Dataset Information

Neighborhood deprivation and biomarkers of health in Britain: the mediating role of the physical environment.

ABSTRACT:

Background

Neighborhood deprivation has been consistently linked to poor individual health outcomes; however, studies exploring the mechanisms involved in this association are scarce. The objective of this study was to investigate whether objective measures of the physical environment mediate the association between neighborhood socioeconomic deprivation and biomarkers of health in Britain.

Methods

We linked individual-level biomarker data from Understanding Society: The UK Household Longitudinal Survey (2010-2012) to neighborhood-level data from different governmental sources. Our outcome variables were forced expiratory volume in 1 s (FEV₁%; n=16,347), systolic blood pressure (SBP; n=16,846), body mass index (BMI; n=19,417), and levels of C-reactive protein (CRP; n=11,825). Our measure of neighborhood socioeconomic deprivation was the Carstairs index, and the neighborhood-level mediators were levels of air pollutants (sulphur dioxide [SO₂], particulate matter [PM₁₀], nitrogen dioxide [NO₂], and carbon monoxide [CO]), green space, and proximity to waste and industrial facilities. We fitted a multilevel mediation model following a multilevel structural equation framework in MPlus v7.4, adjusting for age, gender, and income.

Results

Residents of poor neighborhoods and those exposed to higher pollution and less green space had worse health outcomes. However, only SO₂ exposure significantly and partially mediated the association between neighborhood socioeconomic deprivation and SBP, BMI, and CRP.

Conclusion

Reducing air pollution exposure and increasing access to green space may improve population health but may not decrease health inequalities in Britain.

SUBMITTER: Chaparro MP

PROVIDER: S-EPMC6020450 | biostudies-literature | 2018 Jun

REPOSITORIES: biostudies-literature

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Publications

Neighborhood deprivation and biomarkers of health in Britain: the mediating role of the physical environment.

Chaparro M Pia MP Benzeval Michaela M Richardson Elizabeth E Mitchell Richard R

BMC public health 20180627 1

<h4>Background</h4>Neighborhood deprivation has been consistently linked to poor individual health outcomes; however, studies exploring the mechanisms involved in this association are scarce. The objective of this study was to investigate whether objective measures of the physical environment mediate the association between neighborhood socioeconomic deprivation and biomarkers of health in Britain.<h4>Methods</h4>We linked individual-level biomarker data from Understanding Society: The UK Househ ...[more]

PMID: 29945580

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Project description:BACKGROUND:Living in walkable neighborhoods may provide long-term cardio-metabolic health benefits to residents. Little empirical research has examined the behavioral mechanisms in this relationship. In this longitudinal study, we examined the potential mediating role of physical activity (baseline and 12-year change) in the relationships of neighborhood walkability with 12-year changes in cardio-metabolic risk markers. METHODS:The Australian Diabetes, Obesity and Lifestyle study collected data from adults, initially aged 25+ years, in 1999-2000, 2004-05, and 2011-12. We used 12-year follow-up data from 2023 participants who did not change their address during the study period. Outcomes were 12-year changes in waist circumference, weight, systolic and diastolic blood pressure, fasting and 2-h postload plasma glucose, high-density lipoprotein cholesterol, and triglycerides. A walkability index was calculated, using dwelling density, intersection density, and destination density, within 1?km street-network buffers around participants' homes. Spatial data for calculating these measures were sourced around the second follow-up period. Physical activity was assessed by self-reported time spent in moderate-to-vigorous physical activity (including walking). Multilevel models, adjusting for potential confounders, were used to examine the total and indirect relationships. The joint-significance test was used to assess mediation. RESULTS:There was evidence for relationships of higher walkability with smaller increases in weight (P?=?0.020), systolic blood pressure (P?<?0.001), and high-density lipoprotein cholesterol (P?=?0.002); and, for relationships of higher walkability with higher baseline physical activity (P?=?0.020), which, in turn, related to smaller increases in waist circumference (P?=?0.006), weight (P?=?0.020), and a greater increase in high-density lipoprotein cholesterol (P?=?0.005). There was no evidence for a relationship of a higher walkability with a change in physical activity during the study period (P?=?0.590). CONCLUSIONS:Our mediation analysis has shown that the protective effects of walkable neighborhoods against obesity risk may be in part attributable to higher baseline physical activity levels. However, there was no evidence of mediation by increases in physical activity during the study period. Further research is needed to understand other behavioral pathways between walkability and cardio-metabolic health, and to investigate any effects of changes in walkability.

Project description:BackgroundRecent obesity prevention initiatives focus on healthy neighborhood design, but most research examines neighborhood food retail and physical activity (PA) environments in isolation. We estimated joint, interactive, and cumulative impacts of neighborhood food retail and PA environment characteristics on body mass index (BMI) throughout early adulthood.Methods and findingsWe used cohort data from the Coronary Artery Risk Development in Young Adults (CARDIA) Study [n=4,092; Year 7 (24-42 years, 1992-1993) followed over 5 exams through Year 25 (2010-2011); 12,921 person-exam observations], with linked time-varying geographic information system-derived neighborhood environment measures. Using regression with fixed effects for individuals, we modeled time-lagged BMI as a function of food and PA resource density (counts per population) and neighborhood development intensity (a composite density score). We controlled for neighborhood poverty, individual-level sociodemographics, and BMI in the prior exam; and included significant interactions between neighborhood measures and by sex. Using model coefficients, we simulated BMI reductions in response to single and combined neighborhood improvements. Simulated increase in supermarket density (from 25(th) to 75(th) percentile) predicted inter-exam reduction in BMI of 0.09 kg/m(2) [estimate (95% CI): -0.09 (-0.16, -0.02)]. Increasing commercial PA facility density predicted BMI reductions up to 0.22 kg/m(2) in men, with variation across other neighborhood features [estimate (95% CI) range: -0.14 (-0.29, 0.01) to -0.22 (-0.37, -0.08)]. Simultaneous increases in supermarket and commercial PA facility density predicted inter-exam BMI reductions up to 0.31 kg/m(2) in men [estimate (95% CI) range: -0.23 (-0.39, -0.06) to -0.31 (-0.47, -0.15)] but not women. Reduced fast food restaurant and convenience store density and increased public PA facility density and neighborhood development intensity did not predict reductions in BMI.ConclusionsFindings suggest that improvements in neighborhood food retail or PA environments may accumulate to reduce BMI, but some neighborhood changes may be less beneficial to women.

Project description:PurposeHispanic/Latino adults on the Texas-Mexico border have high rates of chronic disease. Neighborhoods can influence health, though there is a limited research on neighborhood environment and health in Hispanics/Latinos. The purpose of this study was to assess the relation of neighborhood environment with health variables in Hispanic/Latino adults, including physical activity [PA], depression, anxiety, and lab-assessed conditions (type 2 diabetes, metabolic syndrome, and chronic inflammation).MethodsParticipants were randomly-selected from a Hispanic/Latino cohort on the Texas-Mexico border. Neighborhood environment, self-reported PA, anxiety, and depression were assessed through questionnaires. Laboratory values determined Type 2 diabetes, metabolic syndrome, and C-reactive protein (CRP). We conducted multivariable linear and logistic regression analyses to assess the associations of neighborhood environment and health variables, controlling for covariates.ResultsParticipants (n = 495) were mostly females, without insurance. After controlling for covariates, crime (Adjusted Odds Ratio [AOR] = 1.59 (95%CI 1.06-2.38), no streetlights (AOR = 1.65, 95%CI 1.06-2.57), and traffic (AOR = 1.74, 95%CI 1.16-2.62) were all significantly associated with anxiety. Only traffic was significantly associated with depression (AOR = 1.61, 95%CI1.05-2.47). A lack of nearby shops (AOR = 0.57, 95%CI 0.38-0.84) and no one out doing PA (AOR = 0.53, 95% CI 0.34-0.83) were both significantly associated with lower odds of meeting PA guidelines. A lack of nearby shops was associated with a 26% increase in the CRP value (β = 0.26, 95%CI 0.04-0.47).DiscussionSeveral neighborhood environment variables were significantly associated with mental health, PA and CRP, though estimates were small. The neighborhood environment is a meaningful contextual variable to consider for health-related interventions in Hispanic/Latino adults, though more study is needed regarding the magnitude of the estimates.Trial registrationNCT01168765.

Project description:INTRODUCTION:Considering the joint association of neighborhood socioeconomic environment and individual-level health behaviors with health outcomes may help officials design effective disease prevention strategies. This study evaluates the joint influences of neighborhood socioeconomic environment and individual health behaviors on mortality in a cohort primarily comprising people with low individual-level SES. METHODS:The prospective Southern Community Cohort Study includes 77,896 white and African American participants recruited in the years 2002-2009; 55% of participants had a household income <$15,000 at baseline interview. Mortality from cancer (n=2,471), cardiovascular diseases (n=3,005), and all-causes (n=10,099) was identified from the National Death Index through December 31, 2013 (median follow-up, 8 years). Data were analyzed in 2016 and 2017. Associations were assessed between mortality, a neighborhood deprivation index composed of 11 census tract-level variables, five health behaviors, and a composite healthy lifestyle score. RESULTS:Living in a neighborhood with the greatest socioeconomic disadvantage was associated with higher all-cause mortality in both men (hazard ratio=1.41, 95% CI=1.27, 1.57) and women (hazard ratio=1.77, 95% CI=1.57, 2.00). Associations were attenuated after adjustment for individual-level SES and major risk factors (hazard ratio for men=1.09, 95% CI=0.98, 1.22, and hazard ratio for women=1.26, 95% CI=1.12, 1.42). The dose-response association between neighborhood disadvantage and mortality was less apparent among smokers. Nevertheless, individuals who lived in disadvantaged neighborhoods and had the unhealthiest lifestyle scores experienced the highest mortality. CONCLUSIONS:Disadvantaged neighborhood socioeconomic environments are associated with increased mortality in a cohort of individuals of low SES. Positive individual-level health behaviors may help negate the adverse effect of disadvantage on mortality.

Project description:BACKGROUND:Investigating the association of the neighborhood social environment on physical activity is complex. A systematic scoping review was performed to (1) provide an inventory of studies assessing the influence of the neighborhood social environment on physical activity since 2006; (2) describe methodologies employed; and (3) formulate recommendations for the field. METHODS:Two databases were searched using terms related to 'physical activity,' 'neighborhood,' and 'social environment' in January 2017. Eligibility criteria included: 1) physical activity as an outcome; 2) neighborhood social environment as a predictor; 3) healthy population (without diagnosed clinical condition or special population); 4) observational or experimental design. Of 1352 studies identified, 181 were included. Textual data relevant to the social environment measurement and analysis were extracted from each article into qualitative software (MAXQDA) and coded to identify social environmental constructs, measurement methods, level of measurement (individual vs. aggregated to neighborhood), and whether authors explicitly recognized the construct as the social environment. The following measures were generated for each construct: number of unique measurements; % of times measured at an aggregate level; % of times authors referred to the construct as the social environment. Social environmental constructs were then grouped into larger descriptive dimensions. RESULTS/FINDINGS:Fifty-nine social environmental constructs were identified and grouped into 9 dimensions: Crime & Safety (n?=?133 studies; included in 73% of studies); Economic & Social Disadvantage (n?=?55, 33%); Social Cohesion & Capital (n?=?47, 26%); Social Relationships (n?=?22, 12%); Social Environment (n?=?16, 9%); Disorder & Incivilities (n?=?15, 8%); Sense of Place/Belonging (n?=?8, 4%); Discrimination/Segregation (n?=?3, 2%); Civic Participation & Engagement (n?=?2, 1%). Across all articles, the social environment was measured using 176 different methods, was measured at an aggregate-level 38% of the time, and referred to as the social environment 23% of the time. CONCLUSIONS:Inconsistent terminology, definitions, and measurement of the social environment and the lack of explicit language identifying constructs as the social environment make it challenging to compare results across studies and draw conclusions. Improvements are needed to increase our understanding of social environmental correlates and/or determinants of physical activity and facilitate cross-disciplinary conversations necessary to effectively intervene to promote physical activity. TRIAL REGISTRATION:PROSPERO CRD42017059580.

Dataset Information

Neighborhood deprivation and biomarkers of health in Britain: the mediating role of the physical environment.

Background

Methods

Results

Conclusion

Publications

Neighborhood deprivation and biomarkers of health in Britain: the mediating role of the physical environment.

Similar Datasets

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