Inverse relationship between altitude and cardiometabolic risk in the Peruvian population: results of a population-based survey and the importance of waist-to-height ratio as an indicator of cardiometabolic risk

Authors

  • Frank Zela-Coila Universidad Nacional de San Agustín de Arequipa, Arequipa, Perú; Sociedad Científica de Estudiantes de Medicina Agustinos (SOCIEMA), Arequipa, Perú
  • Greysi Cerron-Daga Universidad Nacional Daniel Alcides Carrión, Pasco, Perú; Sociedad Científica de Estudiantes de Medicina Daniel Alcides Carrión (SOCIEMDAC), Pasco, Perú
  • Thalia Porta-Quinto Universidad Nacional del Centro del Perú, Huancayo, Junín, Perú; Sociedad Científica de Estudiantes de Medicina del Centro (SOCIEMC), Huancayo, Perú

DOI:

https://doi.org/10.35434/rcmhnaaa.2022.154.1730

Keywords:

Waist-Height Ratio, Altitude, Cardiometabolic Risk Factors, Peru

Abstract

Presentation: This article presents our critical appraisal of an observational study published in the International Journal of Environmental Research and Public Health in 2022.

Conclusions of the Study: An inverse association was identified between living at higher altitudes and the level of cardiometabolic risk in the Peruvian adult population. However, the prevalence of cardiometabolic risk in the different altitude categories evaluated remains above 82% (80.9 - 84.6), which represents a large proportion of the population at risk at every altitude.

Critical comment: The study is relevant because of the use of the waist-height ratio, considered an anthropometric indicator with greater precision for estimating cardiometabolic risk, being a study with a low risk of bias, and having national representativity. In addition, it is important because the waist-height ratio is inexpensive and easy to use. It is also superior to BMI and ideal for application in Peru. In addition, the general conclusion of the study is valid; however, the lack of evaluation of temporality due to the same characteristic of the study (cross-sectional study) and the residual bias that it has by not evaluating some variables, makes it necessary to carry out a longitudinal study to be able to support the results of the study. The present critical review finds internal validity in the results of the study, but at the moment they would not be applicable to generalize to the entire population due to the residual bias.

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Author Biographies

Frank Zela-Coila, Universidad Nacional de San Agustín de Arequipa, Arequipa, Perú; Sociedad Científica de Estudiantes de Medicina Agustinos (SOCIEMA), Arequipa, Perú

1. Estudiante de Medicina

Greysi Cerron-Daga, Universidad Nacional Daniel Alcides Carrión, Pasco, Perú; Sociedad Científica de Estudiantes de Medicina Daniel Alcides Carrión (SOCIEMDAC), Pasco, Perú

1. Estudiante de Medicina

Thalia Porta-Quinto, Universidad Nacional del Centro del Perú, Huancayo, Junín, Perú; Sociedad Científica de Estudiantes de Medicina del Centro (SOCIEMC), Huancayo, Perú

1.Estudiante de Medicina

References

Hernández-Vásquez A, Azañedo D. The Association between Altitude and Waist–Height Ratio in Peruvian Adults: A Cross-Sectional Data Analysis of a Population-Based Survey. Int J Environ Res Public Health. enero de 2022;19(18):11494 [citado 19 de octubre de 2022]. DOI: 10.3390/ijerph191811494

Documentos metodológicos ENDES [citado 19 de octubre de 2022]. Disponible en: https://proyectos.inei.gob.pe/endes/documentos.asp

Vandenbroucke JP, Von Elm E, Altman DG, Gøtzsche PC, Mulrow CD, Pocock SJ, et al. Mejorar la comunicación de estudios observacionales en epidemiología (STROBE): explicación y elaboración. Gac Sanit. 2009 [citado 19 de octubre de 2022]. DOI: 10.1016/j.gaceta.2008.12.001

Modesti PA, Reboldi G, Cappuccio FP, Agyemang C, Remuzzi G, Rapi S, et al. Newcastle - Ottawa quality assessment scale (adapted for cross sectional studies) - Supporting Information of Panethnic Differences in Blood Pressure in Europe: A Systematic Review and Meta-Analysis. PLOS ONE. 2016 [citado 19 de octubre de 2022]. DOI: 10.1371/journal.pone.0147601

Cvetković Vega A, Maguiña JL, Soto A, Lama-Valdivia J, López LEC. Cross-sectional studies. Rev Fac Med Humana 2021 [citado 19 de octubre de 2022]. Disponible en: https://inicib.urp.edu.pe/rfmh/vol21/iss1/22

Munares-García O, Gómez-Guizado G, Barboza-Del Carpio J, Sánchez-Abanto J. Limitaciones del análisis secundario de bases de datos - réplica. Rev Peru Med Exp Salud Pública. 2013 [citado 19 de octubre de 2022]. DOI. 10.1590/S1726-46342013000100034

Instituto Nacional de Estadística e Informática. Encuesta Demográfica y de Salud Familiar - ENDES | Informes [citado 4 de octubre de 2022]. Disponible en: https://proyectos.inei.gob.pe/endes/

Instituto Nacional de Estadística e Informática. Informe ENDES 2021. [citado 4 de octubre de 2022]. Disponible en: https://proyectos.inei.gob.pe/endes/2021/INFORME_PRINCIPAL/INFORME_PRINCIPAL_ENDES_2021.pdf

Miranda JJ, Barrientos-Gutiérrez T, Corvalan C, Hyder AA, Lazo-Porras M, Oni T, et al. Understanding the rise of cardiometabolic diseases in low- and middle-income countries. Nat Med. 2019 [citado 4 de octubre de 2022]. DOI. 10.1038/s41591-019-0644-7

Dünnwald T, Gatterer H, Faulhaber M, Arvandi M, Schobersberger W. Body Composition and Body Weight Changes at Different Altitude Levels: A Systematic Review and Meta-Analysis. Front Physiol. 2019 [citado 4 de octubre de 2022]. DOI: 10.3389/fphys.2019.00430

Ashwell M, Gunn P, Gibson S. Waist-to-height ratio is a better screening tool than waist circumference and BMI for adult cardiometabolic risk factors: systematic review and meta-analysis: Waist-to-height ratio as a screening tool. Obes Rev. 2012 [citado 4 de octubre de 2022]. DOI: 10.1111/j.1467-789X.2011.00952.x

Liu J, Tse LA, Liu Z, Rangarajan S, Hu B, Yin L, et al. Predictive Values of Anthropometric Measurements for Cardiometabolic Risk Factors and Cardiovascular Diseases Among 44 048 Chinese. J Am Heart Assoc. 2019 [citado 4 de octubre de 2022]. DOI: 10.1161/JAHA.118.010870

Mehta SK. Waist Circumference to Height Ratio in Children and Adolescents. Clin Pediatr (Phila). 2015 [citado 4 de octubre de 2022]. DOI: 10.1177/0009922814557784

Yoo EG. Waist-to-height ratio as a screening tool for obesity and cardiometabolic risk. Korean J Pediatr. 2016 [citado 4 de octubre de 2022]. DOI: 10.3345/kjp.2016.59.11.425

Schneider HJ, Glaesmer H, Klotsche J, Böhler S, Lehnert H, Zeiher AM, et al. Accuracy of anthropometric indicators of obesity to predict cardiovascular risk. J Clin Endocrinol Metab. 2007 [citado 4 de octubre de 2022]. DOI: 10.1210/jc.2006-0254

1. Asgari S, Luo Y, Akbari A, Belbin GM, Li X, Harris DN, et al. A positively selected FBN1 missense variant reduces height in Peruvian individuals. Nature. 2020 [citado 4 de octubre de 2022]. DOI: 10.1038/s41586-020-2302-0

Lo K, Wong M, Khalechelvam P, Tam W. Waist-to-height ratio, body mass index and waist circumference for screening paediatric cardio-metabolic risk factors: a meta-analysis. Obes Rev. 2016 [citado 4 de octubre de 2022]. DOI: 10.1111/obr.12456

Pajuelo-Ramírez J, Torres-Aparcana H, Agüero-Zamora R, Quispe AM. Altitude and its inverse association with abdominal obesity in an Andean country: a cross-sectional study. F1000Research. 2019 [citado 4 de octubre de 2022]. DOI: 10.12688/f1000research.20707.2

Vontobel J. [Heart Patients and Exposure to Altitude]. Praxis. 2021 [citado 4 de octubre de 2022]. DOI: 10.1024/1661-8157/a003649

Published

2023-02-02

How to Cite

1.
Zela-Coila F, Cerron-Daga G, Porta-Quinto T. Inverse relationship between altitude and cardiometabolic risk in the Peruvian population: results of a population-based survey and the importance of waist-to-height ratio as an indicator of cardiometabolic risk. Rev. Cuerpo Med. HNAAA [Internet]. 2023 Feb. 2 [cited 2024 May 18];15(4):644-8. Available from: https://cmhnaaa.org.pe/ojs/index.php/rcmhnaaa/article/view/1730

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