings indicate that diabetes is an important public health problem in China.
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            Global, regional, and national burden of diabetes from 1990 to 2021, with projections of prevalence to 2050: a systematic analysis for the Global Burden of Disease Study 2021

            Summary Background Diabetes is one of the leading causes of death and disability worldwide, and affects people regardless of country, age group, or sex. Using the most recent evidentiary and analytical framework from the Global Burden of Diseases, Injuries, and Risk Factors Study (GBD), we produced location-specific, age-specific, and sex-specific estimates of diabetes prevalence and burden from 1990 to 2021, the proportion of type 1 and type 2 diabetes in 2021, the proportion of the type 2 diabetes burden attributable to selected risk factors, and projections of diabetes prevalence through 2050. Methods Estimates of diabetes prevalence and burden were computed in 204 countries and territories, across 25 age groups, for males and females separately and combined; these estimates comprised lost years of healthy life, measured in disability-adjusted life-years (DALYs; defined as the sum of years of life lost [YLLs] and years lived with disability [YLDs]). We used the Cause of Death Ensemble model (CODEm) approach to estimate deaths due to diabetes, incorporating 25 666 location-years of data from vital registration and verbal autopsy reports in separate total (including both type 1 and type 2 diabetes) and type-specific models. Other forms of diabetes, including gestational and monogenic diabetes, were not explicitly modelled. Total and type 1 diabetes prevalence was estimated by use of a Bayesian meta-regression modelling tool, DisMod-MR 2.1, to analyse 1527 location-years of data from the scientific literature, survey microdata, and insurance claims; type 2 diabetes estimates were computed by subtracting type 1 diabetes from total estimates. Mortality and prevalence estimates, along with standard life expectancy and disability weights, were used to calculate YLLs, YLDs, and DALYs. When appropriate, we extrapolated estimates to a hypothetical population with a standardised age structure to allow comparison in populations with different age structures. We used the comparative risk assessment framework to estimate the risk-attributable type 2 diabetes burden for 16 risk factors falling under risk categories including environmental and occupational factors, tobacco use, high alcohol use, high body-mass index (BMI), dietary factors, and low physical activity. Using a regression framework, we forecast type 1 and type 2 diabetes prevalence through 2050 with Socio-demographic Index (SDI) and high BMI as predictors, respectively. Findings In 2021, there were 529 million (95% uncertainty interval [UI] 500–564) people living with diabetes worldwide, and the global age-standardised total diabetes prevalence was 6·1% (5·8–6·5). At the super-region level, the highest age-standardised rates were observed in north Africa and the Middle East (9·3% [8·7–9·9]) and, at the regional level, in Oceania (12·3% [11·5–13·0]). Nationally, Qatar had the world's highest age-specific prevalence of diabetes, at 76·1% (73·1–79·5) in individuals aged 75–79 years. Total diabetes prevalence—especially among older adults—primarily reflects type 2 diabetes, which in 2021 accounted for 96·0% (95·1–96·8) of diabetes cases and 95·4% (94·9–95·9) of diabetes DALYs worldwide. In 2021, 52·2% (25·5–71·8) of global type 2 diabetes DALYs were attributable to high BMI. The contribution of high BMI to type 2 diabetes DALYs rose by 24·3% (18·5–30·4) worldwide between 1990 and 2021. By 2050, more than 1·31 billion (1·22–1·39) people are projected to have diabetes, with expected age-standardised total diabetes prevalence rates greater than 10% in two super-regions: 16·8% (16·1–17·6) in north Africa and the Middle East and 11·3% (10·8–11·9) in Latin America and Caribbean. By 2050, 89 (43·6%) of 204 countries and territories will have an age-standardised rate greater than 10%. Interpretation Diabetes remains a substantial public health issue. Type 2 diabetes, which makes up the bulk of diabetes cases, is largely preventable and, in some cases, potentially reversible if identified and managed early in the disease course. However, all evidence indicates that diabetes prevalence is increasing worldwide, primarily due to a rise in obesity caused by multiple factors. Preventing and controlling type 2 diabetes remains an ongoing challenge. It is essential to better understand disparities in risk factor profiles and diabetes burden across populations, to inform strategies to successfully control diabetes risk factors within the context of multiple and complex drivers. Funding Bill & Melinda Gates Foundation.
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              Performance of the Cockcroft-Gault, MDRD, and new CKD-EPI formulas in relation to GFR, age, and body size.

              We compared the estimations of Cockcroft-Gault, Modification of Diet in Renal Disease (MDRD), and Chronic Kidney Disease Epidemiology Collaboration (CKD-EPI) equations to a gold standard GFR measurement using (125)I-iothalamate, within strata of GFR, gender, age, body weight, and body mass index (BMI). For people who previously underwent a GFR measurement, bias, precision, and accuracies between measured and estimated kidney functions were calculated within strata of the variables. The relation between the absolute bias and the variables was tested with linear regression analysis. Overall (n = 271, 44% male, mean measured GFR 72.6 ml/min per 1.73 m(2) [SD 30.4 ml/min per 1.73 m(2)]), mean bias was smallest for MDRD (P < 0.01). CKD-EPI had highest accuracy (P < 0.01 compared with Cockcroft-Gault), which did not differ from MDRD (P = 0.14). The absolute bias of all formulas was related to age. For MDRD and CKD-EPI, absolute bias was also related to the GFR; for Cockcroft-Gault, it was related to body weight and BMI as well. In all extreme subgroups, MDRD and CKD-EPI provided highest accuracies. The absolute bias of all formulas is influenced by age; CKD-EPI and MDRD are also influenced by GFR. Cockcroft-Gault is additionally influenced by body weight and BMI. In general, CKD-EPI gives the best estimation of GFR, although its accuracy is close to that of the MDRD.
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                Author and article information

                Journal
                Ann Med
                Ann Med
                Annals of Medicine
                Taylor & Francis
                0785-3890
                1365-2060
                21 February 2024
                2024
                21 February 2024
                : 56
                : 1
                : 2318418
                Affiliations
                [a ]Department of Endocrinology and Metabolism, Shunde Hospital, Southern Medical University (The First People’s Hospital of Shunde, Foshan) , Foshan, Guangdong, China
                [b ]School of Nursing, Southern Medical University , Guangzhou, Guangdong, China
                Author notes

                Heng Wan, Genfeng Yu and Yajun He contributed equally to this work.

                CONTACT Jie Shen sjiesy@ 123456smu.edu.cn
                Lan Liu liulan7@ 123456mail.sysu.edu.cn Department of Endocrinology and Metabolism, Shunde Hospital, Southern Medical University (The First People’s Hospital of Shunde, Foshan) , No.1 of Jiazi Road, Lunjiao, Shunde District, Foshan 528308, Guangdong, China
                Author information
                https://orcid.org/0000-0001-7993-4188
                https://orcid.org/0000-0001-6952-9541
                Article
                2318418
                10.1080/07853890.2024.2318418
                10883085
                38382636
                07551134-b476-4696-8198-9d5ca7a58e1b
                © 2024 The Author(s). Published by Informa UK Limited, trading as Taylor & Francis Group

                This is an Open Access article distributed under the terms of the Creative Commons Attribution License ( http://creativecommons.org/licenses/by/4.0/), which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited. The terms on which this article has been published allow the posting of the Accepted Manuscript in a repository by the author(s) or with their consent.

                History
                Page count
                Figures: 4, Tables: 2, Pages: 11, Words: 6266
                Categories
                Research Article
                Public Health

                Medicine
                impaired sensitivity to thyroid hormones,diabetes,tfqi
                Medicine
                impaired sensitivity to thyroid hormones, diabetes, tfqi

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