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.

scholarly journals Healthy life expectancy in Brazil: applying the Sullivan method

2005 ◽  
Vol 21 (suppl 1) ◽  
pp. S7-S18 ◽  
Author(s):  
Dalia Elena Romero ◽  
Iúri da Costa Leite ◽  
Célia Landmann Szwarcwald
Keyword(s):  
Life Expectancy ◽  
Functional Limitation ◽  
Good Health ◽  
World Health ◽  
Healthy Life Expectancy ◽  
State Of Health ◽  
World Health Survey ◽  
Healthy Life ◽  
Mortality And Morbidity ◽  
Sullivan Method

The objective of this study is to present the method proposed by Sullivan and to estimate the healthy life expectancy using different measures of state of health, based on information from the World Health Survey carried out in Brazil in 2003. By combining information on mortality and morbidity into a unique indicator, simple to calculate and easy to interpret, the Sullivan method is currently the one most commonly used for estimating healthy life expectancy. The results show higher number of healthy years lost if there is a long-term disease or disability that limits daily activities, regardless of the difficulty in performing such activities or the severity of the functional limitations. The two measures of healthy life expectancy adjusted by the severity of functional limitation show results very similar to estimates based on the perception of state of health, especially in advanced age. It was also observed, for all measures used, that the proportion of healthy years lost increases significantly with age and that, although females have higher life expectancy than males, they live proportionally less years in good health.

scholarly journals Ageism, Healthy Life Expectancy and Population Ageing: How Are They Related?

2020 ◽  
Vol 17 (9) ◽  
pp. 3159 ◽  
Author(s):  
Alana Officer ◽  
Jotheeswaran Amuthavalli Thiyagarajan ◽  
Mira Leonie Schneiders ◽  
Paul Nash ◽  
Vânia de la Fuente-Núñez
Keyword(s):  
Older Adults ◽  
Life Expectancy ◽  
Sex Education ◽  
Latent Class ◽  
Multinomial Logistic Regression ◽  
Personal Characteristics ◽  
Healthy Life Expectancy ◽  
Healthy Life ◽  
Individual Level ◽  
Explanatory Factors

Evidence shows that ageism negatively impacts the health of older adults. However, estimates of its prevalence are lacking. This study aimed to estimate the global prevalence of ageism towards older adults and to explore possible explanatory factors. Data were included from 57 countries that took part in Wave 6 of the World Values Survey. Multilevel Latent Class Analysis was performed to identify distinct classes of individuals and countries. Individuals were classified as having high, moderate or low ageist attitudes; and countries as being highly, moderately or minimally ageist, by aggregating individual responses. Individual-level (age, sex, education and wealth) and contextual-level factors (healthy life expectancy, population health status and proportion of the population aged over 60 years) were examined as potential explanatory factors in multinomial logistic regression. From the 83,034 participants included, 44%, 32% and 24% were classified as having low, moderate and high ageist attitudes, respectively. From the 57 countries, 34 were classified as moderately or highly ageist. The likelihood of an individual or a country being ageist was significantly reduced by increases in healthy life expectancy and the proportion of older people within a country. Certain personal characteristics—younger age, being male and having lower education—were significantly associated with an increased probability of an individual having high ageist attitudes. At least one in every two people included in this study had moderate or high ageist attitudes. Despite the issue’s magnitude and negative health impacts, ageism remains a neglected global health issue.

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.

Sex differences in healthy life expectancy from self-perceived assessments of health in the City of São Paulo, Brazil

2008 ◽  
Vol 28 (1) ◽  
pp. 35-48 ◽  
Author(s):  
MIRELA CASTRO SANTOS CAMARGOS ◽  
CARLA JORGE MACHADO ◽  
ROBERTO NASCIMENTO RODRIGUES
Keyword(s):  
Life Expectancy ◽  
Multivariate Analyses ◽  
Perceived Health ◽  
Good Health ◽  
Sao Paulo ◽  
Healthy Life Expectancy ◽  
São Paulo ◽  
Healthy Life ◽  
Healthy State ◽  
The City

ABSTRACTWhether life is spent in good health or disability has a critical influence on the use of health-care services. It is also known that average healthy life expectancy differs by sex. This paper reports estimations of healthy and unhealthy life expectancy in old age using self-reported health assessments for the City of São Paulo, Brazil in 2000–01. The data derived from the Health, Well-being and Aging in Latin America and the Caribbean Project (SABE), and from population censuses and mortality statistics. Sullivan's estimation method was used. It combines the age-specific schedule of the current probabilities of death with the prevalence of self-perceived ‘poor’ and ‘good’ health. The paper also reports multivariate analyses of the factors associated with variations by age group and sex in self-perceived health. The findings revealed that, at all ages, women live longer than men and for more years in a healthy state. Among men, those aged 60, 65 and 70 years were expected to live a higher percentage of their remaining life than women in a healthy state, but among those aged 75, 80 and 85 years, the opposite held. Among women, the percentage of remaining years that were unhealthy did not increase as age increased, which differs from previous findings. The multivariate analyses showed that with increasing age, for women the number of chronic diseases decreased but dependency increased, and for men the opposite held. This finding indicated that the percentage of life spent in poor self-perceived health more accurately predicts mortality in men than women.

scholarly journals Gender difference in trends in healthy life expectancy in 2005-2012 for adults aged 50 years and older in South Africa

2019 ◽  
Vol 4 (2) ◽  
pp. 12 ◽  
Author(s):  
Witness Chirinda ◽  
Yasuhiko Saito ◽  
Danan Gu ◽  
Nompumelelo Zungu
Keyword(s):  
South Africa ◽  
Life Expectancy ◽  
Older People ◽  
Good Health ◽  
Gender Disparities ◽  
Healthy Life Expectancy ◽  
Cross Sectional ◽  
Healthy Life ◽  
Fiscal Planning ◽  
Using Data

Data characterizing older people’s life expectancy by good or poor health isimportant for policy and fiscal planning. This study aims to examine trends and investigategender differences in healthy life expectancy (HLE) for older people in South Africa for theperiod 2005–2012. Using data from three repeated cross-sectional surveys conducted in 2005,2008, and 2012, we applied a self-rated health measure to estimating HLE. The Sullivanmethod was used in the calculations. We found that unhealthy life expectancy decreased overthe period, while HLE and the proportion of life spent in good health increased more thantotal life expectancy in the same period. Gender disparities were evident: Women had higherlife expectancy than men, yet they spent a greater proportion of their lifetime in poor health.We concluded that HLE of older people in South Africa has improved over the period underinvestigation.

scholarly journals Age and Frailty as Key Determinants for Nutritional Therapy Individualization in Elderly Adults with Diabetes

2021 ◽  
pp. 1-3
Author(s):  
Zoe Pafili
Keyword(s):  
Older Adults ◽  
Cognitive Impairment ◽  
Life Expectancy ◽  
Nutritional Therapy ◽  
Diet Therapy ◽  
Healthy Life Expectancy ◽  
Healthy Life ◽  
Social Burden ◽  
Patients With Diabetes ◽  
The Impact

The increasing prevalence of older adults with diabetes has become a major social burden. Diabetes, frailty, and cognitive dysfunction are closely related to the mechanisms of aging. Insulin resistance, arteriosclerosis, chronic inflammation, oxidative stress, and mitochondrial dysfunction may be common mechanisms shared by frailty and cognitive impairment. Hyperglycemia, hypoglycemia, obesity, vascular factors, physical inactivity, and malnutrition are important risk factors for cognitive impairment and frailty in older adults with diabetes. The impact of nutrients on health outcomes varies with age; thus, shifting diet therapy strategies from the treatment of obesity/metabolic syndrome to frailty prevention may be necessary in patients with diabetes who are over 75 years of age, have frailty or sarcopenia, and experience malnutrition. For the prevention of frailty, optimal energy intake, sufficient protein and vitamin intake, and healthy dietary patterns should be recommended. The treatment of diabetes after middle age should include the awareness of proper glycemic control aimed at extending healthy life expectancy with proper nutrition, exercise, and social connectivity. Nutritional therapy in combination with exercise, optimal glycemic and metabolic control, and social participation/support for frailty prevention can extend healthy life expectancy and maintain quality of life in older adults with diabetes mellitus.

Decennial trends and inequalities in healthy life expectancy: The HUNT Study, Norway

2017 ◽  
Vol 46 (1) ◽  
pp. 124-131 ◽  
Author(s):  
Siri H. Storeng ◽  
Steinar Krokstad ◽  
Steinar Westin ◽  
Erik R. Sund
Keyword(s):  
Life Expectancy ◽  
Good Health ◽  
Healthy Life Expectancy ◽  
Healthy Life ◽  
Self Rated Health ◽  
Total Life Expectancy ◽  
Life Years ◽  
Educational Groups ◽  
Hunt Study ◽  
Total Life

Aims: Norway is experiencing a rising life expectancy combined with an increasing dependency ratio – the ratio of those outside over those within the working force. To provide data relevant for future health policy we wanted to study trends in total and healthy life expectancy in a Norwegian population over three decades (1980s, 1990s and 2000s), both overall and across gender and educational groups. Methods: Data were obtained from the HUNT Study, and the Norwegian Educational Database. We calculated total life expectancy and used the Sullivan method to calculate healthy life expectancies based on self-rated health and self-reported longstanding limiting illness. The change in health expectancies was decomposed into mortality and disability effects. Results: During three consecutive decades we found an increase in life expectancy for 30-year-olds (~7 years) and expected lifetime in self-rated good health (~6 years), but time without longstanding limiting illness increased less (1.5 years). Women could expect to live longer than men, but the extra life years for females were spent in poor self-rated health and with longstanding limiting illness. Differences in total life expectancy between educational groups decreased, whereas differences in expected lifetime in self-rated good health and lifetime without longstanding limiting illness increased. Conclusions: The increase in total life expectancy was accompanied by an increasing number of years spent in good self-rated health but more years with longstanding limiting illness. This suggests increasing health care needs for people with chronic diseases, given an increasing number of elderly. Socioeconomic health inequalities remain a challenge for increasing pensioning age.

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