Panel members were first surveyed with the ConsumerStyles survey. The ConsumerStyles survey, conducted May through June 2005, was sent to a stratified random sample of 20,000 adult panel members (N = approximately 450,000 adults aged 18 or older), which was balanced to help create a nationally representative sample. Low income and minority subgroups (blacks and Hispanics) and households with children were oversampled. The response rates were 65% for the main sample, 59% for the low-income and minority sample, and 62% for households with children.

From July through August 2005, approximately half (n = 6,209) of the panel members who completed the ConsumerStyles survey were followed up with the HealthStyles survey for households without children (n = 3,692) or with both the HealthStyles and YouthStyles surveys (n = 2,517) for households with children. Of the 6,209 panel members who received the follow-up surveys, 4,943 (80%) completed them. The HealthStyles survey was completed by an adult or parent in the household. The YouthStyles survey, mailed in conjunction with the HealthStyles survey, was completed by 1 child in the household. The YouthStyles survey targeted children aged 9 to 18 years and provided linked data between parents and their children. Of the 2,517 households with children that received both the HealthStyles and YouthStyles surveys, 1,685 (67%) completed both surveys. Participants who responded to these surveys were nominally compensated for their participation ($1-5).

Of the 1,685 participants who completed both the HealthStyles and YouthStyles surveys, we excluded those who had missing demographic data (n = 30) and those with missing responses to the questions that asked whether children have a television in their bedroom (n = 210), they are active as a family (n = 18), they allow junk food consumption (n = 5), or they go to fast-food restaurants as a family (n = 10). For the analyses that examined whether the household practices were associated with child or adolescent television watching, physical activity, and dietary behaviors, we excluded participants with missing responses to these questions (n = 232), resulting in an effective sample size of 1,190. The analyses that included BMI percentiles had an effective sample size of 1,050 (missing BMI percentiles, n = 140). The panel members included in the analyses, compared with those excluded for the reasons cited above, had a significantly higher weighted proportion of children aged 9 to 12 (46.8% vs 38.8%), whites (71.7% vs 59.5%), families with higher education (34.6% vs 23.7%), higher income families (39.0% vs 28.0%), more parents aged 35 to 44 (46.2% vs 41.6%), and a higher proportion of families with married parents (84.5% vs 76.3%).

Parents self-reported their age, sex, education, race/ethnicity, marital status, and annual household income. Household practices were assessed with 4 questions. Parents were asked, “Does your child have a television in his/her room?” (yes/no). Using a 5-point response format (strongly agree, agree, neutral, disagree, and strongly disagree), we asked parents to what extent they agreed with the following statements: 1) “I don’t allow my children to eat junk food,” and 2) “We are active as a family.” Responses were recoded into 3 categories (agree/neutral/disagree) for the analyses. Family visits to fast-food restaurants were assessed with the question, “How many days per week do you take your children out to eat at fast-food restaurants, such as . . . ?” Answers ranged from 0 to 7 days.

Age and sex of children and adolescents were reported by their parents. Children self-reported their height and weight, which were used to calculate BMI percentile categories; children with a BMI at or above the 85th percentile and less than the 95th percentile were classified as overweight, and those with a BMI at or above the 95th percentile were classified as obese (19–22). Television-watching time was assessed with 2 questions: “After school, on an average weekday (Monday to Friday) during the school year, how many hours a day do you spend watching television?” and “On an average weekend (both Saturday and Sunday) during the school year, how many hours a weekend do you spend watching television?” For both questions, the responses were 0 hours, less than 1, 1, 2, 3, 4, and 5 or more hours. Eating behavior at school was assessed with the following question: “How many days in a typical week did you buy sodas or other snack foods such as chips, chocolate bars, or cookies from vending machines at school?” Answers ranged from 0 to 5 days. Vigorous physical activity (VPA) was assessed with 1 question: “On how many days of the past 7 days did you exercise or participate in physical activity for at least 20 minutes that made you sweat or breathe hard?” Examples were provided and answers ranged from 0 to 7 days. For the analyses, those who were active at least 3 days were classified as meeting the VPA recommendation, those who were active 1 to 2 days were classified as doing some VPA, and those who reported 0 days were classified as doing no VPA. The television watching and VPA questions were selected from the Youth Risk Behavior Surveillance System (YRBSS) survey; the television questions were modified to ask about television watching behaviors on weekday and weekend days instead of just focusing on an average school day (23). The validity of these questions has been assessed previously with accelerometers (r = 0.36 for the VPA question, r = 0.37 for television watching on weekday, and r = 0.47 for television watching on the weekend) (24,25).

Stata version 11.0 (StataCorp LP, College Station, Texas) was used for all the analyses. All analyses were weighted so that the results would be reflective of US families in terms of race/ethnicity, sex, household size, and income matched to the US Census 2004.

Three multivariate polytomous logistic regressions were performed to examine the associations between household practices and the behaviors of children and adolescents (ie, television watching, participation in physical activity, and purchasing sodas and snacks at school). All the household practices were entered as independent variables because parental practices may be inconsistent across areas (eg, families that provide their child with a television in his or her bedroom may or may not have rules regarding access to less healthful foods). A multivariate polytomous logistic regression was performed to examine associations with self-reported BMI percentile categories; household practices and the behaviors of children and adolescents were entered as independent variables.

For all the analyses, sex and age of the child, race/ethnicity of family, and parent education were entered as covariates. Income was also considered as a covariate; however, education had a stronger association and when both variables were entered, income did not remain significant. A Bonferroni correction was used to control for family-wise error rate. Significance was set at P < .01 (.05/4 hypotheses = .013).

The sample comprised predominantly white families (72%) (Table 1). Less than 50% of children reported 14 or less hours of television watching per week; 72% reported engaging in VPA at least 3 times a week, and 43% purchased sodas and snacks at schools at least once a week. In addition, approximately one-third of parents reported having a college degree, 62% of the children and adolescents had a television in their bedroom, 21% of the families were not active as a family, few families reported having junk food restrictions (13%), and more than 75% of the families went to fast-food restaurants at least once a week.

Black children and adolescents were more likely to watch television than white children and adolescents (OR, 1.90) (Table 2). In addition, children and adolescents watched more television if they had a television in their bedroom (OR = 1.58), were less active as a family (OR = 1.84), and had fewer junk food restrictions at home (OR = 1.83).

None of the demographic variables were associated with VPA at P < .01 (Table 2). Children in less active families participated in about half as much VPA as children in more active families (OR = 0.51 for somewhat active families, and OR = 0.35 for inactive families).

The age of the child was related to purchasing sodas and snacks at school (Table 2). Children aged 13 to 15 were more likely to report purchasing sodas and snacks at school than children aged 9 to 12 (OR = 3.50). In addition, children aged 16 to 18 were more likely to report purchasing sodas and snacks at school than children aged 9 to 12 (OR = 4.07). Race/ethnicity was also related to purchasing behaviors at school. Black (OR = 2.01) and Hispanic children and adolescents (OR = 1.67) were more likely than white children and adolescents to report purchasing sodas and snacks at school. Having a television in the bedroom and eating at fast-food restaurants “as a family” were also related to purchasing behaviors at school. Children and adolescents with a television in their bedroom (OR = 1.49) were more likely to purchase sodas and snacks at school than those without a television. Children whose families went to fast-food restaurants at least once a week were more likely to report purchasing sodas and snacks at school than those who did not go to fast-food restaurants (OR = 1.62 for visiting a fast-food restaurant 1 day per week and OR = 1.67 for 2 or more days per week).

In Model 1 (covariate and behavior variables model), television watching was the only behavior associated with self-reported BMI percentile categories among children and adolescents (Table 3). Those who reported watching more than 21 hours of television per week (OR = 1.72) were more likely to have higher self-reported BMI percentile categories than those who reported watching 14 hours or less of television per week. In Model 2 (covariate and household practice model), being active as a family was the only household practice that was significantly associated with self-reported BMI percentiles. Children and adolescents whose families were less active were more likely to have higher self-reported BMI percentile categories (OR = 2.21) than those who had active families. When the 3 behaviors and the 4 household practices were entered into the model (Model 3), television watching (OR = 1.64) and being active as a family (OR = 2.05) remained significant.