Abstract
Background
Hypothyroidism and hyperthyroidism are common but clinically distinct disorders that can impair work through fatigue, cognitive slowing, mood symptoms, weakness, palpitations, and heat intolerance. We quantified the health and formal-labor-market productivity burden of the combined Global Burden of Disease (GBD) thyroid-diseases category among working-age women in Western Europe.
Methods
Historical epidemiological estimates for women aged 20–64 years in 24 Western European countries were obtained from GBD 2023 for 1990–2023. Joinpoint regression and locally weighted smoothing characterized temporal and sociodemographic patterns. A Bayesian age-period-cohort model based on the 1990–2023 series projected years lived with disability and years of life lost for 2024–2029; the 2023 estimate was retained as the baseline. Projected health loss was translated into productivity-adjusted life-years and discounted gross domestic product losses using a Bayesian productivity-adjusted life-year framework.
Results
In 2023, the age-standardized disability-adjusted life-year rate ranged from 56.26 per 100,000 women in Spain (95% uncertainty interval, 29.22–96.78) to 107.71 in Norway (55.61–187.94). The regional rate changed little during 1990–2023 (average annual percent change, −0.06%) but followed six distinct temporal segments. Annual years lived with disability were projected to decline from 108.07 thousand (95% credible interval, 107.18–108.96) in 2023 to 102.55 thousand (90.44–114.66) in 2029, whereas years of life lost were projected to increase from 5.40 thousand (5.21–5.59) to 6.13 thousand (3.68–8.58). Across 2023–2029, cumulative productivity loss was 127.48 thousand productivity-adjusted life-years (112.70–142.26), equivalent to Int$8.23 billion in discounted gross domestic product (7.27–9.18).
Conclusion
The combined noncancer thyroid-diseases category produces a persistent disability-dominated burden and substantial estimated losses in formal-market productivity among working-age women in Western Europe. The estimates should not be interpreted as subtype-specific or as including unpaid, caregiving, informal-sector, or thyroid-cancer-related losses.
Keywords: thyroid diseases, productivity-adjusted life-years, macroeconomic burden, Western Europe, women, global burden of disease
Introduction
Hypothyroidism and hyperthyroidism are clinically distinct disorders. Hypothyroidism reflects deficient thyroid-hormone action and commonly causes fatigue, psychomotor and cognitive slowing, depressed mood, cold intolerance, and reduced physical capacity. Hyperthyroidism reflects excess thyroid-hormone action and can cause palpitations, tremor, anxiety, sleep disturbance, heat intolerance, and proximal muscle weakness.1,2 Autoimmune thyroid disease may also have neuropsychiatric effects, and symptoms can persist despite biochemical treatment in some patients.3,4 These different symptom profiles can affect work through sickness absence, reduced performance while present, impaired work ability, and labor-force exit; the size and direction of the effect vary by disease severity, treatment status, and complications such as thyroid eye disease.5,6
Thyroid dysfunction is common in Europe and disproportionately affects women. A European meta-analysis estimated an incidence of 259.12 cases per 100,000 persons per year for combined thyroid dysfunction, including 226.2 for hypothyroidism and 51.0 for hyperthyroidism; undiagnosed dysfunction was also frequent.7,8 A later synthesis estimated that 4.70% of Europeans had undiagnosed hypothyroidism.9 Comparisons across European settings are complicated by historical and current iodine intake, prevention programs, case definitions, thyroid-function testing, treatment thresholds, and heterogeneous registry coverage.7,10 These regional features make Western Europe a relevant setting in which to examine disease burden without assuming that countries with similarly high socioeconomic development have identical ascertainment or care pathways.
Conventional burden metrics—years lived with disability, years of life lost, and disability-adjusted life-years—summarize health loss but do not directly quantify market productivity. Productivity-adjusted life-years provide a complementary metric by weighting years affected by disease or premature death according to productivity loss.11 Applications to chronic disease have shown how epidemiological burden can be translated into potential macroeconomic output loss.12–14 This approach is particularly relevant to thyroid disease, for which persistent, nonfatal symptoms can influence paid work even when mortality is low.5,6
We therefore assessed women aged 20–64 years in Western Europe using historical estimates from GBD 2023.15 We described geographic and temporal patterns from 1990 through 2023, projected health burden through 2029 with a Bayesian age-period-cohort model, and translated projected years lived with disability and years of life lost into productivity-adjusted life-years and gross domestic product loss. The analysis was designed to estimate potential losses within the formal labor market; it did not value unpaid household work, caregiving, or informal employment.
Methods
Study Design, Geographic Scope, and Data Sources
We conducted a retrospective, population-level secondary analysis and a model-based projection. The study population comprised women aged 20–64 years in the 24 locations assigned to Western Europe in the GBD 2023 location hierarchy: Andorra, Austria, Belgium, Cyprus, Denmark, Finland, France, Germany, Greece, Iceland, Ireland, Israel, Italy, Luxembourg, Malta, Monaco, the Netherlands, Norway, Portugal, San Marino, Spain, Sweden, Switzerland, and the United Kingdom. This explicit list was used for all regional aggregates and country comparisons.
Annual deaths, mortality rates, years lived with disability, years of life lost, disability-adjusted life-years, and age-standardized disability-adjusted life-year rates were obtained from GBD 2023 for 1990–2023.15 Historical and projected population denominators by age, sex, country, and year were obtained from United Nations World Population Prospects 2022.16 Country-year gross domestic product estimates in purchasing-power-parity international dollars were obtained from the International Monetary Fund World Economic Outlook 2023 database.17
The cause labeled “thyroid diseases” was used exactly as reported in the GBD 2023 hierarchy. It is a combined noncancer category and the downloaded estimates did not permit separation into hypothyroidism, hyperthyroidism, or other benign subtypes. Combining disorders with different symptom profiles and productivity effects can average or dilute subtype-specific effects and makes the resulting productivity estimates sensitive to the subtype mix in each country. The estimates therefore apply only to the combined GBD category. Thyroid cancer is modeled as a separate GBD cause and was excluded; this is important because the present years-of-life-lost estimates do not represent the premature-mortality burden of all thyroid conditions.
Burden Measures and Standardization
Disability-adjusted life-years were calculated as the sum of years lived with disability and years of life lost. Age-standardized rates were generated by direct standardization to the GBD standard population and are reported per 100,000 women. Historical GBD estimates are presented with 95% uncertainty intervals, whereas Bayesian projections are presented with 95% credible intervals.
We analyzed both absolute counts and age-standardized rates because they answer different questions: rates facilitate comparison across populations with different age structures, whereas counts determine the volume of health and productivity loss. Age-specific analyses used 5-year groups from 20–24 through 60–64 years.
Temporal and Sociodemographic Analyses
Joinpoint regression was applied to annual age-standardized disability-adjusted life-year rates for 1990–2023. Segmented log-linear models estimated annual percent change within each segment and average annual percent change over the full period, with two-sided 95% confidence intervals.18 Statistical significance was defined as P<0.05. This concise model description replaces the extended methodological justification in the original manuscript.
The association between country-year age-standardized disability-adjusted life-year rates and the Sociodemographic Index was described with locally weighted scatterplot smoothing and a 95% confidence band. The Sociodemographic Index ranges from 0 to 1 and combines income per capita, educational attainment, and fertility in persons younger than 25 years. This analysis was descriptive and was not used to infer causal effects of social development or health-system characteristics.
Bayesian Age-Period-Cohort Projection
Annual age-specific years lived with disability and years of life lost for 1990–2023 were modeled separately. For age group a and calendar year t, the observed burden count Dₐ,t was assumed to follow a Poisson distribution with population offset Nₐ,t and rate λₐ,t:
 |
(1) |
The log rate was decomposed into age, period, and cohort effects:
 |
(2) |
Here, μ is the intercept; αₐ, βt, and γt-a are age, period, and birth-cohort effects; and εₐ,t is an independent overdispersion term. Second-order random-walk priors were assigned to the age, period, and cohort effects. Posterior inference used integrated nested Laplace approximation as implemented in the BAPC and R-INLA packages, following the approach of Riebler and Held and Rue et al,19,20 Because integrated nested Laplace approximation was used rather than Markov chain Monte Carlo sampling, a potential scale-reduction factor was neither applicable nor reported. Posterior medians and 2.5th–97.5th percentiles were retained as point estimates and 95% credible intervals.
The historical series through 2023 informed projections for 2024–2029. The observed/model-estimated 2023 value was included as the baseline in tables and in cumulative 2023–2029 totals. Population projections supplied the future offsets. The projection assumes continuation of recent age, period, and cohort patterns and does not model future changes in diagnostic criteria, iodine policy, treatment, or labor-market conditions beyond the specified demographic and economic inputs.
Bayesian Productivity-Adjusted Life-Year Framework
Productivity-adjusted life-years lost were calculated in each country, age group, and year from two components: complete productivity loss associated with years of life lost and partial productivity loss associated with years lived with disability. The healthy counterfactual was normalized to full productivity. Let Aₐ,t be the proportion of paid work time missed (absenteeism) and Pₐ,t the proportional impairment while present (presenteeism). The combined productivity-loss index was:
 |
(3) |
This index ranges from 0 (no work-productivity loss) to 1 (complete loss). Its construction follows the Work Productivity and Activity Impairment framework.21 The annual loss components were:
 |
(4) |
 |
(5) |
 |
(6) |
PYLL denotes productivity-adjusted years lost through premature death, PYLD denotes productivity-adjusted years lost through disability, and the hats indicate Bayesian posterior estimates. Published PALY and thyroid work-productivity evidence informed the parameterization.5,11–14,21 Because harmonized country- and subtype-specific absenteeism and presenteeism inputs were unavailable, the model used age-specific parameters shared across countries. The annual burden-weighted mean productivity-loss index was 0.118 in 2023 and 0.121 in 2029; all age-specific index values were increased or decreased by 5% in sensitivity analysis. This common-input assumption improves cross-country comparability but prevents causal attribution of national differences to labor-market conditions.
The model measures paid-work productivity only. Unpaid household production, family caregiving, volunteer work, and informal employment were excluded because harmonized age-, sex-, country-, and disease-specific productivity inputs and defensible cross-country valuation denominators were unavailable. Applying market gross domestic product to those activities would mix non-equivalent valuation concepts. Their exclusion is likely to underestimate the wider societal burden, particularly among women, and the results should not be labeled total societal costs.
Gross Domestic Product Valuation and Discounting
For each country and year, gross domestic product per capita (g(c,t)) was calculated from purchasing-power-parity gross domestic product and the corresponding population denominator. The present value of productivity loss was:
 |
(7) |
 |
(8) |
The base-case annual discount rate r was 3%. A review of European health-economic guidance found recommended rates generally between 3% and 5%; 3% was selected as a conservative base case and 0%, 1.5%, and 5% were examined in sensitivity analyses.22 Monetary losses, but not epidemiological counts or productivity-adjusted life-years, were discounted. Values are reported in purchasing-power-parity international dollars (Int$).
One-way sensitivity analyses varied the discount rate, multiplied all productivity-loss index values by 0.95 or 1.05, and decreased or increased projected gross domestic product growth by 5%. All analyses were conducted in R version 4.3.1; figures were prepared from the resulting model outputs.
Results
Geographic Distribution in 2023
The 2023 age-standardized disability-adjusted life-year rate varied markedly across the 24 Western European countries (Figure 1). Norway had the highest rate, 107.71 per 100,000 women (95% uncertainty interval, 55.61–187.94), whereas Spain had the lowest, 56.26 per 100,000 (29.22–96.78). Portugal was also in the highest mapped category (>90 per 100,000), while Spain and Denmark were in a lower category (50–70 per 100,000).
Figure 1.
Geographic distribution of age-standardized disability-adjusted life-year rates for thyroid diseases among women aged 20–64 years in Western Europe, 2023. Countries are shaded by rates per 100,000 women. Grey denotes locations not included in the analysis.
Abbreviation: DALY, disability-adjusted life-year.
Countries with similar Sociodemographic Index values sometimes had different burden estimates. This descriptive pattern identifies heterogeneity but does not determine whether it arose from true disease frequency, data coverage, diagnostic practice, treatment, or model inputs.
Temporal Trends, 1990–2023
Across Western Europe, the age-standardized disability-adjusted life-year rate changed little overall from 1990 to 2023 (average annual percent change, −0.06%) but did not follow a single linear trend (Figure 2). The rate declined in 1990–1995 (annual percent change, −0.25%), increased in 1995–2000 (1.36%), declined in 2000–2010 (−0.51%) and 2010–2015 (−1.06%), increased in 2015–2019 (0.61%), and was approximately stable in 2019–2023 (0.10%). Statistical-significance symbols are defined in the Figure 2 legend.
Figure 2.
Temporal trends in age-standardized disability-adjusted life-year rates for thyroid diseases among women aged 20–64 years in Western Europe, 1990–2023. Black diamonds show observed rates per 100,000 women; colored segments show Joinpoint-fitted trends. *P<0.05; **P<0.01 (two-sided tests of whether the APC or AAPC differs from zero).
Abbreviations: AAPC, average annual percent change; APC, annual percent change; DALY, disability-adjusted life-year.
The relation between the age-standardized rate and the Sociodemographic Index was weak and nonlinear (Figure 3). The fitted rate increased slightly across the lower-to-middle index range, plateaued, and declined modestly at the highest values. Country-year observations remained dispersed around the smooth curve, so the Sociodemographic Index alone did not explain between-country variation.
Figure 3.
Association between age-standardized disability-adjusted life-year rates for thyroid diseases and the Sociodemographic Index among women aged 20–64 years in Western Europe, 1990–2023. Each point is a country-year observation. The red curve is the locally weighted fit and the shaded region is its 95% confidence interval.
Abbreviations: DALY, disability-adjusted life-year; SDI, Sociodemographic Index.
Projected Annual and Cumulative Burden, 2023–2029
Annual years lived with disability were projected to decline from 108.07 thousand (95% credible interval, 107.18–108.96) in 2023 to 102.55 thousand (90.44–114.66) in 2029 (Table 1). Annual years of life lost were projected to increase from 5.40 thousand (5.21–5.59) to 6.13 thousand (3.68–8.58). Thus, nonfatal loss remained the dominant component throughout the projection.
Table 1.
Projected Annual and Cumulative Health Burden, Productivity Loss, and Gross Domestic Product Loss Attributable to Thyroid Diseases Among Women Aged 20–64 Years in Western Europe, 2023–2029
| Year | YLDs, Thousand (95% CrI) |
YLLs, Thousand (95% CrI) |
PALYs Lost, Thousand (95% CrI) |
GDP Lost, Billion Int$ (95% CrI) |
|---|---|---|---|---|
| 2023 | 108.07 (107.18–108.96) | 5.40 (5.21–5.59) | 18.13 (17.43–18.82) | 1.18 (1.13–1.22) |
| 2024 | 105.28 (103.18–107.38) | 5.43 (5.07–5.79) | 17.92 (16.97–18.87) | 1.16 (1.10–1.22) |
| 2025 | 104.79 (101.25–108.34) | 5.57 (4.94–6.20) | 18.04 (16.73–19.36) | 1.17 (1.08–1.26) |
| 2026 | 104.28 (98.94–109.62) | 5.71 (4.72–6.69) | 18.16 (16.32–20.00) | 1.17 (1.05–1.29) |
| 2027 | 103.75 (96.35–111.14) | 5.85 (4.44–7.25) | 18.29 (15.78–20.79) | 1.18 (1.02–1.34) |
| 2028 | 103.17 (93.51–112.83) | 5.99 (4.09–7.89) | 18.41 (15.12–21.69) | 1.18 (0.97–1.39) |
| 2029 | 102.55 (90.44–114.66) | 6.13 (3.68–8.58) | 18.53 (14.34–22.72) | 1.19 (0.92–1.45) |
| Cumulative | 731.89 (690.85–772.93) | 40.07 (32.16–47.99) | 127.48 (112.70–142.26) | 8.23 (7.27–9.18) |
Notes: The 2023 row is the baseline; 2024–2029 are forecasts. Cumulative values were calculated from unrounded 2023–2029 model outputs, so displayed annual values may not sum exactly. Monetary values are discounted to 2023 at 3% per year.
Abbreviations: CrI, credible interval; GDP, gross domestic product; Int$, purchasing-power-parity international dollars; PALY, productivity-adjusted life-year; YLD, year lived with disability; YLL, year of life lost.
Productivity-adjusted life-years lost were projected to increase slightly from 18.13 thousand (17.43–18.82) in 2023 to 18.53 thousand (14.34–22.72) in 2029. The corresponding annual discounted gross domestic product loss was Int$1.18 billion (1.13–1.22) in 2023 and Int$1.19 billion (0.92–1.45) in 2029. Across 2023–2029, cumulative estimates were 731.89 thousand years lived with disability (690.85–772.93), 40.07 thousand years of life lost (32.16–47.99), 127.48 thousand productivity-adjusted life-years lost (112.70–142.26), and Int$8.23 billion in discounted gross domestic product loss (7.27–9.18).
Age-Specific Cumulative Projected Burden
Figure 4 reports cumulative projected values summed over all seven years from 2023 through 2029 within each 5-year age group; it does not report annual 2023 values. This temporal definition resolves the apparent discrepancy with Table 1, which reports 108.07 thousand years lived with disability for all age groups combined in the single year 2023.
Figure 4.
Age-specific cumulative projected thyroid-disease burden and related economic loss among women aged 20–64 years in Western Europe, 2023–2029. All panels show values summed across the seven-year projection horizon within each age group; they are neither annual 2023 values nor historical totals. (A) Years lived with disability. (B) Years of life lost. (C) Productivity-adjusted life-years lost. (D) Discounted gross domestic product loss.
Abbreviations: GDP, gross domestic product; Int$, purchasing-power-parity international dollars; PALY, productivity-adjusted life-year; YLD, year lived with disability; YLL, year of life lost.
Across the seven-year cumulative horizon, years lived with disability increased from approximately 45 thousand in women aged 20–24 years to approximately 120 thousand in those aged 60–64 years. Years of life lost increased from less than 1 thousand to approximately 16 thousand. Cumulative productivity loss rose from approximately 5.6 thousand to 25.8 thousand productivity-adjusted life-years, and cumulative discounted gross domestic product loss rose from approximately Int$0.36 billion to Int$1.67 billion. These are age-specific sums across the full projection horizon and should not be compared directly with a single annual total.
Sensitivity Analyses
The base-case cumulative gross domestic product loss was Int$8.23 billion (95% credible interval, 7.27–9.18) (Table 2 and Figure 5). Estimates were Int$9.01 billion (7.93–10.08) with no discounting, Int$8.60 billion (7.59–9.61) at 1.5%, and Int$7.77 billion (6.89–8.65) at 5%.
Table 2.
One-Way Sensitivity Analysis of Projected Cumulative Gross Domestic Product Losses, 2023–2029
| Scenario | GDP Loss, Billion Int$ | 95% CrI |
|---|---|---|
| Base case (3% discount) | 8.23 | 7.27–9.18 |
| Discount rate 0% | 9.01 | 7.93–10.08 |
| Discount rate 1.5% | 8.60 | 7.59–9.61 |
| Discount rate 5% | 7.77 | 6.89–8.65 |
| Productivity-loss index +5% | 9.46 | 8.33–10.59 |
| Productivity-loss index −5% | 8.56 | 7.53–9.58 |
| GDP growth +5% | 9.46 | 8.33–10.59 |
| GDP growth −5% | 8.56 | 7.53–9.58 |
Notes: Each scenario changed one parameter while holding all others at their base-case values.
Abbreviations: CrI, credible interval; GDP, gross domestic product; Int$, purchasing-power-parity international dollars.
Figure 5.
One-way sensitivity analysis of projected cumulative gross domestic product loss among women aged 20–64 years in Western Europe, 2023–2029. Points show scenario estimates and horizontal bars show 95% credible intervals. The blue vertical line marks the base-case estimate (Int$8.23 billion), and the shaded blue band marks its 95% credible interval (Int$7.27–9.18 billion).
Abbreviations: GDP, gross domestic product; Int$, purchasing-power-parity international dollars.
Increasing the productivity-loss index by 5% increased the estimate to Int$9.46 billion (8.33–10.59), whereas decreasing it by 5% reduced the estimate to Int$8.56 billion (7.53–9.58). Gross domestic product growth changes of +5% and −5% produced the same respective estimates. Across all scenarios, point estimates ranged from Int$7.77 billion to Int$9.46 billion and the credible intervals overlapped the base-case interval.
Discussion
This analysis produced four main findings. First, the combined noncancer thyroid-diseases burden among working-age women varied across Western European countries even at similar levels of sociodemographic development. Second, the regional age-standardized rate changed little overall from 1990 to 2023 but followed a segmented trajectory. Third, projected burden was dominated by years lived with disability rather than years of life lost. Fourth, despite a modest projected decline in disability years, formal-market productivity loss remained near 18 thousand productivity-adjusted life-years per year, yielding Int$8.23 billion in cumulative discounted gross domestic product loss during 2023–2029.
The dominance of nonfatal loss is clinically plausible for a combined category containing common chronic thyroid dysfunctions. Hypothyroidism can impair paid work through fatigue, cognitive slowing, and reduced physical capacity, whereas hyperthyroidism may impair it through adrenergic symptoms, sleep disturbance, anxiety, weakness, and complications such as thyroid eye disease.1,2,5 These distinct pathways reinforce an important limitation: a single productivity index for a broad GBD category averages heterogeneous conditions, severities, and treatment states. The aggregate estimate is useful for regional planning but should not be interpreted as the effect of either hypothyroidism or hyperthyroidism individually.
The cumulative age gradient in Figure 4 reflects the distribution of projected health loss and the model’s paid-work productivity weights across age strata. Higher values in older working-age groups may reflect greater diagnosed burden, longer disease duration, comorbidity, and the accumulation of nonfatal health loss. Our data do not include career stage, family responsibilities, or unpaid caregiving, and we therefore removed the earlier speculation that these factors explained the age pattern. The model supports only an interpretation about potential formal-market output.
Between-country heterogeneity should also be interpreted cautiously. European evidence documents substantial variation in historical iodine status, iodine-fortification programs, thyroid medication and surgery rates, registry completeness, case definitions, and the availability of comparable diagnostic data.7–10 Diagnostic pathways may contribute to ascertainment differences: uncomplicated hypothyroidism is commonly detected and followed in primary care, while overt hyperthyroidism and complex or refractory disease more often prompt endocrinology or secondary/tertiary referral.23 Testing thresholds, repeat-testing practices, access to assays, and referral criteria can therefore alter recorded burden. However, the present ecological analysis contained no country-level testing or care-setting variables, so these factors are evidence-based explanations to investigate rather than demonstrated causes of the observed country rankings.
The segmented temporal pattern may likewise reflect multiple influences. Changes in iodine exposure, diagnostic intensity, assay sensitivity, treatment thresholds, population risk, and GBD source coverage can all affect estimated thyroid-disease burden.7,10,24 The near-zero average annual percent change masks these period-specific movements. Because the joinpoint analysis was descriptive, it cannot distinguish changes in underlying disease occurrence from changes in ascertainment or modeling.
Thyroid cancer warrants separate consideration. GBD models thyroid cancer outside the combined thyroid-diseases cause, so it was not missing at random from our downloaded category; it was deliberately outside the estimand.15,25 Cancer contributes relatively more premature mortality than many benign thyroid disorders. Excluding it therefore likely lowers years of life lost, productivity-adjusted years lost through death, and the macroeconomic burden relative to an analysis of all thyroid conditions. The finding that disability dominates mortality applies only to the noncancer combined category and should not be generalized to thyroid cancer.
The economic estimates are projections of potential gross domestic product loss, not observed employer costs, wages, or intervention savings. Their relative stability across one-way sensitivity analyses indicates that the conclusion of persistent burden was not driven by a single tested parameter. Nevertheless, uncertainty in thyroid-specific productivity inputs remains important. Country- and subtype-specific estimates of absenteeism, presenteeism, labor-force participation, and treatment status would improve future models.
The findings support evaluation of earlier diagnosis, continuity of evidence-based care, and occupational accommodations, but the model did not compare clinical or workplace interventions. We therefore cannot conclude that flexible working arrangements are as effective or as important as clinical treatment. Rather, prospective studies should test whether appropriate workplace support adds benefit after effective clinical management.
This study has strengths. It used a common GBD framework across 24 explicitly listed countries, distinguished historical uncertainty intervals from projection credible intervals, applied an age-period-cohort model with transparent equations, and connected health loss to a defined formal-market productivity estimand. It also clarified annual versus cumulative results and tested key economic assumptions.
Several limitations remain. First, GBD estimates depend on the availability and quality of underlying data and on statistical modeling; cross-country differences may partly reflect ascertainment and source heterogeneity. Second, the combined thyroid-diseases category can mask subtype-specific burden and introduce aggregation bias if subtype composition differs across countries or ages. Third, common age-specific productivity parameters were used across countries because harmonized thyroid-specific inputs were unavailable. Fourth, gross domestic product per capita is a population-level valuation and does not measure wages, employer costs, or welfare. Fifth, unpaid household work, caregiving, volunteer activity, and informal-sector production were excluded for lack of comparable inputs; this likely underestimates the wider socioeconomic burden and may be especially consequential for women. Sixth, thyroid cancer was excluded and the mortality-related results therefore understate the burden of all thyroid conditions. Finally, projections assume continuation of recent patterns and do not anticipate policy, diagnostic, therapeutic, or macroeconomic shocks.
Conclusion
Among women aged 20–64 years in Western Europe, the combined GBD noncancer thyroid-diseases category was characterized by persistent, disability-dominated health loss and an estimated Int$8.23 billion reduction in formal-market gross domestic product during 2023–2029. The estimates are not subtype-specific and exclude unpaid work, caregiving, informal employment, and thyroid cancer. They justify better subtype- and country-specific productivity data and evaluation of clinical and occupational strategies, but they do not establish the effectiveness of any workplace intervention.
Acknowledgments
The authors acknowledge the organizations and research teams that maintain the epidemiological, demographic, and economic data resources used in this study.
Funding Statement
This research did not receive any specific grant from funding agencies in the public, commercial, or not-for-profit sectors.
Data Sharing Statement
The source data are publicly available through the GBD Results Tool, United Nations World Population Prospects, and the International Monetary Fund World Economic Outlook database. The harmonized analytical dataset and code generated for this study are available from corresponding author Fei Yang (yangfei@301hospital.com.cn) upon reasonable request.
Ethics Approval and Consent to Participate
This study was based on anonymized population-level data obtained from publicly accessible health and demographic resources. According to the Ethics Review Committee of Chinese PLA General Hospital, analyses of de-identified aggregated data do not constitute human subjects research and are exempt from additional ethical review requirements.
Author Contributions
All authors made a significant contribution to the work reported, whether that is in the conception, study design, execution, acquisition of data, analysis and interpretation, or in all these areas; took part in drafting, revising or critically reviewing the article; gave final approval of the version to be published; have agreed on the journal to which the article has been submitted; and agree to be accountable for all aspects of the work. Haoyang Hu and Yan Wang contributed equally to this work.
Disclosure
The authors declare no competing interests.
References
- 1.Chaker L, Cooper DS, Walsh JP, Peeters RP. Hyperthyroidism. Lancet. 2024;403(10428):768–12. doi: 10.1016/S0140-6736(23)02016-0 [DOI] [PubMed] [Google Scholar]
- 2.Chaker L, Papaleontiou M. Hypothyroidism: a review. Jama. 2025;334(19):1750–1760. doi: 10.1001/jama.2025.13559 [DOI] [PubMed] [Google Scholar]
- 3.Wei Q, Zhang H, Guan H, Song X, Zhou H. Brain alteration of autoimmune thyroid disease: neuropsychiatric impact, neuroimaging insights, and neurobiological implications. Front Neuroendocrinol. 2024;75:101159. doi: 10.1016/j.yfrne.2024.101159 [DOI] [PubMed] [Google Scholar]
- 4.Molewijk E, Fliers E, Dreijerink K, van Dooren A, Heerdink R. Quality of life, daily functioning, and symptoms in hypothyroid patients on thyroid replacement therapy: a Dutch survey. J Clin Transl Endocrinol. 2024;35:100330. doi: 10.1016/j.jcte.2024.100330 [DOI] [PMC free article] [PubMed] [Google Scholar]
- 5.Leso V, Vetrani I, De Cicco L, et al. The impact of thyroid diseases on the working life of patients: a systematic review. Int J Environ Res Public Health. 2020;17(12):4295. doi: 10.3390/ijerph17124295 [DOI] [PMC free article] [PubMed] [Google Scholar]
- 6.Montagna C, Zangelidis A. Labour market implications of thyroid dysfunctions. Econ Hum Biol. 2023;50:101247. doi: 10.1016/j.ehb.2023.101247 [DOI] [PubMed] [Google Scholar]
- 7.Taylor PN, Albrecht D, Scholz A, et al. Global epidemiology of hyperthyroidism and hypothyroidism. Nat Rev Endocrinol. 2018;14(5):301–316. doi: 10.1038/nrendo.2018.18 [DOI] [PubMed] [Google Scholar]
- 8.Garmendia Madariaga A, Santos Palacios S, Guillén-Grima F, Galofré JC. The incidence and prevalence of thyroid dysfunction in Europe: a meta-analysis. J Clin Endocrinol Metab. 2014;99(3):923–931. doi: 10.1210/jc.2013-2409 [DOI] [PubMed] [Google Scholar]
- 9.Mendes D, Alves C, Silverio N, Batel Marques F. Prevalence of undiagnosed hypothyroidism in Europe: a systematic review and meta-analysis. Eur Thyroid J. 2019;8(3):130–143. doi: 10.1159/000499751 [DOI] [PMC free article] [PubMed] [Google Scholar]
- 10.Møllehave LT, Eliasen MH, Strēle I, et al. Register-based information on thyroid diseases in Europe: lessons and results from the EUthyroid collaboration. Endocr Connect. 2022;11(3):e210525. doi: 10.1530/EC-21-0525 [DOI] [PMC free article] [PubMed] [Google Scholar]
- 11.Ademi Z, Ackerman IN, Zomer E, Liew D. Productivity-adjusted life-years: a new metric for quantifying disease burden. Pharmacoeconomics. 2021;39(3):271–273. doi: 10.1007/s40273-020-00999-z [DOI] [PMC free article] [PubMed] [Google Scholar]
- 12.Tu S, Liew D, Ademi Z, Owen AJ, Zomer E. The health and productivity burden of migraines in Australia. Headache. 2020;60(10):2291–2303. doi: 10.1111/head.13969 [DOI] [PubMed] [Google Scholar]
- 13.Wu H, Zhou H, Huang C, et al. Population-level productivity-adjusted life years lost in individuals with type 2 diabetes in Hong Kong: a life table modelling study. Lancet Reg Health West Pac. 2025;59:101585. doi: 10.1016/j.lanwpc.2025.101585 [DOI] [PMC free article] [PubMed] [Google Scholar]
- 14.Ademi Z, Abushanab D, Arvez MJA, et al. Scoping review of productivity-adjusted life years: methods, applications and policy implications. Pharmacoeconomics. 2025;43(12):1367–1388. doi: 10.1007/s40273-025-01544-6 [DOI] [PMC free article] [PubMed] [Google Scholar]
- 15.GBD 2023 Disease and Injury and Risk Factor Collaborators. Burden of 375 diseases and injuries, risk-attributable burden of 88 risk factors, and healthy life expectancy in 204 countries and territories, including 660 subnational locations, 1990–2023: a systematic analysis for the global burden of disease study 2023. Lancet. 2025;406(10513):1873–1922. doi: 10.1016/S0140-6736(25)01637-X. [DOI] [PMC free article] [PubMed] [Google Scholar]
- 16.United Nations, Department of Economic and Social Affairs, Population Division. World population prospects 2022. Available from: https://population.un.org/wpp/. Accessed August 12, 2026.
- 17.International Monetary Fund. World Economic Outlook Database, October 2023. Available from: https://www.imf.org/en/Publications/WEO/weo-database/2023/October. Accessed August 12, 2026.
- 18.Kim HJ, Fay MP, Feuer EJ, Midthune DN. Permutation tests for joinpoint regression with applications to cancer rates. Stat Med. 2000;19(3):335–351. doi: 10.1002/(SICI)1097-0258(20000215)19:3<335::AID-SIM336>3.0.CO;2-Z [DOI] [PubMed] [Google Scholar]
- 19.Riebler A, Held L. Projecting the future burden of cancer: Bayesian age-period-cohort analysis with integrated nested Laplace approximations. Biom J. 2017;59(3):531–549. doi: 10.1002/bimj.201500263 [DOI] [PubMed] [Google Scholar]
- 20.Rue H, Martino S, Chopin N. Approximate Bayesian inference for latent Gaussian models by using integrated nested Laplace approximations. J R Stat Soc Series B Stat Methodol. 2009;71(2):319–392. doi: 10.1111/j.1467-9868.2008.00700.x [DOI] [Google Scholar]
- 21.Reilly MC, Zbrozek AS, Dukes EM. The validity and reproducibility of a work productivity and activity impairment instrument. Pharmacoeconomics. 1993;4(5):353–365. doi: 10.2165/00019053-199304050-00006 [DOI] [PubMed] [Google Scholar]
- 22.Blüher M, Saunders SJ, Mittard V, Torrejon Torres R, Davis JA, Saunders R. Critical review of European health-economic guidelines for the health technology assessment of medical devices. Front Med Lausanne. 2019;6:278. doi: 10.3389/fmed.2019.00278 [DOI] [PMC free article] [PubMed] [Google Scholar]
- 23.National Institute for Health and Care Excellence. Thyroid disease: assessment and management. NICE guideline NG145. 2023. Available from: https://www.nice.org.uk/guidance/ng145. Accessed August 12, 2026. [PubMed]
- 24.Acosta GJ, Singh Ospina N, Brito JP. Epidemiologic changes in thyroid disease. Curr Opin Endocrinol Diabetes Obes. 2024;31(5):184–190. doi: 10.1097/MED.0000000000000877 [DOI] [PubMed] [Google Scholar]
- 25.Zhou T, Wang X, Zhang J, et al. Global burden of thyroid cancer from 1990 to 2021: a systematic analysis from the global burden of disease study 2021. J Hematol Oncol. 2024;17(1):74. doi: 10.1186/s13045-024-01593-y [DOI] [PMC free article] [PubMed] [Google Scholar]
Associated Data
This section collects any data citations, data availability statements, or supplementary materials included in this article.
Data Availability Statement
The source data are publicly available through the GBD Results Tool, United Nations World Population Prospects, and the International Monetary Fund World Economic Outlook database. The harmonized analytical dataset and code generated for this study are available from corresponding author Fei Yang (yangfei@301hospital.com.cn) upon reasonable request.