title: Area-level socioeconomic characteristics, prevalence and trajectories of cardiometabolic risk.
abstract: This study examines the relationships between area-level socioeconomic position (SEP) and the prevalence and trajectories of metabolic syndrome (MetS) and the count of its constituents (i.e., disturbed glucose and insulin metabolism, abdominal obesity, dyslipidemia, and hypertension). A cohort of 4,056 men and women aged 18+ living in Adelaide, Australia was established in 2000-2003. MetS was ascertained at baseline, four and eight years via clinical examinations. Baseline area-level median household income, percentage of residents with a high school education, and unemployment rate were derived from the 2001 population Census. Three-level random-intercepts logistic and Poisson regression models were performed to estimate the standardized odds ratio (SOR), prevalence risk ratio (SRR), ratio of SORs/SRRs, and (95% confidence interval (CI)). Interaction between area- and individual-level SEP variables was also tested. The odds of having MetS and the count of its constituents increased over time. This increase did not vary according to baseline area-level SEP (ratios of SORs/SRRs ≈ 1; p ≥ 0.42). However, at baseline, after adjustment for individual SEP and health behaviours, median household income (inversely) and unemployment rate (positively) were significantly associated with MetS prevalence (SOR (95%CI) = 0.76 (0.63-0.90), and 1.48 (1.26-1.74), respectively), and the count of its constituents (SRR (95%CI) = 0.96 (0.93-0.99), and 1.06 (1.04-1.09), respectively). The inverse association with area-level education was statistically significant only in participants with less than post high school education (SOR (95%CI) = 0.58 (0.45-0.73), and SRR (95%CI) = 0.91 (0.88-0.94)). Area-level SEP does not predict an elevated trajectory to developing MetS or an elevated count of its constituents. However, at baseline, area-level SEP was inversely associated with prevalence of MetS and the count of its constituents, with the association of area-level education being modified by individual-level education. Population-level interventions for communities defined by area-level socioeconomic disadvantage are needed to reduce cardiometabolic risks.
authors.affiliation: Clinical and Population Perinatal Research, Kolling Institute of Medical Research, University of Sydney at Royal North Shore Hospital, St Leonards, New South Wales, NSW 2065, Australia. anh.ngo@sydney.edu.au.
authors.forename: Anh D
authors.initials: AD
authors.lastname: Ngo
authors.affiliation: Clinical and Population Perinatal Research, Kolling Institute of Medical Research, University of Sydney at Royal North Shore Hospital, St Leonards, New South Wales, NSW 2065, Australia. Catherine.Paquet@unisa.edu.au.
authors.forename: Catherine
authors.initials: C
authors.lastname: Paquet
authors.affiliation: Clinical and Population Perinatal Research, Kolling Institute of Medical Research, University of Sydney at Royal North Shore Hospital, St Leonards, New South Wales, NSW 2065, Australia. Natasha.Howard@unisa.edu.au.
authors.forename: Natasha J
authors.initials: NJ
authors.lastname: Howard
authors.affiliation: Clinical and Population Perinatal Research, Kolling Institute of Medical Research, University of Sydney at Royal North Shore Hospital, St Leonards, New South Wales, NSW 2065, Australia. Neil.Coffee@unisa.edu.au.
authors.forename: Neil T
authors.initials: NT
authors.lastname: Coffee
authors.affiliation: Clinical and Population Perinatal Research, Kolling Institute of Medical Research, University of Sydney at Royal North Shore Hospital, St Leonards, New South Wales, NSW 2065, Australia. Anne.Taylor@adelaide.edu.au.
authors.forename: Anne W
authors.initials: AW
authors.lastname: Taylor
authors.affiliation: Clinical and Population Perinatal Research, Kolling Institute of Medical Research, University of Sydney at Royal North Shore Hospital, St Leonards, New South Wales, NSW 2065, Australia. Robert.adams@adelaide.edu.au.
authors.forename: Robert J
authors.initials: RJ
authors.lastname: Adams
authors.affiliation: Clinical and Population Perinatal Research, Kolling Institute of Medical Research, University of Sydney at Royal North Shore Hospital, St Leonards, New South Wales, NSW 2065, Australia. mark.daniel@unisa.edu.au.
authors.forename: Mark
authors.initials: M
authors.lastname: Daniel
mesh_terms: D000293:Adolescent; D000328:Adult; D000368:Aged; D015331:Cohort Studies; D005260:Female; D006801:Humans; D008297:Male; D024821:Metabolic Syndrome / Q000191:economics / Q000453:epidemiology*; D008875:Middle Aged; D015995:Prevalence; D012959:Socioeconomic Factors; D013021:South Australia / Q000453:epidemiology; D055815:Young Adult