The effect of temperature on infectious diarrhea disease: A systematic review

Abstract

This study aimed to ascertain the delayed effects of various exposure temperatures on infectious diarrhea. We performed a Bayesian random-effects network meta-analysis to calculate relative risks (RR) with 95 % confidence intervals (95 % CI). The heterogeneity was analyzed by subgroup analysis. There were 25 cross-sectional studies totaling 6858735 patients included in this analysis, with 12 articles each investigating the effects of both hyperthermia and hypothermia. Results revealed that both high temperature (RRsingle = 1.22, 95%CI:1.04-1.44, RRcum = 2.96, 95%CI:1.60-5.48, P < 0.05) and low temperature (RRsingle = 1.17, 95%CI:1.02-1.37, RRcum = 2.19, 95%CI:1.33-3.64, P < 0.05) significantly increased the risk of infectious diarrhea, while high temperature caused greater. As-sociations with strengthening in bacillary dysentery were found for high temperatures (RRcum = 2.03, 95%CI:1.41-3.01, P < 0.05; RRsingle = 1.17, 95%CI:0.90-1.62, P > 0.05), while the statistical significance of low temperatures in lowering bacterial dysentery had vanished. This investigation examined that high temperature and low temperature were the conditions that posed the greatest risk for infectious diarrhea. This research offers fresh perspectives on preventing infectious diarrhea and will hopefully enlighten future studies on the impact of temperature management on infectious diarrhea.

Keywords: Bacillary dysentery; Infectious diarrhea; Network-meta-analysis; Other infectious diarrhea; Temperature.

Fig. 1

Flow chart of study search progress.

Fig. 2

Network meta-analysis maps of the studies examining the effect of temperature on infectious diarrhea (A) Network diagram of the single-day effect of temperature on infectious diarrhea (B) Network diagram of the cumulative effect of temperature on infectious diarrhea. High: ambient temperature above the 75th percentile; Low: ambient temperature below the 25th percentile; P50: the percentile for ambient temperature; LRR: the minimal risk temperature determined by a time series analysis of the examined diseases and ambient temperature; Threshold: the temperature above which the risk of ID increases noticeably.

Fig. 3

The rank probability of temperatures using SUCRA-score in networks A, and B. (A)Ranking of the single-day effect of temperature on ID (B)Ranking of the cumulative effect of temperature on ID.

Fig. 4

Contour-enhanced funnel plot comparing the effect of temperature on infectious diarrhea (A): Single-day effect (B): Single-day effect combined with "cut-and-complement method" (C): Cumulative effect (B): Cumulative effect combined with "cut-and-complement method".