Infant mortality is the death of an infant before his or her first birthday. The infant mortality rate is the number of infant deaths for every 1, live births. In addition to giving us key information about maternal and infant health, the infant mortality rate is an important marker of the overall health of a society.
In , the infant mortality rate in the United States was 5. See Mortality in the United States, Almost 21, infants died in the United States in The five leading causes of infant death in were:. Healthy People external icon provides science-based, year national objectives for improving the health of all Americans. One of the Healthy People objectives is to reduce the rate of all infant deaths.
In , 15 states met the Healthy People target of 5. Geographically, infant mortality rates in were highest among states in the south.
CDC is committed to improving birth outcomes. This requires public health agencies working together with health care providers, communities, and other partners to reduce infant mortality in the United States. This joint approach can help address the social, behavioral, and health risk factors that contribute to infant mortality and affect birth outcomes. Skip directly to site content Skip directly to page options Skip directly to A-Z link.
Reproductive Health. Furthermore, as illustrated in Figure 4 , maternal mortality and lack of access to sanitation or water were the most important factor in countries globally. Lack of sanitation appeared to the most prominent factor in Central-South America while a more heterogeneous mixture of the three factors described above were observed in SSA and Eastern Europe-Asia.
HIV prevalence appeared to be the least important factor at a global level based on the determinant Shapley decomposition values Table 3. Variation and significant spatial concentration of Shapley decomposition values for other selected determinants included in the model and by individual countries can be found in Appendix 1.
Map showing the distribution of maternal mortality, lack of sanitation, and lack of water as the most important factors based on Shapley decomposition values for IMR by country, — Figure 5 displays the temporal trends in the relative importance decomposition values of the determinants of IMR both globally and by continent. Globally and more specifically in Africa, the Americas, and Asia, maternal mortality appeared to be the most important determinant accounted for more R 2 , and this increased over the study period.
Lack of sanitation featured prominently and appeared to be the second-most important determinant globally and specifically in the Americas and Asia. In Africa lack of water appeared to be the secondary determinant. In Europe, out-of-pocket health expenditure appeared to replace maternal mortality as the most important determinant toward the end of the study period, in contrast to the global trend.
Decomposition Shapley trends for each determinant by year and continent, — In terms of temporal trends in relative importance at a global level, out-of-pocket health expenditure, lack of immunization, and adolescent fertility appeared to significantly decrease in relative importance over the study period.
Conversely, maternal mortality and lack of access to sanitation and water appeared to increase in relative importance at the global level. HIV appeared to increase in relative importance in the late s and early s but appeared to start declining from The predicted IMR and standard error of the prediction from the multivariable model Table 3 suggests that IMR may have been significantly underreported or underestimated in a number of countries Figure 6 - ordered by modeled descending IMR level , many of which were in Africa, which have known data limitations.
Significant underestimation of IMR predicted by the model based on observed determinant profiles within countries, [note: ordered by descending modeled IMR level]. Little attention has been given to using secondary data to identify spatial differences and clustering in IMR and related determinants, or to the estimation of modifiable determinants and their changes.
This lack of attention is especially surprising given the prominence of IMR as a policy issue in the MDG 4 objectives. A study by Black et al. The approach utilized in our study can more effectively help guide resources at a global and country level.
The proposed framework is also easily adaptable to mortality in other age groups and for other health outcomes, as illustrated in other studies [ 24 ]. The framework, however, would require validation and comparison with existing frameworks, such as the Lives Saved Tool LiST [ 25 ], to confirm its potential routine utility.
Secondary data can be used to help inform the policymaking process with respect to the global incidence of IMR and its associated determinants [ 2 ],[ 12 ].
This study improves on previous work by including spatial inference to identify significant clustering of IMR and associated determinants that can be used to inform regional policy initiatives. It also uses attributable fractions to identify and estimate high-impact determinants that can be targeted at the country level and includes a temporal change component to assist guide time-appropriate policy decisions.
The highest burden of infant mortality is observed in SSA, and this is in line with previous studies [ 23 ]. A high burden of infant mortality is also observed in central-South Asia. Previous studies have demonstrated that the burden of child mortality is highly concentred in these regions, as well as illustrating the relative gap between low- and middle-to-high-income countries [ 23 ]. Causes of infant death differ substantially from country to country, further highlighting the need to expand our understanding of infant health epidemiology at a country level rather than in larger geopolitical regions.
There is, however, substantial variation in death rates within these and other regions, further suggesting that the planning of health interventions should take place at a country level [ 23 ]. Black et al.
Increasing political attention to address inequalities in IMR needs to be accompanied by more scientific-based evidence on the contribution of specific determinants and ways to ensure that interventions reach vulnerable groups [ 26 ]. Little is known about the relative contribution of the different hierarchical determinants of IMR and its inequality, nor with regards to the impact of country- and global-level determinants.
Development of interventions or priority areas for infant mortality requires an understanding of the associated determinants [ 23 ] and how the prevalence of these determinants varies from country to country. Maternal mortality survival emerged as a significant and the most prominent based on decomposition value determinant of infant mortality based on our analyses.
This has been demonstrated extensively in previous literature, for example [ 28 ]-[ 30 ], and is both a result of direct e. Furthermore the relative importance of this determinant appeared to increase over the study period.
Policymakers should take action to address this seemingly key determinant in focal countries if further progress toward reducing infant mortality in line with MDG 4 is to be made. Spatial inference suggests that SSA may be important to target first in reducing maternal mortality as a key determinant of infant mortality in the region and globally. Unhygienic environments place infants and children at greater risk of mortality. Drinking unclean water, using unclean water for hygiene, and a lack of proper sanitation are known risk factors for infant and child mortality [ 6 ],[ 23 ].
Our study has confirmed that lack of sanitation and clean water remain highly prominent and attributable causes of infant mortality at a global-regional level, as well as at a country level as illustrated in previous studies [ 31 ]. Central-South America emerged as focal hotspot for lack of sanitation as a primary determinant of infant mortality Figure 4.
Spatial concentrations of high decomposition values for lack of access to water or sanitation showed almost identical spatial distributions i. Furthermore, given the increase in relative importance of the lack of access to water and sanitation over the study period Figure 6 , this suggests that there is still much room for improvement in the provision of hygienic environments for infants and young children in many countries.
The protective association between increasing maternal education proxied by female education years in our study and infant mortality has been described in previous literature [ 32 ]. This is likely a result of better birth spacing i. Interestingly, out-of-pocket health expenditure emerged as a significant and highly attributable determinant of infant mortality in Europe. A recent study assessing health system determinants of infant mortality also found out-of-pocket health expenditure to be a significant determinant following multivariable adjustment [ 12 ].
This is attributed to a weak health financing system that cannot function without the additional cushion of out-of-pocket costs. This has both a direct and indirect impact on increasing the risk of adverse infant and child outcomes. The direct effect of these medical costs is evident and households often then borrow or sell assets. The loss of income from sick family members constitutes the indirect effect [ 35 ].
The assessment of temporal changes in IMR and the attributability of its associated determinants is important as neither is static, and time-appropriate policy decision-making is critical. Our study suggests that improvements have been made with regards to infant mortality attributed to health service provision DPT immunisation coverage and out-of-pocket health expenditure and young mothers adolescent fertility , as suggested by a decreasing importance of these determinants.
However, significant levels of IMR attributable to these factors still remain. Lapses in efforts to reduce infant mortality and associated contributing factors can lead to a slowing of and even a reversal of the decline in mortality rates in coming years.
Our model suggests that significant underestimation underreporting of IMR occurred in some countries, particularly in SSA. Reliable infant and child mortality data are critical for planning health interventions and assessing progress, yet such data are often not available or reliable in developing countries [ 36 ], especially in SSA [ 37 ].
This study also makes a contribution by more accurately estimating IMR in the presence of underreporting in areas with known higher IMR risk that have poor data sources.
Much of the WDI data comes from individual member countries and is compiled by internationally recognized organizations [ 13 ]. However, the quality of global data still depends on how well the individual national systems perform.
We therefore cannot discount that differential data quality by country may have affected our findings. The World Bank has worked to help developing countries improve national statistical systems and hence the quality of their data.
Therefore, changes in data quality with time may also affect the observed temporal trends. Substantial missing data for certain key indicators e. AF p can be incorrectly overestimated if confounding is not taken into account i.
This can occur for the formula used in this study if unadjusted risk coefficients are utilized. We have tried to limit this potential bias by use of multivariable adjusted risk coefficients. A recent study based on data from countries suggested that suboptimal breastfeeding may rank higher as a risk factor for child mortality than poor water and sanitation [ 38 ]. Thus we cannot also discount the potential impact or contribution of such a missing indicator in our analyses.
Future applications of our proposed framework should include this and other potentially key missing indicators. This study contributes to our understanding of the global burden of infant mortality and disaggregation to the country level with regards to associated high-impact determinants for policy tailoring.
Maternal mortality survival appeared to be the most prominent risk factor for infant mortality, followed by lack of access to sanitation, female education, and lack of access to water. Substantial heterogeneity exists across regions and countries with regards to the most important factor.
The model also suggests that there is potentially significant underestimation of IMR in regions known for poorer data quality. The framework will potentially aid policymakers in retailoring time-appropriate interventions to more effectively reduce IMR and associated high-risk indicators in the post-Millennium Development Goal era and thus potentially build on momentum garnered for associated determinants during this era.
BS and KS contributed to the conception and design, interpretation of data, and drafting of the manuscript. BS contributed to the acquisition of data and analysis. BS and KS have given final approval of the version to be published and agree to be accountable for all aspects of the work in ensuring that questions related to the accuracy or integrity of any part of the work are appropriately investigated and resolved.
Both authors read and approved the final manuscript. In general significant clustering of high attributability decomposition values for all selected determinants was observed Figure 7 a-d below , especially in SSA in general. Descending top 50 decomposition values by selected determinant and country, as well as spatial clustering of these determinants, — [Note: dark grey represents significant spatial clustering of high decomposition values].
Lack of Sanitation: African countries again showed the highest attributably of IMR due to lack of sanitation Figure 7 b , as well as strong spatial clustering of high decomposition values due lack of sanitation. However, high and significant spatial clustering attributably due to sanitation was also in South America and parts of Central Asia. Lack of Water: The distribution of significant clustering of high decomposition importance of lack of access to water was almost identical to that of lack of access to sanitation, particularly in SSA, central Asia, and parts of South America Figure 7 c.
Maternal Mortality: Significant spatial concentration of high contiguous decomposition values for maternal mortality as a determinant of infant mortality was largely concentrated in SSA Figure 7 d with sporadic clustering in parts of the Middle East and Central Asia.
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