Evidence map›Paper›PMID 31814921›Full record

ReviewNutrition research and practice2019

Research trends in obesity & obesogenic environments in Korea.

Myoungsook Lee

Abstract readReview
In one paragraph

Review in Nutrition research and practice, 2019. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 6 papers.

0numbers the graph read from it
0cells of the map it votes in
6citing papers in PubMed
–field-weighted citation impact
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

6 citing papers in PubMed.

  1. Review
  2. Article
  3. Article
  4. Anti-Obesity Effects ofAntioxidants (Basel, Switzerland) · 2022
    Article
  5. Article
  6. 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

1 author.

Myoungsook LeeDepartment of Food and Nutrition & Research Institute of Obesity Sciences, Sungshin Women's University, 76ga-55, Dobong-ro, Gangbuk-gu, Soeul 01133, Republic of Korea.ORCID https://orcid.org/0000-0003-1344-6979

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

BACKGROUND/

objectivesGlobally, it has been projected that there will be 2 billion overweight and 1 billion obese individuals by 2030. In Korea, the prevalence of adult obesity (BMI>25) increased from 29.7% in 2009 to 32.4% in 2015. Moreover, childhood obesity, which leads to adulthood obesity, has increasingly become a social problem. The purpose of this review is to summarize the scientific basis for the development of effective models and policies aimed at preventing obesity over a lifetime based on research modeling obesogenic environments. MATERIALS/

methodsThe review focuses on the characteristics of obesity prevalence and trends in 3P analysis (papers, patents, and products) as well as government-funded projects in Korean obesity obesogenic environments over the last 10 years. RESULTS AND DISCUSSION: As a result of the 3P analysis, studies on obesity risk factors were frequently carried out, according to two data bases RISS (4.9%) and PubMed (24.7%). Since there were only 17% patents related to the mechanism of preventing obesity in 7,951 Korean patents related to obesity, new paradigms of technologies to dominate the global obesity markets are needed. After government-funded projects were analyzed, communication and cooperation in multi-governmental departments were suggested to elucidate the characteristics of Korean obesity. Government should also produce short- and long-term road maps to develop a practical, successful outcome. Although the rate of obesity in Korea is currently lower than in other developed countries according to WHO criteria, without adequate governmental intervention, obesity rates will approach those of the top countries with high incidence rates of obesity within the next 10 years.

Indexed as

3P analysisobesity research modelingobesogenic environmentSystematic review

Identifiers

PMID31814921
PMCPMC6883237

What OpenQuestion holds

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Registered trials

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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.