Association of Neighborhood-Level Socioeconomic Measures With Cognition and Dementia Risk in Australian Adults

Key Points Question Is neighborhood-level socioeconomic status (SES) associated with differences in cognition and dementia risk scores? Findings In this cross-sectional study of 4656 Australian adults aged 40 to 70 years enrolled in the population-based Healthy Brain Project cohort, higher neighborhood-level SES was associated with better memory and lower dementia risk scores. Meaning This study’s findings suggest that dementia research would benefit from including participants living in areas with lower SES to better understand relevant factors and potential interventions.

The IRSAD is derived from a combination of 11 socioeconomic variables, such as income, education, unemployment rates, occupational skills, disability, vehicle ownership, internet connection, family structure (e.g., one parent with a dependent), and housing arrangements (see eTable 1). These variables are expressed by percentage (i.e. % of the population in an area that own a vehicle), and were weighted using Principal Component Analysis by the ABS to proportionately determine the index score per neighbourhood. 1 We used the residential postcode provided by each participant to derive an IRSAD score that ranked participants according to deciles of n-SES (higher deciles indicate greater advantage).
The IRSAD scores and deciles of n-SES are comparable to other measures that describe regions by socioeconomic variables used in other countries. For example, the Area Deprivation Index (ADI) was derived from American census data and similarly utilises the percentage of population and median data to score advantage from SES variables (including education, income, housing and household characteristics). Additionally, the European Deprivation Index (EDI) is used to describe a countryspecific ecological deprivation index at a small area level, incorporating population statistics, income and living conditions.

Personal SES estimations.
Two authors independently coded participants' occupations into the Australian and New Zealand Standard Classification of Occupations (ANZSCO; ABS 2006), with any discrepancies resolved by consensus. Each occupation has a corresponding weighted AUSEI06 score. 3 Where possible, responses were coded into the level of the ANZSCO minor groups, otherwise, a superordinate category was used (i.e., sub-major or major groups). Each occupational group has a corresponding AUSEI06 value which was used as the measure of personal SES. For participants who had retired, we coded the AUSEI06 score using their last occupation prior to retirement.

Measurement of cognition.
The CBB consists of four tests: Detection (DET), Identification (IDN), One Card Learning (OCL), and One-Back (OBK). Briefly, DET is a simple reaction time task shown to measure psychomotor function, and IDN is a choice reaction time task shown to measure visual attention. The primary outcome for DET and IDN was reaction time in milliseconds, with lower scores indicating faster task completion.
OCL is a continuous visual recognition task set within a pattern separation model, and OBK is a task of working memory. The primary outcome for OCL and OBK was the proportion of correct responses, normalized using an arcsine square-root transformation, with higher scores indicating better performance. The Attention Composite was computed by standardizing and averaging the DET and   Body Mass Index. Components of Age, Education, Sex were scored using demographic data collected. Hypercholesterinemia was scored according to participant self-reports of high cholesterol diagnosis in the Healthy History questionnaires rather than quantitative blood work (without diagnosis substituted for ≤6.5 mmol/L and scored 0; with diagnosis substituted for >6.5 mmol/L and scored 2). Hypertension and BMI were also scored using data from Health History questionaries. Lifestyle relating to physical activity levels was captured using the International Physical Activity Questionnaire (IPAQ 4 ). Physical activity was scored using the IPAQ 'Active' categorical score ("High" or "Moderate" activity levels corresponded to "Active" and scored 0; a "Low" activity level corresponded to "Inactive" and scored 1). The scores from each component were summed to acquire the CAIDE Dementia Risk total score.