scholarly journals Dental Status and Compression of Life Expectancy with Disability

2017 ◽  
Vol 96 (9) ◽  
pp. 1006-1013 ◽  
Author(s):  
Y. Matsuyama ◽  
J. Aida ◽  
R.G. Watt ◽  
T. Tsuboya ◽  
S. Koyama ◽  
...  
Keyword(s):  
Life Expectancy ◽  
Functional Disability ◽  
Community Dwelling ◽  
Healthy Life Expectancy ◽  
Baseline Survey ◽  
Compression Of Morbidity ◽  
Healthy Life ◽  
Number Of Teeth ◽  
Significant Compression

This study examined whether the number of teeth contributes to the compression of morbidity, measured as a shortening of life expectancy with disability, an extension of healthy life expectancy, and overall life expectancy. A prospective cohort study was conducted. A self-reported baseline survey was given to 126,438 community-dwelling older people aged ≥65 y in Japan in 2010, and 85,161 (67.4%) responded. The onset of functional disability and all-cause mortality were followed up for 1,374 d (follow-up rate = 96.1%). A sex-stratified illness-death model was applied to estimate the adjusted hazard ratios (HRs) for 3 health transitions (healthy to dead, healthy to disabled, and disabled to dead). Absolute differences in life expectancy, healthy life expectancy, and life expectancy with disability according to the number of teeth were also estimated. Age, denture use, socioeconomic status, health status, and health behavior were adjusted. Compared with the edentulous participants, participants with ≥20 teeth had lower risks of transitioning from healthy to dead (adjusted HR, 0.58 [95% confidence interval (CI), 0.50–0.68] for men and 0.70 [95% CI, 0.57–0.85] for women) and from healthy to disabled (adjusted HR, 0.52 [95% CI, 0.44–0.61] for men and 0.58 [95% CI, 0.49–0.68] for women). They also transitioned from disabled to dead earlier (adjusted HR, 1.26 [95% CI, 0.99–1.60] for men and 2.42 [95% CI, 1.72–3.38] for women). Among the participants aged ≥85 y, those with ≥20 teeth had a longer life expectancy (men: +57 d; women: +15 d) and healthy life expectancy (men: +92 d; women: +70 d) and a shorter life expectancy with disability (men: –35 d; women: –55 d) compared with the edentulous participants. Similar associations were observed among the younger participants and those with 1 to 9 or 10 to 19 teeth. The presence of remaining teeth was associated with a significant compression of morbidity: older Japanese adults’ life expectancy with disability was compressed by 35 to 55 d within the follow-up of 1,374 d.

scholarly journals Inequality of healthy life expectancy for the Chinese elderly and its trend

2019 ◽  
Vol 6 (1) ◽  
Author(s):  
Kaishan Jiao
Keyword(s):  
Socioeconomic Status ◽  
Life Expectancy ◽  
Cohort Effect ◽  
The Elderly ◽  
Healthy Life Expectancy ◽  
Birth Cohorts ◽  
Healthy Life ◽  
Long Term Follow Up

AbstractIn this study, we use long-term follow-up survey data to explore the inequality of the healthy life expectancy among the elderly and the trends of such expectancy among different birth cohorts and at different ages. The results show that older people with higher socioeconomic status do not have a significant advantage in healthy life expectancy. Its advantage in life expectancy is mainly due to the relatively low mortality rate under conditions of disability, i.e., the relatively long life expectancy with disability. This also shows that the elderly with higher socioeconomic status is at the stage of disability expansion. In addition, the study examines the age effect and cohort effect of health inequality and points out that health inequalities among different socioeconomic status groups are likely to increase in the future.

DIAGNOSTICS OF THE CURRENT STATE OF HEALTHCARE IN RUSSIA

2020 ◽  
Vol 15 (5) ◽  
pp. 35-55
Author(s):  
N.P. STARYKH ◽  
◽  
A.V. EGOROVA ◽  
Keyword(s):  
Health Care ◽  
Life Expectancy ◽  
Statistical Data ◽  
Secondary Analysis ◽  
World Health ◽  
Healthy Life Expectancy ◽  
Federal State ◽  
Sociological Research ◽  
Healthy Life ◽  
Current State

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.

scholarly journals Changing Educational Gradients in Life Expectancy With and Without Disease Among U.S. Older Adults From 2000 to 2010

2020 ◽  
Vol 4 (Supplement_1) ◽  
pp. 505-505
Author(s):  
Matthew Farina ◽  
Phillip Cantu ◽  
Mark Hayward
Keyword(s):  
Older Adults ◽  
Life Expectancy ◽  
Chronic Diseases ◽  
Population Aging ◽  
Good Health ◽  
Vital Statistics ◽  
Healthy Life Expectancy ◽  
Healthy Life ◽  
Education Group ◽  
Education Groups

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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