Physical, Sexual, and Intimate Partner Violence Among Transgender and Gender-Diverse Individuals.

Importance: Transgender and gender-diverse (TGD) communities experience disproportionate levels of violence, yet due to limitations in measuring TGD identity, few state-representative estimates are available. Objective: To assess gender identity differences in experiences of violence among adults. Design, Setting, and Participants: Cross-sectional data from the 2023 California Violence Experiences (CalVEX) survey, weighted to provide state-representative estimates, was used to assess associations between gender identity and past-year experiences of violence among adults 18 years and older. Data were analyzed from June to December 2023. Exposure: Gender identity (cisgender women, cisgender men, transgender women, transgender men, and nonbinary individuals). Main Outcomes and Measures: Experience of physical violence (including physical abuse and threat or use of a weapon), sexual violence (verbal sexual harassment, homophobic or transphobic slurs, cyber and physically aggressive sexual harassment, and forced sex), and intimate partner violence (IPV; emotional, physical, or sexual violence) using age-adjusted logistic regression. Results: In total 3560 individuals (weighted cumulative response rate, 5%) completed the 2023 CalVEX survey, with 1978 cisgender women, 1431 cisgender men, 35 transgender women, 52 transgender men, and 64 nonbinary respondents (mean [SD] age, 47.1 [17.5] years; 635 [17%] were Asian, 839 [37%] were Hispanic, and 1159 [37%] were White). Past-year physical violence was reported by 22 transgender men (43%), 9 transgender women (24%), and 9 nonbinary respondents (14%). Past-year sexual violence was reported by 23 transgender men (42%), 11 transgender women (14%), and 31 nonbinary respondents (56%). Compared with cisgender women, transgender women and transgender men had greater risk of past-year physical violence (any form) (transgender women adjusted incidence rate ratio [AIRR], 6.7; 95% CI, 2.5-18.2; transgender men AIRR, 9.7; 95% CI, 5.3-17.7), as well as past-year IPV (any form) (transgender women AIRR, 3.2; 95% CI, 1.3-8.0; transgender men AIRR, 6.7; 95% CI, 4.0-11.3). Relative to cisgender women, transgender men (AIRR, 3.0; 95% CI, 1.7-5.1) and nonbinary respondents (AIRR, 3.3; 95% CI, 2.1-5.2) had greater risk of past-year sexual violence (any form). Conclusions and Relevance: In this survey study of adults in California, results showed that TGD individuals, especially transgender men, are at higher risk of experiencing all forms of violence relative to cisgender women. Results highlight the need for gender-affirming violence prevention and intervention services as well as policies that protect TGD individuals from discriminatory violence.

Understanding feasibility and acceptability of implementation of linking delivery of family planning and infant vaccination care in rural Maharashtra, India: a qualitative study.

BACKGROUND: Linking family planning with infant vaccination care has the potential to increase contraceptive use among postpartum women in rural settings. We explored the multilevel factors that can facilitate or impede uptake of contraception at the time of infant vaccination among postpartum women and couples in rural Maharashtra, India. METHODS: We conducted 60 semi-structured interviews with key stakeholders including: postpartum married women (n = 20), husbands (n = 10), and mothers-in-law (n = 10) of postpartum women, frontline healthcare workers (auxiliary nurse midwives (ANMs) and Accredited Social Health Activists (ASHAs), (n = 10), and community leaders (physician medical officers and village panchayat leaders) (n = 10). We sought to assess the feasibility and acceptability of delivering community-based postpartum family planning care in rural India at the time of infant vaccination. The Consolidated Framework for Implementation Research (CFIR) was used to design a structured interview guide and codebook. Data were analyzed via directed content analysis. RESULTS: Three major themes emerged: (1) Social fertility and gender norms including son preference and male control over contraceptive decision-making influence postpartum contraceptive access and choice. (2) Linking contraceptive care and infant vaccination is perceived as potentially feasible and acceptable to implement by families, health workers, and community leaders. The intervention provides care to women and families in a convenient way where they are in their community. (3) Barriers and facilitators to linked infant postpartum contraception and infant vaccination were identified across the five CFIR domains. Key barriers included limited staff and space (inner setting), and contraceptive method targets for clinics and financial incentives for clinicians who provide specific methods (outer setting). Key facilitators included convenience of timing and location for families (intervention characteristics), the opportunity to engage husbands in decision-making when they attend infant vaccination visits (participant characteristics), and programmatic support from governmental and community leaders (process of implementation). CONCLUSIONS: Linked provision of family planning and infant vaccination care may be feasible and accessible in rural India utilizing strategies identified to reduce barriers and facilitate provision of care. A gender-transformative intervention that addresses gender and social norms has greater potential to impact reproductive autonomy and couples' contraceptive decision-making.

Using machine learning to understand determinants of IUD use in India: Analyses of the National Family Health Surveys (NFHS-4).

Intra-uterine devices (IUDs) are a safe and effective method to delay or space pregnancies and are available for free or at low cost in the Indian public health system; yet, IUD uptake in India remains low. Limited quantitative research using national data has explored factors that may affect IUD use. Machine Learning (ML) techniques allow us to explore determinants of low prevalence behaviors in survey research, such as IUD use. We applied ML to explore the determinants of IUD use in India among married women in the 4th National Family Health Survey (NFHS-4; N = 499,627), which collects data on demographic and health indicators among women of childbearing age. We conducted ML logistic regression (lasso and ridge) and neural network approaches to assess significant determinants and used iterative thematic analysis (ITA) to offer insight into related variable constructs generated from a series of regularized models. We found that couples' shared family planning (FP) goals were the strongest determinants of IUD use, followed by receipt of FP services and desire for no more children, higher wealth and education, and receipt of maternal and child health services. Findings highlight the importance of male engagement and family planning services for IUD uptake and the need for more targeted efforts to support awareness of IUD as an option for spacing, especially for those of lower SES and with lower access to care.