Dietary patterns of households in Scotland: Differences by level of deprivation and associations with dietary goals

BACKGROUND

Foods tend to be consumed in combinations, and dietary pattern analysis and diet-quality scores are often more appropriate methods of assessing overall diet quality than is intakes of individual foods or nutrients.

AIM

The aim of this study was to evaluate dietary patterns from the food and drink purchases of households in Scotland, and to identify any dietary patterns that were associated with closer adherence to the Revised Dietary Goals for Scotland (RDGS).

METHODS

We carried out a cross-sectional study of estimated food and drink intakes using Kantar WorldPanel household purchase data in Scotland collected during 2012. The amounts of food and drink purchased were converted to estimated amounts available for consumption per person by adjusting for household waste, household size and composition ( n = 720). Dietary patterns were identified using principal components analysis. A Diet Quality Index (DQI), based on the RDGS, was calculated.

RESULTS

The mean DQI score was low at 38 out of a possible maximum of 100, indicating that, on average, few of the dietary goals were being met. Six dietary patterns were identified, which explained 35% of the total variance in estimated food and drink intake. Three dietary patterns showed statistically significant associations with lower DQI scores (less healthy diets), and one with significantly higher DQI scores (healthier diets).

CONCLUSIONS

Investigating dietary patterns to show which foods tend to be purchased together may assist in targeting dietary habits by focussing on key food groups, and in gaining the greatest improvement in diet quality from the most achievable change in diet.

Using food intake records to estimate compliance with the Eatwell Plate dietary guidelines

BACKGROUND

The UK Eatwell Plate is consumer based advice recommending the proportions of five food groups for a balanced diet: starchy foods, fruit and vegetables, dairy foods, nondairy sources of protein and foods and drinks high in fat or sugar. Many foods comprise ingredients from several food groups and consumers need to consider how these fit with the proportions of the Eatwell Plate. This involves disaggregating composite dishes into proportions of individual food components. The present study aimed to match the diets of adults in Scotland to the Eatwell Plate dietary recommendations and to describe the assumptions and methodological issues associated with estimating Eatwell Plate proportions from dietary records.

METHODS

Foods from weighed intake records of 161 females and 151 males were assigned to a single Eatwell group based on the main ingredient for composite foods, and the overall Eatwell Plate proportions of each subject's diet were calculated. Food group proportions were then recalculated after disaggregating composite foods.

RESULTS

The fruit and vegetables and starchy food groups consumed were significantly lower than recommended in the Eatwell Plate, whereas the proportions of the protein and foods high in fat or sugar were significantly higher. Failing to disaggregate composite foods gave an inaccurate estimate of the food group composition of the diet.

CONCLUSIONS

Estimating Eatwell Plate proportions from dietary records is not straightforward, and is reliant on methodological assumptions. These need to be standardised and disseminated to ensure consistent analysis.

Attendance and weight outcomes in 4754 adults referred over 6 months to a primary care/commercial weight management partnership scheme

WHAT IS ALREADY KNOWN ON THIS SUBJECT

•  There is growing evidence of the effectiveness of commercial weight management programmes in the community. A recent randomized controlled trial has shown commercial providers to be more effective than NHS providers for weight management solutions in primary care. Some commercial weight management providers have established national slimming on referral schemes for weight management, which result on average in weight losses of 4-5% over a 12-week referral period. A recent randomized controlled trial of a similar scheme over 12 months yielded similar weight loses. Another RCT comparing commercial providers over 6 months showed average weight losses of ∼6.6% across providers.

WHAT THIS STUDY ADDS

•  The present study shows that when local primary care practitioners target resources to where they, as health professionals, felt they would have the most beneficial effect in their local communities, greater weight losses can be achieved. •  Different NHS Trusts extended 12-week referrals by an additional 12 weeks in a total of 4754 patients. •  Mean weight losses of 8.6% were achieved suggesting that local targeting of primary care resources can maximize returns for NHS investments in commissioning the services of commercial weight management organizations.

SUMMARY

This project audited attendance and weight loss in a primary care/commercial weight management partnership scheme in patients who participated over 6 months. 4754 adult patients (575 men, 4179 women) were referred to Slimming World for 24 weekly sessions. Data were analysed using individual weekly weight records. Mean (standard deviation, SD) body mass index (BMI) change was -3.3 kg m(-2) (2.2), weight change -8.9 kg (6.0), percent weight change -8.6% (5.3) and number of sessions attended 21.3 (3.2) of 24. For patients attending at least 20 of 24 sessions (n = 3626 or 76.3%), mean (SD) BMI change was -3.6 kg m(-2) (2.2), weight change -9.6 kg (6.1), percent weight change -9.3% (5.3). Weight loss was greater in men than women (P < 0.001). 74.5% of all patients enrolled, and 79.3% of patients attending 20 or more sessions achieved at least 5% weight loss. 37.3% of the whole population lost ≥10% of their weight. Weight gain was prevented in 96.3% of all patients referred. Referral to a commercial organization for community-based lifestyle intervention is a practical option for longer-term National Health Service weight management strategies.

Problems in identifying predictors and correlates of weight loss and maintenance: implications for weight control therapies based on behaviour change

Weight management is a dynamic process, with a pre-treatment phase, a treatment (including process) phase and post-treatment maintenance, and where relapse is possible during both the treatment and maintenance. Variability in the statistical power of the studies concerned, heterogeneity in the definitions, the complexity of obesity and treatment success, the constructs and measures used to predict weight loss and maintenance, and an appreciation of who and how many people achieve it, make prediction difficult. In models of weight loss or maintenance: (i) predictors explain up to 20-30% of the variance; (ii) many predictors are the sum of several small constituent variables, each accounting for a smaller proportion of the variance; (iii) correlational or predictive relationships differ across study populations; (iv) inter-individual variability in predictors and correlates of outcomes is high and (v) most of the variance remains unexplained. Greater standardization of predictive constructs and outcome measures, in more clearly defined study populations, tracked longitudinally, is needed to better predict who sustains weight loss. Treatments need to develop a more individualized approach that is sensitive to patients' needs and individual differences, which requires measuring and predicting patterns of intra-individual behaviour variations associated weight loss and its maintenance. This information will help people shape behaviour change solutions to their own lifestyle needs.

Developing a methodology for assigning glycaemic index values to foods consumed across Europe

There is growing evidence that the glycaemic index (GI) of the diet is important with respect to body weight and metabolic disease risk. However, research is limited by the paucity of GI values for commonly consumed carbohydrate-rich foods in European countries. A new methodology has been developed for consistent assignment of GI values to foods across five European databases used in the Diogenes intervention study. GI values were assigned according to five decreasing levels of confidence (1) Measured values for specific foods; (2) Published values from published sources; (3) Equivalent values where published values for similar foods existed; (4) Estimated values assigned as one of three values representing low/medium/high GI ranges and (5) Nominal values assigned as 70, where no other value could be assigned with sufficient confidence. GI values were assigned to 5105 foods. In food records collected at baseline, the contribution to carbohydrate intake of foods assigned levels 1-2 ranged from 16% to 43% depending on country, and this increased to 53-81% including level 3 foods. The degree of confidence to assigned GI values differed across Europe. This standardized approach of assigning GI values will be made available to other researchers to facilitate further investigation into the effects of dietary GI on health.

Low-energy reporting and duration of recording period

Three-day, rather than 7-day, food records are frequently used because mis-reporting of food intake is believed to increase with recording period. Data from the National Diet and Nutrition Survey of adults were used to explore trends in reported energy intake (REI) with day of recording and to compare average REIs from Thursday to Saturday and from Sunday to Tuesday to the complete 7-day record. Although REIs decreased from days 2 to 7, this was by a quantitatively insignificant 49 kJ per day (P=0.026) and well within the measurement error of recorded food intakes. Furthermore, REIs were lowest on the first recording day. The 3- and 7-day averages were similar (mean difference 0.039 (s.d.+/-1.0) MJ (NS), range -3.3 to +4.2 MJ). However, the difference was greater for those reporting higher than average energy intakes because of higher REIs on weekend days. Food intake reporting periods of longer than 3 days and ideally 7 days are preferable.

Resistance and susceptibility to weight gain: individual variability in response to a high-fat diet

An obesigenic environment is a potent force for promoting weight gain. However, not all people exposed to such an environment become obese; some remain lean. This means that some people are susceptible to weight gain (in a weight-promoting environment) and others are resistant. Identifying the characteristics of appetite control and food motivation in these two groups could throw light on the causes of weight gain and how this can be either treated or prevented. We have investigated the issue experimentally by identifying people who habitually consume a high-fat diet (greater than 43% fat energy). These individuals have been termed high-fat phenotypes. We have compared individuals, of the same age (mean=37 years old) and gender (male), who have gained weight (BMI=34) or who have remained lean (BMI=22). The susceptible individuals are characterised by a cluster of characteristics including a weak satiety response to fatty meals, a maintained preference for high-fat over low-energy foods in the post-ingestive satiety period, a strong hedonic attraction to palatable foods and to eating, and high scores on the TFEQ factors of Disinhibition and Hunger. The analysis of large databases suggests that this profile of factors contributes to an average daily positive energy balance from food of approximately 0.5 MJ. This profile of characteristics helps to define the symptomatology of a thrifty phenotype.

The evaluation of an electronic visual analogue scale system for appetite and mood

Our objective was to evaluate a new electronic visual analogue scale (VAS) system for logging subjective motivation to eat ratings. In total, 10 men and 10 women completed both electronic and traditional pen and paper versions of the questionnaire every hour of the waking day. Subjects consumed a standard medium-fat diet, which was fixed at 1.6.BMR. Correlation coefficients for scores obtained by both methods were significant for all questions, with R(2) values ranging from 67 to 87%. However, Bland and Altman plots and paired t-tests identified significant bias between the two methods for five of the nine individual questions. These were questions that tended to be scored more towards the ends of the VAS. The new electronic VAS produces comparable, but not interchangeable, results to the traditional pen and paper method in the study of appetite and mood, while offering advantages of improved reliability in data collection.

Energy density, diet composition and palatability: influences on overall food energy intake in humans

This paper considers the role of energy density (ED), diet composition and palatability in the control of energy intake (EI) in humans through several related considerations: (i) the relationship between ED and diet composition, (ii) the relationship between ED, diet composition and EI, (iii) the relationship between palatability and EI, (iv) the relationship between ED, palatability and EI, (v) the importance of postingestive factors in influencing palatability in the longer term, (vi) the contribution of sensory and nutritional factors to dietary hyperphagia and (vii) the implications these considerations have for people living their normal lives in their natural environment. The main factors influencing ED are the fat and water content of foods. Energy density does elevate EI, especially in short-term studies where it can account for >40% of the variance in EI. In real life, ED accounts for only approximately 7% of the variance in EI. This is because the determinants of EI are multifactorial and also because the short-term effects of ED on EI do not translate into the longer term. We argue that part of the longer term amelioration of short-term effects of ED on EI is due to learned compensation, based on the postingestive consequences of consuming familiar food that differ in ED. More energy-dense foods tend to be more palatable but we learn to consume them in smaller portion sizes. In the longer term, the perceived palatability of a food is strongly influenced by the postingestive consequences of eating it. This effect can override sensory factors alone. This implies that nutrient mimetics, if used continuously, would not be as efficacious as initially supposed and that their ad hoc use may undermine the stability of learned appetites and satieties for foods with different EDs and contribute to the poor weight control capability exhibited by consumers at large.

Cross talk between physical activity and appetite control: does physical activity stimulate appetite?

Physical activity has the potential to modulate appetite control by improving the sensitivity of the physiological satiety signalling system, by adjusting macronutrient preferences or food choices and by altering the hedonic response to food. There is evidence for all these actions. Concerning the impact of physical activity on energy balance, there exists a belief that physical activity drives up hunger and increases food intake, thereby rendering it futile as a method of weight control. There is, however, no evidence for such an immediate or automatic effect. Short (1-2 d)-term and medium (7-16 d)-term studies demonstrate that men and women can tolerate substantial negative energy balances of < or = 4 MJ energy cost/d when performing physical activity programmes. Consequently, the immediate effect of taking up exercise is weight loss (although this outcome is sometimes difficult to assess due to changes in body composition or fluid compartmentalization). However, subsequently food intake begins to increase in order to provide compensation for about 30% of the energy expended in activity. This compensation (up to 16 d) is partial and incomplete. Moreover, subjects separate into compensators and non-compensators. The exact nature of these differences in compensation and whether it is actually reflective of non-compliance with protocols is yet to be determined. Some subjects (men and women) performing activity with a cost of < or = 4 MJ/d for 14 d, show no change in daily energy intake. Conversely, it can be demonstrated that when active individuals are forced into a sedentary routine food intake does not decrease to a lower level to match the reduced energy expenditure. Consequently, this situation creates a substantial positive energy balance accompanied by weight gain. The next stage is to further characterize the compensators and non-compensators, and to identify the mechanisms (physiological or behavioural) that are responsible for the rate of compensation and its limits.

Rate and extent of compensatory changes in energy intake and expenditure in response to altered exercise and diet composition in humans

We assessed the effect of no exercise (Nex; control) and high exercise level (Hex; ∼4 MJ/day) and two dietary manipulations [a high-fat diet (HF; 50% of energy, 700 kJ/100 g) and low-fat diet (LF; 20% of energy, 300 kJ/100 g)] on compensatory changes in energy intake (EI) and energy expenditure (EE) over 7-day periods. Eight lean men were each studied four times in a 2 × 2 randomized design. EI was directly quantified by weight of food consumed. EE was assessed by heart rate (HR) monitoring. Body weight was measured daily. Mean daily EE was 17.6 and 11.5 MJ/day ( P < 0.001) on the pooled Hex and Nex treatments, respectively. EI was higher on HF diets (13.4 MJ/day pooled) compared with the LF diets (9.0 MJ/day). Regression analysis showed that these energy imbalances induced significant compensatory changes in EB over time of ∼0.3-0.4 MJ/day ( P < 0.05). These were due to changes in both EI and EE in the opposite direction to the perturbation in energy balance. These changes were significant, small but persistent, amounting to ∼0.2 and ∼0.35 MJ/day for EI and EE, respectively.

Carbohydrates, appetite and feeding behavior in humans

The view of carbohydrates in relation to obesity has changed over the past few decades from being conducive to overconsumption and weight gain to being protective. This article reviews the mechanisms by which carbohydrate is purported to protect against weight gain. Although carbohydrate is metabolized and stored in the body less efficiently than fat, when de novo lipogenesis is invoked on very high carbohydrate diets, the beneficial effect on energy balance is likely to be minimal when typical high fat Western diets are consumed. However, it has been suggested that high carbohydrate foods may influence energy balance by reducing food intake through greater satiety effects, reducing energy density and displacing fat from the diet-the fat-sugar seesaw effect. To date, there seem to be few differences between sugars and starches on satiety and energy intake, but few studies have examined this. Some reduced-fat, and, therefore, higher carbohydrate, foods are highly energy dense. High carbohydrate foods do not necessarily have a low energy density. Evidence from recent studies suggests that adding carbohydrate, and especially sugar, to the diet neither displaces fat from the diet nor protects against elevated energy intake. Although it is easier to overeat on high fat than low fat foods, simply replacing fat with carbohydrate in the diet may not be as protective against overconsumption as the energy density or fat-sugar seesaw arguments suggest.

Altering the temporal distribution of energy intake with isoenergetically dense foods given as snacks does not affect total daily energy intake in normal-weight men

The objectives of the present study were to examine the effects of (1) ingesting mandatory snacks v. no snacks and (2) the composition of isoenergetically-dense snacks high in protein, fat or carbohydrate, on food intake and energy intake (EI) in eight men with ad libitum access to a diet of fixed composition. Subjects were each studied four times in a 9 d protocol per treatment. On days 1-2, subjects were given a medium-fat maintenance diet estimated at 1.6 x resting metabolic rate (RMR). On days 3-9, subjects consumed three mandatory isoenergetic, isoenergetically dense (380 kJ/100 g) snacks at fixed time intervals (11.30, 15.30 and 19.30 hours). Total snack intake comprised 30% of the subjects' estimated daily energy requirements. The treatments were high protein (HP), high carbohydrate (HC), high fat (HF) and no snack (NS). The order was randomized across subjects in a counterbalanced, Latin-square design. During the remainder of the day, subjects had ad libitum (meal size and frequency) access to a covertly manipulated medium-fat diet of fixed composition (fat:carbohydrate:protein, 40:47:13 by energy), energy density 550 kJ/100 g. All foods eaten were investigator-weighed before ingestion and left-overs were weighed after ingestion. Subjective hunger and satiety feelings were tracked hourly during waking hours using visual analogue scales. Ad libitum EI amounted to 13.9 MJ/d on the NS treatment compared with 11.7, 11.7 and 12.2 MJ/d on the HP, HC and HF diets respectively (F(3,21) 5.35; P = 0.007, SED 0.66). Total EI values were not significantly different at 14.6, 14.5, 15.0 and 14.2 MJ/d respectively. Snack composition did not differentially affect total daily food intake or EI. Average daily hunger was unaffected by the composition of the snacks. Only at 12.00 hours did subjects feel significantly more hungry during the NS condition, relative to the other dietary treatments (F(3,18) 4.42; P = 0.017). Body weight was unaffected by dietary treatment. In conclusion, snacking per se led to compensatory adjustments in feeding behaviour in lean men. Snack composition (with energy density controlled) did not affect the amount eaten of a diet of fixed composition. Results may differ in real life where subjects can alter both composition and amount of food they eat and energy density is not controlled.