Townsend Index Research Articles

Circulating ketone bodies, genetic predisposition, and incident atrial fibrillation

Abstract Background Ketone bodies (KB) are essential alternative fuel sources for the myocardium. However, the evidence on the level of circulating KB and heart disorders is inconsistent. Whether the total and individual KB are associated with risk of onset atrial fibrillation (AF) in the general population and in individuals with different genetic susceptibilities to AF are still unclear. Purpose To examine the association between circulating KB and AF risk and to further test whether genetic risk could modify the above association. Methods In the UK Biobank, 247,304 participants (mean age 56.5, 45.3% men) with available data on KB and without baseline AF were included. The concentrations of KB, including β-hydroxybutyrate (β-OHB), acetoacetate, and acetone, were measured using nuclear magnetic resonance, and the values of KB were increased by one and then log10-transformed for analyses. The genetic risk of AF was based on the standard polygenic risk score. The definitions of AF were based on the ICD-10 code I48, which was linked to primary care, hospital admission electronic health records and death records. Cox proportional hazard model was used to estimate the hazard ratio (HR) with 95% confidence interval (CI). Results During a median follow-up of 13.8 years, 16,936 cases of onset of AF were recorded. After adjusting for age, sex, race, Townsend index, education, alcohol intake frequency, smoking status, healthy diet, metabolic equivalent, body mass index, systolic blood pressure (SBP), total cholesterol, estimated glomerular filtration rate, cardiovascular diseases, and diabetes, elevated total KB, β-OHB, acetoacetate, and acetone were all with the risk of AF (HR, 95% CI per 10-fold increase: 1.20, 1.13-1.28; 1.13, 1.07-1.19; 1.12, 1.06-1.18; and 1.78, 1.57-2.01, respectively). The highest risk of AF was observed among individuals at high genetic risk to AF and had the highest quartile of total KB (HR 2.91, 95% CI 2.66-3.19). Participants who had low genetic risk were more susceptible to high total KB for incident AF (p for interaction = 0.036). The associations of total KB, β-OHB, and acetone with AF risk were more prominent for men (HR, 95% CI per 10-fold increase: 1.32, 1.22-1.44; 1.22, 1.14-1.31; 2.01, 1.72-2.36) than for women (p for interaction <0.05). The association between total KB and AF risk was strengthened in individuals <60 years, current smokers, and those with SBP<130 mmHg (p for interaction = 0.033, 0.021, and 0.017, respectively). Conclusions Circulating KB concentrations were associated with AF risk, with acetone showing the strongest relationship with AF. Individuals at low genetic risk were more susceptible to the level of total KB for incident AF. Our findings suggest that KB may be a biomarker, particularly for identifying individuals without AF at baseline who are at low genetic risk. The additive value of plasma KB to a risk prediction score warrants further investigation.

Investigating the Role of Neighborhood Socioeconomic Status and Germline Genetics on Prostate Cancer Risk.

Genetic factors play an important role in prostate cancer (PCa) development with polygenic risk scores (PRS) predicting disease risk across genetic ancestries. However, there are few convincing modifiable factors for PCa and little is known about their potential interaction with genetic risk. We analyzed incident PCa cases (n=6,155) and controls (n=98,257) of European and African ancestry from the UK Biobank (UKB) cohort to evaluate the role of neighborhood socioeconomic status (nSES)-and how it may interact with PRS-on PCa risk. We evaluated a multi-ancestry PCa PRS containing 269 genetic variants to understand the association of germline genetics with PCa in UKB. Using the English Indices of Deprivation, a set of validated metrics that quantify lack of resources within geographical areas, we performed logistic regression to investigate the main effects and interactions between nSES deprivation, PCa PRS, and PCa. The PCa PRS was strongly associated with PCa (OR=2.04; 95%CI=2.00-2.09; P<0.001). Additionally, nSES deprivation indices were inversely associated with PCa: employment (OR=0.91; 95%CI=0.86-0.96; P<0.001), education (OR=0.94; 95%CI=0.83-0.98; P<0.001), health (OR=0.91; 95%CI=0.86-0.96; P<0.001), and income (OR=0.91; 95%CI=0.86-0.96; P<0.001). The PRS effects showed little heterogeneity across nSES deprivation indices, except for the Townsend Index (P=0.03). We reaffirmed genetics as a risk factor for PCa and identified nSES deprivation domains that influence PCa detection and are potentially correlated with environmental exposures that are a risk factor for PCa. These findings also suggest that nSES and genetic risk factors for PCa act independently.

Machine learning uncovers manganese as a key nutrient associated with reduced risk of steatotic liver disease.

Metabolic dysfunction-associated steatotic liver disease (MASLD) affects approximately 20%-30% of the general population and is linked to high-caloric western style diet. However, there are little data that specific nutrients might help to prevent steatosis. We analysed the UK Biobank (ID 71300) 24 h-nutritional assessments and investigated the association between nutrient intake calculated from food questionnaires and hepatic steatosis indicated by imaging or ICD10-coding. The effect of manganese (Mn) on subgroups with risk single nucleotide polymorphism carriage as well as the effect on metabolomics was investigated. All analyses are corrected for age, sex, body mass index, Townsend index for socioeconomic status, kcal, alcohol, protein intake, fat intake, carbohydrate intake, energy from beverages, diabetes, physical activity and for multiple testing. We used a random forest classifier to analyse the feature importance of 63 nutrients and imaging-proven steatosis in a cohort of over 25 000 UK Biobank participants. Increased dietary Mn intake was associated with a lower likelihood of MRI-diagnosed steatosis. Subsequently, we conducted a cohort study in over 200 000 UK Biobank participants to explore the relationship between Mn intake and hepatic or cardiometabolic outcomes and found that higher Mn intake was associated with a lower risk of ICD-10 coded steatosis (OR = .889 [.838-.943], p < .001), independent of other potential confounders. Our study provides evidence that higher Mn intake may be associated with lower odds of steatosis in a large population-based sample. These findings underline the potential role of Mn in the prevention of steatosis, but further research is needed to confirm these findings and to elucidate the underlying mechanisms.

Association between socioeconomic deprivation and bone health status in the UK biobank cohort participants

SummaryThe effect of deprivation on total bone health status has not been well defined. We examined the relationship between socioeconomic deprivation and poor bone health and falls and we found a significant association. The finding could be beneficial for current public health strategies to minimise disparities in bone health.PurposeSocioeconomic deprivation is associated with many illnesses including increased fracture incidence in older people. However, the effect of deprivation on total bone health status has not been well defined. To examine the relationship between socioeconomic deprivation and poor bone health and falls, we conducted a cross-sectional study using baseline measures from the United Kingdom (UK) Biobank cohort comprising 502,682 participants aged 40–69 years at recruitment during 2006–2010.MethodWe examined four outcomes: 1) low bone mineral density/osteopenia, 2) fall in last year, 3) fracture in the last five years, and 4) fracture from a simple fall in the last five years. To measure socioeconomic deprivation, we used the Townsend index of the participant’s residential postcode.ResultsAt baseline, 29% of participants had low bone density (T-score of heel < -1 standard deviation), 20% reported a fall in the previous year, and 10% reported a fracture in the previous five years. Among participants experiencing a fracture, 60% reported the cause as a simple fall. In the multivariable logistic regression model after controlling for other covariates, the odds of a fall, fracture in the last five years, fractures from simple fall, and osteopenia were respectively 1.46 times (95% confidence interval [CI] 1.42–1.49), 1.26 times (95% CI 1.22–1.30), 1.31 times (95% CI 1.26–1.36) and 1.16 times (95% CI 1.13–1.19) higher for the most deprived compared with the least deprived quantile.ConclusionSocioeconomic deprivation was significantly associated with poor bone health and falls. This research could be beneficial to minimise social disparities in bone health.

Habitual coffee and tea consumption and risk of cataract: A prospective cohort study from the UK Biobank

BackgroundTo study the association of habitual coffee and tea consumption with the risk of cataract. MethodsThis prospective cohort study enrolled UK Biobank participants between 2006 and 2010, and prospectively followed them up for cataract diagnosis. We examined the associations of self-reported intake of tea and coffee and the calculated combined caffeine intake, with the risk of incident cataract. Cox proportional hazards models were analyzed after adjusting for age, sex, race, diabetes, Townsend Index, income, education, smoking and alcohol status. ResultsA total of 444,787 UK Biobank participants aged from 37 to 73 years old who had no cataract at baseline were included. Coffee intake of 2 - 3 cups/day (HR 0.973, 95% CI 0.949–0.998) or tea intake of 4 - 6 cups/day (HR 0.962, 95% CI 0.934–0.990) or combination caffeine intake of 160.0 - 235.0 mg/day (HR 0.950, 95% CI 0.925–0.976) were linked with the lowest risk of incident cataract. Cox models with restricted cubic splines showed J-shaped associations of coffee, tea, and combined caffeine intake with the risk of cataract (all p for nonlinear <0.001). ConclusionsModerate habitual consumption of coffee and tea is associated with a lower risk of cataract. To maximize the protective effect against cataract, it is advisable to control total caffeine intake from coffee and tea within a range of 160.0 - 235.0 mg/day.

Sick individuals, sick populations revisited: a test of the Rose hypothesis for type 2 diabetes disparities

IntroductionThe Rose hypothesis predicts that since genetic variation is greater within than between populations, genetic risk factors will be associated with individuals’ risk of disease but not population disparities, and...

Sex specific lifetime risk of incident cardiovascular events. Results from a large British population-based cohort study

Abstract Background There are marked sex differences in cardiovascular (CV) disease, most characteristically with men having a higher risk of coronary heart disease and myocardial infarction (MI). The sex differences in the absolute lifetime risk of CV disease as well as the different profiles of first incident CV events remain poorly described. Purpose Using data from a large British population-based cohort study with long follow-up, we aimed to compare the sex differences in the lifetime risk of incident CV events (MI, stroke, atrial fibrillation (AF), heart failure (HF), peripheral artery disease (PAD) and CV mortality). Methods Eligible participants at the study baseline (1993-1998) were included and followed up until March 2018. Cause-specific hazard ratios were ascertained using Weibull regressions. The sex-specific lifetime risks of each outcome were ascertained using Weibull regressions accounting for the competing risk of death. All models were adjusted for time-updated covariates: ethnicity, Townsend index of deprivation, systolic blood pressure, hypercholesterolaemia, diabetes, smoking, alcohol intake, physical activity, body mass index, fruit/vegetable intake, non-cardiovascular conditions and medication. Results 8975 men and 11,330 women aged ≥40 and free of CV disease at baseline were included. The median follow-up was 22.3 years. Compared to women, men were more likely to be older, have higher systolic blood pressure, higher BMI and be less physically active. Men were less likely to have prevalent non-cardiovascular comorbidities. The adjusted cumulative incidence of a CV event ranged between 13.8%-28.2% for men and 7.5%-21.2% for women (Figure 1). The lifetime risk of CV mortality was 28.7% for men and 22.9% for women. Compared to women, the relative risk of incident CV events for men was two-fold higher for MI (cause specific hazard ratio (95% confidence interval) – 2.05 (1.83-2.30)) and PAD (2.02 (1.83-2.23)), 50% higher for HF (1.52 (1.39-1.66)) and AF (1.51 (1.40-1.62)), 42% for cardiovascular mortality (1.42 (1.32-1.53)) and 12% for stroke (1.12 (1.03-1.22)). There were also sex differences in the lifetime incidence of different types of first CV event (Figure 2). Amongst men, MI had the highest incidence as a first CV event throughout lifetime. The earliest incidence rise in MI occurred by 50 years and was followed by AF, PAD, stroke and heart failure over the following decades. In women, the incidence of MI as a first CV event was highest between 50-60 years but was overtaken by AF by 65 years and stroke by 70 years. Conclusions Men had a higher risk of incident cardiovascular disease throughout their lifetime than women, but these sex differences were most pronounced for MI and PAD, followed by AF, HF and CV mortality. These were also reflected in the different sex profiles characterising the type of first incident CV event. These differences highlight the importance of tailoring sex-specific primary preventative strategies.Figure 1Figure 2

Non-alcoholic fatty liver disease and socioeconomic determinants in an Iranian cohort study

BackgroundNon-alcoholic fatty liver disease (NAFLD) is widespread worldwide. On the other hand, social inequality and socioeconomic status (SES) can affect all aspects of health. Therefore, this study aimed to investigate the relationship between SES indicators and NAFLD.MethodsThis was a cross-sectional study using data from the registration phase of the Hoveyzeh Cohort Study, which included 10,009 individuals aged 35–70 years from May 2016 to August 2018. Fatty liver disease was determined based on Fatty Liver Index (FLI). The crude and adjusted odds ratios were calculated by logistic regression analysis to estimate associations between the fatty liver index and SES after controlling the potential confounders.ResultsAccording to the FLI index, there were 2,006 people with fatty liver (28%) and 5,246 people without fatty liver (72%). Several 4496 people (62%) were women. The chi-square test showed significant relationships between the educational level and skill level (P < 0.001), the wealth index (P < 0.001), and Townsend Index (P < 0.001) with fatty liver index. In multivariable analysis, after adjustment for age, sex, physical activity, smoking, type of residence, calorie intake, dyslipidemia, skill level, and diabetes, the wealth index (p < 0.001) was positively associated with the fatty liver index. Besides, a reverse and significant association was seen between the Townsend index and the fatty liver index(p < 0.001). In contrast, no significant associations were seen between gender and educational level with the fatty liver index.ConclusionsA more vulnerable SES is associated with NAFLD. Fatty liver index and socioeconomic indicators can be powerful monitoring tools to monitor health differences in diagnosing NAFLD.

Construction and validation of CAPSES scale as a composite indicator of SES for health research: an application to modeling social determinants of cardiovascular diseases

BackgroundThe main objective of this study was to construct and validate a composite socioeconomic status indicator containing material capital, human capital, and social capital (CAPSES scale) and also appropriate it for CVDs in a large population-based study.MethodsThis cross-sectional study, the Urban HEART-2 project, was conducted in Tehran, Iran, in 2011. A total of 34,116 households covering 118,542 individuals were assessed in this study. A 14-parts questionnaire was completed for all selected households. All the gathered data were based on the participants’ self-reports. Literacy, wealth index, expenditure, skill level, and Townsend index were used as SES indexes. CVDs, including Hypertension, Myocardial infarction, and stroke, were considered the main outcomes. A structural equation model (SEM) was used to construct a CAPSES scale and a composition index of SES. Criterion validity and Construct validity were used to assess this scale.ResultsA total of 91,830 subjects consisting of 33,884 (49%) men were included in this analysis. The mean age of the participants was 41.5 ± 11.37 years. Among the assessed participants, 5904(6.4%) reported hypertension, 1507(1.6%) myocardial infarction, and 407(0.4%) strokes. The overall weighted prevalence of self-reported cardiovascular events (hypertension, stroke, and MI) was 8.03% (95%CI: 7.8–8.2). Inverse associations were seen between the CAPSES scale and its domains with CVDs, adjusted for sex, age, BMI, smoking, and diabetes by a multiple logistic regression model.ConclusionThe CAPSES scale was significantly associated with stroke and hypertension. Our findings showed that the CAPSES index could be useful for public health research.

Do associations of physical activity and sedentary behaviour with cardiovascular disease and mortality differ across socioeconomic groups? A prospective analysis of device-measured and self-reported UK Biobank data

ObjectiveTo examine if individual-level and area-level socioeconomic status (SES) modifies the association of moderate-to-vigorous physical activity (MVPA), domain-specific physical activity and sedentary behaviour with all-cause mortality (ACM) and incident cardiovascular...

Socioeconomic status and metabolic syndrome in Southwest Iran: results from Hoveyzeh Cohort Study (HCS)

BackgroundSocioeconomic status (SES) strongly predicts morbidity and premature mortality, especially for non-communicable diseases (NCDs). However, the effect of these factors on Metabolic Syndrome (MetS) is not clear yet. This study was conducted to assess the relationship between socioeconomic indicators and MetS.MethodsIn this prospective cohort study, 10,009 people aged 35–70 enrolled from May 2016 to August 2018. The MetS was defined according to The Standard National Cholesterol Education Program (NCEP)—adult treatment panel III (ATP III) or NCEP-ATP III criteria. Demographics and socioeconomic data were gathered face-to-face through trained interviews. Also, lab, anthropometrics, and blood pressure measurements were assayed for participants. Logistic regression was used to estimate the association between SES and MetS, adjusted for the potential confounding factors.ResultsThe overall prevalence of MetS in the participants was 39.1%. The crude odds ratios were statistically significant for all the assessed variables (p < 0.05). After adjustment for age, sex, physical activity, smoking, and alcohol use as potential confounders, the results indicated significant direct independent associations between skill level (p = 0.006) and Townsend index (p = 0.002) with MetS. In contrast, no significant associations between educational level and wealth status with MetS.ConclusionThe results of our study showed that SES is related to MetS. Among the four assessed SES indicators, skilled levels and Townsend score are strongly associated with MetS. We recommend considering people's SES when interventional programs are planned and conducted on MetS in similar communities.

Advanced diffusion‐weighted MRI sensitively detects age and sex effects in 34,423 adults

AbstractBackgroundAging and Alzheimer’s disease (AD) are associated with alterations in the brain’s white matter (WM) microstructure. AD also exhibits significant sex differences and, similar to age, sex has also been associated with WM microstructural variability. A comprehensive characterization of how aging and sex impact WM microstructure may thus improve our understanding of processes involved in AD. Here we examined age and sex effects on traditional and advanced measures of WM microstructure in middle‐ to older‐aged adults.MethodCross‐sectional diffusion‐weighted MRI (dMRI) scans were analyzed from 34,423 UK Biobank participants (aged 45‐80 years; 53% female) using single‐shell models (DTI, TDF), and advanced multi‐shell models (NODDI, MAP). Metrics were projected to a standard WM skeleton using publicly available ENIGMA protocols, based on TBSS (FSL). Mean values for each dMRI metric were extracted from the whole WM skeleton, and age was modeled using fractional polynomial regressions, co‐varying for years of education, waist/hip ratio, population structure, and the Townsend index. Sex‐stratified centile curves were created for each dMRI metric to provide normative reference charts.ResultWM microstructure across the brain was significantly associated with participants’ age and sex for all dMRI models (main effects, ps&lt;.001). Increasing age in our cross‐sectional sample was associated with lower anisotropy (DTI‐FA, TDF‐FA), neurite density (NODDI‐ICVF, MAP‐RTOP, MAPMRI‐RTAP), and restriction (MAP‐RTPP) as well as higher diffusivity (DTI‐AxD, DTI‐MD, DTI‐RD), free water (NODDI‐ISOVF), and white matter dispersion (NODDI‐OD) for both males and females (Figures 1 and 2). Some metrics showed a gentle decline until around age 60, followed by a precipitous decline thereafter (e.g., TDF‐FA, NODDI‐ICVF, MAP‐RTAP, Figures 1 and 2). Significant sex differences in aging were most sensitively detected by the advanced dMRI multi‐shell models NODDI and MAPMRI (age‐by‐sex interaction; males showing a steeper trajectory for NODDI‐OD, p&lt;.001, females showing a steeper trajectory for MAPMRI‐RTPP, p&lt;.01, with age).ConclusionParticipant age and sex are significantly associated with the brain’s WM microstructure; advanced dMRI models displayed the greatest sensitivity, strenghtening previous findings in a smaller UKB sample (15k). Along with our calculated centile curves, we offer an important normative reference to guide future studies of Alzheimer’s disease.

Which combinations of health behaviours are associated with highest risk? An exploration of the UK Biobank population cohort

BackgroundCombinations of unhealthy behaviours are associated with greater mortality than single behaviours, but some combinations might have stronger associations than others. High-risk combinations might be more prevalent among socioeconomically deprived populations. We examined associations between combinations of 11 unhealthy behaviours and mortality and explored socioeconomic distributions of high-risk combinations. MethodsWe used the UK Biobank population cohort (n=502 459; aged 37–73 years) recruited between 2006 and 2010. Analysis included 229 197 participants with complete data. Main exposures were any combination of smoking, alcohol, physical activity, television time, sleep, added salt, social isolation, intake of red meat, processed meat, oily fish, and fruit and vegetables (each classified as healthy or unhealthy via guidelines or latest evidence). Townsend index was used to explore socioeconomic distribution. Cox proportional hazard models were used to examine associations between behaviours and all-cause mortality. Models were adjusted for demographic, health, and socioeconomic factors. FindingsOver a median follow-up of 11·6 years, 9739 (4·2%) of 229 197 participants died. From 716 unique combinations, 77 (11%) were associated with mortality with hazard ratios (HRs) greater than that for smoking alone (2·31 [95% CI 2·11–2·53]); HRs ranged from 9·44 to 2·34. Of these 77 high-risk combinations, smoking featured in 61 (79%), low fruit and vegetables in 45 (58%), and low oily fish in 41 (53%). All combinations featuring social isolation (18 [23%] of 77) had HRs greater than 3·00. Participants with high-risk combinations had greater deprivation scores than those with no unhealthy behaviours. Median deprivation scores of the ten highest risk combinations ranged from –2·0 to 2·1, whereas for participants with no unhealthy behaviours the score was –2·5. Examining women and men separately resulted in similar findings. Examination of ethnic differences was severely limited by small numbers of participants in minority ethnic groups. InterpretationMany unique unhealthy behaviour combinations are strongly associated with mortality and high-risk combinations are more prevalent among more deprived populations than among more affluent populations. Exploring unique combinations of a wide range of health behaviours can identify high-risk populations. Future work with adequately sampled minority ethnic groups is required to examine high-risk combinations by ethnicity. Supporting healthy living in deprived populations, including tackling structural barriers to health, could address a wide range of health behaviours in combination. FundingUK Medical Research Council.

Association of Visual Health With Depressive Symptoms and Brain Imaging Phenotypes Among Middle-Aged and Older Adults

Vision loss and depression are common conditions with major health implications. However, mechanisms of the association of visual health (across the full acuity spectrum) with depression remain unclear. To characterize the association between visual health and depression and investigate the association between depression and brain microstructure and macrostructure in subgroups divided by visual acuity. In the UK Biobank Study cohort, 114 583 volunteers were included at baseline from March to June 2006 to July 2010. Habitual distance visual acuity was examined using the logarithm of the minimum angle of resolution (LogMAR) characters. Depression was identified based on Patient Health Questionnaire (PHQ) or through an interview-based psychiatric diagnosis. Subgroup participants completed multimodal magnetic resonance imaging (MRI) of the brain and PHQ evaluation during the imaging visit after 2014. Data were analyzed from May 5 to August 9, 2022. Depression, depressive symptoms, and imaging-derived phenotypes from T1-weighted and diffusion MRI. Of the 114 583 participants from the UK Biobank Study, 62 401 (54.5%) were women, and the mean (SD) age was 56.8 (8.1) years (range, 39-72 years). A 1-line worse visual acuity (0.1 LogMAR increase) was associated with 5% higher odds of depression (odds ratio, 1.05 [95% CI, 1.04-1.07]) after adjustment for age, sex, race and ethnicity, Townsend index, educational qualifications, smoking, alcohol consumption, obesity, physical activity, history of hypertension, diabetes, hyperlipidemia, and family history of depression. Of the 7844 participants eligible for MRI analysis, there were linear associations between PHQ score and the left volume of gray matter in supracalcarine cortex (coefficient, 7.61 [95% CI, 3.90-11.31]) and mean isotropic volume fraction (ISOVF) in the right fornix (cres) and/or stria terminalis (coefficient, 0.003 [95% CI, 0.001-0.004]) after correction for multiple comparison. In addition, their association could be moderated by visual acuity, whereby increased PHQ score was associated with higher ISOVF levels only among those with poorer visual acuity (P = .02 for interaction). This study suggests an association between visual health and depression and that the diffusion characteristic of ISOVF in the fornix (cres) and/or stria terminalis is associated with depressive symptoms in participants with poorer visual acuity.

Foveal Curvature and Its Associations in UK Biobank Participants.

PurposeTo examine whether sociodemographic, and ocular factors relate to optical coherence tomography (OCT)–derived foveal curvature (FC) in healthy individuals.MethodsWe developed a deep learning model to quantify OCT-derived FC from 63,939 participants (age range, 39–70 years). Associations of FC with sociodemographic, and ocular factors were obtained using multilevel regression analysis (to allow for right and left eyes) adjusting for age, sex, ethnicity, height (model 1), visual acuity, spherical equivalent, corneal astigmatism, center point retinal thickness (CPRT), intraocular pressure (model 2), deprivation (Townsend index), higher education, annual income, and birth order (model 3). Fovea curvature was modeled as a z-score.ResultsMales had on average steeper FC (0.077; 95% confidence interval [CI] 0.077–0.078) than females (0.068; 95% CI 0.068–0.069). Compared with whites, non-white individuals showed flatter FC, particularly those of black ethnicity. In black males, −0.80 standard deviation (SD) change when compared with whites (95% CI −0.89, −0.71; P 5.2e10−68). In black females, −0.70 SD change when compared with whites (95% CI −0.77, −0.63; p 2.3e10−93). Ocular factors (visual acuity, refractive status, and CPRT) showed a graded inverse association with FC that persisted after adjustment. Macular curvature showed a positive association with FC. Income showed a linear trend increase in males (P for linear trend = 0.005).ConclusionsWe demonstrate marked differences in FC with ethnicity on the largest cohort studied for this purpose to date. Ocular factors showed a graded association with FC. Implementation of FC quantification in research and on the clinical setting can enhance the understanding of clinical macular phenotypes in health and disease.

The Risk Factors Potentially Influencing Hospital Admission in People with Diabetes, Following SARS-CoV-2 Infection: A Population-Level Analysis.

IntroductionSince early 2020 the whole world has been challenged by the SARS-CoV-2 virus and the associated global pandemic (Covid-19). People with diabetes are particularly at high risk of becoming seriously unwell after contracting this virus.MethodsThis population-based study included people living in the Greater Manchester conurbation who had a recorded diagnosis of type 1 diabetes mellitus (T1DM) or type 2 diabetes mellitus (T2DM) and subsequent Covid-19 infection. Each individual with T1DM (n = 862) or T2DM (n = 13,225) was matched with three Covid-19-infected non-diabetes controls.ResultsFor individuals with T1DM, hospital admission rate in the first 28 days after a positive Covid-19 test was 10% vs 4.7% in age/gender-matched controls [relative risk (RR) 2.1]. For individuals with T2DM, hospital admission rate after a positive Covid-19 test was 16.3% vs 11.6% in age/gender-matched controls (RR 1.4). The average Townsend score was higher in T2DM (1.8) vs matched controls (0.4), with a higher proportion of people with T2DM observed in the top two quintiles of greatest disadvantage (p < 0.001). For Covid-19-infected individuals with T1DM, factors influencing admission likelihood included age, body mass index (BMI), hypertension, HbA1c, low HDL-cholesterol, lower estimated glomerular filtration rate (eGFR), chronic obstructive pulmonary disease (COPD) and being of African/mixed ethnicity. In Covid-19-infected individuals with T2DM, factors related to a higher admission rate included age, Townsend index, comorbidity with COPD/asthma and severe mental illness (SMI), lower eGFR. Metformin prescription lowered the likelihood. For multivariate analysis in combined individuals with T2DM/controls, factors relating to higher likelihood of admission were having T2DM/age/male gender/diagnosed COPD/diagnosed hypertension/social deprivation (higher Townsend index) and non-white ethnicity (all groups).ConclusionIn a UK population we have confirmed a significantly higher likelihood of admission in people with diabetes following Covid-19 infection. A number of factors mediate that increased likelihood of hospital admission. For T2DM, the majority of factors related to increased admission rate are common to the general population but more prevalent in T2DM. There was a protective effect of metformin in people with T2DM.

Age effects on white matter microstructure in individuals of self‐identified Indian ancestry from the UK Biobank

AbstractBackgroundThe incidence of dementia in India is 14%, and its prevalence doubles with every five‐year increase in age. Given the lack of ethnic diversity in most brain research to date, it is valuable to study cohorts with diverse genetic and environmental backgrounds, to identify predictors of health and disease that can be generalized to other ethnic groups than the commonly studied populations of European ancestry. To address this gap in the literature, we modeled factors that affect aging patterns in the brain’s white matter in individuals with Indian ancestry using advanced diffusion‐weighted MRI (dMRI).MethodCross‐sectional dMRI data from 123 individuals (males, n=78; females, n=45) of self‐reported Indian ancestry (born in India: 44%; mean age: 60.1±8.3 SD, range: 45‐80) from the UK Biobank were analyzed using diffusion tensor imaging (DTI), the tensor distribution function (TDF), neurite orientation dispersion and density imaging (NODDI) and mean apparent propagator MRI (MAPMRI). Main effects of age, sex, and age‐by‐sex interaction were investigated to characterize trajectories in whole‐brain white matter averages and the corpus callosum (CC), parcellated using the JHU‐ICBM atlas, covarying for years of education, waist/hip ratio, population structure (Figure 1) and the Townsend index. Normative lifespan charts were created to visualize white matter aging trajectories for the major diffusivity metrics.ResultNormative centile curves (Figures 2‐3) show, with increasing age, declining white matter integrity, increased diffusivity, lower white matter density and diffusion restriction at the whole‐brain level and CC (Table 1; Figure 4). There was no detectable effect of sex, nor age‐by‐sex interaction, across whole‐brain metrics. In the CC, a steeper aging trajectory, evidenced by more pronounced white matter changes, was observed in males relative to females (Table 1; Figure 5).ConclusionUsing advanced dMRI modeling, we report diffuse white matter changes with respect to age in a subsample of UK Biobank individuals of self‐reported Indian ancestry. Future studies should include larger sample sizes, comparisons with Indian ancestry individuals residing in India, consider vascular factors, and examine genotype interactions (e.g., with apolipoprotein E genotype), to further characterize risk factors and better understand brain aging in diverse populations with varied genetic and environmental backgrounds.

Abstract 11843: Population Effects of Clinical, Laboratory, and Genetic Risk Factors for Incident CAD: A Cohort Study in the UK Biobank

Background: Modifiable clinical risk factors are estimated to account for the majority of population attributable risk (PAR) for first myocardial infarction (MI). Hypothesis: Novel biomarkers and genetic factors additionally contribute to the risk for first MI. Methods: We determined incident coronary artery disease (CAD), defined as first-time MI or revascularization, in the UK Biobank. Exposures included laboratory (ApoB/A1, lipoprotein(a) [Lp(a)], C reactive protein [CRP]), genetic (CAD polygenic risk score [PRS], heterozygous familial hypercholesterolemia [HeFH]), and clinical (waist/hip ratio, hypertension, diabetes, diet, exercise, smoking, Townsend deprivation index) risk factors. We fitted multivariable logistic regression models with clinical risk factors alone, then added CAD PRS, HeFH, CRP and Lp(a). Results: Among 98 387 participants, 5 408 had incident CAD (5.5%). Compared to a model with clinical risk factors alone (PAR 82.3%, 95% CI 77.6-86.9%), adding novel biomarkers (Lp(a), CRP) and genetic risk raised total PAR to 89.0% (95% CI 86.4-91.5%). Novel risk factors Lp(a) &gt; 125 nmol/L (OR 1.22, PAR 2.5%), CRP &gt; 2.0 mg/L (OR 1.22, PAR 8.0%), HeFH (OR 1.52, PAR 0.1%), and high CAD PRS (OR 2.48 for top vs lowest decile, PAR 37.4%) were significantly associated with incident CAD controlling for clinical risk factors. In combination with novel risk factors, smoking (OR 1.25 for current + former vs never, PAR 11.3%), ApoB/A1 ratio (OR 1.60 for top vs lowest quintile, PAR 16.6%), hypertension (OR 2.17, PAR 31.9%), waist-to-hip ratio (OR 1.21 for top vs lowest tertile, PAR 13.3%), diabetes (OR 1.59, PAR 5.6%), diet (OR 1.42, PAR 7.8%), exercise (OR 1.12, PAR 7.1%) and Townsend index (OR 1.34 for top vs lowest decile, PAR 8.6%) were significantly associated with incident CAD at α=0.05. Conclusions: The novel cardiovascular risk factors Lp(a), CRP, CAD PRS, and HeFH contribute significant risk for first-time CAD, with PAR for CAD PRS exceeding conventional risk factors.

The Inequality of Sleep Quality: Social Deprivation and Ethnicity Affect the Sleep Quality of Middle Aged and Older Adults

Background: Duration and other sleep characteristics change as we age. The effects of other demographics on sleep are less clear, although US studies suggest that sleep disorders and duration are influenced by social deprivation and race. Here we use UK Biobank data from almost half-a million adults living in Britain to test the hypothesis that sleep quality shows a ‘social gradient’ in sleep. Methods: Data for this prospective analysis were sourced from the UK Biobank. These consisted of self-reports relating to sleep (duration, waking in the night, sleeping in the day, difficulty waking and snoring), personal wealth (household income, property owning etc), ethnic group, employment and education, as well as post-code-based Townsend indices of social deprivation from c0.5m adults aged 40-70 years. Analyses considered prevalence of each sleep characteristic, and a Positive Sleep Index was derived by combining sleep-related responses. Findings: Almost one-third of participants reported sleeping shorter (24.7%) or longer (7.7%) than age-corrected recommended sleep durations, with the incidence of shorter or longer sleep increasing with social deprivation and varying with ethnicity. Snoring, waking during the night, finding it difficult to get up in the morning and sleeping in the daytime, were subject to similar effects. Regression analyses of our Positive Sleep Index showed that being younger, male, employed, owning one’s home, having a higher household income, higher level of educational achievement and time in education, were all associated with better sleep, as were living in a more affluent area and being white. Interpretation: Sleep quality in the UK shows a social gradient, independently of a range of other demographic and social influences. These sleep inequalities suggest that the protective and recuperative effects of sleep may be disproportionately distributed across the UK and should encourage us to consider the potential benefits of community specific sleep interventions. Funding Information: Funds received from Unilever UK Central Resources Limited to cover application fees, no other funding supported this research. Declaration of Interests: JAG has received research funding, consultancy, travel support, and speaking fees from various industrial companies. PH is employed by Unilever UK Central Resources Limited. Ethics Approval Statement: This retrospective cohort study is based on data from the UKB study that was approved by the North West Multi-Centre Research Ethics Committee; participants provided written informed consent for data collection, data analysis, and record linkage. Re-analysis of UKB data is part of UK Biobank project (NHS National Research Ethics Service 16/NW/0274).

Socioeconomic Deprivation and Genetic Ancestry Interact to Modify Type 2 Diabetes Ethnic Disparities in the United Kingdom

Background: Type 2 diabetes (T2D) is a complex common disease that disproportionately impacts minority ethnic groups in the United Kingdom (UK). Socioeconomic deprivation (SED) is widely considered to be a risk factor for T2D ethnic disparities in the UK, whereas the effect of genetic ancestry (GA) on such disparities has yet to be studied. Methods: We leveraged data from the UK Biobank to model the relationship between SED (Townsend index), GA (clustering principal components of whole genome genotype data), and T2D status (ICD-10 codes) across the three largest ethnic groups in the UK – Asian, Black, and White. Findings: The Asian group shows the highest T2D prevalence (17·9%), followed by the Black (11·7%) and White (5·5%) ethnic groups. We find that both SED (OR: 1·11, 95% CI: 1·10-1·11) and non-European GA (OR South Asian versus European: 4·37, 95% CI: 4·10-4·66; OR African versus European: 2·52, 95% CI: 2·23-2·85) are significantly associated with the observed T2D disparities, with GA showing a stronger effect than SED in the overall population. GA and SED show significant interaction effects on T2D, with SED being a greater risk factor for T2D for individuals with South Asian and African ancestry, compared to those with European ancestry. Interpretation: The significant interaction between SED and GA underscore how the effects of environmental risk factors can differ among ancestry groups, suggesting the need for group-specific interventions. Funding: Applied Bioinformatics Laboratory. National Institutes of Health (NIH) Distinguished Scholars Program, Division of Intramural Research, National Institute on Minority Health and Health Disparities. Declaration of Interests: The author have no competing interests.