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      Exploring the consequences of food insecurity and harnessing the power of peer navigation and mHealth to reduce food insecurity and cardiometabolic comorbidities among persons with HIV: protocol for development and implementation trial of weCare/Secure

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          Abstract

          Background

          Food insecurity, or the lack of consistent access to nutritionally adequate and safe foods, effects up to 50% of people living with HIV (PWH) in the United States (US). PWH who are food insecure have lower antiretroviral adherence, are less likely to achieve viral suppression, and are at increased risk developing of serious illnesses, including cardiometabolic comorbidities. The objectives of this study are to better understand how food insecurity contributes to the development of cardiometabolic comorbidities among PWH and to test a novel bilingual peer navigation-mHealth intervention (weCare/Secure) designed to reduce these comorbidities in food-insecure PWH with prediabetes or Type 2 diabetes (T2DM).

          Methods

          In Aim 1, we will recruit a longitudinal cohort of 1800 adult (≥18 years) PWH from our clinic-based population to determine the difference in the prevalence and incidence of cardiometabolic comorbidities between food-secure and food-insecure PWH. Food insecurity screening, indicators of cardiometabolic comorbidities, and other characteristics documented in the electronic health record (EHR) will be collected annually for up to 3 years from this cohort. In Aim 2, we will conduct a randomized controlled trial among a sample of food-insecure PWH who have prediabetes or T2DM to compare changes in insulin sensitivity over 6 months between participants in weCare/Secure and participants receiving usual care. In Aim 3, we will conduct semi-structured individual in-depth interviews to explore the effect of the intervention among intervention participants with varying insulin sensitivity outcomes.

          Trial status

          Aim 1 (longitudinal cohort) recruitment began in May 2022 and is ongoing. Aim 2 (intervention) recruitment is planned for spring 2023 and is expected to be completed in spring 2024. Aim 3 (process evaluation) data collection will occur after sufficient completion of the 6-month assessment in Aim 2. Final results are anticipated in fall 2025.

          Conclusions

          This research seeks to advance our understanding of how food insecurity impacts the development of cardiometabolic comorbidities among PWH and how food insecurity interventions may alleviate relevant comorbidities. Given the growing interest among health systems in addressing food insecurity, if the intervention is found to be efficacious, it could be broadly disseminated across HIV clinical care settings.

          Trial registration

          ClinicalTrials.gov NCT04943861. Registered on June 29, 2021.

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          Most cited references60

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          Homeostasis model assessment: insulin resistance and beta-cell function from fasting plasma glucose and insulin concentrations in man.

          The steady-state basal plasma glucose and insulin concentrations are determined by their interaction in a feedback loop. A computer-solved model has been used to predict the homeostatic concentrations which arise from varying degrees beta-cell deficiency and insulin resistance. Comparison of a patient's fasting values with the model's predictions allows a quantitative assessment of the contributions of insulin resistance and deficient beta-cell function to the fasting hyperglycaemia (homeostasis model assessment, HOMA). The accuracy and precision of the estimate have been determined by comparison with independent measures of insulin resistance and beta-cell function using hyperglycaemic and euglycaemic clamps and an intravenous glucose tolerance test. The estimate of insulin resistance obtained by homeostasis model assessment correlated with estimates obtained by use of the euglycaemic clamp (Rs = 0.88, p less than 0.0001), the fasting insulin concentration (Rs = 0.81, p less than 0.0001), and the hyperglycaemic clamp, (Rs = 0.69, p less than 0.01). There was no correlation with any aspect of insulin-receptor binding. The estimate of deficient beta-cell function obtained by homeostasis model assessment correlated with that derived using the hyperglycaemic clamp (Rs = 0.61, p less than 0.01) and with the estimate from the intravenous glucose tolerance test (Rs = 0.64, p less than 0.05). The low precision of the estimates from the model (coefficients of variation: 31% for insulin resistance and 32% for beta-cell deficit) limits its use, but the correlation of the model's estimates with patient data accords with the hypothesis that basal glucose and insulin interactions are largely determined by a simple feed back loop.
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            The Association Between Income and Life Expectancy in the United States, 2001-2014.

            The relationship between income and life expectancy is well established but remains poorly understood.
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                Author and article information

                Contributors
                aetanner@uncg.edu
                dpalaksh@wakehealth.edu
                cmorse@wakehealth.edu
                lmann@wakehealth.edu
                jalonzo@wakehealth.edu
                jegarcia@wakehealth.edu
                eswright@wakehealth.edu
                adharod@wakehealth.edu
                sisom@wakehealth.edu
                asucaldi@wakehealth.edu
                lrefugio@wakehealth.edu
                srhodes@wakehealth.edu
                Journal
                Trials
                Trials
                Trials
                BioMed Central (London )
                1745-6215
                12 December 2022
                12 December 2022
                2022
                : 23
                Affiliations
                [1 ]GRID grid.266860.c, ISNI 0000 0001 0671 255X, Department of Public Health Education, , University of North Carolina Greensboro, ; Coleman 437E, Greensboro, NC 27402 USA
                [2 ]GRID grid.241167.7, ISNI 0000 0001 2185 3318, Department of Internal Medicine, , Wake Forest University School of Medicine, ; Winston-Salem, USA
                [3 ]GRID grid.241167.7, ISNI 0000 0001 2185 3318, Department of Pediatrics, , Wake Forest University School of Medicine, ; Winston-Salem, USA
                [4 ]GRID grid.241167.7, ISNI 0000 0001 2185 3318, Department of Epidemiology and Prevention, , Wake Forest University School of Medicine, ; Winston-Salem, USA
                [5 ]GRID grid.241167.7, ISNI 0000 0001 2185 3318, Section on Infectious Diseases, Department of Internal Medicine, , Wake Forest University School of Medicine, ; Winston-Salem, USA
                [6 ]GRID grid.241167.7, ISNI 0000 0001 2185 3318, Department of Social Sciences and Health Policy, , Wake Forest University School of Medicine, ; Winston-Salem, USA
                [7 ]GRID grid.241167.7, ISNI 0000 0001 2185 3318, Department of Implementation Science, , Wake Forest University School of Medicine, ; Winston-Salem, USA
                [8 ]GRID grid.241167.7, ISNI 0000 0001 2185 3318, Department of Internal Medicine, Informatics and Analytics, , Wake Forest University School of Medicine, ; Winston-Salem, USA
                [9 ]GRID grid.241167.7, ISNI 0000 0001 2185 3318, Wake Forest Center for Healthcare Innovation, , Wake Forest University School of Medicine, ; Winston-Salem, USA
                [10 ]GRID grid.241167.7, ISNI 0000 0001 2185 3318, Wake Forest Center for Biomedical Informatics, , Wake Forest University School of Medicine, ; Winston-Salem, USA
                [11 ]GRID grid.241167.7, ISNI 0000 0001 2185 3318, Department of Biostatistics and Data Science, , Wake Forest University School of Medicine, ; Winston-Salem, USA
                Article
                6924
                10.1186/s13063-022-06924-3
                9743787
                36510319
                c8e06b72-f422-4c54-90bc-746d5ada14bd
                © The Author(s) 2022

                Open AccessThis article is licensed under a Creative Commons Attribution 4.0 International License, which permits use, sharing, adaptation, distribution and reproduction in any medium or format, as long as you give appropriate credit to the original author(s) and the source, provide a link to the Creative Commons licence, and indicate if changes were made. The images or other third party material in this article are included in the article's Creative Commons licence, unless indicated otherwise in a credit line to the material. If material is not included in the article's Creative Commons licence and your intended use is not permitted by statutory regulation or exceeds the permitted use, you will need to obtain permission directly from the copyright holder. To view a copy of this licence, visit http://creativecommons.org/licenses/by/4.0/. The Creative Commons Public Domain Dedication waiver ( http://creativecommons.org/publicdomain/zero/1.0/) applies to the data made available in this article, unless otherwise stated in a credit line to the data.

                Funding
                Funded by: FundRef http://dx.doi.org/10.13039/100000056, National Institute of Nursing Research;
                Award ID: 1R01NR020307-01
                Award Recipient :
                Categories
                Study Protocol
                Custom metadata
                © The Author(s) 2022

                Medicine
                hiv,food insecurity,diabetes,peer navigation,mhealth,feasibility studies,united states
                Medicine
                hiv, food insecurity, diabetes, peer navigation, mhealth, feasibility studies, united states

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