Relationship between the latent profiles of health information-seeking behaviour and glycated haemoglobin levels in patients with type 2 diabetes: a cross-sectional survey in rural areas of China

Objective The purpose of this study was to analyse the heterogeneity of health information-seeking behaviour (HISB) among patients with type 2 diabetes (T2D) in rural areas based on latent profiles and to explore the relationship between various behaviours and glycaemic control rates and the factors...

Full description

Saved in:
Bibliographic Details
Main Authors: Xin Zhang, Lin Zeng, Yan-Ping Zhang, Jing-Feng Chen, Chao-Qun Bai, Xiao-Xue Lei, Gui-Fen Fu
Format: Article
Language:English
Published: BMJ Publishing Group 2025-01-01
Series:BMJ Open
Online Access:https://bmjopen.bmj.com/content/15/1/e088891.full
Tags: Add Tag
No Tags, Be the first to tag this record!
_version_ 1832591050906009600
author Xin Zhang
Lin Zeng
Yan-Ping Zhang
Jing-Feng Chen
Chao-Qun Bai
Xiao-Xue Lei
Gui-Fen Fu
author_facet Xin Zhang
Lin Zeng
Yan-Ping Zhang
Jing-Feng Chen
Chao-Qun Bai
Xiao-Xue Lei
Gui-Fen Fu
author_sort Xin Zhang
collection DOAJ
description Objective The purpose of this study was to analyse the heterogeneity of health information-seeking behaviour (HISB) among patients with type 2 diabetes (T2D) in rural areas based on latent profiles and to explore the relationship between various behaviours and glycaemic control rates and the factors influencing glycaemic control rates.Methods Between January and July 2022, a stratified cluster random sampling method was used to sample T2D patients in the rural Guangxi Zhuang Autonomous Region. Participants completed a general information questionnaire and a HISB scale. Latent profile analysis (LPA) identified behaviour categories, and χ2 tests examined differences in glycaemic control rates across these categories. Multivariate logistic regression was used to analyse factors influencing glycaemic control. The glycaemic control rate was defined as the proportion of individuals whose HbA1c levels are less than 7.0%, indicating good control, in relation to the total number of individuals assessed.Results A total of 2178 valid questionnaires were received in this study, and respondents were divided into three categories according to the LPA of their HISB: negative (18.3%), occlusive (46.8%) and inefficient (34.9%). The glycaemic control rate of patients with T2D in rural areas was 22.6% (494/2178 cases). Multivariate logistic regression analysis revealed that the category of patients’ HISB profile, age, course of disease and educational level were the factors influencing the glycaemic control rate (all p<0.05).Conclusion Patients with T2D in rural areas had poor glycaemic control and inadequate HISB. Three latent profile categories were identified that reflect the HISB of this group. We recommend that clinical medical professionals develop personalised health management education based on the various latent profile characteristics of patients to promote HISB and thereby achieve optimal glycaemic control.
format Article
id doaj-art-aab8428bebde413c9a3c36cf461c91b5
institution Kabale University
issn 2044-6055
language English
publishDate 2025-01-01
publisher BMJ Publishing Group
record_format Article
series BMJ Open
spelling doaj-art-aab8428bebde413c9a3c36cf461c91b52025-01-23T05:05:15ZengBMJ Publishing GroupBMJ Open2044-60552025-01-0115110.1136/bmjopen-2024-088891Relationship between the latent profiles of health information-seeking behaviour and glycated haemoglobin levels in patients with type 2 diabetes: a cross-sectional survey in rural areas of ChinaXin Zhang0Lin Zeng1Yan-Ping Zhang2Jing-Feng Chen3Chao-Qun Bai4Xiao-Xue Lei5Gui-Fen Fu61 Department of Geriatric Endocrinology and Metabolism, Guangxi Academy of Medical Sciences and the People’s Hospital of Guangxi Zhuang Autonomous Region, Nanning, Guangxi, China1 Department of Geriatric Endocrinology and Metabolism, Guangxi Academy of Medical Sciences and the People’s Hospital of Guangxi Zhuang Autonomous Region, Nanning, Guangxi, China2 Department of Geriatric Endocrinology and Metabolism, People`s Hospital of Guangxi Zhuang Autonomous Region, Nanning, Guangxi, China3 People`s Hospital of Guangxi Zhuang Autonomous Region, Nanning, Guangxi, China3 People`s Hospital of Guangxi Zhuang Autonomous Region, Nanning, Guangxi, China3 People`s Hospital of Guangxi Zhuang Autonomous Region, Nanning, Guangxi, China4 Department of Nursing, People`s Hospital of Guangxi Zhuang Autonomous Region, Nanning, Guangxi, ChinaObjective The purpose of this study was to analyse the heterogeneity of health information-seeking behaviour (HISB) among patients with type 2 diabetes (T2D) in rural areas based on latent profiles and to explore the relationship between various behaviours and glycaemic control rates and the factors influencing glycaemic control rates.Methods Between January and July 2022, a stratified cluster random sampling method was used to sample T2D patients in the rural Guangxi Zhuang Autonomous Region. Participants completed a general information questionnaire and a HISB scale. Latent profile analysis (LPA) identified behaviour categories, and χ2 tests examined differences in glycaemic control rates across these categories. Multivariate logistic regression was used to analyse factors influencing glycaemic control. The glycaemic control rate was defined as the proportion of individuals whose HbA1c levels are less than 7.0%, indicating good control, in relation to the total number of individuals assessed.Results A total of 2178 valid questionnaires were received in this study, and respondents were divided into three categories according to the LPA of their HISB: negative (18.3%), occlusive (46.8%) and inefficient (34.9%). The glycaemic control rate of patients with T2D in rural areas was 22.6% (494/2178 cases). Multivariate logistic regression analysis revealed that the category of patients’ HISB profile, age, course of disease and educational level were the factors influencing the glycaemic control rate (all p<0.05).Conclusion Patients with T2D in rural areas had poor glycaemic control and inadequate HISB. Three latent profile categories were identified that reflect the HISB of this group. We recommend that clinical medical professionals develop personalised health management education based on the various latent profile characteristics of patients to promote HISB and thereby achieve optimal glycaemic control.https://bmjopen.bmj.com/content/15/1/e088891.full
spellingShingle Xin Zhang
Lin Zeng
Yan-Ping Zhang
Jing-Feng Chen
Chao-Qun Bai
Xiao-Xue Lei
Gui-Fen Fu
Relationship between the latent profiles of health information-seeking behaviour and glycated haemoglobin levels in patients with type 2 diabetes: a cross-sectional survey in rural areas of China
BMJ Open
title Relationship between the latent profiles of health information-seeking behaviour and glycated haemoglobin levels in patients with type 2 diabetes: a cross-sectional survey in rural areas of China
title_full Relationship between the latent profiles of health information-seeking behaviour and glycated haemoglobin levels in patients with type 2 diabetes: a cross-sectional survey in rural areas of China
title_fullStr Relationship between the latent profiles of health information-seeking behaviour and glycated haemoglobin levels in patients with type 2 diabetes: a cross-sectional survey in rural areas of China
title_full_unstemmed Relationship between the latent profiles of health information-seeking behaviour and glycated haemoglobin levels in patients with type 2 diabetes: a cross-sectional survey in rural areas of China
title_short Relationship between the latent profiles of health information-seeking behaviour and glycated haemoglobin levels in patients with type 2 diabetes: a cross-sectional survey in rural areas of China
title_sort relationship between the latent profiles of health information seeking behaviour and glycated haemoglobin levels in patients with type 2 diabetes a cross sectional survey in rural areas of china
url https://bmjopen.bmj.com/content/15/1/e088891.full
work_keys_str_mv AT xinzhang relationshipbetweenthelatentprofilesofhealthinformationseekingbehaviourandglycatedhaemoglobinlevelsinpatientswithtype2diabetesacrosssectionalsurveyinruralareasofchina
AT linzeng relationshipbetweenthelatentprofilesofhealthinformationseekingbehaviourandglycatedhaemoglobinlevelsinpatientswithtype2diabetesacrosssectionalsurveyinruralareasofchina
AT yanpingzhang relationshipbetweenthelatentprofilesofhealthinformationseekingbehaviourandglycatedhaemoglobinlevelsinpatientswithtype2diabetesacrosssectionalsurveyinruralareasofchina
AT jingfengchen relationshipbetweenthelatentprofilesofhealthinformationseekingbehaviourandglycatedhaemoglobinlevelsinpatientswithtype2diabetesacrosssectionalsurveyinruralareasofchina
AT chaoqunbai relationshipbetweenthelatentprofilesofhealthinformationseekingbehaviourandglycatedhaemoglobinlevelsinpatientswithtype2diabetesacrosssectionalsurveyinruralareasofchina
AT xiaoxuelei relationshipbetweenthelatentprofilesofhealthinformationseekingbehaviourandglycatedhaemoglobinlevelsinpatientswithtype2diabetesacrosssectionalsurveyinruralareasofchina
AT guifenfu relationshipbetweenthelatentprofilesofhealthinformationseekingbehaviourandglycatedhaemoglobinlevelsinpatientswithtype2diabetesacrosssectionalsurveyinruralareasofchina