1310 FRAILTY, LONELINESS AND SOCIAL ISOLATION IN THE UK BIOBANK COHORT

Background

Three challenges for ageing populations are frailty (a state of reduced physiological reserve), social isolation (objective lack of social connections), and loneliness (subjective experience of feeling alone). These are associated with adverse outcomes. This study aims to examine how frailty in combination with loneliness or social isolation is associated with all-cause mortality and hospitalisation rate using data from UK Biobank, a large population-based research cohort.

Methods

502,456 UK Biobank participants were recruited 2006-2010. Baseline data assessed frailty (via two measures: Fried frailty phenotype, Rockwood frailty index), social isolation, and loneliness. Adjusted cox-proportional hazards models assessed association between frailty in combination with loneliness or social isolation and all-cause mortality. Negative binomial regression models assessed hospitalisation rate.

Findings

Frailty, social isolation, and loneliness are common in UK Biobank (frail as per frailty phenotype 3.38%, frail as per frailty index 4.68%, social isolation 9.04%, loneliness 4.75%). Social isolation/loneliness were more common in frailty/pre-frailty. Frailty is associated with increased mortality regardless of social isolation/loneliness. Hazard ratios for frailty (frailty phenotype) were 3.38 (3.11-3.67) with social isolation and 2.89 (2.75-3.05) without social isolation, 2.94 (2.64-3.27) with loneliness and 2.9 (2.76-3.04) without loneliness. Social isolation was associated with increased mortality at all levels of frailty; loneliness only in robust/pre-frail. Frailty was also associated with hospitalisation regardless of social isolation/loneliness. Incidence rate ratios for frailty (frailty phenotype) were 3.93 (3.66-4.23) with social isolation and 3.75 (3.6-3.9) without social isolation, 4.42 (4.04-4.83) with loneliness and 3.69 (3.55-3.83) without loneliness. At all levels frailty, social isolation/loneliness are associated with increased hospitalisation Results were similar using the frailty index definition.

Conclusion

Social isolation is relevant at all levels frailty. Risk of loneliness is more pronounced in those who are robust or pre-frail. Proactive identification of loneliness, regardless of physical health status may provide opportunities for intervention.

POS0576 ASSOCIATION BETWEEN POTENTIAL PROGNOSTIC FACTORS AND ADVERSE HEALTH OUTCOMES IN RHEUMATOID ARTHRITIS: A STUDY OF 5658 UK BIOBANK PARTICIPANTS

Background

There is a pressing need to identify simple prognostic factors, which are readily available in primary and secondary care settings, that can predict adverse health outcomes in people with rheumatoid arthritis (RA). Exploring various clinical, physiological and patient-reported measures as prognostic factors may enhance risk stratification and promote more personalised care for RA patients.

Objectives

To determine the association, if any, between selected prognostic factors and all-cause mortality and major adverse cardiovascular events (MACE; including myocardial infarction and stroke) in an RA population.

Methods

UK Biobank participants that self-reported RA were included in this study. Prognostic factors were selected from the literature based on relevance, predictive potential, simplicity and accessibility in a primary/secondary care setting. Those included were categorised into the following domains: anthropometric measures (body mass index (BMI), body fat percentage, waist circumference, waist-to-hip ratio), functional measures (hand grip strength (HGS), usual walking pace (UWP)), inflammatory markers (C-reactive protein (CRP)), patient-reported measures (pain), physiological measures (blood pressure (BP), heart rate (HR)) and serological markers (rheumatoid factor (RF)), with normal ranges used as reference categories. Associations between individual factors and outcomes were explored using Cox proportional hazards models. Models were adjusted for age, sex, socioeconomic status, number of additional long-term conditions and smoking status in the first instance to identify potential individual predictors. Models were then further adjusted for any identified individual predictors to determine the most important prognostic factors.

Results

5658 (1.1%) UK Biobank participants self-reported RA (mean age 59 (standard deviation 7.13); 69.8% female). 670 deaths (median 11 years) and 370 MACE (median 8 years) were recorded during the follow-up period. Several significant individual associations with all-cause mortality (Figure 1A) and MACE (Figure 1B) were found. After further adjustment for these significant individual predictors, the following factors demonstrated significant associations with risk of all-cause mortality, independent of the other significant predictors: underweight BMI (<18.5kg/m2) (hazard ratio (HR) 2.96 [95% confidence intervals (CI) 1.59-5.51]), obese BMI (≥30.0kg/m2) (HR 0.52 [95% CI 0.36-0.76]), 3-10mg/L CRP (HR 1.41 [95% CI 1.14-1.75]), >10mg/L CRP (HR 1.77 [95% CI 1.39-2.26]), low HGS (<16kg female or <27kg male) (HR 1.28 [95% CI 1.05-1.56]) and slow UWP (patient-reported) (HR 1.31 [95% CI 1.06-1.62]). Likewise, the following factors were found to be significantly associated with MACE, independent of other significant factors: >10mg/L CRP (HR 1.62 [95% CI 1.19-2.20]), low HGS (HR 1.61 [95% CI 1.26-2.07]) and slow UWP (HR 1.50 [95 % CI 1.15-1.97]).

Conclusion

In this RA population, the risk of all-cause mortality was approximately three-fold higher in those who have an underweight BMI when compared to those who have a BMI in the normal range, when adjusted for all other significant factors, while an obese BMI appeared to lower this risk, consistent with the “obesity paradox” reported in RA [1]. Increased levels of CRP, low HGS and slow UWP were also all independently associated with an increased risk of all-cause mortality and MACE. Our findings highlight the potential value of these factors for predicting adverse outcomes in RA populations. A simple, yet multidimensional approach to risk assessment, combining well-tolerated, easily repeatable measures such as those included here may provide important prognostic information at both primary and secondary care levels, while limiting excessive and overly invasive testing on RA patients.

References

[1]Wolfe F, Michaud K. Effect of body mass index on mortality and clinical status in rheumatoid arthritis. Arthritis Care Res (Hoboken). 2012; 64(10): 1471-1479. doi:10.1002/acr.21627

Acknowledgements

This work is supported by the Medical Research Council [grant number: MR/N013166/1].

Disclosure of Interests

Jordan Canning: None declared, Stefan Siebert Grant/research support from: Departmental research grants/support from: AbbVie, Amgen, Boehringer Ingelheim, Bristol Myers Squibb, GSK, Janssen, Novartis and UCB., Bhautesh Jani: None declared, Frances Mair: None declared, Barbara Nicholl: None declared.

Associations between multimorbidity and adverse health outcomes in UK Biobank and the SAIL Databank: A comparison of longitudinal cohort studies

BACKGROUND

Cohorts such as UK Biobank are increasingly used to study multimorbidity; however, there are concerns that lack of representativeness may lead to biased results. This study aims to compare associations between multimorbidity and adverse health outcomes in UK Biobank and a nationally representative sample.

METHODS AND FINDINGS

These are observational analyses of cohorts identified from linked routine healthcare data from UK Biobank participants (n = 211,597 from England, Scotland, and Wales with linked primary care data, age 40 to 70, mean age 56.5 years, 54.6% women, baseline assessment 2006 to 2010) and from the Secure Anonymised Information Linkage (SAIL) databank (n = 852,055 from Wales, age 40 to 70, mean age 54.2, 50.0% women, baseline January 2011). Multimorbidity (n = 40 long-term conditions [LTCs]) was identified from primary care Read codes and quantified using a simple count and a weighted score. Individual LTCs and LTC combinations were also assessed. Associations with all-cause mortality, unscheduled hospitalisation, and major adverse cardiovascular events (MACEs) were assessed using Weibull or negative binomial models adjusted for age, sex, and socioeconomic status, over 7.5 years follow-up for both datasets. Multimorbidity was less common in UK Biobank than SAIL (26.9% and 33.0% with ≥2 LTCs in UK Biobank and SAIL, respectively). This difference was attenuated, but persisted, after standardising by age, sex, and socioeconomic status. The association between increasing multimorbidity count and mortality, hospitalisation, and MACE was similar between both datasets at LTC counts of ≤3; however, above this level, UK Biobank underestimated the risk associated with multimorbidity (e.g., mortality hazard ratio for 2 LTCs 1.62 (95% confidence interval 1.57 to 1.68) in SAIL and 1.51 (1.43 to 1.59) in UK Biobank, hazard ratio for 5 LTCs was 3.46 (3.31 to 3.61) in SAIL and 2.88 (2.63 to 3.15) in UK Biobank). Absolute risk of mortality, hospitalisation, and MACE, at all levels of multimorbidity, was lower in UK Biobank than SAIL (adjusting for age, sex, and socioeconomic status). Both cohorts produced similar hazard ratios for some LTCs (e.g., hypertension and coronary heart disease), but UK Biobank underestimated the risk for others (e.g., alcohol-related disorders or mental health conditions). Hazard ratios for some LTC combinations were similar between the cohorts (e.g., cardiovascular conditions); however, UK Biobank underestimated the risk for combinations including other conditions (e.g., mental health conditions). The main limitations are that SAIL databank represents only part of the UK (Wales only) and that in both cohorts we lacked data on severity of the LTCs included.

CONCLUSIONS

In this study, we observed that UK Biobank accurately estimates relative risk of mortality, unscheduled hospitalisation, and MACE associated with LTC counts ≤3. However, for counts ≥4, and for some LTC combinations, estimates of magnitude of association from UK Biobank are likely to be conservative. Researchers should be mindful of these limitations of UK Biobank when conducting and interpreting analyses of multimorbidity. Nonetheless, the richness of data available in UK Biobank does offers opportunities to better understand multimorbidity, particularly where complementary data sources less susceptible to selection bias can be used to inform and qualify analyses of UK Biobank.

Long-term conditions, multimorbidity and colorectal cancer risk in the UK Biobank cohort

PURPOSE

Early identification of colorectal cancer (CRC) is an international priority. Multimorbidity (presence of ≥2 long-term conditions (LTCs)) is increasing and the relationship between CRC and LTCs is little-understood. This study explores the relationship between individual LTCs, multimorbidity and CRC incidence and mortality.

METHODS

Longitudinal analysis of the UK Biobank cohort, participants recruited 2006-2010; N = 500,195; excluding previous CRC at baseline. Baseline data was linked with cancer/mortality registers. Demographic characteristics, lifestyle factors, 43 LTCs, CRC family history, non-CRC cancers, and multimorbidity count were recorded. Variable selection models identified candidate LTCs potentially predictive of CRC outcomes and Cox regression models tested for significance of associations between selected LTCs and outcomes.

RESULTS

Participants' age range: 37-73 (mean age 56.5; 54.5% female). CRC was diagnosed in 3669 (0.73%) participants, and 916 (0.18%) died from CRC during follow-up (median follow-up 7 years). CRC incidence was higher in the presence of heart failure (Hazard Ratio (HR) 1.96, 95% Confidence Interval (CI) 1.13-3.40), diabetes (HR 1.15, CI 1.01-1.32), glaucoma (HR 1.36, CI 1.06-1.74), male cancers (HR 1.44, CI 1.01-2.08). CRC mortality was higher in presence of epilepsy (HR 1.83, CI 1.03-3.26), diabetes (HR 1.32, CI 1.02-1.72), osteoporosis (HR 1.67, CI 1.12-2.58). No significant association was found between multimorbidity (≥2 LTCs) and CRC outcomes.

CONCLUSIONS

The associations of certain LTCs with CRC incidence and mortality has implications for clinical practice: presence of certain LTCs in patients presenting with CRC symptoms could trigger early investigation and diagnosis. Future research should explore causative mechanisms and patient perspectives.

An analysis of frailty and multimorbidity in 20,566 UK Biobank participants with type 2 diabetes

Background

Frailty and multimorbidity are common in type 2 diabetes (T2D), including people <65 years. Guidelines recommend adjustment of treatment targets in people with frailty or multimorbidity. It is unclear how recommendations to adjust treatment targets in people with frailty or multimorbidity should be applied to different ages. We assess implications of frailty/multimorbidity in middle/older-aged people with T2D.

Methods

We analysed UK Biobank participants (n = 20,566) with T2D aged 40–72 years comparing two frailty measures (Fried frailty phenotype and Rockwood frailty index) and two multimorbidity measures (Charlson Comorbidity index and count of long-term conditions (LTCs)). Outcomes were mortality, Major Adverse Cardiovascular Event (MACE), hospitalization with hypoglycaemia or fall/fracture.

Results

Here we show  that choice of measure influences the population identified: 42% of participants are frail or multimorbid by at least one measure; 2.2% by all four measures. Each measure is associated with mortality, MACE, hypoglycaemia, and fall or fracture. The absolute 5-year mortality risk is higher in older versus younger participants with a given level of frailty (e.g. 1.9%, and 9.9% in men aged 45 and 65, respectively, using frailty phenotype) or multimorbidity (e.g. 1.3%, and 7.8% in men with 4 LTCs aged 45 and 65, respectively). Using frailty phenotype, the relationship between higher HbA1c and mortality is stronger in frail compared with pre-frail or robust participants.

Conclusions

Assessment of frailty/multimorbidity should be embedded within routine management of middle-aged and older people with T2D. Method of identification as well as features such as age impact baseline risk and should influence clinical decisions (e.g. glycaemic control).

527 FRAILTY AND MULTIMORBIDITY IN TYPE 2 DIABETES: A UK BIOBANK ANALYSIS

Introduction

Frailty and multimorbidity are common in type 2 diabetes (T2D), including people &lt;65 years. Guidelines recommend adjustment of treatment targets in people with frailty or multimorbidity, however guidelines do not differentiate these two related states. It is unclear how recommendations to adjust treatment targets in people with frailty or multimorbidity should be applied to different ages. It is also not known if the relationship between HbA1c and outcomes is similar in people with and without frailty. We assess implications of frailty/multimorbidity in middle/older-aged people with T2D.

Methods

Analysis of UK Biobank participants (n = 20,566) with T2D aged 40-72 years comparing two frailty measures (frailty phenotype and frailty index) and two multimorbidity measures (Charlson comorbidity index and a simply count of 40 long-term conditions (LTCs)). Outomes: mortality (all-cause, cardiovascular- and cancer-related mortality), Major Adverse Cardiovascular Event (MACE), hospitalization with hypoglycaemia or fall/fracture.

Results

Measure choice influenced the population identified: 42% of participants were identified as frail/multimorbid by at least one measure; only 2.2% were identified by all four measures. Both frailty and multimorbidity, by all measures, were prevalent throughout the age range studied. Each measure was associated with mortality, MACE, hypoglycaemia and falls. The absolute 5-year mortality risk was higher in older versus younger participants with a given level of frailty (e.g. 1.9%, and 9.9% in men aged 45 and 65, respectively, using frailty phenotype) or multimorbidity (e.g. 1.3%, and 7.8% in men with 4 LTCs aged 45 and 65, respectively). Using frailty phenotype, the relationship between higher HbA1c and mortality was stronger in frail compared with pre-frail or robust participants.

Conclusion

Assessment of frailty/multimorbidity should be embedded within routine management of middle-aged and older people with T2D. Method of identification as well as features such as age impact baseline risk and should influence clinical decisions (e.g. glycaemic control).

AB0240 EXAMINING THE RELATIONSHIP BETWEEN RHEUMATOID ARTHRITIS, MULTIMORBIDITY AND ADVERSE HEALTH-RELATED OUTCOMES: A SYSTEMATIC REVIEW

Background:

Rheumatoid arthritis (RA) is a chronic autoimmune disorder characterised by inflammation of the synovial joints causing pain, swelling and stiffness. Multimorbidity (the presence of two or more long-term conditions) affects approximately two thirds of people with RA. However, the relationship between RA and multimorbidity is poorly understand, as is the effect of this relationship on mortality and other health-related outcomes, particularly those relating to physical functioning and well-being.

Objectives:

To explore existing literature to determine what is known about the effect, if any, of multimorbidity on mortality and other health-related outcomes in people with RA.

Methods:

A systematic review was conducted following a protocol prepared using PRISMA-P 2015 reporting guidelines, ensuring the quality of the review. Studies were sourced from electronic medical databases, specifically MEDLINE, Embase, CINAHL, PsycINFO, The Cochrane Library and Scopus, using a pre-defined search strategy. Studies were selected based on specified eligibility criteria and quality appraised using the Cochrane Prognosis Methods Group-developed, Quality in Prognostic Studies (QUIPS) tool. A narrative synthesis of findings was conducted.

Results:

In total, 15 studies fulfilled our criteria for inclusion in our review. Of these, 7 studies had mortality as an outcome, with 6 reporting a significant association between multimorbidity and increased risk of all-cause mortality in people with RA. Nine studies had functional status/disability as an outcome, with 2 of these studies also including quality of life. All 9 studies reported significant associations between multimorbidity and the aforementioned health-related outcomes, demonstrating poorer functional status/increased disability and reduced quality of life in people with RA and multimorbidity.

Conclusion:

Multimorbidity in people with RA is significantly associated with increased mortality and poor health-related outcomes in current literature. A better understanding of this relationship will provide an important foundation of knowledge to guide future health service design.

Acknowledgments:

This work was supported by the Medical Research Council (MRC) [Grant Reference: MR/N013166/1].

Disclosure of Interests:

Jordan Canning: None declared, Stefan Siebert Grant/research support from: BMS, Boehringer Ingelheim, Celgene, GlaxoSmithKline, Janssen, Novartis, Pfizer, UCB, Consultant of: AbbVie, Boehringer Ingelheim, Janssen, Novartis, Pfizer, UCB, Speakers bureau: AbbVie, Celgene, Janssen, Novartis, Bhautesh Jani: None declared, Frances Mair: None declared, Barbara Nicholl: None declared

P238 RA and multimorbidity in UK Biobank: association with all-cause mortality and major adverse cardiac events

Background

Multimorbidity, the presence of ≥ 2 long-term conditions (LTCs) is common in people with rheumatoid arthritis (RA). However, most research in RA has focused on cardiovascular disease and depression as co-occurring morbidities, rather than multiple LTCs or a wide range of conditions. This study hypothesised that risk of all-cause mortality and major adverse cardiac events (MACE) would be greater in those with RA and ≥2 LTCs than those with RA only. Further, we explored which individual LTCs were associated with increased risk of mortality and MACE.

Methods

Data from UK Biobank, a cohort of over 500,000 adults aged 37-73 years across England, Scotland and Wales was analysed. RA and 42 other LTCs of interest were self-reported by participants in a questionnaire and nurse-led interview. Information on sociodemographic (age, gender, socioeconomic status) and lifestyle factors (smoking status, BMI, alcohol frequency, physical activity) were also gathered. Rheumatoid factor levels were also determined. MACE and mortality were classified using linked hospitalisations and mortality register data (median follow up time 9 years). Data were analysed using age-adjusted Cox’s proportional hazard modelling to calculate risk of all-cause mortality or MACE, adjusted for variables listed above. Predictor variable: no RA no LTCs (reference group), only RA, RA + 1-3LTCs, RA + ≥4LTCs. Finally, the relationship between comorbidity with individual LTCs (of the 42 studied) and both health outcomes was considered.

Results

5,658 (1.1%) of participants in UK Biobank self-reported RA (69.8% female, mean age 59 years). 74.7% of participants reported at least one LTC in addition to RA (1-3 LTCs 64.3%, ≥4 LTCs 10.4%), compared to 63.8% of participants without RA. 7.7% (N = 437) of participants with RA died and 5.9% (n = 331) had MACE events during the follow-up period. There was a dose response relationship in RA between LTC category and all-cause mortality and MACE risk. Only RA: mortality HR 1.42, 95% CI 1.08, 1.87, MACE HR 1.61 95% CI 1.20, 2.18; RA + 1-3LTCs: mortality HR 1.99 95% CI 1.74, 2.27, MACE HR 1.89, 95% CI 1.61, 2.20; RA + ≥4LTCs: mortality HR 3.34, 95% CI 2.64, 4.22; MACE HR 3.45, 95% CI 2.66, 4.49) compared to those with no RA no LTCs (results presented from fully adjusted models). Of the 42 individual LTCs considered, comorbid osteoporosis was the most concerning; participants with both RA and osteoporosis had a two-fold increased risk of all-cause mortality (HR 2.20, 95% CI 1.55, 3.12) and three-fold increased risk of MACE outcomes (HR 3.17, 95% CI 2.17, 4.64) compared to those with neither condition.

Conclusion

Participants with RA and multimorbidity or comorbidity, particularly osteoporosis, are at increased risk of adverse health outcomes. These results have important clinical relevance for the monitoring and optimal management of RA across the healthcare system.

Disclosures

B. Nicholl None. R. McQueenie None. B. Jani None. S. Macdonald None. C. McCowan None. J. Canning None. F. Mair None. S. Siebert None.

An App-Delivered Self-Management Program for People With Low Back Pain: Protocol for the selfBACK Randomized Controlled Trial

Background

Low back pain (LBP) is prevalent across all social classes, in all age groups, and across industrialized and developing countries. From a global perspective, LBP is considered the leading cause of disability and negatively impacts everyday life and well-being. Self-management is a recommended first-line treatment, and mobile apps are a promising platform to support self-management of conditions like LBP. In the selfBACK project, we have developed a digital decision support system made available for the user via an app intended to support tailored self-management of nonspecific LBP.

Objective

The trial aims to evaluate the effectiveness of using the selfBACK app to support self-management in addition to usual care (intervention group) versus usual care only (control group) in people with nonspecific LBP.

Methods

This is a single-blinded, randomized controlled trial (RCT) with two parallel arms. The selfBACK app provides tailored self-management plans consisting of advice on physical activity, physical exercises, and educational content. Tailoring of plans is achieved by using case-based reasoning (CBR) methodology, which is a branch of artificial intelligence. The core of the CBR methodology is to use data about the current case (participant) along with knowledge about previous and similar cases to tailor the self-management plan to the current case. This enables a person-centered intervention based on what has and has not been successful in previous cases. Participants in the RCT are people with LBP who consulted a health care professional in primary care within the preceding 8 weeks. Participants are randomized to using the selfBACK app in addition to usual care versus usual care only. We aim to include a total of 350 participants (175 participants in each arm). Outcomes are collected at baseline, 6 weeks, and 3, 6, and 9 months. The primary end point is difference in pain-related disability between the intervention group and the control group assessed by the Roland-Morris Disability Questionnaire at 3 months.

Results

The trial opened for recruitment in February 2019. Data collection is expected to be complete by fall 2020, and the results for the primary outcome are expected to be published in fall 2020.

Conclusions

This RCT will provide insights regarding the benefits of supporting tailored self-management of LBP through an app available at times convenient for the user. If successful, the intervention has the potential to become a model for the provision of tailored self-management support to people with nonspecific LBP and inform future interventions for other painful musculoskeletal conditions.

Trial Registration

ClinicalTrial.gov NCT03798288; https://clinicaltrials.gov/ct2/show/NCT03798288

International Registered Report Identifier (IRRID)

DERR1-10.2196/14720

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.

What characterizes persons who do not report musculoskeletal pain? Results from a 4-year Population-based longitudinal study (the Epifund study)

OBJECTIVE

To identify and characterize persons in the population who do not report musculoskeletal pain.

METHODS

This was a population-based 4-year prospective longitudinal study by postal questionnaire. Population sample recruited from general practice registers in North-West England followed up at 15 months and 4 years.

RESULTS

Of respondents, 17.4% [95% confidence interval (CI) 16.1%-19.7%] reported no pain in the previous month at all 3 measurement intervals over 4 years. They were characterized by low levels of psychological distress [relative risk (RR) low vs high levels of psychological distress 2.3; 95% CI 1.7-2.9], low levels of depression (2.7; 95% CI 2.0-3.6), low levels of anxiety (2.1; 95% CI 1.6-2.7), low health anxiety (1.6; 95% CI 1.2-2.1), and low illness behavior scores (5.8; 95% CI 4.0-8.3), good quality sleep (3.4; 95% CI 2.6-4.4), no somatic symptoms (RR 0 vs 3 or more, 3.1; 95% CI 1.6-6.3) and no adverse life events in the 6 months prior to baseline data collection (RR 0 vs 3 or more, 3.2; 95% CI 1.6-6.2). On multivariable analysis, good quality sleep, low illness behavior, low psychological distress, and absence of recent adverse life events remained statistically independent predictors of musculoskeletal health. In total, 46% of persons who had all 4 of these characteristics consistently reported being free of pain, compared to only 5% of those who had none.

CONCLUSION

In a general population sample, over a period of 4 years, only around 1 in 6 persons do not report musculoskeletal pain. These persons report low levels of psychological distress and high quality sleep, both of which are potentially modifiable risk factors for the targeting of interventional or preventive strategies.

The role of psychosocial factors in predicting the onset of chronic widespread pain: results from a prospective population-based study

OBJECTIVE

Chronic widespread pain (CWP) is strongly associated with psychosocial distress both in a clinical setting and in the community. The aim of this study was to determine the contribution of measures of psychosocial distress, health-seeking behaviour, sleep problems and traumatic life events to the development of new cases of CWP in the community.

METHODS

In a population-based prospective study, 3171 adults aged 25-65 yrs free of CWP were followed-up 15 months later to identify those with new CWP. Baseline data were available on their scores from a number of psychological scales including Illness Attitude Scales (IAS), Somatic Symptom Checklist (SSC), Hospital Anxiety & Depression Scale, Sleep Problems Scale, and Life Events Inventory.

RESULTS

324 subjects [10%, 95% confidence interval (CI) 9.2, 11.3] developed new CWP at follow-up. After adjustment for age and sex, three factors independently predicted the development of CWP: scoring three or more on the SSC [odds ratio (OR) 1.8, 95% CI 1.1, 3.1], scoring eight or more on the Illness Behaviour subscale of the IAS (OR 3.3, 95% CI 2.3, 4.8), and nine or more on the Sleep Problem Scale (OR 2.7, 95% CI 1.6, 3.2). Subjects exposed to all three factors were at 12 times the odds of new CWP than those with low scores on all scales.

CONCLUSION

Subjects are at substantial increased odds of developing CWP if they display features of somatization, health-seeking behaviour and poor sleep. Psychosocial distress has a strong aetiological influence on CWP.

Cryptococcal meningitis associated with steroid therapy

Two patients on prolonged steroid therapy developed meningitis due to Cryptococcus neoformans. The first responded satisfactorily to treatment with amphotericin B, both initially and again following relapse. The second died shortly after treatment was begun. Pathogenicity studies suggest that the strain isolated from the fatal case was the more virulent. Cryptococcal meningitis probably occurs more often in Britain than is generally appreciated, and this possibility should be remembered when investigating patients with obscure forms of meningitis; if not, then the correct diagnosis may not be made. Attention is drawn to the increasing number of recently reported cases of this disease which have been associated with long-term steroid therapy.