Evidence map›Paper›PMID 25889910›Full record

ArticleGlobalization and health2015

Maternal mortality: a cross-sectional study in global health.

Sima Sajedinejad, Reza Majdzadeh, AbouAli Vedadhir, Mahmoud Ghazi Tabatabaei, Kazem Mohammad

Abstract read
In one paragraph

Article in Globalization and health, 2015. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 28 papers, 3 of them syntheses that pooled it.

0numbers the graph read from it
0cells of the map it votes in
28citing papers in PubMed, 3 pooled it
–field-weighted citation impact
1 · What the graph read from it

What it found

Each row is one number read from the abstract, on the scale the paper reported it, with its interval. Left of the dashed line favours the treatment, right favours the comparator. Under each row is the sentence it came from. New to these charts? A ten-minute tutorial.

The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.

2 · The registry

The trial behind it

Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.

Neither the registry nor the abstract names a trial number. If this is a trial report, that itself is worth knowing.

3 · Its place in the literature

Who cites it

28 citing papers in PubMed, 3 syntheses or guidelines pooled it.

  1. Pooled it
  2. Pooled it
  3. Pooled it
  4. Trial
  5. Article
  6. Review
  7. Article
  8. Review
  9. Article
  10. Article
  11. Article
  12. Article
  13. Article
  14. Article
  15. Review
  16. Article
  17. Article
  18. Review
  19. Article
  20. Article
4 · The record

Corrections and comments

PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.

5 · Who and what money

Authors and funding

5 authors.

Sima SajedinejadDepartment of Epidemiology and Biostatistics, School of Public Health, Tehran University of Medical Sciences (TUMS), Tehran, Iran. sima.amis@gmail.com.
Reza MajdzadehDepartment of Epidemiology and Biostatistics, School of Public Health, Tehran University of Medical Sciences (TUMS), Tehran, Iran. rezamajd@tums.ac.ir.
AbouAli VedadhirDepartment of Anthropology, Faculty of Social Sciences, University of Tehran (UT), Tehran, Iran. vedadha@ut.ac.ir.
Mahmoud Ghazi TabatabaeiDepartment of Demography and Population Studies, Faculty of Social Sciences, University of Tehran, Tehran, Iran. smghazi@ut.ac.ir.
Kazem MohammadDepartment of Epidemiology and Biostatistics, School of Public Health, Tehran University of Medical Sciences (TUMS), Tehran, Iran. mohamadk@tums.ac.ir.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

backgroundAlthough most of maternal deaths are preventable, maternal mortality reduction programs have not been completely successful. As targeting individuals alone does not seem to be an effective strategy to reduce maternal mortality (Millennium Development Goal 5), the present study sought to reveal the role of many distant macrostructural factors affecting maternal mortality at the global level.

methodsAfter preparing a global dataset, 439 indicators were selected from nearly 1800 indicators based on their relevance and the application of proper inclusion and exclusion criteria. Then Pearson correlation coefficients were computed to assess the relationship between these indicators and maternal mortality. Only indicators with statistically significant correlation more than 0.2, and missing values less than 20% were maintained. Due to the high multicollinearity among the remaining indicators, after missing values analysis and imputation, factor analysis was performed with principal component analysis as the method of extraction. Ten factors were finally extracted and entered into a multiple regression analysis.

resultsThe findings of this study not only consolidated the results of earlier studies about maternal mortality, but also added new evidence. Education (std. B = -0.442), private sector and trade (std. B = -0.316), and governance (std. B = -0.280) were found to be the most important macrostructural factors associated with maternal mortality. Employment and labor structure, economic policy and debt, agriculture and food production, private sector infrastructure investment, and health finance were also some other critical factors. These distal factors explained about 65% of the variability in maternal mortality between different countries.

conclusionDecreasing maternal mortality requires dealing with various factors other than individual determinants including political will, reallocation of national resources (especially health resources) in the governmental sector, education, attention to the expansion of the private sector trade and improving spectrums of governance. In other words, sustainable reduction in maternal mortality (as a development indicator) will depend on long-term planning for multi-faceted development. Moreover, trade, debt, political stability, and strength of legal rights can be affected by elements outside the borders of countries and global determinants. These findings are believed to be beneficial for sustainable development in Post-2015 Development Agenda.

Indexed as

Global HealthAdolescentAdultCross-Sectional StudiesFemaleHealth Status IndicatorsHumansMaternal MortalityMiddle AgedYoung Adult

Identifiers

PMID25889910
PMCPMC4353673

What OpenQuestion holds

Textmetadata
LicenceCC BY
Read underepoch 390

Registered trials

None linked

Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.