ArticleEnvironmental health : a global access science source2022
The neighbourhood environment and profiles of the metabolic syndrome.
Article in Environmental health : a global access science source, 2022. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 5 papers.
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The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.
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Who cites it
5 citing papers in PubMed, 14 citations in OpenAlex.
- Beyond green: how city greenspace shapes health outcomes in China.BMC public health · 2026Article
- A Review of R Packages for Bayesian Model-based Clustering of High-dimensional Multivariate Environmental Exposures.Current environmental health reports · 2026Review
- Social environments and lifestyles linked to mortality and future health risks in metabolic syndrome: evidence from UK and US nationwide cohort studies.BMJ public health · 2026Article
- Effect of green space in the workplace on hearing thresholds in noise exposed population.Scientific reports · 2025Article
- Multilevel Mediators on the Associations of Neighborhood Social Environmental Factors and Severity of Metabolic Syndrome: The Jackson Heart Study.Journal of the American Heart Association · 2025Article
Corrections and comments
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Authors and funding
8 authors at 7 institutions in 3 countries.
Funding
No grant is acknowledged in the PubMed record.
Abstract
backgroundThere is a dearth of studies on how neighbourhood environmental attributes relate to the metabolic syndrome (MetS) and profiles of MetS components. We examined the associations of interrelated aspects of the neighbourhood environment, including air pollution, with MetS status and profiles of MetS components.
methodsWe used socio-demographic and MetS-related data from 3681 urban adults who participated in the 3rd wave of the Australian Diabetes, Obesity and Lifestyle Study. Neighbourhood environmental attributes included area socio-economic status (SES), population density, street intersection density, non-commercial land use mix, percentages of commercial land, parkland and blue space. Annual average concentrations of NO
resultsLCA yielded three latent classes, one including only participants without MetS ("Lower probability of MetS components" profile). The other two classes/profiles, consisting of participants with and without MetS, were "Medium-to-high probability of high fasting blood glucose, waist circumference and blood pressure" and "Higher probability of MetS components". Area SES was the only significant predictor of MetS status: participants from high SES areas were less likely to have MetS. Area SES, percentage of commercial land and NO
conclusionsThis study supports the utility of operationalising MetS as a combination of latent classes of MetS components and MetS status in studies of environmental correlates. Higher socio-economic advantage, good access to commercial services and low air pollution levels appear to independently contribute to different facets of metabolic health. Future research needs to consider conducting longitudinal studies using fine-grained environmental measures that more accurately characterise the neighbourhood environment in relation to behaviours or other mechanisms related to MetS and its components.
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Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.