Background 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 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. Methods Participants 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. Results Between 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. Conclusions The 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.
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 (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.ObjectiveTo assess the cross-sectional and longitudinal effects of age, using a Marginal Logistic Regression (MLR) model.MethodsIn 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.ResultsFrom 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.ConclusionThe 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.
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.
The risk of obesity commonly changes with age, which is a longitudinal (aging) effect. Also, individuals who 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 model. In the current study, we used the information of individuals who had participated in the Isfahan Cohort Study. Participants were a large group of Iranian adults over 35 years of age in 2001, who lived in the central region of Iran. Repeated measurements were obtained in 2001, 2007, and 2013. 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 a baseline age of 35 to 60 and a decline for the older ones. The odds of obesity had about a 2% increase (on average) with each year of aging, regardless of the baseline age. The high frequency of individuals with obesity and its fast growth has been a serious public health issue among Iranian 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.
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