Oral health‐related quality of life is more strongly correlated with mental health than with oral health in relapsing–remitting multiple sclerosis

Abstract

Background

Multiple sclerosis (MS) is a leading cause of neurological disability in young and middle‐aged populations, associated with substantial burden of illness. Because a growing literature now shows that this burden extends to poorer oral health, oral health‐related quality of life (OHRQoL) may be reduced as well.

Objectives

To test whether people with relapsing–remitting MS (RRMS) have poorer OHRQoL than demographically matched controls, and to establish which variables are associated with worse OHRQoL.

Materials and Methods

In total, 64 people with RRMS and 69 demographically matched controls participated. Both groups completed the Oral Health Impact Profile (OHIP‐14), a validated measure of OHRQoL, as well as an objective oral health examination performed by a qualified dentist, a measure of dental‐related functionality and a measure of mental health.

Results

OHRQoL was significantly poorer in the RRMS relative to the control group. However, although poorer OHRQoL in the RRMS group was moderately associated with objectively assessed oral health (r = .30), it was more strongly associated with mental health (r = .61). For the control group, the reverse pattern of association was evident, with OHRQoL more strongly associated with oral health (r = .48) relative to mental health (r = .20).

Conclusion

People with RRMS report poorer OHRQoL than demographically matched controls, but these appraisals are more strongly linked to mental health than to objective oral health indicators.

1. INTRODUCTION

In young and middle‐aged adults, multiple sclerosis (MS) is the most common inflammatory disease of the central nervous system and is associated with substantial burden of illness. There is growing evidence to indicate that this burden extends to poorer oral health, with a recent systematic review concluding that people with MS are at elevated risk for periodontal disease, poorer oral hygiene, temporomandibular disorders and specific orofacial pathologies, such as trigeminal neuralgia, facial numbness and facial palsy. ¹

Such findings are unsurprising given the chronic and disabling nature of MS, with many factors potentially contributing to poorer oral health outcomes in this group. Common motor symptoms include upper limb weakness, ataxia and spasticity, all of which may limit the ability to engage effectively in daily oral hygiene at a practical level, while fatigue and mobility limitations (which become increasingly common with disease progression) can make it more challenging to access dental health care. Many of the drugs which help to suppress MS symptoms and limit clinical progression can also have side effects directly or indirectly on the oral mucosa (xerostomia, gingival hyperplasia, mucositis/ulcerative stomatitis, dysgeusia, candidiasis and angular cheilitis), potentially contributing to poor oral health. ²

Broader empirical literature also consistently shows that good oral health is fundamental to overall health, well‐being and quality of life, ³ with oral disease linked to pain, discomfort and in some cases, social embarrassment. ⁴ However, little is known about oral health‐related quality of life (OHRQoL) in MS specifically. To date, only two prior studies have examined OHRQoL in this cohort, and in neither of these were a matched control group included. ⁵ , ⁶ While Covelo et al. did not include any control group at all, Cockburn et al. compared MS participants' responses to previously published norms that were dated and which differed from the MS cohort in key respects such as gender and age, limiting the conclusions that could be made. This study therefore sought to provide the first direct test of whether, and if so to what extent OHRQoL, is poorer in people with MS relative to a neurotypical comparison group matched in key demographic characteristics.

In addition, although broader literature reveals that objective indicators of oral health and OHRQoL are often linked, it remains unclear whether this association is also evident in MS. This question is important, because many types of subjective complaints become more common in MS, and do not always correlate with objective indicators of the source of these complaints. For instance, not only have subjective estimates of cognitive function been shown to be weakly correlated with objective indicators of cognitive abilities in MS, ⁷ objective and subjective estimates of cognitive functioning function have also been identified as independent predictors of broader MS‐related quality of life. ⁸ Also of interest in this study was therefore whether OHRQoL in this clinical group is related to oral health, as indexed by an objective oral health assessment.

Broader literature also reveals that neuropsychiatric signs and symptoms such as depression and anxiety present frequently in MS, ⁹ and may not simply reflect a response to living with a chronic disease, but a multifactorial aetiology that includes MS‐related structural and functional brain impairment. ¹⁰ Because higher levels of depression and anxiety in people living with MS have been shown to influence patient‐reported cognitive complaints ¹¹ as well as patient‐reported quality of life, ¹² mental health may therefore contribute to poor OHRQoL in this group.

Finally, oral care capacity is important to consider in any disorder that affects cognitive and/or motor capacity, as it speaks directly to whether the actual ability to engage in oral self‐care is compromised. Although neurocognitive impairment is common in MS, ¹³ , ¹⁴ it appears to be unrelated to oral health. ¹⁵ However, other MS‐related symptoms such as motor disturbances might negatively impact oral care capacity. Also important is therefore to establish whether people with MS exhibit reduced oral care capacity, and how this capacity is related to their OHRQoL and oral health.

The three key hypotheses of this study were as follows: (1) Relative to demographically matched controls, OHRQoL would be poorer in people diagnosed with MS; (2) in both the clinical and control groups, poorer OHRQoL would be associated with worse oral health; (3) in the MS group, poorer OHRQoL would be associated with mental health problems, as well as with other MS‐specific clinical markers (disease severity and disease duration). Because no prior study has assessed oral care capacity in an MS group, no hypotheses were made about whether the MS and control groups would differ on this measure. However, in both groups, it was anticipated that reduced oral care capacity would be associated with poorer OHRQoL and worse oral health.

2. MATERIALS AND METHODS

2.1. Participants

An N of 60 per group allows sufficient power (1 – β > 80%, α = .05) to detect the predicted moderate‐sized group differences on the key measures of interest (the objective assessments of oral health, OHRQoL and mental health), as well as to identify moderate‐sized associations between these constructs separately within each of the two groups. In total, 64 participants with a diagnosis of relapsing–remitting multiple sclerosis (RRMS) and 69 healthy controls contributed to this study. RRMS participants were recruited from general neurology and specialist MS clinics, and all met revised 2017 McDonald diagnostic criteria. ¹⁶ Demographically matched controls were recruited via community‐based advertising. All participants had a high level of English proficiency and normal, or corrected‐to‐normal, vision. Exclusion criteria for all participants included a current diagnosis or history of psychiatric or neurological illness, neurological disorder (other than RRMS for the MS group) and history of substance abuse.

2.2. Protocol

Ethical approval was provided by Mater Misericordiae Ltd Human Research Ethics Committee (HREC/18/MHS/81). After providing written informed consent, all participants were tested individually in a two‐hour individualised laboratory testing session. All assessments were completed by a fully qualified dental practitioner who had completed a Bachelor of Dental Surgery (BDS) and Master of Dental Surgery (MDS). Participants completed a measure of OHRQoL, an objective oral health assessment, a measure of oral care capacity, as well as a measure of mental health. Both groups also provided background demographic information, and for the RRMS group detailed information regarding disease duration, disease disability, age of onset and medication was obtained from clinical records. Participants were remunerated $20AUD per hour. A subset of the participants tested here also contributed to a separate study. ¹⁵

2.3. Measures

2.3.1. Expanded Disability Status Scale

The Expanded Disability Status Scale (EDSS) ¹⁷ was used to quantify MS disease severity. EDSS scores ranged from 0 (indicating that all functional systems were intact) to 8 (indicative of a severe level of disability).

2.3.2. Oral health‐related quality of life

The Oral Health Impact Profile OHIP‐14 ¹⁸ measures OHRQoL by assessing seven dimensions of impact: functional limitation, pain, psychological discomfort, physical disability, psychological disability, social disability and handicap. The OHIP‐14 consists of 14 items with five response items, ranging from 0 (‘never’) to 4 (‘fairly often’). Total scores range from 0 to 56, with higher scores indicative of poorer OHRQoL.

2.3.3. Oral health and hygiene

Oral health and hygiene were assessed by a qualified dentist using a disposable illuminated dental mirror and gentle digital palpation. The modified version of Ramfjord's Periodontal Disease Index ¹⁹ was used to visually measure the gingival status (Gingival Index), plaque (Plaque Index) and calculus levels (Calculus Index). A score for the tooth with the highest score in each sextant was recorded, instead of a score for the 6 specific index teeth, without the use of a periodontal probe. The Gingival Index was scored from 0 (absence of inflammation) to 3 (severe gingivitis consisting of swelling and marked redness); the Plaque Index also ranged from 0 (absence of plaque) to 3 (plaque covering more than half of interproximal, buccal and lingual surfaces); similarly, the Calculus Index was scored from 0 (absence of calculus) to 3 (a large amount of supra and subgingival calculus). The WHO criteria ²⁰ was used to record information on the number of decayed, missing and filled teeth (DMFT). The DMFT score range is between 0 and 32; a higher DMFT score indicates poorer dental condition. Data were also obtained on oral hygiene practices, number of dentist visits and presence/absence of other related oro‐maxillofacial pathologies.

2.3.4. Mental health

The Hospital Anxiety and Depression Scale (HADS) ²¹ was used to index mental health. The HADS has been extensively validated, and shown to have sound psychometric properties. ²² It is particularly suitable for use in neurological disorders such as MS as it omits somatic items that might be attributable to physical illness. The HADS consists of 14 items, seven of which index depression, seven of which index anxiety. Scoring for each item ranged from zero to three, with a sum score range of 0–42. Higher scores are indicative of poorer mental health.

2.3.5. Oral care capacity

The Dental Activities Test (DAT) ²³ is an objective performance‐based assessment, which taps into five domains essential to maintaining oral health: the capacity to manage dentally related medication (two items) to comprehend and follow instructions (two items), to perform oral hygiene (three items) and to perceive and react to oral health problems (three items). The DAT was designed to index global oral care capacity via a summative score. Scores on the task range from 0 to 9, with lower scores indicative of poorer oral care capacity.

2.4. Statistical analyses

All analyses were performed using IBM SPSS Statistical software for Windows version 28.0 and were considered significant at p < .05. Means and standard deviations (SD) were calculated for continuous variables; frequency and percentages were calculated for categorical variables. Independent sample‐t tests were used to establish whether the clinical and control groups were equated on background characteristics. For the primary dependent measures of interest (OHRQoL, oral health, mental health and oral care capacity), the two groups were compared using a series of one‐way between‐group ANOVAs, with estimates of partial eta squared (η _p ²) used to provide an indication of effect size. In instances where violations of the sphericity assumption occurred, degrees of freedom and p‐values were adjusted using Greenhouse–Geisser corrections. Pearson product–moment correlations were calculated to test correlates of OHRQoL in the MS and control groups separately. Because the relative strength of the association between OHRQoL with oral health versus mental health was also of interest here, to test the equality of these two correlations, asymptotic z‐tests were conducted. ²⁴

3. RESULTS

3.1. Background characteristics

Table 1 reports key background characteristics for the RRMS and control groups. Formal analyses of these results revealed no group differences with respect to age, t (131) = 0.13, p = .899, years of education, t (129) = 1.61, p = .109 or gender, χ ² (1, N = 133) = .03, p = .870. The two groups did however differ in employment status, with more than a third of the RRMS (but none of the control participants) unable to work owing to disability.

TABLE 1.

Demographic and clinical descriptive data for the two groups

Variable	RRMS (n = 64)	Control (n = 69)
	Mean (SD)/%	Mean (SD)
Demographic variables
Age (years)	43.4 (10.52)	43.6 (11.74)
Education (years)	13.8 (2.47)	14.5 (2.53)
Male	25 (39.0%)	26 (37.7%)
Employment status
Unemployed	4 (6.3%)	16 (23.2%)
Working	35 (54.7%)	43 (62.3%)
Cannot work due to disability	23 (35.9%)	0 (0%)
Retired	1 (1.6%)	2 (2.9%)
Studying	1 (1.6)%	8 (11.6%)
Clinical variables
Age at symptom onset	32.1 (9.15)	‐
Age at diagnosis	34.1 (8.30)	‐
Disease duration	10.8 (7.92)	‐
EDSS	2.8 (1.99)	‐
DMD therapy
Ocrelizumab	8 (15.1%)	‐
Alemtuzumab	7 (13.2%)	‐
Natalizumab	6 (11.3%)	‐
Dimethyl fumerate	6 (11.3%)	‐
Fingolimod	7 (13.2%)	‐
Cladribine	3 (5.7%)	‐
Peginterferon beta‐1a	1 (1.9%)	‐
Teriflunomide	1 (1.9%)	‐
None	15 (28.3%)	‐
Smoking status
Current smoker	20 (31.3)	11 (15.9)

Note: EDSS data were available for 49 RRMS participants.

Abbreviation: EDSS, Expanded Disability Status Scale.

Clinical characteristics are also reported in Table 1 for the RRMS participants (age at symptom onset, age at diagnosis, disease duration), as well as scores on the EDSS. The average EDSS score of 2.83 (SD – 1.99), indicated that most of the RRMS participants had a mild or moderate level of disability in one or more functional systems. Most (71.7%) participants in the RRMS group were taking a Disease Modifying Drug (DMD).

3.2. Oral health‐related quality of life, oral health, depression and oral care capacity

Table 2 reports descriptive and inferential statistics for measure of OHRQoL, as well as for the objective oral health assessment and measures of mental health and oral care capacity. These results show that the RRMS group report significantly poorer OHRQoL relative to controls. However, the two groups did not differ on most of the objective indicators of oral health, other than a significantly greater number of decayed teeth in the RRMS group. The RRMS group also reported significantly poorer mental health relative to controls. No group differences emerged on the measure of oral care capacity.

TABLE 2.

Descriptive and inferential statistics for the key dependent measures

Measure	RRMS (n = 64)	Control (n = 69)	Inferential statistics
	Mean (SD)	MEAN (SD)	F	df	p	η p 2
OHRQoL
OHIP‐14	10.4 (12.67)	6.2 (8.55)	5.18	131	.024	.038
Oral health
DMFT	10.1 (4.87)	9.9 (5.97)	0.06	131	.801	<.001
Decayed	1.4 (1.43)	0.9 (1.16)	5.37	131	.022	.039
Missing	5.3 (4.24)	5.9 (5.59)	0.53	131	.467	.004
Filled	3.4 (3.34)	3.0 (3.12)	0.42	131	.519	.003
Plaque Index	1.2 (0.37)	1.3 (1.36)	0.58	131	.449	.004
Calculus Index	1.2 (0.75)	1.14(1.59)	0.04	131	.846	<.001
Gingival Index	1.0 (0.56)	1.1 (1.80)	0.06	131	.813	<.001
Mental health
HADS	13.6 (7.08)	9.7 (5.15)	13.83	131	<.001	.096
Oral care capacity
DAT	8.7 (0.60)	8.8 (0.44)	2.42	131	.122	.018

Abbreviations: DAT, Dental Activities Test; HADS, Hospital Anxiety Depression Scale; OHIP‐14, Oral Health Impact Scale – 14 item version.

3.3. Correlates of OHRQoL

The final analyses focused on establishing whether there was any relationship between OHRQoL with oral health, mental health and oral care capacity. To reduce the number of correlations in these analyses, and because the different components of oral health were all significantly correlated (all ps < .05), for these analyses, a composite oral health score was calculated that consisted of the DMFT index and gingival index. Individual raw scores (Z) for each oral health variable were derived first and calculated by subtracting the population mean for a variable from the raw score and then dividing by the amount of variation of a set of values, that is standard deviation (SD). The average composite oral health score was then obtained by summing the two Z scores of the individual oral health variables then dividing by two.

The results of these analyses are reported in Table 3. In the RRMS group, although worse patient‐reported OHRQoL was significantly associated with both poorer oral health and mental health, the latter of these two correlations was significantly larger (Z = 2.30, p = .021). By contrast, in the control group, no significant association emerged between the measure of mental health and OHRQoL, but a large, significant association was evident with objectively assessed oral health. Again, the difference in magnitude between these two correlations was significant (Z = 1.98, p = .048). The only other significant association to emerge was in the RRMS group between OHRQoL and disease duration, which was moderate in magnitude. There were no significant associations between OHRQoL with either disease severity or performance on the DAT.

TABLE 3.

Pearson product–moment correlations with oral health‐related quality of life

Group	Oral health	HADS	DAT	Duration	EDSS
RRMS (n = 64)	.31*	.61***	.07	−.30*	−.01
Control (n = 69)	.50**	.20	−.15	‐	‐

Abbreviations: DAT, Dental Activities Test; Duration, number of years since diagnosis; EDSS, Expanded Disability Status Scale; HADS, Hospital Anxiety Depression Scale.

***p < .001; **p < .01; *p < .05.

4. DISCUSSION

The results from this study provide the first direct evidence that people living with the most common variant of MS (RRMS) report a level of OHRQoL that is significantly poorer than demographically matched controls. These results therefore align with a much broader literature which shows that quality of life is typically reduced in RRMS, ¹² but meaningfully extends it to show that this effect also emerges in the specific domain of oral health.

This study also adds to a much broader literature which shows that multiple factors can and do influence subjective complaints in neurological disorders, and most importantly, how objective impairment may not always be the most important determinant of these complaints. ¹¹ , ²⁵ This is because here, the variable that explained most variance in patient‐reported OHRQoL was not the objective measure of oral health, but instead the measure of mental health. This failure to find a strong degree of convergence between subjectively rated OHRQoL and objectively assessed oral health in the RRMS group also could not be attributed to problems with the oral health assessment. This is because, not only was the oral health assessment completed by a qualified dentist, but in the control group, the objective measure of oral health was significantly and strongly associated with scores on the OHRQoL (r = .50). In the control group too, the association between objective oral health and OHRQoL was significantly larger than the association between OHRQoL and mental health — and indeed, this latter association did not itself attain statistical significance.

Taken together, these findings therefore indicate that, for people living with MS — but not for demographically matched controls — perceptions of poor OHRQoL are more strongly reflective of mental health symptoms than compromised oral health. While this finding raises questions about the value that dental practitioners should place on RRMS patients' subjective oral health complaints, it is obviously insufficient to rely on a purely objective assessment of oral health without any patient‐reported subjective data. These findings instead highlight the importance of a multidisciplinary patient management team to help address secondary factors that might contribute to oral health concerns. This is particularly critical in cases where serious or persistent oral health concerns are reported, but no objective pathology can be identified. This study suggests that broader interventions focused on depression or anxiety management might play an important role in improving OHRQoL in this group.

Another important finding to emerge in this study was the absence of any group differences on the measure of oral care capacity. As noted previously, oral care capacity refers to the practical capacity to engage in oral self‐care. Although previous research has shown that reduced oral care capacity may mediate the association between cognition and oral health in older adults with cognitive impairment, ²³ there has been surprisingly little focus on oral care capacity in neurological disorders other than in age‐associated mild cognitive impairment or dementia, and only one that has used the DAT specifically. In this study, Liu et al. ²⁶ found that for stroke survivors, poorer cognitive and physical function were both associated with worse performance on the DAT assessment. Notably however, although Liu et al.'s ²⁶ study did not include a control group, the average DAT score of the stroke group was lower (7.95) than the RRMS participants in this study (8.66). Moreover, while in Liu et al.'s ²⁶ study some stroke participants scored as low as zero, the minimum score recorded by an RRMS participant in this study was 6, and 70.3% of the RRMS group scored at ceiling. Taken together, although broader literature shows that compromised oral care capacity can contribute to poor oral health in neurological disorders, this study reveals that this capacity is preserved in RRMS, and that there would be little value introducing the DAT into the standard clinical assessment of this neurological disorder.

However, an important caveat is that all participants with MS in this study were diagnosed with the relapsing–remitting variant of the disorder. Although these participants were selected as part of a deliberate recruitment strategy, as the focus here was on better understanding OHRQoL in the most common variant of MS, it also means that the conclusions of this study are restricted to this subtype. The next important step in this literature is therefore to establish whether the results of this study generalise to MS subtypes characterised by more severe symptomatology, such as chronic‐progressive variants of MS. Chronic‐progressive subtypes are more prevalent in older age groups, and typically present with a longer disease duration, more neurological symptoms and increased physical disabilities. ²⁷ It seems possible that for this more severe presentation of MS, oral disease‐related burden may be greater, objective oral health may be more important than mental health for understanding OHRQoL, and oral care capacity might also be reduced.

To conclude, these findings show that although OHRQoL is significantly poorer in people with RRMS, the variable that explained most variance in their OHRQoL was not the objective measure of oral health, but instead the measure of mental health. These findings therefore highlight the importance of multidisciplinary patient management teams when treating populations with complex needs, to help address secondary factors that contribute to oral health concerns.

AUTHOR CONTRIBUTIONS

All co‐authors took part in the conceptualisation and preparation of this manuscript. NM recruited the participants and completed the assessments. JDH performed the analysis, MRN wrote the first draft of the manuscript. NM, AS, HB, SB and JDH revised the manuscript.

FUNDING INFORMATION

Funding for this work was provided by Metro South Health Research Support Scheme (2020, #027). JDH was supported by an Australian Research Council Future Fellowship (FT170100096).

CONFLICT OF INTEREST

None.

PEER REVIEW

The peer review history for this article is available at https://publons.com/publon/10.1111/joor.13387.

Nangle MR, Manchery N, Swayne A, Boocock H, Blum S, Henry JD. Oral health‐related quality of life is more strongly correlated with mental health than with oral health in relapsing–remitting multiple sclerosis. J Oral Rehabil. 2023;50:62‐68. doi: 10.1111/joor.13387

DATA AVAILABILITY STATEMENT

The data that support the findings of this study are available from the corresponding author upon reasonable request.