Sub-County Life Expectancy: A Tool to Improve Community Health and Advance Health Equity

Boothe, Vickie L.; Fierro, Leslie A.; Laurent, Amy A.; Shih, Margaret

doi:10.5888/pcd15.170187

Cited by 9 publications

(11 citation statements)

References 25 publications

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“…≥85 y). We developed ZCTA-, county-, and state-level life expectancy estimates by using the Sub-County Assessment of Life Expectancy (SCALE) methodology ( 6 ), which uses an adjusted Chiang II methodology in the form of a validated tool from the South East Public Health Observatory ( 7 ). We suppressed any life expectancy estimate with a standard error of 2 years or more (n = 21).…”

Section: Methodsmentioning

confidence: 99%

Examining Variation in Life Expectancy Estimates by ZIP Code Tabulation Area (ZCTA) in Hawaii’s Four Main Counties, 2008–2012

et al. 2018

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Section: Methodsmentioning

confidence: 99%

Examining Variation in Life Expectancy Estimates by ZIP Code Tabulation Area (ZCTA) in Hawaii’s Four Main Counties, 2008–2012

et al. 2018

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“…Estimates of life expectancy were also assigned missing values if the county had fewer than 5000 population years at risk in the time frame, the point at which estimates are thought to yield biased values and large errors. 7,12 To test the criterion validity of life expectancy, we examined associations with YPLL-75 and PAAM using studentized residuals, a statistical method to identify outliers. We identified outlier counties by discordance of >3 SDs from the mean of the regression between YPLL-75 and life expectancy or PAAM and life expectancy.…”

Section: Life Expectancymentioning

confidence: 99%

Comparative Methodologic and Practical Considerations for Life Expectancy as a Public Health Mortality Measure

et al. 2021

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Introduction Life expectancy is a public health metric used to assess mortality. We describe life expectancy calculations for US counties and present methodologic considerations compared with years of potential life lost before age 75 (YPLL-75) and premature age-adjusted mortality (PAAM), 2 commonly used length-of-life metrics. Methods We used death data from the National Center for Health Statistics for 2015-2017 and other health measures from the 2019 County Health Rankings & Roadmaps. We calculated life expectancy from birth at the county level using an abridged life table and the Chiang method of variance. Studentized residuals identified counties with discordant life expectancy and YPLL-75 or PAAM values. Correlations tested associations of life expectancy with key health measures (eg, smoking, child poverty, uninsured). Results Among 3073 US counties, life expectancy ranged from 62.4 to 98.0 years, with a mean of 77.4 years. Life expectancy was strongly and negatively correlated with YPLL-75 ( r = −0.91) and PAAM ( r = −0.95) at the county level. Life expectancy was also associated with other key health metrics, such as smoking, employment, and education rates, where an improvement in the health factor indicated improvement in the respective length-of-life measure. Counties with discordant life expectancy and YPLL-75 or PAAM values had differing age structures. Practice Implications Commonly used length-of-life metrics in population health settings are differentiated by methodological matters, such as computation complexity, data availability, and differential risk among age groups, especially among the very old or very young. The choice of metric should consider these factors, in addition to practical concerns, such as the communication needs of the audience.

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“…This present study is conducted in concert with the Florida Department of Health and the Center for Disease Control and Prevention (CDC), and CTSE's (Council of Territorial and State Epidemiologists) Sub-County Assessment of Life Expectancy (SCALE) initiative [20]. Identifying the drivers behind differences in LE can provide researchers with the tools to monitor and address the underlying conditions contributing to unequitable health outcomes [21].…”

Section: Introductionmentioning

confidence: 99%

Florida neighborhood analysis of social determinants and their relationship to life expectancy

Uejio

Kintziger

Reid³

et al. 2020

BMC Public Health

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Background Social determinants of health (SDOH) contribute to unequal life expectancy (LE). Only a handful of papers have analyzed these relationships at the neighborhood level as opposed to the county level. This study draws on both the SDOH and social vulnerability literature to identify relevant factors affecting LE. Methods LE was calculated from mortality records for Florida from 2009 to 2013 for 3640 census tracts with reliable estimates. A spatial Durbin error model (SDEM) quantified the direction and magnitude of the factors to LE. The SDEM contains a spatial error term and jointly estimates both local and neighborhood associations. This methodology controls for non-independence between census tracts to provide unbiased statistical estimates. Results Factors significantly related to an increase in LE, include percentage (%) of the population who identify as Hispanic (beta coefficient [β]: 0.06, p-value [P] < 0.001) and % of age dependent populations (% population < 5 years old and % population > 65) (β: 0.13, P < 0.001). Conversely, the following factors exhibited significant negative LE associations, % of households with no automobile (β: -0.05, P < 0.001), % of mobile homes (β: -0.02, P < 0.001), and % of female headed households (β: -0.11, P < 0.001). Conclusions Results from the SDEM demonstrate social vulnerability indicators account for additional geographic LE variability beyond commonly studied SDOH. Empirical findings from this analysis can help local health departments identify drivers of spatial health disparities at the local level.

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Sub-County Life Expectancy: A Tool to Improve Community Health and Advance Health Equity

Cited by 9 publications

References 25 publications

Examining Variation in Life Expectancy Estimates by ZIP Code Tabulation Area (ZCTA) in Hawaii’s Four Main Counties, 2008–2012

Examining Variation in Life Expectancy Estimates by ZIP Code Tabulation Area (ZCTA) in Hawaii’s Four Main Counties, 2008–2012

Comparative Methodologic and Practical Considerations for Life Expectancy as a Public Health Mortality Measure

Florida neighborhood analysis of social determinants and their relationship to life expectancy

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