We investigated whether residential environment characteristics related to food (unhealthful/healthful food sources ratio), walkability and public open spaces (POS; number, median size, greenness and type) were associated with incidence of four cardio-metabolic risk factors (pre-diabetes/diabetes, hypertension, dyslipidaemia, abdominal obesity) in a biomedical cohort (n=3205). Results revealed that the risk of developing pre-diabetes/diabetes was lower for participants in areas with larger POS and greater walkability. Incident abdominal obesity was positively associated with the unhealthful food environment index. No associations were found with hypertension or dyslipidaemia. Results provide new evidence for specific, prospective associations between the built environment and cardio-metabolic risk factors.
Aggregated area-level characteristics make modest, but significant independent contributions to smoking, obesity and quality of life, but not for other health outcomes.
Walkability of residential environments has been associated with more walking. Given the health benefits of walking, it is expected that people living in locations with higher measured walkability should have a lower risk of cardiometabolic diseases. This study tested the hypothesis that higher walkability was associated with a lower cardiometabolic risk (CMR) for two administrative spatial units and three road buffers. Data were from the North West Adelaide Health Study first wave of data collected between 2000 and 2003. CMR was expressed as a cumulative sum of six clinical risk markers, selected to reflect components of the metabolic syndrome. Walkability was based on an established methodology and operationalised as dwelling density, intersection density, land-use mix and retail footprint. Walkability was associated with lower CMR for the three road buffer representations of the built environment but not for the two administrative spatial units. This may indicate a limitation in the use of administrative spatial units for analyses of walkability and health outcomes.
Residents of areas with lower socioeconomic status (SES) are known to be less physically active during leisure time. Neighborhood walkability has been shown to be related to recreational walking equally in low and high SES areas. This crosssectional study tested whether associations of specific environmental attributes, measured objectively and subjectively, with walking for recreation were moderated by area-level SES. The data of the North West Adelaide Health Study collected in 2007 (n=1500, mean age 57) were used. Self-reported walking frequency was the outcome of the study. Environmental exposure measures included objectively measured walkability components (residential density, intersection density, land use mix, and net retail area ratio) and perceived attributes (access to destinations, neighborhood esthetics, walking infrastructure, traffic/barriers, and crime safety). Participants' suburbs were categorized into low and high SES areas using an indicator of socioeconomic disadvantage. Low SES areas had lower scores in residential density, neighborhood esthetics, walking infrastructure, traffic/barriers, and crime safety. Recreational walking was associated with residential density, access to destinations, esthetics, traffic/barriers, and crime safety. Effect modification was observed for two attributes (out of nine): residential density was associated with walking only in low SES areas, while walking infrastructure was associated with walking only in high SES areas. The associations of neighborhood environmental attributes with recreational walking were largely consistent across SES groups. However, low SES areas were disadvantaged in most perceived environmental attributes related to recreational walking. Improving such attributes in low SES neighborhoods may help close socioeconomic disparities in leisure time physical activity.
BackgroundResidential property is reported as the most valuable asset people will own and therefore provides the potential to be used as a socio-economic status (SES) measure. Location is generally recognised as the most important determinant of residential property value.Extending the well-established relationship between poor health and socio-economic disadvantage and the role of residential property in the overall wealth of individuals, this study tested the predictive value of the Relative Location Factor (RLF), a SES measure designed to reflect the relationship between location and residential property value, and six cardiometabolic disease risk factors, central obesity, hypertriglyceridemia, reduced high density lipoprotein (HDL), hypertension, impaired fasting glucose, and high low density lipoprotein (LDL). These risk factors were also summed and expressed as a cumulative cardiometabolic risk (CMR) score.MethodsRLF was calculated using a global hedonic regression model from residential property sales transaction data based upon several residential property characteristics, but deliberately blind to location, to predict the selling price of the property. The predicted selling price was divided by the actual selling price and the results interpolated across the study area and classified as tertiles. The measures used to calculate CMR were collected via clinic visits from a population-based cohort study. Models with individual risk factors and the cumulative cardiometabolic risk (CMR) score as dependent variables were respectively tested using log binomial and Poisson generalised linear models.ResultsA statistically significant relationship was found between RLF, the cumulative CMR score and all but one of the risk factors. In all cases, participants in the most advantaged and intermediate group had a lower risk for cardio-metabolic diseases. For the CMR score the RR for the most advantaged was 19% lower (RR = 0.81; CI 0.76-0.86; p <0.0001) and the middle group was 9% lower (RR = 0.91; CI 0.86-0.95; p <0.0001) than the least advantaged group.ConclusionsThis paper advances the understanding of the nexus between place, health and SES by providing an objective spatially informed SES measure for testing health outcomes and reported a robust association between RLF and several health measures.
BackgroundIndicators of cardiometabolic risk typically include non-clinical factors (e.g., smoking). While the incorporation of non-clinical factors can improve absolute risk prediction, it is impossible to study the contribution of non-clinical factors when they are both predictors and part of the outcome measure. Metabolic syndrome, incorporating only clinical measures, seems a solution yet provides no information on risk severity. The aims of this study were: 1) to construct two continuous clinical indices of cardiometabolic risk (cCICRs), and assess their accuracy in predicting 10-year incident cardiovascular disease and/or type 2 diabetes; and 2) to compare the predictive accuracies of these cCICRs with existing risk indicators that incorporate non-clinical factors (Framingham Risk Scores).MethodsData from a population-based biomedical cohort (n = 4056) were used to construct two cCICRs from waist circumference, mean arteriole pressure, fasting glucose, triglycerides and high density lipoprotein: 1) the mean of standardised risk factors (cCICR-Z); and 2) the weighted mean of the two first principal components from principal component analysis (cCICR-PCA). The predictive accuracies of the two cCICRs and the Framingham Risk Scores were assessed and compared using ROC curves.ResultsBoth cCICRs demonstrated moderate accuracy (AUCs 0.72 – 0.76) in predicting incident cardiovascular disease and/or type 2 diabetes, among men and women. There were no significant differences between the predictive accuracies of the cCICRs and the Framingham Risk Scores.ConclusionscCICRs may be useful in research investigating associations between non-clinical factors and health by providing suitable alternatives to current risk indicators which include non-clinical factors.
scite is a Brooklyn-based organization that helps researchers better discover and understand research articles through Smart Citations–citations that display the context of the citation and describe whether the article provides supporting or contrasting evidence. scite is used by students and researchers from around the world and is funded in part by the National Science Foundation and the National Institute on Drug Abuse of the National Institutes of Health.