Health expectancy and the problem of substitute morbidity

Taking multi-morbidity into account when attributing DALYs to risk factors: comparing dynamic modeling with the GBD2010 calculation method

BACKGROUND

Disability Adjusted Life Years (DALYs) quantify the loss of healthy years of life due to dying prematurely and due to living with diseases and injuries. Current methods of attributing DALYs to underlying risk factors fall short on two main points. First, risk factor attribution methods often unjustly apply incidence-based population attributable fractions (PAFs) to prevalence-based data. Second, it mixes two conceptually distinct approaches targeting different goals, namely an attribution method aiming to attribute uniquely to a single cause, and an elimination method aiming to describe a counterfactual situation without exposure. In this paper we describe dynamic modeling as an alternative, completely counterfactual approach and compare this to the approach used in the Global Burden of Disease 2010 study (GBD2010).

METHODS

Using data on smoking in the Netherlands in 2011, we demonstrate how an alternative method of risk factor attribution using a pure counterfactual approach results in different estimates for DALYs. This alternative method is carried out using the dynamic multistate disease table model DYNAMO-HIA. We investigate the differences between our alternative method and the method used by the GBD2010 by doing additional analyses using data from a synthetic population in steady state.

RESULTS

We observed important differences between the outcomes of the two methods: in an artificial situation where dynamics play a limited role, DALYs are a third lower as compared to those calculated with the GBD2010 method (398,000 versus 607,000 DALYs). The most important factor is newly occurring morbidity in life years gained that is ignored in the GBD2010 approach. Age-dependent relative risks and exposures lead to additional differences between methods as they distort the results of prevalence-based DALY calculations, but the direction and magnitude of the distortions depend on the particular situation.

CONCLUSIONS

We argue that the GBD2010 approach is a hybrid of an attributional and counterfactual approach, making the end result hard to understand, while dynamic modelling uses a purely counterfactual approach and thus yields better interpretable results.

Changing age patterns of morbidity vis-à-vis mortality in India

The combined effects of decreased fertility and mortality coupled with increasing survivorship across most ages have been upsetting the levels and age patterns of morbidity and mortality in India. This study examined data from the National Sample Survey (NSS) and Sample Registration System (SRS) of India. The results reveal marked structural changes in the age patterns of morbidity and mortality. The analysis also tested whether morbidity contours are being compressed or expanded, connecting it with the ongoing processes of demographic and epidemiological transition. The Sullivan (1971) method was used to estimate the health ratio over three time periods to ascertain the expansion of morbidity. The results reveal an exceptional rise in the prevalence rate of chronic non-communicable diseases in ages 60 and above. The proportion of unhealthy years of the total life expectancy has increased more than before for all older age groups. Overall, the results confirm that an expansion of morbidity is in progress, with a heavier and cumulated concentration of morbidity in older ages. The expansion of morbidity hypothesis is validated for major categories of population: rural, urban, male and female. Older females bear a much heavier burden of chronic non-communicable diseases and are vulnerable to a higher proportion of unhealthy years. The age-structural shifts in morbidity and mortality signal the steady progress of epidemiological transition in India.

Healthy life expectancy for 187 countries, 1990-2010: a systematic analysis for the Global Burden Disease Study 2010

BACKGROUND

Healthy life expectancy (HALE) summarises mortality and non-fatal outcomes in a single measure of average population health. It has been used to compare health between countries, or to measure changes over time. These comparisons can inform policy questions that depend on how morbidity changes as mortality decreases. We characterise current HALE and changes over the past two decades in 187 countries.

METHODS

Using inputs from the Global Burden of Disease Study (GBD) 2010, we assessed HALE for 1990 and 2010. We calculated HALE with life table methods, incorporating estimates of average health over each age interval. Inputs from GBD 2010 included age-specific information for mortality rates and prevalence of 1160 sequelae, and disability weights associated with 220 distinct health states relating to these sequelae. We computed estimates of average overall health for each age group, adjusting for comorbidity with a Monte Carlo simulation method to capture how multiple morbidities can combine in an individual. We incorporated these estimates in the life table by the Sullivan method to produce HALE estimates for each population defined by sex, country, and year. We estimated the contributions of changes in child mortality, adult mortality, and disability to overall change in population health between 1990 and 2010.

FINDINGS

In 2010, global male HALE at birth was 58·3 years (uncertainty interval 56·7-59·8) and global female HALE at birth was 61·8 years (60·1-63·4). HALE increased more slowly than did life expectancy over the past 20 years, with each 1-year increase in life expectancy at birth associated with a 0·8-year increase in HALE. Across countries in 2010, male HALE at birth ranged from 27·9 years (17·3-36·5) in Haiti, to 68·8 years (67·0-70·4) in Japan. Female HALE at birth ranged from 37·1 years (26·9-43·7) in Haiti, to 71·7 years (69·7-73·4) in Japan. Between 1990 and 2010, male HALE increased by 5 years or more in 42 countries compared with 37 countries for female HALE, while male HALE decreased in 21 countries and 11 for female HALE. Between countries and over time, life expectancy was strongly and positively related to number of years lost to disability. This relation was consistent between sexes, in cross-sectional and longitudinal analysis, and when assessed at birth, or at age 50 years. Changes in disability had small effects on changes in HALE compared with changes in mortality.

INTERPRETATION

HALE differs substantially between countries. As life expectancy has increased, the number of healthy years lost to disability has also increased in most countries, consistent with the expansion of morbidity hypothesis, which has implications for health planning and health-care expenditure. Compared with substantial progress in reduction of mortality over the past two decades, relatively little progress has been made in reduction of the overall effect of non-fatal disease and injury on population health. HALE is an attractive indicator for monitoring health post-2015.

FUNDING

The Bill & Melinda Gates Foundation.

Evolution of the needs of older persons

Most countries in the world experienced a major increase in life expectancy during the 20th century and a resulting aging of their populations. Further gains in life expectancy are uncertain, particularly in developed countries already characterized by a high longevity, and little is known concerning the health state of future generations of the elderly. But there is no doubt that further population aging will produce larger numbers of older persons both in developed and developing countries. As the prevalence of most chronic diseases is high in old age, population needs change rapidly in health care systems still organized essentially to provide acute care to children and young adults. Old age is heterogeneous, but a large proportion of older persons is affected by multiple chronic diseases, resulting in a wide range of needs. Health systems will have to adapt to this new situation while still providing appropriate responses to acute diseases affecting all ages. Although future needs are difficult to quantify, their nature is already apparent. Providing for these needs will require a major investment in manpower, a diversification of services delivered by health care systems, changes in the training of health professionals and extensive research to define effective treatments for elderly patients with multiple co-morbidities.