Predominant Objective Cognitive Function Groups and their Association with Risk Factors in Older Adults: Cross-Sectional Study

  

    
 
    
M-1
    
M-2
    
M-3
  
  

    
Presence of factors
    
Major-NCD
    
Minor-NCD=70
    
Minor-NCD<70
    
Major-NCD
    
Minor-NCD=70
    
Minor-NCD<70
    
Major-NCD
    
Minor-NCD=70
    
Minor-NCD<70
  
  

    
Sociodemographic
    
 
    
 
    
 
    
 
    
 
    
 
    
 
    
 
    
 
  
  

    
Marital status (married)
    
1.18 (0.39-3.49)
    
0.62 (0.30-1.29)
    
0.47 (0.22-1.04)
    
1.02 (0.29-3.54)
    
0.55 (0.26-1.19)
    
0.34    (0.14-0.79)
    
0.55 (0.12-2.47)
    
0.39    (0.16-0.92)
    
0.27    (0.10-0.74)
  
  

    
Unqualifiedwork
    
1.20    (0.95-1.53)
    
1.19    (1.01-1.39)
    
1.05 (0.89-1.25)
    
1.24 (0.94-1.62)
    
1.20    (1.01-1.42)
    
1.07 (0.89 1.29)
    
1.32 (0.96-1.81)
    
1.17    (1.00-1.39)
    
1.04 (0.85-1.27)
  
  

    
Living alone
    
6.65    (1.56-28.23)
    
5.66    (1.85-17.32)
    
1.19 (0.31-4.49)
    
3.21 (0.51-19.96)
    
5.21    (1.60-16.98)
    
2.08 (0.46 9.30)
    
7.58 (0.78-72.92)
    
6.01 (1.71-21.19)
    
3.38 (0.60-19.05)
  
  

    
Lifestyle
    
 
    
 
    
 
    
 
    
 
    
 
    
 
    
 
    
 
  
  

    
Smoking
    
0.56 (0.17-1.81)
    
0.70 (0.34-1.45)
    
0.20 (0.08-0.48)
    
0.81 (0.19-3.33)
    
0.69 (0.32-1.51)
    
0.23 (0.09 0.58)
    
1.23 (0.21-7.05)
    
0.82 (0.36-1.87)
    
0.27 (0.09-0.99)
  
  

    
Alcoholism
    
0.61 (0.15-2.54)
    
0.65 (0.29-1.45)
    
0.66 (0.25-1.73)
    
0.42 (0.08-2.22)
    
0.61 (0.26-1.42)
    
0.59 (0.21 1.70)
    
1.03 (0.15-6.79)
    
0.74 (0.30-1.78)
    
0.56 (0.18-1.75)
  
  

    
Physicalactivity
    
0.10    (0.03-0.31)
    
0.29    (0.13-0.66)
    
0.04    (0.01-0.9)
    
0.07    (0.02-0.31)
    
0.30    (0.12-0.75)
    
0.06    (0.03 0.15)
    
0.08    (0.01-0.42)
    
0.18    (0.05-0.57)
    
0.05    (0.01-0.13)
  
  

    
Comorbidity
  
  

    
Type 2 diabetes mellitus
    
 
    
 
    
 
    
1.19 (0.33-4.32)
    
0.70 (0.28-1.74)
    
2.77    (1.18-6.49)
    
2.32 (0.48-11.22)
    
0.62 (0.24-1.60)
    
3.31    (1.28-8.49)
  
  

    
High bloodpressure
    
 
    
 
    
 
    
3.00 (0.77-11.63)
    
2.00 (0.92-4.34)
    
1.57 (0.66-3.72)
    
2.05 (0.42-9.84)
    
1.52 (0.66-3.48)
    
1.50 (0.60-3.73)
  
  

    
Dyslipidemia
    
 
    
 
    
 
    
0.47 (0.11-1.97)
    
0.60 (0.27-1.31)
    
1.16 (0.51-2.65)
    
0.32 (0.06-1.68)
    
0.66 (0.29-1.49)
    
0.97 (0.38-2.47)
  
  

    
Obesity
    
 
    
 
    
 
    
0.45 (0.10-1.87)
    
1.10 (0.48-2.52)
    
1.10 (0.46-2.66
    
0.55 (0.10-2.86)
    
1.43 (0.58-3.53)
    
1.81 (0.66-4.96)
  
  

    
Heartdisease
    
 
    
 
    
 
    
3.34 (0.92-12.08)
    
2.16 (0.93-4.98)
    
2.17 (0.92-5.12)
    
3.37 (0.71-15.87)
    
2.44 (1.00-5.97)
    
2.21 (0.88-5.58)
  
  

    
Chronicobstructivepulmonarydisease
    
 
    
 
    
 
    
1.61 (0.24-10.77)
    
1.85 (0.59-5.80)
    
0.58 (0.10-3.93)
    
1.39 (0.14-13.30)
    
2.01 (0.62-6.48)
    
0.53 (0.09-2.95)
  
  

    
Hypothyroidism
    
 
    
 
    
 
    
7.76 (0.06-1021.3)
    
3.43 (0.15-74.57)
    
3.91(0.08-171.3)
    
6.72 (0.32-1418.3)
    
2.04 (0.05-76.01)
    
2.57(0.08-80.0)
  
  

    
Depression
    
 
    
 
    
 
    
1.62 (0.34-7.60)
    
1.16 (0.45-3.00)
    
0.26 (0.07-0.96)
    
1.27 (0.37-4.35)
    
1.18 (0.95-1.31)
    
0.30 (0.06-1.37)
  
  

    
Motor    functionality
    
 
    
 
    
 
    
 
    
 
    
 
    
 
    
 
  
  

    
Gaitspeed (m/s)
    
 
    
 
    
 
    
 
    
 
    
 
    
1.17 (0.92-1.51)
    
0.93 (0.87-1.00)
    
1.15 (0.88-1.50)
  
  

    
Gripstrength (kg)
    
 
    
 
    
 
    
 
    
 
    
 
    
0.81    (0.71-0.93)
    
0.93    (0.87-0.98)
    
0.99 (0.93-1.05)
  
  

    
Frailty
    
 
    
 
    
 
    
 
    
 
    
 
    
0.58 (0.09-3.58)
    
0.52 (0.13-1.98)
    
0.01 (0.002-0.99)
  
  

    
Katz Index of Independence in Activities of Daily    Living
    
 
    
 
    
 
    
 
    
 
    
 
    
1.14 (0.23-5.57)
    
0.41 (0.14-1.59)
    
1.18 (0.41-3.43)
  
  

    
Likelihood
    
91.74
    
192.88
    
185.36
    
81.43
    
183.34
    
168.64
    
65.92
    
171.78
    
152.37
  
  

    
NCD: NeuroCognitive Disorder

      =70: Adults 70 years old or older 

      < 70: Adults younger than 70 years 

      M-1: Model 1 evaluates sociodemographic factors and    lifestyle in the three groups with any NCD severity compared with the group    without NCD.

      M-2: Model 2 evaluates the variables included in    model 1 plus comorbidity factors in the three groups with any NCD severity    compared with the group without NCD.

      M-3: Model 3 evaluates    the variables included in Model 2 plus motor functionality variables in the    three groups with any NCD severity compared with the group without NCD. 
  

Table 4: The exploratory multivariate analysis of the association among risk factors and patterns of objective cognitive function in older adults.

In Model 2, where comorbidity variables were added, in the major-NCD group, sociodemographic and lifestyle factors were no longer statistically significant risk factors, but physical activity remained as a protective factor. In minor–NCD >70 years group, unqualified work and living alone remained as risk factors and, similarly to Model 1 and in the previous group, physical activity remained as protection factor. For minor-NCD <70 years group, comorbidity DM2 was a risk factor, in addition to physical activity, marital status married was associated as a protection factor.

In Model 3, the motor functionality variables were added to the previous model; in major NCD group, there were no longer statistical association with risk factors, but physical activity and grip strength remained as a protection factor. Minor–NCD ≥70 years group preserved the association with the sociodemographic unqualified work, living alone as risk factors, but heart disease was added as a risk factor. In the same group marital status married was added as protection factor and physical activity continued with its beneficial effect. Finally, Minor-NCD <70 years group remained with the same associated factors as Model 2.

Regarding the likelihood values of the exploratory multivariate analysis models, major-NCD had the lowest similarity values among the other groups, while the minor-NCD <70 years group and the minor-NCD≥70 years group had the highest values; that is, the factors highly explain the screening stratification of minor-NCD ≥ 70 years group and minor-NCD <70 years group, compared with the without-NCD group.

Discussion

Key Results

This study shows evidence of the association among the POCFG and the risk and protective factors from sociodemographic, lifestyle, comorbidity, and motor function variables in OA living in the community. This is relevant because those factors can be affordable, fast and easily identified. Present epidemiological approach considered the characterization of the POCFG groups by the following: i) subjective and objective cognitive function, age, sex and level of education, ii) risk factors and iii) likelihood.

Those factors can provide information for community risk, and interventions aimed at preventing dementia on a large scale. The usefulness of present factors to characterize patterns and validate them will also make it possible to identify groups at risk of dementia in whom prevention is still possible.

The limitations of the study were that other known lifestyle factors such as sleep patterns and diet were not evaluated, as well as aspects of anxiety and stress. Regarding objective cognitive function, neuropsychological tests were not evaluated.

Interpretation and Generalizability

The cluster analysis allowed characterize four groups, which had a similar proportion to the reported clinical groups to dementia and MCI. The other major-NCD group (8.5%) had a proportion within the published range for dementia in Latin America (4.4%-8.4%) and Mexico [8.4%] [1]. Regarding the two groups with MCI, one of them was older than 70 years (minor-NCD >70) and their proportion was 18.8%, a figure contained within the worldwide range prevalence of MCI [6%-30%] [21]. Other group with MCI but younger than 70 years (minor NCD<70), presented the highest number of comorbidities and represented a higher proportion of the sample with SMC (71.1%) compared to other reported [21].

Age, Sex, and Socioeconomic Level

In this study of the exploration of grouping the predominant objective cognitive function in OA living in the community; it was essential to include factors such as age, sex and level of education for the differentiation and characterization of the groups.

Moreover, comorbidity and age are independent factors of increased vascular risk, mainly due to cerebrovascular disease and neurodegenerative processes [22,23]. The risk of dementia in younger adults due to vascular risk is associated with the presence of comorbidities such as diabetes mellitus, hypertension, obesity, heart disease, etc. [23]. In present study, it was possible to discriminate two groups by age the minor NCD <70 years and minor-NCD ≥70 years.

From a sex perspective, in women, in addition to neurodegeneration, the stress factor is added, as well as a high level of smoking, which are factors that affect their cardiovascular health, causing problems such as coronary disease or heart failure [23]. In men, the risk is more related to a history of neurodegeneration such as cerebrovascular disease, Parkinson's, depressive disorders, or hypertension [23]. For this study, there were a higher proportion of women attended in the primary care units, and it is documented that women are the ones who most demand health services [24]. Despite of this, women presented higher proportion of patterns of lower cognitive function.

Low level of education is a risk factor for dementia that occurs at an early age [6]. The method for grouping or classification by similarities by cluster has been used in research for the study of dementia prognosis, which has provided more precise results when risk factors are included [25,22]. In this study, the following facts were distinguished: i) a group of people with an average age of 70 years, a high level of education, and normal global cognitive function. It is possible that this group has a higher cognitive reserve, where more years of education and holding an occupation are protective factors for dementia.

This may compensate for possible brain damage frequently related to aging, so this group has been considered a reference. The group of OA with an average age of 77 years had the lowest educational level and low-global cognitive function. Due to these characteristics, a dementia pattern was considered, either due to vascular or neurodegenerative pathology related to aging [26]. iii) Two groups with MCI, where one had an average age of 73 years and low schooling, and the second group, the youngest with an average age of 63 years and an education of 11 years. In these last two groups, the first could be explained by age, with biological ageing, and the second by living with pathological changes related to chronic diseases and/or fasting pathological ageing.

SCM was another characteristic that was considered in the grouping, and contrasting them with a group with normal cognitive function without SCM. In prospective studies, it has been reported that people with SCM have a 14% chance of MCI [16] and a 27%-30% chance of dementia [16] a while the risk of MCI is two to three times higher [23] and the risk for dementia 7-20 times higher. In our study, the minor-NCD <70 group showed the highest proportion of SCM; this could be associated with the previously mentioned high comorbidity. More important is to point out the younger average age in minor-NCD <70 with respect to normal global cognitive function group, which emits a signal of dementia risk in the following years and is a group in whom effective interventions should be initiated to prevent this condition.

In present study, the MMSE score was able to distinguish the population whit dementia (MMSE=21.2), but not for people with mild cognitive impairment, since the values were in the reference range (minor NCD>70=26 and minor NCD<70=28). In contrast, the evaluation of cognitive function with MoCA, a screening test that evaluates the cognitive domains, it was possible to distinguish the alteration between memory and other domains in the groups with MCI, due to their low levels.

Association with Lifestyle Factors, Comorbidity and Motor Functionality

Modern life is a context that is often antagonistic or risky to the health and quality of life of OA, given that they are exposed to conditions such as poor diets, barriers to physical activity, exposure to smoking, conditions of social isolation and discomfort for restful sleep [5], known risk factors for dementia due to inadequate lifestyles.

This situation favors the consumption of inappropriate foods, increased smoking, physical inactivity and depression, which generates a vicious circle against healthy ageing [27].

In contrast, positive or healthy lifestyle factors have been related to more functional ageing, because most of them allow metabolic control and avoiding weight gain. In studies where interventions have been carried out to implement healthy lifestyles, it has been verified that these interventions give off emotions of happiness and favor social networks; both show long-range of health multiplier effects with successful ageing; that is, with less cognitive impairment and greater functionality-independence [27,28].

Physical activity is not only a protector against dementia, but it can also resolve or mitigate multiple diseases [29,30]. In this study, physical activity was a protective factor for any group with impaired cognitive function. In present study, was remarkable the high frequency of inactivity in the minor-NCD <70 group; therefore, its implementation is fundamental in the prevention in early stages of dementia.

Other factors studied related to global cognitive function were slower walking speed and decreased grip strength. Both were related to early symptoms of dementia, possible due to cognitive-motor impairment [31]. In our analysis, it was impossible to relate the decrease in gait speed with belonging to any group formed, but the higher grip strength was a protection factor in the major and minor NCD>70 groups. It is likely that these subjects, although have low values of cognitive function, may be still in preclinical stages because there is a relationship between lower gait speed and decreased grip strength (as determinants of physical frailty, sarcopenia, and cognitive impairment and dementia).

Likelihood of Lifestyle Factors

In our study, saturated multivariate models were made to obtain the likelihood values, where the minor NCD>70 group had higher likelihood values with significance in sociodemographic factors (age, sex and level of education), lifestyle and functionality. A relevant fact is that it was a group in which comorbidity does not explain cognitive function; it is possible that the OA in this group are survivors of chronic diseases.

The minor-NCD <70 group had slightly lower likelihood values than the minor-NCD <70, since comorbidity was a more important factor than sociodemographic factors, lifestyle and functionality. The modifiable preventive factors derived from present analysis may be improved in OA with the multidisciplinary participation of the family doctor, dentistry, social work, geriatrics, and nursing. The group with the lowest likelihood values was the one with possibly dementia cognitive function, probably this group contains a higher genetic load for dementia [6].

The risk factors for dementia found in the lifestyles of our sample are low education, high blood pressure, social isolation, physical inactivity and DM. These are factors that can impact in the prevention of dementias, since the probability of reducing the incidence up to 40%, has been reported [6].

Association studies between lifestyle factors and cognitive function are important in public health because they allow estimating possible actions to prevent dementia, point out specific groups for possible specific interventions, favor times of greater opportunity or impact, and they focus on areas of greater preventive opportunity [32].

Changes from negative to healthy lifestyles are alternatives for preventing modifiable risk factors for dementia [32]. Additionally, they are optimal interventions with high public impact in low- and middle-income countries [4].

The programs must be adjusted to the general health of the older persons with surveillance measures by qualified personnel, preferably in collective activities, which favor their health by avoiding isolation and depression [29]. Physical activity is a factor highly related to improvements in nutrition, socialization, sleep and emotional well-being [29,32].

Longitudinal studies of these patterns will be future investigations allowing a better understanding of the participation of lifestyle factors and dementia, as well as the investigation of prognostic clinical characteristics and biomarkers at the population level.

Conclusions

There was an association between lifestyle, comorbidity, protective motor function as risk factors with the predominant Objective Cognitive Function Groups.

List of Abbreviations

Activities of daily life: ADL; Body mass index: BMI; Diabetes mellitus: DM2; Diagnostic and Statistical Manual of Mental Disorders, Fifth Edition: DSM-5; Geriatric depression Scale of Yessavage: GDS-15; Mild cognitive impairment: MCI; Mini-Mental State Examination: MMSE; Montreal Cognitive Assessment: MoCA; NeuroCognitive Disorder: NCD; Odds ratio: OR; Older adults: OA; Predominant Objective Cognitive Function Groups: POCFG; Subjective memory complaint: SCM.

Supplementary Information

Additional file 1: Supporting information Table 1: Checklist for reports of observational studies STROBE Statement.

Ethics Approval and Consent to Participate

Registered with the National Commission for Scientific Research: 2018-785-0958.

Competing Interests

The researchers listed below declare that there is no conflict of interest in conducting this research protocol.

Funding

The study was conducted in collaboration with the Faculty of Medicine of the National Autonomous University of Mexico (UNAM) and the Epidemiological and Health Services Research Unit, Centro Medico Nacional Siglo XXI, Instituto Mexicano del Seguro Social (IMSS), and the researchers provided the human and financial resources.

Acknowledgements

Autonomous University of Mexico (UNAM) for providing the funds to make publication possible.

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