Overweight and lifestyle behaviors of low socioeconomic elementary school children in Buenos Aires

BMC Pediatr. 2009 Feb 24:9:17. doi: 10.1186/1471-2431-9-17.

Abstract

Background: There is growing interest in understanding the role that lifestyle behaviors play in relation to children's weight status. The objective of the study was to determine the association between children s BMI and dietary practices and maternal BMI.

Methods: 330 students (168M) aged 8.9 + 2 y from 4 suburban Buenos Aires elementary schools, and their mothers aged 36.2 + 7 y were examined between April and September 2007. Mothers were asked about their children s lifestyle. Data included parental education levels socioeconomic status, mothers and children s BMI, and Tanner stage.

Results: All families were in the low socio-economic class. 79% of parents had an elementary education or less. 61 (18.5%) of children were obese (OB) (BMI>95%ile per CDC norms), and 53 (16.1%) overweight (OW) (BMI>85<95%ile). 103 (31.2%) of mothers were OB (BMI>30 kg/m2), and 102 (30.9%) OW (BMI>25<30). 63% the children were pre-pubertal. 40% had a TV set in their bedroom. 13% of the children skipped breakfast and only 38% watched TV <or=2 hours daily, as recommended. Multiple logistic regression analysis showed a positive association between children s OW/OB and drinking sweetened beverages (OR = 1.24; 95% CI, 1.02-1.52), TV viewing (OR = 1.30; 95% CI,1.05-1.62), and maternal BMI (OR: 1.07; 95% CI,1.02-1.12), and a negative association with eating breakfast (OR = 0.43; 95% CI, 0.19-0.97) adjusted for fruit and vegetables consumption, milk consumption, maternal educational level and socioeconomic class.

Conclusion: Our results suggest that TV viewing, drinking sweet beverages, skipping breakfast, and maternal BMI are important predictive variables for childhood OW/OB.

MeSH terms

  • Argentina / epidemiology
  • Body Mass Index
  • Body Weight / physiology*
  • Child
  • Cross-Sectional Studies
  • Educational Status
  • Female
  • Health Behavior
  • Humans
  • Life Style*
  • Logistic Models
  • Male
  • Overweight / epidemiology*
  • Poverty*
  • Regression Analysis
  • Social Class