Computing travel time when the exact address is unknown: a comparison of point and polygon ZIP code approximation methods

<p>Abstract</p> <p>Background</p> <p>Travel time is an important metric of geographic access to health care. We compared strategies of estimating travel times when only subject ZIP code data were available.</p> <p>Results</p> <p>Using simulated data from New Hampshire and Arizona, we estimated travel times to nearest cancer centers by using: 1) geometric centroid of ZIP code polygons as origins, 2) population centroids as origin, 3) service area rings around each cancer center, assigning subjects to rings by assuming they are evenly distributed within their ZIP code, 4) service area rings around each center, assuming the subjects follow the population distribution within the ZIP code. We used travel times based on street addresses as true values to validate estimates. Population-based methods have smaller errors than geometry-based methods. Within categories (geometry or population), centroid and service area methods have similar errors. Errors are smaller in urban areas than in rural areas.</p> <p>Conclusion</p> <p>Population-based methods are superior to the geometry-based methods, with the population centroid method appearing to be the best choice for estimating travel time. Estimates in rural areas are less reliable.</p

Density estimation and adaptive bandwidths: A primer for public health practitioners

<p>Abstract</p> <p>Background</p> <p>Geographic information systems have advanced the ability to both visualize and analyze point data. While point-based maps can be aggregated to differing areal units and examined at varying resolutions, two problems arise 1) the modifiable areal unit problem and 2) any corresponding data must be available both at the scale of analysis and in the same geographic units. Kernel density estimation (KDE) produces a smooth, continuous surface where each location in the study area is assigned a density value irrespective of arbitrary administrative boundaries. We review KDE, and introduce the technique of utilizing an adaptive bandwidth to address the underlying heterogeneous population distributions common in public health research.</p> <p>Results</p> <p>The density of occurrences should not be interpreted without knowledge of the underlying population distribution. When the effect of the background population is successfully accounted for, differences in point patterns in similar population areas are more discernible; it is generally these variations that are of most interest. A static bandwidth KDE does not distinguish the spatial extents of interesting areas, nor does it expose patterns above and beyond those due to geographic variations in the density of the underlying population. An adaptive bandwidth method uses background population data to calculate a kernel of varying size for each individual case. This limits the influence of a single case to a small spatial extent where the population density is high as the bandwidth is small. If the primary concern is distance, a static bandwidth is preferable because it may be better to define the "neighborhood" or exposure risk based on distance. If the primary concern is differences in exposure across the population, a bandwidth adapting to the population is preferred.</p> <p>Conclusions</p> <p>Kernel density estimation is a useful way to consider exposure at any point within a spatial frame, irrespective of administrative boundaries. Utilization of an adaptive bandwidth may be particularly useful in comparing two similarly populated areas when studying health disparities or other issues comparing populations in public health.</p

A Comparison of Individual Versus Community Influences on Youth Smoking Behaviours: A Cross-Sectional Observational Study

Objectives: To compare individual with community risk factors for adolescent smoking. Design: A cross-sectional observational study with multivariate analysis.Setting: National telephone survey.Participants: 3646 US adolescents aged 13–18 years in 2007 recruited through a random digit-dial survey

Using built environment characteristics to predict walking for exercise

Background: Environments conducive to walking may help people avoid sedentary lifestyles and associated diseases. Recent studies developed walkability models combining several built environment characteristics to optimally predict walking. Developing and testing such models with the same data could lead to overestimating one's ability to predict walking in an independent sample of the population. More accurate estimates of model fit can be obtained by splitting a single study population into training and validation sets (holdout approach) or through developing and evaluating models in different populations. We used these two approaches to test whether built environment characteristics near the home predict walking for exercise. Study participants lived in western Washington State and were adult members of a health maintenance organization. The physical activity data used in this study were collected by telephone interview and were selected for their relevance to cardiovascular disease. In order to limit confounding by prior health conditions, the sample was restricted to participants in good self-reported health and without a documented history of cardiovascular disease. Results: For 1,608 participants meeting the inclusion criteria, the mean age was 64 years, 90 percent were white, 37 percent had a college degree, and 62 percent of participants reported that they walked for exercise. Single built environment characteristics, such as residential density or connectivity, did not significantly predict walking for exercise. Regression models using multiple built environment characteristics to predict walking were not successful at predicting walking for exercise in an independent population sample. In the validation set, none of the logistic models had a C-statistic confidence interval excluding the null value of 0.5, and none of the linear models explained more than one percent of the variance in time spent walking for exercise. We did not detect significant differences in walking for exercise among census areas or postal codes, which were used as proxies for neighborhoods. Conclusion: None of the built environment characteristics significantly predicted walking for exercise, nor did combinations of these characteristics predict walking for exercise when tested using a holdout approach. These results reflect a lack of neighborhood-level variation in walking for exercise for the population studied.University of Washington Royalty Research fund award; by contracts R01-HL043201, R01-HL068639, and T32-HL07902 from the National Heart, Lung, and Blood Institute; and by grant R01-AG09556 from the National Institute on Aging

Healthcare Cost Differences with Participation in a Community-Based Group Physical Activity Benefit for Medicare Managed Care Health Plan Members: HEALTHCARE COST DIFFERENCES

To determine whether participation in a physical activity benefit by Medicare managed care enrollees is associated with lower healthcare utilization and costs

Impact of opioid-free analgesia on pain severity and patient satisfaction after discharge from surgery: multispecialty, prospective cohort study in 25 countries

Background: Balancing opioid stewardship and the need for adequate analgesia following discharge after surgery is challenging. This study aimed to compare the outcomes for patients discharged with opioid versus opioid-free analgesia after common surgical procedures.Methods: This international, multicentre, prospective cohort study collected data from patients undergoing common acute and elective general surgical, urological, gynaecological, and orthopaedic procedures. The primary outcomes were patient-reported time in severe pain measured on a numerical analogue scale from 0 to 100% and patient-reported satisfaction with pain relief during the first week following discharge. Data were collected by in-hospital chart review and patient telephone interview 1 week after discharge.Results: The study recruited 4273 patients from 144 centres in 25 countries; 1311 patients (30.7%) were prescribed opioid analgesia at discharge. Patients reported being in severe pain for 10 (i.q.r. 1-30)% of the first week after discharge and rated satisfaction with analgesia as 90 (i.q.r. 80-100) of 100. After adjustment for confounders, opioid analgesia on discharge was independently associated with increased pain severity (risk ratio 1.52, 95% c.i. 1.31 to 1.76; P &lt; 0.001) and re-presentation to healthcare providers owing to side-effects of medication (OR 2.38, 95% c.i. 1.36 to 4.17; P = 0.004), but not with satisfaction with analgesia (beta coefficient 0.92, 95% c.i. -1.52 to 3.36; P = 0.468) compared with opioid-free analgesia. Although opioid prescribing varied greatly between high-income and low- and middle-income countries, patient-reported outcomes did not.Conclusion: Opioid analgesia prescription on surgical discharge is associated with a higher risk of re-presentation owing to side-effects of medication and increased patient-reported pain, but not with changes in patient-reported satisfaction. Opioid-free discharge analgesia should be adopted routinely

Topical fluoroquinolones for eye and ear

Topical fluoroquinolones are now available for use in the eye and ear. Their broad spectrum of activity includes the common eye and ear pathogens Staphylococcus aureus and Pseudomonas aeruginosa. For the treatment of acute otitis externa, these agents are as effective as previously available otic preparations. For the treatment of otitis media with tympanic membrane perforation, topical fluoroquinolones are effective and safe. These preparations are approved for use in children, and lack of ototoxicity permits prolonged administration when necessary. Topical fluoroquinolones are not appropriate for the treatment of uncomplicated conjunctivitis where narrower spectrum agents suffice; they represent a simplified regimen for the treatment of bacterial keratitis (corneal ulcers). When administered topically, fluoroquinolones are well tolerated and offer convenient dosing schedules. Currently, bacterial resistance appears limited

Medical management of obesity

Obesity is one of the most common medical problems in the United States and a risk factor for illnesses such as hypertension, diabetes, degenerative arthritis and myocardial infarction. It is a cause of significant morbidity and mortality and generates great social and financial costs. Obesity is defined as a body mass index greater than 30. Many patients accomplish weight loss with diet, exercise and lifestyle modification. Others require more aggressive therapy. Weight loss medications may be appropriate for use in selected patients who meet the definition of obesity or who are overweight with comorbid conditions. Medications are formulated to reduce energy intake, increase energy output or decrease the absorption of nutrients. Drugs cannot replace diet, exercise and lifestyle modification, which remain the cornerstones of obesity treatment. Two new agents, sibutramine and orlistat, exhibit novel mechanisms of action and avoid some of the side effects that occurred with earlier drugs. Sibutramine acts to block uptake of serotonin, norepinephrine and dopamine, while orlistat decreases fat absorption in the intestines

Objective Measurement of Sociability and Activity: Mobile Sensing in the Community

PURPOSE Automated systems able to infer detailed measures of a person’s social interactions and physical activities in their natural environments could lead to better understanding of factors influencing well-being. We assessed the feasibility of a wireless mobile device in measuring sociability and physical activity in older adults, and compared results with those of traditional questionnaires