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      Trends in the prevalence of adult overweight and obesity in Australia, and its association with geographic remoteness

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          Abstract

          The prevalence of overweight and obesity has been increasing globally and has become a significant public health concern in Australia in the two past decades. This study explores the most recent national prevalence and trends of adult overweight and obesity in Australia. It will also investigate geographic remoteness as a potential risk factor for an individual being overweight or obese in adulthood. A retrospective longitudinal study that utilised 14 successive waves (wave 6 through 19) of a nationally representative linked individual-level survey. Data was obtained from the Household, Income and Labour Dynamics in Australia survey. The data on 199,675 observations from 26,713 individuals aged ≥ 15 years over the period 2006 to 2019 was analysed. Random-effects logit model was employed to estimate the association between geographic remoteness and the risk of excessive weight gain. The results reveal that the prevalence of overweight, obesity and combined overweight and obesity among Australian adults in 2019 were 34%, 26% and 60%, respectively. The analysis shows that the prevalence of overweight and obesity varies by geographic remoteness. Adults from regional city urban (OR 1.53, 95% CI 1.16–2.03) and rural areas (OR 1.32, 95% CI 1.18–1.47) were more likely to be obese compared with their counterparts from major city urban areas. The results also show that adults living in major city urban areas, regional city urban areas, and regional city rural areas in Australia were 1.53 (OR 1.53, 95% CI 1.16–2.03), 1.32 (OR 1.32, 95% CI 1.18–1.47), and 1.18 (OR 1.18, 95% CI 1.08–1.29) times more likely to be overweight compared with their counterparts from major city urban areas in Australia. Substantial geographic variation in the prevalence of overweight and obesity exists among Australian adults and appears to be increasing. Public health measures should focus on contextual obesogenic factors and behavioural characteristics to curb the rising prevalence of adult obesity.

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          Ror2 signaling regulates Golgi structure and transport through IFT20 for tumor invasiveness

          Signaling through the Ror2 receptor tyrosine kinase promotes invadopodia formation for tumor invasion. Here, we identify intraflagellar transport 20 (IFT20) as a new target of this signaling in tumors that lack primary cilia, and find that IFT20 mediates the ability of Ror2 signaling to induce the invasiveness of these tumors. We also find that IFT20 regulates the nucleation of Golgi-derived microtubules by affecting the GM130-AKAP450 complex, which promotes Golgi ribbon formation in achieving polarized secretion for cell migration and invasion. Furthermore, IFT20 promotes the efficiency of transport through the Golgi complex. These findings shed new insights into how Ror2 signaling promotes tumor invasiveness, and also advance the understanding of how Golgi structure and transport can be regulated.
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            Prevalence of obesity among adults from rural and urban areas of the United States: findings from NHANES (2005-2008).

            Rural residents have higher rates of chronic diseases compared to their urban counterparts, and obesity may be a major contributor to this disparity. This study is the first analysis of obesity prevalence in rural and urban adults using body mass index classification with measured height and weight. In addition, demographic, diet, and physical activity correlates of obesity across rural and urban residence are examined. Analysis of body mass index (BMI), diet, and physical activity from 7,325 urban and 1,490 rural adults in the 2005-2008 National Health and Nutrition Examination Survey (NHANES). The obesity prevalence was 39.6% (SE = 1.5) among rural adults compared to 33.4% (SE = 1.1) among urban adults (P = .006). Prevalence of obesity remained significantly higher among rural compared to urban adults controlling for demographic, diet, and physical activity variables (odds ratio = 1.18, P = .03). Race/ethnicity and percent kcal from fat were significant correlates of obesity among both rural and urban adults. Being married was associated with obesity only among rural residents, whereas older age, less education, and being inactive was associated with obesity only among urban residents. Obesity is markedly higher among adults from rural versus urban areas of the United States, with estimates that are much higher than the rates suggested by studies with self-reported data. Obesity deserves greater attention in rural America. © 2012 National Rural Health Association.
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              A comparison of direct vs. self-report measures for assessing height, weight and body mass index: a systematic review.

              Obesity is a rapidly increasing public health problem, with surveillance most often based on self-reported values of height and weight. We conducted a systematic review to determine what empirical evidence exists regarding the agreement between objective (measured) and subjective (reported) measures in assessing height, weight and body mass index (BMI). Five electronic databases were searched to identify observational and experimental studies on adult populations over the age of 18. Searching identified 64 citations that met the eligibility criteria and examined the relationship between self-reported and directly measured height or weight. Overall, the data show trends of under-reporting for weight and BMI and over-reporting for height, although the degree of the trend varies for men and women and the characteristics of the population being examined. Standard deviations were large indicating that there is a great deal of individual variability in reporting of results. Combining the results quantitatively was not possible because of the poor reporting of outcomes of interest. Accurate estimation of these variables is important as data from population studies such as those included in this review are often used to generate regional and national estimates of overweight and obesity and are in turn used by decision makers to allocate resources and set priorities in health.
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                Author and article information

                Contributors
                syed.afroz@econ.ku.ac.bd
                Journal
                Sci Rep
                Sci Rep
                Scientific Reports
                Nature Publishing Group UK (London )
                2045-2322
                31 May 2021
                31 May 2021
                2021
                : 11
                : 11320
                Affiliations
                [1 ]GRID grid.412118.f, ISNI 0000 0001 0441 1219, Economics Discipline, Social Science School, , Khulna University, ; Khulna, 9208 Bangladesh
                [2 ]GRID grid.1048.d, ISNI 0000 0004 0473 0844, School of Business, , University of Southern Queensland, ; Toowoomba, QLD 4350 Australia
                [3 ]GRID grid.1048.d, ISNI 0000 0004 0473 0844, Centre for Health Research, , University of Southern Queensland, ; Toowoomba, QLD 4350 Australia
                [4 ]GRID grid.412125.1, ISNI 0000 0001 0619 1117, Department of Health Services and Hospital Administration, Faculty of Economics and Administration, , King Abdulaziz University, ; Jeddah, Saudi Arabia
                [5 ]GRID grid.16463.36, ISNI 0000 0001 0723 4123, School of Accounting, Economics, and Finance, , University of KwaZulu-Natal, ; Durban, 4000 South Africa
                [6 ]GRID grid.412125.1, ISNI 0000 0001 0619 1117, Health Economics Research Group, , King Abdulaziz University, ; Jeddah, Saudi Arabia
                Article
                90750
                10.1038/s41598-021-90750-1
                8166878
                34059752
                e4856461-7bd6-4d4a-9c67-f75d91d853c9
                © The Author(s) 2021

                Open Access This article is licensed under a Creative Commons Attribution 4.0 International License, which permits use, sharing, adaptation, distribution and reproduction in any medium or format, as long as you give appropriate credit to the original author(s) and the source, provide a link to the Creative Commons licence, and indicate if changes were made. The images or other third party material in this article are included in the article's Creative Commons licence, unless indicated otherwise in a credit line to the material. If material is not included in the article's Creative Commons licence and your intended use is not permitted by statutory regulation or exceeds the permitted use, you will need to obtain permission directly from the copyright holder. To view a copy of this licence, visit http://creativecommons.org/licenses/by/4.0/.

                History
                : 2 October 2020
                : 10 May 2021
                Categories
                Article
                Custom metadata
                © The Author(s) 2021

                Uncategorized
                diseases,risk factors,signs and symptoms
                Uncategorized
                diseases, risk factors, signs and symptoms

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