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BACKGROUND: High use of computers among college students and the resulting musculoskeletal disorders raises concerns regarding healthy usage patterns. OBJECTIVE: The purpose of this study is to examine college student’s computer usage and related musculoskeletal discomfort. METHODS: A sample of 338 college students completed a cross-sectional survey consisting of demographic questions, musculoskeletal discomfort indicators and questions regarding computer use. RESULTS: The sample included 232 (68.6%) females and 106 (31.3%) males. 61% students had reported discomfort during or after working using computers with greatest discomfort in the neck (68.5%) and lower back (66%). Female students were more likely than male students to report any musculoskeletal discomfort (66% vs 51%), p <  .05. Sitting duration, awkward postures and length of time (more than eight hours) were significantly associated with musculoskeletal discomfort (R2 = 0.24, p <  .01). CONCLUSION: Most female college students reported musculoskeletal discomfort during or after computer use. Daily use of computer for more than eight hours, assuming awkward postures and sitting for long duration without breaks were found to be significantly related to musculoskeletal discomfort. Emphasizing good computing habits in college students to avoid musculoskeletal symptoms in the future will prevent morbidity in future workforce.

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Background: Mortality due to coronavirus disease-2019 among Black and Hispanic populations is disproportionately high compared to white populations. This study aimed to explore the association between COVID-19 mortality and social determinants of health (SDOH) among Black and Hispanic populations in Virginia. Method: County-level publicly available COVID-19 mortality data from Virginia, covariates, and SDOH indicators were used. An independent t-test and hierarchical multiple regression analysis were performed to assess the association between SDOH and COVID-19 death rates, with a focus on racial/ethnic disparities. Results: Counties in the lowest quartile had a mean death rate of 44.72 (SD = 13.8), while those in the highest quartile had a mean death rate of 239.02 (SD = 123.9) per 100, 000 people (P < .001). Counties with the highest death rates had significantly lower mean socioeconomic status. The regression analysis revealed that 32% of the variance in the COVID-19 mortality rate was associated with SDOH after controlling for the covariates (P < .01). Identifying as Hispanic ethnicity accounted for 8.5% of the variance, while median household income, being uninsured, and education accounted for 32.7%, 12.9%, and 7.1%, respectively. Conclusions: The findings provide evidence that disparities in SDOH experienced by Hispanic populations play a significant role in increased COVID-19 mortality, thus highlighting the social needs of low-income, low-education, and Hispanic populations to advance equity in health outcomes.