The long arm of childhood socioeconomic deprivation on mid- to later-life cognitive trajectories: a cross-cohort analysis

INTRODUCTION Earlier studies of the effects of childhood socioeconomic status (SES) on later life cognitive function consistently report a social gradient in later life cognitive function. Evidence for their effects on cognitive decline is, however, less clear. METHODS The sample consists of 5,324 participants in the Whitehall II Study, 8,572 in the Health and Retirement Study, and 1,413 in the Kame Project, who completed self-report questionnaires on their early-life experiences and underwent repeated cognitive assessments. We characterised cognitive trajectories using latent class mixed models, and explored associations between childhood SES and latent class membership using logistic regressions. RESULTS We identified distinct trajectories classes for all cognitive measures examined. Childhood socioeconomic deprivation was associated with an increased likelihood of being in a lower trajectory class. DISCUSSION Our findings support the notions that cognitive ageing is a heterogeneous process and early-life circumstances may have lasting effects on cognition across the life-course

The long arm of childhood socioeconomic deprivation on mid- to later-life cognitive trajectories: a cross-cohort analysis

Introduction Earlier studies of the effects of childhood socioeconomic status (SES) on later-life cognitive function consistently report a social gradient in later-life cognitive function. Evidence for their effects on cognitive decline is, however, less clear. Methods The sample consists of 5324 participants in the Whitehall II study, 8572 in the Health and Retirement Study (HRS), and 1413 in the Kame Project, who completed self-report questionnaires on their early life experiences and underwent repeated cognitive assessments. We characterized cognitive trajectories using latent class mixed models, and explored associations between childhood SES and latent class membership using logistic regressions. Results We identified distinct trajectories classes for all cognitive measures examined. Childhood socioeconomic deprivation was associated with an increased likelihood of being in a lower trajectory class. Discussion Our findings support the notions that cognitive aging is a heterogeneous process and early life circumstances may have lasting effects on cognition across the life-course

Blood immuno-metabolic biomarker signatures of depression and affective symptoms in young adults

BackgroundDepression is associated with alterations in immuno-metabolic biomarkers, but it remains unclear whether these alterations are limited to specific markers, and whether there are subtypes of depression and depressive symptoms which are associated with specific patterns of immuno-metabolic dysfunction.MethodsTo investigate whether immuno-metabolic biomarkers could be used to profile subtypes of depression, we applied regression, clustering, and machine learning to a dataset comprising depression diagnosis, depressive and anxiety symptoms, and blood-based immunological and metabolic biomarkers (n = 118). We measured inflammatory proteins, cell counts, lipids, hormones, and metabolites from up to n = 4161 participants (2363 female, 337 with depression) aged 24 years from the Avon Longitudinal Study of Parents and Children birth cohort.ResultsDepression at age 24 was associated with both altered concentrations of immuno-metabolic markers, and increased extreme-valued inflammatory markers. Inflammatory and metabolic biomarkers show distinct, opposing associations with somatic and anxiety symptoms. We identified two latent components representing the relationship between blood biomarkers, symptoms, and covariates, one characterised by higher somatic symptoms and inflammatory markers (neutrophils, WBC, IL-6), and the other characterised by higher anxiety and worry and lower inflammatory markers (CRP, WBC, IL-6). Individuals with higher somatic-inflammatory component scores had greater depressive symptoms severity over the next five years. Immuno-metabolic biomarkers predicted depression diagnosis (Balanced Accuracy = 0.580) and depression with high somatic symptoms (Balanced Accuracy = 0.575) better than chance, but not depression with high anxiety symptoms (Balanced Accuracy = 0.479).ConclusionsAlterations in immuno-metabolic homeostasis is present in young adults with depression well before the typical age of onset of cardiometabolic diseases. The relationships between affective symptoms and blood immuno-metabolic biomarkers indicate two biotypes of depressive symptoms (somatic-inflamed vs anxious-non-inflamed). These patterns are relevant for prognosis and prediction, highlighting the potential usefulness of immuno-metabolic biomarkers for depression subtyping

Adverse Events of Interest Following Influenza Vaccination in the First Season of Adjuvanted Trivalent Immunization:Retrospective Cohort Study

BACKGROUND: Vaccination is the most effective form of prevention of seasonal influenza; the United Kingdom has a national influenza vaccination program to cover targeted population groups. Influenza vaccines are known to be associated with some common minor adverse events of interest (AEIs), but it is not known if the adjuvanted trivalent influenza vaccine (aTIV), first offered in the 2018/2019 season, would be associated with more AEIs than other types of vaccines. OBJECTIVE: We aim to compare the incidence of AEIs associated with different types of seasonal influenza vaccines offered in the 2018/2019 season. METHODS: We carried out a retrospective cohort study using computerized medical record data from the Royal College of General Practitioners Research and Surveillance Centre sentinel network database. We extracted data on vaccine exposure and consultations for European Medicines Agency–specified AEIs for the 2018/2019 influenza season. We used a self-controlled case series design; computed relative incidence (RI) of AEIs following vaccination; and compared the incidence of AEIs associated with aTIV, the quadrivalent influenza vaccine, and the live attenuated influenza vaccine. We also compared the incidence of AEIs for vaccinations that took place in a practice with those that took place elsewhere. RESULTS: A total of 1,024,160 individuals received a seasonal influenza vaccine, of which 165,723 individuals reported a total of 283,355 compatible symptoms in the 2018/2019 season. Most AEIs occurred within 7 days following vaccination, with a seasonal effect observed. Using aTIV as the reference group, the quadrivalent influenza vaccine was associated with a higher incidence of AEIs (RI 1.46, 95% CI 1.41-1.52), whereas the live attenuated influenza vaccine was associated with a lower incidence of AEIs (RI 0.79, 95% CI 0.73-0.83). No effect of vaccination setting on the incidence of AEIs was observed. CONCLUSIONS: Routine sentinel network data offer an opportunity to make comparisons between safety profiles of different vaccines. Evidence that supports the safety of newer types of vaccines may be reassuring for patients and could help improve uptake in the future

Correcting for the Inflated Adult Population Denominator in An English Nationwide Health Care Cohort: Database Analysis Study

Background:Electronic health care databases are widely used for epidemiological studies. However, they may contain inactive records of individuals no longer participating in the health care system. These inactive records create a methodological challenge as they systematically appear as unexposed with no recorded outcomes. Given the widespread health care system engagement during the COVID-19 pandemic, the English National Health Service (NHS), which hosts a national pandemic planning and research dataset with linkage to COVID-19 vaccination and emergency care data, makes it an ideal setting to identify the extent of overrepresentation due to inactive health care records and assess ways to mitigate them.Objective:The objective of this study is to report any differences between the general practitioner–registered adult population size based on health care records compared to census estimates for England and to apply methodology that could be used to correct for such differences.Methods:We compared the number of adult patients within the General Practice Extraction Service Data for Pandemic Planning and Research (GDPPR) with a valid general practitioner registration as of 1st October 2021, with estimates published by the Office for National Statistics (ONS) for the English population. We used an approach adapted from a weighting method to correct for non-response bias in surveys and down-weighted individuals with no evidence of recent activity in their records.Results:There were 61,194,033 registered NHS patients (in the GDPPR) compared with 56,550,138 in the ONS census-based population. De-duplication on NHS number reduced the population to 57,876,641, including 46,835,968 adults, with the biggest overrepresented group aged 30‐45 years. Of the 46,835,986, 1,121,954 (2.4%) individuals had their initial weights down-weighted due to non-engagement with the health care system since January 2019. The down-weighting removed most of the differences between NHS and ONS populations.Conclusions:There are notable differences in the adult population size as per GDPPR when compared to census estimates. While the overall population size in the GDPPR data was seen to be inflated when compared to ONS census estimates, this was differential with respect to sociodemographic variables. A weighting-based approach can be applied to correct for the inflated denominator. Not correcting for it in large health care datasets, including the English NHS data, could introduce selection bias in epidemiological studies

Development of a modified Cambridge Multimorbidity Score for use with SNOMED CT:an observational English primary care sentinel network study

Background People with multiple health conditions are more likely to have poorer health outcomes and greater care and service needs; a reliable measure of multimorbidity would inform management strategies and resource allocation. Aim To develop and validate a modified version of the Cambridge Multimorbidity Score in an extended age range, using clinical terms that are routinely used in electronic health records across the world (Systematized Nomenclature of Medicine — Clinical Terms, SNOMED CT). Design and setting Observational study using diagnosis and prescriptions data from an English primary care sentinel surveillance network between 2014 and 2019. Method In this study new variables describing 37 health conditions were curated and the associations modelled between these and 1-year mortality risk using the Cox proportional hazard model in a development dataset (n = 300 000). Two simplified models were then developed — a 20-condition model as per the original Cambridge Multimorbidity Score and a variable reduction model using backward elimination with Akaike information criterion as the stopping criterion. The results were compared and validated for 1-year mortality in a synchronous validation dataset (n = 150 000), and for 1-year and 5-year mortality in an asynchronous validation dataset (n = 150 000). Results The final variable reduction model retained 21 conditions, and the conditions mostly overlapped with those in the 20-condition model. The model performed similarly to the 37- and 20-condition models, showing high discrimination and good calibration following recalibration. Conclusion This modified version of the Cambridge Multimorbidity Score allows reliable estimation using clinical terms that can be applied internationally across multiple healthcare settings

Immunometabolic Blood Biomarkers of Developmental Trajectories of Depressive Symptoms:Findings from the ALSPAC Birth Cohort

Depression is associated with immunological and metabolic alterations, but immunometabolic characteristics of developmental trajectories of depressive symptoms remain unclear. Studies of longitudinal trends of depressive symptoms in young people could provide insight into aetiological mechanisms and heterogeneity behind depression, and origins of possible common cardiometabolic comorbidities for depression. Using depressive symptoms scores measured on 10 occasions between ages 10 and 25 years in the Avon Longitudinal Study of Parents and Children (n = 7302), we identified four distinct trajectories: low-stable (70% of the sample), adolescent-limited (13%), adulthood-onset (10%) and adolescent-persistent (7%). We examined associations of these trajectories with: i) anthropometric, cardiometabolic and psychiatric phenotypes using multivariable regression (n = 1565-2828); ii) 67 blood immunological proteins and 57 metabolomic features using empirical Bayes moderated linear models (n = 2059 and n = 2240 respectively); and iii) 28 blood cell counts and biochemical measures using multivariable regression (n = 2246). Relative to the low-stable group, risk of depression and anxiety in adulthood was higher for all other groups, especially in the adolescent-persistent (RRdepression=13.11, 95% CI 9.59-17.90; RRGAD = 11.77, 95% CI 8.58-16.14) and adulthood-onset (RRdepression=6.25, 95% CI 4.50-8.68; RRGAD = 4.66, 95% CI 3.29-6.60) groups. The three depression-related trajectories vary in their immunometabolic profile, with evidence of little or no alterations in the adolescent-limited group. The adulthood-onset group shows widespread classical immunometabolic changes (e.g., increased immune cell counts and insulin resistance), while the adolescent-persistent group is characterised by higher BMI both in childhood and adulthood with few other immunometabolic changes. These findings point to distinct mechanisms and prevention opportunities for adverse cardiometabolic profile in different groups of young people with depression.<br/

COVID-19 booster vaccination uptake and infection breakthrough amongst health care workers in Wales:A national prospective cohort study

Background: From September 2021, Health Care Workers (HCWs) in Wales began receiving a COVID-19 booster vaccination. This is the first dose beyond the primary vaccination schedule. Given the emergence of new variants, vaccine waning vaccine, and increasing vaccination hesitancy, there is a need to understand booster vaccine uptake and subsequent breakthrough in this high-risk population. Methods: We conducted a prospective, national-scale, observational cohort study of HCWs in Wales using anonymised, linked data from the SAIL Databank. We analysed uptake of COVID-19 booster vaccinations from September 2021 to February 2022, with comparisons against uptake of the initial primary vaccination schedule. We also analysed booster breakthrough, in the form of PCR-confirmed SARS-Cov-2 infection, comparing to the second primary dose. Cox proportional hazard models were used to estimate associations for vaccination uptake and breakthrough regarding staff roles, socio-demographics, household composition, and other factors. Results: We derived a cohort of 73,030 HCWs living in Wales (78% female, 60% 18–49 years old). Uptake was quickest amongst HCWs aged 60 + years old (aHR 2.54, 95%CI 2.45–2.63), compared with those aged 18–29. Asian HCWs had quicker uptake (aHR 1.18, 95%CI 1.14–1.22), whilst Black HCWs had slower uptake (aHR 0.67, 95%CI 0.61–0.74), compared to white HCWs. HCWs residing in the least deprived areas were slightly quicker to have received a booster dose (aHR 1.12, 95%CI 1.09–1.16), compared with those in the most deprived areas. Strongest associations with breakthrough infections were found for those living with children (aHR 1.52, 95%CI 1.41–1.63), compared to two-adult only households. HCWs aged 60 + years old were less likely to get breakthrough infections, compared to those aged 18–29 (aHR 0.42, 95%CI 0.38–0.47). Conclusion: Vaccination uptake was consistently lower among black HCWs, as well as those from deprived areas. Whilst breakthrough infections were highest in households with children