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Table 1.

Variables included in the model.

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Table 1 Expand

Table 2.

Modelling strategy.

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Table 2 Expand

Table 3.

Descriptive analysis of the sample.

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Table 3 Expand

Table 4.

Sample composition and support for FGM/C according to citizenship at birth.

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Table 4 Expand

Table 5.

Multinomial probit choice models. Case-specific coefficients and robust standard errors from Model 1a and Model 2a for women who condition FGM/C continuation on medicalization vs women who support FGM/C unconditionally.

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Table 5 Expand

Table 6.

Multinomial probit choice models. Case-specific coefficients and robust standard errors from Model 1b and Model 2b for women who conditioning FGM/C continuation on medicalization vs women who support FGM/C unconditionally.

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Table 6 Expand

Fig 1.

Predicted probabilities of supporting the continuation of FGM/C by the highest level of education achieved (Model 1a).

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Fig 1 Expand

Fig 2.

Predicted probabilities of supporting the continuation of FGM/C by age at the time of the survey and the number of daughters ever born (Model 1a).

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Fig 2 Expand

Fig 3.

Predicted probabilities of supporting the continuation of FGM/C by the level of medicalization in the country of origin (Model 1a).

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Fig 3 Expand

Table 7.

Predicted probabilities of supporting FGM/C based on perceived benefits for cut girls (significant variables according to Model 1).

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Table 7 Expand