您的位置:山东大学 -> 科技期刊社 -> 《山东大学学报(医学版)》

山东大学学报 (医学版) ›› 2021, Vol. 59 ›› Issue (12): 134-142.doi: 10.6040/j.issn.1671-7554.0.2021.1200

• • 上一篇    下一篇

孕期环境温度对早产风险的影响

杜爽1,韩德新2,林少倩3,白硕鑫1,赵小冬3,王兆军4,王志萍1   

  1. 1.山东大学齐鲁医学院公共卫生学院, 山东 济南 250012;2. 山东省济南市市中区党家街道办事处社区卫生服务中心, 山东 济南 250116;3.济南市疾病预防控制中心免疫所, 山东 济南250021;4.山东省济南生态环境监测中心, 山东 济南 250101
  • 发布日期:2021-12-29
  • 通讯作者: 王志萍. E-mail: zhipingw@sdu.edu.cn
  • 基金资助:
    国家自然科学基金(81773386)

Effect of ambient temperature during pregnancy on the risk of preterm birth

DU Shuang1, HAN Dexin2, LIN Shaoqian3, BAI Shuoxin1, ZHAO Xiaodong3, WANG Zhaojun4, WANG Zhiping1   

  1. 1. School of Public Health, Cheeloo College of Medicine, Shandong University, Jinan 250012, Shandong, China;
    2. Community Health Service Center of Dangjia Subdistrict Office in Shizhong District of Jinan City, Jinan 250116, Shandong, China;
    3. Immunization Institute of Jinan Municipal Center for Disease Control and Prevention, Jinan 250021, Shandong, China;
    4. Shandong Jianan Ecological Environment Monitoring Center, Jinan 250101, Shandong, China
  • Published:2021-12-29

摘要: 目的 探讨济南市孕妇孕期环境温度对早产风险的影响,识别暴露的关键窗口期和敏感人群。 方法 依托于2018年1月至2019年12月在济南市建立的出生队列的基线人群,以婴儿母亲为研究对象,收集研究期间每日环境温度数据,观察其对早产的影响。采用分布滞后非线性模型(DLNM)结合Cox比例风险模型来估计孕期环境温度对早产风险的影响并识别关键窗口期。采用似然比检验分析家庭主妇与环境温度间是否存在交互作用,再将研究对象按照家庭主妇进行分层分析以观察其效应修饰作用。 结果 (1)在纳入研究的6 501位母亲中,有285位早产,占4.38%。(2)与孕期中等温度相比,较低和较高的环境温度与早产风险存在统计学联系,较低温时的关键窗口期在第1~27孕周;较高温时的关键窗口期在第1~29周,其危险比(HR)峰值出现在第13~18孕周,危险比HR为1.13(95%CI:1.07~1.20)。(3)似然比检验发现,家庭主妇与温度存在交互作用(χ2=8.73,P=0.013)。(4)在家庭主妇人群中,极端0℃时的效应峰值为4.00(95%CI: 1.63~9.82),高于非家庭主妇[1.71(95%CI:1.08~2.73)];极端30℃时的效应峰值为3.45(95%CI:1.56~7.60),高于非家庭主妇[1.79(95%CI:1.12~2.84)]。 结论 孕期暴露于较低和较高的环境温度可能会增加早产风险,关键窗口期分别是第1~27孕周和第1~29孕周,家庭主妇人群对极端气温更敏感。

关键词: 环境温度, 早产, 分布滞后非线性模型, 家庭主妇, 效应修饰

Abstract: Objective To explore the effect of maternal ambient temperature exposure during pregnancy on the risk of preterm birth in Jinan City, and to identify the critical window period of exposure and sensitive population. Methods The study was based on the baseline population of the birth cohort conducted in Jinan from January 2018 to December 2019. The study subjects were the mother of infant, and the study outcome was preterm birth. The daily ambient temperature data during the study period were collected. The distributed lag nonlinear model(DLNM)combined with Cox proportional hazards model was used to estimate the effect of ambient temperature during pregnancy on the risk of preterm birth and identify the critical window period of exposure. A likelihood ratio test was used to analyze whether there was interaction between housewives and ambient temperature. Then, stratified analysis was carried out according to whether the subjects were housewives to observe the effect modification. Results (1) This study included 6,501 mothers. Of these, 285 had preterm birth, accounting for 4.38%. (2) Compared with the middle temperature on the duration of pregnancy, the lower and higher temperature were statistically associated with the risk of preterm birth. The critical window period at lower temperature was from the 1st to 27th gestational weeks, while that at higher temperature was from the 1st to 29th gestational weeks, and its peak hazard ratio were found in the 13th to 18th gestational weeks(HR = 1.13, 95%CI: 1.07-1.20). (3) A likelihood ratio test showed that housewives and temperature had an interaction effect(χ2 =8.73, P=0.013). (4) Among housewives, the peak effect for extreme 0 ℃ was 4.00(95%CI:1.63-9.82), which was higher than that of non-housewives [1.71(95%CI:1.08-2.73)]; the peak effect for extreme 30 ℃ was 3.45(95%CI:1.56-7.60), which was higher than that of non-housewives [1.79(95%CI:1.12-2.84)]. Conclusion Exposure to low or high ambient temperature during pregnancy may increase the risk of preterm birth, and the critical window periods were the 1st-27th gestational weeks and the 1st-29th gestational weeks, respectively. The housewives may more sensitive to extreme temperatures.

Key words: Ambient temperature, Preterm birth, Distributed lag nonlinear model, Housewives, Effect modification

中图分类号: 

  • R122
[1] Lawn JE, Gravett MG, Nunes TM, et al. Global report on preterm birth and stillbirth(1 of 7): definitions, description of the burden and opportunities to improve data [J]. BMC Pregnancy Childbirth, 2010, 10(1): S1.
[2] Luu TM, Rehman Mian MO, Nuyt AM. Long-term impact of preterm birth: neurodevelopmental and physical health outcomes [J]. Clin Perinatol, 2017, 44(2): 305-314.
[3] Markopoulou P, Papanikolaou E, Analytis A, et al. Preterm birth as a risk factor for metabolic syndrome and cardiovascular disease in adult life: a systematic review and Meta-analysis [J]. J Pediatr, 2019, 210: 69-80.e5. doi: 10.1016/j.jpeds.2019.02.041.
[4] Abitbol CL, Rodriguez MM. The long-term renal and cardiovascular consequences of prematurity [J]. Nat Rev Nephrol, 2012, 8(5): 265-274.
[5] Deng K, Liang J, Mu Y, et al. Preterm births in China between 2012 and 2018: an observational study of more than 9 million women [J]. Lancet Glob Health, 2021, 9(9): e1226-e1241.
[6] 李畅畅, 任萌, 董昊天, 等. 极端气温与早产关系的流行病学研究进展[J]. 环境与职业医学, 2020, 37(1): 15-22. LI Changchang, REN Meng, DONG Haotian, et al. Epidemiological research progress on association of maternal exposure to ambient temperature extremes and preterm birth [J]. J Occup Environ Med, 2020, 37(1): 15-22.
[7] Guo T, Wang Y, Zhang H, et al. The association between ambient temperature and the risk of preterm birth in China [J]. Sci Total Environ, 2018, 613-614: 439-446. doi: 10.1016/j.scitotenv.2017.09.104.
[8] Wang YY, Li Q, Guo Y, et al. Ambient temperature and the risk of preterm birth: a national birth cohort study in the mainland China [J]. Environ Int, 2020, 142:105851. doi: 10.1016/j.envint.2020.105851.
[9] Gasparrini A. Distributed lag linear and non-linear models in R: the package dlnm [J]. J Stat Softw, 2011, 43(8): 1-20.
[10] Yuan L, Zhang Y, Wang W, et al. Critical windows for maternal fine particulate matter exposure and adverse birth outcomes: the Shanghai birth cohort study [J]. Chemosphere, 2020, 240: 124904. doi: 10.1016/j.chemosphere.2019.124904.
[11] Liu X, Xiao J, Sun X, et al. Associations of maternal ambient temperature exposures during pregnancy with the risk of preterm birth and the effect modification of birth order during the new baby boom: a birth cohort study in Guangzhou, China [J]. Int J Hyg Environ Health, 2020, 225: 113481. doi: 10.1016/j.ijheh.2020.113481.
[12] Wu H, Jiang BF, Zhu P, et al. Associations between maternal weekly air pollutant exposures and low birth weight: a distributed lag non-linear model [J]. Environmental Research Letters, 2018, 13(2): 11.
[13] 程欣, 李志浩, 吕跃斌,等. 中国80岁及以上高龄老人静息心率与全因死亡风险的前瞻性队列研究[J].中华预防医学杂志, 2021, 55(1): 53-59. CHENG Xin, LI Zhihao, LYU Yuebin, et al.The relationship between resting heart rate and all-cause mortality among the Chinese oldest-old aged more than 80: a prospective cohort study [J]. Chinese Journal of Preventive Medicine, 2021, 55(1): 53-59.
[14] Ren C, Williams GM, Mengersen K, et al. Temperature enhanced effects of ozone on cardiovascular mortality in 95 large US communities, 1987-2000: assessment using the NMMAPS data [J]. Arch Environ Occup Health, 2009, 64(3): 177-184.
[15] Strand LB, Barnett AG, Tong S. Methodological challenges when estimating the effects of season and seasonal exposures on birth outcomes [J]. BMC Med Res Methodol, 2011, 11(1): 49.
[16] Ilango SD, Weaver M, Sheridan P, et al. Extreme heat episodes and risk of preterm birth in California, 2005-2013 [J]. Environ Int, 2020, 137: 105541. doi: 10.1016/j.envint.2020.105541.
[17] Wang J, Tong S, Williams G, et al. Exposure to heat wave during pregnancy and adverse birth outcomes: an exploration of susceptible windows [J]. Epidemiology, 2019, 30(Suppl 1): S115-S121.
[18] Spolter F, Kloog I, Dorman M, et al. Prenatal exposure to ambient air temperature and risk of early delivery [J]. Environ Int, 2020, 142: 105824. doi: 10.1016/j.envint.2020.105824.
[19] He JR, Liu Y, Xia XY, et al. Ambient temperature and the risk of preterm birth in Guangzhou, China(2001-2011)[J]. Environ Health Perspect, 2016, 124(7): 1100-1106.
[20] Cheng P, Peng L, Hao J, et al. Short-term effects of ambient temperature on preterm birth: a time-series analysis in Xuzhou, China [J]. Environ Sci Pollut Res Int, 2021, 28(10): 12406-12413.
[21] Zhou G, Yang M, Chai J, et al. Preconception ambient temperature and preterm birth: a time-series study in rural Henan, China [J]. Environ Sci Pollut Res Int, 2021, 28(8): 9407-9416.
[22] Pang Y, Yan L, Ren M, et al. Environmental complex exposure and the risk of influenza-like illness among housewives: a case study in Shanxi Province, China[J]. Ecotoxicol Environ Saf, 2020, 194: 110405. doi: 10.1016/j.ecoenv.2020.110405.
[23] Bener A, Al-Hamaq A, Saleh NM. Association between vitamin D insufficiency and adverse pregnancy outcome: global comparisons[J]. Int J Womens Health, 2013, 5: 523-531. doi: 10.2147/IJWH.S51403.
[24] Mäkinen TM, Raatikka VP, Rytkönen M, et al. Factors affecting outdoor exposure in winter: population-based study [J]. Int J Biometeorol, 2006, 51(1): 27-36.
[25] Booth GL, Luo J, Park AL, et al. Influence of environmental temperature on risk of gestational diabetes [J]. CMAJ, 2017, 189(19): E682-E689.
[26] Shashar S, Kloog I, Erez O, et al. Temperature and preeclampsia: epidemiological evidence that perturbation in maternal heat homeostasis affects pregnancy outcome [J]. PLoS One, 2020, 15(5): e0232877.
[27] 张言博, 赵志梅, 杨雪,等. 妊娠期糖尿病对早产发生风险影响[J].中国公共卫生, 2019, 35(9): 1142-1145. ZHANG Yanbo, ZHAO Zhimei, YANG Xue, et al. Association between gestational diabetes mellitus and risk of preterm birth[J]. Chinese Journal of Public Health, 2019, 35(9): 1142-1145.
[28] Carolan-Olah M, Frankowska D. High environmental temperature and preterm birth: a review of the evidence [J]. Midwifery, 2014, 30(1): 50-59.
[29] Basu R, Malig B, Ostro B. High ambient temperature and the risk of preterm delivery [J]. Am J Epidemiol, 2010, 172(10): 1108-1117.
[30] Moriyama M, Hugentobler WJ, Iwasaki A. Seasonality of respiratory viral infections [J]. Annual Review of Virology, 2020, 7(1): 83-101.
[31] Nadeau HCG, Subramaniam A, Andrews WW. Infection and preterm birth [J]. Seminars in Fetal and Neonatal Medicine, 2016, 21(2): 100-105.
[32] Bruckner TA, Modin B, Vågerö D. Cold ambient temperature in utero and birth outcomes in Uppsala, Sweden, 1915-1929 [J]. Ann Epidemiol, 2014, 24(2): 116-121.
[33] Wilson A, Chiu YHM, Hsu HHL, et al. Potential for bias when estimating critical windows for air pollution in childrens health [J]. Am J Epidemiol, 2017, 186(11): 1281-1289.
[34] 杨梅, 肖静, 蔡辉. 多元分析中的多重共线性及其处理方法[J].中国卫生统计, 2012, 29(4): 620-624.
[35] Wang X, Purohit P, Höglund-Isaksson L, et al. Co-benefits of energy-efficient air conditioners in the residential building sector of China [J]. Environ Sci Technol, 2020, 54(20): 13217-13227.
[1] 郝强,高琦,赵然,王海涛,刘志东,姜宝法. 2014~2016年气温和相对湿度对深圳市5岁以下儿童轮状病毒腹泻的影响[J]. 山东大学学报 (医学版), 2022, 60(2): 89-95.
[2] 冯一平,孙大鹏,王显军,纪伊曼,刘云霞. DLNM和LSTM神经网络对临沂市手足口病发病的预测效果比较[J]. 山东大学学报 (医学版), 2022, 60(2): 96-101.
[3] 张文红,王翠翠,王小康,张君,郝薇. 硫酸多黏菌素B治疗极早早产儿感染泛耐药肺炎克雷伯菌1例[J]. 山东大学学报 (医学版), 2022, 60(2): 121-124.
[4] 萧阳,陶宇,王方怡,梁俞秀,张晋,季晓康,王志萍. 山东省部分地区PM2.5和PM10暴露与妊娠期糖尿病的关联性分析[J]. 山东大学学报 (医学版), 2021, 59(12): 101-109.
[5] 王珮竹,郑兆磊,李润滋,许勤勤,康凤玲,许青,李秀君. 济南市昼夜温差对麻疹发病的影响[J]. 山东大学学报 (医学版), 2018, 56(8): 101-106.
[6] 张丹丹,王旭,许勤勤,郑兆磊,王珮竹,李吉庆,刘静,许青,李秀君. 菏泽市与威海市气温对流行性腮腺炎发病的影响[J]. 山东大学学报 (医学版), 2018, 56(8): 88-94.
[7] 李娅,袁鹏,张飞雪,邵广瑞. 肺脏超声在肺表面活性物质治疗早产儿呼吸窘迫综合征中的评价作用[J]. 山东大学学报 (医学版), 2018, 56(2): 34-40.
[8] 许勤勤,李润滋,刘娅飞,孙苑潆,郑兆磊,王珮竹,王志强,李秀君. 基于分布滞后非线性模型的青岛市温度与肾综合征出血热的剂量反应关系[J]. 山东大学学报 (医学版), 2018, 56(1): 90-96.
[9] 仇杰,臧丽娇,庄根苗,安丽. 不同胎龄围生期窒息与多器官功能损伤的相关性[J]. 山东大学学报(医学版), 2016, 54(9): 64-68.
[10] 慈春燕,李文,卢宪梅. 早产儿早期振幅整合脑电图特点的分析[J]. 山东大学学报(医学版), 2012, 50(9): 109-112.
[11] 成锴1,2,张林娜1,孙明2,侯茜2,张敏2,杨海霞2. 773例早产儿视网膜病变筛查结果分析[J]. 山东大学学报(医学版), 2011, 49(9): 149-152.
[12] 杨学勇1,周更须1,李秋平2,付松1,刘宇航1,王辉1,赵鑫2,封志纯3. 早产儿动脉导管未闭的床旁外科治疗[J]. 山东大学学报(医学版), 2011, 49(8): 133-135.
[13] 吴巧灵,孙正芸,林霞. 早产儿血清碱性磷酸酶、钙、磷的代谢特点[J]. 山东大学学报(医学版), 2010, 48(2): 113-.
[14] 王莹,朱薇薇,罗焕华,季超. 早产儿血胃动素和胃泌素的相关性研究[J]. 山东大学学报(医学版), 2007, 45(7): 708-710.
[15] 朱炳亮,李金成,孙素芳,黄秋静. 尼莫地平合用生脉注射液治疗早产儿颅内出血的临床疗效观察[J]. 山东大学学报(医学版), 2007, 45(5): 538-540.
Viewed
Full text


Abstract

Cited

  Shared   
  Discussed   
[1] 史爽,李娟,米琦,王允山,杜鲁涛,王传新. 胃癌miRNAs预后风险评分模型的构建与应用[J]. 山东大学学报 (医学版), 2020, 1(7): 47 -52 .
[2] 黄飞,王怀经,邢毅,高薇,李永刚,邢子英,李振中. NGF和GM1联合应用对坐骨神经损伤大鼠初级传入神经元的保护作用[J]. 山东大学学报(医学版), 2006, 44(4): 332 -335 .
[3] 吕龙飞,李林,李树海,亓磊,鲁铭,程传乐,田辉. 腔镜下细针导管空肠造瘘在微创McKeown食管癌切除术中的应用[J]. 山东大学学报 (医学版), 2020, 1(7): 77 -81 .
[4] 邵海港, 王璇, 王青. 山东地区人下颌第一前磨牙根管系统解剖研究[J]. 山东大学学报(医学版), 2014, 52(9): 85 -89 .
[5] 姜保东,马祥兴,王青,王茜,冯晓源,李克,于富华 . 脑CT静脉造影扫描时相及重建层厚的选择[J]. 山东大学学报(医学版), 2008, 46(11): 1084 -1086 .
[6] 李洧,李道卫,叶茜,高顺翠,姜淑娟. 经支气管镜针吸活检在纵隔疾病诊断中的价值[J]. 山东大学学报(医学版), 2008, 46(11): 1063 -1065 .
[7] 唐芳1,2 ,张颖倩3 ,王志强4 ,康殿民4 ,王洁贞1 ,薛付忠1 . 自然疫源性疾病疫源地空间结构的二维
最小生成树模型及其应用
[J]. 山东大学学报(医学版), 2009, 47(01): 106 -110 .
[8] 王旭平,赵玲,冯玉新,商林珊,刘金成,曹伟朋,朱晓音,辛华. 绞股蓝总苷对谷氨酸诱导的胎鼠大脑皮层神经元氧化性损伤保护机制的研究[J]. 山东大学学报(医学版), 2006, 44(6): 564 -567 .
[9] 王学萍,杨洪玲. 洛汀新治疗高血压50例报告[J]. 山东大学学报(医学版), 2007, (2): 213 .
[10] 朱晓丽1,郭淑玲1,苏磊1,冯玉新2,袁方曙1. 蠕形螨全蛋白提取及相对分子量鉴定[J]. 山东大学学报(医学版), 2014, 52(5): 58 -62 .