Evidence map›Paper›PMID 33751382›Full record

ArticleEnvironmental science and pollution research international2021

Obesity Kuznets curve hypothesis and global warming: a robust estimation under cross-section dependence.

You-How Go, Lin-Sea Lau, Cheong-Fatt Ng, Thian-Hee Yiew

Abstract read
PubMed Publisher
In one paragraph

Article in Environmental science and pollution research international, 2021. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 7 papers.

0numbers the graph read from it
0cells of the map it votes in
7citing papers in PubMed
2.1field-weighted citation impact, top 9% 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

7 citing papers in PubMed, 12 citations in OpenAlex.

  1. Wealth and weight revisited: A Bayesian model averaging approach to the Obesity Kuznets Curve.The European journal of health economics : HEPAC : health economics in prevention and care · 2026
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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

4 authors at 1 institution in 1 country.

You-How GoFaculty of Business and Finance, Universiti Tunku Abdul Rahman, Kampar, Malaysia.
Lin-Sea LauFaculty of Business and Finance, Universiti Tunku Abdul Rahman, Kampar, Malaysia.
Cheong-Fatt NgFaculty of Business and Finance, Universiti Tunku Abdul Rahman, Kampar, Malaysia. ngcf@utar.edu.my.ORCID http://orcid.org/0000-0002-0171-4924
Thian-Hee YiewFaculty of Business and Finance, Universiti Tunku Abdul Rahman, Kampar, Malaysia.
Universiti Tunku Abdul Rahman · MY

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Obesity is a worldwide concern as it leads to adverse effects on human health. This study uses a panel of 165 countries and annual data from 2000 to 2014 to examine the obesity Kuznets curve (OKC) hypothesis. By using tests and estimators that are robust to cross-section dependence (CSD), our results support the OKC hypothesis. This indicates that obesity increases at the initial stage of economic development and eventually would decrease once the threshold is reached. In addition, we find that the role of global warming on obesity is not significant. Food production is found to be a contributing factor to obesity. Besides, one-way and two-way causalities are identified between the variables. This study provides important insights particularly about the relationship between (i) economic growth and obesity and (ii) environmental degradation and obesity. Implication of the results and policy recommendations are also provided to policymakers and health personnel in finding solutions to the obesity epidemic around the world.

Indexed as

Global WarmingSubstance-Related DisordersCarbon DioxideEconomic DevelopmentHumansObesityCarbon DioxideCCEMG and AMGCO2 emissionsD-H causality testObesityWorld panel

Identifiers

PMID33751382
OpenAlexW3135136476

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.