Birthweight and risk markers for type 2 diabetes and cardiovascular disease in childhood: the Child Heart and Health Study in England (CHASE).

AIMS/HYPOTHESIS: Lower birthweight (a marker of fetal undernutrition) is associated with higher risks of type 2 diabetes and cardiovascular disease (CVD) and could explain ethnic differences in these diseases. We examined associations between birthweight and risk markers for diabetes and CVD in UK-resident white European, South Asian and black African-Caribbean children. METHODS: In a cross-sectional study of risk markers for diabetes and CVD in 9- to 10-year-old children of different ethnic origins, birthweight was obtained from health records and/or parental recall. Associations between birthweight and risk markers were estimated using multilevel linear regression to account for clustering in children from the same school. RESULTS: Key data were available for 3,744 (66%) singleton study participants. In analyses adjusted for age, sex and ethnicity, birthweight was inversely associated with serum urate and positively associated with systolic BP. After additional height adjustment, lower birthweight (per 100 g) was associated with higher serum urate (0.52%; 95% CI 0.38, 0.66), fasting serum insulin (0.41%; 95% CI 0.08, 0.74), HbA1c (0.04%; 95% CI 0.00, 0.08), plasma glucose (0.06%; 95% CI 0.02, 0.10) and serum triacylglycerol (0.30%; 95% CI 0.09, 0.51) but not with BP or blood cholesterol. Birthweight was lower among children of South Asian (231 g lower; 95% CI 183, 280) and black African-Caribbean origin (81 g lower; 95% CI 30, 132). However, adjustment for birthweight had no effect on ethnic differences in risk markers. CONCLUSIONS/INTERPRETATION: Birthweight was inversely associated with urate and with insulin and glycaemia after adjustment for current height. Lower birthweight does not appear to explain emerging ethnic difference in risk markers for diabetes

Study protocol: Insight 46 - a neuroscience sub-study of the MRC National Survey of Health and Development

BACKGROUND: Increasing age is the biggest risk factor for dementia, of which Alzheimer's disease is the commonest cause. The pathological changes underpinning Alzheimer's disease are thought to develop at least a decade prior to the onset of symptoms. Molecular positron emission tomography and multi-modal magnetic resonance imaging allow key pathological processes underpinning cognitive impairment - including β-amyloid depostion, vascular disease, network breakdown and atrophy - to be assessed repeatedly and non-invasively. This enables potential determinants of dementia to be delineated earlier, and therefore opens a pre-symptomatic window where intervention may prevent the onset of cognitive symptoms. METHODS/DESIGN: This paper outlines the clinical, cognitive and imaging protocol of "Insight 46", a neuroscience sub-study of the MRC National Survey of Health and Development. This is one of the oldest British birth cohort studies and has followed 5362 individuals since their birth in England, Scotland and Wales during one week in March 1946. These individuals have been tracked in 24 waves of data collection incorporating a wide range of health and functional measures, including repeat measures of cognitive function. Now aged 71 years, a small fraction have overt dementia, but estimates suggest that ~1/3 of individuals in this age group may be in the preclinical stages of Alzheimer's disease. Insight 46 is recruiting 500 study members selected at random from those who attended a clinical visit at 60-64 years and on whom relevant lifecourse data are available. We describe the sub-study design and protocol which involves a prospective two time-point (0, 24 month) data collection covering clinical, neuropsychological, β-amyloid positron emission tomography and magnetic resonance imaging, biomarker and genetic information. Data collection started in 2015 (age 69) and aims to be completed in 2019 (age 73). DISCUSSION: Through the integration of data on the socioeconomic environment and on physical, psychological and cognitive function from 0 to 69 years, coupled with genetics, structural and molecular imaging, and intensive cognitive and neurological phenotyping, Insight 46 aims to identify lifetime factors which influence brain health and cognitive ageing, with particular focus on Alzheimer's disease and cerebrovascular disease. This will provide an evidence base for the rational design of disease-modifying trials

A life course approach to injury prevention: a "lens and telescope" conceptual model

<p>Abstract</p> <p>Background</p> <p>Although life course epidemiology is increasingly employed to conceptualize the determinants of health, the implications of this approach for strategies to reduce the burden of injuries have received little recognition to date.</p> <p>Methods</p> <p>The authors reviewed core injury concepts and the principles of the life course approach. Based on this understanding, a conceptual model was developed, to provide a holistic view of the mechanisms that underlie the accumulation of injury risk and their consequences over the life course.</p> <p>Results</p> <p>A "lens and telescope" model is proposed that particularly draws on (a) the extended temporal dimension inherent in the life course approach, with links between exposures and outcomes that span many years, or even generations, and (b) an ecological perspective, according to which the contexts in which individuals live are critical, as are changes in those contexts over time.</p> <p>Conclusions</p> <p>By explicitly examining longer-term, intergenerational and ecological perspectives, life course concepts can inform and strengthen traditional approaches to injury prevention and control that have a strong focus on proximal factors. The model proposed also serves as a tool to identify intervention strategies that have co-benefits for other areas of health.</p

Mechanistic modelling of dynamic MRI data predicts that tumour heterogeneity decreases therapeutic response

Mechanistic modelling of dynamic MRI data predicts that tumour heterogeneity decreases therapeutic respons

University student engagement inventory (USEI): psychometric properties

Academic engagement describes students’ investment in academic learning and achievement and is an important indicator of students’ adjustment to university life, particularly in the first year. A tridimensional conceptualization of academic engagement has been accepted (behavioral, emotional and cognitive dimensions). This paper tests the dimensionality, internal consistency reliability and invariance of the University Student Engagement Inventory (USEI) taking into consideration both gender and the scientific area of graduation. A sample of 908 Portuguese first-year university students was considered. Good evidence of reliability has been obtained with ordinal alpha and omega values. Confirmatory factor analysis substantiates the theoretical dimensionality proposed (second-order latent factor), internal consistency reliability evidence indicates good values and the results suggest measurement invariance across gender and the area of graduation. The present study enhances the role of the USEI regarding the lack of consensus on the dimensionality and constructs delimitation of academic engagement.Jorge Sinval received funding from the William James Center for Research, Portuguese Science Foundation (FCT UID/PSI/04810/2013). Leandro S. Almeida and Joana R. Casanova received funding from CIEd – Research Centre on Education, projects UID/CED/1661/2013 and UID/CED/1661/2016, Institute of Education, University of Minho, through national funds of FCT/MCTES-PT. Joana R. Casanova received funding from the Portuguese Science Foundation (FCT) as a Doctoral Grant, under grant agreement number SFRH/BD/117902/2016.info:eu-repo/semantics/publishedVersio

Comparing population health in the United States and Canada

<p>Abstract</p> <p>Background</p> <p>The objective of the paper is to compare population health in the United States (US) and Canada. Although the two countries are very similar in many ways, there are potentially important differences in the levels of social and economic inequality and the organization and financing of and access to health care in the two countries.</p> <p>Methods</p> <p>Data are from the Joint Canada/United States Survey of Health 2002/03. The Health Utilities Index Mark 3 (HUI3) was used to measure overall health-related quality of life (HRQL). Mean HUI3 scores were compared, adjusting for major determinants of health, including body mass index, smoking, education, gender, race, and income. In addition, estimates of life expectancy were compared. Finally, mean HUI3 scores by age and gender and Canadian and US life tables were used to estimate health-adjusted life expectancy (HALE).</p> <p>Results</p> <p>Life expectancy in Canada is higher than in the US. For those < 40 years, there were no differences in HRQL between the US and Canada. For the 40+ group, HRQL appears to be higher in Canada. The results comparing the white-only population in both countries were very similar. For a 19-year-old, HALE was 52.0 years in Canada and 49.3 in the US.</p> <p>Conclusions</p> <p>The population of Canada appears to be substantially healthier than the US population with respect to life expectancy, HRQL, and HALE. Factors that account for the difference may include access to health care over the full life span (universal health insurance) and lower levels of social and economic inequality, especially among the elderly.</p

Measurement of the cross section for inclusive isolated-photon production in pp collisions at √s=13TeV using the ATLAS detector

Inclusive isolated-photon production in pp collisions at a centre-of-mass energy of 13TeVis studied with the ATLAS detector at the LHC using a data set with an integrated luminosity of 3.2fb−1. The cross section is measured as a function of the photon transverse energy above 125GeVin different regions of photon pseudorapidity. Next-to-leading-order perturbative QCD and Monte Carlo event-generator predictions are compared to the cross-section measurements and provide an adequate description of the data