Características demográficas, de salud y apoyo familiar de adultos mayores en el Programa de Cuidado Diurnos de Jacaleapa, El Paraíso, Honduras, 2020

El objetivo del estudio fue describir las características de los participantes en un programa de cuidados diurnos que reciben servicios integrados de salud y recreación social además de indagar las percepciones de sus familiares sobre el impacto del programa sobre el bienestar de en adultos mayores del centro de cuidados diurnos, Jacaleapa, Honduras. El diseño fue de tipo descriptivo, con una encuesta de corte transversal con 302 adultos mayores participantes y 302 familiares acompañantes. Se emplearon preguntas estructuradas sociodemográficas, de salud auto reportada, y apoyo familiar. Según las características demográficas, la mayoría fueron de sexo femenino (76.5%), en edades de 60-69 años (70.19%). El 68.9% de los adultos mayores finalizaron sólo su educación primaria; desempeñándose la mayor parte de su vida a quehaceres del hogar (73.8%). La gran mayoría reportó enfermedades crónicas (98%). El impacto percibido de los familiares fue muy positivo. En conclusión, el estudio permitió conocer la realidad acerca de las condiciones del adulto mayor a nivel demográfico y en salud lo que aporta a trazar estrategias que potencien la calidad de los servicios de salud al adulto mayor, en este caso al programa del Centro de Cuidados Diurno de Jacaleapa en el Paraíso

Community Priority Index: utility, applicability and validation for priority setting in community-based participatory research

Background. Providing practitioners with an intuitive measure for priority setting that can be combined with diverse data collection methods is a necessary step to foster accountability of the decision-making process in community settings. Yet, there is a lack of easy-to-use, but methodologically robust measures, that can be feasibly implemented for reliable decision-making in community settings. To address this important gap in community based participatory research (CBPR), the purpose of this study was to demonstrate the utility, applicability, and validation of a community priority index in a community-based participatory research setting. Design and Methods. Mixed-method study that combined focus groups findings, nominal group technique with six key informants, and the generation of a Community Priority Index (CPI) that integrated community importance, changeability, and target populations. Bootstrapping and simulation were performed for validation. Results. For pregnant mothers, the top three highly important and highly changeable priorities were: stress (CPI=0.85; 95%CI: 0.70, 1.00), lack of affection (CPI=0.87; 95%CI: 0.69, 1.00), and nutritional issues (CPI=0.78; 95%CI: 0.48, 1.00). For non-pregnant women, top priorities were: low health literacy (CPI=0.87; 95%CI: 0.69, 1.00), low educational attainment (CPI=0.78; 95%CI: 0.48, 1.00), and lack of self-esteem (CPI=0.72; 95%CI: 0.44, 1.00). For children and adolescents, the top three priorities were: obesity (CPI=0.88; 95%CI: 0.69, 1.00), low self-esteem (CPI=0.81; 95%CI: 0.69, 0.94), and negative attitudes toward education (CPI=0.75; 95%CI: 0.50, 0.94). Conclusions. This study demonstrates the applicability of the CPI as a simple and intuitive measure for priority setting in CBPR

Social Determinants of Racial and Ethnic Disparities in Perinatal Morbidity: Social Origins of Perinatal Health Study

BACKGROUND: The social causation of preterm birth remains elusive, without an adequate explanatory framework. Thus, this study proposed and evaluated a conceptual model of the social determinants of perinatal health for the understanding of perinatal health disparities. METHODS: A prospective cohort study was conducted with pregnant women between 20 and 35 weeks gestation who were participating in two Healthy Start programs in Central Florida, from July 2011-August 2013. Perinatal health was operationalized based on gestational age, birth weight, and healthy start infant risk screen score. The predictors were: early life adversity, social position, maternal health-related quality of life, maternal stress, racism and discrimination, lack of social support, father involvement during pregnancy, intimate partner violence, and adverse maternal behaviors. Data collection consisted of a self-administered survey and birth outcome data was obtained from Healthy Start administrative databases. The statistical framework was structural equation modeling. RESULTS: The study sample was racially and ethnically diverse (N, Hispanics=72; N, non-Hispanic blacks=61; and N, non-Hispanic whites=48). The majority of mothers in this study were single or not married (cumulative 76%), US born (74.6%), and with English speaking preference (74.6%). The sample tended to cluster in low income groups (cumulative 58% less than $25,000 annual household income) and with education levels of less than high school (79.6%). A greater proportion of Hispanic mothers were married (66.7%) compared to non-Hispanic blacks (34.4%) and non-Hispanic whites (47.9%). Only 41.7% had completed high school, compared to 63.9% non-Hispanic blacks and 64.6% non-Hispanic whites. Nearly all non-Hispanic blacks and non-Hispanic whites were born in the US, compared to only 43.1% Hispanic mothers. Only 40% of non-Hispanic blacks reported on currently living with the baby\u27s father at the time of the survey, compared to 66.2% for Hispanic mothers, and 58.3% for non-Hispanic whites. Furthermore, non-Hispanic blacks reported a greater proportion of discriminatory experiences in daily situations (mean = 4.74), compared to the other groups (mean for Hispanics was 2.14, and mean for non-Hispanic whites was 1.95). Non-Hispanic whites reported the greater proportion of daily alcohol use (mean 3.8 beverages per month), compared to other groups (Hispanic mean was 0.69, and non-Hispanic blacks mean was 1.68). Non-Hispanic white mothers also presented a higher mean of adverse childhood experiences before 18 years of life (mean = 3.4), compared to other groups (mean for Hispanics was 1.63, mean for non-Hispanic blacks was 2.48). With the exception of the confirmatory factor analysis for intimate partner violence (low correlations with common factor), all other confirmatory factor analyses demonstrated an acceptable Chi-square to degrees of freedom ratio (\u3c6), and the RMSEA was less than 0.08 (minimum for acceptance). Thus, structural equation models were estimated subsequently. The first model was a model of direct effects between social position and perinatal health (hypothesis 1: direct effects), which demonstrated a good fit as indicated by X2/DF ratio of 1.4 (Chi-Square = 19, DF =13) and a RMSEA of 0.05. However, the direct effect of social position was very small and non-significant (Beta=-.02, p-value =.76), supporting the conclusion that a simple direct effect of social position on perinatal health was not found in this population. The second model explored indirect effects of social position through intermediate factors (hypothesis 2: indirect effects), which demonstrated a good fit to the data, as indicated by a Chi-square/df ratio = 1.45 and RMSEA=.05. Social support was a statistically significant mediator between social position (Beta=0.284, p\u3c0.05) and perinatal health (Beta=0.22, p\u3c0.05). The third model incorporated adverse childhood experiences as predictor of social position effects. Adverse childhood experiences were significantly associated with social position (Beta=.363, p\u3c0.05) and moderated the effects of social position on social support and perinatal health. In the presence of adverse childhood experiences, the social position was significantly associated to maternal health-related quality of life (Beta=-0.226, p\u3c0.05) and maladaptive maternal behaviors (Beta=0.654, p\u3c0.05). CONCLUSION: This study demonstrated synergistic effects of social determinants of health. Controlling for all factors considered, social support was significantly associated with perinatal health, which presents implications for strengthening prenatal programs that provide support to pregnant women. Findings need to be replicated in larger studies with the US general population. Policy makers and researchers need to pay greater attention to the role of early life adversity on perinatal health outcomes

Transformative Use of an Improved All-Payer Hospital Discharge Data Infrastructure for Community-Based Participatory Research: A Sustainability Pathway

Objective: To describe the use of a clinically enhanced maternal and child health (MCH) database to strengthen community-engaged research activities, and to support the sustainability of data infrastructure initiatives. Data Sources/Study Setting Data Sources/Study Setting: Population-based, longitudinal database covering over 2.3 million mother–infant dyads during a 12-year period (1998–2009) in Florida. Setting: A community-based participatory research (CBPR) project in a socioeconomically disadvantaged community in central Tampa, Florida. Study Design: Case study of the use of an enhanced state database for supporting CBPR activities. Principal Findings: A federal data infrastructure award resulted in the creation of an MCH database in which over 92 percent of all birth certificate records for infants born between 1998 and 2009 were linked to maternal and infant hospital encounter-level data. The population-based, longitudinal database was used to supplement data collected from focus groups and community surveys with epidemiological and health care cost data on important MCH disparity issues in the target community. Data were used to facilitate a community-driven, decision-making process in which the most important priorities for intervention were identified. Conclusions: Integrating statewide all-payer, hospital-based databases into CBPR can empower underserved communities with a reliable source of health data, and it can promote the sustainability of newly developed data systems

Community-Based Decision Making and Priority Setting Using the R Software: The Community Priority Index

This paper outlines how to compute community priority indices in the context of multicriteria decision making in community settings. A simple R function was developed and validated with community needs assessment data. Particularly, the first part of this paper briefly overviews the existing methods for priority setting and reviews the utility of a multicriteria decision-making approach for community-based prioritization. The second part illustrates how community priority indices can be calculated using the freely available R program to handle community data by showing the computational and mathematical steps of CPI (Community Priority Index) with bootstrapped 95% confidence intervals

Community-Based Decision Making and Priority Setting Using the R Software: The Community Priority Index

This paper outlines how to compute community priority indices in the context of multicriteria decision making in community settings. A simple R function was developed and validated with community needs assessment data. Particularly, the first part of this paper briefly overviews the existing methods for priority setting and reviews the utility of a multicriteria decision-making approach for community-based prioritization. The second part illustrates how community priority indices can be calculated using the freely available R program to handle community data by showing the computational and mathematical steps of CPI (Community Priority Index) with bootstrapped 95% confidence intervals

Community-Based Decision Making and Priority Setting Using the R Software: The Community Priority Index

This paper outlines how to compute community priority indices in the context of multicriteria decision making in community settings. A simple R function was developed and validated with community needs assessment data. Particularly, the first part of this paper briefly overviews the existing methods for priority setting and reviews the utility of a multicriteria decision-making approach for community-based prioritization. The second part illustrates how community priority indices can be calculated using the freely available R program to handle community data by showing the computational and mathematical steps of CPI (Community Priority Index) with bootstrapped 95% confidence intervals

Bridging the Under-Five Mortality Gap for Africa in the Era of Sustainable Development Goals: An Ordinary Least Squares (OLS) Analysis

Background: While Africa achieved significant progress in reducing under-five mortality rate (U5MR) in the MDGs era, it did not achieve the set target and still has the highest average of 81 deaths per 1000 live births compared to a global average of 43 deaths. The SDG number 3 has set a new target of reducing U5MR to 25 deaths per 1000 births in the world, which serves a huge challenge, especially for Africa. Socioeconomic inequities that remain unaddressed across countries account for Africa’s high U5MR. Unless there is adequate prioritization of important socioeconomic, healthcare, and environmental factors, the new SDGs target will be hindered. Objectives: In this study, our primary objective was to analyse and assess factors that account most for the U5MR inequities between Africa and the rest of the world. Methods: We conducted a series of ordinary least squares (OLS) regression-based prioritization analysis of socioeconomic, healthcare, and environmental variables from 43 African countries in a pool of 109 countries from around the world to understand the most important factors that account most for the high U5MR in Africa. Findings: The results suggest that the most critical category for bridging the U5MR gap with the rest of the world is improved healthcare access. However, with all categories examined together, the OLS regression showed that the most important factors that accounted for Africa’s high U5MR compared with the rest of the world were, in order: fertility rate, access to improved water, total health expenditure per capita, access to improved sanitation, and female employment rate. Conclusions: The findings reveal that Africa will significantly benefit from interventions geared towards both the treatment and prevention of acute infectious diseases in the form of providing affordable maternal healthcare services, as well as providing access to improved drinking water and sanitation