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This study explores the demographic and socioeconomic characteristics of one-person households (OPHs) in Sweden during the transition from an agrarian to an industrial society. While today, 25% of the adult population lives in an OPH – one of the highest rates globally – only 6% of the population lived alone in 1930. Using the 1930 census, we examine the drivers of OPH living through regression analysis of age, gender, marital status, education, income, occupation, and geographical setting. Our analysis shows that socioeconomic status, in terms of education and income, was important for the probability of living alone for both genders, with higher probabilities among the highly educated. However, income affected men and women differently. For women, income had a strong positive effect, while the opposite was true for men, as long as differences in marital status were not accounted for. The results also show substantial occupational effects that operated independently of education and income. White-collar middle-class professionals engaged in non-manual intellectual work, particularly female teachers, formed the avant-garde in single living. The social status in these groups derived primarily from cultural rather than economic capital, which was at least as important as economic resources for the propensity to live alone during this period. By identifying the early adopters of what would become a widespread living arrangement, this study contributes to our understanding of how demographic innovation spreads through society during periods of socioeconomic transformation. 

Since the 1990s, Sweden has implemented aging-in-place policies increasing the share of older adults dependent on home care instead of residing in care homes. At the same time previous research has highlighted that individuals receive home care at a higher age than before. Consequently, services are provided for a shorter time before death, increasing reliance on family and kin as caregivers. Previous studies addressing how homecare is distributed rely primarily on small surveys and are often limited to specific regions. This study aims to ascertain how home care services are distributed regarding individual-level factors such as health status, living arrangements, availability of family, education, and socioeconomic position. To provide estimates that can be generalized to Sweden as a whole, we use register data for the entire Swedish population aged 65 + in 2016. The study's main findings are that home care recipients and the amount of care received are among the oldest old with severe co morbidities. Receiving home care is slightly more common among women, but only in the highest age groups. Childlessness and socioeconomic factors play a small role in who receives home care or not. Instead, the primary home care recipients are those older adults living alone who lack direct support from family members residing in the same household.

In recent decades elderly care policies in Sweden have been characterized by a marked shift from institutional care to home care. Previous research has highlighted how this has resulted in the elderly receiving care at a higher age and increased reliance on family and kin for providing care. Using register data for the entire Swedish population aged 65+ in 2016, we analyze how home care services in contemporary Sweden distribute regarding individual-level factors such as gender, health status, living arrangements, and closeness to kin. By far, the most critical determinants of receiving home care are age, health status, and whether the elderly are living alone or not. Although our results do not discard that access to kin has become more important, our results show that childlessness and geographical proximity to adult children play a minor role for differentials in the reception of home care. The main conduit for informal care instead takes the form of spousal support. Gender plays a role in how living arrangements influence the probability of receiving home care, where cohabiting women are significantly more likely to receive care than cohabiting men. We interpret this as a result of women, on average, being younger than their male partners and more easily adopting caregivers' roles. This gendered pattern is potentially explained by the persistence of more traditional gender roles prevailing in older cohorts.

In this paper, we present a differential privacy preserving approach, which extracts personality-based knowledge to serve privacy guarantee data analysis on personal sensitive data. Based on the approach, we further implement an end-to-end privacy guarantee system, KaPPA, to provide researchers iterative data analysis on sensitive data. The key challenge for differential privacy is determining a reasonable amount of privacy budget to balance privacy preserving and data utility. Most of the previous work applies unified privacy budget to all individual data, which leads to insufficient privacy protection for some individuals while over-protecting others. In KaPPA, the proposed personality-based privacy preserving approach automatically calculates privacy budget for each individual. Our experimental evaluations show a significant trade-off of sufficient privacy protection and data utility.

Aims/hypothesis Little is known about the heritable basis of gene-environment interactions in humans. We therefore screened multiple cardiometabolic traits to assess the probability that they are influenced by genotype-environment interactions.

Methods Fourteen established environmental risk exposures and 11 cardiometabolic traits were analysed in the VIKING study, a cohort of 16,430 Swedish adults from 1682 extended pedigrees with available detailed genealogical, phenotypic and demographic information, using a maximum likelihood variance decomposition method in Sequential Oligogenic Linkage Analysis Routines software.

Results All cardiometabolic traits had statistically significant heritability estimates, with narrow-sense heritabilities (h (2)) ranging from 24% to 47%. Genotype-environment interactions were detected for age and sex (for the majority of traits), physical activity (for triacylglycerols, 2 h glucose and diastolic BP), smoking (for weight), alcohol intake (for weight, BMI and 2 h glucose) and diet pattern (for weight, BMI, glycaemic traits and systolic BP). Genotype-age interactions for weight and systolic BP, genotype-sex interactions for BMI and triacylglycerols and genotype-alcohol intake interactions for weight remained significant after multiple test correction.

Conclusion/hypothesis Age, sex and alcohol intake are likely to be major modifiers of genetic effects for a range of cardiometabolic traits. This information may prove valuable for studies that seek to identify specific loci that modify the effects of lifestyle in cardiometabolic disease.

Most complex diseases have well-established genetic and non-genetic risk factors. In some instances, these risk factors are likely to interact, whereby their joint effects convey a level of risk that is either significantly more or less than the sum of these risks. Characterizing these gene-environment interactions may help elucidate the biology of complex diseases, as well as to guide strategies for their targeted prevention. In most cases, the detection of gene-environment interactions will require sample sizes in excess of those needed to detect the marginal effects of the genetic and environmental risk factors. Although many consortia have been formed, comprising multiple diverse cohorts to detect gene-environment interactions, few robust examples of such interactions have been discovered. This may be because combining data across studies, usually through meta-analysis of summary data from the contributing cohorts, is often a statistically inefficient approach for the detection of gene-environment interactions. Ideally, single, very large and well-genotyped prospective cohorts, with validated measures of environmental risk factor and disease outcomes should be used to study interactions. The presence of strong founder effects within those cohorts might further strengthen the capacity to detect novel genetic effects and gene-environment interactions. Access to accurate genealogical data would also aid in studying the diploid nature of the human genome, such as genomic imprinting (parent-of-origin effects). Here we describe two studies from northern Sweden (the GLACIER and VIKING studies) that fulfill these characteristics.