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Insurance coverage for prenatal care, labor and delivery care, and postpartum care for undocumented immigrants consists of a patchwork of state and federal policies, which varies widely by state. According to federal law, states must provide coverage for labor and delivery through Emergency Medicaid. Various states have additional prenatal and postpartum coverage for undocumented immigrants through policy mechanisms such as the Children’s Health Insurance Program’s “unborn child” option, expansion of Medicaid, and independent state-level mechanisms. Using a search of state Medicaid and federal government websites, we found that 27 states and the District of Columbia provide additional coverage for prenatal care, postpartum care, or both, while 23 states do not. Twelve states include any postpartum coverage; 7 provide coverage for 12 months postpartum. Although information regarding coverage is available publicly online, there exist many barriers to access, such as lack of transparency, lack of availability of information in multiple languages, and incorrect information. More inclusive and easily accessible policies are needed as the first step toward improving maternal health among undocumented immigrants, a population trapped in a complicated web of immigration policy and a maternal health crisis. ( Am J Public Health. 2024;114(10):1051–1060. https://doi.org/10.2105/AJPH.2024.307750 )

Abstract Food environments of urban informal settlements are likely drivers of dietary intake among residents of such settlements. Yet, few attempts have been made to describe them. The objective of this study was to characterize the food environment of a densely-populated informal settlement in Nairobi, Kenya according to the obesogenic properties and spatial distribution of its food vendors. In July–August 2019, we identified food vendors in the settlement and classified them into obesogenic risk categories based on the types of food that they sold. We calculated descriptive statistics and assessed clustering according to obesogenic risk using Ripley’s K function. Foods most commonly sold among the 456 vendors in the analytic sample were sweets/confectionary (29% of vendors), raw vegetables (28%), fried starches (23%), and fruits (21%). Forty-four percent of vendors were classified as low-risk, protective; 34% as high-risk, non-protective; 16% as low-risk, non-protective; and 6% as high-risk, protective. The mean distance (95% confidence interval) to the nearest vendor of the same obesogenic risk category was 26 m (21, 31) for vendors in the low-risk, protective group; 29 m (25, 33) in the high-risk, non-protective group; 114 m (88, 139) in the high-risk, protective group; and 43 m (30, 56) in the low-risk, non-protective group. Clustering was significant for all obesogenic risk groups except for the high-risk, protective. Our findings indicate a duality of obesogenic and anti-obesogenic foods in this environment. Clustering of obesogenic foods highlights the need for local officials to take action to increase access to health-promoting foods throughout informal settlements.