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

作者：Dan Liang, Li Wang, Shuang Liu, Shanglin Li, Xing Zhou, Yun Xiao, Panpan Zhong, Yanxi Chen, Changyi Wang, Shan Xu, Juan Su, Zhen Luo, Changwen Ke, Ying‐Si Lai · 发表于：Nutrients · 年份：2024 · DOI：10.3390/nu16183217 · 被引用次数：32 · 研究领域：Climate Change and Health Impacts、Child Nutrition and Water Access、Viral gastroenteritis research and epidemiology

BACKGROUND: Diarrheal 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. OBJECTIVE: This 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. METHODS: The 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. RESULTS: Globally, 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,...