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Objective To characterize food group purchases from grocery receipts. Methods Food shoppers (aged [greater than or equal to] 19 years with at least one child aged [less than or equal to] 18 years in the home, the family's primary food purchaser) were recruited in front of grocery stores to participate in two interviews, separated by 6 weeks, and to save and mail grocery store receipts from the interim to researchers. Receipt items were coded by food categories; the percentage of total grocery dollars spent in each of the food categories each week was computed. Analyses of variance were performed on the total grocery dollar spent and the percentage spent in each food category by participant characteristics. Results The greatest percentage of purchases were for protein foods (24%), followed by drinks (12%), grains (9.2%), vegetables (8.8%), dairy (8.3%), mixed dishes (7.5%), and fruit (7%). Hispanics purchased a greater percentage of fruit and vegetables than African Americans. Whites purchased more alcohol products than African Americans. Whites purchased more mixed dishes than Hispanics, and African Americans purchased more protein foods than whites (all P<0.001). Conclusions The use of this measurement procedure, unaffected by errors of self-report, should be more thoroughly explored to explain differences in disease prevalence.

Objective: To assess the psychometric characteristics of new scales of shopping practices and social support for purchasing fruits and vegetables. Design: Participants were recruited in front of diverse grocery stores. Telephone data collection was done on 2 occasions, separated by 6 weeks. Participants: 166 food shoppers with children at home participated. Main Outcome Measures: New scales of food shopping practices and social support for purchasing fruits and vegetables were psychometrically analyzed and related to a measure of home fruit or vegetable availability as a test of construct validity. Analysis: Both classical test and item response theory procedures were used. Correlations related the new measures to home fruit and vegetable availability. Results: Single dimension scales were specified for fruit and vegetable shopping practices (35% of the variance), fruit purchase social support (53% of the variance), and vegetable purchase social support (52% of the variance). Item response theory difficulty estimates varied from -0.64 to 0.73 for fruit and vegetable shopping practices, from -0.55 to 0.33 for fruit purchase social support, and from -0.55 to 0.34 for vegetable social support. Each scale significantly correlated with home fruit and vegetable availability (construct validity), even after controlling for social desirability of response (0.19 for shopping practices, 0.37 for fruit purchasing social support, and 0.28 for vegetable purchasing social support). Person separation reliability was 0.80 for food shopping practices, 0.74 for fruit purchasing social support, and 0.73 for vegetable purchasing social support. Conclusion: The scales performed well. Implications for Research and Practice: These scales are now available to help better understand fruit and vegetable shopping practices, fruit purchase social support, and vegetable purchase social support. Key Words: food shopping, social support, fruits, vegetables, validation, scales

In this comment we react to the paper by John R. Schroeter, entitled 'Competition and Value-of-Service Pricing in the Residential Real Estate Brokerage Market, which was published in the Spang, [...]

Background: For patients with suspected acute coronary syndrome, international guidelines indicate that an Electrocardiogram (ECG) should be performed within 10 min of first medical contact, however success at achieving these guidelines is limited. Aims: The purpose of this study was to develop and perform initial testing of a clinical prediction rule embedded in a tablet application, and to expedite the identification of patients who require an electrocardiogram within 10 min. Methods: This derivation of the Acute Coronary Syndrome Application (AcSAP) comprised of three local studies, an unpublished audit and literature critique. The AcSAP was prospectively tested over four months in patients presenting to the Emergency Department (ED) of a Dublin teaching hospital. An audit form retrieved data pertaining to times of: registration to the emergency department, triage, first electrocardiogram and diagnosis. The AcSAP was subsequently evaluated by experienced triage nurses (n=18) who had utilised it. Results: The AcSAP was activated 379 times. Patients with ST Elevation Myocardial Infarction (STEMI) and non-ST Elevation Myocardial Infarction (NSTEMI) were significantly more likely to return a categorisation of 'immediate ECG' or 'ECG within 10 min' (p<0.001). There was a significant difference in 'triage to ECG' times across categories, the 'immediate ECG' categorisation resulting in the shortest time (p=0.002). Evaluations suggest that staff found the tool quick and easy to use and results seemed accurate. Conclusion: Testing of the AcSAP suggests that it accurately identifies patients who require an ECG within 10 min. As such, it has the potential to support the meeting of clinical guidelines for ECG acquisition. [ABSTRACT FROM AUTHOR]

Background: Low physical activity has long been identified as a risk factor for coronary heart disease. Aims: The aim of this study was to determine the factors that influence changes in the physical activity of patients following an acute coronary syndrome event. Methods: The prospective, inferential cohort design recruited patients admitted to hospital following an acute coronary syndrome event across five research sites. Physical activity was assessed using the short form international physical activity questionnaire. Results: Data were collected at baseline and 3 months on 380 patients. The sample profile was: 21% women; body mass index 28 ± 4.6; unstable angina 36%; ST-segment elevation myocardial infarction 25%; non-ST-segment elevation myocardial infarction 39% and a mean age of 63 ± 11.8. There was a significant improvement in physical activity at 3 months (n=380, t=−3.704, P≤0.001). All regression models, baseline, 3 months and change in physical activity were significant (p≤0.001). Low physical activity was associated with: at baseline not having health insurance, older age and depression; at 3 months not having health insurance, not in employment and low baseline physical activity; and improvement in physical activity was associated with low physical activity at baseline and not being in employment. Conclusions: While physical activity improved significantly, 45% did not reach guideline recommendation levels at 3 months post-event. Physical activity change was little influenced by sociodemographic, clinical, psychological and behavioural factors, suggesting the need to look elsewhere such as behavioural change and improved processes across the care divide to improve physical activity in this at-risk population. [ABSTRACT FROM AUTHOR]