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Exploratory-Analysis-BRFSS-2018-Data

This project demonstrates applied regression modeling, effect modification assessment, and transparent reporting using large-scale public health survey data.

  • Overview: The analysis investigates relationships between key health outcomes and demographic factors, utilizing a subset of BRFSS data with 106,285 observations across 12 variables, including sexual orientation, mental health, and health-related covariates. https://www.cdc.gov/brfss/

Data Description

  • Dataset: A subset of the BRFSS 2018 dataset with 106,285 observations and 12 variables, collected from noninstitutionalized U.S. adults aged 18+ via telephone surveys.
  • Variables:
    • Exposure: Sexual Orientation (SO) as the primary exposure variable.
    • Covariates: Sex, Race, Age Category, Income Category, BMI Category, Presence of Health Plan, and Smoking Status.
    • Outcomes: Number of Poor Mental Health Days (MENTHLTH) and Depressive Disorder (ADDEPEV2).
  • Data Handling: Missing values were excluded, and categorical variables were formatted for analysis.

Key Variables

Exposure Variable

  • Sexual Orientation: Lesbian/Gay, Straight/not gay, Bisexual, Something else.

Outcome Variables

  • Poor Mental Health Days: Continuous (0-30 days).

  • Depressive Disorder: Binary (Yes/No).

  • Variable Code List

The following table outlines the key variables used in this analysis, derived from the BRFSS 2018 dataset:

Variable Name Description
SO Sexual Orientation (e.g., Straight, Lesbian/Gay, Bisexual, Something Else)
SEX1 Sex (Male, Female)
RACE Race/Ethnicity (e.g., White Non-Hispanic, Black Non-Hispanic, etc.)
AGECAT Age Category (e.g., 18-29, 30-39, 40-59, 60+)
INCOMECAT Income Category (e.g., < $50,000, ≥ $50,000)
BMICAT BMI Category (e.g., Underweight, Normal, Overweight, Obese)
MENTHLTH Number of Poor Mental Health Days
ADDEPEV2 Depressive Disorder (Yes, No)
POORHLTH Number of Poor Physical Health Days
GENHLTH General Health Status (e.g., Excellent, Poor)
HLTHPLN1 Presence of Health Plan (Yes, No)
SMOKER Smoking Status (e.g., Current, Former, Never)

Research Objectives

The primary goals of this analysis include:

  • Investigate the correlation between sexual orientation and mental health metrics.
  • Measure disparities in mental health across varying sexual orientation categories.
  • Explore age as a potential modifier in the sexual orientation-mental health relationship.

Statistical Methods

  • Descriptive Statistics: Means, SDs, frequencies, percentages by sexual orientation (ANOVA, chi-square, α = 0.05).
  • Bivariate Analysis: ANOVA/t-tests for mental health days; chi-square for categorical variables.
  • Multivariable Analysis: GLM for mental health days; logistic regression for depressive disorder, adjusted for covariates.
  • Effect Modification: Stratified analysis by age; tested age-sexual orientation interactions.
  • Measures of Association: Effect estimates (95% CI) for continuous; odds ratios (95% CI) for binary outcomes.
  • Diagnostics: Checked linearity, normality, homoscedasticity.

Results

Table 1: Overall Participant Characteristics

Characteristic Summary (n=106,285)
Sexual Orientation
- Lesbian or Gay 2,213 (2.08%)
- Straight/not gay 99,446 (93.57%)
- Bisexual 3,280 (3.09%)
- Something else 1,346 (1.27%)
Sex
- Male 44,662 (42.02%)
- Female 61,623 (57.98%)
Race
- White, Non-Hispanic 82,143 (77.29%)
- Black, Non-Hispanic 9,560 (8.99%)
- Asian, Non-Hispanic 2,419 (2.28%)
- American Indian/Alaskan Native, Non-Hispanic 1,725 (1.62%)
- Hispanic 5,967 (5.61%)
- Other race, Non-Hispanic 4,471 (4.21%)
Age
- 18-29 12,492 (11.75%)
- 30-39 12,433 (11.70%)
- 40-59 34,620 (32.57%)
- 60 and older 46,740 (43.98%)
Income Category
- Less than $50,000 78,257 (73.63%)
- $50,000 or more 28,028 (26.37%)
BMI Category
- Underweight 2,008 (1.89%)
- Normal weight 30,656 (28.84%)
- Overweight 35,022 (32.95%)
- Obese 38,599 (36.32%)
Mental Health and Well-being
- Poor mental health days (mean, SD) 7.081 (9.943)
- Depressive Disorder
- Yes 32,670 (30.74%)
- No 73,615 (69.26%)
- Poor health days (mean, SD) 5.449 (9.462)
General Health
- Excellent 10,210 (9.61%)
- Very good 29,529 (27.78%)
- Good 34,422 (32.39%)
- Fair 21,873 (20.58%)
- Poor 10,251 (9.64%)
Health Insurance
- Yes 98,032 (92.24%)
- No 8,253 (7.76%)
Smoking Status
- Current smoker - daily 14,384 (13.53%)
- Current smoker - some days 5,458 (5.14%)
- Former smoker 31,329 (29.48%)
- Never smoked 55,114 (51.85%)

The analytic sample comprised 106,285 adults from the 2018 BRFSS, representing a broad demographic range. Most respondents identified as straight or not gay (93.6%), with bisexual (3.1%), lesbian or gay (2.1%), and “something else” (1.3%) groups also represented. Females made up 58% of the sample, and the majority were White, non-Hispanic (77%). Nearly 44% were aged 60 years or older, and about 74% reported annual incomes below $50,000. On average, participants reported 7 poor mental-health days and 5 poor physical-health days in the past month; 31% had been diagnosed with a depressive disorder. Most respondents had health-insurance coverage (92%), and smoking habits were mixed, with 52% never having smoked.

Table 2: Participant Characteristics by Sexual Orientation

Characteristic Straight (n=99,446) Lesbian/Gay (n=2,213) Bisexual (n=3,280) Something else (n=1,346)
Sex
- Male 41,846 (42.08%) 1,263 (57.07%) 1,008 (30.73%) 545 (40.49%)
- Female 57,600 (57.92%) 950 (42.93%) 2,272 (69.27%) 801 (59.51%)
Race
- White, Non-Hispanic 77,195 (77.63%) 1,664 (75.19%) 2,380 (72.56%) 904 (67.16%)
- Black, Non-Hispanic 9,031 (9.08%) 172 (7.77%) 257 (7.84%) 100 (7.43%)
- Asian, Non-Hispanic 2,261 (2.27%) 42 (1.90%) 68 (2.07%) 48 (3.57%)
- American Indian/Alaskan Native, Non-Hispanic 1,618 (1.63%) 29 (1.31%) 50 (1.52%) 28 (2.08%)
- Hispanic 5,332 (5.36%) 174 (7.86%) 299 (9.12%) 162 (12.04%)
- Other race, Non-Hispanic 4,009 (4.03%) 132 (5.96%) 226 (6.89%) 104 (7.73%)
Age Category
- 18–29 10,414 (10.47%) 475 (21.46%) 1,288 (39.27%) 315 (23.40%)
- 30–39 11,272 (11.33%) 317 (14.32%) 675 (20.58%) 169 (12.56%)
- 40–59 32,784 (32.97%) 765 (34.57%) 775 (23.63%) 296 (21.99%)
- 60 and older 44,976 (45.23%) 656 (29.64%) 542 (16.52%) 566 (42.05%)
Income Category
- Less than $50,000 46,513 (53.73%) 1,084 (53.64%) 1,751 (63.10%) 786 (71.00%)
- $50,000 or more 40,060 (46.27%) 937 (46.36%) 1,024 (36.90%) 321 (29.00%)
BMI Category
- Underweight 1,810 (1.82%) 53 (2.39%) 88 (2.68%) 57 (4.23%)
- Normal weight 28,444 (28.60%) 704 (31.81%) 1,086 (33.11%) 422 (31.35%)
- Overweight 33,017 (33.20%) 707 (31.95%) 881 (26.86%) 417 (30.98%)
- Obese 36,175 (36.38%) 749 (33.85%) 1,225 (37.35%) 450 (33.43%)
Mental Health Metrics
- Poor mental health days (mean, SD) 6.87 (9.85) 8.61 (10.34) 11.05 (10.86) 10.23 (11.31)
Depressive Disorder
- Yes 29,404 (29.57%) 943 (42.61%) 1,731 (52.77%) 592 (43.98%)
- No 70,042 (70.43%) 1,270 (57.39%) 1,549 (47.23%) 754 (56.02%)
- Poor health days (mean, SD) 5.39 (9.46) 5.79 (9.27) 6.25 (9.21) 6.90 (10.11)
General Health
- Excellent 9,566 (9.62%) 236 (10.66%) 295 (8.99%) 113 (8.40%)
- Very good 27,696 (27.85%) 624 (28.20%) 930 (28.35%) 279 (20.73%)
- Good 32,139 (32.32%) 745 (33.66%) 1,097 (33.45%) 441 (32.76%)
- Fair 20,404 (20.52%) 445 (20.11%) 691 (21.07%) 333 (24.74%)
- Poor 9,641 (9.69%) 163 (7.37%) 267 (8.14%) 180 (13.37%)
Health Insurance
- Yes 91,948 (92.46%) 2,033 (91.87%) 2,877 (87.71%) 1,174 (87.22%)
- No 7,498 (7.54%) 180 (8.13%) 403 (12.29%) 172 (12.78%)
Smoking Status
- Current smoker – daily 13,201 (13.27%) 402 (18.17%) 596 (18.17%) 185 (13.74%)
- Current smoker – some days 4,943 (4.97%) 156 (7.05%) 269 (8.20%) 90 (6.69%)
- Former smoker 29,594 (29.76%) 632 (28.56%) 779 (23.75%) 324 (24.07%)
- Never smoked 51,708 (52.00%) 1,023 (46.23%) 1,636 (49.88%) 747 (55.50%)
  • Sex distribution differed across sexual orientation groups, with males comprising 57.07% of lesbian/gay participants compared with 42.08% among straight participants, while females accounted for 69.27% of bisexual participants.

  • Younger age groups were overrepresented among sexual minorities, particularly among bisexual individuals, where 39.27% were aged 18–29, compared with 10.47% among straight participants. Individuals identifying as “something else” also showed a higher concentration in this age group (23.40%).

  • Lower household income was more common among sexual minority groups, with 63.10% of bisexual participants and 71.00% of those identifying as “something else” reporting incomes below $50,000, compared with 53.73% among straight participants.

  • BMI category distributions varied by sexual orientation, with obesity prevalence ranging from 33.43% among those identifying as “something else” to 37.35% among bisexual participants.

  • Depressive disorders were substantially more prevalent among sexual minorities, affecting 52.77% of bisexual individuals, 43.98% of those identifying as “something else,” and 42.61% of lesbian/gay participants, compared with 29.57% among straight participants.

  • Average poor mental health burden was higher among sexual minorities, with bisexual participants reporting a mean of 11.05 days of poor mental health in the past 30 days, compared with 6.87 days among straight participants.

Table 3: Association Between Poor Mental Health Days and Sexual Orientation

Characteristic Measure of Effect (β, 95% CI) P-value
Sexual Orientation
Straight/not gay (ref) 0.00
Lesbian/Gay 1.1790 (0.7713, 1.5866) <0.0001
Bisexual 2.4543 (2.1134, 2.7952) <0.0001
Something else 2.6512 (2.1275, 3.1749) <0.0001
Sex
Male (ref) 0.00
Female 1.0825 (0.9624, 1.2026) <0.0001
Race/Ethnicity
White, Non-Hispanic (ref) 0.00
Black, Non-Hispanic −0.3177 (−0.5258, −0.1097) 0.0028
Asian, Non-Hispanic −1.2726 (−1.6666, −0.8785) <0.0001
American Indian/Alaskan Native, Non-Hispanic 1.1250 (0.6614, 1.5887) <0.0001
Hispanic −0.2293 (−0.4903, 0.0317) 0.0851
Other race, Non-Hispanic 0.7220 (0.4292, 1.0149) <0.0001
Age Category
18–29 (ref) 0.00
30–39 −0.9891 (−1.2323, −0.7460) <0.0001
40–59 −1.1419 (−1.3476, −0.9362) <0.0001
60 and older −3.6062 (−3.8089, −3.4035) <0.0001
Income Category
Less than $50,000 (ref) 0.00
$50,000 or more −2.5905 (−2.7159, −2.4652) <0.0001
BMI Category
Normal weight (ref) 0.00
Underweight 1.2235 (0.7842, 1.6628) <0.0001
Overweight 0.1950 (0.0448, 0.3451) 0.0109
Obese 1.0718 (0.9243, 1.2193) <0.0001
Health Insurance
No (ref) 0.00
Yes −0.6492 (−0.8751, −0.4233) <0.0001
Smoking Status
Never smoked (ref) 0.00
Current smoker – daily 4.2994 (4.1159, 4.4828) <0.0001
Current smoker – some days 3.2445 (2.9733, 3.5158) <0.0001
Former smoker 1.1688 (1.0307, 1.3068) <0.0001
  • Sexual orientation was independently associated with poor mental health days. Compared with straight participants, adjusted mean days were higher among lesbian/gay (β = 1.18), bisexual (β = 2.45), and “something else” participants (β = 2.65) (all p < 0.0001).

  • Female sex was associated with a modest increase in poor mental health days compared with males (β = 1.08; p < 0.0001).

  • Older age was strongly protective, with participants aged 60 years or older reporting 3.61 fewer poor mental health days compared with those aged 18–29 (p < 0.0001).

  • Higher income was associated with fewer poor mental health days (β = −2.59; p < 0.0001).

  • Smoking status showed the largest effect sizes, with daily smokers reporting 4.30 additional poor mental health days compared with never smokers (p < 0.0001).

Table 4: Association Between Sexual Orientation and Depressive Disorder

Multivariable logistic regression was used to assess the association between sexual orientation and self-reported depressive disorder, adjusting for sex, race/ethnicity, age category, income category, BMI category, health insurance status, and smoking status. Note: Odds ratios in this table correspond to the outcome “no depressive disorder” modeled as the event of interest.

Sexual Orientation Adjusted Odds Ratio (95% CI) P-value
Straight/not gay (ref) 1.00
Lesbian/Gay 0.546 (0.499, 0.597) <0.0001
Bisexual 0.446 (0.414, 0.481) <0.0001
Something else 0.536 (0.479, 0.600) <0.0001
  • After adjustment for demographic, socioeconomic, and health-related covariates, sexual orientation was significantly associated with odds of reporting a depressive disorder.

  • Compared with straight participants, individuals identifying as lesbian/gay, bisexual, or “something else” had lower adjusted odds of reporting a depressive disorder (all p < 0.0001).

  • These associations persisted after controlling for sex, age, race/ethnicity, income, BMI category, health insurance status, and smoking status.

Table 5: Effect of Sexual Orientation Stratified by Age Category

Age-stratified multivariable models were fit to evaluate whether age modified the association between sexual orientation and mental health outcomes. Models were adjusted for sex, race/ethnicity, income category, BMI category, health insurance status, and smoking status. Note: For age-stratified logistic regression models, odds ratios correspond to the outcome “ Yes depressive disorder” modeled as the event of interest.

Poor Mental Health Days (β, 95% CI)

Sexual Orientation (vs. Straight/not gay) 18–29 years 30–39 years 40–59 years ≥60 years
Lesbian/Gay 2.61 (1.73, 3.48) 0.74 (0.34, 1.81) 0.86 (0.14, 1.59) 0.84 (0.12, 1.57)
Bisexual 3.48 (2.93, 4.04) 2.81 (2.06, 3.56) 1.67 (0.95, 2.38) 0.87 (0.08, 1.67)
Something else 5.48 (4.40, 6.55) 3.18 (1.73, 4.64) 1.20 (0.03, 2.38) 1.85 (1.07, 2.62)

Interaction p-value: <0.0001

Depressive Disorder (OR, 95% CI)

Sexual Orientation (vs. Straight/not gay) 18–29 years 30–39 years 40–59 years ≥60 years
Lesbian/Gay 2.31 (1.90, 2.81) 2.01 (1.58, 2.55) 1.77 (1.52, 2.06) 1.63 (1.38, 1.92)
Bisexual 2.88 (2.54, 3.26) 2.30 (1.95, 2.72) 1.98 (1.71, 2.31) 1.58 (1.32, 1.89)
Something else 4.10 (3.22, 5.22) 2.14 (1.55, 2.95) 1.60 (1.26, 2.04) 1.30 (1.08, 1.55)

Interaction p-value: <0.0001

  • Age significantly modified the association between sexual orientation and both poor mental health days and depressive disorder (interaction p < 0.0001).

  • Across all age groups, sexual minority participants reported higher poor mental health burden and higher odds of depressive disorder compared with straight participants.

  • The magnitude of association was strongest among adults aged 18–29 and consistently attenuated with increasing age.

  • Bisexual individuals and those identifying as “something else” showed the largest effect sizes across age strata for both outcomes.

Discussion

This analysis of the 2018 BRFSS data identifies meaningful disparities in mental health outcomes by sexual orientation. Several key patterns emerge from the descriptive, multivariable, and age-stratified analyses.

1. Disparities Across Sexual Orientation Categories

  • Sexual minority groups consistently experienced poorer mental health outcomes compared with straight individuals.
  • Bisexual individuals demonstrated the highest burden of poor mental health across multiple measures.
  • Individuals identifying as “something else” also showed elevated mental health challenges, particularly in younger age groups.

2. Demographic Patterns

  • Sexual minority groups were disproportionately represented in younger age categories.
  • Gender distributions differed by sexual orientation, with a higher proportion of males among lesbian/gay respondents and a higher proportion of females among bisexual respondents.
  • Lower income levels were more common among bisexual individuals and those identifying as “something else,” suggesting potential socioeconomic vulnerability.

3. Age as a Critical Modifier

  • The association between sexual orientation and mental health outcomes was strongest among younger adults.
  • Sexual minorities aged 18–29 exhibited the largest disparities in both poor mental health days and depressive disorder.
  • Although the magnitude of association decreased with age, disparities persisted across all age categories.

4. Other Risk Factors

  • Female sex was independently associated with worse mental health outcomes, particularly for depressive disorder.
  • Lower income was strongly associated with increased mental health burden.
  • Racial and ethnic associations varied by outcome, indicating complex and non-uniform patterns across groups.

Repository Structure

  • 00_run_all.sas: Master script to execute the full analytic pipeline
  • 01_import_and_formats.sas: Data import, formatting, and preprocessing
  • 02_clean_and_label.sas: Data cleaning, recoding, and variable labeling
  • 03_descriptives_bivariate.sas: Descriptive statistics and bivariate analyses
  • 04_model_menthlth.sas: Adjusted linear regression for poor mental health days
  • 05_model_depression.sas: Adjusted logistic regression for depressive disorder
  • 06_age_stratified_models.sas: Age-stratified models and interaction analyses

Software

All analyses were conducted using SAS statistical software.

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