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Social Determinants of Health Phenotypes and Cardiometabolic Condition Prevalence Among Patients in a Large Academic Health System: Latent Class Analysis

Social Determinants of Health Phenotypes and Cardiometabolic Condition Prevalence Among Patients in a Large Academic Health System: Latent Class Analysis

The population prevalence of cardiometabolic disease continues to rise [1], increasing patient burden and societal costs. Cardiometabolic disease disproportionately impacts those with low socioeconomic status (SES) [1-4], with marked geographic variations in diabetes and obesity prevalence across the United States [3]. Growing evidence suggests that social determinants of health (SDo H) [5] influence cardiometabolic disease.

Carrie R Howell, Li Zhang, Olivio J Clay, Gareth Dutton, Trudi Horton, Michael J Mugavero, Andrea L Cherrington

JMIR Public Health Surveill 2024;10:e53371

Mediterranean Diet Information on TikTok and Implications for Digital Health Promotion Research: Social Media Content Analysis

Mediterranean Diet Information on TikTok and Implications for Digital Health Promotion Research: Social Media Content Analysis

Reference 17: Association between dietary pattern and cardiometabolic risk in children and adolescents Reference 28: Mediterranean diet and cardiometabolic diseases in racial/ethnic minority populations incardiometabolic cardiometabolic disease

Margaret Raber, Haley Allen, Sophia Huang, Maria Vazquez, Echo Warner, Debbe Thompson

JMIR Form Res 2024;8:e51094

User Engagement, Acceptability, and Clinical Markers in a Digital Health Program for Nonalcoholic Fatty Liver Disease: Prospective, Single-Arm Feasibility Study

User Engagement, Acceptability, and Clinical Markers in a Digital Health Program for Nonalcoholic Fatty Liver Disease: Prospective, Single-Arm Feasibility Study

In this prospective study, we evaluated the feasibility and potential clinical impact of the 12-week digital health program on liver and cardiometabolic health in individuals with metabolic conditions and NAFLD. This was an open-label, single-arm, prospective study conducted between June and September 2022 in Iceland. The study included a 12-week digital health program delivered through the Sidekick app.

Sigridur Björnsdottir, Hildigunnur Ulfsdottir, Elias Freyr Gudmundsson, Kolbrun Sveinsdottir, Ari Pall Isberg, Bartosz Dobies, Gudlaug Erla Akerlie Magnusdottir, Thrudur Gunnarsdottir, Tekla Karlsdottir, Gudlaug Bjornsdottir, Sigurdur Sigurdsson, Saemundur Oddsson, Vilmundur Gudnason

JMIR Cardio 2024;8:e52576

Conversational Agents and Avatars for Cardiometabolic Risk Factors and Lifestyle-Related Behaviors: Scoping Review

Conversational Agents and Avatars for Cardiometabolic Risk Factors and Lifestyle-Related Behaviors: Scoping Review

The search strategy is shown in Textbox 1. 1.Cardiometabolic risk factors Weight “obesity”[Me SH Terms] OR “obese”[tiab] OR “obesity”[tiab] OR “overweight”[tiab] OR “overweight”[tiab] OR “BMI”[tiab] OR “Body mass index”[tiab] OR “Body mass index”[Me SH Terms] OR “physical activity”[Tiab] OR adiposity [tiab] OR weight gain[tiab] OR body weight[tiab] OR “abdominal visceral fat”[Tiab] OR “adipose tissue”[Me SH Terms] “weight loss”[Mesh] OR “weight loss”[tiab] or “metabolic syndrome” Diet and physical activity diets

Lynnette Nathalie Lyzwinski, Mohamed Elgendi, Carlo Menon

JMIR Mhealth Uhealth 2023;11:e39649

Effectiveness of Combined Health Coaching and Self-Monitoring Apps on Weight-Related Outcomes in People With Overweight and Obesity: Systematic Review and Meta-analysis

Effectiveness of Combined Health Coaching and Self-Monitoring Apps on Weight-Related Outcomes in People With Overweight and Obesity: Systematic Review and Meta-analysis

Cardiometabolic outcomes (ie, weight, BMI, WC, blood pressure, TC, LDL-C, HDL-C, triglyceride, and Hb A1c) and total calorie consumption were estimated using weighted mean differences (WMDs). Body fat percentage and physical activity were estimated using standardized mean differences. Standardized mean differences were expressed as Hedges g to account for the small number of studies included in the meta-analyses.

Han Shi Jocelyn Chew, Nagadarshini Nicole Rajasegaran, Yip Han Chin, W S Nicholas Chew, Kyung Mi Kim

J Med Internet Res 2023;25:e42432

The Use of Digital Health Interventions for Cardiometabolic Diseases Among South Asian and Black Minority Ethnic Groups: Realist Review

The Use of Digital Health Interventions for Cardiometabolic Diseases Among South Asian and Black Minority Ethnic Groups: Realist Review

Therefore, cardiometabolic risk reduction is a key target of both primary and secondary prevention programs. Digital health interventions (DHIs) can support such programs by facilitating the diagnosis, management, and prevention of cardiometabolic diseases (CMDs) and improvement of overall health [5], as highlighted in the United Kingdom’s National Health Service Long-Term Plan [6].

Aumeya Goswami, Lydia Poole, Zareen Thorlu-Bangura, Nushrat Khan, Wasim Hanif, Kamlesh Khunti, Paramjit Gill, Madiha Sajid, Ann Blandford, Fiona Stevenson, Amitava Banerjee, Mel Ramasawmy

J Med Internet Res 2023;25:e40630

Online Food Security Discussion Before and During the COVID-19 Pandemic in Native Hawaiian and Pacific Islander Community Groups and Organizations: Content Analysis of Facebook Posts

Online Food Security Discussion Before and During the COVID-19 Pandemic in Native Hawaiian and Pacific Islander Community Groups and Organizations: Content Analysis of Facebook Posts

The goal of HHAPI is to utilize culturally grounded evidence-based interventions to mitigate cardiometabolic conditions in the NHPI population via self-management of hypertension and diabetes at the individual, family, and policy levels.

Cassandra Jean Nguyen, Christian Pham, Alexandra M Jackson, Nicole Lee Kamakahiolani Ellison, Ka`imi Sinclair

Asian Pac Isl Nurs J 2022;6(1):e40436

Frameworks for Implementation, Uptake, and Use of Cardiometabolic Disease–Related Digital Health Interventions in Ethnic Minority Populations: Scoping Review

Frameworks for Implementation, Uptake, and Use of Cardiometabolic Disease–Related Digital Health Interventions in Ethnic Minority Populations: Scoping Review

Individuals of an ethnic minority background constitute at least 14% of the UK population [1] and have an increased risk of type 2 diabetes [2] and cardiovascular disease [3] (together, also known as cardiometabolic disease), particularly South Asian and Black individuals. Even before, but particularly during, the COVID-19 pandemic, digital health interventions became important in the education, prevention, diagnosis, treatment, and rehabilitation [4,5] of diseases such as cardiometabolic disease [6,7].

Mel Ramasawmy, Lydia Poole, Zareen Thorlu-Bangura, Aneesha Chauhan, Mayur Murali, Parbir Jagpal, Mehar Bijral, Jai Prashar, Abigail G-Medhin, Elizabeth Murray, Fiona Stevenson, Ann Blandford, Henry W W Potts, Kamlesh Khunti, Wasim Hanif, Paramjit Gill, Madiha Sajid, Kiran Patel, Harpreet Sood, Neeraj Bhala, Shivali Modha, Manoj Mistry, Vinod Patel, Sarah N Ali, Aftab Ala, Amitava Banerjee

JMIR Cardio 2022;6(2):e37360