Dataset Information

Type 2 diabetes mellitus and neighborhood deprivation index: A spatial analysis in Zhejiang, China.

ABSTRACT:

Aims/introduction

Many studies have reported that socioeconomically disadvantaged people or people who live in deprived areas are more vulnerable to diabetes complications. However, few such studies were carried out in China. The present study examined the spatial association between the incidence of type 2 diabetes mellitus and neighborhood deprivation in Zhejiang, China, from a spatial epidemiology perspective.

Materials and methods

Type 2 diabetes mellitus data (2012-2016) in the present study were derived from a population-based diabetes registry system maintained by Zhejiang Provincial Center for Disease Control and Prevention. Principal components analysis was used to combine different socioeconomic variables together into a composited Neighborhood Deprivation Index. We applied the global Moran's I and Anselin's local Moran's I statistics to explore the spatial patterns of type 2 diabetes mellitus incidence and Neighborhood Deprivation Index.

Results

Type 2 diabetes mellitus incidence (Moran's I: 0.531, P < 0.001) and Neighborhood Deprivation Index (Moran's I: 0.772, P < 0.001) showed positive statistically significant global Moran's I index values, showing a tendency towards clustering. The local Moran's I analyses showed that type 2 diabetes mellitus incidence hot spots were mainly located in urban centers, and type 2 diabetes mellitus incidence cold spots appeared in the provincial capital area (Hangzhou city) and western and south-western regions of Zhejiang; the hot spots of the less deprived areas were concentrated in urban centers (except Lishui city), and the cold spots of the most deprived areas were clustered in western and south-western regions of Zhejiang.

Conclusions

The study showed that the incidence of type 2 diabetes mellitus was higher in affluent areas than the deprived areas across the study period. It will be significant to focus preventive efforts on the least deprived areas.

SUBMITTER: Zhang X

PROVIDER: S-EPMC6400165 | biostudies-literature | 2019 Mar

REPOSITORIES: biostudies-literature

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Publications

Type 2 diabetes mellitus and neighborhood deprivation index: A spatial analysis in Zhejiang, China.

Zhang Xin X Chen Xiaoxiao X Gong Weiwei W

Journal of diabetes investigation 20180828 2

<h4>Aims/introduction</h4>Many studies have reported that socioeconomically disadvantaged people or people who live in deprived areas are more vulnerable to diabetes complications. However, few such studies were carried out in China. The present study examined the spatial association between the incidence of type 2 diabetes mellitus and neighborhood deprivation in Zhejiang, China, from a spatial epidemiology perspective.<h4>Materials and methods</h4>Type 2 diabetes mellitus data (2012-2016) in t ...[more]

PMID: 30040249

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Project description:BackgroundAlthough exercise seems to be beneficial for type 2 diabetes mellitus (T2DM) patients, there is limited research elucidating the optimal accessible indices of adiposity and insulin resistance for identifying elderly T2DM patients with poor glycemic control, which could be improved by performing regular exercise.MethodsA community-based, cross-sectional study was conducted with 918 Chinese elderly individuals with T2DM in Zhejiang. Relevant risk factors for poor glycemic control, as determined using glycated haemoglobin A1c (HbA1c) > 7%, were explored using logistic regression analyses and included body mass index (BMI), waist circumference (WC), waist to height ratio (WHtR), fasting blood glucose (FBG), triglycerides (TGs), total cholesterol (TC), the product of fasting triglycerides and glucose (TyG), visceral adiposity index (VAI), lipid accumulation product (LAP), TyG-BMI, and TyG-WC. Comparisons of the risk factors' ability to discriminate poor glycemic control as well as their optimal cutoff values were determined using receiver operating characteristic (ROC) analyses, and then the extent of poor glycemic control risk reduction through regular exercise was examined using multivariate logistic regression analyses.ResultsThe overall poor glycemic control rate was 49.3%. The factors associated with poor glycemic control included FBG > 3.869, TyG > 8.73, TyG-BMI > 222.45, and TyG-WC > 713.48 in logistic regression analyses. The optimal cutoff points of FBG, TyG, TyG-WC, and TyG-BMI in discriminating poor glycemic control were 7.38, 9.22, 813.33, and 227.77, and their corresponding areas under the ROC curves were 0.864(0.840-0.886), 0.684(0.653-0.714), 0.604(0.571-0.635), and 0.574(0.541-0.606), respectively. Occasional and regular exercise reduced the odds ratios (95% confidence interval) of poor glycemic control to 0.187 (0.063-0.557) and 0.183 (0.059-0.571) for subjects with TyG-WC > 813.33 (p = 0.008), to 0.349 (0.156-0.782) and 0.284 (0.123-0.652) for subjects with TyG > 9.22 (p = 0.011), and to 0.390 (0.175-0.869) and 0.300(0.130-0.688) for subjects with TyG-BMI > 227.77 (p = 0.017), respectively, after adjusting for multiple confounding factors.ConclusionAmong elderly individuals with T2DM, poor glycemic control risk might be identified using indices calculated from FBG, TG, BMI, and WC measurements, which are indicative of adiposity and insulin resistance. TyG-WC seems to be an accessible and useful indicator to identify which elderly T2DM patients would benefit from performing regular exercise to achieve good glycemic control.

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Dataset Information

Type 2 diabetes mellitus and neighborhood deprivation index: A spatial analysis in Zhejiang, China.

Aims/introduction

Materials and methods

Results

Conclusions

Publications

Type 2 diabetes mellitus and neighborhood deprivation index: A spatial analysis in Zhejiang, China.

Similar Datasets

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