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Frontiers of Environmental Science & Engineering

ISSN 2095-2201

ISSN 2095-221X(Online)

CN 10-1013/X

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2018 Impact Factor: 3.883

Front. Environ. Sci. Eng.    2023, Vol. 17 Issue (9) : 105    https://doi.org/10.1007/s11783-023-1705-1
RESEARCH ARTICLE
Evaluating the short-term effect of ambient temperature on non-fatal outdoor falls and road traffic injuries among children and adolescents in China: a time-stratified case-crossover study
Hao Zheng1, Jian Cheng2,3, Hung Chak Ho4, Baoli Zhu1, Zhen Ding1, Wencong Du5, Xin Wang6, Yang Yu1, Juan Fei1, Zhiwei Xu7, Jinyi Zhou5(), Jie Yang6()
1. Department of Environmental Health, Jiangsu Provincial Center for Disease Control and Prevention, Nanjing 210009, China
2. Department of Epidemiology and Biostatistics, School of Public Health, Anhui Medical University, Hefei 230032, China
3. Anhui Province Key Laboratory of Major Autoimmune Disease, Hefei 230032, China
4. Department of Anaesthesiology, School of Clinical Medicine, The University of Hong Kong, Hong Kong 999077, China
5. Department of Noncommunicable Diseases, Jiangsu Provincial Center for Disease Control and Prevention, Nanjing 210009, China
6. Department of Child and Adolescent Health Promotion, Jiangsu Provincial Center for Disease Control and Prevention, Nanjing 210009, China
7. School of Public Health, University of Queensland, Queensland 4006, Australia
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Abstract

● A study assessing the temperature-injury relationship was conducted among students.

● The maximum risks of injury appeared at moderate temperatures.

● The temperature effect on outdoor falls was greater in older students.

Although studies have suggested that non-optimal temperatures may increase the risk of injury, epidemiological studies focusing on the association between temperature and non-fatal injury among children and adolescents are limited. Therefore, we investigated the short-term effect of ambient temperature on non-fatal falls and road traffic injuries (RTIs) among students across Jiangsu Province, China. Meteorological data and records of non-fatal outdoor injuries due to falls and RTIs among students aged 6–17 were collected during 2018–2020. We performed a time-stratified case-crossover analysis with a distributed lag nonlinear model to examine the effect of ambient temperature on the risk of injury. Individual meteorological exposure was estimated based on the address of the selected school. We also performed stratified analyses by sex, age, and area. A total of 57322 and 5455 cases of falls and RTIs were collected, respectively. We observed inverted U-shaped curves for temperature-injury associations, with maximum risk temperatures at 18 °C (48th of daily mean temperature distribution) for falls and 22 °C (67th of daily mean temperature distribution) for RTIs. The corresponding odds ratios (95% confidence intervals) were 2.193 (2.011, 2.391) and 3.038 (1.988, 4.644) for falls and RTIs, respectively. Notably, there was a significant age-dependent trend in which the temperature effect on falls was greater in older students (P-trend < 0.05). This study suggests a significant association between ambient temperature and students’ outdoor falls and RTIs. Our findings may help advance tailored strategies to reduce the incidence of outdoor falls and RTIs in children and adolescents.

Keywords Ambient temperature      Fall      Road traffic injury      Student      China     
Corresponding Author(s): Jinyi Zhou,Jie Yang   
Issue Date: 31 March 2023
 Cite this article:   
Hao Zheng,Jian Cheng,Hung Chak Ho, et al. Evaluating the short-term effect of ambient temperature on non-fatal outdoor falls and road traffic injuries among children and adolescents in China: a time-stratified case-crossover study[J]. Front. Environ. Sci. Eng., 2023, 17(9): 105.
 URL:  
https://academic.hep.com.cn/fese/EN/10.1007/s11783-023-1705-1
https://academic.hep.com.cn/fese/EN/Y2023/V17/I9/105
Variables Categories Falls RTIs
Total 57322 (100%) 5455 (100%)
Sex Male 38303 (66.8%) 3467 (63.5%)
Female 19019 (33.2%) 1988 (36.5%)
Age group (years) 6–8 14434 (25.2%) 992 (18.2%)
9–11 15765 (27.5%) 1136 (20.8%)
12–14 15473 (27.0%) 1910 (35.0%)
15–17 11650 (20.3%) 1417 (26.0%)
Area Urban 31481 (54.9%) 2285 (41.9%)
Rural 25841 (45.1%) 3170 (58.1%)
Tab.1  Descriptive statistics for the cases of falls and RTIs in students in Jiangsu Province, China, 2018–2020
Injuries Variables Min P25 P50 P75 Max Mean SD
Falls (on case days) Mean temperature (°C) 0.2 12.9 18.4 23.2 32.9 17.6 7.1
Relative humidity (%) 20.5 61.4 69.3 78.6 100.0 69.4 13.2
Atmospheric pressure (hPa) 993.3 1010.1 1016.6 1022.3 1041.1 1016.5 8.6
Rainfall (mm) 0 0 0 0 10.0 0.1 0.3
Wind speed (m/s) 0.2 1.3 1.7 2.2 8.3 1.8 0.7
AQI 14.0 47.0 61.0 81.0 292.0 67.3 28.5
Falls (on control days) Mean temperature (°C) 0.1 12.1 18.3 23.3 32.9 17.4 7.3
Relative humidity (%) 20.5 62.5 71.4 81.9 100.0 71.6 14.0
Atmospheric pressure (hPa) 993.3 1009.8 1016.3 1022.3 1040.8 1016.3 8.7
Rainfall (mm) 0 0 0 0 10.0 0.1 0.4
Wind speed (m/s) 0.1 1.3 1.7 2.2 10.5 1.8 0.7
AQI 10.0 45.0 58.0 79.0 321.0 64.8 29.3
RTIs (on case days) Mean temperature (°C) 0.3 12.0 17.9 23.0 32.2 17.1 7.4
Relative humidity (%) 20.5 59.6 69.3 79.5 100.0 69.4 14.6
Atmospheric pressure (hPa) 993.3 1008.4 1015.5 1021.5 1040.3 1015.2 8.8
Rainfall (mm) 0 0 0 0 5.2 0.1 0.4
Wind speed (m/s) 0.3 1.3 1.7 2.3 7.7 1.8 0.8
AQI 14.0 46.0 60.0 80.0 321.0 66.6 30.1
RTIs (on control days) Mean temperature (°C) 0.3 11.5 17.7 23.2 32.6 16.9 7.6
Relative humidity (%) 20.5 60.3 70.1 80.2 100.0 69.8 14.2
Atmospheric pressure (hPa) 993.3 1008.2 1015.3 1021.6 1041.1 1015.2 9.1
Rainfall (mm) 0 0 0 0 10.0 0.1 0.4
Wind speed (m/s) 0.3 1.3 1.7 2.3 11.1 1.8 0.8
AQI 10.0 46.0 60.0 80.0 321.0 67.1 31.8
Tab.2  Summary statistics of daily meteorological variables and AQI on case days and control days for falls and RTIs in Jiangsu Province, China, 2018–2020
Fig.1  Overall lag-cumulative (0–7 days) exposure-response associations for falls (a) and RTIs (b). The dashed vertical line represents the minimum risk temperature, and the dotted vertical line represents the maximum risk temperature. Shaded areas represent 95% confidence intervals.
Variables Categories Falls RTIs
MinRT (%) MaxRT (%) OR (95% CI) P value MinRT (%) MaxRT (%) OR (95% CI) P value
Overall 29 (99) 18 (48) 2.193 (2.011, 2.391) 2 (1) 22 (67) 3.038 (1.988, 4.644)
Sex
Male 29 (99) 18 (48) 2.211 (1.990, 2.458) 0.815# 2 (1) 22 (67) 2.852 (1.666, 4.885) 0.724#
Female 29 (99) 19 (54) 2.164 (1.871, 2.504) 2 (1) 22 (68) 3.340 (1.673, 6.670)
Age groups (years)
6–8 29 (99) 20 (53) 1.523 (1.310, 1.772) < 0.0001* 2 (1) 30 (99) 6.996 (1.926, 25.406) 0.818*
9–11 29 (99) 19 (50) 1.669 (1.426, 1.953) 2 (1) 17 (46) 2.482 (1.043, 5.911)
12–14 29 (99) 17 (45) 3.235 (2.707, 3.865) 2 (1) 23 (76) 1.953 (0.954, 3.998)
15–17 29 (99) 18 (54) 4.062 (3.303, 4.996) 2 (1) 21 (61) 4.766 (2.026, 11.215)
Area
Urban 29 (99) 19 (53) 2.133 (1.908, 2.385) 0.470# 2 (1) 21 (63) 3.885 (2.048, 7.366) 0.326#
Rural 29 (99) 18 (48) 2.272 (1.995, 2.588) 2 (1) 22 (67) 2.538 (1.451, 4.439)
Tab.3  ORs and 95% CIs for falls and RITs and the corresponding subgroups in students in Jiangsu Province, China, 2018–2020
Fig.2  Overall lag-cumulative ORs with 95% CIs for falls (a) and RTIs (b) in subgroup analyses by sex, age group, and area.
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