Gender Differences in Lower Extremity Function in Latin American EldersSeeking Explanations From a...

Gender Differences in LowerExtremity Function in Latin American EldersSeeking Explanations From a Life-Course Perspective

B. E. Alvarado, MD, PhDUniversité de Montréal, CanadaR. Guerra, PhDFederal University of Rio Grande do Norte, BrazilM. V. Zunzunegui, PhDUniversité de Montréal, Canada

Objective: The authors examined the contribution of life-course exposures togender differences in mobility in later life. Method: Data originate from asurvey of persons age 60 and older living in six Latin American and Caribbeancities (n = 10,661). Lower extremity limitations (LEL) were defined as thepresence of three or more reported difficulties with five activities: lifting andcarrying 10 lb, walking several blocks, climbing a flight of stairs, kneeling/stooping/crouching, and getting up from a chair. Data were pooled after testinghomogeneity of effects across cities. A multivariate model was fitted usinglogistic regression analysis. Complete data analyses were performed on 8,166(72%) participants. Results: Prevalence of LEL varies across cities (9.3–23.7%in men, 23.3–42.9% in women). Intervening life-course and health factorsexplained a small proportion of the gender difference in LEL (odds ratio = 2.39;95% confidence interval = 2.04–2.79). Childhood hunger was predictive ofLEL in women, and a stronger association between depression and LEL wasfound in men than in women. Little education and insufficient income wereassociated with LEL for both men and women. Discussion: Life-course expo-sures predict mobility, but further research is needed to identify interveningfactors relating gender to mobility in old age.

Keywords: lower extremities; mobility; gender; life course; aging

Journal of Aging and HealthVolume XX Number X

Month XXXX xx-xx© 2007 Sage Publications

10.1177/0898264307308618http://jah.sagepub.com

hosted athttp://online.sagepub.com

1

Introduction

Gender differences in physical disability have been extensively docu-mented. Compared to men, women report higher prevalence of limita-

tions in upper and lower extremity function and more difficulties ininstrumental and basic activities of daily living. This greater prevalenceamong women has been explained by higher comorbidity (Al Snih et al.,2005; Oman, Reed, & Ferrara, 1999), prevalence of depression and cogni-tive impairment (Oman et al., 1999; van Gool et al., 2005), different biologi-cal constitution (i.e., less muscle mass; Janssen, Heymsfield, & Ross, 2002),and higher rates of utilization of medical care (Verbrugge, 1985). Genderdifferences in functional health may also result from differential exposuresand resources for women and men during their life course (Hatch, 2005).A child’s family structure and social class, and his or her parents’ occupations,have been related to health and function in later life (Ben-Shlomo & Kuh,2002), and although it appears that women are not more likely than men tobe exposed to poor social conditions early in life, women appear to be moresusceptible to them (Keddie, Peek, & Markides, 2005; Lamb, 1997; Omran,1983; Veijola et al., 1998; Wray & Blaum, 2001). Education and occupation,known measures of adulthood socioeconomic position, have also been asso-ciated with mobility limitations (Ahacic, Parker, & Thorslund, 2003; Keddieet al., 2005; Melzer & Parahyba, 2004) and disability (Beydoun & Popkin,2005; Broese van Groenou, Deeg, & Penninx, 2003; Rosa, Benicio, LatorreMdo, & Ramos, 2003), and they may explain the higher prevalence of lowerextremity functional limitations among women in later life (Arber, 1997;Murtagh & Hubert, 2004). Last, income, housing and other measures of well-being during retirement years have been related to functional status anddisability (Beydoun & Popkin, 2005; Broese van Groenou et al., 2003; Cheng,Chi, Boey, Ko, & Chou, 2002; Melzer & Parahyba, 2004; Rosa et al., 2003;von dem Knesebeck, Luschen, Cockerham, & Siegrist, 2003) and mayaccount for some of the greater rate of disability in women (Arber, 1997).

2 Journal of Aging and Health

Authors’ Note: This study was supported by a grant from the Institute of Gender and Health,Canadian Institutes for Health Research (CIHR/IRSC). R. O. Guerra was supported byCoordenação de Aperfeiçoamento de Pessoal de Nível Superior (CAPES - Brazil). B. E. Alvaradoperformed all statistical analysis and wrote the article. R. O. Guerra supervised data analysisand contributed to revising the article. M. V. Zunzunegui planned the study, supervised thedata analysis, and contributed to revising the article. We thank the several thousands of olderpeople who participated in the SABE survey. Please address correspondence to Dr. BeatrizEugenia Alvarado, Département de médecine sociale et préventive, Université de Montréal,CP 6128, Succursale Centre Ville, H3C 3J7, Montréal, Québec, Canada; e-mail: [email protected].

In this article we focus on gender differences in lower body mobility,because lower extremity function is predictive of severe disability, death,and institutionalization (Guralnik, Ferrucci, Simonsick, Salive, & Wallace,1995; Ostir, Markides, Black, & Goodwin, 1998; Peek, Ottenbacher,Markides, & Ostir, 2003). In addition, longitudinal studies of older peoplehave determined that lower extremity limitations (LEL) may be the mainpathway through which gender and poor social conditions, as well as chronicdiseases and mental health problems, are related to disability (Barbosa,Souza, Lebrao, Laurenti, & Marucci Mde, 2005; Femia, Zarit, & Johansson,2001; Lawrence & Jette, 1996; Peek et al., 2003; Wray & Blaum, 2001).The study of gender differences in LEL using a life-course perspective mayhelp identify periods at which socioeconomic factors have the greatestimpact on gender differences in health and function.

Data from the SABE survey on urban elders age 60 and older living inseven Latin American and Caribbean (LAC) cities, pertaining to functionaland health variables, and conditions during the life course are now available(Pelaez et al., 2004). In the seven cities, elderly women presented higherprevalence of difficulties in Instrumental Activities of Daily Living (IADL)and Activities of Daily Living (ADL) as compared with men (Reyes-Ortiz,Ostir, Pelaez, & Ottenbacher, 2006); they also experienced greater rates ofdiabetes, arthritis, obesity, and reported falls (Al Snih, Ray, & Markides,2006; Barcelo, Pelaez, Rodriguez-Wong, & Pastor-Valero, 2006; Reyes-Ortiz, Al Snih, & Markides, 2005). These generations of women in LACcountries (i.e., individuals currently older than 60) had less opportunitiesfor education, qualified employment, and social security compared to men(Pinzon & Solas, 2002; Zunzunegui, Pinzon, Beland, et al., 2002; Zunzunegui,Pinzon, Engler, & Pantelides, 2002b). Therefore, it is reasonable to arguethat gender differences in functional health in LAC elders may be explainedby the differential exposure to life-course circumstances such as education,skilled occupations, and wealth during retirement years. In this work, weexplore whether the higher prevalence of mobility limitations in LACwomen as compared to men is explained by their greater exposure to socialdisadvantage during the life course and by their higher comorbidity.

Materials and Methods

Study Population

The SABE project is a multicentric cross-sectional study conducted in1999–2000 on 10,661 men and women age 60 and older in seven LAC cities:

Alvarado et al. / Mobility Limitations 3

Buenos Aires, Argentina (n = 1,043); Bridgetown, Barbados (n = 1,508);Sao Paulo, Brazil (n = 2,143); Santiago, Chile (n = 1,301); Havana, Cuba(n = 1,905); Mexico City, Mexico (n = 1,311); and Montevideo, Uruguay(n = 1,450; Albala et al., 2005). Response rates varied from 95.3% in Cubato 62.5% in Argentina. Assisted interviews were conducted for 1.1% of theinterviews in Montevideo, 3.8% in Buenos Aires, 4.3% in Bridgetown, 5.9%in Mexico City, 9.0% in Havana, 9.2% in Santiago, and 12.9% in Sao Paulo.Data from Barbados were not included, as values were missing for 28.3%of the data on activities used to construct the lower extremity limitationvariable (Table 1).

Outcome

LEL were defined as the number of limitations that the participantshad at the time of the interview (Lawrence & Jette, 1996). These limitationswere inquired through the following questions: Do you have any difficultywith lifting or carrying weights over 5 kg/10 lb, like a heavy shopping bag?Do you have any difficulty with walking several hundred yards? Do youhave any difficulty with climbing one flight of stairs without resting? Doyou have any difficulty with stooping, kneeling, or crouching? Do you haveany difficulty with getting up from a chair after sitting for long periods?Perceived difficulty in performing each activity was recoded as no difficulty,with difficulty, cannot do it, and do not do it. People who answered do not doit were recorded as missing (n = 844; 9.3%). Answers were dichotomizedas 0 (no difficulty) and 1 (with difficulty or unable to do it). Lower body limi-tations were defined as the number of activities for which the respondentreported difficulty or unable to do (score 0–5) and further classified as nolimitation (0), mild limitation (1–2), and severe limitations (3+). For multi-variate analysis, the first two categories were analyzed jointly. Thus, ourresults refer to the presence of three or more lower body limitations.

Life-Course Socioeconomic Variables

Childhood, adulthood, and current socioeconomic circumstances wereincluded as predisposing factors. Childhood socioeconomic circumstanceswere assessed via the following questions:

During the first 15 years of your life: 1) did you live in a rural area for 5 yearsor more? (yes/no); 2) what was your family’s economic situation? (good/average/poor); 3) was your health excellent, good or poor? (good/average/poor); 4) were there times when you went hungry? (yes/no)


Adulthood socioeconomic circumstances were determined by the respon-dent’s education and lifelong occupation. Education and occupational vari-ables were grouped into two general categories: no schooling (illiterate,no formal education) versus other (some primary or more) and nonmanual/skilled workers (white collar, blue collar) versus manual workers (semiskilled,unskilled, farm workers). Housewives were analyzed in a separate category,


Table 1Distribution of Difficulties in Lower Extremity Function Among

Women and Men Older Than 60 in Seven Latin American and Caribbean Cities

% of Elders Unable to

Walk Several Get Up Climb a Flight Kneel/Stoop/ Lift and Blocks From a Chair of Stairs Crouch Carry 10 lb

Buenos AiresWomen 38.2 35.5 32.0 47.2 39.7Men 21.3 20.7 16.5 34.3 20.8Missing 2.3 0.4 4.3 0.9 7.2

BridgetownWomen 29.6 33.3 21.5 43.4 21.3Men 16.5 16.7 12.2 23.0 7.3Missing 13.3 0.7 9.0 5.2 13.8

Sao PauloWomen 31.2 38.4 30.6 53.2 38.1Men 21.9 21.4 20.0 36.3 15.6Missing 1.6 0.3 1.0 0.9 6.0

SantiagoWomen 41.1 51.3 35.1 60.8 40.9Men 23.3 30.6 21.1 40.0 13.2Missing 2.6 0.2 3.5 0.8 3.4

HavanaWomen 38.4 49.3 32.7 58.4 38.7Men 21.1 28.1 17.5 35.3 13.9Missing 2.0 0.2 2.7 0.9 6.5

Mexico Women 40.8 48.9 32.8 54.2 44.8Men 26.1 33.7 18.6 44.6 16.2Missing 0.8 0.3 2.2 0.5 2.9

MontevideoWomen 39.2 40.6 31.8 45.7 31.6Men 23.2 26.6 18.9 29.0 11.9Missing 1.6 0.3 2.6 0.9 5.6

Note: This table shows weighted data.

as 9.7% (n = 1,031) of the Latin American women in the sample had neverhad gainful employment. Current material resources were defined as per-ceived sufficiency of income and home ownership. Perceived income wasself-reported as sufficient or insufficient. Marital status was categorized intotwo groups: presence or absence of a partner.

Health and Mental Variables

Comorbidity was measured as a summated index of any of the followingmedical conditions reported by respondents (range = 0–7): hypertension,diabetes, cancer, heart disease, stroke, hip fracture, and arthritis; data werefurther dichotomized as none or one versus two or more.

Depressive symptoms were assessed using the Geriatric Depression Scale.The Geriatric Depression Scale score was grouped into three levels usingwell-accepted cutoff points: 0 to 5 indicated no depression, 6 to 10 was mildlysuggestive of depression, and 11 to 15 was strongly suggestive of depres-sion (Yesavage et al., 1982). The last cutoff was chosen to distinguish thoseexperiencing a high number of depressive symptoms (11–15) from thoseexperiencing none or few (0–10).

Cognitive function was measured via a modified version of the Mini-Mental State Examination and the Pfeffer scale as reported previously(Pelaez et al., 2004). Respondents scoring 12 or less in the modified Mini-Mental State Examination and 6 or more on the Pfeffer Scale were consid-ered cognitively impaired; otherwise, respondents were considered to havenormal cognitive function.

Statistical Analysis

First, logistic regression was used to examine the association of healthand life-course factors with LEL, within each city, adjusted by age. Second,the homogeneity/nonhomogeneity of each multivariate coefficient (eachfactor separately on LEL, adjusted by age) across the cities was assessedconsidering the Dyer (1986) approach:

1. A pooled estimate was constructed by weighting each multivariate coefficientwith the inverse of its variance and then summing over all six weighted coeffi-cients, divided by the sum of the weights.

2. The pooled estimate was used in a chi-square test to verify the null hypothesisthat all multivariate coefficients were equal across cities.

3. If the null hypothesis was rejected, an interaction of the “predictor” and “city”(i.e., Education × City) variables on LEL was introduced into the analysis.


4. If the hypothesis of homogeneity was not rejected, no interaction for thepredictor and city variables on LEL was further tested and the predictorvariable was tested jointly for all cities.

Third, after establishing homogeneity/nonhomogeneity effects, the logisticmodels were fitted as follows. We introduced gender and age first and then,using staggered entry, introduced the variables pertaining to childhood, adult-hood, and current social circumstances. Last, we included comorbidity andmental health. At each step, interactions between gender and every risk factorwere tested: (a) In case of homogeneity across cities, two-order interactionterms were included (i.e., Gender × Education), and (b) in the case ofheterogeneity across cities, three-order interactions were tested (Gender ×Education × City). Analyses of interactions with gender allowed for testingdifferential gender vulnerability in the associations of potential risk factorswith mobility.

Results

More women than men reported limitations in lower extremities in allLAC cities and in the five categories of lower extremity function (Table 1).Limitations in kneeling/stooping/crouching were more frequently reportedin all cities. Women were less frequently limited in climbing stairs, and menwere less frequently limited in lifting and carrying 10 lb. For the total LELscore, prevalence of severe limitations was higher in Havana and Santiagoand lower in Mexico (Table 2).

In general, men were more likely than women to have lived under poorsocial conditions during childhood in Havana, Mexico, Santiago, and SaoPaulo, but men and women had shared similar childhood conditions inBuenos Aires and Montevideo (Table 3). Conversely, women were morelikely to be socially deprived (no education, being manual workers) duringadulthood than men in all cities but Havana; current material conditionsmeasured by perceived insufficient income were worse for women thanmen in Buenos Aires and Santiago. In all cities, women were less likely tobe currently married. For all health factors, women reported more chronicconditions and more depressive symptoms, but cognitive impairment wassimilarly prevalent in both women and men (data no shown).

Using the Dyer method, homogeneity in the effect of exposure variableson lower extremity limitations across the cities was confirmed, except formarital status (see Table 4). Pooled logistic regression coefficients confirmedthat rural life, poor health, hunger and disadvantaged socioeconomic conditions


during childhood, no schooling, lifelong lower-skilled occupations, andperceived insufficient income were associated with reporting severe functionallimitations. Odds of limitations in lower extremity function were higher amongthose living without a partner in all cities except Sao Paulo. Reporting twoor more chronic conditions and cognitive impairment predicted the presenceof functional limitations in every city. Suffering from hunger during child-hood was associated with severe mobility limitations in women but not in men,whereas depression was more strongly associated with mobility limitationsamong men than women.

Logistic regression model-building results are shown in Table 5. Greaterodds of functional limitations among women persisted when all social andhealth variables were introduced. The odds of women versus men decreasedafter controlling for comorbidity, depression, and cognitive impairment butremain significant (odds ratio = 2.39, 95% confidence interval = 2.04–2.79).Results were homogeneous across cities except for marital status in BuenosAires and Santiago; in these two cities the absence of a partner remains animportant predictor of mobility limitations. The odds of LEL remained highamong women and men exposed to poor social conditions during childhood,with little education and current insufficient income.

Because anthropometric measures were taken in all cities except BuenosAires, and we excluded Bridgetown from multivariate analysis, we wereable to assess the associations of body mass index (BMI) with mobility infive cities. Further analysis entering obesity (BMI ≥ 30 kg/m2) did notchange the gender odds for mobility.


Table 2Mean and Prevalence of Lower Extremity

Limitations in SABE Cities

% With 1 or 2 Difficulties % With ≥ 3 Difficulties

Women Men Missing City (M, SD) (M, SD) Diff. Women Men Women Men (%)

Buenos Aires 1.892 (1.77) 1.108 (1.48) 0.784* 31.6 35.7 36.2 14.4* 129 (12.4%)Bridgetown 1.423 (1.60) 0.657 (1.22) 0.763* 36.3 23.1 23.3 9.3* 427 (28.3%)Sao Paulo 1.894 (1.73) 1.128 (1.53) 0.766* 33.7 28.5 36 18.8* 206 (9.6%)Santiago 2.248 (1.76) 1.281 (1.52) 0.967* 34.4 36 42.9 19.6* 133 (10.2%)Havana 2.161 (1.73) 1.102 (1.50) 1.059* 34.5 31.9 41.5 16.1* 168 (8.8%)Mexico 1.758 (1.70) 1.401 (1.57) 0.357* 36.2 34.4 31.3 23.7* 95 (5.1%)Montevideo 1.885 (1.76) 1.079 (1.41) 0.806* 32.7 31.8 35.2 17.3* 137 (9.4%)

Note: This table shows weighted data.*Differences between women and men, p < .05.

9

Tabl

e 3

Gen

der

Dis

trib

utio

n of

Chi

ldho

od C

ondi

tion

s in

Si

x L

atin

Am

eric

an C

itie

s

Bue

nos

Air

es

Hav

ana

Mex

ico

Mon

tevi

deo

Sant

iago

de

Sao

Paul

o (A

rgen

tina)

(C

uba)

(Mex

ico)

(Uru

guay

)C

hile

(C

hile

)(B

razi

l)

Con

ditio

nW

omen

Men

W

omen

Men

W

omen

Men

W

omen

Men

W

omen

Men

W

omen

Men

Chi

ldho

od s

ocia

l an

d he

alth

ci

rcum

stan

ces

Rur

al li

fe (

yes)

37.5

39.8

49.7

53.4

53.7

56.5

42.2

45.1

48.3

51.6

58.1

*69

.2Pe

rcep

tion

of

52.9

49.0

70.1

*79

.574

.9*

81.3

62.0

*68

.453

.0*

63.4

67.5

*73

.1so

cioe

cono

mic

st

atus

(av

erag

e/

poor

)Pe

rcep

tion

of h

ealth

47

.151

.064

.264

.153

.850

.557

.858

.265

.961

.051

.948

.8(a

vera

ge/p

oor)

Hun

ger

(yes

)10

.112

.220

.8*

28.2

25.5

*34

.810

.6*

13.8

19.0

22.6

18.5

21.8

*p<

.01.


Table 4Estimated Associations Between Lower Extremity Limitations (3 and

More vs. 0-2) and Gender, Life-Course, and Health Risk Factors

Lower Upper Factor OR Level CI Level CI

GenderWomen vs. men 2.912 2.594 3.270

Childhood conditionsRural Yes vs. no 1.134 1.024 1.257

Childhood hungerYes vs. no 1.596 1.408 1.808

Childhood healthPoor/average vs. good 1.380 1.244 1.532

Childhood socioeconomic statusPoor/average vs. good 1.413 1.263 1.581

Adulthood conditionsEducationNo schooling vs. primary or more 1.828 1.589 2.102

Lifetime occupation Semiskilled, unskilled manual vs. nonmanual/ 1.364 1.215 1.531skilled manual

Housewives vs. nonmanual/skilled manual 1.728 1.440 2.073Current conditions

Perception of incomeInsufficient vs. sufficient 1.802 1.618 2.007

Home ownershipNo vs. yes 1.025 0.881 1.193

Marital statusa

Buenos Aires 2.20 1.58 3.07Havana 1.82 1.42 2.33Mexico 1.31 1.01 1.69Montevideo 1.46 1.13 1.89Santiago de Chile 2.31 1.74 3.07

Sao Paulo 1.16 0.93 1.45Health conditions

Chronic diseases 3.169 2.850 3.524≥ 2 vs. 0–1

Depressionb

11 and more vs. 10 and less 6.429 4.988 8.287Cognitive functionImpaired vs. normal 6.664 4.041 10.992

Note: All regressions adjusted by age. a. Without partner versus with partner. b. Geriatric Depression Scale.

11

Tabl

e 5

Mul

tipl

e L

ogis

tic

Reg

ress

ions

for

the

Ass

ocia

tion

s B

etw

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Low

er E

xtre

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imit

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(3 a

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d H

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acto

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Fact

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(95

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Mod

el 2

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(95

% C

I)b

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el 3

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(95

% C

I)c

Mod

el 4

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(95

% C

I)d

Gen

der

Wom

en v

s. m

en2.

86 (

2.50

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8)2.

84 (

2.47

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5)2.

74 (

2.37

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8)2.

39 (

2.04

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hild

hood

soc

ial a

nd h

ealth

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ditio

nsR

ural

Y

es v

s. n

o1.

16 (

1.04

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9)1.

05 (

0.94

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04(0

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1.17

)1.

05 (

0.93

-1.8

1)C

hild

hood

hun

ger

(yes

vs.

no)

Wom

en

1.72

(1.

45-2

.02)

1.63

(1.

38-1

.93)

1.57

(1.

33-1

.86)

1.47

(1.

23-1

.76)

Men

1.23

(0.

98-1

.55)

1.21

(0.

96-1

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1.15

(0.

92-1

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1.08

(0.

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Chi

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/ave

rage

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1.12

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9)1.

21 (

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-1.3

5)1.

17 (

1.04

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hild

hood

soc

ioec

onom

ic s

tatu

sPo

or/a

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ge v

s. g

ood

1.35

(1.

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1.32

(1.

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1.30

(1.

14-1

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1.28

(1.

12-1

.46)

Adu

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d so

cial

and

mat

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l con

ditio

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No

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g vs

. pri

mar

y or

mor

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53 (

1.31

-1.7

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46 (

1.24

-1.7

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39 (

1.17

-1.6

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ifet

ime

occu

patio

n M

anua

l vs.

non

man

ual

1.16

(1.

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1.07

(0.

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1.11

(0.

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Hou

sew

ives

vs.

non

man

ual

1.08

(0.

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1.00

(0.

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1.04

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Cur

rent

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ondi

tions

Perc

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vs.

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(1.

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1.54

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Mar

ital s

tatu

se

(con

tinu

ed)

12

Tabl

e 5

(con

tinu

ed)

Fact

ors

Mod

el 1

:OR

(95

% C

I)a

Mod

el 2

:OR

(95

% C

I)b

Mod

el 3

:OR

(95

% C

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Mod

el 4

:OR

(95

% C

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Bue

nos

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54 (

1.09

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57 (

1.10

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avan

a 1.

18 (

0.91

-1.5

3)1.

18 (

0.90

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5)M

exic

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86 (

0.65

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82 (

0.61

-1.0

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onte

vide

o0.

97 (

0.74

-1.2

7)0.

94 (

0.71

-1.2

5)Sa

ntia

go d

e C

hile

1.58

(1.

17-2

.13)

1.51

(1.

10-2

.07)

Sao

Paul

o0.

79 (

0.63

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85 (

0.67

-1.0

8)H

ealth

con

ditio

nsC

hron

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ses

≥2

vs. 0

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2.55

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2.59

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4.72

-13.

73)

Cog

nitiv

e im

pair

men

t Im

pair

ed v

s. n

orm

al3.

90 (

2.26

-6.7

4)

Not

e:O

R =

odd

s ra

tio; C

I =

con

fide

nce

inte

rval

.a.

Age

,gen

der,

and

child

hood

cir

cum

stan

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b. A

ge,g

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r,ch

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od,a

nd a

dulth

ood

circ

umst

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s.c.

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,gen

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d,an

d cu

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t cir

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curr

ent c

ircu

mst

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d he

alth

fac

tors

.e.

With

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Discussion

The SABE study provides a unique opportunity to explore gender differ-ences in health and function in LAC elders from a life-course perspective.Results indicate that the prevalence of LEL is higher among women thanmen, and this is true for every city and for each of the activities considered.We found that life-course and health factors only partially explained genderdifferences in mobility. Life-course exposures, cognitive impairment, depres-sion, and chronic conditions are important predictors of mobility in LACelders, but the gender differential in mobility remains largely unexplainedby these risk factors.

Few population studies have sought explanations of gender differencesin LEL (Wray & Blaum, 2001). Studies tend to focus on gender differencesin overall disability (Beland & Zunzunegui, 1999; Keddie et al., 2005; Lamb,1997). Factors explaining gender differences in functional health vary acrosssocieties, and gender differences frequently remain unexplained. In a cross-sectional study of U.S. elders, Wray and Blaum reported that lower bodymobility limitations persisted after controlling for education and chronicconditions (Wray & Blaum, 2001); in Britain, Arber and Cooper (Arber,1997) found that women’s higher odds of ADL disability persistedafter adjustment for education, income, and occupation; and Beland andZunzunegui (1999) found that among Spanish elders, education, chronicdiseases, depression, and cognitive function did not decrease the gendergap in ADL/IADL disability. However, in one study, gender differences inADL disability disappeared after adjustment by a long list of chronic andacute conditions (Murtagh & Hubert, 2004). In LAC elders, gender differencein IADL and ADL disability persisted in some cities (Buenos Aires andSantiago) but lost significance in the remaining five cities after adjustmentfor education, marital status, BMI, age, and chronic diseases (Reyes-Ortizet al., 2006).

Clearer explanations for the gender gap in lower extremity function willdepend on an understanding of biological mechanisms involving hormonesand body composition, nutritional problems (obesity, undernutrition), andloss of muscle mass (sarcopenia), all of which affect elderly women morethan men (Carter, Hambleton, Broome, Fraser, & Hennis, 2006; Morley,Perry, & Miller, 2002). Physical activity may also account for genderdifference in mobility, because women tend to be less physically active ascompared to men (Kuh, Bassey, Butterworth, Hardy, & Wadsworth, 2005;Lacroix, Guralnik, Berkman, Wallace, & Satterfield, 1993; Lamb, 1997;Launer, Harris, Rumpel, & Madans, 1994).


Gender differential vulnerabilities to social and health factors have beendescribed for mental and physical health outcomes (Lamb, 1997; Omanet al., 1999; Veijola et al., 1998). In this study on LAC elders, hardship duringchildhood, as measured by the experience of hunger, appears to generate astronger effect in women. Some evidence suggests that women are morevulnerable to poor childhood conditions compared with men. Infectiousdiseases affect more women than men during the epidemiologic transition(Omran, 1983); poor social conditions during childhood may alter hormonalcycles and predict early menopause (Hardy & Kuh, 2005), which may affectthe onset of osteoporosis, depression, and cognitive impairment; experiencinghunger may be a stressful event, to which women are more reactive thanmen (Veijola et al., 1998). Among Egyptian elders, a stronger relationshipbetween disability and childhood rural life and current poor materialconditions has been reported for women, whereas education was associatedwith disability in men (Lamb, 1997). Conversely, depressive symptoms aremore strongly related to LEL in men than in women, supporting the hypothesisthat men’s mental health is more vulnerable to changes in physical health(Beekman, Kriegsman, Deeg, & van, 1995).

An association between hunger during childhood and lower extremityfunction in old age has been described, reflecting the significant effect ofearly exposures on function in later life. Social, biological, or psychosocialpathways may play a major role (Kuh, Ben-Shlomo, Lynch, Hallqvist, &Power, 2003). For instance, poor social conditions during childhood mayreduce an individual’s chances of becoming highly educated and workingin a high-skilled occupation; they may also increase the risk of chronic diseaseleading to poor functional outcomes as well as high-risk behaviors (Lawloret al., 2005; Wray, Alwin, & McCammon, 2005). Hence, mobility limitations,as well as other health and mental problems, are rooted in the early lives ofurban-dwelling LAC women and men.

Furthermore, education, occupation, and current socioeconomic conditionsgenerate their own specific effects (Beydoun & Popkin, 2005; Coppin et al.,2006; Li, Wu, & Wen, 2000; von dem Knesebeck et al., 2003). Education,occupation, and especially current income influence choice and availabilityof health care (Wallace & Gutierrez, 2005) and the knowledge of healthpromotion and disease prevention practices (e.g., physical activity). Manualworkers may be particularly exposed to environmental risk factors, suchas repetitive-motion injuries, physical strain, and work that is not veryintellectually demanding, the latter of which leads to poor cognition (Alvarado,Zunzunegui, Del, & Beland, 2002; Arndt et al., 2005; Mansson, Rastam,Eriksson, & Israelsson, 1998). In addition, low-income elders tend to be less


integrated into social groups and may experience social exclusion, thusincreasing the risk of functional limitations (Beland, Zunzunegui, Alvarado,Otero, & Del Ser, 2005; Zunzunegui, Alvarado, Del Ser, & Otero, 2003).Perceived financial sufficiency has also been shown to be related to thephysical and mental health of elderly populations (Cheng et al., 2002).

With respect to marital status, those with spouses experienced significantlyfewer mobility limitations, even after controlling for social and health factors.However, this was true in only two of the six cities: Buenos Aires and Santiago.The evidence that marital status can affect functional status decline is diver-gent and depends on living arrangements. For instance, older persons livingwith children and without spouses experienced worse outcomes comparedto those who lived alone (Zyzanski, Medalie, Ford, & Grava-Gubins, 1989),and women living alone are less likely to experience functional decline thanthose sharing households with spouses or nonspouses, given that theyhad no severe impairment at baseline (Sarwari, Fredman, Langenberg, &Magaziner, 1998). In China, living without a spouse is associated with a declinein function despite potential social support provided by other coresidents(Beydoun & Popkin, 2005). The lack of association between marital statusand mobility limitations in LAC elders may be because of the role ofextended family networks (children, relatives, friends) in the productionand/or buffering of the limitations.

Cognitive impairment and depression place an individual at risk of dis-ability (Femia et al., 2001; Tabbarah, Crimmins, & Seeman, 2002). Cognitiveresources allow individuals to respond and adapt to the demands and needsof the environment and remain engaged in higher levels of functioning (socialactivities, physical exercise; Raji et al., 2005; Tabbarah et al., 2002). In addi-tion to cognitive performance, depression has also been linked to both theonset of and changes in disability, providing additional evidence of the roleof motivation in performing daily activities. Depression has been relatedto lower rates of recovery and may alter the course of disablement, especiallyin those with other chronic diseases (van Gool et al., 2005). Last, chronicconditions (especially arthritis and high blood pressure, included as comor-bidity) are strong predictors of functional limitations and disability, aspreviously reported (Fried, Bandeen-Roche, Kasper, & Guralnik, 1999).

Limitations and Strengths

Using survey data precludes exploring whether the higher prevalence ofLEL among women is because of higher incidence or longer duration ofimpairment, or to their low mortality. Studies are more consistent in showing


that greater prevalence in women results from higher incidence and lowerrecovery rates and that higher mortality in men does not explain the greaterprevalence in women (Leveille, Penninx, Melzer, Izmirlian, & Guralnik,2000). In addition, we cannot determine whether education and income affectprevalence because they are related to the onset of the limitation or to recovery.Neither can we determine the direction of the association of sufficient income,depressive symptoms, and LEL because of the cross-sectional nature ofSABE data. It is possible that insufficient income is a consequence of limitedactivities rather than its cause. Depressive symptoms may contribute to anincrease of limitations as well as limitations may limit social integration andtherefore contribute to worse mental health. Longitudinal studies of LACelders are required. Finally, we have used as outcome the presence of threeand more limitations rather than the presence of any so as to being able toevaluate the factors that predict the severity of mobility limitations. Wedecided to do this because of the high prevalence of any type of limitation(64.4%). However, this definition may overestimate the excess of limitationsin women because their strength and muscle development are lower thanthat of men. In fact, if the analysis is done with the outcome “any type ofdifficulty” versus “none,” the gender–age adjusted odds would be 2.54, not2.89, and the gender excess in this case is still unrelated to social and healthcircumstances (all variables adjusted 2.33). This analysis suggests that theoverestimation is very small.

Despite its limitations, this study’s findings increase our understandingof the role of socioeconomic inequalities with respect to mobility, especiallythose that are determined early in life such as childhood deprivation,education, and occupational status. These life-course exposures influencemobility in later life, thus prevention of social disadvantage may result inimprovement of functional status within the elderly population. From a genderperspective, this study provides evidence of higher female vulnerability tohunger in childhood, although life-course exposures and the differentialvulnerability of women did not account for the greater rate of limitedmobility among women.

The implications of our study on aging research in LAC populations arethreefold. First, our results demonstrate that it is necessary to develop andvalidate better instruments to measure childhood conditions because recallbias may lead to underestimation of their effect on older people’s health(Kauhanen, Lakka, Lynch, & Kauhanen, 2006). Second, we demonstratethe existence of a large gender gap in mobility limitations in LAC popula-tions, and further studies should continue to inquire on the differentialexposure and vulnerabilities that explain such gap. Answers to these questions


will help to better delineate the interventions on elderly populations. Finally,our results offered new findings concerning life-course predictors of LEL.Future studies will need to explore the pathways that relate early lifeconditions to functional health in later life (i.e., smoking, physical activity)to identify effective community and clinical interventions.

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