Determining Health Expectancies

Tier 1—Life expectancy and wellbeing—1.19 Life expectancy at birth
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According to James and colleagues, a decrease in the rate of deaths from conditions amenable to medical care made the largest contribution to reducing socio-economic differences in mortality over a year period after the establishment of universal health insurance in Canada Chapter 5 reference 5. This chapter is intended to present recent published Canadian figures for health-adjusted life expectancy by income. Because of the many challenges generally encountered when linking mortality data with income data in order to calculate health-adjusted life expectancy by income, "work-around" solutions must often be sought.

Appendix F describes a continuum of such approaches to measuring health-adjusted life expectancy by income. Health-adjusted life expectancy by neighbourhood income tertile in was published by Statistics Canada Chapter 5 reference 6. The following data sources were used:. Wilkins and colleagues classified census enumeration areas into neighbourhood income tertiles based on income per single-person equivalent, which is a household size-adjusted average household income pre-tax, post-transfer at the enumeration area level Chapter 5 reference 7. Then, life tables by neighbourhood income tertiles were constructed.

Deaths were coded to the enumeration area based on postal codes. The household-size adjusted average income for each enumeration area was calculated, and then enumeration areas were assigned to the bottom, middle or highest neighbourhood income tertile. Life tables were then constructed using the deaths assigned to each neighbourhood income tertile. Later, in order to produce similar results for , the percentage of deaths in each neighbourhood income tertile was applied to the life tables Chapter 5 reference 6.

Using the enumeration area link in the Canadian Community Health Survey, respondents were placed in 1 of the 3 neighbourhood income tertiles. The mean health utility index was calculated for each tertile by age, sex and province. The household longitudinal file of the National Population Health Survey was analyzed to determine the tertile distribution for institutional residents.

The postal codes of respondents who lived in the community in but were living in an institution during a subsequent survey cycle were assigned to a tertile based on their enumeration area of residence in This tertile distribution was then applied to determine the percentage of institutional residents in each neighbourhood income tertile. Health-adjusted life expectancy was calculated for each province according to the method described below for each neighbourhood income tertile:. For details concerning the data sources and the calculations of the coefficient of variation for health-adjusted life expectancy, see the Statistics Canada technical notes Chapter 5 reference 8.

In , women had a higher health-adjusted life expectancy than men, both at birth and at age This difference was more apparent at birth, with women living to Canadians in higher neighbourhood income tertiles generally lived longer, healthier lives than those in lower neighbourhood income tertiles. Women in the highest neighbourhood income tertile had a health-adjusted life expectancy of Comparisons of health-adjusted life expectancy at birth across income tertiles showed that women in the highest neighbourhood income tertile had a health-adjusted life expectancy that was 3.

Similarly, men in the highest tertile had a health-adjusted life expectancy that was 4. This figure is a bar chart with 4 groups of bars corresponding to males at birth, females at birth, males at age 65 and females at age Each group has 3 bars corresponding to the lowest income group, middle income group, and highest income group.

Data is for , Canada.

The DALY Show, Disability-Adjusted Life Year (DALY)

A recent study by McIntosh and colleagues of income-related disparities in health-adjusted life expectancy for Canadian adults from to is the first study to provide nationally representative estimates of socio-economic inequalities in health-adjusted life expectancy for the adult household population of Canada, using individual-level measures of socio-economic status, mortality and morbidity Chapter 5 reference 3.

Death data were obtained from the Canadian census mortality follow-up study conducted by Statistics Canada in collaboration with the Canadian Population Health Initiative Chapter 5 reference 1. Data on health-related quality of life i.

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For the census mortality linked file, deciles tenths of population ranked by income adequacy were created for each economic family or unattached individual in the non-institutional census population of all ages. For the Canadian Community Health Survey, income deciles were constructed in the same manner, except that total household income was used rather than total economic family income. Health-adjusted life expectancy was estimated using a modified version of the Sullivan method Chapter 5 reference 9.

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Census population estimates. In this case, the specific rate by age of not being healthy 5 p x is given by the average of the scores weighted by the proportion of individuals in each category of each age group:. Comparisons of health-adjusted life expectancy at birth across income tertiles showed that women in the highest neighbourhood income tertile had a health-adjusted life expectancy that was 3. Future of an ageing population project: evidence review. Ageing Cell Biology Infection Biology.

The remaining health-adjusted life expectancy at age 25, by income decile and sex, is shown in Table Chapter 5 reference 3. The differences in health-adjusted life expectancy between the highest and lowest deciles were 9. For both sexes, the disparities in health-adjusted life expectancy between the highest and lowest income groups were substantially greater than those for life expectancy alone.

The results of the supplemental analyses of health disparities across educational attainment categories are shown in Table G-2 of Appendix G. Health-adjusted life expectancy was longer at each successively higher level of education.

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From to , differences in life expectancy at birth between the richest and poorest income quintiles diminished by well over 1 year for each sex. For most causes of death, socio-economic disparities in mortality diminished markedly over time Chapter 5 reference 7. However, mortality is only one aspect of population health Chapter 5 reference 3. Two recent reviews Chapter 5 reference 11 Chapter 5 reference 12 reminded readers that, when the worse morbidity experience of lower socio-economic groups is combined with their worse mortality experience, the socio-economic disparities in health become more pronounced than those based on mortality alone.

The McIntosh et al. Canadian women and men in the highest tertile income group in had a health-adjusted life expectancy of Comparison of health-adjusted life expectancy across income groups revealed that, at birth, women in the highest tertile income group had a health-adjusted life expectancy that was 3.

Similarly, men in the highest income group had a health-adjusted life expectancy that was 4. Life expectancy is an indicator of the average number of years that an individual would be expected to live. It is a basic and commonly used measure of population health Chapter 6 reference 1 Chapter 6 reference 2 Chapter 6 reference 3 Chapter 6 reference 4.

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In contrast, health-adjusted life expectancy is a summary measure of population health that attempts to reflect a more complete picture of health than conventional life expectancy. It is a measure of not only quantity of life but also quality of life Chapter 6 reference 5 Chapter 6 reference 6 Chapter 6 reference 7.

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This report provides a perspective and some new data on life expectancy and health-adjusted life expectancy among Canadians by chronic disease status presence or absence of diabetes mellitus, hypertension and cancer and presents recent published estimates of health-adjusted life expectancy in Canada by socio-economic status income.

Health-adjusted life expectancy calculated by the Sullivan method estimates the number of remaining years, at a particular age, that an individual can expect to live in a healthy state however health may be defined. For example, for the period, women in Canada Quebec data unavailable at age 20 years could expect to live a further In Canada, life expectancy is increasing Chapter 6 reference 5 Chapter 6 reference 6 Chapter 6 reference 7 Chapter 6 reference 8.

In , life expectancy at birth was Canadian women lived longer than men by an average of 4.

Introduction

Health expectancies were developed to address the important question of whether or not we are exchanging longer life for poorer health. Health expectancies were developed to address the important question of whether or not we are exchanging longer life for poorer health - replacing quality by.

Health-adjusted life expectancy at birth reflects many chronic diseases that do not develop until a person is older. Therefore, health-adjusted life expectancy at more advanced ages such as the mean age at incidence for a particular disease was also reported. The prevalence of diabetes and obesity has been increasing in Canada, with higher rates among elderly Canadians and among Aboriginal peoples Chapter 6 reference 3. The presence of diabetes was associated with a larger reduction in life expectancy than the presence of hypertension.

At age 20, the loss of life expectancy was higher for both women with diabetes 9. Furthermore, the loss of life expectancy was highest for those with both diabetes and hypertension women: A similar trend was observed for health-adjusted life expectancy. At age 20, the loss of health-adjusted life expectancy was greater when diabetes was present women: Again, the loss of health-adjusted life expectancy was greater when both diabetes and hypertension were present women: This report Chapter 4 also calculated life expectancy and health-adjusted life expectancy in the period for people diagnosed with cancer.

Gender Differences in Health Expectancies across the Disablement Process among Older Thais

The analysis showed that cancer had a substantial impact on life expectancy. People with cancer have a much lower life expectancy and health-adjusted life expectancy than people without cancer. At age 20, the loss of life expectancy for women with cancer was The loss of health-adjusted life expectancy at age 20 for those with cancer was The results showed that, if cancer deaths could be eliminated, the life expectancy at birth of the entire population would increase substantially: by 3. As previously stated, health-adjusted life expectancy is a measure of life expectancy in full health.

It has been increasing faster than life expectancy, but the reasons for this increase are unknown Chapter 6 reference 2 Chapter 6 reference 3 Chapter 6 reference 4 Chapter 6 reference 5. It is likely that there were decreases in the prevalence rates of cancer and heart disease that are attributable to improvements in the health care system and in chronic disease interventions Chapter 6 reference 4.

Canadians have been experiencing continuing increases in life expectancy and in health-adjusted life expectancy Chapter 6 reference 5 Chapter 6 reference 8. In the analyses of health-adjusted life expectancy by chronic disease status, the Public Health Agency of Canada Technical Team on Health-Adjusted Life Expectancy used the health utility index from the Canadian Community Health Survey, which was only available for Canadians aged 12 years and older. There were also data limitations related to coverage for all provinces and territories, with the result that the estimates may not perfectly reflect life expectancy and health-adjusted life expectancy for the entire population Chapter 6 reference 9 Chapter 6 reference 10 Chapter 6 reference Because of those limitations, the actual population-based health-adjusted life expectancy values would be lower than estimated in this report.

Another important limitation was the lack of data for residents of long-term care facilities.

However, this report has demonstrated that linked databases containing information on mortality and on disease prevalence can be used to monitor and estimate health-adjusted life expectancy for subpopulations with other chronic diseases. The reader should keep in mind that the disease-specific results presented in this report are descriptive cross-sectional estimates, not predictive estimates. Life expectancy and health-adjusted life expectancy were also strongly associated with socio-economic status Chapter 6 reference A decrease in the rate of deaths from conditions amenable to medical care made the largest contribution to reducing socio-economic differences in mortality over a year period after the establishment of universal health insurance in Canada Chapter 6 reference 9.

Why is it important?:

Income-related disparities in health-adjusted life expectancy were found to be considerably larger than those for the conventional life expectancy indicator Chapter 6 reference 13 Chapter 6 reference 14 Chapter 6 reference In a recent study of income-related disparities for Canadian adults from to that provided the first nationally representative estimates of socio-economic inequalities in health-adjusted life expectancy in Canada based on individual and family income Chapter 6 reference 12 , health-adjusted life expectancy at age 25 within the highest income decile was Therefore, the disparities in health-adjusted life expectancy between the highest and lowest deciles were 9.

The previously published results described in this report Chapter 5 and Appendix G have provided strong and consistent evidence for an inverse association between socio-economic status and health-adjusted life expectancy. This first report by the Public Health Agency of Canada on health-adjusted life expectancy in Canada has provided policy-relevant information on differences among Canadians in health-adjusted life expectancy based on their chronic disease status and socio-economic status, as well as recommendations from an external consultant for future research at the national level.

The use of data sources available on an ongoing basis and the documentation of the methods used could allow an evaluation of the trends of these indicators in future.