Faktor Determinan Kejadian Pra-Sindrom Metabolik pada Dosen dan Tenaga Kependidikan di Institusi Pendidikan Tinggi
DOI:
https://doi.org/10.37012/jik.v12i1.179Abstract
Pra-sindrom metabolik (Pra-SM) adalah keadaan individu yang mengalami obesitas sentral (lingkar pinggang pria ≥ 90 cm, wanita ≥80 cm) disertai satu indikator sindrom metabolik yaitu tekanan darah ≥130/85 mmHg atau dalam pengobatan antihipertensi atau pernah didiagnosis hipertensi oleh tenaga kesehatan. Bagaimanapun juga, pra-SM merupakan indikator skrining yang baik untuk mengidentifikasi masalah penyakit tidak menular di tempat bekerja, karena produktifitas pekerja harus didukung oleh kondisi kesehatan yang optimal. Tujuan penelitian ini untuk mengetahui faktor determinan pra-SM pada pekerja (dosen dan tenaga kependidikan) di Universitas MH. Thamrin. Metode yang digunakan dalam penelitian ini yaitu Desain cross sectional, terhadap 128 responden yang diperoleh dari metode total sampling. Analisis dilakukan pada data primer meliputi univariat, uji chi square dan analisis multivariat regresi logistik ganda. Prevalens pra-SM sebesar 38,3%;  didominasi oleh: pria (47,9%), berusia >35 tahun (44,9%), dan mengalami kegemukan (55,9%.). Faktor determinan yang paling berisiko terhadap pra-SM adalah: umur >35 tahun (OR: 3,11; 95%CI: 1,18 – 8,23); kegemukan (OR: 5,02; 95%CI: 2,20 – 11,47); jenis kelamin pria (OR: 2,02; 95%CI: 0,87 – 4,67) dan pendapatan <UMR DKI Jakarta tahun 2019 (OR: 1,91; 95%CI: 0,79 – 4,65). Rekomendasi perlunya dilakukan program pencegahan primer yaitu pemeriksaan kesehatan rutin bagi pekerja untuk deteksi dini dan menurunkan risiko pra-SM.
References
Alamri¹, F. A., Amer¹, S. A., Almubarak, A., & Alanazi, H. (2019). Sleep Quality among Healthcare Providers; In Riyadh, 2019. Age (y), 20, 30.
Bantas K; Yosef HK; Moelyono B; 2012. Perbedaan Gender pada Kejadian Sindrom Metabolik pada Penduduk Perkotaan di Indonesia. Kesmas, Jurnal Kesehatan Masyarakat Nasional Vol. 7, No. 5, Desember 2012.
Chackrewarthy S, et al. (2013). A Comparison between Revised NCEP ATP III and IDF Definitions in Diagnosing Metabolic Syndrome in an Urban Sri Lankan Population: The Ragama Health Study. ISRN Endocrinology. Volume 2013, 7 pages: 1-7. http://dx.doi.org/10.1155/2013/320176 . 5 July 2019.
Church TS, Thomas DM, Tudor-Locke C, Katzmarzyk PT, Earnest CP, Rodarte RQ, et al. Trends over 5 decades in U.S. occupation-related physical activity and their associations with obesity. PLoS ONE. 2011; 6(5): e19657. doi:10.1371/journal.pone.0019657.
Foraker, R. E., Rose, K. M., Suchindran, C. M., Chang, P. P., McNeill, A. M., & Rosamond, W. D. (2011). Socioeconomic status, Medicaid coverage, clinical comorbidity, and rehospitalization or death after an incident heart failure hospitalization: Atherosclerosis Risk in Communities cohort (1987 to 2004). Circulation: Heart Failure, 4(3), 308-316.
Grundy, SM. (2018). Metabolic Syndrome. In Bonora E & DeFronzo, RA (Ed). Diabetes complications, comorbidities and related disorders. (pp. 71-107). Switzerland: Springer.
Karalis D; Auberson D; Naqvi SY; (2018). Clinical feature: gender differences in the diagnosis and treatment of the metabolic syndrome. National Lipid association. https://www.lipid.org/node/1448
Kemenkes RI (2013). Riset Kesehatan Dasar 2013. Badan Litbangkes, Kementerian Kesehatan RI.
Kemenkes RI (2018). Riset Kesehatan Dasar 2018. Badan Litbangkes, Kementerian Kesehatan RI.
Kim, Y. H., Kim, H., & Jee, H. (2018). Effects of socioeconomic status, health behavior, and physical activity on the prevalence of metabolic syndrome. Journal of exercise rehabilitation, 14(2), 183.
Lin, Y. C., Chen, J. D., Lo, S. H., & Chen, P. C. (2010). Worksite health screening programs for predicting the development of Metabolic Syndrome in middle-aged employees: a five-year follow-up study. BMC public health, 10(1), 747.
Negi, P. C., Sondhi, S., Merwaha, R., & Asotra, S. (2019). Prevalence and risk determinants of metabolic syndrome in obese worksite workers in hill city of Himachal Pradesh, India. Indian heart journal, 71(1), 45-51.
Özmen, B., Demet, M. M., Güçlü, F., Kafesçiler, S., Aydemir, Ö., & Hekimsoy, Z. (2009). Metabolic Syndrome and Health-related Quality-of-life in Obese Women. INDIAN JOURNAL OF CLINICAL PRACTICE, 19(11).
Shuto, H., Shuto, C., Inoue, T., Nishikata, H., & Tokutake, E. (2015). Assessment of Waist Circumference Index as a New Screening Parameter for Pre-Metabolic Syndrome. J Health Edu Res Dev, 3(139), 2.
Tan, C., Sasagawa, Y., Kamo, K. I., Kukitsu, T., Noda, S., Ishikawa, K., ... & Takahashi, F. (2016). Evaluation of the Japanese Metabolic Syndrome Risk Score (JAMRISC): a newly developed questionnaire used as a screening tool for diagnosing metabolic syndrome and insulin resistance in Japan. Environmental health and preventive medicine, 21(6), 470.
World Health Organization (WHO). (2018). Non communicable diseases. May 5, 2019. https://www.who.int
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