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. Author manuscript; available in PMC: 2022 Jul 1.
Published in final edited form as: Soc Sci Med. 2021 Jun 6;281:114097. doi: 10.1016/j.socscimed.2021.114097

Effects of Peri-Traumatic Stress Experienced During Hurricane Sandy on Functional Limitation Trajectories for Older Men and Women

Rachel Pruchno 1, Maureen Wilson-Genderson 2, Allison R Heid 3, Francine P Cartwright 1
PMCID: PMC8276253  NIHMSID: NIHMS1711485  PMID: 34120083

Abstract

Background and methods.

Although the short-term effects of disasters on the physical health of mid-life and older people have been documented, little is understood about the long-term effects that disasters have on the physical health of these people. Based on the environmental docility hypothesis and research regarding gender effects on functional limitations and disaster, our analyses examined the effects of peri-traumatic stress experienced during Hurricane Sandy using longitudinal data from 5,688 people aged 50 and older collected over six waves (2006–2019).

Results.

We found that functional limitations follow three trajectories, with people in each group having a significant linear increase over time and all but the highest functioning people also having a significant quadratic effect, indicating that the linear increase peaked post-Hurricane and then slowed in later waves.

Conclusion.

Consistent with the environmental docility hypothesis, peri-traumatic stress had its greatest impact on people with more functional limitations before the hurricane. Men experiencing peri-traumatic stress during Hurricane Sandy were more likely to experience an increase in functional limitations than women. These findings, which identify people most likely to experience long-term health effects following a disaster, can be used to inform health policies before, during, and after disaster strikes.

Keywords: disaster, functional ability, gender, Hurricane Sandy

Introduction

Hurricane Sandy, the largest Atlantic hurricane on record, crashed into the Eastern United States on October 29, 2012. The hurricane’s heavy rain, sustained and gushing winds, and rising water levels caused 117 deaths and countless injuries (CDC, 2013). Property damages totaling $65 billion made Sandy the second-costliest hurricane in U.S. history (HRD, 2014). More than three-quarters of a million people were left with uninhabitable homes; numerous others had homes requiring extensive repairs (IDMC, 2013). Over eight million people lost electricity and heat for weeks, a problem exacerbated by an early snowstorm following the hurricane (Commerce, 2013). Power outages left water in 70 water systems undrinkable (https://www.nj.gov/dep/dsr/hurricane-sandy-assessment.pdf). In New Jersey, all-cause mortality rates of older people increased (Kim et al., 2017); applications to assisted living facilities soared (Eltman, 2013). While several studies have documented the short-term effects that disasters have on the psychological and physical health of older people (Gruebner et al., 2015; Hamama-Raz et al., 2015; Sands et al., 2018), and some studies have examined the long-term psychological effects of disasters on older people (Schwartz et al., 2014; Wilson-Genderson et al., 2018), little is known about disasters’ long-term effects on the physical health of mid-life and older people. The analyses that follow fill this gap.

Disaster Research

Disasters are traumatic events that simultaneously affect the lives of many people. According to a report from the Centre for Research on the Epidemiology of Disasters and United Nations Office for Disaster Risk Reduction (2015), 90% of disasters are weather-related. Worldwide, there were 3,751 natural disasters between 2008 and 2018 that wreaked havoc for two billion people and caused estimated damages of $1,658 billion (Red Cross, 2018). In addition to weather-related events, disasters can be human-induced, triggered accidentally (e.g., pilot or air traffic controller errors) or purposely (e.g., the September 11 terrorist attacks). Disasters can be caused by technology failures (e.g., when airplanes have mechanical defects), and by epidemics and pandemics (e.g., COVID-19).

One of the greatest challenges for researchers studying disasters is that systematic information rarely exists about people before the disaster (Arcaya, Raker, & Waters, 2020). Without this information, it is difficult for researchers to understand whether the disaster caused a change or merely provided the opportunity to chronicle an existing situation. When Hurricane Sandy struck, several thousand people aged 50+ in New Jersey had been participating in a longitudinal research panel for six years. This panel, recruited using random digit dialing methods, provides a unique opportunity to understand the long-term impact of disaster on the health of mid-life and older people.

Impact of Disasters on Mid-life and Older People

The issue of whether mid-life and older people are more psychologically vulnerable than younger people when natural disasters strikes is unresolved. Some studies find that with age, people become more vulnerable (Claver et al., 2013; Jia et al., 2010; Kun et al., 2013; Somes & Stephens Donatelli, 2012; Zhu & Sun, 2017). A meta-analysis revealed that older people were more than twice as likely to experience PTSD symptoms and almost twice as likely to develop adjustment disorder when exposed to natural disasters, than younger adults (Parker et al., 2016). On the other hand, there is evidence that the experience and resources older people bring to a disaster make them more psychologically resilient than younger people (Kohn et al., 2005; Rafiey et al., 2016). These discrepant findings suggest that characteristics other than age, including gender, income, education, social support, employment status, and pre-disaster health and functioning, may explain vulnerability to disaster.

Even less is known about the effects of disaster on the physical health of mid-life and older people. The few existing studies focus on earthquakes (Jia et al., 2010; Lin et al., 2002). Findings are heterogeneous (Almazan et al., 2018; Cherry et al., 2008), varying as a function of how physical health is measured (i.e., health, healthcare utilization) and the length of time between the disaster and data collection (Clouston et al., 2013; Wu et al., 2015). Most studies, however, are based on small convenience samples that lack information about people prior to the disaster.

Disaster and Gender

Gender is a key element of human experience affecting identity, relationships, cultural norms, and resources. As such, gender likely bears on capacities, decisions, and outcomes when disaster strikes. Yet, although disaster research generally includes sex as a survey variable, no careful, thorough examination of gender in disasters was undertaken until the 1990s (Enarson et al., 2006).

Since the 1990s, evidence suggesting that women may be more vulnerable to disasters than men has grown, although most of these studies do not focus on older people. Gendered studies of post-disaster health highlight negative health consequences for women (Richter, 2011). The 2004 tsunami, in which three times more women than men died in Sri Lanka, provides a vivid example of how women’s every day lives may lead to deadly outcomes when disaster strikes (Hyndman, 2008). However, the extent to which these findings can be generalized to mid-life and older Americans is unclear. A meta-analysis of 17 studies found that African American women exposed to Hurricane Katrina experienced profound physical and mental health effects despite having strong faith and high levels of cultural support (Laditka et al., 2010) and a study of emergency responders to the 9/11 attacks found that female responders expressed nearly double the rates of post-traumatic stress disorder as their male counterparts (Bowler et al., 2010). Using data from 141 countries, Neumayer and Plumper (2008) found that disasters had a greater effect on lowering life expectancy for women than men. A review by Enarson, Fothergill, and Peek (2018), organized in terms of mortality, health, and well-being; violence; family and work; and grassroots organizing, concluded that the health and well-being of women are at risk when disaster strikes. Overall, this work leads us to hypothesize that midlife and older women will be more vulnerable to a natural disaster, yet to our knowledge, this relationship has yet to be empirically tested.

Functional Limitation Trajectories

Functional limitations are early markers of disability with strong associations to morbidity, mortality, and quality of life (Freedman et al., 2013; Studenski et al., 2011). As such, functional limitations may be a particularly critical measure of change in health following a disaster. More than 5 million Americans aged 65+ cannot walk a quarter of a mile, climb up ten steps without resting, stand for two hours, sit for two hours, stoop, reach overhead, grasp small objects, carry ten pounds, or push large objects (HHS, 2018). Countless others have less serious functional limitations that impair ability to function and threaten quality of life (Clarke et al., 2002).

Functional limitations drive the disablement process, as disease or pathology initiate a spiral from impairment to functional limitation and disability (Nagi, 1976). Not only is minimizing functional limitations a public health priority because functional limitations are early indicators of a disablement process ending in institutionalization and death (Guralnik et al., 1995; Verbrugge & Jette, 1994), but also because the health care costs of people with functional limitations are nearly three times higher than those of others (Hayes et al., 2016). Intervening early in the disablement process can prevent disability, reduce health care costs, and improve quality of life.

Finding that people experience variability in functional limitations over time (Stuck et al., 1999) led Wolinsky et al. (2000) to suggest shifting the focus from single-wave transitions in functional health to patterns of transitions over time. Early studies found that functional limitation trajectories are heterogeneous and dynamic and that change is associated with individual characteristics, including age and gender (Gill et al., 2006; Nusselder et al., 2006). Research has identified up to eight trajectories of functional limitations, with most individuals following stable patterns over time, some experiencing increases in functional limitations, and others experiencing decreases (Deeg, 2005; Han et al., 2013; Rooth et al., 2016).

However, the bulk of these studies has centered on the impact of demographic characteristics (Jonkman et al., 2018; Lin, 2019). Although there is evidence that functional limitations increase following a disaster (Pruchno et al., 2019), few studies have examined how exposure to disaster affects trajectories of functional limitations (Tanji et al., 2017; Tomata et al., 2014). This information is important, because many people who experience functional limitations never recover (Zimmer et al., 2014). Better understanding the long-term effects of disaster provides the opportunity to intervene in effective ways, thereby improving quality of life for older people.

Functional Limitations and Gender

Although functional limitations are consistently greater for women than for men (Murray et al., 2011; Rohlfsen & Kronenfeld, 2014), it is not clear why. Nor is it clear how gender affects change in functional limitations. While some studies have examined individual risk factors (Li, 2005; Liang et al., 2008), others have looked to characteristics of the broader social domain such as neighborhoods and communities (Balfour & Kaplan, 2002; Beard et al., 2009; Freedman et al., 2008; Schootman et al., 2006). Wilson-Genderson and Pruchno (2015), examining both individual and social characteristics associated with functional limitations found that functional limitations of women, but not men, were affected by neighborhood characteristics. Some studies find that the gender gap in functional limitations increases with age (Liang et al., 2010; Lin, 2019; Newman & Brach, 2001), while other research finds that functional limitation trajectories of men and women converge over time, suggesting that health inequalities decline with age (Mendes de Leon et al., 2005). This literature suggests that the functional limitations of women will be more sensitive to disaster than those of men.

Conceptual Underpinnings: The Environmental Docility Hypothesis

The environmental docility hypothesis (Lawton & Nahemow, 1973; Lawton & Simon, 1968) suggests that stimuli from the environment will have its greatest effects on people with limited competence. People with limited competence have fewer resources and less ability to withstand pressures from external sources. That environmental stimuli have greater effects on people with low competence than high competence has been studied by scholars from a host of disciplines, including architecture, sociology, psychology, and human development (Wahl & Gerstorf, 2020). The docility hypothesis has been supported in such diverse situations as the effects of relocation on mortality of nursing home residents (Pruchno & Resch, 1988), the effects of urban living and social relationships on depressive symptoms (Knipscheer et al., 2000), and the effects of cognition on ability to use technology (Schmidt & Wahl, 2019). This literature suggests that Hurricane Sandy should have its greatest impact on people having more functional limitations prior to the disaster.

Disaster Exposure: Peri-Traumatic Stress

Scholars typically define disaster exposure as a function of geographic proximity (Abramson et al., 2008; Boscarino et al., 2013; Gruebner et al., 2015; Gruebner et al., 2017; Schwartz et al., 2016). However, geographic proximity to a disaster can be a crude indicator of exposure, especially when the geographic areas are broad. For example, defining exposure to a hurricane as a function of living in an area or county identified by FEMA as being impacted by a disaster, confounds the experiences of people not directly impacted by the disaster with the experiences of people personally affected by the disaster. Combining people with such different levels of exposure to the disaster minimizes the overall effects of disaster.

Other studies define exposure as a function of personal and property damage (Galea et al., 2007; Lowe et al., 2015; Schwartz et al., 2017; Tsuboya et al., 2016), peri-traumatic stress (Bell et al., 2017; Schwartz et al., 2016; Tang et al., 2014), and post-disaster hardship (Armenian et al., 2002; Forbes et al., 2015; Lock et al., 2012; Schwartz et al., 2016; Tang et al., 2014). However, because few studies have included more than one measure of exposure, it is difficult to know what it is about disaster exposure that is most impactful (Lieberman-Cribbin et al., 2017).

A study by Wilson-Genderson et al. (2018) examining multiple measures of disaster exposure in response to Hurricane Sandy found that although geographic proximity, personal and property loss, peri-trauma stress, and post-storm hardship each had independent effects on depressive symptoms, the effects of peri-traumatic stress dominated. Examining the effects of different types of disaster exposure on functional limitations, Pruchno et al. (2019) found that peri-traumatic stress and post-storm hardship had independent effects, that the effects of peri-traumatic stress dominated, and that effects were evident six years after the disaster. However, this analysis did not examine how exposure impacted the trajectory and recovery of distinct groups of individuals, which is the focus of the following analyses.

Current Study

This study expands understanding about how disasters impact people aged 50+ by: (1) focusing on the effects of disaster on functional limitations; (2) examining differential effects for women and men; (3) defining disaster exposure as a function of peri-traumatic stress; and (4) using longitudinal data from a large representative sample of mid-life and older people collected over a 12-year period. We test the following hypotheses:

  1. Peri-traumatic stress experienced during Hurricane Sandy will have a greater effect on the functional limitation trajectories of people with more functional limitations before the hurricane struck than on people having fewer functional limitations before the hurricane.

  2. The effects of peri-traumatic stress on functional limitation trajectories will be greater for women than men.

Methods

Participants

We recruited and completed interviews with 5,688 people (Wave 1) between 2006 and 2008 who were part of the ORANJ BOWL (Ongoing Research on Aging in New Jersey: Bettering Opportunities for Wellness in Life) panel. The overarching goal of ORANJ BOWL is to identify factors influencing successful aging. To recruit participants, we used cold calling and list-assisted random-digit-dialing procedures. Eligible participants were age 50 −74, living in New Jersey, and able to participate in a one-hour, English-language telephone interview. Coverage loss due to cell phone-only households was minimal (Blumberg & Luke, 2007). ORANJ BOWL achieved a Response Rate of 58.73% and a Cooperation Rate of 72.88%. Details regarding sample development are presented in Pruchno et al., (2010). Participants were representative of adults aged 50+ living in New Jersey in 2006, except for a slightly higher rate of women and people with more years of education. Because we were unable to translate the interview into Spanish, ORANJ BOWL under-represents Hispanics. At Wave 1, ORANJ BOWL participants lived in 1,644 of New Jersey’s 1,912 census tracts. Table 1 includes sample descriptives.

Table 1.

Sample demographic characteristics at each Wave.

Wave 1
N = 5688		 Wave 3
N = 3387		 Wave 4
N = 3608		 Wave 5
N = 3076		 Wave 6
N = 3137
Age [M (SD)] 60.79 (7.10) 65.37 (7.01) 67.66 (6.92) 69.14 (6.73) 70.39 (6.66)
Gender (Women) 3621 (63.7) 2202 (65.0) 2326 (64.5) 1956 (63.6) 1996 (63.6)
African American 646 (11.4) 276 (8.1) 314 (8.7) 222 (7.2) 250 (8.0)
Income
  Less than $15K 365 (6.4) 152 (4.5) 156 (4.3) 85 (2.8) 102 (3.3)
  $15K – $30K 601 (10.6) 289 (8.5) 297 (8.2) 221 (7.2) 215 (6.9)
  $30K – $50K 862 (15.2) 502 (14.8) 509 (14.1) 419 (13.6) 431 (13.7)
  $50K – $80K 1133 (19.9) 698 (20.6) 736 (20.4) 639 (20.8) 646 (20.6)
  $80K – $150K 1291 (22.7) 875 (25.8) 954 (26.4) 864 (28.1) 881 (28.1)
  More than $150K 770 (13.5) 520 (15.4) 573 (15.9) 516 (16.8) 534 (17.0)
  Missing 666 (11.7) 351 (10.4) 383 (10.6) 332 (10.8) 328 (10.5)
Educational Attainment
  Not HS Graduate 306 (5.4) 115 (3.4) 113 (3.1) 59 (1.9) 61 (1.9)
  HS Graduate or GED 1607 (28.3) 863 (25.5) 900 (24.9) 686 (22.3) 706 (22.5)
  Some college 852 (15.0) 487 (14.4) 515 (14.3) 452 (14.7) 459 (14.6)
  2 yr. college degree 530 (9.3) 320 (9.4) 356 (9.9) 313 (10.2) 312 (9.9)
  4 yr. college degree. 1108 (19.5) 697 (20.6) 769 (21.3) 681 (22.1) 714 (22.8)
  Some post baccalaureate 220 (3.9) 162 (4.8) 164 (4.5) 148 (4.8) 153 (4.9)
  Masters 743 (13.1) 521 (15.4) 563 (15.6) 516 (16.8) 517 (16.5)
  Some post-Masters 73 (1.3) 50 (1.5) 52 (1.4) 47 (1.5) 45 (1.4)
 Doctorate 236 (4.1) 168 (5.0) 171 (4.7) 171 (5.6) 167 (5.3)
 Missing 13 (0.2) 4 (0.1) 5 (0.1) 3 (0.1) 3 (0.1)
Functional Limitations [M (SD)] 13.0 (5.6) 14.6 (6.6) 15.4 (6.9) 14.5 (6.3) 14.6 (6.3)
Chronic Illnesses [M (SD)] 1.76 (1.40) 1.70 (1.35) 1.66 (1.32) 1.60 (1.29) 1.57 (1.28)
Peri-traumatic Stressors --- --- 0.86 (1.01) --- ---
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One year after their baseline interview, a subsample of participants was re-contacted and asked to complete a personality measure (Wave 2). Data from this wave are not included in these analyses.

In 2011, ORANJ BOWL respondents were mailed a questionnaire (Wave 3) (see Figure 1 for sample flow); 3,387 panelists completed the survey. In 2014, approximately 18 months after Hurricane Sandy struck, we mailed another questionnaire (Wave 4) to all ORANJ BOWL respondents known to be alive at Wave 3. For participants who did not complete the survey, we called and completed the interview by telephone; 3,608 panelists completed Wave 4. Wave 4 has a larger sample size than Wave 3 due to the availability of additional funds for sample follow-up. Wave 5 was completed approximately 18-months after Wave 4 (2015 to 2017); 3,076 panelists completed Wave 5. Panelists completed the interview by phone with an interviewer, by web using a Qualtrics programmed survey, or by mail. Following similar protocols, Wave 6 was completed approximately 18-months after Wave 5 (2017 to 2019); 3,137 panelists completed Wave 6. At each Wave, completers reported higher levels of education and income than those who had died or did not complete the questionnaires. Completers were also significantly older than non-completers and younger than those who withdrew or died. Completers were more likely to be women than those who died and less likely to be African American than those who died or did not complete the questionnaires (Heid et al., 2021). As this analysis is centered about the effects of Hurricane Sandy on trajectories of functional limitations, participants were required to have baseline and at least Wave 4 data to be included.

Fig. 1.

Fig. 1.

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BLINDED FOR REVIEW Sample completions flow chart.

Measures

Functional Limitations.

At each data collection wave, respondents reported the extent of difficulty they had with nine indicators of functional limitations (walk a 1/4 mile, walk up 10 steps without resting, stand or be on your feet for about 2 hours, sit for about 2 hours, stoop, bend, or kneel, reach up over your head, use your fingers to grasp or handle small objects, lift or carry something as heavy as 10 lbs., such as a full bag of groceries, and push or pull large objects like a living room chair) using a 5-point Likert scale ranging from 1 (can’t do it at all) to 5 (not at all difficult). Items were reverse scored such that higher scores indicate greater functional limitations.

Disaster Exposure.

We conceptualized disaster exposure as a function of peri-traumatic stress which we assessed at Wave 4 (12–53 months after the hurricane). Using questions similar to those developed by Bell et al. (2017), we asked participants whether they felt: 1) in immediate physical danger during Hurricane Sandy, or 2) distressed or fearful during Hurricane Sandy. We used a three-point scale for each question: 0 (no), 1 (a little), or 2 (a lot) and summed responses. The mean was 0.86 (SD = 1.0); range was 0–4.

Demographic Covariates.

At baseline, respondents reported their age, gender (0 = man, 1 = woman), income (range from 1 = less than $15,000 to 6 = more than $150,000), education (range from 1 = less than high school to 9 = doctoral degree) and race (0 = not African American, 1 = African American).

Statistical Analysis

We examined means and standard deviations for functional limitation scores at each wave and created empirical growth plots for functional limitation scores. Because the raw trajectories suggested heterogeneity, we used latent class growth models (LCGM) to simplify the heterogeneous set of functional limitation trajectories into more homogeneous clusters. LCGM is a semi parametric technique used to identify distinct subgroups of individuals following a similar pattern of change over time (Nagin, 2005).

We built LCGM with one to four classes, refining the preliminary models to select the solution with the optimal number of classes, using the Bayesian information criteria (BIC; de Schoot et. al., 2017). As a further assessment of the optimal number of classes in the chosen solution, the BIC log Bayes factor approximation, 2loge (B10) ≈ 2 (∆BIC) where ∆BIC is the BIC of the alternative (more complex) model less the BIC of the null (simpler) model is reported. Interpretation is based on guidelines established by Jones and colleagues (Jones Nagin, & Roeder, 2001).

We risk adjusted the LCGM for death. We then created trajectory plots presenting each LCGM class to permit examination of the average pattern of change within the identified classes. Classes are presented with 95% confidence intervals; if the CI do not overlap there is increased confidence that the groups are meaningfully distinct.

We tested the linear and quadratic (non-linear) models for the slope of the functional limitation trajectories to assess if there was significant change over time and the pattern of that change for each of the LCGM groups. The linear change parameter captures a constant increase or decrease over time (straight line); a quadratic parameter captures change that is not strictly linear but rather may change in one direction (e.g., increase) and then another (e.g., decrease) over time. After these initial LCGM groups were established, we risk-adjusted the models for peri-traumatic stress experienced during Hurricane Sandy. Groups were then compared on participant characteristics and peri-trauma stress using MANOVA (continuous) and Chi-square (categorical).

Given known differences in functional limitation trajectories experienced by men and women (Murray et al., 2011; Rohlfsen & Kronenfeld, 2014), as well as empirical research regarding the effects of gender on disaster (Enarson et al., 2018), we developed all analyses separately for men and women. We report the amount of missing data for functional limitations at each wave, assumptions regarding missingness, and any missing data techniques needed to address it (Sidi & Harel, 2018). Models were implemented using SAS 9.4 (SAS Institute Inc. 2015. SAS. ®. 9.4) proc traj.

Results

Full Sample Results

The BIC values adjusting for death were: −51263.60 (1); −46290.36 (2); −44604.52 (3); −44978.05 (4). We selected the three-class solution (Figure 2a) as it had the lowest BIC; 2 (∆BIC) computations confirm this selection. As seen in Table 2, Group 1 contained 67.9% of the sample (n = 2,432) and had the lowest functional limitation scores (intercept of 10.62) The linear increase was significant; the quadratic effect was not significant and was removed from the model. Group 2 contained 23.2% of the participants (n = 823) with an intercept of 12.50, a significant linear increase, as well as a significant quadratic effect indicating that the linear increase slowed in later waves. Group 3 contained 8.9% of the participants (n = 314) with an intercept of 22.40, a significant linear increase as well as a significant quadratic effect indicating that the linear increase slowed in later waves. Dying during the course of the study was significantly associated with membership in Groups 2 and 3, with more people in these groups dying than in Group 1. This model was re-estimated including the risk adjustment for peri-traumatic stress which was positively associated with membership in Groups 2 and 3.

Fig. 2.

Fig. 2.

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Functional Limitations Over Time for the (a) Whole Sample, (b) Men, and (c) Women; Group 1 is represented in red (lowest ratings of functional limitations), Group 2 is represented in green (moderate ratings of functional limitations), and Group 3 is represented in blue (highest ratings of functional limitations).

Table 2.

LGCM three class solution with change parameters .

Group Whole sample Men Women
beta (se) beta (se) beta (se)
1 N = 2432 N = 960 N = 1146
Intercept 10.62 (0.08) 10.10 (1.10) 10.90 (1.00)
Linear 0.19 (0.02)*** 0.19 (0.02)*** 0.18 (0.03)***
Quadratic -- -- --
Died [referent] [referent] [referent]
Peri-storm Exposure [referent] [referent] [referent]
2 N= 823 N = 250 N = 601
Intercept 12.50 (0.25) 11.57 (0.38) 13.20 (0.32)
Linear 3.02 (0.17)*** 2.39 (0.27)*** 2.96 (0.21)***
Quadratic −0.28 (0.02)*** −0.21 (0.07)*** −0.28 (0.03)***
Died 1.59 (0.20)*** 1.77 (0.30)*** 1.60 (0.29)***
Peri-storm Exposure 0.16 (0.04)*** 0.16 (0.08)* 0.08 (0.05)
3 N = 314 N = 69 N= 260
Intercept 22.40 (0.42) 14.94 (0.74) 23.10 (0.48)
Linear 3.70 (0.27)*** 5.36 (0.50)*** 3.70 (0.31)***
Quadratic −0.45 (0.04)*** −0.51 (0.07)*** −0.46 (0.05)***
Died 2.20 (0.21)*** 2.35 (0.37)*** 2.56 (0.29)***
Peri-storm Exposure 0.18 (0.06)** 0.23 (0.12)+ 0.07 (0.07)
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+

p < .10,

*

p < .05,

**

p < .01,

***

p < .001

Comparisons of demographic characteristics and peri-traumatic stress are reported in Table 3. Group 3 had the greatest percentage of women, followed by Group 2 and Group 1 (χ2 (2, 3566) = 161.7, p < .001). Group 3 also had the greatest percentage of African Americans (χ2 (2, 3567) = 38.8, p < .001), and the greatest proportion of individuals that died (χ2 (2, 3567) = 177.7, p < .001). Groups 2 and 3 were similar on age but older than Group 1 (F (2, 3566) = 91.91, p < .001). Group 1 was significantly higher than Group 2 and Group 2 was significantly higher than Group 3 (F (2, 3561) = 104.84, p < .001) on level of education. Like education, each of the three groups were significantly different from each other on income (F (2, 3190) = 246.37, p < .001). For peri-traumatic stress, the omnibus test was significant (F (2, 3566) = 15.8, p < .001); contrasts revealed that people in Group 3 reported the highest level of peri-traumatic stress, followed by people in Group 2. People in Group 1 reported significantly lower peri-storm stress than the other groups.

Table 3.

Comparing LGCM groups on demographic indicators and Sandy exposure.

Whole Sample Men Women
G1
N = 2432		 G2
N = 823		 G3
N = 314		 G1
N= 960		 G2
N = 250		 G3
N = 69		 G1
N = 1146		 G2
N = 601		 G3
N= 260
N (%) N % N % p N % N % N (%) p N (%) N % N % p
Women 1404 (58) 624 (76) 272 (86) .0001
African American 172 (7) 83 (10) 54 (17) .0001 52 (5) 14 (6) 13 (19) .0001 123 (8) 65 (11) 46 (17) .0001
Died 51 (2) 80 (10) 55 (18) .0001 24 (3) 36 (14) 15 (22) .0001 22 (2) 47 (8) 44 (17) .0001
M (SD) M (SD) M (SD) p M (SD) M (SD) M (SD) p M (SD) M (SD) M (SD) p
Age 59.50 (6.60) 62.90 (6.90) 62.60 (7.20) .0001 59.40 (6.90) 62.20 (6.80) 62.00 (6.50) .0001 59.52 (6.80) 63.09 (6.90) 62.83 (7.10) .0001
Education 4.66 (2.10) 3.81 (1.96) 3.19 (1.80) .0001 4.93 (2.00) 4.11 (2.20) 3.51 (2.00) .0001 4.50 (2.10) 3.72 (1.90) 3.17 (1.80) .0001
Household income 4.49 (1.26) 3.68 (1.36) 2.92 (1.39) .0001 4.71 (1.30) 4.10 (1.40) 3.39 (1.30) .0001 4.34 (1.30) 3.52 (1.40) 2.83 (1.40) .0001
Peri-trauma stress 0.81 (0.97) 1.00 (1.10) 1.04 (1.11) .0001 0.64 (0.88) 0.77 (0.90) 0.79 (1.10) .049 0.94 (1.00) 1.03 (1.10) 1.08 (1.10) .02
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Note. Categorical constructs are compared using chi-square; continuous constructs are compared using MANOVA.

Results for Men

The BIC values for the men, risk-adjusted for death were: 16784.23 (1); 15258.83 (2); 14744.47 (3); nonconvergence (4). We selected the three-class solution (Figure 2b) as it had the lowest BIC amongst the models that converged; 2 (∆BIC) computations confirm this selection. Group 1 contained nearly three-fourths of the men (n = 960; 74.6%) with a functional limitations intercept of 10.10, a significant, though slight, linear increase; the quadratic effect was not significant and was removed from the model. Group 2 contained 19.8% of the men (n = 250) with an intercept of 11.57, a significant linear increase, as well as a significant quadratic effect indicating that the linear increase slowed in later waves. Group 3 contained 5.6% of the men (n = 69) and had the highest functional limitations scores (intercept of 14.94), a significant sharp linear increase, as well as a significant quadratic effect indicating that the linear decrease slowed in later waves. Using Group 1 as the reference for risk adjustment due to death, the men in Group 2 and Group 3 showed a significant risk of dying during the course of this study. This model was re-estimated including the risk adjustment for peri-traumatic stress which was found to be positively associated with membership in Group 2 and marginally associated with membership in Group 3 (p = .07).

Group comparisons revealed that Group 3 had the most African Americans (χ2 (2, 1277) = 20.2, p < .001), as well as the greatest proportion of individuals that died (χ2 (2, 1277) = 84.3, p < .001). The men in Groups 2 and 3 were similar on age but older than men in Group 1 (F (2, 1276) = 20.8, p < .001). Groups 2 and 3 were significantly lower than Group 1 on education (F (2, 1275) = 27.19, p < .001). Each of the three groups were significantly different from each other on income (F (2, 1185) = 53.02, p < .001); Group 3 was the lowest and Group 1 the highest. For peri-trauma stress, the omnibus test for men was significant (F (2, 1266) = 3.25, p < .04); contrasts revealed that Groups 2 and 3 had significantly higher levels of peri-traumatic stress than Group 1.

Results for Women

For the women, the BIC values risk-adjusted for death were: 33788.83 (1); 30626.22 (2); 29562.69 (3); 29664.17 (4); 2 (∆BIC) computations confirm this selection, although the differences between model fit for three classes compared to four was slight. We selected the three-class solution (Figure 2c) as it had the lowest BIC. Group 1 contained 62.5% of the women participants (n = 1446) with a functional limitations intercept of 10.90, a significant, though slight, linear increase; the quadratic effect was not significant and was removed from the model. Group 2 contained 26.3% of participants (n = 601) with an intercept of 13.20, a significant linear increase, as well as a significant quadratic effect indicating that the linear increase slowed in later waves. Group 3 contained 11.3% of the women (n = 260) and had the highest functional limitations intercept of 23.10 a significant linear increase, as well as a significant quadratic effect indicating that the linear increase slowed in later waves. Using Group 1 as the reference for risk adjustment due to death, Groups 2 and 3 showed a significant risk of dying during the course of this study. This model was re-estimated including the risk-adjustment for peri-traumatic stress which was not associated with group membership.

Group comparisons revealed that Group 3 had the most African Americans (χ2 (2, 2322) = 20.4, p < .001), as well as the greatest proportion of individuals that died (χ2 (2, 2322) = 126.25, p < .001). The women in Groups 2 and 3 were similar on age but older than Group 1 (F (2, 2323) = 70.54, p < .001). Each of the three groups were significantly different from each other on education (F (2, 2317) = 68.98, p < .001) and income (F (2, 2030) = 164.56, p < .001); Group 3 was the lowest and Group 1 the highest for both. For peri-traumatic stress, the omnibus test for women was significant (F (2, 2297) = 3.99, p < .02); contrasts revealed that women in Groups 2 and 3 reported significantly higher levels of peri-traumatic stress than women in Group 1.

Missing Data

There were zero participants at baseline missing functional limitations data. There were six participants at Wave 3 and nine participants at Wave 4 missing functional limitations data. At Wave 5 there were 179 people missing functional limitations data. At Wave 6 there were 55 participants missing functional limitations data. Given the extremely small amounts of missing data, data were assumed MAR. Imputation was, however, done for functional limitations at Wave 5 using SAS proc MI. Models re-estimated with the imputation did not differ substantially nor interpretively from the models presented.

Discussion

Informed by the environmental docility hypothesis and disaster research, these analyses examined the impact of Hurricane Sandy on trajectories of functional limitations using three waves of data collected before the hurricane and three waves of data collected after it. Analyses examined the differential effects for women and men and defined disaster exposure as a function of peri-traumatic stress. We found that functional limitations vary over time, that distinct groups of individuals experiencing similar patterns of change in functional limitations are discernable, and that the functional limitations of men experiencing peri-trauma exposure during Hurricane Sandy were more likely to increase than those of women. These results add to our understanding about how functional limitations change over time for mid-life and older people and how a disaster impacted the health of these people. Findings have implications for intervening in the lives of people aged 50+ both before and after disaster strikes.

Consistent with prior work, our analyses found that functional limitations increased over time (Stuck et al., 1999). Also consistent with prior work, three distinguishable trajectory groups were identified based on 12-years of functional limitation data (Deeg, 2005; Han et al., 2013; Rooth et al., 2016). A dominant resilient group (68% of the sample) reported persistently low levels of functional limitations over time (Group 1). A second group (23% of the sample) reported moderate levels of functional limitations that increased following Hurricane Sandy but slowed in later waves (Group 2). A third vulnerable group (9% of the sample) reported higher levels of functional limitations at baseline that increased after Hurricane Sandy and then tapered off over time (Group 3). This third group remained higher than the other groups. These groups were discernable based on gender, race, deceased status, age, education, and income in expected directions. Those in the most vulnerable group (Group 3) were more likely to be older, women, and African American, and were more likely to report lower levels of education and income. Those in the moderate (Group 2) and vulnerable groups (Group 3) was also more likely to have died during the study than those in the resilient group (Group 1).

Our analyses expand our understanding of how disaster exposure impacts the functional limitations of people and, specifically, for whom the impact is greatest. Prior work found that peri-traumatic stress and post-storm hardship experienced in response to Hurricane Sandy were associated with higher levels of functional limitations six years post-storm (Pruchno et al., 2019). The analyses presented here expand those findings to demonstrate that, in line with the environmental docility hypothesis, people with higher levels of pre-storm functional limitations were more vulnerable to the impact of peri-trauma stress. Specifically, individuals belonging to Groups 2 and 3 (those experiencing moderate to high levels of functional limitations at baseline) experienced a significant linear increase in functional limitations over time and reported significantly higher levels of peri-traumatic stress compared to the resilient group (Group 1). That is, storm exposure was also a distinguishing factor between groups; greater exposure to the stressor was associated with greater increases in functional limitations.

In line with prior work, when we examined differences in change of functional limitations and impact of socio-cultural factors by gender (Wilson-Genderson & Pruchno, 2015), we found differential effects for men and women. Namely, while women experienced a greater mean-level of functional limitations within each of the trajectory groups, the effects regarding disaster exposure were greatest for the men in this sample. These findings differ from those summarized by Enarson et al. (2018) and may best be explained as a function age, as few other disaster studies have focused on the experiences of mid-life and older people. Our data showed that risk adjustment findings for group membership based on storm exposure were significant for men but not women. The men experiencing the greatest impact of peri-storm stressors on functional limitations were those with the higher levels of pre-storm functional limitations (men in Groups 2 and 3). Interestingly, despite storm exposure being a distinguishing factor for functional limitation trajectory group membership for men and not women, men reported on average lower levels of peri-traumatic stress than women. This finding may indicate that the functional limitations of men are more sensitive to felt threats from a disaster than are those of women. Alternately, cultural norms may have resulted in men reporting less peri-traumatic stress than they actually experienced. These possibilities require greater attention from future studies.

Overall, these findings carry implications for future research and practice. The findings highlight the importance of examining the long-term effects of a disaster on the functioning of mid-life and older people and the importance of pre-disaster data. By having information about functional limitations before the disaster struck, as well as after, we can understand how disasters impact people and how/if recovery follows. Second, the results here highlight the importance of distinguishing long-term disaster effects by gender. Men and women were distinct in their trajectories. Third, self-reported disaster-exposure scales, such as reports of peri-trauma, are sensitive measures that can be used to capture the impact of a disaster on developmental outcomes. Expanding disaster research to use such measures instead of more global geographic exposure indices can advance the field and our understanding of the impact of disasters on individuals. Fourth, the findings here highlight that when a disaster strikes those adults (specifically men) with pre-existing functional limitations are most vulnerable to the impacts of the disaster on their well-being. Identifying the smaller subset of individuals that are more compromised when a disaster is about to hit, or immediately following impact in one’s community, is critical. Offering resources and support to this subgroup may interrupt the downward spiral of functional disability and promote health for longer periods of time – thereby decreasing healthcare costs, morbidity, and mortality.

Limitations

While these findings are strengthened by our use of 12 years of data from a large state-wide panel of mid-life and older adults, this work is not without limitation. The results presented here are in response to one disaster – Hurricane Sandy. It cannot be determined if these findings are a specific artifact of the effects of this disaster on this sample surveyed or if they are universal to other disasters. Specifically, the hurricane was a short-lived disaster with time-limited exposure. Future work should consider if a longer-lasting disaster (i.e., a pandemic) carries similar or differential effects on the functioning of mid-life and older people. Second, the sample underrepresents Hispanics and sample attrition over the 12-years impacts generalizability. Given the finding here that there is a greater impact of exposure on those with lower levels of functioning, healthy survivor effects within the sample may in fact underestimate the impact of disaster on functional health. Further, as with any repeated measures study, there is some missing data, although it is very modest for functional limitations. We heed guidance regarding missingness in reporting it, the assumptions regarding it, and means of addressing it (Sidi & Harel, 2018). Finally, all data were self-reported. Although self-report data have been shown to be reliable for reporting functional limitations (Latham et al., 2008; Prince et al., 2008; Simonsick et al., 2001), examining medical records data or observational data of individuals may reveal a different story.

Conclusion

Overall, despite limitations, findings demonstrate how disaster exposure can impact the functional limitation trajectories of mid-life and older adults. Results highlight the specific impact of self-rated stress during a storm for men on their subsequent functional health. Future work is needed to test if these findings hold in response to other disasters, or if this result is specific to Hurricane Sandy. Disaster relief specialists can be informed by this work and target intervention efforts to those older individuals, specifically men, with pre-existing functional limitations when disaster strikes.

Highlights.

  1. Study identified three trajectories of functional limitations.

  2. People with more functional limitations before the hurricane were at most risk.

  3. Men experienced a greater increase in functional limitations than women.

Funding

This work was supported by University of Medicine and Dentistry of New Jersey, School of Osteopathic Medicine (UMDNJ-SOM), whose funding enabled establishment of the ORANJ BOWL (“Ongoing Research on Aging in New Jersey – Bettering Opportunities for Wellness in Life”) research panel and collection of baseline data. This work was also supported by the UMDNJ Foundation for Wave 3 data collection, the Assistant Secretary for Preparedness and Response (1 HITEP130008-01-00) and the Rockefeller Foundation (2012_RLC 304; PI: George Bonanno) for Wave 4 data collection, and the NIA (R01 AG046463) for Waves 5 and 6 data collection.

Footnotes

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Conflict of Interests: Authors have no conflicts of interest to disclose.

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