Perceived Age Discrimination in the Second Half of Life: An Examination of Age, Period, and Cohort Effects

Background and Objectives

Ageism is defined as stereotypes, prejudice, and discrimination based on age. Perceived age discrimination (e.g., the behavioral component of ageism) is highly prevalent in society, as reported by 1 in 3 people in Europe. The present study examined variations in perceived age discrimination in the second half of life. We adopt a comprehensive approach that examines whether perceived age discrimination varies by age (chronological time from birth), period (the context when data were collected), or cohort (a group of people with shared life events experienced at a similar age) across gender and ethnic origin.

Research Design and Methods

We relied on psychosocial data from the Health and Retirement Survey between 2006 and 2018. We ran a set of age-period-cohort models to determine the separate effects of aging (age) factors, contextual (period) factors, and generational (cohort) factors on perceived age discrimination.

Results

Our findings show that perceived age discrimination increases with age but reaches a plateau around the age of 75. There also were some cohort effects, but they appeared minimal and inconsistent. No period effects were found.

Discussion and Implications

The findings attest to the consistent nature of perceived age discrimination, which is less likely to be affected by external contextual events. It also is less likely to be affected by gender or ethnicity. The findings also suggest that it is older persons who are more likely to report age discrimination, thus, interventions should address ageism in this age group.

Alerting trends in epidemiology for calcific aortic valve disease, 1990-2019: An age-period-cohort analysis for the Global Burden of Disease Study 2019

AIMS

To assess the trends in calcific aortic valve disease (CAVD) epidemiology, with an emphasis on CAVD mortality, leading risk factors, and their associations with age, period, and birth cohort.

METHODS AND RESULTS

Prevalence, disability-adjusted life years, and mortality were derived from the Global Burden of Disease Study 2019. The age-period-cohort model was employed to study the detailed trends of CAVD mortality and its leading risk factors. Globally, CAVD showed unsatisfactory results from 1990 to 2019, with the CAVD deaths of 127 000 in 2019. CAVD mortality was substantially reduced in high socio-demographic index (SDI) countries [-1.45%, 95% confidence interval (CI) (-1.61 to -1.30)], mildly increased in high-middle SDI countries [0.22%, 95% CI (0.06-0.37)], and unchanged in other SDI quintiles. There was a noticeable transition in CAVD deaths from younger to older populations globally. The CAVD mortality increased exponentially with age, and the male had higher mortality than the female before 80 years old. Favourable period [0.69, 95% CI (0.66-0.72)] and birth effects [0.30, 95% CI (0.22-0.43)] were mainly observed in high SDI countries, while unfavourable effects were mostly noticed in high-middle SDI countries. High systolic blood pressure was the leading risk factor of CAVD deaths globally, and it showed favourable trends in high SDI regions.

CONCLUSION

Although CAVD mortality reduction was observed globally, unfavourable period, and cohort effects were found in many countries. Increase of mortality rate among the population ≥85 years was the common challenge across all SDI quintiles, stressing the necessity to further improve health care for CAVD patients worldwide.

An ecological study of obesity-related cancer incidence trends in Australia from 1983 to 2017

BACKGROUND

Overweight and obesity is a growing public health issue as it contributes to the future burden of obesity-related diseases, including cancer, especially in high-income countries. In Australia, 4.3% of all cancers diagnosed in 2013 were attributable to overweight and obesity. Our aim was to examine Australian age-specific incidence trends over the last 35 years for obesity-related cancers based on expert review (colorectal, liver, gallbladder, pancreas, breast in postmenopausal women, uterine, ovary, kidney, thyroid, and multiple myeloma) individually and pooled.

METHODS

Australian incidence data for 10 obesity-related cancers among people aged 25-84 years, diagnosed from 1983 to 2017, were obtained from the Australian Cancer Database. We used age-period-cohort modelling and joinpoint analysis to assess trends, estimating incidence rate ratios (IRR) by birth-cohort for each individual cancer and pooled, and the annual percentage change. The analyses were also conducted for non-obesity-related cancers over the same period.

FINDINGS

The total number of cancers where some proportion is obesity-related, diagnosed from 1983-2017, was 1,005,933. This grouping was 34.7% of cancers diagnosed. The IRR of obesity-related cancers increased from 0.77 (95% CI 0.73, 0.81) for the 1903 birth-cohort to 2.95 (95% CI 2.58, 3.38) for the recent 1988 cohort relative to the 1943 cohort. The IRRs of non-obesity related cancers were stable with non-significant decreases in younger cohorts. These trends were broadly similar across sex and age groups.

INTERPRETATION

The incidence of obesity-related cancers in Australia has increased by birth-cohort across all age-groups, which should be monitored. Obesity, a public health epidemic, needs to be addressed through increased awareness, policy support and evidence-based interventions.

FUNDING

This research received no specific funding.

Spatially varying age-period-cohort analysis with application to US mortality, 2002-2016

Many public health databases index disease counts by age groups and calendar periods within geographic regions (e.g., states, districts, or counties). Issues around relative risk estimation in small areas are well-studied; however, estimating trend parameters that vary across geographic regions has received less attention. Additionally, small counts (e.g., $<10$) in most publicly accessible databases are censored, further complicating age-period-cohort (APC) analysis in small areas. Here, we present a novel APC model with left-censoring and spatially varying intercept and trends, estimated with correlations among contiguous geographic regions. Like traditional models, our model captures population-scale trends, but it can also be used to characterize geographic disparities in relative risk and age-adjusted trends over time. To specify the joint distribution of our three spatially varying parameters, we adapt the generalized multivariate conditional autoregressive prior, previously used for multivariate disease mapping. Specified in this manner, region-specific parameters are correlated spatially, and also to one another. Estimation is performed using the No-U-Turn Hamiltonian Monte Carlo sampler in Stan. We conduct a simulation study to assess the performance of the proposed model relative to the standard model, and conclude with an application to US state-level opioid overdose mortality in men and women aged 15-64 years.

Long-term trends in the body mass index and obesity risk in Estonia: an age-period-cohort approach

OBJECTIVES

To analyse the age, period and cohort effects on the mean body mass index (BMI) and obesity over the past two decades in Estonia.

METHODS

Study used data from nationally representative repeated cross-sectional surveys on 11,547 men and 16,298 women from 1996 to 2018. The independent effects of age, period and cohort on predicted mean BMI and probability of obesity (BMI ≥ 30 kg/m²) were modelled using hierarchical age-period-cohort analysis.

RESULTS

Curvilinear association between age and mean BMI was found for men, whereas the increase in mean BMI was almost linear for women. The predicted mean BMI for 40-year-old men had increased by 6% and probability of obesity by 1.8 times over 1996-2018; the period effects were slightly smaller for women. Men from the 1970s birth cohort had higher mean BMI compared to the average, whereas no significant cohort effects were found for obesity outcome.

CONCLUSIONS

Population-level BMI changes in Estonia during 1996-2018 were mostly driven by period rather than cohort-specific changes.

Health behaviors and psychological distress: changing associations between 1997 and 2016 in the United States

OBJECTIVES

Smoking rates have declined with a slower pace among those with psychological distress compared to those without. We examined whether other health behaviors (heavy alcohol consumption, physical inactivity, short sleep duration) showed similar trends associated with psychological distress. We also examined differences by age and birth cohort.

METHODS

Data were from the annually repeated cross-sectional U.S. National Health Interview Surveys (NHIS) of 1997-2016 (total n = 603,518). Psychological distress was assessed with the 6-item Kessler Psychological Distress Scale (K6).

RESULTS

Psychological distress became more strongly associated with smoking (OR 1.09 per 10 years; 95% CI 1.07, 1.12), physical inactivity (OR 1.08; 1.05, 1.11), and short sleep (OR 1.12; 1.06, 1.18), but less strongly associated with heavy alcohol consumption (OR 0.93; 0.89, 0.98). The associations of smoking and alcohol consumption attenuated with age, whereas the association with physical inactivity strengthened with age. Compared to older birth cohorts, smoking became more strongly associated with psychological distress among younger birth cohorts up to those born in the 1980s.

CONCLUSIONS

The strength of associations between psychological distress and health behaviors may vary by time period, age, and birth cohort.

Recent increases in depressive symptoms among US adolescents: trends from 1991 to 2018

BACKGROUND

Mental health problems and mental health related mortality have increased among adolescents, particularly girls. These trends have implications for etiology and prevention and suggest new and emerging risk factors in need of attention. The present study estimated age, period, and cohort effects in depressive symptoms among US nationally representative samples of school attending adolescents from 1991 to 2018.

METHODS

Data are drawn from 1991 to 2018 Monitoring the Future yearly cross-sectional surveys of 8th, 10th, and 12th grade students (N = 1,260,159). Depressive symptoms measured with four questions that had consistent wording and data collection procedures across all 28 years. Age-period-cohort effects estimated using the hierarchical age-period-cohort models.

RESULTS

Among girls, depressive symptoms decreased from 1991 to 2011, then reversed course, peaking in 2018; these increases reflected primarily period effects, which compared to the mean of all periods showed a gradual increase starting in 2012 and peaked in 2018 (estimate = 1.15, p < 0.01). Cohort effects were minimal, indicating that increases are observed across all age groups. Among boys, trends were similar although the extent of the increase is less marked compared to girls; there was a declining cohort effect among recently born cohorts, suggesting that increases in depressive symptoms among boys are slower for younger boys compared to older boys in recent years. Trends were generally similar by race/ethnicity and parental education, with a positive cohort effect for Hispanic girls born 1999-2004.

CONCLUSIONS

Depressive symptoms are increasing among teens, especially among girls, consistent with increases in depression and suicide. Population variation in psychiatric disorder symptoms highlight the importance of current environmental determinants of psychiatric disorder risk, and provide evidence of emerging risk factors that may be shaping a new and concerning trend in adolescent mental health.

Increasing varicella incidence rates among children in the Republic of Korea: an age-period-cohort analysis

In the Republic of Korea, despite the introduction of one-dose universal varicella vaccination in 2005 and achieving a high coverage rate of 98.9% in 2012, the incidence rate has been increased sevenfold. This study aimed to investigate time trends of varicella incidence rate, assessing the age, period and birth cohort effects. We used national data on the annual number of reported cases from 2006 to 2017. A log-linear Poisson regression model was used to estimate age-period-cohort effects on varicella incidence rate. From 2006 to 2017, the incidence of varicella increased from 22.5 cases to more than 154.8 cases per 100 000. Peak incidence has shifted from 4 to 6 years old. The estimated period and cohort effects showed significant upward patterns, with a linear increasing trend by net drift. There has been an increase in the incidence among the Korean population regarding period and cohort despite the universal vaccination of varicella vaccine. Our data suggest the need for additional studies to address the current gap in herd immunity.

Seroprevalence of hepatitis B virus in Taiwan 30 years after the commencement of the national vaccination program

Background

In this study, the long-term efficacy of hepatitis B virus (HBV) vaccination was assessed using seroprevalence and an age–period–cohort (APC) model of HBV seromarkers among university entrants 30 years after the introduction of the national neonatal HBV vaccination program in Taiwan.

Methods

In total, data of 17,611 university entrants who underwent university entrance health examinations between 2005 and 2016 were included. The seroprevalence of the HBV surface antigen (HBsAg) and the levels of the antibody against the HBV surface antigen (anti-HBs) in each year group and sex were calculated. The levels of the antibody against the HBV core antigen were examined only for 2012 and 2016. The APC model was used to analyze the HBV carrier rates.

Results

The chronic HBV infection (HBsAg positivity) rate decreased from 9.7% in university students born before June 1974 to <1.0% in students born after 1992. The prevalence of anti-HBs positivity declined, particularly between the 1984–1988 cohort (78.2%–53.2%) and the 1990–1994 cohort (60.6%–44.4%). Our APC model revealed that the chronic HBV carrier rate among the student population was affected significantly by age, period, and cohort (P < 0.001).

Conclusions

HBV vaccination is one of the most effective strategies for preventing HBV infection. However, for complete eradication of HBV infection, the development of strategies that detect vaccination failure more effectively than current strategies do and early implementation of appropriate treatments are both necessary.

A unified approach for assessing heterogeneity in age-period-cohort model parameters using random effects

Age-period-cohort models are a popular tool for studying population-level rates; for example, trends in cancer incidence and mortality. Age-period-cohort models decompose observed trends into age effects that correlate with natural history, period effects that reveal factors impacting all ages simultaneously (e.g. innovations in screening), and birth cohort effects that reflect differential risk exposures that vary across birth years. Methodology for the analysis of multiple population strata (e.g. ethnicity, cancer registry) within the age-period-cohort framework has not been thoroughly investigated. Here, we outline a general model for characterizing differences in age-period-cohort model parameters for a potentially large number of strata. Our model incorporates stratum-specific random effects for the intercept, the longitudinal age trend, and the model-based estimate of annual percent change (net drift), thereby enabling a comprehensive analysis of heterogeneity. We also extend the standard model to include quadratic terms for age, period, and cohort, along with the corresponding random effects, which quantify possible stratum-specific departures from global curvature. We illustrate the utility of our model with an application to metastatic prostate cancer incidence (2004-2013) in non-Hispanic white and black men, using 17 population-based cancer registries in the Surveillance, Epidemiology, and End Results Program.

The hierarchical age-period-cohort model: Why does it find the results that it finds?

It is claimed the hierarchical-age–period–cohort (HAPC) model solves the age–period–cohort (APC) identification problem. However, this is debateable; simulations show situations where the model produces incorrect results, countered by proponents of the model arguing those simulations are not relevant to real-life scenarios. This paper moves beyond questioning whether the HAPC model works, to why it produces the results it does. We argue HAPC estimates are the result not of the distinctive substantive APC processes occurring in the dataset, but are primarily an artefact of the data structure—that is, the way the data has been collected. Were the data collected differently, the results produced would be different. This is illustrated both with simulations and real data, the latter by taking a variety of samples from the National Health Interview Survey (NHIS) data used by Reither et al. (Soc Sci Med 69(10):1439–1448, 2009) in their HAPC study of obesity. When a sample based on a small range of cohorts is taken, such that the period range is much greater than the cohort range, the results produced are very different to those produced when cohort groups span a much wider range than periods, as is structurally the case with repeated cross-sectional data. The paper also addresses the latest defence of the HAPC model by its proponents (Reither et al. in Soc Sci Med 145:125–128, 2015a). The results lend further support to the view that the HAPC model is not able to accurately discern APC effects, and should be used with caution when there appear to be period or cohort near-linear trends.

Racial disparities in self-rated health: trends, explanatory factors, and the changing role of socio-demographics

This paper uses data from the U.S. National Health Interview Surveys (N = 1,513,097) to describe and explain temporal patterns in black-white health disparities with models that simultaneously consider the unique effects of age, period, and cohort. First, we employ cross-classified random effects age-period-cohort (APC) models to document black-white disparities in self-rated health across temporal dimensions. Second, we use decomposition techniques to shed light on the extent to which socio-economic shifts in cohort composition explain the age and period adjusted racial health disparities across successive birth cohorts. Third, we examine the extent to which exogenous conditions at the time of birth help explain the racial disparities across successive cohorts. Results show that black-white disparities are wider among the pre-1935 cohorts for women, falling thereafter; disparities for men exhibit a similar pattern but exhibit narrowing among cohorts born earlier in the century. Differences in socioeconomic composition consistently contribute to racial health disparities across cohorts; notably, marital status differences by race emerge as an increasingly important explanatory factor in more recent cohorts for women whereas employment differences by race emerge as increasingly salient in more recent cohorts for men. Finally, our cohort characteristics models suggest that cohort economic conditions at the time of birth (percent large family, farm or Southern birth) help explain racial disparities in health for both men and women.

Analysis of age-period-cohort effects on overall mortality in Andalusia (Southern Spain)

OBJECTIVES

To evaluate the age-period-cohort effects on overall mortality in Andalusia (Spain).

STUDY DESIGN

An ecological study was implemented with a Lexis diagram triangle comprising each annual age group, year of death and year of birth as the unit of analysis.

METHODS

In all 1,384,899 deaths from all causes were analysed for individuals between the ages of 1 and 84 years who died in Andalusia in the period 1981-2008. A non-linear regression model was estimated for each gender group and geographical area. The effects of age, year of death and birth cohort were parameterized using B-spline smoothing functions.

RESULTS

There is a downward trend in mortality by age to around the age of 15 years, from which point the trend turned upwards. For cohorts born between 1945 and 1965, the rate climbed steadily. From 1965, the rate turned downwards. Death rates increased between 1995 and 2000, only to turn down again until the end of the period. Broadly, these results were similar for both men and women, in all the provinces of Andalusia and for Andalusia as a whole.

CONCLUSIONS

This study points to an age-period-cohort effect on deaths from all causes in all the geographic areas studied.