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      Neighborhood socioeconomic status and mortality in the nurses’ health study (NHS) and the nurses’ health study II (NHSII)

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          Background:

          Few studies have prospectively examined long-term associations between neighborhood socioeconomic status (nSES) and mortality risk, independent of demographic and lifestyle risk factors.

          Methods:

          We assessed associations between nSES and all-cause, nonaccidental mortality among women in the Nurses’ Health Study (NHS) 1986–2014 (N = 101,701) and Nurses’ Health Study II (NHSII) 1989–2015 (N = 101,230). Mortality was ascertained from the National Death Index (NHS: 19,228 deaths; NHSII: 1556 deaths). Time-varying nSES was determined for the Census tract of each residential address. We used principal component analysis (PCA) to identify nSES variable groups. Multivariable Cox proportional hazards models were conditioned on age and calendar period and included time-varying demographic, lifestyle, and individual SES factors.

          Results:

          For NHS, hazard ratios (HRs) comparing the fifth to first nSES quintiles ranged from 0.89 (95% confidence interval [CI] = 0.84, 0.94) for percent of households receiving interest/dividends, to 1.11 (95% CI = 1.06, 1.17) for percent of households receiving public assistance income. In NHSII, HRs ranged from 0.72 (95% CI: 0.58, 0.88) for the percent of households receiving interest/dividends, to 1.27 (95% CI: 1.07, 1.49) for the proportion of households headed by a single female. PCA revealed three constructs: education/income, poverty/wealth, and racial composition. The racial composition construct was associated with mortality (HR NHS: 1.03; 95% CI = 1.01, 1.04).

          Conclusion:

          In two cohorts with extensive follow-up, individual nSES variables and PCA component scores were associated with mortality. nSES is an important population-level predictor of mortality, even among a cohort of women with little individual-level variability in SES.

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          Most cited references39

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          Making Neighborhood-Disadvantage Metrics Accessible — The Neighborhood Atlas

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            Social conditions as fundamental causes of health inequalities: theory, evidence, and policy implications.

            Link and Phelan (1995) developed the theory of fundamental causes to explain why the association between socioeconomic status (SES) and mortality has persisted despite radical changes in the diseases and risk factors that are presumed to explain it. They proposed that the enduring association results because SES embodies an array of resources, such as money, knowledge, prestige, power, and beneficial social connections that protect health no matter what mechanisms are relevant at any given time. In this article, we explicate the theory, review key findings, discuss refinements and limits to the theory, and discuss implications for health policies that might reduce health inequalities. We advocate policies that encourage medical and other health-promoting advances while at the same time breaking or weakening the link between these advances and socioeconomic resources. This can be accomplished either by reducing disparities in socioeconomic resources themselves or by developing interventions that, by their nature, are more equally distributed across SES groups.
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              The development of a standardized neighborhood deprivation index.

              Census data are widely used for assessing neighborhood socioeconomic context. Research using census data has been inconsistent in variable choice and usually limited to single geographic areas. This paper seeks to a) outline a process for developing a neighborhood deprivation index using principal components analysis and b) demonstrate an example of its utility for identifying contextual variables that are associated with perinatal health outcomes across diverse geographic areas. Year 2000 U.S. Census and vital records birth data (1998-2001) were merged at the census tract level for 19 cities (located in three states) and five suburban counties (located in three states), which were used to create eight study areas within four states. Census variables representing five socio-demographic domains previously associated with health outcomes, including income/poverty, education, employment, housing, and occupation, were empirically summarized using principal components analysis. The resulting first principal component, hereafter referred to as neighborhood deprivation, accounted for 51 to 73% of the total variability across eight study areas. Component loadings were consistent both within and across study areas (0.2-0.4), suggesting that each variable contributes approximately equally to "deprivation" across diverse geographies. The deprivation index was associated with the unadjusted prevalence of preterm birth and low birth weight for white non-Hispanic and to a lesser extent for black non-Hispanic women across the eight sites. The high correlations between census variables, the inherent multidimensionality of constructs like neighborhood deprivation, and the observed associations with birth outcomes suggest the utility of using a deprivation, index for research into neighborhood effects on adverse birth outcomes.
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                Author and article information

                Journal
                Environ Epidemiol
                Environ Epidemiol
                EE9
                Environmental Epidemiology
                Lippincott Williams & Wilkins (Hagerstown, MD )
                2474-7882
                February 2023
                14 December 2022
                : 7
                : 1
                : e235
                Affiliations
                [a ]Department of Epidemiology, Harvard T.H. Chan School of Public Health, Boston, Massachusetts
                [b ]Channing Division of Network Medicine, Department of Medicine, Brigham and Women’s Hospital and Harvard Medical School, Boston, Massachusetts
                [c ]Department of Epidemiology and Biostatistics, University of Nevada, Las Vegas School of Public Health, Las Vegas, Naveda
                [d ]Division of Population Sciences, Dana-Farber Cancer Institute, Boston, Massachusetts
                [e ]Department of Nutrition, Harvard T.H. Chan School of Public Health, Boston, Massachusetts
                [f ]Department of Environmental Health, Harvard T.H. Chan School of Public Health, Boston, Massachusetts
                [g ]Department of Population Medicine, Harvard Medical School and Harvard Pilgrim Health Care Institute, Boston, Massachusetts
                [h ]Department of Social and Behavioral Sciences, Harvard T.H. Chan School of Public Health, Boston, Massachusetts, USA
                Author notes
                *Corresponding Author. Address: Department of Epidemiology and Biostatistics, University of Nevada, 4700 S. Maryland Pkwy, Ste. 335, Las Vegas, NV 89119. Email: nicole.deville@ 123456unlv.edu (N.V. DeVille)
                Author information
                https://orcid.org/0000-0002-2199-8805
                Article
                00003
                10.1097/EE9.0000000000000235
                9916023
                36777531
                f323a9bc-e876-4ae4-bad0-ff14b47e7287
                Copyright © 2022 The Authors. Published by Wolters Kluwer Health, Inc. on behalf of The Environmental Epidemiology. All rights reserved.

                This is an open-access article distributed under the terms of the Creative Commons Attribution-Non Commercial-No Derivatives License 4.0 (CCBY-NC-ND), where it is permissible to download and share the work provided it is properly cited. The work cannot be changed in any way or used commercially without permission from the journal.

                History
                : 11 July 2022
                : 12 November 2022
                Categories
                Original Research Article
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                mortality,neighborhood socioeconomic status,principal component analysis,women’s health

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