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Aims: Married individuals have a lower coronary heart disease (CHD) risk than non-married, but the mechanisms behind this are not fully understood. We analyzed whether genetic liability to CHD may affect these associations. Methods: Marital status, a polygenic score of CHD (PGS-CHD), and other risk factors for CHD were measured from 35,444 participants (53% female) in Finnish population-based surveys conducted between 1992 and 2012. During the register-based follow-up until 2020, there were 2439 fatal and non-fatal incident CHD cases. The data were analyzed using linear and Cox regression models. Results: Divorced and cohabiting men and women had a higher genetic risk of CHD than married individuals, but the difference was very small (0.023–0.058 standard deviation of PGS-CHD, p-values 0.011–0.429). Both marital status and PGS-CHD were associated with CHD incidence, but the associations were largely independent. Adjusting for behavioral and metabolic risk factors for CHD explained part of these associations (11–20%). No interaction was found between marital status and PGS-CHD for CHD incidence. Conclusions: We showed minor differences between the marital status categories in PGS-CHD and demonstrated that marital status and genetic liability predicted CHD incidence largely independently. This emphasizes the need to measure multiple risk factors when predicting CHD risk.

Background Previous Mendelian randomization (MR) studies using population samples (population MR) have provided evidence for beneficial effects of educational attainment on health outcomes in adulthood. However, estimates from these studies may have been susceptible to bias from population stratification, assortative mating and indirect genetic effects due to unadjusted parental genotypes. MR using genetic association estimates derived from within-sibship models (within-sibship MR) can avoid these potential biases because genetic differences between siblings are due to random segregation at meiosis. Methods Applying both population and within-sibship MR, we estimated the effects of genetic liability to educational attainment on body mass index (BMI), cigarette smoking, systolic blood pressure (SBP) and all-cause mortality. MR analyses used individual-level data on 72 932 siblings from UK Biobank and the Norwegian HUNT study, and summary-level data from a within-sibship Genome-wide Association Study including >140 000 individuals. Results Both population and within-sibship MR estimates provided evidence that educational attainment decreased BMI, cigarette smoking and SBP. Genetic variant-outcome associations attenuated in the within-sibship model, but genetic variant-educational attainment associations also attenuated to a similar extent. Thus, within-sibship and population MR estimates were largely consistent. The within-sibship MR estimate of education on mortality was imprecise but consistent with a putative effect. Conclusions These results provide evidence of beneficial individual-level effects of education (or liability to education) on adulthood health, independently of potential demographic and family-level confounders.

Background The associations between height, socioeconomic position (SEP) and coronary heart disease (CHD) incidence are well established, but the contribution of genetic factors to these associations is still poorly understood. We used a polygenic score (PGS) for height to shed light on these associations. Methods Finnish population-based health surveys in 1992–2011 (response rates 65–93%) were linked to population registers providing information on SEP and CHD incidence up to 2019. The participants (N=29 996; 54% women) were aged 25–75 at baseline, and there were 1767 CHD incident cases (32% in women) during 472 973 person years of follow-up. PGS-height was calculated based on 33 938 single-nucleotide polymorphisms, and residual height was defined as the residual of height after adjusting for PGS-height in a linear regression model. HRs of CHD incidence were calculated using Cox regression. Results PGS-height and residual height showed clear gradients for education, social class and income, with a larger association for residual height. Residual height also showed larger associations with CHD incidence (HRs per 1 SD 0.94 in men and 0.87 in women) than PGS-height (HRs per 1 SD 0.99 and 0.97, respectively). Only a small proportion of the associations between SEP and CHD incidence was statistically explained by the height indicators (6% or less). Conclusions Residual height associations with SEP and CHD incidence were larger than for PGS-height. This supports the role of material and social living conditions in childhood as contributing factors to the association of height with both SEP and CHD risk.

Background Depression is a risk factor for coronary heart disease (CHD), but less is known whether genetic susceptibility to CHD or regional-level social indicators modify this association. Methods Risk factors of CHD including a Polygenic Risk Score (PRS) were measured for 19 999 individuals residing in Finland in 1997, 2002, 2007 and 2012 (response rates 60%–75%). During the register-based follow-up until 2015, there were 1381 fatal and non-fatal incident CHD events. Unemployment rate, degree of urbanisation and crime rate of the municipality of residence were used as regional level social indicators. HRs were calculated using register-based antidepressant purchases as a non-reversible time-dependent covariate. Results Those having depression and in the highest quartile of PRS had somewhat higher CHD risk than predicted only by the main effects of depression and PRS (HR for interaction 1.53, 95% CI 0.95 to 2.45). Depression was moderately associated with CHD in high crime (HR 1.51, 95% CI 1.20 to 1.90) and weakly in low crime regions (HR 1.07, 95% CI 0.86 to 1.33; p value of interaction=0.087). Otherwise, we did not found evidence for interactions. Conclusions Those having both depression and high genetic susceptibility need a special attention in healthcare for CHD.

Background Genetic vulnerability to coronary heart disease (CHD) is well established, but little is known whether these effects are mediated or modified by equally well-established social determinants of CHD. We estimate the joint associations of the polygenetic risk score (PRS) for CHD and education on CHD events. Methods The data are from the 1992, 1997, 2002, 2007 and 2012 surveys of the population-based FINRISK Study including measures of social, behavioural and metabolic factors and genome-wide genotypes (N=26 203). Follow-up of fatal and non-fatal incident CHD events (N=2063) was based on nationwide registers. Results Allowing for age, sex, study year, region of residence, study batch and principal components, those in the highest quartile of PRS for CHD had strongly increased risk of CHD events compared with the lowest quartile (HR=2.26; 95% CI: 1.97 to 2.59); associations were also observed for low education (HR=1.58; 95% CI: 1.32 to 1.89). These effects were largely independent of each other. Adjustment for baseline smoking, alcohol use, body mass index, igh-density lipoprotein (HDL) and total cholesterol, blood pressure and diabetes attenuated the PRS associations by 10% and the education associations by 50%. We do not find strong evidence of interactions between PRS and education. Conclusions PRS and education predict CHD events, and these associations are independent of each other. Both can improve CHD prediction beyond behavioural risks. The results imply that observational studies that do not have information on genetic risk factors for CHD do not provide confounded estimates for the association between education and CHD.

Previous research has shown that an advantaged social class position protects individuals from unemployment, but less is known about how this relationship has developed after the turn of the millennium, how it varies by gender and to what extent education contributes to the association between these factors. We assess these questions using register-based data on the Finnish labour force over a 28-year period between 1988 and 2015. The overall risk of unemployment was 2.7–3.7-fold among manual classes compared to upper non-manual classes, and 1.4–1.7-fold among lower compared to upper non-manual classes. Controlling for education attenuated the differences between social classes by about two-thirds. Social class disparities were somewhat more distinct among men than among women, but gender differences narrowed over time. Overall, temporal changes were small, especially among men, except for a curvilinear pattern observed for the relative unemployment risk of the lower non-manual class. To conclude, despite a comparatively egalitarian context and drastic changes in economic conditions and labour market structures over time, social stratification in unemployment has been substantial and considerably persistent. This is in line with the conceptualization of social class underpinning differing employment relations and, therefore, inherently creating variation in labour market risks.

Surveys generally overestimate the overall level of voter turnout in elections due to both the misreporting of voting and nonresponse. It is sometimes argued that socioeconomic differences in turnout are exaggerated in surveys because social desirability has a more pronounced effect on eligible voters in more advantaged socioeconomic positions. However, the contribution of nonresponse bias has not been taken into consideration in these assessments. Using a register-linked survey with information on the education, occupational social class, income, and voting in the 2015 Finnish parliamentary elections of both respondents and nonrespondents, this study shows that nonresponse bias leads to not only a larger overestimation of the overall level of turnout than social desirability, but also an underestimation of educational, social class, and income-related differences in the propensity to vote. Socioeconomic differences in the probability of voting in register-based data were at least two-thirds larger than differences obtained when using standard survey techniques. This finding implies that socioeconomic inequality in electoral participation is a more pressing social problem than previous evidence might indicate.

Occupation-based social class is an important, yet under-explored, factor in electoral participation. In this article, social class differences in voter turnout over time are measured, and how two other resources - namely income and health - mediate or modify this relationship is analysed. The analysis is based on an individual-level register-based 11 percent sample of the entire electorate in the 1999 Finnish parliamentary elections, and secondarily on smaller register-based samples in the 2012 presidential and municipal elections. Results show that income mediates part of the effects of social class on voting, while social class and utilised health indicators exert mainly independent effects on turnout. Social class differences remain largely stable in all income and hospital care groups, except that no differences between classes are observed among those most severely affected by health problems. Results are also mostly similar between those of working age and the older population, and between men and women, and remain stable over time and in different types of elections. The findings imply that social class should be taken account in theoretical and empirical models of turnout.