Five-year Evolution Patterns of Physical Activity and Sedentary Behavior in Patients with Lower-limb Osteoarthritis and Their Sociodemographic and Clinical Correlates

ObjectiveThe present study aimed to identify trajectories of physical activity (PA) components (frequency, duration, intensity, and type) and screen-based sedentary behavior (SB) as well as baseline predictors of each trajectory in patients with hip and/or knee osteoarthritis (OA).MethodsWe included 878 patients with a 5-year follow-up from the KHOALA cohort. PA and SB were measured by the Modifiable Activity Questionnaire. We used group-based trajectory analysis to identify the trajectories of PA components and screen-based SB, and multivariable logistic regression to determine predictors of the identified trajectories.ResultsTwo groups of trajectories were identified for each PA component and 3 for SB. High and decreasing PA duration was associated with female sex (OR 0.3, 95% CI 0.1–0.5) as was low and stable, more so than high and decreasing prevalence of weight-bearing activities (OR 0.6, 95% CI 0.4–0.9). Patients with impaired patient-reported outcome measures and obese patients often featured low versus high and decreasing prevalence of weight-bearing activities. Predictors of moderate and high versus low and slightly increasing screen-based SB trajectories were male sex, age < 60 years, single status (OR 1.5, 95% CI 1.1–2.1), obesity (OR 2.1, 95% CI 1.4–3.1), smoking (OR 2.0, 95% CI 1.1–3.7), and less physical jobs. Predictors of moderate and high versus low screen-based SB trajectories were all sociodemographic: male sex, age < 60 years, single status, obesity, smoking, and less physical jobs.ConclusionSociodemographic and clinical predictors of trajectories vary between PA components; they are associated mainly with PA frequency and type. No clinical characteristics were associated with screen-based SB.

Impact of Lifestyle Strategies on Longer-Term Physical Activity and Weight

Background:Lifestyle interventions promote increased physical activity (PA) and weight loss; however, relapse to sedentary behavior and weight regain are common.Methods:We analyzed baseline and 24-month data from participants in the Slow the Adverse Vascular Effects (SAVE) study. SAVE included an 18-month behavioral intervention. At 24 months, participants completed a survey about lifestyle strategies used in past 6 months. PA levels were assessed with the Modifiable Activity Questionnaire. We compared change in weight, BMI, and PA from baseline to 24 months by use of strategies vs. no use.Results:214 participants (61%) completed 24-month visit. 74% were female and 86% were white. At 24 months, 65% used self-monitoring, 67% group/commercial support, 94% other behavioral skills, and 27% used professional support within past 6 months. At 24 months, participants who used self-monitoring (5.2 vs. –0.8 MET-hr/wk; P = .001) and group/commercial support (4.3 vs. 0 MET-hrs/wk; P = .01) had greater PA increases compared with those who did not use strategies. Participants who used other behavioral strategies had a significantly greater percent decrease in weight than those who did not.Conclusions:Of the lifestyle strategies used following intervention, self-monitoring and group/commercial support may be particularly important in longer-term PA levels.

Physical Activity Attitudes, Beliefs, and Practices Among Women in a Woodland Cree Community

Background:Overweight and obesity among Aboriginal women is a growing concern, with increasing prevalence rates linked to a sedentary lifestyle. Physical inactivity is a modifiable risk factor for unhealthy body weight; however before addressing health enhancing behaviors, understanding lifestyle practices, attitudes and beliefs are important.Methods:A mixed methods approach assessed physical activity (PA) practices (n = 58), and attitudes and beliefs (n = 19) among First Nations women. The Modifiable Activity Questionnaire assessed PA, and a focused ethnography explored attitudes and beliefs.Results:Self-reported PA was highest in the youngest age group. Both total and leisure-time PA decreased when house-related activities were not accounted for. Younger participants reported sport-related activities, while older participants reported traditional activities (eg, berry picking, fishing). Participants’ believed PA promoted good health, yet personal (ie, lack of time), community-specific (ie, lack of opportunities/encouragement) and environmental (ie, inclement weather, safety) factors acted as barriers. Age-specific, women-only programs were highlighted as potential enablers.Conclusions:The findings highlight the need to assess cultural specific practices, attitudes and beliefs as PA programs that focus on reducing barriers identified in the community and are designed based on expressed interest and preferences may improve leisure-related PA levels among all age groups.

Most Common Types of Physical Activity Self-Selected by People with Multiple Sclerosis

The promotion of physical activity for people with multiple sclerosis (MS) would benefit from information about the common types of physical activity self-selected by this population. This study examined the most frequent types of physical activity self-reported by a large sample of people with MS. The data were collected as part of the baseline assessment of a longitudinal investigation of physical activity in relapsing-remitting MS (RRMS). The participants (N = 272) were sent a battery of questionnaires through the US Postal Service that included the Modifiable Activity Questionnaire for assessing types of physical activity performed during the previous year. Walking was ranked number 1 for both the first and second most common types of physical activity self-selected by people with MS, and it was ranked number 4 as the third most common type of self-selected physical activity. Collectively, 79% of the sample reported walking as a frequent form of self-selected physical activity in the previous year. Other notable types of physical activities self-selected by people with MS were gardening (44%), weight training (34%), bicycling (30%), and calisthenics (20%). This information may assist clinicians and practitioners in the development of physical activity programs and recommendations for people with MS.

Heterogeneity of Dietary Profiles in Highly Sedentary Young Guadeloupean Women

Objective:The aim was to examine the relationship between physical activity pattern and dietary profile. Although some clustering of the variables related to these major determinants of cardiovascular risk has been demonstrated, they have not been extensively studied together.Participants, Design, and Setting:Two hundred two female university students from the main Guadeloupe (French West Indies) campus participated. They self-administered a validated Food Frequency Questionnaire and the 1-yr recall Modifiable Activity Questionnaire. Principal-component analysis was performed on the scores and the variables related to the physical activity pattern and dietary profile.Results:A model including 10 variables explained 84.9% of the total variance. The physical activity pattern was not associated with the dietary profile, apart from fruit intake. The physical activity level was homogeneously low (median 1.58, first and last quartile cutoffs 1.54 and 1.66, respectively). There was no correlation between the physical activity level and the Food Frequency Questionnaire score (r = –.005).Conclusions:The absence of a strong relationship between the food and physical activity profiles is interpreted as a possible reflection of a dysregulation of the quality of food intake in this population with a sedentary lifestyle.

Validation of an Historical Physical Activity Recall Tool in Postpartum Women

Background:Physical activity (PA) is an important component of a healthy pregnancy and postpartum period. Since prospective PA monitoring throughout gestation is difficult, a valid PA recall tool would be of significant benefit to researchers. The purpose of this study was to evaluate the ability of women to recall their physical activity performed during pregnancy and postpartum, 6 years later.Methods:Thirty women participated in an historical PA recall study. Pregnancy PA was monitored carefully via assisted physical activity diary (PAD) 6 years before the current investigation. A Modifiable Activity Questionnaire (MAQ) was used to assess current and past pregnancy PA. The MAQ was administered for each time period in the order of most distant past to most current. Leisure time energy expenditure values (kcal/kg/day) calculated from the PAD and the MAQ were compared.Results:MAQ energy expenditure values showed good positive relationships with PAD measures at 20 weeks gestation (r = .57; P < .01), 32 weeks gestation (r = .85; P < .01), and 12 weeks postpartum (r = .86; P < .01). Correlations found were similar to those from previous PA recall and MAQ validation studies using nonpregnant populations.Conclusions:The MAQ is an appropriate tool to assess pregnancy and postpartum PA in women 6 years postpartum.