NEW PROJECTIONS OF MORTALITY AND CAUSES OF DEATH TO YEAR 2060

Back in 2006, I published a paper in PLoS Medicine with detailed projections of deaths by age, sex and cause for all regions of the world, from year 2002 to 2030 (https://journals.plos.org/plosmedicine/article?id=10.1371/journal.pmed.0030442).  That paper has proved very popular, with over 9000 citations to date.  I’ve updated these projections to most recent WHO baseline estimates several times, and following the release of the latest update of causes of death for year 2016 by WHO earlier this year (http://www.who.int/healthinfo/global_burden_disease/estimates/en/), I have done another update, extending the projections for the first time beyond 2030 to 2060.

This has now been released by WHO on its website at http://www.who.int/healthinfo/global_burden_disease/projections/en/ where regional and global projections can be downloaded in spreadsheet form, along with a methods note. Apart from synchronising the new projections with the 2016 cause of death estimates, the cause-specific trends in the near term are synchronized with estimated recent trends over the last 10 to 15 years. In the longer term, broad trends are largely driven by projection equations which model the epidemiological transition from infectious to non-communicable diseases in terms of projections of average income per capita, average years of education, time, and for some causes also projections of smoking impact.

In the original projections, separate projection models were developed for HIV/AIDS, tuberculosis, lung cancer, diabetes mellitus and chronic respiratory diseases.  These models were revised and updated for this latest update. Additional special projection models were also been developed for malaria, maternal deaths, road injury, homicide, natural disasters and war and conflict.

At the global level, age-standardized death rates for most important causes are falling with time, faster in most cases for infectious, maternal and perinatal causes than for non-communicable diseases (see figures below). The main exceptions are for diabetes, breast cancer and road injuries. The specific projection model for diabetes is based on projections of the prevalence of overweight and obesity and that for road injury is based on projections of vehicles per capita with continued economic development.

IHD = Ischaemic heart disease, COPD = Chronic Obstructive Pulmonary Disease,
ARI = Acute respiratory infection (mainly pneumonia), TB = tuberculosis

However, for many of these causes, the total projected deaths are rising with time because of population growth and ageing. Only the relatively fast declining infectious, maternal and perinatal causes are likely to also have declining total numbers of deaths (see the following two figures).

The projections of deaths by cause are not intended as forecasts of what will happen in the future but as projections of current and past trends, based on certain explicit assumptions. The methods used base the disease burden projections largely on broad mortality projections driven by projections of future growth in income and increases in human capital in different regions of the world, together with a model relating these to cause-specific mortality trends based on the historical observations in countries with death registration data over the last 60 years. The results depend strongly on the assumption that future mortality trends in poor countries will have a similar relationship to economic and social development as has occurred in the higher income countries. If governments give increased priority and resources to achievement of the Sustainable Development Goals by the year 2030 and progress towards Universal Health Coverage with the most relevant cost-effective interventions, it is entirely possible and certainly to be hoped that future declines in mortality for many causes will be faster than these business-as-usual projections.  On the other hand, if economic growth in low income countries is lower than the forecasts used here, and global warming results in additional adverse impacts on economic and social development, then the world may achieve slower progress and widening of health inequalities.

Despite these uncertainties, projections provide a useful perspective on sustainable health trends and health policies, provided that they are interpreted with a degree of caution. Projections enable us to appreciate better the implications for health and health policy of currently observed trends, and the likely impact of fairly certain future trends, such as the ageing of the population, and the continuation of the epidemiological transition in developing countries.

Projected global deaths in 2030 and 2060 under the business-as-usual scenario  are 68.2 million and 101.8 million respectively. Projected global deaths in 2030 under the UN medium variant projections of the World Population Prospects 2017 (WPP2017) are 2% higher in 2030 at 69.5 million and 0.7% lower at 101.1 million in 2060. These global projections for all-cause mortality are remarkably close to the UN projections given that these are the sum of independent projections for 20 separate cause groups, whereas the UN projections are based on estimated trends in all-cause mortality and fertility. The results are also very similar for all regions except the South East Asian Region and the African Region.  For the South East Asian Region, the UN projections are higher, with 3.5% more deaths in 2030 rising to 12% more deaths in 2060. For the African Region, the UN projections are slightly higher in 2030 but by 2060 are 12% lower.

The following figure compares projected life expectancies at birth for the world and for countries grouped by income. The projections are very similar for the world and for middle- and high-income countries. The main difference is for low income countries (predominantly African) where the projected life expectancy is 1 year lower than the UN projected life expectancy in 2030 rising to 3.9 years difference in 2060.

These updated projections have drawn heavily on WHO official statistics, and data sets and analyses carried out by my former colleagues in WHO, as well as collaborators in other UN agencies and universities. The development of some of the modelling approaches has benefited from discussions with Majid Ezzati, Vasilis Kontis, Margie Peden, Gretchen Stevens and Dan Hogan.

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