Table 2

Adjusted (left) Cox model-estimated and (right) marginal structural model-estimated HRs (95% CI) for the association between falls and fractures and anticholinergic burden in the OAB cohort (n=154 432), including the subgroup aged >65 years (middle); Truven MarketScan databases 2007–2015

Cox model*Marginal structural model*
Overall populationSubgroup aged >65 yearsOverall population
HR (95% CI)P valueHR (95% CI)P valueHR (95% CI)P value
By anticholinergic burden level versus no burden†
 Low (1–89)1.2 (1.2 to 1.3)<0.0011.1 (1.0 to 1.2)0.0061.2 (1.1 to 1.2)<0.001
 Medium (90–499)1.3 (1.2 to 1.4)<0.0011.2 (1.1 to 1.3)<0.0011.2 (1.1 to 1.3)<0.001
 High (500+)1.4 (1.3 to 1.4)<0.0011.2 (1.1 to 1.3)<0.0011.3 (1.3 to 1.4)<0.001
By age category versus ≤45
 46–551.3 (1.2 to 1.3)<0.0011.7 (1.6 to 1.7)‡<0.0011.2 (1.2 to 1.3)<0.001
 56–651.5 (1.4 to 1.6)<0.0011.5 (1.4 to 1.6)<0.001
 66–752.3 (2.2 to 2.4)<0.0012.3 (2.1 to 2.5)<0.001
 76–853.4 (3.2 to 3.6)<0.0013.5 (3.3 to 3.9)<0.001
 86+5.0 (4.6 to 5.4)<0.0015.6 (5.0 to 6.3)<0.001
Sex
 Women versus men1.5 (1.5 to 1.6)<0.0011.6 (1.5 to 1.7)<0.0011.5 (1.5 to 1.6)<0.001
Comorbidity categories at baseline
 Cardiovascular diseases§1.1 (1.1 to 1.1)0.0181.2 (1.1 to 1.2)<0.0011.1 (1.0 to 1.1)0.043
 Neurological impairments1.5 (1.4 to 1.6)<0.0011.7 (1.5 to 1.8)<0.0011.5 (1.4 to 1.6)<0.001
 Endocrine, nutritional and metabolic diseases1.1 (1.1 to 1.2)<0.0011.2 (1.1 to 1.4)<0.0011.2 (1.1 to 1.3)<0.001
 Cardiovascular disease×neurological impairments1.1 (1.0 to 1.2)0.0421.0 (0.9 to 1.1)0.9451.1 (1.0 to 1.2)0.048
 Cardiovascular disease×endocrine, nutritional and metabolic diseases1.0 (1.0 to 1.1)0.7500.9 (0.8 to 1.0)0.1180.9 (0.8 to 1.0)0.219
 Neurological impairments×endocrine, nutritional and metabolic diseases1.1 (1.0 to 1.2)0.0921.0 (0.9 to 1.1)0.7861.0 (0.9 to 1.2)0.558
  • *The Cox models were implemented using function coxph from the R package survival V.2.41–3. The marginal structural model was implemented using function coxph from R package survival V.2.41–3, using the weight argument to apply time-varying weights and setting a cluster term for enrolment ID for robust variance estimation. Time-varying weights were calculated using function ipwtm from R package ipw V.1.0–11 and based on a multinomial logistic regression model (using a generalised logit link) with categorical time-varying anticholinergic burden as the outcome, where age, sex and time-varying comorbidity categories, as well as all two-way interactions between them, were included as predictor variables.

  • †Level of anticholinergic burden assessed using the closest 6-month measure prior to the fall or fracture.

  • ‡Cardiovascular disease=cerebrovascular disease+stroke.

  • §For the subgroup analysis among those aged >65 years, age categories for comparison were 65 to <74 years, vs >75 vs <75 years.

  • OAB, overactive bladder.