Summary Background Systemic lupus erythematosus is a heterogeneous autoimmune disease that is associated with B-cell hyperactivity, autoantibodies, and increased concentrations of B-lymphocyte ...stimulator (BLyS). The efficacy and safety of the fully human monoclonal antibody belimumab (BLyS-specific inhibitor) was assessed in patients with active systemic lupus erythematosus. Methods Patients (aged ≥18 years) who were seropositive with scores of at least 6 on the Safety of Estrogens in Lupus Erythematosus National Assessment–Systemic Lupus Erythematosus Disease Activity Index (SELENA-SLEDAI) were enrolled in a multicentre phase 3 study, which was done in Latin America, Asia-Pacific, and eastern Europe. Patients were randomly assigned by use of a central interactive voice response system in a 1:1:1 ratio to belimumab 1 mg/kg or 10 mg/kg, or placebo by intravenous infusion in 1 h on days 0, 14, and 28, and then every 28 days until 48 weeks, with standard of care. Patients, investigators, study coordinators, and sponsors were masked to treatment assignment. Primary efficacy endpoint was improvement in the Systemic Lupus Erythematosus Responder Index (SRI) at week 52 (reduction ≥4 points in SELENA-SLEDAI score; no new British Isles Lupus Assessment Group BILAG A organ domain score and no more than 1 new B organ domain score; and no worsening <0·3 increase in Physician's Global Assessment PGA score) versus baseline. Method of analysis was by modified intention to treat. This trial is registered with ClinicalTrials.gov , number NCT00424476. Findings 867 patients were randomly assigned to belimumab 1 mg/kg (n=289) or 10 mg/kg (n=290), or placebo (n=288). 865 were treated and analysed in the belimumab (1 mg/kg, n=288; 10 mg/kg, n=290) and placebo groups (n=287). Significantly higher SRI rates were noted with belimumab 1 mg/kg (148 51%, odds ratio 1·55 95% CI 1·10–2·19; p=0·0129) and 10 mg/kg (167 58%, 1·83 1·30–2·59; p=0·0006) than with placebo (125 44%) at week 52. More patients had their SELENA-SLEDAI score reduced by at least 4 points during 52 weeks with belimumab 1 mg/kg (153 53%, 1·51 1·07–2·14; p=0·0189) and 10 mg/kg (169 58%, 1·71 1·21–2·41; p=0·0024) than with placebo (132 46%). More patients given belimumab 1 mg/kg (226 78%, 1·38 0·93–2·04; p=0·1064) and 10 mg/kg (236 81%, 1·62 1·09–2·42; p=0·0181) had no new BILAG A or no more than 1 new B flare than did those in the placebo group (210 73%). No worsening in PGA score was noted in more patients with belimumab 1 mg/kg (227 79%, 1·68 1·15–2·47; p=0·0078) and 10 mg/kg (231 80%, 1·74 1·18–2·55; p=0·0048) than with placebo (199 69%). Rates of adverse events were similar in the groups given belimumab 1 mg/kg and 10 mg/kg, and placebo: serious infection was reported in 22 (8%), 13 (4%), and 17 (6%) patients, respectively, and severe or serious hypersensitivity reactions on an infusion day were reported in two (<1%), two (<1%), and no patients, respectively. No malignant diseases were reported. Interpretation Belimumab has the potential to be the first targeted biological treatment that is approved specifically for systemic lupus erythematosus, providing a new option for the management of this important prototypic autoimmune disease. Funding Human Genome Sciences and GlaxoSmithKline.
Summary Background Statins increase the risk of new-onset type 2 diabetes mellitus. We aimed to assess whether this increase in risk is a consequence of inhibition of 3-hydroxy-3-methylglutaryl-CoA ...reductase (HMGCR), the intended drug target. Methods We used single nucleotide polymorphisms in the HMGCR gene, rs17238484 (for the main analysis) and rs12916 (for a subsidiary analysis) as proxies for HMGCR inhibition by statins. We examined associations of these variants with plasma lipid, glucose, and insulin concentrations; bodyweight; waist circumference; and prevalent and incident type 2 diabetes. Study-specific effect estimates per copy of each LDL-lowering allele were pooled by meta-analysis. These findings were compared with a meta-analysis of new-onset type 2 diabetes and bodyweight change data from randomised trials of statin drugs. The effects of statins in each randomised trial were assessed using meta-analysis. Findings Data were available for up to 223 463 individuals from 43 genetic studies. Each additional rs17238484-G allele was associated with a mean 0·06 mmol/L (95% CI 0·05–0·07) lower LDL cholesterol and higher body weight (0·30 kg, 0·18–0·43), waist circumference (0·32 cm, 0·16–0·47), plasma insulin concentration (1·62%, 0·53–2·72), and plasma glucose concentration (0·23%, 0·02–0·44). The rs12916 SNP had similar effects on LDL cholesterol, bodyweight, and waist circumference. The rs17238484-G allele seemed to be associated with higher risk of type 2 diabetes (odds ratio OR per allele 1·02, 95% CI 1·00–1·05); the rs12916-T allele association was consistent (1·06, 1·03–1·09). In 129 170 individuals in randomised trials, statins lowered LDL cholesterol by 0·92 mmol/L (95% CI 0·18–1·67) at 1-year of follow-up, increased bodyweight by 0·24 kg (95% CI 0·10–0·38 in all trials; 0·33 kg, 95% CI 0·24–0·42 in placebo or standard care controlled trials and −0·15 kg, 95% CI −0·39 to 0·08 in intensive-dose vs moderate-dose trials) at a mean of 4·2 years (range 1·9–6·7) of follow-up, and increased the odds of new-onset type 2 diabetes (OR 1·12, 95% CI 1·06–1·18 in all trials; 1·11, 95% CI 1·03–1·20 in placebo or standard care controlled trials and 1·12, 95% CI 1·04–1·22 in intensive-dose vs moderate dose trials). Interpretation The increased risk of type 2 diabetes noted with statins is at least partially explained by HMGCR inhibition. Funding The funding sources are cited at the end of the paper.
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.
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.
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.
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.
University of Hong Kong, UK Biobank, and UK Economic & Social Research Council.
Increased urbanisation and the associated reduced contact of individuals with natural environments have led to a rise in mental disorders, including depression. Residential greenness, a fundamental ...component of urban design, has been shown to reduce the public health burden of mental disorders. The present study investigates the association between residential green exposure and prevalence of major depressive disorders using a large and diverse cross-sectional dataset from the UK Biobank.
In this cross-sectional, observational, associational study, we used baseline data from the UK Biobank cohort of participants aged 37–73 years from across the UK. Environmental exposure data were derived from a modelled and linked built environment database. Residential greenness was assessed with a 0·5 m resolution Normalised Difference Vegetation Index, which is derived from spectral reflectance measurements in remotely sensed colour infrared data and measured within geocoded dwelling catchments. Other environment metrics included street-level movement density, terrain, and fine particulate exposures. A series of logistic models examined associations between residential greenness and odds of major depressive disorder after adjusting for activity-influencing environments and individual covariates.
Of 122 993 participants with data on major depressive disorder, the study analytical sample comprised 94 879 (77·1%) participants recruited across ten UK Biobank assessment centres between April 29, 2009, and Oct 1, 2010. A protective effect of greenness on depression was consistently observed, with 4·0% lower odds of major depressive disorder per interquartile increment in Normalised Difference Vegetation Index greenness (odds ratio 0·960, 95% CI 0·93–0·99; p=0·0044). Interaction analyses indicated that the beneficial effects of greenness were more pronounced among women, participants younger than 60 years, and participants residing in areas with low neighbourhood socioeconomic status or high urbanicity.
The results point to the benefits of well designed green environments on mental health. Further longitudinal studies are needed to decipher causal pathways. In the UK, policies aimed at optimising allocation and design of green spaces might help preserve psychological ecosystem services, thereby, improving the mental wellbeing of populations and enhancing the mental capital of cities.
University of Hong Kong, UK Biobank, and the UK Economic & Social Research Council.
The role of environmental exposures in chronic obstructive pulmonary disease (COPD) remains inconclusive. We examined the association between environmental exposures (PM2·5, greenness, and ...urbanicity) and COPD prevalence using the UK Biobank cohort data to identify key built environment correlates of COPD.
In this cross-sectional, observational study we used baseline data for UK Biobank participants. Included participants were aged 39 years and older, white, had available spirometry data, and had complete data for phenotypes and exposures. COPD was defined by spirometry with the 2017 Global Initiative for Chronic Obstructive Lung Disease criteria. Environmental exposures were PM2·5 derived from monitoring data and interpolated using land-use regression at the participants' geocoded residential addresses. Built environment metrics of residential greenness were modelled in terms of normalised difference vegetation index from remotely sensed colour infrared data within a 500 m residential catchment, and an urbanicity index derived from spatial analyses and measured with a 1 km buffer around each participant's residential address. Logistic regression models examined the associations between environmental exposures and COPD prevalence adjusting for a range of confounders. Subgroup analyses by urbanicity and effect modification by white blood cell count as an inflammatory marker were also done.
We assessed 96 779 participants recruited between April 4, 2006, and Oct 1, 2010, of which 5391 participants had COPD with a prevalence of 5·6%. Each 10 μg/m3 increment in ambient PM2·5 exposure at a participant's residential location was associated with higher odds of COPD (odds ratio 1·55, 95% CI 1·14–2·10). Among the built environment metrics, urbanicity was associated with higher odds of COPD (1·05, 1·01–1·08 per interquartile increment), whereas residential greenness was protective, being associated with lower odds of COPD (0·89, 0·84–0·93 for each interquartile increment in greenness). The results remained consistent in models of COPD defined as per lower limit of normal criteria. The highest quartile of white blood cell count was associated with lower lung function and higher COPD risk with a significant interaction between PM2·5 and white blood cell count only in the model of lung function (p=0·0003).
In this study of the built environment and COPD, to our knowledge the largest done in the UK, we found that exposure to ambient PM2·5 and urbanicity were associated with a higher risk of COPD. Residing in greener areas, as measured by normalised difference vegetation index, was associated with lower odds of COPD, suggesting the potential value of urban planning and design in minimising or offsetting environmental risks for the prevention and management of COPD.
University of Hong Kong, UK Biobank, and UK Economic & Social Research Council.
Rapid urbanisation and associated socioeconomic transformations have modified current lifestyles, shifting dietary preferences towards ready-to-eat, calorie-dense food of poor nutritional quality. ...The effect of ready-to-eat food environments that sell food for instant consumption on the risk of type 2 diabetes has received scant attention. We therefore aimed to examine the association between exposure to ready-to-eat food environments and type 2 diabetes in a large and diverse population sample.
We conducted a cross-sectional study of adult male and female participants from the baseline phase of the UK Biobank cohort. Participants in this cohort were aged 37–73 years and resided in one of 21 cities in the UK. Ready-to-eat food environments, which we determined from a modelled and linked built environment database, were objectively measured within 1-km catchment areas of the residential streets of participants and were expressed as metrics of density and proximity to the participants' homes. We used logistic regression models to examine the associations between exposure to ready-to-eat food environments and the odds of type 2 diabetes, adjusting for individual covariates such as physical activity. As sensitivity analyses, we investigated the associations between the street distance to the nearest ready-to-eat food outlet and type 2 diabetes. We also tested post hoc for effect modification by sex, income, body-mass index, and location of the UK Biobank collection centre.
Of 502 635 UK Biobank participants enrolled between March 13, 2006, and Oct 1, 2010, the sample analysed included 347 551 (69·1%) participants. The density of ready-to-eat food environments within a 1-km catchment area was associated with higher odds of type 2 diabetes for participants in the groups with highest exposure to restaurants and cafeterias (odss ratio 1·129, 95% CI 1·05–1·21; p=0·0007) and a composite measure of ready-to-eat outlet density (1·112, 1·02–1·21; p=0·0134) compared with those with no exposure. Exposure to hot and cold takeaways was only significantly associated with higher odds of type 2 diabetes at the second highest exposure category that we examined (1·076, 1·01–1·14; p=0·0171), representing a density of 0·75–2·15 units per km2. A protective effect with distance decay was observed: participants in the highest quintile of street distance to nearest ready-to-eat food outlet reported lower odds of type 2 diabetes than those in the lowest quintile (0·842, 0·78–0·91; p<0·0001 for restaurants and cafeterias; and 0·913, 0·85–0·98; p=0·0173 for hot and cold takeaways). These effects were most pronounced in overweight participants (p=0·0329), but there was no evidence of interaction by sex, income, or UK Biobank collection centre.
Access to ready-to-eat food environments was positively associated with type 2 diabetes. Top-down policies aimed at minimising unhealthy food access could potentially reduce unhealthy consumption and risks of chronic diseases. Further long-term studies are needed to effectively guide such interventions.
University of Hong Kong, UK Biobank, and UK Economic & Social Research Council.
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