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Latar belakang: Sindroma metabolik (MS) dapat menyebabkan kecacatan di antara pilot di Indonesia.Tujuan dari penelitian ini adalah untuk mengidentifikasi faktor-faktor risiko MS antara pilot komersialjarak pendek di Indonesia.Metode: Penelitian potong lintang dengan sampling purposif yang dilakukan di antara pilot komersial yangmelakukan uji medik di Balai Kesehatan Penerbangan Sipil, Jakarta tanggal 27 Juli-30 Agustus 2014. Sindromametabolik dinilai menurutkriterian National Cholesterol Education Program Adult Treatment Panel III. Faktorrisiko diperoleh dengan menggunakan kuesioner self-reporting anonim. Data laboratorium diperoleh daricatatan medis. Regresi Cox digunakan untuk mengidentifikasi faktor-faktor risiko yang dominan dari MS.Hasil: Selama pengumpulan data, 2135 pilot melakukan uji medik. Jumlah pilot Asia laki-laki memenuhi kriteriainklusi adalah 864 pilot. Prevalensi MS adalah 18,28%. Dibandingkan dengan kelompok 20-35 tahun, yangberusia berusia 56-65 tahun memiliki risiko 88% lebih tinggi untuk MS [risiko relatif sesuaian (RRa) = 1,88;P = 0,019]. Jika ditinjau dari jumlah sektor dalam 24 jam terakhir, dibandingkan dengan 0-3 sektor, subyekyang memiliki 6-7 sektor mempunyai risiko 66% lebih tinggi untuk MS (RRa = 1,66; P = 0,033), sedangkanyang memiliki 8 atau lebih sektor dalam 24 jam memiliki 82% lebih berisiko untuk MS (RRa = 1,82; P = 0,072).Kesimpulan: Pilot berusia tahun-56-65, yang memiliki 6 atau lebih sektor dalam 24 jam terakhir, memilikirisiko lebih tinggi untuk sindroma metabolik antara jarak pendek pilot komersial di Indonesia. (HealthScience Journal of Indonesia 2015;6:81-6)Kata kunci: Sindroma metabolik, jumlah sektor, pilot, Indonesia Abstract Background: Metabolic syndrome (MS) could cause sudden incapacitation among pilots in Indonesia.The aim of this study was to identify risk factors of MS among short-haul commercial pilots in Indonesia.Methods: A cross-sectional study with purposive sampling was conducted among commercial pilotstaking medical examination at the Civil Aviation Medical Center, Jakarta from July 27-August 30th,2014. Metabolic syndrome was assessed according to the National Cholesterol Education Program AdultTreatment panel III criteria and criteria. Risk factors were collected using anonymous self-reportingquestionnaire. The laboratory data were extracted from medical records. Cox regression was used toidentify dominant risk factors of MS.Results: During data collection, 2135 pilots taking medical examination, Total male Asian pilots metthe inclusion criteria was 864 pilots. Prevalence of MS was 18.28%. Compared to 20-35 year-old group,subjects aged 56-65 years-old had 88% higher risk for MS [adjusted relative risk (RRa) = 1.88; P = 0.019].In term of number of sectors in the last 24 hours, compared to 0-3 sectors, subjects who had 6-7 sectors inthe last 24 hours had 66% higher risk for MS (RRa = 1.66; P = 0.033), while subjects who had 8 or moresectors in 24 hours had 82% more risk for MS (RRa = 1.82; P = 0.072).Conclusions: The pilot aged 56-65 years-old, who had 6 or more sectors in the last 24 hours, had higherrisk for metabolic syndrome among short-haul commercial pilots in Indonesia. (Health Science Journalof Indonesia 2015;6:81-6)Keyword: metabolic syndrome, number of sectors, pilots, Indonesia

Latar belakang: Kelelahan penerbang sipil, termasuk pada penerbangan jarak dekat, dapat mempengaruhi fungsikognitif penerbang sehingga membahayakan keselamatan penerbangan. Tujuan penelitian ini untuk mengidentifikasifaktor-faktor yang mempengaruhi kelelahan penerbang sipil pada penerbangan jarak dekat di Indonesia.Metode: Desain penelitian potong lintang dengan purposive sampling dilakukan di antara penerbang jarak dekatdengan rating Boeing 737 series yang melaksanakan pengujian kesehatan di Balai Kesehatan Penerbanganperiode 5-26 Mei, 2014. Kelelahan diukur dengan Self-Reporting Questionnaire, Fatigue Severity Scale (FSS).Data dikumpulkan dengan pengisian kuesioner oleh subyek yang meliputi demografi, pekerjaan, kehilanganwaktu tidur (Epworth Sleepiness Scale - ESS), faktor personal, dukungan manajemen, dan FSS. Analisis regresilinear dipakai untuk menganalisis faktor-faktor dominan berkaitan kelelahan.Hasil: Di antara 785 penerbang yang melaksanakan pengujian kesehatan, 382 bersedia berpartisipasi, dan239 penerbang yang memenuhi kriteria. Rata-rata skala kelelahan adalah 4,66 (standar deviasi 1,202).Faktor-faktor dominan yang mempertinggi skala kelelahan adalah jumlah sektor 24 jam terakhir, jam terbangpenugasan di luar jadwal, dan kehilangan waktu tidur. Setiap penambahan 1 sektor dalam 24 jam terakhirmeningkatkan 0,371 skala kelelahan [koefisien regresi (β) = 0,371; P = 0,000]. Selanjutnya setiap penambahan1 jam terbang penugasan di luar jadwal mempertinggi 0,033 skala kelelahan (β = 0,033; P = 0,000). Sedangkan setiap penambahan 1 nilai ESS mempertinggi 0,043 skala kelelahan (β = 0,043; P = 0,008).Kesimpulan: Penambahan jumlah sektor 24 jam terakhir, kehilangan waktu tidur, dan penambahanjam terbang penugasan di luar jadwal mempertinggi risiko kelelahan di antara penerbang sipil padapenerbangan jarak dekat di Indonesia. (Health Science Journal of Indonesia 2015;6:69-75)Kata kunci: kelelahan, jumlah sektor, penerbang sipil, Indonesia AbstractBackground: Fatigue could impair cognitive function in pilots which may lead to accidents in short-haul flight. Theaim of this study was to identify the risk factors related to fatigue among short-haul commercial pilots in Indonesia.Methods: A cross-sectional study with purposive sampling was conducted among Boeing 737 seriestyped-rating pilots taking medical examination at the Civil Aviation Medical Center, Jakarta from May5-26, 2014. Fatigue was measured with Self-Reporting Questionnaire, Fatigue Severity Scale (FSS). Datawere collected using anonymous self-reporting questionnaire on demographics, workload, sleep restriction(Epworth Sleepiness Scale-ESS), personal factors, and managerial support. Linear regression was used toidentify dominant risk factors related to fatigue.Results: During data collection, 785 pilots were taking medical examination, 382 pilots were willing toparticipate, and 239 pilots met the criteria. The FSS mean was 4.66 ± 1.202. The number of sectors in 24hours, flight times of unplanned flights in 30 days, and sleep restriction were dominant factors of fatigue.Each additional sector increased FSS by 0.371 points [regression coefficient (β) = 0.371; P = 0.000].Furthermore, each additional ESS, increased FSS by 0.043 points (β = 0.043; P = 0.008), while eachadditional unplanned flights increased FSS by 0.033 points (β = 0.033; P = 0.000).Conclusions: Additional number of sectors in 24 hours, additional unplanned flight times within 30 days,and sleep restriction increased the risk of fatigue among short-haul commercial pilots in Indonesia. (HealthScience Journal of Indonesia 2015;6:69-75)Keyword: Fatigue, number of sectors, pilots, Indonesia