Health Tool

Cermin
Diri.

Find out your metabolic health risk in minutes — calibrated for Malaysian bodies.Check risiko kesihatan metabolik anda sepantas kilat — ikut formula orang Malaysia!

📊 WHO · OWID · NHMS Malaysia
yrs
kg
cm
cm
cm

Your Health ProfileProfil Kesihatan Anda

Overall risk index — lower is betterIndeks risiko keseluruhan — lebih rendah lebih baik
⚠️
BMI
Waist
WHtR
Diabetes risk scoreSkor risiko diabetes
LowRendahSlightly elevatedAgak tinggiModerateSederhanaHighTinggiVery highSangat tinggi
Your measurements — tap any card to exploreUkuran anda — ketik kad untuk maklumat lanjut
📍 BMI vs Waist — Goal plannerBMI vs Pinggang — Perancang sasaran
Healthy zone
Elevated risk
High risk
Your position
Your goal
MY population

What if I improve?Bagaimana jika saya bertambah baik?

Drag to simulate your goal — watch the green dot move on the chart above.Seret untuk mensimulasi sasaran anda — lihat titik hijau bergerak pada carta di atas.

Goal Weight
kg
Goal Waist
cm
📍 Your position among MalaysiansKedudukan anda dalam kalangan rakyat Malaysia
SexJantina
Age groupKumpulan umur
HealthySihat
One risk factorSatu faktor risiko
Both elevatedKedua-dua tinggi
You
Population cloud seeded from NHMS 2019 & 2023 published mean BMI and waist distributions by sex and age group (IKU/MOH Malaysia). Individual points are statistically simulated — not real survey respondents.Data populasi berdasarkan taburan min BMI dan pinggang NHMS 2019 & 2023 mengikut jantina dan kumpulan umur (IKU/KKM Malaysia). Titik-titik adalah simulasi statistik — bukan responden sebenar.
For informational purposes only. Not a substitute for professional medical advice.
Please consult a qualified healthcare provider for diagnosis and treatment.
Untuk tujuan maklumat sahaja. Bukan pengganti nasihat perubatan profesional.
Sila berunding dengan pengamal kesihatan yang berkelayakan untuk diagnosis dan rawatan.
WHO World Health Organization — Asia-Pacific Guidelines (2004)

The WHO published Asia-Pacific-specific BMI and waist circumference cutoffs in 2004, recognising that Asians develop cardiometabolic risk at lower body mass than Western populations. These thresholds underpin the BMI classification, waist circumference risk categorisation, and risk zone shading in the BMI vs Waist chart throughout this app.

WHO Expert Consultation report →
NHMS National Health & Morbidity Survey 2019 & 2023 — Malaysia

Malaysia's national health survey conducted by the Institute for Public Health (IKU) under the Ministry of Health (MOH). The 2019 edition surveyed over 10,000 adults and reported prevalence of overweight, obesity, abdominal obesity, hypertension, and diabetes by sex and age group. This app uses published mean BMI and waist circumference values from NHMS 2019 and 2023 as seed data for the Malaysian population scatter chart. Individual data points in that chart are statistically simulated from those means using Gaussian noise — they are not real survey respondents.

NHMS 2019 full report → NHMS 2023 full report →
FINDRISC Finnish Diabetes Risk Score — Asian Calibration

FINDRISC is a validated, non-invasive diabetes risk screening tool developed by Lindström & Tuomilehto (2003). This app uses an Asian-calibrated version that adjusts waist circumference thresholds for Asian body proportions: men ≥90 cm (standard) / >99 cm (high), women ≥80 cm (standard) / >87 cm (high), consistent with WHO Asia-Pacific and JADE (Joint Asia Diabetes Evaluation) programme recommendations. The score produces a 10-year risk estimate for type 2 diabetes.

Lindström & Tuomilehto 2003 (original FINDRISC) →
ABSI A Body Shape Index — Krakauer & Krakauer (2012)

ABSI was introduced by Krakauer NY & Krakauer JC (2012) as a measure of abdominal obesity that accounts for height and BMI, capturing visceral fat risk that BMI alone misses. Higher ABSI values indicate a more apple-shaped fat distribution pattern independently associated with all-cause mortality risk.

Krakauer & Krakauer 2012 (PLOS ONE) →
BAI Body Adiposity Index — Bergman et al. (2011)

BAI was developed by Bergman RN et al. (2011) as a surrogate measure of body fat percentage derived from hip circumference and height — without requiring weight. It was validated primarily in Hispanic and African-American populations and is included here as an optional supplementary metric when hip circumference is entered. Users should note its validation basis differs from Malaysian populations.

Bergman et al. 2011 (Obesity) →
OWID Our World in Data — Global Obesity & NCD Trends

Our World in Data aggregates long-run health statistics from the Global Burden of Disease study and WHO. Population context figures referenced in this app — including Malaysia's overweight prevalence (~50% of adults) and the global tripling of obesity rates since 1990 — are drawn from OWID's published country-level data.

OWID obesity data →
Metrics Six Anthropometric Indices

All six indices are computed from raw inputs (weight in kg, height in cm, waist in cm, hip in cm). Height and waist are converted to metres where the formula requires it.

1. Body Mass Index (BMI)

BMI = weight (kg) ÷ height (m)²

2. Waist Circumference (WC) — used directly as entered in cm. No formula applied; classified against WHO Asia-Pacific cutoffs.

3. Waist-to-Height Ratio (WHtR)

WHtR = waist (cm) ÷ height (cm)

Boundary: ≥0.50 = elevated risk; ≥0.60 = high risk. Universal across ethnicities.

4. A Body Shape Index (ABSI) — Krakauer & Krakauer (2012)

ABSI = waist (m) ÷ (BMI^(2/3) × height (m)^(1/2))

5. Conicity Index

Conicity = 0.109 × waist (m) ÷ √(weight (kg) ÷ height (m))

Values >1.25 (men) or >1.18 (women) indicate apple-shaped fat distribution.

6. Body Adiposity Index (BAI) — Bergman et al. (2011) — optional, requires hip measurement

BAI = hip (cm) ÷ height (m)^1.5 − 18

Result approximates body fat percentage (%). Note: hip stays in cm; only height converts to metres.

Thresholds Risk Classification Cutoffs per Metric

Each metric is assigned one of three risk tiers — Healthy, Needs attention, or High risk — based on the following cutoffs. Sex-specific values are shown where applicable.

MetricHealthyNeeds attentionHigh risk
BMI (age 18–59)18.5 – 22.923.0 – 27.4≥ 27.5
BMI (age 60–69)20.0 – 24.925.0 – 29.4≥ 29.5
BMI (age 70+)22.0 – 26.927.0 – 31.4≥ 31.5
Waist — men< 90 cm90 – 99 cm≥ 100 cm
Waist — women< 80 cm80 – 87 cm≥ 88 cm
WHtR< 0.500.50 – 0.59≥ 0.60
ABSI — men< 0.0870.087 – 0.099≥ 0.100
ABSI — women< 0.0830.083 – 0.094≥ 0.095
Conicity — men< 1.251.25 – 1.37≥ 1.38
Conicity — women< 1.181.18 – 1.29≥ 1.30
BAI — men< 22%22 – 27%≥ 28%
BAI — women< 30%30 – 35%≥ 36%
FINDRISC Asian-Calibrated Diabetes Risk Score (0 – 26 points)

Points are summed across all applicable questions. Maximum score is 26.

QuestionConditionPoints
Age45 – 54 years+2
55 – 64 years+3
≥ 65 years+4
BMI23.0 – 27.4+1
≥ 27.5+3
Waist — men90 – 99 cm+3
≥ 100 cm+4
Waist — women80 – 87 cm+3
≥ 88 cm+4
Physical activity< 30 min/day moderate activity+2
DietDoes not eat vegetables or fruit daily+1
Blood pressureDiagnosed or on medication+2
Blood glucosePreviously found elevated+5
Family history2nd-degree relative (grandparent / aunt / uncle)+3
1st-degree relative (parent / sibling / child)+5
Gestational diabetesWomen only — history of GDM+5

Score interpretation:

ScoreRisk levelEstimated 10-year T2DM risk
0 – 7Low~1%
8 – 11Slightly elevated~4%
12 – 14Moderate~17%
15 – 20High~33%
21 – 26Very high~50%
Composite Overall Risk Index — Weighting & Normalisation

Each metric is first normalised to a 0–100 scale using its reference range, then weighted and summed to produce a single composite score (0 = lowest risk, 100 = highest risk).

Step 1 — Normalise each metric to 0–100:

Normalised score = (value − min) ÷ (max − min) × 100

Step 2 — Normalisation ranges:

MetricMin (score = 0)Max (score = 100)
BMI1542
Waist circumference55 cm130 cm
WHtR0.300.80
ABSI0.0650.115
Conicity Index0.901.60
FINDRISC score026

Step 3 — Weighted composite:

Composite = (WC × 0.25) + (FINDRISC × 0.25)
              + (BMI × 0.20) + (WHtR × 0.15)
              + (ABSI × 0.10) + (Conicity × 0.05)

Waist circumference and FINDRISC carry the highest weight (25% each) as the strongest independent predictors of cardiometabolic risk in Asian populations. BAI is excluded from the composite as it is an optional supplementary metric.

Step 4 — Composite score tiers:

Composite scoreVerdict
0 – 30Metabolically healthy
31 – 70Some markers to watch
71 – 100Elevated risk

Floor-rule callout: If any single metric is classified as High risk but the composite score remains in the healthy zone (0–30), a separate callout is shown beneath the dial naming that specific metric. The dial verdict and action card are not overridden — the composite score is preserved as the primary output.

Scatter Malaysian Population Reference Cloud

The population scatter chart is seeded from NHMS 2019 and 2023 published mean BMI and waist circumference values by sex and age band. Individual points are generated at runtime using a 6-sample Gaussian approximation:

value = μ + σ × (Σ6 uniform samples − 3) × 0.9

Standard deviations used: σ(BMI) = 3.8, σ(WC) = 9.5. n = 300 points (all ages) or 220 (single age band). Points are clamped to physiologically plausible ranges. These are simulated reference points, not individual survey respondents.

NHMS seed means used (BMI):

Age bandMen (mean BMI)Women (mean BMI)
18 – 2923.823.2
30 – 3925.625.8
40 – 4926.127.4
50 – 5925.828.1
60+24.926.8

NHMS seed means used (Waist circumference, cm):

Age bandMen (mean WC)Women (mean WC)
18 – 2982.077.5
30 – 3988.581.2
40 – 4991.285.6
50 – 5990.887.3
60+89.485.9
Limitations Important Caveats for Clinical Use

This tool is a screening aid, not a diagnostic instrument. Results should be interpreted alongside clinical history, blood investigations, and professional judgement. Specific limitations to note:

  • The composite risk index weighting is based on published epidemiological evidence but has not been independently validated as a combined score in Malaysian populations.
  • BAI validation data originates from Hispanic and African-American cohorts — its accuracy for Malaysian users is not confirmed.
  • The population scatter uses simulated data seeded from NHMS means — it does not represent a random sample of the Malaysian population.
  • FINDRISC was originally developed for Finnish populations. Asian calibration adjusts waist thresholds but other score components retain their original weightings.
  • Age-adjusted BMI thresholds for older adults are based on existing literature but are not yet universally adopted in Malaysian clinical guidelines.
A
Auf Ali @theaufthority · I create evidence-based health tools for Malaysians