Diabetes Prevalence and Associated Risk Factors among Women in a Rural District of Nepal Using HbA1c as a Diagnostic Tool: A Population-Based Study

Int J Environ Res Public Health. 2022 Jun 8;19(12):7011. doi: 10.3390/ijerph19127011.

Abstract

Given the scarcity of data on diabetes prevalence and associated risk factors among women in rural Nepal, we aimed to examine this, using glycated hemoglobin (HbA1c) as a diagnostic tool. A cross-sectional survey addressing reproductive health and non-communicable diseases was conducted in 2012-2013 among non-pregnant, married women in Bolde, a rural district of Nepal. HbA1c ≥ 6.5% (48 mmol/mol) was used as diagnostic criterion for diabetes, a cut-off of 7.0% (53 mmol/mol) was used to increase the specificity. HbA1c was measured in 757 women (17-86 years). The prevalence of diabetes and prediabetes was 13.5% and 38.5%, respectively. When using 7.0% as a cut-off, the prevalence of diabetes was 5.8%. Aging, intake of instant noodles and milk and vegetarian food (ns) were associated with increased risk for diabetes. Waist circumference was higher among women with diabetes, although not significant. The women were uneducated (87.6%), and only 12% had heard about diabetes. In conclusion, we observed a higher prevalence of diabetes and prediabetes than anticipated among rural, Nepalese women. The increased risk was mainly attributed to dietary factors. In contrast to most previous studies in Nepal, we used HbA1c as diagnostic criterion.

Keywords: HbA1c; Nepal; diabetes; instant noodles; prevalence; risk factors; rural; women.

Publication types

  • Research Support, Non-U.S. Gov't

MeSH terms

  • Blood Glucose
  • Cross-Sectional Studies
  • Diabetes Mellitus* / diagnosis
  • Diabetes Mellitus* / epidemiology
  • Female
  • Glycated Hemoglobin / analysis
  • Humans
  • Nepal / epidemiology
  • Prediabetic State* / diagnosis
  • Prediabetic State* / epidemiology
  • Prevalence
  • Risk Factors

Substances

  • Blood Glucose
  • Glycated Hemoglobin A

Grants and funding

This research was funded by a global research grant from the Norwegian University of Science and Technology (NTNU), Norway, grant number 81771136.