Trends in body mass index and obesity prevalence in Western Australian adults, 2002 to 2015

2018 ◽  
Vol 30 (1) ◽  
pp. 60-65 ◽  
Author(s):  
Matt Merema ◽  
Emily O'Connell ◽  
Sarah Joyce ◽  
Joanne Woods ◽  
Denise Sullivan
Keyword(s):  
Body Mass Index ◽  
Body Mass ◽  
Obesity Prevalence ◽  
Western Australian

scholarly journals Challenging the “jolly fat” hypothesis among older adults: High body mass index predicts increases in depressive symptoms over a 5-year period

2016 ◽  
Vol 23 (1) ◽  
pp. 48-58 ◽  
Author(s):  
Peter Joseph Dearborn ◽  
Michael A Robbins ◽  
Merrill F Elias
Keyword(s):  
Older Adults ◽  
Body Mass Index ◽  
Depressive Symptoms ◽  
Body Mass ◽  
Functional Limitations ◽  
High Body Mass Index ◽  
Obesity Prevalence ◽  
Community Based ◽  
Objectively Measured

Several investigators have observed lowered risk of depression among obese older adults, coining the “jolly fat” hypothesis. We examined this hypothesis using baseline and a 5-year follow-up body mass index, depressive symptoms, and covariates from 638 community-based older adults. High objectively measured body mass index and functional limitations predicted increased future depressive symptoms. However, symptoms did not predict future body mass index. Self-reported body mass index showed similar associations despite underestimating obesity prevalence. Results did not differ on the basis of gender. Results for this study, the first longitudinal reciprocal risk analysis between objectively measured body mass index and depressive symptoms among older adults, do not support the “jolly fat” hypothesis.

scholarly journals Abdominal obesity: prevalence, sociodemographic- and lifestyle-associated factors in adolescents

2017 ◽  
Vol 27 (1) ◽  
pp. 56 ◽  
Author(s):  
Willian R. Tebar ◽  
Luiz Carlos M. Vanderlei ◽  
Catarina C. Scarabotollo ◽  
Edner F. Zanuto ◽  
Bruna T. C. Saraiva ◽  
...  
Keyword(s):  
Physical Activity ◽  
Body Mass Index ◽  
Body Weight ◽  
Public Schools ◽  
Sedentary Behaviour ◽  
Body Mass ◽  
Abdominal Obesity ◽  
Associated Factors ◽  
Statistical Significance ◽  
Obesity Prevalence

Objectives: The aim of this study was to determine the prevalence of abdominal obesity and its associated factors among adolescents, independent of confounders. Method: A sample of 14–17-year-old individuals (n=1.231), who were students from Londrina/PR-Brazil public schools, was studied. A questionnaire about physical activity, sedentary behaviour and socioeconomic conditions was applied. Anthropometry was composed of body weight (kg), height (m), body mass index (BMI=kg/m²) and waist circumference (cm). The association of abdominal obesity and independent variables was assessed using the chi-square test and the magnitude of associations was verified using Binary Logistic Regression in an unadjusted model and adjusted for confounders (gender, age, socioeconomic status, physical activity and sedentary behaviour). The confidence interval and statistical significance were set at 95% and 5%, respectively, using SPSS v15.0. Results: The abdominal obesity prevalence was 17.5% (CI = 15.4%–19.6%), and was higher in boys than in girls. Adolescents with abdominal obesity had higher values of body weight, height, body mass index and sedentary behaviour compared to eutrophic individuals. Being male increased the risk of abdominal obesity by 36% in adolescents. This risk was two times higher in those with high levels of sedentary behaviour. Conclusion: Abdominal obesity was significantly associated with gender and high levels of sedentary behaviour, regardless of confounding factors. Lifestyle habits are important modifiable risk factors that can effectively contribute to the reduction of obesity from an early age.

scholarly journals Obesity Trends and Body Mass Index Changes After Starting Antiretroviral Treatment: The Swiss HIV Cohort Study

2014 ◽  
Vol 1 (2) ◽  
Author(s):  
Barbara Hasse ◽  
Martin Iff ◽  
Bruno Ledergerber ◽  
Alexandra Calmy ◽  
Patrick Schmid ◽  
...  
Keyword(s):  
Body Mass Index ◽  
Cohort Study ◽  
Body Mass ◽  
Obesity Prevalence ◽  
Related Factors ◽  
White Ethnicity ◽  
Body Mass Index Increase ◽  
Obesity Trends ◽  
Multivariable Analyses ◽  
Population Demographic

Abstract Background.  The factors that contribute to increasing obesity rates in human immunodeficiency virus (HIV)-positive persons and to body mass index (BMI) increase that typically occurs after starting antiretroviral therapy (ART) are incompletely characterized. Methods.  We describe BMI trends in the entire Swiss HIV Cohort Study (SHCS) population and investigate the effects of demographics, HIV-related factors, and ART on BMI change in participants with data available before and 4 years after first starting ART. Results.  In the SHCS, overweight/obesity prevalence increased from 13% in 1990 (n = 1641) to 38% in 2012 (n = 8150). In the participants starting ART (n = 1601), mean BMI increase was 0.92 kg/m2 per year (95% confidence interval, .83–1.0) during year 0–1 and 0.31 kg/m2 per year (0.29–0.34) during years 1–4. In multivariable analyses, annualized BMI change during year 0–1 was associated with older age (0.15 [0.06–0.24] kg/m2) and CD4 nadir <199 cells/µL compared to nadir >350 (P < .001). Annualized BMI change during years 1–4 was associated with CD4 nadir <100 cells/µL compared to nadir >350 (P = .001) and black compared to white ethnicity (0.28 [0.16–0.37] kg/m2). Individual ART combinations differed little in their contribution to BMI change. Conclusions.  Increasing obesity rates in the SHCS over time occurred at the same time as aging of the SHCS population, demographic changes, earlier ART start, and increasingly widespread ART coverage. Body mass index increase after ART start was typically biphasic, the BMI increase in year 0–1 being as large as the increase in years 1–4 combined. The effect of ART regimen on BMI change was limited.

scholarly journals Validity of self-reported weight: a study of urban brazilian adults

1993 ◽  
Vol 27 (4) ◽  
pp. 271-276 ◽  
Author(s):  
Maria I. Schmidt ◽  
Bruce B. Duncan ◽  
Mário Tavares ◽  
Carísi A. Polanczyk ◽  
Lúcia Pellanda ◽  
...  
Keyword(s):  
Body Mass Index ◽  
Standard Deviation ◽  
Body Mass ◽  
Mean Difference ◽  
Obesity Prevalence ◽  
Porto Alegre ◽  
Measured Weight ◽  
Prevalence Of Obesity ◽  
The Mean

In order to evaluate the validity of self-reported weight for use in obesity prevalence surveys, self-reported weight was compared to measured weight for 659 adults living in the Porto Alegre county, RS Brazil in 1986-87, both weights being obtained by a technician in the individual's home on the same visit. The mean difference between self-reported and measured weight was small (-0.06 +/- 3.16 kg; mean +/- standard deviation), and the correlation between reported and measured weight was high (r=0.97). Sixty-two percent of participants reported their weight with an error of < 2 kg, 87% with an error of < 4 kg, and 95% with an error of < 6 kg. Underweight individuals overestimated their weight, while obese individuals underestimated theirs (p<0.05). Men tended to overestimate their weight and women underestimate theirs, this difference between sexes being statistically significant (p=0.04). The overall prevalence of underweight (body mass index < 20) by reported weight was 11%, by measured weight 13%; the overall prevalence of obesity (body mass index > 30) by reported weight was 10%, by measured weight 11%. Thus, the validity of reported weight is acceptable for surveys of the prevalence of ponderosity in similar settings.

Overweight and obesity prevalence and body mass index trends in Indian children

2011 ◽  
Vol 6 (2-2) ◽  
pp. e216-e224 ◽  
Author(s):  
V. V. Khadilkar ◽  
A. V. Khadilkar ◽  
T. J. Cole ◽  
S. A. Chiplonkar ◽  
Deepa Pandit
Keyword(s):  
Body Mass Index ◽  
Body Mass ◽  
Overweight And Obesity ◽  
Obesity Prevalence ◽  
Indian Children

scholarly journals Spouse Resemblance in Body Mass Index: Effects on Adult Obesity Prevalence in the Offspring Generation

2006 ◽  
Vol 165 (1) ◽  
pp. 101-108 ◽  
Author(s):  
P. Jacobson ◽  
J. S. Torgerson ◽  
L. Sjostrom ◽  
C. Bouchard
Keyword(s):  
Body Mass Index ◽  
Body Mass ◽  
Obesity Prevalence ◽  
Adult Obesity ◽  
Offspring Generation

scholarly journals Overweight and Obesity Prevalence Among School-Aged Nunavik Inuit Children According to Three Body Mass Index Classification Systems

2015 ◽  
Vol 57 (1) ◽  
pp. 31-36 ◽  
Author(s):  
Thierry Comlan Marc Medehouenou ◽  
Pierre Ayotte ◽  
Audray St-Jean ◽  
Salma Meziou ◽  
Cynthia Roy ◽  
...  
Keyword(s):  
Body Mass Index ◽  
Body Mass ◽  
Overweight And Obesity ◽  
Classification Systems ◽  
Obesity Prevalence ◽  
Three Body ◽  
Body Mass Index Classification

scholarly journals Impacts of a sugar sweetened beverage tax on body mass index and obesity in Thailand: A modelling study

PLoS ONE ◽  
2021 ◽  
Vol 16 (4) ◽  
pp. e0250841
Author(s):  
Payao Phonsuk ◽  
Vuthiphan Vongmongkol ◽  
Suladda Ponguttha ◽  
Rapeepong Suphanchaimat ◽  
Nipa Rojroongwasinkul ◽  
...  
Keyword(s):  
Body Mass Index ◽  
Energy Intake ◽  
Body Mass ◽  
Price Elasticity ◽  
Tax Rates ◽  
Obesity Prevalence ◽  
Sugar Sweetened Beverage ◽  
Tax Rate ◽  
Excise Tax ◽  
Sweetened Beverage

BackgroundThe World Health Organization (WHO) recommends sugar-sweetened beverage (SSB) taxes to address obesity. Thailand has just launched the new tax rates for SSB in 2017; however, the existing tax rate is not as high as the 20% recommended by the WHO. The objective for this study was to estimate the impacts of an SSB tax on body mass index (BMI) and obesity prevalence in Thailand under three different scenarios based on existing SSB and recommended tax rates.MethodsA base model was built to estimate the impacts of an SSB tax on SSB consumption, energy intake, BMI, and obesity prevalence. Literature review was conducted to estimate pass on rate, price elasticity, energy compensation, and energy balance to weight change. Different tax rates (11%, 20% and 25%) were used in the model. The model assumed no substitution effects, model values were based on international data since there was no empirical Thai data available. Differential effects by income groups were not estimated.FindingsWhen applying 11%, 20%, and 25% tax rates together with 100% pass on rate and an -1.30 own-price elasticity, the SSB consumption decreased by 14%, 26%, and 32%, respectively. The 20% and 25% price increase in SSB price tended to reduce higher energy intake, weight status and BMI, when compared with an 11% increase in existing price increase of SSB. The percentage changes of obesity prevalence of 11%, 20% and 25% SSB tax rates were estimated to be 1.73%, 3.83%, and 4.91%, respectively.ConclusionsA higher SSB tax (20% and 25%) was estimated to reduce consumption and consequently decrease obesity prevalence. Since Thailand has already endorsed the excise tax structure, the new excise tax structure for SSB should be scaled up to a 20% or 25% tax rate if the SSB consumption change does not meet a favourable goal.

scholarly journals ACCURACY AND PREDICTIVE CAPABILITY OF BODY MASS INDEX IN EVALUATION OF OBESITY AND BODY FATNESS LEVEL IN POLICE OFFICERS

2020 ◽  
Vol 25 (3) ◽  
Author(s):  
Filip Kukic ◽  
Jay Dawes ◽  
Jillian Joyce ◽  
Aleksandar Čvorović ◽  
Milivoj Dopsaj
Keyword(s):  
Body Mass Index ◽  
Body Mass ◽  
Police Officers ◽  
Age Groups ◽  
Obesity Prevalence ◽  
Regression Analyses ◽  
Predictive Capability ◽  
Chi Square ◽  
Body Fatness ◽  
Significant Difference

This study evaluated the accuracy and predictive value of body mass index (BMI) in evaluation of obesity and body fatness. Data on BMI and percent body fat (PBF) were collected on 953 male police officers who were allocated into age groups: 20-29 years, 30-39 years, and 40-49 years. BMI > 30.0 kg/m2 and PBF > 25% were classified as obese, and those with lower values were classified as non-obese. Chi-square was used to evaluate the accuracy in classification in obese and non-obese when officers’ BMI was matched to PBF. Pearson’s correlation and linear regression analyses determined the prediction value of BMI. Chi-square revealed significant difference in obesity prevalence when evaluated by BMI and PBF, with classification accuracy of 44.5%-71.8%, depending on age. BMI had moderate prediction value of body fatness. If the assessment of PBF is not attainable, BMI needs to be used carefully as it is likely to underestimate obesity among police officers.

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