中介或混杂因素:是否应调整肥胖以估计三卤甲烷对甲状腺功能的影响

doi:10.6040/j.issn.1671-7554.0.2023.0983

摘要/Abstract

摘要： 目的探究肥胖以混杂因素还是中介因素在三卤甲烷对甲状腺功能的影响过程中发挥作用。方法使用NHANES数据库中的横断面数据,分别使用加权秩和检验和χ2检验来比较连续变量和分类变量。对偏态分布的变量进行自然ln转换,根据ln转化浓度的四分位数分布对THM进行分类,引入有向无环图(directed acyclic graphs, DAGs)和Logisitic回归探讨肥胖的代理变量BMI在THM暴露与甲状腺功能的因果路径上发挥的潜在作用。结果额外调整BMI(作为分类变量)前后对THM暴露与甲状腺功能的关联无显著影响;但依据肥胖与否进行分层分析时,在肥胖患者中观察到THM是TSH水平升高的危险因素。结论考虑到对撞机偏倚,需要谨慎解释在肥胖分层分析中观察到的潜在异质性,以及谨慎考虑肥胖在THM研究作为混杂和/或中介进行额外分析的必要性。

关键词: 中介效应, 混杂因素, 有向无环图, 三卤甲烷, 肥胖

Abstract: Objective To explore whether obesity plays a confounding or mediating role in the effects of trihalomethanes on thyroid function. Methods The cross-sectional data were obtained from the NHANES database. The continuous and categorical variables were compared with weighted rank sum test and χ2 tests, respectively. Variables with skewed distribution were subjected to natural ln transformation; THM was classified according to the quartile distribution of ln transformed concentration; directed acyclic graphs(DAGs)and Logistic regression were introduced to explore the potential role of body mass index(BMI)in the causal pathway of THM exposure and thyroid function. Results There was no significant effect on the association between THM exposure and thyroid function before and after additional adjustment for BMI as a categorical variable; however, when stratified analyses were performed based on obesity, THM was a risk factor for elevated TSH levels in obese patients. Conclusion Considering collider bias, the potential heterogeneity observed in stratified analyses of obesity needs to be interpreted with caution, as well as the need for additional analyses of obesity as a confounder and/or mediator in THM studies.

Key words: Mediating effects, Confounders, Directed acyclic graph, Trihalomethanes, Obesity

中图分类号:

Q451

范佳旭, 成芳,乔俊鹏,费海程,陈学禹,赵云,贾红英. 中介或混杂因素:是否应调整肥胖以估计三卤甲烷对甲状腺功能的影响[J]. 山东大学学报 (医学版), 2024, 62(1): 102-110.

FAN Jiaxu, CHENG Fang, QIAO Junpeng, FEI Haicheng, CHEN Xueyu, ZHAO Yun, JIA Hongying. Mediators or confounders: should obesity be adjusted to estimate the effects of trihalomethanes on thyroid function[J]. Journal of Shandong University (Health Sciences), 2024, 62(1): 102-110.

参考文献

[1] 曹美苑, 李鰼橙, 黄柏文. 国内饮用水中消毒副产物分布水平与健康风险评价[J]. 公共卫生与预防医学, 2020, 31(3): 90-93. CAO Meiyuan, LI Xiecheng, HUANG Baiwen. Distribution level and health risk assessment of disinfection by-products in drinking water in China [J]. Public Health and Preventive Medicine, 2020, 31(3): 90-93.
[2] 李进义, 方云波, 汪雪涛, 等. 襄阳市城区生活饮用水中氯化消毒副产物暴露水平及健康风险评价[J].公共卫生与预防医学, 2021, 32(4): 67-70. LI Jinyi, FANG Yunbo, WANG Xuetao, et al. Exposure level and health risk assessment of chlorination disinfectant by-products in drinking water in Xiangyang City [J]. Public Health and Preventive Medicine, 2021, 32(4): 67-70.
[3] Sun Y, Wang YX, Liu C, et al. Trimester-specific blood trihalomethane and urinary haloacetic acid concentrations and adverse birth outcomes: identifying windows of vulnerability during pregnancy [J]. Environ Health Perspect, 2020, 128(10): 107001. doi: 10.1289/EHP7195.
[4] Miller MD, Crofton KM, Rice DC, et al. Thyroid-disrupting chemicals: interpreting upstream biomarkers of adverse outcomes [J]. Environ Health Perspect, 2009, 117(7): 1033-1041.
[5] Chu I, Villeneuve DC, Secours VE, et al. Trihalomethanes: II. Reversibility of toxicological changes produced by chloroform, bromodichloromethane, chlorodibromomethane and bromoform in rats [J]. J Environ Sci Health B, 1982, 17(3): 225-240.
[6] Hanna GB, Boshier PR, Markar SR, et al. Accuracy and methodologic challenges of volatile organic compound-based exhaled breath tests for cancer diagnosis: a systematic review and Meta-analysis [J]. JAMA Oncol, 2019, 5(1): e182815. doi: 10.1001/jamaoncol.2018.2815.
[7] 胡涛, 宋一超. S市饮用水中三卤甲烷分析及其超标风险评价[J]. 净水技术, 2020, 39(11): 110-116. HU Tao, SONG Yichao. Analysis and excessive risk assessment for THMs in drinking water in S city [J]. Water Purification Technology, 2020, 39(11): 110-116.
[8] 王晓霜, 董少霞. 中国部分城市饮用水中三卤甲烷类健康风险评价[J]. 中国公共卫生, 2020, 36(9): 1384-1388. WANG Xiaoshuang, DONG Shaoxia. Health risk assessment of trihalomethanes in drinking water in some cities of China: a literature study [J]. Public Health in China, 2020, 36(9): 1384-1388.
[9] Sun Y, Xia PF, Korevaar TIM, et al. Relationship between blood trihalomethane concentrations and serum thyroid function measures in U.S. adults [J]. Environ Sci Technol, 2021, 55(20): 14087-14094.
[10] Wei C, Cao L, Zhou Y, et al. Multiple statistical models reveal specific volatile organic compounds affect sex hormones in American adult male: NHANES 2013-2016 [J]. Front Endocrinol(Lausanne), 2022, 13: 1076664. doi: 10.3389/fendo.2022.1076664.
[11] Andra SS, Charisiadis P, Makris KC. Obesity-mediated association between exposure to brominated trihalomethanes and type II diabetes mellitus: an exploratory analysis [J]. Sci Total Environt, 2014, 485-486: 340-347. doi: 10.1016/j.scitotenv.2014.03.075.
[12] Das S, Kumar A, Seth RK, et al. Proinflammatory adipokine leptin mediates disinfection byproduct bromodichloromethane-induced early steatohepatitic injury in obesity [J]. Toxicol Appl Pharmacol, 2013, 269(3): 297-306.
[13] Seth RK, Kumar A, Das S, et al. Environmental toxin-linked nonalcoholic steatohepatitis and hepatic metabolic reprogramming in obese mice [J]. Toxicol Sci, 2013, 134(2): 291-303.
[14] Blount BC, Backer LC, Aylward LL, et al. Human exposure assessment for DBPs: factors influencing blood trihalomethane levels [A] //Nriagu JO. Encyclopedia of environmental health [C]. Burlington; Elsevier. 2011: 100-107.
[15] Vanderweele TJ. Principles of confounder selection [J]. Eur J Epidemiol, 2019, 34(3): 211-219.
[16] Cole SR, Platt RW, Schisterman EF, et al. Illustrating bias due to conditioning on a collider [J]. Int J Epidemiol, 2010, 39(2): 417-420.
[17] Greenland S. Quantifying biases in causal models: classical confounding vs collider-stratification bias [J]. Epidemiology, 2003, 14(3): 300-306.
[18] Burch JB, Everson TM, Seth RK, et al. Trihalomethane exposure and biomonitoring for the liver injury indicator, alanine aminotransferase, in the United States population(NHANES 1999-2006)[J]. Sci Total Environt, 2015, 521-522: 226-234. doi: 10.1016/j.scitotenv.2015.03.050.
[19] Sun Y, Xia PF, Xie J, et al. Association of blood trihalomethane concentrations with asthma in US adolescents: nationally representative cross-sectional study [J]. Eur Respir J, 2022, 59(5): 2101440. doi: 10.1183/13993003.01440-2021.
[20] Airaksinen J, Komulainen K, García-Velázquez R, et al. Subclinical hypothyroidism and symptoms of depression: evidence from the National Health and Nutrition Examination Surveys(NHANES)[J]. Compr Psychiatry, 2021, 109: 152253. doi: 10.1016/j.comppsych.2021.152253.
[21] Koeppe ES, Ferguson KK, Colacino JA, et al. Relationship between urinary triclosan and paraben concentrations and serum thyroid measures in NHANES 2007-2008 [J]. Science Total Environ, 2013, 445-446: 299-305. doi: 10.1016/j.scitotenv.2012.12.052.
[22] Schisterman EF, Cole SR, Platt RW. Overadjustment bias and unnecessary adjustment in epidemiologic studies [J]. Epidemiology, 2009, 20(4): 488-495.
[23] Elwert F, Winship C. Endogenous selection bias: the problem of conditioning on a collider variable [J]. Annu Rev Sociol, 2014, 40: 31-53. doi: 10.1146/annurev-soc-071913-043455.
[24] Hernández-Díaz S, Schisterman EF, Hernán MA. The birth weight "paradox" uncovered? [J]. Am J Epidemiol, 2006, 164(11): 1115-1120.
[25] Preston SH, Stokes A. Obesity paradox: conditioning on disease enhances biases in estimating the mortality risks of obesity [J]. Epidemiology, 2014, 25(3): 454-461.
[26] Daniel RM, Cousens SN, De Stavola BL, et al. Methods for dealing with time-dependent confounding [J]. Stat Med, 2013, 32(9): 1584-1618.
[27] Liew Z, Olsen J, Cui X, et al. Bias from conditioning on live birth in pregnancy cohorts: an illustration based on neurodevelopment in children after prenatal exposure to organic pollutants [J]. Int J Epidemiol, 2015, 44(1): 345-354.

相关文章 15

[1]	张媛李英敏冯月秋常彩云潘华伟王束玫. 血清脂联素水平与肥胖、胰岛素抵抗的关系探讨[J]. 山东大学学报(医学版), 2209, 47(6): 124-.
[2]	于晴晴,常开锋,李吉庆,张凯,付苹,刘晓雯,赵英淇,薛付忠. 中老年人群高血压在非甾体抗炎药暴露与心脑血管疾病风险关联中的中介分析[J]. 山东大学学报 (医学版), 2023, 61(8): 79-85.
[3]	韩晓婷,于霞,董来慧,纳莉,牛艳玲,赵君利. 月见草油对肥胖型不孕女性代谢及肠道菌群的影响[J]. 山东大学学报 (医学版), 2021, 59(2): 48-54.
[4]	刘新雨,王权,琚号杰,孙晓杰. 认知功能在老年人社会资本与身体功能健康间的中介作用[J]. 山东大学学报 (医学版), 2021, 59(11): 100-107.
[5]	李涵,付婷婷,张磊,延冰,孙涛,郭峰,尹晓. 过氧化物酶增殖物激活受体γ激动剂对24例肥胖症患者米色脂肪细胞分化的影响[J]. 山东大学学报 (医学版), 2020, 1(9): 8-13.
[6]	扈艳雯,王志媛,郁万江,赵蕙琛,韩合理,徐志鹏,马红,张玉超,刘元涛. 52例肥胖患者脂肪分布与代谢综合征及糖代谢指标的相关性[J]. 山东大学学报 (医学版), 2020, 1(8): 101-106.
[7]	安嬿,王律,陈参参,范秀珍. 206名护理硕士生心理资本与科研动机的调查分析[J]. 山东大学学报 (医学版), 2020, 58(12): 102-108.
[8]	王雪纯,董利,曹衍雯,董凯歌,王艺霖,袁莹,李士保,贾存显. 共情在大学生手机依赖倾向与人际交往困扰间的中介作用[J]. 山东大学学报 (医学版), 2019, 57(9): 119-124.
[9]	黄凤艳,许俐,刘平,王志萍. 会阴裂伤在孕前BMI与产后盆底肌功能障碍关联性中的中介作用[J]. 山东大学学报 (医学版), 2019, 57(2): 99-104.
[10]	王敏,王春花,刘鸿丽,何志良,崔薇薇,王磊,刘杰军. 男性儿童瘦素抵抗对成年后健康状况的影响[J]. 山东大学学报 (医学版), 2018, 56(10): 114-118.
[11]	张素萍,王泽,周亚丽, 李敬,路西兰,柏宏伟,石玉华. 来曲唑治疗不同体质量指数多囊卵巢综合征患者的临床效果[J]. 山东大学学报（医学版）, 2017, 55(5): 81-85.
[12]	卿立,何天祎,乔婧婷,崔晨,侯新国,陈丽. 富半胱氨酸蛋白61在高脂诱导肥胖小鼠脂肪组织中的表达[J]. 山东大学学报 (医学版), 2017, 55(12): 7-12.
[13]	沙莎,Chowdhury Sumon Rahman,陈丽,何芹,张婧,范珊珊,孙磊. 利拉鲁肽对高脂诱导肥胖小鼠瘦素、脂肪分布及含量的影响[J]. 山东大学学报（医学版）, 2016, 54(8): 22-27.
[14]	刘瑞红,丁荔洁,薛付忠. 退休前后生活方式及肥胖指标的变化[J]. 山东大学学报（医学版）, 2016, 54(1): 80-85.
[15]	李燕, 汪翼, 乔秀芸, 张莉, 孙瑾. 不同抵抗素水平对血清游离脂肪酸的影响[J]. 山东大学学报（医学版）, 2015, 53(11): 6-9.

多维度评价

Viewed

Full text

Abstract

Cited

Shared

Discussed