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Cardiovascular disease and its concurrent risk factors are prevalent after liver transplant (LT). Most of these risk factors are modifiable by diet. We aimed to synthesise the literature reporting the nutritional intake of liver transplant recipients (LTR) and the potential determinants of intake. We performed a systematic review and meta-analyses of studies published up until July 2021 reporting the nutritional intake of LTR. The pooled daily mean intakes were recorded as 1998 (95% CI 1889, 2108) kcal, 17 (17, 18)% energy from protein, 49 (48, 51)% energy from carbohydrates, 34 (33, 35)% energy from total fat, 10 (7, 13)% energy from saturated fat, and 20 (18, 21) g of fibre. The average fruit and vegetable intake ranged from 105 to 418 g/day. The length of time post-LT and the age and sex of the cohorts, as well as the continent and year of publication of each study, were sources of heterogeneity. Nine studies investigated the potential determinants of intake, time post-LT, gender and immunosuppression medication, with inconclusive results. Energy and protein requirements were not met in the first month post-transplant. After this point, energy intake was significantly higher and remained stable over time, with a high fat intake and low intake of fibre, fruits and vegetables. This suggests that LTR consume a high-energy, low-quality diet in the long term and do not adhere to the dietary guidelines for cardiovascular disease prevention.

BACKGROUND The COVID-19 pandemic accelerated the interest in implementing mobile health (mHealth) in population-based health studies, but evidence is lacking on engagement and adherence in studies. We conducted a fully remote study for ≥6 months tracking COVID-19 digital biomarkers and symptoms using a smartphone app nested within an existing cohort of adults. OBJECTIVE We aimed to investigate participant characteristics associated with initial and sustained engagement in digital biomarker collection from a bespoke smartphone app and if engagement changed over time or because of COVID-19 factors and explore participants’ reasons for consenting to the smartphone substudy and experiences related to initial and continued engagement. METHODS Participants in the Fenland COVID-19 study were invited to the app substudy from August 2020 to October 2020 until study closure (April 30, 2021). Participants were asked to complete digital biomarker modules (oxygen saturation, body temperature, and resting heart rate [RHR]) and possible COVID-19 symptoms in the app 3 times per week. Participants manually entered the measurements, except RHR that was measured using the smartphone camera. Engagement was categorized by median weekly frequency of completing the 3 digital biomarker modules (categories: 0, 1-2, and ≥3 times per week). Sociodemographic and health characteristics of those who did or did not consent to the substudy and by engagement category were explored. Semistructured interviews were conducted with 35 participants who were purposively sampled by sex, age, educational attainment, and engagement category, and data were analyzed thematically; 63% (22/35) of the participants consented to the app substudy, and 37% (13/35) of the participants did not consent. RESULTS A total of 62.61% (2524/4031) of Fenland COVID-19 study participants consented to the app substudy. Of those, 90.21% (2277/2524) completed the app onboarding process. Median time in the app substudy was 34.5 weeks (IQR 34-37) with no change in engagement from 0 to 3 months or 3 to 6 months. Completion rates (≥1 per week) across the study between digital biomarkers were similar (RHR: 56,517/77,664, 72.77%; temperature: 56,742/77,664, 73.06%; oxygen saturation: 57,088/77,664, 73.51%). Older age groups and lower managerial and intermediate occupations were associated with higher engagement, whereas working, being a current smoker, being overweight or obese, and high perceived stress were associated with lower engagement. Continued engagement was facilitated through routine and personal motivation, and poor engagement was caused by user error and app or equipment malfunctions preventing data input. From these results, we developed key recommendations to improve engagement in population-based mHealth studies. CONCLUSIONS This mixed methods study demonstrated both high initial and sustained engagement in a large mHealth COVID-19 study over a ≥6-month period. Being nested in a known cohort study enabled the identification of participant characteristics and factors associated with engagement to inform future applications in population-based health research.

Introduction The ability to collect blood samples remotely without the involvement of healthcare professionals is a key element of future telehealth applications. We developed and validated the application of the Drawbridge OneDraw device for use at home for blood sample collection. The device was then applied in a large population-based remote monitoring study to assess changes in SARS-CoV-2 IgG antibody levels. Methods We tested: (1) feasibility of participants using the device at home without a healthcare professional on the upper arm and thigh sites (2) stability of the dried blood sample collected remotely (3) participant acceptability of the device compared with finger-prick and venous blood samples and the validity of SARS-CoV-2 virus antibody measurement versus venous blood sample (4) application to the Fenland COVID-19 study in which 4023 participants at 3 timepoints across 6 months. Results Participant acceptability was high, with a significantly lower median perceived pain score and 76% of participants preferring the OneDraw device over the other blood collection methods. There was high level of agreement in SARS-CoV-2 virus antibody results with venous blood samples in 120 participants (Cohen's kappa 0.68 (95% CI 0.56, 0.83). In the Fenland COVID-19 study, 92% of participants returned a sample at baseline (3702/4023), 89% at 3 months (3492/3918) and 93% at 6 months (3453/3731), with almost all samples received successfully processed (99.9%). Discussion The OneDraw device enables a standardised blood sample collection at home by participants themselves. Due to its ease-of-use and acceptability the OneDraw device is particularly useful in telehealth approaches where multiple samples need to be collected.

International audience; Background: Risk prediction tools are lacking for patients with stable disease some years after myocardial infarction (MI).Hypothesis: A practical long‐term cardiovascular risk index can be developed.Methods: The long‐Term rIsk, Clinical manaGement and healthcare Resource utilization of stable coronary artery dISease in post‐myocardial infarction patients prospective global registry enrolled patients 1 to 3 years post‐MI (369 centers; 25 countries), all with ≥1 risk factor (age ≥65 years, diabetes mellitus requiring medication, second prior MI, multivessel coronary artery disease, or chronic non‐end‐stage kidney disease [CKD]). Self‐reported health was assessed with EuroQoL‐5 dimensions. Multivariable Poisson regression models were used to determine key predictors of the primary composite outcome (MI, unstable angina with urgent revascularization [UA], stroke, or all‐cause death) over 2 years.Results: The primary outcome occurred in 621 (6.9%) of 9027 eligible patients: death 295 (3.3%), MI 195 (2.2%), UA 103 (1.1%), and stroke 58 (0.6%). All events accrued linearly. In a multivariable model, 11 significant predictors of primary outcome (age ≥65 years, diabetes, second prior MI, CKD, history of major bleed, peripheral arterial disease, heart failure, cardiovascular hospitalization (prior 6 months), medical management (index MI), on diuretic, and poor self‐reported health) were identified and combined into a user‐friendly risk index. Compared with lowest‐risk patients, those in the top 16% had a rate ratio of 6.9 for the primary composite, and 18.7 for all‐cause death (overall c‐statistic; 0.686, and 0.768, respectively). External validation was performed using the Australian Cooperative National Registry of Acute Coronary Care, Guideline Adherence and Clinical Events registry (c‐statistic; 0.748, and 0.849, respectively).Conclusions: In patients >1‐year post‐MI, recurrent cardiovascular events and deaths accrue linearly. A simple risk index can stratify patients, potentially helping to guide management.

Background Cotinine, a nicotine metabolite, is used to measure tobacco use and exposure, but recommended cut-offs to differentiate tobacco users from those exposed through the environment range from 3 to 58 ng/ml in serum, and 2.5 to 550 ng/ml in urine. Cut-offs may differ by ethnicity, sex and age. As data from adults in Africa are scarce, our aim was to evaluate cut-offs for serum and urine cotinine that best predict self-reported tobacco use in South African adults. Methods Two datasets were explored: African-PREDICT (n = 941 black and white healthy young adults, 20–30 years, serum cotinine); and WHO SAGE Wave 2 (n = 604 adults, 18–102 years, urine cotinine). Population specific cut-offs (ROC analyses) were compared with published cut-offs and self-reported tobacco use. Results Overall, 19% (293 of 1545) reported current tobacco use. The following cotinine cut-offs showed the highest sensitivity and specificity: serum ≥15 ng/ml in black and white men, and white women; serum ≥10 ng/ml in black women; urine ≥300 ng/ml for black, mixed ancestry, and older adults (50-plus years); urine ≥500 ng/ml for younger adults (18–49 years). Specificity was lower for urine than for serum cotinine. Conclusion Our study suggests that a serum cotinine level of ≥15 ng/ml and a urine cotinine level of ≥300 ng/ml best distinguish current tobacco users from non-users generally in the South African adult population.

Childhood obesity is an area of intense concern internationally and is influenced by events during antenatal and postnatal life. Although pregnancy complications, such as gestational diabetes and large-for-gestational-age birthweight have been associated with increased obesity risk in offspring, very few successful interventions in pregnancy have been identified. We describe a study protocol to identify if a reduced calorie diet in pregnancy can reduce adiposity in children to 3 years of age. The dietary intervention in gestational diabetes (DiGest) study is a randomised, controlled trial of a reduced calorie diet provided by a whole-diet replacement in pregnant women with gestational diabetes. Women receive a weekly dietbox intervention from enrolment until delivery and are blinded to calorie allocation. This follow-up study will assess associations between a reduced calorie diet in pregnancy with offspring adiposity and maternal weight and glycaemia. Anthropometry will be performed in infants and mothers at 3 months, 1, 2 and 3 years post-birth. Glycaemia will be assessed using bloodspot C-peptide in infants and continuous glucose monitoring with HbA1c in mothers. Data regarding maternal glycaemia in pregnancy, maternal nutrition, infant birthweight, offspring feeding behaviour and milk composition will also be collected. The DiGest follow-up study is expected to take 5 years, with recruitment finishing in 2026.

AimsResting heart rate (RHR) is inversely associated with cardiorespiratory fitness (CRF) but few studies have investigated the nature of this relationship in large population samples. We examined the association between RHR and CRF in UK adults and explored factors that may influence this relationship.Methods and ResultsIn a population-based sample of 5,143 men and 5,722 women (aged 29-65 years), mean (SD) RHR while seated, supine, and during sleep was 67.6 (9.8), 63.5 (8.9), and 56.9 (6.9) bpm, respectively. The age- and sex-adjusted association with CRF as assessed by submaximal treadmill testing was −0.26 (95%CI −0.27; −0.24), −0.31 (95%CI −0.33; −0.29), and −0.31 (95%CI −0.34; −0.29) ml O2 kg-1 beat-1. Sequential adjustment for objectively measured obesity and physical activity attenuated the RHR coefficient by 10% and 50%, respectively. In longitudinal analyses of 6,589 participants re-examined after 6 years, each 1 bpm increase in supine RHR was associated with 0.23 (95%CI 0.20; 0.25) ml O2 min-1 kg-1 decrease in CRF.ConclusionsAcross all measures, RHR is inversely associated with CRF; half of this association is explained by obesity and physical activity, suggesting CRF changes achieved through altered behaviour could be tracked through changes in RHR, a notion supported by longitudinal results. As well as its utility as a biomarker of CRF at population-level, serial measurements of RHR may facilitate personal goal setting/evaluation and remote patient monitoring.

Funder: Wellcome Trust, Gestational diabetes mellitus (GDM) annually affects 35,000 pregnancies in the United Kingdom, causing suboptimal health outcomes to the mother and child. Obesity and excessive gestational weight gain are risk factors for GDM. The Institute of Medicine recommends weight targets for women that are overweight and obese, however, there are no clear guidelines for women with GDM. Observational data suggest that modest weight loss (0.6-2 kg) after 28 weeks may reduce risk of caesarean section, large-for-gestational-age (LGA), and maternal postnatal glycaemia. This protocol for a multicentre randomised double-blind controlled trial aims to identify if a fully controlled reduced energy diet in GDM pregnancy improves infant birthweight and reduces maternal weight gain (primary outcomes). A total of 500 women with GDM (National Institute of Health and Care Excellence (NICE) 2015 criteria) and body mass index (BMI) ≥25 kg/m2 will be randomised to receive a standard (2000 kcal/day) or reduced energy (1200 kcal/day) diet box containing all meals and snacks from 28 weeks to delivery. Women and caregivers will be blinded to the allocations. Food diaries, continuous glucose monitoring, and anthropometry will measure dietary compliance, glucose levels, and weight changes. Women will receive standard antenatal GDM management (insulin/metformin) according to NICE guidelines. The secondary endpoints include caesarean section rates, LGA, and maternal postnatal glucose concentrations.

BACKGROUND: Evidence is lacking on long-term outcomes in unselected patients surviving the first year following myocardial infarction (MI). METHODS AND RESULTS: The TIGRIS (long-Term rIsk, clinical manaGement and healthcare Resource utilization of stable coronary artery dISease in post-myocardial infarction patients) prospective registry enrolled 9176 eligible patients aged ≥50 years, 1-3 years post-MI, from 25 countries. All had ≥1 risk factor: age ≥ 65 years, diabetes mellitus, second prior MI, multivessel coronary artery disease, chronic kidney disease (CKD). Primary outcome was a composite of MI, unstable angina with urgent revascularization, stroke, or all-cause death at 2-year follow-up. Bleeding requiring hospitalization was also recorded. 9027 patients (98.4%) provided follow-up data: the primary outcome occurred in 621 (7.0%), all-cause mortality in 295 (3.3%), and bleeding in 109 (1.2%) patients. Events accrued linearly over time. In multivariable analyses, qualifying risk factors were associated with increased risk of primary outcome (incidence rate ratio [RR] per 100 patient-years [95% confidence interval]): CKD 2.06 (1.66, 2.55), second prior MI 1.71 (1.38, 2.10), diabetes mellitus 1.63 (1.39, 1.92), age ≥ 65 years 1.53 (1.28, 1.83), and multivessel disease 1.24 (1.05, 1.48). Risk of bleeding events was greater in older patients (vs

Summary Background & aims There is currently no consensus on which measure of height should be used in older people's body mass index (BMI) calculation. Most estimates of nutritional status include a measurement of body weight and height which should be reliable and accurate, however at present several different methods are used interchangeably. BMI, a key marker in malnutrition assessment, does not reflect age-related changes in height or changes in body composition such as loss of muscle mass or presence of oedema. The aim of this pilot study was to assess how the use of direct and surrogate measures of height impacts on BMI calculation in people aged ≥75 years. Methods A cross-sectional study of 64 free-living older people (75–96 yrs) quantified height by two direct measurements, current height (HC), and self-report (HR) and surrogate equations using knee height (HK) and ulna length (HU). BMI calculated from current height measurement (BMIC) was compared with BMI calculated using self-reported height (BMIR) and height estimated from surrogate equations for knee height (BMIK) and ulna length (BMIU). Results Median difference of BMIC–BMIR was 2.31 kg/m2. BMIK gave the closest correlation to BMIC. The percentage of study participants identified at increased risk of under-nutrition (BMI Conclusions The results of this pilot study in a relatively healthy sample of older people suggest that interchangeable use of current and reported height in people ≥75 years can introduce substantial significant systematic error. This discrepancy could impact nutritional assessment of older people in poor health and lead to misclassification during nutritional screening if other visual and clinical clues are not taken into account. This could result in long-term clinical and cost implications if individuals who need nutrition support are not correctly identified. A consensus is required on which method should be used to quantify height in older people to improve accuracy of nutritional assessment and clinical care.

To assess the 5-year progression of erosions and joint space narrowing (JSN) and their associations with rheumatoid factor (RF) status in 2 large, multicenter, early rheumatoid arthritis cohorts, spanning 25 years.Radiographic joint damage was recorded using the Sharp/van der Heijde (SHS) method in the Early Rheumatoid Arthritis Study (ERAS), 1986-2001, and the Early Rheumatoid Arthritis Network (ERAN), 2002-2013. Mixed-effects negative binomial regression estimated changes in radiographic damage over 5 years, including erosions and JSN, separately. RF, along with age, sex, and baseline markers of disease activity were controlled for.A total of 1,216 patients from ERAS and 446 from ERAN had radiographic data. Compared to ERAS, ERAN patients had a lower mean total SHS score at baseline (ERAN 6.2 versus ERAS 10.5; P0.001) and mean annual rate of change (ERAN 2.5 per year versus ERAS 6.9 per year; P0.001). Seventy-four percent of ERAS and 27% of ERAN patients progressed ≥5 units. Lower scores at baseline in ERAN were largely driven by reductions in JSN (ERAS 3.9 versus ERAN 1.2; P0.001), along with erosions (ERAS 1.9 versus ERAN 0.8; P0.001). RF was associated with greater progression in each cohort, but the absolute difference in mean annual rate of change for RF-positive patients was substantially higher for ERAS (RF positive 8.6 versus RF negative 5.1; P0.001), relative to ERAN (RF positive 2.0 versus RF negative 1.9; P = 0.855).Radiographic progression was shown to be significantly reduced between the 2 cohorts, and was associated with lower baseline damage and other factors, including changes in early disease-modifying antirheumatic drug use. The impact of RF status as a prognostic marker of clinically meaningful change in radiographic progression has markedly diminished in the context of more modern treatment.

Objective. To evaluate, firstly, all published data on baseline and annual progression rates of radiographic damage from all longitudinal observational cohorts, and secondly, the association of standard clinical and laboratory parameters with long-term radiographic joint damage. Methods. A comprehensive search of the literature from 1975 to 2014, using PubMed, SCOPUS and Cochrane databases, identified a total of 28 studies that investigated long-term radiographic progression, and 41 studies investigating predictors of long-term radiographic progression. This was submitted and approved by PROSPERO in February 2014 (Registration Number: CRD42014007589). Results. Meta-analysis indicated an overall baseline rate of 2.02%, and a yearly increase of 1.08% of maximum damage. Stratified analysis found that baseline radiographic scores did not differ significantly between cohorts recruiting patients pre- and post-1990 (2.01% vs 2.03%; P > 0.01); however, the annual rate of progression was significantly reduced in the post-1990 cohorts (0.68% vs 1.50%; P < 0.05). High levels of acute phase markers, baseline radiographic damage, anti-CCP and RF positivity remain consistently predictive of long-term radiographic joint damage. Conclusion. Critical changes in treatment practices over the last three decades are likely to explain the reduction in the long-term progression of structural joint damage. Acute phase markers and presence of RF/anti-CCP are strongly associated with increased radiographic progression.

The authors would like to correct an error in a recent published paper [...]

To determine optimal body mass index (BMI) cut-points for the identification of cardiometabolic risk in black South African adults. We performed a cross-sectional study of a weighted sample of healthy black South Africans aged 25–65 years (721 men, 1386 women) from the North West and Free State Provinces. Demographic, lifestyle and anthropometric measures were taken, and blood pressure, fasting serum triglycerides, high-density lipoprotein (HDL) cholesterol and blood glucose were measured. We defined elevated cardiometabolic risk as having three or more risk factors according to international metabolic syndrome criteria. Receiver operating characteristic curves were applied to identify an optimal BMI cut-point for men and women. BMI had good diagnostic performance to identify clustering of three or more risk factors, as well as individual risk factors: low HDL-cholesterol, elevated fasting glucose and triglycerides, with areas under the curve >.6, but not for high blood pressure. Optimal BMI cut-points averaged 22 kg/m2 for men and 28 kg/m2 for women, respectively, with better sensitivity in men (44.0–71.9 %), and in women (60.6–69.8 %), compared to a BMI of 30 kg/m2 (17–19.1, 53–61.4 %, respectively). Men and women with a BMI >22 and >28 kg/m2, respectively, had significantly increased probability of elevated cardiometabolic risk after adjustment for age, alcohol use and smoking. In black South African men, a BMI cut-point of 22 kg/m2 identifies those at cardiometabolic risk, whereas a BMI of 30 kg/m2 underestimates risk. In women, a cut-point of 28 kg/m2, approaching the WHO obesity cut-point, identifies those at risk.

Global data on use of evidence-based medical (EBM) therapies following myocardial infarction (MI) are rare. Therefore, we investigated regional differences in EBM therapy use and its association with CV death in patients >1 year post MI. The TIGRIS prospective global registry ([NCT01866904][1])

Nutrition labelling is an important strategic approach for encouraging consumers to make healthier food choices. The availability of highly palatable foods labelled as 'low fat or reduced calorie' may encourage the over-consumption of these products. This study aimed to determine whether the manipulation of nutrition labelling information can influence food portion size consumption. Normal and overweight men (n=24) and women (n=23) were served an identical lunch meal on three separate days, but the information they received prior to consuming the lunch meal was manipulated as follows: "baseline", "high fat/energy" and "low fat/energy". Food and energy intake was significantly increased in the low fat/energy condition compared with both baseline and the high fat/energy condition. An additional 3% (162 kJ) energy was consumed by subjects under the low fat/energy condition compared to baseline. No differences were observed between the baseline and high fat/energy condition. Subjects who consumed most in the low fat/energy condition were found to be mostly men, to have a higher BMI and to be overweight. Low fat/energy information can positively influence food and energy intake, suggesting that foods labelled as 'low fat' or 'low calorie' may be one factor promoting the consumption of large food portions.

ObjectiveThe predominance of marketing of products high in fat, sugar and/or salt to children has been well documented and implicated in the incidence of obesity. The present study aimed to determine whether foods marketed to children in UK supermarkets are nutritionally similar to the non-children's equivalent, focusing on food categories that may be viewed as healthier options.DesignNutritional data were collected on yoghurts (n 147), cereal bars (n 145) and ready meals (n 144) from seven major UK supermarkets and categorised as children's or non-children's products based on the characteristics, promotional nature or information on the product packaging. Fat, sugar and salt content was compared per 100 g and per recommended portion size.SettingUK.ResultsPer 100 g, children's yoghurts and cereal bars were higher in total sugars, fat and saturated fat than the non-children's; this was significant for all except sugar and total fat in cereal bars. Per portion these differences remained, except for sugars in yoghurts. Conversely children's ready meals were significantly lower in these nutrients per portion than non-children's, but not when expressed per 100 g. Children's yoghurts and ready meals had significantly lower sodium content than non-children's both per portion and per 100 g.ConclusionsSignificant differences between the nutritional composition of children's and non-children's products were observed but varied depending on the unit reference. A significant number of products marketed towards children were higher in fat, sugar and salt than those marketed to the general population.

National survey data show that reported energy intake has decreased in recent decades despite a rise in the prevalence of obesity. This disparity may be due to a secular increase in under-reporting or a quantitatively greater decrease in energy expenditure. This study examines the extent of under-reporting of energy intake in the National Diet and Nutrition Survey (NDNS) in young people aged 4–18 years in 1997 using published equations to calculate estimated energy requirements. It explores secular changes by comparison with the Diets of British School Children (DBSC) survey in 10–11- and 14–15-year-olds in 1983. In the NDNS, under-reporting (estimated energy requirements – energy intake) represented 21 % of energy needs in girls and 20 % in boys. The magnitude of under-reporting increased significantly with age (P

Introduction Objective methods like accelerometers are feasible for large studies and may quantify variability in day-to-day physical activity better than self-report. The variability between days suggests that day of the week cannot be ignored in the design and analysis of physical activity studies. The purpose of this paper is to investigate the optimal number of days needed to obtain reliable estimates of weekly habitual physical activity using the wrist-worn GENEActiv accelerometer. Methods Data are from a subsample of the Mitchelstown cohort; 475 (44.6% males; mean aged 59.6±5.5 years) middle-aged Irish adults. Participants wore the wrist GENEActiv accelerometer for 7-consecutive days. Data were collected at 100Hz and summarised into a signal magnitude vector using 60s epochs. Each time interval was categorised according to intensity based on validated cut-offs. Spearman pairwise correlations determined the association between days of the week. Repeated measures ANOVA examined differences in average minutes across days. Intraclass correlations examined the proportion of variability between days, and Spearman-Brown formula estimated intra-class reliability coefficient associated with combinations of 1–7 days. Results Three hundred and ninety-seven adults (59.7±5.5yrs) had valid accelerometer data. Overall, men were most sedentary on weekends while women spent more time in sedentary behaviour on Sunday through Tuesday. Post hoc analysis found sedentary behaviour and light activity levels on Sunday to differ to all other days in the week. Analysis revealed greater than 1 day monitoring is necessary to achieve acceptable reliability. Monitoring frame duration for reliable estimates varied across intensity categories, (sedentary (3 days), light (2 days), moderate (2 days) and vigorous activity (6 days) and MVPA (2 days)). Conclusion These findings provide knowledge into the behavioural variability in weekly activity patterns of middle-aged adults. Since Sunday differed from all other days in the week this suggests that day of the week cannot be overlooked in the design and analysis of physical activity studies and thus should be included in the study monitoring frames. Collectively our data suggest that six days monitoring, inclusive of Saturday and Sunday, are needed to reliably capture weekly habitual activity in all activity intensities using the wrist-worn GENEActiv accelerometer.

While South Africa has one of the highest hypertension rates globally, there are few data on masked hypertension (MHT) and white‐coat hypertension (WCHT). This study measured the frequency of MHT and WCHT in low‐income (

To examine the influence of location on snack intake among Northern Ireland (NI) children aged 5-8 years.Dietary intake was assessed by 7-day weighed dietary records. Parents/children self defined type (meal/snack) and location of eating occasions. Locations were grouped as 'Home' or 'Out of home' (inclusive of school). Children (5-8 years; n=113) were recruited through primary schools in the Coleraine area of NI.Snacks consumed at home contributed 20% to total energy intake (TEI), while out of home snacking accounted for 7% of TEI. Snack food choice was markedly similar in and out of home with sugar confectionery, milks and cakes ranked as the top three choices. Foods contributing significantly more to out of home snack food consumption than to home snack food consumption were milks and dairy products (P0.001), cakes and buns (P=0.001), crisps and savory snacks (P0.001) and sugar confectionery (P=0.01). Portion sizes of snacks consumed out of home were generally higher than that at home, significantly so in the case of milks and non-diet carbonated soft drinks (P0.01, both cases).The current study shows the key importance of the home as the main location for snacking among children aged 5-8 years, albeit that snack food choices both in and out of home were remarkably similar, and portion sizes of out of home snacks generally higher. Given the evidence that dietary behavior tracks from a young age, implementing healthy snacking behavior among primary school-aged children, particularly within the home environment, should be a priority.

Objective. To investigate geographic differences in obesity related metabolic abnormalities in middle-aged and older Chinese people with different levels of adiposity. Method. Data from 3289 individuals aged 50-70 years who participated in a cross-sectional survey in 2005 (1641 from northern [Beijing] and 1648 from southern [Shanghai] China) were analyzed. Overweight or obesity and abdominal obesity were classified as body mass index >= 24 kg/m(2) and waist circumference >= 90 cm for men and >= 80 cm for women. Metabolic abnormalities (metabolic syndrome, dyslipidemia, hypertension and diabetes) were defined using the NCEP/ATPIII criteria. Results. The overall prevalence of overweight and obesity was 53.4%, and the prevalence of abdominal obesity was 48.0%, respectively. The prevalence of the metabolic abnormalities was significantly higher among obese individuals than their normal weight counterparts. The association between obesity and the higher prevalence of the metabolic abnormalities was more pronounced among people who were overweight or obese in the north, especially for those living in rural areas. Conclusion. The prevalence of obesity and associated metabolic abnormalities varies substantially among Chinese people in different geographic region. Individuals who were overweight or obese living in rural areas in the north contribute importantly to the north-south differences in obesity-related metabolic abnormalities among Chinese populations. (C) 2009 Elsevier Inc. All rights reserved.

There is increasing concern that high intakes of added sugars promote micronutrient dilution. However, the overall conclusion to emerge from the existing evidence base is that associations between reported intakes of added sugars and intakes of micronutrients are inconsistent and often non-linear, both across and within age groups, and between the genders. If a nutrient displacement effect does exist, a high consumption of added sugar does not necessarily compromise overall micronutrient intakes and similarly, consuming less added sugar is no guarantee that micronutrient intakes will be optimized. Clarification of this issue has been beset by methodological and conceptual difficulties. The observed associations between added sugars and micronutrient intake have been heavily contingent on both the definition of sugars chosen and the analytical approach used for adjusting for differences in reported energy intake. These issues have been further compounded by mis-reporting of food intake of unknown direction and magnitude and the cut-offs used to determine 'inadequate' micronutrient intakes which vary over time and between studies and countries. In the absence compelling evidence that micronutrient intakes are compromised by a high consumption of added sugars, it may now be appropriate to question the legitimacy of the nutrient dilution hypothesis as it is highly likely that it is oversimplifying more subtle and complex dietary issues. Recommendations for further research are made to help bring resolution to these issues.

Despite the potential link between snack food intake and obesity and the reportedly high prevalence of snacking among adolescents, adolescent snack food patterns (types of foods consumed, frequency and portion size) have not been extensively examined. This study examines these issues using data on the snacking patterns of adolescents aged 13–16 years who took part in the 1997 National Diet and Nutrition Survey (NDNS) and that from a Northern Irish (NI) cohort of adolescents collected 8 years later, in 2005. Overall energy intake was significantly higher in the NI adolescents in 2005 compared with the NDNS adolescents in 1997 (P P v. 29·8 %, respectively). Sugar-sweetened carbonated and soft drinks remained the most popular choice of snack over this 8-year period; however, both the portion size consumed and frequency of consumption were significantly higher among the adolescents in 2005 compared with those in 1997 (P = 0·022 and P = 0·014, respectively). Despite the lower popularity, and correspondingly lower frequency of milks and beverages, the portion size of both food groups was significantly higher among the adolescents in 2005 compared with those in 1997 (P P = 0·007, respectively). These findings may provide scope for policy interventions to place particular emphasis on reducing typical portion sizes consumed of popular snack choices, in particular high-energy carbonated and soft drinks, among UK adolescents.

The aim of this study was to assess the capability of the 3dNX accelerometer to predict energy expenditure in two separate, free-living cohorts. Twenty-three adolescents and 14 young adults took a single dose of doubly labelled water and wore a 3dNX activity monitor during waking hours for a 10-day period while carrying out their normal routines. Multiple linear regression with backward elimination was used to establish the strength of the associations between various indices of energy expenditure, physical activity counts, and anthropometric variables. 3dNX output accounted for 27% and 35% of the variance in the total energy expenditure of the adolescent and young adult cohort, respectively. The explained variance increased to 78%, with a standard error of estimate of 7%, when 3dNX output was combined with body composition variables. The 3dNX accelerometer can be used to predict free-living daily energy expenditure with a standard error of estimate of 1.65 MJ in adolescents and 1.52 MJ in young adults. The inclusion of anthropometric variables reduces the error to approximately 1 MJ. Although it remains to cross-validate these models in other populations, early indications suggest that the 3dNX provides a useful method of predicting energy expenditure in free-living individuals.

Background: Few studies have investigated differences in bone health and associated lifestyle factors between urban and rural populations in countries, such as China, undergoing rapid nutrition transition. Such a study may help to identify risk factors of osteoporosis and provide evidence for future preventive strategies. Objective: To determine primarily whether differences in bone mineral content (BMC) and bone mineral density (BMD) exist between urban and rural Chinese men and women and secondly whether any urban–rural differences could be explained by body size or lifestyle factors. Methods: In total, 490 men and 689 women aged 50–70 were included in the study. 535 of them were from urban Shanghai and 644 from surrounding rural areas. Anthropometric measurements were conducted and spine lumber 1–4 BMC measurements were determined by dualenergy X-ray absorptiometry (DEXA). Information on socioeconomic status, medical history, smoking and drinking habits and physical activity were collected. Results: Urban men and women had significantly higher spine BMC, BMD and bone area than their rural counterparts (Pb0.01). After controlling body size, the differences between urban–rural spine BMC and BMD remained in women (Pb0.001), but were no longer significant in men. The urban and rural differences of BMC and BMD in women could not be explained by including the lifestyle factors such as income, intake of milk, vitamin D and calcium, total physical activity level, walking and social activity. Conclusion: This study found the significant differences in both spine BMC and BMD between urban and rural men and women in Shanghai, China. This difference could be explained by the body size in men; however, it remained unexplained in women after adjusting for body size and certain lifestyle risk factors.

Under-reporting (UR) of energy intake (EI) by self-reported dietary methods is well-documented but the methods used to estimate UR in population-based studies commonly assume a sedentary lifestyle. We compared estimated UR using individualised estimates of energy requirements with a population cut-off based on minimum energy needs. UR was estimated for 1551 adults aged 19–64 years enrolled in the National Diet and Nutrition Survey. Physical activity diaries and 7 d weighed dietary records were completed concurrently. Mean daily EI (kJ/d) was calculated from the dietary records. Reported physical activity was used to assign each subject's activity level, and then to calculate estimated energy requirements (EER) from published equations. UR was calculated both as EER – EI with an adjustment for daily EER and EI variation, and also by a population method. By the individual method UR was approximately 27 % of energy needs in men and 29 % in women, with 75 % of men and 77 % of women classified as under-reporters; by the population method 80 and 88 % were classified as under-reporters respectively. When subjects who reported their eating being affected by dieting or illness during dietary recording were excluded, UR was 25 % of energy needs in both sexes. UR was higher in overweight and obese men and women compared with their lean counterparts (P

There is increasing concern that high intakes of added sugars might compromise intakes of micronutrients. The objectives of this systematic review were (1) to determine whether dietary added sugar intake was associated with micronutrient intakes, and if so, whether there was evidence of micronutrient dilution as a result of higher dietary added sugar intake and (2) if micronutrient dilution was present, to determine whether there was sufficiently robust evidence to support a threshold effect above which there was a significant decline in micronutrient intake or status relative to the recommended intakes. A systematic computerised literature search was undertaken, limited to studies written in English published from 1980 onwards and further studies identified through hand searching papers. Fifteen studies that assessed associations between intakes of added sugars or non-milk extrinsic sugars and micronutrients were included. Overall, there are insufficient data and inconsistency between studies in relationships between added sugars and micronutrient intakes, with no clear evidence of micronutrient dilution or a threshold for a quantitative amount of added sugar intake for any of the micronutrients investigated. The current evidence base is considerably constrained by methodological issues. Further research is required to determine which food products high in added sugars might adversely affect micronutrient intakes by displacing other food items from the diet. Analyses should take into account the magnitude of any observed associations to determine their true biological significance.

With the increasing prevalence of childhood obesity, there is an urgent need to identify risk factors that are amenable to preventative action. However, there is a remarkable lack of consistency between studies that have investigated the relationships between measurements of physical activity and energy expenditure and body fatness in children. This disparity could be because energy intake is a more important determinant in preventing obesity. Alternatively, some of the conflicting results could be related to methodological limitations in assessing activity and body composition. Erroneous conclusions may be drawn if physical activity energy expenditure is not adjusted for differences in body composition, or body fat is not appropriately adjusted for body size. For public health purposes it may be more informative to evaluate the amount and intensity of physical activity required to prevent fat-mass gain than to assess energy expended in physical activity. The lack of consensus in the cut-off points applied to define intensity levels is severely hindering comparisons between studies using accelerometers that have examined relationships between activity intensity and body fatness. Thus, it is not currently possible to develop a firm evidence base on which to establish physical activity recommendations until the limitations are addressed and more prospective studies undertaken. In order to turn research into effective prevention strategies a clearer understanding of the psycho-social, behavioural and environmental factors that influence activity is needed, including the interactions between physical activity and other behaviours such as time spent sedentary, sleeping and eating. Childhood obesity: Physical activity: Energy expenditure: Body fatness

Physical inactivity increases the risk of obesity, but the relations between reported levels of physical activity (PA) and measures of body fatness (BF) in children are remarkably inconsistent.We examined the relation between objective measures of PA and body-composition indexes in nonobese children.A cross-sectional study was conducted in 100 children aged 6-8 y who were recruited according to their risk of future obesity: high-risk children had/=1 obese parent [body mass index (BMI; in kg/m(2)):30] and low-risk children had 2 nonobese biological parents (BMI:30). Free-living activity energy expenditure (AEE) and PA level were calculated from 7-d doubly labeled water measurements, time spent in light-intensity activity was assessed by heart rate monitoring, and body composition was determined from isotopic dilution. To adjust for body size, fat mass and fat-free mass were normalized for height and expressed as fat mass index (FMI) and lean mass index (LMI), respectively.High-risk children had significantly higher BMI, LMI, and FMI than did low-risk children, but no group differences in PA were found. AEE and PA level were positively associated with LMI and, after adjustment for sex and fat-free mass, negatively associated with FMI but not with BMI. Boys who spent more than the median time in light-intensity activities had significantly higher FMI than did less sedentary boys. This difference was not observed in girls.AEE and PA level were negatively associated with BF in nonobese children. Accurate measures of body composition are essential to appropriate assessment of relations between PA and obesity risk.

Methods Volunteer sub-study of 97 men and women (mean ages 54 and 51 years respectively) within the European Investigation into Cancer (EPIC) study in Norfolk (UK). Dietary assessment of energy intake and physical activity was by self-report and weight was measured using standard techniques. Energy expenditure was assessed objectively by recording heart rate for 4 days following a calibration of the relationship between heart rate and oxygen consumption. Results Self-reported energy intake by 7-day diary (mean 8.5 MJ/day) and food frequency questionnaire (FFQ) (mean 8.8 MJ/day) were significantly lower than objectively measured total energy expenditure (mean 11.2 MJ/day). The deattenuated partial correlations between total energy expenditure were 0.33 (7-day diary), 0.34 (FFQ), 0.50 (physical activity), and 0.56 (weight). Weight accounted for 31% (deattenuated) of the sum of squares about the mean of true energy intake after adjusting for age and sex. With the addition of self-reported physical activity, the model was significantly improved (R 2 = 0.57). Adding energy either assessed by the diary or FFQ did not improve the model. Conclusions The results presented here indicate that to adjust for energy intake, for the

Physical activity is an important lifestyle which is often poorly assessed in epidemiological studies. The European Prospective Investigation into Cancer Study-Norfolk cohort (EPIC-Norfolk), a large population-based cohort study, has developed a comprehensive questionnaire to assess activity in different domains of life aimed at assessing total energy expenditure. We report the repeatability of this instrument and its validity against repeated objective measures of fitness and energy expenditure undertaken throughout the time frame of reference of the questionnaire.The validity of the instrument was measured in 173 individuals randomly selected from a continuing population-based cohort study. Energy expenditure was assessed by four separate episodes of 4-day heart-rate monitoring, a method previously validated against whole body calorimetry and doubly-labelled water. Cardio-respiratory fitness was assessed by four repeated measures of sub-maximum oxygen uptake. At the end of the 12-month period, participants completed the physical activity questionnaire that assesses past-year activity at home, work and in recreation. Repeatability was assessed in a separate group of 399 randomly selected participants in EPIC who completed the physical activity questionnaire twice with a 3-month interval.The age- and sex-adjusted correlation between the objective measure of daytime energy expenditure and the sum of recreational and occupational reported physical activity (in MET h per week) was 0.28 (P0.001). The reported time spent in vigorous activity was correlated with cardio-respiratory fitness (0.16, P0.05) and with the proportion of time when energy expenditure was more than five times basal (0.17, P0.05). The repeatability of the sum of recreational and occupational reported activity was high, r = 0.73.The indices of physical activity derived from this questionnaire have levels of validity and repeatability comparable to other physical activity instruments that are used in large epidemiological studies and which have undergone such intense development and testing.

Background and aims Simple, low-cost central obesity measures may help identify individuals with increased cardiometabolic disease risk, although it is unclear which measures perform best in African adults. We aimed to: 1) cross-sectionally compare the accuracy of existing waist-to-height ratio (WHtR) and waist circumference (WC) thresholds to identify individuals with hypertension, pre-diabetes, or dyslipidaemia; 2) identify optimal WC and WHtR thresholds to detect CVD risk in this African population; and 3) assess which measure best predicts 5-year CVD risk. Methods and results Black South Africans (577 men, 942 women, aged >30years) were recruited by random household selection from four North West Province communities. Demographic and anthropometric measures were taken. Recommended diagnostic thresholds (WC > 80 cm for women, >94 cm for men; WHtR > 0.5) were evaluated to predict blood pressure, fasting blood glucose, lipids, and glycated haemoglobin measured at baseline and 5 year follow up. Women were significantly more overweight than men at baseline (mean body mass index (BMI) women 27.3 ± 7.4 kg/m2, men 20.9 ± 4.3 kg/m2); median WC women 81.9 cm (interquartile range 61–103), men 74.7 cm (63–87 cm), all P < 0.001). In women, both WC and WHtR significantly predicted all cardiometabolic risk factors after 5 years. In men, even after adjusting WC threshold based on ROC analysis, WHtR better predicted overall 5-year risk. Neither measure predicted hypertension in men. Conclusions The WHtR threshold of >0.5 appears to be more consistently supported and may provide a better predictor of future cardiometabolic risk in sub-Saharan Africa. •Obesity & CVD are increasing rapidly in Africa.•Low cost measures are needed to find those at risk.•Debate continues on the optimum Waist Circumference threshold for African adults.•Waist-to-height ratio predicts current & future CVD risk in South-African adults.•There is greater global agreement on the WHtR threshold (>0.5) for risk. http://www.sciencedirect.com/science?_ob=ArticleListURL&_method=list&_ArticleListID=-921226990&_sort=r&_st=13&view=c&md5=dce0821726f5c1f0e72702d33bcd99dd&searchtype=a http://dx.doi.org/10.1016/j.numecd.2014.02.005

Objective: Heart rate monitoring has previously been used as a technique for measuring energy expenditure (EE) in field studies. However, the combination of heart rate monitoring with movement sensoring could have theoretical advantages compared to either method used alone. Therefore, this study was undertaken to develop and validate a new combined heart rate monitor and movement sensor instrument (HR+M) for measuring EE. Methods: The HR+M instrument is a single-piece instrument worn around the chest which records minute-by-minute heart rate and movement. Eight subjects underwent an individual calibration in which EE and heart rate were measured at rest and during a sub-maximal bicycle ergometer test. They then wore the HR+M for 24 hours in a whole-body calorimeter and underwent a standard protocol including periods of physical activity and inactivity. Minute-by-minute heart rate was converted to EE using individual calibration curves with the motion data discriminating between periods of inactivity and activity at low heart rate levels. EE was also calculated using the HRFlex method which relies on heart rate alone. Both estimates of EE were compared to EE measured in the whole-body calorimeter. Results: The mean percentage error of the HR+M method calculating TEE compared with the gold standard of the calorimeter measurement was 0.00% (95% CI of the mean error −0.25, 1.25). The HRFlex method using the heart rate information alone resulted in a mean percentage error of 16.5% (95% CI of the mean error −0.57, 1.76). Conclusions: This preliminary test of HR+M demonstrates its ability to estimate EE and the pattern of EE and activity throughout the day. Further validation studies in free-living individuals are necessary. Sponsorship: NJW is an MRC Clinician Scientist Fellow. KLR holds an MRC PhD scholarship. European Journal of Clinical Nutrition (2000) 54, 409–414

Objective:To review and categorize the problems associated with undertaking physical activity validation studies and to construct a checklist against which any study could be compared.Results:The studies reviewed demonstrated problems in defining the dimension of physical activity that is of interest and in the selection of an appropriate comparison technique. Ideally this should be closely related to the true exposure of interest and assess that exposure objectively and without correlated error from the study instrument in question. In many studies inappropriate comparison methods have been chosen which do not measure the true underlying exposure and which are likely to have correlated error. The choice of study populations, the frame of reference of the exposure measurement and the use of appropriate statistical methods are also problematic areas.Conclusions:There is no ideal measurement instrument or validation study design that is suitable for all situations. However, the checklist in this paper provides a means whereby the appropriateness of studies already undertaken or at the planning stage can be assessed.

Background— Inflammatory factors, adipocytokines, and the metabolic syndrome are important determinants of cardiometabolic disease. It remains unclear how physical activity is related to these risk factors. Our objective was to investigate single and joint associations of physical activity with inflammatory factors, adipocytokines, and the metabolic syndrome among middle-aged and older Chinese people. Methods and Results— A total of 3289 individuals (1458 men, 1831 women) 50 to 70 years of age participated in a population-based cross-sectional survey in Beijing and Shanghai, China. Levels of total physical activity were assessed with the International Physical Activity Questionnaire. High-sensitivity C-reactive protein, interleukin-6, tumor necrosis factor-α receptor 2, adiponectin, and retinol-binding protein 4 were measured. The metabolic syndrome was defined using the updated National Cholesterol Education Program/Adult Treatment Panel III criteria for Asian Americans. Plasma concentrations of high-sensitivity C-reactive protein were 1.58, 1.74, and 1.27 mg/L ( P =0.0138) and of adiponectin were 16.12, 16.20, and 17.21 mg/L ( P =0.0078) among individuals with low, medium, and high levels of total physical activity, respectively, with adjustment for potential confounders. In the multivariable-adjusted logistic regression analyses, participants with higher levels of total physical activity had a lower risk of having the metabolic syndrome (odds ratio, 0.68; 95% confidence interval, 0.54 to 0.85; P for trend=0.001) compared with those with lower levels. Conclusions— Being physically active is associated with a better profile of inflammatory factors and adipocytokines and a reduced risk of having the metabolic syndrome among Chinese people.

Large food portions may be facilitating excess energy intake (EI) and adiposity among adults. The present study aimed to assess the extent to which EI and amounts of foods consumed are influenced by the availability of different-sized food portions. A randomised within-subject cross-over, fully residential design was used, where forty-three (twenty-one men and twenty-two women) normal-weight and overweight adults were randomly allocated to two separate 4 d periods where they were presented with either ‘standard’ or ‘large’ food portions of the same foods and beverages. The main outcome measures were the amount of food (g) and EI (MJ) consumed throughout each study period. Mean EI over 4 d was significantly higher on the large portion condition compared with the standard condition in the total group (59·1 (sd 6·6) v. 52·2 (sd 14·3) MJ; P = 0·020); men and women increased their EI by 17 % (10 (sd 6·5) MJ; P sd 6·5) MJ; P = 0·005) respectively when served the large food portions relative to the standard food portions. The increased intakes were sustained over the 4 d in the large portion condition with little evidence of down-regulation of EI and food intake being made by subjects. Increased food portion size resulted in significant and sustained increases in EI in men and women over 4 d under fully residential conditions. The availability and consumption of larger portions of food may be a significant factor contributing to excess EI and adiposity.

Excess fat leads to adverse health outcomes. Most previous studies investigating body fatness using BMI or fat percentage, which contain both fat mass and fat-free mass, were not able to differentiate the exposure.The present study assessed the independent association of fat and fat-free mass with metabolic syndrome (MetS) in Chinese.A population-based study of 1144 subjects aged 50-70 from urban and rural areas of Shanghai in 2005-2006 was employed. Body composition was measured with DEXA. Fat mass index (FMI) and fat-free mass index (FFMI) were calculated. MetS was defined using the National Cholesterol Education Program Adult Treatment Panel III (NCEP ATP III) criteria without waist circumference for its high correlation with body composition.Both FMI and FFMI were significantly related with higher odds of MetS (OR 3.97, 95% CI 2.58-6.09 for FMI; OR 2.67, 95% CI 1.70-4.18 for FFMI, the highest quartile vs the lowest group) after adjusting for age, residence, sex, smoking, drinking, physical activity, medication, family history of chronic diseases, and fat-free mass (for FMI) or fat mass (for FFMI).Both FMI and FFMI are independently associated with increased MetS risks. Proper expression of body composition is essential in assessing body composition and disease risk association.

Background Internet-based physical activity (PA) and weight management programs have the potential to improve employees’ health in large occupational health settings. To be successful, the program must engage a wide range of employees, especially those at risk of weight gain or ill health. Objective The aim of the study was to assess the use and nonuse (user attrition) of a Web-based and monitoring device–based PA and weight management program in a range of employees and to determine if engagement with the program was related to the employees’ baseline characteristics or measured outcomes. MethodsLongitudinal observational study of a cohort of employees having access to the MiLife Web-based automated behavior change system. Employees were recruited from manufacturing and office sites in the North West and the South of England. Baseline health data were collected, and participants were given devices to monitor their weight and PA via data upload to the website. Website use, PA, and weight data were collected throughout the 12-week program. Results Overall, 12% of employees at the four sites (265/2302) agreed to participate in the program, with 130 men (49%) and 135 women (51%), and of these, 233 went on to start the program. During the program, the dropout rate was 5% (11/233). Of the remaining 222 Web program users, 173 (78%) were using the program at the end of the 12 weeks, with 69% (153/222) continuing after this period. Engagement with the program varied by site but was not significantly different between the office and factory sites. During the first 2 weeks, participants used the website, on average, 6 times per week, suggesting an initial learning period after which the frequency of website log-in was typically 2 visits per week and 7 minutes per visit. Employees who uploaded weight data had a significant reduction in weight (−2.6 kg, SD 3.2, P< .001). The reduction in weight was largest for employees using the program’s weight loss mode (−3.4 kg, SD 3.5). Mean PA level recorded throughout the program was 173 minutes (SE 12.8) of moderate/high intensity PA per week. Website interaction time was higher and attrition rates were lower (OR 1.38, P= .03) in those individuals with the greatest weight loss. Conclusions This Web-based PA and weight management program showed high levels of engagement across a wide range of employees, including overweight or obese workers, shift workers, and those who do not work with computers. Weight loss was observed at both office and manufacturing sites. The use of monitoring devices to capture and send data to the automated Web-based coaching program may have influenced the high levels of engagement observed in this study. When combined with objective monitoring devices for PA and weight, both use of the website and outcomes can be tracked, allowing the online coaching program to become more personalized to the individual.

The objective of the present study was to examine the associations between the portion sizes of food groups consumed with measures of adiposity using data from the National Diet and Nutrition Survey of British adults. Seven-day weighed dietary records, physical activity diaries and anthropometric measurements were used. Foods eaten were assigned to thirty different food groups and analyses were undertaken separately for men and women. The median daily portion size of each food group consumed was calculated. The potential mis-reporting [corrected] of dietary energy intake (EI) was identified using the following equation: EI--estimated energy requirements/EER [corrected] x 100 = percentage of under-reporting (UR) of energy needs. Multinomial logistic regression (adjusted for age, social class, physical activity level and UR) was used to determine the portion sizes of food groups most strongly associated with obesity status. Few positive associations between the portion sizes of food groups consumed and obesity status were found. However, UR was prevalent, with a median UR of predicted energy needs of 34 and 33 % in men and women, respectively. After the adjustment was made for UR, more associations between the food groups and obesity status became apparent in both sexes. The present study suggests that the true effect of increased portion size of foods on obesity status may be masked by high levels of UR. Alternatively, these data may indicate that an increased risk of obesity is not associated with specific foods/food groups but rather with an overall increase in the range of foods and food groups being consumed.

The aim of the present study was to investigate the relationships of physical activity types and sedentary behaviour with BMI and waist circumference (WC). The sample comprised 6215 adults (2775 men, 3440 women) aged 16 years and over living in Scotland. Self-reported physical activity of moderate to vigorous intensity (MVIA) included domestic activity, walking, and sports and exercises. MVIA levels were classified as being inactive, being insufficiently active, being sufficiently active for general health benefits and being sufficiently active for obesity prevention. Sedentary time was defined as television and other screen-based entertainment time (TVSE). Dependent variables were BMI-defined obesity (BMI-OB) and WC-defined obesity (WC-OB). TVSE was positively related to both WC-OB (adjusted OR 1·69 (95 % CI 1·39, 2·05) for ≥ 4 h of TVSE per d compared with v. 8·3 %; P v. 10·0 %; P