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Article

Examining the Association of Socioeconomic Position with Microcephaly and Delayed Childhood Neurodevelopment among Children with Prenatal Zika Virus Exposure

1
Department of Disease Control, Faculty of Infectious and Tropical Diseases, London School of Hygiene & Tropical Medicine, London WC1E 7HT, UK
2
Department of Infectious Disease Epidemiology, London School of Hygiene & Tropical Medicine, London WC1E 7HT, UK
3
MRC Integrative Epidemiology Unit, Population Health Sciences, Bristol Medical School, University of Bristol, Bristol BS8 2BN, UK
4
Fundação Oswaldo Cruz, Rio de Janeiro 21040-900, Brazil
5
Pediatrics, University of California, Los Angeles, CA 90095, USA
*
Authors to whom correspondence should be addressed.
Viruses 2020, 12(11), 1342; https://doi.org/10.3390/v12111342
Submission received: 30 September 2020 / Revised: 18 November 2020 / Accepted: 20 November 2020 / Published: 23 November 2020

Abstract

:
Increased rates of Zika virus have been identified in economically deprived areas in Brazil at the population level; yet, the implications of the interaction between socioeconomic position and prenatal Zika virus exposure on adverse neurodevelopmental outcomes remains insufficiently evaluated at the individual level. Using data collected between September 2015 and September 2019 from 163 children with qRT-PCR and/or IgM-confirmed prenatal exposure to Zika virus participating in a prospective cohort study in Rio de Janeiro, Brazil (NCT03255369), this study evaluated the relationships of socioeconomic indicators with microcephaly at birth and Bayley-III neurodevelopmental scores during the early life course. Adjusted logistic regression models indicated increased odds of microcephaly in children born to families with lower household income (OR, 95% CI: 3.85, 1.43 to 10.37) and higher household crowding (OR, 95% CI: 1.83, 1.16 to 2.91), while maternal secondary and higher education appeared to have a protective effect for microcephaly compared to primary education (OR, 95% CI: 0.33, 0.11 to 0.98 and 0.10, 0.03 to 0.36, respectively). Consistent with these findings, adjusted linear regression models indicated lower composite language (−10.78, 95% CI: −19.87 to −1.69), motor (−10.45, 95% CI: −19.22 to −1.69), and cognitive (−17.20, 95% CI: −26.13 to −8.28) scores in children whose families participated in the Bolsa Família social protection programme. As such, the results from this investigation further emphasise the detrimental effects of childhood disadvantage on human health and development by providing novel evidence on the link between individual level socioeconomic indicators and microcephaly and delayed early life neurodevelopment following prenatal Zika virus exposure.

1. Introduction

Zika virus (ZIKV) is a mosquito-borne flavivirus [1,2], principally transmitted by the Aedes aegypti vector. Ae. aegypti is an anthropophilic mosquito species with a high daily survival rate, capable of facilitating explosive arboviral epidemics in urban settings [3]. Vertical transmission of ZIKV during pregnancy has been associated with adverse developmental consequences in infected offspring, including microcephaly and other neurological impairments, which are collectively recognised as congenital Zika syndrome (CZS) [4].
Studies have demonstrated increased frequencies of ZIKV infection and CZS in economically deprived areas of Brazil at the population level [5,6]. While these studies play an important role in assessing the association between ZIKV and social conditions, the existing evidence base relies on ecological study designs with a geographically defined group as the unit of observation. Not only is ecological fallacy a potential limitation for interpreting associations, but socioeconomic risk factors at the individual level remain insufficiently identified and evaluated. In addition to congenital ZIKV infection, socioeconomic position (SEP) may also influence neurodevelopment. Children typically experience poorer health and developmental outcomes with higher levels of disadvantage [7]. Risk factors for cognitive and socioemotional developmental delays have been shown to include nutrient deficiencies and social and economic deprivation, whilst known protective factors comprise breastfeeding and maternal education [8].
This study investigates the associations between socioeconomic factors and two outcomes, microcephaly and neurodevelopmental delays, in a cohort of 163 infants with in utero ZIKV exposure, in the State of Rio de Janeiro, Brazil. We hypothesise that there may be a relationship between measures indicative of lower SEP and adverse neurodevelopmental outcomes among infants with prenatal exposure to ZIKV. A better understanding of the most at-risk groups in the event of a future ZIKV outbreak could help to drive policy solutions that encourage more targeted approaches to public health interventions aimed at reducing health and developmental inequities.

2. Materials and Methods

A prospective cohort study (ZIKAIFF) was conducted between September 2015 and September 2019 at Instituto Nacional de Saúde da Mulher, da Criança e do Adolescente Fernandes Figueira (IFF/Fiocruz), a reference hospital for women, children and adolescents in Rio de Janeiro, Brazil. Mothers of children in the cohort provided informed written consent for their children to participate. Local ethical approval was obtained for the protocol of the original cohort study titled “Exposição Vertical ao Zika Virus e suas conseqüências no neurodesenvolvimento da criança/Vertical Exposure to Zika Virus and Its Consequences for Child Neurodevelopment: Cohort Study in Fiocruz/IFF” by the Oswaldo Cruz Foundation (Fiocruz), Rio de Janeiro, Brazil (Plataforma Brasil, CAAE: 52675616.0.0000.5269 and registered in ClinicalTrials.gov (NCT03255369). Ethical approval for this project was granted on 10 May 2019 by the London School of Hygiene & Tropical Medicine MSc Research Ethics Committee (Ref: 15951).

2.1. Study Population

Participants in the ZIKAIFF cohort comprised children born between February 2016 and September 2017 [9], in the State of Rio de Janeiro, Brazil. The cohort included children with suspected prenatal ZIKV exposure, identified from two key sources: (i) those born to symptomatic women presenting with rash during pregnancy and (ii) those born to women referred to IFF/Fiocruz due to foetal abnormalities during pregnancy detected through ultrasound screening.
The present investigation was limited to the 163 livebirths (55.1%; 163/296 of the full cohort) with lab-confirmed prenatal exposure to ZIKV that participated in infant clinical assessment at birth, and if normocephalic, at least one subsequent neurodevelopmental evaluation with the Bayley-III instrument. For this analysis, in utero ZIKV exposure was confirmed through either (i) the detection of ZIKV RNA by qRT-PCR testing of maternal serum, urine, amniotic fluid, breast milk, and/or placenta samples or neonatal serum, urine and cerebrospinal fluid sample [10] or (ii) through the detection of IgM in neonatal serum samples using the Centers for Disease Control and Prevention (CDC) Zika IgM antibody capture enzyme-linked immunosorbent assay (MAC-ELISA) [11].

2.2. Exposures

Several primary exposures were investigated as potential socioeconomic risk markers at the individual level. These included maternal educational level (partial/completed higher, secondary or primary school education), maternal race/ethnicity (White Brazilians, mixed-race Afro-Brazilians, Black Afro-Brazilians and East Asian Brazilians), household monthly income (relative to the 2019 minimum wage of BRL998) (Classes A, B, C and D: >2× minimum wage and Class E: <2× minimum wage), household participation in the Bolsa Família conditional cash transfer social protection program (yes or no) and household crowding index (individuals in the house/bedrooms in the house), obtained from parent-reported data through survey questionnaires given to caregivers by clinical staff at IFF/Fiocruz in Rio de Janeiro, Brazil, upon enrolment in the cohort.

2.3. Outcomes

2.3.1. Infant Clinical Assessments

The outcome variable of microcephaly was defined as a head circumference Z score of more than two standard deviations (SD) below the mean for gestational age and sex, consistent with the latest Brazilian Ministry of Health’s case definition. Head circumference measurements were taken from all live newborns and evaluated using the INTERGROWTH-21st Global Perinatal Package [12]. All evaluations took place at IFF/Fiocruz in Rio de Janeiro, Brazil by paediatric specialists at birth.

2.3.2. Neurological Evaluations

Bayley-III assessments were offered to all normocephalic children. Bayley-III assessments of children born with microcephaly were not routinely undertaken as the functional challenges faced by children in this group precluded further assessment of developmental milestones using this instrument [13,14]. Bayley-III is an internationally accepted instrument used to assess the development of infants and young children aged between 1 and 42 months. The assessment and training materials have been translated into Brazilian Portuguese and validated for use in Brazil [15].
The Bayley-III scales derive a developmental quotient by evaluating three domains: the language scale, which assesses expressive and receptive language; the motor scale, which assesses fine and gross motor skills; and the cognitive scale [16]. Composite scores were obtained for each subset to determine performance compared with the normative population and presented as a continuous variable. They were scaled to a metric, with a mean of 100, SD of 15 and range of 40 to 160. Developmental delay was defined as “at risk” if performance was between 1 and 2 SD below the mean (i.e., a score of 70–85) and “severely delayed” if the score was more than 2 SD below the mean (i.e., a score <70).
For children who underwent repeated evaluations, the Bayley-III scores obtained at the oldest age were used in the current analysis. Assessments took place at IFF/Fiocruz and were performed by trained psychologists.

2.4. Additional Covariates

Further potential confounders and effect modifiers were considered and integrated into conceptual hierarchical frameworks (Figure 1). These were derived from the literature and through conversations with clinical staff at IFF/Fiocruz [17].
Since being a recipient of BF is conditional on having a low-income as well as school attendance, health monitoring and prenatal care attendance, household participation in BF was not considered a confounder when household income was the main exposure, as it was assumed on the causal pathway [18]. The variables indicating smoking, drug-taking and occupational exposure to toxic products during pregnancy, which may be influenced by SEP, were assumed on the causal pathway between SEP indicators and both outcome measures. Moderate exposure to maternal smoking, drug-taking and toxic products can impact foetal brain development and may consequently be risk factors for microcephaly and neurodevelopmental delays [19] and thus were not included in the multivariable analyses.

2.5. Data Cleaning and Missing Values

Data entry errors were checked as part of the quality assessment. Duplicates were removed and outliers queried and rectified at the study site. Missing data were explored and missingness patterns investigated (Table A1). The complete-case analysis was employed in final multivariable models.

2.6. Statistical Analysis

Multivariate regression analyses were conducted (logistic models for assessing microcephaly and linear models for the three continuous composite Bayley-III score outcomes: language, motor and cognitive). The variable indicating child’s sex was a priori forced into each of the multivariate models. Gestational age was a priori forced into multivariate linear models for continuous Bayley-III score outcomes.
Conceptual hierarchical frameworks aided in the determination of mediators and confounders when fitting models. To estimate the effect of individual level SEP risk factors on the odds of microcephaly, a forward selection approach was used. Primary exposure variables indicating SEP were used to initiate each model with the forced variables that were a priori determined. Potential confounders, including SEP variables that were not considered the main exposure of interest in that particular model, were then built into each model according to how much their inclusion in the model changed the effect estimate for the main exposure. Variables were added to models only if they changed the effect estimate by more than 10%. To avoid problems of data sparsity, models contained no more than five parameters, since there were 51 events of microcephaly. Multiple linear regression models were then fitted for each of the composite Bayley-III score outcomes with SEP exposure variables, the forced variables selected a priori and the strongest potential confounding variables, ensuring that there were at least five observations for each variable added to the model to mitigate sparse data bias. To assess consistency regarding direction and magnitude of estimates, sensitivity analyses were performed using data with participants with suspected prenatal exposure to ZIKV who did not have qRT-PCR or IgM confirmation. This dataset was larger (n = 286) and had 91 microcephaly cases. Data analysis was performed in Stata, version 13.0 (StataCorp., College Station, TX, USA)

3. Results

Of the 296 maternal-child dyads enrolled in the ZIKAIFF cohort, 256 (86.5%; 256/296) were qRT-PCR or IgM laboratory tested and 202 (68.2%; 202/296) had qRT-PCR (85.6%; 173/202) or IgM (36.1%; 73/202) confirmation for ZIKV. Of the confirmed cases, eight (4.0%; 8/202) of the children died prior to outcome ascertainment and 31 (15.3%; 31/202) of the normocephalic children were lost to follow-up. In total, 163 (55.1%; 163/296) participants of the total cohort were included in the final study sample (Figure 2).
The study sample comprised 84 (51.5%) females and 79 males (48.5%). Fifty-one (31.3%) had microcephaly at birth and 112 were normocephalic at birth. Children born with a normal head circumference were followed up with their last Bayley-III neurodevelopmental assessment performed at a median (IQR) age of 19.6 months (range: 4.9 to 40.1 months). The median (IQR) gestational age at delivery was 38 weeks (38–40 weeks) and birthweight was 3060 g (2675–3420 g). In total, 18.4% (30/163) had low birthweight (<2500 g). Mothers were aged between 17 and 43 years and lived in the State of Rio de Janeiro, Brazil at the time of enrolment. Amongst those with data collected on maternal education, 15.0% (22/147) of children were born to mothers with up to primary school education, 52.4% (77/147) with some or completed secondary school education and 32.7% (48/147) with some or completed higher education. Furthermore, 36.6% were (53/145) White Brazilians, 45.5% (66/145) mixed-race Afro-Brazilians, 15.9% (23/145) Black Afro-Brazilians and 2.1% (3/145) East Asian Brazilians. Over half of the participants were in Social Class E, receiving <2× minimum wage (50.8%; 67/132). In total, 19.6% (27/138) of the study population were recipients of Bolsa Família (Table 1).
There was a mean composite language score of 90.3 (SD ± 13.1), minimum and maximum of 47 and 115, a mean composite motor score 95.3 (SD ± 12.4), minimum and maximum of 50 and 124 and a mean composite cognitive score of 102.8 (SD ± 13.5), minimum and maximum of 65 and 145 (Figure 3). Among the 112 children with Bayley-III results, 25.9% (29/112) were at risk or severely delayed (i.e., 1 or more SD below the mean) for the composite language domain, 19.6% (22/112) were at risk or severely delayed for the composite motor domain and 10.7% (12/112) were at risk or severely delayed for the composite cognitive domain.
Crude analyses indicated strong evidence that children born into households with an income up to 2× minimum wage have 5.69 times (95% CI 2.43 to 13.33) the odds of having microcephaly compared to those born into a household with income over 2× minimum wage (Table 2). There was also a positive association between household participation in BF and the odds of microcephaly (OR, 95% CI: 2.55, 1.08 to 6.00). In addition, an increase in the level of maternal education, from primary to secondary school and to higher education, was strongly associated with a decrease in microcephaly odds (p < 0.001). The crude odds ratios for children with a mother with secondary school education and higher education compared with primary education were 0.37 (0.14, 0.99) and 0.12 (0.04, 0.38), respectively. Mothers who identified as Black Afro-Brazilian had the highest odds of having a child with microcephaly (OR, 95% CI: 3.55, 1.29 to 9.80), compared to the group with children born to mothers who identified as White Brazilian and East Asian Brazilian. In addition, there was evidence for a linear association between household crowding index (HCI) groups and the odds of microcephaly (OR, 95% CI: 1.79, 1.23 to 2.61) and no evidence for departures from linearity (p = 0.956).
Upon adjustment for child’s sex and household income, there was no statistical evidence of an association between race/ethnicity and microcephaly. The multivariate analysis indicated that having a household income of up to 2× minimum wage showed strong statistical evidence of an association with microcephaly (OR, 95% CI: 3.85, 1.43 to 10.37). Accounting for child’s sex and birthweight, lower maternal education was associated with an increase in microcephaly (p < 0.001). The adjusted odds for children with a mother with secondary school education and higher education compared with primary education were 0.33 (95% CI: 0.11 to 0.98) and 0.10 (95% CI: 0.01 to 0.36), respectively. After adjusting for child’s sex, maternal education and maternal parity, a linear trend was observed across the four household crowding index groups, such that each increase in household crowding index group (i.e., from least to most crowded) was associated with an 83% increase in the odds of microcephaly (OR, 95% CI: 1.83, 1.16 to 2.91) (Table 3). Consistent patterns of association were observed in sensitivity analyses including children without lab confirmation of prenatal ZIKV exposure (Table A2).
After adjusting for child sex, gestational age, maternal education, maternal race/ethnicity, household crowding index, maternal parity, previous miscarriage or abortion and birthweight, there was evidence of an association between household participation in Bolsa Família and a lower composite language score of −10.78 (95% CI: −19.87 to −1.69), a lower composite motor score of −10.45 (95% CI: −19.22 to −1.69) and a lower composite cognitive score of −17.20 (95% CI: −26.13 to −8.28) (Table 4). Bayley-III assessment scores did not appear to vary by other socioeconomic indicators in this study sample. Unadjusted estimates are presented in the appendices (Table A3).

4. Discussion

In a cohort of 163 infants with prenatal ZIKV exposure in Rio de Janeiro, Brazil, a consistent relationship between adverse neurodevelopmental outcomes and unfavourable socioeconomic indicators was observed. Specifically, these findings provide evidence of an association of microcephaly with lower household income, higher household crowding and lower maternal education. In line with these results, economically deprived children with prenatal ZIKV exposure also appeared to be at greater risk of delayed neurodevelopment during the early life course. Adjusted models provided statistical evidence of lower composite language, motor and cognitive scores in children whose families participated in the in the Bolsa Família social protection programme. Taken together, these findings reinforce the idea that early disadvantage can drive differential health and developmental outcomes [7].
Results from this study are consistent with previous research undertaken at the population level. An ecological analysis completed between 2015 and 2016 in Recife, Brazil, described a strong association between microcephaly from ZIKV infection and poor living conditions, such that only 2.0% of the microcephaly cases resided in the wealthiest districts [5]. Another ecological study conducted using socioeconomic and health status data from the five regions in Brazil reported a strong correlation between the distribution of ZIKV-related microcephaly cases and poverty as measured in an index (p < 0.0001) [20], suggesting the potential for co-acting socioeconomic factors in the microcephaly epidemic [21].
Adverse environmental conditions often cluster together in socially patterned ways [22]. People with low SEP are likely to live in adverse social circumstances, be of low birthweight and be exposed to poor diets [23]. A 1990–1991 cross-sectional study, investigating Aboriginal children under 2 years in Australia provided evidence that wasting was strongly associated with microcephaly on admission to a tertiary referral centre for diarrhoea, independent of intrauterine growth restriction and low birthweight. Low household income may drive food insecurity and thus malnutrition. Malnutrition, in important periods of intra- and extra-uterine development, could cause irreversible damage to intellectual potential and behaviour [24].
Often, where household crowding exists, neighbourhood overcrowding persists. The built environment in poor urban areas may also provide abundant habitats for mosquito proliferation through insufficient infrastructure [25]. In addition, housing can be seen as a key component of wealth as it often accounts for a large proportion of outgoings from income [26].
Education is a frequently used indicator of SEP with origins in the status domain of Weberian theory [26]. The variable of maternal education reflects mothers’ early life SEPs and captures their knowledge-related assets over the life course [26]. Inferences have been made in previous studies about how the underlying social environment, including low maternal education, may play a role in the development of neonatal microcephaly [27,28]. Two 2010 birth cohort studies conducted in Brazil concluded that low maternal schooling was consistently associated with microcephaly, suggesting that prior to the ZIKV epidemic, there may have been a silent endemic of microcephaly caused by other risk factors associated with poverty [28]. Crude analyses revealed a strong association between women who identified as Black Afro-Brazilian and having a child with microcephaly. After controlling for confounders, including household income, there was no statistical evidence of this association. This points to structural racism as a potential driver of neurodevelopmental disparities. Structural racism is defined by social epidemiologist, Nancy Krieger (2014) as “…ways in which societies foster [racial] discrimination… that in turn reinforce discriminatory beliefs, values, and distribution of resources” [29]. Many residents in Rio de Janeiro live in racialised and economically segregated areas of the city [30], which could be associated with health outcomes, including birth outcomes, as previously observed in the US context [31].
Furthermore, the findings from this study may be related to a lack of access to abortion services. Since abortion in Brazil is considered a crime against human life, except under exceptional circumstances, quantifying self-induced or unregulated abortion is extremely challenging [32]. Illegal options are available at a cost. Thus, one potential pathway for the outcomes observed is that those with lower household income may not have the means to pay for an abortion.
This investigation revealed lower composite language, motor and cognitive scores in children whose families were recipients of Bolsa Família. Whilst participation in Bolsa Família can be viewed as a proxy indicator for poverty as it is dependent on having a per capita monthly income ≤BRL 140 (US $35.00), it also indicates receipt of financial and social support. Those eligible for the programme must ensure compliance with selected activities, including schooling and vaccination for children and pre- and post-natal care for women [33]. This poverty-alleviating programme has the potential to improve poor health and development opportunities, as has been shown for diseases like leprosy [33,34]. An important concern in the current investigation may therefore be residual confounding. Thus, this warrants further investigation. Furthermore, eligibility assessments for this programme are made every two years; however, social circumstances may change over time. This highlights the challenges inherent in investigating social determinants of health without utilising a life course approach [22].
This investigation is a unique and important analysis. Whilst social determinants of ZIKV and CZS have been investigated primarily through ecological studies, this is the first study to describe the association of SEP at the individual level with microcephaly and delayed neurodevelopment following in utero exposure to ZIKV. Nevertheless, this study had important limitations. First, Rio de Janeiro presents a unique context of inequality, poverty, urban segregation and deficient infrastructure [35]. The results obtained from this study are therefore specific to this urban setting and thus may not be generalisable to rural communities in Brazil or indeed other urban environments outside of Brazil. Second, although a strength of this study is that it used stringent inclusion criteria and eligible infants were enrolled only if they had nucleic acid and/or serologic evidence of prenatal ZIKV exposure, it was not possible to confirm congenital ZIKV infection in all of the participating children. Third, the enrolment procedure may have introduced systematic error through selection bias. This dataset was biased towards children born with CZS, as women who were asymptomatic or who did not appear to have foetal abnormalities during pregnancy were not enrolled in the cohort. Whilst frequencies of outcomes are likely to be higher than the general population, the same selective forces within the study population that resulted in the outcomes of interest are expected to be similar across exposure groups. This is therefore unlikely to have distorted effect estimates. In addition, whilst the Unified Health System (Sistema Único de Saúde) has helped Brazil to progress towards universal health coverage, structural weaknesses as well as economic and political crises have resulted in disparities in access to effective care [36]. The poorest are less likely to frequent healthcare facilities and the wealthiest often utilise high-cost private clinics. Those of lower SEP not only experience access inequity but poorer knowledge of the full implications of ZIKV and reduced health-seeking behaviour [37]. Under-representation of the lowest and highest SEP categories may have resulted in different measurements of outcomes within these groups, though comparisons between them are still accurate. Fourth, if children did not appear to have microcephaly at birth, parents may have been reluctant to attend the hospital for further evaluations, as CZS is a highly stigmatising diagnosis [38]. This suggests likely attrition bias within the normocephalic group. If the participants with lower SEP who were lost to follow-up are at greater risk of neurodevelopmental delays, then the study will have underestimated the effect of low SEP. Furthermore, hospital visits are time-consuming and economic losses may occur following time off work. Fifth, self-reporting of the exposure variables may have resulted in non-differential social desirability bias, particularly with respect to reporting income, drug-taking and smoking. Since this would increase the similarity between the exposed and non-exposed, any true association between low SEP and the outcome measures would be attenuated. This is not likely to have been exacerbated by requirements in place to be a beneficiary of Bolsa Família, since decisions are based on data captured within the national administrative database, Cadastro Único para Programas Sociais [33]. Finally, sudden and unexpected disease outbreaks, such as the recent ZIKV epidemic, have erupted in settings with notable resource constraints [39,40]. Strategic decisions are thus required to optimise available resources but may lead to missing data, limited sample sizes and losses to follow-up [39]. Conducting analyses on clinical studies in these climates, as this study does, whilst challenging, provides important insight into novel and unknown disease patterns and global health problems.

5. Conclusions

This report provides new evidence of the link between social determinants and the risk of microcephaly and delayed childhood neurodevelopment following in utero exposure to ZIKV. These findings suggest that targeting interventions, such as culturally appropriate and economically viable vector control measures, to socioeconomically marginalised groups may aid in reducing the disease burden of ZIKV in the case of a future epidemic. More broadly, this research also reflects the need in ZIKV research to expand the focus from a strictly biomedical paradigm of health and developmental outcomes, in which diagnosis and treatment focus on an individual’s biology, to an integrated approach that addresses social factors [41]. Further research will be valuable for delineating the mechanisms by which low SEP may exert corrosive effects following prenatal exposure to ZIKV.

Author Contributions

Conceptualisation, G.M.P., E.B.B., M.E.M.; Methodology, G.M.P., E.B.B.; Software, G.M.P.; Validation, E.B.B.; Formal analysis, G.M.P., Investigation, G.M.P.; Resources, M.E.M., Z.V., P.B.; Data Curation, Z.V.; Writing—Original Draft Preparation, G.M.P.; Writing—Review and Editing, G.M.P., S.C.F., N.S.C., Z.V., P.B., K.N.-S., E.B.B., M.E.M.; Visualisation, G.M.P., E.B.B., M.E.M.; Supervision, E.B.B., M.E.M.; Project Administration, G.M.P. All authors have read and agreed to the published version of the manuscript.

Funding

This research was funded by the European Union’s Horizon 2020 research and innovation programme, ZikaPLAN, under Grant Agreement No. 734584; Wellcome Trust & the UK’s Department for International Development (205377/Z/16/Z); and Fiocruz PIP/IFF program, CNPq 441098/2016-9 and 305090/2016-0; Faperj E_18/2015TXB.

Acknowledgments

We would like to thank the field team at IFF/Fiocruz for their guidance and support in consolidating and making available the data for this study and, in particular, Yasmin Villarosa, who regularly amended the database where discrepancies appeared.

Conflicts of Interest

The authors declare no conflict of interest. The funders had no role in the design of the study; in the collection, analyses, or interpretation of data; in the writing of the manuscript, or in the decision to publish the results.

Appendix A

Table A1. Missingness patterns with percentages of missing data for each variable and baseline information stratified into two groups: cases with complete data and cases with missing data (n = 163).
Table A1. Missingness patterns with percentages of missing data for each variable and baseline information stratified into two groups: cases with complete data and cases with missing data (n = 163).
VariableCategoryTotal, No. % Non-Missing DataCases with Complete Data No. (%) n = 83Cases with Missing Data No. (%) p Value
Characteristics of children
Child sexFemale163100%41430.578
Male 4237
Characteristics of mothers
Maternal educational levelPrimary school, including partial14790%1660.119
Secondary school, including partial 3839
Higher education, including partial 2910
Maternal race/ethnicityWhite Brazilian and East Asian Brazilian14589%34220.645
Mixed-race Afro-Brazilian 3531
Black Afro-Brazilian 149
Maternal parity≤115193%41400.291
2 3218
3+ 1010
Previous miscarriage or abortionNo14388%69480.632
Yes 1412
Trimester of pregnancy with rashFirst13080%39170.443
Second 3019
Third 1411
Did the mother smoke during pregnancyNo14589%79600.634
Yes 42
Did the mother use drugs during pregnancyNo14690%80580.256
Yes 35
Occupational exposure to toxic products during pregnancyNo14388%65460.816
Yes 1814
Characteristics of household
Household monthly income (relative to minimum wage of BRL998)Class A: >20× minimum wage13281%38290.684
Class B: 10–20× minimum wage 52
Class C: 4–10× minimum wage 126
Class D: 2–4× minimum wage 2612
Class E: <2× minimum wage 3829
Household participation in Bolsa Família (government cash transfer scheme)No13885%67610.513
Yes 1611
Household crowding index (individuals in the house / rooms in the house)<0.513683%23150.584
0.5–0.75 2521
0.75–1.0 2310
1.0+ 127

Appendix B

Table A2. Multivariate associations of socioeconomic indicators with microcephaly cases in children with and without qRT-PCR or IgM confirmation with suspected prenatal ZIKV exposure (n = 286).
Table A2. Multivariate associations of socioeconomic indicators with microcephaly cases in children with and without qRT-PCR or IgM confirmation with suspected prenatal ZIKV exposure (n = 286).
VariableCategoryAdjusted Odds Ratio (95% CI)p Value *
Maternal educational level a
n = 240
Primary school, including partial1<0.001
Secondary school, including partial0.71 (0.33, 1.54)
Higher education, including partial0.22 (0.09, 0.55)
Maternal race/ethnicity b
n = 212
White Brazilians and East Asian Brazilians10.526
Mixed-race Afro-Brazilians0.83 (0.34, 1.99)
Black Afro-Brazilians0.67 (0.34, 1.35)
Household monthly income (relative to minimum wage) c
n = 204
Classes A, B, C and D: >2× min wage10.004
Class E: <2× min wage2.71 (1.36, 5.43)
Household participation in Bolsa Família (government cash transfer) scheme d
n = 224
No10.371
Yes1.35 (0.70, 2.62)
Household crowding index (individuals in the house/rooms in the house) e
n = 207
Linear trend across four household crowding index groups (<0.5, 0.5–0.75, 0.75–1.0, 1.0+)1.48 (1.06, 2.09)0.021
a adjusted for child’s sex and birthweight. b adjusted for child’s sex and household income. c adjusted for child’s sex, household crowding index and maternal education. d adjusted for child’s sex, maternal education and previous miscarriage or abortion. e adjusted for child’s sex, maternal education and maternal parity * The likelihood ratio test was used to assess the strength of the evidence of an association between exposure variables and outcomes.

Appendix C

Table A3. Unadjusted estimated differences in Bayley-III assessment scores according to risk factors, in the normocephalic study sample (n = 112).
Table A3. Unadjusted estimated differences in Bayley-III assessment scores according to risk factors, in the normocephalic study sample (n = 112).
VariableCategoryNo. (Col %) of Children Taking Bayley-III TestsUnadjusted Estimated Difference in Language Scores (95% CI)p Value */**Unadjusted Estimated Difference in Motor Scores (95% CI)p Value */**Unadjusted Estimated Difference in Cognitive Scores (95% CI)p Value */**
Characteristics of children
SexFemale57 (50.9%)(Reference)0.429(Reference)0.937(Reference)0.752
Male55 (49.1%)−1.97 (−6.90, 2.96) −0.19 (−4.84, 4.47) 0.81 (−4.28, 5.90)
Characteristics of mother
Educational levelPrimary school, including partial9 (8.0)(Reference)0.459(Reference)0.94(Reference)0.139
Secondary school, including partial50 (44.6%)2.34 (−7.00, 11.69) −0.87 (−9.84, 8.10) −3.63 (−12.92, 5.65)
Higher education, including partial41 (36.6%)5.03 (−4.47, 14.53) 0.01 (−9.11, 9.13) 1.79 (−7.65, 11.23)
Missing12 (10.7%)
Race/ethnicityWhite Brazilians and East Asian Brazilians41 (36.6%) (Reference)0.55(Reference)0.369(Reference)0.947
Mixed-race Afro-Brazilians47 (42.0%)−2.78 (−8.32, 2.77) 3.67 (−1.62, 8.96) 0.74 (−4.90, 6.38)
Black Afro-Brazilians10 (8.9%)−3.51 (−12.67, 5.64) 3.42 (−5.31, 12.15) 1.29 (−8.−1, 10.60)
Missing14 (12.5%)
Parity≤157 (50.9%)(Reference)0.211(Reference)0.007(Reference)0.566
234 (30.4%)0.66 (−4.97, 6.30) −7.32 (−12.49, −2.16) 0.93 (−4.92, 6.77)
3+13 (11.6%)7.10 (−0.89, 15.10) 3.04 (−4.28, 10.37) 4.47 (−3.82, 12.76)
Missing8 (7.1%)
Previous miscarriage or abortionNo80 (71.4%)(Reference)0.62(Reference)0.552[Reference)0.932
Yes16 (14.3%)1.76 (−5.27, 8.79) −2.04 (−8.81, 4.74) −0.31 (−7.56, 6.93)
Missing16 (14.3%)
Trimester of pregnancy with rashFirst25 (22.3%)(Reference)0.138(Reference)0.037(Reference)0.523
Second46 (41.1%)−0.30 (−6.81, 6.21) −6.25 (−12.26, −0.23) −0.39 (−6.94, 6.16)
Third23 (20.5%)−6.56 (−14.13, 1.01) −8.72 (−15.71, −1.73) −3.87 (−11.48, 3.75)
Missing18 (16.1%)
Smoke during pregnancyNo96 (85.0%)(Reference)1(Reference)−0.409(Reference)0.944
Yes3 (2.7%)0.00 (−15.21, 15.22) −5.63 (−19.12, 7.86) −0.54 (−15.87, 14.79)
Missing14 (12.4%)
Drug use during pregnancyNo95 (84.8%)(Reference)0.121(Reference)0.797(Reference)0.818
Yes3 (2.7%)−9.30 (−21.09, 2.49) 1.47 (−9.86, 12.81) −1.39 (−13.38, 10.60)
Missing14 (12.5%)
Occupational exposure to toxic products during pregnancyNo74 (66.1%)(Reference)0.735(Reference)0.404(Reference)0.611
Yes22 (19.6%)1.09 (−5.26, 7.44) 2.54 (−3.49, 8.57) 1.65 (−4.78, 8.09)
Missing16 (14.3%)
Characteristics of household
Monthly income (relative to minimum wage)Classes A, B, C and D: > 2× min wage56 (50.0%)(Reference)0.169(Reference)0.895(Reference)0.460
Class E: < 2× Min wage35 (31.3%)−4.03 (−9.79, 1.74) −0.36 (−5.84, 5.12) −2.16 (−7.95, 3.63)
Missing21 (18.8%)
Participation in Bolsa FamíliaNo78 (69.6%)(Reference)0.078(Reference)0.039(Reference)0.019
Yes13 (11.6%)−7.05 (−14.92, 0.81) −7.79 (−15.20, −0.39) −9.42 (−17.23, −1.61)
Missing21 (18.8%)
Household crowding index<0.531 (27.7%)(Reference)0.76(Reference)0.212(Reference)0.280
0.5–0.7533 (29.5%)−0.74 (−7.33, 5.85) 5.17 (−0.99, 11.34) 5.97 (−0.66, 12.59)
0.75–1.020 (17.9%)−0.34 (−7.90, 7.22) 0.94 (−6.13, 8.00) 3.72 (−3.88, 11.31)
1.0+8 (7.1%)−5.57 (−16.02, 4.89) 7.89 (−1.88, 17.65) 7.22 (−3.29, 17.72)
Missing20 (17.8%)
* p values do not include missing data categories ** The likelihood ratio test was used to assess the strength of the evidence of an association between exposure variables and outcomes.

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Figure 1. Conceptual frameworks for the association between the exposures of interest; social determinants and the outcomes; microcephaly (a) and delayed neurodevelopment (b) following in utero exposure to ZIKV.
Figure 1. Conceptual frameworks for the association between the exposures of interest; social determinants and the outcomes; microcephaly (a) and delayed neurodevelopment (b) following in utero exposure to ZIKV.
Viruses 12 01342 g001
Figure 2. Flow diagram for cohort selection based on study inclusion and exclusion criteria.
Figure 2. Flow diagram for cohort selection based on study inclusion and exclusion criteria.
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Figure 3. Histograms of composite language (a), motor (b) and cognitive (c) scores from Bayley-III assessments (thick red lines indicate the mean in a normative population (100) and dotted red lines indicate the threshold for developmental delay (at risk or severely delayed) at 1 or more SD below the mean (i.e., a score ≤85)).
Figure 3. Histograms of composite language (a), motor (b) and cognitive (c) scores from Bayley-III assessments (thick red lines indicate the mean in a normative population (100) and dotted red lines indicate the threshold for developmental delay (at risk or severely delayed) at 1 or more SD below the mean (i.e., a score ≤85)).
Viruses 12 01342 g003aViruses 12 01342 g003b
Table 1. Baseline distribution of selected cohort characteristics (n = 163).
Table 1. Baseline distribution of selected cohort characteristics (n = 163).
VariableCategoryTotal, No.No. (col%)/ Median (IQR)
Characteristics of children
SexFemale16384 (51.5%)
Male 79 (48.5%)
Gestational age (weeks) 16338 (38–40)
Birthweight (g) 1633060 (2675–3420)
Age at last Bayley-III test (months) 11219.6 (12.8–36.0)
Characteristics of mothers
Age at enrolment (years)Median (IQR)12630.8 (23.6–34.7)
Educational levelPrimary school, including partial14722 (15.0%)
Secondary school, including partial 77 (52.4%)
Higher education, including partial 48 (32.7%)
Race/ethnicityWhite Brazilians14553 (36.6%)
Mixed-race Afro-Brazilians 66 (45.5%)
Black Afro-Brazilians 23 (15.9%)
East Asian Brazilians 3 (2.1%)
Parity≤115181 (53.6%)
2 50 (33.1%)
3+ 20 (13.3%)
Previous miscarriage or abortionNo143117 (81.8%)
Yes 26 (19.2%)
Trimester of pregnancy with rashFirst13056 (43.1%)
Second 49 (37.7%)
Third 25 (19.2%)
Smoking during pregnancyNo145139 (95.9%)
Yes 6 (4.1%)
Drug use during pregnancyNo146138 (94.5%)
Yes 8 (5.5%)
Occupational exposure to toxic products during pregnancyNo143111 (77.6%)
Yes 32 (22.4%)
Characteristics of household
Monthly income (relative to 2019 minimum wage of BRL 998)Class A: >20× minimum wage1322 (1.5%)
Class B: 10–20× minimum wage 7 (5.3%)
Class C: 4–10× minimum wage 18 (13.6%)
Class D: 2–4× minimum wage 38 (28.8%)
Class E: <2× minimum wage 67 (50.8%)
Participation in Bolsa FamíliaNo138111 (80.4%)
Yes 27 (19.6%)
Household crowding index<0.5013638 (27.9%)
0.50–0.75 46 (33.8%)
0.75–1.00 33 (24.3%)
1.00+ 19 (14.0%)
Table 2. Baseline distribution of child, maternal and household characteristics with crude odds ratios of microcephaly in children exposed to ZIKV in utero (n = 163).
Table 2. Baseline distribution of child, maternal and household characteristics with crude odds ratios of microcephaly in children exposed to ZIKV in utero (n = 163).
VariableCategoryNumber of Children Exposed to ZIKV In Utero No. (Row %) of Exposed Children with MicrocephalyCrude Odds Ratio (95% CI)p Value */**
Characteristics of children
SexFemale8427 (32.1%)1 0.808
Male7924 (30.4%)0.92 (0.47, 1.79)
Characteristics of mothers
Educational levelPrimary school, including partial2213 (59.1%)1 <0.001
Secondary school, including partial7727 (35.1%)0.37 (0.14, 0.99)
Higher education, including partial487 (14.6%)0.12 (0.04, 0.38)
Missing164 (25.0%)
Race/ethnicityWhite Brazilian and East Asian Brazilian5615 (26.8%)1 0.038
Mixed-race Afro-Brazilian6619 (28.8%)1.10 (0.50, 2.45)
Black Afro-Brazilian2313 (56.5%)3.55 (1.29, 9.80)
Missing184 (22.2%)
Parity≤18124 (29.6%)10.887
25016 (32.0%)1.12 (0.52, 2.39)
3+207 (35.0%)1.28 (0.45, 3.60)
Missing124 (33.3%)
Previous
miscarriage or abortion
No11737 (31.6%)1 0.506
Yes2610 (38.5%)1.35 (0.56, 3.26)
Trimester of pregnancy
with rash
First5631 (55.4%)1 <0.001
Second493 (6.1%)0.05 (0.01, 0.19)
Third252 (8.0%)0.07 (0.02, 0.33)
Missing3315 (45.5%)
Smoking during
pregnancy
No13944 (31.7%)1 0.363
Yes63 (50.0%)2.16 (0.42, 11.13)
Missing184 (22.2%)
Drug use during
pregnancy
No13844 (31.9%)1 0.744
Yes83 (37.5%)1.28 (0.29, 5.61)
Missing174 (23.5%)
Occupational exposure
to toxic products
during pregnancy
No11137 (33.3%)10.824
Yes3210 (31.3%)0.90 (0.39, 2.12)
Missing204 (20.0%)
Characteristics of household
Income per month (relative to minimum
wage)
Classes A, B, C and D: >2× min wage659 (13.8%)1 <0.001
Class E: <2× min wage6732 (47.8%)5.69 (2.43, 13.33)
Missing3110 (32.3%)
Participation in Bolsa FamíliaNo11133 (29.7%)10.033
Yes2714 (51.9%)2.55 (1.08, 6.00)
Missing254 (16.0%)
Household crowding
index
<0.5387 (18.4%)10.081
0.5–0.754613 (28.3%)1.74 (0.62, 4.94)
0.75–1.03313 (39.4%)2.88 (0.98, 8.45)
1.0+1911 (57.9%)6.09 (1.79, 20.74)
Missing277 (25.9%)
* p values do not include missing data categories. ** The likelihood ratio test was used to assess the strength of the evidence of the association between exposure variables and outcomes.
Table 3. Multivariate associations of socioeconomic indicators with microcephaly cases.
Table 3. Multivariate associations of socioeconomic indicators with microcephaly cases.
VariableCategoryAdjusted Odds Ratio (95% CI)p Value *
Maternal educational level a
n = 147
Primary school, including partial1 <0.001
Secondary school, including partial0.33 (0.11, 0.98)
Higher education, including partial0.10 (0.03, 0.36)
Maternal race/ethnicity b
n = 129
White Brazilian and East Asian Brazilian10.439
Mixed-race Afro-Brazilian0.89 (0.35, 2.27)
Black Afro-Brazilian1.79 (0.55, 5.86)
Household monthly income c
n = 122
Classes A, B, C and D: > 2× min wage 1 0.006
Class E: <2× min wage3.85 (1.43, 10.37)
Household participation in Bolsa Família d
n = 135
No
Yes
1
1.74 (0.69, 4.37)
0.239
Household crowding index e
n = 129
Household crowding index groups (<0.5, 0.5–0.75, 0.75–1.0, 1.0+)1.83 (1.16, 2.91)0.008
a adjusted for child’s sex, birthweight; b adjusted for child’s sex, household income; c adjusted for child’s sex, household crowding index, maternal education; d adjusted for child’s sex, maternal education, previous miscarriage or abortion; e adjusted for child’s sex, maternal education, maternal parity; * The likelihood ratio test was used to assess the strength of the evidence of the association of exposure variables and outcomes.
Table 4. Adjusted estimated differences in Bayley-III assessment scores according to risk factors, in the normocephalic study sample (n = 112).
Table 4. Adjusted estimated differences in Bayley-III assessment scores according to risk factors, in the normocephalic study sample (n = 112).
Composite Language Composite Motor Composite Cognitive
VariablesCategoriesAdjusted Estimated Difference in Composite Scores (95% CI)p Value *Adjusted Estimated Difference in Composite Scores (95% CI)p Value *Adjusted Estimated Difference in Composite Scores (95% CI)p Value *
Maternal educational level a
n = 83
Primary school, including partial(Reference)0.821(Reference)0.975(Reference)0.200
Secondary school, including partial3.31(−7.96, 14.57) −0.21 (−10.69, 10.26) −4.19 (−15.09, 6.71)
Higher education, including partial3.00 (−8.61, 14.57) 0.51 (−10.27, 11.29) 1.80 (−9.41, 13.01)
Maternal race/ethnicity b
n = 76
White Brazilians and East Asian Brazilians (Reference)0.945(Reference)0.253(Reference)0.262
Mixed-race Afro-Brazilians0.88 (−6.29, 8.05) 2.86 (−3.97, 9.69) 4.56 (−2.33, 11.46)
Black Afro-Brazilians1.53 (−10.67, 13.73) 8.51 (−3.11, 20.13) 6.38 (−5.35, 18.11)
Household monthly income c
n = 78
Classes A, B, C and D: >2× min wage (Reference)0.411(Reference)0.594(Reference)0.905
Class E: <2× min wage2.77 (−4.58, 10.13) 1.72 (−5.35, 8.80) 0.41 (−7.12, 7.95)
Household participation in Bolsa Família d
n = 80
No
Yes
(Reference)
−10.78 (−19.87, −1.69)
0.011(Reference)
−10.45 (−19.22, −1.69)
0.011(Reference)
−17.20 (−26.13, −8.28)
<0.001
Household crowding index e
n = 76
Linear trend across four household crowding index groups (<0.5, 0.5–0.75, 0.75–1.0, 1.0+)−1.45 (−5.11, 2.20)0.3801.44 (−2.05, 4.92)0.3632.79 (−0.72, 6.30)0.082
a adjusted for child sex, gestational age, maternal race/ethnicity, household income, household participation in Bolsa Família, household crowding index. b adjusted for child sex, gestational age, maternal education, household income, household participation in Bolsa Família, household crowding index, maternal parity, previous miscarriage or abortion, birthweight. c adjusted for child sex, gestational age, maternal education, maternal race/ethnicity, household crowding index, maternal parity, previous miscarriage or abortion, birthweight. d adjusted for child sex, gestational age, maternal education, maternal race/ethnicity, household crowding index, maternal parity, previous miscarriage or abortion, birthweight. e adjusted for child sex, gestational age, maternal education, maternal race/ethnicity, household income, household participation in Bolsa Família, maternal parity, previous miscarriage or abortion, birthweight. * The likelihood ratio test was used to assess the strength of the evidence of the association between exposure variables and outcomes.
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MDPI and ACS Style

Power, G.M.; Francis, S.C.; Sanchez Clemente, N.; Vasconcelos, Z.; Brasil, P.; Nielsen-Saines, K.; Brickley, E.B.; Moreira, M.E. Examining the Association of Socioeconomic Position with Microcephaly and Delayed Childhood Neurodevelopment among Children with Prenatal Zika Virus Exposure. Viruses 2020, 12, 1342. https://doi.org/10.3390/v12111342

AMA Style

Power GM, Francis SC, Sanchez Clemente N, Vasconcelos Z, Brasil P, Nielsen-Saines K, Brickley EB, Moreira ME. Examining the Association of Socioeconomic Position with Microcephaly and Delayed Childhood Neurodevelopment among Children with Prenatal Zika Virus Exposure. Viruses. 2020; 12(11):1342. https://doi.org/10.3390/v12111342

Chicago/Turabian Style

Power, Grace M., Suzanna C. Francis, Nuria Sanchez Clemente, Zilton Vasconcelos, Patricia Brasil, Karin Nielsen-Saines, Elizabeth B. Brickley, and Maria E. Moreira. 2020. "Examining the Association of Socioeconomic Position with Microcephaly and Delayed Childhood Neurodevelopment among Children with Prenatal Zika Virus Exposure" Viruses 12, no. 11: 1342. https://doi.org/10.3390/v12111342

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