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Fulltext Effects of Physical Activity and Micronutrients on Cognitive Performance in Children Aged 6 to 11 Years: A Systematic Review and Meta-Analysis of Randomized Controlled Trials

Meli AM, Ali A, Mhd Jalil AM, Mohd Yusof H, Tan MMC

Medicina (Kaunas), 2021 Dec 30;58(1).
PMID: 35056365 DOI: 10.3390/medicina58010057

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.
Fulltext Prevalence of and factors associated with multimorbidity among 18 101 adults in the South East Asia Community Observatory Health and Demographic Surveillance System in Malaysia: a population-based, cross-sectional study of the MUTUAL consortium

Tan MMC, Prina AM, Muniz-Terrera G, Mohan D, Ismail R, Assefa E, et al.

BMJ Open, 2022 Dec 23;12(12):e068172.
PMID: 36564121 DOI: 10.1136/bmjopen-2022-068172

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.
Determinants of multimorbidity in low- and middle-income countries: A systematic review of longitudinal studies and discovery of evidence gaps

Tan MMC, Barbosa MG, Pinho PJMR, Assefa E, Keinert AÁM, Hanlon C, et al.

Obes Rev, 2024 Feb;25(2):e13661.
PMID: 38105610 DOI: 10.1111/obr.13661

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.

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