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Social and spatial heterogeneity in psychosis proneness in a multilevel case-prodrome-control study.

ABSTRACT: To test whether spatial and social neighbourhood patterning of people at ultra-high risk (UHR) of psychosis differs from first-episode psychosis (FEP) participants or controls and to determine whether exposure to different social environments is evident before disorder onset.We tested differences in the spatial distributions of representative samples of FEP, UHR and control participants and fitted two-level multinomial logistic regression models, adjusted for individual-level covariates, to examine group differences in neighbourhood-level characteristics.The spatial distribution of controls (n = 41) differed from UHR (n = 48; P = 0.04) and FEP participants (n = 159; P = 0.01), whose distribution was similar (P = 0.17). Risk in FEP and UHR groups was associated with the same neighbourhood-level exposures: proportion of single-parent households [FEP adjusted odds ratio (aOR): 1.56 95% CI: 1.00-2.45; UHR aOR: 1.59; 95% CI: 0.99-2.57], ethnic diversity (FEP aOR: 1.27; 95% CI: 1.02-1.58; UHR aOR: 1.28; 95% CI: 1.00-1.63) and multiple deprivation (FEP aOR: 0.88; 95% CI: 0.78-1.00; UHR aOR: 0.86; 95% CI: 0.76-0.99).Similar neighbourhood-level exposures predicted UHR and FEP risk, whose residential patterning was closer to each other's than controls. Adverse social environments are associated with psychosis before FEP onset.

SUBMITTER: Kirkbride JB

PROVIDER: S-EPMC4737210 | biostudies-other | 2015 Oct

REPOSITORIES: biostudies-other

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Project description:OBJECTIVES:To investigate potential geographical and socioeconomic patterning of allostatic load (AL) in China. DESIGN:Multilevel longitudinal study of the 2010 Chronic Disease Risk Factor Surveillance linked to the National Death Surveillance up to 31 December 2015. SETTING:All 31 provinces in China, not including Hong Kong, Macao or Taiwan. PARTICIPANTS:96 466 ≥ 18 years old (women=54.3%). EXPOSURES:Person-level educational attainment and mean years of education in counties. OUTCOME:AL was measured using clinical guidelines for nine biomarkers: body mass index; waist circumference; systolic blood pressure; diastolic blood pressure; fasting blood glucose; total cholesterol; triglycerides; high-density lipoprotein cholesterol; low-density lipoprotein cholesterol. RESULTS:Multilevel logistic regressions adjusted for sex, age, marital status, person-level education, county mean years of education and urban/rural reported ORs of 1.22 (95% CI 1.08 to 1.38) for 5-year all-cause mortality (n=3284) and 1.20 (1.04-1.37) for deaths from non-communicable diseases (n=2891) among people in AL quintile 5 (high) compared with quintile 1 (low). The median rate ratio estimated from unadjusted multilevel negative binomial regression showed AL clustered geographically (province=1.14; county=1.12; town=1.11; village=1.14). After adjusting for aforementioned confounders, AL remained higher with age (rate ratio 1.02, 95% CI 1.02 to 1.02), higher in women compared with men (1.17, 1.15 to 1.19), lower among singletons (0.83, 0.81 to 0.85) and widowers (0.96, 0.94 to 0.98). AL was lower among people with university-level compared with no education (0.92, 0.89 to 0.96), but higher in counties with higher mean education years (1.03, 1.01 to 1.05). A two-way interaction suggested AL was higher (1.04, 1.02 to 1.06) among those with university-level compared with no education within counties with higher mean years of education. Similar results were observed for alternative constructions of AL using 75th and 80th percentile cut-points. CONCLUSIONS:AL in China is patterned geographically. The degree of association between AL and person-level education seems to be dependent on area-level education, which may be a proxy for other contextual factors that warrant investigation.

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Social and spatial heterogeneity in psychosis proneness in a multilevel case-prodrome-control study.

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