Sub-national mapping of population pyramids and dependency ratios in Africa and Asia

Abstract

The age group composition of populations varies substantially across continents and within countries, and is linked to levels of development, health status and poverty. The subnational variability in the shape of the population pyramid as well as the respective dependency ratio are reflective of the different levels of development of a country and are drivers for a country’s economic prospects and health burdens. Whether measured as the ratio between those of working age and those young and old who are dependent upon them, or through separate young and old-age metrics, dependency ratios are often highly heterogeneous between and within countries. Assessments of subnational dependency ratio and age structure patterns have been undertaken for specific countries and across high income regions, but to a lesser extent across the low income regions. In the framework of the WorldPop Project, through the assembly of over 100 million records across 6,389 subnational administrative units, subnational dependency ratio and high resolution gridded age/sex group datasets were produced for 87 countries in Africa and Asia.

Human papillomavirus genotyping among women with cervical abnormalities in Ulaanbaatar, Mongolia

“…Mongolia is a landlocked country with a total population of three million. About two-thirds of the population live in the capital city Ulaanbaatar (Pezzulo et al, 2017); remote areas are sparsely populated. Mongolia has undergone significant socioeconomic changes accompanied by an unstable government and poor systemic policy.…”

Gridded birth and pregnancy datasets for Africa, Latin America and the Caribbean

“…Sub-national information on age and sex structure was collected, specifically women of childbearing age grouped in seven 5-years age groups (i.e., 15–19, 20–24, 25–29, 30–34, 35–39, 40–44, 45–49), as defined by the UNPD 18 . Datasets for the majority of Africa were provided by Pezzulo et al 19 whilst datasets for the remaining African, Latin America and the Caribbean countries were assembled from a variety of sources, following the protocols defined by Pezzulo et al 19 . Table 1 (available online only) shows the source, spatial detail (i.e., administrative unit level) and reference year used for the countries processed in this study.…”

“…Sub-national ASFRs were calculated by dividing the number of births in each age group (e.g., Table 5 ) by the number of females in the corresponding group. The latter was derived from the WorldPop population distribution 15 and age-sex distributions produced following the methodology of Pezzulo et al 19 and outlined in Table 1 (available online only).…”

“…The gridded 5-year age and sex count datasets constructed for Latin America and the Caribbean (e.g., Fig. 2c ) were verified following the protocol outlined in Pezzulo et al 19 , who compiled and assessed similar datasets for Africa and Asia. Briefly, this comprised of summing all the layers into a single dataset (representing the total numbers of people for all age and sex groups at the grid cell level) and then subtracting it from the corresponding WorldPop continental gridded population count dataset to make sure that the country totals matched the UNPD estimates for the year in question.…”

Optimizing Pension Outcomes Using Target‐Driven Investment Strategies: Evidence from Three Asian Countries with the Highest Old‐Age Dependency Ratio*

“…The old-age dependency ratio refers to the ratio between the number of people who are retired and the number of people who are working (Ediev et al 2019). When a country has a high old-age dependency ratio, its working forces face a greater burden to support the living expenses of its elderly population (Pezzulo et al 2017). Therefore, for the present study, we evaluate and compare the performance of a pension portfolio under the lifecycle strategy and the target volatility strategy in three countries that are predicted to have the highest old-age dependency ratio in the future.…”