机构地区:[1]国家卫生健康委职业安全卫生研究中心,北京102308 [2]中国疾病预防控制中心职业卫生与中毒控制所,北京100050 [3]北京市职业病防治研究院,北京100093 [4]北京大学公共卫生学院,北京100191 [5]北京市科学技术研究院城市安全与环境科学研究所,北京100054
出 处:《环境与职业医学》2021年第12期1301-1306,共6页Journal of Environmental and Occupational Medicine
基 金:北京市科研院改革发展项目(BJAST-RDBMILP202108)。
摘 要:[背景]日光温室作业人员劳动时间长,光照条件复杂多变,其屈光参差问题值得关注。[目的]探讨日光温室作业与种植人员屈光参差的关系。[方法]从西北某地区选取温室组和非温室组研究对象,通过问卷调查收集其一般人口学信息。使用GB 11 533—2011《标准对数视力表》测量研究对象工前双侧裸眼视力,计算视力差值绝对值并转化为分类变量,比较温室组与非温室组之间差异。根据温室作业从业时间和拥有温室数量引入累积暴露指数,将温室组人群分为低、中、高三个累积暴露水平进行组间比较。采用广义线性模型和logistic回归模型分析日光温室作业与屈光参差的关系。[结果]本研究共纳入研究对象1 002名,其中温室组739人,非温室组263人。温室组和非温室组屈光参差[M(P_(25),P_(75))]分别为0.1(0,0.2)和0(0,0.1),差异具有统计学意义(P <0.05);温室组屈光参差=0、≤0.2和> 0.2的构成比分别为34.2%、55.2%和10.6%,非温室组构成比分别为58.2%、34.6%和7.2%,两组间分布的差异有统计学意义(P <0.05)。依据累积暴露指数,温室组低、中、高累积暴露水平的人数(构成比)分别为154(21.0%)、188(25.6%)和392(53.4%),三组间屈光参差水平的差异无统计学意义(P> 0.05)。多因素广义线性模型结果显示,日光温室作业与屈光参差有关(b=0.053,P <0.05),多因素logistic回归分析结果显示,日光温室作业与屈光参差风险增加有关(OR=2.586,95%CI:1.473~4.539)。对温室组进行多因素广义线性模型分析,在校正了年龄、性别等因素后,与累积低水平暴露相比,中水平暴露与屈光参差程度增加有关(b=0.054,P <0.05)。[结论]从事日光温室作业可能是种植人员屈光参差增大的危险因素。[Background] Due to long working time and complex and changeable lighting conditions,greenhouse workers’ anisometropia is an issue of concern.[Objective] This study is conducted to evaluate the relationship between solar greenhouse working and anisometropia of workers.[Methods] Subjects of a solar greenhouse group and a non-greenhouse group in northwest area of China were selected. Questionnaire survey was used to collect general demographic information. Standard Logarithmic Visual Acuity Chart(GB 11 533—2011) was used to measure naked eye vision before working, the absolute value of binocular visual acuity difference was calculated and converted into classification variables, and both anisometropia absolute value and classification variables of anisometropia were used as indicators to compare the difference of the two groups. A cumulative exposure index that multiplies exposure time and number of greenhouses was further introduced to evaluate cumulative exposure levels of the greenhouse workers and was used to divide them into low, medium, and high cumulative exposure subgroups. Generalized linear model and logistic regression model were used to analyze possible risk factors associated with anisometropia.[Results] A total of 1 002 subjects were enrolled in this study, including 739 workers in the greenhouse group and 263 workers in the non-greenhouse group. The medians(interquartile intervals) of anisometropia of the greenhouse group and non-greenhouse group were0.1(0, 0.2) and 0(0, 0.1) respectively, and the difference was statistically significant(P < 0.05). The proportions of anisometropia=0,≤0.2, and > 0.2 in the greenhouse group were 34.2%, 55.2%, and 10.6%, respectively, and those in the non-greenhouse group were58.2%, 34.6%, and 7.2%, respectively. The difference of anisometropia distribution between the two groups was statistically significant(P < 0.05). According to the cumulative exposure index, the greenhouse group was divided into low, medium, and high cumulative exposure subgroups, with 154(21
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