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An abnormal Zn status has been suggested to play a role in the pathogenesis of type 2 diabetes. However, epidemiological studies of the relationship between plasma Zn concentrations and diabetes are sparse and inconclusive. We aimed to investigate the association between plasma Zn concentrations and glycaemic markers (fasting glucose, 2-h glucose and homeostatic model assessment of insulin resistance) in rural and urban Cameroon. We studied 596 healthy adults (63·3 % women) aged 25–55 years in a population-based cross-sectional study. The mean plasma Zn concentration was 13·7 ± 2·7 µmol/L overall, with higher levels in men (14·4 ± 2·9 µmol/l) than in women (13·2 ± 2·6 µmol/l), P-value < 0·0001. There was an inverse relationship between tertiles of plasma Zn and 2-h glucose concentrations (P-value for linear trend = 0·002). The difference in 2-h glucose between those in the highest tertile of plasma Zn compared to the lowest was −0·63 (95 % CI − 1·02, −0·23) mmol/l. This remained significant after adjusting for age, sex, smoking status, alcohol intake, education level, area of residence, adiposity and objectively measured physical activity −0·43(–0·82, −0·04). Similar inverse associations were observed between plasma Zn concentrations and fasting glucose and homeostatic model assessment of insulin resistance when adjusted for socio-demographic and health-related behavioural characteristics. The current findings of an inverse association between plasma Zn concentrations and several markers of glucose homeostasis, together with growing evidence from intervention studies, suggest a role for Zn in glucose metabolism. If supported by further evidence, strategies to improve Zn status in populations may provide a cheap public health prevention approach for diabetes.
In May 2021, the Scientific Advisory Committee on Nutrition (SACN) published a risk assessment on lower carbohydrate diets for adults with type 2 diabetes (T2D)(1). The purpose of the report was to review the evidence on ‘low’-carbohydrate diets compared with the current UK government advice on carbohydrate intake for adults with T2D. However, since there is no agreed and widely utilised definition of a ‘low’-carbohydrate diet, comparisons in the report were between lower and higher carbohydrate diets. SACN’s remit is to assess the risks and benefits of nutrients, dietary patterns, food or food components for health by evaluating scientific evidence and to make dietary recommendations for the UK based on its assessment(2). SACN has a public health focus and only considers evidence in healthy populations unless specifically requested to do otherwise. Since the Committee does not usually make recommendations relating to clinical conditions, a joint working group (WG) was established in 2017 to consider this issue. The WG comprised members of SACN and members nominated by Diabetes UK, the British Dietetic Association, Royal College of Physicians and Royal College of General Practitioners. Representatives from NHS England and NHS Health Improvement, the National Institute for Health and Care Excellence and devolved health departments were also invited to observe the WG. The WG was jointly chaired by SACN and Diabetes UK.
Online self-reported 24-h dietary recall systems promise increased feasibility of dietary assessment. Comparison against interviewer-led recalls established their convergent validity; however, reliability and criterion-validity information is lacking. The validity of energy intakes (EI) reported using Intake24, an online 24-h recall system, was assessed against concurrent measurement of total energy expenditure (TEE) using doubly labelled water in ninety-eight UK adults (40–65 years). Accuracy and precision of EI were assessed using correlation and Bland–Altman analysis. Test–retest reliability of energy and nutrient intakes was assessed using data from three further UK studies where participants (11–88 years) completed Intake24 at least four times; reliability was assessed using intra-class correlations (ICC). Compared with TEE, participants under-reported EI by 25 % (95 % limits of agreement −73 % to +68 %) in the first recall, 22 % (−61 % to +41 %) for average of first two, and 25 % (−60 % to +28 %) for first three recalls. Correlations between EI and TEE were 0·31 (first), 0·47 (first two) and 0·39 (first three recalls), respectively. ICC for a single recall was 0·35 for EI and ranged from 0·31 for Fe to 0·43 for non-milk extrinsic sugars (NMES). Considering pairs of recalls (first two v. third and fourth recalls), ICC was 0·52 for EI and ranged from 0·37 for fat to 0·63 for NMES. EI reported with Intake24 was moderately correlated with objectively measured TEE and underestimated on average to the same extent as seen with interviewer-led 24-h recalls and estimated weight food diaries. Online 24-h recall systems may offer low-cost, low-burden alternatives for collecting dietary information.
Evidence from randomised controlled trials supports beneficial effects of total dairy products on body weight, fat and lean mass, but evidence on associations of dairy types with distributions of body fat and lean mass is limited. We aimed to investigate associations of total and different types of dairy products with markers of adiposity, and body fat and lean mass distribution. We evaluated cross-sectional data from 12 065 adults aged 30–65 years recruited to the Fenland Study between 2005 and 2015 in Cambridgeshire, UK. Diet was assessed with an FFQ. We estimated regression coefficients (or percentage differences) and their 95 % CI using multiple linear regression models. The medians of milk, yogurt and cheese consumption were 293 (interquartile range (IQR) 146–439), 35·3 (IQR 8·8–71·8) and 14·6 (IQR 4·8–26·9) g/d, respectively. Low-fat dairy consumption was inversely associated with visceral:subcutaneous fat ratio estimated with dual-energy X-ray absorptiometry (–2·58 % (95 % CI –3·91, –1·23 %) per serving/d). Habitual consumption per serving/d (200 g) of milk was associated with 0·33 (95 % CI 0·19, 0·46) kg higher lean mass. Other associations were not significant after false discovery correction. Our findings suggest that the influence of milk consumption on lean mass and of low-fat dairy consumption on fat mass distribution may be potential pathways for the link between dairy consumption and metabolic risk. Our cross-sectional findings warrant further research in prospective and experimental studies in diverse populations.
A wide variety of methods are available to assess dietary intake, each one with different strengths and weaknesses. Researchers face multiple challenges when diet and nutrition need to be accurately assessed, particularly in the selection of the most appropriate dietary assessment method for their study. The goal of the current collaborative work is to present a collection of available resources for dietary assessment implementation.
As a follow-up to the 9th International Conference on Diet and Physical Activity Methods held in 2015, developers of dietary assessment toolkits agreed to collaborate in the preparation of the present paper, which provides an overview of each toolkit. The toolkits presented include: the Diet, Anthropometry and Physical Activity Measurement Toolkit (DAPA; UK); the National Cancer Institute’s (NCI) Dietary Assessment Primer (USA); the Nutritools website (UK); the Australasian Child and Adolescent Obesity Research Network (ACAORN) method selector (Australia); and the Danone Dietary Assessment Toolkit (DanoneDAT; France). An at-a-glance summary of features and comparison of the toolkits is provided.
The present review contains general background on dietary assessment, along with a summary of each of the included toolkits, a feature comparison table and direct links to each toolkit, all of which are freely available online.
This overview of dietary assessment toolkits provides comprehensive information to aid users in the selection and implementation of the most appropriate dietary assessment method, or combination of methods, with the goal of collecting the highest-quality dietary data possible.
High cost of healthy foods could be a barrier to healthy eating. We aimed to examine the association between dietary cost and adherence to the Mediterranean diet in a non-Mediterranean country. We evaluated cross-sectional data from 12 417 adults in the UK Fenland Study. Responses to 130-item FFQ were used to calculate a Mediterranean diet score (MDS). Dietary cost was estimated by matching food consumption data with retail prices of five major supermarkets. Using multivariable-adjusted linear regression, we examined the association of MDS and individual foods with dietary cost in absolute and relative scales. Subsequently, we assessed how much the association was explained by education, income, marital status and occupation, by conducting mediation analysis and testing interaction by these variables. High compared with low MDS (top to bottom third) was associated with marginally higher cost by 5·4 % (95 % CI 4·4, 6·4) or £0·20/d (95 % CI 0·16, 0·25). Participants with high adherence had higher cost associated with the healthier components (e.g. vegetables, fruits and fish), and lower cost associated with the unhealthy components (e.g. red meat, processed meat and sweets) (Pfor trend<0·001 each). In total, 20·7 % (95 % CI 14·3, 27·0) of the MDS-cost association was explained by the selected socio-economic factors, and the MDS-cost association was of greater magnitude in lower socio-economic groups (Pinteraction<0·005). Overall, greater adherence to the Mediterranean diet was associated with marginally higher dietary cost, partly modified and explained by socio-economic status, but the potential economic barriers of high adherence might be offset by cost saving from reducing unhealthy food consumption.
We aimed to identify sociodemographic, lifestyle and behavioural determinants of consumption of sugar-sweetened beverages (SSB) and artificially sweetened beverages (ASB) among adults in Cambridgeshire, UK.
Cross-sectional data were obtained from a cohort of 9991 adults born between 1950 and 1975. An FFQ was used to assess consumption of beverages and other dietary factors. Multivariable logistic regression was used to examine potential determinants of consuming SSB and ASB (≥1 serving/d).
Recruitment from general practice surgeries to participate in the ongoing population-based Fenland Study.
Adults (n 9991) aged 30–64 years from three areas of Cambridgeshire, UK.
Prevalence estimates for daily SSB and ASB consumption were 20·4 % (n 2041) and 8·9 % (n 893), respectively. SSB consumption (OR; 95 % CI) was more common in men than women (1·33; CI 1·17, 1·50) and among those reporting lower income (<£20 000/year) than those reporting higher income (>£40 000/year; 1·31; 1·09, 1·58). In contrast, daily ASB consumption was more common among women than men (1·62; 1·34, 1·96), those on weight-loss diets than those who were not (2·58; 2·05, 3·24) and those reporting higher income than lower income (1·53; 1·16, 2·00). Factors associated with higher consumption of each of SSB and ASB included being a younger adult, being overweight/obese, having shorter education, eating meals or snack foods while watching television, and skipping breakfast (P<0·05 each).
Frequent consumers of SSB and ASB differ by several sociodemographic characteristics. However, increased BMI, younger age and unhealthy eating behaviours are common to both groups.
Evidence suggests that diets meeting recommendations for fruit and vegetable (F&V) intake are more costly. Dietary costs may be a greater constraint on the diet quality of people of lower socioeconomic position (SEP). The aim of this study was to examine whether dietary costs are more strongly associated with F&V intake in lower-SEP groups than in higher-SEP groups. Data on individual participants’ education and income were available from a population-based, cross-sectional study of 10 020 British adults. F&V intake and dietary costs (GBP/d) were derived from a semi-quantitative FFQ. Dietary cost estimates were based on UK food prices. General linear models were used to assess associations between SEP, quartiles of dietary costs and F&V intake. Effect modification of SEP gradients by dietary costs was examined with interaction terms. Analysis demonstrated that individuals with lowest quartile dietary costs, low income and low education consumed less F&V than individuals with higher dietary costs, high income and high education. Significant interaction between SEP and dietary costs indicated that the association between dietary costs and F&V intake was stronger for less-educated and lower-income groups. That is, socioeconomic differences in F&V intake were magnified among individuals who consumed lowest-cost diets. Such amplification of socioeconomic inequalities in diet among those consuming low-cost diets indicates the need to address food costs in strategies to promote healthy diets. In addition, the absence of socioeconomic inequalities for individuals with high dietary costs suggests that high dietary costs can compensate for lack of other material, or psychosocial resources.
Unhealthy dietary behaviours may contribute to obesity along with energy imbalance. Both positive and null associations of snacking and BMI have been reported, but the association between snacking and total adiposity or pattern of fat deposition remains unevaluated. The objective of this study was to investigate the associations between snacking frequency and detailed adiposity measurements. A total of 10 092 adults residing in Cambridgeshire, England, self-completed eating pattern snacking frequency, FFQ and physical activity questionnaires. Measurements included anthropometry, body composition using dual-energy X-ray absorptiometry scan and ultrasound and assessment of physical activity energy expenditure using heart rate and movement sensing. Linear regression analyses were conducted adjusted for age, socio-demographics, dietary quality, energy intake, PAEE and screen time by sex and BMI status. Among normal-weight individuals (BMI<25 kg/m2), each additional snack was inversely associated with obesity measures: lower total body fat in men and women (−0·41 (95 % CI −0·74, −0·07) %, −0·41 (−0·67, −0·15) %, respectively) and waist circumference (−0·52 (−0·90, −0·14) cm) in men. In contrast, among the overweight/obese (BMI≥25 kg/m2), there were positive associations: higher waist circumference (0·80 (0·34, 0·28) cm) and subcutaneous fat (0·06 (0·01, 0·110) cm) in women and waist circumference (0·37 (0·00, 0·73) cm) in men. Comparing intakes of snack-type foods showed that participants with BMI≥25 kg/m2 had higher intakes of crisps, sweets, chocolates and ice-creams and lower intakes of yoghurt and nuts compared with normal-weight participants. Adjusting for these foods in a model that included a BMI–snacking interaction term attenuated all the associations to null. Snacking frequency may be associated with higher or lower adiposity, with the direction of association being differential by BMI status and dependent on snack food choice. Improving snack choices could contribute to anti-obesity public health interventions.
Consumption of a Mediterranean diet (MD) and genetic variation in the glucokinase regulatory protein (GCKR) gene have been reported to be associated with TAG and glucose metabolism. It is uncertain whether there is any interaction between these factors. Therefore, the aims of the present study were to test the association of adherence to a MD and rs780094 (G>A) SNP in the GCKR gene with the markers of cardiometabolic risk, and to investigate the interaction between genetic variation and MD adherence. We studied 20 986 individuals from the European Prospective Investigation into Cancer (EPIC)-Norfolk study. The relative Mediterranean Diet Score (rMED: range 0–18) was used to assess MD adherence. Linear regression was used to estimate the association between the rMED, genotype and cardiometabolic continuous traits, adjusting for potential confounders. In adjusted analyses, we observed independent associations of MD adherence and genotype with cardiometabolic risk, with the highest risk group (AA genotype; lowest rMED) having higher concentrations of TAG, total cholesterol and apoB (12·5, 2·3 and 3·1 %, respectively) v. those at the lowest risk (GG genotype; highest rMED). However, the associations of MD adherence with metabolic markers did not differ by genotype, with no significant gene–diet interactions for lipids or for glycated Hb. In conclusion, we found independent associations of the rMED and of the GCKR genotype with cardiometabolic profile, but found no evidence of interaction between them.
In the present study, we investigated the association between dietary intake of carbohydrates and the risk of type 2 diabetes. Incident cases of diabetes (n 749) were identified and compared with a randomly selected subcohort of 3496 participants aged 40–79 years. For dietary assessment, we used 7 d food diaries administered at baseline. We carried out modified Cox proportional hazards regression analyses and compared results obtained from the different methods of adjustment for total energy intake. Dietary intakes of total carbohydrates, starch, sucrose, lactose or maltose were not significantly related to diabetes risk after adjustment for confounders. However, in the residual method for energy adjustment, intakes of fructose and glucose were inversely related to diabetes risk. The multivariable-adjusted hazard ratios (HR) of diabetes comparing the extreme quintiles of intake were 0·79 (95 % CI 0·59, 1·07; P for trend = 0·03) for glucose and 0·62 (95 % CI 0·46, 0·83; P for trend = 0·01) for fructose. In the nutrient density method, only fructose was inversely related to diabetes risk (HR 0·65, 95 % CI 0·48, 0·88). The replacement of 5 % energy intake from SFA with an isoenergetic amount of fructose was associated with a 30 % lower diabetes risk (HR 0·69, 95 % CI 0·50, 0·96). Results of the standard and energy partition methods were similar to those of the residual method. These prospective findings suggest that the intakes of starch and sucrose are not associated, but that those of fructose and glucose are inversely associated with diabetes risk. Whether the inverse associations with fructose and glucose reflect the effect of substitution of these carbohydrate subtypes with other nutrients (i.e. SFA), their net higher intake or other nutrients associated with their intake remains to be established through further investigation.
Fish consumption is the major dietary source of EPA and DHA, which according to rodent experiments may reduce body fat mass and prevent obesity. However, human studies have suggested that fish consumption has no appreciable association with body-weight gain. We investigated the associations between fish consumption and subsequent change in waist circumference. Sex, age and waist circumference at enrolment were considered as potential effect modifiers. Women and men (n 89 432) participating in the European Prospective Investigation into Cancer and Nutrition (EPIC) were followed for a median of 5·5 years. Mixed-effect linear regression was used to investigate the associations between fish consumption and subsequent change in waist circumference. Among all participants, the average annual change in waist circumference was − 0·01 cm/10 g higher total fish consumption per d (95 % CI − 0·01, 0·00) and − 0·01 cm/10 g higher fatty fish consumption per d (95 % CI − 0·02, − 0·01), after adjustment for potential confounders. Lean fish consumption was not associated with change in waist circumference. Adjustment for potential over- or underestimation of fish consumption measurements did not systematically change the observed associations, but the 95 % CI became slightly wider. The results in subgroups from analyses stratified by sex, age or waist circumference at enrolment were not systematically different. In conclusion, the present study suggests that fish consumption does not prevent increase in waist circumference.
Phyto-oestrogens have been associated with a decreased risk for osteoporosis, but results from intervention and observational studies in Western countries have been inconsistent. In the present study, we investigated the association between habitual phyto-oestrogen intake and broadband ultrasound attenuation (BUA) of the calcanaeum as a marker of bone density. We collected 7 d records of diet, medical history and demographic and anthropometric data from participants (aged 45–75 years) in the European Prospective Investigation into Cancer-Norfolk study. Phyto-oestrogen (biochanin A, daidzein, formononetin; genistein, glycitein; matairesinol; secoisolariciresinol; enterolactone; equol) intake was determined using a newly developed food composition database. Bone density was assessed using BUA of the calcanaeum. Associations between bone density and phyto-oestrogen intake were investigated in 2580 postmenopausal women who were not on hormone replacement therapy and 4973 men. Median intake of total phyto-oestrogens was 876 (interquartile range 412) μg/d in postmenopausal women and 1212 (interquartile range 604) μg/d in men. The non-soya isoflavones formononetin and biochanin A were marginally significant or significantly associated with BUA in postmenopausal women (β = 1·2; P < 0·1) and men (β = 1·2; P < 0·05), respectively; enterolignans and equol were positively associated with bone density in postmenopausal women, but this association became non-significant when dietary Ca was added to the model. In the lowest quintile of Ca intake, soya isoflavones were positively associated with bone density in postmenopausal women (β = 1·4; P < 0·1). The present results therefore suggest that non-soya isoflavones are associated with bone density independent of Ca, whereas the association with soya or soya isoflavones is affected by dietary Ca.
Uptake of advice for lifestyle change for obesity and diabetes prevention requires access to affordable ‘healthy’ foods (high in fibre/low in sugar and fat). The present study aimed to examine the availability and accessibility of ‘healthy’ foods in rural and urban New Zealand.
We identified and visited (‘mapped’) 1230 food outlets (473 urban, 757 rural) across the Waikato/Lakes areas (162 census areas within twelve regions) in New Zealand, where the Te Wai O Rona: Diabetes Prevention Strategy was underway. At each site, we assessed the availability of ‘healthy’ foods (e.g. wholemeal bread) and compared their cost with those of comparable ‘regular’ foods (e.g. white bread).
Healthy foods were generally more available in urban than rural areas. In both urban and rural areas, ‘healthy’ foods were more expensive than ‘regular’ foods after adjusting for the population and income level of each area. For instance, there was an increasing price difference across bread, meat, poultry, with the highest difference for sugar substitutes. The weekly family cost of a ‘healthy’ food basket (without sugar) was 29·1 % more expensive than the ‘regular’ basket ($NZ 176·72 v. $NZ 136·84). The difference between the ‘healthy’ and ‘regular’ basket was greater in urban ($NZ 49·18) than rural areas ($NZ 36·27) in adjusted analysis.
‘Healthy’ foods were more expensive than ‘regular’ choices in both urban and rural areas. Although urban areas had higher availability of ‘healthy’ foods, the cost of changing to a healthy diet in urban areas was also greater. Improvement in the food environment is needed to support people in adopting healthy food choices.
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