BACKGROUND: Cardiometabolic diseases (CMDs) are a group of interrelated conditions, including heart failure and diabetes, that increase the risk of cardiovascular and metabolic complications. The rising number of Australians with CMDs has necessitated new strategies for those managing these conditions, such as digital health interventions. The effectiveness of digital health interventions in supporting people with CMDs is dependent on the extent to which users engage with the tools. Augmenting digital health interventions with conversational agents, technologies that interact with people using natural language, may enhance engagement because of their human-like attributes. To date, no systematic review has compiled evidence on how design features influence the engagement of conversational agent-enabled interventions supporting people with CMDs. This review seeks to address this gap, thereby guiding developers in creating more engaging and effective tools for CMD management.
OBJECTIVE: The aim of this systematic review is to synthesize evidence pertaining to conversational agent-enabled intervention design features and their impacts on the engagement of people managing CMD.
METHODS: The review is conducted in accordance with the Cochrane Handbook for Systematic Reviews of Interventions and reported in accordance with PRISMA (Preferred Reporting Items for Systematic Reviews and Meta-Analyses) guidelines. Searches will be conducted in the Ovid (Medline), Web of Science, and Scopus databases, which will be run again prior to manuscript submission. Inclusion criteria will consist of primary research studies reporting on conversational agent-enabled interventions, including measures of engagement, in adults with CMD. Data extraction will seek to capture the perspectives of people with CMD on the use of conversational agent-enabled interventions. Joanna Briggs Institute critical appraisal tools will be used to evaluate the overall quality of evidence collected.
RESULTS: This review was initiated in May 2023 and was registered with the International Prospective Register of Systematic Reviews (PROSPERO) in June 2023, prior to title and abstract screening. Full-text screening of articles was completed in July 2023 and data extraction began August 2023. Final searches were conducted in April 2024 prior to finalizing the review and the manuscript was submitted for peer review in July 2024.
CONCLUSIONS: This review will synthesize diverse observations pertaining to conversational agent-enabled intervention design features and their impacts on engagement among people with CMDs. These observations can be used to guide the development of more engaging conversational agent-enabled interventions, thereby increasing the likelihood of regular intervention use and improved CMD health outcomes. Additionally, this review will identify gaps in the literature in terms of how engagement is reported, thereby highlighting areas for future exploration and supporting researchers in advancing the understanding of conversational agent-enabled interventions.
BACKGROUND: PROSPERO CRD42023431579; https://tinyurl.com/55cxkm26.
UNASSIGNED: DERR1-10.2196/52973.

Polycystic ovary syndrome (PCOS) is a common endocrinopathy worldwide with a heterogeneous clinical presentation including reproductive, metabolic, and endocrine elements. However, the assessment and management of PCOS remains inconsistent, with many women undiagnosed and untreated. We now also understand that the management of PCOS should extend throughout a woman\'s lifespan as many elements of the syndrome persist after menopause. Management has traditionally focused on the treatment of hyperandrogenism and oligomenorrhea. Women with PCOS often have dyslipidemia, hypertension, obesity, and metabolic syndrome, which may be worsened by the hormonal abnormalities, and are therefore at higher risk for cardiovascular disease morbidity and mortality, a risk that increases after menopause. While treatment with hormonal therapy, in particular combined oral contraceptives, may improve cardiovascular risk factors, management plans should incorporate specific diagnosis and management of these factors, if present, because of the strong contribution to the risk for atherosclerotic cardiovascular disease (ASCVD). Given the complexities of the syndrome, optimal management often requires a multi-disciplinary approach including the lipid and cardiometabolic specialist to provide counseling and support for lifestyle modification along with pharmacologic therapy as indicated to address the full range of any reproductive, endocrine, and cardiometabolic abnormalities.

Substitution models in epidemiologic studies specifying both substitute and substituted food in relation to disease risk may be useful to inform dietary guidelines. A systematic review of prospective observational studies was performed to quantify the risks of all-cause mortality, cardiovascular disease, and type 2 diabetes (T2D) associated with the substitution of dairy products with other foods and between different dairy products. We systematically searched MEDLINE, Embase, and Web of Science until 28th June, 2023. We calculated summary relative risks (SRRs) and 95% confidence intervals (95% CI) in random-effects meta-analyses. We assessed the risk of bias with the Risk Of Bias In Non-randomized Studies - of Exposure (ROBINS-E) tool and certainty of evidence (CoE) using the Grading of Recommendations Assessment, Development, and Evaluations (GRADE) approach. Fifteen studies (with 34 publications) were included. There was moderate CoE that the substitution of low-fat dairy with red meat was associated with a higher risk of mortality, coronary artery disease, and T2D [SRR (95% CI): 1.11 (1.06, 1.16), 1.13 (1.08, 1.18), and 1.20 (1.16, 1.25)]. A higher risk of mortality and T2D was also observed when substituting low-fat dairy with processed meat [SRR (95% CI): 1.19 (1.11, 1.28) and 1.41 (1.33, 1.49); moderate CoE]. A lower mortality risk was associated with the substitution of dairy and yogurt with whole grains [SRR (95% CI): 0.89 (0.84, 0.93) and 0.91 (0.85, 0.97)], and butter with olive oil [SRR (95% CI): 0.94 (0.92, 0.97); all moderate CoE]. Mainly no associations were observed when substituting dairy products against each other on disease and mortality risk. Our findings indicate associations between substituting dairy with red or processed meat and higher disease risk, whereas its substitution with whole grains was associated with a lower risk. However, there is little robust evidence that substituting whole-fat with low-fat dairy is associated with disease risk. (CRD42022303198).

Cardiometabolic disease (CMD) is increasing along with its predisposing factors and adverse consequences. As gut microbiota dysbiosis is established in these patients, fecal microbiota transplantation (FMT), which alters the bacterial composition of the intestine, supposedly can help improve cardiometabolic disturbances. We conducted a systematic review and meta-analysis evaluating the impact of FMT on the cardiometabolic parameters and gut microbiota composition of patients experiencing at least one cardiometabolic issue.
Eligible studies were searched through the PubMed, Web of Science, and Scopus databases until December 2022. The initial search results underwent duplication removal and screening until each included study was scanned for intended data. The Cochrane risk of bias tool was used to evaluate the methodologic accuracy of studies and the random effects model was used for conducting the meta-analysis.
Eighteen of the original 2414 articles from the literature search were entered into the systematic review; of these, 11 were included in the meta-analysis. Insulin showed a significant decrease by 24.7 pmol/L (weighted mean difference [WMD], -24.77; 95% CI, -48.704 to -0.848) after short-term follow-up, and HDL increased by 0.1 mmol/l(WMD, 0.106; 95% CI, 0.027 to 0.184) and 0.12 mmol/l(WMD, 0.120; 95% CI, 0.003 to 0.237) in those using a capsule deliver mode and in short-term follow-up, respectively. No significant changes were seen in other lipid profiles, blood glucose, insulin resistance, or anthropometric indices. In addition, multiple studies reported gut microbiota alterations after the intervention, including an increase in butyrate-producing species.
Although some articles reported the beneficial effects of FMT on metabolic parameters, we failed to find a clinically significant alteration. Also, information regarding proper donors and the best method to induce FMT have not yet been sufficiently investigated, which should be considered along with means to prevent potential damages. PROSPERO identifier: CRD42022380705.

Light at night (LAN) is a significant but underappreciated risk factor contributing to cardiometabolic disease (CMD). We therefore conducted the review examining the relationship of LAN exposure with CMD in order to investigate the effects of LAN exposure on CMD. We searched PubMed, Web of Science, Embase, and Scopus for eligible studies published from database inception to August 17, 2023. The pooled effect size was calculated using random-effects models. Heterogeneity among the studies was quantified by Cochran\'s Q test and I2 statistic. A total of 1,019,739 participants from 14 studies (5 cohort studies and 9 cross-sectional) were included. Among the 14 eligible studies, 9 on obesity, 4 on diabetes, 2 on hypertension, 1 on dyslipidemia, and 1 on coronary heart disease. Exposure to higher levels of LAN were associated with 21% higher risk of CMD (Summary risk ratio, SRR: 1.21, 95% CI = 1.16-1.27), accompanied by substantial heterogeneity (I2 = 61%; tau2 = 0.004; Cochran\'s Q = 41.02). Specifically, individuals in the highest category of LAN exposure exhibited 23% higher risk of obesity (SRR: 1.23, 95% CI = 1.14-1.32), 46% higher risk of diabetes (SRR: 1.46, 95% CI = 1.05-2.03) and 21% higher risk of other CMDs (SRR: 1.21, 95% CI = 1.10-1.34). Subgroup analyses revealed that the pooled-effect size of LAN and CMD was higher for indoor LAN than outdoor LAN (indoor LAN: SRR = 1.36; outdoor LAN: SRR = 1.17, P = 0.03). The overall quality was rated as moderate using GRADE guideline. Our study strengthens the evidence on the increase in CMD risk due to LAN exposure. Findings from this study have important implications for identifying modifiable risk factor of CMD, future prevention strategy development, and resource allocation for high-risk group.

To evaluate how family support affects cardiometabolic outcomes.
Integrative literature review.
PubMed, CINAHL, EMBASE and Scopus were searched for peer-reviewed primary research published between 2016 and 2021.
Independent screening of 1661 citations resulted in 17 international publications involving 16 experimental studies selected. Data were analysed using a constant comparison method.
While the interventions varied regarding target, duration, setting and the profession of the interventionists, all studies demonstrated some level of the effectiveness for family involvement and support in the management of cardiometabolic diseases. The studies found improvement in health behaviours and clinical/psychosocial outcomes for the patients and the family members.
Based on the findings from this review, we recommend utilizing the following for future family interventions in the management of diabetes and/or hypertension: (1) broader definitions of family and structures; (2) a community participatory/action-research method with embedded healthcare workers; (3) an interdisciplinary approach with attention to goal-setting; (4) multimodal interventions including technology; (5) culturally tailoring interventions for relevance as needed; and (6) clear direction regarding support role and tools.

Indigenous peoples often have higher rates of morbidity and mortality associated with cardiometabolic disease (CMD) than non-Indigenous people and this may be even more so in urban areas. The use of electronic health records and expansion of computing power has led to mainstream use of artificial intelligence (AI) to predict the onset of disease in primary health care (PHC) settings. However, it is unknown if AI and in particular machine learning is used for risk prediction of CMD in Indigenous peoples.
We searched peer-reviewed literature using terms associated with AI machine learning, PHC, CMD, and Indigenous peoples.
We identified 13 suitable studies for inclusion in this review. Median total number of participants was 19,270 (range 911-2,994,837). The most common algorithms used in machine learning in this setting were support vector machine, random forest, and decision tree learning. Twelve studies used the area under the receiver operating characteristic curve (AUC) to measure performance. Two studies reported an AUC of >0.9. Six studies had an AUC score between 0.9 and 0.8, 4 studies had an AUC score between 0.8 and 0.7. 1 study reported an AUC score between 0.7 and 0.6. Risk of bias was observed in 10 (77 %) studies.
AI machine learning and risk prediction models show moderate to excellent discriminatory ability over traditional statistical models in predicting CMD. This technology could help address the needs of urban Indigenous peoples by predicting CMD early and more rapidly than conventional methods.

UNASSIGNED: Transition into menopause is associated with an increased risk of cardiovascular disease (CVD). However, it is unclear whether the association exists between premature menopause (defined as age at menopause 40 years) or early menopause (defined as age at menopause 40-45 years) and CVD or cardiovascular risk factors. The aim of this review was to comprehensively evaluate and meta-analyze the most reliable evidence about the relationship between menopausal age and the risk of long-term cardiometabolic disease.
UNASSIGNED: A comprehensive literature search of the PubMed, Web of Science, and Embase databases from inception to October 1, 2022, for titles and abstracts with a restriction to English language papers led to the discovery of the studies. Data are expressed as the Hazard Ratio (HR) with 95% confidence intervals (CI). The degree of heterogeneity was measured using the I-square (I 2) index.
UNASSIGNED: 921,517 participants from 20 cohort studies published between 1998 and 2022 were considered. Compared to women with menopause at age >45 years, women with premature menopause (PM) or early menopause (EM) had a higher risks of type 2 diabetes (RR: 1.32, 95% CI: 1.08-1.62; RR: 1.11, 95% CI: 0.91-1.36, respectively), hyperlipidemia (RR: 1.21, 95% CI: 1.05-1.39; RR: 1.17, 95% CI: 1.02-1.33, respectively), coronary heart disease (RR: 1.52, 95% CI: 1.22-1.91; RR: 1.19, 95% CI: 1.07-1.32, respectively), stroke (RR: 1.27, 95% CI: 1.02-1.58; RR: 1.13, 95% CI: 0.97-1.32, respectively) and total cardiovascular event (RR: 1.36, 95% CI: 1.16-1.60; RR: 1.14, 95% CI: 0.97-1.35, respectively). No difference was found for hypertension in PM or EM women (RR: 0.98, 95% CI: 0.89-1.07; RR: 0.97, 95% CI: 0.91-1.04, respectively). Additionally, we also found that PM women, but not EM women, were linked with an increased risk of ischemic and hemorrhagic stroke. However, this is not in line with the conclusion that both PM and EM had a higher risk of total stroke.
UNASSIGNED: Women with PM or EM have a higher risk of developing long-term CVD, compared to women with menopause at age >45 years. Therefore, we recommend early lifestyle interventions (e.g., maintaining a healthy lifestyle) and medical treatments (e.g., timely initiation of menopausal hormone therapy) to decrease the risk of cardiometabolic disease in early or premature menopausal women.
UNASSIGNED: PROSPERO, identifier CRD42022378750.

Racial discrimination has been identified as a risk factor for cardiometabolic diseases, the leading cause of morbidity and mortality among racial/ethnic minority groups; however, there is no synthesis of current knowledge on the association between discrimination and cardiometabolic diseases. The objective of this systematic review was to summarize evidence linking racial/ethnic discrimination and cardiometabolic diseases.
The review was conducted based on studies identified via electronic searches of 5 databases (PubMed, Google Scholar, WorldWideScience.org, ResearchGate and Microsoft Academic) using terms related to discrimination and cardiometabolic disease.
Of the 123 eligible studies included in the review, 87 were cross-sectional, 25 longitudinal, 8 quasi-experimental, 2 randomized controlled trials and 1 case-control. Cardiometabolic disease outcomes discussed were hypertension (n = 46), cardiovascular disease (n = 40), obesity (n = 12), diabetes (n = 11), metabolic syndrome (n = 9), and chronic kidney disease (n = 5). Although a variety of discrimination measures was employed across the studies, the Everyday Discrimination Scale was used most often (32.5%). African Americans/Blacks were the most frequently studied racial/ethnic group (53.1%), and American Indians the least (0.02%). Significant associations between racial/ethnic discrimination and cardiometabolic disease were found in 73.2% of the studies.
Racial/ethnic discrimination is positively associated with increased risk of cardiometabolic disease and higher levels of cardiometabolic biomarkers. Identifying racial/ethnic discrimination as a potential key contributor to the health inequities associated with cardiometabolic diseases is important for addressing the significant burden borne by racial/ethnic minorities.

Digital health interventions (DHIs) for the prevention and management of cardiometabolic diseases have become increasingly common. However, there is limited evidence for the suitability of these approaches in minority ethnic populations, who are at an increased risk of these diseases.
This study aimed to investigate the use of DHIs for cardiovascular disease and type 2 diabetes among minority ethnic populations in countries with a majority of White, English-speaking populations, focusing on people who identified as South Asian, Black, or African American.
A realist methodology framework was followed. A literature search was conducted to develop context-mechanism-outcome configurations, including the contexts in which DHIs work for the target minority ethnic groups, mechanisms that these contexts trigger, and resulting health outcomes. After systematic searches, a qualitative analysis of the included studies was conducted using deductive and inductive coding.
A total of 15 studies on the uptake of DHIs for cardiovascular disease or diabetes were identified, of which 13 (87%) focused on people with an African-American background. The review found evidence supporting the use of DHIs in minority ethnic populations when specific factors are considered in implementation and design, including patients\' beliefs, health needs, education and literacy levels, material circumstances, culture, social networks, and wider community and the supporting health care systems.
Our context-mechanism-outcome configurations provide a useful guide for the future development of DHIs targeted at South Asian and Black minority ethnic populations, with specific recommendations for improving cultural competency and promoting accessibility and inclusivity of design.