Is Your Neighborhood Designed to Support Physical Activity? A Brief Streetscape Audit Tool.

INTRODUCTION:Macro level built environment factors (eg, street connectivity, walkability) are correlated with physical activity. Less studied but more modifiable microscale elements of the environment (eg, crosswalks) may also affect physical activity, but short audit measures of microscale elements are needed to promote wider use. This study evaluated the relation of a 15-item neighborhood environment audit tool with a full version of the tool to assess neighborhood design on physical activity in 4 age groups. METHODS:From the 120-item Microscale Audit of Pedestrian Streetscapes (MAPS) measure of street design, sidewalks, and street crossings, we developed the 15-item version (MAPS-Mini) on the basis of associations with physical activity and attribute modifiability. As a sample of a likely walking route, MAPS-Mini was conducted on a 0.25-mile route from participant residences toward the nearest nonresidential destination for children (n = 758), adolescents (n = 897), younger adults (n = 1,655), and older adults (n = 367). Active transportation and leisure physical activity were measured with age-appropriate surveys, and accelerometers provided objective physical activity measures. Mixed-model regressions were conducted for each MAPS item and a total environment score, adjusted for demographics, participant clustering, and macrolevel walkability. RESULTS:Total scores of MAPS-Mini and the 120-item MAPS correlated at r = .85. Total microscale environment scores were significantly related to active transportation in all age groups. Items related to active transport in 3 age groups were presence of sidewalks, curb cuts, street lights, benches, and buffer between street and sidewalk. The total score was related to leisure physical activity and accelerometer measures only in children. CONCLUSION:The MAPS-Mini environment measure is short enough to be practical for use by community groups and planning agencies and is a valid substitute for the full version that is 8 times longer

Development of the State Optimism Measure

Background Optimism, or positive expectations about the future, is associated with better health. It is commonly assessed as a trait, but it may change over time and circumstance. Accordingly, we developed a measure of state optimism. Methods An initial 29-item pool was generated based on literature reviews and expert consultations. It was administered to three samples: sample 1 was a general healthy population (n = 136), sample 2 was people with cardiac disease (n = 96), and sample 3 was persons recovering from problematic substance use (n = 265). Exploratory factor analysis and item-level descriptive statistics were used to select items to form a unidimensional State Optimism Measure (SOM). Confirmatory factor analysis (CFA) was performed to test fit. Results The selected seven SOM items demonstrated acceptable to high factor loadings on a single dominant factor (loadings: 0.64–0.93). There was high internal reliability across samples (Cronbach\u27s alphas: 0.92–0.96), and strong convergent validity correlations in hypothesized directions. The SOM\u27s correlations with other optimism measures indicate preliminary construct validity. CFA statistics indicated acceptable fit of the SOM model. Conclusions We developed a psychometrically-sound measure of state optimism that can be used in various settings. Predictive and criterion validity will be tested in future studies

Association of objective sedentary behaviour and self-rated health in English older adults

Abstract Objective Reducing sedentary behaviour (SB) might improve the health of older adults. However, we know little about how objectively measured SB impacts on self-rated health in older adults. We aimed to explore the associations between objectively measured SB and self-rated health in English older adults. Results A random sub-sample of older adults (≥ 65 years old) from the 2008 Health Survey for England wore an ActiGraph GT1M accelerometer for 7 days. Self-rated health was measured using an item from the General Health Questionnaire. Linear regression and analysis of covariance were used to test the associations between percentage time spent in SB and mean daily minutes in SB and self-rated health (very good/good; fair; bad/very bad), adjusting for covariates. Valid accelerometry datasets were returned by 578 individuals. Significant negative associations between percentage time and mean daily minutes in SB and self-rated health were found. In particular, individuals spending reduced percentages of time being sedentary had higher self-rated health. In conclusion, SB appears to be associated with self-rated health in older people independently from MVPA. If longitudinal research could determine how changes in SB influence self-rated health as individuals’ age, this might be an important lifestyle variable to target for health improvement

Measuring Outcomes in Adult Weight Loss Studies That Include Diet and Physical Activity: A Systematic Review

Background. Measuring success of obesity interventions is critical. Several methods measure weight loss outcomes but there is no consensus on best practices. This systematic review evaluates relevant outcomes (weight loss, BMI, % body fat, and fat mass) to determine which might be the best indicator(s) of success. Methods. Eligible articles described adult weight loss interventions that included diet and physical activity and a measure of weight or BMI change and body composition change. Results. 28 full-text articles met inclusion criteria. Subjects, settings, intervention lengths, and intensities varied. All studies measured body weight (−2.9 to −17.3 kg), 9 studies measured BMI (−1.1 to −5.1 kg/m2), 20 studies measured % body fat (−0.7 to −10.2%), and 22 studies measured fat mass (−0.9 to −14.9 kg). All studies found agreement between weight or BMI and body fat mass or body fat % decreases, though there were discrepancies in degree of significance between measures. Conclusions. Nearly all weight or BMI and body composition measures agreed. Since body fat is the most metabolically harmful tissue type, it may be a more meaningful measure of health change. Future studies should consider primarily measuring % body fat, rather than or in addition to weight or BMI

Youth advocacy for obesity prevention: The next wave of social change for health

Recommended obesity prevention interventions target multiple levels. Effective advocacy is needed to influence factors at individual, social, environmental, and policy levels. This paper describes the rationale for engaging youth in obesity prevention advocacy efforts targeting environment and policy changes to improve nutrition and physical activity. Advocacy involves education, skill development, and behavior and attitude changes, with the goal of persuading others or taking action. Youth advocacy has been successfully used in substance use prevention, but it is relatively new in obesity prevention. A model is presented to guide intervention and evaluation in youth advocacy for obesity prevention. With youth advocacy as a central construct, the model outlines inputs and outcomes of advocacy at individual, social environment, built environment, and policy levels. The model can be used and refined in youth advocacy evaluation projects. By involving youth in their communities, advocacy can produce ownership, engagement, and future involvement yielding sustainable changes

Community design for physical activity

[Extract] This chapter summarizes the research linking built environments to physical activity. It is concerned mainly with total physical activity, which is strongly related to health outcomes

Biodiversity, the Human Microbiome and Mental Health: Moving toward a New Clinical Ecology for the 21st Century?

Advances in research concerning the brain-related influences of the microbiome have been paradigm shifting, although at an early stage, clinical research involving beneficial microbes lends credence to the notion that the microbiome may be an important target in supporting mental health (defined here along the continuum between quality of life and the criteria for specific disorders). Through metagenomics, proteomics, metabolomics, and systems biology, a new emphasis to personalized medicine is on the horizon. Humans can now be viewed as multispecies organisms operating within an ecological theatre; it is important that clinicians increasingly see their patients in this context. Historically marginalized ecological aspects of health are destined to become an important consideration in the new frontiers of practicing medicine with the microbiome in mind. Emerging evidence indicates that macrobiodiversity in the external environment can influence mental well-being. Local biodiversity may also drive differences in human-associated microbiota; microbial diversity as a product of external biodiversity may have far-reaching effects on immune function and mood. With a focus on the microbiome as it pertains to mental health, we define environmental “grey space” and emphasize a new frontier involving bio-eco-psychological medicine. Within this concept the ecological terrain can link dysbiotic lifestyles and biodiversity on the grand scale to the local human-associated microbial ecosystems that might otherwise seem far removed from one another.Peer Reviewe