Consultation behaviors and factors influencing hesitation to seek medical care among local dengue patients in Guangzhou, China: a retrospective analysis
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| Publicado en: | BMC Public Health vol. 25 (2025), p. 1-12 |
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Springer Nature B.V.
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| 001 | 3247124314 | ||
| 003 | UK-CbPIL | ||
| 022 | |a 1471-2458 | ||
| 024 | 7 | |a 10.1186/s12889-025-24271-1 |2 doi | |
| 035 | |a 3247124314 | ||
| 045 | 2 | |b d20250101 |b d20251231 | |
| 084 | |a 58491 |2 nlm | ||
| 100 | 1 | |a Luo, Haipeng | |
| 245 | 1 | |a Consultation behaviors and factors influencing hesitation to seek medical care among local dengue patients in Guangzhou, China: a retrospective analysis | |
| 260 | |b Springer Nature B.V. |c 2025 | ||
| 513 | |a Journal Article | ||
| 520 | 3 | |a Section BackgroundDengue fever remains a significant public health challenge in Guangzhou, China, where healthcare-seeking behavior plays a critical role in shaping disease outcomes. This study investigates patterns of consultation delays and their determinants among locally acquired dengue cases from 2015 to 2024, aiming to inform targeted public health interventions.AbstractSection MethodsSurveillance data on locally acquired dengue fever cases in Guangzhou were extracted from Chinese National Notifiable Infectious Disease Reporting Information System for analysis. Categorical variables were summarized as frequencies and percentages (N, %), while continuous variables were presented as medians with interquartile ranges (IQR). Chi-square tests were used to examine differences in symptom onset and consultation timing across groups with varying demographic characteristics, and non-parametric Wilcoxon rank-sum tests assessed variations in consultation hesitation time (defined as the interval from symptom onset to medical consultation). To identify determinants of delayed care-seeking, a modified Poisson regression model with robust error variance adjustment was employed, incorporating key demographic characteristics as predictors.AbstractSection ResultsFrom 2015 to 2024, Guangzhou recorded 8,533 locally acquired dengue fever cases, with men accounting for 52.5% of cases (men-to-women ratio = 1.12:1). The overall median healthcare-seeking delay was 4 days (IQR 2–6). Notable spatiotemporal variation emerged, as residents of non-central areas presented earlier than those in urban centers (median 3 vs. 4 days), and while the median delay remained unchanged during high-incidence months, the interquartile range (IQR) narrowed from 3 to 6 days in low-incidence months to 2–6 days in high-incidence months. This contraction in IQR suggests more proactive healthcare-seeking behavior during epidemic periods (Z=-4.321, P < 0.001). Multivariable Poisson regression with robust standard errors confirmed significantly longer delays during low-incidence periods (IRR = 1.122, 95%CI:1.052–1.196). Weekend consultation rates decreased significantly during high-incidence months across most subgroups, though no significant weekday-weekend differences were observed among individuals in high-exposure occupations or during low-incidence periods (P > 0.05). Age-stratified analysis demonstrated significantly increased delay risk across all younger age groups compared to patients ≥ 65 years, with the greatest risk elevation in children and adolescents aged 0–18 years (IRR = 1.538, 95%CI:1.436–1.648), followed by adults aged 41–65 years (IRR = 1.093, 95%CI:1.053–1.134) and 19–40 years (IRR = 1.067, 95%CI:1.027–1.108), revealing a bimodal delay pattern. Distinct occupational gradients were equally apparent in the analysis. Workers in low exposure-risk occupations experienced the longest median delays (median 5 days; IQR 4–7) and highest adjusted risk (IRR = 1.429, 95%CI:1.341–1.523) compared with high-risk occupations, while moderate-risk occupations showed both the shortest delays (median 2 days, IQR 1–3) and significantly reduced risk (IRR = 0.652, 95%CI = 0.609–0.699). Similarly, special populations demonstrated reduced risk (IRR = 0.658, 95%CI:0.611–0.708).AbstractSection ConclusionsThis study highlights systematic disparities in dengue fever healthcare-seeking behavior, driven by occupational exposure risk, seasonal transmission dynamics, and demographic factors. To reduce delays, urgent implementation of targeted interventions is required. Interventions should incorporate health education initiatives in workplaces for high exposure risk occupational groups, while also focusing on low exposure risk occupational groups and urban residents experiencing delays in seeking care. Additionally, expanding weekend healthcare accessibility and developing age-specific education programs are essential to enhance epidemic response efficiency and reduce disease burden. | |
| 651 | 4 | |a Guangdong China | |
| 651 | 4 | |a China | |
| 651 | 4 | |a Guangzhou China | |
| 653 | |a Health promotion | ||
| 653 | |a Adolescents | ||
| 653 | |a Demographics | ||
| 653 | |a Mortality | ||
| 653 | |a Infectious diseases | ||
| 653 | |a Health care | ||
| 653 | |a Patients | ||
| 653 | |a Viral diseases | ||
| 653 | |a Occupations | ||
| 653 | |a Epidemics | ||
| 653 | |a Statistical analysis | ||
| 653 | |a Dengue fever | ||
| 653 | |a Men | ||
| 653 | |a Delay | ||
| 653 | |a Education | ||
| 653 | |a Exposure | ||
| 653 | |a Public health | ||
| 653 | |a Vector-borne diseases | ||
| 653 | |a Poisson density functions | ||
| 653 | |a Disease control | ||
| 653 | |a Population | ||
| 653 | |a Risk management | ||
| 653 | |a Data acquisition | ||
| 653 | |a Regression models | ||
| 653 | |a Community health care | ||
| 653 | |a Age | ||
| 653 | |a Health services | ||
| 653 | |a Ethics | ||
| 653 | |a Urban areas | ||
| 653 | |a Robustness | ||
| 653 | |a Urban environments | ||
| 653 | |a Early intervention | ||
| 653 | |a Workplaces | ||
| 653 | |a Subgroups | ||
| 653 | |a Occupational health | ||
| 653 | |a Demography | ||
| 653 | |a Mosquitoes | ||
| 653 | |a Occupational exposure | ||
| 653 | |a Social | ||
| 700 | 1 | |a Liu, Wenhui | |
| 700 | 1 | |a Luo, Lei | |
| 700 | 1 | |a Zhang, Zhoubin | |
| 773 | 0 | |t BMC Public Health |g vol. 25 (2025), p. 1-12 | |
| 786 | 0 | |d ProQuest |t Health & Medical Collection | |
| 856 | 4 | 1 | |3 Citation/Abstract |u https://www.proquest.com/docview/3247124314/abstract/embedded/7BTGNMKEMPT1V9Z2?source=fedsrch |
| 856 | 4 | 0 | |3 Full Text |u https://www.proquest.com/docview/3247124314/fulltext/embedded/7BTGNMKEMPT1V9Z2?source=fedsrch |
| 856 | 4 | 0 | |3 Full Text - PDF |u https://www.proquest.com/docview/3247124314/fulltextPDF/embedded/7BTGNMKEMPT1V9Z2?source=fedsrch |