Digitalcommons@DMU (Des Moines University)
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President Azneer In His Office
No full textA poster size photo of President J. Leonard Azneer sitting at his desk.https://digitalcommons.dmu.edu/archive_images/2058/thumbnail.jp
President Azneer Speaking
No full textA poster size photo of President J. Leonard Azneer leaning on the side of a podium and speaking into a microphone in his hand.https://digitalcommons.dmu.edu/archive_images/2056/thumbnail.jp
COMS 3200 Grand Avenue Entrance
No full textAn exterior photo looking up at the entrance tower of the old St. Joseph\u27s Academy Building. Written above the entrance is COMS 3200 .https://digitalcommons.dmu.edu/archive_images/2069/thumbnail.jp
President Dr. S. S. Still Portrait
No full textA portrait of President Dr. S. S. Still, Professor of Descriptive Anatomy and Philosophy of Osteopathy and President 1898-1906, framed by poster board.https://digitalcommons.dmu.edu/archive_images/2025/thumbnail.jp
Public Water Quality and Birth Outcomes: Evidence from the World’s Largest Nitrate Removal Facility
No full textIn response to rising nitrate levels in Iowa’s public drinking water, the city of Des Moines built the world’s largest nitrate removal facility. The facility operates when nitrate levels exceed the regulatory threshold of 10 mg/L, incurring costs exceeding $10,000 per day. To evaluate the effect of the nitrate removal facility on birth weight and gestational age, we analyzed publicly available birth certificate microdata (1992-2004). In addition to adjusting for maternal and fraternal sociodemographic factors, our linear regression model included county-year fixed-effects to adjust for annual differences across counties and year-month fixed-effects to account for seasonal variation in birth outcomes. Unbiased identification relied on exogenous geotemporal variation in first-trimester exposure to operation of the nitrate removal facility. Operating the nitrate removal facility was associated with a 0.4-percentage-point increase in the probability of normal birth weight and was associated with a 1.6-percentage-point increase in the probability of a normal term birth. The positive associations were largest among mothers with higher risk of adverse outcomes (smoked during pregnancy, cesarean deliveries, prior preterm births, excessive weight gain, unmarried, unknown father). A post-hoc analysis suggests that this intervention may be cost effective, multiplying public investment by 3.5 dollars in health benefits. As policymakers explore how to address rising nitrate pollution, quantifying the value of nitrate reduction strategies could inform future public health interventions. Although the Des Moines nitrate removal facility appears to serve a crucial public health function and advance health equity, challenges remain for deciding how to pay for this potentially cost-effective intervention
Dr. Elizabeth Burrows Portrait
No full textA portrait of Dr. Elizabeth Burrows, Professor of Obstetrics and Gynecology, framed by poster board.https://digitalcommons.dmu.edu/archive_images/2033/thumbnail.jp
Rural–Urban Cancer Incidence and Trends in the United States, 2000 to 2019
No full textBackground:
Despite consistent improvements in cancer prevention and care, rural and urban disparities in cancer incidence persist in the United States. Our objective was to further examine rural–urban differences in cancer incidence and trends. Methods:
We used the North American Association of Central Cancer Registries dataset to investigate rural–urban differences in 5-year age-adjusted cancer incidence (2015–2019) and trends (2000–2019), also examining differences by region, sex, race/ethnicity, and tumor site. Age-adjusted rates were calculated using SEER∗Stat 8.4.1, and trend analysis was done using Joinpoint, reporting annual percent changes (APC). Results:
We observed higher all cancer combined 5-year incidence rates in rural areas (457.6 per 100,000) compared with urban areas (447.9), with the largest rural–urban difference in the South (464.4 vs. 449.3). Rural populations also exhibited higher rates of tobacco-associated, human papillomavirus–associated, and colorectal cancers, including early-onset cancers. Tobacco-associated cancer incidence trends widened between rural and urban from 2000 to 2019, with significant, but varying, decreases in urban areas throughout the study period, whereas significant rural decreases only occurred between 2016 and 2019 (APC = −0.96). Human papillomavirus–associated cancer rates increased in both populations until recently with urban rates plateauing whereas rural rates continued to increase (e.g., APC = 1.56, 2002–2019). Conclusions:
Rural populations had higher overall cancer incidence rates and higher rates of cancers with preventive opportunities compared with urban populations. Improvements in these rates were typically slower in rural populations. Impact:
Our findings underscore the complex nature of rural–urban disparities, emphasizing the need for targeted interventions and policies to reduce disparities and achieve equitable health outcomes
How Did the COVID-19 Pandemic Change Cigarette Smoking Behavior?
No full textBackground: Cigarette smoking is the leading cause of preventable death in the United States. Although smoking rates have been declining, it is unclear how the COVID-19 pandemic impacted smoking behaviors. Methods: With population-based data from the Behavioral Risk Factor Surveillance System (2010–2023), we will analyze four outcomes: (1) currently smoking, (2) started smoking in the past year, (3) number of cigarettes per day, and (4) quit smoking in the past year. By estimating a two-way fixed effect regression model to account for state-level factors and temporal trends, this study identifies the effect of exposure to the COVID-19 pandemic by comparing the change over time in an unexposed group (interviewed January 1–March 20, 2020) to the change over time in the exposed group (interviewed January 1–March 31, 2021–2023). This stage 1-registered report conducts a Power and pilot analysis with an exploratory outcome: being uninsured. Pilot Results: Our power analysis calculates a minimum detectable effect size = 0.7%. The pilot analysis indicates that exposure to the COVID-19 pandemic was associated with a statistically significant decline in the probability of being uninsured (Est. = −2.2%; CI = −3.5, −1.1). There is little evidence that the early and late survey wave cohorts differed before the pandemic. Implications: This registered report outlines a study aimed at investigating the direct impact of the COVID-19 pandemic on smoking behaviors related to prevalence, initiation, intensity, and cessation. The findings will provide valuable insights into the effects of public health crises on health-related behaviors and inform future public health interventions. The preregistration of the study design and analysis plan ensures transparency, trust, and replicability of the results. Quantifying whether and how smoking behaviors changed, and in whom, can inform ongoing tobacco control efforts to continue the downward trend in cigarette smoking. Preregistration: https://osf.io/vq8m4
Leveraging public health cancer surveillance capacity to develop and support a rural cancer network
No full textIntroduction: As the rural–urban cancer mortality gap widens, centering care around the needs of rural patients presents an opportunity to advance equity. One barrier to delivering patient-centered care at rural hospitals stems from limited analytic capacity to leverage data and monitor patient outcomes. This case study describes the experience of a public health cancer surveillance system aiming to fill this gap within the context of a rural cancer network. Methods: To support the implementation of a novel network model intervention in Iowa, the Iowa Cancer Registry began generating hospital-specific and catchment area reports. Then, the Iowa Cancer Registry supported adapting the network model to fit the context of Iowa\u27s cancer care delivery system by performing data monitoring and reporting functions. Informed by a gap analysis, the Iowa Cancer Registry then identified which quality accreditation standards could be achieved with public health surveillance data and analytic support. Results: The network intervention in Iowa supported 5 rural cancer centers across the state, each concurrently pursuing quality accreditation standards. The Iowa Cancer Registry\u27s hospital and catchment-specific reports illuminated the cancer burden and needs of rural cancer centers within the network. Our team identified 19 (of the 36 total) quality standards that can be supported by public health surveillance functions typically performed by the registry. These standards encompassed data-driven quality improvement, patient monitoring, and reporting guideline-concordant care standards. Conclusions: As rural hospitals continue to face resource constraints, multisectoral efforts informed by data from centralized public health surveillance systems can promote quality improvement initiatives across rural communities. While our work remains preliminary, we predict that analytic support provided by the Iowa Cancer Registry will enable the rural network hospitals to focus their capacity toward developing the infrastructure necessary to deliver high-quality care and serve the unique needs of rural cancer patients