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Table 6 Stratification results of the temperature-physical activity associations in five Chinese cities

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

City

Stratification

OptTa

OptT – 10 °C

Change in steps

95% CI

Sig.

OptT

+ 10 °C

Change in steps

95% CI

Sig.

BJ

Male

20.0

10.0

− 344.9

− 453.2, − 236.6

*

29.9

− 353.4

−614.0, − 92.7

*

Female

18.7

8.7

− 339.2

− 456.4, − 222.0

*

28.7

−405.4

−641.1, − 169.6

*

18-64

19.3

9.3

− 344.1

−453.0, − 235.2

*

29.3

− 383.8

− 624.1, − 143.5

*

65+

16.5

6.5

− 314.9

− 517.0, − 112.8

*

26.5

− 466.4

− 762.7, − 170.1

*

SH

Male

18.6

8.6

− 249.6

− 422.6, −76.5

*

28.6

− 427.4

− 656.2, − 198.7

*

Female

17.3

7.3

− 250.6

−427.5, −73.7

*

27.3

− 418.7

− 609.1, − 228.4

*

18-64

18.0

8.0

−251.9

−422.1, −81.8

*

28.0

−430.1

−635.1, − 225.1

*

65+

13.5

3.5

− 318.6

− 657.2, 20.1

 

23.5

− 501.3

−708.4, − 294.2

*

CQ

Male

18.0

8.0

16.1

−200.4, 232.6

 

28.0

− 336.2

− 551.6, −120.9

*

Female

15.6

5.6

−76.6

−383.3, 230.1

 

25.6

− 376.7

− 589.0, − 164.5

*

18-64

16.2

6.2

−20.4

− 289.2, 248.4

 

26.2

− 327.2

− 533.0, − 121.4

*

65+

20a

10.0

−2.4

− 292.9, 288.2

 

30.0

− 1541.8

− 1927.0, − 1156.7

*

SZ

Male

24.3

14.3

− 291.8

− 536.9, −46.6

*

30.8b

− 185.8

− 486.0, 114.5

 

Female

23.5

13.5

−338.1

−629.9, −46.4

*

30.8b

− 242.2

− 571.0, 86.5

 

18-64

24.2

14.2

− 350.8

− 613.5, −88.0

*

30.8b

− 203.5

− 513.1, 106.0

 

65+

22.5

12.5

− 487.5

− 903.1, −71.9

*

30.8b

− 462.4

− 901.8, −23.0

*

HK

Male

20a

10.0

−4.5

− 312.7, 303.7

 

30.0

− 128.9

− 281.8, 24.1

 

Female

20a

10.0

−3.4

− 358.4, 351.6

 

30.0

−96.7

− 272.9, 79.5

 

18-64

20a

10.0

−3.6

− 333.1, 325.8

 

30.0

−104.0

− 267.5, 59.5

 

65+

17.1

9.0 b

−41.6

− 348.9, 265.7

 

27.1

− 193.2

− 290.1, −96.4

*

  1. BJ Beijing, SH Shanghai, CQ Chongqing, SZ Shenzhen, HK Hong Kong, OptT optimal temperature, CI confidence interval. 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)
  2. aWhere association was not curvilinear, the optimal temperature was pre-set to 20 °C
  3. bThe upper or lower limit of temperature was reached for that city’s dataset. The upper limit of temperature in the Shenzhen dataset was at 30.8 °C. The lower limit of temperature in Hong Kong was at 9.0 °C
  4. * p ≤ 0.05 indicates significant difference