In Brief | Non-Communicable Diseases | Obesity


Mapping the Impact of Obesity: New Study Highlights CKD Risk and the Multisystem Impact of Obesity Across 16 Conditions


Time to read: 04:33
Time to listen: 07:22
 
Published on MedED: 5 June 2025
Originally Published: 25 March 2025

Source: NEJM
Type of article: In Brief
MedED Catalogue Reference: MNC002
Category: Non-Communicable Diseases
Cross Reference: Cardiovascular Diseases, CKD

Keywords: CKD, CVD, Obesity, lifestyle diseases, disease-modifying factors
Key Takeaway
This large-scale meta-epidemiological analysis confirmed that Obesity is a significant, modifiable risk factor associated with the incidence of 16 major health conditions—including type 2 diabetes, chronic kidney disease, and metabolic liver disease—with the highest risks observed in individuals with severe (Class III) obesity.
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This article is a review of recent studies originally published in the NEJM 25 March 2025This article does not represent the original research, nor is it intended to replace the original research. Access the full Disclaimer Information.

 

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In Context

The global burden of non-communicable diseases (NCDs) is profound, accounting for 74% of all deaths worldwide. Conditions such as cardiovascular disease, diabetes, chronic respiratory disease, and cancer not only drive mortality but also contribute significantly to years lived with disability.1

South Africa faces an especially severe non-communicable disease (NCD) crisis. The World Health Organisation estimates that the country’s NCD burden is two to three times higher than that of comparable developing nations. Notably, this burden is not evenly distributed—poorer urban communities carry a disproportionate share.1,2

Two increasingly important contributors to South Africa’s NCD profile are chronic kidney disease (CKD) and metabolic dysfunction-associated steatotic liver disease (MASLD). Both are closely linked to one of the most modifiable and rapidly escalating public health risks: obesity.5,6,8

Obesity plays a central role in the development and progression of multiple NCDs. Its association with type 2 diabetes mellitus and hypertension—both primary drivers of CKD and MASLD—has placed it at the forefront of public health concerns. This rising epidemic is fuelled by socioeconomic transitions, urbanisation, dietary shifts toward processed and energy-dense foods, and increasingly sedentary lifestyles.4,5,6

Globally South Africa ranks among the countries with the highest projected increases in obesity, with prevalence expected to rise by 47.7% in women and 23.3% in men by 2025. These shifts are already being felt across the healthcare system.4

According to the International Society of Nephrology (ISN) Global Health Atlas, chronic kidney disease (CKD) affects approximately 10.7% of the South African population.Obesity contributes to CKD both indirectly, through its effect on diabetes and hypertension, and directly, via a complex interplay of metabolic, inflammatory, and haemodynamic mechanisms.4,5,9

Meanwhile, MASLD—a liver disease driven by metabolic dysfunction—is emerging as another under-recognised consequence of obesity. Globally, it affects over 30% of the population. In sub-Saharan Africa, the burden of MASLD is increasing but remains poorly documented. Its key risk factors, such as diabetes, obesity, and hypertension, mirror those of CKD.6,7 

Given the shared metabolic pathways and overlapping risk profiles of MASLD, MASH, and CKD, particularly in relation to obesity, insulin resistance, and hypertension, there is a compelling need to address these conditions not in isolation but as part of a broader, interconnected spectrum of metabolic diseases. 

 South Africa is among the countries with the highest obesity prevalence, with projections suggesting a 47.7% increase in females and 23.3% in males by 2025.5


Study Review

In this context, a large-scale meta-epidemiological analysis published in the NEJM Evidence in March 2025, presented the findings from an analysis of the All of Us Research Program examined 270,657 adults with BMI 18.5 kg/m, using linked electronic health records to study the prevalence and incidence of 16 obesity-related health outcomes, including CKD, cardiovascular, metabolic, and pulmonary diseases.

Importantly, the cohort was diverse compared to previous studies, with 62% being women and 22% being Black. 
 
Obesity was strongly associated with all studied outcomes, with increased risk across higher BMI classes.

The analysis revealed that participants with Class III obesity (BMI ≥40) exhibited the highest risk levels, particularly for obstructive sleep apnoea, type 2 diabetes mellitus, and metabolic dysfunction-associated steatotic liver disease (MASLD).
 
 The hazard ratios (HRs) for these outcomes were striking:
Obstructive sleep apnoea: HR 10.94 (95% CI, 9.97–12.00)
Type 2 diabetes mellitus: HR 7.74 (95% CI, 7.03–8.53)
MASLD: HR 6.72 (95% CI, 6.01–7.50)
 
While less pronounced, significant associations were still observed for asthma (HR 2.14), osteoarthritis (HR 2.06), and atherosclerotic cardiovascular disease (ASCVD) (HR 1.96). These findings reinforce the systemic, multisystem burden of obesity-related morbidity.
 

Importantly, these associations were consistent across sex and race, underscoring the generalisability of the findings within this highly diverse cohort.


Notably, the study population consisted of 62% women and 22% Black participants, which helped address gaps in prior obesity research that had lacked demographic diversity.

The population-attributable fraction (PAF)—a measure of the proportion of disease incidence in the population that can be attributed to obesity—was substantial. For example, obesity was estimated to contribute to over half of obstructive sleep apnoea cases (PAF 51.5%) and a significant proportion of type 2 diabetes, MASLD, and osteoarthritis cases (PAF ranging from 14% to over 40%).


Study Discussion
 
Given the expanding burden of obesity-related disease in South Africa, this study holds particular significance. Importantly, obesity is a modifiable risk factor, presenting a critical opportunity for targeted intervention. In a context where socioeconomic inequalities already drive significant disparities in health outcomes—especially among urban poor communities—the rising prevalence of obesity threatens to further strain an already overstretched healthcare system.
 
Findings from this large, diverse cohort reinforce the urgent need to prioritise early identification, prevention, and management of obesity as a core component of national strategies aimed at reducing the long-term impact of non-communicable diseases. Integrating obesity prevention into renal and cardiovascular care pathways could substantially reduce the incidence of related diseases, improve patients’ quality of life, and alleviate pressure on healthcare services.
 
These data provide a timely and robust evidence base to support clinical decision-making and public health policy in South Africa and comparable settings. They further emphasise the need for a coordinated, evidence-based approach to obesity management within renal and liver care pathways, encompassing both pharmacological treatments and community-level public health initiatives.

 

Access the original study
 



References


1.World Health Organization. (2024, June 1). Noncommunicable diseases. https://www.who.int/news-room/fact-sheets/detail/noncommunicable-diseases

2. Achoki T, Sartorius B, Watkins D., et al. Health trends, inequalities and opportunities in South Africa's provinces, 1990-2019: findings from the Global Burden of Disease 2019 Study. J Epidemiol Community Health. 2022 Jan 19;76(5):471–81. doi: 10.1136/jech-2021-217480. Epub ahead of print. PMID: 35046100; PMCID: PMC8995905.

 
3. Yao Z, Tchang BG, Albert M, Blumenthal RS, Nasir K, Blaha MJ. Associations between Class I, II, or III Obesity and Health Outcomes. NEJM Evid. 2025 Apr;4(4):EVIDoa2400229. doi: 10.1056/EVIDoa2400229. Epub 2025 Mar 25. PMID: 40130972.

4. Manafe M, Chelule PK, Madiba S. The Perception of Overweight and Obesity among South African Adults: Implications for Intervention Strategies. Int J Environ Res Public Health. 2022 Sep 28;19(19):12335. doi: 10.3390/ijerph191912335. PMID: 36231633; PMCID: PMC9564787.

5. Hariparshad, S., Bhimma, R., Nandlal, L. et al. The prevalence of chronic kidney disease in South Africa - limitations of studies comparing prevalence with sub-Saharan Africa, Africa, and globally. BMC Nephrol 24, 62 (2023). https://doi.org/10.1186/s12882-023-03109-1

6. Sedibe A, Maswanganyi K, Mzimela NC, Gamede M. Prevalence of metabolic dysfunction-associated steatotic liver disease in people living with HIV and on antiretroviral treatment: A systematic review and meta-analysis protocol. Health Sci Rep. 2024 Oct 28;7(11):e70071. doi: 10.1002/hsr2.70071. PMID: 39474343; PMCID: PMC11518884.

7. SIndato Emmanuel M. , Kajogoo Violet Dismas , Ngajilo Gloria , Degu Wondwossen Amogne , Khan Zahid , Mlawa Gideon Prevalence and risk factors of metabolic-associated fatty liver disease in sub-Saharan Africa: a systematic review and meta-analysis Frontiers in Gastroenterology Volume 4 - 2025 DOI=10.3389/fgstr.2025.1506032ISSN=2813-1169

 8. Prasad R, Jha RK, Keerti A. Chronic Kidney Disease: Its Relationship With Obesity. Cureus. 2022 Oct 21;14(10):e30535. doi: 10.7759/cureus.30535. PMID: 36415443; PMCID: PMC9675899.

9. Nawaz S, Chinnadurai R, Al-Chalabi S, Evans P, Kalra PA, Syed AA, Sinha S. Obesity and chronic kidney disease: A current review. Obes Sci Pract. 2022 Jul 19;9(2):61-74. doi: 10.1002/osp4.629. PMID: 37034567; PMCID: PMC10073820.


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