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Housing Cost Burden

Households paying more than 30% or 50% of income on housing


I. FACTORS ATTRIBUTABLE TO HEALTH

Affordable, quality housing is central to health, conferring protection from the environment and supporting family life. Substandard housing is associated with increased risks of injury and respiratory ailments. Homes can be a source of exposure to radon, lead, asbestos or other hazardous agents. In children, lead exposure increases the risk of neurological impairment and developmental delays. Chronic homelessness is associated with higher rates of injuries, cancer, cardiovascular disease, substance addictions, mental disorders and death. Children and adolescents with transient housing have impaired academic performance. Housing costs—typically the largest, single expense in a family’s budget—also affect decisions that affect health. As housing consumes larger proportions of household income, families have less income for nutrition, health care, transportation, or education. Severe cost burdens may induce poverty, which is associated with developmental and behavioral problems in children and accelerated cognitive and physical decline in adults. Low-income families and minority communities are disproportionately affected by the lack of affordable, quality housing.

Controlled studies of the impact of housing characteristics or cost burdens on specific health outcomes are limited. However, cohort studies have documented adverse effects to health. Moisture linked to household mold was associated with respiratory illness, nausea, and fatigue. Lead abatement in residential housing was associated with abnormally elevated blood lead levels in children. Overcrowding in households was associated with higher incidence of tuberculosis. Housing insecurity, especially triggered by poverty, was associated with behavioral problems in children and excessive school absences.


II. Data Source and Methodology for Health Equity Analysis

Note to LHDs in California: The California Department of Public Health’s Healthy Communities indicator (HCI) project has already collected, cleaned, and compiled these data for this indicator for California, which can be found at http://www.cdph.ca.gov/programs/Pages/HealthyCommunityIndicators.aspx. For instructions on how to download and filter data from the HCI, see Appendix D.

Two datasets are used to understand housing cost burden at the local level. The ACS collects data on the percentage of household income spent on housing. These data are available for Census tracts in five-year aggregated samples through American FactFinder (tables DP04, B25070, and B25091). For a detailed explanation of how to ACS data, see Appendix B. Additionally, The U.S. Department of Housing and Urban Development (HUD) releases their Comprehensive Housing Affordability Strategy (CHAS) data, available at http://www.huduser.org/portal/datasets/cp.html. The advantage to CHAS data over the ACS tabulations is that CHAS data combine ACS microdata with HUD-adjusted median family incomes (HAMFI) to create estimates of the number of households that would qualify for HUD assistance.

The CHAS data also incorporate household characteristics (e.g., race/ethnicity, age, family size, and disability status) and housing unit characteristics (e.g., number of bedrooms and renter or owner costs). HAMFI is calculated at a place (i.e., city) level and is adjusted based on the apartment size, family size, ages of family members, cost of utilities, as well as other characteristics. It is also possible with CHAS data to include all households, discluding only those households where no rent or mortgage is paid. The smallest geography available for these data is at the Census place level (i.e., cities). For more information on HAMFI and HUD qualification, see the HUD website at http://www.huduser.org/publications/pdf/CHAS_affordability_Analysis.pdf.

The indicators available are households spending 30% or more of adjusted household income on housing and households spending 50% or more of adjusted income on housing, which include rent and home ownership costs. The maps below show housing cost burden at the place level from CHAS and at the Census tract level from the ACS.


How To Analyze Housing Cost Burden Data

Example 1: Bay Area CHAS Data at the Census Place Level

A spreadsheet with the housing cost burden data at the Census place level was joined to an ArcGIS shapefile to produce the maps below. Categories are identified with the natural breaks method in ArcGIS. Upon examination of mapped CHAS data, there appears to be multiple Census places (i.e., towns and cities) in Alameda and Contra Costa counties where a higher percentage of households are spending more than 30% of their adjusted income on housing. To examine more closely, example 2 illustrates the percentage of households paying 50% or more of adjusted income on housing at the Census tract level in Alameda and Contra Costa counties using ACS data. Areas marked as unstable had a relative standard error greater than 30, which is explained in more detail in Appendix D.

Figure 20 shows housing cost burden downloaded from the ACS at the Census tract level. While data from the ACS alone is less robust than the data from HUD–CHAS, it does estimate housing burden at the Census tract level, compared to the city level available only with CHAS. Census tract level analysis may be more useful for health departments if less precise than city-level estimates. The map identifies Census tracts in the western region of Contra Costa and Alameda County where greater than 25% of households are paying more than 50% of their income on housing. Areas marked as unstable had a relative standard error greater than 30, which is explained in more detail in Appendix D.

Figure 19: Percentage of households paying greater than 30% of income on housing by Census place, BARHII Region, 2006–2010

Figure 19: Percentage of households paying greater than 30% of income on housing 
by Census place, BARHII Region, 2006–2010
Figure 20: Percentage of households paying greater than 50% of income on housing
by Census tract, Alameda and Contra Costa Counties, 2006–2010
Figure 20: Percentage of households paying greater than 50% of income on housing 
by Census tract, Alameda and Contra Costa Counties, 2006–2010

III. BAY AREA LOCAL HEALTH DEPARTMENT EXAMPLES


Supporting Affordable Housing Policy in Richmond
Contra Costa County Health Services

Contra Costa Health Services (CCHS) is working with the City of Richmond to support affordable housing policies that maximize health equity within the city. This partnership arose from a draft health impact assessment (HIA) by CCHS on the Richmond Livable Corridors Project, a zoning change within central Richmond. In this HIA, CCHS identified connections between housing and health as a key area of health concern: approximately half of the city’s households pay more than they can afford for housing, with even greater proportions for low-income households (61% of renters and 82% of homeowners). Richmond has also recognized quality affordable housing as a key element of their HiAP framework.

To address this issue, CCHS has drafted a report that analyzes potential updates to Richmond’s inclusionary zoning ordinance—a policy that requires new market rate housing developments to include some percentage of affordable housing, or else to contribute fees to an affordable housing fund. The report uses criteria on the connections between health and housing, such as cost burden, housing quality, and housing stability, to recommend a variety of policy options. These options include targeting households at lower income levels, raising fees to encourage market rate developers to build affordable housing on site, and lengthening the terms of affordability on housing units. CCHS has been invited to present this work to key decision-makers within the city and plans to continue partnering with Richmond to support healthy housing policy.


Tenant Justice Coalition and Gentrification Report
Alameda County Public Health Department

The Alameda County Public Health Department (ACPHD) Place Matters Housing Workgroup partnered with community-based organizations and tenant advocates in Oakland to provide research and city council testimony on the impacts of rising rental costs and lack of affordable, quality housing for neighborhood stability and health. In spring of 2014, the Tenant Justice Coalition won improvements to Oakland’s rent ordinance which capped all rent increases at 10% annually and reduced the amount in rent that landlords can pass through to tenants when making capital improvements on their properties. These policy changes are the first significant reforms for tenants in Oakland in more than ten years.

Additionally, in collaboration with Causa Justa::Just Cause, ACPHD formed a research partnership to analyze gentrification and displacement from a public health and tenants’ rights perspective, and to recommend strategies for preventing displacement in future development. The partnership tackles the controversial and often misunderstood issue of gentrification, and seeks to provide analysis grounded in community experience that leads to policy and systems change for the benefit of communities most affected by gentrification and displacement—urban low-income communities and communities of color. A report, Development without Displacement: Resisting Gentrification in the Bay Area, was released in April 2014 from this partnership and can be found at http://cjjc.org/publications/reports/item/1421-development-without-displacement-report.


Asthma Start and Healthy Homes Programs
Alameda County Public Health Department

Alameda County Public Health Department’s Asthma Start and Alameda County Healthy Homes programs works with Oakland families to eliminate asthma triggers in their homes.  Some triggers are impossible to remove without the landlord’s help, like moldy carpet. In fact, Asthma Start reported that for a recent 12-month period, over 40% of the 370 homes they visited contained some signs of mold. The Place Matters Housing Workgroup prioritized advancing policies that will improve rental housing. They have partnered with the City of Oakland and code enforcement officials to effectively address housing conditions that are linked with poor health in Oakland rental properties. They researched new models of code enforcement that are more focused on preventing health harming conditions and presented the findings to City staff and a Building Services Improvement Taskforce. The Oakland City Council’s Community and Economic Development Committee approved the Task Force’s recommendations to move forward with piloting this model. The proposed program design can be found at http://www2.oaklandnet.com/oakca/groups/ceda/documents/report/oak033410.pdf.



REFERENCES

Baggett TP, Hwang SW, O’Connell JJ et al. 2013. Mortality among Homeless Adults in Boston: Shifts in Causes of Death over a 15-year Period. JAMA Internal Medicine 173(2):189-195.

Robert Wood Johnson Foundation, Commission to Build a Healthier America. 2008. Housing and Health, Issue Brief 2.

Stone ME. 2006. What is Housing Affordability? The Case for the Residual Income Approach. Housing Policy Debate 17(1):151–184.

Thomson H, Thomas S, Sellstrom E, Petticrew M. 2013. Housing Improvements for Health and Associated Socio-economic Outcomes. Cochrane Database of Systematic Reviews 2:335.

Office of the Deputy Prime Minister. 2004. The Impact of Overcrowding on Health & Education: A Review of Evidence and Literature. Wetherby, UK: Office of the Deputy Prime Minister Publications.

California Department of Housing & Community Development. 2013. Housing and Health.