METHODS: We propose a Bayesian joint modelling approach to determine mortality due to cognitive impairment via repeated measures of 3MS scores trajectories over a 21-year follow-up period. Data for this study are taken from the Osteoporotic Fracture longitudinal study among women aged 65+ which started in 1986-88.

RESULTS: The standard relative risk model from the analyses with a baseline 3MS score after adjusting for all the significant covariates demonstrates that, every unit decrease in a 3MS score corresponds to a non-significant 1.059 increase risk of mortality with a 95% CI of (0.981, 1.143), while the extended model results in a significant 0.09% increased risk in mortality. The joint modelling approach found a strong association between the 3MS scores and the risk of mortality, such that, every unit decrease in 3MS scores results in a 1.135 (13%) increased risk of death via cognitive impairment with a 95% CI of (1.056, 1.215).

METHODS: We harmonised data from 13 longitudinal cohort studies of ageing in North America, South America, Europe, Africa, Asia, and Australia. Studies were eligible for inclusion if they had baseline data for social connection markers and at least two waves of cognitive scores. Follow-up periods ranged from 0 years to 15 years across cohorts. We included participants with cognitive data for at least two waves and social connection data for at least one wave. We then identified and excluded people with dementia at baseline. Primary outcomes were annual rates of change in global cognition and cognitive domain scores over time until final follow-up within each cohort study analysed by use of an individual participant data meta-analysis. Linear mixed models within cohorts used baseline social connection markers as predictors of the primary outcomes. Effects were pooled in two stages using random-effects meta-analyses. We assessed the primary outcomes in the main (partially adjusted) and fully adjusted models. Partially adjusted models controlled for age, sex, and education; fully adjusted models additionally controlled for diabetes, hypertension, smoking, cardiovascular risk, and depression.

FINDINGS: Of the 40 006 participants in the 13 cohort studies, we excluded 1392 people with dementia at baseline. 38 614 individual participants were included in our analyses. For the main models, being in a relationship or married predicted slower global cognitive decline (b=0·010, 95% CI 0·000-0·019) than did being single or never married; living with others predicted slower global cognitive (b=0·007, 0·002-0·012), memory (b=0·017, 0·006-0·028), and language (b=0·008, 0·000-0·015) decline than did living alone; and weekly interactions with family and friends (b=0·016, 0·006-0·026) and weekly community group engagement (b=0·030, 0·007-0·052) predicted slower memory decline than did no interactions and no engagement. Never feeling lonely predicted slower global cognitive (b=0·047, 95% CI 0·018-0·075) and executive function (b=0·047, 0·017-0·077) decline than did often feeling lonely. Degree of social support, having a confidante, and relationship satisfaction did not predict cognitive decline across global cognition or cognitive domains. Heterogeneity was low (I2=0·00-15·11%) for all but two of the significant findings (association between slower memory decline and living with others [I2=58·33%] and community group engagement, I2=37·54-72·19%), suggesting robust results across studies.

INTERPRETATION: Good social connections (ie, living with others, weekly community group engagement, interacting weekly with family and friends, and never feeling lonely) are associated with slower cognitive decline.

METHODS: A total of 2406 Malaysian children aged 5 to 12 years, who had participated in the South East Asian Nutrition Surveys (SEANUTS), were included in this study. Cognitive performance [non-verbal intelligence quotient (IQ)] was measured using Raven's Progressive Matrices, while socioeconomic characteristics were determined using parent-report questionnaires. Body mass index (BMI) was calculated using measured weight and height, while BMI-for-age Z-score (BAZ) and height-for-age Z-score (HAZ) were determined using WHO 2007 growth reference.

RESULTS: Overall, about a third (35.0%) of the children had above average non-verbal IQ (high average: 110-119; superior: ≥120 and above), while only 12.2% were categorized as having low/borderline IQ ( 3SD), children from very low household income families and children whose parents had only up to primary level education had the highest prevalence of low/borderline non-verbal IQ, compared to their non-obese and higher socioeconomic counterparts. Parental lack of education was associated with low/borderline/below average IQ [paternal, OR = 2.38 (95%CI 1.22, 4.62); maternal, OR = 2.64 (95%CI 1.32, 5.30)]. Children from the lowest income group were twice as likely to have low/borderline/below average IQ [OR = 2.01 (95%CI 1.16, 3.49)]. Children with severe obesity were twice as likely to have poor non-verbal IQ than children with normal BMI [OR = 2.28 (95%CI 1.23, 4.24)].

METHODS: Two schools in Kuala Lumpur with similar socio-demographic characteristics were assigned as intervention (IG) and control (CG), respectively. Inclusion criteria were healthy Malaysian overweight/obese children aged 9 to 11 years who had no serious co-morbidity. Children who reported consuming whole grain foods in their 3-day diet-recall during recruitment were excluded. A total of 63 children (31 IG; 32 CG) completed the intervention. KAP questionnaire was self-administered at baseline [T0] and post intervention (at 3rd [T1] and 9th month [T2]). The baseline differences between the IG and CG across socio-demographics and scores of KAP toward whole grains were determined using chi-square and t-test, respectively. ANCOVA was performed to determine the effect of the GReat-Child Trial™ on KAP towards whole grains at post-intervention and follow-up. Baseline variables were considered as covariates.