Decomposition analysis of the compositional and contextual factors associated with poor-non-poor inequality in diarrhoea among under-five children in low- and middle-income countries.

OBJECTIVES: The aim of the study was to assess the magnitude of wealth inequalities in the development of diarrhoea among under-five children in low- and middle-income countries (LMICs) and to identify and quantify contextual and compositional factors' contribution to the inequalities. DESIGN: This is a cross-sectional study. METHODS: We used cross-sectional data from 57 Demographic and Health Surveys conducted between 2010 and 2018 in LMICs. Descriptive statistics were used to understand the gap in having diarrhoea between the children from poor and non-poor households and across the selected covariates using Fairlie decomposition techniques with multivariable binary logistic regressions at P = 0.05. RESULTS: Of the 57 countries, we found a statistically significant pro-poor odds ratio in only 29 countries, 7 countries showed pro-non-poor inequality and others showed no statistically significant inequality. Among the countries with statistically significant pro-poor inequality, the risk difference was largest in Cameroon (94.61/1000), whereas the largest pro-non-poor risk difference in diarrhoea was widest in Timor-Leste (-41.80/1000). Important factors responsible for pro-poor inequality varied across countries. The largest contributors to the pro-poor inequalities in having diarrhoea are maternal education, access to media, neighbourhood socio-economic status, place of residence, birth order and maternal age. CONCLUSION: Diarrhoea remains a major challenge in most LMICs, with a wide range of pro-poor inequalities. These disparities were explained by both compositional and contextual factors, which varied widely across the countries. Thus, multifaceted geographically specific economic alleviation intervention may prove to be a potent approach for addressing the poor and non-poor differentials in the risk of diarrhoea with policies tailored to country-specific risk factors. There is a need for further investigation of factors that drive pro-non-poor inequalities found in 9 of the LMICs.

Implementing core NICE guidelines for osteoarthritis in primary care with a model consultation (MOSAICS): a cluster randomised controlled trial.

OBJECTIVE: To determine the effectiveness of a model osteoarthritis consultation, compared with usual care, on physical function and uptake of National Institute for Health and Care Excellence (NICE) osteoarthritis recommendations, in adults ≥45 years consulting with peripheral joint pain in UK general practice. METHOD: Two-arm cluster-randomised controlled trial with baseline health survey. Eight general practices in England. PARTICIPANTS: 525 adults ≥45 years consulting for peripheral joint pain, amongst 28,443 population survey recipients. Four intervention practices delivered the model osteoarthritis consultation to patients consulting with peripheral joint pain; four control practices continued usual care. The primary clinical outcome of the trial was the SF-12 physical component score (PCS) at 6 months; the main secondary outcome was uptake of NICE core recommendations by 6 months, measured by osteoarthritis quality indicators. A Linear Mixed Model was used to analyse clinical outcome data (SF-12 PCS). Differences in quality indicator outcomes were assessed using logistic regression. RESULTS: 525 eligible participants were enrolled (mean age 67.3 years, SD 10.5; 59.6% female): 288 from intervention and 237 from control practices. There were no statistically significant differences in SF-12 PCS: mean difference at the 6-month primary endpoint was -0.37 (95% CI -2.32, 1.57). Uptake of core NICE recommendations by 6 months was statistically significantly higher in the intervention arm compared with control: e.g., increased written exercise information, 20.5% (7.9, 28.3). CONCLUSION: Whilst uptake of core NICE recommendations was increased, there was no evidence of benefit of this intervention, as delivered in this pragmatic randomised trial, on the primary outcome of physical functioning at 6 months. TRIAL REGISTRATION: ISRCTN06984617.

Does a modified STarT Back Tool predict outcome with a broader group of musculoskeletal patients than back pain? A secondary analysis of cohort data.

OBJECTIVES: The STarT Back Tool has good predictive performance for non-specific low back pain in primary care. We therefore aimed to investigate whether a modified STarT Back Tool predicted outcome with a broader group of musculoskeletal patients, and assessed the consequences of using existing risk-group cut-points across different pain regions. SETTING: Secondary analysis of prospective data from 2 cohorts: (1) outpatient musculoskeletal physiotherapy services (PhysioDirect trial n=1887) and (2) musculoskeletal primary-secondary care interface services (SAMBA study n=1082). PARTICIPANTS: Patients with back, neck, upper limb, lower limb or multisite pain with a completed modified STarT Back Tool (baseline) and 6-month physical health outcome (Short Form 36 (SF-36)). OUTCOMES: Area under the receiving operator curve (AUCs) tested discriminative abilities of the tool's baseline score for identifying poor 6-month outcome (SF-36 lower tertile Physical Component Score). Risk-group cut-points were tested using sensitivity and specificity for identifying poor outcome using (1) Youden's J statistic and (2) a clinically determined rule that specificity should not fall below 0.7 (false-positive rate <30%). RESULTS: In PhysioDirect and SAMBA, poor 6-month physical health was 18.5% and 28.2%, respectively. Modified STarT Back Tool score AUCs for predicting outcome in back pain were 0.72 and 0.79, neck 0.82 and 0.88, upper limb 0.79 and 0.86, lower limb 0.77 and 0.83, and multisite pain 0.83 and 0.82 in PhysioDirect and SAMBA, respectively. Differences between pain region AUCs were non-significant. Optimal cut-points to discriminate low-risk and medium-risk/high-risk groups depended on pain region and clinical services. CONCLUSIONS: A modified STarT Back Tool similarly predicts 6-month physical health outcome across 5 musculoskeletal pain regions. However, the use of consistent risk-group cut-points was not possible and resulted in poor sensitivity (too many with long-term disability being missed) or specificity (too many with good outcome inaccurately classified as 'at risk') for some pain regions. The draft tool is now being refined and validated within a new programme of research for a broader musculoskeletal population. TRIAL REGISTRATION NUMBER: ISRCTN55666618; Post results.