medigraphic.com
SPANISH

Archivos de Medicina

Archivos de Medicina (Manizales)
  • Contents
  • View Archive
  • Information
    • General Information        
    • Directory
  • Publish
    • Instructions for authors        
  • medigraphic.com
    • Home
    • Journals index            
    • Register / Login
  • Mi perfil

2022, Number 1

<< Back Next >>

Arch Med 2022; 22 (1)

Evaluation of the effect of loss to followup in a cohort of children under 1 year of age in Huancavelica and Loreto, Peru

Gonzales AE, Morales CB, Quispe GC, Santos AG, Hinojosa MP, Solis SG, Bautista OW, Aparco JP
Full text How to cite this article

Language: Spanish
References: 31
Page: 133-144
PDF size: 502.39 Kb.


Key words:

cohort studies, children, malnutrition, food and nutrition security, nutrition.

ABSTRACT

Objective: to evaluate the effect of losses during follow-up of the study “Factors associated with stunting in a cohort of children from public health facilities in the Huancavelica and Loreto regions.” Materials and methods: the cohort of children was developed to identify the causes of childhood stunting in Huancavelica and Loreto, children were evaluated at 3, 6, 9 and 12 months of age. Children born in health facilities in both regions were enrolled. Information on sociodemographic aspects, food safety, food consumption, anthropometry and hemoglobin was collected at each evaluation stage. A multiple linear regression panel model was used, with the Z-score for height-for-age of the participants as the dependent variable and loss to follow-up as the independent variable. Results: 1508 children were enrolled (748 in Huancavelica and 760 in Loreto), the losses to follow-up represented 39.7% and 26.4% in Huancavelica and Loreto respectively. During enrollment there was a higher prevalence of stunting in Huancavelica (11.8%) than in Loreto (7.7%) (P value = 0.,001). Follow-up losses did not affect HAZ (p value = 0.461 CI: -0.18; 0.08). Conclusions: the cohort study had losses to follow-up within the estimates. Follow-up losses did not affect HAZ, the indicator related.


REFERENCES

  1. Wells JC, Sawaya AL, Wibaek R, Mwangome M, Poullas MS, Yajnik CS, et al. The double burden of malnutrition:aetiological pathways and consequences for health. Lancet. 2020; 395(10217):75–88.doi:10.1016/S0140-6736(19)32472-9

  2. Victora CG, Christian P, Vidaletti LP, Gatica-Domínguez G, Menon P, Black RE. Revisiting maternal and childundernutrition in low-income and middle-income countries: variable progress towards an unfinishedagenda. Lancet. 2021; 397(10282):1388–1399. doi:10.1016/S0140-6736(21)00394-9

  3. Alam MA, Richard SA, Fahim SM, Mahfuz M, Nahar B, Das S, et al. Impact of early-onset persistent stuntingon cognitive development at 5 years of age: Results from a multi-country cohort study. PLoS One. 2020;15(1):e0227839. doi:10.1371/journal.pone.0227839

  4. Heidkamp RA, Piwoz E, Gillespie S, Keats EC, D’Alimonte MR, Menon P, et al. Mobilising evidence, data, andresources to achieve global maternal and child undernutrition targets and the Sustainable DevelopmentGoals: an agenda for action. Lancet. 2021; 397(10282):1400–1418. doi:10.1016/s0140-6736(21)00568-7

  5. Argaw A, Hanley-Cook G, De Cock N, Kolsteren P, Huybregts L, Lachat C. Drivers of under-five stunting trendin 14 low-and middle-income countries since the turn of the millennium: A multilevel pooled analysis of50 demographic and health surveys. Nutrients. 2019; 11(10). doi:10.3390/nu11102485

  6. Dearden KA, Schott W, Crookston BT, Humphries DL, Penny ME, Behrman JR. Children with access toimproved sanitation but not improved water are at lower risk of stunting compared to children withoutaccess: a cohort study in Ethiopia, India, Peru, and Vietnam. BMC Public Health. 2017; 17.doi:10.1186/s12889-017-4033-1

  7. Kwami CS, Godfrey S, Gavilan H, Lakhanpaul M, Parikh P. Water, Sanitation, and Hygiene: Linkages withStunting in Rural Ethiopia. Int J Environ Res Public Health. 2019; 16(20). doi:10.3390/ijerph16203793

  8. Keats EC, Das JK, Salam RA, Lassi ZS, Imdad A, Black RE, et al. Effective interventions to address maternaland child malnutrition: an update of the evidence. Lancet Child Adolesc Health. 2021; 5(5):367–384.doi:10.1016/s2352-4642(20)30274-1

  9. UNICEF, WHO, The Work Bank. Levels and trends in child malnutrition: key findings of the 2019 Editionof the Joint Child Malnutrition Estimates. Geneva: World Health Organization; 2019.

  10. Instituto Nacional de Estadistica e Informatica. Encuesta Nacional de Demografía y Salud ENDES 2019. Lima,Perú: INEI; 2020.

  11. Instituto Nacional de Estadística e Informática. Series anuales de indicadores principales de la ENDES 1986- 2020. Lima, Perú: INEI; 2021.

  12. Huicho L, Huayanay-Espinoza CA, Herrera-Perez E, Segura ER, Niño de Guzman J, Rivera-Ch M, et al. Factorsbehind the success story of under-five stunting in Peru: a district ecological multilevel analysis. BMCPediatr. 2017; 17(1):29. doi:10.1186/s12887-017-0790-3

  13. Sobrino M, Gutiérrez C, Cunha AJ, Dávila M, Jorge A. Desnutrición infantil en menores de cinco años enPerú : tendencias y factores determinantes. Rev Panam Salud Pública. 2014; 35(2):104–112.

  14. Chávez-Zárate A, Maguiña JL, Quichiz-Lara AD, Zapata-Fajardo PE, Mayta-Tristán P. Relationship betweenstunting in children 6 to 36 months of age and maternal employment status in Peru: A sub-analysis ofthe Peruvian Demographic and Health Survey. PLoS One. 2019; 14(4). doi:10.1371/journal.pone.0212164

  15. Jelinek GA. Determining causation from observational studies: A challenge for modern neuroepidemiology.Front Neurol. 2017; 8(JUN):1. doi:10.3389/fneur.2017.00265

  16. Szklo M, Nieto FJ. Epidemiology : beyond the basics; fourth edition. 3a ed. Burlington, Mass; 2019. 515 p.

  17. Nunan D, Aronson J, Bankhead C. Catalogue of bias: attrition bias. BMJ evidence-based Med. 2018; 23(1):21–22.doi:10.1136/ebmed-2017-110883

  18. Nohr EA, Liew Z. How to investigate and adjust for selection bias in cohort studies. Acta Obstet GynecolScand. 2018; 97(4):407–416. doi:10.1111/aogs.13319

  19. Munayco C V, Ulloa-Rea ME, Medina-Osis J, Lozano-Revollar CR, Tejada V, Castro-Salazar C, et al. Evaluacióndel impacto de los multimicronutrientes en polvo sobre la anemia infantil en tres regiones andinas delPerú. Rev Peru Med Exp Salud Publica. 2013; 30(2):229–234. DOI:10.17843/rpmesp.2013.302.196

  20. Lopez De Romaňa G, Brown KH, Black RE, Creed Kanashiro H. Longitudinal studies of infectious diseasesand physical growth of infants in huascar, an underprwileged peri-urban community in lima, Peru. Am JEpidemiol. 1989; 129(4):769–784. doi:10.1093/oxfordjournals.aje.a115192

  21. Fábrega-Cuadros R, Aibar-Almazán A, Martínez-Amat A, Hita-Contreras F. Impact of Psychological Distress andSleep Quality on Balance Confidence, Muscle Strength, and Functional Balance in Community-DwellingMiddle-Aged and Older People. J Clin Med. 2020; 9(9). doi:10.3390/jcm9093059

  22. Sandoval LA, Carpio CE, Garcia M. Comparison between Experience-Based and Household-UndernourishmentFood Security Indicators: A Cautionary Tale. Nutrients. 2020; 12(11). doi:10.3390/nu12113307

  23. Gonzales-Achuy E, Huamán-Espino L, Aparco JP, Pillaca J, Gutiérrez C. Factores asociados al cumplimiento delcontrol de crecimiento y desarrollo del niño menor de un año en establecimientos de salud de Amazonas,Loreto y Pasco. Rev Peru Med Exp Salud Publica. 2016; 33(2):224–232. doi:10.17843/rpmesp.2016.332.2187

  24. Gonzales E, Huamán-Espino L, Gutiérrez C, Aparco JP, Pillaca J. Caracterización de la anemia en niñosmenores de cinco años de zonas urbanas de Huancavelica y Ucayali en el Perú. Rev Peru Med Exp SaludPublica. 2015; 32(3):431–439.

  25. MAL-ED Network Investigators. Childhood stunting in relation to the pre- and postnatal environment duringthe first 2 years of life: The MAL-ED longitudinal birth cohort study. PLoS Med. 2017; 14(10).doi:10.1371/journal.pmed.1002408

  26. Launes J, Hokkanen L, Laasonen M, Tuulio-Henriksson A, Virta M, Lipsanen J, et al. Attrition in a 30-year followupof a perinatal birth risk cohort: factors change with age. PeerJ. 2014; 2:e480. doi:10.7717/peerj.480

  27. Calderón J. New social housing programs and urban land markets in Peru. Eure. 2015; 41(122):27–47.doi:10.4067/s0250-71612015000100002

  28. Livano A. Dianóstico de genero de la provincia de Huancavelica. Eclosio; 2019.

  29. White SW, Eastwood PR, Straker LM, Adams LA, Newnham JP, Lye SJ, et al. The Raine study had no evidenceof significant perinatal selection bias after two decades of follow up: A longitudinal pregnancy cohortstudy. BMC Pregnancy Childbirth. 2017; 17(1):207. doi:10.1186/s12884-017-1391-8

  30. Miranda JJ, Gilman RH, García HH, Smeeth L. The effect on cardiovascular risk factors of migration fromrural to urban areas in Peru: PERU MIGRANT Study. BMC Cardiovasc Disord. 2009; 9:23.doi:10.1186/1471-2261-9-23

  31. Instituto Nacional de estadistica e Informatica (INEI). Encuesta Demográfica y de Salud Familiar (Endes) 2017.Lima; 2018.




2020     |     www.medigraphic.com

Mi perfil

C?MO CITAR (Vancouver)

Arch Med. 2022;22