Community health worker intervention to prevent incident type 2 diabetes: A cluster randomized trial.

PLoS OneOct 30, 2026 (epub)

Mark D Schwartz, Jiyuan Hu, Scott E Sherman et al.

✦ AI-curated · Sources linked

In 30 seconds

This pragmatic cluster-randomized controlled trial tested whether a 12-month community health worker (CHW) program could prevent type 2 diabetes in adults aged 18–75 years with prediabetes receiving care at two New York City health systems. The intervention combined health action plans, motivational interviewing, education, and community referrals, compared with usual care. During follow-up of up to 6 months after the intervention, incident diabetes occurred in 5.9% of intervention patients versus 4.3% of controls (risk difference 1.6%; 95% CI -3.68% to 4.10%). The program did not improve measured metabolic outcomes and was associated with greater health care engagement.

Key findings

  • Incident diabetes occurred in 5.9% of intervention patients versus 4.3% of controls (risk difference 1.6%; 95% CI -3.68% to 4.10%).
  • No significant differences were observed in HbA1c, weight, blood pressure, or lipids.
  • Primary care encounters were more frequent with the intervention (77.6% vs 62.5%), as were emergency department encounters (35.0% vs 29.1%).

Why it matters

The trial provides pragmatic evidence that this CHW model increased health care engagement but did not demonstrate reduced diabetes incidence or improved metabolic measures over the study period. It highlights that greater contact with care does not necessarily translate into measurable short-term metabolic benefit, and that the effectiveness of CHW approaches may depend on intervention design and follow-up.

What to keep in mind

Follow-up for the primary outcome extended only up to 6 months after the 12-month intervention, limiting assessment of longer-term diabetes prevention.

Source

Published in PLoS One. This summary was written by xxcode from the publication's abstract and metadata. It is not peer reviewed and is not a substitute for the original article. For clinical decisions, review the original publication.

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AI-generated summaries may contain errors or omissions. Verify clinically important information with the original publication.

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