Carrilero et al. BMC Public Health (2021) 21:1150 https://doi.org/10.1186/s12889-021-11230-9 RESEARCH Open Access Socioeconomic inequalities in 29 childhood diseases: evidence from a 1,500,000 children population retrospective study Neus Carrilero1,2,3*, Albert Dalmau-Bueno1 and Anna García-Altés1,4,5 Abstract Background: Socioeconomic position (SEP) powerfully affects health status in the childhood population. However, the knowledge of which diseases are more affected by SEP and whose outcomes could be improved by having a more equitable society remains uncertain on a population basis. Methods: We measured socioeconomic and gender inequalities in the pre-COVID-19 era for 29 diseases in the entire childhood population in Catalonia to identify which diseases are most impacted by inequalities. This population-based study included 1,449,816 children under 15 years old from 2014 to 2017 (48.52% girls) and each of their registered diagnoses within the Catalonia National Health System. We calculated frequency measures by SEP and their sex ratios for each disease. We estimated four regression-based inequality measures: slope index of inequality, relative index of inequality (RII), absolute population-attributable fraction, and population-attributable fraction. Results: Twenty-five of the 29 diseases examined showed SEP inequalities. The diseases with the greatest inequalities in both sexes were tuberculosis, obesity, adjustment and anxiety disorders, essential hypertension, poisoning, short gestation, low birth weight, foetal growth retardation and intrauterine hypoxia and birth asphyxia and trauma (RII ≥ 2.0); only food allergy showed the opposite pattern (RII < 1.0). Overall, 80,188 (7.80%) of the disease events in boys and 74,921 (8.88%) in girls would be avoided if all children had the same disease rate as those in the medium-high SEP group, with tuberculosis, intrauterine hypoxia and birth asphyxia and trauma, obesity, and short gestation, low birth weight, foetal growth retardation being those that could be reduced the most in relative terms, and dermatitis, injuries, acute bronquitis, and being overweight those that could be reduced the most in absolute terms. Girls present higher RII than boys for respiratory allergy, asthma, dermatitis, being overweight, and obesity (p < 0.05). In contrast, boys showed higher RII compared to girls only in congenital anomalies (p < 0.05). * Correspondence: neus.carrilero@gencat.cat 1 Agència de Qualitat i Avaluació Sanitàries de Catalunya (AQuAS), Carrer de Roc Boronat, 81-95, 08005 Barcelona, Spain 2 Universitat Pompeu Fabra. Department of Experimental and Health Sciences (DCEXS), Barcelona, Spain Full list of author information is available at the end of the article © The Author(s). 2021 Open Access This article is licensed under a Creative Commons Attribution 4.0 International License, which permits use, sharing, adaptation, distribution and reproduction in any medium or format, as long as you give appropriate credit to the original author(s) and the source, provide a link to the Creative Commons licence, and indicate if changes were made. The images or other third party material in this article are included in the article's Creative Commons licence, unless indicated otherwise in a credit line to the material. If material is not included in the article's Creative Commons licence and your intended use is not permitted by statutory regulation or exceeds the permitted use, you will need to obtain permission directly from the copyright holder. To view a copy of this licence, visit http://creativecommons.org/licenses/by/4.0/. The Creative Commons Public Domain Dedication waiver (http://creativecommons.org/publicdomain/zero/1.0/) applies to the data made available in this article, unless otherwise stated in a credit line to the data. Carrilero et al. BMC Public Health (2021) 21:1150 Page 2 of 14 Conclusions: Socioeconomic and gender inequalities are widely present in childhood health. This indicates that SEP plays a common role in their development although it varies in magnitude according to each disease. It is also a phenomenon that comprises all SEP groups in society. Action needs to be taken to ensure a fairer start in life in terms of health. Keywords: Health inequalities, Socioeconomic position, Gender, Childhood diseases, Health status disparaties, Child Background sugary beverages, and physical activity engagement, Children are one of the most vulnerable population among others [14–18]. groups, since they are entirely dependent on their envir- Socioeconomic inequalities in these outcomes have onment and have few mechanisms to face adversity. Evi- also widened [19], as well as indicators of healthcare use dence suggests that beyond biological factors, social among the youngest population [20]. determinants (i.e household resources, parents’ behav- Despite the growing interest in health inequalities, iours, neighbourhood deprivation, among others) [1] thus far, childhood diseases have mainly been analysed play an important role in children’s health status since individually with different socioeconomic proxies, popu- social determinants have been systematically associated lations, contexts, and inequality measures [6]. These dif- with a wide variety of pathologies of different etiologies ferent approaches do not contribute to an accurate and also in diverse societies [2]. comparison between inequality measures or between The Early Child Development Framework (proposed health outcomes. A parallell but equally important issue by the WHO (TEAM-ECD)) highlights two essential is that gender differences in health inequalities have inputs to be taken into account in regard to the pro- been scarcely analyzed [21]. It is increasingly recognized duction of inequalities in children’s health: (1) the that different axes of social power relations such as gen- stage of development in the early years of childhood, der and SEP, are interrelated impacting on health in an and (2) the socioeconomic position (SEP) of the intersecting process [21–24]. It is strongly recomended child’s family [3, 4]. It is the family context that pro- that SEP should not be analysed by itself because appar- vides the most influence on the child and which also ent inequalities can be misinterpreted without gender controls the inputs received from the distal environ- analysis. It could open a wider area of research in in- ment [1]. Previous studies have established a “gradient equalities and gender since the genderization of health effect” according to the family’s SEP across a wide determinants already starts in childhood [22, 23]. range of outcomes, both in childhood and adulthood, Therefore, the aim of this study is threefold: 1) to cal- in health, educative attaintment, and in future career culate socioeconomic inequality for a wide range of dis- opportunities [5–9]. Therefore, tackling inequalities at eases in an entire childhood population, 2) to determine the beginning of life and focusing on improving fam- gender differences in inequalities in each disease, and 3) ily support is a powerful approach to establishing the to estimate the burden of disease attributable to SEP roots of good health in childhood development and in using public health impact measures. To accomplish the future to come [2–4, 9]. these aims, we analysed 29 diseases by sex using sum- Catalonia’s situation, as in other European countries, is mary inequality and impact measures that are widely far from achieving the Sustainable Development Goal used in public health epidemiology based on regression (SDG) 10 of “Reduced inequality” [10]. In Catalonia, models that quantify inequality and population impact poverty and social exclusion rates in childhood have including all population SEP levels, rather than the two been increasing since 2008 reaching an at-risk-of-pov- extreme groups [25, 26]. erty or social exclusion rate of 33.0% in 2019, far above the European average of 22.5%. Besides, children in Catalonia suffer the most from poverty, more than other Methods age groups [11, 12]. In spite of this high poverty rate, Healthcare in Catalonia is organised as a National macro health indicators such as life expectancy at birth Health System, funded by taxes. All residents (7,348, and infant mortality have improved since 1994, main- 275 as of 2017) are granted universal public health- taining a similar downward trend as is seen in other care coverage by law. The use of publicly funded European countries [13, 14]. By contrast, poor health healthcare services is free; the sole exception is drug outcomes related to social determinants and lifestyle are prescription, which is based on a co-payment system. indicators that have worsened in Catalonia and other Each resident is assigned a unique personal healthcare similar contexts; these indicators include low birth ID which can be used to trace their use of healthcare weight rate, being overweight, higher consumption of services. Carrilero et al. BMC Public Health (2021) 21:1150 Page 3 of 14 Study design and population period. SEP was proxied by the pharmaceutical copay- We carried out a population-based study on a retro- ment level of the child’s parents or guardians, obtained spective review of all children under 15 resident in Cata- from the RCA registry. Pharmaceutical copayment uses lonia during the period 2014–2017 (1,449,816 children, income level and employment status information (spe- 48.52% girls). cially to detect individuals without any income from work) to define four SEP categories as follows: “Very Data collection low” (no member of the household employed or receiv- Two different databases were used: ing welfare support), “Low” (<€18,000/year), “Medium” The Central Registry of Insured Persons (RCA, Catalan (€18,000–€100,000/year), and “High” (>€100,000/year). acronym), to obtain the reference population for the This classification has been used in previous studies [20, 2014–2017 period. This registry also collects and up- 28]. Age was categorised into five groups (0–2 years, 3– dates data on the annual income level, employment sta- 5 years, 6–8 years, 9–11 years, and 12–14 years) and sex tus, and Social Security benefits of each individual, (boys, girls). which are routinely used to calculate citizens’ pharma- ceutical copayment levels. Statistical analysis The Registry of the Minimum Basic Dataset (CMBD, Age and SEP distribution were calculated first with Catalan acronym) is an administrative register contain- absolute (N) and relative frequency (%). Following the ing detailed information on sociodemographic character- profile of each disease (acute or chronic), we calcu- istics and medical diagnoses (coded using the lated for each SEP category age-adjusted incidence International Classification of Diseases, 9th Edition). The proportion or period prevalence. Incidence proportion CMBD encodes all contacts with the public healthcare was calculated only for acute bronchitis, influenza, in- system at an individual level: primary care, hospital care, juries, meningitis, poisoning, and tuberculosis (TB); emergency, mental health, and long-term care services. accounting for the new cases diagnosed in the period; All the diagnostic codes registered in the CMBD during period prevalence was calculated for the rest of the the period 2014–2017 were gathered to create the main diseases, accounting for new and pre-existing cases. dataset which was then linked to the RCA through a The prevalence ratios (PR) or incidence proportion common personal healthcare ID. ratios (IR) for boys and girls were calculated through Both registries are considered of high quality as 1) they a generalised linear model (log-binomial regression) include the entire population of Catalonia since all citi- with a logarithmic link function. Both PR and IR were zens are granted universal healthcare coverage (99.6% of estimated with their respective confidence intervals all residents are registered); 2) they have a validation sys- (95% CI) and associated p-values. tem; and 3) they contain historical diagnosis data. We To quantify SEP inequalities in each disease, we calcu- excluded 307 children (0.02% of the entire child popula- lated two different summary measures: the relative index tion) due to a misclassification of the SEP variable. of inequality (RII) and slope index of inequality (SII). These indices are regression based and accounted for Variables the sample size population and relative weight for every The dependent variables were 29 diseases or risk fac- stratum of SEP, rather than comparing only the two tors representative of the health status of the child most extreme SEP levels. For both indices, the punctual population of Catalonia. This wide selection includes estimate is accompanied by its 95% CI and the associ- both diseases that are strongly influenced by social ated p-value. determinants and others whose influence is not The measure of RII is a relative measure of inequal- clearly established [6, 27]. This selection also repre- ity that involves the following steps: 1) determination sents diseases of diverse etiology, affecting different of the disease frequency of each SEP category and 2) organic systems, and of differing severity. Each disease ranking SEP levels, assigning a hierarchical value from variable was constructed selecting diagnostic codes 0 (lowest SEP) to 1 (highest SEP) according to its based on clinical criteria (see Additional file 1). The proportional size in the population by linear regres- inclusion criteria at an individual level was having at sion. The population of each SEP level is assigned a least one medical diagnosis, being registered on the Ridit score based on the mid-point of the cumulative CMBD, and included in at least one of the defined distribution of the population of participants in the diseases. Duplicate diagnoses were not taken into ac- given category, and finally 3) this weighted SEP is in- count so that each of the disease variables was treated cluded as exposure and disease as a dichotomous as a dichotomous variable. dependent variable in a generalised linear model (log- The independent variables were SEP, age, and sex. SEP binomial regression) with a logarithmic link function. and age were defined at the beginning of the study The highest SEP category was used as a reference. Carrilero et al. BMC Public Health (2021) 21:1150 Page 4 of 14 The RII reflects the risk ratio of an outcome between of interpretation is, for instance: TB in girls has a those on the social hierarchy who are more advan- PAF% = 51.95% of the total TB events in girls which taged and those who are more disadvantaged [29, 30]. could be potentially avoided if all the population had the The SII is an absolute measure of inequality that rep- same TB incidence as medium-high SEP, which is trans- resents the absolute difference in estimated values of a lated in PAFa = 171 TB events. The PAFa and PAF% re- health outcome between the most advantaged and the sults are presented with a 95%CI and the associated p- most disadvantaged. The calculation of SII follows the values [25, 29, 32]. same steps as RII: 1) and 2) and then, 3) weighted SEP is All analyses were performed separately for girls and also included as exposure and frequency of disease as a boys. All methods were carried out in accordance with dependent variable in a generalised linear model ad- relevant guidelines and regulations. We used the STATA justed by age with an identity link function. The differ- IC/15.1 software modules RIIGEN for RII and SII and ence in the predicted values for the extreme SEP Punaf for PAF, to perform all the analyses [33, 34]. categories generates the SII value. If there is no inequal- ity, SII takes the value zero. Greater absolute values indi- Results cate higher levels of inequality [29, 30]. The characteristics of the study population are presented Finally, to study intersectionality between sex and SEP in Table 1. During the study period, the population con- across diseases, sex differences were assessed by insert- tained 1,449,816 children under 15 years old (48.52% ing a two-way interaction term between the SEP Ridit girls and 51.48% boys); the largest group was of those score calculated previously and gender for the RII and aged from newborn to 2 years representing around 30% SII models. A positive and significant coefficient for the of boys and girls. In our population, 4.21% (60,994 chil- two-way interaction term would indicate a larger in- dren) are very low SEP (4.24% in boys and 4.17% in crease in RII or SII in girls compared to boys [31]. girls), and the low SEP represents the main group We calculated population attributable fractions in ab- (62.39% in boys and 62.30% in girls). solute terms (PAFa) and relative terms (PAF%). To achieve this, medium and high SEP categories were Prevalences, incidence proportions, PR and IR grouped and defined as the reference group and low and Prevalences, incidence proportions by sex and SEP, and very low SEP as the exposure group; the log-binomial PR and IR between sexes for each disease are shown in model mentioned previously were performed again. Table 2. The most frequent diseases or risk factors in PAFa are the estimated cases that would be prevented if both sexes were injuries (34.51% in boys and 29.25% in low and very low SEP had the same health status as girls), dermatitis (21.22% in boys and 23.30% in girls), higher SEP levels while other risk factors remain un- and acute bronchitis (18.32% in boys and 15.23% in changed. PAF% is the associated fraction and its PAF% = girls). Congenital anomalies, being overweight, influenza, pd.[(PRa-1)/PRa], where PRa is the prevalence ratio, pd. chronic bronchitis, obesity, and asthma had proportions is the proportion of those with the specific disease and between 5 and 10% in both sexes. PRa-1 represents the risk over the reference point. For Of all the 29 pathologies studied, 25 were more fre- incidence proportion substitute PRa for IRa. An example quent in boys. Autism spectrum disorder (ASD) (PR = Table 1 Characteristics of the child population by SEP and agea in Catalonia during the period 2014–2017 Boys Girls Total N = 746,392 % N = 703,424 % N = 1,449,816 % Age 0–2 224,889 30.13 211,827 30.11 436,716 30.12 3–5 140,194 18.78 131,100 18.64 271,294 18.71 6–8 135,725 18.18 127,797 18.17 263,522 18.18 9–11 127,066 17.02 120,194 17.09 247,260 17.06 12–14 118,518 15.89 112,506 15.99 231,024 15.93 SEP Very low 31,641 4.24 29,353 4.17 60,994 4.21 Low 465,703 62.39 438,256 62.30 903,959 62.35 Medium 243,055 32.57 230,005 32.70 473,060 32.63 High 5993 0.80 5810 0.83 11,803 0.81 a SEP and age were determined for the first year of the study period Carrilero et al. BMC Public Health (2021) 21:1150 Page 5 of 14 Table 2 Disease frequency measures by SEP and sex, and Prevalence ratio (PR) or Incidence proportion ratio (IR) (boys compared to girls) of children in Catalonia PR/IR Period prevalence/ Incidence proportion Boys vs girls Boys Girls Very low Low SEP Medium High Very low Low SEP Medium High SEP SEP SEP SEP SEP SEP Disease PR/IR (95% CI) N (%) N (%) N (%) N (%) N (%) N (%) N (%) N (%) p-value Infectious diseases Tuberculosisa 0.92 (0.79, 1.07) 33 (0.10) 243 (0.05) 47 (0.02) 0 (0.00) 44 (0.15) 229 (0.05) 53 (0.02) 0 (0.00) a Meningitis (bacterial or viral) 1.57 (1.36, 33 (0.10) 330 (0.07) 142 (0.06) 1 (0.02) 12 (0.04) 196 (0.04) 97 (0.04) 1 (0.01) 1.80)*** Influenzaa 1.05 (1.04, 3257 40,304 19,581 234 2940 36,172 17,580 217 1.06)*** (10.29) (8.65) (8.06) (3.91) (10.02) (8.25) (7.64) (3.73) Neoplasms Cancer of the brain and nervous 1.09 (0.90, 1.32) 18 (0.06) 133 (0.03) 75 (0.03) 0 (0.00) 6 (0.02) 126 (0.03) 58 (0.03) 4 (0.06) system Leukaemia 1.26 (1.06, 17 (0.05) 196 (0.04) 105 (0.04) 4 (0.07) 8 (0.03) 157 (0.04) 74 (0.03) 1 (0.02) 1.48)** Malignant neoplasms 1.08 (1.02, 1.15)* 129 (0.41) 1402 667 (0.27) 9 (0.15) 107 (0.36) 1231 572 8 (0.14) (0.30) (0.28) (0.259 Anthropometrics Overweight 1.06 (1.05, 3809 44,974 20,602 267 3252 38,425 16,985 228 1.08)*** (18.77) (17.52) (14.23) (5.93) (17.24) (15.80) (12.30) (5.30) Obesity 1.33 (1.32, 2159 23,454 8886 78 1530 16,237 5880 57 1.35)*** (10.64) (9.14) (6.14) (1.73) (8.11) (6.71) (4.27) (1.32) Mental health Mood disorders 0.87 (0.83, 164 (0.52) 2144 780 (0.32) 10 200 (0.68) 2325 823 (0.36) 10 0.91)*** (0.46) (0.17) (0.53) (0.17) Adjustment and anxiety disorders 1.06 (1.04, 1788 21,098 7596 56 1638 18,764 6682 47 1.08)*** (5.65) (4.53) (3.13) (0.94) (5.58) (4.28) (2.91) (0.82) ADHD 2.70 (2.63, 1323 16,443 7790 139 437 (1.49) 5863 2627 46 2.76)*** (4.18) (3.53) (3.20) (2.32) (1.34) (1.14) (0.79) ASD 4.66 (4.39, 321 (1.01) 4154 2006 21 68 (0.23) 844 (0.19) 401 (0.17) 2 (0.04) 4.94)*** (0.89) (0.83) (0.35) Autoimmune and respiratory diseases Acute bronchitisa 1.21 (1.20, 7014 87,062 41,963 669 5471 68,208 32,929 476 1.21)*** (22.17) (18.60) (17.26) (11.16) (18.64) (15.50) (14.30) (8.20) Chronic bronchitis 1.22 (1.21, 3285 40.515 19,404 282 2560 31,430 14,976 201 1.23)*** (10.38) (8.70) (7.98) (4.71) (8.72) (7.17) (6.51) (3.46) Asthma 1.47 (1.45, 2460 32,359 16,639 232 1641 21,122 10,298 128 1.49)*** (7.77) (6.95) (6.85) (3.87) (5.59) (4.82) (4.48) (2.20) Respiratory allergy 1.13 (1.12, 1677 22,128 9797 125 1310 15,929 6640 79 1.14)*** (5.30) (4.75) (4.03) (2.09) (4.46) (3.63) (2.89) (1.36) Dermatitis 0.94 (0.93, 7610 102,065 47,832 668 7886 106,201 48,956 687 0.94)*** (24.05) (21.92) (19.68) (11.15) (26.87) (24.23) (21.28) (11.82) Food allergy 1.08 (1.06, 316 (1.00) 5502 3811 58 240 (0.82) 5073 3640 59 1.10)*** (1.18) (1.57) (0.96) (1.16) (1.58) (1.01) Cystic fibrosis 1.00 (0.79, 1.28) 3 (0.01) 83 (0.02) 46 (0.02) 1 (0.01) 5 (0.02) 75 (0.02) 44 (0.02) 2 (0.04) Adverse birth outcomes Short gestation, low birth weight, foetal 1.04 (1.01, 1.08)* 320 (1.01) 4795 1677 30 310 (1.05) 4276 1568 28 growth retardation (1.03) (0.69) (0.50) (0.98) (0.68) (0.49) Intrauterine hypoxia and birth asphyxia 1.37 (1.29, 173 (0.55) 2102 746 (0.31) 8 (0.14) 85 (0.29) 1480 506 (0.22) 0 (0.00) and trauma 1.45)*** (0.45) (0.34) Carrilero et al. BMC Public Health (2021) 21:1150 Page 6 of 14 Table 2 Disease frequency measures by SEP and sex, and Prevalence ratio (PR) or Incidence proportion ratio (IR) (boys compared to girls) of children in Catalonia (Continued) PR/IR Period prevalence/ Incidence proportion Boys vs girls Boys Girls Very low Low SEP Medium High Very low Low SEP Medium High SEP SEP SEP SEP SEP SEP Disease PR/IR (95% CI) N (%) N (%) N (%) N (%) N (%) N (%) N (%) N (%) p-value Congenital anomalies 1.18 (1.16, 3343 46,752 21,640 265 2398 36,981 18,183 232 1.19)*** (10.57) (10.04) (8.90) (4.42) (8.17) (8.44) (7.91) (3.99) Nervous system Paralysis 1.24 (1.14, 71 (0.22) 760 (0.16) 306 (0.13) 3 (0.05) 64 (0.22) 544 (0.12) 252 (0.11) 4 (0.07) 1.36)*** Epilepsy 1.16 (1.10, 217 (0.68) 2555 1139 28 175 (0.60) 2024 996 (0.43) 9 (0.16) 1.21)*** (0.55) (0.47) (0.46) (0.46) Circulatory system Essential hypertension 1.28 (1.18, 70 (0.22) 1001 343 (0.14) 4 (0.06) 56 (0.19) 731 (0.17) 256 (0.11) 3 (0.05) 1.38)*** (0.22) Heart valve disorders 1.18 (1.16, 1054 15,078 7584 97 899 (3.06) 11,970 6075 83 1.20)*** (3.33) (3.24) (3.12) (1.61) (2.73) (2.64) (1.43) Acute cerebrovascular disease 1.39 (1.23, 32 (0.10) 413 (0.09) 173 (0.07) 3 (0.06) 22 (0.07) 269 (0.06) 130 (0.06) 3 (0.06) 1.57)*** Others Injuriesa 1.18 (1.17, 13,453 16,4317 78,687 1292 10,493 130,995 63,419 990 1.18)*** (42.52) (35.28) (32.37) (21.57) (35.75) (29.89) (27.57) (17.04) Poisoninga 0.99 (0.92, 1.06) 123 (0.39) 1094 438 (0.18) 10 119 (0.41) 1089 372 (0.16) 15 (0.23) (0.17) (0.25) (0.27) Note: Age-adjusted frequency measures by SEP were calculated according the chronic or acute profile of each disease: aIncidence proportion only for acute bronchitis, influenza, injuries, meningitis, poisoning and tuberculosis, or Period prevalence for the rest of diseases. (Incidence proportion accounts for the number of new cases of the disease and Period prevalence includes all cases of the disease (new and preexisting) during the period) ADHD Attention deficit hyperactivity disorder, ASD Autism spectrum disorder p-value: *(≤0.05), **(≤0.01), ***(≤0.001) 4.66, 95% CI: 4.39, 4.94), attention deficit hyperactivity and anxiety disorders, essential hypertension, poisoning, disorder (ADHD) (PR = 2.70, 95% CI: 2.63, 2.76), short gestation, low birth weight and foetal growth re- meningitis (IR = 1.57, 95% CI:1.36, 1.80), and asthma tardation, and intrauterine hypoxia and birth asphyxia (PR = 1.47, 95% CI:1.45, 1.49) were significantly more and trauma. Following these closely, but with slight dif- frequent in boys than in girls. By contrast, mood disor- ferences depending on sex, were mood disorders, menin- ders (PR = 0.87, 95% CI: 0.83, 0.91) and dermatitis (PR = gitis and paralysis in boys, and mood disorders and 0.94, 95% CI: 0.93, 0.94) were significantly more frequent overweight in girls (see Fig. 1). in girls than in boys. Regarding the differences between sex in inequalities, relative inequalities were significantly higher in girls than Inequality measures in boys for respiratory allergy, asthma, dermatitis, being Measures of SEP inequality are presented in Table 3. overweight, and obesity (p < 0.05). In contrast, boys Overall, 25 of the 29 diseases analysed showed a signifi- showed significantly higher relative inequalities com- cant inverse SEP gradient: the lower the SEP, the higher pared to girls only in congenital anomalies (p < 0.05). the frequency. Only food allergy showed a significant Absolute inequalities were significantly greater in boys direct SEP gradient (RII = 0.86, 95% CI: 0.82, 0.90 in compared to girls for acute cerebrovascular disease and boys and RII = 0.87, 95% CI: 0.83, 0.92). The other dis- cancer of the brain and nervous system (p < 0.05). eases studied (cancer of the brain and nervous system, leukaemia, cystic fibrosis for both sexes, and meningitis Population SEP impact measures and acute cerebrovascular disease for girls) did not show The population SEP impact measures are presented in statistical significance. Table 4. The diseases that could potentially be prevented The diseases with a more pronounced SEP gradient more from equating the health status of the childhood (RII ≥ 2.0) in both sexes were TB, obesity, adjustment population to the medium-high SEP were, in relative Carrilero et al. BMC Public Health (2021) 21:1150 Page 7 of 14 Table 3 Measures of SEP inequality SII and RII and sex differences of each disease in children in Catalonia Disease SII (95% CI) RII (95% CI) Boys Girls p-value* Boys Girls p-value* Infectious diseases Tuberculosis 0.08 (−0.04, 0.21) 0.11 (−0.13, 0.35) 0.675 8.13 (4.83, 13.71) 9.62 (5.70, 16.26) 0.656 Meningitis (bacterial or viral) 0.06 (−0.03, 0.15) 0.02 (− 0.03, 0.08) 0.144 1.89 (1.31, 2.72) 1.23 (0.77, 1.95) 0.153 Influenza 5.00 4.90 0.969 1.29 (1.25, 1.33) 1.33 (1.28, 1.37) 0.286 (−2.68, 12.67) (− 2.47, 12.26) Neoplasms Cancer of the brain and nervous system 0.04 (−0.04, 0.12) − 0.03 0.019 1.28 (0.75, 2.19) 1.13 (0.64, 2.02) 0.765 (− 0.11, 0.05) Leukaemia −0.01 0.01 (− 0.03, 0.05) 0.103 1.01 (0.65, 1.58) 1.16 (0.69, 1.94) 0.695 (− 0.07, 0.04) Malignant neoplasms 0.20 (−0.11, 0.50) 0.17 (− 0.06, 0.41) 0.793 1.37 (1.15, 1.62) 1.44 (1.19, 1.73) 0.696 Anthropometrics Overweight 11.36 (−0.81, 23.53) 10.69 (1.30, 20.08) 0.858 1.63 (1.58, 1.67) 1.78 (1.73, 1.84) < 0.001 Obesity 7.98 (2.52, 13.43) 6.09 (2.35, 9.82) 0.261 2.37 (2.27, 2.48) 2.68 (2.54, 2.82) < 0.001 Mental health Mood disorders 0.31 (0.14, 0.48) 0.44 (0.08, 0.81) 0.205 1.92 (1.65, 2.23) 2.09 (1.81, 2.41) 0.424 Adjustment and anxiety disorders 4.03 (0.66, 7.41) 4.03 (0.47, 7.60) 0.998 2.17 (2.07, 2.27) 2.24 (2.13, 2.36) 0.346 ADHD 1.48 (−0.39, 3.34) 0.60 (0.07, 1.13) 0.090 1.21 (1.15, 1.27) 1.31 (1.20, 1.43) 0.112 ASD 0.53 (−0.31, 1.37) 0.15 (−0.09, 0.40) 0.107 1.29 (1.16, 1.42) 1.36 (1.09, 1.71) 0.636 Autoimmune and respiratory diseases Acute bronchitis 8.62 (−3.28, 20.52) 8.19 (−3.40, 19.77) 0.915 1.35 (1.33, 1.38) 1.39 (1.36, 1.42) 0.090 Chronic bronchitis 4.46 (−1.75, 10.67) 4.13 (−1.62, 9.89) 0.874 1.37 (1.33, 1.41) 1.43 (1.38, 1.49) 0.064 Asthma 3.00 (−2.63, 8.64) 2.68 (− 1.42, 6.78) 0.848 1.08 (1.05, 1.12) 1.23 (1.18, 1.29) < 0.001 Respiratory allergy 2.71 (−0.33, 5.75) 2.58 (−0.03, 5.18) 0.889 1.26 (1.22, 1.29) 1.37 (1.33, 1.41) < 0.001 Dermatitis 10.68 (−3.47, 24.84) 12.55 (−2.75, 27.86) 0.713 1.32 (1.30, 1.35) 1.41 (1.38, 1.43) < 0.001 Food allergy −0.06 (−1.80, 1.67) −0.23 (−2.15, 1.68) 0.791 0.86 (0.82, 0.90) 0.87 (0.83, 0.92) 0.655 Cystic fibrosis 0.00 (−0.03, 0.02) −0.02 (− 0.05, 0.02) 0.113 0.79 (0.40, 1.55) 0.77 (0.38, 1.55) 0.963 Adverse birth outcomes Short gestation, low birth weight, foetal 0.53 (0.42, 0.65) 0.54 (0.39, 0.70) 0.788 2.20 (1.99, 2.43) 2.14 (1.92, 2.38) 0.704 growth retardation. Intrauterine hypoxia and birth asphyxia 0.36 (0.11, 0.61) 0.28 (−0.09, 0.65) 0.453 2.31 (1.98, 2.69) 2.31 (1.93, 2.78) 0.978 and trauma Congenital anomalies 5.21 (−2.26, 12.69) 3.59 (−3.77, 10.96) 0.530 1.38 (1.34, 1.42) 1.23 (1.19, 1.27) < 0.001 Nervous system Paralysis 0.14 (−0.02, 0.30) 0.11 (− 0.12, 0.33) 0.654 1.89 (1.48, 2.41) 1.66 (1.26, 2.2) 0.501 Epilepsy 0.18 (−0.17, 0.53) 0.34 (−0.21, 0.88) 0.312 1.47 (1.29, 1.68) 1.30 (1.13, 1.50) 0.203 Circulatory system Essential hypertension 0.15 (0.07, 0.24) 0.13 (0.06, 0.19) 0.284 2.14 (1.72, 2.68) 2.16 (1.66, 2.79) 0.978 Heart valve disorders 1.40 (−1.40, 4.20) 1.27 (−0.96, 3.50) 0.885 1.17 (1.11, 1.23) 1.21 (1.15, 1.29) 0.318 Acute cerebrovascular disease 0.04 (0.01, 0.06) 0.01 (−0.02, 0.05) 0.039 1.72 (1.23, 2.38) 1.26 (0.85, 1.86) 0.232 Others Injuries 16.35 (−5.98, 38.67) 14.63 (− 5.84, 35.10) 0.815 1.31 (1.29, 1.33) 1.29 (1.28, 1.31) 0.242 Poisoning 0.16 (−0.23, 0.56) 0.11 (− 0.43, 0.65) 0.741 2.02 (1.65, 2.48) 2.51 (2.03, 3.10) 0.150 ADHD attention deficit hyperactivity disorder, ASD autism spectrum disorder *p-value to test sex differences for SII and RII (sex differences were assessed by inserting a two-way interaction term between SEP and sex) Carrilero et al. BMC Public Health (2021) 21:1150 Page 8 of 14 Fig. 1 RII for each disease by sex in the population under 15 in Catalonia terms, TB (PAF% = 56.26, 95% CI: 43.03, 66.41 in boys Table 4). By contrast, food allergy showed a significant and PAF% = 51.95, 95% CI: 38.51, 62.45 in girls), intra- negative attributable population impact (PAF% = − 5.42, uterine hypoxia and birth asphyxia and trauma (PAF% = 95% CI: − 7.07, − 3.8 in boys and PAF% = − 4.46, 95% CI: 30.04, 95% CI: 25.40, 34.39 in boys and PAF% = 32.10, − 6.22, − 2.73 in girls). 95% CI: 26.54, 37.24 in girls), obesity (PAF% = 27.14, Figure 2 for boys and Fig. 3 for girls show three differ- 95% CI: 25.86, 28.39 in boys and PAF% = 30.31, 95% CI: ent inequality measures for each disease and sex. 28.77, 31.80 in girls), and short gestation low birth weight and foetal growth retardation (PAF% = 29.83, Discussion 95% CI: 26.78, 32.75 in boys and PAF% = 28.21, 95% CI: Main findings 24.98, 31.29 in girls). In absolute terms, the diseases or This study confirms that socioeconomic inequalities are risk factors with the highest potential of preventable in- present in a large number of diseases of different etiolo- dividuals affected due to the impact of SEP were derma- gies and levels of seriousness (from malignant neoplasms titis (PAFa = 15,345, 95% CI: 14457, 16,227 in boys and to dermatitis), in the entire population of children in PAFa = 19,027, 95% CI: 18128, 19,921 in girls), injuries Catalonia. The systematic pattern of socioeconomic in- (PAFa = 19,432, 95% CI: 18303, 20,555 in boys and equality observed highlights that, beyond the nature and PAFa = 14,758, 95% CI: 13714, 15,796 in girls), acute idiosyncrasy of each disease, 1) the entire child popula- bronquitis (PAFa = 14,082, 95% CI: 13174, 14,938 in tion is affected by this social phenomenon, 2) SEP plays boys and PAFa = 11,905, 95% CI: 11091, 12,713 in girls), a common role in their development, and 3) gender dif- and being overweight (PAFa = 10,905, 95% CI: 10280, 11, ferences in inequalities exist in different diseases and 524 in boys and PAFa = 10,872, 95% CI: 10299, 11,438 in risk factors. This is consistent with the findings of differ- girls). ent studies where social class and child health status In terms of population impact, 7.80% (95% CI: 7.53, were assessed [6, 7, 9, 27, 35]. 8.06) of the overall disease events analysed in boys and To calculate health inequalities and to enrich later in- 8.88% (95% CI: 8.58, 9.17) in girls would be avoided if all terpretations and findings, we calculated four summary children had the same disease rates as the medium-high measures of health inequalities between SEP levels in SEP group. That is translated into 80,188 disease events each disease and the burden of the diseases attributable (95% CI: 77456, 82,912) in boys and 74,921 disease to SEP. The purpose was to capture both absolute and events (95% CI: 72429, 77,405) in girls that would be po- relative inequality measures accounting for all SEP tentially preventable (data for the total burden of dis- groups and their size in the studied population. On the eases studied; for the PAF results of each disease, see other hand, absolute measures provided the total Carrilero et al. BMC Public Health (2021) 21:1150 Page 9 of 14 Table 4 Measures of SEP impact PAF% and PAFa of each disease by sex in children in Catalonia Disease PAF% (95% CI) PAFa (95% CI) Boys Girls Boys Girls Infectious diseases Tuberculosis 56.26 (43.03, 66.41) 51.95 (38.51, 62.45) 181 (139, 214) 171 (127, 205) Meningitis (bacterial or viral) 18.32 (5.88, 29.11) 7.69 (−9.09, 21.90) 93 (30, 148) 24 (−28, 67) Influenza 7.17 (6.13, 8.20) 7.83 (6.73, 8.91) 4540 (3882, 5191) 4450 (3827, 5065) Neoplasms Cancer of the brain and nervous system 0.54 (−19.66, 17.34) 6.69 (−14.89, 24.21) 1 (−44, 39) 13 (−29, 47) Leukaemia −1.77 (− 18.54, 12.63) 5.93 (− 13.30, 21.90) − 6 (− 60, 41) 14 (− 32, 53) Malignant neoplasms 7.51 (1.57, 13.10) 9.18 (2.85, 15.10) 166 (35, 290) 177 (55, 291) Anthropometrics Overweight 15.63 (14.74, 16.52) 18.44 (17.46, 19.40) 10,905 (10,280, 11,524) 10,872 (10,299, 1438) Obesity 27.14 (25.86, 28.39) 30.31 (28.77, 31.80) 9407 (8694, 9841) 7204 (6840, 7560) Mental health Mood disorders 20.11 (15.29, 24.65) 21.54 (16.96, 25.86) 619 (471, 759) 718 (565, 862) Adjustment and anxiety disorders 22.88 (21.42, 24.31) 23.30 (21.76, 24.81) 6964 (6520, 7400) 6290 (5873, 6699) ADHD 4.01 (2.31, 5.68) 7.34 (4.46, 10.13) 1031 (595, 1459) 658 (399, 908) ASD 7.04 (3.63, 10.33) 8.57 (0.84, 15.69) 459 (237, 673) 113 (11, 207) Autoimmune and respiratory diseases Acute bronchitis 10.30 (9.63, 10.96) 11.11 (10.35, 11.87) 14,082 (13,174, 14,983) 11,905 (11,091, 12,713) Chronic bronchitis 10.30 (9.27, 11.32) 11.52 (10.35, 12.68) 6540 (5887, 7187) 5665 (5089, 6234) Asthma 1.15 (0.03, 2.31) 5.16 (3.69, 6.61) 594 (16, 1196) 1714 (1225, 2194) Respiratory allergy 6.93 (6.01, 7.83) 9.59 (8.59, 10.58) 2335 (2026, 2641) 2295 (2056, 2532) Dermatitis 9.69 (9.13, 10.25) 11.61 (11.06, 12.15) 15,345 (14,457, 16,227) 19,027 (18,128, 19,921) Food allergy −5.42 (−7.07, −3.80) −4.46 (−6.22, −2.73) − 524 (− 683, − 367) − 401 (− 559, − 246) Cystic fibrosis −5.12 (− 32.35, 16.51) −8.90 (− 37.10, 13.50) −7 (− 43, 22) −11 (− 47, 17) Adverse birth outcomes Short gestation, low birth weight,foetal growth retardation 29.83 (26.78, 32.75) 28.21 (24.98, 31.29) 2053 (1843, 2254) 1757 (1556, 1949) Intrauterine hypoxia and birth asphyxia and trauma 30.04 (25.40, 34.39) 32.10 (26.54, 37.24) 915 (774, 1048) 675 (558, 783) Congenital anomalies 11.51 (10.55, 12.45) 8.19 (7.10, 9.26) 8305 (7615, 8988) 4742 (4115, 5362) Nervous system Paralysis 18.50 (10.39, 25.88) 11.37 (1.81, 20.00) 211 (118, 295) 98 (16, 173) Epilepsy 11.22 (6.86, 15.38) 6.11 (1.21, 10.78) 443 (270, 607) 196 (39, 346) Circulatory system Essential hypertension 24.81 (17.73, 31.28) 24.64 (16.36, 32.10) 351 (251, 443) 257 (171, 335) Heart valve disorders 5.62 (3.87, 7.34) 6.39 (4.43, 8.31) 1340 (921, 1750) 1218 (844, 1584) Acute cerebrovascular disease 17.09 (5.93, 26.93) 7.09 (−6.98, 19.31) 107 (37, 169) 30 (−30, 82) Others Injuries 7.54 (7.10, 7.98) 7.17 (6.67, 7.68) 19,432 (18,303, 20,555) 14,758 (13,714, 15,796) Poisoning 20.81 (14.22, 26.90) 27.82 (21.26, 33.84) 347 (237, 449) 442 (337, 537) Note: PAF% and PAFa were calculated using medium-high SEP category as a reference group ADHD attention deficit hyperactivity disorder, ASD autism spectrum disorder number of disease events affected by SEP and relative they provided a gradient that includes the entire popula- measures tend to quantify the association of SEP and the tion, being less biased than using pairwise measures in outcome. Summary measures, based on regression, take which only very low and high SEP would be taken into into account all SEP groups weighted according to their account. This last approach could be more affected by real size rather than an equal distribution. Therefore, undereported health outcomes, mainly in the high Carrilero et al. BMC Public Health (2021) 21:1150 Page 10 of 14 Fig. 2 RII (y axis), frequency (x axis) PAFa (bubble) for each disease in boys population under 15 years old in Catalonia SEP group, due to their use of private healthcare ser- on the identification of those diseases with a high social vices [26, 29]. factor in their construction and distribution. In concord- ance with other studies, the diseases that show the great- Comparison with other studies and interpretation of the est inequalities are TB, obesity, hypertension, adverse results birth outcomes, and mental health disorders [27, 38–41]. SEP, as a social determinant of health, influences the dis- TB is by far the disease with most inequalities in Catalo- tribution of diseases among the population, as shown in nia and elsewhere [38]. TB is related to poverty (children this and previous studies [6, 27, 36]. Although the path- from very low SEP levels are at least up to 8 times more ways by which SEP impacts on health are mostly indir- likely to have it than their most advantaged peers) and it ect, SEP influences factors such as nutrition, housing is particularly exacerbated in immigrant populations [42, conditions, and education, hence the degree of vulner- 43]. Screening programs and an improvement in work- ability and social exclusion of children [1]. ing and housing conditions stand out as the greatest Social vulnerabilities in childhood is a broad concept contributions to eradicating TB [38]. As in other studies that includes all the negative experiences that could which test inequalities in different health outcomes, affect children’s development and, therefore, their health. obesity (the most acute form of overweight) and hyper- However, income level could exacerbates or buffer the tension, both related to lifestyles, show a high associ- effect of the social vulnerabilities in lifestyle and health ation with SEP [27]. There is a lot of evidence which outcomes [1, 7]. All these social experiences in child- shows that diseases related to lifestyles are greatly im- hood impact on a crucial period of development through pacted by social determinants such as SEP or a parent’s different complex and inter-related pathways such as educational level, or nutrition and physical activity, biological embedding, material deprivation, psychosocial among others [15, 16, 27, 39]. Therefore, within a global or structural mechanisms. All these pathways, highly upward trend, the number of children who suffer from dependent on the family’s relative SEP, act simultan- this inequality is also increasing [17]. eously creating social gradients in present and future Special attention should be paid to inequalities in ad- health outcomes [1, 37]. verse birth outcomes. As our results reveal, they are The results observed in this study indicate that the broadly present [40] or even increase in countries similar gradients between SEP and health present different in- to Catalonia [44]. These outcomes are related to preg- tensities depending on the disease. This sheds more light nancy and delivery, which are periods of intense Carrilero et al. BMC Public Health (2021) 21:1150 Page 11 of 14 Fig. 3 RII (y axis), frequency (x axis) PAFa (bubble) for each disease in girls population under 15 years old in Catalonia surveillance by the healthcare system. This situation em- differences in inequalities in more pathologies in com- phasizes that other factors such as employment status or parison to boys. This finding points to an intersectional- SEP level (both individual and neighbourhood) are key ity between sex and SEP where the two axes of in explaining these inequities beyond the responsability inequality jointly create roles of multiplicative discrimin- of the health system [40, 44]. Regarding mental health ation and subordination [46]. disorders, our findings show that SEP inequalities stand This study brings attention to a possible gender bias in out in concordance with other studies [6, 27, 41]. Other paediatrics healthcare. Gender bias in paediatrics in- factors as mental health or the employment status of volves a number of different actors: the infant as a pa- parents (mainly of mothers) also play an important role tient, the parents who present the child’s symptoms, and [28] being particularly incisive in contexts of economic the medical professional who interprets the patient’s crisis [18]. Significant attention must be given to those narratives and behaviours. Several studies have revealed diseases that would potentially be most reduced by im- that girls versus boys receive less effort to obtain an ad- proving children’s SEP. These diseases are not those vanced diagnostic, a therapeutic intervention, or an ad- showing the highest inequalities but those that account equate pain assessment, have different hospitalisation for the largest number of preventable disease events rates for the same conditions and experience more pre- (mainly due to their high prevalence in childhood popu- conceptions about pathology patterns [22, 23, 47, 48]. lation), namely: dermatitis, injuries, acute bronchitis, SEP, sex, gender bias, and their intersections simultan- obesity, and being overweight. eously influence the process of disease construction via Previous studies on children have not taken into ac- diverse pathways and in differing intensities [21, 24]. count gender as an axis of inequality, assuming that the Gender bias is well known in adulthood but little re- social role of gender does not influence health inequal- search has been done on the phenomenon in childhood, ities in childhood. By contrast, our study has shown dif- as if it did not exist [31, 49]. Future research should ex- ferences in many of the measures calculated. In general plore further on gender-related health inequalities in terms, the PR or IR of boys compared to girls is higher, childhood. to the boys’ detriment. This finding is consistent with With regard to food allergy, other studies have also the slightly increased vulnerability in boys (focused in highlighted its direct SEP gradient [27]. An increasing the early ages) and the physiological differences between global trend awareness and the widespread screening of the sexes [21, 45]. However, in terms of inequalities, this food allergy supports our finding of a direct SEP gradi- study has found that girls suffer from significant ent [50]. High-SEP parents tend to be more concerned Carrilero et al. BMC Public Health (2021) 21:1150 Page 12 of 14 with identifying food allergies in their children and seek 30% of all children under the age of 15 use both private out more tests than the lowest-SEP parents, contributing and public healthcare (88% from medium and high SEP) to overdiagnosis in socioeconomically advantaged chil- [53]. This can lead to an underreporting of some dis- dren [51]. Other studies also add that part of these so- eases, especially those among the most frequent, less se- cioeconomic differences may be caused by vere and acute profile, such as respiratory diseases or underdiagnosis in disadvantaged groups [27], dermatitis. eventhough in our study population low SEP children do a higher number of visits to the healthcare system than Conclusion their advantatged peers [20]. Although health inequalities will be difficult to eliminate Our results confirm that, despite the important role of entirely, efforts must be made in all institutions to work universal healthcare coverage in guaranteeing free and actively toward eradicating such social injustice in order equal access to the health system, it does not assure to accomplish one of the SDGs, namely “Reduce in- achieving equity in health status. Thus, similar findings equality within and among countries”, by 2030 [10]. In have encouraged governments to include social determi- the current time, when we are facing a new economic nants as a main cause of health inequalities [9]. crisis resulting from the COVID-19 pandemic, which will likely increase poverty and socioeconomic inequal- Strengths and weaknesses of the study ities, this goal has only increased in importance. This study included a broad representation of the child- Socioeconomic inequalities in childhood not only hood pathology; 29 diseases or risk factors of different imply unequal health outcomes but also inequalities in etiologies, magnitudes, seriousness, and affecting diverse other indicators of wellbeing, educational attainment, systems of the human body. It provides high-value evi- and future career opportunities. It is clear that more at- dence of the broad impact of social determinants on tention is required in childhood to tackle the vicious in- health and a useful variety of inequality measures, abso- tergenerational circle of poverty and social exclusion lute and relative, with the intention of influencing popu- that begins in childhood [2]. lation and political decisions. Policies and programs focused on improving family’s Calculating the same inequality measures in a broad childhood context (i.e housing, nurturing, parent’s be- set of diseases on the same population increases the ro- haviours), specially for the most vulnerable, have been bustness of comparisons between diseases as an homo- identified as the most efficient ways to reduce health in- geneous methodology has been used, and as all the equalities in childhood and achieve a fairer society [3, 4]. population is affected by the same common external factors. Abbreviations This population-based study included the total popula- SEP: Socioeconomic position; SDG: Sustainable Development Goal; RII: Relative index of inequality; Catalan acronym RCA: Central Registry of tion under 15 years old in Catalonia, nearly 1,500,000 in- Insured Persons; Catalan acronym CMBD: Registry of the Minimum Basic dividuals over a 4-year period providing a large capacity Dataset; TB: Tuberculosis; PR: Prevalence ratio; IR: Incidence proportion ratio; to detect more individuals with low-prevalence diseases. PAF%: Population attributable fraction 21; SII: Slope index of inequality; PAFa: Attributable fraction absolute; ASD: Autism spectrum disorder; The study used individual-level data, which allowed ADHD: Attention deficit hyperactivity disorder economic and employment information for one of a child’s guardians to be linked with the child’s health sta- Supplementary Information tus. However, this data does not provide complete infor- The online version contains supplementary material available at https://doi. mation about household economic status or a more org/10.1186/s12889-021-11230-9. detailed segmentation of the SEP variable but it has been used successfully in different studies [20, 28]. Additional file 1. The SEP indicator used is based on the parent’s eco- nomic and employment situation, which is available Acknowledgements from the Catalan Department of Health databases. Other We thank Juan José García García, head of the paediatric service at Sant Joan de Déu Barcelona Hospital, for his help in assessing the health outcomes commonly used indicators such as parental education or construction. occupation were not available. Besides, income has proven to have a strong association with health and to Authors’ contributions influence a wide range of material circumstances with Substantial contributions to the conception or design of the work (all authors); acquisition and data extraction (NC, and ADB); statistical analyses direct implications for health [52]. (NC and ADB); interpretation of the data (all authors); drafting the work Medical diagnoses are based on contacts with the pub- (AGA, and NC); revising it critically for important intellectual content (AGA lic healthcare system. Even where universal healthcare and NC); final approval of the version to be published (all authors); agreement to be accountable for all aspects of the work (all authors). The access is granted, private and public health services co- corresponding author attests that all listed authors meet authorship criteria exist, especially for high SEP families. It is estimated that and that no others meeting the criteria have been omitted. All authors Carrilero et al. BMC Public Health (2021) 21:1150 Page 13 of 14 approved the final manuscript as submitted and agree to be accountable for Received: 23 February 2021 Accepted: 7 June 2021 all aspects of the work. References Author’s information 1. Pearce A, Dundas R, Whitehead M, Taylor-Robinson D. Pathways to This article is part of the Biomedicine PhD accomplished in the following inequalities in child health. Arch Dis Child. 2019;104(10):998–1003. https:// institutions: Agència de Qualitat i Avaluació Sanitàries de Catalunya, doi.org/10.1136/archdischild-2018-314808. Universitat Pompeu Fabra. Department of Experimental and Health Sciences 2. WHO Commission on the Social Determinants of Health. Closing the gap in (DCEXS) and Institut de Recerca de l’Hospital de la Santa Creu i Sant Pau. a generation. Health equity through action on the social determinants of health. 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