Lung Structure and Risk of Sleep Apnea in SPIROMICS

Rationale

The SubPopulations and InteRmediate Outcome Measures in COPD Study (SPIROMICS) is a prospective cohort study that enrolled 2981 participants with the goal of identifying new chronic obstructive pulmonary disease (COPD) subgroups and intermediate markers of disease progression. Individuals with COPD and obstructive sleep apnea (OSA) experience impaired quality of life and more frequent exacerbations. COPD severity also associates with computed tomography scan-based emphysema and alterations in airway dimensions.

Objectives

The objective was to determine whether the combination of lung function and structure influences the risk of OSA among current and former smokers.

Methods

Using 2 OSA risk scores, the Berlin Sleep Questionnaire (BSQ), and the DOISNORE50 (Diseases, Observed apnea, Insomnia, Snoring, Neck circumference > 18 inches, Obesity with body mass index [BMI] > 32, R = are you male, Excessive daytime sleepiness, 50 = age ≥ 50) (DIS), 1767 current and former smokers were evaluated for an association of lung structure and function with OSA risk.

Measurements and Main Results

The study cohort's mean age was 63 years, BMI was 28 kg/m2, and forced expiratory volume in 1 second (FEV1) was 74.8% predicted. The majority were male (55%), White (77%), former smokers (59%), and had COPD (63%). A high-risk OSA score was reported in 36% and 61% using DIS and BSQ respectively. There was a 9% increased odds of a high-risk DIS score (odds ratio [OR]=1.09, 95% confidence interval [CI]:1.03-1.14) and nominally increased odds of a high-risk BSQ score for every 10% decrease in FEV1 %predicted (OR=1.04, 95%CI: 0.998-1.09). Lung function-OSA risk associations persisted after additionally adjusting for lung structure measurements (%emphysema, %air trapping, parametric response mapping for functional small airways disease, , mean segmental wall area, tracheal %wall area, dysanapsis) for DIS (OR=1.12, 95%CI:1.03-1.22) and BSQ (OR=1.09, 95%CI:1.01-1.18).

Conclusions

Lower lung function independently associates with having high risk for OSA in current and former smokers. Lung structural elements, especially dysanapsis, functional small airways disease, and tracheal %wall area strengthened the effects on OSA risk.

Patterns of site-level periodontal disease and within-mouth correlation among older adults in the Hispanic Community Health Study/Study of Latinos

OBJECTIVES

Clinical measures of periodontal disease such as attachment loss (CAL) and probing depth (PD) vary considerably between and within individuals with periodontitis and are known to be influenced by person-level factors (e.g. age and race/ethnicity) as well as intraoral characteristics (e.g. tooth type and location). This study sought to characterize site-level disease patterns and correlations using both person-level and intraoral factors through a model-based approach.

METHODS

This study used full-mouth, six sites per tooth, periodontal examination data collected from 2301 Hispanic/Latino adults aged 60-74 years in the Hispanic Community Health Study/Study of Latinos (HCHS/SOL). The presence of site-level CAL ≥3 mm and PD ≥4 mm was estimated using generalized estimating equations (GEE), explicitly modelling pairwise periodontal site correlations, while adjusting for number of teeth, sex and Hispanic/Latino background. Subsequently tooth- and tooth-site patterns of intraoral CAL ≥3 mm and PD ≥4 mm were estimated and visualized in the HCHS/SOL population.

RESULTS

The findings showed that posterior sites had the highest odds of CAL ≥3 mm and PD ≥4 mm. Sites located in the interproximal space had higher odds of PD ≥4 mm but lower odds of CAL ≥3 mm than non-interproximal sites. Mexicans had the lowest odds of CAL ≥3 mm among all Hispanic/Latino backgrounds. While Mexicans had lower odds of PD ≥4 mm than Central Americans and Cubans, they had higher odds than Dominicans and Puerto Ricans. Site-level proportions and pairwise correlations of PD ≥4 mm were generally smaller than those of CAL ≥3 mm.

CONCLUSIONS

The patterns of site-level probabilities of clinical measures of periodontal disease can be defined based on tooth, site and individual-level characteristics. Intraoral correlation patterns, while complex, are quantifiable. The risk factors for site-level CAL ≥3 mm may differ from those of PD ≥4 mm. Likewise, participant risk factors for site-level clinical measures of periodontal disease are distinct from those that affect individual-level periodontitis prevalence. Future epidemiological investigations should consider model-based approaches when examining site-level disease probabilities to identify intra-oral patterns of periodontal disease and make inferences about the larger population.

GEECORR: A SAS macro for regression models of correlated binary responses and within-cluster correlation using generalized estimating equations

BACKGROUND AND OBJECTIVES

Generalized estimating equations (GEE) provide population-averaged model inference for longitudinal and clustered outcomes via a generalized linear model for the effect of explanatory variables on the marginal mean, while intra-cluster correlations are ordinarily treated as nuisance parameters. Software to richly parameterize and conduct inference for complex correlation structures in the marginal modeling framework is scarce.

METHODS

A SAS macro, GEECORR, has been developed for the analysis of clustered binary data based on GEE to include additional estimating equations for modeling pairwise correlation between binary variates as a function of covariates.

RESULTS

We illustrate the macro in a surveillance study with repeated measures, a longitudinal study, and a study with biological clustering.

CONCLUSIONS

This article provides an overview of the GEE method consisting of a pair of estimating equations, describes the features and capabilities of the GEECORR macro including regression diagnostics and finite-sample bias-corrected covariance estimators, and demonstrates the macro usage for three studies.

The association of insomnia and sleep apnea with deployment and combat exposure in the entire population of US army soldiers from 1997 to 2011: a retrospective cohort investigation

Since 2001, the United States has been engaged in the longest and most expensive overseas conflict in its history. Sleep disorders, especially insomnia and obstructive sleep apnea (OSA), are common in service members and appear related to deployment and combat exposure, but this has not been systematically examined. Therefore, the incidence of clinically diagnosed insomnia and OSA from 1997 to 2011 in the entire population of US Army soldiers was determined and associations of these disorders with deployment and combat exposure examined. This observational retrospective cohort study linked medical, demographic, deployment, and combat casualty data from all active duty US Army soldiers serving from 1997 to 2011 (n = 1 357 150). The mediating effects of multiple known comorbid conditions were considered. From 2003 to 2011, there were extraordinary increases in incidence of insomnia (652%) and OSA (600%). Factors increasing insomnia risk were deployment (risk ratio [RR] [deployed/not deployed] = 2.06; 95% confidence interval [CI], 2.04-2.08) and combat exposure (RR [exposed/not exposed] = 1.20; 95% CI, 1.19-1.22). Risk of OSA was increased by deployment (RR [deployed/not deployed] = 2.14; 95% CI, 2.11-2.17), but not combat exposure (RR [exposed/not exposed] = 1.00; 95% CI, 0.98-1.02). These relationships remained after accounting for other factors in multivariable analyses. A number of comorbid medical conditions such as posttraumatic stress disorder and traumatic brain injury mediated a portion of the association between the sleep disorders and deployment. It is essential to determine underlying mechanisms responsible for these very large increases in insomnia and OSA and introduce effective preventive measures.

Effect of Chronic Low Back Pain and Post-Traumatic Stress Disorder on the Risk for Separation from the US Army

Introduction

Co-morbid post-traumatic stress disorder (PTSD) and low back pain (LBP) are common reasons for increased disability in the Veteran communities. Medical discharge from the military represents a considerable financial cost to society. Little is currently known about the impact of LBP and PTSD as longitudinal risk factors for medical discharge from Active Duty military service.

Materials and Methods

A retrospective analysis of US Army Active Duty Soldiers from 2002 to 2012 was performed to determine the risk for medical discharge. Four levels of exposure for were identified as independent variables: no chronic LBP or PTSD, chronic LBP only, PTSD only, and co-morbid PTSD present with chronic LBP. Statistical analysis utilized modified Poisson regression controlling for sex, age, rank, time in service, deployment, mental health, sleep disorders, alcohol use, tobacco use, obesity, and military occupation. This study was approved by a Department of Defense Institutional Review Board.

Results

After controlling for potential confounding variables, the RR for chronic LBP and PTSD independently was 3.65 (95% CI: 3.59–3.72) and 3.64 (95% CI: 3.53–3.75), respectively, and 5.17 (95% CI: 5.01–5.33) when both were present.

Conclusions

This is the first study to identify a history of both chronic LBP and PTSD as substantial risk factors for medical discharge from the US Army. PTSD and chronic LBP may mutually reinforce one another and deplete active coping strategies, making Soldiers less likely to be able to continue military service. Future research should target therapies for co-morbid PTSD and chronic LBP as these conditions contribute a substantial increase in risk of medical discharge from the US Army.

Characterization of Patients in a Lifestyle Medicine Practice

Objective. Lifestyle medicine is a relatively new specialty within medicine. The aim of this report is to characterize patients who present to a lifestyle medicine clinical practice. Methods. LifeStyle Medical Centers is an independent, community-based practice; this report is based on over 3200 patients within this practice. Most of the data presented were obtained from an intake questionnaire developed by the practice to provide background and screening particularly relevant to lifestyle medicine, including areas such as stress, sleep, physical activity, health knowledge, motivation, weight loss history and goals, and smoking. Results. Patients who present for lifestyle care come with varied goals, past histories, and current lifestyle issues. Many express a very high level of motivation to lose an unrealistically large amount of weight. The prevalence of physical inactivity, inadequate sleep, high stress, and risk of depression are high, yet the importance of these to health and well-being are often not recognized by the patient. Over 90% of the cost of care was covered by insurance. Conclusions. Having a better understanding of the patients who come to a lifestyle medicine clinic will help practices better design their lifestyle programs and guide lifestyle medicine providers to better engagement and care of their patients.