Diabetes, Metabolic Syndrome and Obesity (May 2023)
The Correlation Between Health Risk Factors and Diabesity and Lipid Profile Indicators: The Role Mediator of TSH
Abstract
Yi Zhang,1,2 Yulin Zhang,3,* Li Zhu,4,* Zixiang Yu,5 Fangting Lu,1 Zhen Wang,1 Qiu Zhang1 1Department of Endocrinology, The First Affiliated Hospital of Anhui Medical University, Hefei, Anhui Province, People’s Republic of China; 2Department of Maternal, Child and Adolescent Health, School of Public Health, Anhui Medical University, Hefei, Anhui Province, People’s Republic of China; 3The Second Clinical Medical College, Anhui Medical University, Hefei, Anhui Province, People’s Republic of China; 4Department of Endocrinology, Chaohu Hospital of Anhui Medical University, Hefei, Anhui Province, People’s Republic of China; 5The First Clinical Medical College, Anhui Medical University, Hefei, Anhui Province, People’s Republic of China*These authors contributed equally to this workCorrespondence: Qiu Zhang, Department of Endocrinology, the First Affiliated Hospital of Anhui Medical University, Hefei, 230022, People’s Republic of China, Email [email protected]: Obesity in adults is a problem, particularly when paired with other metabolic abnormalities. Previous research have linked various screening approaches to diabetes, but additional evidence points to the relevance of combining diabetes screening methods with obesity and its effects. This research examined the impact of thyroid hormones (TSHs) and health risk factors (HRFs) in screening for obesity and diabetes in Chinese populations, and whether age can modulate this association.Methods: From March to July 2022, the Hefei Community Health Service Center connected with the First Affiliated Hospital of Anhui Medical University was chosen, and the multi-stage cluster sample approach was utilized to test adults aged 21– 90 in each community. Latent category analysis (LCA) was performed to investigate the clustering patterns of HRFs. A one-way ANOVA was used to examine waist circumference (WC), biochemical markers, and general data. Furthermore, multivariate logistic regression analysis was utilized to investigate the relationship between health risk variables and WC.Results: A total of 750 individuals without a history of major problems who had a community health physical examination were chosen, with missing data greater than 5% excluded. Finally, 708 samples were included in the study with an effective rate of 94.4%. The average WC was (90.0± 10.33) cm, the prevalence in the >P75, P50~P75, P25~P50, and ≤P25 groups were 24.7%, 18.9%, 28.7% and 27.7%, respectively. The average TSH was (2.76± 2.0) μIU/mL. Male (β=1.91), HOMA-IR (β=0.06), TyG (β=2.41), SBP (β=0.08), TG (β=0.94) and UA (β=0.03) were more likely to have a higher prevalence of WC level. The analyses revealed significant correlations between HRFs, TSH, age, other metabolic indexes and WC (P < 0.05).Discussion: Our findings suggest that the quality of metabolic-related indicators used to successfully decrease diabetes in Chinese individuals with high HRFs levels should be prioritized. Comprehensive indicators might be a useful and practical way for measuring the metabolic evolution of diabetes level levels.Keywords: health risk factors, diabetes mellitus, metabolic indicators, TSH, WC, diabesity
