Abstract

Objective

Describe the risk of poverty and social exclusion in children aged 8-11 years from Gipuzkoa and Valencia (Spain), through AROPE (At Risk of Poverty or Social Exclusion) indicators, and evaluate their associated factors in the INMA Project (Childhood and Environment).

Method

Families in Gipuzkoa and Valencia (394 and 382, respectively) completed a questionnaire in 2015-2016. Low work intensity (LWI), at risk of poverty (RP) and material deprivation (MD) were estimated. AROPE consisted in meeting any of the previous sub-indicators. Socio-demographic, family and parental characteristics were considered. Frequencies, Venn's diagrams, and chi-square and Fisher tests were used in bivariate analysis and logistic regression in multivariate analysis.

Results

For LWI, RP, MD and AROPE, prevalence of 2.5%, 5.6%, 2.3% and 7.2% were obtained in Gipuzkoa, and 8.1%, 31.5%, 7.8% and 34.7% in Valencia, respectively. In the multivariate analysis, the AROPE was associated in both areas with maternal social class and non-nuclear families. In Gipuzkoa, it was also related to maternal education. In Valencia, other factors were the mother's foreign origin, and paternal education and smoking.

Conclusion

There is higher AROPE prevalence in Valencia. Social class and family type were shared factors, but a differential pattern is observed in other social determinants. It is essential to implement social policies to reduce this axis of inequalities in health, especially in childhood.

Keywords:
Poverty; Low work intensity; AROPE; Inequalities; Material deprivation; Children

Resumen

Objetivo

Describir el riesgo de pobreza y exclusión social en niños/as de 8-11 años de Gipuzkoa y Valencia (España), mediante los indicadores AROPE (At Risk Of Poverty or Social Exclusion), y evaluar sus factores asociados en el Proyecto INMA (Infancia y Medio Ambiente).

Método

Familias de Gipuzkoa y Valencia (394 y 382, respectivamente) completaron un cuestionario en 2015-2016. Se estimaron la baja intensidad de trabajo (BIT), el riesgo de pobreza (RP) y la privación material (PM). AROPE consistió en cumplir cualquiera de estos subindicadores. Se consideraron características sociodemográficas, familiares y parentales. Se usaron diagramas de Venn, los test de Ji-cuadrado y Fisher en los análisis bivariados, y regresión logística en los análisis multivariados.

Resultados

Se obtuvieron prevalencias para BIT, RP, PM y AROPE del 2,5%, 5,6%, 2,3% y 7,2% en Gipuzkoa, y del 8,1%, 31,5%, 7,8% y 34,7% en Valencia, respectivamente. En el análisis multivariado, el AROPE se asoció en ambas áreas con la clase social materna y la familia no nuclear. En Gipuzkoa, también se relacionó con la educación materna. En Valencia, otros factores fueron el origen extranjero materno y la educación y el tabaquismo paternos.

Conclusión

Hay un AROPE más alto en Valencia. La clase social y el tipo de familia fueron factores compartidos, pero se observa un patrón diferencial en otros determinantes sociales. Es esencial implementar políticas sociales para reducir este eje de desigualdad en salud, especialmente en la infancia.

Palabras clave:
Pobreza; Baja intensidad de empleo; AROPE; Desigualdades; Privación material; Infancia

Introduction

The Great Recession¹1. Karanikolos M, Heino P, McKee M, et al. Effects of the global financial crisis on health in high-income o ecd countries: a narrative review. Int J Health Serv.2016;46:208-40. has spurred poverty and social exclusion.²2. Luque OG, Martínez UF, Lechuga ML. Objetivo Europa 2020. La reducción de la pobreza y la exclusión social en España. Pap Rev Sociol. 2016;101:503-26. Poverty is defined as not having enough resources to live with dignity.³3. European Comission. 1. Informe conjunto sobre la inclusión social en el que seres umen los resultados del examen de los planes nacionales de acción a favor de la inclusión social. Report No.: COM(2003)773 final. Brussels: Asociación estatal de directores y gerentes en servicios sociales; 2003. Social exclusion refers to citizens that are not allowed to play a role in society because of their characteristics.³3. European Comission. 1. Informe conjunto sobre la inclusión social en el que seres umen los resultados del examen de los planes nacionales de acción a favor de la inclusión social. Report No.: COM(2003)773 final. Brussels: Asociación estatal de directores y gerentes en servicios sociales; 2003. This exclusion acts through different paths: by impeding access to higher education, employment opportunities and a regular income, by obstructing the way to governance³3. European Comission. 1. Informe conjunto sobre la inclusión social en el que seres umen los resultados del examen de los planes nacionales de acción a favor de la inclusión social. Report No.: COM(2003)773 final. Brussels: Asociación estatal de directores y gerentes en servicios sociales; 2003., and fostering learned helplessness.⁴4. Evans GW. Childhood poverty and adult psychological well-being. PNAS.2016;113:14949-52.

The economic strategy of European Union (EU) “Europe 2020” proposed reducing in 20 million the European population suffering poverty,⁵5. European Comission. Europa 2020. Una estrategia para un crecimiento inteligente, sostenible e integrador. Report No.: COM(2010)2020 final. Brussels: European Comission; 2010. as measured by the At Risk Of Poverty or Social Exclusion (AROPE).²2. Luque OG, Martínez UF, Lechuga ML. Objetivo Europa 2020. La reducción de la pobreza y la exclusión social en España. Pap Rev Sociol. 2016;101:503-26.^,66. Eurostat. People at risk of poverty or social exclusion - Statistics Explained. 2018. (Accessed 09/26/2018.) Available at: https://ec.europa.eu/eurostat/statistics-explained/index.php/People at risk of poverty or social exclusion .
https://ec.europa.eu/eurostat/statistics...

7. Faura-Martínez U, Lafuente-Lechuga M, García-Luque O. Riesgo de pobreza o exclusión social: evolución durante la crisis y perspectiva territorial/ Risk of Poverty or Social Exclusion: Evolution during the Economic Crisis and Territorial Perspective. REIS. 2016;156:59-76.

8. Llano Ortiz, JCL. El estado de la pobreza. Seguimiento del indicador de riesgo de pobreza y exclusión social en España 2008-2017. European Anti-Poverty Network, (2018), pp. 110

9. J.C.L. Llano Ortiz. El estado de la pobreza. Seguimiento del indicador de riesgo de pobreza y exclusión social en España 2009-2016. European Anti-Poverty Network, (2017), pp. 116^-1010. I.H. Aguayo, E.D. Herráiz, E.M. Marques, et al. Child at risk of poverty or social exclusion: comparative view between Spain and Portugal in the European context. Social Indicators Research., 129 (2016), pp. 961-978 This indicator describes poverty (based on income),¹¹11. S. Beil, J.P. Kolb, R. Münnich. Policy use of Laeken indicators. In: Proceedings of the New Techniques and Technologies for Statistics 2011. Brussels, Belgium, (2011). employment problems (based on work intensity), and material deprivation (lacking some items).⁶6. Eurostat. People at risk of poverty or social exclusion - Statistics Explained. 2018. (Accessed 09/26/2018.) Available at: https://ec.europa.eu/eurostat/statistics-explained/index.php/People at risk of poverty or social exclusion .
https://ec.europa.eu/eurostat/statistics...

In comparison to 2009 (when “Europe 2020” was introduced), by 2015 several countries had reduced AROPE; other had not met their objectives, and three (Greece, Cyprus, and Spain) showed increasing trends.⁶6. Eurostat. People at risk of poverty or social exclusion - Statistics Explained. 2018. (Accessed 09/26/2018.) Available at: https://ec.europa.eu/eurostat/statistics-explained/index.php/People at risk of poverty or social exclusion .
https://ec.europa.eu/eurostat/statistics... In Spain, 22.3% of the population are at risk of poverty, 14.9% have low work intensity, 5.8% have severe material deprivation, and 29.7% are AROPE.⁸8. Llano Ortiz, JCL. El estado de la pobreza. Seguimiento del indicador de riesgo de pobreza y exclusión social en España 2008-2017. European Anti-Poverty Network, (2018), pp. 110 This indicator is not homogeneous throughout Spain, as it reached in 2016 a range of 14-40% depending on the region considered.⁹9. J.C.L. Llano Ortiz. El estado de la pobreza. Seguimiento del indicador de riesgo de pobreza y exclusión social en España 2009-2016. European Anti-Poverty Network, (2017), pp. 116

This issue is important in general population, but a more vulnerable group such as children has even higher rates of poverty: 32.9% of children are in AROPE households, 29.7% are below the poverty threshold, and 7.1% suffers from severe material deprivation.⁸8. Llano Ortiz, JCL. El estado de la pobreza. Seguimiento del indicador de riesgo de pobreza y exclusión social en España 2008-2017. European Anti-Poverty Network, (2018), pp. 110 Childhood and adolescence are periods of evolution,¹²12. M. Flores, P. García-Gómez, M-V. Zunzunegui. Crisis económica, pobreza e infancia. ¿Qué podemos esperar en el corto y largo plazo para los “niños y niñas de la crisis”?. Informe SESPAS 2014. Gac Sanit. , 28 (2014), pp. 132-136 and influences received by then may have short and long term implications. Firstly, this exposure could increase the risk for health problems such as growth retardation, asthma, or injuries.¹³13. L. Rajmil, M.J.Fernández de Sanmamed, I. Choonara, et al. Impact of the 2008 economic and financial crisis on child health: a systematic review. Int J Environ Res Public Health., 11 (2014), pp. 6528-6546^,1414. L. Rajmil , A. Siddiqi, D. Taylor-Robinson, et al. Understanding the impact of the economic crisis on child health: the case of Spain. Int J Equity Health., 14 (2015), pp. 95-104 Secondly, poverty influences mental wellbeing, by having less copying strategies and expectations,¹⁵15. P. Attree. The social costs of child poverty: a systematic review of the qualitative evidence. Children & Society., 20 (2006), pp. 54-66 presenting more cognitive deterioration, and depression.¹²12. M. Flores, P. García-Gómez, M-V. Zunzunegui. Crisis económica, pobreza e infancia. ¿Qué podemos esperar en el corto y largo plazo para los “niños y niñas de la crisis”?. Informe SESPAS 2014. Gac Sanit. , 28 (2014), pp. 132-136 And thirdly, poverty determines health habits such as having a healthy diet or the abuse of substances.¹³13. L. Rajmil, M.J.Fernández de Sanmamed, I. Choonara, et al. Impact of the 2008 economic and financial crisis on child health: a systematic review. Int J Environ Res Public Health., 11 (2014), pp. 6528-6546

Child poverty is often determined by family characteristics: having low educated,⁶6. Eurostat. People at risk of poverty or social exclusion - Statistics Explained. 2018. (Accessed 09/26/2018.) Available at: https://ec.europa.eu/eurostat/statistics-explained/index.php/People at risk of poverty or social exclusion .
https://ec.europa.eu/eurostat/statistics... ^,1616. E. Šoltés; T. Šoltésová. Occurrence of low work intensity in Slovakia in relation to assessment of poverty and social exclusion. 2015. In: The 10th Professor Aleksander Zelias International Conference on Modelling and Forecasting of Socio-Economic Phenomena. Zakopane, Poland, (2015) , young,¹⁶16. E. Šoltés; T. Šoltésová. Occurrence of low work intensity in Slovakia in relation to assessment of poverty and social exclusion. 2015. In: The 10th Professor Aleksander Zelias International Conference on Modelling and Forecasting of Socio-Economic Phenomena. Zakopane, Poland, (2015) ,^,1717. A. Iwacewicz-Orlowska. Diversity of poverty in the chosen European Union countries within the period 2006-2014. Zbornik Radova Ekonomskog Fakulteta u Rijeci: Casopis za Ekonomsku Teoriju i Praksu / Proceedings of Rijeka School of Economics. J Econ Bus., 34 (2016), pp. 481-503 unemployed⁶6. Eurostat. People at risk of poverty or social exclusion - Statistics Explained. 2018. (Accessed 09/26/2018.) Available at: https://ec.europa.eu/eurostat/statistics-explained/index.php/People at risk of poverty or social exclusion .
https://ec.europa.eu/eurostat/statistics... ^,1717. A. Iwacewicz-Orlowska. Diversity of poverty in the chosen European Union countries within the period 2006-2014. Zbornik Radova Ekonomskog Fakulteta u Rijeci: Casopis za Ekonomsku Teoriju i Praksu / Proceedings of Rijeka School of Economics. J Econ Bus., 34 (2016), pp. 481-503 or immigrant⁶6. Eurostat. People at risk of poverty or social exclusion - Statistics Explained. 2018. (Accessed 09/26/2018.) Available at: https://ec.europa.eu/eurostat/statistics-explained/index.php/People at risk of poverty or social exclusion .
https://ec.europa.eu/eurostat/statistics... parents increased the risk of poverty, as well as living in a rural area⁶6. Eurostat. People at risk of poverty or social exclusion - Statistics Explained. 2018. (Accessed 09/26/2018.) Available at: https://ec.europa.eu/eurostat/statistics-explained/index.php/People at risk of poverty or social exclusion .
https://ec.europa.eu/eurostat/statistics... ^,1616. E. Šoltés; T. Šoltésová. Occurrence of low work intensity in Slovakia in relation to assessment of poverty and social exclusion. 2015. In: The 10th Professor Aleksander Zelias International Conference on Modelling and Forecasting of Socio-Economic Phenomena. Zakopane, Poland, (2015) ,^,1717. A. Iwacewicz-Orlowska. Diversity of poverty in the chosen European Union countries within the period 2006-2014. Zbornik Radova Ekonomskog Fakulteta u Rijeci: Casopis za Ekonomsku Teoriju i Praksu / Proceedings of Rijeka School of Economics. J Econ Bus., 34 (2016), pp. 481-503 or in a single-parent family.⁶6. Eurostat. People at risk of poverty or social exclusion - Statistics Explained. 2018. (Accessed 09/26/2018.) Available at: https://ec.europa.eu/eurostat/statistics-explained/index.php/People at risk of poverty or social exclusion .
https://ec.europa.eu/eurostat/statistics... ^,1616. E. Šoltés; T. Šoltésová. Occurrence of low work intensity in Slovakia in relation to assessment of poverty and social exclusion. 2015. In: The 10th Professor Aleksander Zelias International Conference on Modelling and Forecasting of Socio-Economic Phenomena. Zakopane, Poland, (2015) , Parental education appears to be a strong determinant that crosses from one generation to the next: ⁶6. Eurostat. People at risk of poverty or social exclusion - Statistics Explained. 2018. (Accessed 09/26/2018.) Available at: https://ec.europa.eu/eurostat/statistics-explained/index.php/People at risk of poverty or social exclusion .
https://ec.europa.eu/eurostat/statistics... in 2015, at least 65.5% of European children of low educated parents were at risk of poverty or social exclusion.⁶6. Eurostat. People at risk of poverty or social exclusion - Statistics Explained. 2018. (Accessed 09/26/2018.) Available at: https://ec.europa.eu/eurostat/statistics-explained/index.php/People at risk of poverty or social exclusion .
https://ec.europa.eu/eurostat/statistics...

An approach where both parents may play a role will be necessary to understand the differential effect of maternal a paternal education, social class, or unemployment⁶6. Eurostat. People at risk of poverty or social exclusion - Statistics Explained. 2018. (Accessed 09/26/2018.) Available at: https://ec.europa.eu/eurostat/statistics-explained/index.php/People at risk of poverty or social exclusion .
https://ec.europa.eu/eurostat/statistics... on child poverty. We already reported in the INMA Project¹⁸18. M. Guxens, F. Ballester, M. Espada, et al. Cohort profile: the INMA -INfancia y Medio Ambiente- (Environment and Childhood) Project. Int J Epidemiol., 41 (2012), pp. 930-940 a socioeconomic gradient in child's cognitive scores at 5 years of age,¹⁹19. L. González, R. Cortés-Sancho, M. Murcia, et al. The role of parental social class, education and unemployment on child cognitive development. Gac Sanit., (2018 Nov 1), with differential impact, being maternal education and paternal social class the stronger social determinants. Socioeconomic gradient studied by classical concepts such as parental education, social class and employment status has been widely explored; however, more comprehensive indicators need to be considered, such as poverty and social exclusion, to identify those households at social risk.

To our knowledge, none of the reviewed studies have used primary data at regional level to identify factors potentially influential in child poverty: they rather used national²2. Luque OG, Martínez UF, Lechuga ML. Objetivo Europa 2020. La reducción de la pobreza y la exclusión social en España. Pap Rev Sociol. 2016;101:503-26.^,77. Faura-Martínez U, Lafuente-Lechuga M, García-Luque O. Riesgo de pobreza o exclusión social: evolución durante la crisis y perspectiva territorial/ Risk of Poverty or Social Exclusion: Evolution during the Economic Crisis and Territorial Perspective. REIS. 2016;156:59-76.

8. Llano Ortiz, JCL. El estado de la pobreza. Seguimiento del indicador de riesgo de pobreza y exclusión social en España 2008-2017. European Anti-Poverty Network, (2018), pp. 110^-99. J.C.L. Llano Ortiz. El estado de la pobreza. Seguimiento del indicador de riesgo de pobreza y exclusión social en España 2009-2016. European Anti-Poverty Network, (2017), pp. 116 or supranational¹⁰10. I.H. Aguayo, E.D. Herráiz, E.M. Marques, et al. Child at risk of poverty or social exclusion: comparative view between Spain and Portugal in the European context. Social Indicators Research., 129 (2016), pp. 961-978 surveys, which are inaccurate at a regional level.²⁰20. V. Verma, A. Lemmi, G. Betti, et al. How precise are poverty measures estimated at the regional level?. Reg Sci Urban Econ., 66 (2017), pp. 175-184 The aim of the present study is to describe the risk of poverty and social exclusion, as measured by the AROPE indicators, in households of children aged 8 to 11 years in Gipuzkoa and in Valencia INMA cohorts, two regions with different wealth levels; and to assess the relationship of socio-demographic and family characteristics with AROPE indicators in each area, considering maternal and paternal factors.

Method

Study design and population

INMA (INfancia y Medio Ambiente - Environment and Childhood) Project is a Spanish population-based mother-and-child multicenter cohort study.¹⁸18. M. Guxens, F. Ballester, M. Espada, et al. Cohort profile: the INMA -INfancia y Medio Ambiente- (Environment and Childhood) Project. Int J Epidemiol., 41 (2012), pp. 930-940 This study uses data from INMA Valencia and Gipuzkoa cohorts. Mothers were recruited during their first prenatal visit to La Fe Hospital (Valencia) in 2003-2005, and Zumárraga Hospital (Gipuzkoa) in 2006-2008. The inclusion criteria were>16 years of age, singleton pregnancy, intention of undergoing follow-up and delivery in their hospital, no impediment for communication, and no assisted conception.¹⁸18. M. Guxens, F. Ballester, M. Espada, et al. Cohort profile: the INMA -INfancia y Medio Ambiente- (Environment and Childhood) Project. Int J Epidemiol., 41 (2012), pp. 930-940^,1919. L. González, R. Cortés-Sancho, M. Murcia, et al. The role of parental social class, education and unemployment on child cognitive development. Gac Sanit., (2018 Nov 1), Withdrawals, exclusions, and children's age at follow-up visits are shown in Figure 1. A cross-sectional design was used in the present study within the INMA cohort framework. We collected data on AROPE indicators of participant families between 2015 and 2016, when children were 11 and 8 years old in Valencia and Gipuzkoa cohorts, respectively. In the present study, the final sample was 394 families in Gipuzkoa and 382 in Valencia. Cohorts were approved by their local institutional ethical review boards, and consent to participate was obtained from participants.

AROPE indicators

AROPE indicators were assessed by structured questionnaires self-completed by parents in their homes and revised by a trained interviewer at the beginning of the follow-up visits. AROPE comprises three sub-indicators which are calculated in each household (see ^AppendixAppendixSupplementary data associated with this article can be found, in the online version, at doi: 10.1016/j.gaceta.2019.11.002. 1 online): low work intensity (LWI) (having worked <20% of available hours of their members in working age), at risk of poverty (RP) (having <60% of Spanish median income per consumption unit) and risk of material deprivation (MD) (lacking ≥4 necessary items from a list of 9).⁹9. J.C.L. Llano Ortiz. El estado de la pobreza. Seguimiento del indicador de riesgo de pobreza y exclusión social en España 2009-2016. European Anti-Poverty Network, (2017), pp. 116 Traditionally, the cut-off point used for determining families at risk of MD has been severe MD (lacking ≥4 elements). However, for this study, this variable was dichotomized as low vs medium and severe MD (lacking ≥3 elements) due to the few number of cases in severe MD.

AROPE⁸8. Llano Ortiz, JCL. El estado de la pobreza. Seguimiento del indicador de riesgo de pobreza y exclusión social en España 2008-2017. European Anti-Poverty Network, (2018), pp. 110^,99. J.C.L. Llano Ortiz. El estado de la pobreza. Seguimiento del indicador de riesgo de pobreza y exclusión social en España 2009-2016. European Anti-Poverty Network, (2017), pp. 116 were those households fulfilling at least one of the three previous sub-indicators (LWI, PBUP or MD).

In the same follow-up visit, some additional information regarding family economic situation was requested, such as making ends meet, how was their economic situation in comparison to 2007, and if the household had received any income in the past month (see ^AppendixAppendixSupplementary data associated with this article can be found, in the online version, at doi: 10.1016/j.gaceta.2019.11.002. 1 online).

Variables and data collection

Variables regarding other socio-demographic and family characteristics were collected by self-completed questionnaires supported by the interviewer at different follow-up visits (week 12, and 32 of pregnancy, and age 4-5, and 8-11). Socio-demographic characteristics (social class, educational level, country of origin, parental age and parental working status), family and child characteristics (type of family, number of siblings), parental characteristics (mental health, smoking status) were collected at different follow-up points (see ^AppendixAppendixSupplementary data associated with this article can be found, in the online version, at doi: 10.1016/j.gaceta.2019.11.002. 1 online).

Data imputation

Simple data imputation was performed for the household income in 33 and 122 cases in Valencia and Gipuzkoa, respectively, in order to avoid missing data in RP and AROPE (further information on imputation method is described in ^AppendixAppendixSupplementary data associated with this article can be found, in the online version, at doi: 10.1016/j.gaceta.2019.11.002. 2 on line, Tables Ia and Ib). In both cases, a wide range of related variables were used in a forward procedure, by using linear regression, with a p-value for exclusion of 0.20 and a p-value for inclusion of 0.10. Imputation was performed with Stata 12th Version.

Statistical analysis

Percentages and bar and Venn diagrams were used in the descriptive analysis.

The relationship of socio-economic and family characteristics with the AROPE indicator was assessed by cohort and taking into account both mother and father factors, when available, using for bivariate analysis chi-square, Fisher tests, and simple logistic regression. Multivariate logistic models using imputed data were built to identify those factors that better predicted the risk of poverty and social exclusion in the families of each cohort, after adjusting for the other potential determinants. The final model was built according to the following steps: firstly, simple logistic regressions were performed to assess AROPE relation with covariates. Those which obtained a p ≤0.20 were selected, with the exception of employment situation which was part of AROPE. The final models were calculated for each cohort, excluding sequentially those variables not related at p ≤0.10 in the adjusted model following a backward stepwise selection procedure. A sensitivity analysis was performed with non-imputed data including only those variables selected in the final models in order to replicate them. Statistical analyses were carried out using SPSS, version 24.0 and R Version 3.5.1. Figures 2 to 5 were created with R Version 3.5.1, and Figure 1 was created with the open source diagram technology draw.io.

Results

Sample distribution

The sample description is shown in Table II in ^AppendixAppendixSupplementary data associated with this article can be found, in the online version, at doi: 10.1016/j.gaceta.2019.11.002. 2 online. Distributions across cohorts were statistically different. More advantaged positions were observed in Gipuzkoa, where parents were slightly older and more often classified as being employed, or having higher social position or education than in Valencia. In Gipuzkoa, there was a higher proportion of nuclear families than in Valencia and parents were less likely to be smokers or foreigners. No differences were found across parental mental health and paternal current smoking habit.

AROPE indicators and other family economic characteristics

Descriptive analysis of the AROPE and other family's economic indicators is plotted in Figure 2. Most of the indicators considered were found statistically different between cohorts, with the exception of “Not eating meat or fish every two days” and “Not having received income in the last month”. Higher risks were observed in Valencia, in comparison to Gipuzkoa: in Valencia, 7.8% of households had MD, 8.1% had LWI, 31.5% were RP and 34.7% were AROPE; in Gipuzkoa, these rates were 2.3%, 2.5%, 5.6% and 7.2%, respectively.

Interrelation of AROPE sub-indicators

The interrelation between MD, LWI, RP are represented in Figures 3 and 4 by Venn's diagrams for Valencia and Gipuzkoa. When considering non-shared contributions to AROPE, RP sub-indicator emerged as the most relevant, representing 20.8% and 3.5% of the sample for Valencia and Gipuzkoa, respectively. In Valencia, no overlapping between MD and LWI was observed. Several cases were found to be at risk in all three sub-indicators, representing the 2.4% and 0.8% of AROPE in Valencia and Gipuzkoa, respectively.

Determinants of AROPE

Bivariate analysis between AROPE and all the variables considered is depicted in Table III in ^AppendixAppendixSupplementary data associated with this article can be found, in the online version, at doi: 10.1016/j.gaceta.2019.11.002. 2 online, and unadjusted univariate regressions comparing the effect of maternal and paternal characteristics through both cohorts can be observed in Figure 5. Those parents who were unemployed, or those who were placed in the lowest social class, were more prone of being AROPE. Regarding education, in Valencia both parents presented higher risks when having lower education. The same happened for mothers in Gipuzkoa, but not for fathers. In general terms, parents from foreign country of origin, as well as those who lived in non-nuclear families were more likely to be AROPE. Number of children and tobacco use was significantly related in Valencia. To be more precise, in Valencia was found this association for both parents at pregnancy and in the last follow-up visit. Mothers who smoked during pregnancy in Gipuzkoa were also more likely to be AROPE, even when this relation was not statistically significant. Mothers and fathers showed differential patterns of risk when considering cohort: in Valencia, mothers showed stronger associations than fathers in social class and country of origin, and fathers in education and smoking habits. In Gipuzkoa, mothers had a stronger relation than fathers in low social class and education, and fathers in country of origin.

Risk factors model

Our final adjusted risk factors models are shown in Table 1. Social class and type of family were associated with AROPE in both cohorts, being at higher risk those households with low social class mothers and those non-nuclear families. Additionally, in Gipuzkoa, lower educated mothers were also at higher risk (upper vs. lower [odds ratio (OR): 9.05; 95% confidence interval (95%CI): 2.11-43.49]). However, the final model in Valencia showed as predictor paternal rather than maternal education (upper vs. lower [OR: 6.35; 95%CI: 2.67-17.16]), maternal country of origin (Spain vs. not Spain [OR: 4.50; 95%CI: 1.60-13.41]), and current paternal smoking (no vs. yes [OR: 2.41; 95%CI: 1.41-4.16]).

Sensitivity analysis

Sensitivity analysis with non-imputed data is shown in Table IV in ^AppendixAppendixSupplementary data associated with this article can be found, in the online version, at doi: 10.1016/j.gaceta.2019.11.002. 2 online. The trends and estimates did not change greatly when comparing imputed and non-imputed models.

Discussion

We explored the distribution of household poverty or social exclusion in children of two different areas, described by a wide range of variables such as AROPE sub-indicators, economic characteristics and material constraints highly related to child poverty. In the families of our study samples, we found 34.7% and 7.2% of AROPE in Valencia and Gipuzkoa, respectively. For all these descriptive variables, Valencia showed higher risks. In addition, we decomposed AROPE in its sub-indicators, being RP the greater non-shared contributor to AROPE condition, followed by the other two sub-indicators which were widely overlapped to RP. AROPE was more prevalent in unemployed, low educated, low social class and non-Spanish parents, with smoking habits, and in non-nuclear families. Maternal social characteristics showed a preeminent role in Gipuzkoa, especially level of education, in which fathers showed a null effect. Contributions to AROPE were more evenly distributed between parents in Valencia.

AROPE indicators in our data and in general population

European Anti-Poverty Network (EAPN) has previously described regional AROPE, estimating 30.5% in Valencian Community and 15.9% in Basque Country⁸8. Llano Ortiz, JCL. El estado de la pobreza. Seguimiento del indicador de riesgo de pobreza y exclusión social en España 2008-2017. European Anti-Poverty Network, (2018), pp. 110 for 2016 (Table V in ^AppendixAppendixSupplementary data associated with this article can be found, in the online version, at doi: 10.1016/j.gaceta.2019.11.002. 2 online). The differences with our results could be explained because our recruitment area was a part of the region which could not be absolutely representative. In fact, average income in Valencian Community was slightly higher than the average income in Valencia recruitment area,²¹21. Generalitat Valenciana. Municipios y comarcas. 2018. (Accessed 09/25/2018.) Available at: http://www.pegv.gva.es/bdt .
http://www.pegv.gva.es/bdt... (12.398 vs. 12.127 € of family available income), and Basque Country population was less affluent than Gipuzkoa recruitment area (33.766 vs. 35.579 € of family available income).²²22. Eustat. PXWeb. 2018. (Accessed 25/09/2018.) Available at: http://www.eustat.eus/bankupx/pxweb/es/spanish/-/PX_2381_rpf_rf18s.px/table/tableViewLayout1/?rxid=54710f77-42c6-420c-a790-865705579574#axzz5S6N7wKW2 .
http://www.eustat.eus/bankupx/pxweb/es/s...

Additionally, in the general population very different types of household can be found. However, in this study we used data of families with children which are more prone to poverty.²³23. E. Bárcena-Martín, S. Pérez-Moreno. Immigrant-native gap in poverty: a cross-national European perspective. Rev Econ Household., 15 (2017), pp. 1105-1136 Moreover, nuclear and non-nuclear families have different rates of poverty, showing the latter greater risks.⁸8. Llano Ortiz, JCL. El estado de la pobreza. Seguimiento del indicador de riesgo de pobreza y exclusión social en España 2008-2017. European Anti-Poverty Network, (2018), pp. 110 The AROPE prevalence in Valencia may be higher in our sample than in the general population because our cohort has a high rate of non-nuclear families (20.5%).

Finally, in this work, AROPE was calculated using moderate and not severe MD, and this could be overestimating AROPE. However, MD has small weight on AROPE, and the re-estimation with severe MD yielded AROPE rates of 33.6% and 6.6% for Valencia and Gipuzkoa, respectively (Table V in ^AppendixAppendixSupplementary data associated with this article can be found, in the online version, at doi: 10.1016/j.gaceta.2019.11.002. 2 online).²⁴24. J.C.L. Llano Ortiz. El estado de la pobreza. Seguimiento del indicador de riesgo de pobreza y exclusión social en España 2009-2015. European Anti-Poverty Network, (2016), pp. 276

AROPE is highly correlated with RP.⁷7. Faura-Martínez U, Lafuente-Lechuga M, García-Luque O. Riesgo de pobreza o exclusión social: evolución durante la crisis y perspectiva territorial/ Risk of Poverty or Social Exclusion: Evolution during the Economic Crisis and Territorial Perspective. REIS. 2016;156:59-76. Smaller overlapping of LWI and RP was observed in Gipuzkoa in comparison to Valencia, and non-shared rate of LWI is very similar in both cohorts. Coexistence of high rates of RP and low rates of LWI in Valencia reflects that employed people are at risk of poverty (the working poor).²⁵25. Eurofund. Working poor in Europe - Spain. 2018. (Accessed 21/09/2018.) Available at: https://www.eurofound.europa.eu/publications/report/2010/working-poor-in-europe-spain .
https://www.eurofound.europa.eu/publicat... Having an employment does not protect from having low wages, mainly due to precarious contracting. No overlapping of LWI and MD could be partly explained by black economy, which may have been omitted for desirability.

Disparities between Valencia and Gipuzkoa could be consequence of better public policies in Basque Country in comparison to Valencian Community.²⁶26. G. García, L. Barriga, J.M. Ramírez, et al. Índice DEC. Índice de desarrollo de los servicios sociales. Asociación Estatal de Directores y Gerentes en Servicios Sociales, 16 (2015). Taking as an example the minimum insertion income, we can observe that is an unequal policy across regions in Spain: for example, the same household could receive an insertion income of 945.88 € in Basque Country, while in Valencian Community it would be 434.88 €.²⁷27. Ministerio de Sanidad, Servicios Sociales e Igualdad. Informe de rentas mínimas de inserción. Madrid: Ministerio de Sanidad, Servicios Sociales y Sanidad; 2015. 108 p. It is then crucial to implement social policies more equally across the country. In this line of action, Spanish Government proposed the vital minimum income as a national policy to ameliorate situations of poverty and exclusion.²⁸28. Ministerio de Sanidad, Consumo y Bienestar Social. Estrategia nacional de prevención y lucha contra la pobreza y la exclusión social 2019-2023. Madrid: Ministerio de Sanidad, Consumo y Bienestar Social; 2019. 137 p. However, political instability has not allowed the development of this proposal yet.

AROPE risk factors in each cohort

In our study, parental education and social class played an important role, as observed also in a recent European study²³23. E. Bárcena-Martín, S. Pérez-Moreno. Immigrant-native gap in poverty: a cross-national European perspective. Rev Econ Household., 15 (2017), pp. 1105-1136 and in an EU report.⁶6. Eurostat. People at risk of poverty or social exclusion - Statistics Explained. 2018. (Accessed 09/26/2018.) Available at: https://ec.europa.eu/eurostat/statistics-explained/index.php/People at risk of poverty or social exclusion .
https://ec.europa.eu/eurostat/statistics... However, the role of parental education varied according to area: maternal and paternal education was related to AROPE in Valencia, but in Gipuzkoa only maternal education played a role. This may be because in Valencia occupation was highly related with education in mother and father, while these variables were only related in mothers in Gipuzkoa (data not shown), where men seem to be employed independently to their level of education.

Non-nuclear families, especially monomarental ones, are more vulnerable to income scarcity⁶6. Eurostat. People at risk of poverty or social exclusion - Statistics Explained. 2018. (Accessed 09/26/2018.) Available at: https://ec.europa.eu/eurostat/statistics-explained/index.php/People at risk of poverty or social exclusion .
https://ec.europa.eu/eurostat/statistics... ^,88. Llano Ortiz, JCL. El estado de la pobreza. Seguimiento del indicador de riesgo de pobreza y exclusión social en España 2008-2017. European Anti-Poverty Network, (2018), pp. 110^,2323. E. Bárcena-Martín, S. Pérez-Moreno. Immigrant-native gap in poverty: a cross-national European perspective. Rev Econ Household., 15 (2017), pp. 1105-1136 because they also have less flexibility to distribute housework, childcare and paid work in comparison to a nuclear family.²⁹29. L.C. Maldonado, R. Nieuwenhuis. Family policies and single parent poverty in 18 OECD countries, 1978-2008. Community Work Fam., 18 (2015), pp. 395-415

Foreign country of origin have shown trends of higher risk of poverty.⁸8. Llano Ortiz, JCL. El estado de la pobreza. Seguimiento del indicador de riesgo de pobreza y exclusión social en España 2008-2017. European Anti-Poverty Network, (2018), pp. 110^,2323. E. Bárcena-Martín, S. Pérez-Moreno. Immigrant-native gap in poverty: a cross-national European perspective. Rev Econ Household., 15 (2017), pp. 1105-1136 This gap is different across European countries, finding Norway and the Netherlands with the smallest differences between native and non-native citizens, and Spain with the greatest, followed by Greece and Italy.²³23. E. Bárcena-Martín, S. Pérez-Moreno. Immigrant-native gap in poverty: a cross-national European perspective. Rev Econ Household., 15 (2017), pp. 1105-1136

In Valencia, child poverty was also related to current paternal smoking (Table VI in ^AppendixAppendixSupplementary data associated with this article can be found, in the online version, at doi: 10.1016/j.gaceta.2019.11.002. 2 online). In INMA cohorts, smoking is highly related to social class and education.³⁰30. J.J. Aurrekoetxea, M. Murcia , M. Rebagliato, et al. Second-hand smoke exposure in 4-year-old children in Spain: sources, associated factors and urinary cotinine. Environ Res., 145 (2016), pp. 116-125 Households living in economic strain are more vulnerable to stress and anxiety,³¹31. C. Martínez-Vispo, E. Becoña. La sensibilidad a la ansiedad y el consumo de tabaco: una revisión. Ansiedad Estrés., 22 (2016), pp. 118-122^,3232. D.S. Shaw, E.C. Shelleby. Early-starting conduct problems: intersection of conduct problems and poverty. Annu Rev Clin Psycho., 10 (2014), pp. 503-528 and those with less tolerance to anxiety could have more difficulties for dropping tobacco.³¹31. C. Martínez-Vispo, E. Becoña. La sensibilidad a la ansiedad y el consumo de tabaco: una revisión. Ansiedad Estrés., 22 (2016), pp. 118-122

According to recent reports, one third of children in Spain are at risk of poverty or social exclusion.³³33. C. Del Moral. La infancia marca. Análisis de los derechos de los niños y las niñas durante los últimos 100 años de historia de España. Save the Children, (2019), pp. 72^,3434. Save the Children. Pobreza infantil y exclusión social en Europa. Una cuestión de derechos. Brussels, Belgium: Save the Children; 2014. 44 p. The main factors of poverty are having a non-nuclear family,³³33. C. Del Moral. La infancia marca. Análisis de los derechos de los niños y las niñas durante los últimos 100 años de historia de España. Save the Children, (2019), pp. 72^,3434. Save the Children. Pobreza infantil y exclusión social en Europa. Una cuestión de derechos. Brussels, Belgium: Save the Children; 2014. 44 p. and having non-native, and low educated parents.³⁴34. Save the Children. Pobreza infantil y exclusión social en Europa. Una cuestión de derechos. Brussels, Belgium: Save the Children; 2014. 44 p.^,3535. Bello, A. Indicadores de bienestar infantil 2016. UNICEF, Comité Español, (2016), pp. 8. However, it is also argued that the main tool to break the cycle of poverty is children's education.³⁴34. Save the Children. Pobreza infantil y exclusión social en Europa. Una cuestión de derechos. Brussels, Belgium: Save the Children; 2014. 44 p.

Limitations of this work

Firstly, lack of data on household income made necessary a data imputation, but sensitivity analysis showed no differences. Secondly, small numbers in some factors did not allow arising strong conclusions. Thirdly, AROPE was calculated considering medium and severe MP, instead of severe MP, but re-estimation did not changed prevalence greatly. Finally, representativeness of the sample was a problem to generalization; because sample selection was non-representative of population in Gipuzkoa and Valencia and because those families with less advantaged social positions tend to abandon the study follow-up¹⁹19. L. González, R. Cortés-Sancho, M. Murcia, et al. The role of parental social class, education and unemployment on child cognitive development. Gac Sanit., (2018 Nov 1),.

Strengths of this work

Firstly, AROPE is the gold standard for measuring poverty in EU. Secondly, we considered a wide range of variables depicting parental characteristics, and both parents were represented. Finally, although this work presented a cross-sectional design, the prospective nature of the INMA cohort study allow the use of data collected at different stages. Therefore, AROPE will be a key tool to be used as a social determinant for present but also upcoming health outcomes.

Implications for policy makers

It is crucial to foster the accessibility to education by the use of public scholarships and investments in public schools. Additionally, regulating and protecting labour market, would increase economic affluence. Moreover, increasing and equalizing economic policies such as minimum insertion income or developing recent proposals such as the minimum vital income, would reduce poverty and social exclusion. Finally, non-nuclear and foreign country of origin families would have a better support if some services were partially funded by the government, in order to equalize the lack of resources non-nuclear families have in comparison to nuclear families.

Acknowledgements

The authors would particularly like to thank all participants for their generous collaboration, and Esperanza Alabarta Domínguez for her support with the fieldwork. A full list of the INMA Project researchers is available at http://www.proyectoinma.org.

References

Publication Dates

History