amazonkrot.blogg.se

Descriptive cross sectional data analysis methods
Descriptive cross sectional data analysis methods







Humple and Lesli (2002) after reviewing nineteen articles that studied the relationship between physical activity and behavior mentions that providing facilities and opportunities can significantly improve the level of physical activities. A study done in the United Kingdom mentions that Indians and Pakistanis in the age range of 40 to 60 years in Britain, due to working very long hours in shops and restaurants were the key barriers for them not to take part in activities like walking and swimming on a regular basis. Lack of time and money have also been cited as personal barriers. Studies have demonstrated that there are many types of environmental, social and personal barriers for the regular participation in physical activity.Ī study conducted in the United States finds that people who prefer sedentary behavior are prone to be physically inactive. Įven though the importance of physical activity is well known, an alarming percentage (30%) of people throughout the world are physically inactive. Physical exercise either in the form of aerobic or resistance training is known to significantly improve nonalcoholic fatty liver disease (NAFLD). According to Romero et al (2017) lifestyle intervention is effective in treating non-alcoholic fatty liver disease (NAFLD) patients and weight reductions of more than 10% can induce a significant improvement in non-alcoholic steato hepatitis and fibrosis. A study conducted by Pereira et al (2019) demonstrates that participating in regular physical exercise is beneficial to people with bipolar disorders. Regular participation in physical exercise has helped minimally disabled patients with multiple sclerosis to remain active and maintain their independence. Many studies have demonstrated that physical activity has a positive association with quality of life, physical capacity and cardio respiratory fitness. Data used for the analysis.xlsx” contains my minimal data set.įunding: The authors received no specific funding for this work.Ĭompeting interests: The authors have declared that no competing interests exist. I have included a separate caption for supplementary file at the end of the manuscript.

descriptive cross sectional data analysis methods descriptive cross sectional data analysis methods

This is an open access article distributed under the terms of the Creative Commons Attribution License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original author and source are credited.ĭata Availability: All relevant data are within the paper and its Supporting Information files.

descriptive cross sectional data analysis methods

Received: OctoAccepted: ApPublished: May 12, 2020Ĭopyright: © 2020 Karunanayake et al. PLoS ONE 15(5):Įditor: Senaka Rajapakse, University of Colombo Faculty of Medicine, SRI LANKA Citation: Karunanayake AL, Senaratne CD, Stathi A (2020) A descriptive cross sectional study comparing barriers and determinants of physical activity of Sri Lankan middle aged and older adults.









Descriptive cross sectional data analysis methods