Rethinking the "diseases of affluence" paradigm: global patterns of nutritional risks in relation to economic development

Abstract

Background: Cardiovascular diseases and their nutritional risk factors--including overweight and obesity, elevated blood pressure, and cholesterol--are among the leading causes of global mortality and morbidity, and have been predicted to rise with economic development.

Methods and findings: We examined age-standardized mean population levels of body mass index (BMI), systolic blood pressure, and total cholesterol in relation to national income, food share of household expenditure, and urbanization in a cross-country analysis. Data were from a total of over 100 countries and were obtained from systematic reviews of published literature, and from national and international health agencies. BMI and cholesterol increased rapidly in relation to national income, then flattened, and eventually declined. BMI increased most rapidly until an income of about ID 5,000 (international dollars) and peaked at about ID 12,500 for females and ID 17,000 for males. Cholesterol's point of inflection and peak were at higher income levels than those of BMI (about ID 8,000 and ID 18,000, respectively). There was an inverse relationship between BMI/cholesterol and the food share of household expenditure, and a positive relationship with proportion of population in urban areas. Mean population blood pressure was not correlated or only weakly correlated with the economic factors considered, or with cholesterol and BMI.

Conclusions: When considered together with evidence on shifts in income-risk relationships within developed countries, the results indicate that cardiovascular disease risks are expected to systematically shift to low-income and middle-income countries and, together with the persistent burden of infectious diseases, further increase global health inequalities. Preventing obesity should be a priority from early stages of economic development, accompanied by population-level and personal interventions for blood pressure and cholesterol.

Figure 1. Global Mortality and Burden of Disease Attributable to Cardiovascular Diseases and Their Major Risk Factors for People 30 y of Age and Older

The size of each circle is proportional to the number of deaths (left) or burden of disease (right; measured in disability-adjusted life years) (in millions). Overweight and obesity affect non-cardiovascular diseases, including diabetes, endometrial and colon cancers, post-menopausal breast cancer, and osteoarthritis, shown as the portions of yellow circles that fall outside the cardiovascular disease circle [57]. The mortality estimates exclude osteoarthritis, which results in morbidity but not direct deaths. Disease burden does include nonfatal health outcomes associated with diabetes and osteoarthritis (hence the larger size of the circle for overweight and obesity relative to those for blood pressure and cholesterol). Source: re-analysis of data from Ezzati et al. [57,58].

Figure 2. Pair-Wise Relationships of Mean Population BMI, SBP, and Total Cholesterol with National Income, Share of Household Expenditure Spent on Food, and Proportion of Population in Urban Areas

Data for (A) males and (B) females are shown. National income is measured as per-capita gross domestic product (GDP). BHS, Bahamas; CUB, Cuba; EST, Estonia; ETH, Ethiopia; FIN, Finland; GEO, Georigia; GMB, Gambia; IDN, Indonesia; JOR, Jordan; JPN, Japan; KEN, Kenya; KOR, Korea; KWT, Kuwait; MLT, Malta; MWI, Malawi; NGA, Nigeria; NOR, Norway; NPL, Nepal; PNG, Papua New Guinea; POL, Poland; RUS, Russian Federation; SAU, Saudi Arabia; SLB, Solomon Islands; THA, Thailand; TJK, Tajikistan; TZA, Tanzania; USA, United States; VNM, Viet Nam; WSM, Samoa; ZWE, Zimbabwe.

Figure 3. Relationship of Mean Population BMI, SBP, and Total Cholesterol with Average National Income, Food Share of Household Expenditure, and Proportion of Population in Urban Areas

Relationships were estimated using local regression models applied to the data in Figure 2. Results for (A) males and (B) females are shown. National income was measured as gross domestic product (GDP). The following outlier countries were dropped (see also Results): United States for males and females in the income–BMI relationship, and Russian Federation and Tajikistan for males and females in the food share of household expenditure–BMI relationship.

Figure 4. Shifting Relationships of BMI, SBP, and Total Cholesterol with Income in the United States, Estimated Using Local Regression

Data are from the National Health and Examination Survey, 1976–1980, 1988–1992, and 1999–2000.