Evidence map›Paper›PMID 39339819›Full record

ArticleNutrients2024

Global Incidence of Diarrheal Diseases-An Update Using an Interpretable Predictive Model Based on XGBoost and SHAP: A Systematic Analysis.

Dan Liang, Li Wang, Shuang Liu, Shanglin Li, Xing Zhou, Yun Xiao, Panpan Zhong, Yanxi Chen, Changyi Wang, Shan Xu and 4 more

Abstract read
In one paragraph

Article in Nutrients, 2024. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 24 papers, 2 of them syntheses that pooled it.

0numbers the graph read from it
0cells of the map it votes in
24citing papers in PubMed, 2 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

24 citing papers in PubMed, 2 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

14 authors.

Dan LiangDepartment of Immunology and Microbiology, College of Life Science and Technology, Jinan University, Guangzhou 510632, China.
Li WangDepartment of Medical Statistics, School of Public Health, Sun Yat-sen University, Guangzhou 510275, China.
Shuang LiuDepartment of Immunology and Microbiology, College of Life Science and Technology, Jinan University, Guangzhou 510632, China.
Shanglin LiDepartment of Microbiology and Immunology, Basic Medicine College, Jinan University, Guangzhou 510632, China.
Xing ZhouDepartment of Immunology and Microbiology, College of Life Science and Technology, Jinan University, Guangzhou 510632, China.
Yun XiaoSchool of Public Health, Southern Medical University, Guangzhou 510515, China.
Panpan ZhongDepartment of Immunology and Microbiology, College of Life Science and Technology, Jinan University, Guangzhou 510632, China.
Yanxi ChenDepartment of Immunology and Microbiology, College of Life Science and Technology, Jinan University, Guangzhou 510632, China.
Changyi WangDepartment of Cardiovascular and Cerebrovascular and Diabetes Prevention and Treatment, Shenzhen Nanshan Center for Chronic Disease Control, Shenzhen 518000, China.
Shan XuDepartment of Cardiovascular and Cerebrovascular and Diabetes Prevention and Treatment, Shenzhen Nanshan Center for Chronic Disease Control, Shenzhen 518000, China.
Juan SuGuangdong Provincial Key Laboratory for Emergency Detection and Research on Pathogen of Emerging Infectious Disease, Guangdong Provincial Center for Disease Control and Prevention, Guangdong Workstation for Emerging Infectious Disease Control and Prevention, Guangzhou 511430, China.
Zhen LuoDepartment of Immunology and Microbiology, College of Life Science and Technology, Jinan University, Guangzhou 510632, China.ORCID 0000-0002-1142-2845
Changwen KeDepartment of Medical Statistics, School of Public Health, Sun Yat-sen University, Guangzhou 510275, China.ORCID 0000-0002-0341-292X
Yingsi LaiDepartment of Medical Statistics, School of Public Health, Sun Yat-sen University, Guangzhou 510275, China.ORCID 0000-0003-4324-5465

Funding

Guangdong Provincial Science and Technology Project 2022B1111020005Guangdong Special Support Program (Leading Talents in Science and Technology In-novation) 2023A001, Contract Number: 0620220104National Key Research and Development Program of China 2023YFC3041600Science and Technology Project of Nanshan District NS2021108
6 · The paper itself

Abstract

backgroundDiarrheal disease remains a significant public health issue, particularly affecting young children and older adults. Despite efforts to control and prevent these diseases, their incidence continues to be a global concern. Understanding the trends in diarrhea incidence and the factors influencing these trends is crucial for developing effective public health strategies.

objectiveThis study aimed to explore the temporal trends in diarrhea incidence and associated factors from 1990 to 2019 and to project the incidence for the period 2020-2040 at global, regional, and national levels. We aimed to identify key factors influencing these trends to inform future prevention and control strategies.

methodsThe eXtreme Gradient Boosting (XGBoost) model was used to predict the incidence from 2020 to 2040 based on demographic, meteorological, water sanitation, and sanitation and hygiene indicators. SHapley Additive exPlanations (SHAP) value was performed to explain the impact of variables in the model on the incidence. Estimated annual percentage change (EAPC) was calculated to assess the temporal trends of age-standardized incidence rates (ASIRs) from 1990 to 2019 and from 2020 to 2040.

resultsGlobally, both incident cases and ASIRs of diarrhea increased between 2010 and 2019. The incident cases are expected to rise from 2020 to 2040, while the ASIRs and incidence rates are predicted to slightly decrease. During the observed (1990-2019) and predicted (2020-2040) periods, adults aged 60 years and above exhibited an upward trend in incidence rate as age increased, while children aged < 5 years consistently had the highest incident cases. The SHAP framework was applied to explain the model predictions. We identified several risk factors associated with an increased incidence of diarrhea, including age over 60 years, yearly precipitation exceeding 3000 mm, temperature above 20 °C for both maximum and minimum values, and vapor pressure deficit over 1500 Pa. A decreased incidence rate was associated with relative humidity over 60%, wind speed over 4 m/s, and populations with above 80% using safely managed drinking water services and over 40% using safely managed sanitation services.

conclusionsDiarrheal diseases are still serious public health concerns, with predicted increases in the incident cases despite decreasing ASIRs globally. Children aged < 5 years remain highly susceptible to diarrheal diseases, yet the incidence rate in the older adults aged 60 plus years still warrants additional attention. Additionally, more targeted efforts to improve access to safe drinking water and sanitation services are crucial for reducing the incidence of diarrheal diseases globally.

Indexed as

DiarrheaGlobal HealthChild, PreschoolFemaleForecastingHumansHygieneIncidenceMaleRisk FactorsSanitationdiarrheal diseaseepidemiologyforecastingglobal burden of diseaseincidenceSHAPXGBoost

Identifiers

PMID39339819
PMCPMC11434730

What OpenQuestion holds

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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.