Associations of triglyceride-glucose index with hyperuricemia among Royal Thai Army personnel.

BACKGROUND: Hyperuricemia has placed an immense burden on the global healthcare system. Studies have discovered a close correlation between serum uric acid (SUA) and insulin resistance (IR). The objective of this investigation is to examine the association between the triglyceride-glucose (TyG) index, a simple surrogate for IR, and the presence of hyperuricemia. METHODS: Between 2017 and 2021, an epidemiologic study was conducted on Royal Thai Army (RTA) personnel aged 35-60 years, involving a total of 231,286 participants. In the study, hyperuricemia was defined as a SUA level of 7 mg/dL and 6 mg/dL among male and female participants, respectively. Using linear regression analysis and logistic regression analysis, the association between the TyG index and SUA was determined. RESULTS: A positive relationship was demonstrated between the TyG index and the SUA. Overall, SUA increased by 0.32 per unit of TyG index growth (95% CI: 0.31-0.32). In comparison with the first quartile, employees in the fourth TyG quartile had a greater likelihood of having hyperuricemia [adjusted odds ratio (AOR): 2.45, 95% CI: 2.38-2.52]. Effect modification by obesity on the association between the TyG index and SUA was observed (P-interaction < 0.001). Among individuals with obesity, compared with the first TyG index quartile, the AOR for hyperuricemia was 2.15 (95% CI: 2.06-2.25) and 2.14 (95% CI: 1.81-2.53) for the fourth quartile of the TyG index for males and females, respectively. However, for nonobese personnel, in comparison to the top quartile of the TyG index, the AOR for hyperuricemia was 2.73 (95% CI:2.61-2.84) and 5.03 (95% CI: 4.03-6.29) for the fourth quartile of the TyG index for males and females, respectively. Personnel in the fourth TyG index quartile revealed that the prevalence of hyperuricemia reached 44.2%. CONCLUSION: A robust positive association between the TyG index and SUA was illustrated among active-duty RTA personnel. Obesity was identified as a modifier influencing this relationship. Furthermore, individuals in the fourth quarter of the TyG index, regardless of their obesity status, could be considered appropriate candidates for screening SUA levels.

Relationship between pulse pressure and body mass index in active-duty Royal Thai Army personnel in Thailand.

BACKGROUND: Elevated pulse pressure (PP) is a robust independent predictor of cardiovascular diseases. The relationship between PP and body mass index (BMI) was presented in a few studies. However, the findings were inconsistent. Therefore, the aim of the present study is to identify the association between elevated PP and BMI using a large sample of active-duty Royal Thai Army (RTA) personnel. METHODS: A cross-sectional study was conducted through the use of the dataset obtained from the annual health examination database of RTA personnel in Thailand in 2022. BMI 25.0-29.9 kg/m2 was classified as obesity I, whereas BMI ≥ 30.0 kg/m2 was classified as obesity II. Elevated PP was defined as PP ≥ 50 mmHg. Multivariable linear regression and log-binomial regression models were utilized for determining the association between elevated PP and BMI. RESULTS: A total of 62,113 active-duty RTA personnel were included in the study. The average BMI was 25.4 ± 3.8 kg/m2, while the average PP was 50.1 ± 11.2 mmHg. Compared to individuals with normal weight, the [Formula: see text] coefficients of PP and BMI were 1.38 (95% CI: 1.15-1.60) and 2.57 (95% CI: 2.25-2.88) in individuals with obesity I and obesity II, respectively. Effect modification by high blood pressure (BP) on the association between elevated PP and BMI was observed. Among participants with normal BP, in comparison with BMI of 18.5-22.9 kg/m2, the adjusted prevalence ratio (PR) for elevated PP was 1.23 (95% CI: 1.19-1.28) and 1.41 (95% CI: 1.35-1.48) in those with obesity I and obesity II, respectively. Meanwhile, among individuals with high BP, the adjusted PR for elevated PP was 1.05 (95% CI: 1.01-1.08) and 1.09 (95% CI: 1.06-1.13) in those with obesity I and obesity II, respectively. CONCLUSION: PP was positively associated with BMI in active-duty RTA personnel. High BP was the modifier of the association between PP and BMI. A weaker association between elevated PP and BMI was observed among RTA personnel with high BP.

Trends, prevalence and associated factors of obesity among adults in a rural community in Thailand: serial cross-sectional surveys, 2012 and 2018.

BACKGROUND: Obesity is one principle risk factor increasing the risk of noncommunicable diseases including diabetes, hypertension and atherosclerosis. In Thailand, a 2014 study reported obesity (BMI ≥25 kg/m2) in a Thai population aged ≥15 years was 37.5, 32.9 and 41.8% overall and among males and females, respectively. The study aimed to determine trends in the prevalence of obesity among adults residing in a Thai rural community between 2012 and 2018 and investigate the associations between obesity and behavioral factors. METHODS: Serial cross-sectional studies were conducted in 2012 and 2018 among adults in Na-Ngam rural community. In 2012 and 2018, all 635 and 627 individuals, respectively, were interviewed using structured questionnaires related to demographics, risk behaviors, comorbidities and arthrometric measurement. Spot urine was collected by participants and obesity was defined as BMI ≥25 kg/m2. The risk factors for obesity were analyzed in the 2018 survey. RESULTS: A total of 1262 adults in Na-Ngam rural community were included in the study. The prevalence of obesity was 33.9% in 2012 and 44.8% in 2018 (P < 0.001). The average BMI increased from 23.9 ± 4.2 kg/m2 in 2012 to 25.0 ± 4.52 kg/m2 in 2018 (P < 0.001). Obesity was associated with higher age (AOR 0.99; 95%CI 0.97-0.99), smoking (AOR 0.52; 95%CI 0.28-0.94), instant coffee-mix consumption > 1 cup/week (AOR 1.44; 95%CI 1.02-2.04), higher number of chronic diseases (≥1 disease AOR 1.82; 95%CI 1.01-2.68, > 2 diseases AOR 2.15; 95%CI 1.32-3.50), and higher spot urine sodium level (AOR 1.002; 95%CI 0.99-1.01). CONCLUSION: Our data emphasized that obesity constituted a serious problem among adults residing in a rural community. A trend in significant increase was found regarding the prevalence of obesity and average BMI in the rural community over 6 years. Effective public health interventions should be provided at the community level to reduce BMI. Moreover, modifiable risk factors for obesity should be attenuated to inhibit the progression of metabolic syndrome, noncommunicable diseases and their complications.