Age-period-cohort analysis for trends in body mass index in Ireland

Abstract

BackgroundObesity is a growing problem worldwide and can often result in a variety of negative health outcomes. In this study we aim to apply partial least squares (PLS) methodology to estimate the separate effects of age, period and cohort on the trends in obesity as measured by body mass index (BMI).MethodsUsing PLS we will obtain gender specific linear effects of age, period and cohort on obesity. We also explore and model nonlinear relationships of BMI with age, period and cohort. We analysed the results from 7,796 men and 10,220 women collected through the SLAN (Surveys of Lifestyle, attitudes and Nutrition) in Ireland in the years 1998, 2002 and 2007.ResultsPLS analysis revealed a positive period effect over the years. Additionally, men born later tended to have lower BMI (−0.026 kg·m-2 yr-1, 95% CI: -0.030 to −0.024) and older men had in general higher BMI (0.029 kg·m-2 yr-1, 95% CI: 0.026 to 0.033). Similarly for women, those born later had lower BMI (−0.025 kg·m-2 yr-1, 95% CI: -0.029 to −0.022) and older women in general had higher BMI (0.029 kg·m-2 yr-1, 95% CI: 0.025 to 0.033). Nonlinear analyses revealed that BMI has a substantial curvilinear relationship with age, though less so with birth cohort.ConclusionWe notice a generally positive age and period effect but a slightly negative cohort effect. Knowing this, we have a better understanding of the different risk groups which allows for effective public intervention measures to be designed and targeted for these specific population subgroups.

Age–period–cohort analysis of trends in blood pressure and body mass index in children and adolescents in Hong Kong

“…Our cohort effects for BP are consistent with falling BP by cohort among adults in the UK12 and Taiwan13 and for adult BMI in Ireland26 and Taiwanese women13 but are inconsistent with no cohort effect for childhood obesity23 or increasing adult BMI or obesity by cohort seen elsewhere 18–22 24 25. Similar cohort effects for BP and BMI suggest BMI driving BP or common factors driving both BP and BMI.…”

“…Positive period effects are universally identified 13 17–26. Cohort effects are more varied, with positive cohort effects (higher BMI or more obesity among younger cohorts) observed in China,17 Korea,18 Australia,19 France20 and the USA,21 22 but some studies have also suggested no23 or very moderate cohort effects24 25 in the USA or negative cohort effects for women in Taiwan13 or for both men and women in Ireland 26. While period effects due to changes in lifestyle are generally recognised, the varying cohort effects are harder to explain and could be due to faster adoption of unhealthy lifestyle among younger cohorts (for a positive cohort effect)27 and differences between generations (for a negative cohort effect) 28…”

Trends of Esophageal Cancer Mortality in Rural China from 1989 to 2013: An Age-Period-Cohort Analysis

“…However, one longstanding problem associated with the APC analysis, there is a linear relationship between the age, period, and cohort (Period = Age + Cohort) [6]. It is difficult to analyze the unique set for every age, period and cohort effect, which is called as the non-identification problem [6,17].…”

“…It is a popular analytical method in both epidemiological and sociological studies [6,7], and it has been applied to analyze the character and quality of trends in the prevalence of many diseases, such as liver disease, cardiovascular disease, and many kinds of cancer.…”

Age-period-cohort analysis of trends in amyotrophic lateral sclerosis incidence

“…PLSR overcomes the identifiability issue by employing an algorithm that optimizes the estimation separately for all three components. Previous PLSR models have explored effects in blood pressure [15], obesity [16] and overall mortality [17].…”