Evidence map›Paper›PMID 38483443›Full record

ArticleJournal of global health2024

Assessing health determinants worldwide: Econometric analysis of the Global Burden of Diseases Study 2000-18 - Highlighting impactful factors on DALY, YLL, and YLD indicators.

Kamran Irandoust, Rajabali Daroudi, Maryam Tajvar, Mehdi Yaseri

Abstract read
In one paragraph

Article in Journal of global health, 2024. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 4 papers, 1 of them a synthesis that pooled it.

0numbers the graph read from it
0cells of the map it votes in
4citing papers in PubMed, 1 pooled it
–field-weighted citation impact
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

4 citing papers in PubMed, 1 synthesis or guideline pooled it.

  1. Pooled it
  2. Geospatial inequalities in severe leprosy disability in Pernambuco before and during COVID-19.The Brazilian journal of infectious diseases : an official publication of the Brazilian Society of Infectious Diseases · 2026
    Article
  3. Article
  4. Article
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.

Kamran Irandoust *Department of Health Management, Policy, and Economics, School of Public Health, Tehran University of Medical Sciences, Tehran, Iran.
Rajabali Daroudi *Department of Health Management, Policy, and Economics, School of Public Health, Tehran University of Medical Sciences, Tehran, Iran.
Maryam TajvarDepartment of Health Management, Policy, and Economics, School of Public Health, Tehran University of Medical Sciences, Tehran, Iran.
Mehdi YaseriDepartment of Epidemiology and Biostatistics, School of Public Health, Tehran University of Medical Sciences, Tehran, Iran.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Background: As the health status of a population is influenced by a variety of health determinants, we sought to assess their impact on health outcomes, both at the global and regional levels. Methods: This ecological study encompassed all 194 member countries of the World Health Organization (WHO) from 2000 to 2018. We first identified all health determinants and then retrieved the related data from various global databases. We additionally considered three indicators - disability-adjusted life years (DALYs), years of life lost (YLL), and years lived with disability (YLD) - in evaluating health outcomes; we extracted their data from the Global Burden of Disease (GBD) 2019 study. We then applied econometric analyses using a multilevel mixed-effects linear regression model. Results: The analysis using the DALY indicator showed that the variables of sexually transmitted infections, injuries prevalence, and urbanisation had the highest effect size or regression coefficients (β) for health outcomes. The variables of sexually transmitted infection (β = 0.75, P < 0.001) in the African region; drinking water (β = -0.60, P < 0.001), alcohol use (β = 0.20, P < 0.001), and drug use (β = 0.05, P = 0.036) in the Americas region; urbanisation (β = -0.34, P < 0.001) in the Eastern Mediterranean region; current health expenditure (β = -0.21, P < 0.001) in the Europe region; injuries (β = 0.65, P < 0.001), air pollution (β = 0.29, P < 0.001), and obesity (β = 0.92, P < 0.001) in the South-East Asia region; and gross domestic product (β = -0.25, P < 0.001), education (β = -0.90, P < 0.001), and smoking (β = 0.28, P < 0.001) in the Western Pacific region had the most significant role in explaining global health outcomes. Except for the drug use variable in regional findings, the role of other variables in explaining the YLL indicator was greater than that of the YLD indicator. Conclusions: To address global health disparities and optimise resource allocation, global and interregional policymakers should focus on determinants that had the highest β with health outcomes in each region compared to other regions. These determinants likely have a higher marginal health product, and investing in them is likely to be more cost-effective.

Indexed as

Air PollutionHealth StatusAfricaAmericasAsiaEuropeGlobal Burden of DiseaseHumansOceaniaQuality-Adjusted Life Years

Identifiers

PMID38483443
PMCPMC10939113

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LicenceCC BY
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Registered trials

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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.