The effects of smoking-related television advertising on smoking and intentions to quit among adults in the United States: 1999-2007.

OBJECTIVES: We investigated whether state-sponsored antitobacco advertisements are associated with reduced adult smoking, and interactions between smoking-related advertising types. METHODS: We measured mean exposure to smoking-related advertisements with television ratings for the top-75 US media markets from 1999 to 2007. We combined these data with individual-level Current Population Surveys Tobacco Use Supplement data and state tobacco control policy data. RESULTS: Higher exposure to state-sponsored, Legacy, and pharmaceutical advertisements was associated with less smoking; higher exposure to tobacco industry advertisements was associated with more smoking. Higher exposure to state- and Legacy-sponsored advertisements was positively associated with intentions to quit and having made a past-year quit attempt; higher exposure to ads for pharmaceutical cessation aids was negatively associated with having made a quit attempt. There was a significant negative interaction between state- and Legacy-sponsored advertisements. CONCLUSIONS: Exposure to state-sponsored advertisements was far below Centers for Disease Control and Prevention-recommended best practices. The significant negative relationships between antismoking advertising and adult smoking provide strong evidence that tobacco-control media campaigns help reduce adult smoking. The significant negative interaction between state- and Legacy-sponsored advertising suggests that the campaigns reinforce one another.

Safety-focused medication therapy management: a randomized controlled trial.

OBJECTIVE: To evaluate the effect of a medication therapy management (MTM) intervention on adverse drug events (ADEs), health care visits, and drug-related problems (DRPs). DESIGN: Randomized, controlled, clinical trial. SETTING: Academic medical center community pharmacies and family medicine clinics at three U.S. sites between December 2007 and January 2010 PATIENTS: Individuals aged 65 years or older with three or more chronic illnesses, six or more prescription medications, and at risk for a DRP. INTERVENTION: At 0 and 3 months, pharmacists conducted comprehensive medication reviews and screened for and resolved DRPs through patient education and recommendations to physicians. MAIN OUTCOME MEASURES: Frequency of ADEs reported by patients and confirmed by clinical algorithm, health care visits at 3 and 6 months, and number of DRPs, pharmacist recommendations, and medication discrepancies. RESULTS: 637 participants enrolled. No differences were observed in potential ADEs or health care visits among the usual care and MTM groups. DRPs declined in both MTM intervention groups over time. Physicians responded to 54.6% of pharmacist recommendations. Enhanced MTM patients had fewer medication list discrepancies than basic MTM patients (33.8% vs. 47.1%, P < 0.001). CONCLUSION: This specific design of MTM was associated with reduced DRPs but did not reduce potential ADEs or health care visits.

Assessing oral cancer early detection: clarifying dentists' practices.

OBJECTIVE: This study explores new methods for assessing in greater detail what dentists do when they perform oral cancer early detection examinations. It clarifies practice behaviors and opens opportunities to identify factors that facilitate thorough early detection examinations by clinicians and to assess the relative effectiveness of different examination procedures. METHODS: A 38-item survey instrument was e-mailed to dentists in a western US, multistate dental practice group. Questionnaires were received by 241 dentists, and 102 responded. An Oral Cancer Knowledge scale (0 to 14) was generated from correct responses on oral cancer general knowledge. An Oral Cancer Examination Thoroughness scale was calculated from the two dimensions of reported usage and frequency of procedures in oral cancer examinations. RESULTS: Nearly all responding dentists were in general practice (90%), with a median year of graduation from dental school of 1994. The Oral Cancer Knowledge scores ranged from 5 to 14 with a mean of 10.4. The mean Thoroughness of Examination score was 11.34 (range 0 to 20). The two scales were not statistically correlated (r = -0.015, P = 0.883). Statistically, recency of continuing education was significantly associated with knowledge (P = 0.0284) and appears to be marginally associated with thoroughness (P = 0.075). CONCLUSIONS: This study documents considerable variability in dentists' knowledge and thoroughness of examinations. The scales provide tools for future studies for improving understanding of early detection of oral cancer in clinical practice.

The ratio of oleic-to-stearic acid in the prostate predicts biochemical failure after radical prostatectomy for localized prostate cancer.

PURPOSE: To identify lifestyle related factors that may influence the prognosis of clinically localized prostate cancer we evaluated the relative impact of obesity and prostatic fatty acid concentrations at diagnosis on the risk of biochemical failure following radical prostatectomy. MATERIALS AND METHODS: Height and weight were measured in 195 men scheduled for radical prostatectomy for clinically localized prostate cancer. Fatty acids were measured in nonmalignant prostate tissue collected at surgery. Biochemical failure was defined as detectable serum prostate specific antigen (0.1 ng/ml or greater). Cox proportional hazards models and logistic regression, respectively, were used to analyze the association of obesity (body mass index 30 kg/m2 or greater) and prostatic fatty acid concentrations with time to biochemical failure and the relative odds of biochemical failure at different time points after accounting for prostate specific antigen at diagnosis, surgical margin status, pathological stage, Gleason sum, patient age, race/ethnicity and other factors. RESULTS: During an average followup of 56 months the oleic-to-stearic acid ratio predicted the risk of biochemical failure (multivariate HR 1.50, 95% CI 1.17-1.91, p = 0.001 per 1 standard deviation increase). Obesity did not correlate with biochemical failure during the entire study period. However, obesity tended to be associated with biochemical failure within the first 2 years (multivariate OR 2.55, 95% CI 0.84-7.77, p = 0.10). CONCLUSIONS: The oleic-to-stearic acid ratio in the prostate predicts the risk of biochemical failure following radical prostatectomy for clinically localized prostate cancer. This observation and the tendency of obesity to be associated with biochemical failure during the first 2 years in our cohort suggest that lifestyle related factors influence the prognosis of clinically early stage prostate cancer.

Influence of age and production type on liver copper concentrations in calves.

A retrospective study of necropsy reports was undertaken to assess the relation between liver copper concentration and age, sex, and production class for calves that did not have a history compatible with copper toxicosis or with copper deficiency. Results of a generalized least squares regression analysis of 601 records found that copper concentration was as much as 60 mg/kg wet weight higher for dairy calves than for beef calves (P < 0.00001, R2 = 0.172). For both beef and dairy calves, copper concentration also was significantly associated with linear (P = 0.001) and nonlinear (age2, P = 0.002; age3, P = 0.008) functions of age, where the concentration increased for the first 2 months, then declined until 9 months of age, after which it began to increase. Sex was not associated with copper concentration (P = 0.22). The 95% confidence intervals of the mean concentration for a group of calves and the 95% prediction intervals of a single concentration value for an individual animal are presented. As a consequence of the significant influence of both production class (dairy or beef) and age on liver copper concentration of calves with no evidence of copper toxicosis or copper deficiency, diagnosis of copper imbalances based on liver copper concentration in calves should consider the diagnostic covariates of age and production class.

Influence of age, sex, and production class on liver zinc concentration in calves.

Determination of zinc concentrations in the liver of calves and young stock is commonly requested by practitioners and nutritionists to assess whether they receive an appropriate amount of zinc in their diet. However, interpretation of liver zinc concentrations is currently based on information reported for adult cattle for which the health status was unknown and irrespective of production class, sex, and age. A retrospective study of necropsy reports was undertaken to assess the relationships between liver zinc concentrations and age, sex, and production class for calves that did not have a history compatible with zinc toxicosis or zinc deficiency. Results of a generalized least squares, polynomial regression analysis of 474 records found that zinc concentration was not affected by sex (P = 0.29) or production class (P = 0.50). Zinc concentration was significantly associated with linear (P < 0.00001) and nonlinear (quadratic, P = 0.0039) functions of age (r2 = 0.1503), where the concentration decreased from 93 mg/kg wet weight at 30 days of age to 57 mg/kg wet weight at 9 months of age, after which it began to increase. The age-specific 95% confidence limits of the mean concentration for a group of calves and the 95% prediction limits of a single concentration value for an individual animal estimated in this study suggest reconsideration of the recommended limits for liver zinc concentration in calves. As a consequence of the significant influence of age on liver zinc concentration of calves presumably not experiencing zinc toxicosis or deficiency, diagnosis of zinc imbalances based on liver zinc concentration needs to consider age as a diagnostic covariate.

Correlates of self-care in low-income African American and Latino patients with diabetes.

OBJECTIVE: This study aimed to examine diabetes self-care (DSC) patterns in low-income African American and Latino patients with Type 2 diabetes, and identify patient-related, biomedical/disease-related, and psychosocial correlates of DSC. METHOD: We performed cross-sectional analysis of survey data from African Americans and Latinos aged ≥18 years with Type 2 diabetes (n = 250) participating in a diabetes self-management intervention at 4 primary care clinics. The Summary of Diabetes Self-Care Activities captured the subcomponents of healthy eating, physical activity, blood sugar testing, foot care, and smoking. Correlates included patient-related attributes, biomedical/disease-related factors, and psychosocial constructs, with their multivariable influence assessed with a 3-step model building procedure using regression techniques. RESULTS: Baseline characteristics were as follows: mean age of 53 years (SD = 12.4); 69% female; 53% African American; 74% with incomes below $20,000; and 60% with less than a high school education. DSC performance levels were highest for foot care (4.5/7 days) and lowest for physical activity (2.5/7 days). Across racial/ethnic subgroups, diabetes-related distress was the strongest correlate for DSC when measured as a composite score. Psychosocial factors accounted for 14% to 33% of variance in self-care areas for both racial/ethnic groups. Patient characteristics were more salient correlates in Hispanic/Latinos when examining the self-care subscales, particularly those requiring monetary resources. CONCLUSIONS: Important information is provided on specific DSC patterns in a sample of ethnic/racial minorities with Type 2 diabetes. Significant correlates found may help with identification and intervention of patients who may benefit from strategies to increase self-care adherence.

Logistic Regression with Multiple Random Effects: A Simulation Study of Estimation Methods and Statistical Packages.

Several statistical packages are capable of estimating generalized linear mixed models and these packages provide one or more of three estimation methods: penalized quasi-likelihood, Laplace, and Gauss-Hermite. Many studies have investigated these methods' performance for the mixed-effects logistic regression model. However, the authors focused on models with one or two random effects and assumed a simple covariance structure between them, which may not be realistic. When there are multiple correlated random effects in a model, the computation becomes intensive, and often an algorithm fails to converge. Moreover, in our analysis of smoking status and exposure to anti-tobacco advertisements, we have observed that when a model included multiple random effects, parameter estimates varied considerably from one statistical package to another even when using the same estimation method. This article presents a comprehensive review of the advantages and disadvantages of each estimation method. In addition, we compare the performances of the three methods across statistical packages via simulation, which involves two- and three-level logistic regression models with at least three correlated random effects. We apply our findings to a real dataset. Our results suggest that two packages-SAS GLIMMIX Laplace and SuperMix Gaussian quadrature-perform well in terms of accuracy, precision, convergence rates, and computing speed. We also discuss the strengths and weaknesses of the two packages in regard to sample sizes.

Spiritual and religious beliefs and practices and social support's relationship to diabetes self-care activities in African Americans.

PURPOSE: The purpose of this study is to investigate the relationship among spiritual and religious beliefs and practices, social support, and diabetes self-care activities in African Americans with type 2 diabetes, hypothesizing that there would be a positive association. METHOD: This cohort study used a cross-sectional design that focused on baseline data from a larger randomized control trial. Diabetes self-care activities (summary of diabetes self-care activities) and sociodemographic characteristics were assessed, in addition to spiritual and religious beliefs and practices and social support based on the systems of belief inventory subscales I (beliefs and practices) and II (social support). RESULTS: There were 132 participants: most were women, middle-aged, obese, single, high school educated, and not employed. Based on Pearson correlation matrices, there were significant relationships between spiritual and religious beliefs and practices and general diet. Additional significant relationships were found for social support with general diet, specific diet, and foot care. Based on multiple linear regression, social support was a significant predictor for general diet, specific diet, and foot care. Sex was a significant predictor for specific diet, and income was a significant predictor for blood glucose testing. CONCLUSIONS: The findings of this study highlight the importance of spiritual and religious beliefs and practices and social support in diabetes self-care activities. Future research should focus on determining how providers integrate patients' beliefs and practices and social support into clinical practice and include those in behavior change interventions.

Identification of and intervention to address therapeutic gaps in care.

OBJECTIVES: To determine if therapeutic gap identification, notification of community pharmacists, and intervention results in increased gap closure, reduced gap closure time, and fewer adherence gaps reopening. STUDY DESIGN: Prospective, controlled, clusterrandomized study. METHODS: State of Illinois employees and beneficiaries of State health plans filling prescriptions at independently owned community pharmacies were included. For selected chronic conditions and medications, gaps in medication adherence and omitted essential therapies were identified from prescription claims and sent as alerts for resolution with the patient and/or physician. Adherence and omission gap closure at 90 days were analyzed with Kaplan-Meier (KM) survival curve approach and Cox proportional hazards models including covariates. RESULTS: A total of 1433 intervention and 1181 control adherence gaps were identified, while 677 intervention and 534 control omission gaps were generated. Pharmacists intervened on 639 (44.6%) adherence and 506 (74.7%) omission gaps. Gaps were closed more often in intervention than control at 30 days (55.5% in intervention vs 50.6% in control), 45 days (61.1% vs 58.4%, respectively), 60 days (66.1% vs 65.2%, respectively), and 90 days (73.0% vs 72.9%, respectively; adjusted hazard ratio [HR] = 1.242; P = .022; 95% confidence interval [CI] 1.115-1.385). Adherence gaps reopened less frequently in the intervention group (HR = 0.863; P = .012; 95% CI 0.769-0.968). A total of 89 (13.1%) intervention and 29 (5.4%) control omission gaps closed within 90 days (adjusted HR = 1.770; P = .005; 95% CI 1.182-2.653). CONCLUSIONS: Independent community pharmacists reduced gaps in care and had fewer reopened adherence gaps, suggesting improvement in adherence. A continuation study will examine the impact of the program on long-term adherence.

Community-based translation of the diabetes prevention program's lifestyle intervention in an underserved Latino population.

PURPOSE: The objective was to take prevention from the clinic to the community by including a high-risk group and working with the community to tailor, enhance, deliver, and evaluate a community-based version of the Diabetes Prevention Program's (DPP) clinic-based lifestyle intervention. METHODS: This was a nonrandomized prospective study using a single-group design. Study eligibility included a screening glucose value in the normal to prediabetes range with no current diagnosis of diabetes, overweight, not pregnant nor planning to become pregnant during study period, aged 18 to 65, Latino, living in the study target communities, and no reported medical restrictions related to the program goals. A total of 69 individuals participated. The Healthy Living Program (HLP) was based on the DPP's 1-year intensive lifestyle program, was tailored and enhanced for a Latino community, and was delivered by community health workers. Anthropometric and paper and pencil measures were administered to examine program outcome at 6 months and 12 months. RESULTS: In general, results indicate statistically significant improvements in anthropometrics and many behavioral outcomes, particularly at 6 months. Participants demonstrated forward movement through the stages of change during the program. CONCLUSIONS: Results support the effectiveness of the intervention and show that delivery of the translated version of the DPP's lifestyle intervention in the community by community residents holds promise as one strategy to reach people at increased risk of developing diabetes. Use of this translation model, including collaboration with community health workers, offers diabetes educators an opportunity to extend their reach into underserved communities.

Diagnosis using predictive probabilities without cut-offs.

Standard diagnostic test procedures involve dichotomization of serologic test results. The critical value or cut-off is determined to optimize a trade off between sensitivity and specificity of the resulting test. When sampled units from a population are tested, they are allocated as either infected or not according to the test outcome. Units with values high above the cut-off are treated the same as units with values just barely above the cut-off, and similarly for values below the cut-off. There is an inherent information loss in dichotomization. We thus develop a diagnostic screening method based on data that are not dichotomized within the Bayesian paradigm. Our method determines the predictive probability of infection for each individual in a sample based on having observed a specific serologic test result and provides inferences about the prevalence of infection in the population sampled. Our fully Bayesian method is briefly compared with a previously developed frequentist method. We illustrate the methodology with serologic data that have been previously analysed in the veterinary literature, and also discuss applications to screening for disease in humans. The method applies more generally to a variation of the classic parametric 2-population discriminant analysis problem. Here, in addition to training data, additional units are sampled and the goal is to determine their population status, and the prevalence(s) of the subpopulation(s) from which they were sampled.