Dietary quality among men and women in 187 countries in 1990 and 2010: a systematic assessment

Fumiaki Imamura, Renata Micha, Shahab Khatibzadeh, Saman Fahimi, Peilin Shi, John Powles, Dariush Mozaffarian, Global Burden of Diseases Nutrition and Chronic Diseases Expert Group (NutriCoDE), Fumiaki Imamura, Renata Micha, Shahab Khatibzadeh, Saman Fahimi, Peilin Shi, John Powles, Dariush Mozaffarian, Global Burden of Diseases Nutrition and Chronic Diseases Expert Group (NutriCoDE)

Abstract

Background: Healthy dietary patterns are a global priority to reduce non-communicable diseases. Yet neither worldwide patterns of diets nor their trends with time are well established. We aimed to characterise global changes (or trends) in dietary patterns nationally and regionally and to assess heterogeneity by age, sex, national income, and type of dietary pattern.

Methods: In this systematic assessment, we evaluated global consumption of key dietary items (foods and nutrients) by region, nation, age, and sex in 1990 and 2010. Consumption data were evaluated from 325 surveys (71·7% nationally representative) covering 88·7% of the global adult population. Two types of dietary pattern were assessed: one reflecting greater consumption of ten healthy dietary items and the other based on lesser consumption of seven unhealthy dietary items. The mean intakes of each dietary factor were divided into quintiles, and each quintile was assigned an ordinal score, with higher scores being equivalent to healthier diets (range 0-100). The dietary patterns were assessed by hierarchical linear regression including country, age, sex, national income, and time as exploratory variables.

Findings: From 1990 to 2010, diets based on healthy items improved globally (by 2·2 points, 95% uncertainty interval (UI) 0·9 to 3·5), whereas diets based on unhealthy items worsened (-2·5, -3·3 to -1·7). In 2010, the global mean scores were 44·0 (SD 10·5) for the healthy pattern and 52·1 (18·6) for the unhealthy pattern, with weak intercorrelation (r=-0·08) between countries. On average, better diets were seen in older adults compared with younger adults, and in women compared with men (p<0·0001 each). Compared with low-income nations, high-income nations had better diets based on healthy items (+2·5 points, 95% UI 0·3 to 4·1), but substantially poorer diets based on unhealthy items (-33·0, -37·8 to -28·3). Diets and their trends were very heterogeneous across the world regions. For example, both types of dietary patterns improved in high-income countries, but worsened in some low-income countries in Africa and Asia. Middle-income countries showed the largest improvement in dietary patterns based on healthy items, but the largest deterioration in dietary patterns based on unhealthy items.

Interpretation: Consumption of healthy items improved, while consumption of unhealthy items worsened across the world, with heterogeneity across regions and countries. These global data provide the best estimates to date of nutrition transitions across the world and inform policies and priorities for reducing the health and economic burdens of poor diet quality.

Funding: The Bill & Melinda Gates Foundation and Medical Research Council.

Copyright © 2015 Imamura et al. Open Access article distributed under the terms of CC BY. Published by .. All rights reserved.

Figures

Figure 1
Figure 1
Global dietary patterns among men and women in 187 countries in 2010 Values represent degrees of adherence to each dietary pattern, ranging from 0 (least healthy) to 100 (most healthy).
Figure 2
Figure 2
Dietary pattern among men and women in 187 countries in 2010 based on greater consumption of ten more healthy items Values represent degrees of adherence to each dietary pattern, ranging from 0 (least healthy) to 100 (most healthy). 187 countries are ordered by scores among adults aged 20–29 years. Lines show error bars for each country, which represent the lower side of the 95% uncertainty interval for the lowest age-specific estimate and the upper side of the 95% uncertainty interval for the highest age-specific estimate.
Figure 3
Figure 3
Dietary pattern among men and women in 187 countries in 2010 based on less consumption of seven unhealthy items Values represent degrees of adherence to each dietary pattern, ranging from 0 (least healthy) to 100 (most healthy). 187 countries are ordered by scores among adults aged 20–29 years. Lines show error bars for each country, which represent the lower side of the 95% uncertainty interval for the lowest age-specific estimate and the upper side of the 95% uncertainty interval for the highest age-specific estimate.
Figure 4
Figure 4
Changes in dietary patterns from 1990 to 2010 among men and women in 187 countries Top: changes in dietary pattern scores based on greater consumption of ten healthful foods and nutrients. Middle: changes in dietary pattern scores based on less consumption of seven unhealthful foods and nutrients. Bottom: changes in dietary pattern scores based on both healthful and unhealthful foods and nutrients. Values represent degrees of adherence to each dietary pattern, ranging from 0 (least healthful) to 100 (most healthful). Scores in 1990 were standardised to age and sex distribution in 2010.

References

    1. Lim SS, Vos T, Flaxman AD. A comparative risk assessment of burden of disease and injury attributable to 67 risk factors and risk factor clusters in 21 regions, 1990-2010: a systematic analysis for the Global Burden of Disease Study 2010. Lancet. 2012;380:2224–2260.
    1. Lopez AD, Mathers CD, Ezzati M, Jamison DT, Murray CJL. In: Global Burden of Disease and Risk Factors. Lopez AD, Mathers CD, Ezzati M, Jamison DT, Murray CJL, editors. The International Bank for Reconstruction and Development/The World Bank Group; Washington, DC: 2006. Measuring the global burden of disease and risk factors, 1990–2001.
    1. De Onis M, Blössner M, Borghi E, Frongillo EA, Morris R. Estimates of global prevalence of childhood underweight in 1990 and 2015. JAMA. 2004;291:2600–2606.
    1. Lozano R, Naghavi M, Foreman K. Global and regional mortality from 235 causes of death for 20 age groups in 1990 and 2010: a systematic analysis for the Global Burden of Disease Study 2010. Lancet. 2012;380:2095–2128.
    1. Keats S, Wiggins S. Future diets: implications for agriculture and food prices. The Overseas Development Institute; London: 2014.
    1. Hawkes C. Uneven dietary development: linking the policies and processes of globalization with the nutrition transition, obesity and diet-related chronic diseases. Global Health. 2006;2:4.
    1. Vandevijvere S, Monteiro C, Krebs-Smith SM. Monitoring and benchmarking population diet quality globally: a step-wise approach. Obes Rev. 2013;14:135–149.
    1. Lachat C, Otchere S, Roberfroid D. Diet and physical activity for the prevention of noncommunicable diseases in low- and middle-income countries: a systematic policy review. PLoS Med. 2013;10:e1001465.
    1. Ezzati M, Riboli E. Behavioral and dietary risk factors for noncommunicable diseases. N Engl J Med. 2013;369:954–964.
    1. Monteiro CA, Moubarac J-CC, Cannon G. Ultra-processed products are becoming dominant in the global food system. Obes Rev. 2013;14:21–28.
    1. Kennedy G, Nantel G, Shetty P. Globalization of food systems in developing countries: impact on food security and nutrition. FAO Food Nutr Pap. 2004;83:1–300.
    1. Basu S, Yoffe P, Hills N, Lustig RH. The relationship of sugar to population-level diabetes prevalence: an econometric analysis of repeated cross-sectional data. PLoS One. 2013;8:e57873.
    1. Vandevijvere S, Monteiro C, Krebs-Smith SM. Monitoring and benchmarking population diet quality globally: a step-wise approach. Obes Rev. 2013;14:135–149.
    1. Contribution O, Teo K, Lear S. Prevalence of a healthy lifestyle among individuals with cardiovascular disease in high-, middle- and low-income countries: the Prospective Urban Rural Epidemiology (PURE) study. JAMA. 2013;309:1613–1621.
    1. Powles J, Fahimi S, Micha R. Global, regional and national sodium intakes in 1990 and 2010: a systematic analysis of 24 h urinary sodium excretion and dietary surveys worldwide. BMJ Open. 2013;3:e003733.
    1. Micha R, Khatibzadeh S, Shi P. Global, regional, and national consumption levels of dietary fats and oils in 1990 and 2010: a systematic analysis including 266 country-specific nutrition surveys. BMJ. 2014;348:g2272.
    1. Micha R, Kalantarian S, Wirojratana P. Estimating the global and regional burden of suboptimal nutrition on chronic disease: methods and inputs to the analysis. Eur J Clin Nutr. 2012;66:119–129.
    1. Khatibzadeh S, Micha M, Afshin A, Rao M, Yakoob MY, Mozaffarian D. Major dietary risk factors for chronic diseases: a systematic review of the current evidence for causal effects and effect Sizes. Circulation. 2012;125:AP060.
    1. World Bank World Development Indicators. 2013. (accessed Aug 24, 2014).
    1. Willett WC. In: Nutritional Epidemiology. 3rd edn. Willett WC, editor. Oxford University Press; New York: 2012. Implications of Total Energy Intake for Epidemiologic Analyses; pp. 260–286.
    1. Barendregt JJ, Van Oortmarssen GJ, Vos T, Murray CJ. A generic model for the assessment of disease epidemiology: the computational basis of DisMod II. Popul Health Metr. 2003;1:4.
    1. Diez-Roux AV. Multilevel analysis in public health research. Annu Rev Public Health. 2000;21:171–192.
    1. Gelman A, Rubin DB. Inference from iterative simulation using multiple sequences. Stat Sci. 1992;7:457–472.
    1. World Cancer Research Fund/American Institute for Cancer Research . Food, Nutrition, Physical Activity, and the Prevention of Cancer: a Global Perspective. American Institute for Cancer Research; Washington, DC: 2007.
    1. Mozaffarian D. In: Braunwald's Heart Disease: A Textbook of Cardiovascular Medicine. 9th edn. Bonow RO, Mann DL, Zipes DP, Peter L, editors. Elsevier; Philadelphia: 2011. Nutrition and cardiovascular disease; pp. 996–1007.
    1. Murray CJ, Lopez AD. Global mortality, disability, and the contribution of risk factors: Global Burden of Disease Study. Lancet. 1997;349:1436–1442.
    1. McNeill S, Van Elswyk ME. Red meat in global nutrition. Meat Science. 2012;92:166–173.
    1. Carmichael SL, Yang W, Feldkamp ML. Reduced risks of neural tube defects and orofacial clefts with higher diet quality. Arch Pediatr Adolesc Med. 2012;166:121–126.
    1. Rodríguez-Bernal CL, Rebagliato M, Iñiguez C. Diet quality in early pregnancy and its effects on fetal growth outcomes: the Infancia y Medio Ambiente (Childhood and Environment) Mother and Child Cohort Study in Spain. Am J Clin Nutr. 2010;91:1659–1666.
    1. Darmon N, Drewnowski A. Does social class predict diet quality? Am J Clin Nutr. 2008;87:1107–1117.
    1. Trichopoulou A, Naska A, Costacou T. Disparities in food habits across Europe. Proc Nutr Soc. 2002;61:553–558.
    1. Lock K, Stuckler D, Charlesworth K, McKee M. Potential causes and health effects of rising global food prices. BMJ. 2009;339:b2403.
    1. Ohiorhenuan JFE, Stewart F. United Nations Development Programmeme. Post-Conflict Economic Recovery Enabling Local Ingenuity. United Nations Publications; New York: 2008. The legacies of armed conflict; pp. 14–47.
    1. Monteiro CA, Moubarac J-CC, Cannon G. Ultra-processed products are becoming dominant in the global food system. Obes Rev. 2013;14:21–28.

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