Building Support for Place-Based Solutions to Childhood Obesity: Findings From Missouri

Abstract

Background

Place-based efforts offer promise in reducing childhood obesity. Yet, lack of public demand and support may hinder implementation.

Aims

This study aimed to assess whether the emphasis on place-based solutions, community-wide strategies, and multisector engagement in the Healthy Schools Healthy Communities (HSHC) initiative would shift public views on obesity including the need for greater public involvement and an increase in awareness and support for strategies.

Method

As part of the evaluation, two surveys were conducted—in 2014 and 2016—to examine the relationship between HSHC strategies and changes in public perception, support, and awareness of obesity. Both surveys were cross-sectional and conducted with a randomized sample of households.

Results

Most respondents indicated that parents/family (84.3% in 2014; 87.8% in 2016) and children (70.9% in 2014; 74.8% in 2016) had a large/very large responsibility for addressing childhood obesity. A higher percentage of 2016 respondents indicated willingness to work with others to increase availability of healthy foods (71.3% vs. 64.2%, respectively; p = .0280) and increase the number of places to be physically active in their community (71.1% vs. 60.7%, respectively; p = .0015).

Discussion

Findings suggest awareness and support of place-based efforts and willingness to engage may help garner ongoing support. However, individuals and families are still perceived as primarily responsible for addressing childhood obesity. Countering this mindset remains an ongoing challenge.

Conclusion

Streamlined messaging regarding the issue and associated solutions, enhanced skills and capacity to implement these efforts, and citizen engagement to garner support for place-based initiatives are important.

Keywords

exercise health promotion neighborhood obesity physical activity

Childhood obesity is a major concern across the nation. Data trends underscore the persistent geographic disparity of obesity, with Midwestern and Southern states having the highest rates (Trust for America’s Health, 2017). Associated behaviors, including healthy eating and physical activity, are shaped by many factors including the places children live, learn, and play (Economos & Hammond, 2017). There is growing recognition of the importance of multicomponent initiatives including programs, policies, systems, and environmental (PSE) changes designed to achieve place-based improvements to address obesity (Arteaga et al., 2015; Economos et al., 2007; Taylor et al., 2007). Place-based efforts are increasingly accepted as a more informed and robust way to promote population-level health as the role of the community environment and its influence on decisions and circumstances are taken into account (Cheadle et al., 2018; Hussaini et al., 2018). Yet, lack of public demand and support may hinder implementation, as demonstrated by slow progress in relevant policy arenas (Horton, 2013). As suggested by Horton (2013), the political and organizational will to take such action are often absent in both the public and private sectors and might not emerge without greater public demand.

One significant barrier to action is that obesity and its associated behaviors are commonly viewed as individual issues, whereby parents and children, rather than society, are held accountable (Barry et al., 2012; Berkeley Media Studies Group, 2009). When the public and decision makers hold this view, it can be difficult to garner support for place-based efforts, particularly within ideologically conservative states (Barry et al., 2012). Regulation to promote healthy behaviors can also invoke the threat of “big government,” which contradicts the mainstream rhetoric of personal responsibility. Compared with other interventions that aim to increase physical activity and healthy eating, place-based efforts can be more costly (Khan et al., 2009). While the benefits of such efforts have been demonstrated (Coffield et al., 2015; Coleman et al., 2012; Community Preventive Services Task Force, 2017; Economos et al., 2013), they are often not realized for years and may not be prioritized when resources are limited (Ebbeling et al., 2002). Finally, while opinion leaders and decision makers are the key drivers of policy change, they may lack knowledge, skills, resources, and motivation to implement place-based strategies (Coffman & Beer, 2015).

Public awareness and support for place-based efforts to address childhood obesity can be strengthened by consistent and streamlined messaging regarding the issue and associated solutions, enhanced skills and capacity at the local level to implement efforts, and citizen engagement (Huang et al., 2015). Strategies to increase demand for place-based efforts include redefining obesity as a societal problem, using the media to garner support and change public opinion, raising awareness of solutions, and building capacity among diverse sectors and constituencies (Berkeley Media Studies Group, 2009; Huang et al., 2015).

This study describes the evolution of public opinion on obesity as well as support for and awareness of solutions in communities across Missouri implementing Healthy Schools and Healthy Communities (HSHC), a childhood obesity initiative. It was hypothesized that HSHC’s emphasis on place-based solutions, community-wide strategies, and multisector engagement would shift public views on obesity to be seen as the responsibility of a wider set of actors beyond the individual alone and increase support for and awareness of intervention strategies.

Healthy Schools Healthy Communities

HSHC was launched in 2013 to (a) increase support for place-based changes, (b) engage multisector stakeholders, and (c) enhance skills and capacity to implement efforts. HSHC works at the school district level and districts are supported by a grant funded wellness coordinator (herein referred to as grantee) who develops and organizes committees and provides technical assistance. In addition, community organizations and early childcare centers (also referred to as grantees) receive funding to work in targeted communities. Together, partners develop action plans based on local assessments to increase access to healthy foods and physical activity. Efforts varied by grantee but as of August 2017 included (a) communicating strategies and importance of physical activity and healthy eating (1,257 media activities making an estimated 16,701,466 impressions) and (b) implementing multicomponent initiatives to increase knowledge, enhance skills, or modify access and broader conditions (n = 2,887). Furthermore, all grantees received technical assistance (9,917 hours total) and held meetings (3,962) with an average of 11 key stakeholders in attendance (Table 1). Thirteen school districts in 12 targeted communities were funded in 2013, growing to a total of 33 in 13 communities in 2015. See https://mffh.org/our-focus/childhood-obesity/healthy-schools-healthy-communities/ for more information on HSHC.

Table 1.

Activities Implemented Over the First 4 Years of HSHC.

				Activities and reach, n
Type	Purpose	Examples	Measure	Year 1: 2013–2014	Year 2: 2014–2015	Year 3: 2015–2016	Year 4: 2016–2017	Total
Training and TA	Planning and process assistance to build local capacity	• Webinars • Materials • One-on-one assistance	Hours	1,055	3,342	3,183	2,337	9,917
Meetings	Multipartner meetings to build relationships, leverage resources, and engage partners	• City council meetings • School committee meetings • Coalition meetings	MeetingsAverage attendees/meeting	53010	94014	1,22414	1,26810	3,96211
			MeetingsAverage attendees/meeting	53010	94014	1,22414	1,26810	3,96211
Media and awareness	Efforts to increase familiarity of solutions and strengthen public support	• Newspaper articles• Flyers• Presentations• Social media	ActivitiesPeople reached/impressions^a	88391,610	2462,883,038	4095,835,603	5147,591,215	1,25716,701,466
MCIs	Activities to provide information, enhance skills, and support behavior change or improvements in operations, documents, or infrastructure to increase access, improve places, and ensure sustainability	• Walking/running clubs• Walk-to-school days• Health and wellness fairs• Teachers implement classroom physical activity breaks• Trails used to provide hands-on learning• Joint-use agreements signed• School wellness policies and city/town plans revised• Trails/tracks/sidewalks built• Playground/PE equipment installed	MCIsPeople reached^a	18438,477	684176,922	1,021429,313	998569,330	2,8871,214,042
			MCIsPeople reached^a	18438,477	684176,922	1,021429,313	998569,330	2,8871,214,042

Note. HSHC = Healthy Schools Healthy Communities; MCI = multicomponent initiative.

^aMay not be unique individuals.

Method

As part of the HSHC evaluation, two cross-sectional surveys were conducted—in summer/fall of 2014 and summer/fall 2016—to examine the relationship between implementation strategies and changes in public perception, support, and awareness of obesity. Both surveys were conducted with a randomized sample of households from targeted communities. This study was reviewed and approved by John Snow Inc. Institutional Review Board (OHRP IRB00009069.

Study Sample and Procedures

Sample sizes varied from 2014 (n = 2,000) to 2016 (n = 3,095) to reflect the number of schools and their respective communities throughout the state participating in HSHC at each time point. Marketing Systems Group (https://www.m-s-g.com/Pages/genesys/) provided zip code-based samples proportionate to the community population size. All households who responded in 2014 were resurveyed in 2016 (herein referred to as matched sample). Selected households received a packet with an informational letter and eligibility criteria, the survey, a $2 incentive, and a postage-paid envelope. In an effort to randomize respondents in households with more than one adult, the adult ≥18 years) with the closest upcoming birthday was invited to complete the survey. Four reminders were sent to nonresponders, each mailed approximately 14 days apart. The final reminder offered a chance to participate in a random drawing for a $200 gift card. Households could opt out of the survey and/or request a Spanish version. Data collection for the 2014 survey took place between August and October, and the 2016 survey took place between August and November.

Measures

Views

Respondents were asked (a) who should deal with the obesity problem (individuals, communities, or both); (b) the extent to which 10 entities (e.g., individuals, community/local leaders) had responsibility to address obesity (3-point Likert-type scale where 1 = no/little and 3 = large/very large); (c) whether 11 issues (e.g., too much screen time, availability of unhealthy food, individuals’ lack of desire for behavior change) were a major, minor, or not a reason at all for overweight and obesity; and (d) whether respondents supported (yes/no) 10 strategies to increase opportunities for physical activity and healthy eating (e.g., taxing unhealthy foods and drinks, mandating more physical activity in schools).

Awareness

Respondents were asked (yes/no) whether, over the past year, they had heard of or read about: (a) childhood obesity and (b) a list of 18 HSHC strategies (e.g., healthy retail and Complete Streets initiatives).

Community Engagement

Respondents were asked to state how much they agreed or disagreed (4-point Likert-type scale where 1 = strongly disagree and 4 = strongly agree) about willingness to work with other community members to (a) improve their community, (b) increase the availability of healthy foods, and (c) increase the number of places to be physically active.

Demographics

Respondents reported gender, race/ethnicity, age, education, annual household income, Supplemental Nutrition Assistance Program participation, home ownership, employment status, height and weight, and household composition.

Statistical Analysis

All quantitative data analyses were conducted using SAS 9.4 (SAS Institute Inc., Cary, NC). The main analysis compared 2014 and 2016 data for the unmatched sample. A separate analysis for matched addresses was also conducted. Descriptive analyses were completed to describe respondent/household characteristics, views, awareness, and community engagement. Chi-square and McNemar tests were used to compare differences between responses over the two survey periods for both the unmatched and matched samples, respectively. For tests conducted in matched samples with more than two category survey response options, Bowker’s test of symmetry, an extension of McNemar’s test, was used to compare differences between responses. Findings were considered statistically significant at the p < .05 level. In all instances where results are presented in text comparing 2014 and 2016 study years, rates without p values listed were not statistically significant.

Results

In 2014, among the 1,662 households with valid addresses, 586 surveys were completed (35% response rate). In 2016, among the 2,753 households with valid addresses, 921 surveys were completed (34% response rate). Of the 586 matched households resurveyed in 2016, 248 surveys were completed (42% response rate).

Respondent demographics are presented in Table 2. In summary, most respondents at both survey periods were female, identified as White, and were 45 years or older. More than half of respondents reported an annual household income of less than $40,000 and more than two thirds of respondents self-reported as overweight or obese. Among the unmatched sample, a significantly smaller proportion of respondents in 2016 were Black as compared with 2014 (12.0%, 17.5%, respectively; p = .0169), however, 2016 respondents reported completing college/university and graduate/professional school more frequently than 2014 respondents (19.0% and 11.9% vs. 13.9% and 6.5%, respectively; p = .0063). A significantly larger proportion of respondents in 2016 reported owning/buying their home (compared with renting; 72.0% vs. 63.1%, respectively; p = .0060). Matched survey respondents had similar demographic characteristics as the overall sample and between the two survey periods, although a significantly higher proportion of matched respondents in 2016 were female as compared with 2014 (74.8% vs. 69.1%; p = .0280).

Table 2.

Respondent Characteristics.

	Unmatched sample^†			Matched sample^‡ (N = 248)
Characteristic	2014 (N = 338)	2016 (N = 669)	p value	2014	2016	p value
Gender			^⁞
Male	118 (35.9)	196 (29.9)		71 (30.9)	58 (25.2)
Female	211 (64.1)	460 (70.1)		159 (69.1)	172 (74.8)
Race^a
White/Caucasian	263 (77.8)	554 (82.8)	^⁞	193 (77.8)	190 (76.6)
Black/African American	59 (17.5)	80 (12.0)	^*	39 (15.7)	36 (14.5)
Other	17 (5.0)	27 (4.0)		12 (4.8)	12 (4.8)
Hispanic/Latino	14 (4.6)	18 (2.9)		3 (1.5)	5 (2.5)
Age group
18–24 years	25 (7.6)	51 (7.8)		17 (7.2)	16 (6.8)
25–44 years	82 (24.8)	142 (21.8)		44 (18.6)	43 (18.1)
45–64 years	126 (38.1)	248 (38.2)		91 (38.4)	88 (37.1)
≥65 years	98 (29.6)	209 (32.2)		85 (35.9)	90 (38.0)
Education			^**
Some junior or high school	45 (13.9)	76 (11.7)		16 (7.0)	21 (9.1)
High school graduate	91 (28.1)	140 (21.6)		67 (29.1)	62 (27.0)
Some post–high school education	122 (37.7)	232 (35.8)		82 (35.7)	86 (37.4)
Completed college or university	45 (13.9)	123 (19.0)		45 (19.6)	38 (16.5)
Completed graduate or professional school	21 (6.5)	77 (11.9)		20 (8.7)	23 (10.0)
Annual household income
≤$20,000	100 (31.2)	169 (27.3)		57 (25.6)	57 (25.6)
$20,000–$39,999	76 (23.7)	148 (23.9)		55 (24.7)	53 (23.8)
$40,000–$59,999	52 (16.2)	93 (15.0)		30 (13.5)	37 (16.6)
≥$60,000	39 (12.1)	114 (18.4)		46 (20.6)	44 (19.7)
I would prefer not to say	54 (16.8)	94 (15.2)		35 (15.7)	32 (14.3)
Weight status
Underweight	2 (0.7)	8 (1.3)		5 (2.4)	3 (1.4)
Normal weight	94 (30.6)	160 (26.4)		54 (25.7)	59 (28.1)
Overweight	107 (34.9)	196 (32.3)		75 (35.7)	73 (34.8)
Obese	104 (33.9)	243 (40.0)		76 (36.2)	75 (35.7)
Received SNAP benefits in the past year	72 (22.8)	114 (18.0)	^⁞	38 (17.0)	38 (17.0)
Own/rent home currently living in			^**
Rent	116 (36.9)	162 (28.0)		54 (25.8)	56 (26.8)
Own/buying	198 (63.1)	416 (72.0)		155 (74.2)	153 (73.2)
Employment status			No test			no test
Employed for wages (salary)		146 (24.1)			49 (22.5)
Hourly or self-employed		153 (25.3)			40 (18.3)
Out-of-work/unable to work		77 (12.7)			30 (13.8)
Student/homemaker/retired		229 (37.9)			99 (45.4)
At least 1 child <18 years old	105 (35.1)	168 (34.8)		54 (35.8)	56 (37.1)
Schooling of children <18 years old^a
Preschool/childcare	14 (13.3)	43 (25.6)	^*	12 (20.3)	9 (15.5)
Elementary school	58 (55.2)	71 (42.3)	^*	20 (33.9)	27 (46.6)	^⁞
Middle school/junior high school	32 (30.5)	53 (31.5)		14 (23.7)	13 (22.4)
High school	41 (39.0)	47 (28.0)	^⁞	22 (37.3)	22 (37.9)

Note. Not all respondents provided answers for every question; percentages are based on total item responses. Due to a lack of 2014 data, no statistical tests were conducted for employment status.

Respondents could choose more than one category, therefore categories are not mutually exclusive and add to more than 100%, and significance tests were conducted separately by each group.

†Significance based on chi-square test. ^‡Significance based on McNemar’s test for two-category survey questions and Bowker’s test of symmetry for survey questions with more than two categories. Statistical significance: ^*p < .05. ^**p < .01. ^***p < .001. ^****p < .0001. ^⁞Marginally significant at p < .1. ns = not significant at p ≥ .1.

Views

A smaller (though not statistically significant) proportion of 2016 respondents indicated that obesity was something individuals should manage on their own compared with 2014 (30.0% vs. 35.4%, respectively). Findings were similar among the matched sample such that a lower percentage of respondents felt individuals should deal with obesity on their own in 2016 compared with 2014 (30.0% vs. 36.6%, respectively; not statistically significant). Respondents were asked to rate how important it is that their community be involved in addressing childhood obesity. Although there were no significant differences among the unmatched sample between 2014 and 2016, the matched sample showed a decrease (marginally significant) in the proportion of respondents ranking community involvement as somewhat unimportant or not at all important (20.2% vs. 13.7%, respectively).

Respondents also rated the level of responsibility that different entities bear with respect to childhood obesity prevention. Among the unmatched sample and at both survey periods, most respondents indicated that parents/family (84.3% in 2014; 87.8% in 2016) and individual children (70.9% in 2014; 74.8% in 2016) had a large or very large responsibility for addressing childhood obesity. Entities with the lowest rates of importance in both survey periods were employers (10.0% in 2014; 11.1% in 2016), community/local leaders (13.6% in 2014; 17.3% in 2016), and the federal government (19.4% in 2014; 19.4% in 2016). Among the matched sample, a significantly larger proportion of respondents in 2016 compared with 2014 indicated that they believed that the following groups held large or very large responsibility for addressing childhood obesity: the food industry (increase in of 7.6% in 2016; p = .0244), health insurance companies (increase in of 7.1% in 2016; p = .0269), the federal government (increase in of 9.1% in 2016; p = .0015), the State of Missouri and local governments (increase in of 6.7% in 2016; p = .0265), employers (increase in of 5.4% in 2016; p = .0093), and community/local leaders (increase in of 11.7% in 2016; p < .0001).

Respondents rated their perceptions on the extent to which different factors contribute to overweight and obesity, including both individual and environmental-level reasons (Table 3). Among the unmatched sample and across both survey periods, the top five reasons remained the same—too much screen time (98.9% in 2016; 97.9% in 2014), the availability and inexpensiveness of fast food (95.9% in 2016; 93.1% in 2014), the belief that people do not want to change their behaviors (89.2% in 2016; 91.2% in 2014), the high cost of healthy foods (88.8% in 2016; 88.9% in 2014), and people lack the knowledge of how to control their weight (88.0% in 2016; 86.5% in 2014). Among the matched sample, the same pattern exists, and the increase in the proportion of respondents who perceived the price and availability of fast food as a reason for overweight/obesity was significant (+5.1% in 2016; p = .0027).

Table 3.

Entities Responsible for Maintaining Healthy Weight and Reasons for Overweight/Obesity.

Perceived factors that contribute to overweight and obesity	Unmatched sample^†		Matched sample^‡ (N = 248)
Perceived factors that contribute to overweight and obesity	2014 (N = 338)	2016 (N = 669)	2014	2016
Maintaining a healthy weight is something that
Individuals should deal with on their own	112 (35.4)	182 (30.0)	78 (36.6)	64 (30.0)
Whole communities should deal with	7 (2.2)	12 (2.0)	2 (0.9)	5 (2.3)
Individuals and communities should deal with	197 (62.3)	413 (68.0)	133 (62.4)	144 (67.6)
Importance for community to be involved in addressing childhood obesity				^⁞
Not important or somewhat unimportant	63 (18.9)	112 (17.3)	47 (20.2)	32 (13.7)
Neither important nor unimportant	81 (24.3)	151 (23.4)	49 (21.0)	65 (27.9)
Somewhat important or very important	189 (56.8)	383 (59.3)	137 (58.8)	136 (58.4)
Agreement that the following groups hold very large or large responsibility for addressing childhood obesity
Individual people	236 (70.9)	489 (74.8)	180 (74.7)	169 (70.1)
Parents and other family members	280 (84.3)	578 (87.8)	210 (87.1)	212 (88.0)
Doctors and other health care professionals	147 (44.1)	302 (46.0)	109 (45.4)	124 (51.7)
The food industry	135 (41.0)	273 (41.6)	88 (37.3)	106 (44.9)^*
Schools	133 (40.2)	258 (39.4)	93 (38.4)	99 (40.9)
Health insurance companies	70 (21.3)	146 (22.3)	44 (18.3)	61 (25.4)^*
The federal government	63 (19.4)	127 (19.4)	33 (13.8)	55 (22.9)^**
State of Missouri and local governments	65 (19.7)	139 (21.2)	39 (16.3)	55 (23.0)^*
Employers	33 (10.0)	73 (11.1)	15 (6.3)	28 (11.7)^**
Community/local leaders	45 (13.6)	113 (17.3)	23 (9.6)	51 (21.3)^****
Agreement with reason for overweight/obesity
Individual reasons
Too much screen time	324 (97.9)	652 (98.9)	239 (99.2)	239 (99.2)
People do not want to change	299 (91.2)	581 (89.2)	218 (91.6)	216 (90.8)
People do not know how to control weight	283 (86.5)	570 (88.0)	197 (82.8)	201 (84.5)
People lack information about what is in food	256 (77.6)	529 (81.1)	194 (81.2)	188 (78.7)
People lack time to prepare healthy food	219 (66.6)	455 (69.6)	164 (67.8)	177 (73.1)
People lack time to be physically active	228 (68.7)	454 (69.6)	154 (64.2)	170 (70.8)^⁞
Environmental reasons
Fast food is inexpensive and easy to find	309 (93.1)	629 (95.9)^⁞	219 (92.8)	231 (97.9)^**
Healthy foods are expensive	295 (88.9)	579 (88.8)	206 (86.6)	203 (85.3)
Too much advertising of unhealthy foods/drinks	283 (85.5)	562 (86.1)	197 (83.1)	199 (84.0)
Too much unhealthy foods/drinks in schools	257 (78.6)	534 (82.7)	183 (78.5)	187 (80.3)
Not enough safe places to be physically active	219 (66.2)	418 (64.4)	146 (61.3)	139 (58.4)

Note. Not all respondents provided answers for every question; percentages are based on total item responses.

Support for most strategies to address overweight and obesity remained constant between survey periods (Table 4). However, among the unmatched sample, a greater percentage of 2016 respondents indicated support for increased physical activity requirements in schools as compared with 2014 respondents (90.0% vs. 84.2%, respectively; p = .0091) and providing nutritional guidelines and information to make healthy choices (92.9% vs. 85.9%, respectively; p = .0004). Among the matched sample, these same two strategies also showed significant increases in support between 2014 and 2016 (+8.0% in 2016, p = .0023; +7.8% in 2016, p = .0013, respectively). Additionally, there was a statistically significant increase in the proportion of matched respondents indicating support for requiring healthier school meals (+7.9% in 2016; p = .0023). Strategies with the lowest support among the unmatched sample include placing a tax on the sale of unhealthy foods and drinks (21.3% in 2016; 20.5% in 2014) and limiting the types and amounts of foods and drinks people can buy (9.4% in 2016; 8.7% in 2014). Among the matched sample, these same two strategies had the lowest support among respondents for both years, yet both showed statistically significant increases in support between 2014 and 2016 (taxes: +5.9%, p = .0477; limiting sales: +5.9%; p = .0082).

Table 4.

Percentage of Respondents Indicating Support of Strategies for Addressing Childhood Obesity.

	Unmatched sample^†		Matched sample^‡ (N = 248)
Strategies for addressing childhood obesity	2014 (N = 338)	2016 (N = 669)	2014	2016
Heard of efforts to address childhood obesity in community	101 (31.4)	190 (29.1)	81 (35.7)	62 (27.3)^*
Heard of/read about the following happening in their community in the past year
Designing/operating streets to enable safe access for pedestrians/bicyclists (“Complete Streets”)	22 (6.5)	222 (33.2)^****	11 (4.4)	98 (39.5)^****
Community/school yard gardens	130 (38.5)	209 (31.2)^*	104 (41.9)	70 (28.2)^***
Walk/bike to school/“Safe Routes to School”	85 (25.1)	208 (31.1)^*	52 (21.0)	84 (33.9)^***
Farmers markets/community supported agriculture	169 (50.0)	423 (63.2)^****	156 (62.9)	169 (68.1) ns
Farmers markets accepting vouchers/SNAP/EBT/Double Up Food Bucks	71 (21.0)	111 (16.6)^⁞	44 (17.7)	46 (18.5) ns
Bicycle/pedestrian/park master plans	82 (24.3)	126 (18.8)^*	75 (30.2)	63 (25.4)
Agree or strongly agree with the following statements regarding community engagement
Willing to work together with others on something to improve community	228 (73.5)	503 (78.5)^⁞	164 (78.1)	168 (80.0) ns
Willing to work with others to increase the availability of healthy foods in community	194 (64.2)	453 (71.3)^*	140 (67.6)	154 (74.4)^⁞
Willing to work with others to increase the number of places for physical activity in community	182 (60.7)	450 (71.1)^**	140 (68.6)	145 (71.1) ns
Living in neighborhood gives me a sense of community	191 (65.6)	449 (69.5)	155 (75.6)	152 (74.1) ns
Specific strategy for addressing childhood obesity supported^a
Requiring more physical activity in schools	278 (84.2)	591 (90.0)^**	201 (84.1)	220 (92.1)^**
Providing nutritional guidelines and information about how to make healthy choices	286 (85.9)	615 (92.9)^***	209 (86.4)	228 (94.2)^**
Funding healthy community initiatives (e.g., farmer’s markets, bike paths)	279 (85.1)	557 (84.7)	194 (80.8)	197 (82.1) ns
Providing incentives to the food industry to produce healthier foods	250 (75.8)	489 (74.5)	166 (69.5)	178 (74.5) ns
Requiring restaurants to put calorie information on menus	212 (63.5)	427 (65.0)	160 (66.9)	154 (64.4) ns
Banning advertisements for unhealthy foods aimed at children	171 (51.8)	358 (55.0)	136 (56.7)	143 (59.6) ns
Placing a tax on the sale of unhealthy foods and drinks	68 (20.5)	139 (21.3)	41 (17.3)	55 (23.2)^*
Limiting the types or amounts of foods and drinks people can buy	29 (8.7)	61 (9.4)	20 (8.4)	34 (14.3)^**
Requiring healthier school meals	270 (81.6)	546 (83.0)	187 (77.6)	206 (85.5)^**
Requiring healthier foods/beverages in school vending machines, fundraisers, and celebrations	258 (77.5)	518 (78.8)	190 (78.8)	188 (78.0) ns

Note. Not all respondents provided answers for every question; percentages are based on total item responses. SNAP = Supplemental Nutrition Assistance Program; EBT = electronic benefit transfer.

The 2014 question was phrased as support for “government policies”; the 2016 question phrased as support for “strategies for addressing childhood obesity.”

†Significance based on chi-square test. ^‡Significance based on McNemar’s test. Statistical significance: ^*p < .05. ^**p < .01. ^***p < .001. ^****p < .0001. ^⁞Marginally significant at p < .1. ns = not significant at p ≥ .1.

Awareness

Among the unmatched sample, a smaller (though not statistically significant) proportion of 2016 respondents indicated awareness of efforts to address childhood obesity in their community over the past year compared with 2014 (29.1% vs. 31.4%, respectively). A similar pattern was observed for the matched sample (27.3% vs. 35.7%; p = .0241). Regarding specific efforts to address obesity, a significantly greater proportion of unmatched respondents in 2016 compared with 2014 reported hearing or reading about farmer’s markets/community supported agriculture (63.2% vs. 50.0%, respectively; p < .0001), complete streets (33.2% vs. 6.5%, respectively; p < .0001), and safe routes to school (31.1% vs. 25.1%, respectively; p = .0499). Fewer 2016 respondents than 2014 indicated awareness of community/school gardens (31.2% vs. 38.5%, respectively; p = .0220) and Park Master Plans (18.8% vs. 24.3%, respectively; p = .0446). Similar findings were reported for the matched sample with significantly more matched respondents in 2016 than 2014 reporting awareness of Complete Streets (39.5% vs. 4.4%, respectively; p < .0001) and Safe Routes to School (33.9% vs. 21.0%, respectively; p = .0002) and fewer matched respondents in 2016 than 2014 reporting awareness of community/school gardens compared with 2014 (28.2% vs. 41.9%, respectively; p = .0002).

Community Engagement

A higher percentage of 2016 than 2014 unmatched respondents indicated willingness to work with others to increase availability of healthy foods (71.3% vs. 64.2%, respectively; p = .0280) and to increase the number of places to be physically active in their community (71.1% vs. 60.7%, respectively; p = .0015). Among matched respondents, a noticeably higher (but not significant) percentage of 2016 respondents than 2014 reported willingness to work with others to improve their community (80.0% vs. 78.1%, respectively), work with others to increase the availability of healthy foods (74.4% vs. 67.6%, respectively), and to increase the number of places available to be physically active (71.1% vs. 68.6%, respectively).

Discussion

Community-wide surveys are important to identify and understand public perceptions of obesity and support for and awareness of solutions. Research suggests that support for place-based strategies increases when messages contextualize obesity in broader societal terms rather than just children and parents (Dorfman & Wallack, 2007; Institute of Medicine, 2012). After the 2014 survey, a communications firm was contracted to provide technical assistance to HSHC grantees. Emphasis was placed on shifting messaging away from “childhood obesity” to promoting healthy eating and physical activity. Moreover, as collaborative efforts increased among entities that may not have otherwise been engaged, there was an increase in PSE changes, many of which were visible improvements (e.g., playgrounds). As evidenced by a decrease (though not significant) in the percentage of respondents who believed that obesity was something individuals should deal with alone, results suggest the benefits of shifting messaging around obesity as well as increases in collaborative efforts and PSE changes. However, there is still work to be done given that the majority of respondents believed individuals, parents, and family members still held the greatest responsibility for addressing childhood obesity.

Another indication that HSHC may be contributing to increasing perceptions of social responsibility was the increase in responsibility attributed to various groups for addressing childhood obesity. A greater percentage of matched respondents in 2016 compared with 2014 believed the following groups had a large responsibility, indicating a shift in thinking as regard to obesity: the food industry, health insurance companies, the Federal Government, the State of Missouri and local governments, employers, and community/local leaders. Furthermore, there was also increasing or stable support for various community-level strategies to address obesity among the matched and unmatched samples (e.g., more physical activity in schools, requiring healthier school meals, taxing and limiting sales of unhealthy foods/drinks).

People who conceptualize obesity solely in terms of individual behavior are less likely to support place-based efforts (Niederdeppe & Porticella, 2011; Oliver & Lee, 2005). While respondents continued to attribute obesity to certain individual-level factors, there was a persistent recognition of the impact of the environment on weight status as demonstrated by respondents reporting two of the biggest reasons for obesity as cheap and fast food and the high cost of healthy food. Continued and targeted messaging and interventions underscoring the role of the environment with regard to obesity is needed to change perceptions of responsibility and motivate healthy behaviors that counteract obesity.

Interestingly, while respondents attributed some degree of responsibility to the state and federal government for addressing obesity, strategies with the lowest levels of support were those most often associated with government, including taxing and limiting unhealthy foods and drinks. This is not surprising given perceptions of “big government” are especially pronounced in conservative settings like Missouri (Politico, 2016), where general belief supports personal responsibility and limited government action. Nonetheless, among both matched and unmatched respondents, most strategies framed as “requiring” or “mandating” action had increased support in 2016 compared with 2014, and, a shift whereby a greater percentage of respondents attributed responsibility for overweight/obesity to various groups (e.g., State of Missouri, Federal Government) suggests that perhaps even in conservative states like Missouri, public perception is changing.

Research suggests that emphasizing obesity shifts the focus from a more positive frame of healthful lifestyle and instead evokes discrimination and isolation (Cohen & Steadman, 2005). The term “obesity” may hinder place-based approaches by narrowing the problem, stigmatizing populations, detaching industry, and focusing on the individual (Dorfman & Wallack, 2007). While a smaller proportion of 2016 respondents reported recently hearing or reading about childhood obesity efforts in their community, a greater percentage reported awareness of several HSHC healthy eating and physical activity PSE strategies. This shift from the obesity frame to specific strategies can be viewed as favorable for HSHC communities. Moreover, this study found that the majority of respondents indicated willingness to work together to address healthy eating and physical activity, which is essential as community engagement helps ensure sustainability of interventions and activities and reinforces the message of societal responsibility (Cheezum, 2013).

There are limitations to this study. First, although a random sample strengthens external validity, the influence of nonrespondents is unknown. Nevertheless, a response rate of approximately 35% at both periods for the overall sample is acceptable for a survey of this nature, and a response rate of 42% for the matched sample is strong (Edwards et al., 2002). Second, the communities targeted for HSHC may not be representative of other communities. Third, this was a cross-sectional survey; thus, causal relationships cannot be concluded. Resurveying addresses of 2014 respondents was an attempt to assess individual-level change over time. Identifiable information such as name and birthdate was not collected; therefore, it could not be determined whether the same individual completed surveys at both time points (though this was requested). Fifth, to more accurately reflect the work being done in HSHC communities, the phrasing of select strategies changed from 2014 to 2016 (e.g., “community gardens” changed to “community/school yard gardens”). There is no way to tell whether this change affected respondents’ awareness. Finally, HSHC exists within a broader context of past and concurrent efforts to address childhood obesity. This hinders the ability to directly attribute the reported changes to HSHC as it is impossible to control exposure by creating independent groups. While results from national research showed an increase in the perception of obesity as being a community problem, rural respondents were more likely to view obesity as a personal problem (Obesity Society, 2014). Given that HSHC communities were predominantly rural, these findings support the conclusion that the initiative may have played a role in changing views, awareness and engagement.

Implications for Research and Practice

Place-based efforts to address childhood obesity are beyond any one individual or organization’s ability to influence or control, yet obesity and its associated behaviors are commonly viewed as issues of the individual, whereby parents and children, rather than society, are held accountable. Through this individualistic lens, it can be difficult to garner support for place-based efforts. These findings suggest the importance of streamlined messaging regarding the issue and associated solutions, enhanced skills and capacity to implement these efforts, and citizen engagement to garner support for place-based initiatives. Public health advocates need to reexamine their approach and use of resources to address obesity to ensure efforts include messaging that reinforces societal roles and collective action.

Footnotes

Acknowledgements

The authors wish to express appreciation to Missouri Foundation for Health and GMMB for support with survey development.

Declaration of Conflicting Interests

The authors declared no potential conflicts of interest with respect to the research, authorship, and/or publication of this article.

Funding

The authors disclosed receipt of the following financial support for the research, authorship, and/or publication of this article: The Healthy Schools and Healthy Communities implementation and evaluation was funded by the Missouri Foundation for Health (MFH). However, the analysis and preparation of this article were funded by JSI. Findings and conclusions are those of the authors and do not necessarily represent the official position of MFH.

ORCID iD

Tamara Vehige Calise

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