Dietary patterns obtained through principal components analysis: The effect of input variable quantification

Principal components analysis (PCA) is a popular method for deriving dietary patterns. A number of decisions must be made throughout the analytic process, including how to quantify the input variables of the PCA. The present study aims to compare the effect of using different input variables on the patterns extracted using PCA on 3-d diet diary data collected from 7473 children, aged 10 years, in the Avon Longitudinal Study of Parents and Children. Four options were examined: weight consumed of each food group (g/d), energy-adjusted weight, percentage contribution to energy of each food group and binary intake (consumed/not consumed). Four separate PCA were performed, one for each intake measurement. Three or four dietary patterns were obtained from each analysis, with at least one component that described 'more healthy' and 'less healthy' diets and one component that described a diet with high consumption of meat, potatoes and vegetables. There were no obvious differences between the patterns derived using percentage energy as a measurement and adjusting weight for total energy intake, compared to those derived using gram weights. Using binary input variables yielded a component that loaded positively on reduced fat and reduced sugar foods. The present results suggest that food intakes quantified by gram weights or as binary variables both resulted in meaningful dietary patterns and each method has distinct advantages: weight takes into account the amount of each food consumed and binary intake appears to describe general food preferences, which are potentially easier to modify and useful in public health settings. © 2012 The Authors

Comparative Metabolite Fingerprinting of the Rumen System during Colonisation of Three Forage Grass (Lolium perenne L.) Varieties

The rumen microbiota enable ruminants to degrade complex ligno-cellulosic compounds to produce high quality protein for human consumption. However, enteric fermentation by domestic ruminants generates negative by-products: greenhouse gases (methane) and environmental nitrogen pollution. The current lack of cultured isolates representative of the totality of rumen microbial species creates an information gap about the in vivo function of the rumen microbiota and limits our ability to apply predictive biology for improvement of feed for ruminants. In this work we took a whole ecosystem approach to understanding how the metabolism of the microbial population responds to introduction of its substrate. Fourier Transform Infra Red (FTIR) spectroscopy-based metabolite fingerprinting was used to discriminate differences in the plant-microbial interactome of the rumen when using three forage grass varieties (Lolium perenne L. cv AberDart, AberMagic and Premium) as substrates for microbial colonisation and fermentation. Specific examination of spectral regions associated with fatty acids, amides, sugars and alkanes indicated that although the three forages were apparently similar by traditional nutritional analysis, patterns of metabolite flux within the plant-microbial interactome were distinct and plant genotype dependent. Thus, the utilisation pattern of forage nutrients by the rumen microbiota can be influenced by subtleties determined by forage genotypes. These data suggest that our interactomic approach represents an important means to improve forages and ultimately the livestock environment

Longitudinal comparisons of dietary patterns derived by cluster analysis in 7- to 13-year-old children

Little is known about changes in dietary patterns over time. The present study aims to derive dietary patterns using cluster analysis at three ages in children and track these patterns over time. In all, 3 d diet diaries were completed for children from the Avon Longitudinal Study of Parents and Children at 7, 10 and 13 years. Children were grouped based on the similarities between average weight consumed (g/d) of sixty-two food groups using k-means cluster analysis. A total of four clusters were obtained at each age, with very similar patterns being described at each time point: Processed (high consumption of processed foods, chips and soft drinks), Healthy (high consumption of high-fibre bread, fruit, vegetables and water), Traditional (high consumption of meat, potatoes and vegetables) and Packed Lunch (high consumption of white bread, sandwich fillings and snacks). The number of children remaining in the same cluster at different ages was reasonably high: 50 and 43 % of children in the Healthy and Processed clusters, respectively, at age 7 years were in the same clusters at age 13 years. Maternal education was the strongest predictor of remaining in the Healthy cluster at each time point – children whose mothers had the highest level of education were nine times more likely to remain in that cluster compared to those with the lowest. Cluster analysis provides a simple way of examining changes in dietary patterns over time, and similar underlying patterns of diet at two ages during late childhood, that persisted through to early adolescence

Dietary patterns and changes in body composition in children between 9 and 11 years

Objective: Childhood obesity is rising and dietary intake is a potentially modifiable factor that plays an important role in its development. We aim to investigate the association between dietary patterns, obtained through principal components analysis and gains in fat and lean mass in childhood. Design : Diet diaries at 10 years of age collected from children taking part in the Avon Longitudinal Study of Parents and Children. Body composition was assessed using dual-energy X-ray absorptiometry at 9 and 11. Setting: Longitudinal birth cohort. Subjects: 3911 children with complete data. Results: There was an association between the Health Aware (positive loadings on high-fiber bread, and fruits and vegetables; negative loadings on chips, crisps, processed meat, and soft drinks) pattern score and decreased fat mass gain in girls. After adjusting for confounders, an increase of 1 standard deviation (sd) in this score led to an estimated 1.2% decrease in fat mass gain in valid-reporters and 2.1% in under-reporters. A similar decrease was found only in under-reporting boys. There was also an association between the Packed Lunch (high consumption of white bread, sandwich fillings, and snacks) pattern score and decreased fat mass gain (1.1% per sd) in valid-reporting but not under-reporting girls. The main association with lean mass gain was an increase with Packed Lunch pattern score in valid-reporting boys only. Conclusions: There is a small association between dietary patterns and change in fat mass in mid-childhood. Differences between under- and valid-reporters emphasize the need to consider valid-reporters separately in such studies. © 2014 Andrew D. A. C. Smith et al

Multiplex ligation-dependent probe amplification (MLPA) analysis is an effective tool for the detection of novel intragenic PLA2G6 mutations: Implications for molecular diagnosis

Phospholipase associated neurodegeneration (PLAN) comprises a heterogeneous group of autosomal recessive neurological disorders caused by mutations in the PLA2G6 gene. Direct gene sequencing detects 85% mutations in infantile neuroaxonal dystrophy. We report the novel use of multiplex ligation-dependent probe amplification (MLPA) analysis to detect novel PLA2G6 duplications and deletions. The identification of such copy number variants (CNVs) expands the PLAN mutation spectrum and may account for up to 12.5% of PLA2G6 mutations. MLPA should thus be employed to detect CNVs of PLA2G6 in patients who show clinical features of PLAN but in whom both disease-causing mutations cannot be identified on routine sequencin

Diagnosing Patients with Age-Related Hearing Loss and Tinnitus: Supporting GP Clinical Engagement through Innovation and Pathway Redesign in Audiology Services

The public health challenge of hearing impairment is growing, as age is the major determinant of hearing loss. Almost one in four (22.6%) over 75-year olds reports moderate or severe worry because of hearing problems. There is a 40% comorbidity of tinnitus and balance disorders. Good outcomes depend on early presentation and appropriate referral. This paper describes how the NHS Improvement Programme in England used service improvement methodologies to identify referral pathways and tools which were most likely to make significant improvements in diagnosing hearing loss, effective referrals and better patient outcomes. An audiometric screening device was used in GP surgeries to enable thresholds for effective referrals to be measured in the surgery. Revised referral criteria, the use of this device, new “assess and fit” technology in the audiology clinic, and direct access pathways can transform audiology service delivery so that patient outcomes are measurably better. This, in turn, changes the experience of GPs, so they are more likely to refer patients who can benefit from treatment. At the end of 2011, 51 GP practices in one of the audiology pilot areas had bought HearCheck screeners, a substantial development from the 4 practices who first engaged with the pilot

Protocol for the development of guidance for stakeholder engagement in health and healthcare guideline development and implementation

Stakeholder engagement has become widely accepted as a necessary component of guideline development and implementation. While frameworks for developing guidelines express the need for those potentially affected by guideline recommendations to be involved in their development, there is a lack of consensus on how this should be done in practice. Further, there is a lack of guidance on how to equitably and meaningfully engage multiple stakeholders. We aim to develop guidance for the meaningful and equitable engagement of multiple stakeholders in guideline development and implementation. METHODS: This will be a multi-stage project. The first stage is to conduct a series of four systematic reviews. These will (1) describe existing guidance and methods for stakeholder engagement in guideline development and implementation, (2) characterize barriers and facilitators to stakeholder engagement in guideline development and implementation, (3) explore the impact of stakeholder engagement on guideline development and implementation, and (4) identify issues related to conflicts of interest when engaging multiple stakeholders in guideline development and implementation. DISCUSSION: We will collaborate with our multiple and diverse stakeholders to develop guidance for multi-stakeholder engagement in guideline development and implementation. We will use the results of the systematic reviews to develop a candidate list of draft guidance recommendations and will seek broad feedback on the draft guidance via an online survey of guideline developers and external stakeholders. An invited group of representatives from all stakeholder groups will discuss the results of the survey at a consensus meeting which will inform the development of the final guidance papers. Our overall goal is to improve the development of guidelines through meaningful and equitable multi-stakeholder engagement, and subsequently to improve health outcomes and reduce inequities in health