Evidence map›Paper›PMID 38233062›Full record

ArticleBMJ open2024

Protocol for the CHINT study: a cross-sectional observational study of risk factors for cancer and other non-communicable diseases in the Chinese community of Milan.

Alice Avancini, Ivan Baldassari, Giuliana Gargano, Ming Lu, Hao Jing, Hongwei Zhao, Ji Zhang, Sabina Sieri, Francesca Romana Mussa, Vittorio Krogh and 2 more

Open access · goldAbstract read
In one paragraph

Article in BMJ open, 2024. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Not yet cited in PubMed.

0numbers the graph read from it
0cells of the map it votes in
0citing papers in PubMed
–field-weighted citation impact, top 99% 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

0 citing papers in PubMed, 0 citations in OpenAlex.

No citing paper in PubMed yet.

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

12 authors at 7 institutions in 6 countries.

Alice Avancini *Department of Oncology, University of Verona, Verona, Veneto, Italy.
Ivan Baldassari *Department of Epidemiology and Data Science, Fondazione IRCCS Istituto Nazionale dei Tumori, Milano, Italy.
Giuliana GarganoDepartment of Epidemiology and Data Science, Fondazione IRCCS Istituto Nazionale dei Tumori, Milano, Italy.
Ming LuClinical Epidemiology Unit, Shandong University Qilu Hospital, Jinan, China.
Hao JingChina Agricultural University, Beijing, China.
Hongwei ZhaoTexas A&M University, College Station, Texas, USA.
Ji ZhangKarolinska Institute, Stockholm, Sweden.
Sabina SieriDepartment of Epidemiology and Data Science, Fondazione IRCCS Istituto Nazionale dei Tumori, Milano, Italy.
Francesca Romana MussaDepartment of Epidemiology and Data Science, Fondazione IRCCS Istituto Nazionale dei Tumori, Milano, Italy.
Vittorio KroghDepartment of Epidemiology and Data Science, Fondazione IRCCS Istituto Nazionale dei Tumori, Milano, Italy.
Giovanni ApoloneGeneral Directorate for Scientific Research, Fondazione IRCCS Istituto Nazionale dei Tumori, Milano, Lombardia, Italy.
Valeria PalaDepartment of Epidemiology and Data Science, Fondazione IRCCS Istituto Nazionale dei Tumori, Milano, Italy valeria.pala@istitutotumori.mi.it.ORCID 0000-0001-5438-970X
Fondazione IRCCS Istituto Nazionale dei Tumori · ITChina Agricultural University · CNGeneral Commission for Scientific Agricultural Research · SYKarolinska Institutet · SEMitchell Institute · USMRC Epidemiology Unit · GBUniversity of Verona · IT

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

introductionThe Chinese community in Italy is the largest in Europe. The area of Milan hosts the largest Chinese Italian community-about 41 000 people. Since little is known of the health practices of Chinese persons in Italy, we designed the CHINT study (survey of risk factors for cancer and other non-communicable diseases (NCDs) in the Chinese community of Milan) to investigate lifestyle-related risk factors for these diseases in this community. We expect the study to reveal potentially unhealthy lifestyle behaviours that may be addressed in future prevention programmes. METHODS AND ANALYSIS: The CHINT study is a cross-sectional study on a sample of around 600 adults recruited from the Chinese community of Milan and surrounding areas. The non-random sample is clustered by age, sex, occupation and socioeconomic characteristics and is being recruited with the active cooperation of stakeholders within the Chinese community. The study employs face-to-face meetings, text messaging and WeChat. At the first recruitment meeting, participants' physical measurements are taken and a lifestyle questionnaire is administered which enquires about physical activity, the consumption of salt, fruit and vegetables, tobacco and alcohol, and the presence of other risk factors for NCDs. A food frequency questionnaire is in preparation. By analysis of physical data and the results of the two questionnaires, the prevalence and distribution of NCD risk factors, and characteristics associated with these factors, will be identified. Factors associated with recruitment and compliance/retention will be investigated to identify predictors of willingness to participate future intervention studies. ETHICS AND DISSEMINATION: The study has been approved by the ethics committee of the Fondazione IRCCS Istituto Nazionale dei Tumori di Milano, Italy. All participants are required to provide written informed consent. Findings will be disseminated through peer-reviewed scientific publications, conferences and public meetings involving the Chinese community and the lay public.

Indexed as

NeoplasmsNoncommunicable DiseasesAdultChinaCross-Sectional StudiesHumansObservational Studies as TopicRisk FactorsEPIDEMIOLOGIC STUDIESHealth EquityPUBLIC HEALTH

Identifiers

PMID38233062
PMCPMC10806820
OpenAlexW4390955606

What OpenQuestion holds

Textmetadata
LicenceCC BY-NC
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.