普通人群有机氯农药暴露与心血管疾病风险的关联研究

Associations between organochlorine pesticide exposure and cardiovascular disease risk in the general population

摘要

目的：探讨普通人群中有机氯农药（organochlorine pesticides，OCPs）与心血管疾病（cardiovascular disease，CVD）之间的相关性。方法：采用横断面设计，选取2005-2016年美国国家健康与营养调查中符合纳入和排除标准的6 009例普通居民作为研究对象。收集研究对象的一般资料、体格检查和实验室检查指标，纳入7种OCPs，包括β-六氯环己烷（β-hexachlorocyclohexane，β-HCH）、六氯苯（hexachlorobenzene，HCB）、氧化氯丹（oxychlordane，OXY）、反式九氯（trans-nonachlor，T-NONA）、二氯二苯基二氯乙烯[2,2-Bis（4-chlorophenyl)-1,1-dichloroethene，p,p'-DDE]、二氯二苯基三氯乙烷[2,2-Bis（4-chlorophenyl）-1,1,1-trichloroethane，p,p'-DDT]和灭蚁灵（Mirex），并根据是否患CVD将研究对象分为正常组5 499例和CVD组510例。采用多因素logistic回归及限制性立方样条（restricted cubic spline，RCS）模型分析人群中单一OCPs暴露与CVD风险之间的相关性。使用贝叶斯核机器回归（Bayesian kernel machine regression，BKMR）和分位数-g运算（quantile g-computation，Qgcomp）模型进一步分析OCPs联合暴露与CVD风险的关联。结果：多因素logistic回归结果显示，调整混杂因素后，β-HCH、OXY、T-NONA、p,p'-DDE和Mirex浓度升高可增加CVD风险（P＜0.05），与第一分位数浓度相比，β-HCH、OXY、T-NONA、p,p'-DDE和Mirex在第四分位数浓度时CVD风险分别增加3.19、2.96、6.26、2.40和1.89倍。RCS模型显示，β-HCH、OXY、T-NONA和Mirex与CVD风险存在非线性剂量反应关系（P＜0.05）。BKMR模型结果显示，OCPs混合物与CVD风险具有正向联合效应，其中OXY可能是主要贡献物质之一；当其他OCPs浓度固定在第25、50和75百分位数时，OXY与CVD风险存在正相关关系；OXY和β-HCH、OXY和p,p'-DDE、OXY和Mirex之间可能存在交互作用。Qgcomp模型验证了BKMR的稳定性与真实性，仅p,p'-DDE具有负向效应，正向权重排序依次为OXY、T-NONA、Mirex和β-HCH。结论：OCPs混合暴露与CVD风险升高有关，OXY是驱动此关联的主要成分，提示OXY可能是CVD风险升高的独立危险因素。

Abstract

Objective: To explore the associations between organochlorine pesticides (OCPs) and cardiovascular disease (CVD) in the general population. Methods: A cross-sectional study was adopted, and 6,009 residents who met the inclusion and exclusion criteria from the National Health and Nutrition Examination Survey (NHANES) (2005-2016) were enrolled. General data, physical examination, and laboratory test results were collected from the participants. Seven types of OCPs were analyzed, including β-hexachlorocyclohexane (β-HCH), hexachlorobenzene (HCB), oxychlordane (OXY), trans-nonachlor (T-NONA), 2,2-Bis (4-chlorophenyl)-1,1-dichloroethene (p,p'-DDE), 2,2-Bis(4-chlorophenyl)-1,1,1-trichloroethane (p,p'-DDT) and Mirex. The participants were divided into a control group (n=5,499) and a CVD group (n=510) according to the presence or absence of CVD. Multivariate logistic regression analysis and restricted cubic spline (RCS) models were used to analyze the associations between individual exposure to OCPs and CVD risk in the population. The associations between the joint exposure to OCPs and CVD risk were further analyzed using Bayesian kernel machine regression (BKMR) and quantile g-computation (Qgcomp) models. Results: Results from the multivariate logistic regression analysis showed that, after adjusting for confounders, elevated concentrations of β-HCH, OXY, T-NONA, p,p'-DDE and Mirex were associated with an increased risk of CVD (P＜0.05). Compared with the first quartile of concentration, the CVD risk associated with β-HCH, OXY, T-NONA, p,p'-DDE and Mirex at the fourth quartile concentration increased by 3.19-fold, 2.96-fold, 6.26-fold, 2.40-fold and 1.89-fold, respectively. The RCS model revealed non-linear dose-response relationships between β-HCH, OXY, T-NONA, Mirex and CVD risk (P＜0.05). The results from the BKMR model indicated a positive joint effect of OCPs mixture on CVD risk, with OXY likely being one of the major contributors. When the concentrations of other OCPs were fixed at the 25th, 50th, and 75th percentiles, OXY was positively associated with CVD risk. Additionally, potential interactions were observed between OXY and β-HCH, OXY and p,p'-DDE, as well as OXY and Mirex. The Qgcomp model verified the stability and validity of the BKMR, with only p,p'-DDE exerting a negative effect. The positive weights were observed in the following order: OXY, T-NONA, Mirex, and β-HCH. Conclusion: Joint exposure to OCPs is associated with an increased risk of CVD. OXY is the major component driving the associations, suggesting that it may serve as an independent risk factor for increased CVD risk.

关键词

心血管疾病 / 有机氯农药 / 普通人群 / 暴露-效应关系 / 横断面研究 / logistic回归分析 / 贝叶斯核机器回归 / 分位数-g运算

Key words

cardiovascular disease / organochlorine pesticides / general population / exposure-effect relationship / cross-sectional study / logistic regression analysis / Bayesian kernel machine regression / quantile g-computation

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基金资助

国家自然科学基金资助项目(81860570)

国家自然科学基金资助项目(82060088)