Obesity 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 (aging) effect. Also, individuals enter 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.
To assess the cross-sectional and longitudinal effects of age, using a Marginal Logistic Regression (MLR) model.
In the current study, we used the information of individuals who had participated in the Isfahan Cohort Study (ICS). Participants were a large group of Iranian adults over 35 years of age in 2001, who lived in the central region of Iran. They were followed up for 12 years. Repeated measurements of obesity were obtained in 2001, 2007, and 2013. The Marginal Logistic Regression model including the effects of the age at baseline and its difference with current age, is used.
From 2001 to 2013, the percentage of obesity in men and women has raised from 13% to 18% and from 31% to 44%, respectively. Both cross-sectional and longitudinal effects of age were significantly associated with the odds ratio of obesity. There was a rise in the probability of obesity for individuals with baseline age 35 to 60 and a decline for the older ones. Furthermore, the odds of obesity had about 2% increase (on average) by each year of aging, regardless of the baseline age.
The high frequency of obese individuals and its fast growth has been a serious public health issue among Iranians adults aged 35-60 years, especially in women. To better understand the effect of age on obesity and identify the related factors, both cross-sectional and longitudinal effects of age should be considered.