Modelo predictivo del patrón de fertilidad de las mujeres jóvenes (15-24 años) en el Sur de Sulawesi, Indonesia / The Predictive Model of the Fertility Pattern of Young Women (15-24 Years Old) in South Sulawesi, Indonesia

Syahrul Basri, Bs. Titi Haerana, Lilis Widiastuty, Yudi Adnan, Ranti Ekasari, Rimawati Aulia Insani Sadarang, Dian Rezki Wijaya, Wisnu Fadila

Resumen


Las adolescentes que han dado a luz tienen una más alta probabilidad de tener una tasa de fecundidad total alta con mayor prevalencia. Este estudio tuvo como objetivo analizar la contribución de los factores demográficos y socioeconómicos, el acceso a la información, la actividad sexual y nociones sobre planificación familiar a los patrones de fertilidad entre mujeres jóvenes (15-24 años). La investigación utiliza datos de 2017 de la Encuesta de Demografía y Salud de Indonesia (IDHS). Para el análisis de los datos se realizó una regresión logística múltiple con un modelo predictivo. Los predictores para la fecundidad de las mujeres jóvenes (15-24 años) fueron el estado civil (aOR: 373.9, 95%CI 112.7-1239.8), la edad de 19-21 años (aOR: 7.74, 95%CI 2.19-27.32), la edad de 22-24 años (aOR: 4.79, 95%CI 1.61-14.32), un nivel educativo bajo (aOR: 2.53, IC95% 0.94-6.82), estar desempleado (aOR: 2.73, IC95% 1.14-6.55) o trabajar en la agricultura (aOR: 1.16, IC95% 0.19-6.87), y un índice de riqueza bajo (aOR: 1.79, IC95% 0.73-4.41) o medio (aOR: 1.58, IC95% 0.42-5.87), según los datos de SKDI de 2017. Es necesario mejorar el acceso a la educación para aumentar las oportunidades de empleo y mejorar las condiciones socioeconómicas de la comunidad. Esta mejora tendrá efectos positivos en la prevención del matrimonio adolescente y una disminución en la tasa de fertilidad de las mujeres jóvenes
Palabras clave: Predicción, fertilidad, mujeres jóvenes, Sulawesi del Sur

Abstract

Teenagers that have given birth have a high chance of a total fertility rate and prevalence. The study aimed to analyze the contribution of demographic and socio-economic factors, access to information, sexual activity, and literacy on family planning on the fertility pattern of young women (15-24 years old). This research uses 2017 data from the Indonesian Demography and Health Survey (IDHS). Data analysis performed multiple logistic regression with a predictive model. The predictors of young female fertility (15-24 years old) were marital status (aOR: 373.9, 95%CI 112.7-1239.8), age of 19-21 years old (aOR: 7.74, 95%CI 2.19-27.32), age of 22-24 years old (aOR: 4.79, 95%CI 1.61-14.32), a low education level (aOR: 2.53, 95%CI 0.94-6.82), unemployed (aOR: 2.73, 95%CI 1.14-6.55) or working in agriculture (aOR: 1.16, 95%CI 0.19-6.87), and low (aOR: 1.79, 95%CI 0.73-4.41) or medium (aOR: 1.58, 95%CI 0.42-5.87) wealth index, based on SKDI's 2017 data. There needs to be an improvement in the education access to increase job opportunities and improve the socio-economic conditions of the community. This improvement will have positive impacts in preventing adolescent marriage and decreasing the fertility rate of young women Keywords: Predictive, fertility, young women, South Sulawesi

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Referencias


Agyemang, J., Newton, S., Nkrumah, I., Tsoka-Gwegweni, J. M., & Cumber, S. N. (2019). Contraceptive use and associated factors among sexually active female adolescents in Atwima Kwanwoma District, Ashanti region-Ghana. Pan African Medical Journal, 32. https://doi.org/10.11604/pamj.2019.32.182.15344

Ajala, A. O. (2014). Mass Media Exposure and Intention to use Contraceptives in North-West Geo-Political Zone, Nigeria. IISTE, 4(24), 101–114.

Akhiruddin. (2016). Dampak Pernikahan Usia Muda (Studi Kasus Di Desa Mattirowalie Kecamatan Libureng Kabupaten Bone). Mahkamah, 1(1), 205–222.

Bappenas. (2017). Ringkasan Metadata Indikator Tujuan Pembangunan Berkelanjutan (TPB)/Sustainabale Development Goals (SDGs) Indonesia. BAPPENAS.

BKBBN. (2018). Survei Demografi dan Kesehatan 2017. Riset Kesehatan Dasar 2018.

BPS. (2019). Statistik Indonesia 2019. Statistik Indonesia 2019 (Indonesian statistics). Jakarta: Badan Pusat Statistik.

Christabel, G. A. (2019). Socio-Economic Differentials in Adolescent Fertility in Kenya: Evidence from The 2014 KDHS. University of Nairobi.

Cinar, N., & Menekse, D. (2017). Affects of Adolescent Pregnancy on Health of Baby. Open J Pediatr Neonatal Care, 3(1), 12–16.

Dake, F., Natali, L., Angeles, G., de Hoop, J., Handa, S., & Peterman, A. (2018). Cash Transfers, Early Marriage, and Fertility in Malawi and Zambia. Studies in Family Planning, 49(4), 295–317. https://doi.org/10.1111/sifp.12073

ICF. (2018). Demographic and Health Surveys Standard Recode Manual for DHS 7, 145. Retrieved from https://dhsprogram.com/pubs/pdf/DHSG4/Recode7_DHS_10Sep2018_DHSG4.pdf

Impicciatore, R., & Tomatis, F. (2020). The nexus between education and fertility in six European countries. Genus.

Iyanda, A. E., Dinkins, B. J., Osayomi, T., Adeusi, T. J., Lu, Y., & Oppong, J. R. (2020). Fertility knowledge, contraceptive use and unintentional pregnancy in 29 African countries: a cross-sectional study. International Journal of Public Health, 65(4), 445–455. https://doi.org/10.1007/s00038-020-01356-9

Jalovaara, M., Neyer, G., Andersson, G., Dahlberg, J., Dommermuth, L., Fallesen, P., & Lappegård, T. (2019). Education, Gender, and Cohort Fertility in the Nordic Countries. European Journal of Population, 563–586.

Khattak, S. W. (2017). Determinants of Adolescent Fertility in Pakistan: Evidence from PDHS 2012-13. JHSS, 25(2), 95–108.

Luo, D., Yan, X., Xu, R., Zhang, J., Shi, X., Ma, J., … Sawyer, S. M. (2020). Chinese trends in adolescent marriage and fertility between 1990 and 2015: a systematic synthesis of national and subnational population data. The Lancet Global Health, 8(7), e954–e964. https://doi.org/10.1016/S2214-109X(20)30130-3

Maharani, V., Ramadhanty, A. P., Putra, G. M., Pratama, I. M., & Yuhan, R. J. (2020). Penentuan Faktor-Faktor yang Mempengaruhi Tingkat Fertilitas di Indonesia Tahun 2017 dengan Metode Multiple Classification Analysis (Analisis Data SDKI 2017). Business Economic, Communication, and Social Science (BECOSS) Journal, 2(3), 1–9.

Malakar, B., & Roy, S. K. (2017). Effect of socio-economic characteristics on fertility and under-five mortality: Examples from the Santals of Birbhum district, West Bengal, India. Anthropological Review, 80(3), 323–334. https://doi.org/10.1515/anre-2017-0023

Malinda, Y. (2012). Hubungan Umur Kawin Pertama Dan Penggunaan Kontrasepsi Dengan Fertilitas Remaja Berstatus Kawin (Analisis Riskesdas 2010). Jurnal Kesehatan Reproduksi, 3(2 Ags), 69–81. https://doi.org/10.22435/kespro.v3i2Ags.3921.69-81

Ndahindwa, V., Kamanzi, C., Semakula, M., Abalikumwe, F., Hedt-Gauthier, B., & Thomson, D. R. (2014). Determinants of fertility in Rwanda in the context of a fertility transition: a secondary analysis of the 2010 Demographic and Health Survey. Reproductive Health.

Pan, J.-N., & Yang, Y.-J. (2020). The impact of economic uncertainty on the decision of fertility: Evidence from Taiwan. The North American Journal of Economics and Finance, 54, 101090. https://doi.org/https://doi.org/10.1016/j.najef.2019.101090

Raharja, M. B. (2014). Fertilitas Remaja di Indonesia. Kesmas: National Public Health Journal, 9(1), 6–13. https://doi.org/10.21109/KESMAS.V9I1.449.G415

Rahman, A., & Syakur, R. M. (2018). Menelusur Determinan Tingkat Fertilitas. Jurnal Ecces, (57–77).

Rahman, M., & Kabir, M. (2014). Knowledge of Adolescents, 28(April 2005), 164–177.

Sahara, N., Idris, I., & Putri, D. Z. (2019). Faktor-Faktor yang Mempengaruhi Keputusan Wanita Menikah di Sumatera Barat. Jurnal Ecogen, 1(3), 640–647.

Sakshaug, J. W., & West, B. T. (2014). Important considerations when analyzing health survey data collected using a complex sample design. American Journal of Public Health, 104(1), 15–16. https://doi.org/10.2105/AJPH.2013.301515

Sari, N. (2017). Determinan Fertilitas melalui Pendekatan Total Fertility Rate (TFR) di Indonesia: Analisis Data Survei Demografi Kesehatan Indonesia (SDKI) Tahun 2007. Jurnal Dunia Kesmas Volume, 6(2), 55–62.

Sari, N. (2017). Determinan Fertilitas melalui Pendekatan Total Fertility Rate (TFR) di Indonesia: Analisis Data Survei Demografi Kesehatan Indonesia (SDKI) Tahun 2007. Jurnal Dunia Kesmas, 6(2), 55–62.

Skrzeczkowska, A., Heimrath, J., Surdyka, J., & Zalewski, J. (2015). Knowledge of Contraceptive Methods among Adolescents/Young Adults. Polish Journal of Public Health, 125(3), 144–148. https://doi.org/10.1515/pjph-2015-0042

United Nations. (2013). Adolescent Fertility since the International Conference on Population and Development (ICPD) in Cairo (United Nations Publication).

Yuniarti, S., & Setiowati, T. (2015). Analisis Faktor yang berhubungan dengan tingkat fertilitas pada Ibu Pasangan Usian Subur (PUS) di Wilayah Kerja Puskesmas Melong Asih Kota Cimahi. Prosiding IRONS: Industrial Research Workshop and National Seminar, 6.


 

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