Evidence map›Paper›PMID 25143754›Full record

ArticleClinical epidemiology2014

Chiang Mai University Health Worker Study aiming toward a better understanding of noncommunicable disease development in Thailand: methods and description of study population.

Chaisiri Angkurawaranon, Anawat Wisetborisut, Wichuda Jiraporncharoen, Surinporn Likhitsathian, Ronnaphob Uaphanthasath, Patama Gomutbutra, Surin Jiraniramai, Chawin Lerssrimonkol, Apinun Aramrattanna, Pat Doyle and 1 more

Open access · goldAbstract read
In one paragraph

Article in Clinical epidemiology, 2014. 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
3.5field-weighted citation impact, top 7% 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

6 citing papers in PubMed, 11 citations in OpenAlex.

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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

11 authors at 2 institutions in 2 countries.

Chaisiri AngkurawaranonDepartment of Non-Communicable Disease Epidemiology, Faculty of Epidemiology and Population Health, London School of Hygiene and Tropical Medicine, London, UK ; Department of Family Medicine, Faculty of Medicine, Chiang Mai University, Chiang Mai, Thailand.
Anawat WisetborisutDepartment of Family Medicine, Faculty of Medicine, Chiang Mai University, Chiang Mai, Thailand.
Wichuda JiraporncharoenDepartment of Family Medicine, Faculty of Medicine, Chiang Mai University, Chiang Mai, Thailand.
Surinporn LikhitsathianDepartment of Psychiatry, Faculty of Medicine, Chiang Mai University, Chiang Mai, Thailand.
Ronnaphob UaphanthasathDepartment of Family Medicine, Faculty of Medicine, Chiang Mai University, Chiang Mai, Thailand.
Patama GomutbutraDepartment of Family Medicine, Faculty of Medicine, Chiang Mai University, Chiang Mai, Thailand.
Surin JiraniramaiDepartment of Family Medicine, Faculty of Medicine, Chiang Mai University, Chiang Mai, Thailand.
Chawin LerssrimonkolDepartment of Family Medicine, Faculty of Medicine, Chiang Mai University, Chiang Mai, Thailand.
Apinun AramrattannaDepartment of Family Medicine, Faculty of Medicine, Chiang Mai University, Chiang Mai, Thailand.
Pat DoyleDepartment of Non-Communicable Disease Epidemiology, Faculty of Epidemiology and Population Health, London School of Hygiene and Tropical Medicine, London, UK.
Dorothea NitschDepartment of Non-Communicable Disease Epidemiology, Faculty of Epidemiology and Population Health, London School of Hygiene and Tropical Medicine, London, UK.
Chiang Mai University · THLondon School of Hygiene & Tropical Medicine · GB

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

backgroundUrbanization is considered to be one of the key drivers of noncommunicable diseases (NCDs) in Thailand and other developing countries. These influences, in turn, may affect an individual's behavior and risk of developing NCDs. The Chiang Mai University (CMU) Health Worker Study aims to provide evidence for a better understanding of the development of NCDs and ultimately to apply the evidence toward better prevention, risk modification, and improvement of clinical care for patients with NCDs and NCD-related conditions.

methodsA cross-sectional survey of health care workers from CMU Hospital was conducted between January 2013 and June 2013. Questionnaires, interviews, and physical and laboratory examinations were used to assess urban exposure, occupational shift work, risk factors for NCDs, self-reported NCDs, and other NCD-related health conditions.

resultsFrom 5,364 eligible workers, 3,204 participated (59.7%). About 11.1% of the participants had high blood pressure (systolic blood pressure ≥140 mmHg or diastolic blood pressure ≥90 mmHg) and almost 30% were considered to be obese (body mass index ≥25 kg/m(2)). A total of 2.3% had a high fasting blood glucose level (≥126 mg/dL), and the most common abnormal lipid profile was high low-density lipoprotein (≥160 mg/dL), which was found in 19.2% of participants. DISCUSSION: The study of health workers offers three potential advantages. The first is that the study of migrants was possible. Socioenvironmental influence on NCD risk factors can be explored, as changes in environmental exposures can be documented. Second, it allows the investigators to control for access to care. Access to care is potentially a key confounder toward understanding the development of NCDs. Lastly, a study of health personnel allows easy access to laboratory investigations and potential for long-term follow-up. This enables ascertainment of a number of clinical outcomes and provides potential for future studies focusing on therapeutic and prognostic issues related to NCDs.

Indexed as

noncommunicable diseaserisk factorsThailandurbanization

Identifiers

PMID25143754
PMCPMC4137916
OpenAlexW2147588974

What OpenQuestion holds

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LicenceCC BY-NC
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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.