Table 2.
Characteristic | Value | ||
Sex, n (%)a |
|
||
|
Male | 432,847 (59.8) | |
|
Female | 290,755 (40.2) | |
|
Other/Unknown | 2 (<0.1) | |
Gender, n (%)a |
|
||
|
Male | 432,614 (59.8) | |
|
Female | 290,302 (40.1) | |
|
Transgender male | 217 (<0.1) | |
|
Transgender female | 241 (<0.1) | |
|
Non-binary | 229 (<0.1) | |
|
Other/Unknown | 1 (<0.1) | |
Age in years, median (IQR) | 41.0 (27.0) | ||
Age group (years), n (%)a |
|
||
|
18-34 | 279,276 (38.6) | |
|
35-49 | 187,072 (25.9) | |
|
50-64 | 156,250 (21.6) | |
|
≥65 | 101,006 (14.0) | |
Race/ethnicity, n (%)a |
|
||
|
White | 427,606 (59.1) | |
|
Asian/Native Hawaiian/Pacific Islander | 76,197 (10.5) | |
|
Black | 50,601 (7.0) | |
|
Latino/Hispanic | 138,925 (19.2) | |
|
Native American | 7,015 (1.0) | |
|
Other/Unknown | 23,260 (3.2) | |
Household income (US$)b, n (%)a |
|
||
|
0-19,999 | 5,694 (0.8) | |
|
20,000-34,999 | 38,534 (5.3) | |
|
35,000-69,999 | 264,638 (36.6) | |
|
≥70,000 | 409,004 (56.5) | |
|
Unknown | 5,734 (0.8) | |
Educationc, n (%)a |
|
||
|
Less than high school | 32,446 (4.5) | |
|
High school graduate | 171,132 (23.6) | |
|
Some college or higher | 517,624 (71.5) | |
|
Unknown | 2,402 (0.3) | |
Smoking status, n (%)a |
|
||
|
Never or former | 552,618 (76.4) | |
|
Current | 115,557 (16.0) | |
|
Unknown | 55,429 (7.7) | |
Charlson comorbidity score, n (%)a |
|
||
|
0 | 614,422 (84.9) | |
|
1 | 64,420 (8.9) | |
|
≥2 | 44,762 (6.2) | |
Type of insurance, n (%)a |
|
||
|
None | 30,033 (4.2) | |
|
Medicaid | 19,834 (2.7) | |
|
Medicare | 105,393 (14.6) | |
|
Commercial | 561,620 (77.6) | |
|
Other | 6,724 (0.9) | |
Enrolled via California Affordable Care Act exchange, n (%)a | 44,110 (6.1) | ||
Months of follow-up data in the registry, median (IQR) | 21.0 (39.0) | ||
Number of alcohol screenings, minimum-maximum | 0-15 |
aPercentages may not add up to 100% due to rounding error.
bMedian household income from geocoded census blocks to patients’ residential addresses was used as a proxy of individual-level data.
cThe proportion of individuals within a census block with a level of education was used to estimate each patient’s education level.