Disease and demography: a systems-dynamic cohort-component population model to assess the implications of disease-specific mortality targets

INTRODUCTION: The 2015 Sustainable Development Goals include the objective of reducing premature mortality from major non-communicable diseases (NCDs) by one-third by 2030. Accomplishing this objective has demographic implications with relevance for countries’ health systems and costs. However, evidence on the system-wide implications of NCD targets is limited. METHODS: We developed a cohort-component model to estimate demographic change based on user-defined disease-specific mortality trajectories. The model accounts for ageing over 101 annual age cohorts, disaggregated by sex and projects changes in the size and structure of the population. We applied this model to the context of Bangladesh, using the model to simulate demographic outlooks for Bangladesh for 2015–2030 using three mortality scenarios. The ‘status quo’ scenario entails that the disease-specific mortality profile observed in 2015 applies throughout 2015–2030. The ‘trend’ scenario adopts age-specific, sex-specific and disease-specific mortality rate trajectories projected by WHO for the region. The ‘target’ scenario entails a one-third reduction in the mortality rates of cardiovascular disease, cancer, diabetes and chronic respiratory diseases between age 30 and 70 by 2030. RESULTS: The status quo, trend and target scenarios projected 178.9, 179.7 and 180.2 million population in 2030, respectively. The cumulative number of deaths during 2015–2030 was estimated at 17.4, 16.2 and 15.6 million for each scenario, respectively. During 2015–2030, the target scenario would avert a cumulative 1.73 million and 584 000 all-cause deaths compared with the status quo and trend scenarios, respectively. Male life expectancy was estimated to increase from 71.10 to 73.47 years in the trend scenario and to 74.38 years in the target scenario; female life expectancy was estimated to increase from 73.68 to 75.34 years and 76.39 years in the trend and target scenarios, respectively. CONCLUSION: The model describes the demographic implications of NCD prevention and control targets, estimating the potential increase in life expectancy associated with achieving key NCD reduction targets. The results can be used to inform future health system needs and to support planning for increased healthcare coverage in countries.