Sean Callaghan

Previous estimates of the number of women and girls impacted by female genital mutilation and cutting (FGM/C) in the United States (US) failed to account for the impact of migration and acculturation. Similar studies in Europe applied a standard factor to estimate the impact across the entire immigrant population. Several of the resultant European estimates offered two scenarios: no impact, in which prevalence remained unaffected by migration and acculturation, and partial impact, in which risk was assumed to drop by 50% for native-born children. Each of these previous studies was based on adaptations of the extrapolation method, which produces estimates based on the product of three input variables: the immigrant population in the country of residence, the prevalence in the country of origin, and the mitigating impact of migration and acculturation. This paper offers several methodological innovations to better estimate the impact of migration and applies the results to the US. It develops methods to account for selective migration, the mitigating impact of legislation and law enforcement, and it considers the age of migration and the age of cutting to estimate the impact of migration timing on the likelihood that individuals were cut prior to migration. Using these innovations to model the impact of migration on the population in the US suggested that previous studies had underestimated the number of women living with FGM/C, while overestimating the number of girls who were at risk.

These two R scripts provide the computational framework to calculate and validate an Acculturation Index for demographic research, as utilised in the study available at DOI: 10.13140/RG.2.2.27869.58083. They utilise survey-weighted generalised linear models to process census data and output demographic diagnostic metrics.

This protocol describes a computational pipeline to fit a Generalised Gamma (Stacy) distribution using three known quartiles (Q1, Median, and Q3). It is designed for demographic or epidemiological datasets (such as age-at-event data) where individual-level data may be missing, but summary quartiles are available. The protocol estimates shape, scale, and threshold parameters, calculates cumulative probabilities at specific age thresholds (5, 10, 15, and 18 years), and exports publication-quality PDF plots of both Probability Density Functions (PDF) and Cumulative Distribution Functions (CDF) for multiple sample cohorts or countries.

This protocol describes a computational pipeline to fit a Generalised Gamma (Stacy) distribution using three known quartiles (Q1, Median, and Q3). It is designed for demographic or epidemiological datasets (such as age-at-event data) where individual-level data may be missing, but summary quartiles are available. The protocol estimates shape, scale, and threshold parameters, calculates cumulative probabilities at specific age thresholds (5, 10, 15, and 18 years), and exports publication-quality PDF plots of both Probability Density Functions (PDF) and Cumulative Distribution Functions (CDF) for multiple sample cohorts or countries.

Previous estimates of the number of women and girls impacted by female genital mutilation and cutting (FGM/C) in the United States (US) failed to account for the impact of migration and acculturation. Similar studies in Europe applied a standard factor to estimate the impact across the entire immigrant population. The resultant European estimates offered two scenarios no impact, in which prevalence remained unaffected by migration and acculturation, and partial impact, in which risk was assumed to drop by 50% for native-born children. Each of these previous studies was based on Yoder and van Baelen’s extrapolation method, which produces estimates based on the product of three input variables: the immigrant population in the country of residence, the prevalence in the country of origin, and the mitigating impact of migration and acculturation. This paper offers several methodological innovations to better estimate the impact of migration and applies the results to the US. It develops methods to account for selective migration, the mitigating impact of legislation and law enforcement, and it considers the age of migration and the age of cutting to estimate the impact of migration timing on the likelihood that individuals were cut prior to migration. Using these innovations to model the impact of migration on the population in the US suggested that previous studies had underestimated the number of women living with FGM/C, while overestimating the number of girls who were at risk.

Female genital mutilation/cutting (FGM/C) encompasses medically unnecessary procedures involving the partial or total removal of external genitalia. FGM/C causes lasting physical and psychological harm. While most prevalent in parts of Africa, FGM/C has been increasingly documented in Western countries due to global migration. Despite this, national epidemiological data on FGM/C in the United States (US) are not available. We estimated inpatient FGM/C diagnoses using national hospitalization data. Between 2016 and 2022, 8,680 hospitalizations included an FGM/C diagnosis, averaging 3.16 per 10,000 pregnancy-related hospitalizations. Among the 8,680 hospitalizations identified with FGM/C, unspecified types accounted for 55.3% of admissions, followed by Type III (infibulation, 17.0%) and Type II (excision, 14.5%). Across FGM/C subtypes, rates were highest for patients aged 20-39 (90.3%) and among Black females (72.7%). FGM/C diagnoses appear in US health encounters, yet gaps in clinical recognition and documentation underscore the urgent need for improved surveillance, reporting, and culturally informed care.

This paper proposes a refined method for calculating age-specific prevalence rates of Female Genital Mutilation/Cutting (FGM/C) to enhance the accuracy of estimates calculated using Yoder and Van Baelen’s Extrapolation-of-FGM/C-Countries-Prevalence-Data method. Previous studies, particularly in the United States, have faced limitations, including the failure to disaggregate prevalence data by age and overlooking historical trends. To address these limitations, this study outlines a comprehensive seven-step approach. Using Ethiopia as a case study, prevalence rates were calculated and aligned with target migrant population data. This involved adjusting age cohorts, extrapolating prevalence to younger age groups, and considering historical trends. Results demonstrate significant differences compared to previous estimates, indicating overestimation of girls at risk of FGM/C in some studies. The proposed method offers a standardized approach applicable beyond the United States, potentially improving estimates globally. By providing nuanced prevalence data, this method contributes to better understanding the true prevalence of FGM/C in migrant populations. This same method can also be used to predict future trends in FGM/C and other practices.

This paper proposes a refined method for calculating age-specific prevalence rates of Female Genital Mutilation/Cutting (FGM/C) to enhance the accuracy of estimates calculated using Yoder and Van Baelen's Extrapolation-of-FGM/C-Countries-Prevalence-Data method. Previous studies, particularly in the United States, have faced limitations, including the failure to disaggregate prevalence data by age and overlooking historical trends.To address these limitations, this study outlines a comprehensive seven-step approach. Using Ethiopia as a case study, prevalence rates were calculated and aligned with target migrant population data. This involved adjusting age cohorts, extrapolating prevalence to younger age groups, and considering historical trends. Results demonstrate significant differences compared to previous estimates, indicating overestimation of girls at risk and underestimation of women living with FGM/C in some studies.Furthermore, the proposed method offers a standardized approach applicable beyond the United States, potentially improving estimates globally. By providing nuanced prevalence data, this method contributes to better understanding the true prevalence of FGM/C in migrant populations.

The national prevalence of female genital mutilation/cutting (‘FGM/C’) in Kenya reduced from 37.6% of women aged 15–49 in 1998 to 14.8% in 2022. Despite this progress, concerns remain about medicalisation of the practice, changes in the type of cutting and cross-border FGM/C. There is evidence of a trend towards hiding FGM/C by medicalising it, and families in urban areas with higher levels of education are opting for cutting by medical professionals. The prevalence of FGM/C in which some flesh is taken has reduced more noticeably than the prevalence of the most severe type (infibulation). Cross-border FGM/C is a concern, particularly migrants moving into and out of Kenya to be cut. Ethnicity and social identity are the primary drivers, and this has created geographic hotspots where prevalence is well above the national average (between 57% and 87%). To address these concerns, programming must consider ethnic and religious drivers and engage with medical professionals to reduce the likelihood of medicalised FGM/C. In addition, estalibishing a regional coordinating body to address cross-border FGM/C is critical.