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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

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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

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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.
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