Search bioRxivSearch

bioRxiv · 10.1101/408179

Different analysis methods of Scottish and English child physical activity data explain the majority of the difference between the national prevalence estimates

Abstract

BackgroundThe percentage of children in Scotland and England meeting the aerobic physical activity recommendation differ greatly according to the estimates derived from the respective national health surveys. The Scottish Health Survey (SHeS) usually estimates that over 70% meet the guidelines; Health Survey for England (HSE) estimates are usually below 25%. It is plausible that these differences originate from different analysis methods. The HSE monitor the percentage of children that undertake 60 minutes of moderate-to-vigorous physical activity on each day of the week ( the daily minimum method (DMM)). The SHeS monitor the proportion that undertake at least seven sessions of moderate-to-vigorous physical activity, with an average daily duration over 60 minutes ( the average method (WAM)). We aimed to establish how great an influence this difference in analysis methods has on the prevalence estimates.\n\nMethodsPhysical activity data from 5-15 year olds in the 2015 HSE and SHeS were reanalysed (weighted n=3840 and 965, respectively). Two comparable pairs of estimates were derived: a DMM and WAM estimate from the HSE not including travel to/from school, and WAM estimates from the HSE and the SHeS including travel to/from school. It is not possible to calculate a DMM estimate from the SHeS due to the way the questions are asked. Results were presented for the total samples, and by sex and age sub-groups.\n\nResultsThe HSE WAM estimate was 31.7 (95% CI: 30.2-33.3) percentage points higher than the DMM estimate (54.3% (95% CI: 52.6-56.0) and 22.6% (95% CI: 21.2-24.1) respectively). The magnitude of this difference differed by age group but not sex. When comparable WAM estimates were derived from the SHeS and the HSE, the SHeS was 11.8 percentage points higher (73.6% (95% CI: 69.8-77.1) and 61.8% (95% CI: 60.2-63.5) respectively). The magnitude of this difference differed by age group and sex.\n\nConclusionsThe results indicate that the difference in the analysis method explains the majority (approximately 30 percentage points) of the difference in the child physical activity prevalence estimates between Scotland and England. These results will help those involved in national surveillance to determine how to increase comparability between the U.K. home nations.

Source connections

Explore related subjects

Keep this discovery

BibTeXRIS

Williamson, C., Kelly, P., Strain, T.. 2018-09-05. Different analysis methods of Scottish and English child physical activity data explain the majority of the difference between the national prevalence estimates. https://doi.org/10.1101/408179

Cite the original work for its findings. Save a collection to share your selection of sources.

KEEP EXPLORING

Related preprints

Translating surveillance data into incidence estimates

Monitoring a population for a disease requires the hosts to be sampled and tested for the pathogen. This results in sampling series from which to estimate the disease incidence, i.e. the proportion of hosts infected. Existing estimation methods assume that disease incidence is not changing between monitoring rounds, resulting in underestimation of the disease incidence. In this paper we develop an incidence estimation model accounting for epidemic growth with monitoring rounds sampling varying incidence. We also show how to accommodate the asymptomatic period characteristic to most diseases. For practical use, we produce an approximation of the model, which is subsequently shown accurate for relevant epidemic and sampling parameters. Both the approximation and the full model are applied to stochastic spatial simulations of epidemics. The results prove their consistency for a very wide range of situations.

epidemiology

The Swiss Primary Ciliary Dyskinesia registry: objectives, methods and first results

Primary Ciliary Dyskinesia (PCD) is a rare hereditary, multi-organ disease caused by defects in ciliary structure and function. It results in a wide range of clinical manifestations, most commonly in the upper and lower airways. Central data collection in national and international registries is essential to studying the epidemiology of rare diseases and filling in gaps in knowledge of diseases such as PCD. For this reason, the Swiss Primary Ciliary Dyskinesia Registry (CH-PCD) was founded in 2013 as a collaborative project between epidemiologists and adult and paediatric pulmonologists.\n\nThe registry records patients of any age, suffering from PCD, who are treated and resident in Switzerland. It collects information from patients identified through physicians, diagnostic facilities, and patient organisations. The registry dataset contains data on diagnostic evaluations, lung function, microbiology and imaging, symptoms, treatments, and hospitalizations.\n\nBy May 2018, CH-PCD has contacted 566 physicians of different specialties and identified 134 patients with PCD. At present this number represents an overall 1 in 63,000 prevalence of people diagnosed with PCD in Switzerland. Prevalence differs by age and region; it is highest in children and adults younger than 30 years, and in Espace Mittelland. The median age of patients in the registry is 25 years (range 5-73), and 49 patients have a definite PCD diagnosis based on recent international guidelines. Data from CH-PCD are contributed to international collaborative studies and the registry facilitates patient identification for nested studies.\n\nCH-PCD has proven to be a valuable research tool that already has highlighted weaknesses in PCD clinical practice in Switzerland. Development of centralised diagnostic and management centres and adherence to international guidelines are needed to improve diagnosis and management--particularly for adult PCD patients.

epidemiology

Perfect Counterfactuals for Epidemic Simulations

Simulation studies are often used to predict the expected impact of control measures in infectious disease outbreaks. Typically, two independent sets of simulations are conducted, one with the intervetnion, and one without, and epidemic sizes (or some related metric) are compared to estimate the effect of the intervention. Since it is possible that controlled epidemics are larger than uncontrolled ones if there is substantial stochastic variation between epidemics, uncertainty intervals from this approach can include a negative effect even for an effective intervention. To more precisely estimate the number of cases an intervention will prevent within a single epidemic, here we develop a single world approach to matching simulations of controlled epidemics to their exact uncontrolled counterfac-tual. Our method borrows concepts from percolation approaches prune out possible epidemic histories and create potential epidemic graph that can be realized to create perfectly matched controlled and uncontrolled epidemics. We present an implementation of this method for a common class of compartmental models, and its application in a simple SIR model. Results illustrate how, at the cost of some computation time, this method substantially narrows confidence intervals and avoids non-sensical inferences.

epidemiology