Associations Between Body Fat, Muscle Mass, and Nonalcoholic Fatty Liver Disease: A Population-Based Study.

Nonalcoholic fatty liver disease (NAFLD) is one of the most common forms of liver disease worldwide and has emerged as a significant public health concern in China. A better understanding of the etiology of NAFLD can inform effective management strategies for this disease. We examined factors associated with NAFLD in two districts of Hangzhou, China, focusing on the relationship of regional body fat distribution, muscle mass, and NAFLD. We used baseline data to carry out a cross-sectional analysis among 3,589 participants from the Wellness Living Laboratory (WELL) China study, a longitudinal population-based study that aims to investigate and promote well-being among the Chinese population. NAFLD was defined using the widely validated fatty liver index (FLI). Multivariate logistic regressions were performed to assess independent associations between NAFLD and metabolic risk factors (e.g., insulin resistance) and dual x-ray absorptiometry (DXA)-derived measures (e.g., android fat ratio [AFR] and skeletal muscle index [SMI]). Of the 3,589 participants, 476 (13.3%) were classified as having FLI-defined NAFLD (FLI ≥60). Among those, 58.0% were men. According to our analysis, AFR (odds ratio [OR], 10.0; 95% confidence interval [CI], 5.8-18.5), insulin resistance (OR, 4.0; 95% CI, 3.0-5.3), high alanine aminotransferase levels (OR, 7.6; 95% CI, 5.8-10.0), smoking (OR, 2.0; 95% CI, 1.4-3.0), and male sex (OR, 2.9; 95% CI, 2.0-4.2) were positively associated with NAFLD risk, while SMI (OR, 0.1; 95% CI, 0.07-0.13) was inversely associated with NAFLD risk. Conclusion: In addition to known metabolic risk factors, DXA-derived AFR and SMI may provide additional insights to the understanding of NAFLD. Interventions that aim to decrease AFR and increase SMI may be important to reduce the burden of NAFLD in this population.

Understanding Where We Are Well: Neighborhood-Level Social and Environmental Correlates of Well-Being in the Stanford Well for Life Study.

Individual well-being is a complex concept that varies among and between individuals and is impacted by individual, interpersonal, community, organizational, policy and environmental factors. This research explored associations between select environmental characteristics measured at the ZIP code level and individual well-being. Participants (n = 3288, mean age = 41.4 years, 71.0% female, 57.9% white) were drawn from a registry of individuals who completed the Stanford WELL for Life Scale (SWLS), a 76-question online survey that asks about 10 domains of well-being: social connectedness, lifestyle and daily practices, physical health, stress and resilience, emotional and mental health, purpose and meaning, sense of self, financial security and satisfaction, spirituality and religiosity, and exploration and creativity. Based on a nationally-representative 2018 study of associations between an independent well-being measure and county-level characteristics, we selected twelve identical or analogous neighborhood (ZIP-code level) indicators to test against the SWLS measure and its ten constituent domains. Data were collected from secondary sources to describe socio-economic (median household income, percent unemployment, percent child poverty), demographic (race/ethnicity), and physical environment (commute by bicycle and public transit), and healthcare (number of healthcare facilities, percent mammogram screenings, percent preventable hospital stays). All continuous neighborhood factors were re-classified into quantile groups. Linear mixed models were fit to assess relationships between each neighborhood measure and each of the ten domains of well-being, as well as the overall SWLS well-being measure, and were adjusted for spatial autocorrelation and individual-level covariates. In models exploring associations between the overall SWLS score and neighborhood characteristics, six of the twelve neighborhood factors exhibited significant differences between quantile groups (p < 0.05). All of the ten SWLS domains had at least one instance of significant (p < 0.05) variation across quantile groups for a neighborhood factor; stress and resilience, emotional and mental health, and financial security had the greatest number of significant associations (6/12 factors), followed by physical health (5/12 factors) and social connectedness (4/12 factors). All but one of the neighborhood factors (number of Federally Qualified Health Centers) showed at least one significant association with a well-being domain. Among the neighborhood factors with the most associations with well-being domains were rate of preventable hospital stays (7/10 domains), percent holding bachelor's degrees (6/10 domains), and median income and percent with less than high school completion (5/10 domains). These observational insights suggest that neighborhood factors are associated with individuals' overall self-rated well-being, though variation exists among its constituent domains. Further research that employs such multi-dimensional measures of well-being is needed to determine targets for intervention at the neighborhood level that may improve well-being at both the individual and, ultimately, neighborhood levels.

Risk profile of coronary heart disease among the staff members of Qassim University, Saudi Arabia.

OBJECTIVE: To estimate the risk profile of coronary heart disease (CHD) among the staff members of Qassim University and assess their knowledge in a screening campaign in Qassim region, Saudi Arabia. METHODS: A cross-sectional study was conducted among male and female staff at Qassim University campus. All employees of Qassim University were invited to participate in the study. Data were collected through a self-administered questionnaire. The study sample size was 233 staff and employees. The data were entered and analyzed using SPSS version 18. The data analysis focused on providing point estimates for the risk factors. RESULTS: The study found that 30% of participants have one or more risk factors for CHD, namely obesity 20.6%, diabetes 10.3%, hypertension 12.4%, dyslipidemia 10.7%, and smokers (11.6%). About 54% of the participants have a family history of at least one chronic disease as a risk factor for CHD. CONCLUSION: The most common risk factor of CHD among the staff members is obesity by 20.6%. Risk factors for CHD are quite common among Qassim University staff. These findings need to increase the health education and disease promotion program as an important intervention to reduce the occurrence and severity of CHD risk factors and to improve the quality of the life of the staff members of Qassim University.

The Use of Behavior Change Techniques and Theory in Technologies for Cardiovascular Disease Prevention and Treatment in Adults: A Comprehensive Review.

This review examined the use of health behavior change techniques and theory in technology-enabled interventions targeting risk factors and indicators for cardiovascular disease (CVD) prevention and treatment. Articles targeting physical activity, weight loss, smoking cessation and management of hypertension, lipids and blood glucose were sourced from PubMed (November 2010-2015) and coded for use of 1) technology, 2) health behavior change techniques (using the CALO-RE taxonomy), and 3) health behavior theories. Of the 984 articles reviewed, 304 were relevant (240=intervention, 64=review). Twenty-two different technologies were used (M=1.45, SD=+/-0.719). The most frequently used behavior change techniques were self-monitoring and feedback on performance (M=5.4, SD=+/-2.9). Half (52%) of the intervention studies named a theory/model - most frequently Social Cognitive Theory, the Trans-theoretical Model, and the Theory of Planned Behavior/Reasoned Action. To optimize technology-enabled interventions targeting CVD risk factors, integrated behavior change theories that incorporate a variety of evidence-based health behavior change techniques are needed.

Rural Food and Physical Activity Assessment Using an Electronic Tablet-Based Application, New York, 2013-2014.

INTRODUCTION: A community's built environment can influence health behaviors. Rural populations experience significant health disparities, yet built environment studies in these settings are limited. We used an electronic tablet-based community assessment tool to conduct built environment audits in rural settings. The primary objective of this qualitative study was to evaluate the usefulness of the tool in identifying barriers and facilitators to healthy eating and active living. The second objective was to understand resident perspectives on community features and opportunities for improvement. METHODS: Participants were recruited from 4 rural communities in New York State. Using the tool, participants completed 2 audits, which consisted of taking pictures and recording audio narratives about community features perceived as assets or barriers to healthy eating and active living. Follow-up focus groups explored the audit experience, data captured, and opportunities for change. RESULTS: Twenty-four adults (mean age, 69.4 y (standard deviation, 13.2 y), 6 per community, participated in the study. The most frequently captured features related to active living were related to roads, sidewalks, and walkable destinations. Restaurants, nontraditional food stores, and supermarkets were identified in the food environment in relation to the cost, quality, and selection of healthy foods available. In general, participants found the assessment tool to be simple and enjoyable to use. CONCLUSION: An electronic tablet-based tool can be used to assess rural food and physical activity environments and may be useful in identifying and prioritizing resident-led change initiatives. This resident-led assessment approach may also be helpful for informing and evaluating rural community-based interventions.

Neighborhood Eating and Activity Advocacy Teams (NEAAT): engaging older adults in policy activities to improve food and physical environments.

Local food and physical activity environments are known to impact health, and older adults are generally more vulnerable to health-related environmental impacts due to poorer physical function and mobility impairments. There is a need to develop cost-conscious, community-focused strategies that impact local food and physical activity environment policies. Engaging older adult community residents in assessment and advocacy activities is one avenue to address this need. We describe the Neighborhood Eating and Activity Advocacy Team project, a community-based participatory project in low-income communal housing settings in San Mateo County, CA, as one method for engaging older adults in food and physical activity environment and policy change. Methods and strategies used by the "community action teams" to generate relevant neighborhood environmental data, build coalitions, prioritize complex issues, and advocate for change are presented. Advocacy groups are feasible among older adults to improve food and physical activity environments.