International Archives of Medicine · 2012 · 642 citations · 17 references
Veterinary MedicineHealth SciencesImmunologyEpidemiologic MethodsEpidemiologyInflammationCardiovascular DiseaseChronic DiseaseChronic Disease BurdenChronic InflammationNeutrophil BiologyCross-sectional EpidemiologyMultinomial RegressionNeutrophil-mediated InflammationNeutrophil-to-lymphocyte RatioSystemic Inflammation Markers
BACKGROUND: Preliminary evidence has suggested the role of inflammation in development and prognosis of cardiovascular diseases and cancers. Most of the prognostic studies failed to account for the effects of co-morbid conditions as these might have raised the systemic inflammation. We used neutrophil lymphocyte ratio (NLR) as a measure of systemic inflammation and investigated its association with prevalent chronic conditions. METHODS: Present study is a cross sectional study conducted on population of Karachi, Pakistan. A detailed questionnaire about the demographic details of all subjects was filled and an informed consent obtained for blood sampling. Multinomial regression analyses were carried out to investigate the relationship between NLR and prevalent chronic conditions. RESULTS: 1070 apparently healthy individuals participated in the study. Proportion of individuals with hypertension was higher in middle and highest tertile of NLR as compared to the lowest tertile (18.2% & 16.1% compared to 11.8%). Individuals with hypertension were 43% (RRR = 1.43, 95% CI 0.94-2.20) and 66% (RRR = 1.69, 95% CI 1.09-2.54) more likely to be in the middle and highest tertile of NLR respectively compared to the baseline group. Similarly, individuals with diabetes mellitus were 53% (RRR = 1.53, 95% CI 0.93-2.51) and 65% (RRR = 1.65, 95% CI 1.01-2.71) more likely to be in the middle or highest tertile of NLR as compared to the baseline NLR group. CONCLUSIONS: Systemic inflammation measured by NLR has a significant association with prevalent chronic conditions. Future research is needed to investigate this relationship with longitudinal data to establish the temporal association between these variables.
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