Ethnic inequalities in the impact of COVID-19 on primary care consultations: a time series analysis of 460,084 individuals with multimorbidity in South London.

BACKGROUND: The COVID-19 pandemic caused rapid changes in primary care delivery in the UK, with concerns that certain groups of the population may have faced increased barriers to access. This study assesses the impact of the response to the COVID-19 pandemic on primary care consultations for individuals with multimorbidity and identifies ethnic inequalities. METHODS: A longitudinal study based on monthly data from primary care health records of 460,084 patients aged ≥18 years from 41 GP practices in South London, from February 2018 to March 2021. Descriptive analysis and interrupted time series (ITS) models were used to analyse the effect of the pandemic on primary care consultations for people with multimorbidity and to identify if the effect varied by ethnic groups and consultation type. RESULTS: Individuals with multimorbidity experienced a smaller initial fall in trend at the start of the pandemic. Their primary care consultation rates remained stable (879 (95% CI 869-890) per 1000 patients in February to 882 (870-894) March 2020), compared with a 7% decline among people without multimorbidity (223 consultations (95% CI 221-226) to 208 (205-210)). The gap in consultations between the two groups reduced after July 2020. The effect among individuals with multimorbidity varied by ethnic group. Ethnic minority groups experienced a slightly larger fall at the start of the pandemic. Individuals of Black, Asian, and Other ethnic backgrounds also switched from face-to-face to telephone at a higher rate than other ethnic groups. The largest fall in face-to-face consultations was observed among people from Asian backgrounds (their consultation rates declined from 676 (659-693) in February to 348 (338-359) in April 2020), which may have disproportionately affected their quality of care. CONCLUSIONS: The COVID-19 pandemic significantly affected primary care utilisation in patients with multimorbidity. While there is evidence of a successful needs-based prioritisation of multimorbidity patients within primary care at the start of the pandemic, inequalities among ethnic minority groups were found. Strengthening disease management for these groups may be necessary to control widening inequalities in future health outcomes.

Managing stroke risk in patients with atrial fibrillation: a cross-sectional analysis of socio-demographic inequalities in a London borough.

BACKGROUND: Stroke prevention is essential for patients with atrial fibrillation (AF), but some receive sub-optimal management. We reviewed those with a recorded AF diagnosis assessed with CHA2DS2-VASc stroke risk score (SRS) and socio-demographic determinants of anticoagulation prescribing. The objective was to compare with national guidance recommendations, which recommend anticoagulant therapy for SRS ≥ 2, to determine if there were inequalities in management. METHODS: A cross-sectional design was used to analyze records from all (n = 41) general practices in one London borough. Patients were excluded if they were <18 years, had AF resolved or diagnosed < 3 months. Logistic regression identified socio-demographic factors associated with high SRS and anticoagulant prescribing. RESULTS: Of 2913 patients, 2885 (99.0%) had an SRS, and 2411 (83.6%) a score ≥ 2 and 82.9% (1999 of 2411) were prescribed anticoagulation. Women (compared with men), Black and Mixed/Multiple ethnic groups (compared with White), and those living in most deprived areas (compared with least) were more likely to have a score ≥ 2. Patients with a high SRS from Black and Mixed/Multiple ethnic groups and aged 18-74 years were less likely to be prescribed anticoagulation. CONCLUSION: We found evidence of age and ethnic inequity in anticoagulation prescribing for stroke prevention in patients with AF.

The use of future scenario thinking for child public health in a local authority.

BACKGROUND: Socioeconomic, cultural, technological, environment and ecological changes are rapidly transforming how children and young people (CYP) grow up, yet their impacts on CYP are difficult to predict. The traditional ways that Public Health practitioners work may not capture such complex and dynamic change. To address this, Lambeth Council used future scenario thinking. METHODS: A literature review looked at political, socioeconomic and other 'transitions' in the borough. Interviews, focus groups and workshops were held with CYP, parents, carers, local statutory and non-statutory stakeholders about the future for Lambeth CYP in the decade ahead. Themes were analysed to identify which had the potential for the biggest impact or the most uncertainty. RESULTS: The main transitions were described, 100 stakeholders interviewed, and five 'drivers' of the future were identified: protracted austerity, technological explosion, demographic shift, 'democratic shake-up' and planetary health. From all these data, four future scenarios were developed: 'communities care for themselves', 'collaborating to care for all', 'nobody cares' and 'who cares?' CONCLUSIONS: New insights were gained about promoting more responsibility for, and active participation of CYP. This led to Lambeth's CYP Plan and the 'Made in Lambeth' campaign aiming to enlist the community and business in creating a child-friendly borough.

Adapting the definition of multimorbidity - development of a locality-based consensus for selecting included Long Term Conditions.

BACKGROUND: Defining multimorbidity has proved elusive in spite of attempts to standardise definitions. For national studies, a broad definition is required to capture national diversity. For locally based studies, the definition may need to reflect demographic and morbidity patterns. We aimed to define multimorbidity for an inner city, multi-ethnic, deprived, young age community typical of many large cities. METHODS: We used a scoping literature review to identify the international literature, standards and guidelines on Long Term Condition (LTC) definitions for inclusion in our multimorbidity definition. Consensus was categorised into high, medium or low consensus, depending on the number of literature sources citing each LTC. Findings were presented to a workshop consisting of local health service stakeholders who were asked to select LTCs for inclusion in a second stage review. In the second stage, each LTC was tested against seven evaluation domains: prevalence, impact, preventability, treatment burden, progression to multiple LTCs, impact on younger people, data quality. These domains were used to create 12 target criteria. LTC rankings according to consensus group and target criteria scores were presented to a second workshop for a final decision about LTC inclusion. RESULTS: The literature review identified 18 literature sources citing 86 LTCs: 11 were excluded because they were LTC clusters. The remainder were allocated into consensus groupings: 13 LTCs were 'high consensus' (cited by ≥ 11 sources); 15 were 'medium consensus' (cited by 5-10 sources); 47 were 'low consensus' (cited by < 5 sources). The first workshop excluded 31 LTCs. The remaining 44 LTCs consisted of: 13 high consensus LTCs, all with high target score (score 6-12); 15 medium consensus LTCs, 11 with high target scores; 16 low consensus LTCs, 6 with high target scores. The final workshop selected the 12 high consensus conditions, 12 medium consensus LTCs (10 with high target scores) and 8 low consensus LTCs (3 with high target scores), producing a final selection of 32 LTCs. CONCLUSIONS: Redefining multimorbidity for an urban context ensures local relevance but may diminish national generalisability. We describe a detailed LTC selection process which should be generalisable to other contexts, both local and national.

Enhanced Invitations Using the Question-Behavior Effect and Financial Incentives to Promote Health Check Uptake in Primary Care.

Background: Uptake of health checks for cardiovascular risk assessment in primary care in England is lower than anticipated. The question-behavior effect (QBE) may offer a simple, scalable intervention to increase health check uptake. Purpose: The present study aimed to evaluate the effectiveness of enhanced invitation methods employing the QBE, with or without a financial incentive to return the questionnaire, at increasing uptake of health checks. Methods: We conducted a three-arm randomized trial including all patients at 18 general practices in two London boroughs, who were invited for health checks from July 2013 to December 2014. Participants were randomized to three trial arms: (i) Standard health check invitation letter only; (ii) QBE questionnaire followed by standard invitation letter; or (iii) QBE questionnaire with offer of a financial incentive to return the questionnaire, followed by standard invitation letter. In intention to treat analysis, the primary outcome of completion of health check within 6 months of invitation, was evaluated using a p value of .0167 for significance. Results: 12,459 participants were randomized. Health check uptake was evaluated for 12,052 (97%) with outcome data collected. Health check uptake within 6 months of invitation was: standard invitation, 590 / 4,095 (14.41%); QBE questionnaire, 630 / 3,988 (15.80%); QBE questionnaire and financial incentive, 629 / 3,969 (15.85%). Difference following QBE questionnaire, 1.43% (95% confidence interval -0.12 to 2.97%, p = .070); following QBE questionnaire and financial incentive, 1.52% (-0.03 to 3.07%, p = .054). Conclusions: Uptake of health checks following a standard invitation was low and not significantly increased through enhanced invitation methods using the QBE.

Cardiovascular risk at health checks performed opportunistically or following an invitation letter. Cohort study.

Background: A population-based programme of health checks has been established in England. Participants receive postal invitations through a population-based call-recall system but health check providers may also offer health checks opportunistically. We compared cardiovascular risk scores for 'invited' and 'opportunistic' health checks. Methods: Cohort study of all health checks completed at 18 general practices from July 2013 to June 2015. For each general practice, cardiovascular (CVD) risk scores were compared by source of check and pooled using meta-analysis. Effect estimates were compared by gender, age-group, ethnicity and fifths of deprivation. Results: There were 6184 health checks recorded (2280 invited and 3904 opportunistic) with CVD risk scores recorded for 5359 (87%) participants. There were 17.0% of invited checks and 22.2% of opportunistic health checks with CVD risk score ≥10%; a relative increment of 28% (95% confidence interval: 14-44%, P < 0.001). In the most deprived quintile, 15.3% of invited checks and 22.4% of opportunistic checks were associated with elevated CVD risk (adjusted odds ratio: 1.94, 1.37-2.74, P  < 0.001). Conclusions: Respondents at health checks performed opportunistically are at higher risk of cardiovascular disease than those participating in response to a standard invitation letter, potentially reducing the effect of uptake inequalities.

Do health checks improve risk factor detection in primary care? Matched cohort study using electronic health records.

BACKGROUND: To evaluate the effect of NHS Health Checks on cardiovascular risk factor detection and inequalities. METHODS: Matched cohort study in the Clinical Practice Research Datalink, including participants who received a health check in England between 1 April 2010 and 31 March 2013, together with matched control participants, with linked deprivation scores. RESULTS: There were 91 618 eligible participants who received a health check, of whom 75 123 (82%) were matched with 182 245 controls. After the health check, 90% of men and 92% of women had complete data for blood pressure, total cholesterol, smoking and body mass index; a net 51% increase (P < 0.001) over controls. After the check, gender and deprivation inequalities in recording of all risk factors were lower than for controls. Net increase in risk factor detection was greater for hypercholesterolaemia (men +33%; women +32%) than for obesity (men +8%; women +4%) and hypertension in men only (+5%) (all P < 0.001). Detection of smoking was 5% lower in health check participants than controls (P < 0.001). Over 4 years, statins were prescribed to 11% of health -check participants and 7.6% controls (hazard ratio 1.58, 95% confidence interval 1.53-1.63, P < 0.001). CONCLUSION: NHS Health Checks are associated with increased detection of hypercholesterolaemia, and to a lesser extent obesity and hypertension, but smokers may be under-represented.

Estimating the yield of NHS Health Checks in England: a population-based cohort study.

BACKGROUND: This study aimed to evaluate the yield of the NHS Health Checks programme. METHODS: A cohort study, conducted in the Clinical Practice Research Datalink in England. Electronic health records were analysed for patients aged 40-74 receiving an NHS Health Check between 2010 and 2013. RESULTS: There were 65 324 men and 75 032 women receiving a health check. For every 1000 men assessed, there were 205 smokers (95% confidence interval 195-215), 355 (340-369) with hypertension (≥140/90 mmHg) and 633 (607-658) with elevated cholesterol (≥5 mmol/l). Among 1000 women, there were 161 (151-171) smokers, 247 (238-257) with hypertension and 668 (646-689) with elevated cholesterol. In the 12 months following the check, statins were prescribed to 18% of men and 21% of women with ≥20% cardiovascular risk and antihypertensive drugs to 11% of men and 16% of women with ≥20% cardiovascular risk. Slight reductions in risk factor values were observed in the minority of participants with follow-up values recorded in the 15 months following the check. CONCLUSIONS: A universal primary prevention programme identifies substantial risk factor burden in a population without known cardiovascular disease. Research is needed to monitor interventions, and intermediate- and long-term outcomes, in those identified at high risk.

Influences on individuals' decisions to take up the offer of a health check: a qualitative study.

BACKGROUND: Health checks are promoted to evaluate individuals' risk of developing disease and to initiate health promotion and disease prevention interventions. The NHS Health Check is a cardiovascular risk assessment programme introduced in the UK aimed at preventing cardiovascular disease (CVD). Uptake of health checks is lower than anticipated. This study aimed to explore influences on people's decisions to take up the offer of a health check. METHODS: Semi-structured interviews were conducted with people registered at four general practices in South London. The interview schedule was informed by the Theoretical Domains Framework. Data were analysed qualitatively using the Framework method using NVivo for data management. RESULTS: Twenty-seven participants invited for a health check were included in the study. Seventeen received the health check while 10 either did not attend or failed to complete the check. Five themes emerging from the data included a lack of awareness of the health check programme, beliefs about susceptibility to CVD, beliefs about civic responsibility, issues concerning access to appointments, and beliefs about the consequences of having a check. CONCLUSIONS: Health check programmes need to raise public awareness to ensure that people are informed about the objectives and nature of the programme in order to reach an informed decision about taking up the invitation. Emphasizing the benefits of prevention and early detection might encourage attendance in those who are reluctant to burden the public health-care systems. Extending outreach initiatives and increasing 'out of hours' provision at local community sites could facilitate access.

Hypertension: a cross-sectional study of the role of multimorbidity in blood pressure control.

BACKGROUND: Hypertension is the most prevalent cardiovascular long-term condition in the UK and is associated with a high rate of multimorbidity (MM). Multimorbidity increases with age, ethnicity and social deprivation. Previous studies have yielded conflicting findings about the relationship between MM and blood pressure (BP) control. Our aim was to investigate the relationship between multimorbidity and systolic blood pressure (SBP) in patients with hypertension. METHODS: A cross-sectional analysis of anonymised primary care data was performed for a total of 299,180 adult patients of whom 31,676 (10.6 %) had a diagnosis of hypertension. We compared mean SBP in patients with hypertension alone and those with one or more co-morbidities and analysed the effect of type of comorbidity on SBP. We constructed a regression model to identify the determinants of SBP control. RESULTS: The strongest predictor of mean SBP was the number of comorbidities, ß -0.13 (p < 0.05). Other predictors included Afro-Caribbean ethnicity, ß 0.05 (p < 0.05), South Asian ethnicity, ß -0.03 (p < 0.05), age, ß 0.05 (p < 0.05), male gender, ß 0.05 (p < 0.05) and number of hypotensive drugs ß 0.06 (p < 0.05). SBP was lower by a mean of 2.03 mmHg (-2.22, -1.85) for each additional comorbidity and was lower in MM regardless of the type of morbidity. CONCLUSION: Hypertensive patients with MM had lower SBP than those with hypertension alone; the greater the number of MM, the lower the SBP. We found no evidence that BP control was related to BP targets, medication category or specific co-morbidity. Further research is needed to determine whether consultation rate, "white-coat hypertension" or medication adherence influence BP control in MM.

Hypertension prevalence, coding and control in an urban primary care setting in the UK between 2014 and 2021.

OBJECTIVE: Hypertension is a leading preventable cause of mortality, yet high rates of undiagnosed and uncontrolled hypertension continue. The burden falls most heavily on some ethnic minorities and the socially deprived, with the COVID-19 pandemic having further widened inequalities. We sought to determine the prevalence and predictors of unmeasured blood pressure (BP), uncoded elevated BP and uncontrolled hypertension in primary care across 2014-2021. METHODS: A population-based cohort study using data from all 41 general practices in a socioeconomically diverse inner-city borough. BP measurements, sociodemographic, lifestyle and clinical factors were extracted from anonymized primary care data. Hypertension and BP control were defined using NICE guidelines. Associations between patient characteristics and hypertension outcomes were identified using logistical regression modelling. RESULTS: Of 549 082 patients, 39.5% had unmeasured BP; predictors included male sex [AOR 2.40, 95% confidence interval (95% CI) 2.26-2.43] and registration in the pandemic years. Of 71 970 adults with elevated BP, 36.0% were uncoded; predictors included obesity (AOR 2.51, 95% CI 2.42-2.60) and increasing age. Of 44 648 adults on the hypertension register, 46.8% had uncontrolled hypertension; predictors included black ethnicity compared to white (AOR 1.54, 95% CI 1.41-1.68) and cardiovascular co-morbidities (AOR 1.23, 95% CI 1.21-1.25). Social deprivation was only weakly or not significantly associated with hypertension outcomes. CONCLUSION: The burden of uncoded elevated BP and uncontrolled hypertension is high. Obesity and male sex were associated with uncoded elevated BP and uncontrolled hypertension. Black ethnicity was associated with uncontrolled hypertension. Initiatives are needed to optimize hypertension coding and control, with an emphasis on specific population subgroups.

Disease patterns in high-cost individuals with multimorbidity: a retrospective cross-sectional study in primary care.

BACKGROUND: 'High-cost' individuals with multimorbidity account for a disproportionately large share of healthcare costs and are at most risk of poor quality of care and health outcomes. AIM: To compare high-cost with lower-cost individuals with multimorbidity and assess whether these populations can be clustered based on similar disease patterns. DESIGN AND SETTING: A cross-sectional study based on 2019/2020 electronic medical records from adults registered to primary care practices (n = 41) in a London borough. METHOD: Multimorbidity is defined as having ≥2 long-term conditions (LTCs). Primary care costs reflected consultations, which were costed based on provider and consultation types. High cost was defined as the top 20% of individuals in the cost distribution. Descriptive analyses identified combinations of 32 LTCs and their contribution to costs. Latent class analysis explored clustering patterns. RESULTS: Of 386 238 individuals, 101 498 (26%) had multimorbidity. The high-cost group (n = 20 304) incurred 53% of total costs and had 6833 unique disease combinations, about three times the diversity of the lower-cost group (n = 81 194). The trio of anxiety, chronic pain, and depression represented the highest share of costs (5%). High-cost individuals were best grouped into five clusters, but no cluster was dominated by a single LTC combination. In three of five clusters, mental health conditions were the most prevalent. CONCLUSION: High-cost individuals with multimorbidity have extensive heterogeneity in LTCs, with no single LTC combination dominating their primary care costs. The frequent presence of mental health conditions in this population supports the need to enhance coordination of mental and physical health care to improve outcomes and reduce costs.

Why do children under 5 years go to the GP in Lambeth: a cross-sectional study.

OBJECTIVES: This study identifies the most common recorded reason for attendance to primary care for children under 5 years old, including a breakdown via age, ethnicity, deprivation quintile and sex. DESIGN: Cross-sectional. SETTING: 39 of 40 general practices in Lambeth, London, UK. PARTICIPANTS: 22 189 children under 5 years who had attended primary care between the 1 April 2017 and 31 March 2020 and had not opted out of anonymous data sharing within Lambeth DataNet. OUTCOME MEASURE: The primary objective was to identify the most frequently recorded complaint in general practice for children under 5 years old. The secondary objective was to understand how presenting complaint differs by age, ethnicity, sex and deprivation level. The third objective was to create a multivariate logistic regression with frequent attendance as the outcome variable. RESULTS: Nine conditions formed over 50% of all patient interactions: the most common reason was upper respiratory tract infections (14%), followed by eczema (8%) and cough (7%). While there was some variation by ethnicity and age, these nine conditions remained dominant. Children living in the most deprived area are more likely to be frequent attenders than children living in the least deprived area (adjusted OR (AOR) 1.27 (95% CI 1.14 to 1.41)). Children of Indian (AOR 1.47 (1.04 to 2.08)), Bangladeshi (AOR 2.70 (1.95 to 3.74)) and other white (AOR 1.18 (1.04 to 1.34)) ethnicities were more likely to be frequent attenders, compared with those of white British ethnicity. CONCLUSIONS: Most reasons for attendance for children under 5 years to primary care are for acute, self-limiting conditions. Some of these could potentially be managed by increasing access to community care services, such as pharmacies. By focusing on the influence of the broader determinants of health as to why particular groups are more likely to attend, health promotion efforts have the opportunity to reduce barriers to healthcare and improve outcomes.

Non-attendance at diabetic eye screening and risk of sight-threatening diabetic retinopathy: a population-based cohort study.

AIMS/HYPOTHESIS: This study evaluated whether repeated non-attendance for diabetic eye screening is associated with the risk of sight-threatening diabetic retinopathy (STDR). METHODS: This was a cohort study of 6,556 residents with diabetes who were invited for screening between 2008 and 2011 in a population-based eye screening programme in inner London and who attended for their first-ever screen in 2008. The proportion of participants with STDR was evaluated in relation to the number of years in which screening was missed. RESULTS: The proportion of participants who did not attend screening decreased between 2009 and 2011 (annual reduction 1.6% [95% CI 0.9%, 2.3%]). The adjusted relative odds of STDR for 210 participants who did not attend two consecutive years of screening were 3.76 (95% CI 2.14, 6.61; p < 0.001), compared with participants who were screened annually. In 605 participants with mild non-proliferative retinopathy at the first screen, the adjusted relative odds of developing proliferative or moderate to severe non-proliferative retinopathy were 5.72 (95% CI 7.43, 22.83; p = 0.013) for 53 participants who missed two screens. CONCLUSIONS/INTERPRETATION: Patients who do not attend diabetic eye screening are at increased risk of developing STDR. Tracing of non-attenders with evidence of established retinopathy should be an important fail-safe procedure.

Variations in the organization and delivery of the 'NHS health check' in primary care.

BACKGROUND: To evaluate the organization of the new cardiovascular risk assessment programme, NHS Health Checks, in general practices. METHODS: All 99 general practices in two inner London boroughs were invited to participate in a cross-sectional survey by completing an online questionnaire. RESULTS: Data were analysed for 66/99 (67%) eligible practices. Training attended for delivering the Health Check included measurement methods (43%), delivering risk information (65%) and advising on lifestyle change (62%). The Framingham risk score was used by 66% of practices, the QRisk score by 12% and both by 8%. Advice given to patients identified as high risk was 'usually' brief at 26% of practices, advice was given verbally at 92% of practices, in written form at 74% and through interactive visual materials at 29%. Statins were 'usually' prescribed to high-risk patients by 34% of practices and antihypertensive drugs by 22%. The follow-up of high-risk patients was by means of a register with regular recall at 51% of general practices. CONCLUSIONS: There is considerable diversity in general practices' implementation of the NHS Health Check. A formal quality assurance process may be required in order to optimize the implementation of the NHS cardiovascular risk assessment programme.

Identifying populations with chronic pain in primary care: developing an algorithm and logic rules applied to coded primary care diagnostic and medication data.

BACKGROUND: Estimates of chronic pain prevalence using coded primary care data are likely to be substantially lower than estimates derived from community surveys. Most primary care studies have estimated chronic pain prevalence using data searches confined to analgesic medication prescriptions. Increasingly, following recent NICE guideline recommendations, patients and doctors opt for non-drug treatment of chronic pain thus excluding these patients from prevalence estimates based on medication codes. We aimed to develop and test an algorithm combining medication codes with selected diagnostic codes to estimate chronic pain prevalence using coded primary care data. METHODS: Following a scoping review 4 criteria were developed to identify cohorts of people with chronic pain. These were (1) people with one of 12 ('tier 1') conditions that almost always results in the individual having chronic pain (2) people with one of 20 ('tier 2') conditions included when there are also 3 or more prescription-only analgesics issued in the last 12 months (3) chronic neuropathic pain, or (4) 4 or more prescription-only analgesics issued in the last 12 months. These were translated into 8 logic rules which included 1,932 SNOMED CT codes. RESULTS: The algorithm was run on primary care data from 41 GP Practices in Lambeth. The total population consisted of 386,238 GP registered adults ≥ 18 years as of the 31st March 2021. 64,135 (16.6%) were identified as people with chronic pain. This definition demonstrated notably high rates in Black ethnicity females, and higher rates in the most deprived, and older population. CONCLUSIONS: Estimates of chronic pain prevalence using structured healthcare data have previously shown lower prevalence estimates for chronic pain than reported in community surveys. This has limited the ability of researchers and clinicians to fully understand and address the complex multifactorial nature of chronic pain. Our study demonstrates that it may be possible to establish more representative prevalence estimates using structured data than previously possible. Use of logic rules offers the potential to move systematic identification and population-based management of chronic pain into mainstream clinical practice at scale and support improved management of symptom burden for people experiencing chronic pain.

Identifying multimorbidity clusters with the highest primary care use: 15 years of evidence from a multi-ethnic metropolitan population.

BACKGROUND: People with multimorbidity have complex healthcare needs. Some co-occurring diseases interact with each other to a larger extent than others and may have a different impact on primary care use. AIM: To assess the association between multimorbidity clusters and primary care consultations over time. DESIGN AND SETTING: A retrospective longitudinal (panel) study design was used. Data comprised electronic primary care health records of 826 166 patients registered at GP practices in an ethnically diverse, urban setting in London between 2005 and 2020. METHOD: Primary care consultation rates were modelled using generalised estimating equations. Key controls included the total number of long-term conditions, five multimorbidity clusters, and their interaction effects, ethnic group, and polypharmacy (proxy for disease severity). Models were also calibrated by consultation type and ethnic group. RESULTS: Individuals with multimorbidity used two to three times more primary care services than those without multimorbidity (incidence rate ratio 2.30, 95% confidence interval = 2.29 to 2.32). Patients in the alcohol dependence, substance dependence, and HIV cluster (Dependence+) had the highest rate of increase in primary care consultations as additional long-term conditions accumulated, followed by the mental health cluster (anxiety and depression). Differences by ethnic group were observed, with the largest impact in the chronic liver disease and viral hepatitis cluster for individuals of Black or Asian ethnicity. CONCLUSION: This study identified multimorbidity clusters with the highest primary care demand over time as additional long-term conditions developed, differentiating by consultation type and ethnicity. Targeting clinical practice to prevent multimorbidity progression for these groups may lessen future pressures on primary care demand by improving health outcomes.

Inequalities in developing multimorbidity over time: A population-based cohort study from an urban, multi-ethnic borough in the United Kingdom.

BACKGROUND: Social and material deprivation accelerate the development of multimorbidity, yet the mechanisms which drive multimorbidity pathways and trajectories remain unclear. We aimed to examine the association between health inequality, risk factors and accumulation or resolution of LTCs, taking disease sequences into consideration. METHODS: We conducted a retrospective cohort of adults aged 18 years and over, registered between April 2005 and May 2020 in general practices in one inner London borough (n = 826,936). Thirty-two long term conditions (LTCs) were selected using a consensus process, based on a definition adapted to the demographic characteristics of the local population. sThe development and resolution of these LTCs were examined according to sociodemographic and clinical risk factors (hypertension; moderate obesity (BMI 30·0-39·9 kg/m2), high cholesterol (total cholesterol > 5 mmol/L), smoking, high alcohol consumption (>14 units per week), and psychoactive substance use), through the application of multistate Markov chain models. FINDINGS: Participants were followed up for a median of 4.2 years (IQR = 1·8 - 8·4); 631,760 (76%) entered the study with no LTCs, 121,424 (15%) with 1 LTC, 41,720 (5%) with 2 LTCs, and 31,966 (4%) with three or more LTCs. At the end of follow-up, 194,777 (24%) gained one or more LTCs, while 45,017 (5%) had resolved LTCs and 27,021 (3%) died. In multistate models, deprivation (hazard ratio [HR] between 1·30 to 1·64), female sex (HR 1·13 to 1·20), and Black ethnicity (HR 1·20 to 1·30; vs White) were independently associated with increased risk of transition from one to two LTCs, and shorter time spent in a healthy state. Substance use was the strongest risk factor for multimorbidity with an 85% probability of gaining LTCs over the next year. First order Markov chains identified consistent disease sequences including: chronic pain or osteoarthritis followed by anxiety and depression; alcohol and substance dependency followed by HIV, viral hepatitis, and liver disease; and morbid obesity followed by diabetes, hypertension, and chronic pain. INTERPRETATION: We examined the relations among 32 LTCs, taking the order of disease occurrence into consideration. Distinctive patterns for the development and accumulation of multimorbidity have emerged, with increased risk of transitioning from no conditions to multimorbidity and mortality related to ethnicity, deprivation and gender. Musculoskeletal disorders, morbid obesity and substance abuse represent common entry points to multimorbidity trajectories.

Applying resolved and remission codes reduced prevalence of multimorbidity in an urban multi-ethnic population.

OBJECTIVE: To estimate the prevalence and determinants of multimorbidity in an urban, multi-ethnic area over 15-years and investigate the effect of applying resolved/remission codes on prevalence estimates. STUDY DESIGN AND SETTING: This is a population-based retrospective cross-sectional study using electronic health records of adults registered between 2005 -2020 in general practices in one inner London borough (n = 826,936). Classification of resolved/remission was based on clinical coding defined by the patient's general practitioner. RESULTS: The crude and age-adjusted prevalence of multimorbidity over the study period were 21.2% (95% CI: 21.1 -21.3) and 30.8% (30.6 -31.0), respectively. Applying resolved/remission codes decreased the crude and age-adjusted prevalence estimates to 18.0% (95% CI: 17.9 -18.1) and 27.5% (27.4 -27.7). Asthma (53.2%) and depression (20.2%) were responsible for most resolved and remission codes. Substance use (Adjusted Odds Ratio 10.62 [95% CI: 10.30 -10.95]), high cholesterol (2.48 [2.44 -2.53]), and moderate obesity (2.19 [2.15 -2.23]) were the strongest risk factor determinants of multimorbidity outside of advanced age. CONCLUSION: Our study highlights the importance of applying resolved/remission codes to obtain an accurate prevalence and the increased burden of multimorbidity in a young, urban, and multi-ethnic population. Understanding modifiable risk factors for multimorbidity can assist policymakers in designing effective interventions to reduce progression to multimorbidity.

Identifying longitudinal clusters of multimorbidity in an urban setting: A population-based cross-sectional study.

BACKGROUND: Globally, there is increasing research on clusters of multimorbidity, but few studies have investigated multimorbidity in urban contexts characterised by a young, multi-ethnic, deprived populations. This study identified clusters of associative multimorbidity in an urban setting. METHODS: This is a population-based retrospective cross-sectional study using electronic health records of all adults aged 18 years and over, registered between April 2005 to May 2020 in general practices in one inner London borough. Multiple correspondence analysis and cluster analysis was used to identify groups of multimorbidity from 32 long-term conditions (LTCs). RESULTS: The population included 41 general practices with 826,936 patients registered between 2005 and 2020, with mean age 40 (SD15·6) years. The prevalence of multimorbidity was 21% (n = 174,881), with the median number of conditions being three and increasing with age. Analysis identified five consistent LTC clusters: 1) anxiety and depression (Ratio of within- to between- sum of squares (WSS/BSS <0·01 to <0·01); 2) heart failure, atrial fibrillation, chronic kidney disease (CKD), chronic heart disease (CHD), stroke/transient ischaemic attack (TIA), peripheral arterial disease (PAD), dementia and osteoporosis (WSS/BSS 0·09 to 0·12); 3) osteoarthritis, cancer, chronic pain, hypertension and diabetes (0·05 to 0·06); 4) chronic liver disease and viral hepatitis (WSS/BSS 0·02 to 0·03); 5) substance dependency, alcohol dependency and HIV (WSS/BSS 0·37 to 0·55). INTERPRETATION: Mental health problems, pain, and at-risk behaviours leading to cardiovascular diseases are the important clusters identified in this young, urban population. FUNDING: Impact on Urban Health, United Kingdom.