The Covid-19 lockdown has shone a light on the importance of where we live for our health and wellbeing. Living in the countryside; having a garden; living in a cohesive neighbourhood; being within walking distance of a park: these factors create very different lockdown experiences, even between neighbours living a stone’s throw apart.

Research into neighbourhood factors and mental health is not new. However, lockdown has created a natural experiment in which people’s activities outside the home are largely being confined to their immediate neighbourhoods. Lockdown has thus amplified the potential detrimental – and protective – effects of neighbourhood conditions on our mental health. Investigating this relationship is not simple. It is important to take into consideration potential factors that might confound associations (e.g., prior mental health). It is also important to take into consideration how individual-level factors such as housing type might modify any associations of neighbourhood characteristics with mental health.

The current project will explore the relationship between neighbourhood characteristics during lockdown – including population density, greenspace, deprivation, and social fragmentation – and people’s symptoms of anxiety and depression during and after lockdown. Analyses will control for key confounders of the association. Moderation of associations according to household composition, housing type, garden access, and perceived access to nature will be explored.

Sexual health can impact upon a person’s quality of life. Being pregnant and having a child can affect a woman’s body and mind in a way that may affect their sexual health. We know that when couples have babies, their sexual activity is likely be low in the first few months after the birth. Yet what we don't know is if the mode of delivery (in other words having a vaginal or a ceasrean delivery) affects female sexual health, particularly in the medium to long-term.

Asthma, eczema and hay fever and are common diseases in childhood and responsible for a significant burden on families and health services. Atopic eczema, hay fever (allergic rhinitis) and atopic asthma often co-exist. Early diagnosis and appropriate management can reduce progression and severity of these diseases.
The Born in Bradford (BiB) birth cohort includes over 13,500 children born between 2007 and 2011, with around half born to women of Pakistani ethnicity. Linked primary care and hospital admission data are available for 97% of BiB children. Two sub-studies within BiB, the Allergy and Infection Study (ALL IN, n=2559) and Mechanisms of the Development of ALLergy (MeDALL, n=1814), have collected detailed parental questionnaire data at age 1 and 2 years (ALL IN) and at 4 years (MeDALL). The current data collection phase for the whole BiB cohort, Growing Up, at ages 7-11 years is ongoing and also includes questions on these outcomes.
The BiB data provide an opportunity to investigate trajectories of allergic disease and asthma through childhood, by ethnic group. The linked primary care and hospital electronic health records (EHR) will contribute a wealth of data which can be analysed with machine learning methods. There is uncertainty over the validity of routine data but the extensive BiB questionnaire data at different ages provide a rare opportunity to test this.
The aims of this proposed study are:
1) to link research and routine data to explore early life and childhood longitudinal trajectories and describe clinical phenotypes of asthma, eczema and hay fever;
2) to investigate ethnic inequalities in access to care and presentation of these diseases
3) to investigate early life risk factors for these diseases
Questionnaire data are available from the BiB ALL IN sub-study at age 1 year, including questions on pets, family history of asthma/eczema/hay fever, housing conditions (damp, heating, flooring, bedding etc.), and at 2 years (as for age 1 plus eczema, hay fever, food allergy). Detailed data relevant to asthma, eczema and hay fever are available for the MeDALL sub-study participants at 4 years, including skin prick testing for 2269.
BiB receive regular extracts of primary care EHR data on diagnoses and prescriptions for BiB children, which will be linked to the BiB maternal baseline questionnaire data, including socio-demographic and household characteristics. Linked hospital admissions data are available from the Bradford Royal Infirmary. We will also compare EHR data and questionnaire data from the Avon Longitudinal Study of Parents and Children (ALSPAC).
Latent class analysis or other cluster methods, such as k-means clustering, will be used to identify clinical phenotypes of asthma, eczema and hay fever. Longitudinal extensions of these cluster methods will be used to describe trajectories over age.
This study will provide important data on the validity of routine primary care EHR for asthma and allergic diseases, which is relevant as EHR are increasingly used for research studies. The comparison of questionnaire and EHR data will indicate whether there are ethnic differences in access to primary care for these diseases. Identification of clinical phenotypes of asthma, eczema and hay fever will inform appropriate treatment and management and the identification of factors associated with disease progression or severity could indicate potential prevention strategies.

Vascular diseases such as hypertension, migraine, and atherosclerosis (hardening of arteries) involve changes in vascular cell function with reduced ability to contract and relax in response to different stresses. This results in chronic alterations in artery blood flow and maladaptive structural changes to the vascular wall leading to injury, tissue damage, and increased risk for life-threatening diseases such as stroke and heart attacks. Given that naturally occurring genetic variation contributes to changes in vascular function along with environmental risk from early life stages, it is now critical to evaluate the effects of these genetic associations at this stage using more systematic approaches. We plan to integrate these vascular phenotype data with high resolution molecular data to better understand how these genetic risk factors impact vascular disease risk at an early age.

Better Care South-West Partnership is a collaboration of NHS commissioners, primary, secondary, community and mental health care providers, local authorities, and academia. They look to address real-world health problems using the Bristol, North Somerset and South Gloucestershire (BNSSG) Systemwide health and social care dataset and have an ambition to use individual-level, linked routine care and administrative data to deliver a learning, Integrated Care System for the local population.
The Partnership represents a step change in using advanced analytics to deliver Better Care Loops across a care system and benefit patients and partner organisations. Its results will be scalable across the region and nationally.
Research Projects
· P-NEWS: personalised early warning scores for preventing unplanned critical care admission
· Precision antimicrobial prescribing: safeguarding patient outcomes and preserving future efficacy
· Using operation research methods to improve flow between acute and social care: modelling the responsiveness of system-level expenditure to changes in social care capacity
· Improving hospital efficiency by forecasting demand for hospital beds
· Underpinning infrastructure to the BNSSG Systemwide dataset

Infection by the sars-cov-2 virus (coronavirus) causes a range of flu-like symptoms which can be mild or serious. To date, testing for coronavirus in the Bristol area has focussed on people with severe symptoms. This means that existing test results do not give a full picture of how many people in the Bristol area have already had coronavirus infection.

Rather than using tests, it may be possible to track the spread of coronavirus over time by looking at how many people are experiencing flu-like symptoms. This analysis plans to divide flu-like symptoms into two groups (those which are specific to coronavirus and those which are common in many types of cold or flu) and compare how the rate of these has changed between October 2019 and June 2020. This may give more information about the posible true rate of mild infection in the Bristol area, as well as how the number of people with coronavirus is changing over time.

There is strong epidemiological evidence to suggest that paternal postnatal depression (PPD) is associated with adverse offspring developmental outcomes in early childhood. However, few large prospective longitudinal studies have examined whether these adverse outcomes persist into later childhood (7 years of age). Furthermore, the offspring outcomes are heterogenous and effect sizes are small to moderate. Thus, it is important to elucidate putative mechanisms, i.e. mediating factors, that underly associations between PPD and offspring adverse developmental outcomes. Such insights are crucial to highlight those at greater risk and develop targeted interventions to reduce adverse outcomes in offspring of depressed fathers. A substantial body of evidence suggests that an important potential mediator is the quality of parenting. Specifically, evidence suggests that PPD disrupts paternal levels of involvement with the offspring and quality of parenting (e.g., bonding, enjoyment, confidence), which, in turn, is associated with adverse offspring outcomes, including emotional and behavioural problems. However, few population-based studies have examined potential explanatory role of fathers’ involvement and parenting in the association between PPD and offspring development using longitudinal mediation models.

ALSPAC is well-placed to contribute to the national/international Covid-19 research effort given it has an extensive archive of data about participants health and wellbeing and circumstances prior to the Covid-19 outbreak and is now collecting data specifically related to Covid-19. These data can be used with our biobank and genetic data.

This project seeks to enhance these data with NHS and other Covid-19 records. These will bring timely information about symptoms, help-seeking and care and disease outcomes. It will allow ALSPAC to look at Covid-19 specific health (i.e. the health of those with the virus) and wider general physical and mental health (which may be impacted by stretched NHS resources during the outbreak, or due to the 'lock-down' and social distancing).

This data will sit alongside the other health records ALSPAC have collected. The same security mechanisms will be used to keep the data confidential, and ALSPAC will not extract records from participants who have objected to this use of their data.

The records will be sourced from:

1) A new NHS national (English) repository of Covid-19 data (GP records, Hospital Records, Pharmacy data, NHS 111 call records, Ambulance Records, Mortality Records, Covid-19 testing records).
2) Respiratory care records from databases at NHS University Hospital Bristol Trust and NHS North Bristol Trust hospitals.
3) Records from the 'Zoe' symptom tracker app.

ALSPAC will immediately use the data to help understand more about the factors that influence the susceptibility and severity of Covid-19. We will also examine whether Blood Group and the FUT2 gene (and other genes) are associated with Covid-19 susceptibility.