An exploration of socioeconomic variation in lifestyle factors and adiposity in the Ontario Food Survey through structural equation models.
Socioeconomic indicators have been inversely associated with overweight and obesity, with stronger associations observed among women. The objective of the present secondary analysis was to examine the relationships among socioeconomic measures and adiposity for men and women participating in the Ontario Food Survey (OFS), and to explore lifestyle factors as potential mediators of these associations.
The cross-sectional 1997/98 OFS collected anthropometric measurements, a food frequency questionnaire, data on socio-demographics (age, sex, income, and education) and physical activity from 620 women and 467 men, ages 18 to 75. Based on the 2003 Health Canada guidelines, waist circumference and BMI values were used to derive least risk, increased risk, and high risk adiposity groups. Structural equation modeling was conducted to examine increased risk and high risk adiposity in relation to education and income, with leisure time physical activity, fruit and vegetable intake, and smoking status included as potential mediators of these associations.
The probability of high risk adiposity was directly associated with education (β-0.19, p < 0.05) and income (β-0.22, p < 0.05) for women, but not for men. Fruit and vegetable intake was a marginally significant mediator of the relationship between education and high risk adiposity for women. Increased risk adiposity was not associated with income or education for men or women.
The socioeconomic context of adiposity continues to differ greatly between men and women. For women only in the OFS, fruit and vegetable intake contributed to the inverse association between education and high risk adiposity; however, additional explanatory factors are yet to be determined.
Ward, H., Tarasuk, V., Mendelson, R., & McKeown-Eyssen, G. (2007). An exploration of socioeconomic variation in lifestyle factors and adiposity in the ontario food survey through structural equation modeling. The International Journal of Behavioral Nutrition and Physical Activity, 4(1), 8-8. doi:10.1186/1479-5868-4-8
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