913 resultados para acute care, body mass index (BMI), clinical outcomes, corrected arm muscle area (CAMA), covariates, dementia, depression, dietitian referral, discharge destination, elderly, functional status, geriatric, hospitalised, length of stay (LOS), malnutrition


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Objective: To explore the relationship between family average income (FAI; an index of socio-economic status) and body mass index (BMI; a widely used, inexpensive indicator of weight status) above the healthy weight range in a region of Mainland China. Design: Population-based cross-sectional study, conducted between October 1999 and March 2000 on a sample of regular local residents aged 35 years or older who were selected by random cluster sampling. Setting: Forty-five administrative villages selected from three urban districts and two rural counties of Nanjing municipality, Mainland China, with a regional population of 5.6 million. Subjects: In total, 29 340 subjects participated; 67.7% from urban and 32.3% from rural areas; 49.8% male and 50.2% female. The response rate among eligible participants was 90.1%. Results: The proportion of participants classified as overweight was 30.5%, while 7.8% were identified as obese. After adjusting for possible confounding variables (age, gender, area of residence, educational level, occupational and leisure-time physical activity, daily vegetable consumption and frequency of red meat intake), urban participants were more likely to be overweight or obese relative to their rural counterparts, more women than men were obese, and participants in the lowest FAI tertile were the least likely to be above the healthy weight range. Conclusions: The proportion of adults with BMI above the healthy weight range was positively related to having a higher socio-economic status (indexed by FAI) in a regional Chinese population.

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Issues of body image and ability to achieve intimacy are connected to body weight, yet remain largely unexplored and have not been evaluated by gender. The underlying purpose of this research was to determine if avoidant attitudes and perceptions of one's body may hold implications toward its use in intimate interactions, and if an above average body weight would tend to increase this avoidance. The National Health and Nutrition Examination Survey (NHANES, 1999-2002) finds that 64.5% of US adults are overweight, with 61.9% of women and 67.2% of men. The increasing prevalence of overweight and obesity in men and women shows no reverse trend, nor have prevention and treatment proven effective in the long term. The researcher gathered self-reported age, gender, height and weight data from 55 male and 58 female subjects (determined by a prospective power analysis with a desired medium effect size (r=.30) to determine body mass index (BMI), determining a mean age of 21.6 years and mean BMI of 25.6. Survey instruments consisted of two scales that are germane to the variables being examined. They were (1) Descutner and Thelen of the University of Missouri‘s (1991) Fear-of-Intimacy scale; and (2) Rosen, Srebnik, Saltzberg, and Wendt's (1991) Body Image Avoidance Questionnaire. Results indicated that as body mass index increases, fear of intimacy increases (p<0.05) and that as body mass index increases, body image avoidance increases (p<0.05). The relationship that as body image avoidance increases, fear of intimacy increases was not supported, but approached significance at (p<0.07). No differences in these relationships were determined between gender groups. For age, the only observed relationship was that of a difference between scores for age groups [18 to 22 (group 1) and ages 23 to 34 (group 2)] for the relationship of body image avoidance and fear of intimacy (p<0.02). The results suggest that the relationship of body image avoidance and fear of intimacy, as well as age, bear consideration toward the escalating prevalence of overweight and obesity. An integrative approach to body weight that addresses issues of body image and intimacy may prove effective in prevention and treatment.

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Issues of body image and ability to achieve intimacy are connected to body weight, yet remain largely unexplored and have not been evaluated by gender. The underlying purpose of this research was to determine if avoidant attitudes and perceptions of one’s body may hold implications toward its use in intimate interactions, and if an above average body weight would tend to increase this avoidance. The National Health and Nutrition Examination Survey (NHANES, 1999-2002) finds that 64.5% of US adults are overweight, with 61.9% of women and 67.2% of men. The increasing prevalence of overweight and obesity in men and women shows no reverse trend, nor have prevention and treatment proven effective in the long term. The researcher gathered self-reported age, gender, height and weight data from 55 male and 58 female subjects (determined by a prospective power analysis with a desired medium effect size (r =.30) to determine body mass index (BMI), determining a mean age of 21.6 years and mean BMI of 25.6. Survey instruments consisted of two scales that are germane to the variables being examined. They were (1) Descutner and Thelen of the University of Missouri’s (1991) Fear-of-Intimacy scale and (2) Rosen, Srebnik, Saltzberg, and Wendt’s (1991) Body Image Avoidance Questionnaire. Results indicated that as body mass index increases, fear of intimacy increases (p<0.05) and that as body mass index increases, body image avoidance increases (p<0.05). The relationship that as body image avoidance increases, fear of intimacy increases was not supported, but approached significance at (p<0.07). No differences in these relationships were determined between gender groups. For age, the only observed relationship was that of a difference between scores for age groups [18 to 22 (group 1) and ages 23 to 34 (group 2)] for the relationship of body image avoidance and fear of intimacy (p<0.02). The results suggest that the relationship of body image avoidance and fear of intimacy, as well as age, bear consideration toward the escalating prevalence of overweight and obesity. An integrative approach to body weight that addresses issues of body image and intimacy may prove effective in prevention and treatment.

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The maintenance of normal body weight is disrupted in patients with anorexia nervosa (AN) for prolonged periods of time. Prior to the onset of AN, premorbid body mass index (BMI) spans the entire range from underweight to obese. After recovery, patients have reduced rates of overweight and obesity. As such, loci involved in body weight regulation may also be relevant for AN and vice versa. Our primary analysis comprised a cross-trait analysis of the 1000 single-nucleotide polymorphisms (SNPs) with the lowest P-values in a genome-wide association meta-analysis (GWAMA) of AN (GCAN) for evidence of association in the largest published GWAMA for BMI (GIANT). Subsequently we performed sex-stratified analyses for these 1000 SNPs. Functional ex vivo studies on four genes ensued. Lastly, a look-up of GWAMA-derived BMI-related loci was performed in the AN GWAMA. We detected significant associations (P-values <5 × 10(-5), Bonferroni-corrected P<0.05) for nine SNP alleles at three independent loci. Interestingly, all AN susceptibility alleles were consistently associated with increased BMI. None of the genes (chr. 10: CTBP2, chr. 19: CCNE1, chr. 2: CARF and NBEAL1; the latter is a region with high linkage disequilibrium) nearest to these SNPs has previously been associated with AN or obesity. Sex-stratified analyses revealed that the strongest BMI signal originated predominantly from females (chr. 10 rs1561589; Poverall: 2.47 × 10(-06)/Pfemales: 3.45 × 10(-07)/Pmales: 0.043). Functional ex vivo studies in mice revealed reduced hypothalamic expression of Ctbp2 and Nbeal1 after fasting. Hypothalamic expression of Ctbp2 was increased in diet-induced obese (DIO) mice as compared with age-matched lean controls. We observed no evidence for associations for the look-up of BMI-related loci in the AN GWAMA. A cross-trait analysis of AN and BMI loci revealed variants at three chromosomal loci with potential joint impact. The chromosome 10 locus is particularly promising given that the association with obesity was primarily driven by females. In addition, the detected altered hypothalamic expression patterns of Ctbp2 and Nbeal1 as a result of fasting and DIO implicate these genes in weight regulation.

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This Q and A style briefing paper provides an overview of the use of body mass index (BMI) for the measurement of obesity. BMI is a person’s weight in kilograms divided by the square of their height in metres. It is one of the most commonly used ways of estimating whether a person is overweight and hence more likely to experience health problems than someone with a healthy weight. It is used to measure population prevalence of overweight and obesity. It is also a relatively easy, cheap and non-invasive method for establishing weight status. However, BMI is only a proxy for body fatness. Factors such as fitness, ethnic origin and puberty can alter the relation between BMI and body fatness and must be taken into consideration. Other measurements such as waist circumference and skin thickness can be collected to indicate a person’s weight status or body fatness. None of these is as widely used as BMI.

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This report is the sixth in a series of annual reports which use National Child Measurement Programme (NCMP) data to examine changes in children’s body mass index (BMI) that have taken place since 2006/07. It explores trends in obesity, overweight, excess weight and underweight prevalence, as well as changes in mean BMI over time. Trends within different socioeconomic and ethnic groups are also examined to determine whether existing health inequalities are widening or becoming smaller.

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The prevalence of overweight and obesity among children is increasing; hence, it was aimed to assess the Body Mass Index (BMI) in school children aged from 10 to 18 years for girls and to 17 for boys, as well as to identify the factors influencing BMI. This study included 742 students who answered a questionnaire previously approved for application in schools. The results showed some sociodemographic factors associated with BMI classes: age, school year, practicing high competition sport, being federate in a sport or having a vegetarian diet. The educational factors associated with BMI classes included only seminars given at school by a nutritionist. Behavioural factors significantly associated with BMI included: learning in classes, playing in the open air, reading books or use of internet. As conclusion, the results demonstrated that several factors affect BMI, and hence some actions could be taken in order to change them so as to reduce the prevalence of overweight, namely reinforcing the role of school and a more active participation of nutritionists in the education of the adolescents.

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The Republic of Korea (Korea) has been composed of a single ethnic group and, until very recently, has had little or no experience with large-volume of immigrants. The country, once known for its large-scale emigration, has emerged as a popular destination. As the foreign-born populations continue to grow, they experience dietary pattern changes. Dietary changes of immigrants are often associated with weight increase and consequently the risk of non-communicable diseases such as diabetes. This study examined the association of demographic variables and dietary habits on Body Mass Index (BMI) of foreign nationals living in Korea, based on a cross-sectional sample of 193 foreign-born men (120) and women (73). A web-based survey program, Zoho survey, was used to capture self-reported region of origin, socio-demographic variables, weight, height, frequency of physical activity, and food frequencies. For the entire sample (n=193), the World Health Organization (WHO) classification and the Korean Society for the Study of Obesity cut-off points of BMI were used. The average BMI was 24.6 (SD=3.6) kg/m2. Significant associations were observed between BMI and age (χ² (8, N=193) =26.22, p<.01), gender (χ² (2, N=193) =11.45, p<.01), and religious affiliation (χ² (4, N=191) =9.53, p<.05). On average, participants had meat and carbonated drinks 2.2 times a week; high calorie foods 1.5 times a week; and, dairy products 2.4 times a week. A significant correlation (r=.14, p<.05) between BMI and eating meat was also observed. This study showed that the BMI varied with age, gender and religion. Frequent consumption of meat was associated with a significant increase in BMI. This increase in BMI could be associated with the dietary changes experienced by the newcomers or absence of more familiar products. Consequently, as the volume of immigrants continues to increase in Korea, it is imperative to consider designing and implementing public health policies specifically in relation to a healthy diet that can impact the prevalence of preventable chronic diseases. Thus, health education among foreign-born population in Korea should focus on reducing the intake of meat and high energy foods.

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BACKGROUND: The relationship between socioeconomic position and obesity has been clearly established, however, the extent to which specific behavioural factors mediate this relationship is less clear. This study aimed to ascertain the contribution of specific dietary elements and leisure-time physical activity (LTPA) to variations in obesity with education in the baseline (1990-1994) Melbourne Collaborative Cohort Study (MCCS).

METHODS: 18, 489 women and 12, 141 men were included in this cross-sectional analysis. A series of linear regression models were used in accordance with the products of coefficients method to examine the mediating role of alcohol, soft drink (regular and diet), snacks (healthy and sweet), savoury items (healthy and unhealthy), meeting fruit and vegetable guidelines and LTPA on the relationship between education and body mass index (BMI).

RESULTS: Compared to those with lowest educational attainment, those with the highest educational attainment had a 1 kg/m2 lower BMI. Among men and women, 27% and 48%, respectively, of this disparity was attributable to differences in LTPA and diet. Unhealthy savoury item consumption and LTPA contributed most to the mediated effects for men and women. Alcohol and diet soft drink were additionally important mediators for women.

CONCLUSIONS: Diet and LTPA are potentially modifiable behavioural risk factors for the development of obesity that contribute substantially to inequalities in BMI. Our findings highlight the importance of specific behaviours which may be useful to the implementation of effective, targeted public policy to reduce socioeconomic inequalities in obesity.

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OBJECTIVE: To determine the risk of mortality associated with and quantify the deaths attributable to combinations of body mass index (BMI) and waist circumference (WC). METHODS: This study included 41,439 participants. For the hazard ratio (HR) calculation, adiposity categories were defined as: BMI(N) /WC(N) , BMI(N) /WC(O) , BMI(O) /WC(N) , and BMI(O) /WC(O) (N = non-obese, O = obese). For the population attributable fraction analysis, obesity was classified as: (i) obese by BMI and/or WC; (ii) obese by BMI; and (iii) obese by WC. Mortality data was complete to the end of 2012. RESULTS: The prevalence of BMI(N) /WC(N) , BMI(N) /WC(O) , BMI(O) /WC(N) , and BMI(O) /WC(O) was 73%, 6%, 6%, and 15%, respectively. There was an increased risk of all-cause and cardiovascular disease (CVD) mortality in those with BMI(N) /WC(O) (HR (95% CI) 1.2 (1.2, 1.3) and 1.3 (1.1, 1.6)) and BMI(O) /WC(O) (1.3 (1.3, 1.4) and 1.7 (1.5, 1.9)) compared to those with BMI(N) /WC(N) . The estimated proportion of all-cause and CVD mortality attributable to obesity defined using WC or using BMI and/or WC was higher compared to obesity defined using BMI. CONCLUSIONS: Current population obesity monitoring misses those with BMI(N) /WC(O) who are at increased risk of mortality. By targeting reductions in population WC, the potential exists to prevent more deaths in the population than if we continue to target reductions in BMI alone.

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Background: Although the negative consequences on health of being obese are well known, most adults gain weight across the lifespan. The general increase in body mass index (BMI) is mainly considered to originate from behavioral and environmental changes; however, few studies have evaluated the influence of these factors on change in BMI in the presence of genetic risk. We aimed to study the influence of multifactorial causes of change in BMI, over 65 years. Methods and Findings: Totally, 6130 participants from TwinGene, who had up to five assessments, and 536 from the Swedish Adoption/Twin Study of Aging, who had up to 12 assessments, ranging over 65 years were included. The influence of lifestyle factors, birth cohort, cardiometabolic diseases and an individual obesity genetic risk score (OGRS) based on 32 single nucleotide polymorphisms on change in BMI was evaluated with a growth model. For both sexes, BMI increased from early adulthood to age of 65 years, after which the increase leveled off; BMI declined after age of 80 years. A higher OGRS, birth after 1925 and cardiometabolic diseases were associated with higher average BMI and a steeper increase in BMI prior to 65 years of age. Among men, few factors were identified that influence BMI trajectories in late life, whereas for women type 2 diabetes mellitus and dementia were associated with a steeper decrease in BMI after the age of 65 years. Conclusions: There are two turning points in BMI in late adulthood, one at the age of 65 years and one at the age 80 years. Factors associated with an increase in BMI in midlife were not associated with an increase in BMI after the age of 65 years. These findings indicate that the causes and consequences of change in BMI differ across the lifespan. Current health recommendations need to be adjusted accordingly.

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This study examined the prospective associations of reallocating time spent in different types of sedentary behavior, physical activity, and sleep with body mass index (BMI) in children using isotemporal substitution analysis. Methods Chinese children in grades 1-3 were recruited to a cohort study in 2009 and were followed up over a 2-yr period. Reports were gathered from the parents on children's sedentary behavior, sleep duration, and sociodemographic variables. The reported sedentary behavior types were then grouped into three categories: screen time (e.g., watching TV), academic-related activities (e.g., doing homework), and other sedentary behaviors (e.g., sitting and talking). Moderate-to-vigorous physical activity (MVPA) and light-intensity physical activity were assessed by ActiGraph accelerometry (ActiGraph, Pensacola, FL). Isotemporal substitution models were performed to examine the effects of time allocation on BMI. Results A total of 672 children (359 boys, mean age at recruitment = 7.6 yr) who had provided valid accelerometer data for at least one assessment time point were included in the analysis. Controlling for covariates and total behavior time, isotemporal substitution models indicated that the displacement of 30 min·d -1 of other sedentary behaviors with equal amounts of screen time (B = 0.12; 95% confidence interval, 0.04-0.20) or academic-related activities (B = 0.13; 95% confidence interval, 0.04-0.21) was associated with higher BMI. Reallocating 30 min·d -1 of MVPA with each of the sedentary behavior variables resulted in increased BMI. Conclusions The substitution of screen time or academic-related activities with other sedentary behaviors or MVPA was associated with lower BMI in Chinese children.

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BACKGROUND: The aim of this country-wide study was to link individual health and behavioural data with area-level spatial data to examine whether the body mass index (BMI) of adults was associated with access to recreational physical activity (PA) facilities by different modes of transport (bus, car, walking, cycling) and the extent to which any associations were mediated by PA participation. METHODS: Data on individual objectively-measured BMI, PA (number of days of (a) ≥20 min of moderate-to-vigorous PA, and (b) ≥15 min of sport or exercise, in previous 4 weeks), and socio-demographic characteristics were obtained from a nationally representative sample of 6365 adults. The number of accessible PA facilities per 1,000 individuals in each small area (data zones) was obtained by mapping a representative list of all fixed PA facilities throughout mainland Scotland. A novel transport network was developed for the whole country, and routes on foot, by bike, by car and by bus from the weighted population centroid of each data zone to each facility were calculated. Separate multilevel models were fitted to examine associations between BMI and each of the 24 measures of accessibility of PA facilities and BMI, adjusting for age, gender, longstanding illness, car availability, social class, dietary quality and urban/rural classification. RESULTS: We found associations (p < 0.05) between BMI and 7 of the 24 accessibility measures, with mean BMI decreasing with increasing accessibility of facilities-for example, an estimated decrease of 0.015 BMI units per additional facility within a 20-min walk (p = 0.02). None of these accessibility measures were found to be associated with PA participation. CONCLUSIONS: Our national study has shown that some measures of the accessibility of PA facilities by different modes of transport (particularly by walking and cycling) were associated with BMI; but PA participation, as measured here, did not appear to play a part in this relationship. Understanding the multi-factorial environmental influences upon obesity is key to developing effective interventions to reduce it.

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Rationale: The Australasian Nutrition Care Day Survey (ANCDS) evaluated if malnutrition and decreased food intake are independent risk factors for negative outcomes in hospitalised patients. Methods: A multicentre (56 hospitals) cross-sectional survey was conducted in two phases. Phase 1 evaluated nutritional status (defined by Subjective Global Assessment) and 24-hour food intake recorded as 0, 25, 50, 75, and 100% intake. Phase 2 data, which included length of stay (LOS), readmissions and mortality, were collected 90 days post-Phase 1. Logistic regression was used to control for confounders: age, gender, disease type and severity (using Patient Clinical Complexity Level scores). Results: Of 3122 participants (53% males, mean age: 65±18 years) 32% were malnourished and 23% consumed�25% of the offered food. Median LOS for malnourished (MN) patients was higher than well-nourished (WN) patients (15 vs. 10 days, p<0.0001). Median LOS for patients consuming �25% of the food was higher than those consuming �50% (13 vs. 11 days, p<0.0001). MN patients had higher readmission rates (36% vs. 30%, p = 0.001). The odds ratios of 90-day in-hospital mortality were 1.8 times greater for MN patients (CI: 1.03 3.22, p = 0.04) and 2.7 times greater for those consuming �25% of the offered food (CI: 1.54 4.68, p = 0.001). Conclusion: The ANCDS demonstrates that malnutrition and/or decreased food intake are associated with longer LOS and readmissions. The survey also establishes that malnutrition and decreased food intake are independent risk factors for in-hospital mortality in acute care patients; and highlights the need for appropriate nutritional screening and support during hospitalisation. Disclosure of Interest: None Declared.

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Introduction:  Smoking status in outpatients with chronic obstructive pulmonary disease (COPD) has been associated with a low body mass index (BMI) and reduced mid-arm muscle circumference (Cochrane & Afolabi, 2004). Individuals with COPD identified as malnourished have also been found to be twice as likely to die within 1 year compared to non-malnourished patients (Collins et al., 2010). Although malnutrition is both preventable and treatable, it is not clear what influence current smoking status, another modifiable risk factor, has on malnutrition risk. The current study aimed to establish the influence of smoking status on malnutrition risk and 1-year mortality in outpatients with COPD. Methods:  A prospective nutritional screening survey was carried out between July 2008 and May 2009 at a large teaching hospital (Southampton General Hospital) and a smaller community hospital within Hampshire (Lymington New Forest Hospital). In total, 424 outpatients with a diagnosis of COPD were routinely screened using the ‘Malnutrition Universal Screening Tool’, ‘MUST’ (Elia, 2003); 222 males, 202 females; mean (SD) age 73 (9.9) years; mean (SD) BMI 25.9 (6.4) kg m−2. Smoking status on the date of screening was obtained for 401 of the outpatients. Severity of COPD was assessed using the GOLD criteria, and social deprivation determined using the Index of Multiple Deprivation (Nobel et al., 2008). Results:  The overall prevalence of malnutrition (medium + high risk) was 22%, with 32% of current smokers at risk (who accounted for 19% of the total COPD population). In comparison, 19% of nonsmokers and ex-smokers were likely to be malnourished [odds ratio, 1.965; 95% confidence interval (CI), 1.133–3.394; P = 0.015]. Smoking status remained an independent risk factor for malnutrition even after adjustment for age, social deprivation and disease-severity (odds ratio, 2.048; 95% CI, 1.085–3.866; P = 0.027) using binary logistic regression. After adjusting for age, disease severity, social deprivation, smoking status, malnutrition remained a significant predictor of 1-year mortality [odds ratio (medium + high risk versus low risk), 2.161; 95% CI, 1.021–4.573; P = 0.044], whereas smoking status did not (odds ratio for smokers versus ex-smokers + nonsmokers was 1.968; 95% CI, 0.788–4.913; P = 0.147). Discussion:  This study highlights the potential importance of combined nutritional support and smoking cessation in order to treat malnutrition. The close association between smoking status and malnutrition risk in COPD suggests that smoking is an important consideration in the nutritional management of malnourished COPD outpatients. Conclusions:  Smoking status in COPD outpatients is a significant independent risk factor for malnutrition and a weaker (nonsignificant) predictor of 1-year mortality. Malnutrition significantly predicted 1 year mortality. References:  Cochrane, W.J. & Afolabi, O.A. (2004) Investigation into the nutritional status, dietary intake and smoking habits of patients with chronic obstructive pulmonary disease. J. Hum. Nutr. Diet.17, 3–11. Collins, P.F., Stratton, R.J., Kurukulaaratchym R., Warwick, H. Cawood, A.L. & Elia, M. (2010) ‘MUST’ predicts 1-year survival in outpatients with chronic obstructive pulmonary disease. Clin. Nutr.5, 17. Elia, M. (Ed) (2003) The ‘MUST’ Report. BAPEN. http://www.bapen.org.uk (accessed on March 30 2011). Nobel, M., McLennan, D., Wilkinson, K., Whitworth, A. & Barnes, H. (2008) The English Indices of Deprivation 2007. http://www.communities.gov.uk (accessed on March 30 2011).