Biomarkers of aging serve as important outcome measures in longevity-promoting interventions. However, there is limited consensus on which specific biomarkers are most appropriate for human intervention studies. This work aimed to address this need by establishing an expert consensus on biomarkers of aging for use in intervention studies via the Delphi method. A 3-round Delphi study was conducted using an online platform. In Round 1, expert panel members provided suggestions for candidate biomarkers of aging. In Rounds 2 and 3, they voted on 500 initial statements (yes/no) relating to 20 biomarkers of aging. Panel members could abstain from voting on biomarkers outside their expertise. Consensus was reached when there was ≥70% agreement on a statement/biomarker. Of the 460 international panel members invited to participate, 116 completed Round 1, 87 completed Round 2, and 60 completed Round 3. Across the 3 rounds, 14 biomarkers met consensus that spanned physiological (eg, insulin-like growth factor 1, growth-differentiating factor-15), inflammatory (eg, high sensitivity C-reactive protein, interleukin-6), functional (eg, muscle mass, muscle strength, hand grip strength, Timed-Up-and-Go, gait speed, standing balance test, frailty index, cognitive health, blood pressure), and epigenetic (eg, DNA methylation/epigenetic clocks) domains. Expert consensus identified 14 potential biomarkers of aging which may be used as outcome measures in intervention studies. Future aging research should identify which combination of these biomarkers has the greatest utility.

Summary: Multimorbidity—the coexistence of at least two chronic health conditions within the same individual—is an important global health challenge. In high‐income countries (HICs), multimorbidity is dominated by non‐communicable diseases (NCDs); whereas, the situation may be different in low‐ and middle‐income countries (LMICs), where chronic communicable diseases remain prominent. The aim of this systematic review was to identify determinants (including risk and protective factors) and potential mechanisms underlying multimorbidity from published longitudinal studies across diverse population‐based or community‐dwelling populations in LMICs. We systematically searched three electronic databases (Medline, Embase, and Global Health) using pre‐defined search terms and selection criteria, complemented by hand‐searching. All titles, abstracts, and full texts were independently screened by two reviewers from a pool of four researchers. Data extraction and reporting were according to Preferred Reporting Items for Systematic Reviews and Meta‐Analyses (PRISMA) guidelines. Methodological quality and risk of bias assessment was performed using the Newcastle‐Ottawa Scale for cohort studies. Data were summarized using narrative synthesis. The search yielded 1782 records. Of the 52 full‐text articles included for review, 8 longitudinal population‐based studies were included for final data synthesis. Almost all studies were conducted in Asia, with only one from South America and none from Africa. All studies were published in the last decade, with half published in the year 2021. The definitions used for multimorbidity were heterogeneous, including 3–16 chronic conditions per study. The leading chronic conditions were heart disease, stroke, and diabetes, and there was a lack of consideration of mental health conditions (MHCs), infectious diseases, and undernutrition. Prospectively evaluated determinants included socio‐economic status, markers of social inequities, childhood adversity, lifestyle behaviors, obesity, dyslipidemia, and disability. This review revealed a paucity of evidence from LMICs and a geographical bias in the distribution of multimorbidity research. Longitudinal research into epidemiological aspects of multimorbidity is warranted to build up scientific evidence in regions beyond Asia. Such evidence can provide a detailed picture of disease development, with important implications for community, clinical, and interventions in LMICs. The heterogeneity in study designs, exposures, outcomes, and statistical methods observed in the present review calls for greater methodological standardisation while conducting epidemiological studies on multimorbidity. The limited evidence for MHCs, infectious diseases, and undernutrition as components of multimorbidity calls for a more comprehensive definition of multimorbidity globally.

Background: Real-world data on long-term (> 5 years) weight loss and obesity-related complications after newer bariatric surgical procedures are currently limited. The aim of this longitudinal study was to examine the effectiveness and sustainability of bariatric surgery in a cohort with clinically severe obesity in a multidisciplinary publicly funded service in two teaching hospitals in New South Wales, Australia. Methods: Patients were adults with complex clinically severe obesity with a BMI ≥ 35 kg/m² and at least three significant obesity-related comorbidities, who underwent bariatric surgeries between 2009 and 2017. Detailed obesity-related health outcomes were reported from annual clinical data and assessments for up to 9 years of follow-up. Data were also linked with the national joint replacement registry. Results: A total of 65 eligible patients were included (mean, 7; range, 3–12 significant obesity-related comorbidities); 53.8% female; age 54.2 ± 11.2 years, with baseline BMI 52.2 ± 12.5 kg/m² and weight 149.2 ± 45.5 kg. Most underwent laparoscopic sleeve gastrectomy (80.0%), followed by laparoscopic adjustable gastric banding (10.8%) and one anastomosis gastric bypass (9.2%). Substantial weight loss was maintained over 9 years of follow-up (p < 0.001 versus baseline). Significant total weight loss (%TWL ± SE) was observed (13.2 ± 2.3%) following an initial 1-year preoperative intensive lifestyle intervention, and ranged from 26.5 ± 2.3% to 33.0 ± 2.0% between 1 and 8 years following surgery. Type 2 diabetes mellitus (T2DM), osteoarthritis-related joint pain and depression/severe anxiety were the most common metabolic, mechanical and mental health comorbidities, with a baseline prevalence of 81.5%, 75.4% and 55.4%, respectively. Clinically significant composite cumulative rates of remission and improvement occurred in T2DM (50.0–82.0%) and hypertension (73.7–82.9%) across 6 years. Dependence on continuous positive airway pressure treatment in patients with sleep-disordered breathing fell significantly from 63.1% to 41.2% in 6 years. Conclusion: Bariatric surgery using an intensive multidisciplinary approach led to significant long-term weight loss and improvement in obesity-related comorbidities among the population with clinically complex obesity. These findings have important implications in clinical care for the management of the highest severity of obesity and its medical consequences. Major challenges associated with successful outcomes of bariatric surgery in highly complex patients include improving mental health in the long run and reducing postoperative opioid use. Long-term follow-up with a higher volume of patients is needed in publicly funded bariatric surgery services to better monitor patient outcomes, enhance clinical data comparison between services, and improve multidisciplinary care delivery.

Background and Objectives: Cognitive performance is essential for children, given this is a critical stage of brain growth and development. This systematic review and meta-analysis aimed to ascertain if physical activity or micronutrients impact cognitive performance in children. Materials and Methods: Electronic databases (PubMed and Scopus^®) were searched for relevant articles published between 2012 and 2021. We emphasized randomized controlled trials (RCTs) that examined the effect of physical activity and micronutrients on cognitive performance. Data from eligible studies were gathered and evaluated using random-, fixed- or pooled-effects models with 95% confidence intervals (95% CI). Results: Physical activity appeared to improve both Mathematics (d = 1.12, 95% CI: 0.56, 1.67) and attention (d = 0.65, 95% CI: 0.15, 1.14) performances. The micronutrient vitamin B12 had a positive effect on Mathematics (d = 2.39, 95% CI: 0.79, 3.98), English (d = 5.29, 95% CI: 2.76, 7.83), Geography (d = 5.29, 95% CI: 2.76, 7.83), Science (d = 3.39, 95% CI: 2.62, 4.16) and Arts (d = 3.32, 95% CI: 1.84, 4.79). Zinc was found to positively affect English (d = 3.78, 95% CI: 0.44, 7.13), Geography (d = 4.77, 95% CI: 0.56, 8.98) and Arts (d = 2.39, CI: 0.33, 4.45). Iron positively affected Mathematics (d = 1.29, 95% CI: 0.54, 2.06), English (d = 1.29, 95% CI: 0.44, 7.13), Geography (d = 4.77, 95% CI: 0.56, 8.98) and Arts (d = 2.39, 95% CI: 0.33, 4.45). Conclusions: A more comprehensive intervention with a specific dose/level of physical activity, an increased range of cognitive performance, and a well-designed study design that accounts for dietary intake and other health outcomes are required for future studies.

Objectives To assess the prevalence and factors associated with multimorbidity in a community-dwelling general adult population on a large Health and Demographic Surveillance System (HDSS) scale. Design Population-based cross-sectional study. Setting South East Asia Community Observatory HDSS site in Malaysia. Participants Of 45 246 participants recruited from 13 431 households, 18 101 eligible adults aged 18–97 years (mean age 47 years, 55.6% female) were included. Main outcome measures The main outcome was prevalence of multimorbidity. Multimorbidity was defined as the coexistence of two or more chronic conditions per individual. A total of 13 chronic diseases were selected and were further classified into 11 medical conditions to account for multimorbidity. The conditions were heart disease, stroke, diabetes mellitus, hypertension, chronic kidney disease, musculoskeletal disorder, obesity, asthma, vision problem, hearing problem and physical mobility problem. Risk factors for multimorbidity were also analysed. Results Of the study cohort, 28.5% people lived with multimorbidity. The individual prevalence of the chronic conditions ranged from 1.0% to 24.7%, with musculoskeletal disorder (24.7%), obesity (20.7%) and hypertension (18.4%) as the most prevalent chronic conditions. The number of chronic conditions increased linearly with age (p<0.001). In the logistic regression model, multimorbidity is associated with female sex (adjusted OR 1.28, 95% CI 1.17 to 1.40, p<0.001), education levels (primary education compared with no education: adjusted OR 0.63, 95% CI 0.53 to 0.74; secondary education: adjusted OR 0.60, 95% CI 0.51 to 0.70; tertiary education: adjusted OR 0.65, 95% CI 0.54 to 0.80; p<0.001) and employment status (working adults compared with retirees: adjusted OR 0.70, 95% CI 0.60 to 0.82, p<0.001), in addition to age (adjusted OR 1.05, 95% CI 1.05 to 1.05, p<0.001). Conclusions The current single-disease services in primary and secondary care should be accompanied by strategies to address complexities associated with multimorbidity, taking into account the factors associated with multimorbidity identified. Future research is needed to identify the most commonly occurring clusters of chronic diseases and their risk factors to develop more efficient and effective multimorbidity prevention and treatment strategies.

Background: We aimed to identify specific multimorbidity latent classes among multi-ethnic community-dwelling adults aged ≥ 18 years in Malaysia. We further explored the risk factors associated with these patterns and examined the relationships between the multimorbidity patterns and 11-year all-cause mortality risk, as well as health-related quality of life (HRQoL). Methods: Using data from 18,101 individuals (aged 18–97 years) from the baseline Census 2012, Health Round 2013, and Verbal Autopsies 2012–2023 of the South East Asia Community Observatory (SEACO) health and demographic surveillance system, latent class analysis was performed on 13 chronic health conditions to identify statistically and clinically meaningful groups. Multinomial logistic regression and Cox proportional hazards regression models were conducted to investigate the adjusted association of multimorbidity patterns with the risk factors and mortality, respectively. HRQoL was analyzed by linear contrasts in conjunction with ANCOVA adjusted for baseline confounders. Results: Four distinct multimorbidity latent classes were identified: (1) relatively healthy (n = 10,640); (2) cardiometabolic diseases (n = 2428); (3) musculoskeletal, mobility and sensory disorders (n = 2391); and (4) complex multimorbidity (a group with more severe multimorbidity with combined profiles of classes 2 and 3) (n = 699). Significant variations in associations between socio-demographic characteristics and multimorbidity patterns were discovered, including age, sex, ethnicity, education level, marital status, household monthly income and employment status. The complex multimorbidity group had the lowest HRQoL across all domains compared to other groups (p < 0.001), including physical health, psychological, social relationships and environment. This group also exhibited the highest mortality risk over 11 years even after adjustment of confounders (age, sex, ethnicity, education and employment status), with a hazard of death of 1.83 (95% CI 1.44–2.33), followed by the cardiometabolic group (HR 1.42, 95% CI 1.18–1.70) and the musculoskeletal, mobility and sensory disorders group (HR 1.29, 95% CI 1.04–1.59). Conclusions: Our study advances the understanding of the complexity of multimorbidity and its implications for health outcomes and healthcare delivery. The findings suggest the need for integrated healthcare approaches that account for the clusters of multiple conditions and prioritize the complex multimorbidity cohort. Further longitudinal studies are warranted to explore the underlying mechanisms and evolution of multimorbidity patterns.