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MATERIALS AND METHODS
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The model is summarised in Figure 1. The respective QoL score for the three latent variables subjective symptoms, objective symptoms and relationships were 72.4, 74.8 and 57.5 respectively. Their relative weighting was determined by their partial correlation coefficients (r2) and returned values for the path coefficients of 0.485, 0.193 0.381 respectively. These relationships are summarised in Figure 1. The QLI is then calculated by the following equation:
QLI = 0.485× Score subjective symptoms +0.193× Score objective symptoms+0.381×Score relationship. The calculated mean QLI for our subjects is 67.7. A QLI exceeding 50 is regarded as reflecting significant impairment of QoL and was shown in 74% of our patients.
Though both subjective symptoms and objective symptoms have high scores at 72 to 75, the major drivers of impaired quality of life are subjective symptoms and relationships, with partial coefficients (r2) values of 56.3 and 34.8; the the contribution of objective symptoms by contrast is low in comparison at 8.9.
The relative impact of the three latent variables is summarised in Figure 2. Here the y-axis represents the path coefficient, a measure of the relative weighting of the variable to the overall score, while the x-axis represents the QLI score for each variable. Variables falling in the right upper quadrant are highly significant in that they have both a high QLI and a high weighting.
Variables falling in the left lower quadrant are of less significance in that they have a lower QLI and lower impact. The other two quadrants represent high QLI/low weighting and low QLI/high weighting respectively. Subjective symptoms is shown to be the most critical factor.
For each latent variable, the relative impact of the component manifest variables are shown in Figures 3-5. The most critical variables are again those in the upper right quadrant which represent a high QLI and high weighting. For the latent variable subjective symptoms, the highest-ranking concerns are: fear that children may develop alopecia, regret at personal appearance, inability to forget the presence of the problem, fear that it might spread and worries about cost implications. The highest-ranking concerns in terms of the latent variable relationships are embarrassment in social interaction, having to explain one’s appearance to other people, fear of presenting an unpleasant appearance to other people, and fear of appearing unkempt. Concerns about contagiousness and deterioration in work or study performance are not significant factors. The manifest variables contributing to objective symptoms: scalp visibility; itch and physical hair loss on hair grooming are not major factors in their own right.
We identified age as an important factor influencing QoL. A radar plot summarising overall QLI, as well as the mean score for each of the latent variables, is shown in Figure 6. The mean values for the age groups 21-40, 41-16 and 60+ are plotted. Patients appear to become more accepting of their condition with increasing age.
DISCUSSION
Alopecia is highly prevalent. In a recent retrospective survey of 6,664 African patients seen in a predominantly black urban dermatology practice in Durban, hair disorders in general and CCCA in particular, accounted for 5.2% and 0.4% of all skin conditions seen respectively, and
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constituted the fifth commonest skin disorder among black South Africans25. Studies have reported traction alopecia and central centrifugal cicatricial alopecia (CCCA) as the most common types seen in women of African ancestry23. In the present study lichen planus pigmentosus (LPP) and its variants constituted the most prevalent type of alopecia. The frontal fibrosing alopecia pattern was the most common. It is often recognised early as it affects the hairline unlike other hair disorders such as the patchy manifestations of LPP or CCCA, which are usually not noticed until they affect hair density. 64% of our patients reported a history of alopecia for more than one year, and only 12% of the participants had sought medical assistance within the first six months of onset. The delay in consultation could conceivably be due to a lack of understanding of alopecia by the patient, and particularly a failure to understand that there is a potential for irreversible scarring.
Given the major role that hair plays in the identity and self-image of women, it is not surprising that our study has shown a significant impairment in QoL in our patients. This is consistent with other reports6,12,19. Some of our patients were pre-occupied by the condition to the point of obsession. They worried about the cause, which they often do not know, their fear being compounded by societal misperceptions, such as an association between alopecia and HIV/AIDS. This was a cause of serious worry to 52% of the patients.
This is a preliminary study intended to pilot a model for determination of QLI, and is limited by sample size and selection bias. Our statistical model and the calculation of QLI in the identification of the determinants of QoL appears to hold promise and will be further refined and validated. Future prospective longitudinal studies and studies using a cross-sectional design will provide more definitive data on the impact of alopecia in African patients on QoL, and how the perceptions of those with the disease evolve over time. Finlay has recently stressed the importance of rigorous standards in reporting QoL studies in dermatology (and indeed in medicine generally), and has suggested that a set of minimum standards should be agreed11. It is therefore necessary that such follow-up studies conform to these standards.
Our study does however provide strong evidence that alopecia has a significant deleterious impact on QoL in this population, and has provided some indication of the principal factors affecting this as perceived by the patients. We therefore believe it essential that physicians address the psychosocial aspects of alopecia as part of the management of their patients. There may be significant psychological comorbidity in terms of anxiety and depression12, and a multi- faceted approach involving psychologists, social workers and support groups is likely to be of benefit.
ACKNOWLEDGEMENTS:
We thank Prof David Katerere (Tshwane University of Technology), Dr Themba Mabaso of Durdoc Medical Centre, Dr Rosanna Izzo (University of Naples) for their invaluable contribution and critical review of this work.
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4 Sperling LC, Solomon AR, Whiting DA. A new look at scarring alopecia. Arch Dermatol 2000; 136: 235-42.
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6 McMichael AJ. Ethnic hair update: past and present. J Am Acad Dermatol 2003; 48: S127-S33.
7 Finlay AY. Quality of life indices. Indian Journal of Dermatology, Venereology, and Leprology 2004; 70: 143.
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9 Dalgard F, Gieler U, Tomas-Aragones L, Lien L, Poot F et al. The Psychological Burden of Skin Diseases: A Cross-Sectional Multicenter Study Among Dermatological Out- Patients in 13 European Countries. J Invest Dermatol 2014.
10 Finlay AY. The burden of skin disease: quality of life, economic aspects and social issues. Clin Med 2009; 9: 592-4.
11 Dalgard F, Gieler U, Tomas-Aragones L, Lien L, Poot F et al. The psychological burden of skin diseases: a cross-sectional multicentre study among dermatological out-patients in 13 European countries. J Invest Dermatol 2014.
12 Cartwright T, Endean N, Porter A. Illness perceptions, coping and quality of life in patients with alopecia. Br J Dermatol 2009; 160: 1034-9.
13 Biondo S, Sinclair R. Quality of life in Australian women with female pattern hair loss.
Open Dermatol J 2010; 4: 90-4.
14 Van der Donk J, Hunfeld J, Passchier J, Knegt-Junk K, Nieboer C. Quality of life and maladjustment associated with hair loss in women with alopecia androgenetica. Soc Sci Med 1994; 38: 159-63.
15 Van der Donk J, Passchier J, Knegt-Junk C, van der Wegen-Keijser MH, Nieboer C et al. Psychological characteristics of women with androgenetic alopecia: a controlled study. Br J Dermatol 1991; 125: 248-52.
16 Camacho F, García‐Hernández M. Psychological features of androgenetic alopecia. J Eur Acad Dermatol Venereol 2002; 16: 476-80.
17 Gibbs S. Skin disease and socioeconomic conditions in rural Africa: Tanzania. Int J Dermatol 1996; 35: 633-9.
18 Schmidt S, Fischer T, Chren M, Strauss B, Elsner P. Strategies of coping and quality of life in women with alopecia. Br J Dermatol 2001; 144: 1038-43.
19 Hunt N, McHale S. The psychological impact of alopecia. Br Med J 2005; 331: 951.
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20 Al-Mutairi N, Eldin ON. Clinical profile and impact on quality of life: seven years experience with patients of alopecia areata. 2011.
21 Mosam A, Vawda N, Gordhan A, Nkwanyana N, Aboobaker J. Quality of life issues for South Africans with acne vulgaris. Clin Exp Dermatol 2005; 30: 6-9.
22 Hariram P, Mosam A, Aboobaker J, Esterhuizen T. Quality of life in psoriasis patients in KwaZulu Natal, South Africa. Indian Journal of Dermatology, Venereology, and Leprology 2011; 77: 333.
23 Callender VD, McMichael AJ, Cohen GF. Medical and surgical therapies for alopecias in black women. Dermatol Ther 2004; 17: 164-76.
24 Halder R, Grimes P, McLaurin C, Kress M, Kenney Jr J. Incidence of common dermatoses in a predominantly black dermatologic practice. Cutis; cutaneous medicine for the practitioner 1983; 32: 388, 90.
25 Dlova NC, Mankahla A, Madala N, Grobler A, Tsoka-Gwegweni J et al. The spectrum of skin diseases in a black population in Durban, KwaZulu-Natal, South Africa. Int J Dermatol 2015; 54: 279-85.
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TABLE 1
Summary of manifest variables, participant responses and calculated loading, with standard error of the mean (SEM) and interquartile range (IQR). Responses are classified as follows: A:
Distresses me very much; B: A lot; C: A little; D: Not at all.
Participant responses
Manifest Variables A B C D Mean
loading
Std.
Error IQR Latent variable: Subjective symptoms
I am uncomfortable using a wig. 56% 16% 14% 14% 0.760 0.078 0.64-0.91 I need to hide my condition with hats and
bandanas 44% 16% 06% 34% 0.838 0.049 0.74-0.93
It costs me a lot of money to look after
my hair. 42% 24% 20% %14 0.937 0.019 0.91-0.98
I am saddened by the appearance of my
hair /eyebrows/eyelashes 5% 24% 08% 16% 0.971 0.009 0.95-0.99 I worry about having this hair problem
for the rest of my life. 66% 16% 12% 06% 0.955 0.014 0.94-0.98 I cannot forget that i have this hair
problem 52% 22 14% 10% 0.969 0.007 0.96-0.98
I worry that it might spread. 50% 26 08 16 0.969 0.011 0.945-0.986 I do not like to be seen without a wig in
front of my partner/relative.
YES 60%
NO
40% 0.598 0.145 0.281-0.825
I am afraid my children may have
alopecia 54% 14% 08% 24% 0.975 0.007 0.962-0.987
Latent variable: Objective symptoms
My scalp is visible 38% 30% 24% 08% 0.970 0.012 0.941-0.988 I lose tufts of hair when I comb or
shampoo 22% 22% 40% 16% 0.883 0.033 0.819-0.940
I feel itchy on my scalp. 26% 14% 30% 30% 0.952 0.018 0.914-0.980
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Participant responses
Manifest Variables A B C D Mean
loading
Std.
Error IQR Latent variable: Relationships
I feel that people find it unpleasant to
look at me? 32% 14% 30% 22% 0.967 0.009 0.95-0.98
I feel that other people notice my
hair/eyebrows/eyelashes 26% 38% 22% 14% 0.938 0.0144 0.92-0.97 I am afraid that people think my hair is
not well cared for. 24% 30% 26% 20% 0.964 0.010 0.94-0.98 I am embarassed when going out to a
party or function 40% 16% 16% 28% 0.971 0.009 0.95-0.99 have to explain to others what is wrong
with my hair 34% 32% 14% 20% 0.952 0.014 0.93-0.98
I feel that others are afraid of catching
disease from me 12% 8% 22% 58 0.861 0.055 0.74-0.941
My work and studies have deteriorated
because of my hair loss 14% 20% 12% 54% 0.893 0.0501 0.797-0.96
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FIGURE LEGENDS Figure 1
Summary of the structural equation model, indicating impact and relative weighting of the three latent variables Subjective symptoms, Objective symptoms and Relationships, and of 19 manifest variables on these. l represents loading, p.c. the path coefficiient, R2 the R squared coefficient and c.i. the confidence interval.
Figure 2
The impact of the three latent variables on QoL, as measured by the QLI. Variables falling in the right upper quadrant have the highest impact in that they have both a high QL score and a high weighting.
Figure 3
Subjective symptoms: The impact of the relevant manifest variables on QOL, as measured by the QLI. Variables falling in the right upper quadrant have the highest impact in that they have both a high QL score and a high weighting.
Figure 4
Objective symptoms: The impact of the relevant manifest variables on QOL, as measured by the QLI. Variables falling in the right upper quadrant have the highest impact in that they have both a high QL score and a high weighting.
Figure 5
Relationships: The impact of the relevant manifest variables on QOL, as measured by the QLI.
Variables falling in the right upper quadrant have the highest impact in that they have both a high QL score and a high weighting.
Figure 6
Radar plot indicating overall QLI and mean QLI for each latent variable for three age groups.
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FIGURE 1
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FIGURE 2
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FIGURE 3
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FIGURE 4
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FIGURE 5
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FIGURE 6
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