Environmental Health Sciences Division, School of Public Health, University of California at Berkeley, California 94720-7360, USA.
Environ Health Perspect. 2009 Nov;117(11):1730-6. doi: 10.1289/ehp.0900683. Epub 2009 Jun 10.
The evidence that heat waves can result in both increased deaths and illness is substantial, and concern over this issue is rising because of climate change. Adverse health impacts from heat waves can be avoided, and epidemiologic studies have identified specific population and community characteristics that mark vulnerability to heat waves.
We situated vulnerability to heat in geographic space and identified potential areas for intervention and further research.
We mapped and analyzed 10 vulnerability factors for heat-related morbidity/mortality in the United States: six demographic characteristics and two household air conditioning variables from the U.S. Census Bureau, vegetation cover from satellite images, and diabetes prevalence from a national survey. We performed a factor analysis of these 10 variables and assigned values of increasing vulnerability for the four resulting factors to each of 39,794 census tracts. We added the four factor scores to obtain a cumulative heat vulnerability index value.
Four factors explained > 75% of the total variance in the original 10 vulnerability variables: a) social/environmental vulnerability (combined education/poverty/race/green space), b) social isolation, c) air conditioning prevalence, and d) proportion elderly/diabetes. We found substantial spatial variability of heat vulnerability nationally, with generally higher vulnerability in the Northeast and Pacific Coast and the lowest in the Southeast. In urban areas, inner cities showed the highest vulnerability to heat.
These methods provide a template for making local and regional heat vulnerability maps. After validation using health outcome data, interventions can be targeted at the most vulnerable populations.
热浪会导致死亡和疾病增加,这方面的证据确凿,而且由于气候变化,人们对这一问题的担忧正在加剧。可以避免热浪对健康造成的不利影响,并且流行病学研究已经确定了特定的人口和社区特征,这些特征标志着易受热浪影响的脆弱性。
我们将脆弱性定位在地理空间中,并确定了潜在的干预和进一步研究的区域。
我们绘制并分析了美国与热相关的发病率/死亡率的 10 个脆弱性因素:美国人口普查局的 6 个人口统计学特征和 2 个家庭空调变量、卫星图像的植被覆盖和全国调查的糖尿病患病率。我们对这 10 个变量进行了因子分析,并为这四个由此产生的因素中的每一个分配了 39794 个普查区的脆弱性增加值。我们将这四个因素得分相加,得出一个累积热脆弱性指数值。
四个因素解释了原始 10 个脆弱性变量总方差的>75%:a) 社会/环境脆弱性(综合教育/贫困/种族/绿地),b) 社会隔离,c) 空调普及率,d) 老年/糖尿病比例。我们发现全国范围内的热脆弱性存在很大的空间变异性,东北部和太平洋沿岸的脆弱性通常较高,东南部的脆弱性最低。在城市地区,市中心地区对热的脆弱性最高。
这些方法为制作当地和地区热脆弱性地图提供了模板。使用健康结果数据进行验证后,可以针对最脆弱的人群进行干预。