No abstract

ObjectivesTo determine the frequency and predictors of sleep abnormalities among patients with knee osteoarthritis (OA) in Nigeria.Material and methodsA multi-centre, hospital-based, cross-sectional study, involving 250 knee OA patients. Consenting patients 18 years and above, who satisfied the American College of Rheumatology (ACR) criteria for knee OA were recruited from five Nigerian tertiary centres over 3 months. An interviewer-administered questionnaire was used to collect demographic and relevant clinical information. The Pittsburgh Sleep Quality Index (PSQI) was used to assess sleep quality with scores ≥ 5 indicating poor sleep. Other variables assessed were pain, depression, functional class and family functioning. Data were summarized using appropriate measures of central tendency and dispersion. Multiple logistic regression analysis was done to identify predictors of poor sleep. Analysis was done using SPSS version 21.0 with p < 0.05 considered significant. Study approval was obtained from the ethical committees of each of the study sites.ResultsParticipants included 209 females (83.6%) with mean age 59.9 ±10.6 years. One hundred and forty-one participants (56.4%) had PSQI scores ≥ 5 (poor sleep). This was significantly associated with depression (p < 0.001), level of education (p = 0.001), higher pain scores (p < 0.001), body mass index (p = 0.040), medial knee OA (p = 0.032) and patello-femoral OA (p = 0.002). Higher level of education, worse depression scores and higher WOMAC pain scores were the best predictors of poor sleep quality.ConclusionSleep quality was poor in over half of our knee OA patients and best predicted by depression, pain and level of education. Regular sleep quality assessment for knee OA patients is recommended.

No abstract

Biomass use in small unit combustion systems such as for space heating or cooking could lead to ineffective mixing and potential problems arising from emissions of gaseous and particulate pollutants. We therefore conducted a study to measure pollution levels in public kitchens using biomass fuel for cooking and to ascertain their air quality indices. Markers of indoor air quality such as CO, SO2, H2S, PM2.5 and PM10 were measured in eleven (11) public kitchens of selected secondary schools over a period of four months by a set of active sampling devices. It is revealed that the mean average of CO, SO2, H2S, PM2.5 and PM10 sampled in the indoor microenvironments of the selected kitchens are 46.29 ppm, 0.36 ppm, 0.28 ppm, 74 µg/m3 and 138 µg/m3, respectively. The AQI assessed for CO for the kitchens was 36.36% very hazardous, 54.54 % hazardous and 9.09% very unhealthy while 63.64% and 36.36 % of very unhealthy and unhealthy categories, respectively for SO2. This shows that the indoor air pollution levels in selected kitchen are elevated and results in potential negative health consequences.