Ingested Arsenic and Lung Cancer

174 Pages·2015·8.49 MB·English

by  Dave Dauphine

UC Berkeley
UC Berkeley Electronic Theses and Dissertations
Title
Arsenic in Drinking Water and Lung Disease in Chile, California and Nevada
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Dauphine, David
Publication Date
2015

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Arsenic in Drinking Water and Lung Disease
in Chile, California and Nevada

by

David Charles Dauphiné

A dissertation submitted in partial satisfaction of the

requirements for the degree of

Doctor of Philosophy

in

Environmental Health Sciences
in the
Graduate Division
of the
University of California, Berkeley

Committee in charge:

Professor S. Katharine Hammond, Chair
Professor Michael L. Jerrett
Professor Craig M. Steinmaus
Professor Steve Selvin

Summer 2015
Arsenic in Drinking Water and Lung Disease in Chile, California and Nevada

© 2015
By David Charles Dauphiné
Abstract
Arsenic in Drinking Water and Lung Disease in Chile, California and Nevada
By
David Charles Dauphiné
Doctor of Philosophy in Environmental Health Sciences
University of California, Berkeley
Professor S. Katharine Hammond, Chair

Millions of people are exposed to arsenic in drinking water. An ancient poison, arsenic occurs
naturally in groundwater and geothermal springs. Removing arsenic from drinking water costs
about $200 million every year in the United States alone. The brunt of this is borne by California
and other western states, where groundwater is needed more for drinking water.

Arsenic in drinking water causes cardiovascular death, cognitive deficits in children,
reproductive problems, and cancer. Surprisingly, many studies have shown that the human lung
is especially susceptible to ingested arsenic. After being consumed in drinking water, arsenic
accumulates in the lungs. Lung cancer is now believed to be the most common cause of death
from this widespread contaminant.

Most lung carcinogens, including tobacco smoke, asbestos, and silica, also cause non-
malignant respiratory effects. Evidence suggests that arsenic in drinking water follows this
pattern, but nearly all data involve adults with recent exposures. The impacts of early-life arsenic
exposures on nonmalignant lung disease are largely unknown. In northern Chile, the city of
Antofagasta (population 390,000 in 2014) had high concentrations of arsenic in drinking water
(>800 µg/L) from 1958 until 1970, when a new treatment plant was installed. This scenario, with
its large population, distinct period of high exposure, and accurate data on past exposure, is
virtually unprecedented in environmental epidemiology. Chapter 2 of this dissertation describes a
pilot study on early-life arsenic exposure and long-term lung function. We recruited a
convenience sample consisting primarily of nursing school employees in Antofagasta and Arica
(population 160,000) a city with low drinking water arsenic. Lung function and respiratory
symptoms in 32 adults exposed to >800 µg/L arsenic before age 10 were compared to 65 adults
without high early-life exposure. Early-life arsenic exposure was associated with 11.5% lower
forced expiratory volume in one second (FEV ) (p = 0.04), 12.2% lower forced vital capacity
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(FVC) (p = 0.04), and increased breathlessness (prevalence odds ratio = 5.94, 95% confidence
interval 1.36–26.02). Exposure-response relationships between early-life arsenic concentration
and adult FEV and FVC were also identified (p trend = 0.03). These results suggest that early-
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life exposure to arsenic in drinking water may have irreversible respiratory effects of a
magnitude similar to smoking throughout adulthood. Given the small study size and non-random
recruitment methods, further research is needed to confirm these findings.

The arsenic concentrations >800 µg/L in Chile can reveal previously unknown health
outcomes, but they do not shed much light on what the drinking water standard should be.
Arsenic is known to cause lung cancer at concentrations above about 200 µg/L. The effects of
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lower exposures are unknown. This uncertainty has created controversy over the 10 µg/L World
Health Organization guideline and U.S. regulatory limit for public water supplies because arsenic
is widespread in groundwater naturally and expensive to remove. In Chapter 3, I present the first
lung cancer study in the largest U.S. populations with exposures between 50 and 100 µg/L. This
was also the first U.S. lung cancer study with individual data on past drinking water arsenic
concentrations. We enrolled 196 lung cancer cases and 359 controls, matched on age and sex,
from western Nevada and Kings County, California in 2002–2005. After adjusting for age, sex,
education, smoking and occupational exposures, odds ratios for arsenic concentrations ≥85 μg/L
(median = 110 μg/L, mean = 173 μg/L, maximum = 1,460 μg/L) more than 40 years before
enrollment were 1.39 (95% CI = 0.55–3.53) in all subjects and 1.61 (95% CI = 0.59–4.38) in
smokers. Although odds ratios were greater than 1.0, these increases may have been due to chance
given the small number of subjects exposed more than 40 years before enrollment. The findings
suggest that concentrations near 100 μg/L are not associated with markedly high relative risks.

The California Nevada lung cancer case-control study, designed before research in Chile
suggested arsenic-related cancer latencies of 40 years or more, illustrates the difficulties of
identifying arsenic-related health effects in low-exposure countries with mobile populations like
the U.S. Making matters worse, many wells used by participants 20–60 years ago could not be
measured because they could not be located or had fallen into disrepair. A major problem for
health studies of arsenic and other drinking water contaminants is a lack of measurements for
unregulated water sources such as private wells, which are much more likely to have high arsenic
than public supplies. For Chapter 4, I developed models to estimate arsenic in unmeasured wells
in the western Nevada study area. In cross-validations with five partitions of 3138 residential
wells, inverse distance weighted (IDW) averaging was the best categorizer of arsenic, averaging
71% correct assignment to the high, medium and low categories used in the lung cancer study.
The next best categorizers were the random forest model (70% correct) and the median of
measurements within 408 m (69%). These models categorized wells better than kriging (67%),
consistent with findings in other areas. Nearest neighbors averaged 66% correct assignment. For
exact arsenic concentrations, the best models were the random forest model (Arsenic =
0.95*RFM, R2 = 0.34) and kriging (Arsenic = 1.00*OK, R2 = 0.30). The RFM might be
considered the best model overall, since it categorized measurements almost as well as IDW, had
a higher R2 (0.34 versus 0.28), and a linear slope closer to 1 (0.95 versus 0.80). In terms of
detecting high arsenic wells, RFM was also just behind IDW. These models can be substantially
improved, but IDW and RFM already nearly doubled the number of unmeasured wells correctly
categorized around Fallon, compared to the alternative of treating them as zeroes in effect
estimates based on participants’ highest known concentrations. Given that the direction of the
bias is the same whether unmeasured wells are estimated or excluded, the smaller bias using
estimates is preferable.

Chapter 5 presents meta-analyses of low exposure lung cancer studies, and assesses
differences in relative risks between men and women. Pooled results of six independent studies
suggest that increased lung cancer risks reported for concentrations between 10 and 100 µg/L are
not likely due to chance (pooled relative risk = 1.09, 95% CI = 1.02-1.20), but there was
substantial heterogeneity between studies (p<0.001). The higher relative risk of 4.1 (95% CI =
1.8-9.6) in the case-control study by Ferreccio et al. (2000) might be explained by effects in
ecological studies being diluted by in-migration or uncontrolled confounding. Relative risks were
higher in men in Chile, in women in Taiwan, and similar for all countries combined. The gender
2
differences in Chile and Taiwan were not likely due to chance, and may be explained by
differences in study participation, case ascertainment, smoking, occupational, or household
smoke exposures.

Chapter 6 concludes with a summary of recent research and ideas for future studies. New
findings of health effects below 100 µg/L, including lung cancer in people with early life
exposures (Steinmaus et al. 2014), need to be confirmed. However, increasing evidence supports
the 2001 decision to tighten the U.S. regulatory from 50 to 10 µg/L. Detecting the increases in
health risk expected below 50 µg/L (e.g., odds ratios below 1.5) will likely require very large
sample sizes, but may be possible in studies with accurate data on early life exposures, inter-
individual differences in arsenic metabolism, and related susceptibility factors (e.g., age,
genetics, gender, diet, health status, smoking, and occupational exposures). On the
environmental side, high arsenic concentrations have been predicted in many regions that lack
available measurements, including much of the Amazon Basin (Amini et al. 2008), contrary to
the expectations of some geologists (Ravenscroft et al. 2009). Measurements in these areas can
test and improve models of arsenic in groundwater, improve exposure assessment, and help
ensure the safety of millions of people.

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Contents
Abbreviations ................................................................................................................................. vi
Acknowledgements ........................................................................................................................ vi
Chapter 1. Introduction ................................................................................................................... 1
Why Arsenic? .............................................................................................................................. 1
Millions of people are exposed ................................................................................................ 1
The drinking water standard may be associated with unacceptable health risks ................... 2
Health effects of low exposures are unknown ......................................................................... 2
Costs of removing arsenic are high ........................................................................................... 2
Health Effects .............................................................................................................................. 3
Chemistry, Toxicity, and Metabolism ...................................................................................... 3
Carcinogenesis ........................................................................................................................ 3
Dose-Response......................................................................................................................... 4
Why Lung Disease? .................................................................................................................... 4
Environmental Sources and Determinants .................................................................................. 4
Reductive Dissolution .............................................................................................................. 5
Evaporative Concentration...................................................................................................... 6
Depth ....................................................................................................................................... 6
Other Variables ....................................................................................................................... 6
Arsenic Models ........................................................................................................................... 7
Kriging ..................................................................................................................................... 8
Why Chile, California, and Nevada? ........................................................................................ 10
Figures ....................................................................................................................................... 12
Figure 1. Number of arsenic publications by year (chart made using data from NCBI 2015).
............................................................................................................................................... 12
Figure 2. Periodic table of the elements. ............................................................................... 13
Figure 3. Classification of groundwater environments prone to arsenic problems from
natural sources (Smedley and Kinniburgh 2002). ................................................................. 14
Figure 4. Documented problems with arsenic in groundwater and the environment (Smedley
2008) ...................................................................................................................................... 15
Figure 5. Known occurrences of high arsenic in groundwater (in black) and the mechanisms
by which arsenic is released from sediment and rock into water (Ravenscroft et al. 2009, p.
55). ......................................................................................................................................... 16
Figure 6. Global arsenic map based on 20,000 measurements, regression models, and
adaptive neuro-fuzzy inferencing by the Swiss Institute of Aquatic Science and Technology
(Amini et al. 2008)................................................................................................................. 17
Figure 7. U.S. arsenic map based on 31,000 wells and springs sampled from 1973 to 2000
(Ryker 2003). ......................................................................................................................... 18
Figure 8. Observed and predicted arsenic concentrations in basin-fill aquifers of the U.S.
Geological Survey’s Southwest Principal Aquifers study area (Anning et al. 2012). ........... 19
Figure 9. Variograms from Bangladesh, Taiwan, Maine, and Michigan showing
semivariance (y), a function of the change in arsenic, in relation to distance between wells
(h)........................................................................................................................................... 20
Tables..................................................................................................................................... 21
Table 1. Arsenic Kriging Publications. ................................................................................. 21
Chapter 2. Lung Function in Adults following In utero and Childhood Exposures ..................... 22
i
Introduction ............................................................................................................................... 22
Methods ..................................................................................................................................... 22
Study Area.............................................................................................................................. 22
Study design and participants................................................................................................ 22
Interviews............................................................................................................................... 23
Lung function measurement using spirometry ....................................................................... 23
Arsenic exposure assessment ................................................................................................. 24
Statistical methods ................................................................................................................. 24
Results ....................................................................................................................................... 25
Discussion ................................................................................................................................. 26
Conclusions ............................................................................................................................... 29
Tables ........................................................................................................................................ 30
Table 1. Characteristics of participants [mean ± SD or n (%)]. ............................................ 30
Table 2. Lung function residuals (observed minus predicted) and percent of age, sex, and
height-predicted values (mean ± SD). ................................................................................... 31
Table 3. Exposure-response between early-life arsenic and lung function residuals (observed
minus predicted) and percent of age, sex and height-predicted values (mean ± SD). ........... 32
Table 4. Prevalence odds ratios (PORs) and 95% confidence intervals (CIs) for respiratory
symptoms. .............................................................................................................................. 32
Chapter 3. Lung Cancer Case-Control Study in California and Nevada ...................................... 33
Introduction ............................................................................................................................... 33
Methods ..................................................................................................................................... 33
Study Area ............................................................................................................................. 33
Participant Selection .............................................................................................................. 34
Interviews .............................................................................................................................. 34
Arsenic Exposure Assessment ............................................................................................... 35
Statistical Methods ................................................................................................................ 35
Results ....................................................................................................................................... 36
Discussion ................................................................................................................................. 37
Conclusions ............................................................................................................................... 40
Tables ........................................................................................................................................ 41
Table 1. Demographic characteristics of participants. .......................................................... 41
Table 2. Drinking water characteristics. ................................................................................ 42
Table 3. Odds ratios and 95 percent confidence intervals for arsenic in drinking water and
lung cancer. ............................................................................................................................ 43
Table 4. Odds ratios and 95% CIs for arsenic in drinking water and lung cancer among ever
smokers. ................................................................................................................................. 43
Supplemental Table 1. Smoking and drinking water characteristics for 30 subjects with ≥85
µg/L arsenic in drinking water at least 40 years before enrollment. ..................................... 44
Chapter 4. Groundwater Models in Western Nevada ................................................................... 45
Introduction ............................................................................................................................... 45
The health effects of arsenic can take decades to develop .................................................... 45
Past exposures may be impossible to measure ...................................................................... 45
Exposure misclassification is a major limitation of arsenic risk assessment ........................ 46
Study Area.............................................................................................................................. 46
Methods ..................................................................................................................................... 48
ii
Non-detects ............................................................................................................................ 49
Arsenic Histograms ............................................................................................................... 49
Depth ..................................................................................................................................... 50
Spatial Distribution of Arsenic .............................................................................................. 50
Arsenic, Well Depth, and Elevation in each Basin ................................................................ 51
Study Basins ........................................................................................................................... 51
Models ................................................................................................................................... 51
Results ....................................................................................................................................... 52
Interpolations......................................................................................................................... 52
Predictions below 1µg/L ........................................................................................................ 52
Correlations ........................................................................................................................... 53
Scatterplots ............................................................................................................................ 54
Summary Statistics ................................................................................................................. 54
Categorization ....................................................................................................................... 54
Overall Comparisons ............................................................................................................. 55
Fallon Area ............................................................................................................................ 56
Discussion ................................................................................................................................. 57
Limitations and Potential Improvements ............................................................................... 58
Comparison with Previous Estimates in the Study Area ....................................................... 60
Improving Exposure Assessment ........................................................................................... 62
Other Applications ................................................................................................................. 62
Conclusions ............................................................................................................................... 63
Figures ....................................................................................................................................... 65
Figure 1. Study Area. ............................................................................................................. 65
Figure 2. USGS measurements and random forest estimates for western Nevada (Anning et
al. 2012). ................................................................................................................................ 66
Figure 3. Zooming in further. ................................................................................................ 67
Figure 4. Main sources of groundwater recharge in the study area. ...................................... 68
Figure 5. Carson Water Subconservancy District’s map. ...................................................... 69
Figure 6. Carson River Coallition’s drawing of the Carson River watershed. ...................... 70
Figure 7. Aquifer Profile (Welch and Lico 1998). ................................................................ 71
Figure 8. Groundwater flow near end of Carson River (Welch and Lico 1998). .................. 72
Figure 9. Arsenic in upward and lateral flow areas (Welch and Lico 1998). ........................ 73
Figure 10. Arsenic histogram with automatically-generated 88 µg/L intervals. ................... 74
Figure 11. Arsenic histogram with smaller intervals between low concentrations. .............. 74
Figure 12. Log10 arsenic frequency distribution. .................................................................. 75
Figure 13. Depth and arsenic in 3143 residential wells. ........................................................ 75
Figure 14. Physical map of western Nevada and arsenic in 3143 drinking water wells. ...... 76
Figure 15. Satellite image. ..................................................................................................... 77
Figure 16. Map of arsenic in1572 drinking water wells in the Lower Carson Basin. ........... 78
Figure 17. Arsenic (µg/l) in 45 wells used by lung cancer study participants. ..................... 79
Figure 18. Arsenic (µg/l) in wells used by lung cancer study participants, excluding two
outliers (n=43). ...................................................................................................................... 79
Figure 19. Inverse Distance Weighted Average Arsenic in study area using 3143 wells, 15
neighbors maximum and an inverse distance weighting power of 1. .................................... 80
iii
Figure 20. Inverse Distance Weighted Average Arsenic around Fallon, Nevada using 1749
wells, 14 neighbors maximum and an inverse distance weighting power of 1. .................... 81
Figure 21. Universal kriging log 10 arsenic predictions and variogram. .............................. 82
Figure 22. Scatterplot for all models. .................................................................................... 83
Figure 23. Individual scatterplots for each model. ................................................................ 84
Figure 24. Scatterplot for all models around Fallon. ............................................................. 86
Figure 25. Individual scatterplots for each model around Fallon. ......................................... 87
Supplemental Figures ................................................................................................................ 89
Supplemental Figure 1. Predicted arsenic (µg/L) for 2681 wells with a neighbor within 360
m, the distance chosen for local median based on Pearson’s correlation. ............................. 89
Tables ........................................................................................................................................ 90
Table 1. Arsenic measurements used in analyses.a ................................................................ 90
Table 2. Depth and arsenic .................................................................................................... 90
Table 3. Arsenic (µg/L) in 45 wells used by lung cancer study participants and their nearest
measured neighboring wells. ................................................................................................. 90
Table 4. Arsenic, depth, and elevation in each basin. ........................................................... 91
Table 5. Arsenic estimates below 1 µg/L by ordinary kriging, universal kriging, and the
generalized additive model. ................................................................................................... 92
Table 6. Average Spearman’s rank correlations (ρ) between medians and measurements. .. 93
Table 7. Spearman’s correlations between estimates from all models and measurements. .. 94
Table 8. Statistics for models and arsenic measurements (µg/L).a ........................................ 94
Table 9. Correct categorization of wells with neighbors within 408 m, the best-correlated
distance for local medians. .................................................................................................... 95
Table 10. Accuracy for estimates ≥85 µg/L. ......................................................................... 96
Table 11. Combined sensitivity and accuracy: Percentage of high arsenic wells that were
correctly categorized, averaged with the percentage of high estimates that were correct. .... 96
Table 12. Overall comparisons: Spearman's rank correlations (ρ), coefficients of
determination (R2), sensitivity and accuracy for high arsenic wells, sorted by the percentage
of wells correctly categorized. ............................................................................................... 97
Table 13. Average Spearman’s rank correlations (ρ) between medians and measurements
around Fallon. ........................................................................................................................ 97
Table 14. Spearman’s correlations (ρ) for all model estimates versus measurements around
Fallon. .................................................................................................................................... 98
Table 15. Correct categorization of wells around Fallon. ..................................................... 99
Table 16. Spearman's rank correlations (ρ) and coefficients of determination (R2) sorted by
percentage of wells correctly categorized around Fallon. ................................................... 100
Supplemental Tables ............................................................................................................... 101
Supplemental Table 1. Average Pearson’s correlations (R) for 3138 arsenic measurements in
entire study area versus medians of measurements within regular distance intervals and best
correlated intermediate distances.a ...................................................................................... 101
Supplemental Table 2. Average Pearson’s correlations (R) for arsenic measurements versus
predictions for all 3138 wells.a ............................................................................................ 101
Supplemental Table 3. Correct categorization of wells with neighbors within 360 m, the
distance chosen for medians based on Pearson’s correlations. ........................................... 102
Supplemental Table 4. Correct categorization of all 3138 wells. ........................................ 103
iv