to mcgill u school of dietetics & human nutrition: 27 nov 08 food consumption patterns

to McGill U School of Dietetics & Human Nutrition: 27 Nov 08

Food consumption patterns

to reduce and prevent obesity

David BoothSchool of Psychology, College of Life & Environmental Sciences,

University of Birmingham (U.K.)http://www.psychology-people.bham.ac.uk/people/david.booth

Project with:

Louise Thibault, Nutrition, McGill U, Quebec; Caroline Chesneau, INA Paris France; Seolhyang Baek, Nursing, Dongguk U, South Korea; Antonio Laguna-Comacho, Nutrition UAEM, Mexico / Psychology B’ham U, UK.

Slowing the rise of obesityObviously,exercise more and/or eat less!!

Slowing the rise of obesity

Exercise more and/or eat less, as a society (?)


Exercise more and/or eat less, as a society, after big changes (?)


Exercise more and/or eat less, as a society, after big changes (?)

No, obesity is not solely an issue of societal reform, e.g.

public health interventions,

governmental regulations,

responsible businesses.

No doubt, we need all that – but of the right sort.

In the first instance, obesity is not even a societal issue at all.

It’s the individual who is obese or becomes overweight

and has to find ways to exercise more and/or to eat less.


Exercise more and/or eat less:

- each individual within current environment and biology;

- permanently, i.e., maintained across changes in own lifestyle.


Exercise more and/or eat less: - each individual within current environment and biology;

- permanently, i.e., maintained across changes in lifestyle.

Which feasible exercising or eating patterns are

most effective at keeping weight off?






The societal problem is lack of such research

– and for long past (>= 50 yr).






After we get some of this evidence,

we can start looking for the further evidence needed

to start reducing obesity in individuals

and preventing overweight even.- then (NEXT TWO SLIDES)






Educate all in such evidence on the behaviour-patterns to change

[avoid overweight] when unhealthy BMI becomes likely, and

[reduce obesity] when needing to lose some more weight:

- the same energy-balance affecting habits

for prevention and reduction of obesity.






Educate all in this evidence on the patterns to change

when unhealthy BMI becomes likely, or

when needing to lose more weight.

Environmental reform to prevent lapsing from each change,

also according to evidence on that.


THE ISSUES FOR RESEARCH


most effective at lowering weight?

What environmental changes would

support avoidance of unhealthy fattening

by preventing lapses from such patterns?

enABLEr/s

evidence-networking individual diffs. secure, anonymised

evidence-based & evidence-generating

Application of databases for research & services

Better Livingall QoL outcomes e.g. healthy weight, vigour, bodily comfort, ....

Education validated information personally tailored in culture's own terms

research / services universities-based to public &

http://wwiyc.org “what-works-in-your-circs” professionals

http://wwiyc.org/

Research into effective behaviour (comprehensively across habitual patterns)

The list is rather short still.

1. Alan Blair with Vivien Lewis & DAB (UK AFRC 1987-1991)Main bivariate analyses: A.J. Blair et alii (1989) Psychology & HealthSupplementary multivariate analyses of same study (all done in 1989-90):-Blair, A.J., Lewis, V.J., & Booth, D.A. (1990) Appetite [emotional eating & self-efficacy] Booth, D.A., Blair, A.J., Conner, M.T., & Lewis, V.J. (1991). In Y. Oomura et al. (Eds.), Progress in obesity research 1990. Libbey. [sensory preferences (sweetness) & weight control] Blair, A.J., Lewis, V.J., & Booth, D.A. (1994) Appetite [attitudes, emotional eating & self-

efficacy] Booth, D.A. (1996). In A. Angel et al., Progress in obesity research: 7. Libbey.

[‘hunger’/’satiety’]Booth, D.A., Blair, A.J., Lewis, V.J., & Baek, S.H. (2004) Appetite [PCA on least fattening

habits]

2. Simone French with Robert Jeffrey & D. Murray (Pound of Prev’n)S.A. French et alii (1999) International J. Obesity 23, 320-327.

3. Joachim Westenhoefer & associates (Lean Habits Study, Germany)J. Westenhoefer et alii (2004) Int J Obesity 28, 334-335.

4. Vicky Drapeau & co. with Angelo Tremblay (Québec Family Study)V. Drapeau et alii (2004) Am J Clin Nutr 80, 29-37.

No other study that I’ve yet seen covers a full range of specific behaviour. November 2008: nothing such that cites any of the above.

Research into effective behaviour (comprehensively across patterns)

(1) A.J. Blair & co (1989) as in Booth et al. (2004)

Most fattening customs of eatingIn the English Midlands

F1A: energy in or with drinks between meals

Correlation Self-described pattern of with wt. loss eating and drinking over 1 year

“Avoid calories between meals,in drinks and snack foods” 0.31

“Avoid sweet ‘extras’ (biscuits, cakes, sweets, chocolate)” 0.26

“Eat fresh fruit & salad instead ofhigher-calorie foods” 0.21

Score combining the above three 0.28

I.e., cutting out energy intake between meals is the most important “least fattening habit”



Most fattening customs of eatingin the English Midlands

1A: energy in or with drinks between meals

Full exploitation of such PSYCHOSOCIAL evidence requires ‘translation’ into the PSYCHOBIOLOGY,

e.g. (in this case – Factor 1A), timings and sizes of the ‘snack’ and the meal before.

Measure the effects of ‘late mixing’ on gastric emptying Calculate long-term consequences for body weight(Booth & Mather 1978; also Booth IJV&N [Swiss Nutrition Society] 1988)

“Snacking” that is fattening:

NOT a snack in the sense of a light meal;

NOT eating a snack-food (if part of a meal).

Energy sources consumed between regular meals, e.g. in or with drinks an hour or more before a mealtime.

Snacking can be addictive -

NOT because of “palatability” of the food snacked on;

NOT because of “pleasure” or “reward” from sweet (or salty) taste or from crunchy or succulent texture;

NOT because of “weakness in satiety”.

Ingestive movements on any ‘nibble’ / ’sip’ available after a meal are associatively conditioned by glucose from (unsweet, fat-free) starch in that food/drink item.




1B: high-fat foods/cooking

Self-described pattern of Correlation with eating and drinking wt. loss in 1 yr

“Avoid unnecessary fat in meals” 0.23

“Avoid fat in cheese and cream” 0.20

“Keep fat down when using spreads” 0.21

Score combining the above three 0.22

Full exploitation of this PSYCHOSOCIAL evidence requires ‘translation’ into the PSYCHOBIOLOGY of the mouthful:

Fat does satiate strongly but late after its ingestion, e.g., through glucose-sparing oxidation of fatty acids in the triglycerides still in chylomicrons long after the meal.

High-fat foods are fattening -

NOT because high “palatability” increases volume eaten;

NOT because of a high-fat “behavioural phenotype”.

Deposition of adipose fat requires energy to synthesise fatty acids from acetate produced from dietary carbohydrate or protein, unlike deposition from dietary fat.

Eating of high-fat foods is learnt by custom:

NO texture, aroma or taste of “fat” across all high-fat foods;

NO innate preference for fat-based creaminess or crunchiness.

NOT “weakly satiating”: like protein, delayed metabolic satiation.

Traditional or prestigious foods are often high in fat, e.g. (in UK) foods that store well (because of low water activity), foods for masculine image of men (‘great British breakfast’; ‘red’ meat).




Dieting OR Extreme exercise

Correlation of 1-yr weight loss &

Self-described habit frequency of habit

Predicted to be counterproductive (unsustainable, hence de-motivating -> yo-yo)

“Eat slimmers’ meal replacements for one or more meals a day” - 0.05

Predicted to spend extra energy but not to be maintained; hence yo-yo dieting

“Do vigorous exercise regularly” - 0.09

Predicted to spend extra energy and to be a maintainable routine

“Walk or cycle whenever possible” 0.04

Might help identify (=expertise) and/or sustain (=motivation) weight-losing habits

“Go to a slimming club or weight reduction class” 0.11

Research into effective behaviour (comprehensive of the patterns)

(1) A.J. Blair et alii (1989) Psyc Health; D.A. Booth et alii (2004) Appetite

Strengths• Practices asked about edited from words by members of public

- edited into smaller number by using examples from public (AL-C now getting public’s own groupings of new examples)

• Reported weights prospectively at 0 and 12-14 months.• Bivariate analyses from factor-analytical latent variables.• Measured behaviour at the end of the study period. RCTs confound effectiveness of package with adherence to it cp. Knauper et al. ’05 (McGill Psychology) re ‘self-set rules’.

[Blair et al. also assessed beliefs in efficacy of each practice, plus psychological barriers, e.g.:-

low weight-control self-efficacy, emotional eating, [not eating self-efficacy]

chronic dieting (‘restraint’), lack of reasons for action (‘attitudes’)]



Weaknesses• Only one year tracked - need longer for obesity-adequate measure of persistence

• Direct questions about frequency of practices: - unreliable heuristics (e.g., P Slovic; P Sedlmeier & T Betsch, ‘Etc.’) - need timing of two most recent episodes to calculate real frequency (over the exact period since the earlier occasion).

• Analysis only of final frequency - need change in frequency to measure cause of weight change

• Only two points and so no crossed time-lags possible - needed to measure effect of behavour on weight as distinct from

wt on bhvr, or both from 3rd factor causing both changes


(2) S.A. French, R.W. Jeffery, D. Murray (1999) IJO 23, 320-327

Reliable associations (N = 1120)(only these phrases in the Tables are available)

Strategy Loss (g/wk) P < t2D

Reduce calories 27 0.0001

Eliminate sweets 27 0.0001 x

Increase F&V 23 0.0001 x

Reduce food amount 20 0.001

Decrease fat intake 14 0.001

[Less hi-CHO food] 30 ns x

[Eliminate snacks] 23 ns

[Increase exercise] 16 ns while strategy in use

Research into effective behaviour(comprehensive of the patterns)

(2) S.A. French, R.W. Jeffery, D. Murray (1999) IJO 23, 320-327

Strengths

• Large number (23) of so-called “specific weight control behaviors”

• Four successive years of data from N = 1120 (Pounds of Prev’n study)

• The year’s duration of use of each practice recalled

[Prevalences reported (yet again): these may screen for feasibility]

Weaknesses

• Behavioural patterns not specific in analysis, nor defined in report

• Wordings “developed by researchers”: ??recognition by participants

• Orthogonal latent factors not extracted

• Current behaviour not measured at time of weight measurement; hence an association over the year (or 4y) is fallacious because weight stays at asymptote only while behaviour persists.

Raynor, Jeffery et al. (2008) did not replicate in N = 5145 over 1 year in t2D for cutting out sweets, increasing F&V, eating less hi-CHO food.


(3) Westenhoefer & co. (2004) IJOPhysicians’ group counselling 4-5 months, initial meal-replacement formula;

follow-up of weight at 3 years.

Odds ratio for reduced weight at 3 years (N = 1247)practices improved or maintained from 2mth to 12mth / lapsing

Multiple-items score OR P <

Avoid fatty or sweet foods; eat F&V 1.81 0.001

Avoid snacks/nibbles; regular meals 1.71 0.001

Focus on eating within meals 1.36 0.05

Active lifestyle; take exercise 1.35 0.05

Control of emotional eating & stress 1.31 0.05

WSP’99* “Flexible Control” of eating 1.30 0.05 (?an experimenting approach)

WSP’99* “Rigid Control” of eating 1.18 ns

Eat smaller amounts of food 1.17 ns

*J Westenhoefer, AJ Stunkard & V Pudel (1999) IJED 26, 53-64.”graduated vs all or nothing”


(3) Westenhoefer et al. (2004)

Strengths

• Prospective from 2-12 months of change to 0-3 years outcome

• Dietary and movement practices tracked at 2, 12, 24 and 36 mth

Weaknesses

• Investigators chose the wordings of the behavioural reports.

• Unclear distinction between actual action and intention/attitude.

• Specific behaviour patterns (and motives) combined for analysis.

Opportunity taken

The specific behaviours were counted, even though not quantitated: - highest success rate (61% with 3y wt loss)

with 7 improvements maintained at 1y; - 52% success at mode of 5 improvements (quarter of sample).


(4) Drapeau et al. & Tremblay (2004) AJCNWeight & adiposity change in 6 years; at 6y, more/less/same of10 food g’ps

and food portions in 3-day record

Less increase in measures of fatness (weight, body fat %, waistline etc.)

(all 6) recalled more fruit and fruit productsrecorded more whole fruit

recalled less fat and fatty foodsrecorded less full-fat milk (not independent of fruit)

(some) recalled less sugar and sweet foods effects (above) reduced by allowance for 3-d recorded PA

Strengths

• Assessed intakes of particular foods at final weight measurement

• Measured weight and 5 indices of adiposity at both time-points

• Factored out physical activity and other food habits

Weaknesses

• Recalled changes in consumption were not specific to foods

• No intervening measures between 0 and 6 years

Research into effective behaviour

Behaviourally ‘comprehensive’ studies

Most other work does not track any sorts of behavioural pattern

“Psychobehavioural” associates merely psychometric scale scores (restraint, depression etc.):

should be treated as supplementary outcomes and/or motivational moderators (Blair et al., 1989; Lewis, Blair, Booth, 1992a,b)

Important ‘selective’ studies

Coakley et al. & Willett (1998) IJO 22, 89-96: 4y prosp’ve; N=19.5k snacking fattens, not fat intake (except oldest); TV & no vigorous PA

Knauper et al. (2005) Appetite on self-set rules in wt. control: persistence (compliance) usually confounds effectiveness

Disconfounding is possible only if change in each behaviour is tracked during weight loss;

not done by the best RCT so far (DPPRG, 2002 NEJM): weight still increasing at 2y, while PA relapsing; no ‘dietary’ data

Research into effective behaviourcomprehensive across specific self-described patterns

Follow-up & extend Blair et al. (1989) as in Booth et al. (2004, 2007)

Research trainee’s pilot at McGill with updated methods - particularly weekly tracking and cross-lagged analyses (Baek)- ’localised’ (shift culture) to Montreal, French language & students

Concluding part of this talk using Symposium (2006) slides on http://epapers.bham.ac.uk

Research student’s project at Brum- nutrition graduate / obesity dietitian for a degree in psychology

First year: strengthen different parts of the methods e.g. update elicitation & categorisation of descriptions validate recall of self-described activities

Second year onwards: weekly reporting weight & timings of bhvr multiple-baseline to asymptotic weight persistence & antecedents of lapses

More in future at McGill??

Yet more applications for research grants in UK

Theory of ‘enABLE’ research method

1. A subculture’s consensus descriptions of customs objectify communicable patterns of activity.

Theory


2. Autobiographical memory can time episodes of an activity as accurately as a diary record can.

Theory



3. A sustained change in frequency of a custom of eating or moving about will change body weight towards asymptote over a few weeks.

Theory




4. Change to a frequency that is sufficiently prevalent in a culture will be maintained indefinitely, along with the asymptotic change in body fat content.

Theory




4. Change to a frequency that is sufficiently prevalent in a culture will be maintained indefinitely, along with the asymptotic change in body fat content.

5. Antecedents to lapse from change can be identified in food supply, transport and built environment, and evidence found for effective changes in them.

Varieties of intervention

Measurement (tracking) only: “observational”

Multiple-baseline with tracking: quasi-experimental

Multiple baseline tracking in RCT: experimentalversus other wordings of behaviour-changes

The McGill pilot study (observational) Method (with some short-cuts)

1. Consensus descriptions elicited in one culture (UK) were ‘localised’ to another culture (Quebec French) by investigators as participant observers, checked by back-translation to England’s language and environs.

2. Exact current frequency is given by the reciprocal of the time difference between the last two occasions.

3. Effect on weight of maintained change in frequency of a custom after the first week (or 2 weeks) was measured by correlation between the changes,

4. Effects of initial and changed custom frequencies on behaviour change maintenance (and weight change maintenance for an effective custom) were expressed as ‘dose-response’ slopes.

Design

Convenience sample of French-speakers in Montreal:21 recruited; 14 completed the planned 6 weeks of the study: 12 women and 2 men, ages 18-46 years.

At the same time of day on the same day of the week, on a questionnaire in French, each reported body weight (weighed that day on the same scales) and recalled the last two timings of carrying out each of 26 customs of eating and/or drinking and 6 customs of moving about.

AnalysisCorrelations of changes in behaviour and weight (1)

Results are expressed here as r x 100, where r is Pearson’s product-moment correlation coefficient.[Where data are seriously skewed, Spearman’s correlation of ranks, rho, should be used instead.]

If only one pattern of energy intake or expenditure changes in frequency in a given week, correlation with weight change can in theory be perfect (r = 1.0).

With such a small sample, the observed r values are highly unreliable. [When N is adequate for good estimates of effect size, the 95% confidence limits of r should be given.]

Correlations of changes in behaviour and weight (2)

Positive values indicate that the activity is fattening.Negative values indicate an effective slimming habit.

Test of the causal hypothesis:Frequency change correlates with later Weight change. This is a rather severe test, discounting weight lost in 1st week or two (though 1st week is mainly water).

Cross-lagged control:Weight change does not correlate in the same direction with later Frequency change. Correct the r-value measuring Frequency on Weight by subtracting r-value for Weight on Frequency.

Effect of belief on behaviour:Weight change correlated in the opposite direction with later Frequency change indicates action on a correct belief as to what can produce that change in weight.

Evidence for eating that slims in Francophone Canada

correlation of amount of one change in first week of that changewith amount of the other change in subsequent two weeks

r x 100 r x 100 rF,W - rW,F rW,F/rF,W

Activity (described Freq 0-1 Wt 0-1 Cross-lag Strengthin French = “…”) Wt 1-3 Freq 1-3 corrected of belief

smaller meal a -63 -50 -13 -

vegetables in meal -85 54 (-85) 0.6

cheese, dairy cream b -93 38 (-93) 0.4

food with added sugar -25 58 (-25) 2.3

“sucreries en ‘surplus’” -30 45 (-30) 1.5

a smaller than ‘normal’. b “des matières grasses animales [sic] sous forme de ...”

Customs that slim in Montreal (described in French)

Means of correlation values (r x 100) available from up to four lags: behaviour-Frequency change over one week (F0-1) or two weeks (F0-2) and Weight change over the next week (W1-2,W2-3) or two (W1-3,W2-4).

Mean Mean Mean Mean Pattern of behaviour Freq Wt on cross-lag strength

on Wt Freq corrected of belief

smaller meal -62 -43 [-60] 0.9

vegetables in meal -28 -9 -14 [3.0]

cheese, dairy cream -70 17 -48 0.2

food with added sugar -6 45 [-6] 4.3

“sucreries en ‘surplus’” -10 16 1 -

take exercise until tired -34 -28 [-15] 2.4

[…] = (mean) difference from two of the four (or one of the three) lags available

Customs that fatten in Montreal (described in French)Frequency change over one week (F0-1) or two weeks (F0-2) and Weight change over the next week (W1-2,W2-3) or two (W1-3,W2-4) - mean values

Mean Mean Mean Mean Pattern of behaviour Freq Wt on cross-lag strength

on Wt Freq corrected of belief

use fat in cooking/prep’n 59 20 57 -

drink alcohol 53 -48 (40) 1.1

choose fibre-rich foods 55 11 31 -

eat fruit or salad 73 7 65 -

aerobics/“un club sportiv” 75 18 62 -

Other ways to test the causal hypothesise.g., correlation (unlagged) of a persisting change in frequency of an activity with the amount of weight lost

Less food than normal in a meal

0.00 1.00 2.00 3.00 4.00 5.00

weight change

-40.00

-30.00

-20.00

-10.00

0.00

10.00

Big

ge

st c

ha

ng

e i

n F

re

qu

en

cy

1

2

6

7

12

13

14R Sq Linear = 0.396

Increase in frequency with greatest decrease in weight

Decrease in frequency (briefly) with (almost) no change in body weight

Each person’s biggest change in frequency during a period of consistentlyup or down change

Change in weight (kg t1 – t2)) over whole period of change

Does maintenance of changed frequency of a practice depend on how frequent the custom was or is?

Less food than normal in a meal

0.00 3.00 6.00 9.00 12.00 15.00

F0

2.00

2.50

3.00

3.50

4.00

4.50

5.00

No

.of w

ee

k

1

2

6

7

12

13

R Sq Linear = 0.311

-6.00 -4.00 -2.00 0.00 2.00 4.00 6.00 8.00

F0-1

2.00

2.50

3.00

3.50

4.00

4.50

5.00

No

.of

week

1

2

6

7

12

13

R Sq Linear = 0.386

Number

of

weeks

Number

of

weeks

Starting frequency (times per week) Frequency change in first week of change

No sign of effect of size of increase* in frequency.

(Sharp decreases were not well sustained.)

Change in frequency [increase*] of eating smaller meals is maintained for longer if frequency starts higher.

down up

The bigger picture for research (1)

The psychobiological “long haul” (Booth, 1988) = study of the mechanisms of appetite and its sating,

and of vigour and its fatigue . physically energetic

- by itself, such work can’t show how to control weight;

- yet the mechanisms of choice and its satiety/fatigue must be measured, in order to work out how to support these psychosocially identified maintainable least fattening customs,

e.g. through supply of foods, transport, leisure, etc.

The bigger picture for research (2)

Psychosocial “short-cut” (B ’88)

Generalise and differentiate frompersonally tailored locally valid evidence

Track changes in behaviour components - causal evidence without experiment - the only way to rescue obesity RCTs

from unusability and invalidity.

The future for enABLEr/s

Provide service through the researchGenerate research through services

Begin to educate the public (& professionals) inpersonally tailored locally valid evidence to inform a succession of changes each 1-3 weeks,

- especially of eating habits when a more sedentary lifestyle begins.

Create demand on commercial and public providersTo change supply in ways that evidence shows to support effective maintainable patterns of individual behaviour.

Thank you for your attention

SPARE SLIDES

Bio

‘Bio’

David Booth has research doctorates in biochemistry and in psychology.

One of his main areas of research since 1964 has been the neural, digestive, metabolic, sensory and social influences on, and effects of, choices and intakes of foods and drinks, and how all these causal processes interact in the individual’s life.

One major effort has been to characterise and to measure the least fattening customs of eating within local environments. This talk will highlight a pilot study conducted in this School that is now being extended by a nutrition graduate and obesity dietitian from Mexico who is studying for a research degree in Psychology with David and colleagues at the University of Birmingham.

to mcgill u school of dietetics & human nutrition: 27 nov 08 food consumption patterns

Documents

rise of obesityexercise

current environment

rise of obesityobviously

feasible exercising

big changes

dongguk u

societal issue

reduction of obesity