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Nutrition in acute and chronic diseases

Dietary patterns and associations with health outcomes in Australian people with multiple sclerosis

European Journal of Clinical Nutrition volume 75, pages 1506–1514 (2021)Cite this article

Subjects

Abstract

Background/objectives

Associations between patterns of food intake and health in people with multiple sclerosis (MS) are of increasing global interest; however, Australian data are lacking. This study aimed to assess the dietary habits and associations with health outcomes of Australians with MS.

Subjects/methods

This cross-sectional study used 2016 survey data from the Australian MS Longitudinal Study, including the Dietary Habits Questionnaire, Hospital Anxiety and Depression Scale, Assessment of Quality of Life, Fatigue Severity Scale, Patient-Determined Disease Steps Scale and 13 MS symptoms scales. Regression models were constructed using directed acyclic graphs.

Results

Almost all (94.3%) of the 1490 participants reported making an effort to eating healthy with 21.2% following one or more specific diets, although often not strictly. Overall, 7.9% reported not eating meat, 8.1% reported not consuming dairy, and 4.0% consumed neither food group. A healthier diet score was associated with better mental, physical and total quality of life, and lower depression, and pain scores, and fewer cognition, vision and bowel symptoms. Higher reported fibre, fruit, vegetable and healthy fat scores were positively associated with most health outcomes.

Conclusions

Healthier overall diet scores and higher fibre, fruit and vegetable scores were associated with better health outcomes in this sample of Australians adults with MS. However, the proportion of participants avoiding dairy and meat, or adhering to a specific MS diet was much lower than previously reported. Prospective dietary studies are needed to further understand whether dietary change is feasible and affects health outcomes over time.

Introduction

Multiple sclerosis (MS) is a chronic neurological disorder, which is often diagnosed in young adults; the exact aetiology remains unknown. Inflammation in MS is seen in the form of lesions of the central nervous system, which is indicative of disease activity. In MS, T-cell-mediated responses may be triggered by environmental effects including nutrition [1]. An adverse lipid profile and increased adiposity may also increase disease activity in people with a first demyelinating event, a precursor for MS [2, 3]. Dietary approaches may reduce both the inflammation and neurodegeneration that is fundamental to MS [4].

The underlying mechanism of diet on health outcomes in people with MS is thought to be through increased inflammation due to poor dietary patterns [5]. Nutrition is also strongly tied to the composition of the gut microbiome, and for persons with MS, a bi-directional relationship exists between the disease and the microbiome [6]; suggesting that the gut composition may shape the disease pathology [7].

Following diagnosis, ~70% of people with MS adopt complementary and alternative approaches to disease management including nutrition [8]. A plethora of diets to treat MS or related symptoms are recommended through websites, books and organisations [9]. Despite a high level of interest in dietary modification from people with MS, international studies as well as Australian data [10] show that up to 90% of people with MS do not meet dietary guidelines [11]. However, there is limited data from Australian people with MS that relates to their patterns of food intake. This study uses a representative sample of Australians with MS to assess dietary habits and examine the associations between diet and health outcomes.

Methods

Participant recruitment

This cross-sectional study uses data from the Australian MS Longitudinal Study (AMSLS) of which has over 3000 active participants, representative of Australians with MS. Approximately 96% of AMSLS participants were diagnosed with definite MS by their neurologists according to the McDonald criteria [12]. The AMSLS conducted surveys in 2016 including (1) the Lifestyle Survey assessing diet (August to October 2016) for which 3112 survey invitations were sent, and 1518 (48.8%) responded; (2) the Medication and Disease Course Survey assessing disease-related outcomes (November 2016 to March 2017) for which 3098 invitations were sent and 1699 (54.8%) responded and (3) the Economic Impact Survey assessing quality of life (QOL) (March to May 2016) for which 3163 invitations were sent and 1577 (49.9%) responded. To assess whether the study was using a representative sample, key characteristics of the included participants with data on dietary intake were compared with those participants not included in this study. The AMSLS is approved by the Tasmanian Health and Medical Human Research Ethics Committee (approval number: H0014183), and all participants provided informed consent.

Instruments

The Dietary Habits Questionnaire (DHQ) assessed the frequency of type of food groups consumed and the methods of food preparation through 20 items scored between 1 and 5 (Supplementary file 1). The DHQ was designed for a cardiac rehabilitation population in line with Australian dietary guidelines [13] and has been modified for use in a survey for people with MS [14]. The modified version excluded four items regarding sodium and alcohol intake and had good internal consistency (Cronbach’s alpha 0.84). A total summary score (referred to as diet score) was calculated as an average of the 20 items, with scores ranging 20–100 (higher scores suggest a better quality diet, referred to hereon forth as a healthier diet). Completion of at least 16 items was required to obtain a summary score. DHQ subscores of interest for the current study (fibre, fat, fruit and vegetable) were transformed into the following categories: poor < 3.5, moderate = 3.5 to <4.5, healthy = >4.5 as was previously done in another study of people with MS [14]. Whether meat or dairy was consumed by a participant was deduced using the DHQ questions regarding dairy, spreads, processed meats, cooked sauces, trimming fats from meat, cooking fats and snacks.

Participants were further asked: ‘Do you make an effort to eat healthily?’ (yes/no) and ‘Do you follow a particular diet?’ (yes/no); followed by: ‘Which diet(s) do you follow?’, which was a multiple choice question with the following responses: The Swank Diet only, The Overcoming MS Diet (includes Swank Diet), Terry Wahls diet, Asthon Embry’s Best Bet Diet, The Paleo Diet, other, please specify. For each option that was selected, participants were asked if they adhered ‘very strictly’ or not ‘very strictly’.

QOL was measured by the Assessment of Quality of Life (AQoL-8D) instrument [15], comprising a physical and a psychosocial/mental ‘super-dimension’. A score for each was produced and combined to form final AQoL-8D utilities. AQoL data were transformed to a 0–100 scale, so as to compare with studies using other instruments.

Depression and anxiety were measured by the Hospital Anxiety and Depression Scale (HADS) [16]. The Fatigue Severity Scale (FSS) [17], was used to assess fatigue (mean of nine items (1–7 scale)). Before answering the FSS, participants were asked if they experienced any symptoms of fatigue; if they reported not having any symptoms of fatigue they were assigned a score of 0 and instructed to skip the FSS [18].

The Patient-Determined Disease Steps Scale (PDDS, scored from 0 (no disability and only mild symptoms) to 8 (bedridden)) was used to assess disability. PDDS is a validated patient-reported instrument to measure disability in MS and is strongly correlated with the Expanded Disability Status Scale (r = 0.78) [19, 20].

Severity of 13 MS symptoms (MSSyMS) in the past 4 weeks compared to before the participant developed MS was measured by a numeric rating scale (0–10), where 0 signified no problem and 10 signified the worst possible for that individual.

Participants were asked to report weight and height, from which body mass index (BMI) was calculated as weight in kilograms divided by height in meters squared and rounded to one decimal place. BMI was categorised using the World Health Organization classification system where a BMI below 18.5 kg/m2 is classified as underweight, 18.5–24.9 kg/m2 is classified as normal weight, 25.0–29.9 kg/m2 is classified as overweight and 30 kg/m2 or more is classified as obese [21]. Using postcode data, socio-economic status (SES) was assessed by the Socio-Economic Indexes for Areas, developed by the Australian Bureau of Statistics ranking areas in Australia according to relative socio-economic advantage and disadvantage [22]. Information on age, sex, education level, relationship status, MS type and MS diagnosis year was also collected.

Data analyses

All data analysis was performed using STATA V16 statistical software [23]. One-way analysis-of-variance models were used to compare DHQ diet score by sample characteristics. Directed acyclic graphs were created to guide the multivariable statistical models [24], which were adjusted for confounding using age, SES and sex. Linear regressions were performed for continuous variables. Where residuals were not normally distributed, a Box–Cox transformation was performed. Cragg hurdle models were used if distributions were zero-inflated.

Results

Participants who provided dietary data (n = 1490) were included in the current study and were compared with participants not included (n = 1622) from the total AMSLS cohort. No differences were found by sex, education level or MS duration. The included study participants were slightly older (+1.74 years, p < 0.001). The characteristics of included participants are shown in Table 1.

Table 1 Sociodemographic and clinical characteristics.
Full size table

Dietary habits

The mean total DHQ score was 73.4 (SD 10.4), with 10.4% of participants scoring 60 or below, 27.7% scoring >60–70, 35.4% scoring >70–80, 21.4% scoring >80–90 and 5.1% scoring over 90. Almost all participants (94.3%) indicated that they made an effort to eat healthily. Those who reported that they ‘make an effort’ scored 12.8 (p < 0.001) points higher than those who did not. Overall, 7.9% of participants reported not eating meat, 8.1% reported not consuming dairy and 4.0% consumed neither meat nor dairy.

Participants who followed a particular diet (21.2%) scored 8.8 (p < 0.001) points higher on the DHQ than those who did not. Some followed one or more MS-specific diets such as the Swank diet (0.5%), Overcoming MS diet (6.3%) or the Wahls diet (0.9%). Of the 116 participants who reported adhering to MS diets that prohibit dairy consumption (e.g. Overcoming MS, Ashton Embry’s Diet, Wahls Diet or Paleo Diet), 37.9% reported consuming dairy in the relevant DHQ section. When asked how strictly participants followed the MS-specific diets, 53.0% indicated that they did not follow them very strictly. More often participants reported following one or more non-MS-specific diets (13.1%), including FODMAPS (a diet low in fermentable oligo-, di-, mono-saccharides and polyols), 5:2 diet (5 days per week eating usual diet, 2 days per week restricting to a quarter of usual calories), gluten free, sugar free, Lite n Easy, vegetarian, vegan, low fat, low carbohydrates, and diets tailored to the person’s specific allergies or sensitivities (e.g. nuts).

Associations with health outcomes

Quality of life (QOL)

A higher (‘healthier’) diet score was associated with a significantly higher total, as well as higher mental and physical health QOL scores with clear dose–response patterns. Higher scores (‘healthier’) on subscales for fibre, fruit and vegetable and, to a lesser degree, fat were also associated with better QOL scores (Table 2). There were no associations between consumption of meat and/or dairy and QOL.

Table 2 Associations between diet and MS outcomes including quality of life (QOL), fatigue and depression using multivariable linear regression.
Full size table

Depression and anxiety

Participants with higher overall diet, fibre, fat and fruit and vegetable scores had lower depression scores (HADS) in dose–response patterns (Table 2). Those who reported consuming meat and dairy had higher depression scores (HADS) compared to those who reported not consuming meat and dairy. There was little evidence for associations between meat or dairy consumption separately and depression scores. Similar patterns were observed when using the depression symptom scale (MSSymS), with a higher overall diet score, fibre, fat, healthy fruit and vegetable scores associated with not consuming dairy or meat and dairy (but not meat consumption separately, Table 3). There was no association between total diet scores and anxiety (HADS); however, higher fibre and fruit and vegetable scores were associated with lower anxiety scores. Meat and/or dairy consumption (from DHQ items) was not associated with anxiety (Table 2). Similarly, lower anxiety symptom scores (MSSymS) were associated with healthier fibre, moderate healthy fat and fruit scores and healthy vegetable scores only (Table 3).

Table 3 Associations between diet score and MS symptom severity scores.
Full size table

Disability and MS symptoms

Adjusted regression models showed no associations between total diet score and levels of disability (test for trend p = 0.99), diet subscales or meat and/or dairy consumption (test for trend all p > 0.50) (data not shown). There was no association between any of the diet variables and fatigue as measured by FSS, except for healthier fibre scores, which was associated with 0.4 lower score for fatigue compared to poor fibre consumption (Table 2).

For the 13 symptom severity scores, we found associations between diet and cognition, pain, vision and bowel symptoms (Table 3). Moderate (but not healthy) fibre was associated with a lower score for the cognition symptoms scale but there was no dose–response pattern or other associations. There was a stronger association between diet and pain, with the total diet score in a clear dose–response pattern, healthy fibre and fruit and vegetable categories, associated with lower pain scores. Better total diet scores were associated with lower scores on the vision symptom scale, while moderate (but not healthy) fibre and fat scores, no meat and/or dairy consumption were associated with lower scores. The highest diet score was associated with a lower score on the bowel symptom scale, as were moderate/healthy fibre, healthy fat and moderate fruit and vegetable scores in dose–response patterns. There were no associations between any of the diet variables and MS symptoms scores for fatigue, walking, balance, bladder, sexual, sensory and spasticity (data not shown).

Discussion

This is the first study exploring the food intake patterns in a large Australian representative sample of people with MS. The average diet score was 73.4 (SD 10.4), somewhat lower when compared to a large international study (HOLISM) of people with MS (79.0, SD 11.7) using the same dietary questionnaire (albeit in a younger sample) [14]. Almost all participants in the current study reported making an effort to eating a healthy diet, with about one fifth following one or more specific diets. However, previously published data from this cohort showed that only 10.1% had sufficient fruit and vegetable intake according to Australian guidelines [10]. MS-specific diets were not commonly followed, and among followers the diets were not strictly adhered to, in line with previous studies [25]. This may reflect the current lack of high-quality evidence for these MS diets on MS symptoms or prognosis [26, 27], and/or the difficulty in adhering to these diets [27].

Dietary habits

Particular patterns of food intake were being followed by the participants. Overall 7.9% reported not eating meat, 8.1% reported not consuming dairy and 4.0% consumed neither meat nor dairy; all proportions slightly higher than the general population in Australia where 6.6% and 7.7% reported avoiding dairy and meat, respectively, and 2.4% reported avoiding all animal products [28]. This participant self-reported dietary information was obtained using a dietary screener of the previous 1-month period. The screener captured data for key food groups and types (fruit, vegetables, legumes, red and processed meats) food components (added sugars from desserts or sweetened beverages, wholegrains and nutrients (calcium) and analysed using an approach used in populations with coronary heart and cardiovascular disease. A large North American study also reported lower proportions of dairy and meat avoidance, with 1–3% adhering to vegetarian, pescatarian or vegan diets [25]. However, the HOLISM study, which used the same diet tool as used in this study, reported a much higher proportion of dairy and meat avoidance: with 38% of respondents not consuming dairy and 27% not consuming meat [14]. The HOLISM study is closely tied to the overcoming MS diet, which recommends eliminating all dairy and meat.

Associations with health outcomes

A higher total diet score was associated, in a dose–response manner, with better mental, physical and total QOL, and lower depression, and pain scores, in line with results from the HOLISM study [14, 29] albeit with a smaller magnitude. This may be due to the use of a different QOL questionnaire, or a different selection of participants. Our results were also in line with the NARCOMS study, which found that people with higher diet quality (top quintile) had 18% lower odds of severe depressive symptoms, compared to those with the worst diet quality (bottom quintile) [25]. In addition, though this was not in a strong dose–response manner or magnitude, our results also showed some associations between the total diet score and cognition, in line with results from the HOLISM study [30, 31]; but not with the NARCOMS findings [25], which may relate to the differences in the diet tools used in each of the studies. While each of the studies have used a form of dietary screener that was self-completed by the participants, these tools have not been validated for an MS population. While the intent appeared to be a shortened tool to limit user burden, the lack of inclusion of all food groups alongside limited behavioural and environmental queues may explain the differences between the studies.

Higher fibre and fruit and vegetable, and to a lesser degree, healthy fat scores were associated with most of these health outcomes, often in a dose–response manner. Each of these components of food intake has been implicated with both improved dietary quality and a positive impact on the microbiome [32]. Dietary intake of unhealthy fatty acids is of much interest both from the perspective of contributing to a obesogenic diet, as well as inflammation [33]. Overweight or obesity is associated with an increased rate of disease progression [34] and neuro-inflammation [35] in people with MS. Further, the inflammatory response that is instigated by a high saturated fat intake is related to an increase in toll-like receptor 4 response of adipocytes alongside an increased macrophage response. The receptor response in particular has been demonstrated in a dose-dependant manner for palmitic acid and stearic saturated fatty acids as identified by increased inflammatory markers in cellular models [33]. However intervention studies in this area, which are largely focussed on healthy, or polyunsaturated, fatty acid supplementation, find little evidence for benefit for people with MS [36], and data on supplementation were not collected in our study. Previous research has suggested a bi-directional relationship between healthy diet and health outcomes, and from our cross-sectional data we are unable to infer cause-effect [37]. Therefore, it is also possible that participants with better health were better placed to consume a healthier diet.

Total diet score and most other dietary variables were not associated with level of mobility disability, fatigue, walking, balance, bladder, sexual or sensory and spasticity symptoms [14, 30, 38, 39]. These results were not in line with the results from the HOLISM study, which found associations between higher diet score and lower disability and fatigue scores [14, 38]. Also, the NARCOMS study found an association between diet quality and disability; individuals with the best diet (top quintile of diet score) were at 20% lower odds of higher levels of disability compared to people with the worst diet score (the bottom quintile), but no association with fatigue [40]. Further, results from the HOLISM study also reported that those not consuming dairy had slightly higher mental QOL compared to meat and dairy consumers [14], our study did not find evidence for this. Again, these inconsistencies are likely due to the differences in the participants included in the studies and the likely influence of the overcoming MS diet on participants in the HOLISM study. There was little evidence that meat and dairy consumption in our study were associated with health outcomes, in line with the literature. Despite several MS diets advising that eliminating dairy and/or meat is beneficial, there is currently no strong evidence to support this [26, 41, 42]. However, reducing meat and full fat dairy intake is likely to improve overall dietary quality for most people by reducing the intakes of saturated fatty acids, and may have benefits for the environment as well [43].

Strengths and limitations

Due to the cross-sectional design, we are unable to draw conclusions about temporality or causal inferences between diet and MS. However, no associations were found between diet and disease duration, and participants with secondary progressive MS had similar (slightly better) diet scores compared to those with relapsing remitting MS (results not displayed). This indicates that diet quality was not associated with disease worsening, and decreases the likelihood that a poor diet is caused by a longer MS duration. However, there is still a significant risk of reverse causality with these data, which requires prospective blinded intervention studies to ascertain.

The survey tools used in the AMSLS may also be influenced by measurement error and reporting bias. Surveys for the participants are either self-completed or completed by the participants carer. It is likely that a social desirability response bias may be seen for particular items known to be associated with better heath. Social desirability bias is also strongly associated with overweight, female respondents who are educated [44]. These variables all have significant associations with the diet score. Further the dietary tool used in this study only provides an overview of intake in the form of a score, it does not provide a quantified measure of intake for each of the variables, e.g. differentiation of the types of meat or dairy, therefore, this would need to be explored in future studies with a more detailed and robust assessments of dietary intake. Further, only key areas of the diet have been included in the DHQ, which cannot be translated to nutrient or energy intakes. As a result it is not known if participants have over- or under-reported their intakes. Finally, while the amended DHQ has been tested for inter-rater reliability within the MS population, it has not been validated against a representative measure of dietary intake.

Conclusion

In a representative sample of Australians with MS, almost all participants reported making an effort to eat what they thought was a healthy diet, with 21% following one or more specific diets. Less than 10% reported following a MS-specific diet, and most not very strictly. Higher diet scores and higher fibre, fruit and vegetable intake scores were associated with better health outcomes, particularly QOL and depression. Prospective studies are needed to understand whether and how a change in diet can impact on health outcomes over time.

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Acknowledgements

The authors thank all the participants in the Australian Multiple Sclerosis Longitudinal Study for their support and willingness to complete the surveys.

Funding

This study was supported by Multiple Sclerosis Research Australia. CHM was funded by an Early Career Fellowship from the National Health and Medical Research Council (ID: 1120014) and a Fellowship from Multiple Sclerosis Research Australia (ID 20-216).

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Affiliations

  1. Disability and Health Unit, The Melbourne School of Population and Global Health, The University of Melbourne, Parkville, VIC, 3010, Australia

    Claudia H. Marck

  2. School of Medicine, University of Wollongong, Wollongong, NSW, 2522, Australia

    Yasmine Probst

  3. Illawarra Health and Medical Research Institute, Northfields Ave, Wollongong, NSW, 2522, Australia

    Yasmine Probst

  4. Menzies Institute for Medical Research, University of Tasmania, 17 Liverpool St, Hobart, TAS, 7000, Australia

    Jing Chen, Bruce Taylor & Ingrid van der Mei

Authors
  1. Claudia H. Marck
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  2. Yasmine Probst
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  3. Jing Chen
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  4. Bruce Taylor
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  5. Ingrid van der Mei
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Contributions

CHM and IvdM were responsible for formulating the research questions and designing the study. IvdM and JC were responsible for data collection, management and cleaning. CHM analysed the data and drafted the manuscript. YP, BT and IvdM contributed to writing and editing the manuscript.

Corresponding author

Correspondence to Claudia H. Marck.

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Conflict of interest

YP was a participant in the study but was not involved in the data management or data analysis. The authors declare that they have no conflict of interest.

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Marck, C.H., Probst, Y., Chen, J. et al. Dietary patterns and associations with health outcomes in Australian people with multiple sclerosis. Eur J Clin Nutr 75, 1506–1514 (2021). https://doi.org/10.1038/s41430-021-00864-y

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  • DOI: https://doi.org/10.1038/s41430-021-00864-y

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