Correlations of meteorological factors and air pollutants with incidence of hand-foot-and-mouth disease in Lianyungang City
- VernacularTitle:连云港市气象因素和空气污染物与手足口病发病的关联
- Author:
Mengdie XU
1
;
Li YIN
1
;
Furong LYU
1
;
Lei XU
1
;
Qiong TANG
2
;
Haipeng LI
1
Author Information
- Publication Type:Investigation
- Keywords: hand-foot-and-mouth disease; meteorological factor; air pollutant; distributed lag non-linear model; cumulative risk
- From: Journal of Environmental and Occupational Medicine 2026;43(1):51-57
- CountryChina
- Language:Chinese
- Abstract: Background The moderation role of environmental factors in the spread of hand-foot-and-mouth disease (HFMD) has attracted much attention, but the existing conclusions are inconsistent. For example, some scholars believe that high temperature, high humidity, and high concentrations of fine particulate matter (PM2.5) and nitrogen dioxide (NO2) increase the risk of HFMD, but other scholars have reached the opposite conclusion, or believe that there is no significant relationship. Objective Based on distributed lag nonlinear model (DLNM), to investigate the relationship between the incidence of HFMD and meteorological and air pollutant variables in Lianyungang City, and to provide scientific basis for early warning. Methods Daily data of meteorological factors and air pollutants in Lianyungang City from 2021 to 2024 were retrieved. Meteorological factors included average daily temperature, average wind speed, average air pressure, and relative humidity. Air pollutant indicators included PM2.5, inhalable particulate matter (PM10), carbon monoxide (CO), sulfur dioxide (SO2), NO2, and ozone (O3). Spearman correlation analysis was used to analyze their correlations with HFMD, and the R package (version 4.3.1) dlnm was used to construct a DLNM model. Results During the study period, a total of 10503 cases were reported, with a male to female ratio of 1.47∶1 and the highest proportion of scattered children (49.97%). The Spearman correlation analysis results showed that daily average temperature (r=0.40), relative humidity (r=0.17) and O3 (r=0.14) were positively correlated with the incidence of HFMD (all Ps<0.01), while average air pressure (r=−0.34), PM2.5 (r=−0.24), PM10 (r=−0.24), CO (r=−0.22), and NO2 (r=−0.06) were negatively correlated with it (all Ps<0.05). There was no statistical relationship of SO2 and average wind speed with the incidence of HFMD (both Ps>0.05). The cumulative risk effect was greatest when the daily average temperature was 28.50 ℃ (CRR=4.63, 95%CI: 2.68, 8.01). The average wind speed below 0.50 m·s−1 and in the range of 2.50-3.50 m·s−1 showed an acute risk effect, and low pressure (below 1016.00 hPa) could immediately increase the risk of the disease. The cumulative risk effect was greatest when the relative humidity was 100% (CRR=3.16, 95%CI: 1.77, 5.65). The greatest cumulative protective effects of PM2.5 and PM10 were present at concentrations of 158.00 μg·m−3 (CRR=0.12, 95%CI: 0.01, 0.99) and 561.50 μg·m−3 (CRR=0.01, 95%CI: 0.01, 0.99) respectively. The protective effect of CO was the strongest at the highest concentration (67.00 μg·m−3) (RR=0.67, 95%CI: 0.34, 0.64). The cumulative protective effects of SO2 and NO2 were both most significant at the concentration of 0.50 μg·m−3. Low concentrations of O3 (below 48.00 μg·m−3) showed a risk effect, and the single-day protective effect was significant when the concentration was 141.00 μg·m−3. Conclusion There is a nonlinear and hysteretic relationship between environmental factors and the incidence of HFMD. A rational and efficient early warning and prevention and control system can be constructed accordingly.
