FRINK Linked Data Fragments server

Matches in SemOpenAlex for { <https://semopenalex.org/work/W4200188994> ?p ?o ?g. }

• W4200188994 endingPage "107015" @default.
• W4200188994 startingPage "107015" @default.
• W4200188994 abstract "Characteristics of the urban environment may contain upstream drivers of obesity. However, research is lacking that considers the combination of environmental factors simultaneously.We aimed to explore what environmental factors of the urban exposome are related to body mass index (BMI), and evaluated the consistency of findings across multiple statistical approaches.A cross-sectional analysis was conducted using baseline data from 14,829 participants of the Occupational and Environmental Health Cohort study. BMI was obtained from self-reported height and weight. Geocoded exposures linked to individual home addresses (using 6-digit postcode) of 86 environmental factors were estimated, including air pollution, traffic noise, green-space, built environmental and neighborhood socio-demographic characteristics. Exposure-obesity associations were identified using the following approaches: sparse group Partial Least Squares, Bayesian Model Averaging, penalized regression using the Minimax Concave Penalty, Generalized Additive Model-based boosting Random Forest, Extreme Gradient Boosting, and Multiple Linear Regression, as the most conventional approach. The models were adjusted for individual socio-demographic variables. Environmental factors were ranked according to variable importance scores attributed by each approach and median ranks were calculated across these scores to identify the most consistent associations.The most consistent environmental factors associated with BMI were the average neighborhood value of the homes, oxidative potential of particulate matter air pollution (OP), healthy food outlets in the neighborhood (5 km buffer), low-income neighborhoods, and one-person households in the neighborhood. Higher BMI levels were observed in low-income neighborhoods, with lower average house values, lower share of one-person households and smaller amount of healthy food retailers. Higher BMI levels were observed in low-income neighborhoods, with lower average house values, lower share of one-person households, smaller amounts of healthy food retailers and higher OP levels. Across the approaches, we observed consistent patterns of results based on model's capacity to incorporate linear or nonlinear associations.The pluralistic analysis on environmental obesogens strengthens the existing evidence on the role of neighborhood socioeconomic position, urbanicity and air pollution." @default.
• W4200188994 created "2021-12-31" @default.
• W4200188994 creator A5000720907 @default.
• W4200188994 creator A5007877538 @default.
• W4200188994 creator A5026547698 @default.
• W4200188994 creator A5027340392 @default.
• W4200188994 creator A5031468653 @default.
• W4200188994 creator A5045826473 @default.
• W4200188994 creator A5049275296 @default.
• W4200188994 creator A5085784987 @default.
• W4200188994 date "2022-01-01" @default.
• W4200188994 modified "2023-10-05" @default.
• W4200188994 title "Machine learning approaches to characterize the obesogenic urban exposome" @default.
• W4200188994 cites W1596444848 @default.
• W4200188994 cites W1835963183 @default.
• W4200188994 cites W1843935513 @default.
• W4200188994 cites W1969312874 @default.
• W4200188994 cites W1991350060 @default.
• W4200188994 cites W1998561407 @default.
• W4200188994 cites W1998666778 @default.
• W4200188994 cites W2021803540 @default.
• W4200188994 cites W2025266808 @default.
• W4200188994 cites W2062970435 @default.
• W4200188994 cites W2066544083 @default.
• W4200188994 cites W2071721660 @default.
• W4200188994 cites W2094588935 @default.
• W4200188994 cites W2132712784 @default.
• W4200188994 cites W2134843796 @default.
• W4200188994 cites W2138028307 @default.
• W4200188994 cites W2142912905 @default.
• W4200188994 cites W2142930729 @default.
• W4200188994 cites W2144275855 @default.
• W4200188994 cites W2148269779 @default.
• W4200188994 cites W2153630285 @default.
• W4200188994 cites W2154089768 @default.
• W4200188994 cites W2154491486 @default.
• W4200188994 cites W2157426745 @default.
• W4200188994 cites W2276020200 @default.
• W4200188994 cites W2322754609 @default.
• W4200188994 cites W2401468526 @default.
• W4200188994 cites W2408087945 @default.
• W4200188994 cites W2487898712 @default.
• W4200188994 cites W2562162676 @default.
• W4200188994 cites W2604366851 @default.
• W4200188994 cites W2617904387 @default.
• W4200188994 cites W2649137640 @default.
• W4200188994 cites W2735609371 @default.
• W4200188994 cites W2758198687 @default.
• W4200188994 cites W2760883534 @default.
• W4200188994 cites W2789894922 @default.
• W4200188994 cites W2792748998 @default.
• W4200188994 cites W2801705291 @default.
• W4200188994 cites W2803235038 @default.
• W4200188994 cites W2804053021 @default.
• W4200188994 cites W2806446597 @default.
• W4200188994 cites W2893673243 @default.
• W4200188994 cites W2902131310 @default.
• W4200188994 cites W2904596032 @default.
• W4200188994 cites W2912750253 @default.
• W4200188994 cites W2986588406 @default.
• W4200188994 cites W3015281700 @default.
• W4200188994 cites W3027341006 @default.
• W4200188994 cites W3037405412 @default.
• W4200188994 cites W3039020937 @default.
• W4200188994 cites W3047993924 @default.
• W4200188994 cites W3102027041 @default.
• W4200188994 cites W3102476541 @default.
• W4200188994 cites W3106108064 @default.
• W4200188994 cites W3115102688 @default.
• W4200188994 cites W3126914874 @default.
• W4200188994 cites W3138148883 @default.
• W4200188994 doi "https://doi.org/10.1016/j.envint.2021.107015" @default.
• W4200188994 hasPubMedId "https://pubmed.ncbi.nlm.nih.gov/34991269" @default.
• W4200188994 hasPublicationYear "2022" @default.
• W4200188994 type Work @default.
• W4200188994 citedByCount "14" @default.
• W4200188994 countsByYear W42001889942022 @default.
• W4200188994 countsByYear W42001889942023 @default.
• W4200188994 crossrefType "journal-article" @default.
• W4200188994 hasAuthorship W4200188994A5000720907 @default.
• W4200188994 hasAuthorship W4200188994A5007877538 @default.
• W4200188994 hasAuthorship W4200188994A5026547698 @default.
• W4200188994 hasAuthorship W4200188994A5027340392 @default.
• W4200188994 hasAuthorship W4200188994A5031468653 @default.
• W4200188994 hasAuthorship W4200188994A5045826473 @default.
• W4200188994 hasAuthorship W4200188994A5049275296 @default.
• W4200188994 hasAuthorship W4200188994A5085784987 @default.
• W4200188994 hasBestOaLocation W42001889941 @default.
• W4200188994 hasConcept C105795698 @default.
• W4200188994 hasConcept C119709500 @default.
• W4200188994 hasConcept C119857082 @default.
• W4200188994 hasConcept C126322002 @default.
• W4200188994 hasConcept C142724271 @default.
• W4200188994 hasConcept C144024400 @default.
• W4200188994 hasConcept C146508145 @default.
• W4200188994 hasConcept C148803439 @default.
• W4200188994 hasConcept C149923435 @default.
• W4200188994 hasConcept C152877465 @default.

• next