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Background The Global Activity Limitation Indicator (GALI), the measure underlying the European indicator Healthy Life Years (HLY), is widely used to compare population health across countries. However, the comparability of the item has been questioned. This study aims to further validate the GALI in the adult European population. Methods Data from the European Health Interview Survey (EHIS), covering 14 European countries and 152,787 individuals, were used to explore how the GALI was associated with other measures of disability and whether the GALI was consistent or reflected different disability situations in different countries. Results When considering each country separately or all combined, we found that the GALI was significantly associated with measures of activities of daily living, instrumental activity of daily living, and functional limitations (P < 0.001 in all cases). Associations were largest for activity of daily living and lowest though still high for functional limitations. For each measure, the magnitude of the association was similar across most countries. Overall, however, the GALI differed significantly between countries in terms of how it reflected each of the three disability measures (P < 0.001 in all cases). We suspect cross-country differences in the results may be due to variations in: the implementation of the EHIS, the perception of functioning and limitations, and the understanding of the GALI question. Conclusion The study both confirms the relevance of this indicator to measure general activity limitations in the European population and the need for caution when comparing the level of the GALI from one country to another. [ABSTRACT FROM AUTHOR]

Women generally live longer than men, but women's longer lives are not necessarily healthy lives. The aim of this article is to describe the pattern of gender differences in expected years with and without activity limitations across 25 EU countries and to explore the association between gender differences and macro-level factors. We applied to the Eurostat life table's data from the Statistics of Income and Living Conditions Survey to estimate gender differences in life expectancy with and without activity limitations at age 50 for 2005. We studied the relationship between the gender differences and structural indicators using meta-regression techniques. Differences in years with activity limitations between genders were associated with the life expectancy (LE) and the size of the gender difference in LE. Gender difference in years with activity limitations were larger as the gross domestic product, the expenditure on elderly care and the indicator of life-long learning decreased, and as the inequality in income distribution increased. There was evidence of disparity in the associations between the more established EU countries (EU15) and the newer EU10 countries. Among the EU15, gender differences were positively associated with income inequality, the proportion of the population with a low education and the men's mean exit age from labour force. Among the EU10, inequalities were smaller with increasing expenditure in elderly care, with decreasing poverty risk and with decreasing employment rate of older people. The association between structural indicators and the gender gap in years with activity limitations suggests that gender differences can be reduced. [ABSTRACT FROM AUTHOR]

This study compares gender differences in Healthy Life Years (HLY) and unhealthy life years (ULY) between the original (EU15) and new member states (EU10). Based on the number of deaths, population and prevalence of activity limitations from the Statistics of Living and Income Conditions Survey (SILC) survey, we calculated HLY and ULY for the EU10 and EU15 in 2006 with the Sullivan method. We used decomposition analysis to assess the contributions of mortality and disability and age to gender differences in HLY and ULY. HLY at age 15 for women in the EU10 were 3.1 years more than those for men at the same age, whereas HLY did not differ by gender in the EU15. In both populations ULY at age 15 for women exceeded those for men by 5.5 years. Decomposition showed that EU10 women had more HLY because higher disability in women only partially offset (−0.8 years) the effect of lower mortality (+3.9 years). In the EU15 women's higher disability prevalence almost completely offset women's lower mortality. The 5.3 fewer ULY in EU10 men than in EU10 women mainly reflected higher male mortality (4.5 years), while the fewer ULY in EU15 men than in EU15 women reflected both higher male mortality (2.9 years) and higher female disability (2.6 years). The absence of a clear gender gap in HLY in the EU15 thus masked important gender differences in mortality and disability. The similar size of the gender gap in ULY in the EU-10 and EU-15 masked the more unfavourable health situation of EU10 men, in particular the much stronger and younger mortality disadvantage in combination with the virtually absent disability advantage below age 65 in men. [ABSTRACT FROM AUTHOR]

Abstract: Objective: This work aims to validate and increase understanding of the Global Activity Limitation Index (GALI), an activity limitation measure from which the new structural indicator Healthy Life Years is generated. Study Design and Setting: Data from the Survey of Health and Retirement in Europe, covering 11 European countries and 27,340 individuals older than 50 years, was used to investigate how the GALI was associated with other existing measures of function and disability and whether the GALI was consistent or reflected different levels of health in different countries. Results: The GALI was significantly associated with the two subjective measures of activities of daily living score and instrumental activities of daily living (IADL) score, and the two objective measures of maximum grip strength and walking speed (P <0.001 in all cases). The GALI did not differ significantly between countries in terms of how it reflected three of the health measures, with the exception being IADL. Conclusion: The GALI appears to satisfactorily reflect levels of function and disability as assessed by long-standing objective and subjective measures, both across Europe and in a similar way between countries. [Copyright &y& Elsevier]

Background: Healthy life years have superseded life expectancy (LE) as the most important indicator for population health. The most common approach to separate the total number of life years into those spent in good and poor health is the Sullivan method which incorporates the health dimension to the classic period life table, thus transforming the LE indicator into the health expectancy (HE) indicator. However, life years derived from a period life table and health prevalence derived from survey data are based on different conceptual frameworks., Method: We modify the Sullivan method by combining the health prevalence data with the conceptually better fitting cross-sectional average length of life (CAL). We refer to this alternative HE indicator as the "cross-sectional average length of healthy life" (HCAL). We compare results from this alternative indicator with the conventional Sullivan approach for nine European countries. The analyses are based on EU-SILC data in three empirical applications, including the absolute and relative level of healthy life years, changes between 2008 and 2014, and the extent of the gender gap., Results: HCAL and conventional HE differ in each of these empirical applications. In general, HCAL provides larger gains in healthy life years in recent years, but at the same time greater declines in the proportion of healthy life years. Regarding the gender gap, HCAL provides a more favourable picture for women compared to conventional HE. Nonetheless, the extent of these differences between the indicators is only of minor extent., Conclusions: Albeit the differences between HE and HCAL are small, we found some empirical examples in which the two indicators led to different conclusions. It is important to note, however, that the measurement of health and the data quality are much more important for the healthy life years indicator than the choice of the variant of the Sullivan method. Nonetheless, we suggest to use HCAL in addition to HE whenever possible because it widens the spectrum of empirical analyses and serves for verification of results based on the highly sensitive HE indicator.

Background: Prevention aiming at smoking, alcohol consumption, and BMI could potentially bring large gains in life expectancy (LE) and health expectancy measures such as Healthy Life Years (HLY) and Life Expectancy in Good Perceived Health (LEGPH) in the European Union. However, the potential gains might differ by region., Methods: A Sullivan life table model was applied for 27 European countries to calculate the impact of alternative scenarios of lifestyle behavior on life and health expectancy. Results were then pooled over countries to present the potential gains in HLY and LEGPH for four European regions., Results: Simulations show that up to 4 years of extra health expectancy can be gained by getting all countries to the healthiest levels of lifestyle observed in EU countries. This is more than the 2 years to be gained in life expectancy. Generally, Eastern Europe has the lowest LE, HLY, and LEGPH. Even though the largest gains in LEPGH and HLY can also be made in Eastern Europe, the gap in LE, HLY, and LEGPH can only in a small part be closed by changing smoking, alcohol consumption, and BMI., Conclusion: Based on the current data, up to 4 years of good health could be gained by adopting lifestyle as seen in the best-performing countries. Only a part of the lagging health expectancy of Eastern Europe can potentially be solved by improvements in lifestyle involving smoking and BMI. Before it is definitely concluded that lifestyle policy for alcohol use is of relatively little importance compared to smoking or BMI, as our findings suggest, better data should be gathered in all European countries concerning alcohol use and the odds ratios of overconsumption of alcohol.