Abstract
Background:
The prevalence and pattern of skin diseases are influenced by the overall ecosystem of the region. There is a dearth of research about prevalence, health-care seeking, compliance, and treatment outcome in skin diseases among scheduled tribes.
Objectives:
The aim of this study is to understand the magnitude of skin diseases in tribal area of Dahod, Gujarat using a simple “Store and Forward” technique of teledermatology.
Materials and Methods:
A cross-sectional study was conducted in 10 randomly selected villages of Dahod and Jhalod blocks of Dahod district of Gujarat during June–August 2017. Trained surveyors visited households randomly in different localities (called Faliya) of each village ensuring representativeness. Survey responses were captured on mobile-based MAGPI portal, and images of skin conditions were capture on smart phones, and de-identified images were transferred over WhatsApp.
Results:
A total of 781 households were approached in 10 villages and 2214 participants consented. Among them, 549 were identified with suspected skin diseases, but 520 consented for photograph. The skin diseases were more prevalent among males, children, and elderly. Of 520, 44 (8.5%) could not be assess due to poor quality photograph and 35 (6.7%) did not have any clinically significant condition. Thus, of 2214 participants, 441 (20%) had skin diseases, and infections and eczema were major conditions constituting two-third of the skin diseases in the study population. The treatment-seeking behavior and compliance to treatment was poor.
Conclusion:
Considering the high prevalence of skin diseases in tribal villages of Dahod, Gujarat coupled with limited availability of trained dermatologist, new innovative avenues like teledermatology should be explored.
Keywords: Epidemiology, prevalence, skin diseases, teledermatology, tribal
INTRODUCTION
Skin is the largest organ of human body. The prevalence and pattern of skin diseases are influenced by the overall ecosystem of the region including sociocultural milieu, topography, nutrition, genetics, etc.[1] There have been some attempts of profiling skin diseases through hospital-based studies.[2,3,4] The prevalence of skin diseases was reported a bit low in hospital settings[1,2,3,4,5] as compared to community-level medical camps.[6,7] It varies from 4.2% to 11.6% in the general population. However, the prevalence is reported quite high (30%–40%) in pediatric population.[6,8] Surprisingly, a recent community-based survey in the central India reported very high prevalence (60%) of skin diseases.[9]
The prevention and management of skin diseases received less attention in the past decades due to low mortality rates. However, a recent Global Burden of Disease Study finding revealed that skin diseases rank 18 in top 20 diseases in terms of Disease Adjusted Life Years (DALYs) and is fourth leading cause of nonfatal disease burden.[10] Skin diseases contributed about 2% of the global burden of diseases measured in DALYs.[11] Further, skin diseases increase clinical depression and anxiety as well as suicidal ideation.[12]
In general, skin diseases require long-term treatment and the treatment is costly. In a developing country like India, treatment seeking and treatment compliance are marred by poor health-care delivery system and catastrophic out-of-pocket health expenditure.[13]
Appropriate management of skin diseases requires accurate diagnosis by primary physician. Regrettably, the evidence indicates incompetency of primary physicians in diagnosing skin diseases accurately.[14] Innovative approaches are required for effective identification and management of skin diseases. Teledermatology is simply dermatologic care through Information and Communication Technology.[15] Although it can be expanded to research, evaluation and education as well.[16] The advantages of teledermatology are reported unequivocally with respect to reliability, accuracy, accessibility as well as cost reduction.[15,16,17]
The state of Gujarat has about 15% tribal population[18] and most tribal areas are categorized as “high priority” from healthcare perspective by the state government. While “high priority” categorization could be attributed to lagging maternal and child health indicators compared to nontribal areas, epidemiological studies are called for to understand magnitude of illnesses, health-care seeking, medication adherence, and treatment outcome among scheduled tribes. Tribal population has some pros and cons with respect to skin diseases. On one hand, the population is protected against industrial pollutants and overcrowded housing. On the other hand, lack of hygiene and sanitation and poor access to healthcare, especially specialty services increase the risk of skin diseases.
The study was carried out to understand the magnitude of skin diseases in tribal villages of Dahod, Gujarat and identify population subgroups that need targeted interventions.
MATERIALS AND METHODS
A community-based cross-sectional study was conducted in 10 randomly selected villages of Dahod and Jhalod blocks of Dahod district of Gujarat, India during June–August 2017. A list of villages within 20 km periphery from Dahod city in Dahod and Jhalod blocks was prepared. Ten villages from these two blocks were selected randomly by computer generated random numbers using WINPEPI software (Developed by Professor Joe Abramson available at http://www.brixtonhealth.com/pepi4windows.htmlhttp://www.brixtonhealth.com/pepi4windows.html). Field surveyors were trained by experienced dermatologist of a tertiary care teaching hospital. The surveyors consisted three qualified social workers and three female nurses. The training consisted of technical competencies, namely identifying basic primary skin lesions, capturing good quality photographs of suspected lesions (background selection, close up, adjusting angle etc.). This was followed by training in administrative competencies, namely explaining the study, seeking consent for data and photographs, and transferring de-identified survey data and photographs.
Surveyors visited few households randomly in different residential clusters (called Faliya) of each village ensuring representativeness of the sample. Every member present in the household, regardless of their age (except children <5 years of age) and sex, and belonging to the family were explained about the study and consent was sought. Written informed consent for screening as well as photographs of skin condition (s) was obtained from each family member as applicable. As the survey was conducted in the morning and afternoon hours, most of the children were attending the schools. Hence, four schools surrounding study villages were visited by the surveyors to include these children in the study.
The study was performed using “Store and Forward” technique of teledermatology. A structured questionnaire was developed by investigators in a vernacular language and responses were recorded on mobile-based MAGPI portal, which also allows offline data collection. Questionnaire consisted sociodemographic details, details of general physical examination, known medical history of skin conditions (including recurrence), treatment (s) undergone/ongoing, and medication adherence.
On consent, survey questionnaire was filled and general physical examination was carried for diagnosing probable skin condition (s). If medical history or physical examination revealed any skin lesion/condition, picture of probable skin condition (s) was captured by field surveyor using their smartphones.
De-identified pictures along with individual's study identification number were then transmitted through WhatsApp to research coordinator and consultant dermatologist. Skin conditions were diagnosed and reported by dermatologist at a tertiary care teaching hospital, situated about 200 km from the study villages. The diagnosis was entirely based on clinical observation of pictures transmitted through WhatsApp, and no clinical assessment or dermatological investigations were performed by a dermatologist. Classification and grouping of skin conditions for the purpose of this study were done by consultant dermatologist. The participants with skin diseases were provided with the diagnosis and referred to the primary health center/community health center for further management.
Sample size
The aim of the study was to estimate the prevalence and pattern of skin diseases in the tribal population and hence, sufficiently large sample size was required to get stable estimates of the parameters. In the absence of any background study in this tribal region, we assumed 50% prevalence of skin diseases. To estimate a proportion of 50%, a random sample of 385 was required with 95% confidence level and 5% acceptable difference. However, considering feasibility, 10 villages were selected randomly to ensure representativeness and the stability of estimates even in subgroup analysis. A total sample size was expected to be about 2000.
The study was approved by the Institutional Ethics Committee.
Statistical analysis
Data were retrieved and exported from admin panel of MAGPI in Excel sheet format and transformed into statistical software STATA (version 14.2, Stata Corporation, Texas, USA). Descriptive statistics (frequency [%]) was used to assess the prevalence of skin diseases. Chi-square test was performed to evaluate differences in the prevalence and pattern of skin diseases among different population subgroups. A value of P = 0.05 was considered statistically significant.
RESULTS
A community-based clinical skin examination was conducted in 781 households of 10 villages in Dahod district. Of 2256 participants approached, 2214 (98.1%) consented and participated in the study. Of 2214 participants, 549 were identified with suspected skin diseases and only 520 (94.7%) consented for photographs. Most of the participants were below 40 years of age, illiterate and below poverty line. The gender distribution was similar. The skin diseases were more prevalent in males as compared to females. The prevalence was more in pediatric age group as well as older age groups [Table 1].
Table 1.
Profile of study participants and suspected cases
| Variable | Overall frequency (%) (n=2214) | Suspected frequency (%) (n=520)* | P |
|---|---|---|---|
| Age (years) | |||
| <18 | 766 (34.6) | 196 (25.6) | <0.001 |
| 19–40 | 810 (36.6) | 133 (16.4) | |
| 41–60 | 467 (21.1) | 127 (27.2) | |
| >60 | 171 (7.7) | 64 (37.4) | |
| Sex | |||
| Male | 1021 (46.1) | 282 (27.6) | <0.001 |
| Female | 1193 (53.9) | 238 (20) | |
| Education† | |||
| No schooling | 900 (40.7) | 226 (25.1) | 0.32 |
| Primary | 686 (31) | 155 (22.6) | |
| Secondary/higher secondary | 556 (25.1) | 121 (21.8) | |
| Diploma | 37 (1.7) | 9 (24.3) | |
| Graduate | 31 (1.4) | 8 (25.8) | |
| Postgraduate | 4 (0.3) | 1 (25) | |
| Socioeconomic status‡ | |||
| Above poverty line | 382 (17.3) | 84 (22) | 0.45 |
| Below poverty line | 1795 (81.1) | 427 (23.8) | |
| Not known | 37 (1.7) | 9 (24.3) |
*Percentage was calculated based on overall frequency in that category, †The categories were collapsed into no schooling, primary and secondary/higher secondary/diploma/graduate/postgraduate for calculating P value, ‡The category “Not known” was not included for calculating Pvalue
Of 520 identified as suspected cases by the surveyors, 35 (6.7%) did not have any significant skin disease, whereas the dermatologist could not opine about the skin disease in 44 (8.5%) cases due to poor quality of photographs. Thus, of 2214 participants, 441 (20%) had skin diseases as confirmed by consultant dermatologist. Infections and eczema were major conditions and constituted two-third of the skin diseases [Table 2].
Table 2.
Pattern of skin diseases in Dahod
| Variable | n | Category | Frequency (%) |
|---|---|---|---|
| Skin disease | 520 | Infection | 142 (27.3) |
| Eczema | 175 (33.7) | ||
| Papulosquamous | 31 (6) | ||
| Pigmentry | 29 (5.6) | ||
| Unclassified | 64 (12.3) | ||
| Undiagnosed | 79 (15.2) | ||
| Infection | 142 | Viral | 3 (2.1) |
| Warts | 3 (2.1) | ||
| Bacterial | 47 (33.1) | ||
| Furuncle | 2 (1.4) | ||
| Impetigo | 22 (15.5) | ||
| Periporitis | 2 (1.4) | ||
| Pyoderma | 20 (14.1) | ||
| Folliculitis | 1 (0.7) | ||
| Fungal | 90 (63.4) | ||
| Dermatophytoses | 56 (39.4) | ||
| Tinea versicolor | 33 (23.2) | ||
| Onychomycosis | 1 (0.7) | ||
| Parasitic | 2 (1.4) | ||
| Scabies | 2 (1.4) | ||
| Eczema | 175 | Acute Eczema | 1 (0.6) |
| Sub-acute Eczema | 5 (2.9) | ||
| Chronic Eczema | 126 (72) | ||
| Exogeneous | 43 (24.6) | ||
| Papulosquamous disorders | 31 | Lichen planus | 3 (9.7) |
| Pityriasis rosea | 1 (3.2) | ||
| Pityriasis alba | 18 (58.1) | ||
| Plantar fissures | 2 (6.5) | ||
| Psoriasis | 7 (22.6) | ||
| Pigmentary disorders | 29 | Idiopathic guttate hypomelanosis | 4 (13.8) |
| Melasma | 4 (13.8) | ||
| Postinflammatory pigmentation | 5 (17.2) | ||
| Steroid induced hypopigmentation | 2 (7) | ||
| Vitiligo | 14 (48.3) | ||
| Unclassified | 64 | Acne vulgaris | 12 (18.8) |
| Alopecia areata | 3 (4.7) | ||
| Callosity | 2 (3.1) | ||
| Insect bite | 2 (3.1) | ||
| Keloid | 2 (3.1) | ||
| Milia | 7 (10.9) | ||
| Molluscum contagiosum | 2 (3.1) | ||
| Pellagrous dermatitis | 2 (3.1) | ||
| Seborrheic dermatitis | 4 (6.3) | ||
| Seborrheic kersatoses | 5 (7.8) | ||
| Xerosis | 14 (21.9) | ||
| Others* | 9 (14.1) | ||
| Undiagnosed | 79 | Not significant dermatoses | 35 (44.3) |
| Photos not clear | 44 (55.7) |
*Others include acanthosis nigricans, aphthous ulcers, Discoid lupus erythematosus (DLE), intertrigo, purpura, skin tag, tattoo reaction, urticaria and lipoma
About half the participants with confirmed skin disease (257 [49.4%]) had been suffering from the disease for more than 6 months. Most of them (402 [77.3%]) developed the condition gradually. Surprisingly, only 247 (47.5%) out of 520 participants suspected of skin disease have consulted medical professional for the condition. Recurrence (188 [76.1%]) and no improvement (34 [13.8%]) were major causes for the discontinuation of treatment.
DISCUSSION
Although underestimated, the prevalence of skin diseases in the tribal area of Dahod, Gujarat was high. Infections and eczema constituted bulk of the skin diseases. The skin diseases were more prevalent in pediatric and older age groups and males. The treatment seeking and compliance to treatment was poor.
In Indian context, there were few attempts to determine pattern of skin diseases through hospital based studies.[1,2,3,4,5] There were also some attempts to determine prevalence of skin diseases in community settings through medical camps[6,7,8] but attempts to screen the entire community are rare.[9] This is probably first study to determine prevalence and pattern of skin diseases in the scheduled tribe community.
The prevalence of skin diseases in the general population in different geographic regions of India varies from 7.9% to 60%.[6,7,8,9] The staggering proportion of infections and eczema in the current study might indicate poor living conditions and hygiene in the tribal area of Gujarat. The poor health seeking behavior of the participants with confirmed skin diseases might be ascribable to poor health infrastructure as well as poor treatment outcome.
Primary care physicians (PCPs) serve as first contact for most patients seeking medical advice. Unfortunately, they lack knowledge in identifying skin diseases.[14,19,20] Further, the use of potent steroids and irrational use of corticosteroids is common even in tertiary care setting.[21,22] A recent study conducted near the study area also reported the lack of knowledge in identifying and management of skin diseases and highlighted the need of training PCPs.[23] Further research could be directed to explore diagnostic skills and management practices of skin diseases among PCPs in remote rural/tribal villages. Empowering PCPs in the identification and management of skin diseases is need of the hour.[14,20,23] A facility-based training module helped general practitioners improve diagnostic accuracy and referral pattern for common skin lesions.[24]
Tele-dermatology can bridge the gap to improve the identification and management of skin diseases in rural/tribal settings where consultant dermatologists are almost nonexistent. The current study demonstrated the usefulness of primitive teledermatology technique, namely “Store and Forward.” However, there were some technological challenges faced during the study. Storage and proper transmission of photographs lacked in about 8% cases. Furthermore, image resolution was compromised due to transfer using WhatsApp.
Real-time interactive as well as hybrid techniques of teledermatology have been tested successfully in the past, but these techniques need sophisticated interface and connectivity.[15,16,17] Integrating dermatology departments of medical colleges with primary care centers might serve as the first feasible and sustainable step in addressing the issue.
Furthermore, advances in machine learning, neural networks and artificial intelligence can be leveraged for point-of-care clinical diagnosis of skin diseases. Initial research has already shown positive results about the accuracy of such applications in the diagnosis of some common skin diseases.[25]
CONCLUSION
Considering high prevalence of skin diseases in tribal villages of Dahod, Gujarat coupled with the inability of PCPs in the identification and management of skin diseases, new innovative avenues like teledermatology should be explored. Empowering PCPs along with advanced methods of teledermatology and artificial intelligence may be developed to attain accurate identification and evidence-based management of skin diseases in underprivileged communities.
Financial support and sponsorship
Nil.
Conflicts of interest
There are no conflicts of interest.
REFERENCES
- 1.Kar C, Das S, Roy AK. Pattern of skin diseases in a tertiary institution in Kolkata. Indian J Dermatol. 2014;59:209. doi: 10.4103/0019-5154.127707. [DOI] [PMC free article] [PubMed] [Google Scholar]
- 2.Dimri D, Reddy BV, Kumar Singh A. Profile of skin disorders in unreached hilly areas of North India. Dermatol Res Pract. 2016;2016:8608534. doi: 10.1155/2016/8608534. [DOI] [PMC free article] [PubMed] [Google Scholar]
- 3.Jawade SA, Chugh VS, Gohil SK, Mistry AS, Umrigar DD. A clinico-etiological study of dermatoses in pediatric age group in tertiary health care center in South Gujarat region. Indian J Dermatol. 2015;60:635. doi: 10.4103/0019-5154.169147. [DOI] [PMC free article] [PubMed] [Google Scholar]
- 4.Devi T, Zamzachin G. Pattern of skin diseases in Imphal. Indian J Dermatol. 2006;51:149–50. [Google Scholar]
- 5.Agarwal S, Sharma P, Gupta S, Ojha A. Pattern of skin diseases in Kumaun region of Uttarakhand. Indian J Dermatol Venereol Leprol. 2011;77:603–4. doi: 10.4103/0378-6323.84073. [DOI] [PubMed] [Google Scholar]
- 6.Grover S, Ranyal RK, Bedi MK. A cross section of skin diseases in rural Allahabad. Indian J Dermatol. 2008;53:179–81. doi: 10.4103/0019-5154.44789. [DOI] [PMC free article] [PubMed] [Google Scholar]
- 7.Rao GS, Kumar SS, Sandhya Pattern of skin diseases in an Indian village. Indian J Med Sci. 2003;57:108–10. [PubMed] [Google Scholar]
- 8.Dogra S, Kumar B. Epidemiology of skin diseases in school children: A study from Northern India. Pediatr Dermatol. 2003;20:470–3. doi: 10.1111/j.1525-1470.2003.20602.x. [DOI] [PubMed] [Google Scholar]
- 9.Jain S, Barambhe M, Jain J, Jajoo U, Pandey N. Prevalence of skin diseases in rural Central India: A community-based, cross-sectional, observational study. J Mahatma Gandhi Inst Med Sci. 2016;21:111–5. [Google Scholar]
- 10.Hay RJ, Johns NE, Williams HC, Bolliger IW, Dellavalle RP, Margolis DJ, et al. The global burden of skin disease in 2010: An analysis of the prevalence and impact of skin conditions. J Invest Dermatol. 2014;134:1527–34. doi: 10.1038/jid.2013.446. [DOI] [PubMed] [Google Scholar]
- 11.Karimkhani C, Dellavalle RP, Coffeng LE, Flohr C, Hay RJ, Langan SM, et al. Global skin disease morbidity and mortality: An update from the global burden of disease study 2013. JAMA Dermatol. 2017;153:406–12. doi: 10.1001/jamadermatol.2016.5538. [DOI] [PMC free article] [PubMed] [Google Scholar]
- 12.Dalgard FJ, Gieler U, Tomas-Aragones L, Lien L, Poot F, Jemec GBE, et al. The psychological burden of skin diseases: A cross-sectional multicenter study among dermatological out-patients in 13 European countries. J Invest Dermatol. 2015;135:984–91. doi: 10.1038/jid.2014.530. [DOI] [PMC free article] [PubMed] [Google Scholar]
- 13.Pandey A, Ploubidis GB, Clarke L, Dandona L. Trends in catastrophic health expenditure in India: 1993 to 2014. Bull World Health Organ. 2018;96:18–28. doi: 10.2471/BLT.17.191759. [DOI] [PMC free article] [PubMed] [Google Scholar]
- 14.Patro BK, Tripathy JP, De D, Sinha S, Singh A, Kanwar AJ. Diagnostic agreement between a primary care physician and a teledermatologist for common dermatological conditions in North India. Indian Dermatol Online J. 2015;6:21–6. doi: 10.4103/2229-5178.148927. [DOI] [PMC free article] [PubMed] [Google Scholar]
- 15.Bashshur R, Shannon G, Tejasvi T, Kvedar J, Gates M. The empirical foundations of tele-dermatology: A review of the research evidence. Telemed J E Health. 2015;21:953–79. doi: 10.1089/tmj.2015.0146. [DOI] [PMC free article] [PubMed] [Google Scholar]
- 16.Tensen E, van der Heijden JP, Jaspers MW, Witkamp L. Two decades of teledermatology: Current status and integration in national healthcare systems. Curr Dermatol Rep. 2016;5:96–104. doi: 10.1007/s13671-016-0136-7. [DOI] [PMC free article] [PubMed] [Google Scholar]
- 17.Whited J. Tele-dermatology. Med Clin North Am. 2015;99:1365–79. doi: 10.1016/j.mcna.2015.07.005. [DOI] [PubMed] [Google Scholar]
- 18.Registrar General of India, Ministry of Home Affairs, Government of India. Census, Gujarat – Population Census Abstracts. Registrar General of India, Ministry of Home Affairs, Government of India. 2011. [Last accessed on 2019 Apr 03]. Available from: http://www.censusindia.gov.in .
- 19.Rübsam ML, Esch M, Baum E, Bösner S. Diagnosing skin disease in primary care: A qualitative study of GPs' approaches. Fam Pract. 2015;32:591–5. doi: 10.1093/fampra/cmv056. [DOI] [PubMed] [Google Scholar]
- 20.Kownacki S. Skin diseases in primary care: What should GPs be doing? Br J Gen Pract. 2014;64:380–1. doi: 10.3399/bjgp14X680773. [DOI] [PMC free article] [PubMed] [Google Scholar]
- 21.Bylappa B, Patil R, Pillai R. Drug prescribing pattern of topical corticosteroids in dermatology unit of a tertiary-care hospital. Int J Med Sci Public Health. 2015;4:1702–7. [Google Scholar]
- 22.Krishna J, Singh A, Goel S, Roy A, Singh A, Yadav K. Clinical pharmacological study of prescribing pattern of dermatological drugs from a tertiary care teaching hospital. Indian J Sci Res. 2015;6:41–5. [Google Scholar]
- 23.Thakkar SH, Chavda PD, Mehta KG. Do primary care physicians require training in core clinical dermatology? A cross sectional needs assessment study from Western India. Indian J Dermatol Venereol Leprol. 2019;85:380–7. doi: 10.4103/ijdvl.IJDVL_250_18. [DOI] [PubMed] [Google Scholar]
- 24.Beecher SM, Keogh C, Healy C. Dedicated general practitioner education sessions can improve diagnostic capabilities and may have a positive effect on referral patterns for common skin lesions. Ir J Med Sci. 2018;187:959–63. doi: 10.1007/s11845-018-1788-z. [DOI] [PubMed] [Google Scholar]
- 25.Kolkur M, Kalbande D, Kharkar V. Machine learning approaches to multi-class human skin disease detection. Int J Comput Intell Res. 2018;14:29–39. [Google Scholar]
