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Associations of Urban Environment Features with Hypertension and Blood Pressure across 230 Latin American Cities.

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Title: Associations of Urban Environment Features with Hypertension and Blood Pressure across 230 Latin American Cities.
Authors: Avila-Palencia, Ione1 ia384@drexel.edu, Rodríguez, Daniel A.2,3, Miranda, J. Jaime4, Moore, Kari1, Gouveia, Nelson5, Moran, Mika R.6, Caiaffa, Waleska T.7, Diez Roux, Ana V.1
Source: Environmental Health Perspectives. Feb2022, Vol. 130 Issue 2, p027010-1-027010-10. 10p. 4 Charts.
Subject Terms: *Population density, *Built environment, *Environmental health, *Plants, Hypertension risk factors, Hypertension epidemiology, Confidence intervals, Systolic blood pressure, Cross-sectional method, Multiple regression analysis, Age distribution, Population geography, Social context, Risk assessment, Socioeconomic factors, Sex distribution, Descriptive statistics, Disease prevalence, Intersectionality, Metropolitan areas, Odds ratio, Blood pressure measurement, Data analysis software, Educational attainment
Geographic Terms: Colombia, El Salvador, Guatemala, Peru, Argentina, Chile, Brazil, Mexico, Latin America
Abstract: BACKGROUND: Features of the urban physical environment may be linked to the development of high blood pressure, a leading risk factor for global burden of disease. OBJECTIVES: We examined associations of urban physical environment features with hypertension and blood pressure measures in adults across 230 Latin American cities. METHODS: In this cross-sectional study we used health, social, and built environment data from the SALud URBana en América Latina (SALURBAL) project. The individual-level outcomes were hypertension and levels of systolic and diastolic blood pressure. The exposures were city and subcity built environment features, mass transit infrastructure, and green space. Odds ratios (ORs) and mean differences and 95% confidence intervals (CIs) were estimated using multilevel logistic and linear regression models, with single- and multiple-exposure models adjusted for individual-level age, sex, education, and subcity educational attainment. RESULTS: A total of 109,176 participants from 230 cities and eight countries were included in the hypertension analyses and 50,228 participants from 194 cities and seven countries were included in the blood pressure measures analyses. Participants were 18–97 years of age. In multiple-exposure models, higher city fragmentation was associated with higher odds of having hypertension (OR per standard deviation (SD) increase = 1.11; 95% CI: 1.01, 1.21); presence (vs. no presence) of mass transit in the city was associated with higher odds of having hypertension (OR = 1.30; 95% CI: 1.09, 1.54); higher subcity population density was associated with lower odds of having hypertension (OR per SD increase = 0.90; 95% CI: 0.85, 0.94); and higher subcity intersection density was associated with higher odds of having hypertension [OR per SD increase = 1.09; 95% CI: 1.04, 1.15). The presence of mass transit was also associated with slightly higher systolic and diastolic blood pressure in multiple-exposure models adjusted for treatment. Except for the association between intersection density and hypertension, associations were attenuated after adjustment for country. An inverse association of greenness with continuous blood pressure emerged after country adjustment. DISCUSSION: Our results suggest that urban physical environment features—such as fragmentation, mass transit, population density, and intersection density—may be related to hypertension in Latin American cities. Reducing chronic disease risks in the growing urban areas of Latin America may require attention to integrated management of urban design and transport planning. [ABSTRACT FROM AUTHOR]
Copyright of Environmental Health Perspectives is the property of National Institute of Environmental Health Sciences and its content may not be copied or emailed to multiple sites without the copyright holder's express written permission. Additionally, content may not be used with any artificial intelligence tools or machine learning technologies. However, users may print, download, or email articles for individual use. This abstract may be abridged. No warranty is given about the accuracy of the copy. Users should refer to the original published version of the material for the full abstract. (Copyright applies to all Abstracts.)
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  Data: Associations of Urban Environment Features with Hypertension and Blood Pressure across 230 Latin American Cities.
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  Data: <searchLink fieldCode="AR" term="%22Avila-Palencia%2C+Ione%22">Avila-Palencia, Ione</searchLink><relatesTo>1</relatesTo><i> ia384@drexel.edu</i><br /><searchLink fieldCode="AR" term="%22Rodríguez%2C+Daniel+A%2E%22">Rodríguez, Daniel A.</searchLink><relatesTo>2,3</relatesTo><br /><searchLink fieldCode="AR" term="%22Miranda%2C+J%2E+Jaime%22">Miranda, J. Jaime</searchLink><relatesTo>4</relatesTo><br /><searchLink fieldCode="AR" term="%22Moore%2C+Kari%22">Moore, Kari</searchLink><relatesTo>1</relatesTo><br /><searchLink fieldCode="AR" term="%22Gouveia%2C+Nelson%22">Gouveia, Nelson</searchLink><relatesTo>5</relatesTo><br /><searchLink fieldCode="AR" term="%22Moran%2C+Mika+R%2E%22">Moran, Mika R.</searchLink><relatesTo>6</relatesTo><br /><searchLink fieldCode="AR" term="%22Caiaffa%2C+Waleska+T%2E%22">Caiaffa, Waleska T.</searchLink><relatesTo>7</relatesTo><br /><searchLink fieldCode="AR" term="%22Diez+Roux%2C+Ana+V%2E%22">Diez Roux, Ana V.</searchLink><relatesTo>1</relatesTo>
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  Data: <searchLink fieldCode="JN" term="%22Environmental+Health+Perspectives%22">Environmental Health Perspectives</searchLink>. Feb2022, Vol. 130 Issue 2, p027010-1-027010-10. 10p. 4 Charts.
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  Data: *<searchLink fieldCode="DE" term="%22Population+density%22">Population density</searchLink><br />*<searchLink fieldCode="DE" term="%22Built+environment%22">Built environment</searchLink><br />*<searchLink fieldCode="DE" term="%22Environmental+health%22">Environmental health</searchLink><br />*<searchLink fieldCode="DE" term="%22Plants%22">Plants</searchLink><br /><searchLink fieldCode="DE" term="%22Hypertension+risk+factors%22">Hypertension risk factors</searchLink><br /><searchLink fieldCode="DE" term="%22Hypertension+epidemiology%22">Hypertension epidemiology</searchLink><br /><searchLink fieldCode="DE" term="%22Confidence+intervals%22">Confidence intervals</searchLink><br /><searchLink fieldCode="DE" term="%22Systolic+blood+pressure%22">Systolic blood pressure</searchLink><br /><searchLink fieldCode="DE" term="%22Cross-sectional+method%22">Cross-sectional method</searchLink><br /><searchLink fieldCode="DE" term="%22Multiple+regression+analysis%22">Multiple regression analysis</searchLink><br /><searchLink fieldCode="DE" term="%22Age+distribution%22">Age distribution</searchLink><br /><searchLink fieldCode="DE" term="%22Population+geography%22">Population geography</searchLink><br /><searchLink fieldCode="DE" term="%22Social+context%22">Social context</searchLink><br /><searchLink fieldCode="DE" term="%22Risk+assessment%22">Risk assessment</searchLink><br /><searchLink fieldCode="DE" term="%22Socioeconomic+factors%22">Socioeconomic factors</searchLink><br /><searchLink fieldCode="DE" term="%22Sex+distribution%22">Sex distribution</searchLink><br /><searchLink fieldCode="DE" term="%22Descriptive+statistics%22">Descriptive statistics</searchLink><br /><searchLink fieldCode="DE" term="%22Disease+prevalence%22">Disease prevalence</searchLink><br /><searchLink fieldCode="DE" term="%22Intersectionality%22">Intersectionality</searchLink><br /><searchLink fieldCode="DE" term="%22Metropolitan+areas%22">Metropolitan areas</searchLink><br /><searchLink fieldCode="DE" term="%22Odds+ratio%22">Odds ratio</searchLink><br /><searchLink fieldCode="DE" term="%22Blood+pressure+measurement%22">Blood pressure measurement</searchLink><br /><searchLink fieldCode="DE" term="%22Data+analysis+software%22">Data analysis software</searchLink><br /><searchLink fieldCode="DE" term="%22Educational+attainment%22">Educational attainment</searchLink>
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  Data: <searchLink fieldCode="DE" term="%22Colombia%22">Colombia</searchLink><br /><searchLink fieldCode="DE" term="%22El+Salvador%22">El Salvador</searchLink><br /><searchLink fieldCode="DE" term="%22Guatemala%22">Guatemala</searchLink><br /><searchLink fieldCode="DE" term="%22Peru%22">Peru</searchLink><br /><searchLink fieldCode="DE" term="%22Argentina%22">Argentina</searchLink><br /><searchLink fieldCode="DE" term="%22Chile%22">Chile</searchLink><br /><searchLink fieldCode="DE" term="%22Brazil%22">Brazil</searchLink><br /><searchLink fieldCode="DE" term="%22Mexico%22">Mexico</searchLink><br /><searchLink fieldCode="DE" term="%22Latin+America%22">Latin America</searchLink>
– Name: Abstract
  Label: Abstract
  Group: Ab
  Data: BACKGROUND: Features of the urban physical environment may be linked to the development of high blood pressure, a leading risk factor for global burden of disease. OBJECTIVES: We examined associations of urban physical environment features with hypertension and blood pressure measures in adults across 230 Latin American cities. METHODS: In this cross-sectional study we used health, social, and built environment data from the SALud URBana en América Latina (SALURBAL) project. The individual-level outcomes were hypertension and levels of systolic and diastolic blood pressure. The exposures were city and subcity built environment features, mass transit infrastructure, and green space. Odds ratios (ORs) and mean differences and 95% confidence intervals (CIs) were estimated using multilevel logistic and linear regression models, with single- and multiple-exposure models adjusted for individual-level age, sex, education, and subcity educational attainment. RESULTS: A total of 109,176 participants from 230 cities and eight countries were included in the hypertension analyses and 50,228 participants from 194 cities and seven countries were included in the blood pressure measures analyses. Participants were 18–97 years of age. In multiple-exposure models, higher city fragmentation was associated with higher odds of having hypertension (OR per standard deviation (SD) increase = 1.11; 95% CI: 1.01, 1.21); presence (vs. no presence) of mass transit in the city was associated with higher odds of having hypertension (OR = 1.30; 95% CI: 1.09, 1.54); higher subcity population density was associated with lower odds of having hypertension (OR per SD increase = 0.90; 95% CI: 0.85, 0.94); and higher subcity intersection density was associated with higher odds of having hypertension [OR per SD increase = 1.09; 95% CI: 1.04, 1.15). The presence of mass transit was also associated with slightly higher systolic and diastolic blood pressure in multiple-exposure models adjusted for treatment. Except for the association between intersection density and hypertension, associations were attenuated after adjustment for country. An inverse association of greenness with continuous blood pressure emerged after country adjustment. DISCUSSION: Our results suggest that urban physical environment features—such as fragmentation, mass transit, population density, and intersection density—may be related to hypertension in Latin American cities. Reducing chronic disease risks in the growing urban areas of Latin America may require attention to integrated management of urban design and transport planning. [ABSTRACT FROM AUTHOR]
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  Data: <i>Copyright of Environmental Health Perspectives is the property of National Institute of Environmental Health Sciences and its content may not be copied or emailed to multiple sites without the copyright holder's express written permission. Additionally, content may not be used with any artificial intelligence tools or machine learning technologies. However, users may print, download, or email articles for individual use. This abstract may be abridged. No warranty is given about the accuracy of the copy. Users should refer to the original published version of the material for the full abstract.</i> (Copyright applies to all Abstracts.)
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    Identifiers:
      – Type: doi
        Value: 10.1289/EHP7870
    Languages:
      – Code: eng
        Text: English
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        PageCount: 10
        StartPage: 027010-1
    Subjects:
      – SubjectFull: Population density
        Type: general
      – SubjectFull: Built environment
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      – SubjectFull: Environmental health
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      – SubjectFull: Plants
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      – SubjectFull: Hypertension risk factors
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      – SubjectFull: Hypertension epidemiology
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      – SubjectFull: Confidence intervals
        Type: general
      – SubjectFull: Systolic blood pressure
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      – SubjectFull: Cross-sectional method
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      – SubjectFull: Multiple regression analysis
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      – SubjectFull: Age distribution
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      – SubjectFull: Population geography
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      – SubjectFull: Metropolitan areas
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      – SubjectFull: Odds ratio
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      – SubjectFull: Blood pressure measurement
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      – SubjectFull: Data analysis software
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      – SubjectFull: Colombia
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      – SubjectFull: Brazil
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      – SubjectFull: Mexico
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      – SubjectFull: Latin America
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      – TitleFull: Associations of Urban Environment Features with Hypertension and Blood Pressure across 230 Latin American Cities.
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              Text: Feb2022
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              Y: 2022
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