123 resultados para Body Mass Index


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The objective of this study was to examine the effect of self-reported breakfast size, daily eating, and other health habits on body mass index (BMI). We hypothesized that a consumption of a substantial breakfast compared with skipping or small breakfasts would be associated with lower BMI. Three independent, cross-sectional, screening surveys were conducted by Sydney Adventist Hospital in 1976, 1986, and 2005 in the surrounding community. The archived survey forms of 384 men and 338 women in 1976, 244 men and 229 women in 1986, and 270 men and 62 women in 2005 were randomly selected. Body mass index was determined from height and weight measured by hospital staff. The reported amount consumed at breakfast was one of several eating habits that predicted BMI for men but not women. It explained 5% to 6% of the variance in male BMI in all 3 years examined. As the reported breakfast amount increased, men's BMI decreased. Lifestyle confounders including vegetarianism and physical activity did not affect this relationship. However, the consumption of breakfast was significantly positively associated with consumption of cereals, bread, fruit, and spreads, while coffee consumption was significantly associated with smaller breakfasts or breakfast skipping. The consumption of relatively large breakfasts may influence BMI in men, and its promotion may help reduce the prevalence of obesity in Australia and elsewhere.

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To the authors’ knowledge, this is the first study to evaluate maternal child feeding practices, maternal parenting characteristics and mother-child interactions as cross-sectional predictors of child eating and/or weight within the one sample. Maternal pressure for her child to eat was a significant positive correlate of fussiness and a negative correlate of enjoyment. Maternal parenting warmth was associated negatively with child BMIz, while mother-child dysfunctional interaction was associated positively with child BMIz. Our findings suggest that childhood obesity research may be better informed by evaluating not just what mothers do (feeding practices) but also how they parent (parenting behaviours and interactions with their child). Longitudinal studies are needed to identify causal influences of parenting on preschool child eating and weight.

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Objective. To determine whether the health-related quality of life (HRQOL) of overweight and obese adolescents is significantly lower than that of their healthy weight counterparts, and if so, whether any demographic trends exist and the relative contribution of each HRQOL dimension.

Methods.
Cross-sectional analysis of 2,890 students participating in the Pacific Obesity Prevention in Communities Project, Australia. HRQOL was measured using the Pediatric Quality of Life Inventory (PedsQL) adolescent module. Adolescent height and weight were measured by trained field workers and weight categories assigned according to the International Obesity Task Force BMI cut-off points for adolescents. Multivariate linear regression analyses were undertaken to estimate the mean differences in HRQOL scores between (i) overweight and healthy weight, and (ii) obese and healthy weight adolescents, whilst adjusting for gender, age and socioeconomic status quartile.

Results.
The sample had a mean age of 14.6 years (range 11–18), 56.2% boys, 20.2% overweight and 6.3% obese. Higher weight status categories were associated with lower HRQOL scores (mean PedsQL scores: healthy weight: 79.1, overweight: 77.7 and obese: 73.7). Relative to the healthy weight group, and after adjustments, overweight and obese adolescents reported 1.44 (p = 0.005) and 5.55 (p < 0.001) lower HRQOL summary scores, respectively. Overweight adolescents reported significantly lower scores in physical and social functioning, whilst obese adolescents reported significantly lower scores in the same dimensions plus emotional functioning. Girls and younger (< 15 years) adolescents reported greater mean negative HRQOL differences associated with excess weight.

Conclusions.
Overweight and obesity in adolescents are associated with significantly lower HRQOL scores.

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Previous research has shown that involvement in meal preparation is positively associated with better diet quality. However, it is unclear whether there is an association between involvement in meal preparation and being overweight or obese. This study investigated whether the level of involvement in meal preparation was associated with objectively measured weight status in young adults. During 2004-2006, a national sample of 1,996 Australian adults aged 26 to 36 years completed a self-administered questionnaire including questions on sociodemographic characteristics, diet, and physical activity. Participants were asked to report who usually prepared the main meal on working days and responses were categorized as “myself,” “shared,” or “someone else.” Waist circumference, weight, and height were measured by trained staff. Moderate abdominal obesity was defined as waist circumference >94 cm for men and >80 cm for women. Overweight was defined as body mass index (calculated as kg/m2) >25. Prevalence ratios were calculated using log binomial regression. After adjusting for age, education, and leisure time physical activity, men who shared the meal preparation had a slightly lower prevalence of moderate abdominal obesity (prevalence ratio=0.92; 95% confidence interval [CI]: 0.86 to 0.99) than those whose meals were usually prepared by someone else. There was no association with having sole responsibility (prevalence ratio=0.99; 95% CI: 0.92 to 1.06). There were no associations between level of involvement in meal preparation and being overweight (shared responsibility prevalence ratio=0.99; 95% CI: 0.92 to 1.07; sole responsibility prevalence ratio=0.98; 95% CI: 0.91 to 1.05). For women, level of involvement was not associated with moderate abdominal obesity (shared responsibility prevalence ratio=0.93; 95% CI: 0.84 to 1.03; sole responsibility prevalence ratio=0.94; 95% CI: 0.86 to 1.03) or being overweight (shared responsibility prevalence ratio=0.93; 95% CI: 0.84 to 1.02; sole responsibility prevalence ratio=0.93; 95% CI: 0.85 to 1.02). In this sample of young adults, level of involvement in meal preparation was not strongly related to weight status.

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Introduction : Although obesity is a modifiable risk factor for knee osteoarthritis (OA), the effect of weight gain on knee structure in young and healthy adults has not been examined. The aim of this study was to examine the relationship between body mass index (BMI), and change in BMI over the preceding 10-year period, and knee structure (cartilage defects, cartilage volume and bone marrow lesions (BMLs)) in a population-based sample of young to middle-aged females.

Methods :
One hundred and forty-two healthy, asymptomatic females (range 30 to 49 years) in the Barwon region of Australia, underwent magnetic resonance imaging (MRI) during 2006 to 2008. BMI measured 10 years prior (1994 to 1997), current BMI and change in BMI (accounting for baseline BMI) over this period, was assessed for an association with cartilage defects and volume, and BMLs.

Results :
After adjusting for age and tibial plateau area, the risk of BMLs was associated with every increase in one-unit of baseline BMI (OR 1.14 (95% CI 1.03 to 1.26) P = 0.009), current BMI (OR 1.13 (95% CI 1.04 to 1.23) P = 0.005), and per one unit increase in BMI (OR 1.14 (95% CI 1.03 to 1.26) P = 0.01). There was a trend for a one-unit increase in current BMI to be associated with increased risk of cartilage defects (OR 1.06 (95% CI 1.00 to 1.13) P = 0.05), and a suggestion that a one-unit increase in BMI over 10 years may be associated with reduced cartilage volume (-17.8 ml (95% CI -39.4 to 3.9] P = 0.10). Results remained similar after excluding those with osteophytes.

Conclusions :
This study provides longitudinal evidence for the importance of avoiding weight gain in women during early to middle adulthood as this is associated with increased risk of BMLs, and trend toward increased tibiofemoral cartilage defects. These changes have been shown to precede increased cartilage loss. Longitudinal studies will show whether avoiding weight gain in early adulthood may play an important role in diminishing the risk of knee OA.

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Background: Anthropometric measures such as the body mass index (BMI) and waist circumference are widely used as convenient indices of adiposity, yet there are limitations in their estimates of body fat. We aimed to determine the prevalence of obesity using criteria based on the BMI and waist circumference, and to examine the relationship between the BMI and body fat.

Methodology/Principal Findings: This population-based, cross-sectional study was conducted as part of the Geelong Osteoporosis Study. A random sample of 1,467 men and 1,076 women aged 20–96 years was assessed 2001–2008. Overweight and obesity were identified according to BMI (overweight 25.0–29.9 kg/m2; obesity $30.0 kg/m2) and waist circumference (overweight men 94.0–101.9 cm; women 80.0–87.9 cm; obesity men $102.0 cm, women $88.0 cm); body fat mass was assessed using dual energy X-ray absorptiometry; height and weight were measured and lifestyle factors documented by self-report. According to the BMI, 45.1% (95%CI 42.4–47.9) of men and 30.2% (95%CI 27.4–33.0) of women were overweight and a further 20.2% (95%CI 18.0–22.4) of men and 28.6% (95%CI 25.8–31.3) of women were obese. Using waist circumference, 27.5% (95%CI 25.1–30.0) of men and 23.3% (95%CI 20.8–25.9) of women were overweight, and 29.3% (95%CI 26.9–31.7) of men and 44.1% (95%CI 41.2–47.1) of women, obese. Both criteria indicate that approximately 60% of the population exceeded recommended thresholds for healthy body habitus. There was no consistent pattern apparent between BMI and energy intake. Compared with women, BMI overestimated adiposity in men, whose excess weight was largely attributable to muscular body builds and greater bone mass. BMI also underestimated adiposity in the elderly. Regression models including gender, age and BMI explained 0.825 of the variance in percent body fat.

Conclusions/Significance: As the BMI does not account for differences in body composition, we suggest that gender- and age-specific thresholds should be considered when the BMI is used to indicate adiposity.

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Objective . To determine longitudinal relationships between body mass index (BMI) and health-related quality of life (HRQoL) in an adolescent population sample.
Design. Data collected in 2000 and 2005 within the Health of Young Victorians longitudinal cohort study.
Setting. Originally a community sample of elementary school students in Victoria, Australia. Follow-up occurred in either secondary schools or individuals homes.
Participants. Cohort recruited in 1997 via a random sampling design from Victorian elementary schools. Originally comprising 1 943 children, 1 569 (80.8%) participated in 2000 (wave 2, 8 – 13 years) and 851 (54%) in 2005 (wave 3, 13 – 19 years).
Main outcome measures. In both waves participants and their parents completed the PedsQL, a 23-item child HRQoL measure, and BMI z-scores and status (non-overweight, overweight or obese) were calculated from measured height and weight. Associations were tested cross-sectionally and longitudinally (linear regression, adjusted for baseline values)
Results. A total of 81.6% remained in the same BMI category, while 11.4% and 7.0% moved to higher and lower categories, respectively. Cross-sectional inverse associations between lower PedsQL and higher BMI categories were similar to those for elementary school children. Wave 2 BMI strongly predicted wave 3 BMI and wave 2 PedsQL strongly predicted wave 3 PedsQL. Only parent-reported Total PedsQL score predicted higher subsequent BMI, though this effect was small. Wave 2 BMI did not predict wave 3 PedsQL.
Conclusions. This novel study confi rmed previous cross-sectional associations, but did not provide convincing evidence that
BMI is causally associated with falling HRQoL or vice versa across the transition from childhood to adolescence.

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This study extends McPhie et al. (2011)'s [Maternal correlates of preschool child eating behaviours and body mass index: A cross-sectional study. International Journal of Pediatric Obesity, Early Online, 1–5.] McPhie et al. (2011)’s cross-sectional research, by prospectively evaluating maternal child-feeding practices, parenting style and mother–child interactions as predictors of child-eating behaviours, food habits and weight. A sample of 117 mothers of preschoolers (63 girls, 54 boys) participated at two time-points, Time 1 (T1) and Time 2 (T2), 12 months apart. Results from the two path models revealed maternal pressure to eat at T1 positively predicted change in child enjoyment of food. Maternal warmth at T1 negatively predicted child unhealthy food habits at T2. At T1, family income and maternal control negatively predicted change in child body mass index z-scores (BMIz); maternal pressure to eat at T1 also positively predicted change in child BMIz. There were significant results specific to each model. Both final path models provided an adequate fit. Our findings suggest childhood obesity is predicted by a complex interplay of demographic, maternal and child variables.

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This paper is a conceptual and methodological review of the literature on the impact of TV on preschoolers' weight status. A systematic search, of papers published between January 1995 and January 2010, identified twenty-six relevant studies. Fifteen of these were cross-sectional in design and eleven adopted a prospective design; a positive association between hours of TV and child adiposity was found in all but three studies. Although assessed in a limited number of studies, diet may mediate the relationship between TV viewing and BMI. Another likely mediator may be the content of TV programs watched; only three studies examined this association and findings were inconsistent. Our review revealed that research examining mediating effects is limited, focusing more on simple cross-sectional or prospective relationships between TV habits and child body mass index. Further investigation of the mechanisms by which TV viewing affects preschool weight gain is needed.

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Background

This study aimed to examine associations between aspects of the neighborhood social environment and body mass index (BMI) in youth both cross-sectionally and prospectively; and whether this association was mediated by physical activity, screen-time and sedentary time.
Methods

Data were collected in 2004 and 2006 in high and low socio-economic areas of Melbourne, Australia. In 2004, 185 children aged 8-9 years (47% boys) and 359 children aged 13-15 years (45% boys) participated. Parents reported their perceptions of aspects of the social environment (i.e. social networks and social trust/cohesion), and physical activity (i.e. time spent outdoors by their children; and their younger children's walking and cycling trips) and screen-time (i.e. TV viewing, computer use). The older children self-reported their walking and cycling trips and their screen-time. All children wore an accelerometer to objectively assess outside-school hours moderate- to-vigorous physical activity and sedentary time. BMI was calculated from height and weight measured in 2004 and 2006. Multilevel linear regression analyses were conducted to examine associations between the social environment and BMI. Mediation analyses using the products of coefficient method were conducted to determine whether associations between the social environment and BMI were mediated by the time spent in a range of physical activity and sedentary behaviors.
Results

Cross-sectional and prospective regression analyses showed that a more positive social network and higher social trust/cohesion was related to lower BMI among children. There was no evidence that time spent in physical activity or sedentary behaviors mediated this relation, despite significant associations between social networks and screen-time and between screen-time and BMI.
Conclusions

The findings suggest that the neighborhood social environment may be important for preventing overweight and obesity in children. Further research investigating the mechanisms through which the neighborhood social environment exerts its effect on BMI is needed.