Background: As the global prevalence of allergy increases, it is clear that more individuals are presenting with complex and multiple allergies. The impact of various demographic and clinical risk factors on developing allergies has not been explored at a population level. Objectives: To ascertain if age, gender, ethnicity, UK geographical region of residence and being diagnosed with another allergy affect the risk of having allergies. Methods: A retrospective analysis was performed using cross-sectional data for the year 2018 extracted from the from the health improvement network (THIN) database. THIN is a live primary care database which holds entries about 6% of the UK population. A logistic regression analysis was carried out using demographic data and allergy diagnoses as independent variables. Results: Of the 3.03 million records analysed, 49.8% were male and 19.7% were children (aged < 18 yrs). There were gender, ethnicity and region-based differences in the prevalence of GP diagnosed allergic diseases in the UK. The odds of developing anaphylaxis are highest in individuals with food allergy [OR: 54.57 (95%CI: 45.65-65.22); p<0.001 for children and OR:18.05 (95% CI:16.79-19.41); p<0.001 for adults respectively]. Individuals with any diagnosed allergy had significantly higher odds of being diagnosed with others. Conclusions: Having an allergy significantly increases the odds of being diagnosed with others. There are age, gender, ethnicity and region based differences in the prevalence of allergies. These data suggest that the number of individuals with multiple allergies is increasing and that the needs of increasingly cosmopolitan populations should be taken into account when planning allergy services.

Background: Allergic rhinoconjunctivitis (ARC), asthma and eczema carry a substantial morbidity. These conditions often co-exist within the same individual and prevalence can differ based on age, ethnicity and gender. Objectives: Using a UK primary care database, we estimated the trends in prevalence over the last decade for ARC, asthma and eczema and associated risk factors. Methods: Longitudinal cohort analysis of the health improvement (THIN) database between 1 st Jan 2010 and 1 st Jan 2019. Logistic regression analysis was used to explore risk factors for diagnosis of these conditions. Results: An average of 4.17 million records per year were analysed, 19.4% were children and 49.75% were male. There was an increase in prevalence of ARC, asthma and eczema amongst adults during the study period, whereas ARC and asthma prevalence amongst children has fallen. By 2018, 1:8 adults and 1:14 children had ARC; asthma was diagnosed in 1:7 adults and 1:10 children whereas eczema was diagnosed in 1:6 adults and 1:4 children respectively. Ethnicity and gender modify the risk of being diagnosed with these conditions. Having other allergies substantially increases the odds of having asthma, eczema and ARC. Conclusion: The population burden of ARC, asthma and eczema in the UK is substantial. These conditions are often associated with other allergies and can, therefore, be complex to manage. These data support calls for improvement of pathways of care for allergy patients in the UK.

Several observational studies have examined the potential protective effect of angiotensin-converting enzyme inhibitor (ACE-I) use on the risk of age-related macular degeneration (AMD) and have reported contradictory results owing to confounding and time-related biases. We aimed to assess the risk of AMD in a base cohort of patients aged 40 and above with hypertension among new users of ACE-I compared to an active comparator cohort of new users of calcium channel blockers (CCB) using data obtained from IQVIA Medical Research database, a primary care database in the UK. In this study, 53,832 and 43,106 new users of ACE-I and CCB were included between 1995 and 2019, respectively. In an on-treatment analysis, patients were followed up from the time of index drug initiation to the date of AMD diagnosis, loss to follow-up, discontinuation or switch to the comparator drug. A comprehensive range of covariates were used to estimate propensity scores to weight and match new users of ACE-I and CCB. Standardized mortality ratio (SMR) weighted Cox proportional hazards model was used to estimate hazard ratios (HRs) of developing AMD. During a median follow-up of 2 years (interquartile range 1-5 years), the incidence rate of AMD was 2.4 and 2.2 per 1,000 person-years among the weighted new users of ACE-I and CCB, respectively. There was no association of ACE-I use on the risk of AMD compared to CCB use in either the propensity score weighted or matched, on-treatment analysis (aHR: 1.07 (95% CI 0.90-1.27) and 0.87 (0.71-1.07) respectively).

Objective To quantify the inter-dependency between maternal metabolic risk factors and their association with birthweight and cord blood insulin (CBI) level. Design Prospective cohort study. Setting Guangzhou Women and Children’s Medical Centre (GWCMC). Population Pregnant women with a singleton pregnancy who delivered at GWCMC between Jan 2015 and Jun 2016 and had umbilical cord blood retained (total 1522). Methods Multivariable linear regression and Additive Bayesian Network analysis were used to investigate the association between maternal metabolic risk factors (pre-pregnancy body mass index [BMI], fasting glucose, lipid profiles, and early gestational weight gain [GWG]) and their interdependency in predicting birthweight and CBI concentrations. Main outcome measures Birthweight and cord blood insulin. Results High maternal pre-pregnancy BMI was strongly associated with neonatal birthweight (standardized adjusted regression coefficient [βstd] = 0.27, 95%CI 0.22-0.32) directly; and with CBI indirectly. Maternal fasting glucose was positively associated with increased CBI (βstd=0.12, 95%CI 0.07-0.17). Maternal GWG was positively associated with increased birthweight, but not with CBI. None of the maternal lipids profile was independently associated with birthweight or CBI. Conclusions Maternal pre-pregnancy overweight/obesity is the most influential upstream metabolic risk factor for both maternal and neonatal metabolic health, therefore weight management should be addressed from the preconception period. Maternal dyslipidaemia appears to be secondary to maternal metabolic dysfunction with no clear causality relationship with metabolic adverse outcomes in neonates.