title: Modelling preventive effectiveness to estimate the equity tipping point: at what coverage can individual preventive interventions reduce socioeconomic disparities in diabetes risk?
abstract: BACKGROUND
  Most individual preventive therapies potentially narrow or widen health disparities depending on the difference in community effectiveness across socioeconomic position (SEP). The equity tipping point (defined as the point at which health disparities become larger) can be calculated by varying components of community effectiveness such as baseline risk of disease, intervention coverage and/or intervention efficacy across SEP.
  
  
  METHODS
  We used a simple modelling approach to estimate the community effectiveness of diabetes prevention across SEP in Canada under different scenarios of intervention coverage.
  
  
  RESULTS
  Five-year baseline diabetes risk differed between the lowest and highest income groups by 1.76%. Assuming complete coverage across all income groups, the difference was reduced to 0.90% (144 000 cases prevented) with lifestyle interventions and 1.24% (88 100 cases prevented) with pharmacotherapy. The equity tipping point was estimated to be a coverage difference of 30% for preventive interventions (100% and 70% coverage among the highest and lowest income earners, respectively).
  
  
  CONCLUSIONS
  Disparities in diabetes risk could be measurably reduced if existing interventions were equally adopted across SEP. However, disparities in coverage could lead to increased inequity in risk. Simple modelling approaches can be used to examine the community effectiveness of individual preventive interventions and their potential to reduce (or increase) disparities. The equity tipping point can be used as a critical threshold for disparities analyses.
authors.affiliation: Institute for Clinical Evaluative Sciences, Toronto, Ontario, Canada; Dalla Lana School of Public Health, University of Toronto, Toronto, Ontario, Canada; Ottawa Hospital Research Institute, Ottawa, Ontario, Canada; Statistics Canada, Ottawa, Ontario, Canada; Department of Family Medicine and Department of Epidemiology and Community Medicine, University of Ottawa, Ottawa, Ontario, Canada.
authors.forename: D G
authors.initials: DG
authors.lastname: Manuel
authors.affiliation: Institute for Clinical Evaluative Sciences, Toronto, Ontario, Canada.
authors.forename: T H
authors.initials: TH
authors.lastname: Ho
authors.affiliation: Department of Epidemiology, Biostatistics and Occupational Health, McGill University, Montréal, Quebec, Canada.
authors.forename: S
authors.initials: S
authors.lastname: Harper
authors.affiliation: Institute for Clinical Evaluative Sciences, Toronto, Ontario, Canada; Department of Health Policy, Management, and Evaluation, University of Toronto, Toronto, Ontario, Canada.
authors.forename: G M
authors.initials: GM
authors.lastname: Anderson
authors.affiliation: School of Population Health and Clinical Sciences, University of Adelaide, Adelaide, Australia; Department of Social and Community Medicine, University of Bristol, Bristol, United Kingdom.
authors.forename: J
authors.initials: J
authors.lastname: Lynch
authors.affiliation: Institute for Clinical Evaluative Sciences, Toronto, Ontario, Canada; Dalla Lana School of Public Health, University of Toronto, Toronto, Ontario, Canada; Public Health Ontario, Toronto, Ontario, Canada.
authors.forename: L C
authors.initials: LC
authors.lastname: Rosella
mesh_terms: D000328:Adult; D000368:Aged; D002170:Canada; D003430:Cross-Sectional Studies; D003924:Diabetes Mellitus, Type 2 / Q000517:prevention & control*; D004032:Diet; D015444:Exercise; D005260:Female; D054624:Health Status Disparities; D006801:Humans; D007004:Hypoglycemic Agents / Q000627:therapeutic use*; D008019:Life Style; D008297:Male; D008875:Middle Aged; D008962:Models, Theoretical; D061366:Numbers Needed To Treat; D009765:Obesity / Q000517:prevention & control; D011322:Primary Prevention; D018570:Risk Assessment; D012959:Socioeconomic Factors; D055815:Young Adult
chemical_list: D007004:Hypoglycemic Agents
keywords: diabetes; health impact assessment; inequalities; public health