Obesity in Low-Income Communities

Abstract

The relationship between income levels and obesity is complex. Obesity has historically been a disease in affluent countries. Hence it is thought that greater wealth brings greater obesity. However, data suggested overall obesity prevalence decreased with increased levels of income. This observation proved that obesity as a disease is complex and not a simple calorie-in and calorie-out equation. Low socioeconomic communities suffer from inequalities and health disparities that we need to amend by reforming our healthcare delivery system. We will discuss why obesity is a problem in low-income communities and what preventive and treatment strategies we would need to implement to combat this.

1. Introduction

The prevalence of obesity has increased over time [1]. It is now a major public health risk factor that has been linked to several non-communicable diseases such as diabetes, hypertension, cardiovascular disease, obstructive sleep apnea, etc. [1]. It has also been related to increased all-cause mortality and reduced quality of life [1]. To better understand obesity, several studies and research have been ongoing looking at correlations. Epidemiological research depicting the relationship with the socioeconomic status of the community has been ongoing and several hypotheses have been laid out [1]. Socioeconomic status includes the household income level as well as their level of education [2]. The relationship between income levels and obesity is complex [2]. We reviewed current and previous literature depicting this relationship with a thorough web search of journal articles, books, and statistical data from national surveys. These included any articles that appeared on the search criteria including low income and obesity.

The pattern of relation was noted to vary between high-income and low-income countries [1, 2]. In low-income countries, it has been noted to be a disease of the rich [2]. Hence, a thought that greater wealth brings greater obesity [3]. The relationship, however, did not stay the same in medium- to high-income countries. It was the opposite [1, 2]. Obesity prevalence decreased with increased levels of income in affluent countries [1, 2, 3]. This observation also proved that obesity as a disease is complex and not a simple calorie-in and calorie-out equation [2, 4].

Review of NHANES (National Health and Nutrition Examination Survey) 2011–2014 data [4] categorized income levels into three categories: Highest (federal poverty level FPL >350%), middle-income levels (FPL > 130% to <350%), and lowest-income group (FPL ≤ 130%). The data revealed the overall prevalence of obesity was comparatively lower in the highest-income group (31.2%) as compared to middle-income group (40.8%) and lowest-income group (39%) [4].

Various other concomitant determinants such as gender, ethnicity, etc., affected the prevalence in a community [5]. On a gender level, obesity decreased with increased levels of income among women, consistent with overall prevalence [5]. It was 29.7% in FPL > 350% whereas it increased to 42.9% in FPL >130% to <350% group and 45.2% in FPL < 130% group [4]. However, this relationship was complex among men. Men had lower prevalence in both the lowest-income group (31.5%) and the highest-income group (32.6%) but affected middle-income group the most (38.5%) (Figure 1). One of the explanations for this is that men in low-income groups are involved in more labor-intensive jobs [4, 5].

Figure 1.

Obesity prevalence among adults, by household income (percentage of FPL) and sex—National Health and Nutrition Examination Survey, 1999–2002 to 2011–2014.

The relationship between obesity and income levels also varied by race and ethnicity. As shown in Table 1, obesity prevalence decreased as income increased in non-Hispanic whites (30.6% in FPL >350% vs. 35.8% in FPL < 130% and 40.2% in FPL > 130 to <350%). A similar relation was noted in the Asian population with an obesity prevalence of 10.7% in FPL > 350% vs. 15% in FPL < 130% and 11.2% in FPL > 130 to <350%; in the Hispanic population with 39.1% in FPL > 50% vs. 42.6% in FPL < 130 and 45% in FPL > 130 to <350%. Among, non-Hispanic Black men, there was no significant difference in obesity prevalence per poverty level (Table 1).

				Race/Hispanic origin
		Overall	White, non–Hispanic	Black, non–Hispanic	Asian, non–Hispanic	Hispanic
Characteristic	No.	% (95% CI)	% (95% CI)	% (95% CI)	% (95% CI)	% (95% CI)
Overall	10,636	36.3 (34.7–38.0)	34.5 (32.4–36.7)	48.1 (45.5–50.7)	11.7 (9.8–13.7)	42.5 (39.8–45.3)
Women	5413	38.3 (36.1–40.5)	35.5 (32.4–38.6)	56.9 (54.2–59.7)	11.9 (8.8–15.1)	45.7 (42.2–49.2)
Men	5223	34.3 (32.6–36.1)	33.6 (31.4–35.7)	37.5 (34.3–40.8)	11.2 (8.8–13.6)	39.0 (35.4–42.5)
Household income, both sexes
≤130% FPL	3462	39.0 (36.9–41.0)	35.8 (32.8–38.7)	46.6 (43.2–50.0)	15.0 (9.7–20.3)	42.6 (38.1–47.1)
>130 to ≤350% FPL	3331	40.8 (38.2–43.4)	40.2 (36.5–43.9)	48.8 (44.6–52.9)	11.2 (6.6–15.8)	45.0 (40.7–49.2)
>350% FPL	2992	31.2 (28.3–34.2)†^,§	30.6 (27.3–34.0)†^,§	49.3 (43.4–55.1)	10.7 (8.3–13.1)	39.1 (33.9–44.3)
Household income, women
≤130% FPL	1835	45.2 (42.5–48.0)	42.0 (37.4–46.5)	55.8 (52.2–59.4)	17.2 (10.3–24.1)	48.7 (43.1–54.4)
>130 to ≤350% FPL	1702	42.9 (40.1–45.8)	42.5 (38.8–46.1)	59.4 (53.7–65.2)	11.7 (5.6–17.7)	44.6 (37.4–51.8)
>350% FPL	1453	29.7 (26.1–33.3)†^,§	27.9 (24.0–31.9)†^,§	56.7 (50.0–63.5)	9.7 (5.8–13.7)	42.9 (35.2–50.5)
Household income, men
≤130% FPL	1627	31.5 (28.5–34.4)	28.5 (24.4–32.6)	33.8 (28.9–38.6)	11.8 (4.7–18.9)	35.9 (30.9–40.8)
>130 to ≤350% FPL	1629	38.5 (35.1–41.9)†	37.8 (32.7–43.0)†	35.6 (30.7–40.5)	10.3 (5.6–15.0)	44.6 (40.1–49.2)†
>350% FPL	1539	32.6 (29.4–35.8)§	32.9 (29.2–36.6)	42.7 (35.8–49.6)†	11.8 (7.9–15.7)	35.6 (27.8–43.4)§
Education, both sexes
High school graduate or less	4714	40.0 (37.9–42.2)	38.1 (34.5–41.6)	46.6 (42.8–50.4)	11.5 (7.6–15.5)	43.8 (40.6–47.0)
Some college	3231	40.6 (38.1–43.1)	39.2 (35.9–42.5)	50.5 (46.3–54.7)	12.4 (8.9–15.8)	42.9 (38.2–47.5)
College graduate	2683	27.8 (25.0–30.7)¶^,**	27.5 (24.1–30.9)¶^,**	47.3 (43.3–52.1)	11.1 (8.7–13.6)	36.9 (30.6–43.2)¶
Education, women
High school graduate or less	2227	45.3 (42.3–48.3)	43.3 (38.7–47.8)	57.9 (53.2–62.6)	11.4 (6.1–16.7)	49.6 (45.6–53.7)
Some college	1777	41.2 (38.5–43.9)	38.9 (35.1–42.7)	58.8 (53.8–63.9)	13.3 (7.6–19.0)	43.0 (36.3–49.8)
College graduate	1355	27.8 (24.1–31.5)¶^,**	27.0 (22.3–31.6)¶^,**	52.1 (47.4–56.8)**	11.3 (7.6–15.0)	36.1 (26.5–45.6)¶
Education, men
High school graduate or less	2437	35.5 (33.0–37.9)	34.1 (29.7–38.5)	36.0 (30.7–41.2)	11.0 (5.7–16.2)	37.7 (34.0–41.4)
Some college	1454	40.0 (35.9–44.1)	39.9 (34.7–45.1)	38.2 (32.7–43.7)	10.3 (5.6–15.1)	42.9 (36.0–49.9)
College graduate	1328	27.9 (24.3–31.5)¶^,**	28.1 (24.1–32.1)**	40.4 (32.4–48.3)	11.0 (7.9–14.1)	38.5 (28.1–48.8)

Table 1.

Prevalence of obesity among adults, *by race/Hispanic origin, sex, household income (percentage of FPL), and education—National Health and Nutrition Examination Survey, 2011–2014.

^*

Age adjusted by the direct method to the 2000 projected U.S census population using the age groups 20–30, 40–59, and ≤ 60 years.

^†

Significantly different from ≤130% FPL, p < 0.05.

^§

Significantly different from >130 to ≤350% FPL, p < 0.05.

^¶

Significantly different from high school graduates or less, p < 0.05.

^**

Significantly different from some colleges, p < 0.05.

Abbreviations: CI = confidence interval; FPL = federal poverty level.

2. Understand the health disparity

There are lots of disparities and inequalities in our community. People living in low-income communities are one of the groups that suffer from these disparities. They suffer from a higher prevalence of obesity as discussed earlier. They also lack access to effective treatment and preventive measures. They suffer from overall lower levels of education and get lower occupational and other opportunities. This same group also includes certain racial and ethnic minorities, which are already a disadvantaged group [6].

Since obesity prevalence has been on the rise, there is undoubtedly a major need to effectively combat the obesity epidemic. The focus of implementing effective strategies in low-income populations can be challenging. The first step to being able to reform and create equity for this community is understanding this inequity and disparity exist. This understanding will help to allocate resources appropriately among these disadvantaged groups and close the healthcare gap.

3. Understand potential etiologies

For the implementation of health reform, we need to know why such problems exist. So, let us dig in deeper. Several factors lead to an increased prevalence of obesity in low-income communities. In most cases, there is a combination of factors that contribute. A lot of these factors are also interconnected with each other.

3.1 Financial crunch

Obesity in a low-income population comes down to a lack of money for healthy food options. Low income leads to low-quality food. To eat a decent quality meal every day, it can cost significantly more for a person who is living on a minimum wage. Many people in this society barely make their ends meet taking in the cheapest food and drink which include inferior-quality nutrients. Unfortunately, good and healthy food are more expensive options [2], which leads these folks to steer away from these options.

3.2 Lack of education

There are also a lot of nutritional misconceptions in low-income populations. This unfortunately flows through their successive generations. There is a lack of education on how food creates good health versus makes you sick. Children learn from adults as they also lack getting a good education. When adults in families do not eat vegetables daily and have sugary beverages [6], the following generation feels it is acceptable to eat junk food and then the tradition continues.

3.3 Food insecurity

Low-income communities suffer from food insecurity. Food insecurity is the uncertainty of having or inability to acquire sufficient food [2, 3, 6]. It leads to several unhealthy behaviors. They grab and consume what they get. Families mostly choose energy-dense food such as sugars, cereals, potatoes, and processed meat products as these foods are more affordable, readily available, and last longer than fresh vegetables, fruits, lean meats, and fish. The food stamp program, now known as the Supplemental Nutritional Assistance Program (SNAP), was developed to combat food insecurity in low-income communities [6]. SNAP program provides mostly energy-dense food and lacks fresh and healthful food options [6].

Furthermore, food-insecure families also have limited knowledge, time, and resources to engage in healthful eating and exercise. They are all busy running around and working hard to provide for themselves and their families.

3.4 Poor access/resources to fresh food

This is the most saddening part. Not only do they not know what healthy food is, but people who live in poor communities also have poor access to fresh food. These areas are hence termed “food deserts” [3]. The food stamp program developed to combat food insecurity in low-income populations has poorer access to fresh food, and increased access to energy-dense food. Food insecurity has improved since then with a surplus of food, though mostly processed [6]. However, there has been very little change in how the SNAP program rolls out since its inception [6]. This leads to continued poor access to the resources to fresh food in low-income populations.

3.5 Stressful life

Economic insecurity due to low income leads to increased stress. The society they live in is also crime-ridden [3]. Many people are worried about their own or their family’s survival, about gunshots, police abuse, and about society holding them down and not educating them and therefore the jobs they deserve. They sleep with one eye open, in fear, night terrors, and fear due to an insecure society and environment. We all know how stress and anxiety play a role in our hormonal control and hormonal aberrations leading to obesity. People cope with stress by eating unhealthy high-fat sugary and processed food. They also lack adequate sleep. This disrupts their circadian rhythm leading to hormonal aberrations and eventually obesity.

3.6 Sedentary lifestyle

Several factors play a role in this. Low-income communities are crime-ridden, preventing people from being active outdoors. There are also fewer available parks and sports facilities in those communities [3]. Due to a lack of income, affording a gym membership, sports clothing, and exercise equipment are also out of the question [2, 3]. There might be people who are working double shifts to provide for their families, leaving very much less time to indulge in their well-being.

3.7 Racial/ethnic effect

Low-income communities also have a higher number of ethnic minority populations and hence incorporate all the racial or ethnic health disparities. As we all know, obesity is more common in certain racial and ethnic minatory groups [6].

4. Understand potential solutions

As complex as the disease of obesity is, equally complex is its management. Prevention is undoubtedly the best strategy. Not one strategy leads to success in combating obesity in low-income communities but requires a combination of strategies. Failure of certain focused studies like COPTR studies, and the GEMS trial [7] emphasizes how important it is that a combined broader focus on the social, economic, and physical environment is needed to prevent obesity in low-income communities.

This was described by Kumanyika et al. with their equity-oriented obesity prevention framework (Figure 2) [7, 8]. The framework involves four different quadrants with each quadrant specifically addressing different intervention approaches. The upper quadrants include how to increase healthy eating options and improve physical activity along with how to reduce deterrents leading to unhealthy eating and reduced physical activity. The bottom quadrants include improving individual and community resources and the capacity to support them. These focus on addressing health disparities and food insecurities with the development of different public health policies to improve social determinants of health.

Figure 2.

The equity-oriented obesity prevention framework. Adapted from Kumanyika et al. [8].

4.1 Preventive strategies

The preventive strategies include not only dietary and physical activities but also include various regulatory and educational strategies [7].

4.1.1 Dietary strategies

Different educational and environmental dietary interventions can be implemented at multiple levels [9]. At a consumer level, different strategies that can be used or tried are price manipulation to promote healthier food, posters/flyers/shelf labels, interactive sessions like taste testing healthier food, and promotional giveaways /incentivizing healthier food purchases with point of purchase promotions [9].

Improvising policy-level reforms such as increasing the availability of targeted food items, implementing a food labeling system to increase awareness of food ingredients with the number of calories, sugar, saturated fat, and sodium in a product, and increasing access to healthy food by incorporating healthy food supply chain rather than processed food [9]. Improved access to healthy food could reduce food insecurity. The New York Green Carts program used mobile food carts to offer fresh produce in certain poor neighborhoods. Understandably, this will involve extensive collaborations and planning with city council members, city health authorities, department leaders, local and regional retailers, and local community organization representatives [9].

Regulatory strategies at certain places such as schools could also be taken up to combat this problem. Eliminating soft drink vending machines in school, regulating food advertising to children in school, and mandating nutrition labeling can be some reforms that can be made. These are to educate people from low-income communities regarding their healthful vs. unhealthful food choices.

4.1.2 Physical activity strategies

Texts, letters, or telephone calls to promote playground use (as used in COPTR trial) [7]; school hip hop and African and step dance classes (as used in GEMS trials) [7] are different strategies used in different low-income community-based studies. Family-based intervention is used to reduce screen media time.

Furthermore, children may not be physically active unless efforts to improve neighborhood safety are made or provide them with places to play. Individuals do not improve until the community is strong and improved. We need to provide the community with adequate resources, safety, and opportunities [2].

4.1.3 Redesigning food stamp program

Redesigning the food stamp program could have a widespread impact on the health of food stamp recipients, who are the low-income communities. The food stamp program was first established as a pilot project to stabilize agricultural prices by stimulating the consumption of surplus farm commodities and alleviating hunger by providing additional calories to the recipients. Nutritional needs have now changed, nevertheless, the food stamp program operates for the same traditional norm. There needs to be a shift in emphasis on the program from calories to diet quality, from low-nutrient high energy-dense food to high-nutrient low energy-dense food. E.g., whole wheat bread instead of doughnuts. This change will lead the food industry to create low-cost palatable food products that are healthier and provide more fresh fruits and vegetables as options for consumers.

4.1.4 Improving school and head start programs

Schools and Head Start programs which include comprehensive health, nutrition, and education services to children are key influencers to combat childhood and youth obesity. Our youngsters spend a lot of time in them, and these are valued community institutions. Incorporating physical activities and good nutrition into school and preschool programs can create an enormous difference.

4.2 Treatment strategies

The leading strategy to help obesity in a poor environment is counseling. Dietary counseling and educating them about different diets and their nutritional values is especially important [10]. We need to provide all the education as this is their only resource. A randomized trial testing a high-intensity, lifestyle-based treatment program delivered in an underserved community showed a significant weight loss at 24 months [10]. Behavioral treatment strategies to steer them from fast food and get them to cook meals at home and hunt for vegetables in the grocery store remain the mainstay strategy for obesity management in low-income populations.

Most of the low-income individuals will be covered under the medical health plan from the state. Unfortunately, obesity care is still not an approved condition for which they can seek care under these plans. Hence the struggle for management is still present. Some medications are approved to be used for obesity. However, insurance coverage and costs associated with these medications are still outrageous and out of reach for these folks. Phentermine and topiramate are generic medications and certainly can be an option for treatment. Another combination of medication which includes bupropion and naltrexone can also be a cost-effective option for treatment. GLP1 receptor agonists and now GIP agonists are novel agents for obesity management, however, these are expensive and not always covered under the medical card. Semaglutide, one of the newest GLP1 receptor agonists, is approved for diabetes management in a lower dose. These have recently been placed under the formulary and can be used but most of the time these require prior authorization. The process of prior authorization is cumbersome and since care and coverage for obesity is still not an approved condition, these will still be unreachable goals at this time. This can delay the promptness in instituting these medications for the management of their weight, unfortunately. Some of the other GLP1 receptor agonists, like dulaglutide, though not approved for weight loss, can be used for treatment as these have more recently been under formulary in Medicaid plans. Metformin can be used off-label for weight loss, which can offset some of their weight, but it has not been shown to have a significant decrease in weight.

The low-income folks also suffer from grief, depression, anxiety, insomnia, weight stigma, and discrimination. They might be on multiple different medications that can cause weight gain. Working with them and tapering or adjusting some medications to counteract their weight gain side effects can be a helpful strategy to help with their obesity. Metformin can be used to counteract the weight-gaining properties of some psychotropic medications.

Surgery for obesity is not covered under a lot of health plans and particularly for the low income, it is still out of the question.

Furthermore, follow-up care in low-income populations is scarce. The no-show rate is plentiful. Their priority for self-care is low. These may not be entirely because of their choice. Their jobs may not offer time off; patients may be working two full-time jobs just to make enough to pay the bills. These all come into play.

Moreover, there might also be this weight stigma and discrimination that discourages them from seeking care. We also need to understand this. Our goal is to be nonjudgmental about their weight in our day-to-day practice, respect them, and understand these social determinants of health. No one wants to be unhealthy. We need to provide adequate guidance and create a supporting community that they can rely on to achieve their goals. Instead of pointing it out, let us help them to fight this battle.

The Healthcare Reform (The Patient Protection and Affordable Care Act P.L. 111-148) was devised in 2010 to help bridge these gaps to help care for obesity in the United States [11].

5. The cause or the effect?

There has also been a concept of reverse causality [1]. People suffering from obesity tend to also suffer from labor discrimination [1]. They are likely to be perceived as lazy, unsuccessful, weak-willed, and undisciplined [1]. This leads them to conquer low-income jobs in a labor market leading to poverty [1]. These negative energies in the community among people who suffer from obesity further increase higher levels of psychosocial stressors, higher insecurity, social isolation, and mental disorders [1]. This further leads to increased poverty and a higher risk of obesity. One systematic literature search which included 21 studies, from January 2017 suggested strong reverse causality than the causality [1]. However, more studies are needed to further elaborate this relationship [1].

6. Conclusion

Whether it is the cause or effect that came first, one thing is for fact from our observations that these create a cycle of events. The low-income communities experience disparity in health leading to obesity and experience inequity in their obesity care. Inequity in obesity care further leads to obesity. Health reforms involving a combination of strategies at social, economic, and community levels are required to break this cycle and create equity.

Conflict of interest

The authors declare no conflict of interest.