Journey to multimorbidity: longitudinal analysis exploring cardiovascular risk factors and sociodemographic determinants in an urban setting

Abstract

ObjectiveTo study the social determinants and cardiovascular risk factors for multimorbidity and the acquisition sequence of multimorbidity.DesignLongitudinal study based on anonymised primary care data.SettingGeneral practices in an urban multiethnic borough in London, UK.Participants332 353 patients aged ≥18 years.Main outcome measuresClinical and sociodemographic characteristics of patients with multimorbidity, defined as ≥3 of 12 long-term conditions (LTCs) selected according to high predicted healthcare use. Multilevel logistic regression was used to model social determinants and cardiovascular risk factors. Alluvial plots were constructed to illustrate multimorbidity acquisition sequences according to age, ethnicity and social deprivation.Results5597 (1.7%) patients had ≥3 selected LTCs, the ‘multimorbidity cohort’. The the most common LTCs were diabetes (63.0%) and chronic pain (CP) (42.8%). Social deprivation and ethnicity were independent determinants of multimorbidity: most compared with the least deprived quintile (adjusted OR (AOR) 1.56 (95% CI 1.41 to 1.72)); South Asian compared with white ethnicity (AOR 1.44 (95% CI 1.29 to 1.61)); and black compared with white ethnicity (AOR 0.86 (95% CI 0.80 to 0.92)). The included cardiovascular risk factors were relatively strong determinants of multimorbidity: hypertension (AOR 5.05 (95% CI 4.69 to 5.44)), moderate obesity (AOR 3.41 (95% CI 3.21 to 3.63)) and smoking (AOR 2.30 (95% CI 2.16 to 2.45)). The most common initial onset conditions were diabetes and depression; diabetes particularly in older and black ethnic groups; and depression particularly in younger, more deprived and white ethnicity groups. CP was less common as an initial condition.ConclusionOur findings confirm the importance of age, social deprivation and ethnicity as determinants of multimorbidity. Smoking, obesity and hypertension as cardiovascular risk factors were stronger determinants of multimorbidity than deprivation or ethnicity. The acquisition sequence of multimorbidity is patterned by sociodemographic determinants. Understanding onset conditions of multimorbidity and cardiovascular cardiovascular risk factors may lead to the development of interventions to slow the progression of multimorbidity.

Multimorbidity in a cohort of middle-aged women: Risk factors and disease clustering

“…This would be the case of hypertension, which was strongly associated with multimorbidity upon follow-up in our sample. A study addressing 332 thousand subjects in England also reported hypertension as a very strong predictor for multimorbidity [15]. Hypertension prevention, along with securing effective treatment for these patients, would be needed to improve the overall health of the population, and reduce multimorbidity burden.…”

“…This preliminary finding may suggest that not all diabetic patients are at higher risk of multimorbidity, indicating that there may be some diabetes clusters with higher/lower risk. Likewise, another cohort study signaled hypertension, obesity and smoking as multimorbidity risk factors; nonetheless, diabetes was not identified as a risk factor [15].…”

Placing poverty-inequality at the centre of psychiatry

“…The scientific literature has reached a consensus on the health harms of poverty-inequality. In their study of multimorbidity in the ethnically diverse London borough of Lambeth (where a third of a million are registered with a general practitioner (GP)), Ashworth et al 11 concluded that: 'acquisition of multimorbidity is patterned by socioeconomic determinants', with depression and asthma as early drivers of poor physical health. The US and the UK have similar high levels of inequality, and their inhabitants can expect to lose 7-9 healthy years (free from physical disability) by the age of 50 if they are poor, compared with their fellow citizens at the least deprived end of the gradient.…”

Studying trajectories of multimorbidity: a systematic scoping review of longitudinal approaches and evidence

“…In the US, white individuals were more likely to transition from ischaemic heart disease to death, while Asian and Native Hawaiian and Pacific Islander individuals were more likely to transition from diabetes to diabetes plus chronic kidney disease (Siriwardhana et al, 2018). In the UK, disease specific sequences /pathways also differed by ethnicity (Ashworth et al, 2019). For example, the white ethnic group was dominated by depression as a starting point, while diabetes was the most common starting point in the black ethnic group along with depression and serious mental illness.…”

“…Study, year Risk factors considered Findings of association analysis Ashworth et al (2019) Age, ethnicity, deprivation -Trajectories varied by age, ethnicity, and deprivation. For example, those in the least deprived quintile were more likely to start with DM and CHD.…”