Concentrated affluence, concentrated disadvantage, and children's readiness for school: A population-based, multi-level investigation

Carpiano, Richard M.; Lloyd, Jennifer E. V.; Hertzman, Clyde

doi:10.1016/j.socscimed.2009.05.028

Cited by 69 publications

(59 citation statements)

References 45 publications

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“…• In contrast to the Gini Index (for income inequality) and Index of Dissimilarity (for racial segregation), which cannot be meaningfully used at lower levels of geography on account of spatial social segregation [14,44], the ICE can meaningfully be employed for both smaller and larger geographic units (e.g., census tract and city/town) [14][15][16][17][18][19][20][21].…”

Section: Betweenmentioning

confidence: 99%

“…Our concern, building on recent work on extreme concentrations of privilege and deprivation [14][15][16][17][18][19][20][21] and on local segregation [22][23][24][25], is that health outcomes are more likely to exhibit stronger associations with segregation measures that (1) are computed at the local, compared to city level, and (2) are computed jointly in relation to income and race/ethnicity, rather than only one or the other. To test our hypothesis, we selected an outcome welldocumented to be positively associated with adverse racial residential segregation and economic deprivation: fatal and non-fatal assaults, especially those involving firearms [26][27][28][29][30].…”

Section: Introductionmentioning

confidence: 99%

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Local Residential Segregation Matters: Stronger Association of Census Tract Compared to Conventional City-Level Measures with Fatal and Non-Fatal Assaults (Total and Firearm Related), Using the Index of Concentration at the Extremes (ICE) for Racial, Economic, and Racialized Economic Segregation, Massachusetts (US), 1995–2010

et al. 2017

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Research on residential segregation and health, primarily conducted in the USA, has chiefly employed city or regional measures of racial segregation. To test our hypothesis that stronger associations would be observed using local measures, especially for racialized economic segregation, we analyzed risk of fatal and nonfatal assault in Massachusetts (1995Massachusetts ( -2010, since this outcome is strongly associated with residential segregation. The segregation metrics comprised the Index of Concentration at the Extremes (ICE), the Index of Dissimilarity, and poverty rate, with measures computed at both the census tract and city/town level. Key results were that larger associations between fatal and non-fatal assaults and residential segregation occurred for models using the census tract vs. city/town measures, with the greatest associations observed for racialized economic segregation. For fatal assaults, comparing the bottom vs. top quintiles, the incidence rate ratio (and 95% confidence interval (CI)) in models using the census tract measures equaled 3.96 (95% CI 3.10, 5.06) for the ICE for racialized economic segregation, 3.26 (95% CI 2.58, 4.14) for the ICE for income, 3.14 (95% CI 2.47, 3.99) for poverty, 2.90 (95% CI 2.21, 3.81) for the ICE for race/ethnicity, and only 0.93 (95% CI 0.79, 1.11) for the Index of Dissimilarity; in models that included both census tract and city/town ICE measures, this risk ratio for the ICE for racialized economic segregation was higher at the census tract (3.29; 95% CI 2.43, 4.46) vs. city/town level (1.61; 95% CI 1.12, 2.32). These results suggest that, at least in the case of fatal and non-fatal assaults, research on residential segregation should employ local measures, including of racialized economic segregation, to avoid underestimating the adverse impact of segregation on health.

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Section: Betweenmentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

Local Residential Segregation Matters: Stronger Association of Census Tract Compared to Conventional City-Level Measures with Fatal and Non-Fatal Assaults (Total and Firearm Related), Using the Index of Concentration at the Extremes (ICE) for Racial, Economic, and Racialized Economic Segregation, Massachusetts (US), 1995–2010

et al. 2017

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“…30 Introduced into the social science literature in 2001 by Douglas Massey, a leading researcher on residential segregation, 13,14,31 the ICE has been used primarily in the social sciences, [32][33][34] as well as in a handful of etiological public health investigations. [35][36][37][38][39][40][41][42][43][44][45] To our knowledge, however, the ICE has not been used by any health department or agency with the responsibility of monitoring population health.…”

mentioning

confidence: 99%

“…[35][36][37][38][39][40][41][42][43] Recognizing the importance of the entangled realities of socioeconomic and racial/ethnic inequities in the United States, 3,11,22,23,26,[29][30][31] 2 small public health studies, however, used a novel ICE measure pertaining to concentrations of low-income Black persons versus high-income White persons, 44,45 which are the 2 groups who, in Massey's words, "continue to occupy opposite ends of the socioeconomic spectrum" in the United States. 51(p324) To determine whether ICE measures might be useful for monitoring population health, we examined health outcomes in relation to 2 sets of comparisons.…”

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confidence: 99%

Public Health Monitoring of Privilege and Deprivation With the Index of Concentration at the Extremes

et al. 2016

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Objectives. We evaluated use of the Index of Concentration at the Extremes (ICE) for public health monitoring.Methods. We used New York City data centered around 2010 to assess cross-sectional associations at the census tract and community district levels, for (1) diverse ICE measures plus the US poverty rate, with (2) infant mortality, premature mortality (before age 65 years), and diabetes mortality.Results. Point estimates for rate ratios were consistently greatest for the novel ICE P ublic health monitoring data need to be informative about not only health outcomes, but also their societal distribution and determinants, so that the data can be useful for policies, programs, and advocacy focused on improving population health and advancing health equity.1-3 Both the global and US literature increasingly recognize the importance of assessing progress and setbacks in reducing health inequities (i.e., unfair, unnecessary, and preventable health differences between the groups at issue). [1][2][3][4][5][6][7][8][9][10][11] Adding to the urgency of using measures that illuminate inequitable health gaps is growing concern about 21st-century rising concentrations of income and wealth [12][13][14][15][16][17][18][19] and their implications for public health and health inequities. 12,20,21 Most public health monitoring systems, however, do not employ metrics that convey societal distributions of concentrations of privilege and deprivation.1,2 Instead, the typical practice is to present health data in relation to characteristics measured at the individual or household level, such as income, educational level, and also, chiefly in the United States, race/ethnicity. Health outcomes are then compared across groups defined in relation to the chosen characteristics, which may be modeled either continuously or categorically. 1-3,22-24Some analyses additionally employ variants of these measures aggregated to the neighborhood level (e.g., percentage of persons or households below poverty, percentage of persons with less than a highschool education, percentage of persons who are Black). [22][23][24] In either case, although gaps in health outcomes can be quantified by comparing groups with less versus more resources, distributional information on the extent to which the population is divided into the groups at issue is not part of the metric. The excess risk of societal groups that get the proverbial short end of the stick becomes the focus, and these groups effectively become characterized as the "problem"; by contrast, the societal groups holding the stick's other, longer end simply stand as a referent group, and the problematic economic, political, and social relationships that produce health inequities are hidden from view. 11,12,25,26 A troubling feature of our era, however, is not a property of individuals or households but instead pertains to increasing spatial social polarization, part and parcel of growing concentrations of extreme income and wealth. [12][13][14][15][16][17][18][19][20][21]26,27

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“…Thus, the 17-fold variation in EDI-estimated developmental health validates this spatial geographic approach to local differences, since only this tactic captures the circumstances of real neighborhoods (Hertzman 2010;Kershaw et al 2009). Such an approach has been used, for example, to reveal that optimal, area level EDI scores occur within neighborhoods with mixed, rather than uniformly affluent, SES representation, i.e., those with relatively equal proportions of affluent and disadvantaged families (Carpiano et al 2009). Adopted on an even larger scale, such methods are capable of offering social ecological perspectives on the physical, socioeconomic, and social political conditions of children on a global scale (Panter-Brick et al 2012).…”

Section: The Topography Of Vulnerabilitymentioning

confidence: 99%

Early Childhood Health and the Life Course: The State of the Science and Proposed Research Priorities

Boyce

Hertzman

2017

Handbook of Life Course Health Development

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This chapter begins with an assertion that, beyond the cultural traditions that affirm childhood as a period of special and lasting importance, a new science of child development reveals an influence of the early years throughout the life course. Through processes of “biological embedding,” early developmental experiences and exposures become neurobiologically instantiated in the brain and genome, thereby affecting trajectories of health and development for the remainder of life. The socioeconomic maldistribution of exposures to adversities and misfortune allots a disproportionate share of physical and mental morbidities to those growing up in conditions of poverty and disadvantage. These outcomes now appear related to epigenetic interactions between aspects of allelic variation-based vulnerability and the assaultive or supportive conditions of early life. Future research should thus address how epigenetic regulation of gene expression is linked to the neurobiological processes underpinning developmental psychopathology and other maladaptive outcomes. Richer understanding of how early environments can amplify or diminish the impacts of adversity exposure will provide new insights to guide the construction of novel, effective, and early interventions.

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Concentrated affluence, concentrated disadvantage, and children's readiness for school: A population-based, multi-level investigation

Cited by 69 publications

References 45 publications

Public Health Monitoring of Privilege and Deprivation With the Index of Concentration at the Extremes

Early Childhood Health and the Life Course: The State of the Science and Proposed Research Priorities

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