Families in comparison: An individual-level comparison of life-course and family reconstructions between population and vital event registers.

It remains unknown how different types of sources affect the reconstruction of life courses and families in large-scale databases increasingly common in demographic research. Here, we compare family and life-course reconstructions for 495 individuals simultaneously present in two well-known Dutch data sets: LINKS, based on the Zeeland province's full-population vital event registration data (passive registration), and the Historical Sample of the Netherlands (HSN), based on a national sample of birth certificates, with follow-up of individuals in population registers (active registration). We compare indicators of fertility, marriage, mortality, and occupational status, and conclude that reconstructions in the HSN and LINKS reflect each other well: LINKS provides more complete information on siblings and parents, whereas the HSN provides more complete life-course information. We conclude that life-course and family reconstructions based on linked passive registration of individuals constitute a reliable alternative to reconstructions based on active registration, if case selection is carefully considered.

Longevity Relatives Count score identifies heritable longevity carriers and suggests case improvement in genetic studies.

Loci associated with longevity are likely to harbor genes coding for key players of molecular pathways involved in a lifelong decreased mortality and decreased/compressed morbidity. However, identifying such loci is challenging. One of the most plausible reasons is the uncertainty in defining long-lived cases with the heritable longevity trait among long-living phenocopies. To avoid phenocopies, family selection scores have been constructed, but these have not yet been adopted as state of the art in longevity research. Here, we aim to identify individuals with the heritable longevity trait by using current insights and a novel family score based on these insights. We use a unique dataset connecting living study participants to their deceased ancestors covering 37,825 persons from 1,326 five-generational families, living between 1788 and 2019. Our main finding suggests that longevity is transmitted for at least two subsequent generations only when at least 20% of all relatives are long-lived. This proves the importance of family data to avoid phenocopies in genetic studies.

The Long Harm of Childhood: Childhood Exposure to Mortality and Subsequent Risk of Adult Mortality in Utah and The Netherlands.

How do early-life conditions affect adult mortality? Research has yielded mixed evidence about the influence of infant and child mortality in birth cohorts on adult health and mortality. Studies rarely consider the specific role of mortality within the family. We estimated how individuals' exposure to mortality as a child is related to their adult mortality risk between ages 18 and 85 in two historical populations, Utah (USA) 1874-2015 and Zeeland (The Netherlands) 1812-1957. We examined these associations for early community-level exposure to infant and early (before sixth birthday) and late (before eighteenth birthday) childhood mortality as well as exposure during these ages to sibling deaths. We find that that exposure in childhood to community mortality and sibling deaths increases adult mortality rates. Effects of sibling mortality on adult all-cause mortality risk were stronger in Utah, where sibling deaths were less common in relation to Zeeland. Exposure to sibling death due to infection was related to the surviving siblings' risk of adult mortality due to cardiovascular disease (relative risk: 1.06) and metabolic disease (relative risk: 1.42), primarily diabetes mellitus, a result consistent with an inflammatory immune response mechanism. We conclude that early-life conditions and exposure to mortality in early life, especially within families of origin, contribute to adult mortality.

Longevity defined as top 10% survivors and beyond is transmitted as a quantitative genetic trait.

Survival to extreme ages clusters within families. However, identifying genetic loci conferring longevity and low morbidity in such longevous families is challenging. There is debate concerning the survival percentile that best isolates the genetic component in longevity. Here, we use three-generational mortality data from two large datasets, UPDB (US) and LINKS (Netherlands). We study 20,360 unselected families containing index persons, their parents, siblings, spouses, and children, comprising 314,819 individuals. Our analyses provide strong evidence that longevity is transmitted as a quantitative genetic trait among survivors up to the top 10% of their birth cohort. We subsequently show a survival advantage, mounting to 31%, for individuals with top 10% surviving first and second-degree relatives in both databases and across generations, even in the presence of non-longevous parents. To guide future genetic studies, we suggest to base case selection on top 10% survivors of their birth cohort with equally long-lived family members.

Historical demography and longevity genetics: Back to the future.

Research into the genetic component of human longevity can provide important insights in mechanisms that may protect against age-related diseases and multi-morbidity. Thus far only a limited number of robust longevity loci have been detected in either candidate or genome wide association studies. One of the issues in these genetic studies is the definition of the trait being either lifespan, including any age at death or longevity, i.e. survival above a diverse series of thresholds. Likewise heritability and segregation research have conflated lifespan with longevity. The heritability of lifespan estimated across most studies has been rather low. Environmental factors have not been sufficiently investigated and the total amount of genetic variance contributing to longevity has not been estimated in sufficiently well-defined and powered studies. Up to now, genetic longevity studies lack the required insights into the nature and size of the genetic component and the optimal strategies for meta-analysis and subject selection for Next Generation Sequencing efforts. Historical demographic data containing deep genealogical information may help in estimating the best definition and heritability for longevity, its transmission patterns in multi-generational datasets and may allow relevant additive and modifying environmental factors such as socio-economic status, geographical background, exposure to environmental effects, birth order, and number of children to be included. In this light historical demographic data may be very useful for identifying lineages in human populations that are worth investigating further by geneticists.

Clustering of deaths in families: infant and child mortality in historical perspective.

This introduction surveys the field of family clustering of deaths and discusses the contributions in this special issue. The main focus is on mortality in historical contexts. Clustering of deaths in families has been found both in historical and contemporary populations, and we argue that the 'family approach' to infant and child mortality yields important and interesting insights for our understanding of different mortality patterns and the mortality transition. The articles in this issue, representing different but complementary approaches to the problem of death clustering, demonstrate that we should be aware of the strong family effects on child health, but also that we need to develop adequate methods for the analysis of this complex phenomenon. Here we discuss several explanations for death clustering, such as different biodemographic factors and those focusing on socioeconomic and cultural variables. We also discuss some of the methodological challenges in studying family clustering, and emphasize the need for comparison and the adoption of common measures.

Did factory girls make bad mothers? Women's labor market experience, motherhood, and children's mortality risks in the past.

Prior research has suggested that the quality of maternal care given to infants and small children plays an important role in the strong clustering of children's deaths. In this article, we investigate the quality of maternal care provided by those women who most nineteenth-century social commentators declared would never make good housewives or mothers: the young girls and women working in textile mills. We carried out this examination using an analysis of children's mortality risks in two textile cities in The Netherlands between roughly 1900 and 1930. Our analysis suggests that these children's clustered mortality risks cannot have resulted from either their mothers' labor market experience or biological or genetic factors.