The purposes of this study were to use the National Health and Nutrition Examination Study (2011-12) data to determine nationally representative combined handgrip strength ranges and percentile information by sex and age group, examine trends in strength across age by sex, and to determine the relative proportion of children and adults falling into established health benefit zones (HBZ). Results indicate that mean strength was greater among men than women and increased linearly for children and in a quadratic fashion among adults for both sexes. Grip strength peaked in the 30- to 39-year age group for both men (216.4 lbs) and women (136.5 lbs) with subsequent age groups showing gradual decline, p < 0.0001. Relative and absolute increases in grip strength were greater for men than for women, but relative decrease from peak strength was less among women than men. Although absolute strength was greater among men than women, HBZ data indicated that a higher percentage of men than women overall and at each age group fell into the needs improvement zone, with differences particularly pronounced during adolescence and older adulthood. These data provide the first nationally representative population estimates of combined handgrip strength and percentile information from childhood through senescence and suggest consideration of HBZ information in conjunction with grip strength to improve surveillance data interpretation and intervention planning.

Because of the excess burden of preventable chronic diseases and premature death among African American men, identifying health behaviors to enhance longevity is needed. We used data from the Third National Health and Nutrition Examination Survey 1988-1994 (NHANES III) and the NHANES III Linked Mortality Public-use File to determine the association between health behaviors and all-cause mortality and if these behaviors varied by age in 2029 African American men. Health behaviors included smoking, drinking, physical inactivity, obesity, and a healthy eating index score. Age was categorized as 25-44 years (n = 1,045), 45-64 years (n = 544), and 65 years and older (n = 440). Cox regression analyses were used to estimate the relationship between health behaviors and mortality within each age-group. All models were adjusted for marital status, education, poverty-to-income ratio, insurance status, and number of health conditions. Being a current smoker was associated with an increased risk of mortality in the 25- to 44-year age-group, whereas being physically inactive was associated with an increased risk of mortality in the 45- to 64-year age-group. For the 65 years and older age-group, being overweight or obese was associated with decreased mortality risk. Efforts to improve longevity should focus on developing age-tailored health promoting strategies and interventions aimed at smoking cessation and increasing physical activity in young and middle-aged African American men.

Purpose: To assess the public’s trust in health information sources (ie, government health agencies, doctors, family/friends, charitable organizations, and religious leaders/organizations) from 2005 to 2015 and identify sociodemographics factors associated with high trust. Design: Cross-sectional. Setting: Health Information National Trends Survey, a US nationally representative publicly available data on health-related knowledge, behaviors, and attitudes. Participants: Data included 5 iterations (2005-2015) of US adults (2005: N = 5586, 2008: N = 7764, 2011: N = 3959, 2013: N = 3185, and 2015: N = 3738). Measures: Outcome variables were high trust in health information sources and independent variables were sociodemographics. Analysis: A descriptive analysis was conducted to track changes in trust over the past decade. The χ2 and multivariable logistic regression were conducted to assess sociodemographic associations in 2015. Results: Trust in health information across all sources remained stable from 2005 to 2015. Doctors were the most trusted source, followed by government health agencies. Sociodemographics were independently associated with trust. For example, non-Hispanic blacks were more likely to trust charitable organizations (odds ratio [OR] = 2.32, confidence interval [CI] = 1.42-3.79) and religious leaders/organizations (OR = 3.57, CI = 1.20-10.57) compared to non-Hispanic whites. In addition, those with less than high school education (OR = 2.44, CI = 1.32-4.52) were more likely than college graduates to report trust in religious leaders/organizations. Conclusion: Although there are analytic limitations to the specific time periods, the findings demonstrate that public health communication practitioners must consider the role of source credibility among priority populations when disseminating and promoting information.

BackgroundMore than half of all smartphone app downloads involve weight, diet, and exercise. If successful, these lifestyle apps may have far-reaching effects for disease prevention and health cost-savings, but few researchers have analyzed data from these apps.ObjectiveThe purposes of this study were to analyze data from a commercial health app (Lose It!) in order to identify successful weight loss subgroups via exploratory analyses and to verify the stability of the results.MethodsCross-sectional, de-identified data from Lose It! were analyzed. This dataset (n=12,427,196) was randomly split into 24 subsamples, and this study used 3 subsamples (combined n=972,687). Classification and regression tree methods were used to explore groupings of weight loss with one subsample, with descriptive analyses to examine other group characteristics. Data mining validation methods were conducted with 2 additional subsamples.ResultsIn subsample 1, 14.96% of users lost 5% or more of their starting body weight. Classification and regression tree analysis identified 3 distinct subgroups: “the occasional users” had the lowest proportion (4.87%) of individuals who successfully lost weight; “the basic users” had 37.61% weight loss success; and “the power users” achieved the highest percentage of weight loss success at 72.70%. Behavioral factors delineated the subgroups, though app-related behavioral characteristics further distinguished them. Results were replicated in further analyses with separate subsamples.ConclusionsThis study demonstrates that distinct subgroups can be identified in “messy” commercial app data and the identified subgroups can be replicated in independent samples. Behavioral factors and use of custom app features characterized the subgroups. Targeting and tailoring information to particular subgroups could enhance weight loss success. Future studies should replicate data mining analyses to increase methodology rigor.

Patients undergoing cancer treatment experience a multitude of symptoms that can influence their ability to complete treatment as well as their quality of life during and after treatment. This cross-sectional study sought to describe the dietary changes experienced by cancer patients and to identify associations between these changes and common treatment symptoms. A convenience sample of 1199 cancer patients aged 18 yr and older undergoing active treatment were recruited from 7 cancer centers to complete a selfadministered paper-and-pencil survey. Descriptive analyses were conducted to estimate prevalence of dietary changes and chi-squared tests were used to examine associations between dietary changes and health outcomes. Approximately 40% of patients reported a decreased appetite since beginning treatment, and 67.2% of patients reported at least 1 chemosensory alteration. Increased taste sensitivities were more common than decreased taste sensitivities, with increased sensitivity to metallic being the most common taste sensitivity (18.6%). Patients also had increased sensitivities to certain smells including cleaning solutions (23.4%), perfume (22.4%), and food cooking (11.4%). Patients reported a wide range of

The use of mobile health applications (apps) especially in the area of lifestyle behaviors has increased, thus providing unprecedented opportunities to develop health programs that can engage people in real-time and in the real-world. Yet, relatively little is known about which factors relate to the engagement of commercially available apps for health behaviors. This exploratory study examined behavioral engagement with a weight loss app, Lose It! and characterized higher versus lower engaged groups. Cross-sectional, anonymized data from Lose It! were analyzed (n = 12,427,196). This dataset was randomly split into 24 subsamples and three were used for this study (total n = 1,011,008). Classification and regression tree methods were used to identify subgroups of user engagement with one subsample, and descriptive analyses were conducted to examine other group characteristics associated with engagement. Data mining validation methods were conducted with two separate subsamples. On average, users engaged with the app for 29 days. Six unique subgroups were identified, and engagement for each subgroup varied, ranging from 3.5 to 172 days. Highly engaged subgroups were primarily distinguished by the customization of diet and exercise. Those less engaged were distinguished by weigh-ins and the customization of diet. Results were replicated in further analyses. Commercially-developed apps can reach large segments of the population, and data from these apps can provide insights into important app features that may aid in user engagement. Getting users to engage with a mobile health app is critical to the success of apps and interventions that are focused on health behavior change.

Findings from this study illuminate the need to more deeply understand reasons for subscriber non-response and opt out and, in turn, improve program engagement and our ability to increase the likelihood for participants to stop smoking and measure long-term outcomes. Patterns of opt out for the program mirror the relapse curve generally observed for smoking cessation, thus highlighting time points at which to increase efforts to retain participants and provide additional support or incentives.

Although understanding race differences in health behaviors among men is an important step in reducing disparities in leading causes of death in the United States, progress has been stifled when using national data because of the confounding of race, socioeconomic status (SES), and residential segregation. The purpose of this study is to examine the nature of disparities in health behaviors among African American and White men in the Exploring Health Disparities in Integrated Communities Study-Southwest Baltimore (EHDIC-SWB) which was conducted in a racially a racially-integrated neighborhood of Baltimore to data from the 2003 National Health Interview Survey (NHIS). After adjusting for age, marital status, insurance, income, educational attainment, poor or fair health, and obesity status, African American men in NHIS had greater odds of being physically inactive (odds ratio [OR] =1.48, 95% confidence interval [CI] 129, 1.69), reduced odds of being a current smoker (OR= 0.77, 95% CI 0.65, 0.90), and reduced odds of being a current drinker (OR= 0.58, 95% CI 0.50, 0.67). In the EHDIC-SWB sample, African American and white men had similar odds of being physically inactive (OR = 0.79, 95% CI 0.50, 1.24), being a current smoker (OR = 0.86, 95% CI 0.60, 1.23), or being a current drinker (OR = 1.34, 95% CI 0.81, 2.21). Because race disparities in these health behaviors were ameliorated in the sample where African American and white men were living under similar social, environmental and SES conditions, these findings suggest that social environment may be an important determinant of health behaviors among African American and White men. Public health interventions and health promotion strategies should consider the social environment when seeking to better understand men’s health disparities.