Retirement Makes You Old? Causal Effect of Retirement on Biological Age.

Retirement is a critical life event for older people. Health scholars have scrutinized the health effects of retirement, but its consequences on age-related diseases and mortality are unclear. We extend this body of research by integrating measurements of biological age, representing the physiological decline preceding disease onset. Using data from the UK Biobank and a fuzzy regression discontinuity design, we estimated the effects of retirement on two biomarker-based biological age measures. Results showed that retirement significantly increases biological age for those induced to retire by the State Pension eligibility by 0.871-2.503 years, depending on sex and specific biological age measurement. Given the emerging scientific discussion about direct interventions to biological age to achieve additional improvements in population health, the positive effect of retirement on biological age has important implications for an increase in the State Pension eligibility age and its potential consequences on population health, public health care policy, and older people's labor force participation. Overall, this study provides novel empirical evidence contributing to the question of what social factors make people old.

Separating Scarring Effect and Selection of Early-Life Exposures With Genetic Data.

Causal life course research examining consequences of early-life exposures has largely relied on associations between early-life environments and later-life outcomes using exogenous environmental shocks. Nonetheless, even with (quasi-)randomized early-life exposures, these associations may reflect not only causation ("scarring") but also selection (i.e., which members are included in data assessing later life). Investigating this selection and its impacts on estimated effects of early-life conditions has, however, often been ignored because of a lack of pre-exposure data. This study proposes an approach for assessing and correcting selection, separately from scarring, using genetic measurements. Because genetic measurements are determined at the time of conception, any associations with early-life exposures should be interpreted as selection. Using data from the UK Biobank, we find that in utero exposure to a higher area-level infant mortality rate is associated with genetic predispositions correlated with better educational attainment and health. These findings point to the direction and magnitude of selection from this exposure. Corrections for this selection in examinations of effects of exposure on later educational attainment suggest underestimates of 26-74%; effects on other life course outcomes also vary across selection correction methods.

The Big (Genetic) Sort? A Research Note on Migration Patterns and Their Genetic Imprint in the United Kingdom.

This research note reinvestigates Abdellaoui et al.'s (2019) findings that genetically selective migration may lead to persistent and accumulating socioeconomic and health inequalities between types (coal mining or non-coal mining) of places in the United Kingdom. Their migration measure classified migrants who moved to the same type of place (coal mining to coal mining or non-coal mining to non-coal mining) into "stay" categories, preventing them from distinguishing migrants from nonmigrants. We reinvestigate the question of genetically selective migration by examining migration patterns between places rather than place types and find genetic selectivity in whether people migrate and where. For example, we find evidence of positive selection: people with genetic variants correlated with better education moved from non-coal mining to coal mining places with our measure of migration. Such findings were obscured in earlier work that could not distinguish nonmigrants from migrants.

Understanding Internal Migration: A Research Note Providing an Assessment of Migration Selection With Genetic Data.

Migration is selective, resulting in inequalities between migrants and nonmigrants. However, investigating migration selection is empirically challenging because combined pre- and post-migration data are rarely available. We propose an alternative approach to assessing internal migration selection by integrating genetic data, enabling an investigation of migration selection with cross-sectional data collected post-migration. Using data from the UK Biobank, we utilized standard tools from statistical genetics to conduct a genome-wide association study (GWAS) for migration distance. We then calculated genetic correlations to compare GWAS results for migration with those for other characteristics. Given that individual genetics are determined at conception, these analyses allow a unique exploration of the association between pre-migration characteristics and migration. Results are generally consistent with the healthy migrant literature: genetics correlated with longer migration distance are associated with higher socioeconomic status and better health. We also extended the analysis to 53 traits and found novel correlations between migration and several physical health, mental health, personality, and sociodemographic traits.

The Long Shadow: Early-Life Adversity and Later-Life Loneliness in the United States.

OBJECTIVES: This study assesses how early-life adversity (ELA) is associated with later-life loneliness among those aged 55 and older in the United States. We consider multiple domains of ELA to understand domain-specific associations between ELA and later-life loneliness. METHODS: Using data from the 2008 to 2016 rounds of Health and Retirement Study (n = 29,661 person-waves [weighted]), we evaluate whether and how different domains of ELA are associated with loneliness, and how their relationships are explained through adulthood conditions and are dependent on educational attainment. RESULTS: Our analyses demonstrate significant and distinctive relationships between various domains of ELA and later-life loneliness. Whereas adulthood conditions largely explain positive associations between loneliness with some domains of ELA (socioeconomic disadvantages and chronic diseases), disruptive home environment, risky adolescent behaviors, and impairment during childhood are still related to a higher level of loneliness after controlling for adulthood conditions. We also find empirical evidence supporting educational differences in relationships between some ELA domains and later-life loneliness. Our results also show that the associations between ELA and later-life loneliness differ between subdimensions of loneliness (emotional vs. social loneliness). DISCUSSION: This study underscores ELA as an important early-life risk factor contributing to later-life loneliness. Our findings suggest that policy interventions to reduce adverse childhood experiences may alleviate individuals' exposure to loneliness in later life.

Early life environments and cognition in adulthood: New evidence using a semiparametric approach and quantile regression.

Theories and empirical evidence document the importance of early life environmental factors on later life cognition. A next question is how and in what dimension associations between early life environments and later life cognition vary. Using data from the UK Biobank in conjunction with time-place-specific infant mortality rates, we assessed heterogeneous and non-linear associations between early life conditions and later life cognition. We found that the association between the infant mortality rate and later life cognition increased once the UK achieved very low infant mortality rates, suggesting that additional decreases in infant mortality rates in an industrialized society continue to improve later life cognition. We also found that infant mortality rates have stronger effects at upper quantiles of the cognition distribution. This implies that adverse early life environments may have an important role for an early manifestation of cognitive aging.

Living Arrangements, Intergenerational Support, and Married Women's Subjective Well-Being.

Theory suggests that relationships between intergenerational coresidence and married women's subjective well-being may be either positive or negative. We extend previous research on this question in two ways: by focusing also on geographical proximity to parents(-in-law) and by examining differences in married women's well-being both between and within different types of living arrangements. Using data from a nationally representative survey of adults in Japan, we found no differences in married women's subjective well-being between living arrangements, but observed significant differences within living arrangements depending on married women's position in the household and the direction of intergenerational support transfers. Our results suggest that comparisons across living arrangements may be complicated by within-group associations with well-being and that attention to married women's position in the household and the direction of intergenerational transfers is essential for understanding how married women in Japan experience different living arrangements.

GWAS on birth year infant mortality rates provides evidence of recent natural selection.

Following more than a century of phenotypic measurement of natural selection processes, much recent work explores relationships between molecular genetic measurements and realized fitness in the next generation. We take an innovative approach to the study of contemporary selective pressure by examining which genetic variants are "sustained" in populations as mortality exposure increases. Specifically, we deploy a so-called "regional GWAS" (genome-wide association study) that links the infant mortality rate (IMR) by place and year in the United Kingdom with common genetic variants among birth cohorts in the UK Biobank. These cohorts (born between 1936 and 1970) saw a decline in IMR from above 65 to under 20 deaths per 1,000 live births, with substantial subnational variations and spikes alongside wartime exposures. Our results show several genome-wide significant loci, including LCT and TLR10/1/6, related to area-level cohort IMR exposure during gestation and infancy. Genetic correlations are found across multiple domains, including fertility, cognition, health behaviors, and health outcomes, suggesting an important role for cohort selection in modern populations.

Detecting genetic heterogeneities in response to trauma: The case of 9/11.

The current study evaluates genetic heterogeneities in response to trauma among U.S. young adults. Using Add Health Wave III, which coincidently overlapped with the September 11 attacks, and a depression mean and variance polygenic scores, we investigate how the polygenic scores moderate the causal effect of 9/11 on mental health. Our results show the presence of genetic heterogeneity, where those with high genetic plasticity experience an increase in depressive symptoms following trauma while those with low genetic plasticity do not. While the documented differences in reactions to trauma are important, we also note our ability to predict responses based only on genetic measures are too imprecise to identify susceptible clinical patients. We, therefore, contend that the expected benefits from genetic screening to identify susceptible individuals after trauma are limited. Our results provide novel evidence of a specific source of an additional heterogeneity contributing to the inequality of health following trauma.