Neighborhood walkability and poverty predict excessive gestational weight gain : A cross-sectional study in New York City
© 2022 The Obesity Society..
OBJECTIVE: This study evaluated associations between neighborhood-level characteristics and gestational weight gain (GWG) in a population-level study of 2015 New York City births.
METHODS: Generalized linear mixed-effects models were used to estimate odds ratios (ORs) for associations between neighborhood-level characteristics (poverty, food environment, walkability) within 1 km of a residential Census block centroid and excessive or inadequate GWG compared with recommended GWG. All models were adjusted for individual-level sociodemographic characteristics.
RESULTS: Among the sample of 106,285 births, 41.8% had excessive GWG, and 26.3% had inadequate GWG. Residence in the highest versus lowest quartile of neighborhood poverty was associated with greater odds of excessive GWG (OR: 1.17, 95% CI: 1.08-1.26). Residence in neighborhoods in the quartile of highest walkability compared with the quartile of lowest walkability was associated with lower odds of excessive GWG (OR: 0.87, 95% CI: 0.81-0.93). Adjustment for prepregnancy BMI attenuated the associations for neighborhood poverty, but not for walkability. Neighborhood variables were not associated with inadequate GWG.
CONCLUSIONS: These analyses indicate that greater neighborhood walkability is associated with lower odds of excessive GWG, potentially from differences in pedestrian activity during pregnancy. This research provides further evidence for using urban design to support healthy weight status during pregnancy.
Medienart: |
E-Artikel |
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Erscheinungsjahr: |
2022 |
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Erschienen: |
2022 |
Enthalten in: |
Zur Gesamtaufnahme - volume:30 |
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Enthalten in: |
Obesity (Silver Spring, Md.) - 30(2022), 2 vom: 06. Feb., Seite 503-514 |
Sprache: |
Englisch |
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Beteiligte Personen: |
Kinsey, Eliza W [VerfasserIn] |
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Links: |
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Anmerkungen: |
Date Completed 14.04.2022 Date Revised 02.02.2023 published: Print-Electronic Citation Status MEDLINE |
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doi: |
10.1002/oby.23339 |
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funding: |
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Förderinstitution / Projekttitel: |
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PPN (Katalog-ID): |
NLM336026358 |
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500 | |a published: Print-Electronic | ||
500 | |a Citation Status MEDLINE | ||
520 | |a © 2022 The Obesity Society. | ||
520 | |a OBJECTIVE: This study evaluated associations between neighborhood-level characteristics and gestational weight gain (GWG) in a population-level study of 2015 New York City births | ||
520 | |a METHODS: Generalized linear mixed-effects models were used to estimate odds ratios (ORs) for associations between neighborhood-level characteristics (poverty, food environment, walkability) within 1 km of a residential Census block centroid and excessive or inadequate GWG compared with recommended GWG. All models were adjusted for individual-level sociodemographic characteristics | ||
520 | |a RESULTS: Among the sample of 106,285 births, 41.8% had excessive GWG, and 26.3% had inadequate GWG. Residence in the highest versus lowest quartile of neighborhood poverty was associated with greater odds of excessive GWG (OR: 1.17, 95% CI: 1.08-1.26). Residence in neighborhoods in the quartile of highest walkability compared with the quartile of lowest walkability was associated with lower odds of excessive GWG (OR: 0.87, 95% CI: 0.81-0.93). Adjustment for prepregnancy BMI attenuated the associations for neighborhood poverty, but not for walkability. Neighborhood variables were not associated with inadequate GWG | ||
520 | |a CONCLUSIONS: These analyses indicate that greater neighborhood walkability is associated with lower odds of excessive GWG, potentially from differences in pedestrian activity during pregnancy. This research provides further evidence for using urban design to support healthy weight status during pregnancy | ||
650 | 4 | |a Journal Article | |
650 | 4 | |a Research Support, N.I.H., Extramural | |
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700 | 1 | |a Huynh, Mary |e verfasserin |4 aut | |
700 | 1 | |a Van Wye, Gretchen |e verfasserin |4 aut | |
700 | 1 | |a Lovasi, Gina S |e verfasserin |4 aut | |
700 | 1 | |a Neckerman, Kathryn M |e verfasserin |4 aut | |
700 | 1 | |a Rundle, Andrew G |e verfasserin |4 aut | |
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