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      Parental education and inequalities in child mortality: a global systematic review and meta-analysis

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          Summary

          Background

          The educational attainment of parents, particularly mothers, has been associated with lower levels of child mortality, yet there is no consensus on the magnitude of this relationship globally. We aimed to estimate the total reductions in under-5 mortality that are associated with increased maternal and paternal education, during distinct age intervals.

          Methods

          This study is a comprehensive global systematic review and meta-analysis of all existing studies of the effects of parental education on neonatal, infant, and under-5 child mortality, combined with primary analyses of Demographic and Health Survey (DHS) data. The literature search of seven databases (CINAHL, Embase, MEDLINE, PsycINFO, PubMed, Scopus, and Web of Science) was done between Jan 23 and Feb 8, 2019, and updated on Jan 7, 2021, with no language or publication date restrictions. Teams of independent reviewers assessed each record for its inclusion of individual-level data on parental education and child mortality and excluded articles on the basis of study design and availability of relevant statistics. Full-text screening was done in 15 languages. Data extracted from these studies were combined with primary microdata from the DHS for meta-analyses relating maternal or paternal education with mortality at six age intervals: 0–27 days, 1–11 months, 1–4 years, 0–4 years, 0–11 months, and 1 month to 4 years. Novel mixed-effects meta-regression models were implemented to address heterogeneity in referent and exposure measures among the studies and to adjust for study-level covariates (wealth or income, partner's years of schooling, and sex of the child). This study was registered with PROSPERO (CRD42020141731).

          Findings

          The systematic review returned 5339 unique records, yielding 186 included studies after exclusions. DHS data were compiled from 114 unique surveys, capturing 3 112 474 livebirths. Data extracted from the systematic review were synthesized together with primary DHS data, for meta-analysis on a total of 300 studies from 92 countries. Both increased maternal and paternal education showed a dose–response relationship linked to reduced under-5 mortality, with maternal education emerging as a stronger predictor. We observed a reduction in under-5 mortality of 31·0% (95% CI 29·0–32·6) for children born to mothers with 12 years of education (ie, completed secondary education) and 17·3% (15·0–18·8) for children born to fathers with 12 years of education, compared with those born to a parent with no education. We also showed that a single additional year of schooling was, on average, associated with a reduction in under-5 mortality of 3·04% (2·82–3·23) for maternal education and 1·57% (1·35–1·72) for paternal education. The association between higher parental education and lower child mortality was significant for both parents at all ages studied and was largest after the first month of life. The meta-analysis framework incorporated uncertainty associated with each individual effect size into the model fitting process, in an effort to decrease the risk of bias introduced by study design and quality.

          Interpretation

          To our knowledge, this study is the first effort to systematically quantify the transgenerational importance of education for child survival at the global level. The results showed that lower maternal and paternal education are both risk factors for child mortality, even after controlling for other markers of family socioeconomic status. This study provides robust evidence for universal quality education as a mechanism to achieve the Sustainable Development Goal target 3.2 of reducing neonatal and child mortality.

          Funding

          Research Council of Norway, Bill & Melinda Gates Foundation, and Rockefeller Foundation-Boston University Commission on Social Determinants, Data, and Decision Making (3-D Commission).

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          Most cited references76

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          Preferred reporting items for systematic reviews and meta-analyses: the PRISMA statement

          David Moher and colleagues introduce PRISMA, an update of the QUOROM guidelines for reporting systematic reviews and meta-analyses
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            Preferred reporting items for systematic reviews and meta-analyses: the PRISMA Statement

            Systematic reviews and meta-analyses have become increasingly important in health care. Clinicians read them to keep up to date with their field,1,2 and they are often used as a starting point for developing clinical practice guidelines. Granting agencies may require a systematic review to ensure there is justification for further research,3 and some health care journals are moving in this direction.4 As with all research, the value of a systematic review depends on what was done, what was found, and the clarity of reporting. As with other publications, the reporting quality of systematic reviews varies, limiting readers' ability to assess the strengths and weaknesses of those reviews. Several early studies evaluated the quality of review reports. In 1987, Mulrow examined 50 review articles published in 4 leading medical journals in 1985 and 1986 and found that none met all 8 explicit scientific criteria, such as a quality assessment of included studies.5 In 1987, Sacks and colleagues6 evaluated the adequacy of reporting of 83 meta-analyses on 23 characteristics in 6 domains. Reporting was generally poor; between 1 and 14 characteristics were adequately reported (mean = 7.7; standard deviation = 2.7). A 1996 update of this study found little improvement.7 In 1996, to address the suboptimal reporting of meta-analyses, an international group developed a guidance called the QUOROM Statement (QUality Of Reporting Of Meta-analyses), which focused on the reporting of meta-analyses of randomized controlled trials.8 In this article, we summarize a revision of these guidelines, renamed PRISMA (Preferred Reporting Items for Systematic reviews and Meta-Analyses), which have been updated to address several conceptual and practical advances in the science of systematic reviews (Box 1). Terminology The terminology used to describe a systematic review and meta-analysis has evolved over time. One reason for changing the name from QUOROM to PRISMA was the desire to encompass both systematic reviews and meta-analyses. We have adopted the definitions used by the Cochrane Collaboration.9 A systematic review is a review of a clearly formulated question that uses systematic and explicit methods to identify, select, and critically appraise relevant research, and to collect and analyze data from the studies that are included in the review. Statistical methods (meta-analysis) may or may not be used to analyze and summarize the results of the included studies. Meta-analysis refers to the use of statistical techniques in a systematic review to integrate the results of included studies. Developing the PRISMA Statement A 3-day meeting was held in Ottawa, Canada, in June 2005 with 29 participants, including review authors, methodologists, clinicians, medical editors, and a consumer. The objective of the Ottawa meeting was to revise and expand the QUOROM checklist and flow diagram, as needed. The executive committee completed the following tasks, prior to the meeting: a systematic review of studies examining the quality of reporting of systematic reviews, and a comprehensive literature search to identify methodological and other articles that might inform the meeting, especially in relation to modifying checklist items. An international survey of review authors, consumers, and groups commissioning or using systematic reviews and meta-analyses was completed, including the International Network of Agencies for Health Technology Assessment (INAHTA) and the Guidelines International Network (GIN). The survey aimed to ascertain views of QUOROM, including the merits of the existing checklist items. The results of these activities were presented during the meeting and are summarized on the PRISMA Website. Only items deemed essential were retained or added to the checklist. Some additional items are nevertheless desirable, and review authors should include these, if relevant.10 For example, it is useful to indicate whether the systematic review is an update11 of a previous review, and to describe any changes in procedures from those described in the original protocol. Shortly after the meeting a draft of the PRISMA checklist was circulated to the group, including those invited to the meeting but unable to attend. A disposition file was created containing comments and revisions from each respondent, and the checklist was subsequently revised 11 times. The group approved the checklist, flow diagram, and this summary paper. Although no direct evidence was found to support retaining or adding some items, evidence from other domains was believed to be relevant. For example, Item 5 asks authors to provide registration information about the systematic review, including a registration number, if available. Although systematic review registration is not yet widely available,12,13 the participating journals of the International Committee of Medical Journal Editors (ICMJE)14 now require all clinical trials to be registered in an effort to increase transparency and accountability.15 Those aspects are also likely to benefit systematic reviewers, possibly reducing the risk of an excessive number of reviews addressing the same question16,17 and providing greater transparency when updating systematic reviews. The PRISMA Statement The PRISMA Statement consists of a 27-item checklist (Table 1; see also Text S1 for a downloadable template for researchers to re-use) and a 4-phase flow diagram (Figure 1; see also Figure S1 for a downloadable template for researchers to re-use). The aim of the PRISMA Statement is to help authors improve the reporting of systematic reviews and meta-analyses. We have focused on randomized trials, but PRISMA can also be used as a basis for reporting systematic reviews of other types of research, particularly evaluations of interventions. PRISMA may also be useful for critical appraisal of published systematic reviews. However, the PRISMA checklist is not a quality assessment instrument to gauge the quality of a systematic review. Box 1 Conceptual issues in the evolution from QUOROM to PRISMA Figure 1 Flow of information through the different phases of a systematic review Table 1 Checklist of items to include when reporting a systematic review or meta-analysis From QUOROM to PRISMA The new PRISMA checklist differs in several respects from the QUOROM checklist, and the substantive specific changes are highlighted in Table 2. Generally, the PRISMA checklist “decouples” several items present in the QUOROM checklist and, where applicable, several checklist items are linked to improve consistency across the systematic review report. Table 2 Substantive specific changes between the QUOROM checklist and the PRISMA checklist (a tick indicates the presence of the topic in QUOROM or PRISMA) The flow diagram has also been modified. Before including studies and providing reasons for excluding others, the review team must first search the literature. This search results in records. Once these records have been screened and eligibility criteria applied, a smaller number of articles will remain. The number of included articles might be smaller (or larger) than the number of studies, because articles may report on multiple studies and results from a particular study may be published in several articles. To capture this information, the PRISMA flow diagram now requests information on these phases of the review process. Endorsement The PRISMA Statement should replace the QUOROM Statement for those journals that have endorsed QUOROM. We hope that other journals will support PRISMA; they can do so by registering on the PRISMA Website. To underscore to authors, and others, the importance of transparent reporting of systematic reviews, we encourage supporting journals to reference the PRISMA Statement and include the PRISMA web address in their Instructions to Authors. We also invite editorial organizations to consider endorsing PRISMA and encourage authors to adhere to its principles. The PRISMA Explanation and Elaboration Paper In addition to the PRISMA Statement, a supporting Explanation and Elaboration document has been produced18 following the style used for other reporting guidelines.19-21 The process of completing this document included developing a large database of exemplars to highlight how best to report each checklist item, and identifying a comprehensive evidence base to support the inclusion of each checklist item. The Explanation and Elaboration document was completed after several face-to-face meetings and numerous iterations among several meeting participants, after which it was shared with the whole group for additional revisions and final approval. Finally, the group formed a dissemination subcommittee to help disseminate and implement PRISMA. Discussion The quality of reporting of systematic reviews is still not optimal.22-27 In a recent review of 300 systematic reviews, few authors reported assessing possible publication bias,22 even though there is overwhelming evidence both for its existence28 and its impact on the results of systematic reviews.29 Even when the possibility of publication bias is assessed, there is no guarantee that systematic reviewers have assessed or interpreted it appropriately.30 Although the absence of reporting such an assessment does not necessarily indicate that it was not done, reporting an assessment of possible publication bias is likely to be a marker of the thoroughness of the conduct of the systematic review. Several approaches have been developed to conduct systematic reviews on a broader array of questions. For example, systematic reviews are now conducted to investigate cost-effectiveness,31 diagnostic32 or prognostic questions,33 genetic associations,34 and policy-making.35 The general concepts and topics covered by PRISMA are all relevant to any systematic review, not just those whose objective is to summarize the benefits and harms of a health care intervention. However, some modifications of the checklist items or flow diagram will be necessary in particular circumstances. For example, assessing the risk of bias is a key concept, but the items used to assess this in a diagnostic review are likely to focus on issues such as the spectrum of patients and the verification of disease status, which differ from reviews of interventions. The flow diagram will also need adjustments when reporting individual patient data meta-analysis.36 We have developed an explanatory document18 to increase the usefulness of PRISMA. For each checklist item, this document contains an example of good reporting, a rationale for its inclusion, and supporting evidence, including references, whenever possible. We believe this document will also serve as a useful resource for those teaching systematic review methodology. We encourage journals to include reference to the explanatory document in their Instructions to Authors. Like any evidence-based endeavour, PRISMA is a living document. To this end we invite readers to comment on the revised version, particularly the new checklist and flow diagram, through the PRISMA website. We will use such information to inform PRISMA's continued development. Note: To encourage dissemination of the PRISMA Statement, this article is freely accessible on the Open Medicine website and the PLoS Medicine website and is also published in the Annals of Internal Medicine, BMJ, and Journal of Clinical Epidemiology. The authors jointly hold the copyright of this article. For details on further use, see the PRISMA website. The PRISMA Explanation and Elaboration Paper is available at the PLoS Medicine website. Supporting Information Figure S1 Flow of information through the different phases of a systematic review (downloadable template document for researchers to re-use) Text S1 Checklist of items to include when reporting a systematic review or meta-analysis (downloadable template document for researchers to re-use)
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              Global, regional, and national life expectancy, all-cause mortality, and cause-specific mortality for 249 causes of death, 1980–2015: a systematic analysis for the Global Burden of Disease Study 2015

              Summary Background Improving survival and extending the longevity of life for all populations requires timely, robust evidence on local mortality levels and trends. The Global Burden of Disease 2015 Study (GBD 2015) provides a comprehensive assessment of all-cause and cause-specific mortality for 249 causes in 195 countries and territories from 1980 to 2015. These results informed an in-depth investigation of observed and expected mortality patterns based on sociodemographic measures. Methods We estimated all-cause mortality by age, sex, geography, and year using an improved analytical approach originally developed for GBD 2013 and GBD 2010. Improvements included refinements to the estimation of child and adult mortality and corresponding uncertainty, parameter selection for under-5 mortality synthesis by spatiotemporal Gaussian process regression, and sibling history data processing. We also expanded the database of vital registration, survey, and census data to 14 294 geography–year datapoints. For GBD 2015, eight causes, including Ebola virus disease, were added to the previous GBD cause list for mortality. We used six modelling approaches to assess cause-specific mortality, with the Cause of Death Ensemble Model (CODEm) generating estimates for most causes. We used a series of novel analyses to systematically quantify the drivers of trends in mortality across geographies. First, we assessed observed and expected levels and trends of cause-specific mortality as they relate to the Socio-demographic Index (SDI), a summary indicator derived from measures of income per capita, educational attainment, and fertility. Second, we examined factors affecting total mortality patterns through a series of counterfactual scenarios, testing the magnitude by which population growth, population age structures, and epidemiological changes contributed to shifts in mortality. Finally, we attributed changes in life expectancy to changes in cause of death. We documented each step of the GBD 2015 estimation processes, as well as data sources, in accordance with Guidelines for Accurate and Transparent Health Estimates Reporting (GATHER). Findings Globally, life expectancy from birth increased from 61·7 years (95% uncertainty interval 61·4–61·9) in 1980 to 71·8 years (71·5–72·2) in 2015. Several countries in sub-Saharan Africa had very large gains in life expectancy from 2005 to 2015, rebounding from an era of exceedingly high loss of life due to HIV/AIDS. At the same time, many geographies saw life expectancy stagnate or decline, particularly for men and in countries with rising mortality from war or interpersonal violence. From 2005 to 2015, male life expectancy in Syria dropped by 11·3 years (3·7–17·4), to 62·6 years (56·5–70·2). Total deaths increased by 4·1% (2·6–5·6) from 2005 to 2015, rising to 55·8 million (54·9 million to 56·6 million) in 2015, but age-standardised death rates fell by 17·0% (15·8–18·1) during this time, underscoring changes in population growth and shifts in global age structures. The result was similar for non-communicable diseases (NCDs), with total deaths from these causes increasing by 14·1% (12·6–16·0) to 39·8 million (39·2 million to 40·5 million) in 2015, whereas age-standardised rates decreased by 13·1% (11·9–14·3). Globally, this mortality pattern emerged for several NCDs, including several types of cancer, ischaemic heart disease, cirrhosis, and Alzheimer's disease and other dementias. By contrast, both total deaths and age-standardised death rates due to communicable, maternal, neonatal, and nutritional conditions significantly declined from 2005 to 2015, gains largely attributable to decreases in mortality rates due to HIV/AIDS (42·1%, 39·1–44·6), malaria (43·1%, 34·7–51·8), neonatal preterm birth complications (29·8%, 24·8–34·9), and maternal disorders (29·1%, 19·3–37·1). Progress was slower for several causes, such as lower respiratory infections and nutritional deficiencies, whereas deaths increased for others, including dengue and drug use disorders. Age-standardised death rates due to injuries significantly declined from 2005 to 2015, yet interpersonal violence and war claimed increasingly more lives in some regions, particularly in the Middle East. In 2015, rotaviral enteritis (rotavirus) was the leading cause of under-5 deaths due to diarrhoea (146 000 deaths, 118 000–183 000) and pneumococcal pneumonia was the leading cause of under-5 deaths due to lower respiratory infections (393 000 deaths, 228 000–532 000), although pathogen-specific mortality varied by region. Globally, the effects of population growth, ageing, and changes in age-standardised death rates substantially differed by cause. Our analyses on the expected associations between cause-specific mortality and SDI show the regular shifts in cause of death composition and population age structure with rising SDI. Country patterns of premature mortality (measured as years of life lost [YLLs]) and how they differ from the level expected on the basis of SDI alone revealed distinct but highly heterogeneous patterns by region and country or territory. Ischaemic heart disease, stroke, and diabetes were among the leading causes of YLLs in most regions, but in many cases, intraregional results sharply diverged for ratios of observed and expected YLLs based on SDI. Communicable, maternal, neonatal, and nutritional diseases caused the most YLLs throughout sub-Saharan Africa, with observed YLLs far exceeding expected YLLs for countries in which malaria or HIV/AIDS remained the leading causes of early death. Interpretation At the global scale, age-specific mortality has steadily improved over the past 35 years; this pattern of general progress continued in the past decade. Progress has been faster in most countries than expected on the basis of development measured by the SDI. Against this background of progress, some countries have seen falls in life expectancy, and age-standardised death rates for some causes are increasing. Despite progress in reducing age-standardised death rates, population growth and ageing mean that the number of deaths from most non-communicable causes are increasing in most countries, putting increased demands on health systems. Funding Bill & Melinda Gates Foundation.
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                Author and article information

                Contributors
                Journal
                Lancet
                Lancet
                Lancet (London, England)
                Elsevier
                0140-6736
                1474-547X
                14 August 2021
                14 August 2021
                : 398
                : 10300
                : 608-620
                Affiliations
                [a ]Centre for Global Health Inequalities Research, Department of Sociology and Political Science, Norwegian University of Science and Technology, Trondheim, Norway
                [b ]Institute for Health Metrics and Evaluation, University of Washington, Seattle, WA, USA
                [c ]Department of Applied Mathematics, University of Washington, Seattle, WA, USA
                [d ]Department of Sociology and Office of Population Research, Princeton University, Princeton, NJ, USA
                [e ]Department of Health Metrics Sciences, School of Medicine, University of Washington, Seattle, WA, USA
                [f ]Center for Social Medicine and Humanities, University of California Los Angeles, Los Angeles, CA, USA
                [g ]RAND Corporation, Santa Monica, CA, USA
                [h ]Library Section for Humanities, Education and Social Sciences, University Library, Norwegian University of Science & Technology, Trondheim, Norway
                [i ]Department of Health Promotion, Norwegian Institute of Public Health, Bergen, Norway
                Author notes
                [* ]Correspondence to: Prof Terje Andreas Eikemo, Centre for Global Health Inequalities Research, Department of Sociology and Political Science, Norwegian University of Science and Technology, 7491 Trondheim, Norway terje.eikemo@ 123456ntnu.no
                [** ]Prof Emmanuela Gakidou, Institute for Health Metrics and Evaluation, University of Washington, Seattle, WA 98121, USA gakidou@ 123456uw.edu
                [*]

                Contributed equally

                [†]

                Contributed equally

                Article
                S0140-6736(21)00534-1
                10.1016/S0140-6736(21)00534-1
                8363948
                34119000
                d1bc68d1-9c8b-4b0c-b22c-d4aa9dc613c8
                © 2021 The Author(s). Published by Elsevier Ltd. This is an Open Access article under the CC BY 4.0 license

                This is an open access article under the CC BY license (http://creativecommons.org/licenses/by/4.0/).

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