Assessing longitudinal and cross-sectional effects of age on adult obesity in an Iranian population: results from a large population-based cohort study

Abstract

BackgroundObesity is a significant risk factor for Noncommunicable diseases, and it is related to many adverse health consequences. The risk of obesity commonly changes with age, which is called a longitudinal or aging effect. Also, individuals born or enter to the study of the same age have similar living conditions that may influence their obesity risk in a particular way; this is a cross-sectional effect. In the current study, an advanced statistical model is used to distinguish between longitudinal and cross-sectional effects of age on the risk of obesity for men and women.MethodsParticipants are a group of 6504 Iranian adults over 35 years of age in 2001, who live in the central region of Iran. They were followed up for 12 years in a large community-based study. Various medical indexes, including Body Mass Index, were collected in 2001, 2007, and 2013. The Marginal Logistic Regression model, which includes linear and quadratic effects of the Baseline Age and its difference with current age, is used.ResultsBetween 2001 and 2013, the prevalence of obesity raised from 13% to 18% in men and from 31% to 44% in women. The odds of obesity for women was approximately three times the odds of obesity for men on average adjusting for the age effects. Both cross-sectional and longitudinal effects of age were significantly associated with the odds ratio of obesity. There was a rise in the prevalence of obesity for individuals with Baseline Age 35 to 55 and a decline thereafter. Also, the odds ratio of obesity across one’s life course, had about 3% increase, on average, by each year aging, regardless of the age at baseline.ConclusionsThe high rate of obesity and its fast growth is a serious public health issue among Iranians, especially in adults age 35-55, and women. In the present study, Baseline Age was more strongly associated with the risk of obesity than aging. Considering both cross-sectional and longitudinal effects of age, helps us to understand the effect of age on obesity better and to identify the related factors.