1. bookVolume 75 (2021): Issue 3 (June 2021)
Journal Details
License
Format
Journal
First Published
14 Sep 2008
Publication timeframe
6 times per year
Languages
English
access type Open Access

Comparative Analysis of Anthropometric Parameters and Body Composition of Patients with Breast Cancer and Healthy Women in the Postmenopausal Period

Published Online: 22 Jul 2021
Page range: 234 - 237
Received: 12 Jan 2021
Accepted: 24 Feb 2021
Journal Details
License
Format
Journal
First Published
14 Sep 2008
Publication timeframe
6 times per year
Languages
English
Abstract

According to a statistical review (2018) in Latvia, there are more than one thousand women (n = 1266) with the diagnosis of breast cancer. Assessments of anthropometrical parameters were made according to the World Health Organisation recommendations for morbidity risk analysis. The aim of the study was to determine the differences and changes of anthropometric parameters and indices in a control group and in a clinical group (initial oncological diagnosis without treatment intervention). We examined women in their postmenopausal period. The control group included apparently healthy women (n = 181) and the clinical group included women (n = 44) with initial oncological diagnosis (breast cancer 1st and 2nd stage). In order to assess body anthropometric characteristics we used the body mass index (BMI), waist circumference, waist/height ratio and skin fold thickness measurement. The study results were assessed using statistical analyses in the IBM SPSS Statistics for Windows, Version 22.0 software: Shapiro–Wilk and Mann–Whitney tests with a two-tailed p-value < 0.05). The analysis of statistical data showed that, despite the low number of patients in the clinical group, we found a significantly lower waist-to-hip ratio, skinfold thickness above m. biceps brachii, skinfold thickness above m. triceps brachii, and subscapular and suprailiac skin fold thickness in this group.

Keywords

Anonymous (2016). World Health Statistics. World Health Organization. https://www.who.int/gho/publications/world_health_statistics/2016/EN_WHS2016_TOC.pdf (accessed 10.05.2021). Search in Google Scholar

Brown, J. C., Cespesdes, F. E. M., Caan, B. J. (2019). The evolution of body composition in oncology – epidemiology, clinical trials, and the future of patient care: Facts and numbers. J. Cachexia Sarcopenia Muscle, 1, 1200–1208. Search in Google Scholar

Cederholm, T., Jensen, G. L., Correia, M. I. T. D., Gonzalez, M. C., Fukushima, R., Higashiguchi, T., Compher, C. (2019). GLIM criteria for the diagnosis of malnutrition: A consensus report from the global clinical nutrition community. J. Cachexia Sarcopenia Muscle, 10 (1), 207–217. Search in Google Scholar

Chang, Y., Guo, X., Chen, Y., Guo, L., Li, Z., Yu, S., Yang, H., Sun, Y. (2015). A body shape index and body roundness index: Two new body indices to identify diabetes mellitus among rural populations in northeast China. BioMed Central Publ. Health, 15 (1), 794. Search in Google Scholar

Cruz-Jentoft, A. J., Bahat, G., Bauer, J., Boirie, Y., Bruyére, O., Cederholm, T., Schols, J. (2019). Sarcopenia: Revised European consensus on definition and diagnosis. Age Ageing, 48 (1), 16–31. Search in Google Scholar

de Sousa, N. C., MarquesI, F. R. D. M., Pires, G. A. R., da Cruz Scardoelli, I. M. G., da Silva Rêgo, A., Radovanovic I. C. A. T. (2020). Conicity index in people with hypertension followed in the Brazil’s Family Health Strategy. Revista Brasileira de Enfermagem, 73 (5), e20190484. Search in Google Scholar

Dhana, K., Koolhas, C., Schoufour, J., Rivadeneira, F., Hofman, A., Kavousi, M., (2016). Association of anthropometric measures with fat and fat-free mass in the elderly: The Rotterdam study. Maturitas, 88, 96–100. Search in Google Scholar

Eickemberg, M., Amorim, L. D. A. F., Chagas de Almeida, M. C., Pitanga, F. J. G., Lećo de Aquino, E. M., Mendes da Fonseca, M. J., Matos, S. M. A. (2020). Abdominal obesity in ELSA-Brasil (Brazil’s Longitudinal Study of Adult Health): Construction of a latent gold standard and evaluation of the accuracy of diagnostic indicators. Ciência Saúde Coletiva, 25 (8), 2985–2998. Search in Google Scholar

Ehrampoush, E., Arasteh, P., Homayounfara, R., Cheraghpour, M., Alipour, M., Mehdi, M., Hadibarhaghtalab, M., Davoodi, S. H., Askari A., Razaz, J. M. (2017). New anthropometric indices or old ones: Which is the better predictor of body fat? Diabetes Metab. Syndr. Clin. Res. Rev., 11 (4), 257–263. Search in Google Scholar

Ferlay, J., Steliarova-Foucher, E., Lortet-Tieulent, J., Rosso, S., Coebergh, J. W., Comber, H., Forman, D., Bray, F. (2013). Cancer incidence and mortality patterns in Europe: Estimates for 40 countries in 2012. Eur. J. Cancer, 49 (6), 1374–1403. Search in Google Scholar

Godinho-Mota, J. C. M., Gonçalves L.V., Soares L. R., Mota, J. F., Martins, K. A., Freitas-Junior, I., Freitas-Junior, R. (2018). Abdominal adiposity and physical inactivity are positively associated with breast cancer: A case-control study. BioMed Res. Int., 2018, 4783710. Search in Google Scholar

He, S., Chen, X. (2013). Could the new body shape index predict the new onset of diabetes mellitus in the Chinese population? PLoS One, 8 (1), e50573. Search in Google Scholar

Hilmi, M., Jouinot, A., Burns, R., Pigneur, F., Mounier, R., Gondin, J, Goldwasser, F. (2019). Body composition and sarcopenia: The next-generation of personalized oncology and pharmacology? Pharmacol. Ther., 196, 135–159. Search in Google Scholar

Krakauer, N. Y., Krakauer, J. C. (2012). A new body shape index predicts mortality hazard independently of body mass index. PLoS One, 7 (7), e39504. Search in Google Scholar

Krakauer, N. Y., Krakauer, J. C. (2014). Expansion of waist circumference in medical literature: Potential clinical application of a body shape index. J. Obes. Weight Loss Ther., 4, 216. Search in Google Scholar

Majeed, W., Aslam, B., Javed, I. (2014). Breast cancer: Major risk factors and recent developments in treatment. Asian Pac. J. Cancer Prev., 15 (8), 3353–3358. Search in Google Scholar

Matthews, S. B., Thompson, H. J. (2016). The obesity-breast cancer conundrum: An analysis of the issues. Int. J. Mol. Sci., 17 (6), 989. Search in Google Scholar

Quaye, L., Owiredu, W. K. B. A., Amidu, N., Dapare, P. P. M., Adams, Y. (2019). Comparative abilities of Body Mass Index, Waist Circumference, Abdominal Volume Index, Body Adiposity Index, and Conicity Index as predictive screening tools for metabolic syndrome among apparently healthy Ghanaian adults. J. Obesity, 2019, 8143179. Search in Google Scholar

Roriz, A. K. C., Passos, L. C. S., de Oliveira, C. C., Eickemberg, M., Moreira, P. D., Ramos, L. B. (2017). Anthropometric clinical indicators in the assessment of visceral obesity: An update. Nutricion Clinica y Dietetica Hospitalaria, 36 (2), 168–179. Search in Google Scholar

Shah, N. R., Braverman, E. R. (2012). Measuring adiposity in patients: The utility of body mass index (BMI), percent body fat, and leptin. PLoS One, 7 (4), e33308. Search in Google Scholar

Thomas, D. M., Bredlau, C., Bosy-Westphal, A. (2013). Relationships between body roundness with body fat and visceral adipose tissue emerging from a new geometrical model. Obesity, 21 (11), 2264–2271. Search in Google Scholar

Vander-Walde, A., Hurria, A. (2012). Early breast cancer in the older woman. Clinics Geriat. Med., 28 (1), 73–91. Search in Google Scholar

Zaccagni, L., Barbieri D., Gualdi-Russo, E. (2014). Body composition and physical activity in Italian university students. J. Transl. Med., 12 (1), 120. Search in Google Scholar

Recommended articles from Trend MD

Plan your remote conference with Sciendo