Evidence map›Paper›PMID 30464769›Full record

ArticleInternational journal of endocrinology and metabolism2018

World Bank Income Group, Health Expenditure or Cardiometabolic Risk Factors? A Further Explanation of the Wide Gap in Cardiometabolic Mortality Between Worldwide Countries: An Ecological Study.

Mojtaba Lotfaliany, Samaneh Akbarpour, Neda Zafari, Mohammad Ali Mansournia, Samaneh Asgari, Fereidoun Azizi, Farzad Hadaegh, Davood Khalili

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Article in International journal of endocrinology and metabolism, 2018. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 4 papers, 3 of them syntheses that pooled it.

0numbers the graph read from it
0cells of the map it votes in
4citing papers in PubMed, 3 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, 3 syntheses or guidelines pooled it.

  1. Pooled it
  2. Pooled it
  3. Pooled it
  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

8 authors.

Mojtaba LotfalianySchool of Population and Global Health, University of Melbourne, Victoria, Australia.
Samaneh AkbarpourPrevention of Metabolic Disorders Research Center, Research Institute for Endocrine Sciences, Shahid Beheshti University of Medical Sciences, Tehran, Iran.
Neda ZafariPrevention of Metabolic Disorders Research Center, Research Institute for Endocrine Sciences, Shahid Beheshti University of Medical Sciences, Tehran, Iran.
Mohammad Ali MansourniaDepartment of Epidemiology and Biostatistics, School of Public Health, Tehran University of Medical Sciences, Tehran, Iran.
Samaneh AsgariPrevention of Metabolic Disorders Research Center, Research Institute for Endocrine Sciences, Shahid Beheshti University of Medical Sciences, Tehran, Iran.
Fereidoun AziziEndocrine Research Center, Research Institute for Endocrine Sciences, Shahid Beheshti University of Medical Sciences, Tehran, Iran.
Farzad HadaeghPrevention of Metabolic Disorders Research Center, Research Institute for Endocrine Sciences, Shahid Beheshti University of Medical Sciences, Tehran, Iran.
Davood KhaliliPrevention of Metabolic Disorders Research Center, Research Institute for Endocrine Sciences, Shahid Beheshti University of Medical Sciences, Tehran, Iran.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

backgroundFor addressing the burden of non-communicable diseases and policymaking, the world health organization uses World Bank income group to classify countries. This calcification method might not be optimal. This study aimed to investigate the role of World Bank income group, health expenditure, and cardiometabolic risk factors of countries in explaining the gap between their cardiometabolic mortality.

methodsIn total, 190 countries were categorized into four income groups according to the World Bank definition. The energy consumption, health expenditure, and data of sex-specified age-standardized prevalence of obesity, hypercholesterolemia, hypertension, diabetes, smoking, and physical inactivity in 2008 and cardiometabolic mortality in 2012 were used. Multivariable-adjusted mixed-effect linear regression models were applied to relate country-level predictors to their mortality outcomes.

resultsWhile the lowest cardiometabolic mortality was recorded in high-income countries in both genders, the highest rates were recorded in the low-income category for women and in low and middle-income for men. Countries had lower cardiometabolic mortality for women compared to men; however, such a difference was not shown in low-income countries. World Bank income group of countries, per se, explained one-third of the variation in their mortality outcomes while adding health expenditure, energy consumption, and cardiometabolic risk factors increased the explanatory power of the model considerably. Moreover, the more the health expenditure, the weaker the association of prevalence of hypertension with cardiometabolic mortality.

conclusionsAdding countries' health expenditure and/or the prevalence of risk factors to their World Bank income group may contribute to the better explanation of the gap between them in cardiometabolic mortality.

Indexed as

Cardiometabolic MortalityCardiovascular Risk FactorsEcological StudyHealth ExpenditureIncome

Identifiers

PMID30464769
PMCPMC6208042

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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.