­
medigraphic.com
ISSN 1025-0255 (Electronic)

2022, Number 1

<< Back Next >>

AMC 2022; 26 (1)

Normal-weight phenotype in pregnant woman and newborn size

Ramírez-Mesa C, Sarasa-Muñoz NL, Artiles-Santana A, Fernández-Gregorio T, Álvarez-Guerra-González E, Cañizares-Luna O

Language: Spanish
References: 30
Page:
PDF size: 856.46 Kb.


ABSTRACT

Introduction: At the present time it exists, a parallel global epidemic to the pandemic of obesity; given by normal corporal weight and high levels of general adiposity. Their identification like phenotype of obesity allows predicting risks that can affect the development of the pregnancy.
Objective: To determine the anthropometric and metabolic features those distinguish to the obese normal weight pregnant and their relationship with the newborn size.
Methods: An observational analytic traverse study was conducted. Of a population of 526 seemingly healthy pregnant in optimal reproductive age, a sample of 358 metabolically healthy ones was obtained, that was stratified in 163 normal-weight healthy (HNW) and 195 obese normal-weight phenotype (ONW), in those anthropometric, metabolic and ultrasonographic variables was studied and the newborn condition. Theoretical, empiric and statistical methods were used.
Results: The phenotype ONW in pregnant showed superior securities of WC, Index WC/H, % BF, Sum of tricipital and subescapular skin folds and of the LAP. In them the subcutaneous and pre-peritoneal fats were superior and they had bigger frequency of big births for the gestational age.
Conclusions: The phenotype ONW in the pregnant is distinguished for anthropometric, metabolic and ultrasonographic features of central obesity and it is associated with the Big babies for the age gestacional at birth condition.


REFERENCES

  1. Guzmán JR, González Chávez A, Aschner P. Consenso Latinoamericano de la Asociación Latinoamericana de Diabetes (ALAD) Epidemiología, Diagnóstico, Control, Prevención y Tratamiento del Síndrome Metabólico en Adultos. ALAD [Internet]. 2010 [citado 13 Sep 2020];XVIII(1). Disponible en: Disponible en: https://www.revistaalad.com/pdfs/100125-44.pdf 1.

  2. Pastusiak K, Przysławski J. The criteria of the identification of metabolic obesity among people with normal body weight and their use in everyday practice. JMS [Internet]. 2018 Mar [citado 07 Ene 2021];87(1):34-9. Disponible en: Disponible en: https://jms.ump.edu.pl/index.php/JMS/article/view/259 2.

  3. Tatsumi Y, Nakao YM, Masuda I, Higashiyama A, Takegami M, Nishimura K, et al. Risk for metabolic diseases in normal weight individuals with visceral fat accumulation: a cross sectional study in Japan. BMJ Open [Internet]. 2017 [citado 02 Abr 2021];7(1):e013831. Disponible en: Disponible en: https://www.ncbi.nlm.nih.gov/pmc/articles/PMC5253636/ 3. .

  4. Acconcia MC, Caretta Q, Romeo F, Borzi M, Perrone MA, Sergi D, et al. Meta-analyses on intra-aortic balloon pump in cardiogenic shock complicating acute myocardial infarction may provide biased results. Eur Rev Med Pharmacol Sci [Internet]. 2018 [citado 02 Abr 2021];22(8):2405-14. Disponible en: Disponible en: https://www.europeanreview.org/article/14833 4.

  5. Intriago Rosado A, De la Torre Chávez J, Macías Guevara KB, Gómez Vergara S. Trastornos metabólicos que complican el embarazo. Dom Cien [Internet]. 2017 Jul [citado 13 Ene 2021]; 3(4): 462-75. Disponible en: Disponible en: https://dialnet.unirioja.es/descarga/articulo/6325516.pdf 5.

  6. Sam S. Differential effect of subcutaneous abdominal and visceral adipose tissue on cardiometabolic risk. Horm Mol Biol Clin Investig [Internet]. 2018 [citado 14 Mar 2021];33(1):[aprox. 3 p.]. Disponible en: Disponible en: https://www.degruyter.com/document/doi/10.1515/hmbci-2018-0014/html 6.

  7. Amato MC, Giordano C, Galia M, Criscimanna A, Vitabile S, Midiri M, et al. Visceral Adiposity Index. A reliable indicator of visceral function associated with cardiometabolic risk. Diabetes Care [Internet]. 2010 Abr [citado 22 Mar 2020];33(4):920-22. Disponible en: Disponible en: https://care.diabetesjournals.org/content/33/4/920.full-text.pdf 7.

  8. Du T, Yu X, Zhang J, Sun X. Lipid accumulation product and visceral adiposity index are effective markers for identifying the metabolically obese normal-weight phenotype. Acta Diabetol [Internet]. 2015 Oct [citado 04 Abr 2021];52(5):855-63. Disponible en: Disponible en: https://pubmed.ncbi.nlm.nih.gov/25690647/ 8. .

  9. Ahmadi F, Moukhah S, Hosseini R, Maghari A. Ultrasound Evaluation of Visceral Fat Thickness for Prediction of Metabolic Syndrome in the First Trimester of Pregnancy in a Sample of Non-obese Iranian Women. Oman Med J [Internet]. 2019 Jul [citado 17 Dic 2020];34(4):308-12. Disponible en: Disponible en: https://www.ncbi.nlm.nih.gov/pmc/articles/PMC6642717/ 9.

  10. Zhang C, Hediger ML, Albert PS, Grewal J, Sciscione A, Grobman WA, et al. Maternal obesity and longitudinal ultrasonographic measures of fetal growth: Findings from the NICHD fetal Growth Studies-Singletons. JAMA Pediatr [Internet]. 2018 Ene [citado 17 Dic 2020]; 172(1): 24-31. Disponible en: Disponible en: https://www.ncbi.nlm.nih.gov/pmc/articles/mid/NIHMS926715/ 10. .

  11. Carmenate Milián L, Moncada Chévez FA, Borjas Leiva EW. Manual de Medidas Antropométricas [Internet]. Costa Rica: SALTRA/IRED-UNA; 2014 [citado 24 Ene 2021]. Disponible en: Disponible en: https://repositorio.una.ac.cr/bitstream/handle/11056/8632/MANUAL%20ANTROPOMETRIA.pdf 11.

  12. Hernández Rodríguez J, Moncada Espinal OM, Arnold Domínguez Y. Utilidad del índice cintura/cadera en la detección del riesgo cardiometabólico en individuos sobrepesos y obesos. Rev cuba endocrinol [Internet]. 2018 May-Ago [citado 20 Sep 2019];29(2):[aprox. 3 p.]. Disponible en: Disponible en: http://scielo.sld.cu/scielo.php?pid=S1561-29532018000200007&script=sci_arttext&tlng=pt 12.

  13. Rodríguez Pérez MC, Cabrera de León A, Aguirre Jaime A, Domínguez Coello S, Brito Díaz B, Almeida González D, et al. El cociente perímetro abdominal/estatura como índice antropométrico de riesgo cardiovascular y de diabetes. Med clín [Internet]. 2010 Abr [citado 24 May 2021];134(9):386-91. Disponible en: Disponible en: https://pesquisa.bvsalud.org/portal/resource/pt/ibc-82750 13.

  14. Hernández Rodríguez J, Mendoza Choqueticlla J, Duchi Jimbo P. ĺndice de conicidad y su utilidad para detectar riesgo cardiovascular y metabólico. Rev cuba endocrinol [Internet]. 2017 Ene-Abr [citado 20 Sep 2021];28(1):[aprox. 5 p.]. Disponible en: Disponible en: http://scielo.sld.cu/scielo.php?script=sci_arttext&pid=S1561-29532017000100008 14.

  15. Dancause KN, Vilar M, DeHuff C, Wilson M, Soloway LE, Chan C, et al. Relationships between body size and percent body fat among Melanesians in Vanuatu. Asia Pac J Clin Nutr [Internet]. 2010 [citado 04 Jun 2021];19(3):425-31. Disponible en: Disponible en: https://apjcn.nhri.org.tw/server/APJCN/19/3/425.pdf 15.

  16. Kahn HS. The lipid accumulation product performs better than the body mass index forrecognizing cardiovascular risk: a population based comparison. BMC Cardiovasc Disord [Internet]. 2005 [citado 20 Ene 2020];5(26):[aprox. 5 p.]. Disponible en: Disponible en: https://bmccardiovascdisord.biomedcentral.com/articles/10.1186/1471-2261-5-26 16.

  17. Brahimaj A, Rivadeneira F, Muka T, Sijbrands EJG, Franco OH, Dehghan A, et al. Novel metabolic indices and incident type 2 diabetes among women and men: the Rotterdam Study. Diabetologia [Internet]. 2019 [citado 26 Nov 2021];62(9):1581-90. Disponible en: Disponible en: https://www.ncbi.nlm.nih.gov/pmc/articles/PMC6677703/ 17. .

  18. Bermúdez VJ, Salazar J, Añez R, Rivas Ríos JR, Chávez Castillo M, Torres W, et al. Optimal cutoff for visceral adiposity index in a Venezuelan population: Results from the Maracaibo City Metabolic Syndrome Prevalence Study. Rev argent endocrinol metab [Internet]. 2017 Dic [citado 26 Nov 2018];54(4):[aprox. 5 p.]. Disponible en: Disponible en: http://www.scielo.org.ar/scielo.php?pid=S1851-30342017000400004&script=sci_arttext&tlng=en 18.

  19. Nassr AA, Shazly SA, Trinidad MC, El-Nashar SA, Marroquin AM, Brost BC. Body fat index: a novel alternative to body mass index for prediction of gestational diabetes and hypertensive disorders in pregnancy. Eur J Obstet Gynecol Reprod Biol [Internet]. 2018 Sep [citado 26 Nov 2018];228:243-8. Disponible en: https://linkinghub.elsevier.com/retrieve/pii/S0301-2115(18)30328-219.

  20. Hernández Sandoval G, Rivera Valbuena J, Serrano Uribe R, Villalta Gómez D, Abbate León M, Acosta Núñez L, et al. Adiposidad visceral, patogenia y medición. Rev Venez Endocrinol Metab [Internet]. 2017 Jun [citado 26 Nov 2020];15(2):70-77. Disponible en: Disponible en: http://ve.scielo.org/scielo.php?script=sci_arttext&pid=S1690-31102017000200002 20.

  21. Miao M, Dai M, Zhang Y, Sun F, Guo X, Sun G. Influence of maternal overweight, obesity and gestational weight gain on the perinatal outcomes in women with gestational diabetes mellitus. Sci Rep [Internet]. 2017 Dic [citado 05 May 2020];7:305. Disponible en: https://pubmed.ncbi.nlm.nih.gov/28331199/21. .

  22. Domínguez-Reyes T, Quiroz-Vargas I, Salgado-Bernabé AB, Salgado-Goytia L, Muñoz-Valle JF, Parra-Rojas I. Las medidas antropométricas como indicadores predictivos de riesgo metabólico en una población mexicana. Nutr Hosp [Internet]. 2017 Ene-Feb [citado 05 May 2020];34(1):96-101. Disponible en: Disponible en: http://www.redalyc.org/articulo.oa?id=309249952015 22.

  23. Limas Pérez Y, Gómez Estacio L, Sarasa Muñoz N, Hernández Díaz D, Cañizares Luna O, Pérez Martínez D. Composición corporal grasa de las gestantes normopeso y sobrepeso. Morfovirtual [Internet]. 2016 [citado 01 Mar 2020]. Disponible en: Disponible en: http://www.morfovirtual2016.sld.cu/index.php/Morfovirtual/2016/paper/download/361/110 23.

  24. Madeira FB, Silva AA, Veloso HF, Goldani MZ, Kac G, Cardoso VC, et al. Normal weight obesity is associated with metabolic syndrome and insulin resistance in young adults from a middle-income country. PloS One [Internet]. 2013 [citado 20 Ene 2020]; 8(3): e60673. Disponible en: Disponible en: https://www.ncbi.nlm.nih.gov/pmc/articles/PMC3610876/pdf/pone.0060673.pdf 24.

  25. Orozco Muñoz C, Sarasa Muñoz N, Hernández Díaz D, Cañizares Luna O, Álvarez-Guerra González E, Artiles Santana A. Indicadores antropométricos para la caracterización de la adiposidad corporal en gestantes sanas al inicio del embarazo. CorSalud [Internet]. 2018 Oct-Dic [citado 09 Mar 2020];10(4):274-85. Disponible en: Disponible en: http://www.revcorsalud.sld.cu/index.php/cors/article/view/396/807 25.

  26. Sandhu JS, Esht V, Shenoy S, Gupta SK. Comparison between anthropometry, ultrasonography and under water weighing for prediction of body fat and metabolic syndrome in adult Indians. Ibnosina J Med Biomed Sci [Internet]. 2014 [citado 12 Feb 2021];6(2):91-100. Disponible en: Disponible en: https://www.ijmbs.org/article.asp?issn=1947-489X;year=2014;volume=6;issue=2;spage=91;epage=100;aulast=Sandhu;type=0 26.

  27. Motamed N, Razmjou S, Hemmasi G, Maadi M, Zamani F. Lipid accumulation product and metabolic syndrome: a population-based study in northern Iran, Amol. J Endocrinol Invest [Internet]. 2015 Ago [citado 30 Mar 2021];39(4):375-82. Disponible en: Disponible en: https://europepmc.org/article/med/26319991 27.

  28. Kennedy NJ, Peek MJ, Quinton AE, Lanzarone V, Martin A, Benzie R, Nanan R. Maternal abdominal subcutaneous fat thickness as a predictor for adverse pregnancy outcome: A longitudinal cohort study. BJOG [Internet]. 2016 Ene [citado 30 May 2020];123(2):225-32. Disponible en: Disponible en: https://pubmed.ncbi.nlm.nih.gov/26840907/ 28. .

  29. Lindberger E, Wikström AK, Bergman E, Eurenius K, Mulic‑Lutvica A, Poromaa IS, et al. Association of maternal central adiposity measured by ultrasound in early mid pregnancy with infant birth size. Scientific Reports [Internet]. 2020 [citado 30 May 2021]; 10: 19702. Disponible en: Disponible en: https://doi.org/10.1038/s41598-020-76741-8 29.

  30. Selovic A, Belci D. Influence of distribution of mother's abdominal body fat on first trimester fetal growth. J Matern Fetal Neonatal Med [Internet]. 2020 Feb [citado 30 May 2021];33(3):449-54. Disponible en: Disponible en: https://www.tandfonline.com/doi/abs/10.1080/14767058.2018.1494715?journalCode=ijmf20 30.




2020     |     www.medigraphic.com

    Este sitio utiliza cookies   Estoy de acuerdo