Factors Associated with Cognitive Impairment among Adults of 55 Years and Older in Cameroon

Since the fifth edition of the Diagnostic and Statistical Manual of Mental Disorders (DSM-5) published by the American Psychiatric Association, the term “dementia” has been renamed “major neurocognitive disorder” (MNCD) because the term dementia was deemed to be stigmatizing [1]. MNCD is considered as a geriatric syndrome [2] associating both significant impairment of cognitive performance (of gradual onset) and a declining ability to perform the activities of daily living. It is one of the leading causes of dependency (estimated to account for around 11%) in persons aged 60 years and above [1]. MNCD is a major public health challenge because it has serious repercussions both for the healthcare system and for society as a whole [3]. The prevalence of MNCD increases with advancing age [4‒6]. The World Alzheimer Report 2021 as well as several other studies has underlined that the economic impact of MNCD will outstrip that of noncommunicable diseases, such as cancer, stroke, or heart disease [7‒9]. In a study performed in Cameroon in 2019, the authors estimated that the overall prevalence of cognitive impairment (CI) in rural areas was around 33% in individuals aged 60 years and over [10]. It is well established that MNCD is strongly associated with adverse health outcomes (hospitalization, nursing home admission, loss of autonomy, death), as well as impacting the organization of patient care and more generally healthcare delivery [7]. Cameroon, in sub-Saharan Africa, will experience rapid population aging between now and 2050, by which time the proportion of inhabitants aged 60 years and over will rise from 5% to 15% [11]. In line with these demographic projections, there will be a commensurate rise in age-related health problems, notably an increased prevalence of chronic disease, including MNCD, and its attendant consequences, such as incident dependency, unscheduled hospitalization, and admission into long-term care [12].

Since 2019, the World Health Organization program for integrated care for older people (ICOPE), which aims to promote primary prevention initiatives, has highlighted cognitive status (defined by 10 items of the mini-mental state examination [MMSE]) as an intrinsic capacity that is necessary for successful aging [13, 14]. The MMSE is the most widely used instrument worldwide to evaluate cognition. To the best of our knowledge, no study to date has investigated the risk factors for severe cognitive decline in community-dwelling adults with preserved functional status in Cameroon. The aim of this study was therefore to identify the factors associated with CI, as assessed by the MMSE, among community-dwelling adults aged 55 years and older who live in urban areas and are members of an association for older persons in Cameroon (Mutuelle des Personnes Agées du Cameroun, MUPAC, an apolitical, not-for-profit humanitarian association aimed at negotiating the provision of healthcare for older people).

The MUPAC study is a population-based, cross-sectional study conducted in Cameroon. Its primary objective was to negotiate the provision of healthcare to older people. Details of the MUPAC study design have previously been published elsewhere [15]. Briefly, community-dwelling men and women aged 55 years or older were selected from among the members of MUPAC in the city of Douala, Cameroon, from January 1 to May 31, 2019. From a total of about 2,000 members in Douala, 615 agreed to participate, yielding an acceptance rate of 31%. Of the total number of participants, 403 were aged 55 and above and were therefore eligible to take part in the study. However, older people with severe medical conditions (e.g., respiratory pathology, congestive heart failure), severe physical pain/disability, neurological disease that can lead to CI (epilepsy, systemic brain disease, recent stroke), and those with blindness were excluded from the study. It was deemed that these serious medical conditions could compromise the diagnostic test performance.

For the purposes of the present study, the following variables were extracted from the members’ files: socio-demographic data (age, sex, and level of education), marital status, medical history, overall cognitive performance, and functional status. Physical performance was assessed using the Short Physical Performance Battery (SPPB) [16] and the Study of Osteoporotic Fractures (SOF) index [17]. Functional status was assessed using Lawton’s Instrumental Activities of Daily Living (IADLs) [18] and Katz’s Activities of Daily Living (ADL) [19]. Depression was investigated using the Center for Epidemiologic Studies-Depression scale (CES-D) [20], and falls and sensory impairment were self-reported.

The primary endpoint was cognitive status, assessed using the mini-mental state examination (MMSE) [21]. This 30-item instrument evaluates cognitive function in terms of orientation, repetition, verbal recall, attention and calculation, language, and visual construction. Scores range from 0 to 30, and a score of 18/30 or lower is considered as a proxy of severe cognitive decline [22, 23].

Quantitative variables are expressed as medians and interquartiles (quartile [Q]1, Q3) and qualitative variables as number and percentage. Groups were compared using the appropriate parametric and nonparametric tests. The variable MMSE was dichotomized, with individuals having a score <18 considered to have severe cognitive decline. We compared those who had major cognitive decline with those who had normal cognition using the chi-square or Student’s t test, as appropriate. Multivariate logistic regression was used to identify the factors significantly associated with cognitive decline. Variables yielding a p value <0.20 by univariate analysis were included in the multivariate model and stepwise descending selection was applied. Known prognostic factors were forced in the model. The final model was chosen based on the Akaike Information Criterion, to select the most parsimonious model with the lowest Akaike Information Criterion. Results are presented as odds ratios (ORs) with 95% confidence interval (CI). P values <0.05 were considered statistically significant. All analyses were performed with R Studio software (v.3.0.2.21).

A total of 403 adults participated in the study. Their characteristics are described in Table 1. Of these, 16 (3.9%) had an MMSE score <18 and were considered to have CI. The rate of CI increased with rising age, from 2.1% in those aged 55–64 years, to 3.3% in those aged 65–74, and 11% in those aged 75 and older. There was no difference in CI between sexes. Subjects with CI generally had a lower socio-educational level (p = 0.001) and lower body weight (58 vs. 79 kg). They were also more often dependent on IADLs, with impaired physical function according to the SOF index (frailty) and SPPB (risk of sarcopenia). The factors associated with CI (MMSE score <18) by multivariate analysis in our population are displayed in Table 2 and were level of education (OR 0.10 [95% CI: 0.02–0.37], p < 0.01), body mass index (BMI) (OR 0.88 [95% CI: 0.78–0.99], p = 0.03), and IADL score (OR 0.12 [95% CI: 0.03–0.38], p < 0.001).

In this study among members of the MUPAC, comprising a population of urban community-dwelling older adults in Cameroon, the prevalence of CI was estimated at 3.9%. Despite the limitations of this study, this finding is in line with prevalence data for MNCD reported in other studies from sub-Saharan Africa [24]. There is a paucity of research data reporting the prevalence of severe CI or dementia in sub-Saharan Africa, with the result that it is difficult to establish an accurate picture of the situation in each individual country [6, 24‒26]. Studies from Africa have generally reported heterogeneous but usually lower prevalence of dementia than studies from Europe or America. However, the limitations of many African studies include the low quality of the methodology, varying types of study settings (i.e., inpatients, outpatients, nursing homes, and autopsy studies), and limited coverage of the different African regions.

In a report published in 2017, using the DSM-III/IV criteria and based on a total of 10 studies, experts from Alzheimer’s Disease International estimated the prevalence of MNCD in sub-Saharan Africa to be 5.5% in persons aged 60 years and older, with a female predominance (the prevalence among women being twofold than in men of the same age) [27]. In a systematic review of the literature published in 2014 investigating the prevalence of dementia in sub-Saharan Africa, Lekoubou et al. [28] analyzed a total of 49 studies and found a prevalence of 9%. In another study performed in the hospital setting in Cameroon, Kuate Tegueu et al. [6] estimated that the prevalence of CI disorders was 12% in patients aged 65 years and older. Our study provides complementary insights to the existing literature from sub-Saharan Africa, by including urban community-dwelling adults, and by estimating the prevalence of moderate to CI, defined by an MMSE score <18. We observed in our study that the rate of CI increased in line with age, to reach 11% in those aged 75 years and older. This is congruent with the literature.

In our study, we also observed an association between the level of education and cognitive performance, whereby a lower level of education was associated with lower cognitive performance. This level of education was taken into account in the adjusted statistical analyses. More generally, reading, writing, and counting are necessary functions to communicate, exchange, and accomplish the complex tasks of the life. Thus, CI related to education and social level should be considered as functional limits for elderly people as for other parts of the population. This result is also in line with the large body of evidence coming from studies in high- and middle-income countries and also from sub-Saharan Africa. Indeed, Lekoubou et al. [28] also showed that one of the most consistent risk factors for dementia among older adults in sub-Saharan Africa was having fewer than 6 years of education. This is all the more pertinent considering that improvements in educational level have contributed to promoting healthy aging [29]. Several potential mechanisms have been proposed to explain this link between education and the risk of dementia. It is now known that the level of education may play a protective role against neurodegeneration, promoting enhanced function of the neuronal system (whereby, when neurons die, others can perform similar functional tasks), thereby mitigating the signs of functional and cognitive deficiency [30]. For example, in the Personnes Agées Quid (PAQUID) cohort, individuals who had not completed primary school showed more rapid declines in measures of verbal fluency, psychomotor speed, and episodic memory, compared with those who had completed primary school. It has further been shown that the first signs of cognitive decline appear up to 15 years before the onset of clinical disease [31, 32]. A second factor identified in our study as being related to cognitive function was BMI. In our study, low BMI was associated with lower cognitive performance. This has also been reported in other works [33, 34]. In a systematic review and meta-analysis of prospective studies, Yi Qu et al. [35] confirmed that overweight and obesity were positively associated with dementia in middle-aged adults, but negatively associated with dementia in older adults, and with cognitive disorders in both middle-aged and older adults. Weight loss may result from pre-dementia apathy, or reduced olfactive function [36, 37]. Cova et al. [38, 39] also reported in a prospective study that higher BMI was associated with a lower risk of progression to dementia and Alzheimer’s disease in patients with mild CI, while low body weight was associated with 2.5-fold risk of progression to dementia within 2.4 years [37]. Our results provide a good opportunity to underline the utility of performing systematic evaluation of BMI (as a proxy of undernutrition) during home visits and primary care consultations, either by GPs or nurses. BMI can have a deleterious influence on cognitive status, and therefore, early management is essential, especially considering that BMI is often underdiagnosed in older adults. BMI is an effective, user-friendly metric that is easy to implement in routine practice. Furthermore, early intervention for nutritional status in older individuals, before it begins to affect cognition, is an objective that is closely aligned with the practices and goals of GPs in primary care. Regarding the link between loss of IADLs and cognitive decline, it is difficult to discern, in our study, whether the IADL impairment is the cause or the consequence of cognitive decline. Nevertheless, reduced scores on IADLs are associated with lower cognitive performance but seemingly more as a consequence thereof. Roehr et al. [40] previously reported that the risk of dementia and Alzheimer’s disease was highest in individuals with both subjective cognitive decline and impaired IADLs.

Our study has some limitations, the main one being the use of the MMSE as a proxy to assess cognitive function. In the diagnostic workup for MNCD, neuropsychological evaluation uses a battery of tests. The proportion of exclusion (34.5%) explains the low prevalence of CI in this sample and could induce a bias in the analysis of risk factors of CI. Nevertheless, the prevalence of cognitive decline seems to be close to that reported for sub-Saharan Africa. Some strengths of our study should also be noted. First, this is the first time that a study of this type has been conducted in the population of Cameroon and we included a relatively large sample size. Moreover, the quality of the data is reliable because the data were collected by clinicians trained in geriatric assessment. In addition, we achieved good data completeness, thereby maximizing the statistical power of the analyses.

Our study found a prevalence of CI of 3.9% in urban community-dwelling adults aged 55 years and over in Cameroon. The prevalence of CI increases with age. The three main factors associated with cognitive decline were level of education, IADLs, and BMI. This study shows that among older populations in sub-Saharan Africa, the effect of BMI, IADLs, and education on cognitive function seems to be comparable to what is observed in middle- and high-income countries.

Nadine Simo-Tabue, Mélanie Annick Magnerou, Ludwig Mounsamy, Salvatore Metamno, Laurys Letchimy, Jean-François Dartigues, Callixte Kuate-Tegueu, and Maturin Tabué-Teguo are responsible for the contribution to the study of factors associated with severe cognitive decline in community-dwelling older persons in Cameroon.

This study was approved under the number 2019/049/UdM/CIE by the Institutional Ethics Committee of the “Université des Montagnes” (Bangangté, Cameroon). All experiments were performed in accordance with relevant guidelines and regulations. All study participants received an information leaflet outlining the study procedures, and all participants provided written informed consent to participate.

The authors have no conflicts of interest to declare.

This study was not supported by any sponsor or funder.

N.S.-T. and M.T.-T. designed the study; N.S.-T., M.T.-T., and C.K.-T. collected the data; M.T.-T., S.M., N.S.-T., and C.K.-T. developed the data analysis strategy; S.M. analyzed the data; and S.M., N.S.-T., M.A.M., L.M., L.L., J.-F.D., and M.T.-T. interpreted the results and drafted the manuscript. All authors have read and agreed to the published version of the manuscript.

The data that support the findings of this study are not publicly available due to their containing information not useful for work but are available from the corresponding author (M.T.-T.) upon reasonable request. A preprint version of this article is available on Research Square (https://doi.org/10.21203/rs.3.rs-3818956/v1).