Developing and Validating an Individual-Level Deprivation Index for Children's Health in France

Remi Laporte1,2,3, Philippe Babe4,5, Elisabeth Jouve6

  • 1Permanence d'Accès aux Soins de Santé Mère-Enfant, Hôpital Nord, Assistance Publique-Hôpitaux de Marseille, 13005 Marseille, France.

Insights

The French Individual Child Deprivation Index (FrenChILD-Index) effectively identifies children facing moderate and severe deprivation. This validated tool aids healthcare providers in addressing health inequalities and improving care access for vulnerable pediatric populations.

Area of Science:

  • Pediatric Health
  • Social Determinants of Health
  • Health Equity

Background:

  • Socioeconomic deprivation significantly contributes to health disparities in children.
  • Addressing these inequalities requires tools to identify and quantify deprivation for targeted interventions.
  • Current clinical practice and public health initiatives need better methods to assess child deprivation.

Purpose of the Study:

  • To develop and validate a pediatric index for measuring individual-level deprivation.
  • To create a tool applicable in both clinical settings and public health strategies.
  • To enhance appropriate access to care for deprived children.

Main Methods:

  • The French Individual Child Deprivation Index (FrenChILD-Index) was developed through item generation, reduction, derivation, and validation phases.
  • A cross-sectional study involving 986 children in two emergency departments was conducted for index derivation and validation.
  • Expert evaluation and blinded assessments were used to establish thresholds for moderate and severe deprivation levels.

Main Results:

  • The final 12-item FrenChILD-Index demonstrated high sensitivity for identifying moderate (96.0%) and severe (96.3%) deprivation.
  • Specificities for moderate and severe deprivation were 68.3% and 91.1%, respectively.
  • The index successfully differentiated between levels of deprivation requiring different care intensities.

Conclusions:

  • The FrenChILD-Index is the first validated pediatric individual-level deprivation index in Europe.
  • This tool empowers clinicians to address social determinants of health directly within patient care.
  • Implementation of the FrenChILD-Index supports public health goals for reducing child health inequalities.
Abstract

Related Concept Videos

Levels of Health Promotion and Illness Prevention01:26

Levels of Health Promotion and Illness Prevention

Health promotion allows a person to control the determinants of health, resulting in an improved health status. It enhances the quality of life and reduces premature deaths. Health promotion and illness prevention programs help people make beneficial choices to reduce the risk of disease and disabilities. There are three health promotion and illness prevention levels: primary, secondary, and tertiary prevention.
In primary prevention, actions taken before disease onset prevent the disease from...
12.9K
Statistical Methods for Analyzing Epidemiological Data01:25

Statistical Methods for Analyzing Epidemiological Data

Epidemiological data primarily involves information on specific populations' occurrence, distribution, and determinants of health and diseases. This data is crucial for understanding disease patterns and impacts, aiding public health decision-making and disease prevention strategies. The analysis of epidemiological data employs various statistical methods to interpret health-related data effectively. Here are some commonly used methods:
474
Dimensions of Health and Illness01:21

Dimensions of Health and Illness

The factors influencing the health-illness continuum can be internal or external and may or may not be under conscious control. They are related to the following eight human dimensions, and each dimension is interrelated to one other.
7.6K
Bias in Epidemiological Studies01:29

Bias in Epidemiological Studies

Biases can arise at various stages of research, from study design and data collection to analysis and interpretation. Recognizing and addressing these biases is essential to ensure the validity and reliability of epidemiological findings.Broadly speaking, biases in epidemiology fall into three main categories: selection bias, information bias, and confounding. A more detailed description of possible biases is:  
489
Factors Affecting Illness01:18

Factors Affecting Illness

When a person's physical, emotional, intellectual, social development or spiritual functioning is compromised, this deviation from a healthy normal state is called illness. Illness creates stress that in turn harms individuals. Irritation, anger, denial, hopelessness, and fear are behavioral and emotional changes an individual experiences in the phases of illness. A variety of factors influence a person's health and well-being.
For instance, risk factors are connected to illness,...
4.3K
Study Designs in Epidemiology01:20

Study Designs in Epidemiology

Epidemiological study designs are fundamental tools for investigating the distribution, determinants, and control of health conditions in populations. They help researchers understand the relationships between exposures and outcomes, and they broadly fall into two categories: "observational" and "experimental" studies.
Observational studies are those where the researcher does not intervene but rather observes natural variations. They include cross-sectional, cohort, and...
338