Not all commonly reported perceived barriers to healthy eating are significantly associated with meeting the recommended F&V intake.

Background Hospital admissions for Ambulatory Care Sensitive Conditions (ACSC) are those that could potentially be prevented by timely and effective disease management within primary care. ACSC admissions are increasingly used as performance indicators. However, key questions remain about the validity of these measures. The evidence to date has been inconclusive and limited to specific conditions. The aim of this study was to test the robustness of ACSC admissions as indicators of the quality of primary care. It is the first study to examine a wide range of ACSCs using longitudinal data which enables us to control for unmeasured characteristics which differ by practice but which are constant over time. Methods Using longitudinal data at the practice level, from 907 Scottish practices for the time period 1/4/2005 to 31/32012, we explored the relationships between the quality of primary care, and hospital admissions for multiple ACSCs controlling for a wide range of covariates including characteristics of GP practices, characteristics of the practice population, hospital effects and year effects. We examined the impact of two dimensions of quality of care: clinical quality of and access to daytime general practice. Generalised Estimating Equations taking the form of Negative Binomial regression models with the practice population included as the exposure term were estimated. Results We found that higher achievement on some clinical quality measures of primary care was associated with reduced ACSC emergency admissions. We also show that access to primary care was associated with ACSC emergency admissions. However, the effects were small and inconsistent and ACSC emergency admissions were associated with several confounding factors such as deprivation, rurality and distance to the hospital. Conclusions The results suggest caution in the use of crude ACSC admission rates as a performance indicator of quality of primary care. Electronic supplementary material The online version of this article (10.1186/s12875-019-0921-z) contains supplementary material, which is available to authorized users.

The results are of policy interest as they suggest that to reduce inequalities in smoking-related diseases, interventions reducing both smoking and other unhealthy behaviours are required.

BackgroundDisease incidence and premature deaths tend to be influenced by multiple health risky behaviours, including smoking, excessive alcohol consumption and unhealthy diet. Risky behaviours tend not to be independent and may have a multiplicative effect on disease incidence and healthcare cost. Thus, understanding the interrelationship between health behaviours and their effect on health outcomes is crucial in designing behavioural intervention programmes.ObjectiveTo examine the interrelationship between health risky behaviours and associated disease outcomes amongst Scottish adults.MethodsWe use hospitalisation episode data from the Scottish Morbidity Records, (SMR), that have been administratively linked to Scottish Health Surveys (SHeS) respondents with target disease defined by relevant ICD9 and 10 codes. We apply a recursive multivariate probit model to jointly estimate the health risky behaviours and disease incidence to adequately control for unobserved heterogeneity. The model is estimated separately by gender.ResultsModelling health risk behaviours and disease incidence equations independently rather than jointly may be misleading. We find a clear socioeconomic gradient predicting health risky behaviours and the results differ by gender. Specifically, smoking appears to be a key driver of other health risky behaviours. Current smokers are more likely to be drinking above the recommended limit, physically inactive, and eating inadequate diet.ConclusionsInterventions targeting current smokers to quit could spillover to other behaviours by reducing excessive drinking, improve physical activity and adequate diet. Thus, improvements in one behaviour may increase the likelihood of adopting other healthier lifestyle behaviours.