An Analysis of Fertility Differentials Among The Scheduled Tribes in ‎The Kokrajhar District of Assam, Based on Poisson Regression Tech‎nique

  • Authors

    • Sudem Brahma Department of Mathematical Sciences, Bodoland University, Kokrajhar, 783370, Assam, India
    • Dimacha Dwibrang Mwchahary Department of Mathematics, Kokrajhar University, Kokrajhar, 783370, Assam, India
    https://doi.org/10.14419/j7kvz934

    Received date: October 22, 2025

    Accepted date: November 17, 2025

    Published date: November 23, 2025

  • Fertility; Determinant; Scheduled Tribes; Children Ever Born; Poisson Regression

  • Abstract

    The study on the impact of different factors on fertility and determining the groups having higher and lower fertility remains a key interest ‎of policymakers. From such a study, demographers can gain insights into future trends regarding the proportions of different groups in a population. This study aims to investigate the socio-economic and demographic characteristics of children ever born among ‎Scheduled Tribe women in the Kokrajhar district of Assam. Using a stratified random sampling method, the villages within four medical blocks of the Kokrajhar district were chosen. Interviews were conducted with 960 women who had at least one child. In the bivariate ‎and multivariate analyses, one-way ANOVA and Poisson regression were employed. The study found a significant adverse correlation ‎between women’s education and the total number of children ever born. High fertility is linked with women’s age and the utilization of ‎modern contraceptive techniques. The mean number of children ever born in the study region is 1.57 children per woman. Maintaining the ‎fertility rate among the Scheduled Tribes of the study region requires greater focus on using media to highlight the advantages of small ‎families and family planning initiatives‎.

    List of abbreviations:‎

    • ‎Child ever born: CEB.
    • ‎Scheduled Tribes: ST.
    • ‎Scheduled Caste: SC.
    • ‎United Nations: UN.
    • ‎Total Fertility Rate: TFR.
    • ‎National Family Health Survey: NFHS.
    • ‎Incidence Rate Ratio: IRR.
    • ‎Negative binomial: NB.

  • References

    1. Anonymous. India overtakes China to become the world's most populous nation with 1.428 billion people: UN. The Economic Times. 2023 [Inter-net].
    2. Available:https://economictimes.indiatimes.com/news/india/india-population-to-surpass-china-mid-year-un-estimates/articleshow/99605379.cms [ac-cessed April 20, 2023].
    3. Teng Y, Margolis R, & Ramos H (2025), Trends in Indigenous fertility in Canada, 2001–2021. Demographic Research, 53, 175-186. https://doi.org/10.4054/DemRes.2025.53.6.
    4. Ranjan A, Studies in the population of Madhya Pradesh, 2004. Shyam Institute. (2004).
    5. Phukon MJ, & Sultana P (2024), Fertility Pattern and Reproductive Health of Harijan (Dalit) Community in Select Destinations of As-sam. Educational Administration: Theory and Practice, 30(6), 1248-1257.
    6. Mubarak M & Mahanta A (2014), Determinants of Rural Fertility: Evidence from Dibrugarh District of Assam. The International Journal of Hu-manities & Social Studies, 2(8),103–110.
    7. Mazumder MN & Mukherjee S (2018), Level and Differentials of Fertility among Karbis of Kamrup Metropolis, Assam. Studies of tribes and Trib-als, 16(1/2), 24-32. 11.258359/KRE-155 https://doi.org/10.31901/24566799.2018/16.1-2.412.
    8. Mahanta A (2016), Impact of education on fertility: Evidence from a tribal society in Assam, India. International Journal of Population Research, 2016(1), 3153685. https://doi.org/10.1155/2016/3153685.
    9. Nanda S (2005), Cultural Determinants of Human Fertility: A Study of Tribal Population in Orissa. Anthropologist, 7(3), 221-227. https://doi.org/10.1080/09720073.2005.11890912.
    10. Karri B, & Mathew GS. (2022). A comparative analysis of reproductive measures and predictor variables among three tribes of Bilaspur, Chhattis-garh, India. Cogent Social Sciences, 8(1). https://doi.org/10.1080/23311886.2022.2106649.
    11. Mutharayappa R (1994), Factors Affecting Fertility Among Tribals. Man & Development,16(4), 63-79.
    12. Nagdeve DA & Dongardive PB (2021), Fertility and Family Planning Differentials among Social Groups in India. Demography India, 50(1), 1-16.
    13. Maharatna A (2000), Tribal fertility in India: Socio-cultural influences on demographic behaviour. Economic and Political Weekly, 3037-3047. https://www.jstor.org/stable/4409653.
    14. Rarere M, Jarallah Y, & Kukutai T (2023). Indigenous fertility in Aotearoa New Zealand: How does ethnic identity affect birth spacing and tim-ing? Journal of Population Research, 40(4), 25. https://doi.org/10.1007/s12546-023-09321-y.
    15. Rarere M (2022). The importance of whakapapa for understanding fertility. Genealogy, 6(2), 26. https://doi.org/10.3390/genealogy6020026.
    16. Pautunthang N (2024). Fertility Preferences among Women in Meghalaya, India. International Journal of Indian Psychȯlogy, 12(2).
    17. Kshatriya GK, & Gautam RK (2020). Fertility profile of the Bhil tribe of Barmer district, Rajasthan. Genus, 4.
    18. Lepcha M (2022). Association of Socio-economic Factors with Fertility and Mortality among Lepchas of North Sikkim, India. Online Journal of Health and Allied Sciences, 21(1).
    19. Sa'roni C, & Arisanty D (2025). Women Factor Analysis Workers Who Affect Fertility Rates in the Banjar Tribe in Banjarmasin City, 2010-2024. JPG (Jurnal Pendidikan Geografi), 12(2). https://doi.org/10.20527/jpg.v12i2.22541.
    20. Hoffman JP. Generalized linear models: an applied approach. Boston: Pearson Education, Inc. (2004).
    21. Hilbe JM. Negative binomial regression. Cambridge University Press. (2011). https://doi.org/10.1017/CBO9780511973420.
    22. McCullagh P, & Nelder JA. Generalized linear models (2nd ed.). London, United Kingdom: Chapman & Hall. (1989). https://doi.org/10.1007/978-1-4899-3242-6.
    23. Berlie AB & Alamerew YT (2018), Determinants of fertility rate among reproductive age women (15-49) in Gonji-Kollela District of the Amhara National Regional State, Ethiopia. Ethiopian Journal of Health Development, 32(3).
    24. Chauhan BG & Nagarajan R (2023), Trend and determinants of fertility in a declining fertility regime: A study of rural Uttar Pradesh, Community Health Equity Research & Policy, 43(2), 143-152. https://doi.org/10.1177/0272684X211004947.
    25. Kamnuansilpa P & Chamratrithirong A (1986), Contraceptive use and fertility in Thailand: results from the 1984 contraceptive prevalence survey. Studies in Family Planning, 17, 255. https://doi.org/10.2307/1966991.
    26. Murigi MN (2016), Socioeconomic and Demographic Determinants of Fertility in North Eastern Kenya. Ph.D. dissertation. University of Nairobi. http://hdl.handle.net/11295/98794 .
    27. Nibaruta JC, Elkhoudri N, Chahboune M, Chebabe M, Elmadani S, Baali A, & Amor H (2021), Determinants of fertility differentials in Burundi: evidence from the 2016-17 Burundi demographic and health survey. Pan African Medical Journal, 38 (1). https://doi.org/10.11604/pamj.2021.38.316.27649.
    28. Kim J (2023), Female education and its impact on fertility. IZA World of Labor.
    29. Weinberger MB (1987), The relationship between women's education and fertility: selected findings from the World Fertility Surveys. International Family Planning Perspectives, 35-46. https://doi.org/10.2307/2947826.
    30. Sharma MJD, & Aggarwal MPK (2022), Determinants of Fertility Differentials in Jammu and Kashmir. International Journal of Humanities Social Science and Management (IJHSSM), 2(5), 505-508.
    31. Ekawati R, Rahayuwati L, Nurhidayah I, Agustina HS, & Rahayu E (2019), Determinant Factors of Fertility in Reproductive Age Women. Jurnal Keperawatan Padjadjaran, 7(3), 283-293. http://localhost:8080/xmlui/handle/123456789/435. https://doi.org/10.24198/jkp.v7i3.1274.
    32. Adhikari R (2010), Demographic, socio-economic, and cultural factors affecting fertility differentials in Nepal. BMC pregnancy and childbirth., 10, 1-11. https://doi.org/10.1186/1471-2393-10-19.
    33. Karki YB (1982), Fertility and the value of children: A study of rural and urban populations in Nepal. PhD Dissertation. London school of econom-ics. London.
    34. Nahar MZ, & Zahangir MS (2019), Determinants of fertility in Bangladesh: Evidence from the 2014 demographic and health survey. International quarterly of community health education, 40(1), 29-38. https://doi.org/10.1177/0272684X19857426.
    35. Ariho P & Nzabona A (2019), Determinants of change in fertility among women in rural areas of Uganda. Journal of pregnancy, 2019(1), 6429171. https://doi.org/10.1155/2019/6429171.
    36. Mudi PK & Pradhan MR (2023), Attitude and determinants of contraceptive use among the Juang tribe: A cross-sectional study in Odisha, In-dia. Clinical Epidemiology and Global Health, 24, 101448. https://doi.org/10.1016/j.cegh.2023.101448.
    37. Ahirwar RK, Kumar S, Gupta S, Niranjan A, Prajapati K, & Rawal S (2021), A study to assess the socio-demographic factor and knowledge, atti-tude, and practice of family planning methods in Lohpeeta migrants tribe located in Shivpuri central India. Journal of Family Medicine and Primary Care, 10 (3), 1308-1312.. https://doi.org/10.4103/jfmpc.jfmpc_2075_20.
    38. Mukherjee A, Banerjee N, Naskar S, Roy S, Das DK, & Mandal S (2021), Contraceptive behavior and unmet need among the tribal married women aged 15–49 years: a cross-sectional study in a community development block of paschim Bardhaman District, West Bengal. Indian journal of public health, 65(2), 159-165. https://doi.org/10.4103/ijph.IJPH_115_21.
    39. Prusty RK (2014), Use of contraceptives and unmet need for family planning among tribal women in India and selected hilly states. Journal of health, population, and nutrition, 32(2), 342.
    40. Bhandari KR, Ghimire K, Upadhyay HP, Pachhai DB, & Karki S (2023). Children Ever Born and its Associated Factors of Women in Tansen Mu-nicipality of Palpa District Nepal. International Journal of Silkroad Institute of Research and Training, 1(2), 84-90. https://doi.org/10.3126/ijsirt.v1i2.61665.
    41. Monari N, Orwa J, Agwanda A (2022) Adolescent fertility and its determinants in Kenya: Evidence from Kenya demographic and health survey 2014. PLOS ONE. 17. e0262016.. https://doi.org/10.1371/journal.pone.0262016.

  • Downloads

  • How to Cite

    Brahma, S., & Mwchahary, D. D. . (2025). An Analysis of Fertility Differentials Among The Scheduled Tribes in ‎The Kokrajhar District of Assam, Based on Poisson Regression Tech‎nique. International Journal of Basic and Applied Sciences, 14(7), 527-534. https://doi.org/10.14419/j7kvz934