What Vital Signs Tell Underwriters About Risk: A Primer

Vital signs underwriting risk assessment has remained surprisingly unchanged for decades, even as the science behind these measurements has advanced considerably. An underwriter in 1995 and an underwriter in 2026 both look at blood pressure, heart rate, and body mass index. The difference is that researchers now understand far more about what those numbers actually predict, and the tools for collecting them have shifted from a nurse with a cuff to a smartphone camera. This primer breaks down what each vital sign tells underwriters, where the research stands, and why the gap between clinical evidence and underwriting practice is finally starting to close.

A meta-analysis of 87 studies covering 1.8 million participants found that each 10 beat-per-minute increase in resting heart rate was associated with a 17% increase in all-cause mortality risk (Aune et al., 2017). That single number carries more predictive weight than most underwriters currently give it credit for.

What Vital Signs Actually Measure and Why Underwriters Care

Before getting into the specifics, it helps to be clear about what "vital signs" means in an underwriting context. The term gets thrown around loosely. In clinical medicine, the classic four vital signs are heart rate, blood pressure, respiratory rate, and body temperature. Insurance underwriting has historically focused on the first two and largely ignored the latter two, while adding body mass index — which is not technically a vital sign at all, but functions as one in risk classification.

The reason underwriters care about vital signs is straightforward: they are proxy measurements for cardiovascular and metabolic health, which together account for the majority of mortality risk in insured populations. But the relationship between any single vital sign reading and actual mortality is more nuanced than the rating tables suggest.

Vital Signs and Their Underwriting Significance

The following table maps each commonly assessed vital sign to its underwriting application, the strength of its mortality association, and current limitations in how underwriters use it.

Vital Sign	Normal Range	Mortality Association	Current Underwriting Use	Key Limitation
Resting Heart Rate	60–100 bpm	17% increased all-cause mortality per 10 bpm increase (Aune et al., 2017)	Often noted but rarely rated unless severely abnormal	Single readings are unreliable due to anxiety, caffeine, dehydration
Systolic Blood Pressure	<120 mmHg	Strong, well-established dose-response relationship with cardiovascular death	Primary rating factor with established debit tables	White coat hypertension creates false positives
Diastolic Blood Pressure	<80 mmHg	Independent risk factor, especially ages 30–59	Rated alongside systolic in combined assessment	Less predictive than systolic in older applicants
Body Mass Index	18.5–24.9	U-shaped mortality curve; elevated risk at both extremes	Major rating factor with build tables	Does not distinguish muscle from fat; poor in athletes
Respiratory Rate	12–20 breaths/min	Elevated rates predict ICU mortality and cardiac events	Rarely collected in paramedical exams	Difficult to measure accurately outside clinical settings
Heart Rate Variability	Varies by age/fitness	Lower HRV independently predicts cardiovascular and all-cause mortality	Almost never used in traditional underwriting	Requires extended monitoring; no standard underwriting protocol
Walking Pace	Self-reported	Strongest single predictor of mortality in UK Biobank analysis (Wang et al., 2026)	Not currently part of underwriting evidence	Self-reported; no standardized collection method yet

Resting Heart Rate: The Most Underused Signal

Resting heart rate is probably the most interesting case study in the gap between research evidence and underwriting practice. The data supporting its predictive value is extensive, but most underwriting manuals still treat it as background noise unless the reading is clearly abnormal.

RGA's analysis of UK Biobank data for 159,769 healthy males found that elevated pulse rate was associated with excess all-cause mortality, with the effect being relatively stronger at younger ages. That age gradient matters for insurance because younger applicants represent longer exposure periods. A 30-year-old with a resting heart rate of 85 bpm is statistically more concerning than a 60-year-old with the same reading, at least in terms of excess mortality relative to age-matched peers.

The Kailuan Study, which followed 92,562 participants over four years, found that all-cause mortality risk rose by 18% per 10 bpm increase in resting heart rate (Wang et al., 2014). The Melbourne Collaborative Cohort Study reported a hazard ratio of 1.13 per 10 bpm increase across 21,692 participants over nearly 22 years of follow-up (Seviiri et al., 2017).

Why hasn't this translated into standard underwriting debits? Largely because of measurement reliability. A single heart rate reading taken during a paramedical exam — when the applicant may be anxious, recently caffeinated, or slightly dehydrated — is a poor representation of true resting heart rate. Underwriters know this and have been cautious about penalizing applicants based on a number that might be 15 bpm higher than their actual baseline.

Serial readings change the equation entirely. When underwriters have access to multiple heart rate measurements from electronic health records or, increasingly, from digital health screening platforms, the signal becomes much more reliable and actionable.

Blood Pressure: The Established Standard

Blood pressure is the vital sign that underwriters know best and rate most aggressively. The relationship between elevated blood pressure and cardiovascular mortality is among the most replicated findings in epidemiology, and underwriting debit tables reflect decades of actuarial validation.

What has changed recently is the granularity of the data. Traditional underwriting relies on a single blood pressure reading or, at best, two readings taken during the same paramedical visit. Research consistently shows that blood pressure varies significantly throughout the day and across settings. White coat hypertension — elevated readings caused by the stress of a medical examination — affects an estimated 15 to 30% of people diagnosed with hypertension, depending on the study.

Ambulatory and Digital Blood Pressure

Ambulatory blood pressure monitoring, which captures readings over 24 hours, is considered the clinical gold standard for diagnosing hypertension. It is far more predictive of cardiovascular outcomes than office readings. The challenge for underwriting has always been practical: you cannot ask every insurance applicant to wear a blood pressure monitor for 24 hours.

Digital health screening technologies are beginning to bridge this gap. Camera-based methods that estimate blood pressure from facial blood flow patterns provide a way to collect readings in a low-stress, at-home environment. While these measurements are not yet equivalent to ambulatory monitoring, they represent a significant improvement over the single in-office reading that has been the underwriting standard for most of the last century.

BMI: Useful but Blunt

Body mass index remains a primary rating factor despite well-documented limitations. The formula — weight in kilograms divided by height in meters squared — was developed by Adolphe Quetelet in the 1830s for population-level statistical analysis, not individual health assessment. It cannot distinguish between muscle and fat, does not account for fat distribution, and produces misleading results for athletes, the elderly, and certain ethnic groups.

That said, at the population level, BMI works reasonably well as a mortality predictor. The relationship follows a U-shaped curve: both very low and very high BMI are associated with increased mortality. The lowest risk sits roughly in the 22–25 range for most populations, though the optimal range shifts slightly with age.

For underwriters, BMI's real value is as a screening trigger rather than a definitive risk measure. An elevated BMI prompts further investigation — recent lab work, medication history, comorbidity assessment — rather than serving as a standalone rating factor. The industry has moved in this direction over the past decade, with many carriers softening their build tables and placing greater weight on the overall health profile.

Heart Rate Variability: The Frontier

Heart rate variability measures the variation in time intervals between consecutive heartbeats. Higher variability generally indicates better cardiovascular fitness and autonomic nervous system function. Lower variability is associated with increased mortality risk across multiple populations and conditions.

A systematic review and meta-analysis published in Autonomic Neuroscience found that lower HRV parameter values were significant predictors of higher mortality across different ages, sex, continents, populations, and recording lengths. The consistency of this finding across diverse study designs makes HRV one of the more robust predictive biomarkers available.

Despite this, HRV has seen virtually zero adoption in traditional underwriting workflows. The reasons are practical: measuring HRV requires either a clinical-grade ECG or an extended recording from a wearable device. Neither has been part of the standard evidence-gathering process.

This is where digital health screening gets interesting. Smartphone-based rPPG (remote photoplethysmography) can extract HRV data from a short facial video scan. If these measurements prove sufficiently reliable in underwriting populations — and several ongoing studies suggest they will — HRV could transition from a research curiosity to a standard underwriting input within a few years.

New Research Is Shifting the Framework

A 2026 study published in Mayo Clinic Proceedings: Innovations, Quality & Outcomes, conducted by researchers at the University of Leicester with support from RGA, analyzed data from 407,569 UK Biobank participants. The research assessed whether five simple physical measures — walking pace, handgrip strength, resting heart rate, sleep duration, and leisure-time physical activity — could enhance or replace traditional clinical evidence like blood pressure and cholesterol for mortality risk prediction.

The results were striking. Walking pace emerged as the single strongest predictor of mortality risk among the measures tested, demonstrating that everyday indicators of functional health can substitute for more complex clinical tests. The largest improvements in prediction accuracy came among individuals with existing health conditions — precisely the population where underwriting decisions are most consequential.

Professor Tom Yates, who led the Leicester research team, and the study's authors found that supplementing and in some cases replacing conventional risk factors with these simpler measures improved mortality risk assessment meaningfully. For underwriting, the implication is clear: the evidence base for risk classification is expanding beyond the traditional paramedical exam, and simpler inputs may outperform established clinical markers.

Frequently Asked Questions

Which vital sign is most predictive of mortality risk?

It depends on the population and time horizon. For general all-cause mortality in healthy adults, the Leicester-RGA UK Biobank study (2026) found walking pace to be the single strongest predictor. For cardiovascular-specific mortality, systolic blood pressure and resting heart rate both show strong, well-replicated associations. In practice, no single vital sign should be used in isolation — the predictive power comes from combining multiple measurements.

Why don't underwriters rate for resting heart rate more aggressively?

The main barrier has been measurement reliability. A single heart rate reading during a paramedical exam is easily distorted by anxiety, caffeine, recent physical activity, or dehydration. Until serial readings became more accessible through electronic health records and digital screening tools, underwriters lacked confidence that any individual reading reflected the applicant's true baseline. That calculus is changing as digital health data becomes more available.

How does digital health screening change vital signs collection for underwriting?

Digital screening platforms allow applicants to complete health assessments from home, typically using a smartphone. Camera-based methods can capture heart rate, heart rate variability, respiratory rate, and blood pressure estimates from a short facial scan. This eliminates many sources of measurement error (white coat effect, exam anxiety) and enables repeat measurements that improve data quality. The trade-off is that these methods are newer and still building their evidence base in underwriting-specific populations.

Is BMI still a useful underwriting metric?

BMI remains useful as a population-level screening tool and mortality predictor, despite its well-known limitations at the individual level. Most carriers now use BMI as one input among many rather than as a standalone rating factor. The trend is toward supplementing BMI with additional metabolic and cardiovascular data — a direction that digital health screening supports by making it practical to collect more data points without adding friction to the application process.

Where This Is Heading

The vital signs framework in underwriting is not going to be replaced overnight, but it is expanding. The traditional model — a nurse takes your blood pressure, weighs you, and draws blood — captured a narrow slice of health information at a single point in time. The emerging model captures a broader set of physiological signals, potentially over multiple time points, with less friction for the applicant.

Companies like Circadify are building the infrastructure for this transition. Camera-based vital signs screening via rPPG technology makes it possible to collect heart rate, HRV, respiratory rate, and blood pressure estimates from a smartphone — data that historically required clinical equipment. For carriers exploring how to integrate richer biometric data into their underwriting workflows, the digital health assessment approach offers a practical starting point.

The research evidence is there. The collection technology is catching up. The underwriting manuals are the last piece to move, and they tend to move slowly — but the direction is clear.