Age-period-cohort analysis of smoking prevalence among young adults in Korea

An age-period-cohort approach to studying long-term trends in obesity and overweight in England (1992-2019)

OBJECTIVE

This study aims to understand long-term trends in obesity and overweight in England by estimating life-course transitions as well as historical and birth cohort trends for both children and adults.

METHODS

Data on individuals aged 5 to 85 years old from the Health Survey for England were used, covering the period 1992 to 2019 and birth cohorts born between 1909 and 2013. Individual BMI values were classified as healthy weight, overweight, or obesity. Trends were compared, and an age-period-cohort model was estimated using logistic regression and categorical age, period, and cohort groups.

RESULTS

There was significant variation in age trajectories by birth cohorts for healthy weight and obesity prevalence. The odds of having obesity compared with a healthy weight increased consistently with age, increased throughout the study period (but faster between 1992 and 2001), and were higher for birth cohorts born between 1989 and 2008. The odds of having overweight showed an inverted U-shape among children, increased through adulthood, have been stable since 2012, and were considerably higher for the youngest birth cohort (2009-2013).

CONCLUSIONS

Younger generations with higher overweight prevalence coupled with increasing obesity prevalence with age suggest that obesity should remain a high priority for public health policy makers in England.

Status of Workers' Health Behavior and the Association between Occupational Characteristics and Health Behavior

This study investigated differences in unhealthy lifestyle behaviors (ULBs) between workers and nonworkers and demonstrated the association of ULBs with occupational characteristics among workers. This cross-sectional study used data from the Korea National Health and Nutrition Examination Survey from 2007 to 2019. For sociodemographic data, chi-squared tests were used to analyze categorical variables. Odds ratios (ORs) and 95% confidence intervals (CIs) for ULBs were estimated using Poisson regression models after adjusting for age, sex, educational level, and household income. The variables used were current smoking status, heavy drinking, and physical inactivity. Workers were associated with an increased risk of current smoking (adjusted OR (aOR) = 1.48, 95%CI = 1.41-1.56), heavy drinking (aOR = 1.79, 95%CI = 1.68-1.90), and physical inactivity (aOR = 1.07, 95%CI = 1.04-1.11) compared with nonworkers. Among workers, the differential risks of ULB according to occupational characteristics were as follows: skilled manual workers, self-employed workers, and workers working >40 h/week were at a higher risk of engaging in all ULBs than those in other occupational categories, paid workers, and workers working ≤40 h/week, respectively. Workers showed a higher risk of ULBs than nonworkers. The risk of ULBs differed according to occupational characteristics, highlighting the need for additional studies and detailed occupational health management.

Understanding long-term trends in smoking in England, 1972-2019: an age-period-cohort approach

BACKGROUND AND AIMS

Smoking prevalence has been falling in England for more than 50 years, but remains a prevalent and major public health problem. This study used an age-period-cohort (APC) approach to measure lifecycle, historical and generational patterns of individual smoking behaviour.

DESIGN

APC analysis of repeated cross-sectional smoking prevalence data obtained from three nationally representative surveys.

SETTING

England (1972-2019).

PARTICIPANTS

Individuals aged 18-90 years.

MEASUREMENTS

We studied relative odds of current smoking in relation to age in single years from 18 to 90, 24 groups of 2-year survey periods (1972-73 to 2018-19) and 20 groups of 5-year birth cohorts (1907-11 to 1997-2001). Age and period rates were studied for two groups of birth cohorts: those aged 18-25 years and those aged over 25 years.

FINDINGS

Relative to age 18, the odds of current smoking increased with age until approximately age 25 [odds ratio (OR) = 1.48, 95% confidence interval (CI) = 1.41-1.56] and then decreased progressively to age 90 (OR = 0.06, 95% CI = 0.04-0.08). They also decreased almost linearly with period relative to 1972-73 (for 2018-19: OR = 0.30, 95% CI = 0.26-0.34) and with birth cohort relative to 1902-06, with the largest decreased observed for birth cohort 1992-96 (OR = 0.44, 95% CI = 0.35-0.46) and 1997-2001 (OR = 0.35, 95% CI = 0.74-0.88). Smoking declined in the 18-25 age group by an average of 7% over successive 2-year periods and by an average of 5% in those aged over 25.

CONCLUSIONS

Smoking in England appears to have declined over recent decades mainly as a result of reduced smoking uptake before age 25, and to a lesser extent to smoking cessation after age 25.

Gender and tobacco epidemic in South Korea: implications from age-period-cohort analysis and the DPSEEA framework

OBJECTIVES

To understand a 20-year trend of gender-specific smoking prevalence among adults in South Korea.

DESIGN

Age-period-cohort analysis using the intrinsic estimator method was applied to examine the separate contribution of age, period and cohort effect on smoking prevalence. The Driving Force-Pressure-State-Exposure-Effect-Action (DPSEEA) framework was used to explain the observed smoking trends by mapping potential determinants and to address policy implications.

SETTING

General adult population in South Korea.

PARTICIPANTS

34 828 men and 43 632 women who aged 19-78 years, were not currently pregnant and were without a prior diagnosis of cardiovascular disease or cancer.

OUTCOME MEASURES

Gender-specific current smoking prevalence using the 1998-2017 Korea National Health and Nutrition Examination Survey.

RESULTS

Our results showed gender-specific age and birth cohort effects. More specifically, the smoking prevalence peaked at their mid-20s (prevalence rate ratio (PRR): 1.54, 95% CI: 1.49 to 1.59) and cohort born in 1959-1963 (PRR: 1.63, 95% CI: 1.57 to 1.70) and then decreased in men. On the other hand, in women, the smoking prevalence consistently increased until their mid-40s (PRR: 1.53, 95% CI: 1.27 to 1.84) and in recent birth cohort groups (PRR in 1994-1998 cohort: 1.55, 95% CI: 1.13 to 2.13). The period effects declined from 1998-2002 to 2003-2007, following increasing fluctuations in both genders. The smoking-DPSEEA framework showed the absence of policy actions to target female smokers and emphasised a proactive approach that tackles the upstream causes for smoking in women.

CONCLUSIONS

Men and women are clearly in different phases of the smoking epidemic in Korean population, and gender-tailored policies should be implemented.

An age-period-cohort analysis of the difference in smoking prevalence between urban and non-urban areas in Japan (2004-2019)

OBJECTIVES

This study aimed to conduct an age-period-cohort (APC) analysis of smoking prevalence trends in urban and non-urban areas in Japan.

METHODS

Data on smoking prevalence from 2004 to 2019 were extracted from the Comprehensive Survey of Living Conditions in Japan. Government ordinance-designated cities and special wards in Tokyo were defined as urban areas. The respondents ranged from 20 years to 79 years old, and were grouped in 5-year intervals. Cohorts were defined for each age group of each year, and those born between 1925-1929 and 1995-1999 were examined. We calculated the estimated smoking prevalence for each age, period, and cohort, as well as the smoking prevalence ratio of non-urban areas compared with urban areas from the APC analysis results.

RESULTS

The magnitude of the decrease in the period effect on smoking prevalence was larger in urban areas than in non-urban areas for both men and women. The smoking prevalence ratio for non-urban areas compared with that of urban areas was above 1 for men at most time points, except in the older age groups. In addition, the prevalence ratio between the areas decreased, particularly as age increased. For women, the smoking prevalence ratio in non-urban areas compared to urban areas was below 1 until cohorts born in the 1970s, but the trend reversed thereafter.

CONCLUSIONS

The results of this study suggest that further smoking control and cessation measures are necessary, particularly for older cohorts in urban women and for younger ages in non-urban men.

Factors Associated with Single-Use and Co-Use of Tobacco and Alcohol: A Multinomial Modeling Approach

Tobacco smoking and alcohol consumption are among the most important public health concerns not only in South Korea but also globally. This study identified the factors associated with single-use and co-use of tobacco and alcohol in Korean adults and provided more accurate estimates using a multinomial modeling approach. This study used the Korea Community Health Survey Data 2017, of which 205,336 respondents were selected as the sample for a multinomial logistic regression analysis. For the group that identified as only drinking monthly compared to the reference group, we found that the direction of the following factors was opposite to that of the results of the only currently smoking group: Age, marital status, educational level, monthly household income, occupation, obesity, self-rated health, hypertension, and hyperlipidemia. For the currently smoking and drinking monthly group relative to the reference group, the overall direction was a mix of the results of only currently smoking and only drinking monthly. These findings support the development of policies that consider the risk of smoking tobacco and consuming alcohol simultaneously.

The unrealized potential: cohort effects and age-period-cohort analysis

This study aims to provide a systematical introduction of age-period-cohort (APC) analysis to South Korean readers who are unfamiliar with this method (we provide an extended version of this study in Korean). As health data in South Korea has substantially accumulated, population-level studies that explore long-term trends of health status and health inequalities and identify macrosocial determinants of the trends are needed. Analyzing long-term trends requires to discern independent effects of age, period, and cohort using APC analysis. Most existing health and aging literature have used cross-sectional or short-term available panel data to identify age or period effects ignoring cohort effects. This under-use of APC analysis may be attributed to the identification (ID) problem caused by the perfect linear dependency across age, period, and cohort. This study explores recently developed three APC models to address the ID problem and adequately estimate the effects of A-P-C: intrinsic estimator-APC models for tabular age by period data; hierarchical cross-classified random effects models for repeated cross-sectional data; and hierarchical APC-growth curve models for accelerated longitudinal panel data. An analytic exemplar for each model was provided. APC analysis may contribute to identifying biological, historical, and socioeconomic determinants in long-term trends of health status and health inequalities as well as examining Korean’s aging trajectories and temporal trends of period and cohort effects. For designing effective health policies that improve Korean population’s health and reduce health inequalities, it is essential to understand independent effects of the three temporal factors by using the innovative APC models.