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Urban Residence and Higher Education Do Not Protect against Cognitive Decline in Aging and Dementia: 10-Year Follow-Up of the Canadian Study of Health and Aging

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Title: Urban Residence and Higher Education Do Not Protect against Cognitive Decline in Aging and Dementia: 10-Year Follow-Up of the Canadian Study of Health and Aging
Language: English
Authors: Helmes, Edward, Van Gerven, Pascal W. M.
Source: Educational Gerontology. 2017 43(11):552-560.
Availability: Routledge. Available from: Taylor & Francis, Ltd. 530 Walnut Street Suite 850, Philadelphia, PA 19106. Tel: 800-354-1420; Tel: 215-625-8900; Fax: 215-207-0050; Web site: http://www.tandf.co.uk/journals
Peer Reviewed: Y
Page Count: 9
Publication Date: 2017
Document Type: Journal Articles
Reports - Research
Descriptors: Foreign Countries, Aging (Individuals), Urban Areas, Older Adults, Cognitive Ability, Predictor Variables, Comparative Analysis, Dementia, Rural Areas, Educational Attainment, Testing, Statistical Analysis
Geographic Terms: Canada
DOI: 10.1080/03601277.2017.1372951
ISSN: 0360-1277
Abstract: The construct of cognitive reserve has primarily been defined in terms of a single proxy measure, education. There may, however, be alternative, potentially additive, proxy measures of cognitive reserve, such as rural or urban residence. Using a large sample of 10,263 older Canadians, ranging in age between 64 and 99 years (mean age = 75.7 years, SD = 7.1), residents of rural and urban areas were compared using the Modified Mini-Mental State (3MS) examination as a dependent variable. Within this sample, subsamples of demented and non-demented individuals were investigated. The 3MS data were analyzed using a linear mixed model with years of education and residence as proxies of cognitive reserve and time of testing (linear and quadratic) as a within-groups variable. All predictor variables in the model (i.e., gender, age, education, residence, and time of testing) had a significant impact on cognitive functioning. The results showed that, although urban residents and higher educated individuals performed better than rural residents and lower educated individuals at baseline, these performance benefits were nullified at 10-year follow-up. The disappearance of these initial performance benefits suggests that urban dwellers and higher educated individuals are not protected against age-related cognitive decline. Thus, no support was found for the cognitive reserve hypothesis.
Abstractor: As Provided
Number of References: 37
Entry Date: 2017
Accession Number: EJ1158798
Database: ERIC
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  Value: <anid>AN0125880752;egr01nov.17;2019Feb27.13:34;v2.2.500</anid> <title id="AN0125880752-1">Urban residence and higher education do not protect against cognitive decline in aging and dementia: 10-year follow-up of the Canadian Study of Health and Aging. </title> <p>The construct of cognitive reserve has primarily been defined in terms of a single proxy measure, education. There may, however, be alternative, potentially additive, proxy measures of cognitive reserve, such as rural or urban residence. Using a large sample of 10,263 older Canadians, ranging in age between 64 and 99 years (mean age = 75.7 years, SD = 7.1), residents of rural and urban areas were compared using the Modified Mini-Mental State (3MS) examination as a dependent variable. Within this sample, subsamples of demented and non-demented individuals were investigated. The 3MS data were analyzed using a linear mixed model with years of education and residence as proxies of cognitive reserve and time of testing (linear and quadratic) as a within-groups variable. All predictor variables in the model (i.e., gender, age, education, residence, and time of testing) had a significant impact on cognitive functioning. The results showed that, although urban residents and higher educated individuals performed better than rural residents and lower educated individuals at baseline, these performance benefits were nullified at 10-year follow-up. The disappearance of these initial performance benefits suggests that urban dwellers and higher educated individuals are not protected against age-related cognitive decline. Thus, no support was found for the cognitive reserve hypothesis.</p> <p>Although cognitive functions remain relatively intact for the majority of older adults with the passing of time, even until very old age (Gow et al., [<reflink idref="bib8" id="ref1">8</reflink>]), it is recognized that increasing age is a significant risk factor for the development of dementia (Bondi et al., [<reflink idref="bib1" id="ref2">1</reflink>]; Canadian Study of Health and Aging Working Group, [<reflink idref="bib2" id="ref3">2</reflink>]). <emph>Cognitive reserve</emph> has been hypothesized as a factor that differentiates aging individuals who develop dementia from those who do not (Ram, Gerstorf, Lindenberger, & Smith, [<reflink idref="bib19" id="ref4">19</reflink>]; Valenzuela & Sachdev, [<reflink idref="bib32" id="ref5">32</reflink>]), and those whose dementia progresses more slowly than that of others (Elias et al., [<reflink idref="bib7" id="ref6">7</reflink>]; Valenzuela & Sachdev, [<reflink idref="bib33" id="ref7">33</reflink>]). The term refers to the ability of an individual to deal with age-related neural and – as a result – cognitive change by an efficient use of typical brain networks or, if unavailable, the recruitment of alternative networks to perform a cognitive task. Cognitive reserve is differentiated from brain reserve, with the former being described as a primarily active, psychological construct, whereas the latter is described as a more passive, physiological one (Satz, [<reflink idref="bib23" id="ref8">23</reflink>]; Stern, [<reflink idref="bib27" id="ref9">27</reflink>], [<reflink idref="bib29" id="ref10">29</reflink>]). Both constructs are inferred rather than being directly observable. The two terms and their distinction are not universally accepted and "the demarcation between brain reserve and cognitive reserve is not clear cut" (Stern, [<reflink idref="bib28" id="ref11">28</reflink>], p. 2016).</p> <p>Education, along with leisure activities and socioeconomic status, has been coined as a psychosocial proxy of cognitive reserve (e.g., Roe, Xiong, Miller, & Morris, [<reflink idref="bib22" id="ref12">22</reflink>]). However, later evidence has suggested that years of education in itself is not a primary protective factor (Gross et al., [<reflink idref="bib9" id="ref13">9</reflink>]; Ngandu et al., [<reflink idref="bib15" id="ref14">15</reflink>]; Zahodne et al., [<reflink idref="bib37" id="ref15">37</reflink>]), but that the apparent beneficial effect of education is due to early-childhood educational experiences (Richards & Sacker, [<reflink idref="bib21" id="ref16">21</reflink>]). Further research has suggested that the predictive power of years of education is limited to those with higher test scores and does not include those functioning at lower levels (Koepsell et al., [<reflink idref="bib11" id="ref17">11</reflink>]). Other research suggests that the positive influence of years of education is due to ascertainment bias rather than to actual protective power (Tuokko, Garrett, McDowell, Silverberg, & Kristjansson, [<reflink idref="bib31" id="ref18">31</reflink>]). There is also emerging consensus that maintaining the cognitive activity throughout adulthood is more important than basic years of education early in life (Reed et al., [<reflink idref="bib20" id="ref19">20</reflink>]; Valenzuela & Sachdev, [<reflink idref="bib33" id="ref20">33</reflink>]). Satz, Cole, Hardy, and Rassovsky ([<reflink idref="bib24" id="ref21">24</reflink>]) reviewed the construct validity of cognitive reserve and concluded that the concept is not clearly distinguished from concepts such as fluid intelligence and executive functioning. They, therefore, propose several models of cognitive reserve that provide differentiation of the construct.</p> <p>Preservation of function in later life and its determinants have received reasonable attention in the literature. However, some basic demographic factors that may influence the rate of age-related cognitive decline have been investigated to a lesser extent. One such factor is rural versus urban residence. Because urban daily living is cognitively more complex than rural daily living, it is associated with higher cognitive functioning (e.g., Cassarino, O'Sullivan, Kenny, & Setti, [<reflink idref="bib4" id="ref22">4</reflink>]) and, possibly, it increases cognitive reserve as well. On the other hand, urban life may be more stressful than rural life, which could have detrimental effects on cognitive functioning. Evidence supporting such detrimental effects is inconsistent, however (e.g., Paykel, Abbott, Jenkins, Brugha, & Meltzer, [<reflink idref="bib16" id="ref23">16</reflink>]; Peen, Schoevers, Beekman, & Decker, [<reflink idref="bib17" id="ref24">17</reflink>]). Rural–urban differences and their potential effects on cognitive aging have received limited attention from researchers to date. One of the few studies addressing such differences reported that rural residents were frailer than their urban counterparts, with increased mortality after the age of 80 (Song, MacKnight, Latta, Mitnitski, & Rockwood, [<reflink idref="bib26" id="ref25">26</reflink>]). In the current study, rural or urban residence was addressed as a new proxy of cognitive reserve and compared with years of education as a predictor of age-related cognitive decline.</p> <p>In line with previous studies that have used cognitive screening measures to estimate the impact of cognitive reserve on age-related cognitive change (e.g., Koepsell et al., [<reflink idref="bib11" id="ref26">11</reflink>]), we decided to use the Modified Mini-Mental State (3MS) examination (Teng & Chui, [<reflink idref="bib30" id="ref27">30</reflink>]) as the dependent variable. We extracted these screening data from the Canadian Study of Health and Aging (CSHA), a large and representative community sample (<emph>N</emph> = 10,263; Canadian Study of Health and Aging Working Group, [<reflink idref="bib3" id="ref28">3</reflink>]) that has been used in an earlier study on cognitive reserve as approximated by years of education (Lindsay et al., [<reflink idref="bib13" id="ref29">13</reflink>]). Besides rural–urban residence, we analyzed the effects of gender, age (at baseline), and years of education on cognitive change, as measured with the 3MS examination, at three time points: baseline, 5- and 10-year follow-up. Furthermore, we analyzed the same predictor variables in subsamples of demented and non-demented individuals.</p> <hd id="AN0125880752-2">Methods</hd> <p></p> <hd id="AN0125880752-3">Sample and procedure</hd> <p>Participants (<emph>N</emph> = 10,263) were drawn from the Canadian Study of Health and Aging (CSHA), a national epidemiological study into dementia and related health and social factors (for details, see Canadian Study of Health and Aging Working Group, [<reflink idref="bib2" id="ref30">2</reflink>], [<reflink idref="bib3" id="ref31">3</reflink>]; Eastwood, Nobbs, Lindsay, & McDowell, [<reflink idref="bib6" id="ref32">6</reflink>]). CSHA data were collected in three waves at 5-year intervals: 1991, 1996, and 2001 (Lindsay, Sykes, McDowell, Verreault, & Laurin, [<reflink idref="bib14" id="ref33">14</reflink>]). The majority of the current sample were female (59.5%) with an average age of 75.7 years at the first wave of the study (<emph>SD </emph>= 7.1; age range = 64–99 years). Years of education ranged from zero to 33 years, with a mean of 10.1 years (<emph>SD </emph>= 3.90).</p> <p>Apart from the full sample, we analyzed three subsamples: (<reflink idref="bib1" id="ref34">1</reflink>) a subsample of clinically diagnosed dementia patients (i.e., people with possible/probable Alzheimer's disease, vascular dementia, or other types of dementia; <emph>n</emph> = 2,133), (<reflink idref="bib2" id="ref35">2</reflink>) a subsample of, clinically confirmed, non-demented individuals (<emph>n</emph> = 225), and (<reflink idref="bib3" id="ref36">3</reflink>) a subsample of both non-demented individuals and individuals whose clinical status is unknown (<emph>n</emph> = 8,130). We opted for this last category because the sample of clinically confirmed non-demented individuals was relatively small.</p> <p>The Modified Mini-Mental State (3MS) examination (Teng & Chui, [<reflink idref="bib30" id="ref37">30</reflink>]) was utilized for cognitive screening at each of the three waves of the study. The 3MS also provided the dependent variable for our study. The 3MS was administered by a trained nurse at each of the study centers. Rural living status was adopted from Song et al. ([<reflink idref="bib26" id="ref38">26</reflink>]) as those living in a community with 2,500 residents or fewer.</p> <hd id="AN0125880752-4">Statistical analysis</hd> <p>The data were analyzed using the linear mixed models module of PASW Statistics 18.0 for Windows (SPSS Inc., Chicago, IL) to test the effects of residence status on cognitive change, with Time of assessment (0, 5, and 10 years) as the major within-groups variable. Gender (0 = female, 1 = male), Residence (0 = rural, 1 = urban), Age (at baseline), and Education (0 = nine or less years of education, 1 = more than nine years of education) were the main predictors in the model. Dichotomized variables were used to avoid unequal differences between adjacent values. The variable Time<sups>2</sups> was included to account for nonlinear effects over time. Interactions were tested between Residence and Education, Education and Time<sups>2</sups>, Residence and Time<sups>2</sups>, and between Residence, Education, and Time<sups>2</sups>. The linear mixed model was applied to the full sample as well as the three subsamples. See Van Gerven, Van Boxtel, Ausems, Bekers, and Jolles ([<reflink idref="bib36" id="ref39">36</reflink>]) for a similar statistical approach in the Maastricht Aging Study.</p> <hd id="AN0125880752-5">Results</hd> <p></p> <hd id="AN0125880752-6">Attrition</hd> <p>Because of the high average age of the sample, attrition as a result of factors like mortality or disease was substantial throughout the study. By the time of the second assessment, five years after baseline, 36.3% had dropped out (leaving 5,703 participants in the sample). This level of attrition is greater than that in similar studies (e.g., Seeman et al., [<reflink idref="bib25" id="ref40">25</reflink>]; Van Gerven et al., [<reflink idref="bib36" id="ref41">36</reflink>]), which reported attrition rates of 20.3% and 23.0% respectively after six years in samples with a similar age ranges. After 10 years, 62.8% of the participants had dropped out of the study (leaving 3,424 participants in the sample). In addition to mortality and disease, other factors that affected participation were loss of contact and refusal to take part (Lindsay et al., [<reflink idref="bib14" id="ref42">14</reflink>]).</p> <hd id="AN0125880752-7">Parameter estimates</hd> <p>The parameter estimates of the linear mixed-models analyses for the whole sample and the three subsamples are shown in Table 1. Figure 1–4 show the predicted 3MS performance, based on the linear mixed models, at baseline (0 years), 5 and 10 year follow-ups. As can be seen from Table 1, all predictor variables have a statistically significant impact on 3MS performance: Men appear to perform better than women, younger individuals perform better than older individuals, higher educated individuals perform better than lower educated individuals, and urban residents perform better than rural residents. This pattern of results holds for all samples, except for the non-demented subsample, where Residence does not have a significant effect, and the demented subsample, where Gender does not have a significant effect. Moreover, parameter estimates of both Time and Time<sups>2</sups> were highly significant, which indicates that cognitive decline accelerates over a period of 10 years. Note that cognitive decline sets in only after 5-year follow-up in the non-demented and non-demented plus unknown subsamples (see Figures 2 and 3).</p> <p>Table 1. Linear mixed model: Estimates of fixed effects on 3MS performance based on the whole sample and three subsamples.</p> <p> <ephtml> <table><thead><tr><td /><td /><td>Subsample</td></tr><tr><td /><td>Whole sample</td><td>Non-demented</td><td>Non-demented + unknown</td><td>Demented</td></tr><tr><td>Predictor variable</td><td>(<italic>N</italic> = 10,263)</td><td>(<italic>n</italic> = 225)</td><td>(<italic>n</italic> = 8,130)</td><td>(<italic>n</italic> = 2,133)</td></tr></thead><tbody><tr><td>Intercept</td><td>06.137***</td><td>80.688***</td><td>97.743***</td><td>103.131***</td></tr><tr><td>Gender</td><td>0.689***</td><td>0.814*</td><td>0.750***</td><td>0.275</td></tr><tr><td>Age</td><td>−0.396***</td><td>−0.096**</td><td>−0.255***</td><td>−0.500***</td></tr><tr><td>Education</td><td>9.361***</td><td>16.866*</td><td>8.021***</td><td>14.570**</td></tr><tr><td>Residence</td><td>2.232***</td><td>2.758</td><td>1.872***</td><td>3.738*</td></tr><tr><td>Time</td><td>4.682***</td><td>6.599 ***</td><td>5.372***</td><td>0.656**</td></tr><tr><td>Time<sup>2</sup></td><td>−1.018***</td><td>−1.190***</td><td>−1.093***</td><td>−0.602***</td></tr><tr><td>Education × Residence</td><td>−1.080</td><td>−3.838</td><td>−0.699</td><td>−2.523</td></tr><tr><td>Education × Time<sup>2</sup></td><td>−0.080***</td><td>−0.108</td><td>−0.065***</td><td>−0.154*</td></tr><tr><td>Residence× Time<sup>2</sup></td><td>−0.019***</td><td>−0.007</td><td>−0.015***</td><td>−0.019</td></tr><tr><td>Education × Residence × Time<sup>2</sup></td><td>0.011</td><td>0.014</td><td>0.006</td><td>0.037</td></tr></tbody></table> </ephtml> </p> <p>2 <emph>Note</emph>. *<emph>p</emph> < .05. **<emph>p</emph> < .01. ***<emph>p </emph>< .001.</p> <p>Graph: Figure 1. Mean predicted modified mini-mental state (3MS) examination scores based on the linear mixed model of the whole sample (N = 10,263).</p> <p>Graph: Figure 2. Mean predicted modified mini-mental state (3MS) examination scores based on the linear mixed model of the clinically non-demented subsample (n = 225).</p> <p>Graph: Figure 3. Mean predicted modified mini-mental state (3MS) examination scores based on the linear mixed model of the subsample containing non-demented individuals plus individuals with an unknown dementia status (n = 8,130).</p> <p>Graph: Figure 4. Mean predicted modified mini-mental state (3MS) examination scores based on the linear mixed model of the demented subsample (n = 2,133).</p> <p>The effects of Education and Residence appear to be independent, as is suggested by the non-significant parameter estimates for the Education × Residence interaction across all four samples. There is a significant two-way interaction between Education and Time<sups>2</sups> across samples, except for the non-demented subsample, which may be due to limited statistical power resulting from the relatively small sample size (<emph>n</emph> = 225). The negative parameter estimate of this interaction suggests that the exponential decline of performance as a function of time is stronger in higher than in lower educated individuals. This can be seen from Figure 1–4, where higher educated individuals start out at a relatively high level of performance, but decline to a level of performance comparable to that of their lower educated counterparts at 10-year follow-up. There is also a significant two-way interaction between Residence and Time<sups>2</sups> for the whole sample and for the non-demented plus unknown subsample. The negative parameter estimate for this interaction suggests that the exponential performance decline is stronger for urban than for rural residents. As can be seen from Figures 1 and 3, performance of urban dwellers, which is relatively high at baseline, converges toward that of rural dwellers at 10-year follow-up. The interaction is not significant for the non-demented subsample, which may, again, may be due to limited statistical power. Moreover, the interaction is non-significant for the demented subsample, which is unlikely due to a lack of statistical power (<emph>n</emph> = 2,133). In general, it appears that the initial performance benefit at baseline of both high education and urban residence strongly decreases at 5- and 10-year follow-up. Finally, the three-way interaction between Education, Residence, and Time<sups>2</sups> did not reach significance, which suggests that the non-significant interaction between Education and Residence is independent of time.</p> <hd id="AN0125880752-8">Discussion</hd> <p>The interactive effects of residence – urban versus rural – and educational attainment – low versus high – on age-related cognitive decline were investigated over a period of 10-years. Our results demonstrated accelerated decline of performance on the Modified Mini-Mental State (3MS) examination at 5- and 10-year follow-up. Urban dwellers and higher educated individuals showed relatively high levels of performance at baseline compared to rural dwellers and lower educated individuals, but this performance gap was strongly reduced at 10-year follow-up. The effects of residence and education did not interact and did not depend on time of measurement. Effects were roughly the same across subsamples of non-demented and demented individuals. In the demented subsample, however, rates of cognitive decline did not differ between rural and urban dwellers.</p> <p>At baseline, the current results are in line with those of a cross-sectional analysis of data from the Irish Longitudinal Study on Ageing (Cassarino et al., [<reflink idref="bib4" id="ref43">4</reflink>]), which revealed better global cognition scores for urban than for rural residents. What the current study has additionally shown, however, is that this residence-based performance difference, which is also seen in the current dataset, is not robust against the aging process because it tends to disappear at 10-year follow-up.</p> <p>There is a striking parallel between the current results and the results from the Maastricht Aging Study regarding the longitudinal effect of educational attainment on cognitive decline. Where at the 6-year follow-up of this study no effect of educational attainment was found on cognitive decline (Van Dijk, Van Gerven, Van Boxtel, Van Der Elst, & Jolles, [<reflink idref="bib34" id="ref44">34</reflink>]), at the 12-year follow-up, higher educated individuals showed a larger drop in performance than their lower educated counterparts, resulting in a reduced gap between these groups (Van Gerven et al., [<reflink idref="bib36" id="ref45">36</reflink>]). In the current study, we see a similar pattern of results not only in lower versus higher educated individuals, but also in rural versus urban dwellers. The general observation that cognitive performance varies as a function of certain proxy measures of cognitive reserve at younger age but tends to level out at older age may be primarily due to the fact that high performing individuals have more to lose in terms of cognitive abilities. To the extent that education and urban/rural residence are proxies of cognitive reserve, the current results resonate with numerous other longitudinal and cross-sectional studies in which educational attainment was not significantly associated with a relatively strong cognitive decline, and which thus do not support the cognitive reserve hypothesis (e.g., Christensen et al., [<reflink idref="bib5" id="ref46">5</reflink>]; Piccinin et al., [<reflink idref="bib18" id="ref47">18</reflink>]; Van Gerven, Meijer, & Jolles, [<reflink idref="bib35" id="ref48">35</reflink>]).</p> <p>The absence of a protective effect of residence and education stands in stark contrast with the protective effects of physical fitness that have been widely reported (e.g., Jonasson et al., [<reflink idref="bib10" id="ref49">10</reflink>]; Kramer, Colcombe, McAuley, Scalf, & Erickson, [<reflink idref="bib12" id="ref50">12</reflink>]). This suggests that the quest for optimal remediation of age-related cognitive decline though cognitive training is challenged by the sheer effect of good physical health. Instead of promoting cognitively challenging activities as a means to mitigate the detrimental effects of aging on cognitive performance, promoting a healthy lifestyle may be a more fruitful approach.</p> <p>There are three limitations of the current study that should be taken into account. One is the considerable, although certainly not unusual, level of attrition: 36.3% at 5-year follow-up and 62.8% at 10-year follow-up. These attrition levels are markedly higher than those in methodologically comparable studies (e.g., Seeman et al., [<reflink idref="bib25" id="ref51">25</reflink>]; Van Gerven et al., [<reflink idref="bib36" id="ref52">36</reflink>]). It should be noted, however, that these earlier studies only included non-demented individuals, whereas the present sample included at least 2,133 individuals who were clinically diagnosed with different types of dementia. Moreover, the linear mixed models approach was utilized to reduce the impact of attrition. Within this statistical approach, cases with missing data from one or more time points are not excluded from the analysis, but parameters are estimated based on those measurements that are available. Thus, in the current study, data of all individuals in the initial sample, whether or not they survived the duration of the study, were included in the analysis.</p> <p>Another limitation of the current study is that the 3MS examination has its disadvantages as a measure of cognitive ability due to its limited ceiling. For all three waves of data, the distribution of 3MS scores was truncated at the upper end of the distribution with a cluster of scores from 95 to 100. This may explain why differences between groups, especially based on residence, were small. It may also explain the strong acceleration of cognitive decline between 5- and 10-year follow-ups. That is, the strength of this accelerated decline could be overestimated.</p> <p>A third and final limitation of the present study is that it does not include information on the residential history of the participants, but only their current residential status. Therefore, we were not able to take factors into account like time of urban/rural residence (in years) and whether or not participants have switched from rural to urban residence or vice versa (and how frequently). For the same reason, we could not take into account possible preferences for rural or urban residence based on cognitive ability. For example, high-functioning people may have a preference for an urban environment and may, therefore, be inclined to either stay in such an environment or move to it from a rural environment.</p> <p>In sum, the present study has revealed a more pronounced acceleration of cognitive decline in urban residents and higher educated individuals relative to rural residents and lower educated individuals. Although the former groups started out at a higher level of cognitive performance at baseline, this initial benefit was nullified at 10-year follow-up. Thus, no support was found for the cognitive reserve hypothesis, which would predict that higher educated individuals and urban dwellers show less pronounced cognitive decline than their lower educated and rural-dwelling counterparts. This outcome adds to the growing body of literature demonstrating that educational attainment does not protect against age-related decline (e.g., Christensen et al., [<reflink idref="bib5" id="ref53">5</reflink>]; Van Dijk et al., [<reflink idref="bib34" id="ref54">34</reflink>]; Van Gerven et al., [<reflink idref="bib36" id="ref55">36</reflink>]). This study is one of the few to explore the role of residence on cognitive decline. The findings suggest that an urban environment does not protect against longitudinal cognitive decline. Instead, there seems to be a pattern similar to that observed in high versus low educated individuals, demonstrating that urban dwellers show a more rapid decline than their rural counterparts. Over time this relatively strong decline leads to convergence of cognitive performance, eliminating the initial benefit of urban relative to rural residence.</p> <hd id="AN0125880752-9">Acknowledgements</hd> <p>Core funding for Phases 1 and 2 of the Canadian Study of Health and Aging (CSHA) was provided by the Seniors' Independence Research Program, through Health Canada's National Health Research & Development Program (NHRDP). Funding for analysis of the caregiver component was provided by the Medical Research Council (MRC). Additional funding was provided by Pfizer Canada Inc. through the Medical Research Council/Pharmaceutical Manufacturers Association of Canada (MRC/PMAC), NHRDP, Bayer Inc., and the British Columbia Health Research Foundation. Core funding for Phase 3 was provided by the Canadian Institutes of Health Research (CIHR). Supplementary funding for the caregiver component was also obtained from CIHR. Additional funding was provided by Merck-Frosst and by Janssen-Ortho. The CSHA was coordinated through the University of Ottawa and Health Canada.</p> <p>We thank Truls Østbye for providing a copy of the CSHA data. We also thank Carolyn Clark and Runa E. Steenhuis for their comments on an earlier version of this paper.</p> <ref id="AN0125880752-10"> <title> Footnotes </title> <blist> <bibl id="bib1" idref="ref2" type="bt">1</bibl> <bibtext> This article was originally published with errors. This version has been corrected/amended. Please see Erratum (<ulink href="http://dx.doi.org/10.1080/03601277.2017.1386354">http://dx.doi.org/10.1080/03601277.2017.1386354</ulink>).</bibtext> </blist> </ref> <ref id="AN0125880752-11"> <title> References </title> <blist> <bibtext> Bondi, M. W., Jak, A. J., Delano-Wood, L., Jacobson, M. W., Delis, D. C., & Salmon, D. P. (2008). Neuropsychological contributions to the early identification of Alzheimer's disease. 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Van Gerven</p> <p>Reported by Author; Author</p> </aug> <nolink nlid="nl1" bibid="bib19" firstref="ref4"></nolink> <nolink nlid="nl2" bibid="bib32" firstref="ref5"></nolink> <nolink nlid="nl3" bibid="bib33" firstref="ref7"></nolink> <nolink nlid="nl4" bibid="bib23" firstref="ref8"></nolink> <nolink nlid="nl5" bibid="bib27" firstref="ref9"></nolink> <nolink nlid="nl6" bibid="bib29" firstref="ref10"></nolink> <nolink nlid="nl7" bibid="bib28" firstref="ref11"></nolink> <nolink nlid="nl8" bibid="bib22" firstref="ref12"></nolink> <nolink nlid="nl9" bibid="bib15" firstref="ref14"></nolink> <nolink nlid="nl10" bibid="bib37" firstref="ref15"></nolink> <nolink nlid="nl11" bibid="bib21" firstref="ref16"></nolink> <nolink nlid="nl12" bibid="bib11" firstref="ref17"></nolink> <nolink nlid="nl13" bibid="bib31" firstref="ref18"></nolink> <nolink nlid="nl14" bibid="bib20" firstref="ref19"></nolink> <nolink nlid="nl15" bibid="bib24" firstref="ref21"></nolink> <nolink nlid="nl16" bibid="bib16" firstref="ref23"></nolink> <nolink nlid="nl17" bibid="bib17" firstref="ref24"></nolink> <nolink nlid="nl18" bibid="bib26" firstref="ref25"></nolink> <nolink nlid="nl19" bibid="bib30" firstref="ref27"></nolink> <nolink nlid="nl20" bibid="bib13" firstref="ref29"></nolink> <nolink nlid="nl21" bibid="bib14" firstref="ref33"></nolink> <nolink nlid="nl22" bibid="bib36" firstref="ref39"></nolink> <nolink nlid="nl23" bibid="bib25" firstref="ref40"></nolink> <nolink nlid="nl24" bibid="bib34" firstref="ref44"></nolink> <nolink nlid="nl25" bibid="bib18" firstref="ref47"></nolink> <nolink nlid="nl26" bibid="bib35" firstref="ref48"></nolink> <nolink nlid="nl27" bibid="bib10" firstref="ref49"></nolink> <nolink nlid="nl28" bibid="bib12" firstref="ref50"></nolink>
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  Data: Urban Residence and Higher Education Do Not Protect against Cognitive Decline in Aging and Dementia: 10-Year Follow-Up of the Canadian Study of Health and Aging
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  Data: <searchLink fieldCode="AR" term="%22Helmes%2C+Edward%22">Helmes, Edward</searchLink><br /><searchLink fieldCode="AR" term="%22Van+Gerven%2C+Pascal+W%2E+M%2E%22">Van Gerven, Pascal W. M.</searchLink>
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  Data: <searchLink fieldCode="SO" term="%22Educational+Gerontology%22"><i>Educational Gerontology</i></searchLink>. 2017 43(11):552-560.
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  Data: Routledge. Available from: Taylor & Francis, Ltd. 530 Walnut Street Suite 850, Philadelphia, PA 19106. Tel: 800-354-1420; Tel: 215-625-8900; Fax: 215-207-0050; Web site: http://www.tandf.co.uk/journals
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  Data: <searchLink fieldCode="DE" term="%22Foreign+Countries%22">Foreign Countries</searchLink><br /><searchLink fieldCode="DE" term="%22Aging+%28Individuals%29%22">Aging (Individuals)</searchLink><br /><searchLink fieldCode="DE" term="%22Urban+Areas%22">Urban Areas</searchLink><br /><searchLink fieldCode="DE" term="%22Older+Adults%22">Older Adults</searchLink><br /><searchLink fieldCode="DE" term="%22Cognitive+Ability%22">Cognitive Ability</searchLink><br /><searchLink fieldCode="DE" term="%22Predictor+Variables%22">Predictor Variables</searchLink><br /><searchLink fieldCode="DE" term="%22Comparative+Analysis%22">Comparative Analysis</searchLink><br /><searchLink fieldCode="DE" term="%22Dementia%22">Dementia</searchLink><br /><searchLink fieldCode="DE" term="%22Rural+Areas%22">Rural Areas</searchLink><br /><searchLink fieldCode="DE" term="%22Educational+Attainment%22">Educational Attainment</searchLink><br /><searchLink fieldCode="DE" term="%22Testing%22">Testing</searchLink><br /><searchLink fieldCode="DE" term="%22Statistical+Analysis%22">Statistical Analysis</searchLink>
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  Data: 10.1080/03601277.2017.1372951
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  Data: The construct of cognitive reserve has primarily been defined in terms of a single proxy measure, education. There may, however, be alternative, potentially additive, proxy measures of cognitive reserve, such as rural or urban residence. Using a large sample of 10,263 older Canadians, ranging in age between 64 and 99 years (mean age = 75.7 years, SD = 7.1), residents of rural and urban areas were compared using the Modified Mini-Mental State (3MS) examination as a dependent variable. Within this sample, subsamples of demented and non-demented individuals were investigated. The 3MS data were analyzed using a linear mixed model with years of education and residence as proxies of cognitive reserve and time of testing (linear and quadratic) as a within-groups variable. All predictor variables in the model (i.e., gender, age, education, residence, and time of testing) had a significant impact on cognitive functioning. The results showed that, although urban residents and higher educated individuals performed better than rural residents and lower educated individuals at baseline, these performance benefits were nullified at 10-year follow-up. The disappearance of these initial performance benefits suggests that urban dwellers and higher educated individuals are not protected against age-related cognitive decline. Thus, no support was found for the cognitive reserve hypothesis.
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