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目的 探讨不同人群与围生儿先天畸形发生的相关影响因素 ,为适宜的社区人群干预对策与措施提供科学依据。方法 采用病例对照研究方法 ,以随机抽样方法抽取农村与城市先天畸形病例 ,其中城市 16 9例 ,农村2 0 5例。对照组按 1∶1配比的方法选择出生正常的婴幼儿 374例。调查对象均用统一问卷和调查方法 ,并采集血清标本进行实验室分析。数据用条件Logistic回归模型进行分析。 结果 城市人群与先天畸形相关的因素为孕妇知孕时间长 (OR =5 4 90 ,PAR % =13 91% )、孕早期发热 (OR =3 35 2 ,PAR % =12 18% )、孕早期服用解热镇痛药 (OR=3 5 0 1,PAR % =13 98% )、孕早期接触化学毒物 (OR =3 14 7,PAR % =8 0 9% )、父亲接触有害物 (OR =4 4 95 ,PAR % =9 4 9% )、负性生活事件 (OR =1 113,PAR % =2 4 8% ) ;农村人群与先天畸形相关的因素为孕妇知孕时间长 (OR =3 85 0 ,PAR % =13 34% )、孕期服药 (OR =3 95 2 ,PAR % =2 8 82 % )、孕早期营养 (OR =0 2 2 0 ,PAR % =16 0 3% )、既往巨细胞病毒感染 (OR =2 76 0 ,PAR % =16 0 6 % )、母亲优生知识知晓程度 (OR =0 30 5 ,PAR % =18 0 8% )、负性生活事件 (OR =1 5 0 6 ,PAR % =3 5 6 % )。结论 城市、农村人群先天畸形的影响因素及其作用强度不?
Objective To explore the influential factors of congenital malformations among different populations and perinatal children and to provide scientific basis for intervention strategies and measures for appropriate community population. Methods A case-control study was conducted to investigate the prevalence of congenital malformations in rural and urban areas by random sampling method, including 16 9 cities and 205 rural areas. Control group by 1: 1 ratio method to choose the normal birth of 374 infants. All the subjects used unified questionnaire and survey method, and collected serum samples for laboratory analysis. Data were analyzed using conditional Logistic regression model. Results The factors associated with congenital malformations in urban population were as follows: pregnancy for a long time (OR = 54.990, PAR% = 1391%), fever in first trimester (OR = 3552, PAR% = 12 18% (OR = 3 5 0 1, PAR% = 13 98%), exposure to toxic chemicals (OR = 3 14 7, PAR% = 80 9% (OR = 1 113, PAR% = 24.8%). The factors associated with congenital malformations in rural population were the long-term pregnancy expectancy (OR = 3 4 4 95, PAR% = 9 4 9% (OR = 952, PAR% = 28 82%), nutrition during early pregnancy (OR = 0 2 2 0, PAR% = 16 0 3%), previous CMV infection (OR = 2 76 0, PAR% = 16 06%), maternal eugenics knowledge level (OR = 0 30 5, PAR% = 18 0 8%), negative life events 0 6, PAR% = 356%). Conclusions The influencing factors of congenital malformations in urban and rural areas and their intensity are not?