don't fall for weight: a systematic review of weight status and falls

REVIEW

Don’t fall for weight: A systematic review of weightstatus and fallsndi_1557 273..279

Heather MOORE and Anna BOLTONGPeter James Centre, Eastern Health, Melbourne, Victoria, Australia

AbstractAim: To examine the evidence for the contribution of weight status or nutritional status to the incidence of falls.Methods: A systematic review was completed to determine if weight status or nutritional status affects incidenceof falls. Inclusion/exclusion criteria were applied to studies published from 2000 which reported weight statusand/or nutritional status and falls incidence. Electronic databases searched were CINAHL, MEDLINE, AMED, EMBASE,PUBMED and PsycINFO. Quality assessment and data extraction were performed on studies that met the inclusioncriteria.Results: Twenty-seven studies met the inclusion criteria. Six studies found no difference in weight between fallersand non-fallers. Two studies found an association between low weight or weight loss and falls. Eleven studies foundno difference in body mass index between fallers and non-fallers. One study found body mass index to be lower infallers. Five studies found fallers had a higher body mass index than non-fallers or that a higher body mass indexwas associated with falls. Three studies found malnutrition risk to be statistically significantly higher in fallers. Twodescriptive studies identified 45% of a falls population as malnourished or at high risk of malnutrition.Conclusion: This review found limited evidence that being either overweight or underweight increases fallsincidence. Referrals for nutritional management to decrease falls risk should not be based on weight status alone.Malnutrition screening should be used to identify appropriate patient referrals to dietitians in falls clinics.

Key words: body mass index, body weight, fall, malnutrition, nutritional status.

Introduction

Falls are a major contributor to serious injuries in the over65 age group in Australia and New Zealand. Approximatelyone in three people aged over 65 years living in the commu-nity fall each year.1 Falls are the most common cause of deaththrough unintentional injury in people over 75 years in NewZealand.2 The direct cost to the health sector for falls inpeople over 65 years has been estimated to be $AUD 298million.1 The proportion of the population greater than65 years of age is predicted to increase from 13% in 2007 to23–25% in 2056 in Australia and 12.5% in 2009 to 20% in2031 in New Zealand.3,4 The incidence and cost of falls istherefore predicted to increase.

Falls clinics have been established across Australia overthe last two decades to decrease falls and fall injuries. In theyear 2001, there were approximately 20 falls clinic in Aus-tralia.5 Dietitians are not routinely employed in falls clinics

with only one of 14 Australian clinics reported to have adietitian.5 In the absence of a dietitian serviced falls clinic,medical staff and other allied health professionals can insome circumstances refer falls clinic clients to dietitians incommunity rehabilitation programmes or community healthcentres. Referrals to dietitians from falls clinics are com-monly based on body mass index (BMI) or weight status.6

This includes referrals for nutritional management of obesityor overweight clients.6 Clients with high malnutrition riskhowever are not routinely referred.6

Malnutrition within the community setting in Australia isreported to be between 10 and 30% and the prevalence ofmalnutrition is reported to be higher in older adults com-pared with other age groups.7 The mean age of Victorian fallsclinic clients is 76.9 years (SD 10) and 76% of clients arecommunity dwelling.1 It is therefore hypothesised that theincidence of malnutrition would be high in a falls clinicpopulation. Malnutrition may lead to increases in falls due todecreased muscle mass and therefore decreased strength.8

Both underweight and overweight clients can be malnour-ished and therefore screening for malnutrition needs toincorporate more than weight status alone.

This systematic review was undertaken to investigate ifadults who have fallen have different weight and nutritionalstatus than adults who have not fallen.

H. Moore, BSc, Dietitian, Sub Acute Ambulatory Care ServicesA. Boltong, MSc, Dietitian, PhD CandidateCorrespondence: H. Moore, Locked Bag 1 PO, Forrest Hill, VIC3131, Australia. Email: [email protected]

Accepted April 2011

Nutrition & Dietetics 2011; 68: 273–279 DOI: 10.1111/j.1747-0080.2011.01557.x

© 2011 The AuthorsNutrition & Dietetics © 2011 Dietitians Association of Australia

273

Methods

A literature search was conducted using the keywords: mal-nutrition, weight, underweight, nutritional status, falls andfalls risk. The databases CINAHL, MEDLINE, AMED,EMBASE, PUBMED and PsycINFO were searched. Thesearch was limited to the time period of January 2000 toAugust 2010. The 2000 review start date corresponds to anincrease in falls research occurring in the last decade due tothe ageing population, increased falls numbers and theestablishment of increased numbers of falls clinics.5 In addi-tion to the database search performed, dietitians working inaged care and rehabilitation were contacted for grey litera-ture relating to falls, nutrition and weight status. Citationtracking of main studies was performed.

The criteria for inclusion were studies that reportedweight, nutritional status, malnutrition or malnutrition riskand falls. Studies focusing on vitamin or mineral deficien-cies, work-related falls, falls in children, fractures withoutfalls information, falls risk alone or non-English languagestudies were excluded. Studies with a focus on vitamin defi-ciencies were excluded as the focus of this review was overallnutritional status and weight status not micronutrient defi-ciencies. The relationship between Vitamin D and othermicronutrient deficiencies and falls have been reviewed else-where.9 Inclusion and exclusion criteria were applied by tworeviewers to abstracts with 100% agreement being reached at

first application. Full text copies of all studies meeting theinclusion criteria as well as those where conformity withinclusion criteria was unconfirmed were obtained for fullreview.

Quality appraisal of all full text studies was conductedby use of Critical Appraisal Skills Programme (CASP)appraisal tool that was most appropriate for each studydesign.10 Studies were excluded if deemed of poor qualityby CASP.

Data extraction included weight, BMI and malnutritionrisk for fallers and non-fallers. Effect size for measurementsof weight, BMI and malnutrition risk was calculated wheremean and standard deviation values were provided for bothfallers and non-fallers. Effect size is the standardised meandifference between two groups and enables any differencesbetween fallers and non-fallers to be identified.

Results

A total of 1486 studies were identified via the search strategyof which 27 studies were included in this systematic review(Figure 1). The study designs of the 27 studies were retro-spective cohorts (n = 10), prospective cohorts (n = 12), casecontrol (n = 1) and descriptive (n = 4) (Table 1). Twenty outof 27 studies investigated populations aged 59 years orolder. The majority of studies were in female communitydwelling participants. There was large variation in sample

Figure 1 Process of article selection.

H. Moore and A. Boltong


274

Tab

le1

Sum

mar

yof

stud

ies

mea

suri

ngw

eigh

t,BM

Ior

nutr

itio

nal

stat

usin

falle

rsor

falls

clin

iccl

ient

s

Firs

tau

thor

&ye

arTy

peof

stud

y&

NH

MR

Cle

velo

fev

iden

ce24

Age

inye

ars;

mea

n/SD

orra

nge

orm

edia

nn

&ge

nder

ratio

(F)

(M)

Popu

latio

nM

easu

reEf

fect

size

&95

%C

IK

eyfin

ding

s

Baue

rJ

etal

.20

0711

Des

crip

tive

Leve

lIV

Mea

n72

.1SD

14.1

49 43%

F57

%M

Acu

teho

spit

alpt

sw

hofe

lldu

ring

adm

issi

on(B

risb

ane)

SGA

,BM

I,w

tN

A27

(55%

)pt

sw

ell

nour

ishe

d&

22(4

5%)

mal

nour

ishe

d.N

odi

ffer

ence

infa

llnu

mbe

rsbe

twee

nw

ell-

nour

ishe

d&

mal

nour

ishe

dpt

s.W

ell-

nour

ishe

dfa

llers

had

sign

ifica

ntly

high

erBM

I(P

=0.

003)

&w

t(P

=0.

002)

than

mal

nour

ishe

dfa

llers

Stol

zD

etal

.20

0212

Des

crip

tive

Leve

lIV

Mea

nF:

80.2

SD5.

6M

ean

M:8

0.8

SD5.

8ra

nge

>65

90 55%

F45

%M

Pts

from

afa

llscl

inic

(Ade

laid

e)A

NSI

,BM

IN

AH

igh

nutr

itio

nri

sksc

ore:

M12

,F

27,

tota

l41

(45%

).1

in8

pts

had

aBM

Ile

ssth

an22

;1

in5

pts

had

aBM

I>

30.

Prev

alen

ceof

unin

tent

iona

lw

tch

ange

was

31%

John

son

C20

0313

Ret

rosp

ecti

veco

hort

Leve

lII

I-3

Mea

n82

.5SD

6.62

,ra

nge

65–9

889 83

%F

17%

M

Com

mun

ity

dwel

ling

olde

rad

ults

rece

ivin

gho

me

care

(Can

ada)

Nut

riti

onal

risk

leve

lm

easu

red

by10

-poi

ntqu

esti

onna

ire

Nut

riti

onal

risk

:0.

81(0

.36,

1.25

)Fa

llers

had

sign

ifica

ntly

high

ernu

trit

ion

risk

com

pare

dw

ith

non-

falle

rs:

75.9

%of

falle

rsco

mpa

red

wit

h95

.3%

non-

falle

rsre

port

edgo

odor

exce

llent

eati

ngha

bits

(P=

0.03

2).

Nut

riti

onal

risk

was

asi

gnifi

cant

dete

rmin

ate

offa

lls(P

=0.

004)

.E

ffec

tsi

zesh

ows

adi

ffer

ence

innu

trit

iona

lri

sksc

ore

betw

een

falle

rs&

non-

falle

rsV

isva

nath

anR

etal

.20

0314

Pros

pect

ive

coho

rtLe

vel

IIM

ean

79.4

525

069

%F

31%

M

Pts

regi

ster

edfo

rdo

mic

iliar

yca

rese

rvic

es(A

dela

ide)

MN

AN

AN

otw

ell-

nour

ishe

dpt

sw

ere

mor

elik

ely

toha

veha

da

fall

over

a12

-mon

thpe

riod

(P=

0.01

).Fa

llers

who

wer

eno

tw

ell

nour

ishe

d(M

NA

<24

)n

=39

(41.

9%)

falle

rsw

how

ere

nour

ishe

d(M

NA

�24

)n

=33

(26.

0%)

Loyd

Bet

al.

2009

15Pr

ospe

ctiv

eco

hort

Leve

lII

Mea

n81

SD8,

rang

e60

–97

193

72%

F28

%M

Thr

eeac

ute

hosp

ital

spt

s,al

lw

ith

surg

ical

repa

irof

min

imal

trau

ma

#(S

ydne

y)

MN

AN

AM

NA

scor

eno

tdi

ffer

ent

betw

een

non-

falle

r/si

ngle

falle

rs&

recu

rren

tfa

llers

.M

NA

scor

ew

asa

sign

ifica

ntri

skfa

ctor

for

fall

rela

ted

frac

ture

s(P

=0.

001)

Form

iga

Fet

al.

2008

16Pr

ospe

ctiv

eco

hort

Leve

lII

Mea

n93

.7SD

2.8,

rang

e89

+10

477

%F

23%

M

Subj

ects

from

the

Non

aSat

feliu

stud

y(B

arce

lona

)

S-F

MN

AN

AN

odi

ffer

ence

innu

trit

iona

lst

atus

betw

een

falle

rs&

non-

falle

rs

Viv

anti

etal

.20

0917

Pros

pect

ive

coho

rtLe

vel

IIM

edia

n74

126

41%

F59

%M

Pts

pres

enti

ngto

aE

D(Q

ueen

slan

d)SG

AN

AIn

crea

sed

risk

ofbe

ing

asse

ssed

asm

alno

uris

hed

whe

na

frai

lm

echa

nica

lfa

ller

rela

tive

toa

non-

falle

rR

R:

1.5

95%

CI

(1.0

–2.3

)P

=0.

001.

Mal

nour

ishe

dpt

sha

dan

incr

ease

dri

skof

falls

over

6m

onth

s.R

R:1

.595

%C

I(1

.0–2

.5)

P=

0.03

Peel

Net

al.

2006

18C

ase

Con

trol

Leve

lIV

Mea

n82

.5SD

6.9,

rang

e65

+12

682

%F

18%

M

Acu

teho

spit

alpt

sw

ith

fall

rela

ted

#to

prox

imal

fem

ur.

Mat

ched

totw

ora

ndom

cont

rols

(Bri

sban

e)

Self-

repo

rted

wt

chan

ges

BMI

NA

Not

losi

ngw

tbe

twee

nm

id&

olde

rag

eha

da

sign

ifica

ntpr

otec

tive

effe

cton

falls

resu

ltin

gin

hip

frac

ture

risk

(P=

0.00

1).

BMI

<18

.512

%fa

llers

,5%

cont

rol.

BMI

25.0

–>30

33%

falle

rs,

46%

cont

rol.

Falle

rsha

dsi

gnifi

cant

lylo

wer

BMI

(P=

0.00

2)

Plui

jmS

etal

.20

0619

Pros

pect

ive

coho

rtLe

vel

IIM

ean

75.3

SD6.

413

5651

%F

49%

M

Com

mun

ity

dwel

ling

(Net

herl

ands

)W

t,BM

IN

AO

Rfo

rpo

tent

ial

pred

icto

rsof

recu

rren

tfa

lling

:w

tF

�62

kg(v

s>6

2kg

);M

�70

kg(v

s>7

0kg

)O

R1.

4595

%C

I(1

.10–

1.91

).Lo

ww

tw

asas

soci

ated

wit

hre

curr

ent

falls

.BM

Iw

asno

tas

soci

ated

wit

hre

curr

ent

falls

Nit

zJ

etal

.20

0820

Pros

pect

ive

coho

rtLe

vel

IIR

ange

40–8

0at

base

line

503

100%

FC

omm

unit

ydw

ellin

g(B

risb

ane)

Wt,

BMI

NA

Wt

&BM

Ino

tdi

ffer

ent

betw

een

falle

rs&

non-

falle

rs

Nak

amur

aK

etal

.20

0621

Pros

pect

ive

coho

rtLe

vel

IIM

ean

74.3

SD4.

4,ra

nge

70+

609

100%

FC

omm

unit

ydw

ellin

g(J

apan

)W

t,BM

IN

AW

t&

BMI

not

diff

eren

tbe

twee

nfa

llers

&no

n-fa

llers

Shah

arD

etal

.20

0922

Ret

rosp

ecti

veco

hort

Leve

lII

I-3

Ran

ge65

–100

100

73%

F27

%M

Seni

orliv

ing

faci

litie

s(I

srae

l)W

tW

t: 0.03

(-0.

41,

0.46

)E

ffec

tsi

zesh

ows

nodi

ffer

ence

inw

tbe

twee

nfa

llers

&no

n-fa

llers

Gar

ibal

laS

etal

.20

0723

Pros

pect

ive

coho

rtLe

vel

IIM

ean

77SD

6,ra

nge

65+

445

47%

F53

%M

Acu

teho

spit

alpt

s(U

K)

Wt,

BMI

Wt: -0

.08

(-0.

48,

0.33

)BM

I: 0.17

(-0.

23,

0.58

)

Tota

lad

mis

sion

sn

=39

7,BM

I<

2036

(9%

)Fa

llsad

mis

sion

sn

=25

,BM

I<

203

(12%

).E

ffec

tsi

zesh

ows

nodi

ffer

ence

inw

tor

BMI

betw

een

falle

rs&

non-

falle

rs

Saye

rA

etal

.20

0624

Ret

rosp

ecti

veco

hort

Leve

lII

I-3

Ran

ge59

–72

2148

59%

F41

%M

Com

mun

ity

dwel

ling

(UK

)W

t,BM

IBM

I: M:

0.09

(-0.

10,

0.28

)F:

0.58

(0.4

5,0.

72)

Wt: M

:-0

.04

(-0.

23,

0.15

)F:

0.10

(-0.

03,

0.24

)

Eff

ect

size

show

sno

diff

eren

cein

wt

&BM

Ibe

twee

nM

falle

rs&

non-

falle

rsan

dno

diff

eren

cein

wt

betw

een

Ffa

llers

&no

n-fa

llers

.E

ffec

tsi

zesh

owth

ere

was

adi

ffer

ence

inBM

Ibe

twee

nF

falle

rsan

dno

n-fa

llers

.M

ean

BMI

Ffa

llers

=27

.7(S

D1.

2)no

n-fa

llers

=27

.0(S

D1.

2.).

Ffa

llers

had

sign

ifica

ntly

grea

ter

BMI

than

non-

falle

rs(P

=0.

01)

Don’t fall for weight


275

Tab

le1

Con

tinu

ed

Firs

tau

thor

&ye

arTy

peof

stud

y&

NH

MR

Cle

velo

fev

iden

ce24

Age

inye

ars;

mea

n/SD

orra

nge

orm

edia

nn

&ge

nder

ratio

(F)

(M)

Popu

latio

nM

easu

reEf

fect

size

&95

%C

IK

eyfin

ding

s

Woo

Jet

al.

2009

25Pr

ospe

ctiv

eco

hort

Leve

lII

33%

65–6

9,33

%70

–74

33%

75+

3890

50%

F50

%M

Com

mun

ity

dwel

ling

(Chi

na)

BMI

&w

tN

ABM

I&

wt

wer

eno

tas

soci

ated

wit

hre

curr

ent

falli

ng

Tho

mas

Set

al.

2010

26D

escr

ipti

veLe

vel

IVM

ean

80.1

SD5.

965 54

%F

46%

M

Pts

from

afa

llscl

inic

(Ade

laid

e)W

tN

AM

ean

(SD

)w

tba

selin

e71

.5kg

(14.

4),

12-m

onth

follo

w-u

p70

.1kg

(15.

7)P

=0.

033

Wt

ina

grou

pof

falls

clin

icpt

sde

crea

sed

over

12m

onth

sJa

nsse

nH

etal

.20

0427

Ret

rosp

ecti

veco

hort

Leve

lII

I-3

Mea

n80

.6SD

6.7

rang

e65

+70 10

0%F

Ger

iatr

iccl

inic

pts

who

had

vita

min

Dle

vels

of20

–50

nmol

/L(N

ethe

rlan

ds)

BMI

BMI: F:

0.12

(-0.

35,

0.59

)E

ffec

tsi

zesh

ows

nodi

ffer

ence

inBM

Ibe

twee

nfa

llers

&no

n-fa

llers

Mill

erM

etal

.20

0928

Pros

pect

ive

coho

rtLe

vel

IIM

ean

M:

82.7

F:86

.5ra

nge

65–1

0420

0576

%F

24%

M

Res

iden

tial

care

faci

lity

(Syd

ney)

BMI

NA

No

diff

eren

cein

BMI

betw

een

falle

rs&

non-

falle

rs

Rut

ledg

eD

etal

.20

1029

Ret

rosp

ecti

veco

hort

Leve

lII

I-3

Mea

n59

.6SD

7.6

rang

e50

–85

70 93%

F7%

M

Com

mun

ity

dwel

ling

pers

onw

ith

fibro

mya

lgia

(USA

)

BMI

BMI 0.05

(-0.

42,

0.53

)E

ffec

tsi

zesh

ows

nodi

ffer

ence

inBM

Ibe

twee

nfa

llers

&no

n-fa

llers

Gre

any

Jet

al.

2010

30R

etro

spec

tive

coho

rtLe

vel

III-

3R

ange

>70

33 70%

F30

%M

Res

iden

tsof

am

etro

inde

pend

ent

livin

gfa

cilit

y(U

SA)

BMI

BMI 0.66

(-0.

07,

1.38

)E

ffec

tsi

zesh

ows

nodi

ffer

ence

inBM

Ibe

twee

nfa

llers

&no

n-fa

llers

Hel

lstr

ömK

etal

.20

0931

Ret

rosp

ecti

veco

hort

Leve

lII

I-3

Mea

n65

SD9

80 64%

F36

%M

Pts

wit

hC

OPD

who

atte

nda

lung

clin

ic(S

wed

en)

BMI

BMI 0.00

(-0.

05,0

.51)

Eff

ect

size

show

sno

diff

eren

cein

BMI

betw

een

falle

rs&

non-

falle

rs

Jako

vlje

vic

M20

0932

Pros

pect

ive

coho

rtLe

vel

IIM

ean

80SD

783 82

%F

18%

M

Res

iden

tial

care

faci

lity

(Slo

veni

a)BM

IBM

I 0.00

(-0.

52,0

.52)

Eff

ect

size

show

sno

diff

eren

cein

BMI

betw

een

falle

rs&

non-

falle

rs

Dec

ullie

rE

etal

.20

0933

Des

crip

tive

Leve

lIV

Ran

ge>7

566

210

0%F

Com

mun

ity

dwel

ling

falle

rs(F

ranc

e)BM

IN

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276

size, ranging from 33 to 4996 participants. In 23 of 27studies, the method of determining falls frequency was self-reported. The percentage of fallers per study populationranged from 5 to 100%.

Seven studies measured nutritional risk, malnutrition ormalnutrition risk in fallers.11–17 Two of the seven studiesmeasuring malnutrition risk were descriptive studies andfive were cohort studies. Both descriptive studies reported45% of a falls population as either at high malnutrition riskor were malnourished.11,12 Three of the five cohort studiesfound malnutrition or malnutrition risk to be greater infallers than non-fallers.13,14,17 The remaining two cohortstudies found no difference in malnutrition risk scorebetween fallers and non-fallers.15,16

Ten studies measured weight in fallers.11,18–26 Theseincluded two descriptive studies, one case control and sevencohort studies. Two studies found a difference in weight orweight changes between fallers and non-fallers.18,19 Onestudy reported that not losing weight between mid and olderage has a protective effect on falls.18 One study found havinga lower body weight was associated with recurrent fallingwith an odds ratio (OR) for having a lower body weight andfalls being OR 1.45 (1.10–1.91).19 Six of the ten studiesfound no different in weight between fallers and non-fallers.20–25

Twenty studies measured BMI in fallers.11,12,18–21,23–25,27–37

These included three descriptive studies, one case controlstudy and 16 cohort studies. One descriptive study foundone in eight clients (n = 90) attending a falls clinic had a BMI< 22 kg/m2, and one in five had a BMI > 30 kg/m2.12 Sixstudies found a difference in BMI between fallers and non-fallers.18,24,34–37 One study found fallers to have a significantlylower BMI compared with non-fallers (P = 0.002).18 Onestudy found female fallers had a significantly higher BMIthan non-fallers (P = 0.01), although the same result was notfound in male fallers.24 A further four cohort studies foundfallers had a higher BMI than non-fallers or that a higher BMIwas associated with falls.34–37 A further 11 studies found nodifference in BMI between fallers and non-fallers.19–21,23,25,27–32

Discussion

There is evidence that malnutrition is more prevalent in fallspopulations, but a causal effect cannot be assumed. Three offive cohort studies examining malnutrition risk and fallsfound malnutrition risk to be higher in fallers.13,14,17 Further-more, two descriptive studies found 45% of a falls popula-tion to be at high risk of malnutrition or assessed asmalnourished.11,12 The study by Stolz et al. (2002) was con-ducted in a community setting where malnutrition preva-lence has been found to be in the order of 10–30%.7,12 Thisfalls population therefore has a greater prevalence of malnu-trition than the general community. The study by Bauer et al.(2007) was conducted in fallers in an acute setting where theprevalence of malnutrition is reported to be in the order of20–50%.7,11 This study population has a prevalence of mal-nutrition (45%) at the upper end of the level found in the

general acute care population and therefore a higher percent-age malnourished than some studies of patients in acutecare. It is therefore appropriate to conduct malnutritionscreening in elderly falls clients.

This review found limited evidence that weight is differentbetween fallers and non-fallers, with six of ten studies mea-suring weight finding no difference in weight between fallersand non-fallers or found that weight was not a contributingfactor to falls.20–25 Two studies were descriptive studies offalls patients with no comparison to a control group.11,26

Only two studies found an association between low bodyweight or weight loss and falls.18,19 No studies found a rela-tionship between weight gain and falls. A study by Villarealet al. (2009) in the overweight elderly found intentionalweight loss decreased bone mass.38 This brings into questionthe appropriateness of promoting weight loss in the elderlyto decrease falls.

There is limited evidence that BMI is significantly differentbetween fallers and non-fallers with only six of 20 studiesfinding a difference in BMI between fallers and non-fallers.18,24,34–37 One of these six studies found fallers to havelower BMI and five found higher BMI in fallers or an asso-ciation with higher BMI and falls. The clinical relevancehowever of one study that found BMI to be statisticallysignificantly higher in fallers is low (mean BMI: 27.0 kg/m2

non-fallers compared with 27.7 kg/m2 in fallers).24 Onestudy found those in the extreme obese end of the BMI range(BMI � 40) reported more falls; however, the percentage ofparticipants in the extreme obesity group (3.5%) was smallcompared with the other BMI categories.34 Three studieswere descriptive studies and had no comparison to a controlgroup including one study in a falls clinic population.11,12,33

This review suggests that BMI is not an appropriate screen-ing tool to identify those at risk of falls and that nutritionalmanagement of those with high BMI to decrease falls risk isnot appropriate. It may be possible that people at both endsof the BMI spectrum are more likely to fall; however, thisreview did not find this result possible because of the statis-tical averaging effect of having high falls incidences at eitherend of the BMI scale.

A limitation of this review was the use of self-reported data(falls and weight) used in studies, which can show recall biasand makes interpretation of results difficult. Furthermore,interpreting the results of the studies is difficult because of thedifferent tools that were used to determine nutritional status.Two of the tools used were not validated malnutrition screen-ing or assessment tools (ANSI and a self-developed nutri-tional risk tool).12,13 Many of the study’s populations includedconvenience samples, small population sizes and differentpopulations between studies which makes comparing studieshard. This includes two studies examining fallers with frac-tures which may have affected the nutritional status or weightstatus of this group.15,18 The definition of a fall also differedbetween studies with one study separating frail mechanicalfallers and active mechanical fallers.17 One study excludedparticipants with morbid obesity and other studies had higherrates of low BMI and lower falls rates than other studies. Studysettings varied and included acute hospitals, residential care



277

facilities and falls clinics. Many studies may have also had ahealthy population effect due to participants with a disability,dementia, cognitive impairment or using gait aids other thanwalking sticks being excluded.

It is difficult to advise on change to clinical practice basedon the data presented in this review due to the level ofevidence. Fifteen studies were NHMRC Level III evidence orbelow, and all studies were observational studies.39 Cautionis needed when recommending changes to clinical practicebased on observational studies only.10

From a moderate range of variable quality researchstudies, there was found to be limited evidence that adultswho fall have different weight or BMI than those who do notfall (Table 2). A limited number of studies did find thatmalnutrition rates can be high in falls populations possiblerelated to the elderly nature of this population. A duty of caretherefore exists for screening and treating of malnutrition infalls clinics. Falls clinics should utilise validated malnutritionscreening tools for the community setting and refer highmalnutrition risk clients for dietetic assessment and treat-ment.7 Further studies are needed that examine the effect oftreating malnutrition on falls incidence.

Acknowledgements

Thank you to Professor Nick Taylor and Eastern Health forproviding support for this research via the Eastern HealthAllied Health Research Training Scheme 2009. We wouldalso like to thank dietitians from the Victorian branch ofDAA’s Rehabilitation and Aged Care Interest Group (RACIG)for contributing data on dietetic employment in falls clinics.

References

1 Hill K, Black K, Muller L et al. Evaluation of a Minimum Data Setfor Victorian Falls Clinics Final Report. Melbourne: NationalAgeing Research Institute for the Victorian Department ofHuman Services, 2004.

2 Ministry of Older People in New Zealand. Older People’s HealthChart Book 2006. Public Health Intelligence Monitoring ReportNo. 12 (Feb 2007). Wellington: Ministry of Health, 2006.(Available from: http://www.moh.govt.nz/moh.nsf/pagesmh/5795#information, accessed 6 January 2011).

3 Australian Bureau of Statistics. Population Projections, Australia,2006 to 2101. ABS cat no. 3222.0. Canberra: Australian Bureauof Statistics, 2008. (Available from: http://www.abs.gov.au/ausstats/[email protected]/mf/3222.0, accessed 3 February 2010).

4 Ministry of Health. The Health of New Zealand: Total Population.Wellington: Ministry of Health, 2004. (Available from: http://www.moh.govt.nz/moh.nsf/0/2D5AD5B7B3C7817BCC256EE30079D11E/$File/healthofnztotalpopulation.pdf, accessed 6January 2011).

5 Hill K, Smith R, Schwarz J. Falls clinics in Australia: a survey ofcurrent practice, and recommendations for future development.Aust Health Rev 2001; 24: 163–74.

6 Moore H. Audit of Referrals to Community Rehabilitation ProgramDietetics from the Falls and Balance Clinic. Melbourne: EasternHealth, 2010.

7 Watterson C, Fraser A, Banks M et al. Evidence based guidelinesfor the nutritional management of malnutrition in adult patientsacross the continuum of care. Nutr Diet 2009; 66: S1–S34.

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9 Bischoff-Ferrari HA, Dawson-Hughes B, Willett WC et al. Effectof vitamin D on falls: a meta-analysis. JAMA 2004; 291: 1999–2006.

10 Public Health Resource Unit. Critical Appraisal Skills Programme.Oxford UK: National Health Service, 2004. (Available from:http://www.sph.nhs.uk/what-we-do/public-health-workforce/resources/critical-appraisals-skills-programme, accessed 10August 2009).

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12 Stolz D, Miller M, Bannerman E, Whitehead C, Crotty M,Daniels L. Nutrition screening and assessment of patientsattending a multidisciplinary falls clinic. Nutr Diet 2002; 59:234–39.

13 Johnson CS. The association between nutritional risk and fallsamong frail elderly. J Nutr Health Aging 2003; 7: 247–50.

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Table 2 Conclusion box

Main conclusion and recommendation:• There is limited evidence that weight status differs

between fallers and non-fallers• A limited number of studies found malnutrition rates

to be higher in fallers compared to non fallers• Malnutrition screening should occur in falls clinics

due to the elderly nature of this population andtherefore possible high risk of malnutrition



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27 Janssen HCJP, Samson MM, Meeuwsen IBAE, Duursma SA,Verhaar HJJ. Strength, mobility and falling in women referredto a geriatric outpatient clinic. Aging Clin Exp Res 2004; 16:122–25.

28 Miller MD, Thomas JM, Cameron ID et al. BMI: a simple, rapidand clinically meaningful index of under-nutrition in the oldestold? Br J Nutr 2009; 101: 1300–5.

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31 Hellström K, Vahlberg B, Urell C, Emtner M. Fear of falling,fall-related self-efficacy, anxiety and depression in individualswith chronic obstructive pulmonary disease. Clin Rehabil 2009;23: 1136–44.

32 Jakovljevic M. Predictive validity of a modified fall assessmenttool in nursing homes: experience from Slovenia. Nurs HealthSci 2009; 11: 430–35.

33 Decullier E, Couris CM, Beauchet O et al. Falls’ and fallers’profiles. J Nutr Health Aging 2010; 14: 602–08.

34 Beck TJ, Petit MA, Wu G, LeBoff MS, Cauley JA, Chen Z. Doesobesity really make the femur stronger? BMD, geometry, andfracture incidence in the women’s health initiative-observationalstudy. J Bone Miner Res 2009; 24: 1369–79.

35 Yeung PY, Woo J, Wai-Ting Yim V, Rainer TH. Heterogeneity ofhealth profiles of older people presenting to an accident andemergency department with a fall. Int J Gerontol 2009; 3: 156–62.

36 Furuya T, Yamagiwa K, Ikai T et al. Associated factors for fallsand fear of falling in Japanese patients with rheumatoid arthritis.Clin Rheumatol 2009; 28: 1325–30.

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38 Villareal DT, Shah K, Banks MR et al. Effect of Weight Loss andExercise Therapy on Bone Metabolism and Mass in Obese OlderAdults: A One-Year controlled Trial. J Clin Endocrinol Metab2009; 93: 2181–7.

39 Merlin T, Weston A, Tooher R et al. NHMRC levels of evidence andgrades for recommendations for developers of guidelines. Canberra:The National Health and Medical Research Council (NHMRC),December 2009. (Available from: http://www.nhmrc.gov.au/_files_nhmrc/file/guidelines/evidence_statement_form.pdf).



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don't fall for weight: a systematic review of weight status and falls

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