In this national time series study, we found that ambient CO pollutant, was significantly and positively associated with daily YLL from total non-accidental causes, overall CVD, CHD, stroke, overall RD and COPD, even at levels below the current CAAQS, in 49 Chinese cities from 2013–2017. The estimated effects of CO on YLL by individual-level were stronger for elders and people with low education attainment level. In addition, the CO-associated effects on YLL were stable by sensitive analyses including two-pollutant models. To the best of our knowledge, it is the first nationwide study systematically explored the impacts of short-term exposure to CO pollution on YLL due to all non-accidental diseases and different cardiopulmonary diseases, in China.
Previously, it has been well documented in China, that ambient CO is associated with cause-specific mortality including total non-accidental death [3, 14], overall RD death [3, 15], overall CVD death [2, 3, 14] and some specific CVD death [2]. However, we still need the studies estimating the effect of CO on YLL, which could provide both novel and accurate indicators into the impact of ambient CO on human health, and be meaningful in both resource allocation and policy making of public health. In China, some single-city studies [7–9] observed the association of YLL with some other air pollutants, like NO2, SO2, O3 and particle pollutants. One study examined the effects of ambient PM2.5, PM10, SO2 and NO2 on total non-accidental YLL in Beijing, China [7] and they found 15.8, 15.8, 16.2 and 15.1 years increases of YLL, associated with an IQR increase of concentration in PM2.5, PM10, SO2, and NO2, respectively in Beijing during 2004–2008, and the impacts of air pollution appeared short-term and only lasted for two days (lag01).
In our study, we found the greatest effect of CO was on the lag03 for moving average days, and it can last for about 3 days (lag2) for total non-accidental YLL. For YLL from CVD, the CO effect can last for 3 days (lag2) and the greatest increase of CVD YLL related to CO was also on lag03 in our study. This lag pattern is similar with the nationwide study exploring the effect of ambient CO on the death due to CVD in China [2]. The study in Yichang (a city in Central China) [2] found estimated effects for CO were greater for the moving averages with longer lag days, and the strongest effect of CO was at lag 06 on the cause-specific outpatient visit which can reflect the acute health effects. Unlike other air pollutants, CO concentrations were mainly at a low level in the 49 cities of China (mean, 1.1, range, 0.6–2.2 mg/m3), so the effect from CO may need more time to cumulative harm, leading to the morbidity or mortality of the population [4, 16].
In our study, we also estimated a significant CO-related increase of YLL due to some specific CVD, like CHD and stroke. In Guangzhou (a city in South China), a significant and positive relation was found between air pollution (NO2, SO2 and PM10) and YLL due to overall CVD, and CVD subtype including stroke and ischemic heart disease [8]. Compared with the studies on CO and CVD, studies on the association between CO and mortality from RD were limited and showed mixed results. The first multi-city study concentrating on short-term effect of ambient CO in Chinese population by time series analyses was conducted in the Pearl River Delta of China, and found that 0.5-ppm increase in CO concentration in the lag 1–2 (average of previous 1 and 2 days) was related to 3.72% (95% CI, 1.71–5.76%) increases in excessive risks of respiratory mortality [3]. On the contrary, some other studies showed positive, but not statistically significant association between CO and RD mortality [14, 17]. In our study, we found a slight increase of YLL from RD and COPD related to CO on lag0. As the estimated CO-related increase of RD and COPD YLL were not statistically significant on most lag days in the regional-level analyses, we should be cautious about whether CO will increase the YLL of RD and COPD.
In line with the findings of previous studies on the CO-related mortality in 272 cities in China [2] and 19 European cities [18], we observed that the associations remained statistically significant and positive after the adjustment of the other five air pollutants in our study. Some single-city studies found the significant and positive estimations were attenuated to null after controlling for exposure to other air pollutants [14, 19]. It may be due to small sample sizes of a single city, different air pollution components or population characteristics. Comparing effect estimates for ambient CO in both single- and two- pollutant models can observe the more independent effect of ambient CO pollution after adjusting the effect of other air pollutants.
Identifying vulnerable subgroups is essential for resource allocation to reduce CO-related public health impact. Consistent with previous researches, we found much higher vulnerability to CO among males, elders, and those with low education level [14, 17]. However, the health effects of CO pollution could be significantly modified by age, but not by gender [14, 17] after the test of between-subgroup differences. As for the larger CO effect of less-educated populations, it may directly reflect the environmental health inequalities and inequities which were associated with socioeconomic status, like higher prevalence of preexisting diseases, higher level or frequency of exposure and co-exposure (with household and occupational sources), less affordable health care resources and so on [20].
We can’t found the statistically significant associations between CO and YLL from total causes and CVD in the west regions of China (Northwest China and Southwest China). The differences of CO-related effects across the two regions may due to complex factors, like the population susceptibility, variation of air pollutant concentration, quality of YLL data and so on. It may mainly be caused by the small number daily counts of mortality in Northwest China and Southwest China. Besides, the previous study suggested that the adverse effects of CO might not vary substantially by geography in China [2].
Many studies have shown the mechanism and physiological responses to CO poisoning [21, 22]. CO is an odorless, colorless, tasteless, and a nearly ubiquitous gas that could occupy hemoglobin ahead of oxygen with an affinity more than 200 times that of oxygen. Therefore, the process of supplying oxygen to tissues can be interfered when people get CO poisoning [21, 22]. The evidence on the organism reactivity to a low concentration of ambient CO is still insufficient and unclear. Results of the exposure studies have indicated that patients with atherosclerotic CVD may be affected and exacerbated myocardial ischemia by the presence of carboxyhemoglobin owing to the exposure to ambient CO, even at low concentrations [23]. Previous epidemiological and experimental studies have demonstrated that exposure to ambient CO could bring about an increased risk of CVD by several plausible mechanistic pathways, like a systemic inflammatory response, process of reactive oxygen species generation, and interruption of the terminal oxidase of the electron transport chain, acute increased blood pressure, a propensity for arrhythmias, plasma fibrinogen changes, or increased blood viscosity [24–26].
Although the annual-average concentration of CO (1.1 mg/m3, range, 0.6–2.2 mg/m3) was blow the CAAQS in China (4 mg/m3), and was comparable with the level of CO concentration in many European cities [18], it still increased the YLL from many causes. As shown in the previous study in 272 cities of China, no apparent lower threshold was found for the short-term effect of CO on CVD mortality [2]. CO is an almost ubiquitous product of incomplete combustion of carbon-containing fuels, and there are various sources of CO pollution, like motor vehicles, engines on motorboats, coal combustion, tobacco smoking, and so on. In the recent three decades, with the rapid development of economic, urbanization and industrialization in China, air pollutants, especially CO warrant further investigation.
Our study had several strengths. First of all, our study is the first nationwide study observing the association between ambient CO and cause-specific YLL. Compared with mortality risk that ignore the inequality due to different age of death, YLL quantifying premature deaths can be better reflecting the burden of CO pollution. Secondly, we selected the top principal causes of death that ranked high in China [27], to see the whole picture of CO-related YLL. Thirdly, we used the largest death database of 49 major cities in China with good internal consistency in data collection in developing countries, which had reliable external representativeness for our findings. Finally, this investigation also provided evidence regarding the population susceptibility to CO pollution, and public health improvement steps can be efficiently developed. Additionally, the modification by geographical region and regional-level characteristics was also investigated, including climatic, geographical, and socioeconomic characteristics.
The present study was also subject to several limitations. Firstly, as a studies using time series methods, we used aggregated levels of air pollutants as surrogates for individual, so that exposure misclassification was inevitable. Nevertheless, these errors are supposed to be random and may not bias the estimated effects [28]. Secondly, we cannot rule out the potential diagnostic or coding errors for death causes, though most death data used for YLL calculation in the present study was under strict quality control. Finally, there may be other unknown and unmeasured factors, for example, we did not control for smoking or obesity related to CVD, because this information was unavailable. However, such factors are not related to air pollution levels because the distribution of such fixed factors does not vary from day to day. We, therefore, assume that the results would have been only marginally affected because the effects are short term, and the time-series method controls for both long-term and fixed-term factors [29].