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Association of premature hair graying with family history, smoking, and obesity: A cross-sectional study
ORIGINAL
ARTICLE
Association of premature hair graying with family history, smoking, and obesity: A cross-sectional study Hyoseung Shin, MD,a Hyeong Ho Ryu, MD,b Junghee Yoon, MD,c Seongmoon Jo, MD,b Sihyeok Jang, MD,b Mira Choi, MD,b Ohsang Kwon, MD, PhD,b,d,e and Seong Jin Jo, MD, PhDb,d,e Goyang, Seoul, and Uijungbu, Korea Background: Many researchers have been concerned about the association of hair graying with systemic diseases. However, the common factors associated with hair graying and systemic diseases have not been elucidated. Objective: This study aimed to identify risk factors for premature hair graying (PHG) in young men. Methods: We conducted a cross-sectional study using questionnaires in young men. After a pilot study that included 1069 men, we surveyed 6390 men younger than 30 years about their gray hair status and various socioclinical characteristics. Results: The age of participants in the main survey was 20.2 6 1.3 years (mean 6 SD). Of the 6390 participants, 1618 (25.3%) presented with PHG. Family history of PHG (odds ratio [OR], 12.82), obesity (OR, 2.61), and [5 pack-years history of smoking (OR, 1.61) were significantly associated with PHG. In the multivariate analysis, family history of PHG (OR, 2.63) and obesity (OR, 2.22) correlated with the severity of PHG. Limitations: Owing to the use of questionnaires, the possibility of recall bias exists. Women were not evaluated in this study. Conclusion: Smoking, family history of PHG, and obesity are important factors associated with PHG. ( J Am Acad Dermatol http://dx.doi.org/10.1016/j.jaad.2014.11.008.) Key words: body mass index; gray hair; obesity; premature hair graying; smoking.
H
air graying is one of the natural aging processes.1 Although it is generally not a medical problem, it greatly concerns many people for aesthetic reasons.2 Premature hair graying (PHG) is especially important as a cause of low self-esteem, often impeding social life in young people.3 Moreover, because of the strong association between aging and hair graying, many researchers have been concerned that PHG is a predictor of some severe systemic disease. Several studies evaluated the association of PHG with osteopenia or coronary artery disease.4-6 However, the common factors
associated with hair graying and systemic diseases have not been elucidated. In a previous investigation, we noted that sex and smoking were associated
From the Department of Dermatology, Dongguk University Ilsan Hospital, Goyanga; Department of Dermatology, Seoul National University College of Medicine, Seoulb; 306 Supplementary Battalion, Korea Army, Uijungbuc; Institute of HumanEnvironment Interface Biology, Seoul National University, Seould; and Laboratory of Cutaneous Aging and Hair Research, Biomedical Research Institute, Seoul National University Hospital, Seoul.e The first two authors contributed equally to this work. Funding sources: None.
Conflicts of interest: None declared. Accepted for publication November 6, 2014. Reprint requests: Seong Jin Jo, MD, PhD, Department of Dermatology, Seoul National University College of Medicine, 101 Daehak-ro, Jongno-gu, Seoul 110-744, Korea. E-mail: [email protected]. Published online December 4, 2014. 0190-9622/$36.00 Ó 2014 by the American Academy of Dermatology, Inc. http://dx.doi.org/10.1016/j.jaad.2014.11.008
Abbreviations used: BEPSI-K: BMI: CI: OR: PHG:
modified Korean translated Brief Encounter Psychosocial Instrument body mass index confidence interval odds ratio premature hair graying
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smoking history of more than 5 pack-years were with PHG.7 However, many other socioclinical regarded as smokers. Obesity was categorized characteristics were not examined, and further study according to the World Health Organization was needed. In thi study, we aimed to identify the risk (WHO) classification as follows: underweight, factors for PHG in healthy young Korean men. BMI \18.5 kg/m2; normal weight, 18.5 kg/m2 Koreans are suitable candidates for epidemio# BMI \25 kg/m2; overweight, 25 kg/m2 # BMI logic studies of hair graying because gray hair is \30 kg/m2; obese, BMI $ 30 kg/m2.8 Emotional distinctive against their oristress was evaluated using ginal near-black hair color. the modified Korean transCAPSULE SUMMARY We consider hair graying lated Brief Encounter before the age of 30 years Psychosocial Instrument The risk factors for premature hair to represent PHG because (BEPSI-K). BEPSI-K scores graying are not well known. it was found that in most range from 0 to 5, with In the current study, family history, Koreans, hair graying bescores higher than 2.8 indiobesity, and smoking were associated gins after age 30 years.7 cating high stress, scores with premature hair graying, whereas Various socioclinical charbetween 1.6 and 2.8 indifamily history and obesity correlated acteristics were surveyed cating moderate stress, and with its severity. using questionnaires, and scores lower than 1.6 inditheir associations with hair This study yields clues to the cating low stress.9 graying were assessed. pathophysiology of hair graying. Evaluation of the survey’s METHODS validity Study design and population To evaluate the survey’s validity, we compared We conducted 2 cross-sectional studies using the grade of gray hairs from the subject’s self-report questionnaires. The first was designed as a pilot with the investigator’s examination in 100 subjects. study. After the pilot study, we modified the questionnaire. The participants of both surveys Statistical analysis were recruited at the 306 Supplementary Battalion Unanswered questionnaire items were regarded in Uijungbu, Korea. The 306 Supplementary as missing values. At first, we performed a univariate Battalion is one of the Korean military units into logistic regression analysis. We also analyzed ordinal which citizens are conscripted. To participate, subcategorical variables using the Cochran-Armitage jects had to be younger than 30 years, healthy trend test. Factors with associations at the P less enough to engage in military service, and agree to than .10 significance level in these analyses were participate in this study. The exclusion criteria were then entered into a multivariate logistic regression refusal to participate in the study, hypopigmentary analysis to identify risk factors for PHG. P values less disorder, and alopecia (except androgenetic alopethan .05 were considered significant. cia). This study was approved by the institutional To identify factors associated with the severity of review board of Seoul National University Hospital. PHG, an ordinal logistic regression analysis was To avoid the potential for coercion, we heeded performed. Factors with associations at the P less institutional review board advice and emphasized to than .10 significance level in the univariate ordinal subjects that there would be no penalty for declining logistic regression were analyzed together by to participate. multivariate ordinal logistic regression. P values less than .05 were considered significant. The analyses were performed using a software package Questionnaire details (SPSS Statistics 21.0, IBM Corp, Armonk, NY). Participants were asked about the presence of gray hair. The number of gray hairs was selfreported as follows: 0, less than 10, 10 to 100, and RESULTS more than 100. The collected data included age, Pilot study sex, height, body weight, the presence of a In the pilot study, 1104 questionnaires were medical problem including scalp diseases and returned, and 1069 were analyzed after excluding alopecia, the presence of a family history of 35 by the predefined exclusion criteria. In the PHG, lifestyle behaviors (drinking, smoking, exmultivariate binary logistic regression analysis, BMI ercise, and diet), educational background, schol(odds ratio [OR], 1.04; 95% confidence interval [CI], arly achievements, occupation, and Fitzpatrick 1.00-1.08) (P = .041), family history of PHG (OR, skin type. In our study, participants with a 9.11; CI, 5.64-14.69) (P \.001), and emotional stress d
d
d
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(OR, 1.43; CI, 1.13-1.80) (P = .003) were associated with PHG. Other factors including medical history of admission, chronic diseases, scalp disease or alopecia, educational background, diet, drinking, exercise, smoking, occupation, and Fitzpatrick skin type were not significantly associated with PHG. Evaluation of the survey’s validity The simple percent agreement of grade of gray hairs between investigator and subject was 95.0%, and Cohen kappa coefficient was 0.884. Main survey Demographic and socioclinical characteristics of the study participants. On the basis of the results of the pilot study, we modified the questionnaires by making the questions clearer and the answer options more detailed. We distributed 10,000 questionnaires and 6658 participants agreed to provide information about their hair graying. Of these, 268 (failed to respond regarding hair graying, 63; vitiligo, 12; alopecia areata, 128; telogen effluvium, 4; cicatricial alopecia, 22; unclearly described alopecia, 39) were excluded by the exclusion criteria. The final number of participants analyzed was 6390. They were all Korean men aged 20.2 6 1.3 years (mean 6 SD). We classified 1618 (25.3%) participants with gray hair into the PHG group whereas the remaining 4772 (74.7%) were classified into the non-PHG group. The participants’ socioclinical characteristics are described in Table I. Comparison of socioclinical characteristics between the PHG and non-PHG groups. The comparison of socioclinical characteristics between the 2 groups is summarized in Table I. The PHG group was slightly, but significantly, older than the non-PHG group (P = .002). The odds of having PHG were significantly higher in the overweight (P = .002) and obese (P \ .001) groups than in the normalweight group. A family history of PHG was more commonly present in the PHG group (P \ .001). Among participants in the PHG group, the family history of PHG was paternal in 33.3% and maternal in 11.2%. A family history from both parents was present in 4.6% of participants in the PHG group. The proportion of smokers was higher in the PHG group than in the non-PHG group (P = .013). Most of the participants were students, and 25.1% of them had PHG, whereas 36.9% of blue-collar workers had PHG (P = .015). The proportion of participants with PHG was higher in the moderate and severe stress groups than in the mild stress group (P \ .001 for both). In the additionally performed CochranArmitage trend test, obesity category was associated with PHG (P \ .001), whereas exercise and
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Fitzpatrick skin types showed borderline significance (P = .060 and P = .050, respectively). Risk factors for PHG. Age, obesity, family history, scalp disease, smoking status, exercise, diet, occupation, emotional stress, and Fitzpatrick skin type were selected as candidate risk factors for PHG because they showed associations with PHG (P \ .10) in the comparison analyses. In the multivariate logistic regression analyses, we found that family history of PHG, obesity, and smoking was significantly associated with PHG. The odds of having PHG increased as the group BMI increased (Table II). Further logistic regression analyses on family history showed that a paternal history of PHG (OR, 14.84; CI, 10.10-21.81) (P \.001) had a greater association with PHG than a maternal history (OR, 2.92; CI, 1.57-5.43) (P = .001). Socioclinical characteristics associated with the severity of PHG. We further analyzed 1618 participants with PHG. PHG was more severe in the overweight or obese categories (P = .025 and P = .003, respectively). Family history also correlated with the severity of PHG. PHG participants with a family history tended to have more severe PHG (P = .001). In the multivariate ordinal logistic regression analysis, we confirmed that family history and obesity correlated with the severity of PHG. In PHG participants with a family history of PHG, the odds of more severe PHG were 2.63 times those of PHG participants without a family history. Obesity significantly correlated with the severity of PHG. The OR increased as the group BMI increased (Table III).
DISCUSSION In general, PHG is common in healthy people.3 We therefore sought to identify the risk factors for PHG in a healthy population. We obtained a response rate of 66.6% in the main survey. Generally, a survey response rate greater than 60% is considered sufficient.10 In addition, the nonresponse rate of greater than 30% reflected a lack of coercive enrollments even though this study was conducted in the military. Cohen kappa coefficient, 0.884, between subject’s self-reported gray hair grade and investigator’s examination indicates an almost perfect agreement,11 likely because only a single gray hair in Korean populations is very noticeable against the original black hair color. The comparison between participants with and those without PHG revealed that old age, overweight or obesity, family history of PHG, scalp seborrheic dermatitis, smoking, being a blue-collar worker, and moderate or severe stress had a significant association with PHG. At this step of the analysis,
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Table I. Socioclinical characteristics and comparison between respondents with and without premature hair graying Socioclinical characteristics
No. of subjects Age, y, mean 6 SD Obesity categories,yn (%) Underweight Normal Overweight Obese Family history of PHG, n (%) No Yes Unaware Scalp skin disease, n (%) Normal Seborrheic dermatitis Other scalp disease Medical history of admission or operation, n (%) No Yes Chronic disease,zn (%) No Yes Androgenetic alopecia,xn (%) No Yes Medication,//n (%) No Yes Smoking,{n (%) No Yes Alcohol, n (%) No # 1/mo 2-3/mo 1-2/wk $ 3/wk Exercise, n (%) No # 1/mo 2-3/mo 1-2/wk $ 3/wk Diet, n (%) Vegetarian diet Mixed diet Meat-based diet Educational background, n (%) Middle-school graduation High-school graduation College student or graduation Scholarly achievement,#n (%) 0%-10% 10%-30% 30%-70%
non-PHG
PHG
4772 20.2 6 1.3 4654 (100.0) 394 (8.5) 3197 (68.7) 834 (17.9) 229 (4.9) 4772 (100.0) 2356 (49.4) 303 (6.3) 2113 (44.3) 4673 (100.0) 4489 (96.1) 137 (2.9) 47 (1.0) 4672 (100.0) 2920 (62.5) 1752 (37.5) 4669 (100.0) 4345 (93.1) 324 (6.9) 4493 (100.0) 4405 (98.0) 88 (2.0) 4574 (100.0) 4329 (94.6) 245 (5.4) 4630 (100.0) 4038 (87.2) 592 (12.8) 4753 (100.0) 496 (10.4) 649 (13.7) 1467 (30.9) 1506 (31.7) 635 (13.4) 4737 (100.0) 954 (20.1) 761 (16.1) 1352 (28.5) 1108 (23.4) 562 (11.9) 4686 (100.0) 91 (1.9) 2999 (64.0) 1596 (34.1) 1559 (100.0) 33 (2.1) 498 (31.9) 1028 (65.9) 4516 (100.0) 167 (3.7) 985 (21.8) 2476 (54.8)
1618 20.3 6 1.5 1578 (100.0) 126 (8.0) 991 (62.8) 325 (20.6) 136 (8.6) 1618 (100.0) 247 (15.3) 365 (22.5) 1006 (62.2) 1577 (100.0) 1493 (94.7) 65 (4.1) 19 (1.2) 1575 (100.0) 981 (62.3) 594 (37.7) 1575 (100.0) 1460 (92.7) 115 (7.3) 1528 (100.0) 1488 (97.4) 40 (2.6) 1560 (100.0) 1464 (93.8) 96 (6.2) 1546 (100.0) 1310 (84.7) 236 (15.3) 1604 (100.0) 152 (9.5) 206 (12.8) 533 (33.2) 484 (30.2) 229 (14.3) 1597 (100.0) 347 (21.7) 275 (17.2) 447 (28.0) 346 (21.7) 182 (11.4) 1577 (100.0) 20 (1.3) 983 (62.3) 574 (36.4) 4634 (100.0) 103 (2.2) 1447 (31.2) 3084 (66.6) 1539 (100.0) 76 (0.05) 306 (19.9) 877 (57.0)
OR (95% CI)
P value
1.07 (1.03-1.11)*
.002
1.03 (0.83-1.28) 1.00 [Reference] 1.26 (1.09-1.46) 1.92 (1.53-2.40)
.774 _ .002 \.001
1.00 [Reference] 11.49 (9.40-14.05) _
_ \.001 _
1.00 [Reference] 1.43 (1.06-1.93) 1.22 (0.71-2.08)
_ .021 .476
1.00 [Reference] 1.01 (0.90-1.14)
_ .879
1.00 [Reference] 1.06 (0.85-1.32)
_ .648
1.00 [Reference] 1.35 (0.92-1.96)
_ .124
1.00 [Reference] 1.16 (0.91-1.48)
_ .236
1.00 [Reference] 1.23 (1.04-1.45)
_ .013
1.00 [Reference] 1.04 (0.82-1.32) 1.19 (0.96-1.46) 1.05 (0.85-1.29) 1.18 (0.93-1.49)
_ .774 .107 .655 .177
1.00 [Reference] 0.99 (0.83-1.20) 0.91 (0.77-1.07) 0.86 (0.72-1.02) 0.89 (0.72-1.10)
_ .993 .909 .859 .890
0.67 (0.41-1.09) 1.00 [Reference] 1.10 (0.97-1.24)
.109 _ .128
0.96 (0.65-1.43) 1.03 (0.91-1.17) 1.00 [Reference]
.845 .613 _
1.29 (0.97-1.70) 0.88 (0.76-1.02) 1.00 [Reference]
.081 .086 _ Continued
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Table I. Cont’d Socioclinical characteristics
non-PHG
70%-90% 90%-100% Occupation, n (%) Student White-collar worker Blue-collar worker Service industry worker Self-employed Stress severity scale (BEPSI-K), n (%) Mild Moderate Severe Fitzpatrick skin type, n (%) I II III IV V VI
685 203 3687 3145 93 53 378 18 4702 3005 1423 274 4707 316 906 1349 1415 619 102
(15.2) (4.5) (100.0) (85.3) (2.5) (1.4) (10.3) (0.5) (100.0) (63.9) (30.3) (5.8) (100.0) (6.7) (19.2) (28.7) (30.1) (13.2) (2.2)
PHG
212 68 1277 1052 40 31 143 11 1594 872 589 133 1588 111 331 453 477 197 19
(13.8) (4.4) (100.0) (82.4) (3.1) (2.4) (11.2) (0.9) (100.0) (54.7) (37.0) (8.3) (100.0) (7.0) (20.8) (28.5) (30.0) (12.4) (1.2)
OR (95% CI)
P value
0.87 (0.74-1.04) 0.95 (0.71-1.26)
.125 .701
1.00 [Reference] 1.29 (0.88-1.88) 1.75 (1.12-2.74) 1.13 (0.92-1.39) 1.83 (0.86-3.89)
_ .191 .015 .239 .117
1.00 [Reference] 1.43 (1.26-1.61) 1.67 (1.34-2.09)
_ \.001 \.001
1.00 [Reference] 1.04 (0.81-1.34) 0.96 (0.75-1.22) 0.96 (0.76-1.22) 0.91 (0.69-1.19) 0.53 (0.31-0.91)
_ .758 .714 .737 .472 .020
BEPSI-K, Modified Korean translated Brief Encounter Psychosocial Instrument; CI, confidence interval; OR, odds ratio; PHG, premature hair graying. *The OR of age row is for each additional 1 y. The odds of having PHG are increasing as OR as age increases by 1 y. y World Health Organization criteria. z Any disease treated $ 1 y. x Presence of noticeable, characteristically patterned hair loss. // Any drugs taken orally $ 6 mo. { [5 Pack-y. # 0%, Lowest rank; 100%, highest rank.
Table II. Socioclinical factors associated with the prevalence of premature hair graying using multivariate logistic regression analyses Socioclinical characteristics
Family history of PHG Obesity categories* Underweight Normal Overweight Obese Smokingy
OR (95% CI)
P value
12.82 (9.94-16.55)
\.001
0.61 (0.37-1.03) 1.00 [Reference] 1.28 (0.94-1.74) 2.61 (1.62-4.23) 1.61 (1.10-2.37)
.064 .122 \.001 .014
CI, Confidence interval; OR, odds ratio; PHG, premature hair graying. *World Health Organization criteria. y [5 Pack-y.
the difference in age between the PHG group and the non-PHG group was small but significant even though we tried to control for this major confounding factor of hair graying by studying a population of similarly aged men younger than 30 years. This was corrected by the next step of the analysis, which was a multivariate analysis. In the multivariate analysis, only 3 characteristics (family history, obesity, and smoking) were considered as risk factors for PHG.
This was consistent with a previous study in which smoking was revealed as a risk factor for PHG.12 In the analysis of the severity of PHG, excluding smoking, family history and obesity showed significant associations. In this study, we defined hair graying before the age of 30 years as PHG based on our previous study.7 In fact, the definition of PHG was somewhat arbitrary, and there is no universal definition of PHG. Some investigators have defined PHG as 50% gray hair before the age of 50 years, whereas others defined it as nearly all gray hair before age 40 years.1,5,13 To examine more extreme tendencies, we performed additional analyses under the altered definition of PHG as hair graying before the age of 25 years and found nearly the same results. The mechanism of hair graying is currently attributed to accumulated intracellular oxidative stress. During the enzymatic oxidation process of melanogenesis, a radical intermediate that damages DNA is produced.14,15 Because a high level of melanogenic activity in bulbar melanocytes in the hair follicles is ongoing throughout life, endogenous oxidative stress eventually induces the loss of melanocytes and results in hair graying.16,17
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Table III. Socioclinical factors associated with the severity of premature hair graying using multivariate ordinal logistic regression analysis No. of white hair, n (%) Socioclinical characteristics
Family history of PHG No Yes Obesity categories* Underweight Normal Overweight Obese
\10
10-100
[100
OR (95% CI)
P value
171 (69.2) 167 (45.8)
58 (23.5) 148 (40.5)
18 (7.3) 50 (13.7)
1.00 [Reference] 2.63 (1.88-3.69)
\.001
83 628 182 69
36 307 123 54
7 56 20 13
0.89 (0.46-1.73) 1.00 [Reference] 1.35 (0.91-2.01) 2.22 (1.30-3.79)
(65.9) (63.4) (56.0) (50.7)
(28.6) (31.0) (37.8) (39.7)
(5.6) (5.7) (6.2) (9.6)
.726 .136 .004
CI, Confidence interval; OR, odds ratio; PHG, premature hair graying. *World Health Organization criteria.
It was interesting that smoking and obesity were both found to be risk factors for PHG in this study, because they are both well known to be related to oxidative stress. Smoking is a source of free radicals that generates consequent free radicals in vivo.18 Obesity is independently associated with systemic oxidative stress. Many deleterious effects of obesity are now explained by increased oxidative stress.19 In addition, obesity appears to have an effect on melanogenesis via the hormonal system. Morpurgo et al20 suggested that leptin resistance in obese people increases melanocyte-stimulating hormone antagonists, which causes a reduction of melanogenesis and a decreased capacity for melanocyte DNA repair. To our knowledge, this is the first study to report an association between obesity and hair graying in human beings. An association between coronary artery disease and gray hair was reported previously,4 suggesting that obesity acts as a common risk factor for both coronary artery disease and gray hair. In this study, we found that a family history of PHG was the most powerful risk factor for PHG. In particular, a paternal family history affects PHG more than a maternal history. This might simply be because the onset of hair graying is earlier in men than in women,7 and because this study enrolled only men, the concordance rate of PHG would be higher by chance between fathers and sons than between mothers and sons. Another hypothesis is that genetic factors affecting hair graying come from the father. These genetic candidates might be related to oxidative stress or its defense system. To elucidate genetic effects in hair graying, a further study including women is necessary. Emotional stress showed a significant association with PHG in the univariate analysis but not in the multivariate analysis. This is because emotional
stress is a confounding factor for smoking and obesity. In our data, stress and smoking were significantly correlated (P \ .001). Stress and obesity also had a significant correlation in the normal-weight, overweight, and obese groups (P = .013). It has been previously known that smoking and/or obesity affect stress.21,22 Seborrheic dermatitis, which was removed in the multivariate analysis, seems to be a confounding factor that shows correlations with smoking and stress.23,24 Likewise, blue-collar workers tended to smoke more (P \ .001) and to be more obese (P = .022) than students, indicating that occupation is also a confounding factor for PHG. Family history and obesity were correlated not only with the prevalence of PHG, but also with its severity. However, smoking, which is considered to be associated with the prevalence of PHG, did not correlate with the severity of PHG. This can be explained by the fact that the participants in this study were so young that the accumulation of the effects of smoking was insufficient to affect the severity of PHG. Previous studies that reported an association between smoking and PHG also failed to show a correlation between smoking and the severity of PHG.12,25 To confirm whether smoking affects the severity of PHG, a further study including participants with a wide range of ages is needed. This study has some limitations. First, the possibility of recall bias exists because of the use of questionnaires. However, much of the information needed in this study depended on subjects’ answers, because many events related to analyzed variables had happened in the past. Second, young women were not included in this study. Third, generalizability from the homogeneous Korean population to other ethnicities may be limited. Fourth, this study did not show causality. A prospective study is needed to confirm the causality.
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In this study, family history of PHG, obesity, and smoking were significantly associated with PHG. In particular, family history and obesity showed reproducible significance in both the pilot and main studies and were correlated with the severity of PHG. Our findings may be helpful to researchers investigating the aging process and offer a possible approach to health education against obesity and smoking, particularly in young people. REFERENCES 1. Trueb RM. Aging of hair. J Cosmet Dermatol. 2005;4:60-72. 2. Schnohr P, Nyboe J, Lange P, Jensen G. Longevity and gray hair, baldness, facial wrinkles, and arcus senilis in 13,000 men and women: the Copenhagen city heart study. J Gerontol A Biol Sci Med Sci. 1998;53:M347-M350. 3. Pandhi D, Khanna D. Premature graying of hair. Indian J Dermatol Venereol Leprol. 2013;79:641-653. 4. Kocaman SA, Cetin M, Durakoglugil ME, et al. The degree of premature hair graying as an independent risk marker for coronary artery disease: a predictor of biological age rather than chronological age. Anadolu Kardiyol Derg. 2012;12: 457-463. 5. Orr-Walker BJ, Evans MC, Ames RW, Clearwater JM, Reid IR. Premature hair graying and bone mineral density. J Clin Endocrinol Metab. 1997;82:3580-3583. 6. Schnohr P, Lange P, Nyboe J, Appleyard M, Jensen G. Gray hair, baldness, and wrinkles in relation to myocardial infarction: the Copenhagen city heart study. Am Heart J. 1995;130:1003-1010. 7. Jo SJ, Paik SH, Choi JW, et al. Hair graying pattern depends on gender, onset age and smoking habits. Acta Derm Venereol. 2012;92:160-161. 8. WHO Expert Consultation. Appropriate body-mass index for Asian populations and its implications for policy and intervention strategies. Lancet. 2004;363:157-163. 9. Kim KN, Park JY, Shin TS, et al. Degree of stress and stress-related factors by the Korean version of the BEPSI. J Korean Acad Fam Med. 1998;19:559-570. 10. Fincham JE. Response rates and responsiveness for surveys, standards, and the Journal. Am J Pharm Educ. 2008;72:43. 11. Kroemer S, Fruhauf J, Campbell TM, et al. Mobile teledermatology for skin tumor screening: diagnostic accuracy of clinical
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and dermoscopic image tele-evaluation using cellular phones. Br J Dermatol. 2011;164:973-979. Zayed AA, Shahait AD, Ayoub MN, Yousef AM. Smokers’ hair: does smoking cause premature hair graying? Indian Dermatol Online J. 2013;4:90-92. Gould L, Reddy CV, Oh KC, Kim SG, Becker W. Premature hair graying: a probable coronary risk factor. Angiology. 1978;29: 800-803. Tobin DJ, Paus R. Graying: gerontobiology of the hair follicle pigmentary unit. Exp Gerontol. 2001;36:29-54. Chedekel MR. Photochemistry and photobiology of epidermal melanins. Photochem Photobiol. 1982;35:881-885. Arck PC, Overall R, Spatz K, et al. Towards a ‘‘free radical theory of graying’’: melanocyte apoptosis in the aging human hair follicle is an indicator of oxidative stress induced tissue damage. FASEB J. 2006;20:1567-1569. Commo S, Gaillard O, Bernard BA. Human hair graying is linked to a specific depletion of hair follicle melanocytes affecting both the bulb and the outer root sheath. Br J Dermatol. 2004; 150:435-443. Burke A, Fitzgerald GA. Oxidative stress and smoking-induced vascular injury. Prog Cardiovasc Dis. 2003;46:79-90. Keaney JF Jr, Larson MG, Vasan RS, et al. Obesity and systemic oxidative stress: clinical correlates of oxidative stress in the Framingham study. Arterioscler Thromb Vasc Biol. 2003;23:434-439. Morpurgo G, Fioretti B, Catacuzzeno L. The increased incidence of malignant melanoma in obese individuals is due to impaired melanogenesis and melanocyte DNA repair. Med Hypotheses. 2012;78:533-535. Torres SJ, Nowson CA. Relationship between stress, eating behavior, and obesity. Nutrition. 2007;23:887-894. Richards JM, Stipelman BA, Bornovalova MA, Daughters SB, Sinha R, Lejuez CW. Biological mechanisms underlying the relationship between stress and smoking: state of the science and directions for future work. Biol Psychol. 2011;88:1-12. Linder D, Dreiher J, Zampetti A, Sampogna F, Cohen AD. Seborrheic dermatitis and hypertension in adults: a crosssectional study. J Eur Acad Dermatol Venereol. 2014;28:1450-1455. Bae JM, Ha B, Lee H, Park CK, Kim HJ, Park YM. Prevalence of common skin diseases and their associated factors among military personnel in Korea: a cross-sectional study. J Korean Med Sci. 2012;27:1248-1254. Mosley JG, Gibbs AC. Premature gray hair and hair loss among smokers: a new opportunity for health education? BMJ. 1996; 313:1616.
ARTICLE
Association of premature hair graying with family history, smoking, and obesity: A cross-sectional study Hyoseung Shin, MD,a Hyeong Ho Ryu, MD,b Junghee Yoon, MD,c Seongmoon Jo, MD,b Sihyeok Jang, MD,b Mira Choi, MD,b Ohsang Kwon, MD, PhD,b,d,e and Seong Jin Jo, MD, PhDb,d,e Goyang, Seoul, and Uijungbu, Korea Background: Many researchers have been concerned about the association of hair graying with systemic diseases. However, the common factors associated with hair graying and systemic diseases have not been elucidated. Objective: This study aimed to identify risk factors for premature hair graying (PHG) in young men. Methods: We conducted a cross-sectional study using questionnaires in young men. After a pilot study that included 1069 men, we surveyed 6390 men younger than 30 years about their gray hair status and various socioclinical characteristics. Results: The age of participants in the main survey was 20.2 6 1.3 years (mean 6 SD). Of the 6390 participants, 1618 (25.3%) presented with PHG. Family history of PHG (odds ratio [OR], 12.82), obesity (OR, 2.61), and [5 pack-years history of smoking (OR, 1.61) were significantly associated with PHG. In the multivariate analysis, family history of PHG (OR, 2.63) and obesity (OR, 2.22) correlated with the severity of PHG. Limitations: Owing to the use of questionnaires, the possibility of recall bias exists. Women were not evaluated in this study. Conclusion: Smoking, family history of PHG, and obesity are important factors associated with PHG. ( J Am Acad Dermatol http://dx.doi.org/10.1016/j.jaad.2014.11.008.) Key words: body mass index; gray hair; obesity; premature hair graying; smoking.
H
air graying is one of the natural aging processes.1 Although it is generally not a medical problem, it greatly concerns many people for aesthetic reasons.2 Premature hair graying (PHG) is especially important as a cause of low self-esteem, often impeding social life in young people.3 Moreover, because of the strong association between aging and hair graying, many researchers have been concerned that PHG is a predictor of some severe systemic disease. Several studies evaluated the association of PHG with osteopenia or coronary artery disease.4-6 However, the common factors
associated with hair graying and systemic diseases have not been elucidated. In a previous investigation, we noted that sex and smoking were associated
From the Department of Dermatology, Dongguk University Ilsan Hospital, Goyanga; Department of Dermatology, Seoul National University College of Medicine, Seoulb; 306 Supplementary Battalion, Korea Army, Uijungbuc; Institute of HumanEnvironment Interface Biology, Seoul National University, Seould; and Laboratory of Cutaneous Aging and Hair Research, Biomedical Research Institute, Seoul National University Hospital, Seoul.e The first two authors contributed equally to this work. Funding sources: None.
Conflicts of interest: None declared. Accepted for publication November 6, 2014. Reprint requests: Seong Jin Jo, MD, PhD, Department of Dermatology, Seoul National University College of Medicine, 101 Daehak-ro, Jongno-gu, Seoul 110-744, Korea. E-mail: [email protected]. Published online December 4, 2014. 0190-9622/$36.00 Ó 2014 by the American Academy of Dermatology, Inc. http://dx.doi.org/10.1016/j.jaad.2014.11.008
Abbreviations used: BEPSI-K: BMI: CI: OR: PHG:
modified Korean translated Brief Encounter Psychosocial Instrument body mass index confidence interval odds ratio premature hair graying
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smoking history of more than 5 pack-years were with PHG.7 However, many other socioclinical regarded as smokers. Obesity was categorized characteristics were not examined, and further study according to the World Health Organization was needed. In thi study, we aimed to identify the risk (WHO) classification as follows: underweight, factors for PHG in healthy young Korean men. BMI \18.5 kg/m2; normal weight, 18.5 kg/m2 Koreans are suitable candidates for epidemio# BMI \25 kg/m2; overweight, 25 kg/m2 # BMI logic studies of hair graying because gray hair is \30 kg/m2; obese, BMI $ 30 kg/m2.8 Emotional distinctive against their oristress was evaluated using ginal near-black hair color. the modified Korean transCAPSULE SUMMARY We consider hair graying lated Brief Encounter before the age of 30 years Psychosocial Instrument The risk factors for premature hair to represent PHG because (BEPSI-K). BEPSI-K scores graying are not well known. it was found that in most range from 0 to 5, with In the current study, family history, Koreans, hair graying bescores higher than 2.8 indiobesity, and smoking were associated gins after age 30 years.7 cating high stress, scores with premature hair graying, whereas Various socioclinical charbetween 1.6 and 2.8 indifamily history and obesity correlated acteristics were surveyed cating moderate stress, and with its severity. using questionnaires, and scores lower than 1.6 inditheir associations with hair This study yields clues to the cating low stress.9 graying were assessed. pathophysiology of hair graying. Evaluation of the survey’s METHODS validity Study design and population To evaluate the survey’s validity, we compared We conducted 2 cross-sectional studies using the grade of gray hairs from the subject’s self-report questionnaires. The first was designed as a pilot with the investigator’s examination in 100 subjects. study. After the pilot study, we modified the questionnaire. The participants of both surveys Statistical analysis were recruited at the 306 Supplementary Battalion Unanswered questionnaire items were regarded in Uijungbu, Korea. The 306 Supplementary as missing values. At first, we performed a univariate Battalion is one of the Korean military units into logistic regression analysis. We also analyzed ordinal which citizens are conscripted. To participate, subcategorical variables using the Cochran-Armitage jects had to be younger than 30 years, healthy trend test. Factors with associations at the P less enough to engage in military service, and agree to than .10 significance level in these analyses were participate in this study. The exclusion criteria were then entered into a multivariate logistic regression refusal to participate in the study, hypopigmentary analysis to identify risk factors for PHG. P values less disorder, and alopecia (except androgenetic alopethan .05 were considered significant. cia). This study was approved by the institutional To identify factors associated with the severity of review board of Seoul National University Hospital. PHG, an ordinal logistic regression analysis was To avoid the potential for coercion, we heeded performed. Factors with associations at the P less institutional review board advice and emphasized to than .10 significance level in the univariate ordinal subjects that there would be no penalty for declining logistic regression were analyzed together by to participate. multivariate ordinal logistic regression. P values less than .05 were considered significant. The analyses were performed using a software package Questionnaire details (SPSS Statistics 21.0, IBM Corp, Armonk, NY). Participants were asked about the presence of gray hair. The number of gray hairs was selfreported as follows: 0, less than 10, 10 to 100, and RESULTS more than 100. The collected data included age, Pilot study sex, height, body weight, the presence of a In the pilot study, 1104 questionnaires were medical problem including scalp diseases and returned, and 1069 were analyzed after excluding alopecia, the presence of a family history of 35 by the predefined exclusion criteria. In the PHG, lifestyle behaviors (drinking, smoking, exmultivariate binary logistic regression analysis, BMI ercise, and diet), educational background, schol(odds ratio [OR], 1.04; 95% confidence interval [CI], arly achievements, occupation, and Fitzpatrick 1.00-1.08) (P = .041), family history of PHG (OR, skin type. In our study, participants with a 9.11; CI, 5.64-14.69) (P \.001), and emotional stress d
d
d
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(OR, 1.43; CI, 1.13-1.80) (P = .003) were associated with PHG. Other factors including medical history of admission, chronic diseases, scalp disease or alopecia, educational background, diet, drinking, exercise, smoking, occupation, and Fitzpatrick skin type were not significantly associated with PHG. Evaluation of the survey’s validity The simple percent agreement of grade of gray hairs between investigator and subject was 95.0%, and Cohen kappa coefficient was 0.884. Main survey Demographic and socioclinical characteristics of the study participants. On the basis of the results of the pilot study, we modified the questionnaires by making the questions clearer and the answer options more detailed. We distributed 10,000 questionnaires and 6658 participants agreed to provide information about their hair graying. Of these, 268 (failed to respond regarding hair graying, 63; vitiligo, 12; alopecia areata, 128; telogen effluvium, 4; cicatricial alopecia, 22; unclearly described alopecia, 39) were excluded by the exclusion criteria. The final number of participants analyzed was 6390. They were all Korean men aged 20.2 6 1.3 years (mean 6 SD). We classified 1618 (25.3%) participants with gray hair into the PHG group whereas the remaining 4772 (74.7%) were classified into the non-PHG group. The participants’ socioclinical characteristics are described in Table I. Comparison of socioclinical characteristics between the PHG and non-PHG groups. The comparison of socioclinical characteristics between the 2 groups is summarized in Table I. The PHG group was slightly, but significantly, older than the non-PHG group (P = .002). The odds of having PHG were significantly higher in the overweight (P = .002) and obese (P \ .001) groups than in the normalweight group. A family history of PHG was more commonly present in the PHG group (P \ .001). Among participants in the PHG group, the family history of PHG was paternal in 33.3% and maternal in 11.2%. A family history from both parents was present in 4.6% of participants in the PHG group. The proportion of smokers was higher in the PHG group than in the non-PHG group (P = .013). Most of the participants were students, and 25.1% of them had PHG, whereas 36.9% of blue-collar workers had PHG (P = .015). The proportion of participants with PHG was higher in the moderate and severe stress groups than in the mild stress group (P \ .001 for both). In the additionally performed CochranArmitage trend test, obesity category was associated with PHG (P \ .001), whereas exercise and
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Fitzpatrick skin types showed borderline significance (P = .060 and P = .050, respectively). Risk factors for PHG. Age, obesity, family history, scalp disease, smoking status, exercise, diet, occupation, emotional stress, and Fitzpatrick skin type were selected as candidate risk factors for PHG because they showed associations with PHG (P \ .10) in the comparison analyses. In the multivariate logistic regression analyses, we found that family history of PHG, obesity, and smoking was significantly associated with PHG. The odds of having PHG increased as the group BMI increased (Table II). Further logistic regression analyses on family history showed that a paternal history of PHG (OR, 14.84; CI, 10.10-21.81) (P \.001) had a greater association with PHG than a maternal history (OR, 2.92; CI, 1.57-5.43) (P = .001). Socioclinical characteristics associated with the severity of PHG. We further analyzed 1618 participants with PHG. PHG was more severe in the overweight or obese categories (P = .025 and P = .003, respectively). Family history also correlated with the severity of PHG. PHG participants with a family history tended to have more severe PHG (P = .001). In the multivariate ordinal logistic regression analysis, we confirmed that family history and obesity correlated with the severity of PHG. In PHG participants with a family history of PHG, the odds of more severe PHG were 2.63 times those of PHG participants without a family history. Obesity significantly correlated with the severity of PHG. The OR increased as the group BMI increased (Table III).
DISCUSSION In general, PHG is common in healthy people.3 We therefore sought to identify the risk factors for PHG in a healthy population. We obtained a response rate of 66.6% in the main survey. Generally, a survey response rate greater than 60% is considered sufficient.10 In addition, the nonresponse rate of greater than 30% reflected a lack of coercive enrollments even though this study was conducted in the military. Cohen kappa coefficient, 0.884, between subject’s self-reported gray hair grade and investigator’s examination indicates an almost perfect agreement,11 likely because only a single gray hair in Korean populations is very noticeable against the original black hair color. The comparison between participants with and those without PHG revealed that old age, overweight or obesity, family history of PHG, scalp seborrheic dermatitis, smoking, being a blue-collar worker, and moderate or severe stress had a significant association with PHG. At this step of the analysis,
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Table I. Socioclinical characteristics and comparison between respondents with and without premature hair graying Socioclinical characteristics
No. of subjects Age, y, mean 6 SD Obesity categories,yn (%) Underweight Normal Overweight Obese Family history of PHG, n (%) No Yes Unaware Scalp skin disease, n (%) Normal Seborrheic dermatitis Other scalp disease Medical history of admission or operation, n (%) No Yes Chronic disease,zn (%) No Yes Androgenetic alopecia,xn (%) No Yes Medication,//n (%) No Yes Smoking,{n (%) No Yes Alcohol, n (%) No # 1/mo 2-3/mo 1-2/wk $ 3/wk Exercise, n (%) No # 1/mo 2-3/mo 1-2/wk $ 3/wk Diet, n (%) Vegetarian diet Mixed diet Meat-based diet Educational background, n (%) Middle-school graduation High-school graduation College student or graduation Scholarly achievement,#n (%) 0%-10% 10%-30% 30%-70%
non-PHG
PHG
4772 20.2 6 1.3 4654 (100.0) 394 (8.5) 3197 (68.7) 834 (17.9) 229 (4.9) 4772 (100.0) 2356 (49.4) 303 (6.3) 2113 (44.3) 4673 (100.0) 4489 (96.1) 137 (2.9) 47 (1.0) 4672 (100.0) 2920 (62.5) 1752 (37.5) 4669 (100.0) 4345 (93.1) 324 (6.9) 4493 (100.0) 4405 (98.0) 88 (2.0) 4574 (100.0) 4329 (94.6) 245 (5.4) 4630 (100.0) 4038 (87.2) 592 (12.8) 4753 (100.0) 496 (10.4) 649 (13.7) 1467 (30.9) 1506 (31.7) 635 (13.4) 4737 (100.0) 954 (20.1) 761 (16.1) 1352 (28.5) 1108 (23.4) 562 (11.9) 4686 (100.0) 91 (1.9) 2999 (64.0) 1596 (34.1) 1559 (100.0) 33 (2.1) 498 (31.9) 1028 (65.9) 4516 (100.0) 167 (3.7) 985 (21.8) 2476 (54.8)
1618 20.3 6 1.5 1578 (100.0) 126 (8.0) 991 (62.8) 325 (20.6) 136 (8.6) 1618 (100.0) 247 (15.3) 365 (22.5) 1006 (62.2) 1577 (100.0) 1493 (94.7) 65 (4.1) 19 (1.2) 1575 (100.0) 981 (62.3) 594 (37.7) 1575 (100.0) 1460 (92.7) 115 (7.3) 1528 (100.0) 1488 (97.4) 40 (2.6) 1560 (100.0) 1464 (93.8) 96 (6.2) 1546 (100.0) 1310 (84.7) 236 (15.3) 1604 (100.0) 152 (9.5) 206 (12.8) 533 (33.2) 484 (30.2) 229 (14.3) 1597 (100.0) 347 (21.7) 275 (17.2) 447 (28.0) 346 (21.7) 182 (11.4) 1577 (100.0) 20 (1.3) 983 (62.3) 574 (36.4) 4634 (100.0) 103 (2.2) 1447 (31.2) 3084 (66.6) 1539 (100.0) 76 (0.05) 306 (19.9) 877 (57.0)
OR (95% CI)
P value
1.07 (1.03-1.11)*
.002
1.03 (0.83-1.28) 1.00 [Reference] 1.26 (1.09-1.46) 1.92 (1.53-2.40)
.774 _ .002 \.001
1.00 [Reference] 11.49 (9.40-14.05) _
_ \.001 _
1.00 [Reference] 1.43 (1.06-1.93) 1.22 (0.71-2.08)
_ .021 .476
1.00 [Reference] 1.01 (0.90-1.14)
_ .879
1.00 [Reference] 1.06 (0.85-1.32)
_ .648
1.00 [Reference] 1.35 (0.92-1.96)
_ .124
1.00 [Reference] 1.16 (0.91-1.48)
_ .236
1.00 [Reference] 1.23 (1.04-1.45)
_ .013
1.00 [Reference] 1.04 (0.82-1.32) 1.19 (0.96-1.46) 1.05 (0.85-1.29) 1.18 (0.93-1.49)
_ .774 .107 .655 .177
1.00 [Reference] 0.99 (0.83-1.20) 0.91 (0.77-1.07) 0.86 (0.72-1.02) 0.89 (0.72-1.10)
_ .993 .909 .859 .890
0.67 (0.41-1.09) 1.00 [Reference] 1.10 (0.97-1.24)
.109 _ .128
0.96 (0.65-1.43) 1.03 (0.91-1.17) 1.00 [Reference]
.845 .613 _
1.29 (0.97-1.70) 0.88 (0.76-1.02) 1.00 [Reference]
.081 .086 _ Continued
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Table I. Cont’d Socioclinical characteristics
non-PHG
70%-90% 90%-100% Occupation, n (%) Student White-collar worker Blue-collar worker Service industry worker Self-employed Stress severity scale (BEPSI-K), n (%) Mild Moderate Severe Fitzpatrick skin type, n (%) I II III IV V VI
685 203 3687 3145 93 53 378 18 4702 3005 1423 274 4707 316 906 1349 1415 619 102
(15.2) (4.5) (100.0) (85.3) (2.5) (1.4) (10.3) (0.5) (100.0) (63.9) (30.3) (5.8) (100.0) (6.7) (19.2) (28.7) (30.1) (13.2) (2.2)
PHG
212 68 1277 1052 40 31 143 11 1594 872 589 133 1588 111 331 453 477 197 19
(13.8) (4.4) (100.0) (82.4) (3.1) (2.4) (11.2) (0.9) (100.0) (54.7) (37.0) (8.3) (100.0) (7.0) (20.8) (28.5) (30.0) (12.4) (1.2)
OR (95% CI)
P value
0.87 (0.74-1.04) 0.95 (0.71-1.26)
.125 .701
1.00 [Reference] 1.29 (0.88-1.88) 1.75 (1.12-2.74) 1.13 (0.92-1.39) 1.83 (0.86-3.89)
_ .191 .015 .239 .117
1.00 [Reference] 1.43 (1.26-1.61) 1.67 (1.34-2.09)
_ \.001 \.001
1.00 [Reference] 1.04 (0.81-1.34) 0.96 (0.75-1.22) 0.96 (0.76-1.22) 0.91 (0.69-1.19) 0.53 (0.31-0.91)
_ .758 .714 .737 .472 .020
BEPSI-K, Modified Korean translated Brief Encounter Psychosocial Instrument; CI, confidence interval; OR, odds ratio; PHG, premature hair graying. *The OR of age row is for each additional 1 y. The odds of having PHG are increasing as OR as age increases by 1 y. y World Health Organization criteria. z Any disease treated $ 1 y. x Presence of noticeable, characteristically patterned hair loss. // Any drugs taken orally $ 6 mo. { [5 Pack-y. # 0%, Lowest rank; 100%, highest rank.
Table II. Socioclinical factors associated with the prevalence of premature hair graying using multivariate logistic regression analyses Socioclinical characteristics
Family history of PHG Obesity categories* Underweight Normal Overweight Obese Smokingy
OR (95% CI)
P value
12.82 (9.94-16.55)
\.001
0.61 (0.37-1.03) 1.00 [Reference] 1.28 (0.94-1.74) 2.61 (1.62-4.23) 1.61 (1.10-2.37)
.064 .122 \.001 .014
CI, Confidence interval; OR, odds ratio; PHG, premature hair graying. *World Health Organization criteria. y [5 Pack-y.
the difference in age between the PHG group and the non-PHG group was small but significant even though we tried to control for this major confounding factor of hair graying by studying a population of similarly aged men younger than 30 years. This was corrected by the next step of the analysis, which was a multivariate analysis. In the multivariate analysis, only 3 characteristics (family history, obesity, and smoking) were considered as risk factors for PHG.
This was consistent with a previous study in which smoking was revealed as a risk factor for PHG.12 In the analysis of the severity of PHG, excluding smoking, family history and obesity showed significant associations. In this study, we defined hair graying before the age of 30 years as PHG based on our previous study.7 In fact, the definition of PHG was somewhat arbitrary, and there is no universal definition of PHG. Some investigators have defined PHG as 50% gray hair before the age of 50 years, whereas others defined it as nearly all gray hair before age 40 years.1,5,13 To examine more extreme tendencies, we performed additional analyses under the altered definition of PHG as hair graying before the age of 25 years and found nearly the same results. The mechanism of hair graying is currently attributed to accumulated intracellular oxidative stress. During the enzymatic oxidation process of melanogenesis, a radical intermediate that damages DNA is produced.14,15 Because a high level of melanogenic activity in bulbar melanocytes in the hair follicles is ongoing throughout life, endogenous oxidative stress eventually induces the loss of melanocytes and results in hair graying.16,17
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Table III. Socioclinical factors associated with the severity of premature hair graying using multivariate ordinal logistic regression analysis No. of white hair, n (%) Socioclinical characteristics
Family history of PHG No Yes Obesity categories* Underweight Normal Overweight Obese
\10
10-100
[100
OR (95% CI)
P value
171 (69.2) 167 (45.8)
58 (23.5) 148 (40.5)
18 (7.3) 50 (13.7)
1.00 [Reference] 2.63 (1.88-3.69)
\.001
83 628 182 69
36 307 123 54
7 56 20 13
0.89 (0.46-1.73) 1.00 [Reference] 1.35 (0.91-2.01) 2.22 (1.30-3.79)
(65.9) (63.4) (56.0) (50.7)
(28.6) (31.0) (37.8) (39.7)
(5.6) (5.7) (6.2) (9.6)
.726 .136 .004
CI, Confidence interval; OR, odds ratio; PHG, premature hair graying. *World Health Organization criteria.
It was interesting that smoking and obesity were both found to be risk factors for PHG in this study, because they are both well known to be related to oxidative stress. Smoking is a source of free radicals that generates consequent free radicals in vivo.18 Obesity is independently associated with systemic oxidative stress. Many deleterious effects of obesity are now explained by increased oxidative stress.19 In addition, obesity appears to have an effect on melanogenesis via the hormonal system. Morpurgo et al20 suggested that leptin resistance in obese people increases melanocyte-stimulating hormone antagonists, which causes a reduction of melanogenesis and a decreased capacity for melanocyte DNA repair. To our knowledge, this is the first study to report an association between obesity and hair graying in human beings. An association between coronary artery disease and gray hair was reported previously,4 suggesting that obesity acts as a common risk factor for both coronary artery disease and gray hair. In this study, we found that a family history of PHG was the most powerful risk factor for PHG. In particular, a paternal family history affects PHG more than a maternal history. This might simply be because the onset of hair graying is earlier in men than in women,7 and because this study enrolled only men, the concordance rate of PHG would be higher by chance between fathers and sons than between mothers and sons. Another hypothesis is that genetic factors affecting hair graying come from the father. These genetic candidates might be related to oxidative stress or its defense system. To elucidate genetic effects in hair graying, a further study including women is necessary. Emotional stress showed a significant association with PHG in the univariate analysis but not in the multivariate analysis. This is because emotional
stress is a confounding factor for smoking and obesity. In our data, stress and smoking were significantly correlated (P \ .001). Stress and obesity also had a significant correlation in the normal-weight, overweight, and obese groups (P = .013). It has been previously known that smoking and/or obesity affect stress.21,22 Seborrheic dermatitis, which was removed in the multivariate analysis, seems to be a confounding factor that shows correlations with smoking and stress.23,24 Likewise, blue-collar workers tended to smoke more (P \ .001) and to be more obese (P = .022) than students, indicating that occupation is also a confounding factor for PHG. Family history and obesity were correlated not only with the prevalence of PHG, but also with its severity. However, smoking, which is considered to be associated with the prevalence of PHG, did not correlate with the severity of PHG. This can be explained by the fact that the participants in this study were so young that the accumulation of the effects of smoking was insufficient to affect the severity of PHG. Previous studies that reported an association between smoking and PHG also failed to show a correlation between smoking and the severity of PHG.12,25 To confirm whether smoking affects the severity of PHG, a further study including participants with a wide range of ages is needed. This study has some limitations. First, the possibility of recall bias exists because of the use of questionnaires. However, much of the information needed in this study depended on subjects’ answers, because many events related to analyzed variables had happened in the past. Second, young women were not included in this study. Third, generalizability from the homogeneous Korean population to other ethnicities may be limited. Fourth, this study did not show causality. A prospective study is needed to confirm the causality.
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In this study, family history of PHG, obesity, and smoking were significantly associated with PHG. In particular, family history and obesity showed reproducible significance in both the pilot and main studies and were correlated with the severity of PHG. Our findings may be helpful to researchers investigating the aging process and offer a possible approach to health education against obesity and smoking, particularly in young people. REFERENCES 1. Trueb RM. Aging of hair. J Cosmet Dermatol. 2005;4:60-72. 2. Schnohr P, Nyboe J, Lange P, Jensen G. Longevity and gray hair, baldness, facial wrinkles, and arcus senilis in 13,000 men and women: the Copenhagen city heart study. J Gerontol A Biol Sci Med Sci. 1998;53:M347-M350. 3. Pandhi D, Khanna D. Premature graying of hair. Indian J Dermatol Venereol Leprol. 2013;79:641-653. 4. Kocaman SA, Cetin M, Durakoglugil ME, et al. The degree of premature hair graying as an independent risk marker for coronary artery disease: a predictor of biological age rather than chronological age. Anadolu Kardiyol Derg. 2012;12: 457-463. 5. Orr-Walker BJ, Evans MC, Ames RW, Clearwater JM, Reid IR. Premature hair graying and bone mineral density. J Clin Endocrinol Metab. 1997;82:3580-3583. 6. Schnohr P, Lange P, Nyboe J, Appleyard M, Jensen G. Gray hair, baldness, and wrinkles in relation to myocardial infarction: the Copenhagen city heart study. Am Heart J. 1995;130:1003-1010. 7. Jo SJ, Paik SH, Choi JW, et al. Hair graying pattern depends on gender, onset age and smoking habits. Acta Derm Venereol. 2012;92:160-161. 8. WHO Expert Consultation. Appropriate body-mass index for Asian populations and its implications for policy and intervention strategies. Lancet. 2004;363:157-163. 9. Kim KN, Park JY, Shin TS, et al. Degree of stress and stress-related factors by the Korean version of the BEPSI. J Korean Acad Fam Med. 1998;19:559-570. 10. Fincham JE. Response rates and responsiveness for surveys, standards, and the Journal. Am J Pharm Educ. 2008;72:43. 11. Kroemer S, Fruhauf J, Campbell TM, et al. Mobile teledermatology for skin tumor screening: diagnostic accuracy of clinical
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