Publications -- Usha Sambamoorthi

Permanent URI for this collectionhttps://hdl.handle.net/20.500.12503/31897

This collection is limited to articles published under the terms of a creative commons license or other open access publishing agreement since 2016. It is not intended as a complete list of the author's works.

Browse

Now showing 1 - 14 of 14

Prescription Non-Steroidal Anti-Inflammatory Drugs (NSAIDs) and Incidence of Depression Among Older Cancer Survivors With Osteoarthritis: A Machine Learning Analysis
(Sage Publications, 2023-04-27) Shaikh, Nazneen F.; Shen, Chan; LeMasters, Traci; Dwibedi, Nilanjana; Ladani, Amit; Sambamoorthi, Usha
OBJECTIVES: This study examined prescription NSAIDs as one of the leading predictors of incident depression and assessed the direction of the association among older cancer survivors with osteoarthritis. METHODS: This study used a retrospective cohort (N = 14, 992) of older adults with incident cancer (breast, prostate, colorectal cancers, or non-Hodgkin's lymphoma) and osteoarthritis. We used the longitudinal data from the linked Surveillance, Epidemiology, and End Results -Medicare data for the study period from 2006 through 2016, with a 12-month baseline and 12-month follow-up period. Cumulative NSAIDs days was assessed during the baseline period and incident depression was assessed during the follow-up period. An eXtreme Gradient Boosting (XGBoost) model was built with 10-fold repeated stratified cross-validation and hyperparameter tuning using the training dataset. The final model selected from the training data demonstrated high performance (Accuracy: 0.82, Recall: 0.75, Precision: 0.75) when applied to the test data. SHapley Additive exPlanations (SHAP) was used to interpret the output from the XGBoost model. RESULTS: Over 50% of the study cohort had at least one prescption of NSAIDs. Nearly 13% of the cohort were diagnosed with incident depression, with the rates ranging between 7.4% for prostate cancer and 17.0% for colorectal cancer. The highest incident depression rate of 25% was observed at 90 and 120 cumulative NSAIDs days thresholds. Cumulative NSAIDs days was the sixth leading predictor of incident depression among older adults with OA and cancer. Age, education, care fragmentation, polypharmacy, and zip code level poverty were the top 5 predictors of incident depression. CONCLUSION: Overall, 1 in 8 older adults with cancer and OA were diagnosed with incident depression. Cumulative NSAIDs days was the sixth leading predictor with an overall positive association with incident depression. However, the association was complex and varied by the cumulative NSAIDs days.
Multimorbidity and chronic pain management with opioids and other therapies among adults in the United States: A cross-sectional study
(Sage Publications, 2024-03-08) Neba, Rolake A.; Wang, Hao; Kolala, Misozi; Sambamoorthi, Usha
BACKGROUND: Multimorbidity, defined as the concurrent presence of >/= 2 chronic conditions, and chronic pain (i.e., pain lasting >/=3 months) often co-exist. Multimodal pain management that includes non-pharmacologic treatment and non-opioid therapy is recommended to prevent serious risks associated with opioids. PURPOSE: Estimate the prevalence of types of pain treatment and analyze their associations with multimorbidity using a nationally representative survey in the United States (US). METHODS: Data was collected from the 2020 National Health Interview Survey among adults with chronic pain and chronic conditions (N= 12,028). Chronic pain management was grouped into four categories: opioid therapy; non-opioid multimodal pain treatment; pain treatment with monotherapy; and no pain treatment. Chi-square tests and multivariable multinomial logistic regressions were used to analyze the association of multimorbidity with types of pain treatment after controlling for age, sex, social determinants of health (SDoH), and lifestyle characteristics. RESULTS: Among NHIS respondents, 68% had multimorbidity. In adjusted multinomial logistic regressions with "pain management with monotherapy" as the reference group, those with multimorbidity were more likely to utilize opioids (AOR=1.63, 95% CI=1.23, 2.17). Those with severe pain were also more likely to use opioid therapy (AOR=19.36, 95% CI=13.35, 28.06) than those with little pain. Those with low income and education were less likely to have multimodal pain management without opioids. CONCLUSION: Seven in 10 adults had multimorbidity. Those with multimorbidity reported severe pain and relied on opioids for pain control. Regardless of multimorbidity status, SDoH was associated with types of chronic pain management.
Community perspectives on AI/ML and health equity: AIM-AHEAD nationwide stakeholder listening sessions
(PLOS, 2023-06-30) Vishwanatha, Jamboor K.; Christian, Allison; Sambamoorthi, Usha; Thompson, Erika L.; Stinson, Katie; Syed, Toufeeq A.
Artificial intelligence and machine learning (AI/ML) tools have the potential to improve health equity. However, many historically underrepresented communities have not been engaged in AI/ML training, research, and infrastructure development. Therefore, AIM-AHEAD (Artificial Intelligence/Machine Learning Consortium to Advance Health Equity and Researcher Diversity) seeks to increase participation and engagement of researchers and communities through mutually beneficial partnerships. The purpose of this paper is to summarize feedback from listening sessions conducted by the AIM-AHEAD Coordinating Center in February 2022, titled the "AIM-AHEAD Community Building Convention (ACBC)." A total of six listening sessions were held over three days. A total of 977 people registered with AIM-AHEAD to attend ACBC and 557 individuals attended the listening sessions across stakeholder groups. Facilitators led the conversation based on a series of guiding questions, and responses were captured through voice and chat via the Slido platform. A professional third-party provider transcribed the audio. Qualitative analysis included data from transcripts and chat logs. Thematic analysis was then used to identify common and unique themes across all transcripts. Six main themes arose from the sessions. Attendees felt that storytelling would be a powerful tool in communicating the impact of AI/ML in promoting health equity, trust building is vital and can be fostered through existing trusted relationships, and diverse communities should be involved every step of the way. Attendees shared a wealth of information that will guide AIM-AHEAD's future activities. The sessions highlighted the need for researchers to translate AI/ML concepts into vignettes that are digestible to the larger public, the importance of diversity, and how open-science platforms can be used to encourage multi-disciplinary collaboration. While the sessions confirmed some of the existing barriers in applying AI/ML for health equity, they also offered new insights that were captured in the six themes.
The Association of Multimorbidity With Whole Health Activities Among Adults in the United States: Evidence From the NHIS and BRFSS
(Academic Consortium for Integrative Medicine & Health, 2023-05-08) Neba, Rolake A.; Warner, Mayela; Manning, Sydney E.; Wiener, R. Constance; Sambamoorthi, Usha
BACKGROUND: Whole health is a holistic approach encompassing integrative medicine, emotional, and spiritual health and is critical to improving health outcomes among individuals with multimorbidity. OBJECTIVE: To examine the prevalence of Whole Health activities and the association of multimorbidity and Whole Health activities using nationally representative datasets. METHODS: As no single dataset has information on Whole Health self-care activities, data from the 2017 National Health Interview Survey (n = 25 134) was used to measure participants' mind-body therapy usage, sleep, mental health, and physical activity. We used the 2017 Behavioral Risk Factor Surveillance System (n = 347 029) to assess regular vegetable and/or fruit consumption. RESULTS: A significantly lower percentage of adults with multimorbidity had adequate sleep (58.2%vs.67.1%), no psychological distress (71.8%vs.82.1%), adequate physical activity (48.2%vs.62.1%), and regular vegetable and/or fruit consumption (54.2%vs.56.6%) compared to those without multimorbidity. Although lower percentages of adults with multimorbidity utilized mind-body therapies (22.9%vs.25.2%), the association was reversed when adjusted for socioeconomic factors. In the fully adjusted models, adults with multimorbidity were more likely to use mind-body therapies (AOR = 1.19, 95%CI = 1.09, 1.31). Furthermore, when adjusting for other independent variables, the associations of multimorbidity with sleep, psychological distress, and diet were exacerbated, and the association of multimorbidity with physical activity was attenuated. CONCLUSION: Adults with multimorbidity were less likely to engage in most of the Whole Health activities except mind-body therapies compared to the no multimorbidity group. Findings suggest that adjustment for other factors such as age and socioeconomic status changed the magnitude and direction of the association of multimorbidity with Whole Health activities.
Association of multimorbidity with the use of health information technology
(Sage Publications, 2023-05-01) Manning, Sydney E.; Wang, Hao; Dwibedi, Nilanjana; Shen, Chan; Wiener, R. Constance; Findley, Patricia A.; Mitra, Sophie; Sambamoorthi, Usha
OBJECTIVE: To examine the association of multimorbidity with health information technology use among adults in the USA. METHODS: We used cross-sectional study design and data from the Health Information National Trends Survey 5 Cycle 4. Health information technology use was measured with ten variables comprising access, recent use, and healthcare management. Unadjusted and adjusted logistic and multinomial logistic regressions were used to model the associations of multimorbidity with health information technology use. RESULTS: Among adults with multimorbidity, health information technology use for specific purposes ranged from 37.8% for helping make medical decisions to 51.7% for communicating with healthcare providers. In multivariable regressions, individuals with multimorbidity were more likely to report general use of health information technology (adjusted odds ratios = 1.48, 95% confidence intervals = 1.01-2.15) and more likely to use health information technology to check test results (adjusted odds ratios = 1.85, 95% confidence intervals = 1.33-2.58) compared to adults with only one chronic condition, however, there were no significant differences in other forms of health information technology use. We also observed interactive associations of multimorbidity and age on various components of health information technology use. Compared to younger adults with multimorbidity, older adults (>/= 65 years of age) with multimorbidity were less likely to use almost all aspects of health information technology. CONCLUSION: Health information technology use disparities by age and multimorbidity were observed. Education and interventions are needed to promote health information technology use among older adults in general and specifically among older adults with multimorbidity.
Increase in body mass index during the COVID-19 pandemic among people who smoke: An analysis of multi-site electronic health records
(PLOS, 2023-04-12) Wiener, R. Constance; Waters, Christopher; Morgan, Emily; Findley, Patricia A.; Shen, Chan; Wang, Hao; Sambamoorthi, Usha
The effects of the COVID-19 period among people who smoke (compared by sex) are largely unknown. The purpose of this study was to compare body mass index (BMI) increase among men and women who smoked during the pandemic. We used a retrospective longitudinal, observational study design of secondary data. We used electronic health records from TriNetX network (n = 486,072) from April 13, 2020-May 5, 2022 among adults aged 18-64 who smoked and had a normal BMI prior to the pandemic. The main measure was a change of BMI from < 25 to >/=25. Risk ratio was determined between men and women with propensity score matching. Overall, 15.8% increased BMI to >/=25; 44,540 (18.3%) were women and 32,341 (13.3%) were men (Risk Ratio = 1.38, 95% CI: 1.36, 1.40; p < .0001). Adults with diabetes, hypertension, asthma, COPD or emphysema or who were women, were more likely to develop BMI>/=25 during the pandemic. Women who smoked were more likely to have an increase in BMI than men who smoked during the COVID-19 period.
A Multi-Level Analysis of Individual and Neighborhood Factors Associated with Patient Portal Use among Adult Emergency Department Patients with Multimorbidity
(MDPI, 2023-01-22) Wang, Hao; Shen, Chan; Barbaro, Michael; Ho, Amy F.; Pathak, Mona; Dunn, Cita; Sambamoorthi, Usha
BACKGROUND: Patient portals tethered to electronic health records (EHR) have become vital to patient engagement and better disease management, specifically among adults with multimorbidity. We determined individual and neighborhood factors associated with patient portal use (MyChart) among adult patients with multimorbidity seen in an Emergency Department (ED). METHODS: This study adopted a cross-sectional study design and used a linked database of EHR from a single ED site to patients' neighborhood characteristics (i.e., zip code level) from the American Community Survey. The study population included all adults (age > 18 years), with at least one visit to an ED and multimorbidity between 1 January 2019 to 31 December 2020 (N = 40,544). Patient and neighborhood characteristics were compared among patients with and without MyChart use. Random-intercept multi-level logistic regressions were used to analyze the associations of patient and neighborhood factors with MyChart use. RESULTS: Only 19% (N = 7757) of adults with multimorbidity used the patient portal. In the fully adjusted multi-level model, at the patient level, having a primary care physician (AOR = 5.55, 95% CI 5.07-6.07, p < 0.001) and health insurance coverage (AOR = 2.41, 95% CI 2.23-2.61, p < 0.001) were associated with MyChart use. At the neighborhood level, 4.73% of the variation in MyChart use was due to differences in neighborhood factors. However, significant heterogeneity existed in patient portal use when neighborhood characteristics were included in the model. CONCLUSIONS: Among ED patients with multimorbidity, one in five adults used patient portals. Patient-level factors, such as having primary care physicians and insurance, may promote patient portal use.
Factors associated with COVID-19-related mental health among Asian Indians in the United States
(Elsevier B.V., 2023-01-11) Ikram, Mohammad; Shaikh, Nazneen F.; Siddiqui, Zasim A.; Dwibedi, Nilanjana; Misra, Ranjita; Vishwanatha, Jamboor K.; Sambamoorthi, Usha
BACKGROUND: In the United States, the COVID-19 pandemic has caused increased mental health symptoms and mental illness. Specific subgroups such as Asian Indians in the US have also been subject to additional stressors due to unprecedented loss of lives in their home country and increased Asian hate due to the misperception that Asians are to be blamed for the spread of the SARS-CoV-2. OBJECTIVE: We examined the various factors including discrimination associated with COVID-19-related mental health symptoms among Asian Indians. METHODS: We administered an online survey between May 2021 and July 2021 using convenient and snowball sampling methods to recruit Asian Indian adults (age > 18 years, N = 289). The survey included questions on mental health and the experience with unfair treatment in day-to-day life. Descriptive analysis and logistic regressions were performed. RESULTS: Overall, 46.0% reported feeling down, depressed, or lonely and feeling nervous, tense, or worried due to the COVID-19 pandemic; 90.0% had received at least one dose of vaccination and 74.7% reported some form of discrimination. In the fully-adjusted logistic regression, age (AOR = 0.95; 95%CI- 0.92, 0.97;p < 0.01) and general health (AOR=0.84; 95%CI- 0.73, 0.97; p < 0.015) were negatively associated with mental health symptoms. Participants who experienced discrimination were more likely (AOR=1.26; 95%CI- 1.08, 1.46; p < 0.01) to report mental health symptoms. CONCLUSION: In this highly vaccinated group of Asian Indians discriminatory behaviors were associated with mental health symptoms suggesting the need for novel institutional level policy responses to reduce anti-Asian racism.
Leading Predictors of COVID-19-Related Poor Mental Health in Adult Asian Indians: An Application of Extreme Gradient Boosting and Shapley Additive Explanations
(MDPI, 2023-01-09) Ikram, Mohammad; Shaikh, Nazneen F.; Vishwanatha, Jamboor K.; Sambamoorthi, Usha
During the COVID-19 pandemic, an increase in poor mental health among Asian Indians was observed in the United States. However, the leading predictors of poor mental health during the COVID-19 pandemic in Asian Indians remained unknown. A cross-sectional online survey was administered to self-identified Asian Indians aged 18 and older (N = 289). Survey collected information on demographic and socio-economic characteristics and the COVID-19 burden. Two novel machine learning techniques-eXtreme Gradient Boosting and Shapley Additive exPlanations (SHAP) were used to identify the leading predictors and explain their associations with poor mental health. A majority of the study participants were female (65.1%), below 50 years of age (73.3%), and had income >/= $75,000 (81.0%). The six leading predictors of poor mental health among Asian Indians were sleep disturbance, age, general health, income, wearing a mask, and self-reported discrimination. SHAP plots indicated that higher age, wearing a mask, and maintaining social distancing all the time were negatively associated with poor mental health while having sleep disturbance and imputed income levels were positively associated with poor mental health. The model performance metrics indicated high accuracy (0.77), precision (0.78), F1 score (0.77), recall (0.77), and AUROC (0.87). Nearly one in two adults reported poor mental health, and one in five reported sleep disturbance. Findings from our study suggest a paradoxical relationship between income and poor mental health; further studies are needed to confirm our study findings. Sleep disturbance and perceived discrimination can be targeted through tailored intervention to reduce the risk of poor mental health in Asian Indians.
The Association of Mobile Health Applications with Self-Management Behaviors among Adults with Chronic Conditions in the United States
(MDPI, 2021-09-30) Wang, Hao; Ho, Amy F.; Wiener, R. Constance; Sambamoorthi, Usha
BACKGROUND: Mobile applications related to health and wellness (mHealth apps) are widely used to self-manage chronic conditions. However, research on whether mHealth apps facilitate self-management behaviors of individuals with chronic conditions is sparse. We aimed to evaluate the association of mHealth apps with different types of self-management behaviors among patients with chronic diseases in the United States. METHODS: This is a cross-sectional observational study. We used data from adult participants (unweighted n = 2340) of the Health Information National Trends Survey in 2018 and 2019. We identified three self-management behaviors: (1) resource utilization using electronic personal health records; (2) treatment discussions with healthcare providers; and (3) making healthcare decisions. We analyzed the association of mHealth apps to self-management behaviors with multivariable logistic and ordinal regressions. RESULTS: Overall, 59.8% of adults (unweighted number = 1327) used mHealth apps. Adults using mHealth apps were more likely to use personal health records (AOR = 3.11, 95% CI 2.26-4.28), contact healthcare providers using technology (AOR = 2.70, 95% CI 1.93-3.78), and make decisions on chronic disease management (AOR = 2.59, 95% CI 1.93-3.49). The mHealth apps were associated with higher levels of self-management involvement (AOR = 3.53, 95% CI 2.63-4.72). CONCLUSION: Among individuals with chronic conditions, having mHealth apps was associated with positive self-management behaviors.
Coronavirus disease 2019 pandemic associated with anxiety and depression among Non-Hispanic whites with chronic conditions in the US
(Elsevier B.V., 2022-02-22) Wang, Hao; Paul, Jenny; Ye, Ivana; Blalock, Jake; Wiener, R. Constance; Ho, Amy F.; Alanis, Naomi; Sambamoorthi, Usha
OBJECTIVES: During the coronavirus 2019 (COVID-19) pandemic, increased anxiety and depression were reported, with mixed findings among individuals of different races/ethnicities. This study examines whether anxiety and depression increased during the COVID-19 pandemic compared to the pre-COVD-19 period among different racial/ethnic groups in the US. METHODS: The Health Information National Trend Surveys 5 (HINTS 5) Cycle 4 data was analyzed. We used the time when the survey was administered as the pre-COVID-19 period (before March 11, 2020, weighted N = 77,501,549) and during the COVID-19 period (on and after March 11, 2020, weighted N = 37,222,019). The Patient Health Questionnaire (PHQ) was used to measure anxiety/depression and further compared before and during COVID-19. Separate multivariable logistic regression analyses were used to determine the association of the COVID-19 pandemic with anxiety/depression after adjusting for age, sex, insurance, income, and education. RESULT: A higher percentage of Non-Hispanic whites (NHW) with chronic conditions reported anxiety (24.3% vs. 11.5%, p = 0.0021) and depression (20.7% vs. 9.3%, p = 0.0034) during COVID-19 than pre-COVID-19. The adjusted odds ratio (AOR) of anxiety and depression for NHWs with chronic conditions during the COVID-19 pandemic was 2.02 (95% confidence interval of 1.10-3.73, p = 0.025) and 2.33 (1.17-4.65, p = 0.018) compared to NHWs who participated in the survey before the COVID-19. LIMITATIONS: Limited to the NHW US population. PHQ can only be used as the initial screening tool. CONCLUSION: The COVID-19 pandemic was associated with an increased prevalence of anxiety and depression among NHW adults with chronic conditions, but not among people of color.
The association of COVID-19 vaccine availability with mental health among adults in the United States
(Frontiers Media S.A., 2022-08-09) Shen, Chen; Rashiwala, Lucy; Wiener, R. Constance; Findley, Patricia A.; Wang, Hao; Sambamoorthi, Usha
Objective: To assess whether COVID-19 vaccine approval and availability was associated with reduction in the prevalence of depression and anxiety among adults in the United States. Methods: We adopted cross sectional and quasi-experimental design with mental health measurements before vaccine availability (June 2020, N = 68,009) and after vaccine availability (March 2021, N = 63,932) using data from Census Pulse Survey. Depression and anxiety were derived from PHQ-2 and GAD-2 questionnaires. We compared rates of depression and anxiety between June 2020 and March 2021. Unadjusted and adjusted analysis with replicate weights were conducted. Results: Depression prevalence was 25.0% in June 2020 and 24.6% in March 2021; anxiety prevalence was 31.7% in June 2020 and 30.0% in March 2021 in the sample. In adjusted analysis, there were no significant differences in likelihood of depression and anxiety between June 2020 and March 2021. Conclusion: Depression and anxiety were not significantly different between June 2020 and March 2021, which suggests that the pandemic effect continues to persist even with widespread availability of vaccines.
A Machine Learning Approach to Identify Predictors of Potentially Inappropriate Non-Steroidal Anti-Inflammatory Drugs (NSAIDs) Use in Older Adults with Osteoarthritis
(MDPI, 2020-12-28) Patel, Jayeshkumar; Ladani, Amit; Sambamoorthi, Nethra; LeMasters, Traci; Dwibedi, Nilanjana; Sambamoorthi, Usha
Evidence from some studies suggest that osteoarthritis (OA) patients are often prescribed non-steroidal anti-inflammatory drugs (NSAIDs) that are not in accordance with their cardiovascular (CV) or gastrointestinal (GI) risk profiles. However, no such study has been carried out in the United States. Therefore, we sought to examine the prevalence and predictors of potentially inappropriate NSAIDs use in older adults (age > 65) with OA using machine learning with real-world data from Optum De-identified Clinformatics((R)) Data Mart. We identified a retrospective cohort of eligible individuals using data from 2015 (baseline) and 2016 (follow-up). Potentially inappropriate NSAIDs use was identified using the type (COX-2 selective vs. non-selective) and length of NSAIDs use and an individual's CV and GI risk. Predictors of potentially inappropriate NSAIDs use were identified using eXtreme Gradient Boosting. Our study cohort comprised of 44,990 individuals (mean age 75.9 years). We found that 12.8% individuals had potentially inappropriate NSAIDs use, but the rate was disproportionately higher (44.5%) in individuals at low CV/high GI risk. Longer duration of NSAIDs use during baseline (AOR 1.02; 95% CI:1.02-1.02 for both non-selective and selective NSAIDs) was associated with a higher risk of potentially inappropriate NSAIDs use. Additionally, individuals with low CV/high GI (AOR 1.34; 95% CI:1.20-1.50) and high CV/low GI risk (AOR 1.61; 95% CI:1.34-1.93) were also more likely to have potentially inappropriate NSAIDs use. Heightened surveillance of older adults with OA requiring NSAIDs is warranted.
Psychological Distress Among Asian Indians and Non-Hispanic Whites in the United States
(Mary Ann Liebert, Inc., 2022-07-05) Siddiqui, Zasim A.; Sambamoorthi, Usha
Introduction: The prevalence of psychological distress (PD) among Asian Indians is unknown. This study estimated and compared moderate-serious PD in Asian Indians and non-Hispanic Whites (NHWs) in the United States. Methods: We used a cross-sectional design using the National Health Interview Survey (2012-2017). Adult (age >18 years) NHWs and Asian Indians (N=2,218) were included. PD was measured using the six-item Kessler (K6) scale. We used multivariable logistic regression to determine the association of Asian Indian ethnicity with PD. Results: In the analysis, 19.9% of NHWs and 11.0% of Asian Indians reported moderate-serious PD. Asian Indians were less likely to report PD in both unadjusted (unadjusted odds ratio=0.50; 95% confidence interval [CI]=0.42-0.58) and fully adjusted (adjusted odds ratio=0.7; 95% CI 0.59-0.82) models. Conclusions: Asian Indians had a lower prevalence of PD than NHWs, likely due to multiple protective factors such as high socioeconomic status and lower multimorbidity.

Browse

Recent Submissions