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Tuberculosis treatment delays and associated factors within the Zimbabwe national tuberculosis programme

Overview of attention for article published in BMC Public Health, January 2015
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Mentioned by

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1 tweeter

Citations

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47 Dimensions

Readers on

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218 Mendeley
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Title
Tuberculosis treatment delays and associated factors within the Zimbabwe national tuberculosis programme
Published in
BMC Public Health, January 2015
DOI 10.1186/s12889-015-1437-7
Pubmed ID
Authors

Kudakwashe C Takarinda, Anthony D Harries, Barnet Nyathi, Mkhokheli Ngwenya, Tsitsi Mutasa-Apollo, Charles Sandy

Abstract

BackgroundDelayed presentation of pulmonary TB (PTB) patients for treatment from onset of symptoms remains a threat to controlling individual disease progression and TB transmission in the community. Currently, there is insufficient information about treatment delays in Zimbabwe, and we therefore determined the extent of patient and health systems delays and their associated factors in patients with microbiologically confirmed PTB.MethodsA structured questionnaire was administered at 47 randomly selected health facilities in Zimbabwe by trained health workers to all patients aged ¿18 years with microbiologically confirmed PTB who were started on TB treatment and entered in the health facility TB registers between 01 January and 31 March 2013. Multivariate logistic regression was used to calculate adjusted odds ratios (aOR) and 95% confidence intervals (CIs) for associations between patient/health system characteristics and patient delay >30 days or health system delay >4 days.ResultsOf the 383 recruited patients, 211(55%) were male with an overall median age of 34 years (IQR, 28-43). There was a median of 28 days (IQR, 21-63) for patient delays and 2 days (IQR, 1-5) for health system delays with 184 (48%) and 118 (31%) TB patients experiencing health system delays >30 days and health system delays >4 days respectively. Starting TB treatment at rural primary healthcare vs district/mission facilities [aOR 2.70, 95% CI 1.27-5.75, p¿=¿0.01] and taking self-medication [aOR 2.33, 95% CI 1.23-4.43, p¿=¿0.01] were associated with encountering patient delays. Associated with health system delays were accessing treatment from lower level facilities [aOR 2.67, 95% CI 1.18-6.07, p¿=¿0.019], having a Gene Xpert TB diagnosis [aOR 0.21, 95% CI 0.07-0.66, p¿=¿0.008] and >4 health facility visits prior to TB diagnosis [(aOR) 3.34, 95% CI 1.11-10.03, p¿=¿0.045].ConclusionPatient delays were longer and more prevalent, suggesting the need for strategies aimed at promoting timely seeking of appropriate medical consultation among presumptive TB patient. Health system delays were uncommon, suggesting a fairly efficient response to microbiologically confirmed PTB cases. Identified risk factors should be explored further and specific strategies aimed at addressing these factors should be identified in order to lessen patient and health system delays.

Twitter Demographics

The data shown below were collected from the profile of 1 tweeter who shared this research output. Click here to find out more about how the information was compiled.

Mendeley readers

The data shown below were compiled from readership statistics for 218 Mendeley readers of this research output. Click here to see the associated Mendeley record.

Geographical breakdown

Country Count As %
Brazil 2 <1%
United States 1 <1%
Indonesia 1 <1%
Unknown 214 98%

Demographic breakdown

Readers by professional status Count As %
Student > Master 46 21%
Researcher 39 18%
Student > Postgraduate 22 10%
Student > Bachelor 18 8%
Student > Ph. D. Student 14 6%
Other 42 19%
Unknown 37 17%
Readers by discipline Count As %
Medicine and Dentistry 77 35%
Nursing and Health Professions 39 18%
Social Sciences 15 7%
Environmental Science 8 4%
Immunology and Microbiology 8 4%
Other 23 11%
Unknown 48 22%

Attention Score in Context

This research output has an Altmetric Attention Score of 1. This is our high-level measure of the quality and quantity of online attention that it has received. This Attention Score, as well as the ranking and number of research outputs shown below, was calculated when the research output was last mentioned on 02 February 2015.
All research outputs
#2,503,029
of 4,704,502 outputs
Outputs from BMC Public Health
#3,766
of 5,297 outputs
Outputs of similar age
#86,539
of 163,867 outputs
Outputs of similar age from BMC Public Health
#124
of 162 outputs
Altmetric has tracked 4,704,502 research outputs across all sources so far. This one is in the 33rd percentile – i.e., 33% of other outputs scored the same or lower than it.
So far Altmetric has tracked 5,297 research outputs from this source. They typically receive a little more attention than average, with a mean Attention Score of 6.3. This one is in the 19th percentile – i.e., 19% of its peers scored the same or lower than it.
Older research outputs will score higher simply because they've had more time to accumulate mentions. To account for age we can compare this Altmetric Attention Score to the 163,867 tracked outputs that were published within six weeks on either side of this one in any source. This one is in the 34th percentile – i.e., 34% of its contemporaries scored the same or lower than it.
We're also able to compare this research output to 162 others from the same source and published within six weeks on either side of this one. This one is in the 16th percentile – i.e., 16% of its contemporaries scored the same or lower than it.