Evidence map›Paper›PMID 38267807›Full record

ArticlePharmacoEconomics2024

The Burden of Type 2 Diabetes on the Productivity and Economy in Sub-Saharan Africa: A Life Table Modelling Analysis from a South African Perspective.

Assegid Hellebo, Andre P Kengne, Zanfina Ademi, Olufunke Alaba

Open access · hybridAbstract read
In one paragraph

Article in PharmacoEconomics, 2024. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 9 papers.

0numbers the graph read from it
0cells of the map it votes in
9citing papers in PubMed
5.4field-weighted citation impact, top 5% of its field
1 · What the graph read from it

What it found

Each row is one number read from the abstract, on the scale the paper reported it, with its interval. Left of the dashed line favours the treatment, right favours the comparator. Under each row is the sentence it came from. New to these charts? A ten-minute tutorial.

The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.

2 · The registry

The trial behind it

Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.

Neither the registry nor the abstract names a trial number. If this is a trial report, that itself is worth knowing.

3 · Its place in the literature

Who cites it

9 citing papers in PubMed, 8 citations in OpenAlex.

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  9. Impacts of diabetes mellitus in the workplace: an integrative review of occupational and economic factors.Revista brasileira de medicina do trabalho : publicacao oficial da Associacao Nacional de Medicina do Trabalho-ANAMT
    Review
4 · The record

Corrections and comments

PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.

5 · Who and what money

Authors and funding

4 authors at 3 institutions in 2 countries.

Assegid HelleboHealth Economics Unit, School of Public Health, Faculty of Health Sciences, University of Cape Town, Observatory, 7925, South Africa. hllass001@myuct.ac.za.ORCID 0000-0002-1211-844X
Andre P KengneDepartment of Medicine, University of Cape Town and Non-Communicable Diseases Research Unit, South African Medical Research Council (SAMRC), Francie Van Zijl Dr, Parow Valley, Cape Town, 7501, South Africa.
Zanfina AdemiHealth Economics and Policy Evaluation Research (HEPER) Group, Centre for Medicine Use and Safety, Faculty of Pharmacy and Pharmaceutical Sciences, Monash University, Melbourne, Australia.
Olufunke AlabaHealth Economics Unit, School of Public Health, Faculty of Health Sciences, University of Cape Town, Observatory, 7925, South Africa.
University of Cape Town · ZAMonash University · AUSouth African Medical Research Council · ZA

Funding

Division of Research Capacity Development This was a PhD study scholarship
6 · The paper itself

Abstract

BACKGROUND AND

aimThe prevalence of type 2 diabetes (T2D) is rapidly increasing in Sub-Saharan Africa (SSA). T2D increases the risk of premature death and reduces quality of life and work productivity. This population life table modelling analysis evaluated the impact of T2D in terms of productivity-adjusted life years (PALYs) on the South African working-age population. RESEARCH DESIGN AND

methodsLife table modelling was employed to simulate the follow-up of individuals aged 20-65 with T2D in South Africa (SA). Two life table models were developed to simulate health outcomes for a SA cohort with and without diabetes. The difference in the number of deaths, years of life lost (YLL), and PALYs lost between the two cohorts represented the burden of diabetes. Scenarios were simulated in which the proportions of gross domestic productivity (GDP), productivity indices, labour force dropout, and mortality risk trends were adjusted to lower and upper uncertainty bounds. Data were sourced from the International Diabetes Federation, Statistics SA, and both publicly available and published sources. We utilised the World Health Organization (WHO) standard annual discount rate of 3% for YLL and PALYs.

resultsIn 2019, an estimated 9.5% (7.68% men and 11.37% women) or 3.2 million total working-age people had T2D in SA. Simulated follow-up until retirement predicted 669,427 excess mortality, a loss of 6.2 million years of life (9.3%) and 13 million PALYs (30.6%) in SA. On average, this resulted in 3.1 PALYs lost per person. Based on the GDP per full-time employee in 2019, the PALYs loss equated to US$223 billion, or US$69,875 per person.

conclusionsThis study emphasises the significant impact of T2D on society and the economy. Relatively modest T2D prevention and treatment management enhancement could lead to substantial economic benefits in SA.

Indexed as

Diabetes Mellitus, Type 2Quality of LifeCost of IllnessEfficiencyFemaleHumansLife TablesMaleSouth Africa

Identifiers

PMID38267807
PMCPMC11636673
OpenAlexW4391176016

What OpenQuestion holds

Textmetadata
LicenceCC BY-NC
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Registered trials

None linked

Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.