Comparative analysis of regression models in predicting Intimate partner violence: a gender specific analysis using NFHS-5 data

Authors

DOI:

https://doi.org/10.18203/2394-6040.ijcmph20263641

Keywords:

Determinants, Intimate partner violence, Gender characteristics, NFHS

Abstract

Background: Existing regression models for determining intimate partner violence (IPV) against women include characteristics of women and men individually but evidence lacking on couple characteristics and best fit models. We aimed to compare regression models in predicting IPV using characteristics of women and her partner separately and as a dyad.

Methods: We used couple data from National Family Health Survey-5 containing data from both women and her partner. IPV considered as positive response for any of the questions on domestic violence. Multiple logistic regression models were built separately for characteristics of women and men and couple characteristics. Best fit models identified through r-squared value and AIC and BIC statistics.

Results: We included 46445 couple data for final analysis. R-squared value for models including female characteristics were similar to models with couple characteristics and higher than the models with male characteristics. Odds Ratio were also higher for women characteristics compared to their counterparts’ characteristics. Family history of IPV among women, women’s attitude towards wife beating and controlling behavior of partner were associated with higher IPV.

Conclusions: Individual characteristics of women in a couple alone can be an effective determinant of IPV than the traditional view of power relations between men and women in household.

References

WHO. Violence against women. Available from: https://www.who.int/news-room/fact-sheets/detail/violence-against-women. Accessed on 9 February 2025.

UN Women- Headquarters. 2024. FAQs: Types of violence against women and girls. Available from: https://www.unwomen.org/en/articles/faqs/faqs-types-of-violence-against-women-and-girls. Accessed on 9 February 2025.

WHO. Global Database on the Prevalence of Violence Against Women. Available from: https://vaw-data.srhr.org/data?chart1%5Bviolence _type%5D=ipv&chart1%5Bregion%5D=South-East+Asia&chart1%5Bregion_class%5D=WHO&chart1%5Bage_group%5D=15_49&chart1%5Bviolence_time%5D=lifetime. Accessed on 9 February 2025.

United Nations: Gender equality and women’s empowerment. United Nations Sustainable Development. Available from: https://www.un.org/sustainabledevelopment/gender-equality/. Accessed on 9 February 2025.

Ministry of Women and Child Development. Measures to Check violence Against Women. Available from: https://pib.gov.in/newsite/ erelcontent.aspx?relid=35773. Accessed on 9 February 2025.

Mondal D, Paul P. Associations of power relations, wife-beating attitudes, and controlling behavior of husband with domestic violence against women in india: insights from the National Family Health Survey-4. Violence Against Women. 2021;27(14):2530-51.

Ramasubramani P, Krishnamoorthy Y, Vijayakumar K, Rushender R. Burden, trend and determinants of various forms of domestic violence among reproductive age-group women in India: findings from nationally representative surveys. J Public Health. 2024;46(1):e1-14.

Melkam M, Fente BM, Negussie YM, Asmare ZA, Asebe HA, Seifu BL, et al. Impact of partner alcohol use on intimate partner violence among reproductive-age women in East Africa Demographic and Health Survey: propensity score matching. BMC Public Health. 2024;24:2365.

Asmamaw DB, Negash WD, Bitew DA, Belachew TB. Multilevel analysis of intimate partner violence and associated factors among pregnant women in East Africa: evidence from recent (2012-2018) demographic and health surveys. Arch Public Health. 2023;81:67.

Tun T, Ostergren PO. Spousal violence against women and its association with sociodemographic factors and husbands’ controlling behaviour: the findings of Myanmar Demographic and Health Survey (2015-2016). Glob Health Act. 2020;13(1):1844975.

Garg P, Das M, Goyal LD, Verma M. Trends and correlates of intimate partner violence experienced by ever-married women of India: results from National Family Health Survey round III and IV. BMC Public Health. 2021;21(1):2012.

Kanougiya S, Sivakami M, Rai S. Predictors of spousal coercive control and its association with intimate partner violence evidence from National Family Health Survey-4 (2015-2016) India. BMC Public Health. 2021;21:2185.

Iman’ishimwe Mukamana J, Machakanja P, Adjei NK. Trends in prevalence and correlates of intimate partner violence against women in Zimbabwe, 2005-2015. BMC Int Health Hum Rights. 2020;20(1):2.

Wickham RJ. Secondary Analysis Research. J Adv Pract Oncol. 2019;10(4):395-400.

Rodrigues PM, Madeiro JP, Marques JAL. Enhancing health and public health through machine learning: decision support for smarter choices. Bioengineering. 2023;10(7):792.

Chen S, Yu J, Chamouni S, Wang Y, Li Y. Integrating machine learning and artificial intelligence in life-course epidemiology: pathways to innovative public health solutions. BMC Med. 2024;22(1):354.

National Family Health Survey (NFHS-5) 2019-21. Available from: https://www.thehinducentre.com/ the-arena/current-issues/69076238-NFHS-5_Phase-II_0.pdf. Accessed on 13 February 2025.

International Institute for Population Sciences (IIPS). Data Catalog. Available from: https://www.iipsdata.ac.in/datacatalog_detail/1. Accessed on 13 February 2025.

NFHS. Questionnaire. Available from: https://www.nfhsiips.in/nfhsuser/questioner.php. Accessed on 13 February 2025.

Bengesai AV, Khan HTA. Exploring the association between attitudes towards wife beating and intimate partner violence using a dyadic approach in three sub-Saharan African countries. BMJ Open. 2023;13(6):e062977.

Amir-ud-Din R, Idrees R, Farooqui J, Abbasi AS. Exploring spousal disparities: Age, earnings, and education as predictors of intimate partner violence in 29 developing countries. Women’s Health. 2024;20:17455057241310289.

Underwood CR, Casella A, Hendrickson ZM. Gender norms, contraceptive use, and intimate partner violence: A six-country analysis. Sex Reprod Healthcare. 2023;35:100815.

Melkam M, Fentahun S, Rtbey G, Andualem F, Nakie G, Tinsae T, et al. Multilevel analysis of intimate partner violence and associated factors among reproductive-age women: Kenya demographic and health survey 2022 data. BMC Public Health. 2024;24(1):1476.

Benebo FO, Schumann B, Vaezghasemi M. Intimate partner violence against women in Nigeria: a multilevel study investigating the effect of women’s status and community norms. BMC Women’s Health. 2018;18:136.

Solanke BL. Does exposure to interparental violence increase women’s risk of intimate partner violence? Evidence from Nigeria demographic and health survey. BMC Int Health Hum Rights. 2018;18:1.

Puno A, Kim R, Jeong J, Kim J, Kim R. Intergenerational transmission of intimate partner violence among women: evidence from the 2017 Philippines National Demographic and Health Survey. SSM Popul Health. 2023;23:101392.

Aboagye RG, Seidu AA, Asare BY, Peprah P, Addo IY, Ahinkorah BO. Exposure to interparental violence and justification of intimate partner violence among women in sexual unions in sub-Saharan Africa. Arch Public Health. 2021;79(1):162.

Aboagye RG, Okyere J, Seidu AA, Hagan JE, Ahinkorah BO. Experience of intimate partner violence among women in sexual unions: is supportive attitude of women towards intimate partner violence a correlate? Healthcare. 2021;9(5):563.

Antai D. Controlling behavior, power relations within intimate relationships and intimate partner physical and sexual violence against women in Nigeria. BMC Public Health. 2011;11:511.

Nishan MDNH, Ahmed MZEMNU, Mashreky SR, Dalal K. Influence of spousal educational disparities on intimate partner violence (IPV) against pregnant women: a study of 30 countries. Sci Rep. 2025;15:2022.

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Published

2026-09-30

How to Cite

Nachimuthu, N., R., U. M., & Vasudevan , D. (2026). Comparative analysis of regression models in predicting Intimate partner violence: a gender specific analysis using NFHS-5 data. International Journal Of Community Medicine And Public Health, 13(10), 6006–6015. https://doi.org/10.18203/2394-6040.ijcmph20263641

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Original Research Articles