IDEAS home Printed from https://ideas.repec.org/p/ehl/lserod/120395.html

Strikes and gutters: biomarkers and anthropometric measures for predicting diagnosed diabetes mellitus in adults in low- and middle-income countries

Author

Listed:
  • Simmons, Sally Sonia

Abstract

Background: The management of diabetes necessitates the requirement of reliable health indices, specifically biomarkers and anthropometric measures, to detect the presence or absence of the disease. Nevertheless, limited robust empirical evidence exists regarding the optimal metrics for predicting diabetes in adults, particularly within low- and middle-income countries. This study investigates objective and subjective indices for screening diabetes in these countries. Methods: Data for this study was sourced from surveys conducted among adults (aged 18 years and above) in seventeen (17) countries. Self-reported diabetes status, fifty-four biomarkers, and twenty-six core and twenty-eight estimated anthropometric indices, including weight, waist circumference, body mass index, glycaemic triglycerides, and fasting blood glucose, were utilised to construct lasso regression models. Results: The study revealed variances in diabetes prediction outcomes across different countries. Central adiposity measures, fasting plasma glucose and glycaemic triglycerides demonstrated superior predictive capabilities for diabetes when compared to body mass index. Furthermore, fasting plasma or blood glucose, serving as a biomarker, emerged as the most accurate predictor of diabetes. Conclusions: These findings offer critical insights into both general and context-specific tools for diabetes screening. The study proposes that fasting plasma glucose and central adiposity indices should be considered as routine screening tools for diabetes, both in policy interventions and clinical practice. By identifying adults with or at higher risk of developing diabetes and implementing appropriate interventions, these screening tools possess the potential to mitigate diabetes-related complications in low- and middle-income countries.

Suggested Citation

  • Simmons, Sally Sonia, 2023. "Strikes and gutters: biomarkers and anthropometric measures for predicting diagnosed diabetes mellitus in adults in low- and middle-income countries," LSE Research Online Documents on Economics 120395, London School of Economics and Political Science, LSE Library.
  • Handle: RePEc:ehl:lserod:120395
    as

    Download full text from publisher

    File URL: https://researchonline.lse.ac.uk/id/eprint/120395/
    File Function: Open access version.
    Download Restriction: no
    ---><---

    References listed on IDEAS

    as
    1. Bishwajit Bhowmik & Tasnima Siddiquee & Anindita Mujumder & Faria Afsana & Tareen Ahmed & Ibrahimu A. Mdala & Nayla Cristina Do V. Moreira & Abul Kalam Azad Khan & Akhtar Hussain & Gerd Holmboe-Ottese, 2018. "Serum Lipid Profile and Its Association with Diabetes and Prediabetes in a Rural Bangladeshi Population," IJERPH, MDPI, vol. 15(9), pages 1-12, September.
    2. Jennifer Manne-Goehler & Pascal Geldsetzer & Kokou Agoudavi & Glennis Andall-Brereton & Krishna K Aryal & Brice Wilfried Bicaba & Pascal Bovet & Garry Brian & Maria Dorobantu & Gladwell Gathecha & Mon, 2019. "Health system performance for people with diabetes in 28 low- and middle-income countries: A cross-sectional study of nationally representative surveys," PLOS Medicine, Public Library of Science, vol. 16(3), pages 1-21, March.
    3. Sally Sonia Simmons & John Elvis Hagan Jr. & Thomas Schack, 2021. "The Influence of Anthropometric Indices and Intermediary Determinants of Hypertension in Bangladesh," IJERPH, MDPI, vol. 18(11), pages 1-12, May.
    4. Abdulrahman O. Musaiger & Abdelmonem S. Hassan & Omar Obeid, 2011. "The Paradox of Nutrition-Related Diseases in the Arab Countries: The Need for Action," IJERPH, MDPI, vol. 8(9), pages 1-35, September.
    5. Simon, Noah & Friedman, Jerome H. & Hastie, Trevor & Tibshirani, Rob, 2011. "Regularization Paths for Cox's Proportional Hazards Model via Coordinate Descent," Journal of Statistical Software, Foundation for Open Access Statistics, vol. 39(i05).
    6. repec:plo:pmed00:1001230 is not listed on IDEAS
    7. Autcha Araveeporn, 2021. "The Higher-Order of Adaptive Lasso and Elastic Net Methods for Classification on High Dimensional Data," Mathematics, MDPI, vol. 9(10), pages 1-14, May.
    Full references (including those not matched with items on IDEAS)

    Citations

    Citations are extracted by the CitEc Project, subscribe to its RSS feed for this item.
    as


    Cited by:

    1. Simmons, Sally Sonia & Hagan Jr, John Elvis & Schack, Thomas, 2025. "Generative data modelling for diverse populations in Africa: insights from South Africa," LSE Research Online Documents on Economics 129032, London School of Economics and Political Science, LSE Library.

    Most related items

    These are the items that most often cite the same works as this one and are cited by the same works as this one.
    1. Soave, David & Lawless, Jerald F., 2023. "Regularized regression for two phase failure time studies," Computational Statistics & Data Analysis, Elsevier, vol. 182(C).
    2. Hua Xin & Yuhlong Lio & Hsien-Ching Chen & Tzong-Ru Tsai, 2024. "Zero-Inflated Binary Classification Model with Elastic Net Regularization," Mathematics, MDPI, vol. 12(19), pages 1-17, September.
    3. Fritz, Manuela, 2021. "Temperature and non-communicable diseases: Evidence from Indonesia's primary health care system," Passauer Diskussionspapiere, Volkswirtschaftliche Reihe V-84-21, University of Passau, Faculty of Business and Economics.
    4. Zemin Zheng & Jie Zhang & Yang Li, 2022. "L 0 -Regularized Learning for High-Dimensional Additive Hazards Regression," INFORMS Journal on Computing, INFORMS, vol. 34(5), pages 2762-2775, September.
    5. Simon Bussy & Mokhtar Z. Alaya & Anne‐Sophie Jannot & Agathe Guilloux, 2022. "Binacox: automatic cut‐point detection in high‐dimensional Cox model with applications in genetics," Biometrics, The International Biometric Society, vol. 78(4), pages 1414-1426, December.
    6. Biagini, Francesca & Groll, Andreas & Widenmann, Jan, 2013. "Intensity-based premium evaluation for unemployment insurance products," Insurance: Mathematics and Economics, Elsevier, vol. 53(1), pages 302-316.
    7. Benedicte Sjo Tislevoll & Monica Hellesøy & Oda Helen Eck Fagerholt & Stein-Erik Gullaksen & Aashish Srivastava & Even Birkeland & Dimitrios Kleftogiannis & Pilar Ayuda-Durán & Laure Piechaczyk & Dagi, 2023. "Early response evaluation by single cell signaling profiling in acute myeloid leukemia," Nature Communications, Nature, vol. 14(1), pages 1-17, December.
    8. Felix Teufel & Pia Roddewig & Maja E. Marcus & Michaela Theilmann & Glennis Andall-Brereton & Krishna Aryal & Sina Azadnajafabad & Pascal Bovet & Maria Dorobantu & Farshad Farzadfar & Corine Houehanou, 2025. "National evidence on glucose-lowering medication use for diabetes from 62 low- and middle-income countries," Nature Communications, Nature, vol. 16(1), pages 1-8, December.
    9. Matthew F Dixon, 2017. "A High Frequency Trade Execution Model for Supervised Learning," Papers 1710.03870, arXiv.org, revised Dec 2017.
    10. Leandro C. Hermida & E. Michael Gertz & Eytan Ruppin, 2022. "RETRACTED ARTICLE: Predicting cancer prognosis and drug response from the tumor microbiome," Nature Communications, Nature, vol. 13(1), pages 1-15, December.
    11. Ong, Kanyin Liane & Stafford, Lauryn K. & McLaughlin, Susan A. & Boyko, Edward J. & Vollset, Stein Emil & Smith, Amanda E. & Dalton, Bronte E. & Duprey, Joe & Cruz, Jessica A. & Hagins, Hailey & Linds, 2023. "Global, regional, and national burden of diabetes from 1990 to 2021, with projections of prevalence to 2050: a systematic analysis for the Global Burden of Disease Study 2021," Open Access Publications from Kiel Institute for the World Economy 287733, Kiel Institute for the World Economy.
    12. Takumi Saegusa & Tianzhou Ma & Gang Li & Ying Qing Chen & Mei-Ling Ting Lee, 2020. "Variable Selection in Threshold Regression Model with Applications to HIV Drug Adherence Data," Statistics in Biosciences, Springer;International Chinese Statistical Association, vol. 12(3), pages 376-398, December.
    13. Jacob Bigio & Emily MacLean & Nathaly Aguilera Vasquez & Lavanya Huria & Mikashmi Kohli & Genevieve Gore & Emma Hannay & Madhukar Pai & Pierrick Adam, 2022. "Most common reasons for primary care visits in low- and middle-income countries: A systematic review," PLOS Global Public Health, Public Library of Science, vol. 2(5), pages 1-13, May.
    14. Zhixuan Fu & Shuangge Ma & Haiqun Lin & Chirag R. Parikh & Bingqing Zhou, 2017. "Penalized Variable Selection for Multi-center Competing Risks Data," Statistics in Biosciences, Springer;International Chinese Statistical Association, vol. 9(2), pages 379-405, December.
    15. Wenjie Wang & Chongliang Luo & Robert H. Aseltine & Fei Wang & Jun Yan & Kun Chen, 2025. "Survival Modeling of Suicide Risk with Rare and Uncertain Diagnoses," Statistics in Biosciences, Springer;International Chinese Statistical Association, vol. 17(1), pages 35-61, April.
    16. Manuela Fritz & Michael Grimm & Ingmar Weber & Elad Yom-Tov & Benedictus Praditya, 2022. "Uncover your risk! Using Facebook to increase personal risk awareness and screening of type 2 diabetes in Indonesia," Working Papers 221, Bavarian Graduate Program in Economics (BGPE).
    17. Seham Mansour Alyousef & Sami Abdulrahman Alhamidi, 2024. "Mental Health Nurses’ Clinical Experiences Among People with Age-Related Neurocognitive Impairment in Saudi Arabia: A Qualitative Study," SAGE Open, , vol. 14(4), pages 21582440241, November.
    18. Wenhua Liang & Jianhua Yao & Ailan Chen & Qingquan Lv & Mark Zanin & Jun Liu & SookSan Wong & Yimin Li & Jiatao Lu & Hengrui Liang & Guoqiang Chen & Haiyan Guo & Jun Guo & Rong Zhou & Limin Ou & Niyun, 2020. "Early triage of critically ill COVID-19 patients using deep learning," Nature Communications, Nature, vol. 11(1), pages 1-7, December.
    19. Tatyana Deryugina & Garth Heutel & Nolan H. Miller & David Molitor & Julian Reif, 2019. "The Mortality and Medical Costs of Air Pollution: Evidence from Changes in Wind Direction," American Economic Review, American Economic Association, vol. 109(12), pages 4178-4219, December.
    20. Andreas Groll & Gerhard Tutz, 2017. "Variable selection in discrete survival models including heterogeneity," Lifetime Data Analysis: An International Journal Devoted to Statistical Methods and Applications for Time-to-Event Data, Springer, vol. 23(2), pages 305-338, April.

    More about this item

    Keywords

    ;
    ;
    ;
    ;
    ;
    ;

    JEL classification:

    • I10 - Health, Education, and Welfare - - Health - - - General

    NEP fields

    This paper has been announced in the following NEP Reports:

    Statistics

    Access and download statistics

    Corrections

    All material on this site has been provided by the respective publishers and authors. You can help correct errors and omissions. When requesting a correction, please mention this item's handle: RePEc:ehl:lserod:120395. See general information about how to correct material in RePEc.

    If you have authored this item and are not yet registered with RePEc, we encourage you to do it here. This allows to link your profile to this item. It also allows you to accept potential citations to this item that we are uncertain about.

    If CitEc recognized a bibliographic reference but did not link an item in RePEc to it, you can help with this form .

    If you know of missing items citing this one, you can help us creating those links by adding the relevant references in the same way as above, for each refering item. If you are a registered author of this item, you may also want to check the "citations" tab in your RePEc Author Service profile, as there may be some citations waiting for confirmation.

    For technical questions regarding this item, or to correct its authors, title, abstract, bibliographic or download information, contact: LSERO Manager (email available below). General contact details of provider: https://edirc.repec.org/data/lsepsuk.html .

    Please note that corrections may take a couple of weeks to filter through the various RePEc services.

    IDEAS is a RePEc service. RePEc uses bibliographic data supplied by the respective publishers.