Island Women and the Obesity Transition: Examining SES, Ethnicity and Economic Development
Källarsalen Session 7: Health crises: plagues and strikes organized by Nicolas Maughan
Abstract
Rates of overweight and obesity are increasing rapidly in developing countries due to economic development, decreasing levels of physical activity, and shifting diets and Small Island Developing States (SIDS) tend to have significantly higher obesity prevalence than the global average. This study aims to understand socioeconomic differences in female obesity in different island contexts. Dietary habits and obesity among mothers and pregnant women can affect their offspring, thus affecting the health of younger generations. Female obesity is, therefore, a health concern that extends across generations.
The four countries in the study share characteristics such as remote location, growing and often low-skilled populations, limited land-based resources, small domestic markets, and high dependence on international trade. However, they also represent different levels of economic development and obesity patterns. The Maldives, an upper middle-income country located in the Indian Ocean, has a relatively modest prevalence of female obesity (11.4% in 2016). Samoa, in the Pacific Ocean, is a lower middle-income country with one of the highest prevalence rates of female obesity in the world (55% in 2016). Timor-Leste is also a lower middle-income country but has the lowest prevalence of female obesity of the four (4.9 % in 2016). Fiji, an upper-middle-income country in the Pacific Ocean, has a more ethnically diverse population and a lower prevalence of female obesity than other countries in the Pacific Ocean (35% in 2016).
The relationship between socioeconomic status (SES), economic development, and obesity is complex. In lower-income countries, higher SES groups are more likely to be obese, while in high-income countries, those with higher SES are less likely to be obese. Economic development can lead to improvements in health, but it can also lead to overconsumption, which affects SES groups differently.
The study draws upon two data sources: the Multi-Indicator Cluster Survey (MICS) for Fiji and Samoa, and the Demographic and Health Survey (DHS) for the Maldives and Timor-Leste. The variables in the two data sources are highly comparable.
The preliminary regression results indicate that in the Maldives, there is a clear SES gradient in obesity, with the lowest SES group (those with primary or lower education) having the highest odds of being obese. This is a pattern commonly observed in high-income countries. In contrast, in Samoa and Timor-Leste, those with higher levels of education have higher odds of obesity. This is a common pattern in many developing countries at the early stages of the obesity transition. The Fijian patterns do not follow the other countries, as the associations change when control variables are added. Crude estimates show the highest obesity among those least educated, while adjusted estimates. The Fijian results also hide a story of ethnic differences as they play a crucial role in explaining SES patterns in obesity.
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