Data from a cohort study of patients with type 2 diabetes
diabetes.complications.RdAnonymized data from a cohort study of patients with type 2 diabetes followed for ocular and macro-vascular complications.
Usage
data(diabetes.complications)Format
A data frame with 978 observations and 19 variables:
- t
Follow-up time in years.
- epsilon
Event type indicator (0 = censored, 1 = diabetic retinopathy, 2 = macro-vascular complication).
- fruit
Fruit intake (g/day).
- fruitq
Quartile of fruit intake.
- fruitq1
Binary indicator for low fruit intake.
- strata
Stratum used for inverse probability of censoring weights.
- age
Age at baseline (years).
- sex
Sex coded as 0 = woman, 1 = man.
- bmi
Body mass index at baseline.
- hba1c
Hemoglobin A1c (%).
- diabetes_duration
Duration of diabetes (years).
- drug_oha
Indicator for oral hypoglycemic agent use.
- drug_insulin
Indicator for insulin use.
- sbp
Systolic blood pressure (mmHg).
- ldl
Low-density lipoprotein cholesterol (mg/dL).
- hdl
High-density lipoprotein cholesterol (mg/dL).
- tg
Triglycerides (mg/dL).
- current_smoker
Indicator for current smoking status.
- alcohol_drinker
Indicator for current alcohol drinking.
- ltpa
Leisure-time physical activity (METs).
Details
The variables include follow-up time, cause-specific event indicators, exposure indicators for fruit intake, censoring strata, and a set of covariates used in the package vignettes.
Examples
data(diabetes.complications)
str(diabetes.complications)
#> 'data.frame': 978 obs. of 20 variables:
#> $ t : num 8.62 8.51 7.79 8.91 8.94 ...
#> $ epsilon : int 0 0 0 0 0 1 0 1 0 1 ...
#> $ strata : int 1 4 3 1 2 3 1 3 3 1 ...
#> $ fruit : num 75 26.8 64.3 5.35 211.05 ...
#> $ fruitq1 : int 0 1 0 1 0 1 0 0 0 0 ...
#> $ age : int 45 68 63 49 55 61 56 64 67 58 ...
#> $ sex : int 0 0 0 0 0 0 0 1 1 1 ...
#> $ bmi : num 21.5 18.3 23.9 22.9 18.7 23.4 20.1 28.6 25.6 22.8 ...
#> $ hba1c : num 6.97 8.02 6.89 7.24 8.28 ...
#> $ diabetes_duration: num 4.2 2.9 14.3 4.2 16.3 8.9 13 6.1 20.3 13.3 ...
#> $ drug_oha : int 0 0 1 1 1 1 0 1 0 0 ...
#> $ drug_insulin : int 0 1 0 0 0 0 1 0 0 1 ...
#> $ sbp : int 124 128 164 126 136 146 118 136 136 142 ...
#> $ ldl : num 187.3 87.6 74.6 95.7 50.5 ...
#> $ hdl : num 58.1 57.2 35 34.7 55.7 36.7 57.7 52.2 60.5 55.4 ...
#> $ tg : num 123 71 252 83 139 181 71 57 91 115 ...
#> $ current_smoker : int 0 1 1 1 1 0 1 0 0 0 ...
#> $ alcohol_drinker : int 0 0 1 0 0 0 0 0 0 0 ...
#> $ ltpa : num 52.5 11.03 4.38 9.38 12.38 ...
#> $ fruitq : Factor w/ 4 levels "Q1","Q2","Q3",..: 2 1 2 1 4 1 4 2 2 2 ...