Measuring health inequalities in Albania: a focus on the distribution of general practitioners

BACKGROUND: The health workforce has a dynamically changing nature and the regular documentation of the distribution of health professionals is a persistent policy concern. The aim of the present study was to examine available human medical resources in primary care and identify possible inequalities regarding the distribution of general practitioners in Albania between 2000 and 2004. METHODS: With census data, we investigated the degree of inequality by calculating relative inequality indices. We plotted the Lorenz curves and calculated the Gini, Atkinson and Robin Hood indices and decile ratios, both before and after adjusting for mortality and consultation rates. RESULTS: The Gini index for the distribution of general practitioners in 2000 was 0.154. After adjusting for mortality it was 0.126, while after adjusting for consultation rates it was 0.288. The Robin Hood index for 2000 was 11.2%, which corresponds to 173 general practitioners who should be relocated in order to achieve equality. The corresponding figure after adjusting for mortality was 9.2% (142 general practitioners), while after adjusting for consultation rates the number was 20.6% (315). These figures changed to 6.3% (100), 6.3% (115) and 19.8% (315) in 2004. CONCLUSION: There was a declining trend in the inequality of distribution of general practitioners in Albania between 2000 and 2004. The trend in inequality was apparent irrespective of the relative inequality indicator used. The level of inequality varied depending on the adjustment method used. Reallocation strategies for general practitioners in Albania could be the key in alleviating the inequalities in primary care workforce distribution

On the curvature of the reporting function from objective reality to subjective feelings

I suggest the idea of a reporting function, r(.), from reality to feelings. The ‘happiness’ literature claims we have demonstrated diminishing marginal utility of income. I show not, and that knowing r(.)'s curvature is crucial. A quasi-experiment on heights is studied

Lifestyle and self-rated health: a cross-sectional study of 3,601 citizens of Athens, Greece

<p>Abstract</p> <p>Background</p> <p>Self-rated health (SRH) is a popular health measure determined by multiple factors. International literature is increasingly focusing on health-related behaviors such as smoking, dietary habits, physical activity, even religiosity. However, population-based studies taking into account multiple putative determinants of SRH in Greece are scarce. The aim of this study was to clarify possible determinants of SRH with an emphasis on the relationship between SRH and lifestyle variables in a large sample of urban citizens.</p> <p>Methods</p> <p>In this one-year cross-sectional study, a stratified random sample of 3,601 urban citizens was selected. Data were collected using an interview-based questionnaire about various demographic, socioeconomic, disease- and lifestyle related factors such as smoking, physical activity, dietary habits, sleep quality and religiosity. Multivariate logistic regression was used separately in three age groups [15-29 (N = 1,360), 30-49 (N = 1,122) and 50+ (N = 1,119) years old] in order to identify putative lifestyle and other determinants of SRH.</p> <p>Results</p> <p>Reporting of good SRH decreased with age (97.1%, 91.4% and 74.8%, respectively). Overall, possible confounders of the lifestyle-SRH relationship among age groups were sex, education, hospitalization during the last year, daily physical symptoms and disease status. Poor SRH was associated with less physical activity in the 15-29 years old (OR 2.22, 95%CI 1.14-4.33), with past or heavy smoking, along with no sleep satisfaction in the 30-49 years old (OR 3.23, 95%CI 1.35-7.74, OR 2.56, 95%CI 1.29-5.05, OR 1.79, 95%CI 1.1-2.92, respectively) and with obesity and no sleep satisfaction in the 50+ years old individuals (OR 1.83, 95%CI 1.19-2.81, OR 2.54, 95%CI 1.83-3.54). Sleep dissatisfaction of the 50+ years old was the only variable associated with poor SRH at the 0.001 p level of significance (OR 2.45, 99%CI 1.59 to 3.76). Subgroup analyses of the 15-19 years old individuals also revealed sleep dissatisfaction as the only significant variable correlated with SRH.</p> <p>Conclusions</p> <p>Slight differences in lifestyle determinants of SRH were identified among age groups. Sleep quality emerged as an important determinant of SRH in the majority of participants.</p

Factors associated with self-rated health status in university students: a cross-sectional study in three European countries

Mikolajczyk RT, Brzoska P, Maier C, et al. Factors associated with self-rated health status in university students: a cross-sectional study in three European countries. BMC Public Health. 2008;8(1): 215.Background: Self-rated health status (SRHS) is a reliable and valid measure for assessing the subjective and objective health of individuals. Previous studies have either focused predominantly on the elderly or investigated only a narrow range of factors potentially associated with SRHS. In examining student populations, these past studies were limited to single countries. The objectives of this study were to assess which candidate variables were independently associated with SRHS in university students, to compare these variables by country and by gender, and to investigate which of the variables was most important as a rating frame for SRHS. Methods: The data is from the Cross-National Student Health Survey, conducted in 2005 in universities in Germany, Bulgaria, and Poland (n = 2103; mean age = 20.7 years). SRHS was assessed with a single question using a five-point scale ranging from "excellent" to "poor". The study also measured a wide range of variables including: physical and psychological health, studying, social contacts/social support, and socio-demographic status. Results: Psychosomatic complaints (considered an aspect of physical health and, adjusted for psychological health) were the most important indicators in forming a rating frame for students' SRHS. There were few differences in the effects of variables associated with SRHS by gender (well-being: a measure of psychological health) and the variables associated with SRHS by country (well-being and self-efficacy). The remaining variables showed homogenous effects for both genders and for all three countries. Conclusion: The results suggest that SRHS can be reasonably used to compare students' health across countries. SRHS is affected by different physical, psychological and psychosomatic aspects of health; however, its strongest association is with psychosomatic complaints

Healthy life expectancy and the correlates of self-rated health in Bangladesh in 1996 and 2002

BACKGROUND: Life expectancy (LE) at birth has increased steadily in Bangladesh since its independence. When people live longer, quality of life becomes a central issue. This study examines whether healthy life expectancy (HLE) at ages 15, 25, 35, and 45 is keeping pace with LE at those ages between 1996 and 2002. It also seeks to investigate the correlates of self-rated health (SRH) in 1996 and 2002. METHODS: We used data from the World Values Survey conducted in 1996 and 2002 among individuals 15 years and older. The Sullivan method was used to compute HLE. Socio-demographic differences and their association with different states of health were examined by chi-square and Pearson’s correlation tests. Multiple linear regression models were fitted to examine the correlates of SRH. RESULTS: The results show that perceived health improved between 1996 and 2002. For males, statistically significant increases in the expected number of years lived in good SRH were found. Proportionally, in 2002, both males and females at ages 15, 25, 35 and 45 expected more life years in good health and fewer life years in fair and poor health than did their counterparts in 1996. Comparatively, males expected fewer life years spent in good health but a much larger proportion of expected life in good health than did females. Finally, in multivariate analyses, life satisfaction was the only factor found to be significantly and positively associated with SRH for males and females in both years, although in both years the association was much more pronounced for females than for males. CONCLUSION: This study documented changes in HLE during 1996-2002. Women outlive men, but they have a lower quality of life and are more likely to live a greater part of their remaining life in poor SRH. Life satisfaction as well as other significant factors associated with SRH should be promoted, with special attention given to women, to improve healthy life expectancy and the quality of life of the Bangladeshi people

A recursive partitioning approach to investigating correlates of self-rated health: The CARDIA Study

Self-rated health (SRH) is an independent predictor of mortality; studies have investigated correlates of SRH to explain this predictive capability. However, the interplay of a broad array of factors that influence health status may not be adequately captured with parametric multivariate regression. This study investigated associations between several health determinants and SRH using recursive partitioning methods. This non-parametric analytic approach aimed to reflect the social-ecological model of health, emphasizing relationships between multiple health determinants, including biological, behavioral, and from social/physical environments. The study sample of 3648 men and women was drawn from the year 15 (2000–2001) data collection of the CARDIA Study, USA, in order to study a young adult sample. Classification tree analysis identified 15 distinct, mutually exclusive, subgroups (eight with a larger proportion of individuals with higher SRH, and seven with a larger proportion of lower SRH), and multi-domain risk and protective factors associated with subgroup membership. Health determinant profiles were not uniform between subgroups, even for those with similar health status. The subgroup with the largest proportion of higher SRH was characterized by several protective factors, whilst that with the largest proportion of lower SRH, with several negative risk factors; certain factors were associated with both higher and lower SRH subgroups. In the full sample, physical activity, education and income were highest ranked by variable importance (random forests analysis) in association with SRH. This exploratory study demonstrates the utility of recursive partitioning methods in studying the joint impact of multiple health determinants. The findings indicate that factors do not affect SRH in the same way across the whole sample. Multiple factors from different domains, and with varying relative importance, are associated with SRH in different subgroups. This has implications for developing and prioritizing appropriate interventions to target conditions and factors that improve self-rated health status. Keywords: Self-rated health, Health determinants, Recursive partitioning methods, Classification tree analysis, Random forest