Keywords
sudden unexpected infant death (SUID), sudden infant death syndrome (SIDS), verbal autopsy
sudden unexpected infant death (SUID), sudden infant death syndrome (SIDS), verbal autopsy
Child mortality rates in sub-Saharan Africa are particularly high. In 2019, more than half of the global under-five mortalities occurred in sub-Saharan Africa1. Nearly one child in 13 dies before reaching the age of five in sub-Saharan Africa1. The risk of dying before the age of five is almost 20 times higher in sub-Saharan Africa compared to countries in other WHO regions1. Sadly, most of these deaths are preventable. Zambia like other countries in Africa is similarly burdened by high rates of child mortality. In 2018, the under-five mortality rate in Zambia was estimated to be 61 per 1000 live births, nearly two times the global under-five mortality rate2. A total of 69% of the country’s child mortality occurred in children under one year of age2. The infant mortality rate was almost four times the global infant mortality rate (42 vs 11 per 1000 live births)2. While infectious diseases such as pneumonia, and malaria are recognized as leading causes of child mortality in Zambia, the contribution of sleep related conditions such as sudden unexpected infant death (SUID) to child mortality is less well documented.
SUID includes sudden infant death syndrome (SIDS) and accidental suffocation and strangulation in bed (ASSB). SIDS is currently one of the leading causes of preventable infant mortality in wealthier countries and is defined as the sudden unexpected death of an infant less than one year of age where cause of death remains unexplained even after an autopsy and death scene investigation, and where the event occurred after a sleep episode3. National infant mortality statistics in Zambia rarely include data on SIDS or SUID. The prevailing view in Zambia and most African countries is that SIDS is not an important cause of infant mortality. This need not be the case since SIDS has consistently been identified as a leading cause of infant mortality wherever it has been studied. For instance, even in South Africa, mortality due to SIDS is particularly high compared to high-income countries such as the U.S., Australia and the U.K., with estimated rates of between 3.01 to 3.70 per 1000 live births4,5. South Africa is an outlier on the African continent with relatively better socio-economic conditions compared to other countries in Africa including Zambia. SIDS rates in Zambia are likely to be higher since the socio-economic risk factors for SIDS, young maternal age, poor maternal education and low income, are prevalent in Zambia.
Zambia has made tremendous progress in reducing its infant mortality rates from 107 in 1992 to 42 in 20182. To sustain this progress, the contribution of less well documented causes of infant mortality such as SIDS/SUIDs need to be investigated. The objective of this study was to estimate the burden of SIDS/SUIDs in a representative African country such as Zambia using free text narratives from a modified verbal autopsy tool. To guide this study, our research question was ‘What proportion of decedent infants died suddenly and unexpectedly during sleep in Lusaka, Zambia’?
Data collection for this study occurred in Lusaka, the capital city of Zambia. Lusaka has a predominantly urban population (84%) of 1.7 million. It is surrounded by unofficial peri-urban compounds/towns where most of the city’s poor reside bringing the total population of Lusaka to approximately 2.4 million individuals, or roughly 1/8th of the total population of Zambia itself. A dozen primary health facilities provide health care to the population with the University Teaching Hospital (UTH) serving as the main referral facility6. UTH is the largest hospital in Zambia with 1655 beds and serves as the main training institution for doctors, nurses and other clinical officers7,8.
Data was collected as part of the Zambian Pertussis/RSV Infant Mortality Estimation (ZPRIME) project. The ZPRIME project, a Bill and Melinda Gates sponsored project, was a post-mortem prevalence study designed to identify the proportion of deaths aged four days to less than six months that were attributable to Bordetella pertussis and respiratory syncytial virus (RSV) in Lusaka, Zambia9. ZPRIME enrolled deceased subjects aged four days to less than six months who died in UTH or in the community and presented at the UTH morgue9. Ethical approval for ZPRIME was provided by the institutional review board at the University of Zambia (Ref. No. 2017-May-053, Approval date: 07/21/2017) and Boston University Medical Center (IRB Number: H-36469, Approval date: 06/06/2017).
For this present study, we focus on infant deaths that occurred in the community. Verbal autopsies (VA) were conducted with families and/or caregivers of 809 decedents aged four days to six months who presented at the University Teaching Hospital Morgue (UTH) as BIDs (Brought in dead).
An infant was eligible for a verbal autopsy if the infant had died:
Data collectors trained in grief counselling conducted verbal autopsies with families of eligible infants using an abbreviated verbal autopsy tool with close ended questions about the symptoms immediately preceding the infant’s death. An open response narrative question encouraged respondents to describe, in as much detail as possible, the circumstances leading to the infant’s death. The open response field was prompted by the question: “Now, using your own words, please describe the events leading up to your child’s death. Please take as much time as you need and be as detailed as you can.”6 The VA tool modified for use in this study was the IHME-modified version of the verbal autopsy tool created and validated by the Population Health Metrics Research Consortium (PHMRC) (PHMRC: Shortened verbal autopsy instrument)9,10.
Data collectors were notified if an eligible BID decedent presented at the UTH Morgue. Informed consent was sought from respondents and those who gave consent were interviewed. In addition to the VA tool, demographic information such as maternal and paternal education, occupation, and household census was collected. We also collected data on the closest clinic where the infant usually received care as a proxy for the location of the residence. In total, 809 verbal autopsies (VAs) were conducted between August 2017 and August 2020 as part of ZPRIME. Please see the underlying data11.
To estimate the proportion of infants who died suddenly and unexpectedly, we focused our analysis on the open response narrative in the VA tool. We did this in two steps. Firstly, we qualitatively coded the free text narratives in Microsoft Excel 2021 (RRID:SCR_016137) and classified the responses into symptomatic and asymptomatic (suspected SUIDs) deaths based on reports of danger signs of ill health within the week immediately preceding death. Any narrative with reports of fever, difficulty breathing, cough, hospital admissions or other symptoms within the week immediately preceding death were classified as symptomatic deaths and assigned a score of 0. Any narrative that described an infant who was otherwise healthy with no antecedent illness prior to death or reported to have no symptoms or hospital admissions in the week prior to death and reported to be found dead in bed after a sleep episode were classified as asymptomatic deaths or suspected SUID and assigned a score of 1.
We further classified the asymptomatic deaths into unexplained (possible SIDS) and explained deaths (possible suffocation/smothering (ASSB)). A SUID death was explained if the narrative suggested suffocation or smothering as the likely cause of death based on:
finding of blood or vomitus/milk from the nose/mouth after bed sharing with parents with or without a compressed abdomen
descriptions of mothers or fathers rolling on the baby after a night of drinking or
finding of baby in a prone position with a cloth in the mouth or muffled by blankets
In the second step, the coded data was then uploaded into SAS software v9.4 (SAS Institute Inc., Cary, NC, USA) (RRID:SCR_008567) and quantitatively analyzed (The analysis can also be performed using R Statistical Software (v4.2.1; R Core Team 2022) (RRID:SCR_001905)). We calculated frequencies and percentages for dichotomous and categorical data and estimated mean and standard deviation for continuous data. We used logistic regression for univariate and multivariate analysis to test statistical differences between symptomatic and asymptomatic deaths on key infant, maternal and other demographic risk factors of SUIDs. All statistical analysis were conducted at a 0.05 significance level. We calculated odds ratios (OR), and 95% confidence intervals (95% CI) to show statistical differences in univariate and multivariate analysis. Included are sample narratives for SUID cases to show our coding decisions.
There were slightly more females than males in the sample (44% vs 43.8%). Most of the BIDs occurred in infants younger than two months old with a mean age of 2.3 months (SD = 1.7 months). The majority had normal birth weight (mean = 2,629 kg, std = 643 kg) and lived in households with siblings (79.4%, 642/809). The mothers of these infants were mostly unemployed (78.4%, 634/809) and seldom had education beyond secondary school. Only 2.9% (24/809) of mothers reported completing post-secondary school. Educational attainment for fathers was also low. A total of 6.1% (49/809) of fathers had some or completed post-secondary school. However, the majority of fathers were reported to be self-employed or salaried employees (79.4%, 642/809). Almost all the infants lived with their mother at the time of death (99.4%). Nearly a quarter of infants did not live with both parents with fathers present in 77.1% (624/809) of households. Household sizes tended to be larger with a mean of 5.6 persons and standard deviation 2.4 persons. The majority of these households had greater than four children in the household (34.2%, 277/809). Demographic characteristics of these BIDs are presented in Table 1.
Most of the BID infants, 92.6% (749/809), presented with symptoms prior to death with 38.2% (309/809) presenting with respiratory symptoms and 54.4% (440/809) with non-respiratory or other symptoms. The proportions of each cause of death identified in the narratives are shown in Table 2. However, 7.4% (60/809) presented with no preceding symptoms and were classified as suspected SUIDs. Of these, 27% (16/60) had narratives that were suggestive of accidental suffocation or strangulation in bed (ASSB) and 73% (44/60) were classified as suspected SIDS. Table 3 and Table 4 contain a verbatim list of representative narratives for possible SIDS and ASSB to show the coding decisions made in distinguishing between these two causes of SUIDs. A full list of narratives has been included as supplementary tables.
More than half, 51.7% (31/60) of the suspected SUID cases were female with a mean age of 2.1 months (SD = 1.6 months). The majority lived in households with a sibling, 80% (48/60). Educational attainment of SUID mothers was seldom beyond secondary school. Only 1.7% (1/60) were reported to have completed post-secondary school. Most of these mothers were also unemployed, 86.7% (52/60), and lived in larger households with a mean household size of 6.1 persons with more than four children in the household (40%, 24/60). All the suspected SUID cases lived with their mother in the household at the time of death with fathers present in 78.3% (47/60) of these households. Nearly 22% (13/60) of mothers were single mothers. Symptomatic cases were likely to be aged 2.3 months (SD = 1.7months), male (44.6%, 334/749), and with normal birthweight (mean = 2,646 grams, std = 642 grams). Mothers of symptomatic cases were also likely to have had some or completed secondary education (55.3%, 414/809), and were unemployed (77.7%, 582/749). Household sizes of symptomatic cases tended to be smaller (mean = 5.6, std = 2.3), and almost always included the mother (99%, 744/749) or father (77%, 577/809). Demographic characteristics of asymptomatic and symptomatic cases are shown in Table 5.
Peak age of SUID. Figure 1 summarizes the distribution of suspected SUID cases by age, time of death, month, and season. The mean age of suspected SUID cases was 2.1 months. Overall, deaths were concentrated in infants younger than two months with a peak age of 1–2 months. More importantly, we found that a quarter, 25% (15/60) of SUID deaths occurred in infants within the first month of life although it has generally been considered that SUIDs are rare in the neonatal period.
A. Age distribution of suspected SUID cases. B. Distribution of suspected SUID cases by time of day. C. Monthly distribution of suspected SUID cases. D. Seasonal* distribution of suspected SUID cases. * Hot and Rainy: Nov, Dec, Jan, Feb, Mar, Apr; Cold and Dry: May, Jun, Jul, Aug; Hot and Dry: Sept, Oct.
Time of day of SUID. All the suspected SUID cases occurred during sleep with peak incidence in the night, 37% (22/60), and early morning, 38% (23/60). Very few occurred in the evening, 15% (9/60) with even fewer in the afternoon, 10% (6/60).
Month and season of SUID. The majority of the suspected SUID cases occurred in the cold months of May, June, July, and August with peak incidence in August, 15% (9/60). By season, this corresponds to the cold and dry seasons of Lusaka. Half of the suspected SUID deaths occurred in the cold and dry season with almost 40% (24/60) occurring during the rainy season. Fewer deaths occurred in the hot and dry season of September and October.
Univariate and multivariate analysis of factors associated with SUID. In univariate analysis, age of death in months and time of death were found to be statistically associated with an asymptomatic presentation. Compared to infants aged less than one month, infants aged between one and two months had 2.6 times increased odds of suspected SUIDs, and this risk was statistically significant (OR: 2.6, 95% CI: 1.31–5.27). The odds of SUID occurring in the night was also 2.64 times higher compared to the afternoon (OR: 2.64, 95% CI: 1.04–6.63). There was an increased odds of SUIDs for female infants, mothers with low education or no employment, larger families with four or more children and the cold/dry season. However, these were not significant with 95% CI which contained the null value as shown in Table 6. In multivariate analysis, infants aged between one and two months had 2.84 increased odds of suspected SUIDs compared to infants in the first month of life (AOR = 2.84, 95% CI: 1.31, 6.16). Unemployed mothers also had 2.49 increased odds of suspected SUID compared to salaried or self-employed mothers (AOR: 2.49, 95% CI: 1.02, 6.08)
Characteristic | Unadjusted OR (95% CI) | Adjusted OR† (95% CI) |
---|---|---|
Infant characteristics | ||
Age in months | ||
<1 | 1.00 | 1.00 |
1–2 | 2.63 (1.31, 5.27) * | 2.93 (1.36, 6.33) * |
2–3 | 1.23 (0.52, 2.89) | 1.29 (0.52, 3.21) |
3–4 | 0.68 (0.22, 2.11) | 0.82 (0.25, 2.67) |
4–5 | 1.45 (0.57, 3.69) | 1.76 (0.66, 4.70) |
5–6 | 0.85 (0.28, 2.64) | 0.66 (0.18, 2.46) |
Sex/gender | ||
Male | 1.00 | 1.00 |
Female | 1.59 (0.89, 2.85) | 1.51 (0.80, 2.83) |
Unknown | 1.67 (0.74, 3.79) | 2.03 (0.81, 5.08) |
Has siblings | ||
No | 1.00 | 1.00 |
Yes | 1.12 (0.57, 2.22) | 1.00 (0.45, 2.19) |
Maternal characteristics | ||
Education | ||
Secondary/postsecondary | 1.00 | 1.00 |
Primary/never attended school | 1.20 (0.70, 2.08) | 1.02 (0.57, 1.82) |
Occupation | ||
Employed | 1.00 | 1.00 |
Unemployed | 2.34 (0.99, 5.54) | 2.49 (1.02, 6.08) * |
Domestic composition | ||
Number of children | ||
1–3 | 1.00 | 1.00 |
≥4 | 1.34 (0.78, 2.30) | 1.62 (0.86, 3.07) |
Father lives in household | ||
No | 1.00 | 1.00 |
Yes | 1.07 (0.56, 2.02) | 1.33 (0.65, 2.71) |
Time of day, and season | ||
Time of day | ||
Afternoon | 1.00 | 1.00 |
Night | 2.64 (1.04, 6.63) * | 2.70 (0.97, 7.51) |
Morning | 1.92 (0.77, 4.83) | 2.06 (0.75, 5.68) |
Evening | 2.03 (0.70, 5.87) | 2.65 (0.84, 8.37) |
Season | ||
Hot and rainy | 1.00 | 1.00 |
Cold and dry | 1.60 (0.91, 2.79) | 1.67 (0.90, 3.12) |
Hot and dry | 0.91 (0.36, 2.29) | 1.08 (0.41, 2.83) |
Our main finding from this analysis is that apparent sudden unexpected infant death accounts for 7.4% of all BIDS in Lusaka, Zambia of which 5.4% were apparent SIDS deaths and 2% were likely due to accidental suffocation. While there is a dearth of data describing the burden of SUID across most of Africa12, our findings are similar to estimates of SUID from South Africa, where SIDS/SUID deaths accounted for between 6.2% to 8.7% of all infant deaths in medico legal laboratories13,14. These findings suggests that SIDS/SUIDs are an important cause of infant death in Zambia; however, it is going unreported.
Our analysis revealed three noteworthy findings. Firstly, the peak age of SUID in our analysis was one to two months. Age at death was the only factor that was significant in multivariate analysis with infants aged one to two months at significantly higher odds of SUID compared to infants in the first year of life. Our findings are different from estimates in the U.S. and other high-income countries where the peak age of SUID has been reported as two to four months15. However, our findings are similar to findings by Heathfield et al. in South Africa where they reported a peak age of one to two months in SUID cases16. In addition, we found a quarter of our SUID cases occurred in the first month of life. The triple risk model suggest that SIDS occurs in a vulnerable infant at a critical period of development in the presence of an exogenous stressor17. More than half of the SUID cases occurred in families residing in the densely populated peri-urban townships surrounding Lusaka. We hypothesize that these infants are exposed to exogenous stressors at a much earlier age such as infections compared to infants in high-income countries. Moreover, Heathfield et al. hypothesized that infants in overcrowded settlements experience a faster decline in maternal IgG than infants in high-income countries, making them vulnerable to sudden death at an earlier age16.
Secondly, more than half of our SUID cases were female (51.7% vs 33.3%). This finding is different from what has been reported elsewhere. Most studies report higher rates of SUIDs in males than females18. Although not statistically significant, we found females to be at increased odds of SUID compared to males. However, this finding should be interpreted with caution since 12.2% of our cases were missing a gender assignment. We also found the same socio-economic risk factors that have been reported previously including higher SUID cases among unemployed mothers, mothers with lower educational attainment, larger families with more than four children, during the cold season, and in the early morning hours when infants are sleeping19–21, confirming the presence of some of the risk factors of SIDS in these communities.
This is the first study to report on the prevalence of SUIDs in Zambia and the first study to describe the burden of SUID in Africa outside of South Africa. Our findings suggest SUID could be accounting for a significant proportion of infant deaths, but this cause of infant mortality is going unrecognized. The risk factors of SUIDs are modifiable with simple interventions. This study shows that there is a large enough burden of disease to merit the implementation of specific interventions or programs targeted at reducing sudden infant death in this population. A sudden infant death can be stressful to the family especially young mothers. Some of the narratives were heart breaking. A common theme in these narratives was a need to understand what caused the death of their child. The response to a SIDS/SUID death has been one of blame and sometimes mothers have been criminalized on suspicion that they intentionally caused the death of their child. We want to shed a light on this important cause of infant mortality and make a case for increased research as well as the implementation of targeted campaigns and programs on SIDS in Zambia.
A key limitation of this study is that we relied on VA narratives to assign a cause of death. We did not conduct a death scene investigation or formal autopsy. For that reason, we consider these to be ‘presumptive’ SUID cases since they lack the gold standard evaluation. With that said, the apparent burden revealed in our analysis is very similar to what has been described in South Africa using that gold standard evaluation and is also consistent with what was described in high-income settings prior to the introduction of SIDS interventions. While there could be some misclassification, the most parsimonious explanation is that most of these are indeed examples of SUID. Another limitation is that we did not collect any information on other key risk factors of SIDS such as maternal smoking or alcohol use and infant sleep practices from the mothers of the deceased infants. However, in a separate analysis recently accepted for publication, we report a high prevalence of SUID risk factors and behaviors from mothers of infants in the same communities as in the current cohort. These included low rates of sleeping in a prone position as recommended, high frequency of bed sharing, bundling of infants with duvets and blankets, and exposure to indoor air pollution and alcohol use22.
Future studies should prospectively characterize SUID deaths with complete diagnostic autopsy and death scene investigation. This is a preliminary study to show if there is enough burden of disease to encourage future research.
Written informed consent for publication of the participants’ details was obtained from the parents, guardian or relative of the participant.
Figshare: Underlying data for ‘The apparent burden of unexplained sudden infant deaths in Lusaka, Zambia: Findings from analysis of verbal autopsies’.
https://doi.org/10.6084/m9.figshare.2174637511
This project contains the following underlying data:
Data file 1: Supplementary Tables_SIDS in Zambia_VA.pdf
Data file 2: VA_Figshare.xlsx
Data file 3: verbal_autopsy_figshare.sas7bdat
Data file 4: SASCodeVA_figshare.sas
Data file 5: SASCodeVA_figshare.pdf (pdf of SAS Code)
Data are available under the terms of the Creative Commons Attribution 4.0 International license (CC-BY 4.0)
We wish to acknowledge the contribution of the data collection team in Zambia who showed a lot of courage in collecting these heartbreaking narratives. We also thank the families of the deceased infants for their willingness to share their stories with us. Without them this work would not have been possible. We also thank the Bill and Melinda Gates foundation for funding the ZPRIME study which provided these rich narratives for analysis.
Views | Downloads | |
---|---|---|
Gates Open Research | - | - |
PubMed Central Data from PMC are received and updated monthly. | - | - |
Is the work clearly and accurately presented and does it cite the current literature?
Yes
Is the study design appropriate and is the work technically sound?
Yes
Are sufficient details of methods and analysis provided to allow replication by others?
Yes
If applicable, is the statistical analysis and its interpretation appropriate?
Yes
Are all the source data underlying the results available to ensure full reproducibility?
Partly
Are the conclusions drawn adequately supported by the results?
Partly
Competing Interests: No competing interests were disclosed.
Reviewer Expertise: Sudden Infant Death
Alongside their report, reviewers assign a status to the article:
Invited Reviewers | |
---|---|
1 | |
Version 1 15 Feb 23 | read |
Provide sufficient details of any financial or non-financial competing interests to enable users to assess whether your comments might lead a reasonable person to question your impartiality. Consider the following examples, but note that this is not an exhaustive list:
Sign up for content alerts and receive a weekly or monthly email with all newly published articles
Register with Gates Open Research
Already registered? Sign in
If you are a previous or current Gates grant holder, sign up for information about developments, publishing and publications from Gates Open Research.
We'll keep you updated on any major new updates to Gates Open Research
The email address should be the one you originally registered with F1000.
You registered with F1000 via Google, so we cannot reset your password.
To sign in, please click here.
If you still need help with your Google account password, please click here.
You registered with F1000 via Facebook, so we cannot reset your password.
To sign in, please click here.
If you still need help with your Facebook account password, please click here.
If your email address is registered with us, we will email you instructions to reset your password.
If you think you should have received this email but it has not arrived, please check your spam filters and/or contact for further assistance.
Comments on this article Comments (0)