We examined the effects of ambient temperature on TB cases in Jinan, one of the so-called four “ovens” with serious air pollution in mid-eastern China, during the period of 2012 to 2015. Study findings indicated that the temperature–incidence relationship was non-linear, with showing an S-shape at the current day and a U curve over lag 0–70 days. Further, the minimum Tmean effect appeared immediately with a following harvest effect, and the second onset peak appeared after lag 8–9 weeks, whereas the maximum Tmean effect became predominant with about two weeks’ lag. Meanwhile, the Tmean effect on incidence of TB modified by different levels of RH, WS and SD, and varied across different lag period.
Our results of a negative and non-linear relationship between ambient temperature and notified cases of TB infection are consistent with research carried out in other countries with different weather conditions [14, 17, 35]. We also found that the risk of TB incidence was greatly affected by extreme temperature on the current day. On the other hand, the overall cumulative effect showed trends for increased risks for decline of cold temperature and increase of hot temperature.
Many investigators [14, 17, 37] have reported the delayed effect in the relationship between TB and cold or hot effect. Our study also confirmed that the delayed effect existed. For the effects of the minimum and the 5th percentile of Tmean, the immediate effects appeared at that day, and the second onset peak appeared at lag 8–9 weeks. For the effects of the 75th, 95th percentiles and maximum of Tmean, the onset peak appeared after lag about two weeks. The peak of cold effect appeared earlier than that of hot effect, which is comparable to the results of a study [14] conducted in Japan. In contrast to this study’s findings, however, the results in the Japan study showed that high temperature effects were generally constant at lag periods of up to 12 weeks, whereas the effects in low temperature ranges were persistent over shorter lag periods and diminished over time. This may be due to the warm climate in Japan, so the 5th percentile temperature (5.4 °C) in the Japan study was only equivalent to the 25th percentile in our study. Yuanyuan Xiao[35] found that average temperature was inversely associated with TB incidence at a lag period of 2 months. Similarly, we found that Tmean under 15 °C was also negatively associated with TB at lag 63, but hot effect was not significant.
The difference in lag effects as our results of DLNMs suggested would be also related to some characteristics, and some researchers have provided this context for interpreting our results. Fares [38] manifested that lower temperature during winter may induce the susceptibility to respiratory epithelium infection. The fluctuation in weather temperature during winter may also act on the respiratory epithelium by slowing mucociliary clearance and inhibiting phagocytosis, causing pathophysiological responses, which then lead to increase the susceptibility to infection. [39] In addition, in winter in Jinan, the citywide coal-burning heating exacerbates smog, which would increase the number of carriers that can spread pathogens [20] and increase the risk of RD; Liu [23] provided the evidence that heavy pollution are positively correlated with TB incidence. Furthermore, Naranbat [13] hypothesized that temperature may change the time people spend at home or outside. China is a populous country, people gather, and close door and windows during the cold winter, and the crowded indoor environment is also a risk factor for infectious diseases. As the temperature gradually increases with an agreeable weather, citizens were more willing to play outside and open the window for ventilation. Meanwhile, the heat of the summer might trigger a thermal reaction, but it also comes with a reluctance to congregate for residents, preferring to stay indoors with air conditioning. Which may not induce the high risk of transmission of tuberculosis as cold temperature do.
We found some evidence of harvesting effect in our study; there was an incidence deficit for the minimum and the 5th percentile Tmean at the lag about 3 weeks. We speculate that the harvesting effect would support the mechanism of temperature influencing the incidence risk. In particular, it may be that presents in extreme cold temperature only hasten the TB incidences of individuals in a small, frail, infected subset of the population who will attack even in the absence of extreme cold effect. A possible reason is extreme cold air attacks the body's respiratory and immune systems, speeding up the onset of TB to infected people. In contrast, hot temperature might mainly disturb the body's cardiovascular system, and has little direct effect on the respiratory system. [40]
However, meteorological factors may play an important role. Our findings showed that low RH decreased the risk of TB for temperature which was different from Yingjie Zhang’s research[41]. In cold temperature situation, the increased RH may create a suitable environment for the growth and reproduction of tuberculosis. Our study also suggested that low WS could increase the effect of low Tmean on TB at the current day and at lag 70. The higher WS could accelerate ventilation, dilute the concentration of bacteria and help reduce the risk of becoming infected. Although another study [18] indicated that areas with stronger wind speeds tend to have a higher infection risk, our study findings were supported by the findings of Kai Cao[42]. As has been found in a few other studies [17, 42, 43], the low SD would raise the risk of TB. Our findings showed that the low level of SD positively modified on cold temperature effect. We speculate that this result would be also related to some view point indicated by these studies [44, 45] on TB that low serum vitamin D levels were associated with higher risk of active tuberculosis. The low SD would affect the absorption of vitamin D for public. However, there was still a lack of validation of biological mechanisms of vitamin D on TB, which should be a further direction.
A study limitation is the use of data on temperature and air pollution from fixed monitoring sites rather than measuring individual exposure, which would bring about measurement errors because individual exposure temperature may be not entirely identify with outdoor average temperature. Secondly, cold effect and hot effect was calculated by comparing the 5th to the 25th percentile and the 95th to the 75th percentile temperatures. This accounted for the effect of cold and hot temperature to some extent. But the reason for this way is that the study population is not sensitive to Tmean ranging from the 25th to the 75th percentile, there may be inappropriateness when extrapolating calculating method to an unequal population or other diseases. Because the complexity of other factors and the difference of population adaptation. In addition, we only used data from Jinan to examine the effects of temperature on incidence of TB so the findings may not be generalizable to other areas.
In conclusion, tuberculosis incidence in Jinan was found to be nonlinear and negative related with temperature, with a harvesting effect for cold temperature. Findings of this study add to the evidence that high temperatures have slower delayed effects on TB incidence while low temperatures appear to exhibit higher effects. Temperature may determine the amount of time spent indoors and affect the ability of bacteria to survive, and thus the transmissibility of Mycobacterium tuberculosis. Results also suggest that considering effect modification by RH, WS and SD in assessing temperature effects on TB incidence may be essential. These findings may have important implications for public health officials to control and prevent the TB risk of exposure to ambient temperature. Meanwhile, the public are also suggested to keep clear life environment, ventilate usually and supplement Vitamin D. Although China has achieved the 2015 global TB control goal, still a million incident TB cases are reported annually. [10] Exploring the influencing factor and mechanism of TB can shed light on future TB control programs in China and even other country.