Background The general self-rated health (SRH) question is the most common health measure employed in large population surveys. This study contributes to research on the concurrent validity of SRH using representative data with biomarkers from the Czech Republic, a population not previously used to assess the SRH measure. This work determines the relative contribution of biomedical and social characteristics to an individual’s SRH assessment. Studies have already explored the associations between SRH and markers of physical health. However, according to a PubMed systematic literature search, the issue of the relative importance of physiological and psychosocial factors that affect individuals’ assessments of their SRH has generally been neglected. Methodology/Principal findings Using data from a specialized epidemiological survey of the Czech population (N = 1021), this study adopted ordinary least squares regression to analyze the extent to which variance in SRH is explained by biomedical measures, mental health, health behavior, and socioeconomic characteristics. This analysis showed that SRH variance can be largely attributed to biomedical and psychological measures. Socioeconomic characteristics (i.e. marital status, education, economic activity, and household income) contributed to around 5% of the total variance. After controlling for age, sex, location, and socioeconomic status, biomarkers (i.e. C-reactive protein, blood glucose, triglyceride, low-density lipoprotein, and high-density lipoprotein), number of medical conditions, and current medications explained 11% of the total SRH variance. Mental health indicators contributed to an additional 9% of the variance. Body mass index and health behaviors (i.e. smoking and alcohol consumption) explained less than 2% of the variance. Conclusions/Significance The results suggested that SRH was a valid measure of physiological and mental health in the Czech sample, and the observed differences were likely to have reflected inequalities in bodily and mental functions between social groups.
Study Objectives Social jetlag manifests as a difference of sleep timing on workdays and free days. Social jetlag is often associated with shorter, lower quality sleep, so it is unclear how much the chronic circadian misalignment contributes to observed negative health outcomes. We aimed to (1) investigate associations between social jetlag, chronotype (one of its determinants), and the levels of health markers; (2) to describe factors associated with social jetlag; (3) to examine whether working from home can reduce social jetlag. Methods Adult respondents participated in a nationally representative longitudinal survey of Czech households (individuals in each wave: n2018/19/20=5132/1957/1533), which included Munich ChronoType Questionnaire to evaluate chronotype and social jetlag. A subset provided blood samples (n2019=1957) for detection of nine biomarkers and was surveyed in three successive years (social jetlag calculated for n2018/19/20=3930/1601/1237). Data were analyzed by nonparametric univariate tests and mixed-effects multivariate regression with social jetlag, chronotype, sex, age, BMI and reported diseases as predictors and biomarker levels as outcomes. Results Higher social jetlag (≥0.65h) was significantly associated with increased levels of total cholesterol and low-density lipoprotein cholesterol, particularly in participants older than 50 years (Mann-Whitney, men: pCHL=0.0005, pLDL=0.0009; women: pCHL=0.0079, pLDL=0.0068). Extreme chronotypes were associated with cardiovascular disease risk markers regardless of social jetlag (Kruskal-Wallis, p<0.0001). Commuting to work and time stress were identified as important contributors to social jetlag. Individual longitudinal data showed that working from home decreased social jetlag and prolonged sleep. Conclusions We report significant associations between sleep phase preference, social jetlag and cardio-metabolic biomarkers.
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