MATERNAL FACTORS ASSOCIATED WITH CHILD NUTRITION IN RICE-BASED FARM HOUSEHOLDS IN CENTRAL LUZON, PHILIPPINES

Authors

  • R.G. Abilgos -Ramos Rice Chemistry and Food Science Division, Philippine Rice Research Institute, Maligaya, Science City of Muñoz, Nueva Ecija 3119, Philippines
  • J.F. Ballesteros Rice Chemistry and Food Science Division, Philippine Rice Research Institute, Maligaya, Science City of Muñoz, Nueva Ecija 3119, Philippines
  • C.C. Launio Benguet State University, Km. 5 Baguio-La Trinidad-Bontoc Rd, La Trinidad 2601, Benguet, Philippines

Keywords:

anthropometric data, child nutrition, maternal factors, stunting, underweight, wasting

Abstract

Mothers play key roles in the development of children’s eating behavior, food consumption, and nutrition. This study primarily aimed to determine the maternal factors associated with child nutrition. A cross-sectional community survey was conducted in rice-based farm households in Central Luzon to obtain anthropometric measurements from 275 children 0 to 10 years old and their mothers. Socio-demographics were collected on mothers. Mothers’ knowledge level on health and nutrition was also assessed. Among pre-school children, stunting (15.2%), underweight (16.8%), and wasting (19.5%) were low, medium, and very high, respectively. The corresponding figures in school-age children were 16.9%, 18.9%, and 22.1%. Compared with males, female children exhibited higher prevalence in almost all malnutrition indicators (stunting, wasting, and underweight), pre-school age (16.9% to 20.4% vs 16.7% to 19%) and school-age (13.7% to 25.5% vs 19.1% to 23.1%). Logistic regression analyses revealed that low educational attainment for mothers [AOR=2.78 (CI: 1.03, 7.48)] and low household income [AOR=2.28 (CI: 01.08, 4.82)] led to higher odds of underweight. Absence of a major illness or disability [AOR=0.33 (CI: 0.12, 0.87)] in mothers resulted in lower odds of wasting. Mothers with lower BMI [AOR=5.47 (CI: 1.43, 20.95)] and non-membership in organizations (e.g. farmers association) [AOR=2.21 (CI: 1.12, 4.35)] led to higher odds of wasting. Living in rural areas [AOR=2.61 (CI: 1.22, 5.57)] resulted in higher odds of stunting. Maternal factors such as education, nutritional and health status, and other factors such as income and place of residence were associated with the occurrence of malnutrition in children. Hence, this study recommends gender-sensitive nutrition interventions directed to mothers for improved child nutrition.

Downloads

Download data is not yet available.

References

ATWOOD SJ, CODLING K, SHRIMPTON R. 2013. Strategy to Reduce Maternal and Child Undernutrition. Retrieved from http://www.unicef.org/eapro/Strategy_to_reduce_maternal_and_child_undernutrition.pdf on 2 September 2015.
[FNRI] Food and Nutrition Research Institute. 8th National Nutrition Survey. 2013; Taguig City: FNRI-DOST.
HALIM N, SPIELMAN K, LARSON B. 2015. The economic consequences of selected maternal and early childhood nutrition interventions in low- and middle-income countries: a review of the literature, 2000-2013. BMC Women’s Health15:33.
[IFAD]International Fund for Agricultural Development. 2009. Enabling poor rural people to overcome poverty in the Philippines. Retrieved from http://www.ifad.org/operations/projects/regions/pi/factsheets/ph.pdf on 3 September 2015.
[IBM] International Business Machines Corporation. 2011. IBM SPSS Regression 20. Retrieved from: http://www.csun.edu/sites/default/files/regression20-32bit.pdf on 4 April 2015.
LOHMAN GT, ROCHE AF, MARTORELL R.1988. Anthropometric Standardization Reference Manual. Champaign, IL: Human Kinetics Books.
MAKOKA D. 2013. The Impact of Maternal Education on Child Nutrition: Evidence from Malawi, Tanzania, and Zimbabwe. Retrieved from: www.schoolsandhealth.org/Shared%20Documents/The%20Impact%20of%20Maternal%20Education%20on%20Child%20Nutrition%20Evidence%20from%20Malawi%20Tanzania%20and%20Zimbabwe.pdf on 4 March 2015.
MELO AMC, KASSAR SB, LIRA, PIC, COUTINHO SB, EICKMANN SH, LIMA MC. 2013.Characteristics and factors associated with health care in children younger than 1 year with very low birth weight. J Pediatr (Rio J)89(1):75-82.
MULLER O, JAHN A. Malnutrition and Maternal and Child Health. 2009. In: Ehiri J, editor. Maternal and Child Health. New York: Springer. pp. 287-309.
MURARO AP, GONCALVES-SLIVA RM, MOREIRA NF, FERREIRA MG, NUNES-FREITAS AL, ABREU-VILLACA Y et al. 2014. Effect of tobacco smoke exposure during pregnancy and preschool age on growth from birth to adolescence: a cohort study. NMC Pediatr14:99.
PALLANT J. 2005. SPSS Survival Manual: A step by step guide to data analysis using SPSS. Sydney: Allen & Unwin. 2nd edition.
[PSA] Philippine Statistical Authority. 2012. Highlights of the 2012 Full Year Official Poverty Statistics. Available from http://www.nscb.gov.ph/poverty/2012/highlights_fullyear.asp cited on 25 April 2015.
[PSA] Philippine Statistical Authority. 2014. Urban/Rural Classification. Available from: http://www.nscb.gov.ph/activestats/psgc/articles/con_urbanrural.asp cited on 3 June 2015.
[PSA] Philippine Statistics Authority. 2016. Highlights of the Philippine Population 2015 Census of Population. Retrieved from: https://www.psa.gov.ph/content/highlights-philippine-population-2015-census-population on March 26, 2017.
ROGERS I, EMMETT P, ALSPAC Study Team. 2003. The effect of maternal smoking status, educational level and age on food and nutrient intakes in preschool children: results from the Avon Longitudinal Study of Parents and Children. Eur J Clin Nutr57(7): 854-64.
ROHNER F, WOODRUFF A, AARON GJ, YAKES, EA, LEBANAN MA, RAYCO-SOLON P et al. 2013. Infant and young child feeding practices in Urban Philippines and their associations with stunting, anemia, and deficiencies of iron and vitamin A. Food Nutr Bull34 (2 Suppl): S17-34.
STEWART CP, IANNOTTI L, DEWEY KG, MICHAELSEN KF, ONYANGO, AW. 2013. Contextualising complementary feeding in a broader framework for stunting prevention. Matern Child Nutr9 Suppl 2:27-45.
SMITH LC, RUEL MT, NDIAYE A. 2005. Why is Child Malnutrition Lower in Urban than Rural Areas? Evidence from 36 Developing Countries. Retrieved from http://www.cmamforum.org/Pool/Resources/Malnutrition-in-urban-vs-rural-areas-IFPRI-2005.pdf on 3 September 2015.
[UNICEF]United Nations International Children's Emergency Fund. 2013. Improving Child Nutrition The achievable imperative for global progress. UNICEF: New York.
[UNICEF]United Nations International Children's Emergency Fund Indonesia. 2012. Maternal and child nutrition. Retrieved from http://www.unicef.org/indonesia/A6-_E_Issue_Brief_Child_Nutrition_REV2.pdf on 8 August 2015.
[UNICEF]United Nations International Children's Emergency Fund. Nutrition-What are the challenges?Available fromhttp://www.unicef.org/nutrition/index_challenges.html cited on 3 June 2015.
[UNICEF]United Nations International Children's Emergency Fund, [WHO] World Health Organization, World Bank Group. 2016. Levels and Trends in Child Malnutrition UNICEF/WHO/World Bank Group Joint Child Malnutrition Estiamtes Key Findings in the 2016 Edition. Retrieved from:https://data.unicef.org/wp-content/uploads/2016/09/UNICEF-Joint-Malnutrition-brochure.pdf on March 26, 2017.
[USDA] United States Department of Agriculture. 2013. Diet Quality of Children Age 2-15 Years as Measured by the Healthy Eating Index-2010. Retrieved fromhttp://www.cnpp.usda.gov/sites/default/files/nutrition_insights_uploads/Insight52.pdf on 2014.
WILSON R, GEARRY RB, GRANT E, PEARSON J, SKIDMORE P ML. 2014. Home food availability is associated with multiple socio-economic indicators in 50 years from Canterbury, New Zealand. Asia Pac J Clin Nutr 23(4): 714-722.
[WCRF] World Cancer Research Fund International.2013. The link between food, nutrition, diet and non-communicable diseases. Retrieved from: http://www.wcrf.org/sites/default/files/PPA_NCD_Alliance_Nutrition.pdf on 3 September 2015.
[WHO] World Health Organization. BMI Classification. Available from http://apps.who.int/bmi/index.jsp?introPage=intro_3.html cited on 25 April 2015.
[WHO] World Health Organization. 2010. Nutrition Landscape Information System (NLIS) Country Profile Indicators: Interpretation Guide. Retrieved from: http://www.who.int/nutrition/nlis_interpretation_guide.pdf on March 26, 2017.
[WHO] World Health Organization. 2010. WHO Anthro for personal computers, version 3.2.2, 2011: Software for assessing growth and development of the world’s children Manual. Availablefrom http://www.who.int/childgrowth/software/en/ cited on 20 April 2015.
[WHO] World Health Organization. 2009. WHO AnthroPlus for personal computers: Software for assessing growth of the world's children and adolescents Manual. Availablefrom http://www.who.int/growthref/tools/en/ cited on 20 April 2015.
[WHO] World Health Organization Multicentre Growth Reference Study Group. 2006. WHO Child Growth Standards: Length/height-for-age, weight-for-age, weight-for-length, weight-for-height and body mass index-for-age: Methods and development. Geneva: WHO.
WONG HJ, MOY FM, NAIR S. 2014. Risk factors of malnutrition among preschool children in Terengganu, Malaysia: a case control study. BMC Public Health 14:785.

Downloads

Published

2017-12-16

How to Cite

-Ramos, R. A., Ballesteros, J., & Launio, C. (2017). MATERNAL FACTORS ASSOCIATED WITH CHILD NUTRITION IN RICE-BASED FARM HOUSEHOLDS IN CENTRAL LUZON, PHILIPPINES. Proceedings of the International Conference on Public Health, 3(2), 191–207. Retrieved from http://tiikmpublishing.com/proceedings/index.php/icoph/article/view/118