| 1. |
- Omokungbe, Opeyemi R., et al.
(author)
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Analysis of the variability of airborne particulate matter with prevailing meteorological conditions across a semi -urban environment using a network of low-cost air quality sensors
- 2020
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In: Heliyon. - : Elsevier BV. - 2405-8440. ; 6:6
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Journal article (peer-reviewed)abstract
- The concentrations of fine and coarse fractions of airborne particulate matter (PM) and meteorological variables (wind speed, wind direction, temperature and relative humidity) were measured at six selected locations in Ile Ife, a prominent university town in Nigeria using a network of low-cost air quality (AQ) sensor units. The objective of the deployment was to collate baseline air quality data and assess the impact of prevailing meteorological con- ditions on PM concentrations in selected residential communities downwind of an iron smelting facility. The raw data obtained from OPC-N2 of the AQ sensor units was corrected using the RH correction factor developed based k -Kohler theory. This PM (corrected) fast time resolution data (20 s) from the AQ sensor units were used to create daily averages. The overall mean mass concentrations for PM2.5 and PM10 were 213.3, 44.1, 23.8, 27.7, 20.2 and 41.5 mu g/m(3) and; 439.9, 107.1, 55.0, 72.4, 45.5 and 112.0 mu g/m(3) for Fasina (Iron -Steel Smelting Factory, ISSF), Modomo, Eleweran, Fire Service, O.A.U. staff quarters and Obafemi Awolowo University Teaching and Research Farm (OAUTRF), respectively. PM concentration and wind speed showed a negative exponential distribution curve with the lowest exponential fi t coef ficient of determination (R-2) values of 0.08 for PM2.5 and 0.03 for PM10 during nighttime periods at Eleweran and Fire service sites, respectively. The relationship between PM concen- tration and temperature gave a decay curve indicating that higher PM concentrations were observed at lower temperatures. The exponential distribution curve for the relationship between PM concentration and relative humidity (RH) showed that PM concentrations do not vary for RH 80 % while stronger relationship was noticed with higher PM concentration for RH 80 % for both day and nighttime. The performances of the MLR model were slightly poor and as such not too reliable for predicting the concentration but useful for improving predictive model accuracy when other variables contributing to the variability of PM is considered. The study concluded that the anthropogenic and industrial activities at the smelting factory contribute signi ficantly to the elevated PM mass concentration measured at the study locations.
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| 2. |
- Ayoola, A, et al.
(author)
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Overweight and obesity in south central Uganda: A population-based study
- 2022
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In: PLOS global public health. - : Public Library of Science (PLoS). - 2767-3375. ; 2:11, s. e0001051-
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Journal article (peer-reviewed)abstract
- Obesity is a rapidly growing global health challenge, but there are few population-level studies from non-urban settings in sub-Saharan Africa. We evaluated the prevalence of overweight (body mass index (BMI)>25 kg/m2), obesity (BMI>30 kg/m2), and associated factors using data from May 2018 to November 2020 from the Rakai Community Cohort Study, a population-based cohort of residents aged 15 to 49 living in forty-one fishing, trading, and agrarian communities in South Central Uganda. Modified Poisson regression was used to estimate adjusted prevalence risk ratios (PRR) and 95% confidence intervals (CI) in 18,079 participants. The overall mean BMI was 22.9 kg/m2. Mean BMI was 21.5 kg/m2 and 24.1 kg/m2 for males and females, respectively. The prevalence of overweight and obesity were 22.8% and 6.2%, respectively. Females had a higher probability of overweight/obesity (PRR: 4.11, CI: 2.98–5.68) than males. For female participants, increasing age, higher socioeconomic status, residing in a trading or fishing community (PRR: 1.25, CI 1.16–1.35 and PRR: 1.17, CI 1.10–1.25, respectively), being currently or previously married (PRR: 1.22, CI 1.07–1.40 and PRR: 1.16, CI 1.01–1.34, respectively), working in a bar/restaurant (PRR: 1.29, CI 1.17–1.45), trading/shopkeeping (PRR: 1.38, CI 1.29–1.48), and reporting alcohol use in the last year (PRR: 1.21, CI 1.10–1.33) were risk factors for overweight/obese. For male participants, increasing age, higher socioeconomic status, being currently married (PRR: 1.94, CI 1.50–2.50), residing in a fishing community (PRR: 1.68, CI 1.40–2.02), working in a bar/restaurant (PRR: 2.20, CI 1.10–4.40), trading/shopkeeping (PRR: 1.75, CI 1.45–2.11), or fishing (PRR: 1.32, CI 1.03–1.69) increased the probability of overweight/obesity. Non-Muslim participants, male smokers, and HIV-positive females had a lower probability of overweight/obese. The prevalence of overweight/obesity in non-urban Ugandans is substantial. Targeted interventions to high-risk subgroups in this population are needed.
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