Economic instruments for population diet and physical activity behaviour change: a systematic scoping review.

BACKGROUND: Unhealthy diet and low levels of physical activity are common behavioural factors in the aetiology of many non-communicable diseases. Recent years have witnessed an upsurge of policy and research interest in the use of taxes and other economic instruments to improve population health. OBJECTIVE: To assemble, configure and analyse empirical research studies available to inform the public health case for using economic instruments to promote dietary and physical activity behaviour change. METHODS: We conducted a systematic scoping review of evidence for the effects of specific interventions to change, or general exposure to variations in, prices or income on dietary and physical activity behaviours and corollary outcomes. Systematic electronic searches and parallel snowball searches retrieved >1 million study records. Text mining technologies were used to prioritise title-abstract records for screening. Eligible studies were selected, classified and analysed in terms of key characteristics and principal findings, using a narrative, configuring synthesis focused on implications for policy and further research. RESULTS: We identified 880 eligible studies, including 192 intervention studies and 768 studies that incorporated evidence for prices or income as correlates or determinants of target outcomes. Current evidence for the effects of economic instruments and exposures on diet and physical activity is limited in quality and equivocal in terms of its policy implications. Direct evidence for the effects of economic instruments is heavily skewed towards impacts on diet, with a relative lack of evidence for impacts on physical activity. CONCLUSIONS: The evidence-based case for using economic instruments to promote dietary and physical activity behaviour change may be less compelling than some proponents have claimed. Future research should include measurement of people's actual behavioural responses using study designs capable of generating reliable causal inferences regarding intervention effects. Policy implementation needs to be carefully aligned with evaluation planning and design

Service evaluation of weight outcomes as a function of initial BMI in 34,271 adults referred to a primary care/commercial weight management partnership scheme

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Testing Protein Leverage in Lean Humans: A Randomised Controlled Experimental Study

A significant contributor to the rising rates of human obesity is an increase in energy intake. The ‘protein leverage hypothesis’ proposes that a dominant appetite for protein in conjunction with a decline in the ratio of protein to fat and carbohydrate in the diet drives excess energy intake and could therefore promote the development of obesity. Our aim was to test the ‘protein leverage hypothesis’ in lean humans by disguising the macronutrient composition of foods offered to subjects under ad libitum feeding conditions. Energy intakes and hunger ratings were measured for 22 lean subjects studied over three 4-day periods of in-house dietary manipulation. Subjects were restricted to fixed menus in random order comprising 28 foods designed to be similar in palatability, availability, variety and sensory quality and providing 10%, 15% or 25% energy as protein. Nutrient and energy intake was calculated as the product of the amount of each food eaten and its composition. Lowering the percent protein of the diet from 15% to 10% resulted in higher (+12±4.5%, p = 0.02) total energy intake, predominantly from savoury-flavoured foods available between meals. This increased energy intake was not sufficient to maintain protein intake constant, indicating that protein leverage is incomplete. Urinary urea on the 10% and 15% protein diets did not differ statistically, nor did they differ from habitual values prior to the study. In contrast, increasing protein from 15% to 25% did not alter energy intake. On the fourth day of the trial, however, there was a greater increase in the hunger score between 1–2 h after the 10% protein breakfast versus the 25% protein breakfast (1.6±0.4 vs 25%: 0.5±0.3, p = 0.005). In our study population a change in the nutritional environment that dilutes dietary protein with carbohydrate and fat promotes overconsumption, enhancing the risk for potential weight gain

Contradictory phylogenetic signals in the laurasiatheria anomaly zone

G.M.H. was funded by a UCD Ad Astra Fellowship. C.L. was funded by a UCD Ad Astra studentship. L.R. was funded by an SFI Centre for Research Training in Genomics Data Science grant (18/CRT/6214). L.M.D. was supported in part by NSF awards 1838273 and 2032063. E.C.T. and T.L. were funded by an SFI Frontiers for the Future Programme grant (19/FFP/6790).Relationships among laurasiatherian clades represent one of the most highly disputed topics in mammalian phylogeny. In this study, we attempt to disentangle laurasiatherian interordinal relationships using two independent genome-level approaches: (1) quantifying retrotransposon presence/absence patterns, and (2) comparisons of exon datasets at the levels of nucleotides and amino acids. The two approaches revealed contradictory phylogenetic signals, possibly due to a high level of ancestral incomplete lineage sorting. The positions of Eulipotyphla and Chiroptera as the first and second earliest divergences were consistent across the approaches. However, the phylogenetic relationships of Perissodactyla, Cetartiodactyla, and Ferae, were contradictory. While retrotransposon insertion analyses suggest a clade with Cetartiodactyla and Ferae, the exon dataset favoured Cetartiodactyla and Perissodactyla. Future analyses of hitherto unsampled laurasiatherian lineages and synergistic analyses of retrotransposon insertions, exon and conserved intron/intergenic sequences might unravel the conflicting patterns of relationships in this major mammalian clade.Publisher PDFPeer reviewe

Free Sugars and Total Fat Are Important Characteristics of a Dietary Pattern Associated with Adiposity across Childhood and Adolescence

Background The importance of dietary sugar versus fat in the development of obesity is currently a topic of debate. Objective We aimed to identify dietary patterns (DPs) characterized by high sugar and/or high fat content and their longitudinal associations with adiposity during childhood and adolescence. Methods Participants were 6722 children from the Avon Longitudinal Study of Parents and Children (born 1991-92). DPs were characterized by % total energy intake (%E) from free sugars, %E from total fat, dietary energy density (DED) and fiber density, using reduced rank regression at 7, 10 and 13 years of age. Total body fat mass was measured at 11, 13 and 15 years of age. Regression analyses adjusted for dietary misreporting, physical activity and maternal class. Results Two major DPs were identified: higher z scores for DP1 were associated with greater DED, %E from sugars and fat, and lower fiber density; higher z scores for DP2 were associated with greater %E from sugars but lower %E from fat and DED. A 1 SD increase in z score for DP1 was associated with a mean increase in fat mass index z score of 0.04 SD units (95%CI 0.01, 0.07; P=0.017) and greater odds of excess adiposity (OR:1.12, 95%CI: 1.0, 1.25; P=0.038). DP2 was not associated with adiposity. Conclusions An energy-dense DP high in %E from fat and sugars is associated with greater adiposity in childhood and adolescence. This confirms the role of both fat and sugar and provides a basis for food based dietary guidelines to prevent obesity in children.</p

Protocol for the development and evaluation of a tool for predicting risk of short-term adverse outcomes due to COVID-19 in the general UK population

Introduction Novel coronavirus 2019 (COVID-19) has propagated a global pandemic with significant health, economic and social costs. Emerging emergence has suggested that several factors may be associated with increased risk from severe outcomes or death from COVID-19. Clinical risk prediction tools have significant potential to generate individualised assessment of risk and may be useful for population stratification and other use cases. Methods and analysis We will use a prospective open cohort study of routinely collected data from 1205 general practices in England in the QResearch database. The primary outcome is COVID-19 mortality (in or out-of-hospital) defined as confirmed or suspected COVID-19 mentioned on the death certificate, or death occurring in a person with SARS-CoV-2 infection between 24 th January and 30 th April 2020. Our primary outcome in adults is COVID-19 mortality (including out of hospital and in hospital deaths). We will also examine COVID-19 hospitalisation in children. Time-to-event models will be developed in the training data to derive separate risk equations in adults (19-100 years) for males and females for evaluation of risk of each outcome within the 3-month follow-up period (24 th January to 30 th April 2020), accounting for competing risks. Predictors considered will include age, sex, ethnicity, deprivation, smoking status, alcohol intake, body mass index, pre-existing medical co-morbidities, and concurrent medication. Measures of performance (prediction errors, calibration and discrimination) will be determined in the test data for men and women separately and by ten-year age group. For children, descriptive statistics will be undertaken if there are currently too few serious events to allow development of a risk model. The final model will be externally evaluated in (a) geographically separate practices and (b) other relevant datasets as they become available. Ethics and dissemination The project has ethical approval and the results will be submitted for publication in a peer-reviewed journal. Strengths and limitations of the study The individual-level linkage of general practice, Public Health England testing, Hospital Episode Statistics and Office of National Statistics death register datasets enable a robust and accurate ascertainment of outcomes The models will be trained and evaluated in population-representative datasets of millions of individuals Shielding for clinically extremely vulnerable was advised and in place during the study period, therefore risk predictions influenced by the presence of some ‘shielding’ conditions may require careful consideratio

Caloric restriction induces changes in insulin and body weight measurements that are inversely associated with subsequent weight regain

BACKGROUND: Successful weight maintenance following weight loss is challenging for many people. Identifying predictors of longer-term success will help target clinical resources more effectively. To date, focus has been predominantly on the identification of predictors of weight loss. The goal of the current study was to determine if changes in anthropometric and clinical parameters during acute weight loss are associated with subsequent weight regain. METHODOLOGY: The study consisted of an 8-week low calorie diet (LCD) followed by a 6-month weight maintenance phase. Anthropometric and clinical parameters were analyzed before and after the LCD in the 285 participants (112 men, 173 women) who regained weight during the weight maintenance phase. Mixed model ANOVA, Spearman correlation, and linear regression were used to study the relationships between clinical measurements and weight regain. PRINCIPAL FINDINGS: Gender differences were observed for body weight and several clinical parameters at both baseline and during the LCD-induced weight loss phase. LCD-induced changes in BMI (Spearman's ρ = 0.22, p = 0.0002) were inversely associated with weight regain in both men and women. LCD-induced changes in fasting insulin (ρ = 0.18, p = 0.0043) and HOMA-IR (ρ = 0.19, p = 0.0023) were also associated independently with weight regain in both genders. The aforementioned associations remained statistically significant in regression models taking account of variables known to independently influence body weight. CONCLUSIONS/SIGNIFICANCE: LCD-induced changes in BMI, fasting insulin, and HOMA-IR are inversely associated with weight regain in the 6-month period following weight loss

Altering the availability or proximity of food, alcohol, and tobacco products to change their selection and consumption.

BACKGROUND: Overconsumption of food, alcohol, and tobacco products increases the risk of non-communicable diseases. Interventions to change characteristics of physical micro-environments where people may select or consume these products - including shops, restaurants, workplaces, and schools - are of considerable public health policy and research interest. This review addresses two types of intervention within such environments: altering the availability (the range and/or amount of options) of these products, or their proximity (the distance at which they are positioned) to potential consumers. OBJECTIVES: 1. To assess the impact on selection and consumption of altering the availability or proximity of (a) food (including non-alcoholic beverages), (b) alcohol, and (c) tobacco products.2. To assess the extent to which the impact of these interventions is modified by characteristics of: i. studies, ii. interventions, and iii. SEARCH METHODS: We searched CENTRAL, MEDLINE, Embase, PsycINFO, and seven other published or grey literature databases, as well as trial registries and key websites, up to 23 July 2018, followed by citation searches. SELECTION CRITERIA: We included randomised controlled trials with between-participants (parallel group) or within-participants (cross-over) designs. Eligible studies compared effects of exposure to at least two different levels of availability of a product or its proximity, and included a measure of selection or consumption of the manipulated product. DATA COLLECTION AND ANALYSIS: We used a novel semi-automated screening workflow and applied standard Cochrane methods to select eligible studies, collect data, and assess risk of bias. In separate analyses for availability interventions and proximity interventions, we combined results using random-effects meta-analysis and meta-regression models to estimate summary effect sizes (as standardised mean differences (SMDs)) and to investigate associations between summary effect sizes and selected study, intervention, or participant characteristics. We rated the certainty of evidence for each outcome using GRADE. MAIN RESULTS: We included 24 studies, with the majority (20/24) giving concerns about risk of bias. All of the included studies investigated food products; none investigated alcohol or tobacco. The majority were conducted in laboratory settings (14/24), with adult participants (17/24), and used between-participants designs (19/24). All studies were conducted in high-income countries, predominantly in the USA (14/24).Six studies investigated availability interventions, of which two changed the absolute number of different options available, and four altered the relative proportion of less-healthy (to healthier) options. Most studies (4/6) manipulated snack foods or drinks. For selection outcomes, meta-analysis of three comparisons from three studies (n = 154) found that exposure to fewer options resulted in a large reduction in selection of the targeted food(s): SMD -1.13 (95% confidence interval (CI) -1.90 to -0.37) (low certainty evidence). For consumption outcomes, meta-analysis of three comparisons from two studies (n = 150) found that exposure to fewer options resulted in a moderate reduction in consumption of those foods, but with considerable uncertainty: SMD -0.55 (95% CI -1.27 to 0.18) (low certainty evidence).Eighteen studies investigated proximity interventions. Most (14/18) changed the distance at which a snack food or drink was placed from the participants, whilst four studies changed the order of meal components encountered along a line. For selection outcomes, only one study with one comparison (n = 41) was identified, which found that food placed farther away resulted in a moderate reduction in its selection: SMD -0.65 (95% CI -1.29 to -0.01) (very low certainty evidence). For consumption outcomes, meta-analysis of 15 comparisons from 12 studies (n = 1098) found that exposure to food placed farther away resulted in a moderate reduction in its consumption: SMD -0.60 (95% CI -0.84 to -0.36) (low certainty evidence). Meta-regression analyses indicated that this effect was greater: the farther away the product was placed; when only the targeted product(s) was available; when participants were of low deprivation status; and when the study was at high risk of bias. AUTHORS' CONCLUSIONS: The current evidence suggests that changing the number of available food options or altering the positioning of foods could contribute to meaningful changes in behaviour, justifying policy actions to promote such changes within food environments. However, the certainty of this evidence as assessed by GRADE is low or very low. To enable more certain and generalisable conclusions about these potentially important effects, further research is warranted in real-world settings, intervening across a wider range of foods - as well as alcohol and tobacco products - and over sustained time periods