Aryeh D Stein, PhDRollins School of Public Health, Emory University, Atlanta GA , USAOctober 2014

Not all individuals who are recruited into a study are followed for the duration of interest

Deaths from causes that are not of primary interest

Migration away from the study area

Loss of interest in study

Precision

If attrition is random

Bias

If attrition is non-random

Atole Fresco

Ingredients (g/180 ml)

Incaparina 13.5 -

Dry skim milk 21.6 -

Sugar 9.0 13.3

Flavoring agent - 2.1

Nutrients per 180 ml

Energy (kcal) 163 59

Protein (g) 11.5 -

2 smaller villages

Atole Fresco

19 21

110

751 785

153 25

0

200

400

600

800

0

5

10

15

20

25

30

Atole Fresco Atole Fresco

kca

l/d

ay

g /

da

y

PROTEIN ENERGY

INTAKE FROM DIET

INTAKE FROM

SUPPLEMENT

Intakes in children 15-36 mo

2 larger villages

Atole Fresco

Composition of supplement

Boys Girls

Mother

Height (cm) 149.5 149.6

Non-pregnant BMI (kg/m2) 21.7 21.5

Child

Birth weight (g) 3140 3050

0

10

20

30

40

50

1969 1970-71 1972-73 1974-75 1976-77

% s

evere

ly s

tunte

d

Survey year

Atole Fresco

Habicht et al., J Nutr 1995

196

5

197

0

197

5

198

0

198

5

199

0

199

5

200

0

200

5

19

21

23

25

27

29

31

10th 25th 75th 90th

Vo

cab

ula

ry

SES (Percentile ranking)

Atole Fresco

10th 25th 75th 90th

Grade (Percentile ranking)

Pollitt et al J Nutrition 1995;124:111S-1118S

Women living in villages who delivered 1996-1999 (n = 130)Achievement Numeracy Literacy SIA Comprehension SIA Vocabulary General knowledge

0

20

40

60

80

100

<6 >= 6

Su

mm

ary

ach

ievem

en

t te

st

sco

re

Highest grade attained

Atole Fresco

Li et al, Pediatrics 2003; 112: 1156-1162

1855 (78%)

Living in

Guatemala

2392

Individuals in

1969-77 study

272 (11%)

Died between

1969 and 2002

102 (4%)

Untraced

2018 (85%)

Known to be

alive in 2002

163 (7%)

Living

outside

Guatemala

1112

Original villages

154

Nearby villages

419

In or near

Guatemala City

170

Elsewhere in

Guatemala

Grajeda et al., FNB 2005

1196

267

108

1571 (65.7%)

Males Females

Age (y) 32.1 32.5

Schooling (grade) 5.1 4.1

Rural residence (%) 74.3 69.1

Height (m) 1.62 1.51

BMI (kg/m2) 24.7 26.8

Data are means or %Sample sizes vary slightly due to item-missing data

Maluccio et al, Econ J 2009; Stein et al., APAM 2008

Reading comprehension

scores improved by 0.28 SD

Ravens Progressive Matrices

scores improved by 0.24 SD

Hoddinott et al. Lancet 2008

Wages

34% to 46% higher

Annual hours worked

222 Lower

▪ (CI: -572 to 128)

Annual income

US$ 914 higher

▪ ( CI: -$190, $2018)

0.00

0.15

0.30

0.45

0.60

0.75

0-24 0-36 36-72

0.670.62

0.22

US

$ / h

r

Window of exposure (months)

P < 0.01 P < 0.01

P > 0.4

Participation rates are 95% for village residents, 63% for internal migrants, and 0% for external migrants and untracedMigrants, untraced individuals and non-respondents probably differ from respondents Can one assume MAR or MCAR? Does failure to account for attrition bias our

estimates?

Step 1: Is attrition associated with intervention group?Step 2: What else predicts attrition?

Born in Atolevillage

(n=1269)

Born in Fresco village

(n=1123)

Alive in Guatemala, %

77.2 77.9

Migrated outside Guatemala, %

7.0 6.5

Died, % 12.4 10.4

Not traced, % 3.4 5.2

Data represent distribution of cohort members (n= 2392), by intervention group and tracing status

Born in Atole village (n=980)

Born in Fresco village (n=875)

Location (%)

Participated(%)

Location (%)

Participated(%)

In study village, % 57.9 94.9 62.4 95.1

In nearby village, % 11.8 90.5 4.5 89.7

In or near Guatemala City, %

20.9 63.9 24.5 63.4

Elsewhere in Guatemala, %

9.4 65.2 8.7 61.8

Data represent distribution of those eligible for contact (n=1855) and the proportion of those who completed at least one instrument (total n=1571), by intervention group and region of Guatemala

The pattern of attrition, from tracing through location and consent, is not markedly differential by intervention group.

This is reassuring.

But is it convincing?

Interviewed Died Untraced External

migrant

Traced, not

interviewed

n 1571 272 102 163 284

Year of birth 1970.1 1971.5 1970.1 1969.5 1970.2

Male, % 48 59 43 55 65

Atole village, % 53 58 43 55 52

Age of mother at birth, y 27.6 28.3 25.8 26.4 27.2

Age of father at birth, y 32.9 35.0 31.9 31.6 32.5

Mother’s schooling, y 1.3 1.1 0.9 1.5 1.5

Father’s schooling, y 1.7 1.3 3.0 1.7 2.0

SES, SD -0.19 -0.27 -0.60 0.36 0.16

Grajeda et al., FNB 2005All variables p≤0.05 by ANOVA, except for ‘Atole village’ (p=0.15)

Died Untraced External

migrant

Traced, not

interviewed

Male (ref = female) 1.47* 0.65 1.25 1.85*

Year of birth (per y) 1.09* 1.02 0.98 1.02

Age of mother at birth (per y) 1.00 1.02 0.99 1.01

Age of father at birth (per y) 1.02* 0.99 0.99 1.00

Mother’s schooling (per y) 0.97 0.79 1.03 1.05

Father’s schooling (per y) 0.92* 1.28* 0.98 1.04

SES (per SD) 0.99 0.72 1.14* 1.05

Data are odds ratios from polytomous regression models. * P<0.05. Reference category is ‘completed at least one instrument’ (n=1571). Model includes terms for village of birth and dummy indicators for missing values, with missing values imputed to the sample mode or mean, as appropriate Grajeda et al., FNB 2005

Predictors of attrition differ across type of attrition

These variables are likely to feature in any modeling work

Control for these variables will resolve some MAR concerns

Substantial attrition is likely to plague all longitudinal studies Allow for attrition when planning and assembling

cohort Collect data on factors that might predict attritionEnsure multiple contact points (parents, neighbors, population registers) Plan for periodic updates of key details and contact

informationEngage children as they mature Acknowledge their increasing autonomy and need for

privacy

In Guatemala: Generations of prior and

current investigators in the INCAP Longitudinal Study

Three generations of residents of the study villages

The INCAP field and support staff

In USA: Colleagues and students at

Emory University, University of Pennsylvania, IFPRI, Middlebury…

Funding: National Institutes of Health,

USA

▪ PH-43-65-640

▪ TW-005598

▪ HD-046125

▪ HD-075784