ABSTRACT
The social determinants of health (SDoH) influence health outcomes based on conditions from birth, growth, living, and age factors. Diabetes is a chronic condition, impacted by race, education, and income, which may lead to serious health consequences. In Hawai'i, approximately 11.2% of adults have been diagnosed with diabetes. The objective of this secondary cross-sectional study is to assess the relationship between the prevalence of diabetes and the social determinants of health among Hawai'i adults who participated in the Behavioral Risk Factor Surveillance System between 2018-2020. The prevalence of diabetes among adults was 11.0% (CI: 10.4-11.5%). Filipino, Japanese and Native Hawaiian adults had the highest prevalence of diabetes at 14.4% (CI: 12.7-16.2%), 14.2% (CI: 12.7-15.7%), and 13.2% (CI: 12.0-14.4%), respectively. Poverty level and education were significantly associated with diabetes status. Within employment categories, the adjusted odds ratio (AOR) for retired and unable to work adults were large at AOR: 1.51 (CI: 1.26-1.81) and AOR: 2.91 (CI: 2.28-3.72), respectively. SDoH can impact the development and management of diabetes. Understanding the role SDoH plays on diabetes status is crucial for promoting health equity, building community capacity, and improving diabetes management.
Subject(s)
Diabetes Mellitus , Social Determinants of Health , Humans , Hawaii/epidemiology , Male , Social Determinants of Health/statistics & numerical data , Female , Cross-Sectional Studies , Adult , Middle Aged , Diabetes Mellitus/epidemiology , Aged , Prevalence , Behavioral Risk Factor Surveillance System , AdolescentABSTRACT
BACKGROUND: Postpartum depression (PPD) poses a significant maternal health challenge. The current approach to detecting PPD relies on in-person postpartum visits, which contributes to underdiagnosis. Furthermore, recognizing PPD symptoms can be challenging. Therefore, we explored the potential of using digital biomarkers from consumer wearables for PPD recognition. OBJECTIVE: The main goal of this study was to showcase the viability of using machine learning (ML) and digital biomarkers related to heart rate, physical activity, and energy expenditure derived from consumer-grade wearables for the recognition of PPD. METHODS: Using the All of Us Research Program Registered Tier v6 data set, we performed computational phenotyping of women with and without PPD following childbirth. Intraindividual ML models were developed using digital biomarkers from Fitbit to discern between prepregnancy, pregnancy, postpartum without depression, and postpartum with depression (ie, PPD diagnosis) periods. Models were built using generalized linear models, random forest, support vector machine, and k-nearest neighbor algorithms and evaluated using the κ statistic and multiclass area under the receiver operating characteristic curve (mAUC) to determine the algorithm with the best performance. The specificity of our individualized ML approach was confirmed in a cohort of women who gave birth and did not experience PPD. Moreover, we assessed the impact of a previous history of depression on model performance. We determined the variable importance for predicting the PPD period using Shapley additive explanations and confirmed the results using a permutation approach. Finally, we compared our individualized ML methodology against a traditional cohort-based ML model for PPD recognition and compared model performance using sensitivity, specificity, precision, recall, and F1-score. RESULTS: Patient cohorts of women with valid Fitbit data who gave birth included <20 with PPD and 39 without PPD. Our results demonstrated that intraindividual models using digital biomarkers discerned among prepregnancy, pregnancy, postpartum without depression, and postpartum with depression (ie, PPD diagnosis) periods, with random forest (mAUC=0.85; κ=0.80) models outperforming generalized linear models (mAUC=0.82; κ=0.74), support vector machine (mAUC=0.75; κ=0.72), and k-nearest neighbor (mAUC=0.74; κ=0.62). Model performance decreased in women without PPD, illustrating the method's specificity. Previous depression history did not impact the efficacy of the model for PPD recognition. Moreover, we found that the most predictive biomarker of PPD was calories burned during the basal metabolic rate. Finally, individualized models surpassed the performance of a conventional cohort-based model for PPD detection. CONCLUSIONS: This research establishes consumer wearables as a promising tool for PPD identification and highlights personalized ML approaches, which could transform early disease detection strategies.
Subject(s)
Biomarkers , Depression, Postpartum , Wearable Electronic Devices , Humans , Depression, Postpartum/diagnosis , Depression, Postpartum/psychology , Female , Adult , Biomarkers/analysis , Cross-Sectional Studies , Wearable Electronic Devices/statistics & numerical data , Wearable Electronic Devices/standards , Machine Learning/standards , Pregnancy , United States , Datasets as Topic , ROC CurveABSTRACT
We investigate risk factors for severe COVID-19 in persons living with HIV (PWH), including among racialized PWH, using the U.S. population-sampled National COVID Cohort Collaborative (N3C) data released from January 1, 2020 to October 10, 2022. We defined severe COVID-19 as hospitalized with invasive mechanical ventilation, extracorporeal membrane oxygenation, discharge to hospice or death. We used machine learning methods to identify highly ranked, uncorrelated factors predicting severe COVID-19, and used multivariable logistic regression models to assess the associations of these variables with severe COVID-19 in several models, including race-stratified models. There were 3 241 627 individuals with incident COVID-19 cases and 81 549 (2.5%) with severe COVID-19, of which 17 445 incident COVID-19 and 1 020 (5.8%) severe cases were among PWH. The top highly ranked factors of severe COVID-19 were age, congestive heart failure (CHF), dementia, renal disease, sodium concentration, smoking status, and sex. Among PWH, age and sodium concentration were important predictors of COVID-19 severity, and the effect of sodium concentration was more pronounced in Hispanics (aOR 4.11 compared to aOR range: 1.47-1.88 for Black, White, and Other non-Hispanics). Dementia, CHF, and renal disease was associated with higher odds of severe COVID-19 among Black, Hispanic, and Other non-Hispanics PWH, respectively. Our findings suggest that the impact of factors, especially clinical comorbidities, predictive of severe COVID-19 among PWH varies by racialized groups, highlighting a need to account for race and comorbidity burden when assessing the risk of PWH developing severe COVID-19.
ABSTRACT
Bridging the gap between genetic variations, environmental determinants, and phenotypic outcomes is critical for supporting clinical diagnosis and understanding mechanisms of diseases. It requires integrating open data at a global scale. The Monarch Initiative advances these goals by developing open ontologies, semantic data models, and knowledge graphs for translational research. The Monarch App is an integrated platform combining data about genes, phenotypes, and diseases across species. Monarch's APIs enable access to carefully curated datasets and advanced analysis tools that support the understanding and diagnosis of disease for diverse applications such as variant prioritization, deep phenotyping, and patient profile-matching. We have migrated our system into a scalable, cloud-based infrastructure; simplified Monarch's data ingestion and knowledge graph integration systems; enhanced data mapping and integration standards; and developed a new user interface with novel search and graph navigation features. Furthermore, we advanced Monarch's analytic tools by developing a customized plugin for OpenAI's ChatGPT to increase the reliability of its responses about phenotypic data, allowing us to interrogate the knowledge in the Monarch graph using state-of-the-art Large Language Models. The resources of the Monarch Initiative can be found at monarchinitiative.org and its corresponding code repository at github.com/monarch-initiative/monarch-app.
Subject(s)
Databases, Factual , Disease , Genes , Phenotype , Humans , Internet , Databases, Factual/standards , Software , Genes/genetics , Disease/geneticsABSTRACT
Postpartum depression (PPD), afflicting one in seven women, poses a major challenge in maternal health. Existing approaches to detect PPD heavily depend on in-person postpartum visits, leading to cases of the condition being overlooked and untreated. We explored the potential of consumer wearable-derived digital biomarkers for PPD recognition to address this gap. Our study demonstrated that intra-individual machine learning (ML) models developed using these digital biomarkers can discern between pre-pregnancy, pregnancy, postpartum without depression, and postpartum with depression time periods (i.e., PPD diagnosis). When evaluating variable importance, calories burned from the basal metabolic rate (calories BMR) emerged as the digital biomarker most predictive of PPD. To confirm the specificity of our method, we demonstrated that models developed in women without PPD could not accurately classify the PPD-equivalent phase. Prior depression history did not alter model efficacy for PPD recognition. Furthermore, the individualized models demonstrated superior performance compared to a conventional cohort-based model for the detection of PPD, underscoring the effectiveness of our individualized ML approach. This work establishes consumer wearables as a promising avenue for PPD identification. More importantly, it also emphasizes the utility of individualized ML model methodology, potentially transforming early disease detection strategies.
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INTRODUCTION: The increasing prevalence of coexisting health conditions poses a challenge to healthcare providers and healthcare systems. Spinal pain (eg, neck and back pain) and spinal pathologies (eg, osteoporotic fractures and degenerative spinal disease) exist concurrently with other non-spinal health conditions (NSHC). However, the scope of what associations may exist among these co-occurring conditions is unclear. Therefore, this scoping review aims to map the epidemiological literature that reports associations between spine-related pain and pathologies (SPPs) and NSHCs. METHODS AND ANALYSIS: This scoping review will follow the JBI protocol and Preferred Reporting Items for Systematic reviews and Meta-Analyses extension for Scoping Reviews. We will systematically search the literature using key words and MeSH terms for SPPs and NSHCs. Terminology/vocabulary for NSHCs will include those for communicable and non-communicable diseases as reported by WHO Global Burden of Disease reports. Five databases will be searched from inception: MEDLINE, EMBASE, APA PsycInfo, Scopus and Web of Science Core Collection. Papers published in English, in peer-reviewed journals, including measures of association between SPPs and NSHCs and using observational epidemiologic study designs will be included. Excluded will be studies of cadaveric, animal or health behaviours; studies with no measures of association and non-observational epidemiologic studies. Results will include the number of studies, the studies that have evaluated the measures of association and the frequency of the studied associations between SPPs and NSHCs. Results will be reported in tables and diagrams. Themes of comorbidities will be synthesised into a descriptive report. ETHICS AND DISSEMINATION: This scoping review was deemed exempt from ethics review. This review will provide a comprehensive overview of the literature that reports associations between SPPs and NSHCs to inform future research initiatives and practices. Results will be disseminated through publication in peer-reviewed journals and research conferences. REGISTRATION DETAILS: https://osf.io/w49u3.
Subject(s)
Biological Phenomena , Review Literature as Topic , Spinal Diseases , Animals , Humans , Databases, Factual , Epidemiologic Studies , Pain , Research Design , Spinal Diseases/epidemiologyABSTRACT
Objective: The purpose of this study was to describe the types of equestrian-related musculoskeletal injuries and their management. Methods: We retrospectively reviewed the charts of 19 patients who presented with injuries from equestrian activities at a chiropractic practice from December 2000 to December 2020. Deidentified data were extracted from the charts and summarized. Results: Of the 19 patients, 42.3% presented with acute trauma, 38.5% had overuse injuries, and 19.2% had chronic injuries as a result of previous trauma. We found that 90% of overuse injuries and 18.2% of acute injuries led to chronic conditions that needed ongoing management. Conclusion: From this sample of patients, there was a high percentage of overuse and chronic injuries for patients who participated in equestrian activities.
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Spinal pain and chronic health conditions are highly prevalent, burdensome, and costly conditions, both in the United States and globally. Using cross-sectional data from the 2016 through 2018 National Health Interview Survey (n = 26,926), we explored associations between spinal pain and chronic health conditions and investigated the influence that a set of confounders may have on the associations between spinal pain and chronic health conditions. Variance estimation method was used to compute weighted descriptive statistics and measures of associations with multinomial logistic regression models. All four chronic health conditions significantly increased the prevalence odds of spinal pain; cardiovascular conditions by 58%, hypertension by 40%, diabetes by 25% and obesity by 34%, controlling for all the confounders. For all chronic health conditions, tobacco use (45-50%), being insufficiently active (17-20%), sleep problems (180-184%), cognitive impairment (90-100%), and mental health conditions (68-80%) significantly increased the prevalence odds of spinal pain compared to cases without spinal pain. These findings provide evidence to support research on the prevention and treatment of non-musculoskeletal conditions with approaches of spinal pain management.
Subject(s)
Chronic Pain , Humans , United States/epidemiology , Chronic Pain/epidemiology , Neck Pain/epidemiology , Cross-Sectional Studies , Chronic Disease , Health Behavior , Prevalence , Health SurveysABSTRACT
Low back pain and depression have been globally recognized as key public health problems and they are considered co-morbid conditions. This study explores both cross-sectional and longitudinal comorbid associations between back pain and major depression in the adult population in the United States. We used data from the Midlife in the United States survey (MIDUS), linking MIDUS II and III with a sample size of 2358. Logistic regression and Poisson regression models were used. The cross-sectional analysis showed significant associations between back pain and major depression. The longitudinal analysis indicated that back pain at baseline was prospectively associated with major depression at follow-up (PR 1.96, CI: 1.41, 2.74), controlling for health behavioral and demographic variables. Major depression at baseline was also prospectively associated with back pain at follow-up (PR 1.48, CI: 1.04, 2.13), controlling for a set of related confounders. These findings of a bidirectional comorbid association fill a gap in the current understanding of these comorbid conditions and could have clinical implications for the management and prevention of both depression and low back pain.
Subject(s)
Depressive Disorder, Major , Low Back Pain , Adult , Humans , United States , Depression/epidemiology , Low Back Pain/epidemiology , Depressive Disorder, Major/epidemiology , Cross-Sectional Studies , Comorbidity , Back Pain/epidemiologyABSTRACT
The transcription factor Prdm16 functions as a potent suppressor of transforming growth factor-beta (TGF-ß) signaling, whose inactivation is deemed essential to the progression of pancreatic ductal adenocarcinoma (PDAC). Using the KrasG12D-based mouse model of human PDAC, we surprisingly found that ablating Prdm16 did not block but instead accelerated PDAC formation and progression, suggesting that Prdm16 might function as a tumor suppressor in this malignancy. Subsequent genetic experiments showed that ablating Prdm16 along with Smad4 resulted in a shift from a well-differentiated and confined neoplasm to a highly aggressive and metastatic disease, which was associated with a striking deviation in the trajectory of the premalignant lesions. Mechanistically, we found that Smad4 interacted with and recruited Prdm16 to repress its own expression, therefore pinpointing a model in which Prdm16 functions downstream of Smad4 to constrain the PDAC malignant phenotype. Collectively, these findings unveil an unprecedented antagonistic interaction between the tumor suppressors Smad4 and Prdm16 that functions to restrict PDAC progression and metastasis.
Subject(s)
Carcinoma, Pancreatic Ductal , DNA-Binding Proteins , Pancreatic Neoplasms , Smad4 Protein , Transcription Factors , Animals , Humans , Mice , Carcinoma, Pancreatic Ductal/genetics , Carcinoma, Pancreatic Ductal/pathology , Cell Line, Tumor , DNA-Binding Proteins/genetics , DNA-Binding Proteins/metabolism , Pancreatic Neoplasms/genetics , Pancreatic Neoplasms/pathology , Smad4 Protein/genetics , Smad4 Protein/metabolism , Transcription Factors/genetics , Transcription Factors/metabolism , Pancreatic NeoplasmsABSTRACT
A long-standing question in the pancreatic ductal adenocarcinoma (PDAC) field has been whether alternative genetic alterations could substitute for oncogenic KRAS mutations in initiating malignancy. Here, we report that Neurofibromin1 (NF1) inactivation can bypass the requirement of mutant KRAS for PDAC pathogenesis. An in-depth analysis of PDAC databases reveals various genetic alterations in the NF1 locus, including nonsense mutations, which occur predominantly in tumors with wild-type KRAS. Genetic experiments demonstrate that NF1 ablation culminates in acinar-to-ductal metaplasia, an early step in PDAC. Furthermore, NF1 haploinsufficiency results in a dramatic acceleration of KrasG12D-driven PDAC. Finally, we show an association between NF1 and p53 that is orchestrated by PML, and mosaic analysis with double markers demonstrates that concomitant inactivation of NF1 and Trp53 is sufficient to trigger full-blown PDAC. Together, these findings open up an exploratory framework for apprehending the mechanistic paradigms of PDAC with normal KRAS, for which no effective therapy is available.
Subject(s)
Carcinoma, Pancreatic Ductal , Pancreatic Neoplasms , Humans , Carcinoma, Pancreatic Ductal/genetics , Carcinoma, Pancreatic Ductal/pathology , Mutation , Pancreatic Ducts/pathology , Pancreatic Neoplasms/genetics , Pancreatic Neoplasms/pathology , Proto-Oncogene Proteins p21(ras)/genetics , Neurofibromin 1/metabolism , Pancreatic NeoplasmsABSTRACT
Heart disease remains the leading cause of death globally by gender and region. Smoking and alcohol drinking are known modifiable health behaviors of heart disease. Utilizing data from the US Health and Retirement Study and the China Health and Retirement Longitudinal Study, this study examines heart disease disparities and the association with smoking and drinking behavior among men and women in the US and China. Smoking and drinking behavior were combined to neither, smoke-only, drink-only, and both. In the US, the prevalence was higher in men (24.5%, 95% CI: 22.5-26.6%) than in women (20.6%, 95% CI: 19.3-22.1%) and a higher prevalence was found in the smoke-only group for both genders. In contrast, women in China had higher prevalence (22.9%, 95% CI: 21.7-24.1%) than men (16.1%, 95% CI: 15.1-17.2%), and the prevalence for women who smoked or engaged in both behaviors were ~1.5 times (95% CI: 1.3-1.8, p < 0.001) those who did not smoke or drink, but no statistical difference were found in men. The findings might be due to differences in smoking and drinking patterns and cultures by gender in the two countries and gender inequality among older adults in China. Culturally tailored health promotion strategies will help reduce the burden of heart disease.
Subject(s)
Heart Diseases , Retirement , Aged , Alcohol Drinking/epidemiology , China/epidemiology , Cross-Sectional Studies , Female , Health Behavior , Heart Diseases/epidemiology , Humans , Longitudinal Studies , Male , Middle Aged , Prevalence , Smoking/epidemiologyABSTRACT
OBJECTIVE: Globally 37.9 million people are living with HIV/AIDS, and with mortality rates declining, there is an increasing focus on comorbidities including musculoskeletal (MSK) disorders. Therefore, the aim of this scoping review was to generate and summarize an overview of the existing scientific literature dealing with MSK complaints in people living with HIV/AIDS (PLWHAs). METHODS: This scoping review followed the five-stage methodological framework proposed by Arksey and O'Malley. We searched PubMed, EMBASE, CINAHL, and the Cochrane Library from inception to June 1, 2020. Two reviewers independently reviewed the articles for eligibility. A data extraction form was used to chart information such as author, year of publication, data source, sample size, country of origin, ethnicity, age, gender, antiretroviral therapy, MSK condition prevalence, and anatomical location. RESULTS: The search identified 10 522 articles. Of these, 27 studies were included after full-text screening for data extraction. Studies were conducted in thirteen different countries with diverse data sources such as outpatient clinic files, hospital records, primary care clinic files, and AIDS Service Organization files. PLWHAs have a variety of MSK conditions. Most studies reported spinal pain such as lower back or neck pain, but pain in the extremities and osteoarthritis (OA) were also represented. However, the frequencies of pain at various anatomical sites were highly variable. CONCLUSION: There is a lack of knowledge regarding MSK conditions in PLWHAs. Future studies designed to specifically study MSK complaints and disabilities are needed to gain a better picture of the impact of these conditions in PLWHAs and to inform prevention and treatment strategies globally in this often-underserved population.
Subject(s)
HIV Infections/epidemiology , Musculoskeletal Diseases/epidemiology , Acquired Immunodeficiency Syndrome/epidemiology , Comorbidity , HumansABSTRACT
STUDY DESIGN: We combined elements of cohort and crossover-cohort design. OBJECTIVE: The objective of this study was to compare longterm outcomes for spinal manipulative therapy (SMT) and opioid analgesic therapy (OAT) regarding escalation of care for patients with chronic low back pain (cLBP). SUMMARY OF BACKGROUND DATA: Current evidence-based guidelines for clinical management of cLBP include both OAT and SMT. For long-term care of older adults, the efficiency and value of continuing either OAT or SMT are uncertain. METHODS: We examined Medicare claims data spanning a five-year period. We included older Medicare beneficiaries with an episode of cLBP beginning in 2013. All patients were continuously enrolled under Medicare Parts A, B, and D. We analyzed the cumulative frequency of encounters indicative of an escalation of care for cLBP, including hospitalizations, emergency department visits, advanced diagnostic imaging, specialist visits, lumbosacral surgery, interventional pain medicine techniques, and encounters for potential complications of cLBP. RESULTS: SMT was associated with lower rates of escalation of care as compared to OAT. The adjusted rate of escalated care encounters was approximately 2.5 times higher for initial choice of OAT vs. initial choice of SMT (with weighted propensity scoring: rate ratio 2.67, 95% confidence interval 2.64-2.69, Pâ<â.0001). CONCLUSION: Among older Medicare beneficiaries who initiated long-term care for cLBP with opioid analgesic therapy, the adjusted rate of escalated care encounters was significantly higher as compared to those who initiated care with spinal manipulative therapy.Level of Evidence: 3.
Subject(s)
Low Back Pain , Manipulation, Spinal , Aged , Analgesics, Opioid , Hospitalization , Humans , Low Back Pain/diagnosis , Low Back Pain/therapy , Medicare , United StatesABSTRACT
OBJECTIVES: The purpose of this study was to compare Medicare healthcare expenditures for patients who received long-term treatment of chronic low back pain (cLBP) with either opioid analgesic therapy (OAT) or spinal manipulative therapy (SMT). METHODS: We conducted a retrospective observational study using a cohort design for analysis of Medicare claims data. The study population included Medicare beneficiaries enrolled under Medicare Parts A, B, and D from 2012 through 2016. We assembled cohorts of patients who received long-term management of cLBP with OAT or SMT (such as delivered by chiropractic or osteopathic practitioners) and evaluated the comparative effect of OAT vs SMT upon expenditures, using multivariable regression to control for beneficiary characteristics and measures of health status, and propensity score weighting and binning to account for selection bias. RESULTS: The study sample totaled 28,160 participants, of whom 77% initiated long-term care of cLBP with OAT, and 23% initiated care with SMT. For care of low back pain specifically, average long-term costs for patients who initiated care with OAT were 58% lower than those who initiated care with SMT. However, overall long-term healthcare expenditures under Medicare were 1.87 times higher for patients who initiated care via OAT compared with those initiated care with SMT (95% CI 1.65-2.11; P < .0001). CONCLUSIONS: Adults aged 65 to 84 who initiated long-term treatment for cLBP via OAT incurred lower long-term costs for low back pain but higher long-term total healthcare costs under Medicare compared with patients who initiated long-term treatment with SMT.
Subject(s)
Chiropractic , Low Back Pain , Manipulation, Spinal , Aged , Analgesics, Opioid/therapeutic use , Humans , Low Back Pain/therapy , Medicare , United StatesABSTRACT
STUDY DESIGN: RAND/UCLA Appropriateness Method (RUAM) applied to chiropractic manipulation for patients with chronic low-back pain (CLBP) and chronic neck pain (CNP). OBJECTIVE: Determine the rate of appropriate care provided by US chiropractors. SUMMARY OF BACKGROUND DATA: Spinal manipulation has been shown effective for CLBP and CNP but may not be appropriate for all patients with these conditions. METHODS: Ratings of the appropriateness of spinal and cervical manipulation previously developed by two RUAM expert panels were applied to data abstracted from random samples of patient charts from chiropractors in six US regions to determine the appropriateness of manipulation for each patient. RESULTS: Of 125 chiropractors sampled, 89 provided charts that could be abstracted. Of the 2128 charts received, 1054 were abstracted. Charts received but not abstracted included 460 that were unusable (e.g., illegible), and 555 did not have CLBP or CNP. Across the abstracted charts 72% had CLBP, 57% had CNP, and 29% had both; 84% of patients with CLBP and 86% with CNP received manipulation. Patients with CLBP who had minor neurologic findings, sciatic nerve irritation, or no joint dysfunction were significantly less likely to receive manipulation. Patients with CNP who had substantial trauma etiology, no joint dysfunction, or no radiographs were significantly less likely to receive manipulation. Most manipulation for CLBP (64%) was appropriate and most manipulation for CNP (93%) was for patients where appropriateness was uncertain or equivocal. The proportions of patients receiving inappropriate manipulation for either condition were low (1%-3%) as were the numbers of patients presenting to these chiropractors for which manipulation was inappropriate. CONCLUSION: Chiropractors in this US sample tend to provide manipulation to very few patients with CLBP or CNP for which it is inappropriate. However, more research is needed to determine which patients with CNP benefit from manipulation.Level of Evidence: 4.
Subject(s)
Chiropractic , Chronic Pain , Low Back Pain , Manipulation, Chiropractic , Manipulation, Spinal , Chronic Pain/diagnosis , Chronic Pain/therapy , Humans , Low Back Pain/diagnosis , Low Back Pain/therapy , Neck Pain/diagnosis , Neck Pain/therapyABSTRACT
INTRODUCTION: Few studies indicated the impact of ethnicity on an association between central sleep apnea (CSA) and atrial fibrillation/flutter (AF) in older populations. We assessed possible ethnic differences in the association among elderly Japanese-American and White-American men. METHODS: We performed a cross-sectional analysis using two population studies of Japanese-American and White-American men. The Kuakini Honolulu-Asia Aging Study is a longitudinal cohort study of Japanese-American men living in Hawaii. Sleep data were collected between 1999 and 2000. The Osteoporotic Fractures in Men (Mr.OS) Sleep Study was conducted between 2003 and 2005 on the continental U.S. The majority of Mr.OS participants were White-American. We selected 79-90 year old males, who had overnight polysomnography from both studies. Total participants were 690 Japanese-American and 871 White-American men. The central apnea index (CAI) was the measure of the number of central apneas. CSA was defined by CAI>=5. Cheyne-Stokes breathing (CSB) was defined as a minimum consecutive 5-10 min period of a crescendo-decrescendo respiratory pattern associated with CSA. RESULTS: The prevalence of AF was 5.7% in Japanese-American men and 9.0% in White-American men. The prevalence of CSA and CSB in White-Americans were higher than in Japanese-Americans (11.5% vs 6.5% and 5.7% vs 3.3%, respectively). In multivariable-adjusted logistic regression models, CSA was associated with higher odds of AF, and the association was stronger in Japanese-Americans [Odds Ratio (OR) = 4.77, 95% confidence interval (CI): 1.95-11.67] than in White-Americans (OR = 2.09, 95 %CI: 1.09-4.01). CSB showed similar trends as CSA. CONCLUSIONS: After adjustment, CSA and CSB were significantly associated with AF in both Japanese-American and White-American men.
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INTRODUCTION: Waist circumference is a common anthropometric measure for predicting abdominal obesity and insulin resistance. We developed optimal waist circumference cut points for children aged 2 to 8 years in the US-Affiliated Pacific (USAP) region based on the relationship of waist circumference and acanthosis nigricans in this population. METHODS: We conducted a cross-sectional analysis from the Children's Healthy Living Program's 2012-2013 data on 4,023 children. We used receiver-operating characteristic analysis to determine the sensitivity and specificity for acanthosis nigricans across waist circumference, by sex and age. We determined optimal waist circumference cutoff points corresponding to Youden index (J), (equal to [sensitivity + specificity] - 1), with acanthosis nigricans. We compared these cut points with the 90th percentile. RESULTS: The 90th-percentile cut points for boys aged 2 to 5 years (58.15 cm) and 6 to 8 years (71.63 cm) were slightly higher than for girls in both age groups (aged 2-5 y, 57.97 cm; 6-8 y: 70.37 cm). The optimal cut points (corresponding to the highest sensitivity and specificity) were as follows: for boys aged 2 to 5 years, 90th percentile (58.25 cm; sensitivity, 48.0%; specificity, 91.5%); for boys aged 6 to 8 years, 78th percentile (63.59 cm; sensitivity, 86.8%; specificity, 82.8%); for girls aged 2 to 5 years, 62nd percentile (53.27 cm; sensitivity, 71.4%; specificity, 63.1%), and for girls aged 6 to 8 years, 80th percentile (63.63 cm; sensitivity, 55.4%; specificity, 82.9%). CONCLUSION: Among USAP children, waist circumference was a reasonable predictor for acanthosis nigricans. Further analysis is warranted to examine causes of acanthosis nigricans at lower-than-expected waist circumference percentiles. The cut points can be used for early detection of metabolic risk.