Christopher C. Imes

The Obesity Epidemic: The USA as a Cautionary Tale for the Rest of the World

Obesity is a global epidemic and its prevalence continues to increase in many developed and developing countries. This brief review provides an update on the prevalence of obesity in the USA and globally, reviews the underlying mechanism of several comorbidities associated with obesity, and discusses the economic burden of obesity. Although the overall prevalence of obesity in the USA is not increasing, racial and ethnic minorities continue to struggle with rising obesity rates. Globally, the largest increases are being observed in the developing countries. Given the comorbidities associated with obesity and its immense economic burden, nearly every country will soon struggle with the financial and healthcare implications of the epidemic.

Family history of cardiovascular disease, perceived cardiovascular disease risk, and health-related behavior: a review of the literature.

Background:More than 82 million Americans have 1 or more forms of cardiovascular disease (CVD), accounting for 32.8% of all deaths in the United States. Although the evidence for the familial aggregation of CVD is strong, the relationship between family history (FH) of CVD, perceived risk for CVD, and health-related behavior is poorly understood. Objective:The objective of this article was to review and summarize the published research on the relationship between an FH of CVD, an individual’s perceived risk, and health-related behavior to make recommendations for clinical practice and future research. Methods:A literature search was conducted using PubMed, CINAHL Plus, and PsycINFO to identify articles that examined the relationship between an FH of CVD, perceived CVD risk, and health-promoting behaviors. A total of 263 unique articles were reviewed. A total of 238 were excluded, resulting in a total of 25 articles included in the review. Results:There was a positive relationship between a reported FH of CVD and perceived risk. However, the relationship between an FH of CVD and health-related behavior change and perceived risk and behavior change was inconsistent. Conclusions:A person’s awareness of his or her FH of CVD or his or her own risk for CVD is not a sufficient predictor of changes in his or her health-related behavior. Future studies are needed to better explain the processes by which perceived CVD risk or FH of CVD can be used to affect health-related behavior changes. It appears that both FH and perceived personal risk for CVD are necessary but not sufficient conditions to change health-related behavior in high-risk populations. Future studies should also test interventions that help individuals with an FH of CVD attribute increased personal risk to themselves for developing CVD, while providing lifestyle management options to minimize their risk.

Socio-demographic, anthropometric, and psychosocial predictors of attrition across behavioral weight-loss trials.

Preventing attrition is a major concern in behavioral weight loss intervention studies. The purpose of this analysis was to identify baseline and six-month predictors associated with participant attrition across three independent clinical trials of behavioral weight loss interventions (PREFER, SELF, and SMART) that were conducted over 10 years. Baseline measures included body mass index, Barriers to Healthy Eating, Beck Depression Inventory-II (BDI), Hunger Satiety Scale (HSS), Binge Eating Scale (BES), Medical Outcome Study Short Form (MOS SF-36 v2) and Weight Efficacy Lifestyle Questionnaire (WEL). We also examined early weight loss and attendance at group sessions during the first 6 months. Attrition was recorded at the end of the trials. Participants included 504 overweight and obese adults seeking weight loss treatment. The sample was 84.92% female and 73.61% white, with a mean (± SD) age of 47.35 ± 9.75 years. After controlling for the specific trial, for every one unit increase in BMI, the odds of attrition increased by 11%. For every year increase in education, the odds of attrition decreased by 10%. Additional predictors of attrition included previous attempts to lose 50-79 lbs, age, not possessing health insurance, and BES, BDI, and HSS scores. At 6 months, the odds of attrition increased by 10% with reduced group session attendance. There was also an interaction between percent weight change and trial (p<.001). Multivariate analysis of the three trials showed education, age, BMI, and BES scores were independently associated with attrition (ps ≤ .01). These findings may inform the development of more robust strategies for reducing attrition.

The SELF Trial: A self-efficacy based behavioral intervention trial for weight-loss maintenance

The SELF Trial examined the effect of adding individual self‐efficacy (SE) enhancement sessions to standard behavioral weight loss treatment (SBT).

Neighborhood factors and six-month weight change among overweight individuals in a weight loss intervention

The purpose of this study was to examine the neighborhood environment and the association with weight change among overweight/obese individuals in the first six months of a 12-month weight loss intervention, EMPOWER, from 2011 to 2015. Measures of the neighborhood environment included neighborhood racial composition, neighborhood income, and neighborhood food retail stores density (e.g., grocery stores). Weight was measured at baseline and 6 months and calculated as the percent weight change from baseline to 6 months. The analytic sample (N = 127) was 91% female and 81% white with a mean age of 51 (± 10.4) years. At 6 months, the mean weight loss was 8.0 kg (± 5.7), which was equivalent to 8.8% (± 6%) of baseline weight. Participants living in neighborhoods in which 25–75% of the residents identified as black had the greatest percentage of weight loss compared to those living in neighborhoods with < 25% or > 75% black residents. No other neighborhood measures were associated with weight loss. Future studies testing individual-level behavioral weight loss interventions need to consider the influence of neighborhood factors, and how neighborhood-level interventions could be enhanced with individual-level interventions that address behaviors and lifestyle changes.

Screening and evaluation tools for sleep disorders in older adults

The negative effects of impaired sleep on physical and mental well-being in older adults have recently been recognized by health care professionals. However, researchers and clinicians may be unaware of reliable and valid screening and evaluation tools for evaluating sleep disorders in older adults. The purpose of this article is to present subjective and objective instruments that measure sleep quality, excessive daytime sleepiness, obstructive sleep apnea, insomnia and restless leg syndrome that are appropriate for use in adult and older adult patients.

Sleep and other correlates of high-level health in older adults

ABSTRACT A large sample (N = 1139) of adults ≥75 years from the 2011–2014 NHANES cohorts was used to examine predictors of high‐level health. Analyses were done with SAS to control for sample weights and allow results to be reported as population parameters. The majority of participants described their health as high‐level (73.6%). Logistic regression found a longer sleep duration, minority status, decreased income, multiple medications, low physical activity, and late stage memory impairment were significant predictors of low‐level health (p < .05) while sex, education level, marital status, body mass index, and depression symptoms were not. The assessment of sleep should be expanded to cover dimensions such as sleep quality and sleep disorders to help maintain wellness in older adults. This study supports that the majority of older adults have high‐level health and identifies several modifiable factors to maintain wellness.

Trajectories of Weight Change and Predictors Over 18-Month Weight Loss Treatment

BACKGROUND Obesity research has typically focused on weight change patterns using the whole sample in randomized clinical trials (RCTs), ignoring subsets of individuals with varying weight change trajectories (e.g., continuing to lose, or maintaining weight). The purpose was to explore possible trajectories of weight change and their associated predictors. METHODS We conducted a secondary analysis of data from two RCTs using standard behavioral treatment for weight loss. Group-based trajectory modeling was used to identify distinct classes of percent weight change trajectories over 18 months. RESULTS The sample (N = 338) was primarily female (85.2%), White (73.7 %), 45.7 ± 9.0 years old, with 15.6 ± 2.8 years of education. Three trajectory groups were identified: good responders (>15% weight loss), fair responders (5%-10% weight loss), and poor responders (<5% weight loss). The good responders had a significantly larger decrease in perceived Barriers to Healthy Eating subscale scores than the fair and poor responders (p < .01). Compared to the poor responders, there was a significant decrease in fat gram intake in the good responders (p = .01). CONCLUSIONS Good responders differed from poor responders in decreasing their perceived barriers to healthy eating (e.g., managing emotions, social support, and daily mechanics of adopting a healthy diet) and reducing fat intake. Good responders differed from fair responders in perceived barriers to healthy eating. CLINICAL RELEVANCE Clinicians need to focus on how we can assist those who are being unsuccessful in adopting some of the behaviors observed among those who have experienced successful weight loss and maintainers.

Outcomes of a Pilot Intervention Study for Young Adults at Risk for Cardiovascular Disease Based on Their Family History.

Background:Lifestyle choices have a significant impact on cardiovascular disease (CVD) risk. Interventions to promote a heart-healthy lifestyle in young adults at long-term high risk for CVD are needed to decrease the burden of CVD. However, few interventions with this purpose have been developed. Objective:The objective of this study was to examine the effect of a pilot intervention on young adults with a family history of CVD that used 3-generation pedigrees, risk factor information, and counseling on heart disease knowledge, perceived CVD risk, and intention to engage in a heart-healthy lifestyle. Methods:A pretest-posttest design, with within-group analysis, was used to examine the effect of the intervention. Paired t test and Wilcoxon signed rank tests were used to examine the changes in heart disease knowledge, perceived risk, and behavioral intention from baseline to postintervention. The Cohen d was calculated to examine the effect of the intervention on study measures. In addition, Spearman &rgr; was used to examine the associations between postintervention perceived risk, postintervention behavioral intention, and family history. Results:The sample for the pilot study included 15 mostly white and mostly female healthy young adults between the ages of 18 and 25 years. The intervention was effective at increasing CVD knowledge (P = .02) and had a medium effect on perceived risk and intention to engage in a heart-healthy lifestyle (Cohen d, 0.48–0.58). There were significant associations between postintervention perceived risk and postintervention intention to exercise and the participants’ family history of coronary heart disease (r = 0.62, P = .014 and r = 0.55, P = .035, respectively). Conclusions:Interventions are needed to increase individuals’ awareness of their long-term CVD risk and to improve their ability to make lifestyle changes. Although this intervention was only tested in a small sample, it shows promise to improve heart disease knowledge and perceived lifetime CVD risk and may effect longer-term risk for CVD.

Perceived Versus Actual Risk of Type 2 Diabetes by Race and Ethnicity

Purpose The purpose of this study was to examine associations between perceived risk and actual risk of type 2 diabetes by race and/or ethnicity. Methods The study sample included 10 999 adults from the 2011 to 2014 National Health and Nutrition Examination Survey. Sociodemographic, clinical, and behavioral data were collected using interviews and physical examinations. Participants were asked if they felt at risk for diabetes or prediabetes and then asked the reasons why. Data analyses were conducted with SAS to properly analyze complex survey data. Results About 86% of the sample (n = 9496) answered the risk perception question for diabetes, and among those, 28.4% indicated having a high perceived risk. Among this subsample, 38.3% were identified as having an actual risk for prediabetes or diabetes according to the American Diabetes Association guidelines. Across all race groups, the most frequently reported risk factors participants believed to contribute to their risk for diabetes were family history of diabetes, obesity, and poor diet habits. When the percentage of participants with an actual risk factor who correctly perceived it as a risk factor was examined, fewer Asians correctly perceived weight status and physical activity level as a risk for diabetes in contrast to the other racial/ethnic groups. Conclusions Our study showed that when perception was compared to actual risks, associations differed statistically by race. It will be essential to discuss their risk perception to proper screening for diabetes and relevant lifestyle modifications to prevent and delay the onset of diabetes.