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Socio-economic status (SES) and biological aging are risk factors for dementia, including Alzheimer’s disease, however, it is less clear if the associations with SES vary sufficiently across different biological age strata. We used data from 331,066 UK Biobank participants aged 38–73 with mean follow-up of 12 years to examine if associations between SES (assessed by educational attainment, employment status and household income) and dementia and Alzheimer’s disease are modified by biological age (assessed by leucocyte telomere length: LTL). Diagnosis of events was ascertained through hospital admissions data. Cox regressions were used to estimate hazard ratios [HRs]. A consistent dose–response relationship was found, with participants in low SES and shorter LTL strata (double-exposed group) reporting 3.28 (95% confidence interval [CI] 2.57–4.20) and 3.44 (95% CI 2.35–5.04) times higher risks of incident dementia and Alzheimer’s disease respectively, compared to those of high SES and longer LTL (least-exposed group). Of interest is a synergistic interaction between SES and LTL to increase risk of dementia (RERI 0.57, 95% CI 0.07–1.06) and Alzheimer’s disease (RERI 0.79, 95% CI 0.02–1.56). Our findings that SES and biological age (LTL) are synergistic risk factors of dementia and Alzheimer’s disease may suggest the need to target interventions among vulnerable sub-groups.

Background Both physical and psychological health outcomes have been associated with exposure to environmental noise. Noise sensitivity could have the same moderating effect on physical and psychological health outcomes related to environmental noise exposure as on annoyance but this has been little tested. Methods A cohort of 2398 men between 45 and 59 years, the longitudinal Caerphilly Collaborative Heart Disease study, was established in 1984/88 and followed into the mid-1990s. Road traffic noise maps were assessed at baseline. Psychological ill-health was measured in phase 2 in 1984/88, phase 3 (1989/93) and phase 4 (1993/7). Ischaemic heart disease was measured in clinic at baseline and through hospital records and records of deaths during follow up. We examined the longitudinal associations between road traffic noise and ischaemic heart disease morbidity and mortality using Cox Proportional Hazard Models and psychological ill-health using Logistic Regression; we also examined whether noise sensitivity and noise annoyance might moderate these associations. We also tested if noise sensitivity and noise annoyance were longitudinal predictors of ischaemic heart disease morbidity and mortality and psychological ill-health. Results Road traffic noise was not associated with ischaemic heart disease morbidity or mortality. Neither noise sensitivity nor noise annoyance moderated the effects of road traffic noise on ischaemic heart disease morbidity or mortality. High noise sensitivity was associated with lower ischaemic heart disease mortality risk (HR = 0.74, 95%CI 0.57, 0.97). Road traffic noise was associated with Phase 4 psychological ill-health but only among those exposed to 56-60dBA (fully adjusted OR = 1.82 95%CI 1.07, 3.07). Noise sensitivity moderated the association of road traffic noise exposure with psychological ill-health. High noise sensitivity was associated longitudinally with psychological ill-health at phase 3 (OR = 1.85 95%CI 1.23, 2.78) and phase 4 (OR = 1.65 95%CI 1.09, 2.50). Noise annoyance predicted psychological ill-health at phase 4 (OR = 2.47 95%CI 1.00, 6.13). Conclusions Noise sensitivity is a specific predictor of psychological ill-health and may be part of a wider construct of environmental susceptibility. Noise sensitivity may increase the risk of psychological ill-health when exposed to road traffic noise. Noise annoyance may be a mediator of the effects of road traffic noise on psychological ill-health.

With rapid urbanization, built environment has emerged as a set of modifiable factors of cardiovascular disease (CVD) risks. We conducted a systematic review to synthesize evidence on the associations of attributes of urban built environment (e.g. residential density, land use mix, greenness and walkability) with cardiovascular risk factors (e.g. hypertension and arterial stiffness) and major CVD events including mortality. A total of 63 studies, including 31 of cross-sectional design and 32 of longitudinal design conducted across 21 geographical locations and published between 2012 and 2023 were extracted for review. Overall, we report moderately consistent evidence of protective associations of greenness with cardiovascular risks and major CVD events (cross-sectional studies: 12 of 15 on hypertension/blood pressure (BP) and 2 of 3 on arterial stiffness; and longitudinal studies: 6 of 8 on hypertension/BP, 7 of 8 on CVD mortality, 3 of 3 on ischemic heart disease mortality and 5 of 8 studies on stroke hospitalization or mortality reporting significant inverse associations). Consistently, walkability was associated with lower risks of hypertension, arterial stiffness and major CVD events (cross-sectional studies: 11 of 12 on hypertension/BP and 1 of 1 on arterial stiffness; and longitudinal studies: 3 of 6 on hypertension/BP and 1 of 2 studies on CVD events being protective). Sixty-seven percent of the studies were rated as “probably high” risk of confounding bias because of inability to adjust for underlying comorbidities/family history of diseases in their statistical models. Forty-six percent and 14% of the studies were rated as “probably high” risk of bias for exposure and outcome measurements, respectively. Future studies with robust design will further help elucidate the linkages between urban built environment and cardiovascular health, thereby informing planning policies for creating healthy cities.

Medical artificial intelligence (AI) offers great potential for recognizing signs of health conditions in retinal images and expediting the diagnosis of eye diseases and systemic disorders 1 . However, the development of AI models requires substantial annotation and models are usually task-specific with limited generalizability to different clinical applications 2 . Here, we present RETFound, a foundation model for retinal images that learns generalizable representations from unlabelled retinal images and provides a basis for label-efficient model adaptation in several applications. Specifically, RETFound is trained on 1.6 million unlabelled retinal images by means of self-supervised learning and then adapted to disease detection tasks with explicit labels. We show that adapted RETFound consistently outperforms several comparison models in the diagnosis and prognosis of sight-threatening eye diseases, as well as incident prediction of complex systemic disorders such as heart failure and myocardial infarction with fewer labelled data. RETFound provides a generalizable solution to improve model performance and alleviate the annotation workload of experts to enable broad clinical AI applications from retinal imaging. RETFound, a foundation model for retinal images that learns generalizable representations from unlabelled images, is trained on 1.6 million unlabelled images by self-supervised learning and then adapted to disease detection tasks with explicit labels.

BackgroundDisturbed sleep is common throughout the community and is associated with an increase in daytime sleepiness, both of which, in turn are associated with an increased risk of ischaemic vascular disease. The hypothesis that sleep disturbances are predictive of dementia, and in particular vascular dementia was tested in a large community-based cohort of older men.MethodsA questionnaire on sleep disturbances was administered to 1986 men aged 55–69 years in the Caerphilly Cohort Study and 10 years later the men were examined clinically for evidence of dementia or cognitive impairment with no dementia (CIND).FindingsApproximately 20% of the men reported disturbed sleep and 30% reported ‘severe’ daytime sleepiness. Ten years later 1225 men (75% of the surviving men in the cohort) were tested and 268 (22%) were found to be cognitively impaired with 93 (7.6%) showing clear evidence of dementia and the remaining 175 (14.3%) showing evidence of CIND. After adjustment for possible confounding, including cognitive function and the taking of sleeping tablets at baseline, sleep disturbances appeared to be predictive of dementia and CIND of vascular origin, while there was no suggestion of prediction of non-vascular cognitive impairment by sleep. Prediction of vascular dementia appeared to be particularly strong for daytime sleepiness, with an adjusted OR of 4.44 (95% CI 2.05 to 9.61). Further adjustments for psychological distress at baseline reduced the size of the relationships, but the ORs remain large, consistent with a direct positive effect of sleep disturbance on vascular dementia.InterpretationSleep disturbances, and in particular severe daytime sleepiness, appear to be strongly predictive of vascular dementia, but have no predictive power for non vascular dementia.

The rise of the Internet and social media has allowed individuals with different backgrounds, experiences, and opinions to communicate with one another in an open and largely unstructured way. One important question is whether the nature of online engagements between groups relates to the nature of encounters between these groups in the real world. We analyzed online conversations that occurred between members of protest groups from opposite sides of the political spectrum, obtained from Facebook event pages used to organize upcoming political protests and rallies in the United States and the United Kingdom and the occurrence of violence during these protests and rallies. Using natural language processing and text analysis, we show that increased engagement between groups online is associated with increased violence when these groups met in the real world. The level of engagement between groups taking place online is substantial, and can be characterized as negative, brief, and low in integrative complexity. These findings suggest that opposing groups may use unstructured online environments to engage with one another in hostile ways. This may reflect a worsening of relationships, in turn explaining the observed increases in physical violence offline. These findings raise questions as to whether unstructured online communication is compatible with positive intergroup contact, and highlights the role that the Internet might play in wider issues of extremism and radicalization.

The health effects of milk and dairy food consumption would best be determined in randomised controlled trials. No adequately powered trial has been reported and none is likely because of the numbers required. The best evidence comes, therefore, from prospective cohort studies with disease events and death as outcomes. Medline was searched for prospective studies of dairy food consumption and incident vascular disease and Type 2 diabetes, based on representative population samples. Reports in which evaluation was in incident disease or death were selected. Meta-analyses of the adjusted estimates of relative risk for disease outcomes in these reports were conducted. Relevant case–control retrospective studies were also identified and the results are summarised in this article. Meta-analyses suggest a reduction in risk in the subjects with the highest dairy consumption relative to those with the lowest intake: 0.87 (0.77, 0.98) for all-cause deaths, 0.92 (0.80, 0.99) for ischaemic heart disease, 0.79 (0.68, 0.91) for stroke and 0.85 (0.75, 0.96) for incident diabetes. The number of cohort studies which give evidence on individual dairy food items is very small, but, again, there is no convincing evidence of harm from consumption of the separate food items. In conclusion, there appears to be an enormous mis-match between the evidence from long-term prospective studies and perceptions of harm from the consumption of dairy food items.

Childhood adversity and adulthood adversity affect cognition later in life. However, the mechanism through which adversity exerts these effects on cognition remains under-researched. We aimed to investigate if the effect of adversity on cognition was mediated by distress or neuroticism. The UK Biobank is a large, population-based, cohort study designed to investigate risk factors of cognitive health. Here, data were analysed using a cross-sectional design. Structural equation models were fitted to the data with childhood adversity or adulthood adversity as independent variables, distress and neuroticism as mediators and executive function and processing speed as latent dependent variables that were derived from the cognitive scores in the UK Biobank. Complete data were available for 64,051 participants in the childhood adversity model and 63,360 participants in the adulthood adversity model. Childhood adversity did not show a direct effect on processing speed. The effect of childhood adversity on executive function was partially mediated by distress and neuroticism. The effects of adulthood adversity on executive function and processing speed were both partially mediated by distress and neuroticism. In conclusion, distress and neuroticism mediated the deleterious effect of childhood and adulthood adversity on cognition and may provide a mechanism underlying the deleterious consequences of adversity.