Evidence map›Paper›PMID 35587275›Full record

ArticleDiabetologia2022

Low- and middle-income countries demonstrate rapid growth of type 2 diabetes: an analysis based on Global Burden of Disease 1990-2019 data.

Jinli Liu, Ruhai Bai, Zhonglin Chai, Mark E Cooper, Paul Z Zimmet, Lei Zhang

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Article in Diabetologia, 2022. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 82 papers, 5 of them syntheses that pooled it.

0numbers the graph read from it
0cells of the map it votes in
82citing papers in PubMed, 5 pooled it
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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

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3 · Its place in the literature

Who cites it

82 citing papers in PubMed, 5 syntheses or guidelines pooled it.

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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

6 authors.

Jinli LiuChina-Australia Joint Research Center for Infectious Diseases, School of Public Health, Xi'an Jiaotong University Health Science Center, Xi'an, Shaanxi, China.ORCID https://orcid.org/0000-0002-4220-842X
Ruhai BaiSchool of Public Affairs, Nanjing University of Science and Technology, Nanjing, China.ORCID https://orcid.org/0000-0001-5426-6291
Zhonglin ChaiDepartment of Diabetes, Central Clinical School, Monash University, Melbourne, VIC, Australia.ORCID https://orcid.org/0000-0001-8182-8579
Mark E CooperDepartment of Diabetes, Central Clinical School, Monash University, Melbourne, VIC, Australia.ORCID https://orcid.org/0000-0001-7785-2488
Paul Z ZimmetDepartment of Diabetes, Central Clinical School, Monash University, Melbourne, VIC, Australia.ORCID https://orcid.org/0000-0003-0627-0776
Lei ZhangChina-Australia Joint Research Center for Infectious Diseases, School of Public Health, Xi'an Jiaotong University Health Science Center, Xi'an, Shaanxi, China. lei.zhang1@monash.edu.ORCID http://orcid.org/0000-0003-2343-084X

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

aims/hypothesisThe study aims to quantify the global trend of the disease burden of type 2 diabetes caused by various risks factors by country income tiers.

methodsData on type 2 diabetes, including mortality and disability-adjusted life years (DALYs) during 1990-2019, were obtained from the Global Burden of Disease Study 2019. We analysed mortality and DALY rates and the population attributable fraction (PAF) in various risk factors of type 2 diabetes by country income tiers.

resultsGlobally, the age-standardised death rate (ASDR) attributable to type 2 diabetes increased from 16.7 (15.7, 17.5)/100,000 person-years in 1990 to 18.5 (17.2, 19.7)/100,000 person-years in 2019. Similarly, age-standardised DALY rates increased from 628.3 (537.2, 730.9)/100,000 person-years to 801.5 (670.6, 954.4)/100,000 person-years during 1990-2019. Lower-middle-income countries reported the largest increase in the average annual growth of ASDR (1.3%) and an age-standardised DALY rate (1.6%) of type 2 diabetes. The key PAF attributing to type 2 diabetes deaths/DALYs was high BMI in countries of all income tiers. With the exception of BMI, while in low- and lower-middle-income countries, risk factors attributable to type 2 diabetes-related deaths and DALYs are mostly environment-related, the risk factors in high-income countries are mostly lifestyle-related. CONCLUSIONS/

interpretationType 2 diabetes disease burden increased globally, but low- and middle-income countries showed the highest growth rate. A high BMI level remained the key contributing factor in all income tiers, but environmental and lifestyle-related factors contributed differently across income tiers. DATA AVAILABILITY: To download the data used in these analyses, please visit the Global Health Data Exchange at http://ghdx.healthdata.org/gbd-2019 .

Indexed as

Diabetes Mellitus, Type 2Global Burden of DiseaseDeveloping CountriesGlobal HealthHumansQuality-Adjusted Life YearsRisk FactorsDALYsDeathPopulation attributable fractionType 2 diabetes mellitus

Identifiers

PMID35587275
PMCPMC9118183

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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.