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

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 Outdated nutritional information implemented.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.

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.


2005 ◽  
Vol 21 (suppl 1) ◽  
pp. S7-S18 ◽  
Author(s):  
Dalia Elena Romero ◽  
Iúri da Costa Leite ◽  
Célia Landmann Szwarcwald

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.


Author(s):  
Adora D. Holstein

This study applies multivariate regression analysis to cross-section data of 30 OECD countries to determine if there is a trade-off between health care cost and the quality of the health system on one hand, and better health outcomes on the other. It also investigates whether a higher quality health system leads to superior health outcomes. The empirical results provide positive answers to the above two questions. Indices of responsiveness, fairness or accessibility, and overall efficiency of the health system developed by the World Health Organization were used in this study to measure health system quality. The rate of infant mortality and a disability-free or healthy life expectancy measure developed by the WHO are used as indicators of health outcomes. The empirical models control for the effects of cross-country differences in literacy level and health-risk or lifestyle. The study finds evidence that the more responsive and accessible the countrys health system is, the longer is the healthy life expectancy of its people. Moreover, the more accessible and efficient the countrys health system is, the lower is the rate of infant mortality.


2021 ◽  
Vol 8 ◽  
Author(s):  
Zhitao Liu ◽  
Huilie Zheng ◽  
Yuhang Wu ◽  
Shengwei Wang ◽  
Yong Liu ◽  
...  

Background: Globalization has brought about rapid economic and technological development, and life expectancy (LE) is constantly increasing. However, it is not clear whether an increase in LE will result in an increase in healthy life expectancy (HLE). This study evaluates trends in the self-rated healthy life expectancy (SRHLE) of residents aged 15 and older in Jiangxi Province of China from 2013 to 2018 and analyzes gender differences and urban–rural differences. This study provides a basis for the formulation of relevant public health policies.Methods: Based on two National Health Services Survey databases of Jiangxi in 2013 and 2018 as well as infant mortality rates and under-5 mortality rates from the Health Commission of Jiangxi, the Sullivan method was used to calculate SRHLE. The changes in SRHLE were decomposed into health and mortality effects using the decomposition method.Results: SRHLE decreased from 56.55 to 55.54 years and from 60.00 to 57.87 years for men and women aged 15 from 2013 to 2018, respectively. The SRHLE of women aged 15 was 3.45 and 2.34 years longer than that of men in 2013 and 2018, respectively. The SRHLE of urban men aged 15 was 2.9 and 4.46 years longer than that of rural men in 2013 and 2018, respectively, and that of urban women aged 15 was 3.28 and 5.57 years longer than that of rural women.Conclusions: The decreased SRHLE indicated that the self-rated health (SRH) status of residents in Jiangxi has worsened, and it provided evidence for the expansion of morbidity, mainly due to the increased prevalence of chronic diseases and the improvement in residents' health awareness. Policy efforts are necessary to control the increased morbidity of chronic diseases and reduce gender and urban–rural differences in the quantity and quality of years lived.


2019 ◽  
Vol 31 (7) ◽  
pp. 659-670 ◽  
Author(s):  
Yanyan Wu ◽  
Olivia Uchima ◽  
Colette Browne ◽  
Kathryn Braun

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.


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