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Geographically distant social networks elevate perceived preparedness for coastal environmental threats

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Abstract

This study examines the effects of geographically differentiated social network support resources on perceived household preparedness and resource adequacy for coping with environmental hazards. The guiding notion is that socially close but spatially distant network resources will become critical for resilience in disaster contexts when the efficacy of local network resources become compromised due to community-wide disruption. Results from a random sample household survey of 928 coastal Louisiana residents confirm that perceived preparedness and resource adequacy for coping with environmental hazards is higher among those with strong support resources that are more than 2 h away from where they live, whereas access to support from local neighbors plays a lesser role. The implication is that efforts intended to build resilient communities by way of enhancing social network resources can benefit from considering the importance of promoting regional, in addition to localized, social ties.

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Notes

  1. Due to a large number of missing values (n = 223; ~ 19.2%) on the annual household income variable, we developed an OLS regression equation to generate predicted values for annual household income. This equation can be denoted as: \( \mathrm{Income}={b}_0+\mathrm{male}\left(\overline{x}\right)+\mathrm{age}\left(\overline{x}\right)+\mathrm{educational}\ \mathrm{attainmnet}\left(\overline{x}\right)+\mathrm{race}\left(\overline{x}\right)+\mathrm{household}\ \mathrm{size}\left(\overline{x}\right) \)

  2. We also noted missing data on sex among respondents to our mail survey. In these cases, we coded sex using the respondent’s name. A panel of three project team members coded each respondent as male or female. Responses from each panel member were cross checked for consistency and compared to a logistic regression model predicting respondent’s sex. The logistic regression model can be denoted as: \( \mathrm{Sex}=\mathrm{age}\left(\overline{x}\right)+\mathrm{race}\left(\overline{x}\right) \).

  3. The full results of the models are reported in Table 2. Based on these models predicted probabilities are shown in Figs. 2 and 3. All models reported were re-estimated using ordinary least squares regression to obtain multicollinearity diagnostics. All variance inflation factors were within acceptable limits, the highest being 4.08 for no. of children (correlated somewhat with household size – VIF = 3.10). Biased coefficients or standard errors due to collinearity were not a problem with these data.

  4. The 95% confidence intervals for the point estimates illustrated in the Figs. 2 and 3, and the number of cases per value on the network scale, are shown in the Appendix.

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Authors and Affiliations

  1. Department of Sociology, Brigham Young University, 2008 JFSB, Provo, UT, 84602, USA

    Michael R. Cope

  2. Louisiana State University, Baton Rouge, LA, USA

    Matthew R. Lee, Tim Slack, Troy C. Blanchard, Jeff Carney, Forbes Lipschitz & Lydia Gikas

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  1. Michael R. Cope
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Appendix

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Table 3 Predicted probabilities and 95% confidence intervals
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Cope, M.R., Lee, M.R., Slack, T. et al. Geographically distant social networks elevate perceived preparedness for coastal environmental threats. Popul Environ 39, 277–296 (2018). https://doi.org/10.1007/s11111-017-0292-0

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