title: Using handgrip strength to screen for diabetes in developing countries.
abstract: Lack of access to healthcare in the developing world has created a need for locally-based primary and pre-primary healthcare systems. Many regions of the world have adopted Community Health Worker (CHW) programmes, but volunteers in these programmes lack the tools and resources to screen for disease. Because of its simplicity of operation, handgrip strength (HGS) measurements have the potential to be an affordable and effective screening tool for conditions that cause muscle weakness in this context. In the study described in this report, translators were used to collect data on age, gender, height, weight, blood pressure, HGS and key demographic data. HGS was significantly lower for diabetics than patients without diabetes. A simple binary logistic model was created that used HGS, age, blood pressure and BMI to predict a patient's probability of having diabetes. This study develops a predictive model for diabetes using HGS and other basic health measurements and shows that HGS-based screening is a viable method of early detection of diabetes.
authors.affiliation: a The Pennsylvania State University, Humanitarian Engineering and Social Entrepreneurship (HESE) Program, 213U Hammond Building, University Park , PA 16802 , USA ;|b The Pennsylvania State University, Department of Biomedical Engineering, University Park , PA 16802 , USA.
authors.forename: Molly
authors.initials: M
authors.lastname: Eckman
authors.affiliation: a The Pennsylvania State University, Humanitarian Engineering and Social Entrepreneurship (HESE) Program, 213U Hammond Building, University Park , PA 16802 , USA ;|b The Pennsylvania State University, Department of Biomedical Engineering, University Park , PA 16802 , USA.
authors.forename: Christopher
authors.initials: C
authors.lastname: Gigliotti
authors.affiliation: a The Pennsylvania State University, Humanitarian Engineering and Social Entrepreneurship (HESE) Program, 213U Hammond Building, University Park , PA 16802 , USA ;|b The Pennsylvania State University, Department of Biomedical Engineering, University Park , PA 16802 , USA.
authors.forename: Staci
authors.initials: S
authors.lastname: Sutermaster
authors.affiliation: b The Pennsylvania State University, Department of Biomedical Engineering, University Park , PA 16802 , USA.
authors.forename: Peter J
authors.initials: PJ
authors.lastname: Butler
authors.affiliation: a The Pennsylvania State University, Humanitarian Engineering and Social Entrepreneurship (HESE) Program, 213U Hammond Building, University Park , PA 16802 , USA ;
authors.forename: Khanjan
authors.initials: K
authors.lastname: Mehta
mesh_terms: D000368:Aged; D000465:Algorithms; D001794:Blood Pressure; D001827:Body Height; D001835:Body Weight; D003198:Computer Simulation; D003906:Developing Countries / Q000706:statistics & numerical data*; D003920:Diabetes Mellitus / Q000175:diagnosis* / Q000453:epidemiology; D003936:Diagnosis, Computer-Assisted / Q000379:methods*; D005260:Female; D018737:Hand Strength; D006801:Humans; D007630:Kenya / Q000453:epidemiology; D008297:Male; D008403:Mass Screening / Q000379:methods* / Q000706:statistics & numerical data; D008875:Middle Aged; D015233:Models, Statistical; D053581:Muscle Strength Dynamometer / Q000706:statistics & numerical data*; D010363:Pattern Recognition, Automated / Q000379:methods; D010808:Physical Examination / Q000379:methods / Q000706:statistics & numerical data; D015203:Reproducibility of Results; D012680:Sensitivity and Specificity
keywords: Handgrip strength; developing world; diabetes; non-communicable disease