The effect of temperature on physical activity: an aggregated timeseries analysis of smartphone users in five major Chinese cities

Table 5 Mean temperature associations on daily average step count, by city

City	Beijing	Shanghai	Chongqing	Shenzhen	Hong Kong
Optimal temperature	19.3	17.9	16.1	24.2	20 ^a
Change in steps at OptT - 10 °C (95% CI)	− 342.8 * (− 452.2, − 233.4)	− 251.6 * (− 423.0, − 80.1)	− 19.1 (− 293.1, 254.9)	− 351.7* (− 614.8, − 88.6)	−3.0 (− 331.8, 325.8)
Change in steps at OptT + 10 °C (95% CI)	−386.0 * (− 626.6, − 145.5)	−432.7 * (− 636.2, − 229.1)	−321.7 * (− 526.6, − 116.8)	−204.8 ^b (− 514.5, 104.8)	−105.4 (− 268.5, 57.6)
N	366	366	366	361	391
Adjusted R squared	0.88	0.86	0.86	0.80	0.73
AIC	4828.1	4856.0	4931.6	4795.1	5365.2

BJ Beijing, SH Shanghai, CQ Chongqing, SZ Shenzhen, HK Hong Kong, OptT optimal temperature, CI confidence interval, AIC Akaike information criterion. The model for each city was adjusted for relative humidity#, precipitation, windspeed, pressure#, sunshine, AQI/AQHI, month, day of week, public holiday, extra workdays, typhoon, super typhoon, and marathon (#some cities had these variables removed in the stepdown process)
^aWhere association was not curvilinear, the optimal temperature was pre-set to 20 °C
^bA change from 30.8 °C was used for Shenzhen, since this was the upper limit of temperature data in the city
* p ≤ 0.05 indicates significant difference

ISSN: 1479-5868