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Prevalence of Pediatric Metabolic Syndrome and Associated Risk Factors among School-Age Children of 10–16 Years Living in District Shimla, Himachal Pradesh, India

INTRODUCTION: Recently, an increasing trend in the prevalence of pediatric metabolic syndrome (PMS) among school-age children has been documented in different parts of India. There is lack of data on the prevalence of PMS and its associated risk factors among school-age children living in district S...

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Detalles Bibliográficos
Autores principales: Gupta, Anmol, Sachdeva, Amit, Mahajan, Narender, Gupta, Aakriti, Sareen, Neha, Pandey, Ravindra Mohan, Ramakrishnan, Lakshmy, Sati, Hem Chandra, Sharma, Brij, Sharma, Neetu, Kapil, Umesh
Formato: Online Artículo Texto
Lenguaje:English
Publicado: Medknow Publications & Media Pvt Ltd 2018
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC6063189/
https://www.ncbi.nlm.nih.gov/pubmed/30090730
http://dx.doi.org/10.4103/ijem.IJEM_251_17
Descripción
Sumario:INTRODUCTION: Recently, an increasing trend in the prevalence of pediatric metabolic syndrome (PMS) among school-age children has been documented in different parts of India. There is lack of data on the prevalence of PMS and its associated risk factors among school-age children living in district Shimla, Himachal Pradesh. Hence, to fill in the gap in the existing knowledge, the present study was conducted. METHODOLOGY: A cross-sectional study was conducted during 2015–2016. Thirty clusters (schools) were identified from a list of all schools using population proportionate to size sampling methodology. From each school, 70 children in the age group of 10–16 years were selected. Data was collected on the sociodemographic characteristics, anthropometry, waist circumference, blood pressure, and physical activity. Fasting venous blood samples were collected for estimation of blood glucose, triglycerides, and high-density lipoprotein levels. RESULTS: The prevalence of PMS using International Diabetes Federation classification was 3.3% and using modified-adult treatment panel classification criteria was 3.5%. Risk factors identified to be associated with PMS among school-age children were (i) male gender, (ii) high family monthly income, (iii) sedentary lifestyle, (iv) consumption of evening snack, (v) television/computer viewing, and (vi) motorized transportation for commuting to school. CONCLUSION: The PMS prevalence was 3.3% in school-age children residing in District Shimla. There is a need to formulate interventions to prevent and correct metabolic syndrome among them for reducing early onset of cardiovascular disease during adulthood.