Case study based on: Ng, S.W., Zaghloul, S., Ali, H., Yeatts, K., El Sadig, M., & Popkin, B.M. (2011). Nutrition transition in the United Arab Emirates. European Journal of Clinical Nutrition.
The United Arab Emirates (UAE) is a federal state consisting of seven Emirates: Abu Dhabi, Dubai, Sharjah, Umm al Qaywayn, Ajman, Al Fajayrah and Ras al Khaymah (WHO, 2012). The Emirates have experienced remarkable economic and social transformations over the past few decades, going from an impoverished region of small desert principalities to a modern state with a high standard of living (Central Intelligence Agency, 2019). These transformations were accompanied by changes in dietary patterns (Ng et al., 2011) as well as the burden of disease, where non-communicable diseases (NCDs) incidence (cardiovascular diseases, diabetes and cancer) have been rising (WHO, 2012).
This case study, based on work by Ng et al. (2011), illustrates an example of using a nationally representative 24-hour Dietary Recall (24HR) survey to estimate the dietary patterns of adult females, children and adolescents in order to characterize the dietary manifestations of a country’s nutrition transition. The authors also explored underlying factors, such as urbanization and wealth, associated with the nutrition transition, and compared their results with previous surveys conducted in the country to illustrate dietary trends. The following paragraphs summarize the methods and findings from Ng et al. (2011) as well as some strengths and weaknesses of the data source and indicators the authors used to assess food consumption at the individual level.
To examine food consumption, Ng et al. (2011) collected and analyzed 24HR data from a nationally representative sample of urban and rural Emirati households from all seven Emirates. Dietary data, anthropometry, and physical activity data were collected from one female adult, one adolescent, and one child randomly selected from each household, along with basic household-level socio-demographic information. Data obtained from the 24HR were matched with nutrient information in ESHA Research’s Food Composition Database (FCDB), which contains over 35,000 food items with data from more than 1,500 sources, including the latest US Department of Agriculture Reference database (ESHA Research, 2006). The authors derived two indicators from the 24HR data: total individual energy intake (in kcal/day), used to assess intake of sufficient calories—the most basic element of dietary quality; and total individual macronutrient intake, which provided information on the makeup of calories consumed (% of total energy of three major macronutrients: protein, fats and, carbohydrates). Moreover, the analysis included the share of calories for each eating occasion (breakfast, lunch, dinner and between meals) and calories from beverages in kcal/day. Physical activity was measured using the International Physical Activity Questionnaire (IPAQ), which assessed the frequency of three different types of leisure activities in the previous 7 days.
The anthropometric data showed that overweight and obesity increased in 2009/10 compared to 2000. Among children and adolescents, there was a gender differential that suggests the Emirati context may be particularly worse for girls, who are more likely to become overweight or obese. The analysis of total individual energy intake derived from the 24HR found that a large percentage of children (both girls and boys) consumed more calories than needed. This was also the case for adolescents and adult females. A gender differential was again observed, with a higher proportion of female Emirati children and adolescents over-consuming compared to males. No significant differences were found in terms of total individual macronutrient intake, with all values complying with the Acceptable Macronutrient Distribution Range (AMDR). The authors observed increased intake of calorie-dense snacks, high levels of caloric sugar-sweetened beverages and reduced levels of physical activity, especially among females and those living in urban areas, and suggested that these factors could have contributed to overweight and obesity trends. Higher levels of physical inactivity among females were thought to be due to strong sociocultural norms that create obstacles and disincentives and encourage sedentary lifestyle.
The trends unveiled in the analysis represent a high population risk for the development of NCDs such as cardiovascular disease, diabetes and some cancers. To combat these trends, the authors suggest investing in both dietary and physical activity policies and programs. For instance, dietary interventions could include promotion of reduced sugar sweetened beverage intake and increases in the accessibility and affordability of healthier alternatives such as water and low-fat dairy products. Policy responses to increased sedentariness could include improved access to female-only exercise facilities and active transportation (e.g. walking or biking to school/work). The aim of these efforts is to produce a more positive built environment with social support to achieve long lasting health impacts, particularly for female children and adolescent Emiratis.
Given the nutrition transition and rapid transformation of food systems in many countries, there is an increased interest in, and demand for, individual-level quantitative dietary data (Coates et al., 2017). This case study is an example of using 24HR and physical activity data to identify trends in food and nutrient intake (as well as physical activity patterns). The 24HR method provides quantitative information on individual diets and offers a higher degree of accuracy in assessing food and nutrient intake relative to Food Frequency Questionnaires (FFQs) or estimates derived from Household Consumption and Expenditure Surveys (HCES). Whereas FFQs tend to be limited to asking about foods or specific nutrients of interest for a given study’s objective, 24HR data are more multi-purpose as they collect information on all food consumed on a given day or days (when repeated). Although dietary data from 24HR are often collected infrequently and in small samples, the authors used a nationally representative sample, meaning that their results can be extrapolated to the Emirati population of adult women as well as adolescents, and children of both genders. The 24HR surveys are complex and require high level of specialized enumerator training to minimize errors in data collection. Like FFQs and HCES, 24HR are subject to recall bias and interviewer bias since the methods rely on respondent memory and are typically interviewer-administered in low- and middle-income countries.
The researchers’ analysis of 24HR survey data highlighted critical transformations taking place in the UAE. Their findings point to the clear need for policies to facilitate healthier dietary choices and increased access to physical activity, particularly among females.
- Central Intelligence Agency. (2019). Middle East: United Arab Emirates. The World Factbook. CIA Library. Retrieved from https://www.cia.gov/library/publications/the-world-factbook/geos/print_ae.html
- Coates, J., Colaiezzi, B., Bell, W., Charrondiere, R., & Leclercq, C. (2017). Overcoming Dietary Assessment Challenges in Low-Income Countries: Technological Solutions Proposed by the International Dietary Data Expansion (INDDEX) Project. Nutrients, 9(3):289. doi: 10.3390/nu9030289
- ESHA Research. (2006). Food Processor and Genesis SQL Database Sources. Salem: OR.
- Ng, S.W., Zaghloul, S., Ali, H., Yeatts, K., El Sadig, M., & Popkin, B.M. (2011). Nutrition transition in the United Arab Emirates. European Journal of Clinical Nutrition, 65, 1328-1337. doi: 10.1038/ejcn.2011.135
- World Bank. (2016). United Arab Emirates Economic Outlook-Fall 2016. Retrieved from http://www.worldbank.org/en/country/gcc/publication/united-arab-emirates-economic-outlook-fall-2016
- World Health Organization. (2012). Country Cooperation Strategy for WHO and the United Arab Emirates 2012-2017. Retrieved from https://apps.who.int/iris/bitstream/handle/10665/113226/CCS_UAE_2012_EN_14947.pdf?sequence=1