Depressive Symptoms in Multiple Sclerosis: Links to Body Composition, Physical Activity, and Functional Ability

Abstract

Background

In patients with multiple sclerosis, depression and its associated symptoms are factors that reduce the health-related quality of life can affect the course of the disease and the patient’s compliance with therapeutic recommendations, or may even increase the risk of suicide. This study aimed to determine the relationship between body composition, motor function of limbs, physical activity, and the occurrence of depressive symptoms in patients with multiple sclerosis.

Material/Methods

The study group included 110 patients – 84 women (76.4%) and 26 men (23.6%) – with multiple sclerosis and with or without depression. Disability status was assessed using the EDSS scale. Depressive symptoms were recognized based on the Beck Depression Inventory-II, while motor function was determined with the 9-Hole Peg Test and Timed 25-Foot Walk test. Accelerometers were used to evaluate physical activity of patients. Statistical analysis of collected data was performed using logistic regression.

Results

Depressive symptoms (BDI–II score ≥14) were observed in 24.55% of the participants. MS patients with and without depression symptoms differed significantly in terms of fat mass, T25-FW, and 9-HPT-dominant hand. Multivariate regression analyses demonstrated that increased adiposity (OR=1.09; 95% CI=1.02–1.16; P=.008; and decreased motor ability of the upper limb, both dominant (OR=1.07; 95% CI=1.01–1.15; P=.043) and non-dominant one (OR=1.10 95% CI 1.01–1.18; P=.025) were associated with a higher risk of depression. The differences in physical activity and T25-FW between groups were statistically insignificant.

Conclusions

The severity of depression symptoms was related to higher body mass and decreased functional ability of the upper limbs in patients with MS. Thus, a detailed evaluation of the patient’s upper-limb function should constitute an integral part of motor function assessment of patients with MS.

Introduction

Depression is a very common comorbidity in patients with MS [1]. A systematic review and meta-analysis conducted in 2017 among a total of 87 756 persons with MS revealed a prevalence of depression of 30.5% [2]. Another meta-analysis, conducted in 2022, showed that depression was identified in 27.48% of patients with MS in prospective studies and 26.57% in cross-sectional studies [3]. In a cross-sectional study conducted in Poland, 37.6% of patients with MS declared they had depression or depressive mood [4]. Depression and its associated symptoms have a strong negative impact on health-related quality of life [5,6] and may affect the course of the disease, worsening disability and adherence to therapeutic recommendations in patients with MS [7–9]. Depression may also increase the risk of suicide in these patients [10]. Consequently, early diagnosis of depression symptoms and identification of the symptoms correlated with depression are essential to the therapeutic process.

The pathogenesis of depression as a comorbidity of MS has not been fully explained to date. Genetic factors [11], brain pathology [12], inflammation [9], and psychosocial factors may play a significant role in the development of depression [13]. The results of a 2.5-year-long observation showed that the primary factors related to a positive depression-screen were marital status, socioeconomic status, disability, overweight and obesity, fatigue, and use of antidepressants [14]. Depression may occur as a reaction to a diagnosis of MS, a disease that leads to disability during a person’s most intense period of professional and family life [15]. It has been suggested that the prevalence of depression in patients with MS may be higher in persons with higher Extended Disability Status Scale (EDSS) scores [16]. However, a meta-analysis conducted by Peres et al observed a higher incidence of depression in MS patients with an EDSS score of <3 points compared to a group with a higher EDSS (26.69% vs 22.96%, respectively) [3]. The relationships between obesity and depression in patients with MS has not been studied extensively so far. A cross-sectional study conducted in an Italian population confirmed that depression was more than twice as likely to occur in MS patients with obesity compared to patients with normal weight [16]. A potential factor indirectly affecting the development of depression is increased concentration of pro-inflammatory cytokines, which accompanies excessive adiposity [17]. However, a study analyzing body composition found no significant relationships between%BF and depression in patients with MS [18].

The progression of MS is associated with the loss of mobility, manual dexterity, and strength. Therefore, neuropsychiatric symptoms, especially depression, occur frequently in this group of patients, either as one of the first symptoms of the disease, even before diagnosis, or at the later stage of the disease [15]. Analyses of the relationship between motor disability and depression in patients with MS are rare. The mechanisms linking the changes in motor functions and depression symptoms have also not been explained to a satisfactory degree. Studies among patients with different neurological disorders, including MS, showed that depression was more intense in a cohort with gait and balance deficits compared to the control cohort. A study conducted among individuals with MS from Israel observed that depression symptoms were related to a self-assessment of gait, but not to quantitative parameters of gait [19]. Conversely, a study conducted among a Spanish population did not confirm a relationship between depression balance or walking ability [20]. Patients with MS who underwent physical activity counselling showed fewer depression symptoms after 6 months of observation [21]. It has been suggested that the mechanism responsible for alleviating depression symptoms are improvements in behavioral activation.

Little is known about the mutual relationships between PA, motor function, body composition, and depression symptoms in persons with MS, and determining these relationships is difficult due to a high individual variation in MS progression and duration and subjective self-assessment of disability. There is no doubt that PA should be considered the foundation of behavioral activation in persons with MS. Physical activity also plays an important role in maintaining motor function of the lower and upper limbs and reducing fat tissue [22]. Determining the contribution of walking and upper-limb function, hand strength, body composition, and PA as factors that may be associated with depression symptoms will allow estimation of the risk related to the potentially achievable levels of PA in patients with MS during intervention programs. In Poland, extensive research on factors related to the prevalence of depression in patients with MS has not been conducted to date. Consequently, the aim of this study was to investigate the relationship between body composition, physical activity, motor functions, and depressive symptoms in patients with MS in the Świętokrzyskie Voivodeships in Poland.

Material and Methods

This cross-sectional study was performed in a neurology clinic between October 2021 and January 2022 among 110 patients with MS (84 women and 26 men) with and without depression. The diagnosis of MS, according to the McDonald criteria 2017: for brain and spinal cord using MRI and observation of changes over time and space [23] was confirmed by 2 neurologists specializing in diagnosis and treatment of patients with MS. The primary inclusion criteria were a diagnosis of MS, age 18–65 years, and <7 points on the Expanded Disability Status Scale (EDSS). To avoid a potential bias, persons with ≥7 points on the EDSS scale and those with concomitant severe conditions (cancer, stroke, severe forms of mental illness, anxiety disorders, orthopedic and other neurological diseases limiting the movement of upper and/or lower limbs) were excluded from the study. The following information was collected in this study: the participant’s sociodemographic data, form of MS, age at diagnosis, drugs used, and comorbidities.

Methods

A questionnaire was used in this study to assess depression symptoms and collect data concerning anthropometric measurements, analyze body composition, and perform an objective evaluation of physical activity. Depression symptoms were evaluated using the Beck Depression Inventory-II (BDI–II), which is one of the most commonly used psychometric tools, with a high level of reliability and ability to distinguish between individuals with and without depression [24]. BDI–II is widely used in research and clinical practice throughout the world. The results of psychometric analyses of the Polish version of the BDI–II questionnaire have confirmed that it is highly accurate for diagnosis of depressive disorders and assessment of intensity [25].

This self-report inventory comprises 21 items on the occurrence of depression symptoms over the preceding 2 weeks. The responses to all items were rated on a 4-point Likert scale (from 0 to 3 points), with the total score ranging from 0 to 63 points. A score of 14–19 points is classified as a mild depression, 20–28 points as moderate depression, and 20–63 points as severe state. Medical interviews were used to collect information about the general health of the participants, including disorders and factors affecting the intensity of depression symptoms [26].

All anthropometric measurements, including waist circumference (WC), body height, body mass, body composition, and BMI, were made or calculated by trained nurses using standard protocols and techniques [27]. For height measurement, each participant was asked to stand barefoot, with the arms extended along the trunk and the head in the Frankfurt plane. Height was measured from the front using a Harpenden anthropometer based on 2 anthropometric points: basis-vertex. Waist circumference was measured using an anthropometric tape in a standing position, at the mid-point between the iliac crest and the lower edge of the ribs, at the line of the navel. Both measurements were taken with an accuracy of up to 0.1 cm. Body mass and body composition were analysed using a Tanita MC-780MA-N analyzer. Each participant was asked to take off their jewellery and stand in their underwear on the platform, with the arms extended along the trunk and the feet touching the electrodes. At the supervisor’s signal, the participant grabbed the grips (at 2 locations) and maintained this position without moving. After the measurement, the participant stepped down from the platform and put the grips back to their original places.

All measurements using the bioimpedance method were taken according to the latest standards for this method [28].

Hand grip strength was measured in a sitting position (twice for each hand), with the participant’s arm flexed at the elbow joint, using a Kyto hand dynamometer with a power of 290 lbs/90 kg. The analysis was based on the mean values for dominant and non-dominant hands grip strength separately, with the sum of the mean values for each hand and relative strength calculated individually for each participant according to the formula: (sum of strength (kg)/body mass (kg)). The participant’s disability status was determined using the EDSS [29]. The motor function of the upper limbs was assessed using the 9-Hole Peg Test (9-HPT), which is a standardized, quantitative test used to measure finger dexterity [30]. During this test, each participant inserted 9 pegs, one at a time, into the holes in a box and then took them out one by one, as quickly as possible. Each study participant performed the test with the dominant and non-dominant hand twice. The average time needed to complete both attempts with each hand separately was used in further analyses. The test was conducted according to the current protocol [30]. The motor function of the lower limbs was assessed using the Timed 25-Foot Walk (T25-FW) test, which is the most objective assessment of walking disability and can be used in a broad spectrum of walking disabilities in individuals with MS [31]. During this test, each participant walked 7.6 m (25 ft) along a set course, as quickly as possible, in a safe manner. Participants performed each test twice, and the mean time was used for statistical analyses. Physical activity (PA) was assessed objectively using an ActiGraph GT3X-BT GTIM accelerometer. The participants wore the device on their non-dominant wrist for the mean period of 8 days, maintaining their normal activity each day. Every ActiGraph photograph was registered in a separate diary. In addition, the participants were asked to take off the device before getting into contact with water. Many studies indicate that wearing an ActiGraph on the wrist is better tolerated by patients with MS [32] while providing similar activity patterns to those assessed with an ActiGraph worn on the ankle and self-reported patterns of physical activity based on questionnaires. Wearing the device on the wrist also helps to detect activities requiring intense movement of the arms [33]. The data obtained using the device were analysed using ActiLife 6.0. Data Analysis Software. The statistical analysis included days (weekdays and weekends), during which the accelerometer was worn for at least 10 hours (from 6: 00 a.m. to 11: 00 p.m.). Non-wear time was defined as a period of at least 60 consecutive minutes of zero counts and was erased. PA data were collected in 10-second epochs at a 30 Hz frequency [33].

The study was approved by the Bioethics Committee of the Collegium Medicum at the Jan Kochanowski University in Kielce (Approval No. 24/2020 of 25 April 2020). This article follows the STROBE guidelines.

Statistical Analyses

Sample size (N=84) was determined with an effect size 0.4, a 5% probability of type I error, and a 95% confidence interval, based on a known percentage of persons with MS in Świętokrzyskie Province in Poland (N=1384); (G*Power; German) [34]. The distributions of continuous variables were analyzed using the Shapiro-Wilk test.

Arithmetical means and standard deviations were calculated. The significance of differences between the means was calculated using the Student’s t-test or, in case of a non-normal data distribution, the Mann-Whitney U test. Cardinality and percentage indicators were calculated for the categorical variables (eg, sex, form of MS, and comorbidities), while differences in their distribution in relation to the BDI–II score were estimated using the chi-square test. A univariate and multivariate logistic regression analyses were performed to determine the likelihood of the occurrence of depression symptoms, depending on the analyzed variables. The multivariate model included those variables that were found to be significant through the univariate analysis and/or displayed statistically significant differences between the groups of participants with depression (BDI–II score ≥14) and without depression (BDI–II score <14). Due to the strong correlation between 9-HPT results of the dominant and non-dominant hand (Spearman rank correlation rho=0.8; P<.001), models were presented separately for motor function of each upper limb. In the presented models, 9-HPT-dominant hand or 9-HPT non-dominant hand, T25-FW,%BF, and age (due to the large age range in the study group) were used as predictors. Full models (model I) and final models obtained using the backward stepwise method (model II) are presented. Assumptions for the models were tested and a correlation matrix was made for the predictors. The correlation coefficients ranged from 0.1 to 0.39; linearity: P (LR) >.05; fit: Hosner-Lemeshow test for a model with dominant hand P=.546; for a model with non-dominant hand: P=.087. Statistical analysis was performed using the STATISTICA.PL 13.3 software (STATSOFT Sp. z o.o., KRAKÓW, PL, 2017). Significance was assumed at P<.05.

Results

The study group (N=110) consisted of 76.4% women and 23.6% men with a mean age of 43.1±11.9 years. Relapsing-remitting MS was reported in most participants (90.0%); however, regardless of the diagnosed form of MS, patients EDSS were between 1.5–6; mean±sd: 2.46±1.46; median: 2.0. Depression symptoms (BDI–II score ≥14) were observed in a total of 24.55% of the participants, with 11.82%, 8.18%, and 4.55% of the participants displaying mild, moderate, and severe depression, respectively. The analysis of BDI–II score in all participants revealed that changes in sleeping pattern (x=0.94), lack of energy (x=0.89), and tiredness or fatigue (x=0.89) were the most frequently experienced symptoms (Figure 1).

Figure 1.

Mean values of individual BDI–II items in person with multiple sclerosis (total group). 1 – feeling sad; 2 – pessimism; 3 – past failure; 4 – lost of pleasure; 5 – guily feelings; 6 – punishment feelings; 7 – self dislike; 8 – self-criticalness; 9 – suicidal ideations; 10 – crying; 11 – agitation; 12 – lost of interest; 13 – idencisiveness; 14 – feeling of worthlessness; 15 – loss of energy; 16 – change in sleeping pattern; 17 – irriatability; 18 – change in appetite; 19 – concetration difficulty; 20 – tiredness or fatigue; 21 – loss of interest in sex.

No significant differences in sex, age, form of MS, time since diagnosis, and comorbidities were found between the group with symptoms of depression and those without them (Table 1). The individuals with MS and depression symptoms were more likely to have adiposity (%BF) compared to individuals without symptoms of depression (OR=1.07; 95% CI: 1.01–1.13; P=.026) and a higher fat mass (Me: 21.45 vs 18.30; P=.036), but in the latter case, the OR did not reach statistical significance (OR: 1.04;95% CI: 0.99–1.09; P=.065). However, the analysis of the motor function of limbs demonstrated that individuals with depression performed significantly worse in the T25-FW (5.58 vs 4.61; P=.001) and 9-HPT tests. The ORs for the dominant and non-dominant hand in the 9-HPT was 1.16 (95% CI: 1.05–1.28; P=.002) and 1.08,(95% CI: 1.01–1.14; P=.025) respectively. The differences in the results of the other functional tests and physical activity were statistically insignificant.

Table 1.

Baseline characteristic of multiplex sclerosis patients by severity of depression.

Variables		Without depression (BDI–II <14) N=84		With depression (BDI–II ≥14) N=26		p	OR (95% CI)	p
Gender N;% (95% CI)	Men	20	23.81	4	15.38	0.363u	ref.	0.367
	Women	64	76.19	22	84.62		1.72 (0.53–5.58)
Age (years) X±SD; Me (IQR)		42.09±11.33	42.00 (16.50)	46.85±13.25	49.00 (19.00)	0.072t	1.04 (0.99–1.08)	0.078
Period of MS (years) X±SD; Me (IQR)		10.27±7.85	8.00 (12.00)	12.41±10.43	10.00 (16.00)	0.491u	1.03 (0.98–1.08)	0.232
Types of MS N; %
RRMS		77	91.67	22	84.61	0.265c	ref.
SPMS		5	5.95	3	11.54		2.20 (0.49–9.96)	0.306
PPMS		2	2.38	1	3.85		3.67 (0.49–27.60)	0.207
Comorbidities	No	52	61.90	15	57.69	0.840c	ref.
	Yes	32	38.10	11	42.31		1.10 (0.45–2.66)	0.840
Somatic traits X±SD; Me (IQR)
Body height (cm)		168.33±8.38	168.00 (12.50)	167.07±15.02	68.40 (21.90)	0.141t	0.98 (0.93–1.04)	0.515
Body mass (kg)		69.37±15.62	66.65 (19.65)	71.99±15.02	68.40 (21.90)	0.410u	1.01 (0.98=1.04)	0.474
WC (cm)		81.95±13.53	80.00 (16.50)	85.41±13.87	83.00 (21.00)	0.296u	1.02 (0.98–1.05)	0.273
BMI (kg/m2)		24.39±4.69	23.40 (5.05)	25.81±5.41	24.80 (6.20)	0.254u	1.06 (0.97–1.15)	0.215
% BF		26.82±8.22	27.05 (9.35)	31.03±7.61	30.00 (10.60)	0.022t	1.07 (1.01–1.13)	0.026
Fat mass (kg)		19.23±9.40	18.30 (9.50)	23.32±9.98	21.45 (13.10)	0.036u	1.04 (0.99–1.09)	0.065
VFL		5.48±3.61	5.00 (4.50)	6.81±4.95	5.00 (5.00)	0.300u	1.08 (0.97–1.20)	0.149
FFM (kg)		50.13±9.55	47.85 (14.15)	46.90±6.72	46.70 (7.90)	0.997u	0.99 (0.94–1.04)	0.679
PMM (kg)		47.61±9.10	45.45 (13.45)	46.90±6.72	46.70 (7.90)	0.997u	0.99 (0.94–1.04)	0.677
Physical activity and sedentary behaviour X±SD; Me (IQR)
VMC (106 counts/day)		1808.2±604.4	1671.7 (672.7)	1667.8±377.6	1684.8 (531.1)	0.295u	1.00 (0.99–1.01)	0.292
% of sedentary time		62.10±6.99	63.05 (8.82)	62.72±6.48	61.21 (11.96)	0.685t	1.01 (0.95–1.08)	0.681
% in LPA		22.37±3.60	22.29 (4.03)	22.86±4.22	22.02 (5.60)	0.560t	1.04 (0.01–2.21)	0.168
% in MVPA		15.53±5.66	14.79 (6.58)	14.42±4.00	14.48 (6.59)	0.348t	0.96 (0.88–1.05)	0.346
Functional fitness X±SD; Me (IQR)
EDSS score (pts)		2.46±1.46	2.00 (2.00)	2.61±1.66	2.50 (2.00)	0.423u	1.09 (0.82–1.46)	0.418
T25-FW (sec)		5.76±4.87	4.61 (1.35)	6.30±2.01	5.58 (3.04)	0.001u	1.11 (0.96–1.28)	0.166
9-HPT, dominant hand (sec)		20.16±3.77	19.39 (4.19)	24.02±7.24	20.73 (9.39)	0.018u	1.16 (1.05–1.28)	0.002
9-HPT, non-dominant hand (sec)		22.04±5.66	20.66 (4.49)	26.20±10.36	22.89 (10.61)	0.060u	1.08 (1.01–1.14)	0.025
Dominant hand grip strenght (kG)		39.46±22.28	30.00 (19.80)	36.73±21.32	29.20 (19.30)	0.577u	0.99 (0.971.02)	0.549
Non-dominant hand grip strenght (kG)		35.97±19.71	27.85 (23.35)	33.97±22.23	27.85 (27.60)	0.657u	0.99 (0.97–1.02)	0.637
Sum of strenght (kG)		37.71±20.27	29.28 (20.63)	35.35±21.52	29.20 (21.55)	0.545u	0.99 (0.97–1.02)	0.580
Relative strength to body mass (kG/kg)		0.55±0.26	0.46 (0.30)	0.51±0.31	0.40 (0.35)	0.201u	0.56 (0.10–3.07)	0.501

X – arithmetic mean; SD – standard deviation; Me – median; IQR – interquartile range; p – significance level; u – U-Mann-Whitney test; t – Student test; c – chi square test; OR – odds ratio; CI – confidence interval; RRMS – relapsing-remitting multiple sclerosis; SPMS – secondary progressive multiple sclerosis; PPMS – primary progressive multiple sclerosis; WC – waist circumerence; BMI – body mass index; %BF – %body fat; VFL – visceral fat level; FFM – fat free mass; PMM – predictive muscle mass; VMC – vector magnitude counts; LPA – light physical activity; MVPA – moderate-to-vigorous physical activity; 9-HPT – Nine-Hole Peg Test; T25-FW – Timed 25-Foot Walk.

Next, a multivariate analysis of logistic regression was conducted. The analysis included 3 factors regarded as significantly increasing the probability of depression symptoms: %BF, T25-FW, and 9-HPT (2 separate models for the dominant and non-dominant hand) while controlling for age. In the multivariate model I, only higher%BF was associated with a greater risk of depression (OR: 1.09; 95% CI: 1.02–1.19; P=.012; model with 9-HPT – dominant UL; OR=1.09; 95% CI: 1.02–1.17; P=.010, model with 9-HPT non-dominant UL). Final model (model II) demonstrated, that higher%BF values (OR=1.09; 95% CI: 1.02–1.16; P=.001) and poorer results of 9-HPT for both hands (dominant: OR: 1.07 95% CI: 1.01–1.15, P=.043; non-dominant: OR: 1.10; 95% CI: 1.01–1.18; P=.025) significantly increased the probability of depression occurrence (Table 2).

Table 2.

Multivariate logistic regression for multiple sclerosis patients with depression symptoms.

Variables	Model I (full)			Model II (backward step regression analysis model)
	OR	95% CI	p	OR	95% CI	p
Model with 9-HPT, dominant hand
%BF	1.09	1.02; 1.19	0.012	1.09	1.02; 1.16	0.009
9-HPT, dominant hand (sec)	1.08	0.98; 1.19	0.104	1.07	1.01; 1.15	0.043
T25-FW (sec)	0.94;	0.76; 0.1.17	0.562	–	–	–
Age (years)	1.03	0.98; 1.07	0.238	–	–	–
Model with 9-HPT, non-dominant hand
%BF	1.09	1.02; 1.17	0.010	1.09	1.02; 1.16	0.008
9-HPT, non-dominant hand (sec)	1.12	0.99; 1.27	0.065	1.10	1.01; 1.18	0.025
T25-FW (sec)	0.91	0.72; 1.15	0.425	–	–	–
Age (years)	1.02	0.98; 1.07	0.336	–	–	–

OR – odds ratio; CI – confidence interval; p-significant level; %BF – % body fat; 9-HPT – Nine-Hole Peg Test; T25-FW – Timed 25-Foot Walk.

Discussion

The results of this study showed that depression was a very frequent comorbidity of MS, and that higher adiposity and worse motor function of the upper limbs was correlated with a higher probability of depression.

The performed observations related to the effect of excessive fat tissue on the intensification of depression symptoms confirm the results obtained in studies conducted among a population of healthy individuals [35], as well as some results obtained among a group of patients with MS [14,22]. A study by Marck et al conducted on a large group of patients with MS (N=2399) demonstrated that overweight and obesity were associated with worse mental health compared to individuals with a normal BMI, whereas obesity by itself increased the probability of depression by 2.2 times [22]

A 2.5-year-long (N=1441) observation showed that while excessive weight as determined based on the BMI was associated with a higher risk of depression, these relationships were statistically insignificant in the multivariate model [14]. It is important to note that BMI does not differentiate between fat and lean body mass and bone mass, and it may also lead to an underestimation of obesity in patients with MS [36]. However, this study did not confirm the results obtained by Silveira et al, who did not observe any significant relationship with increased depressive symptoms in their analysis of%fat mass [18]. This discrepancy may be due to use of different research methodologies, including the method of assessing depression symptoms.

The relationships between depression symptoms and obesity can be explained through several mechanisms. Most notably, an increase in the pro-inflammatory cytokine concentration, which accompanies excessive adiposity, seems to contribute to development of depression [22]. During the early stages of obesity, selectively enhanced expression of inflammatory genes in fat tissue has been reported. Consequently, fat tissue seems to function as a primary tissue that responds to a high-fat diet (HFD) and initiates inflammation in persons with obesity [37]. Increased levels of pro-inflammatory compounds in patients with overweight and obesity may breach the blood–brain barrier and stimulate neuroinflammation, which in turn not only affects the structures of the central nervous system (CNS), but is also associated with increased prevalence of CNS disorders, including depression and cognitive disorders. Furthermore, MS is accompanied by persistent mild inflammation that is related to an unfavorable profile of cytokines in fat tissue and serum [38]. Depression also develops as a result of immune disorders, suggesting a relationship between depression and the inflammatory process, rather than as a result of psychosocial stress [37]. Another potential mechanism linking obesity with depression is the dysregulation of stress responses along the hypothalamic–pituitary–adrenal axis [22].

Our findings are consistent with previous investigations on motor function of upper limbs and depression symptoms. In a study by Maier et al, correlations between depressive symptoms measured using the Beck scale and 9-HPT performance were moderate and positive in a group with 32 RRMS [39]. Alonso et al observed similar results, which were confirmed in single and multivariate regression analyses [40]. This may also be related to the fact that reduced motor function of the upper limbs is usually accompanied by other neurological disorders, including hand trembling, sensory disorders, and reduced hand strength [40]. Bertoni et al [41] observed that 35% of patients with MS who showed reduced motor function of the upper limbs performed fewer domestic chores. This also included patients with EDSS <4 points [40,41], as in our study.

The 9-HPT score is used to complement the EDSS and T25-FW, which primarily involves assessing gait and, as such, is largely insensitive to disability in the upper limbs [31]. In contrast, upper-limb motor function and dexterity may directly affect everyday activities and independence [40–42]. Difficulties with performing everyday activities may lead to frustration and reduced feeling of self-efficiency and control, which are depression symptoms [1]. Hand function disorders may be related to a feeling of complete dependence on other persons. Furthermore, as a study by Orbach et al showed, the inclusion of 9-HPT and T25-FW in assessment of patients with MS increased the diagnosis rate of MS progression by 2 or 3 times [43], while the use of 9-HPT improved the diagnosis rate of MS progression by 9.7% compared to the total EDSS score (34.4% vs 24.7%, respectively) [16]. Consequently, motor dysfunction of the upper limbs may correlate better with depressive symptoms, as with every other indicator of disability. However, they may also result from the degenerative changes in the brain that are observed over the course of MS, which may also cause depression [44].

The lack of a significant relationship between the EDSS score and/or duration of MS and depression observed in this study is also consistent with the results obtained by some [10,29] but not all authors [13]. Although a Brazilian study found a difference in the assessment of disability in patients with and without depression (2.6 vs 3.9, respectively), this difference was statistically insignificant [10]. A study conducted in the Netherlands, found no significant relationship between disease duration and depression over 10 years of observation, and found a significant increase in the results related to disability [45]. Conversely, a Canadian study showed that individuals with MS and depressive symptoms had higher EDSS scores than individuals without mental comorbidities [8]. Studies analyzing the BDI observed a positive correlation between the BDI–II score and disability and disease course in an Italian population [16]. The age of patients and different neurological disability status might explain these differences. In our study, the disability status was lower (<3), patients were older, and they had similar disease duration. In our study, the T25-FW test also did not show statistically significant relationships with depression in the multivariate model, even though the patients with depressive symptoms performed significantly worse, on average, than the patients without depression. Therefore, our observations partially confirm previous results on motor function of lower limbs and depression symptoms. A study conducted by Kalron and Aloni demonstrated a stronger relationship between depression and self-assessment of gait than between depression and the quantitative parameters of gait in patients with MS [19]. Kalron and Aloni also suggested that the different relationships between depression and gait may have resulted from the participant’s overall disability status. However, the participants displayed a higher degree of disability than in the present study (EDSS: 2.9±1.7), whereas the gait assessment was more extensive. Similar conclusions were reached by Silič et al, who analyzed the relationships between the 12-item Multiple Sclerosis Walking Scale (MSWS-12) and Hospital Anxiety and Depression Scale in 2 subscales: anxiety and depression [46]. Other researchers also reported relationships between gait function and individual symptoms of depression (fatigue and lack of perceived self-efficacy) [31]. Previous research on the relationship between T25-FW and depression does not clearly explain the relationship between these issues. It can be assumed that in our study the low disability status only concerned hand function, which the EDSS scale and T25-FW tests could not detect. T25-FW and EDSS scales are comprehensive assessment tools that encompass different aspects of neurological functions, relying predominantly on the assessment of gait; and while difficulties with walking are a cause for concern, they do not directly and immediately affect everyday activities [47]. They can also be partially compensated for with the use of rehabilitation equipment.

The results of our study did not confirm any relationship between PA and the occurrence of depression. Previous studies indicate that PA-based interventions among patients with MS provide a beneficial effect in the form of reducing the risk of depression [46]. A study by Suh et al involving path analysis demonstrated an indirect relationship between physical activity in patients with MS and depression symptoms in an early stage of the disease (<5 years). Disability played an indirect role in this analysis [48]. However, in this study, the participants self-reported their disability. A meta-analysis conducted by Ensari et al found a small but statistically significant effect of activity on alleviating depression symptoms [49]. In general, persons with MS are less physically active than healthy persons, or even persons with other diseases [50]. According to some reports, the decreased PA results primarily from the chronic nature of MS, rather than disability status [51]. Therefore, it seems reasonable to undertake activity in MS as early as possible.

The results of our study are consistent with the results obtained by Jones et al [52], who assessed PA in 441 persons with MS using ActiGraph. The observed differences in the number of steps taken among groups with low and moderate depression was significant, but once other potential confounding variables were accounted for (age, disability, and years of MS and education), the differences in the number of steps were insignificant. The patterns of physical activity were also insignificant [52]. In an earlier study by Jenssen et al, moderate PA was associated with depressive symptoms, but significant differences only concerned middle-aged persons (45–64 years) [53]. However, it was a questionnaire study.

The lack of significant differences in patterns of PA may result from symptoms accompanying MS other than depression, such as changes in progression of depression, fatigue that accompanies the disease, increased disability due to increased depressive symptoms, or an overall low level of PA in patients with MS [53]. Furthermore, indirect relationships between PA, fat tissue, and motor function of limbs also seem to be important. Physical activity may have had an indirect effect on the risk of depression by affecting obesity [26] and leading to worse motor function performance. It has been suggested that a low level of PA is responsible for increase in fat tissue, which in turn shows a relationship with the symptoms of increased fatigue in patients with MS, resulting in a secondary reduction of activity. In turn, the ‘vicious circle’ effect may be significant for reducing motor function, and thus increasing disability [28].

This study has several limitations. First and foremost, its sample size is relatively small. Furthermore, most of the participants had relapsing-remitting MS, which made it difficult to generalize the obtained results to other types of MS. The assessment based on the BDI–II scale was of a screening nature and demonstrated the presence of specific symptoms related to depression, but its results cannot be regarded as a final diagnosis of depression. Also, no data were available concerning an earlier diagnosis of depression, the use of antidepressants, and fatigue symptoms among the participants. This may prevent a full understanding of the mutual relationships between depression, physical activity, motor function, and the EDSS [1,19,53]. Moreover, due to the cross-sectional design of the study, the causal relationships between the analyzed variables could not be determined. We emphasise that the tests (such as the 9-HPT and T25-FW) utilized in the assessment are widely recognized as the standard for evaluating motor function. Moreover, the 9-HPT was found to be highly effective in the assessment of MS progression over time and to be more sensitive to its treatment than any other test [11,12].

Conclusions

Our study demonstrated that higher body fat percentage, lower PA, and lower motor function of limbs are associated with a higher risk of depressive symptoms in persons with MS. Since higher adiposity (%BF) among patients with MS was associated with a higher likelihood of depressive symptoms, patients with MS should change their lifestyle to reduce excessive fat tissue. A lower motor function of the upper limbs in patients with MS was also associated with depressive symptoms. Thus, a detailed evaluation of the patient’s manual dexterity should constitute an integral part of the functional assessment of patients with MS. The information obtained in our study may help to better identify patients with depression, thereby affecting therapeutic decisions and improving the patients’ quality of life.