Skip to main content
NIHPA Author Manuscripts logoLink to NIHPA Author Manuscripts
. Author manuscript; available in PMC: 2023 Feb 4.
Published in final edited form as: Disaster Med Public Health Prep. 2022 Mar 3;17:e94. doi: 10.1017/dmp.2021.367

Hurricane Michael and Adverse Birth Outcomes in the Florida Panhandle: Analysis of Vital Statistics Data

Emily W Harville 1, Ke Pan 1, Leslie Beitsch 2, Samendra P Sherchan 3, Elaina Gonsoroski 4, Christopher Uejio 4, Maureen Y Lichtveld 3,5
PMCID: PMC9440161  NIHMSID: NIHMS1766407  PMID: 35236537

Abstract

Objective:

The aim of this study was to examine birth outcomes in areas affected by Hurricane Michael.

Methods:

Vital statistics data of 2017–2019 were obtained from the state of Florida. Births occurring in the year before and after the date of Hurricane Michael (October 7, 2018) were used. Florida counties were divided into 3 categories reflecting extent of impact from Hurricane Michael. Birth outcomes including incidence of preterm birth (PTB), low birth weight (LBW), and small for gestational age (SGA) were also compared before and after Hurricane Michael. Spontaneous and indicated PTBs were distinguished based on previously published algorithms. Multiple regression was used to control for potential confounders.

Results:

Both LBW (aRR 1.19, 95% CI: 1.07, 1.32) and SGA (aRR 1.11, 95% CI: 1.01, 1.21) were higher in the year after Michael than the year before in the most-affected area; a similar effect was not seen in other areas. A stronger effect was seen for exposure in the first trimester or in the 2 months after Michael than in the second or third trimester.

Conclusion:

Consistent with many previous studies, this study of Hurricane Michael found an effect on fetal growth.

Keywords: birth weight, disaster, natural, fetal growth, preterm birth, trimester


Disasters have been associated with poor birth outcomes. Most consistent are modest effects on birth weight, generally examined by region of residence and timing of birth. Magnitude of effect has ranged from 160 g decrement in birth weight associated with the Wenchuan and Haiti earthquakes1,2 down to single-digit associations with wildfires,3 landmine explosions,4 with other examinations of earthquakes57 and major disaster declarations8 finding effect estimates that fall in between. (However, other studies have found no effects of hurricanes on birth weight.911) Effects on preterm birth (PTB)/gestational age have been found much less often.12 Studies that have addressed both birth weight and gestational age have tended to find stronger effects on birth weight, if they find an effect at all,7,1328 and only a few have found an effect on PTB but not low birth weight (LBW; birth weight < 2500 g).29,30

This is surprising as LBW and PTB co-occur, with early delivery being a common cause of LBW. Best practice is usually considered to analyze small for gestational age (SGA; usually defined as birth weight < 10th percentile for gestational age) rather than LBW per se, because birth weight is affected both by length of gestation and fetal growth. PTB and LBW have overlapping but not completely identical risk factors31,32; for instance, male fetuses are usually larger but are more likely to be born early, and smoking is a clear risk factor for LBW but is less strongly associated with PTB. If disaster has different effects on these outcomes, it may indicate mechanisms; for instance, effects limited to growth-related outcomes might suggest a focus on behavior, for example, nutrition and smoking.

A secondary issue is that of timing of exposure to disaster, where results have again been inconsistent for both birth weight and gestational age. Studies of disaster and related time-specific stressors such as terrorist attacks have found no difference by trimester of exposure13,18; strongest effects in the first trimester46,33,34; strongest effects in the second trimester3,14,21,23,24,35,36; strongest effects in the third trimester3,25; as well as variation in strongest effects by exposure, outcome,5 and their combinations.8 Theoretically, effects in the first trimester may be more strongly related to placentation, while later effects are more likely to relate to growth or immediate labor triggers.

In examining effects of disaster on pregnant women, it may therefore be useful to compare and contrast effects on birth weight, weight for gestational age, and gestational age. Unlike other hurricanes where the focus has been effects on major cities,26,37 Hurricane Michael hit a primarily rural, less populated area. This study analyzed the data for changes in birth outcomes to address 3 questions: (1) Was Hurricane Michael associated with changes in incidence of LBW and PTB? (2) Did the storm have differential associations depending on its timing in pregnancy?and (3) Were there similar associations with LBW and PTB, and if not, can subtypes of these conditions be distinguished, perhaps to provide information on distinctions between the two?

Methods

Data Source

Vital statistics data of 2017–2019 were obtained from the state of Florida. Births occurring in the year before and after the date of Hurricane Michael (before: October 6, 2017–October 6, 2018; after: October 7, 2018–October 7, 2019) were used to assess changes in births and birth outcomes in counties affected by Hurricane Michael.

Affected areas

Based on FEMA disaster declarations,38 Florida counties were divided into 3 categories reflecting extent of impact from Hurricane Michael: counties receiving both public and individual assistance (Area A), counties receiving only public assistance (Area B), and counties receiving neither public nor individual assistance (Area C). (Individual assistance is provided to individuals who have sustained losses, although it does not compensate for all losses caused by disaster, while public assistance funds repair or reconstruction of public facilities or infrastructure.) The category of each county can be found in Supplementary Table 1. The hypothesis underlying such exposure categorization is that increasing extent of impact is associated with an increased proportion of the population having severe exposure, an increased average exposure, and increased exposure to secondary traumas (devastated neighborhoods, community member deaths) among those not directly affected. Women were classified as exposed based on their residential address.

Outcomes

The total number of births during October 6, 2017–October 6, 2018 and those during October 7, 2018–October 7, 2019 were compared. Birth outcomes including incidence of preterm birth (PTB), low birth weight (LBW), and small for gestational age (SGA) were also compared before and after Hurricane Michael. PTB was defined as a birth before 37 weeks of gestation. LBW was defined as a birth weight of an infant of 2500 g or less, regardless of gestational age. SGA was defined by birth weight below the 10th percentile for gestational age based on the national standard.39

We used the algorithm reported by Klebanoff et al. to distinguish spontaneous versus indicated preterm births.40 Indicators of spontaneous births included premature rupture of membranes, labor characteristics, and vaginal birth, while induction and C-section were associated with indicated PTB (see reference for full algorithm). Using the Ohio birth certificates from 2006 to 2012, the kappa statistic of the algorithm was 0.68 (95% CI: 0.52, 0.83); predictive values for spontaneous and indicated onset were 85% (95% CI: 75%, 92%) and 89% (95% CI: 71%, 98%). While generally a good-quality algorithm, distinguishing spontaneous and indicated births can be difficult even in medical records, especially in cases of premature rupture of membranes.41

Timing of Exposure to Hurricane Michael

Births were categorized into 5 categories according to time relative to Hurricane Michael. Babies who were delivered before October 7, 2018 were categorized into category “before” Hurricane Michael. Women’s exposure was categorized by trimester on October 7, 2018: first trimester (< 14 weeks), second trimester (14 ≤ 28 weeks), and third trimester (28 weeks+), as well as pregnant within 2 months after Hurricane Michael in a “within 2 months after” category. The timing of 2 months was chosen because it allows those pregnancies to have more than 42 weeks (ie, to be complete) before October 6, 2019.

Covariates

Maternal age, race, education, and whether enrolled in the U.S. Department of Agriculture’s special supplemental nutrition program for women, infants, and children (WIC) program were considered as confounders because those variables are known risk factors for adverse birth outcomes and their distribution among women giving birth could have shifted after the hurricane. Access to antenatal care (ANC) services before and after Hurricane Michael was evaluated by whether pregnant women had any ANC visit before delivery, the month of the first ANC visit, and the Kotelchuck Index. There are 4 adequacy categories in the Kotelchuck Index: adequate plus, adequate, intermediate, and inadequate.42 The 4-level categorization is important as it helps distinguish complicated pregnancy (which may require extra prenatal visits) from those that receive limited or acceptable levels of care.

Statistical Analyses

Covariate missing data were minimal: maternal age (0.0025%), education (0.97%), race/ethnicity (1.28%), pre-pregnancy body mass index (BMI) (5.63%), whether enrolled in the WIC program (1.24%), smoking during pregnancy (0.38%), and alcohol drinking during pregnancy (1.51%)—so, a complete case analysis was used. Paired t-tests were used to compare the number of births before and after Hurricane Michael. Linear regression was used to assess whether the change in the number of births was different across different areas. Log-binomial regression was used for binary outcomes; if these failed to converge, logistic models were used. All of the estimates were compared unadjusted and after adjusting for potential confounders. Comparisons were made in 2 directions: before and after Hurricane Michael, and among different levels of exposure. In order to assess these factors jointly, an interaction term was also added in unadjusted and adjusted models. The analysis was also performed stratified by trimester of exposure. Statistical analyses were performed using the software SAS 9.4 (SAS Inc., Cary, NC).

These analyses were conducted under a waiver of informed consent and approved by the Institutional Review Boards of Tulane University, Florida State University, and the Florida Department of Health.

Results

There was a total of 218 903 and 217 966 live births in Florida between October 6, 2017–October 6, 2018 and October 7, 2018– October 7, 2019, respectively. The total numbers of live births were not significantly different before and after Hurricane Michael within each affected area. The change in the number of births across categories of affected areas was not significantly different (P for interaction = 0.83).

The racial composition, mean maternal age, pre-pregnancy BMI, and gestational age at birth were similar before and after Hurricane Michael within each affected area (Table 1). The percentage of women who were enrolled in the WIC program decreased after Hurricane Michael in all areas. In all areas, the maternal education distribution changed after Hurricane Michael so that a smaller proportion of women giving birth were in the middle educational category (more than a high school but less than a college degree) compared to before.

Table 1.

Description of study population, Florida vital statistics, 2017–2019

FEMA individuala (Area A) FEMA public (Area B) not affected (Area C)



Before After Before After Before After



Mean (SE)/ N (%) p-value Mean (SE)/ N (%) p-value Mean (SE)/ N (%) p-value

Total number of births 7555 7261 0.492 4334 4406 0.213 207014 206299 0.417

Maternal age 27.73 (5.72) 27.86 (5.75) 0.157 27.92 (5.89) 28.19 (5.63) 0.024 29.18 (5.83) 29.33 (5.85) <0.0001

Maternal education level

High School or GED or less 3173 (42.67%) 3109 (43.83%) 0.001 1858 (43.35%) 1980 (45.30%) 0.015 86579 (42.26%) 86503 (42.27%) <0.0001

Some College Credit, but No Degree or Associate Degree 2370 (31.87%) 2069 (29.17%) 1412 (32.94%) 1314 (30.06%) 59307 (28.95%) 57797 (28.24%)

Bachelor’s Degree and above 1893 (25.46%) 1915 (27.00%) 1016 (23.71%) 1077 (24.64%) 58962 (28.78%) 60360 (29.49%)

Maternal ethnicity

Non-Hispanic White 4455 (59.55%) 4191 (58.51%) 0.003 2955 (68.29%) 2925 (66.64%) 0.298 83808 (41.16%) 83183 (40.71%) <0.0001

Hispanic white 387 (5.17%) 450 (6.28%) 498 (11.51%) 526 (11.98%) 61018 (29.97%) 62365 (30.52%)

Black 2206 (29.49%) 2169 (30.28%) 552 (12.76%) 613 (13.97%) 45250 (22.22%) 44801 (21.92%)

Other 433 (5.79%) 353 (4.93%) 323 (7.44%) 325 (7.40%) 13526 (6.64%) 13998 (6.85%)

WIC program 3772 (50.98%) 3346 (46.51%) <0.0001 1762 (41.62%) 1735 (39.54%) 0.050 91147 (44.50%) 85758 (42.14%) <0.0001

Pre-pregnancy BMI 27.81 (7.31) 27.86 (7.38) 0.702 27.07 (6.76) 27.32 (7.02) 0.096 26.76 (6.50) 26.95 (6.60) <0.0001

Smoking during pregnancy 534 (7.10%) 597 (8.28%) 0.007 445 (10.29%) 506 (11.50%) 0.070 8126 (3.94%) 7755 (3.77%) 0.004

FEMA, Federal Emergency Management Agency; GED, General Educational Development; WIC, Women’s, Infant’s, and Children; BMI, body mass index

a

Individual-level FEMA aid is available in the most-damaged areas; less-damaged areas are eligible only for public assistance.

Low Birth Weight

There was a higher proportion of LBW among counties in area A after Michael, adjusting for age, education, ethnicity, pre-pregnancy BMI, and participation in WIC (aRR = 1.19, 95% CI: 1.07, 1.32), but the proportion of LBW did not change after Michael among areas B and C (Table 2). Mean decline in birth weight was 4.7 g overall, 29.5 g in area A, 27.8 g in area B, and 3.4 g in area C. The change in the proportion of LBW after Michael was greater in area A compared to area C (aRR = 1.19, 95% CI: 1.07–1.32 vs aRR = 1.003, 95% CI: 0.98–1.02, P for interaction = 0.002). However, the effect was not different between areas B and C.

Table 2.

Changes in perinatal outcomes after Hurricane Michael among different areas, Florida vital statistics, 2017–2019

Unadjusted model Adjusted modela


FEMA individual (Area A) FEMA public (Area B) not affected (Area C) FEMA individual& (Area A) FEMA public (Area B) not affected (Area C)

Low birth weight (LBW) N 1230/14097 693/8508 32335/398486 1230/14097 693/8508 32335/398486

RR (95%CI) 1.210 (1.087, 1.347) 1.125 (0.975, 1.298) 1.000 (0.979, 1.021) 1.190 (1.070, 1.323) 1.095 (0.950, 1.262) 1.003 (0.982, 1.024)

p-value b 0.001 0.109 0.002 0.228

Preterm birth (PTB) N 1639/13265 1069/8141 47621/379087 1639/13265 1069/8141 47621/379087

RR (95%CI) 0.976 (0.891, 1.069) 1.182 (1.057, 1.323) 1.012 (0.995, 1.029) 0.958 (0.876, 1.049) 1.157 (1.034, 1.294) 1.010 (0.993, 1.027)

p-value # 0.441 0.007 0.264 0.018

Small for gestational age (SGA) N 1691/13265 808/8141 41949/379066 1691/13265 808/8141 41949/379066

RR (95%CI) 1.136 (1.039, 1.242) 1.055 (0.925, 1.202) 0.976 (0.959, 0.994) 1.111 (1.018, 1.213) 1.043 0.916, 1.187) 0.986 (0.968, 1.004)

p-value # 0.001 0.254 0.009 0.399

RR, relative risk; FEMA, Federal Emergency Management Agency; BMI, body mass index; WIC, Women’s, Infants, and Children’s

a

LBW adjusting for: mother’s education, age, ethnicity, smoking during pregnancy, and whether in WIC program; PTB, SGA adjusting for: mother’s age, education, ethnicity, pre-pregnancy BMI, smoking during pregnancy, and whether in WIC program

b

RR compares the year after Hurricane Michael to the year before; p-value is for the interaction between effect of disaster and area

Preterm Birth

There was a higher proportion of PTB within area B after Michael, adjusting for covariates (aRR=1.16, 95%CI 1.04, 1.29), but the proportion of PTB did not change after Michael within area A or C (Table 2). There was an interaction between exposure to Michael and area, in that the proportion of PTB was greater in area B compared to area C, but the effect was not different between area A and C.

Small for Gestational Age

There was a higher proportion of SGA in area A after Michael, adjusting for covariates (aRR = 1.11, 95% CI: 1.02, 1.21) (see Table 2). Compared to area C, the effects of Michael on the proportion of SGA were different in area A (P for interaction = 0.01) but not in area B (P= 0.40).

Timing of Exposure

Low birth weight

Within the most affected area A, exposure during the first trimester (aOR = 1.25, 95% CI: 1.03–1.51) or pregnancy within 2 months after Michael (aOR = 1.36, 95% CI: 1.12–1.66) showed the highest increases compared to before the hurricane. These increases were not seen in the unaffected areas; the moderately affected area showed a small increase in risk among conceptions in the 2 months after the hurricane (Table 3). Comparing across regions, the most affected area A was at similar risk to areas B and C for births prior to the hurricane (area A vs area C: aOR = 0.901, 95% CI: 0.84–1.00; area B vs area C: aOR = 0.98, 95% CI: 0.87–1.10) (Table S3).

Table 3.

Perinatal outcomes by timing of pregnancy relative to Hurricane Michael within each area

Unadjusted Adjustinga for maternal characteristics


OR 95%CI OR 95%CI

Low birth weight (LBW)

Area Ab (N=1230/14097)

 3rd trimester vs beforec 0.891 0.721 1.100 0.884 0.715 1.094

 2nd trimester vs before 1.156 0.965 1.385 1.145 0.955 1.374

 1st trimester vs before 1.270 1.052 1.532 1.247 1.032 1.507

 Within 2 months after vs before 1.397 1.150 1.698 1.361 1.118 1.656

Area B (N=693/8508)

 3rd trimester vs before 0.686 0.504 0.936 0.65 0.483 0.900

 2nd trimester vs before 0.949 0.739 1.22 0.917 0.712 1.181

 1st trimester vs before 1.106 0.861 1.421 1.085 0.843 1.398

 Within 2 months after vs before 1.322 1.022 1.711 1.293 0.998 1.677

Area C (N=32335/398486)

 3rd trimester vs before 0.645 0.618 0.674 0.645 0.617 0.674

 2nd trimester vs before 1.005 0.970 1.041 1.006 0.971 1.043

 1st trimester vs before 0.979 0.944 1.016 0.994 0.957 1.031

 Within 2 months after vs before 1.013 0.972 1.056 1.017 0.975 1.060

Preterm birth (PTB)

Area A (N=1639/13265)

 3rd trimester vs before 0.567 0.462 0.696 0.557 0.453 0.684

 2nd trimester vs before 0.888 0.754 1.046 0.878 0.745 1.035

 1st trimester vs before 1.036 0.876 1.225 1.013 0.856 1.199

 Within 2 months after vs before 1.116 0.937 1.328 1.080 0.906 1.288

Area B (N=1069/8141)

 3rd trimester vs before 0.591 0.451 0.775 0.578 0.441 0.759

 2nd trimester vs before 1.161 0.952 1.417 1.132 0.927 1.382

 1st trimester vs before 1.241 1.013 1.521 1.223 0.997 1.500

 Within 2 months after vs before 1.233 0.989 1.539 1.203 0.963 1.502

Area C (N=47621/379087)

 3rd trimester vs before 0.591 0.569 0.614 0.588 0.567 0.611

 2nd trimester vs before 1.050 1.019 1.081 1.046 1.015 1.077

 1st trimester vs before 1.008 0.977 1.039 1.015 0.983 1.047

 Within 2 months after vs before 0.982 0.948 1.017 0.981 0.947 1.017

Small for gestational age (SGA)

Area A (N=1691/13265)

 3rd trimester vs before 1.141 0.967 1.347 1.135 0.959 1.342

 2nd trimester vs before 1.089 0.931 1.275 1.067 0.910 1.251

 1st trimester vs before 1.090 0.921 1.29 1.063 0.896 1.261

 Within 2 months after vs before 1.332 1.124 1.577 1.291 1.087 1.533

Area B (N=808/8141)

 3rd trimester vs before 1.003 0.783 1.286 0.98 0.762 1.259

 2nd trimester vs before 0.975 0.774 1.227 0.951 0.754 1.200

 1st trimester vs before 1.194 0.953 1.496 1.184 0.942 1.487

 Within 2 months after vs before 1.097 0.853 1.411 1.090 0.845 1.405

Area C (N=41949/379066)

 3rd trimester vs before 0.968 0.936 1.001 0.971 0.939 1.004

 2nd trimester vs before 0.985 0.955 1.016 0.994 0.963 1.026

 1st trimester vs before 0.969 0.938 1.001 0.991 0.959 1.025

 Within 2 months after vs before 0.958 0.923 0.995 0.971 0.935 1.008
a

LBW adjusting for: mother’s education, age, ethnicity, smoking during pregnancy, and whether in WIC program; PTB, SGA adjusting for: mother’s age, education, ethnicity, pre-pregnancy BMI, smoking during pregnancy, and whether in WIC program

b

Before: gave birth before Hurricane Michael

c

Area A=FEMA individual; Area B=FEMA public; Area C=non-affected

Preterm birth

Within the moderately affected area B, exposure during the first trimester (aOR = 1.22, 95% CI: 1.00–1.50) or pregnancy within 2 months after Michael (aOR = 1.20, 95% CI: 0.99–1.50) showed the highest increase in PTB compared to before the hurricane. These increases were not seen in the area A or C (see Table 3). When compared across regions, incidence of PTB was lower in area A for exposure in the second trimester (aOR = 0.85, 95% CI: 0.73–0.99).

Small for gestational age

Within the most affected area A, exposure within 2 months after Michael (aOR = 1.29, 95% CI: 1.09–1.53) showed increased risk for SGA compared to before the hurricane, which was not seen in the unaffected areas (see Table 3). Women living in the most affected area A were at small increased risk of delivering an SGA child compared to those in the unaffected area C, regardless of timing (Table S3).

Spontaneous and Indicated PTB

Area B seemed to be at higher risk for induced PTB (Table 4), regardless of trimester of exposure (Table S3), and before the storm had been at lower risk of spontaneous PTB (aOR = 0.75, 95% CI: 0.64–0.87). Area A was at lower risk of induced PTB after exposure in the second trimester (aOR = 0.81, 95% CI: 0.65–0.99). Overall incidence of spontaneous PTB in areas A and B was higher for conceptions in the 2 months after the storm, but this may have been a random variation (aOR = 1.13, 95% CI: 0.90–1.41 for area A; aOR = 1.10, 95% CI: 0.82–1.48 for area B; Table S3).

Table 4.

Changes in induced preterm birth and spontaneous preterm birth after Hurricane Michael among different areas

Unadjusted model Adjusted modela


FEMA individual (Area A) FEMA public (Area B) not affected (Area C) FEMA individual& (Area A) FEMA public (Area B) not affected (Area C)

Induced preterm birth N 815/12441 657/7729 23671/355137 815/12441 657/7729 23671/355137

RR (95%CI) 1.003
(0.878, 1.145)
1.156
(0.998, 1.339)
1.024
(0.999, 1.050)
0.986
(0.864, 1.125)
1.116
(0.965, 1.291)
1.015
(0.991, 1.040)

p for interaction b 0.758 0.111 0.673 0.206

Spontaneous preterm birth N 822/12448 408/7480 23737/355203 822/12448 408/7480 23737/355203

RR (95%CI) 0.951
(0.834, 1.086)
1.279
(1.057, 1.548)
0.997
(0.972, 1.021)
0.931
(0.817, 1.062)
1.254
(1.037, 1.517)
1.002
(0.978, 1.027)

p for interaction b 0.499 0.011 0.285 0.021
a

Adjusting for: mother’s age, education, ethnicity, pre-pregnancy BMI, smoking during pregnancy, and whether in WIC program

b

RR compares the year after Hurricane Michael to the year before; p-value is for the interaction between effect of disaster and area

Discussion

Principal Findings

The impact of a hurricane on a less populated area on maternal and child health outcomes, specifically LBW, PTB, and SGA was examined. Vital statistics data from counties were categorized by degree of damage caused by Hurricane Michael. Overall, an increase in LBW and SGA was found in the most-affected areas, consistent with previous studies,43 and with similar effect sizes.2,20,25 These effects appeared to be stronger among women who experienced the storm in the first trimester, or who conceived shortly after the hurricane, compared to those exposed in the second or third trimester. These findings are consistent with several studies showing the strongest effects with first-trimester exposure.46,33,34

Limitations

Strengths include the large sample size and consideration of multiple definitions of exposure and outcome. Limitations of the study include the reliance on vital statistics, defining exposure by county-level damage and timing, and the lack of information on physiologic, behavioral, or social mechanisms of effect. Future analyses will explore some of these topics in more detail. While a validated classification system was used for spontaneous versus medically indicated preterm births, such systems are still limited relative to detailed research or medical record review. Further subtyping was not possible, and distinctions among preterm premature rupture of membranes (PPROM) and preterm labor or different indications for induction (such as pre-eclampsia or fetal growth restriction) might be relevant to understanding effects of a complex exposure like disaster. A few studies have examined effects of disaster on PPROM alone,5,44,45 and 1 recent analysis examined only spontaneous births, whether preterm or not,46 but that has not necessarily led to any more consistent results.

Interpretation

Few studies have considered the post-disaster period. One study of 9/11 found minimal difference in effects between women who were pregnant at the time of the attack and those who became pregnant later,47 while another found decreased odds of moderate PTB for several weeks post-disaster and increased odds of very LBW around 4 months later,14 but no effects on other outcomes or during other post-disaster time periods. A study of Hurricane Katrina suggested some effects lingered 5–7 years later,48 while 1 study of county-level PTB rates after disasters found effects lasting only for 2 to 3 weeks after the hurricane exposure.46 As many of the effects of disaster exposurestress, economic problems, lack of access to health carelinger for months or years, it is reasonable that exposure to post-disaster life early in pregnancy would have similar effects.

Also consistent with previous studies is the lack of effect on PTB in the most-exposed counties,7,1228 especially confusing as there was an increase in the moderately exposed counties. This is somewhat surprising, as PTB and LBW often go hand-in-hand and some large and detailed studies have found an effect.8,46 Gestational age is often measured less precisely and consistently than birth weight, which may make effects more difficult to detect. For birth weight, where an effect was found, the absolute size of the change was small. Third-trimester effects must be examined carefully, as women who give birth preterm have a shorter third trimester, but this should not affect estimate of first-trimester effects. One analysis of the spatial hazards data across the United States concluded that disaster affected birth weight more strongly in counties that were less vulnerable, while gestational age was most affected in more vulnerable counties,8 and Sun et al. also concluded that effects on PTB are stronger in areas with high social vulnerability.46 Based on the Centers for Disease Control and Prevention social vulnerability index,49 the counties in the affected areas were either ranked highly (Holmes, Washington, Jackson, Calhoun, Liberty, Franklin, Gadsden, Taylor) or moderate to highly vulnerable (Leon, Gulf, Bay, Wakulla). However, a stronger effect was found on birth weight compared to PTB. It is possible that a hurricane could have specific effects, triggering preterm labor alone, for instance, or lead to complications such as hypertensive disorders that would be mainly apparent in induced PTB, but examination of spontaneous versus induced PTB failed to reveal any patterns.

There are several possible mechanisms by which disaster could affect birth weight, including health behaviors such as increased smoking and an unhealthy diet, reduced fetal growth due to higher stress hormones and blood pressure, and increased susceptibility to infection. Our models controlled for covariates that appeared to change between time periods, but the possibility for residual confounding remains (although there is no obvious candidate that would vary across regions, the effects are small enough that relatively minor imbalances could cause a difference). Unlike Hurricane Katrina,11 the overall number of births in the affected areas did not change significantly; therefore, selective fertility or migration is unlikely to be a cause of the findings.50

The decreased enrollment in WIC also suggests possible nutritional effects. Although enrollment is theoretically possible during and after disaster, there are several possible reasons for this decline: physical and communication barriers; evacuation separating women from normal care; the general mental toll of rebuilding (including clean-up, dealing with insurance, and taking care of family and neighbors), which may limit the time and energy available to sign up. Facility shutdowns are another consideration. In some of the affected counties, such as Leon, there was no interruption to services, and benefits were uploaded to recipients’ accounts so they did not need to come into the office. In others, such as Bay County, health departments and offices were shut down for some weeks.

Our analytical strategy, which is at the individual level and examines maternal residence at the time of the hurricane, is probably the type most frequently used in the literature and allows for control of individual-level confounding. Defining exposure by place of delivery might provide additional information on effects on the health care system, but maternal residence provides a better estimate of individual overall hurricane exposure. Other analysis strategies have been used, such as comparisons of county-level rates46,51 or means,8 time series,14 sibling studies,4 and treating the hurricane as a time-varying exposures in a proportional hazards model.52 Difference-in-difference analysis assumes confounders are time-invariant, which may not be realistic, as disaster may induce differential shifts in covariates such as ethnic distribution.6,51 Studies also vary in whether the control group is other unaffected areas or the same area, cohort, or clinical population in a previous or later time period; both types of comparisons were performed. Studies with very fine time scales46,52 or that allow only for exposure in late pregnancy52 inherently focus on hurricane exposure as a short-term trigger. Given the long-term effects of disaster on so many aspects of life, this seems to represent a limited window.

Conclusion

This study adds to the body of evidence, suggesting an effect of disaster on pregnancy outcomes, particularly fetal growth, and that effects early in pregnancy may be particularly severe. The lack of effect on preterm birth is also consistent with many previous studies and warrants further study as to why, if stress is a cause of PTB,53 PTB so rarely rises in the aftermath of a major stressor. Some argue for PTB as an adaptive response under some conditions; the inverseadaptive extension of gestation under conditions of stresscould also be hypothesized.54 It may be that disaster-associated stress contributes to PTB more in the context of chronic or social determinant of health-associated stress, rather than as a short-term stressor. Further studies employing more detailed phenotyping and measurement of mediating factors may be necessary to more comprehensively ascertain these disaster-related effects on maternal and child health (MCH). However, given the large amount of research on the topic, it may be time to move to developing interventions to improve post-disaster outcomes.

Supplementary Material

1

Acknowledgments.

We thank Daniel Irwin and the Florida Department of Health for facilitating access to vital statistics. Any published findings and conclusions are those of the authors and do not necessarily represent the official position of the Florida Department of Health.

Funding statement. This project was supported by NIEHS grant R21ES031020 to EWH and ML.

Abbreviations:

ANC

antenatal care

BMI

body mass index

FEMA

Federal Emergency Management Agency

LBW

low birth weight

OR

odds ratio

PTB

preterm birth

SGA

small for gestational age

Footnotes

Conflict(s) of interest. None of the authors has a conflict of interest.

References

  • 1.Tan CE, Li HJ, Zhang XG, et al. The impact of the Wenchuan earthquake on birth outcomes. PLoS One. 2009;4(12):e8200. doi: 10.1371/journal.pone.0008200 [DOI] [PMC free article] [PubMed] [Google Scholar]
  • 2.Harville EW, Do M. Reproductive and birth outcomes in Haiti before and after the 2010 earthquake. Disaster Med Public Health Prep. 2015:1–8. doi: 10.1017/dmp.2015.69 [DOI] [PubMed] [Google Scholar]
  • 3.Holstius DM, Reid CE, Jesdale BM, Morello-Frosch R. Birth weight following pregnancy during the 2003 Southern California wildfires. Environ Health Perspect. 2012;120(9):1340–1345. doi: 10.1289/ehp.1104515 [DOI] [PMC free article] [PubMed] [Google Scholar]
  • 4.Camacho A. Stress and birth weight: evidence from terrorist attacks. Am Econ Rev. 2008;98(2):511–515. [PubMed] [Google Scholar]
  • 5.Oyarzo C, Bertoglia P, Avendano R, et al. Adverse perinatal outcomes after the February 27th 2010 Chilean earthquake. J Matern Fetal Neonatal Med. 2012;25(10):1868–1873. doi: 10.3109/14767058.2012.678437 [DOI] [PubMed] [Google Scholar]
  • 6.Torche F. The effect of maternal stress on birth outcomes: exploiting a natural experiment. Demography. 2011;48(4):1473–1491. doi: 10.1007/s13524-011-0054-z [DOI] [PubMed] [Google Scholar]
  • 7.Suzuki K, Yamagata Z, Kawado M, Hashimoto S. Effects of the Great East Japan Earthquake on secondary sex ratio and perinatal outcomes. J Epidemiol. 2015; Epub 2015 Dec 5. doi: 10.2188/jea.JE20150055 [DOI] [PMC free article] [PubMed] [Google Scholar]
  • 8.Simeonova E. Out of sight, out of mind? Natural disasters and pregnancy outcomes in the USA. CESifo Econ Stud. 2011;57(3):403–431. [Google Scholar]
  • 9.Grabich SC, Robinson WR, Konrad CE, Horney JA. Impact of hurricane exposure on reproductive health outcomes, Florida, 2004. Disaster Med Public Health Prep 2017;11(4):1–5. doi: 10.1017/dmp.2016.158 [DOI] [PubMed] [Google Scholar]
  • 10.Currie J, Rossin-Slater M. Weathering the storm: hurricanes and birth outcomes. J Health Econ. 2013;32(3):487–503. doi: 10.1016/j.jhealeco.2013.01.004 [DOI] [PMC free article] [PubMed] [Google Scholar]
  • 11.Hamilton BE, Sutton PD, Mathews TJ, et al. The effect of Hurricane Katrina: births in the U. S. Gulf Coast Region, before and after the storm. Natl Vital Stat Rep. 2009;58(2):1–28 [PubMed] [Google Scholar]
  • 12.Hawkins G, Gullam J, Belluscio L. The effect of a major earthquake experienced during the first trimester of pregnancy on the risk of preterm birth. Aust N Z J Obstet Gynaecol. 2018; 59(1):82–88. doi: 10.1111/ajo.12797 [DOI] [PubMed] [Google Scholar]
  • 13.Berkowitz GS, Wolff MS, Janevic TM, et al. The World Trade Center disaster and intrauterine growth restriction. JAMA. 2003;290(5):595–596. [DOI] [PubMed] [Google Scholar]
  • 14.Eskenazi B, Marks AR, Catalano R, et al. Low birthweight in New York city and upstate New York following the events of September 11th. Hum Reprod. 2007;22(11):3013–3020. [DOI] [PubMed] [Google Scholar]
  • 15.Goldman LR, Paigen B, Magnant MM, Highland JH. Low birth-weight, prematurity and birth-defects in children living near the hazardous-waste site, love-canal. Hazard Waste Hazard Mater. 1985;2(2):209–223. [Google Scholar]
  • 16.Maric NP, Dunjic B, Stojiljkovic DJ, et al. Prenatal stress during the 1999 bombing associated with lower birth weight—a study of 3,815 births from Belgrade. Arch Womens Ment Health. 2009;13(1):83–89. [DOI] [PubMed] [Google Scholar]
  • 17.Perera F, Tang D, Rauh V, et al. Relationshps among polycyclic aromatic hydrocarbon-DNA ADDults, proximity to the World Trade Center, and effects on fetal growth. Environ Health Perspect. 2005;113(8):1062–1067. [DOI] [PMC free article] [PubMed] [Google Scholar]
  • 18.Smits L, Krabbendam L, de Bie R, et al. Lower birth weight of Dutch neonates who were in utero at the time of the 9/11 attacks. J Psychosom Res. 2006;61(5):715–717. [DOI] [PubMed] [Google Scholar]
  • 19.Xiong X, Harville EW, Mattison DR, et al. Exposure to Hurricane Katrina, post-traumatic stress disorder and birth outcomes. Am J Med Sci. 2008;336(2):111–115. [DOI] [PMC free article] [PubMed] [Google Scholar]
  • 20.Tong VT, Zotti ME, Hsia J. Impact of the Red River catastrophic flood on women giving birth in North Dakota, 1994–2000. Matern Child Health J. 2011;15(3):281–288. doi: 10.1007/s10995-010-0576-9 [DOI] [PubMed] [Google Scholar]
  • 21.Dancause KN, Laplante DP, Oremus C, et al. Disaster-related prenatal maternal stress influences birth outcomes: Project Ice Storm. Early Hum Dev. 2011;87(12):813–820. doi: 10.1016/j.earlhumdev.2011.06.007 [DOI] [PubMed] [Google Scholar]
  • 22.Sanguanklin N, McFarlin BL, Park CG, et al. Effects of the 2011 flood in Thailand on birth outcomes and perceived social support. J Obstet Gynecol Neonatal Nurs. 2014;43(4):435–444. doi: 10.1111/1552-6909.12466 [DOI] [PubMed] [Google Scholar]
  • 23.Fuller SC. The effect of prenatal natural disaster exposure on school outcomes. Demography. 2014;51(4):1501–1525. doi: 10.1007/s13524-0140310-0 [DOI] [PubMed] [Google Scholar]
  • 24.Wainstock T, Anteby E, Glasser S, et al. The association between prenatal maternal objective stress, perceived stress, preterm birth and low birthweight. J Matern Fetal Neonatal Med. 2013;26(10):973–977. doi: 10.3109/14767058.2013.766696 [DOI] [PubMed] [Google Scholar]
  • 25.Rosales-Rueda M. The impact of early life shocks on human capital formation: evidence from El Nino floods in Ecuador. J Health Econ. 2018;62:13–44. doi: 10.1016/j.jhealeco.2018.07.003 [DOI] [PubMed] [Google Scholar]
  • 26.Mendez-Figueroa H, Chauhan SP, Tolcher MC, et al. Peripartum outcomes before and after Hurricane Harvey. Obstet Gynecol. 2019;134(5):1005–1016. doi: 10.1097/aog.0000000000003522 [DOI] [PMC free article] [PubMed] [Google Scholar]
  • 27.Fujimori K, Kyozuka H, Yasuda S, et al. Pregnancy and birth survey after the Great East Japan earthquake and Fukushima Daiichi nuclear power plant accident in Fukushima Prefecture. Fukushima J Med Sci. 2014;60(1):75–81. [DOI] [PubMed] [Google Scholar]
  • 28.Leppold C, Nomura S, Sawano T, et al. Birth outcomes after the Fukushima Daiichi nuclear power plant disaster: a long-term retrospective study. Int J Environ Res Public Health. 2017;14(5):542. doi: 10.3390/ijerph14050542 [DOI] [PMC free article] [PubMed] [Google Scholar]
  • 29.Mrejen M, Perelman J, Machado DC. Environmental disasters and birth outcomes: impact of a tailings dam breakage in Brazil. Soc Sci Med. 2020;250:112868. doi: 10.1016/j.socscimed.2020.112868 [DOI] [PubMed] [Google Scholar]
  • 30.Antipova A, Curtis A. The post-disaster negative health legacy: pregnancy outcomes in Louisiana after Hurricane Andrew. Disasters. 2015;39(4): 665–686. doi: 10.1111/disa.12125 [DOI] [PubMed] [Google Scholar]
  • 31.Muhihi A, Sudfeld CR, Smith ER, et al. Risk factors for small-for-gestational-age and preterm births among 19,269 Tanzanian newborns. BMC Pregnancy Childbirth. 2016;16:110. doi: 10.1186/s12884-016-0900-5 [DOI] [PMC free article] [PubMed] [Google Scholar]
  • 32.Zeitlin JA, Ancel PY, Saurel-Cubizolles MJ, Papiernik E. Are risk factors the same for small for gestational age versus other preterm births? Am J Obstet Gynecol. 2001;185(1):208–215. doi: 10.1067/mob.2001.114869 [DOI] [PubMed] [Google Scholar]
  • 33.Glynn LM, Wadhwa PD, Dunkel-Schetter C, et al. When stress happens matters: effects of earthquake timing on stress responsivity in pregnancy. Am J Obstet Gynecol. 2001;184(4):637–642. [DOI] [PubMed] [Google Scholar]
  • 34.Hilmert CJ, Kvasnicka-Gates L, Teoh AN, et al. Major flood related strains and pregnancy outcomes. Health Psychol. 2016;35(11):1189–1196. doi: 10.1037/hea0000386 [DOI] [PubMed] [Google Scholar]
  • 35.Catalano R, Hartig T. Communal bereavement and the incidence of very low birthweight in Sweden. J Health Soc Behav. 2001;42(4):333–341. [PubMed] [Google Scholar]
  • 36.Abdo M, Ward I, O’Dell K, et al. Impact of wildfire smoke on adverse pregnancy outcomes in Colorado, 2007–2015. Int J Environ Res Public Health. 2019;16(19):3720. doi: 10.3390/ijerph16193720 [DOI] [PMC free article] [PubMed] [Google Scholar]
  • 37.Harville EW, Tran T,Xiong X, Buekens P. Population changes, racial/ethnic disparities, and birth outcomes in Louisiana after Hurricane Katrina. Disaster Med Public Health Prep. 2010;4(Suppl 1):S39–S45. doi: 10.1001/dmp.2010.15 [DOI] [PubMed] [Google Scholar]
  • 38.Florida Hurricane Michael (DR-4399). FEMA. Last updated Jan 29, 2022. Accessed April 16, 2020. https://www.fema.gov/disaster/4399.
  • 39.Mandy GT,Weisman LE,Kim MS. Infants with fetal (intrauterine) growth restriction. In: Post TW, ed. UpToDate. Author; 2020:32. [Google Scholar]
  • 40.Klebanoff MA, Yossef-Salameh L, Latimer C, et al. Development and validation of an algorithm to determine spontaneous versus provider-initiated preterm birth in US Vital Records. Paediatr Perinat Epidemiol. 2016;30(2):134–140. doi: 10.1111/ppe.12267 [DOI] [PubMed] [Google Scholar]
  • 41.Stout MJ, Busam R, Macones GA, Tuuli MG. Spontaneous and indicated preterm birth subtypes: interobserver agreement and accuracy of classification. Am J Obstet Gynecol. 2014;211(5):530.e1-e4. doi: 10.1016/j.ajog.2014.05.023 [DOI] [PMC free article] [PubMed] [Google Scholar]
  • 42.Kotelchuck M. The adequacy of prenatal care utilization index: its US distribution and association with low birthweight. Am J Public Health. 1994;84(9):1486–1489. [DOI] [PMC free article] [PubMed] [Google Scholar]
  • 43.Harville E, Xiong X, Buekens P. Disasters and perinatal health: a systematic review. Obstet Gynecol Surv. 2010;65(11):713–728. doi: 10.1097/OGX.0b013e31820eddbe [DOI] [PMC free article] [PubMed] [Google Scholar]
  • 44.Sekizuka N, Sakai A, Aoyama K, et al. Association between the incidence of premature rupture of membranes in pregnant women and seismic intensity of the Noto Peninsula earthquake. Environ Health Prev Med. 2010;15(5):292–298. doi: 10.1007/s12199-010-0142-5 [DOI] [PMC free article] [PubMed] [Google Scholar]
  • 45.Santos-Leal E, Vidart-Aragon JA, Coronado-Martin P, et al. Premature rupture of membranes and Madrid terrorist attack. Birth Issues Perinat Care. 2006;33(4):341–342. [DOI] [PubMed] [Google Scholar]
  • 46.Sun S, Weinberger KR, Yan M, et al. Tropical cyclones and risk of preterm birth: a retrospective analysis of 20 million births across 378 US counties. Environ Int. 2020;140:105825. doi: 10.1016/j.envint.2020.105825 [DOI] [PubMed] [Google Scholar]
  • 47.Maslow CB, Caramanica K, Li J, et al. Reproductive outcomes following maternal exposure to the events of September 11, 2001, at the World Trade Center, in New York City. Am J Public Health. 2016;106(10):1796–1803. doi: 10.2105/ajph.2016.303303 [DOI] [PMC free article] [PubMed] [Google Scholar]
  • 48.Harville EW, Giarratano G, Savage J, et al. Birth outcomes in a disaster recovery environment: New Orleans women after Katrina. Matern Child Health J. 2015;19(11):2512–2522. doi: 10.1007/s10995-015-1772-4 [DOI] [PMC free article] [PubMed] [Google Scholar]
  • 49.Agency for Toxic Substances and Disease Registry. CDC’s Social Vulnerability Index. US Department of Health and Human Services. Accessed June 24, 2020. https://svi.cdc.gov/index.html. [Google Scholar]
  • 50.Harville EW, Xiong X, David M, Buekens P. The paradoxical effects of Hurricane Katrina on births and adverse birth outcomes. Am J Public Health. 2020;110(10):1466–1471. doi: 10.2105/ajph.2020.305769 [DOI] [PMC free article] [PubMed] [Google Scholar]
  • 51.Grabich SC, Robinson WR, Engel SM, et al. County-level hurricane exposure and birth rates: application of difference-in-differences analysis for confounding control. Emerg Themes Epidemiol. 2015;12:19. doi: 10.1186/s12982-015-0042-7 [DOI] [PMC free article] [PubMed] [Google Scholar]
  • 52.Grabich SC, Robinson WR, Engel SM, et al. Hurricane Charley exposure and hazard of preterm delivery, Florida 2004. Matern Child Health J. 2016;20(12):2474–2482. doi: 10.1007/s10995-016-2069-y [DOI] [PubMed] [Google Scholar]
  • 53.Lobel M, Dunkel Schetter C. Pregnancy and prenatal stress. In: Friedman HS, ed. Encyclopedia of Mental Health. Academic Press; 2016:318–329. [Google Scholar]
  • 54.WilliamsTC DrakeAJ. Preterm birth in evolutionary context: a predictive adaptive response? Philos Trans R Soc Lond B Biol Sci. 2019;374(1770): 20180121. doi: 10.1098/rstb.2018.0121 [DOI] [PMC free article] [PubMed] [Google Scholar]

Associated Data

This section collects any data citations, data availability statements, or supplementary materials included in this article.

Supplementary Materials

1

RESOURCES