Understanding Predictors of Fatigue Over Time in Persons With Inflammatory Bowel Disease: The Importance of Depressive and Anxiety Symptoms.

INTRODUCTION: Fatigue is a complex and frequent symptom in persons with inflammatory bowel disease (IBD), with detrimental impact. We aimed to determine predictors of fatigue over time. METHODS: Two hundred forty-seven adults with IBD participated in a prospective study conducted in Manitoba, Canada, providing data at baseline and annually for 3 years. Participants reported fatigue impact (Daily Fatigue Impact Scale [DFIS]), depression and anxiety symptoms (Hospital Anxiety and Depression Scale [HADS]), and pain (Pain Effects Scale [PES]). Physician-diagnosed comorbidities, IBD characteristics, and physical and cognitive functioning were also assessed. We tested factors associated with fatigue using multivariable generalized linear models that estimated within-person and between-person effects. RESULTS: Most participants were women (63.2%), White (85.4%), and had Crohn's disease (62%). At baseline, 27.9% reported moderate-severe fatigue impact, 16.7% had clinically elevated anxiety (HADS-A ≥11), and 6.5% had clinically elevated depression (HADS-D ≥11). Overall fatigue burden was stable over time, although approximately half the participants showed improved or worsening fatigue impact between annual visits during the study. On multivariable analysis, participants with a one-point higher HADS-D score had, on average, a 0.63-point higher DFIS score, whereas participants with a one-point higher PES score had a 0.78-point higher DFIS score. Within individuals, a one-point increase in HADS-D scores was associated with 0.61-point higher DFIS scores, in HADS-A scores with 0.23-point higher DFIS scores, and in PES scores with 0.38-point higher DFIS scores. No other variables predicted fatigue. DISCUSSION: Anxiety, depression, and pain predicted fatigue impact over time in IBD, suggesting that targeting psychological factors and pain for intervention may lessen fatigue burden.

Health Care Utilization and Direct Costs Prior to Subspecialty Care in Children with Chronic Pain Compared with Other Chronic Childhood Diseases: A Cohort Study.

OBJECTIVES: To understand the burden associated with pediatric chronic pain (CP) on the health care system compared with other costly chronic diseases prior to subspecialty care. STUDY DESIGN: In this retrospective cohort study, we assessed all-cause health care utilization and direct health care costs associated with pediatric CP (n = 91) compared with juvenile arthritis (n = 135), inflammatory bowel disease (n = 90), type 1 diabetes (n = 475) or type 2 diabetes (n = 289), anxiety (n = 7193), and controls (n = 273) 2 and 5 years prior to patients entering subspecialty care in Manitoba, Canada. Linked data from physician encounters, emergency department visits, hospitalizations, and prescriptions were extracted from administrative databases. Differences in health care utilization and direct health care costs associated with CP vs the other conditions were tested using negative binomial and zero-inflated negative binomial regression models, respectively. RESULTS: After adjustment for age at diagnosis, sex, location of residence, and socioeconomic status, CP continued to be associated with the highest number of consulted physicians and subspecialists and the highest number of physician billings compared with all other conditions (P < .01, respectively). CP was significantly associated with higher physician costs than juvenile arthritis, inflammatory bowel disease, type 1 diabetes, type 2 diabetes, or controls (P < .01, respectively); anxiety was associated with the highest physician and prescription costs among all cohorts (P < .01, respectively). CONCLUSION: Compared with chronic inflammatory and endocrinologic conditions, pediatric CP and anxiety were associated with substantial burden on the health care system prior to subspecialty care, suggesting a need to assess gaps and resources in the management of CP and mental health conditions in the primary care setting.

Introduction of an order set after hip fracture improves osteoporosis medication initiation and persistence: a population-based before-after analysis.

We found that a standardized order set after hip fracture increased initiation of anti-osteoporosis medication and increased persistence at 1 year, but did not reduce secondary fractures. BACKGROUND: A treatment gap exists after osteoporosis-related fractures. Introducing standardized care can improve treatment. We evaluated the impact of a hip fracture order set (OS) on anti-osteoporosis medication (AOM) initiation, persistence, and secondary fracture prevention. METHODS: In 2015, one hospital in Manitoba, Canada, introduced a hip fracture OS including recommendations for the initiation of AOM (OS group). A control group was identified from the other hospitals in the same region. A retrospective cohort study was conducted using linked administrative health data. All individuals 50 + years with surgical treatment for low-energy hip fracture between 2010 and 2019 were included and followed for AOM initiation, medication persistence at 1 year, and secondary fractures. Between-group differences for each year were assessed using chi-square tests. Logistic regression models tested the impact of socio-demographic and clinical factors on initiation, persistence of AOM. Cox regression tested the risk of secondary fracture. RESULTS: No baseline differences between OS group (813 patients) and control group (2150 patients) were observed in demographics, socioeconomic factors, or comorbidities. An increase in post-fracture AOM initiation was seen with OS introduction (OS group year before 16.7% versus year after 48.6%, p < 0.001). No change was seen in the control group. Persistence on AOM also increased (OS group year before 17.7% versus year after 28.4%, p < 0.001). No difference in secondary fractures was observed (OS group 19.8% versus control group 18.8%, p = 0.38). CONCLUSION: Introduction of a hip fracture OS significantly increased AOM initiation and persistence at 1-year post-fracture. There was no significant difference in secondary fractures.

Secular Trends in Peak Bone Mineral Density: The National Health and Nutrition Examination Survey 1999-2018.

Peak bone mineral density (BMD) is one of the most important factors influencing the development of osteoporosis. It was predicted that a 10% increase in peak BMD will delay the onset of osteoporosis by 13 years. However, changes in peak BMD over time are unknown. This study aimed to investigate secular trends in peak BMD among young adults in the United States. Based on the National Health and Nutrition Examination Survey from 1999-2018, 3,975 males aged 19-28 years and 2370 females aged 31-40 years were our target population for estimating peak lumbar spine BMD. BMD was measured by dual-energy X-ray absorptiometry. Generalized linear models adjusted for multiple covariates were used to examine the secular trends in peak BMD in males and females, respectively. Secular trends for peak lumbar spine BMD from 1999-2000 to 2017-2018 were not statistically significant in males or females (all Plinear and Pquadratic > 0.05). Similar results were observed in race/ethnicity subgroups (all Plinear and Pquadratic > 0.05). However, in stratified analyses by obesity category, peak lumbar spine BMD in obese males and females increased from 1999-2000 to 2009-2010 and then decreased until 2017-2018, while peak lumbar spine BMD in non-obese females decreased from 1999-2000 to 2005-2006 and then increased until 2017-2018 (all Pquadratic < 0.05). Peak lumbar spine BMD was greater in obese males and females than in non-obese males and females up to 2009-2010, but not from 2011-2012 onwards. Overall, there were no significant secular trends in peak lumbar spine BMD. However, secular trends differed between obese and non-obese groups.

Understanding the Intersection of Identity and Cancer Experience Among Racially, Ethnically, Gender and Sexual Minoritized Adolescents and Young Adults With Cancer.

OBJECTIVES: Adolescents and young adults (AYAs, 18-39 years) with cancer identifying as racially/ethnically minoritized or 2SLGBTQIA+ (Two-Spirit, lesbian, gay, bisexual, transgender, queer, intersex, asexual and "+" referring to other queer identities) have been underrepresented in cancer research. This study explores the aspects of identity that hold significance for these minoritized AYAs and how these facets impact their healthcare experiences. METHODS: Eligible participants comprised English-speaking AYAs who self-identified as racially/ethnically minoritized and/or 2SLGBTQIA+, were diagnosed with cancer between the ages of 15-39, currently aged > 18, and had received or were receiving cancer care within Canadian healthcare system. Additionally, four patient partners meeting the same criteria were recruited as research collaborators. Semi-structured one-on-one virtual interviews guided by an interview script were conducted, and qualitative analysis employed a framework approach. RESULTS: We recruited 23 participants from 4 Canadian provinces (mean age: 28, Range: 20-44); 17 identified as racially/ethnically minoritized, one as sexual/gender minoritized, and five as racially/ethnically and sexually/gender minoritized. Participants emphasized that their culture/ethnicity, religion/spirituality, sexuality, gender, family, career, and being an immigrant are important aspects of their identity, with only one participant recognizing their identity as a "person with cancer". A cancer diagnosis altered the aspects of identity deemed most significant by participants. Both visible and invisible aspects of identity shaped participants' experiences and influenced their level of trust in the healthcare system. CONCLUSION: Racially, ethnically, gender, or sexually minoritized AYAs with cancer place considerable importance on aspects of their identity that are shaped by their respective communities. Recognizing and respecting these identities are paramount for healthcare professionals to deliver safe and inclusive care.

Screening for depression in patients with epilepsy: same questions but different meaning to different patients.

PURPOSE: Patient-reported outcome measures (PROMs) such as the Neurological Disorders Depression Inventory in Epilepsy (NDDI-E), a 6-item epilepsy-specific PROM, is used to screen for major depressive disorder symptoms for patients with epilepsy (PWE). The validity and interpretation of PROMs can be affected by differential item functioning (DIF), which occurs when subgroups of patients with the same underlying health status respond to and interpret questions about their health status differently. This study aims to determine whether NDDI-E items exhibit DIF and to identify subgroups of PWE that exhibit DIF in NDDI-E items. METHODS: Data were from the Calgary Comprehensive Epilepsy Program database, a clinical registry of adult PWE in Calgary, Canada. A tree-based partial credit model based on recursive partitioning (PCTree) was used to identify subgroups that exhibit DIF on NDDI-E items using patients' characteristics as covariates. Differences in the identified subgroups were characterized using multinomial logistic regression. RESULTS: Of the 1,576 patients in this cohort, 806 (51.1%) were female, and the median age was 38.0 years. PCTree identified four patient subgroups defined by employment status, age, and sex. Subgroup 1 were unemployed patients ≤ 26 years old, subgroup 2 were unemployed patients > 26 years, subgroup 3 were employed females, while subgroup 4 were employed male patients. The subgroups exhibited significant differences on education level, comorbidity index scores, marital status, type of epilepsy, and driving status. CONCLUSION: PWE differed in their interpretation and responses to questions about their depression symptoms, and these differences were a function of sociodemographic and clinical characteristics.

Patient-reported depression screening measures are prone to differential item functioning (DIF), which occurs when patients with the same levels of depression respond to and interpret the questions on the measures differently, as a result of different socio-demographic characteristics. Heterogeneity in how epilepsy patients interpret and respond to depression measures, if not identified, could lead to measurement biases that threaten the validity of inferences from patient-reported outcome measure scores to inform clinical and healthcare decisions for epilepsy management. Using data from a clinical registry of patients with epilepsy, the tree-based item response theory model was used to examine the presence of DIF in the items comprising the patient-reported Neurological Disorders Depression Inventory in Epilepsy (NDDI-E) scale. Four subgroups of epilepsy patients were noted to exhibit DIF on NDDI-E items. These groups were defined by interactions among employment status, age and sex. These characteristics affect the interpretation of NDDI-E item scores. It is recommended that clinicians carefully scrutinize responses to individual items alongside the overall NDDI-E score in different patient groups to inform clinical decisions for epilepsy management.

Response shift results of quantitative research using patient-reported outcome measures: a descriptive systematic review.

PURPOSE: The objective of this systematic review was to describe the prevalence and magnitude of response shift effects, for different response shift methods, populations, study designs, and patient-reported outcome measures (PROM)s. METHODS: A literature search was performed in MEDLINE, PSYCINFO, CINAHL, EMBASE, Social Science Citation Index, and Dissertations & Theses Global to identify longitudinal quantitative studies that examined response shift using PROMs, published before 2021. The magnitude of each response shift effect (effect sizes, R-squared or percentage of respondents with response shift) was ascertained based on reported statistical information or as stated in the manuscript. Prevalence and magnitudes of response shift effects were summarized at two levels of analysis (study and effect levels), for recalibration and reprioritization/reconceptualization separately, and for different response shift methods, and population, study design, and PROM characteristics. Analyses were conducted twice: (a) including all studies and samples, and (b) including only unrelated studies and independent samples. RESULTS: Of the 150 included studies, 130 (86.7%) detected response shift effects. Of the 4868 effects investigated, 793 (16.3%) revealed response shift. Effect sizes could be determined for 105 (70.0%) of the studies for a total of 1130 effects, of which 537 (47.5%) resulted in detection of response shift. Whereas effect sizes varied widely, most median recalibration effect sizes (Cohen's d) were between 0.20 and 0.30 and median reprioritization/reconceptualization effect sizes rarely exceeded 0.15, across the characteristics. Similar results were obtained from unrelated studies. CONCLUSION: The results draw attention to the need to focus on understanding variability in response shift results: Who experience response shifts, to what extent, and under which circumstances?

Unsupervised item response theory models for assessing sample heterogeneity in patient-reported outcomes measures.

PURPOSE: Unsupervised item-response theory (IRT) models such as polytomous IRT based on recursive partitioning (IRTrees) and mixture IRT (MixIRT) models can be used to assess differential item functioning (DIF) in patient-reported outcome measures (PROMs) when the covariates associated with DIF are unknown a priori. This study examines the consistency of results for IRTrees and MixIRT models. METHODS: Data were from 4478 individuals in the Alberta Provincial Project on Outcome Assessment in Coronary Heart Disease registry who received cardiac angiography in Alberta, Canada, and completed the Hospital Anxiety and Depression Scale (HADS) depression subscale items. The partial credit model (PCM) based on recursive partitioning (PCTree) and mixture PCM (MixPCM) were used to identify covariates associated with differential response patterns to HADS depression subscale items. Model covariates included demographic and clinical characteristics. RESULTS: The median (interquartile range) age was 64.5(15.7) years, and 3522(78.5%) patients were male. The PCTree identified 4 terminal nodes (subgroups) defined by smoking status, age, and body mass index. A 3-class PCM fits the data well. The MixPCM latent classes were defined by age, disease indication, smoking status, comorbid diabetes, congestive heart failure, and chronic obstructive pulmonary disease. CONCLUSION: PCTree and MixPCM were not consistent in detecting covariates associated with differential interpretations of PROM items. Future research will use computer simulations to assess these models' Type I error and statistical power for identifying covariates associated with DIF.

The Intergenerational Transfer of Mental Disorders: A Population-Based Multigenerational Linkage Study: Le transfert intergénérationnel des troubles mentaux : une étude sur les liens multigénérationnels basée sur la population.

OBJECTIVES: The aetiology of mental disorders involves genetic and environmental factors, both reflected in family health history. We examined the intergenerational transmission of multiple mental disorders from parents and grandparents using population-based, objectively measured family histories. METHODS: This population-based retrospective cohort study used administrative healthcare databases in Manitoba, Canada and included adults living in Manitoba from 1977 to 2020 with linkages to at least one parent and one grandparent. Index date was when individuals turned 18 or 1 April 1977, whichever occurred later. Mental disorder diagnoses (mood and anxiety, substance use and psychotic disorders) were identified in individuals, parents and grandparents from hospitalization and outpatient records. Cox proportional hazards regression models included sociodemographic characteristics, individual's comorbidity and mental disorder history in a grandparent, mother and father. RESULTS: Of 109,359 individuals with no mental disorder prior to index date, 47.1% were female, 36.3% had a mental disorder during follow-up, and 90.9% had a parent or grandparent with a history of a mental disorder prior to the index date. Both paternal and maternal history of a mental disorder increased the risk of the disorder in individuals. Psychotic disorders had the strongest association with parental history and were mostly influenced by paternal (hazards ratio [HR] 3.73, 95% confidence interval [CI] 2.99 to 4.64) compared to maternal history (HR 2.23, 95% CI, 1.89 to 2.64). Grandparent history was independently associated with the risk of all mental disorders but had the strongest influence on substance use disorders (HR 1.42, 95% CI, 1.34 to 1.50). CONCLUSIONS: Parental history of mental disorders was associated with an increased risk of all mental disorders. Grandparent history of mental disorders was associated with a small risk increase of the disorders above and beyond parental history influence. This three-generation study further highlights the need for family-based interventional programs in families affected by mental disorders. PLAIN LANGUAGE SUMMARY TITLE: The Intergenerational Transfer of Mental Illnesses.

ObjectivesBoth genetics and environmental factors, such as poverty, maltreatment and parental education, have a role in the development of mental illnesses. Some genetic and environmental risk factors for mental illnesses are shared within families. We conducted a large study to test the extent to which mental illnesses are passed down through generations.MethodsThis study used healthcare data from Manitoba, Canada captured during the delivery of healthcare services for administrative purposes. These data included all adults from 1977 to 2020 who had at least one parent and one grandparent with linked data. Mental illnesses were diagnosed in individuals, parents and grandparents by doctors during hospitalizations or physician visits. The illnesses included mood and anxiety, substance use, and psychotic illnesses. We estimated the likelihood of developing a mental illness when parents and/or grandparents had a mental illness as well.ResultsThe study included 109,359 individuals; a third developed a mental illness during the study period. The majority had a history of a mental illness in a parent or grandparent. We found that a history of mental illness in a mother and father increased the chance of developing the illness. Psychotic illnesses had the strongest relation with parental history. In particular, having a father with a psychotic illness increased the chance of developing the illness by four times. The likelihood of developing a mental illness was higher if a grandparent had a mental illness, above and beyond parental history influence, particularly for substance use disorders.ConclusionsHaving a parent or grandparent with a mental illness increases an individual's chance of developing a mental illness. Family-based intervention programs are needed to support families affected by mental illnesses in coping with their heavy burden.

Trends in the incidence and prevalence of cirrhosis in Manitoba, Canada: A population-based study (2010-2019).

INTRODUCTION AND OBJECTIVES: The burden of chronic liver disease and cirrhosis continues to increase in North America. We sought to estimate the incidence and prevalence of cirrhosis in Manitoba, Canada over time and assess changes in trends between 2010-2019. MATERIAL AND METHODS: We performed a population-based study using Manitoba administrative health care data, and two validated case-finding algorithms. Annual incidence and prevalence rates were estimated using a generalized linear model with generalized estimating equations, adjusting for age and sex. Changes in estimates were tested using linear trend regression models. RESULTS: Two algorithms estimated the number of prevalent cirrhosis to be 16,140 and 29,943 respectively. The age- and sex-adjusted incidence rates increased over the study (from 149 to 264 cases per 100,000 population in 2010, to 177 to 388 cases per 100,000 population in 2019). Cirrhosis incidence increased annually by 2-6 %, with the largest increase (6-8 % 95 % CI 7-9 %, p <0.0001) in those aged 18-44 years. Irrespective of the algorithm used, females consistently exhibited higher cirrhosis incidence and prevalence compared to males over time (P <0.0001). Prevalence demonstrated an upward trend among all age groups over time for both algorithms (P < 0.0001). CONCLUSIONS: This population-based study highlights concerning temporal trends in cirrhosis, characterized by rising annual incidence and prevalence estimates, particularly among young adults and females. These findings underscore the urgent need for comprehensive strategies that encompass prevention, early detection, and the delivery of high-quality healthcare and public health initiatives to effectively tackle this escalating health burden.

Short-term effects of a park-based group mobility program on increasing outdoor walking in older adults with difficulty walking outdoors: the Getting Older Adults Outdoors (GO-OUT) randomized controlled trial.

BACKGROUND: We estimated the short-term effects of an educational workshop and 10-week outdoor walk group (OWG) compared to the workshop and 10 weekly reminders (WR) on increasing outdoor walking (primary outcome) and walking capacity, health-promoting behavior, and successful aging defined by engagement in meaningful activities and well-being (secondary outcomes) in older adults with difficulty walking outdoors. METHODS: In a 4-site, parallel-group randomized controlled trial, two cohorts of community-living older adults (≥ 65 years) reporting difficulty walking outdoors participated. Following a 1-day workshop, participants were stratified and randomized to a 10-week OWG in parks or 10 telephone WR reinforcing workshop content. Masked evaluations occurred at 0, 3, and 5.5 months. We modeled minutes walked outdoors (derived from accelerometry and global positioning system data) using zero-inflated negative binomial regression with log link function, imputing for missing observations. We modeled non-imputed composite measures of walking capacity, health-promoting behavior, and successful aging using generalized linear models with general estimating equations based on a normal distribution and an unstructured correlation matrix. Analyses were adjusted for site, participation on own or with a partner, and cohort. RESULTS: We randomized 190 people to the OWG (n = 98) and WR interventions (n = 92). At 0, 3, and 5.5 months, median outdoor walking minutes was 22.56, 13.04, and 0 in the OWG, and 24.00, 26.07, and 0 in the WR group, respectively. There was no difference between groups in change from baseline in minutes walked outdoors based on incidence rate ratio (IRR) and 95% confidence interval (CI) at 3 months (IRR = 0.74, 95% CI 0.47, 1.14) and 5.5 months (IRR = 0.77, 95% CI 0.44, 1.34). Greater 0 to 3-month change in walking capacity was observed in the OWG compared to the WR group (ßz-scored difference = 0.14, 95% CI 0.02, 0.26) driven by significant improvement in walking self-efficacy; other comparisons were not significant. CONCLUSIONS: A group, park-based OWG was not superior to WR in increasing outdoor walking activity, health-promoting behavior or successful aging in older adults with difficulty walking outdoors; however, the OWG was superior to telephone WR in improving walking capacity through an increase in walking self-efficacy. Community implementation of the OWG is discussed. TRIAL REGISTRATION: ClinicalTrials.gov NCT03292510 Date of registration: September 25, 2017.

The validity of electronic health data for measuring smoking status: a systematic review and meta-analysis.

BACKGROUND: Smoking is a risk factor for many chronic diseases. Multiple smoking status ascertainment algorithms have been developed for population-based electronic health databases such as administrative databases and electronic medical records (EMRs). Evidence syntheses of algorithm validation studies have often focused on chronic diseases rather than risk factors. We conducted a systematic review and meta-analysis of smoking status ascertainment algorithms to describe the characteristics and validity of these algorithms. METHODS: The Preferred Reporting Items for Systematic Reviews and Meta-Analyses guidelines were followed. We searched articles published from 1990 to 2022 in EMBASE, MEDLINE, Scopus, and Web of Science with key terms such as validity, administrative data, electronic health records, smoking, and tobacco use. The extracted information, including article characteristics, algorithm characteristics, and validity measures, was descriptively analyzed. Sources of heterogeneity in validity measures were estimated using a meta-regression model. Risk of bias (ROB) in the reviewed articles was assessed using the Quality Assessment of Diagnostic Accuracy Studies-2 tool. RESULTS: The initial search yielded 2086 articles; 57 were selected for review and 116 algorithms were identified. Almost three-quarters (71.6%) of algorithms were based on EMR data. The algorithms were primarily constructed using diagnosis codes for smoking-related conditions, although prescription medication codes for smoking treatments were also adopted. About half of the algorithms were developed using machine-learning models. The pooled estimates of positive predictive value, sensitivity, and specificity were 0.843, 0.672, and 0.918 respectively. Algorithm sensitivity and specificity were highly variable and ranged from 3 to 100% and 36 to 100%, respectively. Model-based algorithms had significantly greater sensitivity (p = 0.006) than rule-based algorithms. Algorithms for EMR data had higher sensitivity than algorithms for administrative data (p = 0.001). The ROB was low in most of the articles (76.3%) that underwent the assessment. CONCLUSIONS: Multiple algorithms using different data sources and methods have been proposed to ascertain smoking status in electronic health data. Many algorithms had low sensitivity and positive predictive value, but the data source influenced their validity. Algorithms based on machine-learning models for multiple linked data sources have improved validity.

Fracture prediction in rheumatoid arthritis: validation of FRAX with bone mineral density for incident major osteoporotic fractures.

OBJECTIVES: FRAX® uses clinical risk factors, with or without bone mineral density (BMD), to calculate 10-year fracture risk. Rheumatoid arthritis (RA) is a risk factor for osteoporotic fracture and a FRAX input variable. FRAX predates the current era of RA treatment. We examined how well FRAX predicts fracture in contemporary RA patients. METHODS: Administrative data from patients receiving BMD testing were linked to the Manitoba Population Health Research Data Repository. Observed cumulative 10-year Major Osteoporotic Fracture (MOF) probability was compared with FRAX-predicted 10-year MOF probability with BMD for assessing calibration. MOF risk stratification was assessed using Cox regression. RESULTS: RA patients (N = 2,099, 208 with incident MOF) and non-RA patients (N = 2,099, with 165 incident MOF) were identified. For RA patients, FRAX predicted 10-year risk was 13.2% and observed 10-year MOF risk was 13.2% (95% CI 11.6% to 15.1%). The slope of the calibration plot was 0.67 (95% CI 0.53-0. 81) in those with RA vs 0.98 (95% CI 0.61-1.34) in non-RA patients. Risk was overestimated in RA patients with high FRAX scores (>20%), but FRAX was well-calibrated in other groups. FRAX stratified risk in those with and without RA (hazard ratios 1.52, 95% 1.25-1.72 vs 2.00, 95% 1.73-2.31), with slightly better performance in the latter (p-interaction = 0.004). CONCLUSIONS: FRAX predicts fracture risk in contemporary RA patients but may slightly overestimate risk in those already at high predicted risk. Thus, the current FRAX tool continues to be appropriate for fracture risk assessment in RA patients.

Within-person fluctuations over three years in depression, anxiety, fatigue, and health-related quality of life in multiple sclerosis.

BACKGROUND: Longitudinal studies of health-related quality of life (HRQoL) in multiple sclerosis (MS) are limited. Most have examined average changes within the population, rather than dynamic changes within individuals. OBJECTIVE: To assess the between- and within-individual association between depression, anxiety, fatigue, cognition, physical functioning, and physical comorbidities and HRQoL. METHODS: Adults with MS underwent physical and cognitive assessments and reported symptoms of fatigue (Daily Fatigue Impact Scale), depression and anxiety (Hospital Anxiety and Depression Scale (HADS)), and HRQoL (RAND-36) annually (n = 4 visits). We evaluated associations of elevated symptoms of anxiety (HADS-A) and depression (HADS-D), fatigue, physical function (timed-walk and nine-hole peg test), cognitive function and comorbidity count with physical (PCS-36) and mental (MCS-36) HRQoL using multivariable linear models-estimating between-person and within-person effects. RESULTS: Of 255 participants with MS enrolled, 81.6% were women. After adjustment, within-person increases in depression and fatigue were associated with decreases in physical HRQoL. Increases in depression, anxiety, and comorbidity count were associated with decreases in mental HRQoL. CONCLUSIONS: Within-person increases in symptoms of depression, anxiety and fatigue, and comorbidity count are associated with HRQoL decreases among adults with MS, highlighting the potential magnitude of individual benefit of intervention for these symptoms.

Developing a prediction model of children asthma risk using population-based family history health records.

BACKGROUND: Identifying children at high risk of developing asthma can facilitate prevention and early management strategies. We developed a prediction model of children's asthma risk using objectively collected population-based children and parental histories of comorbidities. METHODS: We conducted a retrospective population-based cohort study using administrative data from Manitoba, Canada, and included children born from 1974 to 2000 with linkages to ≥1 parent. We identified asthma and prior comorbid condition diagnoses from hospital and outpatient records. We used two machine-learning models: least absolute shrinkage and selection operator (LASSO) logistic regression (LR) and random forest (RF) to identify important predictors. The predictors in the base model included children's demographics, allergic conditions, respiratory infections, and parental asthma. Subsequent models included additional multiple comorbidities for children and parents. RESULTS: The cohort included 195,666 children: 51.3% were males and 17.7% had asthma diagnosis. The base LR model achieved a low predictive performance with sensitivity of 0.47, 95% confidence interval (0.45-0.48), and specificity of 0.67 (0.66-0.67) using a predicted probability threshold of 0.20. Sensitivity significantly improved when children's comorbidities were included using LASSO LR: 0.71 (0.69-0.72). Predictive performance further improved by including parental comorbidities (sensitivity = 0.72 [0.70-0.73], specificity = 0.69 [0.69-0.70]). We observed similar results for the RF models. Children's menstrual disorders and mood and anxiety disorders, parental lipid metabolism disorders and asthma were among the most important variables that predicted asthma risk. CONCLUSION: Including children and parental comorbidities to children's asthma prediction models improves their accuracy.

Latent variable mixture models to address heterogeneity in patient-reported outcome data.

The populations included in studies that investigate patient-reported outcome (PRO) measures of health or well-being, including health-related quality of life, are often heterogeneous with respect to their sociodemographic and health status characteristics. If the sources of heterogeneity are not observed or are not known a priori, latent variable mixture models (LVMMs) can be used to identify homogeneous sub-groups within the study population based on observed patterns of responses in PRO data. Our purpose is to review the characteristics of LVMMs and their applications for PRO data, and provide a demonstration of their use. We focus on mixture item response theory (IRT) models, which combine latent class analysis with the conventional IRT model to define the measurement model for one or more latent variables. In PRO studies, IRT models can be used to assess differential item functioning and response shift. An illustrative example is presented using clinical registry data for 1391 total hip replacement patients who provided responses for the physical component items of the 12-item Short Form Health Survey (SF-12). After assessing model fit and class discrimination statistics, a three-class model was selected. Model parameter estimates across classes were dissimilar for many of the items. Sex and self-reported presence of arthritis and back pain were associated with class membership. LVMMs represent a potentially useful tool to explore patterns of responses in PRO data. Opportunities for other applications of LVMMs to PRO data are discussed.

Implications of the syntheses on definition, theory, and methods conducted by the Response Shift - in Sync Working Group.

PURPOSE: Our aim is to advance response shift research by explicating the implications of published syntheses by the Response Shift - in Sync Working Group in an integrative way and suggesting ways for improving the quality of future response shift studies. METHODS: Members of the Working Group further discussed the syntheses of the literature on definitions, theoretical underpinnings, operationalizations, and response shift methods. They outlined areas in need of further explication and refinement, and delineated additional implications for future research. RESULTS: First, the proposed response shift definition was further specified and its implications for the interpretation of results explicated in relation to former, published definitions. Second, the proposed theoretical model was further explained in relation to previous theoretical models and its implications for formulating research objectives highlighted. Third, ways to explore alternative explanations per response shift method and their implications for response shift detection and explanation were delineated. The implications of the diversity of the response shift methods for response shift research were presented. Fourth, the implications of the need to enhance the quality and reporting of the response shift studies for future research were sketched. CONCLUSION: With our work, we intend to contribute to a common language regarding response shift definitions, theory, and methods. By elucidating some of the major implications of earlier work, we hope to advance response shift research.

Mental Disorders Among Mothers of Children Born Preterm: A Population-Based Cohort Study in Canada.

BACKGROUND: Our aim was to examine the association between preterm delivery and incident maternal mental disorders using a population-based cohort of mothers in Canada. METHODS: Retrospective matched cohort study using Manitoba Centre for Health Policy (MCHP) administrative data in Manitoba. Mothers who delivered preterm babies (<37 weeks gestational age) between 1998 and 2013 were matched 1:5 to mothers of term babies using socio-demographic variables. Primary outcome was any incident mental disorder within 5 years of delivery defined as any of (a) mood and anxiety disorders, (b) psychotic disorders, (c) substance use disorders, and (d) suicide or suicide attempts. Multivariable Poisson regression model was used to estimate the 5-year adjusted incidence rate ratios (IRRs). RESULTS: Mothers of preterm children (N = 5,361) had similar incidence rates of any mental disorder (17.4% vs. 16.6%, IRR = 0.99, 95% CI, 0.91 to 1.07) compared to mothers of term children (N = 24,932). Mothers of term children had a higher rate of any mental disorder in the first year while mothers of preterm children had higher rates from 2 to 5 years. Being the mother of a child born <28 week (IRR = 1.5, 95% CI, 1.14 to 2.04), but not 28-33 weeks (IRR = 1.03, 95% CI, 0.86 to 1.19) or 34-36 weeks (IRR = 0.96, 95% CI, 0.88 to 1.05), was associated with any mental disorder. INTERPRETATION: Mothers of preterm and term children had similar rates of incident mental disorders within 5-years post-delivery. Extreme prematurity was a risk factor for any mental disorder. Targeted screening and support of this latter group may be beneficial.

Mental Health of Royal Canadian Mounted Police at the Start of the Cadet Training Program.

OBJECTIVE: Serving Royal Canadian Mounted Police (RCMP) have screened positive for one or more mental disorders based on self-reported symptoms with substantial prevalence (i.e., 50.2%). Mental health challenges for military and paramilitary populations have historically been attributed to insufficient recruit screening; however, cadet mental health when starting the Cadet Training Program (CTP) was unknown. Our objective was to estimate RCMP Cadet mental health when starting the CTP and test for sociodemographic differences. METHOD: Cadets starting the CTP completed a survey assessing self-reported mental health symptoms (n = 772, 72.0% male) and a clinical interview (n = 736, 74.4% male) with a clinician or supervised trainee using the Mini-International Neuropsychiatric Interview to assess current and past mental health. RESULTS: The percentage of participants screening positive for one or more current mental disorders based on self-reported symptoms (15.0%) was higher than the diagnostic prevalence for the general population (10.1%); however, based on clinical interviews, participants were less likely to screen positive for any current mental disorder (6.3%) than the general population. Participants were also less likely to screen positive for any past mental disorder based on self-report (3.9%) and clinical interviews (12.5%) than the general population (33.1%). Females were more likely to score higher than males (all ps<.01; Cohen's ds .23 to .32) on several self-report mental disorder symptom measures. CONCLUSIONS: The current results are the first to describe RCMP cadet mental health when starting the CTP. The data evidenced a lower prevalence of anxiety, depressive, and trauma-related mental disorders than the general population based on clinical interviews, contrasting notions that more rigorous mental health screening would reduce the high prevalence of mental disorders among serving RCMP. Instead, protecting RCMP mental health may require ongoing efforts to mitigate operational and organizational stressors.

Differences in Treatment Patterns and Outcomes of Acute Myocardial Infarction for Low- and High-Income Patients in 6 Countries.

Importance: Differences in the organization and financing of health systems may produce more or less equitable outcomes for advantaged vs disadvantaged populations. We compared treatments and outcomes of older high- and low-income patients across 6 countries. Objective: To determine whether treatment patterns and outcomes for patients presenting with acute myocardial infarction differ for low- vs high-income individuals across 6 countries. Design, Setting, and Participants: Serial cross-sectional cohort study of all adults aged 66 years or older hospitalized with acute myocardial infarction from 2013 through 2018 in the US, Canada, England, the Netherlands, Taiwan, and Israel using population-representative administrative data. Exposures: Being in the top and bottom quintile of income within and across countries. Main Outcomes and Measures: Thirty-day and 1-year mortality; secondary outcomes included rates of cardiac catheterization and revascularization, length of stay, and readmission rates. Results: We studied 289 376 patients hospitalized with ST-segment elevation myocardial infarction (STEMI) and 843 046 hospitalized with non-STEMI (NSTEMI). Adjusted 30-day mortality generally was 1 to 3 percentage points lower for high-income patients. For instance, 30-day mortality among patients admitted with STEMI in the Netherlands was 10.2% for those with high income vs 13.1% for those with low income (difference, -2.8 percentage points [95% CI, -4.1 to -1.5]). One-year mortality differences for STEMI were even larger than 30-day mortality, with the highest difference in Israel (16.2% vs 25.3%; difference, -9.1 percentage points [95% CI, -16.7 to -1.6]). In all countries, rates of cardiac catheterization and percutaneous coronary intervention were higher among high- vs low-income populations, with absolute differences ranging from 1 to 6 percentage points (eg, 73.6% vs 67.4%; difference, 6.1 percentage points [95% CI, 1.2 to 11.0] for percutaneous intervention in England for STEMI). Rates of coronary artery bypass graft surgery for patients with STEMI in low- vs high-income strata were similar but for NSTEMI were generally 1 to 2 percentage points higher among high-income patients (eg, 12.5% vs 11.0% in the US; difference, 1.5 percentage points [95% CI, 1.3 to 1.8 ]). Thirty-day readmission rates generally also were 1 to 3 percentage points lower and hospital length of stay generally was 0.2 to 0.5 days shorter for high-income patients. Conclusions and Relevance: High-income individuals had substantially better survival and were more likely to receive lifesaving revascularization and had shorter hospital lengths of stay and fewer readmissions across almost all countries. Our results suggest that income-based disparities were present even in countries with universal health insurance and robust social safety net systems.