Lecture: Social Determinants of Diabetes  


Assigned Reading

  • Impact of neighborhood variables on Type 2 diabetes
    • No impact using statistical mediation analysis Read►
    • Some impact using Causal Networks Read►
    • Calculating time in range from multiple A1c readings Read►


Question 1: The attached data show the percent of diabetes in different 2,228 counties within United States in 2010, 2011, and 2012 years. We want to understand if access to food stores affects diabetes. Create the network model, using data from repeated LASSO regressions.  The first regression will be diabetes in 2012 on all 2011 variables.  Other LASSO regressions will have as response/dependent variable the statistically significant variables in the previous regression regressed on all 2010 variables. Draw the network model using Netica.  Stratify the parents in Markov blanket of diabetes in 2012; calculate the impact of access to quality food stores in 2011 on diabetes using stratified covariate balancing.  Data► Instruction for SCB► New SCB Code► Netica► Answer► Sean's Teach One►

The following shows one possible model and not necessarily the model you will construct with your data.  This model was organized without race and education levels higher than 1.
Network Model of food access and diabetes


Question 2: What are causes of diabetes?  Using LASSO regression construct a causal network for explaining variation in incidence of diabetes.  In the attached data, the dependent variable is incidence of diabetes.  This variable is calculated after all other variables.  There are 21 independent variables that may cause diabetes as listed below:
Name Description
id ID of the patient
dm Incidence of Diabetes, 1 if there was diabetes, 0 otherwise
bs1lr (1) Infectious & parasitic
bs2lr (2) Neoplasms
bs3lr (3) Endocrine, metabolic, & immunity
bs4lr (4) Blood system
bs5lr (5) Mental disorders
bs6lr (6) Nervous system
bs7lr (7) Circulatory system
bs8lr (8) Respiratory system
bs9lr (9) Digestive system
bs10lr (10) Genitourinary system
bs11lr (11) Pregnancy, childbirth
bs12lr (12) Skin and subcutaneous tissue
bs13lr (13) Musculoskeletal system & connective tissue
bs14lr (14) congenital anomalies
bs15lr (15) Perinatal period (no data)
bs16lr (16) Ill-defined conditions
bs17lr (17) Injury and poisoning
bs18lr (18) External causes of injury 
bs19lr (19) Supplemental classification
hf (20) Health factors in VA EHRs
vcode (21) Social and supplemental classifications
Vlr (21) EHR-based index of social determinants of diabetes

These variables were constructed so that for each patient the likelihood ratio associated with the worst diagnosis of the patient within the variable is listed. Construct a causal network and describe if social determinants of illness are direct, or indirect, causes of diabetes.  Construct your models using the training data set and cross-validate using the validation data set. 

Resources for Question 2



For additional information (not part of the required reading), please see the following links:

  1. Pearl's direct and indirect effects Read► Web Appendix►
  2. Saeed's lecture Video►
  3. Mediation analysis allowing for exposure-mediator interactions Read►
  4. Mediation analysis through stable weights Read►
  5. Practical guide to mediation analysis through inverse odds ratio Read► Slides►
  6. Mediation analysis revisited Read►

This page is part of the course on Comparative Effectiveness by Farrokh Alemi, PhD Home► Email►