LGBT+ People’s Health Status and Access to Care
Data for this issue brief come from the 2022 KFF Women’s Health Survey, a nationally representative survey of 6,442 people of all genders ages 18 to 64, including 958 LGBT+ people, conducted from May 10, 2022, to June 7, 2022. The objective of the survey is to help better understand respondents’ experiences with contraception, potential barriers to health care access, and other issues related to reproductive health. The survey was designed and analyzed by researchers at KFF (Kaiser Family Foundation) and fielded online and by telephone by SSRS using its Opinion Panel, supplemented with sample from IPSOS’s KnowledgePanel.
The survey asked respondents which sex they were assigned at birth, on their original birth certificate (male or female). They were then asked what their current gender is (man, woman, transgender, non-binary, or other). Those who identified as transgender men are coded as men and transgender women are coded as women. While we attempted to be as inclusive as possible and recognize the importance of better understanding the health of non-cisgendered people, as is common in many nationally representative surveys, we did not have a sufficient sample size (n >= 100) to report gender breakouts other than men and women with confidence that they reflect the larger non-cisgender population as a whole. The data in our reproductive health analyses use the respondent’s sex assigned at birth (inclusive of all genders) to account for reproductive health needs/capacity (e.g., ever been pregnant) while other analyses use the respondent’s gender (inclusive of males and females).
For this survey, LGBT+ people include those who identified their sexual orientation as lesbian, gay, bisexual, or “something else,” and those who identified their gender as transgender, non-binary, “other,” or whose reported gender does not correspond to their reported sex assigned at birth.
The majority of respondents completed the survey using the SSRS Opinion Panel (n=5,202), a nationally representative probability-based panel where panel members are recruited in one of two ways: (1) through invitations mailed to respondents randomly sampled from an Address-Based Sample (ABS) provided by Marketing Systems Group through the U.S. Postal Service’s Computerized Delivery Sequence. (2) from a dual-framed random digit dial (RDD) sample provided by Marketing Systems Group.
In order to have large enough sample sizes for certain subgroups (females ages 18 to 35, particularly females in the following subgroups: lesbian/gay/bisexual; Asian; Black; Hispanic; Medicaid enrollees; low-income; and rural), an additional 1,240 surveys were conducted using the IPSOS KnowledgePanel, a nationally representative probability-based panel recruited using a stratified ABS design. (Note that due to small sample sizes, data for LGBT+ people who are Asian or Pacific Islanders are not presented in this report.)
The majority of surveys completed using the SSRS Opinion Panel (n=5,056) and all of the surveys completed using the KnowledgePanel (n=1,240) were self-administered web surveys. Panelists were emailed an invitation, which included a unique passcode-embedded link, to complete the survey online. In appreciation for their participation, panelists received a modest incentive in the form of a $5 or $10 electronic gift card. In addition to the self-administered web survey, n=146 surveys were completed by telephone with SSRS Opinion Panelists who are web reluctant.
The data are weighted to represent U.S. adults ages 18 to 64. The data include oversamples of females ages 18 to 35 and females ages 36 to 64. Due to this oversampling, the data were classified into three subgroups: females 18 to 35, females 36 to 64, and males 18 to 64. The weighting consisted of two stages: 1) application of base weights and 2) calibration to population parameters. Each subgroup was calibrated separately, then the groups were put into their proper proportions relative to their size in the population.
Calibration to Population Benchmarks
The total sample for the Women’s Health Survey was balanced to match estimates of each of the three subgroups (females ages 18 to 35, females ages 36 to 64, and males ages 18 to 64) along the following dimensions: age; education (less than a high school graduate, high school graduate, some college, four-year college or more); region (Northeast, Midwest, South, West); and race/ethnicity (White non-Hispanic, Black non-Hispanic, Hispanic-born in U.S., Hispanic-born Outside the U.S., Asian non-Hispanic, Other non-Hispanic). The sample was weighted within race (White, non-Hispanic; Black, non-Hispanic; Hispanic; and Asian) to match population estimates. Benchmark distributions were derived from 2021 Current Population Survey (CPS) data. Although the LGBT+ sample in this survey is not weighted separately to match population benchmarks, the full sample is. Comparisons to the available demographic data for the LGBT population from the 2021 Behavioral Risk Factor Surveillance System (BRFSS) found the demographics from our sample closely align with the federal data source.
Margin of Sampling Error
The margin of sampling error, including the design effect for subgroups, is presented in Table 1 below. It is important to remember that the sampling fluctuations captured in the margin of error are only one possible source of error in a survey estimate and there may be other unmeasured error in this or any other survey.
The KFF Women’s Health Survey sample includes people of all genders; however, our sample design is more heavily focused on women. While our survey weights take this gender imbalance into account and we use additional data control measures to ensure the data we present are as reliable and as representative of the population as possible, some data points for certain subgroups with larger margins of error may be more heavily weighted by women than men. Caution should be exercised in interpreting findings among LGBT+ subpopulations due to smaller sample sizes and larger margins of error. Our issue briefs do not present data for subgroups where data limitations precluded us from developing reliable estimates.
All statistical tests are performed at the .05 confidence level. Statistical tests for a given subgroup are tested against the reference group (Ref.) unless otherwise indicated. For example, White is the standard reference for race/ethnicity comparisons and private insurance is the standard reference for types of insurance coverage. Some breakouts by subsets have a large standard error, meaning that sometimes even large differences between estimates are not statistically different.
See the full 2022 KFF Women’s Health Survey methodology for more details. The full survey instrument is available upon request.