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Bad moon on the rise? Lunar cycles and incidents of crime


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Popular cultures in Western societies have long espoused the notion that phases of the moon influence human behavior. In particular, there is a common belief the full moon increases incidents of aberrant, deviant, and criminal behavior. Using police, astronomical, and weather data from a major southwestern American city, this study assessed whether lunar cycles related with rates of reported crime. The findings fail to support popular lore, which has suggested that lunar phase influenced the volume of crime reported to the police. Future research directions examining qualitative rather than quantitative aspects of this problem may yield further inform the understanding of whether lunar cycles appreciably influence demands for policing services.
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Roger Williams University
School of Justice Studies Faculty Papers School of Justice Studies
Bad moon on the rise? Lunar cycles and incidents
of crime
Joseph A. Schafer
Southern Illinois University Carbondale
Sean P. Varano
Roger Williams University,
John P. Jarvis
Behavioral Science Unit, Federal Bureau of Investigation
Jerey M. Cancino
Texas State University-San Marcos
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Recommended Citation
Schafer, Joseph. A., Sean P. Varano, John P. Jarvis, and Jerey M. Cancino. 2010." Bad moon on the rise? Lunar cycles and incidents of
crime." Journal of Criminal Justice38 (4): 359-367.
Bad moon on the rise? Lunar cycles and incidents of crime
Joseph A. Schafer
, Sean P. Varano
, John P. Jarvis
, Jeffrey M. Cancino
Department of Criminology & Criminal Justice, Southern Illinois University Carbondale, Carbondale, IL 62901-4504, United States
School of Justice Studies, Roger Williams University, One Old Ferry Rd., Bristol, RI 02809, United States
Behavioral Science Unit, Federal Bureau of Investigation, Quantico, Virginia 22135, United States
Department of Criminal Justice, Texas State University-San Marcos, 601 University Drive, San Marcos, TX 78666, United States
Popular cultures in Western societies have long espoused the notion that phases of the moon inuence
human behavior. In particular, there is a common belief the full moon increases incidents of aberrant,
deviant, and criminal behavior. Using police, astronomical, and weather data from a major southwestern
American city, this study assessed whether lunar cycles related with rates of reported crime. The ndings fail
to support popular lore, which has suggested that lunar phase inuenced the volume of crime reported to
the police. Future research directions examining qualitative rather than quantitative aspects of this problem
may yield further inform the understanding of whether lunar cycles appreciably inuence demands for
policing services.
© 2010 Elsevier Ltd. All rights reserved.
It is the very error of the moon;
She comes more near the earth than she was wont,
And makes men mad.
-Othello, Act V, Scene II
Western lore has long suggested a relationship between the
phases of the moon and various forms of aberrant, antisocial, deviant,
and criminal human conduct. Popular thinking, visual arts, drama, and
literature have expressed this notion well beyond the legend of
vampire, werewolves, witches, and warlocks. The root of the word
lunaticis luna,Latin for moon(Merriam-Webster Online
Dictionary, 2008). Even in contemporary times with considerable
advances in scientic knowledge, there was a continued belief that
lunar phases effect human behavior (Lieber, 1996; Rotton & Kelly,
1985; Rotton, Kelly, & Elortegui, 1986) including limited evidence of a
high rate of belief among mental health care providers (Vance, 1995).
An on-going debate concerned whether lunar effects could be
empirically veried; that is, whether a disproportionate number of
deviant or abnormal episodes occur when the moon is full(Culver,
Rotton, & Kelly, 1988, p. 684).
Policing, crime, and criminal justice have not been immune from
speculation concerning the lunar-crime relationship. In working
with police ofcers on a wide range of research projects, the authors
frequently heard individuals express the belief that the quality and/or
quantity of activity were linked with full moons (see also Lieber, 1996,
p. 21). Such beliefs have been systematically veried through surveys
of police ofcers (Rotton et al., 1986; Vance, 1995). The study reported
herein examined the lunar-crime relationship using ve years of
policing, astronomical, and weather data from a major southwestern
American city. The results were inconclusive in supporting what
popular lore would suggest being true. With few exceptions the
moon's phase was not related with the level of crime and disorder
reported to the police, controlling for relevant weather conditions.
The limited signicant ndings would tend to contradict the lunar
lore, suggesting that when lunar phase mattered it constrained, rather
than increasing, targeted forms of aberrant behavior.
How might lunar phase affect behavior?
The cultural lore concerning lunar effects is vague in describing the
specic ways and reasons for the moon's effect. Most lunar effect
studies had not gone into great depth in explaining how and why the
moon inuenced human conduct. It simply noted that lunar effects
might have been expected. Scientic study of lunar effects might best
be grouped into two broad categories: (1) the notion that lunar cycle
inuences certain opportunities for criminal acts and (2) the notion
that the moon inuences human behavior in some measurable
manner. Prior research tended to frame inquiry in light of the latter
hypothesisthat lunar cycles inuenced rates of aberrant behavior.
The former category had received less scholarly inquiry, perhaps
because it implied the effect of the moon was far less direct. Rather
than actually causing human behavior, this perspective suggests that
rational choices concerning criminality are inuenced by a number of
Journal of Criminal Justice 38 (2010) 359367
This paper was accepted under the Editorship of Kent Joscelyn.
Corresponding author. Tel.: +1 618 453 6376.
E-mail address: (J.A. Schafer).
0047-2352/$ see front matter © 2010 Elsevier Ltd. All rights reserved.
Contents lists available at ScienceDirect
Journal of Criminal Justice
variables, including lunar illumination. Under this line of thinking, a
full moon does not actually cause offenders to commit criminal acts;
rather, the illumination provided by a full moon serves to facilitate or
hinder certain forms of criminal conduct. Rational offenders might
include lunar illumination in making assessments about their
behaviors. Just as a burglar would look for a property offering easy
entry and with limited guardianship, she/he would also be motivated
to avoid committing that crime in well-lit areas, such as those with
exterior illumination, street lights, or signicant ambient moon light.
To do so would be to risk detection by alert citizens or the police.
The latter category, in contrast, was the subject of much of the
existing social and behavioral scholarship. The physical sciences have
long-established the relationship between the moon and geophysical
conditions on earth, particularly the ebb and ow of tides. This
relationship led some medical and social science researchers to
postulate the high concentration of water in the human body would
result in a similar gravitational pull that could have affected human
behavior (see Lieber, 1978b, 1996). Although most research followed
this line of thinking, the relationship was usually not made explicitly
clear. Research was focused on testing the existence of a lunar effect,
rather than explaining the actual reason for an observed effect. The
vagueness of the mechanisms driving the postulated lunar-behavior
relationships complicated efforts aimed at empirical verication.
Studies of lunar effects
Social science research has studied lunar effects using a wide range
of methodologies, data sources, populations, and variables. The
resulting body of literature tended to suggest weak to non-existent
lunar effects, though a few vocal scholars argued improper method-
ologies were to blame for mixed ndings (Cyr & Kaplan, 1987, 1988;
Lieber & Sherin, 1972; Templer & Veleber, 1980). As addressed below,
the debate over lunar effects was as much a debate over proper
methodology as a debate over actual inuences. Some contended
improper methods resulted in null ndings; others argued that
stray observed effects tended to disappear upon introducing control
variables into an analysis (Bickis, Kelly, & Byrnes, 1995; Durm, Terry, &
Hammonds, 1986; Kelly & Rotton, 1983; Rotton, Kelly, & Frey, 1983).
Studies generally failed to nd a lunar effect, though researchers
found varying associations between lunar phase and some categories
of crime (Purpura, 1979), aggression (Lieber, 1978a), violent incidents
in correctional settings (Pettigrew, 1985), volume of demand for
emergency room services (Blackmon & Catalina, 1973), suicide
attempts (Taylor & Diespecker, 1972), hospital admissions (Templer
& Veleber, 1980; Weiskott & Tipton, 1975), and calls to telephone
counseling services (Templer & Veleber, 1980; Weiskott, 1974). Most
studies employed few (if any) controls, used short time frames (i.e.,
four months, which only measured effects across four lunar cycles),
and achieved relatively weak statistical signicance, sometimes
nding effects on some dependent variables, but not on others. In
addition to nding a lunar effect during periods of full moons, studies
found effects of new moonsperiods when the moon was not
reecting the sun's light back toward earth, making it difcult to
observe with the naked eye (Templer & Veleber, 1980; Templer,
Veleber, & Brooner, 1982).
Despite these positive associations, the majority of lunar research
failed to establish effects. This included failing to nd effects on:
aggressive acts in prisons (Atlas, 1984; Simon, 1998) and psychiatric
facilities (Durm et al., 1986; Quinsey & Varney, 1977), prison escapes
(Pettigrew, 1985), use of hospital psychiatric services (Bauer &
Hornick, 1968; Shapiro, Streiner, Gray, Williams, & Soble, 1970;
Walters, Markley, & Tiffany, 1975), incidents of suicide (Biermann
et al., 2005), use of telephone crisis centers (Wilson & Tobacyk,
1990), hospital admissions for dog bite injuries (Chapman &
Morrell, 2000), aggression among ice hockey players (Russell & de
Graaf, 1985; Russell & Dua, 1983), demands for police and re services
(Bickis et al., 1995; Frey, Rotton, & Barry, 1979), automobile accidents
(Campbell & Beets, 1978; Laverty & Kelly, 1998), suicide (Lester,
Brockopp, & Priebe, 1969), and homicide (Pokorny & Jachimczyk,
1974). Studies often achieved contradictory results on crime-related
outcomes, particularly calls for policing service and homicides. At
times, two sets of researchers examined the same data and achieved
opposite conclusions (cf. Kelly & Rotton, 1983; Templer et al., 1982)
due to inconsistency in conceptualizing and operationalizing key
study variables, as well as using different statistical controls and
Lunar effects on crime
Despite the volume of research testing for lunar effects, few
researchers employed crime-related outcomes (exceptions included
Cohn, 1993; Purpura, 1979). Where relationships were found lunar
inuences were modest, particularly in contrast to temporal and
situational predictors. There are several reasons to hypothesize that
lunar cycles may inuence crime, either due to direct effects on
human behavior or as a factor inuencing rational offenders. First and
foremost, though not directly tested in this study, research has shown
that belief in lunar effects continued to be strong (Russell & Dua,
1983), including among police ofcers (Rotton & Kelly, 1985; Rotton
et al., 1986; Vance, 1995) and tended to be associated with beliefs in
other paranormal phenomena (Rotton & Kelly, 1985). Ofcers have
the benet of directly observing the aftermath of criminal incidents;
their experiences may provide them with unique insights into lunar
effects, or police culture may simply perpetuate false beliefs about
lunar effects. Second, studies of lunar effects on crime tended to use
limited offenses and short time frames, while failing to introduce
control variables. This study sought to overcome weaknesses in
prior studies by considering a long-time frame, multiple offense
types, and salient control variables. Third, moving beyond the beliefs
of police ofcers, there was evidence that beliefs in lunar effects
were prevalent. Testing the veracity of these beliefs was of obvious
Is crime inuenced by seasons or short-term variations in
climate conditions?
One of the rst observations about the effects of weather on crime
was offered by Belgian statistician Adolphe Quételet (1842/1969),
who noted during summer, the greatest number of crimes against
persons are committed and the fewest crimes against property; the
contrary takes place during the winter(p. 90). For over 150 years
scholars tested and elaborated on this assertion, introducing broader
meteorological data into empirical models. The social contact
hypothesis suggests that during times of pleasant weather, aggressive
and hostile acts may be more common because there is an increase in
normal human interactions, which increases the opportunity for
interpersonal conict. Within weather and crime research, scholars
attempted to sort out the social versus physiological effects of weather
on human behavior (Cheatwood, 1995).
More contemporary analyses of policing data from American
communities tended to nd that many types of personal and property
crimes were more common during periods of warm versus cool or
cold weather (Cheatwood, 1995; Cohn, 1990b, 1996; Cohn & Rotton,
2000; Hipp, Bauer, Curran, & Bollen, 2004; Rotton & Cohn, 2003) and
that demand for police services were greater during periods of
warmer temperature and longer hours of daylight (i.e., spring and
summer) (Cohn, 1996; Heller & Markland, 1970; LeBeau & Corcoran,
1990; LeBeau & Langworthy, 1986).
Research suggested this
relationship generally held true, though there were upper limits.
Rotton and Cohn (2000) found disorderly conduct and assault in
Minneapolis had an inverted U-shapedrelationship; during periods
of extreme heat and cold these behaviors were less frequent. In
360 J.A. Schafer et al. / Journal of Criminal Justice 38 (2010) 359367
reviewing early weather and crime research, Cohn (1990a) observed
research established stronger relationships for personal than property
crimes, noting
assaults, burglary, collective violence, domestic violence, and rape
tend to increase with ambient temperatureThe relationship
between heat and homicide is uncertain. High temperatures do
not appear to be correlated with robbery, larceny, and motor
vehicle theft. (p. 61)
When analyses accounted for temporal variables (i.e., time of
day, weekends, holidays, periods when public schools are not in
session), weather effects offered relatively modest explanatory effects
(Cheatwood, 1995; Cohn, 1993). The inuence of temporal and
weather variables were presumably a result of changes in routine
activities of offenders and victims (e.g., Cohen & Felson, 1979), though
these effects might be trumped by situational variables (Rotton &
Cohn, 2000).
Methodological chaos
A signicant challenge surrounding the study of lunar effects on
human behavior is the imprecision of this cultural lore. What, exactly,
is the moon supposed to inuence and how is that inuence exercised?
Such basic questions hold tremendous implications for conceptual,
operational, and analytical decisions. Similar concerns are noted
in literature examining weather-crime relationships (Block, 1983,
How, for example, should lunar phase be dened and
Also important to consider is whether the relationship is
based on the moon's visibility, which would suggest restricting an
analysis to nighttime hours and controlling for salient weather
If there is an effect on crime, is it the quality of crime
(i.e., offenders act more crazythan normal), quantity (i.e., the
volume of crime), or both? Will crime-related effects translate into
police records in an observable manner? The contention that existing
methodological chaos has made impossible any consistency in results
in the evaluation of the lunar hypothesis(Cyr & Kaplan, 1987, p. 391)
was well founded. While characterizing previous efforts to study
this alleged phenomenon as chaotic may be overly dramatic, such
difculties should be expected when scholars sought to study a vague,
ill-dened, and indistinct dimension of western cultural lore.
Decisions concerning proper data sources, variable structures,
operational denitions, and statistical tests, among other considera-
tions, were not straight-forward. Block (1983) noted a similar
assessment when testing for seasonal effects on crime. Her mono-
graph offered a number of insightful parallels to analyzing lunar
effects. For example, Block noted researchers were typically con-
strained by the quality and structure of the data at hand; even when
there was great control over data sources and variable structures,
there were few clear rules for conducting analyses. Given the folklore
origins of the lunar effect, researchers did not have a clear map
informing choices concerning the selection of dependent and
independent variables, or the analytical methods used to examine
data. This situation certainly contributed to the widely varying
methodologies and results observed across salient research literature.
Research objective
The purpose of this study was to test the effects of lunar phase on
criminal and criminal and disorderly behavior through the construct
of methodological framework more rigorous than those found in
many prior studies. San Antonio, Texas, is located in the southwestern
United States and has a population of more than one million residents.
Using call for service (CFS) to the San Antonio Police Department
(SAPD) (e.g., 911) over a ve-year period (2001-2005) as a measure
of crime and disorder, a time-series design was used to determine the
linear relationship between lunar cycles and levels of reported crime
and disorder. Calls for service that occurred during nighttime hours
(8 p.m. 3 a.m.) were grouped into seven categories: assaultive
violence, burglary, theft, drugs/vice, trafc, other disturbances, and
aggregated CFS (the sum of the six categories). In so doing, the study
attempted to control for two competing perspectives about the
inuence of lunar phase. First, did lunar phase itself appear to
inuence activities reported to the police; did lunar phase produce a
quantitative shift in human behavior as measured by the volume of
select categories of calls to the police? Second, could lunar phase
create conditions that would enhance or diminish the rationality of
select offenses? The research design accounted for potential impacts
of land use issues by analyzing citywide trends, but also considered
trends in both San Antonio's entertainment area and non-entertain-
ment areas.
The analysis relied on ve years (2001-2005) of data for police
calls for service and National Weather Service (NWS) records that
depicted San Antonio's weather patterns during the same period. As
state above, the purpose of this research was to determine if there was
a relationship between lunar cycles and nightly crime levels, a
perception that was embedded in the folklore shared by both police
personnel and citizens. The analysis rst considered descriptive
analysis of variables along with bivariate correlation analysis; this
was followed by multivariate and time series analysis on each of the
dependent variables to determine the impact of lunar cycles on levels
of crime and disorder.
Dependent variables
CFS data represented instances of crime and disorder that were
received by the dispatch unit of the SAPD and are more typically
known as 911 callsto most citizens. The data provided by SAPD's
crime analysis unit were limited to calls of direct jurisdiction of law
enforcement (i.e., requests falling under the jurisdiction of other
service providers were not included). Incidents of concern to law
enforcement typically involved alleged crimes or other incidents
requiring that an ofcer be dispatched to a scene. During the time
period under consideration, SAPD received approximately 900,000
CFS per year; this resulted in approximately 225,000 completed police
incident reports per year. Annually, approximately 130,000 CFS
concerned the six disorder categories considered in this analysis.
Nightly counts of crime and disorder were computed for seven CFS
categories: assaultive violence, burglary, theft, drugs/vice, trafc, other
disturbances, and aggregated CFS. Nighttime was operationalized as
reported incidents between 8 p.m. to 3 a.m. Using January 2, 2001 as an
example, total nighttime CFS were calculated for calls received
between 8 p.m. on January 1 and 3 a.m. on January 2, 2001. San
Antonio has a well-known and established entertainment district (the
Riverwalk) within its borders. The Riverwalk draws a high volume of
tourists and residents to restaurants, bars, hotels, convention facilities,
shops, and other entertainment venues. To account for possible land
use effects (see Brantingham & Brantingham, 1995; Robinson &
Rengert, 2006) CFS totals were computed for the entire city, the non-
entertainment area alone, and the entertainment area alone. This
strategy allowed for consideration of any possible interplay with land
use (see Table 1 for descriptive statistics).
Independent variables
The key independent variable, lunar phase, was a continuous level
variable that measured the where the moon was in its lunar cycle at
midnight during each date in the analysis. This data were publicly
available from the Astronomical Applications Department of the U.S.
361J.A. Schafer et al. / Journal of Criminal Justice 38 (2010) 359367
Naval Observatory (see The variable ranged
from 0 (a new moon night) to 1.00 (a full moon night); this value was
based on the presumption of a clear sky and did not take into account
any weather conditions that might have obstructed the actual
visibility of the moon.
Each night constructed for the dependent
variable was paired with the respective lunar phase at midnight. In
other words, the dependent variable consisted of CFS counts for each
night (8 pm 3 am) in the ve years under consideration; these
nights were paired with the lunar phase reported for midnight on that
same night. This approach represented a substantial advancement in
this area of study. Prior research tended to operationalize lunar phase
in dichotomous (full moon versus non-full moon periods) (see Atlas,
1984; Cohn, 1993; Purpura, 1979) or basic ordinal terms (full moon,
new moon, and interphase; new moon, rst quarter, full moon, last
quarter) (see Kelly & Rotton, 1983; Pokorny & Jachimczyk, 1974;
Templer et al., 1982). These approaches restricted the lunar phase to
nominal or ordinal variability; this analysis employed a more robust
ratio variable to represent lunar phase.
Control variables were included to account for possible seasonal,
temporal and weather effects that might have mediate lunar effects.
Winter accounted for seasonal uctuations in weather that might have
affected socialization patterns related with rates of crime. Winter was
a dummy variable where 1indicated dates that fell between
December 1 and March 31. It was expected that crime patterns would
naturally decrease during winter months and then increase during
other months (see Cheatwood, 1988). The variable weekend, also a
binary variable, was coded as 1to represent Fridays, Saturdays, and
Sundays. Social patterns that inuence levels of crime and disorder
were expected to independently affect nightly crime patterns.
Additional control variables represented weather patterns and
were derived from the National Climatic Data Center (NCDC), a
division of the National Oceanic and Atmospheric Association. NCDC
records are based on data and observations collected by instruments
and human observers at NWS stations around the country. Data from
the NWS station located at the San Antonio International Airport were
used to represent weather. These controls were important because if
lunar cycles inuenced the opportunity for crime through increased
visibility, such effects could have been diminished by inclement
weather that obscures such visibility. Weather also had the capacity to
inuence social patterns that may have independently inuenced
crime and disorder levels.
Sunset was a continuous variable that identied the ofcial time of
sunset based on a twenty-four hour (military) clock. Time of sunset
may have inuenced social patterns that also affected crime levels.
Nightly temp reected the temperature recorded by the NCDS in
degrees Fahrenheit. The NCDS data included temperature observa-
tions taken at three hour increments thorough the day. For this
analysis mean nightly temperatures were computed using the 9 pm,
midnight, and 3 am observation periods. The temperature was
expected to be positively associated with crime levels. Finally,
precipitation was a continuous variable that measured precipitation
(in inches) during the twenty-four hours on each day. This measure
was a proxy indicator of the overall extent to which prevailing
weather patterns might have made criminal acts less favorable. Levels
of crime and disorder were expected to be negatively associated with
precipitation. See Table 1 for descriptive statistics.
Analysis and ndings
To test for possible lunar effects on crime and disorder levels,
analyses of nightly crime trends was done while controlling for
temporal and weather variables that may mediate any apparent
effects. The analysis included univariate descriptive statistics that
describes each of the independent variables across the three land use
types (e.g., citywide, non-entertainment area, and entertainment area
only). In addition, bivariate and multivariate statistics were used to
determine the relationships between lunar cycles and crime while
controlling for other possible explanatory variables. The multivariate
analysis included time series design commonly referred to as
autoregressive moving average (ARIMA) technique or ordinary-least
squares regression. The exact analytical techniques used were based
on a preliminary analysis of time or season-related patterns that
required statistical control. A diagnostic tool available in the SPSS was
used to automatically determine if time-or-season-dependent trends
existed in each trend. When no such patterns were evident, simple
OLS analysis was used. When time-dependent trends were apparent,
time-series analysis was used to control for these patterns.
The descriptive statistics are included in Table 1. There were 1,826
nights included in the study period of January 1, 2001 to December
31st 2005. These nightly units comprised each unique observation or
unit of analysis. The statistics included in the top half of Table 1
provide summary measures of nightly crime totals (counts) for
aggregated crime and the six subcategories (assaultive violence,
burglary, theft, drugs/vice, trafc, and disturbances) for all three areas
of the city. It is important to note that these crime classications were
based on how events were classied in call for service (911) data and
not ofcial police reports. This method of measuring crime and
disorder did not take into account if police failed to le a police report
or changed the classication of an incident to another category than
originally classied in the call data. Thus, the categorizations reected
those made by call takers after consultation with complainants/
victims. An advantage of this approach was removing the possibly
biasing effects of ofcer beliefs; if ofcers believed crime increased
during full moon phases they may have had a proclivity to categories
incidents as criminal and/or more serious in nature.
Table 1
Descriptive statistics for nightly totals (n = 1826)
Citywide Totals Non-Entertainment Area Entertainment Area Only
Min. Max. Mean Std. Dev. Min. Max. Mean Std. Dev. Min. Max. Mean Std. Dev.
Totals 0 806 359.81 101.12 0 750 340.97 96.11 0 111 21.80 15.84
Assaultive Violence 0 72 19.38 9.51 0 65 17.62 8.73 0 47 4.55 5.84
Burglary 0 265 58.09 19.32 0 255 55.09 18.54 0 26 2.99 2.61
Theft 0 16 2.11 1.85 0 16 1.90 1.76 0 13 0.39 1.13
Drugs/Vice 0 32 10.97 5.61 0 32 10.14 5.31 0 15 0.83 1.31
Trafc 0 84 23.45 9.29 0 83 22.07 8.70 0 11 1.38 1.62
Disturbances 0 599 226.91 74.14 0 573 216.24 71.10 0 50 10.66 7.52
Lunar Phase 0 1 0.50 0.35
Winter 0 1 0.33 0.47
Weekend 0 1 0.29 0.45
Sunset 1735 1938 1843.72 71.61
Nightly Temp 31 86 65.21 12.90
Precip 0 9.5 0.10 0.39
362 J.A. Schafer et al. / Journal of Criminal Justice 38 (2010) 359367
A comparison of the absolute values of average nightly counts
across geographical areas was not valid because the areas included
different geographical sizes with different size populations at risk. The
data presented in Table 1 indicated that the average number of calls
for service reporting criminal situations was approximately 360 per
night with a range 806 reports (see citywide totals). The largest single
group of reported crimes/disorders was the disturbancescategory
for the citywide data, but also for the entertainment and non-
entertainment areas. This category was a very broad grouping that
included a wide-range of problematic behavior including disorderly
persons, loud parties, suspicious persons, etc. It amounted to a catch
allclassication for events that did not fall neatly into other
categories. The next largest categories were burglary and assaultive
violence for both the citywide and non-entertainment area totals. The
average nightly totals for assaultive violence (x̄= 4.55) were higher in
the entertainment area compared to other sectors of the city. This was
likely due to differences in land use patterns and the nature of
socialization patterns (e.g., high density of bars and other entertain-
ment establishments).
The second grouping of variables included the principle indepen-
dent variables, lunar phase, and ve additional variables that
controlled for seasonal (winter), temporal (weekend and time of
sunset), and weather (nightly temperature and precipitation) varia-
tions. The average lunar phase across the observation time was fty-
percent. The sunset time was measured on a military time scale that
ranges from 0-2400; the average time of sunset was 1843 hours, or
6:43 pm. The average temperature during the nightly observation
periods was 65 degrees (Fahrenheit). Finally, there was approximate-
ly .10 inches of daily precipitation during the study period, though an
appreciable range was noted on that variable.
Bivariate analysis
Bivariate correlations are included in Table 2. At the bivariate level,
the data suggested there was no relationship between lunar phase
and crime. This relationship generally held for citywide disorder
patterns, but also for crime trends in non-entertainment and
entertainment areas with one exception. The relationship between
drugs/vice crimes in the entertainment district was signicant and
negative, although the coefcient was relatively small. This relation-
ship suggested that while illumination was not a factor in crime, the
inuence was dependent on land use patterns. It was also noteworthy
that many of the temporal, seasonal and weather control variables
were signicant across the data, largely in the expected directions.
Winter was a seasonal control variable; it was hypothesized that
due to changes in season-related socialization patterns, crime would
likely be lower during the winter. The signicant and negative
relationship across crime types and locations indicates that crime/
disorder was generally lower during winter months, even in such a
temperate climate. Weekend was a temporal control that depicted if
the observation period occurred on Friday, Saturday, or Sunday.
Related again to natural variations in socialization patterns linked to
day-of-the-week, a positive relationship was expected. That is, more
crime was expected on the weekends. The hypothesis was supported
by the signicant and positive relationships across crime types and
geographical locations, relationships that were greater than 0.7 in
several cases. The data presented in Table 2 also indicated a consistent
signicant and positive relationship between daily sunset and crime.
This indicated that crime increased as sunset was delayed. This nding
was interesting because it suggested levels of crime were positively
associated with levels of solar illumination.
Finally, the data also indicated strong relationships between levels
of crime/disorder and both average nightly temperature and levels of
precipitation. The signicant and positive coefcients for temperature
indicated that crime increased during warmer days across geograph-
ical locations. Finally, a pattern emerged suggesting that when
signicant, the relationship was generally negative. This indicated
that crime decreased on rainy nights. Interesting, the relationship for
precipitation and crime was less apparent in the entertainment area
which might suggest that tourists were less deterred by bad weather.
The bivariate analyses indicated that while all of the control
variables were signicantly related to levels of crime and disorder,
lunar phase demonstrated little explanatory power. With the
exception of levels of drugs and vice in the entertainment area,
lunar phase showed no signicant relationships. Moreover, the
direction of the relationships was scattered across types of disorder-
ly/criminal behavior and geographical areas. Results of the bivariate
analysis seemed contrary to the lore of a lunar affect on crime and
disorder; in fact the weak drugs/vice nding in the entertainment
area is contrary to what lore would predict. To further test this
relationship, multivariate analysis (both ordinary least squares
regression and time series analysis) was used to understand the
relationships between lunar phase and crime while controlling for
other temporal, seasonal, and weather related conditions.
Multivariate analysis
Time-series analysis was an appropriate analytical strategy for
regressing time-and-season dependent variables on independent
variables. The autoregressive integrative moving average model
(ARIMA) was developed by Box and Jenkins (1976) as a methodo-
logical strategy for removing trends from data. ARIMA analysis
involves an iterative model building process where the analyst
diagnoses the structure of the trend and then builds the appropriate
statistical model to these biasing effects that may distort statistical
relationships. ARIMA models have three structural parameters
that must be diagnosed and modeled, autoregressive (p); difference
(d); and moving average (q) parameters (see McDowall, McCleary,
Meidinger & Hay, 1980).
The rst step in constructing these models is to ensure trends are
stationary. Stationary refers to the degree to which the data series
uctuates around a xed mean. A nonstationary trend is represented
by a non-zero integer in the dterm. The differencing process involves
subtracting a value from the preceding k
observations with k
representing the dparameter. The autoregressive parameter reects
the mathematical relationship between an observation and k
preceding values. Finally, the moving average parameter (q) is similar
Table 2
Bivariate Correlations
Winter Weekend Sunset Nightly
City Trafc -0.00 -0.27** 0.57** 0.26** 0.29** 0.05*
City Burglary 0.02 -0.16** 0.24** 0.25** 0.21** 0.14**
City Disturbance 0.00 -0.26** 0.79** 0.22** 0.26** -0.08**
City Assault -0.02 -0.23** 0.71** 0.19** 0.25** -0.07**
City Drugs/Vice -0.01 -0.32** 0.22** 0.31** 0.34** -0.09**
City Theft -0.01 -0.12** 0.15** 0.14** 0.11** -0.02
City Aggregated 0.00 -0.31** 0.78** 0.29** 0.32** -0.05*
NonEnt Trafc -0.00 -0.27** 0.55** 0.26** 0.29** 0.06*
NonEnt Burglary 0.02 -0.17** 0.24** 0.25** 0.22** 0.14**
NonEnt Disturbance -0.00 -0.26** 0.79** 0.23** 0.26** -0.08**
NonEnt Assault -0.01 -0.23** 0.70** 0.19** 0.25** -0.07**
NonEnt Drugs/Vice 0.00 -0.31** 0.19** 0.31** 0.35** -0.09**
NonEnt Theft -0.00 -0.11** 0.12** 0.13** 0.11** -0.03
NonEnt Aggregated 0.00 -0.31** 0.78** 0.29** 0.32** -0.05*
Ent Trafc 0.02 -0.11** 0.30** 0.10** 0.10** -0.01
Ent Burglary 0.01 -0.01 0.08 0.03 0.01 0.06
Ent Disturbance 0.01 -0.12** 0.33** 0.11** 0.10** -0.05*
Ent Assault -0.03 -0.10** 0.33** 0.09** 0.08** -0.02*
Ent Drugs/Vice -0.06* -0.10** 0.17** 0.09** 0.06* -0.02
Ent Theft -0.04 -0.05 0.13* 0.05 0.01 0.06**
Ent Aggregated -0.01 -0.13** 0.35** 0.12** 0.10** -0.03
** pb.01.
363J.A. Schafer et al. / Journal of Criminal Justice 38 (2010) 359367
to the autoregressive parameter except that it represents the affects of
past error that cannot be modeled with the autoregressive parameter.
The iterative process described above can be labor intensive and non-
precise as the analyst visually interprets graphs (correlograms) to
determine the best t for the data. SPSS 14.0, however, includes a time
series modeler that automates this process by running through a
series of iterations and identifying the best model for the data series.
This modeler is useful as it reduces the level of subject interpretation
associated with identifying the proper parameter estimates (see
Bushway & McDowall 2006) for a discussion on the challenges
associated with establishing causal effects in trend data).
Tables 35present the multivariate ndings for the three
geographical areas (citywide, non-entertainment, and entertainment
Each table includes seven different models, one for each of the
crime categories; a description of the model types is located below the
categories. The ARIMA parameter estimates are included when
applicable and OLS indicates a simplied regression model was
used. As indicated above, these model types were determined through
diagnostic procedures available in the statistical software package
The citywide analysis is presented in Table 3. The discussion will
focus primarily on the relationships between lunar phase and not the
other control variables for reasons of brevity (seven categories of
crime across three geographical areas). Looking across the citywide
analysis, lunar phase was signicant only for the burglary model and
in the positive direction. This suggested that as lunar phase increased
(i.e., the moon became more full), so did levels of burglary. While the
lunar phase-crime relationship was positive across the other
categories (with the exception of assault and theft) none of these
reached statistical signicance. The relationships among the control
variables and crime levels largely remained unchanged in the
multivariate models, with the exception of sunset which was
relegated largely insignicant across the models.
The ndings for the non-entertainment area are detailed in
Table 4. This area includes the entire city of San Antonio minus the
Riverwalk district. Similar to Table 3, these ndings indicated that
lunar phase had no effect on levels of crime and disorder in San
Antonio. The relative impact of the sunset variable was also moderated
in these models; sunset was signicant in only the burglary and theft
models, exerting a positive relationship in both instances.
Finally, the ndings for the entertainment area are presented in
Table 5. Looking across the seven models, it is apparent that the
seasonal, temporal, and weather-related control variables that
were so prominent in most of the bivariate relationships and the
prior two multivariate tables largely disappear in Table 5. This
suggested that after including the additional control variables and
detrending the data, crime and disorder levels in the entertainment
district were inuenced to a lesser degree by these factors. The
one notable exception, not unexpectedly, was the weekend control
variable. That is, crime and disorder levels were signicantly greater
in the entertainment area on weekends net all other controls. This
may suggest that socialization patterns that explain the occurrence
of crime and disorder are largely xedregardless of the weather,
temperature, and season. It is also interesting to note that while the
relationships between lunar phase and crime levels were not
signicant across the models, there was one exception; the rela-
tionship between lunar phase and drugs/vice was signicant and
negative. This indicates that as lunar phase increased (i.e., the moon
trended toward a more full state), the reported levels of drugs and
vice decreased.
Lunar lore is an established aspect of western culture, though the
specics of this belief (i.e., how and why the moon might exert an
inuence on human behavior) was imprecise. This study attempted to
determine whether lunar phase inuenced disorderly and criminal
acts as indicated by the volume of incidents reported to the police
each night during a ve year period in a major southwestern US city. If
a presumed lunar effect was supposed to inuence humans through
some form of biosocial mechanism (Lieber, 1978b, 1996) the ndings
reported here offered no real support of this supposition using the
dependent variable at hand. Prior studies were conrmed here; there
was no clear evidence that lunar cycles had more than marginal (and
likely spurious) explanatory power in understanding levels of crime
and disorder. Although popular culture, folk lore, and even certain
occupational lore suggested the freakscome out during full moons
(Lieber, 1996; Rotton & Kelly, 1985; Rotton et al., 1986; Vance, 1995),
this phenomenon was not reected in San Antonio police data as used
here. Though a small number of associations were noted between
lunar phase and various aspects of criminal and disorderly conduct,
this was a common element of prior research and could have been a
probable effect of the large number of associations under consider-
ation (i.e., a spurious nding). A Bonferroni correction to address this
concern could also have been performed to decrease the possibility of
this Type 1 error. The few statistically signicant associations that
were detected and the impact of other variables other than the lunar
phase suggest that such a procedure, while more accurate, would not
substantively impact these ndings or conclusions.
This study relied on CFS, which captured the quantity of reported
incidents, but did not provide robust insights into qualitative aspects
of police encounters involving crime and disorder. CFS were good data
points as they were immune from ofcer discretion, though not call-
taker discretion. It was common, however, for lunar research to focus
on the volume of select forms of behavior, such as violence and
aggression in prisons and psychiatric facilities (Lieber, 1978a, 1978b;
Pettigrew, 1985; Templer & Veleber, 1980; Weiskott & Tipton, 1975)
or calls to crisis centers (Templer & Veleber, 1980; Weiskott, 1974).
This was likely a partial function of convenience; quantitative/volume
indicators of behavior were far more convenient and inexpensive than
Table 3
Multivariate analysis - City Level Analysis
Model Type Trafc Burglary Disturbances Assault Drugs/Vice Theft Aggregated
ARIMA(0,0,8) (OLS) ARIMA(0,0,8) ARIMA(7,0,8) (OLS) (OLS) ARIMA(7,0,8)
B StdError B StdError B StdError B StdError B StdError B StdError B StdError
Sunset 0.009 0.006 0.067* 0.009 -0.008* 0.032 -0.003 0.004 0.007* 0.003 0.002* 0.001 0.050 0.046
Winter -1.738* 0.851 4.116* 1.460 -21.871* 4.701 -2.470* 0.656 -1.318* 0.412 -0.140 0.148 -23.848* 6.703
Weekend 11.372* 0.403 10.361* 0.927 126.698* 2.470 15.410* 0.630 2.719* 0.261 0.602* 0.094 190.794* 4.763
Nightly Temp 0.126* 0.024 0.154* 0.050 1.133* 0.139 0.138* 0.020 0.091* 0.014 0.003 0.005 2.002* 0.187
Precip. 1.008* 0.407 6.510* 1.067 -16.697* 2.282 -1.814* 0.362 -1.569* 0.301 -0.133 0.108 -13.978* 2.835
Lunar Phase 0.102 0.670 1.455* 1.194 2.214 3.633 -0.299 0.472 0.023 .0336 -0.006 0.121 4.083 5.144
Constant -5.031 10.434 -80.994* 16.757 139.067* 57.315 13.385 7.985 -7.638 4.722 -2.772 1.699 88.983 83.023
364 J.A. Schafer et al. / Journal of Criminal Justice 38 (2010) 359367
qualitative indicators, which also suffered from methodological
concerns and limitations.
It is possible that arrest data might be a more accurate repre-
sentation of the quality of calls police handle. Based on this logic,
incidents occurring during times of full moon would be expected
to be more atypical and would result in a greater need for ofcers
to intervene with an arrest. This logic, however, allows for the
introduction of ofcer discretion. Given that lunar effects are
embedded in collective western beliefs (Lieber, 1996; Rotton &
Kelly, 1985; Rotton et al., 1986), affects observed in areas heavily
inuenced by ofcer discretion (such as the decision to arrest, le an
ofcial report, or make referrals) could suffer from social contagion
(Purpura, 1979; Simon, 1998). If ofcers accept that there are lunar
effects (Rotton et al., 1986; Vance, 1995) they may opt for differential
handling of situations based on lunar phase. In effect, the lunar effect
would become a self-fullling prophecy; dependent variables would
be inuenced due to acceptance of the lore, rather than due to actual
citizen/offender behavior. For this reason, the initial classications of
CFS represent a relatively innocuous indicator of situations brought to
the attention of the police, though they are subject to some social
contagion among 911 call takers.
The ndings of this research, rather than conrming a lunar-crime/
disorder relationship, corroborated earlier literature establishing that
crime varied temporally (Cohn, 1996; Heller & Markland, 1970;
LeBeau & Corcoran, 1990; LeBeau & Langworthy, 1986) and due to
weather (Cheatwood, 1995; Cohn, 1990b; Cohn & Rotton, 2000; Hipp
et al., 2004; Quételet, 1842/1969; Rotton & Cohn, 2003). Weekends
and nightly temperature were consistently and positively associated
with aggregated levels of crime, though there was variation based on
specic offense categories. Rates of aggregated crime were much
higher on weekends and were higher during periods of warmer
temperatures. During winter months and periods of greater precip-
itation, crime decreased across the city as a whole and within the non-
entertainment areas. Interestingly, winter and precipitation did not
inuence aggregated crime within the entertainment district.
Substantive lunar effects on crime were not found in the data
analyzed here. If any interpretations regarding the few (and possibly
spurious) relationships were offered, a logical starting point might be
rational choice notions. The mechanisms of inuence are likely a
function of some effects on the availability of suitable targets and the
ability of offenders to escape (or afford) adequate opportunities to
conduct their activities. The limited inuence of lunar phase in the
two instances: (1) citywide burglary (positive relationship found
which might support lunar impacts) and (2) entertainment district
drugs/vice (negative relationship found which may be interpreted to
undermine lunar lore) may be suggestive of such perspectives. On the
whole, however, the data and models examined here were not able
to specify insights or details pertaining to these incidents that would
shed light on this contention. Further scholarly inquiry considering the
choices and decisions of these types of offenders might, for example,
question the role of ambient moon light in shaping offending choices
and behaviors.
That noted, insistent believers in the existence of a lunar effect
may interpret this study differently and offer an alternative
possibility. One could review this study and contend that while this
lunar cycle research failed to nd effects on the volume of crime, the
possibility of effects on the varying character or quality of crimes
reported may remain. More precisely, lunar effects may shape not the
volume of crime encountered by police and other service providers,
but rather alter the nature of problems, individuals, and circum-
stances. As the data used in this study were aggregated and
quantitative, they offered limited insight into these possible aspects
of the nature and character of individual incidents and the motiva-
tions and/or rationales of offenders. For the lunar contention to be
adequately tested and explored further study employing greater
methodological rigor (as this study has employed in examining the
Table 4
Multivariate analysis - Non-Entertainment District Analysis
Model Type Trafc Burglary Disturbances Assault Drugs/Vice Theft Aggregated
ARIMA(0,0,8) (OLS) ARIMA(0,0,8) ARIMA(7,0,8) ARIMA(0,0,14) (OLS) ARIMA(7,0,8)
B StdError B StdError B StdError B StdError B StdError B StdError B StdError
Sunset 0.009 0.005 0.065* 0.009 -0.009 0.030 -0.006 -0.005 0.005 0.003 0.002* 0.001 0.044 0.045
Winter -1.547 0.799 3.956* 1.401 -20.723* 4.515 -2.341* 0.619 -1.076* 0.467 -0.080 0.141 -22.445* 6.519
Weekend 10.39* 0.381 9.878* 0.889 121.390* 2.376 0.351* 0.188 2.997* 0.329 0.462* 0.090 174.976* 5.079
Nightly Temp 0.119* 0.023 0.157* 0.048 1.100* 0.133 8.248* 0.909 0.099* 0.015 0.003 0.005 1.934* 0.180
Precip. 1.053* 0.39 6.149* 1.024 -15.588* 2.197 0.138* 0.019 -1.393* 0.273 -0.157 0.103 -13.147* 2.716
Lunar Phase 0.018 0.628 1.355 1.145 1.970 3.487 -1.684 0.334 0.206 0.295 0.021 0.116 4.018 4.975
Constant -4.848 9.759 -79.468* 16.069 134.465* 55.044 17.015* 8.286 -6.004 5.684 -2.931 1.623 89.851 81.004
Table 5
Multivariate analysis - Entertainment District Analysis
Model Type Trafc Burglary Disturbances Assault Drugs/Vice Theft Aggregated
ARIMA(4,0,7) (OLS) ARIMA(7,0,7) ARIMA(0,0,14) ARIMA(5,0,9) (OLS) ARIMA(7,1,13)
B StdError B StdError B StdError B StdError B StdError B StdError B StdError
Sunset 0.001 0.001 0.002 0.001 0.009 0.009 0.002 0.005 0.001 0.001 0.001 0.001 0.024 0.020
Winter -0.194 0.155 0.160 0.212 -1.038 0.713 -0.244 0.769 -0.202 0.155 -0.125 0.091 -1.636 1.644
Weekend 0.995* 0.078 0.483* 0.134 4.785* 0.578 4.033* 0.288 0.495* 0.065 0.328* 0.058 9.411* 1.223
Nightly Temp 0.004 0.005 -0.003 0.007 0.059* 0.017 0.032 0.019 0.003 0.004 -0.005 0.003 0.137* 0.037
Precip. -0.055 0.081 0.361* 0.155 -1.051* 0.248 -0.228 0.297 -0.093 0.070 0.185* 0.066 -0.776 0.510
Lunar Phase 0.087 0.104 0.099 0.173 .0256 0.328 -0.346 0.561 -0.206* 0.100 -0.119 0.074 -0.280 0.804
Constant -0.858 2.470 -1.526 2.429 -9.690 16.345 -2.819 9.958 -0.614 2.582 -0.646 1.043 -32.233 37.118
365J.A. Schafer et al. / Journal of Criminal Justice 38 (2010) 359367
volume of crime) would be necessary in an effort to examine the
contours of any possible relationship between the quality of crimes
reported and lunar cycles. Only then could this question of the lunar
lore and crime be more fully answered.
1. See Rotton and Cohn (2000) and Cohn (1990b), among others, for a discussion
of theoretical and empirical relationships between weather, temporal variables, social
contact variables, and crime.
2. Block (1984) wrote that although some general seasonal trends could be noted,
they tended to be offense-specic and were not evident in all jurisdictions. Her
comprehensive review of data she analyzed, as well as various published and
unpublished research done by others, found ample variation in seasonal trends. Some
of this might have been attributed to variable data, operational denitions, and
analytical plans.
3. Researchers have employed myriad methods of structuring the timing and
intensity of full moons relative to other periods of the lunar cycle. For example:
contrasting the day of the full moon with all other days in the cycle (Frey et al., 1979);
creating seemingly-capricious windowsof time (i.e., three days) around the full
moon for contrast with the rest of the cycle (sometimes separating out windows of
time around the new moon) (Walters et al., 1975); breaking cycles into equal (Frey et
al., 1979; Quinsey & Varney, 1977; Taylor & Diespecker, 1972) and unequal (Frey et al.,
1979; Lester et al., 1969) periods of times; and, allowing lunar phase to vary from day
to day throughout the lunar cycle (Simon, 1998). The lunar lore is ambiguous
regarding whether the inuence of the moon is truly restricted to full-moon periods
and whether a heightened full moon inuence might be offset by a converse effect
during the new moon.
4. This consideration was another complexity created by the vague nature of the
lunar lore. Was the effect of the full moon mediated by its visibility due to daylight
and/or weather patterns? If the effect was thought to result from the actual intensity
of the moon's illumination, the answer may have been yes.If the effect was thought
to result from the moons pullon water in the human body, the answer might have
been no.
5. An anonymous reviewer pointed out the U.S.N.O. also reports moon rise and
setting times within archival data. It was noted using a sliding window of analysis
based on whether the moon was above the horizon might have been an alternative
approach within the analysis. Additional analyses not reported here, but available from
the lead author upon request, suggest the results were not substantively different with
the use of such a variable window of analysis. The original models (xed 8:00 pm
3:00 am window of analysis) were retained for the analysis reported in this article,
though the alternative scheme was included in later portions of the discussion.
6. The analysis was also conducted using a measure of the moon's actual visibility
above the horizon net of atmospheric conditions that might preclude such visibility.
These models yielded no signicant differences in parameter magnitudes or
signicance levels. Since the same pattern of signicant and non-signicant results
was obtained, the initial results were retained and presented in this article. Those
seeking further information pertaining to these alternative modeling efforts can direct
inquires to the second author.
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... For example, a common fallacy is the suggested relationship between phases of the moon and various forms of atypical behavior, including assaults, homicides, road rage, and theft. The origins of this lore and the specifics related to how the moon influences behavior are not clear, but nonetheless it is not uncommon to hear many individuals publicly, including police officers (e.g., Lieber, 1978;Stolzenberg, D'Alessio, & Flexon, 2017) and mental health professionals (e.g., Schafer, Varano, Jarvis, & Cancino, 2010;Parmar et al., 2014) attribute behaviors considered to be aberrant, criminal, or otherwise atypical to the moon. ...
... With respect to the moon, most lunar-effect studies have failed to replicate positive findings in at least two ways. First, when evaluators have reexamined previously reported data using control comparisons (Drum, Terry, & Hammonds 1986;Schafer et al., 2010), an increased observation window (Kelly & Martens, 1994;Rotton, Kelly, & Frey, 1983), stricter criteria to determine statistical significance (Roy, Biswas, & Roy, 2017), or a combination of these methods (Bickis, Kelly, & Byrnes, 1995;Rotton & Kelly, 1985;Templer, Veleber, & Brooner, 1982), the obtained findings were contradictory to those previously reported (i.e., positive results turned null). Second, when researchers applied these methodological improvements in their own independent investigations, similar failures to replicate were obtained for lunar effects and physical activity (e.g., Parmar et al., 2014), sleep (e.g., Chaput et al., 2016), health (e.g., Roy et al., 2017), aggression (e.g., Simón, 1998), use of hospital and psychiatric services (e.g., Chapman & Morrell, 2000;Walters, Markley, & Tiffany, 1975), incidents of suicide and suicide attempts (e.g., Biermann et al., 2005;Lester, Brockopp, & Priebe, 1969), use of crisis hotlines (Wilson & Tobacyk, 1990), demands for emergency services (e.g., Schafer et al., 2010), road rage (Campbell & Beets, 1978;Laverty & Kelly, 1998), and homicide (Pokorny & Jachimczyk, 1974). ...
... First, when evaluators have reexamined previously reported data using control comparisons (Drum, Terry, & Hammonds 1986;Schafer et al., 2010), an increased observation window (Kelly & Martens, 1994;Rotton, Kelly, & Frey, 1983), stricter criteria to determine statistical significance (Roy, Biswas, & Roy, 2017), or a combination of these methods (Bickis, Kelly, & Byrnes, 1995;Rotton & Kelly, 1985;Templer, Veleber, & Brooner, 1982), the obtained findings were contradictory to those previously reported (i.e., positive results turned null). Second, when researchers applied these methodological improvements in their own independent investigations, similar failures to replicate were obtained for lunar effects and physical activity (e.g., Parmar et al., 2014), sleep (e.g., Chaput et al., 2016), health (e.g., Roy et al., 2017), aggression (e.g., Simón, 1998), use of hospital and psychiatric services (e.g., Chapman & Morrell, 2000;Walters, Markley, & Tiffany, 1975), incidents of suicide and suicide attempts (e.g., Biermann et al., 2005;Lester, Brockopp, & Priebe, 1969), use of crisis hotlines (Wilson & Tobacyk, 1990), demands for emergency services (e.g., Schafer et al., 2010), road rage (Campbell & Beets, 1978;Laverty & Kelly, 1998), and homicide (Pokorny & Jachimczyk, 1974). Thus, many researchers have failed to find a lunar effect, and these researchers have stressed the importance of including comparison samples, appropriate windows for observation, and a careful use of statistics in future investigations. ...
We created an online survey to determine the degree to which 114 participants could correctly identify and categorize scripted visual examples of typical and atypical behavior when the antecedent preceding those behaviors was not present. We also asked participants to determine whether our visual examples of behavior occurred in the presence of a full moon, and subsequently evaluated these data in the context of participant’s self-reported belief in lunar-effects. Our results show the absence of an antecedent event influenced some participants’ identification and categorization accuracy scores, and that participants with a prior belief in lunar effects were more likely to attribute atypical behavior to the presence of a full moon. Future areas for improving measurement in lunar-effects research are discussed.
... The moon has a long history in popular culture as affecting people's propensity towards violence. Within the realm of science, the moon has been studied as a potential influence on a number of factors including crime (Lieber and Sherin 1972;Lieber 1978;Schafer et al. 2010;Stolzenberg, D'Alessio, and Flexon 2017;Thakur and Sharma 1984), violent behavior (Coates, Jehle, and Cottington 1989;Núñez, Méndez, and Aguirre-Jaime 2002;Owen et al. 1998), animal behavior (Bhattacharjee et al. 2000;Chapman and Morrell 2000;Zimecki 2006), suicide (Eisenbach et al. 2008;Mathew et al. 1991;Voracek et al. 2008), and mental illness, (Amaddeo et al. 1997;McLay, Daylo, and Hammer 2006;Raison, Klein, and Steckler 1999;Rotton and Kelly 1985;Wilkinson et al. 1997) with many of these studies finding no effect. ...
... As the effect of ambient light will be strongest during dark hours, this study examines crime occurring between 8:00 pm and 2:59 am, the same hours analyzed by Schafer et al. (2010). 4 5 Crime that occurs between 1:00 am and 2:59 am are included in the crime count for the previous night. ...
... As a result, crimes occurring within that hour are excluded from this study. 5 These hours were used to improve comparability with Schafer et al. (2010), however this introduces some inaccuracies in measuring moonlight as the moon is not always fully risen by 8:00 pm. As this will affect all agencies consistency, the results are unlikely to change when controlling for the precise time of moon rise. ...
Changing the physical design of an area has been long understood to be an effective way to change people's behavior. Within the field of criminology, Crime Prevention Through Environmental Design (CPTED) is an approach that alters the physical environment to decrease opportunities for crime. This dissertation examines two common tools used to reduce opportunities for crime: door locks and outdoor lighting. Though these tools are ubiquitously used, there are limitations in the current research on what effect these tools have on crime. This dissertation uses three papers to extend the CPTED literature by filling in some of these gaps in knowledge. The first paper assesses the effect of installing smart locks on the exterior doors of campus buildings on a major urban university campus. Results show that there is no significant change in the number of crimes per month on buildings that install these locks relative to a comparison group. The second paper measures how the number of outdoor, nighttime crimes change as the amount of moonlight - a relatively dim source of light - changes. Results show that nights with more moonlight have more crime, a finding in contrast to much of the literature on lighting. This suggests that the effects of lighting are non-linear - that a small increase of lighting may increase crime while significant increases in lighting decrease crime. The final paper evaluates one possible mechanism for the bulk of the lighting literature's finding that lighting decreases crime: that more light increases the risk of detection. This study uses the change in evening lighting when the United States transitions to (from) daylight saving time in spring (fall) which causes the evening the gain (lose) an hour of daylight. Results show that when evenings are brighter, the odds of an arrest for violent crimes - and for robbery in particular - significantly increase. Together, these studies advance the field of criminology by providing evidence on the effectiveness of two widely utilized crime control tools - door locks and outdoor lighting - to affect criminal behavior. This contribution can assist both researchers in the CPTED field as well as policy makers who must decide whether - and in which situations - to use door locks or outdoor lighting as crime control measures.
... A study conducted by Joseph A. Schafer et al. (2010) in United State titled 'Bad moon on the rise? Lunar cycles and incidents of crime' and a similar study executed by Teresa Biermann et al (2009) in Germany, titled 'Relationship between lunar phases and serious crimes of battery: a population-based study' also concluded that there is no correlation between the lunar cycle and incidence of crime 6,7 . ...
... Police officers and hospital emergency room personnel have consistently reported an increase in interpersonal violence during a full moon. One study (Lieber, 1978) did, in fact, seem to show a correlation between the moon and homicide rates, although Schafer, Varano, Jarvis, and Cancino (2010) dispute this finding. It has been theorized that since the human body is about 80% water, the moon's influence is similar to the impact it has on tides. ...
... Numerous investigations have been carried out to demonstrate whether or not there really exists a relationship between lunar cycle and erratic behaviour, traffic accidents, hospital admissions, crimes and homicides, suicides and other events and the conclusion in most of these studies has been that there was no scientific evidence for any lunar effect [6][7][8][9][10][11][12][13][14][15][16][17]. In fact, their own study had led Rotton and Kelly [18] to the provocative comment that further research on the topic was unnecessary as there was no thread of evidence to support the idea of a linkage [18]. ...
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Suicide data for this study were available for the period of March 1988 to June 2011, and involved 2111 male and 494 female victims from the Finnish province of Oulu. Data for lunar phases during that period were categorised into three groups: new moon (<25% visible), full moon (>75% visible) and other times with values in between. Seasonal effects were controlled with definitions for winter (Nov, Dec, Jan), spring (Feb, Mar, Apr), summer (May, June, July), and autumn (Aug, Sep, Oct). Suicide occurrences during different lunar phases were compared with their expected distribution using multinomial tests with all tests being two-tailed. Statistical significance was set at p < 0.05. No correlation between suicides and moon phase in any of the four seasons was apparent for male victims, but in winter for women it was (p = 0.001). Further analysis of the data revealed that the full moon association was statistically significant only for premenopausal women, defined as female victims younger than 45 years of age. To explain this unexpected finding a number of factors were considered, e.g., the darkness of a northern Finnish winter with increases of SAD and depression especially in premenopausal women, the influence of the lunar periodicity on the menstrual cycle, and cosmogeophysical effects on the humoral and autonomous nervous system.
... To date, there is an ongoing debate concerning the connection between lunar cycle and psychiatric illness [4,5]. The literature presents conflicting results, with the majority of studies showing no relationship between lunar cycle and either psychiatric admissions or emergency evaluations [6][7][8][9], psychiatric inpatient admissions [10], use of community psychiatry services [11,12], violent behaviour [13][14][15][16][17], suicide [18,19], or sleep disturbances [20,21]. However, some studies do show relationships between the lunar cycle various psychiatric phenomena. ...
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Background: There is an ongoing debate concerning the connection between lunar cycle and psychiatric illness. Aims of the study: The purpose of the present study was to evaluate the rates of admission to and discharge from psychiatric inpatient treatment, as well as the length of stay, in relation to the lunar cycle, including 20 different categories of phases of the moon. Methods: The data of 17,966 cases of people treated in an inpatient setting were analysed. Routine clinical data and data about admission and discharge were used. The lunar calendar was obtained from the website of the US Naval Observatory and was used to calculate the dates of the full moon according to the geographic location of the clinics. The clinics are located in the Canton Grisons in Switzerland. The following phases of the moon throughout the lunar cycle were defined: (a) full moon, (b) quarter waxing moon, (c) new moon, and (d) quarter waning moon. In addition, we coded one day and two days preceding every lunar phase as well as the two days following the respective phases of the moon. Results: The lunar cycles showed no connection with either admission or discharge rates of psychiatric inpatients, nor was there a relationship with the length of stay. Conclusions: Despite the widespread belief that the moon impacts peoples’ mental health and subsequently psychiatric treatment, this study provides no evidence that our celestial neighbour influences our mental well-being.
Background: Trauma patterns in adults are influenced by weather conditions, lunar phases, and time of year. The extent to which these factors contribute to pediatric trauma is unclear. Objective: The present study aimed to review patients from a single Level I pediatric trauma center to determine the influence of weather, the lunar cycle, and time of year on trauma activity. Methods: A retrospective review of trauma activations (n = 1,932) was conducted from 2015 to 2017. Injury type and general demographics were collected. Weather data and lunar cycles were derived from historical databases. Results: Days with no precipitation increased the total number of injuries of all types compared with those with precipitation (p < .001). Blunt and penetrating injuries were more likely to occur during full moons, whereas burn injuries were significantly higher during new moons (p < .001). Blunt trauma was significantly higher in September than all other months, F(11, 1,921) = 4.25, p < .001, whereas January had a significantly higher number of burns than all other months (p < .001). Conclusions: Pediatric trauma trends associated with external factors such as weather, lunar cycles, and time of year can inform hospital staffing decisions in anticipation of likely injuries and help direct injury prevention efforts.
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Objectives: To find the association of ratio of second digit (2D) to fourth digit (4D) lengths (2D:4D ratio) with gender among South Indian medical students. Materials and method: 2D and 4D lengths (right hand) of 316 medical students both male and female from IInd MBBS aged between 18 to 21 years were taken using digital vernier callipers. 2D:4D ratios were calculated by dividing 2D length by 4D length. Results: Statistically significant difference was found between 2D:4D ratios of male and female students. 2D:4D ratio of males was lesser than 2D:4D ratio of females. Conclusion: 2D:4D ratio could be used as a gender determinant in South Indian population as agreed upon by other studies in India.
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Crimes are created by the interactions of potential offenders witb potential targets in settings that make doing tbe crime easy, safe and profitable (see, e.g., Clarke, 1992; Brantingbam and Brantingbam, 1993a and 1993b; Felson, 1994). Eear of crime is created by situations and settings tbat make people feel vulnerable to victimization (see, e.g.. Fisher and Nasar, 1992a and 1992b; Nasar and Eisher, 1992 and 1993; Brantingbam et al., 1995). Tbe urban settings that create crime and fear are human constructions, tbe by-product of tbe environments we build to support the requirements of everyday life: homes and residential neighbourhoods; shops and offices; factories and warehouses; government buildings; parks and recreational sites; sports stadia and theatres; transport systems, bus stops, roadways and parking garages. The ways in which we assemble tbese large building blocks of routine activity into tbe urban backclotb can have enormous impact on our fear levels and on tbe quantities, types and timing of tbe crimes we suffer. Although criminologists bave argued this point in various ways for at least a hundred years (e.g., Eerri, 1896; Burgess, 1916; Shaw and McKay, 1942; Jeffery, 1971; Brantingham and Brantingham, 1993a and 1993b) it is only recently tbat large multipurpose municipal data bases, in conjunction with police information systems, have begun to make it possible to actually explore bow the juxtaposition of land uses and transport networks shapes the backcloth on whicb crime occurs. Tbis paper attempts to set out some of the next steps in understanding the construction of tbe backcloth and its effects on crime. Tbe model that will eventually emerge should provide us with a planning tool tbat will
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Normative, reliability, and validity data for a short (9-item) scale that assesses belief in lunar effects are presented. As hypothesized, scores on this scale were correlated with those on instruments measuring belief in paranormal phenomena. It is suggested that the construct validity of belief in paranormal phenomena can be improved by including this brief scale in research on superstitious behavior.
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Summary.-In this paper the explanations put forward by lunar advocates to account for a "lunar effect" on human behavior are critically appraised. The hypotheses considered are ozone, moonlight, gravity, tidal force, geo- magnetism, electromagnetism, weather, ions, and ELF waves. It is concluded that none of these are sufficient to explain the alleged effects of the moon on human behavior. In view of (a) the lack of a satisfactory mechanism, (b) the lack of a reliable connection between lunar periodicities and human behavior, and (c) the generally negative results obtained in studies, it is suggested that the scientific community exercise great caution with regard to further studies claiming lunar effects on human behavior. Interest
Previous research that related lunar phase to abnormal behavior has led to apparently conflicting findings because of different methodology. The present study, based upon both new data and that already in the literature, combined studies that used the same segments of the synodic cycle. Such analysis indicated a disproportionate frequency of abnormal behavior at the time of the new moon, at the time of the full moon, and in the last half of the lunar phase. These findings were regarded as generally congruent with folklore.
The Belgian polymath Lambert Adolphe Jacques Quetelet (1796-1874) pioneered social statistics. Applying his training in mathematics to the physical and psychological dimensions of individuals, he identified the ‘average man’ as characterised by the mean values of measured variables that follow a normal distribution. He believed that comparing the features of individuals against this average would allow scientists to better explore the processes that determine normal and abnormal qualities. Quetelet's methods influenced many, among them Florence Nightingale, and his simple measure for classifying a person's weight, dividing it by the square of their height, is widely known as the body mass index. First published in French in 1835 and reissued here in the 1842 English translation, this is his most influential work and includes a new preface that succinctly states his aim to be ‘the analysis of normal man through his actions and of intellectual man through his productions’.
In studying the causes of crime, most criminologists have concentrated on traditional socio-demographic variables, such as age, sex, race, and socio-economic status. However, some researchers have investigated the influence of the physical environment on criminal behaviour. There is a recent theoretical basis for research into the influence of weather on crime: the situational approach, rational choice theory, and routine activities theory all suggest that weather could significantly influence crime rates and criminal behaviour. This paper brings together for the first time the accumulated research on weather and crime. It discusses the theoretical background, examines research into the influence of different weather conditions (such as high temperatures, rain, and wind) on various types of criminal behaviour, outlines problems with the current research, and suggests ways of advancing knowledge about weather and crime. © 1990 The Institute for the Study and Treatment of Delinquency.
A series of questions, generated by Rotton and Kelly in response to Cyr and Kalpin's refutation of literature reviews which recommended that attempts to validate the lunar hypothesis be terminated, are addressed. We maintain that it is preferable for researchers to question whether any hypothesis is deemed tenable only after the most advanced methodologies and statistical analyses have been applied rather than to stop all investigations in an area based on results generated by a series of methodologically inconsistent studies which were analyzed inappropriately.
It was hypothesized that police officers and psychiatric professionals would endorse more items indicative of belief in lunar effects than members of the general public. This hypothesis was tested by having 36 psychiatric personnel, 33 police officers, and 60 pedestrians indicate agreement with each of the 9 items on the Belief in Lunar Effects (BILE) scale. Results provided partial confirmation of this hypothesis. Police officers evidenced more belief in lunar effects than either psychiatric personnel or pedestrians, whose degree of belief did not differ.