Novel methods for capturing variation in unintended pregnancy across time and place

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Health outcomes of only children across the life course : an investigation using Swedish register data

This work was partially supported by the Carnegie Trust for the Universities of Scotland [RIG008234] awarded to Katherine Keenan and by the Economic and Social Research Council [grant number ES/S002103/1] to Alice Goisis. This work was also supported by the Swedish Research Council (Vetenskapsrådet) via the Swedish Initiative for Research on Microdata in the Social and Medical Sciences (SIMSAM), grant 340-2013-5164.Only children (with no full biological siblings) are a growing subgroup in many high-income settings. Previous studies have largely focused on the short-term developmental outcomes of only children, but there is limited evidence on their health outcomes. Using Swedish population register data for cohorts born 1940–75, we compare the health of only children with that of children from multi-child sibling groups, taking into account birth order, family size, and presence of half-siblings. Only children showed lower height and fitness scores, were more likely to be overweight/obese in late adolescence, and experienced higher later-life mortality than those with one or two siblings. However, only children without half-siblings were consistently healthier than those with half-siblings, suggesting that parental disruption confers additional disadvantages. The health disadvantage was attenuated but not fully explained by adjustment for parental characteristics and after using within-family maternal cousin comparison designs.Publisher PDFPeer reviewe

Data sources on the older population in Europe: comparison of the generations and gender survey (GGS) and the survey of health, ageing and retirement in Europe (SHARE)

The Survey of Health, Ageing and Retirement in Europe (SHARE) and the Generations and Gender Survey (GGS) are two widely used European longitudinal surveys with data on sociodemographic and health topics, but their comparability has not been systematically investigated. We compared SHARE and GGS data for 50-80 year olds in seven European countries (Belgium, Estonia, France, Germany, Hungary, the Netherlands and Poland) to assess data quality and the potential for joint analyses. The results showed that information on, and distributions by, age, gender, marriage and fertility patterns were broadly similar in both sources. For some countries distributions by educational level varied between the two sources even though both reported using the International Standard Classification of Education, which may reflect variations in the timings of surveys. The wording of health questions and their placement in the questionnaire sometimes differed between the surveys. This may account to some extent for differences between them in estimates of the prevalence of poor health. We investigated what effect these variations might have on analyses of health inequalities by undertaking multivariable analysis of associations between education and marital status and two health indicators

Health outcomes of only children across the life course : an investigation using Swedish register data

The proportion of only children – children with no full biological siblings – is growing in high-income settings, but we know little about their life course outcomes and how this is related to long-term health. Previous studies of only children have tended to focus on short-term, developmental and intellectual outcomes in early life or adolescence, and provide mixed evidence. Using Swedish population register data on children born between 1940 and 1975, we compare only children with children from multi-child sibling groups, taking into account birth order, family size and half-siblings to account for family complexity. We consider physical health outcomes measured at late adolescence (height, body mass index and physical fitness), and mortality. Only children with and without half-siblings had lower height and fitness scores, were more likely to be overweight or obese, and had higher mortality, than those with 1 or 2 biological siblings. Only children without half-siblings generally did better than only children with half-siblings, suggesting that only children experiencing parental disruption experience additional disadvantages. With the exception of height, the patterns persist after adjustment for parental characteristics and after employing within-family cousin comparison designs. In mortality models, some of the excess risk for only children was explained by adjustment for fertility, marriage and educational history. We discuss the extent to which the patterns we observe are explained by selection processes and contextual differences in the prevalence of one-child sibling groups.Publisher PD

Household level health and socio-economic vulnerabilities and the COVID-19 crisis : an analysis from the UK

Objectives. To investigate how COVID-19-related health and socio-economic vulnerabilities occur at the household level, and how they are distributed across household types and geographical areas in the United Kingdom. Design. Cross-sectional, nationally representative study. Setting. The United Kingdom. Participants. ~19,500 households. Main outcome measures. Using multiple household-level indicators and principal components analysis, we derive summary measures representing different dimensions of household vulnerabilities critical during the COVID-19 epidemic: health, employment, housing, financial and digital. Results. Our analysis highlights three key findings. First, although COVID-19 health risks are concentrated in retirement-age households, a substantial proportion of working age households also face these risks. Second, different types of households exhibit different vulnerabilities, with working-age households more likely to face financial, housing and employment precarities, and retirement-age households health and digital vulnerabilities. Third, there are area-level differences in the distribution of vulnerabilities across England and the constituent countries of the United Kingdom. Conclusions. The findings imply that the short- and long-term consequences of the COVID-19 crisis are likely to vary by household type. Policy measures that aim to mitigate the health and socio-economic consequences of the COVID-19 pandemic should consider how vulnerabilities cluster together across different household types, and how these may exacerbate already existing inequalities.Publisher PD

Treatment of missing data in Bayesian network structure learning : an application to linked biomedical and social survey data

The authors acknowledge the Research/Scientific Computing teams at The James Hutton Institute and NIAB for providing computational resources and technical support for the “UK’s Crop Diversity Bioinformatics HPC” (BBSRC grant BB/S019669/1), use of which has contributed to the results reported within this paper. Access to this was provided via the University of St Andrews Bioinformatics Unit which is funded by a Wellcome Trust ISSF award (grant 105621/Z/14/Z and 204821/Z/16/Z). XK was supported by a World-Leading PhD Scholarship from St Leonard’s Postgraduate School of the University of St Andrews. VAS and KK were partially supported by HATUA, The Holistic Approach to Unravel Antibacterial Resistance in East Africa, a three-year Global Context Consortia Award (MR/S004785/1) funded by the National Institute for Health Research, Medical Research Council and the Department of Health and Social Care. KK is supported by the Academy of Medical Sciences, the Wellcome Trust, the Government Department of Business, Energy and Industrial Strategy, the British Heart Foundation Diabetes UK, and the Global Challenges Research Fund [Grant number SBF004\1093]. KK is additionally supported by the Economic and Social Research Council HIGHLIGHT CPC- Connecting Generations Centre [Grant number ES/W002116/1].Background Availability of linked biomedical and social science data has risen dramatically in past decades, facilitating holistic and systems-based analyses. Among these, Bayesian networks have great potential to tackle complex interdisciplinary problems, because they can easily model inter-relations between variables. They work by encoding conditional independence relationships discovered via advanced inference algorithms. One challenge is dealing with missing data, ubiquitous in survey or biomedical datasets. Missing data is rarely addressed in an advanced way in Bayesian networks; the most common approach is to discard all samples containing missing measurements. This can lead to biased estimates. Here, we examine how Bayesian network structure learning can incorporate missing data. Methods We use a simulation approach to compare a commonly used method in frequentist statistics, multiple imputation by chained equations (MICE), with one specific for Bayesian network learning, structural expectation-maximization (SEM). We simulate multiple incomplete categorical (discrete) data sets with different missingness mechanisms, variable numbers, data amount, and missingness proportions. We evaluate performance of MICE and SEM in capturing network structure. We then apply SEM combined with community analysis to a real-world dataset of linked biomedical and social data to investigate associations between socio-demographic factors and multiple chronic conditions in the US elderly population. Results We find that applying either method (MICE or SEM) provides better structure recovery than doing nothing, and SEM in general outperforms MICE. This finding is robust across missingness mechanisms, variable numbers, data amount and missingness proportions. We also find that imputed data from SEM is more accurate than from MICE. Our real-world application recovers known inter-relationships among socio-demographic factors and common multimorbidities. This network analysis also highlights potential areas of investigation, such as links between cancer and cognitive impairment and disconnect between self-assessed memory decline and standard cognitive impairment measurement. Conclusion Our simulation results suggest taking advantage of the additional information provided by network structure during SEM improves the performance of Bayesian networks; this might be especially useful for social science and other interdisciplinary analyses. Our case study show that comorbidities of different diseases interact with each other and are closely associated with socio-demographic factors.PostprintPublisher PDFPeer reviewe

Number of children, partnership status, and later-life depression in Eastern and Western Europe

The research leading to these results has received funding from the European Research Council under the European Union’s Seventh Framework Programme (FP7/2007–2013)/ ERC grant agreement n° 324055.Objectives:  To investigate associations between number of children and partnership with depressive symptoms among older Europeans and assess whether associations are greater in Eastern than Western countries. We further analyze whether associations are mediated by provision and receipt of emotional and financial support. Methods:  Using cross-sectional data for five Eastern (Bulgaria, Czech Republic, Georgia, Romania, and Russia) and four Western European countries (Belgium, France, Norway, and Sweden) (n = 15,352), we investigated variation in depressive symptoms using linear regression. We fitted conditional change score models for depressive symptoms using longitudinal data for four countries (Bulgaria, Czech Republic, Georgia, and France) (n = 3,978). Results:  Unpartnered women and men had more depressive symptoms than the partnered. In Eastern, but not Western, European countries childlessness and having one compared with two children were associated with more depressive symptoms. Formal tests indicated that partnership and number of children were more strongly associated with depressive symptoms in Eastern than Western Europe. Discussion:  Availability of close family is more strongly associated with older people’s depressive symptoms in Eastern than Western Europe. The collapse of previous state supports and greater economic stress in Eastern Europe may mean that having a partner and children has a greater psychological impact than in Western countries.Publisher PDFPeer reviewe

Sibling group size and BMI over the life course : evidence from four British cohort studies

JC and AG were supported by the UK Economic and Social Research Council (ESRC) grant number ES/S002103/1 and the ESRC CLS Centre (ES/M001660/1). KB was supported by the Bank of Sweden Tercentenary Foundation (Riksbankens Jubileumsfond) through a Pro Futura Scientia XIV fellowship. KK was supported by a Carnegie Trust for the Universities of Scotland Research Incentive Grant (RIG008234) and ESRC CPC Connecting Generations Centre (ES/V014188/1).Only children, here defined as individuals growing up without siblings, are a small but growing demographic subgroup. Existing research has consistently shown that, on average, only children have higher body mass index (BMI) than individuals who grow up with siblings. How this difference develops with age is unclear and existing evidence is inconclusive regarding the underlying mechanisms. We investigate BMI trajectories for only children and those with siblings up to late adolescence for four British birth cohorts and across adulthood for three cohorts. We use data on BMI from ages 2–63 years (cohort born 1946); 7–55 years (born 1958); 10–46 (born 1970) and 3–17 years (born 2000–2002). Using mixed effects regression separately for each cohort, we estimate the change in BMI by age comparing only children and those with siblings. The results show higher average BMI among only children in each cohort, yet the difference is substantively small and limited to school age and adolescence. The association between sibling status and BMI at age 10/11 is not explained by differential health behaviours (physical activity, inactivity and diet) or individual or family background characteristics in any of the cohorts. Although persistent across cohorts, and despite the underlying mechanism remaining unexplained, the substantively small magnitude of the observed difference and the convergence of the trajectories by early adulthood in all cohorts raises doubts about whether the difference in BMI between only children and siblings in the UK context should be of research or clinical concern. Future research could usefully be directed more at whether only children experience elevated rates of disease, for which high BMI is a risk factor, at different stages of the life course and across contexts.Publisher PDFPeer reviewe

Editorial introduction: Social and spatial inequalities in health and mortality : the analysis of longitudinal register data from selected European countries

Funding: Economic and Social Research Council. Grant Numbers: ES/K007394/1, ES/K000446/1; European Union's Horizon 2020 research and innovation programme. Grant Number: 834103.Health inequalities—systematic differences in health outcomes between social groups and across spatial units—are ubiquitous, but not necessarily inevitable. They are the product of a complex interplay of social and economic processes operating at various scales. The unequal pattern of infection and death seen in the Covid-19 pandemic has served to highlight the stark social gradient in health that exists within many European countries. Although the complex social determinants of health have been studied for many decades, there is still a great deal of work to do to elucidate explanations for health inequalities across time and space. To rise to the challenge, we need high-quality, representative data capable of capturing multi-scalar longitudinal processes. This special issue brings together eight new studies which all use national population register data linked with various other sources of administrative data (e.g., residence, tax and health records) to investigate different vectors of inequalities in health and mortality, covering spatial, socioeconomic, ethnic and migrant status. This editorial outlines their contributions, argues for the invaluable role of population register data to understand health inequalities and suggests promising future research avenues.Publisher PDFPeer reviewe

Diverse early-life family trajectories and young children's mental health in the UK

Authors gratefully acknowledge funding from the Economic and Social Research Council (ESRC); grant number 2460061.Past research suggests that children from two-parent married families fare better than children from other families on many outcomes. Only fragmented evidence on diverse family trajectories in association with child mental health is available. Using multi-channel sequence analysis and data from the UK Household Longitudinal Study, we jointly capture maternal partnership trajectories and type of father co-residence between birth and age 5. We then assess the association between these family trajectories and child mental health at age 5 and 8 using random effects regression. Children whose trajectories include the entrance of a non-biological father or parental separation have the lowest levels of mental health. However, children of never partnered mothers and those who repartner with the biological father have comparable mental health to children of stably married biological parents. Thus, not all types of family complexity or instability appear to be equally detrimental to children’s mental health.Peer reviewe