Associations between birth registration and early child growth and development: evidence from 31 low- and middle-income countries

Associations between birth registration and early child growth and development: evidence from 31... Background: Lack of legal identification documents can impose major challenges for children in low- and middle- income countries (LMICs). The aim of this study was to investigate the association between not having a birth certificate and young children’s physical growth and developmental outcomes in LMICs. Methods: We combined nationally representative data from the Multiple Indicator Cluster Surveys in 31 LMICs. For our measure of birth registration, primary caregivers reported on whether the child had a birth certificate. Early child outcome measures focused on height-for-age z-scores (HAZ), weight-for-age z-scores (WAZ), weight-for-height z-scores (WHZ), and standardized scores of the Early Childhood Development Index (ECDI) for a subsample of children aged 36–59 months. We used linear regression models with country fixed effects to estimate the relationship between birth registration and child outcomes. In fully adjusted models, we controlled for a variety of child, caregiver, household, and access to child services covariates, including cluster-level fixed effects. Results: In the total sample, 34.7% of children aged 0–59 months did not possess a birth certificate. After controlling for covariates, not owning a birth certificate was associated with lower HAZ (β = − 0.18; 95% CI: -0.23, − 0.14), WAZ (β = − 0.10, 95% CI: -0.13, − 0.07), and ECDI z-scores (β = − 0.10; 95% CI: -0.13, −0.07) amongchildrenaged36–59 months. Conclusion: Our findings document links between birth registration and children’s early growth and development outcomes. Efforts to increase birth registration may be promising for promoting early childhood development in LMICs. Keywords: Birth registration, Early child nutrition, Early child development, Multiple Indicator cluster surveys, Low- and middle-income countries Background Ensuring that all children survive and thrive, receive The United Nations Convention on the Rights of the good health care and education, and have equal chances Child entitles every child to be registered immediately to achieve their full developmental potential during their after birth [1]. Birth registration, an important measure of early years are also key pillars of the SDGs [5, 6]. More legal identity, is recognized in target 16.9 of the Sustain- specifically, the SDGs prioritize reducing malnutrition able Development Goals (SDGs), which aims to “provide (target 2.2) for the estimated 155 million children under-5 legal identity for all, including birth registration” by 2030 globally who were stunted in 2016 [7], and promoting [2]. Yet, globally nearly 230 million children under-5 have early childhood development (ECD; target 4.2) for the es- never been officially been registered [3], or formally recog- timated 250 million children under-5 globally at risk of nized by the state [4]. poor development [2, 8]. Over the past decade, several studies have attempted to determine the key risk factors and correlates of child undernutrition and poor develop- * Correspondence: jjeong@mail.harvard.edu ment outcomes in low- and middle-income countries Department of Global Health and Population, Harvard T.H. Chan School of Public Health, 665 Huntington Avenue, 11th floor, Boston, MA, USA (LMICs), generally highlighting the importance of fetal Full list of author information is available at the end of the article © The Author(s). 2018 Open Access This article is distributed under the terms of the Creative Commons Attribution 4.0 International License (http://creativecommons.org/licenses/by/4.0/), which permits unrestricted use, distribution, and reproduction in any medium, provided you give appropriate credit to the original author(s) and the source, provide a link to the Creative Commons license, and indicate if changes were made. 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. Jeong et al. BMC Public Health (2018) 18:673 Page 2 of 8 growth, poverty, poor water and sanitation, as well as in- ECD outcomes. We combined all nationally representative adequate home environments [9–11]. However, the role of surveys from MICS rounds 4and 5(2010–2014) that were birth registration has been largely absent in these prior publicly available prior to January, 2017. We restricted our global reviews on correlates of early child nutrition and sample to children who had data on birth registration and development outcomes. either data on anthropometric outcomes or data on the Lack of birth registration violates children’s fundamen- Early Childhood Development Index (ECDI), which is pri- tal rights, including their right to nationality, and may marily collected for preschool children aged 36–59 months. also hinder young children’s access to targeted health services and social welfare programs (e.g. cash transfer Outcomes schemes) and enrollment in school [12–17]. Without a We examined four child outcomes relating to early birth certificate, a child's exact age is challenging to nutrition and development: height-for-age z-scores prove, which is important for ensuring that children re- (HAZ), weight-for-age z-scores (WAZ), weight-for-height ceive age-appropriate recommended schedule of vacci- z-scores (WHZ), and ECDI z-scores. Z-scores for an- nations [14], applying correct growth standards to thropometric measures were computed using the 2006 estimate children's nutritional status (i.e., height-for-age WHO Multi-center Growth Reference Study standards or weight-for-age) [18, 19], and verifying that children [29]. Biologically implausible values (HAZ as <−6or>6, are at least a minimum age upon entering school. As WAZ as <− 6 or > 5, and WHZ as <− 5 or > 5) were ex- children grow older, a birth certificate can provide im- cluded based on WHO cutoffs [30]. portant documentation in protecting against child labor, Early child development was measured using the ECDI. trafficking, and sexual exploitation [1, 12]; all which are Developed by UNICEF for 3- and 4-year-olds surveyed in associated with poor child health and wellbeing out- the MICS household survey program, the ECDI is comes [20, 21]. Moreover, unregistered children are not comprised of 10 caregiver-reported, dichotomously-scored counted and thus excluded from civil registration sys- questions to assess 4 developmental domains: cognitive, tems, which provide governments with vital statistics for socioemotional, literacy-numeracy, and physical develop- allocating resources and monitoring programs and pol- ment. These 10 items were determined through icies that have direct implications for children’s nutrition multi-country field tests, validity, and reliability studies, and and development [22]. deliberation with experts [31]. This population measure of To date, much of the global literature on birth regis- ECD has been used in other recent studies [32, 33]. A com- tration has been at a macro-level: arguing principally posite score for ECD was created (ranging from 0 to 10) by from a rights-based legal approach and emphasizing the summing the number of positive responses across the normative importance of birth registration [23], or advo- literacy-numeracy, social-emotional, learning, and physical cating for the importance of civil registration and vital domain items, and normalized to a ECDI z-score for direct statistics systems [24, 25]. A growing body of evidence comparability and ease of interpretation to the standardized has identified predictors of birth registration in order to scale of HAZ, WAZ, and WHZ. develop strategies for increasing birth registration cover- age [13, 26–28]. While a few studies to date have exam- Independent variable ined associations between birth registration and children’s Our primary independent variable of interest was lack of early nutrition and growth outcomes in LMICs [12, 18], a birth certificate. In the MICS questionnaire, two items no study known to the authors has additionally explored directly capture birth registration: first, caregivers are the association between birth registration and ECD asked to show the interviewer the child’s birth certificate. outcomes in LMICs. Given existing research on the If a birth certificate is not available, caregivers are asked importance of birth registration, we hypothesized that not whether the child ever had a birth certificate, and if not, being registered would be negatively associated with early whether the child’s birth had been registered with the childhood growth and development outcomes in LMICs. civil authorities. For our empirical analysis, we created a no birth certificate indicator variable, which was coded 1 Methods if the child did not ever have a birth certificate and 0 if Data the child currently had or previously had a birth We used data from UNICEF’s Multiple Indicator Cluster certificate. Survey (MICS), an international household survey pro- gram that collects information about the health, nutrition, Covariates education, and development of children in LMICs. The We adjusted for a variety of child-, caregiver-, and MICS is unique for collecting and monitoring ECD in a household-level covariates. Child characteristics included standardized and comparable way across LMICs, and re- age (in months) and sex (male or female). Caregiver char- mains the primary data source to measure and monitor acteristics included maternal and paternal highest level of Jeong et al. BMC Public Health (2018) 18:673 Page 3 of 8 education (no formal education, primary, or secondary or magnitude of these associations increased by child age higher), maternal age (5-year age categories from 15 to (categorized in 12-month age groups) we re-specified 49 years), and maternal marital status (currently married, Model 4, excluding early childhood education attendance formerly married, or never married). Household character- as a utilization of service covariate. This allowed us to ex- istics included household wealth index (quintiles within plore the associations between not having a birth certifi- each country: calculated as a principal component of a cate and children’s HAZ and WAZ outcomes in a group of assets owned by the household [34]) and place of separate sample of younger children aged 0–35 months, residency (urban or rural). Utilization of child health and for whom anthropometric data, but not the ECDI, were learning services was measured by the number of vaccina- available. tions received (ranging from 0 to 4 for bcg and at least one dose of dpt/hepb, polio, and measles) and whether or not Results preschool-aged children attended an early education pro- A total of 157,336 children aged 0 to 59 months from 31 gram (asked only regarding children aged 36–59 months). countries were represented in the full sample. No signifi- cant differences were detected between the complete cases Analysis in theanalyticsample and theincomplete cases (N = We conducted a complete case analysis upon verifying 65,425, 29.4% of original sample) that were excluded due to that missingness was not systematic. We specified a series missing data on full covariates. Sample characteristics for of four linear regression models with varying controls for the total sample of children are presented in Table 1.The potential confounders and mediators to estimate the asso- average age of the child was 28 months, and nearly half of ciation between lack of birth registration and each of the thesamplewas female.Overall,28.5% of mothersand four outcome variables of interest: HAZ, WAZ, WHZ, 18.4% of fathers reported no formal education. The major- and ECDI z-score among children aged 36–59 months. ity of households (60.2%) resided in rural areas. Model 1 only adjusted for child age, sex, and country fixed Approximately one in three children under-5 (34.7%) effects. Model 2 further adjusted for all caregiver- and did not possess a birth certificate. The average proportion household-level demographic and socioeconomic covari- of children without a birth certificate varied across coun- ates (maternal and paternal education, maternal age, ma- tries, ranging from as low 0.2 and 0.5% in Ukraine and ternal marital status, household wealth index, and place of Thailand, respectively, (where nearly all children were reg- residency). Model 3 further adjusted for variables repre- istered) to as high as 80.8 and 95.0% in Guinea Bissau and senting utilization of services that may relate to both birth Malawi, respectively (Additional file 1). Children who did registration and ECD outcomes (children’s vaccinations not have a birth certificate were more likely to have par- and early childhood education programs). Finally, Model ents who were less educated, live in poorer households, 4 additionally included primary sampling unit (PSU)/clus- and reside in rural areas of the country (Table 1). ter-level fixed effects, which can account for other observ- The mean HAZ was − 1.01 (SD = 1.7), with 26.2% of able and unobservable differences in socioeconomic, children classified as stunted. The mean WAZ for chil- environmental, and institutional characteristics of local dren was − 0.58 (SD = 1.4), with 13.7% of infants exhibit- enumeration areas that are common to all respondents ing underweight. The mean WHZ for children was − from that area (i.e., local diet, community child health 0.01 (SD = 1.4), with 7.0% classified as wasted. The mean awareness campaigns, cultural and social norms, as well ECDI z-score was 0.00 (SD = 1.0). as within-cluster availability of birth registration and other Of this total sample, we primarily focused on social services). Standard errors across all models were 54,916 children aged 36 to 59 months in 24 LMICs, clustered at the PSU-level to account for the complex for whom full information was available across all MICS survey design. All analyses were conducted using variables of interest. Table 2 presents adjusted associ- Stata version 13 [35]. ations between a lack of birth certificate and preschool-aged children’s nutrition and development Sensitivity analyses and robustness checks outcomes across the four model specifications. In First, to assess whether pooled findings were robust, we models only adjusting for child age, sex, and conducted separate country-specific models (fully adjusted country-level fixed effects (Model 1), not having a Model 4) for the associations between lack of birth regis- birth certificate was negatively associated with chil- tration and each of the four child outcome variables; and dren’sHAZ (β = − 0.48; 95% CI: -0.52, − 0.43), WAZ employed random-effects meta-regressions to re-estimate (β = − 0.30; 95% CI: -0.33, − 0.27), and ECDI z-scores a pooled effect that accounts for the varying sample sizes (β = − 0.32; 95% CI: -0.34, − 0.29); associations how- across country surveys. Second, to examine whether not ever were not significant for WHZ (β = − 0.01; 95% having a birth certificate was related to child outcomes as CI: -0.04, 0.03). In models additionally adjusting for early as in the first 3 years of life and whether the caregiver and sociodemographic covariates (Model 2), Jeong et al. BMC Public Health (2018) 18:673 Page 4 of 8 Table 1 Full sample characteristics among children aged 0–59 months and by children’s birth certificate ownership Total (n = 157,336) Child does not have birth certificate Child has birth certificate (n = 54,605) (n = 102,731) % (95% CI) % (95% CI) % (95% CI) Covariates Female child 49.1 (48.9–49.4) 49.6 (49.2–50.0) 48.8 (48.5–49.1) Age of child, mean (SD), range 0–59 months 28.0 (16.7) 25.3 (16.4) 29.4 (16.6) Maternal education None 28.5 (27.9–29.1) 41.4 (40.4–42.4) 21.6 (21.1–22.2) Primary 33.1 (32.7–33.6) 36.7 (35.9–37.4) 31.2 (30.7–31.8) Secondary or higher 38.4 (37.8–39.0) 21.9 (21.2–22.6) 47.1 (46.5–47.8) Paternal education None 18.4 (17.9–18.9) 28.3 (27.3–29.2) 13.2 (12.7–13.6) Primary 30.7 (30.3–31.2) 35.4 (34.6–36.1) 28.3 (27.8–28.8) Secondary or higher 50.8 (50.3–51.4) 36.4 (35.5–37.2) 58.5 (58.0–59.1) Martial status Currently married/in union 99.8 (99.7–99.8) 99.7 (99.7–99.8) 99.8 (99.8–99.8) Formerly married/in union 0.1 (0.1–0.1) 0.2 (0.1–0.2) 0.1 (0.1–0.1) Never married/in union 0.1 (0.1–0.1) 0.1 (0.1–0.2) 0.1 (0.1–0.1) Maternal age 15–19 4.1 (4.0–4.2) 6.0 (5.7–6.2) 3.1 (3.0–3.2) 20–24 19.6 (19.3–19.9) 23.0 (22.5–23.4) 17.8 (17.5–18.2) 25–29 28.2 (27.9–28.5) 27.4 (27.0–27.9) 28.6 (28.2–28.9) 30–34 23.2 (22.9–23.5) 20.5 (20.1–20.9) 24.7 (24.3–25.0) 35–39 15.8 (15.6–16.1) 14.2 (13.8–14.6) 16.7 (16.4–17.0) 40–44 7.1 (7.0–7.3) 6.6 (6.4–6.9) 7.4 (7.2–7.6) 45–49 2.0 (1.9–2.0) 2.3 (2.2–2.5) 1.8 (1.7–1.9) Wealth quintile Poorest 18.7 (18.2–19.2) 22.4 (21.7–23.1) 16.8 (16.2–17.3) Poor 20 (19.6–20.3) 23.4 (22.8–24.0) 18.1 (17.7–18.5) Middle 19.6 (19.3–19.9) 21.4 (20.9–22.0) 18.6 (18.2–19.0) Rich 19.8 (19.5–20.2) 17.9 (17.3–18.5) 20.8 (20.4–21.3) Richest 21.9 (21.4–22.4) 14.8 (14.2–15.5) 25.7 (25.1–26.2) Rural residence 60.2 (59.4–61.0) 78.4 (77.3–79.5) 50.6 (49.6–51.5) Number of vaccines child received, mean (SD), 3.4 (0.8) 3.3 (0.9) 3.4 (0.8) range 0–4 Child currently attends ECE, among children 24.5 (23.9–25.0) 16.3 (15.4–17.1) 27.5 (26.9–28.2) aged 36–59 months Child outcomes HAZ, mean (SD) −1.01 (1.7) −1.49 (1.7) −0.75 (1.7) WAZ, mean (SD) −0.58 (1.4) −1.05 (1.4) − 0.32 (1.3) WHZ, mean (SD) −0.01 (1.4) − 0.29 (1.4) 0.15 (1.5) ECDI z-scores among children aged 36– 0.00 (1.0) −0.34 (0.9) 0.18 (1.0) 59 months, mean (SD) CI confidence interval, ECE early childhood education, ECDI Early Childhood Development Index, HAZ height-for-age z-scores, SD standard deviation, WAZ weight- for-age z-scores, WHZ weight-for-height z-scores Jeong et al. BMC Public Health (2018) 18:673 Page 5 of 8 Table 2 Associations between no birth certificate and children’s HAZ, WAZ, WHZ, and ECDI z-scores among children aged 36–59 months Child outcomes Model 1 Model 2 Model 3 Model 4 HAZ (n = 50,291) β of no birth certificate −0.48*** −0.26*** − 0.21*** −0.18*** 95% CI (−0.52, − 0.43) (− 0.30, − 0.22) (−0.25, − 0.17) (−0.23, − 0.14) WAZ (n = 50,531) β of no birth certificate − 0.30*** −0.15*** − 0.11*** −0.10*** 95% CI (−0.33, − 0.27) (− 0.18, − 0.11) (−0.14, − 0.08) (−0.13, − 0.07) WHZ (n = 50,178) β of no birth certificate − 0.01 0.02 0.03 0.02 95% CI (−0.04, 0.03) (−0.01, 0.06) (− 0.00, 0.07) (− 0.01, 0.06) ECDI z-score (n = 54,861) β of no birth certificate − 0.32*** −0.15*** − 0.10*** −0.10*** 95% CI (−0.34, − 0.29) (− 0.18, − 0.13) (−0.13, − 0.08) (−0.13, − 0.07) CI confidence interval, ECDI Early Childhood Development Index, HAZ height-for-age z-scores, WAZ weight-for-age z-scores, WHZ weight-for-height z-scores The table presents unweighted standardized mean differences in child growth and development outcomes for children aged 36–59 months in 31 countries who did not have a birth certificate. Model 1 only adjusted for child age, sex, and country-level fixed effects. Model 2 further adjusted for maternal age, maternal education, paternal education, household wealth quintiles, and urban/rural residency. Model 3 additionally adjusted for vaccinations and attendance in an early childhood education program. Model 4 additionally adjusted for primary sampling unit-level fixed effects. All standard errors were clustered at the primary sampling unit level. ***P-value < 0.001 associations were smaller in magnitude but remained In a separate sample of younger children aged 0– significant for HAZ (β = − 0.26; 95% CI: -0.30, − 0.22), 35 months (N = 102,488), the overall associations between WAZ (β = − 0.15; 95% CI: -0.18, − 0.11), and ECDI a lack of birth certificate and children’s HAZ and WAZ z-scores (β = − 0.15; 95% CI: -0.18, − 0.13). In models were smaller in magnitude, but also remained significant additionally adjusting for children’s utilization of (Additional file 6). In addition, findings indicated that the health and education services (Model 3), associations magnitude of these associations increased with child age: were further attenuated for HAZ (β = − 0.21; 95% CI: such that associations were strongest for 2-year-olds (as -0.25, − 0.17), WAZ (β = − 0.11; 95% CI: -0.14, − 0.08), compared to 1-year-olds or children under-1). and ECDI z-scores (β = − 0.10; 95% CI: -0.13, − 0.08). Finally, in models additionally accounting for PSU/ Discussion cluster-level fixed effects (Model 4), significant nega- Using data from 31 LMICs, our study revealed two main tive associations persisted between not having a birth findings. First, birth registration among the children certificate and children’sHAZ (β = − 0.18; 95% CI: under-5 was low in our pooled sample. Despite the rec- -0.23, − 0.14), WAZ (β = − 0.10, 95% CI: -0.13, − 0.07), ommendation for birth registration to occur in the first and ECDI z-scores (β = − 0.10; 95% CI: -0.13, − 0.07). few weeks or months of life, one in three children under-5 in the total sample were still without a birth Sensitivity analyses and robustness checks certificate. We also found inequalities in access to birth Overall pooled estimates based on meta-regression certificates by wealth, maternal and paternal education (using Model 4) were robust and comparable in magni- and rural residency. This is consistent with other global tude to findings from pooled analyses (presented above studies of birth registration that have described large in Table 2) for all outcomes. Significant relationships gaps in access to birth registration [36, 37]. were found for children’s HAZ (Additional file 2), WAZ Second, we found that not having a birth certificate (Additional file 3), and ECDI (Additional file 4); associa- was negatively associated with both preschool-aged chil- tions for WHZ (Additional file 5) were not significant. dren’s growth and developmental outcomes, or more While country specific results highlighted variation in specifically HAZ, WAZ, and ECDI z-scores. Our find- the associations across countries, point estimates were ings build upon the results of a prior study by Coman- largely consistent in magnitude and directionality across dini et al. [18] that documented a negative relationship countries for each outcome. Of note, three countries between birth registration and undernutrition among (Lebanon, Macedonia and Moldova) were exceptions, children aged 2-to-5 years in 37 sub-Saharan African which also had the smallest sample sizes and where only countries. In our study, we newly highlight associations less than 4% of children did not have birth certificates. between birth registration and ECD, as indexed by the Jeong et al. BMC Public Health (2018) 18:673 Page 6 of 8 ECDI; and with respect to both child growth and devel- birth registration reflects a household’ssocialconnected- opment outcomes, even after adjusting for additional co- ness or social status (which could be shaped by sociodemo- variates than considered in prior research. graphic factors that we do not include, e.g. ethnicity, caste, We did not find significant associations between birth or religion) which may serve as a proxy for marginalization registration and WHZ. One explanation could be the or how informed or empowered parents may be feel in fact that WHZ calculations do not require information accessing a range of formal and informal services. Future on age, which has been highlighted as more likely intro- research that investigates parental knowledge and attitudes ducing bias and error among unregistered children and regarding birth registration and more comprehensively as- driving underestimations of their undernutrition status sesses the linkages between birth registration and a wider [18]. Another likely explanation for the null association range of social services may better elucidate the factors that with WHZ could be the fact that wasting is an indicator underlie our exploratory findings. of acute malnutrition, often occurring suddenly due to While our results support robust associations in this contemporaneous shocks, such as infection or famine, pooled sample, it is important to note that the opportun- and largely explained by dietary diversity, food insecurity, ities afforded by a birth certificate vary considerably across and climate change [38, 39]. Moreover, the prevalence of country contexts. For instance, in Vietnam a birth certifi- wasting in our sampled countries was very low (mean of cate is necessary to enroll in both preschool and primary 7.0%, with prevalence of wasting > 10% in only 3 coun- school, while in Sierra Leone and India, national policy tries) and potentially too small to detect differences. mandates that birth certificates are not formally required at With respect to the likely mechanisms, we found that so- any stage of the education system [44]. Moreover, requiring cioeconomic factors (i.e., maternal and paternal education, a certificate to access services may disproportionately im- household wealth index, and place of residency) explained pact the most vulnerable groups within-countries [45]. Fu- nearly half of the unadjusted associations between birth ture research on birth registration should consider a registration and poor early child growth and development country’s legal and policy environment and examine how outcomes. Above and beyond household socioeconomic these associations with early child outcomes are similar or factors, children’s utilization of early health and learning different within and across LMICs and the proportion of services (i.e., child vaccinations and attendance in an early variance explained at the country-level (e.g., using multi- education programs) explained approximately a quarter to level models). a third of the remaining association between birth registra- Despite these policy differences across countries, our tion and child outcomes. Interestingly, we found that add- pooled findings indicate a significant negative relationship itionally controlling for cluster characteristics did not add between birth registration and child growth and develop- explanatory power, thereby minimizing the possibility that ment outcomes across LMICs, and the potential role of these associations are due to community characteristics socioeconomic factors in explaining a part of this relation- within clusters within countries. Prior studies have also ship. This suggests important links between birth registra- documented links between birth registration and children’s tion, social protection, and early child health and education healthcare utilization, school enrollment and completion, services, especially for the children living in the poorest and participation in social services (e.g., cash transfer pro- households. Research from Ghana has affirmed the benefits grams and government food programs) [12–14]. Our find- of incorporating birth registration into community health ings extend this evidence by demonstrating how such care and child health campaigns [40]. Moreover, the recent services do, in turn, explain a considerable proportion of Lancet ECD series has emphasized the need for multisec- the direct associations between birth registration and early toral approaches to coordinating ECD programs, particu- child nutrition and development outcomes. larly with the health and nutrition sectors [46, 47]. However, we found that significant associations persisted However, most ECD interventions and policies do not between birth registration and child outcomes, which were include birth registration as a core component [12–18]. unexplained by the covariates and cluster-fixed effects in- Future efforts should consider integrating birth registration cluded in our models. One possible explanation could be campaigns with other early childhood services and inter- that registration reflects some degree of parental invest- ventions to promote the development and well-being of ment in the child. If completing the registration process is young children. arduous, parents who register their children may be those Birth registration and the estimation of a child’sage is who have more time or financial resources that they are central to the very measurement of early childhood out- able to spend on their children (especially if registration in- comes: a precise measurement of age is needed to accur- volves traveling a distance or financial and opportunity ately measure HAZ and WAZ among children under-5. costs) [40–42], or those who are more motivated and com- Comandini and co-authors describe the negative effects of mitted to following through with formal registration appli- measurement error and age heaping in misestimating HAZ cation procedures [43]. Another possibility could be that and WAZ, especially among children without a birth Jeong et al. BMC Public Health (2018) 18:673 Page 7 of 8 certificate [18, 19]. Efforts to improve birth registration Acknowledgements We thank the United Nations Children’s Fund and individual countries for could also address the processes of imputing, estimating, collecting the MICS data. and guessing a child’s age in household surveys and im- prove the assessment of nutritional outcomes. Availability of data and materials The MICS data supporting the conclusions of this article are publically There are several limitations to this analysis. First, we available from UNICEF’s online database at, http://mics.unicef.org/surveys. were only able to pool data from countries for which the MICS data were available; therefore, our results may not be Authors’ contributions JJ, AB, and GF conceptualized the study. JJ conducted analyses. JJ and AB representative of LMICs as a whole. Second, although we drafted the manuscript. GF reviewed and edited the manuscript. All authors adjusted for a range of covariates and include cluster-level read and approved the final version submitted for publication. fixed effects, we were unable to control for other important Ethics approval and consent to participate variables, such as data on facility birth, maternal autonomy, This study was deemed exempt from ethics review by the Harvard T.H. Chan and access to other services. Third, both the ECDI and School of Public Health Institutional Review Board, as the MICS data used are birth registration were caregiver reported and may be sus- publicly available and fully de-identified. ceptible to recall bias. Fourth, measures of nutritional status Competing interests (e.g. height or weight for age) could be prone to bias among The authors declare that they have no competing interests. unregistered children, as their age cannot be verified [18]. Finally, the MICS are cross-sectional surveys, which pre- Publisher’sNote clude causal interpretation, determination of mediators, Springer Nature remains neutral with regard to jurisdictional claims in published maps and institutional affiliations. and directionality of the associations. Author details Department of Global Health and Population, Harvard T.H. Chan School of Conclusions Public Health, 665 Huntington Avenue, 11th floor, Boston, MA, USA. This study highlights gaps in birth registration for young Department of Social and Behavioral Sciences, Harvard T.H. Chan School of children in LMICs and finds that not having a birth cer- Public Health, Boston, USA. Swiss Tropical and Public Health Institute, Basel, Switzerland. University of Basel, Basel, Switzerland. tificate is negatively associated with early child growth and development outcomes. Early child health, nutrition, Received: 16 January 2018 Accepted: 24 May 2018 and education programs and policies should consider integrating birth registration – and child protection References more broadly – in order to ensure that every child is 1. Birth registration. https://www.unicef.org/protection/57929_58010.html. legally recognized and has a fair chance to achieve her 2. Sustainable Development Goals. https://sustainabledevelopment.un.org/sdgs. 3. Access the data: birth registration. https://data.unicef.org/topic/child- full developmental potential. protection/birth-registration. 4. Cappa C, Gregson K, Wardlaw T, Bissell S. Birth registration: a child's passport to protection. Lancet Glob Health. 2014;2(2):e67–8. Additional files 5. Daelmans B, Darmstadt GL, Lombardi J, Black MM, Britto PR, Lye S, Dua T, Bhutta ZA, Richter LM. Early childhood development: the foundation of Additional file 1: Country mean values for proportion of children not sustainable development. Lancet. 2017;389(10064):9–11. having a birth certificate, children’s HAZ, WAZ, WHZ, and ECDI z-score 6. Britto PR, Lye SJ, Proulx K, Yousafzai AK, Matthews SG, Vaivada T, Perez- values among children aged 0–59 months. (DOCX 96 kb) Escamilla R, Rao N, Ip P, Fernald LCH, et al. Nurturing care: promoting early Additional file 2: Figure of pooled and country-specific associations be- childhood development. Lancet. 2017;389(10064):91–102. tween no birth certificate and HAZ among children aged 36–59 months 7. UNICEF, WHO, World Bank. Joint child malnutrition estimates—levels and based on meta-regression model. (DOCX 718 kb) trends. Geneva: World Health Organization; 2017. 8. Lu C, Black MM, Richter LM. Risk of poor development in young children in Additional file 3: Figure of pooled and country-specific associations be- low-income and middle-income countries: an estimation and analysis at the tween no birth certificate and WAZ among children aged 36–59 months global, regional, and country level. Lancet Glob Health. 2016;4(12):e916–22. based on meta-regression model. (DOCX 732 kb) 9. Black RE, Victora CG, Walker SP, Bhutta ZA, Christian P, de Onis M, Ezzati M, Additional file 4: Figure of pooled and country-specific associations be- Grantham-McGregor S, Katz J, Martorell R, et al. Maternal and child tween no birth certificate and ECDI z-score among children aged 36– undernutrition and overweight in low-income and middle-income 59 months based on meta-regression model. (DOCX 749 kb) countries. Lancet. 2013;382(9890):427–51. Additional file 5: Figure of pooled and country-specific associations be- 10. 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Apland K, Blitz BK, Calabia D, Fielder M, Hamilton C, Indika N, Lakshman R, ECD: Early childhood development; ECDI: Early childhood development Lynch M, Yarrow E. Birth registration and children's rights: a complex story. index; HAZ: Height-for-age z-scores; LMICs: Low- and middle-income coun- UK: Woking; 2014. tries; MICS: Multiple indicator cluster survey; PSU: primary sampling unit; 13. Corbacho A, Osorio Rivas R. Travelling the distance: a GPS-based study of SDGs: Sustainable development goals; WAZ: Weight-for-age z-scores; the access to birth registration services in Latin America and the Caribbean. WHZ: Weight-for-height z-scores In: IDB Working Paper Series; 2012. Jeong et al. BMC Public Health (2018) 18:673 Page 8 of 8 14. Brito S, Corbacho A, Osorio R. Does birth under-registration reduce 40. Fagernas S, Odame J. Birth registration and access to health care: an childhood immunization? Evidence from the Dominican Republic. Health assessment of Ghana's campaign success. Bull World Health Organ. 2013; Economics Review. 2017;7(1):14. 91(6):459–64. 15. Pelowski M, Wamai RG, Wangombe J, Nyakundi H, Oduwo GO, Ngugi BK, 41. Adi AE, Abdu T, Khan A, Rashid MH, Ebri UE, Cockcroft A, Andersson N. Ogembo JG. How would children register their own births? Insights from a Understanding whose births get registered: a cross sectional study in survey of students regarding birth registration knowledge and policy Bauchi and Cross River states, Nigeria. BMC Res Notes. 2015;8:79. suggestions in Kenya. PLoS One. 2016;11(3):e0149925. 42. Duff P, Kusumaningrum S, Stark L. Barriers to birth registration in Indonesia. Lancet Glob Health. 2016;4(4):e234–5. 16. Porteus K, Clacherty G, Mdiya L, Pelo J, Matsai K, Qwabe S, Donald D. ‘Out of 43. Bennouna C, Feldman B, Usman R, Adiputra R, Kusumaningrum S, Stark L. 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Associations between birth registration and early child growth and development: evidence from 31 low- and middle-income countries

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Abstract

Background: Lack of legal identification documents can impose major challenges for children in low- and middle- income countries (LMICs). The aim of this study was to investigate the association between not having a birth certificate and young children’s physical growth and developmental outcomes in LMICs. Methods: We combined nationally representative data from the Multiple Indicator Cluster Surveys in 31 LMICs. For our measure of birth registration, primary caregivers reported on whether the child had a birth certificate. Early child outcome measures focused on height-for-age z-scores (HAZ), weight-for-age z-scores (WAZ), weight-for-height z-scores (WHZ), and standardized scores of the Early Childhood Development Index (ECDI) for a subsample of children aged 36–59 months. We used linear regression models with country fixed effects to estimate the relationship between birth registration and child outcomes. In fully adjusted models, we controlled for a variety of child, caregiver, household, and access to child services covariates, including cluster-level fixed effects. Results: In the total sample, 34.7% of children aged 0–59 months did not possess a birth certificate. After controlling for covariates, not owning a birth certificate was associated with lower HAZ (β = − 0.18; 95% CI: -0.23, − 0.14), WAZ (β = − 0.10, 95% CI: -0.13, − 0.07), and ECDI z-scores (β = − 0.10; 95% CI: -0.13, −0.07) amongchildrenaged36–59 months. Conclusion: Our findings document links between birth registration and children’s early growth and development outcomes. Efforts to increase birth registration may be promising for promoting early childhood development in LMICs. Keywords: Birth registration, Early child nutrition, Early child development, Multiple Indicator cluster surveys, Low- and middle-income countries Background Ensuring that all children survive and thrive, receive The United Nations Convention on the Rights of the good health care and education, and have equal chances Child entitles every child to be registered immediately to achieve their full developmental potential during their after birth [1]. Birth registration, an important measure of early years are also key pillars of the SDGs [5, 6]. More legal identity, is recognized in target 16.9 of the Sustain- specifically, the SDGs prioritize reducing malnutrition able Development Goals (SDGs), which aims to “provide (target 2.2) for the estimated 155 million children under-5 legal identity for all, including birth registration” by 2030 globally who were stunted in 2016 [7], and promoting [2]. Yet, globally nearly 230 million children under-5 have early childhood development (ECD; target 4.2) for the es- never been officially been registered [3], or formally recog- timated 250 million children under-5 globally at risk of nized by the state [4]. poor development [2, 8]. Over the past decade, several studies have attempted to determine the key risk factors and correlates of child undernutrition and poor develop- * Correspondence: jjeong@mail.harvard.edu ment outcomes in low- and middle-income countries Department of Global Health and Population, Harvard T.H. Chan School of Public Health, 665 Huntington Avenue, 11th floor, Boston, MA, USA (LMICs), generally highlighting the importance of fetal Full list of author information is available at the end of the article © The Author(s). 2018 Open Access This article is distributed under the terms of the Creative Commons Attribution 4.0 International License (http://creativecommons.org/licenses/by/4.0/), which permits unrestricted use, distribution, and reproduction in any medium, provided you give appropriate credit to the original author(s) and the source, provide a link to the Creative Commons license, and indicate if changes were made. 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. Jeong et al. BMC Public Health (2018) 18:673 Page 2 of 8 growth, poverty, poor water and sanitation, as well as in- ECD outcomes. We combined all nationally representative adequate home environments [9–11]. However, the role of surveys from MICS rounds 4and 5(2010–2014) that were birth registration has been largely absent in these prior publicly available prior to January, 2017. We restricted our global reviews on correlates of early child nutrition and sample to children who had data on birth registration and development outcomes. either data on anthropometric outcomes or data on the Lack of birth registration violates children’s fundamen- Early Childhood Development Index (ECDI), which is pri- tal rights, including their right to nationality, and may marily collected for preschool children aged 36–59 months. also hinder young children’s access to targeted health services and social welfare programs (e.g. cash transfer Outcomes schemes) and enrollment in school [12–17]. Without a We examined four child outcomes relating to early birth certificate, a child's exact age is challenging to nutrition and development: height-for-age z-scores prove, which is important for ensuring that children re- (HAZ), weight-for-age z-scores (WAZ), weight-for-height ceive age-appropriate recommended schedule of vacci- z-scores (WHZ), and ECDI z-scores. Z-scores for an- nations [14], applying correct growth standards to thropometric measures were computed using the 2006 estimate children's nutritional status (i.e., height-for-age WHO Multi-center Growth Reference Study standards or weight-for-age) [18, 19], and verifying that children [29]. Biologically implausible values (HAZ as <−6or>6, are at least a minimum age upon entering school. As WAZ as <− 6 or > 5, and WHZ as <− 5 or > 5) were ex- children grow older, a birth certificate can provide im- cluded based on WHO cutoffs [30]. portant documentation in protecting against child labor, Early child development was measured using the ECDI. trafficking, and sexual exploitation [1, 12]; all which are Developed by UNICEF for 3- and 4-year-olds surveyed in associated with poor child health and wellbeing out- the MICS household survey program, the ECDI is comes [20, 21]. Moreover, unregistered children are not comprised of 10 caregiver-reported, dichotomously-scored counted and thus excluded from civil registration sys- questions to assess 4 developmental domains: cognitive, tems, which provide governments with vital statistics for socioemotional, literacy-numeracy, and physical develop- allocating resources and monitoring programs and pol- ment. These 10 items were determined through icies that have direct implications for children’s nutrition multi-country field tests, validity, and reliability studies, and and development [22]. deliberation with experts [31]. This population measure of To date, much of the global literature on birth regis- ECD has been used in other recent studies [32, 33]. A com- tration has been at a macro-level: arguing principally posite score for ECD was created (ranging from 0 to 10) by from a rights-based legal approach and emphasizing the summing the number of positive responses across the normative importance of birth registration [23], or advo- literacy-numeracy, social-emotional, learning, and physical cating for the importance of civil registration and vital domain items, and normalized to a ECDI z-score for direct statistics systems [24, 25]. A growing body of evidence comparability and ease of interpretation to the standardized has identified predictors of birth registration in order to scale of HAZ, WAZ, and WHZ. develop strategies for increasing birth registration cover- age [13, 26–28]. While a few studies to date have exam- Independent variable ined associations between birth registration and children’s Our primary independent variable of interest was lack of early nutrition and growth outcomes in LMICs [12, 18], a birth certificate. In the MICS questionnaire, two items no study known to the authors has additionally explored directly capture birth registration: first, caregivers are the association between birth registration and ECD asked to show the interviewer the child’s birth certificate. outcomes in LMICs. Given existing research on the If a birth certificate is not available, caregivers are asked importance of birth registration, we hypothesized that not whether the child ever had a birth certificate, and if not, being registered would be negatively associated with early whether the child’s birth had been registered with the childhood growth and development outcomes in LMICs. civil authorities. For our empirical analysis, we created a no birth certificate indicator variable, which was coded 1 Methods if the child did not ever have a birth certificate and 0 if Data the child currently had or previously had a birth We used data from UNICEF’s Multiple Indicator Cluster certificate. Survey (MICS), an international household survey pro- gram that collects information about the health, nutrition, Covariates education, and development of children in LMICs. The We adjusted for a variety of child-, caregiver-, and MICS is unique for collecting and monitoring ECD in a household-level covariates. Child characteristics included standardized and comparable way across LMICs, and re- age (in months) and sex (male or female). Caregiver char- mains the primary data source to measure and monitor acteristics included maternal and paternal highest level of Jeong et al. BMC Public Health (2018) 18:673 Page 3 of 8 education (no formal education, primary, or secondary or magnitude of these associations increased by child age higher), maternal age (5-year age categories from 15 to (categorized in 12-month age groups) we re-specified 49 years), and maternal marital status (currently married, Model 4, excluding early childhood education attendance formerly married, or never married). Household character- as a utilization of service covariate. This allowed us to ex- istics included household wealth index (quintiles within plore the associations between not having a birth certifi- each country: calculated as a principal component of a cate and children’s HAZ and WAZ outcomes in a group of assets owned by the household [34]) and place of separate sample of younger children aged 0–35 months, residency (urban or rural). Utilization of child health and for whom anthropometric data, but not the ECDI, were learning services was measured by the number of vaccina- available. tions received (ranging from 0 to 4 for bcg and at least one dose of dpt/hepb, polio, and measles) and whether or not Results preschool-aged children attended an early education pro- A total of 157,336 children aged 0 to 59 months from 31 gram (asked only regarding children aged 36–59 months). countries were represented in the full sample. No signifi- cant differences were detected between the complete cases Analysis in theanalyticsample and theincomplete cases (N = We conducted a complete case analysis upon verifying 65,425, 29.4% of original sample) that were excluded due to that missingness was not systematic. We specified a series missing data on full covariates. Sample characteristics for of four linear regression models with varying controls for the total sample of children are presented in Table 1.The potential confounders and mediators to estimate the asso- average age of the child was 28 months, and nearly half of ciation between lack of birth registration and each of the thesamplewas female.Overall,28.5% of mothersand four outcome variables of interest: HAZ, WAZ, WHZ, 18.4% of fathers reported no formal education. The major- and ECDI z-score among children aged 36–59 months. ity of households (60.2%) resided in rural areas. Model 1 only adjusted for child age, sex, and country fixed Approximately one in three children under-5 (34.7%) effects. Model 2 further adjusted for all caregiver- and did not possess a birth certificate. The average proportion household-level demographic and socioeconomic covari- of children without a birth certificate varied across coun- ates (maternal and paternal education, maternal age, ma- tries, ranging from as low 0.2 and 0.5% in Ukraine and ternal marital status, household wealth index, and place of Thailand, respectively, (where nearly all children were reg- residency). Model 3 further adjusted for variables repre- istered) to as high as 80.8 and 95.0% in Guinea Bissau and senting utilization of services that may relate to both birth Malawi, respectively (Additional file 1). Children who did registration and ECD outcomes (children’s vaccinations not have a birth certificate were more likely to have par- and early childhood education programs). Finally, Model ents who were less educated, live in poorer households, 4 additionally included primary sampling unit (PSU)/clus- and reside in rural areas of the country (Table 1). ter-level fixed effects, which can account for other observ- The mean HAZ was − 1.01 (SD = 1.7), with 26.2% of able and unobservable differences in socioeconomic, children classified as stunted. The mean WAZ for chil- environmental, and institutional characteristics of local dren was − 0.58 (SD = 1.4), with 13.7% of infants exhibit- enumeration areas that are common to all respondents ing underweight. The mean WHZ for children was − from that area (i.e., local diet, community child health 0.01 (SD = 1.4), with 7.0% classified as wasted. The mean awareness campaigns, cultural and social norms, as well ECDI z-score was 0.00 (SD = 1.0). as within-cluster availability of birth registration and other Of this total sample, we primarily focused on social services). Standard errors across all models were 54,916 children aged 36 to 59 months in 24 LMICs, clustered at the PSU-level to account for the complex for whom full information was available across all MICS survey design. All analyses were conducted using variables of interest. Table 2 presents adjusted associ- Stata version 13 [35]. ations between a lack of birth certificate and preschool-aged children’s nutrition and development Sensitivity analyses and robustness checks outcomes across the four model specifications. In First, to assess whether pooled findings were robust, we models only adjusting for child age, sex, and conducted separate country-specific models (fully adjusted country-level fixed effects (Model 1), not having a Model 4) for the associations between lack of birth regis- birth certificate was negatively associated with chil- tration and each of the four child outcome variables; and dren’sHAZ (β = − 0.48; 95% CI: -0.52, − 0.43), WAZ employed random-effects meta-regressions to re-estimate (β = − 0.30; 95% CI: -0.33, − 0.27), and ECDI z-scores a pooled effect that accounts for the varying sample sizes (β = − 0.32; 95% CI: -0.34, − 0.29); associations how- across country surveys. Second, to examine whether not ever were not significant for WHZ (β = − 0.01; 95% having a birth certificate was related to child outcomes as CI: -0.04, 0.03). In models additionally adjusting for early as in the first 3 years of life and whether the caregiver and sociodemographic covariates (Model 2), Jeong et al. BMC Public Health (2018) 18:673 Page 4 of 8 Table 1 Full sample characteristics among children aged 0–59 months and by children’s birth certificate ownership Total (n = 157,336) Child does not have birth certificate Child has birth certificate (n = 54,605) (n = 102,731) % (95% CI) % (95% CI) % (95% CI) Covariates Female child 49.1 (48.9–49.4) 49.6 (49.2–50.0) 48.8 (48.5–49.1) Age of child, mean (SD), range 0–59 months 28.0 (16.7) 25.3 (16.4) 29.4 (16.6) Maternal education None 28.5 (27.9–29.1) 41.4 (40.4–42.4) 21.6 (21.1–22.2) Primary 33.1 (32.7–33.6) 36.7 (35.9–37.4) 31.2 (30.7–31.8) Secondary or higher 38.4 (37.8–39.0) 21.9 (21.2–22.6) 47.1 (46.5–47.8) Paternal education None 18.4 (17.9–18.9) 28.3 (27.3–29.2) 13.2 (12.7–13.6) Primary 30.7 (30.3–31.2) 35.4 (34.6–36.1) 28.3 (27.8–28.8) Secondary or higher 50.8 (50.3–51.4) 36.4 (35.5–37.2) 58.5 (58.0–59.1) Martial status Currently married/in union 99.8 (99.7–99.8) 99.7 (99.7–99.8) 99.8 (99.8–99.8) Formerly married/in union 0.1 (0.1–0.1) 0.2 (0.1–0.2) 0.1 (0.1–0.1) Never married/in union 0.1 (0.1–0.1) 0.1 (0.1–0.2) 0.1 (0.1–0.1) Maternal age 15–19 4.1 (4.0–4.2) 6.0 (5.7–6.2) 3.1 (3.0–3.2) 20–24 19.6 (19.3–19.9) 23.0 (22.5–23.4) 17.8 (17.5–18.2) 25–29 28.2 (27.9–28.5) 27.4 (27.0–27.9) 28.6 (28.2–28.9) 30–34 23.2 (22.9–23.5) 20.5 (20.1–20.9) 24.7 (24.3–25.0) 35–39 15.8 (15.6–16.1) 14.2 (13.8–14.6) 16.7 (16.4–17.0) 40–44 7.1 (7.0–7.3) 6.6 (6.4–6.9) 7.4 (7.2–7.6) 45–49 2.0 (1.9–2.0) 2.3 (2.2–2.5) 1.8 (1.7–1.9) Wealth quintile Poorest 18.7 (18.2–19.2) 22.4 (21.7–23.1) 16.8 (16.2–17.3) Poor 20 (19.6–20.3) 23.4 (22.8–24.0) 18.1 (17.7–18.5) Middle 19.6 (19.3–19.9) 21.4 (20.9–22.0) 18.6 (18.2–19.0) Rich 19.8 (19.5–20.2) 17.9 (17.3–18.5) 20.8 (20.4–21.3) Richest 21.9 (21.4–22.4) 14.8 (14.2–15.5) 25.7 (25.1–26.2) Rural residence 60.2 (59.4–61.0) 78.4 (77.3–79.5) 50.6 (49.6–51.5) Number of vaccines child received, mean (SD), 3.4 (0.8) 3.3 (0.9) 3.4 (0.8) range 0–4 Child currently attends ECE, among children 24.5 (23.9–25.0) 16.3 (15.4–17.1) 27.5 (26.9–28.2) aged 36–59 months Child outcomes HAZ, mean (SD) −1.01 (1.7) −1.49 (1.7) −0.75 (1.7) WAZ, mean (SD) −0.58 (1.4) −1.05 (1.4) − 0.32 (1.3) WHZ, mean (SD) −0.01 (1.4) − 0.29 (1.4) 0.15 (1.5) ECDI z-scores among children aged 36– 0.00 (1.0) −0.34 (0.9) 0.18 (1.0) 59 months, mean (SD) CI confidence interval, ECE early childhood education, ECDI Early Childhood Development Index, HAZ height-for-age z-scores, SD standard deviation, WAZ weight- for-age z-scores, WHZ weight-for-height z-scores Jeong et al. BMC Public Health (2018) 18:673 Page 5 of 8 Table 2 Associations between no birth certificate and children’s HAZ, WAZ, WHZ, and ECDI z-scores among children aged 36–59 months Child outcomes Model 1 Model 2 Model 3 Model 4 HAZ (n = 50,291) β of no birth certificate −0.48*** −0.26*** − 0.21*** −0.18*** 95% CI (−0.52, − 0.43) (− 0.30, − 0.22) (−0.25, − 0.17) (−0.23, − 0.14) WAZ (n = 50,531) β of no birth certificate − 0.30*** −0.15*** − 0.11*** −0.10*** 95% CI (−0.33, − 0.27) (− 0.18, − 0.11) (−0.14, − 0.08) (−0.13, − 0.07) WHZ (n = 50,178) β of no birth certificate − 0.01 0.02 0.03 0.02 95% CI (−0.04, 0.03) (−0.01, 0.06) (− 0.00, 0.07) (− 0.01, 0.06) ECDI z-score (n = 54,861) β of no birth certificate − 0.32*** −0.15*** − 0.10*** −0.10*** 95% CI (−0.34, − 0.29) (− 0.18, − 0.13) (−0.13, − 0.08) (−0.13, − 0.07) CI confidence interval, ECDI Early Childhood Development Index, HAZ height-for-age z-scores, WAZ weight-for-age z-scores, WHZ weight-for-height z-scores The table presents unweighted standardized mean differences in child growth and development outcomes for children aged 36–59 months in 31 countries who did not have a birth certificate. Model 1 only adjusted for child age, sex, and country-level fixed effects. Model 2 further adjusted for maternal age, maternal education, paternal education, household wealth quintiles, and urban/rural residency. Model 3 additionally adjusted for vaccinations and attendance in an early childhood education program. Model 4 additionally adjusted for primary sampling unit-level fixed effects. All standard errors were clustered at the primary sampling unit level. ***P-value < 0.001 associations were smaller in magnitude but remained In a separate sample of younger children aged 0– significant for HAZ (β = − 0.26; 95% CI: -0.30, − 0.22), 35 months (N = 102,488), the overall associations between WAZ (β = − 0.15; 95% CI: -0.18, − 0.11), and ECDI a lack of birth certificate and children’s HAZ and WAZ z-scores (β = − 0.15; 95% CI: -0.18, − 0.13). In models were smaller in magnitude, but also remained significant additionally adjusting for children’s utilization of (Additional file 6). In addition, findings indicated that the health and education services (Model 3), associations magnitude of these associations increased with child age: were further attenuated for HAZ (β = − 0.21; 95% CI: such that associations were strongest for 2-year-olds (as -0.25, − 0.17), WAZ (β = − 0.11; 95% CI: -0.14, − 0.08), compared to 1-year-olds or children under-1). and ECDI z-scores (β = − 0.10; 95% CI: -0.13, − 0.08). Finally, in models additionally accounting for PSU/ Discussion cluster-level fixed effects (Model 4), significant nega- Using data from 31 LMICs, our study revealed two main tive associations persisted between not having a birth findings. First, birth registration among the children certificate and children’sHAZ (β = − 0.18; 95% CI: under-5 was low in our pooled sample. Despite the rec- -0.23, − 0.14), WAZ (β = − 0.10, 95% CI: -0.13, − 0.07), ommendation for birth registration to occur in the first and ECDI z-scores (β = − 0.10; 95% CI: -0.13, − 0.07). few weeks or months of life, one in three children under-5 in the total sample were still without a birth Sensitivity analyses and robustness checks certificate. We also found inequalities in access to birth Overall pooled estimates based on meta-regression certificates by wealth, maternal and paternal education (using Model 4) were robust and comparable in magni- and rural residency. This is consistent with other global tude to findings from pooled analyses (presented above studies of birth registration that have described large in Table 2) for all outcomes. Significant relationships gaps in access to birth registration [36, 37]. were found for children’s HAZ (Additional file 2), WAZ Second, we found that not having a birth certificate (Additional file 3), and ECDI (Additional file 4); associa- was negatively associated with both preschool-aged chil- tions for WHZ (Additional file 5) were not significant. dren’s growth and developmental outcomes, or more While country specific results highlighted variation in specifically HAZ, WAZ, and ECDI z-scores. Our find- the associations across countries, point estimates were ings build upon the results of a prior study by Coman- largely consistent in magnitude and directionality across dini et al. [18] that documented a negative relationship countries for each outcome. Of note, three countries between birth registration and undernutrition among (Lebanon, Macedonia and Moldova) were exceptions, children aged 2-to-5 years in 37 sub-Saharan African which also had the smallest sample sizes and where only countries. In our study, we newly highlight associations less than 4% of children did not have birth certificates. between birth registration and ECD, as indexed by the Jeong et al. BMC Public Health (2018) 18:673 Page 6 of 8 ECDI; and with respect to both child growth and devel- birth registration reflects a household’ssocialconnected- opment outcomes, even after adjusting for additional co- ness or social status (which could be shaped by sociodemo- variates than considered in prior research. graphic factors that we do not include, e.g. ethnicity, caste, We did not find significant associations between birth or religion) which may serve as a proxy for marginalization registration and WHZ. One explanation could be the or how informed or empowered parents may be feel in fact that WHZ calculations do not require information accessing a range of formal and informal services. Future on age, which has been highlighted as more likely intro- research that investigates parental knowledge and attitudes ducing bias and error among unregistered children and regarding birth registration and more comprehensively as- driving underestimations of their undernutrition status sesses the linkages between birth registration and a wider [18]. Another likely explanation for the null association range of social services may better elucidate the factors that with WHZ could be the fact that wasting is an indicator underlie our exploratory findings. of acute malnutrition, often occurring suddenly due to While our results support robust associations in this contemporaneous shocks, such as infection or famine, pooled sample, it is important to note that the opportun- and largely explained by dietary diversity, food insecurity, ities afforded by a birth certificate vary considerably across and climate change [38, 39]. Moreover, the prevalence of country contexts. For instance, in Vietnam a birth certifi- wasting in our sampled countries was very low (mean of cate is necessary to enroll in both preschool and primary 7.0%, with prevalence of wasting > 10% in only 3 coun- school, while in Sierra Leone and India, national policy tries) and potentially too small to detect differences. mandates that birth certificates are not formally required at With respect to the likely mechanisms, we found that so- any stage of the education system [44]. Moreover, requiring cioeconomic factors (i.e., maternal and paternal education, a certificate to access services may disproportionately im- household wealth index, and place of residency) explained pact the most vulnerable groups within-countries [45]. Fu- nearly half of the unadjusted associations between birth ture research on birth registration should consider a registration and poor early child growth and development country’s legal and policy environment and examine how outcomes. Above and beyond household socioeconomic these associations with early child outcomes are similar or factors, children’s utilization of early health and learning different within and across LMICs and the proportion of services (i.e., child vaccinations and attendance in an early variance explained at the country-level (e.g., using multi- education programs) explained approximately a quarter to level models). a third of the remaining association between birth registra- Despite these policy differences across countries, our tion and child outcomes. Interestingly, we found that add- pooled findings indicate a significant negative relationship itionally controlling for cluster characteristics did not add between birth registration and child growth and develop- explanatory power, thereby minimizing the possibility that ment outcomes across LMICs, and the potential role of these associations are due to community characteristics socioeconomic factors in explaining a part of this relation- within clusters within countries. Prior studies have also ship. This suggests important links between birth registra- documented links between birth registration and children’s tion, social protection, and early child health and education healthcare utilization, school enrollment and completion, services, especially for the children living in the poorest and participation in social services (e.g., cash transfer pro- households. Research from Ghana has affirmed the benefits grams and government food programs) [12–14]. Our find- of incorporating birth registration into community health ings extend this evidence by demonstrating how such care and child health campaigns [40]. Moreover, the recent services do, in turn, explain a considerable proportion of Lancet ECD series has emphasized the need for multisec- the direct associations between birth registration and early toral approaches to coordinating ECD programs, particu- child nutrition and development outcomes. larly with the health and nutrition sectors [46, 47]. However, we found that significant associations persisted However, most ECD interventions and policies do not between birth registration and child outcomes, which were include birth registration as a core component [12–18]. unexplained by the covariates and cluster-fixed effects in- Future efforts should consider integrating birth registration cluded in our models. One possible explanation could be campaigns with other early childhood services and inter- that registration reflects some degree of parental invest- ventions to promote the development and well-being of ment in the child. If completing the registration process is young children. arduous, parents who register their children may be those Birth registration and the estimation of a child’sage is who have more time or financial resources that they are central to the very measurement of early childhood out- able to spend on their children (especially if registration in- comes: a precise measurement of age is needed to accur- volves traveling a distance or financial and opportunity ately measure HAZ and WAZ among children under-5. costs) [40–42], or those who are more motivated and com- Comandini and co-authors describe the negative effects of mitted to following through with formal registration appli- measurement error and age heaping in misestimating HAZ cation procedures [43]. Another possibility could be that and WAZ, especially among children without a birth Jeong et al. BMC Public Health (2018) 18:673 Page 7 of 8 certificate [18, 19]. Efforts to improve birth registration Acknowledgements We thank the United Nations Children’s Fund and individual countries for could also address the processes of imputing, estimating, collecting the MICS data. and guessing a child’s age in household surveys and im- prove the assessment of nutritional outcomes. Availability of data and materials The MICS data supporting the conclusions of this article are publically There are several limitations to this analysis. First, we available from UNICEF’s online database at, http://mics.unicef.org/surveys. were only able to pool data from countries for which the MICS data were available; therefore, our results may not be Authors’ contributions JJ, AB, and GF conceptualized the study. JJ conducted analyses. JJ and AB representative of LMICs as a whole. Second, although we drafted the manuscript. GF reviewed and edited the manuscript. All authors adjusted for a range of covariates and include cluster-level read and approved the final version submitted for publication. fixed effects, we were unable to control for other important Ethics approval and consent to participate variables, such as data on facility birth, maternal autonomy, This study was deemed exempt from ethics review by the Harvard T.H. Chan and access to other services. Third, both the ECDI and School of Public Health Institutional Review Board, as the MICS data used are birth registration were caregiver reported and may be sus- publicly available and fully de-identified. ceptible to recall bias. Fourth, measures of nutritional status Competing interests (e.g. height or weight for age) could be prone to bias among The authors declare that they have no competing interests. unregistered children, as their age cannot be verified [18]. Finally, the MICS are cross-sectional surveys, which pre- Publisher’sNote clude causal interpretation, determination of mediators, Springer Nature remains neutral with regard to jurisdictional claims in published maps and institutional affiliations. and directionality of the associations. Author details Department of Global Health and Population, Harvard T.H. Chan School of Conclusions Public Health, 665 Huntington Avenue, 11th floor, Boston, MA, USA. This study highlights gaps in birth registration for young Department of Social and Behavioral Sciences, Harvard T.H. Chan School of children in LMICs and finds that not having a birth cer- Public Health, Boston, USA. Swiss Tropical and Public Health Institute, Basel, Switzerland. University of Basel, Basel, Switzerland. tificate is negatively associated with early child growth and development outcomes. Early child health, nutrition, Received: 16 January 2018 Accepted: 24 May 2018 and education programs and policies should consider integrating birth registration – and child protection References more broadly – in order to ensure that every child is 1. Birth registration. https://www.unicef.org/protection/57929_58010.html. legally recognized and has a fair chance to achieve her 2. Sustainable Development Goals. https://sustainabledevelopment.un.org/sdgs. 3. Access the data: birth registration. https://data.unicef.org/topic/child- full developmental potential. protection/birth-registration. 4. Cappa C, Gregson K, Wardlaw T, Bissell S. Birth registration: a child's passport to protection. Lancet Glob Health. 2014;2(2):e67–8. Additional files 5. Daelmans B, Darmstadt GL, Lombardi J, Black MM, Britto PR, Lye S, Dua T, Bhutta ZA, Richter LM. Early childhood development: the foundation of Additional file 1: Country mean values for proportion of children not sustainable development. 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BMC Public HealthSpringer Journals

Published: May 30, 2018

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