Health behaviours, intentions and barriers to change among obesity classes I, II and III.
A BastinA J RomainJ MarleauAurélie BaillotPublished in: Clinical obesity (2018)
Health behaviour change is a cornerstone in the management of obesity, and data on health behaviours, intentions and barriers to change would be useful to inform the development of interventions. The aim of this study was to describe these variables in individuals with obesity, and to compare obesity classes. The study obtained data from the Canadian Community Health Survey 2011-2012 including 5614 adults with body mass index (BMI) ≥30 kg m-2 . The majority of participants reported eating four or more fruits and vegetables daily (65.3% [95% confidence interval {CI}: 64.1-66.6]), being a regular drinker (59.6% [95% CI: 58.4-61.0]) and inactive (58.0% [95% CI: 56.7-59.3]). About 84% of participants answered they should do and/or intend to do something in the next year to improve their health, with increasing exercise being the most reported choice (69.2% [95% CI: 67.1-71.5]). Among the 58.0% (95% CI: 55.9-60.2) of participants facing barriers to change, the lack of willpower was the most reported (37.0% [95% CI: 34.2-39.7]). No difference between classes for intention to change and barriers were found. Comorbidities were the most important factor explaining several health behaviours and barriers to change. The vast majority of participants, regardless of the severity of obesity, know they should do and also want to do something to improve their health, but faced a lack of willpower. Thus, the most important thing to consider during an obesity intervention is the lack of motivation to modify health behaviours and beyond BMI, the presence of comorbidities.
Keyphrases
- healthcare
- public health
- weight loss
- insulin resistance
- weight gain
- body mass index
- metabolic syndrome
- mental health
- type diabetes
- health information
- physical activity
- high fat diet induced
- randomized controlled trial
- health promotion
- human health
- machine learning
- skeletal muscle
- high intensity
- resistance training
- health risk
- artificial intelligence