孕期数字健康的使用情况与早产的可能性。
Digital health utilization during pregnancy and the likelihood of preterm birth.
作者信息
Brinson Alison K, Jahnke Hannah R, Henrich Natalie, Karwa Smriti, Moss Christa, Shah Neel
机构信息
Department of Anthropology, University of North Carolina at Chapel Hill, NC, USA.
Carolina Population Center, Chapel Hill, NC, USA.
出版信息
Digit Health. 2024 Sep 2;10:20552076241277037. doi: 10.1177/20552076241277037. eCollection 2024 Jan-Dec.
OBJECTIVE
Given the complex nature of preterm birth, interventions to reduce rates of preterm birth should be multifaceted. This analysis aimed to explore the association between the duration of using Maven, a digital health platform for women's and family health, and the odds of preterm birth.
METHODS
Data came from 3326 pregnant, nulliparous Maven users who enrolled in Maven during their pregnancy between January 2020 and September 2022. Chi-square and Fisher's exact tests compared characteristics between users who developed gestational conditions and users who did not. This retrospective cohort study used logistic regression models to estimate the association between the duration of Maven use and odds of preterm birth, stratified by the presence of gestational conditions.
RESULTS
Compared to those without gestational conditions, individuals who developed gestational conditions were more likely to have a preterm birth (8.7% vs. 3.4%; < 0.001). For every 1 h of Maven use, users experienced a 2% reduction in their odds of experiencing a preterm birth [adjusted odds ratio (AOR) (95% confidence interval (CI)) = 0.98 (0.95, 0.998), = 0.04]. Among individuals who developed gestational conditions, every 1 h increase in Maven use was associated with a 5% reduction in the odds of experiencing a preterm birth [AOR (95% CI) = 0.95 (0.91, 0.99), = 0.037]. There was no statistically significant association between Maven use and preterm birth in individuals without gestational conditions.
CONCLUSION
Among those who developed gestational conditions, use of a digital health platform was associated with a decreased likelihood of preterm birth.
目的
鉴于早产的复杂性,降低早产率的干预措施应是多方面的。本分析旨在探讨使用Maven(一个针对女性和家庭健康的数字健康平台)的时长与早产几率之间的关联。
方法
数据来自于2020年1月至2022年9月期间孕期注册使用Maven的3326名未生育的孕妇用户。卡方检验和费舍尔精确检验比较了出现妊娠相关状况的用户与未出现此类状况的用户之间的特征。这项回顾性队列研究使用逻辑回归模型来估计Maven使用时长与早产几率之间的关联,并按是否存在妊娠相关状况进行分层。
结果
与未出现妊娠相关状况的人相比,出现妊娠相关状况的个体更有可能早产(8.7%对3.4%;P<0.001)。Maven使用时长每增加1小时,用户早产几率降低2%[调整后的优势比(AOR)(95%置信区间(CI))=0.98(0.95,0.998),P=0.04]。在出现妊娠相关状况的个体中,Maven使用时长每增加1小时,早产几率降低5%[AOR(95%CI)=0.95(0.91,0.99),P=0.037]。在未出现妊娠相关状况的个体中,Maven使用与早产之间无统计学显著关联。
结论
在出现妊娠相关状况的人群中,使用数字健康平台与早产可能性降低相关。
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