Pragmatic trials are important for informing routine clinical practice, but current designs have shortcomings. Clare Relton and colleagues outline the new “cohort multiple randomised controlled trial” design, which could help address the problems associated with existing approaches

Summary Objectives:  To update previous systematic reviews of 12‐month prevalence of complementary and alternative medicine (CAM) use by general populations; to explore trends in CAM use by national populations; to develop and apply a brief tool for assessing methodological quality of published CAM‐use prevalence surveys. Design:  Nine databases were searched for published studies from 1998 onwards. Studies prior to 1998 were identified from two previous systematic reviews. A six‐item literature‐based tool was devised to assess robustness and interpretability of CAM‐use estimates. Results:  Fifty‐one reports from 49 surveys conducted in 15 countries met the inclusion criteria. We extracted 32 estimates of 12‐month prevalence of use of any CAM (range 9.8–76%) and 33 estimates of 12‐month prevalence of visits to CAM practitioners (range 1.8–48.7%). Quality of methodological reporting was variable; 30/51 survey reports (59%) met four or more of six quality criteria. Estimates of 12‐month prevalence of any CAM use (excluding prayer) from surveys using consistent measurement methods showed remarkable stability in Australia (49%, 52%, 52%; 1993, 2000, 2004) and USA (36%, 38%; 2002, 2007). Conclusions:  There was evidence of substantial CAM use in the 15 countries surveyed. Where national trends were discernable because of consistent measurement, there was no evidence to suggest a change in 12‐month prevalence of CAM use since the previous systematic reviews were published in 2000. Periodic surveys are important to monitor population‐level CAM use. Use of government‐sponsored health surveys may enhance robustness of population‐based prevalence estimates. Comparisons across countries could be improved by standardising approaches to data collection.

Randomized controlled trials (RCTs)-the gold standard for evaluating the effects of medical interventions-are notoriously challenging in terms of logistics, planning and costs. The cohort multiple randomized controlled trial approach is designed to facilitate randomized trials for pragmatic evaluation of (new) interventions and is a promising variation from conventional pragmatic RCTs. In this paper, we evaluate methodological challenges of conducting an RCT within a cohort. We argue that equally valid results can be obtained from trials conducted within cohorts as from pragmatic RCTs. However, whether this design is more efficient compared with conducting a pragmatic RCT depends on the amount and nature of non-compliance in the intervention arm.

It is important to account for the important heterogeneity within individuals who are obese. Interventions introduced by clinicians and policymakers should not target obese individuals as a whole but tailor strategies depending upon the subgroups that individuals belong to.

BackgroundMultimorbidity is increasingly being recognized as a serious public health concern. Research into its determinants, prevalence, and management is needed and as the risk of experiencing multiple chronic conditions increases over time, attention should be given to investigating the development of multimorbidity through prospective cohort design studies. Here we examine the baseline patterns of multimorbidity and their association with health outcomes for residents in Yorkshire, England using data from the Yorkshire Health Study.MethodsBaseline data from the Yorkshire Health Study (YHS) was collected from 27,806 patients recruited between 2010 and 2012. A two-stage sampling strategy was implemented which first involved recruiting 43 general practice surgeries and then having them consent to mailing invitations to their patients to complete postal or online questionnaires. The questionnaire collected information on chronic health conditions, demographics, health-related behaviours, healthcare and medication usage, and a range of other health related variables. Descriptive statistics (chi-square and t tests) were used to examine associations between these variables and multimorbidity.ResultsIn the YHS cohort, 10,332 participants (37.2 %) reported having at least two or more long-term health conditions (multimorbidity). Older age, BMI and deprivation were all positively associated with multimorbidity. Nearly half (45.7 %) of participants from the most deprived areas experienced multimorbidity. Based on the weighted sample, average health-related quality of life decreased with the number of health conditions reported; the mean EQ-5D score for participants with no conditions was 0.945 compared to 0.355 for participants with five or more. The mean number of medications used for those without multimorbidity was 1.81 (range 1-13, SD = 1.25) compared to 3.81 (range 1-14, SD = 2.44) for those with at least two long-term conditions and 7.47 (range 1-37, SD = 7.47) for those with 5+ conditions.ConclusionPatterns of multimorbidity within the Yorkshire Health Study support research on multimorbidity within previous observational cross-sectional studies. The YHS provides both a facility for participant recruitment to intervention trials, and a large population-based longitudinal cohort for observational research. It is planned to continue to record chronic conditions and other health related behaviours in future waves which will be useful for examining determinants and trends in chronic disease and multimorbidity.

Background: We sought to quantify the relationship between body mass index (BMI) and health-related quality (HRQoL) of life, as measured by the EQ-5D, whilst controlling for potential confounders. In addition, we hypothesised that certain long-term conditions (LTCs), for which being overweight or obese is a known risk factor, may mediate the association between BMI and HRQoL. Hence the aim of our study was to explore the association between BMI and HRQoL, first controlling for confounders and then exploring the potential impact of LTCs.

Objectives Health-related quality of life (HRQoL) measures have been increasingly used in economic evaluations for policy guidance. We investigate the impact of 11 self-reported long-standing health conditions on HRQoL using the EQ-5D in a UK sample.MethodsWe used data from 13,955 patients in the South Yorkshire Cohort study collected between 2010 and 2012 containing the EQ-5D, a preference-based measure. Ordinary least squares (OLS), Tobit and two-part regression analyses were undertaken to estimate the impact of 11 long-standing health conditions on HRQoL at the individual level.ResultsThe results varied significantly with the regression models employed. In the OLS and Tobit models, pain had the largest negative impact on HRQoL, followed by depression, osteoarthritis and anxiety/nerves, after controlling for all other conditions and sociodemographic characteristics. The magnitude of coefficients was higher in the Tobit model than in the OLS model. In the two-part model, these four long-standing health conditions were statistically significant, but the magnitude of coefficients decreased significantly compared to that in the OLS and Tobit models and was ranked from pain followed by depression, anxiety/nerves and osteoarthritis.ConclusionsPain, depression, osteoarthritis and anxiety/nerves are associated with the greatest losses of HRQoL in the UK population. The estimates presented in this article should be used to inform economic evaluations when assessing health care interventions, though improvements can be made in terms of diagnostic information and obtaining longitudinal data.

This review summarises 12-month prevalence of homeopathy use from surveys conducted in eleven countries (USA, UK, Australia, Israel, Canada, Switzerland, Norway, Germany, South Korea, Japan and Singapore). Each year a small but significant percentage of these general populations use homeopathy. This includes visits to homeopaths as well as purchase of over-the-counter homeopathic medicines.