Science topic

Overweight - Science topic

A status with BODY WEIGHT that is above certain standard of acceptable or desirable weight. In the scale of BODY MASS INDEX, overweight is defined as having a BMI of 25.0-29.9 kg/m2. Overweight may or may not be due to increases in body fat (ADIPOSE TISSUE), hence overweight does not equal "over fat".
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My name is Tharushini Anandam, and I am a PhD student at Swinburne University in Melbourne, Australia. I am currently undertaking a research project as part of a Doctor of Philosophy (PhD). The purpose of my research is to increase the physical activity levels in young men with overweight or obesity by using goal-oriented strategies. They will be invited to participate in a 6-week telehealth-supported exercise program involving cardiorespiratory exercise and resistance training.
In order to conduct this study, I am seeking to recruit male participants between the age range of 18 to 34 years old who are currently with overweight or obesity (BMI 25kg/m2 to 39.9 kg/m2). Participants must be Australian citizens residing in Australia and should not have any mobility impairment. Participants will be asked to complete a pre-screening questionnaire, and if cleared, will be followed by participating in a 6-week exercise program.
It would also be greatly appreciated if you could forward this advertisement to any male friends, colleagues, or family members who meet the above criteria and may be interested to participate in a 6-week exercise program via telehealth. Thank you for your time and assistance.
If you have any questions regarding the project, please contact me via email at tanandam@swin.edu.au
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I wish you all the best
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I investigated the extent and prevalence of physical activity during the school day and sedentary behavior during inactive screen time in youth and their effect on overweight and obesity. Participants were stratified by age (children - adolescents) and gender. Data were compared using t-test and ANOVA and the effect on overweight and obesity was studied using MLR. Are my data considered nested? If so, how do I calculate the ICC requested by the reviewer?
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Dear Sirs,
Thank you for the answers. I need a reasoned response to answer the reviewer. Sincerely,
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Hi everyone,
I have two variables: BMI categories (underweight, healthy weight, overweight, obese) and Perceived Weight Status (underweight, healthy weight, overweight, obese, prefer not to answer).
I am trying to find out if participants guessed their BMI category correctly based on what they selected for their perceived weight status. Which analysis should I use for this?
Thank you!
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There are several possible ways to assess:
1. Spearman's correlation coefficient of four categories (underweight, healthy weight, overweight, obese) - a positive correlation is expected
2. calculate the ratio of the number of accurate estimates (how many respondents were classified in the right category) and the total number of respondents
3. calculate the ratio of the number of those who underestimated their weight (for example, BMI> 25, and the estimate is underweight) and the total number of respondents
4. calculate the ratio of the number of those who overestimated their weight (for example, BMI <25, and the estimate is overweight) and the total number of respondents
5. for the category "prefer not to answer" assess what their real weight status BMI is (to answer who are the respondents who do not want to assess their weight status)
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Dear collogues,
May I ask, What are the best natural herbs for obesity management?
Thanks
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I was wondering if there has been any studies? Or Research
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Also see kindly the following very good RG link:
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I am writing research orientationed book
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Obesity is a complex health problem caused by a variety of causes and human factors such as behavior and genetics. Physical activities, inactivity, food habits, drug usage, and other exposures may all be considered behaviors.
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Participants are randomly assigned to two groups- experimental (internet based) and control (physical visit). BMI Measurements will be conducted at 3, 6, and 12th month. In the end, I want to assess if the treatment is effective in changing the BMI category of patient (from obese to normal; overweight to normal).
I have looked into several statistical tests and I'm still a bit confused. I know you have to test first for a normal distribution and then proceed with the appropriate test. I wish to narrow down my choices for this design.
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As obesity is suggested to be a risk factor of COVID-19, possible relationship between COVID-19 death (data from Johns Hopkins Univ.) and obesity was plotted on a graph (attached file). Since COVID-19 patient data is not readily available, average overweight population or BMI by nation (data from Our World in Data) was used as a surrogate. As shown in attached Fig, nation with average BMI lower than 25 exhibits extremely low COVID-19 death especially for male. This might be related to activated Akt/TORC1 pathway in obesity, of which pathway has an impact on immunity and inflammation. On the other hand, interestingly, quite a few countries with high average BMI showed very low mortality as that with low BMI. Although BMI here is not real patient data, provided that high BMI patients actually resulted in low death probability in some COVID-19 infected segments, we should look into underlying mechanism in detail. There might be some way to find potential COVID-19 therapeutics. I hope that some researchers already have a clue.
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People in attempt of losing weight always experience weight cycling: the repetitions of losing and gaining weight multiple times through their lives, or the so-called “Yo-Yo Effect”. What do you think are the causes of Yo-Yo Effect, and how to overcome them?
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Although restriction of diet often results in initial weight loss, more than 80 per cent of obese dieters fail to maintain their reduced weight. Obese people may regain weight after dieting due to hormonal changes.
It means that even though our weight is reduced, hunger hormones persist to be released in a way by which individual gain weight again.
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Excess weight is a serious concern worldwide which prones the individual to several complications like heart diseases and strokes, high blood pressure, diabetes, certain types of cancer, kidney disease, sleep apnea and fatty liver disease to list as few. According to WHO, more than 1.9 billion adults aged 18 years and older were overweight in 2016, of which over 650 million adults were obese. According to you, what are some of the most effective exercises, diet plan and herbs that can aid in weight loss?
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I personally think those who are overweight or obese are deprived of fibre and complex carbohydrates in their diets. Moreover, they mainly focus on taking only simple sugars and carbohydrates in their diet. Adding a good amount of fruits and raw vegetables will increase the fibre as well as will be full of antioxidants which will help them from certain diseases. Where as intake of Vitamin C in our diets is highly recommended for better immunity. Fibre provides us with satiety and will therefore, elongate the transit time of next meal.
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I am hoping to undertake my first meta-analysis, where the exposure variable it mean number of decayed, missing or filled teeth)and the outcome is BMI category (underweight, normal weight, overweight, obese). I understand that RevMan requires the exposure variable to be categorical. Is there a way of performing meta-analysis with my data? Regards, Louise.
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You have to define a measure of association and its standard error (such as mean difference in decayed teeth between normal and overweight subjects) that is common or can be defined across studies
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Sometimes in obese subjects with grade two and higher fatty liver disease , in spite of all standard medical precise observation, it is difficult to treat the patient completely. What are the best therapeutics agent for this patients?
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Dear Seyed,
Maybe the following recent review will help you on the subject:
Sarwar R, Pierce N, Koppe S. Obesity and nonalcoholic fatty liver disease: current perspectives. Diabetes Metab Syndr Obes 2018;11:533-542. https://www.ncbi.nlm.nih.gov/pmc/articles/PMC6163009/pdf/dmso-11-533.pdf
Best wishes from Germany,
Martin