COVID-19 precautionary behaviors and vaccine acceptance among older individuals: The role of close kin.

The family plays a central role in shaping health behaviors of its members through social control and support mechanisms. We investigate whether and to what extent close kin (i.e., partner and children) matter for older people in taking on precautionary behaviors (e.g., wearing a mask) and vaccination during the COVID-19 pandemic in Europe. Drawing on data from the Survey of Health, Ageing and Retirement in Europe (SHARE), we combine its Corona Surveys (June to September 2020 and June to August 2021) with pre-COVID information (October 2019 to March 2020). We find that having close kin (especially a partner) is associated with a higher probability of both adopting precautionary behaviors and accepting a COVID-19 vaccine. Results are robust to controlling for other potential drivers of precautionary behaviors and vaccine acceptance and to accounting for coresidence with kin. Our findings suggest that policymakers and practitioners may differently address kinless individuals when promoting public policy measures.

A machine learning approach to determine the influence of specific health conditions on self-rated health across education groups.

BACKGROUND: Self-rated health, a subjective health outcome that summarizes an individual's health conditions in one indicator, is widely used in population health studies. However, despite its demonstrated ability as a predictor of mortality, we still do not full understand the relative importance of the specific health conditions that lead respondents to answer the way they do when asked to rate their overall health. Here, education, because of its ability to identify different social strata, can be an important factor in this self-rating process. The aim of this article is to explore possible differences in association pattern between self-rated health and functional health conditions (IADLs, ADLs), chronic diseases, and mental health (depression) among European women and men between the ages of 65 and 79 according to educational attainment (low, medium, and high). METHODS: Classification trees (J48 algorithm), an established machine learning technique that has only recently started to be used in social sciences, are used to predict self-rated health outcomes. The data about the aforementioned health conditions among European women and men aged between 65 and 79 comes from the sixth wave of the Survey of Health, Ageing and Retirement in Europe (SHARE) (n = 27,230). RESULTS: It is confirmed the high ability to predict respondents' self-rated health by their reports related to their chronic diseases, IADLs, ADLs, and depression. However, in the case of women, these patterns are much more heterogeneous when the level of educational attainment is considered, whereas among men the pattern remains largely the same. CONCLUSIONS: The same response to the self-rated health question may, in the case of women, represent different health profiles in terms of the health conditions that define it. As such, gendered health inequalities defined by education appear to be evident even in the process of evaluating one's own health status.

No clear association emerges between intergenerational relationships and COVID-19 fatality rates from macro-level analyses.

The severe acute respiratory syndrome coronavirus 2 originated in Wuhan, China at the end of 2019 and rapidly spread in more than 100 countries. Researchers in different fields have been working on finding explanations for the unequal impact of the virus and deaths from the associated coronavirus disease 2019 (COVID-19) across geographical areas. Demographers and other social scientists have hinted at the importance of demographic factors, such as age structure and intergenerational relationships. Our aim is to reflect on the possible link between intergenerational relationships and spread and lethality of COVID-19 in a critical way. We show that with available aggregate data it is not possible to draw robust evidence to support these links. In fact, despite a higher prevalence of intergenerational coresidence and contacts that is broadly positively associated with COVID-19 case fatality rates at the country level, the opposite is generally true at the subnational level. While this inconsistent evidence demonstrates neither the existence nor the absence of a causal link between intergenerational relationships and the severity of COVID-19, we warn against simplistic interpretations of the available data, which suffer from many shortcomings. We conclude by arguing that intergenerational relationships are not only about physical contacts between family members. Theoretically, different forms of intergenerational relationships may have causal effects of opposite sign on the diffusion of COVID-19. Policies should also take into account that intergenerational ties are a source of instrumental and emotional support, which may favor compliance to the lockdown and "phase-2" restrictions and may buffer their negative consequences on mental health.

What Tears Couples Apart: A Machine Learning Analysis of Union Dissolution in Germany.

This study contributes to the literature on union dissolution by adopting a machine learning (ML) approach, specifically Random Survival Forests (RSF). We used RSF to analyze data on 2,038 married or cohabiting couples who participated in the German Socio-Economic Panel Survey, and found that RSF had considerably better predictive accuracy than conventional regression models. The man's and the woman's life satisfaction and the woman's percentage of housework were the most important predictors of union dissolution; several other variables (e.g., woman's working hours, being married) also showed substantial predictive power. RSF was able to detect complex patterns of association, and some predictors examined in previous studies showed marginal or null predictive power. Finally, while we found that some personality traits were strongly predictive of union dissolution, no interactions between those traits were evident, possibly reflecting assortative mating by personality traits. From a methodological point of view, the study demonstrates the potential benefits of ML techniques for the analysis of union dissolution and for demographic research in general. Key features of ML include the ability to handle a large number of predictors, the automatic detection of nonlinearities and nonadditivities between predictors and the outcome, generally superior predictive accuracy, and robustness against multicollinearity.

Matching on poset-based average rank for multiple treatments to compare many unbalanced groups.

In this article, we propose an original matching procedure for multiple treatment frameworks based on partially ordered set theory (poset). In our proposal, called matching on poset-based average rank for multiple treatments (MARMoT), poset theory is used to summarize individuals' confounders and the relative average rank is used to balance confounders and match individuals in different treatment groups. This approach proves to be particularly useful for balancing confounders when the number of treatments considered is high. We apply our approach to the estimation of neighborhood effect on the fractures among older people in Turin (a city in northern Italy).

Consequences on depression of combining grandparental childcare with other caregiving roles.

Objective: This study examines the effect of combining grandchild care with other care roles on depression among individuals aged 50 to 84. Previous research investigating the health consequences of multiple care roles among older adults found mixed evidence, with most studies being predominantly cross-sectional.Methods: We use longitudinal data from the Survey of Health, Ageing and Retirement in Europe (SHARE) to understand how grandparents' mental health, measured as depressive symptoms, is affected when combining multiple care roles. We estimate logistic regression models, for grandfathers and grandmothers separately, to investigate how depression at wave 2 is affected by multiple care roles at wave 1, controlling for depression at baseline.Results: Consistent with previous studies, we find that providing grandchild care only reduces risk of depression for grandmothers, but not for grandfathers. For both genders, we find a higher risk of depression among those who provide intensive care to co-residents. The negative effect of grandchild care on depression found for grandmothers disappears if they also provide other types of care. In particular, grandmothers who provide care both to grandchildren and to a sick or disabled person show a higher risk of depression compared to those who only provide grandchild care.Conclusions: While multiple caregiving roles are not common, it is important to understand their combined effect on caregivers' health. Grandmothers who provide childcare and other intensive types of care may lose the positive effects grandchild care exert over their wellbeing.

Examining social determinants of health: the role of education, household arrangements and country groups by gender.

BACKGROUND: The majority of empirical studies focus on a single Social Determinant of Health (SDH) when analysing health inequalities. We go beyond this by exploring how the combination of education (micro level) and household arrangements (mezzo level) is associated with self-perceived health. METHODS: Our data source is the 2014 cross-sectional data from the European Survey of Living Conditions (EU-SILC). We calculate the predicted probabilities of poor self-perceived health for the middle-aged European population (30-59 years) as a function of the combination of the two SDHs. This is done separately for five European country groups (dual-earner; liberal; general family support; familistic; and post-socialist transition) and gender. RESULTS: We observe a double health gradient in all the country groups: first, there is a common health gradient by education (the higher the education, the lower the probability of poor health); second, household arrangements define a health gradient within each educational level according to whether or not the individual lives with a partner (living with a partner is associated with a lower probability of poor health). We observe some specificity in this general pattern. Familistic and post-socialist transition countries display large differences in the predicted probabilities according to education and household arrangements when compared with the other three country groups. Familistic and post-socialist transition countries also show the largest gender differences. CONCLUSIONS: Health differences in European populations seem to be defined, first, by education and, second, by living or not living with a partner. Additionally, different social contexts (gender inequalities, educational profile, etc.) in European countries change the influences on health of both the SDHs for both women and men.

A comparison of machine learning algorithms and covariate balance measures for propensity score matching and weighting.

Propensity score matching (PSM) and propensity score weighting (PSW) are popular tools to estimate causal effects in observational studies. We address two open issues: how to estimate propensity scores and assess covariate balance. Using simulations, we compare the performance of PSM and PSW based on logistic regression and machine learning algorithms (CART; Bagging; Boosting; Random Forest; Neural Networks; naive Bayes). Additionally, we consider several measures of covariate balance (Absolute Standardized Average Mean (ASAM) with and without interactions; measures based on the quantile-quantile plots; ratio between variances of propensity scores; area under the curve (AUC)) and assess their ability in predicting the bias of PSM and PSW estimators. We also investigate the importance of tuning of machine learning parameters in the context of propensity score methods. Two simulation designs are employed. In the first, the generating processes are inspired to birth register data used to assess the effect of labor induction on the occurrence of caesarean section. The second exploits more general generating mechanisms. Overall, among the different techniques, random forests performed the best, especially in PSW. Logistic regression and neural networks also showed an excellent performance similar to that of random forests. As for covariate balance, the simplest and commonly used metric, the ASAM, showed a strong correlation with the bias of causal effects estimators. Our findings suggest that researchers should aim at obtaining an ASAM lower than 10% for as many variables as possible. In the empirical study we found that labor induction had a small and not statistically significant impact on caesarean section.

Navigating between two cultures: Immigrants' gender attitudes toward working women.

BACKGROUND: Gender attitudes toward women's employment are of particular importance because they positively influence gender-equal outcomes in the labor market. Our understanding of the mechanisms that promote egalitarian gender attitudes among immigrants, however, remains limited. OBJECTIVE: By studying first- and second-generation immigrants from multiple origins and living in different countries, this article seeks to explain under what conditions the prevalent cultural attitudes toward gender roles at the origin and destination influence immigrants' gender attitudes. We address three main research questions. First, does the country-of-origin gender ideology influence immigrants' views toward working women? Second, does the country-of-destination gender ideology influence immigrants' view toward working women? Are these relationships moderated by (1) the immigrant generation; (2) the age at arrival in the country of destination; (3) the length of residence at destination? METHODS: Using data from the European Social Survey, we model immigrants' gender attitudes toward working women using linear cross-classified models to account for clustering into the country of origin and destination. RESULTS: The results highlight the importance of the context of early socialization in shaping immigrants' gender attitudes. First-generation immigrants, and more specifically, adult migrants hold gender attitudes that reflect more strongly the country of origin's gender culture. In contrast, the positive association between gender ideology at destination and immigrants' gender attitudes is stronger among second-generation immigrants and child migrants. CONTRIBUTION: We add to the literature on gender ideology formation by analyzing the influence of gender ideology at the origin- and destination-levels on the gender attitudes of immigrants from 96 countries of origin and residing across 32 countries of destination.

Propensity score matching with clustered data. An application to the estimation of the impact of caesarean section on the Apgar score.

This article focuses on the implementation of propensity score matching for clustered data. Different approaches to reduce bias due to cluster-level confounders are considered and compared using Monte Carlo simulations. We investigated methods that exploit the clustered structure of the data in two ways: in the estimation of the propensity score model (through the inclusion of fixed or random effects) or in the implementation of the matching algorithm. In addition to a pure within-cluster matching, we also assessed the performance of a new approach, 'preferential' within-cluster matching. This approach first searches for control units to be matched to treated units within the same cluster. If matching is not possible within-cluster, then the algorithm searches in other clusters. All considered approaches successfully reduced the bias due to the omission of a cluster-level confounder. The preferential within-cluster matching approach, combining the advantages of within-cluster and between-cluster matching, showed a relatively good performance both in the presence of big and small clusters, and it was often the best method. An important advantage of this approach is that it reduces the number of unmatched units as compared with a pure within-cluster matching. We applied these methods to the estimation of the effect of caesarean section on the Apgar score using birth register data. Copyright © 2016 John Wiley & Sons, Ltd.

The Role of Family Orientations in Shaping the Effect of Fertility on Subjective Well-being: A Propensity Score Matching Approach.

This article investigates whether and how having a child impacts an individual's subjective well-being, while taking into account heterogeneity in family attitudes. People with different family orientations have different values, gender attitudes, preferences toward career and family, and expectations about how childbearing can affect their subjective well-being. These differences impact fertility decisions and the effect of parenthood on an individual's life satisfaction. We define three groups of people based on their family orientations: Traditional, Mixed, and Modern. Applying propensity score matching on longitudinal data (British Household Panel Survey), we create groups of individuals with very similar socioeconomic characteristics and family orientations before childbearing. We then compare those who have one child with those who are childless, and those who have two children with those who have only one child. We show that parents are significantly more satisfied than nonparents, and this effect is stronger among men than among women. For men, we do not find significant differences across family orientations groups in the effect of the birth of the first child on life satisfaction. Among women, only Traditional mothers seem to be more satisfied than their childless counterparts. Women who have a second child are never more satisfied than those who have only one child, regardless of their family orientations. Traditional and Mixed men experience a gain in life satisfaction when they have a second child, but this effect is not found for Modern men.

It Takes Two to Tango: Couples' Happiness and Childbearing.

The existing literature has so far considered the role of the individual's subjective well-being on fertility, neglecting the importance of the partner's well-being. Using data from the British Household Panel Survey (BHPS) and event history models estimated separately by parity, we find that in a couple, women's happiness matters more than that of the male partner in terms of having the first child. Specifically, we observe that couples in which either partner is happier than usual are more at risk of having the first child, but the effect is stronger with higher happiness of the woman. For the transition to the second child, we find that couples in which the woman declares to be happier or less happy than usual have a lower risk of childbirth. We, moreover, find support for a multiplicative effect of partners' SWB on the decision to have a first child. Our results show that failing to acknowledge that the subjective well-being of both partners matters for the inherently joint decision making of childbearing can lead to an incomplete view of how subjective well-being affects fertility.

Conditioning on the Pre-Test versus Gain Score Modelling: Revisiting the Controversy in a Multilevel Setting.

We consider estimating the effect of a treatment on a given outcome measured on subjects tested both before and after treatment assignment in observational studies. A vast literature compares the competing approaches of modelling the post-test score conditionally on the pre-test score versus modelling the difference, namely, the gain score. Our contribution lies in analyzing the merits and drawbacks of two approaches in a multilevel setting. This is relevant in many fields, such as education, where students are nested within schools. The multilevel structure raises peculiar issues related to contextual effects and the distinction between individual-level and cluster-level treatments. We compare the two approaches through a simulation study. For individual-level treatments, our findings align with existing literature. However, for cluster-level treatments, the scenario is more complex, as the cluster mean of the pre-test score plays a key role. Its reliability crucially depends on the cluster size, leading to potentially unsatisfactory estimators with small clusters.

Is Transition to Retirement Associated With Volunteering? Longitudinal Evidence from Europe.

Studies have shown that retired older adults are more likely to volunteer than their working counterparts. However, whether the transition to retirement is associated with increased volunteering frequency and whether this varies according to material and time resources of participants is unclear. We used four waves of data from the longitudinal Survey of Health, Ageing and Retirement in Europe, collected between 2011-2018 across 19 countries (n = 12,400 person-observations from 6200 individuals over 50). Within-person (or panel fixed-effect) regression analyses revealed that transition to retirement was associated with an increased volunteering frequency over time. This association was stronger among individuals with better health, higher education, improved financial situation and in countries with higher gross domestic product per capita. Overall, transition to retirement tends to open new ways of organizing everyday life and is associated with increased frequency of volunteering.

Changes in Resources and Volunteering: A Longitudinal Study of Active Engagement Among Older Europeans.

BACKGROUND AND OBJECTIVES: Volunteering is an important dimension of successful aging. Although prior studies have found that personal resources such as health and financial situations are associated with volunteering, there is a lack of research exploring the relationship between resource changes and volunteering. Here, we investigated whether changes in individuals' resources were associated with volunteer engagement among older Europeans. RESEARCH DESIGN AND METHODS: Using data from the Survey of Health, Aging, and Retirement in Europe, collected in five waves between 2011 and 2020 across 19 countries (57,410 observations from 17,498 individuals aged 50 and above), we employed asymmetric fixed-effect ordinal regression models to investigate whether positive or negative resource changes were associated with the frequency of volunteering over time. We used three resource indicators: health, financial condition, and time availability (measured by engagement in paid work, grandparenting, and family care). RESULTS: Health deterioration and worsening financial condition were associated with a decreased frequency of volunteering. A transition out of weekly paid work and beginning to provide weekly grandchild care were both associated with an increased frequency of volunteering. We did not detect any further significant effects of resource changes on volunteering. DISCUSSION AND IMPLICATIONS: Our study revealed asymmetrical associations between changes in resources and volunteering, providing new insights into their interplay. The results deepen our understanding of successful aging by emphasizing the need to consider the dynamics of all resources that either facilitate or hinder active engagements among older adults.

Non-standard family histories and wellbeing at older ages.

The life course approach emphasizes that health and wellbeing at older ages are influenced by experiences occurred in the previous stages of life. We contribute to the literature by focusing on the role of the non-standardness of family histories and argue that individuals who experienced non-standard trajectories have been exposed to social sanctions throughout their life course with negative long-term consequences on wellbeing. In our study, non-standardness of family histories is the extent an individual's family history differs from those of the others within reference groups, defined combining birth cohort, gender and country of residence. Family histories between age of 15 and 49 are analyzed using Sequence Analysis, thus accounting for events related to fertility and union formation (marriage and cohabitation) and dissolution, and their timing. Dissimilarities between family sequences are measured using optimal matching and are standardized within the reference groups. We use retrospective data from the seventh wave of the Survey of Health Ageing and Retirement in Europe (SHARE) and estimate linear regression models to assess the association between non-standardness of family histories and older people's life satisfaction. Quality of life and depressive symptoms are examined in additional analyses. A negative association is found between non-standardness of family histories and wellbeing, which is stronger for lower educated individuals and in Southern European countries. Results are consistent with the idea that uncommon family behaviors may have a long-term negative effect on wellbeing. Individual resources and a more tolerant societal context can reduce or eliminate the negative consequences of engaging in non-standard family behaviors.

Changes in Grandparental Childcare During the Pandemic and Mental Health: Evidence From England.

OBJECTIVES: Policies aiming at reducing rates of hospitalization and death from coronavirus disease 2019 (COVID-19) encouraged older people to reduce physical interactions. In England, until July 2021, provision of care for grandchildren was allowed only under very limited circumstances. Evidence also suggests that reduced face-to-face interactions took a toll on mental health during the pandemic. This study aims to investigate associations between changes in grandchild care provision during the first 8/9 months of the pandemic and grandparents' mental health. METHODS: Using prepandemic data from Wave 9 (2018/2019) and the second COVID-19 substudy (November/December 2020) of the English Longitudinal Study of Ageing, we first describe changes in grandchild care provision during the pandemic to then investigate, using regression models, associations between changes in grandchild care provision and mental health (depression, quality of life, life satisfaction), while controlling for prepandemic levels of the outcome variables. RESULTS: About 10% of grandparents stopped looking after grandchildren altogether during the first 9 months of the pandemic, with 22% reporting an overall decrease in the amount of grandchild care provided. Compared to grandparents who mostly maintained unchanged their grandchild care provision, those who stopped altogether and those who mostly reduced the amount of grandchild care provided were more likely to report poorer mental health, even accounting for prepandemic health. DISCUSSION: While measures to limit physical contact and shield older people were necessary to reduce the spread of COVID-19, policymakers should acknowledge potential adverse consequences for mental health among grandparents who experienced changes in their roles as grandchild caregivers.

The prevalence of grandparental childcare in Europe: a research update.

We investigate (a) how the proportion of European grandparents providing childcare changed over a period of 15 years, (b) how these proportions differ by gender and education, and (c) how countries not covered in earlier analyses fit into previously identified regional patterns of grandparental childcare in Europe. Using data from Waves 1, 2, and 8 of the Survey of Health, Ageing and Retirement in Europe (SHARE), our descriptive analysis provides estimates of the prevalence and intensity of grandparental childcare in 26 European countries as well as of the changes therein over time and across socio-demographically defined groups. Overall, the prevalence and intensity of grandparental childcare in Europe has remained fairly stable over time, with minor increases. Proportions of grandparents providing any childcare strongly vary, however, across countries (from 24 to 60%). Grandmothers are generally more likely to provide childcare than grandfathers, while differences based on educational levels are less clear-cut. Central and southeastern Europe, representing the bulk of the 'new' countries in the analysis, exhibit patterns of grandparental childcare closely resembling those observed in Mediterranean countries. Our analysis revealed an overall stability over time rather than change in grandparents' provision of childcare in Europe, with substantial variations across welfare state regimes and within countries when accounting for grandparents' gender and educational levels. Including countries that had previously been excluded from other studies challenges the 'narrative' that has emerged around a negative macrolevel association between the provision of extensive and intensive grandparental childcare.

Less Is (Often) More: Number of Children and Health Among Older Adults in 24 Countries.

OBJECTIVES: Previous evidence about the impact of parenthood on health for older adults is mixed, perhaps due to variation in number of children and context. Higher numbers of children could lead to support or strain, depending on individual and country contexts. Yet, no studies currently exist that examine associations between the number of children and several health indicators among older adults across multiple global regions. METHODS: We analyze cross-sectional data (1992-2017) of 166,739 adults aged 50+ across 24 countries from the Health and Retirement Study family of surveys to document associations between the number of children, treated as a categorical variable, and 5 health outcomes (self-rated health, activities of daily living limitations, instrumental activities of daily living limitations, chronic conditions, and depression). We perform multivariable analyses by estimating logistic regression models for each country and each outcome. RESULTS: Multiple comparisons between categories of number of children revealed at least 1 significant difference in each country, and a majority of significant differences indicated those with more children had poorer health. The risk of poorer health for parents of multiple children was observed in 15 countries, but in some countries, fewer children predict poorer health. The greatest number of differences was identified for depression and chronic conditions, and very few for functional limitations. DISCUSSION: We observe a greater probability that more children are associated with poorer health in later life, especially for chronic conditions and depression. However, a universal global or regional pattern could not be identified. These findings raise new questions about how country contexts shape fertility and health.