ABSTRACT
Cognitive impairment is associated with people with diabetes‐related foot ulcers (DFU). However, it is unclear if cognitive impairment is associated with the ulcer itself or other co‐existing diabetes‐related complications such as peripheral neuropathy. We aimed to investigate cognition in people with diabetes‐related peripheral neuropathy and compare those with DFUs to those without DFUs. In this age‐ and sex‐matched, multicentre, case‐control, observational study of 89 participants with Type 2 diabetes and peripheral neuropathy, we compared 49 participants with DFUs (cases) to 40 without DFUs (controls). Global cognition scores were assessed using the Montreal Cognitive Assessment tool. Participants with DFUs had similar characteristics to those without DFUs (all, p > 0.05), except for lower body mass index (p = 0.028). Participants with active DFUs had significantly lower global cognition scores compared to those without DFUs (median [IQR] 24.0 [21.0–25.0], 26.0 [24.0–28.0]; p < 0.001). After adjusting for other diabetes‐related complications, lower global cognition was independently associated with a DFU, peripheral artery disease, lower physical activity and no family history of diabetes (all, p ≤ 0.019). People with DFUs had lower cognitive scores than those without DFUs, suggesting that the DFU itself is independently associated with cognitive impairment. Future studies should explore causal pathways and targeted management strategies.
Keywords: cognition, cognitive impairment, diabetes, diabetes‐related foot ulcers, peripheral neuropathy
Key Points
People with DFU (cases) had lower global cognition scores compared to those without DFU (controls).
Cases had significantly lower cognition scores in the visuospatial/executive, naming, and attention domains compared to controls.
Although 61.8% of all participants were classified as having cognitive impairment, cases had a significantly higher proportion of cognitive impairment compared to controls.
After adjusting for other diabetes‐related complications, lower global cognition was independently associated with a DFU, peripheral artery disease, lower physical activity, and no family history of diabetes.
Active DFUs may independently contribute to cognitive impairment, highlighting the need for routine cognitive screening to enable early detection of cognitive changes.
1. Introduction
Globally, around 20 million people live with diabetes‐related foot ulcers (DFUs) each year, and around 200 million more have major risk factors for developing DFUs [1]. DFUs have been reported to be the leading cause of hospitalisations, amputations and disease burden in people with diabetes [1, 2, 3]. DFUs are defined as a break in the skin of the foot that involves the dermis in a person with diabetes and nearly always co‐exist with the major risk factors for DFU, those being the other diabetes‐related foot complications of peripheral neuropathy or peripheral artery disease (PAD) [4]. People with DFUs typically take months of intensive multidisciplinary management and self‐care to heal, have poorer quality of life during this time and are constantly at high risk of hospitalisation and amputation [1, 3, 5]. Therefore, people with a DFU ideally require intact cognition to deal with the high demands of managing their DFU, diabetes and overall health [1, 5].
Cognition is defined as the brain's ability to acquire, process, store and retrieve information [6]. Mild cognitive impairment (MCI) represents the level of impairment that begins to impact on activities of daily living and is defined as acquired deficits in one or more cognitive domains [7, 8]. People with diabetes are well‐known to be at risk of developing cognitive impairment [8, 9]. For people with diabetes, the most reported affected cognitive domains include executive function, psychomotor speed, memory and attention [7, 10]. Risk factors for cognitive impairment in people with diabetes include age, depression, hypertension, dyslipidaemia, hyperglycaemia, hypoglycaemia and diabetes‐related complications [7, 11]. Furthermore, MCI with diabetes can detrimentally influence adherence to diabetes self‐care and diabetes‐related complication management, leading to poorer diabetes outcomes [8, 9, 10].
Diabetes‐related peripheral neuropathy is a diabetes‐related foot complication reported in recent systematic reviews to be associated with cognitive impairment [11, 12]. Furthermore, multiple studies have investigated cognition in people with DFUs; however, their findings have been inconsistent, with some finding lower cognition in people with DFUs [13, 14, 15, 16, 17, 18] and others finding no difference in cognition compared with controls [19, 20]. Yet, most previous DFU studies did not match or control for known confounding factors influencing cognition, which likely impacted findings, such as age, sex, other diabetes‐related complications or pre‐existing cognitive impairment [13, 15, 17, 18]. Of three case–control studies that did control for either age, sex, pre‐existing cognitive impairment or diabetes‐related complications, they also reported inconsistent findings; however, none controlled for peripheral neuropathy or PAD [14, 20]. Thus, it remains unclear if cognitive impairment is associated with the ulcer itself or other diabetes‐related complications that typically co‐exist with DFUs, such as peripheral neuropathy or PAD.
Therefore, this study aimed to investigate cognition in people with diabetes‐related peripheral neuropathy and compare those with DFUs (cases) to those without DFUs (controls) and adjust for potential key confounders such as PAD. Findings from this study will help determine whether the ulcer itself or other co‐existing diabetes‐related complications are independently associated with impaired cognition and should shed new light on the cognitive capacity of people with DFUs to manage their DFUs, diabetes and overall health.
2. Materials and Methods
2.1. Study Design and Settings
This was a multicentre, case–control, observational designed study of eligible participants recruited between 18th July 2023 to 30th September 2024 from four Diabetic Foot Centres in Metro‐North Hospitals & Health Services, Brisbane, Australia. Ethical approvals were obtained from Human Research Ethics Committee, Metro‐North Health (HREC/89344) and from Queensland University of Technology (HREC/6859). The protocol for this study has been published elsewhere and is summarised below [21]. This manuscript presents the baseline findings of the case–control study, while the findings of the longitudinal study will be published separately.
2.2. Study Participants
Eligible participants were those aged 18 years and over, diagnosed with Type 2 diabetes and peripheral neuropathy. Peripheral neuropathy was defined as loss of protective sensation to a 10‐g monofilament on at least two of three plantar forefoot locations [4, 5]. Cases for this study were eligible participants with a DFU, and controls were eligible participants without a DFU. A DFU was defined as a break in the skin of the foot, below the ankle, that involved the dermis in a person with diabetes [4, 5]. Exclusion criteria included those previously diagnosed with cognitive impairment, dementia, cerebrovascular accident, other neurodegenerative diseases, were pregnant, or those with current episodes of hypoglycaemia or moderate to severe foot infection that are known to transiently impact cognition [7, 9, 11].
The sample size was calculated based on the assumptions of a previously reported medium effect size difference (d = 0.5) between cases and controls for global cognition in a similar case–control study [14]. However, the previously reported study used a different cognitive assessment tool and did not control for peripheral neuropathy (computerised cognitive assessment tools) [14]. Whereas, this study used the Montreal Cognitive Assessment (MoCA) cognitive assessment tool and did control for peripheral neuropathy. At the time of commencing this research, no established minimally clinically important difference (MCID) in cognitive assessment tools for people with diabetes was available. Therefore, the sample size was calculated to detect a statistically meaningful difference rather than a predefined diabetes‐specific MCID. Assuming a 1:1 case‐to‐control ratio, 80% power and an alpha of 0.05 using a one‐tailed independent t‐test, 57 participants per group were required [21]. Cases and controls were matched by age (to within 10 years) and sex when recruiting the participants as per previous similar DFU case–control studies [14].
2.3. Variables of Interest
Variables of interest for this study were grouped into the domains of demographic (age, sex, marital status, highest education level), diabetes (family history, duration, HbA1c, medications), comorbidities (arthritis, cancer, chronic kidney disease, depression, dyslipidaemia, hypertension, mobility impairment, myocardial infarct), lifestyle (alcohol consumption, body mass index (BMI), current smoker, physical activity levels) and limb characteristics (previous amputation, previous DFU‐related hospitalisation, previous DFU, PAD, foot deformity, acute Charcot foot). DFU characteristics (ulcer size, depth, infection and location) were also collected for cases. All variables were obtained via self‐report or clinical examination by a trained podiatrist or trained researcher using the validated Queensland High Risk Foot Form [22, 23] or other validated methods [24, 25]. Table S1 displays the definitions for all variables.
Important co‐variates of interest for this study were depression and physical activity and these were collected using the validated Patient Health Questionnaire‐Depression (PHQ‐9) [24] and Yale Physical Activity Survey (YPAS) [25], respectively. The PHQ‐9 is a validated, self‐administered, nine‐item depression survey widely used for depression screening and categorises depression levels as follows: nil (scores 0–4), mild (scores 5–9), moderate (scores 10–14), moderately severe (scores 15–19) and severe depression (scores 20–27). The YPAS is a validated, self‐administered, physical activity tool that categorises physical activity levels by the type and amount of physical activity performed in a typical week in the past month [25]. Time spent in each activity is multiplied by an intensity code (kcal·min−1) and summed across all activities to create an index of weekly energy expenditure for each activity (kcal·week−1). Time spent in each activity is then summed to provide a total activity index (h·week−1) [26].
2.4. Outcomes of Interest
The primary outcome of interest for this study was global cognition as measured using the MoCA tool [27]. The MoCA tool is a widely used, validated, 30‐item screening tool for assessing global cognition that is recommended for use in people with diabetes and should be administered by a trained clinician or researcher [28]. The first author completed all mandatory MoCA training (AURANNI710601459‐01), administered the MoCA to all participants and was unblinded to the participants. The MoCA covers seven domains of cognition (secondary outcomes of interest), including visuospatial/executive, naming, attention, language, abstraction, delayed recall, and orientation [27]. These domains are summed to produce a total score (global cognition score) that categorises cognitive impairment levels as follows: no cognitive impairment [26, 27, 28, 29, 30], MCI [18, 19, 20, 21, 22, 23, 24, 25], moderate cognitive impairment [10, 11, 12, 13, 14, 15, 16, 17] and severe cognitive impairment (0–9) [27]. The MoCA was administered in a quiet, separate room to minimise distractions and ensure unbiased cognitive assessment as per the recommendations for administration of the MoCA.
3. Statistical Analysis
All analyses were performed using SPSS 29.0 for Windows (SPSS Inc., Chicago, IL, USA). Categorical variables were presented as numbers and proportions and Pearson's chi‐squared was used to test differences between groups. Continuous variables were presented as means and standard deviations (±SD) if normally distributed, or medians and interquartile ranges (IQR) if not normally distributed and independent t‐tests or Mann–Whitney U tests were used to test differences between groups, respectively. Multiple linear regression was used to test for adjusted associations between variables and global cognition score. All variables with an unadjusted bivariate association of p < 0.1 were entered into the regression model. A backwards stepwise method was used to remove non‐significant variables one at a time (p > 0.05) at each step until only significant adjusted variables remained (p < 0.05). Mandatory assumptions for multiple linear regression models were checked at each step to ensure assumptions were maintained, including collinearity, residual outliers (Cook's distance), normality and linearity (normal P–P plot). Missing data were handled by excluding cases with missing data.
4. Results
Overall, 89 eligible participants were recruited, including 49 cases with DFUs and 40 controls without DFUs matched for age and sex. Table 1 shows all demographic, diabetes, comorbidity, lifestyle and limb variables were similar between cases and controls (all, p > 0.1), except those with DFUs (cases) had a lower mean ± SD BMI than those without DFUs (controls) (31.5 ± 6.1, 34.2 ± 7.3; p = 0.028). Of the 49 cases with DFUs, the median (IQR) ulcer size was 20 mm2 (8.0–68.5), 6.3% were infected, 4.1% were deep and 63.3% were located on the toes.
TABLE 1.
Characteristics for total, cases and control participants (number [%] or mean ± SD unless otherwise stated a ).
| Characteristics | Total | Cases | Controls | p |
|---|---|---|---|---|
| Participants | 89 | 49 | 40 | |
| Demographics | ||||
| Age (years) | 67.2 ± 10.6 | 67.4 ± 10.3 | 66.9 ± 11.1 | 0.808 |
| Males | 66 (74.2%) | 39 (79.6%) | 27 (67.5%) | 0.195 |
| Marital status | ||||
| Married/living together | 50 (56.2%) | 29 (59.2%) | 21 (52.5%) | |
| Single | 18 (20.2%) | 8 (16.3%) | 10 (25.0%) | |
| Divorced | 15 (16.9%) | 9 (18.4%) | 6 (15.0%) | |
| Widowed | 6 (6.7%) | 3 (6.1%) | 3 (7.5%) | 0.752 |
| Highest education level | ||||
| Primary school | 13 (14.6%) | 7 (14.3%) | 6 (15.0%) | |
| High school | 38 (42.7%) | 18 (36.7%) | 20 (50.0%) | |
| Diploma | 24 (27.0%) | 13 (26.5%) | 11 (27.5%) | |
| Degree | 14 (15.7%) | 11 (22.4%) | 3 (7.5%) | 0.256 |
| Diabetes | ||||
| Diabetes family history | 39 (43.8%) | 21 (42.9%) | 18 (45.0%) | 0.839 |
| Diabetes duration (years) | 17.9 ± 8.4 | 18.3 ± 8.6 | 17.8 ± 8.2 | 0.464 |
| HbA1c (mmol/mol) b | 7.0 ± 1.0 | 7.3 ± 1.3 | 6.9 ± 0.6 | 0.248 |
| Diabetes medications | ||||
| None | 8 (9.0%) | 5 (10.2%) | 3 (7.5%) | |
| Oral antidiabetic agents | 42 (47.2%) | 19 (38.8%) | 23 (57.5%) | |
| Insulin | 3 (3.4%) | 3 (6.1%) | 0 (0.0%) | |
| Combination oral and insulin | 36 (40.4%) | 22 (44.9%) | 14 (35.0%) | 0.187 |
| Comorbidities | ||||
| Arthritis | 24 (27.0%) | 12 (24.5%) | 12 (30.0%) | 0.560 |
| Cancer | 21 (23.6%) | 12 (24.5%) | 9 (22.5%) | 0.826 |
| Chronic kidney disease | 12 (13.5%) | 5 (10.2%) | 7 (17.5%) | 0.316 |
| Depression (PHQ score) | 6.0 (2.0–11.0) | 6.0 (2.0–13.5) | 5.0 (1.8–11.0) | 0.352 |
| Dyslipidaemia | 45 (50.6%) | 21 (42.9%) | 24 (60.0%) | 0.108 |
| Hypertension | 58 (65.2%) | 30 (61.2%) | 28 (70.0%) | 0.387 |
| Mobility impairment | 9 (10.1%) | 7 (14.3%) | 2 (5.0%) | 0.148 |
| Myocardial infarction | 22 (24.7%) | 12 (24.5%) | 10 (25.0%) | 0.956 |
| Lifestyle | ||||
| Alcohol consumer | 64 (71.9%) | 32 (65.3%) | 32 (80.0%) | 0.125 |
| Smoking status | 24 (27.0%) | 14 (28.6%) | 10 (25.0%) | 0.706 |
| BMI (kg/m2) | 32.7 ± 6.6 | 31.5 ± 6.1 | 34.2 ± 7.3 | 0.028* |
| Physical activity (YPAS) | ||||
| Total Time Index a | 16.3 (8.8–26.0) | 17.5 (9.3–26.0) | 16.6 (8.6–26.9) | 0.843 |
| Total Energy Index a | 3975.0 (1741.5–5790.0) | 3975.0 (1895.1–5982.6) | 4095.0 (1648.8–5857.7) | 0.814 |
| Vigorous Activity Index a | 0.0 (0.0–27.5) | 0.0 (0–28.6) | 0.0 (0–28.4) | 0.923 |
| Leisurely Walking Index a | 32.5 (0.0–95.5) | 27.5 (0–80.9) | 39.4 (0–115.1) | 0.562 |
| Moving Index a | 75.0 (55.8–108.0) | 70.4 (56.6–108.0) | 80.9 (54.0–111.4) | 0.834 |
| Standing Index a | 52.2 (32.1–82.4) | 57.6 (31.7–73.0) | 50.7 (34.4–90.5) | 0.690 |
| Sitting Index a | 246.0 (162.0–374.4) | 252.0 (152.8–367.2) | 233.0 (167.0–395.9) | 0.925 |
| Total Activity Index a | 489.3 (334.9–689.7) | 505.0 (311.6–660.1) | 448.4 (353.0–696.5) | 0.945 |
| Limb | ||||
| Previous amputation | 36 (40.4%) | 22 (44.9%) | 14 (35.0%) | 0.344 |
| Previous DFU‐related hospitalisation | 48 (53.9%) | 30 (61.2%) | 16 (45.0%) | 0.127 |
| Previous DFU | 77 (86.5%) | 45 (91.8%) | 32 (80.0%) | 0.104 |
| Peripheral artery disease | 30 (33.7%) | 18 (36.7%) | 12 (30.0%) | 0.504 |
| Foot deformity (≥ 3 score) | 41 (46.1%) | 23 (46.9%) | 18 (45.0%) | 0.855 |
| Foot infection | 3 (3.4%) | 3 (6.3%) | 0 (0.0%) | N/A |
Abbreviations: BMI, body mass index; HbA1c, glycated haemoglobin; NA, not applicable as did not meet assumptions for chi‐square test; PHQ‐9, Patient Health Questionnaire—9; YPAS, Yale Physical Activity Survey.
Median (IQR).
Missing data for HbA1c (n = 56 missing; 34 cases, 22 controls).
p < 0.05.
Participants with DFU (cases) had lower global cognition scores compared to those without DFU (controls) (24.0 [21.0–25.0], 26.0 [24.0–28.0]; p < 0.001) (Table 2). Those with DFUs (cases) also had significantly lower scores in the visuospatial/executive, naming and attention domains compared to controls (all, p < 0.05). Overall, 55 (61.8%) of all participants were classified as having cognitive impairment (53 mild and 2 moderate). Participants with DFUs (cases) had a significantly higher proportion of cognitive impairment compared to those without DFUs (controls) (38 [77.6%] vs. 17 [42.5%]; p < 0.001).
TABLE 2.
Cognitive scores for total, cases and control participants (median (IQR) unless otherwise stated a ).
| Cognitive domains (MoCA) | Total (n = 89) | DFUs (n = 49) | Controls (n = 40) | p |
|---|---|---|---|---|
| Visuospatial/executive (score range 0–5) | 4.0 (3.0–5.0) | 4.0 (2.0–4.0) | 4.0 (4.0–5.0) | 0.007* |
| Naming (score range 0–3) | 3.0 (3.0–3.0) | 3.0 (3.0–3.0) | 3.0 (3.0–3.0) | 0.039* |
| Attention (score range 0–6) | 5.0 (5.0–6.0) | 5.0 (4.0–6.0) | 6.0 (5.0–6.0) | < 0.001* |
| Language (score range 0–3) | 2.0 (2.0–3.0) | 2.0 (1.5–3.0) | 3.0 (2.0–3.0) | 0.060 |
| Abstraction (score range 0–2) | 2.0 (2.0–2.0) | 2.0 (2.0–2.0) | 2.0 (2.0–2.0) | 0.463 |
| Delayed recall (score range 0–5) | 3.0 (1.0–3.5) | 2.0 (1.0–3.0) | 3.0 (2.0–4.0) | 0.137 |
| Orientation (score range 0–6) | 6.0 (6.0–6.0) | 6.0 (6.0–6.0) | 6.0 (6.0–6.0) | 0.063 |
| Global cognitive score a (score range 0–30) | 25 (22.5–26.5) | 24 (21.0–25.0) | 26 (24.0–28.0) | < 0.001* |
Abbreviation: MoCA, Montreal Cognitive Assessment.
Mean (±SD).
p < 0.05.
Bivariate analyses identified there were unadjusted associations (p < 0.1) between global cognition score and DFU (group), age, marital status, diabetes family history, cancer history, mobility impairment, BMI, physical activity and PAD (Table S2). As mobility impairment and six physical activity variables were identified as highly correlated, we chose only the total (physical) activity index variable to be entered into the model along with DFU (group), age, marital status, diabetes family history, cancer history, BMI and PAD. The factors that remained independently associated with a lower global cognition score were DFU (cases), PAD, lower total (physical) activity index and no diabetes family history (model: adjusted R 2 = 0.33; p < 0.001; all variables, p ≤ 0.019; Table 3).
TABLE 3.
Multiple linear regression of variables independently associated with total/global cognitive score in people with Type 2 diabetes and peripheral neuropathy.
| Unstandardised coefficients β (95% CI) | Standardised coefficients β | p | |
|---|---|---|---|
| DFU (referent controls a ) | −2.28 (−3.32, −1.24) | −0.38 | < 0.001 |
| Diabetes family history | 1.68 (0.63, 2.73) | 0.28 | 0.002 |
| Total (physical) activity index | 0.002 (0.0, 0.004) | 0.22 | 0.019 |
| PAD | −1.43 (−2.56, −0.28) | −0.23 | 0.015 |
Abbreviations: DFU, diabetes‐related foot ulcers; PAD, peripheral artery disease.
Controls: people without DFUs.
5. Discussion
In this case–control study of people with diabetes‐related peripheral neuropathy, we identified several novel and important findings in people with DFUs. First, there were significantly lower global cognition scores in people with DFUs compared to people without DFUs, even after adjustment of potential covariates. Second, the majority of people with DFUs were classified as having MCI significantly more than in the control group without DFUs. Third, there were also significantly lower scores in the cognitive domains of visuospatial/executive, naming and attention in people with DFUs. Fourth, the relationship between lower global cognition scores and people with DFUs remained after adjusting for known confounders and other diabetes‐related complications, such as age, BMI, physical activity level, PAD, and marital status. Finally, apart from DFUs, we also found the presence of PAD, lower physical activity levels and no diabetes family history were independently associated with lower global cognition.
In our study of people with diabetes‐related peripheral neuropathy and most (> 85%) with a previous DFU history, we found a two‐point statistically significant difference in global cognition scores using the MoCA tool between people with a DFU compared to controls without a DFU. This was despite both groups being well matched for demographic details, comorbidities, lifestyle factors and limb characteristics. Furthermore, this two‐point statistical difference is likely a clinically important difference, considering a one‐to‐two‐point difference in the global cognition score using the MoCA has been reported to be a clinically important difference in cognition for people who have had a cerebrovascular accident [29] or have Alzheimer's disease [30]. However, we note a minimal clinically important difference has yet to be reported to our knowledge in people with diabetes.
Our findings of lower global cognition in those with DFUs compared to those without DFUs mostly build upon and align with findings of previous similar studies [13, 14, 15, 16, 17, 18], with some exceptions [19, 20]. Unlike our study though, most of these previous studies either did not exclude participants with confounding factors known to influence cognition such as dementia or cerebrovascular accident [14, 16, 17, 18, 19], did not include cases with active DFU only as some included cases with a previous DFU [13, 15, 20], or did not match or control for age, sex, pre‐existing cognitive impairment and other diabetes‐related complications, such as peripheral neuropathy or PAD [13, 14, 15, 16, 17, 18, 19, 20]. Regardless, of the three most robust similar previous case–control studies comparing global cognition scores in people with DFUs to diabetes controls [14, 16, 20] two found significantly lower scores in those with DFUs [14, 16] and one found no difference [20]. However, the study finding no difference, included cases with active or previously healed DFUs, did not match for sex, and compared to a diabetes control group that had much lower levels of diabetes‐related neuropathy and PAD; however, much higher levels of diabetes complexity and comorbidities, such as higher HbA1C, insulin management, depression and anxiety. These factors all likely contributed to finding no differences between groups [20].
Additionally, we found 78% of people with DFUs in our study had a global cognition score that according to the MoCA tool classified them as having at least MCI. Considering we excluded participants with pre‐existing diagnosed cognitive impairment, dementia, cerebrovascular accident, and other neurodegenerative conditions that may cause cognitive impairment, this finding indicates considerable underlying cognitive impairment in people with DFUs compared to those without DFUs [27]. The proportion of MCI classified among participants with DFUs in our study also fell within the 56% to 87% range reported by other similar previous studies using the MoCA tool and reporting MCI [17]. Furthermore, these levels of MCI were much higher than the 25% to 55% range reported for people with diabetes in a recent meta‐analysis [31, 32]. Therefore, according to these findings, the majority of people with DFUs are likely to have MCI and at much higher levels than those with diabetes.
We also found lower cognition scores in the specific cognitive domains of visuospatial/executive, naming and attention. Our findings were mostly similar to other studies that also had found significantly lower scores for executive function [13, 14, 17], attention [14, 17] and language [14, 17], when compared to people without DFUs or healthy controls. However, again most of those studies did not exclude pre‐existing cognitive impairment, purely investigate active DFU cases or match them for various confounding factors [13, 14, 15, 16, 17, 18]. Any impairment of executive function and attention has also been reported to affect self‐management, self‐care and activities of daily life in people with diabetes and that could also be hypothesised to lead to a new ulcer or a worsening of an existing DFU in those with diabetes‐related peripheral neuropathy [17, 18, 33].
The cognitive impairment found in our study may have been explained by several well‐known risk factors for cognitive impairment, such as sex (females), older age, education level, hypertension, dyslipidaemia, depression [34], dementia, alcoholism, obesity and physical activity [35]. However, we excluded or adjusted for measures of all these factors and still found that people with DFUs were independently associated with lower global cognition scores. We also found that the presence of PAD, lower total physical activity and no diabetes family history were independently associated with lower global cognition scores in people with diabetes‐related peripheral neuropathy. The finding of PAD being associated with cognitive impairment is not surprising considering that previous studies had also found that PAD was associated with cognitive changes in people with DFUs [13, 18, 20] and we hypothesise that systemic cardiovascular changes are potential causes [13, 36]. Similarly, whilst previous studies investigating cognition and DFUs did not specifically examine physical activity [13, 14, 16, 18], recent meta‐analyses in general populations report that physical activity was a significant moderator of cognitive impairment [35, 37] and has a significant impact on cognition in people with diabetes and in this case potentially on people with DFUs as well. Furthermore, to our knowledge no similar studies have explored diabetes family history as a variable for consideration with cognition and it is unclear why not having a diabetes family history would be associated with lower cognition and further research is needed to confirm and investigate this relationship.
Our findings that people with DFUs, compared to well‐matched or adjusted controls without DFUs, have considerably lower cognitive scores suggest that the ulcer itself is associated with cognitive impairments. Similar to a recent study demonstrating that having a DFU was independently associated with increased major cardiovascular events, we also hypothesise that perhaps persistent low‐grade systemic inflammation in those with DFUs may be implicated in these cognitive deficits as well, and likewise we recommend inflammatory markers are explored in further studies. Otherwise, as others have hypothesised in diabetes populations, many factors may be implicated in the relationship with cognitive impairment [20], such as systemic inflammation, oxidative stress, vascular changes and neuropathic changes [20, 38]. Furthermore, most participants in both groups had a history of previous foot ulcers, and therefore, the primary distinction between groups was the presence of an active ulcer at the time of assessment in cases. Thus, we hypothesise that the active ulceration may be further increasing the inflammatory process and physiological stress as compared to those with a healed ulceration. However, the design of our study did not allow for determination of causality and further longitudinal research is needed to determine if the ulcer itself is a risk factor for cognitive impairment, if cognitive impairment is a risk factor for the ulcer, or alternatively are other moderating factors at play that were not measured in this study.
Regardless of direction of relationship, our findings that considerable cognitive impairments are independently associated with DFUs, should prompt clinicians to consider assessing for and tailoring their DFU management towards people with cognitive impairment [13, 14, 17]. Awareness of the possibility of cognitive changes due to diabetes‐related peripheral neuropathy, PAD and having a DFU should allow treatment teams to adjust their DFU care and consider early cognitive risk assessments [33]. Moreover, people with impaired cognition may lose the ability to adhere to DFU, diabetes and broader health self‐care recommendations [33]. Therefore, specific self‐care support for such individuals needs to be encouraged to mitigate potential non‐adherence to management plans due to cognitive impairment. Such support that has previously been recommended for people with diabetes and poor executive functions, attention and processing speed have included considering limited information at a time, removing distractions and using simple, literal language when providing education [18, 28]. Additionally, modifying the home environment for cognitive support may also be useful in promoting optimal self‐management behaviours [18, 28].
There are some limitations in this study. Firstly, the present study was conducted as a case–control study and hence we are unable to attribute causality to the relationship between cognitive impairment and DFUs. Secondly, recruitment challenges meant the study did not reach the planned sample size, potentially reducing statistical power [21]. The sample size was estimated from prior studies using different cognitive tools and not controlling for neuropathy, which may limit comparability. Furthermore, a diabetes‐specific minimally clinically important difference for MoCA had not been previously established; therefore, the clinical significance of the observed differences should be interpreted cautiously. Larger adequately powered studies are needed to confirm these findings. Thirdly, we only matched for sex and age in 10‐year groups, however we adjusted for these factors and many other known confounders in regression models. Fourthly, the present study used International Working Group on the Diabetic Foot (IWGDF) guidelines [39], including the 10‐g monofilament test, to detect neuropathy in people with diabetes‐related foot complications. However, the study did not assess the severity of peripheral neuropathy, which may influence cognitive changes. Unlike previous studies, all case and control participants in this study had peripheral neuropathy. Fifthly, there were considerable missing data for the HbA1c variable meaning we had to exclude measures of hyperglycaemia and this may have affected the findings as a potential covariate for cognitive impairment. Sixthly, we found the physical activity variable was independently associated with lower cognitive scores; however, physical activity was measured using a validated yet self‐reported tool and hence we cannot rule out this may have confounded results in those with memory or delayed recall deficits. Seventhly, the study did not measure the influence of inflammatory biomarker concentrations on cognition or how these markers changed over time. These unmeasured variables may play an important role in cognitive changes and limit the interpretation of the potential mechanisms underlying such changes. Lastly, this study was conducted in large metropolitan centres in Australia and our findings may not be representative or account for geographical remoteness or socioeconomic status in Australia or elsewhere. Therefore, we recommend future longitudinal designed studies of representative cohorts of people with DFU from diverse backgrounds are conducted and additional variables that we were unable to collect are measured (e.g., HbA1c, blood inflammatory markers, objective physical activity measures) to explore causal relationships between cognitive impairment in people with DFUs.
In summary, this study revealed significantly lower cognition in people with DFUs compared to well‐matched controls without DFUs, and particularly in the visuospatial/executive, naming and attention cognitive domains. This difference was maintained after adjusting for multiple other diabetes‐related complications and other possible confounding factors, such as age, sex, physical activity, PAD and previous DFUs. The findings suggest that the presence of a DFU further influenced cognitive changes in people with diabetes‐related peripheral neuropathy, which may in turn affect DFU self‐management and daily activities. Therefore, cognitive screening of people presenting with DFUs by clinicians should be considered in future to enable the early detection of cognitive changes and the potential tailoring of management strategies to improve care and outcomes for people with DFU.
Funding
N.K. was supported by a QUT Post Graduate Research Award and QUT tuition fee scholarships. P.A.L. was supported by an National Health and Medical Research Council (2034266), Australia.
Ethics Statement
Ethical approval for this research has been granted by the Metro North Human Research Ethics Committee and the QUT Human Research Ethics Committee, Brisbane, Australia.
Conflicts of Interest
The authors declare no conflicts of interest.
Supporting information
Data S1: iwj70867‐sup‐0001‐Supinfo.docx.
Acknowledgements
The authors would like to acknowledge the staff and patients of the diabetes foot services, Metro‐North Hospitals and Health Services and QUT Health Clinics for their support during the data collection. The first author (N.K.) acknowledges the support of QUT as this study has been undertaken in partial fulfilment of a Doctor of Philosophy. Open access publishing facilitated by Queensland University of Technology, as part of the Wiley ‐ Queensland University of Technology agreement via the Council of Australasian University Librarians.
Data Availability Statement
The data that support the findings of this study are available on request from the corresponding author. The data are not publicly available due to privacy or ethical restrictions.
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Associated Data
This section collects any data citations, data availability statements, or supplementary materials included in this article.
Supplementary Materials
Data S1: iwj70867‐sup‐0001‐Supinfo.docx.
Data Availability Statement
The data that support the findings of this study are available on request from the corresponding author. The data are not publicly available due to privacy or ethical restrictions.