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Journal articles on the topic 'Obesity – Australia'

Author: Grafiati

Published: 4 June 2021

Last updated: 25 January 2023

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1

Huse, Oliver, Janitha Hettiarachchi, Emma Gearon, Melanie Nichols, Steven Allender, and Anna Peeters. "Obesity in Australia." Obesity Research & Clinical Practice 12, no. 1 (January 2018): 29–39. http://dx.doi.org/10.1016/j.orcp.2017.10.002.

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Keramat, Syed Afroz, Nusrat Jahan Sathi, Rezwanul Haque, Benojir Ahammed, Rupok Chowdhury, Rubayyat Hashmi, and Kabir Ahmad. "Neighbourhood Socio-Economic Circumstances, Place of Residence and Obesity amongst Australian Adults: A Longitudinal Regression Analysis Using 14 Annual Waves of the HILDA Cohort." Obesities 1, no. 3 (December 8, 2021): 178–88. http://dx.doi.org/10.3390/obesities1030016.

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The prevalence of overweight and obesity is rising dramatically worldwide, including in Australia. Therefore, the necessity of identifying the risk factors of overweight and obesity is pivotal. The main objective of this study is to investigate the influence of neighbourhood socio-economic circumstances and place of residence on obesity amongst Australian adults. This study has used nationally representative panel data on 183,183 person-year observations from 26,032 unique Australian adults from the Household, Income, and Labour Dynamics in Australia (HILDA). Random-effects logistic regression technique was employed to examine the relationships. The prevalence of overweight and obesity has been found at approximately 34% and 24%, respectively. The most striking result to emerge from the analyses is that adults living in the most socio-economic disadvantaged area were 2.04 times (AOR: 2.04, 95% CI: 1.57–2.65) and adults from regional cities of Australia were 1.71 times (AOR: 1.71, 95% CI: 1.34–2.19) more prone to be obese compared to their healthy counterparts. The prevalence of overweight and obesity is very high among Australian adults, especially those living in disadvantaged neighbourhoods and the regional cities. Unhealthy levels of BMI have costly impacts on the individual, the economy, and the health care system. Therefore, this study emphasises effective weight control strategies that can potentially tackle the obesity epidemic in Australia.

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3

Hugo, Graeme, and Julie Franzon. "Child Obesity in South Australia." Food, Culture & Society 9, no. 3 (October 2006): 299–316. http://dx.doi.org/10.2752/155280106778813215.

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4

Hawley, John A., and David W. Dunstan. "Overweight and obesity in Australia." Medical Journal of Australia 188, no. 11 (June 2008): 678–79. http://dx.doi.org/10.5694/j.1326-5377.2008.tb01835.x.

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Travis, Douglas G. "Overweight and obesity in Australia." Medical Journal of Australia 188, no. 11 (June 2008): 678–79. http://dx.doi.org/10.5694/j.1326-5377.2008.tb01836.x.

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6

Thorburn, A. W. "Prevalence of obesity in Australia." Obesity Reviews 6, no. 3 (August 2005): 187–89. http://dx.doi.org/10.1111/j.1467-789x.2005.00187.x.

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Cyril, Sheila, Michael Polonsky, Julie Green, Kingsley Agho, and Andre Renzaho. "Readiness of communities to engage with childhood obesity prevention initiatives in disadvantaged areas of Victoria, Australia." Australian Health Review 41, no. 3 (2017): 297. http://dx.doi.org/10.1071/ah16069.

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Objective Disadvantaged communities bear a disproportionate burden of childhood obesity and show low participation in childhood obesity prevention initiatives. This study aims to examine the level of readiness of disadvantaged communities to engage with childhood obesity prevention initiatives. Methods Using the community readiness model, 95 semi-structured interviews were conducted among communities in four disadvantaged areas of Victoria, Australia. Community readiness analysis and paired t-tests were performed to assess the readiness levels of disadvantaged communities to engage with childhood obesity prevention initiatives. Results The results showed that disadvantaged communities demonstrated low levels of readiness (readiness score = 4/9, 44%) to engage with the existing childhood obesity prevention initiatives, lacked knowledge of childhood obesity and its prevention, and reported facing challenges in initiating and sustaining participation in obesity prevention initiatives. Conclusion This study highlights the need to improve community readiness by addressing low obesity-related literacy levels among disadvantaged communities and by facilitating the capacity-building of bicultural workers to deliver obesity prevention messages to these communities. Integrating these needs into existing Australian health policy and practice is of paramount importance for reducing obesity-related disparities currently prevailing in Australia. What is known about the topic? Childhood obesity prevalence is plateauing in developed countries including Australia; however, obesity-related inequalities continue to exist in Australia especially among communities living in disadvantaged areas, which experience poor engagement in childhood obesity prevention initiatives. Studies in the USA have found that assessing disadvantaged communities’ readiness to participate in health programs is a critical initial step in reducing the disproportionate obesity burden among these communities. However, no studies in Australia have assessed disadvantaged communities’ readiness to engage in obesity prevention initiatives. What does this paper add? This paper addresses the current gap in the knowledge of disadvantaged communities’ level of readiness to engage in childhood obesity prevention initiatives in Australia. The study also identified the key factors responsible for low readiness of disadvantaged communities to participate in current childhood obesity prevention services. By using the Community Readiness model this study shows the readiness levels specific to the various dimensions of the model; Understanding dimension-specific readiness allows us to identify strategies that are tailored to each dimension, as guided by the model. What are the implications for practitioners? With the increasing burden of childhood obesity on disadvantaged communities, policymakers and health practitioners are facing a crisis in obesity prevention and management. Almost every year, new interventions are being planned and implemented. However if the target communities are not ready to participate in the available interventions these efforts are futile. This study exposes the key factors responsible for low readiness to participate in current obesity prevention services by disadvantaged communities. Addressing these key factors and improving readiness before designing new interventions will improve the participation of disadvantaged communities in those interventions. The study findings ultimately have the potential of reducing obesity-related disparities in Australia.

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Cameron, Adrian J., Paul Z. Zimmet, David W. Dunstan, Marita Dalton, Jonathan E. Shaw, Timothy A. Welborn, Neville Owen, Jo Salmon, and Damien Jolley. "Overweight and obesity in Australia: the 1999–2000 Australian Diabetes, Obesity and Lifestyle Study (AusDiab)." Medical Journal of Australia 178, no. 9 (May 2003): 427–32. http://dx.doi.org/10.5694/j.1326-5377.2003.tb05283.x.

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9

Cameron, Adrian J., Paul Z. Zimmet, David W. Dunstan, Marita Dalton, Jonathan E. Shaw, Timothy A. Welborn, Neville Owen, Jo Salmon, and Damien Jolley. "Overweight and obesity in Australia: the 1999–2000 Australian Diabetes, Obesity and Lifestyle Study (AusDiab)." Medical Journal of Australia 180, no. 8 (April 2004): 418. http://dx.doi.org/10.5694/j.1326-5377.2004.tb05998.x.

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10

Moodie, Rob. "Australia gets a “Fail” for obesity." Obesity Research & Clinical Practice 7 (December 2013): e57. http://dx.doi.org/10.1016/j.orcp.2013.12.608.

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Whelan, Jill, Erin Smith, Penny Love, Anne Romanus, Kristy Bolton, Elizabeth Waters, Tim Gill, John Coveney, and Steve Allender. "Community based obesity prevention in Australia." Obesity Research & Clinical Practice 7 (December 2013): e124-e125. http://dx.doi.org/10.1016/j.orcp.2013.12.722.

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Spilchak, Pamela J., Elizabeth Denney-Wilson, Lesley King, and Louise A. Baur. "Tertiary paediatric obesity services in Australia." Journal of Paediatrics and Child Health 44, no. 5 (May 2008): 243–47. http://dx.doi.org/10.1111/j.1440-1754.2007.01266.x.

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Lung, Thomas, Louise A. Baur, Adrian Bauman, and Alison Hayes. "Can Reducing Childhood Obesity Solve the Obesity Crisis in Australia?" Obesity 28, no. 5 (April 22, 2020): 857–59. http://dx.doi.org/10.1002/oby.22711.

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14

Secombe, Paul, Richard Woodman, Sean Chan, David Pilcher, and Frank Van Haren. "Epidemiology and outcomes of obese critically ill patients in Australia and New Zealand." Critical Care and Resuscitation 22, no. 1 (March 2, 2020): 35–44. http://dx.doi.org/10.51893/2020.1.oa4.

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OBJECTIVE: The apparent survival benefit of being overweight or obese in critically ill patients (the obesity paradox) remains controversial. Our aim is to report on the epidemiology and outcomes of obesity within a large heterogenous critically ill adult population. DESIGN: Retrospective observational cohort study. SETTING: Intensive care units (ICUs) in Australia and New Zealand. PARTICIPANTS: Critically ill patients who had both height and weight recorded between 2010 and 2018. OUTCOME MEASURES: Hospital mortality in each of five body mass index (BMI) strata. Subgroups analysed included diagnostic category, gender, age, ventilation status and length of stay. RESULTS: Data were available for 381 855 patients, 68% of whom were overweight or obese. Increasing level of obesity was associated with lower unadjusted hospital mortality: underweight (11.9%), normal weight (7.7%), overweight (6.4%), class I obesity (5.4%), and class II obesity (5.3%). After adjustment, mortality was lowest for patients with class I obesity (adjusted odds ratio, 0.78; 95% CI, 0.74– 0.82). Adverse outcomes with class II obesity were only seen in patients with cardiovascular and cardiac surgery ICU admission diagnoses, where mortality risk rose with progressively higher BMIs. CONCLUSION: We describe the epidemiology of obesity within a critically ill Australian and New Zealand population and confirm that some level of obesity is associated with lower mortality, both overall and across a range of diagnostic categories and important subgroups. Further research should focus on potential confounders such as nutritional status and the appropriateness of BMI in isolation as an anthropometric measure in critically ill patients.

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Zulfiqar, Tehzeeb, Lyndall Strazdins, and Cathy Banwell. "How to Fit In? Acculturation and Risk of Overweight and Obesity. Experiences of Australian Immigrant Mothers From South Asia and Their 8- to 11-Year-Old Children." SAGE Open 11, no. 3 (July 2021): 215824402110317. http://dx.doi.org/10.1177/21582440211031798.

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This study of 14 Australian immigrant mothers from Bangladesh, India, and Pakistan and their 12 children aged 8 to 11 years aims to explore the interplay of cultural and social processes that might elevate the risk of obesity. Mothers and their children were asked in semi-structured, face-to-face interviews about changes in their diet and physical activities after immigration to Australia. Thematic analysis of these interviews showed a transformation in immigrant families’ diets and physical activities as they transitioned from their traditional lifestyles to an Australian pattern. Both mothers and their children recognized the problem—and causes—of obesity. However, different frames of reference—origin countries for mothers and Australian peers for children—resulted in generational disjuncture about healthy bodyweight and the strategies to achieve it. Mothers’ cultural values and high social status associated with overweight and obesity in origin countries led them to struggle to adapt to new health behaviors in Australia. In contrast, their children preferred to eat Australian foods and have high physical activities to fit in with their Australian peers. Children with higher body weights were commonly ridiculed and were unpopular among their peers. Our findings reveal that the social status of food and physical activity reflects cultural meanings from both origin and host countries, creating contradictions and tensions for immigrants that public health campaigns will need to help them navigate.

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Sturgiss, Elizabeth, and Kees van Boven. "Datasets collected in general practice: an international comparison using the example of obesity." Australian Health Review 42, no. 5 (2018): 563. http://dx.doi.org/10.1071/ah17157.

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International datasets from general practice enable the comparison of how conditions are managed within consultations in different primary healthcare settings. The Australian Bettering the Evaluation and Care of Health (BEACH) and TransHIS from the Netherlands collect in-consultation general practice data that have been used extensively to inform local policy and practice. Obesity is a global health issue with different countries applying varying approaches to management. The objective of the present paper is to compare the primary care management of obesity in Australia and the Netherlands using data collected from consultations. Despite the different prevalence in obesity in the two countries, the number of patients per 1000 patient-years seen with obesity is similar. Patients in Australia with obesity are referred to allied health practitioners more often than Dutch patients. Without quality general practice data, primary care researchers will not have data about the management of conditions within consultations. We use obesity to highlight the strengths of these general practice data sources and to compare their differences. What is known about the topic? Australia had one of the longest-running consecutive datasets about general practice activity in the world, but it has recently lost government funding. The Netherlands has a longitudinal general practice dataset of information collected within consultations since 1985. What does this paper add? We discuss the benefits of general practice-collected data in two countries. Using obesity as a case example, we compare management in general practice between Australia and the Netherlands. This type of analysis should start all international collaborations of primary care management of any health condition. Having a national general practice dataset allows international comparisons of the management of conditions with primary care. Without a current, quality general practice dataset, primary care researchers will not be able to partake in these kinds of comparison studies. What are the implications for practitioners? Australian primary care researchers and clinicians will be at a disadvantage in any international collaboration if they are unable to accurately describe current general practice management. The Netherlands has developed an impressive dataset that requires within-consultation data collection. These datasets allow for person-centred, symptom-specific, longitudinal understanding of general practice management. The possibilities for the quasi-experimental questions that can be answered with such a dataset are limitless. It is only with the ability to answer clinically driven questions that are relevant to primary care that the clinical care of patients can be measured, developed and improved.

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Sharman, Melanie J., Monique C. Breslin, Alexandr Kuzminov, Andrew J. Palmer, Leigh Blizzard, Martin Hensher, and Alison J. Venn. "Population estimates and characteristics of Australians potentially eligible for bariatric surgery: findings from the 2011–13 Australian Health Survey." Australian Health Review 42, no. 4 (2018): 429. http://dx.doi.org/10.1071/ah16255.

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Objective The aim of the present study was to determine the potential demand for publicly and privately funded bariatric surgery in Australia. Methods Nationally representative data from the 2011–13 Australian Health Survey were used to estimate the numbers and characteristics of Australians meeting specific eligibility criteria as recommended in National Health and Medical Research Council guidelines for the management of overweight and obesity. Results Of the 3 352 037 adult Australians (aged 18–65 years) estimated to be obese in 2011–13, 882 441 (26.3%; 95% confidence interval (CI) 23.0–29.6) were potentially eligible for bariatric surgery (accounting for 6.2% (95% CI 5.4–7.1) of the adult population aged 18–65 years (n = 14 122 020)). Of these, 396 856 (45.0%; 95% CI 40.4–49.5) had Class 3 obesity (body mass index (BMI) ≥40 kg m–2), 470945 (53.4%; 95% CI 49.0–57.7) had Class 2 obesity (BMI 35–39.9 kg m–2) with obesity-related comorbidities or risk factors and 14 640 (1.7%; 95% CI 0.6–2.7) had Class 1 obesity (BMI 30–34.9 kg m–2) with poorly controlled type 2 diabetes and increased cardiovascular risk; 458 869 (52.0%; 95% CI 46.4–57.6) were female, 404 594 (45.8%; 95% CI 37.3–54.4) had no private health insurance and 309 983 (35.1%; 95% CI 28.8–41.4) resided outside a major city. Conclusion Even if only 5% of Australian adults estimated to be eligible for bariatric surgery sought this intervention, the demand, particularly in the public health system and outside major cities, would far outstrip current capacity. Better guidance on patient prioritisation and greater resourcing of public surgery are needed. What is known about this topic? In the period 2011–13, 4 million Australian adults were estimated to be obese, with obesity disproportionately more prevalent in areas of socioeconomic disadvantage. Bariatric surgery is considered to be cost-effective and the most effective treatment for adults with obesity, but is mainly privately funded in Australia (>90%), with 16 650 primary privately funded procedures performed in 2015. The extent to which the supply of bariatric surgery is falling short of demand in Australia is unknown. What does this paper add? The present study provides important information for health service planners. For the first time, population estimates and characteristics of those potentially eligible for bariatric surgery in Australia have been described based on the best available evidence, using categories that best approximate the national recommended eligibility criteria. What are the implications for practitioners? Even if only 5% of those estimated to be potentially eligible for bariatric surgery in Australia sought a surgical pathway (44 122 of 882 441), the potential demand, particularly in the public health system and outside major cities, would still far outstrip current capacity, underscoring the immediate need for better guidance on patient prioritisation. The findings of the present study provide a strong signal that more funding of public surgery and other effective interventions to assist this population group are necessary.

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Sturgiss, Elizabeth Ann, Chris van Weel, Lauren Ball, Sarah Jansen, and Kirsty Douglas. "Obesity management in Australian primary care: where has the general practitioner gone?" Australian Journal of Primary Health 22, no. 6 (2016): 473. http://dx.doi.org/10.1071/py16074.

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Obesity is a chronic condition with significant health and economic consequences that requires more effective management in Australia. General practitioners (GPs) currently act as care co-ordinators in line with national guidelines for overweight and obesity. Australian patients indicate that they would appreciate more involvement from their GP in the management of obesity, and this is in line with international findings. Not all patients have access to specialist obesity services or affordable allied health care because of location, cost and time, particularly in rural and remote areas where there is a greater prevalence of obesity. Empowering GPs to use their skills as expert generalists to manage obesity is an option that should be explored to improve access for all individuals. GPs will require evidence-based tools to assist them in structuring obesity management within their own general practice environment.

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Al Shams, Hilal Salim, and Abdullah Ghthaith Almutairi. "Obesity Health Policy Agenda Setting in Australia." Global Journal of Health Science 13, no. 3 (February 15, 2021): 138. http://dx.doi.org/10.5539/gjhs.v13n3p138.

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The prevalence of obesity is rising rapidly in Australia. This issue can be a priority for agenda setting, by using the Hall and Kingdon models. Furthermore, the current policy may need to be reviewed or updated because of the high prevalence of obesity and the rate of death.

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Byrne, Linda K., Kay E. Cook, Helen Skouteris, and Michael Do. "Parental status and childhood obesity in Australia." International Journal of Pediatric Obesity 6, no. 5-6 (October 2011): 415–18. http://dx.doi.org/10.3109/17477166.2011.598938.

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Zimmet, Paul. "Obesity in Australia: People, politics and prevention." Obesity Research & Clinical Practice 4 (October 2010): S86. http://dx.doi.org/10.1016/j.orcp.2010.09.168.

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Denney-Wilson, Elizabeth, Karen Campbell, Kylie Hesketh, and Andrea de Silva-Sanigorski. "Funding for child obesity prevention in Australia." Australian and New Zealand Journal of Public Health 35, no. 1 (February 2011): 85–86. http://dx.doi.org/10.1111/j.1753-6405.2010.00665.x.

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23

Buchmueller, Thomas C., and Meliyanni Johar. "Obesity and health expenditures: Evidence from Australia." Economics & Human Biology 17 (April 2015): 42–58. http://dx.doi.org/10.1016/j.ehb.2015.01.001.

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24

Keramat, Syed Afroz, Khorshed Alam, Rezwanul Hasan Rana, Rupok Chowdhury, Fariha Farjana, Rubayyat Hashmi, Jeff Gow, and Stuart J. H. Biddle. "Obesity and the risk of developing chronic diseases in middle-aged and older adults: Findings from an Australian longitudinal population survey, 2009–2017." PLOS ONE 16, no. 11 (November 16, 2021): e0260158. http://dx.doi.org/10.1371/journal.pone.0260158.

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Background Overweight and obesity impose a significant health burden in Australia, predominantly the middle-aged and older adults. Studies of the association between obesity and chronic diseases are primarily based on cross-sectional data, which is insufficient to deduce a temporal relationship. Using nationally representative panel data, this study aims to investigate whether obesity is a significant risk factor for type 2 diabetes, heart diseases, asthma, arthritis, and depression in Australian middle-aged and older adults. Methods Longitudinal data comprising three waves (waves 9, 13 and 17) of the Household, Income and Labour Dynamics in Australia (HILDA) survey were used in this study. This study fitted longitudinal random-effect logistic regression models to estimate the between-person differences in the association between obesity and chronic diseases. Results The findings indicated that obesity was associated with a higher prevalence of chronic diseases among Australian middle-aged and older adults. Obese adults (Body Mass Index [BMI] ≥ 30) were at 12.76, 2.05, 1.97, 2.25, and 1.96, times of higher risks of having type 2 diabetes (OR: 12.76, CI 95%: 8.88–18.36), heart disease (OR: 2.05, CI 95%: 1.54–2.74), asthma (OR: 1.97, CI 95%: 1.49–2.62), arthritis (OR: 2.25, 95% CI: 1.90–2.68) and depression (OR: 1.96, CI 95%: 1.56–2.48), respectively, compared with healthy weight counterparts. However, the study did not find any evidence of a statistically significant association between obesity and cancer. Besides, gender stratified regression results showed that obesity is associated with a higher likelihood of asthma (OR: 2.64, 95% CI: 1.84–3.80) among female adults, but not in the case of male adults. Conclusion Excessive weight is strongly associated with a higher incidence of chronic disease in Australian middle-aged and older adults. This finding has clear public health implications. Health promotion programs and strategies would be helpful to meet the challenge of excessive weight gain and thus contribute to the prevention of chronic diseases.

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Nghiem, Son, Viet-Ngu Hoang, Xuan-Binh Vu, and Clevo Wilson. "THE DYNAMIC INTER-RELATIONSHIP BETWEEN OBESITY AND SCHOOL PERFORMANCE: NEW EMPIRICAL EVIDENCE FROM AUSTRALIA." Journal of Biosocial Science 50, no. 5 (December 4, 2017): 683–705. http://dx.doi.org/10.1017/s0021932017000608.

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SummaryThis paper proposes a new empirical model for examining the relationship between obesity and school performance using the simultaneous equation modelling approach. The lagged effects of both learning and health outcomes were included to capture both the dynamic and inter-relational aspects of the relationship between obesity and school performance. The empirical application of this study used comprehensive data from the first five waves of the Longitudinal Study of Australian Children (LSAC), which commenced in 2004 (wave 1) and was repeated every two years until 2018. The study sample included 10,000 children, equally divided between two cohorts (infants and children) across Australia. The empirical results show that past learning and obesity status are strongly associated with most indicators of school outcomes, including reading, writing, spelling, grammar and numeracy national tests, and scores from the internationally standardized Peabody Picture Vocabulary Test and the Matrix Reasoning Test. The main findings of this study are robust due to the choice of obesity indicator and estimation methods.

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Bell, A. C., A. Simmons, A. M. Sanigorski, P. J. Kremer, and B. A. Swinburn. "Preventing childhood obesity: the sentinel site for obesity prevention in Victoria, Australia." Health Promotion International 23, no. 4 (August 28, 2008): 328–36. http://dx.doi.org/10.1093/heapro/dan025.

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Larg, Allison, John R. Moss, and Nicola Spurrier. "Relative contribution of overweight and obesity to rising public hospital in-patient expenditure in South Australia." Australian Health Review 43, no. 2 (2019): 148. http://dx.doi.org/10.1071/ah17147.

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Objective Arguments to fund obesity prevention have often focused on the growing hospital costs of associated diseases. However, the relative contribution of overweight and obesity to public hospital expenditure growth is not well understood. This paper examines the effect of overweight and obesity on acute public hospital in-patient expenditure in South Australia over time compared with other expenditure drivers. Methods Annual inflation-adjusted acute public admitted expenditure attributable to a high body mass index was estimated for 2007–08 and 2011–12 and compared with other expenditure drivers. Results Expenditure attributable to overweight and obesity increased by A$45million, from 4.7% to 5.4% of total acute public in-patient expenditure. This increase accounted for 7.8% of the A$583million total expenditure growth, whereas the largest component of total growth (62.4%) was a real increase in the average cost per separation. Conclusions The relatively minor contribution of overweight and obesity to expenditure growth over the time period examined invites reflection on arguments to boost preventive spending that centre upon reducing hospital costs. These arguments may inadvertently detract attention from the considerable health and social burdens of overweight and obesity and from unrelated sources of expenditure growth that reduce opportunities for state governments to fund obesity prevention programs despite their comparative benefits to population health. What is known about the topic? Stand-alone estimates suggest that overweight and obesity are placing a considerable financial burden on the Australian public healthcare system. What does this paper add? Our findings challenge common perceptions about the relative importance of overweight and obesity in the context of rising public in-patient expenditure in Australia. What are the implications for practitioners? Consistent serial estimates of overweight- and obesity-attributable expenditure enable its tracking and comparison with other potentially controllable expenditure drivers that may also warrant attention. Explicit consideration of population health trade-offs in expenditure-related decisions, including in enterprise bargaining, would enhance transparency in priority setting.

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Martin, Karen, Michael Rosenberg, Iain Stephen Pratt, Margaret Miller, Gavin McCormack, Billie Giles-Corti, Anthea Magarey, Fiona Bull, and Amanda Devine. "Prevalence of overweight, obesity and underweight in Western Australian school-aged children; 2008 compared with 2003." Public Health Nutrition 17, no. 12 (November 20, 2013): 2687–91. http://dx.doi.org/10.1017/s136898001300311x.

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AbstractObjectiveDue to rising rates of obesity globally, the present study aimed to examine differences in overweight and underweight prevalence in Western Australian schoolchildren in 2008 compared with 2003.DesignCross-sectional study at two time points; using two-stage stratified sampling, primary and secondary schools in both metropolitan and non-metropolitan Western Australia; sample selected was representative of the State's population figures.SettingsSeventeen primary and thirteen secondary (2008) and nineteen primary and seventeen secondary (2003) schools. Government and non-government funded schools in metropolitan and non-metropolitan (regional/rural) Western Australia were recruited.SubjectsHeight and weight were measured for 1708 (961 primary and 747 secondary) students in 2008 and 1694 (876 primary and 817 secondary) students in 2003.ResultsOverweight and obesity prevalence in primary students was similar in 2008 (22·9 %) to 2003 (23·2 %; P > 0·05). In secondary girls overweight and obesity prevalence dropped from 23·1 % (2003) to 15·9 % (2008; P = 0·002). Secondary boys showed a slight decrease in overweight and obesity prevalence; however, this was not statistically significant (P = 0·102). Higher proportions of underweight in primary girls were observed in 2008 (9·9 %) compared with 2003 (4·2 %; P < 0·001) and in secondary girls in 2008 (9·4 %) compared with 2003 (5·5 %; P < 0·001).ConclusionsPrevalence of overweight and obesity in Western Australian primary students was stable; however, it declined in secondary students. Both primary and secondary girls showed an increase in underweight prevalence. Public health interventions are needed for the high percentage of youth still overweight, whereas the observed increase in underweight girls warrants attention and further investigation.

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Hayes, Alison, Eng Joo Tan, Anagha Killedar, and Thomas Lung. "Socioeconomic inequalities in obesity: modelling future trends in Australia." BMJ Open 9, no. 3 (March 2019): e026525. http://dx.doi.org/10.1136/bmjopen-2018-026525.

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ObjectivesTo develop a model to predict future socioeconomic inequalities in body mass index (BMI) and obesity.DesignMicrosimulation modelling using BMI data from adult participants of Australian Health Surveys, and published data on the relative risk of mortality in relation to BMI and socioeconomic position (SEP), based on education.SettingAustralia.Participants74 329 adults, aged 20 and over from Australian Health Surveys, 1995–2015.Primary and secondary outcome measuresThe primary outcomes were BMI trajectories and obesity prevalence by SEP for four birth cohorts, born 10 years apart, centred on 1940, 1950, 1960 and 1970.ResultsSimulations projected persistent or widening socioeconomic inequality in BMI and obesity over the adult life course, for all birth cohorts. Recent birth cohorts were predicted to have greater socioeconomic inequality by middle age, compared with earlier cohorts. For example, among men, there was no inequality in obesity prevalence at age 60 for the 1940 birth cohort (low SEP 25% (95% CI 17% to 34%); high SEP 26% (95% CI 19% to 34%)), yet for the 1970 birth cohort, obesity prevalence was projected to be 51% (95% CI 43% to 58%) and 41% (95% CI 36% to 46%) for the low and high SEP groups, respectively. Notably, for more recent birth cohorts, the model predicted the greatest socioeconomic inequality in severe obesity (BMI >35 kg/m2) at age 60.ConclusionsLower SEP groups and more recent birth cohorts are at higher risk of obesity and severe obesity, and its consequences in middle age. Prevention efforts should focus on these vulnerable population groups in order to avoid future disparities in health outcomes. The model provides a framework for further research to investigate which interventions will be most effective in narrowing the gap in socioeconomic disparities in obesity in adulthood.

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Lacy, Kathleen E., Melanie S. Nichols, Andrea M. de Silva, Steven E. Allender, Boyd A. Swinburn, Eva R. Leslie, Laura V. Jones, and Peter J. Kremer. "Critical design features for establishing a childhood obesity monitoring program in Australia." Australian Journal of Primary Health 21, no. 4 (2015): 369. http://dx.doi.org/10.1071/py15052.

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Efforts to combat childhood obesity in Australia are hampered by the lack of quality epidemiological data to routinely monitor the prevalence and distribution of the condition. This paper summarises the literature on issues relevant to childhood obesity monitoring and makes recommendations for implementing a school-based childhood obesity monitoring program in Australia. The primary purpose of such a program would be to collect population-level health data to inform both policy and the development and evaluation of community-based obesity prevention interventions. Recommendations are made for the types of data to be collected, data collection procedures and program management and evaluation. Data from an obesity monitoring program are crucial for directing and informing policies, practices and services, identifying subgroups at greatest risk of obesity and evaluating progress towards meeting obesity-related targets. Such data would also increase the community awareness necessary to foster change.

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Uddin, Sabah, Peter R. Brooks, and Trong D. Tran. "Chemical Characterization, α-Glucosidase, α-Amylase and Lipase Inhibitory Properties of the Australian Honey Bee Propolis." Foods 11, no. 13 (July 1, 2022): 1964. http://dx.doi.org/10.3390/foods11131964.

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The use of functional foods and nutraceuticals as a complementary therapy for the prevention and management of type 2 diabetes and obesity has steadily increased over the past few decades. With the aim of exploring the therapeutic potentials of Australian propolis, this study reports the chemical and biological investigation of a propolis sample collected in the Queensland state of Australia which exhibited a potent activity in an in vitro α-glucosidase inhibitory screening. The chemical investigation of the propolis resulted in the identification of six known prenylated flavonoids including propolins C, D, F, G, H, and solophenol D. These compounds potently inhibited the α-glucosidase and two other enzymes associated with diabetes and obesity, α-amylase, and lipase on in vitro and in silico assays. These findings suggest that this propolis is a potential source for the development of a functional food to prevent type 2 diabetes and obesity. The chemical analysis revealed that this propolis possessed a chemical fingerprint relatively similar to the Pacific propolis found in Okinawa (South of Japan), Taiwan, and the Solomon Islands. This is the first time the Pacific propolis has been identified in Australia.

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Nahar, Kamrun, Tanveer A. Khan, and Md Kamal Hossain. "Childhood Obesity Status in Australia: A Recent Perspective." Research Journal of Pharmacy and Technology 10, no. 8 (2017): 2727. http://dx.doi.org/10.5958/0974-360x.2017.00500.5.

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Colagiuri, Stephen, Crystal M. Y. Lee, Ruth Colagiuri, Dianna Magliano, Jonathan E. Shaw, Paul Z. Zimmet, and Ian D. Caterson. "The cost of overweight and obesity in Australia." Medical Journal of Australia 192, no. 5 (March 2010): 260–64. http://dx.doi.org/10.5694/j.1326-5377.2010.tb03503.x.

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Lee, Crystal Man Ying, Brandon Goode, Emil Nørtoft, Jonathan E. Shaw, Dianna J. Magliano, and Stephen Colagiuri. "The cost of diabetes and obesity in Australia." Journal of Medical Economics 21, no. 10 (July 19, 2018): 1001–5. http://dx.doi.org/10.1080/13696998.2018.1497641.

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Hocking, Samantha, Anthony Dear, and Michael A. Cowley. "Current and emerging pharmacotherapies for obesity in Australia." Obesity Research & Clinical Practice 11, no. 5 (September 2017): 501–21. http://dx.doi.org/10.1016/j.orcp.2017.07.002.

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Bastable, Alice, Alison McAleese, Maria Szybiak, Steve Pratt, and Victoria Jansen. "The normalisation of overweight and obesity in Australia." Obesity Research & Clinical Practice 13, no. 3 (May 2019): 314. http://dx.doi.org/10.1016/j.orcp.2018.11.216.

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Stanton, R. "Who will take responsibility for obesity in Australia?" Public Health 123, no. 3 (March 2009): 280–82. http://dx.doi.org/10.1016/j.puhe.2008.12.017.

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James, Adrian, Silvia Mendolia, and Alfredo R. Paloyo. "Income-based inequality of adolescent obesity in Australia." Economics Letters 198 (January 2021): 109665. http://dx.doi.org/10.1016/j.econlet.2020.109665.

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Demaio, Alessandro. "A lifeSPANS approach: Addressing child obesity in Australia." Health Promotion Journal of Australia 29 (April 10, 2018): 13–16. http://dx.doi.org/10.1002/hpja.44.

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Jegatheesan, Dev, David W. Johnson, Yeoungjee Cho, Elaine M. Pascoe, Darsy Darssan, Htay Htay, Carmel Hawley, et al. "The Relationship between Body Mass Index and Organism-Specific Peritonitis." Peritoneal Dialysis International: Journal of the International Society for Peritoneal Dialysis 38, no. 3 (May 2018): 206–14. http://dx.doi.org/10.3747/pdi.2017.00188.

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Background Obesity is increasingly prevalent worldwide, and a greater number of patients initiate renal replacement therapy with a high body mass index (BMI). This study aimed to evaluate the association between BMI and organism-specific peritonitis. Methods All adult patients who initiated peritoneal dialysis (PD) in Australia between January 2004 and December 2013 were included. Data were accessed through the Australia and New Zealand Dialysis and Transplant (ANZDATA) Registry. The co-primary outcomes of this study were time to first organism-specific peritonitis episode, specifically gram-positive, gram-negative, culture-negative, and fungal. Secondary outcomes were individual rates of organism-specific peritonitis for the same 4 microbiological categories. Results There were 7,381 peritonitis episodes among the 8,343 incident PD patients evaluated. After multivariable adjustment, obese patients (BMI 30 – 34.9 kg/m2) had an increased risk of fungal peritonitis (adjusted hazard ratio [HR] 1.69, 95% confidence interval [CI] 1.18 – 2.42), very obese patients (BMI ≥ 35 kg/m2) had a significantly higher risk of gram-positive peritonitis (HR 1.15, 95% CI 1.02 – 1.30), while both obese and very obese patients experienced significantly higher risks of gram-negative peritonitis (HR 1.29, 95% CI 1.11 – 1.50 and HR 1.30, 95% CI 1.08 – 1.57, respectively) compared with patients with normal BMI (20 – 24.9 kg/m2). Obesity and severe obesity were independently associated with increased incidence rate ratios of all forms of organism-specific peritonitis with a non-significant trend for severe obesity and gram-negative peritonitis association. Conclusion Among Australian patients, obesity and severe obesity are associated with significantly increased rates of gram-positive, gram-negative, fungal, and culture-negative peritonitis.

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Buru, Kakale, Theophilus I. Emeto, Aduli E. O. Malau-Aduli, and Bunmi S. Malau-Aduli. "The Efficacy of School-Based Interventions in Preventing Adolescent Obesity in Australia." Healthcare 8, no. 4 (November 25, 2020): 514. http://dx.doi.org/10.3390/healthcare8040514.

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Current trends suggest that adolescent obesity is an on-going and recurrent decimal that is still on the rise in Australia and the social burden associated with it can significantly cause low self-esteem and lack of confidence in personal body image in adulthood. Nonetheless, evidence-based prevention programs are not widely implemented in schools, even though they are commonplace for easy access to adolescents. The primary objective of this systematic review was to assess the scope and efficacy of adolescent obesity intervention strategies in Australian schools, to guide future research. Seven electronic databases were searched for peer-reviewed school-based intervention articles written in the English language and targeting 12–18-year-old adolescents. Intervention characteristics were extracted, and quality, efficacy and outcome measures were assessed utilizing thirteen studies that met the inclusion criteria for this review. Most of the Australian adolescent obesity research emanated from the State of New South Wales and none were nationwide. Five studies successfully met all the requirements in all measured outcomes, four met at least one measured outcome and the remaining four were unsuccessful. Despite the weak evidence of intervention efficacy for most of the reviewed studies, school-based interventions with multi-component combinations of physical activity, nutrition and alignment to a theory yielded promising results. Our findings point to the need for future research to assess the perceptions of school stakeholders in relation to the barriers and enablers to establishing school-based prevention and intervention programs for adolescents.

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Janus, Edward D., Tiina Laatikainen, James A. Dunbar, Annamari Kilkkinen, Stephen J. Bunker, Benjamin Philpot, Philip A. Tideman, Rosy Tirimacco, and Sami Heistaro. "Overweight, obesity and metabolic syndrome in rural southeastern Australia." Medical Journal of Australia 187, no. 3 (August 2007): 147–52. http://dx.doi.org/10.5694/j.1326-5377.2007.tb01171.x.

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Harvey, Philip W. J., Geoffrey C. Marks, and Peter F. Heywood. "Variation in estimates of overweight and obesity in Australia." Medical Journal of Australia 155, no. 10 (November 1991): 724. http://dx.doi.org/10.5694/j.1326-5377.1991.tb94001.x.

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Walls, Helen L., Dianna J. Magliano, Christopher E. Stevenson, Kathryn Backholer, Haider R. Mannan, Jonathan E. Shaw, and Anna Peeters. "Projected Progression of the Prevalence of Obesity in Australia." Obesity 20, no. 4 (April 2012): 872–78. http://dx.doi.org/10.1038/oby.2010.338.

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Nghiem, Son, and Rasheda Khanam. "Childhood obesity and the income gradient: evidence from Australia." Applied Economics 48, no. 50 (March 30, 2016): 4813–22. http://dx.doi.org/10.1080/00036846.2016.1164827.

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Walls, H. L., D. J. Magliano, C. Stevenson, K. Backholer, H. R. Mannan, J. Shaw, and A. Peeters. "Projected progression of the prevalence of obesity in Australia." Obesity Research & Clinical Practice 4 (October 2010): S55. http://dx.doi.org/10.1016/j.orcp.2010.09.109.

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MacKay, S. "Legislative solutions to unhealthy eating and obesity in Australia." Public Health 125, no. 12 (December 2011): 896–904. http://dx.doi.org/10.1016/j.puhe.2011.06.004.

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Miura, K., E. Ballard, Susan L. Clemens, C. M. Harper, N. Begum, P. K. O'Rourke, and A. C. Green. "Sex-specific associations with youth obesity in Queensland, Australia." Public Health 145 (April 2017): 146–48. http://dx.doi.org/10.1016/j.puhe.2016.12.029.

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Hayes, Alison, Anna Chevalier, Mario D'Souza, Louise Baur, Li Ming Wen, and Judy Simpson. "Early childhood obesity: Association with healthcare expenditure in Australia." Obesity 24, no. 8 (July 6, 2016): 1752–58. http://dx.doi.org/10.1002/oby.21544.

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Shrapnel, William S., and Belinda E. Butcher. "Sales of Sugar-Sweetened Beverages in Australia: A Trend Analysis from 1997 to 2018." Nutrients 12, no. 4 (April 7, 2020): 1016. http://dx.doi.org/10.3390/nu12041016.

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Lowering intake of sugar-sweetened beverages (SSBs) is being advocated as an obesity prevention strategy in Australia. The purpose of this study was to extend on previous reports of trends in national volume sales of SSBs. Data were extracted from commercially available datasets of beverage sales (AC Nielsen (1997–2011) and IRI Australia (2009–2018)). Linear regression was used to examine trends for the period 1997 to 2018. Per capita attribution of volume sales and sugar contribution was estimated by dividing by the Australian resident population for the relevant year. Per capita volume sales of SSBs fell 27%, from 83L/person to 61L/person, largely driven by declining sales of sugar-sweetened carbonated soft drinks (76 to 45L/person). Volume sales of non-SSB increased, from 48 to 88L/person, the largest contributor being pure unflavoured still waters (6 to 48L/person). Volume sales of non-SSBs have exceeded those of SSBs since 2015. The yearly contribution of SSBs to the sugar content of the national diet declined from 9.0 to 6.4kg/person. Major, long-term shifts are occurring in the market for non-alcoholic, water-based beverages in Australia, notably a fall in per capita volume sales of SSBs and an increase in volume sales of water. Both trends are consistent with obesity prevention strategies.

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