Symptom burden in people with a single morbidity and multimorbidity was explored using multivariate analyses adjusted for age, sex, socioeconomic status (highest completed education, income, assets and work status), degree of urbanisation, cohabitation status, smoking and alcohol consumption. Excess symptom burden for people with multimorbidity (combinations of two diagnosis domains) was assessed in multivariable linear regression models. For each of the three measures of symptom burden (number of symptoms, impairment score and worry score), the (10×9)/2=45 regression coefficients pertaining to the two-way interactions between diagnosis domains were retained from a multivariable linear regression on all combinations of diagnosis domains, adjusted for the same covariates as mentioned above. These coefficients were directly interpreted as the synergy effect, that is, excess symptom burden associated with having diagnoses from two diagnosis domains relative to the sum of the symptom burden associated with having a diagnosis from the diagnosis domains individually. Analyses were performed using SAS V.9.4.