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Environmental Health Perspectives Volume 109, Supplement 3, June 2001 Assessing the Health Benefits of Urban Air Pollution Reductions Associated with Climate Change Mitigation (2000-2020): Santiago, São Paulo, México City, and New York City  Luis Cifuentes,1 Victor H. Borja-Aburto,2 Nelson Gouveia,3 George Thurston,4 and Devra Lee Davis5  1Pontificia Universidad Católica de Chile, Santiago, Chile; 2Secretaria de Salud, Ciudad de México, México; 3Departamento de Medicina Preventiva, Faculdade de Medicina da USP, São Paulo, Brazil; 4Nelson Institute of Environmental Medicine, New York University School of Medicine, Tuxedo, New York, USA; 5H. John Heinz III School for Public Policy and Management, Carnegie Mellon University, Pittsburgh, Pennsylvania, USA  [Citation in PubMed] [Related Articles]

Scenario Development  Health Effects Estimation Methods  Results  Discussion  Conclusion

Abstract To investigate the potential local health benefits of adopting greenhouse gas (GHG) mitigation policies, we develop scenarios of GHG mitigation for México City, México; Santiago, Chile; São Paulo, Brazil; and New York, New York, USA using air pollution health impact factors appropriate to each city. We estimate that the adoption of readily available technologies to lessen fossil fuel emissions over the next two decades in these four cities alone will reduce particulate matter and ozone and avoid approximately 64,000 (95% confidence interval [CI] 18,000-116,000) premature deaths (including infant deaths), 65,000 (95% CI 22,000-108,000) chronic bronchitis cases, and 46 million (95% CI 35-58 million) person-days of work loss or other restricted activity. These findings illustrate that GHG mitigation can provide considerable local air pollution-related public health benefits to countries that choose to abate GHG emissions by reducing fossil fuel combustion. Key words: air pollution, climate policy, greenhouse gases mitigation, morbidity, mortality, ozone, particulate matter, public health. -- Environ Health Perspect 109(suppl 3):419-425 (2001).  http://ehpnet1.niehs.nih.gov/docs/2001/suppl-3/419-425cifuentes/abstract.html Address correspondence to D. Davis, Carnegie Mellon University, 5000 Forbes Ave., Pittsburgh, PA 15213 USA. Telephone: (412) 268-5495. Fax: (412) 268-5337. E-mail: davis@andrew.cmu.edu This work was funded by the W. Alton Jones Foundation, the Rockefeller Family Fund, the U.S. Department of Energy, the U.S. EPA (Integrated Environmental Strategies Program and (Integrated Assessment and NYU-EPA PM center grant), the Latin America Program of the World Bank, the National Ministry of Health, México, Fondecyt, Chile, the Center for Integrated Study of the Human Dimensions of Global Change, a joint creation of the National Science Foundation (SBR-9521914) and Carnegie Mellon University, and a National Institute of Environmental Health Sciences center grant (ES00260) to the New York University School of Medicine. Part of this research was developed under the International Co-Control Benefits Analysis Program, which is managed for the U.S. EPA by the National Renewable Energy Laboratory (http://www.nrel.gov/icap).  Received 20 March 2001; accepted 25 April 2001.

A broad-ranging and lively debate is under way about the long-term consequences of greenhouse gas (GHG)-emitting activities, such as fossil fuel combustion, for global climate change. Although it is generally understood that policies to reduce GHG emissions can also have near-term positive and negative ancillary side effects on public health, ecosystems, land use, and materials, these side effects have not been well characterized or integrated into policy analyses of mitigation (1). This article assesses near-term public health consequences of reductions in ambient concentrations of particulate matter (PM) and ozone (O₃) associated with policies to reduce GHG emissions.

The approach used in this work parallels that of other recent national and regional assessments in which estimates of public health impacts of air pollution are derived from epidemiology-based concentration-
response functions. For example, Künzli et al. (2) relied on established coefficients of changes in health outcomes associated with increments of air pollution to estimate the impact of outdoor (total) and traffic-related air pollution on morbidity and mortality in Austria, France, and Switzerland. Air pollution was found to be associated with 6% of total mortality, or more than 40,000 attributable cases per year, with about half the mortalities linked to traffic-related emissions. Hall et al. (3) employed air pollutant mapping for the South Coast Basin of California and estimated that attaining ambient air pollution standards might save 1,600 lives per year in the region. The U.S. Environmental Protection Agency (U.S. EPA) employed a similar approach to assess the benefits of the U.S. Clean Air Act over its first two decades of application (4) and over the next two decades (5). The potential annual benefits from GHG mitigation options in the United States include thousands of avoided deaths and up to 520,000 work loss days that would result from the adoption of policies that target reductions in both air pollution and GHG emissions (6). Preliminary national assessments for Hungary and Canada have also suggested that substantial numbers of lives can be saved, chiefly from declines in mortality associated with fine particle reductions resulting from increased energy efficiency (7,8).

The Working Group on Fossil Fuels produced a global assessment that calculated the consequences of continuing energy policies that rely on customary practices, called business as usual (BAU), in 2010 and 2020. This study assessed the range of avoidable deaths solely from projected changes in PM that could arise between 2000 and 2020 under current policies and under the scenario proposed by the European Union in 1995 (9,10). On the basis of the estimated changes in PM and associated reductions in mortality, the report predicted that 700,000 avoidable deaths (90% confidence interval [CI] 385,000-1,034,000) will occur annually by 2020 under the BAU forecasts when compared with the climate policy scenario. As a first approximation, the cumulative impact from 2000 to 2020 on public health related to the difference in PM exposure could total 8 million deaths globally (90% CI 4.4-11.9 million). Thus, energy policies have significant impacts on air pollution and associated public health effects.

Scenario Development

The associated reductions in ambient concentrations of PM less than 10 µm in diameter (PM₁₀) and O₃ are approximately 10% of the projected baseline levels in 2020 and occur gradually throughout the two decades. These results agree with another study for Chile developed independently by the Organisation for Economic Co-operation and Development (12). On the basis of these results, we compute the benefits associated with a 10% reduction in PM and O₃ that might be associated with climate change policies in each of these megacities. Although we recognize that other air pollutants may also affect human health, we consider only PM and O₃ in this analysis. These two presently have the best-documented health effects across a wide range of health outcomes and are pollutants that represent, respectively, the particulate and the gaseous components of air pollution. Therefore, although conservative in that only two pollutants are considered, this analysis does consider the breadth of types of air pollution and health effect changes that would result from GHG mitigation measures.

The magnitude and scale of potential benefits of GHG mitigation will vary with the stringency of existing and proposed regulations (13). Where baseline conditions include relatively high ambient levels of pollution and unsophisticated technology, as with many rapidly developing countries such as Chile, México, and Brazil, the potential benefits of reducing emissions will likely be much larger than where baseline conditions already include fairly strict regulatory controls and advanced systems. Mitigation policies in cities that have little regulatory control will have a greater absolute impact than those in areas with well-established controls in place. To develop the scenarios in this analysis, we made a number of simplifying assumptions. We assumed that the fuel and technology mixes in the Latin American cities we assessed here were similar. Although São Paulo relied on ethanol fuels until the mid-1990s, that fuel is not expected to play a major role in the future. On the basis of recent trend information, we assumed that the concentrations of both PM₁₀ and O₃ would remain constant in these cities for the baseline scenarios. For Santiago, where progress is being made in the reduction of PM₁₀, we assumed a reduction of 3% per year in the concentrations of PM₁₀. Applying the 10% reduction to the projected concentrations for 2020 for México City, São Paulo, and Santiago, respectively, we project reductions of 6.4, 5.3, and 4.5 µg/m³ in the annual average of PM₁₀, and 11.4, 6.5, and 4.9 ppb in the annual average of daily 1-hr maximum O₃ by 2020.

In the analysis of air pollution-related impacts associated with GHG mitigation for New York City, a 10% reduction in O₃ and PM₁₀ from present baseline levels amounts to changes in the annual average concentrations of 3.9 ppb daily 1-hr maximum O₃ and 2.2 µg/m³ annual average PM₁₀. This assumed GHG-associated reduction in air pollution compares well with the only estimate that has been made to date regarding potential reductions that could arise from GHG mitigation in the United States. Abt Associates (6) recently estimated for the U.S. EPA that a GHG policy of applying a fee of $56/ton of carbon emitted would be associated with a reduction of between 0.4 and 2.7 µg/m³ PM_2.5 in the Midwest/Northeastern United States (or about 0.6 to 3.9 µm/m³ PM₁₀, assuming 70% is PM_2.5) when compared with various baseline emissions scenarios. (PM_2.5 is the mass of suspended particles less than 2.5 µm in aerodynamic diameter that can penetrate to the deepest recesses of the lung.) Thus, although New York City is very different from Santiago, the assumption of a 10% reduction from present PM₁₀ and O₃ levels in New York City appears reasonable. This is because this assumption is consistent with co-pollutant reductions previously projected to be associated with potential GHG mitigation measures in this region of the United States.

While the reductions in pollutant concentrations estimated here are similar between New York City and the Latin American cities, it must be noted that they might arise from very different policies. For developing countries, which are not required to abate GHGs under the Kyoto Protocol, the reductions stem from nonpositive cost measures of energy efficiency and fuel substitution, whereas for the United States, which is supposed to abate GHG emissions under the Kyoto Protocol, the reductions might result from the application of a carbon tax or other policies.

Health Effects Estimation Methods

E^J_P = [exp(ß^J_P · C_P) - 1] · Pop^J · BR^J₀.

ß^J_P is often referred to as the C-R coefficient of end point, J, associated to pollutant P. BR^J₀ is the base rate of effects, J, in the affected population Pop^J. For example, BR^J₀ might be the number of deaths per 100,000 infants less than 1 year of age during a baseline year. However, it is important to note that the affected population is not necessarily the whole population of a city. It can be separated by age groups (e.g., infants, adults, elder) or by health conditions (e.g., asthmatic population) among many possible divisions.

Table 1. Scope of human health effects of air pollution.a
Quantifiable health effects	Suspected health effects
Mortality (elder)	Induction of asthma
Mortality (infant)	Fetus/child developmental
	effects
Neonatal mortality	Increased airway
	responsiveness
Bronchitis: chronic	Nonbronchitis chronic
and acute	respiratory diseases
Increased asthma attacks	Cancer
Respiratory hospital	Lung cancer
admissions
Cardiovascular hospital	Behavioral effects
admissions	(e.g., learning disabilities)
Emergency room visits	Neurologic disorders
for asthma
Lower respiratory illness	Exacerbation of allergies
Upper respiratory illness	Altered host defense
	mechanisms (e.g.,
	increased shortness of
	breath susceptibility to
	respiratory infection)
Respiratory symptoms	Respiratory cell damage
Days of work loss	Decreased time to onset
	of angina
Moderate or worse	Morphologic changes in
asthma status	the lung
Days with restricted	Cardiovascular arrhythmia
activity
aAdapted from U.S. EPA (5).

Because ß^J_P is small, the previous equation can be linearized and expressed in the following terms:
 
 

where Pop is the total population of an area of analysis and IF^J_P is the health impact factor of pollutant P for end point J. It encompasses the relative risk, the base rate of the effect, and the relative size of the exposed population as a fraction of the total population. By expressing it this way, it is straightforward to compare the relative impact of pollution across different populations, and to compute the changes in health effects from the changes in concentrations and total population of a given city.

An important decision in the estimation of pollution effects involves the selection of pollutants for analysis. Incremental changes in mortality and morbidity associated with changes in exposures to PM have been documented extensively. A number of other common air pollutants, including sulfur dioxide, carbon monoxide, nitrogen oxides (NO_x), and O₃ have also been linked with various health effects. Inclusion of several pollutants in a single analysis simultaneously can lead to overestimation of the total effects if the C-R coefficients for each pollutant have been derived independently and the effects are added up later. Conversely, consideration of only one pollutant (PM₁₀, for example) to estimate the effects can underestimate the total air pollution effects, as several analyses show that the total risk of air pollution increases when more pollutants in addition to PM₁₀, such as O₃ and nitrogen dioxide (NO₂), are considered (16,17). In this analysis we considered two pollutants that have shown consistent and relatively independent associations with an array of adverse health effects: PM and O₃.

Ideally, the estimation of the change in health effects associated with concentrations in a given city should be based on studies conducted locally. However, local studies are not available for every health effect in every city. Therefore, we also use studies from other similar places, as available. For morbidity, C-R functions were derived from pooled estimates from the international literature when more than three studies were available. Random effects models were used to obtain a summary measure in this meta-analysis (18). For the case of O₃, studies taking into account the effects of PM₁₀ simultaneously were employed when available. Latin American studies were preferred for the cities in that region. Regionally relevant information was available for the acute effects of PM on mortality for each of the cities. For example, whereas New York City infant mortality and hospital admissions effects were estimated using U.S.-based studies, the Latin American cities' pollution effect on infant mortality was derived from México City (19), child medical visits from Santiago (20), and hospital admissions from São Paulo (21).

The effects of PM exposure on mortality have been derived both from time-series studies that evaluate the effect of several days of elevated or acute exposures on daily mortality and from cohort studies that evaluate the annual changes in mortality or morbidity associated with long-term, chronic exposures. Because the estimates from these two types of studies focus on different time frames, we used both types to indicate the likely upper- and lower-bound effects on mortality. Two main cohort studies of the general population have reported different central effect estimates, although their CIs overlap. We used the Pope et al. (22) and the Dockery et al. (23) studies to derive the central and high estimates of mortality, respectively. A recent reanalysis of these studies has been conducted by the Health Effects Institute and has confirmed their results (24). The lower bound of mortality effects were obtained from time-series studies, as shown in Table 2. Some have raised the issue that these studies may reflect life shortening of only a few days or weeks [sometimes referred to as "harvesting" (25)], but recent analyses have not borne out this assertion (26-28). The effects of O₃ on mortality in the Latin American cities were obtained from a meta-analysis of several studies.

Table 2. Studies considered in the analysis of the mortality effects of PM10 for México City, São Paulo, and Santiago.
All ages mortality	City	Age group	Relative risk for 10 µg/m3 increase in PM10 (95% CI) (percent)	Reference
Low estimate	México City	All	1.2 (1.1-1.2)	(33)
	São Paulo	All	0.85 (0.46-1.2)	(34,35)
	Santiago	All	0.7 (0.3-1.0)	(16)a
Mid estimate	All cities	> 30 years	3.5 (1.9-5.2)	(22)a
High estimate	All cities	> 25 years	6.8 (2.7-11.4)	(23)a
Infant mortality	All cities	< 1 year	4.0 (1.6-6.5)	(19)
aRelative risks were multiplied by 0.55 when the pollutant in the original study was PM2.5.

In New York, the health effects associated with the GHG mitigation-induced air pollution decreases were based largely on the C-R coefficients derived from the published literature for New York State by the Empire State Electric Energy Research Corporation (ESEERCO) as part of the New York State Environmental Externalities Cost Study (29). In some cases, however, alternative study results were used to define the bounds, such as in the case of PM₁₀-associated mortality. In this case, as for the Latin American cities, the Pope et al. study (22) of the effects of chronic PM exposure was used as the central estimate, the Dockery et al. study (23) was used to estimate the upper bound, and the results of a time-series PM study of the effects of acute PM exposure were used for the lower bound (as derived from the ESEERCO report). In addition, the ESEERCO C-R coefficients were updated with newer studies as appropriate, and studies conducted in or near New York State were chosen when available.

For each end point, we derived health impact factors (as defined above) specific for each city, as presented in Tables 3-5. Although some of the relative risks are similar for the cities, the impact factors differ because the population distribution of those affected differs between cities, as does the baseline rate of hospitalization and other end points. For instance, infant mortality impacts are higher in Latin American cities, in part because they have higher baseline rates. Conversely, the impact factors for adult health outcomes (e.g., work loss days and chronic bronchitis) are usually higher per million people for New York City than for the Latin American cities, largely due to the higher percentage of more frail, older individuals in this more-developed, lower birth rate city. In addition, this analysis assumes a higher percentage of the PM₁₀ is PM_2.5 in New York City versus the developing nation cities (70% vs 55%), which increases the impacts per µg/m³ of PM₁₀ reduction in New York City versus the other cities. To estimate the total health effects avoided during the next two decades, we applied the impact factors to the projected population and concentration changes, making the simplifying assumption that the current health conditions in these cities would prevail and that population would increase according to official projections, except in New York City, where a stable population size was assumed.

Table 3. O3 and PM10 health impact factors and CIs for New York City.
	Health impact factor per million inhabitants
Health effect outcome	Mid	95% CI	Reference
Ozone impacts (effects per part per billion of annual average daily 1-hr maximum ozone)
Acute mortality	1.2	(0.0-2.4)	(36)
Acute respiratory hospital admissions	5	(3-7)	(37)
Acute emergency department visits	40	(25-55)	(38)
Acute asthma attacks	1,005	(570-2,747)	(39)
Acute restricted activity days	17,000	(7,000-27,000)	(40,41)
Acute respiratory symptom days	50,000	(26,000-78,000)	(42)
PM10 impacts (effects per microgram per cubic meter of PM10)
Acute and chronic infant mortality	0.21	(0.1-0.3)	(43)
Acute and chronic adult mortality	33	(8-52)	(22)
Acute respiratory hospital admissions	12	(7-17)	(44)
Chronic adult bronchitis	39	(19-59)	(45)
Acute bronchitis in children	53	(26-78)	(46)
Acute emergency department visits	94	(55-130)	(38)
Acute asthma attacks	774	(446-2,589)	(39)
Acute work loss days	5,300	(2,700-8,300)	(47)
Acute restricted activity days	14,900	(7,616-23,509)	(48)
Acute respiratory symptom days	170,000	(81,000-259,000)	(42)

Table 4. PM10 health impact factors (with 95% CIs) developed for México City, São Paulo, and Santiago.a
		México City		São Paulo		Santiago
End point	Age group (years)	Mid	95% CI	Mid	95% CI	Mid	95% CI	References
Mortality effects
Mortality	Allb	21	(7-41)	20	(2-39)	12	(2-23)	See Table 2
Infant mortality	< 1	2.2	(0.9-3.6)	1.2	(0.5-2.0)	0.9	(0.4-1.5)	See Table 2
Chronic morbidity effects
Chronic bronchitis	> 30	26	25.6	21.1	(8-43)	20.9	(6-36)	(49)
Hospital admissions
Cardiovascular causes	All	2.4	(2-3)	2.4	(2-3)	2.4	(2-3)	Pooled from Los Angeles (50), Ontario  (51), Detroit (52), Michigan (53), Chicago (54)
Respiratory causes	All	5.7	(4-8)	5.7	(4-8)	5.7	(4-8)	Pooled from California (55), Ontario (51), Paris (56), London (57),  Amsterdam (58), Rotterdam (58),  Cleveland (59), Buffalo (37), New  York (37), Ontario (60), Milan (61),  Los Angeles (50)
Children: all causes	< 13	3.2	(2-5)	8.2	(4-12)	8.2	(4-12)	São Paulo (21)
Other hospital visits
Emergency room visits	All	141	(0-351)	93	(0-232)	93	(0-232)	Pooled from London (62), México (63),
								Quebec (64), Steubenville (65)
Children: medical visits	3-15	63	(14-112)	155	(34-275)	83	(18-147)	Santiago (20)
Morbidity effects
Asthma attacks	All	668	(161-1,175)	668	(161-1,175)	668	(161-1,175)	(39)
Children: acute bronchitis	8-12	65	(0-145)	64	(0-143)	62	(0-138)	(46)
Restricted activity
Work loss days	18-65	3,655	(3,095-4,216)	3,965	(3,357-4,573)	3,657	(3,096-4,217)	(47)
Restricted activity days	18-65	10,539	(9,287-11,792)	11,431	(10,073-12,790)	10,543	(9,291-11,796)	(47)
aEffects per million people per microgram per cubic meter PM10. bThe age groups considered vary according to the estimate (see Table 2 for details).

Table 5. Ozone health impact factors and 95% CIs developed for México City, São Paulo, and Santiago.a
		México City		São Paulo		Santiago
End point	Age group (years)	Mid	95% CI	Mid	95% CI	Mid	95% CI	References
Acute mortality
Total	All	1.9	(1.0-2.7)	1.8	(1.0-2.7)	1.0	(0.2-1.7)	México City and São Paulo: pooled from London (66), México (67), México (33), Chicago (68), Phila delphia (69,70), Amsterdam (71), European cities (72), Rotterdam (73). Santiago: summer (16)
Hospital admissions
Respiratory causes	All	15	(2-29)	15	(2-29)	15	(2-29)	Pooled from Buffalo (37), New York (37), Ontario (60)
All causes: children	< 5	0.29	(0.03-0.55)	0.65	(0.07-1.23)	0.50	(0.05-0.94)	Brazil (74)
Other hospital visits
ERV for RSP causes	All	144	(76-212)	95	(50-140)	144	(76-212)	Pooled from Montreal (64), México (75), Ontario (17)
Morbidity effects
Asthma attacks	All	1,140	(0-2,745)	1,140	(0-2,745)	1,140	(0-2,745)	(46)
Restricted activity days	Adults	11,781	(8,036-13,678)	12,779	(8,716-14,835)	11,786	(8,039-13,683)
ERV for RSP, emergency room visits for respiratory causes. aEffects per million people per part per billion per cubic meter annual average daily 1-hr maximum O3.

Results

Figure 1. Health effects avoided from 2000 to 2020 in the four cities analyzed if GHG mitigation measures are taken.

The effects in children are also important to note. Premature deaths of infants less than 1 year of age (including neonatal mortality) that can be avoided amount to 4,100 (95% CI 1,600-6,700). In addition, more than 161,000 (95% CI 0-350,000) cases of acute bronchitis in children 8-12 years of age as well as 202,000 (95% CI 45,000-360,000) medical visits of children 3-15 years of age could be avoided. (This last effect was evaluated only in the Latin American cities.)

Discussion

We believe that our analysis is conservative for various reasons. First, we assumed no major changes in technologies for transport, energy, and commerce in the next two decades. Some air pollutants (such as O₃, some aromatic hydrocarbons, and NO₂) continue to increase in many metropolitan regions; their full impact is not assessed in this analysis. In addition, we could not include estimates of synergistic effects between various air pollutants, or with cofactors such as pollen and other allergens. New studies have indicated that synergies can occur between air pollutants and allergens. Thus, for example, British analyses show that physician visits for asthma and allergic rhinitis are increased more than additively when both pollen and air pollution levels are elevated (30). We also did not consider effects tied with cancer (31) and other diseases linked with exposures to pollution and other airborne toxics, which are not usually monitored and can be quite high in rapidly developing areas (32).

The rapid pace of urbanization globally means that more people are living in large cities than at any point in human history. Policies that increase energy efficiency and promote less carbon-intensive fuels can yield a broad array of benefits by simultaneously improving local and regional air pollution and reducing the long-term buildup of GHG. Given the current and projected patterns of population growth and air pollution concentrations, the cumulative potential impact on public health from fossil fuels for the next two decades is quite high for any of the cities analyzed. Part of this burden can be avoided if GHG abatement policies to reduce the net use of fossil fuels are adopted. For Santiago and the other cities, the adoption of currently available technologies in energy, transport, residences, and industry can reduce population exposure to air pollution by at least 10% by 2020, yielding the associated public health benefits we have presented. Similar types of health impact reductions are expected to occur in other developing world cities if GHG emissions mitigation policies are also implemented in those cities.

This current collaborative analysis stems from an effort to integrate into the public discussion of GHG mitigation policies a consideration of what these policies might mean for public health in the nearer term. We fully recognize that population patterns can be changed by events not integrated into this assessment. We also are not unaware of promising technologies, such as fuel cells for energy production and transportation applications, that might substantially alter air pollutant emissions in the future. The estimates developed here are offered to illustrate the potential scale and scope of impacts. A fuller accounting would likely show still greater public health and natural resource benefits than this preliminary assessment.

Conclusion

The estimates of the potential public health benefits from the adoption of GHG mitigation policies offered in this paper were developed opportunistically, incorporating results from a variety of studies conducted for different purposes. While it must be acknowledged that there is still much that remains to be learned about the intricacies of climate change and the respective (and potentially interactive) roles of the various air pollutants, the numbers developed for these four cities illustrate the magnitude and scale of the air pollution impacts that may be averted by implementing GHG mitigation measures, according to current understanding. As pressures mount for actions to be taken to reduce GHG emissions, decisions being made in the next decade will affect the forms of energy production and transportation systems that will fuel this century in many regions. Further, efforts to promote a sounder accounting of how these technologies will affect public health must be encouraged. The failure to provide a fuller tally of potential health damages tied with air pollution in the discussions of GHG mitigation policies not only limits the utility of those discussions but also fails to meet a basic human concern. People care greatly about their health and the health of their children. Decision makers need to be well informed about the extent to which global climate policies adopted today can be expected to affect public health in both the near and long term.
 
 

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Last Updated: June 8, 2001