Trends in healthy life expectancy in the United States, 1970–1990: gender, racial, and educational differences

2001 ◽  
Vol 52 (11) ◽  
pp. 1629-1641 ◽  
Author(s):  
Eileen M Crimmins ◽  
Yasuhiko Saito
Keyword(s):  
United States ◽  
Life Expectancy ◽  
The United States ◽  
Healthy Life Expectancy ◽  
Healthy Life ◽  
Educational Differences

The Demographic Transformation of America

Daedalus ◽  
2015 ◽  
Vol 144 (2) ◽  
pp. 13-19 ◽  
Author(s):  
S. Jay Olshansky
Keyword(s):  
United States ◽  
Life Expectancy ◽  
Age Structure ◽  
The United States ◽  
Healthy Life Expectancy ◽  
Healthy Life ◽  
The Face ◽  
Recent Trends ◽  
Developed World ◽  
The U.S

The face of aging in America is about to change. Within the next thirty years, the U.S. population will experience a permanent change in its age structure, and there is reason to believe that cohorts reaching older ages in the future will be far different from those reaching older ages today. In this essay, I explain why life expectancy in the United States is likely to diverge from that experienced by the rest of the developed world; describe recent trends in healthy life expectancy; and examine how the age structure of the United States will by mid-century be different from that found today.

scholarly journals Nutritional Eating; What Do You Know and When Did You Know It? (P04-098-19)

2019 ◽  
Vol 3 (Supplement_1) ◽  
Author(s):  
Deborah Calhoun-Parker
Keyword(s):  
Heart Disease ◽  
Life Expectancy ◽  
Chronic Diseases ◽  
The United States ◽  
Time Frame ◽  
Poor Health ◽  
World Health ◽  
Healthy Life Expectancy ◽  
Healthy Life ◽  
Nutritional Information

Abstract Objectives The World Health Organization (W.H.O.) projects by 2020 chronic disease will account for 73% of deaths worldwide (W.H.O., 2010). In the United States (U.S.) minorities are high risk for chronic diseases. U.S. census projects by 2050 American minorities as the majority (Census, 2000). Purposes of pilot study 1) identify individual knowledge of chronic diseases; 2) when known (time frame); and 3) knowledge implemented to improve health. Important because if projections are correct health of the majority of people worldwide and U.S. society in particular, (Americas’ minority/majority) forecast as: poor health with short healthy life expectancy. Leading chronic diseases causing mortality in America: heart disease, cancer and lower respiratory diseases (Center for Disease Control, 2016). Hispanics are 16% of U.S. population. Leading cause of mortality: cancer. African Americans are 13.6% of U.S. population. Leading cause of mortality: heart disease. Societal challenge: mitigating health issues of a minority/majority. Methods A convenience sample adults (N = 15) utilized; most minorities. They completed 32 item questionnaire. Some items were Likert scale 5 strongly agree and 1 strongly disagree. Results Ninety-nine % have family member(s) with health challenges. More than 50% indicate being, “Healthy”. Half indicate being overweight. The majority response to frequency questions: 2–3 weekly. Example, most consume 9 servings of fruits/vegetables (F/V) 2–3 weekly. USDA recommend 9 servings of F/V daily. Time frame questions: ‘when known’. Example, half indicate meat and dairy as a diet necessity. When known, majority indicate over a year ago. Meat/dairy linked with chronic diseases. Majority misidentifies nutrient dense foods. Example, majority indicate white potatoes and iceberg lettuce as nutrient dense. Nutrient dense foods mitigate chronic diseases. Response to Likert type scale items, example, “I work hard to improve my dietary lifestyle”, most indicate ‘agree’. Conclusions Current nutritional information limited. Outdated nutritional information implemented. Nutrient dense diet lacking. The trajectory forecast of a minority/majority with poor health and short healthy life expectancy is on target. Funding Sources N/A.

scholarly journals Healthy Life Expectancy in 2010 for Native Hawaiian, White, Filipino, Japanese, and Chinese Americans Living in Hawai’i

2019 ◽  
Vol 31 (7) ◽  
pp. 659-670 ◽  
Author(s):  
Yanyan Wu ◽  
Olivia Uchima ◽  
Colette Browne ◽  
Kathryn Braun
Keyword(s):  
Life Expectancy ◽  
Policy Development ◽  
Native Hawaiian ◽  
Ethnic Disparities ◽  
Chinese Americans ◽  
The United States ◽  
Native Hawaiians ◽  
Healthy Life Expectancy ◽  
Healthy Life ◽  
Sullivan Method

Healthy life expectancy (HALE) varies substantially among countries, regions, and race/ethnicities. Utilizing the Sullivan method, this article examines HALE for Native Hawaiian, White, Filipino, Japanese, and Chinese Americans living in Hawai’i, the United States. HALE varies by sex and race/ethnicity. The HALE at birth in 2010 for females was 78.3, 77.8, 74.2, 73.7, and 62.6 years in contrast to life expectancy of 90, 88, 88.1, 83.4, and 79.4 for Chinese, Japanese, Filipino Americans, White, and Native Hawaiians, respectively. In the same order, HALE at birth for males was 73.0, 71.6, 72.3 70.7, and 60.7 years, compared with life expectancy of 85.3, 81.2, 80.8, 78.3, and 73.9. The gaps in HALE between Native Hawaiians and the longest living Chinese Americans were 15.7 years for females and 12.3 years for males. Our results highlight sex and racial/ethnic disparities in HALE, which can inform program and policy development.

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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