Neighborhoods and obesity

Black, Jennifer; Macinko, James

doi:10.1111/j.1753-4887.2007.00001.x

Cited by 451 publications

(426 citation statements)

References 128 publications

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“…8,9 Behavioral risk factors for diabetes include poor quality diet, inadequate exercise, limited medication adherence, and depression, 10,11 all of which are common among poor, medically uninsured patients. 12 …”

Section: Introductionmentioning

confidence: 99%

Keys to Successful Diabetes Self-management for Uninsured Patients: Social Support, Observational Learning, and Turning Points: A Safety Net Providers' Strategic Alliance Study

Madden

Tomsik

Terchek

et al. 2011

Journal of the National Medical Association

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Objective To determine how medically uninsured patients with limited material resources successfully manage diabetes. Methods Clinicians at 5 safety net practices enrolled uninsured adult patients (N=26) with prior diagnosis of diabetes for 6 months or longer. Patients were interviewed about enabling factors, motivations, resources, and barriers. Chart reviews and clinician surveys supplemented interview data. Interview, survey, and chart review data were analyzed and findings were summarized. Results Two distinct groups of patients were investigated: 1) “successful,” defined as those with an HbA1c of ≤7% or a recent improvement of at least 2% (n=17); and 2) “unsuccessful,” defined as patients with HbA1c of ≥9% (n=9) without recent improvement. In comparison to unsuccessful patients, successful patients more often reported having friends or family with diabetes, sought information about the disease, used evidence-based self-management strategies, held an accurate perception of their own disease control, and experienced “turning point” events that motivated increased efforts in disease management. Conclusions Uninsured safety net patients who successfully managed diabetes learned from friends and family with diabetes and leveraged disease-related events into motivational turning points. It may be beneficial for clinicians to incorporate social learning and motivational enhancement into diabetes interventions to increase patients’ motivation for improved levels of self-management.

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Section: Introductionmentioning

confidence: 99%

Keys to Successful Diabetes Self-management for Uninsured Patients: Social Support, Observational Learning, and Turning Points: A Safety Net Providers' Strategic Alliance Study

Madden

Tomsik

Terchek

et al. 2011

Journal of the National Medical Association

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“…A number of studies have identified the influence that space and place have on dietary intake, both internationally (9)(10)(11) and in the UK (12)(13)(14) . However, research has focused largely on one of two factors: (i) the effects of neighbourhood-level deprivation (15)(16)(17)(18) ; and (ii) the role that distance or access to food outlets plays in diet (19)(20)(21)(22)(23)(24) .…”

mentioning

confidence: 99%

Rurality and dietary patterns: associations in a UK cohort study of 10-year-old children

Morris

Northstone

2014

Public Health Nutr.

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Objective: Despite differences in obesity and ill health between urban and rural areas in the UK being well documented, very little is known about differences in dietary patterns across these areas. The present study aimed to examine whether urban/rural status is associated with dietary patterns in a population-based UK cohort study of children. Design: Dietary patterns were obtained using principal components analysis and cluster analysis of 3 d diet records collected from children at 10 years of age. Rurality was obtained from the 2001 UK Census urban/rural indicator at the time of dietary assessment. General linear models were used to examine the relationship between rurality and dietary pattern scores from principal components analysis; multinomial logistic regression was used to assess the association between rurality and dietary clusters. Setting: The Avon Longitudinal Study of Parents and Children (ALSPAC), South West England. Subjects: Children (n 5677) aged 10 years (2817 boys and 2860 girls). Results: After adjustment, increases in rurality were associated with increased scores on the 'health awareness' dietary pattern (β = 0·35; 95 % CI 0·14, 0·56; P < 0·001 for the most rural compared with the most urban group) and lower scores on the 'packed lunch/snack' dietary pattern (β = − 0·39; 95 % CI − 0·59, − 0·19; P < 0·001 for the most rural compared with the most urban group). The odds ratio for participants being in the 'healthy' compared with the 'processed' dietary cluster for the most rural areas was 1·61 (95 % CI 1·05, 2·49; P = 0·02) compared with those in the most urban areas. Conclusions: There is evidence to suggest that differences exist in dietary patterns between rural and urban areas. Similar results were found using two different methods of dietary pattern analysis, showing that children residing in rural households were more likely to consume healthier diets than those in urban households.

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“…The patient's home neighbourhood will be used as a surrogate for patient characteristics, because previous literature shows an association between home neighbourhood and cardiac risk factors, unhealthy behaviours, and overall health. [33][34][35][36][37][38][39][40][41][42][43][44][45] The neighbourhood factors of the arrest location (i.e., the pickup address) will be used to study the effects on bystander CPR, because the emergency response (i.e., bystanders and EMS/paramedics) is contingent on the arrest location. [10][11][12][13][46][47][48] A patient's home address is recorded as mailing address with street name, street number, and postal code, whereas the pickup address is recorded as a mailing address, with latitude and longitude coordinates and a Universal Transverse Mercator (UTM) value.…”

Section: Geocodingmentioning

confidence: 99%

Does location matter? A proposed methodology to evaluate neighbourhood effects on cardiac arrest survival and bystander CPR

Buick

Allan

Ray

et al. 2015

CJEM

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Background: Traditional variables used to explain survival following out-of-hospital cardiac arrest (OHCA) account for only 72% of survival, suggesting that other unknown factors may influence outcomes. Research on other diseases suggests that neighbourhood factors may partly determine health outcomes. Yet, this approach has rarely been used for OHCA. This work outlines a methodology to investigate multiple neighbourhood factors as determinants of OHCA outcomes. Methods: A retrospective, observational cohort study design will be used. All adult non-emergency medical service witnessed OHCAs of cardiac etiology within the city of Toronto between 2006 and 2010 will be included. Event details will be extracted from the Toronto site of the Resuscitation Outcomes Consortium Epistry-Cardiac Arrest, an existing population-based dataset of consecutive OHCA patients. Geographic information systems technology will be used to assign patients to census tracts. Neighbourhood variables to be explored include the Ontario Marginalization Index (deprivation, dependency, ethnicity, and instability), crime rate, and density of family physicians. Hierarchical logistic regression analysis will be used to explore the association between neighbourhood characteristics and 1) survival-to-hospital discharge, 2) return-of-spontaneous circulation at hospital arrival, and 3) provision of bystander cardiopulmonary resuscitation (CPR). Receiver operating characteristics curves will evaluate each model's ability to discriminate between those with and without each outcome. Discussion: This study will determine the role of neighbourhood characteristics in OHCA and their association with clinical outcomes. The results can be used as the basis to focus on specific neighbourhoods for facilitating educational interventions, CPR awareness programs, and higher utilization of automatic defibrillation devices.

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Neighborhoods and obesity

Cited by 451 publications

References 128 publications

Keys to Successful Diabetes Self-management for Uninsured Patients: Social Support, Observational Learning, and Turning Points: A Safety Net Providers' Strategic Alliance Study

Keys to Successful Diabetes Self-management for Uninsured Patients: Social Support, Observational Learning, and Turning Points: A Safety Net Providers' Strategic Alliance Study

Rurality and dietary patterns: associations in a UK cohort study of 10-year-old children

Does location matter? A proposed methodology to evaluate neighbourhood effects on cardiac arrest survival and bystander CPR

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