Background: SARS-CoV-2 antibody levels can be used to assess humoral immune responses following SARS-CoV-2 infection or vaccination, and may predict risk of future infection. Higher levels of SARS-CoV-2 anti-Spike antibodies are known to be associated with increased protection against future SARS-CoV-2 infection. However, variation in antibody levels and risk factors for lower antibody levels following each round of SARS-CoV-2 vaccination have not been explored across a wide range of socio-demographic, SARS-CoV-2 infection and vaccination, and health factors within population-based cohorts. Methods: Samples were collected from 9,361 individuals from TwinsUK and ALSPAC UK population-based longitudinal studies and tested for SARS-CoV-2 antibodies. Cross-sectional sampling was undertaken jointly in April-May 2021 (TwinsUK, N = 4,256; ALSPAC, N = 4,622), and in TwinsUK only in November 2021-January 2022 (N = 3,575). Variation in antibody levels after first, second, and third SARS-CoV-2 vaccination with health, socio-demographic, SARS-CoV-2 infection and SARS-CoV-2 vaccination variables were analysed. Using multivariable logistic regression models, we tested associations between antibody levels following vaccination and: (1) SARS-CoV-2 infection following vaccination(s); (2) health, socio-demographic, SARS-CoV-2 infection and SARS-CoV-2 vaccination variables. Results: Within TwinsUK, single-vaccinated individuals with the lowest 20% of anti-Spike antibody levels at initial testing had 3-fold greater odds of SARS-CoV-2 infection over the next six to nine months (OR = 2.9, 95% CI: 1.4, 6.0), compared to the top 20%. In TwinsUK and ALSPAC, individuals identified as at increased risk of COVID-19 complication through the UK 'Shielded Patient List' had consistently greater odds (2- to 4-fold) of having antibody levels in the lowest 10%. Third vaccination increased absolute antibody levels for almost all individuals, and reduced relative disparities compared with earlier vaccinations. Conclusions: These findings quantify the association between antibody level and risk of subsequent infection, and support a policy of triple vaccination for the generation of protective antibodies. Funding: Antibody testing was funded by UK Health Security Agency. The National Core Studies program is funded by COVID-19 Longitudinal Health and Wellbeing - National Core Study (LHW-NCS) HMT/UKRI/MRC (MC_PC_20030 & MC_PC_20059). Related funding was also provided by the NIHR 606 (CONVALESCENCE grant COV-LT-0009). TwinsUK is funded by the Wellcome Trust, Medical Research Council, Versus Arthritis, European Union Horizon 2020, Chronic Disease Research Foundation (CDRF), Zoe Ltd and the National Institute for Health Research (NIHR) Clinical Research Network (CRN) and Biomedical Research Centre based at Guy's and St Thomas' NHS Foundation Trust in partnership with King's College London. The UK Medical Research Council and Wellcome (Grant ref: 217065/Z/19/Z) and the University of Bristol provide core support for ALSPAC.

SARS-CoV-2 antibody levels can be used to assess humoral immune responses following SARS-CoV-2 infection or vaccination, and may predict risk of future infection. From cross-sectional antibody testing of 9,361 individuals from TwinsUK and ALSPAC UK population-based longitudinal studies (jointly in April-May 2021, and TwinsUK only in November 2021-January 2022), we tested associations between antibody levels following vaccination and: (1) SARS-CoV-2 infection following vaccination(s); (2) health, socio-demographic, SARS-CoV-2 infection and SARS-CoV-2 vaccination variables.Within TwinsUK, single-vaccinated individuals with the lowest 20% of anti-Spike antibody levels at initial testing had 3-fold greater odds of SARS-CoV-2 infection over the next six to nine months, compared to the top 20%. In TwinsUK and ALSPAC, individuals identified as at increased risk of COVID-19 complication through the UK “Shielded Patient List” had consistently greater odds (2 to 4-fold) of having antibody levels in the lowest 10%. Third vaccination increased absolute antibody levels for almost all individuals, and reduced relative disparities compared with earlier vaccinations.These findings quantify the association between antibody level and risk of subsequent infection, and support a policy of triple vaccination for the generation of protective antibodies.Lay summaryIn this study, we analysed blood samples from 9,361 participants from two studies in the UK: an adult twin registry, TwinsUK (4,739 individuals); and the Avon Longitudinal Study of Parents and Children, ALSPAC (4,622 individuals). We did this work as part of the UK Government National Core Studies initiative researching COVID-19. We measured blood antibodies which are specific to SARS-CoV-2 (which causes COVID-19). Having a third COVID-19 vaccination boosted antibody levels. More than 90% of people from TwinsUK had levels after third vaccination that were greater than the average level after second vaccination. Importantly, this was the case even in individuals on the UK “Shielded Patient List”. We found that people with lower antibody levels after first vaccination were more likely to report having COVID-19 later on, compared to people with higher antibody levels. People on the UK “Shielded Patient List”, and individuals who reported that they had poorer general health, were more likely to have lower antibody levels after vaccination. In contrast, people who had had a previous COVID-19 infection were more likely to have higher antibody levels following vaccination compared to people without infection. People receiving the Oxford/AstraZeneca rather than the Pfizer BioNTech vaccine had lower antibody levels after one or two vaccinations. However, after a third vaccination, there was no difference in antibody levels between those who had Oxford/AstraZeneca and Pfizer BioNTech vaccines for their first two doses. These findings support having a third COVID-19 vaccination to boost antibodies.

We aimed to assess the association between change in social participation and long‐term improved cognitive function among older adults. Data were obtained from 9648 participants aged ≥60 years in the 2011, 2014 and 2018 waves of the Chinese Longitudinal Healthy Longevity Survey, a national prospective cohort study. Cox regression models were used to calculate adjusted risk ratios (aRRs). Social participation was increased in 20.5% of the participants, decreased in 37.8% of the participants and stable in 41.7% of the participants from the 2011 wave to the 2014–2018 waves. The improved cognitive function rate was 17.9% at follow‐up. Compared to individuals with decreased social participation from the 2011 wave to the 2014–2018 waves, individuals with unchanged total social participation were 59% (aRR = 1.59, 95% CI: 1.35–1.87) more likely to have improved cognitive function in the 2014–2018 waves, and individuals with increased social participation were 61% (aRR = 1.61, 95% CI: 1.43–1.82) more likely to have improved cognitive function, regardless of the baseline social participation status. As for the three forms of social participation, compared with the participants with decreased social participation, those with increased participation in organised social activities, increased participation in group leisure‐time activities, unchanged informal social interactions and increased informal social interactions were 24% (aRR = 1.24, 95% CI: 1.02–1.51), 49% (aRR = 1.49, 95% CI: 1.21–1.84), 55% (aRR = 1.55, 95% CI: 1.37–1.76) and 57% (aRR = 1.57, 95% CI: 1.34–1.84) more likely to have improved cognitive function (all p < 0.05) respectively. The results were stable in the sensitivity analysis. Our findings highlight the importance of promoting social participation from a multidimensional perspective (duration, frequency and forms) to improve cognitive function among older adults, for policy makers and healthcare workers in the community.

This study aims at examining changes in coronary heart disease (CHD) hospitalisation associated with a novel county-scale chronic disease management (CDM) program policy implemented in March 2019 in China during the Thirteenth Five-Year period (Years 2016-2020). The CDM program was designed to improve the health of populations with chronic diseases by means of an integrated way involving both county-level public hospitals and primary care institutes. Data originated from the medical files of CHD inpatients discharged from a secondary hospital from January 2017 to December 2020. A total of 6,111 CHD patient records was collected. Univariate and multivariate regression analyses were performed to assess changes in hospitalisation direct medical costs and length of stay of CHD patients. The mean direct medical cost of CHD hospitalisation was 8,419.73 Yuan and mean length of stay was 7.57 days. Results suggested that the implementation of CDM reduced hospitalisation direct medical cost and bed days by about 23% (1,956.12 Yuan at means) and 11.5% (almost 1 day at means) respectively. In addition, a further decreasing trend in medical cost over time was associated with chronic disease management. It is implied that chronic disease management is an effective way of relieving medical and financial burden of hospitalisation.

BackgroundPeople 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.ObjectiveTo describe the mental health gap between those who live alone and with others in the UK prior to and during the COVID-19 pandemic.MethodsSelf-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.FindingsIn 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.ConclusionsPeople 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 implicationsGreater mental health need and potentially greater barriers to mental healthcare access for those who live alone need to be considered in healthcare planning.