Population aging increases the need for knowledge on positive aspects of aging, and contributions of older people to their own wellbeing and that of others. We defined active aging as an individual's striving for elements of wellbeing with activities as per their goals, abilities and opportunities. This study examines associations of health, health behaviors, health literacy and functional abilities, environmental and social support with active aging and wellbeing. We will develop and validate assessment methods for physical activity and physical resilience suitable for research on older people, and examine their associations with active aging and wellbeing. We will examine cohort effects on functional phenotypes underlying active aging and disability.
For this population-based study, we plan to recruit 1000 participants aged 75, 80 or 85 years living in central Finland, by drawing personal details from the population register. Participants are interviewed on active aging, wellbeing, disability, environmental and social support, mobility, health behavior and health literacy. Physical activity and heart rate are monitored for 7 days with wearable sensors. Functional tests include hearing, vision, muscle strength, reaction time, exercise tolerance, mobility, and cognitive performance. Clinical examination by a nurse and physician includes an electrocardiogram, tests of blood pressure, orthostatic regulation, arterial stiffness, and lung function, as well as a review of chronic and acute conditions and prescribed medications. C-reactive protein, small blood count, cholesterol and vitamin D are analyzed from blood samples. Associations of factors potentially underlying active aging and wellbeing will be studied using multivariate methods. Cohort effects will be studied by comparing test results of physical and cognitive functioning with results of a cohort examined in 1989-90.
The current study will renew research on positive gerontology through the novel approach to active aging and by suggesting new biomarkers of resilience and active aging. Therefore, high interdisciplinary impact is expected. This cross-sectional study will not provide knowledge on temporal order of events or causality, but an innovative cross-sectional dataset provides opportunities for emergence of novel creative hypotheses and theories.
Limited research has examined the association between physical activity, health-related fitness, and disease outcomes in breast cancer survivors. Here, we present the rationale and design of the Alberta Moving Beyond Breast Cancer (AMBER) Study, a prospective cohort study designed specifically to examine the role of physical activity and health-related fitness in breast cancer survivorship from the time of diagnosis and for the balance of life. The AMBER Study will examine the role of physical activity and health-related fitness in facilitating treatment completion, alleviating treatment side effects, hastening recovery after treatments, improving long term quality of life, and reducing the risks of disease recurrence, other chronic diseases, and premature death.
The AMBER Study will enroll 1500 newly diagnosed, incident, stage I-IIIc breast cancer survivors in Alberta, Canada over a 5 year period. Assessments will be made at baseline (within 90 days of surgery), 1 year, and 3 years consisting of objective and self-reported measurements of physical activity, health-related fitness, blood collection, lymphedema, patient-reported outcomes, and determinants of physical activity. A final assessment at 5 years will measure patient-reported data only. The cohort members will be followed for an additional 5 years for disease outcomes.
The AMBER cohort will answer key questions related to physical activity and health-related fitness in breast cancer survivors including: (1) the independent and interactive associations of physical activity and health-related fitness with disease outcomes (e.g., recurrence, breast cancer-specific mortality, overall survival), treatment completion rates, symptoms and side effects (e.g., pain, lymphedema, fatigue, neuropathy), quality of life, and psychosocial functioning (e.g., anxiety, depression, self-esteem, happiness), (2) the determinants of physical activity and health-related fitness including demographic, medical, social cognitive, and environmental variables, (3) the mediators of any observed associations between physical activity, health-related fitness, and health outcomes including biological, functional, and psychosocial, and (4) the moderators of any observed associations including demographic, medical, and biological/disease factors. Taken together, these data will provide a comprehensive inquiry into the outcomes, determinants, mechanisms, and moderators of physical activity and health-related fitness in breast cancer survivors.
To profile participants based on reported outdoor physical activity barriers using a data-driven approach, describe the profiles and study their association with unmet physical activity need.
Cross-sectional analyses of 848 community-dwelling men and women aged 75-90 living in Central Finland in 2012. Barriers to outdoor physical activity and unmet physical activity need were enquired with a questionnaire. The latent profiles were identified by profiling participants into latent groups using a mixture modeling technique on the multivariate set of indicators of outdoor physical activity barriers. A path model was used to study the associations of the profiles with unmet physical activity need.
Five barrier profiles were identified. Profile A was characterized with minor barriers, profile B with weather barriers, profile C with health and weather barriers, profile D with barriers concerning insecurity, health and weather; and profile E with mobility and health barriers. The participants in the profiles differed in the proportion of individual and environmental barriers. The risk for unmet physical activity need was highest among people whose severe mobility difficulties restricted their outdoor physical activity.
Outdoor physical activity barriers reflect the imbalance in person-environment fit among older people, manifested as unmet physical activity need.
We examined the relationship between physical activity parenting (PAP) and child, family, and environmental factors in families. The participants were 840 families with young children (n = 993; 5.40 ± 1.14 years) and parents (n = 993; 35.8 ± 5.29 years). Parents' self-reported PAP (co-participation, (in)direct support, and encouragement), child-specific (sex, age, temperament, outdoor time, organized physical activity or sports, sedentary time, media time, PA enjoyment, motor skills compared to peers, PA, and sport facility use), family-specific (respondent's sex, age, education, exercise frequency, family income, family status, number of children in the family, child's birth order and partner's PAP, and exercise frequency), and environment-specific (residential density, access to sport and outdoor facilities, type of house, and access to electronic devices) factors were collected. Children's motor skills and anthropometrics were measured. After adjusting for the family cluster effect, child, family, and environmental factors were entered into a linear mixed-effects model, with PAP as the response variable. The final model consisted of statistically significant factors, and parental education, which was forced into the model. Nine child- and family-related factors explained 15% of parenting variance between the children and 52% between the families. Partner's PAP (B = 0.68, P
Knowledge of adult activity patterns across domains of physical activity is essential for the planning of population-based strategies that will increase overall energy expenditure and reduce the risk of obesity and related chronic diseases. We describe domain-specific hours of activity and energy expended among participants in a prospective cohort in Alberta, Canada.
The Past Year Total Physical Activity Questionnaire was completed by 15,591 Tomorrow Project® participants, between 2001 and 2005 detailing physical activity type, duration, frequency and intensity. Domain-specific hours of activity and activity-related energy expenditure, expressed as a percent of total energy expenditure (TEE) (Mean (SD); Median (IQR)) are reported across inactive (
Cites: J Am Diet Assoc. 2002 Nov;102(11):1621-3012449285
Cites: Can J Appl Physiol. 2002 Dec;27(6):681-9012501004
The aim was to study objectively assessed walkability of the environment and participant perceived environmental facilitators for outdoor mobility as predictors of physical activity in older adults with and without physical limitations. 75-90-year-old adults living independently in Central Finland were interviewed (n = 839) and reassessed for self-reported physical activity one or two years later (n = 787). Lower-extremity physical limitations were defined as Short Physical Performance Battery score =9. Number of perceived environmental facilitators was calculated from a 16-item checklist. Walkability index (land use mix, street connectivity, population density) of the home environment was calculated from geographic information and categorized into tertiles. Accelerometer-based step counts were registered for one week (n = 174). Better walkability was associated with higher numbers of perceived environmental facilitators (p
Cites: Am J Phys Med Rehabil. 2014 Oct;93(10):876-8324800719
Cites: J Aging Res. 2012;2012:62575822162808
Cites: Scand J Med Sci Sports. 2015 Aug;25(4):e368-7326152855
Cites: Int J Health Geogr. 2014 Mar 04;13:724588848
We investigated child, family, and environmental factors associated with young children's perceptions of locomotor (LM) and object control (OC) skills. The participants comprised 472 children (6.22 ± 0.63) and their parents. The children were assessed for their perception of motor competence in LM and OC skills (using the pictorial scale of Perceived Movement Skill Competence for young children), and actual motor competence (Test of Gross Motor Development 3rd edition and Körperkoordinationstest Für Kinder). Anthropometrics were calculated using the children's body mass index standard deviation scores. A parent questionnaire included questions about child factors (sex, child's independent walking age, time spent sedentary and outdoors, participation in organized sport activities, and access to electronic devices), family factors (parent educational level, physical activity frequency, and sedentary behavior), and environmental factors (access to sport facilities). Variance analysis sought to identify age-related differences, and a linear regression model examined correlates of children's perception of LM and OC skills. The children's movement skill perceptions were found to be generally high. Four factors explained 5.7% of the variance in perceptions of LM skills and 7.5% of the variance in perceptions of OC skills. Two factors, lower age and higher actual motor competence, explained most of the children's skill perceptions. Access to electronic devices (less) and Body mass index (BMI) (higher) were associated with perceptions of LM skills. Participation in organized sport activities (higher) and parental education (lower) were associated with perceptions of OC skills. When promoting children's physical activity and motor competence, perceptions of motor competence are an important consideration.