Living alone and mental health: parallel analyses in UK longitudinal population surveys and electronic health records prior to and during the COVID-19 pandemic

Background People who live alone experience greater levels of mental illness; however, it is unclear whether the COVID-19 pandemic had a disproportionately negative impact on this demographic. Objective To describe the mental health gap between those who live alone and with others in the UK prior to and during the COVID-19 pandemic. Methods Self-reported psychological distress and life satisfaction in 10 prospective longitudinal population surveys (LPSs) assessed in the nearest pre-pandemic sweep and three periods during the pandemic. Recorded diagnosis of common and severe mental illnesses between March 2018 and January 2022 in electronic healthcare records (EHRs) within the OpenSAFELY-TPP. Findings In 37 544 LPS participants, pooled models showed greater psychological distress (standardised mean difference (SMD): 0.09 (95% CI: 0.04; 0.14); relative risk: 1.25 (95% CI: 1.12; 1.39)) and lower life satisfaction (SMD: −0.22 (95% CI: −0.30; −0.15)) for those living alone pre-pandemic. This gap did not change during the pandemic. In the EHR analysis of c.16 million records, mental health conditions were more common in those who lived alone (eg, depression 26 (95% CI: 18 to 33) and severe mental illness 58 (95% CI: 54 to 62) more cases more per 100 000). For common mental health disorders, the gap in recorded cases in EHRs narrowed during the pandemic. Conclusions People living alone have poorer mental health and lower life satisfaction. During the pandemic, this gap in self-reported distress remained; however, there was a narrowing of the gap in service use. Clinical implications Greater mental health need and potentially greater barriers to mental healthcare access for those who live alone need to be considered in healthcare planning.


Supplementary file 3. Further study informationlongitudinal population surveys (as required by the host institutions)
ALSPAC: Pregnant women resident in Avon, UK with expected dates of delivery 1st April 1991 to 31st December 1992 were invited to take part in the study. The initial number of pregnancies enrolled is 14,541 (for these at least one questionnaire has been returned or a "Children in Focus" clinic had been attended by 19/07/99). Of these initial pregnancies, there was a total of 14,676 foetuses, resulting in 14,062 live births and 13,988 children who were alive at 1 year of age. When the oldest children were approximately 7 years of age, an attempt was made to bolster the initial sample with eligible cases who had failed to join the study originally. As a result, when considering variables collected from the age of seven onwards (and potentially abstracted from obstetric notes) there are data available for more than the 14,541 pregnancies mentioned above. The number of new pregnancies not in the initial sample (known as Phase I enrolment) that are currently represented on the built files and reflecting enrolment status at the age of 24 is 913 (456, 262 and 195 recruited during Phases II, III and IV respectively), resulting in an additional 913 children being enrolled. The phases of enrolment are described in more detail in the cohort profile paper and its update (see footnote 4 below). The total sample size for analyses using any data collected after the age of seven is therefore 15,454 pregnancies, resulting in 15,589 foetuses. Of these 14,901 were alive at 1 year of age. A 10% sample of the ALSPAC cohort, known as the Children in Focus (CiF) group, attended clinics at the University of Bristol at various time intervals between 4 to 61 months of age. The CiF group were chosen at random from the last 6 months of ALSPAC births (1432 families attended at least one clinic). Excluded were those mothers who had moved out of the area or were lost to follow-up, and those partaking in another study of infant development in Avon.

ELSA
In which of these ways do you occupy this accommodation? 1=Own it outright; 2=Buying it with the help of a mortgage or loan; 3=Pay part rent and part mortgage shared ownership; 4=Rent it; 5=Live here rent free (including rent free in relative's / friend's property; excluding squatting); 6=Squatting

GS
What is the status of the accommodation in which you and your household live? 1=Own outright; 2=Own with mortgage; 3=Rent from local authority/housing association; 4=Rent from private landlord or agency; 5=Pay part rent and part mortgage;6=Live rent free; 7=Other; 8=Don't know; 9=Prefer not to answer 1/2=1; 3/9=0

TWINS UK
Which describes the home you live in? Owned outright (1); Owned with the help of a mortgage (2); Shared ownership (part owned, part rented) (3); Rented (4); Living rent free (5); Other (Please specify below) (6)  (1) if the address falls within urban settlements with a population of 10,000 or more, or (2) otherwise.

ELSA
Binary indicator classifying the address as falling into an (1) urban or (2) rural area. This is derived from the Office for National Statistics Rural and Urban Classification of Output Areas 2011. The indicator assumes a value of (1) if the address falls within urban settlements with a population of 10,000 or more, or (2) otherwise.

TWINS UK
Binary indicator classifying the address as falling into an (1) urban or (2) rural area. This is derived from the Office for National Statistics Rural and Urban Classification of Output Areas 2011. The indicator assumes a value of (1) if the address falls within urban settlements with a population of 10,000 or more, or (2) otherwise. All data were linked, stored and analysed securely within the OpenSAFELY platform https://opensafely.org/. Data include pseudonymized data such as coded diagnoses, medications and physiological parameters. No free text data are included. All code is shared openly for review and re-use under MIT open license ([https://github.com/opensafely/lone_households]). Detailed pseudonymised patient data is potentially re-identifiable and therefore not shared. We rapidly delivered the OpenSAFELY data analysis platform without prior funding to deliver timely analyses on urgent research questions in the context of the global Covid-19 health emergency: now that the platform is established we are developing a formal process for external users to request access in collaboration with NHS England; details of this process are available at OpenSAFELY.org.

SOFTWARE AND REPRODUCIBILITY
Data management and analysis was performed using the OpenSAFELY software libraries and Python, both implemented using Python 3. This analysis was delivered using federated analysis through the OpenSAFELY platform: codelists and code for data management and data analysis were specified once using the OpenSAFELY tools; then transmitted securely to the OpenSAFELY-TPP platform within TPP's secure environment, and separately to the OpenSAFELY-EMIS platform within EMIS's secure environment, where they were each executed separately against local patient data; summary results were then reviewed for disclosiveness, released, and combined for the final outputs. All code for the OpenSAFELY platform for data management, analysis and secure code execution is shared for review and re-use under open licenses at GitHub.com/OpenSAFELY. Data management was performed using Python 3.8, with analysis carried out using Stata 17. Code for data management and analysis as well as codelists archived online [https://github.com/opensafely/lone_households]. All iterations of the pre-specified study protocol are archived with version control.

ETHICS STATEMENT
We received ethics approval to conduct the data linkage and analyses by the London -City & East Research Ethics Committee on the 2nd of April 2020 (REC reference: 20/LO/0651) and LSHTM Ethics Board (ref 21863). No further ethical or research governance approval was required by the University of Oxford but copies of the approval documents were reviewed and held on record.

INFORMATION GOVERNANCE
NHS England is the data controller; TPP is the data processor; and the key researchers on OpenSAFELY are acting on behalf of NHS England. This implementation of OpenSAFELY is hosted within the TPP environment, which is accredited to the ISO 27001 information security standard and is NHS IG Toolkit compliant 52,53; patient data have been pseudonymized for analysis and linkage using industry standard cryptographic hashing techniques; all pseudonymized datasets transmitted for linkage onto OpenSAFELY are encrypted; access to the platform is through a virtual private network (VPN) connection; the researchers hold contracts with NHS England and only access the platform to initiate database queries and statistical models; all database activity is logged; and only aggregate statistical outputs leave the platform environment following best practice for anonymization of results such as statistical disclosure control for low cell counts54. The OpenSAFELY research platform adheres to the data protection principles of the UK Data Protection Act BMJ Publishing Group Limited (BMJ) disclaims all liability and responsibility arising from any reliance Supplemental material placed on this supplemental material which has been supplied by the author(s)  (COPI) to require organizations to process confidential patient information for the purposes of protecting public health, providing healthcare services to the public and monitoring and managing the COVID-19 outbreak and incidents of exposure55. Together, these provide the legal bases to link patient datasets on the OpenSAFELY platform. GP practices, from which the primary care data are obtained, are required to share relevant health information to support the public health response to the pandemic and have been informed of the OpenSAFELY analytics platform.

Peri-Pandemic 3
Low Life Satisfaction

ALSPAC-G1
Psych    Figure S1. Results of meta-analyses in LPS BMJ Publishing Group Limited (BMJ) disclaims all liability and responsibility arising from any reliance Supplemental material placed on this supplemental material which has been supplied by the author(s)