Bounding Analyses of Age-Period-Cohort Effects

Incidence trends and spatial distribution of thyroid cancer in the Chinese female population from 1990 to 2019

Objective

This study aimed to analyze the incidence trends and spatial distribution characteristics of thyroid cancer among Chinese females from 1990 to 2019, thereby providing a scientific foundation and data support for the development of prevention and control policies.

Methods

Thyroid cancer incidence data from the Global Burden of Disease (GBD) research and the annual report from the Chinese Tumor Registration were utilized. The standardized thyroid cancer incidence rate among Chinese females 1990 to 2019 was described to understand the changes in developmental trends. The JoinPoint Regression Model was employed using Excel 2019, GraphPad Prism 8, JoinPoint Regression Program 4.8.0.1, and ArcGIS 10.2.

Results

Thyroid cancer's standardized incidence among female Chinese continued to increase at 1.7% per year (annual average percentage change [AAPC] = 1.7, P < 0.001), and the spatial distribution was clustered. The main high-incidence areas were North, East, and Northwest China.

Conclusions

Thyroid cancer incidence in Chinese women is rapidly increasing, and its spatial distribution is concentrated. Strengthening monitoring, prevention, and control efforts in the relevant areas is warranted.

Distinct time trends in colorectal cancer incidence in countries with SDI levels from 1990 to 2019: an age-period-cohort analysis for the Global Burden of Disease 2019 study

Introduction

The burden of colorectal cancer (CRC) plays a pivotal role in the global cancer epidemic. Our study reported the incidence trends in CRC and the associated effects of age, period, and birth cohort in 204 countries and territories over the past 30 years.

Methods

The incidence data of CRC were extracted from the Global Burden of Disease Study (GBD) 2019. We performed the age-period-cohort (APC) model to estimate the overall annual percentage change (net drift) in the incidence rate, the annual percentage change by age group (local drift), and the relative risk (period and cohort effects) of the period and cohort in CRC during 1990-2019. This approach allows examining and distinguishing age, period, and cohort effects in incidence and potentially distinguishing colorectal cancer gaps in prevention and screening.

Results

In 2019, the incidence of CRC was 2.17 (95% UI 2.00-2.34) million, of which China, the United States of America, and Japan had the highest incidence population, accounting for 45.9% of the global population. The age-standardized incidence rate (ASIR) was 26.7 (95% UI 28.9-24.6) per 100,000 people, of which 30 countries had an incidence rate greater than 40.0 per 100,000 people. From 1990 to 2019, the middle SDI region had the largest increase in incidence rate, with a net drift of 2.33% (95% CI 2.2-2.46%, p < 0.001). Globally, the incidence population was concentrated in the age group of 50-69 years, and the age group of 30-34 years had the largest increase in incidence rate (local drift 1.19% (95% CI 1.01-1.37%)). At the same time, the sex and age distributions of CRC incidence had significant heterogeneity across regions and countries. In the past 30 years, the incidence rate in 31 countries has been well controlled (net drift <0), and most of them were concentrated in high-and high-middle-SDI regions, such as Australia, Czechia, and Belgium, and the relative risk of incidence generally improved over time and consecutive young birth cohorts. CRC incidence showed an unfavorable trend (net drift ≥1%) in 89 countries, of which 27 countries were more significant (net drift >2%), mostly concentrated in the middle SDI region, such as China, Mexico, and Brazil, and the risk of period and birth cohort was unfavorable.

Conclusion

Globally, the incidence of CRC has shown an overall upward trend over the past 30 years, with the exception of some countries with higher SDI values. Significant age-period-cohort differences were observed in the risk of incidence in CRC worldwide. Effective prevention and control policies need to take into account the age-period-cohort effect characteristics of different regions.

Assessing the "healthy immigrant effect" in mental health: Intra- and inter-cohort trends in mood and/or anxiety disorders

BACKGROUND

The healthy immigrant effect implies that, at the time of immigration, new immigrants are typically healthier than the Canadian-born population. Furthermore, this health advantage fades the longer cohorts of immigrants remain in the host country.

METHODS

Most studies assessing the healthy immigrant effect rely on strong, untestable assumptions to extract unique effects for length of stay (LOS) (i.e., how long an immigrant has been in a host country), period (i.e., year of observation), and cohort (i.e., year of immigration). Rather than attempting to parse out separate effects for LOS, period, and cohort, we adopt a descriptive, cohort-centric approach to study immigrant mental health, which examines intra- and inter-cohort trends, that is, joint LOS-period and cohort-period parameters, respectively. While intra-cohort trends show how immigrants' mental health change with LOS across periods, inter-cohort trends reveal how the mental health of successive cohorts of immigrants differ across time periods. To provide a thorough assessment of the healthy immigrant effect, we use both survey and administrative data on cohorts of Canadian immigrants from 2003 to 2013.

RESULTS

The survey data reveal that mental health declines steeply (i.e., there is an increase in mood and/or anxiety disorders) within and across immigrant cohorts, while the administrative data show little overall change in mental health care utilization within and across cohorts. The divergent results may reflect issues related to barriers in access to mental health services because the administrative data, which are based on health care utilization, do not the capture the increase in mental disorders seen in the survey data.

CONCLUSION

This study highlights the benefit of a cohort-based approach to assess the healthy immigrant effect as it pertains to mental health as well as the importance of using different types of data, which may be measuring different aspects of immigrant mental health and health care utilization.

Are generations a useful concept?

The concepts of generations and generational differences have received much attention in the academic literature, in the popular press, and among practitioners, policymakers, and politicians. Despite the continued interest, research has failed to find convincing evidence for the existence of distinct generations, commonly conceptualized as broad groupings of birth cohorts (e.g., 1980-2000) that have been influenced by a set of significant events (e.g., economic depressions) and labeled with names and qualities that supposedly reflect their defining characteristics (e.g., Millennials). Further, any differences that have been found in empirical studies, and that have been attributed to generational membership, are more likely due to age and/or contemporaneous period effects. Nonetheless, some researchers, employers, institutions, governments, and many laypeople continue to treat generations like they are a powerful and actionable phenomenon. We address these issues in two ways. First, we review the science of generations, focusing on what is known, what is not, and why the evidence points to the conclusion that generations, as popularly conceptualized, do not exist in objectively quantifiable ways. We also address the disconnect between science and practice regarding generations. Second, we explore alternate explanations for effects that are attributed to generations and review approaches that are both more theoretically sound and empirically supported, including lifespan theory and social constructionist frameworks. Finally, we address connections between assumptions made about generations and concerns about diversity, equity, and inclusion at work. Specifically, we address what has been termed generationalism, the belief that members of specific generations possess unique, stereotypic characteristics.

The long-term trend of uterine fibroid burden in China from 1990 to 2019: A Joinpoint and Age-Period-Cohort study

Purpose: Uterine fibroids occur in 40%-60% of women and are symptomatic in 30% of the patients by causing abnormal uterine bleeding, pelvic pressure, pain, and infertility. The study aims to evaluate the long-term trend of uterine fibroids mortality and disability-adjusted life years (DALYs) in China and the relative risks of age, period, and birth cohort effects. Methods: The mortality and DALYs of uterine fibroids from 1990 to 2019 were derived from the Global Burden of Disease 2019. The annual percentage change and average annual percent change (AAPC) were assessed using the Joinpoint regression. The effects of age, period, and birth cohort on death and DALYs were analyzed by the Age-Period-Cohort framework. Results: The age-standardized rates were all on the ascending trend, with the greatest increase in the age-standardized mortality rate (AAPC, 1.53; 95% CI, 1.04-2.02). The net drift was found to be 3.51% (95% CI, 2.25%-4.78%) per year for mortality and 0.34% (95% CI, 0.14%-0.53%) per year for DALYs. Significant age, period, and birth cohort effects were found for mortality and DALYs (p < 0.001 for all). The mortality risk increased overall with age, but the DALYs risk increased first and then decreased with age. The period and birth cohort risks for mortality and DALYs showed different trends. Conclusion: These secular time trends and changes of mortality and DALYs reveal the socioeconomic alterations, reform of diagnosis and therapy, and changes in social lifestyles and behaviors. Uterine fibroids are still the most common benign gynecological tumors in women, and more epidemiological investigations and social health prevention and control should be applied.

Epidemiological Analysis of HIV/AIDS in Kazakhstan During 2018-2020

BACKGROUND

The human immunodeficiency virus (HIV) is a severe threat to public health everywhere, including the Central Asian region and Kazakhstan. The aim of the study was to conduct an epidemiological analysis of newly diagnosed cases of HIV infection during 2018-2020.

STUDY DESIGN

A case series study.

METHODS

A descriptive analysis of national data on registered cases of HIV in Kazakhstan was conducted, and demographic information was collected and studied accordingly. The analysis of the influence of age, period, and cohort was performed using the age-period-cohort method.

RESULTS

Based on the results, men prevailed (68.5%) among all cases of HIV infection (n=1235). Sexual transmission during heterosexual contact was higher in females (88.9%, P=0.005), and the number of new cases as a result of homosexual contact was higher in men (23.0%, P=0.087). In addition, the parenteral route of HIV transmission cases prevailed among men (27.5%, P=0.001), and intravenous drug administration was more common among males (27.4%, P=0.01). Moreover, 68.5% of men and 33.2% of women had a low therapy adherence. In men, the risk of HIV prevalence increased after 32.5 years (deviation [Dv]: 0.134, 95% confidence interval [CI]=0.096 to 0.364). At the age of 37.5 years, there was an increase (Dv: 0.852, 95% CI=0.626 to 1.079) in HIV prevalence. However, no peaks were observed in women.

CONCLUSION

Our findings indicated a rise in the prevalence of HIV infection in Kazakhstan. Men aged 37 and older were identified as the risk category. Eventually, inadequate adherence to treatment was observed in HIV/acquired immunodeficiency syndrome patients.

It Runs in the Family: Testing for Longitudinal Family Flynn Effects

The Flynn effect refers to increases over time in measured (particularly fluid) intelligence of approximately 3 IQ points per decade. We define the Flynn effect at the family level, using longitudinal data and two new family-level cohort definitions. Multilevel growth curve analyses of the National Longitudinal Survey of Youth 1979 data showed that children in families with later-born mothers had higher average PIAT math scores, and lower average reading comprehension scores and growth, in young and middle childhood. Children in families where the first child was born later had higher average PIAT math, reading recognition, and reading comprehension scores, as well as larger developmental growth. The latter family-level Flynn effects were of higher magnitudes than the usual individual-level Flynn effect found in previous studies. Our results, showing family level-intercept and slope Flynn effects for both maternal birthyear and first child birthyear, have implications for research aiming to explain the Flynn effect.

Children of the Revolution: The continued unevenness of the gender revolution in housework, childcare and work time across birth cohorts

This study investigates whether parents spend different amounts of time in housework, childcare, and employment across birth cohorts. We apply data from the American Time Use Survey (ATUS; 2003-2018) and age-cohort-period models to compare parents' time spent in these activities across three successive birth cohorts: Baby Boomers (1946-1965), Generation X (1966-1980) and Millennials (1981-2000). For housework time, we find no evidence of cohort change for mothers but for fathers, we observe an increase in housework time with each subsequent cohort. For time spent caring for children, we identify a period effect whereby mothers and fathers regardless of which cohort they belong to are spending more time in primary care of children over time. For work time, we find an increase in mothers' contributions across these birth cohorts. But, net of this overall trend, we find Generation X and Millennial mothers are spending less time in employment relative to Baby Boom mothers. Fathers' employment time, by contrast, has not changed across cohorts or over our measured period. Ultimately, we find gender gaps in childcare, housework and employment across cohorts remain suggesting cohort replacement and period effects are inadequate to close gender gaps in housework, childcare and paid employment time.

The evolution of demographic methods

Demographic methods have been evolving ever since the birth of demography in response to changes in the field's research contents and theoretical orientations. An early core mission of finding regularities underlying macro-level population phenomena and a later interest in explaining population changes inductively facilitated the development of formal demographic techniques. A more radical methodological shift occurred after the 1960s, with the increasing availability of micro-level survey data and a shift of theoretical focus toward causal mechanisms, leading to the widespread adoption of regression-based models and methods from other social science disciplines. The future development of demographic methods will likely continue to incorporate new methods first developed in other disciplines, including techniques for analyzing unstructured "big" data, but formal demographic techniques will still play a role in population forecasting, measurements improvements, and correction of faulty data, providing foundational knowledge for other social science disciplines.

Beliefs about harms of cigarette smoking among Norwegian adults born from 1899 to 1969. Do variations across education, smoking status and sex mirror the decline in smoking?

Background and aim

Smoking is one of the most important causes of socioeconomic disparities in morbidity and mortality. The aim of this study was to examine if beliefs about harms of smoking differed across gender, smoking status and education among Norwegian adults born between 1899 and 1969.

Methods

Using data from a nationally representative survey of smoking habits and a multinomial logit/negative binomial two-stage hurdle model design, we examined (first hurdle) the associations between birth cohort, gender, education and smoking status and four beliefs about cigarette smoking: i) smoking is not harmful, ii) do not know if smoking is harmful, iii) any number of cigarettes per day (CPD) is harmful and iv) smoking more than a given nonzero number of CPD is harmful, and (second hurdle) the predicted number of CPD that could be smoked without causing harm (from outcome iv).

Results

The probability of believing that smoking was not harmful was close to zero, regardless of birth cohort, sex, education and smoking status. The probability of not knowing if smoking was harmful decreased from around 0.7 to almost zero across cohorts. The probability of believing that smoking more than zero CPD was harmful increased from less than 0.1 to around 0.7, while the probability of believing that there is some safe level of smoking increased with cohorts born from 1900 to 1930 before declining. Respondents with primary/secondary education consistently believed smoking to be less harmful compared to respondents with tertiary education, but cohort trajectories were similar.

Discussion

The similar birth cohort trajectories in beliefs about the harms of smoking do not support the idea that Norwegian adults with lower education has had qualitatively different beliefs about the harmfulness of smoking compared to those with higher education. The persistent and large socioeconomic gradient is likely a result of other factors.

The Age-Period-Cohort-Interaction Model for Describing and Investigating Inter-cohort Deviations and Intra-cohort Life-course Dynamics

Social scientists have frequently sought to understand the distinct effects of age, period, and cohort, but disaggregation of the three dimensions is difficult because cohort = period - age. We argue that this technical difficulty reflects a disconnection between how cohort effect is conceptualized and how it is modeled in the traditional age-period-cohort framework. We propose a new method, called the age-period-cohort-interaction (APC-I) model, that is qualitatively different from previous methods in that it represents Ryder's (1965) theoretical account about the conditions under which cohort differentiation may arise. This APC-I model does not require problematic statistical assumptions and the interpretation is straightforward. It quantifies inter-cohort deviations from the age and period main effects and also permits hypothesis testing about intra-cohort life-course dynamics. We demonstrate how this new model can be used to examine age, period, and cohort patterns in women's labor force participation.

Trends in "Deaths of Despair" Among Working-Aged White and Black Americans, 1990-2017

Life expectancy for US White men and women declined between 2013 and 2017. Initial explanations for the decline focused on increases in "deaths of despair" (i.e., deaths from suicide, drug use, and alcohol use), which have been interpreted as a cohort-based phenomenon afflicting middle-aged White Americans. There has been less attention on Black mortality trends from these same causes, and whether the trends are similar or different by cohort and period. We complement existing research and contend that recent mortality trends in both the US Black and White populations most likely reflect period-based exposures to 1) the US opioid epidemic and 2) the Great Recession. We analyzed cause-specific mortality trends in the United States for deaths from suicide, drug use, and alcohol use among non-Hispanic Black and non-Hispanic White Americans, aged 20-64 years, over 1990-2017. We employed sex-, race-, and cause-of-death-stratified Poisson rate models and age-period-cohort models to compare mortality trends. Results indicate that rising "deaths of despair" for both Black and White Americans are overwhelmingly driven by period-based increases in drug-related deaths since the late 1990s. Further, deaths related to alcohol use and suicide among both White and Black Americans changed during the Great Recession, despite some racial differences across cohorts.

Increase in anticholinergic burden from 1990 to 2015: Age-period-cohort analysis in UK biobank

BACKGROUND

The use of prescription drugs with anticholinergic properties has been associated with multiple negative health outcomes in older people. Moreover, recent evidence suggests that associated adverse effects may occur even decades after stopping anticholinergic use. Despite the implicated importance of examining longitudinal patterns of anticholinergic prescribing for different age groups, few such data are available.

METHODS

We performed an age-period-cohort (APC) analysis to study trends in an aggregate measure of anticholinergic burden between the years 1990 and 2015, utilising data from >220 000 UK Biobank participants with linked prescription data from primary care.

RESULTS

Anticholinergic burden in the sample increased up to 9-fold over 25 years and was observed for both period and age effects across most classes of drugs. The greatest increase was seen in the prescribing of antidepressants. Female sex, lower education and greater deprivation were associated with greater anticholinergic burden.

CONCLUSIONS

The increase in anticholinergic prescribing is mostly due to an increase in polypharmacy and is attributable to both ageing of participants and period-related changes in prescribing practices. Research is needed to clarify the implications of rising anticholinergic use for public health and to contextualise this rise in light of other relevant prescribing practices.

Getting a Grip on Secular Changes: Age-Period-Cohort modeling of grip strength in the English Longitudinal Study of Ageing

BACKGROUND

Grip strength is a popular and valuable measure in studies of physical functional capabilities in old-age. The influence of historical trends and differential period-specific exposures can complicate the interpretation of biomarkers of aging and health and requires careful analysis and interpretation of ageing, birth cohort, and period effects. The current study evaluates the effects of aging, period, and cohort on grip strength in a population of adults and older adults.

METHODS

We use >27,000 observations for individuals ≥50 years of age, born in approximately 1910-1960, from the English Longitudinal Study of Aging to examine a variety of multilevel and cross-classified modeling approaches to evaluate age, period, and cohort effects. Our results extended Hierarchical Age Period Cohort modeling and compared our results with a set of nine sub-models with explicit assumptions to determine the most reliable modeling approach.

RESULTS

Findings suggest grip strength is primarily related to age, with minimal evidence of either period and/or cohort effects. Each year's increase in a person's age was associated with a 0.40-kilogram decrease in grip strength, though this decline differs by gender.

CONCLUSIONS

We conclude that as a population ages, grip strength declines at a systematic and predictable rate equal to -0.40-kilograms per year (approximately -.50-kg for men and -.30-kg for women) in residents of England aged 50 and older. Age-effects were predominant and most consistent across methodologies. While there was some evidence for cohort effects, such effects were minimal and therefore indicative that grip strength is a consistent physiological biomarker of aging.

A simplified approach for establishing estimable functions in fixed effect age-period-cohort multiple classification models

Estimable functions play an important role in learning about certain aspects of the impact of ages, periods, and cohorts in age-period-cohort multiple classification (APCMC) models. The advantage of these estimates is that they are unbiased estimates of, for example, the deviations of age, period, and cohort effects from their linear trends, or changes in the linear trends of cohort effects within cohorts, or the residuals of fixed effect APCMC models. If the fixed effect APCMC model contains the relevant variables (is well specified), these estimable functions are unbiased estimates of functions of the parameters that generated the dependent variable data, even though the parameters that generated that data are not identified. I provide a simplified approach to establishing which functions are estimable in fixed effect APCMC models that provides an intuitive understanding of estimable functions by showing clearly and simply why they are estimable. This approach involves the partitioning of the age, period, and cohort effects into linear components and deviations from the linear components; the use of the "line of solutions"; and of the "extended null vector."