Nutrient Patterns and Their Association with Socio-Demographic, Lifestyle Factors and Obesity Risk in Rural South African Adolescents

Nutrients

Pedro T. Pisa¹  Titilola M. Pedro¹  Kathleen Kahn²  Stephen M. Tollman²  John M. Pettifor¹ 

[1] MRC/Wits Developmental Pathways for Health Research Unit, Department of Paediatrics, Faculty of Health Sciences, University of the Witwatersrand, Johannesburg 2193 South Africa; E-Mails:;MRC/Wits Rural Public Health and Health Transitions Research Unit (Agincourt), School of Public Health, Faculty of Health Sciences, University of the Witwatersrand, Johannesburg 2193, South Africa; E-Mails:

关键词: nutrient patterns;    adolescents;    rural;    South Africa;    transition;    Agincourt health and demographic surveillance system;   

DOI  :  10.3390/nu7053464

来源: mdpi

【 摘 要 】

The aim of this study was to identify and describe the diversity of nutrient patterns and how they associate with socio-demographic and lifestyle factors including body mass index in rural black South African adolescents. Nutrient patterns were identified from quantified food frequency questionnaires (QFFQ) in 388 rural South African adolescents between the ages of 11–15 years from the Agincourt Health and Socio-demographic Surveillance System (AHDSS). Principle Component Analysis (PCA) was applied to 25 nutrients derived from QFFQs. Multiple linear regression and partial R² models were fitted and computed respectively for each of the retained principal component (PC) scores on socio-demographic and lifestyle characteristics including body mass index (BMI) for age Z scores. Four nutrient patterns explaining 79% of the total variance were identified: PCI (26%) was characterized by animal derived nutrients; PC2 (21%) by vitamins, fibre and vegetable oil nutrients; PC3 (19%) by both animal and plant derived nutrients (mixed diet driven nutrients); and PC4 (13%) by starch and folate. A positive and significant association was observed with BMI for age Z scores per 1 standard deviation (SD) increase in PC1 (0.13 (0.02; 0.24); p = 0.02) and PC4 (0.10 (−0.01; 0.21); p = 0.05) scores only. We confirmed variability in nutrient patterns that were significantly associated with various lifestyle factors including obesity.

【 授权许可】

CC BY   
© 2015 by the authors; licensee MDPI, Basel, Switzerland.