Pekka Martikainen’s research while affiliated with University of Helsinki and other places

Mental health problems are increasing, while childlessness is becoming more common. We examine how mental health disorders (MHD) of varying prevalence, severity, and symptoms (common, severe, and behavioural and addiction-related disorders) are related to childlessness, and whether these associations are explained by partnerships and the partner’s mental health.We use Finnish total population register data on cohorts born between 1977 and 1980 and follow individuals from the age of 18 to 39. We estimate discrete-time event history models for the annual likelihood of having a child for men and women, with MHDs, co-residential partnership, and the partner’s MHDs as the main explanatory variables. We measure MHD by using both diagnose information (ICD-10 codes) from the special health care registers and medication information (ATC-codes).All types of MHDs predicted lower likelihood of having a child, the annual probability being 0.8–1.3%-points lower for women and 1.0–1.8 %-points for men in age-controlled models. The strongest association was observed for severe mental disorders. Co-residential partnerships explained part of the difference between those with and without MHD (for any MHD 13% for women and 36% for men compared to age-controlled model). When both partners have an MHD, the likelihood for childlessness was higher compared to partners where only one of the partners had an MHD. We conclude that partnerships and partner’s mental health are important factors in explaining the relationship between mental health disorders and childlessness, particularly among men.

Population ageing may further increase formal care use. Strong predictors in addition to age include time to death and the cause of death. The aim of this study is to analyse trends in the use of formal care in Finland by these factors. We analysed patterns of care use among all Finnish residents who died at the age of 65 and older between 2005 and 2018 (263 660 men and 315 439 women), linking different administrative registers. We used multinomial logistic models to examine the time spent in healthcare and care-home facilities, stratifying our analyses by gender and time to death. Between 2005 and 2018, formal care use became increasingly concentrated in the last years of life for all causes of death, and the effect of age slightly diminished. However, in 2017–18, decedents aged 65 in their last year of life spent up to seven months less in care than their counterparts aged 105. Over time, unadjusted per-capita care usage in the last seven years of life increased from 9.3 to 10.5 months for men, and from 16.8 to 19.3 months for women. Concurrently, the total time spent in care on the population level increased by 44%. Age and time to death are major determinants of formal care use. An increasing age at death drove the increase in per-capita and total care usage over time. Population ageing will continue to increase future care needs; governments must prepare for this scenario.

Background Little is known about how alcohol policies experienced in adolescence are associated with later health. We assess whether age of exposure to stricter alcohol policies is associated with later alcohol-attributable hospitalizations and mortality. We take advantage of an alcohol advertising ban and alcohol tax increases introduced in 1975–1977 with relatively stable alcohol policies before and after. Methods We used Finnish register data on birth cohorts 1950–1964 (1,175,878 individuals) to assess cohort-wise hazard ratios for the first incidence of alcohol-attributable hospitalization and mortality, and mortality due to external and other causes at ages 21–54 years. Results Men who were aged 19 to 25 at the time of the restrictive reform had similar risks for alcohol-attributable hospitalization and mortality to the reference group of those aged 18 – legal drinking age – at the time of reform. For those underage at the time, hospitalization and mortality rates were incrementally smaller cohort by cohort. For example, men who were 17 at the time of the reform had lower hazard ratios of alcohol-attributable hospitalization: 0.91 (95% CI 0.87; 0.95) as did those who were 13 [0.85 (95% CI 0.81; 0.89)]. The findings were similar for external-cause mortality, and similar yet more uncertain for women. In contrast, mortality from other causes declined continuously from cohort to cohort. Conclusions Our findings are consistent with the hypothesis that stricter alcohol policies in adolescence reduce harmful alcohol consumption patterns extending into adulthood and manifesting as lower alcohol-related harm to health.

Background: Polygenic indices (PGIs) of various traits abound, but the knowledge remains limited on how they predict wide-ranging health indicators, including the risk of death. We investigated the associations between mortality and 35 different PGIs related to social, behavioural and psychological traits, and typically non-fatal health conditions. Methods: Data consist of Finnish adults from population-representative genetically informed epidemiological surveys (Finrisk 1992-2012, Health2000/2011, FinHealth 2017), linked to administrative registers (N: 40 097, 5948 deaths). Within-sibship analysis was complemented with dizygotic twins from Finnish twin study cohorts (N: 10 174, 2116 deaths). We estimated Cox proportional hazards models with mortality follow up 1995-2019. Results: PGIs most strongly predictive of all-cause mortality were ever smoking (hazard ratio [HR]=1.12, 95% confidence interval [95%CI] 1.09;1.14 per one standard deviation larger PGI), self-rated health (HR=0.90, 95%CI 0.88;0.93), body mass index (HR=1.10, 95%CI 1.07;1.12), educational attainment (HR=0.91, 95%CI 0.89;0.94, depressive symptoms (HR=1.07, 95%CI 1.04;1.10), and alcohol drinks per week (HR=1.06, 95%CI 1.04;1.09). Within-sibship estimates were approximately consistent with the population analysis. The investigated PGIs were typically more predictive for external than for natural causes of death. PGIs were more strongly associated with death occurring at younger ages, while among those who survived to age 80, the PGI-mortality associations were negligible. Conclusions: PGIs related to the best-established mortality risk phenotypes had the strongest associations with mortality. They offer moderate additional prediction even when mutually adjusting with their phenotype. Within-sibship analysis indicated no evidence for inflation of PGI-mortality associations by population phenomena.

Background The background of educational disparities in coronary heart disease (CHD) risk is still not well understood. We used a polygenic score for education (PGS EDU ), socioeconomic indicators and indicators of CHD risk to investigate whether these disparities result from causality or are influenced by shared factors. Methods Population-based health surveys including baseline measures on cardiometabolic risk factors at 25–70 years of age (N=32 610) and PGS EDU were conducted in Finland between 1992 and 2011. Longitudinal information on education, social class, income and CHD incidence (1716 CHD cases up to 2019) was based on national registers. Linear regression, Poisson regression, Cox regression and linear structural equation models were used. Results Education and PGS EDU were inversely associated with body mass index, systolic and diastolic blood pressure, total cholesterol and CHD incidence and positively associated with high-density lipoprotein cholesterol in men and women. Part of the associations of PGS EDU with CHD incidence (57% in men and 28% in women) and cardiometabolic factors (30%–55% and 31%–92%, respectively) were mediated by education, social class and income, but a substantial part of them was independent of socioeconomic factors. These associations were consistent across different levels of education. Conclusions PGS EDU captures CHD risk that is not solely attributable to education and other socioeconomic indicators. This suggests that not only causality affects the educational disparities of CHD risk but also factors reflected by PGS EDU can contribute to them. Identifying these factors can help to understand and reduce socioeconomic health disparities.

Objective We assessed trends in educational inequalities in obesity‐attributable mortality (OAM) and their contribution to educational inequalities in all‐cause mortality for people aged 30 years and older, in England and Wales (1991–2017), Finland (1978–2017), and Italy (1990–2018). Methods In our population‐level study, we estimated the shares of all‐cause mortality due to OAM by educational level (i.e., low, middle, and high) by applying the population‐attributable fraction formula to harmonized obesity prevalence data by educational level, along with sex‐ and age‐specific relative risks of dying from obesity. We obtained OAM rates by multiplying the shares with individually linked all‐cause mortality data by educational level. We measured absolute inequalities in OAM and all‐cause mortality by the slope index of inequality. Results OAM largely increased for the different sex‐ and education‐specific populations and increased most strongly for those with low educational level up to 2010 to 2015. Educational inequalities in OAM initially increased but stabilized or declined from at least 2008 onward. Obesity contributed, on average, 15% to absolute educational inequalities in all‐cause mortality in 1991 through 2017. Conclusions The mortality impact of the obesity epidemic by educational level changed over time. Although the observed change from increasing to declining or stable educational inequalities is encouraging, reducing OAM in all socioeconomic groups remains a challenge.

Type 1 diabetes (T1D) is known to have adverse long-term health and social outcomes, but the modifying factors are largely unknown. We investigate to what extent T1D outcomes are modified by area-, household-, and individual-level social and economic characteristics in Finland. National registers from 1987 to 2020 were used to identify all 3,048 children with T1D diagnosed at age seven to 17 and matched controls (n=78,883). Using causal forests, we estimated the average association between T1D and adult health, social, and economic outcomes at ages 28-30, and the modifying roles of more than 30 covariates. Individuals with T1D were more likely to be deceased (2.3% vs. 0.9% in the control group), to use antidepressants (17% vs. 13%), and to be unpartnered (36% vs. 32%), and had more months of unemployment (1.18 vs. 1.02) and lower annual income (25,697 euros vs. 27,453 euros), but not significantly lower educational attainment (10.8% vs. 10.3% with only basic education). T1D had a heterogenous association with all outcomes except mortality and income, but no specific population subgroup was vulnerable across all outcomes. However, women with T1D had particularly high rates of antidepressant use, and individuals from low socioeconomic families were more likely to be unpartnered.