Evidence map›Paper›PMID 34374032›Full record

ArticleJournal of urban health : bulletin of the New York Academy of Medicine2021

Energy, Data, and Decision-Making: a Scoping Review-the 3D Commission.

Nason Maani, Grace Robbins, Shaffi Fazaludeen Koya, Opeyemi Babajide, Salma M Abdalla, Sandro Galea

Open access · greenAbstract readScoping Review
In one paragraph

Article in Journal of urban health : bulletin of the New York Academy of Medicine, 2021. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 2 papers.

0numbers the graph read from it
0cells of the map it votes in
2citing papers in PubMed
0.2field-weighted citation impact, top 60% of its field
1 · What the graph read from it

What it found

Each row is one number read from the abstract, on the scale the paper reported it, with its interval. Left of the dashed line favours the treatment, right favours the comparator. Under each row is the sentence it came from. New to these charts? A ten-minute tutorial.

The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.

2 · The registry

The trial behind it

Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.

Neither the registry nor the abstract names a trial number. If this is a trial report, that itself is worth knowing.

3 · Its place in the literature

Who cites it

2 citing papers in PubMed, 6 citations in OpenAlex.

  1. Review
  2. Article
4 · The record

Corrections and comments

PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.

5 · Who and what money

Authors and funding

6 authors at 2 institutions in 2 countries.

Nason MaaniFaculty of Public Health and Policy, London School of Hygiene and Tropical Medicine, London, UK.
Grace RobbinsDepartment of Epidemiology, Boston University School of Public Health, Boston, USA.
Shaffi Fazaludeen KoyaDepartment of Epidemiology, Boston University School of Public Health, Boston, USA.
Opeyemi BabajideRockefeller Foundation-Boston University 3-D Commission on Determinants, Data, and Decision-making, Boston, USA.
Salma M AbdallaDepartment of Epidemiology, Boston University School of Public Health, Boston, USA. abdallas@bu.edu.
Sandro GaleaDepartment of Epidemiology, Boston University School of Public Health, Boston, USA.
Rockefeller Foundation · USLondon School of Hygiene & Tropical Medicine · GB

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Access to energy is an important social determinant of health, and expanding the availability of affordable, clean energy is one of the Sustainable Development Goals. It has been argued that climate mitigation policies can, if well-designed in response to contextual factors, also achieve environmental, economic, and social progress, but otherwise pose risks to economic inequity generally and health inequity specifically. Decisions around such policies are hampered by data gaps, particularly in low- and middle-income countries (LMICs) and among vulnerable populations in high-income countries (HICs). The rise of "big data" offers the potential to address some of these gaps. This scoping review sought to explore the literature linking energy, big data, health, and decision-making.Literature searches in PubMed, Embase, and Web of Science were conducted. English language articles up to April 1, 2020, were included. Pre-agreed study characteristics including geographic location, data collected, and study design were extracted and presented descriptively, and a qualitative thematic analysis was performed on the articles using NVivo.Thirty-nine articles fulfilled eligibility criteria. These included a combination of review articles and research articles using primary or secondary data sources. The articles described health and economic effects of a wide range of energy types and uses, and attempted to model effects of a range of technological and policy innovations, in a variety of geographic contexts. Key themes identified in our analysis included the link between energy consumption and economic development, the role of inequality in understanding and predicting harms and benefits associated with energy production and use, the lack of available data on LMICs in general, and on the local contexts within them in particular. Examples of using "big data," and areas in which the articles themselves described challenges with data limitations, were identified.The findings of this scoping review demonstrate the challenges decision-makers face in achieving energy efficiency gains and reducing emissions, while avoiding the exacerbation of existing inequities. Understanding how to maximize gains in energy efficiency and uptake of new technologies requires a deeper understanding of how work and life is shaped by socioeconomic inequalities between and within countries. This is particularly the case for LMICs and in local contexts where few data are currently available, and for whom existing evidence may not be directly applicable. Big data approaches may offer some value in tracking the uptake of new approaches, provide greater data granularity, and help compensate for evidence gaps in low resource settings.

Indexed as

IncomePovertyHumansDataEnergyGlobal healthInequityPolicyPublic health

Identifiers

PMID34374032
PMCPMC8440708
OpenAlexW3192118817

What OpenQuestion holds

Textmetadata
Read underepoch 390

Registered trials

None linked

Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.