Introduction

According to the World Health Organization (WHO) report in 2012, 12.6 million people (including 2.987 million people in China) died because of unhealthy living or working environments, which accounted for 23% of all deaths (WHO 2016). It has been suggested that the environmental risk factors, such as extreme meteorological conditions and air pollution, have adverse effects on human mortality and morbidity (De Sario et al. 2013; Kelly and Fussell 2015). Several epidemiological studies have reported the effects of air temperature, humidex, and apparent temperature on human health in China (Ma et al. 2018; Ban et al. 2017; Yin and Wang 2017; Ge et al. 2018; Cui et al. 2019) and other countries (Fernández-Raga et al. 2010; Medina-Ramón and Schwartz 2007; Katsouyanni et al. 1993; Zanobetti and Schwartz 2008; Revich and Shaposhnikov 2008). Strong evidence showed that extreme air temperatures have significant impact on human health (Kovats and Hajat 2008; Ma et al. 2019), especially among vulnerable groups (e.g., the elderly, children, and people with chronic diseases) (WHO 2008). In addition, seasonal changes in weather have extensive effects on the outcomes of human health, including mortality rates due to cardiovascular, respiratory, and infectious diseases (Burkart et al. 2014).

In recent years, ambient air temperature has become an adverse health factor. Some epidemiological studies have reported that ambient air temperature is significantly associated with morbidity and mortality. The relationships between daily or monthly mean, maximum, or minimum air temperatures and mortality often showed U-, V-, or J-shaped curves, suggesting that both high and low temperatures would increase health risks (Analitis et al. 2008; Gasparrini et al. 2015; Carmona et al. 2016). For example, Ma et al. (2014) pooled the effect estimates in 17 Chinese cities, indicating that a 1 °C decrease (increase) from the 25th to 1st (the 75th to 99th) percentiles of temperature was associated with increases of 1.69% (2.83%), 2.49% (3.02%), and 1.60% (4.64%) in total, cardiovascular and respiratory mortality, respectively. Zhang et al. (2014) examined the association between temperature and emergency department (ED) visits in Shanghai and found that per 1 °C decrease (increase) in temperature was associated with an overall 2.76% (1.78%) increase in ED visits. Similar results have been confirmed in studies conducted in other parts of China (Ban et al. 2017; Li et al. 2017; Zhou et al. 2014; Jie et al. 2014; Liu et al. 2014; Guo et al. 2012); exposure to high or low temperatures not only affects the respiratory and circulatory systems but can also increase deaths caused by diabetes (Yang et al. 2016), renal colic incidence (Yang et al. 2016); preterm birth rate (He et al. 2015; Guo et al. 2018), and onset of mental disorders (Peng et al. 2017). In addition, ambient air temperatures were also closely related to the incidence of infectious diseases like scarlet fever (Zhang et al. 2018; Duan et al. 2017); chickenpox (Chen et al. 2017); infectious diarrhea (Wang et al. 2015a; Zhou et al. 2013; Yang et al. 2016; Li et al. 2016; Ma et al. 2010); bacillary dysentery (Cheng et al. 2017); varicella infections (Yang et al. 2016); scrub typhus cases (Li et al. 2014a); measles (Ma et al. 2017; Yang et al. 2014); hand, foot, and mouth disease (HFMD) (Li et al. 2014b; Zhao et al. 2016; Yang et al. 2016); and dengue fever (Fan et al. 2014), especially when the temperature rises. In Beijing, Duan et al. (2017) reported that the monthly mean temperature showed a positive effect (RR = 1.196, 95% CI: 1.022, 1.399) on scarlet fever. In Guangzhou, Li et al. (2014a) found that each 1 °C rise in temperature corresponded to an increase of 9.47% (95% CI: 9.36–9.58%) and 14.98% (95% CI: 13.65 to 16.33%) in the weekly number of HFMD cases and scrub typhus cases. In Shanghai, Zhou et al. (2013) also provided a clear evidence of high temperature on increasing the incidence of diarrhea: 1 °C elevation of temperature was associated with 2.68% (95% CI: 1.83–3.52%) increase in diarrhea visits.

Epidemiological studies have pointed out that diurnal temperature range (DTR) and temperature change between the neighboring days (TCN) both showed adverse effects on human health. DTR (defined as the difference between daily maximum and minimum air temperatures) is a meteorological indicator for climate change and urbanization effects. Previous studies reported that DTR is related to mortality (Zhou et al. 2014; Luo et al. 2013; Yang et al. 2012) and the incidence of respiratory and cardiovascular diseases (Ma et al. 2018; Ge et al. 2013; Wang et al. 2013a; Xu et al. 2013). TCN was suggested to be associated with mortality in China (Lin et al. 2013; Cheng et al. 2014), Australia (Guo et al. 2011), and the United States (Zhan et al. 2017). In Brisbane, Australia, mortality of cardiovascular diseases would increase by 35.3% (95% CI: 3.3–77.2%) for per 3 °C increase in TCN (Guo et al. 2011). In Hefei (the capital and largest city of Anhui Province), China, non-accidental mortality would increase by 3% (with the range of 0–5%) with per 3 °C increase in the maximum TCN (Cheng et al. 2014). In the United States, there was a relatively high risk of mortality among people aged ≥ 75 years on the days with positive changes in TCN (Zhan et al. 2017).

A few studies reported the joint effects of air temperature and rainfall on respiratory morbidity (Su et al. 2014; Zhang et al. 2015c), cardiovascular mortality (Jie et al. 2014; Li et al. 2015; Li et al. 2011), hemorrhagic fever with renal syndrome (HFRS) (Liu et al. 2013b), HFMD (Wu et al. 2016; Chen et al. 2015a), bacillary dysentery (Li et al. 2015), and chickenpox (Chen et al. 2017). Some studies reported that air temperature could modify the effect of ambient air pollution on human health risks, such as cardiovascular and respiratory mortality (Li et al. 2011; Qian et al. 2008), COPD morbidity (Qiu et al. 2018), and outpatient visits for eczema (Li et al. 2016).

In this study, we reviewed a total of 175 recent studies on the effects of environmental conditions (158 for outdoor environment and 17 for indoor environment) on human health in China. For the outdoor environment, we summarized the effects of climate change–related phenomena on health, such as temperature, DTR, TCN, or other factors. The reviewed studies covered all areas of China (Fig. 1). The majority of the studies were about big cities, including 36 for Guangzhou, 35 for Beijing, 31 for Shanghai, and 22 for Wuhan. Besides that, 11–20 studies were for Harbin, Shenyang, Tianjin, Ji’nan, Hefei, Nanjing, Chengdu, Changsha, and Hong Kong, and the rest of the studies were for other cities.

Fig. 1
figure 1

Number of reviewed studies that were conducted in different locales of China

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Methods

Data extraction

Two investigators (Yifan Zhang and Haoran Jiao) searched PubMed, Web of Science, the Cochrane Library, and Embase for studies from January 2010 to January 2020, and the following terms were used as search strategy: (“meteorological” or “weather” or “climate” or “temperature” or “hot” or “cold” or “heat wave” or “DTR” or “air pressure” or “humidity” or “wind” or “rainfall” or “precipitation” or “sunshine duration”) and (“circulation” or “circulatory” or “cardiovascular” or “cerebrovascular” or “respiratory” or “communicable” or “infectious” or “digestive” or “metabolic” or “endocrine” or “premature birth” or “preterm birth”) and (“mortality” or “morbidity” or “hospital visit” or “hospital emergency” or “hospital admission”).

A total of 4,367 articles were retrieved; then two investigators screened the titles and abstracts and excluded clearly irrelevant and unusable references independently; any differences were resolved by Bowen Cheng.

We finally selected 272 articles on the impact of environmental factors on human health and added 135 articles we selected from other data platforms. After removing duplicates in Endnote software, we screened out 175 articles with clear classifications of urban and environmental factors in China for regional statistical analysis.

Meta-analysis

The following eligibility criteria were included in the final meta-analysis: (a) focused on the effects of ambient temperature on cardiovascular diseases; (b) reference temperature or threshold was indicated; (c) RR and 95% CI was indicated; (d) no seasonality; (e) not extreme weather events; and (f) not projected temperature-related outcomes.

In the 175 articles, we selected 19 articles to explore the effect of air temperature on cardiovascular diseases in different cities. The characteristics of selected studies (including the first author, publication year, studied area and period, statistical methods, effect estimate of temperature, outcome variable, relative risks with 95% CI) were shown in the appendix (Yang et al. 2013). We divided the effects of temperature into two groups: cold effect and hot effect. In each group, we calculated the combined effect value according to the city. RRs from the individual studies were pooled with the random effects method because of the large degree of variation in the overall effect estimates between studies. The detailed screening process was shown in Fig. 2.

Fig. 2
figure 2

Flow diagram of literatures’ selection process

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Outdoor environment and human health in China

Among the 158 studies of outdoor environment on human health, 54% focused on the associations of temperatures with cardiovascular diseases, including 12% on DTR, 21% on air temperature, and 67% on extreme air temperatures (Fig. 3).

Fig. 3
figure 3

Number of studies on the effects of the different meteorological factors (including DTR, extreme cold, extreme heat, air temperature, and others) on the different types of human diseases (including cardiovascular, respiratory, digestive, endocrine, and infectious diseases) in China.

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Environmental factors and cardiovascular diseases

Epidemiological studies have pointed out that increases in cardiovascular disease morbidity (Ban et al. 2017; Ge et al. 2018; Cui et al. 2019) and mortality (Ma et al. 2014; Li et al. 2017; Chen et al. 2013) were associated with changes in the ambient air temperature. Previous studies have shown that every 1 °C temperature increase/decrease beyond certain reference points can lead to increased health risks of cardiovascular diseases (Zhang et al. 2016a; Gao et al. 2017; Huang et al. 2014). Some studies selected higher and lower reference temperatures as thresholds to explore the health effects of extreme hot and cold temperatures (Zhang et al. 2015b; Ding et al. 2016; Yang et al. 2012; Tian et al. 2012). In addition, the impact of DTR was also announced in many studies. Yang et al. (2018) found that the relationship between DTR and stroke mortality was more significant in Southern China (with a relative risk of 1.02%, 95% CI: 0.62–1.43%) than in Northern China (with a relative risk of 0.10%, 95% CI: − 0.27–0.47%). In Beijing, the extra risk of cardiovascular admissions would increase by 0.76% (95% CI: 0.07–1.46%) for per 1 °C increase in the 3-day moving average of DTR (Wang et al. 2013a).

Since studies related to temperature exposure and cardiovascular diseases accounted for a large proportion of the total studies, we selected appropriate literatures further to assess the health risk of low and high temperatures. After separating the hot and cold exposure, meta-analyses were fitted using a random effect model to pool the estimates of RRs from all the included cities. As presented in Fig. 4, the effect of temperature varies between different cities. The overall effects of all studies for hot and cold temperatures were 1.089 (95% CI: 1.062–1.116) and 1.171 (95% CI: 1.125–1.218), respectively. For the hot effect, the RRs ranged from 1.001 (95% CI: 0.996–1.006) to 1.820 (95% CI: 1.532–2.162), while the RRs of the cold effect ranged from 1.030 (95% CI: 0.656–1.618) to 1.800 (95% CI: 1.384–2.340).

Fig. 4
figure 4

Forest plot for the effects of hot and cold exposure on cardiovascular diseases in different cities of China

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Other meteorological elements such as atmospheric pressure, relative humidity, and precipitation also have important influences. In Changchun, the number of admissions suffering from cerebral infarction was highly correlated with relative humidity and precipitation (Wang et al. 2013a). In Hong Kong, the positive linear association of air pressure with cardiovascular diseases was illustrated by Fong and Ma (2013). In Guangzhou, cardiovascular mortality was also found significantly affected by atmospheric pressure and relative humidity. When atmospheric pressure and relative humidity increased from the 5th percentile to the 25th percentile, cardiovascular mortality increased by 2.27% (95% CI: 0.07–4.51%) and 3.97% (95% CI: 0.67–7.39%), respectively (Ou et al. 2014).

The interactions between meteorological factors and air pollutants also affected human health. In Zhejiang Province, the joint effect of low air temperature and high humidity on cardiovascular mortality showed a significant attributable fraction of 31.36% (95% empirical CI: 14.79–38.41%); the joint effect of low air temperature and low humidity showed a significant attributable fraction of 16.74% (95% empirical CI: 0.89–24.44%) (Zeng et al. 2017). In Tianjin, the interaction between PM10 and air temperature was statistically significant. For per 10 μg/m3 increase in PM10 concentrations when the air temperature was relatively high, cardiovascular mortality would increase by 0.92% (95% CI: 0.47–1.36%) (Li et al. 2011). In Suzhou, Chen et al. (2013) also showed that the O3 effects were stronger in cold season and low temperature days. On days with low temperatures (0th–25th percentile), an interquartile range (IQR) increment in 1-h maximum O3 corresponded to a 18.77% (95% CI: 0.09, 40.95) increase in cardiovascular mortality. On days with normal temperatures (26th–75th percentile) or high temperatures (76th–100th percentile), the estimates were only 7.82% (95% CI: − 15.21, 37.10) or 6.14% (95% CI: − 17.35, 36.31). In Beijing, Luo et al. (2016) further indicated that the associations of PM2.5 with cardiovascular mortality in susceptible populations were more sensitive to further adjustments for temperature and relative humidity.

Environmental factors and respiratory diseases

A strong evidence indicated a link between ambient air temperature and the development of respiratory diseases, including respiratory mortality and morbidity, COPD, bronchitis, upper respiratory infection, and asthma. Exposure to adverse ambient air temperature is associated with the high morbidity of respiratory diseases (Ma et al. 2019; Liu et al. 2014). In Ji’nan of Shandong Province, for per 1 °C increase in the maximum, average, and minimum temperatures that are above the threshold (35, 31, and 26 °C, respectively), the mortality of respiratory diseases would increase by 6.6, 25.3, and 14.7%, respectively (Li et al. 2017). Respiratory mortality has also been linked to extremely cold and hot temperatures (Wang et al. 2016a; Chen et al. 2015a; Song et al. 2017). A multi-city study showed that elderly people and those with respiratory diseases are generally more vulnerable to cold spells, especially in Southern China (Wang et al. 2016b). In Nanjing of Jiangsu Province (located in Eastern China), heat waves (when daily average air temperature is above the 98th percentile for four or more consecutive days) were associated with a 32.0% (95% CI: 8.5–60.5%) increase in respiratory mortality and a 47.6% (95% CI: 14.5–90.3%) increase in COPD mortality (Chen et al. 2015a). As for the effect of DTR, in Taiwan, the number of COPD hospital admissions increased by 14% when DTR increased to above 9.6 °C (Liang et al. 2009). In Shanghai, a 1 °C increase in the 2-day moving average of DTR would lead to a 2.08% (95% CI: 1.24–2.93%) increase in the number of ER visits for respiratory tract infections (Ge et al. 2013); a 1 °C increase in the 4-day moving average of DTR would cause a 1.25% (95% CI: 0.35–2.15%) increase in COPD mortality (Song et al. 2008). In Beijing, a 1 °C increase in DTR could increase respiratory mortality by 1.29% (95% CI: 0.49–2.09%) (Kan et al. 2007). In Changchun of Jilin Province (located in Northeast China), for per 1 °C increase in DTR, the relative risk of COPD could be up to 1.007 (95% CI: 0.994–1.019) during the year, 1.090 (95% CI: 1.077–1.103) during the warm seasons, and 1.115 (95% CI: 1.100–1.129) during the cold seasons (Ma et al. 2018). In particular, the elderly (age 65 and older) are at relatively higher risk of COPD than other people when DTR increases. Respiratory diseases are also affected by other environment factors. A previous study in Hong Kong showed that air pressure had a delayed effect on respiratory admissions (Fong and Ma 2013). In Hefei, the incidence of acute respiratory infection was negatively associated with relative humidity (Duan et al. 2016). In Beijing, among the involved air pollution and meteorological factors, relative humidity showed the most significant effect on COPD incidence, with a relative risk of 1.070 (95% CI: 1.054–1.086) for per 1% increase in relative humidity (Tian et al. 2019).

Joint effects of weather elements also could affect respiratory health. In Beijing, ambient air temperature and humidity showed a joint effect on ER visits for respiratory diseases, upper respiratory infection, and bronchitis. When the humidity level was relatively high, for per 1 °C increase in the average air temperature, the number of ER visits for all respiratory diseases, upper respiratory infection, and bronchitis would increase by 1.84% (95% CI: 1.35–2.13%),1.76% (95% CI: 1.41–2.11%), and 7.48% (95% CI: 4.41–10.65%), respectively (Su et al. 2014). In Tianjin, for per 10 μg/m3 increase in PM10 concentrations when the air temperature was relatively high, respiratory mortality would increase by 0.74% (95% CI: − 0.33–1.82%) (Li et al. 2011). In Chengdu of Sichuan Province (located in Southwest China), the joint effect of particulate matters and low air temperature showed the greatest impact on COPD morbidity. During days with relatively low air temperature, exposure to PM2.5 and PM10 contributed to 17.30% (95% CI: 12.39–22.19%) and 14.72% (95% CI: 10.38–19.06%), respectively, of the total number of hospital admissions for COPD (Qiu et al. 2018).

Environmental factors and digestive system and endocrine diseases

Environmental factors are also linked to the prevalence of digestive system diseases (Wang et al. 2013b; Li et al. 2014a), endocrine and metabolic mortalities (Li et al. 2014b), diabetes deaths (Yang et al. 2016), renal colic (Yang et al. 2016), and hemorrhagic fever with renal syndrome (Liu et al. 2013a). Some studies have shown the significant influence of temperature on digestive system diseases. Li et al. 2014apointed that for per 1 °C increase in the daily maximum air temperature, daily digestive mortality increased by 23.6 and 8.8%, respectively, in Chongqing and Shenzhen, and daily endocrine and metabolic disease mortality would increase by 31.9% (95% CI: 0.6–73.0%) in Shenzhen and 23.6% (95% CI: 1.2–50.9%) in Chongqing. A multi-city study suggested that short-term exposure to extremely high or low temperatures may contribute to an increase in diabetic deaths, especially for the elderly and people who are at pre-primary education level (Yang et al. 2016). In Guangzhou of Guangdong Province (located in South China), the relative risk of diabetic mortality was 1.10 (95% CI: 0.67–1.79), 1.07 (95% CI: 0.80–1.44), 1.92 (95% CI: 1.21–3.05), and 2.45 (95% CI: 1.50–3.99) for a short-term exposure to extremely low, low, high, and extremely high air temperatures, respectively (Yang et al. 2016). In Beijing, for per 1 °C increase in the 8-day moving average of DTR corresponded to 2.14% (95% CI: 0.71–3.59%) increase in the number of ER admissions for digestive diseases (Wang et al. 2013a). In Junan County of Shandong Province, air temperature and precipitation during the preceding 3 months can affect the endemic intensity of hemorrhagic fever with renal syndrome (Liu et al. 2013a).

Environmental factors and infectious diseases

Studies have shown that infectious diseases are related to environmental factors (Li et al. 2016; Duan et al. 2017; Wang et al. 2015a; Zhao et al. 2016; Ma et al. 2010). In Shanghai, weekly mean maximum, minimum, and average air temperatures showed the most effect on infectious diarrhea (Wang et al. 2015b). In Hefei of Anhui Province, the risk of bacillary dysentery would increase by 18.74% for per 1 °C increase in the average air temperature (Cheng et al. 2017). In Changsha of Hunan province, for per 1 °C increase in the average, maximum, and minimum air temperatures, the incidence of bacillary dysentery would increase by 14.8, 12.9, and 15.5%, respectively (Gao et al. 2014). The monthly average air temperature showed a negative effect on scarlet fever (with a relative risk of 0.962, 95% CI: 0.933–0.992) in Hong Kong but a positive effect on scarlet fever (with a relative risk of 1.196, 95% CI: 1.022–1.399) in Beijing (Duan et al. 2017). In Hefei of Anhui Province, there was a statistically significant correlation between DTR and pediatric bacillary dysentery incidence; for per 5 °C increase in the DTR, the number of pediatric bacillary dysentery cases would increase by 8.0% (95% CI: 2.9–13.4%); children younger than 5 years were relatively more sensitive to changes in DTR (Wen et al. 2016). Temperature changes within a day or between neighboring days also affect infectious diseases. In Huainan of Anhui Province, changes in air temperature between the neighboring days showed an adverse effect on the incidence of pediatric hand, foot, and mouth disease (HFMD) (Xu et al. 2016). In general, males and relatively younger children are more vulnerable to changes in air temperature (Yin et al. 2016; Xu et al. 2016). Moreover, humidity and precipitation are also important factors. In Qingdao of Shandong Province (Jiang et al. 2016), Suzhou of Jiangsu Province (Chen et al. 2015b), and Hong Kong (Wang et al. 2016a), increases in air temperature, precipitation, and relative humidity could all lead to an increase in the incidence of HFMD. In Guangzhou of Guangdong Province (located in South China), the weekly number of HFMD cases would increase by 9.38% (95% CI: 8.17–10.51%) and 4.01% (95% CI: 3.05–5.03%) with per 1 °C increase in the average air temperature and per 1 m/h increase in the wind velocity, respectively (Li et al. 2014a). In Shenzhen of Guangdong Province, the daily number of HFMD cases would increase by 3.93% (95% CI: 2.16–5.73%) for per 1 m/second increase in the wind speed (Zhang et al. 2016b). Environmental factors are also associated with other kinds of infectious diseases (Bi et al. 2013; Zhang et al. 2012; Li et al. 2013; Huang et al. 2011; Tian et al. 2008). In Guangdong Province, the monthly number of malaria cases would increase by 0.90% (3.99%) for per 1 °C increase in the average air temperature (1% increase in the relatively humidity) (Li et al. 2013). In Yongcheng of Henan Province (located in Central China), maximum air temperature and relative humidity both showed significant effects on malaria incidence at a 1-month lag (Zhang et al. 2012). In Guangdong, daily vapor pressure and average and minimum air temperatures were associated with an increase in the risk of dengue fever (Fan et al. 2014). For per 1 °C increase in the maximum and minimum air temperatures, dengue fever incidence would increase by 11.9 and 9.9%, respectively; relative humidity exceeding 78.9% was negatively associated with dengue fever incidence (Xiang et al. 2017). In Linyi of Shandong Province (located in Northern China), monthly average air temperature and relative humidity both showed positive correlations between Japanese encephalitis incidences (Lin et al. 2012). In Gansu Province, measles incidence was positively correlated with the monthly wind speed but negatively correlated with the monthly precipitation (Ma et al. 2017). In Wuhan of Hubei Province and Hong Kong, both average air temperature and precipitation showed significant influences on chickenpox incidence (Chen et al. 2017).

Environmental factors and preterm birth

Changes in ambient air temperature are found to be associated with preterm birth rate. In particular, weather extremes were significantly associated with the risk of preterm birth (Guo et al. 2018). In Guangzhou, when women were exposed to extreme cold (7.6 °C, the 1st percentile) or extreme heat (31.9 °C, the 99th percentile) during the last 4 weeks of pregnancy, the risk of preterm birth would increase by 17.9% (95% CI: 10.2–26.2%) or 10.0% (95% CI: 2.9–17.6%) (He et al. 2015). In Shenzhen of Guangdong Province, cold days were associated with the risk of preterm birth (Liang et al. 2016). In 2008, the cold spell caused a 22.44 and 21.25% increase in vaginal preterm birth in Dongguan and Shenzhen, respectively; the effect of the cold spell on preterm birth lasted for more than a week (Liang et al. 2018).

Indoor environment and human health in China

Nowadays, people tend to spend a large amount of time indoors. In particular, urban people spend approximately 90% of their time indoors (Brasche and Bischof 2005; Klepeis et al. 2001). Therefore, an indoor environment plays an important role in human health. To a certain extent, indoor air quality is correlated with outdoor air quality. The concentrations of outdoor air pollutants are associated with the physical characteristics of indoor air temperature and humidity. In a climate-controlled indoor environment, changes in indoor air temperature and humidity are likely to cause headaches, chest tightness, dry skin, etc.

In China, far fewer studies focused on the impact of indoor environment on human health than on the impact of outdoor environment. In this review, we only collected 17 relevant domestic studies. The involved topics were thermal environment (i.e., air temperature and relative humidity) and asthma/respiratory infections among children (Fan et al. 2017); indoor air pollution and respiratory symptoms (Fan et al. 2017; Liu et al. 2013a; Zhang and Smith 2007); indoor mold/dampness and pediatric allergies and asthma (Wang et al. 2013a; Lu et al. 2016; Qian et al. 2016; Zhang et al. 2015a); and indoor exposure to other factors like renovation, cooking, keeping pets, and human health (Zhang et al. 2013; Deng et al. 2015; Liu et al. 2015).

Overall, the reviewed studies about the impact of indoor environment on human health were mostly conducted in big cities in East China (including Beijing, Shanghai, Nanjing, Changsha, and Wuhan) and Northeast China (including five cities in Liaoning Province). In Beijing, a comprehensive investigation indicated that exposure to indoor low air temperature and low relative humidity in winter and dampness in summer could affect childhood health (Fan et al. 2017). Both dry and humid air were found to be positively associated with dampness indices (Qian et al. 2016). In Changsha, Hunan (Southern China), a study reported that prenatal exposure to indoor mold was significantly correlated to eczema incidence and postnatal exposure to indoor dampness was significantly correlated to asthma incidence (Deng et al. 2016). In Wuhan, Hubei, and Nanjing, Jiangsu, studies suggested that home environmental factors (dampness) were significantly associated with the prevalence of childhood pneumonia (Zheng et al. 2013) and asthma and rhinitis (Zhang et al. 2013). Qian et al. (2016) suggested that parents’ perception of odors and relative humidity may be indicators of air pollutants in the surrounding environment and are likely to be the real factors that are associated with children’s allergies. In particular, high levels of indoor PM2.5 and VOCs (in house dust) were rated as the possible main risk factors for children’s health (Hu et al. 2017). In Shanghai, the relative risk of death from stroke was 9.72 (95% CI: 1.88–50.24) among people who are exposed to coal fumes for an extended period of time (Zhang et al. 1988). In addition to indoor meteorological factors and air pollution, indoor renovation, use of gas for cooking, keeping pets, and living with smokers also affect human health (Liu et al. 2014; Zhang et al. 2013; Deng et al. 2015). Yu et al. (2018) also confirmed that solid fuels combusted indoors increased the risk of cardiovascular mortality in rural China. This is because solid fuels generate a large amount of air pollutants, including fine particulate matter.

Summary

In this review, we summarized studies on the impacts of outdoor meteorological factors on human health and then evaluated the potential risks of indoor environment on human health. In sum, ambient air temperature significantly affects human health, and changes in ambient air temperature are closely related to cardiovascular and respiratory morbidity and mortality. Regarding the indoor environment, air temperature, humidity, and dampness are key factors to human health, especially for the sensitive group (i.e., children).