Faculty Bibliography

Purpose: This study aimed to assess the prevalence of self-reported polycystic ovary syndrome (PCOS) among Emiratis and examine bi-directional associations of PCOS with self-reported chronic diseases, namely: diabetes, asthma, high cholesterol, and high blood pressure. Patients and Methods: A cross-sectional analysis was performed using the UAE Healthy Future Study (UAEHFS) data collected from February 2016 to April 2022 involving 1040 Emirati women aged 25"“67 years from recruitment centers in the United Arab Emirates (UAE). The bi-directional associations between self-reported PCOS and self-reported chronic diseases were evaluated by establishing temporality based on reported age-at-diagnoses. Firstly, the associations between PCOS (diagnosed at ≥25 years) and chronic diseases (diagnosed at <25 years) were examined, followed by PCOS (diagnosed at <25 years) and chronic diseases (diagnosed at ≥25 years). Finally, a Poisson regression under unadjusted and age-and-body mass index (BMI) adjusted models was performed to obtain the risk ratio (RR) and its 95% confidence interval (CI). Results: The prevalence of PCOS in this study was 25.9%. Those with asthma and high cholesterol diagnosed at <25 years had increased risks of PCOS diagnosed at ≥25 years (RR = 1.79, 95% CI: 1.17"“2.76 for asthma; and RR = 1.61, 95% CI: 1.01"“2.59 for high cholesterol), compared to those respective healthier counterparts, after adjusting for age and BMI. No significant association was observed between PCOS diagnosed at <25 years and respective chronic diseases diagnosed at ≥25 years. Conclusion: PCOS prevalence among Emirati women was high. Asthma and high cholesterol in earlier life were associated with PCOS in later life. Understanding how chronic disease conditions and PCOS are associated in bi-directional ways may improve the surveillance of chronic disease conditions among women with PCOS and may also contribute to more targeted PCOS prevention strategies.

INTRODUCTION/UNASSIGNED:Asthma and polycystic ovarian syndrome (PCOS) are linked in several possible ways. To date, there has been no study evaluating whether pediatric asthma is an independent risk factor for adult PCOS. Our study aimed to examine the association between pediatric asthma (diagnosed at 0-19 years) and adult PCOS (diagnosed at ≥20 years). We further assessed whether the aforementioned association differed in two phenotypes of adult PCOS which were diagnosed at 20-25 years (young adult PCOS), and at >25 years (older adult PCOS). We also evaluated whether the age of asthma diagnosis (0-10 vs 11-19 years) modified the association between pediatric asthma and adult PCOS. MATERIAL AND METHODS/UNASSIGNED:This is a retrospective cross-sectional analysis using the United Arab Emirates Healthy Future Study (UAEHFS) collected from February 2016 to April 2022 involving 1334 Emirati females aged 18-49 years. We fitted a Poisson regression model to estimate the risk ratio (RR) and its 95% confidence interval (95% CI) to assess the association between pediatric asthma and adult PCOS adjusting for age, urbanicity at birth, and parental smoking at birth. RESULTS/UNASSIGNED:After adjusting for confounding factors and comparing to non-asthmatic counterparts, we found that females with pediatric asthma had a statistically significant association with adult PCOS diagnosed at ≥20 years (RR=1.56, 95% CI: 1.02-2.41), with a stronger magnitude of the association found in the older adult PCOS phenotype diagnosed at >25 years (RR=2.06, 95% CI: 1.16-3.65). Further, we also found females reported thinner childhood body size had a two-fold to three-fold increased risk of adult PCOS diagnosed at ≥20 years in main analysis and stratified analyses by age of asthma and PCOS diagnoses (RR=2.06, 95% CI: 1.08-3.93 in main analysis; RR=2.74, 95% CI: 1.22-6.15 among those diagnosed with PCOS > 25 years; and RR=3.50, 95% CI: 1.38-8.43 among those diagnosed with asthma at 11-19 years). CONCLUSIONS/UNASSIGNED:Pediatric asthma was found to be an independent risk factor for adult PCOS. More targeted surveillance for those at risk of adult PCOS among pediatric asthmatics may prevent or delay PCOS in this at-risk group. Future studies with robust longitudinal designs aimed to elucidate the exact mechanism between pediatric asthma and PCOS are warranted.

OBJECTIVE:The Department of Veterans Affairs' (VA) electronic health records (EHR) offer a rich source of big data to study medical and health care questions, but patient eligibility and preferences may limit generalizability of findings. We therefore examined the representativeness of VA veterans by comparing veterans using VA healthcare services to those who do not. METHODS:We analyzed data on 3051 veteran participants age ≥ 18 years in the 2019 National Health Interview Survey. Weighted logistic regression was used to model participant characteristics, health conditions, pain, and self-reported health by past year VA healthcare use and generate predicted marginal prevalences, which were used to calculate Cohen's d of group differences in absolute risk by past-year VA healthcare use. RESULTS:Among veterans, 30.4% had past-year VA healthcare use. Veterans with lower income and members of racial/ethnic minority groups were more likely to report past-year VA healthcare use. Health conditions overrepresented in past-year VA healthcare users included chronic medical conditions (80.6% vs. 69.4%, d = 0.36), pain (78.9% vs. 65.9%; d = 0.35), mental distress (11.6% vs. 5.9%; d = 0.47), anxiety (10.8% vs. 4.1%; d = 0.67), and fair/poor self-reported health (27.9% vs. 18.0%; d = 0.40). CONCLUSIONS:Heterogeneity in veteran sociodemographic and health characteristics was observed by past-year VA healthcare use. Researchers working with VA EHR data should consider how the patient selection process may relate to the exposures and outcomes under study. Statistical reweighting may be needed to generalize risk estimates from the VA EHR data to the overall veteran population.

Electronic health records (EHRs) are often used for recruitment into research studies, as they efficiently facilitate targeted outreach. While studies increasingly are reaching out to potential participants through the EHR patient portal, there is little available information about which approaches are most effective. We surveyed all investigators at one academic medical center who had used the Epic MyChart patient portal for recruitment. We found that messages were typically adapted for a large group, but not tailored further for individual subgroups. The vast majority of studies sent a message only once. Recruitment costs were modest, averaging $431/study. The results show some promise for recruiting through the patient portal but also identified ways in which messages could be optimized.

Respiratory effects of e-cigarette use among youth are not fully understood. This study investigated the longitudinal association between e-cigarette use and a validated index of functionally important respiratory symptoms among US youth. Data from Waves 3-4 of the Population Assessment of Tobacco and Health Study were analyzed. The sample included youth (aged 12-17) without asthma at baseline (Wave 3), who completed a follow-up survey (Wave 4), and were not missing data for analytic variables (n = 3899). Exposure was e-cigarette use status (never, former, or current) at baseline. The outcome was a respiratory symptom index based on responses for seven wheezing items at Wave 4. An index of ≥2 was defined as having functionally important respiratory symptoms. Lagged logistic regression models examined the association between baseline e-cigarette use and functionally important respiratory symptoms at follow-up by combustible tobacco use status (never or ever), and controlling for baseline covariates. At baseline, 13.7% of participants reported former e-cigarette use, and 4.3% reported current use. Baseline e-cigarette use did not increase the odds of having functionally important respiratory symptoms at follow-up regardless of combustible tobacco use status. Future research on larger populations of e-cigarette users with longer follow-up periods will improve our understanding of the respiratory risks associated with e-cigarette use among youth.

INTRODUCTION/BACKGROUND:Metabolic syndrome (MetS) is a multiplex of risk factors that predispose people to the development of diabetes and cardiovascular disease (CVD), two of the major non-communicable diseases that contribute to mortality in the United Arab Emirates (UAE). MetS guidelines require the testing of fasting samples, but there are evidence-based suggestions that non-fasting samples are also reliable for CVD-related screening measures. In this study, we aimed to estimate MetS and its components in a sample of young Emiratis using HbA1c as another glycemic marker. We also aimed to estimate the associations of some known CVD risk factors with MetS in our population. METHODS:The study was based on a cross-sectional analysis of baseline data of 5161 participants from the UAE Healthy Future Study (UAEHFS). MetS was identified using the NCEP ATP III criteria, with the addition of HbA1c as another glycemic indicator. Fasting blood glucose (FBG) and HbA1c were used either individually or combined to identify the glycemic component of MetS, based on the fasting status. Multivariate regression analysis was used to test for associations of selected social and behavioral factors with MetS. RESULTS:&gt; 0.05). Age, increased body mass index (BMI), and family history of any metabolic abnormality and/or heart disease were consistently strongly associated with MetS. CONCLUSION/CONCLUSIONS:MetS is highly prevalent in our sample of young Emirati adults. Our data showed that HbA1c may be an acceptable tool to test for the glycemic component of MetS in non-fasting samples. We found that the most relevant risk factors for predicting the prevalence of MetS were age, BMI, and family history.

BACKGROUND:The United Arab Emirates Healthy Future Study (UAEHFS) is one of the first large prospective cohort studies and one of the few studies in the region which examines causes and risk factors for chronic diseases among the nationals of the United Arab Emirates (UAE). The aim of this study is to investigate the eight-item Patient Health Questionnaire (PHQ-8) as a screening instrument for depression among the UAEHFS pilot participants. METHODS:The UAEHFS pilot data were analyzed to examine the relationship between the PHQ-8 and possible confounding factors, such as self-reported happiness, and self-reported sleep duration (hours) after adjusting for age, body mass index (BMI), and gender. RESULTS:Out of 517 participants who met the inclusion criteria, 487 (94.2%) participants filled out the questionnaire and were included in the statistical analysis using 100 multiple imputations. 231 (44.7%) were included in the primary statistical analysis after omitting the missing values. Participants' median age was 32.0 years (Interquartile Range: 24.0, 39.0). In total, 22 (9.5%) of the participant reported depression. Females have shown significantly higher odds of reporting depression than males with an odds ratio = 3.2 (95% CI:1.17, 8.88), and there were approximately 5-fold higher odds of reporting depression for unhappy than for happy individuals. For one interquartile-range increase in age and BMI, the odds ratio of reporting depression was 0.34 (95% CI: 0.1, 1.0) and 1.8 (95% CI: 0.97, 3.32) respectively. CONCLUSION/CONCLUSIONS:Females are more likely to report depression compared to males. Increasing age may decrease the risk of reporting depression. Unhappy individuals have approximately 5-fold higher odds of reporting depression compared to happy individuals. A higher BMI was associated with a higher risk of reporting depression. In a sensitivity analysis, individuals who reported less than 6 h of sleep per 24 h were more likely to report depression than those who reported 7 h of sleep.

BACKGROUND:Financial distress is a barrier to cessation among low-income smokers. OBJECTIVE:To evaluate an intervention that integrated financial coaching and benefits referrals into a smoking cessation program for low-income smokers. DESIGN/METHODS:Randomized waitlist control trial conducted from 2017 to 2019. PARTICIPANTS/METHODS:Adult New York City residents were eligible if they reported past 30-day cigarette smoking, had income below 200% of the federal poverty level, spoke English or Spanish, and managed their own funds. Pregnant or breastfeeding people were excluded. Participants were recruited from two medical centers and from the community. INTERVENTION/METHODS:The intervention (n = 208) offered smoking cessation coaching, nicotine replacement therapy, money management coaching, and referral to financial benefits and empowerment services. The waitlist control (n=202) was usual care during a 6-month waiting period. MAIN MEASURES/METHODS:Treatment engagement, self-reported 7-day abstinence, and financial stress at 6 months. KEY RESULTS/RESULTS:At 6 months, intervention participants reported higher abstinence (17% vs. 9%, P=0.03), lower stress about finances (β, -0.8 [SE, 0.4], P=0.02), and reduced frequency of being unable to afford activities (β, -0.8 [SE, 0.4], P=0.04). Outcomes were stronger among participants recruited from the medical centers (versus from the community). Among medical center participants, the intervention was associated with higher abstinence (20% vs. 8%, P=0.01), higher satisfaction with present financial situation (β, 1.0 [SE, 0.4], P=0.01), reduced frequency of being unable to afford activities (β, -1.0 [SE, 0.5], P=0.04), reduced frequency in getting by paycheck-to-paycheck (β, -1.0 [SE, 0.4], P=0.03), and lower stress about finances in general (β, -1.0 [SE, 0.4], P = 0.02). There were no group differences in outcomes among people recruited from the community (P>0.05). CONCLUSIONS:Among low-income smokers recruited from medical centers, the intervention produced higher abstinence rates and reductions in some markers of financial distress than usual care. The intervention was not efficacious with people recruited from the community. TRIAL REGISTRATION/BACKGROUND:ClinicalTrials.gov Identifier: NCT03187730.

Limited studies have focused on maternal early-life risk factors and the later development of gestational diabetes mellitus (GDM). We aimed to estimate the GDM prevalence and examine the associations of maternal early-life risk factors, namely: maternal birthweight, parental smoking at birth, childhood urbanicity, ever-breastfed, parental education attainment, parental history of diabetes, childhood overall health, childhood body size, and childhood height, with later GDM. This was a retrospective cross-sectional study using the UAE Healthy Future Study (UAEHFS) baseline data (February 2016 to April 2022) on 702 ever-married women aged 18 to 67 years. We fitted a Poisson regression to estimate the risk ratio (RR) for later GDM and its 95% confidence interval (CI). The GDM prevalence was 5.1%. In the fully adjusted model, females with low birthweight were four times more likely (RR 4.04, 95% CI 1.36-12.0) and females with a parental history of diabetes were nearly three times more likely (RR 2.86, 95% CI 1.10-7.43) to report later GDM. In conclusion, maternal birthweight and parental history of diabetes were significantly associated with later GDM. Close glucose monitoring during pregnancy among females with either a low birth weight and/or parental history of diabetes might help to prevent GDM among this high-risk group.