Dietary quality of postmenopausal Chinese women in Kuala Lumpur - PowerPoint PPT Presentation

Dietary quality of postmenopausal Chinese women in Kuala Lumpur and Selangor CHAN KS, CHAN YM, CHIN YS, ZALILAH MS , LIEU KH, & LIM SY

Introduction • Dietary Quality Index (DQI) had been used to assess the adherence to dietary guideline, and measure the adequacy of an individual overall diet toward food groups (Nicklas, O’Neil, & Fulgoni, 2012). • Studies on DQI among older Malaysian, especially among the postmenopausal Chinese women, which has the longest longevity, is scarce.

Objective • To determine the dietary quality among postmenopausal Chinese women

Methodology • Cross-sectional study • 220 postmenopausal women were recruited • Seven affiliates under the National Council of Senior Citizens Organizations Malaysia (NACSCOM)

Assessment on Diet Quality • Number of serving for 9 food components were ascertained by Semi-quantitative Food Frequency Questionnaire (sFFQ) • Number serving for each food component was calculated and scored according to Healthy Eating Index for Malaysia (HEI-M) (Lee, Norimah, & Safiah, 2011).

Component and Scoring Criteria of HEI Criteria for Criteria for Criteria for Component Score Range Maximum Minimum Score of 8 Score of 10 Score of 0 Cereals & Grains 0 - 10 4 - 8 servings 0 serving Vegetables 0 - 10 3 servings 0 serving Fruits 0 - 10 2 servings 0 serving Poultry, Meat & 0 - 10 ½ - 2 servings 0 serving Eggs Fish 0 - 10 1 serving 0 serving Legumes 0 - 10 ½ - 1 serving 0 serving Milk & Dairy 0 - 10 1 - 3 servings 0 serving Products Percentage of ≤ 30% energy ≥ 35% energy Energy from Total 0 - 10 from fat from fat Fat Sodium 0 - 10 ≤ 2000 mg 2400 mg ≥ 4200 mg

Overall diet quality  Computed by adding the score for each component to give a composite score with the following formula: (total score of 9 components / 9 × 10) × 100%  Classified into: Poor Improvement Good Required < 51% 51% - 80% ≥ 81% (Lee, Norimah & Safiah, 2011)

Result Cereal & Grains 3.98±1.65 Milk & Dairy Vegetables 0.11 (0.50) Products 2.49±1.58 1.93±1.70 Legume 0.39±0.41 Fruits 1.61±1.05 0.66 (0.79) Poutlry, Meat & Fish Egg Figure 1 Number of servings for food groups

Discussion • In general, the respondents met the dietary recommendation for: cereal and grains, fruits, poultry, meat and egg, % of energy from total fat, Na intakes • Failed to meet the recommendation for vegetables, fish, legumes and milk and dairy products.

Result Cereal & Grains 10.00 (0.00) 6.93±2.44 Sodium intake Vegetables 6.88±2.93 Percentage of Fat Fruits 6.70±3.24 10.00 (0.00) 1.9±2.74 Milk & Dairy Poutlry, Meat & Egg Products 10.00 (1.50) 4.23±3.39 6.28±3.54 Legume Fish Figure 2 Component Score for food groups

Result 100.00 95.9 90.00 80.00 84.9 76.7 70.00 71.2 Percentage (%) 70.3 68.9 66.2 60.00 50.00 40.00 30.00 33.8 31.1 29.7 28.8 20.00 23.3 10.00 15.1 4.1 0.00 CEREAL & VEGETABLES FRUITS POULTRY, FISH LEGUMES MILK & GRAINS MEAT & EGG DAIRY PRODUCTS Adequate Intake Inadequate Intake Figure 3 Proportion of food group intake

Discussion (cont.) • There were relatively higher proportion of respondents with adequate intake of Poultry, meat and egg (PME) group , due to availability and affordability • Norimah et al. (2008) reported that approximately 12% of the Malaysia population consumed egg daily with mean frequency of 1.15 egg every day.

Discussion (cont.) • <5% of the respondents had adequate intakes of dairy products , this was in-line with the earlier data that only 0.11 serving of milk and dairy products were consumed daily • Attributed to Malaysian are not habitual milk and dairy products consumers ; recall bias may underestimate the number of serving for milk and dairy products consumed

Result (cont.) Poor Good (24) 10.9% Overall mean (3) 1.4% dietary score: Need 61.11±9.08 Improvement (192) 87.3% *1 person did not complete FFQ Figure 4 Classification of overall dietary quality

Discussion (cont.) • overall dietary score in the present study was comparable to the study conducted in Hong Kong among older people (Chan et al., 2015) and Brazil among postmenopausal women (Ventura et al., 2014), • but higher than several studies conducted in US (Hamidi, Tarasuk, Corey, & Cheung, 2011;Qiao et al., 2014; Vargas et al., 2016) and Brazil (Tardivo et al., 2010) among postmenopausal women.

Discussion (cont.) • This may due to diet of respondents in present study was low in sodium and fat, and relatively high in protein, fruits and vegetables, which is similar to a healthy dietary pattern (Tayyem et al., 2018) • However, similar dietary quality score can be yield from several different dietary profile (Nicklas, O’Neil, & Fulgoni, 2012)

Discussion (cont.) • For example, a score of 50 can be yield from a different combination of the nine components of DQI (Nicklas , O’Neil, & Fulgoni, 2012). • Individual with high whole grains, fruits and vegetables intake, and low in poultry and fish intake may have a similar score with individual with high refined grains, and poultry and fish intake, but low in fruits and vegetables intake.

Discussion (cont.) • Current DQI and components may be unable to fit into the dietary requirement, and unable to assess the dietary quality of the older population (Hengeveld et al., 2018) • These may serve as a limitation in assessing the DQI of population, as well as the association with risk of morbidity and mortality.

Conclusion • Majority of the postmenopausal Chinese women required improvement on dietary quality, • special attention to be addressed on the number of serving for vegetables, fish, legumes, and especially milk and dairy products • The revision or development of DQI for older person is recommended

References Elwood, P. C., Pickering, J. E., Ian Givens, D., & Gallacher, J. E. (2010). The consumption of milk and dairy foods and the incidence of vascular disease and diabetes: An overview of the evidence. Lipids , 45 (10), 925 – 939. https://doi.org/10.1007/s11745- 010-3412-5 Hamidi, M., Tarasuk, V., Corey, P., & Cheung, A. M. (2011). Association between the Healthy Eating Index and bone turnover markers in US postmenopausal women aged ≥45 y. American Journal of Clinical Nutrition . https://doi.org/10.3945/ajcn.110.009605 Hengeveld, L. M., Wijnhoven, H. A., Olthof, M. R., Brouwer, I. A., Harris, T. B., Kritchevsky , S. B., … Visser, M. (2018). Prospective associations of poor diet quality with long-term incidence of protein-energy malnutrition in community-dwelling older adults: the Health, Aging, and Body Composition (Health ABC) Study. The American Journal of Clinical Nutrition , 107 (2), 155 – 164. https://doi.org/10.1093/ajcn/nqx020

References Institute for Public Health (2015). National Health and Morbidity Survey (2015). Kuala Lumpur, Malaysia: Ministry of Health. Lee TT, Norimah AK, Safiah MY. B17. Development of Healthy Eating Index (HEI) for Malaysian adults. Proceedings of 26th Scientific Conference of the Nutrition Society of Malaysia; 2011 March 24-25; Kuala Lumpur. Kuala Lumpur: Nutrition Society of Malaysia; 2011.18. Nicklas , T. A., O’Neil, C. E., & Fulgoni, V. L. (2012). Diet Quality Is Inversely Related to Cardiovascular Risk Factors in Adults. Journal of Nutrition , 142 (12), 2112 – 2118. https://doi.org/10.3945/jn.112.164889

References Norimah, A. K., Safiah, M., Jamal, K., Siti, H., Zuhaida, H., Rohida , S., … Azmi, M. Y. (2008). Food consumption patterns: Findings from the Malaysian Adult Nutrition Survey (MANS). Malaysian Journal of Nutrition , 14 (1), 25 – 39. Retrieved from http://nutriweb.org.my/publications/mjn0014_1/mjn14n1_art2.pdf Park, S.-J., Joo, S.-E., Min, H., Park, J. K., Kim, Y., Kim, S. S., & Ahn, Y. (2012). Dietary Patterns and Osteoporosis Risk in Postmenopausal Korean Women. Osong Public Health Res Perspect , 3 (4), 199 – 205. https://doi.org/10.1016/j.phrp.2012.10.005 Qiao, Y., Tinker, L., Olendzki, B. C., Hébert, J. R., Balasubramanian, R., Rosal, M. C., … Ma , Y. (2014). Racial/Ethnic disparities in association between dietary quality and incident diabetes in postmenopausal women in the United States: The Women’s Health Initiative 1993-2005 NIH Public Access. Ethn Health , 19 (3), 328 – 347. https://doi.org/10.1080/13557858

References Tardivo, A. P., Nahas-Neto, J., Nahas, E. A., Maesta, N., Rodrigues, M. A., & Orsatti, F. L. (2010). Associations between healthy eating patterns and indicators of metabolic risk in postmenopausal women. Nutrition Journal , 9 , 64. https://doi.org/10.1186/1475-2891-9-64 Tayyem, R. F., Al-Shudifat, A. E., Johannessen, A., Bawadi, H. A., AbuMweis, S. S., Agraib , L. M., … Azab, M. (2018). Dietary patterns and the risk of coronary heart disease among Jordanians: A case – control study. Nutrition, Metabolism and Cardiovascular Diseases , 28 (3), 262 – 269. https://doi.org/10.1016/J.NUMECD.2017.10.026 Ventura, D. D. A., Fonseca, V. D. M., Ramos, E. G., Marinheiro, L. P. F., De Souza, R. A. G., De Miranda Chaves, C. R. M., & Peixoto, M. V. M. (2014). Association between quality of the diet and cardiometabolic risk factors in postmenopausal women. Nutrition Journal , 13 (1). https://doi.org/10.1186/1475- 2891-13-121

Thank You