An Overview of Real-World Data Infrastructure for Cancer Research.

AIMS: There is increasing interest in the opportunities offered by Real World Data (RWD) to provide evidence where clinical trial data does not exist, but access to appropriate data sources is frequently cited as a barrier to RWD research. This paper discusses current RWD resources and how they can be accessed for cancer research. MATERIALS AND METHODS: There has been significant progress on facilitating RWD access in the last few years across a range of scales, from local hospital research databases, through regional care records and national repositories, to the impact of federated learning approaches on internationally collaborative studies. We use a series of case studies, principally from the UK, to illustrate how RWD can be accessed for research and healthcare improvement at each of these scales. RESULTS: For each example we discuss infrastructure and governance requirements with the aim of encouraging further work in this space that will help to fill evidence gaps in oncology. CONCLUSION: There are challenges, but real-world data research across a range of scales is already a reality. Taking advantage of the current generation of data sources requires researchers to carefully define their research question and the scale at which it would be best addressed.

Healthcare utilisation in patients with long-term conditions during the COVID-19 pandemic: a population-based observational study of all patients across Greater Manchester, UK.

OBJECTIVES: Data on population healthcare utilisation (HCU) across both primary and secondary care during the COVID-19 pandemic are lacking. We describe primary and secondary HCU stratified by long-term conditions (LTCs) and deprivation, during the first 19 months of COVID-19 pandemic across a large urban area in the UK. DESIGN: A retrospective, observational study. SETTING: All primary and secondary care organisations that contributed to the Greater Manchester Care Record throughout 30 December 2019 to 1 August 2021. PARTICIPANTS: 3 225 169 patients who were registered with or attended a National Health Service primary or secondary care service during the study period. PRIMARY OUTCOMES: Primary care HCU (incident prescribing and recording of healthcare information) and secondary care HCU (planned and unplanned admissions) were assessed. RESULTS: The first national lockdown was associated with reductions in all primary HCU measures, ranging from 24.7% (24.0% to 25.5%) for incident prescribing to 84.9% (84.2% to 85.5%) for cholesterol monitoring. Secondary HCU also dropped significantly for planned (47.4% (42.9% to 51.5%)) and unplanned admissions (35.3% (28.3% to 41.6%)). Only secondary care had significant reductions in HCU during the second national lockdown. Primary HCU measures had not recovered to prepandemic levels by the end of the study. The secondary admission rate ratio between multi-morbid patients and those without LTCs increased during the first lockdown by a factor of 2.40 (2.05 to 2.82; p<0.001) for planned admissions and 1.25 (1.07 to 1.47; p=0.006) for unplanned admissions. No significant changes in this ratio were observed in primary HCU. CONCLUSION: Major changes in primary and secondary HCU were observed during the COVID-19 pandemic. Secondary HCU reduced more in those without LTCs and the ratio of utilisation between patients from the most and least deprived areas increased for the majority of HCU measures. Overall primary and secondary care HCU for some LTC groups had not returned to prepandemic levels by the end of the study.

Defining trajectories of response in patients with psoriasis treated with biologic therapies.

BACKGROUND: The effectiveness and cost-effectiveness of biologic therapies for psoriasis are significantly compromised by variable treatment responses. Thus, more precise management of psoriasis is needed. OBJECTIVES: To identify subgroups of patients with psoriasis treated with biologic therapies, based on changes in their disease activity over time, that may better inform patient management. METHODS: We applied latent class mixed modelling to identify trajectory-based patient subgroups from longitudinal, routine clinical data on disease severity, as measured by the Psoriasis Area and Severity Index (PASI), from 3546 patients in the British Association of Dermatologists Biologics and Immunomodulators Register, as well as in an independent cohort of 2889 patients pooled across four clinical trials. RESULTS: We discovered four discrete classes of global response trajectories, each characterized in terms of time to response, size of effect and relapse. Each class was associated with differing clinical characteristics, e.g. body mass index, baseline PASI and prevalence of different manifestations. The results were verified in a second cohort of clinical trial participants, where similar trajectories following the initiation of biologic therapy were identified. Further, we found differential associations of the genetic marker HLA-C*06:02 between our registry-identified trajectories. CONCLUSIONS: These subgroups, defined by change in disease over time, may be indicative of distinct endotypes driven by different biological mechanisms and may help inform the management of patients with psoriasis. Future work will aim to further delineate these mechanisms by extensively characterizing the subgroups with additional molecular and pharmacological data.

Assessing the severity of Type 2 diabetes using clinical data-based measures: a systematic review.

AIMS: To identify and critically appraise measures that use clinical data to grade the severity of Type 2 diabetes. METHODS: We searched MEDLINE, Embase and PubMed between inception and June 2018. Studies reporting on clinical data-based diabetes-specific severity measures in adults with Type 2 diabetes were included. We excluded studies conducted solely in participants with other types of diabetes. After independent screening, the characteristics of the eligible measures including design and severity domains, the clinical utility of developed measures, and the relationship between severity levels and health-related outcomes were assessed. RESULTS: We identified 6798 studies, of which 17 studies reporting 18 different severity measures (32 314 participants in 17 countries) were included: a diabetes severity index (eight studies, 44%); severity categories (seven studies, 39%); complication count (two studies, 11%); and a severity checklist (one study, 6%). Nearly 89% of the measures included diabetes-related complications and/or glycaemic control indicators. Two of the severity measures were validated in a separate study population. More severe diabetes was associated with increased healthcare costs, poorer cognitive function and significantly greater risks of hospitalization and mortality. The identified measures differed greatly in terms of the included domains. One study reported on the use of a severity measure prospectively. CONCLUSIONS: Health records are suitable for assessment of diabetes severity; however, the clinical uptake of existing measures is limited. The need to advance this research area is fundamental as higher levels of diabetes severity are associated with greater risks of adverse outcomes. Diabetes severity assessment could help identify people requiring targeted and intensive therapies and provide a major benchmark for efficient healthcare services.

Engaging cancer patients in clinical practice guideline development: a pilot study.

Background: Patient engagement is a key quality component of cancer guideline development; however, the optimal strategy for engaging patients in guideline development remains unclear. The feasibility and efficacy of two patient engagement models was tested by Cancer Care Ontario's cancer guideline development program, the Program in Evidence-Based Care (pebc). Methods: In model 1, patients participated in the guideline development process as active members of a working group. In model 2, patients formed a separate consultation group to review project plans and recommendations generated by multiple working groups. Training included online resources (model 1) and an in-person orientation (model 2). The pebc's standard patient engagement process acted as a control. The study was conducted for 1 year. Surveys measured the satisfaction of patients and members of the guideline working groups with the process and the outcome of each model. Results: Three guideline projects used model 1 to engage patients, six projects used model 2 to receive feedback, and one project was used as a control group (14 patients total). Most participants, whatever the model, reported satisfaction with their experience. Key challenges to implementation included patient recruitment and long wait times between meetings (model 1), and difficulty focusing on the discussion topic and poor meeting attendance on the part of patients (model 2). Conclusions: The pilot study demonstrated that, although both models are feasible and effective for the engagement of patients in cancer guideline development, modifications are required to optimize their continued interest. The pebc will use the study results to inform the implementation of a patient engagement strategy for its program.

The added value of clinical geriatric assessment prior to geriatric rehabilitation.

BACKGROUND: Community dwelling elderly who are temporarily unable to live independently due to functional decline can be referred for geriatric rehabilitation care at a nursing home. This referral is always preceded by a comprehensive geriatric assessment (CGA) by a geriatrician in hospital to rule out an indication for clinical admission and to evaluate geriatric multimorbidity. Because there is little evidence of the effectiveness of this procedure, we aimed to evaluate the results of this assessment and to elaborate on its relevance. METHODS: All patients who were referred by their general practitioner for a CGA in our hospital prior to geriatric rehabilitation care between March and December 2016 were included prospectively. Data were analysed retrospectively. Our primary aim was to describe the percentage of patients with an indication for hospital admission. Other outcomes included new diagnostic findings from the geriatric assessment and recommendations given to the elderly care physician in the geriatric rehabilitation facility. RESULTS: Of the 32 assessed patients, 25% required admission to hospital, either due to somatic illness, mainly infections or suspected neurological disorders, needing clinical treatment, or for further diagnostics. New findings by geriatric assessment mostly concerned vitamin deficiency and infection, for which treatment recommendations were given to the elderly care physician. CONCLUSION: Geriatric assessment prior to geriatric rehabilitation referral is essential as it identifies patients needing hospital care, which cannot be provided at a nursing home. Furthermore, the assessment results in important recommendations to the elderly care physician in the geriatric rehabilitation facility.

Secondary Use and Analysis of Big Data Collected for Patient Care.

Objectives: To identify common methodological challenges and review relevant initiatives related to the re-use of patient data collected in routine clinical care, as well as to analyze the economic benefits derived from the secondary use of this data. Through the use of several examples, this article aims to provide a glimpse into the different areas of application, namely clinical research, genomic research, study of environmental factors, and population and health services research. This paper describes some of the informatics methods and Big Data resources developed in this context, such as electronic phenotyping, clinical research networks, biorepositories, screening data banks, and wide association studies. Lastly, some of the potential limitations of these approaches are discussed, focusing on confounding factors and data quality. Methods: A series of literature searches in main bibliographic databases have been conducted in order to assess the extent to which existing patient data has been repurposed for research. This contribution from the IMIA working group on "Data mining and Big Data analytics" focuses on the literature published during the last two years, covering the timeframe since the working group's last survey. Results and Conclusions: Although most of the examples of secondary use of patient data lie in the arena of clinical and health services research, we have started to witness other important applications, particularly in the area of genomic research and the study of health effects of environmental factors. Further research is needed to characterize the economic impact of secondary use across the broad spectrum of translational research.

The influence of training characteristics on the effect of aerobic exercise training in patients with chronic heart failure: A meta-regression analysis.

Although aerobic exercise training has shown to be an effective treatment for chronic heart failure patients, there has been a debate about the design of training programs and which training characteristics are the strongest determinants of improvement in exercise capacity. Therefore, we performed a meta-regression analysis to determine a ranking of the individual effect of the training characteristics on the improvement in exercise capacity of an aerobic exercise training program in chronic heart failure patients. We focused on four training characteristics; session frequency, session duration, training intensity and program length, and their product; total energy expenditure. A systematic literature search was performed for randomized controlled trials comparing continuous aerobic exercise training with usual care. Seventeen unique articles were included in our analysis. Total energy expenditure appeared the only training characteristic with a significant effect on improvement in exercise capacity. However, the results were strongly dominated by one trial (HF-action trial), accounting for 90% of the total patient population and showing controversial results compared to other studies. A repeated analysis excluding the HF-action trial confirmed that the increase in exercise capacity is primarily determined by total energy expenditure, followed by session frequency, session duration and session intensity. These results suggest that the design of a training program requires high total energy expenditure as a main goal. Increases in training frequency and session duration appear to yield the largest improvement in exercise capacity.

Development of evidence-based clinical algorithms for prescription of exercise-based cardiac rehabilitation.

BACKGROUND: Guideline adherence with respect to exercise-based cardiac rehabilitation (CR) is hampered by a large variety of complex guidelines and position statements, and the fact that these documents are not specifically designed for healthcare professionals prescribing exercise-based CR programs. This study aimed to develop clinical algorithms that can be used in clinical practice for prescription and evaluation of exercise-based CR in patients with coronary artery disease (CAD) and chronic heart failure (CHF). METHODS: The clinical algorithms were developed using a systematic approach containing four steps. First, all recent Dutch and European cardiac rehabilitation guidelines and position statements were reviewed and prioritised. Second, training goals requiring a differentiated training approach were selected. Third, documents were reviewed on variables to set training intensity, modalities, volume and intensity and evaluation instruments. Finally, the algorithms were constructed. RESULTS: Three Dutch guidelines and three European position statements were reviewed. Based on these documents, five training goals were selected and subsequently five algorithms for CAD patients and five for CHF patients were developed. CONCLUSIONS: This study presents evidence-based clinical algorithms for exercise-based CR in patients with CAD and CHF according to their training goals. These algorithms may serve to improve guideline adherence and the effectiveness of exercise-based CR.

Using personas to tailor educational messages to the preferences of coronary heart disease patients.

PURPOSE: Although tailoring health education messages to individual characteristics of patients has shown promising results, most patient education materials still take a one-size-fits-all approach. The aim of this study was to develop a method for tailoring health education messages to patients' preferences for various message features, using the concept of personas. This is a preliminary study focused on education for coronary heart disease (CHD) patients. METHODS: This study used a three-step approach. First, we created personas by (i) performing k-means cluster analysis on data from an online survey that assessed the preferences of 213 CHD patients for various message features and, (ii) creating a vivid description of the preferences per patient cluster in an iterative process with the research team. Second, we developed adaptation rules to tailor existing educational messages to the resulting personas. Third, we conducted a pilot validation by adapting nine existing educational messages to each of the personas. These messages and the resulting personas were then presented to a separate group of 38 CHD patients who visited the cardiology outpatient clinic. They were first asked to choose their most preferred, second most preferred, and least preferred persona. Subsequently, they were asked to rate three of the adapted messages; one for every of the persona choices. RESULTS: We created five personas that pertained to five patient clusters. Personas varied mainly on preferences for medical or lay language, current or future temporal perspective, and including or excluding explicit health risks. Fifty-five different adaptation rules were developed, primarily describing adaptations to the message's perspective, level of detail, sentence structure, and terminology. Most participants in the validation study could identify with one of the five personas, although some of them found it hard to choose. On average, 68.5% of all participants rated the messages that matched their most preferred persona more positively than, or in the same way as, the messages that matched their least preferred persona. CONCLUSIONS: The persona-based method developed in this study can be used to create a manageable set of patient-centered tailored messages, while additionally using the developed personas to assess patients' preferences.

Factors that drive insulin-dosing decisions of diabetes care providers: a vignette-based study in the Netherlands.

AIM: To test how certain patient factors would influence the decision of Dutch care providers regarding insulin dose adjustments. We hypothesize that some of these decisions would diverge from recent evidence and consensus statements. METHODS: We developed narrative vignettes describing clinical scenarios of patients receiving basal insulin therapy. For each vignette, the respondents were asked to indicate whether they would advise a change in insulin dose. A total of 520 paper questionnaires were distributed among physicians and nurses in primary and secondary care in the Netherlands. Multivariate linear and logistic regression analyses were performed to identify factors associated with dosing decisions. RESULTS: A total of 190 (37%) questionnaires were returned. In cases of a severe rather than mild hypoglycaemic event, care providers were nearly five times more likely to decrease the dose (odds ratio 4.77, 95% CI 1.65-13.75). Care providers were six times more likely to increase the dose when the patient's current dose was low (30 units) rather than high (90 units) (odds ratio 6.38, 95% CI 3.04-13.37). The plasma glucose concentration during a hypoglycaemic event and a known history of cardiovascular disease did not influence the care providers' dosing decisions. CONCLUSION: Evidence regarding the optimum insulin titration is not always translated into clinical practice. When formulating guidelines, misconceptions should be identified and addressed.

Technical challenges for big data in biomedicine and health: data sources, infrastructure, and analytics.

OBJECTIVES: To review technical and methodological challenges for big data research in biomedicine and health. METHODS: We discuss sources of big datasets, survey infrastructures for big data storage and big data processing, and describe the main challenges that arise when analyzing big data. RESULTS: The life and biomedical sciences are massively contributing to the big data revolution through secondary use of data that were collected during routine care and through new data sources such as social media. Efficient processing of big datasets is typically achieved by distributing computation over a cluster of computers. Data analysts should be aware of pitfalls related to big data such as bias in routine care data and the risk of false-positive findings in high-dimensional datasets. CONCLUSIONS: The major challenge for the near future is to transform analytical methods that are used in the biomedical and health domain, to fit the distributed storage and processing model that is required to handle big data, while ensuring confidentiality of the data being analyzed.

Reliability of in-hospital mortality as a quality indicator in clinical quality registries. A case study in an intensive care quality register.

OBJECTIVES: Errors in the registration or extraction of patient outcome data, such as in-hospital mortality, may lower the reliability of the quality indicator that uses this (partly) incorrect data. Our aim was to measure the reliability of in-hospital mortality registration in the Dutch National Intensive Care Evaluation (NICE) registry. METHODS: We linked data of the NICE registry with an insurance claims database, resulting in a list of discrepancies in in-hospital mortality. Eleven Intensive Care Units (ICUs) were visited where local data sources were investigated to find the true in-hospital mortality status of the discrepancies and to identify the causes of the data errors in the NICE registry. Original and corrected Standardized Mortality Ratios (SMRs) were calculated to determine if conclusions about quality of care changed compared to the national benchmark. RESULTS: In eleven ICUs, 23,855 records with 460 discrepancies were identified of which 255 discrepancies (1.1% of all linked records) were due to incorrect in-hospital mortality registration in the NICE registry. Two programming errors in computer software of six ICUs caused 78% of errors, the remainder was caused by manual transcription errors and failure to record patient outcomes. For one ICU the performance became concordant with the national benchmark after correction, instead of being better. CONCLUSIONS: The reliability of in-hospital mortality registration in the NICE registry was good. This was reflected by the low number of data errors and by the fact that conclusions about the quality of care were only affected for one ICU due to systematic data errors. We recommend that registries frequently verify the software used in the registration process, and compare mortality data with an external source to assure consistent quality of data.

Exercise training programs in Dutch cardiac rehabilitation centres.

PURPOSE: To assess methods for determination of exercise intensity, and to investigate practice variation with respect to the contents, volume and intensity of exercise training programs in Dutch cardiac rehabilitation (CR) centres. METHODS: A paper questionnaire was sent to all Dutch CR centres, consisting of 85 questions for patients with an acute coronary syndrome (ACS) or after coronary revascularisation (Group 1) and for patients with chronic heart failure (CHF, Group 2). RESULTS: CR professionals from 45 centres completed the questionnaires (58 %). Symptom-limited exercise testing was used to determine exercise capacity in 76 % and 64 % of the CR centres in group 1 and group 2, respectively; in these centres, a percentage of the maximum heart rate was the most frequently used exercise parameter (65 % and 56 %, respectively). All CR centres applied aerobic training and the majority applied strength training (64 % in group 1 and 92 % in group 2, respectively). There was a considerable variation in training intensity for both aerobic and strength training, as well as in training volume (1-20 h and 1-18 h respectively). CONCLUSION: Among Dutch CR centres, considerable variation exists in methods for determination of exercise intensity. In addition, there is no uniformity in training volume and intensity.

Safety of a web-based insulin titration system for patients with type 2 diabetes mellitus - pilot study.

The treatment of type 2 diabetes patients with insulin requires active dose titration to obtain optimal glycemic control. We developed a web-based decision support system to guide patients in performing the titration task autonomously, at their homes. The system is based on a clinically validated algorithm. The aim of this study was to test the safety of the system in a pilot implementation in clinical practice. Patients were blinded from the advice given by the system and instead received insulin dosing advice given by caregivers. At the end of the pilot, advice of the system were evaluated on safety by an expert panel. In this pilot study six patients used the web-based system at their home. In total, 48 advice were logged in the system resulting in eighteen deviating systems dosing advice as compared to the advice of the caregiver. Evaluation of the eighteen deviating systems advice lead to the detection of one unsafe advice indicating a need to extend the algorithm with an additional safety decision rule.

Control charts in healthcare quality improvement. A systematic review on adherence to methodological criteria.

OBJECTIVES: Use of Shewhart control charts in quality improvement (QI) initiatives is increasing. These charts are typically used in one or more phases of the Plan Do Study Act (PDSA) cycle to monitor summaries of process and outcome data, abstracted from clinical information systems, over time. We summarize methodological criteria of Shewhart control charts and investigate adherence of published QI studies to these criteria. METHODS: We searched Medline, Embase and CINAHL for studies using Shewhart control charts in QI processes in direct patient care. We extracted methodological criteria for Shewhart control charts, and for the use of these charts in PDSA cycles, from textbooks and methodological literature. RESULTS: We included 34 studies, presenting 64 control charts of which 40 control charts plotted two phases of the PDSA cycle. The criterion to use 10-35 data points in a control chart was least adhered to (48.4% non-adherence). Other criteria were: transformation of the data in case of a skewed distribution (43.7% non adherence), when comparing data from two phases of the PDSA cycle the Plan phase (the first phase) needs to be stable (40.0% non-adherence), using a maximum of four different rules to detect special cause variation (14.1% non-adherence), and setting control limits at three standard deviations from the mean (all control charts adhered). CONCLUSION: There is room for improvement with regard to the methodological construction of Shewhart control charts used in QI processes. Higher adherence to all methodological criteria will decrease the risk of incorrect conclusions about the process being monitored.

Development of a web-based decision support system for insulin self-titration.

Insulin is the most potent agent for the treatment of diabetes mellitus. However insulin treatment requires frequent evaluation of blood glucose levels and adjustment of the insulin dose. This process is called titration. To guide patients with type 2 diabetes using once-daily long-acting insulin, we have developed a web-based decision support system for insulin self-titration. The purpose of this paper is to provide an overview of the phases of development and the final design of the system. We reviewed the literature, consulted an expert panel, and conducted interviews with patients to elicit system requirements. This revealed four important aspects: the insulin titration algorithm, the handling of hypoglycemic events, telemedicine functionalities, and visiting frequency monitoring. We used these requirements to develop a fully functional system.

Improving guideline adherence for cardiac rehabilitation in the Netherlands.

BACKGROUND: In 2004, the Netherlands Society of Cardiology released the current guideline on cardiac rehabilitation. Given its complexity and the involvement of various healthcare disciplines, it was supplemented with a clinical algorithm, serving to facilitate its implementation in daily practice. Although the algorithm was shown to be effective for improving guideline adherence, several shortcomings and deficiencies were revealed. Based on these findings, the clinical algorithm has now been updated. This article describes the process and the changes that were made. METHODS: The revision consisted of three phases. First, the reliability of the measurement instruments included in the 2004 Clinical Algorithm was investigated by evaluating between-centre variations of the baseline assessment data. Second, based on the available evidence, a multidisciplinary expert advisory panel selected items needing revision and provided specific recommendations. Third, a guideline development group decided which revisions were finally included, also taking practical considerations into account. RESULTS: A total of nine items were revised: three because of new scientific insights and six because of the need for more objective measurement instruments. In all revised items, subjective assessment methods were replaced by more objective assessment tools (e.g. symptom-limited exercise instead of clinical judgement). In addition, four new key items were added: screening for anxiety/depression, stress, cardiovascular risk profile and alcohol consumption. CONCLUSION: Based on previously determined shortcomings, the Clinical Algorithm for Cardiac Rehabilitation was thoroughly revised mainly by incorporating more objective assessment methods and by adding several new key areas.

Effect of predefined order sets and usability problems on efficiency of computerized medication ordering.

OBJECTIVES: To study the effect of predefined order sets on the efficiency of computerized medication ordering, and to analyze the effect of different types of usability problems on ordering efficiency. METHODS: Crossover study to comparing the efficiency of two methods of ordering (with and without use of predefined order sets) in a laboratory setting using a computerized physician order entry system (CPOE). The excess number of mouse clicks and keystrokes (the difference in number of mouse clicks and keystrokes needed by each physician and the minimally required numbers to accomplish the ordering tasks) for each method was measured and per physician, occurrences of usability problems during the task sessions were recorded. Observed usability problems were categorized using Zhang et al.'s heuristic principles of good user interface design. The effect of different types of usability problems on the excess number of mouse clicks and keystrokes was statistically analyzed. RESULTS: The median excess number of mouse clicks and keystrokes needed by physicians was 6.2 times lower in the method with predefined order sets (p<0.01). The excess number of mouse clicks and keystrokes was significantly increased by vague and erroneous system messages with a factor of 2.62 (95% CI 2.24-3.07), the use of unfamiliar language and terminology by a factor of 1.28 (95% CI 1.14-1.43), and non-informative system feedback by a factor of 1.15 (95% CI 1.03-1.28), respectively. Other categories of usability problems had little influence on ordering efficiency. CONCLUSIONS: Predefined order sets can improve the efficiency of computerized ordering by reducing the excess number of mouse clicks and keystrokes. However, the efficiency of computerized ordering can be significantly impaired by usability problems due to vague and incorrect system messages, unfamiliar language, and non-informative system feedback.

A community-based survey of posttraumatic stress disorder in the Netherlands.

In this study, the lifetime prevalence of stressful events and current posttraumatic stress disorder (PTSD) in the general adult population in the Netherlands were examined, and risk groups for PTSD were determined. A representative sample of 2,238 adults (>or=18 years) in the Netherlands completed digital questionnaires by computer-assisted self-interviewing. In total, 52.2% of the population reported at least one stressful event throughout their life. The estimated prevalence of current PTSD in the total population was 3.8%. Rape and physical assault were the stressful events most likely to be associated with PTSD, witness of injury the least likely. Stressful medical events were moderately associated with PTSD. Prevalence of PTSD was elevated among single women and middle-aged men.