Poor diet during pregnancy compromises maternal–fetal health and may reflect broader environmental and structural inequities. This study investigated differences in dietary intake across pregnancy among rural and urban women in the United States and assessed whether socioeconomic status (SES) modified rural–urban differences.
In this prospective study, pregnant women (n = 495; 22.4% rural) from three sites (Iowa, Pennsylvania, West Virginia) had dietary intake estimated via the 26-item Dietary Screener Questionnaire (DSQ) during each trimester. Rural was defined as Rural–Urban Commuting Area (RUCA) code ≥ 4. A SES score was derived using Principal Component Analysis of education, annual household income, and insurance type. Adjusted robust linear mixed-effects models (controlled for site, age, minority status, pre-pregnancy BMI) compared dietary intakes between rural and urban participants, with trimester and SES interactions.
Compared to their urban counterparts, rural participants had higher predicted intakes of added sugars from sugar-sweetened beverages (SSBs) in the first (0.61 tsp eq/day; 95% CI: [0.04, 1.18]) and second trimesters (0.62 tsp eq/day [0.05, 1.21]), and less fiber across all trimesters (ranging from –0.90 g/day [–1.7, –0.1] to –1.2 g/day [–2.0, –0.3]). Women in the high-SES urban group had higher intakes of fiber and calcium, and lower intakes of SSBs compared to their low-SES counterparts in both rural and urban settings.
Although rurality was associated with greater SSBs and lower fiber intake, differences were modest. Low-SES was related to a poorer diet regardless of geography, highlighting the need for targeted interventions for both rural and urban low-SES pregnant women.
Recovery community centers (RCCs) offer a range of non-clinical services for individuals in recovery from substance use disorder (SUD). RCCs may play an important role in addressing rural service gaps. This study aims to increase our understanding of how rural RCCs address SUD, including how they serve individuals receiving medications for opioid use disorder (MOUD).
We conducted a mixed methods study consisting of pre-interview surveys and semi-structured interviews with 12 RCC directors in rural Georgia. The surveys examined organizational and participant characteristics and MOUD attitudes, and the interviews explored rural challenges, strategies to overcome challenges, and community collaborations. We conducted descriptive analyses of the survey data and analyzed interviews using thematic analysis.
RCCs serviced an average of 41 new members per month and had an annual budget of $225,407. RCCs provided in-house or linked to many services that addressed social determinants of health. Most participants were in early recovery (<1 year), had criminal legal involvement, and lacked a high school education. In the thematic analysis, transportation and housing were commonly reported challenges. Additionally, RCCs provided essential treatment linkage, were the primary naloxone distributor in the area, and provided in-house mutual help organizations representing alternative recovery pathways. Collaboration with MOUD providers was minimal despite RCC efforts. Directors generally had positive attitudes towards MOUD.
Rural RCCs address a range of social determinants of health and may fill gaps in the SUD continuum of care, including harm reduction services, linkage to treatment, and expansion of recovery pathways.
To examine how COVID-19 public health emergency (PHE) exposure during pregnancy and telehealth use were associated with rural-urban and racial/ethnic differences in prenatal care initiation timing and frequency.
This retrospective cohort study of 349,682 pregnancies to birthing individuals who received both prenatal and intrapartum care at the 75 health systems in the United States contributing to the National Clinical Cohort Collaborative (N3C) from 6/1/2018 through 5/31/2022. Outcomes included prenatal care initiation timing and the number of prenatal care visits. Prenatal periods were categorized into 3 PHE exposure groups: (1) never, (2) partially, and (3) fully exposed to the PHE. The full-exposure group was further categorized into telehealth users and those with exclusively in-person care.
The full-exposure group with telehealth uptake had the earliest prenatal care initiation (median: 9 weeks [interquartile range: 7-13]) and the most visits (19 visits [12-20]). In contrast, the full-exposure group without telehealth use initiated care the latest (11 weeks [8-21]) and had the fewest visits (13 visits [6-22]). Rural-urban disparities persisted; however, telehealth users in both groups had earlier initiation and more visits. Racial and ethnic disparities in timeliness to initiation were most pronounced among the full-exposure group with telehealth (Black-White: adjusted hazard ratio [aHR]: 0.76, 95% CI, 0.70-0.83; Hispanic-White: aHR: 0.62, 95% CI, 0.58-0.68), compared to the full-exposure group with exclusively in-person care (Black-White: 0.95 [0.93-0.94]; Hispanic-White: 0.80 [0.80-0.81]).
Prenatal telehealth care improved early initiation but also exacerbated racial/ethnic disparities in the timeliness of prenatal care access. However, rural-urban disparities persisted.
To compare the time and distance travel burden to access care for rural and urban Medicaid and commercially insured patients with opioid use disorder (OUD), and to understand where they travel for care.
We used Medicaid and the Health Care Cost Institute commercial insurance administrative claims data from 2019 to examine the travel burden to health care for adults ages 18 years and older with OUD. We calculated the one-way driving distance and travel time between the enrollee's residence and the provider's location. We used the 2013 Urban Influence Codes (UIC) to classify enrollees as either urban (UIC 1–2) or rural (UIC 3–12) based on the patient's residence county.
The median distance traveled for a visit by a rural Medicaid or rural commercially insured enrollee was more than twice as far as their urban counterparts (rural Medicaid: 45.9 miles, urban Medicaid: 13.9 miles; rural commercially insured: 32.9 miles, urban commercially insured: 12.4 miles). When we imputed zeros for care provided in the same ZIP Code as an enrollee's residence, these differences persisted. Rural Medicaid enrollees carried the largest travel burden spending an average of more than 60 min traveling to care, about 30 min more than rural commercially insured enrollees. Urban enrollees, regardless of insurance type received almost all of their care in an urban location while rural Medicaid and commercially insured patients traveled to an urban location for about half their visits.
Rural and urban Medicaid and commercially insured enrollees experience different time and distance travel burdens.
Rural-residing children have poor access to preventive health care due to geographic and socioeconomic issues, yet the role of adverse childhood experiences (ACEs) in preventive care for rural children has been understudied. It is hypothesized that among rural-residing children, those with ≥1 ACE will have lower utilization of preventive health care, with differences by sex.
Data for 425 (weighted n = 3,949,102) children (aged 9-17) residing in “nonmetropolitan” (2013 NCHS Urban-Rural Classification) were drawn from the 2022 National Health Interview Survey. Physician visit in the past 12 months (yes/no), dental visit in the past 12 months (yes/no), COVID-19, flu, and HPV vaccination (yes/no) were self-reported. Participants self-reported (yes/no) to 6 ACEs (high ACEs ≥1). Logistic regression estimated odds ratios and 95% confidence intervals for associations between ACEs and preventive health outcomes, adjusted for demographic and health care factors. This manuscript adheres to STROBE guidelines.
Children with ≥1 ACE were 81% more likely (OR = 1.81, 95% CI 1.04, 3.18) to receive a flu vaccination and 184% (OR = 2.84, 95% CI 1.66, 4.85) more likely to receive an HPV vaccination compared to children with 0 ACEs. No significant associations were found between ACEs and other preventive health care. Boys with ≥1 ACE had decreased odds (OR = 0.34, 95% CI 0.13, 0.94) of visiting a dentist, while girls with ≥1 ACE had increased odds (OR = 3.87, 95% CI 1.56, 9.60) of receiving an HPV vaccination.
Children with ≥1 ACE were more likely to receive a flu vaccination and HPV vaccination. The effect of ACEs on preventive health care may differ by sex among rural residents, yet additional research is warranted to inform prevention efforts in rural communities.
This study examines the effect of nurse staffing (skill mix and flexibility) on the financial sustainability, efficiency, and quality of care in Pennsylvania's critical access hospitals (CAHs) from 2000 to 2023.
This retrospective longitudinal study utilized unbalanced panel data from Pennsylvania's CAHs (n = 357 hospital-year observations). We employed 2-way fixed effects regression models to analyze the relationship between nurse staffing variables (skill mix and flexibility) and hospital performance outcomes (total margin, cost per adjusted discharge [CPAD], cost per adjusted patient day [CPPD], average length of stay [ALOS], and readmission index). We controlled for hospital-specific, socioeconomic, and demographic factors.
A higher registered nurse (RN) skill mix significantly reduced log(winsorized(CPAD)) (β = −0.495, p<0.01) and log(ALOS) (β = −0.571, p<0.01), indicating improved cost efficiency and patient throughput. Increased nurse flexibility significantly increased log(ALOS) (β = 0.315, p<0.05) but reduced the readmission index (β = −0.895, p<0.01). No significant associations were found between skill mix and total margin, CPPD, or readmission index, nor between flexibility and financial metrics.
A richer RN skill mix enhances efficiency by reducing costs and length of stay, while increased staffing flexibility reduces readmissions but extends ALOS. These findings emphasize the complex interplay between nurse staffing and CAH performance. Strategic management of RN skill mix and flexibility is crucial for optimizing resource use and improving patient outcomes in rural hospitals.
Policymakers and CAH administrators should strategically balance RN expertise and staffing flexibility to ensure both financial viability and clinical excellence in these essential rural health care institutions.
Research has found that the use of medications for opioid use disorder (MOUD) varies across the rural-urban divide; however, relationships between rurality, MOUD, and substance use treatment wait times remain underexplored. This study analyzes associations between rurality, MOUD usage, and immediate access to outpatient treatment—that is, “treatment on demand”—in the United States.
Using 2021-2022 Treatment Episode Data Set Admissions (TEDS-A) data on outpatient treatment centers, we employ logistic regression to analyze treatment on demand (0-day wait time) as the outcome and rurality as the key predictor in models disaggregated into patients who utilized MOUD at intake and those who did not. Analyses are also disaggregated by Census region and division of the country.
Results show that rurality reduces the odds of treatment on demand in both MOUD (OR = .513, P <.001) and non-MOUD (OR = .593, P <.001) models, with slightly stronger effects in the former. Associations with rurality vary substantially by region of the country. MOUD models in the Midwest, West, and South show rurality has a significant negative effect; these negative associations held for non-MOUD models only in the South. Further, differences across Census divisions highlight rurality's spatial disparities at a more granular level.
Understanding barriers to treatment on demand for evidence-based treatments is a crucial aspect of ensuring people who have opioid use disorder in rural regions receive the care they need. Policies should focus on increasing access to treatment to avoid delays while considering regional differences.
The recent increase in mental health care providers offering telehealth may improve access by reducing travel costs, particularly for those in rural areas. This paper seeks to understand how mental health care utilization changed from 2019 to 2023 for rural and nonrural areas.
This study uses data from the National Health Interview Survey for 2019 and 2021-2023 (n = 118,652). To adjust the utilization rates for sociodemographic factors, a probit model with survey weights is used. For each year, the adjusted percentage of rural and nonrural populations receiving any mental health care in the past year is reported. Changes in demographic characteristics of those receiving care are also discussed.
This study finds that both rural and nonrural populations experienced large increases in adjusted mental health care utilization rates from 2019 to 2023. Utilization rates in rural areas grew 3.72 percentage points, from 9.35% (95% CI: 8.85-9.84) in 2019 to 13.07% (95% CI: 12.86-13.28) in 2023. For nonrural areas, utilization rates increased 4.40 percentage points, from 12.06% (95% CI: 11.79-12.74) in 2019 to 16.46% (95% CI: 15.82-17.11) in 2023.
Rural populations utilize less mental health care than nonrural populations, but both saw a substantial increase from 2019 to 2023. While telehealth may particularly benefit rural areas, these data suggest a larger increase in utilization for nonrural respondents. Future work is needed to better understand remote mental health care and rural populations.
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