Type 2 Diabetes Mellitus (T2DM) is a metabolic disease associated with modifiable and non-modifiable risk factors (International Diabetes Federation, 2015). Regarding non-modifiable factors, there is clear evidence that certain ethnic groups are at increased risk for developing T2DM (Centers for Disease Control and Prevention, 2017). Latin-Americans have a higher prevalence of T2DM than Caucasian people (Centers for Disease Control and Prevention, 2017), have a higher risk, almost twice, of developing T2DM (American Diabetes Association, 2022) and show high levels of disease burden and complications such as higher rates of kidney failure, diabetes-related vision loss and blindness (Centers for Disease Control and Prevention, 2022). In Chile, the prevalence of T2DM reaches 12.3% of the general population and 30.6% of people 65 years or over (Miniesterio de Salud de Chile, 2017), placing it in second place of South America (International Diabetes Federation, 2015) and in 5th place among all OECD countries (Organisation for Economic Cooperation and Development, 2011).

Public awareness of T2DM is mainly restricted to medical complications such as microvascular, macrovascular, and non-vascular complications (American Diabetes Association, 2022). However, there are critical cognitive aspects that need increased attention. Multiple studies have demonstrated the existence of an association between T2DM and Cognitive Impairment (CI), which are presented in a continuum ranging (Bozanic et al., 2019) from subtle cognitive decreases associated with T2DM (Koekkoek et al., 2015), cognitive decline (Biessels and Despa, 2018), Mild Cognitive Impairment (MCI) (Roberts et al., 2014) to dementia (Cheng et al., 2012). The CI with T2DM has been described as a decrease in cognitive performance in specific domains such as verbal and visual memory, attention and concentration, processing speed, and executive function (Palta et al., 2014). Despite research showing that T2DM causes brain-related cognitive dysfunction, a clinically useful pattern associated with T2DM have not yet established.

A recent systematic review and meta-analysis of observational studies have reported a general combined prevalence of CI with T2DM of 45% (You et al., 2021), with significant differences between countries. Specifically, in China 13.5% (Gao et al., 2016), India 33.7% (Khullar et al., 2016), France 28.8% (Verny et al., 2015), Spain 26.1% (Rodríguez-Sánchez et al., 2016), and Mexico 27.4% (Arjona-Villicaña et al., 2014).

Studies of community-dwelling individuals suggested that the probability of developing CI is 1.39–2.9 times higher in people with T2DM than without the disease (Cheng et al., 2012; Roberts et al., 2014). There is clear evidence that attributed the increased risk of CI with T2DM to poor lifestyle, age, hyperglycemia, hypercholesterolemia (Sharma et al., 2020), T2DM duration (Bozanic et al., 2021), and symptomatic and asymptomatic cerebrovascular disease (Araki and Ito, 2002), among others.

To our knowledge, this is the first study about the prevalence of CI with T2DM and its influencing factors in Chilean population. On the other hand, few Hispanic studies analyze cognitive characteristics using a comprehensive neuropsychological test battery to study CI among older adults with T2DM. Therefore, the present study aimed to estimate the prevalence of CI and its associated risk factors in the Chilean older adult population with T2DM. A secondary aim was to examine differences in cognitive performance between older Chilean adults with T2DM and healthy controls to provide a cognitive profile.

An observational, descriptive, comparative, and cross-sectional population study was conducted between October 2017 to September 2019. The sample was taken from the DIABDEM (DIABetes and DEMentia) project, whose methodology has already been published elsewhere (Bozanic et al., 2019). The DIABDEM project aimed to determine the prevalence of CI and its risk factors in people aged 65 or over with T2DM in Spain and Chile for people 65 or over who lived community-dwelling.

The reference population was Chilean inhabitants in 2017 (17.574.003 inhabitants total), from which 11.4% (2.003.256) were aged 65 or older (Instituto Nacional de Estadísticas, 2018). The sample was taken from 6 different Chilean cities. Recruitment was carried out by invitation to: (1) older adults who participate in Senior Social Clubs contacted by listing independently of active participation in the organization, and (2) older adults attending primary care centers contacted by listing independently of periodic visits. Each participant underwent an in-person interview by trained interviewers administered. The standard assessment included medical history, lifestyle questionnaires, and a comprehensive neuropsychological battery.

A random sample from the DIABDEM project comprised 358 subjects representing the adult population of Chile age 65 and older. Exclusion criteria were as follows: (1) have another nationality than Chilean, (2) live in another country, (3) visual, auditory, or motor impairments that precluded neuropsychological assessments; (4) history of dementia; (5) active psychiatric symptomatology that interfered with the ability to complete neuropsychological assessments.

The study was approved by an independent Ethics Committee of Scientific Research from Pontificia Universidad Católica de Chile (ID 170516002 project) and all participants were provided with written informed consent, according to the recommendations of the Declaration of Helsinki.

Data were analyzed using the Statistical Package for the Social Sciences version 20.0 (SPSS Inc., Chicago, IL, USA). A value of p < 0.05 was considered statistically significant. The chi-squared and Student’s t-test were used for discrete and continuous variables, respectively. Logistic regression was conducted to examine the association between T2DM and CI. The multiple logistic regression model included variables that had a p < 0.25 in the simple logistic regression analysis (age, gender, education, presence of dyslipidemia, and duration of T2DM). A MANOVA analysis of “cognition” was performed to determine the impact of T2DM diagnosis on cognitive functioning after adjusting with covariates found on multiple logistic regression. The variable “cognition” is composed of cognitive performance tests scores of Mini Mental State Examination Chile (MMSE-Ch), Free and Cue Selective Reminding Test (FCSRT)- words; Trail Making Test A (TMT-A), Trail Making Test B (TMT-B), Weschler Adult Intelligence Scale (WAIS-IV), Rey Osterreich Complex Figure (ROCF), and Boston Naming Test (BNT). Interactions effects were explored within covariates to analyze the relationship between factors on cognitive performing. F, Cohens, IC 90%, and p-values were provided.

Our results indicated that the prevalence of CI with T2DM was 30.6%. Multiple studies demonstrated different rates of prevalence of CI with T2DM across ethnicity (Noble et al., 2012). T2DM with CI was more prevalent among African Americans and Hispanics than Caucasians (11.4 vs. 4.9%; p = 0.06) (Albert et al., 2011). This finding was even slightly higher than studies conducted on Hispanic populations in Spain and Mexico (Arjona-Villicaña et al., 2014; Rodríguez-Sánchez et al., 2016). Chile has a distinctive epidemiological profile. So, ethnicity, demographics, nutritional, and physical activity changes may be playing a crucial role in increasing the prevalence of metabolic risk factors and accelerating the incidence of diseases like T2DM and, possibly, comorbid CI.

According to method 1, people with T2DM are 2.8 times as likely to show a risk associated with CI, which is consistent with previous cross-sectional and longitudinal studies that demonstrated epidemiological evidence suggesting that T2DM is associated with CI at 2.5 times greater risk than subjects without the disease (Cheng et al., 2012). We found no significant differences between the groups using method 2, diagnostic criteria recommended by the National Institute on Aging and Alzheimer’s Association workgroup (Cervi et al., 2005). We theorize that this disparity could be associated with the high functional performance of the evaluated sample. In addition, only a low number of participants showed reduced IADL or ADL.

Our study proven a significant association between CI and T2DM with age and years of education as protective factors, and presence of Dyslipidemia, and duration of T2DM as risk factors. Several studies showed that age is a primary risk factor for cognitive decline. Further, CI has been shown to be correlated with brain structure and function (Naninck et al., 2017) and a decreased cognitive performance on tasks for memory and information-processing speed was associated with increased age in T2DM people (Ruis et al., 2009). Education levels were one of the strongest predictors of maintained cognitive function (Albert et al., 1995; Rowe and Kahn, 1997). Some studies commented that education plays a more significant role than age in cognitive test performance (de Azeredo Passos et al., 2015). Of note, people with T2DM and low education showed poor cognitive performance (Teixeira et al., 2020; Kowall and Rathmann, 2022).

Even though it is unclear if hyperlipidemia or hypercholesterolemia contributes to cognitive decline or having a risk of developing Alzheimer Disease in T2DM subjects, it is well known that hypercholesterolemia and hypertriglyceridemia are associated with an increased risk for Alzheimer Disease (Appleton et al., 2017). Thus, further clinical studies on the impact of hyperlipidemia on the risks of cognitive impairment in T2DM subjects are needed. An unhealthy lifestyle is considered the major contributor to T2DM, causing a progressive deterioration of mental health. Finally, T2DM duration is another crucial contributor to CI. Cognitive decline is more prominent when the duration of Diabetes is more than 5 years (Bozanic et al., 2021). Besides, a long T2DM diagnosis significantly influences the conversion to dementia in T2DM with CI patients (Albai et al., 2019).

These findings supported our prediction that T2DM negatively impacts cognitive functioning. The T2DM group consistently performed worse on all measures, showing a decline in global cognitive performance but also in specific cognitive fields such as attention, language, verbal memory, visual memory, visual constructional ability, and executive function, as previous studies showed (Palta et al., 2014; Teixeira et al., 2020). Even after adjusting by cofounders as age, gender, education, presence of dyslipidemia, and duration of T2DM, T2DM significantly impacted cognitive function negatively. The influence of T2DM on cognition interacts with other dimensions. For instance, older individuals with T2DM and lower education tend to perform lower cognitive testing. Thus, age and education are factors to consider when individuals with T2DM perform cognitive assessments. It was suggested that pathophysiologic changes related with advancing age and low education, in addition to T2DM, has synergistic effects resulting in higher CI.

These functions are particularly relevant because they involve behaviors such as problem- solving, judgment, and changing habits that be crucial in prescribing complex tasks (Nici and Hom, 2019). Despite current recommendations for an annual cognitive assessment as a good practice in treating subjects with T2DM (Srikanth et al., 2020), a structured approach for evaluating cognitive impairment associated with T2DM is not currently part of daily practice. Moreover, this geriatric syndrome is not yet considered one of the main complications of the disease. There is also no standard cognitive assessment battery to assess cognitive impairment associated with T2DM specifically. However, a comprehensive neuropsychological assessment has been strongly proposed, including measuring different cognitive domains beyond an essential cognitive screening (American Diabetes Association, 2022).

Our data suggest a specific pattern for impaired function in the affected cognitive domains: amnesic multi-domain impairment. “Diabetes-related dementia” presents a unique pattern of pathologies in the cognitive domain (Hanyu, 2019). Neuroimaging has shown a more significant impairment in memory and executive function than that experienced in people with Alzheimer’s disease (Hanyu, 2019). Despite pathological differences, people with dementia-related to T2DM are often screened for cognitive status using the same brief cognitive assessment tests as people with Alzheimer’s disease, such as the Mini-Mental State Examination (MMSE), which is not suitable. It is suggested to apply the MoCA test, which has proven to be a brief, simple and effective tool to detect cognitive impairment in T2DM population (Mordenfeld et al., 2020).

Characterization of cognitive performance patterns, and their associated risk factors, could provide a basis for the early screening and intervention of CI in Older adults. Detection of CI and an accurate neurocognitive profile could help clinicians to give recommendations to maintain an adequate self-management of T2DM and mitigate poor clinical outcomes for patients and their families, keeping lining the incidence of all kinds of diabetes-related complications. A high degree of vigilance for cognitive deficits should be maintained in this population, particularly in those with additional risk factors for CI (Hanyu, 2019). Therefore, unifying the diagnostic criteria for CI with T2DM in the community-dwelling population was highly urgent.

There are several strengths of this study. First, due to the high heterogeneity of the population over 65, it is common for geriatric research to focus research and conclusions on a specific geriatric subpopulation. We do not claim the representativeness of the entire older population.

However, our results could be extrapolated to the community-dwelling older adults population and relatively robust users of outpatient primary health care settings. Second, our study utilized a comprehensive neuropsychological evaluation that allowed us to observe the performance in detail of different cognitive domains and thus propose a specific cognitive profile. However, it presents some limitations as well. First, a causal relationship between cognition and T2DM could not be concluded because of the cross-sectional nature of the observation. Second, considering the lack of laboratory data and diagnostic classifications based on participant responses, the prevalence of CI underlying diseases might be underestimated. Heart diseases and obesity could be independent factors of cognitive impairment, so it will be important to collect this data on the future. Third, we did not focus the analyses on the relationship between the different subtypes of cognitive impairment and cognitive function. Finally, longitudinal data from larger samples are needed to verify the above hypothesis.

Our ongoing research has found a higher prevalence of CI with T2DM among Chilean older adults in a community-based population aged 65. T2DM is significantly associated with a higher risk of CI, and education, presence of dyslipidemia, and duration of T2DM are risk factors in CI with T2DM people. T2DM patients with CI are impaired in multiple cognitive fields, such as general mental status, attention, language, verbal memory, visual memory, constructional ability, and executive function, even adjusting by cofounders, providing an amnesic multi-domain cognitive profile.

These findings will help policymakers estimate the potential burden of T2DM in healthcare settings, specifically among middle- and low-income Latin-American countries. Our data demonstrate that even a brief cognition evaluation is essential to assess the impact of T2DM on the mental health of this population, so these types of preventive strategies have been taken in order to avoid worsening cognition functions in these high-risk individuals.

The raw data supporting the conclusions of this article will be made available by the authors, without undue reservation.

The studies involving human participants were reviewed and approved by Ethics Committee of Scientific Research from Pontificia Universidad Católica de Chile (ID 170516002 project). The patients/participants provided their written informed consent to participate in this study.

AB contributed to the conception or design of the work. AB, PT, and SB-L contributed to interpretation of data for the work and drafting the work. SB-L contributed with data analysis. SB-L, CB, JH-O, and CV contributed to data collection. PT, SB-L, CB, JH-O, CV, and FF revising it critically for important intellectual content and final approval of the version to be published. All authors contributed to the article and approved the submitted version.