Prevalence of skin diseases in old age

The prevalence of skin disorders was studied in an elderly population comprising 584 individuals. The mean age was 80 years (range 55-106). The prevalence of pityriasis of the scalp and asteatosis was high, 44.3% and 28.9%, respectively. Psoriasis vulgaris was found in 2.9%, vitiligo in 1.2%, and contact dermatitis in 3.8% of the group.     

Skin colorimetric parameters involved in skin age perception

Background/purpose: Age perception is based on a number of facial attributes such as wrinkles, skin gravity effects, feature lines, and skin optical appearance. The colorimetric and optical diffusion properties of skin have been compared with the consumer interpretation of ‘skin age’ of cheek area pictures without wrinkles or feature lines. Methods: Controlled lighting images of skin were taken with the Visia CR. Skin sections from the cheek area were selected without eye region wrinkles or naso‐labial lines for consumer interpretation. These same skin sections were analyzed for optical roughness and colorimetric parameters in the LCH color space, by distinguishing several roughness parameters according to their physical scale. Results: Three main optical parameters of skin were found to influence the consumer's interpretation of skin ‘visual age’: the chroma (color saturation), lightness, and the local light‐diffusing ability of skin. For the chroma and lightness, mainly large‐scale inhomogeneities in the 0.8–2 cm^?1 range are taken into account by the consumer. Surprisingly, variations in the skin hue show a total absence of correlation with the consumer grading.     

The influence of age and sex on skin thickness, skin collagen and density

Forearm skin collagen, dermal thickness and collagen density were measured in a large number of normal subjects as a standard reference for future studies. Skin collagen decreased with age and was less in the females at all ages. There is a direct relationship between skin collagen and dermal thickness but variations in collagen density in disease limit the use of dermal thickness as a guide to changes in its collagen content.     

Influence of age on the wrinkling capacities of skin

Background: Comparisons of clinical assessment with measurement of physical parameters are rare.
Objective: To standardize the horizontal wrinkling of the skin in order to define a reference chart of the different wrinkling grades and to propose an interpretation of the clinical pattern in terms of skin layers thickness and mechanical parameters.
Methods: A device allowing reproducible wrinkling of the skin was made. The skin folds created in this way were clinically assessed on women of different ages. Measurements of the mechanical properties of the skin were carried out by using a Torquemeter. Skin layers' thicknesses were measured by using in vivo Confocal Microscopy (CM) and Ultrasound Imaging (B mode).
Results: Skin wrinkling grades increase versus age. Skin elasticity, extensibility and echogenicity decrease also versus age and the wrinkling grade. Wrinkling appears to be related to skin rigidification (for both stratum corneum and dermis) coupled to a certain weakening of the upper dermis (loss of echogenicity).
Conclusion: This study points out the key role of the age-related alterations of the upper dermis in skin wrinkling capacities.     

Pattern of skin diseases in paediatric age group and adolescents

A total of 300 patients from first day of life to 17 years of age were analysed for pattern of skin disorders. School going children formed majority (41.3%) of cases followed by preschool children (32%). Infections formed the commonest disorder (31 %) followed by eczemas (24%), papulosquamous disorders (12%), infestation (8.6%) and urticaria (5.3%) while vitiligo, acne vulgaris, alopecia areata and genodermatoses were seen in 2.7% cases each.     

In vitro effects of skin lipid extracts on skin bacteria in relation to age and acne changes

Skin lipid extracts of 185 persons of different age were tested in vitro against single representatives of skin bacteria: Staphylococcus aureus, S. epidermidis, Propionibacterium acnes, P. granulosum and Corynebacterium sp. in order to find differences in their inhibitory effects. Percentages of the extracts inhibiting the first 4 bacteria were nearly the same (about 20%) while corynebacteria were inhibited by only 3 extracts. Extracts showing these properties were isolated mainly from adolescents with acne changes, young adults, about 20 yr old, and from children 8--10 yr old, but not from elderly people. The age-related differences in growth inhibition may be related to known differences in relative composition of the sebum constituents according to age. Forty-two extracts of acne patients and healthy adults and adolescents showed an inverse effect in vitro: they enhanced bacterial growth. Growth enhancement was demonstrated only for P. granulosum.     

女性颈部皮肤生理学特性与年龄、季节相关性研究

目的:采用无创性评价技术量化检测女性颈部皮肤生理学特性,分析其与年龄和季节的关系.方法:检测62名女性健康志愿者颈部皮肤(曝光部位)的弹性﹑水分﹑经皮水分丢失(trans-epidermal water loss,TEWL)、皮肤颜色[包括黑素(M)值及血红素(E)值],并选取前臂内侧(非曝光部位)作为对照组,于春夏秋冬4个季节进行随访,每次随访均对志愿者颈部皮肤拍照.结果:①皮肤弹性、角质层含水量与年龄呈负相关.60岁以上年龄组TEWL明显低于其他年龄组.皮肤M值和E值随年龄增加变化有波动.②颈部皮肤弹性与季节相关,夏季、秋季较低.颈部和前臂内侧皮肤角质层含水量夏季最高,颈部角质层含水量高于前臂内侧.两部位在夏秋季皮肤TEWL值较高.颈部M值在秋季最高,E值在夏季最高,前臂内侧M值和E值在季节间无统计学差异.曝光部位颈部皮肤生理特性相较于非曝光部位前臂内侧更易受季节因素影响.结论:利用无创性评价可以量化地揭示不同季节、不同年龄皮肤表面生理学特性,了解皮肤的生理状态,并可以通过监测这些参数的变化了解健康皮肤或疾病的发展,采取干预措施改善皮肤表面特征.     

Influence of skin area,age and sex on corneometric determinations

Background/aims: Comeometry represents a useful tool for dermatologists, even though several interfering variables may reduce its reliability level. The present study describes some of the methodological points that optimize corneometric measurements and analyzes the interference due to the skin area selected, the age and the sex of the individuals observed. Results: The results show that skin areas may present significantly different corneometric values. In addition, a significant correlation of the corneometric values at most of the sites was observed independently of the sun-exposed site. Conclusions: The corneometric values were clearly age dependent and sex independent. Measurements were obtained from eight different body areas (two of them were symmetric and presented superimposable results). The volar forearm appears to be the area least influenced by the patients’age and presents the lowest correlation coefficients with other skin sites.     

Relative contribution of intrinsic vs extrinsic factors to skin aging as determined by a validated skin age score

OBJECTIVE: To assess the relative contribution of intrinsic aging vs lifestyle factors to facial skin age. DESIGN: Prospective analysis of a cohort. SETTING: Skin research institute. STUDY SUBJECTS: A cohort of 361 white women (age range, 18-80 years) with apparently healthy skin. MEASUREMENTS: Visual and tactile assessment of facial skin features. RESULTS: Twenty-four skin characteristics were used to build a skin age score (SAS). The relationship between the SAS and chronological age followed a linear model with 2 plateaus--1 before age 30 years and 1 after age 71 years. An analysis was performed to determine whether certain lifestyle habits known to have effects on skin aging were related to the discrepancies between chronological age and the SAS. Significant effects were identified for phototype, body mass index, menopausal status, degree of lifetime sun exposure, and number of years of cigarette smoking. However, these factors accounted for only 10% of the discrepancies. Moreover, most skin characteristics used reflected changes understood to represent intrinsic aging rather than photodamage or other extrinsic factors. CONCLUSIONS: An SAS can be generated from multiple discrete signs evaluated on facial skin and is an informative tool for quantifying skin aging. The SAS is influenced by factors already recognized to affect the aging phenotypes; however, factors related to the rate of intrinsic aging, presumably genetic in character, seem to play a larger role than previously suspected.     

Effectiveness of skin cancer screening for individuals age 14 to 34 years

Background: Approximately 15 % of all cases of melanoma are diagnosed before age 35 years. In Germany, individuals ≥ 35 years are eligible for the national skin cancer screening program. The effectiveness of a population‐based skin cancer screening in general and in particular for young adults is unclear. Objectives: Assessment of the effectiveness of a skin cancer screening program and of risk factors for detection of a melanoma/atypical nevus in the setting of a screening for the age group 14 to 34 years. Methods: A total of 12 187 individuals age 14 to 34 years were screened in Saxony for skin cancer by a dermatologist in the program “Haut‐Check 14–34 Jahre” of the AOK PLUS, a large German health insurance, between January and July 2009. Demographic, clinical and histopathological data and UV‐exposure data were collected from each participant. Multivariate logistic regression models were used to assess risk factors for the detection of a (histopathologically confirmed) melanoma or atypical nevus. Results: 2.8 % of the eligible individuals participated in the skin cancer screening program with women being more likely to do so. In 1 072 individuals (8.8 %) screening included at least one excision of a skin lesion leading to the diagnosis of melanoma in two participants, melanoma in situ in four persons, and atypical nevus in 641 persons. Use of tanning beds, higher age, number of nevi, and previous cutaneous excision were independent risk factors for the detection of a melanoma or atypical nevus. Conclusions: In 5.5 % of all cases skin cancer screening resulted in the excision of a malignant or atypical melanocytic lesion. It remains unclear what proportion of these cases would have been detected in routine care. The rate of excisions per newly diagnosed melanoma was 179 : 1. Further investigations are necessary to explore the reasons for this low diagnostic specificity. This study highlights the possibilities and limitations of routine data to evaluate screening programs and indicates the need to collect additional information on healthcare utilization behaviour.