The facial measurements in health workers at Dr. Sardjito General Hospital, Yogyakarta

https://doi.org/10.19106/JMedSci005502202306

Nadiya Husna Aliya(1), Neni Trilusiana Rahmawati(2*), Janatin Hastuti(3), Sri Awalia Febriana(4)

(1) Undergraduate Program in School of Medicine, Faculty of Medicine, Public Health and Nursing, Universitas Gadjah Mada, Yogyakarta
(2) Department of Health Nutrition, Faculty of Medicine, Public Health and Nursing, Universitas Gadjah Mada, Yogyakarta/Laboratory of Bio- & Paleoanthropology, Faculty of Medicine, Public Health and Nursing, Universitas Gadjah Mada, Yogyakarta
(3) Laboratory of Bio- & Paleoanthropology, Faculty of Medicine, Public Health and Nursing, Universitas Gadjah Mada, Yogyakarta
(4) Department of Dermatology and Venereology, Faculty of Medicine, Public Health and Nursing, Universitas Gadjah Mada, Yogyakarta
(*) Corresponding Author

Abstract


The appropriate mask is based on facial anthropometric measurements that may be affected by sex, race, age, and body mass index (BMI). This study aimed to determine the difference and relationship between the bizygomatic width (BW) and nasion-menton height (NMH) with sex and BMI in health workers. This descriptive-analytical study used a cross-sectional method. The subjects were 39 health workers (nurses and doctors) at Dr. Sardjito General Hospital, Yogyakarta consisting of 15 male subjects and 24 female subjects, aged between 25-55 years old. Anthropometric measurements were performed on the subjects, including body weight, height, NW, and NMH. The data were analyzed using the Shapiro-Wilk test, independent t-test, and Pearson’s test. There was a significant difference in the BW between male and female subjects (p<0.05), with the males’ BW (13.1 ± 0.76 cm) being larger than that of the female subjects (12.35 ± 0.62 cm). There were no differences in the BMI and nasion-menton height between the male and female subjects (p>0.05). The Pearson’s test results showed no significant relationship between the BW with BMI in both the male subjects (r=0.351; p=0.199) and the female subjects (r=0.349; p=0.094), and between the nasion-menton height with BMI in both the male subjects (r=0.101; p=0.721) and the female subjects (r=0.390, p=0.060). In conclusion, the males’ BW was larger than the female health workers. It is necessary to consider facial anthropometric measurements in face mask manufacturing to provide comfort and good protection.


Keywords


anthropometry, bizygomatic width, body mass index, health workers, nasion-menton height

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References

1.Qaseem A, Etxeandia-Ikobaltzeta I, Yost J, Miller MC, Abraham GM, Obley AJ, et al. Use of N95, surgical, and cloth masks to prevent COVID-19 in health care and community settings: living practice points From the American College of Physicians (Version 1). Ann Intern Med 2020; 173(8):642-9.
https://doi.org/10.7326/M20-3234
2.Wear Compliance and Donning/Doffing of Respiratory Protection for Bioaerosols or Infectious Agents: A Review of the Effectiveness, Safety, and Guidelines [Internet]. Ottawa (ON): Canadian Agency for Drugs and Technologies in Health; 2014 Aug 19. PMID: 25411670.
https://pubmed.ncbi.nlm.nih.gov/25411670/
3.Oestenstad RK, Bartolucci AA. Factors affecting the location and shape of face seal leak sites on half-mask respirators. J Occup Environ Hyg 2010; 7(6):332-41.
https://doi.org/10.1080/15459621003729909
4.Regli A, Sommerfield A, von Ungern-Sternberg BS. The role of fit testing N95/FFP2/FFP3 masks: a narrative review. Anaesthesia 2021; 76(1):91-100.
https://doi.org/10.1111/anae.15261
5.Lin YC, Chen CP. Characterization of small-to-medium head-and-face dimensions for developing respirator fit test panels and evaluating fit of filtering facepiece respirators with different faceseal design. PLoS ONE 2017; 12(11):e0188638.
https://doi.org/10.1371/journal.pone.0188638
6.Zhang X, Jia N, Wang Z. The relationship between the filtering facepiece respirator fit and the facial anthropometric dimensions among Chinese people. Ind Health 2020; 58(4):318-24.
https://doi.org/10.2486/indhealth.2019-0158
7.Sanders MS, McCormick EJ. Human Factors in Engineering and Design. New York: McGraw-Hill; 1993.
8.Kim H, Han DH, Roh YM, Kim K, Park YG. Facial anthropometric dimensions of Koreans and their associations with fit of quarter-mask respirators. Ind Health 2003; 41(1):8-18.
https://doi.org/10.2486/indhealth.41.8
9.Simpson E, Henneberg M. Variation in soft-tissue thicknesses on the human face and their relation to craniometric dimensions. Am J Phys Anthropol 2002; 118(2):121-33.
https://doi.org/10.1002/ajpa.10073
10.Nádaždyová A, Štefánková E, Samohýl M. The impact of body mass index on craniofacial parameters. Kontakt 2016; 18(4): e253-7.
https://doi.org/10.1016/j.kontakt.2016.10.003
11.Zhuang Z, Landsittel D, Benson S, Roberge R, Shaffer R. Facial anthropometric differences among gender, ethnicity, and age groups. Ann Occup Hyg 2010; 54(4):391-402.
https://doi.org/10.1093/annhyg/meq007
12.World Health Organization, 2007. Growth reference data for 5-91 years.
http://www.who.int/tools/growth-reference-data-for-5to19-years
13.Aliya NH. Hubungan antara ukuran antropometri wajah dengan jenis kelamin dan indeks massa tubuh pada tenaga kesehatan di RSUP Dr. Sardjito. (Skripsi). Yogyakarta: Universitas Gadjah Mada, 2021.
14.Badan Penelitian dan Pengembangan Kesehatan. Laporan Nasional Riskesdas 2018. Jakarta: Badan Penelitian dan Pengembangan Kesehatan; 2018.
15.Kunyahamu MS, Daud A, Jusoh N. Obesity among health-care workers: which occupations are at higher risk of being obese? Int J Environ Res Public Health 2021; 18(8):4381.
https://doi.org/10.3390/ijerph18084381
16.Adaja TM, Idemudia OJ. Prevalence of overweight and obesity among health-care workers in University of Benin Teaching Hospital, Benin City, Nigeria. Ann Trop Pathol 2018; 9(2):150-4.
https://doi.org/10.4103/atp.atp_30_18
17.World Health Organization. Obesity: preventing and managing the global epidemic. Geneva: World Health Organization; 2000 p. i–253. (WHO technical report series). Report No: 894.
18.Kasu ES, Ayim A, Tampouri J. Prevalence of obesity among health workers in Kadjebi District of Ghana. J Biol 2015; 13.
19.Skaal L, Pengpid S. Obesity and health problems among South African healthcare workers: do healthcare workers take care of themselves? South African Fam Pract 2014; 53(6):563-7.
https://doi.org/10.1080/20786204.2011.10874153
20.Ramadhaniah R, Julia M, Huriyati E. Durasi tidur, asupan energi, dan aktivitas fisik dengan kejadian obesitas pada tenaga kesehatan puskesmas. Jurnal Gizi Klinik Indonesia 2014; 11(2):85-96.
https://doi.org/10.22146/ijcn.19011
21.Kit LP. Determinants of Obesity Indices Among Primary Healthcare Workers in Perak, Malaysia. [Malaysia]: Universiti Putra Malaysia; 2019.
22.Asil E, Surucuoglu MS, Cakiroglu FP, Ucar A, Ozcelik AO, Yilmaz MV, et al. Factors that affect body mass index of adults. Pakistan J Nutr 2014; 13(5):255-60.
https://doi.org/10.3923/pjn.2014.255.260
23.Xiao X, Wang W, Sa R, Qiu L, Liu F. The investigation of sex differences in the effect of body mass index. Int J Hypertens 2019; 2019:1360328.
https://doi.org/10.1155/2019/1360328
24.Centers for Disease Control and Prevention. Body Mass Index: Considerations for Practitioners [Internet]. CDC; 2011.
https://stacks.cdc.gov/view/cdc/25368
25.Fouad MF, Rastam S, Ward KD, Maziak W. Prevalence of obesity and its associated factors in Aleppo, Syria. Prev Control 2006; 2(2):85-94.
https://doi.org/10.1016/j.precon.2006.09.001
26.Jaakkola J, Hakala P, Isolauri E, Poussa T, Laitinen K. Eating behavior influences diet, weight, and central obesity in women after pregnancy. Nutrition 2013; 29(10):1209-13.
https://doi.org/10.1016/j.nut.2013.03.008
27.Rooney BL, Schauberger CW. Excess pregnancy weight gain and long-term obesity: one decade later. Obstet Gynecol 2002; 100(2):245-52.
https://doi.org/10.1016/s0029-7844(02)02125-7
28.Nadimin, Ayumar, Fajarwati. Obesitas pada orang dewasa anggota keluarga miskin di kecamatan lembang Kabupaten Pinrang. Media Kesehatan Masyarakat Indonesia 2015; 11(3):9-15.
https://doi.org/10.30597/mkmi.v11i3.521
29.Chiolero A, Faeh D, Paccaud F, Cornuz J. Consequences of smoking for body weight, body fat distribution, and insulin resistance. Am J Clin Nutr 2008; 87(4):801-9.
https://doi.org/10.1093/ajcn/87.4.801
30.Komalawati, Indriaty E, Supartinah A. Profil jaringan lunak dan keras wajah lelaki dan perempuan dewasa etnis Aceh berdasarkan keturunan campuran Arab, Cina, Eropa Dan Hindia. Cakradonya Dent J 2013; 5(2):542-618.
31.Lakhiani C, Somenek MT. Gender-related facial analysis. Facial Plast Surg Clin North Am 2019; 27(2):171-7.
https://doi.org/10.1016/j.fsc.2019.01.006
32.Oh J, Han JJ, Ryu SY, Oh HK, Kook MS, Jung S, et al. Clinical and cephalometric analysis of facial soft tissue. J Craniofac Surg 2017; 28(5): e431-8.
https://doi.org/10.1097/SCS.0000000000003614
33.Osunwoke EA, Amah-Tariah FS, Obia O, Ekere IM, Ede O. Sexual dimorphism in facial dimensions of the Bini’s of South-Southern Nigeria. Asian J Med Sci 2011; 3(2):71-3.
34.Marečková K, Weinbrand Z, Chakravarty MM, Lawrence C, Aleong R, Leonard G, et al. Testosterone-mediated sex differences in the face shape during adolescence: subjective impressions and objective features. Horm Behav 2011; 60(5):681-90.
https://doi.org/10.1016/j.yhbeh.2011.09.004
35.Dong Y, Huang L, Feng Z, Bai S, Wu G, Zhao Y. Influence of sex and body mass index on facial soft tissue thickness measurements of the northern Chinese adult population. Forensic Sci Int 2012; 222(1-3):396.e1-7.
https://doi.org/10.1016/j.forsciint.2012.06.004
36.Mayer C, Windhager S, Schaefer K, Mitteroecker P. BMI and WHR are reflected in female facial shape and texture: a geometric morphometric image analysis. PLoS ONE 2017; 12(1):e0169336.
https://doi.org/10.1371/journal.pone.0169336
37.Windhager S, Patocka K, Schaefer K. Body fat and facial shape are correlated in female adolescents. Am J Hum Biol 2013; 25(6): 847-50.
https://doi.org/10.1002/ajhb.22444
38.Kotrashetti VS, Mallapur MD. Radiographic assessment of facial soft tissue thickness in South Indian population: an anthropologic study. J For Legal Med 2016; 39:161-8.
https://doi.org/10.1016/j.jflm.2016.01.032
39.Solano T, Mittal R, Shoele K. One size fit all? modeling face-mask fit on population-based faces. PLos ONE 2021; 16(6):e0252143.
https://doi.org/10.1371/journal.pone.0252143



DOI: https://doi.org/10.19106/JMedSci005502202306

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