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目的明确广东省高温热浪期间发生中暑的脆弱人群,为采取措施保护该人群提供科学依据。方法于2010年9—11月采用4阶段分层整群抽样的方法在广东省内抽取5个市,每市抽取1个县及区,每个县区抽取6个片区,每片区抽取50户,对每户随机选出1名15～69岁居民进行入户面对面询问调查,调查内容包括一般人口学特征、社会经济状况、热浪相关知识和适应行为。采用2检验、非条件logistic回归分析广东省居民发生中暑的影响因素。结果共调查2 183人,平均年龄为(39.31±14.16)岁,其中男性占53.37%(1 165/2 183),城市居民占48.74%(1 064/2 183)。总体中暑发生率为6.8%(149/2 183)。不同社会经济状况(包括职业、地区和收入)人群中暑发生率不同(P﹤0.05),农林牧渔业(11.4%,58/507)、农村(10.1%,113/1 119)、月收入<1 000元(11.2%,75/671)居民中暑发生率最高。所有调查对象对健康风险认知平均得分为(4.21±1.47)分(得分范围1～7),对热浪的知晓率为38.11%(832/2 183),对热浪的平均适应得分为(4.80±2.39)分(得分范围0～9)。Logistic回归结果显示农林牧渔业和离退休人员发生中暑的风险分别高于其他职业(OR=2.40、2.32),农村居民发生中暑的风险高于城市居民(OR=2.62),人均月收入<1 000元的居民发生中暑的风险高于收入≥10 000元人群(OR=2.48)。结论高温热浪期间广东省居民中暑发生率较高,农村及社会经济状况低下的人群是中暑的脆弱人群,需要重点加以保护。
Objective To clarify the vulnerable population of heat stroke during high temperature and heat wave in Guangdong Province and provide a scientific basis for taking measures to protect this population. Methods From September to November in 2010, 5 cities were sampled in Guangdong province by using four-stage stratified cluster sampling method. One county and district were taken from each city, and six districts were extracted from each county. Fifty households , A randomly selected household from 15 to 69 residents to conduct a face-to-face interrogation survey, the survey includes general demographic characteristics, socio-economic status, heat wave-related knowledge and adaptive behavior. Using χ2 test, non-conditional logistic regression analysis of factors affecting the occurrence of heat stroke in Guangdong residents. Results A total of 2 183 people were surveyed, with an average age of (39.31 ± 14.16) years, of whom 53.37% were male (1 165/2 183) and 48.74% (1064/2 183) were urban residents. The overall rate of heat stroke was 6.8% (149/2 183). The incidence of heat stroke in different socioeconomic status (including occupation, region and income) was different (P <0.05), and that of agriculture, forestry, animal husbandry and fishery (11.4%, 58/507) and rural areas (10.1%, 113/1 119) 1 000 yuan (11.2%, 75/671) residents had the highest incidence of heat stroke. All respondents reported an average score of 4.21 ± 1.47 (range 1 ~ 7) for health risk, 38.11% (832/2 183) for heatwave, and (4.80 ± 2.39) points (score range 0 ~ 9). Logistic regression showed that the risk of heat stroke was higher in HFCs and retired workers than those in other occupations (OR = 2.40 and 2.32, respectively). The risk of heat stroke among rural residents was higher than that of urban residents (OR = 2.62) The risk of sunstroke was higher for residents with $ 000 than for those with income> 10,000 yuan (OR = 2.48). Conclusion The incidence of heat stroke among residents in Guangdong province during high temperature and heat wave period is relatively high. People in rural areas and those with low social and economic status are the vulnerable people with stroke, and need to be protected emphatically.