Nutritional Status of Children Under 5 by Sex
Data as of 2022Distribution of weight-for-age (WAZ), height-for-age (HAZ), and weight-for-height (WHZ) scores for children under 5 years old based on WHO standards, which are used to assess malnutrition (underweight, stunting, wasting, and overweight).
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How is this data produced?
This data is tabulated based on survey records collected via the National Health and Morbidity Survey (NHMS), which is conducted by the Ministry of Health once every 4 years. The NHMS is design to collect representative data on various healthcare outcomes, especially those which cannot be assessed through administrative hospital data. For a fuller description of the methodology, please refer to the NHMS 2019 report. Figures for 2016 are from NHMS 2016: Maternal and Child Health, figures for 2019 are from NHMS 2019, and figures for 2022 are from NHMS 2022: Maternal and Child Health.
For this dataset specifically, the distributions of WAZ, HAZ and WHZ for Malaysia were calculated by comparing the weights and heights of children under 5 years old to the World Health Organization Growth Standard 2006 (WHO 2006). Following that, the prevalence of 4 key malnutrition indicators is defined as follows:
- Underweight: Weight-for-age (WAZ) less than 2 standard deviations below the median
- Stunting: Height-for-age (HAZ) less than 2 standard deviations below the median
- Wasting: Weight-for-height (WHZ) less than 2 standard deviations below the median
- Overweight: Weight-for-height (WHZ) more than 2 standard deviations above the median
What caveats I should bear in mind when using this data?
NHMS 2016 and NHMS 2022 report weight-for-height (WHZ) above 2 standard deviations as a single category, so overweight and obesity are not shown separately for 2016 and 2022. Estimates whose relative standard error is too large have been omitted; users should consult the NHMS 2022 report for greater detail.
Metadata
Dataset description
Distribution of weight-for-age (WAZ), height-for-age (HAZ), and weight-for-height (WHZ) scores for children under 5 years old based on WHO standards, which are used to assess malnutrition (underweight, stunting, wasting, and overweight).
Variable definitions
- Date
- Sex
- Indicator
- Range
- Description
- Prevalence (%)
Name in Dataset | Variable | Definition |
|---|---|---|
date (Date) | Date | The date in YYYY-MM-DD format, with MM-DD set to 01-01 as this is annual data |
sex (Categorical) | Sex | Either both sexes ('both'), male ('male') or female ('female') |
indicator (Categorical) | Indicator | Either weight-for-age (WAZ), height-for-age (HAZ), or weight-for-height (WHZ) |
range (String) | Range | The range for the indicator (e.g., < -2SD, -2SD to 2SD, > 2SD). |
description (String) | Description | The interpretation of the range (e.g., Underweight, Normal, Overweight). |
prevalence (Float, %) | Prevalence (%) | The proportion of the population in the range, expressed as a percentage. |
Last updated:
11 Oct 2026, 12:00
Next update:
N/A
Data source(s)
- Ministry of Health Malaysia
URLs to dataset
License
This data is made open under the Creative Commons Attribution 4.0 International License (CC BY 4.0). A copy of the license is available Here.
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Data
Full Dataset (CSV)
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Full Dataset (Parquet)
Recommended for data scientists seeking to work with data via code.
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Code
Connect directly to the data with Python.
# If not already installed, do: pip install pandas fastparquet
import pandas as pd
URL_DATA = 'https://storage.data.gov.my/healthcare/nutrition_status_u5_sex.parquet'
df = pd.read_parquet(URL_DATA)
if 'date' in df.columns: df['date'] = pd.to_datetime(df['date'])
print(df)Sample OpenAPI query
The following code is an example of how to make an API query to retrieve the data catalogue mentioned above. You can use different programming languages by switching the code accordingly. For a complete guide on possible query parameters and syntax, please refer to the official Open API Documentation.
import requests
import pprint
url = "https://api.data.gov.my/data-catalogue?id=nutrition_children_sex&limit=3"
response_json = requests.get(url=url).json()
pprint.pprint(response_json)
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