NEIGHBORHOODS AND HEALTH: Building Evidence for Local Policy Cross-Site Analysis Kathy Pettit and Tom Kingsley The Urban Institute

NNIP uCollaborative effort - Urban Institute and local partners in twenty cities uPartners operate local information systems - Recurrently updated neighborhood data - Multiple topics-data sources uSuccess from 3 kinds of innovations 1. Technological 2. Institutional 3.Using information for change uCompetitive procurement this study - 9 proposals, 5 selected

Research questions Neighborhood conditions and health outcomes uBasic relationships health, demographic and contextual variables - Multiple cities, consistent definitions -Variations across sites uHow relationships change over time -Long time series almost all sites -Specifically – 1990s trends in high-poverty areas uFeasibility – tract level analysis

5 sites - major differences Metro area population growth - Slow in Cleveland and Providence - Rapid in Denver, moderate Indianapolis, Oakland

Racial/ethnic contrasts - Cleveland, Indianapolis: high share black - Denver, Providence: rapid Hispanic growth - Oakland: minority-majority expanding

Concentrated Poverty uDevastating effects, inner-city neighborhoods -Loss of the middle-class, institutions and role models -Concentration “magnifies poverty and exacerbates its effects.” uConcentration - seemingly inexorable trend - Major increases in 1970s and 1980s share of poor in high-poverty tracts uWhat happened in the 1990s?

Nationally – important reduction in concentrated poverty - Share of poor: down in high categories up in middle categories

5 sites, overall poverty rate - change not dramatic, 1990s

Concen. poverty: bigger changes - major drops, Cleveland, Denver - modest declines, Indianapolis, Oakland - increase in Providence

% adults without HS degree Improvements in high-poverty neighborhoods – all sites

% adults without HS degree but major gaps remain re rest of city

% households rec. pub. assistance Major declines, high-poverty neighborhoods – all sites

% households rec. pub. assistance again, major gaps remain

Rental vacancy rates Tight housing markets exacerbate other problems

Research approach Neighborhood conditions and health outcomes uScan of Birth and Mortality Outcomes - Diversity of levels and trends within & between cities uExamine relationships between health and neighborhood conditions -Bivariate and Multivariate analyses

Maternal and Infant Health Indicators u Pct. low-birth weight infants u Pct. of births to mothers with early prenatal care u Teen birth rates (age 15-19) u Age-adjusted mortality rate u Infant mortality rate

Gaps between poor/non-poor vary u Confirmed that gaps exist between high- poverty and non-poor tracts u BUT gaps vary by city and indicator -Gaps most consistent for prenatal care -Gaps generally lower in Oakland, Providence (smaller geographies)

Pct. low birth weight births, 1998/2000 Large gaps seen in black/white cities

Teen Birth Rates in Denver

Some progress in health outcomes across all neighborhoods u Improvements in both high-poverty and non-poor neighborhoods u BUT generally not enough to close gaps u Direction and speed of change varies by city and indicator -Oakland generally saw most improvements -Teen birth, infant mortality rates dropped in all -Some troubling signs in Providence

Age-Adjusted Death Rates Begin together, but paths diverge High poverty census tracts

Oakland: Change in Early Prenatal Care Rates

Lessons from Introductory Scan u Improvements are possible u Racial/ethnic differences -Change in teen births -Low birth rates u Policy and programs can have impact -Healthy Start -Campaign for Healthy Babies

Pathways of Neighborhood Effects on Health (Ellen et al. 2001) u Physical Stressors u Social Stressors u Neighborhood-based Networks & Norms u Neighborhood Institutions & Resources

Static Research Hypotheses Poorer birth & mortality outcomes will be associated with: -higher levels of minority and immigrant population -higher shares of low-income households -higher levels of social risk factors -poor housing quality -higher crime rates -more mobile and transient population

Dynamic Research Hypotheses Some relationships will remain positive, but have decreased in strength over the 1990s -high minority tracts and poor birth and mortality outcomes -lower-income tracts and lower prenatal care rates -lower-income tracts and higher low-birth weight rates

Socioeconomic Links Hold True uPoorer birth & mortality outcomes will be associated with: -higher levels of minority and immigrant population »True except for foreign-born with low-birth weight & mortality rates -higher shares of low-income households »True for all measures (poverty, income, TANF, public assistance) -higher levels of social risk factors »True for all measures (No HS, female-headed HH with children, unemployed)

Physical, Social Stressors Matter Social Network Proxies Mixed uPoorer birth & mortality outcomes will be associated with: -poor housing quality »True for all measures (older housing, overcrowded, home values and mortgage amounts) -higher crime rates »Not true for prenatal care, strongest with teen birth rates -more mobile and transient population »True for renter-occupancy & vacancy, mobility »Not true for change in population

Mixed results in link between non-white areas & poor health outcomes uSome relationships will remain positive, but have decreased in strength over the 1990’s: -High minority tracts and poor birth and mortality outcomes »True for low birth weight »Not true for prenatal care and pct. Hispanic »Not true for teen birth (much higher correlations) or mortality rates (about the same)

Again, mixed results in link between low- income areas & poor health outcomes uSome relationships will remain positive, but have decreased in strength over the 1990’s: -lower-income tracts and lower prenatal care rates »True but only slight drop in relationship -lower-income tracts and higher low-birth weight rates »True for all measures of income

Multivariate Regression uTo test independent relationships of birth/mortality outcomes with neighborhood context variables uTo test how much variation the neighborhood context variables explained uTo test shifts over time for significance

Regression Model uNeighborhood Indicators -Pct. African-American, Pct. Hispanic -Average Family Income -Pct. population not employed -Pct pop > age 5 who moved in past 5 years uDummy Variables -City, year, and interaction of city & year

Regression Summary u Regression strongest for prenatal care rates -R-Squared:.45 (teen births) to.77 (prenatal care) uNeighborhood variables did explain some variation -Pct. population not employed had highest coefficient uConditions specific to time and place matter -not just due to racial or income change

How well do neighborhood conditions explain differences in rates? Reference City is Cleveland

Testing for significance of change in unobserved characteristics Reference is Cleveland 1999 rate Differences in Early Prenatal Care Rates

NEIGHBORHOODS AND HEALTH: Building Evidence for Local Policy Cross-Site Analysis Kathy Pettit and Tom Kingsley The Urban Institute