POOR AIR
QUALITY in Homes of Medicare Recipients With Diabetes Poor air quality has been associated with chronic
A
ir quality is regulated outdoors, in public works, and in commercial housillness such as diabetes. This can be of particular ing including Skilled Nursing Facilities but importance for older adults with diabetes and not in private homes after construction other chronic conditions who spend most of certification (“40 CFR Part 50,” 2006; Davis Del Bene, 2007; “Standards for Adult Homes their time indoors. The purpose of this study Part 487,” n.d.). The U.S. Environmental was to assess home air quality and residents’ Protection Agency (EPA), National Ambiawareness and concerns about air quality in ent Air Quality Standards (NAAQS), and 40 CFR Part 50 define levels for modifiable rural underserved areas of upstate New York. conditions (e.g., pollutants, temperature, Implications for home care clinicians are discussed. humidity) above which are considered hazardous for specific populations, such as the elderly with diabetes (Schneider et al., 2010; Sun Philip C. Morin, MS et al., 2009). Current regulations, however, may understate health hazards. For example, particulate matter (PM) exposure below the NAAQS set point may cause Paula F. Rosenbaum, PhD problems for those with chronic illnesses (Johnson & Graham, 2005). Enhanced susceptibility is particularly important to Jerrold L. Abraham, MD, and consider in caring for older adults with diabetes and comorbidities such as hypertension, heart disease, cereRuth S. Weinstock, MD, PhD brovascular disease, dyslipidemia, obesity, and lung disease. Older adults may be indoors 80% to 90% per day, mainly in private homes (Oswald & Wahl, 2004). In upstate New York (NY), the median age is increasing (Blakely-Armitage et al., 2011) and privately owned homes are the primary site of activity for 75% of seniors (Humphreys, 2007). Health status was well characterized for upstate NY participants in the Informatics for Diabetes Education and Telemedicine (IDEATel) demonstration project for
354 Home Healthcare Nurse
www.homehealthcarenurseonline.com
Copyright © 2014 Lippincott Williams & Wilkins. Unauthorized reproduction of this article is prohibited.
Medicare beneficiaries with diabetes living in medically underserved areas (Shea et al., 2002, 2006, 2009). IDEATel randomized individuals to receive usual diabetes care or usual care plus the use of home telemedicine. We report home air quality assessments, concern for air conditions, and associations with comorbid medical conditions in 154 IDEATel participants who lived in upstate NY. This is of particular interest, as the most frequent cause of morbidity and mortality in individuals with diabetes is cardiovascular disease, and both depression and exposure to poor air quality are associated with increased cardiovascular events (Zanobetti & Schwartz, 2002).
Methodology IDEATel enrolled Medicare beneficiaries ages ≥ 55 years, residing in federally designated medically underserved areas of NY. All participants had diabetes and most had multiple chronic illnesses (Shea et al., 2006). The study design has been reported previously (Shea et al., 2002). Depression was measured using the Short-Care Depression Scale (Gurland et al., 1984). Participants with barriers to travel received annual evaluations inhome by study nurses. Participants using home telemedicine and receiving in-home annual study evaluations in
vol. 32 • no. 6 • June 2014
upstate NY were invited to take part in a home environmental assessment. After written informed consent was obtained, study nurses recorded information concerning the age and construction specifications of the home, housing setting and proximal land uses (e.g., near a farm), type of heating system, exposure to in-home tobacco smoke, presence of pets and pests, visible mold or standing water, as well as a history of mold and dampness. The nurse graded potential sources of indoor air pollution (e.g., smoking materials, visible mold, heating system type, pets or pests) and general home hygiene in a walk-through inspection of living spaces. The inspection documented participant perceptions of the in-home and surrounding environment using a combination of structured interview prompts, checklists with multiple choice responses, and queries with open response fields. Participants were given copies of their air testing results and interpretation. The Institutional Review Board for the Protection of Human Subjects at SUNY Upstate Medical University, Syracuse, NY approved the study. Indoor air quality (IAQ) was sampled for 21 days at 2-minute intervals at the breathing zone level in the most used seating location using an Air Advice model 5100 monitor (Air Advice, Inc., Portland, OR). This commercially available
Home Healthcare Nurse 355
Copyright © 2014 Lippincott Williams & Wilkins. Unauthorized reproduction of this article is prohibited.
Table 1. Participants’ Housing Characteristics, n =154 Characteristic
N
(%)
67 45 35 7
(44) (29) (23) (4)
Attached garage No Yes
105 46
(70) (30)
Heating system Forced hot air Hot water, radiator Electric heat Other
83 39 17 15
(54) (25) (11) (10)
Kitchen stove type Gas Electric Other
60 91 3
(39) (59) (2)
Working kitchen fan No Yes
41 111
(27) (73)
Smoking in the home None Indoor and outdoor Mostly indoor Mostly outdoor
125 19 7 3
(81) (12) (5) (2)
Pets No Yes
79 75
(51) (49)
Wall-to-wall carpeting No Yes
33 121
(21) (79)
Home insulated No Yes
5 138
(3) (97)
Participant rating of airtightness Airtight Average airtightness Not airtight
44 96 14
(29) (62) (9)
Standing water/condensation No Yes
145 9
(94) (6)
Visible mold No Yes
141 13
(92) (8)
Recent indoor paint No Yes
142 12
(92) (8)
Solvents use (hobbies) No Yes
149 5
(97) (3)
Air fresheners use No Yes
46 108
(30) (70)
Dust-producing hobbies No Yes
148 6
(96) (4)
Traffic on adjacent road Light Moderate Heavy
58 67 29
(38) (44) (18)
Year home built Before 1950 1950–1980 1980–2007 Does not know
356 Home Healthcare Nurse
instrument, designed to detect unhealthy IAQ, is small, relatively inexpensive, robust, and permits downloading of data from the home by telephone. The monitor uses interference of a light wave to estimate average mass of respirable (particle diameters 0.7 to 10 micrometers [µm]) PM per cubic meter of air propelled through an aperture and reports the concentration of PM as micrograms per cubic meter (µg/m3). This device also measures CO2, CO, humidity, temperature, and volatile organic compounds (VOCs). If air monitoring was disrupted before 21 days, another monitor was provided to achieve 21 days of data. Monitor recordings were downloaded to Air Advice, Inc., and data were transmitted to the study team for analysis. Participants’ home assessment and annual IDEATel health assessment data were analyzed to identify possible associations between in-home environmental conditions (e.g., stove type, smoking) and chronic diseases. Associations also were evaluated between housing characteristics and the indoor environmental measures. Frequencies were tabulated for all variables as well as means, standard deviation, median, and ranges for continuous variables (e.g., age, HbA1c, air parameters). Associations between categorical variables were assessed using Pearson’s chi-square, whereas comparisons of means across categorical variables were evaluated using t-tests or analyses of variance. Analyses were undertaken using SPSS, version 19 (IBM Corp., Armonk, NY).
Results Of the 154 participants, 53% were male (n = 82), with a mean age of 73.9 years; 64% were living with a spouse or partner. 78% had annual incomes of 130°F • Relocate pets
• Vacuum carpets and furniture regularly • Keep pets out of sleeping areas • If possible choose less allergenic pets
Radon
• Soil: enters home via cracks/ gaps/holes in floors and walls • Well water
• Detect with in-home radon test kit • May need to install ventilation fan • Information on testing and fixing: http://www.epa.gov/radon/ radontest.html
• If radon levels are 4 pCi/L or higher, fix problem • Radon hot-line: 1-800-SOSRADON
Note. VOC = xxx.
vol. 32 • no. 6 • June 2014
Home Healthcare Nurse 359
Copyright © 2014 Lippincott Williams & Wilkins. Unauthorized reproduction of this article is prohibited.
Strengths of this study include the characterization of the participants and their homes. There are few assessments of indoor environmental quality in nonurban, medically underserved populations. Despite the relatively small numbers of upstate NY homes characterized, it is of concern that some older adults with diabetes have PM in air at levels appropriate for mitigation. There are several limitations to this study. We studied a relatively small number of individuals and their homes in upstate NY. They were all Medicare beneficiaries from medically underserved areas; most were obese and most had low income. Consequently, it is not known if similar results would be found in other populations of older adults. There is also the possibility of selection bias, as participants were volunteers from within the larger IDEATel study. Additionally, this substudy was cross-sectional in design; results from cross-sectional studies do not provide support for causation, but are useful in generating hypotheses and descriptions of possible associations.
Recommendations Older adults with diabetes and other chronic diseases living in underserved rural areas are exposed at home to contaminants in their air, about which they are unaware. This suggests that clinicians should consider discussing with their patients potential sources of poor air quality such as smoking, indoor combustion (improperly or unvented fuel-burning stoves, heaters, dryers, fireplaces), upwind traffic and diesel generators, and improper storage of volatile compounds such as paints, varnishes, lacquers, and pesticides. Amelioration steps that can be discussed with clients include better ventilation to dilute indoor air with cleaner fresh air, filtration of indoor air, and/or reduction of penetration of outdoor air pollutants (http://www.epa.gov/iaq/homes/ index.html). Residents should also be reminded to change filters in heaters and air conditioners, and avoid high humidity. Our findings suggest that attention to these home environmental factors may benefit older adults with chronic diseases who spend most of their time indoors.
Philip C. Morin, MS, is a Project Manager, Department of Medicine, Upstate Medical University, Syracuse, New York. Paula F. Rosenbaum, PhD, is an Associate Professor, Department of Public Health and Preventive Medicine, Upstate Medical University, Syracuse, New York.
360 Home Healthcare Nurse
Jerrold L. Abraham, MD, is a Professor, Department of Pathology, Upstate Medical University, Syracuse, New York. Ruth S. Weinstock, MD, PhD, is a SUNY Distinguished Service Professor, Department of Medicine, Upstate Medical University, Syracuse, New York. This study was supported, in part, by the Centers for Medicare and Medicaid Services (CMS) and the New York State Office of Science, Technology and Academic Research (NYSTAR). The authors declare no conflicts of interest. Address for correspondence: Ruth S. Weinstock, MD, PhD, SUNY Distinguished Service Professor, Upstate Medical University, 750 E. Adams St., CWB 353, Syracuse, NY 13210 ([email protected]). DOI:10.1097/NHH.0000000000000094 REFERENCES Andersen, Z. J., Raaschou-Nielsen, O., Ketzel, M., Jensen, S. S., Hvidberg, M., Loft, S., …, Sørensen, M. (2012). Diabetes incidence and long-term exposure to air pollution: A cohort study. Diabetes Care, 35(1), 92-98. Auchincloss, A. H., Diez Roux, A. V., Dvonch, J. T., Brown, P. L., Barr, R. G., Daviglus, M. L., …, O’Neill, M. S. (2008). Associations between recent exposure to ambient fine particulate matter and blood pressure in the multi-ethnic study of atherosclerosis (MESA). Environmental Health Perspectives, 116(4), 486-491. Balluz, L., Wen, X. J., Town, M., Shire, J. D., Qualter, J., & Mokdad, A. (2007). Ischemic heart disease and ambient air pollution of particulate matter 2.5 in 51 counties in the U.S. Public Health Reports, 122(5), 626-633. Blakely-Armitage, R., Sanders, S., Francis, S., & Vink, J. (2011). Upstate New York in profile: Cornell University 2011 state of upstate New York initiative. Retrieved from http://devoc.cals.cornell.edu/ cals/devsoc/outreach/cardi/upload/Chartbook-final-1pdf Brook, R. D., Rajagopalan, S., Pope, C. A. 3rd, Brook, J. R., Bhatnagar, A., Diez-Roux, A. V., ..., Kaufman J. D. (2010). Particulate matter air pollution and cardiovascular disease: An update to the scientific statement from the American Heart Association. Circulation, 121(21), 2331-2378. doi:10.1161/CIR.0b013e3181dbece1 40 CFR Part 50. (2006, October 17). United States environmental protection agency, national ambient air quality standards for particulate matter. Federal Register 71(200), 61144 Retrieved from http://www.epa.gov/airquality/particlepollution Clyde, M., Smith, K. J., Gariépy, G., Schmitz, N. (2013). The association between smoking and depression in a Canadian community-based sample with Type 2 diabetes. Canadian Journal Diabetes, 37(3), 150-155. Davis Del Bene, A. (2007). Home environmental health risks. OJIN: The Online Journal of Issues in Nursing, 12(2), 4. doi:10.3912/ OJIN.Vol12No202Man04 Dust control handbook for minerals processing: Chapter 1—dust and its control. (2013). Retrieved from http://www.osha.gov/dsg/ topics/silicacrystalline/dust/chapter_1html Franchini, M., & Mannucci, P. M. (2009). Particulate air pollution and cardiovascular risk: Short-term and long-term effects. Seminars in Thrombosis and Hemostasis, 35(7), 665-670. doi:10.1055/s-0029-1242720 Gurland, B., Golden, R. R., Teresi, J. A., Challop, J. (1984). The SHORT-CARE: An efficient instrument for the assessment of depression, dementia and disability. Journal of Gerontology, 39(2), 166-169. Humphreys, J. (2007). Aging in place in upstate New York. Upstate New York Regional Review. 2(2), 1-4. Retrieved from http://www. newyorkfed.org/research/regional_economy/upstatenews.html Johnson, P. R., & Graham, J. J. (2005). Fine particulate matter national ambient air quality standards: Public health impact on populations in the northeastern United States. Environmental Health Perspectives, 113(9), 1140-1147. Katon, W., Von Korff, M., Ciechanowski, P., Russo, J., Lin, E., Simon, G., ..., Young, B. (2004). Behavioral and clinical factors associated with depression among individuals with diabetes. Diabetes Care, 27(4), 914-920.
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Copyright © 2014 Lippincott Williams & Wilkins. Unauthorized reproduction of this article is prohibited.
Krämer, U., Herder, C., Sugiri, D., Strassburger, K., Schikowski, T., Ranft, U., & Rathmann, W. (2010). Traffic-related air pollution and incident type 2 diabetes: Results from the SALIA cohort study. Environmental Health Perspectives, 118(9), 1273-1279. doi:10.1289/ehp.0901689 Oswald, F., & Wahl, H. W. (2004). Housing and health in later life. Reviews on Environmental Health, 19(3-4), 223-252. Patel, C. J., Bhattacharya, J., & Butte, A. J. (2010). An environmentwide association study (EWAS) on type 2 diabetes mellitus. PLoS ONE, 5(5), e10746. doi:10.1371/journal.pone.0010746 Pearson, J. F., Bachireddy, C., Shyamprasad, S., Goldfine, A. B., Brownstein, J. S. (2010). Association between fine particulate matter and diabetes prevalence in the U.S. Diabetes Care, 33(10), 2196-2201. Peel, J. L., Metzger, K. B., Klein, M., Flanders, W. D., Mulholland, J. A., Tolbert, P. E. (2007). Ambient air pollution and cardiovascular emergency department visits in potentially sensitive groups. American Journal of Epidemiology, 165(6), 625-633. doi:10.1093/aje/kwk051 Pickett, A. R., & Bell, M. L. (2011). Assessment of indoor air pollution in homes with infants. International Journal of Environmental Research and Public Health, 8(12), 4502-4520. doi:10.3390/ ijerph8124502 Schneider, A., Neas, L. M., Graff, D. W., Herbst, M. C., Cascio, W. E., Schmitt, M. T., … Devlin, R. B. (2010). Association of cardiac and vascular changes with ambient PM2.5 in diabetic individuals. Particle and Fibre Toxicology, 7, 14. Retrieved from http://www. particleandfibretoxicology.com/content/7/1/14 Shea, S., Starren, J., Weinstock, R. S., Knudson, P. E., Teresi, J., Holmes, D., ..., Liss, D. (2002). Columbia University’s Informatics for Diabetes Education and Telemedicine (IDEATel) project: Rationale and design. Journal of the American Medical Informatics Association, 9(1), 49-62.
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Shea, S., Weinstock, R. S., Starren, J., Teresi, J., Palmas, W., Field, L., ...., Lantigua, R. A. (2006). A randomized trial comparing telemedicine case management with usual care in older, ethnically diverse, medically underserved patients with diabetes mellitus. Journal of the American Medical Informatics Association, 13(1), 40-51. doi:10.1197/jamia.M1917 Shea, S., Weinstock, R. S., Teresi, J. A., Palmas, W., Starren, J., Cimino, J. J., ..., Eimicke, J. P. (2009). A randomized trial comparing telemedicine case management with usual care in older, ethnically diverse, medically underserved patients with diabetes mellitus: 5 year results of the IDEATel study. Journal of the American Medical Informatics Association, 16(4), 446-456. doi:10.1197/jamia.M3157 Standards for adult homes part 487. (n.d.). Retrieved from http:// www.ny-assisted-living.org/nysdoh/pdf/DOHpart487.pdf Sun, Q., Yue, P., Deiulis, J. A., Lumeng, C. N., Kampfrath, T., Mikolaj, M. B. ... Rajagoplan, S. (2009). Ambient air pollution exaggerates adipose inflammation and insulin resistance in a mouse model of diet-induced obesity. Circulation, 119(4), 538-546. doi:10.1161C IRCULATIONAHA.108.799015/DCI Symons, J. M., Wang, L., Guallar, E., Howell, E., Dominici, F., Schwab, M., ..., Geyh, A. (2006). A case-crossover study of fine particulate matter air pollution and onset of congestive heart failure symptom exacerbation leading to hospitalization. American Journal of Epidemiology, 164(5), 421-433. doi:10.1093/aje/ kwj206 Tomao, E., Tiziana, P. B., Rosati, V., Marcellini, L., & Tomei, F. (2002). The effects of air pollution on the lipid balance of traffic police personnel. Annals of Saudi Medicine, 22(5-6), 287-290. Zanobetti, A., & Schwartz, J. (2002). Cardiovascular damage by airborne particles: Are diabetics more susceptible? Epidemiology, 13(5), 588-592. doi:10.1097/01.EDE.0000020321. 67963.7B
Home Healthcare Nurse 361
Copyright © 2014 Lippincott Williams & Wilkins. Unauthorized reproduction of this article is prohibited.
QUALITY in Homes of Medicare Recipients With Diabetes Poor air quality has been associated with chronic
A
ir quality is regulated outdoors, in public works, and in commercial housillness such as diabetes. This can be of particular ing including Skilled Nursing Facilities but importance for older adults with diabetes and not in private homes after construction other chronic conditions who spend most of certification (“40 CFR Part 50,” 2006; Davis Del Bene, 2007; “Standards for Adult Homes their time indoors. The purpose of this study Part 487,” n.d.). The U.S. Environmental was to assess home air quality and residents’ Protection Agency (EPA), National Ambiawareness and concerns about air quality in ent Air Quality Standards (NAAQS), and 40 CFR Part 50 define levels for modifiable rural underserved areas of upstate New York. conditions (e.g., pollutants, temperature, Implications for home care clinicians are discussed. humidity) above which are considered hazardous for specific populations, such as the elderly with diabetes (Schneider et al., 2010; Sun Philip C. Morin, MS et al., 2009). Current regulations, however, may understate health hazards. For example, particulate matter (PM) exposure below the NAAQS set point may cause Paula F. Rosenbaum, PhD problems for those with chronic illnesses (Johnson & Graham, 2005). Enhanced susceptibility is particularly important to Jerrold L. Abraham, MD, and consider in caring for older adults with diabetes and comorbidities such as hypertension, heart disease, cereRuth S. Weinstock, MD, PhD brovascular disease, dyslipidemia, obesity, and lung disease. Older adults may be indoors 80% to 90% per day, mainly in private homes (Oswald & Wahl, 2004). In upstate New York (NY), the median age is increasing (Blakely-Armitage et al., 2011) and privately owned homes are the primary site of activity for 75% of seniors (Humphreys, 2007). Health status was well characterized for upstate NY participants in the Informatics for Diabetes Education and Telemedicine (IDEATel) demonstration project for
354 Home Healthcare Nurse
www.homehealthcarenurseonline.com
Copyright © 2014 Lippincott Williams & Wilkins. Unauthorized reproduction of this article is prohibited.
Medicare beneficiaries with diabetes living in medically underserved areas (Shea et al., 2002, 2006, 2009). IDEATel randomized individuals to receive usual diabetes care or usual care plus the use of home telemedicine. We report home air quality assessments, concern for air conditions, and associations with comorbid medical conditions in 154 IDEATel participants who lived in upstate NY. This is of particular interest, as the most frequent cause of morbidity and mortality in individuals with diabetes is cardiovascular disease, and both depression and exposure to poor air quality are associated with increased cardiovascular events (Zanobetti & Schwartz, 2002).
Methodology IDEATel enrolled Medicare beneficiaries ages ≥ 55 years, residing in federally designated medically underserved areas of NY. All participants had diabetes and most had multiple chronic illnesses (Shea et al., 2006). The study design has been reported previously (Shea et al., 2002). Depression was measured using the Short-Care Depression Scale (Gurland et al., 1984). Participants with barriers to travel received annual evaluations inhome by study nurses. Participants using home telemedicine and receiving in-home annual study evaluations in
vol. 32 • no. 6 • June 2014
upstate NY were invited to take part in a home environmental assessment. After written informed consent was obtained, study nurses recorded information concerning the age and construction specifications of the home, housing setting and proximal land uses (e.g., near a farm), type of heating system, exposure to in-home tobacco smoke, presence of pets and pests, visible mold or standing water, as well as a history of mold and dampness. The nurse graded potential sources of indoor air pollution (e.g., smoking materials, visible mold, heating system type, pets or pests) and general home hygiene in a walk-through inspection of living spaces. The inspection documented participant perceptions of the in-home and surrounding environment using a combination of structured interview prompts, checklists with multiple choice responses, and queries with open response fields. Participants were given copies of their air testing results and interpretation. The Institutional Review Board for the Protection of Human Subjects at SUNY Upstate Medical University, Syracuse, NY approved the study. Indoor air quality (IAQ) was sampled for 21 days at 2-minute intervals at the breathing zone level in the most used seating location using an Air Advice model 5100 monitor (Air Advice, Inc., Portland, OR). This commercially available
Home Healthcare Nurse 355
Copyright © 2014 Lippincott Williams & Wilkins. Unauthorized reproduction of this article is prohibited.
Table 1. Participants’ Housing Characteristics, n =154 Characteristic
N
(%)
67 45 35 7
(44) (29) (23) (4)
Attached garage No Yes
105 46
(70) (30)
Heating system Forced hot air Hot water, radiator Electric heat Other
83 39 17 15
(54) (25) (11) (10)
Kitchen stove type Gas Electric Other
60 91 3
(39) (59) (2)
Working kitchen fan No Yes
41 111
(27) (73)
Smoking in the home None Indoor and outdoor Mostly indoor Mostly outdoor
125 19 7 3
(81) (12) (5) (2)
Pets No Yes
79 75
(51) (49)
Wall-to-wall carpeting No Yes
33 121
(21) (79)
Home insulated No Yes
5 138
(3) (97)
Participant rating of airtightness Airtight Average airtightness Not airtight
44 96 14
(29) (62) (9)
Standing water/condensation No Yes
145 9
(94) (6)
Visible mold No Yes
141 13
(92) (8)
Recent indoor paint No Yes
142 12
(92) (8)
Solvents use (hobbies) No Yes
149 5
(97) (3)
Air fresheners use No Yes
46 108
(30) (70)
Dust-producing hobbies No Yes
148 6
(96) (4)
Traffic on adjacent road Light Moderate Heavy
58 67 29
(38) (44) (18)
Year home built Before 1950 1950–1980 1980–2007 Does not know
356 Home Healthcare Nurse
instrument, designed to detect unhealthy IAQ, is small, relatively inexpensive, robust, and permits downloading of data from the home by telephone. The monitor uses interference of a light wave to estimate average mass of respirable (particle diameters 0.7 to 10 micrometers [µm]) PM per cubic meter of air propelled through an aperture and reports the concentration of PM as micrograms per cubic meter (µg/m3). This device also measures CO2, CO, humidity, temperature, and volatile organic compounds (VOCs). If air monitoring was disrupted before 21 days, another monitor was provided to achieve 21 days of data. Monitor recordings were downloaded to Air Advice, Inc., and data were transmitted to the study team for analysis. Participants’ home assessment and annual IDEATel health assessment data were analyzed to identify possible associations between in-home environmental conditions (e.g., stove type, smoking) and chronic diseases. Associations also were evaluated between housing characteristics and the indoor environmental measures. Frequencies were tabulated for all variables as well as means, standard deviation, median, and ranges for continuous variables (e.g., age, HbA1c, air parameters). Associations between categorical variables were assessed using Pearson’s chi-square, whereas comparisons of means across categorical variables were evaluated using t-tests or analyses of variance. Analyses were undertaken using SPSS, version 19 (IBM Corp., Armonk, NY).
Results Of the 154 participants, 53% were male (n = 82), with a mean age of 73.9 years; 64% were living with a spouse or partner. 78% had annual incomes of 130°F • Relocate pets
• Vacuum carpets and furniture regularly • Keep pets out of sleeping areas • If possible choose less allergenic pets
Radon
• Soil: enters home via cracks/ gaps/holes in floors and walls • Well water
• Detect with in-home radon test kit • May need to install ventilation fan • Information on testing and fixing: http://www.epa.gov/radon/ radontest.html
• If radon levels are 4 pCi/L or higher, fix problem • Radon hot-line: 1-800-SOSRADON
Note. VOC = xxx.
vol. 32 • no. 6 • June 2014
Home Healthcare Nurse 359
Copyright © 2014 Lippincott Williams & Wilkins. Unauthorized reproduction of this article is prohibited.
Strengths of this study include the characterization of the participants and their homes. There are few assessments of indoor environmental quality in nonurban, medically underserved populations. Despite the relatively small numbers of upstate NY homes characterized, it is of concern that some older adults with diabetes have PM in air at levels appropriate for mitigation. There are several limitations to this study. We studied a relatively small number of individuals and their homes in upstate NY. They were all Medicare beneficiaries from medically underserved areas; most were obese and most had low income. Consequently, it is not known if similar results would be found in other populations of older adults. There is also the possibility of selection bias, as participants were volunteers from within the larger IDEATel study. Additionally, this substudy was cross-sectional in design; results from cross-sectional studies do not provide support for causation, but are useful in generating hypotheses and descriptions of possible associations.
Recommendations Older adults with diabetes and other chronic diseases living in underserved rural areas are exposed at home to contaminants in their air, about which they are unaware. This suggests that clinicians should consider discussing with their patients potential sources of poor air quality such as smoking, indoor combustion (improperly or unvented fuel-burning stoves, heaters, dryers, fireplaces), upwind traffic and diesel generators, and improper storage of volatile compounds such as paints, varnishes, lacquers, and pesticides. Amelioration steps that can be discussed with clients include better ventilation to dilute indoor air with cleaner fresh air, filtration of indoor air, and/or reduction of penetration of outdoor air pollutants (http://www.epa.gov/iaq/homes/ index.html). Residents should also be reminded to change filters in heaters and air conditioners, and avoid high humidity. Our findings suggest that attention to these home environmental factors may benefit older adults with chronic diseases who spend most of their time indoors.
Philip C. Morin, MS, is a Project Manager, Department of Medicine, Upstate Medical University, Syracuse, New York. Paula F. Rosenbaum, PhD, is an Associate Professor, Department of Public Health and Preventive Medicine, Upstate Medical University, Syracuse, New York.
360 Home Healthcare Nurse
Jerrold L. Abraham, MD, is a Professor, Department of Pathology, Upstate Medical University, Syracuse, New York. Ruth S. Weinstock, MD, PhD, is a SUNY Distinguished Service Professor, Department of Medicine, Upstate Medical University, Syracuse, New York. This study was supported, in part, by the Centers for Medicare and Medicaid Services (CMS) and the New York State Office of Science, Technology and Academic Research (NYSTAR). The authors declare no conflicts of interest. Address for correspondence: Ruth S. Weinstock, MD, PhD, SUNY Distinguished Service Professor, Upstate Medical University, 750 E. Adams St., CWB 353, Syracuse, NY 13210 ([email protected]). DOI:10.1097/NHH.0000000000000094 REFERENCES Andersen, Z. J., Raaschou-Nielsen, O., Ketzel, M., Jensen, S. S., Hvidberg, M., Loft, S., …, Sørensen, M. (2012). Diabetes incidence and long-term exposure to air pollution: A cohort study. Diabetes Care, 35(1), 92-98. Auchincloss, A. H., Diez Roux, A. V., Dvonch, J. T., Brown, P. L., Barr, R. G., Daviglus, M. L., …, O’Neill, M. S. (2008). Associations between recent exposure to ambient fine particulate matter and blood pressure in the multi-ethnic study of atherosclerosis (MESA). Environmental Health Perspectives, 116(4), 486-491. Balluz, L., Wen, X. J., Town, M., Shire, J. D., Qualter, J., & Mokdad, A. (2007). Ischemic heart disease and ambient air pollution of particulate matter 2.5 in 51 counties in the U.S. Public Health Reports, 122(5), 626-633. Blakely-Armitage, R., Sanders, S., Francis, S., & Vink, J. (2011). Upstate New York in profile: Cornell University 2011 state of upstate New York initiative. Retrieved from http://devoc.cals.cornell.edu/ cals/devsoc/outreach/cardi/upload/Chartbook-final-1pdf Brook, R. D., Rajagopalan, S., Pope, C. A. 3rd, Brook, J. R., Bhatnagar, A., Diez-Roux, A. V., ..., Kaufman J. D. (2010). Particulate matter air pollution and cardiovascular disease: An update to the scientific statement from the American Heart Association. Circulation, 121(21), 2331-2378. doi:10.1161/CIR.0b013e3181dbece1 40 CFR Part 50. (2006, October 17). United States environmental protection agency, national ambient air quality standards for particulate matter. Federal Register 71(200), 61144 Retrieved from http://www.epa.gov/airquality/particlepollution Clyde, M., Smith, K. J., Gariépy, G., Schmitz, N. (2013). The association between smoking and depression in a Canadian community-based sample with Type 2 diabetes. Canadian Journal Diabetes, 37(3), 150-155. Davis Del Bene, A. (2007). Home environmental health risks. OJIN: The Online Journal of Issues in Nursing, 12(2), 4. doi:10.3912/ OJIN.Vol12No202Man04 Dust control handbook for minerals processing: Chapter 1—dust and its control. (2013). Retrieved from http://www.osha.gov/dsg/ topics/silicacrystalline/dust/chapter_1html Franchini, M., & Mannucci, P. M. (2009). Particulate air pollution and cardiovascular risk: Short-term and long-term effects. Seminars in Thrombosis and Hemostasis, 35(7), 665-670. doi:10.1055/s-0029-1242720 Gurland, B., Golden, R. R., Teresi, J. A., Challop, J. (1984). The SHORT-CARE: An efficient instrument for the assessment of depression, dementia and disability. Journal of Gerontology, 39(2), 166-169. Humphreys, J. (2007). Aging in place in upstate New York. Upstate New York Regional Review. 2(2), 1-4. Retrieved from http://www. newyorkfed.org/research/regional_economy/upstatenews.html Johnson, P. R., & Graham, J. J. (2005). Fine particulate matter national ambient air quality standards: Public health impact on populations in the northeastern United States. Environmental Health Perspectives, 113(9), 1140-1147. Katon, W., Von Korff, M., Ciechanowski, P., Russo, J., Lin, E., Simon, G., ..., Young, B. (2004). Behavioral and clinical factors associated with depression among individuals with diabetes. Diabetes Care, 27(4), 914-920.
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Krämer, U., Herder, C., Sugiri, D., Strassburger, K., Schikowski, T., Ranft, U., & Rathmann, W. (2010). Traffic-related air pollution and incident type 2 diabetes: Results from the SALIA cohort study. Environmental Health Perspectives, 118(9), 1273-1279. doi:10.1289/ehp.0901689 Oswald, F., & Wahl, H. W. (2004). Housing and health in later life. Reviews on Environmental Health, 19(3-4), 223-252. Patel, C. J., Bhattacharya, J., & Butte, A. J. (2010). An environmentwide association study (EWAS) on type 2 diabetes mellitus. PLoS ONE, 5(5), e10746. doi:10.1371/journal.pone.0010746 Pearson, J. F., Bachireddy, C., Shyamprasad, S., Goldfine, A. B., Brownstein, J. S. (2010). Association between fine particulate matter and diabetes prevalence in the U.S. Diabetes Care, 33(10), 2196-2201. Peel, J. L., Metzger, K. B., Klein, M., Flanders, W. D., Mulholland, J. A., Tolbert, P. E. (2007). Ambient air pollution and cardiovascular emergency department visits in potentially sensitive groups. American Journal of Epidemiology, 165(6), 625-633. doi:10.1093/aje/kwk051 Pickett, A. R., & Bell, M. L. (2011). Assessment of indoor air pollution in homes with infants. International Journal of Environmental Research and Public Health, 8(12), 4502-4520. doi:10.3390/ ijerph8124502 Schneider, A., Neas, L. M., Graff, D. W., Herbst, M. C., Cascio, W. E., Schmitt, M. T., … Devlin, R. B. (2010). Association of cardiac and vascular changes with ambient PM2.5 in diabetic individuals. Particle and Fibre Toxicology, 7, 14. Retrieved from http://www. particleandfibretoxicology.com/content/7/1/14 Shea, S., Starren, J., Weinstock, R. S., Knudson, P. E., Teresi, J., Holmes, D., ..., Liss, D. (2002). Columbia University’s Informatics for Diabetes Education and Telemedicine (IDEATel) project: Rationale and design. Journal of the American Medical Informatics Association, 9(1), 49-62.
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Shea, S., Weinstock, R. S., Starren, J., Teresi, J., Palmas, W., Field, L., ...., Lantigua, R. A. (2006). A randomized trial comparing telemedicine case management with usual care in older, ethnically diverse, medically underserved patients with diabetes mellitus. Journal of the American Medical Informatics Association, 13(1), 40-51. doi:10.1197/jamia.M1917 Shea, S., Weinstock, R. S., Teresi, J. A., Palmas, W., Starren, J., Cimino, J. J., ..., Eimicke, J. P. (2009). A randomized trial comparing telemedicine case management with usual care in older, ethnically diverse, medically underserved patients with diabetes mellitus: 5 year results of the IDEATel study. Journal of the American Medical Informatics Association, 16(4), 446-456. doi:10.1197/jamia.M3157 Standards for adult homes part 487. (n.d.). Retrieved from http:// www.ny-assisted-living.org/nysdoh/pdf/DOHpart487.pdf Sun, Q., Yue, P., Deiulis, J. A., Lumeng, C. N., Kampfrath, T., Mikolaj, M. B. ... Rajagoplan, S. (2009). Ambient air pollution exaggerates adipose inflammation and insulin resistance in a mouse model of diet-induced obesity. Circulation, 119(4), 538-546. doi:10.1161C IRCULATIONAHA.108.799015/DCI Symons, J. M., Wang, L., Guallar, E., Howell, E., Dominici, F., Schwab, M., ..., Geyh, A. (2006). A case-crossover study of fine particulate matter air pollution and onset of congestive heart failure symptom exacerbation leading to hospitalization. American Journal of Epidemiology, 164(5), 421-433. doi:10.1093/aje/ kwj206 Tomao, E., Tiziana, P. B., Rosati, V., Marcellini, L., & Tomei, F. (2002). The effects of air pollution on the lipid balance of traffic police personnel. Annals of Saudi Medicine, 22(5-6), 287-290. Zanobetti, A., & Schwartz, J. (2002). Cardiovascular damage by airborne particles: Are diabetics more susceptible? Epidemiology, 13(5), 588-592. doi:10.1097/01.EDE.0000020321. 67963.7B
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