Universidad Peruana Cayetano Heredia

Prevalence and Burden of PRISm in Population Cohorts From Three LMIC Settings

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dc.contributor.author Grealis, K
dc.contributor.author Siddharthan, T
dc.contributor.author Pollard, S
dc.contributor.author Hossain, D
dc.contributor.author Alupo, P
dc.contributor.author Chandyo, R
dc.contributor.author Cárdenas García-Santillán, María Kathia
dc.contributor.author Flores-Flores, O
dc.contributor.author Kirenga, B
dc.contributor.author Miranda, J. Jaime
dc.contributor.author Sharma, A
dc.contributor.author Shrestha, L
dc.contributor.author Checkley, W
dc.contributor.author Hurst, J
dc.date.accessioned 2023-10-12T15:30:10Z
dc.date.available 2023-10-12T15:30:10Z
dc.date.issued 2023
dc.identifier.uri https://hdl.handle.net/20.500.12866/14305
dc.description.abstract Introduction: Over 90% of morbidity and mortality from chronic respiratory disease occurs in low-and middle-income countries (LMICs), with significant economic impact. Preserved ratio impairedspirometry (PRISm) is a prevalent lung function abnormality associated with increased mortality. Inparent research we conducted a multi-country, population-based study to assess the discriminativeaccuracy of simple questionnaires and peak expiratory flow (PEF) to screen for COPD in threediverse LMIC settings. Here we report the prevalence and burden of PRISm from the samepopulations. Methods: We recruited a random, age-and sex-stratified sample of the population inurban Bhaktapur, Nepal; Lima, Peru; and rural Nakaseke, Uganda. Quality-assured post-bronchodilator spirometry was performed to ATS standards and PRISm was defined as forcedexpiratory volume in 1 second (FEV1) <80% predicted with FEV1/FVC ratio ≥70%. We used chi-squared to assess relationship between demographic, biometric, and comorbidity factors withPRISm. Logistic mixed-effects models were used to assess the odds ratios (OR) with 95%confidence intervals (CI). All analysis was performed using R (version 4.2.1).Results: BetweenJanuary 2018 and March 2020, 10,709 adults aged ≥40 years, consented to participate in the studyand were included in the primary analysis. The mean age was 56.3 years (SD ±11.7) with equaldistribution of gender across sites. The weighted prevalence of PRISm was 9.1% in Nepal, 2.5% inPeru and 15.8% in Uganda (Χ2p<0.001). The overall prevalence of PRISM was 9.2%. Age, sex,BMI, education level, current exposure to biomasses, history of smoking, and being a currentsmoker were significant predictors of PRISm (p≤0.006, inclusively). Modeling used predictors: site,current exposure to biomasses, age, gender, current smoking status, attained education, BMI,history of heart disease, history of tuberculosis, and history of diabetes. Mean St. George’sRespiratory Questionnaire (SGRQ) total score for PRISm was 8.73(SD ±12.2), compared to 6.44(SD ±9.7) for those with normal lung function (non-PRISM, non-obstructed) and was significant(p<0.001). A number of risk factors for PRISm were identified including, female gender, heartdisease and tuberculosis, while current smoking status was not a significant predictor (p=0.154)(Figure 1). The average participant in Uganda had 3.45 times the odds of PRISm than otherparticipants in the sample.Conclusions: The prevalence of PRISm is heterogeneous across settingsand associated with a number of risk factors common to LMIC settings, most strongly currentbiomass exposure. PRISm is additionally associated with worse respiratory outcomes compared tohealthy participants en_US
dc.language.iso eng
dc.publisher American Thoracic Society
dc.relation.ispartofseries American Journal of Respiratory and Critical Care Medicine
dc.rights info:eu-repo/semantics/restrictedAccess
dc.rights.uri https://creativecommons.org/licenses/by-nc-nd/4.0/deed.es
dc.subject Prevalence en_US
dc.subject Burden en_US
dc.subject PRISm en_US
dc.subject Population Cohorts en_US
dc.subject LMIC Settings en_US
dc.subject.mesh Prevalencia
dc.subject.mesh Estudios de Cohortes
dc.subject.mesh Países en Desarrollo
dc.title Prevalence and Burden of PRISm in Population Cohorts From Three LMIC Settings en_US
dc.type info:eu-repo/semantics/article
dc.identifier.doi https://doi.org/10.1164/ajrccm-conference.2023.207.1_MeetingAbstracts.A4510
dc.relation.issn 1535-4970


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