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      Sex-specific differences in the effect of the atherogenic index of plasma on prediabetes and diabetes in the NHANES 2011–2018 population

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      1 , 2 , , 1 ,
      Cardiovascular Diabetology
      BioMed Central
      Atherogenic index of plasma, Prediabetes, Diabetes, Sex differences, Females

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          Abstract

          Background

          Although a great deal of scientific evidence on the epidemiological risk factors for diabetes and prediabetes has been accumulated, there is still insufficient evidence to explore sex-related differences. The aim of this study was to examine sex-specific differences in the effect of the atherogenic index of plasma (AIP) on prediabetes and diabetes.

          Methods

          This cross-sectional study included data from 10099 American adults. The exposure variable was the AIP, which was defined as log10 (triglycerides/high-density lipoprotein cholesterol). The outcome variables included prediabetes and diabetes defined by the 2013 American Diabetes Association guidelines.

          Results

          The median age (mean ± SD) was 48.51 ± 18.42 years, and the average value (SD) of the AIP was − 0.09 (0.34). The prevalence of prediabetes was 40.24%, and that of diabetes was 21.32%. Overall, there was a significant positive association between the AIP and prediabetes and diabetes (per 1-unit increment in the AIP: OR, 2.49; 95% CI 1.75, 3.54). The multivariate logistic regression model demonstrated that for each unit increment in the AIP, the prediabetes and diabetes prevalence increased 4.96-fold among female participants (OR 4.96, 95% CI 2.68, 9.18) but not among male participants. We found that the AIP was not related to the prevalence of prediabetes or diabetes (OR 1.41; 95% CI 0.87, 2.29) among males. There was an interaction between sex and the AIP (P for interaction < 0.0001).

          Conclusions

          This study showed that a higher AIP was significantly associated with an increased prevalence of prediabetes and diabetes, and the above relationships occurred only among women and not men.

          Supplementary Information

          The online version contains supplementary material available at 10.1186/s12933-023-01740-8.

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          Most cited references33

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          A new equation to estimate glomerular filtration rate.

          Equations to estimate glomerular filtration rate (GFR) are routinely used to assess kidney function. Current equations have limited precision and systematically underestimate measured GFR at higher values. To develop a new estimating equation for GFR: the Chronic Kidney Disease Epidemiology Collaboration (CKD-EPI) equation. Cross-sectional analysis with separate pooled data sets for equation development and validation and a representative sample of the U.S. population for prevalence estimates. Research studies and clinical populations ("studies") with measured GFR and NHANES (National Health and Nutrition Examination Survey), 1999 to 2006. 8254 participants in 10 studies (equation development data set) and 3896 participants in 16 studies (validation data set). Prevalence estimates were based on 16,032 participants in NHANES. GFR, measured as the clearance of exogenous filtration markers (iothalamate in the development data set; iothalamate and other markers in the validation data set), and linear regression to estimate the logarithm of measured GFR from standardized creatinine levels, sex, race, and age. In the validation data set, the CKD-EPI equation performed better than the Modification of Diet in Renal Disease Study equation, especially at higher GFR (P < 0.001 for all subsequent comparisons), with less bias (median difference between measured and estimated GFR, 2.5 vs. 5.5 mL/min per 1.73 m(2)), improved precision (interquartile range [IQR] of the differences, 16.6 vs. 18.3 mL/min per 1.73 m(2)), and greater accuracy (percentage of estimated GFR within 30% of measured GFR, 84.1% vs. 80.6%). In NHANES, the median estimated GFR was 94.5 mL/min per 1.73 m(2) (IQR, 79.7 to 108.1) vs. 85.0 (IQR, 72.9 to 98.5) mL/min per 1.73 m(2), and the prevalence of chronic kidney disease was 11.5% (95% CI, 10.6% to 12.4%) versus 13.1% (CI, 12.1% to 14.0%). The sample contained a limited number of elderly people and racial and ethnic minorities with measured GFR. The CKD-EPI creatinine equation is more accurate than the Modification of Diet in Renal Disease Study equation and could replace it for routine clinical use. National Institute of Diabetes and Digestive and Kidney Diseases.
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            WITHDRAWN: Global and regional diabetes prevalence estimates for 2019 and projections for 2030 and 2045: results from the International Diabetes Federation Diabetes Atlas, 9th edition

            To provide global estimates of diabetes prevalence for 2019 and projections for 2030 and 2045.
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              Prediabetes: a high-risk state for diabetes development

              Prediabetes (intermediate hyperglycaemia) is a high-risk state for diabetes that is defined by glycaemic variables that are higher than normal, but lower than diabetes thresholds. 5-10% of people per year with prediabetes will progress to diabetes, with the same proportion converting back to normoglycaemia. Prevalence of prediabetes is increasing worldwide and experts have projected that more than 470 million people will have prediabetes by 2030. Prediabetes is associated with the simultaneous presence of insulin resistance and β-cell dysfunction-abnormalities that start before glucose changes are detectable. Observational evidence shows associations between prediabetes and early forms of nephropathy, chronic kidney disease, small fibre neuropathy, diabetic retinopathy, and increased risk of macrovascular disease. Multifactorial risk scores using non-invasive measures and blood-based metabolic traits, in addition to glycaemic values, could optimise estimation of diabetes risk. For prediabetic individuals, lifestyle modification is the cornerstone of diabetes prevention, with evidence of a 40-70% relative-risk reduction. Accumulating data also show potential benefits from pharmacotherapy. Copyright © 2012 Elsevier Ltd. All rights reserved.
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                Author and article information

                Contributors
                shiyumeng666@126.com
                wmh618@126.com
                Journal
                Cardiovasc Diabetol
                Cardiovasc Diabetol
                Cardiovascular Diabetology
                BioMed Central (London )
                1475-2840
                30 January 2023
                30 January 2023
                2023
                : 22
                : 19
                Affiliations
                [1 ]GRID grid.412455.3, ISNI 0000 0004 1756 5980, Department of Cardiovascular Medicine, , The Second Affiliated Hospital of Nanchang University, ; No. 1 Minde Road, Nanchang, 330006 Jiangxi China
                [2 ]Jiangxi Provincial Cardiovascular Disease Clinical Medical Research Center, Nanchang, Jiangxi China
                Article
                1740
                10.1186/s12933-023-01740-8
                9887826
                36717829
                19a82f6d-11cb-4098-beb3-c54b8c64dd02
                © The Author(s) 2023

                Open AccessThis article is licensed under a Creative Commons Attribution 4.0 International License, which permits use, sharing, adaptation, distribution and reproduction in any medium or format, as long as you give appropriate credit to the original author(s) and the source, provide a link to the Creative Commons licence, and indicate if changes were made. The images or other third party material in this article are included in the article's Creative Commons licence, unless indicated otherwise in a credit line to the material. If material is not included in the article's Creative Commons licence and your intended use is not permitted by statutory regulation or exceeds the permitted use, you will need to obtain permission directly from the copyright holder. To view a copy of this licence, visit http://creativecommons.org/licenses/by/4.0/. The Creative Commons Public Domain Dedication waiver ( http://creativecommons.org/publicdomain/zero/1.0/) applies to the data made available in this article, unless otherwise stated in a credit line to the data.

                History
                : 1 December 2022
                : 10 January 2023
                Funding
                Funded by: National Natural Science Foundation of China, Regional Science Foundation
                Award ID: 82060063
                Award Recipient :
                Funded by: Jiangxi Youth Science Foundation
                Award ID: 20202BABL216004
                Award Recipient :
                Categories
                Research
                Custom metadata
                © The Author(s) 2023

                Endocrinology & Diabetes
                atherogenic index of plasma,prediabetes,diabetes,sex differences,females
                Endocrinology & Diabetes
                atherogenic index of plasma, prediabetes, diabetes, sex differences, females

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