Air Date: 7-15-2016| Episode: 422
This week IAQ Radio will be flashing back to January 21, 2011 for a show we did with Mark J. Mendell, PhD. of the Lawrence Berkeley Lab and the California Dept. of Health. When looking back at shows to replay this one stood out so we remixed the sound, tweaked a few things and will replay it today…
Full Description:
This week IAQ Radio will be flashing back to January 21, 2011 for a show we did with Mark J. Mendell, PhD. of the Lawrence Berkeley Lab and the California Dept. of Health. When looking back at shows to replay this one stood out so we remixed the sound, tweaked a few things and will replay it today. Mark Mendell, Ph.D., is currently a Staff Scientist/Epidemiologist in the Indoor Environment Group at EETD, and an Air Pollution Research Specialist at the California Department of Public Health. Dr. Mendell is on the editorial board of the journal Indoor Air and a member of the International Academy of Indoor Air Sciences. He was formerly at the Centers for Disease Control/National Institute for Occupational Safety and Health, where he was head of the National Occupational Research Agenda Team on Indoor Environments. Dr. Mendell holds a BA from Cornell University; a Bachelor of Landscape Architecture from the University of Oregon; and a PhD in epidemiology from the University of California at Berkeley, School of Public Health. Dr. Mendell has worked for 20 years in the field of environmental epidemiology, focused on health effects related to indoor environments in buildings. His work includes field research to help understand relationships between specific factors and conditions in buildings and health effects in occupants, and critical reviews of the literature that summarize what we know, how well we know it, and what we do not know, about specific environment/health relationships in buildings. His research interests include health risks associated with buildings, ventilation systems, moisture, and microbial growth; effects of indoor environments in schools on health and performance of students, and effects of indoor chemical exposures in residences on asthma and allergies. LEARN MORE about indoor environments and the health effects related to mold and moisture this week on IAQ Radio!
Z-Man’s Blog:
- Qualitative review is what we know altogether; qualitative reviews support conclusions without providing specific numbers.
- Quantitative review is a number weighted study summarized in a specific number for each relationship.
- Ventilation influences, either positively or negatively, health effects related to indoor environments.
- Moisture and dampness in indoor environments is the one issue that researchers know most about.
- Respiratory infection is the most common health symptom related to dampness in buildings. Respiratory inflammation involves either the upper or lower respiratory tracts. Acute (short term) inflammation is caused by infection, colds and flu. Chronic (long term) inflammation is not caused by infection and is caused by environmental tobacco smoke, fumes and other environmental exposures.
- Otitis media are inflammations of the middle ear. Dampness increases these inflammations and is consistent with a finding of an association between dampness and otitis media.
- If you see dampness, see mold, smell mold there is a 40%-50% probability of the building occupants developing a health problem.
- In litigation, the paper “Association of residential dampness and mold with respiratory tract infections and bronchitis: a meta-analysis” may be aid for the defense as it concludes that no causality has been established.
- There is no basis for using mold measurements to decide health issues in buildings.
- The Stachybotrys and mycotoxin health effects argument has not been established.
- IEPs can find a summary of what we know about IAQ www.iaqscience.lbl.gov
- Studies find random answers around the true answer they seek.
- Scientific researchers need to improve efforts in making their scientific research useful.
- Dieterisms: An association is different than proof. Applying a statistic to any set of data always results in an association. How good is the association?
