Appropriate inclusion of interactions was needed to avoid bias in multiple imputation

OBJECTIVE: Missing data are a pervasive problem, often leading to bias in complete records analysis (CRA). Multiple imputation (MI) via chained equations is one solution, but its use in the presence of interactions is not straightforward. STUDY DESIGN AND SETTING: We simulated data with outcome Y dependent on binary explanatory variables X and Z and their interaction XZ. Six scenarios were simulated (Y continuous and binary, each with no interaction, a weak and a strong interaction), under five missing data mechanisms. We use directed acyclic graphs to identify when CRA and MI would each be unbiased. We evaluate the performance of CRA, MI without interactions, MI including all interactions, and stratified imputation. We also illustrated these methods using a simple example from the National Child Development Study (NCDS). RESULTS: MI excluding interactions is invalid and resulted in biased estimates and low coverage. When XZ was zero, MI excluding interactions gave unbiased estimates but overcoverage. MI including interactions and stratified MI gave equivalent, valid inference in all cases. In the NCDS example, MI excluding interactions incorrectly concluded there was no evidence for an important interaction. CONCLUSIONS: Epidemiologists carrying out MI should ensure that their imputation model(s) are compatible with their analysis model

Empirical evidence of study design biases in randomized trials:Systematic review of meta-epidemiological studies

To synthesise evidence on the average bias and heterogeneity associated with reported methodological features of randomized trials.Systematic review of meta-epidemiological studies.We retrieved eligible studies included in a recent AHRQ-EPC review on this topic (latest search September 2012), and searched Ovid MEDLINE and Ovid EMBASE for studies indexed from Jan 2012-May 2015. Data were extracted by one author and verified by another. We combined estimates of average bias (e.g. ratio of odds ratios (ROR) or difference in standardised mean differences (dSMD)) in meta-analyses using the random-effects model. Analyses were stratified by type of outcome ("mortality" versus "other objective" versus "subjective"). Direction of effect was standardised so that ROR < 1 and dSMD < 0 denotes a larger intervention effect estimate in trials with an inadequate or unclear (versus adequate) characteristic.We included 24 studies. The available evidence suggests that intervention effect estimates may be exaggerated in trials with inadequate/unclear (versus adequate) sequence generation (ROR 0.93, 95% CI 0.86 to 0.99; 7 studies) and allocation concealment (ROR 0.90, 95% CI 0.84 to 0.97; 7 studies). For these characteristics, the average bias appeared to be larger in trials of subjective outcomes compared with other objective outcomes. Also, intervention effects for subjective outcomes appear to be exaggerated in trials with lack of/unclear blinding of participants (versus blinding) (dSMD -0.37, 95% CI -0.77 to 0.04; 2 studies), lack of/unclear blinding of outcome assessors (ROR 0.64, 95% CI 0.43 to 0.96; 1 study) and lack of/unclear double blinding (ROR 0.77, 95% CI 0.61 to 0.93; 1 study). The influence of other characteristics (e.g. unblinded trial personnel, attrition) is unclear.Certain characteristics of randomized trials may exaggerate intervention effect estimates. The average bias appears to be greatest in trials of subjective outcomes. More research on several characteristics, particularly attrition and selective reporting, is needed

Childhood wheezing phenotypes influence asthma, lung function and exhaled nitric oxide fraction in adolescence

The objective of this study was to examine the associations of childhood wheezing phenotypes with asthma, lung function and exhaled nitric oxide fraction (FeNO) in adolescence.In a population-based, prospective cohort study of 6841 children, we used latent class analysis to identify wheezing phenotypes during the first 7 years of life. Physician-diagnosed asthma, spirometry and FeNO were assessed at 14–15 years.Compared with never/infrequent wheeze, intermediate-onset and persistent wheeze were consistently strongest associated with higher risk of asthma (risk ratio (95% CI) 10.9 (8.97–13.16) and 9.13 (7.74–10.77), respectively), lower forced expiratory volume in 1 s (FEV1)/forced vital capacity (FVC) ratio (mean difference in standard deviation units (SDU) (95% CI) −0.34 (−0.54– −0.14) and −0.50 (−0.62– −0.38), respectively), lower forced expiratory flow at 25–75% of FVC (FEF25–75%) (mean difference in SDU (95% CI) −0.30 (−0.49– −0.10) and −0.42 (−0.54– −0.30), respectively) and increased FEV1 bronchodilator reversibility (mean difference in SDU (95% CI) 0.12 (0.02–0.22) and 0.13 (0.06–0.19), respectively). Prolonged early and persistent wheeze were associated with a decline in FEV1/FVC ratio and FEF25–75% between 8–9 and 14–15 years. Intermediate-onset, late-onset and persistent wheeze were associated with higher FeNO ratios (ratio of geometric means (95% CI) 1.90 (1.59–2.29), 1.57 (1.39–1.77) and 1.37 (1.22–1.53), respectively, compared with never/infrequent wheeze).Early-onset wheezing phenotypes persisting after 18 months of age show the strongest associations with asthma, lower lung function, even worsening from mid-childhood, and higher FeNO levels in adolescence.</jats:p

An evaluation of a multi-component adult weight management on referral intervention in a community setting

BACKGROUND: National Institute for Health and Care Excellence (NICE) guidance on adult weight management recommends interventions are multi-component. We aimed to assess the implementation and health benefits of a primary care referral to an adult multi-component weight management intervention in a community setting. The intervention was offered through Primary care in National Health Service (NHS) South Gloucestershire, UK, from Oct 2008 to Nov 2010, in partnership with statutory, community and commercial providers. The scheme offered 12 weeks’ community based concurrent support of dietary (Weight Watchers, WW), physical activity (Exercise on Prescription, EOP) and behavioural change (motivational interviewing) components to obese adults. Funding was available for 600 places. RESULTS: Five hundred and fifty nine participants engaged with the intervention, mean age 48 years, 88 % female. Mean weight loss for all engagers was 3.7 kg (95 % confidence interval 3.4, 4.1). Participants completing the intervention achieved the largest weight reduction (mean loss 5.9 kg; 5.3, 6.6). Achievement of 5 % weight loss was higher in completers (58 %; 50, 65) compared to non-completers (19 %; 12, 26) and people who only participated in one commercial component of the intervention (either WW or EOP; 19 %; 13, 24). CONCLUSION: A multi-component weight management programme may be beneficial for weight loss, but a randomized controlled trial is needed to establish effectiveness and to evaluate cost