Physical-mental health comorbidity: A population-based cross-sectional study

Background Multimorbidity is associated with physical-mental health comorbidity (PMHC). However, the scope of overlap between physical and mental conditions, associated factors, as well as types of mental illness involved are not well described in Eastern Europe. This study aims to assess the PMHC burden in the Estonian population. Methods In this population-based cross-sectional study we obtained health claims data for 55 chronic conditions from the Estonian Health Insurance Fund (EHIF) database, which captures data for all publicly insured individuals (n = 1 240 927 or 94.1% of the total population as of 31 December 2017). We assessed the period-prevalence (3 years) of chronic physical and mental health disorders, as well as associations between them, by age and sex. Results Half of the individuals (49.1% (95% CI 49.0–49.3)) had one or more chronic conditions. Mental health disorders (MHD) were present in 8.1% (8.1–8.2) of individuals, being higher among older age groups, women, and individuals with a higher number of physical conditions. PMHC was present in 6.2% (6.1–6.2) of the study population, and 13.1% (13.0–13.2) of the subjects with any chronic physical disorder also presented with at least one MHD. Dominating MHDs among PMHC patients were anxiety and depression. The prevalence of MHD was positively correlated with the number of physical disorders. We observed variation in the type of MHD as the number of physical comorbidities increased. The prevalence of anxiety, depression, and mental and behavioral disorders due to the misuse of alcohol and other psychoactive substances increased as physical comorbidities increased, but the prevalence of schizophrenia and dementia decreased with each additional physical disease. After adjusting for age and sex, this negative association changed the sign to a positive association in the case of dementia and mental and behavioral disorders due to psychoactive substance misuse. Conclusions The burden of physical-mental comorbidity in the Estonian population is relatively high. Further research is required to identify clusters of overlapping physical and mental disorders as well as the interactions between these conditions. Public health interventions may include structural changes to health care delivery, such as an increased emphasis on integrated care models that reduce barriers to mental health care.

Risk Assessment of the Progression of Early Knee Osteoarthritis by Collagen Neoepitope C2C: A Longitudinal Study of an Estonian Middle-Aged Cohort

One of the unmet needs to be addressed is prognostic biomarkers for early knee osteoarthritis (kOA). We aimed to study the association of urinary collagen type-II C-terminal cleavage neoepitope (uC2C) with the emergence and progression of kOA. The longitudinal data of 330 subjects (aged 32–60 years) from an Estonian population-based cohort were used. The radiographic progression was evaluated by the grading system of Nagaosa et al. of knee compartments at baseline and three years later. The emerging kOA consisted of subjects with developing osteophytes or joint space narrowing, whereas kOA progressors showed aggravation of radiographic grade. Baseline uC2C levels were measured by the IBEX-uC2C assay. At baseline, the subjects were middle-aged (mean age, 47.6 years) and overweight (mean BMI, 28.0 kg/m2), and the majority of them (51.2%) had a diagnosis of kOA grade 1. Multiple logistic regression models adjusted for sex, age, and BMI were used for risk calculations. We demonstrate that increased uC2C accurately predicted the risk of emerging of kOA (OR = 5.87 (1.71–20.22); AUC = 0.79) compared with controls without radiographic kOA over 12 years. However, the most accurate prediction of progression by the biomarker was found in women (OR = 23.0 (2.2–245), AUC = 0.91). In conclusion, uC2C may be a promising candidate as a prognostic biomarker for kOA progression, particularly of emerging kOA in women.

Understanding gender segregation through Call Data Records: An Estonian case study

Understanding segregation plays a significant role in determining the development pathways of a country as it can help governmental and other concerned agencies to prepare better-targeted policies for the needed groups. However, inferring segregation through alternative data, apart from governmental surveys remains limited due to the non-availability of representative datasets. In this work, we utilize Call Data Records (CDR) provided by one of Estonia’s major telecom operators to research the complexities of social interaction and human behavior in order to explain gender segregation. We analyze the CDR with two objectives. First, we study gender segregation by exploring the social network interactions of the CDR. We find that the males are tightly linked which allows information to spread faster among males compared to females. Second, we perform the micro-analysis using various users’ characteristics such as age, language, and location. Our findings show that the prime working-age population (i.e., (24,54] years) is more segregated than others. We also find that the Estonian-speaking population (both males and females) are more likely to interact with other Estonian-speaking individuals of the same gender. Further to ensure the quality of this dataset, we compare the CDR data features with publicly available Estonian census datasets. We observe that the CDR dataset is indeed a good representative of the Estonian population, which indicates that the findings of this study reasonably reflect the reality of gender segregation in the Estonian Landscape.

Differences in local population history at the finest level: the case of the Estonian population

Several recent studies detected fine-scale genetic structure in human populations. Hence, groups conventionally treated as single populations harbour significant variation in terms of allele frequencies and patterns of haplotype sharing. It has been shown that these findings should be considered when performing studies of genetic associations and natural selection, especially when dealing with polygenic phenotypes. However, there is little understanding of the practical effects of such genetic structure on demography reconstructions and selection scans when focusing on recent population history. Here we tested the impact of population structure on such inferences using high-coverage (~30×) genome sequences of 2305 Estonians. We show that different regions of Estonia differ in both effective population size dynamics and signatures of natural selection. By analyzing identity-by-descent segments we also reveal that some Estonian regions exhibit evidence of a bottleneck 10–15 generations ago reflecting sequential episodes of wars, plague and famine, although this signal is virtually undetected when treating Estonia as a single population. Besides that, we provide a framework for relating effective population size estimated from genetic data to actual census size and validate it on the Estonian population. This approach may be widely used both to cross-check estimates based on historical sources as well as to get insight into times and/or regions with no other information available. Our results suggest that the history of human populations within the last few millennia can be highly region specific and cannot be properly studied without taking local genetic structure into account.

Households and families in Estonian population

The statistical distribution of households and families by their size and structure can be received from population and household censuses, but it is also important to know this information between the censuses, as changes during the ten-year period can be quite remarkable. It is demonstrated that, since the last census in Estonia in 2011, the share of older age-groups has increased and the rate of children – decreased. The age at first marriage has increased for men and women respectively by 3 and 4 months per year. Consequently, the share of young people living without a partner has increased, but the process is different in men and women. The number of divorces has dropped, but this seems to be caused by the decline of marriages during the last decades. The age of women giving birth has also increased. During the last years, the number of third children has increased, but the number of first children has decreased. The distribution of households by their types was also studied and is presented in Table 1. It is evident that about one-sixth of the population lives alone; single-person households form the most numerous household type in present-day Estonia. From all households containing a couple, somewhat more than two-thirds are households with a married couple, others are households with a cohabiting couple. In average, the first ones are much older than the second ones. The number of households where two or more generations live together is marginal.