Khan Diba, Rossen Lauren M, Hamilton Brady, Dienes Erin, He Yulei, Wei Rong
National Center for Health Statistics, Hyattsville, USA.
Rocky Mountain Poison and Drug Center, Denver, USA.
J R Stat Soc Ser A Stat Soc. 2018 Jan;181(1):35-58. doi: 10.1111/rssa.12266. Epub 2017 Jan 19.
The objective of this analysis was to explore temporal and spatial variation in teen birth rates TBRs across counties in the USA, from 2003 to 2012, by using hierarchical Bayesian models. Prior examination of spatiotemporal variation in TBRs has been limited by the reliance on large-scale geographies such as states, because of the potential instability in TBRs at smaller geographical scales such as counties. We implemented hierarchical Bayesian models with space-time interaction terms and spatially structured and unstructured random effects to produce smoothed county level TBR estimates, allowing for examination of spatiotemporal patterns and trends in TBRs at a smaller geographic scale across the USA. The results may help to highlight US counties where TBRs are higher or lower and to inform efforts to reduce birth rates to adolescents in the USA further.
本分析的目的是通过使用分层贝叶斯模型，探究2003年至2012年美国各县青少年生育率（TBRs）的时空变化。此前对TBRs时空变化的研究因依赖州等大规模地理区域而受到限制，因为在县等较小地理尺度上TBRs可能不稳定。我们实施了具有时空交互项以及空间结构化和非结构化随机效应的分层贝叶斯模型，以生成平滑的县级TBR估计值，从而能够在美国较小地理尺度上考察TBRs的时空模式和趋势。研究结果可能有助于凸显美国TBRs较高或较低的县，并为进一步降低美国青少年生育率的努力提供信息。
