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. Author manuscript; available in PMC: 2014 Jun 4.
Published in final edited form as: Psychol Med. 2012 Aug 9;43(4):865–879. doi: 10.1017/S0033291712001468

Cross-national differences in the prevalence and correlates of burden among older family caregivers in the WHO World Mental Health (WMH) Surveys

V Shahly 1, S Chatterji 2, M J Gruber 1, A Al-Hamzawi 3, J Alonso 4, L H Andrade 5, M C Angermeyer 6, R Bruffaerts 7, B Bunting 8, J M Caldas-de-Almeida 9, G de Girolamo 10, P de Jonge 11, S Florescu 12, O Gureje 13, J M Haro 14, H R Hinkov 15, C Hu 16, E G Karam 17, J-P Lépine 18, D Levinson 19, M E Medina-Mora 20, J Posada-Villa 21, N A Sampson 1, JK Trivedi 22, M C Viana 23, R C Kessler 1,*
PMCID: PMC4045502  NIHMSID: NIHMS588969  PMID: 22877824

Abstract

Background

Current trends in population aging affect both recipients and providers of informal family caregiving, as the pool of family caregivers is shrinking while demand is increasing. Epidemiologic research has not yet examined the implications of these trends for burdens experienced by aging family caregivers.

Methods

Cross-sectional community surveys in 20 countries asked 13,892 respondents ages 50+ about the objective (time, financial) and subjective (distress, embarrassment) burdens they experience in providing care to first-degree relatives with 12 broadly-defined serious physical and mental conditions. Differential burden was examined by country income category, kinship status, and type of condition.

Results

Among the 26.9-42.5% respondents in high, upper-middle, and low/lower-middle income countries reporting serious relative health conditions, 35.7-42.5% reported burden. Of those, 25.2-29.0% spent time and 13.5-19.4% money, while 24.4-30.6% felt distress and 6.4-21.7% embarrassment. Mean caregiving hours/week given any was 16.6-23.6 (169.9-205.8 hours/week/100 people ages 50+). Burden in low/lower-middle income countries was 2-3-fold higher than in higher income countries, with financial burden given any averaging 14.3% of median family income in high, 17.7% in upper-middle, and 39.8% in low/lower-middle income countries. Higher burden was reported by women than men and for conditions of spouses and children than parents or siblings.

Conclusions

Uncompensated family caregiving is an important societal asset that offsets rising formal healthcare costs. However, the substantial burdens experienced by aging caregivers across multiple family health conditions and geographic regions threaten the continued integrity of their caregiving capacity. Initiatives supporting older family caregivers are consequently needed, especially in low/lower-middle income countries.

Keywords: family burden, cross-national, caregivers, epidemiology, mental health

INTRODUCTION

A global “caregiving crisis” (Carter, 2008) is widely forecast owing to dramatic demographic transitions and health trends that strain conventional healthcare mechanisms (Wiener, 2003). Rapid population aging (Bloom, 2011; Carter, 2008; Lee, 2011; Wiener, 2003) is accompanied by increases in age-related morbidity and disability (Christensen et al., 2009; Vogeli et al., 2007). The Old Age Dependency Ratio is accordingly projected to double by 2050 and triple by 2100 (Lee, 2011). Confronted with the resultant growth in long-term care (LTC) needs and critical shortages of professional resources (Carter, 2008; Christensen et al., 2009; Jacobzone, 2000; Kakuma et al., 2011; Levine et al., 2010; Wiener, 2003), public health systems increasingly seek community solutions, including deinstitutionalization, laws mandating care of dependent relatives, and “cash-for-care” incentives (Bolin et al., 2008; Jacobzone, 2000; Levine et al., 2010). Such initiatives will doubtlessly compound the burden of family caregivers (Awad & Voruganti, 2008; Jacobzone, 2000; Lamura et al., 2008) who already shoulder the vast majority of LTC responsibilities without pay or compensation for forgone wages (Carter, 2008; Jacobzone, 2000; Levine et al., 2010; Wiener, 2003).

But informal caregiving systems are simultaneously dwindling (Ekwall et al., 2007) due to socio-demographic trends towards delayed childbearing, smaller families, more divorce and remarriage, more female employment and dual-earner households, higher migration and globalization, and less inter-generational co-residency (Bolin et al., 2008; Heitmueller, 2007; Lamura et al., 2008; Wiener, 2003). As a result of these trends, the burden of chronic care increasingly falls on family caregivers who are themselves aging (Jacobzone, 2000; Kakuma et al., 2011; Lee, 2011; Levine et al., 2010; Wiener, 2003) and vulnerable to the burdens of caregiving, which include financial strain (Bolin et al., 2008; Carmichael & Charles, 2003; Heitmueller & Inglis, 2007; Hickenbottom et al., 2002; Kusano et al., 2011), depression (Haley et al., 2009; Opree & Kalmijn, 2012; Papastavrou et al., 2012; Pinquart & Sorensen, 2003a, 2007), sleep disruption (Happe & Berger, 2002), mobility limitation (Fredman et al., 2008; Fredman et al., 2009), immunosuppression (Kiecolt-Glaser et al., 1991), neuroendocrine dysregulation (Brummett et al., 2008; Kring et al., 2010), general physical morbidity (Haley et al., 2010; Pinquart & Sorensen, 2007; Vitaliano et al., 2003), and even excess mortality (Christakis & Allison, 2006; Schulz & Beach, 1999).

Although the above trends lead experts to conclude that informal care is among the most pressing public policy challenges of our time (Wiener, 2003), credible data evaluating current burden among family caregivers are few and fragmentary. Most evidence on caregiving has been collected incidentally in research on specific conditions (Awad & Voruganti, 2008; Hickenbottom et al., 2002; National Alliance for Caregiving in collaboration with AARP, 2009; Prince, 2004; Torti et al., 2004), often based on small convenience samples in industrialized countries that focused on particular relationships and burdens. Few large population-based estimates of condition- or region-specific burden exist (Awad & Voruganti, 2008; Hickenbottom et al., 2002; Prince, 2004; Wimo et al., 2007), while multinational assessments are generally confined to overviews and meta-analyses of small-scale studies (Pinquart & Sorensen, 2003a, 2005, 2006, 2007, 2011; Torti et al., 2004). For instance, a recent meta-analysis of kinship differences in 168 caregiver studies over the last three decades identified no pertinent cross-national surveys (Pinquart & Sorensen, 2011), while a systematic review of 93 studies on dementia caregivers (Torti et al., 2004) identified no contemporary large-scale cross-national surveys, leading experts to conclude that culturally inclusive large-scale studies are sorely needed (Pinquart & Sorensen, 2011; Torti et al., 2004). The small amount of cross-national research undertaken in this area to date focused largely on topical issues such as service use (Lamura et al., 2008), palliative caregiving (Gysels et al., 2012), dementia caregiving (Schneider et al., 1999), and compound caregiving (Opree & Kalmijn, 2012) in small European samples. While these studies document significant objective and subjective burden among family caregivers (Gysels et al., 2012; Schneider et al., 1999), virtually no broad-based population data exist on the magnitude of the burden experienced by family caregivers across developed and developing countries.

The current report presents data on this issue based on cross-sectional community epidemiological surveys of older (ages 50+) family caregivers in 20 countries participating in the World Health Organization (WHO) World Mental Health (WMH) Survey Initiative (Kessler & Üstün, 2008). We examine both objective and subjective burdens associated with a wide range of family health problems. We focus on older caregivers based on concerns about the aging of the world population (Opree & Kalmijn, 2012), the rising share of caregiving provided by older family members (Bolin et al., 2008; Heitmueller & Inglis, 2007; Opree & Kalmijn, 2012), and the vulnerability of older caregivers to burden due to their own pre-existing health problems and functional limitations (King & Brassington, 1997; Schneider et al., 1999).

METHODS

Sample

Surveys were administered in ten countries classified by the World Bank (World Bank, 2009) as high income (Belgium, France, Germany, Israel, Italy, Netherlands, Northern Ireland, Portugal, Spain, United States), five upper-middle income (São Paulo in Brazil, Bulgaria, Lebanon, Mexico, Romania), and five low/lower-middle income (Colombia, Pondicherry in India, Iraq, Nigeria, Shenzhen in the People’s Republic of China). 13,892 respondents ages 50+ (7,265 in high income, 4,077 in upper-middle income, and 2,550 in low/lower-middle income countries) were interviewed about family burden. All but five surveys were based on national household samples. The exceptions were two surveys of urban areas (Colombia, Mexico) and three of specific Metropolitan areas (São Paulo, Brazil; Pondicherry, India; Shenzhen, People’s Republic of China). Interviews were conducted face-to-face in respondent households after obtaining informed consent. Human Subjects Committees monitored the study and approved recruitment and consent procedures in each country. Response rates ranged from 45.9% in France to 98.6% in Pondicherry and averaged 71.8%. Further details about WMH design are presented elsewhere (Harkness et al., 2008; Heeringa et al., 2008; Pennell et al., 2008).

Sub-sampling within interviews was used to reduce respondent burden. The family burden questions were consequently administered to between a random 15% (Portugal) and 100% (in five surveys) of respondents. The number of such respondents ages 50+ ranges from 233-287 respondents in six surveys (Belgium, Colombia, Lebanon, Mexico, Pondicherry, and Portugal) to highs of 1,110-1,904 in five others (Israel, Northern Ireland, Romania, São Paulo, and the USA). Because of this wide sample size variability, analyses were implemented in pooled cross-national samples disaggregated into high, upper-middle, and low/lower-middle income countries.

Measures

Burden was conceptualized according to the traditional distinction between objective and subjective (Awad & Voruganti, 2008; Idstad et al., 2011). Questioning began by asking respondents how many living first-degree relatives of four types they had (parents, siblings, spouses, children) and whether one or more of each type had each of 12 broadly-defined classes of health conditions: four physical (cancer, serious heart problems, permanent physical disability like blindness or paralysis, any other serious chronic physical illness) and eight mental (serious memory problems like senility or dementia, mental retardation, alcohol or drug problems, depression, anxiety, schizophrenia or psychosis, manic-depression, any other serious chronic mental problem). We did not assess number of each kinship type with each condition but only whether any kin of each type had each condition. The condition list was purposefully kept short based on concerns that respondents might provide superficial answers to longer lists, the intent being to provide an operational definition of “serious” by beginning with a short set of exemplar conditions to establish an implicit threshold before asking a more general question about “any other” comparably serious condition. To the extent respondents experience some family health conditions as burdensome but not “serious,” this approach underestimates conditions.

Respondents reporting at least one first-degree relative with at least one condition were then asked: Taking into consideration your time, energy, emotions, finances, and daily activities, would you say that (his/her/their) health problems affect your life a lot, some, a little, or not at all? This question was asked only once, implicitly asking respondents to consider all conditions of all first-degree relatives. Respondents who answered a lot or some were then asked two questions about subjective burden: how much their family members’ health conditions caused them to be either psychologically distressed (worried, anxious, or depressed) or embarrassed (a lot, some, a little, not at all). Additional yes/no questions then assessed whether respondents helped with practical tasks (e.g., washing, getting around, housework) and spent more time keeping company or giving emotional support to their ill relatives than they would otherwise. This strategy of asking about additional time due to relative conditions was designed to adjust for between-country differences in normal amount of interaction with relatives. Respondents were also asked whether they had any financial burden (either money spent or earnings foregone) due to their relatives’ conditions and, if so, average monthly amount of this burden. Responses were converted to median national household income equivalents to adjust for between-country differences in currency.

First-degree relatives were selected as the focus to create a well-defined network for sampling purposes. While respondents could doubtlessly have reported caregiving activities involving other kin (e.g., grandparents, grandchildren) and nonrelatives, it was less clear whether respondents would have reliable information regarding serious mental and physical health problems in these broader networks, leading to upward bias in estimates of conditional probability of burden given a condition. Although the focus on first-degree relatives avoids that bias, it leads to underestimating total caregiver burden by excluding other care recipients.

Analysis methods

Seven outcome measures were considered. Five are dichotomies: any burden, any time burden, any financial burden, a lot/some psychological distress, and a lot/some embarrassment. Two others are continuous: amount of time (in hours) and amount of financial burden (as a proportion of median within-country household income). Regression analysis was used to predict each outcome among respondents with at least one relative with a condition. Predictors included count variables (coded 0-4) for number of kinship types with each condition (i.e., 12 separate variables, each coded 0-4), three count variables (coded 0-12) for number of condition types experienced by each kinship type (parents, spouse, children, compared to the contrast category of siblings), and demographic controls (respondent age, sex, marital status, education).

Logistic regression analysis (Hosmer & Lemeshow, 2000) was used to predict dichotomous outcomes. Coefficients and standard errors were exponentiated to produce odds-ratios (OR) with 95% confidence intervals. Generalized Linear Models (GLMs) with a log link function and Poisson error variance structure (McCullagh & Nelder, 1989) were used to predict continuous outcomes. We explored numerous model specifications and selected log link/Poisson based on standard fit comparisons (Buntin & Zaslavsky, 2004). Coefficients and standard errors were exponentiated to produce incidence density ratios (IDR) with 95% confidence intervals. IDRs can be interpreted as ratios of expected scores on the continuous outcomes among respondents who differ by one point on the predictor.

Population Attributable Risk Proportions (PARPs) of the continuous outcomes were calculated to characterize proportions of time and financial burden due to particular kinship types and conditions. PARP can be interpreted as the proportion of burden that would be prevented if particular conditions were eliminated and regression coefficients represented causal effects (Northridge, 1995). The methods used to calculate PARP are described elsewhere (Levinson et al., 2010). The design-based jack-knife repeated replications method (Wolter, 1985) was used to adjust standard errors for sample weighting-clustering. Statistical significance was consistently evaluated using .05-level, two-sided design-based tests.

RESULTS

Prevalence

Serious health conditions of first-degree relative were reported by 26.9-42.5% of respondents across country income groups (Table 1). Relative physical conditions were reported by more respondents (22.0-33.5%) than were mental conditions (9.6-19.4%). The fact that we did not assess number of family members of given types with conditions partly explains the highest estimates being in high-income countries despite epidemiological evidence that prevalence of chronic conditions is inversely related to country income level (Mathers et al., 2006). More detailed analyses not presented in the table show that these cross-national differences are much less pronounced when focusing on the sub-samples of respondents reporting particular relative-condition combination, such as parent conditions among respondents with living parents. (The results of this and other preliminary analyses reported verbally in various parts of the paper but not shown in tables are available in appendix tables posted on the WMH web site at www.hcp.med.harvard.edu/wmh.) Any burden was reported by 35.7-42.5% of respondents who reported relative conditions, among whom 25.2-29.0% devoted time, 13.5-19.4% reported financial burden, 24.4-30.6% reported distress, and 6.4-21.7% reported embarrassment.

Table 1. Prevalence and reported burden of family health problems.

Total sample
 Sub-sample with family health problems
Country income level
 Country income level
High Upper-
middle		 Low/lower
-middle		 Total High Upper-
Middle		 Low/lower-
middle		 Total
% (se) % (se) % (se) % (se) Est1 (se) Est1 (se) Est1 (se) Est1 (se)
I. Prevalence of family health problems
 Parent 11.6 (0.5) 8.7 (0.5) 9.6 (0.8) 10.5 (0.3) 27.4 (10) 26.5 (14) 35.7 (2.2) 28.2 (0.7)
 Spouse 10.2 (0.5) 7.8 (0.5) 6.0 (0.7) 8.8 (0.3) 24.0 (10) 23.8 (14) 22.3 (2.0) 23.7 (0.7)
 Child 9.7 (0.5) 7.5 (0.6) 5.9 (0.7) 8.4 (0.3) 22.8 (0.9) 22.7 (16) 22.1 (2.2) 22.7 (0.7)
 Sibling 21.3 (0.6) 15.6 (0.8) 10.9 (10) 17.9 (0.4) 50.0 (0.9) 47.4 (19) 40.5 (2.5) 48.2 (0.8)
 Any physical 33.5 (0.7) 24.6 (0.9) 22.0 (14) 29.0 (0.5) 78.7 (0.7) 74.6 (16) 81.6 (16) 78.1 (0.6)
 Any mental Any physical or mental 19.4 42.5 (0.6)
(0.7)		 15.3
32.9		 (0.7)
(10)		 9.6
26.9		 (0.9)
(14)		 16.5
37.2		 (0.4)
(0.6)		 45.6
100.0		 (10)
( --- )		 46.4
100.0		 (17)
( --- )		 35.6
100.0		 (2.4)
( --- )		 44.5
100.0		 (0.8)
( --- )
 Mean number1 0.8 (0.02) 0.6 (0.02) 0.4 (0.02) 0.7 (0.01) 1.9 (0.04) 1.7 (0.04) 1.5 (0.05) 1.8 (0.02)
II. Burden of family health problems
 Any burden 17.6 (0.6) 14.0 (0.8) 9.6 (10) 15.2 (0.4) 41.2 (10) 42.5 (18) 35.7 (2.5) 40.8 (0.8)
 Any time 12.4 (0.5) 8.3 (0.6) 7.2 (0.8) 10.4 (0.3) 29.0 (0.9) 25.2 (15) 26.7 (2.3) 27.8 (0.7)
 Any financial 5.8 (0.3) 6.4 (0.6) 4.6 (0.6) 5.8 (0.3) 13.5 (0.6) 19.4 (16) 17.2 (15) 15.4 (0.6)
 Distress2 10.9 (0.4) 10.1 (0.6) 6.6 (0.8) 9.9 (0.3) 25.5 (0.8) 30.6 (13) 24.4 (2.2) 26.6 (0.7)
 Embarrassment2 2.7 (0.2) 7.1 (0.5) 2.5 (0.4) 3.9 (0.2) 6.4 (0.5) 21.7 (13) 9.2 (10) 10.4 (0.5)
(n) (7,265) (4,077) (2,550) (13,892) (3,079) (1,327) (579) (4,985)
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1

Mean number of family health problems out of 48 (12 types of problems for each of four types of family members)

2

Alot or some distress or embarrassment reported in response to questions about intensity of these feelings

Estimates of mean caregiving hours/week among those devoting any time are substantial: 18.9 hours/week across all countries and more in low/middle income (23.3-23.6) than high income (16.6) countries (Table 2). Population-level equivalents are 169.9-205.8 hours/week/100 people ages 50+ in the population (i.e., including within these 100 people those without ill first-degree family members). As noted above, these estimates are conservative due to health problems not considered “serious” and of non-first-degree relatives and non-relatives not being considered. Mean financial burden among those with any is equivalent to nearly one-fourth (23.9%) of median within-country family income among respondents who report any financial burden, with lower estimates in high (14.3%) and upper-middle (17.7%) income countries than in low/lower-middle (39.8%) income countries. Population-level equivalents, again likely to be underestimates, are 0.83-1.83% of total sample-wide median family income among all people ages 50+ in the samples (i.e., including those without ill family members).

Table 2. Individual-level and population-level time and financial burdens of family health problems.

Country income level
High Upper-
middle		 Low/lower-
Middle		 Total
Est (se) Est (se) Est (se) Est (se)
I. Time (number of hours per week)
 Individual level (mean)1 16.6 (1.3) 23.3 (2.4) 23.6 (2.8) 18.9 (1.2)
 Per 100 in the population (total)2 205.8 (3.2) 193.4 (3.6) 169.9 (6.1) 196.7 (2.8)
II. Financial (mean percent of median household income)
 Individual level3 14.3 (1.3) 17.7 (1.2) 39.8 (7.6) 23.9 (1.7)
 Per 100 in the population4 0.83 (0.02) 1.13 (0.04) 1.83 (0.06) 1.39 (0.03)
(n1)5 (859) (318) (154) (1,331)
(n2)5 (410) (184) (111) (705)
(n3)5 (7,265) (4,077) (2,550) (13,892)
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1

Individual-level reports of hours per week spent with or doing things for ill family members

2

The population-level estimate was obtained by multiplying the individual-level estimate by the proportion of respondents who reported spending any time.

3

Individual-level reports of financial burden were converted to percentages of median household income in the country. The means of these transformed scores among respondents who reported any financial burden are reported here. For example, the mean monthly financial impact of family illness (due either to out-of-pocket expenses or foregone income) across countries among respondents who reported such costs was equal to 23.9% of the median monthly household income in the country.

4

The population-level estimate of financial burden was obtained by multiplying the individual-level estimate by the proportion of respondents who reported such burdens. The resulting estimate can be interpreted as the total financial costs of family health problems as a percentage of total household income in the country.

5

n1 = sub-sample of responded who devoted any time to family health problems; n3 = sub-sample of respondents with any financial burden due to family health problems; n3 = total sample, including respondents who had no family health problems.

Socio-demographic correlates

Preliminary analyses not shown in tables found three significant socio-demographic correlates of multiple burden dimensions in total-sample multivariate models. (i) Women reported significantly more burden than men on all indicators other than financial burden, with ORs of 1.3-1.8. (ii) The previously married reported significantly less distress and less time on relative conditions than the married (0.6-0.8). (iii) Education was positively associated with having any financial burden (1.1) and with magnitude of financial burden among those having any (1.1). However, little geographic consistency was found in these patterns, with the only statistically significant patterns found in more than one country income group being higher ORs of distress (1.9-2.2) and time spent (1.8-2.3) by women than men in both high and upper-middle income countries.

Variations in burden by kinship and condition

Total-sample multivariate models show spouse and child conditions associated with highest and sibling conditions lowest burden across all outcomes other than amount of financial burden, where relationship type is not significant (Table 3). This result is likely conservative, as the most plausible bias in such reports would be for less severe conditions of siblings to be under-reported relative to those of spouses, parents, and children. Correction for such bias would yield even stronger evidence for lowest burden associated with sibling conditions. These patterns are generally consistent across high and upper-middle country income groups. For low/lower-middle income countries, though, child problems are associated with substantially higher relative effects on time, financial burden, and distress, with relative effects of spouse conditions closer to those of parent and sibling conditions.

Table 3. Differential burdens of family health problems by type of relative1.

Country income level
High Upper-middle Low/lower-middle Total
Est2 (se) Est2 (se) Est2 (se) Est2 (se)
I. Any burden (compared to siblings)
 Parent 1.4* (1.2-1.7) 1.5* (1.2-1.9) 1.7 (0.9-3.2) 1.4* (1.3-1.6)
 Spouse 2.4* (2.0-3.0) 2.1* (1.6-2.9) 2.0 (1.0-4.2) 2.2* (1.9-2.6)
 Child 1.6* (1.4-1.9) 2.1* (1.6-2.8) 4.7* (2.1-10.6) 1.8* (1.6-2.1)
    χ 2 3 111.8* 51.1* 14.5* 151.3*
II. Any time (compared to siblings)
 Parent 1.7* (1.4-2.1) 1.5* (1.1-2.0) 1.5 (0.9-2.7) 1.6* (1.4-1.9)
 Spouse 2.5* (2.1-3.0) 2.0* (1.4-2.9) 1.8 (0.8-3.7) 2.3* (2.0-2.7)
 Child 1.5* (1.2-1.8) 1.6* (1.2-2.1) 3.8* (1.8-7.7) 1.6* (1.4-1.8)
    χ 2 3 101.9* 27.5* 13.0* 115.9*
III. Any financial burden (compared to siblings)
 Parent 1.4* (1.1-1.9) 1.8* (1.3-2.6) 1.4 (0.7-2.7) 1.5* (1.2-1.9)
 Spouse 2.9* (2.3-3.6) 3.6* (2.4-5.3) 1.8 (0.8-3.7) 2.9* (2.4-3.5)
 Child 2.1* (1.6-2.7) 2.2* (1.6-3.0) 3.0* (1.5-6.1) 2.2* (1.8-2.6)
    χ 2 3 84.3* 52.2* 10.3* 136.5*
IV. Distress (compared to siblings)
 Parent 1.2* (1.0-1.5) 1.4* (1.1-1.8) 3.1* (2.0-4.9) 1.3* (1.2-1.5)
 Spouse 1.9* (1.6-2.3) 2.2* (1.6-3.2) 3.1* (1.8-5.4) 2.0* (1.7-2.4)
 Child 1.7* (1.4-2.1) 2.5* (1.8-3.4) 9.0* (3.8-21.6) 2.0* (1.7-2.4)
    χ 2 3 59.7* 46.0* 34.0* 106.7*
V. Embarrassment (compared to siblings)
 Parent 1.5* (1.1-2.0) 1.4* (1.0-2.0) 2.5* (1.5-4.2) 1.5* (1.2-1.8)
 Spouse 2.3* (1.7-3.0) 2.2* (1.5-3.2) 4.5* (1.7-12.0) 2.3* (1.9-2.9)
 Child 2.3* (1.7-3.0) 2.3* (1.7-3.3) 2.8* (1.3-5.9) 2.2* (1.8-2.7)
    χ 2 3 49.1* 35.3* 15.8* 92.5*
VI. Amount of time (among those devoting any time)
 Parent 1.0 (0.8-1.3) 1.2 (0.9-1.6) 2.5* (1.7-3.6) 1.2 (1.0-1.4)
 Spouse 1.3* (1.0-1.6) 1.3 (0.9-1.9) 1.6* (1.0-2.7) 1.3* (1.1-1.6)
 Child 1.2* (1.0-1.6) 1.2 (0.9-1.5) 1.6 (1.0-2.6) 1.3* (1.1-1.5)
  F3 3.8 (.010) 0.8 (.475) 8.2 (.000) 3.5 (016)
VII. Amount of financial burden (among those with any)
 Parent 1.0 (0.8-1.4) 0.8 (0.6-1.2) 0.5 (0.2-1.4) 0.9 (0.7-1.3)
 Spouse 1.0 (0.8-1.3) 0.9 (0.7-1.2) 1.4 (0.4-4.3) 1.0 (0.8-1.2)
 Child 1.0 (0.7-1.3) 1.0 (0.7-1.2) 3.0* (1.2-7.8) 1.2 (0.9-1.5)
  F3 0.1 (.981) 0.4 (.784) 5.9 (.001) 1.3 (.260)
(n1)2 (3,079) (1,327) (579) (4,985)
(n2)2 (859) (318) (154) (1,331)
(n3)2 (410) (184) (111) (705)
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*

Significant at the .05 level, two-sided test

1

Based on multivariate models (logistic for dichotomous outcomes; GLM for continuous outcomes with log link function and Poisson error distribution) with predictors that included a separate count variable (coded 0-4) for the number of types of relatives with each of the 12 health problems, a separate count variable for (coded 0-12) for the number of types of health problems experienced by each of 3 types of relatives (parents, spouse, children, compared to the implicit contrast category of siblings), and demographic controls (respondent age, sex, marital status, and level of educational attainment). All equations were estimated in a pooled dataset across either the entire set of 20 countries or in the high, upper-middle, and low/lower-middle income countries. Romania was removed from the models for financial burden, as this aspect of burden was not assessed in Romania.

Coefficient estimates (Est) are odds-ratios for the first five outcomes (I-V), all of which are dichotomies, and Incidence Density Ratios for the last two outcomes (VI-VII), which are continuous.

2

n1 = total sub-ample of respondents with family health problems; n2 = sub-sample of responded who devoted any time to family health problems; n3 = sub-sample of respondents with any financial burden due to family health problems;

The same total-sample multivariate models find significant variation in burden by type of condition for all indicators other than amount of financial burden (Table 4). However, little consistency exists in the most burdensome conditions across outcomes. Results not reported in the table also failed to detect geographic consistencies in differential burden across conditions for individual outcomes. The most consistent pattern is for mental retardation to be associated with elevated odds of both devoting any time (1.8 in the total sample, 1.6-2.1 across country groups) and having any financial burden (1.8; 1.4-3.3). Physical disability is the only other family condition consistently (across all country groups) associated with elevated odds relative to other conditions of devoting any time (1.4; 1.3-2.1), while memory problems are the only other condition associated with elevated odds relative to other conditions of devoting time in high and upper-middle income countries (1.5; 1.5-1.6). In interpreting this result, though, it must be recalled that our ascertainment method is biased against detecting between-disorder variation in burden because we assessed only conditions rated serious. While significant differential burden presumably exists due to between-condition variation in severity, these differences are beyond the scope of the present study.

Table 4. Differential burdens of family health problems by type of problem in the total sample (n = 4,985)1.

Any
burden		 Any time Any financial
burden		 Distress Embarrassment Amount
Time		 Amount financial
I. Physical disorder OR (95% CI) OR (95% CI) OR (95% CI) OR (95% CI) OR (95% CI) IDR (95% CI) IDR (95% CI)
 Cancer 1.0 (0.8-1.3) 1.0 (0.8-1.2) 0.7 (0.5-1.0) 1.1 (0.9-1.4) 1.1 (0.8-1.5) 1.0 (0.8-1.5) 0.7 (0.4-1.2)
 Heart problems 1.0 (0.9-1.2) 0.9 (0.7-1.0) 0.8 (0.7-1.0) 1.2 (1.0-1.4) 0.6* (0.5-0.8) 0.9 (0.7-1.2) 0.8 (0.5-1.2)
 Physical disability 1.2 (1.0-1.5) 1.4* (1.1-1.8) 1.0 (0.8-1.4) 1.2 (0.9-1.4) 0.9 (0.6-1.3) 1.2 (1.0-1.6) 0.8 (0.4-1.4)
 Other serious chronic illness 1.2 (1.0-1.4) 1.2 (1.0-1.5) 1.0 (0.8-1.3) 1.2* (1.0-1.4) 0.8 (0.6-1.1) 0.9 (0.7-1.2) 0.8 (0.4-1.5)
    χ 2 4 8.1 21.3* 7.9 6.6 20.3* 1.6 (.175) 0.7 (.569)
II. Mental disorder
 Serious memory problem 1.4* (1.1-1.8) 1.5* (1.1-1.9) 0.9 (0.6-1.3) 1.2 (0.9-1.5) 1.2 (0.8-1.6) 0.9 (0.7-1.2) 1.1 (0.6-2.0)
 Mental retardation 1.4* (1.0-2.0) 1.8* (1.2-2.6) 1.8* (1.2-2.8) 1.4 (1.0-2.0) 1.0 (0.7-1.6) 1.2 (0.9-1.6) 1.0 (0.6-1.6)
 Alcohol/drug problem 1.1 (0.9-1.4) 0.8 (0.6-1.0) 0.8 (0.6-1.2) 1.1 (0.9-1.4) 1.6* (1.2-2.2) 0.6* (0.5-0.9) 0.8 (0.4-1.6)
 Depression 1.0 (0.7-1.3) 0.9 (0.7-1.2) 0.7 (0.5-1.1) 0.9 (0.7-1.2) 0.8 (0.5-1.1) 1.0 (0.7-1.4) 0.5* (0.3-0.9)
 Anxiety 1.1 (0.8-1.4) 0.9 (0.7-1.2) 0.6* (0.4-0.9) 1.2 (0.9-1.5) 0.7 (0.5-1.1) 0.7* (0.5-1.0) 1.3 (0.8-2.1)
 Psychosis 0.9 (0.6-1.4) 1.1 (0.7-1.7) 0.8 (0.4-1.6) 1.0 (0.6-1.6) 1.0 (0.4-2.0) 1.1 (0.7-1.8) 4.2* (1.3-12.8)
 Manic-depression 0.6* (0.4-0.9) 0.6 (0.4-1.0) 0.8 (0.4-1.6) 0.5* (0.3-0.9) 0.6 (0.2-1.6) 0.8 (0.5-1.2) 1.0 (0.5-1.8)
 Other serious chronic illness 1.1 (0.7-1.6) 1.3 (0.9-1.9) 1.6* (1.0-2.5) 0.9 (0.6-1.4) 0.9 (0.5-1.7) 1.8* (1.2-2.6) 0.3 (0.1-1.1)
  χ28/F32 23.3* 45.4* 31.0* 18.7* 23.9* 3.1* (.002) 1.7 (.088)
  χ212/F122 26.7* 57.3* 36.9* 26.1* 54.1* 2.4* (.005) 1.3 (.188)
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*

Significant at the 0.05 level

1

Based on multivariate models (logistic for dichotomous outcomes; GLM for continuous outcomes with log link function and Poisson error distribution) with predictors that included a separate count variable (coded 0-4) for the number of types of relatives with each of the 12 health problems, a separate count variable for (coded 0-12) for the number of types of health problems experienced by each of 3 types of relatives (parents, spouse, children, compared to the implicit contrast category of siblings), and demographic controls (respondent age, sex, marital status, and level of educational attainment). All equations were estimated in a pooled dataset across the entire set of 20 countries. Romania was removed from the models for financial burden, as this aspect of burden was not assessed in Romania.

2

χ2 tests were used for the first five (dichotomous) outcomes and F tests for the last two (continuous) outcomes

In a similar way, our failure to find strong between-condition variation in psychological distress does not mean that serious conditions are not distressing (as indicated by 24.4-30.6% of respondents reporting distress associated with serious relative health conditions) but rather that the magnitude of this distress does not differ significantly across conditions. The bias against detecting such differences due to our truncation of the severity distribution makes it all the more striking that two particular conditions are consistently associated with differential embarrassment: relative heart problems with comparatively low embarrassment (0.6; 0.3-0.6); and relative alcohol/drug problems (in high/upper-middle income countries) with comparatively high embarrassment (1.6; 1.7-2.0). Relative alcohol/drug problems (0.6; 0.1-0.9) and anxiety (0.7; 0.2-0.8) are the only two conditions associated with low differential time devoted to caregiving, while relative depression (0.5; 0.2-0.8) and psychosis (4.2; 3.0-4.1 in high/upper-middle income countries) are the only conditions associated with differential financial burden in more than one country income group.

Interactions between kinship and condition

Analyses not reported in the tables found that interactions between kinship and condition types are globally significant in predicting both amount of time and amount of financial burden among those with any in the total sample. However, inspection of detailed data patterns found few consistencies across country income groups. The latter were confined to models for time. In particular, six kinship-condition combinations were found to have significant differential effects on time across two or more country income groups: parent depression (1.7; 2.6-3.3 in upper-middle and low/lower-middle income countries), spouse physical disability (1.8; 2.1-2.8), spouse depression (2.6; 2.0-4.8 in high/upper-middle income countries), spouse other mental illness (2.6; 1.8-3.7), child mental retardation (1.4; 1.5-3.6), and child other mental illness (3.3; 2.6-5.0 in high/upper-middle income countries). As with the above results regarding differential burden by kinship and condition, these interactions are likely to be conservative.

Population attributable risk proportions (PARPs)

Five significant patterns are noteworthy in the PARP estimates (Table 5). First, sibling health problems are generally associated with insignificant PARPS, meaning that little time or financial resources are devoted in the aggregate to ill siblings. Second, PARPS are consistently highest for spouses and generally lower for parents than children in high/upper-middle income countries, but highest for children in low/lower-middle income countries. These differences reflect the joint influences of two factors: (i) roughly equivalent prevalence of reported health conditions across kinship types in high/upper-middle income countries versus much higher prevalence of parent than spouse/child problems in low/lower-middle income countries (see Table 1), and (ii) highest individual-level associations for spouses in high/upper-middle income countries and for children in low/lower-middle income countries, with generally lower associations for parents than either spouses or children in all country income groups (see Table 3).

Table 5. Significant population attributable risk proportions of time and financial burdens due to family health problems.

Country income level
High Upper-middle Low/lower-
middle		 Total
Time Financial Time Financial Time Financial Time Financial
I. Type of relative
 Parent 18.6 16.2 14.9 - 19.4 - 18.8 -
 Spouse 31.3 31.0 26.6 38.0 - - 27.3 20.9
 Child 11.8 19.9 20.4 22.3 40.1 33.8 19.0 36.5
 Sibling - - - - - 15.2 - -
II. Type of health problem
 Physical 39.0 22.0 41.5 26.1 32.3 16.4 39.7 25.6
 Mental 27.3 35.3 32.4 18.8 21.0 26.5 29.4 31.3
(n) (3,079) (1,327) (579) (4,985)
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Third, despite between-kinship differences, conditions of parents, spouses, and children all account for meaningful components of burden in all three country income groups. Fourth, the sums of PARP estimates across kinship types are consistently less than 100. This reflects the fact that the effects of compound caregiving are not captured in the condition-specific and kinship-specific PARP estimates. Fifth, while the PARPS for physical conditions are almost always higher than those for mental conditions, with the exception of financial burden in high and low/lower-middle income countries, comparative importance of mental conditions is much higher than expected from relative prevalence (see Table 1) due to generally higher individual-level associations of mental (especially mental retardation and memory problems) conditions than physical conditions with most burden dimensions (see Table 3).

DISCUSSION

The above results are broadly consistent with more focused studies of specific conditions such as dementia (Prince, 2004; Torti et al., 2004; Wimo et al., 2007), stroke (Hickenbottom et al., 2002), and schizophrenia (Awad & Voruganti, 2008) in documenting that many older caregivers experience significant burdens associated with serious family health conditions. Our estimate of 16.6-23.6 mean caregiving hours/week among those with any is broadly consistent with a pooled estimate of 26.8 hours/week obtained in a meta-analysis that averaging estimates across many smaller studies (Pinquart & Sorensen, 2003b), but our large-scale representative samples and wide range of conditions allowed us to go beyond this previous type of aggregation by producing true population-level estimates. The magnitude of these estimates is staggering. The 205.8 hours/week/100 people ages 50+ devoted to family caregiving in high income countries translates in the US (with roughly 60 million people ages 50+) into approximately 3.2 million full-time-equivalent older adults working as informal family caregivers. The 0.83% average household income among people ages 50+ in high income countries devoted to family caregiving translates in the US alone into $5.3 billion USD/year, equivalent to the average annual salaries of over 130,000 US workers. The individual-level financial burdens in low/lower-income countries are especially striking, with 39.8% of median household income devoted to family caregiving among the 4.6% of respondents with this burden (compared to 14.3-17.7% of household income among the 5.8-6.4% of respondents with this burden in high/upper-middle income countries).

Caregivers in the low/lower-middle income group are especially burdened. The higher relative burden for children and siblings in low/lower-middle income than higher income countries is consistent with previous evidence of greater “familism” in developing countries; i.e., with the fact that the relationships of parents with adult children and of adult siblings with each other are not nearly as attenuated in developing than developed countries (Losada et al., 2006; Torti et al., 2004; Youn et al., 1999). The much higher magnitude of financial burden in low/lower-middle income than richer countries presumably reflects the well-documented fact that government resources and supports for family caregivers are relatively low in these countries (Beaglehole et al., 2008; Maulik & Darmstadt, 2007; Prince et al., 2007), although strong social norms encouraging intra-familial financial support could also play a role (Izuhara, 2004; Lin & Yi, 2011; Youn et al., 1999). It is important to recall that these cost estimates are lower bounds because they exclude costs associated with self-defined non-serious conditions and with care recipients who are not first-degree relatives. It is more difficult to quantify psychological burdens, but finding as we did that 6.6-10.1% of the population ages 50+ has meaningful distress and 2.5-7.1% meaningful embarrassment related to serious first-degree family health problems shows clearly that psychological burdens are nontrivial.

Our results on variations in burden are also consistent with most previous studies and meta-analyses in finding higher caregiving burdens for women than men (Bedard et al., 2000; Harwood et al., 2000; Navaie-Waliser et al., 2002; Pinquart & Sorensen, 2006; Torti et al., 2004; Yee & Schulz, 2000). Although our finding that greater burden was associated with health conditions of spouses and children than parents-siblings is also consistent with previous empirical research and large recent meta-analyses (Chumbler et al., 2003; Pinquart & Sorensen, 2011), our lack of data on co-residence prevented any assessment of the extent to which this variation is attributable to differences in residential propinquity (Siegler et al., 2010). Nor did we consider complex kinship profiles (e.g., variation in burden by number of siblings or birth order in caring for elderly parents) or complex caregiving profiles (i.e., caring for multiple relatives with multiple conditions). Our evidence that higher burden is associated more with mental than physical conditions also confirms previous research (Hastrup et al., 2011; Pinquart & Sorensen, 2011), although our exclusive focus on self-defined serious conditions prevented closer study of between-condition differences and almost certainly led to an underestimate of true differences in burden across different types of conditions.

The above results must be interpreted in light of possible sample biases (i.e., that older adults caring for severely ill family might have been less likely than others to participate in the survey, or conversely that we had a “healthy caregiver effects” whereby those who participated were more robust than those who refused), limitations in focus (i.e., exclusion of non-serious conditions and conditions of care recipients who were not first-degree relatives) and measurement (i.e., short checklists rather than more comprehensive and objective assessments of family health conditions, short assessments of caregiver burden, failure to obtain information on the number of each kinship type with health conditions), and the fact that the small sample sizes in individual countries required us to carry out analyses at a high level of geographic aggregation. Due to our broad focus we failed to consider some important variables previously addressed in more focused studies, such as independent observer-based and perceived health effects on the caregivers themselves (Pinquart & Sorensen, 2003b, 2007; Torti et al., 2004; Vitaliano et al., 2003), caregiver “load” (Gallo et al., 2011; Opree & Kalmijn, 2012), general quality of life (Ekwall et al., 2007), and opportunity costs (Carmichael & Charles, 2003; Heitmueller & Inglis, 2007). Also beyond the scope of the present study were possible burden offsets such as premorbid relationship, caregiving rewards (e.g., enhanced closeness with care recipients or sense of mattering), coping styles and traits (e.g., resilience, self-efficacy, locus of control), and service availability (Ekwall et al., 2007; Lamura et al., 2008; Lockenhoff et al., 2011; Morse et al., 2012; Nomura et al., 2005; Poulin et al., 2010; Schneider et al., 1999; Winter et al., 2010). Future epidemiological research would benefit from tandem assessments of caregiver and care recipient health status as well as multi-level studies of the effects of national social policies and cultural norms-expectations on caregiver burdens.

Notwithstanding these limitations and despite some evidence of differential burden by gender, kinship type, and condition, the consistency of the basic data patterns reported here is striking in arguing for the existence of substantial caregiver burden comparable to that suggested in cross-national comparisons of smaller, more focused, and less representative samples (Schneider et al., 1999; Torti et al., 2004). This uniformity indicates that important basic aspects of caregiving burden extend across a range of serious mental and physical conditions, health delivery systems, and cultures. When seen against the backdrop of global population trends, this consistency adds compelling evidence to concerns that the shrinking and aging family caregiving system is becoming increasingly strained as it responds to rising demand. Policy makers need to recognize the importance of maintaining the well-being and functional capacities of this aging cadre of family caregivers in light of the vital role they play in the worldwide healthcare and human services delivery systems. While formal interventions that help reduce the burden of family caregivers exist, most address narrow needs of condition-specific caregivers in industrialized countries, and few of these have been rigorously evaluated (Sorensen et al., 2002; Stoltz et al., 2004; Torti et al., 2004). The data presented here suggest that more broad-based programs are needed not only in industrialized countries but perhaps even more so in developing countries to reduce both the objective and subjective burdens of family caregivers.

Acknowledgments

FINANCIAL SUPPORT

The World Health Organization World Mental Health (WMH) Survey Initiative is supported by the National Institute of Mental Health (NIMH; R01 MH070884), the John D. and Catherine T. MacArthur Foundation, the Pfizer Foundation, the US Public Health Service (R13-MH066849, R01-MH069864, and R01 DA016558), the Fogarty International Center (FIRCA R03-TW006481), the Pan American Health Organization, Eli Lilly and Company, Ortho-McNeil Pharmaceutical, Inc., GlaxoSmithKline, and Bristol-Myers Squibb. We thank the staff of the WMH Data Collection and Data Analysis Coordination Centres for assistance with instrumentation, fieldwork, and consultation on data analysis.

Each WMH country obtained funding for its own survey. The São Paulo Megacity Mental Health Survey is supported by the State of São Paulo Research Foundation (FAPESP) Thematic Project Grant 03/00204-3.The Bulgarian Epidemiological Study of common mental disorders EPIBUL is supported by the Ministry of Health and the National Center for Public Health Protection. The Shenzhen Mental Health Survey is supported by the Shenzhen Bureau of Health and the Shenzhen Bureau of Science, Technology, and Information. The Colombian National Study of Mental Health (NSMH) is supported by the Ministry of Social Protection. The ESEMeD project is funded by the European Commission (Contracts QLG5-1999-01042; SANCO 2004123), the Piedmont Region (Italy), Fondo de Investigación Sanitaria, Instituto de Salud Carlos III, Spain (FIS 00/0028), Ministerio de Ciencia y Tecnología, Spain (SAF 2000-158-CE), Departament de Salut, Generalitat de Catalunya, Spain, Instituto de Salud Carlos III (CIBER CB06/02/0046, RETICS RD06/0011 REM-TAP), and other local agencies and by an unrestricted educational grant from GlaxoSmithKline. The Epidemiological Study on Mental Disorders in India was funded jointly by Government of India and WHO. Implementation of the Iraq Mental Health Survey (IMHS) and data entry were carried out by the staff of the Iraqi MOH and MOP with direct support from the Iraqi IMHS team with funding from both the Japanese and European Funds through United Nations Development Group Iraq Trust Fund (UNDG ITF). The Israel National Health Survey is funded by the Ministry of Health with support from the Israel National Institute for Health Policy and Health Services Research and the National Insurance Institute of Israel. The Lebanese National Mental Health Survey (LEBANON) is supported by the Lebanese Ministry of Public Health, the WHO (Lebanon), National Institute of Health / Fogarty International Center (R03 TW006481-01), anonymous private donations to IDRAAC, Lebanon, and unrestricted grants from Astra Zeneca, Eli Lilly, GlaxoSmithKline, Hikma Pharm, Janssen Cilag, MSD, Novartis, Pfizer, Sanofi Aventis, and Servier. The Mexican National Comorbidity Survey (MNCS) is supported by The National Institute of Psychiatry Ramon de la Fuente (INPRFMDIES 4280) and by the National Council on Science and Technology (CONACyT-G30544-H), with supplemental support from the PanAmerican Health Organization (PAHO). The Nigerian Survey of Mental Health and Wellbeing (NSMHW) is supported by the WHO (Geneva), the WHO (Nigeria), and the Federal Ministry of Health, Abuja, Nigeria. The Northern Ireland Study of Mental Health was funded by the Health & Social Care Research & Development Division of the Public Health Agency. The Portuguese Mental Health Study was carried out by the Department of Mental Health, Faculty of Medical Sciences, NOVA University of Lisbon, with collaboration of the Portuguese Catholic University, and was funded by Champalimaud Foundation, Gulbenkian Foundation, Foundation for Science and Technology (FCT) and Ministry of Health. The Romania WMH study projects “Policies in Mental Health Area” and “National Study regarding Mental Health and Services Use” were carried out by National School of Public Health & Health Services Management (former National Institute for Research & Development in Health, present National School of Public Health Management & Professional Development, Bucharest), with technical support of Metro Media Transilvania, the National Institute of Statistics – National Centre for Training in Statistics, SC. Cheyenne Services SRL, Statistics Netherlands and were funded by Ministry of Public Health (former Ministry of Health) with supplemental support of Eli Lilly Romania SRL. The US National Comorbidity Survey Replication (NCS-R) is supported by the National Institute of Mental Health (NIMH; U01-MH60220) with supplemental support from the National Institute of Drug Abuse (NIDA), the Substance Abuse and Mental Health Services Administration (SAMHSA), the Robert Wood Johnson Foundation (RWJF; Grant 044708), and the John W. Alden Trust. A complete list of all within-country and cross-national WMH publications can be found at http://www.hcp.med.harvard.edu/wmh/.

The views and opinions expressed in this report are those of the authors and should not be construed to represent the views or policies of any of the sponsoring organizations, agencies, the World Health Organization, or the U.S. Government. A complete list of NCS publications and the full text of all NCS-R instruments can be found at http://www.hcp.med.harvard.edu/ncs.

Footnotes

Declaration of Interest: Dr. Haro has been a consultant for AstraZeneca, Eli Lilly and Co., and Lunbeck. Dr. Lépine has given lectures for Servier, Pfizer-Wyeth, Sanofi Aventis, and Pierre Fabre. Dr. Kessler has been a consultant for GlaxoSmithKline Inc., Kaiser Permanente, Pfizer Inc., Sanofi-Aventis, Shire Pharmaceuticals, and Wyeth-Ayerst; has served on advisory boards for Eli Lilly & Company and Wyeth-Ayerst; and has had research support for his epidemiological studies from Bristol-Myers Squibb, Eli Lilly & Company, GlaxoSmithKline, Johnson & Johnson Pharmaceuticals, Ortho-McNeil Pharmaceuticals Inc., Pfizer Inc., and Sanofi-Aventis. The remaining authors report nothing to declare.

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