The health state curve and the health state life table: Life expectancy and healthy life expectancy estimates

2015 ◽  
Vol 45 (6) ◽  
pp. 1682-1692
Author(s):  
Christos H. Skiadas ◽  
Charilaos Skiadas
2021 ◽  
Vol 50 (Supplement_1) ◽  
Author(s):  
Rumi Tsukinoki ◽  
Takehito Hayakawa ◽  
Aya Kadota ◽  
Yoshitaka Murakami ◽  
Katsuyuki Miura ◽  
...  

Abstract Background Healthy life expectancy (HLE) is an important measure of an ageing society. We estimated HLE based on combinations of smoking, blood pressure (BP), and body mass index (BMI) in the Japanese population using a multistate life table. Methods A nationwide cohort study of Japan was performed using NIPPON DATA90 (N = 6,676) with the Katz Activities of Daily Living Index as the HLE endpoint. Combinations of smoking (non-smokers and smokers), BP (2018 ESC/ESH Guidelines classification), and BMI (underweight, normal, and overweight) were developed, and the group-specific HLEs were calculated using a multistate life table. Results At age 65, smokers had shorter HLE than non-smokers for all BMI and BP groups. The HLE of men who were overweight, hypertensive (Grade 2 or 3), and smokers was 14.05 years (95% confidence interval: 15.77-21.36); in contrast, the HLE of men who were normal weight, normotensive, and non-smokers was 19.04 years (16.46-21.61). Among all BMI and smoking status groups, HLE decreased linearly as BP increased regardless of sex. The HLE distribution showed a slight inverted U-shape as BMI increased in both sexes. Conclusions This study showed that HLE at age 65 was considerably shorter in smokers and individuals with higher BP. Furthermore, both underweight and overweight had modest effects on HLE at age 65. Key messages HLE was considerably shorter in smokers and individuals with higher BP. In addition, both underweight and overweight had modest effects on HLE.


Author(s):  
M. Mazharul Islam ◽  

Objectives: The objective of this study was to examine the life expectancy (LE) and healthy life expectancy (HLE) of Omani adults with age and gender differentials, focusing on whether the higher LE of women than men is a gain or burden for women. Method: Data for the study come from multiple sources such as the 2010 population census, the 2008 World Health Survey in Oman, and secondary data published in the Statistical Yearbook of Oman. The life table and the modified life table proposed by Sullivan were used for estimating the LE and HLE of adult people of age 20 and above, respectively. Results: LE in Oman reached 76 years for both sexes in recent times. However, since 2010 LE has been stalled in the vicinity of 76 years in Oman. Women had higher LE than men (79 years versus 74 years). In terms of HLE, men outweighed women in Oman. At the age of 20, the gap between male-female LE was found to be 4.7 years in favor of females, whereas the gap between male-female HLE was found to be 5.8 years in favor of males. Females spent a relatively long time in poor health status than males (20.8 years versus 10.8 years) and the proportion of life spent in poor health was greater for females than males (35.0% vs. 19.3%). This revealed the paradox of less mortality but higher morbidity among women, supporting the “Failure of Success” hypothesis. Conclusion: Appropriate health policy and strategy need to be taken to reduce the gender gap in LE and HLE in Oman.


2020 ◽  
Vol 15 (5) ◽  
pp. 35-55
Author(s):  
N.P. STARYKH ◽  
◽  
A.V. EGOROVA ◽  

The purpose of the article is to analyze the current state of healthcare in Russia. Scientific novelty of the study: the authors suggest that the efficiency of the health care system depends on the state of such indicators of public health as life expectancy and healthy life expectancy. Life expectancy is an integrated demographic indicator that characterizes the number of years that a person would live on average, provided that the age-specific mortality rate of a generation would be at the level for which the indicator was calculated throughout life. The indicator ‘healthy life expectancy’ is formed by subtracting the number of years of unhealthy life (due to chronic diseases, disabilities, mental and behavioral disorders, etc.) from the life expectancy indicator. Results: the article presents an analysis of the current state of Russian healthcare based on statistical data provided by the Federal State Statistics Service, the World Health Organization, and world rankings. Attention is focused on the perceptions of Russians about the quality of medical services and Russian healthcare. Conclusions about the current state of health care in Russia are formulated by the authors, based on a secondary analysis of statistical data, as well as data from sociological research presented by leading Russian sociological centers.


2020 ◽  
Vol 4 (Supplement_1) ◽  
pp. 505-505
Author(s):  
Matthew Farina ◽  
Phillip Cantu ◽  
Mark Hayward

Abstract Recent research has documented increasing education inequality in life expectancy among U.S. adults; however, much is unknown about other health status changes. The objective of study is to assess how healthy and unhealthy life expectancies, as classified by common chronic diseases, has changed for older adults across education groups. Data come from the Health and Retirement Study and National Vital Statistics. We created prevalence-based life tables using the Sullivan method to assess sex-specific life expectancies for stroke, heart disease, cancer, and arthritis by education group. In general, unhealthy life expectancy increased with each condition across education groups. However, the increases in unhealthy life expectancy varied greatly. While stroke increased by half a year across education groups, life expectancy with diabetes increased by 3 to 4 years. In contrast, the evidence for healthy life expectancy provides mixed results. Across chronic diseases, healthy life expectancy decreased by 1 to 3 years for respondents without a 4-year degree. Conversely, healthy life expectancy increased for the college educated by .5 to 3 years. While previous research shows increases in life expectancy for the most educated, trends in life expectancy with chronic conditions is less positive: not all additional years are in lived in good health. In addition to documenting life expectancy changes across education groups, research assessing health of older adults should consider the changing inequality across a variety of health conditions, which will have broad implications for population aging and policy intervention.


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