A Community Based Study to Estimate Prevalence and Determine Correlates of Premature Graying of Hair among Young Adults in Srinagar, Uttarakhand, India.

BACKGROUND: There are several ways by which aging is identified, of which graying of hair is perhaps the most common way. Nowadays, graying of hairs, which was expected to occur after 40s, can be easily observed among younger age group, even before 20s. The present study aims to estimate the prevalence of graying of hairs and its correlates among young adults in Srinagar, Uttarakhand, India.
METHODOLOGY: A community-based cross-sectional study was conducted among 384 young adults between 15 and 30-year age group in the urban area of Srinagar tehsil of Pauri district. Graying of hair was assessed on the basis of the number of white hairs on examination of scalp.
RESULTS: The prevalence of premature graying of hairs (PMGHs) was found to be 27.3%. Binary logistic regression analysis showed that a paternal history of PMGH, history of smoking, maternal history of PMGH, sunlight exposure, and body mass index were significant predictors of PMGH. LIMITATIONS: The factors found associated could be better determined through a follow-up study which could not be done in the current study. The present study was carried in a tehsil of one district of Uttarakhand therefore has limited external validity.
CONCLUSION: The present study highlights the importance of maintaining a healthy lifestyle as well as adequate exposure to sunlight in preventing PMGH. Copyright:

INTRODUCTION

Aging is a universal phenomenon in all the species of organisms in this world. Human beings are also determined to undergo the process of aging which ultimately culminates into the end of life. Aging is characterized by several signs in the body, some of which are evident, whereas others are hidden. The signs of aging, therefore, signal the initiation of the process of regression to the end of life. Of all the signs of aging, graying of hairs (white hairs) is considered to be the most evident sign of aging.

Although the average age of individuals all over the world has been reported to be increasing with the increase in life expectancy, due to reduction in various mortality rates, it is very uncommon to observe or hear of an individual living till the age of 100 years or more nowadays as compared to previous times.[123] This reduction of life span is expected to herald the onset of aging characteristics early in life, which is further compounded by various stress factors which have become part and parcel of every individual's life. Also contributing to this aging process are the changing environmental conditions, the quality of food, and various other factors common to the present-day lifestyle.

Graying of hair begins to get apparent after the increased shedding of thicker, darker hairs coupled with an enhanced growth of thinner white hairs. Hair becomes gray with chronological aging. Premature graying of hair (PMGH) may have a significant effect on the appearance and sociocultural acceptance of the affected individual. The exact etio-pathologic mechanism causing PMGH is still not clear and is under speculation.[4]

The average age of graying of hairs in the Indian population has been observed to be beyond 30 years of age. Although there is no universal consensus regarding the definition of PMGH, it is generally described as “greying of hair before the age of 20 years in whites and before 30 years in blacks.” Premature canities or PMGH may occur alone or as an autosomal dominant condition or in association with various autoimmune or premature aging syndromes.[5]

Uttarakhand is a hilly state in India, with relatively preserved environmental conditions and more natural and stress-free lifestyle of individuals, in general. Community-based studies on the prevalence of PMGH characteristics of aging and their risk factors are lacking in India and more so in Uttarakhand. The present study is therefore intended with an objective to estimate the prevalence of PMGH and its correlates.

METHODOLOGY

Study design and study population

The present study was a community-based cross-sectional study carried out among young adults in the urban area of Srinagar tehsil of Pauri district which is divided into nine wards. Young adults were defined as those who were between 15 and 30 years of age at the time of data collection.

Sample size

We assumed a prevalence of 50% PMGH in young adults, for the purpose of calculating maximum sample size, due to lack of community-based estimates of PMGH in India. The following formula was used to calculate the sample size of the study:[6]

n = required sample size

Z(0.05)= 1.96

p (prevalence rate of PMGH) = 50%

q = 100− p = 50

L = least permissible error (absolute precision) = 5%

Desired confidence level = 95%

Hence, sample size

Sampling procedure

As per the census 2011 data, Srinagar is one of the ten tehsils in Pauri district in Garhwal division of Uttarakhand, a northern hilly state in India. It has a Nagar Palika Parishad and is divided into none wards with 4669 households and a total population of 20,115, of which 10,751 are males, while 9364 are females.[7] Participants were selected from each ward based on population proportion to size. An equal number of males and females were selected from each ward. The first household was selected randomly from the list of households. An inquiry was made about the presence of an individual between the ages of 15 and 30 years for the purpose of recruitment into the study. Only one eligible person was recruited for the study from one household. Informed written consent was obtained from the individual after explaining him/her about the purpose of the study. Any individual already diagnosed with a disease leading to graying of hairs such as hypothyroidism, albinism, vitiligo, skin disorders, or any other major illness was excluded from the study. Thereafter, the participants were recruited consecutively from consecutive households till the required sample size of both males and females was completed.

Data collection procedures and instruments used

A pretested, predesigned questionnaire was used to collect the data. The questionnaire included variables on sociodemographic characteristics such as a family history of PMGH in first-degree relatives, diet pattern, drinking water consumption, addiction, hours of use of electronic devices, exercise pattern, sleep disturbances at night, assessment for presbyopia by near vision chart, and dietary intake of protein, calcium, and water by 24-h recall method of dietary intake. A validated questionnaire for the potential level of stress by McGraw Hill was used for the assessment of stress.[8]

Graying of hair was assessed on the basis of number of white hairs on examination of the scalp. This was further divided into four categories as follows:

Category 1: No white hair

Category 2: 1–10 white hairs

Category 3: 11–100 white hairs

Category 4: >100 white hairs.

Data were collected by the same investigator to overcome the interviewer bias. Data entry was done on the day of data collection for ensuring completeness of data entry and minimizing the error.

Data analysis

Data were entered into Microsoft (MS) Excel and were analyzed using SPSS 23.0 (IBM SPSS Statistics version 23, SPSS South Asia Pvt Limited Bangalore, India). For comparison of proportions, Chi-square test was used. Association of various factors with the outcomes was also analyzed. Binary logistic regression was applied to predict the variables which had significant association with graying of hair. P < 0.05 was considered significant for all statistical tests.

Ethical considerations

Ethical clearance from the Institutional Ethical Committee was obtained. Informed written consent was also obtained from all the participants on the “Patient information document and consent form.” Participants were told about the purpose of the study, steps taken to ensure confidentiality, and were informed that they could refuse to answer any question or withdraw at any time if they are uneasy with the questions put to them.

RESULTS

The mean age of participants was 22.9 ± 4.4 years. Most of the respondents were Hindu (98.4%) and belonged to general caste (73.7%). About 81% of the respondents lived in joint family and half were vegetarian and belonged to upper middle class according to Kuppuswamy classification. About one-fifth of the participants had one or more addictions such as gutka, paan, tobacco chewing, smoking, or alcohol drinking and a similar proportion reported sleep disturbances. The prevalence of PMGH was found to be 27.3%, of which only 1% of respondents had severe graying of hairs (not provided in table separately).

The mean age of participants with gray hair was observed to be 23.7 ± 4.5 years, while that of participants without gray hair was 22.7 ± 4.3 years. An equal number of males and females were recruited for the study and it was observed that 37% (n = 71) of males had graying of hairs as compared to 17.7% (n = 34) of females. These differences were observed to be statistically significant (χ2 = 17.9, P < 0.05). Analysis for studying the association of sociodemographic characteristics and graying of hairs showed that age, gender (odds ratio [OR], confidence interval [CI] = 2.7, 1.7–4.3), positive paternal history (OR, CI = 3.4, 2.1–5.5), positive maternal history (OR, CI = 3.6, 2.2–5.8), people having low body mass index (BMI) (OR, CI = 28.5, 13.4–60.6), having less than the recommended daily calcium intake (OR, CI = 2.8, 1.2–6.5), having a history of addiction of alcohol (OR, CI = 1.9, 1.1–3.5), or smoking (OR, CI = 3.6, 2.2–6.1) had a significant association with graying of hairs as compared to others [Table 1].

Table 1

Association of graying of hairs with various sociodemographic characteristics

Sociodemographic characteristics	Individuals with PMGH (105)		Individuals without PMGH (279)		χ2/t value, P value#	OR, 95% CI
	n (%)	95% CI	n (%)	95% CI
Age (mean, SD)	23.7, 4.5		22.7, 18.6		1.9, 0.03	-
Gender
Male (192)	71 (37)	30.1-44.2	121 (63)	55.8-69.9	17.9, 0.00	2.7 (1.7-4.3)
Females (192)	34 (17.7)	12.6-23.9	158 (82.3)	76.1-87.4
Family history
Paternal history positive (120)	54 (45.0)	35.9-54.3	66 (55.0)	45.7-64.1	26.1, 0.00	3.4 (2.1-5.5)
Paternal history negative (264)	51 (19.3)	14.7-24.6	213 (80.7)	75.4-86.3
Maternal history positive (96)	46 (47.9)	37.9-57.9	50 (52.1)	42.1-62.1	25.9, 0.00	3.6 (2.2-5.8)
Maternal history negative (288)	59 (20.5)	15.8-25.1	229 (79.5)	74.8-84.2
BMI
<18.5 (62)	52 (83.9)	74.7-93.0	10 (16.1)	6.9-25.3	111.2,0.00	28.5 (13.4-60.6)
18.5-22.9 (normal and reference category) (259)	40 (15.4)	11.0-19.8	219 (84.6)	80.1-88.9	-	-
≥23 (63)	13 (20.6)	10.6-30.6	50 (79.4)	69.3-89.4	0.65, 0.42	0.7 (0.3-1.41)
Socioeconomic status
Upper (40)	15 (37.5)	22.5-52.5	25 (62.5)	47.5-77.5	3.3, 0.1	0.3 (0.1-0.9)
Upper middle (222)	63 (28.4)	22.4-34.3	159 (71.6)	65.7-77.5	1.8, 0.2	0.4 (0.1-1.3)
Lower middle/upper lower (122) (reference)	27 (22.1)	14.8-29.5	95 (77.9)	70.5-85.2	-	-
Diet
Vegetarians (166)	44 (26.5)	19.8-33.2	122 (73.5)	66.7-80.2	0.0, 0.8	0.9 (0.6-1.5)
Nonvegetarians (218)	61 (28.0)	22.0-33.9	157 (72.0)	66.0-78.0
Water consumption (per day in milliliters)
<1500 (73)	25 (34.2)	23.4-45.1	48 (65.7)	54.8-76.6	1.7, 0.2	1.5 (0.9-2.6)
≥1500 (311)	80 (25.7)	20.9-30.6	231 (74.3)	69.4-79.1
Protein consumption (g/day)
<30 (131)	36 (27.5)	19.8-35.1	95 (72.5)	64.9-80.2	0, 1	1.0 (0.6-1.6)
≥30 (253)	69 (27.3)	21.8-32.7	184 (72.7)	67.2-78.2
Calcium consumption (g/day)
<0.5 (330)	98 (29.7)	24.7-34.6	232 (70.3)	65.4-75.2	5.7, 0.0	2.8 (1.2-6.5)
≥0.5 (54)	7 (13.0)	4.0-21.9	47 (87.0)	78.1-96.0
Alcoholics
Alcoholics (58)	23 (39.6)	27.1-52.2	35 (60.3)	47.7-72.9	4.5, 0.0	1.9 (1.1-3.5)
Nonalcoholics (326)	82 (25.1)	20.4-29.9	244 (74.8)	70.1-79.5
Smoking status
Smokers (78)	39 (50)	38.9-61.1	39 (50)	38.9-61.1	23.9, 0.0	3.6 (2.2-6.1)
Nonsmokers (306)	66 (21.6)	16.9-26.2	240 (78.4)	73.8-83.0
Tobacco use
Tobacco chewers (52)	19 (36.5)	23.4-49.6	33 (63.5)	50.3-76.5	2.0, 0.1	1.6 (0.9-3.0)
Nonchewers (332)	86 (25.9)	21.2-30.6	246 (74.1)	69.4-78.8
Vision problem
Near vision problem (45)	14 (31.1)	17.6-44.6	31 (68.9)	55.3-82.4	0.2, 0.7	1.2 (0.6-2.4)
No near vision problem (339)	91 (26.8)	22.1-31.6	248 (73.1)	68.4-77.8
Sleep disturbance
Sleep disturbance (58)	21 (36.2)	23.8-48.6	37 (63.8)	51.4-76.2	2.2, 0.1	1.6 (0.9-2.9)
No sleep disturbance (326)	84 (25.8)	21.0-30.5	242 (74.2)	69.5-79.0

BMI – Body mass index; CI – Confidence interval; OR – Odds ratio; PMGH – Premature graying of hairs; SD – Standard deviation; #P value of <0.05 was considered significant

Another analysis for exploring the association of attributes of personal care and graying of hair showed that people involved in sedentary activities for <8 h a day (OR, CI = 0.5, 0.3–0.8), doing exercise daily/on alternate days (OR, CI = 0.4, 0.2–0.8), and having dry/oily scalp (OR, CI = 0.5, 0.3–0.8) had lesser chances of hair graying. On the other hand, exposure to sunlight for <15 min per day (OR, CI = 2.7, 1.5–4.7) and application of oil on daily or alternate day to the scalp (OR, CI = 2.8, 1.7–4.6) increased the chances of graying of hairs [Table 2].

Table 2

Association of graying of hairs to factors of personal care

Personal care	Individuals with PMGH (105)		Individuals without PMGH (279)		χ2, P value#	OR (95% CI)
	n (%)*	95% CI	n (%)*	95% CI
Time sitting on a chair
<8 h (173)	35 (20.2)	14.2-26.2	138 (79.8)	73.8-85.7	7.4, 0.0	0.5 (0.3-0.8)
>8 h (211)	70 (33.2)	26.8-39.5	141 (66.8)	60.5-73.2
Time spent on electronic device
<3 h (178)	49 (27.5)	20.9-34.1	129 (72.5)	65.9-79.3	1.0, 0.3	0.7 (0.4-1.3)
>3 h (206)	56 (27.2)	21.1-33.2	150 (72.8)	66.7-78.9
Exercise frequency
Daily/alternate days (60)	8 (13.3)	4.7-21.9	52 (86.7)	78.1-95.3	6.2, 0.0	0.4 (0.2-0.8)
2-3 times/week/never (324)	97 (29.9)	24.9-34.9	227 (70.0)	65.1-75.0
Frequency of oil application to hair and scalp
Daily/alternate (93)	41 (44.1)	34.0-54.2	52 (55.9)	45.8-66.0	16.2, 0.0	2.8 (1.7-4.6)
Once in 3 days/once a week/never (291)	64 (22.0)	17.2-26.7	227 (78.0)	73.2-82.7
Shampoo application to hair and scalp
Daily/alternate (153)	45 (29.4)	22.2-36.6	108 (70.6)	63.4-77.8	0.4, 0.5	1.2 (0.7-1.9)
Others (231)	60 (26)	20.3-31.6	171 (74.0)	68.4-79.7
Scalp type
Dry type (108)	41 (38.0)	21.8-87.1	67 (62.0)	52.8-71.1	13.3, 0.0	0.5 (0.3-1.0)
Oily type (91)	29 (31.8)	22.2-41.4	62 (68.1)	58.5-77.7	6.8,0.0	0.3 (0.19-0.76)
Combined type (74)	18 (23.1)	13.7-32.4	56 (71.8)	61.8-81-7	1.8,0.17	0.5 (0.3-1.1)
Normal (reference) (111)	17 (15.3)	8.6-22.0	94 (84.7)	78.0-91.4	1.8, 0.2	0.4 (0.3-0.6)
Exposure of sunlight
<15 min (66)	30 (45.4)	33.4-57.5	36 (54.5)	42.5-66.5	12.1, 0.0	2.7 (1.5-4.7)
≥15 min (318)	75 (23.6)	18.9-28.2	243 (76.4)	71.7-81.1
Stress levels
Low/moderate (284)	73 (25.7)	20.6-30.8	211 (74.3)	69.2-79.4	1.2, 0.3	0.7 (0.4-1.2)
High/very high (100)	32 (32)	22.8-41.1	68 (68)	58.8-77.1

CI – Confidence interval; OR – Odds ratio; PMGH – Premature graying of hairs; * Indicates row percentage; #P value of <0.05 was considered significant

The − 2 log likelihood ratio for the regression model in our study was reported to be 256.8. The goodness of fit (Hosmer and Lemeshow test) was not found to be significant (P > 0.05). Significant predictors in the model in the sequence of decreasing order of odds ratio were paternal history of graying of hair (OR = 7.2), history of smoking (OR = 5.4), maternal history of graying of hair (OR = 3.9), sunlight exposure for <15 min (OR = 2.8), and BMI <18.5 (OR = 1.3) [Table 3].

Table 3

Logistic regression model of graying of hairs

	B	Significant	Exp (B)	95% CI for Exp (B)
				Lower	Upper
Paternal history positive	1.969	0.000	7.2	3.6	14.1
Maternal history positive	1.365	0.000	3.9	2.0	7.6
Sunlight exposure for 15 min	1.028	0.007	2.8	1.3	5.9
BMI (<18.5)	0.264	0.539	1.3	0.560	3.028
BMI (≥23.0)	−3.607	0.000	0.03	0.009	0.083
Smoking status	1.688	0.000	5.4	2.6	11.4
Constant	−2.7	0.000	0.06	-	-

BMI – Body mass index; CI – Confidence interval

DISCUSSION

The present study is unique in being a community-based study in India, which aimed to study the prevalence of aging characteristics of hair, i.e., graying of hairs in younger individuals; other studies carried out in India till date have been conducted in hospital settings and therefore have limited generalizability.

The mean age of graying of hair in our study was 23.7 ± 4.5 years in comparison to 11.6 ± 3.6 years in a study from Delhi. The reason for the difference was different age groups of the study sample included in both the studies.[9]

The present study found that the prevalence of PMGH (27.4%) was comparable to that reported in a Turkish study (28.1%).[10] The 50/50/50 rule of thumb states that by the age of 50 years, 50% of the population have at least 50% gray hair.[11] This has been investigated by other researchers who have reported a 6%–23% prevalence of 50% gray hairs in 50 years of age people.[12] However, we observed a higher prevalence than this study in a younger age group, thus favoring the rule of thumb hypothesis. Another study in Saudi Arabia reported a much higher prevalence of 42.5% among people 18–30 years of age.[13] We also observed a higher prevalence among males (37%) as compared to females (17.7%), which was different from the findings of Almutairi and Dhafiri, who reported an opposite pattern (15.8% vs. 84.2%).

The association of PMGH with paternal and maternal history seems to be biologically plausible and has been reported in other studies as well.[913]

It was observed in the present study that individuals with PMGH had a greater proportion of individuals with BMI out of normal range, with the majority of being underweight. Similar findings have been reported in other studies also, thereby stressing the role of maintenance of ideal weight and nutritional status.[10111213]

The present study did not observe any significant association between type of diet and PMGH, which was not in accordance with other studies which reported a positive association of graying of hairs with vegetarian diet.[10] A role of sulfur, calcium, ferritin, protein, and Vitamin D3 deficiency has been reported in PMGH in various studies; we observed a positive association of low calcium intake with PMGH but no association with low protein intake.[14151617] We did not study the role of other nutrients due to the limitation of resources in undertaking blood investigations in community settings. The role of water consumption in preventing graying of hair was not found to be positive in the present study, and the hypothesis that good hydration is good for hairs could not be established.

Consumption of alcohol and smoking was reported to be significantly associated with PMGH in the present study as well as other studies in other parts of the world.[101819202122232425] No significant association was reported between near vision defect or sleep disturbances and PMGH in the present study. The association between sleep disturbances and graying of hair or loss of hair may work indirectly through stress rather than directly.

The importance of a maintaining healthy lifestyle was emphasized in the present study by the observations regarding the positive association of sedentary lifestyle and use of electronic gadgets with PMGH. This was also corroborated by the finding that undertaking regular exercise had a negative association with PMGH.

The role of application of hair oil in preventing graying of hairs has always been an issue of debate, and it was observed in the present study that applying oil on daily/alternate days was associated with PMGH. This was also corroborated by the observation that having a dry/oily scalp was associated with higher percentages of PMGH, thereby stressing the importance of maintaining normal oil balance of the scalp. Another study from Saudi Arabia did not observe any association between oil application and PMGH.[13] On the contrary, the application of shampoo, another much debated and advertised hair applicant, was not found to have any association with PMGH.

There is a common saying in Hindi which associates the exposure to sunlight as a causative factor for graying of hair (“Dhoop me baal safaid nahi hue hain”). Keeping this in mind, we tried to study the association of exposure to sunlight and graying of hairs, and it was observed that exposure to ≥15 min of sunlight was actually preventive. This could because of the deficiency of Vitamin D3 in those exposed to <15 min to sunlight. However, a causal association can only be established by a longitudinal study. Another study by Almutairi and Dhafiri did not observe any association between sun exposure and PMGH.[13]

No significant association was observed between stress levels and PMGH in the present study, which is rather surprising. The findings in our study are different from that reported in other studies which have reported a positive association between stress and PMGH.[102125]

CONCLUSION

The present study highlights the importance of maintaining a healthy lifestyle such as adequate diet, exercise, abstinence from smoking and alcohol, as well as adequate exposure to sunlight in preventing PMGH.

Financial support and sponsorship

Nil.

Conflicts of interest

There are no conflicts of interest.