# paper.pdf ## Metadata - PDFFormatVersion=1.4 - Language=en-US - IsLinearized=false - IsAcroFormPresent=false - IsXFAPresent=false - IsCollectionPresent=false - IsSignaturesPresent=false - Creator=Arbortext Advanced Print Publisher 9.1.510/W Unicode - ModDate=D:20260605134101+05'30' - Title=WNL-2025-205623 1..11 - Producer=Acrobat Distiller 7.0 (Windows) - CreationDate=D:20260605124655+05'30' - xmp:modifydate=2026-06-05T13:41:01+05:30 - xmp:metadatadate=2026-06-05T13:41:01+05:30 - xmp:createdate=2026-06-05T12:46:55+05:30 - xmp:creatortool=Arbortext Advanced Print Publisher 9.1.510/W Unicode - pdf:producer=Acrobat Distiller 7.0 (Windows) - dc:title=WNL-2025-205623 1..11 ## Contents ### Page 1 ![Figure]() RESEARCH ARTICLE OPEN ACCESS # Drivers of Rising Prevalence in Major MotorNeurodegenerative Diseases Temporal Trends in Sweden and France (2003–2022) Octave Guinebretiere,1,2,* Fen Yang,3,* Dang Wei,3 Quentin Calonge,1,4 Yihan Hu,3 Karin Wirdefeldt,5,6Caroline Ingre,6,7 Fredrik Piehl,6,7,8 Karin Modig,3 Weimin Ye,5 Maria Del Mar Amador,1,9 Stanley Durrleman,1Gaelle Bruneteau,9 Celine Louapre,1,10 Jean-Christophe Corvol,1,10 Fang Fang,3,† and Thomas Nedelec1,† Neurology® 2026;107:e218072. doi:10.1212/WNL.0000000000218072 ## Abstract ### Background and Objectives The prevalence of Parkinson disease (PD), multiple sclerosis (MS), and motor neuron diseases(MNDs) is rising globally. However, it is unclear to what degree this is related to an increase inincidence or to improved survival after diagnosis. ### Methods We performed 2 nationwide, population-based, retrospective cohort studies, including allindividuals living in Sweden between 2001 and 2016 and living in France between 2009 and2022, respectively. Pooled mixed-effects regression models, with country as a random effect,were used to determine temporal trends in prevalence, crude and age-standardized and sexstandardized incidence, and age and life expectancy at diagnosis. ### Results Annualized prevalence of PD, MS, and MNDs increased significantly between 2003 and 2022 inthe pooled model (PD: prevalence ratio [PR] per year = 1.014, p < 0.001; MS: PR = 1.029, p <0.001; MND: PR = 1.028, p < 0.001). While the crude incidence of both PD and MS remainednearly stable over time (PD: incidence rate ratio [IRR] per year = 0.998, p < 0.001; MS: IRR =0.992, p < 0.001), the standardized incidence showed a more marked decrease for PD (IRR =0.986, p < 0.001) while remaining almost unchanged for MS (IRR = 0.995, p < 0.001). ForMNDs, both the crude and standardized incidence increased over time (crude IRR = 1.018, p <0.001; standardized IRR = 1.008, p < 0.001). Life expectancy at diagnosis of PD increasedbetween 2003 and 2013 (+0.95 months per calendar year, p < 0.001) and then decreasedbetween 2013 and 2022 (−1.20 months, p = 0.002), while it increased significantly over theentire study period for MS (+2.35 months, p < 0.001) and MNDs (+0.34 months, p = 0.01). CorrespondenceDr. Nedelec RELATED ARTICLE ![Figure]() #### Editorial Rising Prevalence of MajorMotor NeurodegenerativeDiseases: Increase inIncidence, ImprovedSurvival After Diagnosis, orBoth? Page e218169 MORE ONLINE #### Supplementary Material ### Discussion These findings indicate that the rising MS prevalence is largely survival-driven and the rising MNDprevalence reflects a true increase in incidence, whereas PD prevalence grows modestly, largelyindependent of incidence. Depending on the mechanism that drives prevalence, whether increasedincidence reflecting changing risk factor exposures, improved survival due to therapeutic advances, ordemographic aging of the population, inferences about underlying causes differ substantially betweenPD, MS, and MNDs, with direct implications for health care planning and etiologic research. *These authors contributed equally to this work and share first authorship. - †These authors contributed equally to this work and share last authorship. - 1Sorbonne University, Paris Brain Institute - ICM, CNRS, Inria, Inserm, AP-HP, H opitalˆ de la Piti´e Salpˆetri`ere, France;2Sorbonne Universit´e, INSERM, Institut Pierre Louis d’Epid´emiologie et de Sant´e Publique, Equipe PEPITES, AP-HP, H opitalˆ Piti´e Salpˆetri`ere, D´epartement de Sant´e Publique, Centre de Pharmaco, France;3Institute of Environmental Medicine, Karolinska Institutet, Stockholm, Sweden;4AP-HP, Epilepsy Unit, Center of Reference for Rare Epilepsies, ERN EpiCARE, Piti´e-Salpˆetri`ere Hospital, DMU Neurosciences, Paris, France;5Departmentof Medical Epidemiology and Biostatistics, Karolinska Institutet, Stockholm, Sweden;6Department of Clinical Neuroscience, Karolinska Institutet, Stockholm, Sweden;7Department ofNeurology, Karolinska University Hospital, Stockholm, Sweden;8Neuroimmunology Unit, Center for Molecular Medicine, Karolinska Institutet, Stockholm, Sweden;9Paris ALS Center,ˆ Department of Neurology, Hopital de la Piti´e-Salpˆetri`ere, Assistance Publique-Hopitaux de Paris (AP-HP), DMU Neurosciences, Paris, France; and10Department of Neurology, Hopital ˆ ˆ ˆ de la Piti´e Salpˆetri`ere, Assistance Publique Hopitaux de Paris (APHP), DMU Neurosciences, Paris, France. The Article Processing Charge was funded by the authors. This is an open access article distributed under the, which permits unrestricted use, distribution, and reproduction in any medium,provided the original work is properly cited. Copyright © 2026 The Author(s). Published by Wolters Kluwer Health, Inc. on behalf of the American Academy of Neurology. e218072(1) ### Page 2 ## Glossary COVID-19 = coronavirus disease 2019; GDPR = General Data Protection Regulation; ICD-19 = International Classification ofDiseases, Ninth Revision; ICD-10 = International Classification of Diseases, Tenth Revision; IRR = incidence rate ratio;MND = motor neuron disease; MS = multiple sclerosis; NDD = neurodegenerative disease; PD = Parkinson disease; PR =prevalence ratio; SNDS = French National Health Data System; SNPR = Swedish National Patient Register. ## Introduction Neurodegenerative diseases (NDDs) with motor symptoms,such as Parkinson disease (PD), multiple sclerosis (MS), andmotor neuron diseases (MNDs), pose significant public healthchallenges due to their progressive nature and profound impacton quality of life. Understanding and comparing the burden ofthese diseases, including incidence, prevalence, and mortality, iscrucial for informing health care planning, resource allocation,and the development of targeted interventions.1-4 While theprevalence of these diseases seems to be increasing globally, theunderlying reasons for this trend are not well understood andcould vary between diseases.5,6 An increasing prevalence couldbe attributed to an increase in disease incidence in aging populations, as well as improvements in life expectancy due to bettermanagement of NDDs and general health conditions such ascardiovascular diseases or cancers. To date, comprehensive studies across multiple NDDs leveragingnationwide data from single or multiple countries are rare.7 Theuse of data from multiple countries is especially relevant to betterunderstand how population-specific factors such as environmental exposures, lifestyle, and health care system may contributeto differences in disease burden. In addition, differences in recording practices—standardized coding, update frequency, anddiagnostic criteria in health registers—can significantly influencehow patients with NDDs are detected and tracked, affecting theaccuracy and comparability of epidemiologic data across countries.8,9 Using health registers from multiple countries may,therefore, enable a more robust analysis of temporal trends indisease burden, alleviating the concern that any observed trendsare reflective of not only the true trends but also artifacts inpopulation-specific recording or database biases. To this end, we established a research collaboration betweenFrench and Swedish teams to investigate the prevalence, incidence, age at diagnosis, and mortality of PD, MNDs, and MS inthe entire Swedish (2003–2016) and French (2011–2022) populations. By leveraging data from 2 countries with availability ofnational health registers and universal coverage, our aim was toprovide a comprehensive overview of the temporal trends in theburden of these diseases and highlight any disparities or similaritiesthat may exist between countries. ## Methods ### Data Sources The Swedish Total Population Register contains demographic information (including the date and place of birth, sex, and civil status) of Swedish residents since 1968.10 TheSwedish National Patient Register (SNPR) collects information (disease diagnosis and date) on specialized inpatientcare since 1964 (nationwide since 1987) and on outpatient caresince 2001.11,12 The Swedish Prescribed Drug Register,12 initiated in July 2005, collects information on all dispensed druguse, from either specialized care or primary care. The FrenchNational Health Data System (SNDS) is a comprehensive andextensive repository of health care information established in2009 and incorporates data from 2 primary sources, the national hospital discharge database for inpatient care and thenational health insurance claims information system for outpatient care, covering approximately 99% of the population ofFrance. SNDS contains detailed information on all reimbursedprescriptions in both inpatient and outpatient services. ### Identification of Patients With NDDs andStudy Design In Sweden, patients with NDDs were identified from the SNPR,13using information on the primary or a secondary diagnosis madeat an inpatient or outpatient hospital visit, namely ICD-9 code332A and ICD-10 code G20 for PD, ICD-9 code 340 and ICD-10code G35 for MS, and ICD-9 code 335C and ICD-10 code G12.2for MNDs (eTable 1). The ascertainment of these diseases usingSNPR has been validated in previous studies, showing a positivepredictive value of 70.8% for PD14 and 95% for MS.15 Althoughthe validity of MND diagnosis in Sweden has not yet been evaluated, the SNPR is generally recognized for its high completenessand accuracy.16 In France, patients with PD, MNDs, or MS wereidentified using the SNDS with validated algorithms from theliterature (eTable 1). In Sweden, the date of diagnosis was definedas the first time the patient received a diagnosis of the respectivedisease in either an inpatient or outpatient hospital visit. In France,the date of diagnosis was defined as the first time the patient met 1criterion from the validated algorithm, either through a prescription for a specific treatment or the first related diagnosis. Agerestriction was only applied to PD, that is, an age at diagnosis of20 years or older. We performed 2 nationwide, population-based,retrospective cohort studies, including all individuals living inSweden between 2001 and 2016 and living in France between2009 and 2022, respectively, using data from the Swedish TotalPopulation Register and the French National Institute of Statisticsand Economic Studies in France, respectively.17-19 ### Statistical Analysis #### Washout Period As we aimed to study incidence to explain prevalence trends,we used the first 2 years of the study period in each cohort as Neurology | Volume 107, Number 1 | July 14, 2026 e218072(2) ### Page 3 a washout period for PD and MNDs to exclude prevalentcases, that is, starting in 2003 in Sweden and 2011 in France.For MS, however, the situation is more complex because ofthe existence of primary progressive and benign forms thatmay not require frequent medical attention. Therefore,a more conservative approach with a longer washout period of5 years was applied for MS to better capture true incidentcases. #### Trend in Prevalence Annual prevalence of NDDs was estimated by dividing thenumber of patients with PD/MS/MNDs still alive by the sizeof reference population in each cohort,17-19 using December31st of 2003–2016 for Sweden and January 1st of 2011–2022for France as cutoff dates. Temporal trends in prevalenceduring the study period were assessed using prevalence ratios(PRs) with 95% CIs, derived from Poisson regression modelsassuming a linear relationship between prevalence and time.20 #### Trend in Incidence Annual incidence rates of NDDs were defined as the numberof newly diagnosed cases in each calendar year divided by theperson-years of the reference population on December 31st ofthat year for Sweden and on January 1st of the next year forFrance and were expressed per 100,000 person-years. Toadjust for the potential impact of demographic shifts on incidence rates, standardized incidence rates were computedusing the age and sex distributions of the total population atthe baseline year of the study period (2003 for Sweden and2011 for France) and in 5-year age and sex strata. 95% CIs ofthe crude and standardized incidence rates were calculatedunder a Poisson distribution assumption and assuming a linear relationship between incidence and time. Because thecoronavirus disease 2019 (COVID-19) pandemic likely affected MNDs more strongly, given that its care pathway oftenrequires hospitalization, we decided to exclude the years2020–2022 from the Poisson regression analysis, whileretaining them in the incidence curves for transparency. #### Life Expectancy at Diagnosis Life expectancy at diagnosis was estimated using both diseasespecific and general population mortality life tables. Life expectancy at diagnosis was estimated using the median age atdiagnosis in the pooled sample of the 2 cohorts, that is,75.6 years for PD, 42.4 years for MS, and 69.2 years for MNDs.Specifically, we constructed abridged life tables over successive2-year periods to summarize mortality patterns across all agegroups. We reported the yearly variation in life expectancy (inmonths), assuming a restricted cubic spline model relationshipbetween life expectancy and time as the primary analysis. Ina secondary analysis, because the linear assumption did nothold for PD, we fitted 2 separate linear models: one for theperiod 2003–2013 and another for 2013–2022. #### Pooled Models In addition to reporting country-specific results, we alsoused mixed-effects models (Poisson regression models for incidence and prevalence and regression models for age atdiagnosis and life expectancy at diagnosis) to account forbetween-country heterogeneity and report pooled resultsbetween countries. ### Sensitivity Analyses In the primary analyses, we assumed a linear relationshipbetween calendar year and prevalence and incidence becausevisual inspection supported linearity and this approachallowed estimation of annual prevalence and incidence rateratios (IRRs). Nonlinearity was explored in secondary analyses using restricted cubic spline models with 3–5 knots andcompared using Akaike information criterion and Bayesianinformation criterion; a 3-knot model was retained, withknots at 2007 (Sweden-only period), 2013 (common period),and 2019 (France-only period). For life expectancy, nonlinearmodels were used in the primary analysis because trends wereclearly nonlinear, with an additional secondary analysis approximating trends using 2 linear segments. A similar approach was applied to age at diagnosis because the linearityassumption was not met for MS. In a second sensitivityanalysis, we further investigated potential between-countryheterogeneity in temporal trends of incidence and disentangled effect of time and country, through fitting countryspecific models during a period with greater overlap betweencountries (2009–2018). ### Standard Protocol Approvals, Registrations,and Patient Consents The use of Swedish register data for this study was approvedby the Swedish Ethical Review Authority (DNR 2024-0589601). Owing to the register-based nature of this study, informed consent from individual participants was waived bythis approval. The Swedish data are pseudonymized and thussubject to General Data Protection Regulation (GDPR) andcannot be shared openly. We accessed and processed datafrom the SNDS, as permanent access to the Caisse NationaleAssurance Maladie data portal was granted through theInstitut National de Recherche en Informatique Appliqu´eaffiliation of the ARAMIS team, in application of the provisions of Articles R. 1461–11 to R. 1461–17 of the FrenchPublic Health Code and the French data protection authoritydecision Commission Nationale Informatique Libert´e(CNIL)-2016-316. As permanent users of the SNDS, theauthors declared the study to the INRIA’s SNDS registry andwere exempted from Institutional Review Board approval.The data from the SNDS are governed by Articles R. 1461–11to R. 1461–17 of the French Public Health Code and theFrench data protection authority decision CNIL-2016-316. ### Data Availability The data for analyzing medications and health conditions areavailable for research purposes to qualified researchers onrequest to the Swedish National Board of Health and Welfareand Statistics Sweden, provided that they meet specificrequirements. The data from the SNDS (France) are governed by Articles R. 1461–11 to R. 1461–17 of the French Neurology | Volume 107, Number 1 | July 14, 2026 e218072(3) ### Page 4 Public Health Code and the French data protection authoritydecision CNIL-2016-316 and cannot be shared publicly. ## Results ### Prevalence In Sweden, 15,273 (185 per 100,000 individuals) patientswith prevalent PD, 12,457 (151) with prevalent MS, and 825(10.0) with prevalent MND were identified in 2003 and20,839 (243) patients with prevalent PD, 19,864 (231) withprevalent MS, and 1,285 (15.0) with prevalent MND wereidentified in 2016. In France, 188,072 (290 per 100,000individuals) patients with prevalent PD, 94,438 (145) withprevalent MS, and 5,796 (8.9) with prevalent MND wereidentified in 2011, and 227,594 (336) patients with prevalentPD, 130,676 (193) with prevalent MS, and 8,221 (12.1) withprevalent MND were identified in 2022 (Table 1). Thenumber of individuals under each diagnosis is shown ineFigures 1–3. For all 3 diseases, the prevalence increased over time in bothcountries (Figure 1, Table 2, eFigure 4). Pooled analyses ofthe 2 countries demonstrated an annual increase of 1.4%for PD, 2.9% for MS, and 2.8% for MND (all p < 0.001)(Table 2). ### Incidence #### PD Crude incidence rates were slightly higher in France (34.4[95% CI 34.0–34.9]) than in Sweden (29.2 [28.0–30.3]), andthe pattern was similar for standardized rates (France: 32.2[31.8–32.6]; Sweden: 28.1 [26.9–29.3]), per 100,000 personyears (Figure 2). In Sweden, crude incidence rates remainedrelatively stable during the study period (IRR per year = 1.002,p = 0.07), whereas in France, a modest but significant declinewas observed during the study period (IRR = 0.997, p <0.001) (Figure 2, Table 2, eFigure 5). Mixed-effects modelspooling results from both countries demonstrated a small yetsignificant decrease in the crude incidence rates (IRR = 0.998,p < 0.001). Standardized incidence rates decreased signifi-cantly in both countries (France: −1.6% per year, p < 0.001;Sweden: −0.6% per year, p < 0.001). The trends in crude andstandardized incidence rates were consistent between countries during the overlapping study period (2009–2018)(eTable 2). #### MS Crude incidence rates were higher in Sweden (11.4 [95% CI10.7–12.1]) than in France (7.79 [7.57–8.00]); the samepattern was noted for standardized incidence rates (Sweden:11.2 [10.3–12.2]; France: 7.94 [7.70–8.19]), per100,000 person-years (Table 2). In Sweden, crude incidencerates declined from 11.2 per 100,000 person-years in 2006 to9.7 per 100,000 person-years in 2016 (IRR per year = 0.985,95% CI 0.979–0.992) (Table 2, Figure 2, eFigure 5). InFrance, a modest decline was also noted, from 8.2 cases in 2011 to 7.2 cases in 2022 per 100,000 person-years (IRR =0.993, 95% CI 0.991–0.995). The mixed-effects models indicated a modest but significant decline in crude incidencerates (IRR = 0.9898, 95% CI 0.9824–0.9973) and standardized incidence rates (IRR = 0.9928, 95% CI 0.9849–1.0008)(Table 2). The trends in incidence rates were consistent between countries during the overlapping study period exceptfor the standardized incidence rates (Sweden: IRR = 0.987[0.977–0.997], p = 0.011, France: IRR = 0.999 [0.994–1.003],p = 0.5) (eTable 2). #### MNDs Crude incidence rates were 4.07 (95% CI 3.64–4.50) inSweden and 3.23 (3.10–3.37) in France, whereas standardizedincidence rates were 3.90 (95% CI 3.46–4.33) in Sweden and3.05 (95% CI 2.91–3.19) in France (Table 2). In Sweden, thecrude incidence rates increased from 3.77 in 2003 to 4.47 in2016 per 100,000 person-years, indicating an annual increaseof 2.1% (p < 0.001) (Table 2, Figure 2, eFigure 5). In France,the crude incidence rates increased from 2.99 in 2011 to 3.43in 2019 per 100,000 person-years, reflecting an annual rise of1.5% (p < 0.001). Standardized incidence rates demonstratedan annual increase of 1.4% (p = 0.005) in Sweden and anannual increase of 0.5% in France (p = 0.078). Mixed-effectsmodels confirmed the increasing trend for both the crude(IRR = 1.018 [1.013–1.022]) and standardized (IRR = 1.009[1.001–1.017]) incidence rates. The trends in crude incidencerates were consistent between countries during the overlapping study period, although the rise in crude incidence wasno longer significant in Sweden (IRR = 1.009 [0.993–1.025]).Standardized incidence rates were consistent across countries(Sweden: IRR = 1.000 [0.984–1.016], p = 0.9, France: IRR =1.004 [0.998–1.011], p = 0.2) (eTable 2). ### Age at Diagnosis The median age at diagnosis was also comparable betweencountries: 75.1 years in Sweden and 76.1 years in France forPD, 43.2 years in Sweden and 41.6 years in France for MS, and69.4 years in Sweden and 69.1 years in France for MND(Table 1). This median age remained generally stable overtime in both countries (Figure 3), with the notable exceptionof MS in Sweden, where it decreased by 5.0 years between2003 and 2016. In Sweden, the median (interquartile range)age at diagnosis in 2003 was 45.3 (35.3–55.7), whereas it was40.3 (30.0–51.7) in 2016. ### Life Expectancy at Diagnosis When diagnosed in the years 2013–2014, life expectancy at PDdiagnosis (median age: 75 years) was 7.5 years in Sweden,10.9 years in France, and 9.0 years in the pooled analysis. In thereference population, life expectancy at the corresponding agewas 13.3 years in Sweden and 13.9 years in France (Figure 4A,eTable 3). Over the entire study period (2003–2022) of thepooled analysis, life expectancy at PD diagnosis remained relatively stable (−0.21 months per calendar year, p = 0.5) althoughthe life expectancy of the reference population increased by0.87 months per calendar year (p = 0.005) (eTable 3). Life Neurology | Volume 107, Number 1 | July 14, 2026 e218072(4) ### Page 5 | Parkinson disease | Multiple sclerosis | Motor neuron diseases | | - | - | - | | Sweden | France | Sweden | France | Sweden | France | | Identification years | 2003–2016 | 2011–2022 | 2003–2016 | 2011–2022 | 2003–2016 | 2011–2022 | | No. of cases (prevalent[crude ratio per 100,000individuals]/incident[crude rate per 100,000person-years]) | | 2003 | 15,273 (185)/2,244(27.8) | — | 12,457 (151)/1,178(14.6) | — | 825 (10.0)/305 | — | | (3.8) | | 2005 | 16,103 (194)/2,332(28.8) | — | 14,014 (169)/1,020(12.6) | — | 875 (10.6)/284 | — | | (3.5) | | 2007 | 17,132 (206)/2,503(30.7) | — | 15,307 (184)/966(11.8) | — | 938 (11.3)/298 | — | | (3.6) | | 2009 | 18,124 (216)/2,371(28.9) | — | 16,525 (197)/914(11.1) | — | 1,061 (12.7)/360 | — | | (4.4) | | 2011 | 19,109 (226)/2,544(30.8) | 188,072 (290)/22,253(34.7) | 17,701 (210)/976(11.8) | 94,438 (145)/5,295(8.2) | 1,115 (13.2)/355 | 5,796 (8.9)/1,940(3.0) | | (4.3) | | 2013 | 19,965 (234)/2,382(28.6) | 201,955 (308)/22,462(34.3) | 18,851 (221)/900(10.8) | 102,291 (156)/ | 1,162 (13.6)/346 | 6,388 (9.7)/2,024(3.1) | | 5,122 (7.9) | (4.1) | | 2015 | 20,839 (243)/2,454(29.2) | 214,079 (323)/23,551(35.6) | 19,864 (231)/842(10.0) | 110,029 (166)/ | 1,285 (15.0)/368 | 6,982 (10.5)/ | | 5,239 (7.9) | (4.4) | 2,105 (3.2) | | 2017 | — | 222,623 (335)/23,003(34.6) | — | 117,180 (176)/ | — | 7,552 (11.4)/ | | 5,048 (7.6) | 2,209 (3.3) | | 2019 | — | 227,889 (340)/23,047(34.4) | — | 124,156 (185)/ | — | 8,021 (12.0)/ | | 5,158 (7.7) | 2,301 (3.4) | | 2021 | — | 227,594 (336)/23,014(34.0) | — | 130,676 (193)/ | — | 8,221 (12.1)/ | | 5,292 (7.9) | 2,257 (3.3) | | Age at diagnosis, y, median(IQR) | 75.1 (68.0–81.3) | 76.1 (68.5–82.5) | 43.2 (32.7–54.7) | 41.6 (32.1–52.1) | 69.4 (61.2–76.9) | 69.1 (60.8–76.8) | | Sex (incident), n (%) | | Men | 19,995 (59.4%) | 155,260 (56.6%) | 4,145 (31.5%) | 19,149 (31.0%) | 2,648 (56.2%) | 15,928 (56.7%) | | Women | 13,653 (40.6%) | 119,219 (43.4%) | 9,006 (68.5%) | 42,650 (69.0%) | 2,061 (43.8%) | 12,184 (43.3%) | Abbreviations: IQR = interquartile range; MNDs = motor neuron diseases; MS = multiple sclerosis; PD = Parkinson disease. expectancy at diagnosis increased significantly between 2003 and2013 (+0.95 months per calendar year, p < 0.001), but decreasedbetween 2013 and 2022 (−1.20 months per calendar year, p =0.002), in the pooled analysis. Life expectancy at MS diagnosis (median age: 42 years) was33.2 years in Sweden (vs 42.2 years in the reference population)and 37.6 years in France (vs 41.6 years in the reference population) in 2013–2014. Over the entire study period in thepooled analysis, life expectancy at MS diagnosis increased significantly (+2.35 months per calendar year, p < 0.001), that is,faster than the increase in life expectancy in the referencepopulation (+1.32, p < 0.001) (Figure 4B, eTable 3). Life expectancy at MND diagnosis (median age: 69 years) was3.1 years in Sweden and 3.5 years in France in 2013–2014.Life expectancy at MND diagnosis showed a slight but statistically significant increase over time, with a gain of +-0.34 months per calendar year (p = 0.014), in the pooledanalysis (Figure 4C, eTable 3). ## Discussion This study leveraged 2 nationwide, population-based European cohorts to provide a comprehensive analysis of temporaltrends in the burden of PD, MS, and MNDs over the past 2decades. Our headline findings confirm a rising prevalence ofall 3 NDDs in both countries. To explain this increasingprevalence, our results highlight 3 key points. First, age atdiagnosis remained relatively stable across both countries andall 3 diseases, suggesting that earlier detection is unlikely toaccount for the observed trends. The only exception was MSin the early 2000s in Sweden, coinciding with expanded access Neurology | Volume 107, Number 1 | July 14, 2026 e218072(5) ### Page 6 ![Figure]() Prevalence curves were estimated using single calendar year data points and the predictions of (A) the Poisson regression models from each country and (B)the population effect of the Poisson regression mixed-effects models. We assumed a linear relationship between time and incidence to compute prevalenceratios. Graph points were obtained from observed data. to magnetic resonance imaging. Second, while crude incidence rates remained nearly stable for PD and MS—andeven declined slightly for PD after age standardization—bothcrude and standardized incidence rates of MND increased consistently in the pooled analyses. This pattern indicates thatfactors beyond demographic aging may be driving the risingincidence of MND. Third, increases in life expectancy at diagnosis largely explain the growing prevalence of MS. By | Time trend effect size(95% CI), p value | Crude | Standardized | | - | - | - | | Sweden | France | Pooled | Sweden | France | Pooled | | Parkinson disease | | Prevalence (PR) | 1.022(1.021–1.024), p <0.001 | 1.013 (1.009–1.017),p < 0.001 | 1.014(1.014–1.014), p <0.001 | — | — | — | | Incidence (IRR) | 1.002(0.999–1.005), p =0.07 | 0.997 (0.996–0.998),p < 0.001 | 0.998(0.997–0.999), p <0.001 | 0.995(0.992–0.997), p <0.001 | 0.984(0.983–0.985), p <0.001 | 0.986(0.985–0.987), p <0.001 | | Multiple sclerosis | | Prevalence (PR) | 1.033(1.030–1.036), p <0.001 | 1.028 (1.026–1.029),p < 0.001 | 1.029(1.028–1.029), p <0.001 | — | — | — | | Incidence (IRR) | 0.985(0.979–0.992), p <0.001a | 0.993 (0.991–0.995),p < 0.001 | 0.992(0.990–0.994), p <0.001 | 0.988(0.982–0.994), p <0.001a | 0.996(0.994–0.999), p =0.002 | 0.995(0.993–0.997), p <0.001 | | Motor neuron diseases | | Prevalence (PR) | 1.033(1.030–1.036), p <0.001 | 1.027 (1.023–1.032),p < 0.001 | 1.028(1.026–1.030), p <0.001 | — | — | — | | Incidence (IRR) | 1.021(1.014–1.029), p <0.001 | 1.015 (1.010–1.021),p < 0.001b | 1.018(1.013–1.022), p <0.001 | 1.014(1.007–1.021), p =0.005 | 1.005 (0.999–1.01),p = 0.078b | 1.008(1.004–1.012), p <0.001 | Abbreviations: COVID-19 = coronavirus disease 2019; IRR = incidence rate ratio; PR = prevalence ratio. IRRs from country-specific regression models and mixed-effects models. We assumed a linear relationship between time and incidence.a IRR computed for the 2006–2016 period. b IRR computed for the 2011–2019 period (COVID-19 pandemic period excluded). Neurology | Volume 107, Number 1 | July 14, 2026 e218072(6) ### Page 7 ![Figure]() Panel A: country-specific crude incidence rate. Panel B: pooled crude incidence rates. Panel C: country-specific age-standardized and sex-standardizedincidence rate. Panel D: pooled age-standardized and sex-standardized incidence rate. Graph points were obtained from observed data. Incidence curveswere estimated using single calendar year data points and Poisson regression. The incidence rate ratio refers to the average increase in incidence rate over 1year. contrast, the deceleration in life expectancy gains amongpatients with PD in the most recent decade (2013–2022),compared with the previous one (2003–2013), may underliethe recent stabilization in PD prevalence. Finally, becausethere was no clear gain in life expectancy at diagnosis forMND, the increase in its prevalence seems to be primarilydriven by a genuine rise in incidence. Prevalence of PD is rising globally.21,22 In our study, crudeincidence rates of PD remained stable, whereas agestandardized and sex-standardized incidence rates declinedduring the study period, suggesting a potential real decrease inPD incidence. Recent projections have forecast a rising burden of PD based on demographic shifts5,21,23 and continuedgains in survival of patients with PD, based on the historicaltrend of rising life expectancy in the general populations ofFrance and Sweden (+0.25 months per year in France overthe past 6 decades).5 However, we find that life expectancy at diagnosis of PD has plateaued, or even declined since 2010 inboth Sweden and France, mirroring a broader stagnationrelative to the improving life expectancy in the general population.24 This likely helps explain why PD prevalence hasrisen more slowly than some models predicted.25 The declining standardized incidence rates may reflect thechanging profiles of risk factor exposure, or improved diagnostic specificity (e.g., fewer atypical parkinsonisms aremisclassified as PD). Notably, the median age at PD diagnosisremained stable at approximately 75 years, suggesting littleshift toward earlier detection over time, consistent with previous findings.26,27 We observed differences in the prevalence, incidence, and lifeexpectancy at diagnosis of PD between Sweden and France.PD was more prevalent and had a higher incidence rate inFrance, whereas life expectancy at PD diagnosis was shorter in Neurology | Volume 107, Number 1 | July 14, 2026 e218072(7) ### Page 8 ![Figure]() Age curves were estimated using single calendar year datapoints and the predictions of the population effect of nonlinear regression mixed-effects models. We assumed a nonlinear relationship between time and incidence, usingrestricted cubic splines interpolation. Sweden. Multiple reasons might underlie such differences. InSweden, PD diagnoses are usually made in specialized inpatient or outpatient care, likely capturing more severe casesand contributing to lower prevalence and incidence andshorter survival. On the contrary, the French data set alsoincluded patients with PD managed entirely in primary care,even if this may involve evaluations by community neurologists, which may inflate estimates of prevalence and incidencerates by reduced diagnostic specificity. This diagnostic variability should, however, be less relevant for MS and MND,because specialist input is often required early on for these 2conditions. Our finding on the rising prevalence of MS corroborates andextends recent studies in developed Western countries, confirming an ongoing trend of increasing prevalence in line withimproved survival.7,28-30 Incidence rates and age at diagnosisremained fairly stable in France throughout the study. However, in Sweden, a more marked decline in incidence rates wasnoted between 2001 and 2005, which may represent an artifact due to prevalent cases with rarer contacts with health carebeing misclassified as incident MS. This interpretation issupported by alternative data sources, such as the Swedish MSRegister that shows a relatively stable MS incidence in2000–2010, ranging from 10 to 12 per 100,000 personyears.31 To reduce this potential bias from using administrative registry data lacking precise information on the date ofdiagnosis, which is less relevant with PD and MND thattypically involve more frequent follow-ups, we, therefore,opted for a 5-year washout period to capture true incidentcases in subsequent analyses. In addition, although revisions to the McDonald diagnosticcriteria (in 2001, 2005, 2010, and 2017)32-35 have been made to allow for an earlier diagnosis of MS with preserved specificity and sensitivity because of incorporation of imaging andfluid biomarker data, they have not been paralleled by a sustained increase in MS incidence.31 Our findings, therefore,support the growing consensus that while regional differencesin incidence trends may still exist,36 the dominant factor behind a rising prevalence of MS is improved survival rather thanincreased incidence.37 Arguably, this may bear witness to theimportance of improved access to disease-modulatory therapies,38 which so far lack for PD and MND. MND prevalence has increased, primarily due to populationaging, as we observed a significant upward trend in crudeincidence in France and Sweden.25,39 This trend was notentirely mitigated by age and sex standardization, however,suggesting that factors beyond aging, such as environmentalexposures or health care access, may also play a role. Unlikeother NDDs, the life expectancy at diagnosis of MND hasremained stable over the past 2 decades, reflecting the limitedimpact of available treatments on disease progression.40,41 MND is particularly well suited for studies using nationalhealth registers because of its rapid progression and the needfor hospital-based care, ensuring reliable diagnostic data. Theconsistency in age at diagnosis and life expectancy at diagnosisbetween Sweden and France, which differed more with MS orPD, supports the robustness of case identification and crosscountry comparisons. The higher incidence observed inSweden compared with France may reflect true epidemiologicdifferences rather than data artifacts. In fact, a recent Swedishstudy showed a north-south gradient in MND incidence,13similar to patterns seen in MS.42 However, to what degreea similar geographic gradient also exists in Europe as a wholeremains to be explored. Neurology | Volume 107, Number 1 | July 14, 2026 e218072(8) ### Page 9 ![Figure]() We assumed a nonlinear relationship between life expectancy and calendar time. MNDs = motor neuron diseases; MS = multiple sclerosis; PD = Parkinsondisease. This study leverages nationwide health registers withpopulation-wide coverage in 2 European countries, enablingrobust analyses of long-term trends in large and representativecohorts. We selected PD, MS, and MND because they sharea predominant motor phenotype, are among the most prevalent neurodegenerative disorders after Alzheimer disease,and, crucially, have well-defined, traceable care pathways innational health registers, including characteristic diagnosticcodes, long-term disease status, specialist care, and specificreimbursed treatments, which together enable reliable andcomparable case identification across both countries. A majorstrength is the use of truly population-based data, whichcaptures the full range of disease severity, comorbidities, andage groups, different from clinical cohorts that are often biasedtoward younger or more severe patients. However, our studyalso has limitations. First, the generalizability of our resultswarrants careful consideration. Sweden and France arehigh-income European countries with universal health carecoverage and well-established diagnostic and therapeuticinfrastructures for NDDs. The stable PD incidence observedmay partly reflect progress in reducing known risk factors (e.g., occupational exposures and pesticide regulations), whichmay not extend to countries with different environmentalpolicies or exposure patterns. For MS, the survival improvements we observed are likely driven by disease-modifyingtherapies that are expensive and not universally available, limiting the applicability of our findings to lower resource settings.For MND, a north-south gradient in incidence has been previously reported in Sweden; however, whether our findings arerepresentative of the entire European population or otherpopulations remains unknown. Caution is, therefore, warrantedwhen extrapolating these findings to other geographic or healthcare contexts, and similar studies in diverse settings are neededto assess the global applicability of these trends. Despite efforts to standardize analyses, we observed notabledifferences in the incidence rates of NDDs: more incidentcases of MS and MND were identified in Sweden, while PDwas more frequently diagnosed in France. These variationscould reflect true differences in disease risk between countriesdue to genetic (frequency of known risk alleles such as HLADRB1*15:01 for MS, LRRK2 for PD, and C9orf72 for MND), Neurology | Volume 107, Number 1 | July 14, 2026 e218072(9) ### Page 10 environmental, or other contextual factors. However, theymay also be influenced by database-specific characteristics,such as differences in coding practices, access to specialist careand diagnostic services, or the criteria used to identify cases.The data sets did not provide precise information on theclinical onset of disease, limiting our ability to evaluate diagnostic delays or prodromal periods. Case identification relied on diagnostic codes in Sweden and on prescriptions anddiagnostic codes in France, which may reduce specificity,particularly in the absence of confirmatory information. Thestudy periods in Sweden and France were not entirely overlapping, which may have influenced comparisons, especiallygiven temporal trends in disease recognition or coding. Thewashout periods applied, 2 years for PD and MND and 5 yearsfor MS, were determined through visual inspection of theincidence curves, selecting the first year in which the incidencedisplayed a stable, monotonic pattern as the start of the studyperiod to reduce the influence of prevalent cases. This approach required a trade-off between retaining sufficient datato observe meaningful temporal trends and removing individuals with preexisting disease. However, because the trueunderlying incidence trajectory is unknown, relying on apparent monotonicity may introduce misclassification, whichrepresents a limitation of the study.43 Finally, the Frenchstudy period included the COVID-19 pandemic, which mayhave influenced mortality patterns through both direct andindirect effects of the pandemic on health care access andvulnerable populations. Our study confirms that the prevalence of MS, PD, and MNDcontinues to rise, although the patterns in incidence andsurvival trends seem to differ between diseases. While improved survival—both disease-specific and as a byproduct ofbroader advances in the management of other chronic orsystemic conditions—may have contributed to the risingprevalence of PD and MS, incidence trends remain heterogeneous across diseases. Leveraging large-scale health registries for multinational studies will provide deeper insights intothe evolving epidemiology of NDDs and inform targetedpublic health interventions. ### Author Contributions O. Guinebretiere: drafting/revision of the manuscript forcontent, including medical writing for content; major role inthe acquisition of data; study concept or design; analysis orinterpretation of data. F. Yang: drafting/revision of themanuscript for content, including medical writing for content;major role in the acquisition of data; study concept or design;analysis or interpretation of data. D. Wei: drafting/revision ofthe manuscript for content, including medical writing forcontent. Q. Calonge: drafting/revision of the manuscript forcontent, including medical writing for content. Y. Hu:drafting/revision of the manuscript for content, includingmedical writing for content. K. Wirdefeldt: drafting/revisionof the manuscript for content, including medical writing forcontent. C. Ingre: drafting/revision of the manuscript forcontent, including medical writing for content. F. Piehl: drafting/revision of the manuscript for content, includingmedical writing for content. K. Modig: drafting/revision ofthe manuscript for content, including medical writing forcontent. W. Ye: drafting/revision of the manuscript for content, including medical writing for content. M. Del MarAmador: drafting/revision of the manuscript for content, including medical writing for content. S. Durrleman: drafting/revision of the manuscript for content, including medicalwriting for content. G. Bruneteau: drafting/revision of themanuscript for content, including medical writing for content.C. Louapre: drafting/revision of the manuscript for content,including medical writing for content. J.-C. Corvol: drafting/revision of the manuscript for content, including medicalwriting for content. F. Fang: drafting/revision of the manuscript for content, including medical writing for content;major role in the acquisition of data; study concept or design;analysis or interpretation of data. T. Nedelec: drafting/revision of the manuscript for content, including medicalwriting for content; major role in the acquisition of data; studyconcept or design; analysis or interpretation of data. ### Study Funding This work and the group of contributors were supported byEU Joint Programme–Neurodegenerative Disease Research(grant number: ANR-21-JPW2-0002-01; grant number atSwedish Research Council: 2021-00696) and the “Investissements d’avenir” program, reference ANR-10-IAIHU-06(Agence Nationale de la Recherche-10-IA Institut HospitaloUniversitaire-6) and reference ANR-19-P3IA-0001 (PRAIRIE 3IA Institute). ### Disclosure The LeMeReND consortium was established to build a predictive algorithm for neurodegenerative diseases, designed forimplementation in primary care settings. This initiative issupported by financial backing from the EU Joint Programme–Neurodegenerative Disease Research and involvesresearchers from Australia, France, and Sweden. F. Piehl hasreceived research grants from Denka, Janssen, Merck KGaA,Novartis, Pfizer, and UCB unrelated to commercial products,as well as fees for serving on DMC in clinical trials withLundbeck and Roche, and is supported by the Swedish Research Council (grant no. 2023-02639), the Region Stockholm (grant no. FoUI-987565), the Swedish Brain Fund(grant no. FO2023-0336), and Erling Persson’s Foundation.K. Modig received support from the Swedish ResearchCouncil for Health, Working Life and Welfare for researchprojects. K. Modig also serves as a board member on theboard for national screening of diseases at the Swedish National Board of Health and is the Vice chair in the SwedishEpidemiology Association. S. Durrleman is the co-founderand stakeholder of Qairnel SAS. C. Louapre has receivedspeaker or consultancy fees from Biogen, Sanofi, Novartis,Merck, and Oculis, not related to this study. J.-C. Corvol hasserved in advisory boards for Alzprotect, Bayer, Ferrer, iRegene, Lilly, Novartis, Servier, UCB, and Roche and receivedgrants from AXA and the ICM Foundation outside of this Neurology | Volume 107, Number 1 | July 14, 2026 e218072(10) ### Page 11 work. All other authors report no disclosures relevant to themanuscript. Generative AI (ChatGPT) was used to improvereadability and language of the work. Go tofor full disclosures. ### Publication History Received by Neurology® September 22, 2025. Accepted in final formMarch 23, 2026. Submitted and externally peer reviewed. The handlingeditor was Associate Editor Peter Hedera, MD, PhD. ## References - 1. Deuschl G, Beghi E, Fazekas F, et al. The burden of neurological diseases in Europe:an analysis for the Global Burden of Disease Study 2017. 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