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Prevalence of metabolic syndrome among adolescents in India: a population-based study.
Ramesh, Sowmya; Abraham, Ransi Ann; Sarna, Avina; Sachdev, Harshpal S; Porwal, Akash; Khan, Nizamuddin; Acharya, Rajib; Agrawal, Praween K; Ashraf, Sana; Ramakrishnan, Lakshmi.
Afiliação
  • Ramesh S; Population Council, Zone 5A, Ground Floor India Habitat Centre, Lodi Road, New Delhi, Delhi, 110003, India. sramesh@popcouncil.org.
  • Abraham RA; Cardiac Biochemistry, All India Institute of Medical Sciences, Delhi, India.
  • Sarna A; Population Council, Zone 5A, Ground Floor India Habitat Centre, Lodi Road, New Delhi, Delhi, 110003, India.
  • Sachdev HS; Sitaram Bhartia Institute of Science and Research, New Delhi, India.
  • Porwal A; Population Council, Zone 5A, Ground Floor India Habitat Centre, Lodi Road, New Delhi, Delhi, 110003, India.
  • Khan N; Population Council, Zone 5A, Ground Floor India Habitat Centre, Lodi Road, New Delhi, Delhi, 110003, India.
  • Acharya R; Population Council, Zone 5A, Ground Floor India Habitat Centre, Lodi Road, New Delhi, Delhi, 110003, India.
  • Agrawal PK; IPE Global Limited, New Delhi, India.
  • Ashraf S; Population Council, Zone 5A, Ground Floor India Habitat Centre, Lodi Road, New Delhi, Delhi, 110003, India.
  • Ramakrishnan L; Cardiac Biochemistry, All India Institute of Medical Sciences, Delhi, India.
BMC Endocr Disord ; 22(1): 258, 2022 Oct 24.
Article em En | MEDLINE | ID: mdl-36280821
ABSTRACT

BACKGROUND:

In India, the prevalence of overweight among adolescents is on the rise, setting the stage for an increase in metabolic syndrome (MS). This paper presents the national prevalence of MS in adolescents in India.

METHODS:

A nationally representative data of adolescents (10-19 years) from the Comprehensive National Nutrition Survey was used. MS was defined based on the NCEP-ATP III criteria for adolescents. Bivariate analysis was used to report socio-demographic differentials in prevalence and to assess interstate variability. Multivariate logistic regression model was constructed to measure the association between socio-demographic characteristics and prevalence of MS. Census data from 2011 was projected to 2017 to calculate burden.

RESULTS:

The prevalence of MS was 5.2% among adolescents. 11.9%, 15.4%, 26.0%, 31.9% and 3.7% had central obesity, high blood pressure, hypertriglyceridemia, low HDL-cholesterol and high fasting glucose, respectively. The prevalence was higher among males (5.7% vs. 4.7%, adjusted odds ratio (AOR) 1.3, 95% confidence interval [CI] 1.0, 1.6), those residing in urban areas (7.9% vs 4.2%, AOR 1.4, 95% CI 1.1, 1.8), and from wealthier households as compared to their counterparts (8.3% vs. 2.4%, AOR 3.4, 95% CI 2.1, 5.5). There was wide interstate variability in the prevalence of MS (0.5% - 16.5%). In 2017, 14.2 million adolescents had MS in India.

CONCLUSIONS:

The prevalence of MS among adolescents in India is low and clustered in urban areas and richer households. Early prevention interventions promoting a healthy lifestyle, especially in high prevalence areas, are needed to keep MS from becoming a public health issue.
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Texto completo: 1 Bases de dados: MEDLINE Assunto principal: Síndrome Metabólica Tipo de estudo: Etiology_studies / Prevalence_studies / Prognostic_studies / Risk_factors_studies Limite: Adolescent / Humans / Male País/Região como assunto: Asia Idioma: En Revista: BMC Endocr Disord Ano de publicação: 2022 Tipo de documento: Article País de afiliação: Índia

Texto completo: 1 Bases de dados: MEDLINE Assunto principal: Síndrome Metabólica Tipo de estudo: Etiology_studies / Prevalence_studies / Prognostic_studies / Risk_factors_studies Limite: Adolescent / Humans / Male País/Região como assunto: Asia Idioma: En Revista: BMC Endocr Disord Ano de publicação: 2022 Tipo de documento: Article País de afiliação: Índia