In the first chapter I will investigate the practice of sex-selective abortion among immigrants living in Italy, exploiting administrative data on the universe of the Italian births registered from 1999 to 2019. I will computer sex ratios at birth by citizenship of the mother in order to highlight possible imbalances. The analysis allows me to quantify the implied number of missing women over a 20-year timeframe. I will then make use of logistic regression models to estimate the likelihood of registering the birth of a female rather than a male for different population groups, conditional to family size and adjusting for individual characteristics of the parents, time and area fixed effects. The second chapter, co-authored by Carlo Devillanova and Helen Banks, examines avoidable hospitalization (AH) rates as an indicator of poor access to primary care in Italy, where the universal healthcare system fails to assign general practitioners to un- documented immigrants. Using anonymized national hospital discharge records in 2019, undocumented immigrants will be conveniently identified through an administrative fi- nancing code. Potential effects of poor access to primary care will be measured by focusing on the incidence of AH, differentiated among chronic, acute and vaccine-preventable con- ditions, comparing Italian citizens, documented (foreign nationals with residence permits) and undocumented immigrants. Logistic regression models will be estimated controlling for individual and contextual confounders. Using the same data source as in Chapter II, in the third chapter I provide novel descriptive evidence on patients with FGM/C diagnosis in the universe of hospitalisations over a 15-year time frame (2005-2019). I also calculate the incidence of hospitalisation due to FGM/C-related diseases, divided into physical and obstetrical, for the most recent year (2019) comparing three different populations: natives, immigrants from countries where FGM/C is practiced, and other immigrants, while controlling for individual, time and contextual confounders.

Immigrants’ Differential Health and Demographic Outcomes: Evidence from Italian Administrative Data

ALLEGRI, CHIARA
2022

Abstract

In the first chapter I will investigate the practice of sex-selective abortion among immigrants living in Italy, exploiting administrative data on the universe of the Italian births registered from 1999 to 2019. I will computer sex ratios at birth by citizenship of the mother in order to highlight possible imbalances. The analysis allows me to quantify the implied number of missing women over a 20-year timeframe. I will then make use of logistic regression models to estimate the likelihood of registering the birth of a female rather than a male for different population groups, conditional to family size and adjusting for individual characteristics of the parents, time and area fixed effects. The second chapter, co-authored by Carlo Devillanova and Helen Banks, examines avoidable hospitalization (AH) rates as an indicator of poor access to primary care in Italy, where the universal healthcare system fails to assign general practitioners to un- documented immigrants. Using anonymized national hospital discharge records in 2019, undocumented immigrants will be conveniently identified through an administrative fi- nancing code. Potential effects of poor access to primary care will be measured by focusing on the incidence of AH, differentiated among chronic, acute and vaccine-preventable con- ditions, comparing Italian citizens, documented (foreign nationals with residence permits) and undocumented immigrants. Logistic regression models will be estimated controlling for individual and contextual confounders. Using the same data source as in Chapter II, in the third chapter I provide novel descriptive evidence on patients with FGM/C diagnosis in the universe of hospitalisations over a 15-year time frame (2005-2019). I also calculate the incidence of hospitalisation due to FGM/C-related diseases, divided into physical and obstetrical, for the most recent year (2019) comparing three different populations: natives, immigrants from countries where FGM/C is practiced, and other immigrants, while controlling for individual, time and contextual confounders.
21-giu-2022
Inglese
33
2020/2021
PUBLIC POLICY AND ADMINISTRATION
Settore SECS-S/05 - Statistica Sociale
DEVILLANOVA, CARLO
JEANNET, ANNE-MARIE
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Utilizza questo identificativo per citare o creare un link a questo documento: https://hdl.handle.net/11565/4058713
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