Because of the snow and cold effect on winter counts, it is required to apply the adjustment factors to improve the accuracy of winter SDCs.
However, high RRs were observed for mortality at low temperature with the 0 21 days' lag, meaning that the cold effect took place relatively slowly and could last 3 weeks.
According to the sensitivity test of different lag days, in this study we quantified the "heat effect" as the extreme heat-related mortality risk with 0 3 lag days; and we used the models with lags of 0 21 days to calculate the extreme cold-related mortality risk as the "cold effect".
With 0 21 days' lag, the cold effect was pronounced in all city clusters, with the highest extreme cold-related mortality risk found in the PRD area (RR = 2.27; 95% CI: 1.63 3.16), followed by the YRD area (RR = 1.85; 95% CI: 1.56 2.20) and BTH region (RR = 1.33; 95% CI: 0.96 1.83).
In our study, the cold effect appeared more obvious than the heat effect in all city clusters (Table 2), and was consistent with the results of Anderson and Bell (2009), Guo et al. (2013), and Ma, Wang et al.. Therefore, considering the high sensitivity of population to cold stress, more attention should be paid to both types of extreme events, rather than only heat waves.
The cold effect has been somewhat less studied, although there are hints that being uncomfortably chilly can contribute to conflict in some situations and quell it in others.
To show the effect of cold on the skin, filters were gradually drawn over the lights on the set, revealing the "cold effect" makeup.
However, no cold effect was observed in their study.
Studies using short lags may have underestimated the cold effect: in our results, the estimated cold effect was delayed by 3 days and lasted for 10 days.
Little modification of the cold effect by sex was observed in England and Wales (44).
4 16 45 The higher cold effect in southern areas may suggest the evidence for acclimatisation.
