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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.

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.

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.

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.

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.

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.

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.

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.

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

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.

Underreporting is endemic in most dietary studies and ways to reliably identify individuals who may underreport energy intake are needed. Whether questions on self-reported dieting and dietary restraint, in addition to weight status, would identify individuals who may underreport energy intakes was examined in a United Kingdom representative survey. Mean daily energy intake was calculated from the 7-day dietary record of 668 men and 826 women. Reported physical activity was used to assign each subject's activity level and to calculate estimated energy requirements from published equations. Underreporting was calculated as estimated energy requirements minus energy intake with adjustment for daily variation. The Dutch Eating Behavior Questionnaire assessed dietary restraint. Underreporting was higher in men and women reporting current dieting than nondieters (P

Since 1980 the prevalence of obesity in Great Britain in adults has almost trebled. Latest figures show that 23% of men and 25% of women were obese in 2002. In children, obesity prevalence is lower but the increase in the prevalence of overweight is similar to the rise in obesity in adults. Data from national surveys also show that there are marked differences in the prevalence of obesity that underpin health inequalities. Obesity is higher in low social classes, some ethnic minority groups particularly from South Asia and in Scotland and Wales relative to England.

Objective:To determine the prevalence of overweight and obesity in British young people (4–18 years) in 1997.Design:Cross-sectional analysis of the National Diet and Nutrition Survey of young people.Setting:Great Britain.Subjects:Nationally representative sample of 1836 young people (age 4–18 years).Results:The prevalence of obesity based on body mass index (weight/height2) and the International Obesity Task Force cut–offs was 4.0%, with a further 15.4% identified as overweight. Asians were almost four times as likely to be obese as white subjects (13.6 vs. 3.5%, P < 0.001). Among white subjects there was no significant difference in the prevalence of obesity between girls and boys, or with age. The risk of obesity was significantly higher in subjects from social classes IV and V than from social classes I–III (6.5 vs. 2.7%, P = 0.003). Subjects living in Scotland and Wales were significantly more likely to be obese than those in England (7.6 and 6.5 vs. 2.9%, respectively, P < 0.01). Multiple logistic regression showed that, among white subjects, those in social classes IV and V living in Wales and Scotland were three times more likely to be obese than the other children in the survey (odds ratio 3.3, 95% confidence interval 1.1–9.8).Conclusion:These data provide information on the national prevalence of overweight and obesity in Great Britain and baseline data from which to monitor future trends. This analysis provides important demographic information on those most at risk of obesity, which may be used to inform public health strategies to prevent obesity in young people.

Physical inactivity and low resting heart rate variability (HRV) are associated with increased coronary heart disease incidence. In the Whitehall II study of civil servants aged 45-68 years (London, United Kingdom, 1997-1999), the strength of the association of moderate and vigorous activity with higher HRV was examined. Five-minute recordings of heart rate and HRV measures were obtained from 3328 participants. Calculated were time domain (standard deviation of NN intervals) and high-frequency-power measures as indicators of cardiac parasympathetic activity and low-frequency power of parasympathetic-sympathetic balance. Leisure-time physical activity (metabolic equivalent-hours per week) was categorized as moderate (or=3-5) and vigorous (or=5). Moderate and vigorous physical activity were associated with higher HRV and lower heart rate. For men, linear trends of higher low-frequency power with increasing quartile of vigorous activity (304.6 (low), 329.0, 342.4, 362.5 (high); p0.01) and lower heart rate with increasing quartile of moderate activity (69.6 (low), 69.2, 68.9, 67.8 (high); p0.05) were found. These associations remained significant after adjustment for smoking and high alcohol intake. For men whose body mass index was25 kg/m(2), vigorous activity was associated with HRV levels similar to those for normal-weight men who engaged in no vigorous activity. Vigorous activity was associated with higher HRV, representing a possible mechanism by which physical activity reduces coronary heart disease risk.

Objective:To assess the validity and repeatability of a simple index designed to rank participants according to their energy expenditure estimated by self-report, by comparison with objectively measured energy expenditure assessed by heart-rate monitoring with individual calibration.Design:Energy expenditure was assessed over one year 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 a physical activity questionnaire that assessed past-year activity. A simple four-level physical activity index was derived by combining occupational physical activity together with time participating in cycling and other physical exercise (such as keep fit, aerobics, swimming and jogging).Subjects:One hundred and seventy-three randomly selected men and women aged 40 to 65 years.Results:The repeatability of the physical activity index was high (weighted kappa = 0.6, P < 0.0001). There were positive associations between the physical activity index from the questionnaire and the objective measures of the ratio of daytime energy expenditure to resting metabolic rate (P = 0.003) and cardio-respiratory fitness (P = 0.001). As an indirect test of validity, there was a positive association between the physical activity index and the ratio of energy intake, assessed by 7-day food diaries, to predicted basal metabolic rate.Conclusions:The summary index of physical activity derived from the questions used in the European Prospective Investigation into Cancer and Nutrition (EPIC) study suggest it is useful for ranking participants in terms of their physical activity in large epidemiological studies. The index is simple and easy to comprehend, which may make it suitable for situations that require a concise, global index of activity.

ObjectiveTo evaluate habitual levels of physical activity in a nationally representative sample of adults in Ireland.DesignCross-sectional survey using a self-administered questionnaire. Usual levels of work, recreational and household activities were evaluated in relation to anthropometric, demographic and socio-economic characteristics. The amount and intensity of all activities were quantified by assigning metabolic equivalents (METS) to each activity.SettingRepublic of Ireland and Northern Ireland, 1997–1999.SubjectsRandom sample of 1379 adults aged 18–64 years.ResultsMen were approximately twice as active in work and recreational activity (139.7 ± 83.9 METS) as women (68.5 ± 49.8 METS; P < 0.001), but women were three times more active in household tasks (65.9 ± 58.7 METS vs. 22.6 ± 24.6 METS; P < 0.001). Overall levels of physical activity declined with increasing age, particularly leisure activity in men. In women the decline in work activity was offset by spending more time in household pursuits. Twenty-five per cent of the subjects were extremely overweight (body mass index (BMI) > 28kg m−2) or obese (BMI > 30kg m−2). Fewer obese subjects reported higher levels of work and leisure activities. However, a higher percentage of obese women reported participation in the higher levels of household activities. Participation rates in recreational activities were low. Walking was the most important leisure activity of both men (41%) and women (60%). In terms of hours per week spent in vigorous physical activity, men were more active than women, professional and skilled non-manual women were more active than women in other social classes, and younger subjects (aged 18–35 years) were more active than older subjects.ConclusionsThe holistic approach used in the assessment of physical activity in this study has revealed important and subtle differences in the activity patterns of men and women. Failure to fully characterise the respective activity patterns of men and women could lead to ill-informed public health policy aimed at promoting and sustaining lifetime habits of physical activity. The results suggest that simple population-focused programmes to promote physical activity are unlikely to offer the same chance of long-term success as more sensitive and individualised strategies.

Heart rate monitoring has been shown to be a valid method for measuring free-living energy expenditure at the group level, but its use in large-scale studies is limited by the need for an individual calibration of the relationship between heart rate and energy expenditure.To determine whether energy expenditure can be estimated from heart rate monitoring without individual calibration in epidemiological studies.Our previously validated heart rate monitoring method relies on measuring individual calibration parameters obtained from resting energy expenditure and the regression line between energy expenditure and heart rate during exercise. We developed prediction equations for these parameters using easily measured variables in a population-based study of 789 individuals. The predictive ability of these parameters was tested in a separate population-based sample (N = 97).Physical activity level (PAL = total energy expenditure/basal metabolic rate) using the four estimated parameters was correlated with PAL using the measured parameters (r = 0.82, P0.01). Comparison of measured and estimated PAL showed that 97.9% of the scores were placed in the same or adjacent quartile.A combination of simple measurements and heart rate monitoring produces estimates of energy expenditure that are highly correlated with those obtained using full individual calibration. This simplification of the heart rate monitoring method could extend its use in ranking individuals in epidemiological studies.

Background Previous studies have demonstrated an association between physical inactivity and hypertension, but the methods used to assess activity have been subjective and imprecise. Recently methods have become available allowing measurement of energy expenditure in free-living populations. Our aim was to employ these methods to assess the independent association between energy expenditure, cardio-respiratory fitness and blood pressure. Methods In a cross-sectional study of 775 people (45‐70 years) participating in a continuing population-based cohort study, energy expenditure was assessed by 4 days of heart rate monitoring with individual calibration of the relationship between heart rate and energy expenditure, a method validated against doubly-labelled water and whole body calorimetry. Cardio-respiratory fitness was assessed in a sub-maximal test. To adjust for measurement error in the assessment of usual energy expenditure and fitness, 190 subjects repeated both tests on three further occasions at 4-monthly intervals. Results A highly significant linear trend in blood pressure was found across quintiles of the physical activity level, the ratio of total energy expenditure to basal metabolic rate. The differences in the mean systolic/diastolic blood pressure between the top and bottom quintile was 6.3/4.4 mmHg in men and 10.7/5.9 mmHg in women. These effects were independent of obesity and cardio-respiratory fitness. Correction for measurement error suggests that the true underlying relationship between usual energy expenditure and blood pressure is stronger still. Conclusions These findings are compatible with a strong association between usual energy expenditure and blood pressure and support public health strategies aimed at increasing overall energy expenditure.

OBJECTIVE—The aim of this study was to determine whether overweight and obese individuals with type 2 diabetes have higher basal and 24-h energy expenditure compared with healthy control subjects before and after adjustment for body composition, spontaneous physical activity (SPA), sex, and age. RESEARCH DESIGN AND METHODS—Data from 31 subjects with type 2 diabetes and 61 nondiabetic control subjects were analyzed. The 24-h energy expenditure, basal metabolic rate (BMR), and sleeping energy expenditure (EEsleep) between 1:00 a.m. and 6:00 a.m. were measured in whole-body respiratory chambers. Body composition was assessed by dual-energy X-ray absorptiometry (DXA). RESULTS—No significant differences in unadjusted EEsleep, BMR, and 24-h energy expenditure were observed between the type 2 diabetic group and the control group. After adjustment for fat-free mass (FFM), fat mass, SPA, sex, and age, EEsleep and BMR were, respectively, 7.7 and 6.9% higher in the type 2 diabetic group compared with the control group. This was equivalent to 144 ± 40 kcal/day (P = 0.001) and 139 ± 61 kcal/day (P = 0.026), respectively. Adjusted 24-h energy expenditure was 6.5% higher in the type 2 diabetic group compared with the nondiabetic control subjects (2,679 ± 37 vs. 2,515 ± 23 kcal/day, P = 0.002). In multiple regression analyses, FFM, fat mass, SPA, and diabetes status were all significant determinants of EEsleep and 24-h energy expenditure, explaining 83 and 81% of the variation, respectively. CONCLUSIONS—This study confirms reports in Pima Indians that basal and 24-h energy expenditure adjusted for body composition, SPA, sex, and age are higher in individuals with type 2 diabetes compared with nondiabetic control subjects and may be even more pronounced in Caucasians.

BACKGROUND: The contribution of energy density (ED) of the total diet to increased risk of obesity from childhood into adolescence is unclear. OBJECTIVE: We assessed the relation between the ED of the diet in childhood, calculated in a number of ways, and change in adiposity from childhood to adolescence. DESIGN: In a prospective study, 48 children (30 boys, 18 girls) were initially studied at age 6-8 y (baseline) and followed up at age 13-17 y. Daily ED, energy intake, and food intake were assessed at baseline by 7-d weighed food records concurrent with estimates of total energy expenditure (TEE) by doubly labeled water. ED was calculated with the use of 5 published methods. Obesity risk was defined with the use of body fat from total body water by isotope dilution. Body fat was normalized for height and expressed as fat mass index (FMI). Change in adiposity was calculated as follow-up FMI minus baseline FMI. RESULTS: Misreporting of energy intake at the group level at baseline was low relative to the TEE. ED of the total diet at baseline by the 3 methods for calculating ED that excluded all or most beverages was prospectively associated with change in FMI. However, ED of the total diet by any of the methods was not associated with change in the percentage body fat, body mass index, or waist circumference z scores. CONCLUSION: The methods used to calculate ED and to assess obesity risk lead to different conclusions about the relation between the ED of the diet in childhood and gain in fat into adolescence.