Assessment 40604

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Health Promotion Plan: Adult Obesity in a Columbus, Ohio Community Group

September ,2026

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Health Promotion Plan: Adult Obesity in a Columbus, Ohio Community Group

Adult obesity remains a leading community health concern because it increases chronic

disease risk and reduces quality of life (Office of Disease Prevention and Health Promotion

[ODPHP], n.d.-a). This hypothetical plan describes a 60-minute face-to-face session for

community-dwelling working-age adults in Columbus, Ohio. The plan examines the issue, finds

a vulnerable population, maps social factors, and establishes collaborative SMART objectives to

be achieved in the subsequent educational session.

Analysis of the Health Concern

Adults with a body mass index (BMI) of 30 kg/m² or higher are classified as having

obesity (Emmerich et al., 2024). Obesity increases the risk of type 2 diabetes, cardiovascular

disease, stroke, some types of cancer, and decreased quality of life (ODPHP, n.d.-a). Healthy

People 2030 goal NWS-03 targets to decrease adult obesity to 36.0% (ODPHP, n.d.-b). The most

recent age-adjusted estimate is 40.2% in 2021-2023, and the change is not significant (ODPHP,

n.d.-b). August 2021 to August 2023 National Health and Nutrition Examination Survey data

show 40.3% of adults with obesity, 46.4% of adults ages 40–59, and 9.4% with severe obesity

(Emmerich et al., 2024).

The maps of the 2024 Behavioral Risk Factor Surveillance System indicate that all

reporting states are at 25% or more (Centers for Disease Control and Prevention [CDC], 2025).

The Midwest leads at 35.9%, and Ohio remains at or above 35% (CDC, 2025). In most states,

Black and Hispanic adults have a higher rate of obesity compared to White and Asian adults and

decreases with education (CDC, 2025). Clinicians are supposed to provide or make referrals to

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adults with a BMI of 30 and above to intensive, multicomponent behavioral interventions (U.S.

Preventive Services Task Force [USPSTF], 2018). These programs result in an average weight

loss of 1.56 kg among lower-income adults, with the greatest weight loss due to incentives and

feedback (Li et al., 2024).

This plan assumes attendees are contemplating change, will report usual intake and

activity honestly, and will accept four-week follow-up. It assumes beverages, walking, and

home-food changes can start without medication. Uncertainty remains: BMI imperfectly marks

risk across groups, stigma can reduce attendance, and shift work plus food cost limit what one

hour can change. Expected outcomes are skills and a first supported attempt, not a large

immediate BMI drop.

Target Population, Scenario, and Predisposing Factors

The session is a 60-minute evening class at the Linden Community Recreation Center in

Columbus, Ohio. After recruiting them by use of flyers, church bulletins, and two local work

sites, eight community-dwelling adults will be invited. None of them reside in a hospital, assisted

living, nursing home, or other institution.

The sample consists of five females and three males aged 36-56 years. There are four

non-Hispanic Black, two non-Hispanic White, and two Hispanic. Six evening or rotating shifts in

warehousing, food service, or retail. Education ranges from a high school diploma to some

college, and income is about $32,000–$54,000. Five have school-going children. It covers both

Medicaid and high-deductible plans. BMI values range from 31 to 39. Daily sodas, late takeout,

and fewer than 60 minutes of planned activity per week are common.

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Tanya R. is a 47-year-old married non-Hispanic Black warehouse associate and mother

of two who earns about $41,000. Her last BMI was 34.8 kg/m². Fasting glucose last year was in

the prediabetes range, and her mother has type 2 diabetes. She does not eat breakfast, consumes a

few sodas during working days, orders carryout most evenings, and has never maintained a food

diary.

This group is predisposed to obesity because rates peak in midlife and among adults

without a bachelor’s degree (Emmerich et al., 2024). In most states that report, obesity is at 35%

or more prevalent in Black adults (CDC, 2025). The adult rate is higher than the NWS-03 target

in Ohio (CDC, 2025). Healthy habits and intensive treatment are limited by shift work, low

access to evening groceries, the density of carryout, caregiving, and high deductibles (USPSTF,

2018). A recreation center class can access those workers who do not visit a primary-care weight

visit frequently.

Sociogram Considerations and Learning Needs

A sociogram will map ties that sustain energy-dense eating and inactivity and ties that

could support change. Respondents will identify who they will eat with, who would not welcome

change, and who would assist them in walking, cooking, or avoiding sugary beverages. Arrows

will indicate influence to enable the nurse to recognize stars, isolates, and the work-versus-home

split.

Some of the risk ties are overtime to dinner, colleagues who share carryout, children who

like packaged foods, local soda stores, and family members who consider second helpings as a

sign of hospitality. Family history includes Tanya’s mother with diabetes. Protective

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relationships consist of a walking spouse, a teen who is ready to pack lunches, the center

coordinator, and a primary-care nurse.

Participants know excess weight raises diabetes risk but cannot explain BMI categories or

the 5%–7% prevention threshold (ODPHP, n.d.-a). They have not been practicing label reading

and step goals and are unaware that there are local track hours and Diabetes Prevention Program

cohorts. The session will educate on energy balance, compare carryout with packed lunch,

practice a brief walk, finish the sociogram, and establish a single collaborative goal.

Current Behaviors, Session Expectations, and Collaborative SMART Goals

The current behaviors are daily sodas, frequent carryout, missed breakfast, minimal

planned activity, and no log. The expectations include full attendance, truthful reporting,

sociogram work, one teach-back, and at least one personal goal. Supports include plain-language

visuals, a lunch comparison, a short track walk, printed logs, and a two-minute private goal talk.

Agreed-upon goals matter because change lasts longer when participants help define

success (MacLeod, 2012). MacLeod suggests specific, measurable, achievable, relevant, and

time-bound objectives, which are also engaging and rewarding. The cooperation between the

desire to cook at home and the fear of rejected food or lost time of walking appears. Shared goals

are the evaluation criteria for Assessment 4. Working with Tanya and the group produced the

following SMART goals. By the end of the 60-minute session, each participant will state their

current BMI category and list three personal triggers with one realistic substitute for each, shown

on a worksheet and confirmed by teach-back.

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1. Within seven days, at least six of eight participants will complete a three-day food-and-

step log and identify one 30-minute walking block on four workdays, confirmed by

follow-up contact.

2. Within four weeks, each participant will replace sugar-sweetened beverages on at least

five days each week and accumulate at least 150 minutes of moderate activity or 8,000

steps on at least four days each week or will record a barrier and a revised plan.

These goals follow assessment, counseling, skill practice, and self-monitoring (USPSTF,

2018). They remain realistic because similar behavioral programs produce modest, measurable

change (Li et al., 2024). The same goals will be used to evaluate the later educational session.

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References

Centers for Disease Control and Prevention. (2025). Adult obesity prevalence maps. U.S.

Department of Health and Human Services. https://www.cdc.gov/obesity/data-and-

statistics/adult-obesity-prevalence-maps.html

Emmerich, S. D., Fryar, C. D., Stierman, B., & Ogden, C. L. (2024). Obesity and severe obesity

prevalence in adults: United States, August 2021–August 2023 (NCHS Data Brief No.

508). National Center for Health Statistics. https://doi.org/10.15620/cdc/159281

Li, P., Huang, Y., & Wong, A. (2024). Behavioural strategies to reduce obesity among lower

socio-economic adults living in high-income countries: A Grades of Recommendation,

Assessment, Development and Evaluation-assessed systematic review and meta-analysis

of randomised controlled trials. British Journal of Nutrition, 131(3), 544–552.

https://doi.org/10.1017/S0007114523001940

MacLeod, L. (2012). Making SMART goals smarter. Physician Executive, 38(2), 68–72.

Office of Disease Prevention and Health Promotion. (n.d.-a). Overweight and obesity. Healthy

People 2030. U.S. Department of Health and Human Services.

https://odphp.health.gov/healthypeople/objectives-and-data/browse-

objectives/overweight-and-obesity

Office of Disease Prevention and Health Promotion. (n.d.-b). Reduce the proportion of adults

with obesity (NWS-03). Healthy People 2030. U.S. Department of Health and Human

Services. https://odphp.health.gov/healthypeople/objectives-and-data/browse-

objectives/overweight-and-obesity/reduce-proportion-adults-obesity-nws-03

U.S. Preventive Services Task Force. (2018). Behavioral weight loss interventions to prevent

obesity-related morbidity and mortality in adults: US Preventive Services Task Force

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recommendation statement. JAMA, 320(11), 1163–1171.

https://doi.org/10.1001/jama.2018.13022