A Mediterranean-type diet is associated with better metabolic profile in urban Polish adults: Results from the HAPIEE study

The aim of this study was to evaluate the relationship between adherence to a Mediterranean-type diet and metabolic syndrome (MetS) in the Polish arm of the Health, Alcohol and Psychosocial factors In Eastern Europe (HAPIEE) cohort study

Determinants of self rated health and mortality in Russia – are they the same?

BACKGROUND: Research into Russia's health crisis during the 1990s includes studies of both mortality and self-rated health, assuming that the determinants of the two are the same. In this paper, we tested this assumption, using data from a single study on both outcomes and socioeconomic, lifestyle and psychological predictor variables. METHODS: We analysed data from 7 rounds (1994-2001) of the Russia Longitudinal Monitoring Survey, a panel study of a general population sample (11,482 adults aged over 18 living in households of 2 or more people). Self-rated health was measured on a 5 point scale and dichotomised by combining responses "very poor" and "poor" into poor health. Deaths (n = 782) during a mean follow up of 4.1 years were reported by another household member. Associations between several predictor variables and poor or very poor self-rated health and mortality were measured using logistic regression and Cox proportional hazards analysis respectively. RESULTS: Poor self-rated health was significantly associated with mortality; hazard ratios, compared with very good, good or average health, were 1.69 (1.36-2.10) in men and 1.74 (1.38-2.20) in women. Low education predicted both mortality and poor self-rated health, but income predicted subjective health more strongly. Smoking doubled the risk of death but was unrelated to subjective wellbeing. Frequent drinkers experienced greater mortality than occasional drinkers, despite reporting better health. In contrast, dissatisfaction with life predicted poor self-rated health, but not mortality. CONCLUSION: Differences between the predictors of subjective health and mortality, even though these outcomes were strongly associated, suggest that influences on subjective health are not restricted to serious disease. These findings also suggest the presence of risk factors for relatively sudden deaths in apparently well people, although further research is required. Meanwhile, caution is required when using studies of self-rated health in Russia to understand the determinants of mortality

Determinants of cardiovascular disease and other non-communicable diseases in Central and Eastern Europe: Rationale and design of the HAPIEE study

BACKGROUND: Over the last five decades, a wide gap in mortality opened between western and eastern Europe; this gap increased further after the dramatic fluctuations in mortality in the former Soviet Union (FSU) in the 1990s. Recent rapid increases in mortality among lower socioeconomic groups in eastern Europe suggests that socioeconomic factors are powerful determinants of mortality in these populations but the more proximal factors linking the social conditions with health remain unclear. The HAPIEE (Health, Alcohol and Psychosocial factors In Eastern Europe) study is a prospective cohort study designed to investigate the effect of classical and non-conventional risk factors and social and psychosocial factors on cardiovascular and other non-communicable diseases in eastern Europe and the FSU. The main hypotheses of the HAPIEE study relate to the role of alcohol, nutrition and psychosocial factors. METHODS AND DESIGN: The HAPIEE study comprises four cohorts in Russia, Poland, the Czech Republic and Lithuania; each consists of a random sample of men and women aged 45–69 years old at baseline, stratified by gender and 5 year age groups, and selected from population registers. The total planned sample size is 36,500 individuals. Baseline information from the Czech Republic, Russia and Poland was collected in 2002–2005 and includes data on health, lifestyle, diet (food frequency), socioeconomic circumstances and psychosocial factors. A short examination included measurement of anthropometric parameters, blood pressure, lung function and cognitive function, and a fasting venous blood sample. Re-examination of the cohorts in 2006–2008 focuses on healthy ageing and economic well-being using face-to-face computer assisted personal interviews. Recruitment of the Lithuanian cohort is ongoing, with baseline and re-examination data being collected simultaneously. All cohorts are being followed up for mortality and non-fatal cardiovascular events. DISCUSSION: The HAPIEE study will provide important new insights into social, behavioural and biological factors influencing mortality and cardiovascular risk in the region

Have regional inequalities in life expectancy widened within the European Union between 1991 and 2008?

<b>BACKGROUND:</b> Health inequalities have widened within and between many European countries over recent decades, but Europe-wide sub-national trends have been largely overlooked. For regions across the European Union (EU), we assess how geographical inequalities (i.e., between regions) and sociospatial inequalities (i.e., between regions grouped by an area-level measure of average household income) in male and female life expectancy have changed between 1991 and 2008.<p></p> <b>METHODS:</b> Household income, life expectancy at birth and population count data were obtained for 129 regions (level 2 Nomenclature of Statistical Territorial Units, 'NUTS') in 13 European countries with 1991-2008 data (2008 population = 272 million). We assessed temporal changes in the range of life expectancies, for all regions and for Western and Eastern European regions separately.<p></p> <b>RESULTS:</b> Between 1991 and 2008, the geographical range of life expectancies found among European regions remained relatively constant, with the exception of life expectancy among male Eastern Europeans, for whom the range widened by 2.8 years. Sociospatial inequalities in life expectancy (1999-2008 data only) remained constant for all regions combined and for Western Europe, but more than doubled in size for male Eastern Europeans. For female Eastern Europeans, life expectancy was unrelated to regional household income.<p></p> <b>CONCLUSIONS:</b>Regional life-expectancy inequalities in the EU have not narrowed over 2 decades, despite efforts to reduce them. Household income differences across European regions may partly explain these inequalities. As inequalities transcend national borders, reduction efforts may require EU-wide coordination in addition to national efforts.<p></p&gt

ATHLOS Healthy Aging Scale score as the predictor of all-cause mortality in Poland and Czechia

Background: The ATHLOS consortium (Aging Trajectories of Health-Longitudinal Opportunities and Synergies) used data from several aging cohorts to develop a novel scale measuring healthy aging comprehensively and globally (ATHLOS Healthy Aging Scale). In the present study, we assessed the predictive performance of the ATHLOS Healthy Aging Scale for all-cause mortality in middle-aged and older adults. Methods: Data from the Polish and Czech HAPIEE (Health Alcohol and Psychosocial factors In Eastern Europe) prospective cohorts were used. There were 10,728 Poles and 8,857 Czechs recruited. The ATHLOS Healthy Aging Scale score was calculated for all participants using data from the baseline examination carried out from 2002 to 2005. The follow-up for all-cause mortality was completed over 14 years. The associations between quintiles of the ATHLOS Healthy Aging Scale and all-cause mortality were estimated using Cox proportional hazards models. Results: A total of 9,922 Polish and 8,518 Czech participants contributed ATHLOS Healthy Aging Scale and mortality data with 1,828 and 1,700 deaths, respectively. After controlling for age, the ATHLOS Healthy Aging Scale score was strongly associated with mortality in a graded fashion for both genders and countries (hazard ratios for lowest vs. highest quintile were 2.98 and 1.96 for Czech and Polish women and 2.83 and 2.66 for Czech and Polish men, respectively). The associations were only modestly attenuated by controlling for education, economic activity, and smoking, and there was further modest attenuation after additional adjustment for self-rated health. Conclusion: The novel ATHLOS Healthy Aging Scale is a good predictor of all-cause mortality in Central European urban populations, suggesting that this comprehensive measure is a useful tool for the assessment of the future health trajectories of older persons

Development and validation of two SCORE-based cardiovascular risk prediction models for Eastern Europe: a multicohort study.

AIMS: Cardiovascular disease (CVD) risk prediction models are used in Western European countries, but less so in Eastern European countries where rates of CVD can be two to four times higher. We recalibrated the SCORE prediction model for three Eastern European countries and evaluated the impact of adding seven behavioural and psychosocial risk factors to the model. METHODS AND RESULTS: We developed and validated models using data from the prospective HAPIEE cohort study with 14 598 participants from Russia, Poland, and the Czech Republic (derivation cohort, median follow-up 7.2 years, 338 fatal CVD cases) and Estonian Biobank data with 4632 participants (validation cohort, median follow-up 8.3 years, 91 fatal CVD cases). The first model (recalibrated SCORE) used the same risk factors as in the SCORE model. The second model (HAPIEE SCORE) added education, employment, marital status, depression, body mass index, physical inactivity, and antihypertensive use. Discrimination of the original SCORE model (C-statistic 0.78 in the derivation and 0.83 in the validation cohorts) was improved in recalibrated SCORE (0.82 and 0.85) and HAPIEE SCORE (0.84 and 0.87) models. After dichotomizing risk at the clinically meaningful threshold of 5%, and when comparing the final HAPIEE SCORE model against the original SCORE model, the net reclassification improvement was 0.07 [95% confidence interval (CI) 0.02-0.11] in the derivation cohort and 0.14 (95% CI 0.04-0.25) in the validation cohort. CONCLUSION: Our recalibrated SCORE may be more appropriate than the conventional SCORE for some Eastern European populations. The addition of seven quick, non-invasive, and cheap predictors further improved prediction accuracy

Age at natural menopause in three Central and Eastern European urban populations: The HAPIEE study

Objectives: To investigate the age at menopause in three urban populations in Central and Eastern Europe and to assess whether the (suspected) differences can be explained by a range of socioeconomic, reproductive and behavioural factors. Methods: The Health, Alcohol and Psychosocial factors in Eastern Europe (HAPIEE) Study examined random samples of populations aged 45-69 years in Novosibirsk (Russia), Krakow (Poland) and six Czech towns. Participants completed a questionnaire and attended an examination in clinic. A total of 12,676 of women were included in these analyses. Results: The median age at menopause was 50 years in Novosibirsk, 51 years in Czech towns and 52 years in Krakow; the Cox regression hazard ratios of menopause, compared with Krakow, were 1.47 (95% CI 1.40-1.55) for Novosibirsk and 1.10 (1.04-1.16) for Czech women. In multivariate analyses, higher education, using vitamin and mineral supplements and ever use of oral contraceptives were associated with later menopause, while smoking, abstaining from alcohol and low physical activity were associated with earlier menopause. These factors, however, did not explain the differences between populations; the multivariate hazard ratios of menopause, compared with Krakow, were 1.48 (1.40-1.57) for Novosibirsk and 1.11 (1.05-1.17) for Czech women. Conclusions: In this large population based study, differences in age at menopause between Central and Eastern Europe populations were substantial and unexplained by a range of risk factors. Associations of age at menopause with risk factors were largely consistent with studies in other populations. © 2013 Elsevier Ireland Ltd

The effects of socioeconomic status and indices of physical environment on reduced birth weight and preterm births in Eastern Massachusetts

This is an Open Access article distributed under the terms of the Creative Commons Attribution License (http://creativecommons.org/licenses/by/2.0), which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited.Background: Air pollution and social characteristics have been shown to affect indicators of health. While use of spatial methods to estimate exposure to air pollution has increased the power to detect effects, questions have been raised about potential for confounding by social factors.Methods: A study of singleton births in Eastern Massachusetts was conducted between 1996 and 2002 to examine the association between indicators of traffic, land use, individual and area-based socioeconomic measures (SEM), and birth outcomes ( birth weight, small for gestational age and preterm births), in a two-level hierarchical model.Results: We found effects of both individual ( education, race, prenatal care index) and area-based ( median household income) SEM with all birth outcomes. The associations for traffic and land use variables were mainly seen with birth weight, with an exception for an effect of cumulative traffic density on small for gestational age. Race/ethnicity of mother was an important predictor of birth outcomes and a strong confounder for both area-based SEM and indices of physical environment. The effects of traffic and land use differed by level of education and median household income.Conclusion: Overall, the findings of the study suggested greater likelihood of reduced birth weight and preterm births among the more socially disadvantaged, and a greater risk of reduced birth weight associated with traffic exposures. Results revealed the importance of controlling simultaneously for SEM and environmental exposures as the way to better understand determinants of health.This work is supported by the Harvard Environmental Protection Agency (EPA) Center, Grants R827353 and R-832416, and National Institute for Environmental Health Science (NIEHS) ES-0002