Exposure to Outdoor Particles (PM2.5) and Associated Child Morbidity and Mortality in Socially Deprived Neighborhoods of Nairobi, Kenya

Egondi, Thaddaeus; Ettarh, Remare; Kyobutungi, Catherine; Ng, Nawi; Rocklöv, Joacim

doi:10.3390/atmos9090351

Cited by 23 publications

(30 citation statements)

References 40 publications

(54 reference statements)

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“…The adverse effects of PM 2.5 on the respiratory-cardiovascular system have been repeatedly confirmed [1][2][3][4][5][6][7][8][9][10][11][12]. Epidemiologic studies that assess exposure risk to different ambient PM 2.5 concentration levels have relied on the U.S. Environmental Protection Agency's (EPA) network of ground-based ambient air pollutant monitors [4,[13][14][15][16].…”

Section: Introductionmentioning

confidence: 99%

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Contribution of Satellite-Derived Aerosol Optical Depth PM2.5 Bayesian Concentration Surfaces to Respiratory-Cardiovascular Chronic Disease Hospitalizations in Baltimore, Maryland

et al. 2020

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The fine particulate matter baseline (PMB), which includes PM 2.5 monitor readings fused with Community Multiscale Air Quality (CMAQ) model predictions, using the Hierarchical Bayesian Model (HBM), is less accurate in rural areas without monitors. To address this issue, an upgraded HBM was used to form four experimental aerosol optical depth (AOD)-PM 2.5 concentration surfaces. A case-crossover design and conditional logistic regression evaluated the contribution of the AOD-PM 2.5 surfaces and PMB to four respiratory-cardiovascular hospital events in all 99 12 km 2 CMAQ grids, and in grids with and without ambient air monitors. For all four health outcomes, only two AOD-PM 2.5 surfaces, one not kriged (PMC) and the other kriged (PMCK), had significantly higher Odds Ratios (ORs) on lag days 0, 1, and 01 than PMB in all grids, and in grids without monitors. In grids with monitors, emergency department (ED) asthma PMCK on lag days 0, 1 and 01 and inpatient (IP) heart failure (HF) PMCK ORs on lag days 01 were significantly higher than PMB ORs. Warm season ORs were significantly higher than cold season ORs. Independent confirmation of these results should include AOD-PM 2.5 concentration surfaces with greater temporal-spatial resolution, now easily available from geostationary satellites, such as GOES-16 and GOES-17.In urban areas, PMB gives more "weight" to PM 2.5 monitor readings than CMAQ PM 2.5 model predictions. In rural areas, CMAQ PM 2.5 model predictions exert more influence than PM 2.5 monitor readings on PMB, since there are fewer monitors or no monitors. Ambient air monitors are usually found in urban areas. In the last 15 years, PMB has turned out to be a more representative PM 2.5 concentration surface, compared to the interpolation of PM 2.5 monitor data, as a method to resolve spatial gaps between ambient air monitors [16,18,22]. CDC subsequently incorporated PMB into its Environmental Public Health Tracking (EPHT) network of state and New York City partners [16,18,22,26]. To date, PMB has been used by federal and state epidemiologists completing EPHT projects in different parts of the US [16,18,22,26].Within this decade, the availability and use of satellite AOD data have become more routine [6,16,[27][28][29][30][31]. Newer generation satellite instruments measure AOD with increased temporal accuracy and finer spatial resolution [27,[32][33][34][35][36][37]. AOD is a unitless measure of the scattering and absorption of visible light by aerosols (particles) in the atmosphere [38][39][40]. AOD data are, by definition, actual physical measurements, an improvement over CMAQ PM 2.5 model predictions. Once AOD unitless measurements have been calibrated with actual PM 2.5 readings from on-the-ground ambient air monitors, it is then possible to utilize the derived AOD-PM 2.5 concentration readings to estimate actual ambient PM 2.5 concentration in areas where there are no on-the-ground air monitors. The relationship between AOD measurements and on-the-ground measurements of PM 2.5 concentration readings has b...

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Section: Introductionmentioning

confidence: 99%

“…Each column displays total observations (n) and percent (%) for emergency department (ED)/inpatient (IP) asthma case-control groups 2. Significance was evaluated with the Chi Square test: * = p ≤ 0.05; † = p ≤ 0.01 3. Significant age group differences between ED asthma cases and IP asthma cases, p ≤ 0.01 4.…”

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confidence: 99%

Contribution of Satellite-Derived Aerosol Optical Depth PM2.5 Bayesian Concentration Surfaces to Respiratory-Cardiovascular Chronic Disease Hospitalizations in Baltimore, Maryland

et al. 2020

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“…Another approach is to consider existing death tolls from related causes. As a cause of death, AGW will hardly be inseparable from poverty, which is also linked to air pollution (Egondi et al, 2018). Outdoor air pollution (mostly by PM2.5) is now causing 3 × 10 6 premature deaths per year, mainly in Asia; in a business-as-usual scenario, this figure could double by 2050 (Lelieveld et al, 2015).…”

Section: Best-case Estimatementioning

confidence: 99%

The Human Cost of Anthropogenic Global Warming: Semi-Quantitative Prediction and the 1,000-Tonne Rule

Parncutt

2019

Front. Psychol.

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Greenhouse-gas emissions are indirectly causing future deaths by multiple mechanisms. For example, reduced food and water supplies will exacerbate hunger, disease, violence, and migration. How will anthropogenic global warming (AGW) affect global mortality due to poverty around and beyond 2100? Roughly, how much burned fossil carbon corresponds to one future death? What are the psychological, medical, political, and economic implications? Predicted death tolls are crucial for policy formulation, but uncertainty increases with temporal distance from the present and estimates may be biased. Order-of-magnitude estimates should refer to literature from diverse relevant disciplines. The carbon budget for 2°C AGW (roughly 1012 tonnes carbon) will indirectly cause roughly 109 future premature deaths (10% of projected maximum global population), spread over one to two centuries. This zeroth-order prediction is relative and in addition to existing preventable death rates. It lies between likely best- and worst-case scenarios of roughly 3 × 108 and 3 × 109, corresponding to plus/minus one standard deviation on a logarithmic scale in a Gaussian probability distribution. It implies that one future premature death is caused every time roughly 1,000 (300–3,000) tonnes of carbon are burned. Therefore, any fossil-fuel project that burns millions of tons of carbon is probably indirectly killing thousands of future people. The prediction may be considered valid, accounting for multiple indirect links between AGW and death rates in a top-down approach, but unreliable due to the uncertainty of climate change feedback and interactions between physical, biological, social, and political climate impacts (e.g., ecological cascade effects and co-extinction). Given universal agreement on the value of human lives, a death toll of this unprecedented magnitude must be avoided at all costs. As a clear political message, the “1,000-tonne rule” can be used to defend human rights, especially in developing countries, and to clarify that climate change is primarily a human rights issue.

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“…PM 2.5 pollution remains an under-recognized environmental health risk in such countries [ 18 ]. Applying logistic and Poisson regression models, Egondi et al [ 20 ] found that exposure to high levels of PM 2.5 pollution is associated with a high risk for childhood morbidity and a high children mortality rate in Nairobi, Kenya. Using cross-country level data of Africa from 2000 to 2015, Owili et al [ 21 ] provided the evidence that there exists a significant relationship between PM 2.5 and under-five and maternal mortality in Africa.…”

Section: Introductionmentioning

confidence: 99%

“…Since the epithelial linings of children’s lungs and immune systems are not fully developed, children are more vulnerable to ambient air pollution compared to adults [ 20 , 27 , 28 ]. This paper focuses on evaluating the impacts of fine particulate air pollution on U5MR, as well as explores the role of public service in moderating the PM 2.5 -mortality relationship with panel data of 94 countries over the period 1998–2014.…”

Section: Introductionmentioning

confidence: 99%

Fine Particulate Air Pollution, Public Service, and Under-Five Mortality: A Cross-Country Empirical Study

et al. 2020

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The impacts of fine particulate matter (PM2.5) air pollution on health outcomes, especially those of children, have attracted worldwide attention. Based on the PM2.5 concentration data of 94 countries, including the least developed countries estimated by satellite observations in nearly 20 years, this paper investigated the impacts of PM2.5 pollution on under-five mortality rate (U5MR) and analyzed the role of public service in moderating the PM2.5-mortality relationship. Results indicated that PM2.5 pollution had significantly positive influence on U5MR globally. However, the effects of fine particulate pollution on child mortality were heterogeneous in terms of their significance and degrees in countries with different levels of development. A further test based on panel threshold model revealed that public service, measured by public education spending and sanitation service, played a positive moderating role in the PM2.5-mortality relationship. Specifically, when the ratio of public education expenditure in GDP of a country exceeded the first threshold value 3.39% and the second threshold value 5.47%, the magnitude of the impacts of PM2.5 pollution on U5MR significantly decreased accordingly. When the percentage of population with access to improved sanitation facilities in a country was over 41.3%, the health damaging effects were reduced by more than half. This paper fills the current gap of PM2.5 research in least developed countries and provides key policy recommendations.

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Exposure to Outdoor Particles (PM2.5) and Associated Child Morbidity and Mortality in Socially Deprived Neighborhoods of Nairobi, Kenya

Cited by 23 publications

References 40 publications

Contribution of Satellite-Derived Aerosol Optical Depth PM2.5 Bayesian Concentration Surfaces to Respiratory-Cardiovascular Chronic Disease Hospitalizations in Baltimore, Maryland

Contribution of Satellite-Derived Aerosol Optical Depth PM2.5 Bayesian Concentration Surfaces to Respiratory-Cardiovascular Chronic Disease Hospitalizations in Baltimore, Maryland

The Human Cost of Anthropogenic Global Warming: Semi-Quantitative Prediction and the 1,000-Tonne Rule

Fine Particulate Air Pollution, Public Service, and Under-Five Mortality: A Cross-Country Empirical Study

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