Lincoln Trail District Health Department's Innovative Shift to Public Health 3.0.

The Lincoln Trail District Health Department's (LTDHD) transformation into the Public Health 3.0 model was applied from frameworks established through public health accreditation standards and innovative strategies. The awareness of strengths and weaknesses discovered through strategic planning and a culture of quality improvement built over time has created numerous performance improvement opportunities. Those opportunities established greater collaboration and transparency between departments. The shift to the Public Health 3.0 and focus on Foundational Public Health Services model made for an easier transition into Kentucky's larger plan for public health transformation. LTDHD continues to provide public health protection by preventing the spread of disease, ensuring the safety of food, air, and water quality, supporting maternal and child health, improving access to clinical care services, and preventing chronic disease and injury.

Hepatitis A Outbreaks Associated With the Opioid Epidemic in Kentucky Counties, 2017-2018.

Objectives. To describe county-level socioeconomic profiles associated with Kentucky's 2017-2018 hepatitis A outbreak that predominately affected communities affected by the opioid epidemic.Methods. We linked county-level characteristics on socioeconomic and housing variables to counties' hepatitis A rates. Principal component analysis identified county profiles of poverty, education, disability, income inequality, grandparent responsibility, residential instability, and marital status. We used Poisson regression to estimate adjusted relative risks (RRs) and 95% confidence intervals (CIs).Results. Counties with scores reflecting an extremely disadvantaged profile (RR = 1.21; 95% CI = 0.99, 1.48) and greater percentage of nonmarried men, residential instability, and income inequality (RR = 1.15; 95% CI = 0.94, 1.41) had higher hepatitis A rates. Counties with scores reflecting more married adults, residential stability, and lower income inequality despite disability, poverty, and low education (RR = 0.77; 95% CI = 0.59, 1.00) had lower hepatitis A rates. Counties with a higher percentage of workers in the manufacturing industry had slightly lower rates (RR = 0.97; 95% CI = 0.94, 1.00).Conclusions. As expected, impoverished counties had higher hepatitis A rates. Evaluation across the socioeconomic patterns highlighted community-level factors (e.g., residential instability, income inequality, and social structures) that can be collected to augment hepatitis A data surveillance and used to identify higher-risk communities for targeted immunizations.

Residence in urban or rural counties in relation to opioid overdose mortality among Kentucky hospitalizations before and during the COVID-19 pandemic.

BACKGROUND: At the beginning of the opioid overdose epidemic, overdose mortality rates were higher in urban than in rural areas. We examined the association between residence in an urban or rural county and subsequent opioid overdose mortality in Kentucky, a state highly impacted by the opioid epidemic, and whether this was modified by the COVID-19 pandemic. METHODS: We captured hospitalizations in Kentucky from 2016 to 2020, involving an opioid using ICD-10-CM codes T40.0-T40.4 and T40.6. Patient's county was classified as urban or rural based on the NCHS Urban-Rural Classification Scheme. Multivariable logistic regression was used to estimate odds ratios (ORs) and 95% confidence intervals (CIs) of opioid overdose mortality, adjusted for demographics, hospitalization severity, and zip code SES. We assessed effect modification by the COVID-19 pandemic. RESULTS: Overall, patients living in urban counties had 46% higher odds of opioid overdose death than patients residing in rural counties (adjusted OR=1.46; 95% CI=1.22, 1.74). Before the pandemic, patients in urban counties had 63% increased odds of opioid overdose death (adjusted OR=1.63; 95% CI=1.34, 1.97); however, during the COVID-19 pandemic, patients in urban and rural counties became more similar in regard to opioid overdose mortality (adjusted OR=0.72; 95% CI=0.45, 1.16; p-value for interaction =0.02). CONCLUSION: Before the pandemic, living in urban counties was associated with higher opioid overdose mortality among Kentucky hospitalizations; however, during the COVID-19 pandemic, opioid overdose mortality in rural areas increased, approaching rates in urban areas. COVID-19 posed social, economic, and healthcare challenges that may be contributing to worsening mortality trends affecting both urban and rural patients.

Exposure to natural vegetation in relation to mammographic density in a Massachusetts-based clinical cohort.

Inverse associations between natural vegetation exposure (i.e., greenness) and breast cancer risk have been reported; however, it remains unknown whether greenness affects breast tissue development or operates through other mechanisms (e.g., body mass index [BMI] or physical activity). We examined the association between greenness and mammographic density-a strong breast cancer risk factor-to determine whether greenness influences breast tissue composition independent of lifestyle factors. Methods: Women (n = 2,318) without a history of breast cancer underwent mammographic screening at Brigham and Women's Hospital in Boston, Massachusetts, from 2006 to 2014. Normalized Difference Vegetation Index (NDVI) satellite data at 1-km2 resolution were used to estimate greenness at participants' residential address 1, 3, and 5 years before mammogram. We used multivariable linear regression to estimate differences in log-transformed volumetric mammographic density measures and 95% confidence intervals (CIs) for each 0.1 unit increase in NDVI. Results: Five-year annual average NDVI was not associated with percent mammographic density in premenopausal (ß = -0.01; 95% CI = -0.03, 0.02; P = 0.58) and postmenopausal women (ß = -0.02; 95% CI = -0.04, 0.01; P = 0.18). Results were similar for 1-year and 3-year NDVI measures and in models including potential mediators of BMI and physical activity. There were also no associations between greenness and dense volume and nondense volume. Conclusions: Greenness exposures were not associated with mammographic density. Impact: Prior observations of a protective association between greenness and breast cancer may not be driven by differences in breast tissue composition, as measured by mammographic density, but rather other mechanisms.

County-level demographic, social, economic, and lifestyle correlates of COVID-19 infection and death trajectories during the first wave of the pandemic in the United States.

BACKGROUND: The US COVID-19 epidemic impacted counties differently across space and time, though large-scale transmission dynamics are unclear. The study's objective was to group counties with similar trajectories of COVID-19 cases and deaths and identify county-level correlates of the distinct trajectory groups. METHODS: Daily COVID-19 cases and deaths were obtained from 3141 US counties from January through June 2020. Clusters of epidemic curve trajectories of COVID-19 cases and deaths per 100,000 people were identified with Proc Traj. We utilized polytomous logistic regression to estimate Odds Ratios for trajectory group membership in relation to county-level demographics, socioeconomic factors, school enrollment, employment and lifestyle data. RESULTS: Six COVID-19 case trajectory groups and five death trajectory groups were identified. Younger counties, counties with a greater proportion of females, Black and Hispanic populations, and greater employment in private sectors had higher odds of being in worse case and death trajectories. Percentage of counties enrolled in grades 1-8 was associated with earlier-start case trajectories. Counties with more educated adult populations had lower odds of being in worse case trajectories but were generally not associated with worse death trajectories. Counties with higher poverty rates, higher uninsured, and more living in non-family households had lower odds of being in worse case and death trajectories. Counties with higher smoking rates had higher odds of being in worse death trajectory counties. DISCUSSION: In the absence of clear guidelines and personal protection, smoking, racial and ethnic groups, younger populations, social, and economic factors were correlated with worse COVID-19 epidemics that may reflect population transmission dynamics during January-June 2020. After vaccination of high-risk individuals, communities with higher proportions of youth, communities of color, smokers, and workers in healthcare, service and goods industries can reduce viral spread by targeting vaccination programs to these populations and increasing access and education on non-pharmaceutical interventions.