Risk Factors

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Risk factors related to race/ethnicity
Data Standard Race/ethnicity
Measure Annual estimates of:
  • Count: number of children aged 0-17 years with current asthma for each single best race as defined by the Office of Management and Budget 1997 Standards (1):
    • white
    • black
    • Asian
    • American Indian/Alaska Native
    • Native Hawaiian or other Pacific Island
    • Two or more races (multiple race)
  • Count: Number of children aged 0- 17 years with current asthma in each Hispanic origin (ethnicity) category:
    • Hispanic
    • non-Hispanic
  • Count: Number of children aged 0-17 years with current asthma in each race/ethnic category:
    • Non-Hispanic white
    • Non-Hispanic black
    • Non-Hispanic other
    • Hispanic
  • At-risk rate: N/A*
  • Population-based rate: N/A*

*Calculating outcomes rates is not necessarily applicable for this indicator which is a demographic characteristic.
Numerator definition Numerator: Number of children aged 0-17 years with current asthma in each category of race, Hispanic Origin and/or race/ethnicity (race is defined as the single race selected that best represents child’s race).

Survey questions (Source: NHIS):

  • “Do you consider [child’s name] to be Hispanic or Latino? If YES, please give me the group that represents [child’s name]’s Hispanic origin or ancestry.” (Puerto Rican, Cuban/Cuban American, Dominican (Republic), Mexican, Mexican American, Central or South American, Other Latin American, Other Hispanic/Latino/Spanish)
  • “Which race or races [does child’s name] consider [himself/herself]] to be? Please select 1 or more of these categories.”(White, Black/African American, Indian (American), Alaska Native, Native Hawaiian, Guamanian or Chamorro, Samoan, Other Pacific Islander, Asian Indian, Chinese, Filipino, Japanese, Korean, Vietnamese, Other Asian, Some other race )
    • If more than one race selected, “Which one of these groups [read groups above] would you say BEST represents [child’s name]’s race?

Benchmark data sources:
Denominator definition This measure is intended as an indicator of socioeconomic status to help more precisely measure disparities. Therefore, the denominator will depend on the analysis being conducted.
Background National health statistics reported by race/ethnicity are based on the 1997 Office of Management and Budget (OMB) standards (1). The OMB guidelines define race as a social definition rather than an attempt to define genetics, biology, or anthropology. Hispanic origin (ethnicity) and race are separate concepts, and thus collection of race and ethnicity data are collected using separate questions in federal data systems. Hispanic persons may be of any race, and includes persons of Mexican, Puerto Rican, Cuban, Central and South American and/or Spanish origins. Race is based on the family respondent’s description of his or her own race background, as well as the race background of other family members. The 1997 OMB race groups are white, black/African American, American Indian/Alaska Native, Asian, and Native Hawaiian/Other Pacific Islander. A person may report more than one race, but OMB guidelines are based on the race that the respondent reports best represents their or their child’s race. Additional categorization methods may separately classify those choosing more than one race as “multiple race.”
Significance to disparities Higher asthma prevalence among specific race/ethnic groups translates into a higher proportion of those groups at risk of adverse asthma outcomes such as exacerbations, need for emergent care, and in rare cases, death. Non-Hispanic black children had a growing prevalence rate compared to non-Hispanic white children from 2001-2010(2). Alaska Native/American Indian and multiracial children also have higher rates of asthma compared to non-Hispanic white children(3). Puerto Rican children have among the highest rates, while Mexican children have among the lowest rates of current asthma prevalence(4,5). Data for asthma outcomes (such as hospitalizations) by Hispanic origin in national data sets are more limited.
Data considerations In federal health surveys, respondents self-reported race/ethnicity, or proxy reported race/ethnicity for other family members. Beginning with the 2003 NHIS, in cases where “other race” was mentioned with one or more OMB race groups, the “other race” response is dropped and the OMB race group information is retained on the NHIS data file. In cases where “other race” is the only response, race is treated as missing and imputed in the NHIS data file.
Data resources US Census information:

US Census data:
Related data standards Race/ethnicity is associated with many sociodemographic factors, some of which are included in this document:
  • Poverty status
  • Educational attainment
  • Exposure and housing characteristics
  • Psychological distress
  • Insurance coverage
  • Cost barriers
  • Unemployment
References (1) Office of Management and Budget. Revisions to the Standards for the Classification of Federal Data on Race and Ethnicity. Federal Register Notice, October 30, 1997. (https://www.whitehouse.gov/wp-content/uploads/2017/11/Revisions-to-the-Standards-for-the-Classification-of-Federal-Data-on-Race-and-Ethnicity-October30-1997.pdfpdf iconexternal icon)
(2) Akinbami LJ, Moorman JE, Simon AE, Schoendorf KC. Trends in racial disparities for asthma outcomes among children 0 to 17 years, 2001-2010. J Allergy Clin Immunol. 2014 Sep;134(3):547-553
(3) Health Data Interactive. Asthma and chronic obstructive pulmonary disease: US (Source: NHIS) data table. Accessed 3/3/2015.
(4) Moorman JE, Akinbami LJ, Bailey CM, et al. National Surveillance of Asthma: United States, 2001–2010. National Center for Health Statistics. Vital Health Stat 3(35). 2012.
(5) Lara M, Akinbami L, Flores G, Morgenstern H. Heterogeneity of childhood asthma among Hispanic children: Puerto Rican children bear a disproportionate burden. Pediatrics. 2006 Jan;117(1):43-53.

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Risk factors related to poverty status
Data Standard Poverty status
Measure Annual estimates of:
  • Count: Number of children aged 0-17 years with current asthma with family income:
    • <100% federal poverty level (poor)
    • 100-<200% federal poverty level (near poor)
    • ≥200% federal poverty level (non-poor)
  • At-risk rate: N/A*
  • Population-based rate: N/A*

*Calculating outcomes rates is not necessarily applicable for this indicator which is a sociodemographic characteristic.
Numerator definition Numerator: Number of children aged 0-17 years with current asthma in each category of poverty status.Survey question for family income (Source: NHIS):
  • “When answering this next question, please remember to include your income plus the income of all family members living in this household. What is your best estimate of the total family income of all family members from all sources, before taxes in the last calendar year?”

This question is preceded in the National Health Interview Survey by detailed questions about income to prompt respondents to count all the sources used to compute poverty status. According to US Census definition, before-tax money income for the family is totaled, and includes earnings, unemployment compensation, worker’s compensation, Social Security, Supplemental Security Income, public assistance, veteran’s payments, survivor benefits, pension or retirement income, interest, dividends, rents, royalties, income from estates, trusts, educational assistance, alimony, child support, assistance from outside the household, and other miscellaneous sources. Noncash benefits (food stamps, housing subsidies) and capital gains or losses do not count. Money income for all family members are included (but non- relatives, such as housemates, do not count). See https://www.census.gov/topics/income-poverty/poverty/guidance/poverty-measures.htmlexternal icon

Note that nonresponse for this question is relatively high in the NHIS. Therefore, missing responses are multiply imputed to reduce the bias that would result if the other health information associated with these missing responses were excluded from analysis. See the NHIS Description for additional information (ftp://ftp.cdc.gov/pub/Health_Statistics/NCHS /Dataset_Documentation/NHIS/2013/srvydesc.pdfpdf icon)

Survey summary variable for poverty status (Source: NHIS):
Reported family income is used to calculate the ratio of family income to the poverty threshold (RAT_CAT contained in the family file). US Census federal poverty thresholds are defined annually in dollar amounts according to family size and composition.

Survey summary variable for family size (Source: NHIS):
Family type and structure is determined with a series of screening questions in the NHIS and summarized to characterize family size and structure (FM_SIZE and FM_KIDS contained in the family file, which are used to calculate the survey summary variable for poverty status described above).

Benchmark data source:
Denominator definition This measure is intended as an indicator of socioeconomic status to help more precisely measure disparities. Therefore, the denominator will depend on the analysis being conducted.
Background Based on the Office of Management and Budget’s (OMB) Statistical Policy Directive 14, the Census Bureau establishes a set of income thresholds that vary by family size and composition. If family income is less that the family poverty threshold, that family is categorized as poor (<100% federal income threshold). The official poverty definition uses money income before taxes and does not include capital gain or noncash benefits (e.g., food stamps).
Significance to disparities Current asthma prevalence is significantly higher among children with family income below the federal poverty level(1). While national data on outcomes is not generally available by income level, it has been well documented that risk factors for asthma and for poor asthma outcomes are higher among lower income groups, including housing quality, stress, family resources to manage chronic conditions, etc. (2-4)
Data considerations Nonresponse for family income and personal earnings in the NHIS are high (~20%, depending on survey year). To address this limitation, the National Center for Health Statistics provides multiply imputed values for family income variables from 1997 onward. It is highly recommended to use imputed income values when analyzing NHIS income data. Detailed technical documentation is available for each survey year (e.g., 2003: https://www.cdc.gov/nchs/nhis/2003imputedincome.htm)
Data resources U.S Bureau of Census surveys provide estimates of poverty by geographical area:
Related data standards Poverty status is associated and affected by many sociodemographic factors. Those included in this document:
  • Race/ethnicity
  • Educational attainment
  • Exposure and housing characteristics
  • Psychological distress
  • Insurance coverage
  • Cost barriers
  • Unemployment
References (1) Moorman JE, Akinbami LJ, Bailey CM, et al. National Surveillance of Asthma: United States, 2001–2010. National Center for Health Statistics. Vital Health Stat 3(35). 2012.
(2) Bellin M, Osteen P, Collins K, Butz A, Land C. Kub J. The influence of community violence and protective factors on asthma morbidity and healthcare utilization in high-risk children. J Urban Health 2041;91(4):677-689.
(3) Thakur N, Martin M. Castellanos E et al. Socioeconomic status and asthma control in African American youth in SAGE II. J Asthma 2014; 51(7):720-728.
(4) Patel MR, Brown RW, Clark NM. Perceived parent financial burden and asthma outcomes in low-income, urban children. J Urban Health 2013;90(2):329-342.

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Risk factors related to parental educational attainment
Data Standard Parental educational attainment
Measure Annual estimates of:
  • Count: Number of children aged 0-17 years with current asthma in each category of the highest level of educational attainment in the family
  • At-risk rate: N/A*
  • Population-based rate: N/A*

*Calculating outcomes rates is not necessarily applicable for this indicator which is a sociodemographic characteristic. It may be used to assess differences in asthma outcomes, and whether racial/ethnic disparities are partially explained by differences in educational attainment.
Numerator definition Numerator: Number of children aged 0-17 years with current asthma in each category of highest levels of educational attainment of parent(s)/adult(s) in the family.Survey question (Source: NHIS):
  • “What is the HIGHEST level of school [you have/adult’s name has] completed or the highest degree [you have/adult’s name has] received?”

Benchmark data source:

NHIS categorization of highest level of educational attainment in the family:

  • <8th grade; 9-12 grade no HS diploma; HS grad/GED; Some college no degree; AA degree technical; AA degree academic; Bachelor’s degree; Master/professional/doctoral degree.
  • Small sample size or comparison across surveys may require collapsing categories, for example: No HS diploma; HS grade/GED; Some college or AA degree; Bachelor’s degree or higher
Denominator definition This measure is intended as an indicator of socioeconomic status to help more precisely measure disparities. Therefore, the denominator will depend on the analysis being conducted.
Background Educational attainment refers to the highest level of education that an individual has completed (distinct from the current grade level). Categories used by US Census for adults 18 years and older are more detailed than those used by the NHIS: less than high school (none, 1-4th grade, 5-6th grade, 7-8th grade, 9th grade, 10th grade, 11th grade), HS graduate, some college no degree, associate’s degree (occupational, academic), bachelor’s degree, master’s degree, professional degree, doctoral degree.

Parental educational attainment is associated with measures of well-being including school readiness, educational achievement, incidence of low birthweight, and health-related behaviors(1). Health literacy as well as health-related behaviors, such as smoking, may be related to asthma management and outcomes. (2, 3)
Significance to disparities Although the percentage of children with a parent with less than a high school diploma or equivalent has increased since the 1970s, children of minority race/ethnicity have a lower percentage of resident mothers and fathers with at least a bachelor’s degree. (1, 4) Furthermore, children in single-parent households were more likely to live with a parent who had not attained a bachelor’s degree or higher, or had not completed high school(4). The factors of a single-parent household and low educational achievement may compound the risk of suboptimal management of asthma.
Data considerations Assessment of highest level of educational achievement in the family requires determination of family structure and a knowledgeable respondent about the educational achievement of all adults in the family.
Data resources
Related data standards Asthma prevalence, management, and outcomes may vary by socioeconomic status as well as by other demographic factors. Other measures also capture aspects of socioeconomic status:
  • Poverty status
  • Insurance coverage
  • Usual source of health care
  • Unable to pay medical bills
References (1) Child Trends Data Bank. Parental education: indicators on children and youth. Updated July 2014 (http://www.childtrends.org/wp- content/uploads/2012/04/67-Parental_Education.pdfpdf iconexternal icon)
(2) Harrington KF, Zhang B, Magruder T, Bailey WC, Gerald LB. The impact of parent’s health literacy on pediatric asthma outcomes. Pediatr Allergy Immunol Pulmonol 2015;28(1):20-26.
(3) Akinbami LJ, Kit BK, Simon AE. Impact of environmental tobacco smoke on children with asthma, 2003-2010. Acad Pediatr 2013;13(6):508- 516.
(4) National Center for Education Statistics. The condition of education: parental education. Last updated January 2015. (http://nces.ed.gov/programs/coe/indicator_saa.aspexternal icon)

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Risk factors related to exposure to environmental factors inside homes
Data Standard Exposure to environmental factors inside homes
Measure Annual estimates of:
  • Count: Number of children aged 0-17 years with current asthma who report exposure to mold or cockroach in the past 30 days, or exposure to environmental tobacco smoke (ETS) in the past week.
  • At-risk rate: N/A*
  • Population-based rate: N/A*

*Calculating outcomes rates is not necessarily applicable for this indicator which is an environmental risk factor. It may be used to assess differences in asthma outcomes, and whether racial/ethnic disparities are partially explained by differences in exposure to environmental factors.

Numerator: Number of children aged 0-17 years with current asthma who lived in home where anyone saw or smelled mold in the past 30 days; saw cockroach in the past 30 days; or reported someone smoked in the past week (environmental tobacco smoke [ETS]).

Survey questions (Source: Asthma Call-Back Survey): YES response to any of the following questions:

  • “In the past 30 days, has anyone seen or smelled mold or a musty odor inside [his/her] home? Do not include mold on food.”
  • “In the past 30 days, has anyone seen a cockroach inside [child’s name]’s home?”
  • “In the past week, has anyone smoked inside [child’s name]’s home?”

Benchmark data source:

  • State: BRFSS Asthma Call-Back Survey (ACBS) can be used to obtain average annual estimates for survey years starting in 2006 for participating States. Aggregation of at least 2 survey years is recommended to obtain reliable estimates by State. (https://www.cdc.gov/brfss/acbs/index.htm)
Denominator definition This measure is intended as an indicator environmental risk factor to help more precisely measure disparities. Therefore, the denominator will depend on the analysis being conducted.
Background Exposure to environmental factors inside homes can exacerbate asthma symptoms (2, 3). According to the National Asthma Education and Prevention Program (NAEPP) guidelines, in addition to receiving appropriate medical treatment, asthma symptoms can be controlled by avoiding exposure to environmental allergens and irritants (1).

Exposure to environmental factors inside home can be assessed at state-level using the child ACBS. The ACBS has several measures to assess indoor air quality (saw or smelled mold, saw a cockroach, anyone smoked inside home, saw mice or rats; pets allowed in bedroom, gas used for cooking, wood burning fireplace or stove used, gas appliance used). For this indicator, a combination of mold, cockroach, and ETS related measures is recommended. These are the exposures highlighted in the Institute of Medicine report as having sufficient scientific evidence of association with exacerbation of asthma(3).

Healthy People 2020: Respiratory Diseases Objectives (RD-7.5): Increase the proportion of persons with current asthma who have been advised by a health professional to change things in their home, school, and work environments to reduce exposure to irritants or allergens to which they are sensitive according to National Asthma Education and Prevention Program (NAEPP) guidelines (https://www.healthypeople.gov/2020/topics-objectives/topic/respiratory-diseases/objectivesexternal icon)(2).
Significance to disparities Among sensitive individuals, exposure to cockroach, ETS, fungi, or molds is associated with the exacerbation of asthma. (3,4)
Data considerations Limitations:
  • Based on reported data rather than on actual inspection/measurement of home environment
  • Does not capture different levels of exposure
  • Does not capture other environments where children may spend a substantial amount of time and be exposed to indoor air pollutants and irritants (e.g., school, vehicles).
Data resources
Related data standards Educational attainment and income are the indicators that are most commonly used to measure the effect of socioeconomic status (SES) on health. SES is associated with health care access, environmental exposure, and health behaviors(5).
  • Educational attainment
  • Income
References (1) National Institutes of Health, National Asthma Education and Prevention Program. Expert panel report 3: guidelines for the diagnosis and management of asthma. Expert panel report 3. Bethesda, MD: National Institutes of Health, National Heart, Lung, and Blood Institute. 2007. Available at: http://www.nhlbi.nih.gov/guidelines/asthma/index.htmexternal icon. Accessed February 19, 2015.
(2) Healthy People 2020; Respiratory Diseases Objective 7.5. available at: http://www.healthypeople.gov/2020/topics-objectives/topic/respiratory- diseases/objectivesexternal icon
(3) Institute of Medicine (U.S.). (2000). Clearing the air: Asthma and indoor air exposures. Washington, DC: National Academy Press.
(4) Akinbami LJ, Kit BK, Simon AE. Impact of environmental tobacco smoke on children with asthma, United States, 2003-2010. Acad Pediatr 2013;13(6):508-516. (5) Centers for Disease Control and Prevention. CDC Health Disparities and Inequalities Report — United States, 2013: Education and Income — United States, 2009 and 2011. MMWR 2013;62(Suppl 3): 9-19.

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Risk factors related to weight status
Data Standard Weight status
Measure Annual estimates of:
  • Count: Number of children aged 2-17 years* with current asthma in the following weight categories based on BMI age- and sex-specific percentiles:
    • Underweight: <5th percentile BMI
    • Normal weight: 5th to <85th percentile BMI
    • Overweight: 85th to <95th percentile BMI
    • Obese: ≥95th percentile BMI
  • At-risk rate: N/A**
  • Population-based rate: N/A*

* BMI percentiles are available for children starting at age 2 years.
**Calculating outcomes rates is not applicable for this indicator which is a demographic characteristic. It may be used to assess differences in asthma outcomes, and whether racial/ethnic disparities are partially explained by differences in weight status.
Numerator definition Numerator: Number of children aged 2-17 years with current asthma in each category of weight statusSurvey items (Source: National Health and Nutrition Examination Survey):
  • Weight, measured in kilograms (kg)
  • Height, measured in meters (m)

These items are measured during an examination in a Mobile Exam Center and not based on self-report by survey respondents.

Calculated indicators:

  • Body mass index (BMI=kg/m2)—calculated from height and weight
  • BMI category (based on BMI percentile-for-age)—determined using age and sex percentiles for BMI

Benchmark data source:
Denominator definition This measure is intended as an indicator of risk of having asthma and/or asthma complications to help more precisely measure disparities. Therefore, the denominator will depend on the analysis being conducted.
Background Body mass index (BMI) is calculated from measured weight and height to reliably indicate body fatness for most children (weight/height2). BMI does not measure body fat directly, but correlates with direct measures, such as dual energy x-ray absorptiometry. It is an inexpensive alternative for direct measures of body fat.

Unlike adults who have static ranges of BMI that indicate weight status (normal weight versus overweight versus obese), for children ranges of BMI that indicate weight status vary with age and sex. Percentiles for BMI for age and sex have been calculated using a normative, nationally representative sample of children aged 2-19 years by CDC(1). Individual BMI is plotted on the BMI age- and sex-specific growth charts to obtain a percentile ranking for that individual. Weight status category for children is based on percentile ranking rather than directly on BMI.
Significance to disparities Overweight and obese children have increased risk of developing asthma compared to children of normal weight status(2). Higher BMI values also increased the risk for seasonal asthma exacerbations among children with persistent asthma(3).
Data considerations
  • BMI is calculated for children aged 2 years and older. For children younger than 2 years, recumbent length is measured rather than standing height. Therefore, the standard BMI calculation and percentiles for age do not apply to this age group. For children under 2 years of age, weight-for-length percentiles can be reported, but these also do not correlate with BMI percentile-defined weight status categories.
  • Parent-reported height and weight, compared to measured values, may lead to misclassification of weight status, particularly for younger children. An analysis comparing measured and reported weight in national surveys found that classification of young children as obese was increased using reported height and weight, most likely because of underestimation of height of young children. Use of measured rather than parent-reported height and weight was recommended(4).
Data resources
Related data standards Other measures that correlate either with weight status, or with risk of having asthma or adverse asthma outcomes include:
  • Race/ethnicity
  • Poverty status
  • Parental educational attainment
  • Exposure to environmental factors inside homes
  • Perceived health status
References (1) CDC growth charts: https://www.cdc.gov/growthcharts/cdc_charts.htm)
(2) Chen YC1, Dong GH, Lin KC, Lee YL. Gender difference of childhood overweight and obesity in predicting the risk of incident asthma: a systematic review and meta-analysis. Obes Rev. 2013 Mar;14(3):222-31.
(3) Schatz M, Zeiger RS, Zhang F, Chen W, Yang SJ, Camargo CA Jr. Overweight/obesity and risk of seasonal asthma exacerbations. Allergy Clin Immunol Pract. 2013 Nov-Dec;1(6):618-22.
(4) Akinbami LJ, Ogden CL. Childhood overweight prevalence in the United States: the impact of parent-reported height and weight. Obesity (Silver Spring). 2009 Aug;17(8):1574-80

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Risk factors related to lack of health insurance coverage
Data Standard Lack of health insurance coverage
Measure Annual estimates of:
  • Count: Number of children aged 0-17 years with current asthma who are uninsured
  • At-risk rate: N/A
  • Population-based rate: N/A

Calculating outcomes rates is not necessarily applicable for this indicator which is a demographic characteristic. It may be used to assess differences in asthma outcomes, and whether racial/ethnic disparities are partially explained by differences in not having health insurance coverage.
Numerator definition Numerator: Number of children aged 0-17 years (in the demographic group of interest) with current asthma who are uninsured.Survey questions (Source: National Health Interview Survey):
NO response to:
  • “The next questions are about health insurance. Include health insurance obtained through employment or purchased directly as well as government programs like Medicare and Medicaid that provide Medical care or help pay medical bills. [Are you/Is anyone in the family] covered by any kind of health insurance or some other kind of health care plan?”

AND/OR responses to the following question that include the three bolded responses below:

  • “What kind of health insurance or health care coverage [fill: do you/does ALIAS] have?” INCLUDE those that pay for only one type of service (nursing home care, accidents, or dental care). EXCLUDE private plans that only provide extra cash while hospitalized. (Choose all that apply)
    • Private health insurance
    • Medicare
    • Medi-Gap
    • Medicaid
    • SCHIP (CHIP/Children’s Health Insurance Program)
    • Military health care (TRICARE/VA/CHAMP-VA)
    • Indian Health Service
    • State-sponsored health plan
    • Other government program
    • Single service plan (e.g., dental, vision, prescriptions)
    • No coverage of any type”

Benchmark data source:
Denominator definition This measure is intended as an indicator of socioeconomic status to help more precisely measure disparities. Therefore, the denominator will depend on the analysis being conducted.
Background The NHIS determines health insurance coverage at the time of participation in the survey. Uninsured persons are those not covered by private insurance, Medicaid, Children’s Health Insurance Program (CHIP), state-sponsored or other government- sponsored health plans, Medicare, or military plans. Person with only Indian Health Service coverage, or with only a private plan that paid for one type of service (e.g., accidents or dental care) are considered to have no health insurance coverage(1).

Recommendations found in the Guideline Implementation Panel (GIP) report specifically recommend examining insurance coverage gaps due to the link to possible underutilization of routine (non-emergent) care. The GIP report also recommends increasing surveillance of disparities related to insurance status(2).
Significance to disparities Lack of insurance coverage differs significantly by race and ethnicity(3). Patients with chronic illnesses without insurance are less likely to visit a health care professional, not to have a usual site for healthcare, or to identify the emergency room as their usual source of care(3). Lack of health insurance is also associated with reduced use of preventive services and medical treatment(4).
Data considerations Uninsured populations may be less likely to seek medical care. Those without insurance with less opportunity for health care encounters may be more likely to have undiagnosed asthma.

The NHIS definition of lack of health insurance is based on reported health insurance coverage at the time of survey participation, but does not account for periods of gaps in coverage. That is, persons insured at the time of NHIS participation may have only intermittent coverage and periods of lack of insurance which are not detected.
Data resources
Related data standards Previous reports have found differences in insurance rates by demographic and health care access factors. Indicators in this document include:
  • Race/ethnicity
  • Poverty status
  • Educational attainment
  • Usual source of health care
  • Unable to pay medical bills
  • Personal doctor
References (1) The National Health Interview Survey Early Release Program (https://www.cdc.gov/nchs/nhis/releases.htm), Early Release Reports on Detailed Estimates of Health Insurance Coverage.
(2) National Asthma Education and Prevention Program. Guidelines Implementation Panel Report for: Expert Panel Report 3—Guidelines for the Diagnosis and Management of Asthma. NIH Publication No. 09-6147. December 2008 (http://www.nhlbi.nih.gov/files/docs/guidelines/gip_rpt.pdfpdf iconexternal icon)
(3) Centers for Disease Control and Prevention, CDC Health Disparities and Inequalities Report- United States 2011 (https://www.cdc.gov/mmwr/pdf/other/su6001.pdfpdf icon)
(4) Hargraves JL. The insurance gap and minority health care 1997–2001. Washington, DC: Center for Studying Health System Change; 2002.

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Risk factors related to Type of health insurance coverage
Data Standard Type of health insurance coverage
Measure Annual estimates of:
  • Count: Number of children aged 0-17 years with current asthma and/or an asthma attack in the past 12 months within each category of health insurance coverage:
    • Private
    • Public
    • Uninsured
  • At-risk rate: N/A*
  • Population-based rate: N/A*

*Calculating outcomes rates is not necessarily applicable for this indicator which is a demographic characteristic. It may be used to assess differences in asthma outcomes, and whether racial/ethnic disparities are partially explained by differences in type of insurance coverage.
Numerator definition Numerator: Number of children aged 0-17 years within each category of health insurance coverage:Survey questions (Source: National Health Interview Survey):
  • “The next questions are about health insurance. Include health insurance obtained through employment or purchased directly as well as government programs like Medicare and Medicaid that provide Medical care or help pay medical bills. [Are you/Is anyone in the family] covered by any kind of health insurance or some other kind of health care plan?”
  • “What kind of health insurance or health care coverage [fill: do you/does ALIAS] have?” INCLUDE those that pay for only one type of service (nursing home care, accidents, or dental care). EXCLUDE private plans that only provide extra cash while hospitalized. (Choose all that apply)
    • Private health insurance
    • Medicare
    • Medi-Gap
    • Medicaid
    • SCHIP (CHIP/Children’s Health Insurance Program)
    • Military health care (TRICARE/VA/CHAMP-VA)
    • Indian Health Service
    • State-sponsored health plan
    • Other government program
    • Single service plan (e.g., dental, vision, prescriptions)
    • No coverage of any type

Private coverage: YES to first question, and “Private health insurance” to second question (includes comprehensive insurance— including health maintenance and preferred provider organizations–obtained through the workplace, self-employment, direct purchase, or a professional association).

Public coverage: YES to first question, and any of the following responses for the second question: “Medicare,” “Medi-Gap,” “Medicaid,” “SCHIP,” “Military health care,” “State-sponsored health plan” or “Other government program.”

Uninsured: NO to the first question, AND/OR any of the following responses for the second question “Indian Health Service,” “Single service plan,” or “No coverage of any type.”

Benchmark data source:
Denominator definition This measure is intended as an indicator of socioeconomic status to help more precisely measure disparities. Therefore, the denominator will depend on the analysis being conducted.
Background The NHIS determines health insurance coverage at the time of participation in the survey(1).

Recommendations found in the Guideline Implementation Panel (GIP) report specifically recommend examining insurance coverage gaps due to the link to possible underutilization of routine (non-emergent) care. The GIP report also recommends increasing surveillance of disparities related to insurance status(2).
Significance to disparities Lack of insurance coverage differs significantly by race and ethnicity(3). Patients with chronic illnesses without insurance are less likely to visit a health care professional, not to have a usual site for healthcare, or to identify the emergency room as their usual source of care(3). Lack of health insurance is also associated with reduced use of preventive services and medical treatment(4).
Data considerations
  • Uninsured populations may be less likely to seek medical care. Those without insurance with less opportunity for health care encounters may be more likely to have undiagnosed asthma.
  • The NHIS definition of type of health insurance is based on reported health insurance coverage at the time of survey participation, but does not account for periods of gaps in coverage. That is, persons insured at the time of NHIS participation may have only intermittent coverage and periods of lack of insurance which are not detected.
Data resources
Related data standards Previous reports have found differences in insurance type by demographic and health care access factors. Indicators in this document include:
  • Race/ethnicity
  • Poverty status
  • Educational attainment
  • Usual source of health care
  • Unable to pay medical bills
  • Personal doctor
References (1) The National Health Interview Survey Early Release Program (https://www.cdc.gov/nchs/nhis/releases.htm), Early Release Reports on Detailed Estimates of Health Insurance Coverage.
(2) National Asthma Education and Prevention Program. Guidelines Implementation Panel Report for: Expert Panel Report 3—Guidelines for the Diagnosis and Management of Asthma. NIH Publication No. 09-6147. December 2008 (http://www.nhlbi.nih.gov/files/docs/guidelines/gip_rpt.pdfpdf iconexternal icon)
(3) Centers for Disease Control and Prevention, CDC Health Disparities and Inequalities Report- United States 2011 (https://www.cdc.gov/mmwr/pdf/other/su6001.pdfpdf icon)
(4) Hargraves JL. The insurance gap and minority health care 1997–2001. Washington, DC: Center for Studying Health System Change; 2002.

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Risk factors related to no usual source of health care
Data Standard No usual source of health care
Measure Annual estimates of:
  • Count: Number of children aged 0-17 years with current asthma who do not have a usual source of health care
  • At-risk rate: N/A*
  • Population-based rate: N/A*

*Calculating outcomes rates is not necessarily applicable for this indicator which is a demographic characteristic. It may be used to assess differences in asthma outcomes, and whether racial/ethnic disparities are partially explained by differences in having a usual source of health care.
Numerator definition Numerator: Number of children aged 0-17 years with current asthma who do not have a usual source of health careSurvey question:
  • “Is there a place that [child’s name] USUALLY goes when [he/she] is sick or you need advice about [his/her] health?”
  • AND “What kind of place does [child’s name] go to most often?”
    • Clinic or health center
    • Doctor’s office or HMO
    • Hospital emergency room
    • Some other place
    • Doesn’t go to one place most often”

Count of persons with either a “no” response to the first question, or a response “hospital emergency room” or “doesn’t go to one place most often” to the second question.

Benchmark data source:
Denominator definition This measure is intended as an indicator of socioeconomic status to help more precisely measure disparities. Therefore, the denominator will depend on the analysis being conducted.
Background Having a usual source of care is associated with higher rates of preventive care and fewer acute care visits and hospitalizations(1). Uninsured children without a usual source of care report higher rates of unmet need(2).

Recommendations found in the Guideline Implantation Panel (GIP) report include encouraging asthma patients to establish a medical home as part of a healthcare delivery system. The GIP report also recommends increasing surveillance of disparities related to access to medical homes(3).

Healthy People 2020 is the most recent set of objectives developed with 4 overarching goals: attain high quality of life, eliminate disparities, create social and physical environment to promote good health, and promote healthy behaviors across all life stages. The topic area of Access to Health Services has 9 main objectives. More information is available at: https://www.healthypeople.gov/2020/topics-objectives/topic/Access-to-Health-Servicesexternal icon Healthy People 2020: AHS-5.1 Increase the proportion of persons who have a specific source of ongoing care
Significance to disparities Prevalence of a medical home in US children has been shown to vary by insurance type, race and ethnicity, and primary language spoken. Prevalence was lower in publically insured children compared to privately insured children, racial and ethnic minorities, and non-English language speakers(4).
Data considerations
  • Analysts may prefer to further limit the definition of “usual source of care.” Potential answers such as retail store clinics, friend or relative, or locations outside of the US may not represent a true medical home.
  • Having an asthma diagnosis from a health professional may bias the sample towards those with access to care. This may artificially increase the percent of those with asthma that have a usual source of care, as those without a usual source of care may be lacking the medical diagnosis.
Data resources
Related data standards This measure is closely related to other measures of health care access:
  • Insurance coverage
  • Unable to pay medical bills
  • Personal doctor
References (1) Newacheck PW, Hughes DC, Stoddard JJ. Children’s access to primary care: differences by race, income, and insurance status. Pediatrics.1996;97 (1):26– 32
(2) Hoilette LK1, Clark SJ, Gebremariam A, Davis MM. Usual source of care and unmet need among vulnerable children: 1998-2006. Pediatrics. 2009 Feb;123(2):e214-9.
(3) National Asthma Education and Prevention Program. Guidelines Implementation Panel Report for: Expert Panel Report 3—Guidelines for the Diagnosis and Management of Asthma. NIH Publication No. 09-6147. December 2008 (http://www.nhlbi.nih.gov/files/docs/guidelines/gip_rpt.pdfpdf iconexternal icon)
(4) Zickafoose JS, Gebermariam A, Davis MM. Medical home disparities for children by insurance type and state of residence. Journal of Maternal and Child Health. April 2012. Suppl 1: S178-87

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Risk factors related to being unable to pay medical bills
Data Standard Unable to pay medical bills
Measure Annual estimates of:
  • Count: Number of children aged 0-17 years with current asthma whose family had difficulty paying medical bills
  • At-risk rate: N/A*
  • Population-based rate: N/A*

*Calculating outcomes rates is not necessarily applicable for this indicator which is a demographic characteristic. It may be used to assess differences in asthma outcomes, and whether racial/ethnic disparities are partially explained by differences in ability to pay medical bills.
Numerator definition Numerator: Number of children aged 0-17 years with current asthma whose family had difficulty paying medical bills in the past 12 monthsSurvey question (Source: NHIS):
  • “In the past 12 months did [you/anyone in the family] have problems paying or were unable to pay any medical bills? Include bills for doctors, dentists, hospitals, therapists, medication, equipment, nursing home or home care.”

Benchmark data source:
Denominator definition This measure is intended as an indicator of socioeconomic status to help more precisely measure disparities. Therefore, the denominator will depend on the analysis being conducted.
Background The family perspective in paying medical bills is important to consider given the financial risk to the entire family unit of significant expenses. Although a child may have health insurance, insurance coverage among family members may differ. In 2012, 16.5% of US families had problems paying medical bills in the past 12 months. Low income families had the highest rate of difficulty paying medical bills (26%), as did families with one or more children (21.8%)(1).

Healthy People is a federal interagency effort to identify a comprehensive set of 10-year national health objectives. Healthy People 2020 is the most recent set of objectives developed with 4 overarching goals: attain high quality of life, eliminate disparities, create social and physical environment to promote good health, and promote healthy behaviors across all life stages. The topic area of Access to Health Services has 9 main objectives. More information is available at: https://www.healthypeople.gov/2020/topics-objectives/topic/Access-to-Health-Servicesexternal icon. The Healthy People 2020 objective “AHS-1.1 Increase the proportion of persons with health insurance” has a stated goal of reduction in burden from large medical bills.
Significance to disparities Poverty status in asthma patients has been shown to have differing impacts based on race and ethnicity(2). In the 2010 Asthma Call Back Survey, 13.5% of adults and 5.4% of children reported cost as a barrier to seeing a primary care physician. 18.6% of adults and 9.8% of children reported cost as a barrier to filling a prescription asthma medication. Black and Hispanic adults were more likely to report cost as a barrier to asthma care than white adults(3).
Data considerations Limitation:
  • The question does not address the amount of the medical bill the family has difficulty paying. There may be a difference in those who had difficulty paying a bill due to hospitalization versus those who had difficulty paying a co-pay or other smaller bill.
Data resources
Related data standards Other indicators related to health care access:
  • Insurance coverage
  • Usual source of health care
  • Frustrated in obtaining health care services
  • Personal doctor
References (1) Cohen RA, Kirzinger WK. Financial burden of medical care: A family perspective. NCHS data brief, no 142. Hyattsville, MD: National Center for Health Statistics. 2014.
(2) Moorman JE, Zahran H, Truman BI, Molla MT. Current Asthma Prevalence -United States, 2006–2008. MMWR January 14, 2011 60(01);84-86
(3) Centers for Disease Control and Prevention. Asthma Facts—CDC’s National Asthma Control Program Grantees. Atlanta, GA: U.S. Department of Health and Human Services, Centers for Disease Control and Prevention, 2013.

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Risk factors related to personal doctor
Data Standard Personal doctor
Measure Annual estimates of:
  • Count: Number of children aged 0-17 years with current asthma who do not have a personal doctor
  • At-risk rate: N/A*
  • Population-based rate: N/A*

*Calculating outcomes rates is not necessarily applicable for this indicator which is a demographic characteristic. It may be used to assess differences in asthma outcomes, and whether racial/ethnic disparities are partially explained by differences in having a personal doctor.
Numerator definition Numerator: Number of children aged 0-17 years with current asthma who currently do not have a personal doctor or nurseSurvey question (Source: NSCH):
  • “A personal doctor or nurse is a health professional who knows your child well and is familiar with your child’s health history. This can be a general doctor, a pediatrician, a specialist doctor, a nurse practitioner, or a physician’s assistant. Do you have one or more persons you think of as [child’s name]’s personal doctor or nurse?”

Benchmark data source:
Denominator definition This measure is intended as an indicator of socioeconomic status to help more precisely measure disparities. Therefore, the denominator will depend on the analysis being conducted.
Background Recommendations found in the Guideline Implementation Panel (GIP) report specifically recommends encouraging asthma patients to establish a medical home as part of a healthcare delivery system. The GIP report also recommends increasing surveillance of disparities related to access to medical homes(1).

Healthy People is a federal interagency effort to identify a comprehensive set of 10-year national health objectives. Healthy People 2020 is the most recent set of objectives developed with 4 overarching goals: attain high quality of life, eliminate disparities, create social and physical environment to promote good health, and promote healthy behaviors across all life stages. The topic area of Access to Health Services has 9 main objectives. More information is available at: https://www.healthypeople.gov/2020/topics-objectives/topic/Access-to-Health-Servicesexternal icon Healthy People 2020: AHS-3 Increase the proportion of persons with a usual primary care provider
Significance to disparities Uninsured people with asthma are less likely to have a primary care physician(2). Insurance status significantly differs by race and ethnicity (3).
Data considerations The survey question does not specify the site of care. To function as an indicator of receiving care in a medical home, as advised by the American Academy of Pediatrics(4), having a personal doctor should be considered in the context of other indicators such as having a usual source of care.
Data resources
Related data standards This measure is closely related to the measure regarding having a usual source of care. Other indicators related to health care access:
  • Insurance coverage
  • Usual source of health care
  • Unable to pay medical bills
References (1) National Asthma Education and Prevention Program. Guidelines Implementation Panel Report for: Expert Panel Report 3—Guidelines for the Diagnosis and Management of Asthma. NIH Publication No. 09-6147. December 2008 (http://www.nhlbi.nih.gov/files/docs/guidelines/gip_rpt.pdfpdf iconexternal icon)
(2) Vital Signs: Asthma Prevalence, Disease Characteristics, and Self-Management Education- United States, 2001 – 2009. MMWR May 6,2011 / 60 (17);547-552
(3) Centers for Disease Control and Prevention, CDC Health Disparities and Inequalities Report- United States 2011 (https://www.cdc.gov/mmwr/pdf/other/su6001.pdfpdf icon)
(4) American Academy of Pediatrics. Joint principles of the patient-centered medical home. http://www.aafp.org/dam/AAFP/documents/practice_management/pcmh/initiatives/PCMHJoint.pdfpdf iconexternal icon
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Page last reviewed: July 14, 2016
Content source: National Center for Environmental Health