Socioeconomic inequalities in cardiovascular disease: a causal perspective.

Socioeconomic inequalities in cardiovascular disease (CVD) persist in high-income countries despite marked overall declines in CVD-related morbidity and mortality. After decades of research, the field has struggled to unequivocally answer a crucial question: is the association between low socioeconomic position (SEP) and the development of CVD causal? We review relevant evidence from various study designs and disciplinary perspectives. Traditional observational, family-based and Mendelian randomization studies support the widely accepted view that low SEP causally influences CVD. However, results from quasi-experimental and experimental studies are both limited and equivocal. While more experimental and quasi-experimental studies are needed to aid causal understanding and inform policy, high-quality descriptive studies are also required to document inequalities, investigate their contextual dependence and consider SEP throughout the lifespan; no simple hierarchy of evidence exists for an exposure as complex as SEP. The COVID-19 pandemic illustrates the context-dependent nature of CVD inequalities, with the generation of potentially new causal pathways linking SEP and CVD. The linked goals of understanding the causal nature of SEP and CVD associations, their contextual dependence, and their remediation by policy interventions necessitate a detailed understanding of society, its change over time and the phenotypes of CVD. Interdisciplinary research is therefore key to advancing both causal understanding and policy translation.

Trends in the ability of socioeconomic position to predict individual body mass index: an analysis of repeated cross-sectional data, 1991-2019.

BACKGROUND: The widening of group-level socioeconomic differences in body mass index (BMI) has received considerable research attention. However, the predictive power of socioeconomic position (SEP) indicators at the individual level remains uncertain, as does the potential temporal variation in their predictive value. Examining this is important given the increasing incorporation of SEP indicators into predictive algorithms and calls to reduce social inequality to tackle the obesity epidemic. We thus investigated SEP differences in BMI over three decades of the obesity epidemic in England, comparing population-wide (SEP group differences in mean BMI) and individual-level (out-of-sample prediction of individuals' BMI) approaches to understanding social inequalities. METHODS: We used repeated cross-sectional data from the Health Survey for England, 1991-2019. BMI (kg/m2) was measured objectively, and SEP was measured via educational attainment, occupational class, and neighbourhood index of deprivation. We ran random forest models for each survey year and measure of SEP adjusting for age and sex. RESULTS: The mean and variance of BMI increased within each SEP group over the study period. Mean differences in BMI by SEP group also increased: differences between lowest and highest education groups were 1.0 kg/m2 (0.4, 1.6) in 1991 and 1.3 kg/m2 (0.7, 1.8) in 2019. At the individual level, the predictive capacity of SEP was low, though increased in later years: including education in models improved predictive accuracy (mean absolute error) by 0.14% (- 0.9, 1.08) in 1991 and 1.05% (0.18, 1.82) in 2019. Similar patterns were obtained for occupational class and neighbourhood deprivation and when analysing obesity as an outcome. CONCLUSIONS: SEP has become increasingly important at the population (group difference) and individual (prediction) levels. However, predictive ability remains low, suggesting limited utility of including SEP in prediction algorithms. Assuming links are causal, abolishing SEP differences in BMI could have a large effect on population health but would neither reverse the obesity epidemic nor reduce much of the variation in BMI.

Systemic inflammation and subsequent risk of amyotrophic lateral sclerosis: Prospective cohort study.

BACKGROUND: While systemic inflammation has been implicated in the etiology of selected neurodegenerative disorders, its role in the development of amyotrophic lateral sclerosis (ALS), a condition with high case-fatality, is untested. Accordingly, we quantified the relationship of C-reactive protein (CRP), an acute-phase reactant and marker of systemic inflammation, with subsequent ALS occurrence. METHODS: We used data from UK Biobank, a prospective cohort study of 502,649 participants who were aged 37 to 73 years when examined at research centers between 2006 and 2010. Venous blood was collected at baseline in the full cohort and assayed for CRP, and repeat measurement was made 3-7 years later in a representative subgroup (N = 14,514) enabling correction for regression dilution. ALS was ascertained via national hospitalization and mortality registries until 2021. We computed multivariable hazard ratios with accompanying 95% confidence intervals for log-transformed CRP expressed as standard deviation and tertiles. RESULTS: In an analytical sample of 400,884 initially ALS-free individuals (218,203 women), a mean follow-up of 12 years gave rise to 231 hospitalizations and 223 deaths ascribed to ALS. After adjustment for covariates which included health behaviors, comorbidity, and socio-economic status, a one standard deviation higher log-CRP was associated with elevated rates of both ALS mortality (hazard ratios; 95% confidence intervals: 1.32; 1.13, 1.53) and hospitalizations (1.20; 1.00, 1.39). There was evidence of dose-response effects across tertiles of CRP for both outcomes (p for trend ≤ 0.05). Correction for regression dilution led to a strengthening of the relationship with CRP for both mortality (1.62; 1.27, 2.08) and hospitalizations (1.37; 1.05, 1.76). CONCLUSIONS: Higher levels of CRP, a blood-based biomarker widely captured in clinical practice, is associated with moderately increased future risk of amyotrophic lateral sclerosis.

Weakening of the cognition and height association from 1957 to 2018: Findings from four British birth cohort studies.

Background: Taller individuals have been repeatedly found to have higher scores on cognitive assessments. Recent studies have suggested that this association can be explained by genetic factors, yet this does not preclude the influence of environmental or social factors that may change over time. We thus tested whether the association changed across time using data from four British birth cohorts (born in 1946, 1958, 1970, and 2001). Methods: In each cohort height was measured and cognition via verbal reasoning, vocabulary/comprehension, and mathematical tests; at ages 10/11 and 14/17 years (N=41,418). We examined associations between height and cognition at each age, separately in each cohort, and for each cognitive test administered. Linear and quantile regression models were used. Results: Taller participants had higher mean cognitive assessment scores in childhood and adolescence, yet the associations were weaker in later (1970 and 2001) cohorts. For example, the mean difference in height comparing the highest with lowest verbal cognition scores at 10/11 years was 0.57 SD (95% CI = 0.44-0.70) in the 1946 cohort, yet 0.30 SD (0.23-0.37) in the 2001 cohort. Expressed alternatively, there was a reduction in correlation from 0.17 (0.15-0.20) to 0.08 (0.06-0.10). This pattern of change in the association was observed across all ages and cognition measures used, was robust to adjustment for social class and parental height, and modeling of plausible missing-not-at-random scenarios. Quantile regression analyses suggested that these differences were driven by differences in the lower centiles of height, where environmental influence may be greatest. Conclusions: Associations between height and cognitive assessment scores in childhood-adolescence substantially weakened from 1957-2018. These results support the notion that environmental and social change can markedly weaken associations between cognition and other traits. Funding: DB is supported by the Economic and Social Research Council (grant number ES/M001660/1); DB and LW by the Medical Research Council (MR/V002147/1). The Medical Research Council (MRC) and the University of Bristol support the MRC Integrative Epidemiology Unit [MC_UU_00011/1]. NMD is supported by an Norwegian Research Council Grant number 295989. VM is supported by the CLOSER Innovation Fund WP19 which is funded by the Economic and Social Research Council (award reference: ES/K000357/1) and Economic and Social Research Council (ES/M001660/1). The funders had no role in study design, data collection and analysis, decision to publish, or preparation of the manuscript.

The association between cognitive ability and body mass index: A sibling-comparison analysis in four longitudinal studies.

BACKGROUND: Body mass index (BMI) and obesity rates have increased sharply since the 1980s. While multiple epidemiologic studies have found that higher adolescent cognitive ability is associated with lower adult BMI, residual and unobserved confounding due to family background may explain these associations. We used a sibling design to test this association accounting for confounding factors shared within households. METHODS AND FINDINGS: We used data from four United States general youth population cohort studies: the National Longitudinal Study of Youth 1979 (NLSY-79), the NLSY-79 Children and Young Adult, the NLSY 1997 (NLSY-97), and the Wisconsin Longitudinal Study (WLS); a total of 12,250 siblings from 5,602 households followed from adolescence up to age 62. We used random effects within-between (REWB) and residualized quantile regression (RQR) models to compare between- and within-family estimates of the association between adolescent cognitive ability and adult BMI (20 to 64 years). In REWB models, moving from the 25th to 75th percentile of adolescent cognitive ability was associated with -0.95 kg/m2 (95% CI = -1.21, -0.69) lower BMI between families. Adjusting for family socioeconomic position reduced the association to -0.61 kg/m2 (-0.90, -0.33). However, within families, the association was just -0.06 kg/m2 (-0.35, 0.23). This pattern of results was found across multiple specifications, including analyses conducted in separate cohorts, models examining age-differences in association, and in RQR models examining the association across the distribution of BMI. Limitations include the possibility that within-family estimates are biased due to measurement error of the exposure, confounding via non-shared factors, and carryover effects. CONCLUSIONS: The association between high adolescent cognitive ability and low adult BMI was substantially smaller in within-family compared with between-family analysis. The well-replicated associations between cognitive ability and subsequent BMI may largely reflect confounding by family background factors.

Systemic inflammation and subsequent risk of amyotrophic lateral sclerosis: prospective cohort study.

Importance: While systemic inflammation has been implicated in the aetiology of selected neurodegenerative disorders, its role in the development of amyotrophic lateral sclerosis (ALS) is untested. Objective: To quantify the relationship of C-reactive protein (CRP), an acute-phase reactant and marker of systemic inflammation, with ALS occurrence. Design Setting Participants: UK Biobank, a prospective cohort study of 502,649 participants who were aged 37 to 73 years when examined at research centres between 2006 and 2010. Exposure: Venous blood was collected at baseline in the full cohort and assayed for CRP. Repeat measurement was made 3-7 years later in a representative subgroup (N=14,514) enabling correction for regression dilution. Main Outcomes and Measures: ALS as ascertained via national hospitalisation and mortality registries. We computed multi-variable hazard ratios with accompanying 95% confidence intervals for log-transformed CRP expressed as standard deviation and tertiles. Results: In an analytical sample of 400,884 individuals (218,203 women), a mean follow-up of 12 years gave rise to 231 hospitalisations and 223 deaths ascribed to ALS. After adjustment for covariates which included health behaviours, comorbidity, and socio-economic status, a one standard deviation higher log-CRP was associated with elevated rates of both ALS mortality (hazard ratios; 95% confidence intervals: 1.32; 1.13, 1.53) and hospitalisations (1.20; 1.00, 1.39). There was evidence of dose-response effects across tertiles of CRP for both outcomes (p for trend≤0.05). Correction for regression dilution led to a strengthening of the relationship with CRP for both mortality (1.62; 1.27, 2.08) and hospitalisations (1.37; 1.05, 1.76) ascribed to ALS. Conclusions and Relevance: Higher levels of CRP, a blood-based biomarker widely captured in clinical practice, were associated with a higher subsequent risk of ALS. Key Points: Question: Is C-reactive protein (CRP), a marker of systemic inflammation widely used in clinical practice, associated with later risk of amyotrophic lateral sclerosis (ALS)?Findings: Following 11 years disease surveillance in 400,884 individuals (218,203 women), after adjustment for covariates and correction for regression dilution, a one standard deviation higher CRP levels were associations with both mortality (hazard ratio; 95% confidence interval: 1.62; 1.27, 2.08) and hospitalisations (1.37; 1.05, 1.76) ascribed to ALS.Meaning: In the present study, CRP has a dose-response relationship with the risk of later ALS.

Biophysical models of early mammalian embryogenesis.

Embryo development is a critical and fascinating stage in the life cycle of many organisms. Despite decades of research, the earliest stages of mammalian embryogenesis are still poorly understood, caused by a scarcity of high-resolution spatial and temporal data, the use of only a few model organisms, and a paucity of truly multidisciplinary approaches that combine biological research with biophysical modeling and computational simulation. Here, we explain the theoretical frameworks and biophysical processes that are best suited to modeling the early mammalian embryo, review a comprehensive list of previous models, and discuss the most promising avenues for future work.

Investigating change across time in prevalence or association: the challenges of cross-study comparative research and possible solutions.

Cross-study research initiatives to understand change across time are an increasingly prominent component of social and health sciences, yet they present considerable practical, analytical and conceptual challenges. First, we discuss the key challenges to comparative research as a basis for detecting societal change, as well as possible solutions. We focus on studies which investigate changes across time in outcome occurrence or the magnitude and/or direction of associations. We discuss the use and importance of such research, study inclusion, sources of bias and mitigation, and interpretation. Second, we propose a structured framework (a checklist) that is intended to provide guidance for future authors and reviewers. Third, we outline a new open-access teaching resource that offers detailed instruction and reusable analytical syntax to guide newcomers on techniques for conducting comparative analysis and data visualisation (in both R and Stata formats). Supplementary Information: The online version contains supplementary material available at 10.1007/s44155-022-00021-1.

Capturing the experiences of UK healthcare workers during the COVID-19 pandemic: A structural topic modelling analysis of 7,412 free-text survey responses.

BACKGROUND: Healthcare workers (HCWs) have provided vital services during the COVID-19 pandemic, but existing research consists of quantitative surveys (lacking in depth or context) or qualitative interviews (with limited generalisability). Structural Topic Modelling (STM) of large-scale free-text survey data offers a way of capturing the perspectives of a wide range of HCWs in their own words about their experiences of the pandemic. METHODS: In an online survey distributed to all staff at 18 geographically dispersed NHS Trusts, we asked respondents, "Is there anything else you think we should know about your experiences of the COVID-19 pandemic?". We used STM on 7,412 responses to identify topics, and thematic analysis on the resultant topics and text excerpts. RESULTS: We identified 33 topics, grouped into two domains, each containing four themes. Our findings emphasise: the deleterious effect of increased workloads, lack of PPE, inconsistent advice/guidance, and lack of autonomy; differing experiences of home working as negative/positive; and the benefits of supportive leadership and peers in ameliorating challenges. Themes varied by demographics and time: discussion of home working decreasing over time, while discussion of workplace challenges increased. Discussion of mental health was lowest between September-November 2020, between the first and second waves of COVID-19 in the UK. DISCUSSION: Our findings represent the most salient experiences of HCWs through the pandemic. STM enabled statistical examination of how the qualitative themes raised differed according to participant characteristics. This relatively underutilised methodology in healthcare research can provide more nuanced, yet generalisable, evidence than that available via surveys or small interview studies, and should be used in future research.

Polygenic and socioeconomic risk for high body mass index: 69 years of follow-up across life.

Genetic influences on body mass index (BMI) appear to markedly differ across life, yet existing research is equivocal and limited by a paucity of life course data. We thus used a birth cohort study to investigate differences in association and explained variance in polygenic risk for high BMI across infancy to old age (2-69 years). A secondary aim was to investigate how the association between BMI and a key purported environmental determinant (childhood socioeconomic position) differed across life, and whether this operated independently and/or multiplicatively of genetic influences. Data were from up to 2677 participants in the MRC National Survey of Health and Development, with measured BMI at 12 timepoints from 2-69 years. We used multiple polygenic indices from GWAS of adult and childhood BMI, and investigated their associations with BMI at each age. For polygenic liability to higher adult BMI, the trajectories of effect size (ß) and explained variance (R2) diverged: explained variance peaked in early adulthood and plateaued thereafter, while absolute effect sizes increased throughout adulthood. For polygenic liability to higher childhood BMI, explained variance was largest in adolescence and early adulthood; effect sizes were marginally smaller in absolute terms from adolescence to adulthood. All polygenic indices were related to higher variation in BMI; quantile regression analyses showed that effect sizes were sizably larger at the upper end of the BMI distribution. Socioeconomic and polygenic risk for higher BMI across life appear to operate additively; we found little evidence of interaction. Our findings highlight the likely independent influences of polygenic and socioeconomic factors on BMI across life. Despite sizable associations, the BMI variance explained by each plateaued or declined across adulthood while BMI variance itself increased. This is suggestive of the increasing importance of chance ('non-shared') environmental influences on BMI across life.

The effects of early life adversity on children's mental health and cognitive functioning.

Emerging evidence suggests that partially distinct mechanisms may underlie the association between different dimensions of early life adversity (ELA) and psychopathology in children and adolescents. While there is minimal evidence that different types of ELA are associated with specific psychopathology outcomes, there are partially unique cognitive and socioemotional consequences of specific dimensions of ELA that increase transdiagnostic risk of mental health problems across the internalizing and externalizing spectra. The current review provides an overview of recent findings examining the cognitive (e.g., language, executive function), socioemotional (e.g., attention bias, emotion regulation), and mental health correlates of ELA along the dimensions of threat/harshness, deprivation, and unpredictability. We underscore similarities and differences in the mechanisms connecting different dimensions of ELA to particular mental health outcomes, and identify gaps and future directions that may help to clarify inconsistencies in the literature. This review focuses on childhood and adolescence, periods of exquisite neurobiological change and sensitivity to the environment. The utility of dimensional models of ELA in better understanding the mechanistic pathways towards the expression of psychopathology is discussed, with the review supporting the value of such models in better understanding the developmental sequelae associated with ELA. Integration of dimensional models of ELA with existing models focused on psychiatric classification and biobehavioral mechanisms may advance our understanding of the etiology, phenomenology, and treatment of mental health difficulties in children and youth.

Trajectories of Compliance With COVID-19 Related Guidelines: Longitudinal Analyses of 50,000 UK Adults.

BACKGROUND: Governments have implemented a range of measures focused on changing citizens' behaviors to lower the transmission of COVID-19. While international data shows that compliance did decline from the start of the pandemic, average trends could mask considerable heterogeneity in compliance behaviors. PURPOSE: To explore trajectories of compliance with COVID-19 guidelines. METHODS: We used longitudinal data on self-reported compliance from 50,851 adults in the COVID-19 Social Study collected across two waves of the pandemic in the UK (April 01, 2020-February 22, 2021). We modeled typical compliance trajectories using latent class growth analysis (LCGA) and used multinomial logistic regression to examine whether individual personality and demographic characteristics were related to compliance trajectories. RESULTS: We selected a four-class LCGA solution. Most individuals maintained high levels of compliance and reported similar levels of compliance across the first and second waves. Approximately 15% of participants had decreasing levels of compliance across the pandemic, reporting noticeably lower levels of compliance in the second wave. Individuals with declining compliance levels were younger on average, in better physical health, had lower empathy and conscientiousness and greater general willingness to take risks. CONCLUSIONS: While a minority, not all individuals have maintained high compliance across the pandemic. Decreasing compliance is related to several psychological traits. The results suggest that targeting of behavior change messages later in the pandemic may be needed to increase compliance.

How Did People Cope During the COVID-19 Pandemic? A Structural Topic Modelling Analysis of Free-Text Data From 11,000 United Kingdom Adults.

Background: The COVID-19 pandemic has had substantial impacts on lives across the globe. Job losses have been widespread, and individuals have experienced significant restrictions on their usual activities, including extended isolation from family and friends. While studies suggest population mental health worsened from before the pandemic, not all individuals appear to have experienced poorer mental health. This raises the question of how people managed to cope during the pandemic. Methods: To understand the coping strategies individuals employed during the COVID-19 pandemic, we used structural topic modelling, a text mining technique, to extract themes from free-text data on coping from over 11,000 UK adults, collected between 14 October and 26 November 2020. Results: We identified 16 topics. The most discussed coping strategy was 'thinking positively' and involved themes of gratefulness and positivity. Other strategies included engaging in activities and hobbies (such as doing DIY, exercising, walking and spending time in nature), keeping routines, and focusing on one day at a time. Some participants reported more avoidant coping strategies, such as drinking alcohol and binge eating. Coping strategies varied by respondent characteristics including age, personality traits and sociodemographic characteristics and some coping strategies, such as engaging in creative activities, were associated with more positive lockdown experiences. Conclusion: A variety of coping strategies were employed by individuals during the COVID-19 pandemic. The coping strategy an individual adopted was related to their overall lockdown experiences. This may be useful for helping individuals prepare for future lockdowns or other events resulting in self-isolation.

Public opinion about the UK government during COVID-19 and implications for public health: A topic modeling analysis of open-ended survey response data.

BACKGROUND: Confidence in the central UK Government has declined since the beginning of the COVID-19 pandemic, and while this may be linked to specific government actions to curb the spread of the virus, understanding is still incomplete. Examining public opinion is important, as research suggests that low confidence in government increases the extent of non-compliance with infection-dampening rules (for instance, social distancing); however, the detailed reasons for this association are still unclear. METHODS: To understand public opinion on the central UK government during the first phase of the COVID-19 pandemic, we used structural topic modeling, a text mining technique, to extract themes from over 4000 free-text survey responses, collected between 14 October and 26 November 2020. RESULTS: We identified eleven topics, among which were topics related to perceived government corruption and cronyism, complaints about inconsistency in rules and messaging, lack of clear planning, and lack of openness and transparency. Participants reported that elements of the government's approach had made it difficult to comply with guidelines (e.g., changing rules) or were having impacts on mental wellbeing (e.g., inability to plan for the future). CONCLUSIONS: Results suggested that consistent, transparent communication and messaging from the government is critical to improving compliance with measures to contain the virus, as well as protecting mental health during health emergencies.

Interpersonal traits and the neural representations of cognitive control in the prefrontal cortex.

Adaptive interpersonal functioning relies on the effectiveness of behavioral and neural systems involved in cognitive control. Whether different subcomponents of cognitive control and their neural representations are associated with distinctive interpersonal dispositions has yet to be determined. The present study investigated the relationships between prefrontal cortex (PFC) activation associated with two subcomponents of cognitive control and individual differences in interpersonally relevant traits and facets within the Five-Factor Model of personality. Undergraduate participants (n = 237) provided self-ratings of interpersonal traits and underwent functional near-infrared spectroscopy to measure activation in regions-of-interest linked to subcomponents of cognitive control: the right lateral PFC and its involvement in response selection and inhibition/suppression (RS) during a go/no-go task, and the left lateral PFC associated with goal selection, updating, representation, and maintenance (GS) on a tower planning task. Multilevel models revealed that during both RS and GS, Neuroticism and Extraversion were associated with lower and higher levels of activation, respectively. Higher Agreeableness was related to lower activation during RS but also with greater activation during GS. More narrowly defined interpersonal facets subsumed within the broader trait domains were differentially associated with RS- and GS-related neural responses. Taken together, these findings highlight potential avenues of future research to better understand the ways in which the neural processes that subserve cognitive control may underlie interpersonal dispositions.

Risk factors relate to the variability of health outcomes as well as the mean: A GAMLSS tutorial.

Background: Risk factors or interventions may affect the variability as well as the mean of health outcomes. Understanding this can aid aetiological understanding and public health translation, in that interventions which shift the outcome mean and reduce variability are typically preferable to those which affect only the mean. However, most commonly used statistical tools do not test for differences in variability. Tools that do have few epidemiological applications to date, and fewer applications still have attempted to explain their resulting findings. We thus provide a tutorial for investigating this using GAMLSS (Generalised Additive Models for Location, Scale and Shape). Methods: The 1970 British birth cohort study was used, with body mass index (BMI; N = 6007) and mental wellbeing (Warwick-Edinburgh Mental Wellbeing Scale; N = 7104) measured in midlife (42-46 years) as outcomes. We used GAMLSS to investigate how multiple risk factors (sex, childhood social class, and midlife physical inactivity) related to differences in health outcome mean and variability. Results: Risk factors were related to sizable differences in outcome variability-for example males had marginally higher mean BMI yet 28% lower variability; lower social class and physical inactivity were each associated with higher mean and higher variability (6.1% and 13.5% higher variability, respectively). For mental wellbeing, gender was not associated with the mean while males had lower variability (-3.9%); lower social class and physical inactivity were each associated with lower mean yet higher variability (7.2% and 10.9% higher variability, respectively). Conclusions: The results highlight how GAMLSS can be used to investigate how risk factors or interventions may influence the variability in health outcomes. This underutilised approach to the analysis of continuously distributed outcomes may have broader utility in epidemiologic, medical, and psychological sciences. A tutorial and replication syntax is provided online to facilitate this (https://osf.io/5tvz6/). Funding: DB is supported by the Economic and Social Research Council (grant number ES/M001660/1), The Academy of Medical Sciences / Wellcome Trust ("Springboard Health of the Public in 2040" award: HOP001/1025); DB and LW are supported by the Medical Research Council (MR/V002147/1). The funders had no role in study design, data collection and analysis, decision to publish, or preparation of the manuscript.

Facilitators and barriers to compliance with COVID-19 guidelines: a structural topic modelling analysis of free-text data from 17,500 UK adults.

BACKGROUND: During the COVID-19 pandemic, the UK government implemented a series of guidelines, rules, and restrictions to change citizens' behaviour to tackle the spread of the virus, such as the promotion of face masks and the imposition of lockdown stay-at-home orders. The success of such measures requires active co-operation on the part of citizens, but compliance was not complete. Detailed research is required on the factors that aided or hindered compliance with these measures. METHODS: To understand the facilitators and barriers to compliance with COVID-19 guidelines, we used structural topic modelling, a text mining technique, to extract themes from over 26,000 free-text survey responses from 17,500 UK adults, collected between 17 November and 23 December 2020. RESULTS: The main factors facilitating compliance were desires to reduce risk to oneself and one's family and friends and to, a lesser extent, the general public. Also of importance were a desire to return to normality, the availability of activities and technological means to contact family and friends, and the ability to work from home. Identified barriers were difficulties maintaining social distancing in public (due to the actions of other people or environmental constraints), the need to provide or receive support from family and friends, social isolation, missing loved ones, and mental health impacts, perceiving the risks as low, social pressure to not comply, and difficulties understanding and keep abreast of changing rules. Several of the barriers and facilitators raised were related to participant characteristics. Notably, women were more likely to discuss needing to provide or receive mental health support from friends and family. CONCLUSION: The results demonstrated an array of factors contributed to compliance with guidelines. Of particular policy importance, the results suggest that government communication that emphasizes the potential risks of the virus and provides simple, consistent guidance on how to reduce the spread of the virus would improve compliance with preventive behaviours as COVID-19 continues and for future pandemics.

Patterns of compliance with COVID-19 preventive behaviours: a latent class analysis of 20 000 UK adults.

BACKGROUND: Governments have implemented a range of measures to tackle COVID-19, primarily focusing on changing citizens' behaviours in order to lower the transmission of the virus. Few studies have looked at the patterns of compliance with different measures within individuals: whether people comply with all measures or selectively choose some but not others. Such research is important for designing interventions to increase compliance. METHODS: We used cross-sectional data from 20 947 UK adults in the COVID-19 Social Study collected from 17 November to 23 December 2020. Self-report compliance was assessed with six behaviours: mask wearing, hand washing, indoor household mixing, outdoor household mixing, social distancing and compliance with other guidelines. Patterns of compliance behaviour were identified using latent class analysis, and multinomial logistic regression was used to assess demographic, socioeconomic and personality predictors of behaviour patterns. RESULTS: We selected a four-latent class solution. Most individuals reported similar levels of compliance across the six behaviour measures. High level of compliance was the modal response. Lower self-reported compliance was related to young age, high risk-taking behaviour, low confidence in government and low empathy, among other factors. Looking at individual behaviours, mask wearing had the highest level of compliance while compliance with social distancing was relatively low. CONCLUSION: Results suggest that individuals choose to comply with all guidelines, rather than some but not others. Strategies to increase compliance should focus on increasing general motivations to comply alongside specifically encouraging social distancing.