Risk Factors For Infant Mortality Research Articles

Risk factors of children's low birth weight and infant mortality in Bangladesh: Evidence from binary logistic regression and Cox PH models.

Low birth weight is recognized as a pivotal risk factor affecting child survival and growth. Although Bangladesh has made commendable progress in public health, an infant mortality rate of 38 per 1000 live births and a 16% prevalence of low birth weight remain significant concerns compared to other developing countries. This situation poses a significant challenge for the formulation of future health policies in Bangladesh. As a result, this study aims to identify potential risk factors contributing to low birth weight and infant mortality among children in Bangladesh. The data is extracted from the 2014 Bangladesh Demographic and Health Survey. The response variables are infant mortality and low birth weight. In the bivariate analysis, Log-rank tests and Chi-square tests of independence were conducted. Cox proportional hazards and binary logistic regression models were utilized to determine the impact of risk factors on infant mortality and low birth weight. This study identified several significant factors associated with children's low birth weight, including wealth index, parental education, birth order, twin births, mother's body mass index, and child sex. Additionally, wealth index, parental education, twin status, media exposure, birth order, antenatal care visits, prenatal care assistance, and low birth weight were identified as potential risk factors for infant mortality in Bangladesh. This study revealed that maternal and child characteristics, along with knowledge about child health care during pregnancy, can potentially reduce the risk of low birth weight and infant mortality among children in Bangladesh. To improve child health and survival, policymakers should prioritize community-based health education programs, and encourage parents to seek healthcare information from institutional medical facilities during pregnancy and after birth.

The risk factors of infant mortality in Somalia: evidence from the 2018/2019 Somali health & demographic survey

BackgroundGlobally, infant mortality is one of the major public health threats, especially in low-income countries. The infant mortality rate of Somalia stands at 73 deaths per 1000 live births, which is one of the highest infant death rates in the region as well as in the world. Therefore, the aim of this study was to ascertain the risk factors of infant mortality in Somalia using national representative data.MethodIn this study, data from the Somali Health and Demographic Survey (SHDS), conducted for the first time in Somalia in 2018/2019 and released in 2020, were utilized. The analysis of the data involved employing the Chi-square test as a bivariate analysis. Furthermore, a multivariate Cox proportional hazard model was applied to accommodate potential confounders that act as risk factors for infant death.ResultsThe study found that infant mortality was highest among male babies, multiple births, and those babies who live in rural areas, respectively, as compared to their counterparts. Those mothers who delivered babies with small birth size and belonged to a poor wealth index experienced higher infant mortality than those mothers who delivered babies with average size and belonged to a middle or rich wealth index. Survival analysis indicated that mothers who did use ANC services (HR = 0.740; 95% CI = 0.618–0.832), sex of the baby (HR = 0.661; 95% CI = 0.484–0.965), duration of pregnancy (HR = 0.770; 95% CI = 0.469–0.944), multiple births (HR = 1.369; 1.142–1.910) and place of residence (HR = 1.650; 95% CI = 1.451–2.150) were found to be statistically significantly related to infant death.ConclusionThe study investigated the risk factors associated with infant mortality by analyzing data from the first Somali Health and Demographic Survey (SHDS), which included a representative sample of the country’s population. Place of residence, gestational duration, infant’s gender, antenatal care visits, and multiple births were identified as determinants of infant mortality. Given that infant mortality poses a significant public health concern, particularly in crisis-affected countries like Somalia, intervention programs should prioritize the provision of antenatal care services, particularly for first-time mothers. Moreover, these programs should place greater emphasis on educating women about the importance of receiving antenatal care and family planning services, in order to enhance their awareness of these vital health services and their positive impact on infant survival rates.

Trends and distribution patterns of infant mortality and maternal HIV positivity in South Africa: A decade review (2007 - 2016).

The infant mortality rate (IMR) (24 per 1 000 live births) remains high in South Africa (SA), well above the recommended sustainable development goal (SDG) 3 of 12 deaths per 1 000 live births. High infant mortality is a poor indicator of the health of a population and will hamper attainment of the SDGs. To investigate the trends and distribution patterns of IMR between 2007 and 2016 and its association with HIV-positive pregnant mothers in SA. This study used a cross-sectional study design by analysing secondary data on infant mortality from the 2007 and 2016 Statistics South Africa Community Surveys (CSs), as well as data from the 2007 National Antenatal Sentinel HIV and Syphilis Prevalence Survey. (Antenatal HIV Sentinel Survey - ANCHSS). Line charts with descriptive statistics were used to detail trends in IMRs, and multiple logistic regression models were used to identify risk factors for infant mortality in the 2007 and 2016 CS datasets. Spearman's rank-order correlation (rho) was used to correlate infant mortality with data from the 2007 ANCHSS. All analyses were performed with Stata version 16.0. A total sample of 87 805, comprising 43 922 males and 43 883 females, was included in the analysis. The results revealed a decline in IMR from 55 deaths per 1 000 live births in 2007 to 32 in 2016. Overall, there was a significant decrease in the mortality rate from 2007 to 2016. The infant mortality proportions by province showed KwaZulu-Natal Province having the highest IMR (17.5 deaths per 1 000 live births in 2007 and 6.3 in 2016). Males had a higher IMR (28 deaths per 1 000 live births in 2007 and 17.7 in 2016) compared with females at 26.7 deaths per 1 000 live births in 2007 and 13.8 in 2016. IMR data from the 2007 CS was correlated with the 2007 ANCHSS (28% HIV prevalence in 2007), using Spearman's rank-order correlation, which showed a moderate correlation of 0.58 (p<0.001). The study findings showed a reduction in the trends of infant mortality between 2007 and 2016 in SA; despite the reduction, health inequalities persist. There is a correlation evident between maternal HIV prevalence and IMR in SA. We recommend the use of disability-adjusted life expectancy in SA to measure population health and introduce robust data sets that can better inform policy.

Evolution of infant mortality in the Paris region over the past two decades

Abstract Background Infant mortality is one of the major health indicators to appreciate the population health and the organization of the health system. Since the 1990s, the infant mortality rate (IMR) declines less rapidly in France as compared to other Western countries, taking the country from 7th to 27th place in 2017. As the Paris region recorded a quarter of the under one French mortality, we aimed to analyze the evolution of the regional IMR over the last two decades. Methods Using 2000 to 2019 data from the National Institute of Statistic and Economic Study on births and deaths, we ran joinpoint regressions model to analyze the evolution of mortality of infant under one. We also examined IMR by age at death subgroups (early neonatal [Day 0-D6], late neonatal [D7-27], and post-neonatal[D28-364]). We also analyzed territorial disparities. Results Over 20 years, 13,401 deaths and 3,389,048 live births were recorded among children under one in the Paris region, IMR: 3.,93 deaths per 1000 live births, an average of 18% higher than the national IMR. Data from evolution shows that Paris region’ IMR was 4.51‰ in 2001 and reached its lowest level in 2013 with 3.65‰ before rising to 3.99‰ in 2019. The joinpoint regression model shows a decline in the IMR between 2000 and 2003 (-3.78% annually), followed by a slow and steady decline between 2003 and 2011 (-1.57%). However, from 2011 to 2019 a significant increase was observed in IMR (+1.48% annually). The analysis of deaths by age-group shows that the IMR increase was mainly driven by the increase in early neonatal mortality and a little less by late neonatal deaths while the post-neonatal mortality continued to decrease. Additional analyses showed territorial disparities in global and subgroups IMR with higher IMR in poorer areas. Conclusions These results are of a higher importance and should alert French authorities. Further studies, considering risk factors of infant mortality are needed to understand the reason of such increase. Key messages • We showed anhistoric and worrying increase in infant mortality in the Paris region. • We showed territorial disparities in global and subgroups IMR with higher IMR in poorer of the Paris region areas.

Geographical disparities and determinants of infant mortality in Ethiopia: mapping and spatial analysis using EDHS data

BackgroundInfant mortality remains a public health challenge in Ethiopia. Exploring infant mortality will aid in tracking the progress toward achieving sustainable development goals.ObjectiveThe study aimed to explore the geographical variations and associated factors of infant mortality in Ethiopia.MethodA total of 11,023 infants from the 2016 Ethiopian Demographic and Health Survey (EDHS) data were extracted and included in the analysis. EDHS used a two-stage cluster sampling design with a census enumeration area as the primary sampling unit and households as the secondary sampling unit. Arc GIS software was used for spatial analysis using clusters for exploring geographical variations in infant mortality. A binary logistic regression was employed using R software to identify the significant determinants of infant mortality.ResultsThe study revealed that the spatial distribution of infant mortality was non-random in the country. Infants whose mothers not receiving ANC (AOR = 1.45; 95%CI: 1.17, 1.79), not breastfed status (AOR = 3.94; 95%CI: 3.19, 4.81), poor wealth index (AOR = 1.36; 95%CI: 1.04, 1.77), male infants (AOR = 1.59; 95%CI: 1.29, 1.95), birth order of six or above (AOR = 3.11; 95%CI: 2.08, 4.62), small birth size (AOR = 1.27; 95%CI: 1.26, 1.60), birth spacing [(≤ 24 months (AOR = 2.29; 95%CI: 1.79, 2.92), 25–36 months (AOR = 1.16; 95%CI: 1.12, 1.49)], multiple births (AOR = 6.82; 95%CI: 4.76, 10.81), rural residence (AOR = 1.63; 95%CI: 1.05, 2.77) and regions [Afar (AOR = 1.54; 95%CI: 1.01, 2.36), Harari (AOR = 1.56; 95%CI: 1.04, 2.56), and Somali (AOR = 1.52; 95%CI: 1.03, 2.39)] were the determinants of infant death in Ethiopia.ConclusionsThere is a great geographical disparity in infant mortality rates across regions. Afar, Harari, and Somali regions were verified as hot spot areas. ANC usage, breastfed status, wealth index, sex of the infant, birth order, birth size, birth spacing, birth type, residence, and region were the determinants of infant death in Ethiopia. Therefore, appropriate interventions need to be implemented in the hot spots to alleviate the risk factors for infant mortality.

Evaluation of a Program to Reduce Infant Mortality Risk Factors in Central Indiana.

The purpose of the program WeCare was to provide a personalized approach to addressing the wide array of psycho-social-cultural-fiscal needs to reduce risk factors for infant mortality (IM) by supporting maternal and infant health through health coaching by community health workers (CHWs). A prospective cohort study of 1,513 women from highest risk ZIP codes for IM in central Indiana were followed over three years. The WeCare program focused on training and deploying CHWs to provide evidence-based, patient-centered social care and support to pregnant and postpartum women and tracked outcomes in health risk categories (mental health, nutrition, safe sleep, breastfeeding) targeted for behavioral change. The low birth weight rate among program participants was lower (8.9%) than Marion County's rate (10%) (p=0.23) with statistically significant improvement in many risk behaviors. Despite limitations, the personalized coaching provided by the CHWs provided an effective, practical approach to maternal and child health disparities.

Birth weight reference for Japanese twins and risk factors for infant mortality: A population-based study.

There is no standard birth weight curve for twins in Japan other than a prototype curve based on 1988–1991. Twins have a high perinatal mortality rate than singletons; therefore, we developed a new standard curve for twin birth weight using data from the 1995–2016 Vital Statistics and compared it with previous reports. We used 469,064 cases for analysis, excluding stillbirths and cases with missing values, and created a standard curve using LMS (statistical methods to vary the distribution by using skewness, median, and coefficient of variation) method. In comparison with previous reports, the mean birth weight decreased by 100–200 g. The groups with the lowest neonatal death rates (NDRs) and infant death rates (IDRs) were those with a birth weight of 1,500–2,499 g (NDR: 0.3%, IDR: 0.6%) and those born at 34–36 weeks (NDR: 0.2%, IDR: 0.4%). Compared to these, the IDR was significantly higher in the 2,500–3,999 g group and the 37–39 weeks group (incidence rate ratio (IRR): 1.1 in the 2,500–3,999 g group, IRR: 1.3 in the 37w0d–39w6d group). In particular, the risks of neonatal mortality and infant mortality were higher in infants born at a birth weight above 3,500 g. Infants born at a birth weight above 3,500 g may include recipients of twin-to-twin transfusion syndrome. The most common causes of infant mortality are accidental death and sudden infant death syndrome (SIDS). We considered the possibility that infants treated as healthy newborns and whose mothers were discharged from the hospital without adequate twin care guidance may be more likely to experience unintentional accidents and SIDS at home. The present study suggested that creating a new twin birth weight standard curve and guidance on managing twins at home for full-term and normal birth weight infants may lead to a reduction in infant deaths.

Low Birth Weight Baby and Its Associated Factors among Rural Women in Bangladesh: A Decision Curve Analysis

Background: Low birth weight is considered to be one of the main risk factors for infant mortality and morbidity. It is associated with a range of both short- and long-term consequences. Objectives: The study examined the factors contributing to low birth weight of the baby in Bangladesh. This study also attempted with the objective of ensuing a prediction of low birth weight. Methods: The study was a case-control quantitative survey. A three-stage cluster sample design was used to conduct the survey. A total of 674 (337 cases and 337 control) mothers/care givers of under 1 year children were selected from 2 districts of Bangladesh. Binary logistic regression and decision curve analysis were used to investigate the factors which attribute to low birth weight baby born. Results: The findings of the study revealed that mean birth weight was 2.1±0.4 kg among low birth weight children whereas it was 3.0±0.5 kg for normal birth weight children. The mean age of sampled mothers was 25.2±5.4 years. Every 2 in 3 mage got married before 18 years. The prevalence of low birth weight baby among the women with secondary or higher education was lower (47.4%) compared to the women no formal education (65.4%). Analysis revealed that several socio-demographic factors like parental education level, maternal age at first marriage, working status were significantly associated with low birth weight of the baby (p&lt;0.05). Some biological and medical factors like multiple births, maturity of the birth, prenatal care and taking iron and folic acid during pregnancy were also significantly associated with low birth weight baby born. Finally, decision curve analysis technique predicted a net benefit of 0.3907 for the profitable model with highest number of factors. This result implies that the fitted model can predict 39% low birth weight based on independent factors. Conclusion: Prediction model indicates that parental and biological factors are caused for low birth weight baby born in rural areas. Maternal and child health program should focus behavioural change regarding create awareness of disadvantage of early marriage, intake IFA supplementation, at least 4 ANC visit to reduce low birth weight baby born. Bangladesh Med Res Counc Bull 2021; 47(1): 42-49

The Partial Least Squares Spline Model for Public Health Surveillance Data.

Factor discovery of public health surveillance data is a crucial problem and extremely challenging from a scientific viewpoint with enormous applications in research studies. In this study, the main focus is to introduce the improved survival regression technique in the presence of multicollinearity, and hence, the partial least squares spline modeling approach is proposed. The proposed method is compared with the benchmark partial least squares Cox regression model in terms of accuracy based on the Akaike information criterion. Further, the optimal model is practiced on a real data set of infant mortality obtained from the Pakistan Demographic and Health Survey. This model is implemented to assess the significant risk factors of infant mortality. The recommended features contain key information about infant survival and could be useful in public health surveillance-related research.

A survey study of the impact of COVID-19 on women at high risk for infant mortality in Central Indiana

Background/Objective: The WeCare program aims to reduce infant mortality through the community health worker model by assisting high risk women of child-bearing age. The COVID-19 pandemic introduced additional challenges for women already at high risk factor for infant mortality (IM). The aim of this survey study is to assess the impact of the COVID-19 pandemic in this population.&#x0D; Methods: Enrolled WeCare participants were given an optional COVID-19 phone survey (modified from the IeDEA survey*) between August 2020 and May 2021 to assess the impact of COVID-19 on their daily lives, income, food security, and mental health. Trained research assistants and community health workers administered surveys. Verbal consent was obtained over the phone. Data was entered into REDCap. From REDCap, data was exported to SAS version 9.4 to calculate descriptive statistics and chi square tests.&#x0D; Results: Fifty-six primarily women of color (68%) completed the survey. Sixty-two percent of women lived in high-risk zip codes for infant mortality in Central Indiana. Fifty-seven percent of women worked prior to the outbreak. Forty-eight percent of the working women lost income, and seventy percent of women worked jobs requiring interaction with the public. These women experienced greater food insecurity (38%), depression (24%), and anxiety (31%) compared to before the pandemic (p&lt;0.001).&#x0D; Conclusion/Discussion: The demographics and residence of those interviewed were representative of the WeCare cohort (NS differences in race/ethnicity/age). In comparing the prevalence of food insecurity, depression and anxiety between the survey sampled during covid and prior to covid, all factors were significantly increased. These vulnerable women (many pregnant or postpartum), often major breadwinners in their household, held jobs putting them at high risk for covid infections, and lost these high-risk jobs at an alarming rate. These data confirm the detrimental impact of COVID-19, especially on a population already at high risk for IM. &#x0D; Acknowledgement of original authors of the *IeDEA survey: Suzanne Goodrich, Michael Scanlon, Leslie Enane, Kara Wools-Kaloustian

Risk factors of infant mortality in rural The Gambia: a retrospective cohort study

ObjectiveThe main objective was to assess the risk factors for infant mortality among children living in the Health and Demographic Surveillance System (HDSS) in Farafenni, The Gambia. Our secondary objective...

Maternal Factors Associated with Low Birth Weight Babies Delivered in Selected Primary Health Care Centres in Abuja Municipal Area Council, FCT, Nigeria

Introduction: Globally, low birth weight remains a public health challenge and is a major risk factor for infant mortality. Therefore, this study investigated the factors associated with low birth weight babies delivered in health facilities within Abuja, Nigeria. Methodology: Secondary data from January 2017 to December 2020 was extracted from 330 delivery records in ten (10) Primary Health Care centres to assess the determinants of low birth weight babies born in Abuja. Findings: The results showed that the mean age of mothers was 27.8 ± 5.1. Majority of the mothers (93.6%) were between 16 and 35 years of age, 93.6% were married, 67% were Christians, 23.3% had no formal education, 31.5% were housewives and 75.8% lived in rural communities. The mean birth weight of babies was 3.05 ± 0.55 kg and 20.3% of the babies had low birth weight compared to 79.7% with normal weights at birth. Maternal age, p=0.02; marital status, p=0.02; religion, p=001; occupation, p=0.001; and weight, p=0.000 were found to be significantly associated with having LBW babies. Maternal obstetric characteristics such as birth spacing, p=0.00; haematocrit level, p=0.001; pregnancy termination, p=0.001; and medical conditions, p=0.00 were also significantly associated with birth weight. Conclusion: The study reported a high prevalence of low birth weight; it also revealed the protective effects of being married on LBW. However, being a housewife significantly increased the risk for having a low birth weight baby.

Predictive Factors of Infant Mortality Using Data Mining in Iran

Objectives: Reducing infant mortality in the whole world is one of the millennium development goals.The aim of this study was to determine the factors related to infant mortality using data mining algorithms. Methods: This population-based case-control study was conducted in eight provinces of Iran. A sum of 2,386 mothers (1,076 cases and 1,310 controls) enrolled in this study. Data were extracted from health records of mothers and filled with checklists in health centers. We employed several data mining algorithms such as AdaBoost classifier, Support Vector Machine, Artificial Neural Networks, Random Forests, K-nearest neighborhood, and Naïve Bayes in order to recognize the important predictors of infant death; binary logistic regression model was used to clarify the role of each selected predictor. Results: In this study, 58.7% of infant mortalities occurred in rural areas, that 55.6% of them were boys. Moreover, Naïve Bayes and Random Forest were highly capable of predicting related factors among data mining models. Also, the results showed that events during pregnancy such as dental disorders, high blood pressure, loss of parents, factors related to infants such as low birth weight, and factors related to mothers like consanguineous marriage and gap of pregnancy (&lt; 3 years) were all risk factors while the age of pregnancy (18 - 35 year) and a high degree of education were protective factors. Conclusions: Infant mortality is the consequence of a variety of factors, including factors related to infants themselves and their mothers and events during pregnancy. Owing to the high accuracy and ability of modern modeling compared to traditional modeling, it is recommended to use machine learning tools for indicating risk factors of infant mortality.

Assessing Risk Factors for Infant Mortality in the US: State of the Art

Assessing Risk Factors for Infant Mortality in the US: State of the Art

Trends and risk factors for infant mortality in the Lao People\u2019s Democratic Republic

A high infant mortality rate (IMR) indicates a failure to meet people’s healthcare needs. The IMR in Lao People’s Democratic Republic has been decreasing but still remains high. This study aimed to identify the factors involved in the high IMR by analyzing data from 53,727 live births and 2189 women from the 2017 Lao Social Indicator Survey. The estimated IMR decreased from 191 per 1000 live births in 1978–1987 to 39 in 2017. The difference between the IMR and the neonatal mortality rate had declined since 1978 but did not change after 2009. Factors associated with the high IMR in all three models (forced-entry, forward-selection, and backward-selection) of multivariate logistic regression analyses were auxiliary nurses as birth attendants compared to doctors, male infants, and small birth size compared to average in all 2189 women; and 1–3 antenatal care visits compared to four visits, auxiliary nurses as birth attendants compared to doctors, male infants, postnatal baby checks, and being pregnant at the interview in 1950 women whose infants’ birth size was average or large. Maternal and child healthcare and family planning should be strengthened including upgrading auxiliary nurses to mid-level nurses and improving antenatal care quality.

Estimating infant mortality risk in Uruguay using artificial neural networks

Abstract Background Uruguay has a national electronic live birth certificate that includes variables of risk factors for infant mortality. Accurate risk stratification of newborns is needed to optimize the use of resources for homes visits. Artificial neural networks are computational tools that have been used successfully in many types of prediction problems. Objective To develop a neural network able to estimate the risk of infant mortality using information available in the electronic live birth and mortality certificate in Uruguay. Methods A historical cohort of records of newborns in Uruguay from 2014 to 2017 was used. The variables of the electronic live birth certificate were considered for the model. Infant mortality was obtained from the national mortality registry. A multilayer perceptron was trained with a random sample of 70% of the cohort; the remaining 30% was the validation set. The variables included were birth weight, Apgar score at 5 minutes, number of prenatal consultations, maternal educational level, multiple pregnancy and cohabiting father. ROC curve analysis was performed. Results The 2014-2017 birth cohort contains 187,388 records. 1,307 children under one year died (IMR 6.97 per 1,000 births). The area under the curve (AUC) was 88.7%, 95% CI [87.6% - 89.8%]. The optimal cut-off point of pseudoprobability of infant mortality was 0.008 (78.9% of sensibility and 82.4% of specificity). The IMR in high-risk newborns identified by the neural network was 32.8 per 1,000 births. Conclusions The neural network identifies high-risk newborns at the time of entering the data in the electronic live birth certificate as other models have done. This information could be used to plan and implement preventive actions. Key messages In Uruguay, high-risk newborns can be identified by applying artificial intelligence to data collected routinely. The procedure can be applied in other countries with electronic birth certificate.

Maternal education and offspring birth weight for gestational age: the mediating effect of smoking during pregnancy.

Small for gestational age (SGA) birth weight, a risk factor for infant mortality and delayed child development, is associated with maternal educational attainment. Maternal tobacco smoking during pregnancy could contribute to this association. We aimed to quantify the contribution of maternal smoking during pregnancy to social inequalities in child birth weight for gestational age (GA). Data come from the French nation-wide ELFE cohort study, which included 17 155 singletons. Birth weights for GA were calculated using z-scores. Associations between maternal educational attainment, tobacco smoking during pregnancy and child birth weight for GA were ascertained using mediation analysis. Mediation analyses were also stratified by maternal pre-pregnancy body mass index. Low maternal educational attainment was associated with an increased odd of tobacco smoking during pregnancy [adjusted OR (ORa) = 2.58 (95% CI 2.34-2.84)] as well as a decrease in child birth weight for GA [RRa = 0.94 (95% CI 0.91-0.98)]. Tobacco smoking during pregnancy was associated with a decrease in offspring birth weight for GA [RRa = 0.73 (95% CI 0.70-0.76)]. Mediation analysis suggests that 39% of the effect of low maternal educational attainment on offspring birth weight for GA was mediated by smoking during pregnancy. A more important direct effect of maternal educational attainment on child birth weight for GA was observed among underweight women [RRa = 0.82 (95% CI 0.72-0.93)]. The relationship between maternal educational attainment and child birth weight for GA is strongly mediated by smoking during pregnancy. Reducing maternal smoking could lessen the occurrence of infant SGA and decrease socioeconomic inequalities in birth weight for GA.

Maternal Bereavement the Year Before or During Pregnancy and Total and Cause-Specific Infant Mortality: A Cohort Study From Denmark and Sweden.

We analyzed the associations between maternal bereavement the year before or during pregnancy and total and cause-specific infant mortality (IM). We studied live singleton births from the Danish (1978-2008) and Swedish Medical Birth Registers (1973-2006; N = 5,114,246). Information on maternal sociodemographic, pregnancy-related, and health-related factors, and death of family members was obtained from nationwide registers. Among children of mothers with register links to family members and without the considered IM risk factors, 110,993 (2.76%) were exposed and 15,199 (0.4%) died in infancy. Death of an older child the year before or during pregnancy was associated with an increased IM risk (adjusted odds ratio [aOR; 95% confidence intervals {CIs}] = 2.05 [1.44-2.92]). Losing an older child the year before pregnancy or during pregnancy was associated with risks of prematurity-related IM (aOR [95% CI] = 2.61 [1.44-4.72] and 3.08 [1.70-5.57]) and with infant death in term-born children due to causes other than sudden infant death syndrome, congenital malformations, or asphyxia (aOR [95% CI] = 3.31 [1.58-6.96] and 5.10 [1.27-20.43]). Losing an older child during pregnancy was also associated with increased risks of sudden infant death syndrome (aOR [95% CI] = 5.41 [1.34-21.83]). Death of a partner during pregnancy was associated with IM (aOR [95% CI] = 1.83 [1.01-3.32]). The number of events was small and CIs were wide in some subanalyses, and caution is needed when interpreting our results. Severe prenatal stress may increase the risk of several types of IM. Whether less severe but more common maternal stressors shortly before or during pregnancy also increase IM risk warrants further investigation.

Determinants of infant mortality in Pakistan: evidence from Pakistan Demographic and Health Survey 2017–18

The infant mortality rate was very high in Pakistan until the early 1990s, at 86 deaths/1000 live births. It has decreased 24 points and declined to 62 deaths/1000 in the last 3 decades, but Pakistan is still in the group of countries with highest infant mortality rate. The present study aimed to assess the magnitude of infant mortality in Pakistan and its causes and associated risk factors. For this study, data from the 2018 Pakistan Demographic and Health Survey were used. Risk factors for infant mortality were first examined in bivariate analyses. Chi-square test was employed to understand the significance level of the categorical difference of independent variables. The Cox proportional hazard model was used to account for potential confounders that function as risk factors for infant deaths. Large differentials in infant survival by socioeconomic and demographic factors indicate poor coverage of social and health schemes for the public. Mothers who did not use the ANC services experienced about 1.5 times higher infant mortality than those who did (52 vs. 36/1000 LB; p = 0.007). The hazard model shows that rich households experienced about 30% (HR = 0.735; 95% CI = 0.614–0.878) less infant mortality than poor ones. The rural-urban differential in public health services and gender inequities are the underlying causes of the stagnation of infant mortality in Pakistan. The low status of women’s education, poor economic conditions and low level of using public health care services are closely tied to higher infant death rates in Pakistan. Health interventions in Pakistan should be designed to reach the most under-served—women and children—especially in rural areas.

Individual and contextual determinants of infant mortality in Brazilian state capitals: a multilevel approach

The study sought to identify individual and contextual risk factors in healthcare and their interactions and regional differences in the determination of infant mortality in Brazilian state capitals. This was a case-control study that analyzed 7,470 infant deaths in 2012 in the 27 state capitals, recorded in the Brazilian Mortality Information System (SIM) and matched with the Brazilian Information System on Live Births (SINASC) through linkage and 24,285 controls obtained by sampling the surviving liveborn infants from 2011 to 2012 from the total of 1,424,691 births. The individual explanatory variables corresponded to information available in the SINASC database, and the contextual variable consisted of a quality index for hospital care in the 702 healthcare services where the births occurred. A multilevel logistic model was used to analyze interaction. The principal determinants of infant mortality were biological factors (low birthweight, prematurity, congenital malformations, severe/moderate asphyxia, and race/color), mediated by maternal socioeconomic factors (schooling, marital status, and occupation) and insufficiency of prenatal care. Low number of prenatal visits was a risk factor for infant mortality, independently of the service's quality, except in the state capitals in the South of Brazil. In the interaction between income and prenatal care, few prenatal visits and birth in high-income state capitals showed a higher risk when compared to births in low-income state capitals (OR = 0.68). Multilevel analysis evidenced regional inequalities in the risk models and reiterated the importance of biological determinants in the mediation of socioeconomic and healthcare factors in infant mortality.