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After the Storm: Short-term and Long-term Health Effects Following Superstorm Sandy among the Elderly

Published online by Cambridge University Press:  05 March 2019

Wayne R. Lawrence ,
Ziqiang Lin ,
Emily A. Lipton ,
Guthrie Birkhead ,
Michael Primeau ,
Guang-Hui Dong  and
Shao Lin
Wayne R. Lawrence
Affiliation:
Department of Epidemiology and Biostatistics, School of Public Health, University at Albany, State University of New York, Rensselaer, New York (Mr Lawrence, Dr Birkhead, and Dr Shao Lin)
Ziqiang Lin
Affiliation:
Department of Environmental Health Sciences, School of Public Health, University at Albany, State University of New York, Rensselaer, New York (Dr Ziqiang Lin, Ms Lipton, and Dr Shao Lin) Department of Mathematics and Statistics, College of Arts and Sciences, University at Albany, State University of New York, Albany, New York (Dr Ziqiang Lin)
Emily A. Lipton
Affiliation:
Department of Environmental Health Sciences, School of Public Health, University at Albany, State University of New York, Rensselaer, New York (Dr Ziqiang Lin, Ms Lipton, and Dr Shao Lin)
Guthrie Birkhead
Affiliation:
Department of Epidemiology and Biostatistics, School of Public Health, University at Albany, State University of New York, Rensselaer, New York (Mr Lawrence, Dr Birkhead, and Dr Shao Lin)
Michael Primeau
Affiliation:
Department of Health Policy Management and Behavior, School of Public Health, University at Albany, State University of New York, Rensselaer, New York (Ms Lipton); Office of Health Emergency Preparedness, New York State Department of Health, Albany, New York (Mr Primeau);
Guang-Hui Dong
Affiliation:
Department of Preventive Medicine, School of Public Health, Sun Yat-sen University, Yuexiu District Guangzhou, Guangdong, China (Dr Dong)
Shao Lin*
Affiliation:
Department of Epidemiology and Biostatistics, School of Public Health, University at Albany, State University of New York, Rensselaer, New York (Mr Lawrence, Dr Birkhead, and Dr Shao Lin) Department of Environmental Health Sciences, School of Public Health, University at Albany, State University of New York, Rensselaer, New York (Dr Ziqiang Lin, Ms Lipton, and Dr Shao Lin)
*
Correspondence and reprint requests to Shao Lin, Department of Environmental Health Science, School of Public Health, Rm 212d, University at Albany, State University of New York, One University Place, Rensselaer, NY 12144 (e-mail: slin@albany.edu).
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Abstract

Objective

Investigate short- and long-term effects of Superstorm Sandy on multiple morbidities among the elderly.

Methods

We examined emergency department visits; outpatient visits; and hospital admissions for cardiovascular disease (CVD), respiratory disease, and injury among residents residing in 8 affected counties immediately, 4 months, and 12 months following Superstorm Sandy. Control groups were defined as visits/admissions during the identical time window in the 5 years before (2007-2011) and 1 year after (2013-2014) the storm in affected and nonaffected counties in New York. We performed Poisson regression to test whether there was an association of increased visits/admissions for periods following Superstorm Sandy while controlling for covariates.

Results

We found that the risk for CVD, respiratory disease, and injury visits/admissions was more than twice as high immediately, 4 months, and 12 months after the storm than it was in the control periods. Women were at greater risk at all time periods for CVD (risk ratio [RR], 2.04) and respiratory disease (RRs: 1.89 to 1.92). Whites had higher risk for CVD, respiratory disease, and injury than other racial groups during each period.

Conclusion

We observed increases in CVD, respiratory disease, and injury up to a year following Superstorm Sandy. Findings demonstrate the need to incorporate short- and long-term health effects into public health recovery. (Disaster Med Public Health Preparedness. 2019;13:28-32)

Keywords

hurricanedisastersvulnerable populationsmorbidity

Information

Type
Brief Report
Information
Disaster Medicine and Public Health Preparedness , Volume 13 , Special Issue 1: Serial Hurricanes , February 2019 , pp. 28 - 32
Copyright
Copyright © 2019 Society for Disaster Medicine and Public Health, Inc. 

Since Hurricane Katrina in 2006, hurricanes have emerged as a major public health concern because of the increased frequency and magnitude of storms. In 2012, Superstorm Sandy gained national attention as a result of its impact on residents in the New York City (NYC) metropolitan area. During the storm period, thousands of residents were without power, mandatory evacuations were ordered, and several hospitals were forced to close. Prior studies that examined the effects of hurricanes on health observed that increases in mortality and emergency department visits can persist for at least 1 year, especially for cardiovascular-related diseases.Reference Sharp, Sun and Ledneva 1 , Reference Gautam, Menachem and Srivastav 2 Public health emergency response traditionally focuses on reducing mortality and preventing injuries during or immediately following a disaster; however, the long-term health effects remain unclear. Additionally, limited knowledge exists on the relationship between hurricanes and health outcomes for multiple morbidities.

Previous publications that evaluated the effects of hurricanes on health assessed health outcomes among either the general population or the nonelderly Medicaid population; thus the elderly population has been overlooked.Reference Sharp, Sun and Ledneva 1 , Reference Gautam, Menachem and Srivastav 2 The limited studies that evaluated the health of elderly dual-eligible Medicare-Medicaid beneficiaries found that they were generally frailer and had more chronic conditions than did individuals covered under other insurance types.Reference Liu, Long and Aragon 3 , Reference Kane, Wysocki and Parashuram 4 However, vulnerability to disasters such as hurricanes by race and gender among this group remains unknown. Additionally, the majority of studies have focused on health effects during a hurricane and failed to explore short- and long-term health effects after the storm period and potential changes in disease risk patterns by sociodemographic characteristics. Moreover, studies generally used hospital admission data only, capturing severe cases and potentially missing other less severely affected vulnerable groups.

The aim of this study is to address these gaps by investigating whether cardiovascular disease (CVD), respiratory disease, and injury morbidity, as reflected in emergency department (ED) visits and hospitalizations, increased immediately, 4 months, and 12 months following Superstorm Sandy among elderly dual-eligible Medicare-Medicaid beneficiaries when compared to other years and nonaffected counties in New York State (NYS). In addition, we examined if morbidity related to Sandy varied with gender and race after the storm.

METHODS

Data Sources

We obtained health claims data from the Office of the Assistant Secretary of Preparedness and Response Enclave for the period of October 1, 2007 through November 30, 2014. The Enclave was created to inform disaster preparedness, response, and recovery. The population consisted primarily of elderly (≥65 years of age) dual-eligible Medicare-Medicaid beneficiaries in NYS. Claims data for these enrollees were used to identify health outcomes. Cases combined all services for outpatient, hospitalization, and emergency department visits. This project received approval with respect to its use of data by the institutional review board at the University at Albany, The State University of New York.

Outcome Measures

Health outcomes including CVD, respiratory disease, and injury were defined by Clinical Classifications Software (CCS) code values for ICD-9-CM. CCS was developed as part of the Healthcare Cost and Utilization Project sponsored by the Agency for Healthcare Research and Quality. The Superstorm Sandy period was defined as October 28, 2012, the date when an emergency evacuation order was issued in advance of Sandy’s landfall, and November 9, 2012, the end date of the active storm response period determined by the US Federal Emergency Management Agency (FEMA). Data were examined for Medicaid beneficiaries who were residents in 1 of 8 identified Superstorm Sandy–affected counties (Bronx, Kings, New York, Richmond, Queens, Nassau, Suffolk, and Westchester).

To quantify both short-term (immediate) and long-term (4- and 12-month) health effects from Sandy, we defined immediate, 4-month, and 12-month periods following the hurricane on the basis of the starting and ending months: October 2012 and November 2012. The immediate effect period was defined as October 1, 2012, to November 30, 2012; the 4-month period was defined as October 1, 2012, to January 31, 2013; and the 12-month period was defined as October 1, 2012, to September 30, 2013. During the storm period, service counts for all elderly enrollees were compared based on recipient residence inside or outside of the storm area as determined by FEMA. Recipients’ addresses were determined by the address at which the recipient resided when services were received. Analyses of monthly service counts per county were conducted separately for each period from claims service dates to determine the effect period. The potential confounding effects of temporal factors and sociodemographic differences by counties are potential concerns for the results. To address these concerns, we used 2 control groups: (1) the identical time window to the storm period dates 5 years prior (2007-2011) and 1 year after (2013-2014) the storm in the affected counties, and (2) all nonaffected (according to a FEMA report) counties in NYS during the same storm period.

Statistical Analysis

We analyzed regression models separately for monthly counts of all cases in each affected period following the storm (immediate, 4 months, and 12 months). Overall monthly cases were calculated by demographic characteristics (race and gender) within each affected period. We performed Poisson regression to compare differences in case counts during the storm year to that during control years, within affected and nonaffected counties, adjusting for race and gender. For cases, adjusted risk ratio (RR) with 95% confidence interval (95% CI) was calculated. All statistical tests were 2-tailed. Statistical analysis was performed using SAS software version 9.4 (SAS Institute Inc., Cary, NC) inside the ASPR Virtual Research Data Center.

RESULTS

The total numbers of Medicaid and Medicare claims over the 12-month study period were 217873 and 433985, respectively. Table 1 shows the association between exposure to Superstorm Sandy and the number of cases stratified by period following the storm and health condition (CVD, respiratory disease, and injury). In the 4-month period following the storm, the risk of CVD (RR, 2.13; 95% CI, 2.12-2.14) was twice as high as it was in the corresponding period in other years (referent). Respiratory disease was also significantly elevated 4 months following Superstorm Sandy (RR, 2.22; 95% CI, 2.21-2.22). However, the strongest association was risk of injury 12 months after the hurricane period (RR, 2.43; 95% CI, 2.43-2.44). When comparing affected areas versus nonaffected areas (referent), we found that CVD had the greatest risk immediately (RR, 2.65; 95% CI, 2.64-2.66), 4 months (RR, 2.62; 95% CI, 2.62-2.63), and 12 months (RR, 2.64; 95% CI 2.64-2.65) after the hurricane period.

Table 1

Short- and Long-term Effects of Superstorm Sandy on Morbidity among the Elderly by Storm Period and Affected Areaa

Abbreviations: RR, risk ratio; CI, confidence interval.

a Adjusted for gender and race.

b Superstorm Sandy period (October 2012 to November 2012) versus nonhurricane period (identical time window 5 years prior to [2007-2011] and 1 year after [2013-2014] Hurricane Sandy).

c Eight affected counties in New York State (Bronx, Kings, Nassau, New York, Richmond, Queens, Suffolk, Westchester) versus nonaffected counties (the rest of New York State).

The association between risk by demographic characteristics stratified by time period following storm exposure and health condition is shown in Table 2. We observed that the risk of CVD for women immediately, 4 months, and 12 months after Superstorm Sandy was twice as high as it was for men (referent). There was also a slight upward trend for respiratory disease among women immediately (RR, 1.89; 95% CI, 1.88-1.90), 4 months (RR, 1.91; 95% CI, 1.90-1.92), and 12 months (RR, 1.92; 95% CI, 1.91-1.92) following the storm period. Additionally, injury had over a 2.2-fold increased risk for all time periods following the storm, and effects 4 months (RR, 2.31; 95% CI, 2.30-2.32) and 12 months (RR, 2.30; 95% CI, 2.30-2.31) after the storm were greatest among women. Moreover, when comparing racial differences in risk, we found that whites had a higher risk for CVD, respiratory disease, and injury during each period following the storm than did other racial groups.

Table 2

Short- and Long-term Effects of Superstorm Sandy on Morbidity among the Elderly by Demographic Characteristics a

Abbreviations: RR, risk ratio; CI, confidence interval.

a Adjusted for race.

b Adjusted for gender.

DISCUSSION

Our results showed that the immediate period following Superstorm Sandy period was associated with greater than 2-fold risk for CVD, respiratory disease, and injury-related outpatient visits, ED visits, and hospital admissions among the elderly. These findings are consistent with those of a prior study in NYS that evaluated ED visits among elderly individuals following a disaster, which found an increase in ED visits 3 weeks after the storm for cardiovascular- and respiratory-related diseases.Reference Malik, Lee and Doran 5 A NYC study that examined injury-related mortality associated with Hurricane Sandy found that the majority of deaths following the storm occurred among the elderly, and the associated indirect risk of injury-related mortality was observable 30 days later.Reference Seil, Spira-Cohen and Marcum 6 This could be explained by resource theory, where elderly dual-eligible Medicare-Medicaid beneficiaries may take longer to recover following a disaster because of lower socioeconomic status, which potentially contributes to limited access to health services and needed resources.

In addition to the immediate effects, we found that Hurricane Sandy’s effect on adverse health was observable for 12 months following the storm period. Similar to our findings, a study that examined the long-term cardiovascular effects of Hurricane Katrina showed a persistent 3-fold increased rate of acute myocardial infarction 2 years after the storm period.Reference Gautam, Menachem and Srivastav 2 However, it is difficult to compare our findings with those of other studies because of the lack of literature examining long-term health effects of a hurricane on respiratory disease and injury. We hypothesize that a potential contributor to the long-term effects on respiratory health is the disruption in flu vaccination, because of health services closure, and injury resulting from storm-related cleanup and repair.

We observed that females were at a higher risk than males immediately, 4 months, and 12 months following the storm period. These findings are similar to those of a study that showed that women had a greater proportion of hospitalization during the 2003 Northeast Blackout.Reference Lin, Fletcher and Luo 7 Neumayer and Plumper (2007) suggested that gender differences in risk are the result of women being marginalized during a disaster when resources become scarce, which would hinder equitable access to relief resources and services.Reference Neumayer and Plümper 8 We also found that the risk for all health outcomes was lower among nonwhites. Our findings are similar to those of a study that assessed the effects of Hurricane Katrina on health outcomes among the elderly 1 year after the storm, which found that blacks experienced lower morbidity than whites.Reference Burton, Skinner and Uscher-Pines 9 Additionally, a NYC study that examined the effect of a large disaster on health showed that whites were more vulnerable to hospitalization.Reference Lin, Fletcher and Luo 7 The authors suggested that property damage and loss of services were greater contributors to adverse health following a disaster among whites and individuals of high socioeconomic status, as they are more dependent on having easy access to health services and resources than low socioeconomic status groups that experienced more sporadic access prior to the event.Reference Lin, Fletcher and Luo 7 , Reference Davidson, Price and McCauley 10

This is the first study to examine both immediate and long-term health effects for multiple diseases among dual-eligible Medicare-Medicaid beneficiaries. Although our study provides new insight that the effects of a hurricane on health can last for at least 1 year, we must note few limitations. This study selected a unique population that consisted of primarily elderly dual-eligible Medicare-Medicaid beneficiaries who are generally poorer, more vulnerable, and have worse health than the general population. Additionally, because of data limitations, we were unable to compare differences in risk between elderly Medicare beneficiaries and elderly dual-eligible Medicare-Medicaid beneficiaries. This limitation prevents us from clearly understanding if there are differences in risk between Medicare only and dual-eligible Medicare-Medicaid beneficiaries. On the other hand, our study has the advantage of taking into account outpatient and ED visits, rather than hospitalizations only. Nonetheless, previous literature shows that both the elderly Medicare-insured group and the dual-eligible Medicare-Medicaid insured group are generally more susceptible to chronic conditions.Reference Liu, Long and Aragon 3 , Reference Kane, Wysocki and Parashuram 4 We were also unable to include the exact Superstorm Sandy period or define Sandy-affected areas; however, we did use the standard defined by FEMA. For this reason, the potential misclassification bias would be nondifferential and the total storm effect on cases could potentially be underestimated. Moreover, the confounding effects of temporal factors and demographic differences between counties may be a concern for the results. To address these concerns, we used pre/post and affected versus nonaffected county comparisons. The pre/post comparison would control for sociodemographic differences as the same areas were compared, while affected versus nonaffected counties would control for temporal factors.

CONCLUSIONS

Our findings suggest that in addition to the immediate health effects, the effects of hurricane on health (CVD, respiratory disease, and injury) among the elderly population can last for 1 year following the storm period. This study provides evidence for incorporating long-term health effects following a disaster into public health preparedness. In addition, our results highlight the need to tailor intervention towards the elderly, whites, and women, as they are more vulnerable to health effects following a hurricane.

Funding

This work was supported by Grant# HITEP1500270101 from the Office of the Assistant Secretary of Preparedness and Response. The content is solely the responsibility of the authors and does not necessarily represent the official views of the US Department of Health and Human Services.

Conflict of Interest

None.

Acknowledgments

The authors would like to thank the Office of the Assistant Secretary of Preparedness and Response for its support on data management.

References

REFERENCES

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Figure 0

Table 1 Short- and Long-term Effects of Superstorm Sandy on Morbidity among the Elderly by Storm Period and Affected Areaa

Figure 1

Table 2 Short- and Long-term Effects of Superstorm Sandy on Morbidity among the Elderly by Demographic Characteristicsa