Extreme temperatures and cardiovascular mortality: assessing effect modification by subgroups in Ganzhou, China

Figures & data

Figure 1. The city (in black) into this research

Table 1. Summary statistics of meteorological data and air pollution (mean (SD)), mortality (mean (%)) from cause-specific cardiovascular diseases and individual characteristics, in Ganzhou during

Variables	Mean		Min	P25	P50	P75	Max
Meteorological data
MinT(°C)	17.2	(7.7)	−3.0	10.4	18.6	24.3	30.0
MeanT (°C)	20.4	(8.0)	1.0	13.6	21.9	27.5	33.0
MaxT(°C)	25.0	(8.8)	1.7	18.0	26.7	32.6	39.0
Relative humidity (%)	76.4	(12.0)	36.0	67.0	77.0	86.0	99.0
Air pressure (hPa)	998.6	(7.9)	980.7	992.1	998.3	1004.7	1024.4
Air pollution
PM2.5 (ug/m^3)	40.7	(20.3)	7.0	27.0	36.0	51.0	180.0
PM10 (ug/m^3)	63.4	(32.6)	12.0	40.3	55.0	79.0	250.0
SO2 (ug/m^3)	22.4	(13.2)	3.0	13.0	19.0	28.0	110.0
NO2 (ug/m^3)	23.8	(12.4)	8.0	15.0	20.0	29.0	84.0
CO (mg/m^3)	1.3	(0.3)	0.6	1.1	1.3	1.5	3.0
O3 (ug/m^3)	59.4	(25.5)	5.0	41.0	57.0	75.0	167.0
Cause-specific mortality
CVD	57	(100.0)	14	44	54	67	142
HPD	11	(19.3)	0	8	10	13	33
IHD	16	(28.1)	3	12	16	20	46
CBD	25	(43.9)	1	19	24	37	72
Gender
Males	31	(54.4)	7	24	30	37	87
Females	26	(45.6)	4	19	24	31	68
Marital status
Unmarried	16	(28.1)	1	12	15	19	52
Married	41	(71.9)	9	31	39	48	100
Age
<65 years	12	(21.1)	1	9	11	15	39
≥65 years	45	(78.9)	8	34	43	53	120

2015 to 2019.

Note: MeanT: daily mean temperature; P25, 25th percentile; P50, 50th percentile; P75, 75th percentile;

Figure 2. Three-dimensional graph of the relative risks of cardiovascular mortality by daily mean temperature (°C) days and lag days, during 2015–2019. The relative risks for mortality of types of CVD and individual characteristics. The relative risks used eight of degree of freedom for time trend and daily mean temperature for temperature indicator. The reference temperature was the median temperature during the study period

Table 2. The cumulative cold effects on lag 0, 0–7, 0–14, 0–21 days from cause-specific cardiovascular disease and individual characteristics

	lag 0	lag 0–7	lag 0–14	lag 0–21
Cause-specific mortality
CVD	0.992 (0.927–1.061)	1.195 (1.039–1.376)*	1.341 (1.108–1.622)*	1.384 (1.087–1.764)*
HPD	0.967 (0.864–1.082)	1.357 (1.072–1.716)*	1.402 (1.019–1.928)*	1.389 (0.926–2.083)
IHD	1.019 (0.927–1.121)	1.165 (0.955–1.421)	1.324 (1.012–1.732)*	1.332 (0.947–1.873)
CBD	0.973 (0.894–1.060)	1.160 (0.972–1.385)	1.327 (1.043–1.687)*	1.428 (1.051–1.940)*
Gender
Males	1.028 (0.951–1.111)	1.347 (1.145–1.585)*	1.671 (1.341–2.082)*	1.798 (1.358–2.381)*
Females	0.948 (0.871–1.032)	1.034 (0.867–1.233)	1.022 (0.805–1.298)	1.005 (0.743–1.361)
Marital status
Unmarried	0.937 (0.850–1.032)	1.115 (0.911–1.365)	1.148 (0.873–1.510)	1.091 (0.769–1.546)
Married	1.011 (0.940–1.088)	1.223 (1.050–1.423)*	1.421 (1.157–1.745)*	1.539 (1.185–2.000)*
Age
<65 years	1.027 (0.921–1.145)	1.193 (0.949–1.499)	1.567 (1.152–2.132)*	1.641 (1.106–2.434)*
≥65 years	0.983 (0.914–1.057)	1.197 (1.029–1.391)*	1.289 (1.051–1.582)*	1.328 (1.024–1.722)*

*p < 0.05.

Figure 3. The relationship between mean temperature and the mortality of types of CVDs and individual characteristics and over lag 0–21 days, during 2015–2019. The green lines are the maximum likelihood estimate of relative risks, and the gray regions are 95% CIs. The solid line marks RR at 1

Figure 4. RRs showing the effect modification by various mortality subgroups at the 1st, 5th, 95th, and 99th temperature percentiles