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Cited by 371

The DOI matches its Crossref record; 26 of the 26 references it cites were found in a registry or an index.

Understanding ‘energy insecurity’ and why it matters to health

Open access
Hernández, Diana·2016·Social Science & Medicine

Abstract

Energy insecurity is a multi-dimensional construct that describes the interplay between physical conditions of housing, household energy expenditures and energy-related coping strategies. The present study uses an adapted grounded theory approach based on in-depth interviews with 72 low-income families to advance the concept of energy insecurity. Study results illustrate the layered components of energy insecurity by providing rich and nuanced narratives of the lived experiences of affected households. Defined as an inability to adequately meet basic household energy needs, this paper outlines the key dimensions of energy insecurity-economic, physical and behavioral- and related adverse environmental, health and social consequences. By thoroughly examining this understudied phenomenon, this article serves to raise awareness of an increasingly relevant issue that merits more attention in research and policy.

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Crossref · 10.1016/j.socscimed.2016.08.029

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Metadata

Authors
Hernández, D.
Venue
Social Science & Medicine
Publisher
Elsevier BV
Published
2016-10
Volume
167
Pages
1-10
ISSN
0277-9536 (ISSN-L)
OpenAlex
W2512930938
Cited by
371
References
26
FWCI
4.03
Type
journal article
Language
en
Open access
green

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CoChat. (2026). Citation check: Understanding ‘energy insecurity’ and why it matters to health. https://app.cochat.ai/papers/10.1016/j.socscimed.2016.08.029
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Hernández, D. (2016). Understanding ‘energy insecurity’ and why it matters to health. Social Science & Medicine. https://doi.org/10.1016/j.socscimed.2016.08.029

Data sources

Bibliographic data: Semantic Scholar, OpenAlex, Crossref.

Contains information from the Semantic Scholar Academic Graph Datasets, made available under the ODC Attribution License (ODC-BY 1.0).

Semantic Scholar’s data is described in: Kinney, R., et al. (2023). The Semantic Scholar Open Data Platform. arXiv:2301.10140.