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Variability in haemoglobin concentration by measurement tool and blood source: an analysis from seven countries
  1. Aviva I Rappaport1,2,
  2. Crystal D Karakochuk3,
  3. Sonja Y Hess4,
  4. Ralph D Whitehead, Jr.5,
  5. Sorrel M L Namaste6,
  6. Omar Dary7,
  7. Megan E Parker8,
  8. Lynnette M Neufeld9,
  9. Leila M Larson10,
  10. Sam Newton11,
  11. Rita Wegmuller12,13,
  12. Denish Moorthy14
  1. 1 Strengthening Partnerships, Results, and Innovations in Nutrition Globally (SPRING), Arlington, Virginia, USA
  2. 2 School of Human Nutrition, McGill University, Sainte-Anne-de-Bellevue, Quebec, Canada
  3. 3 Food, Nutrition, and Health, University of British Columbia, Vancouver, British Columbia, Canada
  4. 4 Institute for Global Nutrition, Department of Nutrition, University of California Davis, Davis, California, USA
  5. 5 Division of Nutrition, Physical Activity, and Obesity, National Center for Chronic Disease Prevention and Health Promotion, Atlanta, Georgia, USA
  6. 6 The Demographic and Health Survey (DHS) Program, ICF, Rockville, Maryland, USA
  7. 7 US Agency for International Development (USAID), Bureau of Global Health, Office of Maternal Child Health and Nutrition, Washington, DC, USA
  8. 8 Maternal, Newborn, Child Health and Nutrition, PATH, Seattle, Washington, USA
  9. 9 Knowledge Leadership, Global Alliance for Improved Nutrition, Geneva, Switzerland
  10. 10 Department of Health Promotion, Education, and Behavior, University of South Carolina, Columbia, South Carolina, USA
  11. 11 School of Public Health, Kwame Nkrumah University of Science and Technology, Kumasi, Ghana
  12. 12 GroundWork, Fläsch, Switzerland
  13. 13 Medical Research Council Unit The Gambia, Keneba, The Gambia
  14. 14 USAID Advancing Nutrition, John Snow Inc. Research and Training Institute, Arlington, Virginia, USA
  1. Correspondence to Dr Denish Moorthy, USAID Advancing Nutrition, Arlington, Virginia 22202, USA; denish_moorthy{at}jsi.com

Abstract

Objective We explore factors such as the blood sampling site (capillary vs venous), the equipment (HemoCue vs automated haematology analyser) and the model of the HemoCue device (201+ vs 301) that may impact haemoglobin measurements in capillary and venous blood.

Methods Eleven studies were identified, and bias, concordance and measures of diagnostic performance were assessed within each study.

Findings Our analysis included 11 studies from seven countries (Cambodia, India, The Gambia, Ghana, Laos, Rwanda and USA). Samples came from children, men, non-pregnant women and pregnant women. Mean bias ranged from −8.7 to 2.5 g/L in Cambodian women, 6.2 g/L in Laotian children, 2.4 g/L in Ghanaian women, 0.8 g/L in Gambian children 6–23 months and 1.4 g/L in Rwandan children 6–59 months when comparing capillary blood on a HemoCue to venous blood on a haematology analyser. Bias was 8.3 g/L in Indian non-pregnant women and 2.6 g/L in Laotian children and women and 1.5 g/L in the US population when comparing capillary to venous blood using a HemoCue. For venous blood measured on the HemoCue compared with the automated haematology analyser, bias was 5.3 g/L in Gambian pregnant women 18–45 years and 11.3 g/L in Laotian children 6–59 months.

Conclusion Our analysis found large variability in haemoglobin concentration measured on capillary or venous blood and using HemoCue Hb 201+ or Hb 301 or automated haematology analyser. We cannot ascertain whether the variation is due to differences in the equipment, differences in capillary and venous blood, or factors affecting blood collection techniques.

  • diagnostic techniques and procedures
  • epidemiology
  • evidence-based practice
  • nutritional sciences

Data availability statement

Data are available upon reasonable request. Data provided for this pooled analysis were received from each co-author as deidentified participant data.

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Data availability statement

Data are available upon reasonable request. Data provided for this pooled analysis were received from each co-author as deidentified participant data.

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Footnotes

  • Handling editor Mary Frances McMullin.

  • Twitter @avivarapp

  • Contributors The authors’ responsibilities were as follows: AIR was responsible for data management, analysis, interpretation and manuscript draft preparation. DM contributed to study concept, planned analysis, assisted with data management. OD contributed to study concept and planned analysis. SMLN contributed to study concept, planned analysis and assisted with the data interpretation, and manuscript draft. CDK and SYH assisted with the data interpretation and manuscript draft preparation. All authors read, interpreted data, revised the manuscript and approved the final manuscript as submitted.

  • Funding This work was funded by USAID under the terms of the Cooperative Agreement (AIDOAA-A-11-00031, SPRING), managed by JSI Research & Training Institute, Inc. (JSI). The work was led by SPRING & International Micronutrient Malnutrition Prevention and Control (IMMPaCt) programme, CDC.

  • Disclaimer The findings and conclusions in this manuscript are those of the authors and do not necessarily represent the official position of the Centers for Disease Control and Prevention, USAID or the US Government.

  • Competing interests None declared.

  • Provenance and peer review Not commissioned; externally peer reviewed.