text:
These tough predators will battle grizzlies, but they're no match for climate change
by Douglas H. Chadwick
© Barbara von Hoffmann
The mid-January snowstorm cleared off overnight. By morning, the temperature had plunged to minus 25 F, and the mountain valley around me was muttering about the cold. Sap deep inside the pine and fir trees had started to freeze hard, making the woodlands creak and pop. The lakes banged and whoomped as their ice cover expanded. Even the air felt brittle, scraping the inside of my throat as I skied hard toward the valley's upper end.
I was tracking the male wolverine we called M1. His big paw prints were fresh. He must have come through at dawn. But where was he bound? There was nothing before him but a sheer headwall whose rim marked the Continental Divide, where the snows were far deeper and the temperatures lower yet.
I stopped skiing after a while. My goal hadn't been to catch up; I'd simply wanted to reach a point high enough to let me monitor M1's radio signal a while longer. He was one of a number of wolverines carrying transmitters as part of a six-year-long study in Glacier National Park, Montana, directed by Jeff Copeland and Rick Yates of the U.S. Forest Service Rocky Mountain Research Station. I was part of a band of volunteers who helped capture and follow the animals, learning the hard way that no carnivore in North America keeps on the move as constantly as a wolverine does. Or as fearlessly.
When the male reached the headwall, he started up its towering stone face via a cleft known as Iceberg Notch. It would have taken me half a day to reach the top of the nearly vertical, 1,500-foot chute using climbing rope and pitons. But M1 didn't pause. With his two-inch long claws digging into the wind-packed snow like crampons, he scaled the wall in about 20 minutes. Then he crossed through the notch in a plume of gust-driven flakes and dropped onto the Pacific side of North America. The ridgeline blocked his radio signal. And just like that, the wild mountaineer was gone, off to patrol the rest of a territory that encompassed almost 200 square miles along the continent's crown.
The wolverine, Gulo gulo, arose during the latter part of the Pleistocene epoch, when glaciers still claimed much of the Northern Hemisphere. Though this hunter-scavenger ranks as the biggest terrestrial member of the mustelid, or weasel, family, it is only about three feet long (four counting its bushy tail) and weighs just 25 to 40 pounds on average. But what the gulo lacks in stature, it makes up for in strength and intensity. In addition to taking down prey as large as adult caribou, solitary wolverines have been seen driving grizzly bears from food. That's world-class attitude.
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Given the wolverine's Ice Age origins, it's not too surprising that it can survive some of the most extreme conditions in modern-day winters. But what this elusive and little-studied carnivore may not be able to take is more heat. Wolverines depend on cool year-round temperatures and deep, persistent snows. As habitats with those qualities shrink in an era of rapid global warming, so do this species' chances of survival, making it something like a land-based counterpart of the better-known polar bear.
Perhaps the most critical period for wolverines begins in February, when pregnant females go into dens dug from the snowpack. They give birth at the end of that month or the start of March. Wolverines don't hibernate. Nor does a mother keep to the den while living off energy reserves. She regularly heads out hunting, often covering dozens of miles. At some point, she may move the young, called kits, from the birth den to a second den and sometimes a third—particularly if there has been a disturbance in the area. The nursing young will remain hidden away for a full 10 weeks, well into May.
Fewer than two dozen wolverine dens have ever been located in the Lower 48. About half of those were discovered during the Glacier Wolverine Project, which Defenders of Wildlife helped fund. Many of the rest were found during an earlier study by Copeland in Idaho and another long-running study, headed by Bob Inman, in the greater Yellowstone ecosystem. Nearly all the dens were located at high altitudes and eight to 10 feet down in the snowpack. Baby wolverines, which weigh only a few ounces at birth, need every foot of snow overhead for insulation—and for protection against passing predators.
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Deep snow and prolonged winter conditions benefit wolverines in other ways, too. These animals' feet are enormous relative to their body size. Like bears—and humans—gulos land on their heels as well as the front part of their feet when walking or running. This full-sole contact spreads the wolverines' weight like snowshoes, giving the animals a major advantage in mobility over competitors and prey.
A long, harsh winter drains the energy reserves of hoofed animals, leaving some dead, available for scavenging, and others weaker, more easily brought down for dinner. In mountain terrain like Glacier, heavy snowfalls also mean more avalanches. These claim their own share of the grazing herds. "Wolverines also cache a lot of food in snowbanks and in boulderfields that often have snowmelt running underneath," Inman says. "I think some of these supplies not only keep for months but might even stay available from year to year."
Wolverines have a somewhat higher basal metabolic rate than other animals their size, which means their internal fire burns a little hotter. To help hold in heat, they wear a long, luxuriously thick coat. Trappers prize this fur because the texture of wolverine hair also keeps it from absorbing moisture. Used for the trim on parka hoods, it readily sheds frost that would otherwise build up from steaming breath.
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The list of adaptations helping wolverines contend with winter is impressive. But until scientists started to focus on climate change, no one gave much thought to how animals with a warm fur coat, a stoked-up metabolism and food cached in nature's refrigerators handle bathing-suit weather. The answer is: by avoiding it.
Jeff Copeland and other wolverine scientists used satellite imagery to create a map showing where snow lasts through the first half of May in the Northern Hemisphere. Then they mapped out the general distribution of Gulo gulo. Predictably, the two patterns were nearly identical. Next, Copeland and his colleagues took a closer look at the species' exact whereabouts in western North America. "When we charted temperatures in the southern portion of wolverine range, we discovered that the animals rarely occurred in places where the average maximum daily temperature in August exceeds 70 degrees F," he says. "In other words, hot weather may have as much to say about where wolverines live as winter snow does."
Gulo gulo is fairly widespread in the Arctic, the subarctic taiga and the boreal forest, Copeland explains. Farther south, the animals have to go up in elevation to find the accumulations of snow they require for denning, just as they must to reach more tolerable summer temperatures. This is why they are restricted mainly to western mountain regions in the lower 48 states.
During frontier times, wolverines were at home in the snowcapped ranges of the Pacific states all the way to the Sierras of southern California and down the Rockies into northern New Mexico. But unchecked trapping and poisoning wiped out the species south of Canada early in the 20th century. With stricter limits on the use of poisons, wolverines eventually returned along the Canadian Rockies to the Glacier Park area and began recolonizing neighboring mountainscapes. Today, they are found mainly in remote uplands of Montana, Idaho and northern Wyoming, plus there is a small resident population in Washington's North Cascades.
Altogether, the wolverine enclaves in the contiguous states may hold 450 animals, but more likely 250 to 300. Either way, the total is much smaller than it was for grizzlies, wolves or bald eagles when those species were declared threatened or endangered. Defenders and others have submitted petitions to add wolverines to the federal list over the years, but between bureaucratic inertia, political interference, scarce data and lack of popular support, Gulo gulo still has no official protection. In fact, the animal is currently being legally trapped in Montana, which likely holds 100 to 150 at most.
Wolverines naturally exist at extremely low densities. For example, 1,500-square-mile Glacier Park supports the largest, densest group south of Canada, yet it amounts to no more than 40 to 50 animals. Why? Because their territories are so immense. In addition to the fact that wolverines will always be very thinly spread even in the best of homelands, conservationists trying to secure the species' future have to take into account its low rate of reproduction. Gulos live 10 to 12 years in the wild, but females may not produce young until age three or four—and thereafter have an average of only two kits every other year.
Now add the growing challenge of climate change, which appears to be especially acute in polar and mountainous regions. According to mountain ecologist Dan Fagre of the U.S Geological Survey, the average temperature in rugged northwest Montana has risen 3 degrees F in just the past few decades. This is two to three times the rate recorded in other parts of the globe. Fagre finds the snowpack in Glacier melting off sooner, soils on the slopes heating up earlier and forests marching up into the alpine tundra zone. Boasting 150 glaciers when set aside in 1910, this park is on track to lose its last one by the year 2020, he points out. The implications for wolverines are anything but promising.
Researchers are now looking into the effects of increasing levels of disturbance in wolverine denning habitat, from motorized activities such as snowmobiling and heli-skiing to ski touring. Copeland is helping conduct a study in Idaho's national forests to see how wolverines in areas with heavy winter recreational use are faring compared to wolverines that rarely encounter people.
"It would be a mistake to view the wolverines holding on in the contiguous states as a single population," he says. "What's left is a metapopulation of widely scattered groups. Many are quite small and inhabit isolated mountain ranges, making the animals exceptionally vulnerable."
To endure, each of these surviving enclaves needs to be more carefully safeguarded. Most of all, each needs to be connected to others, for none is large enough to stay viable over time by itself. With that in mind, researchers are mapping out landscape corridors that would give gulos the best chance to keep in contact with one another throughout the mountain West. That the experts' models extend to Colorado, Utah and California is promising, especially since, within the past two years, one wolverine showed up in California and another in Colorado after an absence of nearly a century. Both were young males dispersing from points far to the north. Let's hope the next young explorer to arrive brings a date.
"Originally," Inman says, "we set aside national parks thinking those areas would safeguard nature by themselves. Then the challenge of conserving big, mobile species—especially carnivores like bears and wolves—forced managers to consider lands around the parks such as national forests as part of the same ecosystem. Wolverines make it clear that if we want to keep wildlife metapopulations going over time, we need to be working on a still larger scale."
A petition by Defenders and other conservation groups to list wolverines as endangered was recently accepted for consideration by the U.S. Fish and Wildlife Service. "The agency has acknowledged that the wolverine faces possible extinction simply due to the extremely low number of breeding adults," notes David Gaillard, Defenders' representative for the northern Rockies region. "When you add climate change, plus ongoing development and disturbance in the high country, this animal needs protection—now." As the magazine went to press, a decision on the listing petition was still pending.
Far roaming, incredibly hardy and indomitably wild, the wolverine embodies a will to live as bright and fierce as any force on the planet. The least we could do is grant this creature the freedom to keep traveling the high country on those big snowshoe paws, safe and undisturbed, while we search for ways to turn down the global thermostat for all our sakes.
Montana-based wildlife biologist Douglas H. Chadwick is a longtime Defenders contributor. This article is adapted from his book, The Wolverine Way, to be published this spring by Patagonia books.
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Beach Place
17101 N Bay Road
- Sunny Isles Beach, FL
Beach Place, nestled along the Florida Riviera in Sunny Isles Beach, is just steps from the beach and Intracoastal Waterway and minutes to Biscayne Boulevard, I-95, Bal Harbour Shops and Aventura Mall. The community comprises 308 one- and two-bedroom apartments and has just undergone a complete unit interior renovation to complement the exterior improvements undertaking by Jamestown. Banyan trees and lush native species, a billiard room, bocce court, dog park, and a resort-style heated pool with spa, sun decks, and grill areas all unite with a resident clubhouse, fitness facility, and business center to form this boutique-like, coastal-urban apartment community.

subset: commoncrawl


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Social and demographic influences are important for sleep attainment. Geographic
location has not been previously explored.
Data from the 2006 Behavioral Risk Factor Surveillance System (BRFSS) were used
(N = 157,319). Participants answered a question on Sleep Disturbance and Daytime
Fatigue. Thirty-six states/regions provided data on these items. Prevalence estimates
were adjusted for age, sex, ethnoracial group, education, income, employment, general
health, healthcare access, and depression. Chi-squared tests were conducted across
states and census regions, and pseudo-R2 values were computed for the
effect of state, relative to other predictors. To evaluate potential mediators of
census region differences, an analysis of p value change associated with specific
covariates and covariate groups was undertaken.
Adjusted prevalence rates of Sleep Disturbance differed across states/regions overall
(χ2 = 412.3, p < 0.0001), as well as separately for men
(χ2 = 139.5, p < 0.0001) and women (χ2
= 350.0, p < 0.0001), as did rates of Daytime Fatigue overall (χ2
= 245.7, p < 0.0001), and separately for men (χ2 = 117.5,
p < 0.0001) and women (χ2 = 181.2, p < 0.0001). Analysis
of pseudo-R2 values revealed that despite these significant findings,
state differences were an overall weak predictor, representing 1.30% to 1.73% of
the magnitude of the effect of the best predictor (mental health). When Census regions
were compared, significant differences were found for Sleep Disturbance (p = 0.002),
but after adjustment for covariates, these were no longer significant. Differences
existed for Daytime Fatigue in adjusted analyses overall (p < 0.0001), with the
West reporting the fewest complaints and the South reporting the most.
These results demonstrate that reports of sleep related complaints vary across states,
independent (at least partially) of factors that influence circadian rhythms (e.g.,
Grandner MA; Jackson NJ; Pigeon WR; Gooneratne NS; Patel NP. State and regional
prevalence of sleep disturbance and daytime fatigue. J Clin Sleep Med 2012;8(1):77-86.
Sleep problems are increasingly recognized as an important health outcome. These
various sleep problems, ranging from impaired sleep quality to short sleep duration,
may be associated with poor overall health and all-cause mortality,1–4 as well
as psychiatric (e.g., depression,5,6 anxiety7–9),
metabolic (e.g., obesity,10–12
cardiovascular (e.g., hypertension15,16), and other outcomes, including serious
auto accidents.17,18
Increasing attention has focused on social, demographic, and societal influences
on sleep.1,2,19,20
One such influence that has received little attention is geographical location.
Although several recent reports have discussed how characteristics of neighborhood
may influence sleep-related outcomes,21–25
and many reports have focused on national data,26–29 regional and state-level sleep
data have not been a focus of previous inquiry. These data could assist health authorities
at various levels (national, regional, and state) discern the public health burden
of sleep disturbance.
Capitalizing on the existence of a large national sample, we focus on whether there
are state or regional differences regarding prevalence of sleep-related complaints
such as daytime fatigue and sleep disturbance (characterized as problems falling
asleep, problems staying asleep, and/or sleeping too much). Our hypotheses are:
(1) sleep disturbance and daytime fatigue will be differentially distributed across
states, (2) the prevalence of sleep disturbance and daytime fatigue across states
will be different for men and women, and (3) prevalence of sleep disturbance and
daytime fatigue will differ by Census region, reflecting broad geographical differences
in sleep-related complaints.
Current Knowledge/Study Rationale: Sleep disturbance is an important public
health concern. However, geographic dispersion of sleep problems, and the factors
that may play a role, have been largely unexplored.
Study Impact: This study includes the first sleep maps for the USA that include
data on sleep disturbance and daytime fatigue across most states/territories. In
addition, this study demonstrates that not only are sleep and fatigue problems distributed
differentially by state and region, but that these differences are partially explained
by measurable mediators.
Data from the 2006 Behavioral Risk Factor Surveillance System (BRFSS)30 were used for this analysis. The BRFSS is an
annual, state-based, random-digit-dialed telephone interview survey of adults aged
≥ 18 years from all over the United States. It is the world's largest telephone
survey, designed to monitor health-related behaviors in the general population.
The overall response rate (completed interviews relative to total eligible households)
varied across states, with a mean of 41.1%, median of 40.5%, and range of 20.5%
to 72.5%.31 Of those who completed interviews,
> 98% of respondents completed the Sleep Disturbance and Daytime Fatigue items,
suggesting that it is likely that the present data accurately represent the sample
selected for study. In addition, reliability and validity are improved with the
use of BRFSS-specific weighting scores, which weight each respondent's data, taking
into account variables such as region, sex, race/ethnicity, and age to ensure that
for each telephone area code region, responses match Census distributions.
Thirty-six states/regions were represented. This included 33 states: Alabama, Alaska,
Arkansas, California, Delaware, Florida, Georgia, Hawaii, Indiana, Iowa, Louisiana,
Maine, Michigan, Minnesota, Mississippi, Missouri, Montana, Nevada, New Hampshire,
New Mexico, North Dakota, Oklahoma, Oregon, Rhode Island, South Carolina, Tennessee,
Texas, Utah, Vermont, Virginia, West Virginia, Wisconsin, and Wyoming. Also, the
non-state regions of the District of Columbia, Puerto Rico, and the U.S. Virgin
Islands were included. See Supplementary Table S1 for
the N for each state, by Model, for all participants and separated by sex. The N
for each state ranged from 1974 (Alaska) to 9961 (Florida), with a median of 4987.5.
Participants were respondents who had answered a question on Sleep Disturbance:
"Over the last 2 weeks, how many days have you had trouble falling asleep
or staying asleep or sleeping too much?" and respondents who answered the
question, "Over the last 2 weeks, how many days have you felt tired or had
little energy?" Answers for both questions ranged from 0-14. However, the
distributions were bimodal, with peaks at 0 and 14, with the preponderance of reports
≤ 3 and ≥ 12 days. In this case, linear regression is not appropriate
because of violations of the normality and homoscedasticity assumptions. Sleep Disturbance
and Daytime Fatigue were thus dichotomized into those who report complaints ≥
6 days and those who report complaints < 6 days. Although the results did not
appreciably change when cutoffs were placed anywhere between 3/14 and 12/14 days,
the cutoff used (6/14 days) equates to 3/7 days, which is the clinical cutoff for
Other variables employed in the current analysis served as covariates included at
the individual and geographic levels. Individual-level variables included age, sex,
body mass index (BMI), number of alcoholic drinks per month, smoking (never, former,
some days, every day), ethnoracial group (White, Black/African American, Hispanic/Latino,
Asian/Other, and Multiracial), education (less than high school, high school graduate,
some college, college graduate), income level (< $10,000 pre-tax income per year,
$10,000-$15,000, $15,000-$20,000, $20,000-$25,000, $25,000-$35,000, $35,000-$50,000,
$50,000-$75,000, > $75,000), employment status (employed, self-employed, retired,
student, homemaker, unemployed < 1 year, unemployed > 1 year, unable to work),
physical health (days in past 30 poor physical health), mental health (days in past
30 poor mental health), general health (excellent, very good, good, fair, poor),
access to healthcare (last checkup within past year, within past 2 years, within
past 5 years, more than 5 years ago, never), and depressed mood ("How many
days in the last 2 weeks did you feel down or depressed?"). Previous analyses
have found that these variables are significant predictors of sleep complaint in
this sample.33 State-based covariates
(geographical) were included in the model because they are related to factors that
play a role in habitual light exposure. These variables included geographic center
of the state (latitude and longitude), mean high temperature, percent sunlight exposure,
and shortest day length. These data were gathered from publicly available sources.34
Response bias was addressed by comparing sociodemographics of responders versus
non-responders to the Sleep Disturbance and Daytime Fatigue questions. There were
no major group differences identified, indicating minimal response bias at least
at the individual level. Sunshine exposure was a mean of 63% in the non-missing
group versus 58% in the missing group, suggesting that those in states with less
sunshine were more likely to not respond to at least one of the outcome items.
All analyses were performed using Stata Version 11 software (StataCorp LP, College
Station, TX). Logistic regression was utilized to estimate prevalence and adjust
for covariates. Plausible covariates were identified a priori. Sampling weights
specifically developed for BRFSS 2006 were applied to address population representativeness.30 Prevalence estimates were calculated
using a hierarchical approach. State was included as a fixed effect. The unadjusted
model included only Sleep Disturbance or Daytime Fatigue. Adjusted models added
known covariates, including age, sex, race/ethnicity, education, income, employment,
BMI, alcohol intake, smoking, mental health, physical health, general health, healthcare
access, and depressed mood, as well as state-based covariates including latitude
and longitude of the state's geographic center, mean temperature, percent sunshine
exposure, and length of the shortest day of the year. Analyses then examined both
state-level differences and region-level differences separately.
State-level differences were investigated using χ2 global
tests for differences. Because of the large sample size, this study is highly powered
to detect even small differences across states. Because of this, a strategy to estimate
the relative effect size of geography (i.e., state) in the estimation of Sleep Disturbance
and Daytime Fatigue was undertaken, utilizing McFadden's pseudo R2 to
determine the relative importance of state differences, compared to other effects
in the adjusted model. Other effects included Demographics (age, sex, race/ethnicity),
Socioeconomics (education, income, employment), Body Mass (body mass index), Mental
Health (depression, mental health), Physical Health (general health, physical health,
checkup), and Substances (alcohol, smoking). Pseudo R2 values for each
independent variable were calculated as the change in pseudo R2 from
the full model to a model without the independent variable category. Because these
values can only be evaluated relative to other values, they were transformed so
that they expressed the ratio of the pseudo R2 value, relative to the
highest Pseudo R2 value for that analysis. For all analyses, the largest
pseudo R2 value was for Mental Health, so all values were expressed as
[(pseudo Rvariable2)/(pseudo RMental Health2)],
expressed as a percentage. Pseudo R2 values, while analogous to R2
derived from least squares regression, cannot be interpreted in the same manner
(as proportions of variance explained). As a result, pseudo R2 values
cannot be interpreted independently; rather, they can only be interpreted relative
to other independent variables in models predicting the same outcome. Despite this
limitation, this analysis strategy can provide information on the importance of
state differences, relative to other predictors.
To evaluate regional differences, χ2 global tests for differences
were conducted across Census regions35
using the same covariates as in the analysis of state differences. A post hoc analysis
exploring which covariates mediated observed relationships was conducted. Because
some covariates were conceptually related (e.g., latitude and longitude, sunlight,
and day length), some covariates were analyzed together. The following covariates/covariate
groups were considered as possible mediators: sex, age, race/ethnicity, socioeconomics
(education, income, employment), geography (latitude, longitude), weather (temperature,
sunlight, day length), BMI, physical health (physical health, general health), mental
health, alcohol, smoking, and medical checkup. The influence of covariates (or covariate
groups) on census region effect size was examined to understand the how the covariates
confound the census region relationships. A measure of covariate influence was computed
in terms of percentage change in the census region estimates after adjustment for
a given covariate. We examined the confounding influence of the covariates in terms
of percentage change in the census region estimates after adjustment. This was calculated
by subtracting the unadjusted estimate from the adjusted estimated and dividing
by the adjusted estimate [(Adjusted-Unadjusted)/(Adjusted)]. Census region estimates
were referenced to the South region. Conventional interpretation of confounding
via percentage change in estimates regards a covariate to be a confounder when there
is greater than 10% change from the unadjusted estimate.
In addition, the mediational effects of covariates (or covariate groups) on census
region significance was examined by calculating the resultant change in statistical
significance for census region when unadjusted for each covariate. Each potential
covariate set was individually removed from the full model (model 2), and Census
region global p values were estimated. Differences in Census region p values in
the full model to the model with missing covariate sets were computed. As such,
those covariates (or covariate groups) with negative values reflect covariates that
would cause the adjusted p value to become smaller by that amount, while those with
positive values indicate variables that cause the p value to increase by that amount.
Using this approach, if the p value change were 0.05, then even if an analysis that
excluded the variable had a very low p value (e.g., p = 0.00001), the analysis that
includes that variable would be nonsignificant (e.g., (0.00001 + 0.05 = 0.05001).
This approach was chosen due to the complications of conducting a standard mediation
analysis (i.e., Sobel-Goodman) because of the binary outcome and multinomial predictor.
A total of 183,436 individuals were included in the unadjusted analyses, and 157,319
individuals were included in the adjusted analyses (due to missing covariates).
Sociodemographic, health, and geographic/climactic characteristics of the sample
are reported in Table 1 by presence of absence of self-reported
Sleep Disturbance and Daytime Fatigue. Sleep Disturbance was different for groups
across all levels of all variables except for temperature. Daytime Fatigue was similarly
different for groups across all levels of all variables, except for age, alcoholic
drinks/month, and temperature.
Differences in characteristics of participants relative to Sleep Disturbance and
Daytime Fatigue
Differences in characteristics of participants relative to Sleep Disturbance and
Daytime Fatigue
(more ...)
State-based prevalence estimates of Sleep Disturbance are reported in
Table S2 (see supplement that follows). In unadjusted analyses, prevalence
rates ranged from 7.2% to 26.0%, with a mean rate of 18.5% (SD 3.3%). For men, the
range was 6.2% to 22.1%, with a mean of 15.8% (SD 2.9%); for women, the range was
8.1% to 29.6%, with a mean of 21.1% (SD 3.9%). In the adjusted model, prevalence
rates for the entire sample ranged from 7.8% to 22.9%, with a mean rate of 18.3%
(SD 2.4%). For men, the range was 6.2% to 20.4%, with a mean of 15.4% (SD 2.1%);
for women, the range was 9.4% to 25.4%, with a mean of 21.3% (SD 2.8%). Global χ2
tests demonstrated differences in Sleep Disturbance across states in the entire
group (χ2 = 562.8, p < 0.0001), as well as for men (χ2
= 187.6, p < 0.001) and women (χ2 = 493.5, p < 0.0001)
separately. After adjustment for covariates, these relationships all remained highly
significant at the p < 0.0001 level ([all] χ2 = 386.3,
[men] χ2 = 143.6, [women] χ2 = 286.6).
State-based prevalence estimates of Daytime Fatigue are reported in
Table S5. In unadjusted analyses, prevalence rates ranged from 16.4%
to 30.0%, with a mean rate of 21.8% (SD 3.4%). For men, the range was 11.4% to 24.8%,
with a mean of 17.9% (SD 3.1%); for women, the range was 19.5% to 35.3%, with a
mean of 25.5% (SD 4.1%). In the adjusted model, prevalence rates for the entire
sample ranged from 18.0% to 25.4%, with a mean rate of 21.6% (SD 2.0%). For men,
the range was 13.9% to 22.3%, with a mean of 17.4% (SD 2.0%); for women, the range
was 21.2% to 29.6%, with a mean of 25.8% (SD 2.3%). Global χ2
tests demonstrated differences in Daytime Fatigue across states at the p < 0.0001
level in the entire group (χ2 = 649.5), as well as for men
(χ2 = 228.5) and women (χ2 = 539.8)
separately. After adjustment for covariates, these relationships all remained highly
significant at the p < 0.0001 level ([all] χ2 = 190.0,
[men] χ2 = 95.9, [women] χ2 = 140.8).
Figures 1 and 2 display cartographic
representations (by state) of adjusted prevalence rates for Sleep Disturbance and
Daytime Fatigue. Adjusted prevalence weights across the total sample (men and women)
were pooled and ranked separately for Sleep Disturbance and Daytime Fatigue. Consequently,
since women reported higher percentage of Sleep Disturbance and Daytime Fatigue,
the image for women displays more states in higher quintiles and the figure for
men represents more states in lower quintiles.
Graphical representation of prevalence rates for Sleep Disturbance by state
Inset boxes for Alaska, Hawaii, Puerto Rico, U.S. Virgin Islands and Washington
DC, which do not otherwise appear on the map. Colors denote sextile, which are reported
in Table S4. Higher sextile numbers (darker shade) denote higher
prevalence rates. States that appear in white (i.e., unshaded) did not collect Sleep
Disturbance data.
Graphical representation of prevalence rates for Sleep Disturbance by state
Graphical representation of prevalence rates for Daytime Fatigue by state
Inset boxes for Alaska, Hawaii, Puerto Rico, U.S. Virgin Islands and Washington
DC, which do not otherwise appear on the map. Colors denote sextile, which are reported
in Table S4. Higher sextile numbers (darker shade) denote higher
prevalence rates. States that appear in white (i.e., unshaded) did not collect Daytime
Fatigue data.
Graphical representation of prevalence rates for Daytime Fatigue by state
A determination of the proportion of variance explained by the State variable for
Sleep Disturbance and Daytime Fatigue could not be calculated because State is a
nominal variable and our outcomes were binomial. Notwithstanding, a change in model
fit was examined relative to other groups of independent variables. In all analyses
(total sample and by gender) for both outcomes (Sleep Disturbance and Daytime Fatigue),
Mental Health was the strongest predictor and was thus used as the reference value
to compute ratios for other variables. These values are displayed in
Table S5. The improvement in model fit associated with the State variable
was of a much smaller magnitude than Mental Health, representing an effect that
ranged in size from 1.30% to 1.73% of the size of the effect for Mental Health.
Compared to the other independent variables, this effect was of the smallest magnitude,
followed by Body Mass (range 2.20% to 5.06%).
State prevalence rates were next pooled by census region, with states divided into
West, Midwest, South, and Northeast regions. See Table 2
for sample characteristics by Census region, with one-way ANOVAs showing regional
differences in all covariates except for sex. Prevalence rates by Census region
are reported in Table 3 before and after inclusion of covariates.
In unadjusted analysis (of the combined sample and in women), a significantly differential
rate of report of Sleep Disturbance was found, with the least prevalence in the
West and the most in the South. This difference was no longer significant after
adjustment. For Daytime Fatigue, unadjusted prevalence rates were lowest in the
West and highest in the South for the combined sample and women, and in the Midwest
for men. After adjustment, significant differences remained, with the lowest values
in the West and the highest values in the South for the combined sample and for
women, and in the Northeast for men.
Differences in characteristics of participants relative to Census region
Differences in characteristics of participants relative to Census region
Unadjusted and adjusted differences in prevalence of Sleep Disturbance and Daytime
Fatigue by Census region*
* Census Regions include West (Alaska, California, Hawaii, Montana, Nevada,
New Mexico, Oregon, Utah, Wyoming); Midwest (Indiana, Iowa, Michigan, Minnesota,
Missouri, North Dakota, Wisconsin); South (Alabama, Arkansas, Delaware, Florida,
Georgia, Louisiana, Oklahoma, South Carolina, Tennessee, Texas, Virginia, Washington
DC, West Virginia); and Northeast (Maine, Rhode Island, New Hampshire, Vermont).
Unadjusted and adjusted differences in prevalence of Sleep Disturbance and Daytime
Fatigue by Census region*
When men were evaluated alone, no differential rates of reporting were found among
Census regions for Sleep Disturbance, but differences for Daytime Fatigue were found
in unadjusted analysis, with the highest rates in the Midwest and the lowest in
the West, and adjusted analyses, with the highest rates in the South and, again,
the lowest rates in the West. When women were evaluated separately, the pattern
for Sleep Disturbance was the same as when the groups were combined, with a significant
difference in unadjusted analyses only (fewest complaints in the West and the most
in the South). For Daytime Fatigue, there were significant differences for both
adjusted and unadjusted models, demonstrating the highest rate of problems in the
South and the fewest problems in the West.
A confounding analysis regarding percent change in estimates due to inclusion of
covariates was conducted. Mental health had the greatest effect on Sleep Disturbance
for the Western region, such that adjusting for mental health resulted in > 15%
change in the estimate regardless of gender. No other covariates showed confounding
at a > 10% level for any of the other regions. For the daytime fatigue outcome,
geography (latitude and longitude) and mental health produced > 20% change in
the Western region estimate, regardless of gender. Weather was a substantial confounder
(> 10%) for the overall and men-only models. For the Northeast region, geography
was the most influential confounder across genders (> 10%) followed by weather
for the overall and men-only models (> 10%). For complete results see
Table 4.
Examination of covariate mediation on Census region effects, expressed as percent
change in Census region estimate after adjustment (reference = South)
Examination of covariate mediation on Census region effects, expressed as percent
change in Census region estimate after adjustment (reference = South)
To determine which covariates were mediators of the relationship between Census
region and both Sleep Disturbance and Daytime Fatigue, we examined the change in
p value associated with each covariate set. For the present analyses, these results
are displayed in Table S6. For Sleep Disturbance, the
largest change in p value was seen for Race/Ethnicity. In the combined sample, p
value change of > 0.05 (which would produce a nonsignificant result regardless
of other covariates) was produced by (in order of magnitude) Medical Checkup, Weather
(day length, temperature, sunshine), BMI, and Geography (latitude, longitude). When
men and women were examined separately, variables with a p value change > 0.05
for men included Geography, Smoking, Medical Checkup, Race/Ethnicity, and BMI, while
variables for women included Race/Ethnicity, Weather, and Medical Checkup.
The present study evaluated state-based prevalence of self-reported Sleep Disturbance
and Daytime Fatigue across 36 states/non-state regions. We created a cartographic
map of the United States representing the population burden for sleep related problems,
adding a new dimension to current knowledge of population level sleep problems that
has some translational value at the clinical level. Furthermore, we examined differences
in Sleep Disturbance and Daytime Fatigue across Census regions and examined potential
mediators of these differences.
Overall, the prevalence of Sleep Disturbance was differentially distributed across
states in the entire sample and by gender. Adjusting for a large number of plausible
confounders did not completely account for the geographical differences observed.
This suggests that there is an independent effect of "place" on Sleep
Disturbance and Daytime Fatigue that is not completely explained by demographics,
socioeconomics, health, regional differences in sunlight and weather patterns, and
other factors. It is unclear why individuals in different places would report different
levels of these outcomes, though other factors not assessed, such as regional differences
in public policy, social norms, beliefs and attitudes, or habitual health-related
behaviors, may explain some of these differences.
Pseudo R2 values were computed to address the question of how much of
Sleep Disturbance and Daytime Fatigue is an effect of State, relative to other potential
determinants. The results of these analyses showed that although there was a discernable
state effect, it was small compared to the effects of mental health. The effects
of State were much closer in magnitude to the effects of Body Mass and Substance
Use. This demonstrates, though, that the effects of geography on these complaints
are comparable to those of other determinants of sleep disturbance that are well-described
and known to play an important role in the interface between sleep and public health.36 Further, this suggests that in addition
to recent initiatives to better understand the relationship of sleep to obesity,10,37–43
attention should be paid to geography as well.
When comparing Census regions instead of specific states, interesting patterns emerged.
Overall, the findings suggest that, in general, those in the South are often most
likely to report Sleep Disturbance and Daytime Fatigue, and those in the West are
often least likely. This finding is consistent with other geographic studies, showing
that states in the South are often at the greatest risk of negative health outcomes.44
To evaluate which factors explain differences in Sleep Disturbance and Daytime Fatigue
across Census regions, we conducted an analysis that evaluated the change in the
region p value for given sets of covariates. This processes is analogous to performing
multiple and prespecified backward selection procedures, but for the purposes of
examining covariate influence rather than model selection. Caution should be applied
when interpreting these results. While conventional procedures for examining confounders
make use of similar p value based assessments, it is important that relative change
in effect size is not ignored. While examining a single measure of relative effect
size change is complicated by the categorical independent variable, one cannot simply
look at significance as the determinant of confounding. Given these limitations,
the results showed that very few of these factors explained differences in Daytime
Fatigue across Census regions—none of these covariates produced a p value
increase ≥ 0.01 in the overall sample or when men were examined alone. When
women were examined alone, changes ≥ 0.01 but ≤ 0.05 (necessary to render
the effect nonsignificant) were seen for race/ethnicity, healthcare access, and
weather. Regarding Sleep Disturbance, though, many variables impacted the p value.
In the overall analysis (men and women combined), the largest p value change was
seen for race/ethnicity, followed by healthcare access, weather, BMI, and latitude/longitude.
The inclusion of any of these would render regional differences nonsignificant.
Other notable effects were seen for age and smoking. When men were examined alone,
a p value change ≥ 0.05 was found for latitude/longitude, smoking, medical
checkup, race/ethnicity and BMI. P value changes of ≥ 0.01 were seen for age
and socioeconomic factors. Similarly, when women were examined alone, p value change
≥ 0.05 was found for race/ethnicity, weather, healthcare access, and BMI.
P value change ≥ 0.01 was seen only for physical health. These results suggest
that regional differences in Sleep Disturbance are best explained by regional differences
in race/ethnicity (separate from socioeconomics), healthcare access and BMI, with
strong effects for latitude/longitude and smoking in men and weather in women.
There are a number of limitations to this study. First, not all states reported
these outcome measures, including some of the most populous, including New York
and Illinois. A better map of population burden across the U.S. will hopefully be
drawn at a time when more states begin reporting these outcomes. Second, the measures
of Sleep Disturbance and Daytime Fatigue are very broad compound measures, and those
reporting these complaints likely include a wide variety of individuals, including
those with sleep disorders (e.g., sleep apnea, insomnia), opposing or orthogonal
complaints (e.g., insomnia and hypersomnia), and subclinical problems. Furthermore,
they do not specifically address the issue of short sleep duration, which can be
voluntary or due to other sleep disorders. Thus, it is impossible to extrapolate
further than these broadly defined subjective complaints that have relatively high
sensitivity but consequently low specificity. This limits the abilities of this
study to meet the aim of informing allocation of resources. Third, Age × State
and Sex × State interactions were not included, as this would introduce an
additional 36 variables into the model for each interaction; this would greatly
impact our statistical power and contribute disproportionately to likelihood of
type II error. To address potential interactions, we conducted both a combined analysis
and an analysis stratified by gender. It is possible that geographic relationships
were confounded by age and sex. Fourth, this study is based on a telephone survey
with a modest (though acceptable) response rate. This is further complicated since
not all survey respondents responded to both sleep-related items; however, those
that responded were generally similar to those who did not respond to both items.
The primary problem associated with the selection bias that inevitably occurs with
phone surveys is generalizability of the sample to the general population. The present
study addresses generalizability in a number of ways. First, the very large sample
size mitigates some of the bias inherent in nonresponse. Further, generalizability
of the sample to the general population is maximized with the use of weighting scores,
which ensure that each region × age × sex × race/ethnicity group
is accurately weighted in analyses. The combination of large sample size and individual
subject weights specifically developed for BRFSS 2006 ensure that the results closely
represent the characteristics of the American population.
Despite these limitations, this analysis contributes to the current literature in
three ways. First, we demonstrate that sleep-related complaints vary by geographical
area at the State and Census region level. Few epidemiological studies of sleep
have taken geography into account,29 and
even fewer experimental studies have recognized this limitation.2 These results demonstrate that geographical region should be
included in models of sleep in the population, as they have in other important health
domains, such as obesity.44 Second, this
analysis suggests that regional differences in sleep-related complaints are likely
to be independent (or at least partially so) of the geographical factors that influence
circadian rhythms (i.e., amount of sunlight and temperate climate),45,46 as the distribution
did not consistently favor brighter, more comfortable regions. Third, these state-based
prevalence rates allow for comparison to other state-based rates. For example, many
of the states that report worse sleep and fatigue problems are the same states that
tend to report higher prevalence of other conditions, such as obesity.44
In addition, these unique extensions of population level sleep data have research,
public health policy and clinical pertinence. From a research perspective, this
analysis sets the stage for several future research questions, including: (1) What
would a complete map of data look like? (2) Why are there persistent interstate
adjusted differences? (4) Are there intrastate driving factors not captured in our
analysis? and (5) How might these representations change with time?
Developing a state-level understanding of rates of sleep-related problems (and tracking
these over time) may have a number of important clinical and public health implications.
As a model, the CDC has tracked the obesity epidemic over for more than 2 decades
and shared this publicly by publishing BMI maps of the USA.47 This cartographic data has been used to implement important
public health programs and policies and track their effects.
Also, health authorities in certain states may regard the sleep disturbance and
fatigue as significantly burdensome to their population's health, especially if
they are overseeing a region with particularly high prevalence rates. Certain regions
(e.g., states with higher prevalence of Sleep Disturbance) might benefit from screening
programs for sleep symptoms, as we better understand the extent these problems represent
health risks (these items in particular have been associated with a number of health
risks33,48) or possible sleep disorders.
Although daytime fatigue is a common feature of a number of sleep disorders, it
can be an indicator of many other types of adverse health outcomes, such as cardiometabolic
disease, cancer, and depression. An increased prevalence may indicate that the clinical
importance of access to sleep specialists may be more pronounced in these regions,
though an increase in screening for sleep disorders might be helpful regardless
of prevalence.
This was not an industry supported study. The authors have indicated no financial
conflicts of interest.
This work was supported by T32HL007713. Also, we wish to thank the Centers for Disease
Control and Prevention for collecting these data and making it available. Data analysis
was performed at the University of Pennsylvania.
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Grandner MA, Perlis ML, Martin JL, et al., authors. Sleep complaints and fatigue
decline across the lifespan: Getting older does not necessarily mean poor subjective
sleep and daytime fatigue. Sleep. 2010;33:A345
Inset boxes for Alaska, Hawaii, Puerto Rico, U.S. Virgin Islands, and Washington
DC, which do not otherwise appear on the map. Figures represent (A) men and
(B) women. Colors denote sextile, determined separately for the total sample,
men, and women. Sextiles are reported in Table S4. Higher sextile
numbers (darker shade) denote higher prevalence rates. States that appear in white
(i.e., unshaded) did not collect Sleep Disturbance data.
Inset boxes for Alaska, Hawaii, Puerto Rico, U.S. Virgin Islands, and Washington
DC, which do not otherwise appear on the map. Figures represent (A) men and
(B) women. Colors denote sextile, determined separately for the total sample,
men, and women. Sextiles are reported in Table S4. Higher sextile
numbers (darker shade) denote higher prevalence rates. States that appear in white
(i.e., unshaded) did not collect Daytime Fatigue data.
Sample sizes by state for men and women in unadjusted and adjusted analyses
Sample sizes by state for men and women in unadjusted and adjusted analyses
Unadjusted and adjusted prevalence rates (with 95% confidence interval) of Sleep
Disturbance by state
Unadjusted and adjusted prevalence rates (with 95% confidence interval) of Sleep
Disturbance by state
Unadjusted and adjusted prevalence rates (with 95% confidence interval) of Daytime
Fatigue by state
Unadjusted and adjusted prevalence rates (with 95% confidence interval) of Daytime
Fatigue by state
Sextiles of prevalence rates for Sleep Disturbance and Daytime Fatigue
Sextiles of prevalence rates for Sleep Disturbance and Daytime Fatigue
Pseudo R2 and ratioa that describe relative
change in model fit for each group of independent variables
a R2 is expressed as McFadden's pseudo R2 which can only be
evaluated relative to other values. Thus, the ratio represents the ratio of that
R2 to the largest value for that analysis (Mental Health, in all cases).
Pseudo R2 and ratioa that describe relative change in model fit for each group of
independent variables
Effects of covariates on Census region differences in Sleep Disturbance and Daytime
Fatigue (expressed as p value difference)
Effects of covariates on Census region differences in Sleep Disturbance and Daytime
Fatigue (expressed as p value difference)


text:
Shavua Tov!
Definition of awareness is knowledge, to be informed. This was my goal when I opened a Facebook group page last week.
I want to bring an awareness of the plight of Israeli citizens who live in the South of Israel. What plight you ask.... the firing of thousand of missiles from Gaza into southern Israel cities, moshavim, kibbutzim and yishuvim.
The other day I read a talkback from a very young and naïve American girl who was answering a southern mother posting about her children's fears and the inaction of the government. This mother wanted to know why the government has not sent the IDF to clean up Gaza.
This young poster replied "politics may have to come before human life because in the long run, in the big picture-people will be SAFER." I want to know if she is for real...


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NEW YORK -- Coach Pete Carroll said owner Paul Allen played "big licks" with his own band on stage late into the night at the Seattle Seahawks team party following Sunday's Super Bowl XLVIII victory.
"Sleep wasn't in order last night," Carroll said Monday at the Sheraton New York news conference. "There wasn't much of it. We can sleep some other time."
The Seahawks throttled the Denver Broncos 43-8 at MetLife Stadium, earning the first sports championship for Seattle since the NBA's Sonics in 1979.
"I think it's unique it was here in New York/New Jersey," Carroll said. "I know there was concern about the weather and all but that wasn't an issue, it was just a great event."
Delays of up to 90 minutes were seen on public transit from New York to East Rutherford, N.J. Some trains from New York to Secaucus, N.J., where free shuttles were available to the game, experienced delays of more than an hour.
"We had a couple things we obviously will review and improve on," commissioner Roger Goodell said Monday morning, congratulating the region on a successful week.
"We are thrilled with not only their effort but the outcome," Goodell said. "Obviously our work continues today, getting our fans back home."
Weather did not impact the game. Light drizzle fell during the game, which kicked off with a temperature near 50 degrees, and grew to rain and then heavy snow by early morning Monday. The National Weather Service issued a winter storm warning calling for five to eight inches of snow by 7 p.m. ET.
There was plenty of sun and relative warmth Saturday and Sunday. Goodell said close to 25,000 people used the NFL-staged toboggan run and more than 1.25 million experience Super Bowl Boulevard.
"Nineteen teams now have won a Super Bowl amongst our 32," Goodell said. "I guess most importantly for Pete Carroll and Seahawks fans, they have the youngest team in the league right now.
Carroll, who coached the Jets 20 years ago, said the Seahawks envisioned this moment from the time he was hired. He said the mentality is not arrogant, it was to build a foundation of confidence the team created with a strict, disciplined approach.
"We had an extraordinary week in the area," Carroll said. "It was a great week. Everything went just exactly as we had hoped, of course the game did as well, so we're really happy about that."
One of the young players Carroll built a trust level with, linebacker Malcolm Smith, played for Carroll at USC. He was the 242nd overall pick in the draft, not invited to the Scouting Combine and became the ninth defensive player to win Super Bowl MVP. Smith was asked if he considered when he left Seattle that he might need a suit for the MVP press conference.
"I'm dressed to go to Disney World," Smith said Monday morning. "We had a lot of guys, for it to be me I'm surprised but excited."
Seattle led the NFL with 39 regular-season turnovers and tacked on four Sunday.
Carroll said flattering conversation about the Seahawks as a great defense in line with the 2000 Ravens or 1985 Bears isn't on his mind, and he's not able to measure whether the Seahawks belong at this stage.
That will come in time, with multiple successes on the Super Bowl stage, Carroll said. While schools in the Seattle region are expected to be closed Wednesday when the Seahawks celebrate with a championship parade through downtown at 11 a.m. Pacific, the mantra of the team to be '"Seahawks 24/7 and Leave No Doubt" won't be paused.
"The first meeting that we'll have will be tomorrow," Carroll said. "Our guys would be surprised if we didn't. We really have an eye on what's coming and don't dwell on what happened. We'll have a celebration with our fans Wednesday and enjoy it.
"I think we are in a very fortunate situation. One of the things that happen is teams have a big fallout after the Super Bowl. We won't do that."


text:
Once again a call received, but it was from Raju's uncle. He asked her about their life. Madhu said that they were so happy. He asked about Raju's health condition. She managed very well. Uncle daughter was amazed that Madhu was complaining about Raju. She will make this small thing into a big problem. Balu told Raju that there will be some problems will come and go. But Raju should adjust. Now madhu was carrying a baby and mood changing was usual.
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Book 17, Adventures of Tintin
No. of pages 64
Love this book? Recommend it to your friends! Fill in their details below and we will send them an email on your behalf. If you wish to include a message please fill in the message box! Go recommend!
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Explorers on the Moon is book 17 in the series Tintin. Explorers on the Moon is an illustrated book and features the illustrations of Herge. It was written for young readers to enjoy. The book includes the characters Tintin and Snowy.
Genres: adventure
This book is in the following series:


text: Neuro-Oncology Glossary of Terms You may hear many words associated with oncology that you have not heard before. Please ask for an explanation for any terms you may not understand. You may hear the following common terms before, during and after your treatment. 3-Dimensional conformal radiation therapy: A procedure that uses a computer to create a 3-dimensional picture of the tumor. This allows doctors to give the highest possible dose of radiation to the tumor, while sparing the normal tissue as much as possible. Anaplastic: A term used to describe cancer cells that divide rapidly and have little or no resemblance to normal cells. Astrocyte: A large, star-shaped cell that holds nerve cells in place and helps them work the way they should. It is a type of glial cell. Astrocytoma: A tumor that begins in the brain or spinal cord in small, star-shaped cells called astrocytes. Benign: Not cancerous. Benign tumors may grow larger, but do not spread to other parts of the body. Biopsy: The removal of cells or tissues for examination by a pathologist. The pathologist may study the tissue under a microscope or perform other tests on the cells or tissue. Brachytherapy (BRAK-ee-THER-ah-pee): A type of radiation therapy in which radioactive material sealed in needles, seeds, wires, or catheters is placed directly into or near the tumor. Also called radiation brachytherapy, internal radiation therapy, and implant radiation therapy. Brain stem: The part of the brain that is connected to the spinal cord. Brain stem glioma (glee-OH-muh): A tumor located in the part of the brain that connects to the spinal cord (the brain stem). It may grow rapidly or slowly, depending on the grade of the tumor. Burr hole: A small opening in the skull made with a surgical drill. Cancer: A term for diseases in which abnormal cells divide without control. Cancer cells can invade nearby tissues and can spread through the bloodstream and lymphatic system to other parts of the body. Catheter: A thin flexible, hollow tube through which fluids enter or leave the body. Radioactive materials may be placed in catheters that are placed near the cancer. Cell: The individual unit that makes up the tissues of the body. All living things are made up of one or more cells. Cerebellum (ser-uh-BEL-um): The portion of the brain in the back of the head between the cerebrum and the brain stem. The cerebellum controls balance for walking and standing, and other complex motor function. Cerebral hemisphere (she-REE-bral HEM-is-feer): One half of the cerebrum, the part of the brain that controls muscle functions and also controls speech, thought, emotions, reading, writing, and learning. The right hemisphere controls the muscles on the left side of the body, and the left hemisphere controls the muscles on the right side of the body. Cerebrospinal fluid (she-REE-broh-SPY-nul): CSF. The fluid that flows in and around the hollow spaces of the brain and spinal cord, and between two of the meninges (the thin layers of tissue that cover and protect the brain and spinal cord). Cerebrospinal fluid is made by tissue called the choroid plexus in the ventricles (hollow spaces) in the brain. Cerebrum (she-REE-brum): The largest part of the brain. It is divided into two hemispheres, or halves, called the cerebral hemispheres. Areas within the cerebrum control muscle functions and also control speech, thought, emotions, reading, writing, and learning. Chemotherapy: Treatment with drugs that kill cancer cells. Clinical trial: A type of research study that tests how well new medical approaches of screening, prevention, diagnosis, or treatment of a disease. Contrast material: A dye or other substance that helps to show abnormal areas inside the body. It is given by injection into a vein, by enema, or by mouth. Contrast material may be used with x-rays, CT scans, MRI or other imaging tests. Craniotomy (KRAY-nee-AH-toh-mee: An operation in which an opening is made in the skull. CT (computerized tomography) scan: A series of detailed pictures of areas inside the body taken from different angles. The pictures are created by a computer linked to an x-ray machine. Also called CAT scan, computed tomography scan, computerized axial tomography scan, and computerized tomography. Ependymoma (eh-PEN-dih-MOH-muh)): A type of brain tumor that begins in cells lining the spinal cord central canal (fluid-filled space down the center) or the ventricles (fluid-filled space down the center) or the ventricles (fluid-filled spaces of the brain). Ependymomas may also form in the choroid plexus (tissue in the ventricles that make cerebrospinal fluid). External radiation therapy: A type of radiation therapy that uses a machine to aim high-energy rays at the cancer from outside of the body. Also called external beam radiation therapy. Gamma ray: A type of high-energy radiation that is different from an x-ray. Gilaial cell (GLEE-ul): Any of the cells that hold nerve cells in place and help them work the way they should. Glioblastoma (GLEE-oh-blas-TOH-muh): A fast-growing type of central nervous system tumor that forms from glial (supportive) tissue of the brain and spinal cords and has cells that look very different from normal cells. Glioblastoma usually occurs in adults and affects the brain more often than the spinal cord. Also called GBM, glioblastoma multiforme, and grade IV astrocytoma. Glioma (glee-OH-muh): A cancer of the brain that begins in glial cells (cells that surround and support nerve cells). Grade: The grade of a tumor depends on how abnormal the cancer cells look under a microscope and how quickly the tumor is likely to grow and spread. Grading systems are different for each type of cancer. Implant: A radioactive source in a small holder that is placed in the body in or near a cancer. Intensity-modulated radiation therapy: A type of 3-dimensional radiation therapy that uses computer-generated images to show the size and shape of the tumor. Thin beams of radiation of different intensities are aimed at the tumor from many angles. This type of radiation therapy reduces the damage to healthy tissue near the tumor. Internal radiation therapy: A type of radiation therapy in which radioactive material sealed in needles, seeds, wires, or catheters is place directly into or near a tumor. Also called brachytherapy, radiation brachytherapy, and implant radiation therapy. Intravenous (IV): Into or within a vein. Intravenous usually refers to a way of giving a drug or other substance through a needle or tube inserted into a vein. Malignant: Cancerous. Malignant tumors can invade and destroy nearby tissue and spread to other parts of the biopsy. Medical oncologist: A doctor who specializes in treating cancer with chemotherapy, hormonal therapy, and biological therapy. Medulloblastoma: A malignant brain tumor that begins in the lower part of the brain and that can spread to the spine or to other parts of the body. Medulloblastomas are a type of primitive neuroectodermal tumor (PNET). Meninges (meh0NIN-jees): The three thin layers of tissues that cover and protect the brain and spinal cord. Meningioma (meh-NIN-jee-OH-muh): A type of slow-growing tumor that forms in the meninges (thin layers of tissue that cover and protect the brain and spinal cord). Meningiomas usually occur in adults. Metastatic: Having to do with metastasis, which is the spread of cancer from one part of the body to another. MRI (magnetic resonance imaging): A procedure in which radio waves and a powerful magnet linked to a computer are used to create detailed pictures of areas inside the body. These pictures can show the difference between normal and diseased tissue. MRI makes better images of organs and soft tissue than other scanning techniques, such as CT scan or x-ray. MRI is especially useful for imaging the brain, the spine, the soft tissue of joints, and the inside of bones Nerve cell: A type of cell that receives and sends messaged from the body to the brain and back to the body. The messages are sent by a weak electrical current. Neuro-oncologist: A doctor who specialized in diagnosing and treating brain tumors and other tumors of the nervous system. Neurologic: Having to do with nerves or the nervous system. Neurologist: A doctor who specialized in the diagnosis and treatment of disorders of the nervous system. Neuroradiologist: A doctor trained in radiology who specialized in creating and interpreting pictures of the nervous system. The pictures are produced using forms of radiation, such as x-rays, sound waves, or other types of energy. Neurosurgery: A doctor who specialized in surgery on the brain, spine, and other parts of the nervous systems. Occupational therapist: A health professional trained to help people who are ill or disables learn to manage their daily activities. Oligodendrogioma: A rare, slow-growing tumor that begins in oligodendrocytes (cells that cover and protect nerve cells in the brain and spinal cord). Oncologist: A doctor who specializes in treating cancer. Palliative care, palliation: Treatment that relieves symptoms but does not cure disease. Palliative care can help people with cancer live more comfortably. Paralysis: Loss of ability to move all or part of the body. Pathologist: A doctor who identifies diseases by studying cells and tissues under a microscope. Physical therapist: A health professional who teaches exercises and physical activities that help condition muscles and restore strength and movement. Pituitary gland: The main endocrine gland. It produces hormones that control other glands and many body functions, especially growth. Primitive neuroectodermal tumor: One of a group of cancers that develop from the same type of early cells, and share certain biochemical and genetic features. Some primitive neuroectodermal tumors develop in the brain and central nervous system, and others develop in sites outside of the brain such as the limbs, pelvis, and chest wall. Proton: A small, positively charged particle of matter found in the atoms of all elements. Streams of protons generated by special equipment can be used for radiation treatment. Proton beam radiation therapy: A type of high-energy, external radiation therapy that uses streams of proton (small, positively charged particles) that come from a special machine. Proton beam radiation is different from x-ray radiation. Radiation oncologist: A doctor who specializes in treating cancer with radiation. Radiation therapy: Treatment with high-energy rays (such as x-rays) to kill cancer cells. The radiation may come from outside of the body (external radiation) or from radioactive materials placed directly in the tumor (internal or implant radiation). Types of radiation include x-rays, electron beams, gamma rays, neutron beams, and proton beams. Radioactive substances include cobalt, iridium, iodine and cesium. Risk factor: Something that may increase the chance of developing a disease. Some examples of risk factors for cancer include age, a family history of certain cancers, use of tobacco products, certain eating habits, obesity, lack of exercise, exposure to radiation or other cancer-causing agents, and certain genetic changes. Seizure: Convulsion; a sudden, involuntary movement of the muscles. Shunt: In medicine, a passage that is made to allow blood or other fluid to move from one part of the body to another. For example, a surgeon may implant a tube to drain cerebrospinal fluid from the brain to the abdomen. A surgeon may also change normal blood flow by making a passage that leads from one blood vessel to another. Side effect: A problem that occurs when treatment affects health tissues or organs. Some common side effects of cancer treatment are fatigue, pain, nausea, vomiting, decreased blood cell counts, hair loss, and mouth sores. Social worker: A professional trained to talk with people and their families about emotional or physical needs, and to find them support services. Speech therapist: A specialist who evaluates and treats people with communication and swallowing problems. Also called a speech pathologist. Spinal tap: A procedure in which a thin needle called a spinal needle is put into the lower part of the spinal column to collect cerebrospinal fluid or to give drugs. Also called lumbar puncture. Stereotactic biopsy: A biopsy procedure that uses a computer and a 3-dimensional scanning device to find a tumor site and guide the removal of tissue for examination under a microscope. Stereotactic radiation therapy: A type of external radiation therapy that uses a special equipment to position the patient and precisely deliver radiation to a tumor. The total dose of radiation is divided into several smaller doses given over several days. Stereotactic radiation therapy is used to treat brain tumors and other brain disorders. It is also being studied in the treatment of other types of cancer, such as lung cancer. Also called stereotactic external beam radiation therapy and stereotaxic radiation therapy. Stereotactic radiosurgery (SRS): A type of external radiation therapy that uses special equipment to position the patient and precisely give a single large dose of radiation to a tumor. It is used to treat brain tumors and other brain disorders that cannot be treated by regular surgery. It is also being studied in the treatment of other types of cancer. Also called radiation surgery, radiosurgery, and stereotaxic radiosurgery. Steroid drug: A type of drug used to relive swelling and inflammation. Some steroid drugs may also have antitumor effects. Surgeon: A doctor who removes or repairs a part of the body by operating on the patient. Surgery: A procedure to remove or repair a part of the body or to find out whether disease is present. An operation. Tissue: A group or layer of cells that work together to perform a specific function. Tumor: An abnormal mass of excess tissue that results from excessive cell division. Tumors perform no useful body function and may be either benign (not cancerous) or malignant (cancerous). Ventricle: A fluid-filled cavity in the heart or brain. X-rays: High-energy radiation that is used in low doses to diagnose disease and in high doses to treat cancer.


text:
Date Created: 4/3/2012
Date Modified: 7/18/2014
College Funding Options -- --
Custodial Accounts, Coverdell Education Savings Accounts and Section 529 Plans
For decades, parents have used custodial accounts to transfer funds to their minor-aged children to help build assets for college costs. However the 2001 tax law has enhanced the tax benefits of other types of asset ownership that should be considered. Coverdell Education Savings Accounts (Education IRAs) and Qualified Tuition Programs (Section 529 Plans) have become very attractive.
Custodial Accounts
Using a Uniform Gifts to Minors Act (UGMA) or Uniform Transfer to Minor Act (UTMA) account is an easy and legal way to transfer the ownership of assets to a child. With a UGMA or UTMA account, the parent creates a custodial account on behalf of the minor child. Assets are transferred into the account and the custodian, usually a parent, manages the account until the child reaches legal age. At that point, the child can do whatever he or she wishes with the assets.
Transfers to these accounts are irrevocable. You cannot change your mind later and take the assets back. Your child becomes the owner when you make the transfer an on reaching the age of majority (18 or 21 in most states) the child can do whatever they wish with the money.
Transfers into a custodial account are just like any other gift. For 2014, you can make annual gifts up to $14,000 in cash, securities or other property to anyone without owing any federal gift tax and without filing a gift tax return. If you are married, gifts can be considered to be half from you and half from your spouse. This enables transfers up to $28,000 to be made. However, a simple gift tax return may be required if you use this gift-splitting technique. The annual $14,000 exclusion applies to each person receiving the gift.
When the assets become the child's, any income the assets produce is taxed to the child. There are special tax rules that apply to children under the age of 18, 18 year olds with earned income less than half of their support, and 19 to 23 year old students with earned income less than half of their support. These rules are commonly called the "Kiddie" tax.
The tax laws provide that the first $1000 in 2014 of investment income from assets held in the child's name is tax free. The next $1000 is taxed at the child's tax rate (usually the lowest rate of 10%). Investment income greater than $2000 in 2013, is taxed at the parent's rate until the child is no longer subject to the Kiddie tax.
The Kiddie tax rules were changed in 2007 and you may want to consult a tax advisor to determine how the rules may apply in your situation.
Coverdell Education Savings Accounts (Education IRAs)
Education IRAs provide parents and others the opportunity to save for a child's education expenses in a tax advantaged account. The 2001 tax law increased the annual limit from $500 to $2000 for contributions to these accounts. There is also a new income limit for those making the contributions. Married couples filing a joint tax return can make a full $2000 contribution if their adjusted gross income is less than $190,000; they can make a partial contribution if their AGI is between $190,000 and $220,000; and no contribution if their income is above $220,000. For single taxpayers, the limit is one half of those amounts.
Earnings within the account are tax deferred and withdrawals are not subject to tax if they are used for qualified education expenses. The new law expanded this definition to include expenses for elementary and high school expenses. Withdrawals not used for qualified education expenses are subject to regular income tax and a 10% penalty. Withdrawals must also be completed before the child reaches age 30.
Education IRA accounts function like IRA accounts and are available from most banks, credit unions, brokerage firms and mutual fund companies. Investment options vary depending on the firm. Usually there is considerable flexibility with "self-directed" type accounts.
Qualified Tuition (Section 529) Plans
These college savings plans are now offered by over 40 states and were also enhanced by the 2001 tax law. While the plans are offered by the state, there is no restriction on where the child may attend college. It is expected that many universities will soon start offering these plans. One potential drawback is that there are usually limited investment options. It makes sense to look at several states' programs to find one that offers the investment choices you desire.
With a Section 529 Plan, there are no income limits on the donors and contributions of up to $14,000 per year can be made. The annual limit increased from $13,000 in 2013. In addition, there are special provisions to allow a "front-end loading" of up to five years of contributions to be made without gift taxes.
Custodial accounts offer the greatest flexibility in terms of how the money is ultimately used. However, they lack the tax benefits of the other programs.
Coverdell Education Savings Accounts offer the greatest flexibility in terms of how the money is used for education. However, there are limits on the income of the donors and the annual contribution limit is $2000 and reverts to $500 in 2013 unless Congress takes action.
Section 529 Plans offer the highest contribution limits without income limits on the donors. However, in many cases the investment options may be limited.
As with most financial decisions, you must consider what you are trying to accomplish. Be mindful of the tax implications and choose the one (or combination) that best fits your situation.
This information has been provided by Financial Wisdom Marketing Services, Inc. and is for educational purposes only. Content from Financial Wisdom and/or Redwood Credit Union is not, in any way, intended to provide legal, tax, or financial advice.


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First off, let me apologize for not writing anything for a long(ish) time. I have been busy with school and work and, well, have used my time to focus on other things (such as playing a certain game on Facebook) when I should have been editing photos and posting on here. So so sorry. Really. I love writing blog posts and everything, and sharing fun things with you. AND I am sorry I have not posted a recipe on here in an even longer time. So here's just a few to get things rolling.
As you may already know, I like doing things in more than one way. This time around, I used coffee in three different recipes. For starters, I tried making coffee ice cream, but that turned out to be less than desirable.
The next recipe I tried was this Hot Fudge Pudding Cake, from Delish. Instead of making one large cake, I made cupcakes, which were good, but a bit sticky. I called them muddy cupcakes because they were so moist and soaked through with coffee.
The third recipe I tried was a version of rice krispies that involved chocolate and coffee, among other things. It had been years since I made anything in the rice krispie treat realm.
Anyway, my treats do not look as dark/chocolatey as the pictures shown on Shutterbean, but are just as tasty. Also, I did not add dried cherries or extra 'mallows, as the recipe calls for. I figured it was chock-full of stuff as it was. Feel free to change up the mix-ins as desired.
Coffee Chocolate Marshmallow Krispies
from Shutterbean!
makes 12
recipe adapted slightly from Christina Tosi of Milk Bar via Rachael Ray Magazine
- 1 stick salted butter
- 2 bags (10 oz. each) mini marshmallows
- 5 cups crispied rice cereal
- 2 cups salted roasted almonds, coarsely chopped
- 1 1/2 cups dried cherries, chopped
- 2 teaspoons ground coffee (not instant)
- 1/4 teaspoon coarse salt
- 1 cup semi-sweet chocolate chips
- cooking spray
Line a 9 inch square baking dish with foil and spray lightly with cooking spray. In a 10-12 quart pot, melt the butter over medium low heat. Add 10 cups mini marshmallows and cook, stirring occasionally, until melted and smooth, about 5 minutes; remove the pot from the heat.
Using a wet spoon or spatula, fold in the rice cereal. Sprinkle in the almonds, cherries, ground coffee & salt; fold quickly to distribute. Sprinkle in the chocolate chips and remaining mini marshmallows; fold gently to distribute.
Spoon mixture into the prepared baking dish. Using slightly damp hands or a wet spatula, press into an even layer. Let cool completely and cut into square to serve.


text: Hello everyone, just received my " DEAD TED " Final Chapter Replica. #5 This is my first piece from Bob, or Scarewear. I'm very happy with it. I'm very impressed with the sculpt. I may be adding a Tech-Optics glass eye. The bust is made of nice thick translucent resin, with an extra layer of hard foam. Enjoy..


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* Foreign minister decries outside "interference" in Syria
* He mentions Qatar, Saudi Arabia, Turkey, US, France, Libya
* U.N. chief strongly criticizes Syria's government
(Adds details throughout)
By Michelle Nichols and Louis Charbonneau
UNITED NATIONS, Oct 1 (Reuters) - Syria's foreign minister on Monday accused the United States, France, Qatar, Saudi Arabia and Turkey of supporting "terrorism" by funneling arms, money and foreign fighters to rebels seeking to topple President Bashar al-Assad while the U.N. chief decried killings and rights abuses by Assad's government.
Speaking on the last day of the annual 193-nation U.N. General Assembly, Foreign Minister Walid al-Moualem also accused Libya of backing the rebels and said an arm of the al Qaeda network had taken responsibility for some bomb attacks in Syria.
Moualem said outside calls for Assad to step down amid the 18-month-old conflict were a "blatant interference in the domestic affairs of Syria, and the unity of its people and its sovereignty."
His speech came three days after countries calling for Assad's ouster met on the sidelines of the General Assembly but announced steps far short of what the rebels wanted as they press ahead in the bloody civil war.
U.N. Secretary-General Ban Ki-moon met with Moualem earlier on Monday and "raised in the strongest terms the continued killings, massive destruction, human rights abuses, and aerial and artillery attacks committed by the government," Ban's spokesman said in a statement.
"He stressed that it was the Syrian people who were being killed every day, and appealed to the Government of Syria to show compassion to its own people," the spokesman said.
Ban raised the growing humanitarian crisis inside Syria, which was also spilling over to neighboring countries, the spokesman added. The United Nations said about 294,000 refugees from Syria had fled into Jordan, Iraq, Lebanon and Turkey.
More than 30,000 people have been killed, according to opposition activists, and there are fears the civil war could destabilize the wider Middle East.
Moualem said that Qatar, Saudi Arabia, Turkey, the United States and France "clearly induce and support terrorism in Syria with money, weapons and foreign fighters."
Qatar, Saudi Arabia and Turkey have denied aiding the rebels. The United States and France have said they are providing "non-lethal" support and not weapons.
"Under the pretext of humanitarian intervention, these countries interfere in the domestic affairs of states, and impose unilateral economic sanctions that lack the moral and legal basis," Moualem said.
"And under the pretext of concepts such as the 'Responsibility to Protect,' drums of war are beaten, and sedition and unrest are spreading and damaging the structure of national societies," he said.
Moualem was referring to a concept about governments' responsibility to protect civilians that has become increasingly popular in Western diplomatic and academic circles. The concept was used to justify last year's military intervention in Libya that led to the ouster and death of leader Muammar Gaddafi.
"Worst of all is to see permanent members of the Security Council, who launched wars under the pretext of combating terrorism, now support terrorism in my country," Moualem said.
At a meeting of countries supporting Assad's ouster held on Friday, the United States and France announced increased support for the Syrian opposition. But the meeting produced no sign that the direct military aid sought by the rebels to create safe havens for civilians was on the way.
Russia, backed by China, repeatedly has vetoed Western- and Arab-backed council resolutions that criticized the Syrian government and threatened it with sanctions, saying the United States, Europe and Gulf Arabs are seeking regime change.
Moualem said the Syrian government welcomed the appointment of international mediator Lakhdar Brahimi and had itself long called for talks to end the conflict, but said the opposition was not interested.
"The success of any international effort requires, in addition to the commitment of the Syrian government, committing the states supporting armed groups in my country, particularly Turkey, Saudi Arabia, Qatar, Libya and others, to stop arming, funding, training and harboring armed terrorist groups, and instead to encourage dialogue and renounce violence," he said.
Moualem told the U.N. General Assembly that some people had tried to "fabricate a refugee crisis through inciting armed groups to intimidate Syrian civilians in border areas and forcing them to flee into neighboring countries."
"I appeal from this podium to those Syrian citizens to return to their towns and villages where the state will guarantee their safe return and their precious lives away from inhuman conditions they suffer in these camps," he said.
Moualem also used his speech to criticize Israel for not joining the nuclear Non-Proliferation Treaty and not allowing the U.N. International Atomic Energy Agency to inspect its facilities.
Syria has not allowed U.N. inspectors to visit a site in its desert Deir al-Zor region that U.S. intelligence reports say was a nascent, North Korean-designed reactor designed to produce plutonium for nuclear weapons before Israel bombed it in 2007.
(Editing by Will Dunham)
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)) Keywords: UN ASSEMBLY/SYRIA