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Supervisors: Dr Pia Hardelid, Dr Laura Shallcross, Dr Lucy Pembrey
Background:
Antimicrobial resistance (AMR) is a major public health emergency. Antibiotics are still frequently prescribed to young children for viral respiratory infections, despite evidence that antibiotics are not effective in improving symptoms of sore throat, cough or otitis media.(1) One third of children under five years old are prescribed at least one antibiotic annually in primary care(2). Inappropriate antibiotic prescribing in childhood has been linked with adverse health outcomes in later childhood, including asthma(3) and obesity(4).
Severity of presenting illness has been shown to be a key determinant of the likelihood of being prescribed an antibiotic for common infections among children(5). Antibiotic prescribing rates among children can therefore be expected to vary according to family and child risk factors that increase the risk of contracting common infections, such as overcrowding and the presence of older siblings, and factors that either reduce the ability of the immune system to fight infections if exposed, or increase the symptom severity of common infections, including prematurity, exposure to ambient air pollution, and lack of breastfeeding. However, there is a dearth of studies in a UK context on the role of such broader determinants of antibiotic prescribing in children.
Aims/Objectives:
The aim of this study is to examine family and environmental risk factors for antibiotic prescribing in children to inform effective information and prevention strategies. The specific objectives are to:
1) Develop and validate family clusters (primarily including mothers and children) within NHS health databases
2) Examine the degree to which antibiotic prescribing clusters within families, and determine which child and family characteristics (including prematurity and presence of older siblings) increase the risk of antibiotic prescribing
3) Establish the degree to which environmental factors including air pollution or household overcrowding contribute to antibiotic prescribing
4) Explore new datasets that can be used to inform interventions to reduce excess antibiotic prescribing in children.
Methods:
The student will use several large health databases, including the Born in Bradford (BiB) cohort study, the Clinical Practice Research Datalink (CPRD, a UK primary care database), and linked NHS databases from Scotland in order to address the research objectives. There is scope for developing specialist methodological expertise, including in multi-level models, latent class analyses or time series modelling. There will also be opportunities to explore novel datasets including e-prescribing data from Great Ormond Street and University College London Hospitals. This is an excellent opportunity for a student with a strong background in quantitative data analysis (such as an MSc in statistics, epidemiology or demography) and statistical programming (in Stata, R or SAS) to build skills in using ‘big’ administrative health data to inform strategies to reduce inappropriate antibiotic prescribing in children.
References:
1. National Institute of Health and Clinical Excellence. Respiratory tract infections and antibiotic prescribing. 2008.
2. Sun X, Gulliford MC. Reducing antibiotic prescribing in primary care in England from 2014 to 2017: population-based cohort study. BMJ Open. 2019;9(7):e023989.
3. Patrick DM, Sbihi H, Dai DLY, Al Mamun A, Rasali D, Rose C, et al. Decreasing antibiotic use, the gut microbiota, and asthma incidence in children: evidence from population-based and prospective cohort studies. The Lancet Respiratory Medicine. 2020.
4. Bailey LC, Forrest CB, Zhang P, Richards TM, Livshits A, DeRusso PA. Association of antibiotics in infancy with early childhood obesity. JAMA Pediatr. 2014;168(11):1063-9.
5. O'Brien K, Bellis TW, Kelson M, Hood K, Butler CC, Edwards A. Clinical predictors of antibiotic prescribing for acutely ill children in primary care: an observational study. Br J Gen Pract. 2015;65(638):e585-92.
