Skip to main content
Download PDF
  • Research article
  • Open access
  • Published:

Cognitive, functional, physical, and nutritional status of the oldest old encountered in primary care: a systematic review

BMC Family Practice volume 21, Article number: 58 (2020) Cite this article

Abstract

Background

The oldest old (individuals over 90 years) are a fast-growing population. Characterizing their specificity would be helpful to adapt health care. This study aimed to characterize the cognitive, functional, nutritional, and physical status of individuals over 90.

Methods

We conducted a systematic review of cross-sectional or cohort studies of individuals aged 90 years old or more, living at home or in a nursing home, in April 2018. Two reviewers selected eligible articles, extracted data, and evaluated the risk of bias (assessed by the Newcastle-Ottawa Scale).

Results

The search strategy identified 3086 references; 35 articles were included referring to 8 cross-sectional and 27 longitudinal studies. Dementia was diagnosed in 30–42.9% of study participants, cognitive impairment in 12–50%, and 31–65% had no cognitive impairment. In terms of activities of daily living, 14–72.6% of individuals had no difficulty, 35.6–38% had difficulty, and 14.4–55.5% were dependent. For instrumental activities of daily living, 20–67.9% needed help. Regarding nutritional status, the Mini Nutritional Assessment Short Form mean score ranged from 10.3 (SD: 1.8) to 11.1 (SD: 2.4). Eight to 32% of individuals could not stand up from a chair, 19–47% could stand without the use of their arms; and 12.9–15% were not able to walk 4 m.

Conclusions

These results suggest a heterogeneous population with a certain proportion of oldest old with a low level of disability. These findings suggest that a specific approach in the care of the oldest old could help prevent disability.

Peer Review reports

Background

Population forecasts suggest that the population of 80 years old and over is likely to more than triple by the year 2050, from 126.5 million to 446.6 million [1].

This is a result of modifications in socio-environmental and biological factors during the human life course [2], with recent studies suggesting that some diets, economic status, the presence of a caregiver, are correlated with better aging [2,3,4,5,6]. Genetic signatures that predict the phenotypic outcome of exceptional long-living individuals are also identified [5, 6].

The oldest among the elderly are called the “oldest old”. Several definitions are proposed: the American Geriatric Society and the World Health Organization define the oldest old as individuals aged over 80 years, while the British Geriatrics Society uses 85 years as a threshold. In recent publications, the cut off has been fixed at 85 or 90 years and over [7,8,9,10].

The care of the oldest old is a growing topic in medical research and is a challenge for health care organizations. In this population, the aim of individual care is to allow a successful aging at home by preventing disability and loss of abilities [11, 12]. The desire to age at home, as well as population projections, create challenges for health care organizations, particularly in primary care.

Research on risk factors and preventive interventions for individuals 80 and over is limited. Despite an increasing number of cohorts studied in order to describe this population, such as the 90+ study, the Leiden 85-plus study, the Vitality 90+ study, the Newcastle 85+ study [e.g. 7–10], or recent literature on centenarians [13,14,15], few data describe the global status of individuals aged 90 and over.

We carried out a systematic review of the literature to better understand the characteristics of this population encountered in primary care in the coming years.

This study aimed to characterize the cognitive, functional, nutritional, and physical status of individuals over 90.

Methods

This review was realized according to a systematic review process derived from the Preferred Reporting Items for Systematic reviews and Meta-Analyses (PRISMA) statement [16].

Inclusion criteria

Cross-sectional or cohort studies of geriatric assessments, with individuals aged 90 years and over, were included. We set a cut off of individuals aged 90 and over in order to select a specific population of very old individuals. Participants had to live at home or in a nursing home. The studies had to assess at least one of the following outcomes (i.e. dimensions of a geriatric assessment): cognitive, functional, nutritional, or physical status, and had to be conducted with a minimum sample size of 100 participants. In order to ensure a sufficient precision of estimates, baseline data had to be described. In studies conducted on participants both under and over 90, the data for participants 90 and over had to be clearly identified and only those data were included. We restricted this review to high quality studies according to the Newcastle-Ottawa Scale (NOS), adapted to cross sectional reviews based on previous studies [17]. Data were only included for the studies allocated at least one star for 6 out of 7 items. There was no limitation on publication year.

Exclusion criteria

We did not select studies that focused on a particular disease. Duplicate studies, or studies without any data about the studied outcomes and sample constitution, were not included. For studies that studied the same cohort, we included data only when different dimensions were assessed. Otherwise, we included only the most complete article.

Search strategy and selection criteria

Preliminary to the extraction, two authors (E.E., F.D.) searched the websites World Health Organization, American Geriatric Society, European Geriatric Medicine Society, British Geriatric Society, French Geriatric and Gerontology Society, National Institute of Health, French National Authority of Health, and Google Scholar to delineate the subject and the search strategies.

Two authors (E.E., F.D.) applied the search strategies (See Additional file 1) to Medline, Cochrane Library, Pascal, and Web of Science related to mesh terms “aged 80 and over” “geriatric assessment” on April 24th, 2018. If available, the reference lists of previous similar literature reviews were carefully examined to manually identify potential eligible articles.

A two-step article screening was independently and blindly performed by the same two authors. The first selection was based on the title and/or abstract. Full texts were obtained for those studies that met the inclusion criteria, or when there was uncertainty. The second step was based on full text screening. Disagreements at each stage of selection were resolved by discussion, and through consultation with a third author (V.G.) if necessary.

Data extraction

Data were extracted from the included studies by two authors (E.E. and F.D.), independently, using a pre-established standard assessment. The assessment included: author, year, country, cohort name, type of study (study design), settings, rate of participation, demographic characteristics, size of the sample, details of the gerontological assessment, and any or all of the following assessment results: cognitive, functional, nutritional, and physical status. For longitudinal studies, we used baseline data. Some studies did not provide adequate details on sex of the participants, in which case we provided aggregated results for men and women.

Results

Study selection

The search identified 3086 references. After the exclusion of duplicates, 2659 references were screened, and of these, 261 full text articles were reviewed (Fig. 1). Finally, 35 articles were included in this review and assessed for risk of bias [18,19,20,21,22,23,24,25,26,27,28,29,30,31,32,33,34,35,36,37,38,39,40,41,42,43,44,45,46,47,48,49,50,51,52]. No article was excluded after that assessment.

Fig. 1
figure 1

Flow chart of the review selection process

Full size image

Study characteristics (see Additional file 2)

Studies were conducted in 15 countries across four continents: Europe (n = 20) [20, 22, 23, 27,28,29,30,31,32, 37,38,39,40, 42,43,44, 47,48,49, 51], North America (n = 9) [18,19,20, 24,25,26, 41, 45, 46], Asia (n = 5) [33,34,35,36, 52], and Oceania (n = 1) [46].

Studies included individuals over 90 (n = 22) [18,19,20,21,22,23,24,25, 28, 30, 34, 35, 37, 38, 43,44,45,46,47, 49,50,51], individuals under and over 90 (only data from individuals over 90 were included) (n = 8) [29, 31, 32, 39, 40, 42, 48, 52], and centenarians (n = 5) [26, 30, 33, 36, 41].

The participation rate ranged between 47% [24] and 89% [18]; it was over 70% in more than 40% of studies. There were 27 longitudinal studies [18, 20,21,22,23, 25, 28, 29, 31, 34,35,36,37,38,39,40,41,42,43,44,45,46,47,48,49, 51, 52] and eight cross-sectional studies [19, 24, 26, 27, 30, 32, 33, 50] (three using databases from electronic medical files or administrative databases [29, 32, 50]).

Participants were living in a private home or nursing home (n = 27) [18,19,20,21, 23,24,25,26,27,28,29, 31, 33, 36,37,38,39,40,41,42, 44,45,46,47,48,49, 51], only living in private homes (n = 3) [34, 43, 50], and not specified (n = 5) [22, 30, 32, 35, 52].

Only four studies carried out an evaluation of all variables, cognitive, functional, physical and nutritional status [27, 32, 44, 48], providing a global approach of a same study population (Table 1).

Table 1 Results of the studies with an evaluation of the four characteristics of interest: cognitive, functional, physical and nutritional status
Full size table

Dimensions of gerontological evaluation

Cognition

Cognitive status data (See Additional file 2) were provided in 25 studies [19, 23,24,25,26,27,28, 30,31,32,33, 35, 39,40,41,42,43,44,45,46,47,48,49, 51, 52], based on the Mini Mental State Examination (MMSE) (n = 22) [19, 23,24,25,26,27,28, 31,32,33, 35, 39, 40, 42,43,44,45,46,47,48,49, 51, 52], the Diagnostic and Statistical Manual of Mental Disorders, third or fourth edition, criteria for dementia (n = 6) [25, 40, 42, 47, 49, 51], and the Short Portable Mental Status Questionnaire (n = 1) [41]. One study did not provide this information [30].

Dementia was diagnosed in 30% [25] to 42.9% [42] of participants. Cognitive impairment was diagnosed in 12% [19] to 50% [41] of participants. No cognitive impairment was found in 31% [25] to 65.8% [45] of participants. The prevalence of dementia was more than 50% in studies where participants were over 95, and mean MMSE scores were also lower in these studies.

For articles reporting on populations with low MMSE, we searched the education level (if available) of the study population in order to suggest a link [24, 26, 27, 35]. (Table 2).

Table 2 Mini Mental State Evaluation results and education level for studies with low Mini Mental State Evaluation results in older people aged 90 and over
Full size table

Functional status

Functional status data were provided in 19 studies (See Additional file 2), and were based on Activities of Daily Living (ADL) (n = 19) [18, 22, 23, 26,27,28, 32, 36,37,38,39, 42,43,44, 46, 48, 49, 51, 52], and Instrumental ADL (IADL) (n = 7) [26, 28, 32, 36, 39, 46, 51].

The ADL Katz index was used, either the six-item version (n = 4) [18, 32, 36, 49, 52], the five-item version (n = 3) [22, 39, 44], or unspecified (n = 3) [23, 27, 43]. Four studies used the Barthel Index, either the 100-item version (n = 3) [28, 37, 38] or the 20-item version (n = 1) [42]. Two studies used another ADL index (ADL-staircase) [48], the Lawton 25 item B-ADL [46]. Three studies did not describe their scale [26, 51].

An eight-item IADL index (n = 3) [28, 32, 36], five-item IADL Katz Index (n = 1) [39], and the Bayer-IADL (n = 1) [46], were used, and one study did not provide this information [26, 51].

Based on these data, 14% [51] to 72.6% [49] of individuals were classed with the ADL scale as having no difficulty, 35.6% [44] to 38% [28] of individuals as “having difficulty”, and 14.4% [49] to 55.5% [18] as “dependent”. In addition, 20% [51] to 67.9% [32] needed help according to the IADL scale, and this was close to 90% [36] for centenarians.

As with cognition, studies with participants older than 95 [18, 23, 36, 39, 40, 42, 44, 46, 48] had lower ADL scores.

Nutritional status

Thirteen studies provided data on nutritional status (See Additional file 2) [20, 27,28,29,30, 32, 34, 37, 38, 41, 42, 44, 48], most commonly using Body Mass Index (BMI) (n = 9) [20, 27, 29, 30, 32, 37, 38, 41, 42, 44], followed by the Mini Nutritional Assessment Short Form (n = 2) [28, 34], the Mini Nutritional Assessment (n = 1) [48], the Malnutrition Universal Screening Tool (n = 1) [20], unintentional weight loss (n = 1) [32] and a serum albumin test (n = 1) [34].

The distribution of the study sample by BMI is as follows: less than 18.5: 1.9–12% [20, 30]; between 18.5 and 24.9: 58[30]-63.4% [29]; between 25 and 29.9: 15[30]-25% [30]; and over 30: 6 [30]-9.6% [29]. The mean BMI ranged from 23.68 (SD: 3.96) [27] to 25.1 (SD: 4.1) [42]. The Mini Nutritional Assessment Short Form mean score ranged from 10.3 (SD: 1.8) [34] to 11.1 (SD: 2.4) [28] (a score ≤ 11 indicates a risk of malnutrition).

Physical status

Nine studies provided data on physical status (See Additional file 2) [21, 23, 27, 32, 37, 43, 44, 48, 50], using mostly clinical tests, for example hand grip strength (n = 5) [21, 23, 27, 43, 44], ability to stand from a chair (n = 5) [21, 23, 37, 44, 48], and gait speed (n = 3) [23, 48]. The other tests were standing balance (n = 1) [21], a physical activity index based on the daily energy expenditure (kcal/kg/day) in the past 3 months (n = 1) [50] and the International Physical Activity Questionnaire (IPAQ) (n = 1) [32]. The results indicated that 32% [21] to 85% [23] of individuals over 90 could not stand up from a chair, and 19 [21] to 47% [23] could stand without the use of their arms. The overall mean grip strength (kilograms) was 14.5 (SD: 6.8) [43] to 16.1 (SD: 6.6) [23]; 10.85 for women and 16.29 for men [27]. Of the study population, 12.9% [21] to 15% [23] could not walk 4 m. A low level of physical activity was found in more than half of the study population.

Discussion

Commentary on results

Of 3086 references, we included 35 studies in our systematic review aiming to characterize the oldest old. The cognitive status was the most explored function (25/35), followed by functional status (19/35), nutritional status (13/35) and physical status (9/35).

The tests chosen for geriatric assessment were common tests used in most countries. However, there was a considerable variability in the tools used to assess each dimension with 3 tools for cognition (mostly represented by the Mini Mental State Evaluation), 6 for nutritional and physical status, and 9 for functional status. Such variability in the tests used in each of the 4 explored dimensions could bring variability in our results. We know for example that the prevalence of impairment may depend of the test used [53, 54]. The nutritional status was mainly described by BMI, whereas MNA-SF may be more accurate [55]. It could have been interesting to verify if sensitivity and specificity were identical when they were used for people aged 90 and over [56,57,58]. This gives rise to the need for a standardization in the assessments performed.

It has been demonstrated that some outcomes are associated with gender, in particular nutritional status (being female and unmarried determines poor nutritional status) [59] or physical status (difference in the mean hand grip strength, or mean gait speed) [60]. For those outcomes, we distinguished separate results for men and women if possible. Data were particularly different regarding physical outcomes, with lower performance in women.

Only four studies provided data on the four dimensions explored. Longitudinal and cohort studies appeared to focus mostly on cognitive and functional status. This limited the ability to provide several global evaluations of a sample of oldest old and to allow comparison between geographic areas for example.

For the studies with participants living at home and living in a nursing home, there was no information about the proportion of people living at home vs living in a nursing home. We cannot distinguish those 2 populations.

Cognitive impairment or functional disability was found half of the time. Nutritional status was abnormal for one quarter of the population. Physical status was abnormal for a third to half of the participants.

Our results indicated that individuals over 90 appeared as a heterogeneous population regarding cognitive, functional, physical, and nutritional status. Therefore, primary health care professionals may receive a range of patients, from those with preserved functions to those with dementia or a physical disability. Globally, the proportion of the oldest old with preserved functions is known. These findings are in line with forecasted trends for disabilities [61, 62].

Comparison with younger elderly

Comparison with individual aged 65 and over

The prevalence of cognitive impairment (dementia excepted) appeared lower for individuals aged 65 and over [63, 64]. The nutritional status was comparable between populations of individuals aged 65 and over and individuals aged 90 and over [65]. Functional status was better among individuals aged 65 and over [66]. Hand grip strength decreased with age [67, 68], explaining a lower score in our result, in favor of higher prevalence of sarcopenia (See Additional file 3).

Comparison with frail individuals aged 65 and over

In a “younger” sample of 1108 frail individuals, cognitive function seemed higher [69]. Functional status was preserved while nutritional and physical status were altered but in a lower proportion compared to our results [69] (See Additional file 3).

The results of our review seem in a continuum with the data for individuals aged 65 and over [70].

What are the implications for prevention and care for the oldest old?

Care plans for individuals need to take into account functions that can be preserved or maintained, as well as any disability already observed. A global evaluation would be helpful, such as the Comprehensive Geriatric Assessment recommended by the British Geriatrics Society for frail older people [71, 72], which includes a physical, psychological, and social assessment, from which a list of areas of need can be used to generate a care plan aimed at maintaining autonomy [73]. Person-centered care, after a global evaluation, and with efficient communication between all professionals, could improve healthcare quality and coordination, and thus, improve quality of life [71, 74,75,76,77,78,79].

As we have seen, there is more likely a continuum in the alteration of functions than a rupture with age. The solution may be to propose a care plan based on a global geriatric assessment earlier in the ageing trajectory to provide better maintenance of functions and autonomy among the oldest old in the future.

For the current population of oldest old, the implementation of such a care plan raises the question of its feasibility. The assessment of older patients is carried out in some geriatric day hospitals, especially for complex cases. New organizations for a geriatric assessment are proposed, to allow its realization in primary care [80, 81]. The geriatric assessment could be realized for example by a trained nurse in the patient’s home or in multi-professional primary care health centers with good results [82].

Which interventions could be proposed?

Different interventions have been proposed to prevent cognitive dysfunction or disability [83,84,85]. These interventions are focused on cardiovascular disease management (e.g. nutrition, physical activity, and cognitive training) and oral supplementation (e.g. omega-3 for example) for individuals aged 60 or 70 and over. The benefits of such programs have to be studied for this specific population. The interventions showing a positive effect on preservation of function may have to be adapted to the physiopathological characteristics of the oldest old. A new approach should also be designed as suggested by Tischa et al. “the establishment of collaborative networks between clinicians and designers, academia and industry is required to advance design for autonomous ageing” [86].

Strengths and limitations

Our study is the first to synthetize data relative to global descriptions of the oldest old. The studies included in this review are representative of the target population due to the decision to include older people living at home and in nursing homes, including those with loss of mobility. Data collection was generally performed in participants’ homes. This permitted the inclusion of individuals with mobility difficulties, and thus made samples more representative of the target population.

Our findings should be interpreted in light of several limitations. First, the studies included were from Western countries, with only four Asian studies and none from Africa, limiting the generalizability of findings. Second, when applicable, we used data from the base line and not from longitudinal surveys. This choice was made to prevent bias in longitudinal studies introduced by differential dropout [87]. Third, the NOS used to assess quality has been previously used in studies [88, 89] but not strictly methodologically validated. As far as we know, no other scale was available or recommended for cross sectional studies. Lastly, we decided to focus on 4 major dimensions, which are the most studied and have been used in intervention. It could have been interesting to complete with social, psychological, neurosensorial outcomes.

Conclusion

These results suggest a heterogeneous population with a certain proportion of oldest old with preserved functions. It could encourage a specific approach in the care of the oldest old in order to prevent disability. These findings may inform an adaptation of health care services to address global and comprehensive care. This approach involves a better characterization of the population. Future research should evaluate interventions specific to this population.

Availability of data and materials

Additional file 1 provides the search strategies applied to Medline, Cochrane Library, Pascal, and Web of Science; additional file 2 provides the characteristics of included studies; additional file 3 provides a comparison between individuals aged 65 and over, frail individuals aged 65 and over, and individuals aged 90 and over regarding cognitive, functional, nutritional and physical status. The datasets generated during this study (i.e. quality score assessment) are available on reasonable request.

Abbreviations

MMSE:

Mini Mental State Evaluation

ADL:

Activities of Daily Living

IADL:

Instrumental Activities of Daily Living

BMI:

Body Mass Index

References

  1. Cire B. World’s older population grows dramatically: NIH-funded Census Bureau report offers details of global aging phenomenon. US Department of Health & Human Services 2016. https://www.nih.gov/news-events/news-releases/worlds-older-population-grows-dramatically. Accessed December 21, 2019.

    Google Scholar 

  2. Hoffmann R, Kröger H, Pakpahan E. Health inequalities and the interplay of socioeconomic factors and health in the life course. In: Meloni M, Cromby J, Fitzgerald D, Lloyd S, editors. The Palgrave handbook of biology and society. London: Palgrave Macmillan; 2018.

    Google Scholar 

  3. Cesari F, Sofi F, Molino Lova R, et al. Aging process, adherence to Mediterranean diet and nutritional status in a large cohort of nonagenarians: effects on endothelial progenitor cells. Nutr Metab Cardiovasc Dis. 2018;28(1):84–90.

    Article  CAS  PubMed  Google Scholar 

  4. Bosworth B. Increasing disparities in mortality by socioeconomic status. Annu Rev Public Health. 2018;39:237–51.

    Article  PubMed  Google Scholar 

  5. Villa F, Ferrario A, Puca AA. Genetic signatures of centenarians. In: Caruso C, editor. Centenarians. Cham: Springer; 2019.

    Google Scholar 

  6. Huang Y, Yim OS, Lai PS, et al. Successful aging, cognitive function, socioeconomic status, and leukocyte telomere length. Psychoneuroendocrinology. 2019;103:180–7.

    Article  PubMed  Google Scholar 

  7. Legdeur N, Visser PJ, Woodworth DC, et al. White matter Hyperintensities and hippocampal atrophy in relation to cognition: the 90+ study. J Am Geriatr Soc. 2019;67(9):1827–34.

    Article  PubMed  PubMed Central  Google Scholar 

  8. Du Puy RS, Poortvliet RKE, Snel M, et al. Associations of elevated Antithyroperoxidase antibodies with thyroid function, survival, functioning, and depressive symptoms in the oldest old: the Leiden 85-plus study. Thyroid. 2019;29(9):1201–8.

    Article  CAS  PubMed  Google Scholar 

  9. Kauppi M, Raitanen J, Stenholm S, et al. Predictors of long-term care among nonagenarians: the vitality 90 + study with linked data of the care registers. Aging Clin Exp Res. 2018;30(8):913–9.

    Article  PubMed  Google Scholar 

  10. Mendonça N, Kingston A, Granic A, et al. Protein intake and transitions between frailty states and to death in very old adults: the Newcastle 85+ study. Age Ageing. 2019;49(1):32–8.

    Article  PubMed  PubMed Central  Google Scholar 

  11. Karppinen H, Laakkonen M-L, Strandberg TE, et al. Do you want to live to be 100? Answers from older people. Age Ageing. 2016;45(4):543–9.

    Article  PubMed  Google Scholar 

  12. Kingston A, Robinson L, Booth H, et al. Projections of multi-morbidity in the older population in England to 2035: estimates from the population ageing and care simulation (PACSim) model. Age Ageing. 2018;47(3):374–80.

    Article  PubMed  PubMed Central  Google Scholar 

  13. Rong C, Shen SH, Xiao LW, et al. A Comparative Study on the Health Status and Behavioral Lifestyle of Centenarians and Non-centenarians in Zhejiang Province, China-A Cross-Sectional Study. Front Public Health. 2019;22(7):344.

    Article  Google Scholar 

  14. Arosio B, Ferri E, Casati M, et al. The frailty index in centenarians and their offspring. Aging Clin Exp Res. 2019;31(11):1685–8.

    Article  PubMed  Google Scholar 

  15. Gimeno-Miguel A, Clerencia-Sierra M, Ioakeim I, et al. Health of Spanish centenarians: a cross-sectional study based on electronic health records. BMC Geriatr. 2019;19:226. https://doi.org/10.1186/s12877-019-1235-7.

  16. Liberati A, Altman DG, Tetzlaff J, et al. The PRISMA statement for reporting systematic reviews and meta-analyses of studies that evaluate health care interventions: explanation and elaboration. J Clin Epidemiol. 2009 Oct;62(10):e1–34.

    Article  PubMed  Google Scholar 

  17. Herzog R, Álvarez-Pasquin MJ, Díaz C, et al. Are healthcare workers’ intentions to vaccinate related to their knowledge, beliefs and attitudes? A systematic review. BMC Public Health. 2013;19(13):154.

    Article  Google Scholar 

  18. Berlau DJ, Corrada MM, Kawas C. The prevalence of disability in the oldest-old is high and continues to increase with age: findings from the 90+ study. Int J Geriatr Psychiatry. 2009;24(11):1217–25.

    Article  PubMed  PubMed Central  Google Scholar 

  19. Boeve B, McCormick J, Smith G, et al. Mild cognitive impairment in the oldest old. Neurology. 2003;60(3):477–80.

    Article  CAS  PubMed  Google Scholar 

  20. Bonaccorsi G, Santomauro F, Lorini C, et al. Risk of malnutrition in a sample of nonagenarians: specific versus classic bioelectrical impedance vector analysis. Nutr. 2016;32(3):368–74.

    Article  Google Scholar 

  21. Bullain SS, Corrada MM, Shah BA, et al. Poor physical performance and dementia in the oldest old: the 90+ study. JAMA Neurol. 2013;70(1):107–13.

    Article  PubMed  PubMed Central  Google Scholar 

  22. Cevenini E, Cotichini R, Stazi MA, et al. How to classify the oldest old according to their health status: a study on 1160 subjects belonging to 552 90+ Italian sib-ships characterized by familial longevity recruited within the GEHA EU project. Mech Ageing Dev. 2013;134(11–12):560–9.

    Article  PubMed  Google Scholar 

  23. 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 Lond Engl. 2013;382(9903):1507–13.

    Article  Google Scholar 

  24. Cimarolli VR, Jopp DS. Sensory impairments and their associations with functional disability in a sample of the oldest-old. Qual Life Res. 2014;23(7):1977–84.

    Article  PubMed  Google Scholar 

  25. Corrada MM, Berlau DJ, Kawas CH. A population-based clinicopathological study in the oldest-old: the 90+ study. Curr Alzheimer Res. 2012;9(6):709–17.

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  26. Dai T, Davey A, Woodard JL, et al. Sources of variation on the mini-mental state examination in a population-based sample of centenarians. J Am Geriatr Soc. 2013;61(8):1369–76.

    Article  PubMed  PubMed Central  Google Scholar 

  27. De Rango F, Montesanto A, Berardelli M, et al. To grow old in southern Italy: a comprehensive description of the old and oldest old in Calabria. Gerontology. 2011;57(4):327–34.

    Article  PubMed  Google Scholar 

  28. Formiga F, Ferrer A, Chivite D, et al. Predictors of long-term survival in nonagenarians: the NonaSantfeliu study. Age Ageing. 2011;40(1):111–6.

    Article  PubMed  Google Scholar 

  29. Hajek A, Lehnert T, Ernst A, et al. Prevalence and determinants of overweight and obesity in old age in Germany. BMC Geriatr. 2015;15:83.

    Article  PubMed  PubMed Central  Google Scholar 

  30. Hazra NC, Dregan A, Jackson S, et al. Differences in health at age 100 according to sex: population-based cohort study of centenarians using electronic health records. J Am Geriatr Soc. 2015;63(7):1331–7.

    Article  PubMed  PubMed Central  Google Scholar 

  31. Heeren TJ, Lagaay AM, Hijmans W, et al. Prevalence of dementia in the ‘oldest old’ of a Dutch community. J Am Geriatr Soc. 1991;39(8):755–9.

    Article  CAS  PubMed  Google Scholar 

  32. Herr M, Arvieu JJ, Robine JM, et al. Health, frailty and disability after ninety: results of an observational study in France. Arch Gerontol Geriatr. 2016;66:166–75.

    Article  CAS  PubMed  Google Scholar 

  33. Inagaki H, Gondo Y, Hirose N, et al. Cognitive function in Japanese centenarians according to the mini-mental state examination. Dement Geriatr Cogn Disord. 2009;28(1):6–12.

    Article  PubMed  Google Scholar 

  34. Ji L, Meng H, Dong B. Factors associated with poor nutritional status among the oldest-old. Clin Nutr. 2012;31(6):922–6.

    Article  PubMed  Google Scholar 

  35. Ji-Rong Y, Bi-Rong D, Chang-Quang H, et al. Cognitive impairment and depression among Chinese nonagenarians/centenarians. Am J Geriatr Psychiatry. 2010;18(4):297–304.

    Article  PubMed  Google Scholar 

  36. Kim H, Lee T, Lee S, et al. Factors associated with ADL and IADL dependency among Korean centenarians: reaching the 100-year-old life transition. Int J Aging Hum Dev. 2012;74(3):243–64.

    Article  PubMed  Google Scholar 

  37. Lisko I, Stenholm S, Raitanen J, et al. Association of Body Mass Index and waist circumference with physical functioning: the vitality 90+ study. J Gerontol A Biol Sci Med Sci. 2015;70(7):885–91.

    Article  PubMed  Google Scholar 

  38. Lisko I, Tiainen K, Raitanen J, et al. Body mass index and waist circumference as predictors of disability in nonagenarians: the vitality 90+ study. J Gerontol A Biol Sci Med Sci. 2017;72(11):1569–74.

    Article  PubMed  Google Scholar 

  39. Lucca U, Garrì M, Recchia A, et al. A population-based study of dementia in the oldest old: the Monzino 80-plus study. BMC Neurol. 2011;11:54.

    Article  PubMed  PubMed Central  Google Scholar 

  40. Lucca U, Tettamanti M, Logroscino G, et al. Prevalence of dementia in the oldest old: the Monzino 80-plus population based study. Alzheimers Dement. 2015;11(3):258–270.e3.

    Article  PubMed  Google Scholar 

  41. Martin P, Deshpande-Kamat N, Margrett JA, et al. Exceptional longevity: an introduction to the Iowa centenarian study. Int J Aging Hum Dev. 2012;75(4):297–316.

    Article  PubMed  Google Scholar 

  42. Molander L, Gustafson Y, Lövheim H. Low blood pressure is associated with cognitive impairment in very old people. Dement Geriatr Cogn Disord. 2010;29(4):335–41.

    Article  PubMed  Google Scholar 

  43. Montesanto A, De Rango F, Berardelli M, et al. Glomerular filtration rate in the elderly and in the oldest old: correlation with frailty and mortality. Age. 2014;36(3):9641.

    PubMed  PubMed Central  Google Scholar 

  44. Nybo H, Petersen HC, Gaist D, et al. Predictors of mortality in 2,249 nonagenarians - the Danish 1905-cohort survey. J Am Geriatr Soc. 2003;51(10):1365–73.

    Article  PubMed  Google Scholar 

  45. Peltz CB, Corrada MM, Berlau DJ, et al. Incidence of dementia in oldest-old with amnestic MCI and other cognitive impairments. Neurology. 2011;77(21):1906–12.

    Article  PubMed  PubMed Central  Google Scholar 

  46. Sachdev PS, Levitan C, Crawford J, et al. The Sydney centenarian study: methodology and profile of centenarians and near-centenarians. Int Psychogeriatr. 2013;25(6):993–1005.

    Article  PubMed  Google Scholar 

  47. Skoog J, Backman K, Ribbe M, et al. A longitudinal study of the mini-mental state examination in late nonagenarians and its relationship with dementia, mortality, and education. J Am Geriatr Soc. 2017;65(6):1296–300.

    Article  PubMed  Google Scholar 

  48. von Heideken WP, Gustafson Y, Lundin-Olsson L. Large variations in walking, standing up from a chair, and balance in women and men over 85 years: an observational study. Aust J Physiother. 2009;55(1):39–45.

    Article  Google Scholar 

  49. von Strauss E, Fratiglioni L, Viitanen M, et al. Morbidity and comorbidity in relation to functional status: a community-based study of the oldest old (90+ years). J Am Geriatr Soc. 2000;48(11):1462–9.

    Article  Google Scholar 

  50. Wister AV, Wanless D. A health profile of community-living nonagenarians in Canada. Can J Aging Rev Can Vieil. 2007;26(1):1–18.

    Article  Google Scholar 

  51. Xie J, Matthews FE, Jagger C, et al. The oldest old in England and Wales: a descriptive analysis based on the MRC cognitive function and ageing study. Age Ageing. 2008;37(4):396–402.

    Article  PubMed  PubMed Central  Google Scholar 

  52. Zeng Y, Feng Q, Hesketh T, et al. Improvements in survival and activities of daily living despite declines in physical and cognitive functioning among the oldest-old in China – Evidence from a cohort study. Lancet. 2017;389(10079):1619–29.

    Article  PubMed  PubMed Central  Google Scholar 

  53. Webster L, Groskreutz D, Grinbergs-Saull A, et al. Core outcome measures for interventions to prevent or slow the progress of dementia for people living with mild to moderate dementia: Systematic review and consensus recommendations. PLoS One. 2017;12(6):e0179521.

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  54. Senger J, Bruscato NM, Werle B, et al. Nutritional status and cognitive impairment among the very old in a community sample from southern Brazil. J Nutr Health Aging. 2019;23(10):923–9.

    Article  CAS  PubMed  Google Scholar 

  55. Koren-Hakim T, Weiss A, Hershkovitz A, et al. Comparing the adequacy of the MNA-SF, NRS-2002 and MUST nutritional tools in assessing malnutrition in hip fracture operated elderly patients. Clin Nutr. 2017;36(3):912.

    Article  PubMed  Google Scholar 

  56. Kahle-Wrobleski K, Corrada MM, Li B, et al. Sensitivity and specificity of the mini-mental state examination for identifying dementia in the oldest-old: the 90+ study. J Am Geriatr Soc. 2007;55(2):284–9.

    Article  PubMed  PubMed Central  Google Scholar 

  57. Arosio B, Ostan R, Mari D, et al. Cognitive status in the oldest old and centenarians: a condition crucial for quality of life methodologically difficult to assess. Mech Ageing Dev. 2017;165(Pt B):185–94.

    Article  PubMed  Google Scholar 

  58. Arnau A, Espaulella J, Méndez T, et al. Lower limb function and 10-year survival in population aged 75 years and older. Fam Pract. 2016;33(1):10–6.

    Article  PubMed  Google Scholar 

  59. Maseda A, Diego-Diez C, Lorenzo-López L, et al. Quality of life, functional impairment and social factors as determinants of nutritional status in older adults: the VERISAÚDE study. Clin Nutr. 2018;37(3):993–9.

    Article  PubMed  Google Scholar 

  60. Peel NM, Kuys SS, Klein K. Gait speed as a measure in geriatric assessment in clinical settings: a systematic review. Gerontol A Biol Sci Med Sci. 2013;68(1):39–46.

    Article  Google Scholar 

  61. Guzman-Castillo M, Ahmadi-Abhari S, Bandosz P, et al. Forecasted trends in disability and life expectancy in England and Wales up to 2025: a modelling study. Lancet Public Health. 2017;2(7):e307–13. https://doi.org/10.1016/S2468-2667(17)30091-9.

    Article  PubMed  PubMed Central  Google Scholar 

  62. Duffill MC. Disability Future Direections 2025 Demographic trends monograph. Demographic Trends and Implications for Disability Service Provision 2018. http://www.disability.wa.gov.au/Global/Publications/About%20us/Count%20me%20in/Research/demographic_trends.pdf. Accessed December 21, 2019.

    Google Scholar 

  63. Rao D, Luo X, Tang M, et al. Prevalence of mild cognitive impairment and its subtypes in community-dwelling residents aged 65 years or older in Guangzhou. China Arch Gerontol Geriatr. 2018;75:70–5.

    Article  PubMed  Google Scholar 

  64. Vega Alonso T, Miralles Espí M, Mangas Reina JM, et al. Prevalence of cognitive impairment in Spain: the Gómez de Caso study in health sentinel networks. Neurologia. 2018;33(8):491–8.

    Article  CAS  PubMed  Google Scholar 

  65. Kucukerdonmez O, Navruz Varli S, Koksal E. Comparison of nutritional status in the elderly according to living situations. J Nutr Health Aging. 2017;21(1):25–30.

    Article  CAS  PubMed  Google Scholar 

  66. Millán-Calenti JC, Tubío J, Pita-Fernández S, et al. Prevalence of functional disability in activities of daily living (ADL), instrumental activities of daily living (IADL) and associated factors, as predictors of morbidity and mortality. Arch Gerontol Geriatr. 2010;50(3):306–10.

    Article  PubMed  Google Scholar 

  67. Amaral CA, Amaral TLM, Monteiro GTR, et al. Hand grip strength: reference values for adults and elderly people of Rio Branco, acre, Brazil. PLoS One. 2019;14(1):e0211452.

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  68. Wearing J, Konings P, Stokes M, et al. Handgrip strength in old and oldest old Swiss adults – a cross-sectional study. BMC Geriatr. 2018;18:266.

    Article  PubMed  PubMed Central  Google Scholar 

  69. Tavassoli N, Guyonnet S. Abellan Van Kan G, et al. description of 1,108 older patients referred by their physician to the “geriatric frailty clinic (G.F.C) for assessment of frailty and prevention of disability” at the gerontopole. J Nutr Health Aging. 2014;18(5):457–64.

    Article  CAS  PubMed  Google Scholar 

  70. Cohen-Mansfield J, Shmotkin D, Blumstein Z, et al. The old, old-old, and the oldest old: continuation or distinct categories? An examination of the relationship between age and changes in health, function, and wellbeing. Int J Aging Hum Dev. 2013;77(1):37–57.

    Article  PubMed  Google Scholar 

  71. Turner G, Clegg A. Best practice guidelines for the management of frailty: a British geriatrics society, age UK and Royal College of general practitioners report. Age Ageing. 2014;43(6):744–7.

    Article  PubMed  Google Scholar 

  72. Parker SG, McCue P, Phelps K, et al. What is comprehensive geriatric assessment (CGA)? An umbrella review. Age Ageing. 2018;47(1):149–55.

    Article  CAS  PubMed  Google Scholar 

  73. British Geriatrics Society. CGA in Primary Care Settings. 2019. https://www.bgs.org.uk/sites/default/files/content/resources/files/2018-08-23/CGA%20in%20Primary%20Care%20Settings.pdf. Accessed December 21, .

    Google Scholar 

  74. Howard EP, Schreider R, Morris JN, et al. Collage 360: a model of person-centered care to promote health among older adults. J Ageing Res Health. 2016;1(1):21–30.

    Article  Google Scholar 

  75. Dann T. Global elderly care in crisis. Lancet. 2014;383(9921):927.

    Article  Google Scholar 

  76. Integrated care for older people. guidelines on community-level interventions to manage declines in intrinsic capacity: World Health Organization; 2017. http://apps.who.int/iris/bitstream/handle/10665/258981/9789241550109-eng.pdf;jsessionid=D63EA4C07713750553231AAE677974A5?sequence=1. Accessed December 21. 2019.

  77. Global health and aging. National Institutes of Health 2011. http://www.who.int/ageing/publications/global_health.pdf. Accessed December 21, 2019.

    Google Scholar 

  78. Home care: delivering personal care and practical support to older people living in their own homes. National Institute for Clinical Excellence 2015. https://www.nice.org.uk/guidance/ng21. Accessed December 21, 2019.

    Google Scholar 

  79. Preventive care and healthy ageing: a global perspective. Observatoire international de la santé et services sociaux - MSSS 2013 http://www.msss.gouv.qc.ca/ministere/observatoiresss/index.php?preventive-care-and-healthy-ageing-a-global-perspective. Accessed December 21, 2019.

    Google Scholar 

  80. Garrard JW, Cox NJ, Dodds RM, Roberts HC, Sayer AA. Comprehensive geriatric assessment in primary care: a systematic review. Aging Clin Exp Res. 2020;32(2):197–205. https://doi.org/10.1007/s40520-019-01183-w. Epub 2019 Apr 9.

  81. Chadborn NH, Goodman C, Zubair M, et al. Role of comprehensive geriatric assessment in healthcare of older people in UK care homes: realist review. BMJ Open. 2019;9(4):e026921.

    Article  PubMed  PubMed Central  Google Scholar 

  82. Fougère B, Oustric S, Delrieu J, et al. Implementing assessment of cognitive function and frailty into primary care: data from frailty and Alzheimer disease prevention into primary care (FAP) study pilot. J Am Med Dir Assoc. 2017;18(1):47–52.

    Article  PubMed  Google Scholar 

  83. Vellas B, Carrie I, Gillette-Guyonnet S, et al. MAPT study: a multidomain approach for preventing Alzheimer’s disease: design and baseline data. J Prev Alzheimers Dis. 2014;1(1):13–22.

    CAS  PubMed  PubMed Central  Google Scholar 

  84. Barbera M, Mangialasche F, Jongstra S, et al. Designing an internet-based multidomain intervention for the prevention of cardiovascular disease and cognitive impairment in older adults: the HATICE trial. J Alzheimers Dis JAD. 2018;62(2):649–63.

    Article  PubMed  Google Scholar 

  85. Rosenberg A, Ngandu T, Rusanen M, et al. Multidomain lifestyle intervention benefits a large elderly population at risk for cognitive decline and dementia regardless of baseline characteristics: the FINGER trial. Alzheimers Dement J Alzheimers Assoc. 2018;14(3):263–70.

    Article  Google Scholar 

  86. van der Cammen TJM, Albayrak A, Voûte E, et al. New horizons in design for autonomous ageing. Age Ageing. 2017;46(1):11–7.

    PubMed  Google Scholar 

  87. Chatfield MD, Brayne CE, Matthews FE. A systematic literature review of attrition between waves in longitudinal studies in the elderly shows a consistent pattern of dropout between differing studies. J Clin Epidemiol. 2005;58(1):13–9.

    Article  PubMed  Google Scholar 

  88. Masefield SC, Prady SL, Sheldon TA, et al. The Caregiver Health Effects of Caring for Young Children with Developmental Disabilities: A Meta-analysis. Matern Child Health J. 2020. https://doi.org/10.1007/s10995-020-02896-5. [Epub ahead of print].

  89. Bremer D, Inhestern L, von dem Knesebeck O. Social relationships and physician utilization among older adults-a systematic review. PLoS One. 2017;12(9):e0185672.

    Article  CAS  PubMed  PubMed Central  Google Scholar 

Download references

Acknowledgements

The authors are grateful to Pr Herve Maisonneuve, for assistance with the redaction of this study.

Funding

None.

Author information

Authors and Affiliations

  1. Département Universitaire de Médecine Générale, Faculté de Médecine Rangueil, Université Paul Sabatier Toulouse III, Toulouse, France

    Emile Escourrou, Florence Durrieu, Bruno Chicoulaa, Julie Dupouy & Stéphane Oustric

  2. UMR 1027 INSERM, Université Paul Sabatier Toulouse III, Toulouse, France

    Emile Escourrou, Julie Dupouy, Stéphane Oustric, Sandrine Andrieu & Virginie Gardette

  3. Maison de Santé Pluri Professionnelle Universitaire La Providence, 1 avenue Louis Blériot, 31500, Toulouse, France

    Emile Escourrou & Stéphane Oustric

  4. Service d’épidémiologie, Centre Hospitalier Universitaire de Toulouse, Toulouse, France

    Sandrine Andrieu & Virginie Gardette

Authors
  1. Emile Escourrou
    View author publications

    You can also search for this author in PubMed Google Scholar

  2. Florence Durrieu
    View author publications

    You can also search for this author in PubMed Google Scholar

  3. Bruno Chicoulaa
    View author publications

    You can also search for this author in PubMed Google Scholar

  4. Julie Dupouy
    View author publications

    You can also search for this author in PubMed Google Scholar

  5. Stéphane Oustric
    View author publications

    You can also search for this author in PubMed Google Scholar

  6. Sandrine Andrieu
    View author publications

    You can also search for this author in PubMed Google Scholar

  7. Virginie Gardette
    View author publications

    You can also search for this author in PubMed Google Scholar

Contributions

EE and FD contributed substantially to the conception, design, analysis, and interpretation of the data with critical guidance from the SO, SA, and VG. JD and BC assisted EE and FD with the design of the search strategies. All the authors have revised the manuscript critically for intellectual content. All authors have seen and approved the final content and agreed to be accountable for all aspects of the work.

Corresponding author

Correspondence to Emile Escourrou.

Ethics declarations

Ethics approval and consent to participate

Not applicable.

Consent for publication

Not applicable.

Competing interests

The authors declare that they have no competing interests.

Additional information

Publisher’s Note

Springer Nature remains neutral with regard to jurisdictional claims in published maps and institutional affiliations.

Supplementary information

Additional file 1.

Different queries.

Additional file 2.

Characteristics of included studies (ordered by continent (more represented by number of studies) and by dates in chronological order).

Additional file 3.

Comparison between individuals aged 65 and over, frail individuals aged 65 and over, and individuals aged 90 and over regarding cognitive, functional, nutritional and physical status.

Rights and permissions

Open Access This article is licensed under a Creative Commons Attribution 4.0 International License, which permits use, sharing, adaptation, distribution and reproduction in any medium or format, as long as you give appropriate credit to the original author(s) and the source, provide a link to the Creative Commons licence, and indicate if changes were made. The images or other third party material in this article are included in the article's Creative Commons licence, unless indicated otherwise in a credit line to the material. If material is not included in the article's Creative Commons licence and your intended use is not permitted by statutory regulation or exceeds the permitted use, you will need to obtain permission directly from the copyright holder. To view a copy of this licence, visit http://creativecommons.org/licenses/by/4.0/. The Creative Commons Public Domain Dedication waiver (http://creativecommons.org/publicdomain/zero/1.0/) applies to the data made available in this article, unless otherwise stated in a credit line to the data.

Reprints and permissions

About this article

Check for updates. Verify currency and authenticity via CrossMark

Cite this article

Escourrou, E., Durrieu, F., Chicoulaa, B. et al. Cognitive, functional, physical, and nutritional status of the oldest old encountered in primary care: a systematic review. BMC Fam Pract 21, 58 (2020). https://doi.org/10.1186/s12875-020-01128-7

Download citation

  • Received:

  • Accepted:

  • Published:

  • DOI: https://doi.org/10.1186/s12875-020-01128-7

Keywords

BMC Primary Care

ISSN: 2731-4553

Contact us