Social determinants of health in patients with arthritis: a cross-sectional analysis of the 2017 Behavioral Risk Factor Surveillance System

CONTEXT

Social determinants of health (SDOH) are economic, social, and political conditions that affect a person's overall health or the health of a group of people. Researchers have investigated the effects of SDOH on various diseases, such as asthma, obesity, and chronic stress, but few publications have been made regarding its effects on arthritis.

OBJECTIVES

Our primary objective was to analyze the implications of SDOH on disease severity relating to pain levels and limitations experienced among people with diagnosed arthritis.

METHODS

We performed a cross-sectional analysis of the 2017 Behavioral Risk Factor Surveillance System (BRFSS). We included individuals who reported having arthritis, were over the age of 45, and who also completed the SDOH module. Pain scores from the four-question Arthritis Burden Module were correlated to question responses pertaining to SDOH to determine their associations.

RESULTS

For the analysis, our sample size was 25,682, with response rates varying slightly among the SDOH questions. Individuals diagnosed with arthritis were more likely to report functional limitations if they experienced food insecurity (χ2=234.0, p<0.001), financial instability (χ2=149.7, p<0.001), or frequent stress (χ2=297.6, p<0.001). Further, we found that individuals with arthritis experiencing any domain of SDOH reported higher mean pain scores than those not experiencing that domain, with the highest pain score difference among those reporting frequent stress (Coefficient: 1.93, CI=1.74-2.13, t=19.43, p<0.001).

CONCLUSIONS

Our results show that SDOH profoundly impact pain levels and limitations experienced by patients with arthritis. Although work has already begun to help alleviate burdens associated with SDOH, more research and actions are required to create equitable health throughout the population.

Prevalence of depression among caregivers based on the condition and relationship of care recipient

BACKGROUND

Caregiver distress is the strain experienced by individuals providing care for people with chronic conditions which limit their self-sufficiency for tasks of daily living. Over 1 in 5 Americans are caregivers-a number expected to increase with an aging population.

METHODS

We performed a cross-sectional analysis using the 2021 Behavioral Risk Factor Surveillance System (BRFSS) conducted by the Centers for Disease Control and Prevention (CDC) to determine rates of depressive disorders among caregivers and associations between demographic and relational aspects of the care recipient.

RESULTS

The included sample size for analysis was 32,676, representing 17,274,935 US caregivers. We found that caregivers who were female, American Indian/Alaskan Native, race-not-listed, earning less than $15,000 a year, or did not complete high school, had higher rates of depression diagnosis. The rates of depression were higher among caregivers if the recipient had a mental or chronic respiratory condition, or if the recipient was their live-in partner. Rates of depression were lower for caregivers of their mother-in-law or spouse.

LIMITATIONS

Results were based on self-reported survey data, which are susceptible to social desirability bias. Diagnoses of depression may also be over or under reported across several demographic variables, which may confound results.

CONCLUSION

Our findings add to previous research showing that specific groups of caregivers are at higher risk for caregiver stress. Future qualitative research may elucidate underlying causes of depression among caregivers. Analysis into the risk factors for depression among caregivers is vital in providing effective therapeutic options for the caregiver.

Associations of clinical personnel characteristics and controlled substance prescribing practices

CONTEXT

Over 68,000 deaths were attributed to opioid-related overdose in 2020. Evaluative studies have shown that states that utilized Prescription Drug Monitoring Program (PDMP) systems have decreased opioid-related deaths. With the growing use of PDMPs and an ongoing opioid epidemic, determining the demographics of physicians at risk of overprescribing can elucidate prescribing practices and inform recommendations to change prescribing behaviors.

OBJECTIVES

This study aims to assess prescribing behaviors by physicians in 2021 based on four demographics utilizing the National Electronic Health Record System (NEHRS): physician's age, sex, specialty, and degree (MD or Doctor of Osteopathic Medicine [DO]).

METHODS

We performed a cross-sectional study of the 2021 NEHRS to determine the relationship between physician characteristics and PDMP use on opioid-prescribing behaviors. Differences between groups were measured via design-based chi-square tests. We constructed multivariable logistic regression models to assess the relationships, via adjusted odds ratios (AOR), between physician characteristics and alternate prescribing patterns.

RESULTS

Compared to female physicians, male physicians were more likely to alter their original prescription to reduce morphine milligram equivalents (MMWs) prescribed for a patient (AOR: 1.60; CI: 1.06-2.39; p=0.02), to change to a nonopioid/nonpharmacologic option (AOR: 1.91; 95 % CI: 1.28-2.86; p=0.002), to prescribe naloxone (AOR=2.06; p=0.039), or to refer for additional treatment (AOR=2.07; CI: 1.36-3.16; p<0.001). Compared to younger physicians, those over the age of 50 were less likely to change their prescription to a nonopioid/nonpharmacologic option (AOR=0.63; CI: 0.44-0.90; p=0.01) or prescribe naloxone (AOR=0.56, CI: 0.33-0.92; p=0.02).

CONCLUSIONS

Our results showed a statistically significant difference between specialty category and frequency of prescribing controlled substances. After checking the PDMP, male physicians were more likely to alter their original prescription to include harm-reduction strategies. Optimizing the use of PDMP systems may serve to improve prescribing among US physicians.

Assessing the United States' most frequently asked questions about osteopathic medicine, osteopathic education, and osteopathic manipulative treatment

CONTEXT

Osteopathic medicine in the United States continues to produce a substantial number of physicians and medical educators. However, recently popularized misconceptions about osteopathic medical practice, education, and manual therapy suggest an unsettling prevalence of inaccurate beliefs held by the public. The public often searches the internet to find out information about osteopathic medicine, but the content of questions and the transparency of the resulting information is unknown.

OBJECTIVES

We sought to explore frequently asked questions (FAQs) generated by Google to assess commonly searched questions about the osteopathic profession and to determine the level of information transparency associated with resulting sources.

METHODS

On June 16, 2021, we searched Google for three terms: "osteopathic medicine," "doctor of osteopathic medicine," and "DO," until a minimum of 100 FAQs and their answer links were extracted from each search. After excluding irrelevant FAQs, we used Rothwell's Classification of Questions to categorize the FAQs. We then used the Journal of the American Medical Association's Benchmark Criteria to assess information transparency for each corresponding answer source provided by Google. The answer sources were screened for the inappropriate use of "osteopathy" in place of "osteopathic medicine" and for "osteopath" in place of "DO," "Doctor of Osteopathic Medicine," or "Osteopathic Physician." We performed statistical tests to ascertain the differences in information transparency between osteopathic and nonosteopathic information sources.

RESULTS

Our Google search revealed 110 unique FAQs about osteopathic medicine. The majority of FAQs were classified as fact-based (82/110; 74.55%), nearly half of which (45.12%) were related to the medical practicing privileges of DOs. The FAQs were most commonly answered by academic institutions (44/110, 40.0%). Nearly half (49.09%) of the linked answer sources were deemed inadequate by JAMA benchmark criteria. Of the 110 linked answer sources, 19 (17.27%) misused either osteopathy, osteopath, or both to describe osteopathic physicians. Only 30 sources were linked to US-based osteopathic organizations. Osteopathic organizations were statistically less likely to meet high-transparency criteria than nonosteopathic organizations (p=0.002).

CONCLUSIONS

Our study shows that the US public may be unsure about the physician status of DOs, which may prevent securing the professional identity of osteopathic physicians in the eyes of the public. Osteopathic organizations should tailor awareness campaigns toward addressing the common misconceptions revealed by our study. Osteopathic organizations should use transparency criteria as a rubric when publishing information to enhance transparency.

Utilizing Zoom Breakout Rooms to Expose Preclerkship Medical Students to TeleMedicine Encounters

Emergency Remote Teaching (ERT) presented various challenges as the Oklahoma State University Center for Health Sciences (OSU-CHS) campus closed to students in response to COVID-19 mitigation efforts in late March 2020. While some classes transitioned easily to virtual platforms already in place, such as learning management systems and the lecture recording software, other classes that involved coordinated group activities did not have as many suitable alternatives. One College of Osteopathic Medicine (COM) class utilized the teleconferencing tool Zoom. Zoom's breakout rooms and waiting room features were used to facilitate a clinical interviewing skills lab and telemedicine-type encounter with standardized patients. We were able to successfully designate groups of approximately 10 students into three rooms, amongst which the standardized patients moved at set intervals. Faculty facilitators participated in each room to guide students, and one support staff member served as host to manage the technical aspects of the overall meeting. We found this approach to be a successful alternative to live group activities and a worthwhile opportunity to expose preclerkship students to telemedicine.

Dual-task gait speed assessments with an electronic walkway and a stopwatch in older adults. A reliability study

BACKGROUND/OBJECTIVES

Slow gait speed prospectively predicts elevated risk of adverse events such as falls, morbidity, and mortality. Additionally, gait speed under a cognitively demanding challenge (dual-task gait) predicts further cognitive decline and dementia incidence. This evidence has been mostly collected using electronic walkways; however, not all clinical set ups have an electronic walkway and comparability with simple manual dual-gait speed testing, like a stopwatch, has not yet been examined. Our main objective was to assess concurrent-validity and reliability of gait speed assessments during dual-tasking using a stopwatch and electronic walkway in older adults with mild and subjective cognitive impairment (MCI and SCI).

DESIGN

Cross-sectional, reliability study.

SETTING

Clinic based laboratory at an academic hospital in London, ON, Canada.

PARTICIPANTS

237 walk tests from 34 community-dwelling participants (mean age 71.84 SD 5.38; 21 female - 62%, 13 male - 38%) with SCI and MCI. were included from the Comprehensive Assessment of Neurodegeneration and Dementia (COMPASS-ND) study.

INTERVENTION

Each participant performed seven walk tests: three single gait walks at their normal pace, three dual-task walks (walking and counting backwards by one, by sevens, and naming animals), and one fast walk.

MEASUREMENTS

Gait speed (cm/s) for each walk was measured simultaneously with an electronic walkway (Zeno Mat®) and a handheld stopwatch (Ultrak chronometer®). Dual-task cost (DTC) was calculated for the three individual dual-task walks as [((single gait speed - dual-task gait speed) / single gait speed) ∗ 100]. Level of agreement between the two measurement methods was analyzed using Pearson correlations, paired t-tests, and Bland-Altman plots.

RESULTS

Gait speed was consistently lower when measured with the stopwatch than with the electronic walkway (mean speed difference: 10.6 cm/s ± 5.1, p < 0.001). Calculating DTC, however, yielded very similar results with both methods (mean DTC difference: 0.19 ± 1.18, p = 0.872). The higher the DTC, the closer the measurement between methods.

CONCLUSION

Assessing and calculating DTC with a stopwatch is simple, accessible and reliable. Its validity and reliability were high in this clinical sample of community older adults with SCI and MCI.

A randomised controlled trial and cost-consequence analysis of traditional and digital foot orthoses supply chains in a National Health Service setting: application to feet at risk of diabetic plantar ulceration

BACKGROUND

Diabetic foot ulceration is a considerable cost to the NHS and foot orthotic provision is a core strategy for the management of the people with diabetes and a moderate to high risk of foot ulceration. The traditional process to produce a custom-made foot orthotic device is to use manual casting of foot shape and physical moulding of orthoses materials. Parts of this process can be undertaken using digital tools rather than manual processes with potential advantages. The aim of this trial was to provide the first comparison of a traditional orthoses supply chain to a digital supply chain over a 6 month period. The trial used plantar pressure, health status, and health service time and cost data to compare the two supply chains.

METHODS

Fifty-seven participants with diabetes were randomly allocated to each supply chain. Plantar pressure data and health status (EQ5D, ICECAP) was assessed at point of supply and at six-months. The costs for orthoses and clinical services accessed by participants were assessed over the 6 months of the trial. Primary outcomes were: reduction in peak plantar pressure at the site of highest pressure, assessed for non-inferiority to current care. Secondary outcomes were: reduction in plantar pressure at foot regions identified as at risk (> 200 kPa), cost-consequence analysis (supply chain, clinician time, service use) and health status.

RESULTS

At point of supply pressure reduction for the digital supply chain was non-inferior to a predefined margin and superior (p < 0.1) to the traditional supply chain, but both supply chains were inferior to the margin after 6 months. Custom-made orthoses significantly reduced pressure for at risk regions compared to a flat control (traditional - 13.85%, digital - 20.52%). The digital supply chain was more expensive (+£13.17) and required more clinician time (+ 35 min). There were no significant differences in health status or service use between supply chains.

CONCLUSIONS

Custom made foot orthoses reduce pressure as expected. Given some assumptions about the cost models we used, the supply chain process adopted to produce the orthoses seems to have marginal impact on overall costs and health status.

TRIAL REGISTRATION

Retrospectively registered on ISRCTN registry (ISRCTN10978940, 04/11/2015).

Pseudoalignment for metagenomic read assignment

Motivation

Read assignment is an important first step in many metagenomic analysis workflows, providing the basis for identification and quantification of species. However ambiguity among the sequences of many strains makes it difficult to assign reads at the lowest level of taxonomy, and reads are typically assigned to taxonomic levels where they are unambiguous. We explore connections between metagenomic read assignment and the quantification of transcripts from RNA-Seq data in order to develop novel methods for rapid and accurate quantification of metagenomic strains.

Results

We find that the recent idea of pseudoalignment introduced in the RNA-Seq context is highly applicable in the metagenomics setting. When coupled with the Expectation-Maximization (EM) algorithm, reads can be assigned far more accurately and quickly than is currently possible with state of the art software, making it possible and practical for the first time to analyze abundances of individual genomes in metagenomics projects.

Availability and Implementation

Pipeline and analysis code can be downloaded from http://github.com/pachterlab/metakallisto.

Contact

lpachter@math.berkeley.edu.