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Background@#The role of uric acid in the development of diabetic peripheral neuropathy remains unclear. This study aimed to determine the association between uric acid and peripheral neuropathy among type 2 diabetes mellitus (T2DM) patients. @*Methods@#We conducted a nationwide cross-sectional study based on the diabetes and hypertension study of the Medical Research Network of the Consortium of Thai Medical Schools. Adult T2DM patients from 831 public hospitals in Thailand were evaluated. The serum uric acid level was categorized into five groups based on quintiles (7.3 mg/dL). A multivariate logistic regression model was used to assess the independent association between serum uric acid level and peripheral neuropathy. @*Results@#In total, 7,511 T2DM patients with available data about serum uric acid levels were included in the analysis. The mean age of the participants was 61.7±10.9 years, and approximately 35.6% were men. The prevalence rate of peripheral neuropathy was 3.0%. Moreover, the prevalence rates of peripheral neuropathy stratified according to uric acid levels 7.3 mg/dL were 2.5%, 2.8%, 2.4%, 2.5%, and 4.7%, respectively. A serum uric acid level ≥7.3 mg/dL was found to be associated with an increase in odds ratio (1.54; 95% confidence interval, 1.02–2.32) for peripheral neuropathy compared with a serum uric acid level <4.4 mg/dL. @*Conclusion@#Serum uric acid level is independently associated with peripheral neuropathy in T2DM patients, and elevated serum uric acid levels should be considered a risk factor for diabetic peripheral neuropathy in clinical practice.
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PURPOSE: Information about overweight and obesity among students in rural areas of Thailand is limited. Therefore, we aimed to determine overweight and obesity prevalences and associated factors among school-aged children in a rural community of Thailand. METHODS: We selected 9 public schools through cluster sampling in 2 provinces located in central Thailand in 2016. Anthropometric measurements were measured using standard techniques, classified as overweight (>1 standard deviation [SD]) and obese (>2 SD) with respect to their age and sex using 2007 World Health Organization reference charts. Standardized questionnaires on risk factors were sent to parents to be completed together with their child. RESULTS: Among 1,749 students, 8.98% had overweight and 7.26% had obesity. Mean age (range) was 11.5 years (5–18 years). Independent factors associated with overweight and obesity included primary school student (reference as secondary school) (adjusted odds ratio [aOR], 2.25; 95% confidence interval [CI], 1.24–4.08; P=0.07), mother's body mass index (aOR, 1.07; 95% CI, 1.02–1.12; P=0.001), self-employed father (aOR, 1.99; 95% CI, 1.12–3.55; P=0.018), number of siblings (aOR, 0.61; 95% CI, 0.47–0.81; P=0.001), having sibling(s) with obesity (aOR, 1.82; 95% CI, 1.20–2.77; P=0.005), more than one (aOR, 7.16; 95% CI, 2.40–21.32; P3 ladles of rice/meal (aOR, 2.69; 95% CI, 1.11–6.46; P=0.27), watching 2 hours of television/day (aOR, 2.60; 95% CI, 1.36–4.96; P=0.004). CONCLUSION: Many sociodemographic, dietary, and behavioral factors were related to overweight and obesity among school-aged children not only in urban but also rural communities of Thailand.