Browsing by Author "Manning, Sydney E."
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Item A Non-Parametric Alternative to The Cochran-Armitage Trend Test in Genetic Case-Control Association Studies: The Two-sided Jonckheere's Test(2020) Zhou, Zhengyang; Ku, Hung-Chih; Xing, Chao; Manning, Sydney E.Purpose: In genetic association studies with case-control design, standard practice is to perform the Cochran-Armitage (CA) trend test under the assumption of additive genetic model. The CA trend test is a parametric statistical test, and under the null hypothesis of no association between the genetic variant and disease, the test statistic asymptotically follows a chi-square distribution with 1 degree-of-freedom. However, when the sample size and/or variant minor allele frequency are small, asymptotic properties may not hold, which can lead to reduced statistical power in detecting genetic associations. Methods: To improve statistical power in this case, we consider the two-sided Jonckheere's test, which is a rank-based nonparametric test. By not imposing assumptions on the distributions of the data, it is expected to have better statistical power than parametric tests for small sample sizes and/or rare variants. We conducted extensive simulations to compare the statistical power between the CA trend test and the two-sided Jonckheere's test under various scenarios. Results: We found for small sample size (e.g., n=200) and low minor allele frequency (e.g., p=0.05), the two-sided Jonckheere's test outpowered the CA trend test for all genetic models ranging from recessive to dominant. Conclusion: This finding provides an alternative to the CA trend test in genetic association studies under these circumstances. With higher statistical power from the two-sided Jonckheere's test, genetic epidemiologists will be able to detect more genetic associations for complex diseases, which may lead to better prevention and treatment strategies.Item A Non-Parametric Alternative to The Cochran-Armitage Trend Test in Genetic Case-Control Association Studies: The Two-sided Jonckheere's Test(2021) Manning, Sydney E.; Xing, Chao; Ku, Hung-Chih; Zhou, ZhengyangPurpose: In genetic association studies with case-control design, standard practice is to perform the Cochran-Armitage (CA) trend test under the assumption of additive genetic model. The CA trend test is a parametric statistical test, and under the null hypothesis of no association between the genetic variant and disease, the test statistic asymptotically follows a chi-square distribution with 1 degree-of-freedom. However, when the sample size and/or variant minor allele frequency are small, asymptotic properties may not hold, which can lead to reduced statistical power in detecting genetic associations. Methods: To improve statistical power in this case, we consider the two-sided Jonckheere's test, which is a rank-based nonparametric test. By not imposing assumptions on the distributions of the data, it is expected to have better statistical power than parametric tests for small sample sizes and/or rare variants. We conducted extensive simulations to compare the statistical power between the CA trend test and the two-sided Jonckheere's test under various scenarios. Results: We found for small sample size (e.g., n=200) and low minor allele frequency (e.g., p=0.05), the two-sided Jonckheere's test outpowered the CA trend test for all genetic models ranging from recessive to dominant. Conclusion: This finding provides an alternative to the CA trend test in genetic association studies under these circumstances. With higher statistical power from the two-sided Jonckheere's test, genetic epidemiologists will be able to detect more genetic associations for complex diseases, which may lead to better prevention and treatment strategies.Item A nonparametric alternative to the Cochran-Armitage trend test in genetic case-control association studies: The Jonckheere-Terpstra trend test(PLOS, 2023-02-03) Manning, Sydney E.; Ku, Hung-Chih; Dluzen, Douglas F.; Xing, Chao; Zhou, ZhengyangIdentifications of novel genetic signals conferring susceptibility to human complex diseases is pivotal to the disease diagnosis, prevention, and treatment. Genetic association study is a powerful tool to discover candidate genetic signals that contribute to diseases, through statistical tests for correlation between the disease status and genetic variations in study samples. In such studies with a case-control design, a standard practice is to perform the Cochran-Armitage (CA) trend test under an additive genetic model, which suffers from power loss when the model assumption is wrong. The Jonckheere-Terpstra (JT) trend test is an alternative method to evaluate association in a nonparametric way. This study compares the power of the JT trend test and the CA trend test in various scenarios, including different sample sizes (200-2000), minor allele frequencies (0.05-0.4), and underlying modes of inheritance (dominant genetic model to recessive genetic model). By simulation and real data analysis, it is shown that in general the JT trend test has higher, similar, and lower power than the CA trend test when the underlying mode of inheritance is dominant, additive, and recessive, respectively; when the sample size is small and the minor allele frequency is low, the JT trend test outperforms the CA trend test across the spectrum of genetic models. In sum, the JT trend test is a valuable alternative to the CA trend test under certain circumstances with higher statistical power, which could lead to better detection of genetic signals to human diseases and finer dissection of their genetic architecture.Item 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, UshaOBJECTIVE: 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.Item Evaluating the Relationship between Race and Amblyogenic Risk Factors in Preschool Children in Fort Worth, Texas(2021) Karsaliya, Gopal; Omar, Salma; Manning, Sydney E.; Luna-Smith, Annabel; Aryal, Subhash; Mozdbar, SimaBackground Amblyopia (lazy eye) is the most common cause of vision loss in children. The prevalence is between 2-5% in the United States. Amblyogenic risk factors include early visual deprivation, strabismus, anisometropia, and media opacities such as a cataract. If treatment for amblyopia is not initiated before the age of 7, the likelihood of successful correction begins to drastically decline with age. Previous studies have found correlations between race and various vision abnormalities. This study aims to assess the incidence of myopia, hyperopia, and astigmatism among pre-Kindergarten children of different racial groups in Fort Worth, TX, as well as evaluate any racial differences in the presence of amblyogenic risk factors. Methods Using the PlusoptiX refractometers at 37 local elementary schools, researchers collected refractive error data of N=2,258 children under the age of 6, allowing for the detection of hyperopia, myopia, astigmatism, and anisometropia. The children's age, race, and sex were also recorded. A chi-square test was done to compare proportions of male/female participants, and odds ratios were calculated for each amblyogenic risk factor between racial/ethnic groups. Results Those with at least one amblyogenic risk factor accounted for 27.82% of the sample. There was a significant difference in astigmatism as an amblyogenic risk factor between Black and Hispanic groups (OR=0.6039, 95%CI 0.46-0.79) and between White and Hispanic groups (OR=0.2387, 95%CI 0.17-0.34). Conclusion The results of this study suggest Hispanic children were at increased risk of developing amblyopia compared to Black and White children in Fort Worth.Item Interactive Association of Chronic Illness and Food Insecurity with Emergency Room Visits among School-aged Children in the United States(2022) Ghani, Farheen; Manning, Sydney E.; Sambamoorthi, UshaObjective: This study examined the prevalence of food insecurity among children aged 6-17 years and the interactive association of chronic conditions and food insecurity with healthcare utilization, specifically ER visits. Methods: Data on children aged 6-17 (N = 5,518, representing 50,479,419 children) were obtained from the 2017 Medical Expenditure Panel Survey (MEPS). We measured food insecurity (Yes/No) using responses to a 10-item food security scale developed and validated by the USDA, adapted here for the MEPS 30-day window. Healthcare utilization consisted of cumulative ER visits in 12 months. Chi-square tests and adjusted Poisson regression were used to determine interactive associations of chronic conditions and food insecurity on ER visits. All analyses involved complex survey procedures. Results: 20% of school-aged children had food insecurity; 21% had a chronic condition. After adjusting for age, sex, race, insurance coverage, poverty status, physical and mental health status, obesity, and region, we observed that children with chronic conditions and food insecurity had a higher number of ER visits (Incident rate ratio = 2.79, 95% CI = 1.892, 4.120), compared to children without food insecurity and chronic conditions. Conclusions: 1 in 16 school-aged children had both a chronic condition and experienced food insecurity in the last 12 months. Food insecurity in children with chronic conditions was associated with more ER visits. Our findings suggest that policies and programs that provide linkages to community resources can help reduce food insecurity among children in the US and reduce healthcare utilization.Item Leading Predictors and Their Associations with Combination Pain Therapy in Older Adults with Cancer: Application of Machine Learning Approaches(2022) Manning, Sydney E.; Madhavan, Suresh; Rasu, Rafia; Sambamoorthi, UshaOBJECTIVES: Opioid combination therapy is frequently prescribed in older adult cancer survivors despite negative outcomes. The objective of this study was to identify the leading predictors and their associations with opioid combination therapy prescribing after cancer diagnosis using interpretable machine learning approaches. METHODS: This is a retrospective longitudinal cohort of older (> 66 years old) cancer survivors (N = 2,673) diagnosed with primary and incident cancer in 2014 using the Surveillance, Epidemiology, and End Results (SEER) cancer registry linked with Medicare claims. Recursive feature elimination with random forest was used to extract the optimal number of predictors out of 119 likely ones for predictive modeling. eXtreme Gradient Boosting (XGBoost), SHapley Additive exPlanations (SHAP), and global feature importance were used to identify the leading predictors and their associations with opioid combination therapy. SAS 9.4 was used for data management and Python 3.9.7 was used for machine learning model calibration and tuning. RESULTS: Specificity (0.858), sensitivity (0.843), and area under the curve (AUC, 0.85) of our predictive model were high. Thirty-four features were included in the final predictive model. Baseline use of NSAIDs, opioids, benzodiazepines, and gabapentinoids, and chemotherapy, surgery, Complex relationships were observed between zip code percent of Hispanic and Native American residents living below poverty, care fragmentation (FCI), age at diagnosis, and opioid combination therapy. CONCLUSIONS: 1 in 3 older cancer survivors were prescribed opioid combination therapy. Patient-level baseline medication use, biological factors, cancer treatment, and zip code level social determinants were leading predictors of opioid combination therapy. Although observed relationships were complex, further analysis of predictors may help compute individual risk of patients on combination therapy, which in turn may help clinicians and policy makers utilize targeted interventions at the outset and prevent long-term effects of combination pain therapy such as prolonged and inappropriate use.Item Multimorbidity and Whole Health among Adults in the United States: Evidence from the NHIS and BRFSS(2022) Warner, Mayela; Neba, Rolake A.; Manning, Sydney E.; Wiener, Constance; Sambamoorthi, UshaPUPROSE Whole health is a patient-centered approach that promotes self-management of what matters to the patient. Whole health focuses on mind-body, recharge(sleep), healthy diet, emotional health, and movement, all of which are critical for those with multimorbidity. We examined the association of multimorbidity with good whole health among adults in the United States. METHODS We conducted a cross-sectional design. As no one dataset provided information on all components of whole health, we analyzed mind-body therapies, recharge, emotional health, and movement from the 2017 National Health Interview Survey (NHIS), and healthy diet from the 2017 Behavioral Risk Factor Surveillance System (BRFSS). Multimorbidity was defined as the co-occurrence of two or more chronic conditions. Recharge was measured by adequate duration of sleep and the Kessler Psychological Distress Scale (K6) was used to measure emotional health. All unadjusted and adjusted analyses were conducted using the SAS survey procedures. The samples from NHIS (N=25,134) and BRFSS (N=347,029) represented 213 million and 183 million adults, respectively. RESULTS Prevalence of the whole health components varied from 24.4% (mind-body therapies use), 55.7% (healthy-diet), 57.1% (movement), 63.9% (adequate sleep), and good emotional health (78.4%). Based on NHIS, only 3.4% reported good health in all four components. A lower percentage of adults with multimorbidity used mind-body therapies (22.9% vs 25.2%), had adequate sleep (58.2% vs 67.1%), good emotional health (71.8% vs 82.1%), adequate movement (16.2% vs 28.2%), and healthy diet (54.5% vs 56.5%) compared to those without multimorbidity (p < .001). Adjusted analyses revealed that those with multimorbidity were less likely to engage in whole health practices compared to those without multimorbidity. CONCLUSIONS Seven in 10 adults had poor health in two or more components of whole health. Adults with multimorbidity were found to have poorer health in all components of whole health. Nationally representative data surveys should strive to collect information on all components of whole health with standardized measures.Item 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, UshaBACKGROUND: 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.