Background: Socioeconomic variables influence various healthcare issues in different ways. The effect of socioeconomic variables on the shoulder has not been well studied. Because activity level, defined by how much a patient actually does, is an important patient outcome measure and prognostic factor for the shoulder, studying its association with occupation and income will advance our understanding of how these variables relate to shoulder disorders, treatments, and outcomes. Questions/purpose: We asked: (1) Does shoulder activity score correlate with income level, stratified by gender? (2) Do different employment groups—heavy, moderate, light, student, retired—have different shoulder activity scores, as stratified by gender? (3) Is type of sports participation (contact or overhead) associated with income level, employment type, race, or household size? Methods: A survey collected the Brophy and Marx shoulder activity score and demographic information, such as age, gender, race, income, type of employment, and household size from 1625 individuals 18 years and older with no current or previous shoulder pain or injury who are members of a research panel matched to the United States population by age, gender, household income and size, race/ethnicity, and geography. Men and women were analyzed separately. Activity level was controlled for age. Results: Shoulder activity correlated with income level among men (R = 0.03; p < 0.001) and women (R = 0.06; p = 0.0002). For men, heavy employment had the highest Shoulder Activity Scale (SAS) level (12.1 ± 4.9), which was more than SAS levels in sedentary (9.1 ± 4.5; mean difference, 3.0; 95% CI, 2.5–3.6; p = 0.001), student (8.8 ± 5.1; mean difference, 3.3; 95% CI, 3.0–3.7; p = 0.007), retired (8.0 ± 4.6; mean difference, 4.1; 95% CI, 3.6–4.7; p = 0.0001), and not working (7.5 ± 5.3; mean difference, 4.6; 95% CI, 4.6–4.6; p < 0.001) categories; similarly, for women, heavy employment had the highest SAS level (12.0 ± 5.8). However, as there were few women working in heavy labor, the only significant difference in women was between moderate employment (8.8 ± 4.2) and sedentary employment (7.0 ± 4.1; mean difference, 1.8; 95% CI, 1.6–1.9; p = 0.0015). Participation in contact (19.9% vs 12.0%; p = 0.006) and overhead sports (25.2% vs 14.2%; p < 0.001) was greater among males with higher incomes. Conclusions: Shoulder activity level is related to the socioeconomic factors of income and type of employment. Heavy laborers have higher shoulder activity level, likely directly related to their work. Individuals with higher incomes also have higher shoulder activity level, probably attributable to recreation as evidenced by their greater participation in contact and overhead sports. Independent of the underlying cause, these patients probably are more likely to seek treatment for shoulder disorders and may be more challenging to treat because of their elevated activity level. Future research should focus on how elevated activity level in these populations affects their risk for shoulder disorders, and their use of and outcomes from treatment for these disorders.