# Investigating Heart Disease: The burden, costs, and early risk

> Heart disease in Plum's health insurance claims in India: 9,534 heart-related claims from 7,402 patients, analysed by condition, age, severity and cost.

- Source: https://www.plumhq.com/datalabs/heart-health
- Published by DataLabs by Plum (Plum, https://www.plumhq.com) on 12 February 2026; updated 13 October 2026
- By Ganapathi Ramanathan (Content and brand, Plum), Saurabh Arora (Co-founder and CTO, Plum); with Shriram Rajakumar (Designer), Sharvan TG (Engineer), Prayat Shah (Head of Healthcare, Plum), Dr. Anirudh Anilkumar (Doctor)

Plum (plumhq.com) is an India-based employee health benefits and insurance platform. Plum Benefits Insurance Brokers Pvt Ltd is an IRDAI-registered direct broker (Life & General), registration no. 897.

## Key findings

- In Plum's cohort of 9,534 heart-related health insurance claims from 7,402 patients, the total amount claimed was ₹148.34 crore.
- In Plum's heart-related claims, the median cost of a hospitalisation ranged from ₹38,000 for a mild episode to ₹4.2 lakh for a critical one, and the median hospital stay from 3 days to 12 days.
- In Plum's cost-outlier analysis of 8,941 heart-related claims, 33.5% cost more than twice the median for their condition group (the overall median, for six small groups) and 10.9% cost more than five times that median.
- In Plum's breakdown of heart-related claims into 14 condition groups, ischemic heart disease, caused by blocked or narrowed coronary arteries, made up 54.9% (5,459 of the 9,945 claims counted across the 14 groups), followed by stroke at 13.3% and hypertensive diseases at 11.8%.
- In Plum's claims data, cardiovascular conditions accounted for 45.7% of patients across five non-communicable disease groups (cardiovascular, cancer, diabetes and kidney, neurological and respiratory) from 2023-Q1 to 2025-Q4, nearly twice cancer's 24.4%. Counted as a running total from 2023-Q1, the cardiovascular share stayed between 44.8% and 48.3% at the end of every quarter.
- Among Plum's heart-related claims with a recorded gender, men filed 2.3 times as many claims as women. After adjusting for that skew, men with a heart-related claim had 1.58 times the odds of an ischemic heart disease diagnosis that women had (95% confidence interval 1.35 to 1.86), the only one of the 10 conditions tested where men's odds were significantly higher.
- In Plum's claims data, the median age at a heart-related hospitalisation was 59. In the edition's separate health checkup data, the first age at which at least half of the people tested had suboptimal HDL cholesterol was 20, and for non-HDL cholesterol it was 28; the edition calls the resulting gaps of 39 and 31 years the prevention window.
- In the health checkup data behind Plum's heart disease edition, 55% of 21 to 30 year olds who had an ApoB/ApoA1 test showed a high-risk ratio, the measure the INTERHEART study found to be the strongest lipid predictor of heart attack. Only 826 people in the checkup data had this ratio measured.

## Questions and answers

### How much does heart disease treatment cost in India?

In Plum's heart-related claims, the median cost of a hospitalisation ranged from ₹38,000 for a mild episode to ₹4.2 lakh for a critical one. In the edition's cost-outlier analysis of 8,941 claims, about one in ten cost more than ₹4.1 lakh. In both the edition's cost-by-condition table and its cost-outlier chart, hypertension had the lowest median cost and conduction disorders the highest. These figures describe Plum's claims, not treatment prices across India.

### How much does heart attack treatment cost in India?

In Plum's claims data, acute myocardial infarction (heart attack) made up 6.4% of heart-related claims in the edition's breakdown of 14 condition groups (634 claims). The edition's conditions chart lists its cost as ₹84,000 for routine treatment and ₹2.2 lakh for treatment that included ICU care. These figures come from Plum's claims, not from hospital prices across India.

### What is the most common heart condition in health insurance claims?

Ischemic heart disease, caused by blocked or narrowed coronary arteries, is the most common in Plum's claims data at 54.9% of heart-related claims. Stroke (13.3%) and hypertensive diseases (11.8%) come next, and chronic coronary artery disease alone accounts for 22% of heart-related claims.

### At what age are people hospitalised for heart disease?

In Plum's claims data, the median age at a heart-related hospitalisation was 59, and hospitalisations peak in the 50s and 60s. The median age varied by condition, from 47 for cardiomyopathy and 48 for venous disease to 65 for heart failure and 66 for conduction disorders. The edition's age chart also shows heart-related claims from people aged 21 to 30, notably for venous disease and rheumatic heart disease.

### Are men more likely to get heart disease than women?

Plum's claims data shows who claims for heart conditions, not who develops them, so it does not measure the risk of heart disease in the population. Among Plum's heart-related claims with a recorded gender, men filed 2.3 times as many as women. Comparing conditions within those claims, after adjusting for that baseline gender skew, ischemic heart disease was the only condition significantly more likely among men (odds ratio 1.58). Hypertensive diseases, arrhythmias and heart failure were relatively more likely among women (odds ratios 0.61, 0.58 and 0.58), and the other six conditions tested showed no significant difference.

### How long is a hospital stay for heart disease?

In Plum's heart-related claims, the median hospital stay was 3 days for mild cases, 5 days for moderate cases, 7 days for severe cases and 12 days for critical cases.

### Do young people in India have heart disease risk factors?

In the health checkup data behind Plum's heart disease edition, 55% of 21 to 30 year olds who had an ApoB/ApoA1 test showed a high-risk ratio, and the share with high non-HDL cholesterol (above 160 mg/dL) rose from 17.8% at ages 21 to 30 to 30.8% at ages 31 to 40. In the same data, 58.6% of 21 to 30 year olds had suboptimal HDL cholesterol. The edition describes the people tested as young professionals getting routine checkups, so these figures are not a sample of all young people in India.

### What is the prevention window for heart disease?

This edition defines the prevention window as the years between the first age at which at least half of the people of that age in its health checkup data show suboptimal levels of a biomarker and the median age of a heart-related hospitalisation in Plum's claims, which is 59. By that measure, the window was 39 years for HDL cholesterol, where at least half showed suboptimal levels from age 20, and 31 years for non-HDL cholesterol, from age 28.

## The edition

### Section 00 · Setting the scene

**Heart disease rarely arrives out of nowhere — its costs build up quietly over years.**

In India, one in four deaths is a heart death. We analysed 9,534 cardiovascular claims worth ₹148 crore alongside 12,000+ health checkups to answer two questions: what does heart disease actually cost — and how early can we see it coming? The answer is sobering. Critical hospitalisations can erase over a decade of savings, a third of cases cost more than double the median, and the risk factors that drive them are already visible in the bloodwork of 20-year-olds — up to four decades before they're hospitalised. This is the gap between what we know and when we act.

- Total Claims: 9,534 (heart disease claims)
- Total Patients: 7,402 (unique patients)
- Total Amount Claimed: ₹148.34 Cr (total claim value)

### Section 01 · Heart vs other NCDs

**Heart disease has had the most patients among India's top NCDs over the last three years.**

Among India's top 5 non-communicable diseases by DALY burden, cardiovascular conditions — ischemic heart disease, stroke, hypertension, and venous disorders — account for 46% of all NCD patients, nearly twice the next largest category (cancer at 24%). Across 20,000+ NCD patients over three years, this share has barely moved — heart disease isn't just the biggest burden, it's the most persistent one.

#### Chart: Share of NCD Patients by Condition

The share of patients in each of the five non-communicable disease (NCD) groups, by quarter from 2023-Q1 to 2025-Q4. Each quarter's shares are taken from the running total of unique patients in each group since 2023-Q1.

| Quarter | Cardiovascular (%) | Cancer (%) | Diabetes & Kidney (%) | Neurological (%) | Respiratory (%) |
| --- | --- | --- | --- | --- | --- |
| 2023-Q1 | 44.8 | 24.5 | 15.0 | 7.3 | 8.4 |
| 2023-Q2 | 45.8 | 25.7 | 12.9 | 8.8 | 6.8 |
| 2023-Q3 | 47.8 | 24.4 | 11.4 | 9.3 | 7.1 |
| 2023-Q4 | 48.3 | 23.9 | 10.9 | 9.8 | 7.0 |
| 2024-Q1 | 48.0 | 23.9 | 11.0 | 10.1 | 6.9 |
| 2024-Q2 | 47.8 | 23.9 | 11.2 | 10.8 | 6.2 |
| 2024-Q3 | 46.4 | 24.3 | 11.8 | 11.2 | 6.3 |
| 2024-Q4 | 45.4 | 24.1 | 12.8 | 11.5 | 6.2 |
| 2025-Q1 | 45.5 | 23.8 | 13.3 | 11.2 | 6.2 |
| 2025-Q2 | 45.6 | 24.6 | 13.0 | 11.1 | 5.7 |
| 2025-Q3 | 45.6 | 24.4 | 12.9 | 11.4 | 5.7 |
| 2025-Q4 | 45.7 | 24.4 | 12.7 | 11.3 | 5.9 |

Key insight: Heart disease consistently accounts for ~46% of all chronic NCD patients — nearly double the next largest category (cancer at 24%). This share has remained stable across 3 years.

### Section 02 · Understanding heart conditions

**14 conditions. One organ. Vastly different costs.**

While ischemic heart disease – caused by blocked arteries – is the leading condition afflicting Indians, strokes, arrhythmias, and hypertensive disorders also have a high incidence. In this section, we break down the top heart conditions affecting Indians. This section captures each condition, along with a description, share of claims, growth over the last three years, as well as the high-tail cost of treatment.

Conditions are classified using the GBD 2019 framework (IHME) — the global standard for epidemiological reporting, aligned with WHO and national health data.

#### Chart: Understanding different heart conditions

The 14 condition groups in the edition's heart-related claims, sized on the page by share of claims, with the figures the chart's side panel gives for each: share of claims, median age, the share that required ICU care, and the cost of routine and of ICU treatment.

| Condition group | Share of CVD claims (%) | Claims (count) | Median age (years) | Require ICU (%) | Routine cost (₹) | ICU cost (₹) |
| --- | --- | --- | --- | --- | --- | --- |
| Ischemic Heart Disease | 54.9 | 5,459 | 59 | 47 | ₹58K | ₹1.9L |
| Stroke (Cerebrovascular Disease) | 13.3 | 1,322 | 59 | 23 | ₹69K | ₹1.7L |
| Hypertensive Diseases | 11.8 | 1,174 | 56 | 12 | ₹35K | ₹55K |
| Venous Disease | 6.3 | 627 | 48 | 22 | ₹94K | ₹1.2L |
| Other CVD | 2.8 | 277 | 55 | 18 | ₹49K | ₹4.0L |
| Arrhythmias | 1.9 | 187 | 63 | 29 | ₹58K | ₹2.9L |
| Heart Failure | 1.7 | 169 | 65 | 30 | ₹78K | ₹1.3L |
| Aortic Aneurysm & Dissection | 1.6 | 164 | 59 | 66 | ₹1.5L | ₹2.1L |
| Arterial Disease (PAD) | 1.6 | 160 | 62 | 53 | ₹45K | ₹2.7L |
| Conduction Disorders | 1.0 | 101 | 66 | 66 | ₹2.8L | ₹3.8L |
| Cardiomyopathy | 0.9 | 91 | 47 | 33 | ₹79K | ₹1.0L |
| Rheumatic Heart Disease | 0.8 | 84 | 52 | 19 | ₹46K | ₹6.2L |
| Pulmonary Heart Disease | 0.8 | 79 | 51 | 24 | ₹74K | ₹41K |
| Cardiac Arrest | 0.5 | 51 | 59 | 37 | ₹1.3L | ₹2.9L |

Sub-conditions, shown when a group is opened (21 sub-conditions in 7 groups):

| Condition group | Sub-condition | Share of CVD claims (%) | Claims (count) | Median age (years) | Require ICU (%) | Routine cost (₹) | ICU cost (₹) | What it is |
| --- | --- | --- | --- | --- | --- | --- | --- | --- |
| Ischemic Heart Disease | Coronary Artery Disease | 22.0 | 2,192 | 59 | 35 | ₹81K | ₹2.0L | Chronic narrowing of coronary arteries from plaque buildup. |
| Ischemic Heart Disease | Angina Pectoris | 14.4 | 1,432 | 59 | 51 | ₹38K | ₹1.7L | Chest pain from reduced blood flow. Warning sign of potential heart attack. |
| Ischemic Heart Disease | Acute MI (Heart Attack) | 6.4 | 634 | 58 | 24 | ₹84K | ₹2.2L | Complete blockage causing heart muscle death. Medical emergency. |
| Ischemic Heart Disease | Other IHD | 12.1 | 1,201 | 60 | 14 | ₹56K | ₹2.0L | Other ischemic conditions including silent ischemia and chronic IHD. |
| Stroke (Cerebrovascular Disease) | Ischemic Stroke | 7.4 | 735 | 59 | 11 | ₹66K | ₹1.6L | Blocked vessel cutting blood supply to brain. Most common type (80%). |
| Stroke (Cerebrovascular Disease) | Hemorrhagic Stroke | 1.8 | 182 | 58 | 25 | ₹73K | ₹2.8L | Bleeding in the brain. More severe, higher mortality. |
| Stroke (Cerebrovascular Disease) | Other Cerebrovascular | 2.5 | 251 | 58 | 8 | ₹78K | ₹1.0L | TIA (mini-stroke), cerebral aneurysm, vascular malformations. |
| Stroke (Cerebrovascular Disease) | Stroke Sequelae | 1.4 | 136 | 61 | 3 | ₹49K | ₹1.3L | Long-term effects and rehabilitation after stroke. |
| Hypertensive Diseases | Essential Hypertension | 7.8 | 772 | 55 | 7 | ₹34K | ₹55K | Primary high BP with no identifiable cause. Most common form. |
| Hypertensive Diseases | Hypertensive Crisis | 1.6 | 160 | 56 | 11 | ₹44K | ₹65K | Severely elevated BP requiring immediate treatment. |
| Hypertensive Diseases | Hypertensive Heart Disease | 1.2 | 118 | 56 | 3 | ₹33K | ₹68K | Heart damage from long-term uncontrolled hypertension. |
| Hypertensive Diseases | Other Hypertensive | 1.2 | 124 | 56 | 6 | ₹36K | ₹53K | Secondary hypertension and hypertensive kidney disease. |
| Venous Disease | Varicose Veins | 4.6 | 454 | 48 | 26 | ₹1.0L | ₹1.2L | Enlarged, twisted veins usually in legs. Often requires surgical intervention. |
| Venous Disease | Other Venous Disorders | 1.7 | 173 | 43 | 17 | ₹57K | ₹2.0L | Deep vein thrombosis, pulmonary embolism, chronic venous insufficiency. |
| Arrhythmias | Other Arrhythmias (SVT, VT) | 1.0 | 100 | 58 | 14 | ₹54K | ₹2.3L | Supraventricular and ventricular tachycardias. |
| Arrhythmias | Atrial Fibrillation & Flutter | 0.9 | 87 | 65 | 20 | ₹59K | ₹4.3L | Irregular, rapid heart rate. Major stroke risk factor. |
| Aortic Aneurysm & Dissection | Aortic Atherosclerosis | 1.2 | 118 | 59 | 67 | ₹1.5L | ₹2.1L | Plaque buildup in the aorta wall. |
| Aortic Aneurysm & Dissection | Aortic Aneurysm | 0.3 | 28 | 60 | 68 | ₹1.7L | ₹2.2L | Bulging of aorta wall. Requires monitoring or surgery. |
| Aortic Aneurysm & Dissection | Aortic Dissection | 0.2 | 18 | 57 | 56 | ₹1.4L | ₹2.0L | Tear in aorta wall. Surgical emergency. |
| Arterial Disease (PAD) | Atherosclerosis & Other | 0.8 | 80 | 62 | 10 | ₹45K | ₹1.7L | Plaque buildup in peripheral arteries. |
| Arterial Disease (PAD) | Peripheral Artery Disease | 0.8 | 80 | 62 | 28 | ₹44K | ₹2.9L | Reduced blood flow to limbs. Causes leg pain, wound healing issues. |

What each condition group is, with the risk factors and key biomarkers the chart lists for it:

- **Ischemic Heart Disease**: Reduced blood flow to the heart due to blocked or narrowed coronary arteries from atherosclerotic plaque buildup. This is what most people mean by 'heart disease.' Risk factors: Smoking, Diabetes, High BP, High LDL, Obesity, Family history. Key biomarkers: Troponin-I/T, LDL-C >100 mg/dL, HbA1c >6.5%, hsCRP, Lp(a), ApoB.
- **Stroke (Cerebrovascular Disease)**: Brain attack from disrupted blood supply. Second leading cause of death globally, top cause of adult disability. Risk factors: High BP (strongest), Atrial fibrillation, Diabetes, Smoking, High cholesterol. Key biomarkers: BP >140/90, INR, HbA1c, Lipid panel, D-dimer, Carotid IMT.
- **Hypertensive Diseases**: Chronic high blood pressure causing heart strain and organ damage. 'Silent killer' — often no symptoms until damage occurs. Risk factors: High sodium, Obesity, Inactivity, Alcohol, Stress, Family history. Key biomarkers: BP ≥130/80, Serum creatinine, Microalbuminuria, Potassium, ECG for LVH.
- **Venous Disease**: Disorders of veins including blood clots (DVT) and valve dysfunction (varicose veins). Often affects leg veins. Risk factors: Prolonged sitting/standing, Obesity, Pregnancy, Oral contraceptives, Surgery. Key biomarkers: D-dimer, Venous duplex ultrasound, CEAP classification.
- **Other CVD**: Other cardiovascular conditions including non-rheumatic valve disease, endocarditis, lymphatic disorders. Risk factors: Varies by condition. Key biomarkers: Varies by condition.
- **Arrhythmias**: Abnormal heart rhythms — too fast, too slow, or irregular electrical activity. Risk factors: Age, Hypertension, Heart disease, Thyroid disorders, Alcohol, Sleep apnea. Key biomarkers: ECG/Holter monitor, TSH, Electrolytes (K+, Mg2+), BNP, Echocardiogram.
- **Heart Failure**: Heart cannot pump enough blood to meet body's needs. Usually results from damage by IHD, hypertension, or valve disease. Risk factors: Prior MI, Hypertension, Diabetes, Obesity, Valve disease, Alcohol abuse. Key biomarkers: BNP/NT-proBNP, EF <40% (HFrEF), Troponin, Creatinine, Chest X-ray.
- **Aortic Aneurysm & Dissection**: Abnormal dilation/bulging of the aorta or tearing of its wall layers. Life-threatening if ruptures. Risk factors: Hypertension, Atherosclerosis, Smoking, Connective tissue disorders, Age >60. Key biomarkers: CT/MRI angiography, Surveillance imaging, D-dimer.
- **Arterial Disease (PAD)**: Atherosclerosis affecting arteries outside the heart — primarily legs (PAD) and other peripheral vessels. Risk factors: Smoking (strongest), Diabetes, Hypertension, High cholesterol, Age >50. Key biomarkers: ABI <0.9, CT angiography, LDL-C, HbA1c, Homocysteine.
- **Conduction Disorders**: Electrical system problems causing slow heartbeat or blocked signals. Often requires pacemaker. Risk factors: Age, Prior MI, Cardiac surgery, Lyme disease. Key biomarkers: ECG (AV block, BBB), Electrophysiology study, Lyme serology.
- **Cardiomyopathy**: Primary heart muscle disease. Heart becomes enlarged, thick, or rigid. Risk factors: Genetic mutations, Viral infections, Alcohol abuse, Pregnancy, Chemotherapy. Key biomarkers: BNP, Troponin, Echocardiogram, Cardiac MRI, Genetic testing.
- **Rheumatic Heart Disease**: Valve damage from untreated strep throat (rheumatic fever). Preventable but still affects young populations in developing countries. Risk factors: History of rheumatic fever, Poverty, Overcrowding, Limited healthcare. Key biomarkers: ASO titer, Anti-DNase B, ESR, CRP, Echocardiogram.
- **Pulmonary Heart Disease**: Right heart failure caused by lung disease or pulmonary hypertension. Risk factors: COPD, Pulmonary embolism, Sleep apnea, High altitude, Pulmonary fibrosis. Key biomarkers: BNP, D-dimer, ABG, Chest CT, Echocardiogram.
- **Cardiac Arrest**: Sudden loss of heart function. Medical emergency with high mortality if not treated immediately. Risk factors: Prior MI, Coronary artery disease, Cardiomyopathy, Arrhythmias, Drug overdose. Key biomarkers: Troponin, ABG, Lactate, Potassium, Toxicology screen.

Reference: GBD 2019 Diseases and Injuries Collaborators. The Lancet, 2020.

#### Methodology notes

- Essential Hypertension included under Hypertensive Diseases: GBD strictly separates "Essential Hypertension" (I10) from "Hypertensive Heart Disease" (I11). We combined them because: (1) Essential HTN is the precursor to hypertensive heart disease, (2) Both represent the hypertension disease burden, (3) Improves statistical power for analysis.
- Arrhythmias kept separate from Conduction Disorders: Though both are electrical disorders, they have different mechanisms (rhythm generation vs. signal transmission), different treatments (ablation/drugs vs. pacemakers), and vastly different costs (₹63K vs ₹286K median).
- Venous Disease retained as separate category: GBD groups venous disease under "Other CVD", but given its distinct clinical profile (younger patients, elective procedures) and significant volume (6.1%), we maintain it separately.
- Aortic Aneurysm & Dissection: GBD 2019 strictly defines Aortic Aneurysm as I71 only (aneurysm and dissection of aorta). We have expanded this to include I70.0 (Atherosclerosis of aorta) based on shared anatomical focus and similar clinical acuity in hospitalized patients. This is a clinical grouping, not a strict GBD classification.

### Section 03 · Age distribution

**Heart disease sets in as early as the 30s.**

Our horizon chart captures how different heart conditions manifest across age groups. While hospitalisations peak in the 50s and 60s, heart disease isn't just an older person's problem anymore.

Venous Disorders and Rheumatic Conditions see significant incidence amongst younger Indians, and conditions like Ischemic Heart Disease, Strokes, and Aneurysms that show up among the elderly, could now impact patients as early as 30 years of age.

#### Chart: Age Distribution of CVD Conditions

For each heart condition, the percentage of its claims that fall in each age band.

| Condition | 0-10 (%) | 11-20 (%) | 21-30 (%) | 31-40 (%) | 41-50 (%) | 51-60 (%) | 61-70 (%) | 71-80 (%) | 81-90 (%) |
| --- | --- | --- | --- | --- | --- | --- | --- | --- | --- |
| Ischemic Heart Disease | 0.0 | 0.0 | 1.3 | 3.1 | 4.3 | 15.9 | 13.7 | 4.2 | 0.3 |
| Stroke | 0.5 | 0.1 | 2.9 | 3.6 | 5.8 | 16.3 | 17.3 | 7.1 | 0.5 |
| Hypertensive Diseases | 0.0 | 0.0 | 2.8 | 5.6 | 5.2 | 17.7 | 12.1 | 2.8 | 0.3 |
| Venous Disease | 0.3 | 0.3 | 10.4 | 8.4 | 5.9 | 12.6 | 6.9 | 2.1 | 0.0 |
| Aortic Aneurysm | 0.0 | 0.0 | 3.0 | 7.9 | 11.6 | 26.2 | 27.4 | 9.2 | 1.2 |
| Arterial Disease | 0.6 | 0.0 | 1.3 | 1.9 | 2.5 | 17.5 | 17.5 | 8.8 | 0.6 |
| Heart Failure | 0.0 | 0.0 | 2.4 | 2.4 | 4.1 | 21.9 | 32.5 | 22.5 | 2.4 |
| Arrhythmias | 0.0 | 0.0 | 2.1 | 5.9 | 6.4 | 7.5 | 16.0 | 14.4 | 0.5 |
| Rheumatic Heart Disease | 2.4 | 0.0 | 19.1 | 3.6 | 7.1 | 27.4 | 9.5 | 1.2 | 0.0 |
| Conduction Disorders | 0.0 | 0.0 | 1.0 | 2.0 | 0.0 | 8.9 | 19.8 | 13.9 | 2.0 |
| Pulmonary Heart Disease | 0.0 | 0.0 | 11.4 | 15.2 | 0.0 | 20.3 | 7.6 | 2.5 | 0.0 |

For each condition these age-band percentages add up to less than 100%, from 42.9% (Ischemic Heart Disease) to 88.2% (Heart Failure); the edition does not show where the rest of the claims fall.

Chart summary, as shown on the page: peak age range 51-70; average share of a condition's claims at ages 51-70: 33.9%; highest cell: Heart Failure at 61-70, 33%; early onset (more than 5% of a condition's claims at ages 21-30 or 31-40): 6 conditions.

Key insight: Heart disease is becoming a young person's disease. The 31-40 age band shows significant incidence across nearly all cardiovascular conditions — with some conditions like pulmonary heart disease and venous disorders hitting hardest in the 30s.

### Section 04 · Gender analysis

**Men show a greater risk for Ischemic Heart Disease, but other conditions are gender neutral.**

Men file 2.3x more CVD claims than women. That said, the raw ratio masks a more nuanced story. Using odds ratios — which control for the baseline gender skew — we find that only Ischemic Heart Disease (heart attacks) is truly male-predominant. Most other conditions are gender-neutral or female-predominant.

#### Chart: Only one heart condition is truly male-dominant. The rest tell a different story.

The odds ratio of each condition in men compared with women, adjusted for the baseline gender skew in claims, with its 95% confidence interval. An odds ratio above 1.0 means the condition is more common in men and below 1.0 more common in women; if the confidence interval crosses 1.0, the difference is not statistically significant.

| Condition | Odds ratio, men vs women | 95% CI, lower | 95% CI, upper | Statistically significant | Age, women (years) | Age, men (years) |
| --- | --- | --- | --- | --- | --- | --- |
| Ischemic Heart Disease | 1.58 | 1.35 | 1.86 | Yes | 57 | 58 |
| Cerebrovascular Disease | 1.11 | 0.89 | 1.38 | No | 54 | 57 |
| Aortic Aneurysm | 1.06 | 0.74 | 1.54 | No | 51 | 57 |
| Arterial Disease | 0.98 | 0.69 | 1.40 | No | 56 | 58 |
| Conduction Disorders | 0.91 | 0.44 | 1.89 | No | 66 | 63 |
| Venous Disease | 0.77 | 0.57 | 1.04 | No | 51 | 42 |
| Pulmonary Heart Disease | 0.70 | 0.33 | 1.51 | No | 53 | 44 |
| Hypertensive Diseases | 0.61 | 0.49 | 0.75 | Yes | 55 | 53 |
| Arrhythmias | 0.58 | 0.36 | 0.92 | Yes | 55 | 60 |
| Heart Failure | 0.58 | 0.39 | 0.86 | Yes | 61 | 64 |

The two age columns are the ages the chart prints beside each row for women and for men.

Key insight: Only Ischemic Heart Disease is statistically male-predominant (OR 1.58). Hypertensive Diseases, Arrhythmias, and Heart Failure all skew female after controlling for baseline gender distribution. Most other conditions show no significant gender difference.

### Section 05 · Severity impact

**Critical hospitalisations can wipe out years of savings.**

A single heart-related hospitalisation can range from a ₹38K mild episode to a ₹4.2L critical event — wiping out 4.5 months to over 4 years of household savings. Some extreme cases can cost up to ₹25-28L, translating to decades of savings lost.

To understand the spectrum of heart-related hospitalisation, we classify claims into four categories – keeping length of stay, cost of treatment, and type of treatment required. This approach mirrors established methodologies, including the Case Mix Index (CMI) — hospital severity adjustment using administrative data, All Patient Refined DRG (APR-DRG) — 4-tier severity system used by CMS, and APACHE scoring principles — combining multiple indicators for severity assessment.

#### Understanding Severity

Heart disease hospitalisations are classified into four severity levels based on clinical complexity, interventions required, and resource utilisation.

| Severity level | In short | Criteria |
| --- | --- | --- |
| TIL 1 (Mild) | Short stay, conservative treatment | LOS ≤ 3 days, No ICU, Conservative/Unknown treatment |
| TIL 2 (Moderate) | Extended stay or intervention | LOS 4-7 days OR Interventional procedure (no ICU) |
| TIL 3 (Severe) | ICU or major surgery | ICU admission OR Major surgery OR (LOS ≥ 8 + PCI) |
| TIL 4 (Critical) | ICU with complex intervention | ICU + (Major surgery OR LOS ≥ 10 OR Cost > P85) |

TIL stands for Treatment Intensity Level. LOS is length of stay in days; P85 is the 85th percentile of cost; PCI is percutaneous coronary intervention (angioplasty).

Key findings:

- 8% of cases are Severe or Critical, but consume disproportionate resources
- Critical hospitalisations cost 11× more and last 4× longer
- 13+ years of savings can be wiped out by a critical cardiac event

#### Chart: Years of Savings Lost

Years of household savings that one heart-related hospitalisation would use up, by severity level: the median, with the interquartile range. The chart notes that this is based on average Indian household savings rates.

| Severity level | Median (years) | 25th percentile (years) | 75th percentile (years) |
| --- | --- | --- | --- |
| TIL 1 (Mild) | 1.1 | 0.4 | 2.8 |
| TIL 2 (Moderate) | 4.5 | 1.8 | 11.4 |
| TIL 3 (Severe) | 7.6 | 3.6 | 15.9 |
| TIL 4 (Critical) | 13.4 | 6.3 | 24.0 |

#### Chart: Total Cost Distribution

The cost of one heart-related hospitalisation by severity level: median, interquartile range, and the lowest and highest cost.

| Severity level | Median (₹) | 25th percentile (₹) | 75th percentile (₹) | Minimum (₹) | Maximum (₹) |
| --- | --- | --- | --- | --- | --- |
| TIL 1 (Mild) | ₹38K | ₹15K | ₹95K | ₹1K | ₹5.0L |
| TIL 2 (Moderate) | ₹87K | ₹45K | ₹1.6L | ₹5K | ₹8.0L |
| TIL 3 (Severe) | ₹1.3L | ₹60K | ₹2.6L | ₹10K | ₹15.0L |
| TIL 4 (Critical) | ₹4.2L | ₹2.1L | ₹5.6L | ₹50K | ₹50.0L |

#### Chart: Median Hospital Stay

Length of hospital stay by severity level. On the page, the violin shapes are drawn from these summary values.

| Severity level | Median (days) | 25th percentile (days) | 75th percentile (days) | Minimum (days) | Maximum (days) |
| --- | --- | --- | --- | --- | --- |
| TIL 1 (Mild) | 3 | 2 | 4 | 1 | 7 |
| TIL 2 (Moderate) | 5 | 3 | 7 | 2 | 12 |
| TIL 3 (Severe) | 7 | 5 | 10 | 3 | 18 |
| TIL 4 (Critical) | 12 | 8 | 18 | 5 | 30 |

### Section 06 · Cost by condition

**How much does treatment cost for different heart conditions?**

Treatment costs vary by condition – and severity of hospitalization. While a simple hospitalization with a couple of days' stay at the hospital can cost under a lakh, treatment for complex cases involving surgery and ICU admissions can be as high as ₹4-7L on average.

#### Chart: Treatment Costs by Severity

The overall median cost per claim for each condition, and the range in which the middle 50% of costs fall (25th to 75th percentile) at each treatment intensity level: TIL 1 is routine care, TIL 2 procedures, TIL 3 surgery and TIL 4 ICU care with complex surgery.

| Condition | Overall median (₹) | TIL 1 (₹) | TIL 2 (₹) | TIL 3 (₹) | TIL 4 (₹) |
| --- | --- | --- | --- | --- | --- |
| ALL CVD (all conditions) | ₹86K | ₹21K – ₹1.0L | ₹52K – ₹3.1L | ₹65K – ₹3.4L | ₹1.9L – ₹4.6L |
| IHD | ₹97K | ₹20K – ₹1.1L | ₹61K – ₹3.4L | ₹59K – ₹3.7L | ₹2.0L – ₹3.8L |
| Stroke | ₹89K | ₹30K – ₹88K | ₹46K – ₹2.0L | ₹77K – ₹1.8L | ₹1.5L – ₹5.7L |
| Hypertension | ₹45K | ₹16K – ₹51K | ₹40K – ₹1.2L | ₹37K – ₹84K | ₹97K – ₹4.9L |
| Venous Disease | ₹1.1L | ₹66K – ₹1.9L | ₹41K – ₹2.0L | ₹1.0L – ₹1.1L | ₹5.3L – ₹6L |
| Aortic Aneurysm | ₹2.2L | ₹19K – ₹60K | ₹2.0L – ₹3.7L | ₹94K – ₹5.9L | ₹1.8L – ₹4.4L |
| Arterial Disease | ₹1.1L | ₹22K – ₹1.0L | ₹57K – ₹3.0L | ₹3.0L – ₹11.1L | ₹3.0L – ₹8.0L |
| Arrhythmias | ₹75K | ₹26K – ₹65K | ₹68K – ₹3.9L | ₹1.0L – ₹1.7L | ₹2.7L – ₹11.5L |
| Heart Failure | ₹87K | ₹29K – ₹73K | ₹61K – ₹1.5L | ₹79K – ₹1.6L | ₹2.2L – ₹2.9L |
| Conduction | ₹3.3L | ₹29K – ₹4.4L | ₹1.6L – ₹5.0L | ₹1.3L – ₹4.9L | ₹2.7L – ₹4.1L |
| Rheumatic Heart | ₹1.2L | ₹19K – ₹50K | ₹77K – ₹8.6L | ₹3.4L – ₹6.5L | ₹9.6L+ |

IHD is ischemic heart disease. For Venous Disease TIL 3, Venous Disease TIL 4, Arterial Disease TIL 4, Arrhythmias TIL 4 and Heart Failure TIL 4, the source data gives the lowest and highest cost instead of the 25th to 75th percentile. Rheumatic Heart TIL 4 is a single claim, shown as ₹9.6L+.

Key insight: Treatment costs vary dramatically by condition and intensity. TIL 4 cases can cost 10× more than TIL 1 cases.

### Section 07 · Cost outliers

**The tail end costs of heart disease treatment.**

While median costs provide a baseline, the tail end of the cost distribution reveals extreme variations. Some patients face costs 5-10x higher than the median, highlighting the unpredictable financial burden of heart disease.

For instance, a third of heart hospitalizations are greater than 2x the median cost, and a tenth are greater than 5x the cost. This analysis focuses on these outliers, the patients who bear the heaviest economic weight.

#### Chart: Treatment Cost Deviation from Median

How far each claim's cost sits above or below the median cost for its condition group. Deviation from median (%) is the claim's cost minus the median, divided by the median. The chart plots individual claims as dots; this table gives the statistics the chart shows for each condition filter, not the individual claims.

| Condition group | Claims (count) | Median cost (₹) | Above 2× median (%) | Above 5× median (%) | 90th percentile cost (₹) |
| --- | --- | --- | --- | --- | --- |
| All CVD | 8,941 | ₹72K | 33.5 | 10.9 | ₹4.1L |
| Ischemic Heart Disease | 4,931 | ₹78K | 39.6 | 12.4 | ₹4.3L |
| Cerebrovascular Disease | 1,153 | ₹78K | 28.6 | 10.3 | ₹4.0L |
| Hypertensive Diseases | 1,087 | ₹37K | 23.7 | 7.5 | ₹1.4L |
| Venous Disease | 546 | ₹1.0L | 18.5 | 1.5 | ₹2.7L |
| Arterial Disease | 282 | ₹1.5L | 22.3 | 8.2 | ₹6.4L |
| Arrhythmias | 175 | ₹69K | 34.9 | 16.6 | ₹4.7L |
| Heart Failure | 146 | ₹86K | 19.2 | 6.2 | ₹2.9L |
| Conduction Disorders | 94 | ₹3.0L | 11.7 | 1.1 | ₹6.2L |

The All CVD statistics cover all 8,941 claims, including Other Heart Disease (145 claims) and Other Circulatory (88 claims), which have no filter of their own and are not plotted in the All CVD view. The All CVD median is the median of all 8,941 claims, while its shares above 2× and 5× compare each claim with the median for its own condition group.

Key insight: 34% of all CVD claims cost more than 2× the median, revealing a substantial long-tail of high-cost treatments.

### Understanding heart risk

**Cardiovascular risk builds up silently over decades — its factors are visible long before symptoms appear.**

An analysis of the burden of heart disease would be incomplete without addressing heart risk. Heart disease builds up silently over decades, often exacerbated by our lifestyles. To understand the risk of heart disease among Indians, we analysed biomarker data across 10,248 health checkups.

Modern cardiology recognizes that CVD risk is multifactorial, requiring assessment across multiple biological pathways. We adopt a 4-Domain Framework based on American Heart Association (AHA) guidelines, European Society of Cardiology (ESC) recommendations, and Global Burden of Disease (GBD) risk factor framework.

#### The 4 Domains of CVD Risk

| Domain | What It Measures | Biomarkers Used | Clinical Significance |
| --- | --- | --- | --- |
| Atherogenic | Plaque-building particles | Non-HDL Cholesterol, ApoB | Particles that deposit in arterial walls, causing blockages |
| Protective | Plaque-clearing function | HDL Cholesterol, ApoA1 | Reverse cholesterol transport — clears plaque from arteries |
| Inflammation | Vascular damage | hs-CRP, Homocysteine | Chronic inflammation accelerates atherosclerosis |
| Metabolic/Diabetic | Insulin resistance continuum | Triglycerides, Fasting Glucose, HbA1c | Metabolic dysfunction accelerates atherosclerosis |

### Section 08 · CVD risk factors

**Traditional cholesterol testing provides an incomplete picture of cardiovascular risk.**

62% of Indians showed high risk when measured by ApoA/ApoB ratios, a higher number compared to Atherogenic (23%) and Protective (40%) risk. Traditional health checkups do not measure ApoA/ApoB ratios, relying instead on HDL and non-HDL cholesterol as relevant biomarkers.

This implies that the average Indian is at greater risk than reported, especially given that the INTERHEART study found ApoB/ApoA1 ratio to be the strongest lipid predictor of heart attack, superior to LDL, HDL, or total cholesterol.

This interactive section lets you compare heart risk across different biomarker domains.

#### Chart: Five Risk Domains, One Pattern

How the people in the health checkup data are spread across risk levels for five biomarkers, one for each risk domain, with the cardiovascular risk the chart gives for each level.

| Domain | Biomarker | Risk level | Range | Share of people (%) | CVD risk vs baseline | What it means |
| --- | --- | --- | --- | --- | --- | --- |
| Atherogenic Risk | Non-HDL Cholesterol | Optimal | < 130 mg/dL | 45.8 | Baseline (1.0×) | Low plaque-building burden |
| Atherogenic Risk | Non-HDL Cholesterol | Elevated | 130 – 160 mg/dL | 30.2 | 1.5 – 2.0× | Moderate atherogenic load |
| Atherogenic Risk | Non-HDL Cholesterol | High | > 160 mg/dL | 23.9 | 2.0 – 3.0× | High plaque risk, intervention needed |
| Protective Function | HDL Cholesterol | Optimal | ≥ 40 mg/dL | 38.9 | Baseline (1.0×) | Good protective function |
| Protective Function | HDL Cholesterol | Low | 35 – 40 mg/dL | 21.6 | 1.5× | Reduced protection |
| Protective Function | HDL Cholesterol | Very Low | < 35 mg/dL | 39.5 | 2.0 – 2.5× | Poor protection, intervention needed |
| Lipid Balance | ApoB/ApoA1 Ratio | Optimal | < 0.7 | 20.1 | Baseline (1.0×) | Net protective — clearing cholesterol |
| Lipid Balance | ApoB/ApoA1 Ratio | Moderate | 0.7 – 0.8 | 17.7 | 1.5 – 2.0× | Borderline — balance tipping |
| Lipid Balance | ApoB/ApoA1 Ratio | High Risk | > 0.8 | 62.2 | 2.0 – 3.0× | Net atherogenic — depositing cholesterol |
| Inflammation | hs-CRP | Low Risk | < 1.0 mg/L | 26.5 | Baseline (1.0×) | Minimal vascular inflammation |
| Inflammation | hs-CRP | Moderate Risk | 1.0 – 3.0 mg/L | 37.5 | 2.0× | Chronic low-grade inflammation |
| Inflammation | hs-CRP | High Risk | > 3.0 mg/L | 35.9 | 3.0×+ | Significant inflammation, intervention needed |
| Metabolic Health | HbA1c | Normal | < 5.7% | 78.9 | Baseline (1.0×) | Normal long-term glucose control |
| Metabolic Health | HbA1c | Pre-Diabetic | 5.7 – 6.4% | 14.2 | ~1.5× | Pre-diabetes, intervention critical |
| Metabolic Health | HbA1c | Diabetic | ≥ 6.5% | 6.9 | ~2.0×+ | Diabetes mellitus |

**Atherogenic Risk (Non-HDL Cholesterol).** 24% have high atherogenic burden, placing them at 2-3× higher risk for heart attack and stroke. Atherogenic particles are lipoproteins that penetrate the arterial wall and initiate plaque formation. The more particles, the higher the risk of Coronary Artery Disease (blocked heart arteries), Heart Attack (Myocardial Infarction), Ischemic Stroke (blocked brain arteries), and Peripheral Artery Disease (blocked leg arteries).

**Protective Function (HDL Cholesterol).** 61% have suboptimal HDL levels, reduced ability to clear cholesterol from arterial walls. HDL particles perform 'reverse cholesterol transport' — they remove cholesterol from arterial plaques and transport it back to the liver for disposal. Low protective function means reduced plaque clearance, accelerated atherosclerosis progression, and higher risk of cardiovascular events even when "bad" cholesterol is controlled.

**Lipid Balance (ApoB/ApoA1 Ratio).** 80% have unfavorable ApoB/ApoA1 ratio, indicating net cholesterol deposition in arterial walls. ApoB/ApoA1 Ratio measures the balance between atherogenic particles (ApoB) and protective particles (ApoA1). Instead of looking at 'bad' and 'good' cholesterol separately, the ratio tells you whether you're net depositing (atherogenic) or net clearing (protective) cholesterol from arteries. The INTERHEART study found ApoB/ApoA1 ratio to be the strongest lipid predictor of heart attack, superior to LDL, HDL, or total cholesterol. Reference: https://pubmed.ncbi.nlm.nih.gov/18640459/

**Inflammation (hs-CRP).** 73% show elevated inflammatory markers, among patients with suboptimal metabolic health. Chronic low-grade inflammation is now recognized as a key driver of atherosclerosis. Inflammation damages the arterial endothelium (inner lining), promotes plaque formation and instability, and increases risk of plaque rupture. The landmark JUPITER and CANTOS trials proved that reducing inflammation (even without lowering cholesterol) reduces cardiovascular events. C-Reactive Protein (CRP) is a protein produced by the liver in response to inflammation. hs-CRP detects low-level chronic inflammation that standard CRP tests miss. The AHA and CDC classify hs-CRP as a marker for CVD risk stratification as elevated levels doubles CVD risk, independent of cholesterol. Note: Data filtered to patients with High LDL OR Low HDL OR Elevated HbA1c.

**Metabolic Health (HbA1c).** 21% are pre-diabetic or diabetic, each 1% increase in HbA1c associated with ~15% increased CVD risk. The metabolic-diabetic spectrum represents a progressive continuum of insulin resistance that accelerates cardiovascular damage. Elevated triglycerides lead to the formation of small, dense LDL (more atherogenic). High glucose levels cause direct endothelial damage, resulting in easier plaque deposition. Insulin resistance translates to chronic low-grade inflammation, and advanced glycation leads to arterial stiffening and dysfunction. Each 1% increase in HbA1c is associated with ~15% increased CVD risk.

### Section 09 · Risk by age

**Cardiovascular risk starts decades before symptoms appear.**

Risk factors don't wait for middle age. Analysis of 12,000+ health checkups reveals that lipid abnormalities are already prevalent in the 20s, atherogenic damage accelerates sharply in the 30s, and metabolic dysfunction follows a classic late-onset pattern.

55% of 21-30 year olds already have unfavorable ApoB/ApoA1 ratios, the strongest lipid predictor of heart attack. By the 30s, nearly two-thirds show elevated atherogenic burden. These aren't people with symptoms; they're young professionals getting routine checkups.

#### Chart: Risk by age, for each risk domain

For five biomarker domains, the share of people tested in each age band who are at high risk (high or very high, shown in red) and who are at suboptimal or worse levels (yellow and red). The chart shows one domain at a time.

| Age band | 21-30 | 31-40 | 41-50 | 51-60 | 61-70 | 71+ |
| --- | --- | --- | --- | --- | --- | --- |
| People tested (count) | 6,400 | 3,700 | 875 | 586 | 247 | 35 |

| Domain | Biomarker | Measure | 21-30 (%) | 31-40 (%) | 41-50 (%) | 51-60 (%) | 61-70 (%) | 71+ (%) |
| --- | --- | --- | --- | --- | --- | --- | --- | --- |
| Atherogenic | Non-HDL Cholesterol | High risk | 17.8 | 30.8 | 31.5 | 33.3 | 29.1 | 20.0 |
| Atherogenic | Non-HDL Cholesterol | Suboptimal or worse | 45.8 | 64.1 | 66.2 | 64.8 | 59.9 | 45.7 |
| Protective | HDL Cholesterol | High risk | 37.6 | 42.5 | 41.4 | 39.9 | 35.0 | 40.0 |
| Protective | HDL Cholesterol | Suboptimal or worse | 58.6 | 65.6 | 62.7 | 58.5 | 57.7 | 51.4 |
| Lipid Balance | ApoB/ApoA1 Ratio | High risk | 55.0 | 66.8 | 67.2 | 62.5 | 61.0 | 50.0 |
| Lipid Balance | ApoB/ApoA1 Ratio | Suboptimal or worse | 73.5 | 83.2 | 84.4 | 86.1 | 78.0 | 50.0 |
| Inflammation | hs-CRP | High risk | 8.6 | 9.7 | 12.0 | 10.3 | 10.7 | 4.8 |
| Inflammation | hs-CRP | Suboptimal or worse | 66.2 | 74.4 | 75.9 | 79.4 | 77.9 | 57.1 |
| Metabolic | HbA1c | High risk | 1.9 | 6.0 | 18.8 | 28.3 | 46.6 | 47.6 |
| Metabolic | HbA1c | Suboptimal or worse | 10.5 | 23.1 | 42.2 | 63.7 | 76.0 | 66.7 |

What the chart says for each domain:

- **Atherogenic (Non-HDL Cholesterol)**: Atherogenic damage accelerates in your 30s. Risk nearly doubles from 18% to 31% between 20s and 30s, then plateaus.
- **Protective (HDL Cholesterol)**: Low HDL is everyone's problem — not age-related. 38-43% have very low HDL across all ages. This is a population-wide issue.
- **Lipid Balance (ApoB/ApoA1 Ratio)**: Lipid imbalance starts in your 20s. 55% of 21-30 year olds already have unfavorable ratios — the strongest predictor of heart attack.
- **Inflammation (hs-CRP)**: Chronic inflammation builds over decades. Suboptimal levels climb from 66% to 79% between 20s and 50s.
- **Metabolic (HbA1c)**: Diabetes risk climbs steeply with age. High-risk jumps from 2% (20s) to 47% (60s+). Classic late-onset pattern.

### Section 10 · Gender risk

**Heart risk domains by gender.**

Gender differences in cardiovascular risk aren't uniform — they vary by risk domain. Men dominate atherogenic risk, while women show higher rates of low protective cholesterol and inflammation.

Atherogenic risk is male-dominated – 29% of men vs 15% of women have high Non-HDL cholesterol. Testosterone promotes visceral fat and atherogenic lipid profiles. 52% of women fall below gender-appropriate HDL thresholds vs 33% of men. 3% of women have elevated hs-CRP compared to 8% of men, consistent with research. Metabolic risk is gender-neutral: Diabetes risk (HbA1c) shows no meaningful gender difference.

#### Chart: High/Very High Risk: Who's at greatest danger?

The share of men and of women at high or very high risk in each risk domain, the chart's default view. The chart marks a gender as meaningfully higher when the gap is more than 5 percentage points.

| Domain | Biomarker | Men (%) | Women (%) | Gap (percentage points) | Meaningfully higher in |
| --- | --- | --- | --- | --- | --- |
| Atherogenic | Non-HDL Cholesterol | 28.5 | 15.4 | 13.1 | Men |
| Protective | HDL Cholesterol | 32.9 | 51.6 | 18.7 | Women |
| Lipid Balance | ApoB/ApoA1 Ratio | 62.1 | 62.6 | 0.5 | Neither |
| Inflammation | hs-CRP | 7.5 | 12.6 | 5.1 | Women |
| Metabolic | HbA1c | 6.9 | 7.0 | 0.1 | Neither |

Key insight: Men accumulate atherogenic cholesterol faster (29% vs 15%), while women struggle more with protective HDL (52% vs 33% at risk) and inflammation markers.

Key findings:

- 29% of men have elevated Non-HDL cholesterol vs only 15% of women — nearly double the rate.
- Women struggle more with protective HDL: 52% fall below thresholds vs 33% of men.
- Women show higher inflammation: 13% have elevated hs-CRP vs 8% of men.

#### Chart: Suboptimal Levels: Who needs attention?

The share of men and of women at suboptimal or worse levels in each risk domain, the chart's second view. The chart marks a gender as meaningfully higher when the gap is more than 5 percentage points.

| Domain | Biomarker | Men (%) | Women (%) | Gap (percentage points) | Meaningfully higher in |
| --- | --- | --- | --- | --- | --- |
| Atherogenic | Non-HDL Cholesterol | 60.7 | 42.1 | 18.6 | Men |
| Protective | HDL Cholesterol | 57.3 | 67.9 | 10.6 | Women |
| Lipid Balance | ApoB/ApoA1 Ratio | 78.9 | 82.0 | 3.1 | Neither |
| Inflammation | hs-CRP | 68.2 | 73.8 | 5.6 | Women |
| Metabolic | HbA1c | 20.6 | 22.2 | 1.6 | Neither |

Key insight: At suboptimal levels, 61% of men show concerning Non-HDL cholesterol vs 42% of women. The protective HDL deficit in women persists (68% vs 57%).

Key findings:

- 61% of men have suboptimal Non-HDL levels vs 42% of women — a major gender gap.
- 68% of women have suboptimal HDL levels vs 57% of men, confirming the protective deficit pattern.
- Most of the population (79-82%) shows unfavorable ApoB/ApoA1 ratios regardless of gender.

### Section 11 · Prevention window

**Heart disease is decades in the making.**

By comparing biomarker data (to identify when greater than 50% of the population show suboptimal levels) with claims data (the median age when hospitalization occurs), we quantify the prevention window — the years of opportunity between early risk detection and clinical events.

Half the population shows cardiovascular risk factors in their 20s and 30s. Hospitalization doesn't occur until age 59 on average. That's up to four decades of preventable progression that we often ignore.

#### Chart: Heart disease is decades in the making

For each risk domain, the age at which at least half of the people tested show suboptimal levels (risk onset), the median age of a heart-related hospitalisation in the claims, and the years between the two (the prevention window).

| Domain | Biomarker | Risk onset age (years) | Median hospitalisation age (years) | Prevention window (years) |
| --- | --- | --- | --- | --- |
| Protective | HDL Cholesterol | 20 | 59 | 39 |
| Inflammation | hs-CRP | 21 | 59 | 38 |
| Lipid Balance | ApoB/ApoA1 Ratio | 23 | 59 | 36 |
| Atherogenic | Non-HDL Cholesterol | 28 | 59 | 31 |
| Metabolic | HbA1c | 43 | 59 | 16 |

Note: Inflammation filtered to patients with suboptimal lipid OR metabolic markers. Risk onset = first age where ≥50% of cohort shows suboptimal biomarkers.

Key insight: Lipid and inflammation risk appears by early 20s. Metabolic risk surfaces in 40s. All converge at hospitalization around age 59.

### Conclusion

Most cardiac hospitalisations in this report were preceded by years of detectable, treatable risk. While the median patient is hospitalised at 59, their biomarkers were most likely abnormal by 28. That's three decades where intervention was possible.

Whether we catch it during a routine health check-up or after a critical hospitalisation is up to us. The economics of prevention have never been clearer.

## About the data

This edition is built from Plum's de-identified health insurance claims and health checkup results. The headline cohort is 9,534 heart-related (cardiovascular) claims from 7,402 unique patients, with a total amount claimed of ₹148.34 crore; individual charts use their own subsets and counts (the 14 condition groups' claim counts sum to 9,945, the cost-outlier analysis covers 8,941 claims and the gender odds ratios cover 2,967 patients). Conditions are grouped into 14 categories adapted from the Global Burden of Disease (GBD) 2019 framework from IHME, with four stated deviations: essential hypertension is counted under hypertensive diseases, arrhythmias are kept separate from conduction disorders, venous disease is kept as its own category, and the aortic aneurysm group also includes atherosclerosis of the aorta (I70.0), which the edition calls a clinical grouping rather than a strict GBD classification.

The headline total is the amount claimed. The cost charts show cost per claim or per hospitalisation as medians, interquartile ranges (25th to 75th percentile) and multiples of the median cost for the claim's condition group; the edition does not say whether these costs are claimed, approved or paid amounts. Hospitalisations are sorted into four severity levels, called Treatment Intensity Levels (TIL), using length of stay, ICU admission, type of treatment and cost. The edition defines them as follows: mild (TIL 1) is a stay of up to 3 days with no ICU and conservative or unrecorded treatment; moderate (TIL 2) is a 4 to 7 day stay or an interventional procedure, without ICU; severe (TIL 3) is an ICU admission, major surgery, or a stay of 8 days or more with PCI; critical (TIL 4) is an ICU admission combined with at least one of major surgery, a stay of 10 days or more, or a cost above the 85th percentile.

The risk sections use biomarker results from routine health checkups. The edition groups them using a four-domain framework based on American Heart Association, European Society of Cardiology and GBD risk factor guidance, charted as atherogenic (non-HDL cholesterol), protective (HDL cholesterol), inflammation (hs-CRP) and metabolic (HbA1c), and adds a lipid balance domain (the ApoB/ApoA1 ratio), which it supports with the INTERHEART study. Far fewer people had an ApoB/ApoA1 result (826) than a cholesterol result (about 11,900), and the hs-CRP results are limited to people with high LDL, low HDL or elevated HbA1c. The prevention window compares the first age at which at least half of the people tested show suboptimal levels with the median age of heart-related hospitalisation in the claims, which is 59.

This edition uses de-identified claims and health checkup records: names, phone numbers, email addresses, policy numbers and other direct identifiers do not appear in its analysis or charts. The edition's privacy statement also says that rare combinations are grouped and that every chart is reviewed before publication. The edition describes the analysis as an ongoing process and asks readers to report discrepancies to datalabs@plumhq.com.

- Dataset: Plum DataLabs heart disease claims cohort. 9,534 heart-related health insurance claims from 7,402 patients in Plum's de-identified claims data, with ₹148.34 crore claimed, analysed alongside biomarker results from routine health checkups.
- Claims: 9,534
- Patients: 7,402
- Measures: amount claimed, cost per claim, condition (14 groups adapted from GBD 2019), age, gender, severity level (TIL 1 to 4), length of hospital stay, ICU admission, checkup biomarkers (non-HDL and HDL cholesterol, ApoB/ApoA1 ratio, hs-CRP, HbA1c)

## How to cite

Ganapathi Ramanathan and Saurabh Arora, "Investigating Heart Disease: The burden, costs, and early risk", DataLabs by Plum, 2026. https://www.plumhq.com/datalabs/heart-health

## Further reading on plumhq.com

- [India's Corporate Leaders Have a Heart Disease Problem They're Likely Ignoring](https://www.plumhq.com/library/indias-corporate-leaders-heart-disease-problem): A Plum Library article on heart disease and chronic conditions among working professionals.
- [Employee health checkups at home](https://www.plumhq.com/health-checkups): At-home health checkups for teams, with test panels, scheduling and reports.
- [Preventive health check-up for employees: full guide](https://www.plumhq.com/blog/preventive-health-check-up-for-employees): A guide to routine check-ups that look for health risks before they need hospital care.
- [What is critical illness cover?](https://www.plumhq.com/blog/critical-illness-cover): How a critical illness policy pays a one-time amount on diagnosis of a life-threatening illness.
- [The Standard of Employee Benefits 2026–27](https://www.plumhq.com/standard-of-employee-benefits): Plum's India report benchmarking how employers fund employee health benefits.