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Epidemiology and burden

TL;DR — HHD burden cannot be represented by one prevalence number because modeled HHD, coded HHD, imaging-defined remodeling and hypertension exposure have different denominators. GBD 2019 estimated 14.35 million prevalent HHD cases, 0.85 million deaths and 14.56 million DALYs among adults aged 60–89 in 2019; prevalence rates rose while mortality and DALY rates fell over 1990–2019 (Yang 2023, PMID 37698022). GBD 2021 analyses estimate that population growth and aging continued to raise absolute burden even when age-standardized mortality declined (Liu 2025, PMID 40604684; Li 2025, PMID 41350658). Lower-SDI settings, women at older ages and populations with high BMI carry disproportionate modeled burden, but estimates are sensitive to cause attribution, input completeness and model version. Clinical phenotype surveillance remains much thinner than modeled burden surveillance.

1. Four epidemiologies, not one

Layer Unit measured Typical source Interpretable output
Exposure Elevated blood pressure Representative measurement surveys Hypertension prevalence, awareness, treatment, control
Subclinical phenotype LV mass, geometry, strain, diastolic function, fibrosis Cohort imaging Prevalence of a prespecified cardiac phenotype
Clinical syndrome HF, AF, ischemia with attributed hypertension Clinical cohorts and records Incidence/outcomes under a stated diagnostic rule
Population attribution HHD cause, deaths, DALYs Vital registration plus GBD modeling Modeled burden by place, age, sex and time

The exposure population is much larger than the HHD population. NCD-RisC pooled 1,201 representative studies with 104 million participants to estimate hypertension prevalence and treatment from 1990–2019, but it did not image those participants for HHD (NCD-RisC 2021, PMID 34450083). Mortality interpretation also benefits from multiple-cause methods: record linkage can redistribute deaths assigned to HF, and Brazilian certificates show hypertensive disease in several causal positions (Bierrenbach 2019, PMID 31166417; Villela 2018, PMID 29870833).

The clinical phenotype also extends beyond LVH to fibrosis, atrial and ventricular remodeling and functional change, making study-to-study prevalence dependent on the chosen case definition (Nwabuo 2020, PMID 32016791; Masenga 2023, PMID 37342440).

2. Global estimates: what the numbers mean

Estimate Population/year Result Interpretation boundary
Older-adult HHD prevalence Age 60–89, global, 2019 14.35 million prevalent cases GBD 2019 modeled HHD, not measured echo prevalence
Older-adult HHD deaths Age 60–89, global, 2019 0.85 million Cause-attributed estimate
Older-adult HHD DALYs Age 60–89, global, 2019 14.56 million Combined fatal and nonfatal modeled loss
Prevalence-rate trend Age 60–89, 1990–2019 AAPC +0.38% (95% CI 0.36–0.41) Rate rose despite mortality-rate decline
Mortality-rate trend Age 60–89, 1990–2019 AAPC −0.83% (−0.99 to −0.66) Age-specific modeled trend
DALY-rate trend Age 60–89, 1990–2019 AAPC −1.03% (−1.19 to −0.87) Does not mean absolute DALYs fell

All six estimates come from a secondary analysis of GBD 2019 (Yang 2023, PMID 37698022).

A GBD 2021 HHD analysis estimated 12.51 million prevalent cases and 25.46 million DALYs across the full population; East Asia had the largest counts, while the lowest-SDI regions had the highest age-standardized rates (Liu 2025, PMID 40604684). The apparent difference from the 2019 older-adult estimate is not a contradiction that can be averaged: it reflects different GBD rounds, age scopes and outputs.

An independent GBD 2021 analysis estimated HHD deaths rising from 714,000 (95% UI 578,000–795,000) in 1990 to 1.332 million (1.121–1.469 million) in 2021 while age-standardized mortality declined at EAPC −0.68% (Li 2025, PMID 41350658). BMI-attributable projections to 2040 are modeled futures rather than observations (Xu 2025, PMID 41078923).

3. Absolute counts versus standardized rates

Pattern What can drive it Correct interpretation
Counts ↑, age-standardized rate ↓ Population growth and aging exceed epidemiologic improvement More people affected despite lower risk at a standardized age structure
Crude rate ↑, standardized rate ↓ Older population composition Crude service burden rises while age-specific risk improves
Prevalence ↑, mortality ↓ Longer survival, case accumulation, coding/model change Not automatically better prevention
DALYs ↑, DALY rate ↓ Demography plus incomplete rate improvement Absolute societal loss grows

The global cardiovascular GBD 2023 analysis estimated 437 million CVD DALYs (95% UI 401–465 million), 1.4 times the 1990 count; population growth, aging and risk exposure were explicit decomposition drivers (Global Burden of Cardiovascular Diseases and Risks 2023 Collaborators 2025, PMID 40990886).

GBD 2023 cause-of-death estimates cover 292 causes, 204 countries and 660 subnational locations using cause-specific models and years of life lost; HHD comparisons inherit that model architecture (GBD 2023 Causes of Death Collaborators 2025, PMID 41092928).

4. Heart failure attribution

HHD can be counted as an underlying cause of heart failure rather than as all HF occurring with hypertension. A GBD 2021 HF analysis estimated 55.5 million people with HF globally (95% UI 49.0–63.8 million), with HHD the second-ranked underlying cause after ischemic heart disease and an age-standardized HHD-attributed HF prevalence of 148.3 per 100,000 (117.3–186.3) (Chen 2025, PMID 39774847).

A separate GBD 2019 analysis estimated global HF prevalence at 711.90 per 100,000 (95% UI 591.15–858.29) in 2019 and identified ischemic and hypertensive heart disease as the leading underlying causes (Yan 2023, PMID 36892088). A GBD 2021 HF analysis reported a similar etiologic ordering with a different model round and trend specification (Ran 2025, PMID 39849627). These are etiologic partitions inside a modeled HF envelope, not direct clinical adjudication of every case.

Direct clinical assignment in a prospective hospital cohort produces a different kind of number. THESUS-HF II enrolled 1,578 adults presenting with acute HF at 50 hospitals in 17 African countries between 1 July 2024 and 31 July 2025 (median age 56.0 years, IQR 40.0–69.0; 50.5% female). Hypertensive heart disease was the leading aetiology at 576 of 1,578 (36.5%), ahead of cardiomyopathy (370, 23.4%) and ischaemic heart disease (367, 23.3%); 64.2% of presentations were de novo, in-hospital mortality was 8.7% (95% CI 7.3–10.2) and 180-day all-cause mortality was 20.6% (18.4–23.0) (Sliwa 2026, PMID 42669305).

That figure comes from a hospital-presentation series with clinically assigned aetiology, not a population prevalence, and it is not interchangeable with the GBD partition above. The weekly acute-HF presentation rate was 0.03 per 10,000 adults (95% CI 0.02–0.05) in the catchment populations, 33.7% of patients were lost to follow-up before 180 days, and the investigators attribute part of the apparent aetiologic shift from the original THESUS-HF cohort to changes in ascertainment and diagnostic capability rather than to disease biology (Sliwa 2026, PMID 42669305).

5. Sex and age

Older-adult GBD estimates reported higher HHD prevalence rates in men but higher mortality and DALY rates in women (Yang 2023, PMID 37698022). A sex-stratified joinpoint analysis found global crude mortality rising from 12.2 to 14.9 per 100,000 between 1990 and 2019 while age-adjusted mortality fell from 19.3 to 15.1 per 100,000 (Khalid 2025, PMID 40565965).

Those patterns should not be reduced to a biological sex effect. Exposure duration, competing ischemic disease, survival, diagnosis, access to imaging, certificate practices and GBD redistribution may all contribute; a dedicated commentary cautioned against naive interpretation of observed sex contrasts (Chan 2024, PMID 37607268).

Stratifier Recurrent finding Main uncertainty
Older age Counts and crude rates concentrate at older ages Survivor and competing-risk effects
Female sex Higher mortality/DALY rates in several modeled analyses Biology versus longevity/coding/access
Male sex Higher older-adult prevalence rate in one GBD 2019 analysis Case definition and competing IHD
Low SDI Higher age-standardized HHD burden Sparse vital registration and treatment access
High SDI Often lower standardized burden but substantial absolute numbers Aging and diagnostic intensity

6. Regional inequality

GBD 2021 analysis placed the highest counts in East Asia and the highest age-standardized burden in lowest-SDI regions (Liu 2025, PMID 40604684). The older-adult analysis likewise found pronounced country variation and an association between burden patterns and sociodemographic development (Yang 2023, PMID 37698022).

Poland illustrates why national context matters: GBD 2016 estimated prevalence increasing from 0.29% in 1990 to 0.47% in 2016, approximately 180,000 people living with HHD and nearly 5,000 deaths in 2016; age-standardized death and DALY rates declined despite rising crude burden (Miazgowski 2021, PMID 34336015).

No single regional hierarchy should be treated as timeless because model inputs and risk exposure change between GBD rounds (GBD 2021 Causes of Death Collaborators 2024, PMID 38582094; GBD 2021 Risk Factors Collaborators 2024, PMID 38762324).

7. United States signals

GBD 2019 estimated 1,487,975 prevalent U.S. HHD cases and 51,253 deaths in 2019. Female prevalence rose at AAPC 0.3% (95% CI 0.2–0.4), male prevalence was approximately stable, and mortality increased, especially in men (Abughazaleh 2024, PMID 38718934).

CDC WONDER analysis restricted to HHD with heart failure (ICD-10 I11.0) found age-adjusted mortality rising from 3.7 to 13.5 per 100,000 between 1999 and 2020, with APC 14.44% (95% CI 11.12–20.62) from 2014–2020; rates were highest among non-Hispanic Black adults and higher outside metropolitan areas (Goyal 2025, PMID 40083536).

These studies use different data systems and case definitions. Their agreement on increasing coded mortality is a signal; their exact values are not interchangeable. More broadly, five common risk factors jointly shaped lifetime CVD estimates in 2,078,948 participants across 133 cohorts, illustrating that HHD sits inside competing multirisk trajectories (Global Cardiovascular Risk Consortium 2025, PMID 40162648).

8. Adiposity-attributable burden

GBD 2021 comparative-risk analysis used 54,561 sources and modeled 88 risk factors across 631 risk–outcome pairs (GBD 2021 Risk Factors Collaborators 2024, PMID 38762324). A secondary HHD analysis attributed 44% of HHD deaths and 49% of HHD DALYs in 2021 to high BMI and reported both deaths and DALYs attributable to high BMI doubling over 30 years (Sun 2025, PMID 40873620).

Those are population-attributable fractions under GBD causal and exposure assumptions, not the proportion of individual HHD patients whose cardiac phenotype can be clinically assigned to obesity.

9. Undermeasurement and surveillance gaps

Gap Consequence Needed design
Few representative imaging surveys Clinical phenotype prevalence unknown Population echo/CMR subsamples with calibrated weights
Variable LVH thresholds and indexation Cross-study prevalence instability Shared raw measures and reference limits
Sparse longitudinal pressure history Exposure misclassification Linked office, home and ambulatory trajectories
Limited cause adjudication HHD conflated with coexisting hypertension Standard competing-etiology protocol
Weak vital registration in some settings Wider modeled uncertainty Multiple-cause certification and linkage
Underrepresentation of younger adults Early disease transition poorly measured Life-course cohorts

The mechanistic literature recognizes HHD as a spectrum from subtle dysfunction to overt HF, but this spectrum is not yet captured by a unified surveillance system (Huang 2024, PMID 39076964; Nwabuo 2020, PMID 32016791).

10. How to quote burden responsibly

Every burden statement should provide:

  1. GBD round or clinical data source.
  2. Calendar period.
  3. Age range and geography.
  4. Count, crude rate or age-standardized rate.
  5. Confidence or uncertainty interval when available.
  6. Case/attribution definition.
  7. Whether the quantity was measured, coded or modeled.
  8. For clinical series, whether the denominator is a population, a hospital catchment or a presenting cohort (Sliwa 2026, PMID 42669305).

Forecasts to 2040 or 2050 should be labeled projections rather than observations (Liu 2025, PMID 40604684; Li 2025, PMID 41350658).

Open questions

  • What is the population prevalence of imaging-defined HHD under a shared protocol, and how does it compare with GBD prevalence in the same populations? (Yang 2023, PMID 37698022; Ismail 2023, PMID 37176563)
  • Which components of sex and regional disparities persist after harmonizing pressure exposure, survival, imaging access and cause certification? (Chan 2024, PMID 37607268; Khalid 2025, PMID 40565965)
  • How much of the rise in coded U.S. mortality reflects true disease, improved causal linkage, coding change or COVID-era disruption? (Abughazaleh 2024, PMID 38718934; Goyal 2025, PMID 40083536)
  • Does the clinically assigned HHD share of acute HF in African hospital cohorts match the modeled HHD share of HF in the same regions, and if not, which construct is wrong? (Sliwa 2026, PMID 42669305; Chen 2025, PMID 39774847)
  • Can longitudinal BP control and regression of cardiac injury be incorporated into population-attributable burden models? (NCD-RisC 2021, PMID 34450083; GBD 2021 Risk Factors Collaborators 2024, PMID 38762324)

References

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