Anthropometric Indices in Detecting Metabolic Syndrome for Low-Resource Settings

Abstract

The aim of this literature review was to find out how metabolic syndrome could be screened in low-resource settings (LRS) in a resource-effective manner. The review seeks to identify existing anthropometric indices and find out which anthropometric indices are most effective, accessible, and being up to be implemented for detecting metabolic syndrome (MetS) in populations with limited access to advanced diagnostic tools and healthcare infrastructure. In addition, this study aims to explore the potential for these indices to serve as cost-effective alternatives for more complex metabolic assessments, contributing to early detection, prevention, and management strategies of MetS in LRSs. Throughout the review process, the special focus is on assessing whether there are existing anthropometric indices or indices combinations applicable for community health workers (CHWs) to be used in community-based interventions. According to research, early detection of risk factors for severe health conditions benefits not only individuals but communities as whole and the whole system around. As the prevalence of metabolic syndrome and related non-communicable diseases is increasing worldwide, LRSs not being an exception, an effective and efficient means are needed to tackle the disease burden on people and healthcare systems. Hence, utilizing the evidence obtained from the literature I intended to appraise whether anthropometric tools could answer to the call for a resource effective, agilely applicable tool to detect hidden conditions that could - when detected at their early stage – be prevented, observed and treated more easily before their challenging manifestation. The results of the literature review were promising regarding the implementability of the anthropometric methods for screening metabolic syndrome in community-based LRSs. Both the test performance of various anthropometric indices as well as the findings on the contextual usability are encouraging. However, the test performance being quite varying in different contexts and between different populations, more studies are needed to provide strong evidence and insight into the true feasibility of anthropometric methods in screening MetS.