Low Income and its impact on Childhood Obesity

Introduction

Nearly 17% of children and adolescents in the United States are affected by obesity. Furthermore, 8.5% of children and adolescents globally are obese. (Zhang et al.) Lower-income children are disproportionately at risk for obesity (Chou et al.) According to research by Jin and Jones-Smith, lower-income children had much higher BMI scores than high-income children.

Childhood obesity is becoming increasingly prevalent in low-and middle-income countries (LMICs), as well as minority ethnicities in high-income countries (HICs). It contributes to an increased risk of early-onset chronic diseases. In HICs, the intervention approaches are inadequate for nutrition, lifestyle, and physical activity in minority populations, which exacerbates the already prevalent issue at hand. Thus, the implementation of new solutions that mediate this problem must take place. According to research by Alkhatib and Obita, using objective adiposity fat percentage measurements with anthropometric and physiological components can rectify ineffective obesity screening by body mass index (BMI). Adiposity is the degree of fatness of the body or part of the body especially excessive fatness, anthropometric is the scientific study of the measurements and proportions of the human body, and BMI is a weight-to-height ratio, calculated by dividing one’s weight in kilograms by the square of one’s height in meters and used as an indicator of obesity and underweight, as defined by Oxford Languages. 

Data

Among children and adolescents aged 5 to 19, the global prevalence has quadrupled in the last 41 years. Additionally, up to 250 million children worldwide are projected to have obesity by 2030. (Alkhatib and Obita) Although this projection does not account for disparities amongst ethnic groups, the 2011-2012 National Health and Nutrition Examination Survey of 6-17 year-olds in the US displayed that only 12% of non-Hispanic white American children were obese, in comparison to 25% of black, Hispanic, and American Indian/Alaska Native children. 

Proposed Solutions – Direct and Indirect Assessments 

Furthermore, there should be obesity cut-off points for minority ethnicities, whose obesity-related metabolic risks are often underestimated, included in national healthcare childhood obesity prevention initiatives. (Alkhatib and Obita) Lastly, physical activity and nutrition interventions for ethnic minority children with obesity comorbidities are highly effective. 

One way to reduce the disparity in obesity screenings is to consider ethnic differences in body fat distribution. Asian populations have a 2-3 kg/m^2 lower BMI than Caucasians for the same body fat percentage. This displays that there is an increased cardiometabolic risk for Asian populations if the same BMI is used. (Alkhatib and Obita) Furthermore, a large cross-section study recommended ethnicity-specific BMI cut-off points as the type 2 diabetes risks varied for each ethnic population, including Caucasian, black, South Asian, Chinese, and Arab populations. (Caleyachetty et al.) Although ethnicity-specific BMI cut-offs are useful, having one standard cut-off for each ethnic group is very complex to develop. Therefore, ethnicity-specificity BMI cut-offs should be utilized for indirect estimation of obesity in children, but they should be combined with at least one direct assessment. (Alkhatib and Obita)

Direct assessments for obesity include DEXA, BIA, magnetic resonance imaging (MRI), computed tomography (CT), computed tomography body composition (CTBC), air displacement plethysmography (ADP), whole body potassium counters (WBKCs), the isotope dilution method (hydrometry), and underwater weighing. (Alkhatib and Obita)

Out of those, DEXA and BIA are the most feasible in large populations. DEXA operates using a three-component model that estimates fat, FFM, and bone mineral density. According to a large cross-sectional cohort in HICs including Dutch children aged 10-11, DEXA was proven practical. (Alkhatib and Obita) BIA is a less expensive method compared toDEXA, and it operates using two components (%BF and FFM %). Bioelectrical Impedance Analysis (BIA) can estimate body composition via a small electrical current through the body. (Beestone). BIA is suitable for large populations as shown by a large-scale obesity screening that included around 13000 Chinese school children ages 7-17 and used BIA bipedal devices in community healthcare centers.  (Alkhatib and Obita) Thus, BIA is an adequate and effective method for large populations in school or community environments.  

Although, the best method to reduce ethnic disparities in obesity prevalence would be to combine a direct and indirect approach, where resources are scarce, an indirect assessment would still be useful to reduce some disparity. 

Lifestyle interventions are an essential part of reducing disparities; however, they must be taken in context with the population in question. According to a NICE statement in 2011, the implementation of obesity-related interventions in high-risk ethnic minority groups was ineffective because of the perceived cultural barriers.  (Alkhatib and Obita). This can be explained by  (Alkhatib and Obita) preliminary study in Northeast England, which showed that parents were aware of their children’s obesity, however, were less aware of the support for it. In order to mediate this, direct engagement of children and parents in implementing PA interventions and healthy diets should be utilized, as it is proven more useful rather than distributing educational materials and classroom education.

Conclusion

In conclusion, disparities in childhood obesity prevention and prevalence must be mediated through direct and indirect approaches. This issue is encompassed by a broader problem in our healthcare system. Often healthcare policies do not offer equal care to all and thus they must be changed. For obesity specifically, healthcare policy should take into account the differences in high-risk ethnic minority populations that deviate from the standardized assessments. Lastly, increasing awareness of this issue is important to raise attention for new healthcare policies. This can be done through petitions that increase obesity health coverage that communities can support. If interested in helping mediate this issue, relevant petitions are linked below. 

Petitions

OCW2020 Childhood Obesity Petition

Bibliography

1. Alkhatib, Ahmad, and George Obita. “Childhood Obesity and Its Comorbidities in High-Risk Minority Populations: Prevalence, Prevention and Lifestyle Intervention Guidelines.” Nutrients, vol. 16, no. 11, 31 May 2024, pp. 1730–1730, https://doi.org/10.3390/nu16111730. Accessed 29 June 2024.

2. Chou, Yi-Chang, et al. “Impact of Household Income on the Risk of Overweight and Obesity over Time among Preschool-Aged Children: A Population-Based Cohort Study.” BMC Public Health, vol. 24, no. 1, 21 Feb. 2024, https://doi.org/10.1186/s12889-024-18010-1.
3. Jin, Yichen, and Jessica C. Jones-Smith. “Associations between Family Income and Children’s Physical Fitness and Obesity in California, 2010–2012.” Preventing Chronic Disease, vol. 12, 12 Feb. 2015, www.cdc.gov/pcd/issues/2015/14_0392.htm, https://doi.org/10.5888/pcd12.140392
4. Caleyachetty, Rishi, et al. “Ethnicity-Specific BMI Cutoffs for Obesity Based on Type 2 Diabetes Risk in England: A Population-Based Cohort Study.” The Lancet Diabetes & Endocrinology, vol. 9, no. 7, May 2021, www.thelancet.com/journals/landia/article/PIIS2213-8587(21)00088-7/fulltext, https://doi.org/10.1016/s2213-8587(21)00088-7.

5. Zhang, Xinyue, et al. “Global Prevalence of Overweight and Obesity in Children and Adolescents: A Systematic Review and Meta-Analysis.” JAMA Pediatrics, 10 June 2024, jamanetwork.com/journals/jamapediatrics/fullarticle/2819322, https://doi.org/10.1001/jamapediatrics.2024.1576.
6. Image Citation: “Learn How to Prevent and Address Childhood Obesity for Lifelong Health.” Physicians Premiere Weight & Wellness Center, healthymeweightloss.com/childhood-obesity/.