Lifestyle determinants of the drive to eat: a meta-analysis1–3
Colin Daniel Chapman, Christian Benedict, Samantha Jane Brooks, and Helgi Birgir Schi€ oth
Background: Obesity is emerging as the most significant health
concern of the 21st century. Although this is attributable in part
to changes in our environment—including the increased prevalence
of energy-dense food—it also appears that several lifestyle factors
may increase our vulnerability to this calorie-rich landscape. Epi-
demiologic studies have begun to show links between adiposity and
behaviors such as television watching, alcohol intake, and sleep
deprivation. However, these studies leave unclear the direction of
this association. In addition, studies that investigated the acute im-
pact of these factors on food intake have reported a wide variety of
effect sizes, from highly positive to slightly negative.
Objective: The purpose of this article was to provide a meta-analysis
of the relation between lifestyle choices and increases in acute food
Design: An initial search was performed on PubMed to collect
articles relating television watching, sleep deprivation, and alcohol
consumption to food intake. Only articles published before Febru-
ary 2012 were considered. Studies that took place in a controlled,
laboratory setting with healthy individuals were included. Studies
were analyzed by using 3 meta-analyses with random-effects
models. In addition, a 1-factor ANOVA was run to discover
any main effect of lifestyle.
Results: The 3 most prominent lifestyle factors—television watch-
ing, alcohol intake, and sleep deprivation—had significant short-
term effects on food intake, with alcohol being more significant
(Cohen’s d = 1.03) than sleep deprivation (Cohen’s d = 0.49) and
television watching (Cohen’s d = 0.2).
Conclusions: Our results suggest that television watching, alcohol
intake, and sleep deprivation are not merely correlated with obesity
but likely contribute to it by encouraging excessive eating. Because
these behaviors are all known to affect cognitive functions involved
in reward saliency and inhibitory control, it may be that they
represent common mechanisms through which this eating is
facilitated.Am J Clin Nutr 2012;96:492–7.
The risk of obesity is increasing at an alarming rate, partic-
ularly in the Western world (1). Many researchers have focused
their concerns over this growing epidemic on the underlying
factors that may support an “obesogenic environment” in
westernized countries (2). This has led to an extensive analysis
of external factors influencing weight gain, such as the density
of fast-food restaurants and the prevalence of food-related
marketing (3–5). These studies argued that this environment
causes obesity in part through increasing the accessibility and
salience of energy-dense foods.
Although the increased availability and purchasing of high-
calorie food should certainly promote weight gain, it may be that
this does so through an interaction with obesogenic lifestyle
choices that facilitate increased consumption (6). Evidence is
emerging that links prominent behavioral patterns in the Western
world—such as a tendency toward sleep deprivation, television
watching, and alcohol consumption—to increased sensitivity to
food reward and adiposity (7, 8). A recent epidemiologic study
showed that 58.9% of adults in the United States watch television
for .2 h/d and that those who do have higher daily energy intakes
and are more likely to be overweight (9). Similarly, sleep depri-
vation has been shown to enhance the brain’s response to hedonic
food stimuli and encourage the development of obesity (10–14).
Finally, alcohol use, which is ubiquitous in the Western world, has
emerged as a possible risk factor for weight gain (15–17). This
cluster of behaviors may constitute an “obesogenic lifestyle” that
leaves our brains vulnerable to our obesogenic environment.
However, there is some controversy with regard to the role of
these behaviors in the production of increased food intake.
Studies have reported a wide range of effect sizes, indicating that
these factors have high variability, and showed a range from
strong increases in acute consumption to mild decreases in
consumption. For example, despite several prior studies that
sleep loss produces a mild, although nonsignificant, reduction in
next-day food intake (18). Similarly, some studies have found
a lack of stimulatory impact for both alcohol and television on
food intake (19–21). This variety of findings shows the need for
a systematic analysis of the role of these lifestyle factors in the
induction of spontaneous food intake.
Against this background, the purpose of this study was to
television watching, short sleep duration, and alcohol consumption—
on acute food intake. To do this, controlled laboratory studies that
involved the effects of these factors on consumption were assessed.
The aim was to show whether or not these factors are linked to
increased acute caloric consumption.
1Fromthe Department of Neuroscience, Uppsala University, Uppsala,
2Supportedby the Swedish Research Council (SJB, CB, and HBS), the
Brain Research Foundation (HBS), the A˚ke Wiberg Foundation (CB), and
Novo Nordisk (HBS and CB).
3Addresscorrespondence to CD Chapman, Department of Neuroscience,
Uppsala University, Box 593, 751 24 Uppsala, Sweden. E-mail: colin.
ReceivedMarch 22, 2012. Accepted for publication June 6, 2012.
Firstpublished online July 25, 2012; doi: 10.3945/ajcn.112.039750.
Am J Clin Nutr 2012;96:492–7. Printed in USA. ? 2012 American Society for Nutrition
by guest on November 11, 2012
Supplemental Material can be found at:
For each of the factors assessed, PubMed (http://www.ncbi.
nlm.nih.gov/pubmed/) searches were performed to collect pri-
mary source articles for analysis. PubMed was considered the
best freely available database and was thus the exclusive search
database used. In the case of alcohol consumption, searches were
performed with the use of combinations of the following words:
“alcohol,” “ethanol,” “food,” “intake,” and “hunger.” In the case
of sleep deprivation, searches were performed with the use of
the words “sleep,” “reduced,” “deprivation,” “short,” “food,”
“intake,” and “hunger.” Finally, for television the words “tele-
vision,” “food,” “intake,” and “hunger” were used in different
In all of the cases only controlled, laboratory studies in healthy
participants were used. In studies that used alcohol, the ad-
ministrationof alcohol must haveoccurred a maximumof 30min
before an ad libitum test meal. Calorie consumption for all al-
cohol studies was calculated as the total energy consumed in the
preload and meal (for both the alcohol and the control condi-
tions). In studies that examined television viewing, only designs
eating were included (as opposed to eating before or after
watching). Sleep-deprivation studies were included if they in-
volvedamaximumof5.5h of sleep(inthe deprivationcondition)
and a minimum of 8 h of sleep in the sleep condition on the day
before intake measurements. Because the effect of sleep depri-
vation is not specific to meal type, only studies involving a full
day of food intake after sleep deprivation were included. Studies
with multiple comparison groups were included, and each group
was considered independently. By using these criteria, 8 tele-
vision studies, 5 sleep studies, and 10 alcohol studies were in-
cluded for analysis (12, 18–39). Only studies published before 1
February 2012 were included.
Mean food intake, SD, and sample sizes were included for
analysis in both the experimental and control conditions.Cases in
which data were missing (eg, SDs) were either calculated from
existing data (eg, the SD was calculated from the SEM) or re-
trieved via e-mail from corresponding authors. However, if it was
not possible to recalculate the data or to contact the authors, the
study was excluded from the meta-analysis.
Quantitative data synthesis
each lifestyle factor (sleep deprivation, television watching, and
the studies presented with a variety of heterogeneous qualities
(participant ages, food items presented, precise paradigm used,
etc). Correlations between sample size and effect size were made
to investigate the common problem with small studies of inflating
the effect sizes in meta-analysis. A funnel plot was created to in-
vestigate publication bias (also called the drawer problem) in which
null results are often “left in the drawer.” In addition, a 1-factor
ANOVA was conducted on the cumulative effect sizes of the 3
studies to determine whether there was a main effect.
Initially, 4759 articles were screened as potential candidates.
From this initial screening, 35 articles emerged for possible
inclusion. The majority of exclusions at this stage were because
articles were reviews, irrelevant, or correlational in nature. Of
these 35 studies, 12 were excluded on the basis of our exclusion
criteria, which left 23 studies for quantitativeanalysis (Figure1).
Forest plots of all of the studies included in the analysis for
alcohol, sleep deprivation, and television watching are shown in
Figure 2. All 3 lifestyle factors showed significant cumulative
effect sizes (Cohen’s d) on food intake. The effect was greatest
for alcohol (Cohen’s d = 1.03; 95% CI: 0.66, 1.4; P , 0.001)
followed by sleep deprivation (Cohen’s d = 0.49; 95% CI: 0.11,
0.88; P , 0.05) and television watching (Cohen’s d = 0.2; 95%
CI: 0.04, 0.37; P , 0.05). Specific study characteristics, in-
cluding design and population, are included in Supplementary
Tables S1–S3 under “Supplemental data” in the online issue.
Cumulative effect sizes
As shown in Figure 3, a 1-factor ANOVA determined that
alcohol produced a significantly greater effect size (for calorie
intake) than did television watching (P , 0.001) and trended
toward producing a greater effect size than did sleep deprivation
(P , 0.10). The effect sizes were 1.03 for alcohol consumption,
0.49 for sleep deprivation, and 0.20 for television watching.
Correlations between sample and effect size
No significant correlations were found between effect and
sample size for any of the lifestyle factors analyzed.
Visual inspection of the funnel plot showed relative symmetry
along the treatment-effects axis, which suggests little publication
bias (see Figure S1 under “Supplemental data” in the online
FIGURE 1. Flow chart of the literature search and study selection
LIFESTYLE AND FOOD INTAKE
by guest on November 11, 2012
These results show that lifestyle factors, such as television
watching, sleep deprivation, and alcohol consumption, stimulate
spontaneous food intake, with alcohol causing the most signif-
icant increases. This finding supports the notion that these be-
havioral patterns are not merely linked to weight gain but that
they likely contribute to it by promoting less restricted food con-
sumption. This is a serious concern because of the increasingly
obesogenic environment of the Western world in which calorie-
dense foods are a seemingly permanent part of the landscape. In the
following paragraphs, we discuss potential mechanisms by
which television watching, sleep deprivation, and alcohol con-
sumption increase food intake.
From food reward to hedonic experience
Obesity results, in part, from the reward saliency of food be-
coming abnormally enhanced to the point that it overwhelms the
brain’s homeostatic control mechanisms (40). The reward value
of food can be amplified in genetically vulnerable individuals, but
it can also be increased by environmental factors (40). There are
FIGURE 2. Forest plots (meta-analyses, random-effects models) indicating the cumulative effect sizes (Cohen’s d) for the impact of alcohol intake, sleep
deprivation, and television watching on acute food intake. Sleep-deprivation studies observed intake over the entire day, whereas alcohol and television studies
observed single meals. TV, television.
CHAPMAN ET AL
by guest on November 11, 2012
several lines of evidence that suggest that the lifestyle factors
analyzed in this study increase food intake, partly through en-
hancing this reward value, and this may explain their association
with obesity. Alcohol is known to induce alterations in circulating
ghrelin, a peptide implicated in food reward (41, 42). In addition,
alcohol affects g-aminobutyric acid and opioid systems. The al-
teration of g-aminobutyric acid signaling in reward centers of the
brain stimulates appetite, and opioid signaling has been implicated
in regulating the orosensory reward components of eating (43, 44).
These pharmacologic findings are consistent with human studies
that showed a greater increase in hunger during the early phase of
a test meal after an alcohol preload compared with an energy-
matched carbohydrate preload (45). This mimics the pattern of
response shown when the palatability of food is enhanced through
flavor manipulation (46).
There is similar evidence that links sleep deprivation to an
increase in the hedonic value of food. Sleep loss causes a con-
stellation of metabolic and endocrine changes, including an in-
crease in circulating ghrelin (47). Interestingly, recent studies on
sleep deprivation have found that it increases overall brain re-
increased activation in brain areas involved in reward processing,
such as the putamen, nucleus accumbens, thalamus, insula, and
anterior cingulate cortex. This strongly suggests that sleep
deprivation, like alcohol, leads to deregulation of reward system
activation in response to food.
Finally, there is evidence that suggests that television watching
also increases the saliency of food reward. Several of the studies
included in the meta-analysis found that the effect of television
viewing on food intake was most pronounced with high-calorie
foods, which suggests that television viewing alters the saliency
of food reward (25, 27). Epidemiologic studies have shown
a similar trend, in that those who watch more television tend to
snack more while watching and to consume more energy-dense
snacks (49). Additional evidence suggests that watching images
of palatable food increases plasma ghrelin concentrations (50).
This shows that visual stimuli associated with food evoke changes
in circulating ghrelin; however, it remains unclear whether this
effect translates to all television viewing (including non–food-
related television shows).
Repeated consumption of a rewarding food results in the
formation of new linked memories that condition the individual
to anticipate reward not only in response to the food but also in
response to any environmental stimulus that is often paired with
the reward. With regardto the lifestyle factors analyzed, all three,
when experienced habitually, should strengthen memory traces
that trigger reward expectancy to food cues: that is, when pre-
sented with rewarding food or food cues, people who often suffer
from sleep deprivation or who often watch television or drink
alcohol while eating are more likely to experience a greater
reward response as a result. In addition, both alcohol and tele-
vision likely become their own conditioned cues for those who
consume food in conjunction with these factors. This is partic-
ularly concerning given that obese individuals have been shown
to be more responsive to environmental food cues (51), and
converging evidence indicates a strong role for cues in addictive-
like overeating (52).
Is our inhibitory control out of control?
Whereas these alterations in reward-response likely contribute
be only part of the story. These behavioral patterns may, in
addition to increasing the saliency offood reward, decrease one’s
capacity or tendency to exhibit inhibitory control. Compulsive
behaviors, including excessive eating, are motivated by a com-
bination of enhanced activation of reward saliency and disrupted
activity in brain regions involved in inhibitory control (53). The
orbitofrontal cortex, cingulate gyrus, and dorsolateral prefrontal
cortex are all involved in inhibitory control (54). Neuroimaging
data have implicated the prefrontal cortex as a brain region that
is particularly vulnerable to sleep deprivation (55). Similarly,
both alcohol and fast-paced television have been reported to
impair prefrontal and executive function, respectively (56, 57).
Thus, it may be that these behaviors increase food intake in the
short term not only by increasing reward saliency but also by
decreasing inhibitory control (Figure 4).
There are some limitations to this analysis. There were only 5
studies available for analysis in the case of sleep deprivation, and
thus our findings that sleep deprivation increases food intake the
following day are tentative and warrant further investigation. In
addition, food items included for consumption varied from study
to study; it could be that this had an impact on the cumulative
of these manipulations are more prominent on certain types of
food (eg, calorie-dense items). Demographic variables such as
sex and age were also variable; however, all of the studies were
conducted in healthy individuals, and the majority were con-
ducted inyoung adults. This is a strength in that the data are more
of the impact of these stimuli in other populations, including
youth and the elderly. Young people are known to be relatively
FIGURE 3. Graph indicating the relative cumulative mean (6SEM)
effect size on food intake for alcohol consumption, sleep deprivation, and
television watching. A 1-factor ANOVA showed a significant main effect,
such that alcohol’s effect size was greater than television’s effect size (P ,
0.001) and trended toward being larger than that of sleep deprivation (P ,
0.10). There was no difference between television watching and sleep
deprivation. The effect size was greatest for alcohol (Cohen’s d = 1.03,
n = 278, P , 0.001), followed by sleep deprivation (Cohen’s d = 0.49,
n = 78, P , 0.05) and television watching (Cohen’s d = 0.2, n = 363,
P , 0.05). **P , 0.001,#P , 0.10. ns, nonsignificant; TV, television.
LIFESTYLE AND FOOD INTAKE
by guest on November 11, 2012
flexible in their habits, whereas the elderly tend to rely on more
set routines. Thus, it may be that these lifestyle factors are more
dangerous in younger populations. Finally, the effect sizes of
these different factors are not perfectly comparable, because, in
the case of sleep deprivation, the effect was significant for cu-
mulative food intake on the day after deprivation, whereas for
television and alcohol the effect was relative to a single meal
Taken together, the results of this meta-analysis show that
prominent Western lifestyle factors, such as sleep deprivation,
alcohol consumption, and television watching, promote increases
in acute caloric consumption. These increases are likely related
to a series of neurologic and endocrine adaptations, which result
in an increased value for food reinforcers, predisposing an in-
dividual to food addiction, adiposity, and ultimately obesity.
Fortunately, emerging evidence suggests that curtailing these
lifestyles can reverse this trend. A recent study showed that
shifting sleep from a short to a healthier length, over a 6-y time
span, was associated with the attenuation of fat mass gain (58).
Similarly, research that investigated the effects of reduced
televisionviewing on children found that children whowatched
,1 h of television/d had reduced body weights, BMIs, skin-fold
thicknesses, and fat mass and were less likely to be categorically
overweight (59). Finally, reduced alcohol consumption in early
adulthood can help to attenuate weight gain and abdominal
obesity in adulthood (60). These results thus highlight the
importance of increasing awareness of the prominent role that
these lifestyles play in inducing food intake and subsequent
The authors’ responsibilities were as follows—CDC and SJB: designed the
study; CDC: analyzed data; and CDC, CB, SJB, and HBS: critically revised
the manuscript for important intellectual content and contributed to writing the
manuscript. All authors had full access to all of the data and take responsibility
for the integrity and accuracy of the data analysis. The funding sources had no
input in the design or conduct of this meta-analysis; in the collection, analysis,
or interpretation of the data; or in the preparation, review, or approval of the
manuscript. None of the authors had a conflict of interest.
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by guest on November 11, 2012