The prevalence of childhood obesity is increasing at an alarming rate. Many local governments have enacted policies to increase physical activity in schools as a way to combat childhood obesity. We ...conducted a systematic review and meta-analysis to determine the effect of school-based physical activity interventions on body mass index (BMI) in children.
We searched MEDLINE, EMBASE, CINAHL and the Cochrane Central Register of Controlled Trials up to September 2008. We also hand-searched relevant journals and article reference lists. We included randomized controlled trials and controlled clinical trials that had objective data for BMI from before and after the intervention, that involved school-based physical activity interventions and that lasted for a minimum of 6 months.
Of 398 potentially relevant articles that we identified, 18 studies involving 18 141 children met the inclusion criteria. The participants were primarily elementary school children. The study duration ranged from 6 months to 3 years. In 15 of these 18 studies, there was some type of co-intervention. Meta-analysis showed that BMI did not improve with physical activity interventions (weighted mean difference -0.05 kg/m(2), 95% confidence interval -0.19 to 0.10). We found no consistent changes in other measures of body composition.
School-based physical activity interventions did not improve BMI, although they had other beneficial health effects. Current population-based policies that mandate increased physical activity in schools are unlikely to have a significant effect on the increasing prevalence of childhood obesity.
Findings from the Global Burden of Diseases, Injuries, and Risk Factors Study (GBD) have provided valuable insight into the descriptive epidemiology of diseases and injuries for many countries over ...time.1 GBD 2019 approximates incidence, prevalence, and years of life lived with disability (YLDs) for more than 350 unique diseases and injuries for 204 countries and territories from 1990 to 2019.2 Among these diseases and injuries is spinal cord injury, a debilitating neurological condition that can result in lifelong disability and costly medical care, which has become a global health priority owing to the preventability of some injuries. For the GBD 2019 spinal cord injury findings to reliably “facilitate health-care planning, especially in terms of guiding evidence-based prevention and resource allocation”,5 readers must understand the data from which the estimates were derived, including all data items outlined in the Guidelines for Accurate and Transparent Health Estimates Reporting (GATHER).7 GATHER consists of a checklist of 18 items that are essential for best practice reporting in studies that use many information sources to compute health estimates for more than one population.7 Although the GBD Spinal Cord Injuries Collaborators acknowledge that data were unavailable for 111 (54%) of 204 countries studied, data availability is not explicitly reported by country for each year. Valid self-report proxies of spinal cord injury, its severity, and its completeness are also needed; for example, self-reported spinal cord injury in population-based surveys can be confused with lower back injuries.8 With respect to increasing the volume of spinal cord injury data that are collected, greater awareness of health registries and administrative claims data sources (consisting of insurance claims and electronic health data), and their value, is needed among researchers.
Purpose
In drug safety and effectiveness studies based on secondary data, the choice of an appropriate exposure measure for a given outcome can be challenging. Different measures of exposure can ...yield different estimates of treatment effect and safety. There is a knowledge gap with respect to developing and refining measures of drug exposure, to ensure that the exposure measure addresses the study question and is suitable for statistical analysis.
Methods
We present a transparent, step‐by‐step approach to the development of drug exposure measures involving secondary data. This approach would be of interest to students and investigators with initial training in pharmacoepidemiology. We illustrate the approach using a study about Parkinson's disease.
Results
We described the exposure specifications according to the study question. Next, we refined the exposure measure by linking it to knowledge about four major concepts in drug safety and effectiveness studies: drug use patterns, duration, timing, and dose. We then used this knowledge to guide the ultimate choice of exposure measure: time‐varying, cumulative 6‐month exposure to tamsulosin (a drug used to treat prostate hyperplasia).
Conclusions
The proposed approach links exposure specifications to four major concepts in drug safety and effectiveness studies. Formulating subject‐matter knowledge about these major concepts provides an avenue to develop the rationale and specifications for the exposure measure.
ObjectivesTo describe an approach using concomitant medication log records for the construction of treatment episodes. Concomitant medication log records are routinely collected in clinical studies. ...Unlike prescription and dispensing records, concomitant medication logs collect utilisation data. Logs can provide information about drug safety and drug repurposing.DesignA prospective multicentre, multicohort observational study.SettingTwenty-one clinical sites in the USA, Europe, Israel and Australia.Participants415 subjects from the de novo cohort of the Parkinson’s Progression Markers Initiative.MethodsWe construct treatment episodes of concomitant medication use. The proposed approach treats temporal gaps as a stoppage of medication and temporal overlaps as simultaneous use or changes in dose. Log records with no temporal gaps were combined into a single treatment episode.Results5723 concomitant medication log records were used to construct 3655 treatment episodes for 65 medications. There were 405 temporal gaps representing a stoppage of medication; 985 temporal overlaps representing simultaneous regimens of the same medication and 2696 temporal overlaps representing a change in dose regimen. The median episode duration was 37 months (IQ interval: 11–73 months).ConclusionsThe proposed approach for constructing treatment episodes offers a method of estimating duration and dose of treatment from concomitant medication log records. The accompanying recommendations guide log data collection to improve their quality for drug safety and drug repurposing.
Summary
Little is known about post-acute care following hip fracture surgery. We investigated discharge destinations from surgical hospitals for nine Canadian provinces. We identified significant ...heterogeneity in discharge patterns across provinces suggesting different post-acute recovery pathways. Further work is required to determine the impact on patient outcomes and health system costs.
Introduction
To examine discharge destinations by provinces in Canada, adjusting for patient, injury, and care characteristics.
Methods
We analyzed population-based hospital discharge abstracts from a national administrative database for community-dwelling patients who underwent hip fracture surgery between 2004 and 2012 in Canada. Discharge destination was categorized as rehabilitation, home, acute care, and continuing care. Multinomial logistic regression modeling compared proportions of discharge to rehabilitation, acute care, and continuing care versus home between each province and Ontario. Adjusted risk differences and risk ratios were estimated.
Results
Of 111,952 previously community-dwelling patients aged 65 years or older, 22.5% were discharged to rehabilitation, 31.6% to home, 27.0% to acute care, and 18.2% to continuing care, with significant variation across provinces (
p
< 0.001). The proportion of discharge to rehabilitation ranged from 2.4% in British Columbia to 41.0% in Ontario while the proportion discharged home ranged from 20.3% in Prince Edward Island to 52.2% in British Columbia. The proportion of discharge to acute care ranged from 15.2% in Ontario to 58.8% in Saskatchewan while the proportion discharged to continuing care ranged from 9.3% in Manitoba and Prince Edward Island to 22.9% in New Brunswick. Adjusting for hospital type changed the direction of the provincial effect on discharge to continuing care in two provinces, but statistical significance remained consistent with the primary analysis.
Conclusions
Discharge destination from the surgical hospital after hip fracture is highly variable across nine Canadian provinces. Further work is required to determine the impact of this heterogeneity on patient outcomes and health system costs.
Background. Falls are the most common cause of injury among elderly people; half of those people fall recurrently. The objective of these simulation studies was to describe the Mean Cumulative ...Function (MCF) and to evaluate the utility of the MCF in detecting differences between groups experiencing different patterns of event intensities. Methods. We specified 250 participants per group with a maximum follow-up time of 365 days. A participant could experience 0, 1, 2, 3, or 4 falls. In the baseline experiment, Groups A and B had an average intensity of 60 and 90 days to the first fall event. These event intensities remained constant for events 2–4. Group C represents a short term “strong” initial impact of the intervention modeled for falls 1 and 2, with an average intensity of one fall per 117 days; however, the intervention wanes to “moderate” for falls 3 and 4 with an average intensity of one fall per 90 days. Group D represents a long-term “strong” impact of the intervention modeled by an average intensity of one fall per 117 days for all subsequent events. Results. The MCF was able to detect differences between groups that had varying intensities of subsequent falls. In Group A, all participants experienced at least one fall, whereas Groups B, C, and D had 4, 9, and 15 participants, respectively, who did not experience any falls. The proportion of participants who had 4 falls declined from 84% to 40% in Groups A and D, respectively. When Group A was compared to Group D, the MCF difference detected the prevention of, on average, one fall per person within 175 days. Discussion. A novel instrument for this field of clinical research—the MCF—allows investigators to compare the average number of falls per participant when the intervention reduces the intensity of subsequent falls.
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