Using family-based experiential learning to improve nutrition knowledge, dietary intake, physical activity, and food purchasing behaviors among Northern Virginia Latina WIC participants and their children: A pilot study

Objective: To examine the impact of a family-based nutrition education program on nutrition knowledge, diet, physical activity, and food purchasing behaviors of Latina mothers and children participating in Northern Virginia Women, Infant, Children (WIC) programs. Methods: Surveys were administered to mothers (n=15) using a pre-test/post-test design. The family-based nutrition intervention included 1) Discussion and lecture on food labels, food purchasing, portion sizes, and healthy meals, 2) Experiential learning focused on preparation and storage of low-cost, healthy meals incorporating WIC foods, and 3) A Zumba class and discussion on physical activity. Results: The data revealed improved diet such that mothers reported increased fruit and vegetable consumption, decreased juice consumption among their children. Mothers reported their children were more physically active. Further, mothers prepared more meals at home using raw ingredients. Conclusions: The findings are significant in that they support growing literature of the success of family based interventions. Further, these data show the importance of integrating experiential learning activities such as cooking and physical activity with the more traditional didactic methods. This research was supported the Virginia Department of Health and the HRSA funded Virginia Commonwealth Public Health Training Center

Drug Adverse Event Detection in Health Plan Data Using the Gamma Poisson Shrinker and Comparison to the Tree-based Scan Statistic

Background: Drug adverse event (AE) signal detection using the Gamma Poisson Shrinker (GPS) is commonly applied in spontaneous reporting. AE signal detection using large observational health plan databases can expand medication safety surveillance. Methods: Using data from nine health plans, we conducted a pilot study to evaluate the implementation and findings of the GPS approach for two antifungal drugs, terbinafine and itraconazole, and two diabetes drugs, pioglitazone and rosiglitazone. We evaluated 1676 diagnosis codes grouped into 183 different clinical concepts and four levels of granularity. Several signaling thresholds were assessed. GPS results were compared to findings from a companion study using the identical analytic dataset but an alternative statistical method—the tree-based scan statistic (TreeScan). Results: We identified 71 statistical signals across two signaling thresholds and two methods, including closely-related signals of overlapping diagnosis definitions. Initial review found that most signals represented known adverse drug reactions or confounding. About 31% of signals met the highest signaling threshold. Conclusions: The GPS method was successfully applied to observational health plan data in a distributed data environment as a drug safety data mining method. There was substantial concordance between the GPS and TreeScan approaches. Key method implementation decisions relate to defining exposures and outcomes and informed choice of signaling thresholds

Examining sociodemographic correlates of opioid use, misuse, and use disorders in the All of Us Research Program

BACKGROUND: The All of Us Research Program enrolls diverse US participants which provide a unique opportunity to better understand the problem of opioid use. This study aims to estimate the prevalence of opioid use and its association with sociodemographic characteristics from survey data and electronic health record (EHR). METHODS: A total of 214,206 participants were included in this study who competed survey modules and shared EHR data. Adjusted logistic regressions were used to explore the associations between sociodemographic characteristics and opioid use. RESULTS: The lifetime prevalence of street opioids was 4%, and the nonmedical use of prescription opioids was 9%. Men had higher odds of lifetime opioid use (aOR: 1.4 to 3.1) but reduced odds of current nonmedical use of prescription opioids (aOR: 0.6). Participants from other racial and ethnic groups were at reduced odds of lifetime use (aOR: 0.2 to 0.9) but increased odds of current use (aOR: 1.9 to 9.9) compared with non-Hispanic White participants. Foreign-born participants were at reduced risks of opioid use and diagnosed with opioid use disorders (OUD) compared with US-born participants (aOR: 0.36 to 0.67). Men, Younger, White, and US-born participants are more likely to have OUD. CONCLUSIONS: All of Us research data can be used as an indicator of national trends for monitoring the prevalence of receiving prescription opioids, diagnosis of OUD, and non-medical use of opioids in the US. The program employs a longitudinal design for routinely collecting health-related data including EHR data, that will contribute to the literature by providing important clinical information related to opioids over time. Additionally, this data will enhance the estimates of the prevalence of OUD among diverse populations, including groups that are underrepresented in the national survey data

Self-Care Instruments to Measure Nutrition Practices in Children and Parents: Psychometric Analysis

The purposes of this study were to evaluate the psychometric properties of English and Spanish instruments that measure the nutrition behavior and practices of children and their parents. Orem’s self-care deficit nursing theory was used in this methodological study. A convenience sample of 333 children and 262 mothers participated from two schools in Washington, D.C. and two schools in Santiago, Chile. Principal component analysis indicated three component per instrument corresponding to Orem’s Theory of operations demonstrating construct validity of the instrument. The study findings showed evidence for validity and reliability of the English and Spanish versions and indicated that the instruments appropriately represented Orem’s operations. The results have implications for the development of health behavior measurement instruments that are valid, reliable, designed for children, culturally appropriate, and efficient. Measuring the nutrition behavior of children and parents is critical for determining the effectiveness of nutrition intervention programs. Furthermore, instruments are needed so that researchers can compare corresponding child and parent behaviors or compare behaviors across cultures

Gender-Based Determinants of Obesity among Thai Adolescent Boys and Girls

Understanding the determinants that influence obesity among children and adolescents is critical to the prevention of obesity and obesity-related diseases later in life. The findings presented here broaden the understanding of obesity-related challenges by adding analyses that compare nutritional indicators among boys and girls between the ages of 11 and 16 years, by exploring the more recent literature to examine if past trends have continued or not, and by synthesizing the recent findings concerning the causes and determinants of such trends in obesity. Both data from 2005 and the more recent literature review have shown that the consumption of high calorie foods and snacks, greater screen time, body image, and depressive factors play a significant role regarding obesity during adolescence in Thailand. There continues to be a trend of increasing obesity among adolescents in Thailand, and this may be more of a concern in boys. Interviews with health professionals and parents from the 2005 study suggested that girls were more aware of their physical appearance, and there was more societal acceptance to be obese as a boy in Thailand compared to girls. These findings can inform nutritional education practices and policies

Drug safety data mining with a tree-based scan statistic

PURPOSE: In post-marketing drug safety surveillance, data mining can potentially detect rare but serious adverse events. Assessing an entire collection of drug-event pairs is traditionally performed on a predefined level of granularity. It is unknown a priori whether a drug causes a very specific or a set of related adverse events, such as mitral valve disorders, all valve disorders, or different types of heart disease. This methodological paper evaluates the tree-based scan statistic data mining method to enhance drug safety surveillance. METHODS: We use a three-million-member electronic health records database from the HMO Research Network. Using the tree-based scan statistic, we assess the safety of selected antifungal and diabetes drugs, simultaneously evaluating overlapping diagnosis groups at different granularity levels, adjusting for multiple testing. Expected and observed adverse event counts were adjusted for age, sex, and health plan, producing a log likelihood ratio test statistic. RESULTS: Out of 732 evaluated disease groupings, 24 were statistically significant, divided among 10 non-overlapping disease categories. Five of the 10 signals are known adverse effects, four are likely due to confounding by indication, while one may warrant further investigation. CONCLUSION: The tree-based scan statistic can be successfully applied as a data mining tool in drug safety surveillance using observational data. The total number of statistical signals was modest and does not imply a causal relationship. Rather, data mining results should be used to generate candidate drug-event pairs for rigorous epidemiological studies to evaluate the individual and comparative safety profiles of drugs. Copyright (c) 2013 John Wiley and Sons, Ltd