scholarly journals Summary Measures of Population Health: Methods for Calculating Healthy Life Expectancy

2001 ◽  
Author(s):  
Michael T. Molla ◽  
Diane K. Wagener ◽  
Jennifer H. Madans
Keyword(s):  
Life Expectancy ◽  
Population Health ◽  
Healthy Life Expectancy ◽  
Healthy Life ◽  
Summary Measures

An equity - effectiveness framework linking health programs and healthy life expectancy

2011 ◽  
Vol 17 (4) ◽  
pp. 309 ◽  
Author(s):  
David Banham ◽  
John Lynch ◽  
Jon Karnon
Keyword(s):  
Life Expectancy ◽  
Health System ◽  
Population Health ◽  
South Australia ◽  
Relevant Information ◽  
Intervention Programs ◽  
Health Programs ◽  
Healthy Life Expectancy ◽  
Healthy Life ◽  
Health Gains

South Australia’s Strategic Plan includes a target to improve the population’s healthy life expectancy. A common question among health policy and service planners is: ‘How do health programs and services in the community relate to healthy life expectancy?’ In response, this paper outlines an effectiveness and equity framework (EEF) for evaluating health interventions in applied settings. Using the example of coronary heart disease (CHD) management in general practice in South Australia, the EEF: (1) applies an internally consistent approach to accounting for population healthy life expectancy at state and smaller geographic levels; (2) estimates average population health gains from health programs, and gains across different socioeconomic subgroups within the community; (3) conducts economic evaluation by equating health gains against health system costs in population subgroups; (4) summarises relevant information about candidate intervention programs within a multi-criteria performance matrix for presentation to decision makers; (5) reassesses outcomes (and processes) following the implementation of a program and iteratively adds to the relevant knowledge and evidence base. The EEF offers a practical approach to selecting and evaluating intervention programs. The challenge is to develop system culture and data capture methods clearly focussed on linking health system activities to population health outcomes.

Healthy Life Expectancy in the Context of Population Health and Ageing in India

2010 ◽  
Vol 24 (1) ◽  
pp. 195-207 ◽  
Author(s):  
Robin S. Lau ◽  
Shanthi Johnson ◽  
T. J. Kamalanabhan
Keyword(s):  
Life Expectancy ◽  
Population Health ◽  
Healthy Life Expectancy ◽  
Healthy Life

scholarly journals The Significant Association between Health Examination Results and Population Health: A Cross-Sectional Ecological Study Using a Nation-Wide Health Checkup Database in Japan

2021 ◽  
Vol 18 (2) ◽  
pp. 836
Author(s):  
Yukinori Nagakura ◽  
Hideaki Kato ◽  
Satoshi Asano ◽  
Yasuhiro Jinno ◽  
Shigeharu Tanei
Keyword(s):  
Life Expectancy ◽  
Health Outcomes ◽  
Population Health ◽  
Healthy Life Expectancy ◽  
National Database ◽  
Health Examination ◽  
Health Habits ◽  
Health Checkup ◽  
Cross Sectional ◽  
Healthy Life

In Japan, population health with life expectancy (LE) and healthy life expectancy (HALE) as indicators varies across the 47 prefectures (administrative regions). This study investigates how health examination results, including attitude toward improving life habits, are associated with population health. The association between health checkup variables and summary population health outcomes (i.e., life expectancy and healthy life expectancy) was investigated using a cross-sectional ecological design with prefectures as the unit of analysis. The medical records, aggregated by prefecture, gender, and age in the National Database of Health Insurance Claims and Specific Health Checkups of Japan (NDB) Open Data Japan, were used as health checkup variables. Body weight, blood pressure, liver enzymes, drinking habits, smoking habits, diabetes, serum lipids, and answers to questions regarding attitude toward improving health habits were significantly correlated to population health outcomes. Multiple regression analysis also revealed significant influence of these variables on population health. This study highlights that health examination results, including attitude toward improving health habits, are positively associated with population health. Consequently, implementing measures to improve health habits in response to the examination results could help the population maintain a healthy life.

scholarly journals The Relationship and Trends of Socio-Demographic Index, Healthy Life Expectancy and Life Expectancy in China

2020 ◽  
Author(s):  
Xinlei Miao ◽  
Xiuhua Guo ◽  
Yue Cai ◽  
Xiang Zhang ◽  
Qun Meng
Keyword(s):  
Life Expectancy ◽  
Population Health ◽  
Matrix Analysis ◽  
Healthy Life Expectancy ◽  
Strong Positive Correlation ◽  
Adult Health ◽  
Fertility Rates ◽  
Healthy Life ◽  
The Government ◽  
The Relationship

Abstract Background Socio-Demographic Index (SDI) is an index to evaluate social development. Healthy life expectancy (HLE/HALE) can comprehensively measure the population health. This paper analyzes the relationship and trend of Socio-Demographic Index, life expectancy (LE) and healthy life expectancy, which provides a reference for improving population health. Methods We used R Studio (version 1.2.5033) for correlation matrix analysis of SDI, HALE and LE. Meanwhile, we divided provinces into 3 regions according to the 2019 Chinese Health Statistics Yearbook and analyzed the distribution by ArcGIS 10.5 of healthy life expectancy and SDI of 31 provinces and cities in China.Results From 1990 to 2016, socio-demographic, life expectancy and healthy life expectancy showed a gradual increasing trend, and the level in eastern provinces were higher than western provinces in China. There is a correlation between socio-demographic (included its composition that education for aged 15 and older, Gross Domestic Product and total fertility rates under the age of 25), healthy life expectancy and life expectancy. Total fertility rates under the age of 25 has a negative correlation with other variables.Conclusions There is a strong positive correlation between healthy life expectancy, life expectancy and socio-demographic index. The government should consider take the implementation of personalized policies to steadily improve the development of SDI, at the same time to improve healthy life expectancy from improving maternal health and reducing infant mortality, paying attention to adult health, reducing the early death rate of chronic diseases.

scholarly journals The Relationship and Trends of Socio-Demographic Index, Healthy Life Expectancy and Life Expectancy in China

2020 ◽  
Author(s):  
Xinlei Miao ◽  
Xiuhua Guo ◽  
Yue Cai ◽  
Xiang Zhang ◽  
Qun Meng
Keyword(s):  
Life Expectancy ◽  
Population Health ◽  
Elderly Women ◽  
The Elderly ◽  
Development Trend ◽  
Healthy Life Expectancy ◽  
Healthy Life ◽  
Positive Correlation ◽  
The Relationship ◽  
D Value

Abstract Background Socio-Demographic Index is an index to evaluate social development. Healthy life expectancy can comprehensively measure the population health. This paper indirectly infers the relationship between SDI and HALE, which provides a reference for improving population health. Methods We used SAS 9.4 to analyze the relationship between SDI and LE, and the development trend of SDI and LE in 1990-2010. Meanwhile, we divided into 3 regions according to the 2019 Chinese Health Statistics Yearbook. Results From 1990 to 2010, SDI and LE showed a trend of gradually increasing from west to East. In the regression analysis of SDI and LE,r=0.90335，P<0.0001, meaning that there was a positive correlation between SDI and LE. The D value of men was lower than that of women. Among the five SDI levels, the high SDI level usually had higher LE, so the D value was relatively high. However, in the middle SDI and low-middle SDI areas, the results showed the opposite situation. The SDI in India is lower than that in China, and the D value of female in China is higher than that in India, which indicates that Chinese elderly women have a long life with disease and disability. Conclusions Socio-Demographic Index has a positive correlation with life expectancy and healthy life expectancy. Therefore, we can consider improving healthy life expectancy from the components of SDI to improve the healthy level of the population. At the same time, we should pay more attention to the care of the elderly population.

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.

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