Objectives This study aimed to evaluate the cause-of-death data in Minnesota (2011-2021) to understand the usage of "garbage codes" on death certificates. Study design We conducted a logistic regression analysis using death data from the Minnesota Vital Statistics System that compiles statistical data on all births, deaths, infant deaths, and fetal deaths in Minnesota. Methods Death certificate data from the Minnesota Department of Health were analyzed, and garbage codes were classified using ANACONDA criteria. Logistic regression assessed associations with socioeconomic variables, considering demographic factors, county characteristics, and fixed effects. Results Garbage codes constituted 3-4% of deaths, with variations by location, demographics, and office affiliation. Logistic regression revealed significant odds variations, notably related to age, rural residence, education, marital status, and place of death. Conclusions The study unveiled variations in cause-of-death data reliability in Minnesota, emphasizing the prevalence of garbage codes. Enhancing cause-of-death data accuracy is pivotal for informed public health decisions and accurate death statistics to guide targeted public health interventions and mitigate health disparities.

Objectives. To understand the occupational risk associated with COVID-19 among civilian critical workers (aged 16-65 years) in Minnesota. Methods. We estimated excess mortality in 2020 to 2021 for critical occupations in different racial groups and vaccine rollout phases using death certificates and occupational employment rates for 2017 to 2021. Results. Excess mortality during the COVID-19 pandemic was higher for workers in critical occupations than for noncritical workers. Some critical occupations, such as transportation and logistics, construction, and food service, experienced higher excess mortality than did other critical occupations, such as health care, K-12 school staff, and agriculture. In almost all occupations investigated, workers of color experienced higher excess mortality than did White workers. Excess mortality in 2021 was greater than in 2020 across groups: occupations, vaccine eligibility tiers, and race/ethnicity. Conclusions. Although workers in critical occupations experienced greater excess mortality than did others, excess mortality among critical workers varied substantially by occupation and race. Public Health Implications. Analysis of mortality across occupations can be used to identify vulnerable populations, prioritize protective interventions for them, and develop targeted worker safety protocols to promote equitable health outcomes. (Am J Public Health. 2023;113(11):1219-1222. https://doi.org/10.2105/AJPH.2023.307395).