OBJECTIVE

Latinos with type 2 diabetes (T2D) face major healthcare access and disease management disparities. We examined the impact of the Diabetes Among Latinos Best Practices Trial (DIALBEST), a community health worker (CHW)–led structured intervention for improving glycemic control among Latinos with T2D.

RESEARCH DESIGN AND METHODS

A total of 211 adult Latinos with poorly controlled T2D were randomly assigned to a standard of healthcare (n = 106) or CHW (n = 105) group. The CHW intervention comprised 17 individual sessions delivered at home by CHWs over a 12-month period. Sessions addressed T2D complications, healthy lifestyles, nutrition, healthy food choices and diet for diabetes, blood glucose self-monitoring, and medication adherence. Demographic, socioeconomic, lifestyle, anthropometric, and biomarker (HbA1c, fasting blood glucose, and lipid profile) data were collected at baseline and 3, 6, 12, and 18 months (6 months postintervention). Groups were equivalent at baseline.

RESULTS

Participants had high HbA1c at baseline (mean 9.58% [81.2 mmol/mol]). Relative to participants in the control group, CHWs had a positive impact on net HbA1c improvements at 3 months (−0.42% [−4.62 mmol/mol]), 6 months (−0.47% [−5.10 mmol/mol]), 12 months (−0.57% [−6.18 mmol/mol]), and 18 months (−0.55% [−6.01 mmol/mol]). The overall repeated-measures group effect was statistically significant (mean difference −0.51% [−5.57 mmol/mol], 95% CI −0.83, −0.19% [−9.11, −2.03 mmol/mol], P = 0.002). CHWs had an overall significant effect on fasting glucose concentration that was more pronounced at the 12- and 18-month visits. There was no significant effect on blood lipid levels, hypertension, and weight.

CONCLUSIONS

DIALBEST is an effective intervention for improving blood glucose control among Latinos with T2D.

Latinos, the fastest growing minority group in the U.S. (1), suffer from a disproportionate burden of type 2 diabetes (T2D) (2) and related complications (3,4). Tangible disparities exist among Latinos in socioeconomic status, health insurance coverage, and use and quality of healthcare services (5,6). Prevalence of obesity (37.9% vs. 33.9%) (7) and physical inactivity (8)—risk factors associated with poor diabetes control—are also more prevalent among Latinos.

Effective metabolic glycemic control has been consistently shown to reduce the incidence of diabetes-related complications in large clinical trials (9,10). Current T2D care guidelines emphasize healthy lifestyles and behavioral change, such as eating a healthy diet, getting regular physical activity, attending primary and specialty clinic visits, and monitoring glycemic control (11). Traditional treatment strategies that focus on medication alone are not enough to achieve diabetes goals among Latinos (12). Limited English proficiency often leads to communication barriers between healthcare providers and Latino patients (13). Lack of provider cross-cultural communication skills to address cultural values among Latinos might result in patient dissatisfaction, treatment noncompliance, and delay in seeking medical help (14). Medical education and support delivered in a community setting by well-trained and supervised local, bilingual community health workers (CHWs) who understand the community’s social determinants of health are likely to improve T2D care among Latinos (15,16).

Only a handful of randomized controlled trials (RCTs) have tested the effectiveness of diabetes education programs delivered by CHWs (1726). Collectively, these studies demonstrated significant improvements in healthy lifestyle behaviors, diabetes knowledge, and HbA1c levels. Most intervention strategies have been group based (17,1925), clinic based (18), or telephone based (20,25) rather than home based (26). In the only home-based intervention study (26), CHWs were not integrated as part of the healthcare management team, and the sustainability of impact on glycemic control postintervention was not assessed. Thus, the objective of the present community-based RCT was to evaluate whether home-based, culturally appropriate counseling delivered by CHWs integrated as part of the healthcare management team can improve glycemic control among Latino adults with T2D and whether the impact is sustained after the intervention ends.

Study Design

The Diabetes Among Latinos Best Practices Trial (DIALBEST) was a parallel, community-based RCT. DIALBEST targeted Latino adults with T2D who attended a community-based ambulatory primary care clinic. Baseline screening was conducted using an electronic medical record database to identify eligible candidates who were contacted in person by recruiters on their clinical appointment day at the primary care clinic. Patients were eligible to participate if they 1) were aged ≥21 years; 2) had a documented diagnosis of T2D for >12 months; 3) lived in Hartford County, CT; 4) had HbA1c levels ≥7% (53 mmol/mol); and 5) self-identified as Hispanic/Latino. Exclusion criteria were 1) pregnancy or breastfeeding; 2) renal failure; 3) active cancer; 4) active hepatitis or advanced cirrhosis; 5) end-stage liver disease; 6) cognitive impairment, dementia, or Alzheimer disease; 7) active and severe mental health problems; 8) a cardiovascular disease event in the previous 12 months (assessed by a physician at the clinic); 9) medical conditions that completely limit ability to perform physical activity independently (e.g., limb amputation, permanent physical disability, blindness); and 10) inability to consume meals orally. Written informed consent and contact information were collected at the clinic.

A total of 211 participants were enrolled from December 2006 to February 2009 and were randomly assigned into either the standard of care (n = 106) or standard of care plus a 12-month-long, CHW-led, culturally tailored diabetes education and counseling treatment group (n = 105). Block randomization involving randomly selected block sizes of four was implemented through computer-generated binary random group assignment. The CHWs visited the treatment group participants at home weekly during the first month, biweekly during months 2 and 3, and monthly thereafter until month 12. Data collection took place at baseline and 3, 6, and 12 months postenrollment to assess the intervention phase and then 6 months thereafter to assess the intervention maintenance phase. Overall, the 18-month attrition rate was 29.9% (34.9% in the control group vs. 24.8% in the intervention group, P = 0.107) (Fig. 1).

Figure 1

Study design flowchart. f/up, follow-up.

Figure 1

Study design flowchart. f/up, follow-up.

Standard of Care

At the time of the study, clinic providers were trained based on American Diabetes Association guidelines and the practice guidelines developed for the clinics. Goals for care, metrics for success, and quality outcomes were monitored to ensure compliance with these guidelines. Every physician (resident or attending) was trained to check HbA1c levels every 3 months and to conduct yearly foot, urine, and eye examinations. The standard practice in the clinic was to measure height, weight, and blood pressure at each visit. Five attending physicians served as mentors to ∼42–48 residents per year equally split across 3 years of residency. The resident physicians were considered as the primary providers and, thus, were responsible for scheduled appointments and routine medical follow-ups. Patients needing urgent evaluation or intervention were able to access the same clinic system but often had to be seen by a different physician for acute care. All patients with T2D were given a glucometer and prescription for glucose test strips and were educated on their proper use. Patients were referred to a clinic dietitian if during a medical visit the healthcare provider discovered major nutrition-related issues. Patients were allowed to purchase their prescriptions at a hospital-based pharmacy at greatly discounted costs. In the last year of this program, the dispensing of discounted medications was discontinued, but study participants received their medications free of cost from the hospital for the duration of their enrollment so as not to adversely affect the study design. This study was approved by the institutional review boards of the University of Connecticut, Hartford Hospital, and the Hispanic Health Council.

CHW DIALBEST Intervention Curriculum

The DIALBEST curriculum was built upon extensive community-based participatory research work in the target community (27,28) and was designed to provide culturally and health literacy appropriate counseling, including informational and instrumental education, skills, and support in the areas of nutrition and food access, physical activity, blood glucose monitoring, medication adherence, and compliance with medical appointments. The DIALBEST curriculum was organized into 17 home-visit sessions delivered by two well-trained and supervised bilingual/bicultural CHWs. Each participant in the intervention group was randomly assigned to and only seen by one of the CHWs. The CHW delivered a comprehensive set of well-structured curriculum modules that exceeded the American Diabetes Association medical nutrition therapy standards (29). The modules focused on T2D and its complications, nutrition, physical activity, blood glucose self-monitoring, adherence to medications and medical appointments, and mental health (Supplementary Table 1). Each module included educational materials with graphics to illustrate key concepts and hands-on activities to improve instrumental knowledge for T2D self-management (e.g., onsite supermarket education on comparative shopping guided by food label reading).

DIALBEST was patient centered and grounded in principles of behavioral change theory, including stages of change, problem-solving theory, and motivational interviewing. As recommended (29,30), the intervention was individually tailored, taking heavily into account the language preference and specific socioeconomic circumstances of each participant. At each visit, the CHW and patient jointly developed a T2D self-management plan based on the individual patient’s clinical history and previous challenges experienced with T2D self-management. Further individual tailoring was determined based on the patient’s stage of change, level of motivation, health literacy, and social support. Home visits were scheduled only during weekdays. If endorsed by the patient, family members present at home during home sessions were allowed to participate.

CHW Training

The two DIALBEST bilingual/bicultural CHWs, a nurse trained in Puerto Rico and a medical assistant originally from El Salvador, underwent 65 h of core training that included T2D pathophysiology and risk factors, lifestyle strategies for glycemic control (nutrition, physical activity, prevention of diabetes complications, and diabetes care), glucose self-monitoring, and T2D medications. More than 25 h of supplemental training were provided, including program delivery topics on motivational interviewing and communication skills (Supplementary Table 2) and topics related to social determinants of health and cultural competence. The trainings were delivered by an interdisciplinary team of academics and practitioners with expertise in clinical medicine, health inequities, Latino health, diabetes self-management, diabetes medications, nutrition, exercise, cross-cultural counseling, and mental health.

CHW Integration Into Healthcare Management Team

The CHWs were employed at a community-based nonprofit organization. They attended weekly meetings with the field supervisor as well as with the health management coordination team at the clinic, which included the primary care clinic medical team and the clinic’s dietitian. At these meetings, the CHWs informed the healthcare professionals of any serious barriers and challenges and T2D management issues faced by participants in the intervention group. Medical providers explained various treatment and management options that might work better with those patients unable to self-manage their T2D. This helped to coordinate the feedback of the CHWs with the care given. Feedback was delivered to the individual providers by the clinic director, who was also the study’s medical director, along with education indicating why management change was suggested. Recommended management changes included adjustments in medication type or dose, timing for eating, timing for taking medication, and adding a snack in the diet before bed (to manage nocturnal hypoglycemia) as well as the type of bedtime snack (high in protein to prevent hyperglycemia at night). Thus, one of the key goals of DIALBEST was to improve the continuum of care of highly impoverished patients with T2D following the Chronic Care Model framework (31).

Data Collection

Data were collected at each participant’s home at baseline and 3, 6, 12, and 18 months by one of five community bilingual interviewers not involved with the healthcare team and blinded to the care delivery group. At baseline, a battery of questions captured socioeconomic; demographic; acculturation; social support; T2D self-management knowledge, attitudes, and behaviors (diet, physical activity, blood glucose self-monitoring, and medication use); and mental health information (3234). Findings of the impact of the intervention on T2D self-management will be reported elsewhere.

A blood collection home visit was conducted for each participant after a 12-h overnight fast by a DIALBEST phlebotomist blinded to study group allocation. HbA1c levels were measured in the home using the A1cNow InView point-of-care device (Metrika Inc., Sunnyvale, CA) from fasting capillary blood. Venous blood (20 mL) was collected into evacuated tubes coated with EDTA and EDTA/sodium fluoride for the measurement of plasma glucose and lipid concentrations (triglycerides and total, HDL, and LDL cholesterol). Blood samples were transported to the laboratory, centrifuged at 2,200g for 30 min at 4°C to separate plasma, and stored at −70°C until analyzed by trained laboratory assistants blinded to group assignment. All biomarkers were measured in duplicate. Body weight (kg), height, waist and hip circumferences (cm), and blood pressure (assessed using a portable sphygmomanometer) were measured by trained interviewers in triplicate following recommended procedures.

A process evaluation ancillary study was conducted in the sample of participants who completed the intervention (n = 76). A research staff member not involved with the delivery of the intervention or prior data collection reviewed the CHWs’ home visit intake forms and progress notes and phone call logs. He also reviewed changes in T2D self-management knowledge assessed by the CHWs during the home visits following a pre/posttest and interviewed the intervention completers to assess their satisfaction with DIALBEST (Supplementary Data) (3538).

Data Analyses

We used SAS for Windows version 9.3 (SAS Institute Inc., Cary, NC) to impute missing values in all the analyses. We used multiple imputation methods to create five data sets with nonmissing values using the PROC MI procedure and then ran all the analyses on each data set followed by combining the estimates from multiple data sets to obtain a single estimate using the PROC MIANALYZE procedure. Fully conditional specification methods were used, with linear or logistic regression to impute continuous and binary variables, respectively (39), which achieved >90% relative efficiency. To assess baseline group balance, we conducted between-group baseline comparisons for demographic, socioeconomic, blood glycemic and lipid levels, and anthropometric characteristics using the χ2 test for categorical variables and independent samples ANOVA for continuous variables. Confounders of the primary and secondary outcomes were selected on the basis of the following criteria: 1) did not interact with intervention and 2) was significantly related to the outcome and intervention in the bivariate analysis. To assess the impact of the intervention on the primary outcome HbA1c and to be able to compare and contrast the results to previously published studies, we modeled the HbA1c outcome in three different ways: the measured raw HbA1c values, HbA1c reduction values, and HbA1c percent change values. HbA1c reduction at 3, 6, 12, and 18 months were defined as the HbA1c values at 3, 6, 12, and 18 months minus the HbA1c baseline value, respectively. HbA1c percent change was calculated at 3, 6, 12, and 18 months as the HbA1c reduction value divided by the HbA1c baseline value. Subsequently, we followed two approaches. First, we conduct a linear mixed-effects (LME) repeated-measures analysis of HbA1c raw values, HbA1c reduction values, and HbA1c percent change, adjusting for baseline HbA1c, and included an interaction term that allowed us to estimate the net between-group HbA1c difference across time points adjusted for confounders. The second approach was to conduct an LME repeated-measures analysis of postbaseline (i.e., excluding the baseline point from the model) HbA1c raw values, HbA1c reduction values, and HbA1c percent change adjusted for time and confounders. We used the PROC MIXED procedure to conduct all LME modeling. LME models were also used to assess the secondary outcomes, including lipid profile, blood pressure, and weight. In all LME analyses of primary and secondary outcomes, we selected the best variance–covariance structure and final fixed- and random-effects models using Akaike information criteria. The best model was the one with the smallest Akaike information criteria value. All analyses were conducted based on intention-to-treat principles, and values were imputed to replace missing data as indicated previously.

Attrition Bias Analysis

To assess attrition bias, we compared the baseline characteristics described previously between completers (n = 148) and noncompleters (n = 63) at 18 months using χ2 test for categorical variables and independent samples t test for continuous variables.

Sample Descriptive Characteristics

Study participants were, on average, 56 years old; 29% were married or living in common law; 26% had at least a high school education; 32% had a home computer, 22% Internet service at home, and 48% a car; 60% had a monthly income of ≤$1,000, 84% were covered by Medicaid, 68.9% received supplemental security income, and 73% were enrolled in the Supplemental Nutrition Assistance Program. There were no significant between-group differences in any of the demographic and socioeconomic variables compared at baseline (Table 1).

Table 1

Demographic and socioeconomic characteristics among Connecticut Latinos with T2D participating in the DIALBEST trial

VariableAll (N = 211)Control (n = 106)CHW (n = 105)P value
Age (years) 56.3 ± 11.8 57.3 ± 12.1 55.4 ± 11.5 0.245 
Female sex 73.5 74.5 72.4 0.724 
Language    0.439 
 English and Spanish 34.6 32.1 37.1  
 Spanish 65.4 67.9 47.8  
Marital status    0.861 
 Single 28.0 29.2 26.7  
 Married 22.3 22.6 21.9  
 Common law 7.1 4.7 9.5  
 Separated 10.9 11.3 10.5  
 Divorced 17.1 17.0 17.1  
 Widowed 14.7 15.1 14.3  
Highest school grade    0.628 
 No schooling 4.3 3.8 4.8  
  ≤8th grade 47.9 49.1 46.7  
 Some high school 21.8 24.5 19.0  
 High school/GED 17.1 15.1 19.0  
 Technical 2.8 3.8 1.9  
 Some college 5.2 2.8 7.6  
 College 0.9 0.9 1.0  
Working 15.6 14.2 17.1 0.550 
Possessions     
 Telephone 77.3 82.1 72.4 0.093 
 Cell phone 64.5 67.0 61.9 0.441 
 Radio/CD player 77.7 77.4 78.1 0.898 
 Cable television 86.7 86.8 86.7 0.595 
 Video player 63.0 62.3 63.8 0.973 
 DVD player 69.0 71.7 66.3 0.402 
 Computer 32.2 31.1 33.3 0.732 
 Internet 22.3 20.8 23.8 0.713 
 Car 48.3 49.1 47.6 0.835 
 Microwave oven 93.8 94.3 93.3 0.748 
Total monthly income    0.548 
 $0–500 53.6 53.8 53.4  
 $501–1,000 25.4 24.5 26.2  
 $1,001–1,500 4.8 2.8 6.8  
 $1,501–2,000 2.4 3.8 1.0  
 $2,001–3,000 7.2 8.5 5.8  
 Unknown 6.7 6.6 6.8  
VariableAll (N = 211)Control (n = 106)CHW (n = 105)P value
Age (years) 56.3 ± 11.8 57.3 ± 12.1 55.4 ± 11.5 0.245 
Female sex 73.5 74.5 72.4 0.724 
Language    0.439 
 English and Spanish 34.6 32.1 37.1  
 Spanish 65.4 67.9 47.8  
Marital status    0.861 
 Single 28.0 29.2 26.7  
 Married 22.3 22.6 21.9  
 Common law 7.1 4.7 9.5  
 Separated 10.9 11.3 10.5  
 Divorced 17.1 17.0 17.1  
 Widowed 14.7 15.1 14.3  
Highest school grade    0.628 
 No schooling 4.3 3.8 4.8  
  ≤8th grade 47.9 49.1 46.7  
 Some high school 21.8 24.5 19.0  
 High school/GED 17.1 15.1 19.0  
 Technical 2.8 3.8 1.9  
 Some college 5.2 2.8 7.6  
 College 0.9 0.9 1.0  
Working 15.6 14.2 17.1 0.550 
Possessions     
 Telephone 77.3 82.1 72.4 0.093 
 Cell phone 64.5 67.0 61.9 0.441 
 Radio/CD player 77.7 77.4 78.1 0.898 
 Cable television 86.7 86.8 86.7 0.595 
 Video player 63.0 62.3 63.8 0.973 
 DVD player 69.0 71.7 66.3 0.402 
 Computer 32.2 31.1 33.3 0.732 
 Internet 22.3 20.8 23.8 0.713 
 Car 48.3 49.1 47.6 0.835 
 Microwave oven 93.8 94.3 93.3 0.748 
Total monthly income    0.548 
 $0–500 53.6 53.8 53.4  
 $501–1,000 25.4 24.5 26.2  
 $1,001–1,500 4.8 2.8 6.8  
 $1,501–2,000 2.4 3.8 1.0  
 $2,001–3,000 7.2 8.5 5.8  
 Unknown 6.7 6.6 6.8  

Data are mean ± SD or %. CD, compact disc; DVD, digital video disc; GED, General Educational Development.

At baseline, blood glycemic and lipid profiles were not different between groups, but mean systolic blood pressure was significantly higher in the intervention group yet within normal limits. Mean HbA1c was 9.6% (81 mmol/mol), glucose 10.6 mmol/L, triglycerides 1.75 mmol/L, total cholesterol 4.65 mmol/L, LDL cholesterol 2.55 mmol/L, HDL cholesterol 1.33 mmol/L, and systolic blood pressure 118 mmHg. Likewise, there were no between-group differences in baseline anthropometry, including waist circumference (107.2 cm), weight (85.1 kg), height (1.58 m), and BMI (33.7 kg/m2) (Table 2).

Table 2

Health insurance, food assistance, social protection, and baseline biomedical factors among Connecticut Latinos with T2D participating in the DIALBEST trial

VariableAll (N = 211)Control (n = 106)CHW (n = 105)P value
Health insurance, food assistance,  and social protection     
 Medicare 33.7 34.0 33.3 0.924 
 Medicaid 84.1 80.0 88.3 0.099 
 Supplemental security income 68.9 69.8 68.0 0.773 
 SNAP 73.3 69.8 76.9 0.244 
 Systolic blood pressure (mmHg) 118 ± 0.48 116 ± 0.65 119 ± 0.70 0.001 
Fasting HbA1c, plasma glucose,  and lipid concentrations     
 HbA1c (%) 9.58 ± 0.12 9.58 ± 0.17 9.57 ± 0.18 0.981 
 HbA1c (mmol/mol) 81.2 ± 1.36 81.2 ± 1.91 81.1 ± 1.94 0.981 
 Glucose (mmol/L) 10.57 ± 0.32 10.48 ± 0.48 10.67 ± 0.44 0.765 
 Triglycerides (mmol/L) 1.75 ± 0.08 1.69 ± 0.10 1.81 ± 0.12 0.487 
 Total cholesterol (mmol/L) 4.65 ± 0.08 4.60 ± 0.11 4.69 ± 0.11 0.578 
 HDL (mmol/L) 1.33 ± 0.02 1.37 ± 0.02 1.29 ± 0.04 0.145 
 LDL (mmol/L) 2.55 ± 0.07 2.49 ± 0.09 2.61 ± 0.10 0.382 
Anthropometry     
 Waist circumference (cm) 107.16 ± 1.11 105.85 ± 1.44 108.49 ± 1.70 0.237 
 Weight (kg) 85.07 ± 1.59 83.34 ± 1.87 86.82 ± 2.57 0.275 
 Height (cm) 158.48 ± 0.61 158.22 ± 0.85 158.75 ± 0.88 0.669 
 BMI (kg/m233.74 ± 0.53 33.38 ± 0.74 34.10 ± 0.77 0.498 
VariableAll (N = 211)Control (n = 106)CHW (n = 105)P value
Health insurance, food assistance,  and social protection     
 Medicare 33.7 34.0 33.3 0.924 
 Medicaid 84.1 80.0 88.3 0.099 
 Supplemental security income 68.9 69.8 68.0 0.773 
 SNAP 73.3 69.8 76.9 0.244 
 Systolic blood pressure (mmHg) 118 ± 0.48 116 ± 0.65 119 ± 0.70 0.001 
Fasting HbA1c, plasma glucose,  and lipid concentrations     
 HbA1c (%) 9.58 ± 0.12 9.58 ± 0.17 9.57 ± 0.18 0.981 
 HbA1c (mmol/mol) 81.2 ± 1.36 81.2 ± 1.91 81.1 ± 1.94 0.981 
 Glucose (mmol/L) 10.57 ± 0.32 10.48 ± 0.48 10.67 ± 0.44 0.765 
 Triglycerides (mmol/L) 1.75 ± 0.08 1.69 ± 0.10 1.81 ± 0.12 0.487 
 Total cholesterol (mmol/L) 4.65 ± 0.08 4.60 ± 0.11 4.69 ± 0.11 0.578 
 HDL (mmol/L) 1.33 ± 0.02 1.37 ± 0.02 1.29 ± 0.04 0.145 
 LDL (mmol/L) 2.55 ± 0.07 2.49 ± 0.09 2.61 ± 0.10 0.382 
Anthropometry     
 Waist circumference (cm) 107.16 ± 1.11 105.85 ± 1.44 108.49 ± 1.70 0.237 
 Weight (kg) 85.07 ± 1.59 83.34 ± 1.87 86.82 ± 2.57 0.275 
 Height (cm) 158.48 ± 0.61 158.22 ± 0.85 158.75 ± 0.88 0.669 
 BMI (kg/m233.74 ± 0.53 33.38 ± 0.74 34.10 ± 0.77 0.498 

Data are % or mean ± SE. SNAP, Supplemental Nutrition Assistance Program.

DIALBEST Impact on HbA1c

Results of the LME models that included time-by-intervention interaction and adjusted for baseline HbA1c levels and age revealed that the DIALBEST intervention led to a net reduction HbA1c difference from baseline of −0.42% (−4.62 mmol/mol) at 3 months (P = 0.043) followed by a net reduction difference of −0.47% (−5.10 mmol/mol) at 6 months (P = 0.050), −0.57% (−6.18 mmol/mol) at 12 months (P = 0.021), and −0.55% (−6.01 mmol/mol) at 18 months (P = 0.009) in favor of the CHW group (Table 3, Fig. 2). Consistent with these findings, the LME repeated-measures analyses that adjusted for baseline HbA1c levels and age and were restricted to postbaseline time points identified a significant overall group effect such that the intervention group had lower HbA1c levels compared with the control group (mean difference −0.51% [−5.57 mmol/mol], 95% CI −0.83, −0.19% [−9.11, −2.03 mmol/mol], P = 0.002). Similarly, the HbA1c percent change was significantly higher in the CHW group compared with the control group (mean difference −5.52% [−7.33 mmol/mol], 95% CI −8.93, −2.11% [−11.9, −2.81 mmol/mol], P = 0.002) (Table 3).

Table 3

LME models of intervention on primary and secondary outcomes among Connecticut Latinos with T2D participating in the DIALBEST trial

OutcomeControlCHWGroup! differenceP value
Primary outcome     
 HbA1c (%)@ 9.36 (8.96, 9.75) 8.85 (8.41, 9.28) −0.51 (−0.83, −0.19) 0.002 
 HbA1c (mmol/mol) 78.8 (74.4, 83.1) 73.2 (68.4, 78.0) −5.57 (−9.11, −2.03) 0.002 
 HbA1c (%)@@    0.002~ 
  Baseline 9.76 (9.35, 10.2) 9.70 (9.30, 10.1) −0.06 (−0.44, 0.33) 0.780 
  3 months 9.19 (8.71, 9.67) 8.77 (8.34, 9.17) −0.42 (−0.83, −0.01) 0.043 
  6 months 9.28 (8.90, 9.66) 8.81 (8.37, 9.26) −0.47 (−0.93, 0.0001 0.050 
  12 months 9.42 (9.07, 9.77) 8.85 (8.47, 9.23) −0.57 (−1.04, −0.09) 0.021 
  18 months 9.32 (8.91, 9.74) 8.77 (8.35, 9.20) −0.55 (−0.96, −0.14) 0.009 
 HbA1c (mmol/mol)@@    0.002~ 
  Baseline 83.2 (78.7, 87.6) 82.6 (78.1, 87.0) −0.61 (−4.85, 3.64) 0.780 
  3 months 76.9 (71.7, 82.2) 72.3 (67.7, 77.0) −4.62 (−9.09, −0.14) 0.043 
  6 months 77.9 (73.7, 82.1) 72.8 (67.9, 77.7) −5.10 (−10.2, −0.002) 0.050 
  12 months 79.4 (75.6, 83.3) 73.3 (69.1, 77.4) −6.18 (−11.4, −0.96) 0.021 
  18 months 78.4 (73.9, 83.0) 72.4 (67.7, 77.0) −6.01 (−10.5, −1.50) 0.009 
 HbA1c percent change (%)* −0.96 (−4.96, 3.04) −6.48 (−11.0, −1.99) −5.52 (−8.93, −2.11) 0.002 
 HbA1c percent change (mmol/mol)* −0.68 (−5.89, 4.53) −8.01 (−13.9, −2.13) −7.33 (−11.9, −2.81) 0.002 
 HbA1c percent change (%)**    0.002~ 
  3 months −2.26 (−7.69, 3.17) −6.90 (−11.9, −1.93) −4.64 (−9.17, −0.11) 0.045 
  6 months −1.48 (−6.00, 3.03) −6.40 (−11.6, −1.24) −4.92 (−10.0, 0.19) 0.059 
  12 months 0.16 (−3.75, 4.08) −6.02 (−10.4, −1.63) −6.19 (−11.1, −1.24) 0.015 
  18 months −0.39 (−5.17, 4.38) −6.76 (−11.8, −1.72) −6.37 (−11.1, −1.64) 0.009 
 HbA1c percent change (mmol/mol)**    0.002~ 
  3 months −2.45 (−9.51, 4.61) −8.55(−15.1, −2.04) −6.10 (−12.1, −0.12) 0.046 
  6 months −1.44 (−7.35, 4.48) −7.90 (−14.7, −1.09) −6.47 (−13.2, 0.26) 0.059 
  12 months 0.81 (−4.32, 5.94) −7.45 (−13.2, −1.70) −8.26 (−14.7, −1.82) 0.012 
  18 months 0.19 (−6.04, 6.41) −8.35 (−15.0, −1.74) −8.54 (−14.8, −2.26) 0.008 
Secondary outcomes     
 Glucose (mmol/L)# 11.3 (10.4, 12.3) 10.3 (9.26, 11.3) −1.08 (−1.78, −0.39) 0.002 
 Glucose (mmol/L)##    0.002~ 
  Baseline 11.3 (10.4, 12.3) 11.3 (10.3, 12.2) −0.06 (−1.05, 0.94) 0.913 
  3 months 10.9 (9.64, 12.1) 10.1 (9.12, 11.2) −0.75 (−1.84, 0.34) 0.179 
  6 months 10.7 (9.74, 11.7) 10.3 (9.37, 11.3) −0.43 (−1.50, 0.65) 0.434 
  12 months 11.6 (10.7, 12.5) 10.2 (9.07, 11.4) −1.38 (−2.52, −0.25) 0.018 
  18 months 11.7 (10.8, 12.6) 9.92 (8.75, 11.1) −1.79 (−2.94, −0.64) 0.003 
 Triglycerides (mmol/L)$ 1.65 (1.53, 1.79) 1.59 (1.47, 1.73) −0.05 (−0.23, 0.13) 0.549 
 Triglycerides (mmol/L)$$    0.523~ 
  Baseline 1.68 (1.53, 1.85) 1.73 (1.57, 1.90) 0.05 (−0.18, 0.27)  
  3 months 1.59 (1.41, 1.77) 1.63 (1.46, 1.81) 0.04 (−0.23, 0.31)  
  6 months 1.68 (1.51, 1.86) 1.53 (1.36, 1.69) −0.16 (−0.40, 0.08)  
  12 months 1.66 (1.46, 1.86) 1.56 (1.37, 1.75) −0.11 (−0.40, 0.19)  
  18 months 1.74 (1.55, 1.93) 1.67 (1.49, 1.86) −0.06 (−0.36, 0.24)  
 Total cholesterol (mmol/L)% 4.51 (4.38, 4.64) 4.56 (4.40, 4.71) −0.05 (−0.17, 0.28) 0.628 
 Total cholesterol (mmol/L)%%    0.865~ 
  Baseline 4.60 (4.40, 4.79) 4.61 (4.43, 4.82) 0.01 (−0.26, 0.28)  
  3 months 4.48 (4.30, 4.69) 4.53 (4.35, 4.74) 0.04 (−0.24, 0.32)  
  6 months 4.62 (4.40, 4.82) 4.62 (4.43, 4.82) −0.00 (−0.28, 0.29)  
  12 months 4.53 (4.33, 4.71) 4.62 (4.43, 4.82) 0.09 (−0.20, 0.38)  
  18 months 4.55 (4.33, 4.77) 4.49 (4.20, 4.79) −0.06 (−0.48, 0.36)  
 HDL cholesterol (mmol/L)^ 1.39 (1.34, 1.44) 1.40 (1.36, 1.45) 0.01 (−0.05, 0.08) 0.720 
 HDL cholesterol (mmol/L)^^    0.564~ 
  Baseline 1.35 (1.30, 1.41) 1.33 (1.27, 1.39) −0.02 (−0.10, 0.06)  
  3 months 1.33 (1.28, 1.39) 1.39 (1.31, 1.45) 0.05 (−0.05, 0.14)  
  6 months 1.39 (1.31, 1.47) 1.36 (1.30, 1.43) 0.03 (−0.12, 0.07)  
  12 months 1.39 (1.32, 1.46) 1.47 (1.40, 1.53) 0.08 (−0.02, 0.18)  
  18 months 1.40 (1.34, 1.47) 1.40 (1.33, 1.47) −0.003 (−0.08, 0.08)  
 LDL cholesterol (mmol/L)& 2.39 (2.26, 2.52) 2.45 (2.30, 2.62) 0.06 (−0.15, 0.27) 0.564 
 LDL cholesterol (mmol/L)&&    0.598~ 
  Baseline 2.39 (2.34, 2.69) 2.58 (2.40, 2.75) 0.06 (−0.19, 0.32)  
  3 months 2.41 (2.23, 2.59) 2.46 (2.26, 2.46) 0.05 (−0.22, 0.31)  
  6 months 2.46 (2.26, 2.67) 2.55 (2.35, 2.75) 0.09 (−0.20, 0.37)  
  12 months 2.38 (2.19, 2.56) 2.42 (2.22, 2.62) 0.04 (−0.22, 0.31)  
  18 months 2.38 (2.17, 2.59) 2.36 (2.10, 2.62) −0.02 (−0.43, 0.40)  
 Weight (kg)+ 86.1 (83.7, 88.4) 86.0 (83.3, 88.7) −0.07 (−3.34, 3.19) 0.964 
 Weight (kg)++    0.964~ 
  Baseline 84.8 (82.2, 87.5) 85.3 (82.7, 87.9) 0.49 (−3.24, 4.21)  
  3 months 86.9 (83.4, 90.3) 85.3 (82.1, 88.4) −1.62 (−6.69, 3.44)  
  6 months 85.9 (82.9, 88.9) 85.3 (82.1, 88.5) −0.60 (−5.03, 3.83)  
  12 months 86.4 (82.3, 90.5) 87.3 (84.0, 90.6) 0.90 (−3.31, 5.11)  
  18 months 85.4 (82.5, 88.2) 85.9 (81.6, 90.3) 0.54 (−5.70, 6.78)  
 Systolic blood pressure (mmHg)= 116 (115, 118) 118 (116, 120) 1.71 (−1.45, 4.86) 0.279 
 Systolic blood pressure (mmHg)==    0.313~ 
  Baseline 119 (116, 121) 120 (117, 123) 1.50 (−2.40, 5.39)  
  3 months 115 (112, 117) 117 (114, 119) 2.09 (−1.74, 5.92)  
  6 months 118 (114, 121) 117 (113, 120) −1.02 (−7.11, 5.08)  
  12 months 118 (114, 121) 119 (117, 122) 1.20 (−2.70, 5.11)  
  18 months 116 (113, 119) 119 (116, 122) 2.87 (−1.74, 7.47)  
OutcomeControlCHWGroup! differenceP value
Primary outcome     
 HbA1c (%)@ 9.36 (8.96, 9.75) 8.85 (8.41, 9.28) −0.51 (−0.83, −0.19) 0.002 
 HbA1c (mmol/mol) 78.8 (74.4, 83.1) 73.2 (68.4, 78.0) −5.57 (−9.11, −2.03) 0.002 
 HbA1c (%)@@    0.002~ 
  Baseline 9.76 (9.35, 10.2) 9.70 (9.30, 10.1) −0.06 (−0.44, 0.33) 0.780 
  3 months 9.19 (8.71, 9.67) 8.77 (8.34, 9.17) −0.42 (−0.83, −0.01) 0.043 
  6 months 9.28 (8.90, 9.66) 8.81 (8.37, 9.26) −0.47 (−0.93, 0.0001 0.050 
  12 months 9.42 (9.07, 9.77) 8.85 (8.47, 9.23) −0.57 (−1.04, −0.09) 0.021 
  18 months 9.32 (8.91, 9.74) 8.77 (8.35, 9.20) −0.55 (−0.96, −0.14) 0.009 
 HbA1c (mmol/mol)@@    0.002~ 
  Baseline 83.2 (78.7, 87.6) 82.6 (78.1, 87.0) −0.61 (−4.85, 3.64) 0.780 
  3 months 76.9 (71.7, 82.2) 72.3 (67.7, 77.0) −4.62 (−9.09, −0.14) 0.043 
  6 months 77.9 (73.7, 82.1) 72.8 (67.9, 77.7) −5.10 (−10.2, −0.002) 0.050 
  12 months 79.4 (75.6, 83.3) 73.3 (69.1, 77.4) −6.18 (−11.4, −0.96) 0.021 
  18 months 78.4 (73.9, 83.0) 72.4 (67.7, 77.0) −6.01 (−10.5, −1.50) 0.009 
 HbA1c percent change (%)* −0.96 (−4.96, 3.04) −6.48 (−11.0, −1.99) −5.52 (−8.93, −2.11) 0.002 
 HbA1c percent change (mmol/mol)* −0.68 (−5.89, 4.53) −8.01 (−13.9, −2.13) −7.33 (−11.9, −2.81) 0.002 
 HbA1c percent change (%)**    0.002~ 
  3 months −2.26 (−7.69, 3.17) −6.90 (−11.9, −1.93) −4.64 (−9.17, −0.11) 0.045 
  6 months −1.48 (−6.00, 3.03) −6.40 (−11.6, −1.24) −4.92 (−10.0, 0.19) 0.059 
  12 months 0.16 (−3.75, 4.08) −6.02 (−10.4, −1.63) −6.19 (−11.1, −1.24) 0.015 
  18 months −0.39 (−5.17, 4.38) −6.76 (−11.8, −1.72) −6.37 (−11.1, −1.64) 0.009 
 HbA1c percent change (mmol/mol)**    0.002~ 
  3 months −2.45 (−9.51, 4.61) −8.55(−15.1, −2.04) −6.10 (−12.1, −0.12) 0.046 
  6 months −1.44 (−7.35, 4.48) −7.90 (−14.7, −1.09) −6.47 (−13.2, 0.26) 0.059 
  12 months 0.81 (−4.32, 5.94) −7.45 (−13.2, −1.70) −8.26 (−14.7, −1.82) 0.012 
  18 months 0.19 (−6.04, 6.41) −8.35 (−15.0, −1.74) −8.54 (−14.8, −2.26) 0.008 
Secondary outcomes     
 Glucose (mmol/L)# 11.3 (10.4, 12.3) 10.3 (9.26, 11.3) −1.08 (−1.78, −0.39) 0.002 
 Glucose (mmol/L)##    0.002~ 
  Baseline 11.3 (10.4, 12.3) 11.3 (10.3, 12.2) −0.06 (−1.05, 0.94) 0.913 
  3 months 10.9 (9.64, 12.1) 10.1 (9.12, 11.2) −0.75 (−1.84, 0.34) 0.179 
  6 months 10.7 (9.74, 11.7) 10.3 (9.37, 11.3) −0.43 (−1.50, 0.65) 0.434 
  12 months 11.6 (10.7, 12.5) 10.2 (9.07, 11.4) −1.38 (−2.52, −0.25) 0.018 
  18 months 11.7 (10.8, 12.6) 9.92 (8.75, 11.1) −1.79 (−2.94, −0.64) 0.003 
 Triglycerides (mmol/L)$ 1.65 (1.53, 1.79) 1.59 (1.47, 1.73) −0.05 (−0.23, 0.13) 0.549 
 Triglycerides (mmol/L)$$    0.523~ 
  Baseline 1.68 (1.53, 1.85) 1.73 (1.57, 1.90) 0.05 (−0.18, 0.27)  
  3 months 1.59 (1.41, 1.77) 1.63 (1.46, 1.81) 0.04 (−0.23, 0.31)  
  6 months 1.68 (1.51, 1.86) 1.53 (1.36, 1.69) −0.16 (−0.40, 0.08)  
  12 months 1.66 (1.46, 1.86) 1.56 (1.37, 1.75) −0.11 (−0.40, 0.19)  
  18 months 1.74 (1.55, 1.93) 1.67 (1.49, 1.86) −0.06 (−0.36, 0.24)  
 Total cholesterol (mmol/L)% 4.51 (4.38, 4.64) 4.56 (4.40, 4.71) −0.05 (−0.17, 0.28) 0.628 
 Total cholesterol (mmol/L)%%    0.865~ 
  Baseline 4.60 (4.40, 4.79) 4.61 (4.43, 4.82) 0.01 (−0.26, 0.28)  
  3 months 4.48 (4.30, 4.69) 4.53 (4.35, 4.74) 0.04 (−0.24, 0.32)  
  6 months 4.62 (4.40, 4.82) 4.62 (4.43, 4.82) −0.00 (−0.28, 0.29)  
  12 months 4.53 (4.33, 4.71) 4.62 (4.43, 4.82) 0.09 (−0.20, 0.38)  
  18 months 4.55 (4.33, 4.77) 4.49 (4.20, 4.79) −0.06 (−0.48, 0.36)  
 HDL cholesterol (mmol/L)^ 1.39 (1.34, 1.44) 1.40 (1.36, 1.45) 0.01 (−0.05, 0.08) 0.720 
 HDL cholesterol (mmol/L)^^    0.564~ 
  Baseline 1.35 (1.30, 1.41) 1.33 (1.27, 1.39) −0.02 (−0.10, 0.06)  
  3 months 1.33 (1.28, 1.39) 1.39 (1.31, 1.45) 0.05 (−0.05, 0.14)  
  6 months 1.39 (1.31, 1.47) 1.36 (1.30, 1.43) 0.03 (−0.12, 0.07)  
  12 months 1.39 (1.32, 1.46) 1.47 (1.40, 1.53) 0.08 (−0.02, 0.18)  
  18 months 1.40 (1.34, 1.47) 1.40 (1.33, 1.47) −0.003 (−0.08, 0.08)  
 LDL cholesterol (mmol/L)& 2.39 (2.26, 2.52) 2.45 (2.30, 2.62) 0.06 (−0.15, 0.27) 0.564 
 LDL cholesterol (mmol/L)&&    0.598~ 
  Baseline 2.39 (2.34, 2.69) 2.58 (2.40, 2.75) 0.06 (−0.19, 0.32)  
  3 months 2.41 (2.23, 2.59) 2.46 (2.26, 2.46) 0.05 (−0.22, 0.31)  
  6 months 2.46 (2.26, 2.67) 2.55 (2.35, 2.75) 0.09 (−0.20, 0.37)  
  12 months 2.38 (2.19, 2.56) 2.42 (2.22, 2.62) 0.04 (−0.22, 0.31)  
  18 months 2.38 (2.17, 2.59) 2.36 (2.10, 2.62) −0.02 (−0.43, 0.40)  
 Weight (kg)+ 86.1 (83.7, 88.4) 86.0 (83.3, 88.7) −0.07 (−3.34, 3.19) 0.964 
 Weight (kg)++    0.964~ 
  Baseline 84.8 (82.2, 87.5) 85.3 (82.7, 87.9) 0.49 (−3.24, 4.21)  
  3 months 86.9 (83.4, 90.3) 85.3 (82.1, 88.4) −1.62 (−6.69, 3.44)  
  6 months 85.9 (82.9, 88.9) 85.3 (82.1, 88.5) −0.60 (−5.03, 3.83)  
  12 months 86.4 (82.3, 90.5) 87.3 (84.0, 90.6) 0.90 (−3.31, 5.11)  
  18 months 85.4 (82.5, 88.2) 85.9 (81.6, 90.3) 0.54 (−5.70, 6.78)  
 Systolic blood pressure (mmHg)= 116 (115, 118) 118 (116, 120) 1.71 (−1.45, 4.86) 0.279 
 Systolic blood pressure (mmHg)==    0.313~ 
  Baseline 119 (116, 121) 120 (117, 123) 1.50 (−2.40, 5.39)  
  3 months 115 (112, 117) 117 (114, 119) 2.09 (−1.74, 5.92)  
  6 months 118 (114, 121) 117 (113, 120) −1.02 (−7.11, 5.08)  
  12 months 118 (114, 121) 119 (117, 122) 1.20 (−2.70, 5.11)  
  18 months 116 (113, 119) 119 (116, 122) 2.87 (−1.74, 7.47)  

Data are mean (95% CI).

!Reference is the control group.

@Models of HbA1c % and HbA1c change gave identical results. Models included group, time, baseline HbA1c level, age, and antidiabetic medications.

@@Models of HbA1c % and HbA1c change gave identical group mean difference results. Models included group, time, group-by-time interaction, baseline HbA1c level, age, and antidiabetic medications.

~Overall effect P value; P values for time point comparisons not reported if P > 0.05.

*Model included group, time, baseline HbA1c level, age, and antidiabetic medications.

**Model included group, time, group-by-time interaction, baseline HbA1c level, age, and antidiabetic medications.

#Model included group, time, baseline glucose level, age, and antidiabetic medications.

##Model included group, time, group-by-time interaction, baseline glucose level, age, and antidiabetic medications.

$Model included group, time, baseline triglyceride level, glucose level, and total cholesterol level.

$$Model included group, time, group-by-time interaction, baseline triglyceride level, glucose level, and total cholesterol level.

%Model included group, time, baseline total cholesterol level, triglyceride level, and anticholesterol medications.

%%Model included group, time, group-by-time interaction, baseline total cholesterol level, triglyceride level, and anticholesterol medications.

^Model included baseline HDL level and triglyceride level.

^^Model included group, time, group-by-time interaction, baseline HDL level, and triglyceride level.

&Model included group, time, baseline LDL level, triglyceride level, and anticholesterol medications.

&&Model included group, time, group-by-time interaction, baseline LDL level, triglyceride level, and anticholesterol medications.

+Model included group, time, and baseline weight.

++Model included group, time, group-by-time interaction, and baseline weight.

=Model included group, time, baseline systolic blood pressure, total cholesterol level, and antihypertension medications.

==Model included group, time, group-by-time interaction, baseline systolic hypertension, total cholesterol level, and antihypertension medications.

Figure 2

Participant HbA1c percent decline compared with baseline. Net reduction difference in HbA1c between CHW and control groups at 3, 6, 12, and 18 months were −0.42% (P = 0.043), −0.47% (P = 0.050), −0.57% (P = 0.021), and −0.55% (P = 0.009), respectively. Mean differences and P values are from adjusted LMEs.

Figure 2

Participant HbA1c percent decline compared with baseline. Net reduction difference in HbA1c between CHW and control groups at 3, 6, 12, and 18 months were −0.42% (P = 0.043), −0.47% (P = 0.050), −0.57% (P = 0.021), and −0.55% (P = 0.009), respectively. Mean differences and P values are from adjusted LMEs.

DIALBEST Impact on Secondary Outcomes

We also observed a significant effect of the intervention on fasting glucose. The CHW group had lower glucose concentrations compared with the control group (mean difference −1.08 mmol/L [95% CI −1.79, −0.39 mmol/L], P = 0.002) (Table 3). The intervention did not have a significant effect on HDL, LDL, and total cholesterol; triglycerides; systolic blood pressure; or weight (Table 3).

Attrition Bias Analysis

The overall dropout rate was 29.9% at 18 months, which was slightly lower among intervention than control participants (24.8% vs. 34.9%, respectively, P = 0.107). The majority of the noncompleters reported lack of time as a reason for dropping out (Fig. 1). Completers and noncompleters were similar in baseline characteristics except that of 31 baseline comparisons, completers were more likely to have a cell phone (68.9% vs. 54%, P = 0.038) and were less likely to be married (18.2% vs. 31.7%, P = 0.013).

Process Evaluation

The positive impact of DIALBEST is well supported by the process evaluation conducted with study completers by a research assistant not involved with the trial. Specifically, the process evaluation based on CHW logs documented strong fidelity in the delivery of the intervention by CHWs, which in turn translated into improved T2D self-management knowledge. Client satisfaction with DIALBEST was very high (3538) (Supplementary Data).

DIALBEST Impact

To our knowledge, this RCT is the first to document the strong impact a home-based model can have on improving glycemic control among highly impoverished Latinos when a CHW is fully integrated within the healthcare management team. The study has several design and community-based methodological strengths. The 12-month-long intervention was followed by a 6-month postintervention maintenance period, allowing us to document the sustainability of the impact. All intervention procedures and data collection occurred in the participants’ homes. Although the nature of the intervention did not lend itself to total concealment, the data were collected by highly trained community interviewers (one of which also served as the study’s community phlebotomist) not involved in the delivery of the CHW intervention, and the individuals conducting laboratory analyses were blinded to group assignment. The findings have strong internal validity because the RCT achieved remarkable between-group baseline balance. The strong community- and clinic-based supervisory system assured strong intervention fidelity that relied on having only two highly trained CHWs who provided consistent information to participants (Supplementary Data).

The present findings of an HbA1c reduction among the CHW group, ranging from −0.93% [−10.3 mmol/mol] at 3 months to −0.85% [−9.3 mmol/mol] at 12 months followed by sustaining the effect size during the 6-month maintenance period, strongly suggest a clinical (9) and public health (40) impact of DIALBEST. The size of the HbA1c reduction observed in our intervention group at 6 months post enrollment of −0.9% [−9.8 mmol/mol] is fully consistent with the one documented by Spencer et al. (24) of −0.8% [−8.7 mol/mol] at the same time point in their RCT targeting African Americans and Latinos (predominantly Mexican Americans) with T2D living in Detroit predominantly through group sessions (vs. individual home visits as in the present study). In that study, the CHW intervention comprised 11 2-h-long comprehensive diabetes education group sessions offered every other week at community agencies, 2 60-min-long home visits, and 1 clinic visit with a healthcare provider. The study by Rothschild et al. (26) documented among Mexican Americans that 36 CHW home sessions delivered over 2 years led to a net HbA1c reduction of −0.69% [−7.5 mmol/mol] compared with a net reduction of −0.55% [−6.01 mmol/mol] at 18 months postenrollment in our study. Thus, DIALBEST was found to have a similarly strong glycemic control benefit compared with a stand-alone group-based and a more intensive home-based model. However, their study design differed from DIALBEST because it did not integrate CHWs as part of the healthcare management team, the control arm was a newsletter (vs. usual healthcare in DIALBEST), and the study did not assess the sustainability of impact once the intervention ended, included twice as many CHW home visits, and the intervention lasted twice as long. In addition, participants in the Rothschild et al. study had better blood glucose control compared with DIALBEST participants, with ∼30% of their participants having a baseline HbA1c <7% (53 mmol/mol) (vs. 5.2% of DIALBEST participants), and they targeted Mexican Americans (vs. Puerto Ricans/Dominicans in DIALBEST). Thus, DIALBEST adds significant new knowledge from both the perspective of community-based healthcare delivery of T2D self-management and the impact of CHWs on blood glucose control among a highly impoverished population with very poor blood glycemic control. DIALBEST represents the testing of a community-based real-world healthcare model that can be replicated elsewhere and that is closely aligned with the priorities of the Affordable Care Act.

The more-advanced formal education of the present study’s CHWs contrasts with the lower levels of formal education of CHWs used in the study by Rothschild et al. (26). Thus, it is likely that CHWs with lower levels of education than those in DIALBEST can also improve T2D self-management.

Study Limitations

The main study design limitation is that because provider-level data were not collected, it is not possible to disentangle the CHW- and provider-driven pathways that may have led to the significant impact of DIALBEST on improved glycemic control. On the one hand, it is possible that the T2D self-management education provided by the CHWs led to this outcome. On the other hand, because CHWs were integrated as part of the healthcare management team, it is possible that healthcare providers adjusted the treatment of patients accordingly. We speculate that it is likely that both pathways played a role in the observed results, although this hypothesis would need to be tested through further research. Control group participants did not receive the CHW intervention but were also visited at home for data collection, including HbA1c assessment. This may explain why HbA1c also declined in this group, biasing findings toward the null hypothesis.

Conclusion

DIALBEST is a successfully implemented culturally and health literacy–appropriate intervention that took into account language preferences and socioeconomic circumstances while tailoring the intervention to individual participants. CHWs proved to be essential not only for delivering education on topics directly relevant to T2D self-management but also for providing care coordination and social support services to patients. Thus, CHWs filled huge vacuums of needs that are currently not being addressed by healthcare, public care, and social assistance systems surrounding the target community. The Affordable Care Act may represent an opportunity to formalize the role of CHWs as part of T2D healthcare management teams. CHW models should take into account needed service intensity of highly impoverished populations.

Clinical trial reg. no. NCT01299844, clinicaltrials.gov.

See accompanying articles, pp. 186, 189, 206, 213, 220, and 228.

Acknowledgments. The authors thank all the study participants and CHWs at the Hispanic Health Council, Hartford, CT.

Funding. DIALBEST was funded by the NIH Minority Health and Health Disparities Institute (grant number P20-MD-001765 to R.P.-E., principal investigator). R.P.-E. received funding support for this publication from the Yale Center for Clinical Investigation through Clinical and Translation Science Award grant UL1-TR-000142 from the National Center for Advancing Translational Scienceshttp://dx.doi.org/10.13039/100006108, a component of NIH.

The content is solely the responsibility of the authors and does not necessarily represent the official views of the National Center on Minority Health and Health Disparities or the National Institutes of Healthhttp://dx.doi.org/10.13039/100000002 (NIH).

Duality of Interest. No potential conflicts of interest relevant to this article were reported.

Author Contributions. R.P.-E. was the principal investigator for the study, contributed to the study concept and design, wrote the first draft of the manuscript and subsequent revisions, supervised the trial, and contributed to the data analyses. G.D. contributed to the study concept and design, conducted the trial, and reviewed drafts of the manuscript. J.C. contributed to the study concept and design and conduct of the study, was Hartford Hospital’s senior study coordinator, and reviewed drafts of the manuscript. M.L.F. contributed to the study design, was the study’s biomarkers senior scientist, and reviewed drafts of the manuscript. S.S.-P. was the Hispanic Health Council’s senior study coordinator; contributed to the study concept, conduct of the study, coordination of the trial, and data quality control; and reviewed drafts of the manuscript. S.V.-L. was a senior study coordinator responsible for fieldwork oversight, intervention fidelity, and data quality checks and reviewed drafts of the manuscript. G.K.-S. contributed to the statistical analyses, managed the study database, conducted laboratory analyses of biomarkers, and reviewed drafts of the manuscript. M.C. conducted laboratory analyses of biomarkers and reviewed drafts of the manuscript. F.M.S. contributed to the statistical analyses framework and reviewed drafts of the manuscript. D.D. was the study’s medical director, contributed to the intervention design, and reviewed drafts of the manuscript. R.P.-E. is the guarantor of this work and, as such, had full access to all the data in the study and takes responsibility for the integrity of the data and the accuracy of the data analysis.

Prior Presentation. Parts of this study were presented in abstract form at the Experimental Biology Annual Meeting, New Orleans, LA, 18–22 April 2009, and the 70th Scientific Sessions of the American Diabetes Association, Orlando, FL, 25–29 June 2010.

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Supplementary data