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The Elderly Nutrient Density Study Nicola Lauren Winter A thesis submitted in partial fulfilment of the requirements for the degree of Master of Dietetics At the University of Otago, Dunedin, New Zealand June 2013 Abstract Background: Life expectancy is improving and birth rates slowing, causing an increase in the population over 65 years of age. As a result of different lifetime exposures to risk factors causing disease manifestations, and medication use, this age group is a very heterozygous age group. Adequate nutrition is essential for good health at all ages and plays a role in the prevention and treatment of non-communicable diseases associated with ageing. Total energy intake declines, the prevalence of nutritional inadequacies increases, and diet quality may decline with age. The inclusion of nutrient dense foods in the diet is currently recommended, but there is no standard definition of nutrient density, or index by which to assess the nutrient density of single foods or whole diets. Therefore examination of the nutrient density of the older New Zealand population is essential to determine the quality of food choices and overall diets. Objective: The three objectives of this study were: 1) to examine nutrient density scores of the diets of older New Zealanders 71 years and over (≥ 71 years) in comparison to other age categories 2) To examine the relationships between nutrient density scores and demographic variables for older New Zealanders 3) To discuss the implications of these results in relation to current recommendations for older New Zealanders. Design: We analysed nationally representative, cross-sectional data from the 2008/09 Adult Nutrition Survey (ANS). Nutrient density scores were calculated for all ANS participants. Mean comparison tests were performed across the 5 age categories to identify differences in nutrient density. Linear regression was performed to determine whether demographic variables were related to nutrient density scores. Results for each nutrient were ii interpreted alongside Estimated Average Requirement (EAR) and percentage of inadequate intakes to formulate food based recommendations suitable for older New Zealanders. Results: Mean zinc nutrient density scores were significantly higher for age category 5 (≥ 71 years) than age category 1 (15-18 years). Mean calcium, selenium and vitamin B6 nutrient density scores were all significantly higher for age category 5 than age categories 1 and 2 (19-30 years). Mean vitamin A nutrient density scores were higher for age category 5 than age categories 1, 2 and 3 (31-50 years). Both mean thiamin and riboflavin nutrient density scores were significantly higher in age category 5 than all other age categories. Vitamin B12 nutrient density was similar across all age categories. No demographic variable was related to all eight nutrient density scores, but some relationships between demographic variables and nutrient density scores were found. Conclusion: Diet quality of older New Zealanders is as good if not better than younger New Zealanders. Therefore, older adults make good food choices but do not eat adequate total energy to maintain nutritional status. Consequently, recommendations for the careful selection of foods to be consumed from each food group have been suggested to maximise the nutrient density of older New Zealanders diets and address the high prevalence of nutritional inadequacies. Key Words: Adult Nutrition Survey, New Zealand, Nutrient Density, Diet Quality, Elderly. iii Preface The New Zealand Ministry of Health funded the 2008/09 New Zealand Adult Nutrition Survey. The New Zealand Crown is the owner of the copyright for the survey data. The results presented in this paper are the work of the authors. The ANS was a nationally representative, cross-sectional survey of 4721 free living New Zealand adults 15 years and over. Data was collected between 27 October 2008 and the 28 October 2009. Data collected included data on dietary intakes, eating patterns, food security, supplement use, blood pressure, body size and biochemical indices. This survey provided sound data for 1065 adults ≥ 71 years to be used to examine the nutrient density of older New Zealanders’ diets. This thesis contains work from August 2012 till June 2013, and was submitted in partial fulfilment of the requirements for the degree of Master of Dietetics at the University of Otago. As a Master of Dietetic candidate I was responsible for the following: Study idea progression Nutrient density calculations All statistical analyses Interpretation of the data/results Write up of all sections of thesis Professor Christine Thomson and Associate Professor Winsome Parnell supervisors of this project were responsible for the development of the study idea, gaining permission to use the ANS data and overseeing the completion of the study and thesis write up. iv Acknowledgements Many people have contributed to the final product of this thesis in their own unique way. I would like to thank my supervisors Professor Christine Thomson and Associate Professor Winsome Parnell for their on-going support, patience, thoughts and ideas that have proven to be invaluable additions to my thesis, Dr Jill Hazard for her assistance with the statistical side of things and all those involved in the ANS, both participants and staff for providing a sounds dataset for me to work with. Also a special thanks to…. My fellow Master of Dietetics peers for 2013 who have provided support and light relief on tap throughout this challenging process My family and friends who have provided support, encouragement, ideas, direction and distractions exactly when I have needed it And last but certainly not least my partner Drew who has supported me in every way possible, kept a smile on my face and made my difficult days brighter throughout this whole research experience. v List of Tables Table 2.1 Change in RDIs1 of males 51-70 and >70 years compared to 31-50 year olds ...................... 9 Table 2.2 Change in RDIs1 of females 51-70 and >70 years compared to 31-50 year olds................... 9 Table 2.3 Nutritional adequacy of the older New Zealand population from the Adult Nutrition Survey1 ............................................................................................................................................................... 10 18 Table 5.1 Demographic (n (%)) and anthropometric (mean (SE)) data of participants ≥71 years from the Adult Nutrition Survey1 ................................................................................................................... 30 Table 5.2 Crude nutrient intakes (mean (SE)) of participants ≥71 years from the Adult Nutrition Survey1................................................................................................................................................... 31 30 Table 5.3 Comparison of mean (SE) micronutrient density scores for all participants from the Adult Nutrition Survey1 ................................................................................................................................... 31 Table 5.4 Comparison of mean (SE) micronutrient density scores for males from the Adult Nutrition Survey1................................................................................................................................................... 32 Table 5.5 Comparison of mean (SE) micronutrient density scores for females from the Adult Nutrition Survey1................................................................................................................................................... 33 Table 5.6 Linear regression for demographic variables and vitamin A density scores (µgRE/MJ) for participants ≥ 71 years from the Adult Nutrition Survey1..................................................................... 36 Table 5.7 Linear regression for demographic variables and thiamin density scores (mg/MJ) for participants ≥ 71 years from the Adult Nutrition Survey1..................................................................... 37 Table 5.8 Linear regression for demographic variables and riboflavin density scores (mg/MJ) for participants ≥ 71 years from the Adult Nutrition Survey1..................................................................... 38 Table 5.9 Linear regression for demographic variables and vitamin B6 density scores (mg/MJ) for participants ≥ 71 years from the Adult Nutrition Survey1..................................................................... 39 Table 5.10 Linear regression for demographic variables and vitamin B12 density scores (µg/MJ) for participants ≥ 71 years from the Adult Nutrition Survey1..................................................................... 40 Table 5.11 Linear regression for demographic variables and calcium density scores (mg/MJ) for participants ≥ 71 years from the Adult Nutrition Survey1..................................................................... 41 Table 5.12 Linear regression for demographic variables and zinc density scores (mg/MJ) for participants ≥ 71 years from the Adult Nutrition Survey1..................................................................... 42 vi Table 5.13 Linear regression for demographic variables and selenium density scores (µg/MJ) for participants ≥ 71 years from the Adult Nutrition Survey1..................................................................... 43 Table 8.1 Calculated reference nutrient density indices for males and females ≥71 years using “Cutpoint approach”1 ................................................................................................................................... 65 Table 8.2 Number of participants meeting reference nutrient density indices calculated by “Cut-point approach”1 ............................................................................................................................................ 65 Table 8.3 Calculated nutrient density indices for males and females ≥ 71 years calculated by EAR/EER ............................................................................................................................................................... 66 Table 8.4 Number of participants meeting reference nutrient density indices calculated by EAR/EER ............................................................................................................................................................... 66 vii List of Figures Figure 2.1 Median energy intake across age groups from 1997 National Nutrition Survey ................... 9 Figure 2.2 Median energy intakes across age groups from 2008/09 Adult Nutrition Survey................. 9 viii List of Abbreviations AI Adequate Intake ANS Adult Nutrition Survey BMI Body Mass Index BMR Basal Metabolic Rate DFE Dietary Folate Equivalents EAR Estimated Average Requirement EER Estimated Energy Requirement NNS National Nutrition Survey NRVs Nutrient Reference Values NZFCD New Zealand Food Composition Database RDA Recommended Dietary Allowance RDI Recommended Dietary Intake SES Socioeconomic Status ≥ 71 years 71 Years and over (Age category 5 in the Adult Nutrition Survey) ix Table of Contents Abstract ....................................................................................................................................... ii Preface ........................................................................................................................................ iv Acknowledgements ...................................................................................................................... v List of Tables ............................................................................................................................... vi List of Figures ............................................................................................................................ viii List of Abbreviations .................................................................................................................... ix 1 Introduction ......................................................................................................................... 1 2 Literature Review ................................................................................................................. 3 2.1 Ageing Population ........................................................................................................ 3 2.2 Physiological Changes That Affect Nutritional Status ..................................................... 3 2.2.1 Body Compositional Changes ............................................................................................ 4 2.2.2 Gastrointestinal Function .................................................................................................. 5 2.2.3 Drug-Nutrient Interactions ................................................................................................ 6 2.3 Non-Physiological Factors Affecting Nutritional Status ................................................... 6 2.4 Energy Content of Older Populations Diet ..................................................................... 7 2.5 The 2008/09 Adult Nutrition Survey .............................................................................. 8 2.6 The Current Nutritional Status of New Zealand Older Adults ........................................ 10 2.6.1 Vitamin E ......................................................................................................................... 10 2.6.2 Vitamin D ......................................................................................................................... 10 2.6.3 Folate ............................................................................................................................... 11 2.6.4 Vitamin A ......................................................................................................................... 12 2.6.5 Thiamin ............................................................................................................................ 12 x 2.6.6 Riboflavin ......................................................................................................................... 13 2.6.7 Vitamin B6 ....................................................................................................................... 13 2.6.8 Vitamin B12 ..................................................................................................................... 14 2.6.9 Calcium ............................................................................................................................ 15 2.6.10 Iron .............................................................................................................................. 15 2.6.11 Zinc .............................................................................................................................. 16 2.6.12 Selenium...................................................................................................................... 17 2.7 Nutrient Density ......................................................................................................... 17 2.8 Reference Nutrient Density Index ............................................................................... 18 3 Objective Statement ........................................................................................................... 20 4 Participants and Methods ................................................................................................... 22 4.1 Study Design of Adult Nutrition Survey ....................................................................... 22 4.1.1 Sampling Frame ............................................................................................................... 22 4.1.2 Data Collection ................................................................................................................ 22 4.1.3 Dietary Data Collection.................................................................................................... 23 4.1.4 Food to Nutrient Conversion ........................................................................................... 24 4.1.5 Estimates of Nutritional Inadequacy ............................................................................... 24 4.1.6 Anthropometric Data Collection ..................................................................................... 24 4.2 Study Design of Elderly Nutrient Density Study............................................................ 25 4.2.1 The Elderly Nutrient Density Study Participants ............................................................. 25 4.2.2 Demographic Variables ................................................................................................... 25 4.2.3 Calculation of Nutrient Density Scores ............................................................................ 25 4.2.4 Reference Nutrient Density Index ................................................................................... 26 xi 4.2.5 5 6 Statistical Analyses .......................................................................................................... 26 Results ............................................................................................................................... 28 5.1 Characteristics of Participants ..................................................................................... 28 5.2 Comparison of Mean Nutrient Density Scores Across Age Groups ................................ 28 5.3 Linear Regression of Nutrient Density and Demographic Variables ............................... 34 Discussion and Conclusions ................................................................................................. 44 6.1 Summary of Main Findings.......................................................................................... 44 6.2 Relationship Between Nutrient Density and Demographic Variables ............................ 44 6.3 Micronutrient Status .................................................................................................. 45 6.3.1 Vitamin A Status .............................................................................................................. 45 6.3.2 Thiamin Status ................................................................................................................. 46 6.3.3 Riboflavin Status .............................................................................................................. 46 6.3.4 Vitamin B6 Status ............................................................................................................ 47 6.3.5 Vitamin B12 Status .......................................................................................................... 48 6.3.6 Calcium Status ................................................................................................................. 48 6.3.7 Zinc Status ....................................................................................................................... 49 6.3.8 Selenium Status ............................................................................................................... 49 6.4 Summary of Food Group Examination ......................................................................... 50 6.5 Reference Nutrient Density Index ............................................................................... 50 6.6 Strengths.................................................................................................................... 50 6.7 Limitations ................................................................................................................. 51 6.8 Implications for Future Research ................................................................................. 51 6.9 Conclusion.................................................................................................................. 52 xii 7 Application to Dietetic Practice ........................................................................................... 54 References ................................................................................................................................. 55 8 Appendices ........................................................................................................................ 62 List of Tables .............................................................................................................................. 63 Appendix A............................................................................................................................. 64 Calculated Reference Nutrient Density Index Results and Discussion ......................................... 64 References ................................................................................................................................. 67 xiii 1 Introduction Population ageing is occurring worldwide at alarming rates with life expectancy also increasing (1). For that reason, optimal dietary intakes in older adults are imperative to promote health expectancy throughout the extended life cycle. Therefore the nutritional status of the older population is becoming increasingly of concern. Additionally, because of high rates of medication use and disease manifestations, the older population (over 65 years) is a very dissimilar cohort. Many physiological and non-physiological changes occur with age. Collectively these issues can affect food intake in older adults, make setting nutritional requirements for them difficult, and assessing their nutritional status very challenging (2). It is well established that older adults consume less total energy than adults of all other ages (3), and they have higher risk of many micronutrient inadequacies (4). What is less well established is whether dietary quality parallels this decrease in total energy intake and is the cause of the increasingly prevalent nutritional inadequacies seen in older New Zealanders. Current studies evaluating dietary quality examine the number of nutrients below the Recommended Dietary Allowance (RDA) or a similar measurement decided upon by the investigator (5, 6). However, because it is established that energy declines and nutritional deficiencies are more common in this population, examining dietary quality in this way will always show that dietary quality declines. Therefore, dietary quality is different from dietary nutritional inadequacies, it is the quality of the foods that make up the diet (their nutrient and energy profile), and this needs to be examined separately from nutritional inadequacies. The 2008/09 Adult Nutrition Survey (ANS) began in 2008 and collected dietary information from 4721 (61% weighted response rate) community dwelling New Zealanders (7). This data set provides dietary and lifestyle related information on 1065 adults ≥71years and is the sole data set used in this thesis. 1 This thesis aims to identify whether the nutrient density of the diet (in nutrient/MJ), for specific at risk micronutrients identified in the ANS, declines with age in a representative sample of adults ≥71 years compared to other age categories. Special attention is given to defining nutrient density, enabling one to distinguish between a high quality diet in insufficient amounts and a poor quality diet as the cause of the increasing prevalence of nutritional deficiencies in older New Zealanders. Demographic variables previously shown to relate to dietary quality are also examined to identify areas that could be targeted at the population level to help improve dietary intakes in older New Zealanders. 2 2 Literature Review 2.1 Ageing Population The population is ageing worldwide in both developed and developing countries, attributable to declining birth and death rates (8). Projections show that in New Zealand by the year 2031 between 20 and 22% of the population will be aged 65 years and over, compared with 14% in 2012 (8). Population growth is not expected to slow, with projections rising to over one quarter (22-30%) of the population falling into the 65 years or over age group by 2061 (8). Not only are more adults living past 65 years, but because of declining birth rates, the proportion of the population in the work force supporting them is also decreasing (8). Further, due to technological and medical advances in developed countries, life expectancy is also increasing (1). New Zealand men and women are currently expected to live 14.1 and 17.8 years respectively, after the age of 65 (9). Therefore, at the population level nutritional status of this age group is becoming important for economic reasons, and at the individual level to maintain quality of life throughout these extended years (10). 2.2 Physiological Changes That Affect Nutritional Status Physiological changes occur as we age that affect our nutritional requirements. However, because of differences in exposure to risk factors unique to these changes, they occur at different rates in different individuals. This combined with disease state and medication use evident in the older population result in the over 65 year olds being a very heterogenic cohort. This makes establishing appropriate nutritional requirements and assessing nutritional adequacy in this population problematic (2, 11). If nutrient intakes are not aligned with altered requirements then over or under nutrition will ensue. The effects of this can be seen through the many diseases and complications experienced by the elderly (10). Initially it was thought that by the time adults reached older age (65 years) the cumulative effects of risk factors for non-communicable diseases were inevitable and altering dietary 3 habits to minimise risk factors would not produce the effects seen in younger adults (12). However, it is now well established that non-communicable disease risk factors remain significant and modifying them produces improvements and decreases risk factors even in older individuals (13-15). This verifies the importance of consuming a high quality, healthy diet throughout the lifecycle. 2.2.1 Body Compositional Changes Sarcopenia is the loss of lean body mass and subsequent muscle strength that often occur with ageing (16). Sarcopenia has many causes and is not a direct result of ageing (16). Both amount and quality of protein in the diet have been well-established as modifiable risk factors to delay sarcopenia (17). However, there is discrepancy about appropriate levels to recommend (16). Fat mass increases with age, and redistributes from subcutaneous to abdominal and intramuscular (16, 18). Collectively these changes in body composition contribute to the lower Basal Metabolic Rate (BMR) in the elderly (19, 20). Increasing physical inactivity which occurs with ageing, compounds the loss of lean body mass and further decreases energy requirements (21). This is reflected in lower Estimated Energy Requirements (EER) for adults ≥ 71 years (22). A loss of bone density also occurs with ageing (23). This is more prominent in women than men because of the lower peak bone mass achieved, and oestrogen loss that follows menopause (24, 25). Calcium and vitamin D have been identified as important dietary constituents to delay the loss of bone mass, osteoporosis and its consequences, including increased fracture risk, loss of independence and loss of physical ability (26-29). This is reflected in the New Zealand Nutrient Reference Values (NRVs), specifically the Recommended Dietary Intake (RDI), which increases for women at 50 and men at 70 years (22). Further, due to the diminishing ability of the skin to produce vitamin D with age, and its 4 important role in osteoporosis, the Adequate Intake (AI) increases for New Zealand men and women from 50 years (22). 2.2.2 Gastrointestinal Function As we age many changes occur throughout the entire gastrointestinal system. Changes occur in the oral cavity, including loss of teeth, xerostomia (dry mouth), periodontal disease, odour perception changes and taste changes (11, 23, 30). All of these can decrease and limit dietary choices, decrease enjoyment of eating and increase the risk of inadequate dietary intake in the older population (11, 23). A notable change in gastrointestinal function in a subgroup of the older population is the decreased secretions of gastric acid, intrinsic factor and pepsin known as atrophic gastritis. (31-33). This reduces the bioavailability of calcium, iron, folate and vitamin B12 from food (32). Of these micronutrients vitamin B12 is of most unease because, not only is it less available for absorption, but it is also consumed by bacterial overgrowth resulting from having less stomach acid (19). The National Health and Medical Research Council acknowledge that even though the RDI is not increased, older adults may need to consume more B12 rich foods, B12 fortified foods or supplements to meet the RDI than younger adults, to overcome the effects of atrophic gastritis (22). Constipation is a common complaint in the elderly and is often a complication of diseases or medication, however, there is not one clear physiological cause (34). Constipation is reported subjectively, increasing the difficulty of both diagnosis and treatment (34). Two mechanisms for causing constipation that have been identified are a loss of smooth muscle tone causing reduced peristalsis and pelvic floor muscle dysfunction (34). These mechanisms are often compounded by non-physiological lifestyle factors common in the elderly, such as a low fibre diet and low fluid intake (19). Gastric emptying is also slower in older adults, which 5 can lead to early satiety (35). Both constipation and slowed gastric emptying can negatively influence food intake and consequently nutritional status. 2.2.3 Drug-Nutrient Interactions When prescription drugs are not producing expected results, concomitant food consumption is often blamed (36). This interaction is not often examined in reverse but it can play a large role, especially in the older population where multiple medications are common. Medications can interfere with nutrient absorption or increase nutrient needs, increasing the risk of nutritional deficiencies (30, 37). Alternatively medications can cause nausea, appetite suppression, taste, olfactory or gastrointestinal disturbances, and therefore influence food intake and negatively impact on nutritional status (19, 27, 38). In 2002 Martin et al showed that New Zealanders over 65 years picked up an average of 4.8 prescriptions and an average of 19.7 medication items per annum (39). Unfortunately this study did not control for long term medications that would be prescribed multiple times a year; consequently we cannot estimate the average number of medications this population consume. Further, the study did not include a measure for over the counter medications such as supplements. The ANS found that 25.5% and 44.2% of males and females respectively ≥71 years were regular consumers of supplements (4). As a result of both supplement use and prescription medications there is huge potential for drug-nutrient interactions to occur in the older population. Therefore, minimising medications and being aware of their potential side effects is important to minimise negative effects on food consumption and overall nutritional status. 2.3 Non-Physiological Factors Affecting Nutritional Status Many lifestyle factors (social, economic, environmental, family) may also change with age. Although these do not directly alter nutritional requirements they can impact on dietary intakes (40). Consequently these are important to examine as they could be manipulated to positively influence dietary intake and therefore nutritional status. Cross-sectional studies 6 have identified living arrangements to be a strong predictor of diet quality where older individuals living with their spouse are less likely to have inadequate micronutrient intakes than those in any other living arrangement (6). Moreover, living alone is correlated with increased nutritional risk (41), and an unfavourable Body Mass Index (BMI) (42). One explanation for this is that these individuals are ‘socially isolated’ (41). De Castro et al have identified that the elderly eat their meals with fewer other people present; they also showed that there is a positive correlation between the presence of people and meal size (43). Another association identified was that meals consumed at restaurants and fast food outlets were larger than those consumed at home (43). Therefore, encouraging this population to eat with others or to eat out could be avenues to explore to increase overall intake (44). Other important lifestyle factors that negatively affect food consumption in this population are Socioeconomic Status (SES), no access to a car or limited access to food outlets, limited storage facilities and poor physical and mental health status (40, 41). Evidence of the influence of lifestyle factors on dietary intakes in older New Zealanders is limited, but similar predicting factors of nutrition risk such as being widowed and living alone have been found (45). 2.4 Energy Content of Older Populations Diet It is well established from both cross sectional and longitudinal studies that total energy intake declines with age, and, that older adults have the lowest energy intakes (3, 46-50). The 1997 National Nutrition Survey (NNS) demonstrated that in New Zealand usual energy intake decreased gradually with age for both men and women after 24 years (Figure 2.1) (51). The more recent ANS confirmed that this downwards trend in energy intake is still apparent (Figure 2.2), and clearly demonstrated the extent of the reduction in energy intake, with the oldest age category (≥ 71years) having much lower energy intakes than the preceding age category (51-70 years) for both men (by 1232 KJ) and women (by 1057 KJ) (4). This has 7 important implications in the elderly because, although energy requirements are lower, micronutrients are required in equal if not larger amounts (Tables 2.1.and 2.2) (22). Two possible explanations for decreasing energy intake with ageing can be given; a lower appetite and therefore lower food and total energy intakes (35), or a lower nutrient density due to different dietary choices. It is possible that both these factors play a role in the declining energy intake seen in older New Zealanders. Independent of cause the consequence of a lower energy intake is that a high quality diet must be consumed to obtain all the required macronutrients and micronutrients at adequate levels, to maintain health and nutritional status. 2.5 The 2008/09 Adult Nutrition Survey The ANS was the most recent cross-sectional adult nutrition survey to evaluate the adequacy of the New Zealand population’s food and nutrient intake. It assessed participants’ macronutrient, micronutrient intakes, and their dietary sources, dietary habits, dietary supplement use, food security and nutrition related health outcomes (7). Overall, 4721 people completed the survey (weighted response rate of 61%), with 378 and 480 males in the 51-70 years and ≥ 71 years age categories, respectively, and 517 and 585 females in the 51-70 years and ≥ 71 years age categories, respectively (7). Foods were then matched to the New Zealand Food Composition Database (NZFCD) for calculation of energy and nutrient intakes (7). The results for these participants are the focus of the following summary of the current nutritional adequacy of the older New Zealanders’ diets. 8 14000 Energy Intake (kJ) 12000 10000 8000 6000 Male 4000 Female 2000 0 15-18 19-24 25-44 45-64 65 and over Age groups (Years) Figure 2.1 Median energy intake across age groups from 1997 National Nutrition Survey 14,000 Energy Intakes (kJ) 12,000 10,000 8,000 6,000 Male 4,000 Female 2,000 0 15-18 19-30 31-50 51-70 70 and over Age Groups (Years) Figure 2.2 Median energy intakes across age groups from 2008/09 Adult Nutrition Survey F9 Table 2.1 Change in RDIs1 of males 51-70 and >70 years compared to 31-50 year olds Lower RDI1 No Change in RDI1 Vitamin A Higher RDI1 Riboflavin2 Thiamin Vitamin B63 Niacin Vitamin D4 Vitamin B125 Calcium6 Folate Vitamin C Vitamin E Vitamin K Iron Selenium Zinc Source: National Health and Medical Research Council Nutrient Reference Values for Australia and New Zealand. 2005. (22) 1. Recommended Dietary Intake: The average daily dietary intake level that is sufficient to meet the nutrient requirements of nearly all (97– 98 per cent) healthy individuals in a particular life stage and gender group. 2. Increases at >70 years to 1.6 mg. 3. Increases at >50 years to 1.7 mg. 4. Increases first at > 50 years to 10 µg and further increases at > 70 years and over to 15 µg. 5. Acknowledges that older adults with atrophic gastritis may require larger amounts of B12 rich foods or fortified foods but the RDI remains the same. 6. Increases at > 70 years to 1300 mg. Table 2.2 Change in RDIs1 of females 51-70 and >70 years compared to 31-50 year olds Lower RDI1 No Change in RDI1 Higher RDI1 Iron2 Vitamin A Riboflavin3 Thiamin Vitamin B64 Niacin Vitamin D5 Vitamin B126 Calcium 7 Folate Vitamin C Vitamin E Vitamin K Iron Selenium Zinc Source: National Health and Medical Research Council Nutrient Reference Values for Australia and New Zealand. 2005. (22). 1. Recommended Dietary Intake: The average daily dietary intake level that is sufficient to meet the nutrient requirements of nearly all (97–98 per cent) healthy individuals in a particular life stage and gender group. 2. Decreases at > 50 years to 8 mg. 3. Increases at > 70 years 1.3 mg. 4. Increases at >50 years 1.5 mg. 5. Increases first at > 50 years to 10µg and further increases at >70 years and over to 15µg. 6. Acknowledges that older adults with atrophic gastritis may require larger amounts of B12 rich foods or fortified foods but the RDI remains the same. 7. Increases at > 50 years to 1300 mg. 9 Table 2.3 Nutritional adequacy of the older New Zealand population from the Adult Nutrition Survey1 Age Group (Yrs.) % with Inadequate Intake EAR2/ AI3 Median Intake (95% CI) M F M F 51-70 9158 (8701-9615) 7071 (6777-7365) - - 70+ 7926 (7646-8206) 6014 (5812-6216) - - - - Vitamin A (µgRE) 51-70 825 (712-938) 828 (708-948) 625 500 30.5 8.7* 71+ 851 (779-923) 768 (705-831) 625 500 21.7 12.0 Vitamin C (mg) 51-70 90 (80-100) 97 (87-107) 30 30 6.8 3.0* 71+ 96 (88-104) 89 (82-96) 30 30 2.2* 4.1 Vitamin E (mg) 51-70 10.9 (10.1-11.7) 9.7 (9.1-10.3) 10 7 - - 71+ 10.2 (9.6-10.8) 8.5 (8.1-8.9) 10 7 - - Thiamin (mg) 51-70 1.5 (1.3-1.6) 1.2 (0.9-1.4) 1.0 0.9 20.5 20.5* 71+ 1.4 (1.3-1.5) 1.1 (1.0-1.2) 1.0 0.9 21.3 27.8 Riboflavin (mg) 51-70 2.0 (1.9-2.1) 1.7 (1.6-1.8) 1.1 0.9 6.6 1.3* 71+ 1.8 (1.7-1.9) 1.5 (1.5-1.6) 1.3 1.1 18.7 15.4 Niacin (mg NE) 51-70 36.6 (34.0-39.2) 27.7 (26.4-29.0) 12 11 0.1 0.0 71+ 31.4 (29.8-33.0) 23.3 (22.3-24.3) 12 11 0.0 0.4 Vitamin B6 (mg) 51-70 1.7 (1.6-1.9) 1.4 (1.3-1.5) 1.4 1.3 27.5 36.6 71+ 1.6(1.5-1.7) 1.3 (1.2-1.4) 1.4 1.3 28.8 53.0 Vitamin B12 (µg) 51-70 4.5 (3.6-5.4) 3.4 (2.8-4.0) 2.0 2.0 2.8* 1.1* 71+ 4.2(2.6-5.8) 2.7 (2.2-3.1) 2.0 2.0 3.8* 27.0 Calcium (mg) 51-70 828 (767-889) 737 (687-787) 840 1100 51.6 88.2 71+ 743 (699-787) 676 (632-720) 1100 1100 86 92.8 Iron (mg) 51-70 12.8 (12-13.6) 9.9 (9.4-10.4) 6 5 1.3 0.7 71+ 11.4 (10.8-12.0) 8.9 (8.5-9.3) 6 5 1.3* 2.3* 51-70 11.8 (10.1-13.5) 8.9 (8.4-9.4) 12 6.5 52.0 9.2* 71+ 9.7 (9.2-10.2) 7.6 (7.3-7.9) 12 6.5 89.7 28.3 51-70 61.0 (53.3-68.7) 47.0 (40.8-53.2) 60 50 46.8 55.0 71+ 52.0 (46.3-57.7) 39.5 (36.2-42.8) 60 50 63.8 78.5 Energy (KJ) Zinc (µg) Selenium (µg) M - F - RE, Retinol Equivalents. NE, Niacin Equivalents. Yrs, Years. * Estimate needs to be interpreted with caution due to a high level of imprecision. 1. University of Otago and Ministry of Health. 2011. Methodology Report for the 2008/09 New Zealand Adult Nutrition Survey. Wellington: Ministry of Health (7). 2. EAR: Estimated Average Requirement: A daily nutrient level estimated to meet the requirements of half the healthy individuals in a particular life stage and gender group (22). 3. AI: Adequate Intake (used when an RDI cannot be determined): The average daily nutrient intake level based on observed or experimentally-determined approximations or estimates of nutrient intake by a group (or groups) of apparently healthy people that are assumed to be adequate (22). F10 2.6 The Current Nutritional Status of New Zealand Older Adults From Table 2.3 we can immediately identify numerous micronutrient intakes of concern in older New Zealanders, specifically those ≥ 71 years; vitamin A, thiamin, riboflavin, vitamin B6, vitamin B12, calcium, zinc and selenium. The data demonstrates that as energy intake declines (with increasing age) nutrient inadequacies are generally more prevalent. This highlights the importance of examining nutrient density when assessing the elderly’s dietary intakes, something not well examined in the current New Zealand literature. 2.6.1 Vitamin E Vitamin E is fat soluable and found in 8 forms with varying bioavailability. The primary role of vitamin E is as an antioxidant, helping to protect cell membranes and plasma lipoproteins from oxidative damage (52). The estimated percentage of inadequate intakes for vitamin E cannot be calculated as there is no Estimated Average Requirement (EAR) set for this nutrient (22). This is due to controversy surrounding the issue of the benefits of excess vitamin E beyond requirements for the prevention of chronic disease such as cardiovascular disease, diabetes and some cancers (22, 53, 54) and because deficiency attributable solely to low dietary intakes has not been reported (22). Therefore, the AI was set at the median intakes of the Australia and New Zealand population from 1997 and 1998 national surveys (22). 2.6.2 Vitamin D Vitamin D is found in two forms in foods, both at very low levels (27, 55). Vitamin D status is largely maintained through sun exposure, therefore it was considered inappropriate to estimate adequacy of the population from dietary intakes (7, 27). Thus, serum 25hydroxyvitamin D was used to assess adequacy. The ANS showed that the majority of the population had good vitamin D status (68.1 %) with 27.1% below the recommended level and 4.9% in a deficient state (56). Vitamin D status of New Zealanders 15 years and over did not significantly vary with age or sex, however, a relationship with high levels of deprivation and 10 higher vitamin D deficiency was identified (56). Notably, the age categories in this report are defined differently making these results less comparable to the status of other important nutrients that they influence, in this instance calcium. The elderly are an at risk group for vitamin D deficiency because vitamin D is less efficiently produced in the skin, they spend less time in the sun and are less active whilst in the sun (27, 57). In New Zealand Rockell found only older women had lower serum 25-hydroxyvitamin D (58) demonstrating it is possible to maintain vitamin D status with increasing age if sufficient safe sun exposure is provided. 2.6.3 Folate Folate is found in two forms in food, its natural form, food folate and its fortificant form, folic acid (59). These have different bioavailabilities, therefore, they need to be calculated separately to estimate total Dietary Folate Equivalents (DFE) and accurately assess intake: DFE (µg) = (food folate (µg) + 1.67 x folic acid (µg)) Information on DFE in the NZFCD was considered unreliable because there is no internationally recognized method that measures both folic acid and food folate (7). Values for products were entered based on manufacturers’ labels for folic acid content, however, this was subject to availability of information, so accuracy and completeness may be questionable (7). Therefore, DFE of participants and dietary adequacy could not be accurately estimated. Instead, folate status has been assessed by a combination of serum folate and red blood cell folate which assess short-term and long-term status, respectively (59). Overall, females had better serum folate status than males but red blood cell folate status was similar (4). In addition, females ≥ 71 years had better serum folate status than younger females, except those 51-70 years (4). Both males and females ≥71 years had better red blood cell folate than younger age groups except those aged 51-70 years (4). Therefore, the status of older adults is 11 more than satisfactory but that of the younger age categories, specifically females of child bearing age, demonstrates some concern. 2.6.4 Vitamin A Vitamin A is a fat soluble vitamin found in two forms in the diet; retinol and carotenoids (27, 60). Vitamin A is expressed in retinol equivalents (RE) to control for the different bioactivity of these two forms (61). Vitamin A plays a role in vision, growth, development, reproduction and immune function (60, 61). From the ANS 30.5% and 8.7% (of males and females respectively) aged 51-70 years had inadequate dietary intakes (4). Moreover, the percentage with dietary inadequacy increased in those ≥ 71 years for females (12.0%) and decreased for males (21.0%) (4). This could be attributable to older men consuming more vegetables than younger men. Increasing inadequacy in older females again highlights the difficulty in reaching micronutrient requirements with lower total energy intakes. 2.6.5 Thiamin Thiamin is a coenzyme required for carbohydrate metabolism (59). It also plays a linking role between carbohydrate, fat and protein metabolism (59). Although in the modern world thiamin deficiency is rare, a reasonable proportion of older New Zealanders had inadequate dietary intakes, specifically 20.5% of the population 51-70 years, and 21.3% of males and 27.8% of females ≥ 71 years (4). The EAR for both age groups is the same, therefore, differences in food consumption likely explains the increased dietary inadequacy. However, thiamin is widely distributed in the food supply (59), making it difficult to pin point dietary choices that may explain the increase in inadequate intake. Further, as thiamin requirements are based on energy intake and energy expenditure, perhaps with the lower energy intake and expenditure of older age groups, a lower thiamin intake may be adequate. 12 However, this has not been thoroughly explored, so requirements currently remain the same (22). 2.6.6 Riboflavin Riboflavin is a part of two coenzymes (flavin adenine dinucleotide and flavin mononucleotide) involved in redox reactions within the body and plays a role in the conversions of tryptophan to niacin, methylene-tetrahydrofolate to methyl-tetrahydrofolate and vitamin B6 to its bioactive form pyridoxal-5-phosphate (59). The dietary adequacy of riboflavin is of concern in the older population with 18.7% of males and 15.4% of females ≥ 71 years having inadequate intakes, compared with 6.6% and 1.3% in those aged 51-70 years (4). Riboflavin is widely distributed in foods, with milk and milk products being the richest sources (52). The EAR for riboflavin surprisingly increases with age (22), therefore, this is likely to be the cause of the higher prevalence of inadequacy in adults ≥ 71 years rather than specific dietary choices that substantially compromise riboflavin intake (22). Again this demonstrates the difficulty in obtaining adequate micronutrients with declining total energy intakes. 2.6.7 Vitamin B6 Vitamin B6 is an essential coenzyme for amino acid metabolism. It occurs in three forms which are interconverted within the body, with each of the three forms also occurring with a phosphate attached (27, 59). Pyridoxal-5-Phosphate is the most common form in food and in the body (59). Solo vitamin B6 deficiency is not common; it usually presents alongside other vitamin deficiencies or commonly alongside protein deficiency (59). Vitamin B6 is found in many foods, specifically those unprocessed (27, 59). The current status of New Zealand older adults is of concern, with more than a quarter (27.5%) of males and more than a third of females (36.6%) 51-70 years in the ANS having inadequate dietary intakes (4). The percentage of inadequate dietary intakes increased hugely in females ≥ 71 years to more than 13 half (53.0%) and only slightly increased in males to 28.8% (4). This again identifies the difficulty in achieving nutrient requirements with low total energy intakes. 2.6.8 Vitamin B12 Vitamin B12 is a coenzyme involved in two important processes in the body; catabolism of propionate and synthesis of methionine from homocysteine (27, 59). Vitamin B12 is only found in animal products therefore, strict vegans are at high risk of deficiency and will require supplementation, although body stores are thought to last for 3-6 years (59). Dietary inadequacy at any age is of concern but it may not be the main cause of deficiency in the older population (59). It is thought that malabsorption of vitamin B12 due to gastric atrophy (see section 2.2.2) is the primary cause of deficiency in the older population (30, 59). However, Green et al demonstrated that, although atrophic gastritis increases the risk of having marginal and/or deficient serum vitamin B12 status in older New Zealanders, it does not fully explain the high prevalence of serum vitamin B12 deficiencies (40%) (33). Further, they found that intakes of vitamin B12 from foods reaching the RDI were not necessarily sufficient to protect against deficient and marginal serum vitamin B12 status. Those who reported to consume supplements were less likely to have deficient and marginal serum vitamin B12 status (RR= 0.3 95% CI 0.1-0.8) (33). The ANS demonstrated that vitamin B12 dietary intakes of older New Zealanders were not uniformly of concern, however, in one subgroup (females ≥ 71 years) 27% had inadequate dietary intakes (4). The low percentage of inadequate dietary intakes found in older adults (except women ≥ 71 years) needs to be confirmed from biochemical data to rule out the presence of deficiency resulting from atrophic gastritis. Further, as outlined by Green et al, dietary intakes above the RDI may not be high enough to protect against suboptimal serum vitamin B12, and supplements may be required by a large proportion of the population. This needs to be determined on an individual basis by examining biochemical data (33). 14 2.6.9 Calcium Calcium is required throughout the life cycle to develop and maintain the integrity of the skeleton and is required for neuromuscular and cardiovascular function (62). Calcium is recognised as a key nutrient required at all ages to reach and maintain peak bone mass (26), however, high levels of dietary inadequacies were prominent in the New Zealand population (4). The ANS demonstrated that maintaining adequate dietary calcium became more problematic with age and was more difficult for females (4). The highest dietary inadequacy was in those ≥ 71 years with 86.0% of males and 92.8% of females having inadequate intakes. This is likely to be explained by a combination of factors. In the latest review of the NRVs, that for calcium was increased considerably (22). This was based on some questionable assumptions. Because calcium absorption is thought to be less efficient in the older population, an additional 250 mg was added to the EAR for both men and women (22, 63). Sound evidence exists that women require extra calcium to cover increased urinary losses after menopause, which is why the EAR for women increases at > 50 years (63). However, there is little concluding evidence that older men require increased calcium intakes, and the increase in the EAR for men at >70 years was more a precaution (63). Nevertheless, considering the relationship with inadequate calcium intake and risk of osteoporosis (24), the dietary adequacy of the whole population, specifically those over 50 years, is of concern. If the current EAR is reflective of true requirements, calcium intake may need to be addressed at the public health rather than the individual level. Conversely, it could demonstrate that the EARs are not only unachievable for the majority of the population, but in fact overestimate requirements. 2.6.10 Iron Iron as a part of haemoglobin and myoglobin has major functions of oxygen transportation and oxygen availability for muscle contraction, respectively (64). In food iron is present in two forms; haem iron found in meat, fish and poultry and non-haem iron in most 15 foods. Haem iron is more readily absorbed than non-haem iron because it is protected by the haem molecule (64). Dietary iron intake is difficult to accurately estimate considering the different bioavailability of non-haem iron in different foods. Although older males and females ≥ 71 years had lower iron intakes than younger males (15-50 years) and females (3170 years), the proportion with an inadequate intakes was similar and small in both males (1.3%) and females (2.3%) (4). However, the NZFCD does not account for different bioavailabilities of non-haem iron (7). Nor do they take into account enhancers (vitamin C and meat fish poultry factor) and inhibitors (phytate and polyphenols) of iron absorption. Therefore the percentage of inadequate intake estimates can be considered meaningless and may provide a false sense of security (64). Examining biochemical measures of iron status is essential to provide a more meaningful measure of iron status. 2.6.11 Zinc Zinc is a mineral that plays a vital role as a cofactor for more than three hundred enzymes in the body and is involved in the immune system, growth and transportation processes (52). Zinc is found in foods of animal and plant origin but its bioavailability is substantially higher in animal products, particularly meat (52). Deficiency of zinc can present many symptoms including growth deficiency, impaired wound healing, compromised immune system and loss of taste (52). These are important complications to avoid at all stages of life, but particularly in the elderly, to maintain a high quality of life. Older New Zealanders’ zinc intakes were of concern, particularly in men ≥ 71 years where almost 90% had inadequate intakes (4). Older females ≥ 71 years were also at higher risk than younger females where 28.3% had inadequate intakes compared with 9.2% of those 51-70 years (4). This again highlights the difficulty in meeting nutrient requirements with lower total energy intakes. Further, the estimate of dietary inadequacy could in fact underestimate those with clinical or subclinical zinc deficient states because total zinc intake was assessed and bioavailability was not considered in the values in the NZFCD (7). Therefore, examining 16 biochemical measures of zinc may provide a more meaningful measure of the zinc status of older New Zealanders. 2.6.12 Selenium Selenium is active in the body in the form of selenoproteins which are involved in metabolic processes, the neutralisation of free radicals, and the immune system (65). Selenium adequacy in New Zealand has always been questioned due to the low soil content. Although selenium intakes have improved hugely (66), and trends show status is still improving in both men and women, large proportions of the population are still consuming inadequate amounts. The ANS revealed that almost half of the population 51-70 years had inadequate dietary intakes, increasing to 63.8% of males and 78.5% of females ≥ 71 years (4). The selenium EAR is consistent from 19 years (22), and inadequacy is prominent in all age groups (4), therefore, a low total selenium content of the diet is likely to explain this. Interestingly, imported wheat (with a higher selenium content than NZ grown) is used more frequently by bread manufacturers in the north island than the south island (66). Consequently, dietary selenium intakes of south island elderly may be overestimated because NZFCD values are national averages, not region specific (7, 67). However, bread may be distributed throughout the country from any one manufacturer so this is difficult to control for in a national survey. As a result selenium status, as for zinc, will provide more meaningful results when examined in conjunction with a biochemical measure. 2.7 Nutrient Density Assessment of nutrient intakes in national nutrition surveys is important to evaluate the nutritional status of the population. However, we need to explore more thoroughly to identify food related causes of nutritional inadequacies, and to formulate solutions to address the problems and alleviate them. The common theme emerging from current literature in elderly nutrition is the difficulty in maintaining adequate nutrient intakes with declining energy 17 intakes (4, 51). This demonstrates the importance of assessing nutrient intakes in relation to energy intakes (nutrient density). Nutrient density of foods is thoroughly discussed in the literature and recently recommendations have been made to encourage consumers to increase consumption of nutrient dense foods (68-70). Although current definitions of nutrient density are not consistent, generally ‘nutrient dense foods’ are referred to when discussing foods that provide “substantial amounts of vitamins and minerals and relatively few calories” (71). The earliest definition of nutrient density was in 1973 when nutrient density of a food was defined by Hansen as “the ratio of the nutrient composition of a food to the nutrient requirements of the human”(72). It is clear that consuming foods rich in nutrients is important to maintain adequate nutritional status at all ages. However, it is not well known that if a diet of nutrient poor, energy rich foods is consumed, energy requirements and often satiety may be reached long before the nutrient requirements of the individual are satisfied, and deficiencies will occur (68, 69, 73). Therefore, nutrient density is an important concept because foods consumed have to satisfy both nutrient and energy requirements and assessment of both in conjunction is important (74). 2.8 Reference Nutrient Density Index Many indices to measure nutrient density of foods and/or whole diets are discussed in the literature. However, although studies all compare nutrients to energy in some way, there is no standard definition of ‘nutrient density’ or a criteria list by which foods can be evaluated (68, 75, 76). The current indices representing ‘nutrient density’ have completely different focuses and do not assess single nutrients in relation to energy intakes. For example, some indices focus only on foods with high levels of ‘good’ nutrients such as vitamins, minerals and fibre (77, 78), while others focus on foods having low levels of the ‘bad’ nutrients such as fat, salt and sugar (68). Some approaches focus on both beneficial nutrients and nutrients to 18 limit in the diet (79-82). Even though these indices and endorsement programmes are all attempting to assess ‘nutrient density’, they are based on different combinations of nutrients and serving sizes and do not allow assessment of individual nutrient densities of foods or whole diets. Beaton and Swiss acknowledged the difficulties associated with assessing nutrient density when establishing safe protein calorie ratios, specifically the variability in individual and population energy intakes, the difficulty in establishing nutrient requirements and the relationship between energy and nutrient requirements (83). Hansen and Wyse calculated the expression of nutrient allowances per 1000 kilocalories for each nutrient by dividing the current RDI by the average energy requirements (74). However, they acknowledged that this approach is based on individuals meeting energy requirements, which may not occur in the elderly. Furthermore, Backstrand later agreed that dividing the RDI by the average energy intake for a group of people grossly underestimates the required nutrient density estimate as this does not allow for variation in energy intakes, such as the lower than average energy intakes of the elderly (4, 73). Another method proposed to calculate a reference nutrient density is the “Cut-point approach” which is derived from “The Beaton approach” but a simpler calculation (73). The EAR of a specific nutrient for the subpopulation is divided by the 2.5th percentile of energy intake of that subpopulation. Using the 2.5th percentile of energy intake accounts for those with a lower than average energy intake (73). However, in a population with extremely low energy intakes this could largely overestimate the required nutrient density estimate for the majority of the population. Ideal reference nutrient density indices have not been established. A reference index for each nutrient would enable better critical evaluation of the nutrient density of the diet and assessment of nutrient inadequacies. 19 3 Objective Statement Little information is presented on nutrition in the elderly specific to New Zealand. Therefore, it is essential to thoroughly examine the current nutrient content of older New Zealanders diets. This includes the nutrient density of the diets of the elderly from the ANS compared with other age groups for nutrients which were at high risk of nutritional inadequacy, specifically, vitamin A, vitamin B6, vitamin B12, riboflavin, thiamin, calcium, zinc and selenium (4). Assessment of nutrient density may help distinguish between a high quality diet in insufficient amounts, and a poor quality diet at both the individual and/or population level as the cause of nutritional inadequacies. Recommendations can then be made for individuals that are at nutritional risk, because of low nutrient density, to increase the nutrient density of their diets without unrealistically increasing total energy intake. Further, evidence suggests a relationship between SES and lower overall diet quality in New Zealand. This was apparent in the ANS where females in the highest deprivation quintile were more likely to consume hot chips than those in the lowest deprivation quintile, and both males and females in the highest deprivation quintile were more likely to drink soft drinks compared to those in the lowest deprivation quintile (4). Interestingly, in the ANS elderly people ≥71 years were the least likely to classify themselves as food insecure (4). Therefore, by examining nutrient density in relation to social deprivation levels we can determine whether SES is associated with lower diet quality. It is also important to examine other demographic variables in order to evaluate if they are related to nutrient density of the diets of the elderly and identify potential areas that can be targeted at the public health level to improve the current situation. For this thesis we have defined nutrient density as ‘the ratio of the nutrient content of the diet to the energy intake in MJ’ and we have determined nutrient density of selected 20 nutrients at risk for older New Zealanders. Those identified from the ANS were vitamin A, riboflavin, thiamin, vitamin B6, vitamin B12 calcium, selenium, and zinc. This formulates the primary aims: To establish whether the nutritional inadequacies found in the population ≥71 years result from poor diet quality and food choices, or declining energy intakes. To establish whether nutrient density is related to demographic variables in the elderly New Zealand population ≥71 years. To establish whether improving the nutrient density of the diet of adults ≥71 years is needed, realistic, and would achieve adequacy in this population without substantially increasing their overall energy intake. These will be met by the following objectives: To examine nutrient density scores of the diets of older New Zealanders ≥ 71 years in comparison to other age categories. To examine the relationships between nutrient density scores and demographic variables such as age in years, gender, ethnicity, BMI, waist circumference, SES status (classified by NZ Deprivation index) and living arrangements for older New Zealanders ≥ 71 years. To discuss the implications of these results in relation to current recommendations for older New Zealanders. 21 4 Participants and Methods 4.1 Study Design of Adult Nutrition Survey 4.1.1 Sampling Frame The ANS is the fourth and most recent nationally representative, cross sectional, nutrition survey to be carried out in 4721 community dwelling New Zealand adults (15 years and over) (7). Participation in the study was voluntary. Participants were randomly selected through a three-stage stratified method to ensure the data collected could be extrapolated to reflect the status of the wider New Zealand population (7). The New Zealand Health and Disability Multi-Region Ethics Committee granted ethical approval for the survey. Specific subgroups (Maori, Pacific, younger 15-19 year olds and older adults ≥71 years) were over sampled to allow adequate numbers to provide sound age and ethnicity data (7). Both urban and rural areas were included in the survey. However, those not living in private dwellings were excluded (7). 4.1.2 Data Collection Screening and recruitment took place over the period from 13 October 2008 to 04 October 2009 (84). Data collection took place over a period of 12 months from 27 October 2008 to 28 October 2009 to account for seasonal differences in the food supply. Trained interviewers from the University of Otago collected data from participants in their own homes using the computer assisted personal interview software (LINZ® Electronic Dietary Data Acquisition System (LEDDAS©)) (7). Ethnicity was self-defined with participants allowed to select up to six ethnicities from nine available ethnicities as defined in the 2006 census (85). As a result, comparisons between ethnic groups cannot be made. SES was defined based on the New Zealand Deprivation Index 2006 where people are classified on a 10 point scale by the mesh block in which they reside (86). The 10 point New Zealand deprivation scale 2006 was then sorted into quintiles with quintile 1 representing the 20% of areas with lowest 22 deprivation levels and quintile 5 representing the 20% of areas with the highest deprivation levels (84). Additional SES information was collected at the individual level (income, education, employment status) (7), which may provide a more accurate measure of socioeconomic position than mesh block location for some age groups. Additional questions were included to assess participants’ dietary habits, dietary supplement use, nutrition related health, and food security (7). 4.1.3 Dietary Data Collection Dietary data was collected using a pre-tested, computer assisted multiple-pass-24 hour diet recall (7). This method involves four stages to collect quantitative information on all food and beverages consumed both at home and away from the home in the preceding 24 hours from midnight to midnight (7). The first step was a quick list of foods consumed in the 24 hour period. The second stage collected more detailed descriptions including cooking methods used, recipes for mixed dishes, anything added “to the plate”, brand and product, the time the food was consumed and where it was sourced. The third stage estimated the quantities of all foods, beverages and any supplements consumed using a variety of household measures, food portion assessment aids, shape dimensions, food photographs, and packaging information. The fourth stage involved a review of the diet recall to verify that descriptions and quantities of foods recorded were correct (84). A repeat 24 hour recall was carried out on a subset (25%) of participants to control for day-to-day intra-individual variation and to allow estimations of usual nutrient intakes to be calculated (7). Dietary intake data was collected across all days of the week to control for variation in food consumption from weekdays to weekends. However, this was not quite achieved with Saturday and Sunday being under represented (7). Foods were then classified into one of the 33 pre-defined food groups to allow percentage of food group contributions to energy and micronutrient intakes to be calculated. 23 4.1.4 Food to Nutrient Conversion Food items were then matched to foods in the NZFCD to provide the nutritional content. If foods could not be matched then overseas data was sourced (7). If still no match could be made and the food item was frequently consumed by ANS participants, the New Zealand Institute of Plant and Food Research Ltd analysed the food and the value was added to the NZFCD. If the food was not popularly consumed, the Institute of Plant and Food Research Ltd entered the food item as a recipe from raw foods and approximated its moisture and nutrient retention after cooking. Fortified foods were adjusted in the NZFCD to be consistent with manufacturers’ specifications (7). 4.1.5 Estimates of Nutritional Inadequacy The data was adjusted for day to day variation using PC-side software. The EAR cut point method was used to estimate the adequacy of nutrient intakes within the population, however, could not be calculated for nutrients without an EAR (7). The EAR cut point method could not be used for iron intakes of women 15-50 years because iron requirements are highly skewed as a result of menstruation, therefore, the full probability approach was employed for this subgroup (7). 4.1.6 Anthropometric Data Collection University of Otago trained interviewers undertook height, weight and waist circumference measurements on participants. Repeat measures were taken and if these two measurements differed by more than 1%, a third measure was taken. The two closest measurements were averaged to represent the index for each individual. Height was recorded to the nearest 0.1 cm, weight was recorded to the nearest 0.1kg. BMI was derived from these measurements by using the equation BMI= weight(kg)/(height)2(m) (7).Waist circumference was recorded to the nearest 0.1cm with measurements taken over light clothing at the narrowest point between the iliac crest and the lower costal border. 24 4.2 Study Design of Elderly Nutrient Density Study 4.2.1 The Elderly Nutrient Density Study Participants Of the 4721 participants in the ANS, 480 males and 585 females aged ≥71 years provided dietary intake data and have been included in the subsequent analysis. Of this 454 males (94.6%) and 553 females (94.5%) provided height, weight and BMI measurements, and 449 males (93.5%) and 542 females (93.5%) provided satisfactory waist circumference measurements to be included in the relevant subsequent analysis. 4.2.2 Demographic Variables Information collected on age in years, gender, ethnicity, BMI, waist circumference, SES status (classified by NZ Deprivation index) and living arrangements was used in the elderly nutrient density study. For this study living arrangements was classified into two categories, living alone or living with one or more person, because relationships with higher nutritional risk and living alone have been reported in older men (45). Similarly, prioritised ethnicity was used where participants were classified into one of three groups; Maori, Pacific or Other depending on their preferred identifiable ethnicity (84). 4.2.3 Calculation of Nutrient Density Scores Nutrient density scores were calculated by dividing participants’ intake (from a single recall) of each nutrient (unadjusted for individual variation) by energy intake in mega joules (MJ) as outlined below. Nutrient density score = Nutrient (mg/µg/µgRE)/ Energy (MJ) The purpose of the nutrient density scores was to enable us to look at nutrient density and quality of the diet irrespective of total energy intake. This would help to distinguish between whether the elderly diet is low in a specific nutrient as a result of poor food choices or lower total energy intakes. In this respect the nutrient density score removes energy intake as a confounder of diet quality. The nutrient density scores were calculated for the eight 25 micronutrients that were identified as inadequate from previously discussed ANS data; vitamin A, thiamin, riboflavin, vitamin B6, vitamin B12, calcium, zinc and selenium (See section 2.6.1-2.6.12). 4.2.4 Reference Nutrient Density Index A Reference Nutrient Density Index was calculated for each nutrient by using the ‘Cutpoint Approach’ outlined by Backstrand to estimate the prevalence of inadequate nutrient density in the population. Reference Nutrient Density = EAR/ 2.5th percentile energy intake for subpopulation Another method was employed to calculate a reference nutrient density index for each of the eight micronutrients. The number of participants exceeding these values was then calculated. These results are presented in Appendix 1. 4.2.5 Statistical Analyses The basis of the statistical analysis was to compare nutrient density scores across age groups to determine if nutrient densities were similar throughout the life cycle. Nutrient density scores were then examined alongside demographic variables that may be associated with nutrient intake (and therefore nutrient density) in the elderly. These demographic variables were age in years, gender, ethnicity, BMI, waist circumference, SES status (classified by NZ Deprivation index) and living arrangements. For this project all of the following statistical analyses were carried out using the STATA statistical software package for PC (StataCorp. Stata Statistical Analysis Software release 12.1. Stata Corporation 2011). The relationships between nutrient density scores and age group for the eight micronutrients identified from the ANS as problematic for the ≥71 years age group; calcium, zinc, selenium, vitamin A, thiamin, riboflavin, vitamin B6 and vitamin B12 were examined. Mean nutrient density scores across the five categories of age of the ANS, age category 5 (71 years and over), age category 4 (51-70 years), age category 3 (31-50 years), age category 2 26 (19-30 years), age category 1 (15-18 years) were compared. An adjusted Wald test identified whether the age categories did not have similar mean nutrient density scores. Results are present as mean and linearised standard errors (SE) for each age category. Post Hoc analyses using a Bonferonni adjustment for multiple comparisons were undertaken to determine which of the age categories differed significantly from age category 5 (the oldest age category and age group of interest) in terms of mean nutrient density scores. Statistical significance was determined at =0.05. Data were also stratified for sex to examine if relationships differed for males and females. Relationships between dietary nutrient density scores for the eight problematic nutrients and specific demographic variables age in years, gender, ethnicity, BMI, waist circumference, SES status (classified by NZ Deprivation index) and living arrangements were examined. Both unadjusted and adjusted non-standardised regression coefficients were calculated along with 95% confidence intervals and dna P-values. As the residuals of these analyses were not normal, the nutrient density scores were log-transformed. Both unadjusted and adjusted linear regression results are presented separately for each micronutrient. Significance was determined at =0.05 level and presented at two levels of significance † 0.05-0.01, ‡<0.01. Tests for interaction effects between sex and the other variables showed minimal significant effects, therefore, it was decided not to stratify for sex. 27 5 Results 5.1 Characteristics of Participants Demographic and anthropometric characteristics of the 1065 community dwelling participants in the ≥ 71 years (age group 5) who provided dietary data for the subsequent elderly micronutrient density study are shown in Table 5.1. Crude macronutrient intakes and specific at risk micronutrient intakes are presented in Table 5.2 as mean (Standard Error (SE)) for all participants as well as separately for males and females. 5.2 Comparison of Mean Nutrient Density Scores Across Age Groups Mean comparison tests were performed to determine if age group 5 (≥71 years) had similar nutrient densities to other age groups. Results are presented in Table 5.3 (All participants), Table 5.4 (Males) and Table 5.5 (Females). Table 5.3 shows that for all nutrient density scores except vitamin B12, differences across age categories were significant. Mean zinc nutrient density was higher in age category 5 than age category 1 (15-18years). Mean calcium, selenium and vitamin B6 nutrient density scores were all significantly higher for age group 5 than age categories 1 and 2 (19-30years). Mean vitamin A nutrient density scores were higher for age category 5 than age categories 1, 2 and 3 (31-50 years). Both mean thiamin and riboflavin nutrient density scores were significantly higher in age category 5 than all other age categories. For males, mean zinc nutrient density scores did not remain significant overall or for age category 5 and any other age category (Table 5.4). Mean vitamin B6 nutrient density score remained significant overall but there were no differences between age category 5 and any other age category. Mean thiamin nutrient density remained significantly higher for males in age category 5 than age category 2 and 3, but was no longer higher than age categories 1 and 4 (51-70years). Riboflavin nutrient density scores for males in age category 5 were no longer higher than age 28 category 4, but remained higher than age categories 1, 2 and 3. The only difference between the results for all participants and females was for vitamin B6 nutrient density where there was an overall significant difference among mean vitamin B6 nutrient density and age category, but there was no difference between age category 5 and any other age category (Table 5.5). 29 Table 5.1 Demographic (n (%)) and anthropometric (mean (SE)) data of participants ≥71 years from the Adult Nutrition Survey1 M (n=480) F (n=585) All Participants (n=1065) Age (Years) 77.59 (0.29) 77.58 (0.30) 77.58 (0.21) Weight (kg) 80.80 (0.60) 67.67 (0.67) 73.59 (0.51) Height (m) 170.87 (0.40) 157.54 (0.36) 163.55 (0.35) BMI (kg/m 27.68 (0.21) 27.22 (0.24) 27.43 (0.16) Waist Circumference (cm) 101.45 (0.56) 90.39 (0.63) 95.40 (0.48) Maori 18 (3.75) 29 (5.00) 47 (4.41) Pacific 12 (2.50) 14 (2.39) 26 (2.41) Other 450 (93.75) 542(92.65) 992(93.14) n=454 n=553 n=1007 2 (0.44) 16 (2.90) 18 (1.79) Normal 18.5-24.9 103 (22.69) 184 (33.27) 247 (24.52) Overweight ≥25.0-29.9 229 (50.44) 206 (37.25) 435 (43.20) Obese ≥30.00 120 (26.43) 147 (26.58) 267 (26.51) Quintile 1 103 (21.46) 83 (14.19) 186 (17.46) Quintile 2 81 (16.88) 119 (20.34) 200 (18.78) Quintile 3 92 (19.17) 104 (17.78) 196 (18.40) Quintile 4 113 (23.54) 145 (24.79) 228 (21.41) Quintile 5 91 (18.96) 134 (22.91) 225 (21.13) 167 (34.79) 373 (63.76) 540 (50.70) 313 (65.21) 212 (36.24) 525 (49.30) 2 Ethnicity 2) 3 2 BMI Category Underweight <18.5 NZ Deprivation Index 4 Living Situation Living alone Living with 1 or more person(s) 1. University of Otago and Ministry of Health. 2011. A Focus on Nutrition: Key Finding from the 2008/09 New Zealand Adult Nutrition Survey. Wellington: Ministry of Health (4). 2. BMI= Body Mass Index calculated by Weight (kg)/ (Height (m)) 2. 3. Prioritised ethnicity where participants are classified into one category by their preferred ethnicity (84). 4. New Zealand Deprivation quintile where individuals are classified into quintiles based on the deprivation score of the mesh block in which they reside from the 2006 census (86). F30 Table 5.2 Crude nutrient intakes (mean (SE)) of participants ≥71 years from the Adult Nutrition Survey1 M (n=480) F (n=585) Energy (KJ) 8071 (142) 6121 (103) All Participants (n=1065) 6994 (93) Protein (g) 78.48 (1.68) 61.78 (1.39) 69.25 (1.16) Fat (g) 69.43 (2.05) 52.92 (1.11) 60.31 (1.15) SAFA (g) 26.65 (0.83) 20.46 (0.51) 23.23 (0.49) MUFA (g) 24.96 (0.84) 18.62 (0.45) 21.46 (0.47) PUFA (g) 10.42 (0.36) 8.01 (0.21) 9.09 (0.19) Carbohydrates (g) 228 (4.0) 177(3.2) 200 (2.8) Vitamin A (µgRE) 1210 (205) 841 (39) 1006 (96) Thiamin (mg) 1.57(0.05) 1.19 (0.03) 1.36 (0.03) Riboflavin (mg) 1.94 (0.07) 1.58 (0.04) 1.74 (0.04) Vitamin B6 (mg) 1.62 (0.04) 1.33 (0.04) 1.46 (0.03) Vitamin B12 (µg) 4.80 (0.82) 2.99 (0.18) 3.80 (0.38) Calcium (mg) 784 (23) 709 (19) 743 (16) Selenium (µg) 56.31 (2.69) 41.65 (1.53) 48.21 (1.51) Zinc (mg) 9.84 (0.26) 7.88 (0.21) 8.76 (0.18) SAFA, Saturated Fat. MUFA, Monounsaturated Fat. PUFA, Polyunsaturated Fat. RE, Retinol Equivalents. 1. University of Otago and Ministry of Health. 2011. A Focus on Nutrition: Key Finding from the 2008/09 New Zealand Adult Nutrition Survey. Wellington: Ministry of Health (4). 30 Table 5.3 Comparison of mean (SE) micronutrient density scores for all participants from the Adult Nutrition Survey1 Nutrient Density Scores2 31 Vitamin A density (µgRE/MJ) Thiamin density (mg/MJ) Riboflavin density (mg/MJ) Vitamin B6 density (mg/MJ) Vitamin B12 density (µg/MJ) Calcium density (mg/MJ) Zinc density (mg/MJ) Selenium density (µg/MJ) All Participants Age category 1 (15-18 years) Age category2 (19-30 years) Age category 3 (31-50 years) Age category 4 (51-70 years) Age category 5 (≥ 71 years) Overall P Value 104.13 (2.82) 77.19 (2.25) ‡ 82.21 (3.10) ‡ 98.30 (4.90) ‡ 120.61 (6.14) 146.13 (11.39) <0.001 0.168 (0.002) 0.174 (0.007) ‡ 0.151 (0.006) ‡ 0.160 (0.004) ‡ 0.179 (0.005) ‡ 0.202 (0.004) <0.001 0.230 (0.003) 0.213 (0.006) ‡ 0.216 (0.007) ‡ 0.226 (0.004) ‡ 0.242 (0.005) † 0.258 (0.005) <0.001 0.236 (0.006) 0.262 (0.017) † 0.286 (0.020) ‡ 0.229 (0.010) 0.210 (0.006) 0.215 (0.004) <0.001 0.494 (0.013) 0.438 (0.020) 0.470 (0.022) 0.472 (0.015) 0.543 (0.034) 0.535 (0.045) 0.065 100.50 (1.21) 91.86 (2.01) ‡ 90.13 (2.49) ‡ 102.65 (2.24) 104.31 (2.24) 109.65 (2.01) <0.001 1.256 (0.010) 1.195 (0.023) † 1.203 (0.024) 1.260 (0.016) 1.300 (0.022) 1.273 (0.019) 0.002 6.653 (0.109) 5.626 (0.147) ‡ 5.852 (0.222) ‡ 6.846 (0.208) 7.140 (0.233) 7.001 (0.199) <0.001 † Statistically significant from age group 5 P=0.01-0.05. ‡ Statistically significant from age group 5 P<0.01. RE, Retinol Equivalents. 1. University of Otago and Ministry of Health. 2011. A Focus on Nutrition: Key Finding from the 2008/09 New Zealand Adult Nutrition Survey. Wellington: Ministry of Health (4). 2. Nutrient density scores calculated by crude nutrient intake/energy in MJ. Table 5.4 Comparison of mean (SE) micronutrient density scores for males from the Adult Nutrition Survey1 Nutrient Density Scores2 32 Vitamin A density (µgRE/MJ) Thiamin density (mg/MJ) Riboflavin density (mg/MJ) Vitamin B6 density (mg/MJ) Vitamin B12 density (µg/MJ) Calcium density (mg/MJ) Zinc density (mg/MJ) Selenium density (µg/MJ) All Participants Age category 1 (15-18 years) Age category2 (19-30 years) Age category 3 (31-50 years) Age category 4 (51-70 years) Age category 5 (≥ 71 years) Overall P Value 95.99 (3.78) 69.18 (2.31) † 78.06 (4.71) ‡ 89.69 (4.18) † 106.34 (8.93) 152.90 (24.06) <0.001 0.175 (0.004) 0.189(0.011) 0.166 (0.011) † 0.162 (0.006) ‡ 0.184 (0.008) 0.203 (0.007) <0.001 0.224 (0.003) 0.215 (0.007) ‡ 0.212 (0.010) † 0.215 (0.005) ‡ 0.238 (0.007) 0.249 (0.008) <0.001 0.232 (0.008) 0.254 (0.022) 0.279 (0.029) 0.226 (0.012) 0.208 (0.009) 0.207 (0.005) 0.026 0.499 (0.021) 0.408 (0.022) 0.461 (0.027) 0.453 (0.020) 0.584 (0.059) 0.589 (0.095) 0.022 93.27 (1.42) 89.62 (2.73) † 87.24(3.43) † 92.40 (2.43) 97.69 (3.21) 100.04 (3.11) 0.028 1.258(0.014) 1.204 (0.031) 1.246 (0.037) 1.239 (0.023) 1.317 (0.033) 1.234 (0.022) 0.150 6.577 (0.151) 5.894 (0.220) ‡ 5.544 (0.269) ‡ 6.878 (0.265) 6.975 (0.382) 7.072 (0.315) <0.001 † Statistically significant from age group 5 P=0.01-0.05. ‡ Statistically significant from age group 5 P<0.01. RE, Retinol Equivalents. 1. University of Otago and Ministry of Health. 2011. A Focus on Nutrition: Key Finding from the 2008/09 New Zealand Adult Nutrition Survey. Wellington: Ministry of Health (4). 2. Nutrient density scores calculated by crude nutrient intake/energy in MJ. Table 5.5 Comparison of mean (SE) micronutrient density scores for females from the Adult Nutrition Survey1 Nutrient Density Scores2 33 Vitamin A density (µgRE/MJ) Thiamin density (mg/MJ) Riboflavin density (mg/MJ) Vitamin B6 density (mg/MJ) Vitamin B12 density (µg/MJ) Calcium density (mg/MJ) Zinc density (mg/MJ) Selenium density (µg/MJ) All Participants Age category 1 (15-18 years) Age category2 (19-30 years) Age category 3 (31-50 years) Age category 4 (51-70 years) Age category 5 (≥ 71 years) Overall P Value 111.585 (4.041) 85.477 (4.087) ‡ 86.123 (4.173) ‡ 105.938 (8.585) ‡ 134.125 (8.631) 140.635 (5.818) <0.001 0.162 (0.003) 0.159 (0.007) ‡ 0.137 (0.006) ‡ 0.157 (0.004) ‡ 0.174 (0.007) ‡ 0.201 (0.005) <0.001 0.236 (0.004) 0.211 (0.008) ‡ 0.219 (0.009) ‡ 0.236 (0.006) ‡ 0.244 (0.006) † 0.265 (0.005) <0.001 0.240 (0.008) 0.271 (0.026) 0.292 (0.029) 0.231 (0.015) 0.213 (0.006) 0.222 (0.004) 0.016 0.490 (0.015) 0.469 (0.031) 0.480 (0.035) 0.489 (0.024) 0.504 (0.035) 0.490 (0.027) 0.961 107.121 (1.862) 94.176 (2.939) ‡ 92.852 (3.841) ‡ 111.735 (3.582) 110.581 (3.140) 117.437 (2.628) <0.001 1.254 (0.013) 1.186 (0.034) † 1.163 (0.032) ‡ 1.279 (0.024) 1.285 (0.026) 1.305 (0.027) <0.001 6.722 (0.156) 5.348 (0.180) ‡ 6.141 (0.342) 6.817 (0.316) 7.296 (0.291) 6.943 (0.247) <0.001 † Statistically significant from age group 5 P=0.01-0.05. ‡ Statistically significant from age group 5 P<0.01. RE, Retinol Equivalents. 1. University of Otago and Ministry of Health. 2011. A Focus on Nutrition: Key Finding from the 2008/09 New Zealand Adult Nutrition Survey. Wellington: Ministry of Health (4). 2. Nutrient density scores calculated by crude nutrient intake/energy in MJ. 5.3 Linear Regression of Nutrient Density and Demographic Variables Linear regression was performed on nutrient density scores for each of the eight at risk micronutrients identified in Section 2.6 and demographic variables (age in years, gender, ethnicity, BMI, waist circumference, SES status (classified by NZ Deprivation index) and living arrangements) to assess their association with dietary nutrient density scores for participants ≥71 years. Both unadjusted and adjusted results are presented in Tables 5.6-5.13. Being male, being of ‘Other’ prioritised ethnicity, living in deprivation quintile 5, and living alone were used as comparison groups. The majority of interactions with gender were not significant, therefore, to maintain consistency we did not stratify for sex, which allowed us to have maximal power to detect overall significant effects. However, there was a significant interaction for gender with number in dwelling for calcium nutrient density scores, which for females were positively associated with living alone (B=1.110, 95% CI=1.013-1.218, P=0.026). Being of ‘Other’ ethnicity was significantly associated with riboflavin nutrient density scores (B=1.376, 95% CI=1.158-1.637, P=<0.001), and being of Pacific ethnicity was positively associated with selenium nutrient density scores (B=1.868, 95% CI= 1.053-0.316, P=0.033) for males but not for females. Being of ‘Other’ ethnicity was positively associated with thiamin nutrient density scores for females (B=0.750, 95% CI=0.612-0.920, P=0.06) but not for males. Although participants in age group 5 often had higher mean nutrient density scores than other age groups, after adjusting for all other factors, there were no significant associations between age in years within age group 5 and any dietary nutrient density. Once adjusted for all other factors, vitamin A nutrient density scores within age group 5 were positively associated with being female (P=0.015) and living in deprivation quintile 1 (lowest deprivation level) compared to quintile 5 (highest deprivation level) (P=0.014) (Table 5.6). Adjusted thiamin nutrient density scores were positively associated with living in deprivation 34 quintiles 1 (P=0.015), 3 (P=0.027) and 4 (P=0.008) compared to deprivation quintile 5 (Table 5.7). Similarly, riboflavin nutrient density scores were positively associated with living in deprivation quintile 1 compared to 5 (P=0.013) (Table 5.8). Vitamin B6 nutrient density scores were positively associated with being in deprivation quintiles 1 (P=0.022), 2 (P= 0.003) and 3 (P=0.033) compared to deprivation quintile 5 (Table 5.9). Interestingly, none of these demographic variables showed any significant associations with vitamin B12 nutrient density scores after adjustment for all other variables (Table 5.10). Calcium nutrient density scores were positively associated with being female (P=0.034) and being of Pacific ethnicity (P=0.049) (Table 5.11). Zinc nutrient density scores were positively associated with being female (P=0.009) and being in deprivation quintile 1 compared to those in quintile 5 (P=0.025) (Table 5.12). Selenium nutrient density scores were positively associated with waist circumference (P=0.012) (Table 5.13). 35 Table 5.6 Linear regression for demographic variables and vitamin A density scores (µgRE/MJ) for participants ≥ 71 years from the Adult Nutrition Survey 1 Unadjusted Adjusted B 95% Confidence Interval P Value B 95% Confidence Interval P Value Age 1.006 0.997-1.015 0.187 1.007 0.997-1.016 0.176 Male 0.891 0.816-0.973 0.010 1.123 1.028-1.226 0.010 1.161 1.030-1.310 0.015 Maori 1.045 0.854-1.278 0.668 1.099 0.843-1.432 0.485 Pacific 0.716 0.479-1.070 0.103 0.784 0.484-1.269 0.321 1.079 0.893-1.305 0.429 Body Mass Index (kg/m ) 0.995 0.986-1.005 0.342 0.992 0.976-1.010 0.389 Waist Circumference 0.998 0.994-1.001 0.147 1.002 0.996-1.009 0.467 Deprivation Quintile 14 1.118 0.996-1.255 0.058 1.198 1.037-1.385 0.014 5 0.997 0.895-1.112 0.963 1.094 0.944-1.269 0.233 Deprivation Quintile 36 0.920 0.809-1.045 0.200 1.014 0.867-1.187 0.858 Deprivation Quintile 4 7 1.045 0.946-1.155 0.387 1.110 0.974-1.265 0.118 Deprivation Quintile 5 8 0.926 0.830-1.033 0.169 Living Alone 1.075 0.986-1.172 0.100 Living with 1 or more persons 0.930 0.853-1.014 0.100 0.960 0.872-1.056 0.397 Female Ethnicity 2 Other 3 2 36 Deprivation Index Deprivation Quintile 2 RE, Retinol Equivalents. 1. University of Otago and Ministry of Health. 2011. A Focus on Nutrition: Key Finding from the 2008/09 New Zealand Adult Nutrition Survey. Wellington: Ministry of Health (4). 2. Prioritised ethnic group where participant may only exist in one group (84). 3. Body Mass Index calculated by Weight (kg)/ (Height (m)) 2. Deprivation Index: 4.Quintile 1: Lowest Deprivation Quintile representing the 20% of areas with the lowest levels of deprivation 5. Quintile 2: representing the second 20% of areas least deprived, 6. Quintile 3: representing the middle 20% of areas, 7.Quintile 4: representing the second top 20% of areas most deprived 8. Deprivation Quintile 5: representing the 20% of areas with the highest deprivation (84). Table 5.7 Linear regression for demographic variables and thiamin density scores (mg/MJ) for participants ≥ 71 years from the Adult Nutrition Survey 1 Unadjusted Adjusted B 95% Confidence Interval P Value B 95% Confidence Interval P Value Age 1.009 1.002-1.015 0.007 1.006 0.999-1.013 0.096 Male 0.987 0.917-1.062 0.728 1.013 0.942-1.090 0.728 0.997 0.915-1.087 0.951 Maori 1.182 0.986-1.416 0.070 1.209 0.990-1.477 0.063 Pacific 1.072 0.837-1.371 0.582 1.093 0.834-1.431 0.519 0.870 0.747-1.012 0.071 Body Mass Index (kg/m ) 1.000 0.993-1.007 0.984 0.999 0.986-1.012 0.883 Waist Circumference 1.000 0.997-1.003 0.984 1.000 0.996-1.005 0.843 Deprivation Quintile 14 1.032 0.950-1.122 0.457 1.147 1.027-1.282 0.015 5 0.924 0.861-0.991 0.026 1.049 0.947-1.161 0.358 Deprivation Quintile 36 1.027 0.950-1.111 0.504 1.134 1.015-1.267 0.027 Deprivation Quintile 4 7 1.078 0.995-1.169 0.068 1.155 1.038-1.285 0.008 Deprivation Quintile 5 8 0.926 0.849-1.011 0.085 Living Alone 1.044 0.981-1.111 0.171 Living with 1 or more persons 0.958 0.900-1.019 0.171 0.941 0.878-1.010 0.092 Female Ethnicity 2 Other 3 2 37 Deprivation Index Deprivation Quintile 2 1. University of Otago and Ministry of Health. 2011. A Focus on Nutrition: Key Finding from the 2008/09 New Zealand Adult Nutrition Survey. Wellington: Ministry of Health (4). 2. Prioritised ethnic group where participant may only exist in one group (84). 3. Body Mass Index calculated by Weight (kg)/ (Height (m)) 2. Deprivation Index: 4.Quintile 1: Lowest Deprivation Quintile representing the 20% of areas with the lowest levels of deprivation 5. Quintile 2: representing the second 20% of areas least deprived, 6. Quintile 3: representing the middle 20% of areas, 7.Quintile 4: representing the second top 20% of areas most deprived 8. Deprivation Quintile 5: representing the 20% of areas with the highest deprivation (84). Table 5.8 Linear regression for demographic variables and riboflavin density scores (mg/MJ) for participants ≥ 71 years from the Adult Nutrition Survey 1 Unadjusted Adjusted B 95% Confidence Interval P Value B 95% Confidence Interval P Value Age 1.007 1.002-1.013 0.011 1.006 0.999-1.012 0.085 Male 0.916 0.861-0.974 0.005 1.092 1.026-1.162 0.005 1.067 0.982-1.158 0.124 Maori 0.865 0.728-1.028 0.099 0.923 0.761-1.120 0.416 Pacific 0.857 0.705-1.043 0.123 0.868 0.701-1.075 0.193 1.163 1.015-1.333 0.029 Body Mass Index (kg/m ) 0.995 0.990-1.001 0.076 1.003 0.992-1.014 0.593 Waist Circumference 0.997 0.995-0.998 <0.001 0.997 0.993-1.002 0.215 Deprivation Quintile 14 1.056 0.973-1.147 0.192 1.123 1.025-1.230 0.013 5 1.000 0.932-1.073 1.000 1.062 0.978-1.154 0.150 Deprivation Quintile 36 0.992 0.906-1.086 0.862 1.056 0.957-1.166 0.279 Deprivation Quintile 4 7 1.014 0.942-1.091 0.710 1.073 0.991-1.163 0.083 Deprivation Quintile 5 8 0.929 0.874-0.987 0.018 Living Alone 1.046 0.991-1.105 0.105 Living with 1 or more persons 0.956 0.905-1.010 0.105 0.985 0.929-1.044 0.608 Female Ethnicity 2 Other 3 2 38 Deprivation Index Deprivation Quintile 2 1. University of Otago and Ministry of Health. 2011. A Focus on Nutrition: Key Finding from the 2008/09 New Zealand Adult Nutrition Survey. Wellington: Ministry of Health (4). 2. Prioritised ethnic group where participant may only exist in one group (84). 3. Body Mass Index calculated by Weight (kg)/ (Height (m)) 2. Deprivation Index: 4.Quintile 1: Lowest Deprivation Quintile representing the 20% of areas with the lowest levels of deprivation 5. Quintile 2: representing the second 20% of areas least deprived, 6. Quintile 3: representing the middle 20% of areas, 7.Quintile 4: representing the second top 20% of areas most deprived 8. Deprivation Quintile 5: representing the 20% of areas with the highest deprivation (84). Table 5.9 Linear regression for demographic variables and vitamin B6 density scores (mg/MJ) for participants ≥ 71 years from the Adult Nutrition Survey 1 Unadjusted Adjusted B 95% Confidence Interval P Value B 95% Confidence Interval P Value Age 1.002 0.995-1.008 0.629 1.000 0.993-1.007 0.919 Male 0.948 0.894-1.006 0.078 1.054 0.994-1.118 0.078 1.057 0.983-1.138 0.136 Maori 0.895 0.785-1.021 0.099 0.938 0.808-1.088 0.398 Pacific 1.062 0.880-1.281 0.532 1.141 0.907-1.434 0.259 1.060 0.945-1.189 0.320 Body Mass Index (kg/m ) 0.997 0.991-1.003 0.387 0.999 0.987-1.010 0.834 Waist Circumference 0.998 0.996-1.001 0.168 1.000 0.995-1.005 0.935 Deprivation Quintile 14 1.039 0.950-1.136 0.405 1.135 1.018-1.264 0.022 5 1.066 0.991-1.146 0.087 1.163 1.052-1.286 0.003 Deprivation Quintile 36 1.011 0.931-1.098 0.790 1.118 1.009-1.239 0.033 Deprivation Quintile 4 7 0.981 0.908-1.060 0.633 1.093 0.992-1.205 0.073 Deprivation Quintile 5 8 0.897 0.835-0.964 0.003 Living Alone 1.008 0.951-1.068 0.793 Living with 1 or more persons 0.992 0.937-1.051 0.793 0.997 0.935-1.063 0.933 Female Ethnicity 2 Other 3 2 39 Deprivation Index Deprivation Quintile 2 1. University of Otago and Ministry of Health. 2011. A Focus on Nutrition: Key Finding from the 2008/09 New Zealand Adult Nutrition Survey. Wellington: Ministry of Health (4). 2. Prioritised ethnic group where participant may only exist in one group (84). 3. Body Mass Index calculated by Weight (kg)/ (Height (m)) 2. Deprivation Index: 4.Quintile 1: Lowest Deprivation Quintile representing the 20% of areas with the lowest levels of deprivation 5. Quintile 2: representing the second 20% of areas least deprived, 6. Quintile 3: representing the middle 20% of areas, 7.Quintile 4: representing the second top 20% of areas most deprived 8. Deprivation Quintile 5: representing the 20% of areas with the highest deprivation (84). Table 5.10 Linear regression for demographic variables and vitamin B12 density scores (µg/MJ) for participants ≥ 71 years from the Adult Nutrition Survey 1 Unadjusted Adjusted B 95% Confidence Interval P Value B 95% Confidence Interval P Value Age 1.002 0.993-1.011 0.620 1.002 0.992-1.011 0.719 Male 0.969 0.867-1.084 0.582 1.032 0.923-1.154 0.582 1.092 0.953-1.251 0.203 Maori 0.979 0.753-1.273 0.876 1.065 0.790-1.435 0.680 Pacific 0.934 0.623-1.400 0.740 0.959 0.621-1.482 0.850 1.037 0.829-1.298 0.748 Body Mass Index (kg/m ) 1.000 0.991-1.009 0.992 0.994 0.975-1.014 0.557 Waist Circumference 1.000 0.996-1.003 0.910 1.003 0.995-1.011 0.481 Deprivation Quintile 14 1.092 0.927-1.286 0.293 1.153 0.962-1.383 0.124 5 0.986 0.881-1.104 0.809 1.073 0.928-1.242 0.340 Deprivation Quintile 36 0.981 0.871-1.104 0.748 1.043 0.899-1.209 0.580 Deprivation Quintile 4 7 1.002 0.882-1.139 0.030 1.098 0.950-1.270 0.205 Deprivation Quintile 5 8 0.932 0.825-1.052 0.254 Living Alone 1.023 0.927-1.130 0.649 Living with 1 or more persons 0.977 0.885-1.079 0.649 1.008 0.902-1.127 0.887 Female Ethnicity 2 Other 3 2 40 Deprivation Index Deprivation Quintile 2 1. University of Otago and Ministry of Health. 2011. A Focus on Nutrition: Key Finding from the 2008/09 New Zealand Adult Nutrition Survey. Wellington: Ministry of Health (4). 2. Prioritised ethnic group where participant may only exist in one group (84). 3. Body Mass Index calculated by Weight (kg)/ (Height (m)) 2. Deprivation Index: 4.Quintile 1: Lowest Deprivation Quintile representing the 20% of areas with the lowest levels of deprivation 5. Quintile 2: representing the second 20% of areas least deprived, 6. Quintile 3: representing the middle 20% of areas, 7.Quintile 4: representing the second top 20% of areas most deprived 8. Deprivation Quintile 5: representing the 20% of areas with the highest deprivation (84). Table 5.11 Linear regression for demographic variables and calcium density scores (mg/MJ) for participants ≥ 71 years from the Adult Nutrition Survey 1 Unadjusted Adjusted B 95% Confidence Interval P Value B 95% Confidence Interval P Value Age 1.004 0.998-1.011 0.175 1.003 0.996-1.011 0.411 Male 0.855 0.798-0.916 <0.001 1.170 1.092-1.253 <0.001 1.113 1.008-1.230 0.034 Maori 0.785 0.668-0.923 0.003 0.853 0.713-1.021 0.083 Pacific 0.752 0.613-0.922 0.006 0.761 0.580-0.998 0.049 1.299 1.142-1.479 <0.001 Body Mass Index (kg/m ) 0.994 0.988-1.000 0.048 1.006 0.993-1.020 0.339 Waist Circumference 0.995 0.993-0.997 <0.001 0.995 0.990-1.001 0.109 Deprivation Quintile 14 1.032 0.929-1.146 0.559 1.112 0.991-1.248 0.070 5 1.017 0.931-1.111 0.706 1.085 0.983-1.199 0.107 Deprivation Quintile 36 1.005 0.922-1.096 0.908 1.066 0.961-1.181 0.226 Deprivation Quintile 4 7 1.012 0.940-1.089 0.756 1.065 0.975-1.162 0.160 Deprivation Quintile 5 8 0.925 0.866-0.989 0.022 Living Alone 1.077 1.009-1.150 0.025 Living with 1 or more persons 0.928 0.870-0.991 0.025 0.961 0.896-1.029 0.225 Female Ethnicity 2 Other 3 2 41 Deprivation Index Deprivation Quintile 2 1. University of Otago and Ministry of Health. 2011. A Focus on Nutrition: Key Finding from the 2008/09 New Zealand Adult Nutrition Survey. Wellington: Ministry of Health (4). 2. Prioritised ethnic group where participant may only exist in one group (84). 3. Body Mass Index calculated by Weight (kg)/ (Height (m)) 2. Deprivation Index: 4.Quintile 1: Lowest Deprivation Quintile representing the 20% of areas with the lowest levels of deprivation 5. Quintile 2: representing the second 20% of areas least deprived, 6. Quintile 3: representing the middle 20% of areas, 7.Quintile 4: representing the second top 20% of areas most deprived 8. Deprivation Quintile 5: representing the 20% of areas with the highest deprivation (84). Table 5.12 Linear regression for demographic variables and zinc density scores (mg/MJ) for participants ≥ 71 years from the Adult Nutrition Survey 1 Unadjusted Adjusted B 95% Confidence Interval P Value B 95% Confidence Interval P Value Age 0.998 0.994-1.002 0.331 0.998 0.994-1.002 0.396 Male 0.959 0.918-1.002 0.064 1.043 0.998-1.090 0.064 1.081 1.020-1.147 0.009 Maori 0.994 0.890-1.110 0.915 1.073 0.953-1.210 0.245 Pacific 1.112 0.959-1.289 0.161 1.092 0.933-1.279 0.274 0.971 0.882-1.068 0.541 Body Mass Index (kg/m ) 0.997 0.993-1.002 0.239 0.992 0.983-1.001 0.074 Waist Circumference 0.999 0.998-1.001 0.274 1.003 0.999-1.006 0.129 Deprivation Quintile 14 1.029 0.968-1.094 0.354 1.085 1.010-1.165 0.025 5 0.989 0.929-1.053 0.726 1.054 0.977-1.137 0.175 Deprivation Quintile 36 1.015 0.955-1.079 0.622 1.066 0.989-1.149 0.096 Deprivation Quintile 4 7 0.999 0.946-1.054 0.967 1.041 0.970-1.117 0.267 Deprivation Quintile 5 8 0.958 0.905-1.014 0.141 Living Alone 0.985 0.940-1.032 0.521 Living with 1 or more persons 1.015 0.969-1.064 0.521 1.021 0.969-1.075 0.437 Female Ethnicity 2 Other 3 2 42 Deprivation Index Deprivation Quintile 2 1. University of Otago and Ministry of Health. 2011. A Focus on Nutrition: Key Finding from the 2008/09 New Zealand Adult Nutrition Survey. Wellington: Ministry of Health (4). 2. Prioritised ethnic group where participant may only exist in one group (84). 3. Body Mass Index calculated by Weight (kg)/ (Height (m)) 2. Deprivation Index: 4.Quintile 1: Lowest Deprivation Quintile representing the 20% of areas with the lowest levels of deprivation 5. Quintile 2: representing the second 20% of areas least deprived, 6. Quintile 3: representing the middle 20% of areas, 7.Quintile 4: representing the second top 20% of areas most deprived 8. Deprivation Quintile 5: representing the 20% of areas with the highest deprivation (84). Table 5.13 Linear regression for demographic variables and selenium density scores (µg/MJ) for participants ≥ 71 years from the Adult Nutrition Survey 1 Unadjusted Adjusted B 95% Confidence Interval P Value B 95% Confidence Interval P Value Age 1.002 0.994-1.010 0.647 0.999 0.991-1.007 0.861 Male 0.965 0.886-1.052 0.421 1.036 0.951-1.129 0.421 0.935 0.838-1.042 0.223 Maori 1.115 0.885-1.405 0.355 1.062 0.870-1.296 0.557 Pacific 1.258 0.910-1.738 0.164 1.375 0.910-2.077 0.130 0.860 0.711-1.042 0.124 Body Mass Index (kg/m ) 0.996 0.988-1.005 0.395 1.013 0.996-1.030 0.138 Waist Circumference 0.996 0.993-1.000 0.025 0.991 0.984-0.998 0.012 Deprivation Quintile 14 0.993 0.895-1.101 0.888 1.006 0.889-1.139 0.922 5 0.989 0.901-1.084 0.808 0.979 0.875-1.096 0.712 Deprivation Quintile 36 0.997 0.890-1.118 0.965 1.018 0.893-1.161 0.789 Deprivation Quintile 4 7 1.024 0.938-1.118 0.596 1.039 0.926-1.166 0.512 Deprivation Quintile 5 8 0.997 0.911-1.091 0.950 Living Alone 1.050 0.969-1.137 0.232 Living with 1 or more persons 0.952 0.879-1.032 0.232 0.967 0.886-1.054 0.443 Female Ethnicity 2 Other 3 2 43 Deprivation Index Deprivation Quintile 2 1. University of Otago and Ministry of Health. 2011. A Focus on Nutrition: Key Finding from the 2008/09 New Zealand Adult Nutrition Survey. Wellington: Ministry of Health (4). 2. Prioritised ethnic group where participant may only exist in one group (84). 3. Body Mass Index calculated by Weight (kg)/ (Height (m)) 2. Deprivation Index: 4.Quintile 1: Lowest Deprivation Quintile representing the 20% of areas with the lowest levels of deprivation 5. Quintile 2 representing the second 20% of areas least deprived, 6. Quintile 3 representing the middle 20% of areas, 7.Quintile 4 representing the second top 20% of areas most deprived 8. Deprivation Quintile 5 representing the 20% of areas with the highest deprivation (84). 6 Discussion and Conclusions 6.1 Summary of Main Findings This study is the first study to examine the nutrient density (defined in section 3.0) of older New Zealanders ≥ 71years for eight micronutrients identified in the ANS as problematic for this age group. We have compared nutrient density scores across age categories to identify the underlying quality of the foods and therefore diets consumed. Examining nutrient density scores for these eight nutrients has shown that nutrient density scores were equal if not better in those aged ≥ 71years than all other age categories (see section 6.3). Further, none of the demographic variables examined were associated with all eight nutrient density scores. 6.2 Relationship Between Nutrient Density and Demographic Variables No single demographic variable was related to all eight nutrient density scores evaluated. This was not expected as studies have reported dietary quality (5, 71), as well as energy intakes to decline with increasing age (4, 51). In contrast, we found increasing age within the ≥ 71 years age group was not associated with any nutrient density scores. Living alone has been associated with increased “nutritional risk” (41), however, we found no differences in nutrient density scores between individuals that lived alone or those who lived with one or more persons. Furthermore, studies have reported that individuals living with their spouse are less likely to have nutritional deficiencies than all other individuals (6), and that men living alone were likely to have poorer quality diets than men living with their spouse (87). We did not find any relationship between living alone or living with one or more persons and nutrient density scores except for the surprisingly higher calcium nutrient density scores in females who lived alone. However, we were not able to distinguish between individuals who live with their spouse and individuals who live with one 44 person who is not their spouse, as this information was not obtained in the ANS. Previous studies that have shown living alone increases nutritional risk may have picked up other comorbidities associated with living alone or life events, such as recent loss of a spouse, rather than living alone itself. SES is a well-established factor associated with dietary intake and dietary quality (87, 88). In this study New Zealand deprivation index scores were used as a measure of SES. Our results showed that for adults ≥71 years for certain micronutrients, specifically thiamin, riboflavin, vitamin B6 and zinc, lower levels of deprivation were significantly associated with higher mean nutrient density scores. This was in spite of the fact that none of these four nutrients showed any relationships with New Zealand deprivation index quintiles when examined as crude nutrient intakes for the population as a whole in the ANS (4). Our results suggest that SES is a factor influencing the diet of older New Zealanders. However, SES is difficult to accurately assess in the elderly as income and education level become less relevant than for younger ages. The New Zealand deprivation index score represents a measure of the area in which individuals reside and not the individuals themselves (86). Therefore, the suitability of using this index is questionable as the elderly may move residence for convenience, for example, to be closer to shops, transport or family, and this may not relate well to their SES. 6.3 Micronutrient Status 6.3.1 Vitamin A Status The vitamin A status of elderly New Zealanders is less than ideal with one fifth of men ≥ 71 years having inadequate intakes (4). Examining vitamin A density of the diet revealed older adults had higher vitamin A density than the 15-18, 19-30, and 31-50 year olds but similar vitamin A density to the 51-70 year olds. Although vitamin A density is maintained in older adults, it is clearly not sufficient to avoid inadequate intakes. Therefore, a solution needs 45 to be found to increase vitamin A intake without augmenting total energy intake. In older males ≥ 71 years, vitamin A equivalents come from different food groups than younger males, specifically more from vegetables and less from bread based dishes (4). This likely reflects different food preferences of the elderly. Although food choices are different, when assessed all together, they were of equal vitamin A density compared to those made by younger age categories. Since vegetables contribute the highest proportion of vitamin A equivalents (via βcarotene) and are the least energy dense sources, older men could maximise the consumption of vitamin A rich vegetables such as carrots, leeks, pumpkin, and tomato rather than other vegetables (such as cauliflower, mushrooms, parsnips or marrow) to increase the vitamin A density of their diet. 6.3.2 Thiamin Status Thiamin nutrient density was higher in older New Zealanders ≥ 71 years than all other age categories. However, the thiamin status of the elderly is of concern with more than one fifth of females and one quarter of males having inadequate thiamin intakes (4). The thiamin EAR is the same for the two oldest age categories (22), therefore, the increase in percentage of inadequate intakes is likely a result of lower total energy intakes in adults ≥ 71 years. Main sources of thiamin in older males’ diets were bread, breakfast cereals, vegetables, grains and pasta, and milk. In comparison for females, the largest sources were bread, breakfast cereals, vegetables, milk and savoury sauces and condiments (4). As for vitamin A, vegetables are the least energy dense food group which could be modified to increase thiamin intake without increasing total energy intake. Therefore, older adults could enhance thiamin density by consuming broccoli or leeks rather than vegetables such as beetroot, mushrooms or marrow. 6.3.3 Riboflavin Status Riboflavin density was higher in adults ≥ 71 years than other age categories. However, inadequate intakes were still prevalent in just less than a fifth of males and just over one sixth 46 of females (4). The EAR increases for both men (1.1-1.3mg) and women (0.9-1.1mg) at > 70 years (22). Therefore, the increase in dietary inadequacy between the two older age categories can be explained in part by the higher EAR, but also by lower total energy intakes. The largest contributor to riboflavin intakes for older adults was milk. In men this was followed by breakfast cereals, vegetables, and bread. However, breakfast cereals, non-alcoholic beverages, vegetables and dairy products were higher contributors in women (4). This identifies a new difficulty in improving riboflavin density, because even between males and females of the same age category, food preferences are somewhat different. Nonetheless older adults could maximise riboflavin density by consuming broccoli and green or red capsicum rather than celery and onions to increase riboflavin density without increasing total energy intake. 6.3.4 Vitamin B6 Status Vitamin B6 status is less than ideal in New Zealanders ≥ 71 years, as more than a quarter of males and more than half of females had inadequate vitamin B6 intakes. Percentage of inadequate intakes in older adults were substantially higher than females aged 51-70 years, but similar for males (4). However, vitamin B6 nutrient density scores were similar between adults aged ≥ 71 years and 51-70 years. As the EAR for vitamin B6 remains the same for males and females from 50 years, the small increase of inadequate vitamin B6 intakes in males and larger increase in females, must be explained by lower total energy intakes (22). For older New Zealanders ≥ 71 years the largest vitamin B6 contributors were fruit, vegetables, and potatoes, kumara and taro (4). Fruit and vegetables are both low energy density food groups. Therefore, the choices made within these categories could be modified to increase vitamin B6 density. For example, fruits such as bananas could be included in the diet rather than canned fruit salad in syrup, rhubarb or plums. Vegetables such as silver beet, broccoli and red capsicum could be included in the diet in the place of broad beans, butter beans or green beans, therefore substituting foods and increasing the vitamin B6 density without increasing total energy intake. 47 6.3.5 Vitamin B12 Status Vitamin B12 status was not generally of concern in the New Zealand population except in older females ≥ 71 years, and vitamin B12 nutrient density was similar across all age groups. Therefore, the substantial increase in percentage of inadequate intakes of females between the two older age categories is likely attributable to lower total energy intakes. Further, as Green et al demonstrated and the NRVs acknowledge, older adults may not be protected from clinical deficiency when consuming foods reaching the RDI and may require supplementation or fortified foods (22, 33). Therefore, it is important to validate percentage of inadequate dietary intakes against biochemical data. These findings demonstrate the importance for older adults to increase the vitamin B12 density of the diet. Vitamin B12 is only found in animal products, which makes increasing the content of the diet without augmenting energy intakes difficult. However, older adults could be encouraged to add a tablespoon of skim milk powder to mashed vegetables, creamy vegetable soups, porridge, milk puddings or casseroles to increase the vitamin B12 density without noticeably increasing the volume of food consumed or total energy intake. 6.3.6 Calcium Status Calcium status is of concern for the entire New Zealand population, especially in men ≥ 71 years and women ≥ 51 years (4). Calcium density was similar among those 51-70 and ≥ 71 years. For men the increase in inadequate intakes at ≥ 71 years is likely explained by the 260 mg increase in the EAR at > 70 years and in part by lower total energy intakes (22). In contrast, for women the EAR does not increase at > 70 years (22), therefore, the small increase in percentage of inadequate intakes, in spite of similar calcium nutrient density scores is likely the result of lower total energy intakes. Hence, it is clear solutions to increase calcium density need to be found. The elderly get most of their calcium from milk and bread. Older men also get a reasonable proportion of calcium from vegetables and cheese, while older women get a larger proportion from the dairy products and vegetables (4). To increase 48 the calcium density of the diet, older adults could add approximately a tablespoon of skim milk powder to creamy vegetable soups, porridge, mashed vegetables, milk puddings or casseroles, increasing the calcium density without substantially increase total energy intake or food volume. 6.3.7 Zinc Status Zinc status is more of concern in males of all ages than females and in ≥ 71 year olds than 51-70 year olds (4). However, zinc density was similar and the EAR remains constant for both genders and the two older age categories. Therefore, the increases in inadequate intakes are most likely explained again by lower total energy intakes. Major sources of zinc for older males were bread, beef and veal, milk and vegetables. Although zinc is available in both plant and animal foods, animal sources have a higher bioavailability because they do not contain phytate (89). However, animal sources are usually more energy dense than plant sources of zinc, therefore, there is some difficulty in increasing zinc content without increasing total energy intake. 6.3.8 Selenium Status Selenium status of New Zealanders is less than ideal at all ages. The EAR is constant from 19 years but the percentage of inadequate intakes of selenium decreases from 15-50 year olds then increases considerably from 51 years (4, 22). Selenium density of ≥ 71 year olds was higher than younger adults (15-18 and 19-30 years) but similar to older adults (31-50 and 51-70 years). Therefore, the increases in percentage of dietary inadequacy in the two older age categories must be explained by lower total energy intakes rather than lower selenium dietary densities. Brazil nuts are a rich source of selenium and a handful of nuts including at least one Brazil nut would be a good snack food for older adults (90). Therefore, the selenium density of older adults’ diets could be maximised by substituting nuts for other snack foods consumed including biscuits or snack bars which contribute poorly to total selenium intake. 49 Further, more egg based dishes or tinned fish could replace other main meal items to enrich the selenium density of the diet. 6.4 Summary of Food Group Examination Identifying food groups and specific foods to suggest modifying to increase nutrient intakes within current energy restraints has proven challenging. This is because recommendations to increase the dietary nutrient density of one micronutrient have the potential to decrease the dietary nutrient density of another micronutrient. Further, differences in food preferences even among males and females of the same age are apparent. These issues have been carefully considered in the examples previously discussed (section 6.3). If the suggested modifications (or some of) were implemented in the diets of older New Zealanders we would expect the nutrient density for at least some of the at risk micronutrients to increase, with none of the other at risk micronutrients decreasing from the current levels. 6.5 Reference Nutrient Density Index Although we have established that nutrient density scores did not decline with increasing age, we could not conclude that these scores were adequate to maintain nutritional status of older New Zealanders. With no appropriate standard reference nutrient density indices available, we attempted to establish these using published methods proposed. We were not successful in doing so (see Appendix 1). However, in spite of this the nutrient density data obtained in this study has provided some insight into the quality of food choices made by older New Zealanders. 6.6 Strengths The strength of this study was the sound study design and subsequent dataset provided by the ANS (7). Specifically, it was a population based survey which increases the external validity of the study (91). This allowed us to draw conclusions and make applicable 50 recommendations to the target population, the free living adult New Zealand population 15 years and over. Further, the final weighted response rate in the ANS was 61%, which is considered good in national nutrition surveys that have a considerable participant burden (7). 6.7 Limitations The usual limitations of dietary intake surveys discussed elsewhere (7) apply to this study. Briefly, these include social desirability bias, reliance upon memory, unintentional underreporting, small sample sizes in some ethnic and age groups and the inadequacy of food composition databases (7, 91). Further, cross sectional data as in the ANS compares different groups of people attempting to identify ageing effects. However, because it does not follow the same group of people as they age, we cannot distinguish between physiological changes that occur with ageing and differences that result from cohort effects (46). Lastly, although this study is a population based survey, the generalisability may be limited because only free living community dwelling adults were included in the study sample. It has been shown that free living community dwelling adults had more teeth and reported no difficulty in consuming a wider range of foods compared to those living in institutionalised facilities (92). Further, in a UK study older adults residing in the community were at lower risk (14% compared to 21%) of medium or high under nutrition based on measures of low BMI and recent weight loss (93). Therefore we recommend a nutrition survey be undertaken in an institutionalised population, where interventions to increase diet quality may be easier because food is provided. 6.8 Implications for Future Research The use of nutrient density to assess foods and/or whole diets is looking promising. However, there needs to be a standardised definition and standardised criteria to measure nutrient dense foods. The majority of current nutrient density research is aimed at assisting the consumer to make better food choices. Whilst this is very important, there is a need for reference nutrient density indices to be established and validated against biochemical data so 51 that health professionals can draw conclusions about the nutrient density of whole diets. This would allow health professionals to distinguish between a nutrient poor diet and a nutrient rich diet and enable more appropriate recommendations to be made at both the individual and population level. We believe this will be particularly helpful for use in the older population where energy intake is considerably lower than at other ages, and as we have shown, every, individual food choice within food groups becomes very important (4, 51). This research has identified the need for the dietary inadequacy estimates from the ANS to be validated against biochemical indices to identify the prevalence of clinical deficiency of micronutrients in the older population. If in fact 90% of the older population that had inadequate calcium intakes have a clinical calcium deficiency and are consequently at risk of osteoporosis, then strategies to address this need to be implemented at the national level. Our research highlights the importance of the NRVs in evaluating diets and although they may be difficult to establish, their accuracy is imperative. The NRVs for the older population may need to be reviewed and validated against biochemical data and/or clinical end points to identify if current recommendations are correct, or unrealistic and unnecessarily high. 6.9 Conclusion Examining nutrient density scores for eight at risk micronutrients has shown that there was no fall in nutrient density of older New Zealanders’ diets compared to those of younger age categories. However, there were substantial increases in the percentages of the older population with inadequate intakes of these micronutrients. This strongly suggests that the reason older adults have greater levels of nutrient inadequacies is not the result of poorer diet quality but likely attributable to either lower total energy intakes, increased micronutrient recommendations or a combination of the two. Although we acknowledge that there are more prevalent dietary inadequacies with increasing age, we question previous research that suggests ‘diet quality’ of the elderly decreases with increasing age (5, 71). Further, we have 52 shown that with a few alterations to the fruits and vegetables selected, and the addition of skim milk powder to soups, porridge or casseroles, the nutrient density of older adults’ diets could be substantially increased within current energy restraints. Therefore, education needs to be provided to older adults to increase awareness about which foods within food groups are the richest sources of vitamins and minerals lacking in their diets, and to ensure they understand the importance of every food consumed as part of a healthy diet. 53 7 Application to Dietetic Practice As dietitians we are experts in the field of nutritional science but we need to be able to translate this into appropriate and realistic food based recommendations to individuals and subgroups of the population (94). Dietitians can use this research to increase their awareness about the status of the elderly, understanding that although there are numerous inadequate micronutrient intakes, advising older people to eat more nutrient rich foods may not be appropriate or realistic. Dietitians need to recommend to older New Zealanders the careful selection of foods within food groups. For example to maximise the vitamin A, riboflavin, thiamin and vitamin B6 density of the diet dietitians could recommend vegetables such as pumpkin, leeks, tomato and broccoli to be prioritised in the diet over other vegetables, specifically marrow, mushrooms or cauliflower. As another example, to maximise the calcium, riboflavin and vitamin B12 density of the diet, a tablespoon of skim milk powder could be added to meals such as soups, casseroles, mashed vegetables or milk puddings increasing the nutrient density of the meal without substantially increasing total energy intake or the volume of food consumed. Further, perhaps for the elderly with very low energy intakes where increasing the nutrient density is still not likely to achieve adequacy, a fortified food/supplement may need to be developed to help these individuals meet their requirements, or avenues explored to increase their total energy and nutrient intakes. 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Wellington: Ministry of Health; 2012. 61 8 Appendices 8 Appendices ........................................................................................................................ 62 List of Tables .............................................................................................................................. 63 Appendix A............................................................................................................................. 64 Calculated Reference Nutrient Density Index Results and Discussion ......................................... 64 References ................................................................................................................................. 67 List of Tables Table 8.1 Calculated reference nutrient density indices for males and females ≥71 years using “Cutpoint approach”1 ................................................................................................................................... 65 Table 8.2 Number of participants meeting reference nutrient density indices calculated by “Cut-point approach”1 ............................................................................................................................................ 65 Table 8.3 Calculated nutrient density indices for males and females ≥ 71 years calculated by EAR/EER ............................................................................................................................................................... 66 Table 8.4 Number of participants meeting reference nutrient density indices calculated by EAR/EER ............................................................................................................................................................... 66 63 Appendix A Calculated Reference Nutrient Density Index Results and Discussion The 2.5th percentile of energy for adults ≥71 years from the ANS was 3.520 MJ for men and 2.822MJ for women (1). We used the “Cut-point approach” to calculate a reference nutrient density index for the eight micronutrients (EAR/2.5th percentile usual energy intake) for our elderly population (Table 8.1). Because the 2.5th percentile of energy intake in older adults in the ANS was so low (males 3.520 MJ, and females 2.822 MJ), the corresponding reference index was excessively high. For example only 2/1065 (0.18%) individuals met the calcium reference index and the most was 187/1065 (17.5%) for vitamin A (Table 8.2). This did not correspond with the percentage of inadequate dietary intakes from the ANS. This indicates how high unachievable and unrealistically high these reference values were. We then attempted to calculate a reference index from the EAR and Estimated Energy Requirements (EER) of the elderly, approximated from the table of EER in the NRVs document (2). An appropriate approximation was difficult because of the number of variables associated with energy requirements, namely BMI, weight, age, physical activity level. Nonetheless we approximated and estimated an energy requirement of 9.55 MJ for males and 8.20 MJ for females and calculated a nutrient density index from this (Table 8.3). However, because the average energy intake of our population was substantially below the approximated EER values for this age group, (Males 8.07MJ, Females 6.12 MJ), only 133 males and 88 females reached this energy intake yet many more individuals reached this nutrient density level but had lower energy intakes. This clearly resulted in an underestimation of the nutrient density required by these older adults. (Table 8.4) This supports our conclusion that inadequate dietary intakes reported in the ANS were due to low total energy intakes. However we could not determine how many older New Zealanders had sufficient nutrient density to maintain nutritional status. 64 Table 8.1 Calculated reference nutrient density indices for males and females ≥71 years using “Cut-point approach”1 M Vitamin A (µg RE) Thiamin (mg) Riboflavin (mg) Vitamin B6 (mg) Vitamin B12 (mg) Calcium (mg) Selenium (µg) Zinc (mg) F EAR Calculated RNDI EAR Calculated RNDI 625 177.558 500 177.187 1.0 0.284 0.9 0.319 1.3 0.369 1.1 0.390 1.4 0.398 1.3 0.461 2.0 0.568 2.0 0.709 1100 312.503 1100 389.811 60.0 17.046 50.0 17.719 12.0 3.409 6.5 2.303 EAR, Estimated Average Requirement. RNDI, Reference Nutrient Density Index where 2.5th percentile of energy for males=3.520 and females=2.822. RE, Retinol Equivalence. 1. Backstrand JR. Quantitative approaches to nutrient density for public health nutrition. Public Health Nutrition. 2003;6(8):829-37. Table 8.2 Number of participants meeting reference nutrient density indices calculated by “Cut-point approach”1 Vitamin A (µg RE3) Thiamin (mg) Riboflavin (mg) Vitamin B6 (mg) Vitamin B12 (mg) Calcium (mg) Selenium (µg) Zinc (mg) M (n=480) F (n=585) All Participants (n=1065) 68 119 187 92 83 175 55 78 133 14 10 24 105 74 179 2 0 2 29 25 54 1 22 23 RE, Retinol Equivalence. 1. Backstrand JR. Quantitative approaches to nutrient density for public health nutrition. Public Health Nutrition. 2003;6(8):829-37. 65 Table 8.3 Calculated nutrient density indices for males and females ≥ 71 years calculated by EAR/EER M Vitamin A (µg RE3) Thiamin (mg) Riboflavin (mg) Vitamin B6 (mg) Vitamin B12 (mg) Calcium (mg) Selenium (µg) Zinc (mg) F EAR Calculated RNDI EAR Calculated RNDI 625 65.45 500 60.98 1.0 0.105 0.9 0.108 1.3 0.136 1.1 0.134 1.4 0.147 1.3 0.159 2.0 0.209 2.0 0.244 1100 115.18 1100 134.15 60.0 6.28 50.0 6.10 12.0 1.26 6.5 0.793 EAR, Estimated Average Requirements. EER, Estimated Energy Requirements. RE, Retinol Equivalence. RNDI: Reference Nutrient Density Index where EER was 8.07MJ for males and 6.12MJ for females. Table 8.4 Number of participants meeting reference nutrient density indices calculated by EAR/EER Vitamin A (µg RE) Thiamin (mg) Riboflavin (mg) Vitamin B6 (mg) Vitamin B12 (mg) Calcium (mg) Selenium (µg) Zinc (mg) M (n=480) F (n=585) All Participants (n=1065) 366 491 857 395 499 894 427 521 948 331 427 758 393 497 890 131 194 325 176 231 407 199 522 721 RE, Retinol Equivalents. 66 References 1. University of Otago and Ministry of Health. A Focus on Nutrition: Key Findings of the 2008/09 New Zealand Adult Nutrition Survey. Wellington: Ministry of Health; 2011. 2. Australian National Health and Medical Research Council and New Zealand Ministry of Health. Nutrient Reference Values for Australia and New Zealand. Canberra & Wellington: Australian National Health and Medical Research Council and New Zealand Ministry of Health; 2005. 67
