Local descriptive body weight and dietary norms, food availability, and 10-year change in glycosylated haemoglobin in an Australian population-based biomedical cohort.
Individual-level health outcomes are shaped by environmental risk conditions. Norms figure prominently in socio-behavioural theories yet spatial variations in health-related norms have rarely been investigated as environmental risk conditions. This study assessed: 1) the contributions of local descriptive norms for overweight/obesity and dietary behaviour to 10-year change in glycosylated haemoglobin (HbA1c), accounting for food resource availability; and 2) whether associations between local descriptive norms and HbA1cwere moderated by food resource availability.



HbA1c, representing cardiometabolic risk, was measured three times over 10 years for a population-based biomedical cohort of adults in Adelaide, South Australia. Residential environmental exposures were defined using 1600 m participant-centred road-network buffers. Local descriptive norms for overweight/obesity and insufficient fruit intake (proportion of residents with BMI ≥ 25 kg/m2[n = 1890] or fruit intake of <2 serves/day [n = 1945], respectively) were aggregated from responses to a separate geocoded population survey. Fast-food and healthful food resource availability (counts) were extracted from a retail database. Separate sets of multilevel models included different predictors, one local descriptive norm and either fast-food or healthful food resource availability, with area-level education and individual-level covariates (age, sex, employment status, education, marital status, and smoking status). Interactions between local descriptive norms and food resource availability were tested.



HbA1cconcentration rose over time. Local descriptive norms for overweight/obesity and insufficient fruit intake predicted greater rates of increase in HbA1c. Neither fast-food nor healthful food resource availability were associated with change in HbA1c. Greater healthful food resource availability reduced the rate of increase in HbA1cconcentration attributed to the overweight/obesity norm.



Local descriptive health-related norms, not food resource availability, predicted 10-year change in HbA1c. Null findings for food resource availability may reflect a sufficiency or minimum threshold level of resources such that availability poses no barrier to obtaining healthful or unhealthful foods for this region. However, the influence of local descriptive norms varied according to food resource availability in effects on HbA1c. Local descriptive health-related norms have received little attention thus far but are important influences on individual cardiometabolic risk. Further research is needed to explore how local descriptive norms contribute to chronic disease risk and outcomes.
Spatial Epidemiology and Evaluation Research Group, School of Health Sciences and Centre for Population Health Research, University of South Australia, IPC CWE-48, GPO Box 2471, Adelaide, South Australia, 5001, Australia. suzanne.carroll@unisa.edu.au.
Suzanne J
SJ
Carroll
Spatial Epidemiology and Evaluation Research Group, School of Health Sciences and Centre for Population Health Research, University of South Australia, IPC CWE-48, GPO Box 2471, Adelaide, South Australia, 5001, Australia.|Research Centre of the Douglas Mental Health University Institute, Verdun, Québec, Canada.
Catherine
C
Paquet
Spatial Epidemiology and Evaluation Research Group, School of Health Sciences and Centre for Population Health Research, University of South Australia, IPC CWE-48, GPO Box 2471, Adelaide, South Australia, 5001, Australia.
Natasha J
NJ
Howard
Spatial Epidemiology and Evaluation Research Group, School of Health Sciences and Centre for Population Health Research, University of South Australia, IPC CWE-48, GPO Box 2471, Adelaide, South Australia, 5001, Australia.
Neil T
NT
Coffee
Discipline of Medicine, The University of Adelaide, Adelaide, South Australia, Australia.
Robert J
RJ
Adams
Discipline of Medicine, The University of Adelaide, Adelaide, South Australia, Australia.
Anne W
AW
Taylor
Spatial Epidemiology and Evaluation Research Group, School of Health Sciences and Centre for Population Health Research, University of South Australia, IPC CWE-48, GPO Box 2471, Adelaide, South Australia, 5001, Australia.
Theo
T
Niyonsenga
Spatial Epidemiology and Evaluation Research Group, School of Health Sciences and Centre for Population Health Research, University of South Australia, IPC CWE-48, GPO Box 2471, Adelaide, South Australia, 5001, Australia.|Department of Medicine, The University of Melbourne, St. Vincent's Hospital, Melbourne, VIC, Australia.|South Australian Health & Medical Research Institute, Adelaide, South Australia, Australia.
Mark
M
Daniel
D001835:Body Weight / Q000502:physiology*; D015331:Cohort Studies; D004032:Diet / Q000379:methods* / Q000706:statistics & numerical data; D004777:Environment; D005260:Female; D005500:Follow-Up Studies; D005523:Food Supply / Q000706:statistics & numerical data*; D006442:Glycated Hemoglobin / Q000032:analysis*; D006801:Humans; D008297:Male; D008875:Middle Aged; D050177:Overweight / Q000097:blood* / Q000453:epidemiology*; D011446:Prospective Studies; D013021:South Australia / Q000453:epidemiology
D006442:Glycated Hemoglobin
Built environment; Cardiometabolic risk; Descriptive norms; Food environment; Multilevel models