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Meta-Analysis
. 2021 Nov 11;11(1):22075.
doi: 10.1038/s41598-021-01573-z.

Defining skin aging and its risk factors: a systematic review and meta-analysis

Affiliations
Meta-Analysis

Defining skin aging and its risk factors: a systematic review and meta-analysis

Qi Yi Ambrose Wong et al. Sci Rep. .

Abstract

Skin aging has been defined to encompass both intrinsic and extrinsic aging, with extrinsic aging effected by environmental influences and overlaying the effects of chronological aging. The risk factors of skin aging have been studied previously, using methods of quantifying skin aging. However, these studies have yet to be reviewed. To better understand skin aging risk factors and collate the available data, we aimed to conduct a systematic review and meta-analysis. We conducted our systematic review in compliance with Preferred Reporting Item for Systematic Review and Meta-Analyses (PRISMA) guidelines. Embase, PubMed and Web of Science databases were searched in October 2020 using specific search strategies. Where odds ratios were reported, meta-analyses were conducted using the random effects model. Otherwise, significant factors were reported in this review. We identified seven notable risk factors for various skin aging phenotypes: age, gender, ethnicity, air pollution, nutrition, smoking, sun exposure. This review's results will guide future works, such as those aiming to examine the interaction between genetic and environmental influences.

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Conflict of interest statement

Dr. CHEW Fook Tim (Singapore) received grants from the Singapore Ministry of Education Academic Research Fund, Singapore Immunology Network, National Medical Research Council (NMRC) (Singapore), and the Agency for Science Technology and Research (A*STAR) (Singapore); Grant Numbers: N-154-000-038-001; R-154-000-191-112; R-154-000-404-112; R-154-000-553-112; R-154-000-565-112; R-154-000-630-112; R-154-000-A08-592; R-154-000-A27-597; R-154-000-A91-592; R-154-000-A95-592; R154-000-B99-114; BMRC/01/1/21/18/077; BMRC/04/1/21/19/315; BMRC/APG2013/108; SIgN-06-006; SIgN-08-020; NMRC/1150/2008; H17/01/a0/0088; and APG2013/108. The funding agencies had no role in the study design, data collection and analysis, decision to publish, or preparation of the manuscript. The other authors declare no other competing interests.

Figures

Figure 1
Figure 1
PRISMA flow diagram (from Moher et al.. Preferred Reporting Items for Systematic Reviews and Meta-Analyses: The PRISMA Statement. PLoS Med 6(7): e1000097. https://doi.org/10.1371/journal.pmed1000097).
Figure 2
Figure 2
Forest plot for skin aging phenotypes and age as a continuous variable.
Figure 3
Figure 3
Forest plot for skin aging phenotypes and male gender (female gender as reference).
Figure 4
Figure 4
Forest plot for skin aging and HRT use.
Figure 5
Figure 5
(a) Forest plot for skin aging and current smoking (non-smoking as reference). (b) Forest plot for skin aging and former smoking (non-smoking as reference). (c) Forest plot for skin aging and being a smoker (ever smoking or smoker = yes), with non-smoker as reference. (d) Forest plot illustrating dose response relationship for smoking (in pack-years) and wrinkling.
Figure 6
Figure 6
(a) Forest plots for more than 1 h/day of sun exposure and skin aging. The comparison exposure for all odds ratio is 1 h/day of sun exposure. Model 1 and 2: Ernster et al. adjusted for age, BMI, and smoking exposure. Model 3 and 4: Ernster et al. adjusted for age, BMI, and smoking status. (b) Forest plots for more than 2 h/day of sun exposure and wrinkling (compared with less than 2 h/day of sun exposure). Model 1 and 2: Ernster et al. excluded from models. Model 3 and 4: included Ernster et al., 1995. (c) Forest plots for sunscreen use and skin aging.

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