Quantifying unmet need in General Practice: a retrospective cohort study of administrative data.

OBJECTIVES: To assess whether patients attending general practices (GPs) in socioeconomically (SE) deprived areas receive the same amount of care, compared with similar patients (based on age, sex and level of morbidity) attending GPs in less deprived areas. If not, to quantify the additional resource that would be required by GPs in deprived areas to achieve parity. DESIGN: Retrospective cohort study. SETTING: 150 GPs in Scotland, UK, divided into two groups: 80 practices in Scottish Index of Multiple Deprivation (SIMD) deciles 1-5 (more SE deprived); 70 practices in SIMD deciles 6-10 (less SE deprived). PATIENTS: 437 590 patients registered with a more SE deprived GP, and 333 994 patients registered with a less SE deprived GP, for the whole study period (2013-2016), who made at least one appointment. OUTCOMES: The number of contacts and total contact time between patients and clinical staff. RESULTS: Patients in more SE deprived areas had slightly more discrete contacts over 3 years (11.8 vs 11.4), but each patient had marginally less contact time (146.1 vs 149.5 min). Stratified by sex and age, differences were also small. Stratified by the number of long-term conditions (LTCs), practices in more SE deprived areas delivered significantly less contact time than practices in less SE deprived areas. Over 3 years, 8 fewer minutes for patients with no LTCs, and 24, 27, 38 and 28 fewer minutes for patients with 1, 2, 3-4 or 5+LTCs, respectively. CONCLUSION: If GPs in more SE deprived areas were to give an equal amount of direct contact time to patients with the same level of need served by GPs in less SE deprived areas, this would require a 14% increase in patient contact time. This represents a significant unmet need, supporting the case for redistribution of resources to tackle the inverse care law.

Association between risk, duration and cause of hospitalisations in people with rheumatoid arthritis and multimorbidity in the UK Biobank and Scottish Early Rheumatoid Arthritis (SERA) cohorts: Longitudinal observational study.

OBJECTIVES: To investigate association between presence of multimorbidity in people with established and early rheumatoid arthritis (RA) and risk, duration and cause of hospitalisations. DESIGN: Longitudinal observational study. SETTING: UK Biobank, population-based cohort recruited between 2006 and 2010, and the Scottish Early Rheumatoid Arthritis (SERA), inception cohort recruited between 2011 and 2015. Both linked to mortality and hospitalisation data. PARTICIPANTS: 4757 UK Biobank participants self-reporting established RA; 825 SERA participants with early RA meeting the 2010 ACR/EULAR classification criteria. Participants stratified by number of long-term conditions (LTCs) in addition to RA (RA only, RA + 1 LTC and RA + ≥ 2 LTCs) and matched to five non-RA controls. MAIN OUTCOME MEASURES: Number and duration of hospitalisations and their causes. Incidence rate ratios (IRR) and 95% confidence intervals (CI) calculated using negative binomial regression models. RESULTS: Participants with RA + ≥ 2 LTCs experienced higher hospitalisation rates compared to those with RA alone (UK Biobank: IRR 2.10, 95% CI 1.91 to 2.30; SERA: IRR 1.74, 95% CI 1.23 to 2.48). Total duration of hospitalisation in RA + ≥ 2 LTCs was also higher (UK Biobank: IRR 2.48, 95% CI 2.17 to 2.84; SERA: IRR 1.90, 95% CI 1.07 to 3.38) than with RA alone. Rate and total duration of hospitalisations was higher in UK Biobank RA participants than non-RA controls with equivalent number of LTCs. Hospitalisations for respiratory infection were higher in early RA than established RA and were the commonest cause of hospital admission in early RA. CONCLUSIONS: Participants with established or early RA with multimorbidity experienced a higher rate and duration of hospitalisations than those with RA alone and with non-RA matched controls.

Educational associations with missed GP appointments for patients under 35 years old: administrative data linkage study.

BACKGROUND: There is an evidence gap about whether levels of engagement with public services such as schools and health care affect people across the lifespan. Data on missed patient appointments from a nationally representative sample of Scottish general practices (GP) (2013-2016) were probabilistically linked to secondary school pupil data. We tested whether school attendance, exclusions (2007-2011) or lower educational attainment (2007-2016) was associated with an increased risk of missing general practice appointments. METHODS: School attendance data were classified into quartiles of possible days attended for years we had data. School exclusions were derived as a categorical variable of 'ever excluded'. Attainment data were categorised via the Scottish Credit and Qualifications Framework (SCQF) level 3 or 6; a cumulative measure of attainment on leaving school. The associations between school attendance, exclusions and attainment and risk of missing medical appointments were investigated using negative binomial models, offset by number of GP appointments made and controlling for potential confounders. RESULTS: 112,534 patients (all aged under 35) had GP appointment and retrospective school attendance and exclusion data, and a subset of 66,967 also had attainment data available. Patients who had lower attendance, had been excluded from school or had lower educational attainment had an increased risk of missing GP appointments (all rate ratios > 1.40). CONCLUSIONS: This study provides the first evidence from a population-representative sample in a high-income country that increased numbers of missed appointments in health care are associated with reduced school attendance, higher levels of school exclusion and lower educational attainment. Insights into the epidemiology of missingness across public services can support future research, policy and practice that aim to improve healthcare, health outcomes and engagement in services.

'Missingness' in health care: Associations between hospital utilization and missed appointments in general practice. A retrospective cohort study.

OBJECTIVES: Are multiple missed appointments in general practice associated with increased use of hospital services and missingness from hospital care? This novel study explores this in a population representative sample for the first time. DESIGN, SETTING, PARTICIPANTS: A large, retrospective cohort (n = 824,374) of patient records from a nationally representative sample of GP practices, Scotland, 2013-2016. Requested data were extracted by a Trusted Third Party for the NHS, anonymised and linked to a unique patient ID, in the NHS Safehaven for analysis using established NHS Scotland linkage. We calculated the per-patient number of GP missed appointments from individual appointments and investigated the likelihood of hospital appointment or admission outcomes using a negative binomial model offset by number of GP appointments made. These models also controlled for age, sex, Scottish Index of Multiple Deprivation (SIMD) and number of long- term conditions (LTCs). MAIN OUTCOME MEASURES: Hospital attendance: Outpatient clinic attendances; hospital admissions; Emergency Department (ED) attendances. Hospital missingness: 'Did not attend' (DNAs) outpatient clinic appointments, 'irregular discharges' from admissions, and 'left before care completed' ED care episodes. RESULTS: Attendance: Patients in the high missed GP appointment (HMA) category were higher users of outpatient services (rate ratio (RR) 1.90, 95% confidence intervals (CI) 1.88-1.93) compared to those who missed none (NMA) with a much higher attendance risk at mental health services (RR 4.56, 95% CI 4.31-4.83). HMA patients were more likely to be admitted to hospital; general admissions (RR 1.67, 95% CI 1.65-1.68), maternity (RR 1.24, 95% CI 1.20-1.28) and mental health (RR 1.23, 95% CI 1.15-1.31), compared to NMA patients. Missing GP appointments was not associated with ED attendance; (RR 1.00, CI 0.99-1.01). Missingness: HMA patients were at greater risk of missing outpatient appointments (RR 1.62, 95% CI 1.60-1.64) than NMA patients; with a much higher risk of non-attendance at mental health services (RR 7.83, 95% CI 7.35-8.35). Patients were more likely to leave hospital before their care plan was completed-taking 'irregular discharges' (RR 4.56, 95% CI 4.31-4.81). HMA patients were no more at risk of leaving emergency departments 'without care being completed' (RR1.02, 95 CI 0.95-1.09). CONCLUSIONS: Patients who miss high numbers of GP appointments are higher users of outpatient and inpatient hospital care but not of emergency departments, signalling high treatment burden. The pattern of 'missingness' is consistent from primary care to hospital care: patients who have patterns of missing GP appointments have patterns of missing many outpatient appointments and are more likely to experience 'irregular discharge' from in-patient care. Missingness from outpatient mental health services is very high. Policymakers, health service planners and clinicians should consider the role and contribution of 'missingness' in health care to improving patient safety and care.

Correction: Multimorbidity, polypharmacy, and COVID-19 infection within the UK Biobank cohort.

[This corrects the article DOI: 10.1371/journal.pone.0238091.].

Association between patterns of alcohol consumption (beverage type, frequency and consumption with food) and risk of adverse health outcomes: a prospective cohort study.

BACKGROUND: Alcohol consumption is a leading contributor to death and disability worldwide, but previous research has not examined the effects of different patterns of alcohol consumption. The study objective was to understand the relationship between different alcohol consumption patterns and adverse health outcomes risk, adjusting for average amount consumed among regular drinkers. METHODS: This was a prospective cohort study of UK Biobank (UKB) participants. Abstainers, infrequent alcohol consumers or those with previous cancer, myocardial infarction (MI), stroke or liver cirrhosis were excluded. We used beverage type, consumption with food and consumption frequency as exposures and adjusted for potential confounding. All-cause mortality, major cardiovascular events-MACE (MI/stroke/cardiovascular death), accidents/injuries, liver cirrhosis, all-cause and alcohol-related cancer incidence over 9-year median follow-up period were outcomes of interest. RESULTS: The final sample size for analysis was N = 309,123 (61.5% of UKB sample). Spirit drinking was associated with higher adjusted mortality (hazard ratio (HR) 1.25; 95% confidence intervals (CI) 1.14-1.38), MACE (HR 1.31; 95% CI 1.15-1.50), cirrhosis (HR 1.48; 95% CI 1.08-2.03) and accident/injuries (HR 1.10; 95% CI 1.03-1.19) risk compared to red wine drinking, after adjusting for the average weekly alcohol consumption amounts. Beer/cider drinkers were also at a higher risk of mortality (HR 1.18; 95% CI 1.10-1.27), MACE (HR 1.16; 95% CI 1.05-1.27), cirrhosis (HR 1.36; 95% CI 1.06-1.74) and accidents/injuries (HR 1.11; 95% CI 1.06-1.17). Alcohol consumption without food was associated with higher adjusted mortality (HR 1.10; 95% CI 1.02-1.17) risk, compared to consumption with food. Alcohol consumption over 1-2 times/week had higher adjusted mortality (HR 1.09; 95% CI 1.03-1.16) and MACE (HR 1.14; 95% CI 1.06-1.23) risk, compared to 3-4 times/week, adjusting for the amount of alcohol consumed. CONCLUSION: Red wine drinking, consumption with food and spreading alcohol intake over 3-4 days were associated with lower risk of mortality and vascular events among regular alcohol drinkers, after adjusting for the effects of average amount consumed. Selection bias and residual confounding are important possible limitations. These findings, if replicated and validated, have the potential to influence policy and practice advice on less harmful patterns of alcohol consumption.

Prevalence of chronic pain in LTCs and multimorbidity: A cross-sectional study using UK Biobank.

OBJECTIVES: Chronic pain is often experienced alongside other long-term conditions (LTCs), yet our understanding of this, particularly in relation to multimorbidity (≥2 LTCs) is poor. We aimed to examine associations between the presence/extent of chronic pain with type/number of LTCs experienced. METHODS: We examined the relationship between number/type of LTCs (N = 45) in UK Biobank participants (n = 500,295) who self-reported chronic pain lasting ≥3 months in seven body sites or widespread. Relative risk ratios (RRR) for presence/extent of chronic pain sites were compared using logistic regression adjusted for sociodemographic (sex/age/socioeconomic status) and lifestyle factors (smoking/alcohol intake/BMI/physical activity). RESULTS: 218,648 participants self-reported chronic pain. Of these, 69.1% reported ≥1 LTC and 36.2% reported ≥2 LTCs. In 31/45 LTCs examined, >50% of participants experienced chronic pain. Chronic pain was common with migraine/headache and irritable bowel syndrome where pain is a primary symptom, but also with mental health conditions and diseases of the digestive system. Participants with >4 LTCs were over three times as likely to have chronic pain (RRR 3.56, 95% confidence intervals (CIs) 3.44-3.68) and 20 times as likely to have widespread chronic pain (RRR 20.13, 95% CI 18.26-22.19) as those with no LTCs. CONCLUSIONS: Chronic pain is extremely common across a wide range of LTCs. People with multimorbidity were at higher risk of having a greater extent of chronic pain. These results show that chronic pain is a key factor for consideration in the management of patients with LTCs or multimorbidity.

Patterns of multimorbidity and their effects on adverse outcomes in rheumatoid arthritis: a study of 5658 UK Biobank participants.

OBJECTIVE: To investigate how the type and number of long-term conditions (LTCs) impact on all-cause mortality and major adverse cardiovascular events (MACE) in people with rheumatoid arthritis (RA). DESIGN: Population-based longitudinal cohort study. SETTING: UK Biobank. PARTICIPANTS: UK Biobank participants (n=502 533) aged between 37 and 73 years old. PRIMARY OUTCOME MEASURES: Primary outcome measures were risk of all-cause mortality and MACE. METHODS: We examined the relationship between LTC count and individual comorbid LTCs (n=42) on adverse clinical outcomes in participants with self-reported RA (n=5658). Risk of all-cause mortality and MACE were compared using Cox's proportional hazard models adjusted for lifestyle factors (smoking, alcohol intake, physical activity), demographic factors (sex, age, socioeconomic status) and rheumatoid factor. RESULTS: 75.7% of participants with RA had multimorbidity and these individuals were at increased risk of all-cause mortality and MACE. RA and >4 LTCs showed a threefold increased risk of all-cause mortality (HR 3.30, 95% CI 2.61 to 4.16), and MACE (HR 3.45, 95% CI 2.66 to 4.49) compared with those without LTCs. Of the comorbid LTCs studied, osteoporosis was most strongly associated with adverse outcomes in participants with RA compared with those without RA or LTCs: twofold increased risk of all-cause mortality (HR 2.20, 95% CI 1.55 to 3.12) and threefold increased risk of MACE (HR 3.17, 95% CI 2.27 to 4.64). These findings remained in a subset (n=3683) with RA diagnosis validated from clinical records or medication reports. CONCLUSION: Those with RA and other LTCs, particularly comorbid osteoporosis, are at increased risk of adverse outcomes, although the role of corticosteroids could not be evaluated in this study. These results are clinically relevant for the monitoring and management of RA across the healthcare system, and future clinical guidelines for RA should acknowledge the importance of multimorbidity.

Association between childhood maltreatment and the prevalence and complexity of multimorbidity: A cross-sectional analysis of 157,357 UK Biobank participants.

BACKGROUND: Child maltreatment is associated with long-term conditions (LTCs) in adulthood. Its relationship to multimorbidity (≥2 LTCs) is less clear. We explore the relationship between child maltreatment, multimorbidity and factors complicating management. METHODS: Cross-sectional analysis of 157,357 UK Biobank participants. Experience of four maltreatment types (physical/sexual/emotional/neglect) was identified. We explored the relationship between type, number and frequency of maltreatment and LTC count (0, 1, 2, 3, ≥4) using multinomial logistic regression. Binary logistic regression assessed the relationship between maltreatment and self-rated health, loneliness, social isolation, frailty and widespread pain in those with multimorbidity, adjusting for sociodemographics and lifestyle factors. RESULTS: 52,675 participants (33%) experienced ≥1 type of maltreatment; 983 (0.6%) experienced all four. Type, frequency and number of types of maltreatment were associated with higher LTC count. People experiencing four types of maltreatment were 5 times as likely to have a LTC count of ≥4 as those experiencing none (odds ratio (OR): 5.16; 99% confidence interval (CI): 3.77-7.07). Greater number of types of maltreatment was associated with higher prevalence of combined physical/mental health LTCs (OR: 2.99; 99% CI: 2.54-3.51 for four types of maltreatment). Compared to people who reported no maltreatment, people experiencing all four types of maltreatment were more likely to have poor self-rated health (OR: 3.56; 99% CI: 2.58-4.90), loneliness (OR: 3.16; 99% CI: 2.17-4.60), social isolation (OR: 1.45; 99% CI: 1.03-2.05), widespread pain (OR: 3.19; 99% CI: 1.87-5.44) and frailty (OR: 3.21; 99% CI: 2.04-5.05). CONCLUSION: Peoplewith a history of maltreatment have higher LTC counts and potentially more complicated management needs reinforcing calls for early intervention.

Multimorbidity, polypharmacy, and COVID-19 infection within the UK Biobank cohort.

BACKGROUND: It is now well recognised that the risk of severe COVID-19 increases with some long-term conditions (LTCs). However, prior research primarily focuses on individual LTCs and there is a lack of data on the influence of multimorbidity (≥2 LTCs) on the risk of COVID-19. Given the high prevalence of multimorbidity, more detailed understanding of the associations with multimorbidity and COVID-19 would improve risk stratification and help protect those most vulnerable to severe COVID-19. Here we examine the relationships between multimorbidity, polypharmacy (a proxy of multimorbidity), and COVID-19; and how these differ by sociodemographic, lifestyle, and physiological prognostic factors. METHODS AND FINDINGS: We studied data from UK Biobank (428,199 participants; aged 37-73; recruited 2006-2010) on self-reported LTCs, medications, sociodemographic, lifestyle, and physiological measures which were linked to COVID-19 test data. Poisson regression models examined risk of COVID-19 by multimorbidity/polypharmacy and effect modification by COVID-19 prognostic factors (age/sex/ethnicity/socioeconomic status/smoking/physical activity/BMI/systolic blood pressure/renal function). 4,498 (1.05%) participants were tested; 1,324 (0.31%) tested positive for COVID-19. Compared with no LTCs, relative risk (RR) of COVID-19 in those with 1 LTC was no higher (RR 1.12 (CI 0.96-1.30)), whereas those with ≥2 LTCs had 48% higher risk; RR 1.48 (1.28-1.71). Compared with no cardiometabolic LTCs, having 1 and ≥2 cardiometabolic LTCs had a higher risk of COVID-19; RR 1.28 (1.12-1.46) and 1.77 (1.46-2.15), respectively. Polypharmacy was associated with a dose response higher risk of COVID-19. All prognostic factors were associated with a higher risk of COVID-19 infection in multimorbidity; being non-white, most socioeconomically deprived, BMI ≥40 kg/m2, and reduced renal function were associated with the highest risk of COVID-19 infection: RR 2.81 (2.09-3.78); 2.79 (2.00-3.90); 2.66 (1.88-3.76); 2.13 (1.46-3.12), respectively. No multiplicative interaction between multimorbidity and prognostic factors was identified. Important limitations include the low proportion of UK Biobank participants with COVID-19 test data (1.05%) and UK Biobank participants being more affluent, healthier and less ethnically diverse than the general population. CONCLUSIONS: Increasing multimorbidity, especially cardiometabolic multimorbidity, and polypharmacy are associated with a higher risk of developing COVID-19. Those with multimorbidity and additional factors, such as non-white ethnicity, are at heightened risk of COVID-19.

Association of SBP and BMI with cognitive and structural brain phenotypes in UK Biobank.

OBJECTIVE: To test for associations between SBP and BMI, with domain-specific cognitive abilities and examine which brain structural phenotypes mediate those associations. METHODS: Using cross-sectional UK Biobank data (final N = 28 412), we examined SBP/BMI vs. cognitive test scores of pairs-matching, matrix completion, trail making test A/B, digit symbol substitution, verbal-numerical reasoning, tower rearranging and simple reaction time. We adjusted for potential confounders of age, sex, deprivation, medication, apolipoprotein e4 genotype, smoking, population stratification and genotypic array. We tested for mediation via multiple structural brain imaging phenotypes and corrected for multiple testing with false discovery rate. RESULTS: We found positive associations for higher BMI with worse reaction time, reasoning, tower rearranging and matrix completion tasks by 0.024-0.067 SDs per BMI SD (all P < 0.001). Higher SBP was associated with worse reasoning (0.034 SDs) and matrix completion scores (-0.024 SDs; both P < 0.001). Both BMI and SBP were associated with multiple brain structural metrics including total grey/white matter volumes, frontal lobe volumes, white matter tract integrity and white matter hyperintensity volumes: specific metrics mediated around one-third of the associations with cognition. CONCLUSION: Our findings add to the body of evidence that addressing cardiovascular risk factors may also preserve cognitive function, via specific aspects of brain structure.

General practice recording of adverse childhood experiences: a retrospective cohort study of GP records.

BACKGROUND: Adverse childhood experiences (ACEs) are linked to negative health outcomes in adulthood. Poor engagement with services may, in part, mediate the association between adverse outcomes and ACEs. While appointment recording is comprehensive, it is not yet known if or how ACEs are recorded in the GP clinical record (GPR). AIM: To investigate recording of ACEs in the GPR and assess associations between available ACE-related Read codes and missed appointments. DESIGN & SETTING: Retrospective cohort study of 824 374 anonymised GPRs. Nationally representative sample of 136 Scottish general practices; data collected 2013-2016. METHOD: Read codes were mapped onto ACE questionnaire and wider ACE-related domains. Natural language processing (NLP) was used to augment capture of non-Read-coded ACEs. Frequency counts and proportions of mapped codes, and associations of these with defined levels of missing GP appointments, are reported. RESULTS: In total, 0.4% of patients had a record of any code that mapped onto the ACE questionnaire, contrasting with survey-reported rates of 47% in population samples. This increased only modestly by including inferred ACEs that related to safeguarding children concerns, wider aspects of ACEs, and adult consequences of ACEs. Augmentation via NLP did not substantially increase capture. Despite poor recording, there was an association between ever having an ACE code recorded and higher rates of missing GP appointments. CONCLUSION: General practices would require substantial support to implement the recording of ACEs in the GPR. This study adds to the evidence that patients who often miss appointments are more likely to be socially vulnerable.

Relationship between multimorbidity, demographic factors and mortality: findings from the UK Biobank cohort.

BACKGROUND: Multimorbidity is associated with higher mortality, but the relationship with cancer and cardiovascular mortality is unclear. The influence of demographics and type of condition on the relationship of multimorbidity with mortality remains unknown. We examine the relationship between multimorbidity (number/type) and cause of mortality and the impact of demographic factors on this relationship. METHODS: Data source: the UK Biobank; 500,769 participants; 37-73 years; 53.7% female. Exposure variables: number and type of long-term conditions (LTCs) (N = 43) at baseline, modelled separately. Cox regression models were used to study the impact of LTCs on all-cause/vascular/cancer mortality during median 7-year follow-up. All-cause mortality regression models were stratified by age/sex/socioeconomic status. RESULTS: All-cause mortality is 2.9% (14,348 participants). Of all deaths, 8350 (58.2%) were cancer deaths and 2985 (20.8%) vascular deaths. Dose-response relationship is observed between the increasing number of LTCs and all-cause/cancer/vascular mortality. A strong association is observed between cardiometabolic multimorbidity and all three clinical outcomes; non-cardiometabolic multimorbidity (excluding cancer) is associated with all-cause/vascular mortality. All-cause mortality risk for those with ≥ 4 LTCs was nearly 3 times higher than those with no LTCs (HR 2.79, CI 2.61-2.98); for ≥ 4 cardiometabolic conditions, it was > 3 times higher (HR 3.20, CI 2.56-4.00); and for ≥ 4 non-cardiometabolic conditions (excluding cancer), it was 50% more (HR 1.50, CI 1.36-1.67). For those with ≥ 4 LTCs, morbidity combinations that included cardiometabolic conditions, chronic kidney disease, cancer, epilepsy, chronic obstructive pulmonary disease, depression, osteoporosis and connective tissue disorders had the greatest impact on all-cause mortality. In the stratified model by age/sex, absolute all-cause mortality was higher among the 60-73 age group with an increasing number of LTCs; however, the relative effect size of the increasing number of LTCs on higher mortality risk was larger among those 37-49 years, especially men. While socioeconomic status was a significant predictor of all-cause mortality, mortality risk with increasing number of LTCs remained constant across different socioeconomic gradients. CONCLUSIONS: Multimorbidity is associated with higher all-cause/cancer/vascular mortality. Type, as opposed to number, of LTCs may have an important role in understanding the relationship between multimorbidity and mortality. Multimorbidity had a greater relative impact on all-cause mortality in middle-aged as opposed to older populations, particularly males, which deserves exploration.

Morbidity, mortality and missed appointments in healthcare: a national retrospective data linkage study.

BACKGROUND: Recently, studies have examined the underlying patient and practice factors for missed appointments, but less is known about the impact on patient health. People with one or more long-term conditions who fail to attend appointments may be at risk of premature death. This is the first study to examine the effect of missed primary healthcare appointments on all-cause mortality in those with long-term mental and physical health conditions. METHODS: We used a large, nationwide retrospective cohort (n = 824,374) extracted from routinely collected general practice data across Scotland over a 3-year period from September 2013 until September 2016. This data encompasses appointment history for approximately 15% of the Scottish population, and was linked to Scottish deaths records for patients who had died within a 16-month follow-up period. We generated appointment attendance history, number of long-term conditions and prescriptions data for patients. These factors were used in negative binomial and Cox's proportional hazards modelling to examine the risk of missing appointments and all-cause mortality. RESULTS: Patients with a greater number of long-term conditions had an increased risk of missing general practice appointments despite controlling for number of appointments made, particularly among patients with mental health conditions. These patients were at significantly greater risk of all-cause mortality, and showed a dose-based response with increasing number of missed appointments. Patients with long-term mental health conditions who missed more than two appointments per year had a greater than 8-fold increase in risk of all-cause mortality compared with those who missed no appointments. These patients died prematurely, commonly from non-natural external factors such as suicide. CONCLUSIONS: Missed appointments represent a significant risk marker for all-cause mortality, particularly in patients with mental health conditions. For these patients, existing primary healthcare appointment systems are ineffective. Future interventions should be developed with a particular focus on increasing attendance by these patients.

Frailty and pre-frailty in middle-aged and older adults and its association with multimorbidity and mortality: a prospective analysis of 493 737 UK Biobank participants.

BACKGROUND: Frailty is associated with older age and multimorbidity (two or more long-term conditions); however, little is known about its prevalence or effects on mortality in younger populations. This paper aims to examine the association between frailty, multimorbidity, specific long-term conditions, and mortality in a middle-aged and older aged population. METHODS: Data were sourced from the UK Biobank. Frailty phenotype was based on five criteria (weight loss, exhaustion, grip strength, low physical activity, slow walking pace). Participants were deemed frail if they met at least three criteria, pre-frail if they fulfilled one or two criteria, and not frail if no criteria were met. Sociodemographic characteristics and long-term conditions were examined. The outcome was all-cause mortality, which was measured at a median of 7 years follow-up. Multinomial logistic regression compared sociodemographic characteristics and long-term conditions of frail or pre-frail participants with non-frail participants. Cox proportional hazards models examined associations between frailty or pre-frailty and mortality. Results were stratified by age group (37-45, 45-55, 55-65, 65-73 years) and sex, and were adjusted for multimorbidity count, socioeconomic status, body-mass index, smoking status, and alcohol use. FINDINGS: 493 737 participants aged 37-73 years were included in the study, of whom 16 538 (3%) were considered frail, 185 360 (38%) pre-frail, and 291 839 (59%) not frail. Frailty was significantly associated with multimorbidity (prevalence 18% [4435/25 338] in those with four or more long-term conditions; odds ratio [OR] 27·1, 95% CI 25·3-29·1) socioeconomic deprivation, smoking, obesity, and infrequent alcohol consumption. The top five long-term conditions associated with frailty were multiple sclerosis (OR 15·3; 99·75% CI 12·8-18·2); chronic fatigue syndrome (12·9; 11·1-15·0); chronic obstructive pulmonary disease (5·6; 5·2-6·1); connective tissue disease (5·4; 5·0-5·8); and diabetes (5·0; 4·7-5·2). Pre-frailty and frailty were significantly associated with mortality for all age strata in men and women (except in women aged 37-45 years) after adjustment for confounders. INTERPRETATION: Efforts to identify, manage, and prevent frailty should include middle-aged individuals with multimorbidity, in whom frailty is significantly associated with mortality, even after adjustment for number of long-term conditions, sociodemographics, and lifestyle. Research, clinical guidelines, and health-care services must shift focus from single conditions to the requirements of increasingly complex patient populations. FUNDING: CSO Catalyst Grant and National Health Service Research for Scotland Career Research Fellowship.

Risk factors and mortality associated with multimorbidity in people with stroke or transient ischaemic attack: a study of 8,751 UK Biobank participants.

BACKGROUND: Multimorbidity is common in stroke, but the risk factors and effects on mortality remain poorly understood. OBJECTIVE: To examine multimorbidity and its associations with sociodemographic/lifestyle risk factors and all-cause mortality in UK Biobank participants with stroke or transient ischaemic attack (TIA). DESIGN: Data were obtained from an anonymized community cohort aged 40-72 years. Overall, 42 comorbidities were self-reported by those with stroke or TIA. Relative risk ratios demonstrated associations between participant characteristics and number of comorbidities. Hazard ratios demonstrated associations between the number and type of comorbidities and all-cause mortality. Results were adjusted for age, sex, socioeconomic status, smoking, and alcohol intake. Data were linked to national mortality data. Median follow-up was 7 years. RESULTS: Of 8,751 participants (mean age 60.9±6.7 years) with stroke or TIA, the all-cause mortality rate over 7 years was 8.4%. Over 85% reported ≥1 comorbidities. Age, socioeconomic deprivation, smoking and less frequent alcohol intake were associated with higher levels of multimorbidity. Increasing multimorbidity was associated with higher all-cause mortality. Mortality risk was double for those with ≥5 comorbidities compared to those with none. Having cancer, coronary heart disease, diabetes, or chronic obstructive pulmonary disease significantly increased mortality risk. Presence of any cardiometabolic comorbidity significantly increased mortality risk, as did any non-cardiometabolic comorbidity. CONCLUSIONS: In stroke survivors, the number of comorbidities may be a more helpful predictor of mortality than type of condition. Stroke guidelines should take greater account of comorbidities, and interventions are needed that improve outcomes for people with multimorbidity and stroke.

Examining patterns of multimorbidity, polypharmacy and risk of adverse drug reactions in chronic obstructive pulmonary disease: a cross-sectional UK Biobank study.

OBJECTIVE: This study aims: (1) to describe the pattern and extent of multimorbidity and polypharmacy in UK Biobank participants with chronic obstructive pulmonary disease (COPD) and (2) to identify which comorbidities are associated with increased risk of adverse drug reactions (ADRs) resulting from polypharmacy. DESIGN: Cross-sectional. SETTING: Community cohort. PARTICIPANTS: UK Biobank participants comparing self-reported COPD (n=8317) with no COPD (n=494 323). OUTCOMES: Multimorbidity (≥4 conditions) and polypharmacy (≥5 medications) in participants with COPD versus those without. Risk of ADRs (taking ≥3 medications associated with falls, constipation, urinary retention, central nervous system (CNS) depression, bleeding or renal injury) in relation to the presence of COPD and individual comorbidities. RESULTS: Multimorbidity was more common in participants with COPD than those without (17% vs 4%). Polypharmacy was highly prevalent (52% with COPD taking ≥5 medications vs 18% in those without COPD). Adjusting for age, sex and socioeconomic status, those with COPD were significantly more likely than those without to be prescribed ≥3 medications contributing to falls (OR 2.27, 95% CI 2.13 to 2.42), constipation (OR 3.42, 95% CI 3.10 to 3.77), urinary retention (OR 3.38, 95% CI 2.94 to 3.87), CNS depression (OR 3.75, 95% CI 3.31 to 4.25), bleeding (OR 4.61, 95% CI 3.35 to 6.19) and renal injury (OR 2.22, 95% CI 1.86 to 2.62). Concomitant cardiovascular disease was associated with the greatest risk of taking ≥3 medications associated with falls/renal injury. Concomitant mental health conditions were most strongly associated with medications linked with CNS depression/urinary retention/bleeding. CONCLUSIONS: Multimorbidity is common in COPD and associated with high levels of polypharmacy. Co-prescription of drugs with various ADRs is common. Future research should examine the effects on healthcare outcomes of co-prescribing multiple drugs with similar potential ADRs. Clinical guidelines should emphasise assessment of multimorbidity and ADR risk.

Multimorbidity and co-morbidity in atrial fibrillation and effects on survival: findings from UK Biobank cohort.

Aims: To examine the number and type of co-morbid long-term health conditions (LTCs) and their associations with all-cause mortality in an atrial fibrillation (AF) population. Methods and results: Community cohort participants (UK Biobank n = 502 637) aged 37-73 years were recruited between 2006 and 2010. Self-reported LTCs (n = 42) identified in people with AF at baseline. All-cause mortality was available for a median follow-up of 7 years (interquartile range 76-93 months). Hazard ratios (HRs) examined associations between number and type of co-morbid LTC and all-cause mortality, adjusting for age, sex, socio-economic status, smoking, and anticoagulation status. Three thousand six hundred fifty-one participants (0.7% of the study population) reported AF; mean age was 61.9 years. The all-cause mortality rate was 6.7% (248 participants) at 7 years. Atrial fibrillation participants with ≥4 co-morbidities had a six-fold higher risk of mortality compared to participants without any LTC. Co-morbid heart failure was associated with higher risk of mortality [HR 2.96, 95% confidence interval (CI) 1.83-4.80], whereas the presence of co-morbid stroke did not have a significant association. Among non-cardiometabolic conditions, presence of chronic obstructive pulmonary disease (HR 3.31, 95% CI 2.14-5.11) and osteoporosis (HR 3.13, 95% CI 1.63-6.01) was associated with a higher risk of mortality. Conclusion: Survival in middle-aged to older individuals with self-reported AF is strongly correlated with level of multimorbidity. This group should be targeted for interventions to optimize their management, which in turn may potentially reduce the impact of their co-morbidities on survival. Future AF clinical guidelines need to place greater emphasis on the issue of co-morbidity.