Identifying subgroups of age and cohort effects in obesity prevalence

2020 ◽  
Author(s):  
Tatjana Miljkovic ◽  
Xin Wang
Keyword(s):  
Cohort Effects ◽  
Obesity Prevalence ◽  
Age And Cohort Effects

Changing predictors of self-rated health: Disentangling age and cohort effects.

2015 ◽  
Vol 30 (2) ◽  
pp. 462-474 ◽  
Author(s):  
Svenja M. Spuling ◽  
Susanne Wurm ◽  
Clemens Tesch-Römer ◽  
Oliver Huxhold
Keyword(s):  
Cohort Effects ◽  
Self Rated Health ◽  
Age And Cohort Effects

scholarly journals Birth cohort effects among US-born adults born in the 1980s: foreshadowing future trends in US obesity prevalence

2012 ◽  
Vol 37 (3) ◽  
pp. 448-454 ◽  
Author(s):  
W R Robinson ◽  
K M Keyes ◽  
R L Utz ◽  
C L Martin ◽  
Y Yang
Keyword(s):  
Birth Cohort ◽  
Cohort Effects ◽  
Future Trends ◽  
Obesity Prevalence

scholarly journals Gender-specific temporal trends in overweight prevalence among Chinese adults: a hierarchical age-period-cohort analysis from 2008 to 2015

2020 ◽  
Vol 5 (1) ◽  
Author(s):  
Yinmei Yang ◽  
Mohammedhamid Osman Kelifa ◽  
Bin Yu ◽  
Carly Herbert ◽  
Yongbo Wang ◽  
...  
Keyword(s):  
Cohort Analysis ◽  
Temporal Trends ◽  
General Social Survey ◽  
Cohort Effects ◽  
Chinese Adults ◽  
Cross Sectional Survey ◽  
Cross Sectional ◽  
Gender Specific ◽  
Overweight Prevalence ◽  
Age And Cohort Effects

Abstract Background As a key health risk, the prevalence of overweight has been strikingly increasing worldwide. This study aimed to disentangle the net age, period, and cohort effects on overweight among Chinese adults by gender. Methods Data came from the Chinese General Social Survey from 2008 to 2015, which was a repeated cross-sectional survey (n = 55,726, aged 18 and older). χ2 or t tests were used to estimate the gender disparities in overweight and socioeconomic status (SES). A series of hierarchical age-period-cohort cross-classified random-effects models were performed using SAS version 9.4 to estimate the overall and gender-specific temporal trends of overweight, as well as the association between SES and overweight. Further, a series of line charts were used to present the age and cohort variations in overweight. Results After controlling for covariates, significant age and cohort effects were observed among adults in China (b = 0.0205, p < 0.001; b = 0.0122, p < 0.05; respectively). Specifically, inverted U-shaped age effects were identified for both genders, with a high probability of overweight occurring in middle age (b = –0.0012, p < 0.001). Overweight was more prevalent among men than women before 60 years old, and this trend reversed thereafter (b = –0.0253, p < 0.001). Moreover, men born during the war (before 1950) and reform cohorts (after the 1975s) demonstrated a substantial decline in overweight, while men born in 1950–1975 showed an increasing trend in overweight prevalence (b = 0.0378, p < 0.05). However, the cohort effect on women was not statistically significant. Additionally, a higher SES was related to an elevated probability of overweight. Conclusion Gender-specific age and cohort effects on the prevalence of overweight were observed among Chinese adults. Both China and other developing countries need to pay attention to the coming obesity challenge and related health inequality. Full life-cycle overweight prevention interventions should focus on middle-aged adults, men born in the war and reform eras, and adults with a higher SES.

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