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Table 1.  Characteristics of the 2000 and 2012 Cohortsa
Characteristics of the 2000 and 2012 Cohortsa
Table 2.  Cognitive Function, at Age 65 Years or Older, in the 2000 and 2012 Cohortsa
Cognitive Function, at Age 65 Years or Older, in the 2000 and 2012 Cohortsa
Table 3.  Cognitive Function, by Age Range, 2000 and 2012 Cohorts
Cognitive Function, by Age Range, 2000 and 2012 Cohorts
Table 4.  Odds Ratios for Presence of Dementia in 2000 and 2012 Among a Cohort of 21 057a
Odds Ratios for Presence of Dementia in 2000 and 2012 Among a Cohort of 21 057a
1.
Plassman  BL, Langa  KM, Fisher  GG,  et al.  Prevalence of dementia in the United States: the aging, demographics, and memory study.  Neuroepidemiology. 2007;29(1-2):125-132.PubMedGoogle ScholarCrossref
2.
Hurd  MD, Martorell  P, Delavande  A, Mullen  KJ, Langa  KM.  Monetary costs of dementia in the United States.  N Engl J Med. 2013;368(14):1326-1334.PubMedGoogle ScholarCrossref
3.
Prince  M, Bryce  R, Albanese  E, Wimo  A, Ribeiro  W, Ferri  CP.  The global prevalence of dementia: a systematic review and meta-analysis.  Alzheimers Dement. 2013;9(1):63-75.Google ScholarCrossref
4.
Larson  EB, Yaffe  K, Langa  KM.  New insights into the dementia epidemic.  N Engl J Med. 2013;369(24):2275-2277.PubMedGoogle ScholarCrossref
5.
Gerstorf  D, Hülür  G, Drewelies  J,  et al.  Secular changes in late-life cognition and well-being: towards a long bright future with a short brisk ending?  Psychol Aging. 2015;30(2):301-310.PubMedGoogle ScholarCrossref
6.
Wu  YT, Fratiglioni  L, Matthews  FE,  et al.  Dementia in western Europe: epidemiological evidence and implications for policy making.  Lancet Neurol. 2016;15(1):116-124.PubMedGoogle ScholarCrossref
7.
Satizabal  CL, Beiser  AS, Chouraki  V, Chêne  G, Dufouil  C, Seshadri  S.  Incidence of dementia over three decades in the Framingham Heart Study.  N Engl J Med. 2016;374(6):523-532.PubMedGoogle ScholarCrossref
8.
Matthews  FE, Arthur  A, Barnes  LE,  et al; Medical Research Council Cognitive Function and Ageing Collaboration.  A two-decade comparison of prevalence of dementia in individuals aged 65 years and older from three geographical areas of England: results of the Cognitive Function and Ageing Study I and II.  Lancet. 2013;382(9902):1405-1412.PubMedGoogle ScholarCrossref
9.
Ogden  CL, Carroll  MD, Kit  BK, Flegal  KM.  Prevalence of childhood and adult obesity in the United States, 2011-2012.  JAMA. 2014;311(8):806-814.PubMedGoogle ScholarCrossref
10.
Ogden  C, Carroll  M. Prevalence of overweight, obesity, and extreme obesity among adults: United States, trends 1960-1962 through 2007-2008. June 2010. http://www.cdc.gov/nchs/data/hestat/obesity_adult_07_08/obesity_adult_07_08.pdf. Accessed August 8, 2016.
11.
Gregg  EW, Li  Y, Wang  J,  et al.  Changes in diabetes-related complications in the United States, 1990-2010.  N Engl J Med. 2014;370(16):1514-1523.PubMedGoogle ScholarCrossref
12.
Federal Interagency Forum on Aging-Related Statistics. Older Americans 2012: Key Indicators of Well-Being. Washington, DC: US Government Printing Office. June 2012. http://www.agingstats.gov/docs/PastReports/2012/OA2012.pdf. Accessed August 8, 2016.
13.
Langa  KM, Larson  EB, Karlawish  JH,  et al.  Trends in the prevalence and mortality of cognitive impairment in the United States: is there evidence of a compression of cognitive morbidity?  Alzheimers Dement. 2008;4(2):134-144.PubMedGoogle ScholarCrossref
14.
Vemuri  P, Lesnick  TG, Przybelski  SA,  et al.  Association of lifetime intellectual enrichment with cognitive decline in the older population.  JAMA Neurol. 2014;71(8):1017-1024.PubMedGoogle ScholarCrossref
15.
Stern  Y, Albert  S, Tang  MX, Tsai  WY.  Rate of memory decline in AD is related to education and occupation: cognitive reserve?  Neurology. 1999;53(9):1942-1947.PubMedGoogle ScholarCrossref
16.
Sonnega  A, Faul  JD, Ofstedal  MB, Langa  KM, Phillips  JW, Weir  DR.  Cohort Profile: the Health and Retirement Study (HRS).  Int J Epidemiol. 2014;43(2):576-585.PubMedGoogle ScholarCrossref
17.
Health and Retirement Study (HRS) Sample Sizes and Response Rates. 2011; http://hrsonline.isr.umich.edu/sitedocs/sampleresponse.pdf. Accessed August 8, 2016.
18.
Crimmins  EM, Kim  JK, Langa  KM, Weir  DR.  Assessment of cognition using surveys and neuropsychological assessment: the Health and Retirement Study and the Aging, Demographics, and Memory Study.  J Gerontol B Psychol Sci Soc Sci. 2011;66(suppl 1):i162-i171.PubMedGoogle ScholarCrossref
19.
Langa  KM, Plassman  BL, Wallace  RB,  et al.  The Aging, Demographics, and Memory Study: study design and methods.  Neuroepidemiology. 2005;25(4):181-191.PubMedGoogle ScholarCrossref
20.
Ofstedal  MB, Fisher  GG, Herzog  AR. Documentation of cognitive functioning measures in the Health and Retirement Study. 2005; http://hrsonline.isr.umich.edu/sitedocs/userg/dr-006.pdf. Accessed August 8, 2016.
21.
Norton  S, Matthews  FE, Barnes  DE, Yaffe  K, Brayne  C.  Potential for primary prevention of Alzheimer’s disease: an analysis of population-based data.  Lancet Neurol. 2014;13(8):788-794.PubMedGoogle ScholarCrossref
22.
Rietveld  CA, Medland  SE, Derringer  J,  et al; LifeLines Cohort Study.  GWAS of 126,559 individuals identifies genetic variants associated with educational attainment.  Science. 2013;340(6139):1467-1471.PubMedGoogle ScholarCrossref
23.
Rietveld  CA, Esko  T, Davies  G,  et al.  Common genetic variants associated with cognitive performance identified using the proxy-phenotype method.  Proc Natl Acad Sci U S A. 2014;111(38):13790-13794.PubMedGoogle ScholarCrossref
24.
Deary  IJ, Yang  J, Davies  G,  et al.  Genetic contributions to stability and change in intelligence from childhood to old age.  Nature. 2012;482(7384):212-215.PubMedGoogle Scholar
25.
Fitzpatrick  AL, Kuller  LH, Lopez  OL,  et al.  Midlife and late-life obesity and the risk of dementia: cardiovascular health study.  Arch Neurol. 2009;66(3):336-342.PubMedGoogle ScholarCrossref
26.
Hughes  TF, Borenstein  AR, Schofield  E, Wu  Y, Larson  EB.  Association between late-life body mass index and dementia: the Kame Project.  Neurology. 2009;72(20):1741-1746.PubMedGoogle ScholarCrossref
27.
Tolppanen  AM, Ngandu  T, Kåreholt  I,  et al.  Midlife and late-life body mass index and late-life dementia: results from a prospective population-based cohort.  J Alzheimers Dis. 2014;38(1):201-209.PubMedGoogle Scholar
28.
Schrijvers  EM, Verhaaren  BF, Koudstaal  PJ, Hofman  A, Ikram  MA, Breteler  MM.  Is dementia incidence declining? trends in dementia incidence since 1990 in the Rotterdam Study.  Neurology. 2012;78(19):1456-1463.PubMedGoogle ScholarCrossref
29.
Qiu  C, von Strauss  E, Bäckman  L, Winblad  B, Fratiglioni  L.  Twenty-year changes in dementia occurrence suggest decreasing incidence in central Stockholm, Sweden.  Neurology. 2013;80(20):1888-1894.PubMedGoogle ScholarCrossref
30.
Christensen  K, Thinggaard  M, Oksuzyan  A,  et al.  Physical and cognitive functioning of people older than 90 years: a comparison of two Danish cohorts born 10 years apart.  Lancet. 2013;382(9903):1507-1513.PubMedGoogle ScholarCrossref
31.
Dodge  HH, Zhu  J, Lee  CW, Chang  CC, Ganguli  M.  Cohort effects in age-associated cognitive trajectories.  J Gerontol A Biol Sci Med Sci. 2014;69(6):687-694.PubMedGoogle ScholarCrossref
Original Investigation
January 2017

A Comparison of the Prevalence of Dementia in the United States in 2000 and 2012

Author Affiliations
  • 1Department of Internal Medicine, University of Michigan Medical School, Ann Arbor
  • 2Veterans Affairs Center for Clinical Management Research, Ann Arbor, Michigan
  • 3Institute for Social Research, University of Michigan, Ann Arbor
  • 4Institute for Healthcare Policy and Innovation, University of Michigan, Ann Arbor
  • 5Group Health Research Institute, Departments of Medicine and Health Services, University of Washington, Seattle
  • 6Andrus Gerontology Center, University of Southern California, Los Angeles
  • 7Department of Neurology and Stroke Program, University of Michigan, Ann Arbor
JAMA Intern Med. 2017;177(1):51-58. doi:10.1001/jamainternmed.2016.6807
Key Points

Question  Has the prevalence of dementia among older adults in the United States changed between 2000 and 2012?

Findings  In this observational cohort study of more than 21 000 US adults 65 years or older from the nationally representative Health and Retirement Study, dementia prevalence declined significantly, from 11.6% in 2000 to 8.8% in 2012.

Meaning  Population brain health seemed to improve between 2000 and 2012; increasing educational attainment and better control of cardiovascular risk factors may have contributed to the improvement, but the full set of social, behavioral, and medical factors contributing to the improvement is still uncertain.

Abstract

Importance  The aging of the US population is expected to lead to a large increase in the number of adults with dementia, but some recent studies in the United States and other high-income countries suggest that the age-specific risk of dementia may have declined over the past 25 years. Clarifying current and future population trends in dementia prevalence and risk has important implications for patients, families, and government programs.

Objective  To compare the prevalence of dementia in the United States in 2000 and 2012.

Design, Setting, and Participants  We used data from the Health and Retirement Study (HRS), a nationally representative, population-based longitudinal survey of individuals in the United States 65 years or older from the 2000 (n = 10 546) and 2012 (n = 10 511) waves of the HRS.

Main Outcomes and Measures  Dementia was identified in each year using HRS cognitive measures and validated methods for classifying self-respondents, as well as those represented by a proxy. Logistic regression was used to identify socioeconomic and health variables associated with change in dementia prevalence between 2000 and 2012.

Results  The study cohorts had an average age of 75.0 years (95% CI, 74.8-75.2 years) in 2000 and 74.8 years (95% CI, 74.5-75.1 years) in 2012 (P = .24); 58.4% (95% CI, 57.3%-59.4%) of the 2000 cohort was female compared with 56.3% (95% CI, 55.5%-57.0%) of the 2012 cohort (P < .001). Dementia prevalence among those 65 years or older decreased from 11.6% (95% CI, 10.7%-12.7%) in 2000 to 8.8% (95% CI, 8.2%-9.4%) (8.6% with age- and sex-standardization) in 2012 (P < .001). More years of education was associated with a lower risk for dementia, and average years of education increased significantly (from 11.8 years [95% CI, 11.6-11.9 years] to 12.7 years [95% CI, 12.6-12.9 years]; P < .001) between 2000 and 2012. The decline in dementia prevalence occurred even though there was a significant age- and sex-adjusted increase between years in the cardiovascular risk profile (eg, prevalence of hypertension, diabetes, and obesity) among older US adults.

Conclusions and Relevance  The prevalence of dementia in the United States declined significantly between 2000 and 2012. An increase in educational attainment was associated with some of the decline in dementia prevalence, but the full set of social, behavioral, and medical factors contributing to the decline is still uncertain. Continued monitoring of trends in dementia incidence and prevalence will be important for better gauging the full future societal impact of dementia as the number of older adults increases in the decades ahead.

Introduction

Dementia, a decline in memory and other cognitive functions that leads to a loss of independent function, is a common and feared geriatric syndrome that affects an estimated 4 to 5 million older adults in the United States1 and has a large social and economic impact on patients, families, and government programs.2 Although the number of older adults with dementia in the United States and around the world is expected to grow up to 3-fold by 2050 owing to the large increase in the size of the elderly population,3 recent studies suggest that the age-specific risk of dementia may have actually declined in some high-income countries over the past 25 years, perhaps owing to increasing levels of education and better control of key cardiovascular risk factors, such as hypertension, diabetes, and hypercholesterolemia.4-6 For instance, the incidence of dementia among older participants in the Framingham Heart Study declined by about 20% per decade between 1977 and 2008, and the decline in risk was seen only among those with at least a high school education.7

If confirmed in representative populations, a decline in age-specific risk for dementia would have important implications for public health and public policy. For instance, a recent population-based study8 of dementia in England found a 24% decline in the expected number of cases of dementia between 1991 and 2011 (a 6.5% prevalence among older adults in 2011, compared with 8.3% in 1991; P = .003), which translates to more than 200 000 fewer cases of dementia.

Quiz Ref IDThere have been changes over the past 2 to 3 decades in both the prevalence and treatment of cardiovascular risk factors that also influence the risk for dementia. For instance, 23% of US adults were obese in 1990 compared with 35% in 20129,10; among adults 65 years or older, the prevalence of diabetes increased from 9% to 21%.10 However, intensity of treatment for diabetes, hypertension, and high cholesterol level has increased with more patients achieving treatment goals, and a significant decline in the vascular complications of diabetes such as heart attack, stroke, and lower-extremity amputations,11 suggesting that there could be a “spill-over” benefit of a decline in the vascular-related risk for dementia.4,7

Rising levels of education among US adults over the past 25 years may also have contributed to decreased dementia risk. The proportion of adults 65 years or older with a high school diploma increased from 55% in 1990 to 80% in 2010, while the proportion with a college degree increased from 12% to 23%.12 More years of formal education is associated with a reduced risk of dementia, likely through multiple causal pathways, including a direct effect on brain development and function (ie, the building of “cognitive reserve”), health behaviors, as well as the general health advantages of having more wealth and opportunities.13-15

To further address these questions, we used the Health and Retirement Study16 (HRS), a large nationally representative prospective cohort study of US adults, to test whether the age-specific prevalence of dementia declined in the United States between 2000 and 2012. Since most prior studies of dementia trends have used samples from geographically restricted regions and with limited representation of minority populations, we could determine if those studies’ findings were replicated in a sample representative of the US population.

Methods
Data and Study Sample

We used data from the 2000 and 2012 waves of the HRS. The HRS is a biennial survey of US adults that started in 1992 and collects a wide-range of data on health, cognition, family, employment, and wealth.16 The HRS follows respondents longitudinally until death, and new cohorts have been enrolled at different times since the 1992 baseline interviews in order to maintain population representativeness as the study sample has aged.16 As a result, 4008 individuals in our analysis were included in both the 2000 and 2012 cohorts, while 6538 were included only in 2000 and 6503 only in 2012.

Our study sample of 21 057 included all HRS participants aged 65 or older, living in the community or in nursing homes in 2000 and 2012. There were 10 546 respondents in 2000 and 10 516 respondents in 2012, after excluding 165 (1.5%) and 218 (2.0%) respondents from the 2000 and 2012 samples, respectively, owing to missing data for 1 or more covariates used in the analysis. If a respondent is unable or unwilling to participate in the survey, the HRS attempts to identify a proxy respondent (usually a spouse or adult child) to complete the survey for them. There were 1317 (12.5% unweighted) respondents represented by a proxy in 2000 and 860 (8.2% unweighted) in 2012. The response rate for the full HRS sample was 88% in 2000 and 89% in 2012.17

Verbal informed consent to participate in the HRS is obtained from all respondents, and they are provided about $80 in compensation for their participation. The HRS has been approved by the Health Sciences and Behavioral Sciences institutional review board at the University of Michigan.

Measurement of Cognitive Function and Cognitive Category Definitions

The HRS assesses cognitive function in self-respondents with a range of tests adapted from the Telephone Interview for Cognitive Status (TICS). Based on our prior work,18 we used a 27-point cognitive scale that included an immediate and delayed 10-noun free recall test, a serial 7 subtraction test, and a backward count from 20 test. Cutpoints for normal, cognitive impairment—no dementia (CIND), and dementia were validated against the prevalence of CIND and dementia in the Aging, Demographics, and Memory Study (ADAMS), an HRS substudy of Alzheimer disease and dementia that uses a 3-to 4-hour in-home neuropsychological and clinical assessment as well as expert clinician adjudication to obtain a gold-standard diagnosis of CIND or dementia.18,19 Respondents who scored from 0 to 6 on the 27-point scale were classified as having dementia, 7 to 11 as having CIND, and 12 to 27 as normal.

For respondents represented by a proxy, an 11-point scale was developed using the proxy’s assessment of the respondent’s memory ranging from excellent to poor (score, 0-4), the proxy’s assessment of whether the respondent had limitations in 5 instrumental activities of daily living (IADLs) (managing money, taking medication, preparing hot meals, using phones, and shopping for groceries; score, 0-5), and the survey interviewer’s assessment of whether the respondent had difficulty completing the interview because of a cognitive limitation (a score of 0-2 indicating, none, some, and prevents completion). Using this information, respondents with high scores (6-11) were classified as having dementia, and those with mid-range scores (3-5) as having CIND.18

Using the ADAMS dementia diagnosis as the gold standard, this categorization method correctly classifies 78% of HRS respondents as having dementia or not (76% of self-respondents and 84% of those represented by a proxy).18 More details on the HRS self-report and proxy cognition measures are available at the HRS web site.20

Independent Variables Used as Covariates

The following sociodemographic measures were included in the regression analyses as independent variables: age, self-reported race/ethnicity (white, black, Hispanic, other), sex, education (<12 years, 12 years, 13-15 years, and ≥16 years), and net worth (quartiles in year-2000 dollars). The self-reported chronic medical conditions and cardiovascular risk factors included were stroke, diabetes, heart disease, hypertension, and body-mass index (BMI) (derived from self-reported height and weight). All of these sociodemographic and health measures were selected for inclusion in the regression analyses a priori, based on prior studies suggesting that they are associated with dementia risk.

Analytic Framework

For descriptive analyses (Tables 1, 2, and 3), the 2012 sample was age- and sex-standardized to the 2000 population using direct standardization. For multivariable analyses (Table 4), we pooled data from 2000 and 2012 and estimated logistic regression models with a dichotomous dependent variable indicating whether an individual had dementia (the reference group included those with normal cognition or CIND). A linear trend variable that took the value of 0 in 2000 and 1 in 2012 was included in the regression models. An odds ratio (OR) of less than 1 for this trend variable would indicate a decrease in the prevalence of dementia (ie, a decrease in the overall odds of dementia among those ≥65 years) between 2000 and 2012. We estimated 4 separate logistic models with different sets of independent variables added sequentially (eg, trend variable only, an age- and sex-adjusted model, and then subsequent models that included sociodemographic variables and then health variables) to better assess which variables were associated with a change in the prevalence of dementia between 2000 and 2012. We tested for interactions between each independent variable and the year of observation.

Statistical analyses were performed using STATA software (release 13.1, Stata Corp). We used HRS sampling weights to adjust for nonresponse and the complex sampling design of the HRS survey.

Results
Characteristics of the Study Sample

Table 1 shows the characteristics of the 21 057 individuals in the 2000 and 2012 study cohorts (with age- and sex-standardization to the 2000 cohort). Quiz Ref IDCompared with the 2000 cohort, the 2012 cohort had a significantly larger proportion of those who were 85 years or older, but the average age for the full cohort was similar across the 2 years. The 2012 cohort had significantly more years of education; individuals with fewer than 12 years of education comprised 32.6% (95% CI, 30.8%-34.4%) of the sample in 2000 but only 20.6% (95% CI, 18.8%-22.6%) in 2012 (P < .001). On average, individuals in the 2012 cohort had nearly 1 more year of education compared with those in the 2000 cohort (12.7 years [95% CI, 12.6-12.9 years] vs 11.8 years [95% CI, 11.6-11.9 years]; P < .001). There was a greater disparity in household net worth in 2012 (in constant year-2000 dollars), with a greater proportion of the 2012 cohort in both the lowest and highest wealth quartiles (P = .02).

The 2012 cohort had significantly higher rates of self-reported cardiovascular risk factors, including obesity (29.2% [95% CI, 27.9%-30.4%] in 2012 vs 18.3% [95% CI, 17.2%-19.4%] in 2000; P < .001), diabetes (24.7% [95% CI, 23.5%-26.0%] vs 16.4% [95% CI, 15.5%-17.3%]; P < .001), and hypertension (67.6% [95% CI, 66.2%-68.7%] vs 54.6% [95% CI, 53.7%-55.5%]; P < .001). The prevalence of heart disease increased from 29.1% (95% CI, 28.1%-30.1%) to 31.8% (95% CI, 30.8%-33.1%) between 2000 and 2012 (P < .001), but the prevalence of stroke did not change significantly. There was a small decline between 2000 and 2012 in the proportion of individuals with 1 or more IADL limitations, but this change was not significant (P = .14). The proportion of the sample living in a nursing home at the time of their HRS interview declined from 4.4% (95% CI, 4.0%-4.8%) in 2000 to 2.8% (95% CI, 2.5%-3.2%) in 2012 (P < .001), and the weighted and standardized proportion of the HRS sample represented by a proxy respondent declined from 12.1% (95% CI, 11.%-13.1%) in 2000 to 6.6% (95% CI, 6.2%-7.3%) in 2012 (P < .001).

Trend in Prevalence and Adjusted Odds of Dementia

Table 2 displays the weighted percentage of individuals in each cognitive function category in 2000 and 2012, and shows a significant decrease in the proportion of individuals 65 years or older with dementia between 2000 and 2012 (11.6% [95% CI, 10.7%-12.7%] in 2000 compared with 8.8% [95% CI, 8.2%-9.4%] in 2012; P < .001). The prevalence of CIND also decreased significantly across the 2 cohorts from 21.2% [95% CI, 20.1%-22.3%] to 18.8% [95% CI, 17.8%-19.9%] (P < .001). After age- and sex-standardizing the 2012 cohort to the 2000 cohort, the decline in dementia prevalence was slightly greater (8.6% in 2012) because of the greater proportion of those who were 85 years or older in 2012. Table 3 provides results stratified by age groups (65-74 years, 75-84 years, and ≥85 years).

Table 4 reports the results of 4 different logistic regression models with the presence of dementia as the outcome variable, using pooled 2000 and 2012 data. The trend variable in the first row of the table represents the OR of dementia in 2012 compared with 2000. Model 1 shows the significant decline (OR, 0.73; 95% CI, 0.67-0.82) in unadjusted dementia prevalence already noted in Table 2, and model 2 shows the OR after adjusting for differences across the cohorts in age and sex (OR, 0.69; 95% CI, 0.62-0.77). Controlling for education, net worth, and race (model 3) explained 9 percentage points of the decrease in age- and sex-standardized odds of dementia between 2000 and 2012 (OR, 0.78; 95% CI, 0.70-0.88), while the addition of cardiovascular risk factors and BMI (model 4) accounted for 4 additional percentage points of the decline in prevalence (OR, 0.82; 95% CI, 0.73-0.92). Quiz Ref IDIn the fully adjusted model (model 4), more years of education and higher net worth were associated with a significantly lower odds of dementia, while older age, being African American or Hispanic, and having a history of stroke or diabetes were all associated with increased odds.Quiz Ref ID Being underweight was also associated with higher odds of dementia, while being overweight or obese was associated with lower odds of dementia, compared with those at normal BMI.

When testing for an interaction effect between each independent variable and year, controlling for the main effects of all other variables, heart disease had a significantly lower OR for dementia in 2012 compared with 2000 (P < .001). No other interactions were significant at the P < .05 level.

Discussion

In a large nationally representative survey of older Americans we found that, among those 65 years or older, the prevalence of dementia decreased from 11.6% to 8.8% between 2000 and 2012, representing an absolute decrease of 2.8 percentage points, and a relative decrease of about 24%. Educational attainment increased significantly, with those 65 years or older in 2012 having nearly 1 additional year of education compared with the 2000 cohort. After controlling for the socioeconomic factors of education, wealth, and race/ethnicity, controlling for changes in the prevalence of cardiovascular risk factors did not explain much of the additional difference in dementia risk across the two cohorts.

Our study, along with prior studies, supports the notion that “cognitive reserve” resulting from early-life and lifelong education and cognitive stimulation may be a potent strategy for the primary prevention of dementia in both high- and low-income countries around the world.21 However, it should be noted that the relationships among education, brain biology, and cognitive function are complex and likely multidirectional; for instance, a number of recent population-based studies have shown genetic links with level of educational attainment,22,23 and with the risk for cognitive decline in later life.24 Higher levels of educational attainment are also associated with health behaviors (eg, physical activity, diet, and smoking), more cognitively-complex occupations, and better access to health care, all of which may play a role in decreasing lifetime dementia risk.

The prevalence of obesity and diabetes among those 65 years or older increased significantly between 2000 and 2012, and diabetes was associated with 39% higher odds of dementia, after controlling for all other factors. As in prior studies among older adults, we found that obesity was associated with a decreased risk of dementia, consistent with the hypothesis that, while obesity in mid-life may increase risk for later-life cognitive decline and dementia, obesity at older ages may be associated with cognitive and other health advantages.25-27 The trend toward a declining risk for dementia in the face of a large increase in the prevalence of diabetes suggests that improvements in treatments between 2000 and 2012 may have decreased dementia risk, along with the documented declines in the incidence of common diabetes-related complications, such as heart attack, stroke, and amputations.11 Our finding of a significant decline between 2000 and 2012 of the heart disease-related OR for dementia would also be consistent with improved cardiovascular treatments leading to a decline in dementia risk. To explore this hypothesis further, we used additional HRS data on self-reported treatments for diabetes (either oral medications or insulin). The proportion of adults with diabetes reporting either oral medication or insulin use increased from 86% in 2000 to 90% in 2012 (P < .01). Furthermore, the interaction of diabetes treatment by survey year in our regression model was statistically significant (P < .01), suggesting that diabetes treatment in 2012 was associated with a significantly lower OR of dementia compared with 2000.

Our findings are consistent with those of a number of recent studies that also found declines in dementia incidence or prevalence in high-income countries around the world6-8,28-31 and also suggest that the trend toward a declining prevalence of cognitive impairment or dementia in the United States that we found between 1993 and 2002 using earlier waves of the HRS data13 has continued through 2012, even with significant increases in the prevalence of cardiovascular risk factors that may increase dementia risk. Our findings are consistent with the declining incidence of dementia found over the past 4 decades in the Framingham Heart Study,7 as well as the decline in dementia prevalence between 1991 and 2011 in the Cognitive Function and Aging Study (CFAS) in England.8 Both the Framingham and CFAS studies also pointed to increases in education and better control of cardiovascular risk factors as likely contributors to declining dementia risk.7,8

Limitations

Our study has several limitations. Our dementia diagnosis is based on a limited set of cognitive tests, although prior validation studies show a 78% concordance for dementia diagnosis when using these tests compared with the detailed ADAMS clinical evaluation.18 The recent Framingham7 and CFAS8 studies both used more extensive cognitive testing and clinical information when making a dementia diagnosis in their studies, so likely have less diagnostic misclassification. In addition, although we used a validated method to define diagnostic categories for both self-respondents and respondents represented by a proxy, the proportion of the HRS sample represented by a proxy declined significantly between 2000 and 2012 (from 12.5% to 8.2% unweighted), likely due in part to a change in HRS field procedures between these 2 waves. In 2006, the HRS purposefully increased the proportion of interviews administered face-to-face in respondents’ homes and decreased the proportion administered by phone. Since 2006, about one-half of HRS interviews at each wave have been administered face-to-face, while prior to 2006 only about 20% were face-to-face. This shift in survey mode likely encouraged an increase in self-interviews that in prior waves would have been completed by proxy, possibly leading to a change in the calibration of the self- and proxy-cognitive measures to dementia status. Quiz Ref IDAnother potential limitation is that changes in diagnostic thresholds and in the frequency of diagnostic testing between 2000 and 2012 may have affected the self-reported prevalence of cardiovascular risk factors, and the relationship of treatments to both cardiovascular and cognitive outcomes. Finally, the accuracy of self-report of cardiovascular risk factors may be less reliable for those with cognitive impairment or dementia.

Conclusions

Using nationally representative data, we found a significant decline in dementia prevalence among older US adults between 2000 and 2012, using the same cognitive measures and the same diagnostic classification strategy in both years. Increases in the level of education among the later-born cohort accounted for some of the decreased dementia risk, and there was some evidence that improvements in treatments for cardiovascular risk factors (eg, diabetes) may also have played a role. However, the full set of social, behavioral, and medical factors contributing to the decline in dementia prevalence is still uncertain. Continued monitoring of trends in dementia incidence and prevalence will be important for better gauging the full future societal impact of dementia as the number of older adults increases in the decades ahead, as well as for clarifying potential protective and risk factors for cognitive decline.

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Article Information

Corresponding Author: Kenneth M. Langa, MD, PhD, Division of General Medicine, University of Michigan, 2800 Plymouth Rd, Building 16, Room 430W, Ann Arbor, MI 48109-2800 (klanga@umich.edu).

Accepted for Publication: September 6, 2016.

Published Online: November 21, 2016. doi:10.1001/jamainternmed.2016.6807

Author Contributions: Dr Langa and Mr Kabeto had full access to all of the data in the study and take responsibility for the integrity of the data and the accuracy of the data analysis.

Concept and design: Langa, Larson, Faul, Levine, Kabeto, Weir.

Acquisition, analysis, or interpretation of data: Langa, Larson, Crimmins, Faul, Kabeto, Weir.

Drafting of the manuscript: Langa, Kabeto.

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

Statistical analysis: Langa, Crimmins, Faul, Kabeto, Weir.

Administrative, technical, or material support: Larson, Faul, Levine, Weir.

Study supervision: Langa, Faul.

Conflict of Interest Disclosures: None reported.

Funding/Support: This work was supported by cooperative agreement U01 AG009740 (Dr Weir) from the National Institute on Aging (NIA), National Institutes of Health. Additional support was provided by grants K23 AG040278 (Dr Levine), P30 AG053760 (Dr Langa), and P30 AG024824 (Dr Langa) from the NIA. The Health and Retirement Study is performed at the Institute for Social Research, University of Michigan, Ann Arbor.

Role of the Funder/Sponsor: Representatives of the NIA reviewed the manuscript but were not directly involved in the collection, management, analysis, or interpretation of the data, or the decision to submit the manuscript for publication.

Disclaimer: The content of this article is solely the responsibility of the authors and does not necessarily represent the official views of the NIA or the Department of Veterans Affairs.

References
1.
Plassman  BL, Langa  KM, Fisher  GG,  et al.  Prevalence of dementia in the United States: the aging, demographics, and memory study.  Neuroepidemiology. 2007;29(1-2):125-132.PubMedGoogle ScholarCrossref
2.
Hurd  MD, Martorell  P, Delavande  A, Mullen  KJ, Langa  KM.  Monetary costs of dementia in the United States.  N Engl J Med. 2013;368(14):1326-1334.PubMedGoogle ScholarCrossref
3.
Prince  M, Bryce  R, Albanese  E, Wimo  A, Ribeiro  W, Ferri  CP.  The global prevalence of dementia: a systematic review and meta-analysis.  Alzheimers Dement. 2013;9(1):63-75.Google ScholarCrossref
4.
Larson  EB, Yaffe  K, Langa  KM.  New insights into the dementia epidemic.  N Engl J Med. 2013;369(24):2275-2277.PubMedGoogle ScholarCrossref
5.
Gerstorf  D, Hülür  G, Drewelies  J,  et al.  Secular changes in late-life cognition and well-being: towards a long bright future with a short brisk ending?  Psychol Aging. 2015;30(2):301-310.PubMedGoogle ScholarCrossref
6.
Wu  YT, Fratiglioni  L, Matthews  FE,  et al.  Dementia in western Europe: epidemiological evidence and implications for policy making.  Lancet Neurol. 2016;15(1):116-124.PubMedGoogle ScholarCrossref
7.
Satizabal  CL, Beiser  AS, Chouraki  V, Chêne  G, Dufouil  C, Seshadri  S.  Incidence of dementia over three decades in the Framingham Heart Study.  N Engl J Med. 2016;374(6):523-532.PubMedGoogle ScholarCrossref
8.
Matthews  FE, Arthur  A, Barnes  LE,  et al; Medical Research Council Cognitive Function and Ageing Collaboration.  A two-decade comparison of prevalence of dementia in individuals aged 65 years and older from three geographical areas of England: results of the Cognitive Function and Ageing Study I and II.  Lancet. 2013;382(9902):1405-1412.PubMedGoogle ScholarCrossref
9.
Ogden  CL, Carroll  MD, Kit  BK, Flegal  KM.  Prevalence of childhood and adult obesity in the United States, 2011-2012.  JAMA. 2014;311(8):806-814.PubMedGoogle ScholarCrossref
10.
Ogden  C, Carroll  M. Prevalence of overweight, obesity, and extreme obesity among adults: United States, trends 1960-1962 through 2007-2008. June 2010. http://www.cdc.gov/nchs/data/hestat/obesity_adult_07_08/obesity_adult_07_08.pdf. Accessed August 8, 2016.
11.
Gregg  EW, Li  Y, Wang  J,  et al.  Changes in diabetes-related complications in the United States, 1990-2010.  N Engl J Med. 2014;370(16):1514-1523.PubMedGoogle ScholarCrossref
12.
Federal Interagency Forum on Aging-Related Statistics. Older Americans 2012: Key Indicators of Well-Being. Washington, DC: US Government Printing Office. June 2012. http://www.agingstats.gov/docs/PastReports/2012/OA2012.pdf. Accessed August 8, 2016.
13.
Langa  KM, Larson  EB, Karlawish  JH,  et al.  Trends in the prevalence and mortality of cognitive impairment in the United States: is there evidence of a compression of cognitive morbidity?  Alzheimers Dement. 2008;4(2):134-144.PubMedGoogle ScholarCrossref
14.
Vemuri  P, Lesnick  TG, Przybelski  SA,  et al.  Association of lifetime intellectual enrichment with cognitive decline in the older population.  JAMA Neurol. 2014;71(8):1017-1024.PubMedGoogle ScholarCrossref
15.
Stern  Y, Albert  S, Tang  MX, Tsai  WY.  Rate of memory decline in AD is related to education and occupation: cognitive reserve?  Neurology. 1999;53(9):1942-1947.PubMedGoogle ScholarCrossref
16.
Sonnega  A, Faul  JD, Ofstedal  MB, Langa  KM, Phillips  JW, Weir  DR.  Cohort Profile: the Health and Retirement Study (HRS).  Int J Epidemiol. 2014;43(2):576-585.PubMedGoogle ScholarCrossref
17.
Health and Retirement Study (HRS) Sample Sizes and Response Rates. 2011; http://hrsonline.isr.umich.edu/sitedocs/sampleresponse.pdf. Accessed August 8, 2016.
18.
Crimmins  EM, Kim  JK, Langa  KM, Weir  DR.  Assessment of cognition using surveys and neuropsychological assessment: the Health and Retirement Study and the Aging, Demographics, and Memory Study.  J Gerontol B Psychol Sci Soc Sci. 2011;66(suppl 1):i162-i171.PubMedGoogle ScholarCrossref
19.
Langa  KM, Plassman  BL, Wallace  RB,  et al.  The Aging, Demographics, and Memory Study: study design and methods.  Neuroepidemiology. 2005;25(4):181-191.PubMedGoogle ScholarCrossref
20.
Ofstedal  MB, Fisher  GG, Herzog  AR. Documentation of cognitive functioning measures in the Health and Retirement Study. 2005; http://hrsonline.isr.umich.edu/sitedocs/userg/dr-006.pdf. Accessed August 8, 2016.
21.
Norton  S, Matthews  FE, Barnes  DE, Yaffe  K, Brayne  C.  Potential for primary prevention of Alzheimer’s disease: an analysis of population-based data.  Lancet Neurol. 2014;13(8):788-794.PubMedGoogle ScholarCrossref
22.
Rietveld  CA, Medland  SE, Derringer  J,  et al; LifeLines Cohort Study.  GWAS of 126,559 individuals identifies genetic variants associated with educational attainment.  Science. 2013;340(6139):1467-1471.PubMedGoogle ScholarCrossref
23.
Rietveld  CA, Esko  T, Davies  G,  et al.  Common genetic variants associated with cognitive performance identified using the proxy-phenotype method.  Proc Natl Acad Sci U S A. 2014;111(38):13790-13794.PubMedGoogle ScholarCrossref
24.
Deary  IJ, Yang  J, Davies  G,  et al.  Genetic contributions to stability and change in intelligence from childhood to old age.  Nature. 2012;482(7384):212-215.PubMedGoogle Scholar
25.
Fitzpatrick  AL, Kuller  LH, Lopez  OL,  et al.  Midlife and late-life obesity and the risk of dementia: cardiovascular health study.  Arch Neurol. 2009;66(3):336-342.PubMedGoogle ScholarCrossref
26.
Hughes  TF, Borenstein  AR, Schofield  E, Wu  Y, Larson  EB.  Association between late-life body mass index and dementia: the Kame Project.  Neurology. 2009;72(20):1741-1746.PubMedGoogle ScholarCrossref
27.
Tolppanen  AM, Ngandu  T, Kåreholt  I,  et al.  Midlife and late-life body mass index and late-life dementia: results from a prospective population-based cohort.  J Alzheimers Dis. 2014;38(1):201-209.PubMedGoogle Scholar
28.
Schrijvers  EM, Verhaaren  BF, Koudstaal  PJ, Hofman  A, Ikram  MA, Breteler  MM.  Is dementia incidence declining? trends in dementia incidence since 1990 in the Rotterdam Study.  Neurology. 2012;78(19):1456-1463.PubMedGoogle ScholarCrossref
29.
Qiu  C, von Strauss  E, Bäckman  L, Winblad  B, Fratiglioni  L.  Twenty-year changes in dementia occurrence suggest decreasing incidence in central Stockholm, Sweden.  Neurology. 2013;80(20):1888-1894.PubMedGoogle ScholarCrossref
30.
Christensen  K, Thinggaard  M, Oksuzyan  A,  et al.  Physical and cognitive functioning of people older than 90 years: a comparison of two Danish cohorts born 10 years apart.  Lancet. 2013;382(9903):1507-1513.PubMedGoogle ScholarCrossref
31.
Dodge  HH, Zhu  J, Lee  CW, Chang  CC, Ganguli  M.  Cohort effects in age-associated cognitive trajectories.  J Gerontol A Biol Sci Med Sci. 2014;69(6):687-694.PubMedGoogle ScholarCrossref
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