Examining if the relationship between BMI and incident type 2 diabetes among middle-older aged adults varies by race/ethnicity: evidence from the Multi-Ethnic Study of Atherosclerosis (MESA)

Automated lifestyle interventions and weight loss: a systematic review of randomized controlled trials

BACKGROUND/OBJECTIVES

Overweight and obesity drive cardiometabolic disease and high-intensity lifestyle interventions are standard. However, many health-systems cannot offer these interventions and many patients cannot participate even when available. Trials have assessed automated digital lifestyle interventions to improve accessibility. This systematic review identified automated digital lifestyle interventions and assessed their impact on weight loss.

SUBJECTS/METHODS

The review (CRD42023435700) identified randomized controlled trials of at least 3-months duration assessing automated digital lifestyle interventions' impact on weight loss. Data were managed through Covidence with double-blinded screening of titles/abstracts and double-blinded full-text review to determine study inclusion. Data extraction was completed by one reviewer (NWC) and verified by a second (MM, JS, TE, CE). The Cochrane Collaboration's tool was used to assess bias risk and study quality was rated as High, Moderate, Low, or Very Low.

RESULTS

The search identified 1817 citations. The full-text of 60 reports were assessed and 17 reports of 16 studies were included. The majority (63%) were of moderate quality. No intervention produced 5% weight loss from baseline. Intervention components with the largest impact were text message encouragement and education with a cognitive behavioral approach. No specific form of self-monitoring was most effective, though some form of self-monitoring was included in most trials.

CONCLUSIONS

Some components of the automated digital lifestyle interventions showed promise. Research is needed to optimize these components (e.g., tailored messaging, cognitive-behavioral approaches) balanced with human contact. Considering the magnitude of the problem and its disproportionate impact on low socioeconomic and minority patients, interventions optimized for effect and scalability are needed to address overweight and obesity.

Sociodemographic modifiers of effects of statin initiation on dementia incidence: An emulated trial design in a large health care member population with 10+ years of follow-up

INTRODUCTION

Mixed evidence on how statin use affects risk of Alzheimer's disease and related dementias (ADRD) may reflect heterogeneity across sociodemographic factors. Few studies have sufficient power to evaluate effect modifiers.

METHODS

Kaiser Permanente Northern California (KPNC) members (n = 705,061; n = 202,937 with sociodemographic surveys) who initiated statins from 2001 to 2010 were matched on age and low-density lipoprotein cholesterol (LDL-C) with non-initiators and followed through 2020 for incident ADRD. Inverse probability-weighted Cox proportional hazards models were used to evaluate effect modification by age, gender, race/ethnicity, education, marital status, income, and immigrant generation.

RESULTS

Statin initiation (vs non-initiation) was not associated with ADRD incidence in any of the 32 subgroups (p > .05). Hazard ratios ranged from 0.964 (95% CI: 0.923 to 1.006) among Asian-identified participants to 1.122 (95% CI: 0.995 to 1.265) in the highest income category.

DISCUSSION

Sociodemographic heterogeneity appears to have little to no influence on the relationship between statin initiation and dementia.

HIGHLIGHTS

The study includes a large and diverse cohort from Kaiser Permanente (N = 705,061). An emulated trial design of statin initiation on dementia incidence was used. Effect modification by sociodemographic factors was assessed. There were no significant Alzheimer's disease and related dementias (ADRD) risk differences in 32 sociodemographic subgroups (p > 0.05).

Structural and social determinants of health: The multi-ethnic study of atherosclerosis

BACKGROUND

Researchers have increasingly recognized the importance of structural and social determinants of health (SSDOH) as key drivers of a multitude of diseases and health outcomes. The Multi-Ethnic Study of Atherosclerosis (MESA) is an ongoing, longitudinal cohort study of subclinical cardiovascular disease (CVD) that has followed geographically and racially/ethnically diverse participants starting in 2000. Since its inception, MESA has incorporated numerous SSDOH assessments and instruments to study in relation to CVD and aging outcomes. In this paper, we describe the SSDOH data available in MESA, systematically review published papers using MESA that were focused on SSDOH and provide a roadmap for future SSDOH-related studies.

METHODS AND FINDINGS

The study team reviewed all published papers using MESA data (n = 2,125) through January 23, 2023. Two individuals systematically reviewed titles, abstracts, and full text to determine the final number of papers (n = 431) that focused on at least one SSDOH variable as an exposure, outcome, or stratifying/effect modifier variable of main interest (discrepancies resolved by a third individual). Fifty-seven percent of the papers focused on racialized/ethnic groups or other macrosocial/structural factors (e.g., segregation), 16% focused on individual-level inequalities (e.g. income), 14% focused on the built environment (e.g., walking destinations), 10% focused on social context (e.g., neighborhood socioeconomic status), 34% focused on stressors (e.g., discrimination, air pollution), and 4% focused on social support/integration (e.g., social participation). Forty-seven (11%) of the papers combined MESA with other cohorts for cross-cohort comparisons and replication/validation (e.g., validating algorithms).

CONCLUSIONS

Overall, MESA has made significant contributions to the field and the published literature, with 20% of its published papers focused on SSDOH. Future SSDOH studies using MESA would benefit by using recently added instruments/data (e.g., early life educational quality), linking SSDOH to biomarkers to determine underlying causal mechanisms linking SSDOH to CVD and aging outcomes, and by focusing on intersectionality, understudied SSDOH (i.e., social support, social context), and understudied outcomes in relation to SSDOH (i.e., sleep, respiratory health, cognition/dementia).

Multi-ancestry polygenic mechanisms of type 2 diabetes

Type 2 diabetes (T2D) is a multifactorial disease with substantial genetic risk, for which the underlying biological mechanisms are not fully understood. In this study, we identified multi-ancestry T2D genetic clusters by analyzing genetic data from diverse populations in 37 published T2D genome-wide association studies representing more than 1.4 million individuals. We implemented soft clustering with 650 T2D-associated genetic variants and 110 T2D-related traits, capturing known and novel T2D clusters with distinct cardiometabolic trait associations across two independent biobanks representing diverse genetic ancestral populations (African, n = 21,906; Admixed American, n = 14,410; East Asian, n =2,422; European, n = 90,093; and South Asian, n = 1,262). The 12 genetic clusters were enriched for specific single-cell regulatory regions. Several of the polygenic scores derived from the clusters differed in distribution among ancestry groups, including a significantly higher proportion of lipodystrophy-related polygenic risk in East Asian ancestry. T2D risk was equivalent at a body mass index (BMI) of 30 kg m-2 in the European subpopulation and 24.2 (22.9-25.5) kg m-2 in the East Asian subpopulation; after adjusting for cluster-specific genetic risk, the equivalent BMI threshold increased to 28.5 (27.1-30.0) kg m-2 in the East Asian group. Thus, these multi-ancestry T2D genetic clusters encompass a broader range of biological mechanisms and provide preliminary insights to explain ancestry-associated differences in T2D risk profiles.

Apolipoprotein E E3/E4 genotype is associated with an increased risk of type 2 diabetes mellitus complicated with coronary artery disease

OBJECTIVE

Dyslipidemia is a co-existing problem in patients with diabetes mellitus (DM) and coronary artery disease (CAD), and apolipoprotein E (APOE) plays an important role in lipid metabolism. However, the relationship between the APOE gene polymorphisms and the risk of developing CAD in type 2 DM (T2DM) patients remains controversial. The aim of this study was to assess this relationship and provide a reference for further risk assessment of CAD in T2DM patients.

METHODS

The study included 378 patients with T2DM complicated with CAD (T2DM + CAD) and 431 patients with T2DM alone in the case group, and 351 individuals without DM and CAD were set as controls. The APOE rs429358 and rs7412 polymorphisms were genotyped by polymerase chain reaction (PCR) - microarray. Differences in APOE genotypes and alleles between patients and controls were compared. Multiple logistic regression analysis was performed after adjusting for age, gender, body mass index (BMI), history of smoking, and history of drinking to access the relationship between APOE genotypes and T2DM + CAD risk.

RESULTS

The frequencies of the APOE ɛ3/ɛ4 genotype and ε4 allele were higher in the T2DM + CAD patients, and the frequencies of the APOE ɛ3/ɛ3 genotype and ε3 allele were lower than those in the controls (all p < 0.05). The T2DM + CAD patients with ɛ4 allele had higher level in low-density lipoprotein cholesterol (LDL-C) than those in patients with ɛ2 and ɛ3 allele (p < 0.05). The results of logistic regression analysis showed that age ≥ 60 years old, and BMI ≥ 24.0 kg/m2 were independent risk factors for T2DM and T2DM + CAD, and APOE ɛ3/ɛ4 genotype (adjusted odds ratio (OR) = 1.93, 95% confidence interval (CI) = 1.18-3.14, p = 0.008) and ɛ4 allele (adjusted OR = 1.97, 95% CI = 1.23-3.17) were independent risk factors for T2DM + CAD. However, the APOE genotypes and alleles were not found to have relationship with the risk of T2DM.

CONCLUSIONS

APOE ε3/ε4 genotype and ε4 allele were independent risk factors for T2DM complicated with CAD, but not for T2DM.

Multi-ancestry Polygenic Mechanisms of Type 2 Diabetes Elucidate Disease Processes and Clinical Heterogeneity

We identified genetic subtypes of type 2 diabetes (T2D) by analyzing genetic data from diverse groups, including non-European populations. We implemented soft clustering with 650 T2D-associated genetic variants, capturing known and novel T2D subtypes with distinct cardiometabolic trait associations. The twelve genetic clusters were distinctively enriched for single-cell regulatory regions. Polygenic scores derived from the clusters differed in distribution between ancestry groups, including a significantly higher proportion of lipodystrophy-related polygenic risk in East Asian ancestry. T2D risk was equivalent at a BMI of 30 kg/m2 in the European subpopulation and 24.2 (22.9-25.5) kg/m2 in the East Asian subpopulation; after adjusting for cluster-specific genetic risk, the equivalent BMI threshold increased to 28.5 (27.1-30.0) kg/m2 in the East Asian group, explaining about 75% of the difference in BMI thresholds. Thus, these multi-ancestry T2D genetic subtypes encompass a broader range of biological mechanisms and help explain ancestry-associated differences in T2D risk profiles.

Multi-ancestry Polygenic Mechanisms of Type 2 Diabetes Elucidate Disease Processes and Clinical Heterogeneity

We identified genetic subtypes of type 2 diabetes (T2D) by analyzing genetic data from diverse groups, including non-European populations. We implemented soft clustering with 650 T2D-associated genetic variants, capturing known and novel T2D subtypes with distinct cardiometabolic trait associations. The twelve genetic clusters were distinctively enriched for single-cell regulatory regions. Polygenic scores derived from the clusters differed in distribution between ancestry groups, including a significantly higher proportion of lipodystrophy-related polygenic risk in East Asian ancestry. T2D risk was equivalent at a BMI of 30 kg/m2 in the European subpopulation and 24.2 (22.9-25.5) kg/m2 in the East Asian subpopulation; after adjusting for cluster-specific genetic risk, the equivalent BMI threshold increased to 28.5 (27.1-30.0) kg/m2 in the East Asian group, explaining about 75% of the difference in BMI thresholds. Thus, these multi-ancestry T2D genetic subtypes encompass a broader range of biological mechanisms and help explain ancestry-associated differences in T2D risk profiles.

Psychosocial and diabetes risk factors among racially/ethnically diverse adults with prediabetes

Psychosocial factors such as self-efficacy may be important in helping high-risk adults prevent diabetes. We aimed to describe psychosocial and diabetes risk factors in adults with prediabetes and evaluate if these varied by demographic characteristics. Cross-sectional data came from baseline surveys and electronic health records (2018-2021) of adults with prediabetes enrolled in a randomized study of peer support for diabetes prevention at Kaiser Permanente Northern California and Michigan Medicine. Linear regression was used to compare differences between racial/ethnic groups, adjusting for age, sex, and clinic. Of 336 participants in the study, 62% were female; median age was 57; 41% were White, 35% African American, 9% Hispanic. Mean autonomous motivation was 6.6 and self-efficacy to prevent diabetes was 6.0 (1-7 scale); mean perceived social support was 47 (12-72 scale). Hispanic adults reported higher autonomous motivation and African American adults reported higher self-efficacy compared to White adults. Hispanic and African American adults had more diabetes risk factors than White adults, including greater family history of diabetes, hypertension, sugar-sweetened beverage consumption, physical inactivity and food insecurity. In conclusion, participants reported high levels of autonomous motivation and self-efficacy at baseline, with Hispanic and African American adults reporting higher levels of some psychosocial factors related to behavior change, suggesting a significant opportunity to engage a diverse population of adults with prediabetes in diabetes prevention strategies. However, Hispanic and African American participants showed greater diabetes risk factors levels. Diabetes prevention efforts should address both to reduce diabetes incidence.

Non-Invasive radial pressure wave analysis may digitally predict women's risks of type 2 diabetes (T2DM): A case and control group study

Background

Women not only have worse diabetes complications, but also have menstrual cycle, pregnancy, and menopause which can make managing diabetes more difficult. The aim of this study was to investigate if radial pressure wave analysis may non-invasively screen for women’s risk of type 2 diabetes.

Methods

Spectrum analysis of the radial pressure wave was performed to evaluate the first five harmonic components, C1 to C5. The study consisted of a total of 808 non-pregnant female subjects aged 20–95 over the period of 4 years, and 404 of them were diagnosed with Type 2 diabetes as the case group.

Result

The first five harmonic components are significantly different in a comparison of the case group and the control group. In the logistic regression analysis, T2DM was found to be associated with C1 (OR = 1.055, CI = 1.037–1.074, p < 0.001), C2 (OR = 1.051, CI = 1.019–1.085, p = 0.002), and C3 (OR = 0.972, CI = 0.950–0.994, p = 0.013). In the Receiver Operating Characteristic curve analysis, the Area Under Curve of using C3 only (70%, p <0.05), weighted C1, C2 and C3, (75%, p < 0.05), and weighted C1, C2 and C3 and Body mass Index (84%, p <0.05) were tested for the accuracy on how well these tests separate the women into the groups with and without the T2DM.

Conclusion

We thus concluded that pulse spectrum was a non-invasive predictor for women’s risk of T2DM.