Tessa needs 10.0 apples to make a pie.  She has 5.0 apples but Anita eats 4.0 of them.  How many more apples does she need? Answer:

Question: There are several books on a bookshelf. If one book is the 4th from the left and 6th from the right, how many books are on the shelf?
Answer: 9. Try sketching the problem out to see it.
Haha. There could also be seventeen in that case.

John is three times younger than his father, but two times older than his brother Jim. How old is John if Jim is 40 years younger than his father?
Answer: John is 16 years old.
Let X be John’s age, F be father’s age, and J be Jim’s age. Then, 3X=F, X/2 =J, and J+40=F. Solving this system of three equations for X, we get X=16.
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Joe’s code has 20 bugs. If Joe fixes 2 bugs per hour for 8 hours, how many bugs does Joe’s code have now? Answer: 27.

Question: Mr. Paige is an only child. Mr and Mrs Paige have 3 daughters and for each daughter in the family there is a brother how many members are in the Paige family?
Answer: 9, because including Mrs. Paige there is 4 daughters.
Mrs. Paige's brother is not a Paige, so only 8.
For each daughter in the family there is a brother. It is not referring to Mrs. Paige's brother, it is referring to a brother in the family (i.e. a son of Mr. and Mrs. Paige), so the answer is 9.

A nurse put 100 gloves into 4 containers. She puts gloves in the containers in such a way that each container has two more gloves than the one before. How many gloves are in each container?
Answer: 22, 24, 26, and 28 gloves.
Let X be the number of gloves in the first container. Then there are X+2 gloves in the 2-nd container, X+4 gloves in the 3-rd container, and X+6 gloves in the 4-th container. Hence, we have X+X+2+X+4+X+6=100. Solving for X, we get X=22 gloves in the first container, 24 gloves in the 2-nd container, 26 gloves in the 3-rd container and 28 gloves in the 4-th container.
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Explanation: Being able to calculate with negative integers is a valuable skill. Using a number line is helpful and you may want to have one available while you complete these problems. Moving left on a number line indicates adding a negative number.
- 2 + _ = 7 You started at - 2 and ended at 7. What did you add? Answer: 9 Easy!
4 + _ = - 4 You started at 4 but ended at - 4. What did you add? Answer: - 8 Easy!
Directions: Use the number line to find the missing number. Strive for understanding the topic, strive for accuracy and then strive to increase your speed. Good luck and enjoy the challenge!

5 lizards are on the ceiling. 3 of them decided to jump on a person passing by. How many lizards are left on the ceiling?
Answer: 5. Deciding to do something isn’t the same as taking action.
It’s easy to declare those things. Much harder to follow through and actually do it.
Making a decision is nice. But execution is where life happens.
PS: I hate lizards. I hope none will ever jump on me or you.
just subscribe your blog. so inspiring and motivating.
looking forward to work with you ulit Sir.

Question: There are five fish in a fish tank. Two swim away, one swims towards the ocean, and two die. How many fish are left in the tank?
Answer: Five. They never left because can’t get out of the fish tank.

Question: A hobo picks up cigarette butts from the ground and can make a cigarette with 4 butts. If he finds 16 cigarette butts, how many cigarettes can he make?
Answer: 5. He makes 4 cigarettes with the 16 butts. Then he smokes them and has 4 more butts to make another cigarette.

How many teaspoons of dried apricots in 3/4 gram?
How many teaspoons of dried apricots in 3/4 gram?
(*) or precisely 0.18949 US teaspoon. All values are approximate.

UCLA and ASU face off in a PAC 10. Spoiler there is a perfect 10!
Nice 10.0 by Madison Kocian on bars!
WOW The wedgie on Jessica Ginn by the end of her floor routine is mouth watering.

How many people in a kendo match?
How many people in a kendo match?
How many people in a kendo match?
Answer: Thank you for your question. And I am so sorry for the delay and my reply.
Even in a team fight, we fight individually. It is one person vs. one person. Usually in team fight, we have three or five team members. And they fight individually.

Investment Implications of the U.S. Election - Epoch Investment Partners, Inc.
On November 9, 2016, the U.S. elected Donald Trump to become the country’s 45th President. The balance of power in congress remained unchanged with the Republicans retaining a majority in both the House and Senate.
The election of Donald Trump was a surprising outcome that can be viewed as a rebellion against the policy consensus of the past 30 years. The election of an antiestablishment candidate introduces greater uncertainty and risk into the markets. There are a number of areas of concern for us, based on the rhetoric espoused on the campaign trail, particularly the anti-trade sentiment and potential for trade spats. In addition, markets generally prefer some diversity in the balance of power in Washington, not one party controlling both the executive and legislative branches. Finally, the election of a populist candidate in the U.S. may bolster the support for similar candidates in the European Union, introducing additional uncertainty into those markets.
On the flip side, there are a number of potential policies and initiatives that may be beneficial for investors. For example, looser fiscal policy could act as a stimulus to growth, corporate tax reform may lead companies to repatriate huge sums of capital currently sitting abroad, and deregulation may benefit sectors such as financials, health care and energy.
Ultimately, the election has not changed our core outlook for diminished global growth prospects. We are in a period of secular stagnation. Much of that is driven by demography, and demography is, in the end, destiny. GDP is made up of growth in the workforce plus productivity growth. Measured productivity growth in the U.S is currently running around zero. Growth in the workforce is somewhere between 1% and 1.5%. Combined, this shows why we have been saying for some time that 2% (GDP growth) is the new 4% for developed economies. The good news is that wages are growing at a rate of 2% to 2.2%. While not a huge growth rate, it is growth nonetheless.
President-elect Trump’s policies are likely to mean higher bond yields, principally because we are going to see a substitution of fiscal policy for monetary policy. First, real bond yields have been trending down for 30 years. Currently, real yields are touching zero and we believe the chances of that continuing are small. We will likely remain in a lower-for-longer rate environment, but it is unlikely that we will the see the yield curve shift down again. What is more likely is that there will be modest increases in the short end and, depending on how much debt is needed to finance some of Trump’s stated plans, you could see a rise in the long-term rate as well.
The market is still pricing in a 78% percent probability that the Federal Reserve will hike rates in December and this did not change much in the closing days of the election or following the outcome. We are likely to see some fiscal policy expansion, which would result in 10-year yields rising. In this type of environment, the U.S. dollar could appreciate. We believe that most other central banks will remain on hold for some time, so a Fed that is in a modest rate-hiking cycle could benefit the dollar.
One factor that will be important for determining monetary policy is the composition of the Federal Reserve Board of Governors and there will some important changes to it over the next year or so. The first change would be to the Chair of the Board. Current Chair Janet Yellen’s term expires on February 3, 2018. President-elect Trump had been highly critical of her during the campaign process. It is unprecedented for a sitting chair to resign following a change in government, so we do not think that will happen, but it is also unlikely that she would be reappointed for another term. Additionally, two of the seven positions on the board are currently open. Given the Republican sweep, it is likely that the President’s appointments would be easily confirmed and those nominees should tend toward the hawkish side. Overall it appears that we will be in an environment where both the long short ends of the yield curve will likely be going up (modestly) coupled with some of US dollar appreciation.
President-elect Trump talked often about fiscal expansion but did not provide many details on what that might look like. One benchmark might be Secretary Clinton’s proposed plans. She spoke about $275 billion of spending, which alone is a huge number, but in the context of U.S. GDP ($19 trillion) is not all that big. In addition, that money would be spent over five years, which amounts to about 0.3% of GDP per year. At the same time, state and local governments are reducing their own investments due to budgetary pressures. Given these factors, we believe that net total government spending will grow over the next couple of years, but not by an eye popping number. Nonetheless, this could be boost to GDP, albeit a small one.
What’s more important, as it relates to policy, is corporate tax reform. President-elect Trump spoke passionately about the need for corporate tax reform, which is long overdue. The last time that the U.S. had comprehensive reform was 1986. President-elect Trump indicated his intention to reduce the headline corporate tax rate from 35% to something closer to 15%. Most people, however, believe that something closer to 20% is possible. This change would have a number of implications, the largest of which would be hundreds of billions of dollars being repatriated, similar to what happened following the 2006 Homeland Investment Act. This influx would leave many companies awash with cash and, given that they need less of it to generate a dollar of revenue today, it would likely boost the levels of dividends, buybacks and debt reduction.
Antitrade sentiment was a recurring theme of presidential campaign rhetoric and President-elect Trump’s voice was often the loudest. He maintained that trade agreements typically result in fewer jobs and lower wages for U.S. workers. Historical evidence suggests otherwise, as we detailed in our paper The Case for Trade Remains Overwhelming (May 2016). Global trade, despite some of its failures, has delivered remarkable returns to investors over the past 30 years, particularly equity investors. So, it’s hard to see how blowback against this investor-friendly policy can be good for investors. We acknowledge, however, that with globalization, there is often a proportion of the labor force that is hurt profoundly. Further, the U.S. and other developed markets have not done a good job of working to help these people through skill training and income support.
Even before Trump’s election, protectionists had already succeeded in beginning to turn back the globalization clock. Over the past eight years, protectionist policies have expanded globally and, in our view, this proliferation has helped to bring about the longest period of trade stagnation since World War II. The election of Mr. Trump will likely to extend this period, and the degree of further stagnation depends on what his intentions are in terms of renegotiating or canceling existing trade pacts such as the North American Free Trade Agreement and in increasing tariffs against countries such as China and Mexico. Such outcomes could trigger renewed global trade spats, with a detrimental impact on the global economy and financial markets. Further, the chances of ratifying trade agreements that are now being negotiated, such as those with Asia or Europe are extremely unlikely.
While an environment of low growth and low inflation is not great for financials, we are likely to see short rates, and possibly long rates, go up, as mentioned. This would create a mild tailwind for the financial sector. More importantly, the Trump administration will be less inclined to introduce the types of regulation on the sector that Secretary Hillary Clinton intended to enact. This is particularly true in relation to systematically important financial institutions. In addition, the sector appears cheap, especially some of the smaller regional institutions. Ultimately, however, for robust strength in the sector we need to see strong loan growth, particularly commercial and industrial loan growth. We have been seeing some signs of that, but the outlook does appear to be uncertain.
Health care will remain a deeply divisive issue. President-elect Trump has been a harsh and caustic critic of the Affordable Care Act, but has not been clear on what he would like to replace it with. He has spoken quite a bit on the other issue facing the sector, pharmaceutical pricing. Based on his comments, it is likely that there will be interventions from a Trump administration, but they will less harsh than what we would have seen from a Clinton administration. This could be considered a positive for the sector, but negative public sentiment and growing competition within the industry will make it difficult for companies in that space to raise prices. In our minds, though, the re-rating that the sector has experienced appears to be overdone. The sector looks cheap and it does possess solid cash flow growth potential going forward.
President-elect Trump feels strongly about the energy sector and thinks that a friendlier regulatory environment can help the sector grow and create jobs. Support for the sector will likely increase the supply of U.S. oil. This will have the effect of creating domestic jobs and pushing down the price of WTI..
Despite the increased risk and uncertainty created by this election and potential growth stimulating policy initiatives, our core outlook remains unchanged. Growth is likely to remain in a lower 2% range than its historic 4% range for the foreseeable future. As quantitative easing winds down and rates rise, the support for PE expansion will diminish. With stagnant or contracting PE multiples the other two components of equity return, dividends and earnings, will become more important for investors. The companies that will do well are the ones that generate cash flows and are prudent in their capital allocation policies, as reflected in shareholder yield and capital investment opportunities. As we have said many times, the value of a company is driven by its cash flow.

If Starla paid $40.00 before tax, how many napkins did she buy? A.
Drag each equation to the correct location on the model. Not all equations will be used.
Arrange the steps to show how to solve for x.

We are still in the strange glow of this over-victory, and we are still holding the microphone, with our thuggy athletes, our apologetic rapper, our unapologetic socialist, our fugitive. But what does it all mean? Is there something to it, something deeper? Or is this just a concentrated series of accidents that has no meaning?
Combine that shining symbol of open collaboration with the progressive optimism of coach Pete Carroll, the surprising talent of the young, big-hearted Russell Wilson and the quiet, “all ’bout that action” work ethic of Marshawn Lynch and it starts to look like whatever the Seahawks proved about themselves at that Super Bowl, they also proved about their city.
Clearly, our region punches above its weight. Super Bowl victory notwithstanding, the Seattle Times observed a few weeks ago that we’re a “Beta” city that has spawned a disproportionate number of global brands that have changed the world: from [Jeff] Bezos’ online retail giant [Amazon] to Microsoft, Boeing, Starbucks, Costco and so much more. No wonder that as Bloomberg Global Tech recently surveyed innovation across the United States, it put Washington State at the top of the list. It’s fundamentally a “Go West Young Man” freedom to make new rules, and break old ones, even as we foster a strong sense of community in our remote corner of the United States.
(1) We’re co-hosting the local launch of global PR agency Edelman’s influential 2014 Trust Barometer report (which I wrote about in my Storyteller Uprising book) on Tuesday, Feb 11 at 6:30 p.m. at the UW Club.
This event is co-sponsored by the PRSA and IABC. I’m giving introductory remarks, then introducing David Brain, Edelman’s CEO of Asia-Pacific, Middle East and Africa (flying in from London for this) who will keynote.
(2) I’m emceeing the IN-NW Social Media & Digital Marketing Conference Presented by Google that we host every year with the Seattle Chamber (co-organized with 206inc, sponsored by our friends at Weber Shandwick) Registration: http://in-nw.com, Wednesday, Feb 12 9 a.m., Showbox SODO. This one is definitely worth your while (or your organization’s investment).
(3) I’ll be keynoting a closed-door Chief Marketing Officer roundtable at the end of this month. They’ve asked me to provoke a conversation about the shifting agency business model as marketing, PR, digital, advertising all blend together…the role of the professional communicator is truly expanding, especially with the Second Machine Age upon us. Weber Shandwick’s extraordinary addition to Ad Age’s “A-List” this week because of its content marketing success is testimony to this shift, as communications merges with marketing.
I’ll also be at at our graduate program’s First Friday reception with our friends at 206inc on Friday at 5:30 p.m. They’ve been our collaborators for 3 years on the IN-NW conference (see #2).

The availability of high-performance and low-cost desktop computing systems and digital camera equipment has given rise to a public interest towards applications that include the visual identification of human individuals. Examples for such applications are surveillance, biometrical identification or computer-human interaction. To that effect, research in biometrical technologies follows naturally. Above other methods, images of human faces offer a non-intrusive and easy-to-use means of identification. Although the recognition of faces is a problem that is effortlessly solved by human beings during their daily routine, it poses a challenge for researchers and scientists. Boundary conditions like illumination and occlusion, as well as pose and expression of an individual lead to intrapersonal variations that often exceed those between images of different persons under similar conditions.
In association with Falcontrol Security GmbH we are researching reliable face recognition algorithms by using Bayesian methods on infrared image data.

You are here: Home / General / Home Brewing Recipes – Find Them or Invent Them?
Home Brewing Recipes – Find Them or Invent Them?
Brewing beer at home is a hobby that many men and women enjoy. It is an opportunity to create new flavors and try out something different. The problem is that many individuals struggle with the decision to make up personal recipes or follow the recipes of others. The final choice is made based on personal preferences, but most beginners are recommended to find and use other recipes.
Any beginner to brewing should start by finding recipes because it is important to understand the basic processes of brewing before trying to create something new. If the process is still slightly confused, then it is easy to end up creating a beer that does not taste good.
Replicating an existing recipe for brewing will make it easier to learn how different ingredients react based on when it is added and the particular items used. The experience and the order adding ingredients to the brew makes it possible to learn about the brew before making any attempts to create something new.
Beyond simply learning the basics, trying out a wide range of recipes others have created will make it easier to identify preferred tastes and avoid options that create an unpleasant taste in the mouth. Discovering preferred ingredients and flavors will make creation of a new recipe later much easier.
While beginners will find that using other recipes is important for learning the process, even experienced brewers can benefit from finding recipes rather than making up a new recipe. The key benefit of using an existing recipe is learning different brewing techniques and identifying the preferred techniques based on the experience of others and the practice using an existing recipe.
Different types of brews require various techniques, equipment and ingredients. The use of existing recipes provides the opportunity to learn more about personal abilities and preferences based on experience. Creating a new recipe always starts with the basics and works out to the addition of something new.
Finding a recipe is not only about the techniques or learning the basics, it is also about having a consistent outcome. Following a recipe will always have the same result. This is not the case when trying to create a new recipe because the creation of a brew will require trial and error to get the measurements right and to determine the best ingredients. The results will often end up different than the previous batch and often the inconsistent results will have an unpleasant taste in the beginning the process.
The benefit of consistent results is that trial and error is not part of the equation. The existing recipes have already worked out the best ingredients for the taste and the appropriate measurements to bring out the best in the brew.
When the goal is getting the same result as the last time, the existing recipes are ideal. It makes it easier to enjoy the brew as often as preferred without the potential to change the taste due to putting in a little too much or too little of certain ingredients.
While the obvious benefits of learning and consistency make the option to find recipes a good choice, it is the time problem of inventing new recipes that often dictates the decision.
Brewing at home is an enjoyable hobby, but time constraints in a busy society often limit the amount of time available to make the brew. Inventing a new recipe takes more time because it is about trial and error, which ultimately makes the hobby harder to fit into a schedule. If time is a problem, then finding the recipes is the best solution.
Recipes for home brewing are usually the best option for those who are busy and for beginners. Advanced home brewers can work on inventing the brews if enough time is available for the process, but the decision to find or create a new recipe is ultimately a personal choice.

Ready, steady, reset! The Sun is in Aries, the zodiac’s first sign, from March 20-April 19. Aries is a go-getter, the sign of solo ventures and independent pursuits. We’re impatient, eager and sometimes a little rushed during Aries season, wanting to seize every moment NOW. For parents, this is a time to stay on your toes, as the pace of life speeds up. For children, it’s a great time to express individuality and explore what makes them unique. Since Aries is ruled by energetic Mars, families can become more active under this physical sign—just in time for spring.
Flower essences to calm and manage 12 common emotional patterns in children, by Bach Flower practitioner Kerri Aab of Seed to Blossom.
You’re dynamic and independent––play to your strengths––but you can be impatient and a little hot-tempered, so be mindful of your challenges, too.
Lace up your sneakers: the on-the-go Aries child will keep you active all day. There’s never a dull moment with the pint-sized Ram, so learn all about your little Aries here!
Decoding your Aries––a peek into the “owner’s manual” for your child. Who says kids don’t come with instructions? Read a sample chapter from our Momstrology book.
Inspiration for art projects and delightful items that appeal to this fiery sign.

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Some studies have noted an association between maternal occupational exposures to chlorinated solvents and birth defects in offspring, but data are lacking on the potential impact of industrial air emissions of these solvents on birth defects.
With data from the Texas Birth Defects Registry for births occurring in 1996–2008, we examined the relation between maternal residential proximity to industrial air releases of chlorinated solvents and birth defects in offspring of 60,613 case-mothers and 244,927 control-mothers. Maternal residential exposures to solvent emissions were estimated with metrics that took into account residential distances to industrial sources and annual amounts of chemicals released. Logistic regression was used to generate odds ratios and 95% confidence intervals for the associations between residential proximity to emissions of 14 chlorinated solvents and selected birth defects, including neural tube, oral cleft, limb deficiency, and congenital heart defects. All risk estimates were adjusted for year of delivery and maternal age, education, race/ethnicity, and public health region of residence.
Relative to exposure risk values of 0, neural tube defects were associated with maternal residential exposures (exposure risk values >0) to several types of chlorinated solvents, most notably carbon tetrachloride (adjusted odds ratio [aOR] 1.42, 95% confidence interval [CI] 1.09, 1.86); chloroform (aOR 1.40, 95% CI 1.04, 1.87); ethyl chloride (aOR 1.39, 95% CI 1.08, 1.79); 1,1,2-trichloroethane (aOR 1.56, 95% CI 1.11, 2.18); and 1,2,3-trichloropropane (aOR 1.49, 95% CI 1.08, 2.06). Significant associations were also noted between a few chlorinated solvents and oral cleft, limb deficiency, and congenital heart defects. We observed stronger associations between some emissions and neural tube, oral cleft, and heart defects in offspring of mothers 35 years or older, such as spina bifida with carbon tetrachloride (aOR 2.49, 95% CI 1.09, 5.72), cleft palate with 1,2-dichloroethane (aOR 1.93, 95% 1.05, 3.54), cleft lip with or without cleft palate with ethyl chloride (aOR 1.81, 95% CI 1.06, 3.07), and obstructive heart defects with trichloroethylene (aOR 1.43, 95% CI 1.08, 1.88).
These findings suggest that maternal residential proximity to industrial emissions of chlorinated solvents might be associated with selected birth defects in offspring, especially among older mothers.
Oxidative stress has been suggested as a mechanism by which some teratogens cause birth defects, and several chlorinated solvents, such as carbon tetrachloride, chloroform, methylene chloride, and trichloroethylene, have been identified as inducing oxidative stress through giving rise to reactive oxygen species. These compounds have been widely used as solvents for industrial processes, such as metal degreasing and dry cleaning, and for the production of pharmaceuticals, pesticides, adhesives and refrigerants. Findings from several experimental studies of animal models have indicated significantly increased prevalence of various congenital malformations, including exencephaly, musculoskeletal defects and cardiac defects with exposures to some chlorinated solvents[4–8]. These findings were not corroborated, however, by other investigators with experimental studies of rodents exposed to methylene chloride, methyl chloroform, perchloroethylene, and trichloroethylene[9, 10].
Several epidemiologic studies have examined the relation between maternal occupational exposure to various chlorinated solvents and birth defects in offspring[11–14] with associations noted between these compounds and cleft lip with or without cleft palate, spina bifida, limb defects, and heart defects. Very limited information has been published on the relation between residential proximity to industrial air releases of chlorinated solvents and birth defects. Yauck et al. examined whether living near industrial facilities in Wisconsin (USA) with trichloroethylene (TCE) emissions increased the risk of congenital heart defects in offspring. Mothers who lived within 1.32 miles of the TCE-emitting facilities had a three-fold excess risk of congenital heart defects, but this association was restricted to mothers aged 38 years and older. Two studies conducted in Texas (USA)[16, 17] found no elevated risk of oral cleft or conotruncal heart defects among offspring born to mothers who lived within 1 mile of any industrial facility with reported air emissions of solvents. Increased odds ratios for isolated oral clefts, especially for cleft palate, were noted among offspring to mothers 35 years or older in the Texas study population, although the 95% confidence intervals for the odds ratios were compatible with the null. In the same study population, residential proximity to industrial facilities with solvent emissions was modestly associated with neural tube defects, and a stronger association was noted in offspring of older mothers. The aforementioned studies of potential maternal ambient air exposures to chlorinated solvents and birth defects did not take into account residential proximity to multiple sites nor the amounts of chemicals released from each of the facilities. Furthermore, the study populations tended to be small, thereby limiting examination of associations of birth defects with specific chemicals by maternal age.
In the present study, we examined whether maternal residential proximity to industrial air emissions of chlorinated solvents was associated with neural tube, oral cleft, limb deficiency, and congenital heart defects in offspring. We accounted for residential proximity to multiple facilities and the annual amounts of specific chlorinated solvents released from each. We also examined whether older maternal age modified associations between residential proximity to chlorinated solvent emissions and birth defects with one of the largest study populations to date.
Live births, fetal deaths, and induced terminations with selected congenital malformations, including neural tube defects, oral cleft defects, limb deficiencies, and congenital heart defects, were identified from the Texas Birth Defects Registry (TBDR) for births occurring during 1996–2008. The Registry used active surveillance in which trained staff reviewed medical records from hospital, birth centers, and midwifery locations. TBDR covered all cases that were live births, spontaneous fetal deaths (reportable in Texas if 350 grams or more or length of gestation 20 weeks or greater), and pregnancy terminations. Cases were selected in the study if they were delivered between 1996 through 2008, had a maternal address in Texas at time of delivery, and had a diagnosis of one or more of the selected birth defects. The majority of case deliveries were live births (97.1%) with 1.4% classified as spontaneous fetal deaths, 1.5% induced terminations of pregnancy, and 0.1% unspecified fetal deaths. Live birth and fetal death cases were linked to their respective birth or fetal death certificates that contained information about maternal residential address at the time of delivery and demographic characteristics.
Birth defects were further classified as either isolated or not isolated. Isolated defects were defined as those having a single major defect alone or together with one or more of a list of minor defects used in the National Birth Defects Prevention Study.
Control-births, defined as live births without any recorded birth defects, were randomly selected from live birth certificate data obtained from the Center for Health Statistics at the Texas Department of State Health Services. These births were frequency matched to cases by year of delivery (1996–2008) and public health service region (11 regions) in which the case-mothers resided at the time of delivery. We frequency matched birth defect cases and controls by public health region because between 1996 and 1999, active surveillance of birth defect cases did not occur statewide, but was confined to certain regions, including 2 regions in 1996, 6 regions in 1997, and 8 regions in 1998. These regions range from 12,060 (Region 5) to 61,456 square miles (Regions 9/10 combined).
ESRI ArcGIS 8.3 ArcMap 9.3 was used to geocode the maternal addresses obtained from live birth and fetal death certificates. A total of 86.7% of the maternal addresses for case-mothers and 87.2% for those of control-mothers were successfully geocoded to street level.
Data regarding air emissions from Texas industrial facilities were obtained from the U.S. Environmental Protection Agency Toxic Release Inventory (TRI) program. The online TRI databases contain names of facilities required to report under section 313 of the Emergency Planning and Community Right-to-Know Act and include information about location, reporting year, chemicals released, and estimated pounds per year released into various environmental media, such as air and water bodies. For the present project, industrial air releases of 14 chlorinated solvents were identified for study, including carbon tetrachloride; chloroform; 1,1-dichloroethane; 1,2-dichloroethane; 1,2-dichloroethylene; ethyl chloride; methyl chloroform; methylene chloride; perchloroethylene; propylene dichloride; tetrachloroethane; 1,1,2-trichloroethane, trichloroethylene; and 1,2,3-trichloropropane.
Based on the addresses available in the USEPA TRI databases, we geocoded the TRI facilities in three steps. The addresses were first geocoded using Centrus Geocoder for ArcGIS. Then, the TRI addresses that were not geocoded in the first step were geocoded by the default geocoding tools from ArcGIS 10.0 using the Census 2000 street map as the reference layer. Finally, the remaining TRI addresses that were not successfully geocoded using the first two methods were geocoded with Google map geocoding API. Only TRI addresses geocoded to the premise level were considered successful matches. Over the 13 year period of 1996–2008, approximately 90% of the industrial facilities, on average, were successfully geocoded.
To estimate potential intensities of various chlorinated solvent air releases in the vicinity of maternal residences, a modified version of the Emission Weighted Proximity Model (EWPM) was used. This model takes into consideration emissions from all sources within a 10-km effective threshold potentially affecting a person at a specific location and the amounts of chemical released from each source during a given time period. The formula for calculating the combined quantity of air pollutant θ at location i from all emission sources is given by Expression (1).
where A θ i is the estimated quantity of air pollutant θ at location i from all emission sources j (j = 1, 2, ……, m) within the threshold distance. This quantity was used as a proxy to represent the exposure risk value of a person at location i to air pollutant θ; m is the number of emission sources relevant to a person at location i in the area in question; E θ ij is the emission rate of air pollutant θ from any emission source j that is within the effective threshold distance related to location i; T θ ij is the duration of emission of air pollutant θ from emission source j; k θ is effective threshold distance beyond which air pollutant θ is considered to have no harm to an individual and is determined by the physical and photochemistry characteristics of the pollutant in question; and D ij is the distance between location i and location of j. Based on Expression (1), an exposure risk value for each of the 14 chlorinated solvents was assigned to case- and control-mothers based on their residence location at the time of delivery. The TRI facilities and maternal addresses were linked through the EWPM. Given the effective threshold distance, only the facilities within the distance of a maternal address were considered to have potential harm on that person.
The EWPM exposure risk values were categorized into two groups (exposure risk values for a given solvent equaling zero or greater than zero) and four or seven levels (exposure risk values at zero and greater than zero divided into three or six equal groups) based on the control-mothers distribution of scores. In the analyses with more than two categories of exposure risk values, the number of categories used (4 or 7) depended on the numbers of cases available. We used logistic regression to examine the relation (odds ratio [OR] and 95% confidence interval [CI]) between maternal residential exposures to chlorinated solvents and neural tube defects, oral clefts, limb deficiencies, and selected heart defects in offspring. The lowest level of exposure risk value served as the referent group for all analyses. In the analyses of odds ratios associated with varying intensities of exposure risk values, the Wald statistic was used to test for significance of linear trends. To reduce potential confounding, the ORs were adjusted for the year of delivery (1996–2008), maternal age (<20, 20–24, 25–29, 30–34, 35–39, >39 years), education (<12 years, 12 years, >12 years), race/ethnicity (white non-Hispanic, black non-Hispanic, Hispanic, other non-Hispanic), and public health region of residence (11 regions in Texas).
Because sufficient numbers of exposed cases were available, analyses of the association between chlorinated solvents and oral clefts were restricted to isolated defects. Analyses of the other types of birth defects included all identified cases. Heart defects were grouped into five major categories including conotruncal defects (truncus arteriosus, transposition of the great arteries, double outlet right ventricle, and Tetralogy of Fallot); obstructive heart defects (Ebstein anomaly, aortic valve stenosis, hypoplastic left heart syndrome, coarctation of the aorta, pulmonary artery atresia); septal defects (ventricular septal defect, atrial septal defect); atrioventricular septal defects (atrial septal defect primum, single common atrium, complete atrioventricular canal, endocardial cushion defect); and anomalous pulmonary venous return.
We also examined the effect of maternal age on the risk of selected birth defects associated with higher residential exposures to solvents. The EWPM exposure risk values as dichotomous variables (0, >0) were stratified by categories of maternal age (<35 years and 35 years or older) and age-specific ORs and respective 95% CIs were calculated. Additive and multiplicative interactions were assessed for the associations of birth defects with EWPM exposure risk values that appeared to vary by maternal age. Additive interaction was examined using a statistical program developed by Andersson et al. that estimated measures of relative excess risk due to interaction (RERI) and attributable proportion due to interaction (AP). If either or both measures differed from zero and their 95% CIs excluded 0, significant additive interaction was considered present. To assess multiplicative interaction, the product terms of EWPM risk values for a given solvent with maternal age were included in the logistic models and were considered significant if the p-value was less than 0.05.
Table 1 provides a comparison of case-mothers (of deliveries with neural tube defects, limb deficiencies, oral clefts, and congenital heart defects) and control mothers by demographic characteristics, delivery year, public health region of residence at the time of delivery, and geocoding status of residence. A total of 3245 cases with neural tube defects, 2406 cases with limb deficiencies, 7416 cases with oral clefts, 60154 cases with selected heart defects, and 280764 controls without major birth defects were available for the study. Compared with control-mothers, mothers of neural tube defect cases were more likely to be Hispanic and have less education, while mothers of babies with limb deficiencies and oral clefts were more likely to be non-Hispanic White. Mothers with babies with limb deficiencies and oral clefts were more likely than control-mothers to smoke during pregnancy, although smoking appeared underreported overall, given the low prevalence reported on the birth and fetal death certificates. Maternal residential street addresses were successfully geocoded to street level for 87.2%, 69.1%, 83.9%, 84.7%, and 87.4% respectively for control-births, and births with neural tube defects, limb deficiencies, oral cleft defects, and heart defects. Maternal addresses for neural tube defect cases were less likely to be geocoded because 21% of these deliveries were induced terminations for which maternal residential addresses were unavailable.
Neural tube defects were significantly associated with maternal residential proximity to several types of chlorinated solvent air emissions (Table 2), most notably with carbon tetrachloride (adjusted odds ratio [aOR] 1.42, 95% CI 1.09, 1.86); chloroform (aOR 1.40, 95% CI 1.04, 1.87); 1,2 dichloroethane (aOR 1.28, 95% CI 1.01, 1.62); ethyl chloride (aOR 1.39, 95% CI 1.08, 1.79); methyl chloroform (aOR 1.29, 95% CI 1.01, 1.63); 1,1,2 trichloroethane (aOR 1.56, 95% CI 1.11, 1.28); and 1,2,3 trichloropropane (aOR 1.49, 95% CI 1.08, 2.06). Further examination of the neural tube defect phenotypes revealed that spina bifida, but not anencephaly, was associated with these chemicals. Spina bifida was also associated with maternal residential proximity to emissions of 1,1-dichloroethane (aOR 1.70, 95% CI 1.06, 2.71), 1,2 dichloroethylene (aOR 1.60, 95% CI 1.01, 2.53), and tetrachloroethane (aOR 1.78, 95% CI 1.12, 2.82).
aExposure risk value based on residential proximity to source(s) of air emissions and estimated pounds of chemical emitted annually.
bAdjusted for birth year and maternal age, education, race/ethnicity, and public health region of residence (referent group: exposure risk value = 0).
cOdds ratios and respective 95% confidence intervals are not reported for analyses with less than five exposed cases.
With respect to chlorinated solvent emissions and oral clefts, a few positive associations were observed with cleft palate alone (Table 3). Propylene dichloride, in particular, was associated with cleft palate (aOR 1.77, 95% CI 1.05, 2.99).
aExposure risk value based on residential proximity to source(s) of air emissions and estimated pounds of chemical emitted annually.
bAdjusted for birth year and maternal age, education, race/ethnicity, and public health region of residence (referent group: exposure risk value = 0).
In analyses of congenital heart defects, only septal heart defects showed a significant association with emissions of chlorinated solvents, and these associations tended to be weak with the ORs ranging from 1.06 to 1.23 (Table 4, data for atrioventricular heart defects and anomalous venous return not shown). The only associations noted with limb defects included perchloroethylene with transverse limb deficiencies (aOR 1.21, 95% CI 1.01, 1.45) (Table 5) and any type of chlorinated solvent (exposure risk values summed for 14 chemicals) with lower limb deficiencies (aOR 1.21, 95% CI 1.00, 1.45, data not shown).
aExposure risk value based on residential proximity to source(s) of air emissions and estimated pounds of chemical emitted annually.
bAdjusted for birth year and maternal age, education, race/ethnicity, and public health region of residence (referent group: exposure risk value = 0).
aExposure risk value based on residential proximity to source(s) of air emissions and estimated pounds of chemical emitted annually.
bAdjusted for birth year and maternal age, education, race/ethnicity, and public health region of residence (referent group: exposure risk value = 0).
Tables 6,7, and8 display results of analyses of chlorinated solvents with spina bifida, cleft palate alone, and septal heart defects, respectively, in which exposure risk values were divided into four groups (zero, low, middle, high) based on the control-mother’s distributions. Significant linear trends were noted between the emissions of several chlorinated solvents and spina bifida, including chloroform; 1,1-dichloroethane; 1,2-dichloroethane; ethyl chloride; methyl chloride; tetrachloroethane; 1,1,2-trichloroethane; and 1,2,3-trichloropropane (Table 6). The strongest linear trends were noted with 1,2-dichloroethane (aOR for spina bifida in the fourth quartile: 1.85, 95% CI 1.21, 2.84) and with 1,2,3-trichloropropane (aOR in the fourth quartile: 2.62, 95% CI 1.55, 4.46). Several of the trends were not monotonic in that the highest odds ratios were noted in the second quartile versus the fourth quartile.
aExposure risk value based on maternal residential proximity to source(s) of air emissions and estimated pounds of chemical emitted annually.
bAdjusted for birth year and maternal race/ethnicity, age, education, and public health region.
aExposure risk value based on maternal residential proximity to source(s) of air emissions and estimated pounds of chemical emitted annually.
bAdjusted for birth year and maternal race/ethnicity, age, education, and public health region.
aExposure risk value based on maternal residential proximity to source(s) of air emissions and estimated pounds of chemical emitted annually.
bAdjusted for birth year and maternal race/ethnicity, age, education, and public health region.
Although the trends were not uniformly monotonic, the strongest associations between cleft palate alone and propylene dichloride, tetrachloroethane, 1,1,2-trichloroethane, and 1,2,3-trichloropropane were observed in the highest categories of exposure risk values (Table 7). These trends were statistically significant (p <0.05) for propylene dichloride and tetrachloroethane.
Positive linear trends were observed between septal heart defects and seven types of chlorinated solvents, including carbon tetrachloride; 1,1-dichloroethane; 1,2-dichloroethane; ethyl chloride; 1,1,2-trichloroethane; trichloroethylene; and 1,2,3-trichloropropane (Table 8). These associations tended to be weak with the ORs close to 1.00, even in the highest exposure categories, and not monotonic with increasing intensities of exposure risk values, with the exception of odds ratios in relation to carbon tetrachloride emissions. We noted similar patterns of odds ratios and p-values for trend between categorization of exposure risk values into four (Table 8) or seven groups (data not shown), with the exception of all chlorinated solvents combined in which p-values for trend were 0.180 versus 0.035 respectively for the seven versus four levels of categorization. Significant linear trends were observed in the association between ethyl chloride emissions and obstructive heart defects (aOR in the highest exposure risk value 1.49, 95% CI 1.09, 2.05) and in the association between methylene chloride and isolated conotruncal heart defects (aOR in the highest exposure risk value 1.56, 95% CI 1.05, 2.32) (data not shown).
Associations between various chlorinated solvents and birth defects in offspring tended to be stronger among mothers 35 years or older than for younger mothers (Table 9). This pattern was most consistently observed with oral cleft defects and these solvents, including associations with any chlorinated solvent (older versus younger, aORs 1.22 versus 0.99, respectively), carbon tetrachloride (aORs 1.66 versus 1.02), 1,1-dichloroethane (aORs 1.49 versus 0.85), 1,2-dichloroethane (aORs 1.50 versus 0.98), 1,2-dichloroethylene (aORs 1.65 versus 0.87), ethyl chloride (aORs 1.66 versus 1.05), methylene chloride (aORs 1.38 versus 1.02), tetrachloroethane (aORs 1.63 versus 0.85), 1,1,2-trichloroethane (aORs 1.78 versus 1.06), trichloroethylene (with cleft lip with or without cleft palate aORs 1.39 versus 1.02), and 1,2,3-trichloropropane (aORs 1.92 versus 1.12).
aOdds ratios adjusted for year of birth and maternal education, race/ethnicity, and public health region of residence.
bStatistically significant additive interaction by maternal age group.
cStatistically significant multiplicative interaction by maternal age group.
ORs for neural tube defects in offspring were also higher in older than younger mothers in relation to residential proximity to emissions of carbon tetrachloride (aORs 2.46 versus 1.31, respectively), chloroform (aORs 2.09 versus 1.33), and ethyl chloride (aORs 1.75 versus 1.36). On the other hand, this pattern was reversed for NTDs by maternal age in relation to 1,2-dichloroethane (younger versus older mothers, aORs 1.31 versus 0.98, respectively). With respect to heart defects, associations were stronger for among older than younger women for residential proximity near trichloroethylene (with obstructive heart defects aORs 1.43 versus 0.97) and any chlorinated solvent emissions (with obstructive heart defects aORs 1.27 versus 0.98). In contrast, associations were stronger for younger mothers than older mothers for the relation between ethyl chloride and atrioventricular septal defects, obstructive heart defects, and septal heart defects in offspring. While only one set of associations with higher odds ratios in younger versus older mothers showed significant multiplicative interaction, 16 sets of the stronger associations in older versus younger mothers showed significant additive and/or multiplicative interaction by maternal age. Too few older case-mothers of babies with limb deficiencies were available to assess interaction by maternal age in this birth defect group.
In this large population-based, case–control study, case-mothers (of offspring with neural tube defects, oral cleft defects, and congenital heart defects) were more likely than control-mothers to have higher estimated exposures to industrial air emissions of chlorinated solvents, based on their residential distance to such facilities and reported annual releases. Associations between maternal residential proximity to these emissions and birth defects in offspring tended to be stronger among mothers who were 35 years or older than among younger mothers, especially with oral cleft defects.
Other studies of the relation between maternal occupational and environmental exposures to chlorinated solvents have indicated associations between these solvents and various birth defects. In the NBDPS population, maternal occupational exposure to chlorinated solvents during the periconceptional period was strongly associated with neural tube defects (aOR 1.96, 95% CI 1.34, 2.97), especially spina bifida (aOR 2.26, 95% CI 1.44, 3.53). Odds ratios for specific chlorinated solvents were not reported, although the prevalence of occupational exposures to chloroform, methylene chloride, perchloroethylene, trichloroethane, and trichloroethylene were all higher among case-mothers of babies with spina bifida than control mothers. In the present study, case-mothers of babies with spina bifida were also more likely than control-mothers to live near industrial emissions of chloroform, methylene chloride, trichloroethane, and trichloroethylene, but the same proportion of case-mothers as control-mothers lived near industrial emissions of perchloroethylene.
In two French study populations, maternal occupational exposures to chlorinated solvents or halogenated aliphatic solvents (also known as alkyl halide solvents of which chlorinated solvents are a subgroup) were associated with oral cleft defects in offspring, specifically with cleft lip with or without cleft palate. These findings were not corroborated in a U.S. study population in which the odds for any oral cleft, cleft palate, and cleft lip with or without cleft palate in offspring in relation to maternal occupational exposures to chlorinated solvents were close to 1.00. With respect to environmental exposures, case-mothers of babies were oral clefts were not more likely than control- mothers in Texas to live within a mile of an industrial facility with emissions of alkyl halide solvents. In the present study, few associations were noted between maternal proximity to emissions of specific chlorinated solvents and oral clefts, except for cleft palate with propylene dichloride, tetrachloroethane, and 1,1,2-trichloroethane. With stratification by maternal age, however, proximity to chlorinated solvent emissions overall was significantly associated with any oral cleft and specifically with cleft lip with or without cleft palate among mothers 35 years or older. Stronger associations were observed among older mothers between residential proximity to several types of chlorinated solvent emissions and cleft palate alone and cleft lip with or without cleft palate in offspring.
In a study conducted in France in which metabolites of chlorinated solvents were measured in urine, case-mothers of babies with limb malformations were more likely than control mothers to have higher levels of urinary metabolites of tetrachloroethylene (perchloroethylene) and trichloroethylene. We also observed an association between maternal proximity to emissions of perchloroethylene and transverse limb defects in offspring, but the odds ratios were close to 1.0 for associations between trichloroethylene emissions and limb deficiencies in our study.
With respect to heart defects, maternal occupational exposures to chlorinated solvents were associated with perimembranous ventricular septal defects (aOR 1.7, 95% CI 1.0, 2.8) in the National Birth Defects Study population; other associations were noted with d-transposition of the great arteries and aortic stenosis although the 95% confidence intervals were compatible with the null. In a study of maternal residential proximity to industrial facilities and selected birth defects in offspring in Texas, conotruncal heart defects were not associated with maternal residential proximity to facilities reporting air emissions of alkyl halide solvents. In the present study, we also did not observe any associations with conotruncal heart defects with chlorinated solvent emissions, and most of the significant associations with these solvents were restricted to septal heart defects. However, among older mothers, obstructive heart defects in offspring were associated with maternal proximity to emissions of any chlorinated solvents and specifically with emissions of ethyl chloride and trichloroethylene. Older mothers of offspring with any type of heart defect and septal heart defects were also more likely than older control-mothers to live near emissions of trichloroethylene.
Maternal age has been found in other studies to modify associations between maternal prenatal exposures to chemicals and pregnancy outcomes. In a study of trichloroethylene-emitting sites and congenital heart defects in Wisconsin, older case-mothers (38 years or older) of offspring with congenital heart defects were over three times more likely than older control-mothers to live within 1.32 miles of trichloroethylene-emitting sites; no association between congenital heart defects and this residential characteristic was noted among offspring of younger women. Infants of mothers 35 years or older who were exposed to tetrachloroethylene in drinking water had lower mean birth weights and were more likely to be small for gestational age than infants among unexposed women in the same age group in a study conducted at a U.S. Marine Corps base in North Carolina; these patterns were not observed in offspring of younger mothers. The study investigators suggested that advanced maternal age might increase susceptibility of the developing fetus to chemical insults.
In the present study, we used maternal residential addresses at delivery to determine residential proximity to emissions of chlorinated solvents. While maternal address at delivery corresponds to maternal address during the first trimester for most mothers, results from two previous studies of Texas case-mothers and control-mothers who participated in the National Birth Defects Prevention Study indicated that up to 33% of the case-mothers and 31% of the control-mothers changed residence between conception and delivery[24, 25]. Therefore, some mothers in this study may have been misclassified with respect to residential proximity to emissions of chlorinated solvents during the first trimester, the relevant period of morphogenesis of the birth defects included in this study. On the other hand, older mothers in Texas were observed to move less during pregnancy than younger mothers with approximately 15% of the case- and control-mothers, who were 30 years or older, changing residences between conception and delivery. Furthermore, maternal residential movement of mothers in all age categories tended to involve short distances which would have minimal impact on exposure assessment to air pollutants.
Sufficient address information was not available to geocode all maternal addresses to street level, although proportions geocoded to this level included approximately 87% of the control group addresses and 84 to 87% of case group addresses, with the exception of neural tube defects with 69.1% geocoded to the street level. Geocoded and ungeocoded controls and case groups (heart, oral cleft, limb reduction, and neural tube defect groups) had similar distributions by maternal age, but the ungeocoded case groups and controls had higher proportions of mothers who were Hispanic and who had less than a high school education than the respective geocoded groups. Given that the differences were in the same direction and similar in magnitude among case and control groups, it is most likely that a compensating bias occurred (both cases and controls had the bias in the same direction and of similar magnitude). Therefore, we might expect that the exclusion of the ungeocoded cases and controls to have minimal impact on the odds ratios other than reducing their precision due to reduced sample sizes. Approximately 10% of industrial facilities also could not be geocoded because of insufficient and/or inaccurate address information. These missing industries may have led to misclassification of exposure status for some case and control residences, although it is not likely that this misclassification would have been differential with respect to case or control status.
As a proxy for potential exposure to emissions of chlorinated solvents, we used a metric (EWPM) that incorporated residential distance from all TRI facilities within a 10 km radius that reported air emissions of chlorinated solvents and annual amounts of chemicals reported released from each facility. This approach probably introduced some misclassification of exposures. To assess the performance of EWPM in predicting the presence and intensity of chemical air emissions, we examined how well the EWPM exposure metrics correlated with air measurements of chlorinated solvents taken by the Texas Commission of Environmental Quality at 48 monitoring sites in Texas during 2005. The EWPM measurements were positively correlated with air measurements for the six chemicals available for comparison, including carbon tetrachloride, chloroform, 1,1-dichloroethane, methyl chloroform, 1,1,2-trichloroethane, and trichloroethylene, with the strongest correlations noted with carbon tetrachloride and chloroform [unpublished observations, Gong and Zhan]. In addition to the limitation of chemical quantities aggregated into pounds per year, further misclassification could have been introduced if the amounts released per year varied since the first trimester of some pregnancies might have been during the preceding year. Furthermore, length of gestation for fetal deaths and induced terminations (cases) would have been shorter than that for the majority of live births, although approximately 97% of the cases were liveborn and the most vulnerable period for teratogenesis is the first trimester.
While the Texas Birth Defects Registry includes elective terminations in their active surveillance of birth defects, we were unable to include these cases in this study because of missing data from lack of linkage to a vital record. This lack of linkage had the greatest impact on our analyses of the relation between chlorinated solvent emissions and neural tube defects in which 69% of maternal addresses were geocoded to street level and 22% were missing information regarding maternal education, a variable strongly related to maternal residential proximity to industrial facilities along with maternal race/ethnicity.
With respect to specific defects, the highest proportion of induced terminations were found with anencephalic cases (39.7%) with percentages less than 5% for the other studied defects with the exception of spina bifida (8.3%) and lower limb reduction defects (5.6%). Given the high proportion of anencephalic cases that could not be analyzed because of missing information, findings related to this defect should be interpreted cautiously because it is not known whether women who undergo induced terminations are more or less likely to live near sources of industrial emissions.
In this study, we were unable to account for recurrence of birth defects in subsequent pregnancies of case-women, a known risk factor for birth defects. Recurrence would most likely introduce bias into the study if it was related to maternal residence as well as prevalence of birth defects. We are not aware of any studies that document a higher or lower likelihood of mothers living near industrial sites with chemical emissions if they have had a previous birth defect-affected pregnancy. On the other hand, while Lie et al. noted less than a 5% recurrence of birth defects in Norwegian women whose first infants had birth defects, women who resided in the same municipality during both pregnancies were 11.6 times more likely than women whose first infant had no defect, to have a second infant with the same defect. In contrast, women who moved to another municipality after the birth of their first infant were 5.1 times more likely to have a second infant with the same defect. The authors concluded that these findings suggested that environmental factors contribute to the familial risk of birth defects and that important environmental teratogens have yet to be discovered.
The large sample size of this study allowed examination of associations between specific chlorinated solvents and birth defects as well as stratification by maternal age. Furthermore, a refined exposure assessment accounted for multiple facilities and their respective annual quantities of chemical releases, an improvement from previous studies that estimated exposure based on distance to the nearest industrial facility.
Study findings suggest that maternal residential proximity to air emissions of chlorinated solvents are associated with neural tube, oral cleft, and congenital heart defects, especially among offspring of older mothers. To better understand the relation between maternal exposure to chlorinated solvent emissions and birth defects in offspring, we recommend that future studies focus on populations in which air measurements of these chemicals and residential histories during pregnancy are available.
The research reported in this paper was made possible in part by a USEPA-STAR grant (#R834790). The contents are solely the responsibility of the authors and do not necessarily represent the official views of the USEPA. Furthermore, USEPA and the authors do not endorse the purchase of any commercial products or services mentioned in the poster. This publication was also supported in part through a cooperative agreement (U01DD000494) between the Centers for Disease Control and Prevention and the Texas Department of State Health Services (DSHS) and by Title V Maternal and Child Health Block Grants Funds from the Office of Title V and Family Health, Texas DSHS. Its contents are solely the responsibility of the authors and do not necessarily represent the official views of the Centers for Disease Control and Prevention. Some of the data used in the analyses were provided by the Texas Department of State Health Services (DSHS) Birth Defects Epidemiology and Surveillance Branch and the DSHS Center for Health Statistics. The authors express their appreciation to the USEPA and Texas Department of State Health Services.
JB (in conjunction with FZ) conceived of the study, participated in the study design and data analyses, drafted the discussion section, and coordinated the final draft of the manuscript. MS carried out the data analyses and wrote the initial draft of the manuscript. FZ supervised and participated in the geocoding of industrial sites, the linkage of industrial sites and releases to maternal addresses, the development of exposure risk values, and the writing of the environmental sections of the manuscript. XG participated in the geocoding of industrial sites, the linkage of industrial sites and releases to maternal addresses, and performed the correlation analyses between exposure risk values and air monitoring data. PH supplied the birth defect case and control databases, participated in various aspects of study design and data analysis, and the drafting of the manuscript. All authors read and approved the final manuscript.