British Nutrition Foundation Annual Lecture 2017 – Diet,obesity and cardiovascular risk

This paper provides a summary of the British Nutrition Foundation Annual Lecture by Professor Susan Jebb held at the Royal College of Physicians, London, on 14 November 2017. Professor Jebb, recipient of the 2016 British Nutrition Foundation Prize for outstanding achievement in the area of nutrition, spoke of her research on diet, obesity and cardiovascular disease (CVD) risk and her work to translate science into action to help improve the nation's diet. This paper briefly summarises her research, including analyses of the links between dietary patterns and cardiometabolic risk in prospective cohorts, mechanistic studies such as the effect of portion size on energy intake, a series of randomised controlled trials to test the impact of diet composition on markers of CVD risk, and clinical trials of interventions to treat obesity in primary healthcare settings. Professor Jebb emphasised the need to translate the considerable scientific knowledge about the prevention of CVD through modification of risk factors such as obesity, into systems embedded in routine practice and population‐level interventions, in order to improve public health and tackle health inequalities.     

A Census of Midsize to Large Supermarkets in Toronto: A Cross-Sectional Analysis of the Consumer Nutrition Environment

Objective

Assess the consumer nutrition environment in midsize to large supermarkets by supermarket type and area-level socioeconomic variables.

On the use of the not‐at‐random fully conditional specification (NARFCS) procedure in practice

The not‐at‐random fully conditional specification (NARFCS) procedure provides a flexible means for the imputation of multivariable missing data under missing‐not‐at‐random conditions. Recent work has outlined difficulties with eliciting the sensitivity parameters of the procedure from expert opinion due to their conditional nature. Failure to adequately account for this conditioning will generate imputations that are inconsistent with the assumptions of the user. In this paper, we clarify the importance of correct conditioning of NARFCS sensitivity parameters and develop procedures to calibrate these sensitivity parameters by relating them to more easily elicited quantities, in particular, the sensitivity parameters from simpler pattern mixture models. Additionally, we consider how to include the missingness indicators as part of the imputation models of NARFCS, recommending including all of them in each model as default practice. Algorithms are developed to perform the calibration procedure and demonstrated on data from the Avon Longitudinal Study of Parents and Children, as well as with simulation studies.     

A comparison of seven random‐effects models for meta‐analyses that estimate the summary odds ratio

Comparative trials that report binary outcome data are commonly pooled in systematic reviews and meta‐analyses. This type of data can be presented as a series of 2‐by‐2 tables. The pooled odds ratio is often presented as the outcome of primary interest in the resulting meta‐analysis. We examine the use of 7 models for random‐effects meta‐analyses that have been proposed for this purpose. The first of these models is the conventional one that uses normal within‐study approximations and a 2‐stage approach. The other models are generalised linear mixed models that perform the analysis in 1 stage and have the potential to provide more accurate inference. We explore the implications of using these 7 models in the context of a Cochrane Review, and we also perform a simulation study. We conclude that generalised linear mixed models can result in better statistical inference than the conventional 2‐stage approach but also that this type of model presents issues and difficulties. These challenges include more demanding numerical methods and determining the best way to model study specific baseline risks. One possible approach for analysts is to specify a primary model prior to performing the systematic review but also to present the results using other models in a sensitivity analysis. Only one of the models that we investigate is found to perform poorly so that any of the other models could be considered for either the primary or the sensitivity analysis.     

The combination of cardiorespiratory fitness and muscle strength,and mortality risk

Little is known about the combined associations of cardiorespiratory fitness (CRF) and hand grip strength (GS) with mortality in general adult populations. The purpose of this study was to compare the relative risk of mortality for CRF, GS, and their combination. In UK Biobank, a prospective cohort of >?0.5 million adults aged 40–69 years, CRF was measured through submaximal bike tests; GS was measured using a hand-dynamometer. This analysis is based on data from 70,913 men and women (832 all-cause, 177 cardiovascular and 503 cancer deaths over 5.7-year follow-up) who provided valid CRF and GS data, and with no history of heart attack/stroke/cancer at baseline. Compared with the lowest CRF category, the hazard ratio (HR) for all-cause mortality was 0.76 [95% confidence interval (CI) 0.64–0.89] and 0.65 (95% CI 0.55–0.78) for the middle and highest CRF categories, respectively, after adjustment for confounders and GS. The highest GS category had an HR of 0.79 (95% CI 0.66–0.95) for all-cause mortality compared with the lowest, after adjustment for confounders and CRF. Similar results were found for cardiovascular and cancer mortality. The HRs for the combination of highest CRF and GS were 0.53 (95% CI 0.39–0.72) for all-cause mortality and 0.31 (95% CI 0.14–0.67) for cardiovascular mortality, compared with the reference category of lowest CRF and GS: no significant association for cancer mortality (HR 0.70; 95% CI 0.48–1.02). CRF and GS are both independent predictors of mortality. Improving both CRF and muscle strength, as opposed to either of the two alone, may be the most effective behavioral strategy to reduce all-cause and cardiovascular mortality risk.     

Supporting nursing students with dyslexia in clinical practice

AIMS: To determine whether pre-registration nursing students with dyslexia experience specific problems in developing clinical competence, identify what strategies they use and how they may be supported in clinical practice. METHOD: Qualitative case study methodology was used. Stage 1 involved semi-structured interviews with seven students, three support and eight teaching staff, postal questionnaires from nine mentors, in addition to a review of policy documentation. Stage 2 involved a two-year study of four students on their branch programme and included semi-structured interviews with seven mentors. FINDINGS: The students' difficulties in clinical practice fell into three categories: dealing with information; performing the role; and administering drugs. Specific supporting measures included: informal and formal support networks; portable information technology equipment; and personal strategies, for example, rehearsing difficult tasks such as the handover report. The students' relationships with their mentors and the type of environment they were working in were key to the successful development of clinical competence. CONCLUSION: Nursing students who have dyslexia have specific learning difficulties in practice. Their response to these difficulties is individual and support needs to be tailored to meet their specific needs.