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Cardio-metabolic traits and its socioeconomic differentials among school children including metabolically obese normal weight phenotypes in India: A post-COVID baseline characteristics of LEAP-C cohort.
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- المؤلفون: Kalaivani, Mani1 (AUTHOR) ; Hemraj, Chitralok1 (AUTHOR); Varhlunchhungi, Varhlunchhungi1 (AUTHOR); Ramakrishnan, Lakshmy2 (AUTHOR); Malhotra, Sumit3 (AUTHOR); Gupta, Sanjeev Kumar3 (AUTHOR); Marwaha, Raman Kumar4 (AUTHOR); Abraham, Ransi Ann2 (AUTHOR); Arora, Monika5 (AUTHOR); Rawal, Tina5 (AUTHOR); Khan, Maroof Ahmad1 (AUTHOR); Sinha, Aditi6 (AUTHOR); Tandon, Nikhil7 (AUTHOR)
- المصدر:
PLoS ONE. 5/6/2025, Vol. 20 Issue 5, p1-26. 26p.
- الموضوع:
- معلومة اضافية
- نبذة مختصرة :
Background: Cardio-metabolic risks emerge in early life and progress further in adult life. In recent times, COVID-19 pandemic aggravated risks owing to poor food security and diet quality. We aimed to assess the prevalence of cardiometabolic traits including the metabolically obese normal weight phenotype and its socioeconomic differentials in children and adolescents aged 6–19 years in India. Methods: A baseline assessment was conducted between August and December, 2022, as part of a school-based cohort study that aimed at longitudinally evaluating the anthropometric and metabolic parameters among urban children and adolescents aged 6–19 years from three public (non-fee paying) and two private (fee paying) schools in India. Private and public schools were considered as a proxy for higher and lower socioeconomic status respectively. Blood pressure and blood samples in a fasting state were obtained only from adolescents aged 10–19 years. The prevalence and its 95% confidence interval using the Clopper exact method and adjusted prevalence ratios were calculated using random-effects logistic regression models. Findings: Among 3888 recruited students, 1985 (51.05%) were from public schools, and 1903 (48.95%) were from private schools aged 6–19 years. The overall prevalence of underweight was 4.95% (95% CI 4.29–5.69), with a significantly higher prevalence in public schools (8.09%) than private schools (1.69%). The overall prevalences of general obesity and central obesity were 13.41% (95% CI 12.35–14.52) and 9.15% (95% CI 8.26–10.11), respectively, with significantly higher prevalence in private schools (p < 0.001). The prevalences of general and central obesity were four times (adjusted PR = 4.42, 95% CI 2.90–6.72) and eight times (adjusted PR = 8.31, 95% CI 4.82–14.35) higher, respectively, in private schools than public schools. The overall prevalence of hypertension was 7.37% (95% CI 6.33–8.51), and similar prevalences were found in public and private schools. Private school students had 2.37 times higher prevalence of impaired fasting plasma glucose (adjusted PR = 2.37, 95% CI 1.19–4.72) and 3.51 times higher prevalence of metabolic syndrome (adjusted PR = 3.51, 95% CI 1.54–8.01) than public school students. Among 2160 adolescents, 67.73% (1463) had normal body mass index. The prevalence of metabolically obese normal weight phenotype (MONW) was 42.86% (95% CI 40.30–45.44), which is higher in public [46.39% (95% CI 43.25–49.54)] than private [35.33% (95% CI 30.99–39.86)] schools (p < 0.001) with adjusted PR of 0.91 (95% CI 0.70–1.17). The most prevalent cardio-metabolic abnormality among metabolically obese normal weight phenotype was low high-density lipoprotein-c, significantly higher among adolescents from public schools (62.12% vs 52.73%, p = 0.039) than private schools. The prevalence of metabolically obese underweight (MOUW) (48/115) was 41.74% (95% CI 32.61–51.30), being higher among adolescents in public schools than private schools but not significant (p = 0.264). Interpretation: Effective implementation of food security measures and targeted initiatives will be crucial to mitigate the socioeconomic disparities associated with the growing burden of cardiometabolic traits. Metabolic obesity among phenotypically normal or underweight adolescents should not be overlooked but should be intervened early through novel screening criteria to prevent future cardiovascular burdens. These findings also have implications for low- and -middle income countries like India, which are undergoing a nutritional transition where socioeconomic status strongly influences cardio-metabolic traits. [ABSTRACT FROM AUTHOR]
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