The Effect of Dietary Intake and Social Economic Factors on the Risk of Stunting in Primary School Children in Surakarta, Central Java

• Main Authors: Agustina Dwi Utami, Dono Indarto, Yulia Lanti Retno Dewi
• Format: Article
• Language: English
• Published: Masters Program in Public Health, Universitas Sebelas Maret 2017-01-01
• Series: Journal of Epidemiology and Public Health
• Subjects: children; stigma; discrimination.; Primary school students; Nutrient Intake; Stunting
• Online Access: http://www.jepublichealth.com/index.php?journal=jepublichealth&page=article&op=view&path%5B%5D=27&path%5B%5D=30

Background: It is estimated there are 156 million of children or as much as (23%) all over the world who endure stunting. Stunting prevalence in Indonesia reaches 29%, the figure is the highest among South East Asia countries. Whereas stunting can cause the escalating mortality and morbidity rate on children, delayed mental development, and reduced intellectual capacity. The study aimed to elaborate the effect of nutrient intake and socioeconomic factor toward stunting incidence among primary school students. Subjects and Method: The study used analytic observational study with cross sectional design. The location of the study was in the city of Surakarta in February up to March 2017. There was a total of 145 subjects of the study. The sampling technique used was multi stage random sampling. Independent variables of the study were protein intake, energy intake, maternal education, maternal occupational status and family income. Dependent variable was stunting. The study used questionnaires and body height measurement for data collection. The data processing used was path analysis. Results: Statistical result showed that Stunting Incidence was affected by energy intake (b=0.02,p<0.001), protein intake (b=0.02; p<0.001), maternal education (b=0.23; p=0.187), family income (b=0.01; p=0.051). Â Energy intake was affected by maternal education (b=9.56; p=0.77) and family income (b=1.81; p=0.0.05). Protein intake was affected by maternal education (b=1.75; p=0.051), maternal occupational status (b=-2.30; p=0.33) and family income (b=0.12; p=0.11). Conclusion: Height per age was affected by energy intake, protein intake, maternal education and family income. Energy intake was affected by maternal education and family income. Protein intake was affected by maternal education, maternal occupational status, and family income.