Appendix Methodology | 2024 Health Of Women And Children Report

Executive Brief Introduction National SnapshotFindingsHealth Outcomes Social and Economic Factors Clinical Care Behaviors State RankingsAppendixMeasures Table – Women Measures Table – Children Data Source Descriptions MethodologyState Summaries
US Summary
2024 Health of Women and Children Report 2024 Health of Women and Children Report – Executive Brief 2024 Health of Women and Children Report – State Summaries 2024 Health of Women and Children Report – Concentrated Disadvantage County-Level Maps 2024 Health of Women and Children Report – Measures Table 2024 Health of Women and Children Report – Infographics 2024 Health of Women and Children Report – Report Data (All States)
Individual Measures
This year, 123 measures (including 82 weighted and 41 additional unweighted measures) were analyzed for the America’s Health Rankings 2024 Health of Women and Children Report, using the most recent data available as of August 16, 2024. Data years varied by measure because of the variety of data sources. Multiple data years were combined for some measures to ensure reliable state-level estimates. Measure definitions, sources and data years are available in the Appendix: Measures Table – Women, Measures Table – Children. Measure changes were based on input from the Health of Women and Children Report Advisory Committee and are detailed on the 2024 Health of Women and Children Measures Selection and Changes webpage.
Each state was ranked according to its value for each measure, with a rank of 1 assigned to the state with the healthiest value. Ties in value were assigned equal ranks. If a state value was not available for a measure in this edition, it was noted as unavailable or suppressed. Rankings are a relative measure of health. Not all changes in rank translate into actual declines or improvements in health. For additional methodology information, submit an inquiry on the America’s Health Rankings website.
How State Rankings Were Generated
Summations were generated overall and by model category. Summations show how a state compares with other states for a model category, such as Social and Economic Factors or Overall. 
Overall state rankings were based on 82 weighted measures that met the following criteria:
Represented issues that affect population health. 
Had data available at the state level. 
Used common measurement criteria across the 50 states.
Were current and updated periodically.
Were amenable to change. 
The state value for each measure was normalized into a z-score, hereafter referred to as “score,” using the following formula: 
The score indicates the number of standard deviations a state value was above or below the U.S. value. Scores were capped at +/- 2.00 to prevent an extreme score from excessively influencing the state’s overall score. If a U.S. value was not available from the original data source for a measure, the mean of all states and the District of Columbia was used. If a value was not available for a state, its value from the most recent available data year was used to generate a score. 
Summation scores were calculated by adding the products of the score for each measure multiplied by that measure’s assigned model weight and association with health. Measures positively associated with population health, such as Breastfed and Flu Vaccination, were multiplied by 1, while measures with a negative association, such as Smoking and Mortality, were multiplied by -1. A state that ranked No. 1 had a higher summation score (e.g., 2.00), reflecting better health than a state that ranked No. 50 with a lower summation score (e.g., -2.00). The overall state rank was calculated by ranking the overall summation score, which included all 35 measures with weights in the model (see Measures, Weights and Direction for model and measure weights).
Scores and ranks were not calculated for the District of Columbia because of its unique status as an entirely urban population with different governing and funding mechanisms than states. While the District of Columbia was not included in the overall rankings, its data are available in this report and on the America’s Health Rankings website.
Data Notes 
Data presented in this report were aggregated at the state level and cannot be used to make inferences at the individual level. Additionally, estimates cannot be extrapolated beyond the population upon which they were created. Values and ranks from prior years were updated on the America’s Health Rankings website to reflect known errors and updates from the reporting source.
Use caution when interpreting data on certain health and behavioral measures. Many are self-reported and rely on an individual’s perception of health and behaviors. Additionally, some health outcome measures are based on respondents being told by a health care professional that they have a disease and may exclude those who have not received a diagnosis or sought or obtained treatment. 
Significance is based on non-overlapping 95% confidence intervals when comparing data over time or across demographic groups.
Demographic Group Definitions
Analyses were performed to illuminate disparities by age, disability status, education, gender and sexual orientation, income, metropolitan status, race/ethnicity and veteran status. Not all groups were available for all data sources and measures. Individual estimates were suppressed if they did not meet the reliability criteria laid out by the data source or internally established criteria. Some values had wide 95% confidence intervals, meaning the true value may be far from the estimate listed.
Age
Age data in this report were available for measures from the Centers for Disease Control and Prevention’s (CDC’s) Behavioral Risk Factor Surveillance System (BRFSS) and the Maternal and Child Health Bureau’s Federally Available Data (FAD), which were sourced from the National Vital Statistics System (NVSS) and the Healthcare Cost Utilization Project (HCUP). BRFSS groupings in this report were limited to females of reproductive age and included the following self-reported age ranges: 18-24, 25-34 and 35-44. FAD groupings were based on maternal age and were grouped into five age ranges: <20, 20-24, 25-29, 30-34 and ≥35. 
Disability Status
Disability status data in this report were available for measures from the CDC’s Behavioral Risk Factor Surveillance System. Groupings were based on responses to the questions in the core disability section. Responses of yes to the question, “Are you deaf or do you have serious difficulty hearing?” were coded as “difficulty hearing.” Responses of yes to the question, “Are you blind or do you have serious difficulty seeing, even when wearing glasses?” were coded as “difficulty seeing.” Responses of yes to the question, “Because of a physical, mental, or emotional condition, do you have serious difficulty concentrating, remembering, or making decisions?” were coded as “difficulty with cognition.” Responses of yes to the question, “Do you have serious difficulty walking or climbing stairs?” were coded as “difficulty with mobility.” Responses of yes to the question, “Do you have difficulty dressing or bathing?” were coded as “difficulty with self-care.” Responses of yes to the question, “Because of a physical, mental, or emotional condition, do you have difficulty doing errands alone such as visiting a doctor's office or shopping?” were coded as “independent living difficulty.” Responses of no or missing to all questions, with at least one response being no, were coded as “without a disability.”
Education
Education data in this report were available for measures from BRFSS and FAD data sourced from NVSS. BRFSS groupings were limited to females ages 25-44 and based on responses to the question, “What is the highest grade or year of school you completed?” Responses of grades 9 through 11 were classified as “less than high school.” Responses of grade 12 or GED were classified as “high school/GED.” Responses of college or technical school (1 year to 3 years) were classified as “some post-high school.” Responses of college (4 years or more) were classified as “college graduate.” FAD groupings were based on the education level that best described the highest degree or level of school completed at the time of death, grouped into four categories: less than high school (no diploma), high school graduate or GED completed, some college (no degree) and college or technical school (associate degree or higher).
Gender
This report highlights data on women and includes gender stratification (girls, boys) for youth and children’s measures as available through public data sources — even though not all people identified with these two categories. Data did not differentiate between assigned sex at birth and current gender identity. While sex and gender influence health, the current data collection practices of many national surveys limit the ability to describe the health of transgender and nonbinary individuals, especially at the state level.
Sexual Orientation
Sexual orientation data in this report were available for measures from BRFSS. Groupings were based on responses to the question, “Which of the following best represents how you think of yourself?” Responses of lesbian or gay, gay, bisexual or something else were summed and classified as “LGBQ+.” Responses of straight, that is, not gay were summed and classified as “straight.” 
Income
Income data in this report were available for measures from BRFSS and FAD data sourced from HCUP. BRFSS groupings were limited to females ages 25-44 and based on responses to the question, “[What] is your annual household income from all sources?” Responses of less than $10,000, $10,000 to less than $15,000, $15,000 to less than $20,000 and $20,000 to less than $25,000 were summed and classified as “less than $25,000.” Responses of $25,000 to less than $35,000 and $35,000 to less than $50,000 were summed and classified as “$25,000-$49,999.” Responses of $50,000 to less than $75,000 were classified as “$50,000-$74,999.” Responses of $75,000 or more were classified as “$75,000 or more.” FAD groupings were based on quartiles (poorest to wealthiest) of current year median zip code household income obtained from Claritas, a data-driven marketing company.
Metropolitan Status
Metropolitan status data in this report were available for measures from BRFSS and FAD data sourced from HCUP. BRFSS groupings were coded based on the respondent’s residence. Identification as large central metro, large fringe metro, medium metro or small metro was classified as “metro,” and identification as micropolitan or noncore was classified as “non-metro.” FAD groupings were based on the 2013 National Center for Health Statistics Urban-Rural Classification Scheme for Counties. Metropolitan areas with at least 1 million residents were classified as “large metro.” Metropolitan areas of fewer than 1 million residents were classified as “small to medium metro.” Micropolitan, non-metropolitan and non-micropolitan areas were classified as “non-metro.”
Race/Ethnicity
Data were provided where available for the following racial and ethnic groups: American Indian/Alaska Native, Asian, Black or African American (classified in this report as “Black”), Hispanic or Latino/a (classified as “Hispanic”), Native Hawaiian or Other Pacific Islander (classified as “Hawaiian/Pacific Islander”), white, multiracial and those who identify as other race. Hispanic ethnicity includes members of all racial groups. Racial/ethnic groups were defined differently across data sources (details below). In summary, BRFSS, CDC WONDER and FAD race groupings are all non-Hispanic, while the American Community Survey data were presented as Hispanic-inclusive, except for white, which is non-Hispanic. 
Race and ethnicity categories by source:
American Community Survey: American Indian and Alaska Native; Asian; Black or African American; Hispanic or Latino Origin (any race); Native Hawaiian or Other Pacific Islander; white (non-Hispanic); two or more races; and some other race.
BRFSS: American Indian/Alaskan Native (non-Hispanic); Asian (non-Hispanic); Black or African American (non-Hispanic); Hispanic, Latino/a or Spanish origin (any race); Native Hawaiian or Other Pacific Islander (non-Hispanic); white (non-Hispanic); and multiracial (non-Hispanic).
CDC WONDER: American Indian or Alaska Native (non-Hispanic); Asian (non-Hispanic); Black or African American (non-Hispanic); Hispanic (any race); Native Hawaiian or Other Pacific Islander (non-Hispanic); white (non-Hispanic); and more than one race (non-Hispanic).
FAD: American Indian/Alaska Native (non-Hispanic); Asian (non-Hispanic); Black (non-Hispanic); Hispanic (any race); Native Hawaiian/Other Pacific Islander (non-Hispanic); and white (non-Hispanic). NVSS also included multiple race (non-Hispanic) while HCUP categorized multiple race and other race as Other (Hispanic inclusive).
National Survey of Children’s Health: American Indian/Alaskan Native (non-Hispanic); Asian (non-Hispanic); Black or African American (non-Hispanic); Hispanic (any race); Native Hawaiian or Other Pacific Islander (non-Hispanic); white (non-Hispanic); and multiple race (non-Hispanic).
Veteran Status
Veteran status data in this report were available for measures from BRFSS. Groupings were based on responses to the question, “Have you ever served on active duty in the United States Armed Forces, either in the regular military or in a National Guard or military reserve unit?” Responses of yes were summed and classified as “served.” Responses of no were summed and classified as “not served.”
Language
This report uses language aligned with the AP Style Guide when labeling women and children due to the complexity of having similar measures for women and children and the many referenced sources. The report uses women instead of females, except for in measure definitions, which use language consistent with the underlying data sources to ensure accuracy. BRFSS is the exception and uses women rather than females in measure definitions to differentiate BRFSS measures in the Health of Women and Children Report from measures in the Annual Report. The report uses boys and girls instead of males and females when describing gender demographic groups for children’s measures. It also uses teens or adolescents for measures that exclude younger children (teen suicide, teen births). Youth represents the population that excludes younger children but includes tweens (overweight or obesity - youth, tobacco use - youth).
Inclusive language in public health is vital for ensuring that all individuals feel seen, heard and understood. Inclusivity in data collection is essential to ensure that the disparities that people experince are documented, analyzed and addressed.
State Summary Content Creation
Each year, America’s Health Rankings identifies strengths, challenges, key findings and disparities for each state. This information is displayed in the State Summaries for each of the annually updated reports: the Senior Report, the Health of Women and Children Report and the Annual Report. Public health officials, policymakers and researchers can use these insights to guide their decisions and strategies to improve health at the state and national levels.
The data points included in these State Summaries are selected via the following methodology, which identifies noteworthy trends and disparities in the health of a state’s population and how it compares relative to other states. These insights are intended to spark conversations about and spur action to improve key areas of population health.
Strengths and Challenges Methodology 
The top positive and negative contributors to a state’s overall health ranking are selected as strengths and challenges using each state’s Rankings & Impacts diagram, which orders the ranking measures by their calculated impact (weight*score*direction). Additional considerations for identifying which measures to include in this section are: 1) whether the data were recently updated; 2) whether the measure is in another report (i.e., how specific to the report/population the measure is); and 3) the model category (we strive for a mix of topic areas). Of note, additional (nonweighted) measures are not included in the state’s overall rankings and are therefore excluded from the selection process. 
The District of Columbia is an exception to this methodology since it is not part of the overall rankings and does not have a Rankings & Impacts diagram. Strengths and challenges are written for the District by comparing its values with the healthiest and least healthy states for all ranking (weighted) measures. The U.S. Summary does not include strengths and challenges since it is the reference point for calculating z-scores and overall state rankings.
Key Findings Methodology 
The key findings identify notable changes in measures for each state. Changes are presented as a percent change between two time periods. Only statistically significant changes based on nonoverlapping 95% confidence intervals are selected for measures with confidence intervals. For measures without confidence intervals, only measures with changes of 5% or more are selected. Priorities for selection are to: 1) include a mix of measures that are improving and worsening; 2) include a mix of model and topic areas; and 3) include varying time frames (i.e., a mix of long-term and short-term changes). Some measures do not lend themselves to changes over time and are therefore excluded from this analysis (e.g., disparity measures). 
Disparities Methodology
Disparities dive deeper into measures where demographic group data are available. Disparities are selected for each state to highlight gaps within measures with groupings based on race/ethnicity, gender, age, disability, educational attainment, income level, metropolitan status, sexual orientation and veteran status. 
For each demographic group within a measure, the disparity ratio is calculated by dividing the value of one group by the value of another. For example, the value of the group with the highest value divided by that of the group with the lowest value. Only measures with significant differences between two groups based on nonoverlapping 95% confidence intervals are included. A disparity ratio cutoff point is used if no confidence intervals are available for a measure (e.g., ≥3.0). Priorities for selection are as follows: 1) measures with confidence intervals; 2) measures with disparity ratios above 2.0, with priority for the largest ratios within a demographic group; 3) a mix of model and topic areas; and 4) a mix of demographic groups. For more information, see Disparity Measurement Methodology.
Healthy People 2030 Methodology
State values for Adequate Prenatal Care, Low Birth Weight and Child Mortality measures were compared with equivalent Healthy People 2030 targets. A light blue bar indicates that the state has met the target with this year's reported value; a dark blue bar indicates that the state has not yet met the target. Confidence intervals, which account for uncertainty in an estimated value, were not accounted for in the color coding to identify states that met the target.
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