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Background: Descriptive norms (what other people do) relate to individual-level dietary behaviour and health outcome including overweight and obesity. Descriptive norms vary across residential areas but the impact of spatial variation in norms on individual-level diet and health is poorly understood. This study assessed spatial associations between local descriptive norms for overweight/obesity and insufficient fruit intake (spatially-specific local prevalence), and individual-level dietary intakes (fruit, vegetable and sugary drinks) and 10-year change in body mass index (BMI) and glycosylated haemoglobin (HbA1c). Methods: HbA1c and BMI were clinically measured three times over 10 years for a population-based adult cohort (n = 4056) in Adelaide, South Australia. Local descriptive norms for both overweight/obesity and insufficient fruit intake specific to each cohort participant were calculated as the prevalence of these factors, constructed from geocoded population surveillance data aggregated for 1600 m road-network buffers centred on cohort participants' residential addresses. Latent growth models estimated the effect of local descriptive norms on dietary behaviours and change in HbA1c and BMI, accounting for spatial clustering and covariates (individual-level age, sex, smoking status, employment and education, and area-level median household income). Results: Local descriptive overweight/obesity norms were associated with individual-level fruit intake (inversely) and sugary drink consumption (positively), and worsening HbA1c and BMI. Spatially-specific local norms for insufficient fruit intake were associated with individual-level fruit intake (inversely) and sugary drink consumption (positively) and worsening HbA1c but not change in BMI. Individual-level fruit and vegetable intakes were not associated with change in HbA1c or BMI. Sugary drink consumption was also not associated with change in HbA1c but rather with increasing BMI. Conclusion: Adverse local descriptive norms for overweight/obesity and insufficient fruit intake are associated with unhealthful dietary intakes and worsening HbA1c and BMI. As such, spatial variation in lifestyle-related norms is an important consideration relevant to the design of population health interventions. Adverse local norms influence health behaviours and outcomes and stand to inhibit the effectiveness of traditional intervention efforts not spatially tailored to local population characteristics. Spatially targeted social de-normalisation strategies for regions with high levels of unhealthful norms may hold promise in concert with individual, environmental and policy intervention approaches. Refereed/Peer-reviewed

Associations between local-area residential features and glycosylated hemoglobin (HbA 1c ) may be mediated by individual-level health behaviors. Such indirect effects have rarely been tested. This study assessed whether individual-level self-reported physical activity mediated the influence of local-area descriptive norms and objectively expressed walkability on 10-year change in HbA 1c . HbA 1c was assessed three times for adults in a 10-year population-based biomedical cohort (n = 4056). Local-area norms specific to each participant were calculated, aggregating responses from a separate statewide surveillance survey for 1600 m road-network buffers centered on participant addresses (local prevalence of overweight/obesity (body mass index ≥25 kg/m 2 ) and physical inactivity ( < 150 min/week)). Separate latent growth models estimated direct and indirect (through physical activity) effects of local-area exposures on change in HbA 1c , accounting for spatial clustering and covariates (individual-level age, sex, smoking status, marital status, employment and education, and area-level median household income). HbA 1c worsened over time. Local-area norms directly and indirectly predicted worsening HbA 1c trajectories. Walkability was directly and indirectly protective of worsening HbA 1c . Local-area descriptive norms and walkability influence cardiometabolic risk trajectory through individual-level physical activity. Efforts to reduce population cardiometabolic risk should consider the extent of local-area unhealthful behavioral norms and walkability in tailoring strategies to improve physical activity. Refereed/Peer-reviewed

Descriptive norms vary between places. Spatial variation in health-related descriptive norms may predict individual-level health outcomes. Such relationships have rarely been investigated. This study assessed 10-year change in glycosylated haemoglobin (HbA1c) in relation to local descriptive norms for overweight/obesity (n = 1890) and physical inactivity (n = 1906) in models accounting for features of the built environment. HbA1c was measured three times over 10 years for a population-based biomedical cohort of adults in Adelaide, South Australia. Environmental exposures were expressed for cohort participants using 1600 m road-network buffers centred on participants' residential address. Local descriptive norms (prevalence of overweight/obesity [body mass index ≥25 kg/m2] and of physical inactivity [

Consistent associations have been observed between macro-level urban sprawl and overweight/obesity, but whether residential proximity to urban centres predicts adiposity change over time has not been established. Further, studies of local-area walkability and overweight/obesity have generated mixed results. This study examined 4-year change in adults' waist circumference in relation to proximity to city centre, proximity to closest suburban centre, and local-area walkability. Data were from adult participants (n = 2080) of a cohort study on chronic conditions and health risk factors in Adelaide, Australia. Baseline data were collected in 2000–03 with a follow-up in 2005–06. Multilevel regression models examined in 2015 the independent and joint associations of the three environmental measures with change in waist circumference, accounting for socio-demographic covariates. On average, waist circumference rose by 1.8 cm over approximately 4 years. Greater distance to city centre was associated with a greater increase in waist circumference. Participants living in distal areas (20 km or further from city centre) had a greater increase in waist circumference (mean increase: 2.4 cm) compared to those in proximal areas (9 km or less, mean increase: 1.2 cm). Counterintuitively, living in the vicinity of a suburban centre was associated with a greater increase in adiposity. Local-area walkability was not significantly associated with the outcome. Residential proximity to city centre appears to be protective against excessive increases in waist circumference. Controlled development and targeted interventions in the urban fringe may be needed to tackle obesity. Additional research needs to assess behaviours that mediate relationships between sprawl and obesity. Refereed/Peer-reviewed

Background: Efforts to reduce cardiometabolic disease often target individual-level risk factors. However, individual dietary behaviour and body mass index (BMI) may be influenced by the geographic patterning of food sources and local-area norms. Norms figure prominently in socio-behavioural theories yet spatial variations in norms have rarely been investigated in predicting individual health outcomes. This study assessed the contributions of fast-food availability and local-area norms for dietary behaviour and BMI to 10-year change in cardiometabolic risk. Methods: Cardiometabolic risk, expressed using a validated continuous clinical index, was calculated using data from a population-based biomedical cohort in Adelaide, South Australia over three waves of follow up, 2000—2010. Local-area exposures were defined for participants (n = 2228) using 1600m road-network buffers. Local-area norms (proportion residents with BMI ≥25 kg/m2 or not meeting fruit intake of ≥2 serves/day) were aggregated from individual-level self-reported data from a state-wide surveillance system, pooled across 2006—2010 for the study area. Fast-food availability (count of outlets) was extracted from a retail database. Separate multilevel models each featuring one local-area norm with fast-food availability as predictors of 10-year change in cardiometabolic risk were adjusted for area-level socioeconomic status and individual-level covariates. Results: In separate models including fast-food availability, greater local-area proportion of residents with BMI ≥25 kg/m2 or not meeting fruit intake of ≥2 serves/day predicted worsening cardiometabolic risk across 10-years of follow up. Fast-food availability was not related to cardiometabolic risk. There was no evidence of interaction effects between local-area exposures. Conclusions: Local-area norms (prevalence of unhealthful BMI and fruit consumption) reflect compositional population characteristics. Fast-food availability reflects built environmental context. In this study, only compositional norms, not fast-food context, predicted 10-year worsening of cardiometabolic risk. The implication of this longitudinal investigation is that the targeting of compositional norms might be more important than the targeting of fast-food context.

Background: 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 HbA1c were moderated by food resource availability. Methods: 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