Table 4

Intervention Effects on HbA_1c, Blood Pressure, Health Care Use, and Diabetes Management Behaviors (N = 304)

	Baseline			Time (Baseline to 12 Months)			Group*Time

	Beta Estimate	SE	P Value	Beta Estimate	SE	P Value	Beta Estimate	SE	P Value
Health Status (medical record)
HbA_1c^a	0.0163	0.0257	.53	0.00002	0.00004	.15	−0.00012	0.00006	.05
Systolic blood pressure^a	0.0302	0.0195	.12	0.00005	0.00003	.30	−0.00004	0.00005	.38
Diastolic blood pressure^a	0.0139	0.0161	.39	−0.00003	0.00003	.18	0.00000	0.00004	.92
Health care use (interview)
Planned diabetes care visits^b	−0.0170	0.0959	.86	−0.00050	0.00023	.02	0.00020	0.00034	.56
Diabetes management behaviors (interview)
Days in past week …
5+ fruits & vegetables consumed^b	−0.1472	0.0929	.11	−0.00020	0.00018	.87	0.00044	0.00026	.09
High fat foods consumed^b	0.1514	0.1115	.18	0.00004	0.00018	.52	−0.00025	0.00027	.35
30 minutes of physical activity^b	−0.1199	0.1289	.35	0.00011	0.00025	.41	0.00010	0.00038	.80
Blood sugar checked^b	−0.0432	0.0871	.62	0.00022	0.00011	.02	−0.00006	0.00017	.74
Feet checked^b	0.0169	0.0683	.81	0.00053	0.00012	<.001	−0.00037	0.00017	.03
Medication adherence^c	−0.1611	0.2830	.57	0.00163	0.00051	<.001	−0.00034	0.00074	.64

The Beta estimate can be interpreted as follows: Group: the adjusted mean difference in the outcome between intervention and usual care participants at baseline. Time: the adjusted rate of change per day in the outcome among all participants. Group*Time: the adjusted rate of change (per day) in the outcome among intervention vs usual care participants. For example, log-transformed HbA_1c was 0.0163 points higher among intervention participants than among usual care participants at baseline (P = .53). Among all participants, log-transformed HbA_1c increased from baseline to 12 months by 0.00002 points per day (P = .15). From baseline to 12 months, log-transformed HbA_1c decreased by −0.00012 more points per day among intervention participants than among usual care participants (P = .05).
↵a Fitted 3 level linear mixed models for log-transformed outcomes, adjusting for clustering at individual and clinic levels, and the following covariates: poverty status, having a personal doctor, medication adherence, and intervention dose.
↵b Fitted 3 level Poisson regression for counts, adjusting for clustering at individual and clinic levels and for the following covariates: poverty status, having a personal doctor, medication adherence, and intervention dose.
↵c Fitted 3 level logistic regression model for a binary outcome, adjusting for clustering at individual and clinic levels and for the following covariates: poverty status, having a personal doctor, and intervention dose.