Impact of Nutrition Counselling on Multiple Sclerosis Patients Nutritional Status: Randomized Controlled Clinical Trial

doi:10.21203/rs.3.rs-1425231/v1

Background: Faulty dietary habits and overnutrition are prevalent among Egyptian multiple sclerosis (MS) patients who do not receive nutrition care as part of treatment. This study was conducted to explore the impact of nutrition counselling on the nutritional status of MS patients.

Methods: A single-blinded, parallel randomized controlled clinical trial (RCT) was conducted at Kasr Alainy MS Unit (KASMU) on 120 Eligible MS patients from September 2019 to February 2020. Patients were randomly allocated to either Nutrition counseling intervention group (IG) or control group (CG). Allocation concealment was done by sequentially numbered opaque sealed envelopes. All patients were assessed initially then followed the KASMU standard management protocol for the study period. Only patients in the IG underwent initial teaching sessions followed by monthly evaluation (nutrition counseling). All patients were assessed at the end of end of 3 month follow up period. Sociodemographic data was gathered through a structured interview. Nutritional status was assessed anthropometrically, by 24-hour recall and by Malnutrition Universal Screening Tool (MUST). The 2 groups were compared initially and at the end of follow-up. Analysis of covariance (ANCOVA) was used to analyze the difference between the two arms in quantitative outcomes. Chi-squared or Fisher's exact tests, and Mann-Whitney U test were used in quantitative outcomes. The alpha value (α) was set at 5%. Both Intention To Treat (INT) and Perprotocol (PP) analyses were performed.

Results: At baseline assessment, the prevalence of overweight and obesity was 31.7% and 32.5% respectively, mean body mass index (BMI) was 27.7 ± 5.7 kg/m². The mean waist circumference was 93.5±11.9 and 99.2±13.1 cm for males and females, respectively. About 27.3% of males and 83.9% of females showed abdominal obesity. After 3 months of counseling, weight, BMI, waist circumference, food consumption and nutrient intake and adequacy significantly improved in the IG (p<0.05).

Conclusion: Nutrition counselling significantly improved anthropometric measurements, food consumption, nutrient intake and adequacy. The study was registered on ClinicalTrial.gov and was given a code (NCT04217564).

Multiple sclerosis

RCT

nutritional counseling

overweight/obesity

macronutrients

micronutrients

Multiple sclerosis (MS) is the most common non-traumatic disabling disease that affects young adults [1]. MS leads to physical and cognitive disability [2]. According to the MS International Federation (MSIF), one out of every 3,000 people in the world is living with MS. In Egypt, 9,244 new subjects are diagnosed with MS every year (10 new cases/100,000 population/year). Egypt is one of the few notable countries where the reported prevalence tripled from 20/100,000 in 2013 to 59.7/100,000 in 2020. Accordingly, one in every 1,500 Egyptians currently lives with MS [3].

MS patients were reported to have a double burden of malnutrition; overweight and obesity occur initially, then weight loss and cachexia follow when disability is advanced [4]. A study conducted in Egypt at Kasr Alainy Multiple Sclerosis Unit (KAMSU) revealed a high prevalence of malnutrition among the relapsing remitting MS (RRMS) patients attending the clinic (67.1%). About a quarter (27.6%) of the studied patients was overweight, 36.8% were obese, and 2.6% were underweight. Unhealthy dietary habits were prevalent among considerable proportions of this group of patients, such as eating junk food, only a few meals, and skipping breakfast [5].

Although there is no solid evidence to support following a specific diet for MS patients, adherence to the dietary guidelines and adopting a healthy lifestyle are suitable choices [6]. Dietary interventions have been claimed to improve the nutritional status of MS patients. In a clinical setting, nutritional care is provided through nutritional counseling. The goal of nutritional counselling is to produce a desirable change in food behaviour to achieve and/or maintain a healthy body weight, macronutrient balance, and micronutrient adequacy. It is a two-way interaction through which a client and a trained counsellor interpret the results of a nutrition assessment, identify individual nutrition needs and goals, discuss ways to meet these goals, agree on next steps, and focus on practical actions to address nutrition needs as well as the benefits of behaviour change [6, 7].

The aim of this study was to identify the effect of nutritional counselling on MS patients’ nutritional status. This might provide evidence for the value of counselling in such a setting and pave the way for integration of nutritional counselling into the routine management of MS patients.

Study design, setting, and population

The researchers conducted a single-blinded, parallel randomized controlled clinical trial (RCT) among multiple sclerosis patients registered at KAMSU, Faculty of Medicine, Cairo University. The patient flow rate was between 13 and 25 patients per working day.

Sample size, recruitment of participants, and randomization technique

The sample size was calculated using Statcalc [8]. Assumptions for the calculation of sample size were a percentage of outcome (bad dietary habits and/or high BMI) in the non-exposed 70% [5], relative risk 0.6, alpha 0.05, and power 80. The calculated sample size was 100, 50 intervention subjects, and 50 control subjects [9]. Assuming a 20% drop out rate, the sample size became 120 patients: 60 intervention and 60 controls.

Patients whose records fulfilled the inclusion criteria (diagnosed with Relapsing Remitting MS (RRMS), Secondary Progressive MS (SPMS), or Primary Progressive MS (PPMS), both sexes, aged 20 to 65 years and having finished their secondary school education, its equivalents, or higher education) were included. We excluded patients having Clinically isolated syndrome (CIS), a relapse, those known to have diabetes mellitus, malabsorption syndrome, food allergy to some food items such as milk and wheat, patients who underwent bariatric surgeries, patients on special diets, pregnant or lactating women, and patients receiving drugs that affect appetite, e.g., psychotropic drugs, or patients receiving steroids. Eligible patients who consented to participate in the study (120 patients) were randomized by block design into either a control (CG) or an intervention group (IG). The randomization ratio was 1:1. The block size was 4 [10].

The allocation was concealed in sequentially numbered opaque sealed envelopes. Each participant chose a sealed envelope and was assigned to the intervention group specified in that envelop. Figure 1 shows the participants' flow during the study.

Study phases

Preparatory Phase

The researchers prepared a booklet in Arabic with educational material and instructions to be followed by the study participants. The ChooseMyPlate model was adopted and the concept of food groups with healthy choices from each group was illustrated [11]. Foods for and against MS were emphasized [12, 13]. Dietary records were included in the booklet to check patients' adherence to the instructions. Color coded sets to measure the quantity of different foods were purchased, and cards to illustrate each bushel in household equivalents were printed.

Preintervention phase (the initial assessment)

The following data was gathered through a structured face to face interview and/or measurement:

1. Personal and sociodemographic data (age, gender, marital status, occupation, education, residency, and telephone/mobile number).

2. 24-hour Dietary recall, detailed data about food preparation, ingredients in mixed dishes, and the brand names of different commercial products. The amounts of each food consumed were estimated using standard measuring cups and spoons, as well as common size containers (e.g., bowls, cups, and glasses) [12].

Daily nutrient intake was analyzed using National Nutrition Institute food composition tables for Egyptian foods [14]. Patients were classified according to their level of consumption compared to the FAO, WHO, and UNU, 2001 human energy requirements [15] and the FAO and WHO 2001 human vitamin and mineral requirements [16]. Consumption < 50% was considered an unsafe, ≥ 50–75% was considered unacceptable, > 75–120% was considered acceptable, and > 120% was considered over consumption [15, 16].

3. Anthropometry. Measurements were taken according to CDC Anthropometry Procedures Manual [17]. Weight was measured by the German Beurer Glass Bathroom Scale model GS11. Height was measured by the Indian wall-mounted DESCO stature meter (Model HSHA 101) with a resolution of 0.5 cm. Waist circumference was measured using a measuring tape at the end of a normal expiration to the nearest 0.1 cm. BMI was calculated using the standard formula weight (kg)/height (m)². The cutoff points for waist circumference are those set by the World Health Organization (WHO) [18]. Waist circumference of > 94 cm in males or > 80 cm in females indicated increased risk of metabolic complications. Waist circumference of > 102 cm in males or in > 88 cm females indicated substantially increased risk of metabolic complications.

4. Malnutrition Universal Screening Tool (MUST). A five-step screening tool for adults who are malnourished, at risk of undernutrition, or obese. An overall risk of malnutrition score was derived. Patients were classified into low, medium, or high risk of malnutrition if their scores were 0, 1 or ≥ 2 respectively. Management guidelines and/or local policies were used to develop the care plan [19].

Intervention (only for the intervention group):

Each patient was scheduled to receive 3 sessions 4 weeks apart. The first session was for counselling. The second and the third were to follow on patient's adherence to the nutrition plan and to answer any questions he/she has.

i. Each patient was individually counseled. Dietary intake during the last 24 hours, daily effort practice of sports, sedentary habits, exposure to sun and dietary supplement intake were identified. Patient caloric requirements were calculated by the Harris Benedict equation [17]. It was adjusted according to BMI, unintentional weight loss of 5% or more of his/her body weight in the previous 3–6 months and overall MUST score. Patients with acceptable BMI (20 to 25 kg/m2) [20, 21] who did not report an unintentional weight loss of 5% or more of their body weight in the previous 3–6 months were given diet menus that met their daily caloric requirements to stay on track. Patients with medium or high risk of undernutrition according to MUST [20, 21] with BMI of ≤ 20 kg/m2 and/or patients who reported unintentional weight loss of 5% or more of their body weight in the previous 3–6 months received diet menus with 500 kcal extra to their daily caloric requirements to gain 0.5 kg/week [21, 22]. Overweight and obese patients (BMI ≥ 25 kg/m²) received diet menus with a daily caloric restriction of 22% of their daily caloric requirement [23]. A tailored diet menu was provided considering the patient preferences and economic classes.

At the end of the counseling session, each patient received a package containing a booklet of instructions, dietary compliance records, foods and beverages color-coded measuring set, a card illustrating household equivalents of each bushel of the color-coded set and the tailored diet menu. A WhatsApp group was created and all patients who had smart phones and WhatsApp accounts (100% of the patients) were added to the group immediately at the first session. Regular messages were posted by the admin of the group to motivate patients to stick to a healthy diet and to remind them of their follow up and final assessment appointments.

Those in the control group did not receive nutrition counselling during the study period but were instructed to attend for final assessment by the end of the study. Apart from counselling, patients received the same care from the clinic's medical staff. After the final assessment, the control group received the nutritional counselling material to gain its expected benefits.

Post intervention phase (the final assessment):

All patients in the IG and the CG were finally assessed 3 months after the initial assessment. We used the same tools as the initial assessment. Patients of the IG were asked about their compliance (always-often-sometimes-rarely or never) to the prescribed regimen (described by the clinic neurologist in addition to the dietary advice). Patients of the CG group were also asked about their compliance to the conventional regimen prescribed by the clinic neurologist. Patients who reported always, often, or sometimes adherences were considered compliant, while patients who reported rarely or never were considered non-compliers. The statistician analyzing the data was blinded to the study arms.

Statistical analysis

Pre-coded data was fed into the computer using the "Microsoft Office Excel Software 365" program. Data were transferred to the IBM SPSS version 20 Statistical Package for Social Science Software [24] and the R Statistical Environment (version 4.0.2) for statistical analysis [25].

Qualitative variables were expressed in percentages. Quantitative variables were expressed as mean and standard deviation. The IG and CG were initially compared with respect to their sociodemographic and MS disease characteristics (t test, Mann-Whitney U, Chi square and Fisher’s Exact test). Independent variable is counseling, outcome variables are quantitative (weight, BMI, waist circumference, food groups' intake and nutrient intake) and qualitative (BMI categories, risk of metabolic complications, risk of malnutrition, adequacy of intake of nutrients, activity, exposure to sun and supplements). Statistical tests used to assess the effect of counseling were ANCOVA in case of quantitative outcomes, Chi-squared or Fisher's exact test in case of categorical outcomes and Mann-Whitney U test in case of ordinal or continuous, but not normally distributed outcomes. Parametric ANCOVA is robust to violations of either normality or homoscedasticity [26].

Three and four patients (5% and 6.7%) of IG and CG patients did not continue the study till the final assessment. The total dropout rate of the study was 5.8%. All other patients were included in the analysis. Intention to treat analysis (ITTA) was carried out then per-protocol analysis (PPA) of the compliers was done.

Ethical considerations

The study was approved by the Research Ethical Committee (REC) of the Faculty of Medicine, Cairo University, on August 24th, 2019 and given a code (MD-57-2019). All the included patients were treated according to the Declaration of Helsinki. Written informed consent was obtained from each patient after proper orientation regarding the objectives of the study. Data confidentiality and informants’ identity were maintained throughout the study.

Table 1shows the sociodemographic characteristics of enrolled patients (120) at baseline assessment and compares them in the IG and CG. The mean age of enrolled patients was 33.1 ± 7.5 years; females represented more than 70% of them. Regarding education, 41.7% of patients were university graduates, while 45% of them received secondary education or equivalent. Two thirds of patients were married and 53.3% were unemployed or housewives. Most patients lived in urban communities (75.8%); 81.7% of IG and 70% of CG, respectively. All the studied sociodemographic characteristics did not differ significantly between IG and CG (p ≥ 0.05).

Table 1

Sociodemographic characteristics of the studied multiple sclerosis patients at KAMSU*
Characteristics		IG (N = 60)	CG (N = 60)	Total (N = 120)	P-value #
Age in years (mean ± SD)		33.5 ± 8.4	32.7 ± 6.4	33.1 ± 7.5	0.659
Gender, N (%)	Female	44 (73.3%)	43 (71.7%)	87 (72.5%)	0.838
Gender, N (%)	Male	16 (26.7%)	17 (28.3%)	33 (27.5%)	0.838
Education, N (%)	Secondary	28 (46.7%)	26 (43.3%)	54 (45%)	0.459
	Intermediate institutes	8 (13.3%)	4 (6.7%)	12 (10%)
	University graduate	23 (38.3%)	27 (45%)	50 (41.7%)
	Postgraduate degree	1 (1.7%)	3 (5%)	4 (3.3%)
Occupation, N (%)	Non-working/ housewife	29 (48.3%)	35 (58.3%)	64 (53.3%)	0.535
	Unskilled manual worker	3 (5%)	3 (5%)	6 (5%)
	Skilled manual worker/ Farmer	4 (6.7%)	6 (10%)	10 (8.3%)
	Trades/ Business	5 (8.3%)	1 (1.7%)	6 (5%)
	Semi-professional	8 (13.3%)	8 (13.3%)	16 (13.3%)
	Professional	4 (6.7%)	4 (6.7%)	8 (6.7%)
	Student	7 (11.7%)	3 (5%)	10 (8.3%)
Marital Status, N (%)	Married	41 (68.3%)	39 (65%)	80 (66.7%)	0.921
	Single	18 (30%)	20 (33.3%)	38 (31. 7%)
	Divorced	1 (1.7%)	1 (1.7%)	2 (1.7%)
Residency, N (%)	Urban	49 (81.7%)	42 (70%)	91 (75.8%)	0.136
Residency, N (%)	Rural	11 (18.3%)	18 (30%)	29 (24.2%)	0.136
# P-value: Mann-Whitney U test for age, Pearson Chi-Square test for gender and residency, Fisher’s Exact test for education, occupation and marital status Kasr Alainy MS Unit*

RRMS was the major subtype of MS, affecting patients in both IG and CG (85% and 88.3%, respectively). One case in the CG was suffering from PPMS. The 2 groups were comparable regarding MS subtypes and the average disease duration which was 6.6 ± 6.1 and 7.3 ± 4.5 years for the IG and CG, respectively (p ≥ 0.05).

At baseline assessment, the prevalence of overweight and obesity was 31.7% and 32.5% respectively. The mean BMI was 27.7 ± 5.7 kg/m2. About 27.3% of males and 83.9% of females were at a substantially increased risk of metabolic complications due to abdominal obesity. The mean baseline waist circumference was 93.5 ± 11.9 and 99.2 ± 13.1 cm for males and females, respectively. A quarter or more overconsumed energy, carbohydrates, fats and proteins (25%, 25.8%, 31.7% and 78.3% respectively). After randomization, the IG and CG were comparable in almost all outcome variables (anthropometry, nutritional status, nutrient intake, intake of supplements, exposure to the sun, the risk of malnutrition (MUST scores) and activity), p > 0.05. The 2 groups differed significantly in their intake of added fat.

ITTA showed that following intervention, mean weight significantly decreased from 76.9 ± 17.1 to 75.4 ± 15.8 kg in the intervention group while it remained almost the same in the control group (72.4 ± 14.3 and 72.8 ± 14.7 kg). (Table 2) Weight loss expressed as percent of initial weight was significantly higher in the counseled overweight and obese patients (3.9 ± 4.3% and 4.5 ± 4.6% of their initial weights respectively) while overweight patients of the CG lost less weight (0.24 ± 2.3% of their initial weights) and obese patients gained more weight (0.32 ± 1.1% of their initial weights) after the 3 months follow up. The observed changes were statistically significant for overweight and obese patients (p = 0.001 and 0.012 respectively). Percentage of obese patients decreased in IG group from 40–31.6% after counseling (p = 0.025).

Similarly, mean BMI significantly decreased after the intervention from 28.7 ± 6.1 to 28 ± 5.5 kg/m2 while it remained almost the same in the control group (26.8 ± 5.3 and 26.9 ± 5.5 kg/m2). Mean waist circumference of females decreased from 101.5 ± 13.5 cm to 100.7 ± 11.5 cm in the IG while it increased in the CG from 97.1 ± 12.3 cm to 97.9 ± 12.3 cm (p = 0.011). Counseling intervention significantly reduced weight, BMI and female waist circumference (p value 0.000, 0.001 and 0.011 respectively). Intervention did not significantly affect the waist circumference in males (p = 0.280). (Table 2)

Table 2

Mean of anthropometric measures of the studied multiple sclerosis patients at KAMSU
Anthropometry	Pre-intervention				Post-intervention				P-value #
	IG (N = 60)		CG (N = 60)		IG (N = 57)		CG (N = 56)		P-value #
	Mean	SD	Mean	SD	Mean	SD	Mean	SD
Weight (kg)	76.9	17.1	72.4	14.3	75.4	15.8	72.8	14.7	0.000
BMI (kg/m²)	28.7	6.1	26.8	5.3	28	5.5	26.9	5.5	0.001
Waist circumference *
- Female	101.5	13.5	97.1	12.3	100.7	11.5	97.9	12.3	0.011
- Male	95.3	13.8	91.8	10.1	93.8	12.1	91.4	10.5	0.280

*Normal value for males is below 94 cm and for females is below 80 c

# P-value: ANCOVA *Kasr Alainy MS Unit

Analysis of 24-hour recall showed that the 2 groups initially consumed comparable number of servings during the last 24 hours from all food groups (p ≥ 0.05) but added fat where the IG reported consuming more than that reported by the CG (7 ± 3 versus 5 ± 2 respectively). Following counselling, the patients in the IG changed their intake from food groups favorably. They consumed significantly less grains (13.7 ± 6.7 to 10.4 ± 4.0 serving/day), added sugar (4.1 ± 3.1 to 1.7 ± 1.7 serving/day) and added fat (6.6 ± 3.5 to 4.5 ± 3.5 serving/day). They consumed more milk (0.3 ± 0.5 to 0.8 ± 0.8 serving/day), vegetables (2.0 ± 1.8 to 4.8 ± 2.6 serving/day 0.000), and fruits (0.5 ± 0.9 to 2.6 ± 1.5 serving/day). Figure 2 ANCOVA p values were < 0.01 in all cases (were 0.002, 0.000, 0.000 in the first and 0.000, 0.000, 0.000).

Table 3 shows the mean 24-hour intake of energy, macronutrients and some micronutrients pre and post counseling. Nutritional counseling significantly improved the intake of most nutrients (energy, fat, Na, P, fiber, K. Mg and vitamin C). IG patients consumed significantly less energy, protein, fat, carbohydrate, sodium, phosphorus and zinc. They consumed significantly more fibers, potassium, magnesium, vitamins A and C.

Table 3

Mean 24-hour intake of energy, macronutrients and some micronutrients of the studied multiple sclerosis patients at KAMSU
Intake	Pre-intervention				Post-intervention				P-value #
	IG (N = 60)		CG (N = 60)		IG (N = 57)		CG (N = 56)
	Mean	SD	Mean	SD	Mean	SD	Mean	SD
Energy (Kcal)	2528.8	1008.3	2413.7	889.4	2130.1	728.8	2517.7	924	0.004
Protein (grams)	89.3	35.8	84.6	37.9	72.3	27.1	93.8	45	0.001
Fat (grams)	88.9	42.4	78	36	68.4	32.5	84.9	37.5	0.008
Carbohydrates (grams)	342.4	150	341.6	128.9	300.4	96.6	342.1	147	0.053
Fibers (grams)	8.6	5.2	8.8	3.9	21	8.3	9.3	4.6	0.000
Na (mg)	3222.7	1450.7	3274.8	1488.5	2067.1	1383	3504.9	2012.1	0.000
K (mg)	2380.8	1205	2339.4	819.2	3044.3	838.6	2604.5	1032.3	0.015
Mg (mg)	127.4	74.3	133.2	69.7	160.4	48	132.8	65	0.008
Ca (mg)	694.3	394.6	729.2	376.2	695.6	254.9	720	371.1	0.813
P (mg)	1190.6	541.5	1304.7	602.8	1093.1	354.6	1328.8	668.4	0.04
Zn (mg)	12.9	7	12	5.2	9.9	5	13.2	7.8	0.005
Fe (mg)	16.8	9.6	16.3	7.1	16.9	5.8	18.4	9	0.261
Cu (mg)	1	0.7	0.9	0.5	1	0.3	1	0.7	0.749
Vit. A (µg)	430	1056.5	628.4	840.3	1370.8	1470	1025.1	1701.5	0.254
Vit. C (mg)	43.7	133.2	44.8	38.9	96.3	57.1	36.8	31.6	0.000
Vit. B1 (Thiamin) (mg)	0.9	0.6	0.9	0.4	0.9	0.3	1	0.5	0.835
Vit. B2 (mg)	1	1	1	0.9	1.1	0.6	1.2	2	0.558

# P-value: ANCOVA *Kasr Alainy MS Unit

Considering the adequacy of intake after counseling, Table (4) shows that two thirds (66.7%) of IG patients, compared to 39.3% of CG patients, consumed acceptable amounts of calories. Less IG patients over-consumed calories than CG patients (8.8% vs. 26.8%, respectively, p = 0.015). Nearly two thirds (64.9%) of IG patients compared to 30.4% of CG patients consumed acceptable amount of fat, while more patients in CG over-consumed fat than IG (8.8% and 26.8% respectively, p = 0.002). Similar but marginally significant effect was observed in the case of carbohydrates (p = 0.051). Similarly, Counseling had favorable impact on acceptable consumption of magnesium, iron, vitamins C, B1 and B2 but not on calcium, zinc, and vitamin A.

Table 4

**Distribution of cases according to adequacy of intake of energy and macronutrients among the study groups** pre and post intervention.
Compared intake with RDA^*		Pre-intervention				Post-intervention				P-value #
		IG (N = 60)		CG (N = 60)		IG (N = 57)		CG (N = 56)
		N	%	N	%	N	%	N	%
Calories	Unsafe	4	6.7	8	13.3	4	7.0	4	7.1	0.015
	Unacceptable	14	23.3	11	18.3	10	17.5	15	26.8
	Acceptable	26	43.3	27	45.0	38	66.7	22	39.3
	Overconsumption	16	26.7	14	23.3	5	8.8	15	26.8
Carbohydrate	Unsafe	11	18.3	10	16.7	7	12.3	11	19.6	0.051
	Unacceptable	17	28.3	10	16.7	10	17.5	10	17.9
	Acceptable	15	25.0	26	43.3	36	63.2	23	41.1
	Overconsumption	17	28.3	14	23.3	4	7.0	12	21.4
Fat	Unsafe	8	13.3	10	16.7	6	10.5	8	14.3	0.002
	Unacceptable	9	15.0	12	20.0	8	14.0	12	21.4
	Acceptable	22	36.7	21	35.0	37	64.9	17	30.4
	Overconsumption	21	35.0	17	28.3	6	10.5	19	33.9
Protein	Unsafe	1	1.7	1	1.7	0	0.0	0	0.0	0.091
	Unacceptable	3	5.0	1	1.7	0	0.0	4	7.1
	Acceptable	6	10.0	14	23.3	10	17.5	6	10.7
	Overconsumption	50	83.3	44	73.3	47	82.5	46	82.1

*Unsafe < 50%, Unacceptable 50–75%, Acceptable 75–120%, Overconsumption ≥ 120% of RDA

# P-value: Pearson Chi-Square test for carbohydrate and fat, Fisher’s Exact test for calories and proteins *Kasr Alainy MS Unit

Following counseling, patients of IG group spent shorter time in sedentary activity than CG patients (4.7 ± 2.2 hours/day versus 5.9 ± 2.5 hours/day). Table 5 shows that after counselling more patients in IG group (70.2%) practiced sports than CG group (18%); 63.2% and 62.5% of IG and CG patients were taking vitamin and mineral supplements, one third of IG patient were exposed to the sun versus 7.1% in the CG. None of IG patients were at moderate or high risk of malnutrition during the post-intervention assessment compared with 12.5% in the CG. The observed impact of counseling on duration of sedentary time, sports practice, exposure to the sun and the risk of malnutrition is statistically significant (p = 0.000, 0.000, 0.000 and 0.006). Counseling significantly reduced sedentary time and the risk of malnutrition in the IG (p = 0.006) compared to CG patients. The intervention increased the practice of sports and exposure to the sun but did not significantly affect Vitamin and mineral supplement intake (p = 0.942).

Table 5

Distribution of the studied patients by activity, vitamin and mineral supplement intake, exposure to the sun and risk of malnutrition before and after counseling.
Physical Activity		Pre-intervention					Post-intervention				P-value #
		IG (N = 60)			CG (N = 60)		IG (N = 57)		CG (N = 56 )
		N	%		N	%	N	%	N	%
Daily Effort	Very light	21	35.0	18		30.0	13	22.8	23	41	0.111
	Light	31	51.7	31		51.7	33	57.9	24	42.9
	Moderate	8	13.3	11		18.3	11	19.3	9	16.1
Sport Practice	≥ 3times/Week	3	5	8		13.3	23	40.4	5	9	0.000
	< 3times/Week	12	20	4		6.7	17	29.8	5	9
	No	45	75	48		80	17	29.8	46	82
Supplement intake	Yes	36	60	42		70	36	63.2	35	62.5	0.942
Supplement intake	No	24	40	18		30	21	36.8	21	37.5	0.942
Exposure to sun	Yes	14	23.3	7		11.7	19	33.3	4	7.1	0.000
Exposure to sun	No	46	76.7	53		88.3	38	66.7	52	92.9	0.000
Risk of malnutrition	Low Risk	56	93.3	50		83.3	57	100	49	87.5	0.006
	Moderate Risk	1	1.7	7		11.7	-	-	3	5.4
	High Risk	3	5	3		5	-	-	4	7.1

# P-value: Pearson Chi-Square or Fisher’s Exact test *Kasr Alainy MS Unit

The results obtained by PPA were similar to those by ITTA. Also counselling appeared to have significant effect on lowering male waist circumference among compliant patients.

The current study revealed a high prevalence of overweight, obesity and central obesity among the enrolled 120 patients close to that reported for MS patients in the same unit before [5]. The prevalence of overweight and obesity is higher than that reported by Marck et al., [27]. Mean waist circumference is also higher than that reported by Drehmer E et al, [28] thus indicating a higher risk of metabolic complications. The observed higher prevalence in the current study can be attributed to the overconsumption of macronutrients, low intake of dietary fibers and the sedentary nature of most of the patients. The mean 24-hour energy, carbohydrates, proteins and fat consumption was higher in our study than that reported by Armon-Omer et al [29] which together with lower fiber intake account for the difference in mean BMI between the two studies (27.7 ± 5.7 kg/m² and 25.0 ± 4.4 kg/m2 respectively). Dietary fibers were consumed at less than the acceptable levels by our patients (8.7 ± 4.6 g/day in all enrolled patients, 8.0 ± 4.1 in females and 10.6 ± 5.2 in males) as the 2020–2025 Dietary Guidelines recommend 22–28 g for women and 28–34 g for men over the age of 19 [30]. Most of the studied patients described their daily efforts as light or very light and more than three quarters of the patients did not practice sports.

The prevalence of underweight among enrolled MS patients was low. Only 1.7% of the CG group was underweight (BMI less than 18.5 kg/m2). Most enrolled patients (88.3%) were at low risk of malnutrition according to MUST scores (93.3% in IG and 83.3% in the CG). Weight loss is known to occur in advanced MS. In our study, patients were at a relatively early stage of the disease as most of them were suffering from RRMS.

Regarding micronutrients, the intake of sodium, potassium, calcium, phosphorous, magnesium, iron, zinc, copper and vitamins A, C, B1 and B2 intake was comparable in the IG and CG in pre-counselling assessment (p > 0.05). Those intakes were lower than the RDA for all nutrients except sodium which was much higher, phosphorous and copper which were slightly higher [16]. The lower intake of calcium, magnesium, zinc, and iron was in consistency with Armon-Omer et al [29]. Sodium was consumed in very large amounts by patients of both IG and CG (3222.7mg and 3274.8 mg/day respectively). This was higher than the 2300 mg recommended by 2020–2025 Dietary Guidelines for people older than 19 years [30]. Also, it was higher than the mean sodium intake reported in the Armon-Omer et al. study (2392.66 mg) [29]. Kleinewietfeld mentioned that increased dietary salt intake might be an environmental risk factor for the development of autoimmune diseases by inducing pathogenic cells and related proinflammatory cytokines [31]. Those cells have been involved in the development of MS [32]. Fitzgerald KC et al, [33] based on multiple assessments of urine sodium excretion over 5 years and standardized clinical and MRI follow-up, suggested that salt intake does not influence MS disease course or activity[33]. Even though the evidence linking high salt intake and MS is contradictory, combining the DASH diet with low sodium intake might be beneficial in MS. It also improves the vascular health of MS patients [6].

In order to identify the effect of nutrition counselling on the nutritional status of KAMSU patients this randomized controlled clinical trial was carried out. This design is the gold standard for measuring the effectiveness of a new intervention or treatment. Blinding of patients and health care providers was not possible due the nature of intervention; however, we blinded the statistician who analyzed the data. Nutrition counselling was provided by a specialized nutritionist and follow up was optimized through phone calls and WhatsApp messaging. About 78.9% and 89.3% of IG and CG patients were compliant with the prescribed regimens as reported in the final assessment. The lower compliance rate among the IG compared to the CG may be attributed to the patient’s readiness to adopt healthy dietary behavior.

The current trial revealed that nutrition counselling significantly helped MS patients achieve a healthier weight, better waist circumference, macronutrient intake and adequacy compared to those in the control arm. The PPA highlighted the significant change in the compliant male’s waist circumference (p = 0.043) in contrast to the insignificant change revealed by the ITTA. (p = 0.280). Also, the PP analysis showed that more weight was lost by compliant overweight and obese patients after the exclusion of non-compliers who diluted the change observed in the ITT analysis.

Following counseling, the risk of malnutrition, the prevalence of obesity and the prevalence of patients who were at substantially increased risk of metabolic complications decreased in males and females. The changes in the percentages of the different BMI categories were not significant in both the ITT and PP analyses. After controlling for the initial BMI categories, there was a significant difference between the outcomes of obese patients in the IG and CG (p = 0.025). The observed effect is attributed to the improved food intake, less sedentary hours and more activity induced by counseling.

Regarding nutrition supplementation, the most recent ESPEN guidelines on clinical nutrition in neurology did not recommend routine supplementation for MS patients, but rather to correct established deficiencies [34]. In the pre- and postintervention assessments, vitamin and mineral supplements were taken by ≥ 60% of the IG and CG patients (60% and 70% pre and 63.2% and 65.5% post-counselling respectively). Similar findings were reported in an American study where 68.6% of the studied MS patients consumed vitamin and mineral supplements [35]. Higher frequency of supplement intake was even reported in a Danish study conducted on 967 MS patients (78.5%) [36]. Nutrition counseling did not affect supplement intake in our study as it was initially high and continued to be so because patients were taking it as a part of the standard management at KAMS unit.

Nutrition counseling induced considerable improvement in fiber intake in the IG from 8.6 ± 5.2 g to 21.0 ± 8.3g (p = 0.000), the level of intake of both males (27.0g) and females (20.9g) became close to the minimum recommended. Extra emphasis needs to be addressed regarding eating fiber rich foods.

Counselling did not improve the intake of macronutrients only, but it did improve the intake of micronutrients as well. ANCOVA analysis revealed a significant increase in the consumption of potassium, magnesium, and vitamin C; decrease in the consumption of sodium, phosphorus and zinc (p < 0.05). The percentage of IG patients who consumed acceptable amounts of magnesium and iron increased significantly over the percent in CG. Similarly, the percentages of IG patients who consumed unsafe and unacceptable amounts of vitamin C, B1 and B2 had decreased. Impairments of micronutrient intake might be of clinical significance in MS as they contribute to existing symptoms such as muscle wasting, weakness, fatigue, and muscle spasms [20]. Counseling appears to ameliorate the effect of many of these impairments.

The effect of counseling on nutrient intake can be explained by the changes in food intake of patients. Patients in the intervention group significantly improved their consumption from the food groups into a healthier one. They increased their intake of milk, vegetables and fruits and decreased their intake of grains, added sugar and fat (p < 0.05). Milk is an excellent source of many vitamins and minerals, including vitamin B12, calcium, riboflavin, and phosphorus. It’s often fortified with other vitamins, especially vitamin D [37].

Vegetables and fruits are good sources of vitamins and minerals including vitamin C, carotene, calcium, iron and potassium [38]. They are good sources of magnesium and fiber and are usually low in fat and calories.

Eating a variety of vegetables and fruits clearly ensures an adequate intake of most micronutrients, dietary fibers and a host of essential non-nutrient substances. As well, increased fruit and vegetable consumption can help displace foods high in saturated fats, sugar or salt. A healthy diet includes at least 400 g (i.e. five portions) of fruit and vegetables per day, excluding potatoes, sweet potatoes and other starchy roots [39].

In conclusion, overweight, obesity, abdominal obesity and faulty dietary habits are prevalent among the MS patients attending KAMSU. Nutrition counselling significantly improved eating and activity pattern of MS patients into a healthier pattern, it helped patients achieve better weight, waist circumference, nutrient intake and adequacy compared to those in the control arm who did not receive the counseling. Accordingly, nutritional counselling and care must be considered an integral part of the health care of MS patients at KAMSU and elsewhere.

Study Limitations

The current study findings should be interpreted considering the following limitations: First, the 24-hour dietary recall may have some weaknesses, such as recall bias, inaccurate estimation of portion sizes, possible over/under-reporting of certain foods, and that data from a single day cannot accurately represent the respondent’s usual intake. One of the researchers, who is a ESPEN-qualified clinical nutrition specialist, conducted all interviews herself to ensure good quality of data. Also, the 24-hour dietary recall was complemented by other tools of nutritional assessment, such as anthropometric and clinical. Secondly, the compliance rate among the intervention group (78.9%) was lower than that of the control group (89.3%). The patient’s readiness to adopt healthy dietary behaviour is an important factor to take into consideration.

Acknowledgment: The authors are thankful to the Chairman of the Neurology Department and to all study participants and to Dr.El Sayed Hammad Lecturer at the National Nutrition Institute

Consent for publication: Not applicable.

Availability of data and materials: The datasets used and/or analyzed during this study are available from the corresponding author on reasonable request.

Competing interests: The authors declare that they have no competing interests.

Funding: This research did not receive any specific grant from funding agencies in the public, commercial, or not-for-profit sectors.

Authors’ contributions: Z.A made substantial contributions to the study conceptualization and design, data analysis and interpretation, and manuscript writing. A.F made substantial contributions to the data acquisition and manuscript writing M.S, N.A and A.H were involved in drafting the manuscript (methods and results section) and revising it carefully for important intellectual content and statistical analysis. All authors read and approved the final version of the manuscript.

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No competing interests reported.

Impact of Nutrition Counselling on Multiple Sclerosis Patients Nutritional Status: Randomized Controlled Clinical Trial

Status:

Journal Publication

Version 1

Abstract

Figures

Introduction

Methods

Study design, setting, and population

Sample size, recruitment of participants, and randomization technique

Study phases

Preparatory Phase

Preintervention phase (the initial assessment)

Intervention (only for the intervention group):

Post intervention phase (the final assessment):

Statistical analysis

Ethical considerations

Results

*Normal value for males is below 94 cm and for females is below 80 c

# P-value: ANCOVA *Kasr Alainy MS Unit

# P-value: ANCOVA *Kasr Alainy MS Unit

*Unsafe < 50%, Unacceptable 50–75%, Acceptable 75–120%, Overconsumption ≥ 120% of RDA

# P-value: Pearson Chi-Square or Fisher’s Exact test *Kasr Alainy MS Unit

Discussion

Declarations

References

Additional Declarations

Status:

Journal Publication

Version 1