Does the Same Wine Volume Worsen Night-Vision Tests More in Women? A 37-Person Study

The forensic question is not simply whether alcohol affects eyesight

The more specific issue is whether a person who sees well on an ordinary high-contrast acuity chart must also perform normally when detecting faint objects near a bright light at night. The study examined a different set of visual functions: detection of peripheral light stimuli around a bright source, contrast sensitivity, binocular depth discrimination, and optical image quality. These functions are related to vision, but none is identical to ordinary distance acuity, and none by itself is a measurement of actual driving behavior.

The investigators also asked whether biological sex explained variation in the changes after alcohol exposure. The crucial design feature was that each participant consumed the same volume of wine, rather than receiving a dose adjusted to produce the same breath alcohol concentration in every person. Consequently, a difference between sex groups might reflect achieved exposure, visual physiology, body characteristics, experimental variability, or several factors together. It should not be converted into a statement that all women are more impaired than all men at a matched alcohol concentration.

Who participated and how was the wine challenge conducted?

The analyzed sample comprised 37 adults: 20 women and 17 men. The investigators initially assessed 39 people and excluded two—one because of abnormal binocular-vision testing and one because of simulator sickness. Participants had corrected near and distance acuity meeting the study’s criterion, no reported disorder that would limit binocular visual performance, no prior refractive surgery, and no medication expected to affect the tests or alcohol absorption. They were characterized as social drinkers, with Alcohol Use Disorders Identification Test scores of eight or lower.

Each participant attended two experimental sessions, separated by two weeks and held at the same time of day. The order of the sessions was randomized. In one session the participant was tested under baseline conditions; in the other, the participant consumed 450 mL of red wine containing 13.5% alcohol by volume over approximately 30–40 minutes. The wine was consumed about two hours after the last meal. Training was supplied before the baseline testing so subjects understood the visual tasks.

There was no alcohol-free, taste-matched beverage placebo challenge. The baseline condition was not a separate randomized sham-drinking experience. Randomizing the order of the two sessions helps mitigate some order effects but does not blind the participant or experimenters to all differences in the experience of drinking wine.

What was actually measured: exhaled breath, not venous whole-blood ethanol

The investigators used a Dräger Alcotest 6820 to measure ethanol in exhaled breath. The original measurement unit was milligrams of ethanol per liter of exhaled air (mg/L). An initial breath measurement was taken 30 minutes after wine consumption; additional measurements followed at approximately 20-minute intervals, providing four readings averaged for each participant. This protocol measures breath alcohol during the test period. It does not supply four gas-chromatographic measurements of venous whole-blood ethanol.

For all 37 participants, the mean measured breath concentration was 0.34 ± 0.01 mg/L; the male subgroup averaged 0.30 ± 0.02 mg/L and the female subgroup 0.38 ± 0.02 mg/L. The paper expressed 0.34 mg/L as an approximately 0.07% BAC-equivalent, relying on a breath-to-blood convention. That author-provided equivalence is not a separate laboratory analysis of a blood specimen and should not be entered into a forensic record as though a venous whole-blood ethanol assay had been performed.

The researchers used a modified Widmark calculation before the challenge, assigning distribution factors of 0.60 for women and 0.70 for men. Those factors helped plan exposure, but a calculated target or expected BAC is not interchangeable with a breath-instrument reading. Both are different again from an actual chromatographic whole-blood measurement. For general distinctions between measured samples and later concentration calculations, see the two-blood-sample alcohol elimination research brief.

How did the researchers test visual disturbance around a bright light?

One outcome was the visual disturbance index (VDI), derived from a halometer examination. Participants looked toward a central bright stimulus under dim-room conditions and attempted to identify peripheral targets. The central stimulus had a reported luminance of 176 cd/m²; peripheral stimuli were 61 cd/m². An increased VDI meant that more peripheral stimuli were not detected in the presence of the bright central source—an operational measure of visual disturbance or halo perception.

The protocol tested both one-eye viewing and binocular viewing. It did not recreate an individual driver’s exact windshield, headlamps, vehicle speed, road contrast, weather, visual field, gaze behavior, or hazard timing. A halometer result can reveal poorer laboratory detection under glare-like conditions without measuring whether a particular roadside object was visible to a particular driver.

The original results showed monocular VDI increasing from 0.21 ± 0.02 at baseline to 0.31 ± 0.03 after alcohol (p < .001), and binocular VDI increasing from 0.14 ± 0.01 to 0.19 ± 0.02 (p = .005). Participants’ average measured pupil size also increased from 5.6 ± 0.2 mm to 5.9 ± 0.2 mm (p < .001). These are sample averages and source-reported standard errors, not a clinical prediction interval for an individual.

Which visual measurements changed after the same wine volume?

The original study assessed more than glare. It measured stereopsis—the ability to discriminate depth from binocular disparity—at near and far distances. Stereoacuity is expressed in arc seconds, and a higher threshold means poorer performance on that task. It also assessed contrast sensitivity using patterned targets, where a lower score indicated worse sensitivity on the authors’ test. Optical image quality was characterized using double-pass retinal imaging, including the objective scatter index (OSI), the Strehl ratio and modulation-transfer-function (MTF) cut-off.

These are outcomes in the same 37 participants before and after the alcohol condition, not measurements from 74 independent people. The study compared different physical and psychophysical constructs. A difference of 0.10 in VDI cannot be equated numerically with a 0.10 change in breath alcohol, and a change in arc seconds cannot be treated as a percentage change in crash risk.

Does decreased contrast sensitivity tell us what a driver could detect?

Contrast sensitivity is the ability to detect patterns that differ only modestly from their surroundings. It is not synonymous with resolving high-contrast black letters against a white background. The researchers used monocular and binocular assessments across spatial frequencies from 0.75 to 18 cycles per degree. Their results indicated worse contrast sensitivity after alcohol on the tested spatial frequencies, with the pattern of deterioration depending on frequency and whether viewing was monocular or binocular.

The group mean monocular summary score declined from 124.9 to 99.9; the source reports a statistically significant paired difference. The binocular summary score also fell, from 149.8 to 130.1. Those numerical scores belong to this testing arrangement and should not be presented as universal contrast-detection probabilities. Environmental glare, angular size, the contrast of the actual object, corrective lenses, adaptation to darkness and attention all affect practical detectability.

The investigators reported that higher visual disturbance was correlated with worse contrast sensitivity: VDI versus monocular contrast sensitivity had Spearman ρ = −0.461 and VDI versus binocular contrast sensitivity had ρ = −0.558, both with p < .001. These correlations do not prove that one test causes the result in the other or that either score can reconstruct an individual driver’s missed hazard.

What did the retinal optical-quality measurements add?

The double-pass system introduced a point of infrared light into the eye and collected the reflected retinal image. This gives optical-quality information that is not obtained simply by asking a person whether they felt intoxicated. An increased OSI indicates greater light scattering under the device’s conditions; decreases in Strehl ratio or MTF cut-off indicate diminished optical image quality by their respective definitions.

At a fixed 4-mm pupil, the mean OSI rose from 0.56 ± 0.06 to 0.82 ± 0.10 (p < .001). At a 5-mm artificial pupil, mean MTF cut-off decreased from 36.31 ± 1.82 to 31.28 ± 1.65 cycles per degree (p < .001); mean Strehl ratio decreased from 0.21 ± 0.01 to 0.17 ± 0.01 (p < .001). The researchers observed a modest association between OSI and VDI (Spearman ρ = 0.288, p = .042).

These optical measurements reflect changes in ocular imaging within the study protocol, not directly measured brain ethanol, eye-movement coordination, mental workload, road tracking or collision probability. Optical quality, behavioral detection and driving performance are related concepts, but each requires its own evidence.

Did women and men have the same measured breath exposure?

No. Although everyone received the same volume of wine, the mean breath alcohol readings differed: 0.38 ± 0.02 mg/L in women versus 0.30 ± 0.02 mg/L in men. The study found that women also had lower average body mass index. This matters because fixed-volume administration is not a matched-concentration experiment. At one end, individuals can achieve different breath concentrations from the same beverage volume; at the other, even matching concentrations would not automatically guarantee identical visual responses.

The investigators constructed a composite visual deterioration score (VDS) using standardized changes across their visual variables. On their coding scheme, more negative VDS values indicated greater deterioration. Women had an average VDS of −0.22 ± 0.12 and men 0.27 ± 0.12; the unadjusted difference was reported at p = .005. This means the direction of the score cannot be inferred from its name alone: a value moving down was worse under the paper’s coding convention.

Across individuals, the article reported a negative correlation between breath concentration and VDS (Spearman ρ approximately −0.47, p < .01). That is directionally consistent with greater reported deterioration at higher achieved breath concentrations. A correlation is not a dose-response calibration that converts a new person’s breath result into a defensible individual VDS.

Which sex differences remained significant for individual visual tests?

The authors compared deterioration by sex on multiple measures. The results were not a uniform finding that each endpoint differed significantly by sex. The source’s Table 3 identified significant unadjusted sex-group differences in monocular contrast sensitivity and two optical-quality measures at the 5-mm pupil. Several other sex contrasts—including the monocular and binocular halo indices, near and distance stereoacuity and the 4-mm objective scatter index—were not statistically significant in those unadjusted comparisons.

The key distinction is between a within-person baseline-versus-alcohol effect and a between-sex effect on the size of that change. They are different statistical comparisons. A visual function can deteriorate after alcohol for the combined sample while its observed deterioration does not differ significantly by sex. Likewise, a significant composite difference does not make all of its contributing measurements significant.

What happens when breath alcohol, age and BMI are considered together?

The researchers performed an analysis of covariance with the composite VDS as the outcome, biological sex as a group factor, and breath alcohol concentration, age and BMI as covariates. Their stated interpretation was that breath concentration remained associated with composite visual deterioration (reported p = .041), while a separate sex difference was not significant after adjustment. BMI and age were not reported as independently significant covariates in that analysis.

This is a more limited conclusion than saying “sex is irrelevant.” There were only 37 participants, the same wine volume yielded different average breath exposure by sex, and adjustment is a statistical modeling technique rather than a new experiment that holds dose, breath concentration and all biological variables constant. The study does not supply a sex-specific individual prediction interval, a validated forensic impairment threshold or proof about another age distribution. Forensic interpretation should preserve the distinction between association with achieved breath exposure and proof of an inherent sex-dependent susceptibility.

Are halo perception, optical scatter and stereopsis all measures of the same impairment?

No. The halo test required subjects to detect peripheral targets around a light; contrast sensitivity required recognizing faint spatial patterns; stereoacuity required distinguishing depth from binocular disparity; the double-pass optical instrument measured image quality. Participants might change on several outcomes for different reasons. The paper documented group changes across those domains, but it did not establish one latent “driving impairment” score with a known false-positive rate, diagnostic specificity or cross-population calibration.

The composite VDS was assembled by standardizing each study variable and averaging the changes with equal weights, reversing some signs so more-negative values consistently represented worse outcomes. Equal weighting was a methodological choice, not proof that each component has equal importance in a crash reconstruction. A score assembled for an experiment may summarize a group pattern yet still lack validation for a new clinical, police or expert-witness purpose.

Nor does a fall in contrast sensitivity explain all observed visual disturbance. Pupil diameter, intraocular scatter, the tear film, optical aberrations, binocular alignment, attention and test strategy are distinct possible contributors. The study measured some of these domains, discussed others from published literature, and did not independently measure every proposed biological mechanism.

How far can these data travel into DUI or collision testimony?

They provide a scientifically relevant caution against assuming that ordinary visual-acuity performance rules out impairment on other visual functions. They also show how averaging a breath measurement across a testing session is different from obtaining an instantaneous value at a specified driving time. But no participant drove a real vehicle in the analyzed experiment, and the researchers did not measure crash involvement, detection distance for a real roadway obstacle, steering variability, emergency-braking latency, night-adaptation at a collision location or causal responsibility for an event.

When the question concerns one person at one time, the relevant evidence must be considered separately: the original breath instrument and its readings; observation and specimen times; actual reported blood specimen type if any; roadway illumination and object contrast; vision correction; sightline and headlamp geometry; medical eye history; and contemporaneous behavior. The original study cannot retrospectively determine these facts. A person may have experienced a visual change without the evidence proving that the change caused a specific failure to see; conversely, a normal acuity test alone cannot exclude the type of laboratory change studied here.

The study also cannot establish a conversion from a person’s BrAC in mg/L to a sex-specific halo score. A breath measurement is analytically different from a whole-blood ethanol assay, a Widmark estimate is a model rather than a specimen, and a correlated task score is not a direct indicator of driving causation. For broader reading about what research material is and is not being used in a forensic appraisal, consult the editorial and research source policy and the scientific research library.

What design limitations should remain visible in the interpretation?

First, 37 people provide limited precision for subgroup interactions and do not represent every driver, age range, visual condition or alcohol exposure history. All participants met specific baseline ocular criteria, and the mean ages reported for the two sex groups were in the late twenties or early thirties. The source did not validate the composite score in older drivers or people with ocular disease. The study was not designed as a population-level screening trial.

Second, everyone consumed the same 450 mL of one 13.5% red wine rather than an independently titrated, blood-confirmed equal-concentration dose. Measured breath concentrations varied. This is important because the central comparative claim depends on separating group membership from achieved exposure. The investigators addressed these factors statistically, but no analysis removes all possible confounding in a small experimental sample.

Third, participants necessarily knew whether they had consumed a substantial amount of wine, and there was no parallel taste-matched sham-drinking control. Although the two sessions were randomized in order and separated by two weeks, expectation, fatigue, learning and differences between sessions may still affect some psychophysical tests. Finally, multiple vision endpoints and exploratory sex comparisons were analyzed. Individual p values should not be read as independent replications of a single broad claim or as evidence of an individual’s legal impairment.

Seven practical questions about the original study

1. Does this paper say every woman has worse night vision than every man after drinking?

No. It compares group averages under one fixed-volume red-wine challenge. Female participants had a higher mean BrAC and a more negative average composite score, while many individual between-sex visual tests were not statistically significant. The study did not establish a rule about every individual at the same achieved alcohol concentration.

2. Did the investigators measure blood alcohol by gas chromatography?

No. They recorded exhaled-breath ethanol with a Dräger Alcotest 6820 in mg/L, then discussed conventional BAC equivalents and used a planning calculation. No separate forensic venous whole-blood gas-chromatography concentration was measured in this experiment.

3. Did all 37 people receive the same amount of alcohol per kilogram?

No. They received the same 450 mL wine volume, not the same weight-adjusted grams per kilogram. Body size and ethanol distribution differences help explain why achieved breath readings differed. The paper’s Widmark estimates do not convert the protocol into a matched-BrAC experiment.

4. Did alcohol increase halos around a bright light?

The group’s monocular and binocular visual disturbance indices were significantly higher after wine consumption in a laboratory halometer test. That finding supports a change in the test’s target-detection measure; it does not calculate glare disability for a particular oncoming headlamp or establish what someone saw before a collision.

5. Was every visual outcome significantly different between women and men?

No. Selected unadjusted contrast-sensitivity and 5-mm optical-quality measures differed by sex, while the two halo-indices, stereopsis measures and several other contrasts did not. This is different from the separate finding that many visual measures deteriorated for the sample as a whole after wine.

6. Does a higher breath measurement prove exactly how poor a person’s vision was?

No. The composite visual score and measured BrAC were associated across the sample, but no validated individual prediction equation, sensitivity/specificity threshold or interval for an individual driver was supplied. A measured breath exposure is not itself an observed visual-task result.

7. Can the results determine whether alcohol caused an accident or a witness failed to observe something?

No. The study did not test road driving, real incident reconstruction, eyewitness identification or collision causation. It is relevant background evidence about distinct visual functions that may change after alcohol; applying it to an individual requires independent case evidence and careful attention to the specific inferential question.

Primary source and narrow conclusion

Casares-López M, Castro-Torres JJ, Ortiz-Peregrina S, Martino F, Ortiz C. Changes in Visual Performance under the Effects of Moderate–High Alcohol Consumption: The Influence of Biological Sex. International Journal of Environmental Research and Public Health. 2021;18(13):6790. https://doi.org/10.3390/ijerph18136790.

Bottom line: A single fixed wine volume was followed by group deterioration on halo-related visual detection, contrast sensitivity, stereoacuity and optical image quality. Apparent sex-group differences were entangled with different achieved breath alcohol exposures. The study supports careful separation of visual-test performance, the measured breath specimen, a modeled blood-equivalent concentration and the entirely different question of whether an identified person was functionally impaired or caused a specific event.