Promoting Healthier Home Food Environments Through 2-1-1: A… : Family & Community Health


OVER TWO-THIRDS of adults in the United States (US) are overweight or obese, with 39.8{bf9f37f88ebac789d8dc87fbc534dfd7d7e1a7f067143a484fc5af4e53e0d2c5} classified as obese in 2015-2016 and significant disparities by socioeconomic status and race/ethnicity.1–3Nutrition-focused public health efforts to address the obesity epidemic are wide-ranging, but typically focus on increasing access to healthy foods in a range of settings from farmers’ markets to corner stores.4–10 The home environment, while present in ecologic models of obesity, is rarely the target of interventions, particularly for adult obesity or weight gain prevention.11–14 From both theoretical and practical perspectives, home environments may be particularly influential in weight-related behaviors. Social and physical cues can support either healthy or unhealthy eating behaviors.15–17 And, importantly, a significant amount of time is spent at home, and the majority of calories are consumed at home.18–20

Interventions that target the home food environment are typically focused on childhood obesity prevention,21–28 although a few weight-loss interventions have targeted adult home food environments.29,30 Others have used a “small change” approach, which targets simple actions, some of which focus on the home environment (eg, hide snacks in inconvenient place and turn off TV during meals) that participants can take to facilitate healthy eating and lower energy intake.31–33 Healthy Homes/Healthy Families (HH/HF), developed by our team through community-based participatory research,34,35 is one of only a few interventions targeting home food environments for adults and focused on dietary outcomes and weight gain prevention rather than weight loss.12,36–40 While the targeted behaviors of dietary intake and physical activity may be the same in weight gain prevention and weight-loss interventions, there are a few key differences. The prevention of weight gain is essential to maintaining a healthy weight for most adults. In contrast, weight loss is relevant once excess weight is gained and sustaining weight loss over time is very difficult. Additionally, small and easily sustained changes in eating behavior may be sufficient to prevent weight gain.

The purpose of the current study was twofold: (1) to adapt the research-tested HH/HF intervention from home and telephone-based delivery to telephone and text messages, and (2) to test the feasibility and acceptability of delivering it to 2-1-1 clients. A nationally designated 3-digit telephone exchange, 2-1-1 provides extensive reach to populations who are disproportionately low-income, unemployed, uninsured, and have fewer years of education relative to the general population.41 Given the relatively high prevalence of overweight and obesity among socially disadvantaged populations,3 it is important to develop intervention strategies in collaboration with systems that have the potential to reach populations at risk.


Description of the original intervention and adaptations made for 2-1-1 collaboration

The original intervention, HH/HF was delivered through 3 home visits and 4 coaching calls over 16 weeks. The goal was to prevent weight gain by decreasing energy intake and increasing physical activity. Core elements were informed by Social Cognitive Theory and the Social Ecological model42,43 and include a tailored home environment profile, goal-setting, and behavioral contracting for healthy actions.34,35 Healthy actions, in this case simple steps that people can take to change their environment, were supported by associations with dietary quality, physical activity, or body mass index (BMI) reported in the literature.15,44–47 For example, studies show that healthier home food inventories are associated with better diets.48–51 Related healthy actions include: (1) Identify one unhealthy food or drink and do not allow it in the home, (2) always have a low-calorie beverage available instead of sugar soda and/or sweet tea, and (3) purchase fresh fruits and vegetables at least once a week, and make them easy to see and grab.

Baseline data on the home food and activity environment were used to generate a tailored home environment profile showing areas in need of improvement (eg, too many high-fat/salty snacks) and positive aspects of the home environment (eg, family has rules to limit screen time). Coaches hired locally, with social service or customer service experience, guided participants in choosing 6 healthy actions over the course of the intervention, based on baseline data presented via the tailored home environment profile. The chosen healthy actions were recorded on a family contract. Participants received supportive materials via mail (eg, portion size plate and family exercise log) that matched the selected healthy actions, along with positive reinforcement from the coach for steps taken and suggestions for overcoming challenges. Tested in collaboration with 3 federally qualified health centers, the intervention was effective in preventing weight gain, reducing energy intake, improving dietary quality, and changing numerous dimensions of the home environment. Significant changes occurred for food inventories (ie, unhealthy snacks and unhealthy drinks), frequency of purchasing fruits and vegetables, food preparation methods, food serving practices, eating in front of the TV, and family meals from non-home food sources. The intervention was not successful in changing physical activity levels, despite some success in changing the home activity environment (eg, making physical activity equipment visible). Participants (n = 349) in the original efficacy trial were women, ages 35 to 65 years, and lived with at least one other person.

Major adaptation for collaboration with 2-1-1 included elimination of the physical activity component of the intervention, changing from a blended home visit and telephone delivery to telephone and text messages, reducing the intervention from 16 to 12 weeks, dropping the mailed materials that supported each selected healthy action, and broadening eligibility criteria to include normal weight adults, a much wider age range, men, and people who lived alone. Following guidelines for adaptation,52 additional refinements for collaborating with 2-1-1 were informed through formative interviews with 5 line agents and 16 2-1-1 clients, as well as input from a Steering Committee with representatives from a food bank, state and local health departments, Supplemental Nutrition Assistance Program Education (SNAP Ed), cooperative extension, and United Way of Greater Atlanta 2-1-1. Core elements of the intervention remained the same; changes included language in the healthy actions (eg, changing purchase to obtain), expanding the list of barriers to address in the text messages, and resources that coaches could share with participants (eg, list of farmers markets).

Pilot study design

The pilot study, conducted from February 2017 to February 2018, used a 1-arm design with data collection at baseline and 1 month postintervention (ie, 4 months postbaseline). In addition, we conducted postintervention qualitative interviews with participants who had varying levels of engagement with the intervention. The primary role of 2-1-1, in addition to serving on the Steering Committee, was to recruit participants. Eligibility criteria were age 18 to 70 years, able to speak English, and a BMI (kg/m2) of 20 or greater. The study protocol was approved by the Emory University Institutional Review Board. Participants received a $30 gift card for baseline and another $30 gift card for follow-up data collection.

Unlike in the original intervention in which the first intervention contact was in-person, participants were mailed a welcome letter from their assigned coach, along with their tailored home environment profile, stickers with the healthy actions, the healthy action checklist, and a family contract. Over 12 weeks, 12 contacts were made, alternating between coaching calls and text messages. Coaches were masters-level Emory staff with counseling degrees. As in the original intervention, the first coaching contact involved reviewing the home environment profile and guiding participants through a process of selecting one healthy action to prioritize. Text messages focused on anticipated and actual barriers to implementing the healthy action. New healthy actions were added in calls 3 and 5 for a total of 3 healthy actions focusing on improving the home food environment, with calls 2, 4, and 6 focused on reinforcing and problem-solving to address challenges.


The 2 primary outcomes, energy intake and diet quality as measured through the USDA Healthy Eating Index (HEI)-2015,53 were assessed through 2 telephone 24-hour recalls (1 weekday and 1 weekend day) at baseline and again at 4 months. All diet recalls were collected, processed, and analyzed using the most recent version of the Automated Self-administered 24-hour Recall.54

Household food inventory was assessed by asking which of 50 food and drink items were in the home in the past week.48,49,55Food placement was assessed with a 3-item measure that asks whether or not fruit and vegetable and high-calorie snacks are placed in easy or hard-to-reach places in the home (yes/no).49 Frequency of fruit and vegetable shopping was assessed by asking, in the past month, when grocery shopping, how often did you or someone in your household buy [vegetables/fruit], with response options of (1 = less than once per week, 2 = once per week, and 3 = more than once per week). Meal preparation and serving practices were assessed by asking how often each of 18 meal preparation and/or serving methods was done in the past month, with response options of 1 = never/rarely to 4 = very often.56,57Frequency of non-home food sources was assessed by asking about the number of days in the past week that family meals were purchased from 4 types of restaurants (ie, fast food, full service or sit-down, take-out, and delivery).58Family TV and eating patterns were assessed with 3 items asking how often meals and snacks are eaten in front of the TV (1 = never/rarely to 4 = very often).57 We used 1 item to assess whether there was a TV in the room where meals are eaten.57 We also asked about presence of a scale and frequency of self-monitoring weight.

Participant satisfaction measures were included in the follow-up survey and covered interaction with the materials (yes/no), for signing the contract, posting the contract, etc, along with assessments of the coach, coaching calls, and text messages.

We assessed sociodemographic characteristics of participants, along with food security, depression, and stress. Food security was assessed by the US Household Food Security Survey Module,59 depression was assessed by the Patient Health Questionnaire-2,60 and stress by the Perceived Stress Scale 4.61 Process evaluation questions were from our prior work with 2-1-162 and our intervention trial for HH/HF.35 The postintervention qualitative interviews (n = 12) asked about intervention delivery and materials, data collection procedures, and potential sustainability of their healthy actions.

Data analysis

After removing 1 person from the analyses due to homelessness (Figure), we conducted descriptive analyses for all variables of interest, calculating means, standard deviations, and frequencies. We conducted bivariate analyses, comparing those who were reached for follow-up data collection to those who were not, on baseline sociodemographic characteristics using independent t test and χ2 tests. For the intervention impact analysis, we conducted paired t tests for all continuous and Likert scale variables and McNemar’s test for presence of a TV in the dining room (yes/no). All analyses were conducted in SAS 9.4 with α set at .05. Qualitative analysis of the follow-up interviews involved content analysis of the written interview summaries, with results stratified by level of engagement with the program (0-3 coaching calls vs 4-6 coaching calls).


Flow diagram of study participation.


Feasibility of recruiting from 2-1-1

The Figure summarizes recruitment, enrollment, and retention of study participants through the 4-month pilot study. Community connection specialists from 2-1-1 conducted an initial screening of 341 callers. Based on interest and initial eligibility, they provided 261 names with contact information to Emory study staff for potential enrollment in the study. Of these, 54.8{bf9f37f88ebac789d8dc87fbc534dfd7d7e1a7f067143a484fc5af4e53e0d2c5} (n = 143) were assessed for eligibility and consented by Emory staff. Participants who completed all parts of the data collection were then enrolled in the study (n = 101).

Description of study participants enrolled and retained through follow-up

Table 1 describes sociodemographic characteristics of study participants and compares those retained through follow-up to those lost to follow-up. Participants were predominantly women (75{bf9f37f88ebac789d8dc87fbc534dfd7d7e1a7f067143a484fc5af4e53e0d2c5}) and African American (82{bf9f37f88ebac789d8dc87fbc534dfd7d7e1a7f067143a484fc5af4e53e0d2c5}), with a relatively high proportion unemployed (48{bf9f37f88ebac789d8dc87fbc534dfd7d7e1a7f067143a484fc5af4e53e0d2c5}). Mean age was 43.7 years, and all participants reported an annual household income less than $25000. Less than half of the households included a child (45{bf9f37f88ebac789d8dc87fbc534dfd7d7e1a7f067143a484fc5af4e53e0d2c5}), and the vast majority were food insecure (84{bf9f37f88ebac789d8dc87fbc534dfd7d7e1a7f067143a484fc5af4e53e0d2c5}). Major depressive symptoms and stress levels were reported by 34{bf9f37f88ebac789d8dc87fbc534dfd7d7e1a7f067143a484fc5af4e53e0d2c5} and 84{bf9f37f88ebac789d8dc87fbc534dfd7d7e1a7f067143a484fc5af4e53e0d2c5} of participants at baseline, respectively. Those not reached for follow-up were younger with larger households.

TABLE 1. -
Description of Study Population and Comparison Between Those Reached and Not Reached for Follow-up

Characteristic All (n = 100) Reached for FUP (n = 61) Not Reached for FUP (n = 39)
P Value
n/Mean ({bf9f37f88ebac789d8dc87fbc534dfd7d7e1a7f067143a484fc5af4e53e0d2c5})/SD n/Mean ({bf9f37f88ebac789d8dc87fbc534dfd7d7e1a7f067143a484fc5af4e53e0d2c5})/SD n/Mean ({bf9f37f88ebac789d8dc87fbc534dfd7d7e1a7f067143a484fc5af4e53e0d2c5})/SD
Age 43.7 12.5 45.8 11.9 40.4 12.90 .04
Female 75 75.0 47 77.1 28 71.8 .70
Male 24 24.0 14 22.9 10 25.6
Prefer not to answer 1 1.0 0 0 1 2.6
White 8 8.0 7 11.5 1 2.6 .26
African American/black 82 82.0 48 78.7 34 87.2
Other 9 9.0 5 8.2 4 10.3
Prefer not to answer 1 1.0 1 1.6 0 0
Unemployed 48 48.0 32 52.5 16 41.0 .50
Full time 29 29.0 18 29.5 11 28.2
Part time 15 15.0 7 11.5 8 20.5
Retired 8 8.0 4 6.6 4 10.3
8th grade or less 1 1.0 0 0 1 2.6 .15
Some high school 9 9.0 7 11.5 2 5.1
High school or GED certificate 22 22.0 10 16.4 12 30.8
Some college/technical school 49 49.0 30 49.2 19 48.7
College graduate 14 14.0 9 14.8 5 12.8
Postgraduate/professional degree 5 5.0 5 8.2 0 0
≤$10000 28 28.0 17 27.9 11 28.2 .75
$10001 to $15000 33 33.0 19 31.2 14 35.9
$15001 to $20000 29 29.0 20 32.8 9 23.1
$20001 to $25000 4 4.0 2 3.3 2 5.1
>$25000 0 0 0 0 0
Prefer not to answer 5 5.0 2 3.3 3 7.7
Don’t know/Refused 1 1.0 1 1.6 0 0
Marital status
Not married 46 46.0 25 41.0 21 53.9 .46
Married 17 17.0 10 16.4 7 18.0
Divorced 14 14.0 12 19.7 2 5.1
Not married, but living with partner 9 9.0 5 8.2 4 10.3
Separated 8 8.0 5 8.2 3 7.7
Widowed 6 6.0 4 6.6 2 5.1
Household size 2.8 1.70 2.5 1.48 3.3 1.93 .03
Children in the household
Yes 45 45.0 23 37.7 17 43.6 .07
No 55 55.0 38 62.3 22 56.4
Public assistance (multiple answers possible)
SNAP 44 44.0 26 42.6 18 46.2 .73
Medicaid 32 32.0 16 26.2 16 41.0 .12
Disability, unemployment, child support/alimony 28 28.0 16 26.2 12 30.8 .62
Medicare 16 16.0 8 13.1 8 20.5 .33
Other 8 8.0 5 8.2 3 7.7 .93
TANF 3 3.0 2 3.3 1 2.6 .84
Major depressive symptoms (yes) 34 34.3 23 37.7 11 29.0 .37
Food insecure (yes) 84 84.0 51 83.6 33 84.6 .89
Stress (range 1-16) 6.7 3.80 6.7 3.85 6.6 3.77 .91

Abbreviations: GED, General Educational Development; SNAP, Supplemental Nutrition Assistance Program; TANF, Temporary Assistance for Needy Families.

Description of home food environments and food practices (not shown)

Baseline participants (n = 100) reported an average of 4.4 of 13 types of fruit and 9.3 of 17 types of vegetables in the home in the past 7 days. Apples, oranges, bananas, onions, peas/beans/green beans, potatoes (not French fries), and corn were most common. Of the less healthy foods assessed, 73{bf9f37f88ebac789d8dc87fbc534dfd7d7e1a7f067143a484fc5af4e53e0d2c5} of respondents had bacon/sausage, 70{bf9f37f88ebac789d8dc87fbc534dfd7d7e1a7f067143a484fc5af4e53e0d2c5} had cookies/cakes, and 64{bf9f37f88ebac789d8dc87fbc534dfd7d7e1a7f067143a484fc5af4e53e0d2c5} had regular potato chips in the home. Additionally, 63{bf9f37f88ebac789d8dc87fbc534dfd7d7e1a7f067143a484fc5af4e53e0d2c5} had sugared drinks other than soft drinks in the home, 50{bf9f37f88ebac789d8dc87fbc534dfd7d7e1a7f067143a484fc5af4e53e0d2c5} had regular soft drinks, and 74{bf9f37f88ebac789d8dc87fbc534dfd7d7e1a7f067143a484fc5af4e53e0d2c5} had regular or 2{bf9f37f88ebac789d8dc87fbc534dfd7d7e1a7f067143a484fc5af4e53e0d2c5} milk in the home. Less than half owned a scale (46{bf9f37f88ebac789d8dc87fbc534dfd7d7e1a7f067143a484fc5af4e53e0d2c5}), with 77{bf9f37f88ebac789d8dc87fbc534dfd7d7e1a7f067143a484fc5af4e53e0d2c5} reporting access to a scale to weigh themselves.

The majority of participants shopped for fruit (52{bf9f37f88ebac789d8dc87fbc534dfd7d7e1a7f067143a484fc5af4e53e0d2c5}) and vegetables (41{bf9f37f88ebac789d8dc87fbc534dfd7d7e1a7f067143a484fc5af4e53e0d2c5}) less than once per week. Fast food was served for family meals an average of 1.5 times per week, take out/delivery 0.6 times per week, and households went to sit down restaurants 0.5 times per week. Healthy meal preparation practices occurred occasionally (mean score of 2.3).

Changes in self-reported weight, diet quality, and home food environments

Table 2 shows changes from baseline to follow-up among those with data at both time points (n = 61). As noted earlier, the pilot study was not powered to detect postintervention changes, but rather to provide information on feasibility and potential effect sizes for a larger trial. Among the weight and diet quality measures, all improved in the direction intended, with BMI, weight, caloric intake, and percent energy from fat all decreasing, and fruit and vegetable intake and the HEI-2015 increasing. Only the HEI-2015 was significantly improved (P = .02).

TABLE 2. -
Changes in Weight, Dietary, and Home Food Environment Outcomes From Baseline to Follow-upa

n Baseline Mean (SD) Follow-up Mean (SD) Difference Meanb (SD)
P Valuec
Health and behavioral outcomes
BMI, kg/m2 60 32.8 (8.59) 32.2 (8.91) −0.6 (3.66) .23
Weight, lb 60 199.9 (54.93) 195.9 (54.29) −4.0 (19.79) .12
Energy intake, kcal/d 60 1810.6 (841.28) 1607.2 (769.67) −203.4 (953.00) .10
kcal from fat, {bf9f37f88ebac789d8dc87fbc534dfd7d7e1a7f067143a484fc5af4e53e0d2c5} 60 35.2 (7.21) 33.9 (7.51) −1.3 (8.67) .25
F&V intake (servings/d) 60 2.4 (2.43) 2.7 (1.97) 0.3 (2.27) .37
Healthy Eating Index-2015 60 54.0 (10.30) 58.0 (11.97) 4.0 (13.56) .02

Home environment
Home food inventories
Fruit (of 13) 61 4.1 (2.71) 5.5 (2.47) 1.3 (2.95) .001
Vegetables (of 17) 61 8.5 (3.69) 9.7 (3.10) 1.2 (3.71) .02
Healthy snacks (of 5) 61 1.4 (0.98) 1.3 (0.98) −0.2 (0.93) .10
Unhealthy snacks/foods (of 8) 61 4.2 (2.02) 2.8 (1.94) −1.5 (2.10) <.0001
Healthy drinks (of 4) 61 1.4 (0.88) 1.2 (0.97) −0.3 (1.16) .10
Unhealthy drinks (of 3) 61 1.7 (0.97) 1.5 (0.94) −0.2 (1.15) .12
Food practices
Shopping frequency for vegetables 61 1.8 (0.84) 2.0 (0.81) 0.2 (0.95) .11b
Shopping frequency for fruit 61 1.7 (0.84) 2.0 (0.82) 0.3 (0.92) .01b
Healthy food preparation 61 2.2 (0.48) 2.3 (0.44) 0.1 (0.48) .05
Healthy food serving 61 2.0 (0.73) 2.2 (0.75) 0.2 (0.79) .03
Family meal from non-home source, past 7 d 61 2.7 (3.42) 1.6 (2.13) −1.2 (3.56) .02
Eating meals with TV on 61 2.8 (1.18) 1.8 (0.96) −1.0 (1.20) <.0001
Snacking in front of TV 61 2.7 (1.14) 1.8 (0.88) −0.9 (1.19) <.0001

n ({bf9f37f88ebac789d8dc87fbc534dfd7d7e1a7f067143a484fc5af4e53e0d2c5})

n ({bf9f37f88ebac789d8dc87fbc534dfd7d7e1a7f067143a484fc5af4e53e0d2c5})

n ({bf9f37f88ebac789d8dc87fbc534dfd7d7e1a7f067143a484fc5af4e53e0d2c5})

TV in dining room (yes) 61 34 (55.7) 22 (36.1) −12 (19.6) .01
Weighing practices
Weighing yourself 61 1.2 (0.56) 1.5 (0.74) 0.3 (0.86) .01b

Abbreviations: BMI, body mass index; F&V, fruit and vegetable.

aWeight and BMI: One person excluded due to unrealistic weight reduction.

bRounding error for some pre-/postdifferences.

cP values are from paired t tests and are congruent with P values from Wilcoxon signed rank tests.

The majority of home food environment measures improved significantly, in the direction expected, including fruit and vegetable home food inventories (P = .001 and P = .02, respectively), unhealthy snacks (P < .0001), fruit shopping (P = .01), healthy food preparation (P = .05) and serving (P = .03), family meals from non-home sources (P = .02), eating with the TV on (P < .0001), TV location (P = .01), and weighing practices (P = .01). The largest changes occurred for home food inventories (ie, fruit, vegetable, and unhealthy snacks at home), non-home food sources for family meals, and eating with the TV on.

Intervention delivery and dose

While the majority (73.3{bf9f37f88ebac789d8dc87fbc534dfd7d7e1a7f067143a484fc5af4e53e0d2c5}) completed the first coaching call, 27 participants did not. Coaching call completion or “dose” data are reported in the Figure. Approximately 38{bf9f37f88ebac789d8dc87fbc534dfd7d7e1a7f067143a484fc5af4e53e0d2c5} (n = 38) completed the full intervention (all 6 coaching calls), with a majority completing at least 3 calls. As noted in the Figure, there was a substantive drop after the second coaching call.

The coaching calls varied in length, with coaching call 1 the longest (mean of 33.5 minutes), followed by coaching call 3 (21.9 minutes) and coaching call 5 (19.0 minutes). These were the calls that involved adding healthy actions. Coaching calls 2, 4, and 6 ranged from 10.5 to 14.8 minutes on average.

Of the 8 healthy actions (Table 3), the most commonly selected by far was to identify one unhealthy food or drink and not allow it in the home (77.0{bf9f37f88ebac789d8dc87fbc534dfd7d7e1a7f067143a484fc5af4e53e0d2c5}). Establishing rules that limit eating while watching TV was also selected frequently (45.9{bf9f37f88ebac789d8dc87fbc534dfd7d7e1a7f067143a484fc5af4e53e0d2c5}). The 2 least common healthy actions were (1) bringing home fresh fruits and vegetables at least once a week (18.0{bf9f37f88ebac789d8dc87fbc534dfd7d7e1a7f067143a484fc5af4e53e0d2c5}), and making them easy to see and grab, and (2) cutting back on how often your family eats fast food or restaurant food (18.0{bf9f37f88ebac789d8dc87fbc534dfd7d7e1a7f067143a484fc5af4e53e0d2c5}).

TABLE 3. -
Process Evaluation Results (n = 61)

Process Measure {bf9f37f88ebac789d8dc87fbc534dfd7d7e1a7f067143a484fc5af4e53e0d2c5} or Mean (SD)
Healthy actions selected (yes), {bf9f37f88ebac789d8dc87fbc534dfd7d7e1a7f067143a484fc5af4e53e0d2c5}
Identify one unhealthy food or drink and do not allow it in the home 77.0
Establish rules that limit eating while watching TV 45.9
Use healthier methods to cook vegetables, meat, and/or fish 32.8
Reduce portion sizes and avoid second helpings 31.1
Place a scale in a visible location to weigh in weekly 29.5
Always have a low-calorie beverage available instead of sugar soda and/or sweet tea 26.2
Bring home fresh fruits and vegetables at least once a week, and make them easy to see and grab 18.0
Cut back on how often your family eats fast food or restaurant food 18.0
Interaction with materials (yes), {bf9f37f88ebac789d8dc87fbc534dfd7d7e1a7f067143a484fc5af4e53e0d2c5}
Looked at most/all of the materials 90.2
Sign the contract 82.8
Post the contract 51.7
Use the stickers 84.5
Assessment of the coach, mean (SD)
Easy to understand 3.9 (0.38)
A good motivator 3.9 (0.24)
Spent the right amount of time with you 3.9 (0.27)
Assessment of the coaching calls, mean (SD)
Interesting 3.9 (0.35)
Helpful 4.0 (0.20)
Relevant 3.8 (0.52)
Related to you personally 3.7 (0.65)
Information was useful 3.9 (0.31)
Satisfaction 4.0 (0.28)
Assessment of the text messages, mean (SD)
Helpful 3.8 (0.58)
Relevant 3.8 (0.50)
Motivating 3.7 (0.57)
Assessment of the support materials, mean (SD)
Helpful 3.9 (0.35)
Motivating 3.8 (0.37)

Participant perspectives

At follow-up, participants provided feedback on their coach, the coaching calls, the text messages, and the support materials. Opinions were very positive, with participants viewing various components of the intervention as very helpful, relevant, and motivating. Over 80{bf9f37f88ebac789d8dc87fbc534dfd7d7e1a7f067143a484fc5af4e53e0d2c5} of participants signed the contract and used the stickers, while fewer (51.7{bf9f37f88ebac789d8dc87fbc534dfd7d7e1a7f067143a484fc5af4e53e0d2c5}) posted the contract. There was no consensus on preferred length of the intervention among those participating in the qualitative interviews. The number of calls was viewed as appropriate by most, but challenges with scheduling were commonly mentioned. All participants described at least 1 healthy action they planned to continue. The baseline and follow-up surveys were viewed as lengthy, and $50 was commonly suggested as an appropriate incentive for participation rather than the offered $30.


This study evaluated the feasibility and potential impact of shortening and simplifying the HH/HF intervention and delivering it to 2-1-1 clients. This shortened version of the HH/HF intervention was able to promote numerous changes in the home food environment. Each aspect of the home environment targeted by the intervention changed in the expected direction except for availability of healthy snacks and healthy drinks, with many of these changes statistically significant despite the small sample size. The largest and perhaps most notable changes were decreases in eating out, increased inventories of fruits and vegetables, removal of the TV from the dining area, and reductions in eating with the TV on (both snacks and meals). The more intensive intervention, with in-home visits, resulted in similar changes to most aspects of the home food environment.35 Of note, dietary quality also improved significantly despite the small sample size, energy consumption and weight-related outcomes, were in the desired direction, and effect sizes were consistent with the original intervention trial.

As mentioned, most home environment interventions are within the context of childhood obesity prevention and generally target just a few dimensions of the home environment, along with individual-level knowledge and skills related to healthy eating and/or physical activity.21–23,28 Additionally, these interventions are generally longer and include group sessions, which may limit reach and generalizability to households willing and able to participate in group sessions for an extended period. Results have been mixed in these more intensive interventions.21–23,28 A study by French et al26 most closely parallels HH/HF. At 12 months, the intervention was effective in promoting physical activity and self-weighing, and it reduced TV viewing, snacks/sweets intake, and dollars per person spent eating out; however, no significant intervention effects were observed for BMI among children or adults.

The few interventions focused on home environments and targeting adults had weight loss as opposed to weight gain prevention as the primary outcome. Gorin et al29 documented weight loss and environmental change at 6 months in an enhanced home environment intervention relative to a standard behavioral weight-loss program, but differences between intervention and control were mostly absent at 18 months, and no differences in energy intake were observed at either time point. The intervention was weekly for 6 months, and bimonthly for 12 months. Participants were asked to restrict TV viewing, change their household food inventory, grocery shop online, and they were provided with cues for healthy food choices. The intervention involved similar strategies for physical activity.

“Small changes,” such as the healthy actions, may be easier to sustain than individual dietary changes. To date, small change interventions have focused on weight loss rather than weight gain prevention.32,33 The Veterans Affairs (VA) tested a weight-loss program in which goal setting was personalized, and while not focused on the home environment and much more intensive than HH/HF, participants were encouraged to identify external cues and develop plans to manage them. The 1-year results were noteworthy, with participants in the small changes intervention achieving double the weight loss of participants in the comparison arm.32 However, contrary to expectations, the differential weight loss was not maintained at 24 months.33

Of note, none of the adult or child-focused interventions had an exclusive emphasis on the home environment. It is possible that an intervention, such as HH/HF with an explicit focus on the home environment (eg, tailored profiles, goal setting, reinforcement, and problem-solving specific to the environment), may be easier for families to implement and sustain than interventions that focus simultaneously on knowledge, skills, and environment.

Our study has a number of limitations. By design, we had no comparison group so it is difficult to attribute the observed changes solely to the intervention. However, consistency with our prior research strengthens the likelihood that the changes were related to the intervention. Social desirability bias may be a factor, as participants knew what home environment features the intervention was targeting and all measures were self-reported.

The next step in this line of research is to conduct a hybrid effectiveness-implementation trial with 4 2-1-1 agencies and 12-month follow-up. We will more rigorously assess whether this shorter and telephone-based version of the program is effective and we will also learn about how best to integrate a prevention program such as HH/HF into an infrastructure with deep reach into populations that are often challenging for public health to engage.


1. Hales CM, Carroll MD, Fryar CD, Ogden CL. Prevalence of obesity among adults and youth: United States, 2015-2016. NCHS Data Brief. 2017;(288):1–8.

2. Hales CM, Fryar CD, Carroll MD, Freedman DS, Ogden CL. Trends in obesity and severe obesity prevalence in US youth and adults by sex and age, 2007-2008 to 2015-2016. JAMA. 2018;319(16):1723–1725.

3. Ogden CL, Fakhouri TH, Carroll MD, et al. Prevalence of obesity among adults, by household income and education—United States, 2011-2014. MMWR Morb Mortal Wkly Rep. 2017;66(50):1369–1373.

4. Adam A, Jensen JD. What is the effectiveness of obesity related interventions at retail grocery stores and supermarkets? A systematic review. BMC Public Health. 2016;16(1):1247.

5. Gittelsohn J, Trude ACB, Kim H. Pricing strategies to encourage availability, purchase, and consumption of healthy foods and beverages: a systematic review. Prev Chronic Dis. 2017;14:E107.

6. Woodruff RC, Raskind IG, Harris DM, et al. The dietary impact of introducing new retailers of fruits and vegetables into a community: results from a systematic review. Public Health Nutr. 2018;21(5):981–991.

7. Khan LK, Sobush K, Keener D, et al. Recommended community strategies and measurements to prevent obesity in the United States. MMWR Recomm Rep. 2009;58(Rr-7):1–26.

8. Liberato SC, Bailie R, Brimblecombe J. Nutrition interventions at point-of-sale to encourage healthier food purchasing: a systematic review. BMC Public Health. 2014;14:919.

9. Centers for Disease Control and Prevention. CDC’s Division of Nutrition, Physical Activity, and Obesity’s Implementation Guide for the Notice of Funding Opportunity. Racial and Ethnic Approaches to Community Health Programs. Atlanta, GA: Centers for Disease Control and Prevention; 2018.

10. United States Department of Agriculture. Supplemental Nutrition Assistance Program Education. FY 19 SNAP Ed Plan Guidance. Washington DC: US Department of Agriculture; 2018.

11. Hutfless S, Gudzune KA, Maruthur N, et al. Strategies to prevent weight gain in adults: a systematic review. Am J Prev Med. 2013;45(6):e41–e51.

12. Lombard CB, Deeks AA, Teede HJ. A systematic review of interventions aimed at the prevention of weight gain in adults. Public Health Nutr. 2009;12(11):2236–2246.

13. Peirson L, Douketis J, Ciliska D, Fitzpatrick-Lewis D, Ali MU, Raina P. Prevention of overweight and obesity in adult populations: a systematic review. CMAJ Open. 2014;2(4):E268–E272.

14. Hayba N, Partridge SR, Nour MM, Grech A, Allman Farinelli M. Effectiveness of lifestyle interventions for preventing harmful weight gain among young adults from lower socioeconomic status and ethnically diverse backgrounds: a systematic review. Obes Rev. 2018;19(3):333–346.

15. Kegler MC, Alcantara I, Haardorfer R, Gazmararian JA, Ballard D, Sabbs D. The influence of home food environments on eating behaviors of overweight and obese women. J Nutr Educ Behav. 2014;46(3):188–196.

16. Rosenkranz RR, Dzewaltowski DA. Model of the home food environment pertaining to childhood obesity. Nutr Rev. 2008;66(3):123–140.

17. Wickrama KA, Ralston PA, O’Neal CW, et al. Life dissatisfaction and eating behaviors among older African Americans: the protective role of social support. J Nutr Health Aging. 2012;16(9):749–753.

18. Lin BH, Guthrie J. Nutritional Quality of Food Prepared at Home and Away From Home, 1977-2008. Washington, DC: US Department of Agriculture, Economic Research Service; 2012.

19. US Bureau of Labor Statistics. Average hours per day spent in selected activities by sex and day. Published 2018. Accessed July 5, 2019.

20. Eldridge JD, Devine CM, Wethington E, et al. Environmental influences on small eating behavior change to promote weight loss among Black and Hispanic populations. Appetite. 2016;96:129–137.

21. Fulkerson JA, Friend S, Flattum C, et al. Promoting healthful family meals to prevent obesity: HOME Plus, a randomized controlled trial. Int J Behav Nutr Phys Act. 2015;12:154.

22. Fulkerson JA, Friend S, Horning M, et al. Family home food environment and nutrition-related parent and child personal and behavioral outcomes of the Healthy Home Offerings via the Mealtime Environment (HOME) Plus Program: a randomized controlled trial. J Acad Nutr Diet. 2018;118(2):240–251.

23. Byrd-Bredbenner C, Martin-Biggers J, Povis GA, Worobey J, Hongu N, Quick V. Promoting healthy home environments and lifestyles in families with preschool children: HomeStyles, a randomized controlled trial. Contemp Clin Trials. 2018;64:139–151.

24. Haire-Joshu D, Schwarz CD, Steger-May K, et al. A randomized trial of weight change in a national home visiting program. Am J Prev Med. 2018;54(3):341–351.

25. Tabak RG, Morshed AB, Schwarz CD, Haire-Joshu D. Impact of a healthy weight intervention embedded within a national home visiting program on the home food environment. Front Public Health. 2018;6:178.

26. French SA, Gerlach AF, Mitchell NR, Hannan PJ, Welsh EM. Household obesity prevention: Take Action—a group-randomized trial. Obesity. 2011;19(10):2082–2088.

27. Haines J, McDonald J, O’Brien A, et al. Healthy Habits, Happy Homes: randomized trial to improve household routines for obesity prevention among preschool-aged children. JAMA Pediatrics. 2013;167(11):1072–1079.

28. Boles RE, Yun L, Hambidge SJ, Davidson A. Influencing the home food and activity environment of families of preschool children receiving home-based treatment for obesity. Clin Pediatr. 2015;54(14):1387–1390.

29. Gorin AA, Raynor HA, Fava J, et al. Randomized controlled trial of a comprehensive home environment-focused weight-loss program for adults. Health Psychol. 2013;32(2):128–137.

30. Butryn ML, Forman EM, Lowe MR, Gorin AA, Zhang F, Schaumberg K. Efficacy of environmental and acceptance-based enhancements to behavioral weight loss treatment: the ENACT trial. Obesity. 2017;25(5):866–872.

31. Phillips EG, Wells MT, Winston G, et al. Innovative approaches to weight loss in a high-risk population: the Small Changes and Lasting Effects (SCALE) trial. Obesity (Silver Spring). 2017;25(5):833–841.

32. Damschroder LJ, Lutes LD, Kirsh S, et al. Small-changes obesity treatment among veterans: 12-month outcomes. Am J Prev Med. 2014;47(5):541–553.

33. Lutes LD, Damschroder LJ, Masheb R, et al. Behavioral treatment for veterans with obesity: 24-month weight outcomes from the ASPIRE-VA small changes randomized trial. J Gen Intern Med. 2017;32(suppl 1):40–47.

34. Kegler MC, Alcantara I, Veluswamy JK, Haardorfer R, Hotz JA, Glanz K. Results from an intervention to improve rural home food and physical activity environments. Prog Community Health Partnersh. 2012;6(3):265–277.

35. Kegler MC, Haardorfer R, Alcantara IC, et al. Impact of improving home environments on energy intake and physical activity: a randomized controlled trial. Am J Public Health. 2016;106(1):143–152.

36. Hutchesson MJ, Hulst J, Collins CE. Weight management interventions targeting young women: a systematic review. J Acad Nutr Diet. 2013;113(6):795–802.

37. Hebden L, Chey T, Allman-Farinelli M. Lifestyle intervention for preventing weight gain in young adults: a systematic review and meta-analysis of RCTs. Obes Rev. 2012;13(8):692–710.

38. Lemmens VE, Oenema A, Klepp KI, Henriksen HB, Brug J. A systematic review of the evidence regarding efficacy of obesity prevention interventions among adults. Obes Rev. 2008;9(5):446–455.

39. Brown T, Avenell A, Edmunds LD, et al. Systematic review of long-term lifestyle interventions to prevent weight gain and morbidity in adults. Obes Rev. 2009;10(6):627–638.

40. Gudzune KA, Lau BD, Hutfless S, Boult C, Segal JB. AHRQ Future Research Needs Papers. In: Strategies to Prevent Weight Gain in Adults: Future Research Needs: Identification of Future Research Needs From Comparative Effectiveness Review No. 97. Rockville, MD: Agency for Healthcare Research and Quality; 2013.

41. Kreuter MW. Reach, effectiveness, and connections: the case for partnering with 2-1-1 to eliminate health disparities. Am J Prev Med. 2012;43(6, suppl 5):S420–S421.

42. Bandura A. Social Foundations of Thought and Action: A Social Cognitive Theory. Englewood Cliffs, NJ: Prentice Hall; 1986.

43. McLeroy KR, Bibeau D, Steckler A, Glanz K. An ecological perspective on health promotion programs. Health Educ Q. 1988;15(4):351–377.

44. Pinard CA, Yaroch AL, Hart MH, Serrano EL, McFerren MM, Estabrooks PA. Measures of the home environment related to childhood obesity: a systematic review. Public Health Nutr. 2012;15(1):97–109.

45. Couch SC, Glanz K, Zhou C, Sallis JF, Saelens BE. Home food environment in relation to children’s diet quality and weight status. J Acad Nutr Diet. 2014;114(10):1569–1579.e1561.

46. Jackson JA, Smit E, Branscum A, et al. The family home environment, food insecurity, and body mass in Index in rural children. Health Educ Behav. 2017;44(4):648–657.

47. Bates CR, Buscemi J, Nicholson LM, Cory M, Jagpal A, Bohnert AM. Links between the organization of the family home environment and child obesity: a systematic review. Obes Rev. 2018;19(5):716–727.

48. Patterson RE, Kristal AR, Shannon J, Hunt JR, White E. Using a brief household food inventory as an environmental indicator of individual dietary practices. Am J Public Health. 1997;87(2):272–275.

49. Gattshall ML, Shoup JA, Marshall JA, Crane LA, Estabrooks PA. Validation of a survey instrument to assess home environments for physical activity and healthy eating in overweight children. Int J Behav Nutr Phys Act. 2008;5:3.

50. Hermstad A, Swan D, Kegler M, Barnette J, Glanz K. Individual and environmental correlates of dietary fat intake in rural communities: a structural equation model analysis. Soc Sci Med. 2010;71:93–101.

51. Larson N, Laska M, Story M, Neumark-Sztainer D. Predictors of fruit and vegetable intake in young adulthood. J Acad Nutri Diet. 2012;112(8):1216–1222.

52. Escoffery C, Lebow-Skelley E, Udelson H, et al. A scoping study of frameworks for adapting public health evidence-based interventions. Transl Behav Med. 2019;9(1):1–10.

53. Reedy J, Lerman JL, Krebs-Smith SM, et al. Evaluation of the Healthy Eating Index-2015. Acad Nutr Diet. 2018;118(9):1622–1633.

54. Subar AF, Kirkpatrick SI, Mittl B, et al. The Automated Self-Administered 24-hour dietary recall (ASA24): a resource for researchers, clinicians, and educators from the National Cancer Institute. J Acad Nutr Diet. 2012;112(8):1134–1137.

55. Glanz K, Sallis JF, Saelens BE, Frank LD. Nutrition Environment Measures Survey in stores (NEMS-S): development and evaluation. Am J Prev Med. 2007;32(4):282–289.

56. Kristal AR, Shattuck AL, Patterson RE. Differences in fat-related dietary patterns between black, Hispanic and White women: results from the Women’s Health Trial Feasibility Study in Minority Populations. Public Health Nutr. 1999;2(3):253–262.

57. Spurrier NJ, Magarey AA, Golley R, Curnow F, Sawyer MG. Relationships between the home environment and physical activity and dietary patterns of preschool children: a cross-sectional study. Int J Behav Nutr Phys Act. 2008;5:31.

58. Fulkerson JA, Story M, Neumark-Sztainer D, Rydell S. Family meals: perceptions of benefits and challenges among parents of 8- to 10-year-old children. J Am Diet Assoc. 2008;108(4):706–709.

59. Economic Research Service. Household Food Security Survey Module: Three-Stage Design, with Screeners. Washington, DC: US Department of Agriculture; 2012.

60. Kroenke K, Spitzer RL, Williams JB. The Patient Health Questionnaire-2: validity of a two-item depression screener. Med Care. 2003;41(11):1284–1292.

61. Cohen S, Kamarck T, Mermelstein R. A global measure of perceived stress. J Health Soc Behav. 1983;24(4):385–396.

62. Escoffery C, Bundy L, Haardoerfer R, et al. A process evaluation of an intervention to promote home smoking bans among low income households. Eval Program Plann. 2016;55:120–125.

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