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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 <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.Results: HbA1c concentration 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 HbA1c concentration attributed to the overweight/obesity norm.Conclusions: 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. [ABSTRACT FROM AUTHOR]

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. [ABSTRACT FROM AUTHOR]

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 (HbA 1c ) 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. HbA 1c 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/m 2 ] and of physical inactivity [<150 min/week]) were aggregated from responses to a separate geocoded population survey. Built environment measures were public open space (POS) availability (proportion of buffer area) and walkability. Separate sets of multilevel models analysed different predictors of 10-year change in HbA 1c . Each model featured one local descriptive norm and one built environment variable with area-level education and individual-level covariates (age, sex, employment status, education, marital status, and smoking status). Interactions between local descriptive norms and built environment measures were assessed. HbA 1c increased over time. POS availability and local descriptive norms for overweight/obesity and physical inactivity were each associated with greater rates of HbA 1c increase. Greater walkability was associated with a reduced rate of HbA 1c increase, and reduced the influence of the overweight/obesity norm on the rate of increase in HbA 1c . Local descriptive health-related norms and features of the built environment predict 10-year change in HbA 1c . The impact of local descriptive norms can vary according to built environment features. Little researched thus far, local descriptive norms may play an important role in the evolution of HbA 1c and thus cardiometabolic risk, over time. Further empirical research on local descriptive norms is necessary to understand how residential environments shape chronic disease risk. [ABSTRACT FROM AUTHOR]

Rationale and Objectives: In epidemiological research, it is essential to account for the confounding effects of factors such as age, stage, and comorbidity for accurate prediction of cancer outcomes. There are several internationally developed and commonly used comorbidity indices. However, none are regarded as the gold-standard method. This study will assess and compare the predictive validity of established indices for use in a South Australian (SA) colorectal cancer (CRC) population against a local index. Furthermore, the prognostic influence of comorbidity on survival is investigated., Methods: A population-based study of patients diagnosed with CRC from 2003 to 2012 and linked to in-hospital data to retrieve comorbidity information was conducted. The predictive performance of established indices, Charlson comorbidity index (CCI), National Cancer Institute comorbidity index (NCI), Elixhauser comorbidity index (ECI), and C3 index was evaluated using the Fine and Gray competing risk regression and reported using measures of calibration and discrimination, area under the curve (AUC), and Brier score. Furthermore, to identify the optimal index, a local CRC comorbidity index (CRCCI) was also developed and its performance compared with the established indices., Results: Comorbidity models adjusted for age, sex, and stage showed that all indices were good predictors of mortality as measured by the AUC (CCI: 0.738, NCI: 0.742, ECI: 0.733, C3: 0.739). CRCCI had similar mortality prediction as established indices (CRCCI: 0.747). There was a significant increase in cumulative risk of noncancer and CRC-specific mortality with increase in comorbidity scores. The two most prevalent comorbidities were hypertension and diabetes., Conclusions: The existing indices are still valid for adjusting for comorbidity and accurately predicting mortality in an SA CRC population. Internationally developed indices are preferred when policymakers and researchers wish to compare local study results with those of studies (national and international) that have used these indices. Comorbidity is a predictor of mortality and should be considered when assessing CRC survival., (© 2019 John Wiley & Sons, Ltd.)

Objective: This study sought to assess whether changes in depressive symptoms, general health, and area-level socio-economic status (SES) were associated to changes over time in waist circumference and body mass index (BMI)., Methods: A total of 2871 adults (18 years or older), living in Adelaide (South Australia), were observed across three waves of data collection spanning ten years, with clinical measures of waist circumference, height and weight. Participants completed the Centre for Epidemiologic Studies Depression (CES-D) and Short Form 36 health questionnaires (SF-36 general health domain). An area-level SES measure, relative location factor, was derived from hedonic regression models using residential property features but blind to location. Growth curve models with latent variables were fitted to data., Results: Waist circumference, BMI and depressive symptoms increased over time. General health and relative location factor decreased. Worsening general health and depressive symptoms predicted worsening waist circumference and BMI trajectories in covariate-adjusted models. Diminishing relative location factor was negatively associated with waist circumference and BMI trajectories in unadjusted models only., Conclusions: Worsening depressive symptoms and general health predict increasing adiposity and suggest the development of unhealthful adiposity might be prevented by attention to negative changes in mental health and overall general health., Competing Interests: The authors declare that no competing interests exist.