Evidence map›Paper›PMID 30753195›Full record

ArticlePloS one2019

Assessment of factors affecting diabetes management in the City Changing Diabetes (CCD) study in Tianjin.

Jiageng Chen, Xiyue Jing, Xiaoqian Liu, Anna-Mari Volkmann, Yunfeng Chen, Yuanyuan Liu, Dandan Li, Duolan Han, Yuting Guo, Fei Gao and 8 more

Abstract read
In one paragraph

Article in PloS one, 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. Article
  2. Review
  3. Review
  4. Article
  5. Review
  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

18 authors.

Jiageng ChenSchool of Public Health, Tianjin Medical University, Tianjin, China.
Xiyue JingSchool of Public Health, Tianjin Medical University, Tianjin, China.
Xiaoqian LiuSchool of Public Health, Tianjin Medical University, Tianjin, China.
Anna-Mari VolkmannUniversity College London, London, United Kingdom.
Yunfeng ChenSchool of Public Health, Tianjin Medical University, Tianjin, China.
Yuanyuan LiuSchool of Public Health, Tianjin Medical University, Tianjin, China.
Dandan LiSchool of Public Health, Tianjin Medical University, Tianjin, China.
Duolan HanSchool of Public Health, Tianjin Medical University, Tianjin, China.
Yuting GuoSchool of Public Health, Tianjin Medical University, Tianjin, China.
Fei GaoSchool of Public Health, Tianjin Medical University, Tianjin, China.
Na HanSchool of Public Health, Tianjin Medical University, Tianjin, China.
Xuying WangSchool of Public Health, Tianjin Medical University, Tianjin, China.
Haozuo ZhaoSchool of Public Health, Tianjin Medical University, Tianjin, China.
Xinjun ShiSchool of Public Health, Tianjin Medical University, Tianjin, China.
Yanan DongSchool of Public Health, Tianjin Medical University, Tianjin, China.
Liming ChenMetabolic Diseases Hospital, Tianjin Medical University, Tianjin, China.
David NapierUniversity College London, London, United Kingdom.
Jun MaSchool of Public Health, Tianjin Medical University, Tianjin, China.ORCID 0000-0002-9319-1285

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

objectiveThis study aimed to identify the local levels of vulnerability among patients with Type-II diabetes (T2DM) in Tianjin. The study was aimed at curbing the rise of T2DM in cities.

methods229 participants living with T2DM were purposively sampled from hospitals in Tianjin. Collected data were coded and analysed following well-established thematic analysis principles.

resultsTwelve themes involving 29 factors were associated with diabetes patients' vulnerability: 1. Financial constraints (Low Income, Unemployment, No Medical Insurance/Low ratio reimbursement); 2. Severity of disease (Appearance of symptoms, complications, co-morbidities, high BMI, poor disease control); 3. Health literacy (No/Low/Wrong knowledge of health literacy); 4. Health beliefs (Perceived diabetes indifferently, Passively Acquire Health Knowledge, Distrust of primary health services); 5. Medical environment (Needs not met by Medical Services); 6. Life restrictions (Daily Life, Occupational Restriction); 7. Lifestyle change (Adhering to traditional or unhealthy diet, Lack of exercise, Low-quality sleep); 8. Time poverty (Healthcare-seeking behaviours were limited by work, Healthcare-seeking behaviours were limited by family issues); 9. Mental Condition (Negative emotions towards diabetes, Negative emotions towards life); 10. Levels of Support (Lack of community support, Lack of support from Friends and Family, Lack of Social Support); 11. Social integration (Low Degree of Integration, Belief in Suffering Alone); 12. Experience of transitions (Diet, Dwelling Environment).

conclusionBased on our findings, specific interventions targeting individual patients, family, community and society are needed to improve diabetes control, as well as patients' mental health care and general living conditions.

Indexed as

ChinaCitiesDiabetes Mellitus, Type 2FemaleHealth LiteracyHealth ServicesHealth Services AccessibilityHumansMaleMiddle AgedQualitative ResearchSocial Support

Identifiers

PMID30753195
PMCPMC6372168

What OpenQuestion holds

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LicenceCC BY
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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.