Contributions of social context to inequalities in years of life lost to heart disease in Texas, USA

Franzini, Luisa; Spears, William

doi:10.1016/s0277-9536(03)00018-2

Cited by 87 publications

(76 citation statements)

References 64 publications

Supporting

Mentioning

Contrasting

Order By: Relevance

“…First, our analysis confirms previously published observations of a socioeconomic gradient in premature mortality in the U.S., as reported in both the handful of other analyses using CT poverty, 7,14,23 as well as those employing economic indicators based on larger geographic areas (e.g., neighborhoods, metropolitan areas, and counties). [4][5][6] Only two of these prior studies used a multilevel analysis 7,23 ; the rest used the more conventional approach of comparing rates based on aggregating the death and population data into strata defined by area-based socioeconomic position. Although this latter approach, by ignoring spatial variation, could potentially yield biased estimates, we note in our study that this did not occur, as shown by the similarity of the socioeconomic gradients estimated in Tables 1 and 2.…”

Section: Discussionsupporting

confidence: 89%

“…Additionally, a growing body of research documents that premature mortality is a powerful indicator of disparities in both health status and access to health care, with risk of premature death directly increasing with economic deprivation. [4][5][6][7][8] For example, in Massachusetts in 2001, the premature mortality rate (deaths before age 75, age-standardized to the year 2000 standard million) was two times higher in the worst-off cities and towns (with rates in excess of 450 per 100,000) compared with the best-off areas (rates õ220/100,000). 9 Regarding socioeconomic measures, major obstacles have been the lack of routinely collected socioeconomic data in U.S. public health surveillance systems and the inability to link to population denominators stratified by the same measures.…”

Section: Introductionmentioning

confidence: 99%

See 1 more Smart Citation

Mapping and Measuring Social Disparities in Premature Mortality: The Impact of Census Tract Poverty within and across Boston Neighborhoods, 1999–2001

et al. 2006

View full text Add to dashboard Cite

The identification and documentation of health disparities are important functions of public health surveillance. These disparities, typically falling along lines defined by gender, race/ethnicity, and social class, are often made visible in urban settings as geographic disparities in health between neighborhoods. Recognizing that premature mortality is a powerful indicator of disparities in both health status and access to health care that can readily be monitored using routinely available public health surveillance data, we undertook a systematic analysis of spatial variation in premature mortality in Boston (1999Boston ( -2001 across neighborhoods and sub-neighborhoods in relation to census tract (CT) poverty. Using a multilevel model based framework, we estimated that the incidence of premature mortality was 1.39 times higher (95% credible interval 1.09-1.78) among persons living in the most economically deprived CTs (Q20% below poverty) compared to those in the least impoverished tracts (G5% below poverty). We present maps of model-based standardized mortality ratios that show substantial withinneighborhood variation in premature mortality and a sizeable decrease in spatial variation after adjustment for CT poverty. Additionally, we present maps of modelbased direct standardized rates that can more readily be compared to externally published rates and targets, as well as maps of the population attributable fraction that show that in some of Boston's poorest neighborhoods, the proportion of excess deaths associated with CT poverty reaches 25-30%. We recommend that these methods be incorporated into routine analyses of public health surveillance data to highlight continuing social disparities in premature mortality.

show abstract

Section: Discussionsupporting

confidence: 89%

Section: Introductionmentioning

confidence: 99%

Mapping and Measuring Social Disparities in Premature Mortality: The Impact of Census Tract Poverty within and across Boston Neighborhoods, 1999–2001

et al. 2006

View full text Add to dashboard Cite

show abstract

“…As in our study, some research has previously investigated whether associations between area characteristics and health are stronger for theoretically better scales of measurement. Several such studies have reported stronger health effects for characteristics measured at a smaller level within the range being considered here (Hyndman et al, 1995, Krieger et al, 2002a, Franzini and Spears, 2003, Schuurman et al, 2007, while others have reported that results were similar across neighborhood definitions (Davey Smith et al, 1998, Diez Roux et al, 2001a, Fiscella and Franks, 2001, Thomas et al, 2006, Berke et al, 2007. In particular, while the use of US ZIP codes has been critiqued because of their instability over time, variability in size, and lack of correspondence with other political, statistical or administrative boundaries (Krieger et al, 2002b), others have recommended ZIP codes for ease of use (Fiscella and Franks, 2001).…”

Section: Discussionmentioning

confidence: 91%

Evaluating options for measurement of neighborhood socioeconomic context: Evidence from a myocardial infarction case–control study

et al. 2008

View full text Add to dashboard Cite

We hypothesized that neighborhood socioeconomic context would be most stronly associated with risk of myocardial infarction (MI) for smaller "neighborhood" definitions. We used data on 487 nonfatal, incident MI cases and 1,873 controls from a case-control study in Washington State. Census data on income, home ownership, and education were used to estimate socioeconomic context across four neighborhood definitions: one-kilometer buffer, block group, census tract, and ZIP code. No neighborhood definition led to consistently stronger associations with MI. Although we confirmed the association between neighborhood socioeconomic measures and risk of MI, we did not find these associations sensitive to neighborhood definition. Gina Lovasi, PhD, 820 IAB, MC 3355, 420 W 118th St, New York NY 10027, 212-854-3804 (office), 646-761-1362 (mobile), 212-854-8925 (fax), gl2225@columbia.edu. Publisher's Disclaimer: This is a PDF file of an unedited manuscript that has been accepted for publication. As a service to our customers we are providing this early version of the manuscript. The manuscript will undergo copyediting, typesetting, and review of the resulting proof before it is published in its final citable form. Please note that during the production process errors may be discovered which could affect the content, and all legal disclaimers that apply to the journal pertain. Socioeconomic disparities in health have received increasing attention by researchers (Adler and Ostrove, 1999) and policy makers (Mackenbach and Bakker, 2003) in recent decades. Socioeconomic status (SES) has been posited to be a "fundamental cause" of health disparities (Phelan et al., 2004, Williams andCollins, 2001), such that the association between SES and health is created when higher status individuals or groups mobilize flexible resources, such as money and prestige, to avoid illness and death. There is also evidence from human and animal studies that psychosocial stress in response to relative social status contributes to mortality and disease for low status individuals (Wilkinson,1999, Steptoe andMarmot, 2002) and those living in more deprived areas (Elliott, 2000). Socioeconomic characteristics measured for individuals and areas have commonly included the domains of education, employment, occupational status, income, and material resources (Braveman et al., 2005, Krieger et al., 2002a, Carstairs, 2000. The questionnaires or other methods used to ascertain such characteristics differ across settings and studies (Krieger et al., 1997), and area-based socioeconomic characteristics have the additional complication of being measured at different scales or levels of aggregation (Pickett and Pearl, 2001). NIH Public AccessIn studies of neighborhood socioeconomic context and health, several scales of measurement are used without consensus as to which is most relevant. The modifiable areal unit problem, like the ecological fallacy, is a concern for such studies because study results may be sensitive to the selected measurement scale (Guagliard...

show abstract

“…Based on a review of literature, we identified 20 census variables that have been used consistently to approximate neighborhood-level environments for possible inclusion in the deprivation index. These measures included the following * : one education variable, 47,48 two employment, 49,50 five housing, [51][52][53] four variables representing occupation, 10,54 five poverty, [55][56][57][58] one racial composition, 51,59 and two residential stability.…”

Section: Data Reduction and Exposure Definitionmentioning

confidence: 99%

The Development of a Standardized Neighborhood Deprivation Index

et al. 2006

View full text Add to dashboard Cite

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)(1999)(2000)(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 Bdeprivation^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.

show abstract

Contributions of social context to inequalities in years of life lost to heart disease in Texas, USA

Cited by 87 publications

References 64 publications

Mapping and Measuring Social Disparities in Premature Mortality: The Impact of Census Tract Poverty within and across Boston Neighborhoods, 1999–2001

Mapping and Measuring Social Disparities in Premature Mortality: The Impact of Census Tract Poverty within and across Boston Neighborhoods, 1999–2001

Evaluating options for measurement of neighborhood socioeconomic context: Evidence from a myocardial infarction case–control study

The Development of a Standardized Neighborhood Deprivation Index

Contact Info

Product

Resources

About