Metropolitan Fragmentation and Health Disparities: Is There a Link?

Peer Reviewedhttp://deepblue.lib.umich.edu/bitstream/2027.42/90559/1/j.1468-0009.2011.00659.x.pd

Structurally vulnerable neighbourhood environments and racial/ethnic COVID-19 inequities

Preliminary evidence indicates that the experience of the novel coronavirus is not shared equally across geographic areas. Findings in the United States suggest that the burden of COVID-19 morbidity and mortality may be hardest felt in disadvantaged and racially segregated places. Deprived neighbourhoods are disproportionately populated by people of colour, the same populations that are becoming sicker and dying more often from COVID-19. This commentary examines how structurally vulnerable neighbourhoods contribute to racial/ethnic inequities in SARS-COV-2 exposure and COVID-19 morbidity and mortality and considers opportunities to intervene through place-based initiatives and the implementation of a Health in All Policies strategy

Socioeconomic position, John Henryism, and incidence of acute myocardial infarction in Finnish men

Previous cross-sectional studies examining whether John Henryism (JH), or high-effort coping with socioeconomic adversity, potentiates the inverse association between socioeconomic position (SEP) and cardiovascular health have focused mainly on hypertension in African Americans. We conducted the first longitudinal test of this hypothesis on incident acute myocardial infarction (AMI) using data from the Kuopio Ischemic Heart Disease Risk Factor Study in Finland (N = 1405 men, 42-60 years). We hypothesized that the expected inverse gradient between SEP and AMI risk would be stronger for men scoring high on JH than for those scoring low. John Henryism was measured by a Finnish version of the JH Scale for Active Coping. Four different measures of SEP were used: childhood SEP, education, income, and occupation. AMI hazard ratios (HR) by SEP and JH were estimated using COX proportional hazard models, before and after adjustment for study covariates. 205 cases of AMI occurred over a median of 14.9 years. Men employed in lower rank (farmer, blue-collar) occupations who scored high on JH had significantly higher age-adjusted risks of AMI than men in higher rank (white-collar) occupations (HR = 3.14, 95% CI: 1.65-5.98 for blue collar; HR = 2.33, 95% Cl: 1.04-5.22 for farmers) who also scored high on JH. No socioeconomic differences in AMI were observed for men who scored low on JH (HR = 136, 95% CI: 0.74 2.47 for blue collar; HR = 0.93, 95% CI: 0.59-1.48 for farmers; p = 0.002 for the SEP x JH interaction). These findings persisted after adjustment for sociodemographic, behavioral, and biological factors. Results for other SEP measures were in the same direction, but did not reach statistical significance. Repetitive high-effort coping with adversity (John Henryism) was independently associated with increased risk for AMI in Finnish men, underscoring the potential relevance of the John Henryism hypothesis to CVD outcomes other than hypertension and to populations other than African Americans. (C) 2016 Published by Elsevier Ltd.Peer reviewe

Gentrification and Displacement in the San Francisco Bay Area: A Comparison of Measurement Approaches.

Gentrification may play an important role in influencing health outcomes, but few studies have examined these associations. One major barrier to producing empirical evidence to establish this link is that there is little consensus on how to measure gentrification. To address this barrier, we compared three gentrification classification methodologies in relation to their ability to identify neighborhood gentrification in nine San Francisco Bay Area counties: the Freeman method, the Landis method, and the Urban Displacement Project (UDP) Regional Early Warning System. In the 1580 census tracts, 43% of the population had a bachelor's degree or higher. The average median household income was $79,671 in 2013. A comparison of gentrification methodologies revealed that the Landis and Freeman methodologies characterized the vast majority of census tracts as stable, and only 5.2% and 6.1% of tracts as gentrifying. UDP characterized 46.7% of tracts at risk, undergoing, or experiencing advanced stages of gentrification and displacement. There was substantial variation in the geographic location of tracts identified as gentrifying across methods. Given the variation in characterizations of gentrification across measures, studies evaluating associations between gentrification and health should consider using multiple measures of gentrification to examine the robustness of the study findings across measures

Technology, community, and equity: Considerations for collecting social determinants data

Gathering detailed information on an individual’s neighborhood environment is becoming increasingly recognized as a crucial component of understanding the impact that social determinants have on individual and public health, and this has been further highlighted by the ongoing COVID-19 pandemic. Emerging research clearly demonstrates COVID-19’s differential impact on underserved and rural communities, and it is imperative to adequately capture important neighborhood-level predictors of health outcomes to better understand the extent to which these communities have been affected, and to equitably promote their recovery and healing. mHealth tools have drastically transformed the framework of data collection within clinical and population health research and can significantly reduce accessibility barriers for research participants to allow for convenient, continuous real-time health and activity space assessments. Digital interventions leveraging remote data collection, and providing study participants with requisite devices when necessary, serves to bridge the digital divide that would otherwise preclude rural populations’ participation in key research opportunities for advancing health equity

Racial/ethnic differences in adequacy of information and support for women with breast cancer

BACKGROUND. Providing breast cancer patients with needed information and support is an essential component of quality care. This study investigated racial/ethnic variations in the information received and in the availability of peer support. METHODS. In total, 1766 women who were diagnosed with nonmetastatic breast cancer and reported to the Los Angeles County Surveillance, Epidemiology, and End Results registry from June 2005 to May 2006 were mailed a survey after initial treatment. Among accrued cases, 96.2% met eligibility criteria (n = 1698), and 72% completed the survey. Race/ethnicity categories were white, African American, and Latinas (2 categories indicating low or high acculturation, which was determined by using the Short Acculturation Scale for Hispanics). Outcomes included receipt and need for treatment-related and survivorship-related information, difficulty understanding information, and support from women with breast cancer. RESULTS. More women reported receiving treatment-related information than survivorship-related information. After adjusting for sociodemographic, clinical, and treatment factors, a higher percentage of low acculturated Latina women desired more information on treatment-related and survivorship-related issues ( P < .001). Significantly more Latina low acculturated women than white women reported difficulty understanding written materials, with 74.5% requiring help from others. A higher percentage of all minority groups compared with whites reported no contact with other women with breast cancer ( P < .05) and reported less contact through family/friends ( P < .05). Women rated the benefit of talking to other women high, particularly with emotional issues. CONCLUSIONS. Continued efforts to provide culturally appropriate information and support needs to women with breast cancer are necessary to achieve quality care. Latinas with low acculturation reported more unmet information and care support needs than women in other racial/ethnic groups. Cancer 2008. © 2008 American Cancer Society.Peer Reviewedhttp://deepblue.lib.umich.edu/bitstream/2027.42/60993/1/23660_ftp.pd

Mujahid et al. Respond to "Beyond the Metrics for Measuring Neighborhood Effects"

In her commentary, Dr. Lynne Messer (1) recognizes the important contributions of our paper (2) to the discussion of methodological issues related to measurement of neighborhood or area-level properties. Dr. Messer reviews the many challenges involved in observational studies of neighborhood health effects, which we and other investigators have noted (3–8). A major challenge is developing theoretical models of the processes through which neighborhoods (or areas) may affect health. Messer argues that our paper "promises more, from a theoretical perspective, than it delivers" (1, p. 869). Our paper is merely a methodological illustration, with no grandiose theoretical aims. However, we do base the measures we explore on a theoretical model of the processes through which residential context may affect cardiovascular disease risk (1, 9). In her discussion of this model, Messer confuses inconsistent empirical support for aspects of the model with the absence of theory itself. Theorizing on the spatial scale at which different area processes operate is obviously important, but unfortunately there is very little information on which to base this theory. Additional qualitative research on the ways in which individuals interact with spaces may help us develop better theoretical models that may then be empirically tested. However, even if we were able to offer some crude hypotheses regarding spatial scales relevant to different processes, there are features of areas that could plausibly operate at multiple levels. Ultimately, we must rely on empirical research to uncover such relations rather than make a priori assertions under the guise of theory. For this, improving the validity of area-level measures and sensitivity analyses like the ones we present is crucial. Dr. Messer also alludes to the well-established challenges in estimating causal effects from observational data. Nonexchangeability (or its simpler and less fashionable synonym, "residual confounding") is always a concern. Messer implies that because of this, observational work in neighborhood health-effects research is meaningless. Firm believers in nonexchangeability will accept no defense of observational studies because it is impossible to categorically rule out residual confounding, except in the case of the ideal counterfactual experiment. However, claims of residual confounding also need to be subjected to empirical inquiry: What specific confounders have been omitted, and how strong are their effects expected to be? Careful observational work can empirically examine the sensitivity of results to different degrees of residual confounding and degrees of extrapolation. In this, neighborhood effects research is no different than the rest of epidemiology. Given the many limitations and logistical challenges of randomized trials (particularly for the study of neighborhood effects), reliance on observational and quasi-experimental data is likely to continue. Hence, anything we can do to improve the rigor of observational work is crucial. Our objective in the current paper was (merely) to contribute to emerging work on the measurement of area-level constructs, not to fully develop a theory on neighborhood causal effects or to resolve the issue of relevant spatial scale. Our objective was not even to estimate associations between neighborhood characteristics and health outcomes. Instead, we wanted to further develop and evaluate our ability to measure area-level constructs. Epidemiologists are very sophisticated at measuring individual-level characteristics but not as sophisticated at measuring features of ecologic settings. This seriously hampers their ability to examine contextual effects. Our analyses illustrate one approach to quantifying the measurement properties of area-based measures. This approach can be adapted to different constructs and different spatial scales, depending on the research problem and underlying theory. We firmly believe that improving the quality of measurement of area-level constructs is a prerequisite for more rigorous observational work. In fact, several of the inferential problems that arise when area socioeconomic status characteristics are used as proxies for features of areas may be reduced when specific features of areas are examined instead of aggregate socioeconomic status measures (which are, by definition, correlated with individual socioeconomic status, thus magnifying the extrapolation and exchangeability problems). We hope that the illustration we provide in our paper (2) will encourage other investigators to develop and test theoretically relevant area measures and to contrast different approaches to their measurement. Understanding if and how contexts (including neighborhoods) affect health is challenging and complex, but it is also enormously important from the point of view of public health and policy. In order to answer questions regarding these effects, we need to move beyond blanket (and sometimes facile) critiques, roll up our sleeves, and see if we can improve on the work that has been done to date. This means dealing with a messy, correlated, and confounded reality and doing the best we can to glean truth from our observations. As epidemiologists, this is our job, and also our responsibility to the public.http://deepblue.lib.umich.edu/bitstream/2027.42/58002/1/Mujahid et al Respond to Beyond the Metrics for Measuring Neighborhood Effects.pd

Neighborhood Stressors and Race/Ethnic Differences in Hypertension Prevalence (The Multi-Ethnic Study of Atherosclerosis)

Background: The reasons for racial/ethnic disparities in hypertension (HTN) prevalence in the United States are poorly understood.Methods: Using data from the Multi-Ethnic Study of Atherosclerosis (MESA), we investigated whether individual- and neighborhood-level chronic stressors contribute to these disparities in cross-sectional analyses. The sample consisted of 2,679 MESA participants (45-84 years) residing in Baltimore, New York, and North Carolina. HTN was defined as systolic or diastolic blood pressure ≥140 or 90 mm Hg, or taking antihypertensive medications. Individual-level chronic stress was measured by self-reported chronic burden and perceived major and everyday discrimination. A measure of neighborhood (census tract) chronic stressors (i.e., physical disorder, violence) was developed using data from a telephone survey conducted with other residents of MESA neighborhoods. Binomial regression was used to estimate associations between HTN and race/ethnicity before and after adjustment for individual and neighborhood stressors.Results: The prevalence of HTN was 59.5% in African Americans (AAs), 43.9% in Hispanics, and 42.0% in whites. Age- and sex-adjusted relative prevalences of HTN (compared to whites) were 1.30 (95% confidence interval (CI): 1.22-1.38) for AA and 1.16 (95% CI: 1.04-1.31) for Hispanics. Adjustment for neighborhood stressors reduced these to 1.17 (95% CI: 1.11-1.22) and 1.09 (95% CI: 1.00-1.18), respectively. Additional adjustment for individual-level stressors, acculturation, income, education, and other neighborhood features only slightly reduced these associations.Conclusion: Neighborhood chronic stressors may contribute to race/ethnic differences in HTN prevalence in the United States.American Journal of Hypertension (2010).http://deepblue.lib.umich.edu/bitstream/2027.42/78329/1/MujahidDiezRoux2010_AmJHTN.pd

Neighborhood Resources for Physical Activity and Healthy Foods and Incidence of Type 2 Diabetes Mellitus

Background: Despite increasing interest in the extent to which features of residential environments contribute to incidence of type 2 diabetes mellitus, no multisite prospective studies have investigated this question. We hypothesized that neighborhood resources supporting physical activity and healthy diets are associated with a lower incidence of type 2 diabetes. Methods: Person-level data came from 3 sites of the Multi-Ethnic Study of Atherosclerosis, a population-based, prospective study of adults aged 45 to 84 years at baseline. Neighborhood data were derived from a populationbased residential survey. Type 2 diabetes was defined as a fasting glucose level of 126 mg/dL or higher ( 7 mmol/L) or taking insulin or oral hypoglycemic agents. We estimated the hazard ratio of type 2 diabetes incidence associated with neighborhood (US Census tract) resources. Results: Among 2285 participants, 233 new type 2 diabetes cases occurred during a median of 5 follow-up yearsBetter neighborhood resources, determined by a combined score for physical activity and healthy foods, were associated with a 38% lower incidence of type 2 diabetes (hazard ratio corresponding to a difference between the 90th and 10th percentiles for resource distribution, 0.62; 95% confidence interval, 0.43-0.88 adjusted for age, sex, family history of diabetes, race/ethnicity, income, assets, educational level, alcohol use, and smoking status). The association remained statistically significant after further adjustment for individual dietary factors, physical activity level, and body mass index. Conclusion: Better neighborhood resources were associated with lower incidence of type 2 diabetes, which suggests that improving environmental features may be a viable population-level strategy for addressing this disease.This research was supported by contracts R01 HL071759 and N01-HC-95159 through N01-HC-95165 and N01-HC-95169 from the National Heart, Lung, and Blood Institute, National Institutes of Health.Peer Reviewedhttp://deepblue.lib.umich.edu/bitstream/2027.42/64274/1/auchincloss_archiveinternalmedicine_oct2009.pd

Neighborhood disinvestment and severe maternal morbidity in the state of California

BACKGROUND Social determinants of health, including neighborhood context, may be a key driver of severe maternal morbidity and its related racial and ethnic inequities; however, investigations remain limited. OBJECTIVE This study aimed to examine the associations between neighborhood socioeconomic characteristics and severe maternal morbidity, as well as whether the associations between neighborhood socioeconomic characteristics and severe maternal morbidity were modified by race and ethnicity. STUDY DESIGN This study leveraged a California statewide data resource on all hospital births at ≥20 weeks of gestation (1997–2018). Severe maternal morbidity was defined as having at least 1 of 21 diagnoses and procedures (eg, blood transfusion or hysterectomy) as outlined by the Centers for Disease Control and Prevention. Neighborhoods were defined as residential census tracts (n=8022; an average of 1295 births per neighborhood), and the neighborhood deprivation index was a summary measure of 8 census indicators (eg, percentage of poverty, unemployment, and public assistance). Mixed-effects logistic regression models (individuals nested within neighborhoods) were used to compare odds of severe maternal morbidity across quartiles (quartile 1 [the least deprived] to quartile 4 [the most deprived]) of the neighborhood deprivation index before and after adjustments for maternal sociodemographic and pregnancy-related factors and comorbidities. Moreover, cross-product terms were created to determine whether associations were modified by race and ethnicity. RESULTS Of 10,384,976 births, the prevalence of severe maternal morbidity was 1.2% (N=120,487). In fully adjusted mixed-effects models, the odds of severe maternal morbidity increased with increasing neighborhood deprivation index (odds ratios: quartile 1, reference; quartile 4, 1.23 [95% confidence interval, 1.20–1.26]; quartile 3, 1.13 [95% confidence interval, 1.10–1.16]; quartile 2, 1.06 [95% confidence interval, 1.03–1.08]). The associations were modified by race and ethnicity such that associations (quartile 4 vs quartile 1) were the strongest among individuals in the “other” racial and ethnic category (1.39; 95% confidence interval, 1.03–1.86) and the weakest among Black individuals (1.07; 95% confidence interval, 0.98–1.16). CONCLUSION Study findings suggest that neighborhood deprivation contributes to an increased risk of severe maternal morbidity. Future research should examine which aspects of neighborhood environments matter most across racial and ethnic groups