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The emergence of the COVID-19 pandemic significantly changed the prenatal care experience, specifically regarding medical appointments and social opportunities. It is critical to capture this change through the narratives of pregnant people, particularly those of marginalized populations, whose voices may often be underrepresented in the literature. This mixed-methods paper summarizes the experiences of 40 pregnant Black/African American (AA) women during the COVID-19 pandemic. A cross-sectional, online survey was administered between 2020 and 2021 to assess prenatal health and the impacts of the COVID-19 pandemic on patients' pregnancy experience. Coping behaviors during the pandemic were self-reported using the COPE-IS. Univariate analyses were conducted. An additional analysis of participants (n = 4) was explored through a week-long qualitative exercise using a photo documentation procedure. Photo-Elicitation Interviews (PEI) were conducted to capture and center their pandemic pregnancy experiences. Sources of stress during the pandemic varied, with the most common being financial concerns (n = 19, 47.5%). Over half of the sample (n = 18, 54.5%) self-reported increases in their positive coping behaviors during the pandemic, such as communicating with friends and family, talking to healthcare providers, listening to music, and engaging in spiritual practices–such as prayer. The four PEI study participants reflected on the impacts of social distancing on their prenatal experience and mentioned hospital and provider-related weariness due to their race. The findings of this study suggest that during the COVID-19 pandemic, Black/AA pregnant women in Charlotte, NC used social support, mindfulness practices, self-advocacy, and health literacy to navigate challenges present during their prenatal health experience. This paper highlights the personal, social, and structural experiences of pregnant women during a public health crisis so that responsive and effective programs or policies can be planned in the future. [ABSTRACT FROM AUTHOR]

Introduction: Action 3 of the UN Decade of Healthy Ageing plan is to deliver integrated care to improve older adults' lives. Integrated care is vital in meeting the complex needs of people with dementia but little is known about how this is or could be delivered in low and middle income countries (LMIC). This paper provides insights into previously unknown care system structures and on the potential and reality of delivering integrated care in Central America for people with dementia. Methods: A social network analysis (SNA) methodology was adopted to engage with providers of services for older adults and families with dementia in Guatemala, El Salvador, Honduras, Costa Rica and Panama. Sixty-eight (68) semi-structured interviews were completed, 57 with organisations and 11 with families. Results: Across the five countries there was evidence of fragmentation and low integration within the dementia care systems. A variety of services and types of providers are present in all five countries, and high levels of diversified connections exist among organisations of differing disciplines. However, unawareness among network members about other members that they could potentially form active links with is a barrier on the path to integration. Conclusion: This innovative and robust study demonstrates SNA can be applied to evaluate LMIC care systems. Findings provide baselines of system structures and insights into where resources are needed to fortify integration strategies. Results suggest that Central American countries have the building blocks in place to develop integrated care systems to meet the needs of people with dementia, but the links across service providers are opportunistic rather than context based coordinated integration policies. [ABSTRACT FROM AUTHOR]

Aim: This study examined cross-sectional population-based rates in reported need and unmet need for occupational, physical, and speech therapy services in children with autism spectrum disorder (ASD) compared with children with attention-deficit-hyperactivity disorder (ADHD) and cerebral palsy (CP).Method: The 2005-2006 and 2009-2010 (USA) National Survey of Children with Special Health Care data sets were used to compare therapy need and unmet need among children younger than 18 years with ASD (n=5178), ADHD (n=20 566), and CP (n=1183). Bivariate approaches and multivariate logistic regression using imputed data were used to identify associations between child and family characteristics, and access to therapy services.Results: After adjusting for other variables, children with ASD had a significantly greater likelihood of having an unmet therapy need compared with children with ADHD (odds ratio [OR] 1.66, 95% confidence interval [CI] 1.36-2.03), but a similar unmet need as children with CP (OR 1.30, 95% CI 0.97-1.74). Factors associated with unmet need included survey year, younger child age, no health insurance, and increased functional and behavioral difficulties.Interpretation: Children in our sample had greater unmet therapy needs in 2009 than in 2005. Caregiver-reported reasons for unmet need included cost and school resources. Research examining future trends in therapy access are warranted for children with ASD and CP.What This Paper Adds: Children with complex diagnoses of autism spectrum disorder and cerebral palsy had reported unmet need for therapy services. High costs of therapy were the primary reported reason contributing to reduced access among children. [ABSTRACT FROM AUTHOR]

Background: Annually since 2010, the University of Wisconsin Population Health Institute and the Robert Wood Johnson Foundation have produced the County Health Rankings--a "population health checkup" for the nation's over 3,000 counties. The purpose of this paper is to review the background and rationale for the Rankings, explain in detail the methods we use to create the health rankings in each state, and discuss the strengths and limitations associated with ranking the health of communities. Methods: We base the Rankings on a conceptual model of population health that includes both health outcomes (mortality and morbidity) and health factors (health behaviors, clinical care, social and economic factors, and the physical environment). Data for over 30 measures available at the county level are assembled from a number of national sources. Z-scores are calculated for each measure, multiplied by their assigned weights, and summed to create composite measure scores. Composite scores are then ordered and counties are ranked from best to worst health within each state. Results: Health outcomes and related health factors vary significantly within states, with over two-fold differences between the least healthy counties versus the healthiest counties for measures such as premature mortality, teen birth rates, and percent of children living in poverty. Ranking within each state depicts disparities that are not apparent when counties are ranked across the entire nation. Discussion: The County Health Rankings can be used to clearly demonstrate differences in health by place, raise awareness of the many factors that influence health, and stimulate community health improvement efforts. The Rankings draws upon the human instinct to compete by facilitating comparisons between neighboring or peer counties within states. Since no population health model, or rankings based off such models, will ever perfectly describe the health of its population, we encourage users to look to local sources of data to understand more about the health of their community. [ABSTRACT FROM AUTHOR]

Introduction Accurate measurement of health inequities is indispensable to track progress or to identify needs for health equity policy interventions. A key empirical task is to measure the extent to which observed inequality in health - a difference in health - is inequitable. Empirically operationalizing definitions of health inequity has generated an important question not considered in the conceptual literature on health inequity. Empirical analysis can explain only a portion of observed health inequality. This paper demonstrates that the treatment of unexplained inequality is not only a methodological but ethical question and that the answer to the ethical question - whether unexplained health inequality is unfair - determines the appropriate standardization method for health inequity analysis and can lead to potentially divergent estimates of health inequity. Methods We use the American sample of the 2002-03 Joint Canada/United States Survey of Health and measure health by the Health Utilities Index (HUI). We model variation in the observed HUI by demographic, socioeconomic, health behaviour, and health care variables using Ordinary Least Squares. We estimate unfair HUI by standardizing fairness, removing the fair component from the observed HUI. We consider health inequality due to factors amenable to policy intervention as unfair. We contrast estimates of inequity using two fairness- standardization methods: direct (considering unexplained inequality as ethically acceptable) and indirect (considering unexplained inequality as unfair). We use the Gini coefficient to quantify inequity. Results Our analysis shows that about 75% of the variation in the observed HUI is unexplained by the model. The direct standardization results in a smaller inequity estimate (about 60% of health inequality is inequitable) than the indirect standardization (almost all inequality is inequitable). Conclusions The choice of the fairness-standardization method is ethical and influences the empirical health inequity results considerably. More debate and analysis is necessary regarding which treatment of the unexplained inequality has the stronger foundation in equity considerations. [ABSTRACT FROM AUTHOR]