Lifecourse trajectories and cross-generational trends in social isolation: Findings from five successive British birth cohort studies

Despite growing concerns in the UK about social isolation, there remains a lack of data on the extent and time trends of social isolation from longitudinal, population-based studies. There is also little research that assesses the multiple domains of social isolation across the lifecourse and between generations in a holistic way accounting for different contexts. By applying a multi-context, multi-domain framework of social isolation to 5 successive British birth cohorts, we provide conceptual and empirical understanding of social isolation trajectories across the lifecourse and identify potential generational and sex differences in trends. Where data were available, comparable social isolation indicators were generated to enable lifecourse trajectories and cross-generational trends to be explored. Information on isolation was available across the following relational contexts: household i.e., living alone; partnership, family and friends outside the household; education and employment networks; and community engagement. Trajectories were modelled stratified by sex using a multilevel growth curve framework. Data were analysed from 73,847 individuals (48.5% female), in 5 successive cohorts born in 1946 (N = 5,362), 1958 (N = 16,742), 1970 (N = 16,950), 1989-90 (N = 15,562), and 2000-01 (N = 19,231). Exploring a range of social isolation indicators across several contexts provided a nuanced picture of social isolation across the lifecourse and between generations in the UK, with no consistent pattern of increased or decreased isolation over time. For example, more people are living alone, less women are out of education and employment in midlife, more people are volunteering, but fewer people regularly engage in religious activity. It therefore highlights the need to focus on a range of social isolation indicators across contexts to understand how people compensate for specific types of isolation, and to understand structural differences in social configurations in the UK, which may not only define the timing and sequencing of life transitions but also social isolation.

Detecting Cohort Effects in Accelerated Longitudinal Designs Using Multilevel Models

Accelerated longitudinal designs allow researchers to efficiently collect longitudinal data covering a time span much longer than the study duration. One important assumption of these designs is that each cohort (a group defined by their age of entry into the study) shares the same longitudinal trajectory. Although previous research has examined the impact of violating this assumption when each cohort is defined by a single age of entry, it is possible that each cohort is instead defined by a range of ages, such as groups that experience a particular historical event. In this paper we examined how including cohort membership in linear and quadratic multilevel models performed in detecting and controlling for cohort effects in this scenario. Using a Monte Carlo simulation study, we assessed the performance of this approach under conditions related to the number of cohorts, the overlap between cohorts, the strength of the cohort effect, the number of affected parameters, and the sample size. Our results indicate that models including a proxy variable for cohort membership based on age at study entry performed comparably to using true cohort membership in detecting cohort effects accurately and returning unbiased parameter estimates. This indicates that researchers can control for cohort effects even when true cohort membership is unknown.

Racial and Ethnic Trajectories of Sleep Disturbances: Variations by Age and Cohort

BACKGROUND

The racial and ethnic differences in trajectories of sleep disturbances in later life are crucial for addressing health disparities, but are not well understood. This study examines (a) how trajectories of sleep disturbances vary by race and ethnicity and birth cohort and (b) whether social and health risk factors explain such variations.

METHODS

The study uses longitudinal data from the 2002-2018 Health and Retirement Study (N = 21 963) and the multilevel growth curve model to assess trajectories of sleep disturbances and their variations across 6 cohorts of White, Black, and Hispanic older adults. Sleep disturbances are measured using a modified Jenkins Sleep Scale.

RESULTS

Without controls, sleep disturbances increased with aging for all racial and ethnic groups, but more rapidly among minorities, particularly younger cohorts of Hispanic older adults. When controlling for social and health risks, sleep disturbances did not change with aging for Whites and Blacks and increased for younger cohorts of Hispanics. Cohort effects were observed among White older adults, with higher sleep disturbances in younger cohorts. Importantly, the racial and ethnic disparities in age and cohort effects were not fully explained by social and health risks. Of the symptoms, the most salient racial and ethnic disparities were found in "waking up at night" and "not feeling rested."

CONCLUSIONS

Findings reveal several differences by race and ethnicity and birth cohort in trajectories of sleep disturbances. Efforts should be made to improve sleep health for older adults as they age, especially for younger cohorts of Blacks and Hispanics.

Age-specific disparities in fatal drug overdoses highest among older black adults and American Indian/Alaska native individuals of all ages in the United States, 2015-2020

INTRODUCTION

Increasing disparities within and between racial/ethnic groups in overdose deaths underscore the need to identify drivers and patterns to optimize overdose prevention strategies. We assess age-specific mortality rates (ASMR) in drug overdose deaths by race/ethnicity in 2015-2019 and 2020.

METHODS

Data were from the CDC Wonder, and included information for N = 411,451 deceased individuals in the United States (2015-2020) with a drug overdose-attributed cause of death (ICD-10 codes: X40-X44, X60-X64, X85, Y10-Y14). We compiled overdose death counts by age, race/ethnicity, and population estimates to derive ASMRs, mortality rate ratios (MRR), and cohort effects.

RESULTS

The ASMRs for Non-Hispanic Black adults (2015-2019) followed a different pattern than other racial/ethnic groups-low ASMRs among young individuals and peaking between 55-64 years-a pattern exacerbated in 2020. Younger Non-Hispanic Black individuals had lower MRRs than young Non-Hispanic White individuals, yet, older Non-Hispanic Black adults had much higher MRRs than older Non-Hispanic White adults (45-54yrs:126%, 55-64yrs:197%; 65-74yrs:314%; 75-84:148%) in 2020. American Indian/Alaska Native adults had higher MRRs than Non-Hispanic White adults in death counts compiled from pre-pandemic years (2015-2019); however, MRRs increased in 2020 (15-24yrs:134%, 25-34yrs:132%, 35-44yrs:124%, 45-54yrs:134%, 55-64yrs:118%). Cohort analyses suggested a bimodal distribution of increasing fatal overdose rates among Non-Hispanic Black individuals aged 15-24 and 65-74.

CONCLUSIONS AND RELEVANCE

Overdose fatalities unprecedently impact older Non-Hispanic Black adults and American Indian/Alaska Native populations of all ages, deviating from the pattern found for Non-Hispanic White individuals. Findings highlight the need for targeted naloxone and low-threshold buprenorphine programs to reduce racial disparities.

Examining Racial Disparities in Historical Change of Mental and Physical Health Across Midlife and Old Age in the United States

OBJECTIVES

To examine whether racial disparities are narrowing or widening with historical time among U.S. middle-aged and older adults, and test the extent to which educational attainment moderates racial disparities over historical time.

METHODS

Multilevel models were applied to longitudinal data on middle-aged (ages 40-65) and older adults (ages 66 and older) from the Health and Retirement Study. Historical change was indexed as cohort or birth year. The outcomes of focus were depressive symptoms, episodic memory, health conditions, functional limitations, and self-rated health.

RESULTS

Results revealed a differential pattern of racial disparities in historical change between midlife and old age. Across midlife and old age, on average, Blacks and Hispanics reported poorer levels of mental and physical health, compared with Whites. In midlife, racial disparities narrowed with historical time; later-born cohorts of Hispanics but not Whites reported fewer depressive symptoms than their earlier-born peers. Likewise, historical improvements in health were stronger among Hispanics and Blacks than Whites. Conversely, in old age, later-born cohorts across race consistently showed historical improvements in each of the outcomes examined. Regarding educational attainment, we observed little consistent evidence that health-promoting effects of educational attainment differ across race and cohort. Examining questions about heterogeneity, results revealed that in midlife and old age there was greater heterogeneity between race across each of the outcomes.

DISCUSSION

Our discussion elaborates on reasons behind the documented racial differences in historical changes among U.S. middle-aged and older adults, and how the protective role of education is changing over time.

How is the distribution of psychological distress changing over time? Who is driving these changes? Analysis of the 1958 and 1970 British birth cohorts

AIMS

The main objective of this study was to investigate distributional shifts underlying observed age and cohort differences in mean levels of psychological distress in the 1958 and 1970 British birth cohorts.

METHODS

This study used data from the 1958 and 1970 British birth cohorts (n = 24,707). Psychological distress was measured by the Malaise Inventory at ages 23, 33, 42 and 50 in the 1958 cohort and 26, 34, 42 and 46-48 in the 1970 cohort.

RESULTS

The shifts in the distribution across age appear to be mainly due to changing proportion of those with moderate symptoms, except for midlife (age 42-50) when we observed polarisation in distress- an increase in proportions of people with no symptoms and multiple symptoms. The elevated levels of distress in the 1970 cohort, compared with the 1958 cohort, appeared to be due to an increase in the proportion of individuals with both moderate and high symptoms. For instance, at age 33/34 42.3% endorsed at least two symptoms in the 1970 cohort vs 24.7% in 1958, resulting in a shift in the entire distribution of distress towards the more severe end of the spectrum.

CONCLUSIONS

Our study demonstrates the importance of studying not only mean levels of distress over time, but also the underlying shifts in its distribution. Due to the large dispersion of distress scores at any given measurement occasion, understanding the underlying distribution provides a more complete picture of population trends.

Cohort Variation in U.S. Violent Crime Patterns from 1960 to 2014: An Age-Period-Cohort-Interaction Approach

Objectives

Previous research in criminology has overlooked that cohort effects on crime should be age-time-specific (Ryder in Am Sociol Rev 30(6):843-861, 1965) and consequently assumed cohort effects to be the same across the life course. The current study addresses these limitations by modeling cohort effects as the differential impacts of social change depending on age groups. With this new operationalization that is closely tied to Ryder's conceptualization, we examine both inter-cohort differences and intra-cohort dynamics in violent crime.

Methods

We use the age-period-cohort-interaction (APC-I) model developed by Luo and Hodges (Sociol Methods Res 2020) to analyze the UCR age-specific arrest statistics for robbery, aggravated assaults, and homicide from 1960 to 2014. Specifically, we estimate and test two types of cohort variation: average cohort deviations and life-course dynamics.

Results

Our findings reveal varying degrees of cohort deviations at different ages. The early boomers (born between 1945 and 1954) and the late boomers (born between 1955 and 1964) demonstrate different intra-cohort dynamics of robbery arrest, and the violence epidemic cohorts' (born between 1975 and 1984) high risks of homicide arrest appear to be driven by cohort deviations at young ages.

Conclusions

The APC-I framework introduced in this study provides new insights into the dynamic aspect of cohort effects on violent crime that have not been examined in the criminological literature. Criminological studies on cohort effects would benefit by shifting away from the problematic assumption of constant and additive cohort effects to the dynamic and interactive approach represented by the APC-I framework.

Body image across the adult lifespan: A longitudinal investigation of developmental and cohort effects

The current study examined patterns of normative change and cohort effects in body image across the male and female adult lifespan. Body satisfaction was assessed in longitudinal data spanning six years, from 2010 to 2015. Cohort sequential latent growth curve modelling was utilized to assess patterns of mean-level change due to both aging and cohort effects in 15,264 participants (62.9 % women) aged between 18-94 years (M = 46.55, SD = 14.24). Results demonstrated a very slight increase in body satisfaction across the lifespan for both men and women. Cohort effects demonstrated that for women aged 54 years and below, all but two cohorts (24-29 and 34-39 years) displayed an upward trajectory in their body satisfaction over the 5-year period of assessment. No consistent cohort effects were evident for men. Finally, men, relative to women, consistently displayed higher levels of body satisfaction across the lifespan. This study provides insights into the trajectory of body image across the lifespan for men and women. The findings also suggest recent (cohort) improvements in body image for women, and potential explanations for this unexpected shift are discussed.

A recipe for accurate estimation of lifespan brain trajectories, distinguishing longitudinal and cohort effects

We address the problem of estimating how different parts of the brain develop and change throughout the lifespan, and how these trajectories are affected by genetic and environmental factors. Estimation of these lifespan trajectories is statistically challenging, since their shapes are typically highly nonlinear, and although true change can only be quantified by longitudinal examinations, as follow-up intervals in neuroimaging studies typically cover less than 10% of the lifespan, use of cross-sectional information is necessary. Linear mixed models (LMMs) and structural equation models (SEMs) commonly used in longitudinal analysis rely on assumptions which are typically not met with lifespan data, in particular when the data consist of observations combined from multiple studies. While LMMs require a priori specification of a polynomial functional form, SEMs do not easily handle data with unstructured time intervals between measurements. Generalized additive mixed models (GAMMs) offer an attractive alternative, and in this paper we propose various ways of formulating GAMMs for estimation of lifespan trajectories of 12 brain regions, using a large longitudinal dataset and realistic simulation experiments. We show that GAMMs are able to more accurately fit lifespan trajectories, distinguish longitudinal and cross-sectional effects, and estimate effects of genetic and environmental exposures. Finally, we discuss and contrast questions related to lifespan research which strictly require repeated measures data and questions which can be answered with a single measurement per participant, and in the latter case, which simplifying assumptions that need to be made. The examples are accompanied with R code, providing a tutorial for researchers interested in using GAMMs.

Are Advances in Survival Among the Oldest Old Seen Across the Spectrum of Health and Functioning?

BACKGROUND

Mortality rates have been reduced by half over the last 60 years for nonagenarians, and the progress is continuing. The greater survival might be due to overtreatment of severely physically and cognitively disabled individuals, which is a big concern for societies and individuals.

METHODS

The study population comprised two Danish birth cohorts: the 1905 Cohort and the 1915 Cohort. At age 95, all from the two cohorts who were still alive and living in Denmark were invited to participate in a health survey that used the same assessment instrument. A total of 2,670 (56.8%) persons participated in the two surveys and survival was assessed through a 7.3-year follow-up period during which 2,497 (93.5%) had died, and with virtually no loss to follow-up.

RESULTS

Despite the increasing chance of surviving to age 95, the 1915 Cohort had significantly better health and functioning than the 1905 Cohort. The survival advantage in the 1915 Cohort continued in the follow-up period after age 95: Median survival length was 2.4 months longer, p = .011. This advantage was not statistically associated with different levels of activities of daily living, physical performance, cognitive functioning, self-rated health and life satisfaction. However, the advantage tended to be more pronounced among people with better health.

CONCLUSIONS

Life span and health increases among the oldest old. The improvement in survival for 95-year olds born in 1915 compared with 1905 was seen across the whole spectrum of health and functioning, with a tendency towards bigger improvement among those in good health.

Differences in Cancer Mortality Trends between Metropolitan and Non-Metropolitan Areas in Japan, 1999-2018

Background:

Although socioeconomic statuses affect cancer mortality rates, the specific difference between metropolitan and non-metropolitan areas in Japan has not been evaluated. This study analyzed differences in cancer mortality between metropolitan and non-metropolitan areas in Japan, using an age-period-cohort (APC) analysis.

Methods:

Data on cancer mortality from 1999 to 2018 for metropolitan and non-metropolitan areas in Japan were used. Here metropolitan areas were defined as government ordinance-designated municipalities in 1999 and special wards of Tokyo. In addition to general mortality data for all cancer sites, data on mortality for stomach, colorectal, liver, gallbladder, pancreatic, lung, prostate, and breast cancers were used for analysis. A Bayesian APC analysis was administered to the data for each type of cancer for area and for sex-distinguished data. Additionally, the ratios for estimated mortality rate by periods and cohorts between the two areas were calculated.

Results:

The age-standardized mortality rate for cancer in all sites in non-metropolitan areas was lower than that in metropolitan areas throughout the analyzed years for both men and women, but the mortality difference decreased during the periods for men. The rates of decrease in mortality rate in cohorts differed for some cancers between the two area types, and the mortality rate ratios of metropolitan compared with non-metropolitan areas decreased for cancer in all sites over the analyzed cohorts for men. Also, the rate of decrease in mortality rate over the cohorts was completely different between the areas for stomach cancer in men and for liver cancer for women.

Conclusion:

Mortality rates for cancer in all sites tended to diverge between the two area types in younger cohorts for men, and people in younger cohorts in non-metropolitan areas should take more extensive preventive measures against cancer than their counterparts in metropolitan areas.

Changes in the depression gender gap from 1992 to 2014: Cohort effects and mediation by gendered social position

The depression gap (i.e., higher rates of depression among women than men) represents an important mental health disparity in the US. Differences in gendered social position (i.e., the roles, responsibilities, and opportunities available to women and men), which have been changing since the mid-20th Century may contribute to this gender gap. The present study examined the evidence for a changing depression gap across birth cohorts and tested the extent to which any changes over time were mediated by changes in relative social position between women and men. Data were from the National Longitudinal Surveys. The depression gap was defined as differences in mean CESD scores for women vs. men. The analytic sample included 13,666 respondents interviewed from 1992 to 2014. Hierarchical mixed models estimated the magnitude of the gender depression gap over time, its association with 10-year birth cohort (range: 1957-1994), and whether any variation was mediated by ratios among women relative to men of obtaining a college degree, being employed full-time, and the average number of hours spent doing housework per week, three indicators of gendered social position. There was a linear decrease in the depression gap by 0.18 points across birth cohort (95% CI = -0.26, -0.10). The results of the mediation analysis estimated that an increasing ratio of college degree attainment mediated 39% of the gender depression gap across cohorts (95% CI = 0.18, 0.78). There was no evidence of mediation due to changing employment or housework ratios. These findings partially support the hypothesis that the depression gap is changing over time and is meaningfully related to the social environment. Understanding the social causes of the depression gap can illuminate the fundamental processes through which depression disparities may be perpetuated or attenuated over time and may aid in the identification of strategies to reduce them.

Age-Period-Cohort Analysis of the Sex Differences in Cancer Mortality Rates in Japan from 1995 to 2015

BACKGROUND

The current study aimed to analyze the sex differences in cancer mortality rates in Japan via an age-period-cohort (APC) analysis.

METHODS

We used data about cancer mortality rates from 1995 to 2015 in Japan based on the Vital Statistics survey. In addition to the data about mortality from all sites of cancer, we specifically used data about stomach, lung, colorectal, and liver cancers. A Bayesian APC analysis was performed to identify changes in mortality rates based on three effects, which were as follows: age, period, and cohort. Then, we finally calculated the mortality rate ratios for each effect between men and women.

RESULTS

The sex differences in age-adjusted mortality rates for all-sites cancer, lung cancer, and liver cancer were decreasing from 1995 to 2015, and the mortality rate ratios in terms of sex decreased from 2.17 in 1995 to 1.93 in 2015. Based on the results of the APC analyses, only minimal changes were observed in the mortality rate ratios for all types of cancer between men and women during the analyzed periods. The cohort effects began to decrease from the early 20th century in all types of cancer in both men and women, and the mortality rate ratios for all types of cancer between men and women began to increase in the cohorts born from 1926 to 1935. For all-sites cancer, the ratio increased from 0.49 (0.44, 0.57) in the cohort born from 1926 to 1930 to 0.81 (0.60, 1.03) in the cohort born from 1971 to 1975.

CONCLUSION

The sex differences in cancer mortality rates were decreasing in the more recent born generations in Japan. If this trend continues, there will be a minimal difference in the morality rates in the following generations.<br />.

Life Expectancy: Frequently Used, but Hardly Understood

Period life expectancy is one of the most used summary indicators for the overall health of a population. Its levels and trends direct health policies, and researchers try to identify the determining risk factors to assess and forecast future developments. The use of period life expectancy is often based on the assumption that it directly reflects the mortality conditions of a certain year. Accordingly, the explanation for changes in life expectancy are typically sought in factors that have an immediate impact on current mortality conditions. It is frequently overlooked, however, that this indicator can also be affected by at least three kinds of effects, in particular in the situation of short-term fluctuations: cohort effects, heterogeneity effects, and tempo effects. We demonstrate their possible impact with the example of the almost Europe-wide decrease in life expectancy in 2015, which caused a series of reports about an upsurge of a health crisis, and we show that the consideration of these effects can lead to different conclusions. Therefore, we want to raise an awareness concerning the sensitivity of life expectancy to sudden changes and the menaces a misled interpretation of this indicator can cause.

A generalized additive model to disentangle age and diagnosis-specific cohort effects in psychological and behavioral outcomes in people living with HIV: the French cross-sectional ANRS-VESPA2 survey

BACKGROUND

Unlike their younger counterparts, some of today's older HIV patients were diagnosed before the advent of highly active antiretroviral therapy (HAART). The psychosocial and behavioral outcomes of people living with HIV (PLWH) have been widely studied, and associated factors are well known. However, their evolution both in terms of age and diagnosis-specific cohort effects is not well understood.

METHODS

Data from the ANRS-VESPA2 cross-sectional survey, representative of French PLWH, were used to investigate whether psychosocial and behavioral outcomes such as quality of life, need for support and HIV status disclosure, evolve under both the influence of patients' age and diagnosis-specific cohort effects. A semi-parametric generalized additive model (GAM) was employed. The physical and mental components of health-related quality of life, the need for material and moral support, and HIV-status disclosure, constituted our outcomes.

RESULTS

Non-linear diagnosis-specific cohort effects were found for physical and mental QoL and HIV-status disclosure. Overall, physical QoL was better in recently diagnosed patients than in those diagnosed in the early 1980s. An increasing influence of diagnosis-specific cohort effects between 1983 and 1995 was observed. No cohort effects were noticeable between 1996 and 2000, while an increasing influence was apparent for patients diagnosed with HIV from 2000 to 2011 (year of study). For mental QoL, the only increase was observed in participants diagnosed with HIV between 1983 and 2000. The relationship between diagnosis-specific cohort effects and HIV status disclosure was negative overall: participants diagnosed after 2000 were much less likely to disclose than those diagnosed before 1995. The effect of age was significantly associated with all outcomes, with a non-linear influence on mental QoL and with the need for material/moral support.

CONCLUSIONS

Psychosocial and behavioral outcomes are complex processes which can be explained in different ways by a combination of the clinical and social contexts which PLWH are exposed to at the time of diagnosis, and by developmental characteristics. A greater understanding of these processes could inform healthcare policy-making for specific HIV generations and different HIV age groups.

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.

Changes in the Lethality of Frailty Over 30 Years: Evidence From Two Cohorts of 70-Year-Olds in Gothenburg Sweden

Background

With aging, health deficits accumulate: people with few deficits for their age are fit, and those with more are frail. Despite recent reports of improved health in old age, how deficit accumulation is changing is not clear. Our objectives were to evaluate changes over 30 years in the degree of deficit accumulation and in the relationship between frailty and mortality in older adults.

Methods

We analyzed data from two population based, prospective longitudinal cohorts, assembled in 1971-1972 and 2000-2001, respectively. Residents of Gothenburg Sweden, systematically drawn from the Swedish population registry. The 1901-1902 cohort (N = 973) had a response rate of 84.8%; the 1930 cohort (N = 500) had a response rate of 65.1%. A frailty index using 36 deficits was calculated using data from physical examinations, assessments of physical activity, daily, sensory and social function, and laboratory tests. We evaluated mortality over 12.5 years in relation to the frailty index.

Results

Mean frailty levels were the same (x¯ = 0.20, p = .37) in the 1901-1902 cohort as in the 1930 cohort. Although the frailty index was linked to the risk of death in both cohorts, the hazards ratio decreased from 1.67 per 0.1 increment in the frailty index for the first cohort to 1.32 for the second cohort (interaction term p = .005).

Discussion

Although frailty was as common at age 70 as before, its lethality appears to be less. Just why this is so should be explored further.

Better Cognition in New Birth Cohorts of 70 Year Olds, But Greater Decline Thereafter

OBJECTIVES

To evaluate birth cohort differences in level of cognition and rate of change in old age.

METHODS

Data were drawn from three population-based Swedish samples including age-homogenous cohorts born 1901/02, 1906/07, and 1930, and measured on the same cognitive tests at ages 70, 75, and 79 as part of the Gerontological and Geriatric Populations Studies in Gothenburg (H70). We fitted growth curve models to the data using a Bayesian framework and derived estimates and inferences from the marginal posterior distributions.

RESULTS

We found moderate to large birth cohort effects in level of performance on all cognitive outcomes. Later born cohorts, however, showed steeper linear rate of decline on reasoning, spatial ability, and perceptual- and motor-speed, but not on picture recognition memory and verbal ability.

DISCUSSION

These findings provide strong evidence for substantial birth cohort effects in cognition in older ages and emphasize the importance of life long environmental factors in shaping cognitive aging trajectories. Inferences from cognitive testing, and standardization of test scores, in elderly populations must take into account the substantial birth cohort differences.

Estimating direct effects of parental occupation on Spaniards' health by birth cohort

Background

Social health inequalities in adult population are partly due to socioeconomic circumstances in childhood. A better understanding of how those circumstances affect health during adulthood may improve the opportunities for reducing health disparities. The objective of this study is to investigate the effect of parental socioeconomic status, which is proxied by occupation, on adult Spaniards’ health by birth cohort. The analysis will allow checking not only the direct impact of parental occupation on their offspring’s health, but also whether inherited inequality has been reduced over time.

Methods

We use data from the Bank of Spain’s Survey of Household Finances on Spanish households from 2002 to 2008. Sequential models were used to estimate the influence of the father’s and mother’s occupation on their offspring’s health, trying to disentangle direct from indirect effects. With a sample of 26,832 persons we consider effects for four different cohorts by birth periods ranging from 1916 to 1981.

Results

The results show that parental occupation has a significant direct impact on individuals’ health (p < 0.01). The effect of father’s occupation exceeds that of mother’s. For those born before 1936, the probability of reporting a good health status ranges from 0.31 (95% confidence interval (CI) 0.14–0.48), when fathers were classified as unskilled elementary workers, to 0.98 (95% CI 0.98–0.99) when they were managers or mid-level professionals. For those born during the period 1959–1975, those probabilities are 0.49 (95% CI 0.39–0.59) and 0.97 (95% CI 0.96–0.98), respectively. Therefore, health inequalities linked to parental socioeconomic status have been noticeably reduced, although discrimination against unskilled workers persists over time.

Conclusions

Great progress has been made in the health area during the twentieth century, so that the impact of parental socioeconomic status on individuals’ health has been significantly tempered for those at the bottom of the social scale. However, more efforts focused on the improvement of living conditions for most socioeconomically disadvantaged are needed in order to further reduce social inequalities in health.

Why did Danish women's life expectancy stagnate? The influence of interwar generations' smoking behaviour

The general health status of a population changes over time, generally in a positive direction. Some generations experience more unfavourable conditions than others. The health of Danish women in the interwar generations is an example of such a phenomenon. The stagnation in their life expectancy between 1977 and 1995 is thought to be related to their smoking behaviour. So far, no study has measured the absolute effect of smoking on the mortality of the interwar generations of Danish women and thus the stagnation in Danish women's life expectancy. We applied a method to estimate age-specific smoking-attributable number of deaths to examine the effect of smoking on the trends in partial life expectancy of Danish women between age 50 and 85 from 1950 to 2012. We compared these trends to those for women in Sweden, where there was no similar stagnation in life expectancy. When smoking-attributable mortality was excluded, the gap in partial life expectancy at age 50 between Swedish and Danish women diminished substantially. The effect was most pronounced in the interwar generations. The major reason for the stagnation in Danish women's partial life expectancy at age 50 was found to be smoking-related mortality in the interwar generations.

Clarifying hierarchical age-period-cohort models: A rejoinder to Bell and Jones

Previously, Reither et al. (2015) demonstrated that hierarchical age-period-cohort (HAPC) models perform well when basic assumptions are satisfied. To contest this finding, Bell and Jones (2015) invent a data generating process (DGP) that borrows age, period and cohort effects from different equations in Reither et al. (2015). When HAPC models applied to data simulated from this DGP fail to recover the patterning of APC effects, B&J reiterate their view that these models provide "misleading evidence dressed up as science." Despite such strong words, B&J show no curiosity about their own simulated data--and therefore once again misapply HAPC models to data that violate important assumptions. In this response, we illustrate how a careful analyst could have used simple descriptive plots and model selection statistics to verify that (a) period effects are not present in these data, and (b) age and cohort effects are conflated. By accounting for the characteristics of B&J's artificial data structure, we successfully recover the "true" DGP through an appropriately specified model. We conclude that B&Js main contribution to science is to remind analysts that APC models will fail in the presence of exact algebraic effects (i.e., effects with no random/stochastic components), and when collinear temporal dimensions are included without taking special care in the modeling process. The expanded list of coauthors on this commentary represents an emerging consensus among APC scholars that B&J's essential strategy--testing HAPC models with data simulated from contrived DGPs that violate important assumptions--is not a productive way to advance the discussion about innovative APC methods in epidemiology and the social sciences.

Should age-period-cohort analysts accept innovation without scrutiny? A response to Reither, Masters, Yang, Powers, Zheng and Land

This commentary clarifies our original commentary (Bell and Jones, 2014c) and illustrates some concerns we have regarding the response article in this issue (Reither et al., 2015). In particular, we argue that (a) linear effects do not have to be produced by exact linear mathematical functions to behave as if they were linear, (b) linear effects by this wider definition are extremely common in real life social processes, and (c) in the presence of these effects, the Hierarchical Age Period Cohort (HAPC) model will often not work. Although Reither et al. do not define what a 'non-linear monotonic trend' is (instead, only stating that it isn't a linear effect) we show that the model often doesn't work in the presence of such effects, by using data generated as a 'non-linear monotonic trend' by Reither et al. themselves. We then question their discussion of fixed and random effects before finishing with a discussion of how we argue that theory should be used, in the context of the obesity epidemic.

Variation in early-life telomere dynamics in a long-lived bird: links to environmental conditions and survival

Conditions experienced during early life can have profound consequences for both short- and long-term fitness. Variation in the natal environment has been shown to influence survival and reproductive performance of entire cohorts in wild vertebrate populations. Telomere dynamics potentially provide a link between the early environment and long-term fitness outcomes, yet we know little about how the environment can influence telomere dynamics in early life. We found that environmental conditions during growth have an important influence on early-life telomere length (TL) and attrition in nestlings of a long-lived bird, the European storm petrel Hydrobates pelagicus. Nestlings reared under unfavourable environmental conditions experienced significantly greater telomere loss during postnatal development compared with nestlings reared under more favourable natal conditions, which displayed a negligible change in TL. There was, however, no significant difference in pre-fledging TL between cohorts. The results suggest that early-life telomere dynamics could contribute to the marked differences in life-history traits that can arise among cohorts reared under different environmental conditions. Early-life TL was also found to be a significant predictor of survival during the nestling phase, providing further evidence for a link between variation in TL and individual fitness. To what extent the relationship between early-life TL and mortality during the nestling phase is a consequence of genetic, parental and environmental factors is currently unknown, but it is an interesting area for future research. Accelerated telomere attrition under unfavourable conditions, as observed in this study, might play a role in mediating the effects of the early-life environment on later-life performance.

Should age-period-cohort studies return to the methodologies of the 1970s?

Social scientists have recognized the importance of age-period-cohort (APC) models for half a century, but have spent much of this time mired in debates about the feasibility of APC methods. Recently, a new class of APC methods based on modern statistical knowledge has emerged, offering potential solutions. In 2009, Reither, Hauser and Yang used one of these new methods - hierarchical APC (HAPC) modeling - to study how birth cohorts may have contributed to the U.S. obesity epidemic. They found that recent birth cohorts experience higher odds of obesity than their predecessors, but that ubiquitous period-based changes are primarily responsible for the rising prevalence of obesity. Although these findings have been replicated elsewhere, recent commentaries by Bell and Jones call them into question - along with the new class of APC methods. Specifically, Bell and Jones claim that new APC methods do not adequately address model identification and suggest that "solid theory" is often sufficient to remove one of the three temporal dimensions from empirical consideration. They also present a series of simulation models that purportedly show how the HAPC models estimated by Reither et al. (2009) could have produced misleading results. However, these simulation models rest on assumptions that there were no period effects, and associations between period and cohort variables and the outcome were perfectly linear. Those are conditions under which APC models should never be used. Under more tenable assumptions, our own simulations show that HAPC methods perform well, both in recovering the main findings presented by Reither et al. (2009) and the results reported by Bell and Jones. We also respond to critiques about model identification and theoretically-imposed constraints, finding little pragmatic support for such arguments. We conclude by encouraging social scientists to move beyond the debates of the 1970s and toward a deeper appreciation for modern APC methodologies.

Age, sex, and racial differences in harsh physical punishment: results from a nationally representative United States sample

The purpose of this research was to examine age, sex, and racial differences in the prevalence of harsh physical punishment in childhood in a nationally representative sample of the United States. Data were from the National Epidemiologic Survey on Alcohol and Related Conditions (NESARC) collected in 2004 and 2005 (n=34,653). Logistic regression analyses were conducted to examine age, sex, and racial differences in the prevalence of harsh physical punishment. Results suggest that the prevalence of harsh physical punishment has been decreasing among more recently born age groups; however, there appear to be sex and racial differences in this trend over time. The magnitude of the decrease appears to be stronger for males than for females. By race, the decrease in harsh physical punishment over time is only apparent among Whites; Black participants demonstrate little change over time, and harsh physical punishment seems to be increasing over time among Hispanics. Prevention and intervention efforts that educate about the links of physical punishment to negative outcomes and alternative non-physical discipline strategies may be particularly useful in reducing the prevalence of harsh physical punishment over time.

Mortality cohort effects from mid-19th to mid-20th century Britain: did they exist?

PURPOSE

Identification is a central problem with age-period-cohort analysis. Because age + cohort = period, there is no unique solution to the linear effect using generalized linear modeling, but cohort effects have caused greater controversy than age and period effects. To illustrate the magnitude of cohort effects given the presence of collinearity, we reanalyze data from the seminal study by Kermack et al, with an update.

METHODS

Relative mortality data in England and Wales between year 1845 and 1995 were analyzed using partial least squares regression. There were seven age groups ranging from 5 to 74 years old and 16 periods with 22 cohorts.

RESULTS

Our reanalysis seemed to support the existence of cohort effects in the mortality trends. Period and cohort effects were generally consistent with changes in the social, economic, and environmental factors taking place in the last two centuries. Our analysis also showed a declining trend in period effects up to 1950s.

CONCLUSIONS

Partial least squares and related methods provide intuitive pointers toward the separation of linear age, period, and cohort effects. Because statistical algorithms cannot distinguish between relative and actual mortality rates, cohort effects may be underestimated because of contamination by negative age effects.

Birth cohort differences in the prevalence of longevity-associated variants in APOE and FOXO3A in Danish long-lived individuals

Gene variants found to associate with human longevity in one population rarely replicate in other populations. The lack of consistent findings may partly be explained by genetic heterogeneity among long-lived individuals due to cohort differences in survival probability. In most high-income countries the probability of reaching e.g. 100years increases by 50-100% per decade, i.e. there is far less selection in more recent cohorts. Here we investigate the cohort specificity of variants in the APOE and FOXO3A genes by comparing the frequencies of the APOE ε4 allele and the minor alleles of two variants in FOXO3A at age 95+ and 100+ in 2712 individuals from the genetically homogeneous Danish birth cohorts 1895-96, 1905, 1910-11, and 1915. Generally, we find a decrease in the allele frequencies of the investigated APOE and FOXO3A variants in individuals from more recent birth cohorts. Assuming a recessive model, this negative trend is significant in 95+ year old individuals homozygous for the APOE ε4 allele (P=0.026) or for the FOXO3A rs7762395 minor allele (P=0.048). For the APOE ε4 allele, the significance is further strengthened when restricting to women (P=0.006). Supportive, but non-significant, trends are found for two of the three tested variants in individuals older than 100years. Altogether, this indicates that cohort differences in selection pressure on survival to the highest ages are reflected in the prevalence of longevity gene variants. Although the effect seems to be moderate, our findings could have an impact on genetic studies of human longevity.

The role of under-employment and unemployment in recent birth cohort effects in Australian suicide

High suicide rates evident in Australian young adults during an epidemic period in the 1990s appear to have been sustained in older age-groups in the subsequent decade. This period also coincides with changes in employment patterns in Australia. This study investigates age, period, and birth cohort effects in Australian suicide over the 20th century, with particular reference to the period subsequent to the 1990s youth suicide epidemic in young males. Period- and cohort-specific trends in suicide were examined for 1907-2010 based on descriptive analysis of age-specific suicide rates and a series of age-period-cohort (APC) models using Poisson regression. Under-employment rates (those employed part-time seeking additional hours of work) and unemployment rates (those currently seeking employment) for the latter part of this time series (1978-2010) were also examined and compared with period- and cohort-specific trends in suicide. A significant increasing birth cohort effect in male suicide rates was evident in birth cohorts born after 1970-74, after adjusting for the effects age and period. An increasing birth cohort effect was also evident in female suicide rates, but was of a lesser magnitude. Increases in male cohort-specific suicide rates were significantly correlated with increases in cohort-specific under-employment and unemployment rates. Birth cohorts that experienced the peak of the suicide epidemic during the 1990s have continued to have higher suicide rates than cohorts born in earlier epochs. This increase coincides with changes to a labour force characterised by greater 'flexibility' and 'casualised' employment, especially in younger aged cohorts.

Density dependence in a fluctuating wild reindeer herd; maternal vs. offspring effects

The Hardangervidda wild reindeer herd in Norway is the largest in Western Europe. It has fluctuated between 7000 and 32000 animals during the last 35 years. Four density-dependent effects were found: 1. A food limitation effect due to a shift in diet after overgrazing lichen on the winter range. This led to increased tooth wear and lowered body size and fat reserves. 2. A significant correlation between population density and juvenile winter survival rate. No effect on adult female survival rate was found. 3. A cohort effect. After population increase and overgrazing, recruitment was reduced by 30% and remained so after population reduction. Birth weights had increased by 30% 5 years after population reduction and the mean calving time was earlier. As a result, after population reduction weights of newborns were 40% greater at a comparable date. Neonatal survival rate was related to maternal condition during the last part of gestation which coincides with the peak winter snow accumulation. The slow increase in adult dressed body weights (DBW) after population reduction is due to the combined effects of increased tooth wear when winter range was limiting and to the cohort-generation time, so that an improvement in neonatal survival and size was first expressed in subsequent offspring cohorts. 4. An inter-generation effect. During 30 years of resource limitation, DBW decreased by 23%, birth rate was unchanged after the first peak, while fecundity increased by 15%, suggesting increased reproductive effort per unit body weight. Natural selection for increased reproductive effort by smaller females when food was limiting was suggested. Some size-effect due to hunters selecting the largest adult phenotypes was possible but not the main cause. These results do not support some earlier hypotheses about the effects of population density on size at maturity in ungulates.