Worldwide incidences of neonatal early- and late-onset invasive group B streptococcal disease (iGBS), estimated at 0.4 and 0.3 cases per 1000 live births, mask considerable heterogeneity even between countries with similar resources.1 Within-country differences in infant iGBS related to ethnicity are also evident. In the United States, the national picture indicates up to twofold higher iGBS rates in Black compared with White infants against a backdrop of declining early-onset but not late-onset disease.2 Black women in the United States are more likely to be identified as colonized with Streptococcus agalactiae during pregnancy and to have iGBS infection.3 In England, maternal iGBS rates were similarly higher in non-White groups, with some evidence of higher GBS colonization rates in Black women from a study in London.4,5 Here we report rates of infant iGBS by ethnicity using national data for England over a 5-year period.
Methods
Laboratory-confirmed iGBS cases with specimen dates between January 1, 2016, and December 31, 2020, were extracted from the United Kingdom Health Security Agency (UKHSA) national microbiology surveillance system.6 Infant iGBS was defined as isolation of Streptococcus agalactiae from a normally sterile site at 0 to 6 days of life for early-onset iGBS and 7 to 90 days for late-onset disease. Parent-reported infant ethnicity was obtained by linking iGBS cases to National Health Service [NHS] Digital Hospital Episode Statistics hospital admission records. Hospital records from the NHS in England use ethnic categories defined by the United Kingdom Office for National Statistics. Annual live births data from the Office for National Statistics by ethnic group were used to calculate iGBS rates and rate ratios. All data were collected within statutory approvals granted to UKHSA for infectious disease surveillance and control.
Results
There were 2512 infant iGBS cases in England during 2016 to 2020, of which 1639 (65.3%) were early-onset and 873 (34.8%) late-onset (0.52 and 0.28 cases per 1000 live births). Linkage was successful for 92.3% (2318) of cases, of which 92.7% (2149) had ethnicity data. Compared with White infants (0.43 per 1000 live births), Black infants had 48% higher (0.63) and Asian infants 40% higher (0.60) rates of early-onset iGBS (Table 1), the latter driven by 87%, 38% and 55% higher rates in infants of Bangladeshi (0.81), Pakistani (0.59), and other Asian (0.67) descent. In contrast, Indian infants had a similar early-onset rate (0.47) to White infants. Black infants had 57% higher rates of late-onset iGBS (0.37) than White infants (0.24), accounted for by 74% higher rates among Black African infants (0.41), who represented 70% of live births among all infants of Black ethnicity.
Rates of Early- And Late-Onset Invasive Group B Streptococcal Disease in England By Infant’s Ethnicity, 2016–2020
. | Early-Onset . | Late-Onset . | Live Births (2016–2020)b . | Early-Onset Rate Per 1000 Live Births (95% CI) . | Early-Onset Rate Ratio (95% CI) . | Late-Onset Rate Per 1000 Live Births (95% CI) . | Late-Onset Rate Ratio (95% CI) . | Early- Plus Late-Onset Rate Per 1000 Live Births (95% CI) . | Early- Plus Late-Onset Rate Ratio (95% CI) . |
---|---|---|---|---|---|---|---|---|---|
Infant’s Ethnicitya . | n . | n . | N . | ||||||
Total | 1639 | 873 | 3 154 637 | 0.52 (0.49–0.55) | — | 0.28 (0.26–0.30) | — | 0.80 (0.77–0.83) | — |
Recorded ethnicity | 1409 | 740 | 3 063 372 | 0.46 (0.44–0.48) | — | 0.24 (0.22–0.26) | — | 0.70 (0.67–0.73) | — |
White | 969 | 530 | 2 253 635 | 0.43 (0.40–0.46) | 1.00 (Reference) | 0.24 (0.22–0.26) | 1.00 (Reference) | 0.67 (0.63–0.70) | 1.00 (Reference) |
British | 801 | 460 | 1 881 682 | 0.43 (0.40–0.46) | — | 0.24 (0.22–0.27) | — | 0.67 (0.63–0.71) | — |
Other | 168 | 70 | 371 953 | 0.45 (0.39–0.53) | — | 0.19 (0.15–0.24) | — | 0.64 (0.56–0.73) | — |
Multiple ethnic background | 70 | 39 | 204 018 | 0.34 (0.27–0.43) | 0.80 (0.62–1.02) | 0.19 (0.14–0.26) | 0.81 (0.57–1.13) | 0.53 (0.44–0.64) | 0.80 (0.66–0.98) |
White and Asian | 14 | 7 | — | — | — | — | — | — | — |
White and Black | 24 | 16 | — | — | — | — | — | — | — |
Other | 32 | 16 | — | — | — | — | — | — | — |
Black | 100 | 58 | 157 582 | 0.63 (0.52–0.77) | 1.48 (1.19–1.81) | 0.37 (0.28–0.48) | 1.57 (1.17–2.06) | 1.00 (0.85–1.17) | 1.51 (1.27–1.78) |
African | 68 | 45 | 110 081 | 0.62 (0.48–0.78) | 1.44 (1.11–1.84) | 0.41 (0.30–0.55) | 1.74 (1.25–2.36) | 1.03 (0.85–1.23) | 1.54 (1.26–1.87) |
Caribbean | 18 | 7 | 28 041 | 0.64 (0.38–1.01) | 1.49 (0.88–2.37) | 0.25 (0.10–0.51) | 1.06 (0.42–2.20) | 0.89 (0.58–1.32) | 1.34 (0.86–1.99) |
Other Black | 14 | 6 | 19 460 | 0.72 (0.39–1.21) | 1.67 (0.91–2.82) | 0.31 (0.11–0.67) | 1.31 (0.48–2.87) | 1.03 (0.63–1.59) | 1.55 (0.94–2.40) |
Asian | 224 | 91 | 370 894 | 0.60 (0.53–0.69) | 1.40 (1.21–1.63) | 0.25 (0.20–0.30) | 1.04 (0.83–1.31) | 0.85 (0.76–0.95) | 1.28 (1.13–1.44) |
Bangladeshi | 39 | 8 | 48 405 | 0.81 (0.57–1.10) | 1.87 (1.32–2.58) | 0.17 (0.07–0.33) | 0.70 (0.30–1.39) | 0.97 (0.71–1.29) | 1.46 (1.07–1.95) |
Pakistani | 82 | 40 | 137 863 | 0.59 (0.47–0.74) | 1.38 (1.09–1.73) | 0.29 (0.21–0.40) | 1.23 (0.87–1.70) | 0.88 (0.73–1.06) | 1.33 (1.10–1.60) |
Indian | 49 | 18 | 103 505 | 0.47 (0.35–0.63) | 1.10 (0.81–1.47) | 0.17 (0.10–0.27) | 0.74 (0.43–1.18) | 0.65 (0.50–0.82) | 0.97 (0.75–1.24) |
Other Asianc | 54 | 25 | 81 121 | 0.67 (0.50–0.87) | 1.55 (1.15–2.04) | 0.31 (0.20–0.45) | 1.31 (0.84–1.96) | 0.97 (0.77–1.21) | 1.46 (1.15–1.84) |
Other | 46 | 22 | 77 243 | 0.60 (0.44–0.79) | 1.39 (1.01–1.86) | 0.28 (0.18–0.43) | 1.21 (0.75–1.85) | 0.88 (0.68–1.12) | 1.32 (1.02–1.69) |
. | Early-Onset . | Late-Onset . | Live Births (2016–2020)b . | Early-Onset Rate Per 1000 Live Births (95% CI) . | Early-Onset Rate Ratio (95% CI) . | Late-Onset Rate Per 1000 Live Births (95% CI) . | Late-Onset Rate Ratio (95% CI) . | Early- Plus Late-Onset Rate Per 1000 Live Births (95% CI) . | Early- Plus Late-Onset Rate Ratio (95% CI) . |
---|---|---|---|---|---|---|---|---|---|
Infant’s Ethnicitya . | n . | n . | N . | ||||||
Total | 1639 | 873 | 3 154 637 | 0.52 (0.49–0.55) | — | 0.28 (0.26–0.30) | — | 0.80 (0.77–0.83) | — |
Recorded ethnicity | 1409 | 740 | 3 063 372 | 0.46 (0.44–0.48) | — | 0.24 (0.22–0.26) | — | 0.70 (0.67–0.73) | — |
White | 969 | 530 | 2 253 635 | 0.43 (0.40–0.46) | 1.00 (Reference) | 0.24 (0.22–0.26) | 1.00 (Reference) | 0.67 (0.63–0.70) | 1.00 (Reference) |
British | 801 | 460 | 1 881 682 | 0.43 (0.40–0.46) | — | 0.24 (0.22–0.27) | — | 0.67 (0.63–0.71) | — |
Other | 168 | 70 | 371 953 | 0.45 (0.39–0.53) | — | 0.19 (0.15–0.24) | — | 0.64 (0.56–0.73) | — |
Multiple ethnic background | 70 | 39 | 204 018 | 0.34 (0.27–0.43) | 0.80 (0.62–1.02) | 0.19 (0.14–0.26) | 0.81 (0.57–1.13) | 0.53 (0.44–0.64) | 0.80 (0.66–0.98) |
White and Asian | 14 | 7 | — | — | — | — | — | — | — |
White and Black | 24 | 16 | — | — | — | — | — | — | — |
Other | 32 | 16 | — | — | — | — | — | — | — |
Black | 100 | 58 | 157 582 | 0.63 (0.52–0.77) | 1.48 (1.19–1.81) | 0.37 (0.28–0.48) | 1.57 (1.17–2.06) | 1.00 (0.85–1.17) | 1.51 (1.27–1.78) |
African | 68 | 45 | 110 081 | 0.62 (0.48–0.78) | 1.44 (1.11–1.84) | 0.41 (0.30–0.55) | 1.74 (1.25–2.36) | 1.03 (0.85–1.23) | 1.54 (1.26–1.87) |
Caribbean | 18 | 7 | 28 041 | 0.64 (0.38–1.01) | 1.49 (0.88–2.37) | 0.25 (0.10–0.51) | 1.06 (0.42–2.20) | 0.89 (0.58–1.32) | 1.34 (0.86–1.99) |
Other Black | 14 | 6 | 19 460 | 0.72 (0.39–1.21) | 1.67 (0.91–2.82) | 0.31 (0.11–0.67) | 1.31 (0.48–2.87) | 1.03 (0.63–1.59) | 1.55 (0.94–2.40) |
Asian | 224 | 91 | 370 894 | 0.60 (0.53–0.69) | 1.40 (1.21–1.63) | 0.25 (0.20–0.30) | 1.04 (0.83–1.31) | 0.85 (0.76–0.95) | 1.28 (1.13–1.44) |
Bangladeshi | 39 | 8 | 48 405 | 0.81 (0.57–1.10) | 1.87 (1.32–2.58) | 0.17 (0.07–0.33) | 0.70 (0.30–1.39) | 0.97 (0.71–1.29) | 1.46 (1.07–1.95) |
Pakistani | 82 | 40 | 137 863 | 0.59 (0.47–0.74) | 1.38 (1.09–1.73) | 0.29 (0.21–0.40) | 1.23 (0.87–1.70) | 0.88 (0.73–1.06) | 1.33 (1.10–1.60) |
Indian | 49 | 18 | 103 505 | 0.47 (0.35–0.63) | 1.10 (0.81–1.47) | 0.17 (0.10–0.27) | 0.74 (0.43–1.18) | 0.65 (0.50–0.82) | 0.97 (0.75–1.24) |
Other Asianc | 54 | 25 | 81 121 | 0.67 (0.50–0.87) | 1.55 (1.15–2.04) | 0.31 (0.20–0.45) | 1.31 (0.84–1.96) | 0.97 (0.77–1.21) | 1.46 (1.15–1.84) |
Other | 46 | 22 | 77 243 | 0.60 (0.44–0.79) | 1.39 (1.01–1.86) | 0.28 (0.18–0.43) | 1.21 (0.75–1.85) | 0.88 (0.68–1.12) | 1.32 (1.02–1.69) |
—, Live birth denominators unavailable for these subgroups..
Recorded in hospital admission records.
Office for National Statistics. Neonatal deaths by ethnicity of infant in England, 2007 to 2019 (2019 data were used for 2020 births because 2020 data were not yet available).
Including infants of Chinese ethnicity (15 early-onset, 4 late-onset).
Discussion
This population-wide data analysis reveals marked differences in iGBS rates among Black and minority ethnic infants in England, excepting infants of Indian heritage. Differences in iGBS rates may reflect differential maternal GBS carriage, including for late-onset iGBS,7 with a hospital study in England reporting higher prevalence of GBS colonization in mothers from Black and some Asian ethnic groups, but lower prevalence in mothers from the Indian subcontinent (mainly from India).4 National data show higher rates of maternal iGBS in Black and minority ethnic groups, albeit without differentiating Indian mothers,5 whereas international data show higher early- and late-onset iGBS rates in Africa than in Europe, North America, and Australia, but lower or similar rates in Asia (again, without differentiating between countries).1
Our findings echo differentials by ethnicity in maternal colonization and neonatal iGBS incidence in the United States.2,3 The factors to which these differences might be attributed may not be the same in both countries, given that race and ethnicity are social constructs. Studies in the United Kingdom and United States have shown that differences in pregnancy outcomes by ethnicity cannot simply be explained by socioeconomic inequalities.8–10 In the United Kingdom, intrapartum antibiotic prophylaxis is offered to mothers who present with specific risk factors for infection in the neonate, such as preterm labor or a previous infant with iGBS.11,12
A strength of our study is that it uses whole population data because the NHS provides 98% of hospital care in England. However, whereas all NHS laboratories feed data automatically to the UKHSA national microbiology surveillance system, reporting of GBS is not mandatory. Observational data such as these do not allow elucidation of causality, such as whether higher preterm birth rates in minority ethnic groups (for reasons other than GBS carriage or infection) lead to increased iGBS risk in neonates or whether maternal GBS leads to higher preterm birth rates and subsequent neonatal iGBS. Future linkage of NHS maternal and infant data could support a more in-depth investigation of pregnancy duration, mode of delivery, and other factors that might account for some of the observed differences by ethnicity.
Understanding the factors underpinning differences in rates of early-onset iGBS within south Asian groups in England may lead to new opportunities for prevention such as prioritized antenatal screening. Strategies to prevent neonatal iGBS must be tailored from high-quality quantitative and qualitative data to reach all women and protect all infants, irrespective of racial or ethnic background.
Dr Lamagni conceptualized the study, drafted the initial manuscript, and reviewed and revised the manuscript; Dr Collin extracted and linked the data, conducted the analyses, drafted the initial manuscript, and reviewed and revised the manuscript; Drs Demirjian and Swann critically reviewed the manuscript for important intellectual content; and all authors approved the final manuscript as submitted and agree to be accountable for all aspects of the work.
FUNDING: No external funding.
CONFLICT OF INTEREST DISCLAIMER: The authors have indicated they have no conflicts relevant to this article to disclose.
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