Impact of Breastfeeding Barriers on Racial/Ethnic Disparities in Breastfeeding Outcomes in North Dakota.

OBJECTIVE: Exclusive breastfeeding is recommended for the first 6 months of life, but there are racial/ethnic disparities in meeting this recommendation. METHODS: 2017-2020 North Dakota Pregnancy Risk Assessment Monitoring System (weighted N = 11,754) data were used to examine racial/ethnic differences in the association between self-reported breastfeeding barriers and breastfeeding duration. Breastfeeding duration was self-reported breastfeeding at 2 and 4 months, and number of weeks until breastfeeding cessation. Self-reported breastfeeding barriers were yes/no responses to 13 barriers (e.g., "difficulty latching," "household duties"). Logistic regression estimated odds ratios and 95% confidence intervals to determine if barriers accounted for breastfeeding disparities by race/ethnicity. Cox proportional hazard models estimated hazard ratios for stopping breastfeeding for American Indian and other race/ethnicity individuals, compared to White individuals. Models were adjusted for birthing parents' demographic and medical factors. RESULTS: Logistic regression results suggest American Indian birthing parents had similar odds for breastfeeding duration (2-month duration: OR 0.94 (95%CI 0.50, 1.77); 4-month duration: OR 1.24 (95%CI 0.43, 3.62)) compared to White birthing parents, after accounting for breastfeeding barriers. Cox proportional hazard models suggest American Indian birthing parents had a lower hazard of stopping breastfeeding (HR 0.76 (95%CI 0.57, 0.99)) than White parents, after accounting for breastfeeding barriers. CONCLUSIONS: Accounting for breastfeeding barriers eliminated observed disparities in breastfeeding outcomes between American Indian and White birthing parents. Targeted and culturally safe efforts to reduce barriers to breastfeeding are warranted to reduce racial/ethnic disparities in breastfeeding.

Adverse Childhood Experiences, Interpersonal Violence, and Racial Disparities in Early Prenatal Care in North Dakota (ND PRAMS 2017-2019).

In North Dakota (ND), American Indian women are more likely to be exposed to adverse childhood experiences (ACEs) and interpersonal violence, and receive late prenatal care (PNC) compared to other racial groups. In a sample of 1,849 (weighted n = 26,348) women from the 2017 to 2019 North Dakota Pregnancy Risk Assessment Monitoring System, we performed a series of logistic regression models to estimate odds ratios (OR) and 95% confidence intervals (95% CI) for AI and Other Racial Identity women compared to White women regarding risk of late PNC (initiated after week 13) and dissatisfaction of PNC timing. Models were adjusted for interpersonal violence (from husband/partner, family member, someone outside of family, ex-husband/partner, or any) to determine if violence accounts for racial/ethnic disparities in PNC. AI women experienced two-fold higher risk of late PNC (OR: 2.25, 95% CI: 1.55, 3.26) and dissatisfaction of PNC timing (OR: 2.34, 95% CI: 1.61, 3.40) than White women. In the analyses for the association between joint ACEs (Higher: ≥4; Lower: <4)/Race and PNC outcomes, odds of late PNC were two-fold among AI women with Higher ACEs (OR: 2.35, 95% CI: 1.41, 3.94) and Lower ACEs (OR: 2.73, 95% CI: 1.69, 4.41), compared to White women with Lower ACEs. Results were similar for dissatisfaction of PNC timing. Accounting for violence did not significantly change odds ratios in any analyses. Thus, interpersonal violence surrounding pregnancy does not explain racial disparities in PNC in ND. To understand disparities in PNC among AI women, risk factors like historic trauma and systemic oppression should be examined.

Estimating the prevalence of COVID-19 cases through the analysis of SARS-CoV-2 RNA copies derived from wastewater samples from North Dakota.

The SARS-CoV-2 virus was first detected in December 2019, which prompted many researchers to investigate how the virus spreads. SARS-CoV-2 is mainly transmitted through respiratory droplets. Symptoms of the SARS-CoV-2 virus appear after an incubation period. Moreover, the asymptomatic infected individuals unknowingly spread the virus. Detecting infected people requires daily tests and contact tracing, which are expensive. The early detection of infectious diseases, including COVID-19, can be achieved with wastewater-based epidemiology, which is timely and cost-effective. In this study, we collected wastewater samples from wastewater treatment plants in several cities in North Dakota and then extracted viral RNA copies. We used log-RNA copies in the model to predict the number of infected cases using Quantile Regression (QR) and K-Nearest Neighbor (KNN) Regression. The model's performance was evaluated by comparing the Mean Absolute Percentage Error (MAPE). The QR model performs well in cities where the population is >10000. In addition, the model predictions were compared with the basic Susceptible-Infected-Recovered (SIR) model which is the golden standard model for infectious diseases.

Geographic disparities and temporal changes of COVID-19 hospitalization risks in North Dakota.

Background: Although the burden of the coronavirus disease 2019 (COVID-19) has been different across communities in the US, little is known about the disparities in COVID-19 burden in North Dakota (ND) and yet this information is important for guiding planning and provision of health services. Therefore, the objective of this study was to identify geographic disparities of COVID-19 hospitalization risks in ND. Methods: Data on COVID-19 hospitalizations from March 2020 to September 2021 were obtained from the ND Department of Health. Monthly hospitalization risks were computed and temporal changes in hospitalization risks were assessed graphically. County-level age-adjusted and spatial empirical Bayes (SEB) smoothed hospitalization risks were computed. Geographic distributions of both unsmoothed and smoothed hospitalization risks were visualized using choropleth maps. Clusters of counties with high hospitalization risks were identified using Kulldorff's circular and Tango's flexible spatial scan statistics and displayed on maps. Results: There was a total of 4,938 COVID-19 hospitalizations during the study period. Overall, hospitalization risks were relatively stable from January to July and spiked in the fall. The highest COVID-19 hospitalization risk was observed in November 2020 (153 hospitalizations per 100,000 persons) while the lowest was in March 2020 (4 hospitalizations per 100,000 persons). Counties in the western and central parts of the state tended to have consistently high age-adjusted hospitalization risks, while low age-adjusted hospitalization risks were observed in the east. Significant high hospitalization risk clusters were identified in the north-west and south-central parts of the state. Conclusions: The findings confirm that geographic disparities in COVID-19 hospitalization risks exist in ND. Specific attention is required to address counties with high hospitalization risks, especially those located in the north-west and south-central parts of ND. Future studies will investigate determinants of the identified disparities in hospitalization risks.

Examining the Role of Interpersonal Violence in Racial Disparities in Breastfeeding in North Dakota (ND PRAMS 2017-2019).

BACKGROUND: The 2019 overall breastfeeding initiation rate in the US was 84.1%, yet only 76.6% of American Indian (AI) women initiated breastfeeding. In North Dakota (ND), AI women have greater exposure to interpersonal violence than other racial/ethnic groups. Stress associated with interpersonal violence may interfere with processes important to breastfeeding. We explored whether interpersonal violence partially explains racial/ethnic disparities in breastfeeding in ND. METHODS: Data for 2161 women were drawn from the 2017-2019 ND Pregnancy Risk Assessment Monitoring System. Breastfeeding questions in PRAMS have been tested among diverse populations. Breastfeeding initiation was self-report to "Did you ever breastfeed or pump breast milk to feed your new baby, even for a short period?" (yes/no). Breastfeeding duration (2 months; 6 months) was self-reported how many weeks or months of breastmilk feeding. Interpersonal violence for both 12 months before and during pregnancy based on self-report (yes/no) of violence from a husband/partner, family member, someone else, or ex-husband/partner. An "Any violence" variable was created if participants reported "yes" to any violence. Logistic regression models estimated crude and adjusted odds ratios (OR) and 95% confidence intervals (95% CI) for breastfeeding outcomes among AI and Other Race women compared to White women. Sequential models were adjusted for interpersonal violence (husband/partner, family member, someone else, ex-husband/partner, or any). RESULTS: AI women had 45% reduced odds of initiating breastfeeding (OR: 0.55, 95% CI: 0.36, 0.82) compared to white women. Including interpersonal violence during pregnancy did not change results. Similar patterns were observed for all breastfeeding outcomes and all interpersonal violence exposures. DISCUSSION: Interpersonal violence does not explain the disparity in breastfeeding in ND. Considering cultural ties to the tradition of breastfeeding and the role of colonization may provide a better understanding of breastfeeding among AI populations.

Geographic disparities and temporal changes of COVID-19 incidence risks in North Dakota, United States.

BACKGROUND: COVID-19 is an important public health concern due to its high morbidity, mortality and socioeconomic impact. Its burden varies by geographic location affecting some communities more than others. Identifying these disparities is important for guiding health planning and service provision. Therefore, this study investigated geographical disparities and temporal changes of the percentage of positive COVID-19 tests and COVID-19 incidence risk in North Dakota. METHODS: COVID-19 retrospective data on total number of tests and confirmed cases reported in North Dakota from March 2020 to September 2021 were obtained from the North Dakota COVID-19 Dashboard and Department of Health, respectively. Monthly incidence risks of the disease were calculated and reported as number of cases per 100,000 persons. To adjust for geographic autocorrelation and the small number problem, Spatial Empirical Bayesian (SEB) smoothing was performed using queen spatial weights. Identification of high-risk geographic clusters of percentages of positive tests and COVID-19 incidence risks were accomplished using Tango's flexible spatial scan statistic. ArcGIS was used to display and visiualize the geographic distribution of percentages of positive tests, COVID-19 incidence risks, and high-risk clusters. RESULTS: County-level percentages of positive tests and SEB incidence risks varied by geographic location ranging from 0.11% to 13.67% and 122 to 16,443 cases per 100,000 persons, respectively. Clusters of high percentages of positive tests were consistently detected in the western part of the state. High incidence risks were identified in the central and south-western parts of the state, where significant high-risk spatial clusters were reported. Additionally, two peaks (August 2020-December 2020 and August 2021-September 2021) and two non-peak periods of COVID-19 incidence risk (March 2020-July 2020 and January 2021-July 2021) were observed. CONCLUSION: Geographic disparities in COVID incidence risks exist in North Dakota with high-risk clusters being identified in the rural central and southwest parts of the state. These findings are useful for guiding intervention strategies by identifying high risk communities so that resources for disease control can be better allocated to communities in need based on empirical evidence. Future studies will investigate predictors of the identified disparities so as to guide planning, disease control and health policy.

Epidemiology of Hepatitis C virus infection among incarcerated populations in North Dakota.

This retrospective cohort study was conducted to determine the prevalence of HCV infections among individuals incarcerated in a state prison system and identify potential contributing factors to HCV infection. North Dakota Department of Corrections and Rehabilitation (NDDOCR) data from 2009 to 2018 was used and period prevalence was calculated for this 10-year time period. The period prevalence of HCV infection was (15.13% (95% CI 14.39-15.90) with a marginally significant (p-value: 0.0542) increasing linear trend in annual prevalence over this period. Multivariate logistic regression analysis was used to identify risk factors associated with HCV infection. The main significant independent risk factors for HCV infection in this incarcerated population were age >40 years [OR: 1.78 (1.37-2.32)]; sex [OR: 1.21 (1.03-1.43)]; race/ethnicity [OR: 1.97 (1.69-2.29)]; history of intravenous drug use (IVDU) [OR: 7.36 (6.41-8.44)]; history of needle or syringe sharing [OR: 7.57 (6.62-8.67)]; and alcohol use [OR: 0.87 (0.77-0.99)]. Study limitations include uncollected information on sexual history, frequency or duration of injection drug use and blood transfusion history of the incarcerated population. Considering the high prevalence of HCV infection and its associated risk factors, it is important to implement prevention programs such as syringe/needle exchanges and counsel with imprisoned IVD users.

Investigation of Predictors of Newborn Screening Refusal in a Large Birth Cohort in North Dakota, USA.

Objectives The objective of this study was to identify maternal and provider predictors of newborn screening (NBS) refusal in North Dakota between 2011 and 2014. Methods Records of 40,440 live resident births occurring in North Dakota between 2011 and 2014 were obtained from the North Dakota Department of Health and included in the study. Factor-specific percentages of NBS refusals and 95% confidence intervals were computed for each predictor. Since the outcome is rare, multivariable Firth logistic regression was used to investigate maternal and provider predictors of NBS refusal. Model goodness-of-fit test was evaluated using the Hosmer-Lemeshow test. All analyses were conducted in SAS 9.4. Results Of the 40,440 live births, 135 (0.33%) were NBS refusals. 97% of the refusals were to white women, 94% were homebirths, and 93% utilized state non-credentialed birth attendants. The odds of NBS refusals were significantly higher among non-credentialed birth attendants (p < 0.0001), homebirths (p < 0.0001), and among those that refused Hepatitis B vaccination (HBV) at birth (p = 0.047). On the other hand, odds of NBS refusals were significantly (p < 0.0001) lower among women that had more prenatal visits. Conclusions for Practice This study provides preliminary evidence of association between NBS refusal and provider type, home births, and HBV refusal. Additional studies of obstetric providers, home births and women are needed to improve our understanding of the reasons for NBS refusal to better deliver preventive services to newborns.