Investigation of the faecal microbiota of kittens: monitoring bacterial succession and effect of diet

Weaning is a stressful process for kittens, and is often associated with diarrhoea and the onset of infectious diseases. The gastrointestinal microbiota plays an essential role in host well-being, including improving homeostasis. Composition of the gastrointestinal microbiota of young cats is poorly understood, and the impact of diet on the kitten microbiota unknown. The aims of this study were to monitor the faecal microbiota of kittens and determine the effect(s) of diet on its composition. Bacterial succession was monitored in two groups of kittens (at 4 and 6 weeks, and 4 and 9 months of age) fed different foods. Age-related microbial changes revealed significantly different counts of total bacteria, lactic acid bacteria, Desulfovibrionales, Clostridium cluster IX and Bacteroidetes between 4-week- and 9-month-old kittens. Diet-associated differences in the faecal microbiota of the two feeding groups were evident. In general, fluorescence in situ hybridization analysis demonstrated bifidobacteria, Atopobium group, Clostridium cluster XIV and lactic acid bacteria were dominant in kittens. Denaturing gradient gel electrophoresis profiling showed highly complex and diverse faecal microbiotas for kittens, with age- and/or food-related changes seen in relation to species richness and similarity indices. Four-week-old kittens harboured more diverse and variable profiles than those of weaned kittens.

Selecting from amongst non–nested conditional variance models: information criteria and portfolio determination

We consider the finite sample properties of model selection by information criteria in conditionally heteroscedastic models. Recent theoretical results show that certain popular criteria are consistent in that they will select the true model asymptotically with probability 1. To examine the empirical relevance of this property, Monte Carlo simulations are conducted for a set of non–nested data generating processes (DGPs) with the set of candidate models consisting of all types of model used as DGPs. In addition, not only is the best model considered but also those with similar values of the information criterion, called close competitors, thus forming a portfolio of eligible models. To supplement the simulations, the criteria are applied to a set of economic and financial series. In the simulations, the criteria are largely ineffective at identifying the correct model, either as best or a close competitor, the parsimonious GARCH(1, 1) model being preferred for most DGPs. In contrast, asymmetric models are generally selected to represent actual data. This leads to the conjecture that the properties of parameterizations of processes commonly used to model heteroscedastic data are more similar than may be imagined and that more attention needs to be paid to the behaviour of the standardized disturbances of such models, both in simulation exercises and in empirical modelling.

Inequalities in diet and nutrition

The inequality of nutrition and obesity re-focuses concern on who in society is consuming the worst diet. Identification of individuals with the worst of dietary habits permits for targeting interventions to assuage obesity among the population segment where it is most prevalent. We argue that the use of fiscal interventions does not appropriately take into account the economic, social and health circumstances of the intended beneficiaries of the policy. This paper reviews the influence of socio-demographic factors on nutrition and health status and considers the impacts of nutrition policy across the population drawing on methodologies from both public health and welfare economics. The effects of a fat tax on diet are found to be small and while other studies show that fat taxes saves lives, we show that average levels of disease risk do not change much: those consuming particularly bad diets continue to do so. Our results also suggest that the regressivity of the policy increases as the tax becomes focused on products with high saturated fat contents. A fiscally neutral policy that combines the fat tax with a subsidy on fruit and vegetables is actually more regressive because consumption of these foods tends to be concentrated in socially undeserving households. We argue that when inequality is of concern, population-based measures must reflect this and approaches that target vulnerable populations which have a shared propensity to adopt unhealthy behaviours are appropriate.

Attitudinal and demographic determinants of diet quality and implications for policy targeting

Background:  Poor diet quality is a major public health concern that has prompted governments to introduce a range of measures to promote healthy eating. For these measures to be effective, they should target segments of the population with messages relevant to their needs, aspirations and circumstances. The present study investigates the extent to which attitudes and constraints influence healthy eating, as well as how these vary by demographic characteristics of the UK population. It further considers how such information may be used in segmented diet and health policy messages. Methods:  A survey of 250 UK adults elicited information on conformity to dietary guidelines, attitudes towards healthy eating, constraints to healthy eating and demographic characteristics. Ordered logit regressions were estimated to determine the importance of attitudes and constraints in determining how closely respondents follow healthy eating guidelines. Further regressions explored the demographic characteristics associated with the attitudinal and constraint variables. Results:  People who attach high importance to their own health and appearance eat more healthily than those who do not. Risk-averse people and those able to resist temptation also eat more healthily. Shortage of time is considered an important barrier to healthy eating, although the cost of a healthy diet is not. These variables are associated with a number of demographic characteristics of the population; for example, young adults are more motivated to eat healthily by concerns over their appearance than their health. Conclusions:  The approach employed in the present study could be used to inform future healthy eating campaigns. For example, messages to encourage the young to eat more healthily could focus on the impact of diets on their appearance rather than health.

Milk in the diet: good or bad for vascular disease?

CVD still represent the greatest cause of death and disease burden in Europe and there remains uncertainty whether or not diets rich in milk and/or dairy products affect CVD risk. This paper reviews current evidence on this from prospective studies and the role of serum lipids and blood pressure as markers of CVD risk with such diets. Also the potential of animal nutrition-based approaches aimed at reducing CVD risk from consumption of milk and dairy products is outlined. Briefly, the evidence from prospective studies indicates that increased consumption of milk does not result in increased CVD risk and may give some long-term benefits, although few studies relate specifically to cheese and butter and more information on the relationship between milk/dairy product consumption and dementia is needed. Recent data suggest that the SFA in dairy products may be less of a risk factor than previously thought; although this is based on serum cholesterol responses which taken in isolation may be misleading. Milk and some dairy products have counterbalancing effects by reducing blood pressure and possibly BMI control. Despite this, animal nutrition strategies to replace some SFA in milk with cis-MUFA or cis-PUFA are extensive and intuitively beneficial, although this remains largely unproven, especially for milk. There is an urgent need for robust intervention studies to evaluate such milk-fat modifications using holistic markers of CVD risk including central arterial stiffness.

Nutritional biomarkers for objective dietary assessment

The accurate assessment of dietary exposure is important in investigating associations between diet and disease. Research in nutritional epidemiology, which has resulted in a large amount of information on associations between diet and chronic diseases in the last decade, relies on accurate assessment methods to identify these associations. However, most dietary assessment instruments rely to some extent on self-reporting, which is prone to systematic bias affected by factors such as age, gender, social desirability and approval. Nutritional biomarkers are not affected by these and therefore provide an additional, alternative method to estimate intake. However, there are also some limitations in their application: they are affected by inter-individual variations in metabolism and other physiological factors, and they are often limited to estimating intake of specific compounds and not entire foods. It is therefore important to validate nutritional biomarkers to determine specific strengths and limitations. In this perspective paper, criteria for the validation of nutritional markers and future developments are discussed.