基于加权延迟效应的某农村地区气温与冠心病关联性

李刚刚; 朱清; 雷苗; 刘瑞芳; 翁俊; 韩晓丽; 崔旭东; 张本忠; 裴泓波; 任晓卫

doi:10.16462/j.cnki.zhjbkz.2019.06.010

基于加权延迟效应的某农村地区气温与冠心病关联性

doi: 10.16462/j.cnki.zhjbkz.2019.06.010

1.
730000 兰州, 兰州大学公共卫生学院流行病与卫生统计学研究所
2.
730000 兰州, 兰州大学公共卫生学院劳动卫生与环境卫生学研究所

基金项目:

甘肃省卫生行业科研计划项目 2015-94-GSWSKY

详细信息

通讯作者:
任晓卫, E-mail: renxw@lzu.edu.cn

中图分类号: R181.22
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出版历程
- 收稿日期: 2018-12-04
- 修回日期: 2019-04-01
- 刊出日期: 2019-06-10

Study on the association between ambient temperature and coronary heart disease in rural area based on weighted delay effect

1.
Institute of Epidemiology and Health Statistics, School of Public Health, Lanzhou University, Lanzhou 730000, China
2.
Institute of Occupational and Environmental Health, School of Public Health, Lanzhou University, Lanzhou 730000, China

Funds:

Health Research Project of Gansu Provincial 2015-94-GSWSKY

More Information

Corresponding author: REN Xiao-wei, E-mail: renxw@lzu.edu.cn

摘要

摘要: 目的探讨气温指标与冠心病发病的关联，为冠心病的防治提供参考。方法利用2010-2016年庆阳农村地区冠心病及气象数据，在考虑气象因素对冠心病发病的短期相关性和滞后效应基础上，构建加权指标估计延迟效应分布，采用广义相加模型分性别、年龄段探讨加权气温指标与冠心病发病的关联。结果庆阳农村地区各气温指标对65岁以上男性人群冠心病发病影响均具有统计学意义(均有P < 0.05)，加权24 h变温的效应最大，加权24 h变温每增加1℃，发病风险增大8.775%(95%CI：4.630%~13.084%)；各人群冠心病发病对加权24 h变温均敏感(均有P < 0.05)，且在65岁以上男性、65岁以下男性、65岁以上女性和65岁以下女性四个人群中，其效应值依次递减；加权最高气温和加权气温日较差仅在65岁以上人群中有效应，且男性人群效应高于女性。结论温度变化对冠心病发病影响最大，无论是骤冷或是骤热，均会增加冠心病发病风险。65岁以上男性人群冠心病发病对气温变化更敏感，且冠心病人次与气温指标有明显的短期相关性。
- 气温 /
- 冠心病 /
- 加权延迟效应 /
- 广义相加模型
Abstract: Objective To explore the relationship between temperature and the incidence of coronary heart disease, so as provide reference for early prevention and treatment of coronary heart disease. Methods Using the coronary heart disease and meteorological data of rural in Qingyang from 2010 to 2016, based on the short-term correlation and hysteresis effect of meteorological factors on the incidence of coronary heart disease, the weighted indicator was used to estimate the delay effect distribution, and the generalized additive model was used to analyze the relationship between weighted temperature indicators and the incidence of coronary heart disease by gender and age group. Results The temperature indicators in rural areas of Qingyang had significant effects on the incidence of coronary heart disease in males over 65 years old (All P < 0.05), and the effect of weighted 24 h temperature change was the largest. For every 1℃ increase in weighted 24 h temperature change, the risk of disease increased by 8.775% (95% CI: 4.630%-13.084%). The incidence of coronary heart disease in all populations was sensitive to weighted 24 h temperature change (All P < 0.05), and in the four groups of men over 65 years old, men under 65, women over 65 and women under 65, the effect value decreases in turn. The weighted maximum temperature and diurnal temperature range were only significant in people over 65 years old, and the male population effect was higher than women. Conclusions Temperature change has the greatest impact on the incidence of coronary heart disease. Whether it is sudden heat or cold, it will increase the risk of coronary heart disease. The temperature indicator has a significant impact on the daily incidence of coronary heart disease among males over 65 years old, and the short-term correlation of temperature indicators is obvious.
- Ambient temperature /
- Coronary heart disease /
- The weighted hysteresis effect /
- The generalized additive model

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图 1 各气象指标不同滞后天数(lag0~lag7)对各人群冠心病发病影响的权重

Figure 1. Weights of different lag days (lag0-lag7) of various meteorological indicators on the incidence of coronary heart disease

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图 2 加权气温指标对冠心病逐日入院人次的暴露反应关系图(≥65岁男性)

Figure 2. Diagram of exposure response of weighted temperature indicators to daily admission to coronary heart disease (≥65, male)

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表 1 2010-2016年庆阳农村地区气象因素基本情况

Table 1. Basic situation of meteorological factors in rural areas from 2010 to 2016

气象因素	x±s	极小值	P₂₅	P₅₀	P₇₅	极大值
平均气温	9.922±9.904	-15.900	1.300	11.300	18.825	28.250
24 h变温	0.000±2.013	-11.250	-1.100	0.200	1.330	6.800
最高温度	15.895±10.157	-10.850	7.300	17.450	24.600	34.700
最低温度	5.240±9.874	-21.200	-3.350	6.300	14.050	23.050
日较差	10.655± 4.138	1.000	7.625	10.800	13.700	23.450
相对湿度	58.350±19.781	11.000	43.000	58.000	74.500	99.000
平均气压	86.702± 0.543	85.290	86.280	86.675	87.105	88.700

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表 2 冠心病逐日入院数及气象因素的相关关系

Table 2. Correlation between the number of daily admissions to coronary heart disease and meteorological factors

	人次	平均温度	24 h变温	日较差	相对湿度	平均气压	最高温度
平均温度	0.021
24 h变温	0.093^a	0.098^a
日较差	0.151^a	0.064^a	0.431^a
相对湿度	-0.173^a	0.171^a	-0.205^a	-0.657^a
平均气压	-0.082^a	-0.750^a	-0.162^a	-0.096^a	-0.089^a
最高温度	0.050^a	0.977^a	0.167	0.257^a	0.042	-0.743^a
最低温度	-0.019	0.971^a	-0.014	-0.155^a	0.330^a	-0.717^a	0.909^a
注：^a表示P＜0.05。

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表 3 2010-2016年庆阳农村地区加权气温指标对冠心病发病的影响

Table 3. Impact of weighted temperature indicators on the incidence of coronary heart disease from 2010 to 2016

		加权指标	β值	P值	RR(95% CI)值	ER(95% CI)值
男	≥65岁	平均气温	0.014	< 0.001	1.014(1.008~1.020)	1.398(0.823~1.977)
		最高气温	0.013	< 0.001	1.013(1.008~1.019)	1.345(0.810~1.884)
		最低气温	0.014	< 0.001	1.014(1.008~1.021)	1.435(0.817~2.056)
		24小时变温	0.084	< 0.001	1.088(1.046~1.131)	8.775(4.630~13.084)
		日较差	0.024	0.003	1.024(1.008~1.041)	2.430(0.822~4.064)
	< 65岁	平均气温	0.006	0.132	1.006(0.998~1.014)	0.608(-0.182~1.405)
		最高气温	0.005	0.194	1.005(0.998~1.012)	0.478(-0.242~1.203)
		最低气温	0.007	0.124	1.007(0.998~1.015)	0.667(-0.182~1.522)
		24小时变温	0.072	0.003	1.074(1.024~1.127)	7.434(2.427~12.686)
		日较差	-0.000	0.989	1.000(0.981~1.019)	-0.014(-1.917~1.926)
女	≥65岁	平均气温	0.007	0.083	1.007(0.999~1.014)	0.661(-0.086~1.414)
		最高气温	0.008	0.023	1.008(1.001~1.014)	0.774(0.108~1.445)
		最低气温	0.006	0.149	1.006(0.998~1.014)	0.584(-0.208~1.382)
		24小时变温	0.066	< 0.001	1.068(1.036~1.102)	6.848(3.637~10.159)
		日较差	0.013	0.044	1.013(1.000~1.026)	1.300(0.037~2.579)
	< 65岁	平均气温	-0.006	0.211	0.994(0.984~1.004)	-0.623(-1.591~0.354)
		最高气温	-0.004	0.305	0.996(0.987~1.004)	-0.448(-1.298~0.410)
		最低气温	-0.007	0.208	0.993(0.983~1.004)	-0.669(-1.703~0.376)
		24小时变温	0.056	0.004	1.057(1.018~1.098)	5.723(1.754~9.846)
		日较差	0.000	0.988	1.000(0.984~1.016)	0.013(-1.583~1.635)
注：模型控制了相对湿度、平均气压，加入了节假日和星期效应，分别引入了平均气温、最高气温、最低气温、24小时变温、气温日较差。

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