Prevalence of dementia and cognitive impairment with no dementia in a primary care setting in southern Brazil

Prevalência de demência e declínio cognitivo sem demência em contexto de atenção primária no sul do Brasil

ABSTRACT

Background:

Cognitive decline is a common condition, but is still underrepresented in studies conducted in developing countries.

Objective:

To calculate the prevalence of cognitive decline and depression in an elderly community-dwelling population in a city in southern Brazil.

Methods:

We calculated the prevalences of dementia, cognitive impairment with no dementia (CIND) and symptoms of depression in an elderly population relying on the public healthcare system. This epidemiological study in Pelotas, Brazil, was conducted within the primary care setting. It included 299 older adults (mean age = 69.75 ± 7.6 years) who presented low levels of education (mean = 4.16 ± 3.17 years of education). They underwent cognitive screening and their medical records were analyzed.

Results:

Among these older adults, 142 (47.5%) presented cognitive decline: 104 (34.8%) matching the cognitive criteria for CIND and 38 (12.7%) matching the cognitive criteria for dementia. Among all the individuals who completed the cognitive screening, 141 (48.4%) were positive for symptoms of depression, of whom 99 (34%) did not have any previous diagnosis in their medical records.

Conclusion:

There was high prevalence of cognitive impairment among these older adults in a primary care setting. A large number of older adults were found to have symptoms of depression without any diagnosis.

Keywords:
Dementia; Public health; Depression; Cognitive decline; Alzheimer’s disease

RESUMO

Introdução:

Declínio cognitivo é uma condição prevalente, apesar de ainda pouco representada em estudos de países em desenvolvimento.

Objetivo:

Calcular a prevalência de declínio cognitivo e depressão de uma população de idosos de uma cidade do Sul do Brasil.

Métodos:

Nós calculamos a prevalência de demência, declínio cognitivo sem demência (DCSD) e sintomas de depressão de uma população idosa de uma cidade assistida pelo sistema público de saúde. Um estudo epidemiológico foi conduzido em Pelotas, Brasil, no contexto de atenção primária incluindo 299 idosos (idade média = 69.75±7.6 anos), apresentando baixo nível educacional (média de anos de educação = 4.16±3.17). Esses indivíduos realizaram teste de rastreio cognitivo, e seus prontuários foram analisados.

Resultados:

Um total de 142 (47.5%) idosos apresentaram declínio cognitivo, dos quais 104 (34.8%) destes indivíduos atenderam a critérios cognitivos de DCSD e 38 (12.7%) indivíduos atenderam a critérios cognitivos para demência. Dentre todos indivíduos que completaram o rastreio, 141 (48.4%) foram positivos para sintomas de depressão, enquanto 99 (34%) não tinham diagnóstico em seus prontuários.

Conclusão:

Em suma, nós descrevemos uma prevalência alta de deterioro cognitivo entre idosos em um estudo de atenção primária. Nós também achamos um grande número de idosos com sintomas de depressão sem diagnóstico.

Palavras-chave:
Demência; Saúde pública; Depressão; Declínio cognitivo; Doença de Alzheimer

INTRODUCTION

With increasing life expectancy worldwide, epidemiological data about dementia is becoming very important in order to address this challenging situation. In this context, few studies have described the prevalence and incidence of cognitive disorders in developing countries like Brazil1^,2. In a recent study, it was estimated that 77% of individuals with dementia in Brazil had not been properly diagnosed3, which would give rise to a massive public health problem. Indirectly, the cost of dementia will create a significant economic burden for the Brazilian care and social security systems, with an estimated cost per patient of 16,000 dollars annually4.

Recent advances in neurology and cognitive disorders have contributed to a redefinition of cognitive decline as a continuum, in which clinical manifestations occur at advanced stages. Pathological cognitive decline, initially in the form of mild Cognitive impairment (MCI) or even cognitive impairment with no dementia (CIND), is manifested mostly in the elderly population. Patients with CIND can be characterized as those who demonstrate cognitive impairment without significant impact on their daily activities5, but who do not match the cognitive criteria for MCI6. The cornerstone of the definition of dementia is that it involves significant impairment of individual’s activities of daily living7^,8. However, cognitive impairment may be the chief complaint in patients with depression. Mood disorders are highly prevalent among older adults9, and these also have a significant impact on quality of life and functional autonomy among the elderly10.

It is well known that cognitive impairment is generally underdiagnosed within the primary care system. These patients with cognitive impairment will not receive adequate treatment in the early stages of dementia, which will result in a faster pace of pathological progression and poorer quality of life11. It has been estimated that about two thirds of dementia patients are not diagnosed at this first contact in developed countries12 and in even greater proportions in developing country settings3. The lack of training of general practitioners with regard to diagnosing cognitive impairment and, especially, the lack of awareness of this condition in general population are major contributors to underdiagnosis of dementia13. Even in the tertiary-level care setting, cognitive decline has been demonstrated to be underdiagnosed14.

Primary care physicians have a key position in the healthcare system. These professionals can identify the first signs of cognitive decline, which ultimately leads to early intervention and better quality of life12. In addition, many public policy proposals end up lacking information on the prevalence and incidence of dementia in society15. Although the importance of investigating the prevalence of dementia in a community has been recognized, only a few studies are generally available in developing countries16. Furthermore, there is a lack of consensus on the impact of dementia on the elderly populations of developing countries17^,18. Therefore, the aim of this study was to calculate the prevalence of cognitive decline and depression in an elderly community-dwelling population relying on the public healthcare system, in Pelotas, a city in southern Brazil.

METHODS

A cross-sectional study was conducted in a primary care facility from April 2017 to August 2017, in Pelotas, a city located in the state of Rio Grande do Sul, the southernmost state of Brazil. This city has a population of 344,385 inhabitants, and 14.4% of them are estimated elderly19. The participants included in this study were community-dwelling residents in an area covered by the primary care system (Sistema Único de Saúde, SUS), comprising approximately 5000 people in total and, thus, an estimated 685 elderly people. All individuals who attended a consultation in this facility for any reason within the abovementioned timeframe and who were over 60 years old were invited to participate in this study. Since this was a study to estimate neuropsychiatric symptoms in a sample covered by the public healthcare system, we did not exclude any individual because of their diagnosis. Thus, individuals who attended the primary care setting were included without any restriction, provided that they signed an informed consent statement, as previously approved by the ethics committee of the Federal University of Pelotas.

All participants in the study underwent a clinical and neurological examination, at which sociodemographic and medical history data were also gathered, followed by cognitive screening. The latter included the mini-mental state examination (MMSE)20, the Clinical Dementia Rating (CDR)21, the Memory Assessment Complaint Questionnaire (MAC-Q)22 and the Geriatric Depression Scale reduced (GDS-15)23. Individuals were deemed to be positive for symptoms of depression if they presented a GDS score above 5. Their medical records were also analyzed to extract information about previous pathological conditions and previous use of medications.

Many approaches for defining cognitive impairment have been proposed 24. In the present study, individuals were classified into three groups according to their cognitive scores and other criteria, as follows. Individuals were included in the cognitively normal (CN) group if they presented MMSE scores higher than the normative values for age and education25, and if they also presented CDR scores of zero. Individuals were included in the CIND group if they presented MMSE scores lower than the normative values for age and education, and if they also presented CDR scores of 0.5 or zero. Individuals were included in the dementia group if they presented MMSE scores lower than the normative values for age and education, and if they also presented CDR scores higher than 0.5.

Descriptive analysis was performed to characterize the sample and calculate the prevalences of cognitive decline, CIND and dementia in this sample. Quantitative data were presented through calculation of proportions. For numerical variables, the mean and standard deviation were calculated. Wald’s test was used for ascertain heterogeneity and linear trends. Pearson’s correlation was performed and group comparisons were made with parametric tests and Tukey’s post-hoc test. The Stata software was used (v12.0, StataCorp LP, College Station, Texas, USA). Associations with p ≤ 0.05 were considered significant.

RESULTS

Out of the total of 685 older adults who had been estimated to live in the study area, 347 individuals over 60 years of age sought the primary care facility during the study period. Among these 347 eligible subjects, a total of 46 individuals (13.3%) were not interviewed at the time of their consultation and were not found through an active search and two individuals (0.6%) did not agree to participate. These proportions of individuals were representative of community-dwelling older adults in previous descriptions.

Our sample thus consisted of 299 individuals (44% of all older adults estimated to live in the area) who agreed to undergo the study protocol. Their mean age was 69.75 ± 7.6 years and 4.16 ± 3.17 years of education (Table 1). Importantly, 51 individuals (17.1%) were illiterate and 56 (18.7%) reported that they could not read although they had previously gone to school. The whole sample included 203 women (67.8%), and 157 patients (52.5%) were in the CN group.

Table 1.
Sociodemographic characteristics of the sample.

	CN (n = 157)	CIND (n = 104)	Dementia (n = 38)
Age, mean (SD)	68.57 (6.03)*	69.33 (7.57)*	75.91 (10.44)
60 - 69 years, n	95 (60.5%)	58 (55.8%)	11 (29%)
70 - 79 years, n	51 (32.5%)	33 (31.7%)	10 (26.3%)
80 years or over, n	11 (7%)	13 (12.5%)	17 (44.7%)
Years of education, mean (SD)	4.59 (3.28)*	4.13 (2.96)*	2.29 (2.55)
0 years, n	23 (14.6%)	12 (11.6%)	16 (42.2%)
1 - 3 years, n	27 (17.2%)	36 (34.6%)	5 (13.1%)
4 - 7 years, n	79 (50.3 %)	41 (39.4%)	12 (31.6%)
8 years or more, n	28 (17.9%)	15 (14.4%)	5 (13.1%)
Illiterate, n	20 (12.7%)	21 (20.2%)	15 (39.4%)
Women, n	99 (63%)	76 (73%)	27 (71%)
Living alone, n	27 (17.2%)	28 (26.9%)	8 (21%)
Psychiatric disease, n	39 (24.8%)	27 (25.9%)	12 (31.5%)
GDS-15, mean (SD)	4.7 (3.34)*	5.2 (3.44)*	7.66 (3.4)
Subjective memory decline (Yes), n	49 (31.2%)	27 (25.9%)	23 (60.5%)
MAC-Q, mean (SD)	4.38 (4.2)*	4.22 (4.0)*	8.1 (4.76)
MMSE, mean (SD)	26.97 (2.53)*	22.11 (3.89)*	16.3 (4.94)

• CN: cognitively normal; CIND: cognitive impairment with no dementia; GDS-15: Geriatric Depression Scale - 15 item version; MAC-Q: Memory Assessment Questionnaire; MMSE: Mini-Mental State Examination; * p < 0.05 in relation to the dementia group.

We identified that a total of 142 of these older adults (47.49%) presented cognitive decline, of whom 104 (34.8%) were in the CIND group and 38 (12.7%) were in the dementia group. Importantly, the individuals included in the dementia group were older than the individuals included in the CIND and CN groups (75.91 ± 10.44 vs. 69.33 ± 7.57 vs. 68.57 ± 6.03 respectively; p < 0.001). The total scores from the MMSE were significantly different higher in the CIND group than in the dementia group (22.11 ± 3.89 vs. 16.3 ± 4.94; p < 0.001). In addition, the total MMSE score showed a positive correlation with education for the whole sample (r = 0.52; p < 0.05). Individuals classified in the dementia group (8.1 ± 4.76) showed significantly increased MAC-Q scores than those of the CIND group (4.22 ± 4; p < 0.001) or the CN group (4.38± 4.2; p < 0.001), but no correlation was found between MAC-Q scores and MMSE or education (p > 0.05 for both).

Among all the study participants, eight subjects did not complete the GDS assessment due to clinical, functional or cognitive disability. Among the remaining 291 individuals, 141 (48.4%) showed GDS scores above 4, which represents positivity for symptoms of depression. A total of 113 participants (38.8%) scored between 5 and 10 in the GDS, and 28 (9.6%) scored above 11 in the GDS (Table 1), which represents severe symptoms of depression. The dementia group showed more symptoms of depression than did the CN group (7.66 ± 3.4 vs. 4.7 ± 3.34; p < 0.001) or the CIND group (5.2 ± 3.44; p = 0.001). There was a weak correlation between the total MMSE score and the GDS score (r = -0.18; p = 0.002). Altogether, almost a third of the whole sample (99 individuals) showed GDS scores above 5 but did not have a diagnosis of depression in their medical reports. However, 42 individuals showed GDS scores above 5 and had a diagnosis of major depression in their medical records, while 13 individuals had a diagnosis of major depression in their medical records, but they showed GDS score below 5 and were using medication for depression.

There were 33 individuals with CDR scores above 0.5, but only 8 were formally classified as presenting dementia, in their medical records. A linear regression model that included age, years of education and total GDS score as predictors of the CDR score was statistically significant (R² = 0.12; p < 0.0001). There was a large effect size for the associations between CDR and age, and between CDR and GDS score (Cohen’s d = 12.8 and 1.9, respectively).

Among the entire sample, 109 (36.4%) of the patients had a medical diagnosis of a neuropsychiatric disorder in their medical records. Among these individuals, 56 (18.73%) were diagnosed with major depression, 23 (7.7%) with general anxiety disorder, 8 (2.67%) with Parkinson's disease, 8 (2.67%) with unspecified dementia, 6 (2%) with Alzheimer's disease, 5 (1.67%) with schizophrenia, 4 (1.33%) with insomnia, 4 (1.33%) with bipolar affective disorder and 1 (0.3%) with mild retardation.

A descriptive analysis on previous medical histories was conducted in order to clarify the characteristics of the sample. Regarding the presence of clinical comorbidities, 225 (75.3%) of the elderly subjects had a previous diagnosis of hypertension, 204 (68.2%) had diabetes mellitus, 149 (49.8%) had dyslipidemia and 39 (13%) had a history of stroke. In addition, 137 (45.8%) of all the subjects had smoked cigarettes and 4 (1.6%) had used some type of illicit drug. Regarding alcohol consumption, 219 (73.2%) of the elderly subjects did not use alcohol, 43 (14.4%) drank alcohol once a month, 21 (7%) did this 2-4 times a month, 4 (1.3%) did this 2-3 times a week and 12 (4%) did this more than 4 times a week. A total of 181 (60.5%) of the elderly subjects did not use any type of psychotropic medication. Among the 118 (39.5%) who used this, 84 (28.1%) used antidepressants, 66 (22.1%) used benzodiazepines, 16 (5.4%) used anticonvulsants, 12 (4%) used antipsychotic drugs, 5 (1.7%) used antiparkinsonian drugs and 1 (0.3%) used lithium carbonate.

DISCUSSION

To our knowledge, this was the first study conducted to identify the epidemiological and sociodemographic characteristics of cognitive decline in a city in southern Brazil. The prevalence of all types of dementia was higher in our sample than the prevalence estimated for the whole country (12.7% vs. 7.6%)15. It has been estimated that the median proportion of older adults living with dementia in Latin America is 7.13%15, which is higher than the global average predicted by the World Health Organization (WHO)26. Many studies have found different prevalences of MCI around the world, ranging from 6.1 to 85%2^,27.

In the present study, the prevalence of cognitive impairment with no dementia in the whole sample was higher than in previous Brazilian studies on CIND28 (34.8% vs. 17.5%, respectively). Specifically, there was a trend towards stability in the prevalence of dementia from 60-69 years to 70-79 years (29% and 26.3% of all individuals with dementia, respectively). This stability was also described in another study conducted in southeastern Brazil29. This finding may have been associated with a notable number of older adults with dementia presenting high scores for depressive symptoms, in association with low literacy in this region. This may also explain the high prevalence of CIND between 60-69 years in this sample (55.8% of all individuals with CIND). These two factors combined ultimately lead to important loss of functionality and independence. This significant difference can also be explained by the diversity of methodologies among different studies, such as use of a population-based approach or differences in the criteria used to define MCI and CIND28^,30. A previous study using an epidemiological approach27 indicated that the prevalence of MCI was between 7.7 and 25.2% in several populations around the world. Despite limited data from the Brazilian setting, the incidence of MCI appears to be similar to what has been found in other countries2. Nonetheless, broader, population-based studies are necessary in order to increase the numbers of estimates of MCI in developing countries, using previously established clinical criteria for its diagnosis.

An alarming number of individuals scored positive for any degree of depression in this study (48.4% of the total sample). A previous study31 demonstrated a lower rate of depressive symptoms (14.9%) than that of our sample. Importantly, approximately a third of our total sample had symptoms of depression at the time of the evaluation without any medical diagnosis of major depression in their medical records. Furthermore, even individuals with the diagnostic criteria for major depression showed important symptoms of depression, thus indicating that their treatment should be re-evaluated. Although a single instrument is not enough to diagnose this disease, the high prevalence of symptoms of depression found in this study indicates that major depression may be underdiagnosed in older adults. Other studies have also found that older adults present high prevalence of depression in primary care evaluations32^,33. Moreover, a meta-analysis showed that there was a close relationship between depression and cognitive decline, in which the presence of depression not only was a confounding factor for neurodegeneration34, but also was a risk factor for the development of some type of dementia35. There is evidence supporting the benefits of screening for depression among older adults36^,37, especially done by physicians in the primary care setting.

Importantly, a significant number of subjects in this study had a very low level of education. The mean number of years of education for the whole sample was similar to the rates for the state (4.16 ± 3.17 and 4.1 ± 0.06, respectively)19, and about a quarter of the participants had not completed one year of schooling. Also, the dementia group showed significantly fewer years of education than the cognitively normal controls (Table 1; p < 0.001). It is already known that developing countries have lower educational levels than do developed countries2. Moreover, the association between lower education and increased risk of dementia is a recurrent subject of interest. Recent studies have suggested that there is a negative association between the number of years of formal education and the risk of dementia, which appears to be stronger before old age38^,39. Thus, targeting formal education should be a priority for public health policies, in order to reduce the incidence of dementia and its impact on society.

Even though the present study was conducted with our best efforts, it was subject to bias. One major limitation was the way in which the study groups were defined, given that only one cognitive screening (MMSE) was performed, in association with one tool for measuring the severity of disease (CDR), without a scale to evaluate activities of daily living. Because the individuals studied were selected in a specific city region, external validation of this study should be done with caution. In addition, individuals with greater cognitive and functional impairment may have been restricted from primary medical care, which thus would make the dementia group underrepresented. Another important characteristic of our population was the lower-income conditions of the subjects included: patients with better economic conditions are usually attended through private healthcare systems and, hence, they are not properly represented in our sample.

As previously discussed, cognitive decline was only identified through cognitive screenings in our study, which ultimately leads to a higher proportion of differential diagnoses such as major depressive disorder and rapidly progressing dementia. Considering that the prevalence of neurodegenerative disorders is higher than that of other causes of dementia, this may have a slight impact on the interpretation of our results. It is essential that other communities in developing countries should estimate their prevalences and incidences of dementia, so that comparisons can be made and so that the results from our study can be confirmed.

In summary, we described the prevalences of cognitive decline with no dementia (34.8%) and dementia (12.7%) among older adults in a community-based study in Brazil. Importantly, a large number of older adults with symptoms of depression, but no medical diagnosis or treatment, were identified. Practical screening for depression may help to increase recognition and proper treatment of depression among elderly people.

REFERENCES

• 1. Boff MS, Sekyia FS, Bottino CM de C. Revisão sistemática sobre prevalência de demência entre a população brasileira. Rev Med (São Paulo). 2015;94(3):154-61. https://doi.org/10.11606/issn.1679-9836.v94i3p154-161
  » https://doi.org/10.11606/issn.1679-9836.v94i3p154-161
• 2. Chaves ML, Camozzato AL, Godinho C, Piazenski I, Kaye J. Incidence of mild cognitive impairment and Alzheimer disease in Southern Brazil. J Geriatr Psychiatry Neurol. 2009 Sep;22(3):181-7. https://doi.org/10.1177/0891988709332942
  » https://doi.org/10.1177/0891988709332942
• 3. Nakamura AE, Opaleye D, Tani G, Ferri CP. Dementia underdiagnosis in Brazil. Lancet. 2015 Jan 31;385(9966):418-9. https://doi.org/10.1016/S0140-6736(15)60153-2
  » https://doi.org/10.1016/S0140-6736(15)60153-2
• 4. Ferretti C, Sarti FM, Nitrini R, Ferreira FF, Brucki SMD. An assessment of direct and indirect costs of dementia in Brazil. PLoS One. 2018 Mar 1;13(3):e0193209. https://doi.org/10.1371/journal.pone.0193209
  » https://doi.org/10.1371/journal.pone.0193209
• 5. Jacova C, Peters KR, Beattie BL, Wong E, Riddehough A, Foti D, et al. Cognitive impairment no dementia - neuropsychological and neuroimaging characterization of an amnestic subgroup. Dement Geriatr Cogn Disord. 2008;25(3):238-47. https://doi.org/10.1159/000115848
  » https://doi.org/10.1159/000115848
• 6. Petersen RC. Mild cognitive impairment. Continuum (Minneap Minn). 2016 Apr;22(2 Dementia):404-18. https://doi.org/10.1212/CON.0000000000000313
  » https://doi.org/10.1212/CON.0000000000000313
• 7. Jack Jr CR, Lowe VJ, Senjem ML, Weigand SD, Kemp BJ, Shiung MM, et al. 11C PiB and structural MRI provide complementary information in imaging of Alzheimer’s disease and amnestic mild cognitive impairment. Brain. 2008 Mar;131(3):665-80. https://doi.org/10.1093/brain/awm336
  » https://doi.org/10.1093/brain/awm336
• 8. McKhann GM, Knopman DS, Chertkow H, Hyman BT, Jack Jr CR, Kawas CH, et al. The diagnosis of dementia due to Alzheimer’s disease: recommendations from the National Institute on Aging-Alzheimer’s Association workgroups on diagnostic guidelines for Alzheimer’s disease. Alzheimers Dement. 2011 May;7(3):263-9. https://doi.org/10.1016/j.jalz.2011.03.005
  » https://doi.org/10.1016/j.jalz.2011.03.005
• 9. Alexopoulos GS. Mechanisms and treatment of late-life depression. Transl Psychiatry. 2019 Aug 5;9(1):188. https://doi.org/10.1038/s41398-019-0514-6
  » https://doi.org/10.1038/s41398-019-0514-6
• 10. Sperling RA, Aisen PS, Beckett LA, Bennett DA, Craft S, Fagan AM, et al. Toward defining the preclinical stages of Alzheimer’s disease: recommendations from the National Institute on Aging-Alzheimer’s Association workgroups on diagnostic guidelines for Alzheimer’s disease. Alzheimers Dement. 2011 May;7(3):280-92. https://doi.org/10.1016/j.jalz.2011.03.003
  » https://doi.org/10.1016/j.jalz.2011.03.003
• 11. Wucherer D, Eichler T, Kilimann I, Hertel J, Michalowsky B, Thyrian JR, et al. Antidementia drug treatment in people screened positive for dementia in primary care. J Alzheimers Dis. 2015;44(3):1015-21. https://doi.org/10.3233/JAD-142064
  » https://doi.org/10.3233/JAD-142064
• 12. Valcour VG, Masaki KH, Curb JD, Blanchette PL. The detection of dementia in the primary care setting. Arch Intern Med. 2000 Oct 23;160(19):2964-8. https://doi.org/10.1001/archinte.160.19.2964
  » https://doi.org/10.1001/archinte.160.19.2964
• 13. Lawlor B. The local and global imperative to raise public awareness and knowledge about dementia. Arq Neuropsiquiatr. 2018 Nov;76(11):729-30. https://doi.org/10.1590/0004-282X20180118
  » https://doi.org/10.1590/0004-282X20180118
• 14. Jacinto AF, Brucki S, Porto CS, Martins M de A, Nitrini R. Detection of cognitive impairment in the elderly by general internists in Brazil. Clinics (São Paulo). 2011;66(8):1379-84. https://doi.org/10.1590/S1807-59322011000800012
  » https://doi.org/10.1590/S1807-59322011000800012
• 15. Burlá C, Camarano AA, Kanso S, Fernandes D, Nunes R. Panorama prospectivo das demências no Brasil: um enfoque demográfico. Cien Saúde Colet. 2013 Oct;18(10):2949-56. https://doi.org/10.1590/S1413-81232013001000019
  » https://doi.org/10.1590/S1413-81232013001000019
• 16. Ferri CP, Jacob KS. Dementia in low-income and middle-income countries: different realities mandate tailored solutions. PLoS Med. 2017 Mar 28;14(3):e1002271. https://doi.org/10.1371/journal.pmed.1002271
  » https://doi.org/10.1371/journal.pmed.1002271
• 17. Herrera Jr E, Caramelli P, Silveira ASB, Nitrini R. Epidemiologic survey of dementia in a community-dwelling Brazilian population. Alzheimer Dis Assoc Disord. 2002 Apr-Jun;16(2):103-8. https://doi.org/10.1097/00002093-200204000-00007
  » https://doi.org/10.1097/00002093-200204000-00007
• 18. Engedal K, Laks J. Towards a Brazilian dementia plan? Lessons to be learned from Europe. Dement Neuropsychol. 2016 Apr-Jun;10(2):74-8. https://doi.org/10.1590/S1980-5764-2016DN1002002
  » https://doi.org/10.1590/S1980-5764-2016DN1002002
• 19. IBGE. Síntese de indicadores sociais: uma análise das condições de vida da população brasileira: 2016. Rio de Janeiro(RJ): IBGE; 2016.
• 20. Lourenço RA, Veras RP. Mini-Exame do estado mental: características psicométricas em idosos ambulatoriais. Rev Saúde Pública. 2006 Aug;40(4):712-9. https://doi.org/10.1590/S0034-89102006000500023
  » https://doi.org/10.1590/S0034-89102006000500023
• 21. Montaño MBMM, Ramos LR. Validade da versão em português da Clinical Dementia Rating. Rev Saúde Pública. 2005 Dec 12;39(6):912-7. https://doi.org/10.1590/S0034-89102005000600007
  » https://doi.org/10.1590/S0034-89102005000600007
• 22. Mattos P, Lino V, Rizo L, Alfano Â, Araújo C, Raggio R. Memory complaints and test performance in healthy elderly persons. Arq Neuropsiquiatr. 2003 Dec;61(4):920-4. https://doi.org/10.1590/S0004-282X2003000600006
  » https://doi.org/10.1590/S0004-282X2003000600006
• 23. Sheikh JI, Yesavage JA. Geriatric Depression Scale (GDS): recent evidence and development of a shorter version. Clin Gerontologist. 1986;5(1-2):165-73. https://doi.org/10.1300/J018v05n01_09
  » https://doi.org/10.1300/J018v05n01_09
• 24. Jak AJ, Bondi MW, Delano-Wood L, Wierenga C, Corey-Bloom J, Salmon DP, et al. Quantification of five neuropsychological approaches to defining mild cognitive impairment. Am J Geriatr Psychiatry. 2009 May;17(5):368-75. https://doi.org/10.1097/JGP.0b013e31819431d5
  » https://doi.org/10.1097/JGP.0b013e31819431d5
• 25. Brucki SMD, Nitrini R, Caramelli P, Bertolucci PHF, Okamoto IH. Sugestões para o uso do mini-exame do estado mental no Brasil. Arq Neuropsiquiatr. 2003 Sep;61(3B):777-81. https://doi.org/10.1590/S0004-282X2003000500014
  » https://doi.org/10.1590/S0004-282X2003000500014
• 26. World Health Organization. World Health Statistics 2016: monitoring health for the SDGs, sustainable development goals. Geneva: World Health Organization; 2016. 121p.
• 27. Brucki SMD. Epidemiology of mild cognitive impairment in Brazil. Dement Neuropsychol. 2013 Oct-Dec;7(4):363-6. https://doi.org/10.1590/S1980-57642013DN74000002
  » https://doi.org/10.1590/S1980-57642013DN74000002
• 28. César KG, Brucki SMD, Takada LT, Nascimento LFC, Gomes CMS, Almeida MCS, et al. Prevalence of cognitive impairment without Dementia and Dementia in Tremembé, Brazil. Alzheimer Dis Assoc Disord. 2016 Jul-Sep;30(3):264-71. https://doi.org/10.1097/WAD.0000000000000122
  » https://doi.org/10.1097/WAD.0000000000000122
• 29. Scazufca M, Menezes PR, Vallada HP, Crepaldi AL, Pastor-Valero M, Coutinho LMS, et al. High prevalence of dementia among older adults from poor socioeconomic backgrounds in São Paulo, Brazil. Int Psychogeriatr. 2008 Apr;20(2):394-405. https://doi.org/10.1017/S1041610207005625
  » https://doi.org/10.1017/S1041610207005625
• 30. Luis CA, Loewenstein DA, Acevedo A, Barker WW, Duara R. Mild cognitive impairment: directions for future research. Neurology. 2003 Aug 26;61(4):438-44. https://doi.org/10.1212/01.WNL.0000080366.90234.7F
  » https://doi.org/10.1212/01.WNL.0000080366.90234.7F
• 31. Holz AW, Nunes BP, Thumé E, Lange C, Facchini LA. Prevalence of cognitive impairment and associated factors among the elderly in Bagé, Rio Grande do Sul, Brazil. Rev Bras Epidemiol. 2013 Dec;16(4):880-8. https://doi.org/10.1590/S1415-790X2013000400008
  » https://doi.org/10.1590/S1415-790X2013000400008
• 32. Mojtabai R. Diagnosing depression in older adults in primary care. N Engl J Med. 2014 Mar 27;370(13):1180-2. https://doi.org/10.1056/NEJMp1311047
  » https://doi.org/10.1056/NEJMp1311047
• 33. Kunik ME, Roundy K, Veazey C, Souchek J, Richardson P, Wray NP, et al. Surprisingly high prevalence of anxiety and depression in chronic breathing disorders. Chest. 2005 Apr;127(4):1205-11. https://doi.org/10.1378/chest.127.4.1205
  » https://doi.org/10.1378/chest.127.4.1205
• 34. Lima-Silva TB, Yassuda MS. The relationship between memory complaints and age in normal aging. Dement Neuropsychol. 2009 Apr-Jun;3(2):94-100. https://doi.org/10.1590/S1980-57642009DN30200005
  » https://doi.org/10.1590/S1980-57642009DN30200005
• 35. Bastida JD, Pomés NP, Font SJ, Eickhoff AF. La depresión: un predictor de demencia. Rev Esp Geriatr Gerontol. 2016 Mar-Apr;51(2):112-8. https://doi.org/10.1016/j.regg.2015.10.008
  » https://doi.org/10.1016/j.regg.2015.10.008
• 36. Vieira ER, Brown E, Raue P. Depression in older adults: screening and referral. J Geriatr Phys Ther. 2014 Jan-Mar;37(1):24-30. https:doi.org/10.1519/JPT.0b013e31828df26f
  » https:doi.org/10.1519/JPT.0b013e31828df26f
• 37. Smithson S, Pignone MP. Screening adults for depression in primary care. Med Clin North Am. 2017 Jul;101(4):807-21. https://doi.org/10.1016/j.mcna.2017.03.010
  » https://doi.org/10.1016/j.mcna.2017.03.010
• 38. Frankish H, Horton R. Prevention and management of dementia: a priority for public health. Lancet. 2017 Dec 16;390(10113):2614-5. https://doi.org/10.1016/S0140-6736(17)31756-7
  » https://doi.org/10.1016/S0140-6736(17)31756-7
• 39. Wilson RS, Yu L, Lamar M, Schneider JA, Boyle PA, Bennett DA. Education and cognitive reserve in old age. Neurology. 2019 Mar 5;92(10):e1041-50. https://doi.org/10.1212/WNL.0000000000007036
  » https://doi.org/10.1212/WNL.0000000000007036

Publication Dates

• Publication in this collection
  25 Aug 2021
• Date of issue
  July 2021

History

• Received
  24 Aug 2020
• Reviewed
  16 Oct 2020
• Accepted
  21 Oct 2020