Associations between air change rate of the child s bedroom during night and childhood asthma in Shanghai, China: A case-control study Wei Liu 1, *, Chen Huang 1, Xueying Wang 1, Jiao Cai 1, Li Shen 2, Zhijun Zou 1, Jing Chang 1, 3, Xiaoyang Wei 1, Haidong Wang 1, Yuexia Sun 4, Jan Sundell 1, 5 1 University of Shanghai for Science and Technology, Shanghai, China 2 R&B Technology (Shanghai) Company Limited, Shanghai, China 3 Shandong Jiaotong University, Jinan, China 4 Tianjin University, Tianjin, China 5 Tsinghua University, Beijing, China * Corresponding email: lsc198708@hotmail.com; liuw@st.usst.edu.cn SUMMARY We conducted a case-control study regarding associations between household environment and childhood asthma among children 5-10 years-old in Shanghai during 2013-2014. In this paper, we estimated air change rate (ACR) of the child s bedroom during mid-night (00:00-06:00), and investigated its association with the risk of childhood asthma. We successfully calculated the ACR in 369 residences. Herein 147 and 222 residences were from children with (cases) and without (controls) lifetime-ever asthma, respectively. The overall averaged ACR was 1.69 (range: 0.11-16.41) ach. The bedrooms inspected in winter had significantly lower ACR than those bedrooms inspected in summer (p-value = 0.043) and autumn (p-value = 0.006). Although none significant differences were found in the averaged ACRs among cases and controls groups, higher quartiles of ACR could be associated with lower risk of being a case. Our findings indicates household ventilation status during winter should be improved, these improvement may decrease the risk of childhood asthma. PRACTICAL IMPLICATIONS During cold spring and winter, most of the child s bedrooms in Shanghai could have low air change rate, and thus had bad indoor air quality during mid-night when the children deeply sleep. Therefore household ventilation status in spring and winter should be pay more attention to greatly improved. The improvement of household ventilation seemingly could be benefit in enhancing childhood respiratory health. KEYWORDS Residential ventilation; Childhood asthma; Carbon dioxide; Case-control study; Shanghai 1 INTRODUCTION Childhood prevalence of asthma has greatly increased in China (Zhang et al., 2013). In Shanghai, prevalence of asthma has increased from 2.1% in 1990 to 10.2% in 2011 among 3-7 year-olds children (Huang et al., 2015). Changes in the indoor environment of the residence were speculated to be strongly associated with the rapid increases in the childhood asthma 1
prevalence (Beasley et al., 2015; Diette et al., 2007). Household ventilation could effectively reduce indoor air pollution and thus improve the occupant s health (Bornehag et al., 2005; Daisey et al., 2003; Godish and Spengler, 1996; Mi et al., 2006; Nafstad et al., 1999; Sundell et al., 2011; Wargocki et al., 2002). Whereas indoor ventilation probably have been worse along with the requirement of building energy-saving (Beköet al., 2010; Dimitroulopoulou, 2012; Liu et al., 2014; Sundell et al., 2011). For most residences without mechanical ventilation, natural ventilation via opening windows and/or doors is a sole method to translate indoor air pollutants to outside and improve indoor air quality (IAQ) of the residence (Bornehag et al., 2005; Persily et al., 2016; Sundell et al., 2011). Many studies have been conducted to evaluate natural ventilation status of the residence and its associations with childhood asthma (Bornehag et al., 2005; Mi et al., 2006; Wargocki et al., 2002). However, few similar studies were accomplished in China (Liu et al., 2014; Wei et al., 2011). Therefore, in the present study, according to the data from on-site inspection in the phase two (case-control study) of the China, Children, Homes, Health (CCHH) study in Shanghai, China, we aims to report the status of air change rate in the child s bedroom during night (00:00-06:00), and investigate its association with childhood asthma. We suspected that the air change rate probably is associated with the increased risk of asthma in childhood. 2 METHODS Phase two of the CCHH study is a case-control study, which was nested on a large-scale crosssectional questionnaire-based study on associations of home environment and family lifestyles habits with asthma, allergies, and airway diseases in childhood (Zhang et al., 2013). During April 2011-April 2012, we conducted the cross-sectional study in 88 kindergartens form six districts of Shanghai and collected 16,948 valid questionnaires from parents/guardians of 1-8 years-old children (Huang et al., 2015). Herein a total of 1,682 children from the pilot survey in the Yang-Pu district, were excluded in the analyses for associations of home environment with childhood health by data in this phase, but these children were included in the selection of the inspected residences in the case-control study. From March 2013 to December 2014, we contacted those parents who agreed to cooperate with home inspection. We finally measured indoor air quality on-site in 454 residences. Herein 186 residences were for children with lifetime-ever history of doctor-diagnosed asthma (Cases) and 268 were for children without asthma (Controls). These residences were not changed or redecorated after the cross-sectional study. All participants consented for themselves and for their preschool children for whom they responded to questionnaires, and voluntarily responded to the survey. The questionnaire and detailed proposal for the CCHH study were approved by the ethical committee in the School of Public Health, Fudan University in Shanghai, China. During home inspection, the concentration of carbon dioxide (CO2), as well as air temperature and relative humidity, continuously measured 24 hours (one value per 10 minutes) in the child s bedroom, living room, and ambient outdoor by HUMLOG20 (E+E Inc., Austria; accuracy: ± 50 ppm). The instrument was checked and corrected every month during the home inspection. To obtain the common status of indoor ventilation status, we asked family members to keep their normal lifestyle behaviors during home inspection. We also collected data with respect to 2
dwelling characteristics mainly investigated by the inspector, and data with regard to family lifestyle habits mainly reported by the occupant. A previous article provided more information about the case-control study in Shanghai and about our home inspection (Huang et al., 2016). We calculated air change rate (N, ach) of the child s bedroom according to the CO2-track buildup and steady state method proposed by Stavova et al. (2011). This method was based on the mass-balance law and the equation could be expressed as: C CO2 = t V zone [ Q CO2 N V zone (C 1 C out )] (1) Herein, C CO2 is the unit increase of indoor CO2 concentration (m 3 /m 3 ) in time interval (Δt, s); C1 is the indoor CO2 concentration (m 3 /m 3 ) measured at the beginning of the time interval Δt; Cout is the outdoor CO2 concentration (m 3 /m 3 ); Vzone is the interior volume of the inspected room (m 3 ); Q CO2 is summation of the CO2 generation rate for persons existed in the inspected room (ml/s); is the air change rate (ach). Herein Q CO2 could be estimated via the equation proposed by Persily (1997) and updated by Qi et al. (2014): Q CO2 = 0.201 RQ M H0.725 W 0.425 21 (0.23 RQ+0.77) (2) Herein, RQ is respiratory quotient (dimensionless, RQ = 0.83 for light or sedentary activities of the average adult); M is the metabolic rate (W/m 2 ) and approximately equals to 40 W/m 2 during sleeping (ASHRAE, 2013); H is height (m) of the persons sleep in the child s bedroom; W is weight (kg) of the persons sleep in the child s bedroom. According to the measured data, we found that it is stable for most of the indoor concentration of CO2 during mid-night (00:00-06:00) when family members deeply sleep and ambient CO2 concentration. Therefore, in the present study, we considered that C CO2 equals to zero and Cout equals to 410 ppm (10-6 ), which approximately equals to the averaged value of ambient CO2 concentration in all inspected residences. C1 is the averaged concentration of the child s bedroom during mid-night. Then, we combined the equation (1) and equation (2), as well as put the constant values in the equations, thus the air change rate (N) could be calculated as: N = 0.331 H0.725 W 0.425 (3) V zone (C 1 410) 10 6 We used Statistical Product and Service Solutions (SPSS) version 17.0 (SPSS Ltd., USA) to perform the statistical analyses. Origin 8.0 (OriginLab Corp., USA) were used to conduct the figures. Student s t test was used to compare the difference of air change rate among the residences inspected in different seasons (Spring: March to May; Summer: June to August; Autumn: September to November; and Winter: December to February), as well as between cases and controls among all inspected residences and stratified by the inspected seasons. We 3
stratified the sampled children by the four quartiles of air change rate, and consistently took the children in the first quartiles as reference, to compare the risk of childhood asthma among children in second, third, and forth quartiles. Pearson s chi-square test was applied to compare differences in the prevalences of cases in different quartiles of air change rate. Logistic regression model was used to analyze the associations between the calculated air change rate of the child s bedroom during night and the prevalence of asthma in childhood. We indicated these associations by odds ratio (OR) with 95% confidence interval (CI). Significance in all statistical analyses was set at p-value < 0.05. 3 RESULTS Among the inspected 454 residences, a total of 369 (81.3%) residences were successfully calculated the air change rate during mid-night. Herein 147 (39.8%) residences were from children with lifetime-ever history of asthma (cases) and 222 (60.2%) residences from children without asthma (controls). Ages of these children were ranged 5-10 (mean ± SD: 6.96 ± 1.08) years-old (Figure 1(a)). Boys and girls are occupied for 186 (50.4%) and 183 (49.6%), respectively. The air change rate during mid-night among all inspected children was averaged in 1.69 ach and mainly ranged from 0.11-2.00 ach (Figure 1(b)). The averaged air change rate was significantly lower in those child s bedrooms which were inspected during spring than in those bedrooms inspected during autumn, as well as significantly lower in those child s bedrooms which were inspected during winter than in those bedrooms inspected during summer and during autumn (Table 1). (a) (b) Figure 1. Age distribution of the inspected children and frequency distribution of air change rate during mid-night in the child s bedroom. 4
Table 1. Comparison of air change rate among the residences inspected in various seasons. Season Sample Quartiles Mean ± SD Min size, n (%) p-value a Max 25th 50th 75th vs. Summer vs. Autumn vs. Winter Spring 108 (29.3) 1.47 ± 2.28 0.11 0.36 0.71 1.46 13.20 0.204 0.044 0.311 Summer 100 (27.1) 1.92 ± 2.86 0.12 0.51 0.79 1.83 16.41 0.507 0.043 Autumn 83 (22.5) 2.20 ± 2.69 0.17 0.41 0.92 3.34 11.22 0.006 Winter 78 (21.1) 1.13 ± 2.15 0.12 0.30 0.59 1.12 16.05 a Student s t test for paired comparison in mean values among various seasons. Figure 2 shows comparison of air change rates of the child s bedroom among cases children and controls children in the overall inspected residences and in the residences inspected in different seasons. None significant differences were found in the averaged air change rates among cases and controls in all studied groups. In summer, the averaged air change rates were slightly lower among cases than among controls; whereas the averaged air change rates were slightly higher among cases than among controls in other three seasons. However, compared to children with the first quartiles of air change rate, several lower prevalences of cases among children in high quartiles were found (Table 2), although differences in these prevalences had no statistical significances. Moreover, in the logistic regression analysis (Table 2), most of the associations between high quartiles of air change rate and the risk of being a case were negative, although all associations also had no statistical significances and had low consistence in the reverse linear trend between quartiles of air change rate and the risk of being a case. (a) Total (b) Spring (c) Summer (d) Autumn (e) Winter Figure 2. Comparison of air change rate of the bedroom among cases and controls. Table 2. Associations of different quartiles of air change rate with childhood asthma. Items Quartiles of the air change rate during mid-night in the child s bedroom a p- 1st 2nd 3rd 4th value b Case, n(%) Case, n (%) OR (p-value) Case, n (%) OR (p-value) Case, n (%) OR (p-value) Total 39 (40.6) 37 (40.7) 1.00 (0.996) 36 (40.0) 0.99 (0.931) 35 (38.0) 0.97 (0.717) 0.982 Spring 12 (41.1) 10 (38.5) 0.89 (0.825) 10 (37.0) 0.91 (0.856) 13 (50.0) 1.12 (0.522) 0.779 Summer 15 (60.0) 15 (57.7) 0.91 (0.867) 14 (58.3) 0.97 (0.906) 12 (48.0) 0.85 (0.396) 0.827 Autumn 6 (28.6) 4 (20.0) 0.63 (0.525) 2 (9.1) 0.50 (0.117) 5 (25.0) 0.94 (0.797) 0.415 Winter 9 (45.0) 5 (25.0) 0.41 (0.190) 8 (40.0) 0.90 (0.749) 7 (38.9) 0.92 (0.703) 0.597 a The quartiles for different indictors/pollutants were presented in Figure 1(b) and Table 1. The children in the first quartiles were took as reference. b In the chi-square test for differences in prevalence of cases (4*2 tables). 5
4 DISCUSSION In this study, we found that more than half of the child s bedrooms had lower air change rate, during mid-night when the children deeply sleep, than the minimum requirement for air change rate (1/h) in the residential buildings in hot summer and cold winter zone (MC-PRC, 2001). However, the averaged air change rate among the inspected bedrooms are higher than this minimum requirement (MC-PRC, 2001) and higher than the values from similar studies in Denmark (Beköet al., 2010) and in Sweden (Bornehag et al., 2005), as well as the values from most of the similar studies form other countries summarized in the systematic reviews (Dimitroulopoulou, 2012; Godish and Spengler, 1996; Sundell et al., 2011; Wargocki et al., 2002). Beköet al. (2010) inspected 500 residences for children 3-5 years-old in Denmark and reported that the geometric mean of the air change rates in these residences is 0.46/h and approximate 57% of the child s bedroom have lower than 0.5/h air change rate in the new dwellings. Bornehag et al. (2005) inspected 390 homes of children in Sweden and found that approximate 60% of the multi-family houses and about 80% of the single-family houses have lower than 0.5/h air change rate in the child s bedroom. Besides, our finding, that the air change rates among the inspected bedrooms in cold winter and spring are significantly lower than in hot summer and warm autumn, is consistent with findings from the similar study in Sweden (Bornehag et al. 2005). These findings indicate that the household ventilation status during mid-night in Shanghai could be better than in those European countries (Beköet al., 2010; Dimitroulopoulou, 2012; Bornehag et al. 2005); whereas household ventilation in Shanghai, especially in winter and spring, still should be gave more attention to improve. Furthermore, unexpectedly, we did not find significant differences in the averaged air change rates between cases and controls in the whole sampled residences and when stratified by inspected seasons. Whereas the logistic regression analyses on associations of quartiles of air change rate with childhood asthma seemingly suggest that higher air change rate is associated with lower risk of childhood asthma. This finding is consistent with findings from many previous studies (Bornehag et al. 2005; Nafstad et al., 1999; Sundell et al., 2011; Wargocki et al., 2002). The similar study in Sweden suggested that the ventilation rate of the child s bedroom during night is significantly lower among children with asthma than among children without asthma and they also reported a reverse dose-response relationship between the ventilation rate and the risk of childhood asthma (Bornehag et al. 2005). That, the associations between indoor ventilation during night and childhood asthma were not strong and significant as in the Bornehag et al. s study (Bornehag et al. 2005), probably due to that the whole situation of household ventilation status in Shanghai were better than in Sweden as we discussed above. However, it should be noticed that the calculated air change rate of the child s bedroom during mid-night in the present study could be larger than the actual value. Firstly, a recent study found that the commonly used empirical equation, namely the equation (2) in the present study, may over-predicted CO2 generation rates among Chinese people (Qi et al., 2014). Therefore, our calculated air change rate could by over-predicted. Secondly, some studies also suggested that using the steady state method with taking people-exhausted CO2 as tracer gas, could obtain relatively higher air change rate than the actual values (Persily, 2016; Wang et al., 2007). Another point should be noticed that the outdoor air pollution usually was heavy during winter 6
in Shanghai and other large cities of China (Kan et al., 2012). It is possible that increasing ACR together with heavy outdoor air pollution and traffic pollution may lead to worse indoor air quality, and thus actually lead to more asthma and its related symptoms (Kim et al., 2013). This study also has some other limitations, which included that: 1) the CO2 concentration only was measured in 24 hours, and thus the calculated air change rate may be unable to indicate the normal ventilation situation of the child s bedroom over the year; 2) the sample sizes in some items could be too small to compare differences of air change rates in different options of these items, and to get significant associations between air change rate and childhood asthma. Nevertheless, to our best knowledges, this study is the largest study on household air change rate during mid-night with on-site inspection in the mainland of China. That, family members were asked to keep their normal activities during home inspection, also make our results more close to the common situation regarding indoor ventilation level. Therefore, we consider that our results provide a credible picture regarding indoor ventilation level of the young child s bedroom in different seasons and its associations with childhood asthma in Shanghai, China. 5 CONCLUSIONS The household ventilation status of the child s bedroom during mid-night in Shanghai could be better than in those residences from European countries. Whereas household ventilation, especially in winter and in spring, still should be gave more attention to improve to decrease the risk of childhood asthma among young children in Shanghai, China. ACKNOWLEDGEMENT The authors thank all of the parents and children who took part in this study and others who provided assistance for our home inspection. This work is financially supported by the National Natural Science Foundation of China (51278302), Hujiang Foundation of China (D14003), the Innovation Program of Shanghai Municipal Education Commission (14ZZ132), and the Innovation Fund Project for Graduate Student of Shanghai (JWCXSL1401). 6 REFERENCES ASHRAE. 2013. ASHRAE Handbook-Fundamentals, Atlanta, GA, American Society of Heating, Refrigerating and Air-Conditioning Engineers. Beasley R, Semprini A and Mitchell EA. 2015. Risk factors for asthma: is prevention possible?. The Lancet, 386(9998), 1075-1085. BeköG, Lund T, et al. 2010. Ventilation rates in the bedrooms of 500 Danish children. Building and Environment, 45, 2289-2295. Bornehag C, Sundell J, et al. 2005. Association between ventilation rates in 390 Swedish homes and allergic symptoms in children. Indoor Air, 15, 275-280. Daisey JM, Angell WJ and Apte MG. 2003. Indoor air quality, ventilation and health symptoms in schools: an analysis of existing information. Indoor air, 13, 53-64. Diette GB, Hansel NN, et al. 2007. Home indoor pollutant exposures among inner-city children with and without asthma. Environmental Health Perspectives, 115, 1665-1669. Dimitroulopoulou C. 2012. Ventilation in European dwellings: A review. Building and Environment, 47, 109-125. 7
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