Popcorn science: One, big, federal household

A car that educates us on the expenditures of the U.S. Federal Government. What if households had to provide like a nation?

It’s time for another popcorn science. An oft-repeated claim, backed by few thoughts or facts, is that the U.S. Federal Government should take a cue from Main Street and run its budget like a household runs its budget. Households, so the claim goes, work within their constraints and don’t carry huge debt-to-income ratios. Why can’t the U.S. government be more like a household?

Let’s look at U.S. households first.

According to the U.S. Census Bureau, American households have a median income of about $49,777 and a mean (average) income of about $67,976 [1] (these numbers are pre-tax). According to statistics available on CreditCards.com, a self-described marketplace for obtaining a credit card, the average total debt carried by a household (including credit cards, mortgage, home equity, student loans, and other sources) $16,046 [2].  That means that, on average, the percent of income represented by household debt is 23.6%.

Let’s now look at the Federal Government, the representative of the People. In 2011, the total revenue of the U.S. Federal Government was $2,173.7 trillion (in 2009, where the above household statistics come from, the number was $2,105.0 trillion).  The estimated debt for 2011 is $15,476 trillion (in 2009, the actual number was $11,875 trillion) [3]. Relative to per annum Federal income, this represents a debt/income ratio of 7.12, or 712%.

So if we treat the Federal Government like a typical American household, then it would certainly seem that this is a family living far outside of its means. The problem with this is that the analogy may not be apropos; can we really treat a national government with the same principles that we treat a single household? Are we even comparing the right numbers?

Since we’re talking about national numbers here regarding deficit, we might argue that the United States is worth more than simply the intake from Federal revenues. The Gross Domestic Product is a measure of the national income due to productivity, which is really a more accurate assessment of our national income. The GDP in 2011 is estimated to be $15,079 trillion (actual in 2009 was $14,258 trillion). If we compute the national debt/GDP ratio, we obtain 1.10, or 110%.

But again, is the statement that “the Federal Government should operate under the same constraints as a typical American household” a correct assumption? Is what is good for the house good for the nation?

A few weakpoints in this statement immediately become obvious. They lie in the differences between a typical American household and a Federal Government.

  1. The Federal Government must provide for the common defense. This includes raising an army, provisioning it, and paying it. A household does not have to shoulder its fractional burden of defense, except through taxes.
  2. The Federal Government must provide monies for public education, which are distributed to states and then to local schools. While household income is often taxed to pay for public education, the household does not need to directly provide the funds for books, teachers, buildings, etc. Part of that comes from the Federal Government. Households are not directly responsible for the education of their children, unless they home-school.
  3. The Federal Government provides support for those who cannot work and those who are retired through social financial programs like Medicare and Medicaid. Households rarely have to shoulder the entire burden of caring for an out-of-work or retired individual.
  4. The Federal Government provides support for risky ventures with a high-risk, high-payoff profile. Think scientific or educational research. Households rarely invest significant amounts of money in ventures which are not likely to succeed immediately, but may have long-term unintended benefits.

These are the things that immediately leap to mind as different between a typical household and a Federal Government.

What if we instead frame the issue as follows: what if the typical American household was structured more like the U.S.? How then might the typical American household look in terms of its debt/income ratio?

For this thought experiment, let us define the following parameters:

  1. The proportion of working individuals bringing in an average, single-person income from an external source will be as it presently exists in the United States – about 62%, according to Ref. [4]. These individuals represent the income to the household, taking the place of revenue sources for the Federal Government.
  2. The proportion of underage, non-working individuals (<18) will be as it is in the U.S. – about 26%. These are dependents, who also need to be educated.
  3. The proportion of retired, non-working individuals will be as it is in the U.S. – about 12%. These will be also be dependents, relying primarily in the income earners for support.
  4. The household will need to provide for defense, something usually provided by the local municipality. This will mean employing a security force (e.g. guards). The current proportion of the U.S. population which is participating in the military is about 10%.
  5. The household will need to provides its children with education. This means hiring a tutor. We can assume one tutor is needed for all the children in the household.
  6. We will assume that the security guard and the tutor make the current average amount of money for a military combat individual and a public school teacher: $16,000 [5] and $51,000 [6] (these are median salaries).
  7. We will assume that each person requires the average amount of food [7] and healthcare needed for their age bracket. Wage earners are between 18-65 years of age, children under 18, retirees over 65, security personnel are between 18-40, and teachers are anywhere between 18-65.
    1. Food cost, per year: (<18) we’ll assume the kids are about 9-11 years of age, so that’s about $150/month on the “Thrifty Plan”; for (18-65) the cost is about $160/month; for >65, the cost is about $150/month.
    2. Health costs: health care costs are often hidden from us by insurance plans, so we’ll have to make do with the best public numbers on typical household healthcare costs including some basic insurance plan. This averages out across every man, woman, and child in the U.S. to be $6,280 per person, per year; this represents the raw cost per person. However, people typically pay insurance premiums to a company that then provides benefits to them. If you don’t use the benefits, the average total cost of premiums is less than the average total cost estimated for raw healthcare each year. People under 18 cost on average $1350 per year in premiums; the average premium for people between 18-65 is about $3500. For people over 65, they receive Medicare or Medicaid but in our example we are assuming the family provides the cost of healthcare, and thus pays the premium, for the elderly. Thus we’ll underestimate the cost of >65 people at $5800, the premium cost per year for people aged 64.

Now we have our numbers. We need to build our family. Taking the proportions into account above, we want to achieve a number of people in a household that rounds the lowest number in any category to at least 1 person.  You get about the right proportions if you construct the following minimum family:

  1. <18: 2 persons
  2. 18-65: 2 wage earners, 1 security person, 1 teacher/tutor
  3. >65: 1 person

This represents a 2 parent family with 2 children and 1 elderly parent to take care of, with their own personal security and a teacher for the child. This family represents the population distribution, and major outlay expenditures (security, health costs, education) of the U.S. Federal Government.

What will the income be, and what will the costs be? Let’s add it up!

  1. Income: Most two-earner family situations involve a male and female couple, so let’s assume that our household’s total income is the sum of the average male and female incomes. More females than males obtain Bachelor’s Degrees, so let’s assume that the female has a degree and thus earns $31k per year (median income). The male has some college and makes $35k per year. That totals $35k + $31k, or $66k. We’ll take the pre-tax number, since our taxes primarily are spent on social security and defense, which are the very things our model family will provide for themselves. [9]

Here are the outlays:

  1. Healthcare: Adding up the per-person cost for the kids, parents, and elder (premiums only), we get $15.5k
  2. Food: $9.2k per year
  3. Home: the per year cost of a 30-year home mortgage for a median U.S. home ($212k for the home and the land is the median price in 2011 [10])  is $7.1k
  4. The average yearly cost utilities, including gas, electric, phone, and some entertainment, is about $3000 [11]
  5. The family (2 kids, 2 parents, 1 elder) will have their own vehicles. Typical families in the U.S. own two vehicles. The average distance driven per year is 15,000 miles per vehicle. We’ll assume that there are 3 small sedans and 1 minivan in this household. That yields a cost per year for the sedans of $6300, including gas, maintenance, and other normal costs; for the minivan, it is $8900 per year [12]. That’s a total cost for transportation of $15,200 per year.
  6. Cost of salaries for teacher and security guard: we’ll set these at the current medians for military and teachers, or $16k and  $51k. The security person is obviously underpaid; real military get benefits, like healthcare and food and housing. If we add the yearly costs of those into their salary to make it more reasonable, then we obtain a total security cost of $31.6k. The total cost of the teacher and the security person is $82.6k per year. We’ll assume the teacher uses their salary to buy books, supplies for teaching, food, an apartment, utilities, etc.

So what is the total outlay of this household per year? It’s $133.7k. That’s a cost-to-income ratio of 2.0, and a debt-to-income ratio of 1.0 (debt is outlays minus income). These costs don’t include other things, like supplies for the household (soap, towels, clothes, etc.) so clearly my little experiment is an underestimate of the cost to the family of providing for themselves like a normal household, plus paying directly for security and education.

Let’s compare that to the present Federal debt ratio (debt to GDP), 1.1. We have a household debt ratio of 1.0, about the same as that of our Federal Government. It seems that if a typical household were to assume things typically handled by the Federal Government, the debt-to-income picture would be VERY different.

Caveats and Conclusions

It would be easy to tinker with the model and change the ratio. A LOT of assumptions went into this. For instance, if both wage earners have Bachelor’s degrees, their combined salary increases by nearly 50% and their debt-to-income ratio drops to 0.6 from 1.0. You could argue that there is no way such a family would agree to pay $51k for a tutor. Fine. What is the average salary of a private tutor in the U.S.? A whopping $57k [13]. That $51k for a public-school teacher is looking like a bargain now. You could then argue they would just take in the tutor, pay their housing and food costs, etc. and try to drop the overall cost. That might work. Same for the security guard.

But the point here is that when you try to make a household look more like a nation, rather than the other way around (which is ridiculous) you begin to realize that there is a hidden cost to things we take for granted. We take for granted the cost of the public education of our children. We take for granted that the nation cares for its elderly, so that we assume less of a burden on the nuclear family. We take for granted the security that our taxes pay for. These are significant costs on a per household basis, and they are no less significant on a per nation basis.

I also neglected something very important in the household model: GROWTH. Economic growth is the single most important thing in the long-term survivability of a nation. If a nation is to grow, it must invest. Investment has risk, and even if it pays off it may not be for decades. Nations can make those kinds of decisions, but households rarely can. They tend to lean toward job security, stability, and short-term needs (food, utilities, etc.). They don’t think about what it would take to raise their annual income at 5% or 7% per year. What kinds of job risks would the wage earners need to take to secure that kinds of wage growth? Significant risks. The kinds of risks that people take out business loans for.

Taking into account growth means accepting more debt to gamble on risky investments that may pay off. That’s nowhere in my model. A nation can afford to take risks, because it has money invested in such diverse buckets in its budget, but a household cannot do that very often. Households, like nations, run up debt to achieve stability. They obtain a mortgage to buy a house they cannot actually afford now, under the promise of stable/increasing income over 30 years so that they CAN afford it later. They take our college loans to invest in their kids’ education, a cost they cannot afford now but which the kids can assume once they earn a degrees and thus a ticket to increasing wages.  These are typical household risks, which zero out or pay off in some cases over very long periods of time (30-50 years).

So is it fair to compare a household and a nation? Not really. Nations and households have different priorities. They both take risks, but nations can afford to do that on larger scales and more frequently than can a household. If households assumed the cost of defense and education, in addition to healthcare, it would break their meager budgets. The same is true for a nation. But does that mean that governments should not provide these things?

What made the U.S. great was, in part, its public education and its national defense. If households had to provide these, with private tutors and their own militia, they too would assume a great deal of debt. There is no doubt that a debt-to-income ration of 1.0 or 1.1 can’t be sustained forever, but nobody says it has to be. The reality is that all entities assume some amount of risk from time to time to achieve larger goals. In a household, it’s a mortage or college loans or a business loan; in government, it’s defense spending, social programs to help those who cannot help themselves, education for all, and research and development. Achieving long-term stability is necessary, but we cannot confuse the short-term needs of a home with those of a nation.


[1] “FINC-01. Selected Characteristics of Families by Total Money Income in 2009,” http://www.census.gov/hhes/www/cpstables/032010/faminc/new01_001.htm

[2] Credit Card Industry Total Household Debt Statistics from 2009, http://www.creditcards.com/credit-card-news/credit-card-industry-facts-personal-debt-statistics-1276.php (at the recommendation of the site owner, who noted this article linked to their data, I provide an updated link to this data: http://www.creditcards.com/credit-card-news/credit-card-debt-statistics-1276.php)

[3] Budget Analysis, http://www.usgovernmentrevenue.com/#usgs302a

[4] http://2010.census.gov/2010census/data/

[5] http://www1.salary.com/E1-Recruit-Basic-Training-Army-Salary.html

[6] http://www1.salary.com/Public-School-Teacher-Salary.html

[7] http://www.cnpp.usda.gov/Publications/FoodPlans/2009/CostofFoodJan09.pdf

[8] http://www.ahrq.gov/research/ria19/expendria.htm and http://www.ahipresearch.org/pdfs/2009IndividualMarketSurveyFinalReport.pdf

[9] http://en.wikipedia.org/wiki/American_middle_class and http://en.wikipedia.org/wiki/Educational_attainment_in_the_United_States

[10] www.census.gov/const/uspricemon.pdf

[11] http://www.whitefenceindex.com/

[12] http://www.vtpi.org/tdm/tdm66.htm#_Toc18284946

[13] http://www.indeed.com/salary/Tutor.html

Photo from http://www.flickr.com/photos/moyix/174053226/sizes/z/in/photostream/

Popcorn Science: Lazy CO2?

I hear a lot of interesting things when I play the “fly-on-the-wall scientist.” Most statements uttered casually between friends can be tested scientifically; at the very least, research has already been done and one only needs to dig a little to find out whether the statement is true. There are many things in life that can be demonstrated true and false. Grab a bowl; let’s pop a serving of buttery science!

Carbon dioxide (CO2) levels lag behind changes in global temperature. Therefore, CO2 is not a greenhouse gas and/or other causes are at work in global climate change and therefore the current changes are not human-induced (“anthropogenic”).

After concluding a review and Q&A session for my introductory physics course, I had to remain late at SMU until Jodi returned from a formal dinner event. I was killing time (trying not to think about the norovirus that was playing havoc with my intestines that same day) when a conversation between two colleagues at the other end of the room caught my attention. One of my colleagues was arguing, apparently as he usually does, that anthropogenic climate  change has little or no scientific basis. To support his claim, he repeated a statement I have heard before from anthropogenic climate-change deniers (ACCDs): CO2 levels are a lagging, not a leading indicator (that is, the rise in CO2 levels TRAILS the change in temperature), and therefore CO2 is either not a greenhouse gas or global climate change is induced by factors other than CO2, so humans cannot be responsible.

I decided that this was a real opportunity to me to investigate the background of this statement. So here we go!

A look at the chart

Here is a great example of a plot that gets referred to by many ACCDs (reproduced from [1]).

CO2 levels, Isotopic atmospheric temperatures, CH4 levels, change in O18 levels, and mid-June insolation.

Above, we see a lot of data being shown at once. Concentrate on a, b, and c. Curves a and b are the levels of CO2 and CH4 (methane), both greenhouse gases (that is, these are gases that can trap heat). We see the levels rising and falling over long periods of time, but if we compare to curve b, the isotopic atmospheric temperature, we see that changes in temperature for warming lead the changes in CO2 and CH4. For a slightly marked up version of this plot which helps see where warming trends fall and how insolation changes match to those, see the appendix below.

Why can warming ever lead greenhouse gases?

Before we proceed, it’s definitely worth understanding how the researchers came to these results. They obtained and studied ice cores from Antarctica. Ice traps bubbles of atmospheric gas, effectively encasing a snap-shot of atmospheric conditions over vast periods of time. Studying the trapped gases taught the researchers about atmospheric CO2 and CH4 levels. How do they determine temperature changes? They compare the level of Deuterium present at each level of the ice core. Heavy water isotopes are always present in water; however, water vapor will tend to contain lower levels of heavy isotopes and high levels of light ones; precipitation will contain more of the heavy isotopes and lower levels of the light ones. Changes in deuterium levels therefore are a proxy for temperature, and changes relative to modern temperatures (and the Deuterium levels at present) can be used to chart temperature back in time.

Finally, what is “insolation” shown in curve e in the above plot? According to Wikipedia [2]:

Insolation is a measure of solar radiation energy received on a given surface area in a given time. It is commonly expressed as average irradiance in watts per square meter (W/m2) or kilowatt-hours per square meter per day (kW·h/(m2·day)) (or hours/day).

As the Earth’s relationship to the sun changes due to the eccentricity of the orbit, the tilt of the rotation axis, and the precession of the earth’s orbit, so does the amount of radiation received per unit area. There is a fairly clear understanding of how this change influences Earth’s climate in regular cycles, called “Milankovitch cycles.” [3] The above graph shows that insolation, specifically increases in Joules striking the Earth, can initiate warming trends.

Increases in solar radiation can initiate warming trends by causing ice-age glaciers to recede. Melting/receding glaciers reduce Earth albedo – the property of reflectivity that, rather than trapping solar radiation simply reflects it back into space. Reduced albedo means more heating. As the heating starts to increase, CO2 and CH4 are released from storage on or in the earth (in sea water, for instance, where under cooler temperatures the gases remain trapped in the water). We see then how CO2 and CH4 levels can begin to rise after warming has begun. This then creates a feedback loop; higher levels of heat-trapping gases trap more heat, and heating begins to accelerate, causing more glacier to melt. This defines the sharp warming we see in the graph above. Subsequent re-cooling of the earth can take tens of thousands of years, after only a couple of thousand years of this warming. Then the whole thing repeats again. This, according to Antarctic ice samples, has been repeating every 100,000 years or so for the last 400,000 years.

It is important to note that the lead that temperature has on CO2 levels, historically, is a small one. Current estimates range between 200-1000 years of leading. However, the warming trend lasts thousands of years – so it does not end when CO2 and CH4 enter the atmosphere in increased amounts, it continues strongly thereafter.

What’s happening now?

So we see how insolation (the change in earth’s reception of energy from the sun) can lead to warming (decreasing glaciation), which then releases greenhouse gases after the warming is initiated and begins a few thousand year runaway period of warming.

Is that what is happening in the current period? Are ACCDs right?

The answer, quite simply, is no. Here is why.

First, look at the above graph. Our current era is at the left of the graph. We see that solar insolation is at a minimum right now – that is, we are in a period where energy from the sun is at a low-point. Previously, warming trends were always initiated on the increasing side of insolation, not on the down-side or at a minimum. So already we see a distinction between the last 400,000 years and the current warming trend.

Second, atmospheric CO2 levels have not lagged the current warming – they have led it. This is very clear in all of the data that has been analyzed looking at CO2 levels and global temperature over the past 200 years, since anthropogenic expulsion of CO2 into the atmosphere began to ramp during the American and European industrial revolutions. The story is told in the CO2 data shown in the insets of the figure below.

IPCC Report 4, Working Group 1, Figure 3.6: Greenhouse Gas Concentrations
IPCC Report 4, Working Group 1, Figure 3.6: Greenhouse Gas Concentrations

The above figure is taken from Ref. [4]. We see that rapid increases in atmospheric CO2 levels (the top plot) began in the 1800s and have continued unabated since. The real up-tick in levels began in 1900, when the slope of the change increased. The next increase in slope was then in about 1955-1960. Let’s then compare that to when temperature changes began over the same period. The figure below, also from [4], shows these relative to the average temperature between 1850-2006:

IPCC Report 5, Working Group 1, Supplemental Material 1: Temperature Changes
IPCC Report 5, Working Group 1, Supplemental Material 1: Temperature Changes relative to 1850-2006 average

Whether we look at global average temperature or just the average in the Northern or Southern Hemispheres, we see the same trend. Temperature seemed to be going in regular cycles around a flat average from the start of the graph (1850) until about 1920. Then in 1920, the average around which regular cycles occurred obtained a new slope – no longer zero (flat), but positive (increasing). From about 1920 to 1980, a period of 60 years,  the global average temperature increased by  0.2 degrees Celcius. From 1980-2006, a period of 26 years, global average temperature increased by an additional 0.2 degrees Celcius. The time to double the temperature change cut in half between 1920-1980 and 1980-2006. That’s stunning.

But CO2 levels began increasing long before these temperature changes took off. So in the current era of warming, CO2 is driving the change and not the other way around. CO2 now leads temperature.

Is that CO2 really from human activity?

A final statement that ACCDs might make about all of this is the following: so what . . . there’s no proof that this CO2 comes from human activity, so maybe this is just a natural cycle where CO2 happens to lead temperature for a change.

Actually, there is a clear physics answer to this question: isotope ratios. I have commented on this before [5] based on studies like those in reference [6]. CO2 that remains in the atmosphere for a very long time, or which is present in biological material on the surface of the earth, is constantly exposed to cosmic ray radiation. This radiation can generate the isotope of stable carbon-12, unstable carbon-14, in a ratio that is actually easily measurable to high precision. In other words, CO2 that derives from close to the surface of the earth has a larger C-14 content ratio than carbon that is more shielded from cosmic ray radiation.

Carbon that has been underground for a long time, in the form of fossil fuels, is just such a kind of carbon that will have a lower C-14 level. By studying the level of C-14 in the air trapped in tree rings and other sources, we can watch to see if over time the atmosphere loses C-14 as more C-12-rich fossil-fuel carbon is pumped into the air. Sure enough, this is exactly what is seen. C-14 is a fingerprint, and we observe that since the 1800s the level of C-14 has decreased dramatically in the atmosphere. This tells us that less radiogenic carbon is entering the atmosphere – just the kind of carbon obtained from deep sequestered fossil fuel. The only species burning lots of deep-sequestered carbon is humans, and thus the modern CO2 levels are anthropogenic in origin.


So, does CO2 lag temperature? Yes, it can, and historically it has. The ice core record is clear on that. However, in the modern warming cycle CO2 and other gases have led the warming trend. In addition, that CO2 is rich in C-12 but depleted in C-14 because it comes from reserves deep in the earth. Anthropogenic warming is the status quo, and acting otherwise is wishing your doctor hadn’t diagnosed you with cancer and shopping around for a doctor that will say otherwise.


4/17/2011: Based on a reader comment, I produced an annotated version of the Vostok Ice Core data plot. The blue lines help you to see how significant warming trends match to locations on the insolation curve. I made the plot “blind”: I zoomed way in on the temperature curve, marked the start of significant warming trends with blue lines, and when I drew all lines I zoomed out and extended the lines to the axes. That way I wouldn’t only choose warming trends that definitely correlated with high radiation from the sun. The blue lines show that this appears to be the case,  but any bias I possess should not be a factor in that relationship.


[1] J. R. Petit, J. Jouzel, D. Raynaud, N. I. Barkov, J.-M. Barnola, I. Basile, M. Bender, J. Chappellaz, M. Davis, G. Delaygue, M. Delmotte, V. M. Kotlyakov, M. Legrand, V, Y Lipenkov, C. Lorius, L. Pepin, C. Ritz, E, Saltzman, and M. Stievenard, “Climate and history of the past 420,000 years from the Vostok ice core, Antarctica,” Nature 399 (1999) 429-436

[2] http://en.wikipedia.org/wiki/Insolation

[3] http://en.wikipedia.org/wiki/Milankovitch_cycles

[4] “Contribution of Working Group I to the Fourth Assessment Report of the Intergovernmental Panel on Climate  Change, 2007,” Solomon, S., D. Qin, M. Manning, Z. Chen, M. Marquis, K.B. Averyt, M. Tignor and H.L. Miller (eds.) http://www.ipcc.ch/publications_and_data/ar4/wg1/en/contents.html

[5] “Seen and Unseen” http://steve.cooleysekula.net/blog/2010/05/25/seen-and-unseen/

[6] http://adsabs.harvard.edu/abs/1981E&PSL..53..349S [“Atmospheric C changes resulting from fossil fuel CO2 release and cosmic ray flux variability.” Stuiver, M. and Quay, P. D. Earth and Planetary Science Letters, vol. 53, no. 3, May 1981, p. 349-362. ]

Atmospheric14C changes resulting from fossil fuel CO2 release and cosmic ray flux variability

Popcorn Science: Teething and fevers

I hear a lot of interesting things when I play the “fly-on-the-wall scientist.” Most statements uttered casually between friends can be tested scientifically; at the very least, research has already been done and one only needs to dig a little to find out whether the statement is true. There are many things in life that can be demonstrated true and false. Grab a bowl; let’s pop a serving of buttery science!

You can tell a baby is teething because they are running a fever; or, conversely, because a baby is running a fever it may imply they are teething.

Teething infant (photo by Bryan Anthony, 2007)

With two siblings-in-law who have both had two kids each in the past 3 years, I hear this one a lot. I hear it from parents, grandparents, and a variety of great aunts and uncles. But does the cutting of gums by teeth cause a fever? I was really curious, and did some digging around.

First of all, what are the typical things that induce fever? According to the Wikipedia article “Fever”,

Fever (also known as pyrexia or controlled hyperthermia) is a common medical sign characterized by an elevation of temperature above the normal range of 36.5–37.5 °C (98–100 °F) due to an increase in the body temperature regulatory set-point. This increase in set-point triggers increased muscle tone and shivering.

As a person’s temperature increases, there is, in general, a feeling of cold despite an increasing body temperature. Once the new temperature is reached, there is a feeling of warmth. A fever is one of the body’s immune responses that attempts to neutralize a bacterial or viral infection. A fever can be caused by many different conditions ranging from benign to potentially serious. With the exception of very high temperatures, treatment to reduce fever is often not necessary; however, antipyretic medications can be effective at lowering the temperature, which may improve the affected person’s comfort.

So fever is typically considered to be a medical condition associated with the body’s immune response to a foreign agent in the body. On the surface, it might seem unlikely that teething and fever can be correlated (unless teething leads to an opportunistic infection). The pervasion of this lore in parenting suggests there must be a correlation between fever and teething.

So what does research literature state? A recent study by Australian researchers from the year 2000 published in the journal Pediatrics [1] reported no discernable correlation between elevated infant body temperature and periods preceding tooth eruption (the first day the tooth penetrates through the gum). The only symptom that was elevated was loose stool, and this was reported by parental monitors but not staff monitors of children at daycare centers.

Another independent study in 1999, published in the same journal but performed by researchers from the Cleveland Clinic, also surveyed the frequency of symptoms in teething children. This study similarly windowed around the date of a tooth eruption and looked at a range of symptoms. Their findings are nicely summarized:

Daily symptom data were available for 19 422 child-days and 475 tooth eruptions. Symptoms were only significantly more frequent in the 4 days before a tooth emergence, the day of the emergence, and 3 days after it, so this 8-day window was defined as the teething period. Increased biting, drooling, gum-rubbing, sucking, irritability, wakefulness, ear-rubbing, facial rash, decreased appetite for solid foods, and mild temperature elevation were all statistically associated with teething. Congestion, sleep disturbance, stool looseness, increased stool number, decreased appetite for liquids, cough, rashes other than facial rashes, fever over 102°F, and vomiting were not significantly associated with tooth emergence. Although many symptoms were associated with teething, no symptom occurred in >35% of teething infants, and no symptom occurred >20% more often in teething than in nonteething infants. No teething child had a fever of 104°F and none had a life-threatening illness.

So while biting, drooling, and other oral symptoms were correlated, those like fever or other immune-response related symptoms were not significantly associated with teething.

So the science seems clear: teething and fever are not correlated. If your child has a fever, it is because their immune system is fighting a virus or bacteria, but not because of teething. So it makes more sense to monitor the fever and consult a physician to make sure it’s not a serious problem.

[1] “Teething and Tooth Eruption in Infants: A Cohort Study” http://pediatrics.aappublications.org/cgi/content/abstract/106/6/1374

[2] “Symptoms Associated With Infant Teething: A Prospective Study” http://pediatrics.aappublications.org/cgi/content/abstract/105/4/747

Daily symptom data were available for 19 422 child-days and 475 tooth eruptions. Symptoms were only significantly more frequent in the 4 days before a tooth emergence, the day of the emergence, and 3 days after it, so this 8-day window was defined as the teething period. Increased biting, drooling, gum-rubbing, sucking, irritability, wakefulness, ear-rubbing, facial rash, decreased appetite for solid foods, and mild temperature elevation were all statistically associated with teething. Congestion, sleep disturbance, stool looseness, increased stool number, decreased appetite for liquids, cough, rashes other than facial rashes, fever over 102°F, and vomiting were not significantly associated with tooth emergence. Although many symptoms were associated with teething, no symptom occurred in >35% of teething infants, and no symptom occurred >20% more often in teething than in nonteething infants. No teething child had a fever of 104°F and none had a life-threatening illness.

Popcorn Science: Hunger and Artificial Sweetener

I hear a lot of interesting things when I play the “fly-on-the-wall scientist.” Most statements uttered casually between friends can be tested scientifically; at the very least, research has already been done and one only needs to dig a little to find out whether the statement is true. There are many things in life that can be demonstrated true and false. Grab a bowl; let’s pop a serving of buttery science!

Consuming artificially sweetened beverages causes you to gain weight because artificial sweeteners increase your hunger.

Photo by Becky Stern, 2009. This and other photos by Becky are available from http://www.flickr.com/photos/bekathwia/3286606272/

I heard this statement uttered recently at a party where people were downing lots of chips, cake, soda, fatty meats, and other assorted party foods. A casual conversation about weight and losing weight arose nearby  in the living room. The above statement was uttered fairly casually, as if fact. But is it true? Do people who consume artificially sweetened foods gain weight over people who don’t? If so, is this because such sweeteners increase your hunger (appetite), and thus make you consume more food?

First of all, a statement about science. Science is the process of understanding the natural world by forming a hypothesis, designing an experiment to gather data to test the hypothesis, and understanding the data to see if the hypothesis is correct. Science can be messy; things don’t usually happen in an orderly way. But we need guiding principles, and these are a few.

We also need some guiding principles. What will constitute a “good study” of this question? Here are a few things:

  • test subjects must have nearly identical characteristics – weight, eating and exercise habits, etc.
  • test subjects should be divides into “control” and “test” groups; the control group gets sugar, the “test” group gets artificial sweetener. Ideally, the study should be double-blind: the researchers shouldn’t know who is getting sugar and sweetener, and subjects should also not know this.
  • the food industry does pump a lot of money into such studies; while scientists always have external funding, we should at least consider the possible effects of different funding sources.

I took a look on scholar.google.com for some studies matching the search terms “artificial sweetener and hunger.” I found a review article by Qing Yang, from the Department of Molecular, Cellular and Developmental Biology at Yale University. It referenced a large number of articles that contain the actual research. Based on a readinf of several of the referenced articles, this review is a pretty coherent summary of the current state of understanding of the effects that artificial sweeteners have on human weight changes. Here are some relevant excerpts from the review article:

Surprisingly, epidemiologic data suggest [artificial sweeteners do not help you lose weight]. Several large scale prospective cohort studies found positive correlation between artificial sweetener use and weight gain [3]. The San Antonio Heart Study examined 3,682 adults over a seven- to eight-year period in the 1980s. When matched for initial body mass index (BMI), gender, ethnicity, and diet, drinkers of artificially sweetened beverages consistently had higher BMIs at the follow-up, with dose dependence on the amount of consumption. Average BMI gain was +1.01 kg/m2 for control and 1.78 kg/m2 for people in the third quartile for artificially sweetened beverage consumption. The American Cancer Society study conducted in early 1980s included 78,694 women who were highly homogenous with regard to age, ethnicity, socioeconomic status, and lack of preexisting conditions. At one-year follow-up, 2.7 percent to 7.1 percent more regular artificial sweetener users gained weight compared to non-users matched by initial weight. The difference in the amount gained between the two groups was less than two pounds, albeit statistically significant. Saccharin use was also associated with eight-year weight gain in 31,940 women from the Nurses’ Health Study conducted in the 1970s.

The review goes on to talk about data from youth studies; while the review author claims that those youth studies suggest more obese children show weight gain when using artificially sweetened beverages, a closer look at the reference [4] reveals a non-significant result, suggesting that there is no measurable effect on weight in this study.

But, overall, the studies seem to suggest that there is a trend, in populations that consume significant quantities of artificial sweetener, toward increased body-mass index (BMI). That trend is not extreme, but the data supports its existence. The study in [3] offers several hypotheses, ranging from correlation but not causation (people who overeat tend to adopt artificial beverages and so that population naturally demonstrates an increase in weight) to causation (people who consume artificial sweetener then tend to overcompensate by eating more).

Is there any clarity on whether this is correlation or causation?

The review article in [2] goes on to note other studies that suggest that people that experience a stronger sweet taste report increased appetite; since most artificial sweeteners are much sweeter in taste than sucrose or glucose, this might suggest causation due to the extreme sweetness triggering a more enhanced hunger response.  The article then explores the neuronal connection between sugar and satisfaction, between the response of taste receptors and the brain’s mechanisms for sending the “all satisfied” signal.

The paper ends with a very nice point, based on these recent pilot studies of the neurological sweetness connection:

Lastly, artificial sweeteners, precisely because they are sweet, encourage sugar craving and sugar dependence. Repeated exposure trains flavor preference. A strong correlation exists between a person’s customary intake of a flavor and his preferred intensity for that flavor. Systematic reduction of dietary salt  or fat  without any flavorful substitution over the course of several weeks led to a preference for lower levels of those nutrients in the research subjects. In light of these findings, a similar approach might be used to reduce sugar intake. Unsweetening the world’s diet may be the key to reversing the obesity epidemic. [emphasis is mine]

Our modern American diet is swimming in fat, salt, and sugar. We have been conditioned by the kinds of products commonly available in restaurants to expect fatty texture, savory and sweet foods. Artificial sweeter only appears to exaggerate an underlying problem; our expectation for sweetness leads us to greater consumption of high-energy-content foods. Altering our preferred tastes is more important than slashing artificial sweetener, because the problem may be our preferences and not what’s in the can of diet cola.

[1] http://www.ncbi.nlm.nih.gov/pmc/articles/PMC2771213/

[2] http://www.ncbi.nlm.nih.gov/pmc/articles/PMC2892765/

[3] http://www.nature.com/oby/journal/v16/n8/full/oby2008284a.html

[4] http://www.ncbi.nlm.nih.gov/pubmed/16510646