United States community births increased by 20% from 2019 to 2020.

BACKGROUND: Anecdotal and emerging evidence suggested that the 2020 COVID-19 pandemic may have influenced women's attitudes toward community birth. Our purpose was to examine trends in community births from 2019 to 2020, and the risk profile of these births. METHODS: Recently released 2020 birth certificate data were compared with prior years' data to analyze trends in community births by socio-demographic and medical characteristics. RESULTS: In 2020, there were 71 870 community births in the United States, including 45 646 home births and 21 884 birth center births. Community births increased by 19.5% from 2019 to 2020. Planned home births increased by 23.3%, while birth center births increased by 13.2%. Increases occurred in every US state, and for all racial and ethnic groups, particularly non-Hispanic Black mothers (29.7%), although not all increases were statistically significant. In 2020, 1 of every 50 births in the United States was a community birth (2.0%). Women with planned home and birth center births were less likely than women with hospital births to have several characteristics associated with poor pregnancy outcomes, including teen births, smoking during pregnancy, obesity, and preterm, low birthweight, and multiple births. More than two-thirds of planned home births were self-paid, compared with one-third of birth center and just 3% of hospital births. CONCLUSIONS: It is to the great credit of United States midwives working in home and birth center settings that they were able to substantially expand their services during a worldwide pandemic without compromising standards in triaging women to optimal settings for safe birth.

Complex systems models for causal inference in social epidemiology.

Systems models, which by design aim to capture multi-level complexity, are a natural choice of tool for bridging the divide between social epidemiology and causal inference. In this commentary, we discuss the potential uses of complex systems models for improving our understanding of quantitative causal effects in social epidemiology. To put systems models in context, we will describe how this approach could be used to optimise the distribution of COVID-19 response resources to minimise social inequalities during and after the pandemic.