Chapter 10. Priority Populations (continued)

National Healthcare Disparities Report, 2011


Low-Income Groups

In this report, poor populations are defined as people living in families whose household income falls below specific poverty thresholds. These thresholds vary by family size and composition and are updated annually by the U.S. Bureau of the Census (U.S. Census Bureau, 2011b). After falling for a decade (1990-2000), the number of poor people in America rose from 31.6 million in 2000 to 42.9 million in 2009. In 2009, 14.3% of the U.S. population had incomes below their respective poverty thresholds (Bishaw & Macartney, 2010).

Poverty varies by race and ethnicity. In 2010, 14% of Whites, 36% of Blacks, 35% of Hispanics, and 23% of other races had incomes below the poverty level (Urban Institute and Kaiser, 2010).  People with low incomes often experience worse health and are more likely to die prematurely (Adler & Newman, 2002). In general, poor populations have reduced access to high-quality care. While people with low incomes are more likely to be uninsured, income-related differences in quality of care that are independent of health insurance coverage have also been demonstrated (Brown, et al., 2003).

Previous chapters of this report describe health care differences by income. Of all measures of health care quality and access that are tracked in the reports and support trends over time, poorvi individuals had worse care than high-incomevii individuals in the most recent year for 52 measures.  Most of these measures showed no significant change in disparities over time.

For 5 measures, the gap between poor and high-income individuals grew smaller, indicating improvement:

  • Hospital admissions for uncontrolled diabetes per 100,000 population age 18 and over.
  • Hospital admissions for long-term complications of diabetes per 100,000 population age 18 and over.
  • Hospital admissions for congestive heart failure per 100,000 population.
  • Children ages 2-17 who had a dental visit in the calendar year.
  • Hospital admissions for asthma per 100,000 population.

For 4 measures, the gap grew larger, indicating worsening disparities:

  • Adults age 50 and over who ever received a colonoscopy, sigmoidoscopy, or proctoscopy.
  • Deaths per 1,000 adult hospital admissions with pneumonia.
  • People without a usual source of care who indicated a financial or insurance reason for not having a source of care.
  • Adults who did not have problems seeing a specialist they needed to see in the last 12 months.

Residents of Rural Areas

About one in five Americans lives in a nonmetropolitan area (IOM, 2005). Compared with their urban counterparts, rural residents are more likely to be older, be poor (Ziller, et al., 2003), be in fair or poor health, and have chronic conditions (IOM, 2005). Rural residents are less likely than their urban counterparts to receive recommended preventive services and on average report fewer visits to health care providers (Larson & Fleishman, 2003).

Although about 19% of Americans live in rural areas, only 11% of physicians in America practice in those settings (Rosenblatt, et al., 2010). Other important providers of health care in those settings include nurse practitioners, nurse midwives, and physician assistants. A variety of programs deliver needed services in rural areas, such as the National Health Service Corps Scholarship Program, Indian Health Service, State offices of rural health, rural health clinics, and community health centers.

Many rural residents depend on small rural hospitals for their care. There are approximately 2,000 rural hospitals throughout the country (AHA, 2011). Most of these hospitals are critical access hospitals that have 25 or fewer beds. Rural hospitals face unique challenges due to their size and case mix. During the 1980s, many were forced to close due to financial losses (AHRQ, 1996). More recently, finances of small rural hospitals have improved and few closures have occurred since 2003.

Transportation needs are pronounced among rural residents, who must travel longer distances to reach health care delivery sites. Of the nearly 1,000 "frontier counties"viii in the Nation, most have limited health care services and many do not have any (Frontier Education Center, 2000).

Geographic areas are classified in different ways depending on the data source. Chapter 1, Introduction and Methods, provides more information on the classifications used. In this chapter, we compare residents of noncoreix (rural) areas with residents of large fringe metropolitan (suburban) areas because residents of suburban areas tend to have higher quality health care and better outcomes.  Of all measures of health care quality and access that are tracked in the reports and support trends over time, residents of noncore areas had worse care than residents of large fringe metropolitan areas in the most recent year for 30 measures. Most of these measures showed no significant change in disparities over time. 

For one measure, the gap between residents of noncore and large fringe metropolitan areas grew smaller, indicating improvement:

  • Hospital admissions for uncontrolled diabetes per 100,000 population age 18 and over.

For 3 measures, the gap grew larger, indicating worsening disparities:

  • Cancer deaths per 100,000 population per year.
  • Deaths per 1,000 adult hospital admissions with pneumonia.
  • Adults with obesity who ever received advice from a health provider about eating fewer high-fat or high-cholesterol foods.

Individuals With Disabilities or Special Health Care Needs

The NHDR tracks many measures of relevance to individuals with disabilities or special health care needs. Data are often limited, and AHRQ has worked with Federal partners to improve reporting on health care quality for individuals with disabilities.

In 2007, AHRQ convened a disabilities subgroup of the NHQR/NHDR Interagency Work Group. This subgroup received assistance from the Interagency Subcommittee on Disability Statistics of the Interagency Committee on Disability Research. The charge to the disabilities subgroup was to advise AHRQ on measures of disabilities from existing data that could track disparities for disabled individuals in quality of and access to care and that would be comparable across national surveys. For this initial effort, the subgroup focused on measures for adults, a population for which the most survey data are available.

For the 2011 NHDR, AHRQ is again using a broad, inclusive measure of disability for adults. This definition is intended to be consistent with statutory definitions of disability, such as the first criterion of the 1990 Americans With Disabilities Act (ADA) (i.e., having a physical or mental impairment that substantially limits one or more major life activities [HHS, 2005; LaPlante, 1991]) and Federal program definitions of disability based on the ADA. For the purpose of the NHDR, adults with disabilities are those with physical, sensory, and/or mental health conditions that can be associated with a decrease in functioning in such day-to-day activities as bathing, walking, doing everyday chores, and engaging in work or social activities.

In displaying the data on disability, paired measures are shown to preserve the qualitative aspects of the data:

  • Limitations in basic activities represent problems with mobility and other basic functioning at the person level.
  • Limitations in complex activities represent limitations encountered when the person, in interaction with the environment, attempts to participate in community life.

Limitations inbasicactivities include problems with mobility, self-care (activities of daily living), domestic life (instrumental activities of daily living), and activities that depend on sensory functioning (limited to people who are blind or deaf). Limitations in complex activities include limitations experienced in work and in community, social, and civic life. The use of the subgroup's recommendation of these paired measures of basic and complex activity limitations is conceptually similar to the way others have divided disability and is consistent with the International Classification of Functioning, Disability, and Health separation of activities and participation domains (WHO, 2001).

These two categories are not mutually exclusive; people may have limitations in basic activities and complex activities. The residual category Neither includes adults with neither basic nor complex activity limitations.

In this year's reports, analyses by activity limitations for adults are presented for selected measures in the Effectiveness, Lifestyle Modification section and in the Care Coordination chapter of the NHDR and in the Patient Centeredness and Access chapters of the NHQR. In addition, the Data Tables appendix includes activity limitations as a stub variable for all National Health Interview Survey and Medical Expenditure Panel Survey tables.

Of all measures of health care quality and access that are tracked in the reports and support trends over time, individuals with basic activity limitations had worse care than individuals with neither basic nor complex activity limitations in the most recent year for 15 measures. Individuals with complex activity limitations had worse care than individuals with neither basic nor complex activity limitations in the most recent year for 16 measures. None of these measures showed any significant change in disparities over time.

New! Lesbian, Gay, Bisexual, and Transgender Populations

Note: This section is excerpted with permission from the National Transgender Discrimination Survey Report on Health and Health Care (Grant, et al., 2011). Minor edits have been made to conform to Government style conventions and make the text consistent with the rest of the report.

Every day, transgender and gender-nonconforming people bear the brunt of social and economic marginalization due to their gender identity. Advocates who work with transgender and gender-nonconforming people have known this for decades as they have worked with clients to find housing, obtain health and partnership benefits, or save jobs for clients who are terminated due to bias. Too often, policymakers, service providers, the media, and society at large have dismissed or discounted the needs of transgender and gender-nonconforming people in their communities, and a paucity of hard data on the scope of antitransgender discrimination has hampered the struggle for basic fairness.

In 2008, the National Center for Transgender Equality and the National Gay and Lesbian Task Force formed a groundbreaking research partnership to address this problem, launching the first comprehensive national transgender discrimination study. Transgender individuals are the most vulnerable among the LGBT populations. Therefore, this partnership sought to address the gap in information for these individuals as a first step.

Over 8 months, a team of community-based advocates, transgender leaders, researchers, lawyers, and LGBT policy experts came together to create an original survey instrument. More than 7,000 people responded to the 70-question survey, providing data on virtually every significant aspect of transgender discrimination, including housing, employment, health and health care, education, public accommodation, family life, criminal justice, and identity documents. The health findings are presented here. More extensive demographic and methodological information can be accessed in the original report, Injustice at Every Turn: A Report of the National Transgender Discrimination Survey.

Access to Health Care

A majority of study participants sought care through a doctor's office (60%); however, a significant minority used health centers and clinics (28%).

Figure 10.1. Primary source of medical care, LGBT population, 2008

Figure 10.1. Primary source of medical care, LGBT population, 2008. For details, go to [D] Text Description below.

[D] Select for Text Description.

Source: Reprinted from the National Transgender Discrimination Survey Report on Health and Health Care, 2011.

Four percent of respondents primarily used emergency rooms (ERs) for care. Several studies have shown that individuals who use ERs for primary care experience more adverse health outcomes than those who regularly see a primary physician.x Factors that correlated with increased use of ERs were:

  • Race—17% of African Americans used ERs as did 8% of Latino/a respondents.
  • Income—8% of respondents earning under $10,000 per year used ERs.
  • Employment status—10% of unemployed respondents and 7% of those who had lost their jobs due to bias used ERs.
  • Education—13% of those with less than a high school diploma used ERs.

Visual conformersxi and those who had identity documents that matched their presentation had the highest rates of using doctor's offices for their care.

Discrimination by Medical Providers

Denial of health care and multiple barriers to care are commonplace in the lives of transgender and gender-nonconforming people. Subjects in our study seeking health care were denied equal treatment in doctor's offices and hospitals (24%), in ERs (13%), in mental health clinics (11%), by EMTs (5%), and in drug treatment programs (3%).xii

Female-to-male (FTM) respondents reported higher rates of unequal treatment than male-to-female (MTF) respondents. Latino/a respondents reported the highest rate of unequal treatment of any racial category (32% by a doctor or hospital and 19% in both ERs and mental health clinics).

Figure 10.2. People who were refused medical care, by race and gender identity

Figure 10.2. People who were refused medical care, by race and gender identity. For details, go to [D] Text Description below.     Figure 10.2. People who were refused medical care, by race and gender identity. For details, go to [D] Text Description below.

[D] Select for Text Description.

Source: Reprinted from the National Transgender Discrimination Survey Report on Health and Health Care, 2011.

Respondents were also asked whether they had been denied service altogether by doctors and other providers. Nineteen percent had been refused treatment by a doctor or other provider because of their transgender or gender-nonconforming status.

Twenty-two percent of MTF respondents reported having been refused treatment altogether, and 19% of FTM respondents did. Respondents who had lost jobs due to bias (36%); those who engaged in sex work, drug sales, or other underground economies for income (30%); those on public insurance (28%); and those living full time as their gender identity (25%) experienced high occurrence of refusal to treat.

Postponement

Respondents were asked whether they postponed or did not try to get two types of health care: preventive care "like checkups" and necessary care "when sick or injured." Many postponed care because they could not afford it, and many postponed care because of discrimination and disrespect from providers.

Figure 10.3. Postponement of care due to discrimination

Figure 10.3. Postponement of care due to discrimination. For details, go to [D] Text Description below.
[D] Select for Text Description.

Source: Reprinted from the National Transgender Discrimination Survey Report on Health and Health Care, 2011.

A significant number of study participants postponed needed medical care due to inability to afford it, whether seeking care when sick or injured (48%) or pursuing preventive care (50%). FTM transgender respondents report postponing care due to inability to afford it at higher rates (55%) than MTF transgender respondents (45%).

Insurance played a significant factor: those who have private insurance were much less likely to postpone care because of inability to afford it when sick or injured (37%) than those with public (46%) or no insurance (86%).

In terms of preventive care, those without insurance reported delaying care due to inability to afford it much more frequently (88%) than those with private insurance (39%) or public insurance (44%). Failing to obtain preventive care is known to lead to poor long-term health outcomes.

Due to discrimination and disrespect, 28% postponed or avoided medical treatment when they were sick or injured, and 33% delayed or did not try to get preventive health care. FTM transgender respondents reported postponing care due to discrimination and disrespect at a much higher frequency (42%, sick/injured; 48%, preventive) than MTF transgender respondents (22%, sick/injured; 25%, preventive).

Those with the highest rates of postponement included those who have lost a job due to bias (45%) and those who have done sex work, sold drugs, or engaged in other underground economies for income (45%). Twenty-nine percent of respondents who were "out" or "mostly out" to medical providers reported they had delayed care when ill, and 33% postponed or avoided preventive care because of discrimination by providers.

Access to Insurance

Figure 10.4. Source of insurance

Figure 10.4. Source of insurance. For details, go to [D] Text Description below.

[D] Select for Text Description.

Source: Reprinted from the National Transgender Discrimination Survey Report on Health and Health Care, 2011.

Study participants were less likely than the general population to have health insurance, more likely to be covered by State programs such as Medicaid, and less likely to be insured by an employer. Nineteen percent of the sample lacked any health insurance compared with 15% of the general population (DeNavas-Walt, et al., 2009).

African-American respondents had the worst health insurance coverage of any racial category: 39% reported private coverage and 30% public. Thirty-one percent of Black respondents reported being uninsured; by contrast, 66% of White respondents reported private insurance, 17% public insurance, and 17% no insurance.

Undocumented noncitizens had very low rates of coverage: 26% reported private insurance, 38% public insurance, and 36% no insurance. The South was the lowest region for coverage, where 59% of respondents reported private insurance, 17% public insurance, and 25% no insurance. In terms of gender, MTFs reported private insurance at 56%, public insurance at 23%, and no insurance at 20%. Gender-nonconforming respondents were insured at higher rates than their transgender counterparts, with 73% private insurance, 11% public insurance, and 17% uninsured.

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vi. Household income less than Federal poverty thresholds.
vii. Household income 400% of Federal poverty thresholds and higher.
viii. "Frontier counties" have a population density of less than 7 people per square mile; thus, residents may have to travel long distances for care.
ix. Noncore areas are outside of metropolitan or micropolitan statistical areas. Micropolitan and noncore areas are typically regarded as "rural."
x. For example, Foraselli P, DeAngelis C, Kaszuba A. Compliance with followup appointments generated in a pediatric emergency room. Am J Prev Med 1985;1(3); Chande VT, Krug SE, Warm EF. Pediatric emergency department utilization habits: a consumer survey. Pediatr Emerg Care 1996;12(1).
xi. Visual conformers are defined as respondents who believed their presentation matched their gender identity. This study notes the significance of visual nonconformity as a risk factor in eliciting antitransgender bias and its attendant social and economic burdens.
xii. These results were based on a question prefaced by: "Based on being transgender/gender non-conforming, please check whether you have experienced any of the following in this public space," and asked respondents to indicate whether they had been "denied equal treatment of service" for each of the various locations.

Page last reviewed April 2012
Internet Citation: Chapter 10. Priority Populations (continued): National Healthcare Disparities Report, 2011. April 2012. Agency for Healthcare Research and Quality, Rockville, MD. http://www.ahrq.gov/research/findings/nhqrdr/nhdr11/chap10a.html