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Social deprivation, inequality, and the neighborhood-level incidence of psychotic syndromes in East London.

ABSTRACT: Although urban birth, upbringing, and living are associated with increased risk of nonaffective psychotic disorders, few studies have used appropriate multilevel techniques accounting for spatial dependency in risk to investigate social, economic, or physical determinants of psychosis incidence. We adopted Bayesian hierarchical modeling to investigate the sociospatial distribution of psychosis risk in East London for DSM-IV nonaffective and affective psychotic disorders, ascertained over a 2-year period in the East London first-episode psychosis study. We included individual and environmental data on 427 subjects experiencing first-episode psychosis to estimate the incidence of disorder across 56 neighborhoods, having standardized for age, sex, ethnicity, and socioeconomic status. A Bayesian model that included spatially structured neighborhood-level random effects identified substantial unexplained variation in nonaffective psychosis risk after controlling for individual-level factors. This variation was independently associated with greater levels of neighborhood income inequality (SD increase in inequality: Bayesian relative risks [RR]: 1.25; 95% CI: 1.04-1.49), absolute deprivation (RR: 1.28; 95% CI: 1.08-1.51) and population density (RR: 1.18; 95% CI: 1.00-1.41). Neighborhood ethnic composition effects were associated with incidence of nonaffective psychosis for people of black Caribbean and black African origin. No variation in the spatial distribution of the affective psychoses was identified, consistent with the possibility of differing etiological origins of affective and nonaffective psychoses. Our data suggest that both absolute and relative measures of neighborhood social composition are associated with the incidence of nonaffective psychosis. We suggest these associations are consistent with a role for social stressors in psychosis risk, particularly when people live in more unequal communities.

SUBMITTER: Kirkbride JB

PROVIDER: S-EPMC3885290 | biostudies-literature | 2014 Jan

REPOSITORIES: biostudies-literature

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Social deprivation, inequality, and the neighborhood-level incidence of psychotic syndromes in East London.

Kirkbride James B JB Jones Peter B PB Ullrich Simone S Coid Jeremy W JW

Schizophrenia bulletin 20121212 1

Although urban birth, upbringing, and living are associated with increased risk of nonaffective psychotic disorders, few studies have used appropriate multilevel techniques accounting for spatial dependency in risk to investigate social, economic, or physical determinants of psychosis incidence. We adopted Bayesian hierarchical modeling to investigate the sociospatial distribution of psychosis risk in East London for DSM-IV nonaffective and affective psychotic disorders, ascertained over a 2-yea ...[more]

PMID: 23236081

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Project description:ObjectiveAssess associations of Social Determinants of Health (SDoH) using Area Deprivation Index (ADI), race/ethnicity and insurance type with Textbook Outcomes (TO).Summary background dataIndividual- and contextual-level SDoH affect health outcomes, but only one SDoH level is usually included.MethodsThree healthcare system cohort study using National Surgical Quality Improvement Program (2013-2019) linked with ADI risk-adjusted for frailty, case status and operative stress examining TO/TO components (unplanned reoperations, complications, mortality, Emergency Department/Observation Stays and readmissions).ResultsCohort (34,251 cases) mean age 58.3 [SD=16.0], 54.8% females, 14.1% Hispanics, 11.6% Non-Hispanic Blacks, 21.6% with ADI>85, and 81.8% TO. Racial and ethnic minorities, non-Private insurance, and ADI>85 patients had increased odds of urgent/emergent surgeries (aORs range: 1.17-2.83, all P<.001). Non-Hispanic Black patients, ADI>85 and non-Private insurances had lower TO odds (aORs range: 0.55-0.93, all P<.04), but ADI>85 lost significance after including case status. Urgent/emergent versus elective had lower TO odds (aOR=0.51, P<.001). ADI>85 patients had higher complication and mortality odds. Estimated reduction in TO probability was 9.9% (CI=7.2%-12.6%) for urgent/emergent cases, 7.0% (CI=4.6%-9.3%) for Medicaid, and 1.6% (CI=0.2%-3.0%) for non-Hispanic Black patients. TO probability difference for lowest-risk (White-Private-ADI≤85-elective) to highest-risk (Black-Medicaid-ADI>85-urgent/emergent) was 29.8% for very frail patients.ConclusionMulti-level SDoH had independent effects on TO, predominately affecting outcomes through increased rates/odds of urgent/emergent surgeries driving complications and worse outcomes. Lowest-risk versus highest-risk scenarios demonstrated the magnitude of intersecting SDoH variables. Combination of insurance type and ADI should be used to identify high-risk patients to redesign care pathways to improve outcomes. Risk adjustment including contextual neighborhood deprivation and patient-level SDoH could reduce unintended consequences of value-based programs.

Project description:ImportancePeople with psychosis are more likely to be born and live in densely populated and socioeconomically deprived environments, but it is unclear whether these associations are a cause or consequence of disorder.ObjectiveTo investigate whether trajectories of exposure to deprivation and population density before and after diagnosis are associated with psychotic disorders or nonpsychotic bipolar disorder.Design, setting, and participantsThis nested case-control study included all individuals born in Sweden between January 1, 1982, and December 31, 2001, diagnosed for the first time with an International Statistical Classification of Diseases and Related Health Problems, Tenth Revision (ICD-10) psychotic disorder or nonpsychotic bipolar disorder between their 15th birthday and cohort exit (December 31, 2016). One sex- and birth year-matched control participant per case was selected. Data analysis was performed from July 2021 to June 2023.ExposuresThe main exposures were quintiles of neighborhood-level deprivation and population density each year from birth to age 14 years and from first diagnosis until cohort exit.Main outcomes and measuresThe main outcomes were the odds of a serious mental illness outcome associated with trajectories of deprivation and population density, before and after diagnosis in cases. Group-based trajectory modeling was used to derive trajectories of each exposure in each period. Logistic regression was used to examine associations with outcomes.ResultsA total of 53 458 individuals (median [IQR] age at diagnosis in case patients, 23.2 [15.0-34.8] years; 30 746 [57.5%] female), including 26 729 case patients and 26 729 control participants, were studied. From birth to early adolescence, gradients were observed in exposure to deprivation and population density trajectories during upbringing and psychotic disorder, with those in the most vs least deprived (adjusted odds ratio [AOR], 1.17; 95% CI, 1.08-1.28) and most vs least densely populated (AOR, 1.49; 95% CI, 1.34-1.66) trajectories at greatest risk. A strong upward mobility trajectory to less deprived neighborhoods was associated with similar risk to living in the least deprived trajectory (AOR, 1.01; 95% CI, 0.91-1.12). Only 543 case patients (2.0%) drifted into more deprived areas after diagnosis; people with psychotic disorder were more likely to belong to this trajectory (AOR, 1.38; 95% CI, 1.16-1.65) or remain in the most deprived trajectory (AOR, 1.36; 95% CI, 1.24-1.48) relative to controls. Patterns were similar for nonpsychotic bipolar disorder and deprivation but weaker for population density.Conclusions and relevanceIn this case-control study, greater exposure to deprivation during upbringing was associated with increased risk of serious mental illness, but upward mobility mitigated this association. People with serious mental illness disproportionately remained living in more deprived areas after diagnosis, highlighting issues of social immobility. Prevention and treatment should be proportionately located in deprived areas according to need.

Project description:Determining the level of social distancing, quantified here as the reduction in daily number of social contacts per person, i.e. the daily contact rate, needed to maintain control of the COVID-19 epidemic and not exceed acute bed capacity in case of future epidemic waves, is important for future planning of relaxing of strict social distancing measures. This work uses mathematical modelling to simulate the levels of COVID-19 in North East London (NEL) and inform the level of social distancing necessary to protect the public and the healthcare demand from future COVID-19 waves. We used a Susceptible-Exposed-Infected-Removed (SEIR) model describing the transmission of SARS-CoV-2 in NEL, calibrated to data on hospitalised patients with confirmed COVID-19, hospital discharges and in-hospital deaths in NEL during the first epidemic wave. To account for the uncertainty in both the infectiousness period and the proportion of symptomatic infection, we simulated nine scenarios for different combinations of infectiousness period (1, 3 and 5 days) and proportion of symptomatic infection (70%, 50% and 25% of all infections). Across all scenarios, the calibrated model was used to assess the risk of occurrence and predict the strength and timing of a second COVID-19 wave under varying levels of daily contact rate from July 04, 2020. Specifically, the daily contact rate required to suppress the epidemic and prevent a resurgence of COVID-19 cases, and the daily contact rate required to stay within the acute bed capacity of the NEL system without any additional intervention measures after July 2020, were determined across the nine different scenarios. Our results caution against a full relaxing of the lockdown later in 2020, predicting that a return to pre-COVID-19 levels of social contact from July 04, 2020, would induce a second wave up to eight times the original wave. With different levels of ongoing social distancing, future resurgence can be avoided, or the strength of the resurgence can be mitigated. Keeping the daily contact rate lower than 5 or 6, depending on scenarios, can prevent an increase in the number of COVID-19 cases, could keep the effective reproduction number Re below 1 and a secondary COVID-19 wave may be avoided in NEL. A daily contact rate between 6 and 7, across scenarios, is likely to increase Re above 1 and result in a secondary COVID-19 wave with significantly increased COVID-19 cases and associated deaths, but with demand for hospital-based care remaining within the bed capacity of the NEL health and care system. In contrast, an increase in daily contact rate above 8 to 9, depending on scenarios, will likely exceed the acute bed capacity in NEL and may potentially require additional lockdowns. This scenario is associated with significantly increased COVID-19 cases and deaths, and acute COVID-19 care demand is likely to require significant scaling down of the usual operation of the health and care system and should be avoided. Our findings suggest that to avoid future COVID-19 waves and to stay within the acute bed capacity of the NEL health and care system, maintaining social distancing in NEL is advised with a view to limiting the average number of social interactions in the population. Increasing the level of social interaction beyond the limits described in this work could result in future COVID-19 waves that will likely exceed the acute bed capacity in the system, and depending on the strength of the resurgence may require additional lockdown measures.

Project description:BACKGROUND:Little is known about the impact of urbanicity, adverse neighborhood conditions and violent crime victimization on the emergence of adolescent psychotic experiences. METHODS:Participants were from the Environmental Risk (E-Risk) Longitudinal Twin Study, a nationally-representative cohort of 2232 British twins who were interviewed about adolescent psychotic experiences at age 18. Urbanicity, neighborhood characteristics, and personal victimization by violent crime were measured during childhood and adolescence via geocoded census data, surveys of over 5000 immediate neighbors of the E-Risk participants, and interviews with participants themselves. RESULTS:Adolescents raised in urban vs rural neighborhoods were significantly more likely to have psychotic experiences (OR = 1.67, 95% CI = 1.21-2.30, P = .002). This association remained significant after considering potential confounders including family socioeconomic status, family psychiatric history, and adolescent substance problems (OR = 1.43, 95% CI = 1.01-2.03, P = .042), but became nonsignificant after considering adverse social conditions in urban neighborhoods such as low social cohesion and high neighborhood disorder (OR = 1.35, 95% CI = 0.94-1.92, P = .102). The combined association of adverse neighborhood social conditions and personal crime victimization with adolescent psychotic experiences (adjusted OR = 4.86, 95% CI = 3.28-7.20, P < .001) was substantially greater than for either exposure alone, highlighting a potential interaction between neighborhood conditions and crime victimization (interaction contrast ratio = 1.81, 95% CI = -0.03 to 3.65) that was significant at the P = .054 level. CONCLUSIONS:Cumulative effects of adverse neighborhood social conditions and personal victimization by violent crime during upbringing partly explain why adolescents in urban settings are more likely to report psychotic experiences. Early intervention efforts for psychosis could be targeted towards victimized youth living in urban and socially adverse neighborhoods.

Dataset Information

Social deprivation, inequality, and the neighborhood-level incidence of psychotic syndromes in East London.

Publications

Social deprivation, inequality, and the neighborhood-level incidence of psychotic syndromes in East London.

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