Food Protection Trends - January/February 2020 - 20

effects. For discrete characteristics, the estimated average
marginal effect is the average of the difference between two
predicted probabilities: the probability that each at-home
meal preparer in the sample affirms the discrete characteristic
and the probability that each at-home meal preparer in the
sample does not affirm the discrete characteristic. These
average marginal effects were estimated using factor variables
in Stata® as recommended by Williams (28).
To understand the determinants of food thermometer
use, this study initially examined the impacts of various
socio-demographic variables for at-home meal preparers
and characteristics describing their household. Specifically,
the set of at-home meal preparer characteristics includes
an indicator for male or female; an indicator for married or
not married; an indicator for age under 35 or 35 and older;
an indicator for Hispanic or non-Hispanic; an education
indicator for at least a bachelor's degree versus at most
some college; and an indicator for being employed or not
working, meaning unemployed or not in the labor force.
The household characteristics consisted of household size,
household location, and household income. Specifically, the
total number of people in the household; an indicator for a
household located in the Midwest, since Lando and Chen
(14) found that food thermometer ownership was highest
in the Midwest, and an indicator for a household with a total
income above 185% of the federal poverty line, adjusted for
household size. Year indicators are included to control for
possible trends in thermometer use: an indicator for 2015
versus 2014 and an indicator for 2016 versus 2014.
Next, this study examined whether an at-home meal
preparer's time use for primary eating, shopping, or meal
preparation during an average day affected food thermometer
use. Specifically, time-use variables were added to the
regressions that controlled for the demographic variables.
The variables added included an indicator if an at-home
meal preparer used a grocery store for the majority of food
shopping needs. This study also included indicators for an
at-home meal preparer who spends over 30 minutes on food
shopping during an average day, an indicator for spending
over 90 minutes on eating during an average day, and an
indicator for spending over 120 minutes on food preparation
and cleaning during an average day.
This study also examined whether health characteristics
of at-home meal preparers, the number of at-risk household
members, and food insufficiency affected food thermometer
use. Specifically, this study added health-status, at-risk, and
food-insufficiency variables to the regression that already
controlled for at-home meal preparer demographics and
household characteristics. For health status, this study
included an indicator for at-home meal preparers who rank
their physical health as poor. To examine at-risk populations,
this study tested whether the presence of children in the
household affected food thermometer use by including an
indicator for the presence of at least one child, as well as

Food Protection Trends January/February

whether the presence of a household member (other than
the at-home meal preparer), over the age of 62 affected food
thermometer use. To examine the food environment, this
study tested whether a lack of food in the household in the
past 30 days affected food thermometer use.
Last, since some workers in the food industry have received
formal food safety training or work with someone who has
received it, this study examined whether working in a food-service related job influenced food safety practices at home.
Specifically, this study categorized at-home meal preparers
according to the industries and occupations most relevant to
food preparation that are available in the ATUS-EHM: leisure
and hospitality, accommodation and food service, and food
preparation and serving.
RESULTS
Population-weighted statistics
Descriptive statistics calculated from ATUS for at-home
meal preparers are shown in Table 1. From 2014 to 2016, 14%
of at-home meal preparers were Hispanic, 35% were male,
52% were married, and 45% were between the ages of 35 and
59. For formal education attainment, 39% of at-home meal
preparers had at most a high school diploma, 27% had at most
an associate's degree, and 34% had at least a bachelor's degree.
For general employment status, 3% were unemployed, 37%
were not in the labor force, and 60% were employed. The average household size was 2.6 people. For household geographic
location, 24% of at-home meal preparers were located in the
Midwest. Based on pre-tax income, 63% of surveyed at-home
meal preparers had a household income level that exceeded
185% of the federal poverty level, corrected for household size.
When food shopping, 69% of at-home meal preparers primarily used grocery stores, 28% mainly used super centers or
warehouse clubs and 3% primarily used drug, convenience or
other stores. For physical health, 4% of at-home meal preparers
self-rated their physical health as poor. For other household
members, 33% of at-home meal preparers lived with at least
one child, and 19% lived with a person age 62 or older. For the
food environment, 94% of at-home meal preparers had enough
to eat while 6% sometimes or often did not have enough to eat.
During an average week, 14% of at-home meal preparers used food thermometers. Descriptively analyzing the
same data, Rhodes et al. (18) found that at-home meal
preparers who used food thermometers earn more than
non-users, report better physical health, are more likely
married, and have larger households compared with those
who did not use food thermometers. They also found
that at-home thermometer use was statistically higher for
at-home meal preparers working in food service industries
or occupations. Specifically, thermometer use at home was
18%, 20%, and 24% for meal preparers who worked in the
leisure and hospitality industry, accommodation and food
service industry, or food preparation and serving occupations, respectively (18).

Food Protection Trends - January/February 2020

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