Jeff Jones

Background/Objectives: Digital platforms are increasingly used to access health information and healthcare services, yet engagement with online health services varies across individuals. This study examined factors associated with three forms of digital health engagement among U.S. adults: using the Internet to message healthcare providers or their offices, view medical test results, and make medical appointments. Methods: Cross-sectional data from the 2022 Health Information National Trends Survey (HINTS 6) were analyzed. Survey-weighted multivariable logistic regression models were used to examine associations between the three digital health engagement outcomes and Internet use for health information, social media use for health decision-making, confidence in finding helpful health resources online, trust in the healthcare system, and delayed needed care, while adjusting for selected demographic and health characteristics. Results: Across all three models, respondents who used the Internet to look for health information had substantially higher odds of messaging healthcare providers (AOR = 9.88, 95% CI [7.59, 12.87]), viewing test results (AOR = 14.46, 95% CI [10.80, 19.37]), and making medical appointments online (AOR = 7.38, 95% CI [5.16, 10.54]). Lower confidence in finding helpful health resources online was also associated with lower odds of selected forms of digital health engagement. Delayed needed care was associated with lower odds of viewing test results, while age and race/ethnicity were associated with selected forms of digital engagement. Conclusions: Internet health information seeking and confidence in finding helpful health resources online were consistently associated with engagement in online health services. These findings highlight the importance of prior online health experience and confidence in understanding patterns of digital healthcare engagement and may inform efforts to promote equitable access to and use of online healthcare services.

Background/Objectives: Chronic kidney disease (CKD) is a severe health problem with dire consequences for the quality of life of millions of individuals and their families around the globe. This quantitative study analyzes the factors associated with hemodialysis patients’ quality of life (QoL) in Lahore City, Pakistan. Methods: Primary data from a sample of 384 patients were collected through regular visits to the hospital. We employed proportional odds models (POMs) and structural equation models to identify factors associated with the QoL. Results: The results revealed significant associations between various factors and patients’ quality of life. While gender showed no association with quality of life, younger age, single marital status, higher education, higher family income, and employment status were associated with a better QoL. Clinical variables such as the absence of diabetes and hypertension and specific laboratory parameters were protective against deteriorating QoL. Physical symptoms like muscle soreness, cramps, and shortness of breath significantly impacted QoL. Social and environmental factors adversely affected patient well-being, including family distress and financial issues. Psychological variables such as anxiety, depression, and fear of death also influenced QoL. Conclusions: The findings underscore the importance of holistic, patient-centered care approaches in renal failure management, highlighting the need for tailored interventions to address the diverse needs of dialysis patients and enhance their QoL. Further longitudinal research is recommended to validate these findings and guide the development of targeted interventions for improving patient well-being in hemodialysis settings.

This paper examines the efficacy of telemedicine (TM) technology compared to traditional face-to-face (F2F) visits as an alternative healthcare delivery service for managing diabetes in populations residing in urban medically underserved areas (UMUPAs). Retrospective electronic patient health records (ePHR) with type 2 diabetes mellitus (T2DM) were examined from 1 January 2019 to 30 June 2021. Multiple linear regression models indicated that T2DM patients with uncontrolled diabetes utilizing TM were similar to traditional visits in lowering hemoglobin (HbA1c) levels. The healthcare service type significantly predicted HbA1c % values, as the regression coefficient for TM (vs. F2F) showed a significant negative association (B = −0.339, p < 0.001), suggesting that patients using TM were likely to have 0.34 lower HbA1c % values on average when compared with F2F visits. The regression coefficient for female (vs. male) gender showed a positive association (B = 0.190, p < 0.034), with HbA1c % levels showing that female patients had 0.19 higher HbA1c levels than males. Age (B = −0.026, p < 0.001) was a significant predictor of HbA1c % levels, with 0.026 lower HbA1c % levels for each year’s increase in age. Black adults (B = 0.888, p < 0.001), on average, were more likely to have 0.888 higher HbA1c % levels when compared with White adults.

This study quantifies the transmission potential of SARS-CoV-2 across public health districts in Georgia, USA, and tests if per capita cumulative case count varies across counties. To estimate the time-varying reproduction number, R_t of SARS-CoV-2 in Georgia and its 18 public health districts, we apply the R package ‘EpiEstim’ to the time series of historical daily incidence of confirmed cases, 2 March–15 December 2020. The epidemic curve is shifted backward by nine days to account for the incubation period and delay to testing. Linear regression is performed between log₁₀-transformed per capita cumulative case count and log₁₀-transformed population size. We observe R_t fluctuations as state and countywide policies are implemented. Policy changes are associated with increases or decreases at different time points. R_t increases, following the reopening of schools for in-person instruction in August. Evidence suggests that counties with lower population size had a higher per capita cumulative case count on June 15 (slope = −0.10, p = 0.04) and October 15 (slope = −0.05, p = 0.03), but not on August 15 (slope = −0.04, p = 0.09), nor December 15 (slope = −0.02, p = 0.41). We found extensive community transmission of SARS-CoV-2 across all 18 health districts in Georgia with median 7-day-sliding window R_t estimates between 1 and 1.4 after March 2020.

Background: This study examines whether having a required health inspector on a local board of health (LBOH) improves the board’s information on environmental health. Methods: Analysis uses the national random sample of 351 U.S. LBOHs in the 2011 Profiles collected by the National Association of Local Boards of Health (NALBOH) and examines whether having a required health inspector on a LBOH increases the likelihood it receives information on 10 environmental health topics. Results: LBOHs overall received little information on environmental health, and 48% reported wanting no or little additional information. Having a required health inspector on a LBOH did not increase the likelihood of a LBOH receiving information on 8 environmental health topics. On two additional topics, food safety and groundwater protection, LBOHs with a required health inspector are less likely to report receiving information. A required health inspector board member also did not significantly influence the openness of a LBOH to receiving more information on environmental health. Conclusions: While LBOHs are the predominant public health department governing agencies in the United States, this study points to a low level of training and knowledge about environmental health issues. Having a required health inspector board member also does not improve LBOHs’ reported likelihood of receiving information. Keywords: Local boards of health, sanitarians, environmental health, governance, health inspectors

Background: The continuous improvement function, 1 of the 6 public health governance functions, can be usefully applied in the context of local boards of health (LBoHs) operations to target self-improvements. Purpose: The purpose of this study was to determine the engagement level of LBoHs in continuous improvement efforts and to identify factors associated with this function. Methods: Negative binomial regression was performed to analyze data from the 2015 Local Board of Health National Profile. The LBoH taxonomy was used as the guiding model. The taxonomy includes 6 governance functions as structural domains and LBoHs' characteristics and strengths as the central or seventh domain. Results: For the 17 items that comprise the continuous improvement domain, the mean of the dichotomous responses was 4.97 (SD = 3.41). The negative binomial regression analysis showed that the overall summary scale for the other 5 governance domains and the LBoHs' other strengths domain had a significant positive association with the governance domain continuous improvement domain (incidence rate ratio [IRR] = 1.05, P < .001). The 5 individual scales for the governance domains also had significant positive associations with the continuous improvement domain, which included the governance functions of policy development (IRR = 1.13, P < .001), resource stewardship (IRR = 1.18, P < .001), legal authorization (IRR = 1.09, P < .001, partnership engagement (IRR = 1.12, P < .001), and oversight (IRR = 1.29, P < .001). The scale for other characteristics and strengths also showed positive association with continuous improvement (IRR = 1.14, P < .001). Conclusion: The findings of this study revealed that there was room for improvement in LBoHs' engagement in the continuous improvement governance function. The results also identified other governance functions and LBoHs' characteristics as factors associated with their continuous improvement.

Objective: U.S. pedestrian fatalities increased by 25% between 2010 and 2015. Risk factors include distractions, the built environment, urbanization, economic variables, and weather conditions. Of interest is the role of alcohol and drugs in premature death among pedestrians. This study sought to explore the prevalence of substance use screenings among pedestrian fatalities in the United States between 2014 and 2016. Methods: Data were collected from the Fatality Analysis Reporting System provided by the NHTSA. Pedestrian crash variables included demographics as well as information regarding alcohol or drug testing status. Frequency and cross-tabulation tables were constructed to assess the prevalence of screening by person, place, and time. Log-linear analyses were completed to explore age, race, and sex differences. A 3-year examination period was used to control for yearly fluctuations and to incorporate an increasing trend in cases. Results: Pedestrian fatalities accounted for 84% of all deaths among vulnerable road users during the examination period. Those most at risk were white males between the ages of 45 and 64. Over all states, 74.7% of fatalities were tested for alcohol and 67.1% were tested for drugs; further, 66.5% of cases were tested for both alcohol and drugs and 24.8% were tested for neither substance. Cases screened for both alcohol and drugs ranged from 2.9% in North Carolina to 95.7% in Nevada and those testing for neither substance ranged from a high of 68.9% in Indiana to a low of 1.1% in Maryland. Log-linear regression revealed significant differences in alcohol screening by age and race but not by sex. Differences in drug screening were not identified for any demographic variable. Fatalities tested for alcohol were significantly more likely to be tested for drugs; only 8.2% were screened solely for alcohol and 0.05% were screened for drugs alone. Conclusions: Preventive strategies become more important as pedestrian crashes and fatalities increase. Risk reduction in the form of policy change, alterations to the built environment, or interdisciplinary approaches to injury prevention is dependent upon best evidence supported in part by more deliberate and consistent screening.