The study identified 11 factors that contribute to stunting in children under 5 years old in Putrajaya, Malaysia. The strongest associated factor was complications during pregnancy like intrauterine growth restriction. Other significant factors included mid-parental height less than 150cm, low household income, low birth weight, use of pacifiers, lower maternal education, unemployed fathers, anemia in children, bottle feeding, lack of minimum dietary diversity, and care by babysitters. Addressing these maternal, socioeconomic, childcare and nutritional factors through community interventions and policies could help reduce the high prevalence of stunting in Putrajaya.

1. ASSOCIATED FACTORS TO
STUNTED CHILDREN IN PUTRAJAYA
1
Mohammad Hasnan Ahmad
Nutritionist
Principal Investigator
Centre for Nutrition Epidemiology Research
Institute for Public Health
National Institutes of Health
Ministry of Health Malaysia

2. RESEARCH TEAM MEMBERS
2
Name Organisation
Mohamad Hasnan Ahmad (PI) IPH
Nor Azian Mohd Zaki IPH
Dr Tahir Aris IPH
Dr. Noor Ani Ahmad IPH
Rashidah Ambak IPH
Dr Noor Safiza Mohamad Nor IPH
Ruhaya Salleh IPH
Azli Baharudin IPH
Fatimah Othman IPH
Syafinaz Mohd Sallehudin IPH
Cheong Siew Man IPH
Name Organisation
Nur Shahida Abdul Aziz IPH
Lalitha A/P Palaniveloo IPH
Dr. Mohd Azahadi Omar IPH
Rusidah Selamat Nutrition Division
Mohd Zamir Majid Nutrition Division
Dr. Rozita Ab Rahman Family Health
Development Division
Dr. Husnina Ibrahim Putrajaya Health Office
Dr. Sophia Mohd Ramli Putrajaya Health Office
Masrisa Mohd Esa Putrajaya Health Office
Prof. Dr. Poh Bee Koon UKM
Prof. Madya Dr. Hazizi Abu Saad UPM

3. Introduction
• Stunting, or being too short for one’s age, is defined as a
height that is less than negative two standard
deviations in the World Health Organization (WHO)
child growth standards median.1,2
• It is a largely irreversible outcome of inadequate nutrition
and repeated bouts of infection during the first 1000
days of a child’s life.1,2
• Stunting has long-term effects on individuals and
societies, including: diminished cognitive and physical
development, reduced productive capacity and poor
health, and an increased risk of degenerative diseases
such as diabetes.3,4
3
Stunting (HAZ <-2sd)

4. 4
Figure 1. Prevalence of stunted among children less than 5 years old in
Malaysia and Putrajaya
Introduction
The prevalence of stunted
in Putrajaya was higher
than national prevalence
(20.7%) and higher than
global prevalence (22.9%)
in 2016
# NPANM target by 2025:
Stunting <11%
# Global Nutrition Target
2025: Reduce by 40%
the number of children
aged under 5 years who
are stunted
16.6 17.7
20.7
21.8
10.9
14.6
24.3
20.3*
0
5
10
15
20
25
30
NHMS 2011 NHMS 2015 NHMS 2016 NHMS 2019
prevalence(%)
Malaysia Putrajaya
*Prevalence with high RSE, interpret with caution

5. 5
Factor related to stunted among children under 5 years old
Adapted from : 1. Childhood Stunting-Context, cause and consequences WHO framework 20135
2. UNICEF Conceptual Framework of Malnutrition6
3. Nutrition Landscape Analysis 2017, Institute Public Health & Nutrition Division, Ministry of Health7
Parental factors
- Parental height
- Education
- Occupation
- Household income
- Maternity care during pregnancy
Children factors
- Low birth weight
- Delayed initiation
- More than 4 sibling
- Frequent illness / injury
- - Worm infection
- Anaemia
Food intake factors
- Non-exclusive BF
- Early cessation of BF
- Not start complementary feeding at 6 months
- Infrequent and inadequate feeding
- Low dietary diversity
- Food insecurity
Environment factors
- Inadequate child stimulation
and activity
- Poor care practice
Stunted

6. Research Question
What are the factors that contribute to stunted among
children aged 6 to 59 months in Putrajaya.
6
Objectives
To determine the factors that contribute to stunted
among children aged 6 to 59 months

7. Methodology
Study Design
• Case-control study with 1 to 1 ratio
• Match by sex and age groups
(6-11, 12-35 & 36-59 month as in RNI 2017)*
Sample size
• Calculated using the formula for comparing 2-Proportions in PS software (α=0.05, β= 0.8 and m= 1)
according to identified risk factors based on previous survey. 7-10
7
❖Stunting:
380
❖Normal:
380
Target population
• Children aged 6 to 59 months old staying in Putrajaya
• Inclusion criteria - Case (stunted children), control
(normal children) & Putrajaya resident.
• Exclusion criteria - Children with mental or physical
disabilities & ill at time of data collection.

8. Recruitment of the respondent
8
Phase 1
Screening (measure height
& weight) at nursery,
preschool & health clinic
1. Face to face interview
A. Sociodemographic profile
B. Health/Medical history
C. Knowledge, attitude & practice
towards child’s feeding
D. Dietary behaviour
E. Breastfeeding, Infant & young child
feeding (IYCF) history
F. Food security
G. Screen time & physical activity
2. Anthropometry measurements
3. 3 days food diary
4. Finger prick for hemoglobin level
Identify & selection
the case & control
children
Phase 2
Interview parents &
caregivers for the risk of
malnutrition
Screening
8,054
Stunted
2105 (26.1%)
Normal
5223 (64.0%)
Randomly select
380 children
Match by sex & age
groups with selected
stunted children
Boy
▪ 6 - 11 months : 26
▪ 12 - 35 months : 77
▪ 36 - 59 months : 87
Girl
▪ 6 - 11 months : 33
▪ 12 - 35 months : 75
▪ 36 - 59 months : 82

9. Data Processing & Analysis
• WHO Anthro software was used to identified the case (stunted)
and control (normal) respondent
• =RANDBETWEEN(bottom,top) command in excel was used to
select respondent randomly.
• Survey Creating System (SCS) Application in tablet was used
for data collection and the data collected sent to SCS Server
located in IPH.
• NutritionistPro Software was used to translate nutrient intake
from the 3 days food diary.
• SPSS ver. 23 was used for the data cleaning and analysis
(cross tab. and logistic regression)
9

10. Results
10
Stunted in Putrajaya based on the screening on 8,054 children…
26.1%
(2,105 children)
Putrajaya
Health clinics
31.9%
Boy
Girl
28.7%
23.4%
Pre-schools
16.3%
SexFacility
1 in 4 children under 5 years old
in Putrajaya are stunted

11. Results
11
Factors that contribute to stunted in Putrajaya…
Hosmer-Lameshow test = 0.247 (>0.05)
Classification table = 65.2%
Area under Receiver Operating Characteristics (ROC) curve = 0.711

12. Discussion
• As many as 11 factors were identified in the final model. Complication during pregnancy which is IUGR
was shown to have the strongest association with stunting. Infants with IUGR often suffer from delayed
neurological and intellectual development and deficit of gain height.11
• Mid-parental height less than 150cm, low monthly household income, low birth weight, and use of
pacifiers were about three times more likely to be stunted compared to the respective reference groups
• Other significant associated factors were primary or secondary level education of the mother,
unemployed father, anemic children, use of bottle feeding, do not meet minimum dietary diversity (MDD),
and children cared by babysitter.
• A large number of risk factors for stunting have been identified in many epidemiological studies and it
varies between countries. Reducing the burden of stunting requires a paradigm shift from interventions
focusing solely on children and infants to those that reach mothers and families and improve their living
environment and nutrition.12
12

13. Conclusion
• As conclusion, pregnancy complications which is IUGR was the strongest
associated factor of stunted children in Putrajaya followed by mid-parental
height less than 150 cm, low monthly household income (B40 & M40), low
birth weight, use of pacifiers, primary or secondary education of the mother,
unemployed father, anemic children, use of bottle feeding, lack of minimum
dietary diversity (MDD) and children cared for by babysitter.
13

14. Recommendation
• Scale up coverage of stunting prevention activity such as enact policies and/or
strengthen interventions to improve maternal nutrition and health beginning
with adolescent girls.
• Strengthen community based intervention by including stunting as one of
criteria for receiving food basket
• Increase enforcement on code of ethics for the marketing of infant foods and
related products.
• Reintroduce and create sustainable program for urban farming as it can play
important role in advancing food and nutritional security especially now during
the covid-19 pandemic.
14

15. References
1. World Health Organization (WHO) (2016). What is malnutrition. http://www.who.int/features/qa/malnutrition/en/. Accessed 10 March
2018.
2. WHO Multicentre Growth Reference Study Group. Assessmentof differences in linear growth among populations in the WHO
Multicentre Growth Reference Study. (2006) Acta Paediatr;(Suppl 450):56–65.
3. De Onis M and F Branca (2013). Maternal and Child Nutrition. 12 – 26. http://onlinelibrary.wiley.com/doi/10.1111/mcn.12231/epdf;
World Health Organization. (2014). Global nutrition targets 2025: Stunting policy brief (No. WHO/NMH/NHD/14.3). World Health
Organization.
4. ASEAN/UNICEF/WHO (2016). Regional Report on Nutrition Security in ASEAN, Volume 2. Bangkok; UNICEF
5. UNICEF (2018). Undernutrition contributes to nearly half of all deaths in children under 5 and is widespread in Asia and Africa.
https://data.unicef.org/topic/nutrition/malnutrition/# Accessed 10 March 2018.
6. Institute for Public Health, Ministry of Health Malaysia. National Health and Morbidity Survey 2016
7. Cheah WL, Wan Muda WA, Mohd Hussin ZA, & Thon CC. (2012). Factors associated with undernutrition among children in a rural
district of Kelantan, Malaysia. Asia Pac J Public Health. 2012 Mar;24(2):330-42.
8. Shariff ZM, Lin KG, Sariman S, Siew CY, Yusof BNM, Mun CY & Mohamad M. (2016). Higher Dietary Energy Density is Associated
with Stunting but not Overweight & Obesity in a Sample of Urban Malaysian Children. Eco & Nutr, 55(4), 378–89.
9. 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(1), 785.
10.Dewey KG & Begum K. (2011) Long‐term consequences of stunting in early life. Matern Child Nutr 7, 5-18.
11.Danaei G, Andrews KG, Sudfeld CR et al. (2016) Risk factors for childhood stunting in 137 developing countries: a comparative risk
assessment analysis at global, regional, and country levels. PLoS med. doi: 10.1371/journal.pmed.1002164.
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16. THANK YOU
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