Folio Bound VIEWS - Food Habits in Later Lifeapjcn.nhri.org.tw/server../apjcn/FHILL/Chapter5.pdf ·...

METHODOLOGYPopulation selection and representativeness, response rate and refusals, data collection,modification and application of questionnaire

5.1 Aboriginal Australians A Kouris-Blazos

5.1.1 Population selection and representativeness

The Junjuwa Aboriginal community was chosen as the prime location for the research due to itsaccessibility (2 km from the townsite) and the considerable number of elderly. The research teammet with Aboriginal councillors and gained permission to interview the elderly, obtainanthropometric data and perform the skin test. A nutritionist-nurse, who has lived in FitzroyCrossing and worked with Aborigines for 9 years, assisted in identifying the elderly at Junjuwa.A computer printout of all pensioners was obtained from the bookkeeper. The elderly weredefined as 50 years and over, representing the upper decile of the population at Junjuwa. The lifeexpectancy for Aboriginal Australians is about 50 years. The exact age of the elderly wasdifficult to obtain because birth dates were either not recorded or unreliable.

The elderly were assigned into age groups by comparing them with an Aboriginal man whoseage was known. They were cast into three age brackets: 50-60 years, 60-70 years, 70-80 years. Atotal of 54 elderly Aboriginals aged over 50 resided in Junjuwa in 1988, which comprised about16% (M: 7%, F: 9%) of the total population (n=336). Most of the elderly in the community wereincluded in the anthropometric study as well as the skin test, but they were not all intervieweddue to difficulties in administering the questionnaire on a one-to-one basis.

Photo 5.1. West Australia, Fitzroy Crossing, Junjuwa 1988: researchersProfessor Mark Wahlqvist (right), Dr Antigone Kouris-Blazos(left), Professor Michael Gracey and Sister Helen Sullivanmeet with the Junjuwa community leaders and elders to obtainpermission for the study.

Food Habits in Later Life 84 Auscript InfoDisk

Rapid assessment procedures (RAP) (see Appendix RAP) were used to obtain information ontheir food intake, health status and lifestyle (see also Section 5.1.4). About 83% of the elderlysample were from the river area (Walmadjeri n=22, Bunaba n=16, other n=7) and the remainderwere from the desert (Wonggadjunga n=9). Many of the 'desert people' have only recently comeout of the desert; their diet was different to a 'river' diet and needs to be studied in isolation.Time constraints did not allow this.

5.1.2 Response rate and refusals

A total of 42 elderly (M: 19, F: 23) aged 50 and over in Junjuwa agreed to the anthropometryand the skin test giving a 'biological' response rate of 77%. The remaining 12 subjects wereabsent from Junjuwa. None agreed to have blood tests. We could not use the questionnaire on aone-to-one basis, but rather had to depend on RAP to get the information on the elderlycommunity as a whole (see Section 5.1.1).

Of the 54 elderly Aboriginals in the study, 55% were women and 45% men. There was a higherpercentage of women aged 50-60 (40%) and 60-70 years (37%) compared to 70-80 (23%). Incontrast, there were almost twice as many men in the 60-70 year-old age group (58%) comparedto 50-60 years (25%) and 70-80 years (17%) age groups. Of the total population at Junjuwa(n=336), 16% were 50 or more, 5.4% were between 50-60, 7.3% were between 60-70 and 3.3%were between 70-80.


5.1.3 Data collection

All data were gathered during February and March 1988. Information regarding health wasobtained from medical records at the Community Health Centre at the town site and from theHealth Clinic at Junjuwa. Anthropometry was performed on 42 subjects (M: 19, F: 23).Measurements were taken by the nutritionist/ nurse at Junjuwa. Stature was measured using aportable stature stick and weight taken using step-on scales. Mid upper arm circumference,triceps skinfold thickness, umbilical circumference, and maximum hip circumference were alsomeasured. The skin test using silicone rubber was performed on 42 subjects.

5.1.4 Modification and application of questionnaire

In the IUNS study, it was intended that extensive health and dietary information be obtained onindividuals using questionnaire data to correlate each subject's diet and health status. This wasnot possible with elderly Aboriginal Australians because information provided by individualswas not complete. The approach was therefore changed to describe the diet of the elderly atJunjuwa as a group, rather than as individuals, using RAP methodology [1,2].

Previous researchers have used qualitative methods to describe food intakes in Aboriginalcommunities [3,4] because individual determinations are expensive, time consuming, unreliableand not validated [5,6]. There were problems with the questionnaire approach because somequestions required understanding of non-Aboriginal concepts like "health", "time", "frequency",and "quantity". Information considered to be more valid was obtained by interviewing "key"informants (e.g. health workers, supermarket managers) and groups of selected elderlyAborigines (a total of 25 people were interviewed), which allowed cross-checking ortriangulation to reconstruct the typical elderly diet. The quantitative food frequencyquestionnaire was modified, using RAP, to be usable for the "key" informants and for groups, soas to build a consensus statement about group food intake patterns.

A few key questions and concepts were taken from the questionnaire (mainly on diet and health)and used to probe the elderly in a conversational approach. All interviews were taped with thesubject's permission. Those interviewed included:

a) fifteen 'reliable' elderly persons, selected by the local non-Aboriginal nutritionist/ nurse;b) daughters of the elderly;c) managers of the local food store and supermarket (non-Aborigines) and Aborigines who

operated the cash registers;d) a project planner and bookkeeper of Junjuwa (non-Aborigine); ande) Aboriginal health workers. The information collected from all sources was verified by

triangulation.

The elderly sample, who were interviewed, was limited to 25 because food patterns were so


similar that it was unlikely that further useful information would be obtained. Interviewinggroups of six elderly individuals was found to be an effective way to obtain information. Onthree occasions a daughter was present who assisted greatly, and on two occasions a husband andwife were interviewed together.

A list of commonly eaten foods (including bush foods) considered representative for thecommunity was constructed using the RAP approach. The quantitative food frequencyquestionnaire was then modified to be usable at the group level to build a consensus statementabout group food intake patterns. Portion sizes were estimated using food photographs, foodscales, play dough, and items from the supermarket. Diet histories and food frequencies wereobtained on food consumed during the wet season, dry season and when the Fitzroy Riverflooded.

Food photographs of non-Aboriginal foods were used to help quantify food consumed. Foodscales and play dough were used to quantify damper (a kind of bread cooked in the ashes of afire or fried in a pan) which is consumed in large quantities. An Aboriginal health worker wasinterviewed regarding bush foods in the river area commonly now consumed and those eaten inthe past to devise a food frequency checklist of these foods. Aboriginal names for the foods wereobtained (mainly in Walmadjeri language) to facilitate communication. The interviewer wastaken to the bush to collect fruits commonly eaten. Bush fruits were photographed and describedfor the purpose of identification.

Past food intake information on cattle stations was obtained in the form of diet history and foodfrequency. The police sergeant and cattle station owners were interviewed regarding foodrations. Information was also obtained from subjects and informants regarding food beliefs,preferences and taboos, factors affecting food acquisition, cooking facilities and storage, lifestylehabits, social activity, exercise and economic status.


5.2 Anglo-Celtic Australians W Lukito


A sample of 99 Anglo-Celtic Australians aged 70 years and over were selected from an area of 5postcodes in the south-eastern region of Melbourne Metropolitan Area (East Bentleigh 3165,South Oakleigh 3167, Moorabbin 3189, Highett 3190 and Cheltenham 3192). These 5 postcodeswere chosen because the characteristics of the sample area are representative of those ofMelbourne with respect to the distribution of age, percent born in Australia with Australian-bornparents, percent household income, educational level (as the age of leaving school), occupationand percentage of unemployment. Study subjects were selected by computerised random numbergeneration, from a computerised telephone listing of the 5 postcodes, drawn from the 1990Melbourne telephone directory. It is estimated that 92% of households in the MelbourneStatistical Division are telephone subscribers [38]. Households were then contacted by phone toidentify eligible individuals. Non-responders were asked to answer a few questions by phoneinterview to establish if they differ in any major characteristics from responders.


From 159 phone calls made, 99 subjects agreed to answer the questionnaires. This makes a'questionnaire' response rate of 62.26%. From 99 subjects who answered the questionnaires, 89subjects agreed to have physical examination. This is a 'biological' response rate of 56%.


Questionnaires were used to collect data on: food habits, food and health beliefs, self-reportedhealth (health problems, self-perceived health, medication, performance score), life-style factors(physical activity, social activity, social network, alcohol consumption, smoking), andsocio-economic and demographic situations.

Food intake data were obtained by using a food frequency questionnaire. Portion sizes wereestimated using food photographs. These self-administered questionnaires were sent to theparticipants. They were asked to fill them in at their convenience. Appointments were then madefor blood tests and physical examinations. Whole blood was collected after an overnight fast.Full blood examination including haemoglobin, haematocrit, platelets, white blood cells, meancorpuscular volume, mean corpuscular haemoglobin, mean corpuscular haemoglobinconcentration, mean platelet volume, and differential counts, serum B-12 and folate wereassessed at the Department of Haematology, Monash Medical Centre.

Biochemical indices included: sodium, potassium, chloride, calcium, phosphate, albumin, totalprotein, ALT, AST, ALP, total bilirubin, urea, creatinine, lipids: total cholesterol (TC),


triglycerides (TG), high density lipoprotein cholesterol (HDLC), low density lipoproteincholesterol (LDLC), LDLC/ HDLC ratio, fasting glucose, glycated haemoglobin, iron, ferritin,vitamin D, iron saturation and iron binding capacity. These measurements were made at theDepartment of Biochemistry, Monash Medical Centre.

Aliquots of serum/ plasma were stored at -70°C for vitamin analyses (vitamins A, E andß-carotene). Study subjects were invited to have blood collection and physical examination atMonash University Department of Medicine, Monash Medical Centre. To examineanthropometric indices, body weight, height, arm span, skinfold thicknesses (biceps, triceps,subscapular and suprailiac skinfolds) and circumferences (mid-arm, waist and umbilical, hip,maximal gluteal circumferences) were measured by trained investigators. A bioelectricalimpedance test was also performed to measure body fat mass to estimate total body water.

Photo 5.2. Melbourne, Australia (Anglo-Celtic) (1992): fit couple in theirlate seventies being interviewed at study centre.


This study adopted all the questionnaires proposed by IUNS. Additional questions on bodyimage were incorporated in socio-demography and lifestyle questionnaires.


5.3 Greeks in Melbourne, Australia A Kouris-Blazos

5.3.1. Population selection and representativeness

In Melbourne, it was not possible to study Greeks originally from Spata because only a fewfamilies had left Spata to immigrate to Melbourne. Alternatively, a cross-section of the Greekcommunity in Melbourne were sampled. The telephone directory was successfully used [38] toobtain a representative sample of Greek Australians [39]. This method was therefore employedin Australia to recruit elderly Greeks. In contrast, in countries with low telephone usage, such asGreece, it is preferable to use electoral rolls. Greek sounding surnames were randomly selectedfrom the Melbourne telephone directory, with reference to a list of commonly used Greeksurnames subscribing to a local Greek newspaper.

All individuals selected lived in the urban parts of Melbourne. All subjects in the household,aged 70 and over and who claimed to be of Greek ancestry, were eligible for the study. Therepresentativeness of the Melbourne sample was checked against the wider Greek elderlycommunity (1986 Victorian census) according to gender and age group distribution as well asgeographic distribution (percentage living in various suburbs in Melbourne). The sample wasfound to be representative for geographic distribution, but under represented for elderly womenaged 70-79 (significant at 5% level).

5.3.2 Response rate

A total of 189 elderly Greeks (M: 94, F: 95) were interviewed with the questionnaire (mean age:78 years; 65% were 70-79; 35% were 80+). Only 37 elderly (M: 19, mean age 77; F: 18, meanage 80) refused to take part in the study giving a 'questionnaire' response rate of 83.6%. Of the189 subjects interviewed (most also had their anthropometry measured), 109 (M: 60, F: 49)agreed to have their blood tested giving a 'biological' response rate of 48%. Proportionately moremen (55%) had their blood tested, of which 77% were aged 70-79 and 23% were over 80.Compared to the men, there were proportionately more older women over 80 (33%) that hadtheir blood tested (70-79: 67%). Due to small numbers of elderly Greek people living inMelbourne (only 2% of the Greek community were aged 70+) it was time consuming to recruitsubjects for the study. After two years of recruitment and interviewing, 189 subjects had beenstudied.


After the announcement of the study in a local Greek paper as well as a local Greek radio stationin December 1989, Greek sounding surnames were randomly selected from the telephonedirectory and approached by telephone by a Greek-speaking researcher in 1990 and 1991.


If a household was rung and subjects were not eligible or if they refused to participate, thesubsequent name randomly picked in the telephone directory was rung, and so on, until therequired sample size was achieved. There was no attempt to ensure that equal numbers of menand women were recruited.

The study was briefly described on the phone and inquiry was made about individuals in thehousehold aged 70 and over. If no such individual lived there, we asked for a name and phonenumber of someone they knew that was aged over 70, such as a relative. This system of referralwas limited to no more than two names from each contact made. All subjects aged 70 and over ina household were eligible for the study, including both husband and wife if married. If subjectswere unable to answer most questions independently or if they did not identify themselves asGreek they were excluded (e.g. Slavo-Macedonians).

Photo 5.3. Melbourne, Australia (Greek) (1990-91): interviewing in anelderly subject's home; one of the oldest men in the Greeksample (late 90s)being interviewed by Dr AntigoneKouris-Blazos, a Greek Australian.

Photo 5.4. Melbourne, Australia (Greek) (1990-91): preparation of thesilicon rubber material used in the skin test.


Photo 5.5. Melbourne, Australia (Greek) (1990-91): application of thesilicon rubber to the palmar aspect of the forearm; dried in acouple of minutes; painlessly peeled off and graded under themicroscope.


Individuals who agreed to be interviewed and have their blood tested were seen on twooccasions. One time in their home where the questionnaire (nutritional and non-nutritionalquestions) was administered and where interview time often ranged between 2-4 hours. One totwo subjects were studied per day. A few weeks later, the subject would come to the hospital tohave anthropometry and blood pressure measured as well as the skin and blood tested. About 2-4subjects were studied per week. Due to literacy problems and cultural apprehension in signingpapers, consent forms were not used. Nevertheless, detailed explanation was given to bothparticipants and relatives before verbal consent was obtained.

Blood test results were briefly explained in a personalised letter, in Greek, to each participantalong with a print out of their results in English which they were instructed to show to theirdoctor. The food frequency questionnaire consisted of 250 foods, of which 50 were specific toGreek cuisine. Usual portion size was estimated using food photographs. Anthropometryperformed on 186 subjects (M: 70-79 yrs = 64, 80+ yrs = 28; F: 70-79 yrs = 59, 80+ yrs = 35).The tests included: weight (on calibrated weighing scales), height (using a height stick), tricepskinfold, bicep skinfold, subscapular skinfold, suprailiac skinfold, mid upper arm circumference,umbilical circumference, maximum hip circumference, hip length and electrical impedance (M:70-79 yrs = 42, 80+ yrs = 10; F: 70-79 yrs = 24, 80+ yrs = 10). The skin test was performed on177 subjects (M: 70-79 yrs = 59, 80+ yrs = 27; F: 70-79 yrs = 56, 80+ yrs = 35) and graded bytwo trained researchers.


Photo 5.6. Melbourne, Australia (Greek) (1990-91): measuring thesubscapular skinfold using Harpenden callipers on an elderly.

Blood pressure was measured on 183 subjects (M: 70-79 yrs = 63, 80+ yrs = 28; F: 70-79 yrs =57, 80+ yrs = 35) using a standard sphygmomanometer with the subject in a sitting position. Theblood test was performed on 109 subjects (M: 70-79 yrs = 47, 80+ yrs = 14; F: 70-79 yrs = 33,80+ yrs = 16). A total of 35 ml blood was collected after an overnight fast. The following testswere performed: haemoglobin, mean corpuscular haemoglobin concentration, mean corpuscularvolume, platelets, haematocrit, sodium, potassium, chloride, bicarbonate, urea, creatinine,glucose, alkaline phosphatase, glutamyl transferase, aspartate aminotransferase, bilirubin,calcium, phosphate, total protein, albumin, glycated haemoglobin, cholesterol, triglycerides,HDL, LDL, ferritin, B-12, folate, iron, total iron binding capacity, iron saturation, uric acid,dehydroepiandrosterone sulphate, fructosamine, Lp(a), vitamin E, retinoic acid, carotenoids andvitamin K. A total of 26 individuals were also randomly selected to collect 24 hour urinesamples (the day prior to blood collection). Of the 26 samples, 20 followed the instructionscorrectly (M: 13, F: 7). Nitrogen excretion was measured as well as Na, K, Ca, phosphate andcreatinine. Urine was collected in order to validate the food frequency questionnaire bycomparing protein intake calculated from urinary nitrogen excretion to protein intake calculatedfrom the food frequency.


5.4 Greeks in Spata, Greece A Kouris-Blazos


At the time of the study in Spata in 1988, the total population was about 10,000, of which 640(M: 284, F: 356) subjects were identified from the electoral rolls as being 70 or more (6.4%).These subjects formed the sampling base. A representative sample of 104 subjects (M: 51, F: 53)aged 70 and over were randomly selected from the electoral rolls. The electoral rolls werechosen to sample the elderly because less than 90% of all households have a telephone inGreece. The gender and age group distribution of the sample was not found to be significantlydifferent from the wider elderly community in Spata (sample elderly M: 49%, F: 51%; totalelderly (M: 44%, F: 56%).

5.4.2 Response rate

A total of 104 elderly Greeks (M: 51, F: 53) were interviewed with the questionnaire. The meanage of the sample was 77 years for both men and women (65% were 70-79; 35% were 80+).Only 13 subjects (M: 7, F: 6) refused to be in the study giving a 'questionnaire' response rate of89%. Of the 104 subjects interviewed, 67 subjects (M: 40, F: 27) agreed to come to the localhealth centre to have anthropometry measured as well as their blood tested giving a 'biological'measurement response rate of 57%. Similar proportions of men and women aged 70-79 and 80+had their blood tested (65%, 35% respectively). In many cases more than two housecoats werenecessary to complete the questionnaire, for the following reasons:

a) It was during the holiday season from August to September.b) Elderly men were often at the local coffee shop (cafeneion) drinking coffee and playing

cards.c) The elderly were helping during the grape harvest in September.

As a result, only 104 subjects were interviewed in the time available (three months) to do thestudy.

Photo 5.7. Spata, Greece (1988): a fit man aged in his mid 70's beinginterviewed.



The questionnaire designed for the IUNS study was first used on the Greeks in Spata fromAugust-October 1988 [7,8]. The rapid assessment procedures [1] were used to get an overallpicture of the community and to ensure that the questionnaire was sensitive to areas that mayhave been overlooked. This was achieved by having the director of the Spata Community HealthCentre, researchers from the Athens School of Public Health and Spata community leaders,check the questionnaire. The questionnaire was also piloted on ten elderly inhabitants of Spatabefore use on the elderly selected for the study. The Australian researcher, fluent in Greek andfamiliar with Greek culture and tradition, found an apartment in Spata which would facilitaterapport and acceptance of the study. There was no need to announce the study, as word of mouthin such a tight-knit community rapidly spread the news.

Electoral rolls were obtained from the Spata council as well as the names of people that had diedsince the last revision of the electoral rolls-- these names were subsequently removed. The totalnumber of available voters aged 70 and over numbered 640 (M: 284, F: 356). Names wererandomly selected from the electoral rolls and interviewed until the required sample size wasachieved. Eligible spouses were also included in the study once the housecall was made. Noattempt was made to achieve equal numbers of men and women.


The electoral rolls did not include the phone numbers of voters and had incomplete addresses. Asa result, it was not possible to send a letter to elderly subjects describing the study nor was itpossible to make a phone call prior to the housecall. The elderly selected were located by wordof mouth (in other words by asking locals for directions).

There were two home visits. The first visit was to inform the participants of the study, toascertain their willingness to participate and complete part one (non-nutritional section) of thequestionnaire which took about 60 minutes. The second visit involved completing part two, thenutritional section of the questionnaire, which took about 90-120 minutes. Food photos wereused to ascertain food intake and serving size. Due to literacy problems and culturalapprehension in signing papers, consent forms were not used. Nevertheless, detailed explanationwas given to both participants and relatives before verbal consent was obtained.

In October 1988, all participants were contacted by phone and asked to attend the SpataCommunity Health Centre to have their blood sampled. Blood pressure and anthropometry weremeasured and skin microtopography tested. It was explained that they would have their bloodtest results after 1-2 months from Australia, distributed through the health centre.

Anthropometry was performed on 70 subjects (M: 70-79 yrs = 26, 80+ yrs = 15; F:70-79 yrs =20, 80+ yrs = 9). A trained local researcher measured the height and weight of each subject. TheAustralian researcher measured the tricep skinfold (only one skinfold was measured), hip lengthand all circumferences. Equipment was not available to perform electrical impedance analysis.

The skin test was performed on 70 subjects (M: 70-79 yrs = 26, 80+ yrs = 15; F: 70-79 yrs = 20,80+ yrs = 9).

Blood pressure was measured on 70 subjects (M: 70-79 yrs = 26, 80+ yrs = 15; F: 70-79 yrs =20, 80+ yrs = 9); a local nurse measured systolic and diastolic blood pressure using a standardsphygmomanometer with the subject seated.

Blood tests were performed on 67 subjects (M: 70-79 yrs = 25, 80+ yrs = 15; F: 70-79 yrs = 18,80+ yrs = 9). A local researcher withdrew 20 ml of blood, which was immediately centrifugedand divided into three tubes which would be taken to Australia for the biochemical tests (seeSection 5.3.3).

About 1 ml of serum was removed to measure:

a) serum glucose (measured immediately after blood was drawn using the laboratoryprocedure 'glucose oxidase method'),

b) hepatitis B (stipulated by the permit to import biological specimens into Australia).


The serum samples were initially kept on ice at -4°C for a few hours and then transferred to-34°C. The centrifuged blood was sent to a local Greek hospital to have haematological testsperformed e.g. haemoglobin, platelet, lymphocyte counts, and haematocrit.


5.5 Swedes in Gothenburg Sweden E Rothenberg

E Rothenberg, O Augustsson, I Bosaeus and B Steen


This study of an elderly free-living population in a small area of Gothenburg (Johanneberg),Sweden, is part of two studies. On the one hand, it is the Swedish part of the IUNS transculturalstudy of food habits in later life. On the other hand, it constitutes the nutritional part of theJohanneberg project, which is a gerontological, socio-medical intervention project focusing onhealth, social network, activities of daily living, nutrition and hearing ability.

The apartment housing area, Johanneberg, was built during 1936-40. During the last three yearsmany houses have been cleared and renewed. The apartments are modern. Johanneberg is astable society. (It has a high proportion of elderly (31% are 65 years or over), and has very fewimmigrants. The sampling base for the study consisted of 340 individuals aged 70 and overliving in a geographically well defined central area of Gothenburg.

A sample of 217 subjects (M: 73, F: 144) was studied and recruited from the sampling base (seeTable 5.1). The sample was not found to be representative for age and sex distribution whencompared with the wider elderly population in Gothenburg. The Swedish study population wasnot representative of the Swedish elderly population as a whole. All subjects were from the samearea. They were, on average, healthy, active (both mentally and physically), and lived anindependent life. They had good food habits and knowledge about which foods are healthy. Thefemales were markedly older than the males which partly explains the differences between thesexes. Health status was more impaired in the higher age groups but the population was stillsurprisingly homogeneous and healthy (Table 5.1).

Table 5.1. Age Distribution of the Swedish SampleAge Men Women(yr) n % n %70-74 27 37 38 2675-79 25 34 42 2980-84 9 12 36 25+85 12 16 28 19


A total of 54 subjects were excluded from the study because:


a) currently living in an institution (n=27);b) change of address (n=7);c) dementia (n=5);d) died prior to recruitment (n=15)

This left 286 for investigation. Of these, 69 declined to participate. The Swedish studypopulation then comprised 73 men and 144 women (average ages were 76 and 78 yearsrespectively). Of these, 66 males and 122 females participated in the nutritional part of the study.The primary non-response was, thus, 24.1% and the secondary non-response for the nutritionalpart 13.4%.

The responders were more educated (p<0.01), generally professionals (p<0.01) and subjectivelyin better health (p<0.01) than the non-responders. The responders were younger than thenon-responders, (77.8 compared to 78.6 years). Reasons for not participating were disability andpoor health especially in those aged 80 and over. In the group below 80 years the most commonreason was lack of time and that the individuals regarded themselves too healthy to participate.Some reported family reasons and others unwillingness or fear. The reason for secondarynon-response was mainly unwillingness due to tiredness.


The same protocol as in the other IUNS studies was used. A research nurse was responsible forthe completion of the health and life-style part. This part was identical with the originalquestionnaire. For the nutrition part, a dietician was responsible. The interviews were performedin the probands' own homes first by a registered nurse and then some days to three weeks laterby a dietician. Each interview took on average between 1.5 to 2.5 hours. Three nurses and twodieticians performed the interviews, after a period of training to minimise interobservervariation.

5.5.4 Modification and Application of questionnaire

Thirty-three local Swedish food items and dishes were added to the food frequency part of thequestionnaire. To facilitate estimation of serving sizes, colour photographs of small and largeportions were used. Since fruit and berries are eaten mainly when in season, subjects were askedto indicate if consumption was seasonal.

The Swedish Food Composition Tables, were used to analyse the food intake data. The nutrientanalysis program used took into consideration average cooking losses of thiamine (30%),riboflavin (25%), niacin (15%), vitamin B6 (20%) and ascorbic acid (50%).

Complete information about income per year (ECO103) was difficult to get from the probands.This information must be interpreted with care, and therefore supplemented information about


income was obtained from the Tax Charge Office.

Anthropometric measurements were performed by three registered nurses. Lean body mass andtotal body water were estimated with bioelectrical impedance. Blood pressure was measuredwith subjects sitting, using a sphygmomanometer. Anthropometric measurements were made asinstructed in the IUNS protocol.

Fasting blood samples were collected by registered nurses or laboratory assistants from all studysubjects. The following biochemical variables were measured:

• Haemoglobin (g/l)• LPK (x 100 9/l)• Total lymphocyte count (% lymphocytes x white blood cells/100)• TPK (10 9/l)• Glucose (mmol/L) in serum• Cholesterol (mmol/L) in serum• High density lipoprotein (mmol/L)• Triglyceride (mmol/L) in serum• P-cobalamine (pMOL/L in plasma• P-folate (nMOL/L) in plasma not in serum• B-folate (nMOL/L) in blood, not in serum• Creatinine (mmol/L) in Sweden estimated in the unit (mmol/L) in serum• Ferritin (mG/L) in serum

All variables were determined with standard methods. Cutaneous microtopography Intra- andinterobserver variation studies have been performed in Gothenburg, and Melbourne. The foodhabits of Swedes are strongly influenced by the cattle and crops available. The country ischaracterised by stability and continuing development and economical growth. Thisdevelopment has also marked the food habits. The probands found it therefore difficult to reportchanges in their food habits over the past 50 years.

Changes have chiefly depended on:

• Influences from other cuisines such as French, Greek and Italian because of immigrationof these groups to Sweden and tourism from Sweden to countries in southern Europe

• Improved food distribution and storage systems• Health propaganda

The habits have moved towards more vegetables, fruit, high fibre bread and low fat products aslow fat milk, cheese and spreads. This is also seen in the answers to questions about food beliefs.The Swedes are on average are well aware of which foods are healthy and unhealthy.Interestingly enough, no marked age differences were noticed in either food beliefs or in food


choice.


5.6 Filipinos in Manila P de Guzman


The elderly in this study were from an urban community and residential institutions for theelderly. One institution is managed by the government and the other by a religious organisation.

San Juan, the urban community, is one of the seventeen cities and municipalities in metropolitanManila. It has an estimated population of 226,000 distributed in twenty-one villages. Themunicipality, which is located at the heart of the metropolis, depends largely on income derivedfrom industrial establishments and affluent subdivisions. It is a heterogeneous communitycharacterised by a large influx of migrants from different provinces outside Metro Manila. Theresources available in the community vary from health and medical facilities owned and operatedby the local government and private practitioners. Other amenities include a market, shoppingcomplex, church, mini-parks, private and government schools. The municipal government has itsown local unit of social welfare which caters to prioritised groups identified by the Departmentof Social Welfare and Development (DSWD) which includes the elderly.

Golden Acres is a government institution for the elderly. It is managed by the DSWD and relieson national government funds and support from non-governmental organisations andcivic-spirited individuals, and is manned by a team consisting of a medical doctor, registerednutritionist-dietician, social workers and welfare aides. The elderly residing in this institutionwere referred by social workers from different DSWD local units after a brief interview andappraisal. Walk-ins were also accepted on emergency cases but further investigations were alsoconducted for some socio-economic information.

Religious of the Virgin Mary (RVM) is a private organisation with a special unit providing careand concern to ageing nuns of the congregation. RVM has modern dining, medical, clinical,social and therapeutic facilities financed and maintained by the religious order and benefactors.The elderly in this institution enjoy warm attention from a team of nuns composed ofgerontologists, nurses, midwives and attendants.


The pilot study covered two groups of elderly. The first group are those residing with theirrelatives (n = 212) and the second group are those found in institutions (n = 129). For group 1,the communities or barangays were selected from the 19 barangays in San Juan, Metro Manila.For group 2, these were the Golden Acres Home for the Aged and the Religious of Virgin Mary(RVM) Home for the Aged. A two-stage stratified sampling design was employed for the firstgroup which are the barangays in San Juan, Metro Manila. The sample size per barangay wasbased on the present population of the aged in the area.


Table 5.6.2.1 1991 Population of 60 years old and over for Barangay, San Juan, MetroManila.

District N1. Balong Bato 2572. Batis 3443. Corazon de Jesus 4254. Ermitano 1435. Pasadena 1256. Pedro Cruz 1777. Progreso 728. Rivera 1179. Salapan 30710 San Perfecto 14611. Tibagan 13312. Halohalo 14213. Isabelita 5114. Little Baguio 20415. Maytunas 8816. Onse 15517. Sta. Lucia 26518. West Crame 48319. Kabayanan 187

TOTAL SAMPLING BASE 3821Determination of sample size for San Juan, Metro Manila: Community-based elderly sampling base, n = 3821.

n = [N * Z2 * p * (1 - p)] / [N * d2 + Z2 * p * (1 - p)]Where:• N is the total number of sampling units in the population;• Z is the prescribed reliability;• p is the proportion of sampling units in the population relevant to the study;• d is the maximum error deemed acceptable;

In this study:• N = 3821;• Z = 3.000;• p = 0.5 (if p is not known);• d = 0.10;

Study sample:

n = 212 = [3821 * (3.0)2 * (0.5) * (1-0.5)] / [3821 * (1.10)2 + (3.0)2 * (0.5) * (1- 0.5)]


Determination of Sample Size for Golden Acres: Institutionalised elderly sampling base, n =300.

n = [N * Z2 * p * (1 - p)] / [N * d2 * Z2 + p * (1 - p)]

Where:• N is the total number of sampling units in the population;• Z is the prescribed reliability;• p is the proportion of sampling units in the population relevant to the study;• d is the maximum error deemed acceptable.

In this study:N = 300;Z = 3.000;p = 0.5 (if p is not known);d = 0.10.

Study samplen = 129 = [300 * (3.0)2 * (0.5) * (1 - 0.5)] / [3000 * (1.10)2 + (3.0)2 * (0.5) * (1 - 0.5)]

Table 5.3. Randomly Selected BarangaysBarangays No of respondents

1. Balong Bato 362. Corazon de Jesus 363. Pedro Cruz 364. Isabelita 365. Sta. Lucia 366. West Crame 36

TOTAL 216


Two types of data were gathered for this study. These were primary and secondary data. Theformer was obtained from the sampled respondents while the latter was collected from availabledata/ information in the community, municipality or institution. Four sets of instruments/questionnaires were formulated in order to gather the needed information.

These are as follows:Set 1. includes both the non-nutritional and nutritional variables; using the IUNS instruments;Set 2 includes the anthropometric data;


Set 3 provides information on the biochemical status of the respondents;Set 4 provides guide questions used during the Focus Group Discussions.

Anthropometric measurements were collected using methods suggested by trainednutritionist-dieticians. Weight and height were measured on all study subjects according to theIUNS protocol. Mid-upper arm circumference and only one skinfold (tricep) were alsomeasured.

5.6.4 Modification of questionnaire

The food frequency method was not suitable for use on Filipino elderly. One-day food intakedata using 24-hour recall technique seemed more appropriate for use with this study group.


5.7 Chinese in Beijing, PRC YF Wang & D Roe


The Beijing Study was carried out from November 1990 to February 1991, with twocommunities from different districts of the urban area of Beijing. The elderly were defined as 55years and over (55+ for women and 60+ for men) because:

1. this represented the upper decile of the population in Beijing and2. life expectancy at birth for China is about 60-70 years.

The IUNS protocol stipulated a sample size of about 100 men and 100 women. The sample sizein this study was also computed using information derived from the 1986 Nutritional Survey forElderly Population in Six Different Geographic Areas in China. Specifically, the standarddeviations of fat, protein and vegetable intakes were used from previous studies to confirm anideal sample size for the study of Chinese elderly.

Consider rating vegetable and milk intake, the total sample size was computed to be 300,including 150 men and 150 women. However, the proportion of females (two thirds) in the over60 age group tends to be larger than that of men (one third), as women outlive men by a marginof 4-10 years throughout the industrialised world, as well as in China.

The present study randomly recruited a total of 305 subjects (M: 124, F: 181). In both studycommunities, male subjects represented about 40% of the total study sample.

The two communities were selected based on their differences in socio-economic situations,mainly education level and occupation distribution. Community 1 located in one of the foururban districts (Chongwen District) of Beijing; Community 2 is from Fengtai District, asemi-urban district. However, the location of this community is in an urban area. The selectionof the study communities also depended on the co-operation of the district Health Departmentand Community Organisations. Two communities were selected from two different districts ofthe urban area of Beijing in order to achieve the wider variability in demographic characteristicsof the study subjects, such as economic status, occupation and education level.

The residents in two communities were all registered as non-agricultural residents. However, thecharacteristics of education level, occupation, and economic status of residents in these twocommunities were expected to be different from each other.

Community 1 consisted of mainly blue collar workers with a lower level of education, especiallyamong older women. This community had 863 households with a total of 2,555 residents,including 1,283 males and 1,272 females. The number of residents who were over the official


retirement age (60 for men and 55 for women) was 387 according to the resident registrationrecords. This represented 15 per cent of total population in this community.

Community 2 is an area where most residents are professional, technical workers or governmentofficials and most of them have a higher level of education than the residents in Community 1.There were 490 households in this community with a total of 1,197 residents. Among them,49.5% (588) were male and 50.5% (599) were female. There were 220 people of retirement agein this community, according to resident registration record, which represented about 18% of thetotal population in Community 2.


All elderly people resident in the study communities (which means they were registered asnon-agricultural population), aged 60 and over for men and 55 and over for women were eligiblefor participation in the study. All subjects were non-institutionalised and non-hospitalised, freeliving, healthy elderly. All subjects recruited (M: 124, F: 181) agreed to be in the study. Theresponse rate was defined as the percentage of elderly who responded to the letters of invitationto participate in the study. The non-response rate was the percentage of the elderly who receivedthe letter but did not respond. The refusal rate was determined as the percentage of elderlypersons who responded to the letter but decided not to participate in the study after beingcontacted. The response rates were 96.3% and 93.7% for communities 1 and 2 with an overallaverage of 95.2%. Sixteen people (7 in Community 1 and 9 in Community 2) did not respond tothe letter, making the non-response rate 3.1% and 5.6% for community 1 and 2, respectively.The refusal rates for the two communities were 0 and 2.8 per cent respectively (see Table 5.4).

Table 5.4. Response and refusal rates for the study communitiesCommunity Responses Non-response Refusals

Contacted No. % No. % No. %1 191 184 96.3 7 3.7 0 0.02 142 133 93.7 9 5.3 4 2.8Total 333 317 95.2 16 4.8 4 1.2

From the response and refusal rates, it was estimated that a total 333 elderly people agreed toparticipate the study, of which 184 were in Community 1 and 133 in Community 2. However, 8(7 in community 1 and 1 in Community 2) of these subjects had to be excluded from the studybecause of physical or mental ill health. Therefore, the final number of study participants was305 (177 in Community 1 and 128 in Community 2), and they represented 45.7% and 58.2% ofretirement age population in Community 1 and 2, respectively.

5.7.2.1 Gender Distribution


Overall 41% (124) of the subjects were male and 59% (181) of them were female. Statisticallysignificant gender differences were not found between the two communities (P > 0.05). Thestudy subjects in both communities consisted of 40% males and 60% females.


The district administrative offices were used to obtain information on subjects aged 55 and over,including name, age, sex, address, occupation and education. A consent letter was subsequentlysent to eligible elderly explaining the purpose and procedures of the study. Finally, those whoindicated their willingness to participate were contacted to schedule a date for an interview.

The assistants who helped in data collection were trained locally in conjunction with theDepartment of Geriatric Nutrition, Institute of Nutrition and Food Hygiene, three weeks beforethe interviews began. Training included an explanation of the study purposes, an explanation ofthe questionnaires, advice on the appropriate language to use when interviewing subjects, andfamiliarisation with the equipment used for anthropometric assessments, blood pressure andblood glucose.

Appointments for home visits were scheduled by the interviewer and community workers. Thesubjects who were absent from home on the first visit were requested to choose another time fora second visit. During the home visit, the questionnaire was administered. Records ofprescription and non-prescription drugs taken by respondents were obtained by recordinginformation on the labels of medications. Anthropometric measurements of weight, height, kneeheight, mid-arm circumference and triceps skinfold thickness were assessed, as well as bloodpressure and blood glucose. The home visit was completed in about 45 minutes, the interviewtaking about 30 minutes and anthropometric measurements about 15 minutes for each subject.


The questionnaire designed for IUNS study was modified according to the characteristics of foodhabits, living style and culture in the Chinese population, especially the elderly (see Table 5.5).Some questions were dropped because they were either irrelevant or non-acceptable to Chinesesociety or culture. A copy of the questionnaire used is included in Appendix (A). Furthermore,the 24 hour recall method was included, along with the food frequency questionnaire, to obtainfood intake data.

Currently, there are two versions of the Chinese food composition tables, both of which wereused in this study to convert food intake data to nutrients. Each subject was asked to recall all thefoods and amounts he or she had eaten in the last 24 hours. All recalls were conducted onweekdays. The utensils commonly used in the household, such as cups, bowls, dishes, glasses, aswell as spoons were used by subjects to identify their "serving size".


All anthropometric measurements were made by trained researchers and checked forinter-observer variation. Measurement included weight, height, knee height, mid-armcircumference and tricep skinfold. Blood glucose was measured using the Ames Glucometer(model # 5550) with a read out screen. Since the interviews were not conducted in the earlymorning, the time of the last meal was recorded in order to interpret blood glucose levelsaccurately. Measurement was in mg/ dl. Blood pressure was measured on the left arm of thesubject using a standard mercury sphygmomanometer, with the subject sitting. Threemeasurements were taken and the average value was recorded. Before converting the dietarydata into nutrient intake data, the following modifications on the food composition tables wereconducted to get a complete dataset for foods consumed by the study subjects:

1. Food names were checked against the new food composition tables. A matching foodfrom the earlier version was taken if a food item could not be matched in the new version.If an exact match was not found a similar food was chosen as a substitute.

2. A significant number of food items have missing values for different nutrients. This couldresult in an underestimation of nutrient intake and cause errors in the process ofcomputing nutrients. Each blank data point was filled with a value taken from previousfood composition tables or from other sources.

3. At the time when the nutrient conversion was performed, there was no computer storedfood composition database. A DBase database for food composition was created on thebasis of a preliminary data file written in Chinese. The food composition data was thentransferred into mainframe in the ASCII format, and actual nutrient conversion wasperformed in Mainframe using the SAS program.

Table 5.5. Differences between the IUNS and Beijing Questionnaires1. Questions irrelevant to society or culture:a) Omission of questions on eating out.b) Modification of questions on foods purchased, cooking methods and foods eaten.c) Omission of questions on country of birth of respondent and direct relatives.2. Questions not acceptable for political or other reasons:a) Omission of questions on living with someone of the opposite sex without marriage.b) Omission of direct question about religion, information was elicited about attendance at

church/ religious meeting place.3. Questions related to local practice:a) Modification of food-related questionsb) Modification of leisure time activity questions4. Related to time constraints:a) Omission of questions on food beliefsb) Reduction in question on well being


c) Reduction in question on social activities


5.8 Chinese in Rural and Urban Tianjin, PRC S Xi


Samples were drawn from urban and rural parts of Tianjin. Subject selection was based onincome, life characteristics, population composition and convenience in field work. Tianjin iscomposed of six boroughs and five affiliated counties. The administrative structure from thelowest to highest in urban areas are the resident committee, subdistrict office, borough and citygovernment. The resident committee is the basic urban administrative unit, responsible for theaffairs of several hundred households. Our work was conducted at this level.

Photo 5.8. Rural Tianjin, China (1989): location chosen for the study atthe foot of the mountain.

A total of six resident committees were selected using the method of drawing lots from sixsubdistricts which themselves were selected using the same method from two boroughs. Hepingand Hedong respectively representing the typical business districts and industrial districts ofTianjin. In addition, people living in those two areas have different educational backgrounds,thus probably influencing their life characteristics.

The rural location, 100 km north of downtown Tianjin, was mainly chosen on the basis that theannual income was very close to the average income per citizen (800 RMB) of similar age andlife characteristics. Typical farming life is less influenced by urbanisation than the downtownareas.


Photo 5.9. Rural Tianjin, China (1989): study was supported by villagecouncil (left); researcher Dr Xi Si de (right).

The sampling process in the urban area was implemented with the help of community doctors.Firstly, they provided the list of all the elderly living in the selected resident committee, thendivided them into healthy and unhealthy groups according to their disease record, using thecriteria recommended by the Chinese Medical Society. In order to ensure 60 subjects for eachgroup, we selected 70 subjects in the beginning using the random sampling method.

Sampling in the rural location was also helped by two village doctors who gave us the list of allthe elderly within the village aged 70 years and over. Since there is no disease record kept inrural areas, we could not group them first and had to interview all the subjects. In this case, wecould not balance the number in each group. The sample dietary survey was taken from theinterviewed cohort. A total of 200 subjects (100 from urban and rural location, respectively andequal numbers for healthy and unhealthy groups) were recalled after finishing the questionnaireinterview.


Except for some persons who were unable to speak or stand or had some other troubles inaccepting interview and measurements, all of the subjects accepted the interview. The followingproportions of elderly refused to be in the study: 11.4% [8], 8.6% [6] and 8.6% [6] respectivelyfor the group of healthy males, unhealthy males and unhealthy females.


Photo 5.10. Rural Tianjin, China (1989): a woman aged 94 years old wasbeing interviewed Dr Zhang.

Photo 5.11. Rural Tianjin, China (1989): measuring blood pressure at theresearch centre.

Photo 5.12. Rural Tianjin, China (1989): an elderly was being interviewedby Professor Ming-Tan Sun.



The questionnaire was conducted first. In the urban location, we were guided by the communitydoctors who were also responsible for the interview process in participants' households. Sincethe community doctors were well acquainted with every subject, interviews were managed in arelaxed atmosphere. The research team was responsible for anthropometric measurements. In therural location, subjects were informed prior to the interview day and subjects who could walkwere requested to gather in the office of the village committee to wait for interview. For thedisabled subjects, we asked at least one family member or relative to stay at home when theywere visited.

The interview process of the questionnaire took, on average, one hour for each subject. Thedietary survey was conducted at the end of the questionnaire. In order to diminish the influenceof seasonal change, the four seasons were generally included in the dietary survey. Due to timeconstraints, we could not conduct a study in each season. We chose the period from May 1 toNovember 30 that we thought to be most representative. In North China, vegetable suppliesincrease in May and decrease in November.

Photo 5.13. Rural Tianjin, China (1989): village men waiting to beinterviewed.


5.8.4 Modification of questionnaire

The 24-hour recall method was chosen after weighing the advantages and disadvantages of thevarious dietary methods. This is the most frequently used method in Chinese dietary surveys.The weighing method is complicated and time consuming and more unreliable for the elderly.The self-recording method is impracticable because very few elderly were educated and if weask their family members or relatives to do the recording, they often forget or ignore the process.Dietary recall possesses the advantages of being simple, time-saving and more valuable in thecase of Chinese elderly whose diets have less daily changes and are simply made. To minimisethe impact of daily intake diversity, three consecutive days were recalled by each subject. Eachsubject was visited three times, and food items, serving size and cooking methods used duringthe preceding 24 hours were recorded.

The number and age of all persons sharing a meal was also recorded. The subject wasencouraged to follow their usual food habits and intakes. The 24-hour recall provedcomparatively more convenient and precise, particularly since the diet of elderly Chinese issimple, composed of less than 3-5 types of foods daily. Of these, steamed bread, rice, noodlesand pancake are eaten most often. These foods are simply made from flour or rice.

The quantities of ingredients used in cooking of such staple foods was calculated. The estimationof subsidiary foods was more complicated, because they were usually cooked in a mixed way:one vegetable or more, meat and seasonings and they were often served in one dish at the dinnertable. We had to ask how many kinds of subsidiary foods were cooked, including the quantitiesof each kind and how many members accompanied the subject during meal time, everyone's ageand intake situation. By weighing each member's intake, we then could estimate the portioneaten by the subject. Cooking oil, salt and sugar were recorded in monthly estimates at the end ofthe recall and then converted into quantities of daily consumption.


China is quite different in cultural background and life habits from Western countries, forexample, with respect to privacy, immigration and personal relationships. Therefore thequestionnaire was adapted to suit Chinese cultural background.

Photo 5.14. Rural Tianjin, China (1989): a 94 year old woman answeringquestions independently.

Part 1: These items were added to the questionnaire:

1. J08-J10 (Tianjin code):Family support is the traditional way of caring for the elderly. Atmosphere betweenfamily members is considered very important in influencing elderly health status withdietary intakes.

2. K08-K10:Living condition is generally considered to be relative to one's social position in China.Most of the housing is government owned. A person who has a higher social positionoften is well treated.

3. G05-G07:Physical exercise especially beginning early in their twenties is considered helpful forlater health.

4. M01-M02:Chinese like to add salt and sugar in the cooking process, not at the dinner table.


5. Q02-Q03:Breakfast is often ignored by Chinese, but is considered harmful to remain empty duringthe whole morning. Also, irregular meals (no fixed meal time) are considered harmful byChinese.

6. D20:Misfortune is considered very harmful to one's health status by Chinese.

7. Food frequency:We used the consecutive 3 x 24-hour diet recall to represent usual food intakes. The24-hour recall method was chosen after weighing the advantages and disadvantages of thevarious dietary method as described above. Rather than date past food intakes from beforethe second world war, we thought the marker should be 1949, when the People's Republicof China was founded. Chinese people consumed a limited variety and quantity of foodsbefore 1949 because of the long civil war and natural disasters. Therefore, it was onlypossible to use the description of "much less" to past food intakes. In addition, theMelbourne questionnaire includes more than 10 pages of food items, but Chinese foodschange much less from day to day and the number of different types of foods eaten dailyare very small. Going through this long list of foods in the food frequency questionnairewould take too much time and we were afraid that subjects would become impatient.

Part 2: These questions were excluded from the Tianjin questionnaire.

1. Migration:How many years have you been in this country? This is not possibility for Chinese.

2. H43x-H43y:It was difficult for elderly women to remember the date of their first menstrual period andalso elderly Chinese women are ashamed to answer this question, especially in ruralareas.

3. Chinese activities of daily living are different and were thus changed to suit Chineseculture.

4. Social activities:Very few elderly Chinese after 70 years still have social occupations or social activitiessuch as eating out.

5. SAR97C-SAR97D:Very few elderly were educated or had a telephone in their house.

6. DH60:


Chinese elderly seldom eat out.

7. DH66-67B:Very few elderly Chinese believe in religion or follow one. If there is religion, fastingpractices were enquired about.

8. DH68:Chinese people tend eat fat on meat, DH69: same as DH68. DH71: Chinese like to addsalt or sugar during cooking.

9. DH720N:Chinese never pay attention to what brand of oil they consume.

Some additional background:

1. Males generally enjoy privileges in food distribution within the family, especially in ruralareas.

2. Males earn money to support the family while females stay at home and do housework.3. Migration: changing one's living place is not allowed in China.4. Males have more power inside family.5. Remarriage and divorce are often unacceptable.6. Inharmonious relations between family members is often considered a private matter.


5.9 Swedish Validation Study E Rothenberg, I Bosaeus & B Steen

5.9.1 Introduction

Several authors like Willett, Burema & van Staveren, Isaksson and Bingham [9-12] haveindicated that validation of dietary intake by other methods as well as biomarkers is veryimportant. Validity refers to the degree to which the method actually measures the aspects of dietthat it was designed to measure. There are of course no "gold standards", but two differentapproaches to validate a dietary assessment.

First, the method can be compared with another dietary assessment judged to be superior, or withother methods involving different errors. The most commonly used approach to validate a diethistory or semi-quantitative food frequency is the use of diet record. This method is by someauthors assumed to be more accurate and precise than the diet history. In contrast, this methodrecords rather than reports the pattern and intake, and because of that is unlikely to overestimatethe intake. It can underestimate actual intake because it catches, as Block and Hartman noticed[13], only snapshots of the diet.

Another approach is to validate against a biomarker. The fundamental advantage in using abiomarker is that measurement errors are essentially uncorrelated with errors in any dietarymethod. The food frequency method used in the present study was designed to estimate food andnutrient intakes of populations in different parts of the world. Validation of the food frequencyquestionnaire was performed to determine to what extent the data collected were representativeof true food intake in the Swedish population.

5.9.2 Population and method

5.9.2.1 Population

The population in this study comprised 25 randomly selected individuals, (M: 10, F: 15). Theaverage age was 77 years; 74 for men and 79 for women. BMI was on average 25.7, (M: 27.7, F:24.7) compared with a slightly lower mean for the whole study population (M: 25.3, F: 24.0).

5.9.2.2 Food record method

The subjects completed a 4 day estimated record approximately six months to one year after thefood frequency data collection. The interviewing dietician visited each proband prior to urinecollection and recording days to review the procedures. The recording was performed on apurpose designed questionnaire, which had clear instructions on how to describe the food eaten.The probands were instructed to continue normal eating habits and to keep a complete andaccurate record for 4 consecutive days, including 3 weekdays and one weekend day.


The subjects expressed all quantities in common household measures and provided a completedescription of the preparation and cooking methods. The records were then checked by thedietician.

5.9.2.3 Collection of urinary nitrogen

Twenty-four-hour urine samples were collected during the same period of time as the food wasrecorded. The subjects were told to discard the first portion of morning urine and then collect allurine, including the first portion on the next day, and to keep the container cold. The collectionwas frozen and urinary nitrogen was analysed using the Technicon Autoanlyzer Method N-3b.Urinary nitrogen was converted to protein intake according to Isaksson [11]. This conversionassumes nitrogen losses of 2.0 g per day.

5.9.3 Results

Mean energy intake for the food frequency method was 10.4 MJ compared to 7.9 MJ with the4-day record. Correlation coefficients varied from 0.29 (thiamine) to 0.66 (calcium), with a meanof 0.47. For comparison between the methods see Table 5.6.


Table 5.6. Food frequency versus 4-day food record and urinary nitrogen. Mean intake(M) for and correlations (r) between nutrient estimates by the 4-day foodrecord, food frequency method in 25 probands.

FFQ as Food Food fre-unadjusted adjusted% of record quency

M M r p r p RecordEnergy (KJ) 7903 10432 0.45 <0.05 135Protein (g) 66 90 0.49 <0.05 0.67 <0.001 137Fat (g) 73 100 0.42 <0.05 0.05 NS 144Carbohydrates(g) 227 298 0.44 <0.05 0.25 NS 135Alcohol (g) 7.3 6.3 0.65 <0.01 0.54 <0.05 102Total sugar(g) 85 114 0.59 <0.01 0.45 <0.05 154Fibre (g) 17 24 0.56 <0.01 0.52 <0.01 144Vitamin D (mg) 4.4 8.4 0.28 NS 0.10 NS 249Thiamine (mg) 1.41 1.63 0.29 NS 0.23 NS 124Vitamin C (mg) 87 135 0.33 NS 0.24 NS 194Calcium (mg) 834 1037 0.66 <0.001 0.77 <0.0002 132Iron (mg) 14 19 0.53 <0.051 0.39 <0.06 141

Data for all nutrients except energy and vitamin C were transformed using log to reduceskewedness and improve normality, as required by the statistical assumption of tests related tothe correction coefficient, unadjusted and adjusted for energy.

Relative contribution to total energy intake by the macronutrients were almost identical for theboth methods (See Table 5.7). The proportion of subjects within the same tertile, andmisclassification, was on average 46% and 11%, respectively (see Table 5.8). The confidencelimit was 95%, for standard errors of the mean for both dietary methods see Table 5.9. Urinarynitrogen showed a mean protein intake of 82 g per day, compared to 90 g for the food frequencyand 60 g for the food record method.

Table 5.7. Relative contribution to total energy intake (%).Frequency Food record FoodProtein 15 15Fat 35 31Carbohydrates 48 49Alcohol 1.8 1.6Total sugar 18 18


Table 5.8. Per cent in the same third of distribution, and overall misclassification,defined as per cent of total sample in both food record (FR) and foodfrequency (FFQ). U = urinary analysis.

Nutrient Same third Overall misclassificationEnergy 36% 16%Protein 60% 8%Protein U vs FR 58% 4%Protein U vs FFQ 38% 17%Fat 44% 16%Carbohydrates 48% 16%Alcohol 36% 4%Total sugar 48% 4%Fibre 44% 8%Vitamin D 46% 24%Thiamine 44% 8%Vitamin C 40% 12%Calcium 72% 4%Iron 44% 8%


Table 5.9. Confidence Limit 95% and Standard Error of Mean: SEM for the FoodFrequency Method and the 4-Day Record Among 25 Probands.

Food Frequency Method 4-day RecordNutrient 95% SEM 95% SEM

confidence confidencelimit limit

Energy (KJ) 9214-11651 591 7184-8623 349Protein (g) 79-101 5.3 60-73 3.1Fat (g) 87-112 6.2 64-82 4.4Carbohydrates(g) 258-339 20 203-251 12Alcohol (g) 3.5-9.1 1.4 3.5-11 1.8Total sugar (g) 94-134 9.8 67-102 8.6Fibre (g) 20-28 2.0 15-20 1.1Vitamin D (mg) 7.3-9.5 0.55 2.9-5.9 0.73Thiamine (mg) 1.4-1.9 0.11 1.2-1.6 0.09Vitamin C (mg) 103-167 15 71-104 8.0Calcium (mg) 872-1201 80 695-973 68Iron (mg) 16-22 1.4 12-15 0.75

5.9.4 Discussion

Validation of the food frequency questionnaire against the 4-day record method showed anaverage energy intake of 10.4 Mj and 7.9 Mj respectively. Different authors [14-17] have shownthat the diet history method, which is very similar to the food frequency method, gives about20% higher nutrient intake estimates than other short-term methods. The average of the foodfrequency estimates as a per cent of the food record based on individual differences would be147%. Of course, this way of comparing is questionable and comparisons must be madecarefully. However, it gives an opportunity to examine this study in relation to other studies evenif the reference methods vary. For comparison with other studies see Table 5.10.

The difference between the urinary protein measure and the food frequency was, based on meanvalues, 10% compared with 23% with the diet record method. However, based on individualvalues the difference was higher between the food frequency and the urinary protein measurebecause of separate extremely low urinary protein values. The correlation coefficient betweenurinary nitrogen and the food frequency method was 0.23 compared to 0.36 with the diet recordmethod. None of the correlations were significant, partly because of the small number ofsubjects. The proportion of misclassification was greater for the food frequency method than forthe food record. Higher correlation and smaller misclassification for the food record can beexplained by the fact that the urinary collection was made under the same period as the dietrecord and that the food frequency method reflects food intakes during a longer period of time.


Table 5.10. Earlier validation studies and resultAuthors Range of Dietary Method Population

correlationMahalko, 1985 0.22-0.76 7-day record 54 older adults 71±9 year (28)Jain, 1980 0.13-0.66 7-day record 16 males (25)Willett, 1985 0.27-0.53 7-day record 173 females (30)

0.18-0.53 Means of 4 records 173 femalesPietinen, 1988 0.40-0.80 2 12-day records 297 males 55-69 years (24)Larkin, 1989 0.26-0.62 16 day record 64 white males (27)

0.27-0.57 16 day record 73 white femalesBoutron, 1989 0.31-0.90 14-day record 20 males and females (29)

0.03-0.62 14-day record 20 males and femalesPototsky, 1990 0.35-0.65 4-day record 97 females 45-70 years (31) years (32)Engle, 1990 0.16-0.33 50 males and females, 49-96Block, 1990 0.47-0.71 4 x 3-day record 102 females 45-70 usual diet group (33)

0.37-0.74 158 females 45-70 low fat groupEURONUT, 1991 0.18-0.78 3-day record 59 women and 23 men (34)

Willett (1), Energy adjusted correlation coefficients for questionnaire 1 vs record 1.; Willett (2),Correlation coefficients for questionnaire 1 vs means of 4 records; Pietinen, Correlationcoefficients for 25 nutrients; Boutron, Spearman's rank order correlation coefficient were usedfrom questionnaire, 3) by meal, and questionnaire, 4) by food groups; Pototsky, Correlationsbetween estimates from a single 4-day record, except correlation coefficient for per cent energyfrom fat; Engle, Spearman's rank older correlation coefficient were used for seven nutrients, exceptcorrelation coefficient for per cent energy from fat; Block, Correlation coefficients for 23 nutrientsincluding supplements except correlation coefficient for per cent energy from fat; EURONUT,Correlation coefficients for 22 nutrients and energy. Record is weighed.

5.9.5 Conclusion

In comparison with urinary protein, we conclude there is an overestimation in the frequencyquestionnaire of at least 10% for protein, and we assume that this also applies to othermacronutrients. The questionnaire reflects well the proportion of energy from the macronutrientscompared to the food record. The range of correlations in this study is within the same range asin other validation studies. In relation to most other studies, the intake still remains high.However, this is a very healthy and active population. Similar energy intakes have recently beenreported from some populations in the EURONUT [18] study and from a study on elderly men inEastern & Western Finland [19].


5.10 Greek Validation Study, A Kouris-Blazos

5.10.1 Introduction

There is no gold standard in the assessment of individual dietary intake methodology [20,22].Food records for a few days or 24 hour recalls are commonly used to estimate short-term foodintake of individuals. These methods are expensive and unrepresentative of usual intake andtherefore may not appropriate for the validation of long-term intake as measured by foodfrequency questionnaires (FFQ) or diet histories, where the denominator is usually the 'past year'[9]. There is a great need for independent external validation of dietary measurement techniques.More appropriate methods for validating food intake methods, especially if measuring long-termintake, include [22-24]:

a) comparison of reported energy intakes with minimal energy requirements (MER);b) comparison of nutrient intake estimates with appropriate biochemical markers e.g. protein

intake vs urinary nitrogen excretion.

5.10.2 Reported energy intakes & minimal energy requirements

Bias in energy intake will lead to false conclusions if the aim of the study is to establish themean population intake and the probability of malnutrition, particularly relevant in elderlystudies. In the past, the incidence of undernutrition has been overestimated due to thecombination of a biased (low) mean for energy and artefactorial extension of the range towardslow intakes [22]. Bias on the measurement of energy intake is likely to lead to bias onmeasurement of other nutrients closely correlated with total energy such as the macronutrientsand B vitamins. Basal metabolic rate (BMR) is a measurement of the energy expended formaintenance of normal body functions and homeostasis, plus a component for activation of thesympathetic nervous system. BMR accounts for 60 to 75% of total energy expenditure (TEE).The thermic effect of exercise represents the cost of physical activity above basal levels andranges from 15-30% of TEE in a moderately active individual. The thermic effect of foodaccounts for 10% of TEE and is the energy expended to digest, transport, metabolise and storefood. The Schofield equations for predicting BMR from body weight, age and sex are shown inTable 5.11. [25].

Table 5.11. Equations for estimating basal metabolic rate in Mj/ day from body weight(kg) (25).

Age EquationMales 10-18 (0.074 x wt) + 2.754 = BMR

18-30 (0.063 x wt) + 2.89630-60 (0.049 x wt) + 3.653


60+ (0.049 x wt) + 2.459Females 10-18 (0.056 x wt) + 2.898

18-30 (0.062 x wt) + 2.03630-60 (0.034 x wt) + 3.53860+ (0.038 x wt) + 2.755

The normal range of variation in BMR is such that most healthy individuals are expected to havemeasured BMRs which fall within about 10% of predicted values, although the range ofvariation is greater in infants and elderly [25,26]. Shah et al. [27], concluded that the equationscould be applied to normal weight women who had never been obese, but that theyoverestimated BMR in a group of normal weight but 'post-obese' women. Foster et al. [28],reported that the equations were not appropriate for moderately or severely obese patients. Thephysical activity level or PAL is defined as TEE divided by BMR.

Expressing expenditure as a multiple of BMR provides a useful index by which the activity levelof all individuals can be directly compared. The 1985 FAO/WHO/UNU report calculatedminimal energy requirements (MER) for maintenance or survival to be at least 1.27 X BMR forboth men and women. This allowed for minimum movement not compatible with long termhealth and made no allowance for the energy needed to earn a living or prepare food. The samereport used factorial calculations to estimate the MER associated with a sedentary lifestyle to be1.55. This covers the cost of processes essential to life (BMR), the thermic effect of food, plusthe cost of 'minimal' activity [29].

A cut-off limit of PAL = 1.55 for MER is recommended when validating energy estimatesderived from FFQ or diet histories reflecting long-term/ habitual intake. A dietary method isregarded as invalid if the population mean habitual energy intake is less than the MER calculatedfrom BMR and an activity factor [22,29]. There appears to be conflicting data on what isappropriate for the elderly [26]. As a general guide, various expert groups have judged theaverage energy requirement in healthy elderly men to be about 1.55 times the BMR [22,29],including the WHO/FAO/UNU report in 1985. To validate the FFQ in this study, the MER wascalculated for each subject by firstly calculating BMR using the Schofield equations for the 60+age group (see Table 5.11) and then multiplying by an activity factor of 1.55 (sedentary lifestyle)as recommended by Black et al., [22], Goldberg et al., [29] and WHO/FAO/UNU.

Wilcoxon signed rank test was performed to examine whether or not mean estimated energyintake from the FFQ was the same as the mean expected MER (Table 5.12). Subjects were alsocategorised into two groups; those whose energy intake estimates derived from the FFQ werehigher than the expected value derived from MER, and those who had a lower estimate.Differences in energy intakes were then tested (see Tables 5.12, 5.13).

The mean MERs were not significantly different from those estimated from the FFQ for men, butwere for the women (p=0.05). The percentage of subjects falling above and below 10% of their


MER is shown in Table 5.14. There were striking similarities in the percentage of men andwomen in both sites above and below their MER. Overall, 40%-50% of the men and women inSpata and Melbourne fell within 10% of their MER. About 40% of the women in both sites werebelow their MER when compared to energy intake estimated from the FFQ. Since the majority(two thirds) of women not meeting their MER were obese, this suggests either under-reporting ornegative energy balance to lose weight.


Table 5.12. Comparison of mean reported energy intakes (Mj/d) (FFQ) and expectedminimum energy requirements (BMR x 1.55).

Spata MelbourneMj/d (Kcal/d) Reported MER Reported MER

FFQ BMR x 1.55 FFQ BMR x 1.55MenN 51 41 94 92Mean 9.3 (2211) 9.4 (2236) 10.0 (2374) 9.6 (2277)SD 1.8 (435) 1.0 (234) 2.2 (533) 0.8 (201)Minimum 3.8 (907) 7.4 (1775) 6.0 (1437) 6.9 (1639)Maximum 13.6 (3246) 12.2 (2901) 20.0 (4764) 11.7 (2783)FFQ - MER -0.1 (-35) +0.2 (+48)WomenN 53 29 95 94Mean 7.2 (1708) 8.0 (1919)* 7.8 (1863) 8.2 (1953)*SD 1.9 (463) 0.6 (140) 1.7 (405) 0.8 (180)Minimum 4.0 (967) 7.0 (1677) 4.8 (1145) 6.2 (1487)Maximum 12.0 (2841) 9.5 (2262) 12.2 (2895) 10.6 (2529)FFQ - MER -0.5 (-129) -0.4 (-85)

*, p=0.05 Wilcoxon signed rank test comparing MER (minimal energy requirement) with FFQ (energy intakecalculated from food frequency questionnaire).

Table 5.13. Reported energy intakes (FFQ) falling above and below 10% of the MERwith reference to body mass index.

Spata Melbourne% above % below % above % below

BMR x 1.55 BMR x 1.55 BMR x 1.55 BMR x 1.55(+10%) (-10%) (+10%)- (-10%)

MenN 41 41 92 92all subjects 27% 24% 31% 25%subjects with BMI>28 5% 19% 13% 19%WomenN 29 29 94 94all subjects 24% 45% 21% 40%subjects with BMI>28 14% 31% 14% 29%

Alternatively, the PAL factor of 1.55 may be too high for elderly Greek women who are not asactive as their male counterparts (mean exercise score (range 0-7; M: 3.6; F: 2.8). However,when a PAL factor of 1.4 was used, the percentage of women not meeting their MER droppedonly to 30%. Compared to the women, half as many men (25%) were not meeting their MER, ofwhich more than two thirds were obese. This also suggests under-reporting by obese Greek menin both study sites.

Obesity was more prevalent overall in the women than the men (BMI >30; F: 42%, M: 27%)


which may explain the greater percentage of under-reporting (or attempts to lose weight) byelderly Greek women. Overweight and obese subjects have been reported to underestimate foodintake in other studies [30,31]. Comparisons with reported data: there is increasing evidence tosuggest that energy intake data tend to underestimate what is actually consumed, especially byelderly women [32] and obese subjects [22,33,34].

This conclusion is supported by studies of food intake observed under controlled conditions[34,35]. However, the diet history and FFQ method are less prone to underestimation [23]. In theEuropean study on 2000 elderly people aged 75 [18] in 19 centres located in 12 countries,women in seven centres had group means below the MER (BMR x 1.4) [32]. The chiefinvestigators of this study (de Groot et al., unpublished data) argue that such low values suggestunderestimation of energy intake. However, recent data from their institute (WageningenAgricultural University) showed an overestimation of predicted versus measured BMR by some9-22%.

This raises questions about the applicability of the Schofield equation for use in the elderly.Black et al. [22] stress the importance of such validation of dietary instruments because "it isimportant that the possibility of bias is acknowledged and that the data are examined with thispossibility in mind and interpreted accordingly...the common assumption that carefully collecteddietary data are valid is no longer tenable...this view had propagated many misleadinghypotheses and will continue to do so until corrected".

Black et al. [22] provide suggestions in determining whether data collected is biased/ valid: "Inany survey some individuals will be studied in a period of low intake and others in a period ofhigh intake. This is part of the normal random variation and does not produce bias, and the meanintake should reflect the habitual intake of that group. If the overestimates cancel theunderestimates, then no bias is observed and the mean intake reflects the habitual intake of thatgroup - the error of the measurement of individual intakes, however, is increased and the rangeof reported intakes may be widened". For the Greek men (but not the women), the overestimatescancelled the underestimates thus explaining why the differences between the reported meanenergy intake from FFQ and MER were not significantly different.

When interpreting the data on elderly Greek women, the following possibilities should be kept inmind. Either:

a) under-reporting is operating bringing down the means for nutrient intake (actual intake >reported intake) OR

b) negative energy balance is operating in an attempt to lose weight (actual intake = reportedintake) OR

c) the Schofield equation and the physical activity factor of 1.55 overestimate total energyexpenditure (actual intake = reported intake)


5.10.3 Reported protein intakes & urinary nitrogen excretion

Urine was collected from participants in Melbourne In order to validate the food frequencyquestionnaire by comparing protein intake calculated from urinary nitrogen excretion to proteinintake calculated from the FFQ. Urine could not be collected in Greece for technical reasons.Urine was collected over 24 hours, the day prior to blood collection, so that the urine could bebrought to the hospital.

Urine was collected using the following procedure: subjects were instructed to discard the firsturine on the morning of collection and to start collecting from the second urine onwards till thefollowing morning. The urine was kept in a cool place and brought to the hospital/ researchcentre on the day of blood collection. The urine was stored at -20oC. Urinary total nitrogen wasanalysed by the Kjeltec Kjeldahl technique (Tecator Ltd). Single measurements were performedat the Monash Medical Centre, Department of Clinical Biochemistry on a small subsample ofGreek subjects in Melbourne (M: 20, F: 10). The co-operation of subjects to collect urinecorrectly was fraught with difficulties. Of the 30 urine samples, only 21 were collected properly,which were subsequently used for the validation exercise (M: 14, F: 7). In the subsample, 71%of the women and 86% of the men were over 80 years old which was similar to the agedistribution of the whole sample (62% and 70% respectively).

Expected protein intake was calculated by using the following equation [36]:estimated protein intake = (24 hr urinary nitrogen (g) + 4g faecal/dermal loss) x 6.25

Expected mean protein intake calculated from urinary nitrogen was compared with meanreported protein intake derived from the FFQ using Wilcoxon signed rank test. The mean proteinintakes of men n=14 (110g/day) and women n=7 (94g/day) in the subsample were notsignificantly different to the sample means shown in the table in brackets (M: 110g/day n=94, F:84 g/day n=95). Subjects were also categorised into two groups; those whose reported proteinintake derived from the FFQ was higher than the expected value derived from urinary nitrogen,and those who had a lower estimate. Differences in protein intakes were then tested (Tables 5.14,5.15).

For the women in the subsample, the mean protein intake estimated from 24-hour urinarynitrogen output was not significantly different to the mean protein intake estimated from theFFQ. In contrast, the mean protein intake estimated from the FFQ for the men was higher thanthat estimated from urinary nitrogen (P=0.05). The validation of habitual protein intake usingFFQ or diet history with a short term biochemical measurement such as 24-hour urinarynitrogen, has been reported to be a poor marker of long-term or habitual protein intake [24].Bingham and Cummings [12] showed that single 24-hour urine collection can be substantially inerror. In healthy individuals with normal western diets, an 8-day 24-hour urine nitrogencollection was necessary to obtain habitual protein intake.


It has also been shown that individuals with a higher protein intake have a lower urinary nitrogenoutput than expected [12,37]. In summary, single 24-hour urinary nitrogen output is notappropriate for the individual validation of protein intake because the steady state condition israrely achieved in free-living individuals and large day-to-day fluctuations in protein intakeexist. The single 24-hour urinary nitrogen output, however, provides a good 'ball-park' figure forthe validation of group mean intake in the case where urinary nitrogen does not exceed theestimate of dietary intake over a short period of time [12]. Therefore, the FFQ used in this studygives a reasonable estimate of group mean protein intake.

Table 5.14. Comparison of mean reported protein intakes (FFQ) of a subsample ofelderly Greeks in Melbourne and expected protein intake (urinary nitrogenoutput).

Men WomenReported Expected Reported Expected

FFQ urinary FFQ urinarynitrogen nitrogen

N 14 (94) 14 7 (95) 7.0Mean subsample 110.0* (110) 90.0* 94.0 (85) 84.0SD 26.8 (11.2) 17.0 23.0 (23.4) 27.0Minimum 74.7 (65) 58.6 73.4 (38.2) 55.2Maximum 149.0 (188) 117.0 142.3 (160) 135.0FFQ-urinary +21 +10

* p=0.05 Wilcoxon signed rank test; FFQ = food frequency questionnaire .

Table 5.15. Reported protein intakes (FFQ) of a subsample of Melbourne Greeks fallingabove and below their expected protein intake (urinary nitrogen).

Men WomenN 14 7% above (+10%) 57 43% below (-10%) 7 14


5.11 Summary

Table 5.16 Participating communities: community code, location, ethnicity, and samplesize (men, women, and total).

SAMPLE SIZEMen Women Combined

Code Location Rural Ethnicity Young Old Young Old Young Old Totalor urban

ABOR* Fitzroy Crossing, Australia rural Aboriginal 16 4 16 7 32 11 43ACA Melbourne, Australia urban Anglo-Celtic 42 7 40 6 82 13 95GRK-M Melbourne, Australia urban Greeks 66 28 59 36 125 64 189GRK-S Spata, Greece rural Greeks 32 19 31 22 63 41 104SWE Gothenburg, Sweden urban Swedes 52 21 80 64 132 85 217FIL* Manila, Philippines urban Filipinos 33 41 109 98 142 139 281JPN-O Okazaki, Japan semi-urban Japanese 28 15 33 13 61 28 89JPN-H Hiroshima, Japan urban Japanese 37 53 90JPN-K Kumamoto, Japan semi-urban Japanese 43 48 91JPN-Y Yokohama, Japan urban Japanese 28 40 68CBJ* Beijing, China urban Chinese 80 45 124 56 204 101 305CTJ-R Tianjin, China rural Chinese 73 10 79 19 152 29 181CTJ-U Tianjin, China urban Chinese 107 19 102 32 209 51 260TOTAL 846 1167 2013

*, the upper decile of the community was sampled, 50 years and over for Beijing women and Aboriginal Australians,and 55 years and over for Beijing men and Filipinos.


Table 5.17. Age range, by study communityABOR* ACA GRK-M GRK-S SWE FIL JPN-O CBJ CTJ-R CTJ-U

MenYoung elderly 50-70 70-79 70-79 70-79 69-79 57-69 70-78 57-69 70-79 70-79Old elderly 70-80 80-84 80-97 80-91 80-91 70-83 80-91 70-88 80-89 80-87Total 50-80 70-84 70-97 70-91 69-91 57-83 70-91 57-88 70-89 70-87WomenYoung elderly 50-70 70-79 70-79 70-78 69-79 58-69 70-79 53-69 70-79 70-79Old elderly 70-80 80-94 80-104 80-94 80-96 70-91 80-87 70-95 80-94 80-96Total 50-80 70-94 70-104 70-94 69-96 58-91 70-87 53-95 70-94 70-96

*, relative age was obtained based upon members of the community.

Table 5.18 Information gathered, by study community.ABOR ACA GRK SWE FIL JPN CBJ CTJ

M & S H,K,O&Y R & UQuestionnaires yes* IUNS/mod IUNS** IUNS IUNS IUNS mod modFood intake yes* FFQ FFQ FFQ 24-hr FFQ 3-d 24-hr 24-hr FFQ 3-d 24-hrAnthropometry WT, HT all all all WT, HT, HT BMI all exc all

BMI, WHR BMI WT & WHR WHRTSF

Blood pressure no yes yes yes yes no yes yesBlood tests no yes yes yes yes no no no

*, RAP was used to obtain demographic and community food intake information.**, RAP was used to obtain information on food beliefs.


5.12 REFERENCES

1 Scrimshaw WS, Hurtado E. Rapid assessment procedures for nutrition and primary healthcare. Los Angeles, UCLA Latin American Centre Publications; 1987.

2. Wahlqvist M, Kouris A, Gracey M, Sullivan H. An Anthropological Approach to theStudy of Food and Health in an Indigenous Population. Food and Nutrition Bulletin1991(b)13,2: 145-149.

3. McArthur M. Food consumption and dietary levels of the Aborigines at the Settlements.In: Mountford CP (ed). Records of the American-Australian Scientific Expedition intoArnhem Land. Melbourne: Melbourne University Press, 1960: 14-26.

4. Cutter T. Nutrition and food habits of the central Australian Aboriginals. In: Hetzel BS,Frith HJ, eds. The nutrition of Aborigines in relation to the ecosystem of centralAustralia. Melbourne: CSIRO, 1978; 63-70.

5. Coles-Ruthishauser IHE. Growing up in Western Australia: if you are Aboriginal. ProcNutr Soc Austral 1979; 4: 27-31.

6. Lee A. Apparent Consumption of Food and Nutrients in Coastal and Desert AboriginalCommunities: Implications for Nutrition Education. In: Proceedings of the MenziesSymposium on "Nutrition and Health in the Tropics", Townsville. 26-27 August 1987:270-288 (ISBN 0731619358).

7. Wahlqvist M, Kouris A, Davies L, Scrimshaw N. Development of a Survey Instrumentfor the Assessment of food habits and health in later life. In: Moyal M (ed). Dietetics inthe 90s. Role of the Dietitian/Nutritionist. 1st ed. Paris: John Libbey Eurotext, 1988:235-9.

8. Kouris A, Wahlqvist M, Trichopoulou A, Polychronopoulos E. Food Habits and Health ofElderly in Spata, Greece: Application of Survey Instrument In: IUNS Proceedings 14thInternational Congress of Nutrition "New Global Era: Global Harmony throughNutrition", Seoul, August 1989: 229-230.

9. Willett W. Nutritional epidemiology. Willet W (ed), Oxford University press, 1990:61-62, 110-114.

10. Burema J, van Staveren WA. Validation of the dietary history method. The Diet HistoryMethod. Proceedings of the 2nd Berlin Meeting on Nutritional Epidemiology, KohlmeierL. (ed), 1989: 73-85.


11. Isaksson B. Urinary nitrogen output as a validity test in dietary surveys. Am J Clin Nutr,1980; 33: 4-6.

12. Bingham SA, Cummings JH. Urine nitrogen as an independent validatory measure ofdietary intake: a study of nitrogen balance in individuals consuming their normal diet. AmJ Clin Nutr, 1985; 42: 1276-1289.

13. Block G, Hartman AM. Issues in reproducibility and validity of dietary studies. Am J ClinNutr, 1989; 50: 1133-1138.

14. Pietinen P, Hartman AM, Haapa E, Räsänen L, Haapakoski J, Palmgren J, Albanese D,Virtamo J, Huttunen JK. Reproducibility and validity of dietary assessment instruments. I.A self-administrated food use questionnaire with a portion size picture booklet. Am JEpidmiol, 1988; 3: 655-666.

15. Jain M, Howe GR, Johnson KC, Miller AB. Evaluation of a diet history questionnaire forepidemiological studies. Am J Epidemiol, 1980; 107: 488-498.

16. Morgan RW, Jain M, Miller AB, Choi NW, Matthews V, Munan L, Burch JD, Feather J,Howe GR, Kelly A. A comparison of dietary methods in epidemiologic studies. Am JEpidemiol, 1978; 107: 488-498.

17. Larkin FA, Metzner MA, Thompson FE, Fegal KM Quire KE. Comparison of estimatednutrient intakes by food frequency and dietary records in adults. J Am Diet Assoc, 1989;89: 215-223.

18. EURONUT-SENECA. In: de Groot CPGM, van Staveren WA, Hautvast GAJ. (eds). EurJ Clin Nutr, 1991; 45(3).

19. Räsänen L, Mutanen M, Pekkanen J, Laitinen S, Koski K, Halonen S, Kivinen P,Stengård J, Nissinen A. Dietary intakes of 70 to 89 years old men in Eastern and WesternFinland. J Intern Med, in press, 1992.

20. Bingham SA. Limitations of the various methods for collecting dietary intake data. AnnNutr Metab 1991; 35: 117-27.

21. Block G. A review of validations of dietary assessment methods. Am J Epidemiol 1982;115: 492.

22. Black AE, Goldberg GR, Jebb SA, Livingstone MBE, Cole TJ, Prentice AM. Criticalevaluation of energy intake data using fundamental principles of energy physiology: 2.Evaluating the results of published surveys. Eur J Clin Nutr 1991; 45: 583-599.


23. Bingham SA. The dietary assessment of individuals: methods, accuracy, new techniquesand recommendations. Nutr Abstr Rev 1987; 57: 705-42.

24. Hsu-Hage B, Wahlqvist ML. A food frequency questionnaire for use in Chinesepopulations and its validation. Asia Pacific J Clin Nutr 1992; 1: 211-223.

25. Schofield WN, Schofield C, James WPT. Basal metabolic rate-review, prediction,together with annotated bibliography source material. Hum Nutr: Clin Nutr 1985; 39C(1):1-96.

26. Warwick PM. Predicting food energy requirements from estimates of energy expenditure.Aust J Nutr Diet 1989; 46: 3-28.

27. Shah M, Miller DS, Geissler CA. Lower metabolic rates of post-obese versus leanwomen: thermogenesis, basal metabolic rate and genetics. Eur J Clin Nutr 1988; 42: 741.

28. Foster GD, Wadden TA, Mullen JL. Resting energy expenditure, body composition andexcess weight in the obese. Metabolism 1988; 37: 467-472.

29. Goldberg GR, Black AE, Jebb SA, Cole TJ, Murgatroyd PR, Prentice AM. Criticalevaluation of energy intake data using fundamental principles of energy physiology: 1.Derivation cut-off limits to identify under-recording. Eur J Clin Nutr 1991; 45: 569.

30. Lansky D, Brownell K. Estimate of food quantity and calories: errors in self-report amongobese patients. Am J Clin Nutr 1982; 35: 727.

31. Zegman M. Errors in food recording and calorie estimation: Clinical and theoreticalimplications for obesity. Addict Behaviours 1984; 9: 347.

32. Moreiras O, van Staveren WA, Amorim Cruz JA, Nes M, Lund-Larsen K. EURONUTSENECA study on nutrition and the elderly. Intake of energy and nutrients. Eur J ClinNutr 1991; 45 (3): 105.

32. Lichtman S, Pisarska K, Raynes E, Thomas S, Weisel H, Matthews DE, Heymsfield SB.Treatment resistant obesity: mechanism of failure to lose weight on a prescribedhypo-caloric diet. Am J Clin Nutr 1991; 53: 23.

33. Lissner L, Habicht J, Strupp BJ, Levitsky DA, Haas JD, Roe DA. Body composition andenergy intake: do overweight women overeat & under-report. Am J Clin Nutr 1989; 49:320.


34. Hallfrisch JJ, Steele P, Cohen L. Comparison of seven-day diet record with measuredfood intake of twenty-four subjects. Nutr Res 1982; 2: 263-273.

35. Gibson R. Principles of Nutritional Assessment. Oxford University Press; 1990.

36. Alpers DH, Clouse RE, Stenson WF. Manual of nutritional therapeutics. Moston, Mass:Little Brown; 1983: 101.

37. Hage BH-H, Oliver RG, Powles JW, and Wahlqvist ML. Telephone directory listings ofpresumptive Chinese surnames: an appropriate sampling frame for a dispersed populationwith characteristic surnames. Epidemiology 1990; 1: 405-8.

38. Rutishauser I, Wahlqvist ML. Food intake patterns of Greek migrants to Melbourne inrelation to duration of stay. Proc Nutr Soc Aust 1983; 49-55.


5.13 ILLUSTRATIONS

Photo 5.1. West Australia, Fitzroy Crossing, Junjuwa 1988: researchers Professor MarkWahlqvist (right), Dr Antigone Kouris-Blazos (left), Professor Michael Graceyand Sister Helen Sullivan meet with the Junjuwa community leaders and elders toobtain permission for the study.

Photo 5.2. Melbourne, Australia (Anglo-Celtic) (1992): fit couple in their late seventiesbeing interviewed at study centre.

Photo 5.3. Melbourne, Australia (Greek) (1990-91): interviewing in an elderly subject'shome; one of the oldest men in the Greek sample (late 90s) being interviewed byDr Antigone Kouris-Blazos, a Greek Australian.

Photo 5.4. Melbourne, Australia (Greek) (1990-91): preparation of the silicon rubbermaterial used in the skin test.

Photo 5.5. Melbourne, Australia (Greek) (1990-91): application of the silicon rubber to thepalmar aspect of the forearm; dried in a couple of minutes; painlessly peeled offand graded under the microscope.

Photo 5.6. Melbourne, Australia (Greek) (1990-91): measuring the subscapular skinfoldusing Harpenden callipers on an elderly.

Photo 5.7. Spata, Greece (1988): a fit man aged in his mid 70's being interviewed.

Photo 5.8. Rural Tianjin, China (1989): location chosen for the study at the foot of themountain.

Photo 5.9. Rural Tianjin, China (1989): study was supported by village council (left);researcher Dr Xi Si de (right).

Photo 5.10. Rural Tianjin, China (1989): a woman aged 94 years old was being interviewedDr Zhang.

Photo 5.11. Rural Tianjin, China (1989): measuring blood pressure at the research centre.

Photo 5.12. Rural Tianjin, China (1989): an elderly was being interviewed by ProfessorMing-Tan Sun.

Photo 5.13. Rural Tianjin, China (1989): village men waiting to be interviewed.


Photo 5.14. Rural Tianjin, China (1989): a 94 year old woman answering questionsindependently.


CHAPTER 5METHODOLOGY

5.1 ABORIGINAL AUSTRALIANS5.1.1 Population selection and representativeness5.1.2 Response rate and refusals5.1.3 Data collection5.1.4 Modification and application of questionnaire

5.2 ANGLO-CELTIC AUSTRALIANS5.2.1 Population selection and representativeness5.2.2 Response rate and refusals5.2.3 Data collection5.2.4 Modification and application of questionnaire

5.3 GREEKS IN MELBOURNE, AUSTRALIA5.3.1 Population selection and representativeness5.3.2 Response rate5.3.3 Data collection

5.4 GREEKS IN SPATA, GREECE5.4.1 Population selection and representativeness5.4.2 Response rate5.4.3 Data collection

5.5 SWEDEN5.5.1 Population selection and representativeness5.5.2 Some characteristics of population5.5.3 Data collection5.5.4 Modification and Application of questionnaire

5.6 PHILIPPINES5.6.1 Population selection and representativeness5.6.2 Response rate and refusals5.6.3 Data collection5.6.4 Modification of questionnaire

5.7 CHINESE IN BEIJING5.7.1 Population selection and representativeness5.7.2 Response rate and refusals5.7.3 Data collection5.7.4 Modification and application of questionnaire


5.8 CHINESE IN RURAL AND URBAN TIANJIN5.8.1 Population selection and representativeness5.8.2 Response rate and refusals5.8.3 Data collection5.8.4 Modification of questionnaire

5.9 SWEDISH VALIDATION STUDY5.9.1 Introduction5.9.2 Population and method

5.9.2.1 Population5.9.2.2 Food record method5.9.2.3 Collection urinary nitrogen

5.9.3 Results5.9.4 Discussion5.9.5 Conclusion

5.10 GREEK VALIDATION STUDY5.10.1 Introduction5.10.2 Reported energy intakes & minimal energy requirements5.10.3 Reported protein intakes & urinary nitrogen excretion

5.11 SUMMARY

5.12 REFERENCES

5.13 ILLUSTRATIONS


Folio Bound VIEWS - Food Habits in Later Lifeapjcn.nhri.org.tw/server../apjcn/FHILL/Chapter5.pdf ·...

Documents

Transcript of Folio Bound VIEWS - Food Habits in Later Lifeapjcn.nhri.org.tw/server../apjcn/FHILL/Chapter5.pdf ·...