Association between adiposity outcomes and residential density: a full-data, cross-sectional analysis of 419 562 UK Biobank adult participants

Background Obesity is a major health issue and an important public health target for urban design. However, the evidence for identifying the optimum residential density in relation to obesity has been far from compelling. We examined the association of obesity with residential density in a large and diverse population sample drawn from the UK Biobank to identify healthy-weight-sustaining density environments. Methods For this full-data, cross-sectional analysis, we used UK Biobank data for adult men and women aged 37–73 years from 22 cities across the UK. Baseline examinations were done between 2006 and 2010. Residential unit density was objectively assessed within a 1 km street catchment of a participant's residence. Other activity-influencing built environment factors were measured in terms of density of retail, public transport, and street-level movement density, which were modelled from network analyses of through movement of street links within the defined catchment. We regressed adiposity indicators of body-mass index (BMI; kg/m2), waist circumference (cm), whole body fat (kg), and obesity (WHO criteria of BMI ≥30 kg/m2) on residential density (units per km2), adjusting for activity-influencing built environment factors and individual covariates. We also investigated effect modification by age, sex, employment status, and physical activity. We used a series of linear continuous and logistic regression models and non-linear restricted cubic spline models as appropriate. Findings Of 502 649 adults in the prospective cohort, 419 562 (83·5%) participants across 22 UK Biobank assessment centres met baseline data requirements and were included in the analytic sample. The fitted restricted cubic spline adiposity-residential density dose–response curve identified a turning point at a residential density of 1800 residential units per km2. Below a residential density of 1800 units per km2, an increment of 1000 units per km2 was positively related with adiposity, being associated with higher BMI (β 0·19 kg/m2, 95% CI 0·14 to 0·24), waist circumference (β 0·41 cm, 0·28 to 0·54), and whole body fat (β 0·40 kg, 0·30 to 0·50), and with increased odds of obesity (odds ratio [OR] 1·10, 1·07 to 1·14). Beyond 1800 units per km2, residential density had a protective effect on adiposity and was associated with lower BMI (β −0·22 kg/m2, −0·25 to −0·20), waist circumference (β −0·54 cm, −0·61 to −0·48), and whole body fat (β −0·38 kg, −0·43 to −0·33), and with decreased odds of obesity (OR 0·91, 0·90 to 0·93). Subgroup analyses identified more pronounced protective effects of residential density among individuals who were younger, female, in employment, and accumulating higher levels of physical activity, except in the case of whole body fat, for which the protective effects were stronger in men. Interpretation Housing-level policy related to the optimisation of healthy density in cities might be a potential upstream-level public health intervention towards the minimisation and offsetting of obesity; however, further research based on accumulated prospective data is necessary for evidencing specific pathways. The findings might mean that governments, such as the UK Government, who are attempting to prevent suburban densification by, for example, prohibiting the subdivision of single lot housing and the conversion of domestic gardens to housing lots, will potentially have the effect of inhibiting the conversion of suburbs into more healthy places to live.published_or_final_versio

Cohort profile: design and methods in the eye and vision consortium of UK Biobank

PURPOSE: To describe the rationale, methods and research potential of eye and vision measures available in UK Biobank. PARTICIPANTS: UK Biobank is a large, multisite, prospective cohort study. Extensive lifestyle and health questionnaires, a range of physical measures and collection of biological specimens are collected. The scope of UK Biobank was extended midway through data collection to include assessments of other measures of health, including eyes and vision. The eye assessment at baseline included questionnaires detailing past ophthalmic and family history, measurement of visual acuity, refractive error and keratometry, intraocular pressure (IOP), corneal biomechanics, spectral domain optical coherence tomography (OCT) of the macula and a disc-macula fundus photograph. Since recruitment, UK Biobank has collected accelerometer data and begun multimodal imaging data (including brain, heart and abdominal MRI) in 100 000 participants. Dense genotypic data and a panel of 20 biochemistry measures are available, and linkage to medical health records for the full cohort has begun. FINDINGS TO DATE: A total of 502 665 people aged between 40 and 69 were recruited to participate in UK Biobank. Of these, 117 175 took part in baseline assessment of vision, IOP, refraction and keratometry. A subgroup of 67 321 underwent OCT and retinal photography. The introduction of eye and vision measures in UK Biobank was accompanied by intensive training, support and a data monitoring quality control process. FUTURE PLANS: UK Biobank is one of the largest prospective cohorts worldwide with extensive data on ophthalmic diseases and conditions. Data collection is an ongoing process and a repeat of the baseline assessment including the questionnaires, measurements and sample collection will be performed in subsets of 25 000 participants every 2-3 years. The depth and breadth of this dataset, coupled with its open-access policy, will create a powerful resource for all researchers to investigate the eye diseases in later life

Periodontitis and Outer Retinal Thickness: a Cross-Sectional Analysis of the United Kingdom Biobank Cohort

\ua9 2024 American Academy of OphthalmologyPurpose: Periodontitis, a ubiquitous severe gum disease affecting the teeth and surrounding alveolar bone, can heighten systemic inflammation. We investigated the association between very severe periodontitis and early biomarkers of age-related macular degeneration (AMD), in individuals with no eye disease. Design: Cross-sectional analysis of the prospective community-based cohort United Kingdom (UK) Biobank. Participants: Sixty-seven thousand three hundred eleven UK residents aged 40 to 70 years recruited between 2006 and 2010 underwent retinal imaging. Methods: Macular-centered OCT images acquired at the baseline visit were segmented for retinal sublayer thicknesses. Very severe periodontitis was ascertained through a touchscreen questionnaire. Linear mixed effects regression modeled the association between very severe periodontitis and retinal sublayer thicknesses, adjusting for age, sex, ethnicity, socioeconomic status, alcohol consumption, smoking status, diabetes mellitus, hypertension, refractive error, and previous cataract surgery. Main Outcome Measures: Photoreceptor layer (PRL) and retinal pigment epithelium–Bruch\u27s membrane (RPE–BM) thicknesses. Results: Among 36 897 participants included in the analysis, 1571 (4.3%) reported very severe periodontitis. Affected individuals were older, lived in areas of greater socioeconomic deprivation, and were more likely to be hypertensive, diabetic, and current smokers (all P < 0.001). On average, those with very severe periodontitis were hyperopic (0.05 \ub1 2.27 diopters) while those unaffected were myopic (−0.29 \ub1 2.40 diopters, P < 0.001). Following adjusted analysis, very severe periodontitis was associated with thinner PRL (−0.55 μm, 95% confidence interval [CI], −0.97 to −0.12; P = 0.022) but there was no difference in RPE–BM thickness (0.00 μm, 95% CI, −0.12 to 0.13; P = 0.97). The association between PRL thickness and very severe periodontitis was modified by age (P < 0.001). Stratifying individuals by age, thinner PRL was seen among those aged 60 to 69 years with disease (−1.19 μm, 95% CI, −1.85 to −0.53; P < 0.001) but not among those aged < 60 years. Conclusions: Among those with no known eye disease, very severe periodontitis is statistically associated with a thinner PRL, consistent with incipient AMD. Optimizing oral hygiene may hold additional relevance for people at risk of degenerative retinal disease. Financial Disclosure(s): Proprietary or commercial disclosure may be found in the Footnotes and Disclosures at the end of this article

Mood and cognition in healthy older European adults: the Zenith study

YesBackground: The study aim was to determine if state and trait intra-individual measures of everyday affect predict cognitive functioning in healthy older community dwelling European adults (n = 387), aged 55-87 years. Methods: Participants were recruited from centres in France, Italy and Northern Ireland. Trait level and variability in positive and negative affect (PA and NA) were assessed using self-administered PANAS scales, four times a day for four days. State mood was assessed by one PANAS scale prior to assessment of recognition memory, spatial working memory, reaction time and sustained attention using the CANTAB computerized test battery. Results: A series of hierarchical regression analyses were carried out, one for each measure of cognitive function as the dependent variable, and socio-demographic variables (age, sex and social class), state and trait mood measures as the predictors. State PA and NA were both predictive of spatial working memory prior to looking at the contribution of trait mood. Trait PA and its variability were predictive of sustained attention. In the final step of the regression analyses, trait PA variability predicted greater sustained attention, whereas state NA predicted fewer spatial working memory errors, accounting for a very small percentage of the variance (1-2%) in the respective tests. Conclusion: Moods, by and large, have a small transient effect on cognition in this older sample

Association between adiposity outcomes and residential density: a full-data, cross-sectional analysis of 419 562 UK Biobank adult participants

Background Obesity is a major health issue and an important public health target for urban design. However, the evidence for identifying the optimum residential density in relation to obesity has been far from compelling. We examined the association of obesity with residential density in a large and diverse population sample drawn from the UK Biobank to identify healthy-weight-sustaining density environments. Methods For this full-data, cross-sectional analysis, we used UK Biobank data for adult men and women aged 37–73 years from 22 cities across the UK. Baseline examinations were done between 2006 and 2010. Residential unit density was objectively assessed within a 1 km street catchment of a participant’s residence. Other activity-influencing built environment factors were measured in terms of density of retail, public transport, and street-level movement density, which were modelled from network analyses of through movement of street links within the defined catchment. We regressed adiposity indicators of body-mass index (BMI; kg/m²), waist circumference (cm), whole body fat (kg), and obesity (WHO criteria of BMI ≥30 kg/m²) on residential density (units per km²), adjusting for activity-influencing built environment factors and individual covariates. We also investigated effect modification by age, sex, employment status, and physical activity. We used a series of linear continuous and logistic regression models and non-linear restricted cubic spline models as appropriate. Findings Of 502 649 adults in the prospective cohort, 419 562 (83·5%) participants across 22 UK Biobank assessment centres met baseline data requirements and were included in the analytic sample. The fitted restricted cubic spline adiposity-residential density dose–response curve identified a turning point at a residential density of 1800 residential units per km². Below a residential density of 1800 units per km², an increment of 1000 units per km² was positively related with adiposity, being associated with higher BMI (β 0·19 kg/m², 95% CI 0·14 to 0·24), waist circumference (β 0·41 cm, 0·28 to 0·54), and whole body fat (β 0·40 kg, 0·30 to 0·50), and with increased odds of obesity (odds ratio [OR] 1·10, 1·07 to 1·14). Beyond 1800 units per km², residential density had a protective effect on adiposity and was associated with lower BMI (β –0·22 kg/m², –0·25 to –0·20), waist circumference (β –0·54 cm, –0·61 to –0·48), and whole body fat (β –0·38 kg, –0·43 to –0·33), and with decreased odds of obesity (OR 0·91, 0·90 to 0·93). Subgroup analyses identified more pronounced protective effects of residential density among individuals who were younger, female, in employment, and accumulating higher levels of physical activity, except in the case of whole body fat, for which the protective effects were stronger in men. Interpretation Housing-level policy related to the optimisation of healthy density in cities might be a potential upstream-level public health intervention towards the minimisation and offsetting of obesity; however, further research based on accumulated prospective data is necessary for evidencing specific pathways. The findings might mean that governments, such as the UK Government, who are attempting to prevent suburban densification by, for example, prohibiting the subdivision of single lot housing and the conversion of domestic gardens to housing lots, will potentially have the effect of inhibiting the conversion of suburbs into more healthy places to live.</p

Residential density and adiposity: Findings from the UK Biobank

Poster Presentation -Diet, diabetes and obesity: Manuscript No. THELANCET-D-17-04013R1Background Obesity has emerged as a global pandemic, however the evidence for identifying the optimum residential density in relation to obesity has been far from compelling. High residential density may be hypothesized to constitute leptogenic multi-functional environments promoting active living. We examine the association between adiposity and housing unit density. Methods This cross-sectional study involved 450,433 adults from the UK Biobank aged 38-73 years with full data. Residential unit density was objectively assessed within one-kilometer street catchment of participants' residence. Other activity-influencing built environment included density of retail, public transport and street movement density modelled from network analyses of through-movement of street links within the defined catchment. Adiposity is expressed in-terms of measured body mass index (BMI; Kg/m²), waist circumference (WC; cm), whole body fat (WBF; Kg), and obesity as defined by WHO. We fitted linear and non-linear (restrictedcubic-spline) models after adjusting for activity-influencing built environment, neighbourhood deprivation, socio-demographics, lifestyle and co-morbidities and investigated effect modification by gender, age, and physical activity. Findings Restricted-cubic-spline model with three knots best fitted the data identifying two inflexion points at residential densities of 1600 and 3400 units/Km². Below a density of 1600 units/Km², increment of 1000 units/Km² was significantly associated with higher BMI (βBMI=0.24, 95% CI: 0.19 to 0.30), WC (βWC=0.55, 0.40 to 0.69), WBF (βWBF=0.57, 0.46 to 0.68) and odds of obesity (ORObesity=1.13, 1.09 to 1.13). Between 1600-3400 units/Km², it was associated with lower BMI (βBMI=-0.13, -0.18 to -0.08), WC (βWC=-0.19, -0.32 to -0.07), WBF (βWBF=-0.20, -0.30 to -0.10) and obesity (ORObesity=0.96, 0.94 to 0.99). Above 3400 units/Km², each increment of 1000 units/Km2 was leptogenic, being associated with lower BMI (βBMI=-0.15, -0.19 to -0.11), WC (βWC=-0.50, -0.60 to -0.40), WBF (βWBF=-0.26, -0.34 to -0.18) and obesity (ORObesity= 0.93, 0.91 to 0.95). Stronger leptogenic effects of housing density were observed among younger, female and participants doing higher physical activity. Interpretation High residential density is associated with lower adiposity in a large and diverse population sample. The evidence point to the value of housing-level policy related to densification as an upstream-level candidate for public health intervention against adiposity. Further longitudinal evidence are needed to establish causality

Residential Density and Adiposity: Findings from the UK Biobank

Manuscript Number: THELANCET-D-17-04013R1 Background Obesity has emerged as a global pandemic, however the evidence for identifying the optimum residential density in relation to obesity has been far from compelling. High residential density may be hypothesized to constitute leptogenic multi-functional environments promoting active living. We examine the association between adiposity and housing unit density. Methods This cross-sectional study involved 450,433 adults from the UK Biobank aged 38-73 years with full data. Residential unit density was objectively assessed within one-kilometer street catchment of participants' residence. Other activity-influencing built environment included density of retail, public transport and street movement density modelled from network analyses of through-movement of street links within the defined catchment. Adiposity is expressed in-terms of measured body mass index (BMI; Kg/m²), waist circumference (WC; cm), whole body fat (WBF; Kg), and obesity as defined by WHO. We fitted linear and non-linear (restrictedcubic-spline) models after adjusting for activity-influencing built environment, neighbourhood deprivation, socio-demographics, lifestyle and co-morbidities and investigated effect modification by gender, age, and physical activity. Findings Restricted-cubic-spline model with three knots best fitted the data identifying two inflexion points at residential densities of 1600 and 3400 units/Km². Below a density of 1600 units/Km², increment of 1000 units/Km² was significantly associated with higher BMI (βBMI=0.24, 95% CI: 0.19 to 0.30), WC (βWC=0.55, 0.40 to 0.69), WBF (βWBF=0.57, 0.46 to 0.68) and odds of obesity (ORObesity=1.13, 1.09 to 1.13). Between 1600-3400 units/Km², it was associated with lower BMI (βBMI=-0.13, -0.18 to -0.08), WC (βWC=-0.19, -0.32 to -0.07), WBF (βWBF=-0.20, -0.30 to -0.10) and obesity (ORObesity=0.96, 0.94 to 0.99). Above 3400 units/Km², each increment of 1000 units/Km2 was leptogenic, being associated with lower BMI (βBMI=-0.15, -0.19 to -0.11), WC (βWC=-0.50, -0.60 to -0.40), WBF (βWBF=-0.26, -0.34 to -0.18) and obesity (ORObesity= 0.93, 0.91 to 0.95). Stronger leptogenic effects of housing density were observed among younger, female and participants doing higher physical activity. Interpretation High residential density is associated with lower adiposity in a large and diverse population sample. The evidence point to the value of housing-level policy related to densification as an upstream-level candidate for public health intervention against adiposity. Further longitudinal evidence are needed to establish causality

Association between individual-level socioeconomic position and incident dementia using UK Biobank data: a prospective study

Background Under-education and living in poverty are known risk factors for dementia. However, single-variable makers of socioeconomic position (SEP) are often correlated and cannot reflect the overall SEP. We examined association between composite SEP and incident dementia using UK-wide data. Methods We leveraged data from the UK Biobank, a nation-wide cohort of half-a-million participants recruited across 22 assessment centres during 2006–10. Participants with data on SEP and without dementia at baseline were included. A composite individual-level metric of SEP (low, medium, or high) was developed through latent class analysis using Stata's gsem command and identified through item-response probabilities based on participants' single socioeconomic factors (ie, education, employment, and household income). Cox proportional hazard models were developed to examine the association between composite SEP and incident dementia after adjusting for age, ethnicity, lifestyle factors (eg, living alone), social interaction (eg, frequency of visits from acquaintances), urbanicity, clinical variables (eg, central obesity), and stratified by sex. As sensitivity test, we repeated our analysis with single socioeconomic factors. Electronic informed consent was obtained from participants at the UK Biobank assessment centres before participations and UK Biobank acquired ethical approval from the National Health Service National Research Ethics Service. Findings We included 340 366 adult participants (17 8195 [52·4%] were women and 32 6753 [96·0%] White) aged 38–73 with 3541 incident dementia cases over a mean follow-up period of 12·0 years (SD 1·7). Relative to participants in the highest SEP, those in the medium (HR 1·53 [95% CI 1·33–1·77]; p<0·0001) and low (2·38 [2·05–2·77]; p<0·0001) SEP were associated with higher risks of incident dementia. Sensitivity analyses consistently found higher risks of incident dementia in participants of low educational attainment (HR 1·14 [95% CI 1·03–1·27]; p=0·0107), low household income (HR 2·33 [95% CI 2·03–2·68]; p<0·0001) and being unemployed (HR 1·27 [95% CI 1·11–1·47]; p=0·0008), relative to those of high education, high household income, and being employed, respectively. Limitations of the study include a response of only 503 325 (5·5%) of 9·2 million participants registered with the National Health Service and residual confounding. Interpretation This study presented a parsimonious approach to construct a composite metric of SEP by employing three key indicators. We found that participants of low SEP were associated with an elevated risk of incident dementia. Socially deprived populations maybe more likely to be exposed to unfavourable psychosocial and environmental stressors that escalate risk of dementia. Our study further strengthens the evidence base for designing policy interventions for at-risk subgroups of lower SEP strata to reduce burdens of dementia

Recurrent depression has persistent effects on cognition but this does not appear to be mediated by neuroinflammation

Background Later-life depression appears to be different to depression in younger adults. The underlying pathology may also differ. Depression is linked to dementia but whether it is a risk factor or an early sign of a developing dementia remains unclear. Neuroinflammation is increasingly recognised in both depression and Alzheimer's Disease. Aims To investigate the link between depression, inflammation and dementia. We hypothesised that recurrent depression has adverse effects on performance in cognitive tests in middle to older age and that this effect is modified by anti-inflammatory medication. Methods We identified UK based cohort studies which included individuals aged >50, had medical information, results from detailed cognitive testing and had used reliable measures to assess depression. Individuals with recurrent depression had ≥ 2 episodes of depression. Controls had no history of depression. The presence/absence of inflammatory illness was assessed using a standardised list of inflammatory conditions. Individuals with dementia, chronic neurological and psychotic conditions were excluded. Logistic and linear regression were used to examine the effect of depression on cognitive test performance and the mediating effect of chronic inflammation. Results Unexpectedly in both studies there was evidence that those with recurrent depression performed better in some cognitive tasks (e.g Mill Hill vocabulary) but worse in others (e.g. reaction time). In UK Biobank there was no evidence that anti-inflammatories moderated this effect. Limitations Cross-sectional assessment of cognition. Conclusions Although previous recurrent depression has small effects on cognitive test performance this does not appear to be mediated by chronic inflammatory disease