Fatalism, Social Support and Self-Management Perceptions among Rural African Americans Living with Diabetes and Pre-Diabetes

Diabetes is a public health problem and a major risk factor for cardiovascular disease, the leading cause of death in the United States. Diabetes is prevalent among underserved rural populations. The purposes of this study were to perform secondary analyses of existing clinical trial data to determine whether a diabetes health promotion and disease risk reduction intervention had an effect on diabetes fatalism, social support, and perceived diabetes self-management and to provide precise estimates of the mean levels of these variables in an understudied population. Data were collected during a cluster randomized trial implemented among African American participants (n = 146) in a rural, southern area and analyzed using a linear mixed model. The results indicated that the intervention had no significant effect on perceived diabetes management (p = 0.8), diabetes fatalism (p = 0.3), or social support (p = 0.4). However, the estimates showed that, in the population, diabetes fatalism levels were moderate (95% CI = (27.6, 31.3)), and levels of social support (CI = (4.0, 4.4)) and perceived diabetes self-management (CI = (27.7, 29.3)) were high. These findings suggest that diabetes fatalism, social support, and self-management perceptions influence diabetes self-care and rural health outcomes and should be addressed in diabetes interventions.

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Influencing cardiovascular health habits in the rural, deep south: results of a cluster randomized trial

Health Education Research ◽

10.1093/her/cyy052 ◽

2019 ◽

Vol 34 (2) ◽

pp. 200-208

Author(s):

Laurie S Abbott ◽

Elizabeth H Slate ◽

Jennifer L Lemacks

Keyword(s):

Health Program ◽

Mixed Model ◽

Cardiovascular Health ◽

Linear Mixed Model ◽

Intervention Group ◽

The United States ◽

Control Group ◽

Cvd Risk ◽

Health Habits ◽

Cluster Randomized

Abstract Cardiovascular disease (CVD) is a major cause of death among people living in the United States. Populations, especially minorities, living in the rural South are disproportionately affected by CVD and have greater CVD risk, morbidity and mortality. Culturally relevant cardiovascular health programs implemented in rural community settings can potentially reduce CVD risk and facilitate health behavior modification. The purpose of this study was to examine the effects of a cardiovascular health promotion intervention on the health habits of a group of rural African American adults. The study had a cluster randomized controlled trial design involving 12 rural churches that served as statistical clusters. From the churches (n = 6) randomized to the intervention group, 115 participants were enrolled, received the 6-week health program and completed pretest–posttest measures. The 114 participants from the control group churches (n = 6) did not receive the health program and completed the same pretest–posttest measures. The linear mixed model was used to compare group differences from pretest to posttest. The educational health intervention positively influenced select dietary and confidence factors that may contribute toward CVD risk reduction.

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Social support and diabetes self-management behavior among Caribbean, Caribbean American, and African American women: A descriptive correlation study

Journal of Social Health and Diabetes ◽

10.4103/2321-0656.193994 ◽

2017 ◽

Vol 05 (01) ◽

pp. 016-024 ◽

Cited By ~ 1

Author(s):

Idethia Harvey ◽

Ledric Sherman ◽

Erica Spears ◽

Chanee Ford ◽

Helena Green

Keyword(s):

Social Support ◽

African American ◽

African American Women ◽

The United States ◽

Demographic Characteristics ◽

Self Management ◽

Foot Care ◽

Caribbean Women ◽

Management Behaviors ◽

Care Procedure

Abstract Background: Type-2 diabetes (T2D) is one of the most prevalent chronic and noncommunicable conditions both domestically and globally. The objective of this descriptive study was to examine how perceived social support impacted self-care management behavior among female African American and Caribbean populations. Materials and Methods: The cross-sectional study recruited 42 African American and Caribbean women diagnosed with T2D (M = 69.1, SD = 12.0). Univariate and bivariate analyses were conducted to explore the relationship between (1) demographic characteristics, (2) desired and received social support variables, and (3) self-management behaviors. Results: Caribbean women residing in the United States were more likely to follow general diet (M = 5.38, SD = 1.43) and to engage in physical activity (M = 4.31, SD = 2.39), whereas African American women were more likely to follow a specific diabetes diet (M = 3.79, SD = 1.60) and to monitor their glucose (M = 5.70, SD = 1.75). Caribbean women living in the United States Virgin Islands were more likely to follow recommended foot care procedure (M = 4.65, SD = 1.36). A negative correlation occurred between female participants exercising and the desired support in exercising. Women who reported that they desired more support with physical activity exercised less (r s= −0.34; P = 0.04). No relationship was found between foot care procedure and demographic characteristics or social support variables (i.e. desired or received). Conclusion: This study suggests directions for future studies that would examine the dynamics of social support and T2D self-management behaviors, and this study might be relevant to other Caribbean and African American communities with T2D both in North America and the Caribbean.

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A Bayesian linear mixed model for prediction of complex traits

Bioinformatics ◽

10.1093/bioinformatics/btaa1023 ◽

2020 ◽

Author(s):

Yang Hai ◽

Yalu Wen

Keyword(s):

Complex Traits ◽

Mixed Model ◽

Linear Mixed Model ◽

Rare Variants ◽

Disease Risk ◽

R Package ◽

Underlying Disease ◽

Supplementary Information ◽

True Effect Size ◽

Bayes Algorithm

Abstract Motivation Accurate disease risk prediction is essential for precision medicine. Existing models either assume that diseases are caused by groups of predictors with small-to-moderate effects or a few isolated predictors with large effects. Their performance can be sensitive to the underlying disease mechanisms, which are usually unknown in advance. Results We developed a Bayesian linear mixed model (BLMM), where genetic effects were modelled using a hybrid of the sparsity regression and linear mixed model with multiple random effects. The parameters in BLMM were inferred through a computationally efficient variational Bayes algorithm. The proposed method can resemble the shape of the true effect size distributions, captures the predictive effects from both common and rare variants, and is robust against various disease models. Through extensive simulations and the application to a whole-genome sequencing dataset obtained from the Alzheimer’s Disease Neuroimaging Initiatives, we have demonstrated that BLMM has better prediction performance than existing methods and can detect variables and/or genetic regions that are predictive. Availability The R-package is available at https://github.com/yhai943/BLMM Supplementary information Supplementary data are available at Bioinformatics online.

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Factors Influencing Crash Frequency on Colombian Rural Roads

PROMET - Traffic&Transportation ◽

10.7307/ptt.v32i4.3385 ◽

2020 ◽

Vol 32 (4) ◽

pp. 449-460

Author(s):

Andrea Arévalo-Támara ◽

Mauricio Orozco-Fontalvo ◽

Víctor Cantillo

Keyword(s):

Mixed Model ◽

Linear Mixed Model ◽

Negative Binomial ◽

Public Health Problem ◽

Operational Parameters ◽

Severe Injuries ◽

Crash Frequency ◽

Rural Roads ◽

National Network ◽

Analysis Of Results

Traffic crashes in Colombia have become a public health problem causing about 7,000 deaths and 45,000 severe injuries per year. Around 40% of these events occur on rural roads, taking note that the vulnerable users (pedestrians, motorcyclists, cyclists) account for the largest percentage of the victims. The objective of this research is to identify the factors that influence the frequency of crashes, including the singular orography of the country. For this purpose, we estimated Negative Binomial (Poisson-gamma) regression, Zero-inflated model, and generalized the linear mixed model, thus developing a comparative analysis of results in the Colombian context. The data used in the study came from the official sources regarding records about crashes with consequences; that is, with the occurrence of fatalities or injuries on the Colombian roads. For collecting the highway characteristics, an in-field inventory was conducted, gathering information about both infrastructure and operational parameters in more than three thousand kilometres of the national network. The events were geo-referenced, with registries of vehicles, involved victims, and their condition. The results suggest that highways in flat terrain have higher crash frequency than highways in rolling or mountainous terrain. Besides, the presence of pedestrians, the existence of a median and the density of intersections per kilometre also increase the probability of crashes. Meanwhile, roads with shoulders and wide lanes have lower crash frequency. Specific interventions in the infrastructure and control for reducing crashes risk attending the modelling results have been suggested.

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Robots Versus Humans: Automated Annotation Accurately Quantifies Essential Ocean Variables of Rocky Intertidal Functional Groups and Habitat State

Frontiers in Marine Science ◽

10.3389/fmars.2021.691313 ◽

2021 ◽

Vol 8 ◽

Author(s):

Gonzalo Bravo ◽

Nicolas Moity ◽

Edgardo Londoño-Cruz ◽

Frank Muller-Karger ◽

Gregorio Bigatti ◽

...

Keyword(s):

Machine Learning ◽

Functional Groups ◽

Mixed Model ◽

Linear Mixed Model ◽

Visual Analysis ◽

Gulf Of Maine ◽

The United States ◽

Marine Biodiversity ◽

Percent Cover ◽

Automated Annotation

Standardized methods for effectively and rapidly monitoring changes in the biodiversity of marine ecosystems are critical to assess status and trends in ways that are comparable between locations and over time. In intertidal and subtidal habitats, estimates of fractional cover and abundance of organisms are typically obtained with traditional quadrat-based methods, and collection of photoquadrat imagery is a standard practice. However, visual analysis of quadrats, either in the field or from photographs, can be very time-consuming. Cutting-edge machine learning tools are now being used to annotate species records from photoquadrat imagery automatically, significantly reducing processing time of image collections. However, it is not always clear whether information is lost, and if so to what degree, using automated approaches. In this study, we compared results from visual quadrats versus automated photoquadrat assessments of macroalgae and sessile organisms on rocky shores across the American continent, from Patagonia (Argentina), Galapagos Islands (Ecuador), Gorgona Island (Colombian Pacific), and the northeast coast of the United States (Gulf of Maine) using the automated software CoralNet. Photoquadrat imagery was collected at the same time as visual surveys following a protocol implemented across the Americas by the Marine Biodiversity Observation Network (MBON) Pole to Pole of the Americas program. Our results show that photoquadrat machine learning annotations can estimate percent cover levels of intertidal benthic cover categories and functional groups (algae, bare substrate, and invertebrate cover) nearly identical to those from visual quadrat analysis. We found no statistical differences of cover estimations of dominant groups in photoquadrat images annotated by humans and those processed in CoralNet (binomial generalized linear mixed model or GLMM). Differences between these analyses were not significant, resulting in a Bray-Curtis average distance of 0.13 (sd 0.11) for the full label set, and 0.12 (sd 0.14) for functional groups. This is the first time that CoralNet automated annotation software has been used to monitor “Invertebrate Abundance and Distribution” and “Macroalgal Canopy Cover and Composition” Essential Ocean Variables (EOVs) in intertidal habitats. We recommend its use for rapid, continuous surveys over expanded geographical scales and monitoring of intertidal areas globally.

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A Public Health Problem: Consequences of Trauma on Health Outcomes and the Role of Social Support

10.35831/sor.pubh/071119jp ◽

2019 ◽

Author(s):

Jennifer Prevost ◽

Rachel Worrell ◽

Margaret Gough Courney ◽

Kanye Godde

Keyword(s):

Social Support ◽

Stress Reactivity ◽

Public Health Problem ◽

High Sensitivity ◽

The United States ◽

Health Conditions ◽

Traumatic Experiences ◽

C Reactive Protein ◽

Reactive Protein

Abstract Introduction: Extensive research substantiates a negative correlation between stress and health. The implications of traumatic stress are complex, affecting the physical, psychological, physiological, and social health of individuals. The aim of this study was to examine the role of social support in relation to trauma-related health consequences. Methods: Nationally representative data were obtained from the Midlife in the United States study, covering the period 2004-2006, and used in regression models to predict the relationships between types of trauma (adult vs. childhood), measures of social support, and biomarkers of stress reactivity (cortisol, high sensitivity C-reactive protein (CRP), and number of health conditions). Results: The study found that an increase in traumatic experiences during adulthood was associated with a higher logged cortisol level, but social support did not buffer these effects. No significant trends were observed with childhood trauma. Conclusions: Results suggest the importance of addressing indicators from multiple domains simultaneously to investigate the effects of trauma and social support on biomarkers of stress. Keywords: social support, trauma, cortisol, high sensitivity C-reactive protein, health conditions

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Abstract P358: Discovery Loci and Generalization of Platelet Count Associations in the Hispanic Community Health Study: Study of Latinos (HCHS/SoL)

Circulation ◽

10.1161/circ.131.suppl_1.p358 ◽

2015 ◽

Vol 131 (suppl_1) ◽

Author(s):

Chani J Hodonsky ◽

Ursula Schick ◽

Jean Morrison ◽

Cathy Laurie ◽

John H Eckfeldt ◽

...

Keyword(s):

Platelet Count ◽

Mixed Model ◽

Linear Mixed Model ◽

Structural Integrity ◽

Genome Wide Association Study ◽

Genetic Model ◽

The United States ◽

Actin Binding ◽

Health Study ◽

A Genome

Background: The biology of platelets_anuclear megakaryocyte fragments required for clotting_is well defined, with abnormalities resulting in clotting disorders ranging from asymptomatic to severe. Although platelet count (PLT) is highly heritable (h 2 =0.57 in NHANES), genetic regulation of this trait remains incompletely characterized. In particular, Hispanic Latinos are a diverse population in which the genetic variability of PLT has not been analyzed. We aimed to 1) identify novel loci associated with PLT in participants of HCHS/SoL; and 2) determine if previously identified PLT loci generalize to the Hispanic Latino population. Methods: We performed a genome-wide association study of PLT in 12,491 participants of HCHS/SoL, which includes individuals with Dominican, Puerto Rican, Mexican, Cuban, South American, and Central American ancestral origins residing in the United States. Participants were genotyped on the Illumina SoL Omni2.5M array and imputed to the 1000 Genomes Phase I Reference panel. We implemented linear mixed-model regression assuming an additive genetic model, adjusting for sex, age, study center, ancestry and sample weights, and including random effects for individual relatedness, household, and block group. Results: Ten independent loci were significantly (α = 5x10 -8 ) associated with PLT in HCHS/SoL and 13 of 57 previously identified platelet-count GWAS loci generalized to HCHS/SoL (+/-500kb, α = 8.78x10 -4 ). Discovery loci included a significant association near GABBR1 (rs3131857, MAF = 40%, β = -0.16) and a suggestive association near ETV7 (rs9470264, MAF = 20%, β = -0.19). Furthermore, a noncoding variant in ACTN1 was associated with increased PLT (rs117672662, MAF = 6%, β = 0.61); ACTN1 codes for alpha-actinin, a multi-isoform actin-binding protein involved in cytoskeleton organization and platelet/megakaryocyte structural integrity. Missense mutations in ACTN1 were recently implicated in congenital thrombocytopenia; exome sequencing also associated this locus with PLT, which supports a potential functional role in PLT for this gene. Conditional regression analyses to assess secondary association signals are in progress. Conclusions: Genetic associations in two discovery loci ( ETV7 and GABBR1 ) underscore the benefit of using diverse populations in GWAS. Expanding the number of loci associated with platelet count will help elucidate disease mechanisms and develop approaches to treat platelet disorders in populations of all ancestries.

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Code-switching attitudes and their effects on acceptability judgment tasks

Linguistic Approaches to Bilingualism ◽

10.1075/lab.16006.bad ◽

2017 ◽

Vol 8 (1) ◽

pp. 5-24 ◽

Cited By ~ 18

Author(s):

Lucia Badiola ◽

Rodrigo Delgado ◽

Ariane Sande ◽

Sara Stefanich

Keyword(s):

United States ◽

Mixed Model ◽

Linear Mixed Model ◽

The United States ◽

Code Switching ◽

Negative Attitudes ◽

Bilingual Speakers ◽

Positive Attitudes ◽

Acceptability Judgment

Abstract The present study examines the effects of code-switching (CS) attitudes in Acceptability Judgment Tasks (AJTs) among early Spanish/English bilinguals in the United States. In doing so, we explore whether negative attitudes towards CS result in lower/degraded ratings, and, likewise, whether positive attitudes result in higher acceptability ratings. Fifty Spanish/English bilinguals completed a survey that comprised a linguistic background questionnaire and a set of monolingual and code-switched sentences featuring two sets of stimuli, pro-drop (Sande, 2015) and pronouns (Koronkiewicz, 2014), that they rated on a 1–7 Likert scale; additionally, the survey included a final component that gathered information about the speakers’ attitudes towards CS. The pro-drop and pronouns code-switched stimuli gave rise to a total of four conditions. Results from a Linear Mixed Model revealed that all participants, regardless of attitude, distinguished between all Conditions. Furthermore, an effect for attitude was found for two of the conditions, such that the more positive the attitude, the higher the rating given on the AJT. In fact, these two conditions were composed of the CS structures that were rated higher by participants in Sande (2015) and Koronkiewicz (2014). No effect for attitude was found for CS structures that were rated low in the original studies. Thus, this investigation suggests that the attitudes that bilingual speakers have towards CS play a role in the ratings that they provide in AJTs, but in a manner that highlights, rather than obscures, the rule-governed nature of CS.

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Barriers and Opportunities

The Diabetes Educator ◽

10.1177/0145721714559131 ◽

2014 ◽

Vol 41 (1) ◽

pp. 86-94 ◽

Cited By ~ 32

Author(s):

Emily Ann Hallgren ◽

Pearl Anna McElfish ◽

Jellesen Rubon-Chutaro

Keyword(s):

United States ◽

Focus Groups ◽

Health Beliefs ◽

Access To Health Care ◽

Diabetes Management ◽

Transportation Cost ◽

The United States ◽

Self Management ◽

Management Interventions ◽

Management Behaviors

PurposeThis study investigates the beliefs and perceptions related to type 2 diabetes that influence diabetes self-management behaviors for Marshallese in the United States. Using the health belief model as a theoretical framework, the researchers seek to better understand the underlying beliefs that motivate or impede diabetes self-management behaviors.MethodsThe community-based participatory research (CBPR) collaborative engaged in 14 months of preliminary fieldwork and conducted 2 tiers of focus groups for this project as part of the long-term commitment to reducing health inequalities in the Marshallese community. The CBPR team conducted an initial round of 2 exploratory focus groups (n = 15). Based on the knowledge gained, researchers held a second round of focus groups (n = 13) on health beliefs regarding diabetes. All participants were Marshallese, aged 18 years and older, and included men and women. Participants either had a diagnosis of diabetes or were a caretaker of someone with diabetes.ResultsThe findings elucidate the structural and nonstructural barriers to successful diabetes self-management for Marshallese in the United States. Barriers include eating differently from the rest of the family, social stigma of diabetes, transportation, cost, lack of access to health care, and cultural and language barriers.ConclusionsWhile there are significant barriers to improving diabetes self-management, there are also areas of opportunity, including family and peer reinforcement to encourage proper diabetes management behaviors and a growing community desire to lift the stigma of diabetes. The CBPR team offers recommendations to make diabetes management interventions more culturally appropriate and effective for the Marshallese population.

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Developing Biomarkers of Rice Bran and Navy Bean Intake via Integrated Metabolomics from Infants, Children and Adults for Association with Gut Health Properties

Current Developments in Nutrition ◽

10.1093/cdn/nzaa045_096 ◽

2020 ◽

Vol 4 (Supplement_2) ◽

pp. 463-463

Author(s):

Elizabeth Ryan ◽

Bridget Baxter ◽

Katherine Li ◽

Lisa Wolfe ◽

Linxing Yao ◽

...

Keyword(s):

Rice Bran ◽

Dietary Patterns ◽

Mixed Model ◽

Linear Mixed Model ◽

Disease Risk ◽

Placebo Control ◽

Targeted Metabolomics ◽

Navy Bean ◽

Dietary Biomarkers ◽

Navy Beans

Abstract Objectives Self-reporting methods for dietary exposure are error-prone and have had limited impact to identify food components that mitigate disease risk. The purpose of this study was to use non-targeted and targeted metabolomics from feeding trials with rice bran and navy beans for the identification of dietary biomarkers across the lifespan. Methods Prepared meals/snacks, and biological samples from randomized-controlled trials performed in 50 infants, 38 children and 49 adults were utilized in this study. Diet groups were placebo control, rice bran, cooked navy bean powder, or a combination of rice bran/navy beans with increasing daily doses by age group and for duration of 4, 12 or 24 weeks per protocol. Plasma/dried blood spots, urine or stool samples were collected at a baseline, midpoint and endpoint. Non-targeted profiling was performed with UPLC-MS/MS, and metabolite quantification by LC-triple-quadropole (LC-QQQ-MS). A linear mixed model to compare between time points in each group was performed using SAS. Results The plasma/blood metabolomes contained between 771–1001 metabolites and showed variation in ∼20–30% of the profile following intervention. Fold changes over time and fold-differences in metabolite abundance were assessed by age (P < 0.05). There were 10–20 candidate identified from metabolomics across studies and with relevance to rice bran and/or navy bean were applied for targeted assay development. Food metabolomes confirmed metabolite origins and the host and microbial metabolism. Candidate metabolites included pipecolate, S-methlycysteine, S-methylcysteine sulfoxide, trigonelline, N-methyl-pipecolate, pyridoxal, 2-hydroxyhippurate, apigenin, xanthurenate, chiro-inositol, and salicylate. Inter-individual variation was reported across studies, ages and dietary patterns. Conclusions Dietary biomarkers for rice bran and/or navy bean intake merit additional selection criteria from non-targeted metabolomics. Targeted assays will need validation in larger cohort investigations using cross-over study designs and diverse dietary patterns. Funding Sources This work was supported by a grant from the National Institute of Foods and Agriculture-U.S Department of Agriculture (NIFA-USDA).

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