Predictors of body mass index change in Australian primary school children

Objective. To assess associations between multiple potential predictors and change in child body mass index (BMI). Methods.In the 1997 Health of Young Victorians Study, children in Grades preparatory to three (aged 510 years) had their height and weight measured. Parents provided information on potential predictors of childhood overweight across six domains (children’s diet, children’s activity level, family composition, sociodemographic factors, prenatal factors and parental adiposity). Measures were repeated three years later in 2000/1. BMI was transformed to standardised (z) scores using the US 2000 Growth Chart data and children were classified as non-overweight or overweight according to international cutpoints.Regression analyses, including baseline BMI z-score as a covariate, assessed the contribution of each potential predictor to change in BMI z-score, development of overweight and spontaneous resolution of overweight in 1 373 children.Results. BMI z-score change was positively associated with frequency of take-away food, food quantity, total weekly screen time, non-Australian paternal country of birth, maternal smoking during pregnancy, and maternal and paternal BMI.Inverse associations were noted for the presence of siblings and rural residence (all pB0.05). Predictors of categorical change (development and resolution of overweight) were less clearly identified, apart from an association between maternal BMI and overweight development (p0.02). Multivariable models suggested individual determinants have a cumulative effect on BMI change. Conclusions. Strong short-term tracking of BMI makes it difficult to identify predictors of change. Nonetheless, putative determinants across all domains assessed were independently associated with adiposity change. Multi-faceted solutions are likely to be required to successfully deal with the complexities of childhood overweight.

Habitual active transport moderates the association of tv viewing time with body mass index

Background: Television viewing time is associated with obesity risk independent of leisure-time physical activity (LTPA). However,
it is unknown whether the relationship of TV viewing time with body mass index (BMI) is moderated by other domains of physical activity. Methods: A mail survey collected height;weight; TV viewing time; physical activity for transportation (habitual transport behavior; past week walking and bicycling), for recreation (LTPA), and in workplace; and sociodemographic variables in Adelaide, Australia. General linear models examined whether physical activity domains moderate the association between BMI and TV viewing time. Results: Analysis of the sample (N = 1408) found that TV time, habitual transport, and LTPA were independently associated with participant’s BMI. The interaction between TV time and habitual transport with BMI was significant, while that between TV time and LTPA was not. Subgroup analyses found that adjusted mean BMI was significantly higher for the high TV viewing category, compared with the low category,
among participants who were inactive and occasionally active in transport, but not among those who were regularly active. Conclusions: Habitual active transport appeared to moderate the relationship between TV viewing time and BMI. Obesity risk associated with prolonged TV viewing may be mitigated by regular active transport.

The longitudinal influence of home and neighbourhood environments on children's body mass index and physical activity over 5 years : the CLAN study

Objective: To determine the independent contributions of family and neighbourhood environments to changes in youth physical activity and body mass index (BMI) z-score over 5 years.

Methods: In 2001, 2004 and 2006, 301 children (10–12 years at baseline) had their height and weight measured (BMI was converted to z-scores using Centers for Disease Control and Prevention reference charts; see http://www.cdc.gov/growthcharts) and moderate-to-vigorous physical activity (MVPA) assessed using accelerometers. In 2001, parents reported on the home environment (social support, role modelling, rules and restrictions, physical environment) and perceived neighbourhood environment (local traffic, road safety, sporting venues, public transport), and Geographic Information Systems were used to map features of the neighbourhood environment (destinations, road connectivity, traffic exposure). Generalized estimating equations were used to predict average BMI z-score and MVPA over time from baseline home and perceived and objective neighbourhood environment factors.

Results: Among boys, maternal education and heavy traffic were inversely associated, and sibling physical activity, maternal role modelling of MVPA and the presence of dead-end roads were positively associated with MVPA. Having unmarried parents, maternal MVPA role modelling and number of home sedentary items were positively associated with BMI z-score among boys. Among girls, having siblings, paternal MVPA role modelling, physical activity rules and parental physical activity co-participation were positively associated with MVPA. Having unmarried parents and maternal sedentary behaviour role modelling were positively associated, and number of sedentary behaviour rules and physical activity items were inversely associated with BMI z-score among girls.

Conclusion: The home environment seems more important than the neighbourhood environment in influencing children's physical activity and BMI z-score over 5 years. Physical activity and weight gain programmes among youth should focus on parental role modelling, rules around sedentary and active pursuits, and parental support for physical activity. Intervention studies to investigate these strategies are warranted.

Breakfast size is related to body mass index for men, but not women

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.

Maternal correlates of preschool child eating behaviours and body mass index : a cross-sectional study

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.

The health-related quality of life of overweight and obese adolescents - a study measuring body mass index and adolescent-reported perceptions

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.

Involvement of young Australian adults in meal preparation : cross-sectional associations with abdominal obesity and body mass index

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.

Does an increase in body mass index over 10 years affect knee structure in a population-based cohort study of adult women?

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.

Prevalence of obesity and the relationship between the body mass index and body fat : cross-sectional, population-based data

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.

Changes in body mass index and health related quality of life from childhood to adolescence

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.