Investigation of the Prevalence of Obesity in Iran: a Systematic Review and Meta-Analysis Study.
Student Research Committee | Psychosocial Injuries Research Center | The Tisch Cancer Institute
Abstract
Obesity is one of the main public health problems which underlie many chronic illnesses and socioeconomic difficulties. According to the literature review, there are limited data on the prevalence of obesity in different parts of Iran as well as its trend and prevalence among different age and gender groups. The aim of this study was to estimate the obesity prevalence in Iran using meta-analysis. All the corresponding articles published in the external and internal journals, final reports of research projects, articles of related congresses and the reference index of the correlated papers published between 1995 and 2010 were collected via the electronic research engines (PubMed, Scopus, SID, Magiran, IranMedex). Data were analyzed using meta-analysis (random effects model) and meta-regression). A total of 144 articles with the sample size of 377858 people (134588 males and 164858 females) were enrolled in the study. The prevalence of obesity in populations above the age of 18 was estimated as 21.7% (CI 95%: 18.5% - 25%) and in populations below 18 as 6.1% (CI 95%: 6.8%-5.4%). Meta-regression analysis showed an ascending trend in the prevalence of obesity in Iran. The prevalence rates of obesity according to the BMI index, NCHC and percentile above 95 were 17.4%, 7.6% and 7.4%, respectively. The BMI mean was 19.3 in populations below the age of 18 (CI 95%: 17-21.6) and 25.2 in those above the age of 18 (CI 95%: 27.1-23.3). Considering the increasing rate of obesity in Iran and its effects on the public health, corresponding health authorities should revise the obesity preventive programs and, using public health interventions, reduce the rate of obesity in the country.
MoreTranslated text
Key words
Iran,Meta-analysis,Obesity,Overweight,Prevalence
求助PDF
上传PDF
View via Publisher
AI Read Science
AI Summary
AI Summary is the key point extracted automatically understanding the full text of the paper, including the background, methods, results, conclusions, icons and other key content, so that you can get the outline of the paper at a glance.
Example
Background
Key content
Introduction
Methods
Results
Related work
Fund
Key content
- Pretraining has recently greatly promoted the development of natural language processing (NLP)
- We show that M6 outperforms the baselines in multimodal downstream tasks, and the large M6 with 10 parameters can reach a better performance
- We propose a method called M6 that is able to process information of multiple modalities and perform both single-modal and cross-modal understanding and generation
- The model is scaled to large model with 10 billion parameters with sophisticated deployment, and the 10 -parameter M6-large is the largest pretrained model in Chinese
- Experimental results show that our proposed M6 outperforms the baseline in a number of downstream tasks concerning both single modality and multiple modalities We will continue the pretraining of extremely large models by increasing data to explore the limit of its performance
Upload PDF to Generate Summary
Must-Reading Tree
Example

Generate MRT to find the research sequence of this paper
Related Papers
2008
被引用27 | 浏览
2009
被引用98 | 浏览
2006
被引用208 | 浏览
2011
被引用14 | 浏览
2011
被引用44 | 浏览
2012
被引用38 | 浏览
2004
被引用45 | 浏览
2010
被引用10 | 浏览
2010
被引用24 | 浏览
2010
被引用25 | 浏览
2013
被引用10 | 浏览
2006
被引用26 | 浏览
2008
被引用17 | 浏览
2002
被引用25 | 浏览
Data Disclaimer
The page data are from open Internet sources, cooperative publishers and automatic analysis results through AI technology. We do not make any commitments and guarantees for the validity, accuracy, correctness, reliability, completeness and timeliness of the page data. If you have any questions, please contact us by email: report@aminer.cn
Chat Paper
GPU is busy, summary generation fails
Rerequest