BackgroundWorldwide, populations are aging and the health of elderly individuals is deteriorating. Healthy habits may slow the process of health deterioration, but research investigating relationships between health and various health behaviors is lacking. This study aimed to investigate the relationships between health and health behaviors (alcohol consumption, smoking, dietary behavior, and physical activity) among older men and women in Russia.MethodsWave 1 Study on Global AGEing and Adult Health data (2007–2010) collected in the European portion of the Russian Federation, southern federal districts of the European portion of Russia and from the Asian portion of the country were used for this study. Relationships between self-rated health and four risk behavior measures [physical activity, alcohol consumption, smoking, and dietary behavior (fruit and vegetable consumption)] were examined. Analyses controlled for several socioeconomic factors: gender, age, marital status, educational level, area of residence, ethnicity, and employment status. To estimate the effect of healthy behavior on the probability that participants rated their health as very good/good/moderate/bad/very bad, the ordered logit model and average marginal effects were used.ResultsSufficient physical activity affected self-rated health most significantly in both genders, whereas excessive alcohol consumption had no significant effect. Smoking had explanatory power (being a current smoker decreased the probability of a very good health assessment and increased the probability of a very bad rating compared with being a non-smoker) among men, but not women. Fruit and vegetable consumption had a strong effect on self-rated health among women, but not men.ConclusionsThe results of this study indicate that health behaviors, especially physical activity, are important for the health of Russia’s older population. Smoking behavior had a strong impact on the health of men, whereas fruit and vegetable consumption was a relevant factor for women. Policies promoting smoking reduction and healthy diet should thus target older men and women, respectively.

This study examined relationships between and predictors of objective and subjective health measures among 766 individuals aged ≥ 45 years in India using the 2010 pilot wave of the Longitudinal Aging Study in India (LASI). Correlations between and gender differences in objective [grip strength, lung function] and subjective [self-rated health (SRH), dependence in activities of daily living (dADL)] health measures were examined. Multivariate logistic regression analyses, accounting for sample design, were conducted to identify predictors of poor health. Fewer individuals were classified as at risk according to subjective (SRH, 9 %; dADL, 12 %) than objective (lung function, 57 %; grip strength, 77 % women, 87 % men) indicators. Poor SRH was only weakly correlated with dADL (r = 0.103, p ≤ 0.05) and grip strength (r = −0.138, p ≤ 0.001). From this study we conclude that older Indians tend to report more positive perception of health than the objective measures of health indicates, and that subjective and objective health indicators capture different aspects of health and only weakly correlated.

BackgroundThe EQ-5D is a widely used preference-based instrument to measure health-related quality of life. Some methodological drawbacks of its three-level version (EQ-5D-3L) prompted development of a new format (EQ-5D-5L). There is no clear evidence that the new format outperforms the standard version.ObjectiveThe objective of this study was to make a head-to-head comparison of the EQ-5D-3L and EQ-5D-5L in a discrete choice model setting giving special attention to the consistency and logical ordering of coefficients for the attribute levels and to the differences in health-state values.MethodsUsing efficient designs, 240 pairs of EQ-5D-3L health states and 240 pairs of EQ-5D-5L health states were generated in a pairwise choice format. The study included 3698 Dutch general population respondents, analyzed their responses using a conditional logit model, and compared the values elicited by EQ-5D-3L and EQ-5D-5L for different health states.ResultsNo inconsistencies or illogical ordering of level coefficients were observed in either version. The proportion of severe health states with low values was higher in the EQ-5D-5L than in the EQ-5D-3L, and the proportion of mild/moderate states was lower in the EQ-5D-5L than in the EQ-5D-3L. Moreover, differences were observed in the relative weights of the attributes.ConclusionOverall distribution of health-state values derived from a large representative sample using the same measurement framework for both versions showed differences between the EQ-5D-3L and EQ-5D-5L. However, even small differences in the phrasing (language) of the descriptive system or in the valuation protocol can produce differences in values between these two versions.

To develop patient-centered health content for a novel generic instrument (Château Sant e Base [CS-Base]) that is suitable to generate values for health status. Methods: Candidate items were drawn from existing health frameworks of generic health status instruments and placed in a diagram (HealthFAN TM , Zeist, the Netherlands). Through an online survey, patients with a wide range of diseases were asked to select the 9 items that were most important to them. The importance of the items for the whole study group was determined by means of frequency distributions. Results: After handling duplicates and overlap, the remaining set of 47 items was placed in the HealthFAN. Among the 2256 Dutch patients who started the survey, the most common diagnoses were neck and back pain, diabetes, and asthma/chronic obstructive pulmonary disease. The 5 health items mentioned most frequently as most important were pain, personal relationships, fatigue, memory, and vision. Hearing and vision, anxiety and depression, and independence and self-esteem seemed highly intertwined, so we chose to pair these items. Conclusions: A total of 12 health items were included in CS-Base. Its content is largely based on patient input and enables classification of patients' health status. CS-Base can be administered by means of an app on a mobile phone, which makes it a convenient and attractive tool for patients and researchers.