Determining adult type 2 diabetes-related health care needs in an indigenous population from rural Guatemala: a...

In Guatemala, diabetes is an emerging public health concern. Guatemala has one of the largest indigenous populations in Latin America, and this population frequently does not access the formal health care system. Therefore, knowledge about the emergence of diabetes in this population is limited.

Interview participants (n=23) were recruited from a convenience sample of indigenous adults with type 2 diabetes at one rural diabetes clinic in Guatemala. A structured interview was used to assess knowledge about diabetes and its complications; access to diabetes-related health care and treatment; dietary and lifestyle changes; and family and social supports for individuals living with diabetes. Interviews were supplemented with two group interviews with community leaders and health care providers. Thematic analysis was used to produce insights into diabetes knowledge, attitudes, and practices. In addition, a chart review of the clinic's electronic medical record identified all adult patients (n=80) presenting in one calendar year for a first-time diabetic consultation. Sociodemographic and clinical variables were extracted and summarized from these records.

Salient demographic factors in both the structured interview and chart review samples included low educational levels and high indigenous language preference. In the interview sample, major gaps in biomedical knowledge about diabetes included understanding the causes, chronicity, and long-term end-organ complications of diabetes. Medication costs, medical pluralism, and limited social supports for dietary and lifestyles changes were major practical barriers to disease management. Quantitative data from medical records review revealed high rates of poor glycemic control, overweight and obesity, and medication prescription.

This study provides a preliminary sketch of type 2 diabetes in an indigenous Guatemalan population. Combined qualitative and quantitative data point towards particular needs for implementation and future research, including the need to address gaps in diabetes knowledge, to improve social support systems, and to address the cost barriers associated with disease treatment.