Research report

Extreme temperatures and paediatric emergency department admissions Zhiwei Xu,1 Wenbiao Hu,2 Hong Su,3 Lyle R Turner,1 Xiaofang Ye,1,4 Jiajia Wang,1 Shilu Tong1 1

School of Public Health and Social Work & Institute of Health and Biomedical Innovation, Queensland University of Technology, Kelvin Grove, Queensland, Australia 2 School of Population Health, University of Queensland, Brisbane, Queensland, Australia 3 Department of Epidemiology and Health Statistics, School of Public Health, Anhui Medical University, Hefei, Anhui, China 4 Shanghai Meteorological Bureau, Shanghai, China Correspondence to Dr Shilu Tong, School of Public Health and Social Work & Institute of Health and Biomedical Innovation, Queensland University of Technology, Kelvin Grove, QLD 4059, Australia; [email protected] Received 9 April 2013 Revised 14 September 2013 Accepted 6 November 2013 Published Online First 23 November 2013

ABSTRACT Background Children are particularly vulnerable to the effects of extreme temperatures. Objective To examine the relationship between extreme temperatures and paediatric emergency department admissions (EDAs) in Brisbane, Australia, during 2003–2009. Methods A quasi-Poisson generalised linear model combined with a distributed lag non-linear model was used to examine the relationships between extreme temperatures and age-, gender- and cause-specific paediatric EDAs, while controlling for air pollution, relative humidity, day of the week, influenza epidemics, public holiday, season and long-term trends. The model residuals were checked to identify whether there was an added effect due to heat waves or cold spells. Results There were 131 249 EDAs among children during the study period. Both high (RR=1.27; 95% CI 1.12 to 1.44) and low (RR=1.81; 95% CI 1.66 to 1.97) temperatures were significantly associated with an increase in paediatric EDAs in Brisbane. Male children were more vulnerable to temperature effects. Children aged 0–4 years were more vulnerable to heat effects and children aged 10–14 years were more sensitive to both hot and cold effects. High temperatures had a significant impact on several paediatric diseases, including intestinal infectious diseases, respiratory diseases, endocrine, nutritional and metabolic diseases, nervous system diseases and chronic lower respiratory diseases. Low temperatures were significantly associated with intestinal infectious diseases, respiratory diseases and endocrine, nutritional and metabolic diseases. An added effect of heat waves on childhood chronic lower respiratory diseases was seen, but no added effect of cold spells was found. Conclusions As climate change continues, children are at particular risk of a variety of diseases which might be triggered by extremely high temperatures. This study suggests that preventing the effects of extreme temperature on children with respiratory diseases might reduce the number of EDAs.

INTRODUCTION

To cite: Xu Z, Hu W, Su H, et al. J Epidemiol Community Health 2014;68:304–311. 304

Climate change has been recognised as the biggest global threat to health in the 21st century.1 The average global surface temperature has increased, and the frequency and intensity of extreme weather events have also risen,2 3 posing a huge threat to human health and well-being. In particular, the adverse effects of extreme temperatures on morbidity have become a great public health concern.4 Previous studies of the impact of temperature on morbidity have focused mainly on adults, particularly the elderly.5 6 Children are particularly

vulnerable to environmental hazards,7–11 but limited studies have examined the relationship between temperature and morbidity among children.12 In previous studies, temperature was considered as a continuous risk factor, and the exposure–response relationship between temperature and specific paediatric morbidity was assessed. However, to date, no study has quantified the effects of extreme temperatures on a wide range of health outcomes among children. Some public health publications have emphasised that persistent extreme temperatures may increase the incidence of paediatric diseases. Heat waves (or cold spells) were more likely to be considered as a distinct event in the literature, and the excess morbidity due to heat waves (or cold spells) was calculated by comparing heat wave (or cold spell) days with non-heat-wave (or non-cold-spell) days.13–16 Some researchers have argued that the effects of heat waves and cold spells on human health might be due to the main effect of daily temperature fluctuations, and also the added effect of persistent extreme temperatures.17–19 To the best of our knowledge, no study has separately quantified the effects of daily temperatures and added the effects of persistent extreme temperatures on paediatric morbidity. This study examined three key questions: (i) what is the relationship between extreme temperatures and paediatric emergency department admissions (EDAs) in Brisbane, Australia? (ii) is there any added effect due to heat waves and cold spells? (iii) which subgroups of children are more sensitive to extreme temperatures?

METHODS Data collection Brisbane is the capital of Queensland, located on the east coast of Australia (27° 300 S, 153° 000 E). It has a subtropical climate, and generally experiences mild winters and hot summers, and thus the heat– health relationship in Brisbane needs particular research attention.20–22 Children aged 0–14 years account for 20% of the residential population in Brisbane.23 EDA data for the period 1 January 2003 to 31 December 2009 were obtained from Queensland Health. Before the data were collected, ethical approval was obtained from the human research ethics committee of Queensland University of Technology. Because the data were de-identified and aggregated, written consent was not needed. Data on EDAs were classified according to the International Classification of Disease, 10th version. The main paediatric diseases in Brisbane during 2003–2009 were analysed, including all-cause

Xu Z, et al. J Epidemiol Community Health 2014;68:304–311. doi:10.1136/jech-2013-202725

Research report diseases, intestinal infectious diseases (A00–A09), endocrine, nutritional and metabolic diseases (E00–E90), nervous system diseases (G00–G99), respiratory diseases ( J00–J99), acute upper respiratory infections ( J00–J06), chronic lower respiratory diseases ( J40–J47) (most of which were EDAs for childhood asthma), digestive system diseases (K00–K93) and genitourinary system diseases (N00–N99). Daily data on maximum and minimum temperatures and relative humidity in Brisbane for the same period were retrieved from the Australian Bureau of Meteorology. Daily data on average particulate matter ≤10 mm (PM10) (mg/m3) and 8 h maximum ozone (O3) ( ppb) were obtained from the Queensland Department of Environmental and Resources Management. The data were collected from two monitor stations in Brisbane, and then averaged.

Definitions of heat wave and cold spell To date, owing to variations in population characteristics and adaptation,21 24–26 there are no standard definitions for heat waves and cold spells. In this study, we combined intensity and duration of extreme temperatures to define both heat waves and cold spells: (1) intensity: the 4th (13.5°C) and 5th (13.8°C) centiles of daily mean temperature as the cold threshold, and the 95th (26.5°C) and 96th (26.7°C) centiles of the daily mean temperature as the hot threshold; (2) duration: a minimum of 2–4 consecutive days with temperatures below the cold threshold or above the hot threshold.

Statistical analyses Stage I: estimation of the main temperature effects on paediatric EDAs To quantify the main effect of temperature on paediatric EDAs, we used a quasi-Poisson generalised linear regression model combined with a distributed lag non-linear model (DLNM). Many studies have reported a lagged effect of temperature on morbidity.27 28 Further, the temperature–morbidity relationship has been found to be non-linear.29 Thus, we used the DLNM to examine both non-linear and lagged effects of temperature simultaneously.30 Previous studies have reported that there is no ‘best’ temperature indicator,31 32 and daily mean temperature was used in this study. A ‘natural cubic spline–natural cubic spline’ DLNM was used to examine the temperature effect using four degrees of freedom (df ) and 4 df for the temperature and lag dimensions, respectively. Previous research has shown that the cold effects on morbidity last for more than 7 days, while heat effects are relatively acute.4 We found that there was a negligible effect of temperature on paediatric EDAs for lags above 21 days, and we therefore used a maximum lag of 21 days to examine the effect of temperature. Several different covariates were included in the model. PM10, O3 and relative humidity were controlled for as potential confounders using a natural cubic spline with 4 df. Maximum lags of 21 days were also used for PM10, O3 and relative humidity. Seasonal and long-term trends were controlled for using a natural cubic spline with 8 df per year of data. Influenza epidemics and public holidays were also controlled for in the model. For the choice of df for all non-linear functions, we used a Poisson model and checked the Akaike information criterion and residuals. After the best df was chosen, we changed the Poisson model to a quasi-Poisson model. Day of week was controlled for as a categorical variable. When all the other parameters had been confirmed, we checked the temperature–EDAs plot and chose the reference temperature by visual inspection. We evaluated the relative risk

of paediatric EDAs associated with high temperature (≥26.5°C, 95th centile of mean temperature) relative to the reference temperature (24.0°C). Similarly, we evaluated the relative risk of paediatric EDAs associated with low temperature (≤13.8°C, 5th centile of mean temperature) relative to the reference temperature (24.0°C).

Stage II: examining the added effects of heat waves and cold spells Previous studies have reported that sustained periods of heat and cold produce an added effect on mortality which is independent of main temperature effects.18 19 33 We analysed the residuals of the stage I model to examine the possible added effects of heat waves and cold spells—that is, we took the residuals of the model in stage I and then performed the analysis for heat waves and cold spells. We assumed a maximum lag of 21 days for the delayed effects of heat waves and cold spells. EDAs for childhood asthma on extreme temperature days were compared with non-extreme temperature days. Effect estimates were obtained for both male and female children, different age groups (0–4, 5–9 and 10–14 years) and different EDA categories. To perform sensitivity analyses, we varied the df (8–15 per year) for time to control for both seasonal and long-term trend. We also varied the df (5–7) for temperature and humidity for the DLNM. All data analysis was conducted using the R statistical environment (V.2.12.2) with the ‘dlnm’ package used to fit the regression model.34

Table 1 Summary statistics for mean temperature, relative humidity, air pollution, total and cause-specific paediatric EDAs in Brisbane, Australia, during 2003–2009 Centile Variables

Mean

SD

Min

25

50

75

Max

Mean temperature (°C) Relative humidity (%) O3 (ppb) PM10 (mg/m3) Total morbidity Intestinal infectious diseases Endocrine, nutritional and metabolic diseases Nervous system diseases Respiratory diseases Acute upper respiratory infections Chronic lower respiratory diseases Digestive system diseases Genitourinary system diseases Total morbidity in children aged 0–4 years Total morbidity in children aged 5–9 years Total morbidity in children aged 10–14 years Total morbidity in male children Total morbidity in female children

20.6 57.3 22.3 16.0 51.4 8.7

4.1 16.0 7.2 10.1 15.8 5.1

9.0 5.0 5.0 4.4 3 0

17.3 49.0 18.0 11.7 44 5

20.9 58.0 21.0 14.5 53 8

23.8 67.0 26.0 17.9 61 11

34.2 98.0 60.0 355.2 108 57

1.2

1.1

0

0

1

2

7

1.3 20.0 5.6

1.2 9.5 3.3

0 0 0

0 13 3

1 20 5

2 26 8

7 53 19

5.5

3.4

0

3

5

7

24

3.4 2.2

2.0 1.5

0 0

2 1

3 2

5 3

12 8

33.5

11.2

1

27

34

41

68

9.3

4.0

1

6

9

12

27

8.7

3.9

1

6

8

11

60

28.9

9.6

1

24

29

35

85

22.5

7.9

1

18

23

27

50

EDA, emergency department admission; PM10, particular matter ≤10 mm.

Xu Z, et al. J Epidemiol Community Health 2014;68:304–311. doi:10.1136/jech-2013-202725

305

Research report RESULTS In total, there were 131 249 EDAs among children in the whole study period. Table 1 shows the summary statistics for mean temperature, relative humidity, air pollutants and total, cause-specific, age-specific and gender-specific paediatric EDAs. The average mean temperature was 20.6°C (range 9.0–34.2), and the average relative humidity was 57.3% (5.0%–98.0%). The average values of O3 and PM10 were 22.3 ppb (5.0–60.0) and 16.0 mg/m3 (4.4–355.2), respectively. The daily number of EDAs was greater among children aged 0–4 years (mean 33.5, SD 11.2) than those aged 5–9 years (mean 9.3, SD 4.0) and 10–14 years (mean 8.7, SD 3.9). The daily number of EDAs was greater among male children (mean 28.9, SD 9.6) than female children (mean 22.5, SD 7.9). Figure 1A presents the decomposed distribution of paediatric EDAs, showing a strong seasonal trend. The daily distributions of PM10, O3 and relative humidity are presented in figure 1B–D.

Figure 2 shows the cumulative effects of temperature on total, age- and gender-specific paediatric EDAs, and demonstrates that paediatric EDAs increased during both high and low temperatures. Hot and cold effects were much greater among male children than female children. For age-specific paediatric EDAs, it can be seen that children aged 0–4 years were vulnerable to heat effects, and those aged 10–14 years were sensitive to both hot and cold effects. Figure 3 shows the effects of high temperature (95th centile (26.5°C) and low temperature (5th centile (13.8°C) relative to the threshold temperature (24.0°C)) on total paediatric EDAs according to the lags. Both hot and cold effects persisted, and cold effects were relatively more acute. Table 2 shows the cumulative effects of both high (26.5°C) and low (13.8°C) temperatures on total and cause-specific paediatric morbidity at lags of 0–1, 0–13 and 0–21 days. High

Figure 1 (A) The daily distribution of paediatric emergency department admissions in Brisbane, from 2003 to 2009. (B) The daily distribution of particular matter ≤10 mm (PM10) in Brisbane, from 2003 to 2009. (C) The daily distribution of ozone (O3) in Brisbane, from 2003 to 2009. (D) The daily distribution of relative humidity in Brisbane, from 2003 to 2009. 306

Xu Z, et al. J Epidemiol Community Health 2014;68:304–311. doi:10.1136/jech-2013-202725

Research report

Figure 2 The overall effect of temperature on paediatric emergency department admissions (EDAs).

temperatures were statistically significantly associated with the following paediatric diseases: intestinal infectious diseases, respiratory diseases, endocrine, nutritional and metabolic diseases, nervous system diseases and chronic lower respiratory diseases. Low temperatures were significantly associated with intestinal infectious diseases, respiratory diseases and endocrine, nutritional and metabolic diseases. Table 3 shows the daily excess EDAs for total and causespecific paediatric EDAs on heat wave (or cold spell) days as opposed to non-heat wave (or non-cold spell) days. The number of heat waves and cold spells is shown in table 4. Using heat wave definitions of a minimum of 2 days’ temperature sustained over the 95th or 96th centile, we found there was no significant increase in total and cause-specific EDAs in heat waves. However, using heat wave definitions of a minimum of 3 days’ temperature sustained over the 95th or 96th centile, we found

there were significant increases in EDAs for chronic lower respiratory diseases in heat waves. There was no significant increase in paediatric EDAs during cold spells. To conduct a sensitivity analysis, we changed the df (8–15 per year) for time to control for season. We also varied the df (5–7) for temperature and relative humidity, and found that the effects of high (26.5°C) and low (13.8°C) temperatures decreased slightly when the df for time, temperature or relative humidity was increased, but were still significant.

DISCUSSION This study yielded several notable findings. Both high and low temperatures had significant impacts on paediatric EDAs. Male children were more vulnerable to temperature effects. Children aged 0–4 years were more vulnerable to heat effects and children aged 10–14 years were more sensitive to both hot and cold

Figure 3 The lagged effects of temperature on paediatric emergency department admissions (EDAs). Xu Z, et al. J Epidemiol Community Health 2014;68:304–311. doi:10.1136/jech-2013-202725

307

Research report Table 2 Cumulative effect of high and low temperatures on cause-specific paediatric EDAs, with 95th centile (26.5°C) and 5th centile (13.8°C) of temperature relative to reference temperature (24°C) Heat effect (RR (95% CI))

Cold effect (RR (95% CI))

Diseases

Lag 0–1

Lag 0–13

Lag 0–21

Lag 0–1

Lag 0–13

Lag 0–21

Total paediatric morbidity Intestinal infectious diseases Endocrine, nutritional and metabolic diseases Nervous system diseases Respiratory diseases Acute upper respiratory infections Chronic lower respiratory diseases Digestive system diseases Genitourinary system diseases

1.07 (1.04 to 1.10)* 1.06 (1.01 to 1.12)* 1.01 (0.84 to 1.23)

1.34 (1.24 to 1.46)* 1.18 (0.98 to 1.43) 1.34 (0.78 to 2.31)

1.27 (1.12 to 1.44)* 0.94 (0.70 to 1.27) 1.80 (1.10 to 2.57)*

1.11 (1.05 to 1.16)* 0.90 (0.80 to 1.01) 0.89 (0.65 to 1.22)

1.68 (1.57 to 1.78)* 1.43 (1.23 to 1.66)* 1.94 (1.28 to 2.93)*

1.81 (1.66 to 1.97)* 1.74 (1.41 to 2.14)* 2.05 (1.16 to 3.62)*

1.06 1.11 1.08 0.98

1.04 1.67 1.12 1.13

1.11 (0.52 1.50 (1.21 1.15 (0.68 1.09 (1.01

1.14 (0.85 1.31 (1.22 1.23 (0.82 0.96 (0.83

1.37 (0.94 2.80 (2.52 1.10 (0.99 1.05 (0.77

1.54 (0.92 2.67 (2.31 1.83 (0.77 0.80 (0.52

(1.01 (1.05 (0.88 (0.91

to to to to

1.13)* 1.16)* 1.26) 1.05)

1.07 (0.98 to 1.17) 0.91 (0.82 to 1.02)

(0.64 (1.46 (0.75 (1.02

to to to to

1.69) 1.92)* 1.78) 1.38)*

0.99 (0.84 to 1.18) 0.99 (0.77 to 1.29)

to to to to

2.38) 1.86)* 1.71) 1.46)*

0.94 (0.74 to 1.21) 0.92 (0.63 to 1.35)

to to to to

1.53) 1.42)* 1.50) 1.12)

1.02 (0.84 to 1.23) 0.95 (0.75 to 1.20)

to to to to

2.00) 3.12)* 1.25) 1.43)

1.08 (0.73 to 1.60) 1.04 (0.64 to 1.68)

to to to to

2.59) 3.08)* 4.05) 1.23)

1.05 (0.61 to 1.79) 0.94 (0.48 to 1.84)

*p

Extreme temperatures and paediatric emergency department admissions.

Children are particularly vulnerable to the effects of extreme temperatures...
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