Are Unhealthy Diets Contributing to the Rapid Rise of Type 2 Diabetes in India?

The prevalence of diabetes is increasing at an alarming rate globally, particularly in India. In the urban areas, the prevalence of diabetes among adults aged ≥20 y, which was around 2% in the early 1970's, has increased by >20% in 50 y. The rapid nutrition transition due to high economic growth rates increased urbanization and globalization has resulted in higher intakes of processed refined grain staples, mainly white rice in Southern and Eastern India and refined wheat in Northern and Western India. This coupled with inadequate quantity and quality of protein; unhealthy fats; lower intake of vegetables, fruits, and fiber; and a sedentary lifestyle are the main drivers of the diabetes epidemic in India. This review attempts to discuss both the quality and quantity of Indian diets with specific reference to macronutrients. This review also outlines some of the strategies that can be employed to slow down the diabetes epidemic in this region. We believe that the lessons learned from India would be applicable to other developing nations as well, particularly to the South East Asian region.

Development and validation of the Asian Diabetes Quality of Life (AsianDQOL) Questionnaire.

AIM: To construct a type-2 diabetes specific quality of life (QOL) tool for Asian populations that is valid and reliable across different ethnicities, languages, and socio-economic backgrounds. METHODS: A focus group determined the domains affecting QOL in consultation with an expert group. A pilot study was conducted to validate the Asian Diabetes QOL (AsianDQOL) in English, Malay and Chinese-Mandarin. The World Health Organization Brief Quality of Life Questionnaire (WHOQOL-BREF) was used for comparison. Exploratory factor analysis (EFA), reliability analysis (RA) using Cronbach's alpha, test-retest reliability, and confirmatory factor analysis (CFA) using structural equation modeling (SEM) was undertaken using the statistical software IBM SPSS Statistics version 20. RESULTS: EFA with eigenvalues (>1) and factor loadings ≥0.3 for English and Malay language demonstrated 21 items (5 components). CFA (English version) confirmed the model (CMIN 201.08, p-value 0.071, GFI 0.88, RMSEA 0.036, CFI 0.978). CFA (Malay version) confirmed the 5-factor model (CMIN 189.39, p-value 0.085, GFI 0.937, RMSEA 0.025, CFI 0.987). The Cronbach's alpha scores (English version) were 0.917, 0.818, 0.816, 0.749 and 0.719, respectively. The Malay version scored 0.833, 0.819, 0.816, 0.775, 0.673, respectively, whilst the Chinese/Mandarin version scored 0.890, 0.719, 0.826, 0.862 and 0.759, respectively. Test-retest reliability showed Pearson correlation of 0.600 (English version), 0.700 (Malay version) and 0.500 (Chinese-Mandarin version). A scoring system was generated based on the 25th, 50th and 75th centiles for all the three languages. CONCLUSION: The AsianDQOL is a valid, reliable and stable tool for assessing QOL in multi-ethnic and multi-lingual T2DM Asian populations.