Whether self-reported noise sensitivity — a stable disposition to react negatively to everyday sounds — is a cause of ill health, a marker of an underlying susceptibility that also produces ill health, or an artifact of negative self-reporting has remained unresolved since Fyhri and Klæboe's 2009 structural-equation study of 1842 Oslo residents found that sensitivity, but not calculated road traffic noise exposure, predicted self-reported hypertension and chest pain. The problem is to determine, with designs that have temporal identification and validated multi-item measurement, the causal status of noise sensitivity in the road-traffic-noise → annoyance → health pathway: causal component (mediator or effect modifier), non-causal marker of latent individual susceptibility, or reporting artifact — together with the direction and possible bidirectionality of the noise–annoyance–health relationships and a longitudinal operationalization of the transactional appraisal–coping model. Later prospective studies establish that sensitivity predicts future psychological ill-health and that annoyance mediates aircraft-noise effects on self-reported health, but none discriminates the three accounts; recent work (2023–2025) still calls for causal-inference designs, so the causal status of sensitivity remains open.

Background

Long-term exposure to road traffic noise is assessed through the day–evening–night average sound level LdenL_{den} — an energy-equivalent outdoor noise metric with 5 dB and 10 dB penalties added to evening and night levels — and its principal subjective outcome is noise annoyance: the self-reported degree of disturbance, irritation or dissatisfaction caused by the noise, usually measured on standardized verbal or 11-point ICBEN (International Commission on the Biological Effects of Noise) scales. A large literature links transportation noise and annoyance to health outcomes, but most of it is cross-sectional, so the direction of the causal arrows is not identified. Two individual-difference constructs occupy a central and contested place in these analyses. Noise sensitivity is a relatively stable disposition to react negatively to sounds across situations, typically measured with multi-item questionnaires (most commonly the Weinstein Noise Sensitivity Scale) or single self-rating items; it is among the strongest non-acoustic predictors of annoyance and is repeatedly associated with health complaints. Whether that association is causal is precisely what is at issue: a latent individual 'susceptibility' — a broader vulnerability of the person — could produce both high sensitivity and ill health (making sensitivity a confounder rather than a cause), or a dispositional negative affect and illness behavior could inflate both self-reports (making the association an artifact).

Fyhri and Klæboe (2009) made this ambiguity explicit using a structural equation model (SEM) — a multivariate technique that simultaneously estimates a hypothesized system of causal paths among observed and latent variables, allowing direct and indirect effects to be decomposed — on 1842 Oslo residents from two surveys, with calculated LdenL_{den} and nitrogen-dioxide air pollution at each dwelling, self-reported noise sensitivity, annoyance, and self-reported hypertension and heart problems. Only sensitivity predicted hypertension and chest pain; no path from noise exposure to health was identified. Rather than noise being the causal agent, the authors suggested that noise–health relationships in such cross-sectional studies may be spurious, with individual vulnerability reflected both in ill health and in being sensitive to noise. They explicitly left sensitivity's causal status open — causal factor, marker of a latent susceptibility, or reporting artifact — and noted that the association could equally be bidirectional; they further noted design limitations that any definitive answer must overcome: exposure estimated only around the interview time, health outcomes self-reported rather than clinically validated, a single-item sensitivity measure, coping assessed only through window-closing behavior, and residual confounding by unmeasured neighbourhood and individual variables (for example baseline psychiatric vulnerability, objective sleep disturbance, or long-term cumulative exposure). They also observed that the transactional model of annoyance proposed by Lercher — in which annoyance and health emerge from continuous appraisal–coping–reappraisal loops between person and environment (as described in the source study and elaborated in Lercher, Dzhambov and Persson Waye, 2025) — had not been operationalized or tested in longitudinal designs.

Methodological vocabulary used in the later lineage: cross-lagged panel models estimate reciprocal effects between variables measured repeatedly over waves, providing one way to probe temporal ordering; marginal structural models with inverse-probability weighting estimate causal effects in longitudinal data even under time-dependent confounding (for example, when earlier health affects later exposure or annoyance); mediation analysis decomposes a total effect into direct and indirect components. These are the natural tools for the question at hand.

Problem Statement

Determine the causal status of noise sensitivity in the road-traffic-noise → annoyance → health-complaints pathway, as left open by Fyhri and Klæboe (2009). A complete answer specifies a design with temporal identification — longitudinal cohorts or panels with at least three waves, or quasi-experimental exposure change — and the analysis that would formally discriminate among the three hypotheses: (i) noise sensitivity is a causal component of the pathway (in either of two distinct senses that must be told apart: as a mediator lying on the causal path, noise exposure → sensitivity → health, or as an effect modifier, not itself on the causal path but changing the strength of the exposure–health relation); (ii) sensitivity is a non-causal marker of a latent individual susceptibility that produces both sensitivity and ill health and confounds observed noise–health associations; (iii) the sensitivity–health association is a reporting artifact (for example of dispositional negative affect or illness behavior inflating both self-reports). These components form one objective: each is a constraint the source study placed on what would count as a causal answer, not an independent deliverable. The design must therefore also specify, within the same analysis: how the direction and possible bidirectionality of the noise–annoyance–health relationships would be identified; measurement of sensitivity with a validated multi-item instrument rather than a single item, with health outcomes that are clinically or formally validated; how the transactional appraisal–coping–reappraisal processes proposed by Lercher would be operationalized with validated coping measures rather than proxies such as window-closing; and how robustness to residual confounding by unmeasured neighbourhood and individual variables (for example baseline psychiatric vulnerability, objective sleep disturbance, long-term cumulative exposure history) would be assessed, for example through adjustment for the measurable neighbourhood and individual covariates together with a stated quantitative sensitivity analysis for unmeasured confounding (such as an E-value or bias analysis). The answer should state, for each of the three hypotheses, which pattern of results would reject it and which would support it, together with the effect magnitudes and the precision the design must attain to discriminate among them.

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