Food and Brisbane households : dietary, social and health consequences of food insecurity

Background & Aims: Access to sufficient amounts of safe and culturally-acceptable foods is a fundamental human right. Food security exists when all people, at all times, have physical, social, and economic access to sufficient, safe and nutritious food to meet their dietary needs and food preferences for an active and healthy life. Food insecurity therefore occurs when the availability or access to sufficient amounts of nutritionally-adequate, culturally-appropriate and safe foods, or, the ability to acquire such foods in socially-acceptable ways, is limited. Food insecurity may result in significant adverse effects for the individual and these outcomes may vary between adults and children. Among adults, food insecurity may be associated with overweight or obesity, poorer self-rated general health, depression, increased health-care utilisation and dietary intakes less consistent with national recommendations. Among children, food insecurity may result in poorer self or parent-reported general health, behavioural problems, lower levels of academic achievement and poor social outcomes. The majority of research investigating the potential correlates of food insecurity has been undertaken in the United States (US), where regular national screening for food insecurity is undertaken using a comprehensive multi-item measurement. In Australia, screening for food insecurity takes place on a three yearly basis via the use of a crude, single-item included in the National Health Survey (NHS). This measure has been shown to underestimate the prevalence of food insecurity by 5%. From 1995 – 2004, the prevalence of food insecurity among the Australian population remained stable at 5%. Due to the perceived low prevalence of this issue, screening for food insecurity was not undertaken in the most recent NHS. Furthermore, there are few Australian studies investigating the potential determinants of food insecurity and none investigating potential outcomes among adults and children. This study aimed to examine these issues by a) investigating the prevalence of food insecurity among households residing in disadvantaged urban areas and comparing prevalence rates estimated by the more comprehensive 18-item and 6-item United States Department of Agriculture (USDA) Food Security Survey Module (FSSM) to those estimated by the current single-item measure used for surveillance in Australia and b) investigating the potential determinants and outcomes of food insecurity, Methods: A comprehensive literature review was undertaken to investigate the potential determinants and consequences of food insecurity among developed countries. This was followed by a cross-sectional study in which 1000 households from the most disadvantaged 5% of Brisbane areas were sampled and data collected via mail-based survey (final response rate = 53%, n = 505). Data were collected for food security status, sociodemographic characteristics (household income, education, age, gender, employment status, housing tenure and living arrangements), fruit and vegetable intakes, meat and take-away consumption, presence of depressive symptoms, presence of chronic disease and body mass index (BMI) among adults. Among children, data pertaining to BMI, parent-reported general health, days away from school and activities and behavioural problems were collected. Rasch analysis was used to investigate the psychometric properties of the 18-, 10- and 6-item adaptations of the USDA-FSSM, and McNemar's test was used to investigate the difference in the prevalence of food insecurity as measured by these three adaptations compared to the current single-item measure used in Australia. Chi square and logistic regression were used to investigate the differences in dietary and health outcomes among adults and health and behavioural outcomes among children. Results were adjusted for equivalised household income and, where necessary, for indigenous status, education and family type. Results: Overall, 25% of households in these urbanised-disadvantaged areas reported experiencing food insecurity; this increased to 34% when only households with children were analysed. The current reliance on a single-item measure to screen for food insecurity may underestimate the true burden among the Australian population, as this measure was shown to significantly underestimate the prevalence of food insecurity by five percentage points. Internationally, major potential determinants of food insecurity included poverty and indicators of poverty, such as low-income, unemployment and lower levels of education. Ethnicity, age, transportation and cooking and financial skills were also found to be potential determinants of food insecurity. Among Australian adults in disadvantaged urban areas, food insecurity was associated with a three-fold increase in experiencing poorer self-rated general health and a two-to-five-fold increase in the risk of depression. Furthermore, adults from food insecure households were twoto- three times more likely to have seen a general practitioner and/or been admitted to hospital within the previous six months, compared to their food secure counterparts. Weight status and intakes of fruits, vegetables and meat were not associated with food insecurity. Among Australian households with children, those in the lowest tertile were over 16 times more likely to experience food insecurity compared to those in the highest tertile for income. After adjustment for equivalised household income, children from food insecure households were three times more likely to have missed days away from school or other activities. Furthermore, children from food insecure households displayed a two-fold increase in atypical emotions and behavioural difficulties. Conclusions: Food insecurity is an important public health issue and may contribute to the burden on the health care system through its associations with depression and increased health care utilisation among adults and behavioural and emotional problems among children. Current efforts to monitor food insecurity in Australia do not occur frequently and use a tool that may underestimate the prevalence of food insecurity. Efforts should be made to improve the regularity of screening for food insecurity via the use of a more accurate screening measure. Most of the current strategies that aim to alleviate food insecurity do not sufficiently address the issue of insufficient financial resources for acquiring food; a factor which is an important determinant of food insecurity. Programs to address this issue should be developed in collaboration with groups at higher risk of developing food insecurity and should incorporate strategies to address the issue of low income as a barrier to food acquisition.

Validity of dietary questionnaires in Sri Lankan adults and the association of dietary intake with obesity

Traditionally, infectious diseases and under-nutrition have been considered major health problems in Sri Lanka with little attention paid to obesity and associated non-communicable diseases (NCDs). However, the recent Sri Lanka Diabetes and Cardiovascular Study (SLDCS) reported the epidemic level of obesity, diabetes and metabolic syndrome. Moreover, obesity-associated NCDs is the leading cause of death in Sri Lanka and there is an exponential increase in hospitalization due to NCDs adversely affecting the development of the country. Despite Sri Lanka having a very high prevalence of NCDs and associated mortality, little is known about the causative factors for this burden. It is widely believed that the global NCD epidemic is associated with recent lifestyle changes, especially dietary factors. In the absence of sufficient data on dietary habits in Sri Lanka, successful interventions to manage these serious health issues would not be possible. In view of the current situation the dietary survey was undertaken to assess the intakes of energy, macro-nutrients and selected other nutrients with respect to socio demographic characteristics and the nutritional status of Sri Lankan adults especially focusing on obesity. Another aim of this study was to develop and validate a culturally specific food frequency questionnaire (FFQ) to assess dietary risk factors of NCDs in Sri Lankan adults. Data were collected from a subset of the national SLDCS using a multi-stage, stratified, random sampling procedure (n=500). However, data collection in the SLDCS was affected by the prevailing civil war which resulted in no data being collected from Northern and Eastern provinces. To obtain a nationally representative sample, additional subjects (n=100) were later recruited from the two provinces using similar selection criteria. Ethical Approval for this study was obtained from the Ethical Review Committee, Faculty of Medicine, University of Colombo, Sri Lanka and informed consent was obtained from the subjects before data were collected. Dietary data were obtained using the 24-h Dietary Recall (24HDR) method. Subjects were asked to recall all foods and beverages, consumed over the previous 24-hour period. Respondents were probed for the types of foods and food preparation methods. For the FFQ validation study, a 7-day weight diet record (7-d WDR) was used as the reference method. All foods recorded in the 24 HDR were converted into grams and then intake of energy and nutrients were analysed using NutriSurvey 2007 (EBISpro, Germany) which was modified for Sri Lankan food recipes. Socio-demographic details and body weight perception were collected from interviewer-administrated questionnaire. BMI was calculated and overweight (BMI ≥23 kg.m-2), obesity (BMI ≥25 kg.m-2) and abdominal obesity (Men: WC ≥ 90 cm; Women: WC ≥ 80 cm) were categorized according to Asia-pacific anthropometric cut-offs. The SPSS v. 16 for Windows and Minitab v10 were used for statistical analysis purposes. From a total of 600 eligible subjects, 491 (81.8%) participated of whom 34.5% (n=169) were males. Subjects were well distributed among different socio-economic parameters. A total of 312 different food items were recorded and nutritionists grouped similar food items which resulted in a total of 178 items. After performing step-wise multiple regression, 93 foods explained 90% of the variance for total energy intake, carbohydrates, protein, total fat and dietary fibre. Finally, 90 food items and 12 photographs were selected. Seventy-seven subjects completed (response rate = 65%) the FFQ and 7-day WDR. Estimated mean energy intake (SD) from FFQ (1794±398 kcal) and 7DWR (1698±333 kcal, P<0.001) was significantly different due to a significant overestimation of carbohydrate (~10 g/d, P<0.001) and to some extent fat (~5 g/d, NS). Significant positive correlations were found between the FFQ and 7DWR for energy (r = 0.39), carbohydrate (r = 0.47), protein (r = 0.26), fat (r =0.17) and dietary fiber (r = 0.32). Bland-Altman graphs indicated fairly good agreement between methods with no relationship between bias and average intake of each nutrient examined. The findings from the nutrition survey showed on average, Sri Lankan adults consumed over 14 portions of starch/d; moreover, males consumed 5 more portions of cereal than females. Sri Lankan adults consumed on average 3.56 portions of added sugars/d. Moreover, mean daily intake of fruit (0.43) and vegetable (1.73) portions was well below minimum dietary recommendations (fruits 2 portions/d; vegetables 3 portions/d). The total fruit and vegetable intake was 2.16 portions/d. Daily consumption of meat or alternatives was 1.75 portions and the sum of meat and pulses was 2.78 portions/d. Starchy foods were consumed by all participants and over 88% met the minimum daily recommendations. Importantly, nearly 70% of adults exceeded the maximum daily recommendation for starch (11portions/d) and a considerable proportion consumed larger numbers of starch servings daily, particularly men. More than 12% of men consumed over 25 starch servings/d. In contrast to their starch consumption, participants reported very low intakes of other food groups. Only 11.6%, 2.1% and 3.5% of adults consumed the minimum daily recommended servings of vegetables, fruits, and fruits and vegetables combined, respectively. Six out of ten adult Sri Lankans sampled did not consume any fruits. Milk and dairy consumption was extremely low; over a third of the population did not consume any dairy products and less than 1% of adults consumed 2 portions of dairy/d. A quarter of Sri Lankans did not report consumption of meat and pulses. Regarding protein consumption, 36.2% attained the minimum Sri Lankan recommendation for protein; and significantly more men than women achieved the recommendation of ≥3 servings of meat or alternatives daily (men 42.6%, women 32.8%; P<0.05). Over 70% of energy was derived from carbohydrates (Male:72.8±6.4%, Female:73.9±6.7%), followed by fat (Male:19.9±6.1%, Female:18.5±5.7%) and proteins (Male:10.6±2.1%, Female:10.9±5.6%). The average intake of dietary fiber was 21.3 g/day and 16.3 g/day for males and females, respectively. There was a significant difference in nutritional intake related to ethnicities, areas of residence, education levels and BMI categories. Similarly, dietary diversity was significantly associated with several socio-economic parameters among Sri Lankan adults. Adults with BMI ≥25 kg.m-2 and abdominally obese Sri Lankan adults had the highest diet diversity values. Age-adjusted prevalence (95% confidence interval) of overweight, obesity, and abdominal obesity among Sri Lankan adults were 17.1% (13.8-20.7), 28.8% (24.8-33.1), and 30.8% (26.8-35.2), respectively. Men, compared with women, were less overweight, 14.2% (9.4-20.5) versus 18.5% (14.4-23.3), P = 0.03, less obese, 21.0% (14.9-27.7) versus 32.7% (27.6-38.2), P < .05; and less abdominally obese, 11.9% (7.4-17.8) versus 40.6% (35.1-46.2), P < .05. Although, prevalence of obesity has reached to epidemic level body weight misperception was common among Sri Lankan adults. Two-thirds of overweight males and 44.7% of females considered themselves as in "about right weight". Over one third of both male and female obese subjects perceived themselves as "about right weight" or "underweight". Nearly 32% of centrally obese men and women perceived that their waist circumference is about right. People who perceived overweight or very overweight (n = 154) only 63.6% tried to lose their body weight (n = 98), and quarter of adults seek advices from professionals (n = 39). A number of important conclusions can be drawn from this research project. Firstly, the newly developed FFQ is an acceptable tool for assessing the nutrient intake of Sri Lankans and will assist proper categorization of individuals by dietary exposure. Secondly, a substantial proportion of the Sri Lankan population does not consume a varied and balanced diet, which is suggestive of a close association between the nutrition-related NCDs in the country and unhealthy eating habits. Moreover, dietary diversity is positively associated with several socio-demographic characteristics and obesity among Sri Lankan adults. Lastly, although obesity is a major health issue among Sri Lankan adults, body weight misperception was common among underweight, healthy weight, overweight, and obese adults in Sri Lanka. Over 2/3 of overweight and 1/3 of obese Sri Lankan adults believe that they are in "right weight" or "under-weight" categories.

Too early to proclaim the end of the war on childhood obesity

Parents winning childhood war on obesity, Australian Bureau of Statistics data reveals, screamed the headline. Sounds like a good news story to make every parent breathe a sigh of relief, but is it really true? The article in question quoted obesity expert and University of South Australia Professor Tim Olds, who argued that “the media and public health authorities are getting carried away” about childhood obesity. He pointed to the fact that recent ABS data showed rates of overweight and obesity in children plateaued between 2007/08 and between 2011/12. But that still means one in four Australian children is overweight or obese; it’s clear we still have a lot of work to do. As a nutritionist working with parents every day (both in practical obesity programs and in research into reducing this considerable health risk), I was concerned that the article could be taken at face value. Because there’s more, much more, to this story.

Accuracy of weight status perception in contemporary Australian children and adolescents

Aim: To explore weight status perception and its relation to actual weight status in a contemporary cohort of 5- to 17-year-old children and adolescents. Methods: Body mass index (BMI), derived from height and weight measurements, and perception of weight status (‘too thin’, ‘about right’ and ‘too fat’) were evaluated in 3043 participants from the Healthy Kids Queensland Survey. In children less than 12 years of age, weight status perception was obtained from the parents, whereas the adolescents self-reported their perceived weight status. Results: Compared with measured weight status by established BMI cut-offs, just over 20% of parents underestimated their child's weight status and only 1% overestimated. Adolescent boys were more likely to underestimate their weight status compared with girls (26.4% vs. 10.2%, P < 0.05) whereas adolescent girls were more likely to overestimate than underestimate (11.8% vs. 3.4%, P < 0.05). Underestimation was greater by parents of overweight children compared with those of obese children, but still less than 50% of parents identified their obese child as ‘too fat’. There was greater recognition of overweight status in the adolescents, with 83% of those who were obese reporting they were ‘too fat’. Conclusion: Whilst there was a high degree of accuracy of weight status perception in those of healthy weight, there was considerable underestimation of weight status, particularly by parents of children who were overweight or obese. Strategies are required that enable parents to identify what a healthy weight looks like and help them understand when intervention is needed to prevent further weight gain as the child gets older.

Incidence of unilateral arm lymphoedema after breast cancer : a systematic review and meta-analysis

Background The body of evidence related to breast-cancer-related lymphoedema incidence and risk factors has substantially grown and improved in quality over the past decade. We assessed the incidence of unilateral arm lymphoedema after breast cancer and explored the evidence available for lymphoedema risk factors. Methods We searched Academic Search Elite, Cumulative Index to Nursing and Allied Health, Cochrane Central Register of Controlled Trials (clinical trials), and Medline for research articles that assessed the incidence or prevalence of, or risk factors for, arm lymphoedema after breast cancer, published between January 1, 2000, and June 30, 2012. We extracted incidence data and calculated corresponding exact binomial 95% CIs. We used random effects models to calculate a pooled overall estimate of lymphoedema incidence, with subgroup analyses to assess the effect of different study designs, countries of study origin, diagnostic methods, time since diagnosis, and extent of axillary surgery. We assessed risk factors and collated them into four levels of evidence, depending on consistency of findings and quality and quantity of studies contributing to findings. Findings 72 studies met the inclusion criteria for the assessment of lymphoedema incidence, giving a pooled estimate of 16·6% (95% CI 13·6–20·2). Our estimate was 21·4% (14·9–29·8) when restricted to data from prospective cohort studies (30 studies). The incidence of arm lymphoedema seemed to increase up to 2 years after diagnosis or surgery of breast cancer (24 studies with time since diagnosis or surgery of 12 to <24 months; 18·9%, 14·2–24·7), was highest when assessed by more than one diagnostic method (nine studies; 28·2%, 11·8–53·5), and was about four times higher in women who had an axillary-lymph-node dissection (18 studies; 19·9%, 13·5–28·2) than it was in those who had sentinel-node biopsy (18 studies; 5·6%, 6·1–7·9). 29 studies met the inclusion criteria for the assessment of risk factors. Risk factors that had a strong level of evidence were extensive surgery (ie, axillary-lymph-node dissection, greater number of lymph nodes dissected, mastectomy) and being overweight or obese. Interpretation Our findings suggest that more than one in five women who survive breast cancer will develop arm lymphoedema. A clear need exists for improved understanding of contributing risk factors, as well as of prevention and management strategies to reduce the individual and public health burden of this disabling and distressing disorder.

No sex difference in body fat in response to supervised and measured exercise

It is often reported that females lose less body weight than males do in response to exercise. These differences are suggested to be a result of females exhibiting a stronger defense of body fat and a greater compensatory appetite response to exercise than males do. Purpose This study aimed to compare the effect of a 12-wk supervised exercise program on body weight, body composition, appetite, and energy intake in males and females. Methods A total of 107 overweight and obese adults (males = 35, premenopausal females = 72, BMI = 31.4 ± 4.2 kg·m−2, age = 40.9 ± 9.2 yr) completed a supervised 12-wk exercise program expending approximately 10.5 MJ·wk−1 at 70% HRmax. Body composition, energy intake, appetite ratings, RMR, and cardiovascular fitness were measured at weeks 0 and 12. Results The 12-wk exercise program led to significant reductions in body mass (males [M] = −3.03 ± 3.4 kg and females [F] = −2.28 ± 3.1 kg), fat mass (M = −3.14 ± 3.7 kg and F = −3.01 ± 3.0 kg), and percent body fat (M = −2.45% ± 3.3% and F = −2.45% ± 2.2%; all P < 0.0001), but there were no sex-based differences (P > 0.05). There were no significant changes in daily energy intake in males or females after the exercise intervention compared with baseline (M = 199.2 ± 2418.1 kJ and F = −131.6 ± 1912.0 kJ, P > 0.05). Fasting hunger levels significantly increased after the intervention compared with baseline values (M = 11.0 ± 21.1 min and F = 14.0 ± 22.9 mm, P < 0.0001), but there were no differences between males and females (P > 0.05). The exercise also improved satiety responses to an individualized fixed-energy breakfast (P < 0.0001). This was comparable in males and females. Conclusions Males and premenopausal females did not differ in their response to a 12-wk exercise intervention and achieved similar reductions in body fat. When exercise interventions are supervised and energy expenditure is controlled, there are no sex-based differences in the measured compensatory response to exercise.

The adaptive metabolic response to exercise-induced weight loss influences both energy expenditure and energy intake

BACKGROUND/OBJECTIVEs A decline in resting energy expenditure (REE) beyond that predicted from changes in body composition has been noted following dietary-induced weight loss. However, it is unknown whether a compensatory downregulation in REE also accompanies exercise (EX)-induced weight loss, or whether this adaptive metabolic response influences energy intake (EI). SUBJECTS/METHODS Thirty overweight and obese women (body mass index (BMI)=30.6±3.6 kg/m2) completed 12 weeks of supervised aerobic EX. Body composition, metabolism, EI and metabolic-related hormones were measured at baseline, week 6 and post intervention. The metabolic adaptation (MA), that is, difference between predicted and measured REE was also calculated post intervention (MApost), with REE predicted using a regression equation generated in an independent sample of 66 overweight and obese women (BMI=31.0±3.9 kg/m2). RESULTS Although mean predicted and measured REE did not differ post intervention, 43% of participants experienced a greater-than-expected decline in REE (−102.9±77.5 kcal per day). MApost was associated with the change in leptin (r=0.47; P=0.04), and the change in resting fat (r=0.52; P=0.01) and carbohydrate oxidation (r=−0.44; P=0.02). Furthermore, MApost was also associated with the change in EI following EX (r=−0.44; P=0.01). CONCLUSIONS Marked variability existed in the adaptive metabolic response to EX. Importantly, those who experienced a downregulation in REE also experienced an upregulation in EI, indicating that the adaptive metabolic response to EX influences both physiological and behavioural components of energy balance.

Dietetic practice by Australian and Canadian dietitians with people with Parkinson's disease

Although Parkinson’s disease (PD) is a complex disease for which appropriate nutrition management is important, limited evidence is currently available to support dietetic practice. Existing PD-specific guidelines do not span all phases of the Nutrition Care Process (NCP). This study aimed to document PD-specific nutrition management practice by Australian and Canadian dietitians. DAA members and PEN subscribers were invited to participate in an online survey (late 2011). Eighty-four dietitians responded (79.8% Australian). The majority (70.2%) worked in the clinical setting. Existing non-PD guidelines were used by 52.4% while 53.6% relied on self-initiated literature reviews. Weight loss/malnutrition, protein intake, dysphagia and constipation were common issues in all NCP phases. Respondents also requested more information/evidence for these topics. Malnutrition screening (82.1%) and assessment (85.7%) were routinely performed. One-third did not receive referrals for weight loss for overweight/obesity. Protein intake meeting gender/age recommendations (69.0%), and high energy/high protein diets to manage malnutrition (82.1%) were most commonly used. Constipation management was through high fibre diets (86.9%). Recommendations for spacing of meals and PD medications varied with 34.5% not making recommendations. Nutritional diagnosis (70.2%) and stage of disease (61.9%) guided monitoring frequency. Common outcome measures included appropriate weight change (97.6%) and regular bowel movements (88.1%). With limited PD-specific guidance, dietitians applied best available evidence for other groups with similar issues. Dietitians requested evidence-based guidelines specifically for the nutritional management of PD. Guideline development should focus on those areas reported as commonly encountered. This process can identify the gaps in evidence to guide future research.

Reported consumption of takeaway food and its contribution to socioeconomic inequalities in body mass index

The aim of this study was to examine whether takeaway food consumption mediated (explained) the association between socioeconomic position and body mass index (BMI). A postal-survey was conducted among 1500 randomly selected adults aged between 25 and 64 years in Brisbane, Australia during 2009 (response rate 63.7%, N=903). BMI was calculated using self-reported weight and height. Participants reported usual takeaway food consumption, and these takeaway items were categorised into "healthy" and "less healthy" choices. Socioeconomic position was ascertained by education, household income, and occupation. The mean BMI was 27.1kg/m(2) for men and 25.7kg/m(2) for women. Among men, none of the socioeconomic measures were associated with BMI. In contrast, women with diploma/vocational education (β=2.12) and high school only (β=2.60), and those who were white-collar (β=1.55) and blue-collar employees (β=2.83) had significantly greater BMI compared with their more advantaged counterparts. However, household income was not associated with BMI. Among women, the consumption of "less healthy" takeaway food mediated BMI differences between the least and most educated, and between those employed in blue collar occupations and their higher status counterparts. Decreasing the consumption of "less healthy" takeaway options may reduce socioeconomic inequalities in overweight and obesity among women but not men.

Validity of maternal-reported weight and height of children 2-5 year olds

To the Editor: In affluent-urban areas of India, overweight (6 %) and obesity (8 %) are prevalent in children as young as 2–5 y [1]. A potential risk factor for childhood obesity could be parent’s under-reporting their child’s anthropometry. In Indian culture, a larger body size is typically acceptable, and mothers may consider a chubby baby as healthy [2]. Therefore, it was proposed that Indian mothers may under-report their child’s weight status. The present study examined the validity of maternal reported height and weight of young, urban-affluent Indian children aged 2–5 y. After receiving approval from the QUT Human Research Ethics Committee, Australia 111 mothers with children aged 2–5 y attending private medical clinics (n = 5) in the affluent areas of Mumbai were recruited. Child’s height and weight were measured by the researcher using standard equipment/protocols. Mothers also reported their child’s height and weight.

Accuracy of mothers’ perceptions of their child’s weight status

The study examined the accuracy of maternal perceived child weight. Urban-affluent mothers with 111 children aged 2-5 years were recruited. Nearly a quarter of mothers overestimated their underweight child as healthyweight and all overweight/obese children were perceived as healthyweight. Mothers therefore were unable to recognize their child’s true weight status.

TNF and TNF receptor expression and insulin sensitivity in human omental and subcutaneous adipose tissue--influence of BMI and adipose distribution

Tumour necrosis factor (TNF)alpha is implicated in the relationship between obesity and insulin resistance/ type 2 diabetes. In an effort to understand this association better we (i) profiled gene expression patterns of TNF, TNFR1 and TNFR2 and (ii) investigated the effects of TNF on glucose uptake in isolated adipocytes and adipose tissue explants from omental and subcutaneous depots from lean, overweight and obese individuals. TNF expression correlated with expression of TNFR2, but not TNFR1, and TNF and TNFR2 expression increased in obesity. TNFR1 expression was higher in omental than in subcutaneous adipocytes. Expression levels of TNF or either receptor did not differ between adipocytes from individuals with central and peripheral obesity. TNF only suppressed glucose uptake in insulin-stimulated subcutaneous tissue and this suppression was only observed in tissue from lean subjects. These data support a relationship between the TNF system and body mass index (BMI), but not fat distribution, and suggest depot specificity of the TNF effect on glucose uptake. Furthermore, adipose tissue from obese subjects already appears insulin 'resistant' and this may be a result of the increased TNF levels.

Physical activity among children attending preschools

Objectives Obesity rates are increasing among children of all ages, and reduced physical activity is a likely contributor to this trend. Little is known about the physical activity behavior of preschool-aged children or about the influence of preschool attendance on physical activity. The purpose of this study was to describe the physical activity levels of children while they attend preschools, to identify the demographic factors that might be associated with physical activity among those children, and to determine the extent to which children's physical activity varies among preschools. Methods A total of 281 children from 9 preschools wore an Actigraph (Fort Walton Beach, FL) accelerometer for an average of 4.4 hours per day for an average of 6.6 days. Each child's height and weight were measured, and parents of participating children provided demographic and education data. Results The preschool that a child attended was a significant predictor of vigorous physical activity (VPA) and moderate-to-vigorous physical activity (MVPA). Boys participated in significantly more MVPA and VPA than did girls, and black children participated in more VPA than did white children. Age was not a significant predictor of MVPA or VPA. Conclusions Children's physical activity levels were highly variable among preschools, which suggests that preschool policies and practices have an important influence on the overall activity levels of the children the preschools serve.

Physical activity and determinants of physical activity in obese and non-obese children

OBJECTIVE To compare the physical activity (PA) patterns and the hypothesized psychosocial and environmental determinants of PA in an ethnically diverse sample of obese and non-obese middle school children. DESIGN Cross-sectional study. SUBJECTS One-hundred and thirty-three non-obese and 54 obese sixth grade children (mean age of 11.4 +/-0.6). Obesity status determined using the age-, race- and gender-specific 95th percentile for BMI from NHANES-1. MEASUREMENTS Objective measurements were collected of PA over a 7-day period using the CSA 7164 accelerometer: total daily counts; daily moderate (3-5.9 METs) physical activity (MPA); daily vigorous physical activity (greater than or equal to 6 METs; VPA); and weekly number of 5, 10 and 20 min bouts of moderate-to-vigorous physical activity (greater than or equal to 3 METs, MVPA). Self-report measures were collected of PA self-efficacy; social influences regarding PA, beliefs about PA outcomes; perceived PA levels of parents and peers, access to sporting and/or fitness equipment at home, involvement in community-based PA organizations; participation in community sports teams; and hours spent watching television or playing video games. RESULTS Compared to their non-obese counterparts, obese children exhibited significantly lower daily accumulations of total counts, MPA and VPA as well as significantly fewer 5, 10 and 20 min bouts of MVPA. Obese children reported significantly lower levels of PA self-efficacy, were involved in significantly fewer community organizations promoting PA and were significantly less likely to report their father or male guardian as physically active. CONCLUSIONS The results are consistent with the hypothesis that physical inactivity is an important contributing factor in the maintenance of childhood obesity. Interventions to promote PA in obese children should endeavor to boost self-efficacy perceptions regarding exercise, increase awareness of, and access to, community PA outlets, and increase parental modeling of PA.