In this study, LE and HALE were estimated for Canadians with and without diabetes by sex and 19 five-year age intervals using a period life table method. Period life tables provide a convenient approach for summarizing mortality data. Benefits of the life table approach are that HRQOL information is easily integrated and reference to an external standard population is not required. The estimates of LE and HALE were based on the mortality and morbidity experience of Canadians with and without diabetes for the period of 2004 to 2006 (mortality) and 2000 to 2005 (morbidity). Therefore, they should be treated as descriptive cross-sectional statistics based on the past experience of the population rather than as predictive, as the mortality and morbidity experience will change with time.
The results show that LE decreases with increasing age and that the decline is faster for LE than HALE. To explain this observation, the age gradient in the HUI3 scores and mortality rates were compared, revealing that mortality rates increased faster than the HUI3 scores declined with increasing age. The results also confirm that in Canada the LE for females is higher than for males, a direct result of higher mortality among men. This is also true for populations of people with diagnosed diabetes (Table 1).
To evaluate the impact of diabetes on health, the number of years and the proportion of life spent in poor health were assessed and compared between populations of people with and without diabetes (Table 2). The difference in the number of years spent in poor health between populations of people without and with diabetes was not statistically significant for all ages. Table 2 shows the estimated number of unhealthy years with confidence intervals for males and females at selected ages. A test for the difference in the estimated number of years spent in poor health for the diseased and nondiseased populations confirmed statistical significance (p-value <0.05) for females at birth and those who are 70 years and older. This test was also statistically significant for 0- to 19- and 25- to 49-year-old males. Females with diabetes at birth had a significantly greater number of years spent in poor health than their counterparts without diabetes. The reverse pattern was found in women who were 70 years and older; those without diabetes had a significantly greater number of unhealthy years than the corresponding females with diabetes. However, these results, along with the pattern of decline in HUI3 estimates in female populations with and without diabetes 55 years and older, may be misleading due to a data limitation. The CCHS data used in the study do not include persons who lived in institutions. The HRQOL estimates for women in the oldest age groups, as reported by Berthelot et al., could be up to 30% lower if those women who lived in institutions were included [28]. HUI3 could be even lower for persons with diabetes because they might be overrepresented in institutions. In addition, women with diagnosed diabetes receive better health care when they visit physicians and gain advice on how to maintain good health, as opposed to women who have not been diagnosed [1].
Males with diabetes from birth up to 49 years, excluding 20- to24-year-olds, had a significantly greater number of years spent in poor health than their counterparts without diabetes. The reverse pattern (similar to females 70 years and older) was also found for 65- to 79-year-old males, but the difference was not statistically significant. Therefore, it could be concluded that diabetes affects both longevity and quality of life (to some extent). The relationship was different among males and females of different ages and was associated with a significant reduction in the number of healthy years among females at birth and among males younger than 50 years.
A further comparison of female and male populations in the study revealed that females spent more years and a greater portion of life in poor health than did males, confirmed by a large body of evidence [26, 27, 29]. It was also observed that the number of years spent in poor health decreased and the portion of life a person spent in poor health increased with increasing age. This was true for both sexes, among people with and without diabetes. For example, at birth, females with diabetes spent 17% of their life in poor health, and the percentage gradually increased to 36% by the age of 80. This age gradient in relative differences varied from 14% to 37% for females without diabetes. The same pattern was observed for males, but the proportions were smaller. Females with diabetes lived shorter lives and spent an even greater portion of their lives in poor health than did females without diabetes. The same applies for males.
To evaluate the impact of diabetes on longevity and the number of healthy years, the loss in LE and HALE associated with diabetes was estimated and presented in Table 2. It was observed that females in the age interval of 0 to 54 years had a slightly greater number of years of life lost in HALE than in LE. The reverse pattern was identified for females 55 years and older. The loss in LE was greater than the loss in HALE. For males, the loss in HALE was greater than the loss in LE for all ages excluding 65- to 79-year-old males for whom the reverse pattern was also observed.
In a similar study on hypertension [30], 55-year-old females had a 1.5 year loss in LE and 2.0 year loss in HALE as compared with their counterparts with diabetes who experienced greater losses of 6.0 years and 5.8 years, respectively. Males with hypertension who were 55 years old had a 2.1 year loss in LE and 2.7 year loss in HALE, compared with their counterparts with diabetes who also experienced greater losses of 5.0 years and 5.3 years, respectively. The impact of diabetes on the loss of LE and HALE was greater than the impact of hypertension.
The loss in LE presented in this study is conceptually similar to the life-years lost reported by Narayan et al. [7] for the US population. But because there are differences in the methods of calculation of loss in LE and life-years lost, results may not be directly compared. For example, in our study, the loss in LE estimated for 10-year-old females with diagnosed diabetes was 10.1 years (result not shown), and the life-years lost reported by Narayan et al. was 19.0 years. Notably, the mortality rate ratios [31] used in the Narayan paper were for North Dakota and for a period 10 years earlier than our study. As another example, our loss in HALE estimated for 10-year-old females with diabetes was 10.9 years, and the corresponding QALYs lost in the study by Narayan et al. was 32.8 years. The difference is attributed to a number of differences in the methods of calculation of loss in HALE and QALYs lost. First, the loss in HALE in our study is defined as the difference between HALE for people without diabetes and HALE for people with diabetes. We deduced from the Narayan et al. paper that the QALYs lost are the difference between LE for people without diabetes and QALYs for people with diabetes. Second, in our HALE calculations we applied age-specific HUI3 weights that vary across all age groups. The mean HUI3 for all ages in our data was 0.825 for people with diabetes and 0.872 for people without diabetes. A constant quality of life weight of 0.75 [32] was used for all age groups in the QALYs lost calculations [7].
To quantify the potential gain in LE (or HALE) if hypothetical eradication of diagnosed diabetes was possible, the difference in LE (or HALE) between the population without diabetes and total population was calculated and analyzed. This method, referred to as disease-deleted in this study, is different than the traditional cause-deleted approach [2, 3, 6]. The principal difference between these two approaches is how mortality rates are adjusted to represent the mortality experience of a diabetes-free population. For the cause-deleted approach the number of deaths categorized as “caused” by diabetes are subtracted from the numerator and the denominator is the total population. This adjustment guarantees that the cause-deleted mortality rates will be lower than the rates for the total population. For the disease-deleted approach all prevalent cases of diabetes (and their deaths) are removed and mortality rates are calculated. Thus, the numerator is the number of deaths among people without diagnosed diabetes and the denominator is the number of people in the population without diagnosed diabetes. It more accurately represents the mortality experience of a population free of diagnosed diabetes. The cause-deleted method works well for diseases with poor survival like myocardial infarction, some types of cancer, or infectious diseases where the underlying cause of death is clear. But it does not work very well for diseases such as diabetes that are associated with comorbidity and manifest themselves in many different causes of death [33]. Using the life expectancy among people without diagnosed diabetes instead of diabetes-deleted life expectancy [2, 3, 6] (or to be exact diabetes-specific death deleted life expectancy) avoids this problem and allows a more accurate assessment of the diagnosed diabetes burden. Although this method more accurately represents the mortality experience of a population free of diagnosed diabetes, it does not accommodate for competing disease risk factors.
According to this study, the gain in LE at birth after the hypothetical elimination of diagnosed diabetes was 1.4 years for females and 1.3 years for males. The corresponding gain in HALE was 1.2 and 1.3 years for females and males, respectively. This indicates that diabetes is an important disease burden in Canada. These estimates were greater than estimates of the gain in LE and HALE after removing only diabetes-specific death reported by Manuel et al. [5], but the pattern was similar. According to Manuel [2], an expansion of morbidity is evident when years of HALE gained were less than the years gained in life expectancy. In this study, the gain in HALE was less than the gain in LE for males and females of all ages, but the difference between the gain in LE and the gain in HALE was not large, which is consistent with other studies. Although diabetes is an important disease burden, it does not affect morbidity to a great extent. The ratio of HALE to LE reported by Manuel et al. [4, 5] for Ontarians with and without diabetes implies the similar conclusion. This ratio quantifies a portion of life people spent in a healthy state. It was estimated to be 0.91 for males without diabetes and 0.90 for males with diabetes. The ratio of HALE to LE was 0.89 for females in both populations. This evidence suggests that impact of diabetes on length of life is similar or slightly smaller than the impact on years of healthy life. LE and HALE for the same population share the same mortality and are highly correlated (r ≈ 1).
Type 1 and type 2 diabetes were not distinguished in this study due to data limitations. However, the majority of cases of diabetes were type 2. There is growing evidence that type 2 diabetes and its complications can be prevented through the reduction of key risk factors such as obesity and physical inactivity. Evidence from the most recently published US study [8] suggests that the lifetime risk of developing diabetes increases over time, thereby decreasing diabetes-free life expectancy. According to the authors, this decrease is closely related to increased obesity prevalence, especially in youth. Type 2 diabetes, previously known as an adult’s disease, is more often seen among children in recent years [34]. The pattern of obesity in Canada is similar to the US and therefore the findings in this research may be applicable to Canada as well. Temporal increases in obesity and diabetes prevalence in Canada may result in decreasing diabetes-free LE and increasing LE with diabetes. Earlier onset of diabetes will likely contribute to decreases in LE and HALE for people with diabetes. However, improvements in diabetes care and further decreases in mortality rates will play the opposite role. The impact of increased obesity and diabetes prevalence and achievements in diabetes care requires further investigation. Therefore, it is important to track changes in both LE and HALE and to monitor the gap between those measures.
The results in this study could be biased toward the null because it was limited to Canadians with or without diagnosed diabetes (those who have been identified by a health professional). Using fasting blood samples collected in the 2007 to 2009 Canadian Health Measures Survey (CHMS), the magnitude of undiagnosed diabetes in Canada was estimated as 0.9% (95% CI: 0.5%-1.4%) of the Canadian population aged 6 years and older (PHAC. Unpublished analysis using 2007–2009 CHMS data. 2011). Therefore, it is possible that those who have been falsely identified by the CCDSS as having diabetes may have had prediabetes.
Another limitation was that the potential gain in HALE might be overestimated due to using the disease-deleted method for this paper. Hypothetically, if diagnosed diabetes could be eliminated, the health status of those people who were living with diagnosed diabetes would likely be lower than of those people who have never had diagnosed diabetes. As a result, the gain in HALE estimated in this study should be somewhat lower than reported.
In addition, the true values of HALE would be somewhat lower than reported because data for residents of long-term care facilities were unavailable. Misclassification of diabetes status was present in both the survey data and the surveillance system data we used. In the CCHS, misclassification can be due to self-reporting bias, generally a tendency to underreport the true disease status. In the CCDSS, misclassification toward the nondiabetic status can be present in geographic areas where data were incomplete. Areas with a larger proportion of salaried physicians provide the least complete data, which results in identifying fewer individuals with disease. Consequently, the disease status concordance between the two data sources varies by province and territory [35, 36]. Linkage of these two data sources (CCDSS and CCHS) would provide a method to reduce the self-reporting bias and the misclassification error.
In summary, this paper describes the method used by the Public Health Agency of Canada to calculate life expectancy and health-adjusted life expectancy among Canadian adults with and without diabetes, based on mortality data for the period from 2004 to 2006 and morbidity data for the period from 2000 to 2005. Our work shows that it is possible to calculate HALE for all Canadians and for subpopulations with this particular chronic condition. The results of the study confirm that diabetes is an important disease burden in Canada and it has various impacts for female and male populations of different ages. Our method can be adapted for calculations for other chronic conditions in order to monitor the gap between LE and HALE so that health professionals can assess the impact on good health and revise programs and policies, if warranted.