The effect of heatwaves on adverse birth outcomes is not well understood and may vary by how heatwaves are defined. The study aims to examine acute associations between various heatwave definitions and preterm and early-term birth.th percentile of MSA-specific temperature metrics, or the 85th percentile of positive excessive heat factor (EHF) were created. Odds ratios (OR) for heatwave exposures in the week preceding birth  were estimated using conditional logistic regression adjusting for maternal age, marital status, and seasonality. Effect modification by maternal education, age, race/ethnicity, child sex, and region was assessed.Using national vital records from 50 metropolitan statistical areas (MSAs) between 1982 and 1988, singleton preterm (< 37 weeks) and early-term births (37–38 weeks) were matched (1:1) to controls who completed at least 37 weeks or 39 weeks of gestation, respectively. Matching variables were MSA, maternal race, and maternal education. Sixty heatwave definitions including binary indicators for exposure to sustained heat, number of high heat days, and measures of heat intensity (the average degrees over the threshold in the past 7 days) based on the 97.5th percentile of mean temperature in the past week compared to zero days, the OR was 1.027 for early-term birth . Although we generally found null associations when assessing various heatwave definitions and preterm birth, ORs for both preterm and early-term birth were greater in magnitude among Hispanic and non-Hispanic black mothers.There were 615,329 preterm and 1,005,576 early-term case-control pairs in the analyses. For most definitions, exposure to heatwaves in the week before delivery was consistently associated with increased odds of early-term birth. Exposure to more high heat days and more degrees above the threshold yielded higher magnitude ORs. For exposure to 3 or more days over the 97.5Although associations varied across metrics and heatwave definitions, heatwaves were more consistently associated with early-term birth than with preterm birth. This study’s findings may have implications for prevention programs targeting vulnerable subgroups as climate change progresses.The online version contains supplementary material available at 10.1186/s12940-021-00733-y. Preterm birth  is a leading cause of infant mortality and long-term neurological disabilities in children . ChildreRecent studies suggest that higher ambient temperatures are associated with an increase in preterm birth –16 and ath percentile) for more than a certain number of consecutive days [th percentile of temperature and to temperatures over the past 30 days. The choice of temperature metrics may be important, because different metrics measure different aspects of heatwaves. For example, minimum temperatures may reflect the lack of overnight cooling [Broadly, there are two major frameworks for defining heatwaves commonly used in the literature. One widely used framework is based on a temperature metric  exceeding a pre-specified threshold, which can be absolute  or relative  for the years 1982–1988, years for which location and exact birth date are publicly available. A total of 25,328,335 births occurred during 1982–1988. We selected births from the 50 most populous metropolitan statistical areas (MSA), accounting for 52% of all births in the US. Delineation of MSAs was based on the 2010 Census. The 50 MSAs contained 416 counties. 20% of births were in the two most populous MSAs ; because of the disproportionate number of births in those two MSAs, we split them into smaller areas. Los Angeles-Long Beach-Santa Ana, CA was split into two parts  and Td is mean dew-point temperature.where https://www2.census.gov/programs-surveys/popest/tables/1980-1990/counties/totals/e8089co.xls) to the meteorological data and calculating population-weighted mean of the county-level estimates within a location.For study locations comprised of more than one county, we calculated daily meteorological variables for each location by linking county-level population size obtained from the 1980 Census (th percentile [97.5) as the cut-off value for six temperature metrics: Tmin, ATmin, Tmax, ATmax, Tmean, and ATmean.We used two major heatwave definition frameworks Fig.  from thercentile , 38–40 . Specifically, the calculations are given asT95 is the 95th percentile (location-specific) of daily temperature for the climate reference period 1982–1988;accl is the difference between 3-day average temperature and 30-day average temperature; and2.The other framework Arrow 2, Fig. , Fig. 2 97.5 or EHF+ 85), we operationalized heatwave exposures in each location on each day in three different ways , categorized as 0, 1, 2, and 3 or more days, 3–7 days were grouped together to gain more precision;CX: emphasizes the impact of sustained heat, indicator variables for ≥x consecutive (denoted as subscript CX) hot days in the past week ;HW297.5 threshold value from the daily temperature  and averaging these daily differences over the last week. If the 7-day average was less than 0, the AUC was set to 0. AUC values were analyzed as a non-negative continuous variable.HW3: area under the curve (AUC) during the previous week is a continuous metric incorporating both intensity and duration, calculated by subtracting the THeatwave indicators were linked to women based on their MSA codes and gestational exposure window. Using the above 12 indicators for hot days  [CX was modeled as a binary variable  consecutive-day heatwave in the past week, 0 = otherwise, Table S2 for EHF, Table SWe used a 1:1 matched case-control design with cumulative sampling , which e5 years) , 21, marTo examine possible effect modification by maternal characteristics on the associations of heatwaves with preterm and early-term births, we conducted analyses stratified by maternal education , maternal race/ethnicity , child sex , and region  and tested interaction by adding an interaction term with heatwave indicators to our primary model (Table Sth percentile (HW1) was 18 times more common than having 4 or more consecutive days above the 85th percentile for EHF (HW2). In general, the 97.5th percentile of temperature metrics (T97.5) resulted in more heatwave days compared to the 85th percentile of positive EHF (EHF+ 85). For example, the mean number of days per year (across years and locations) which had 3 or more days over the threshold in the past week was between 8.5–9.9 days (depending on the temperature metric when T97.5 was used), whereas it ranged between 2.0–2.4 days for EHF+ 85 (Table 97.5 compared to 0.8–1.2 days per year per location using EHF+ 85. The mean area under the curve (AUC) for EHF+ 85 was larger than T97.5 due to the inflation factor by extreme temperature relative to the past 30 days  in the EHF calculation. The mean AUC was between 0.52–0.91 °C and 1.2–3.8°C2 for T97.5 and EHF+ 85, respectively, varying by temperature metrics used ; 28.8% of mothers completed exactly 12 years of education, and 30.8% were from southern study locations , the OR for early-term birth was 1.027  for mothers who experienced 3 or more hot days during the week before delivery, compared to those who experienced zero hot days , the OR was 1.045  in the week before delivery. For example, when exposed to 1, 2, or 3 or more days with Tmax over Tmax97.5 in the week before delivery compared to 0 days, ORs were 1.002 , 1.017 , and 1.018 , respectively  of heatwaves for each outcome and found that using apparent temperature produced results similar to those using temperature only Fig. . To exam97.5. Results from the stratified analysis by maternal race/ethnicity suggested that associations of heatwaves and early-term birth tended to be of larger magnitude for Hispanic and non-Hispanic black mothers compared to non-Hispanic white mothers. When exposed to HW2C4 (≥4 consecutive days of heat in the week before delivery vs otherwise), the ORs for Hispanic and non-Hispanic black mothers were 1.100  and 1.054 , respectively, whereas the OR for non-Hispanic white mothers was 1.019 . Although we did not observe a significant overall association with preterm birth, we found a higher OR among Hispanic and non-Hispanic black mothers. For example, per 1 °C increase in HW3 (average number of degrees that 7-day average Tmean higher than Tmean97.5), the ORs for Hispanic and non-Hispanic black mothers were 1.064  and 1.060 , respectively, whereas it was 0.977  for non-Hispanic white mothers  impacted the association between heatwave and preterm and early-term birth using data from 50 metropolitan areas in the US during 1982–1988. Across definitions, exposure to heatwaves in the week before delivery was consistently associated with increased odds of early-term birth. Specifically, we found that exposure to 3 or more single hot days in the past week, ≥3 consecutive days of a sustained heatwave, and increased heatwave intensity (the average degrees over the threshold in the past 7 days) were associated with early-term birth. Associations with preterm birth were weaker compared to early-term birth. Heatwaves defined using maximum temperature showed the most elevated ORs, but the elevation was modest, and most estimates were close to the null. However, effect modification by maternal race/ethnicity was found for both preterm and early-term birth. Specifically, heatwave associations were larger in magnitude among Hispanic and non-Hispanic black mothers compared to non-Hispanic white mothers. In several previous studies, investigators reported positive associations between heatwaves and preterm birth, with larger magnitudes compared to our study , 42. In th percentile. Based on our results we expect modest differences in association based on heatwave definition between these studies, but a HR of 1.27 is a considerably higher than any estimate observed in our study.In the existing literature, early-term birth has received less attention in temperature and heatwave studies. Our findings on early-term birth were consistent with previous findings that exposure to heatwaves or high ambient temperature in the last week before delivery was associated with an increase in the rate of early-term birth , 43. EveHeat-related mechanisms are plausible to explain the early onset of labor during extreme heat. Some studies suggest that heat stress increases uterine contraction , 45, andWe observed that heatwaves were more strongly associated with both early-term and preterm birth among non-Hispanic black and Hispanic mothers. These findings are in-line with those from previous studies , 47, 48.Although previous physiological research has shown that high humidity increases the risk of heat-related illness associated with high temperatures , 55, wheIn our study, no single temperature metric best predicted health outcomes. Overall, the use of mean, maximum, minimum temperature, as well as apparent temperature variants, showed similar patterns of associations with the outcomes. When they differed from each other, the associations were not always stronger for a specific temperature metric, indicating that the specific temperature metric might not be an important factor impacting the magnitude of the association between heatwaves and early-term and preterm birth.th percentile of temperature, even in our large dataset. Broadly, using EHF as a metric to define heatwaves generally produced similar patterns but a larger magnitude in the ORs for most heatwave definitions. Reasons why including an acclimation factor in the calculation might help to identify heatwaves that most strongly impact birth outcomes remains an outstanding question.Heatwaves defined using EHF were more intense and rare. We observed larger associations in heatwave indicators using EHF with early-term birth; however, due to the rarity of heatwaves based on this framework, estimates were discernibly more uncertain compared to heatwaves defined based on the 97.5This was a nationwide study evaluating the impact of heatwaves on adverse birth outcomes across 50 metropolitan areas covering different climate zones in the US. We systematically evaluated various heatwave definitions to examine how changing those parameters would affect the effect estimates of heatwaves on preterm and early-term birth. To estimate the acute impact of heatwaves while also accounting for seasonality in conception rates, we used a matched case-control study to compare exposure during the same gestational window for cases and controls. To be a confounder in our analysis, a risk factor for these outcomes would have to be correlated with heatwaves, and we controlled tightly for the seasonality and longer-term time trends using indicators for the month of study (based on LMP) to reduce this possibility. The results were robust to matching on LMP month and year instead of location and exclusion of observations with missing covariates.A study limitation is that our data are from the 1980s, which is some time in the past. Even so, our findings could enable researchers to compare the impact of heatwaves on health changes across decades, when factors such as air conditioning prevalence as well as the frequency, duration, and intensity of heatwaves were different. In addition, we investigated a variety of heatwave definitions, which increases the probability of type one error due to multiple comparisons. However, our interpretations focus on the holistic trends across definitions instead of isolated statistically significant associations. In addition, maternal education was missing for 28% of the birth records. However, maternal education not expected to be a confounder because it is not associated with heatwaves, which lessens concerns about missingness. We also examined the associations of heatwave indicators and preterm and early-term birth among those with missing education; we did not find differences in odds ratios between those missing an education value and other education groups.th percentile threshold cut-off, the EHF measures yielded higher ORs with increased uncertainty.Our results suggest that heatwave duration and intensity are positively associated with an increase in early-term births. The association with preterm birth was slightly elevated for some heatwave definitions, but most of the results suggested no association. However, subgroup analyses by race/ethnicity yielded evidence of positive associations; heatwaves had stronger associations with both early-term and preterm birth for Hispanic and non-Hispanic black mothers, which could help guide intervention programs to mitigate heatwave impacts for vulnerable populations. Our findings suggest that estimated associations based on apparent temperature were similar to those based on temperature. We found no consistent indication that minimum, maximum, or mean temperature was most strongly associated with the outcomes, suggesting that any of these metrics may be appropriate for future research. Finally, relative to the 97.5Additional file 1: Figure S1. Map of Los Angeles-Long Beach-Santa Ana MSA. The MSA was split into Los Angeles county (mint green) and Orange county (light orange). Figure S2. Map of New York-North New Jersey-Long Island MSA. The MSA was split into the Long Island area (blue), New York City area (pink), and other New York and New Jersey counties (green). Figure S3. Illustration of the selection of pregnancies whose at-risk windows overlap with the warm season for preterm (blue) and early-term birth (orange) where pregnancy 1-4 (four arrow lines) are extreme examples determining the range of the eligible LMP dates. The at-risk window was defined as 28 weeks and 0 days to 36 weeks and 6 days for preterm birth and 37 weeks and 0 days to 38 weeks and 6 days for early-term birth. Figure S4. Flow chart of identification of preterm and early-term cases and matching control. Table S1. Detailed model specification for the analyses of preterm and early-term birth for different types of heatwave indicators. Table S2. Odds ratio estimates of heatwave indicators based on definition framework 1 (97.5th percentile of temperature) on early-term birth matching on maternal race, maternal education, and location. Table S3. Odds ratio estimates of heatwave indicators based on definition framework 2 (85th percentile of positive excessive heat factor) on early-term birth matching on maternal race, maternal education, and location. Table S4. Odds ratio estimates of heatwave indicators based on definition framework 1 (97.5th percentile of temperature) on preterm birth matching on maternal race, maternal education, and location. Table S5. Odds ratio estimates of heatwave indicators based on definition framework 2 (85th percentile of positive excessive heat factor) on preterm birth matching on maternal race, maternal education, and location. Table S6. Odds ratio estimates of heatwave indicators based on definition framework 1 (97.5th percentile of temperature) on preterm birth matching on maternal race, maternal education, and month and year of the last menstrual period. Table S7. Odds ratio estimates of heatwave indicators based on definition framework 2 (85th percentile of positive excessive heat factor) on preterm birth matching on maternal race, maternal education, and month and year of the last menstrual period. Table S8. Odds ratio estimates of heatwave indicators based on definition framework 1 (97.5th percentile of temperature) on early-term birth matching on maternal race, maternal education, and month and year of the last menstrual period. Table S9. Odds ratio estimates of heatwave indicators based on definition framework 2 (85th percentile of positive excessive heat factor) on early-term birth matching on maternal race, maternal education, and month and year of the last menstrual period. Table S10. Odds ratio estimates of heatwave indicators based on definition framework 1 (97.5th percentile of temperature) on preterm birth matching on maternal race, maternal education, and location, excluding those with missing matching factors and covariates. Table S11. Odds ratio estimates of heatwave indicators based on definition framework 1 (97.5th percentile of temperature) on early-term birth matching on maternal race, maternal education, and location, excluding those with missing matching factors and covariates. Figure S5. Odds ratio estimates of heatwave indicators on early-term birth by maternal education  using mean temperature over 97.5th percentile to quantify heatwave. P-values were calculated from the joint test for interaction. Figure S6. Odds ratio estimates of heatwave indicators on preterm birth by maternal education  using mean temperature over 97.5th percentile to quantify heatwave. P-values were calculated from the joint test for interaction. Figure S7. Odds ratio estimates of heatwave indicators on early-term birth by child sex  using mean temperature over 97.5th percentile to quantify heatwave. P-values were calculated from the joint test for interaction. Figure S8. Odds ratio estimates of heatwave indicators on preterm birth by child sex  using mean temperature over 97.5th percentile to quantify heatwave. P-values were calculated from the joint test for interaction. Figure S9. Odds ratio estimates of heatwave indicators on early-term birth by region  using mean temperature over 97.5th percentile to quantify heatwave. P-values were calculated from the joint test for interaction. Figure S10. Odds ratio estimates of heatwave indicators on preterm birth by region  using mean temperature over 97.5th percentile to quantify heatwave. P-values were calculated from the joint test for interaction.


Fibroblast growth factor 19 (FGF19) has been implicated in glucose homeostasis. Gestational diabetes mellitus (GDM) enhances fetal insulin secretion and fetal growth. Girls weigh less and are more insulin resistant than boys at birth. We sought to assess whether FGF19 is associated with GDM and fetal growth and explore potential sex dimorphic associations. This was a nested case-control study in the Shanghai Birth Cohort, including 153 pairs of newborns of GDM versus euglycemic mothers matched by infant’s sex and gestational age at birth. Cord plasma FGF19, insulin, C-peptide, proinsulin, IGF-I and IGF-II concentrations were measured. Cord plasma FGF19 concentrations were similar in GDM versus euglycemic pregnancies . FGF19 was not correlated with IGF-I or IGF-II. FGF19 concentrations were positively correlated with birth weight  and length  z scores, C-peptide  and proinsulin  concentrations in females. Each SD increment in cord plasma FGF19 was associated with a 0.25 (0.07-0.43) increase in birth weight z score in females. In contrast, FGF19 was not correlated with birth weight or length in males. These sex dimorphic associations remained after adjusting for maternal and neonatal characteristics. The study is the first to demonstrate that GDM does not matter for cord blood FGF19 concentrations. The female specific positive correlation between FGF19 and birth weight is suggestive of a sex-dimorphic role of FGF19 in fetal growth. The observations call for more studies to validate the novel findings and elucidate the underlying mechanisms. FGF1ogenesis , 7, 8. Dogenesis . Animal ogenesis –16, and ogenesis , 18.de novo glucose intolerance in pregnancy) is a common cause of enhanced fetal insulin secretion and overgrowth   case-control study in the Shanghai Birth Cohort (SBC) . The SBCGDM was diagnosed according to the International Association of Diabetes and Pregnancy Study Groups (IADPSG) criteria  - if anyAs part of the SBC, a nested case control study was designed to study the impacts of GDM on metabolic health biomarkers in the newborns . BrieflyBirth weight z scores were calculated using the 2015 Chinese sex- and gestational age-specific birth weight standards . Birth lCord plasma FGF19 was measured by an enzyme-linked immunosorbent assay (ELISA) kit , and the absorbance was determined using a microplate spectrophotometer . Serum insulin and insulin-like growth factor I (IGF-I) concentrations were detected by chemiluminescent assays . Plasma IGF-II was measured by an ELISA kit from R&D systems . Plasma C-peptide and proinsulin were measured by ELISA kits from Mercodia system . Plasma total and high-molecular-weight (HMW) adiponectin were measured by an ELISA kit from ALPCO . Plasma leptin was measured by an ELISA kit from Invitrogen . The detection limits were 1.17 pg/mL for FGF19, 3.5 pmol/L for insulin, 25 ng/mL for IGF-I, 1.88 pg/mL for IGF-II, 25 pmol/L for C-peptide, and 1.7 pmol/L for proinsulin, 0.034 ng/mL for HMW and total adiponectin, and 3.5 pg/mL for leptin, respectively. Intra-assay and inter-assay coefficients of variation were in the ranges of 6.4-11.6% for FGF19, 2.0-6.5% for insulin and IGF-I, 5.0-8.6% for proinsulin, 0.4-13.5% for C-peptide, 2.4-9.3% for IGF-II, and 6.9%-10.4% for leptin, HMW and total adiponectin, respectively. In all biomarker assays, the laboratory technicians were blinded to the clinical status (GDM or not) of study subjects.2), smoking or alcohol use in pregnancy (yes/no), gestational hypertension, family history of diabetes, family history of hypertension, mode of delivery , infant’s sex and gestational age (weeks) at birth. We estimated the changes in birth weight and length z scores per SD increment in FGF19. Mediation analyses were conducted to assess whether fetal growth factors may mediate any associations between FGF19 and fetal growth (birth weight or length) using the product (“Baron and Kenney”) method (Data are presented as mean ± SD (standard deviation) or median (interquartile range) for continuous variables, and frequency (percentage) for categorical variables. Log-transformed biomarker data were used in t-tests, correlation and regression analyses. Pearson partial correlation was used to evaluate the correlations with biomarkers adjusting for gestational age at cord blood sampling/delivery. Differences in correlations in male and female infants were examined by Fisher’s z test. Generalized linear models were applied to assess the associations of cord blood FGF19 with GDM, fetal growth and fetal growth factors adjusting for maternal and neonatal characteristics. The co-variables included maternal age, ethnicity, parity, education (university: yes/no), pre-pregnancy BMI (kg/m) method . Data ma2) and were more likely to have gestational hypertension (5.2% versus 0.6%) and tended to be more likely to have a family history of diabetes (16.5% versus 9.5%) than women with a euglycemic pregnancy. There were no significant differences in other maternal characteristics including maternal age, education, parity, alcohol use or smoking during pregnancy. The newborns of GDM mothers were more likely to be delivered by caesarean section than the newborns of euglycemic mothers (54.3% versus 33.1%). Mean gestational age at delivery was about 39 weeks in both GDM and euglycemic pregnancies (39.1 and 39.3 weeks). There were 142 (46.6%) caesarean section deliveries (97 elective caesarean sections), and 13 (4.3%) preterm births .Characteristics of study subjects in this nested study in the Shanghai birth cohort have been described recently . BrieflyAdjusting for maternal and neonatal characteristics including pre-pregnancy BMI, family history of hypertension, parity, cesarean section and gestational age at delivery , cord plasma FGF19 , proinsulin  and C-peptide  concentrations were similar in GDM and euglycemic pregnancies Table 1.Descriptive data on cord plasma insulin, IGF-I, IGF-II, leptin, total and HMW adiponectin were reported elsewhere , 32. BriCord plasma FGF19 concentrations were similar in male versus female newborns , and were higher in preterm versus term births  and in caesarean section versus vaginal deliveries . Compared with vaginal deliveries, FGF19 concentrations were higher in elective caesarean sections , but similar in emergency caesarean sections . Other maternal and neonatal factors were not associated with cord plasma FGF19 concentrations .There were significant interactions  between FGF19 and infant sex in relation to fetal growth (birth weight or length z score), C-peptide and proinsulin. Therefore, we present the correlation coefficients stratified by infant’s sex. Gestational age was negatively correlated with cord plasma FGF19 . Adjusting for gestational age at delivery/blood sampling, cord plasma FGF19 concentrations were positively correlated with birth weight  and birth length  z scores, C-peptide  and proinsulin  concentrations in female newborns Figure 1Adjusting for maternal and neonatal characteristics in female newborns, each SD increment in cord plasma FGF19 was associated with a 0.25  increase in birth weight (P=0.01), a 0.20  increase in birth length (P=0.047), a 0.18  increase in cord blood insulin (P<0.001), a 0.32  increase in C-peptide (P<0.001), and a 0.44  increase in proinsulin (P<0.001), respectively  in females only, suggesting a sex-dimorphic role of FGF19 in fetal growth.Decreased circulating FGF19 levels have been reported in women with GDM , and in A previous study did not detect any association between caesarean section on cord blood FGF19, probably due to small sample size  and low power . In contvia sex specific intrauterine endocrine or metabolic factors   did not  factors . FGF19 m factors , 23, 24.Our data provide some weak evidence suggesting that insulin may mediate the association between FGF19 and fetal growth in females. Mediation analyses showed that cord blood proinsulin - a precursor to insulin, a surrogate indicator of insulin secretion, partly mediated the positive association between FGF19 and birth weight or length in female newborns, but no mediation effects were observed for insulin, C-peptide, IGF-I or IGF-II. A study in diabetic patients reported that serum FGF19 was positively associated with insulin . We did Interestingly, opposite to the positive correlations between cord plasma FGF19 and C-peptide or proinsulin in females, negative correlations were observed in males. We are unaware of any reports on the correlations between FGF19 and insulin or its secretion related C-peptide and proinsulin in newborns. Our data are suggestive of a sex dimorphic association between FGF19 and chronic insulin secretion levels during fetal life. The positive correlation between FGF19 and C-peptide is consistent with the positive correlation between FGF19 and fetal growth in females. However, the negative correlation between FGF19 and C-peptide is incongruent with the absence of a negative correlation between FGF19 and fetal growth in males, suggesting the need for caution in data interpretation. More studies are warranted to confirm this finding.Circulating FGF19 and insulin concentrations are positively correlated in patients with type 2 diabetes , suggestThe main strengths include the large birth cohort, timely collection and processing of cord blood specimens, and high-quality biochemical assays (low inter-assay and intra-assay coefficients of variation). The main limitation is the observational nature of the study; causality cannot be ascertained. We had no data on inflammatory biomarkers. Future studies may explore whether fetal FGF19 levels are correlated with inflammatory biomarkers. The study was limited to Chinese subjects. More studies in other ethnic groups are required to understand the generalizability of the study findings.In conclusion, our study data indicate that GDM may not affect cord blood FGF19 levels, and that there may be a sex-dimorphic role of FGF19 in fetal growth. The observations call for more studies to validate the novel findings and elucidate the underlying mechanisms.zcluo@lunenfeld.ca; ouyangfengxiu@xinhuamed.com.cn) for assistance in data access request.The datasets presented in this article are not readily available because access to the deidentified participant research data must be approved by the research ethics board on a case-by-case basis, please contact the corresponding authors , the Shanghai Municipal Health Commission (2020CXJQ01), the Shanghai Municipal Science and Technology Commission , the National Natural Science Foundation of China , the National Human Genetic Resources Sharing Service Platform (2005DKA21300), and the Canadian Institutes of Health Research (158616). The funders have no role in all aspects of the study, including study design, data collection and analysis, the preparation of the manuscript and the decision for publication.The authors declare that the research was conducted in the absence of any commercial or financial relationships that could be construed as a potential conflict of interest.All claims expressed in this article are solely those of the authors and do not necessarily represent those of their affiliated organizations, or those of the publisher, the editors and the reviewers. Any product that may be evaluated in this article, or claim that may be made by its manufacturer, is not guaranteed or endorsed by the publisher.


Quantitative risk assessments for Bovine spongiform encephalopathy (BSE) necessitate estimates for key parameters such as the prevalence of infection, the probability of absence of infection in defined birth cohorts, and the numbers of BSE-infected, but non-detected cattle entering the food chain. We estimated three key parameters with adjustment for misclassification using the German BSE surveillance data using a Gompertz model for latent  age-dependent detection probabilities and a Poisson response model for the number of BSE cases for birth cohorts 1999 to 2015. The models were combined in a Bayesian framework. We estimated the median true BSE prevalence between 3.74 and 0.216 cases per 100,000 animals for the birth cohorts 1990 to 2001 and observed a peak for the 1996 birth cohort with a point estimate of 16.41 cases per 100,000 cattle. For birth cohorts ranging from 2002 to 2013, the estimated median prevalence was below one case per 100,000 heads. The calculated confidence in freedom from disease  was above 99.5% for the birth cohorts 2002 to 2006. In conclusion, BSE surveillance in the healthy slaughtered cattle chain was extremely sensitive at the time, when BSE repeatedly occurred in Germany (2000–2009), because the entry of BSE-infected cattle into the food chain could virtually be prevented by the extensive surveillance program during these years and until 2015 . Bovine spongiform encephalopathy was first observed in the United Kingdom in 1986 and spread mainly to other European countries via contaminated cattle feed supplements by trade. The use of rendered bovine carcasses as cattle feed supplements led to exposure of cattle to the prion protein that causes BSE. In 1996, it became evident that a variant of Creutzfeldt-Jakob disease (vCJD) in humans was caused by consumption of beef containing BSE prion protein  No 999/2001 . In Germany, BSE testing of all slaughtered cattle above the age of 24, 30, 48, 72, and 96 months was mandatory in 2001–2005, 2006, 2007, 2008–2010, and 2011–2015. Thus, in effect from 28 April 2015, the systematic testing of healthy slaughtered cattle for BSE was no longer mandatory. Nevertheless, testing of risk animals  above the age of 48 months has continued to date. Thus, 413 BSE cases were detected out of a total number of 22,039,044 tests conducted until May 2020 . These priors are conservative  compared to epidemiological reasoning about the occurrence of BSE in the respective birth cohorts. We chose this conservative approach to avoid any underestimation of true prevalence in birth-cohorts for which surveillance data are available. This evidence-based approach precludes any inferences about data-sparse birth cohorts 2016–2020.a priori assumptions .The increase suggested by the model is an effect of the method: If there is not enough data (information), the model ‘sticks’ to the It was known from other sources of evidence  that there had been an almost complete disruption of the infection events after the “feed ban” had been enforced. Based on this knowledge, the surveillance measures were adjusted over time to test older animals and fallen stock, so that the testing of healthy younger cattle at slaughter could be reduced. This led to the decrease in confidence for the surveillance compound of testing healthy young cattle at slaughter, which was compensated, however, by testing all fallen stock, culled and older cattle, so that the total sensitivity and reliability of the BSE surveillance system was not impaired.In this analysis of the German BSE epidemic, we calculated birth cohort-specific classical BSE prevalence estimates for the German cattle population adjusted for diagnostic misclassification using a Bayesian model. The model allows estimating the age-depending detection probability, which can be interpreted as the diagnostic sensitivity, from the surveillance data. Birth cohort-specific BSE prevalence estimates can be used to project the BSE epidemic curve on the birth cohorts. Under the realistic assumption of exposure to and infection with BSE prions early in life, this projection is an appropriate reflection of the changes in the infection pressure over time. The results of our model also suggest that the birth cohorts from 2002–2006 can be assumed as free from classical BSE using a formal quantification of the evidence from available negative testing results. The number of BSE-infected, but non-detected cattle that may have entered the food chain as estimated by our model is a minor, if not negligible, public health risk. Any potentially remaining public risk was further reduced by other preventive measures , some of which are still in place.