Geographic variation in cardiometabolic risk factor prevalence explained by area-level disadvantage in the Illawarra-Shoalhaven region of the NSW, Australia

Sci Rep. 2020 Jul 29;10(1):12770. doi: 10.1038/s41598-020-69552-4.

Abstract

Cardiometabolic risk factors (CMRFs) demonstrate significant geographic variation in their distribution. The study aims to quantify the general contextual effect of the areas on CMRFs; and the geographic variation explained by area-level socioeconomic disadvantage. A cross sectional design and multilevel logistic regression methods were adopted. Data included objectively measured routine pathology test data between years 2012 and 2017 on: fasting blood sugar level; glycated haemoglobin; total cholesterol; high density lipoprotein; urinary albumin creatinine ratio; estimated glomerular filtration rate; and body mass index. The 2011 Australian census based Index of Relative Socioeconomic Disadvantage (IRSD) were the area-level study variables, analysed at its smallest geographic unit of reporting. A total of 1,132,029 CMRF test results from 256,525 individuals were analysed. After adjusting for individual-level covariates, all CMRFs significantly associated with IRSD and the probability of higher risk CMRFs increases with greater area-level disadvantage. Though the specific contribution of IRSD in the geographic variation of CMRF ranged between 57.8 and 14.71%, the general contextual effect of areas were found minimal (ICCs 0.6-3.4%). The results support universal interventions proportional to the need and disadvantage level of populations for the prevention and control of CMRFs, rather than any area specific interventions as the contextual effects were found minimal in the study region.

MeSH terms

  • Adolescent
  • Adult
  • Aged
  • Aged, 80 and over
  • Blood Glucose / analysis
  • Body Mass Index
  • Cardiovascular Diseases / blood*
  • Cardiovascular Diseases / epidemiology*
  • Cholesterol / blood
  • Cholesterol, HDL / blood
  • Creatinine / urine
  • Cross-Sectional Studies
  • Female
  • Geography
  • Glomerular Filtration Rate
  • Health Status Disparities*
  • Humans
  • Logistic Models
  • Male
  • Middle Aged
  • New South Wales / epidemiology
  • Obesity / complications
  • Obesity / genetics
  • Prevalence
  • ROC Curve
  • Risk
  • Risk Factors
  • Social Class
  • Young Adult

Substances

  • Blood Glucose
  • Cholesterol, HDL
  • Cholesterol
  • Creatinine