Effects of Nonnutritive Sweeteners on the BMI of Children and Adolescents: A Systematic Review and Meta-Analysis of Randomized Controlled Trials and Prospective Cohort Studies.

The effect of nonnutritive sweeteners (NNSs) on the body mass index [BMI (in kg/m2)] of children and adolescents remains unclear despite rising consumption. Detailed systematic evaluations are warranted. We aimed to summarize evidence on NNS consumption and BMI sex- and age-specific absolute changes (kg/m2) in pediatric populations, by NNS type, study design, duration, analysis type, conflicts of interest (COI), geographical region, age, sex, and baseline BMI. We searched randomized controlled trials (RCTs) and prospective cohort studies in children (2-9 y), adolescents (10-24 y), and young adults (20-24 y). Pooled estimates derived from random-effects meta-analysis for BMI changes, and the evidence quality was evaluated overall and by subgroup. From 2789 results, we included 4 RCTs [n = 1372; mean follow-up = 42.6 wk (standard deviation = 18.4); 2 (50%) with COI], and 8 prospective cohort studies [n = 35,340; median follow-up 2.5 y (interquartile range = 1.7-6.3), 2 (25%) with COI]. No identified studies evaluated NNS in food, NNS beverages compared with water, or participants aged 20-24 y. Random allocation to NNS beverages (25-2400 mg/d, from beverages) showed less BMI gain [mean difference = -0.114 kg/m2 (95% confidence interval [CI]: -0.207, -0.021); I2 = 87.02%] compared with sugar-sweetened beverages (SSBs). Stratified estimates resulted in less BMI gain in adolescents, participants with baseline obesity, consumers of mixed NNS, longer trials, and trials without COI. Pooled estimates from prospective cohorts showed a nonsignificant association between NNS beverages and BMI gain [0.05 kg/m2 (95% CI: -0.03, 0.13); I2 = 75.06%; per daily 355 mL serving]. Stratified estimates remained consistent. Removing studies with COI attenuated estimates. Evidence had low to moderate quality. In summary, pooled results from RCTs comparing NNS beverages compared with SSBs showed less BMI gain in adolescents with obesity. Meta-analyses of long-term cohort studies did not display a significant association between NNS beverages and BMI changes. This trial was registered at PROSPERO as CRD42022352284.

Integration of epidemiological and blood biomarker analysis links haem iron intake to increased type 2 diabetes risk.

Dietary haem iron intake is linked to an increased risk of type 2 diabetes (T2D), but the underlying plasma biomarkers are not well understood. We analysed data from 204,615 participants (79% females) in three large US cohorts over up to 36 years, examining the associations between iron intake and T2D risk. We also assessed plasma metabolic biomarkers and metabolomic profiles in subsets of 37,544 (82% females) and 9,024 (84% females) participants, respectively. Here we show that haem iron intake but not non-haem iron is associated with a higher T2D risk, with a multivariable-adjusted hazard ratio of 1.26 (95% confidence interval 1.20-1.33; P for trend <0.001) comparing the highest to the lowest quintiles. Haem iron accounts for significant proportions of the T2D risk linked to unprocessed red meat and specific dietary patterns. Increased haem iron intake correlates with unfavourable plasma profiles of insulinaemia, lipids, inflammation and T2D-linked metabolites. We also identify metabolites, including L-valine and uric acid, potentially mediating the haem iron-T2D relationship, highlighting their pivotal role in T2D pathogenesis.

Improving nutrition science begins with asking better questions.

A priority of nutrition science is to identify dietary determinants of health and disease to inform effective public health policies, guidelines, and clinical interventions. Yet, conflicting findings in synthesizing evidence from randomized trials and observational data has contributed to confusion and uncertainty. Often, heterogeneity can be explained by the fact that seemingly similar bodies of evidence are asking very different questions. Improving the alignment within and between research domains begins with investigators clearly defining their diet-disease questions; however, nutritional exposures are complex and often require a greater degree of specificity. First, dietary data are compositional, meaning a change in a food may imply a compensatory change of other foods. Second, dietary data are multidimensional; that is, the primary components (i.e., foods) are comprised of sub-components (e.g., nutrients), and sub-components can be present in multiple primary components. Third, because diet is a lifelong exposure, the composition of a study population's background diet has implications on the interpretation of the exposure and the transportability of effect estimates. Collectively clarifying these key aspects of inherently complex dietary exposures when conducting research will facilitate appropriate evidence synthesis, improve certainty of evidence, and improve the ability of these efforts to inform policy and decision-making.

Invited commentary: five hundred twenty-five thousand, six hundred calories, how do you measure diet in a year?

Nearly 4 decades after its landmark validation study, researchers undertook a major comprehensive reevaluation of the semi-quantitative food frequency questionnaire (FFQ). Although it has evolved with trends in science and our expanding food environment, this FFQ has been administered continuously to over 250,000 US cohort participants for several decades and has contributed enormously to our understanding of the role long-term diet plays in health and disease across the lifespan. Nonetheless, it is critical that the field takes time to validate, recalibrate, and reassure researchers that the FFQ continues to generate useful estimates of dietary intake. There are persistent misconceptions among both nutritional epidemiologists and its critics about what the FFQ can and cannot measure that require regular re-education on the principles underlying FFQ development and validation. Thus, the carefully conducted validation study by Gu et al. (Am J Epidemiol. 2024;193(1):170-179) provides an important benchmark for nutrition science, underscoring the continued value and utility that the FFQ brings to epidemiologic research.

Reporting guidelines for precision medicine research of clinical relevance: the BePRECISE checklist.

Precision medicine should aspire to reduce error and improve accuracy in medical and health recommendations by comparison with contemporary practice, while maintaining safety and cost-effectiveness. The etiology, clinical manifestation and prognosis of diseases such as obesity, diabetes, cardiovascular disease, kidney disease and fatty liver disease are heterogeneous. Without standardized reporting, this heterogeneity, combined with the diversity of research tools used in precision medicine studies, makes comparisons across studies and implementation of the findings challenging. Specific recommendations for reporting precision medicine research do not currently exist. The BePRECISE (Better Precision-data Reporting of Evidence from Clinical Intervention Studies & Epidemiology) consortium, comprising 23 experts in precision medicine, cardiometabolic diseases, statistics, editorial and lived experience, conducted a scoping review and participated in a modified Delphi and nominal group technique process to develop guidelines for reporting precision medicine research. The BePRECISE checklist comprises 23 items organized into 5 sections that align with typical sections of a scientific publication. A specific section about health equity serves to encourage precision medicine research to be inclusive of individuals and communities that are traditionally under-represented in clinical research and/or underserved by health systems. Adoption of BePRECISE by investigators, reviewers and editors will facilitate and accelerate equitable clinical implementation of precision medicine.

Associations Between Food Insecurity and Diet Quality Among Graduate Students and Postdoctoral Trainees in the Health Sciences at a Private University in Boston: A Cross-Sectional Study.

Background: Food insecurity is a pivotal determinant of health outcomes. Little evidence exists on the association between food insecurity and health behaviors and outcomes, including diet quality, among graduate students or postdoctoral trainees. Objectives: This study aimed to examine the association between food insecurity and diet quality among graduate students and postdoctoral trainees at 3 health-focused graduate schools (public health, medical, and dental medicine) within Harvard University. Methods: Between April and June 2023, 1287 graduate students and 458 postdoctoral trainees at the health-focused schools within Harvard University completed a web-based survey. The primary exposure was food security status, assessed using the United States Household Food Security Survey Module. The primary outcome was diet quality, measured using the 30-day Prime Diet Quality Score screener (ranges from 0 to 126, with higher scores indicating healthier diets). The associations between food insecurity and diet quality were examined using multivariable regression models, adjusting for sociodemographic covariates. Results: Among graduate students, compared with those with high food security, diet quality was significantly lower among those experiencing marginal food security [ß: -4.7; 95% confidence interval (CI): -6.5, -2.9], low food security (ß: -5.4; 95% CI: -7.6, -3.3), and very low food security (ß: -4.4; 95% CI: -7.4, -1.4). Poor diet quality included lower intake frequencies of vegetables, fruits, beans/peas/soy products, nuts/seeds, poultry, fish, low-fat dairy, and liquid oils, and higher intake frequencies of refined grains/baked products, sugar-sweetened beverages, and fried foods. Among postdoctoral trainees, compared with those with high food security, diet quality was significantly lower among those experiencing low food security (ß: -5.1; 95% CI: -8.8, -1.4), and very low food security (ß: -5.2; 95% CI: -10.2, -0.2). Poor diet quality included lower intake frequencies of dark green leafy vegetables, other fruits, and whole grains. Conclusions: Graduate students and postdoctoral trainees who experienced degrees of food insecurity reported lower diet quality. These observations underscore the need for policies and interventions to simultaneously reduce food insecurity and improve diet quality.

Prediction of 24-Hour Urinary Sodium Excretion Using Machine-Learning Algorithms.

BACKGROUND: Accurate quantification of sodium intake based on self-reported dietary assessments has been a persistent challenge. We aimed to apply machine-learning (ML) algorithms to predict 24-hour urinary sodium excretion from self-reported questionnaire information. METHODS AND RESULTS: We analyzed 3454 participants from the NHS (Nurses' Health Study), NHS-II (Nurses' Health Study II), and HPFS (Health Professionals Follow-Up Study), with repeated measures of 24-hour urinary sodium excretion over 1 year. We used an ensemble approach to predict averaged 24-hour urinary sodium excretion using 36 characteristics. The TOHP-I (Trial of Hypertension Prevention I) was used for the external validation. The final ML algorithms were applied to 167 920 nonhypertensive adults with 30-year follow-up to estimate confounder-adjusted hazard ratio (HR) of incident hypertension for predicted sodium. Averaged 24-hour urinary sodium excretion was better predicted and calibrated with ML compared with the food frequency questionnaire (Spearman correlation coefficient, 0.51 [95% CI, 0.49-0.54] with ML; 0.19 [95% CI, 0.16-0.23] with the food frequency questionnaire; 0.46 [95% CI, 0.42-0.50] in the TOHP-I). However, the prediction heavily depended on body size, and the prediction of energy-adjusted 24-hour sodium excretion was modestly better using ML. ML-predicted sodium was modestly more strongly associated than food frequency questionnaire-based sodium in the NHS-II (HR comparing Q5 versus Q1, 1.48 [95% CI, 1.40-1.56] with ML; 1.04 [95% CI, 0.99-1.08] with the food frequency questionnaire), but no material differences were observed in the NHS or HPFS. CONCLUSIONS: The present ML algorithm improved prediction of participants' absolute 24-hour urinary sodium excretion. The present algorithms may be a generalizable approach for predicting absolute sodium intake but do not substantially reduce the bias stemming from measurement error in disease associations.

Plasma metabolites of a healthy lifestyle in relation to mortality and longevity: Four prospective US cohort studies.

BACKGROUND: A healthy lifestyle is associated with a lower premature mortality risk and with longer life expectancy. However, the metabolic pathways of a healthy lifestyle and how they relate to mortality and longevity are unclear. We aimed to identify and replicate a healthy lifestyle metabolomic signature and examine how it is related to total and cause-specific mortality risk and longevity. METHODS: In four large cohorts with 13,056 individuals and 28-year follow-up, we assessed five healthy lifestyle factors, used liquid chromatography mass spectrometry to profile plasma metabolites, and ascertained deaths with death certificates. The unique healthy lifestyle metabolomic signature was identified using an elastic regression. Multivariable Cox regressions were used to assess associations of the signature with mortality and longevity. FINDINGS: The identified healthy lifestyle metabolomic signature was reflective of lipid metabolism pathways. Shorter and more saturated triacylglycerol and diacylglycerol metabolite sets were inversely associated with the healthy lifestyle score, whereas cholesteryl ester and phosphatidylcholine plasmalogen sets were positively associated. Participants with a higher healthy lifestyle metabolomic signature had a 17% lower risk of all-cause mortality, 19% for cardiovascular disease mortality, and 17% for cancer mortality and were 25% more likely to reach longevity. The healthy lifestyle metabolomic signature explained 38% of the association between the self-reported healthy lifestyle score and total mortality risk and 49% of the association with longevity. CONCLUSIONS: This study identifies a metabolomic signature that measures adherence to a healthy lifestyle and shows prediction of total and cause-specific mortality and longevity. FUNDING: This work was funded by the NIH, CIHR, AHA, Novo Nordisk Foundation, and SciLifeLab.

Lifetime Duration of Breastfeeding and Cardiovascular Risk in Women With Type 2 Diabetes or a History of Gestational Diabetes: Findings From Two Large Prospective Cohorts.

OBJECTIVE: Breastfeeding duration is inversely associated with risks of cardiovascular disease (CVD) and type 2 diabetes in parous women. However, the association among women at high risk, including women with type 2 diabetes or gestational diabetes mellitus (GDM) is unclear. RESEARCH DESIGN AND METHODS: We included 15,146 parous women with type 2 diabetes from the Nurses' Health Study I and II (NHS, NHS II) and 4,537 women with a history of GDM from NHS II. Participants reported history of breastfeeding via follow-up questionnaires. Incident CVD by 2017 comprised stroke or coronary heart disease (CHD) (myocardial infarction, coronary revascularization). Adjusted hazard ratios (aHRs) and 95% CIs were estimated using Cox models. RESULTS: We documented 1,159 incident CVD cases among women with type 2 diabetes in both cohorts during 188,874 person-years of follow-up and 132 incident CVD cases among women with a GDM history during 100,218 person-years of follow-up. Longer lifetime duration of breastfeeding was significantly associated with lower CVD risk among women with type 2 diabetes, with pooled aHR of 0.68 (95% CI 0.54-0.85) for >18 months versus 0 months and 0.94 (0.91-0.98) per 6-month increment in breastfeeding. Similar associations were observed with CHD (pooled aHR 0.93 [0.88-0.97]) but not with stroke (0.96 [0.91-1.02]) per 6-month increment in breastfeeding. Among women with GDM history, >18 months versus 0 months of breastfeeding was associated with an aHR of 0.49 (0.28-0.86) for total CVD. CONCLUSIONS: Longer duration of breastfeeding was associated with lower risk of CVD in women with type 2 diabetes or GDM.

Sugar-sweetened or artificially-sweetened beverage consumption, physical activity, and risk of cardiovascular disease in adults: a prospective cohort study.

BACKGROUND: Whether physical activity could mitigate the adverse impacts of sugar-sweetened beverages (SSBs) or artificially sweetened beverages (ASBs) on incident cardiovascular disease (CVD) remains uncertain. OBJECTIVES: This study aimed to examine the independent and joint associations between SSB or ASB consumption and physical activity and risk of CVD, defined as fatal and nonfatal coronary artery disease and stroke, in adults from 2 United States-based prospective cohort studies. METHODS: Cox proportional hazards models were used to calculate hazard ratios (HRs) and 95% CIs between SSB or ASB intake and physical activity with incident CVD among 65,730 females in the Nurses' Health Study (1980-2016) and 39,418 males in the Health Professional's Follow-up Study (1986-2016), who were free from chronic diseases at baseline. SSBs and ASBs were assessed every 4-y and physical activity biannually. RESULTS: A total of 13,269 CVD events were ascertained during 3,001,213 person-years of follow-up. Compared with those who never/rarely consumed SSBs or ASBs, the HR for CVD for participants consuming ≥2 servings/d was 1.21 (95% CI: 1.12, 1.32; P-trend < 0.001) for SSBs and 1.03 (95% CI: 0.97, 1.09; P-trend = 0.06) for those consuming ≥2 servings/d of ASBs. The HR for CVD per 1 serving increment of SSB per day was 1.18 (95% CI: 1.10, 1.26) and 1.12 (95% CI: 1.04, 1.20) for participants meeting and not meeting physical activity guidelines (≥7.5 compared with <7.5 MET h/wk), respectively. Compared with participants who met physical activity guidelines and never/rarely consumed SSBs, the HR for CVD was 1.47 (95% CI: 1.37, 1.57) for participants not meeting physical activity guidelines and consuming ≥2 servings/wk of SSBs. No significant associations were observed for ASB when stratified by physical activity. CONCLUSIONS: Higher SSB intake was associated with CVD risk regardless of physical activity levels. These results support current recommendations to limit the intake of SSBs even for physically active individuals.

Consumption of 100% Fruit Juice and Body Weight in Children and Adults: A Systematic Review and Meta-Analysis.

Importance: Concerns have been raised that frequent consumption of 100% fruit juice may promote weight gain. Current evidence on fruit juice and weight gain has yielded mixed findings from both observational studies and clinical trials. Objective: To synthesize the available evidence on 100% fruit juice consumption and body weight in children and adults. Data Sources: MEDLINE, Embase, and Cochrane databases were searched through May 18, 2023. Study Selection: Prospective cohort studies of at least 6 months and randomized clinical trials (RCTs) of at least 2 weeks assessing the association of 100% fruit juice with body weight change in children and adults were included. In the trials, fruit juices were compared with noncaloric controls. Data Extraction and Synthesis: Data were pooled using random-effects models and presented as ß coefficients with 95% CIs for cohort studies and mean differences (MDs) with 95% CIs for RCTs. Main Outcomes and Measures: Change in body mass index (BMI; calculated as weight in kilograms divided by height in meters squared) was assessed in children and change in body weight in adults. Results: A total of 42 eligible studies were included in this analysis, including 17 among children (17 cohorts; 0 RCTs; 45 851 children; median [IQR] age, 8 [1-15] years) and 25 among adults (6 cohorts; 19 RCTs; 268 095 adults; median [IQR] age among cohort studies, 48 [41-61] years; median [IQR] age among RCTs, 42 [25-59]). Among cohort studies in children, each additional serving per day of 100% fruit juice was associated with a 0.03 (95% CI, 0.01-0.05) higher BMI change. Among cohort studies in adults, studies that did not adjust for energy showed greater body weight gain (0.21 kg; 95% CI, 0.15-0.27 kg) than studies that did adjust for energy intake (-0.08 kg; 95% CI, -0.11 to -0.05 kg; P for meta-regression <.001). RCTs in adults found no significant association of assignment to 100% fruit juice with body weight but the CI was wide (MD, -0.53 kg; 95% CI, -1.55 to 0.48 kg). Conclusion and Relevance: Based on the available evidence from prospective cohort studies, in this systematic review and meta-analysis, 1 serving per day of 100% fruit juice was associated with BMI gain among children. Findings in adults found a significant association among studies unadjusted for total energy, suggesting potential mediation by calories. Further trials of 100% fruit juice and body weight are desirable. Our findings support guidance to limit consumption of fruit juice to prevent intake of excess calories and weight gain.

Type 2 diabetes metabolomics score and risk of progression to type 2 diabetes among women with a history of gestational diabetes mellitus.

BACKGROUND: Several metabolites are individually related to incident type 2 diabetes (T2D) risk. We prospectively evaluated a novel T2D-metabolite pattern with a risk of progression to T2D among high-risk women with a history of gestational diabetes mellitus (GDM). METHODS: The longitudinal Nurses' Health Study II cohort enroled 116,429 women in 1989 and collected blood samples from 1996 to 1999. We profiled plasma metabolites in 175 incident T2D cases and 175 age-matched controls, all with a history of GDM before the blood draw. We derived a metabolomics score from 21 metabolites previously associated with incident T2D in the published literature by scoring according to the participants' quintile (1-5 points) of each metabolite. We modelled the T2D metabolomics score categorically in quartiles and continuously per 1 standard deviation (SD) with the risk of incident T2D using conditional logistic regression models adjusting for body mass index at the blood draw, and other established T2D risk factors. RESULTS: The percentage of women progressing to T2D ranged from 10% in the bottom T2D metabolomics score quartile to 78% in the highest score quartile. Adjusting for established T2D risk factors, women in the highest quartile had more than a 20-fold greater diabetes risk than women in the lowest quartile (odds ratios [OR] = 23.1 [95% CI = 8.6, 62.1]; p for trend<0.001). The continuous T2D metabolomics score was strongly and positively associated with incident T2D (adjusted OR = 2.7 per SD [95% CI = 1.9, 3.7], p < 0.0001). CONCLUSIONS: A pattern of plasma metabolites among high-risk women is associated with a markedly elevated risk of progression to T2D later in life.

Precision stratification of prognostic risk factors associated with outcomes in gestational diabetes mellitus: a systematic review.

BACKGROUND: The objective of this systematic review is to identify prognostic factors among women and their offspring affected by gestational diabetes mellitus (GDM), focusing on endpoints of cardiovascular disease (CVD) and type 2 diabetes (T2D) for women, and cardiometabolic profile for offspring. METHODS: This review included studies published in English language from January 1st, 1990, through September 30th, 2021, that focused on the above outcomes of interest with respect to sociodemographic factors, lifestyle and behavioral characteristics, traditional clinical traits, and 'omics biomarkers in the mothers and offspring during the perinatal/postpartum periods and across the lifecourse. Studies that did not report associations of prognostic factors with outcomes of interest among GDM-exposed women or children were excluded. RESULTS: Here, we identified 109 publications comprising 98 observational studies and 11 randomized-controlled trials. Findings indicate that GDM severity, maternal obesity, race/ethnicity, and unhealthy diet and physical activity levels predict T2D and CVD in women, and greater cardiometabolic risk in offspring. However, using the Diabetes Canada 2018 Clinical Practice Guidelines for studies, the level of evidence was low due to potential for confounding, reverse causation, and selection biases. CONCLUSIONS: GDM pregnancies with greater severity, as well as those accompanied by maternal obesity, unhealthy diet, and low physical activity, as well as cases that occur among women who identify as racial/ethnic minorities are associated with worse cardiometabolic prognosis in mothers and offspring. However, given the low quality of evidence, prospective studies with detailed covariate data collection and high fidelity of follow-up are warranted.

Gestational diabetes mellitus (GDM) occurs when levels of sugar in the blood are high during pregnancy. We sought to identify factors associated with short- and long-term cardiometabolic disease risk, health conditions that involve heart-related issues and complications in bodily function, among women with GDM and their offspring. We reviewed publications on factors related to type 2 diabetes (T2D) and cardiovascular disease (CVD) risk among women with GDM, and additionally assessed body composition in offspring of women with GDM. We found that GDM severity, maternal obesity, self-identified race/ethnicity, poor diet, and low physical activity levels predict postpartum T2D and CVD in the women, and unfavorable long-term cardiometabolic disease risk in offspring. The quality of evidence was poor, emphasizing a need for high-quality research capturing detailed short- and long-term outcome data to facilitate preventative interventions to improve health of women and children.

Second international consensus report on gaps and opportunities for the clinical translation of precision diabetes medicine.

Precision medicine is part of the logical evolution of contemporary evidence-based medicine that seeks to reduce errors and optimize outcomes when making medical decisions and health recommendations. Diabetes affects hundreds of millions of people worldwide, many of whom will develop life-threatening complications and die prematurely. Precision medicine can potentially address this enormous problem by accounting for heterogeneity in the etiology, clinical presentation and pathogenesis of common forms of diabetes and risks of complications. This second international consensus report on precision diabetes medicine summarizes the findings from a systematic evidence review across the key pillars of precision medicine (prevention, diagnosis, treatment, prognosis) in four recognized forms of diabetes (monogenic, gestational, type 1, type 2). These reviews address key questions about the translation of precision medicine research into practice. Although not complete, owing to the vast literature on this topic, they revealed opportunities for the immediate or near-term clinical implementation of precision diabetes medicine; furthermore, we expose important gaps in knowledge, focusing on the need to obtain new clinically relevant evidence. Gaps include the need for common standards for clinical readiness, including consideration of cost-effectiveness, health equity, predictive accuracy, liability and accessibility. Key milestones are outlined for the broad clinical implementation of precision diabetes medicine.

A Primer on Systematic Review and Meta-analysis in Diabetes Research.

A systematic review is a rigorous process that involves identifying, selecting, and synthesizing available evidence pertaining to an a priori-defined research question. The resulting evidence base may be summarized qualitatively or through a quantitative analytic approach known as meta-analysis. Systematic review and meta-analysis (SRMAs) have risen in popularity across the scientific realm including diabetes research. Although well-conducted SRMAs are an indispensable tool in informing evidence-based medicine, the proliferation of SRMAs has led to many reviews of questionable quality and misleading conclusions. The objective of this article is to provide up-to-date knowledge and a comprehensive understanding of strengths and limitations of SRMAs. We first provide an overview of the SRMA process and offer ways to identify common pitfalls at key steps. We then describe best practices as well as evolving approaches to mitigate biases, improve transparency, and enhance rigor. We discuss several recent developments in SRMAs including individual-level meta-analyses, network meta-analyses, umbrella reviews, and prospective meta-analyses. Additionally, we outline several strategies that can be used to enhance quality of SRMAs and present key questions that authors, editors, and readers should consider in preparing or critically reviewing SRMAs.

Impact of individual and environmental factors on dietary or lifestyle interventions to prevent type 2 diabetes development: a systematic review.

BACKGROUND: The variability in the effectiveness of type 2 diabetes (T2D) preventive interventions highlights the potential to identify the factors that determine treatment responses and those that would benefit the most from a given intervention. We conducted a systematic review to synthesize the evidence to support whether sociodemographic, clinical, behavioral, and molecular factors modify the efficacy of dietary or lifestyle interventions to prevent T2D. METHODS: We searched MEDLINE, Embase, and Cochrane databases for studies reporting on the effect of a lifestyle, dietary pattern, or dietary supplement interventions on the incidence of T2D and reporting the results stratified by any effect modifier. We extracted relevant statistical findings and qualitatively synthesized the evidence for each modifier based on the direction of findings reported in available studies. We used the Diabetes Canada Clinical Practice Scale to assess the certainty of the evidence for a given effect modifier. RESULTS: The 81 publications that met our criteria for inclusion are from 33 unique trials. The evidence is low to very low to attribute variability in intervention effectiveness to individual characteristics such as age, sex, BMI, race/ethnicity, socioeconomic status, baseline behavioral factors, or genetic predisposition. CONCLUSIONS: We report evidence, albeit low certainty, that those with poorer health status, particularly those with prediabetes at baseline, tend to benefit more from T2D prevention strategies compared to healthier counterparts. Our synthesis highlights the need for purposefully designed clinical trials to inform whether individual factors influence the success of T2D prevention strategies.

Clinical trials to prevent development of type 2 diabetes (T2D) that test dietary and lifestyle interventions have resulted in different results for different study participants. We hypothesized that the differing responses could be because of different personal, social and inherited factors. We searched different databases containing details of published research studies investigating this to look at the effect of these factors on prevention of the development of T2D. We found a small amount of evidence suggesting that those with poorer health, particularly those with a higher amount of sugar in their blood, tend to benefit more from T2D prevention strategies compared to healthier counterparts. Our results suggest that further clinical trials that are designed to examine the effect of personal and social factors on interventions for T2D prevention are needed to better determine the impact of these factors on the success of diet and lifestyle interventions for T2D.

Treatment effect heterogeneity following type 2 diabetes treatment with GLP1-receptor agonists and SGLT2-inhibitors: a systematic review.

BACKGROUND: A precision medicine approach in type 2 diabetes requires the identification of clinical and biological features that are reproducibly associated with differences in clinical outcomes with specific anti-hyperglycaemic therapies. Robust evidence of such treatment effect heterogeneity could support more individualized clinical decisions on optimal type 2 diabetes therapy. METHODS: We performed a pre-registered systematic review of meta-analysis studies, randomized control trials, and observational studies evaluating clinical and biological features associated with heterogenous treatment effects for SGLT2-inhibitor and GLP1-receptor agonist therapies, considering glycaemic, cardiovascular, and renal outcomes. After screening 5,686 studies, we included 101 studies of SGLT2-inhibitors and 75 studies of GLP1-receptor agonists in the final systematic review. RESULTS: Here we show that the majority of included papers have methodological limitations precluding robust assessment of treatment effect heterogeneity. For SGLT2-inhibitors, multiple observational studies suggest lower renal function as a predictor of lesser glycaemic response, while markers of reduced insulin secretion predict lesser glycaemic response with GLP1-receptor agonists. For both therapies, multiple post-hoc analyses of randomized control trials (including trial meta-analysis) identify minimal clinically relevant treatment effect heterogeneity for cardiovascular and renal outcomes. CONCLUSIONS: Current evidence on treatment effect heterogeneity for SGLT2-inhibitor and GLP1-receptor agonist therapies is limited, likely reflecting the methodological limitations of published studies. Robust and appropriately powered studies are required to understand type 2 diabetes treatment effect heterogeneity and evaluate the potential for precision medicine to inform future clinical care.

This study reviews the available evidence on which patient features (such as age, sex, and blood test results) are associated with different outcomes for two recently introduced type 2 diabetes medications: SGLT2-inhibitors and GLP1-receptor agonists. Understanding what individual characteristics are associated with different response patterns may help clinical providers and people living with diabetes make more informed decisions about which type 2 diabetes treatments will work best for an individual. We focus on three outcomes: blood glucose levels (raised blood glucose is the primary symptom of diabetes and a primary aim of diabetes treatment is to lower this), heart disease, and kidney disease. We identified some potential factors that reduce effects on blood glucose levels, including poorer kidney function for SGLT2-inhibitors and lower production of the glucose-lowering hormone insulin for GLP1-receptor agonists. We did not identify clear factors that alter heart and kidney disease outcomes for either medication. Most of the studies had limitations, meaning more research is needed to fully understand the factors that influence treatment outcomes in type 2 diabetes.

Plasma metabolomic profiles associated with mortality and longevity in a prospective analysis of 13,512 individuals.

Experimental studies reported biochemical actions underpinning aging processes and mortality, but the relevant metabolic alterations in humans are not well understood. Here we examine the associations of 243 plasma metabolites with mortality and longevity (attaining age 85 years) in 11,634 US (median follow-up of 22.6 years, with 4288 deaths) and 1878 Spanish participants (median follow-up of 14.5 years, with 525 deaths). We find that, higher levels of N2,N2-dimethylguanosine, pseudouridine, N4-acetylcytidine, 4-acetamidobutanoic acid, N1-acetylspermidine, and lipids with fewer double bonds are associated with increased risk of all-cause mortality and reduced odds of longevity; whereas L-serine and lipids with more double bonds are associated with lower mortality risk and a higher likelihood of longevity. We further develop a multi-metabolite profile score that is associated with higher mortality risk. Our findings suggest that differences in levels of nucleosides, amino acids, and several lipid subclasses can predict mortality. The underlying mechanisms remain to be determined.