Prevalence of and intention to change dietary and physical activity health risk behaviours

Intention to change multiple health risk behaviors and predictors of behavior change in vocational education students

Objective: No studies have examined vocational education students' intention to change multiple health risk behaviors and whether baseline characteristics predict behavior change. Participants: Paticipants were vocational education students in New South Wales, Australia. Methods: Students in the no-intervention control arm of a cluster randomized controlled trial completed an online survey at baseline and 6 months later. Results: Of 450 participants (83.3%) who reported multiple health risk behaviors at baseline, one-third (33.1%) intended to change at least two risk behaviors within 6 months. Participants experiencing symptoms of anxiety [OR = 7.43, 95% CIs 1.26-43.87; p = 0.03] and who intended to change three to four risk behaviors [OR = 23.30, 95% CIs 4.01-135.40; p = 0.001] rather than one behavior had significantly greater odds of changing at least one behavior in 6 months. Conclusions: Interventions could support vocational education students to change behaviors they wish to as well as motivate them to address other risk behaviors.

The relationship between process use and stage of change for sugary drinks

BACKGROUND

Decreasing sugar-sweetened beverage consumption may reduce obesity and obesity-related diseases. To better understand what processes could facilitate a reduction in sugary beverage intake, we examined the relationship between stage-of-change and use of 10 processes of change. Secondarily, reliability of the measure was assessed.

METHODS

A cross-sectional study was conducted, using a newly developed stage-of-change and process of change questionnaire. Participants (n = 105; male, n = 28) were aged between 18 and 60 years. A one-way analysis of variance, with Tukey's and Benjamini-Hochberg post hoc tests, was used to compare process use by stages. Paired t-tests were used to compare total cognitive and total behavioural process use within each stage. Cronbach's α coefficient and mean inter-item correlation was used to assess internal consistency. Reliability of repeated items was examined using kappa.

RESULTS

Cognitive and behavioural processes were used more in the contemplation/preparation and maintenance stages than in precontemplation (all P < 0.05). Compared to precontemplation, process use was significantly higher in contemplation/preparation for five individual processes, action for four processes and maintenance for five processes. The use of dramatic relief and self liberation was lower in maintenance than contemplation/preparation. Across the stages, the use of eight of the 10 processes differed. The use of consciousness raising, self re-evaluation and self liberation differed between stages more frequently than other processes.

CONCLUSIONS

The use of many processes differed by stage and could be incorporated into programmes aiming to assist adults in reducing their consumption of sugary drinks.

A population-based survey on physical inactivity and leisure time physical activity among adults in Chiang Mai, Thailand, 2014

Background

Reducing physical inactivity among the population is a challenge for many nations. Targeting leisure time physical activity (LTPA) may be useful in increasing overall physical activity as it is assumed it is associated with a higher degree of free choice and personal preference than physical activity at work and during travel. The study explored the prevalence of physical inactivity and focused on the overall level of energy expenditure and energy level spent during leisure time among those who were physically inactive and assessed the stages of change for LTPA among those who were physically inactive.

Methods

A population-based survey was conducted in 2014 in Chiang Mai, Thailand using a stratified two-stage cluster sampling technique. The Global Physical Activity Questionnaire (GPAQ) was used to collect the data on physical activity. Sufficient levels of physical activity (PA) were defined as ≥150 min/week of moderate-intensity PA or ≥75 min/week of vigorous-intensity PA or ≥600 metabolic equivalent of task (MET)-minutes/week. Weighted analyses were used to estimate the prevalence of physical inactivity, the total energy expenditure and expenditure during LTPA as well as stages of change among the physically inactive population.

Results

A total of 1744 people (808 men and 936 women), aged 15 to 64 years, participated in the study. We estimated that a quarter (26%) of the population were physically inactive. Physical inactivity was more commonly found among women than men in most age groups. LTPA contributed a small proportion of overall PA. On average, physically inactive men spent 132.8 MET-minutes/week and inactive women spent 208.2 MET-minutes/week in overall PA which is well below the 600 MET-minutes/week recommend by the World Health Organization. Around 75% of physically inactive people had no intention of engaging in regular LTPA.

Conclusion

About a quarter of the investigative population were physically inactive. Most physically inactive members of the population participate in low levels of LTPA, but the majority has no intention of increasing PA during leisure time. A large-scale health promotion program is needed, and it should focus on an approach for the pre-contemplated population.

Improved confidence in performing nutrition and physical activity behaviours mediates behavioural change in young adults: Mediation results of a randomised controlled mHealth intervention

BACKGROUND

The burden of weight gain disproportionally affects young adults. Understanding the underlying behavioural mechanisms of change in mHealth nutrition and physical activity interventions designed for young adults is important for enhancing and translating effective interventions.

PURPOSE

First, we hypothesised that knowledge, self-efficacy and stage-of-change for nutrition and physical activity behaviours would improve, and second, that self-efficacy changes in nutrition and physical activity behaviours mediate the behaviour changes observed in an mHealth RCT for prevention of weight gain.

METHODS

Young adults, aged 18-35 years at risk of weight gain (n = 250) were randomly assigned to an mHealth-program, TXT2BFiT, consisting of a three-month intensive phase and six-month maintenance phase or to a control group. Self-reported online surveys at baseline, three- and nine-months assessed nutrition and physical activity behaviours, knowledge, self-efficacy and stage-of-change. The mediating effect of self-efficacy was assessed in multiple PROCESS macro-models for three- and nine-month nutrition and physical activity behaviour change.

RESULTS

Young adults randomised to the intervention increased and maintained knowledge of fruit requirements (P = 0.029) compared to controls. Intervention participants' fruit and takeaway behaviours improved to meet recommendations at nine months, with a greater proportion progressing to action or maintenance stage-of-change (P < 0.001 and P = 0.012 respectively) compared to controls. Intervention participants' vegetable and physical activity behaviours did not meet recommendations, thereby halting progress to action or maintenance stage-of-change. Indirect effects of improved nutrition and physical activity behaviours at three- and nine-months in the intervention group were explained by changes in self-efficacy, accounting for 8%-37% of the total effect.

CONCLUSIONS

This provides insights into how the mHealth intervention achieved part of its effects and the importance of improving self-efficacy to facilitate improved eating and physical activity behaviours in young adults.

A Mobile Health Lifestyle Program for Prevention of Weight Gain in Young Adults (TXT2BFiT): Nine-Month Outcomes of a Randomized Controlled Trial

Background

The unprecedented rise in obesity among young adults, who have limited interaction with health services, has not been successfully abated.

Objective

The objective of this study was to assess the maintenance outcomes of a 12-week mHealth intervention on prevention of weight gain in young adults and lifestyle behaviors at 9 months from baseline.

Methods

A two-arm, parallel, randomized controlled trial (RCT) with subjects allocated to intervention or control 1:1 was conducted in a community setting in Greater Sydney, Australia. From November 2012 to July 2014, 18- to 35-year-old overweight individuals with a body mass index (BMI) of 25-31.99 kg/m2 and those with a BMI ≥ 23 kg/m2 and a self-reported weight gain of ≥ 2 kg in the past 12 months were recruited. A 12-week mHealth program “TXT2BFiT” was administered to the intervention arm. This included 5 coaching calls, 96 text messages, 12 emails, apps, and downloadable resources from the study website. Lifestyle behaviors addressed were intake of fruits, vegetables, sugar-sweetened beverages (SSBs), take-out meals, and physical activity. The control group received 1 phone call to introduce them to study procedures and 4 text messages over 12 weeks. After 12 weeks, the intervention arm received 2 further coaching calls, 6 text messages, and 6 emails with continued access to the study website during 6-month follow-up. Control arm received no further contact. The primary outcome was weight change (kg) with weight measured at baseline and at 12 weeks and self-report at baseline, 12 weeks, and 9 months. Secondary outcomes were change in physical activity (metabolic equivalent of task, MET-mins) and categories of intake for fruits, vegetables, SSBs, and take-out meals. These were assessed via Web-based surveys.

Results

Two hundred and fifty young adults enrolled in the RCT. Intervention participants weighed less at 12 weeks compared with controls (model β=−3.7, 95% CI −6.1 to −1.3) and after 9 months (model β=− 4.3, 95% CI − 6.9 to − 1.8). No differences in physical activity were found but all diet behaviors showed that the intervention group, compared with controls at 9 months, had greater odds of meeting recommendations for fruits (OR 3.83, 95% CI 2.10-6.99); for vegetables (OR 2.42, 95% CI 1.32-4.44); for SSB (OR 3.11, 95% CI 1.47-6.59); and for take-out meals (OR 1.88, 95% CI 1.07-3.30).

Conclusions

Delivery of an mHealth intervention for prevention of weight gain resulted in modest weight loss at 12 weeks with further loss at 9 months in 18- to 35-year-olds. Although there was no evidence of change in physical activity, improvements in dietary behaviors occurred, and were maintained at 9 months. Owing to its scalable potential for widespread adoption, replication trials should be conducted in diverse populations of overweight young adults.

Trial Registration

Australian and New Zealand Clinical Trials Registry (ANZCTR): ACTRN12612000924853; (Archived by WebCite at http://www.webcitation.org/6i6iRag55)