[Skip to Content]
Sign In
Individual Sign In
Create an Account
Institutional Sign In
OpenAthens Shibboleth
[Skip to Content Landing]
Figure 1.
Secular Trends in Incidence Rates (Period Effects)
Secular Trends in Incidence Rates (Period Effects)

Incidence rate curves for men (blue) and women (orange) estimated using single calendar year data points (directly standardized by age to the total 1990 US population) and negative binomial regression (A-C, parkinsonism overall; D-F, Parkinson disease). The relative risk refers to the average increase in incidence rate over 10 years.

Figure 2.
Birth Cohort Trends in Incidence Rates
Birth Cohort Trends in Incidence Rates

Birth cohort curves of age- and sex-specific incidence rates for parkinsonism overall (A and B) and Parkinson disease (C and D). The central year of each 10-year birth cohort served as the cohort label. Each birth cohort contributed 3 age-specific incidence rates over 3 decades that are shown with different colors and symbols.

Figure 3.
Analyses Using Age–Period-Cohort Models
Analyses Using Age–Period-Cohort Models

Birth cohort component of the age–period-cohort models for parkinsonism overall (A and B) and Parkinson disease (C and D) in men and women separately. The birth cohort effects were displayed relative to 1920 (median year of birth for all patients with parkinsonism; circle with relative risk of 1.0) and fixing the period component to 1990 (midpoint of the study interval). For a given birth cohort year (x-axis), the figure shows the ratio of the incidence rate in that year compared with the incidence rate in the 1920 birth cohort (relative risk on the y-axis).

Table 1.  
Person-year Denominators Used to Calculate Incidence Rates
Person-year Denominators Used to Calculate Incidence Rates
Table 2.  
Age- and Sex-Specific Incidence Rates (per 100 000 Person-years) Across 3 Decades for Parkinsonism and Parkinson Diseasea
Age- and Sex-Specific Incidence Rates (per 100 000 Person-years) Across 3 Decades for Parkinsonism and Parkinson Diseasea
1.
Morozova  N, O’Reilly  EJ, Ascherio  A.  Variations in gender ratios support the connection between smoking and Parkinson’s disease.  Mov Disord. 2008;23(10):1414-1419.PubMedGoogle ScholarCrossref
2.
Thacker  EL, O’Reilly  EJ, Weisskopf  MG,  et al.  Temporal relationship between cigarette smoking and risk of Parkinson disease.  Neurology. 2007;68(10):764-768.PubMedGoogle ScholarCrossref
3.
Rocca  WA, Bower  JH, McDonnell  SK, Peterson  BJ, Maraganore  DM.  Time trends in the incidence of parkinsonism in Olmsted County, Minnesota.  Neurology. 2001;57(3):462-467.PubMedGoogle ScholarCrossref
4.
Akushevich  I, Kravchenko  J, Ukraintseva  S, Arbeev  K, Yashin  AI.  Time trends of incidence of age-associated diseases in the US elderly population: Medicare-based analysis.  Age Ageing. 2013;42(4):494-500.PubMedGoogle ScholarCrossref
5.
Lix  LM, Hobson  DE, Azimaee  M, Leslie  WD, Burchill  C, Hobson  S.  Socioeconomic variations in the prevalence and incidence of Parkinson’s disease: a population-based analysis.  J Epidemiol Community Health. 2010;64(4):335-340.PubMedGoogle ScholarCrossref
6.
Mylne  AQ, Griffiths  C, Rooney  C, Doyle  P.  Trends in Parkinson’s disease related mortality in England and Wales, 1993-2006.  Eur J Neurol. 2009;16(9):1010-1016.PubMedGoogle ScholarCrossref
7.
Goldacre  MJ, Duncan  M, Griffith  M, Turner  MR.  Trends in death certification for multiple sclerosis, motor neuron disease, Parkinson’s disease and epilepsy in English populations 1979-2006.  J Neurol. 2010;257(5):706-715.PubMedGoogle ScholarCrossref
8.
Horsfall  L, Petersen  I, Walters  K, Schrag  A.  Time trends in incidence of Parkinson’s disease diagnosis in UK primary care.  J Neurol. 2013;260(5):1351-1357.PubMedGoogle ScholarCrossref
9.
Ajdacic-Gross  V, Schmid  M, Tschopp  A, Gutzwiller  F.  Birth cohort effects in neurological diseases: amyotrophic lateral sclerosis, Parkinson’s disease and multiple sclerosis.  Neuroepidemiology. 2012;38(1):56-63.PubMedGoogle ScholarCrossref
10.
Bower  JH, Maraganore  DM, McDonnell  SK, Rocca  WA.  Incidence and distribution of parkinsonism in Olmsted County, Minnesota, 1976-1990.  Neurology. 1999;52(6):1214-1220.PubMedGoogle ScholarCrossref
11.
Savica  R, Grossardt  BR, Bower  JH, Ahlskog  JE, Rocca  WA.  Incidence and pathology of synucleinopathies and tauopathies related to parkinsonism.  JAMA Neurol. 2013;70(7):859-866.PubMedGoogle ScholarCrossref
12.
Savica  R, Grossardt  BR, Bower  JH, Boeve  BF, Ahlskog  JE, Rocca  WA.  Incidence of dementia with Lewy bodies and Parkinson disease dementia.  JAMA Neurol. 2013;70(11):1396-1402.PubMedGoogle ScholarCrossref
13.
St Sauver  JL, Grossardt  BR, Yawn  BP, Melton  LJ  III, Rocca  WA.  Use of a medical records linkage system to enumerate a dynamic population over time: the Rochester epidemiology project.  Am J Epidemiol. 2011;173(9):1059-1068.PubMedGoogle ScholarCrossref
14.
St Sauver  JL, Grossardt  BR, Leibson  CL, Yawn  BP, Melton  LJ  III, Rocca  WA.  Generalizability of epidemiological findings and public health decisions: an illustration from the Rochester Epidemiology Project.  Mayo Clin Proc. 2012;87(2):151-160.PubMedGoogle ScholarCrossref
15.
St Sauver  JL, Grossardt  BR, Yawn  BP,  et al.  Data resource profile: the Rochester Epidemiology Project (REP) medical records-linkage system.  Int J Epidemiol. 2012;41(6):1614-1624.PubMedGoogle ScholarCrossref
16.
Rocca  WA, Yawn  BP, St Sauver  JL, Grossardt  BR, Melton  LJ  III.  History of the Rochester Epidemiology Project: half a century of medical records linkage in a US population.  Mayo Clin Proc. 2012;87(12):1202-1213.PubMedGoogle ScholarCrossref
17.
Commission on Professional and Hospital Activities, National Center for Health Statistics.  H-ICDA, Hospital Adaptation of ICDA.2nd ed. Ann Arbor, MI: Commission on Professional and Hospital Activities; 1973.
18.
World Health Organization.  Manual of the International Classification of Diseases, Injuries, and Causes of Death, Based on the Recommendations of the Ninth Revision Conference, 1975, and Adopted by the Twenty-Ninth World Health Assembly. Geneva, Switzerland: World Health Organization; 1977.
19.
Collins  SJ, Ahlskog  JE, Parisi  JE, Maraganore  DM.  Progressive supranuclear palsy: neuropathologically based diagnostic clinical criteria.  J Neurol Neurosurg Psychiatry. 1995;58(2):167-173.PubMedGoogle ScholarCrossref
20.
Gilman  S, Low  P, Quinn  N,  et al; American Autonomic Society and American Academy of Neurology.  Consensus statement on the diagnosis of multiple system atrophy.  Clin Auton Res. 1998;8(6):359-362.PubMedGoogle ScholarCrossref
21.
McKeith  IG.  Consensus guidelines for the clinical and pathologic diagnosis of dementia with Lewy bodies (DLB): report of the Consortium on DLB International Workshop.  J Alzheimers Dis. 2006;9(3)(suppl):417-423.PubMedGoogle Scholar
22.
de Rijk  MC, Tzourio  C, Breteler  MM,  et al.  Prevalence of parkinsonism and Parkinson’s disease in Europe: the EUROPARKINSON Collaborative Study: European Community Concerted Action on the Epidemiology of Parkinson’s disease.  J Neurol Neurosurg Psychiatry. 1997;62(1):10-15.PubMedGoogle ScholarCrossref
23.
Bureau  UC.  1990 Census of Population and Housing Summary Tape File 1. Washington, DC: US Government Printing Office; 1990.
24.
Gardner  W, Mulvey  EP, Shaw  EC.  Regression analyses of counts and rates: Poisson, overdispersed Poisson, and negative binomial models.  Psychol Bull. 1995;118(3):392-404.PubMedGoogle ScholarCrossref
25.
Carstensen  B.  Age-period-cohort models for the Lexis diagram.  Stat Med. 2007;26(15):3018-3045.PubMedGoogle ScholarCrossref
26.
Seals  RM, Hansen  J, Gredal  O, Weisskopf  MG.  Age-period-cohort analysis of trends in amyotrophic lateral sclerosis in Denmark, 1970-2009.  Am J Epidemiol. 2013;178(8):1265-1271.PubMedGoogle ScholarCrossref
27.
Bronstein  J, Carvey  P, Chen  H,  et al.  Meeting report: consensus statement-Parkinson’s disease and the environment: collaborative on health and the environment and Parkinson’s Action Network (CHE PAN) conference 26-28 June 2007.  Environ Health Perspect. 2009;117(1):117-121.PubMedGoogle ScholarCrossref
28.
Singh  M, Ramassamy  C.  Environmental exposure to pesticides and neurodegenerative diseases.  J Alzheimers Dis Parkinsonism. 2012;2(3):e116. doi:10.4172/261-0460.100e116.Google Scholar
29.
Escobedo  LG, Peddicord  JP.  Smoking prevalence in US birth cohorts: the influence of gender and education.  Am J Public Health. 1996;86(2):231-236.PubMedGoogle ScholarCrossref
30.
American Lung Association. Trends in Tobacco Use. Chicago, IL: American Lung Association, Research and Program Services, Epidemiology and Statistics Unit; 2011.
31.
Savica  R, Grossardt  BR, Bower  JH, Ahlskog  JE, Rocca  WA.  Risk factors for Parkinson’s disease may differ in men and women: an exploratory study.  Horm Behav. 2013;63(2):308-314.PubMedGoogle ScholarCrossref
32.
Frigerio  R, Sanft  KR, Grossardt  BR,  et al.  Chemical exposures and Parkinson’s disease: a population-based case-control study.  Mov Disord. 2006;21(10):1688-1692.PubMedGoogle ScholarCrossref
33.
Tobi  EW, Slieker  RC, Stein  AD,  et al.  Early gestation as the critical time-window for changes in the prenatal environment to affect the adult human blood methylome.  Int J Epidemiol. 2015;44(4):1211-1223.PubMedGoogle ScholarCrossref
34.
Hirtz  D, Thurman  DJ, Gwinn-Hardy  K, Mohamed  M, Chaudhuri  AR, Zalutsky  R.  How common are the “common” neurologic disorders?  Neurology. 2007;68(5):326-337.PubMedGoogle ScholarCrossref
35.
Dorsey  ER, Constantinescu  R, Thompson  JP,  et al.  Projected number of people with Parkinson disease in the most populous nations, 2005 through 2030.  Neurology. 2007;68(5):384-386.PubMedGoogle ScholarCrossref
Original Investigation
August 2016

Time Trends in the Incidence of Parkinson Disease

Author Affiliations
  • 1Department of Health Sciences Research, Mayo Clinic, Rochester, Minnesota
  • 2Department of Neurology, Mayo Clinic, Rochester, Minnesota
 

Copyright 2016 American Medical Association. All Rights Reserved. Applicable FARS/DFARS Restrictions Apply to Government Use.

JAMA Neurol. 2016;73(8):981-989. doi:10.1001/jamaneurol.2016.0947
Abstract

Importance  Changes over time in the incidence of parkinsonism and Parkinson disease (PD) remain uncertain.

Objective  To investigate secular trends (period effects) and birth cohort trends in the incidence of parkinsonism and PD over 30 years in a geographically defined American population.

Design, Setting, and Participants  We used the medical records–linkage system of the Rochester Epidemiology Project to identify incidence cases of PD and other types of parkinsonism in Olmsted County, Minnesota, from 1976 to 2005. All cases were classified by a movement disorder specialist using defined criteria through the review of the complete medical records within the system. The analyses for this study were conducted between May 2015 and January 2016.

Main Outcomes and Measures  Incidence rates of parkinsonism and PD over 30 years. We tested for secular trends (period effects) using negative binomial regression models and for birth cohort effects using age–period-cohort models.

Results  Of 906 patients with parkinsonism, 501 were men, and the median age at onset was 74 years (interquartile range, 66-81 years). Of the 464 patients with PD, 275 were men, and the median age at onset was 73 years (interquartile range, 64-80 years). The overall incidence rates increased significantly over 30 years in men for both parkinsonism (relative risk [RR], 1.17 per decade; 95% CI, 1.03-1.33) and PD (RR, 1.24 per decade; 95% CI, 1.08-1.43). These trends were driven primarily by the older age groups. In particular, for men 70 years or older, incidence rates increased for both parkinsonism (RR, 1.24 per decade; 95% CI, 1.07-1.44) and PD (RR, 1.35 per decade; 95% CI, 1.10-1.65). The secular trends were not significant for women overall or in age strata. We observed an increased risk for both men and women born in the 1920 cohort (1915-1924). However, this birth cohort effect was significant only for PD and only in men.

Conclusions and Revelance  Our study suggests that the incidence of parkinsonism and PD may have increased between 1976 and 2005, particularly in men 70 years and older. These trends may be associated with the dramatic changes in smoking behavior that took place in the second half of the 20th century or with other lifestyle or environmental changes. However, the trends could be spurious and need to be confirmed in other populations.

Introduction

In 2008, Morozova et al1 suggested that smokers have a 74% reduction in risk of Parkinson disease (PD) because some constituents of tobacco may reduce the risk of PD. Under the assumption that smoking is causally associated with PD, they postulated that the drastic decline in smoking frequency that took place in US men after the peak in the 1940s and 1950s would predict an increase in the incidence of PD several decades later.1,2 However, to our knowledge, their predictions have not been tested empirically, and the long-term time trends for PD remain uncertain.3-9 Therefore, we studied time trends for parkinsonism overall and for PD over 30 years in a well-defined US population.3,10-12

Box Section Ref ID

Key Points

  • Question Is the incidence of parkinsonism and Parkinson disease changing over time?

  • Findings In this study in Olmsted County, Minnesota, the incidence of both parkinsonism and Parkinson disease increased over 30 years, particularly in men 70 years old and older. In addition, an increased risk of Parkinson disease was observed in men born in the 1920 cohort (1915-1924) compared with other birth cohorts.

  • Meaning If these trends are confirmed in other populations, they may be associated with the dramatic changes in smoking behavior during the last 50 years or with other lifestyle or environmental changes.

Methods
Case Ascertainment

Extensive details about the case ascertainment were reported elsewhere.3,10-12 Briefly, we ascertained cases of parkinsonism through the records-linkage system of the Rochester Epidemiology Project. This system provides the infrastructure for indexing and linking essentially all medical information of the population of Olmstead County, Minnesota.13-16 All medical diagnoses, surgical interventions, and other procedures are abstracted and entered into computerized indexes using the Hospital Adaptation of the International Classification of Diseases, Eighth Revision17 or the International Classification of Diseases, Ninth Revision.18

We ascertained potential cases of parkinsonism using a computerized screening phase and a subsequent clinical confirmation phase, as described in the original articles.3,10-12 The complete medical records of all persons who received at least 1 of the screening diagnostic codes from 1976 through 2005 were reviewed by a movement disorders specialist using a specifically designed abstracting form (J.H.B. for 1976 to 1990 and R.S. for 1991 to 2005). In addition, we also reviewed the records for all persons who received at least 1 of the screening diagnostic codes in 2006 to 2010. This extended period of capture ensured that patients who came to clinical attention up to 5 years after the study period were appropriately counted as incident patients if the onset of symptoms had occurred during the study period (lag time between onset of symptoms and clinical diagnosis). The movement disorder specialist defined the year of onset of parkinsonism and the type of parkinsonism using specified diagnostic criteria and following a manual of instructions.10,19-21 To be included in our study, patients were required to reside in Olmsted County at the time of onset of parkinsonian symptoms, and we excluded persons who denied authorization to use their medical records for research.13 However, informed consent specific for this study was not required because all of the data were abstracted from medical records, and none of the patients were contacted. All study procedures and ethical aspects were approved by the institutional review boards of the Mayo Clinic and Olmsted Medical Center.

Diagnostic Criteria

Our diagnostic criteria included 2 steps: the definition of parkinsonism as a syndrome and the definition of the different types of parkinsonism within the syndrome. Parkinsonism was defined as the presence of at least 2 of 4 cardinal signs: rest tremor, bradykinesia, rigidity, and impaired postural reflexes. Parkinson disease was defined as parkinsonism with all 3 of the following features: no other cause (eg, repeated stroke with stepwise progression, repeated head injury, history of encephalitis, neuroleptic treatment ≤6 months before onset, hydrocephalus, or brain tumor); no documentation of unresponsiveness to levodopa at doses of at least 1 g/day in combination with carbidopa (applicable only to patients who were treated); and no prominent or early (<1 year from onset) signs of more extensive nervous system involvement (eg, dysautonomia) not explained otherwise.10 The other types of parkinsonism were classified as reported elsewhere.11

Reliability and Validity of Diagnoses

The case-finding procedures were valid and reliable as described more extensively elsewhere.10,11 In brief, an independent records review by the 2 movement disorders specialists who applied the same diagnostic criteria (J.H.B. and R.S.) showed 90% agreement on the presence of parkinsonism and 70% agreement on the exclusion of parkinsonism (sample classified by R.S. as 30 patients with parkinsonism and 10 persons free of parkinsonism from the 1991-2005 incidence study).11 In general, the agreement on the year of onset of parkinsonism was also high (intraclass correlation coefficient, 0.85; 95% CI, 0.77-0.92).11 Finally, a comparison of clinical diagnoses of specific proteinopathies (synucleinopathies and tauopathies) with autopsy findings in 65 patients who had died showed 81.5% agreement.11

Data Analysis

All individuals who met criteria for parkinsonism and were residents of Olmsted County at the time of symptom onset between January 1, 1976, and December 31, 2005, were included as incident patients. We calculated incidence rates using incident patients as the numerator and population counts from the Rochester Epidemiology Project Census as the denominator.13 Consistent with the methods used in the initial incidence study10 and used again in the more recent incidence study,11 the denominator person-years were corrected by removing prevalent patients with parkinsonism.22

We computed age-, sex-, and decade-specific incidence rates for parkinsonism (of all types) and for PD. In addition, we investigated changes in incidence rates separately for men and women in 2 broad age classes: younger than 70 years and 70 years and older. Incidence rates were directly standardized by age to the total US population from the 1990 decennial census (midpoint of the 30-year period) when overall rates were compared.23

We performed statistical testing of the time trends (period effects) using negative binomial regression models.24 Negative binomial regression was used instead of Poisson regression because we had a number of zero counts and larger variance in some models.24 The unit of observation was the incidence rate in a single calendar year (directly standardized by age to the total 1990 US population).23 We calculated a relative risk (RR) and the corresponding 95% CI to measure the average increase in the incidence rate over 10 calendar years.

Changes in incidence rates of parkinsonism and PD across individuals born at different times (birth cohort effects) were investigated graphically using birth cohort curves constructed with decennium-specific incidence rates for men and women separately. Birth cohorts of 10 calendar years were considered; the central year served as the cohort label.3 Consistent with the 10-year frame of analysis, we disaggregated the incidence rates by 10-year age classes. We also explored birth cohort effects and period effects using age–period-cohort models as described elsewhere.25,26 For these analyses, we constructed 5-year period incidence rates and 5-year birth cohort incidence rates and used natural splines to model nonlinear effects. All statistical testing was done at the conventional α level of .05 (2-tailed). We used SAS, version 9.3 (SAS Institute Inc) and the EPI package in R (R Foundation for Statistical Computing) for analyses.25

Results
Secular Trends (Period Effects)

We included 906 incident cases of parkinsonism of any type with onset between January 1, 1976, and December 31, 2005.3,10,11Table 1 shows the person-year denominators used to calculate the incidence rates. Table 2 shows the age- and sex-specific incidence rates (cases per 100 000 person-years) for parkinsonism (of all types) and PD in 3 decades. Figure 1 shows incidence rates age-standardized to the total 1990 US population estimated using single calendar year data points and negative binomial regression in men and women separately for parkinsonism and for PD. The incidence rates for parkinsonism of all types and for PD were higher in men than in women across all 3 decades (Figure 1).

Age-adjusted incidence rates of parkinsonism were stable for women over the 30-year time frame; however, they increased in men from 38.8 cases per 100 000 person-years between 1976 and 1985 to 56.0 between 1996 and 2005 (Table 2). Analyses using negative binomial regression models showed a significant increase in incidence rates for men (RR, 1.17 per decade; 95% CI, 1.03-1.33; P = .01, Figure 1A) but not for women. We also observed a significant sex by calendar year interaction (the slope of increase was greater in men than women). The increase in incidence rates was greater for men 70 years or older (RR, 1.24 per decade; 95% CI, 1.07-1.44; P = .005, Figure 1C) than in men younger than 70 years (Figure 1B). However, the age by calendar year interaction in men was not significant.

Similarly, the age-adjusted incidence rate of PD increased in men from 18.2 between 1976 and 1985 to 30.5 between 1996 and 2005 (Table 2). Analyses using negative binomial regression models showed a significant increase in incidence rates in men (RR, 1.24 per decade; 95% CI, 1.08-1.43; P = .003, Figure 1D) but not for women. However, the sex by calendar year interaction was not significant. The increase was greater for men 70 years or older (RR, 1.35 per decade; 95% CI, 1.10-1.65; P = .004, Figure 1F) than for men younger than 70 years (Figure 1E). However, the age by calendar year interaction in men was not significant. Women 70 years or older also experienced an increase in the incidence rate of PD; however, the trend was not statistically significant (RR, 1.24 per decade; 95% CI, 0.94-1.64; P = .12, Figure 1F).

Birth Cohort Trends

Each 10-year birth cohort contributed 3 age-specific incidence rates over 3 decades that are shown with different colors and symbols in Figure 2. Our graphical analyses of birth cohort effects revealed a possible higher incidence of both parkinsonism and PD in men and women born in the 1920 cohort. Men and women born in the 1920 cohort (1915-1924) are represented by the orange line with square symbols. However, in age–period-cohort models, the birth cohort effect was significant only for PD and only for men (Figure 3).

Discussion

Our study suggests an increase in the incidence of both parkinsonism of all types and of PD during the 30-year period between 1976 and 2005, particularly in men 70 years or older. Although no trend was evident overall for women, women in the age group 70 years or older experienced an increase in the incidence of PD with borderline statistical significance. We also observed higher incidence rates of PD for men born in the 1920 cohort. Our study provides evidence contrary to 2 previous US studies and 1 Canadian study that showed no trend and particularly contrary to 3 UK studies suggesting a possible decline in the occurrence of PD over time.3-8 A study using Swiss mortality data suggested a possible birth cohort effect, with higher risk for cohorts born before the 1920s.9

The time trends that we observed need to be interpreted with caution. First, the trends may be an artifact caused by increased awareness of symptoms and improved access to care of patients or to increased awareness of signs and symptoms of parkinsonism by physicians. For example, the trends may be associated with a better recognition by physicians of parkinsonism and PD in the older patients in the past few decades or to a more inclusive diagnostic adjudication in the more recent segment of the study (R.S. vs J.H.B. adjudication). It is possible that in the earlier years of our study, elderly persons with cardiovascular conditions, cancer, or other diseases were not diagnosed as having parkinsonism because the symptoms of parkinsonism were not considered important in the overall clinical management and were not considered a major cause of disability or of mortality. In the more recent years, physicians may have started to recognize parkinsonism even in the context of complex multimorbidity. Against a diagnostic artifact is the decline in the incidence of drug-induced parkinsonism observed in this same population during the same period (data not shown). In addition, against a diagnostic artifact is the adequate agreement between the 2 movement disorders specialists and the good validity of the clinical diagnosis compared with autopsy findings.10,11 Finally, the observation that the time trends were more evident in men than in women may support a genuine trend in incidence because the recognition of the symptoms of parkinsonism in the context of multimorbidity should have changed similarly over time in men and women.

A second possible cause for a spurious increase in incidence rates is a change in coding practices in the records-linkage system or the switch from International Classification of Diseases, Eighth Revision to International Classification of Diseases, Ninth Revision coding in 1994. Because our case ascertainment was a laborious process involving a sensitive screening phase (inclusion of a large set of diagnostic codes to increase sensitivity even at the expense of lower specificity) and a detailed review of the medical records of those patients who screened positive, we did not rely on electronic codes to define the disease.10,11 Although we cannot exclude a trend in coding practices, we do not think that this was sizeable, if any. Finally, another possible cause for a spurious trend is a change over time in the percentage of people who denied authorization to use their medical records for research. However, the law requiring authorization was only introduced in 1997 (Minnesota state privacy law), and the authorization rate has always been greater than 95% since 1997.15 In summary, during the 30 years of study, the health care practices in Olmsted County have not changed, the in and out migration has been limited, especially in the age groups at risk for parkinsonism, and the percentage of the population covered by the Rochester Epidemiology Project has remained stable.15

If the trend of increasing incidence rates is genuine and can be replicated in other populations, it has major implications for etiologic research and for public health. From a research perspective, the trend should prompt studies to identify possible environmental or lifestyle changes during the life span of the study participants.1,27,28 If we assume that the association of smoking with reduced risk of PD has a biological basis, our findings may be explained in part by time trends in smoking.1,2 Smoking behavior in industrialized nations, including the United States, has changed dramatically over the second half of the 20th century, with diverging patterns in men and women.29 The prevalence of smoking in the United States peaked in the 1940s and 1950s at approximately 67% for men and in the 1960s at approximately 44% for women. However, in the past 25 years, the gap between men and women has narrowed. Between 1965 and 2009 (44 years), the frequency declined from 51.9% to 23.5% in men and from 33.9% to 17.9% in women.30 The decline in smoking rates in men may explain in part the increasing incidence of parkinsonism and PD.1 However, other environmental or lifestyle risk or protective factors that are related to sex may also be involved such as pesticide use, head trauma, and coffee consumption.1,31,32 The possible higher risk of PD for men and women born in the 1920 birth cohort (1915-1924) may suggest exposures that took place during intrauterine life or in early life (eg, intrauterine infection, toxic exposure, or dietary deficiency).33 Further studies are needed to confirm these etiologic hypotheses. From a public health perspective, an increase in the incidence of parkinsonism and PD would modify our projections for the total number of persons with parkinsonism or PD in the coming decades.34,35

Our study has a number of strengths. To our knowledge, it is the first study to consider long-term secular trends in incidence (over 30 years) and to analyze the data both as secular trends (period effects) and as birth cohort trends. Our study is also unique in the extent of clinical precision. The full record of each patient was reviewed by a movement disorders specialist to confirm the diagnosis of parkinsonism and to meticulously classify different types of parkinsonism. This level of diagnostic precision is impossible when dealing with death certificate data or with administrative data (eg, billing data). Second, our study was conducted in a relatively stable population, using a population-based records-linkage system that spans across the entire life of the individuals included.13-16 The case-finding procedures and the diagnostic criteria used in the 2 studies that were combined were similar, so the observed changes are not caused by changes in methods. In addition, all of the patients with parkinsonism were adjudicated by a movement disorders specialist at the time of medical record abstraction to reduce differences in the diagnostic criteria over time or across the different specialists. Third, all of the medical facilities in Olmsted County are included in the Rochester Epidemiology Project,13-16 and it is unlikely that a patient with parkinsonism would have been seen exclusively outside of the county while living in the county. To avoid the risk of underestimating incidence rates of parkinsonism in the eldest age groups, we corrected our census denominators by removing prevalent cases of parkinsonism. However, the effects of these corrections were small (data not shown).

Our study also has a number of limitations. First, our study population was somewhat small to provide stable incidence rates and to conduct more definitive age–period-cohort analyses. This limitation was insurmountable because our case finding is based on the unique records-linkage system serving Olmsted County, and a study of time trends for PD would be highly impractical in another population without the system. Second, we could not analyze the time trends in less common subtypes of parkinsonism (eg, multiple system atrophy) because of sample size limitations. Third, changes in clinical practice and the introduction of new sets of diagnostic criteria during the time frame of the 1991-2005 study could have changed the differential diagnosis by subtypes of parkinsonism, thus creating spurious trends in subtypes. As evidence against this possible bias, the overall distribution of subtypes of parkinsonism was similar in the 1976-1990 study and in the 1991-2005 study. In addition, a trend in the classification of subtypes of parkinsonism should not influence the overall trends for parkinsonism.

Conclusions

Our study suggests that the incidence of parkinsonism and PD may have increased between 1976 and 2005, particularly in men 70 years old and older. These trends may be associated with the dramatic changes in smoking behavior that took place in the second half of the 20th century or with other lifestyle or environmental changes. However, the trends could be spurious and need to be confirmed in other populations.

Back to top
Article Information

Corresponding Author: Walter A. Rocca, MD, MPH, Department of Health Sciences Research, Mayo Clinic, 200 First St SW, Rochester, MN 55905 (rocca@mayo.edu).

Accepted for Publication: March 8, 2016.

Published Online: June 20, 2016. doi:10.1001/jamaneurol.2016.0947.

Author Contributions: Dr Rocca had full access to all of the data in the study and takes responsibility for the integrity of the data and the accuracy of the data analysis.

Study concept and design: Rocca, Savica.

Acquisition, analysis, or interpretation of data: All authors.

Drafting of the manuscript: Rocca, Savica.

Critical revision of the manuscript for important intellectual content: All authors.

Statistical analysis: Grossardt.

Obtained funding: Rocca.

Administrative, technical, or material support: Rocca, Savica.

Study supervision: Rocca.

Conflict of Interest Disclosures: None reported.

Funding/Support: This study was supported by award R01 AG034676 from the National Institute on Aging of the National Institutes of Health and by the Mayo Foundation for Medical Education and Research.

Role of the Funder/Sponsor: The funding organizations and sponsors had no role in the design and conduct of the study; collection, management, analysis, and interpretation of the data; preparation, review, or approval of the manuscript; and decision to submit the manuscript for publication.

References
1.
Morozova  N, O’Reilly  EJ, Ascherio  A.  Variations in gender ratios support the connection between smoking and Parkinson’s disease.  Mov Disord. 2008;23(10):1414-1419.PubMedGoogle ScholarCrossref
2.
Thacker  EL, O’Reilly  EJ, Weisskopf  MG,  et al.  Temporal relationship between cigarette smoking and risk of Parkinson disease.  Neurology. 2007;68(10):764-768.PubMedGoogle ScholarCrossref
3.
Rocca  WA, Bower  JH, McDonnell  SK, Peterson  BJ, Maraganore  DM.  Time trends in the incidence of parkinsonism in Olmsted County, Minnesota.  Neurology. 2001;57(3):462-467.PubMedGoogle ScholarCrossref
4.
Akushevich  I, Kravchenko  J, Ukraintseva  S, Arbeev  K, Yashin  AI.  Time trends of incidence of age-associated diseases in the US elderly population: Medicare-based analysis.  Age Ageing. 2013;42(4):494-500.PubMedGoogle ScholarCrossref
5.
Lix  LM, Hobson  DE, Azimaee  M, Leslie  WD, Burchill  C, Hobson  S.  Socioeconomic variations in the prevalence and incidence of Parkinson’s disease: a population-based analysis.  J Epidemiol Community Health. 2010;64(4):335-340.PubMedGoogle ScholarCrossref
6.
Mylne  AQ, Griffiths  C, Rooney  C, Doyle  P.  Trends in Parkinson’s disease related mortality in England and Wales, 1993-2006.  Eur J Neurol. 2009;16(9):1010-1016.PubMedGoogle ScholarCrossref
7.
Goldacre  MJ, Duncan  M, Griffith  M, Turner  MR.  Trends in death certification for multiple sclerosis, motor neuron disease, Parkinson’s disease and epilepsy in English populations 1979-2006.  J Neurol. 2010;257(5):706-715.PubMedGoogle ScholarCrossref
8.
Horsfall  L, Petersen  I, Walters  K, Schrag  A.  Time trends in incidence of Parkinson’s disease diagnosis in UK primary care.  J Neurol. 2013;260(5):1351-1357.PubMedGoogle ScholarCrossref
9.
Ajdacic-Gross  V, Schmid  M, Tschopp  A, Gutzwiller  F.  Birth cohort effects in neurological diseases: amyotrophic lateral sclerosis, Parkinson’s disease and multiple sclerosis.  Neuroepidemiology. 2012;38(1):56-63.PubMedGoogle ScholarCrossref
10.
Bower  JH, Maraganore  DM, McDonnell  SK, Rocca  WA.  Incidence and distribution of parkinsonism in Olmsted County, Minnesota, 1976-1990.  Neurology. 1999;52(6):1214-1220.PubMedGoogle ScholarCrossref
11.
Savica  R, Grossardt  BR, Bower  JH, Ahlskog  JE, Rocca  WA.  Incidence and pathology of synucleinopathies and tauopathies related to parkinsonism.  JAMA Neurol. 2013;70(7):859-866.PubMedGoogle ScholarCrossref
12.
Savica  R, Grossardt  BR, Bower  JH, Boeve  BF, Ahlskog  JE, Rocca  WA.  Incidence of dementia with Lewy bodies and Parkinson disease dementia.  JAMA Neurol. 2013;70(11):1396-1402.PubMedGoogle ScholarCrossref
13.
St Sauver  JL, Grossardt  BR, Yawn  BP, Melton  LJ  III, Rocca  WA.  Use of a medical records linkage system to enumerate a dynamic population over time: the Rochester epidemiology project.  Am J Epidemiol. 2011;173(9):1059-1068.PubMedGoogle ScholarCrossref
14.
St Sauver  JL, Grossardt  BR, Leibson  CL, Yawn  BP, Melton  LJ  III, Rocca  WA.  Generalizability of epidemiological findings and public health decisions: an illustration from the Rochester Epidemiology Project.  Mayo Clin Proc. 2012;87(2):151-160.PubMedGoogle ScholarCrossref
15.
St Sauver  JL, Grossardt  BR, Yawn  BP,  et al.  Data resource profile: the Rochester Epidemiology Project (REP) medical records-linkage system.  Int J Epidemiol. 2012;41(6):1614-1624.PubMedGoogle ScholarCrossref
16.
Rocca  WA, Yawn  BP, St Sauver  JL, Grossardt  BR, Melton  LJ  III.  History of the Rochester Epidemiology Project: half a century of medical records linkage in a US population.  Mayo Clin Proc. 2012;87(12):1202-1213.PubMedGoogle ScholarCrossref
17.
Commission on Professional and Hospital Activities, National Center for Health Statistics.  H-ICDA, Hospital Adaptation of ICDA.2nd ed. Ann Arbor, MI: Commission on Professional and Hospital Activities; 1973.
18.
World Health Organization.  Manual of the International Classification of Diseases, Injuries, and Causes of Death, Based on the Recommendations of the Ninth Revision Conference, 1975, and Adopted by the Twenty-Ninth World Health Assembly. Geneva, Switzerland: World Health Organization; 1977.
19.
Collins  SJ, Ahlskog  JE, Parisi  JE, Maraganore  DM.  Progressive supranuclear palsy: neuropathologically based diagnostic clinical criteria.  J Neurol Neurosurg Psychiatry. 1995;58(2):167-173.PubMedGoogle ScholarCrossref
20.
Gilman  S, Low  P, Quinn  N,  et al; American Autonomic Society and American Academy of Neurology.  Consensus statement on the diagnosis of multiple system atrophy.  Clin Auton Res. 1998;8(6):359-362.PubMedGoogle ScholarCrossref
21.
McKeith  IG.  Consensus guidelines for the clinical and pathologic diagnosis of dementia with Lewy bodies (DLB): report of the Consortium on DLB International Workshop.  J Alzheimers Dis. 2006;9(3)(suppl):417-423.PubMedGoogle Scholar
22.
de Rijk  MC, Tzourio  C, Breteler  MM,  et al.  Prevalence of parkinsonism and Parkinson’s disease in Europe: the EUROPARKINSON Collaborative Study: European Community Concerted Action on the Epidemiology of Parkinson’s disease.  J Neurol Neurosurg Psychiatry. 1997;62(1):10-15.PubMedGoogle ScholarCrossref
23.
Bureau  UC.  1990 Census of Population and Housing Summary Tape File 1. Washington, DC: US Government Printing Office; 1990.
24.
Gardner  W, Mulvey  EP, Shaw  EC.  Regression analyses of counts and rates: Poisson, overdispersed Poisson, and negative binomial models.  Psychol Bull. 1995;118(3):392-404.PubMedGoogle ScholarCrossref
25.
Carstensen  B.  Age-period-cohort models for the Lexis diagram.  Stat Med. 2007;26(15):3018-3045.PubMedGoogle ScholarCrossref
26.
Seals  RM, Hansen  J, Gredal  O, Weisskopf  MG.  Age-period-cohort analysis of trends in amyotrophic lateral sclerosis in Denmark, 1970-2009.  Am J Epidemiol. 2013;178(8):1265-1271.PubMedGoogle ScholarCrossref
27.
Bronstein  J, Carvey  P, Chen  H,  et al.  Meeting report: consensus statement-Parkinson’s disease and the environment: collaborative on health and the environment and Parkinson’s Action Network (CHE PAN) conference 26-28 June 2007.  Environ Health Perspect. 2009;117(1):117-121.PubMedGoogle ScholarCrossref
28.
Singh  M, Ramassamy  C.  Environmental exposure to pesticides and neurodegenerative diseases.  J Alzheimers Dis Parkinsonism. 2012;2(3):e116. doi:10.4172/261-0460.100e116.Google Scholar
29.
Escobedo  LG, Peddicord  JP.  Smoking prevalence in US birth cohorts: the influence of gender and education.  Am J Public Health. 1996;86(2):231-236.PubMedGoogle ScholarCrossref
30.
American Lung Association. Trends in Tobacco Use. Chicago, IL: American Lung Association, Research and Program Services, Epidemiology and Statistics Unit; 2011.
31.
Savica  R, Grossardt  BR, Bower  JH, Ahlskog  JE, Rocca  WA.  Risk factors for Parkinson’s disease may differ in men and women: an exploratory study.  Horm Behav. 2013;63(2):308-314.PubMedGoogle ScholarCrossref
32.
Frigerio  R, Sanft  KR, Grossardt  BR,  et al.  Chemical exposures and Parkinson’s disease: a population-based case-control study.  Mov Disord. 2006;21(10):1688-1692.PubMedGoogle ScholarCrossref
33.
Tobi  EW, Slieker  RC, Stein  AD,  et al.  Early gestation as the critical time-window for changes in the prenatal environment to affect the adult human blood methylome.  Int J Epidemiol. 2015;44(4):1211-1223.PubMedGoogle ScholarCrossref
34.
Hirtz  D, Thurman  DJ, Gwinn-Hardy  K, Mohamed  M, Chaudhuri  AR, Zalutsky  R.  How common are the “common” neurologic disorders?  Neurology. 2007;68(5):326-337.PubMedGoogle ScholarCrossref
35.
Dorsey  ER, Constantinescu  R, Thompson  JP,  et al.  Projected number of people with Parkinson disease in the most populous nations, 2005 through 2030.  Neurology. 2007;68(5):384-386.PubMedGoogle ScholarCrossref
×