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Prevalence and the Association of Body Mass Index and Other Risk Factors with Prediabetes and Type 2 Diabetes Among 50,867 Adults in China and Sweden: A Cross-Sectional Study

INTRODUCTION: Understanding socioeconomic differences for prediabetes and type 2 diabetes (T2DM) can offer guidance for the most effective development of both prevention and intervention programmes in different settings. This study aims to determine the prevalence and risk factors for prediabetes an...

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Autores principales: Zhang, Yue, Santosa, Ailiana, Wang, Na, Wang, Weibing, Ng, Nawi, Zhao, Qi, Jiang, Yonggen, Weinehall, Lars, Zhao, Genming
Formato: Online Artículo Texto
Lenguaje:English
Publicado: Springer Healthcare 2019
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC6848580/
https://www.ncbi.nlm.nih.gov/pubmed/31512070
http://dx.doi.org/10.1007/s13300-019-00690-3
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author Zhang, Yue
Santosa, Ailiana
Wang, Na
Wang, Weibing
Ng, Nawi
Zhao, Qi
Jiang, Yonggen
Weinehall, Lars
Zhao, Genming
author_facet Zhang, Yue
Santosa, Ailiana
Wang, Na
Wang, Weibing
Ng, Nawi
Zhao, Qi
Jiang, Yonggen
Weinehall, Lars
Zhao, Genming
author_sort Zhang, Yue
collection PubMed
description INTRODUCTION: Understanding socioeconomic differences for prediabetes and type 2 diabetes (T2DM) can offer guidance for the most effective development of both prevention and intervention programmes in different settings. This study aims to determine the prevalence and risk factors for prediabetes and T2DM and to explore the effect of high body mass index (BMI) on the probability of T2DM being present among adults in China and Sweden. METHODS: This study enrolled 25,356 adults (35–64 years old) from the Shanghai Survey in China and 25,511 adults (aged 40, 50, 60) from the Västerbotten Intervention Programme in Sweden. Data on haemoglobin A1c, capillary fasting plasma glucose, 2-h plasma glucose and self-reported diagnoses of T2DM were used in the analysis. Multinomial logistic regression was used to examine the determinants of prediabetes and T2DM. The average predicted probabilities of T2DM developing or presenting were determined for the different ages and levels of BMI in each population. RESULTS: Chinese participants had a higher adjusted prevalence of T2DM (men 12.8% vs. 4.6%; women 10.6% vs. 3.1%) and prediabetes (men 12.4% vs. 12.2%; women 14.4% vs. 12.2%) than Swedish participants. Age, overweightedness/obesity, hypertension and a family history of diabetes were significant risk factors for prediabetes and T2DM. In both populations, the predicted probability of T2DM increased as the BMI increased in all age groups. At the same BMI level, Chinese participants were more likely to have T2DM compared to their Swedish counterparts. The average predicted probability of T2DM was less than 20% in nearly all age groups among Swedish women. CONCLUSIONS: Chinese adults had the higher prevalence of prediabetes and T2DM and a higher probability of T2DM at the same BMI level compared with Swedish adults. These results indicate the importance of addressing the ongoing obesity epidemic as a matter of urgency in order to curb what has become an apparent diabetes epidemic in both countries. ELECTRONIC SUPPLEMENTARY MATERIAL: The online version of this article (10.1007/s13300-019-00690-3) contains supplementary material, which is available to authorized users.
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spelling pubmed-68485802019-11-22 Prevalence and the Association of Body Mass Index and Other Risk Factors with Prediabetes and Type 2 Diabetes Among 50,867 Adults in China and Sweden: A Cross-Sectional Study Zhang, Yue Santosa, Ailiana Wang, Na Wang, Weibing Ng, Nawi Zhao, Qi Jiang, Yonggen Weinehall, Lars Zhao, Genming Diabetes Ther Original Research INTRODUCTION: Understanding socioeconomic differences for prediabetes and type 2 diabetes (T2DM) can offer guidance for the most effective development of both prevention and intervention programmes in different settings. This study aims to determine the prevalence and risk factors for prediabetes and T2DM and to explore the effect of high body mass index (BMI) on the probability of T2DM being present among adults in China and Sweden. METHODS: This study enrolled 25,356 adults (35–64 years old) from the Shanghai Survey in China and 25,511 adults (aged 40, 50, 60) from the Västerbotten Intervention Programme in Sweden. Data on haemoglobin A1c, capillary fasting plasma glucose, 2-h plasma glucose and self-reported diagnoses of T2DM were used in the analysis. Multinomial logistic regression was used to examine the determinants of prediabetes and T2DM. The average predicted probabilities of T2DM developing or presenting were determined for the different ages and levels of BMI in each population. RESULTS: Chinese participants had a higher adjusted prevalence of T2DM (men 12.8% vs. 4.6%; women 10.6% vs. 3.1%) and prediabetes (men 12.4% vs. 12.2%; women 14.4% vs. 12.2%) than Swedish participants. Age, overweightedness/obesity, hypertension and a family history of diabetes were significant risk factors for prediabetes and T2DM. In both populations, the predicted probability of T2DM increased as the BMI increased in all age groups. At the same BMI level, Chinese participants were more likely to have T2DM compared to their Swedish counterparts. The average predicted probability of T2DM was less than 20% in nearly all age groups among Swedish women. CONCLUSIONS: Chinese adults had the higher prevalence of prediabetes and T2DM and a higher probability of T2DM at the same BMI level compared with Swedish adults. These results indicate the importance of addressing the ongoing obesity epidemic as a matter of urgency in order to curb what has become an apparent diabetes epidemic in both countries. ELECTRONIC SUPPLEMENTARY MATERIAL: The online version of this article (10.1007/s13300-019-00690-3) contains supplementary material, which is available to authorized users. Springer Healthcare 2019-09-11 2019-12 /pmc/articles/PMC6848580/ /pubmed/31512070 http://dx.doi.org/10.1007/s13300-019-00690-3 Text en © The Author(s) 2019 https://creativecommons.org/licenses/by-nc/4.0/This article is distributed under the terms of the Creative Commons Attribution-NonCommercial 4.0 International License (http://creativecommons.org/licenses/by-nc/4.0/ (https://creativecommons.org/licenses/by-nc/4.0/) ), which permits any noncommercial use, distribution, and reproduction in any medium, provided you give appropriate credit to the original author(s) and the source, provide a link to the Creative Commons license, and indicate if changes were made.
spellingShingle Original Research
Zhang, Yue
Santosa, Ailiana
Wang, Na
Wang, Weibing
Ng, Nawi
Zhao, Qi
Jiang, Yonggen
Weinehall, Lars
Zhao, Genming
Prevalence and the Association of Body Mass Index and Other Risk Factors with Prediabetes and Type 2 Diabetes Among 50,867 Adults in China and Sweden: A Cross-Sectional Study
title Prevalence and the Association of Body Mass Index and Other Risk Factors with Prediabetes and Type 2 Diabetes Among 50,867 Adults in China and Sweden: A Cross-Sectional Study
title_full Prevalence and the Association of Body Mass Index and Other Risk Factors with Prediabetes and Type 2 Diabetes Among 50,867 Adults in China and Sweden: A Cross-Sectional Study
title_fullStr Prevalence and the Association of Body Mass Index and Other Risk Factors with Prediabetes and Type 2 Diabetes Among 50,867 Adults in China and Sweden: A Cross-Sectional Study
title_full_unstemmed Prevalence and the Association of Body Mass Index and Other Risk Factors with Prediabetes and Type 2 Diabetes Among 50,867 Adults in China and Sweden: A Cross-Sectional Study
title_short Prevalence and the Association of Body Mass Index and Other Risk Factors with Prediabetes and Type 2 Diabetes Among 50,867 Adults in China and Sweden: A Cross-Sectional Study
title_sort prevalence and the association of body mass index and other risk factors with prediabetes and type 2 diabetes among 50,867 adults in china and sweden: a cross-sectional study
topic Original Research
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC6848580/
https://www.ncbi.nlm.nih.gov/pubmed/31512070
http://dx.doi.org/10.1007/s13300-019-00690-3
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