Validation of Different Dementia Code-based Definitions in a Population-based Study of Rheumatoid Arthritis.

OBJECTIVE: Rheumatoid arthritis (RA) has been associated with an elevated dementia risk. The study aimed to examine how different diagnostic dementia definitions perform in those with RA compared to individuals without RA. METHODS: This study population included 2050 individuals (1025 with RA) from a retrospective population-based cohort in southern Minnesota and compared the performance of three code-based dementia diagnostic algorithms with medical record review diagnosis of dementia. For the overall comparison, no time frames were used, and each patient's complete medical history was used. Sensitivity analyses were performed using 1, 2, and 5-year windows around the date that dementia was identified in the medical record (reference standard). RESULTS: Algorithms performed very similarly in persons with and without RA. The algorithms generally had high specificity, negative predictive values, and accuracy, regardless of the time window studied (>88%). Sensitivity and positive predictive values varied depending on the algorithm and the time window studied. Sensitivity values ranged from 56.5% to 95.9%, and positive predictive values ranged from 55.2% to 83.1%. Performance measures declined with more restrictive time windows. CONCLUSION: Routinely collected electronic health record (EHR) data was used to define code-based dementia diagnosis algorithms with good performance (vs. diagnosis by medical record review). These results can inform future studies that use retrospective databases (especially in the same or similar EHR infrastructure) to identify dementia in individuals with RA.

FedFSA: Hybrid and federated framework for functional status ascertainment across institutions.

INTRODUCTION: Patients' functional status assesses their independence in performing activities of daily living, including basic ADLs (bADL), and more complex instrumental activities (iADL). Existing studies have discovered that patients' functional status is a strong predictor of health outcomes, particularly in older adults. Depite their usefulness, much of the functional status information is stored in electronic health records (EHRs) in either semi-structured or free text formats. This indicates the pressing need to leverage computational approaches such as natural language processing (NLP) to accelerate the curation of functional status information. In this study, we introduced FedFSA, a hybrid and federated NLP framework designed to extract functional status information from EHRs across multiple healthcare institutions. METHODS: FedFSA consists of four major components: 1) individual sites (clients) with their private local data, 2) a rule-based information extraction (IE) framework for ADL extraction, 3) a BERT model for functional status impairment classification, and 4) a concept normalizer. The framework was implemented using the OHNLP Backbone for rule-based IE and open-source Flower and PyTorch library for federated BERT components. For gold standard data generation, we carried out corpus annotation to identify functional status-related expressions based on ICF definitions. Four healthcare institutions were included in the study. To assess FedFSA, we evaluated the performance of category- and institution-specific ADL extraction across different experimental designs. RESULTS: ADL extraction performance ranges from an F1-score of 0.907 to 0.986 for bADL and 0.825 to 0.951 for iADL across the four healthcare sites. The performance for ADL extraction with impairment ranges from an F1-score of 0.722 to 0.954 for bADL and 0.674 to 0.813 for iADL across four healthcare sites. For category-specific ADL extraction, laundry and transferring yielded relatively high performance, while dressing, medication, bathing, and continence achieved moderate-high performance. Conversely, food preparation and toileting showed low performance. CONCLUSION: NLP performance varied across ADL categories and healthcare sites. Federated learning using a FedFSA framework performed higher than non-federated learning for impaired ADL extraction at all healthcare sites. Our study demonstrated the potential of the federated learning framework in functional status extraction and impairment classification in EHRs, exemplifying the importance of a large-scale, multi-institutional collaborative development effort.

Exploring social determinants of health and physical activity levels in older adults living with mild cognitive impairment and dementia in the Upper Midwest of the United States.

BACKGROUND: Physical activity can improve physical health for people living with mild cognitive impairment (MCI) and dementia and may have cognitive benefits. Identifying modifiable social factors inhibiting physical activity among this group is needed. We sought to examine the relationship between reported physical activity levels and social determinants of health (SDOH) in a population of older adults living with MCI or dementia. METHODS: This descriptive study included people with a diagnosis of MCI or dementia followed by Community Internal Medicine at Mayo Clinic (Rochester, Minnesota, United States), aged over 55 years, who had a clinic visit between June 1, 2019 and June 30, 2021 and had completed a SDOH questionnaire. We focused on 8 SDOH domains: education, depression, alcohol use, stress, financial resource strain, social connections, food insecurity, and transportation needs. Data were analyzed based on physical activity level (inactive, insufficiently active, sufficiently active). SDOH domains were compared according to physical activity level using the χ2 test and multinomial logistic regression. RESULTS: A total of 3224 persons with MCI (n = 1371) or dementia (n = 1853) who had completed questions on physical activity were included. Of these, 1936 (60%) were characterized as physically inactive and 837 (26%) insufficiently active. Characteristics associated with an increased likelihood of physical inactivity were older age, female sex, obesity, lower education, dementia diagnosis, screening positive for depression and increased social isolation (p < 0.001). CONCLUSIONS: Physical inactivity is common among people living with MCI and dementia. Physical activity levels may be influenced by many factors, highlighting potential areas for intervention.

Association of socio-demographic characteristics with alcohol use initiation among never users during the COVID-19 pandemic: a longitudinal study.

BACKGROUND: In this longitudinal cohort study, we examined the socio-demographic and psychological predictors of alcohol use initiation during the COVID-19 pandemic in a sample of never alcohol users aged ≥21 prior to COVID-19. METHODS: Our study population consisted of 56 930 patients aged ≥21, as of 30 March 2019 were collected from a pre-COVID period of 1 year before 31 March 2020, and during-COVID, a period between 1 April 2020 and 30 March 2021. Univariable and multivariable logistic regression models were utilized to examine the roles of socio-demographic variables (gender, age, education, Area Deprivation Index and rural residence) changes in anxiety and depression severity as predictors of alcohol use initiation. RESULTS: Age, gender, race, ethnicity, education and rural status were significant predictors in multivariable analysis. A subgroup analysis showed neither anxiety nor depression had a significant association with alcohol use initiation. CONCLUSION: Women, younger individuals, those living in a rural area and people who smoke cigarettes were more likely to initiate alcohol use during the pandemic. Our study has public health and clinical implications such as the need for targeted alcohol use screening and intervention for vulnerable individuals.

Longitudinal factors associated with increased alcohol consumption in adults during the COVID-19 pandemic.

Background: Alcohol is the most abused substance among adults in the United States. The COVID-19 pandemic impacted patterns of alcohol use, but data are conflicting, and previous studies are largely limited to cross-sectional analyses.Objective: This study aimed to longitudinally assess sociodemographic and psychological correlates of changes in three patterns of alcohol use (number of alcoholic drinks, drinking regularity, and binge drinking) during COVID-19.Methods: We studied changes in self-reported drinking behaviors in 222,195 Mayo Clinic patients over 21 years of age (58.1% female and 41.9% male) between April 1, 2019, and March 30, 2021. Logistic regression models were used to estimate associations between patient characteristics and change in alcohol consumption.Results: Sociodemographically younger age, White race, having a college degree, and living in a rural area were associated with increased alcohol use regularity (all p < .05). Younger age, male, White, high-school education or less, living in a more deprived neighborhood, smoking, and living in a rural area were associated with increases in number of alcohol drinks (all p ≤ .04) and binge drinking (all p ≤ .01). Increased anxiety scores were associated with increased number of drinks, while depression severity was associated with both increased drinking regularity and increased number of drinks (all p ≤ .02) independent of sociodemographic characteristics.Conclusion: Our study showed that both sociodemographic and psychological characteristics were associated with increased alcohol consumption patterns during the COVID-19 pandemic. Our study highlights specific target groups previously not described in the literature for alcohol interventions based on sociodemographic and psychological characteristics.

Identification of sex-specific genetic associations in response to opioid analgesics in a White, non-Hispanic cohort from Southeast Minnesota.

The study of sex-specific genetic associations with opioid response may improve the understanding of inter-individual variability in pain treatments. We investigated sex-specific associations between genetic variation and opioid response. We identified participants in the RIGHT Study prescribed codeine, tramadol, hydrocodone, and oxycodone between 01/01/2005 and 12/31/2017. Prescriptions were collapsed into codeine/tramadol and hydrocodone/oxycodone. Outcomes included poor pain control and adverse reactions within six weeks after prescription date. We performed gene-level and single-variant association analyses stratified by sex. We included 7169 non-Hispanic white participants and a total of 1940 common and low-frequency variants (MAF > 0.01). Common variants in MACROD2 (rs76026520), CYP1B1 (rs1056837, rs1056836), and CYP2D6 (rs35742686) were associated with outcomes. At the gene level, FAAH, SCN1A, and TYMS had associations for men and women, and NAT2, CYP3A4, CYP1A2, and SLC22A2 had associations for men only. Our findings highlight the importance of considering sex in association studies on opioid response.

Implementation of preemptive DNA sequence-based pharmacogenomics testing across a large academic medical center: The Mayo-Baylor RIGHT 10K Study.

PURPOSE: The Mayo-Baylor RIGHT 10K Study enabled preemptive, sequence-based pharmacogenomics (PGx)-driven drug prescribing practices in routine clinical care within a large cohort. We also generated the tools and resources necessary for clinical PGx implementation and identified challenges that need to be overcome. Furthermore, we measured the frequency of both common genetic variation for which clinical guidelines already exist and rare variation that could be detected by DNA sequencing, rather than genotyping. METHODS: Targeted oligonucleotide-capture sequencing of 77 pharmacogenes was performed using DNA from 10,077 consented Mayo Clinic Biobank volunteers. The resulting predicted drug response-related phenotypes for 13 genes, including CYP2D6 and HLA, affecting 21 drug-gene pairs, were deposited preemptively in the Mayo electronic health record. RESULTS: For the 13 pharmacogenes of interest, the genomes of 79% of participants carried clinically actionable variants in 3 or more genes, and DNA sequencing identified an average of 3.3 additional conservatively predicted deleterious variants that would not have been evident using genotyping. CONCLUSION: Implementation of preemptive rather than reactive and sequence-based rather than genotype-based PGx prescribing revealed nearly universal patient applicability and required integrated institution-wide resources to fully realize individualized drug therapy and to show more efficient use of health care resources.

Longitudinal Correlates of Increased Alcohol Use Among Adolescents and Young Adults During the COVID-19 Pandemic.

AIMS: The objective of this study is to longitudinally assess sociodemographic and psychological correlates of increased alcohol use during the coronavirus disease of 2019 (COVID-19) period among adolescents and young adults. METHODS: Pre-COVID period is defined as the 1-year period on or before 31 March 2020, and during-COVID period is defined as the period from 1st April 2020 to 30 March 2021. Univariable logistic regression models are used to evaluate the association of demographic characteristics, Area Deprivation Index (ADI), rurality, changes in Patient Health Questionnaire (PHQ-9) and Generalized Anxiety Disorder (GAD-7) scale severity, and the risk of increased alcohol consumption (binge drinking, number of drinks and drinking regularity) from pre-COVID to during-COVID period. RESULTS AND CONCLUSION: Our study found that worsened anxiety symptoms, older age, being in college and current cigarette smoking status were associated with increased alcohol use among youth during the pandemic year. Socioeconomic position (measured by ADI) and rural status were not found to be associated with increased alcohol use among adolescents and young adults.

Systematic review of the evidence on the cost-effectiveness of pharmacogenomics-guided treatment for cardiovascular diseases.

PURPOSE: To examine the evidence on the cost-effectiveness of implementing pharmacogenomics (PGx) in cardiovascular disease (CVD) care. METHODS: We conducted a systematic review using multiple databases from inception to 2018. The titles and abstracts of cost-effectiveness studies on PGx-guided treatment in CVD care were screened, and full texts were extracted. RESULTS: We screened 909 studies and included 46 to synthesize. Acute coronary syndrome and atrial fibrillation were the predominantly studied conditions (59%). Most studies (78%) examined warfarin-CYP2C9/VKORC1 or clopidogrel-CYP2C19. A payer's perspective was commonly used (39%) for cost calculations, and most studies (46%) were US-based. The majority (67%) of the studies found PGx testing to be cost-effective in CVD care, but cost-effectiveness varied across drugs and conditions. Two studies examined PGx panel testing, of which one examined pre-emptive testing strategies. CONCLUSION: We found mixed evidence on the cost-effectiveness of PGx in CVD care. Supportive evidence exists for clopidogrel-CYP2C19 and warfarin-CYP2C9/VKORC1, but evidence is limited in other drug-gene combinations. Gaps persist, including unclear explanation of perspective and cost inputs, underreporting of study design elements critical to economic evaluations, and limited examination of PGx panel and pre-emptive testing for their cost-effectiveness. This review identifies the need for further research on economic evaluations of PGx implementation.

Known-groups validity and responsiveness to change of the Patient Experience with Treatment and Self-management (PETS vs. 2.0): a patient-reported measure of treatment burden.

PURPOSE: The purpose of this study was to test the known-groups validity and responsiveness to change of the Patient Experience with Treatment and Self-management (PETS, vs. 2.0), a measure of treatment burden. METHODS: The PETS and other standard measures were mailed at baseline and 12-month follow-up to adults living with multiple chronic conditions in southeast Minnesota (USA). A sample of 365 people (mean age = 62.1 years) completed both surveys. Baseline, 12-month, and changes in PETS burden scores were examined. Clinical anchors used to test validity included number of diagnoses (2-4 vs. 5+), mental health diagnosis (yes/no), medication adherence and health literacy (suboptimal/optimal), and changes in self-efficacy, global physical, and global mental health (worsening/improving). Independent-samples t-tests were used to compare scores. RESULTS: PETS scales showed good internal consistency (αs ≥ 0.80). There were few differences across number of diagnoses, but having a mental health diagnosis was associated with higher baseline PETS burden scores (Ps < .05). Suboptimal medication adherence and health literacy over time were associated with worse 12-month PETS burden scores (Ps < .05). Compared with improvements, declines over time in self-efficacy, global physical health, and global mental health were each associated with worsening change scores on PETS impact summary, medical expenses, and bother due to medication reliance and medication side effects (Ps < .05). CONCLUSION: Among multi-morbid adults, the PETS demonstrated evidence of known-groups validity and responsiveness to change across both objective (e.g., mental health diagnoses) and subjective anchors (e.g., changes in self-efficacy, global physical, and global mental health).

Correction to: Neighborhood socioeconomic disadvantage is associated with multimorbidity in a geographically-defined community.

An amendment to this paper has been published and can be accessed via the original article.

Neighborhood socioeconomic disadvantage is associated with multimorbidity in a geographically-defined community.

BACKGROUND: Persons with low socioeconomic status may be disproportionately at risk for multimorbidity. METHODS: Adults aged ≥20 years on 4/1/2015 from 7 counties in Minnesota were identified using the Rochester Epidemiology Project (population-based sample). A composite measure of neighborhood socioeconomic disadvantage, the area deprivation index (ADI), was estimated at the census block group level (n = 251). The prevalence of 21 chronic conditions was obtained to calculate the proportion of persons with multimorbidity (≥2 chronic conditions) and severe multimorbidity (≥5 chronic conditions). Hierarchical logistic regression was used to estimate the association of ADI with multimorbidity and severe multimorbidity using odds ratios (OR). RESULTS: Among 198,941 persons (46.7% male, 30.6% aged ≥60 years), the age- and sex-standardized (to the United States 2010 census) median prevalence (Q1, Q3) was 23.4% (21.3%, 25.9%) for multimorbidity and 4.8% (4.0%, 5.7%) for severe multimorbidity. Compared with persons in the lowest quintile of ADI, persons in the highest quintile had a 50% increased risk of multimorbidity (OR 1.50, 95% CI 1.39-1.62) and a 67% increased risk of severe multimorbidity (OR 1.67, 95% CI 1.51-1.86) after adjusting for age, sex, race, and ethnicity. Associations were stronger after further adjustment for individual level of education; persons in the highest quintile had a 78% increased risk of multimorbidity (OR 1.78, 95% CI 1.62-1.96) and a 92% increased risk of severe multimorbidity (OR 1.92, 95% CI 1.72-2.13). There was evidence of interactions between ADI and age, between ADI and sex, and between ADI and education. After age 70 years, no difference in the risk of multimorbidity was observed across quintiles of ADI. The pattern of increasing multimorbidity with increasing ADI was more pronounced in women. Finally, there was less variability across quintiles of ADI for the most highly educated group. CONCLUSIONS: Higher ADI was associated with increased risk of multimorbidity, and the associations were strengthened after adjustment for individual level of education, suggesting that neighborhood context plays a role in health above and beyond individual measures of socioeconomic status. Furthermore, associations were more pronounced in younger persons and women, highlighting the importance of interventions to prevent chronic conditions in younger women, in particular.

Early temporal characteristics of elderly patient cognitive impairment in electronic health records.

BACKGROUND: The aging population has led to an increase in cognitive impairment (CI) resulting in significant costs to patients, their families, and society. A research endeavor on a large cohort to better understand the frequency and severity of CI is urgent to respond to the health needs of this population. However, little is known about temporal trends of patient health functions (i.e., activity of daily living [ADL]) and how these trends are associated with the onset of CI in elderly patients. Also, the use of a rich source of clinical free text in electronic health records (EHRs) to facilitate CI research has not been well explored. The aim of this study is to characterize and better understand early signals of elderly patient CI by examining temporal trends of patient ADL and analyzing topics of patient medical conditions in clinical free text using topic models. METHODS: The study cohort consists of physician-diagnosed CI patients (n = 1,435) and cognitively unimpaired (CU) patients (n = 1,435) matched by age and sex, selected from patients 65 years of age or older at the time of enrollment in the Mayo Clinic Biobank. A corpus analysis was performed to examine the basic statistics of event types and practice settings where the physician first diagnosed CI. We analyzed the distribution of ADL in three different age groups over time before the development of CI. Furthermore, we applied three different topic modeling approaches on clinical free text to examine how patients' medical conditions change over time when they were close to CI diagnosis. RESULTS: The trajectories of ADL deterioration became steeper in CI patients than CU patients approximately 1 to 1.5 year(s) before the actual physician diagnosis of CI. The topic modeling showed that the topic terms were mostly correlated and captured the underlying semantics relevant to CI when approaching to CI diagnosis. CONCLUSIONS: There exist notable differences in temporal trends of basic and instrumental ADL between CI and CU patients. The trajectories of certain individual ADL, such as bathing and responsibility of own medication, were closely associated with CI development. The topic terms obtained by topic modeling methods from clinical free text have a potential to show how CI patients' conditions evolve and reveal overlooked conditions when they close to CI diagnosis.

Rochester Epidemiology Project Data Exploration Portal.

INTRODUCTION: The goal of this project was to develop an interactive, web-based tool to explore patterns of prevalence and co-occurrence of diseases using data from the expanded Rochester Epidemiology Project (E-REP) medical records-linkage system. METHODS: We designed the REP Data Exploration Portal (REP DEP) to include summary information for people who lived in a 27-county region of southern Minnesota and western Wisconsin on January 1, 2014 (n = 694,506; 61% of the entire population). We obtained diagnostic codes of the International Classification of Diseases, 9th edition, from the medical records-linkage system in 2009 through 2013 (5 years) and grouped them into 717 disease categories. For each condition or combination of 2 conditions (dyad), we calculated prevalence by dividing the number of persons with a specified condition (numerator) by the total number of persons in the population (denominator). We calculated observed-to-expected ratios (OERs) to test whether 2 conditions co-occur more frequently than would co-occur as a result of chance alone. RESULTS: We launched the first version of the REP DEP in May 2017. The REP DEP can be accessed at http://rochesterproject.org/portal/. Users can select 2 conditions of interest, and the REP DEP displays the overall prevalence, age-specific prevalence, and sex-specific prevalence for each condition and dyad. Also displayed are OERs overall and by age and sex and maps of county-specific prevalence of each condition and OER. CONCLUSION: The REP DEP draws upon a medical records-linkage system to provide an innovative, rapid, interactive, free-of-charge method to examine the prevalence and co-occurrence of 717 diseases and conditions in a geographically defined population.

Participant-perceived understanding and perspectives on pharmacogenomics: the Mayo Clinic RIGHT protocol (Right Drug, Right Dose, Right Time).

PURPOSE: To examine predictors of understanding preemptive CYP2D6 pharmacogenomics test results and to identify key features required to improve future educational efforts of preemptive pharmacogenomics testing. METHODS: One thousand ten participants were surveyed after receiving preemptive CYP2D6 pharmacogenomics test results. RESULTS: Eighty-six percent (n = 869) of patients responded. Of the responders, 98% were white and 55% were female; 57% had 4 years or more of post-secondary education and an average age of 58.9 ± 5.5 years. Twenty-six percent said that they only somewhat understood their results and 7% reported they did not understand them at all. Only education predicted understanding. The most common suggestion for improvement was the use of layperson's terms when reporting results. In addition, responders suggested that results should be personalized by referring to medications that they were currently using. Of those reporting imperfect drug adherence, most (91%) reported they would be more likely to use medication as prescribed if pharmacogenomic information was used to help select the drug or dose. CONCLUSION: Despite great efforts to simplify pharmacogenomic results (or because of them), approximately one-third of responders did not understand their results. Future efforts need to provide more examples and tailor results to the individual. Incorporation of pharmacogenomics is likely to improve medication adherence.Genet Med advance online publication 05 January 2017.

Multidisciplinary model to implement pharmacogenomics at the point of care.

PURPOSE: Despite potential clinical benefits, implementation of pharmacogenomics (PGx) faces many technical and clinical challenges. These challenges can be overcome with a comprehensive and systematic implementation model. METHODS: The development and implementation of PGx were organized into eight interdependent components addressing resources, governance, clinical practice, education, testing, knowledge translation, clinical decision support (CDS), and maintenance. Several aspects of implementation were assessed, including adherence to the model, production of PGx-CDS interventions, and access to educational resources. RESULTS: Between August 2012 and June 2015, 21 specific drug-gene interactions were reviewed and 18 of them were implemented in the electronic medical record as PGx-CDS interventions. There was complete adherence to the model with variable production time (98-392 days) and delay time (0-148 days). The implementation impacted approximately 1,247 unique providers and 3,788 unique patients. A total of 11 educational resources complementary to the drug-gene interactions and 5 modules specific for pharmacists were developed and implemented. CONCLUSION: A comprehensive operational model can support PGx implementation in routine prescribing. Institutions can use this model as a roadmap to support similar efforts. However, we also identified challenges that will require major multidisciplinary and multi-institutional efforts to make PGx a universal reality.Genet Med 19 4, 421-429.

Telephone triage utilization among patients with limited English proficiency.

BACKGROUND: Communication between patients with limited English proficiency (LEP) and telephone triage services has not been previously explored. The purpose of this study was to determine the utilization characteristics of a primary care triage call center by patients with LEP. METHODS: This was a retrospective cohort study of the utilization of a computer-aided, nurse-led telephone triage system by English proficiency status of patients empaneled to a large primary care practice network in the Midwest United States. Interpreter Services (IS) need was used as a proxy for LEP. RESULTS: Call volumes between the 587 adult patients with LEP and an age-frequency matched cohort of English-Proficient (EP) patients were similar. Calls from patients with LEP were longer and more often made by a surrogate. Patients with LEP received recommendations for higher acuity care more frequently (49.4% versus 39.0%; P < 0.0004), and disagreed with recommendations more frequently (30.1% versus 20.9%; P = 0.0004). These associations remained after adjustment for comorbidities. Patients with LEP were also less likely to follow recommendations (60.9% versus 69.4%; P = 0.0029), even after adjusting for confounders (adjusted odds ratio [AOR] = 0.65; 95% confidence interval [CI], 0.49, 0.85; P < 0.001). CONCLUSION: Patients with LEP who utilized a computer-aided, nurse-led telephone triage system were more likely to receive recommendations for higher acuity care compared to EP patients. They were also less likely to agree with, or follow, recommendations given. Additional research is needed to better understand how telephone triage can better serve patients with LEP.

Younger age at initiation of the human papillomavirus (HPV) vaccination series is associated with higher rates of on-time completion.

Vaccination rates for human papillomavirus (HPV) have remained disappointingly low. It is critical to identify methods to increase on-time vaccine series completion rates (before 13 or 15years). To determine whether younger age (9 to 10years of age) at HPV vaccine series initiation was associated with improved on-time completion rates compared to initiation at 11 to 12years, we examined the prevalence of on-time HPV vaccine series completion rates from August 2006 through December 2012 in a large, population-based cohort of children and adolescents (aged 9.5 to 27years) residing in Olmsted County, MN on December 31, 2012 (n=36,223). We compared age at vaccine initiation between individuals who successfully completed both 2 and 3 doses of the vaccination series on-time (before age 13.5 or 15.0years) using multivariate logistic regression. On-time completion of both 2 and 3 doses of the vaccine series by age 13.5 or 15.0years was significantly associated with initiation at 9 to 10years as compared to 11 to 12years after adjusting for sex, race, insurance status, frequent health care visits, and year of first vaccination (all p<.01). Interventions focused on beginning the vaccination series at 9 to 10years of age may result in higher rates of timely series completion.

Associations Between Anxiety Disorder Diagnoses and Body Mass Index Differ by Age, Sex and Race: A Population Based Study.

BACKGROUND: Few large studies have examined correlations between anxiety and body mass index (BMI) by gender or racial groups using clinical data. OBJECTIVE: This study aimed to determine associations between diagnosed anxiety disorders and BMI, and evaluate whether observed associations varied by demographic characteristics. METHOD: Data from the Rochester Epidemiology Project (REP) data linkage system were analyzed to examine associations between anxiety disorders and BMI among adults ages 18-85 residing in Olmsted County, MN in 2009 (n=103,557). Height and weight data were available for 75,958 people (73%). The international classification of underweight, overweight, and obesity by BMI was used. RESULTS: Population consisted of 56% females, 92.8% White individuals, with median age of 46 years. When adjusted for age, sex, and race, we observed a U-shaped association between anxiety and BMI group. Underweight and obese individuals were more likely to have an anxiety diagnosis compared to normal weight individuals. Stratification by sex yielded a U-shaped association between anxiety and BMI only in women. Stratification by race showed a U-shaped association between anxiety and BMI only in the White population. Anxiety was significantly associated only with obesity in the Black population. Anxiety was not associated with a BMI category in Asian or Hispanic groups. Among elderly group, there is inverse correlation between anxiety and obesity. CONCLUSION: Our results suggest that anxiety may have heterogeneous associations with BMI in the population. Further research on potential mechanisms contributing to these findings will help direct efforts in anxiety and obesity management across diverse population groups.