Neighborhood Influences and BMI in Urban Older Adults

Mathis, Arlesia; Rooks, Ronica N.; Tawk, Rima; Kruger, Daniel J.

doi:10.1177/0733464815584670

Cited by 16 publications

(10 citation statements)

References 29 publications

(40 reference statements)

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“…Fourteen studies examined the relative importance of selected objectively and perceived measured NE attributes on PA in general [ 120 , 122 , 123 , 129 , 133 – 142 ] and four studies investigated associations between attributes of the NE and specific PA or walking domains [ 40 , 121 , 124 , 127 ]. Some studies aimed to explore the relationships between different NE attributes and PA in a specific population group, for example in adults with type 2 diabetes [ 119 ], kidney cancer survivors [ 128 ] or overweight and obese urban older adults [ 143 ]. One quarter of the studies (n = 9) tested the mediating role of demographic, psychosocial, functional, behavioral, and/or environmental features on the association between NE and PA [ 125 , 127 , 128 , 130 – 132 , 144 – 146 ].…”

Section: Resultsmentioning

confidence: 99%

Measuring the association of objective and perceived neighborhood environment with physical activity in older adults: challenges and implications from a systematic review

et al. 2020

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Background A supportive environment is a key factor in addressing the issue of health among older adults. There is already sufficient evidence that objective and self-reported measures of the neighborhood environment should be taken into account as crucial components of active aging, as they have been shown to influence physical activity; particularly in people aged 60+. Thus, both could inform policies and practices that promote successful aging in place. An increasing number of studies meanwhile consider these exposures in analyzing their impact on physical activity in the elderly. However, there is a wide variety of definitions, measurements and methodological approaches, which complicates the process of obtaining comparable estimates of the effects and pooled results. The aim of this review was to identify and summarize these differences in order to emphasize methodological implications for future reviews and meta analyzes in this field and, thus, to create a sound basis for synthesized evidence. Methods A systematic literature search across eight databases was conducted to identify peer-reviewed articles examining the association of objective and perceived measures of the neighborhood environment and objectively measured or self-reported physical activity in adults aged ≥ 60 years. Two authors independently screened the articles according to predefined eligibility criteria, extracted data, and assessed study quality. A qualitative synthesis of the findings is provided. Results Of the 2967 records retrieved, 35 studies met the inclusion criteria. Five categories of methodological approaches, numerous measurement instruments to assess the neighborhood environment and physical activity, as well as several clusters of definitions of neighborhood, were identified. Conclusions The strength of evidence of the associations of specific categories of environmental attributes with physical activity varies across measurement types of the outcome and exposures as well as the physical activity domain observed and the operationalization of neighborhood. The latter being of great importance for the targeted age group. In the light of this, future reviews should consider these variations and stratify their summaries according to the different approaches, measures and definitions. Further, underlying mechanisms should be explored.

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Section: Resultsmentioning

confidence: 99%

Measuring the association of objective and perceived neighborhood environment with physical activity in older adults: challenges and implications from a systematic review

et al. 2020

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“…To the best of our knowledge, no previous study has examined the association between the perceived proximity of exercise facilities and CVD risk, although research on other health outcomes has produced similar findings to the associations seen among men in this study. For example, Auchincloss et al [ 43 ] found that neighborhood physical activity resources were associated with a lower hazard ratio for diabetes (0.65) in the U.S. Mathis et al [ 44 ] investigated the association between BMI and local recreational facilities and showed that obese older adults had a significantly lower probability of having a park in their neighborhood. Previous research has also highlighted the ways in which such an environment might be beneficial for health.…”

Section: Discussionmentioning

confidence: 99%

“…Similarly, neighborhood safety (defined as being able to walk safely during the day and at night, crime and violence) has also been linked to the cardiovascular health (CVH) score, a concept recently introduced by the American Heart Association [ 1 ]. The perceived risk of traffic accidents and reduced personal safety have also been associated with other health indicators such as obesity [ 21 , 44 ], mental well-being [ 45 – 47 ] and physical functioning [ 47 ]. Living in fear might result in more time being spent indoors, lower levels of physical activity, and higher levels of psychological stress, all of which have the possibility to impact on CVD risk.…”

Section: Discussionmentioning

confidence: 99%

Neighborhood Characteristics and Cardiovascular Risk among Older People in Japan: Findings from the JAGES Project

et al. 2016

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Previous studies have found an association between neighborhood characteristics (i.e., aspects of the physical and social environment) and the incidence of cardiovascular disease (CVD) and elevated CVD risk. This study investigated the relationship between neighborhood characteristics and CVD risk among older people in Japan where research on this association is scarce. Data came from the Japan Gerontological Evaluation Study project; questionnaire data collected from 3,810 people aged 65 years or older living in 20 primary school districts in Aichi prefecture, Japan, was linked to a computed composite CVD risk score based on biomarker data (i.e., hemoglobin A1c, systolic blood pressure, diastolic blood pressure, high-density lipoprotein cholesterol, low-density lipoprotein cholesterol, and estimated glomerular filtration rate). A sex-stratified multilevel linear regression analysis revealed that for male participants, living in neighborhoods with a higher perceived occurrence of traffic accidents and reduced personal safety was associated with an elevated CVD risk (coefficient = 1.08 per interquartile range increase, 95% confidence interval [CI] = 0.30 to 1.86) whereas males living in neighborhoods with a higher perceived proximity of exercise facilities had a lower risk (coefficient = −1.00, 95% CI = −1.78 to −0.21). For females, there was no statistically significant association between neighborhood characteristics and CVD risk. This study suggests that aspects of the neighborhood environment might be important for CVD morbidity and mortality in Japan, particularly among men.

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“…Several studies assessed the relationship between neighborhood crime and obesity using objective crime data, which were drawn from a number of different sources including state and local law enforcement agencies [54-56, 53•, 57] and the Federal Bureau of Investigation (FBI) [58]. For instance, one longitudinal study examined associations between crime rate and obesity among young adults over time [54].…”

Section: The Role Of Neighborhood Social Environment Factors In Pa Anmentioning

confidence: 99%

Neighborhood Social Environment and Cardiovascular Disease Risk

Tamura

Langerman

Ceasar

et al. 2019

Curr Cardiovasc Risk Rep

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Purpose of review: Limited physical activity (PA) and obesity are two primary risk factors for cardiovascular disease (CVD). Within a socio-ecological framework, neighborhood social environment may play a key role in influencing PA and obesity. However, the mechanisms underlying this relationship remain ambiguous. Our goals in this review are: (1) to summarize findings from the recent studies on neighborhood social environment in relation to PA and obesity as CVD risk factors, and (2) to briefly describe several innovative approaches to assessing neighborhood social environment. Recent findings: Almost all recent studies assessed neighborhood social environment around residential areas. There were consistent associations between neighborhood social environment and PA and obesity, with some exceptions (indicating null associations or paradoxical associations). However, a focus on residential social environment may limit results because these studies did not account for any exposures occurring away from individuals’ homes. Additionally, the majority of studies utilized a cross-sectional design, which limits our ability to make inferences regarding the causality of the association between social environment and PA or obesity as CV risk factors. Summary: The majority of the studies on neighborhood social environment characterized factors around residential areas and assessed participant activity via self-reported surveys. Future research should leverage tools to account for the spatial mismatch between environmental exposures and outcomes by using global positioning systems, ecological momentary assessments, virtual neighborhood audits, and simulation modeling. These approaches can overcome major limitations by tracking individuals’ daily activity and real-time perceptions of neighborhood social environments linked to CVD events.

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Neighborhood Influences and BMI in Urban Older Adults

Cited by 16 publications

References 29 publications

Measuring the association of objective and perceived neighborhood environment with physical activity in older adults: challenges and implications from a systematic review

Measuring the association of objective and perceived neighborhood environment with physical activity in older adults: challenges and implications from a systematic review

Neighborhood Characteristics and Cardiovascular Risk among Older People in Japan: Findings from the JAGES Project

Neighborhood Social Environment and Cardiovascular Disease Risk

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