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Age and gender differences in the influence of social support on mental health: a longitudinal fixed-effects analysis using 13 annual waves of the HILDA cohort
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Original Research
Age and gender differences in the influence of social support on mental health: a longitudinal fixed-effects analysis using 13 annual waves of the HILDA cohort A. Milner a,b,*,c, L. Krnjacki b, A.D. LaMontagne a,b a Work, Health and Wellbeing Unit, Centre for Population Health Research, School of Health & Social Development, Deakin University, Melbourne, Australia b Centre for Health Equity, Melbourne School of Population and Global Health, The University of Melbourne, Victoria 3010, Australia
article info
abstract
Article history:
Objectives: Perceived social support is associated with better mental health. There has been
Received 11 March 2016
limited attention to how these relationships are modified by age and gender. We assessed
Received in revised form
this topic using 13 years of cohort data.
23 May 2016
Study design: Prospective cohort study.
Accepted 28 June 2016
Methods: The outcome was the Mental Health Inventory-5 (MHI-5), a reliable and valid
Available online xxx
screening instrument for mood disorders. The main exposure was a social support scale composed of 10 items. We used longitudinal fixed-effects regression modelling to investigate
Keywords:
within-person changes in mental health. Analytic models controlled for within-person sour-
Social support
ces of bias. We controlled for time-related factors by including them into regression modelling.
Mental health
Results: The provision of higher levels of social support was associated with greater im-
MHI-5
provements in mental health for people aged under 30 years than for older age groups. The
Gender
mental health of females appeared to benefit slightly more from higher levels of social
Age
support than males. Improvements in the MHI-5 were on a scale that could be considered
Longitudinal analysis
clinically significant. Conclusions: The benefits of social support for young people may be connected to agerelated transitions in self-identity and peer friendship networks. Results for females may reflect their tendency to place greater emphasis on social networks than males. © 2016 The Royal Society for Public Health. Published by Elsevier Ltd. All rights reserved.
Abbreviations: MHI-5, Mental Health Inventory-5. * Corresponding author. Work, Health & Wellbeing, Population Health Strategic Research Centre, Building BC3.213, School of Health & Social Development, Deakin University, Burwood, VIC 3125 Australia. Fax: þ61 03 9244 6624. E-mail address: [email protected] (A. Milner). c www.deakin.edu.au. http://dx.doi.org/10.1016/j.puhe.2016.06.029 0033-3506/© 2016 The Royal Society for Public Health. Published by Elsevier Ltd. All rights reserved. Please cite this article in press as: Milner A, et al., Age and gender differences in the influence of social support on mental health: a longitudinal fixed-effects analysis using 13 annual waves of the HILDA cohort, Public Health (2016), http://dx.doi.org/10.1016/ j.puhe.2016.06.029
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Introduction Social support (defined as the social resources that persons perceive to be available or that are actually provided to them by non-professionals1) is provided through people's connections or contacts with others.2 The degree to which an individual may rely on these social resources differs depending on a variety of factors, including age3,4 and gender.5e7 Past research suggests that women are more likely to give and receive emotional support than males.6 As women have a greater number of female friends than men, they may have a greater range of people to call on for emotional support should they need it.6 There is also some evidence that reliance on different social groups changes as people grow older; e.g. adolescents appear to draw more on peer networks as they age.3 In contrast, older adults tend to have smaller social networks, are less close to network members, and have fewer nonprimary group ties than younger persons.8 There is substantial evidence that those with greater social support have better mental health than those with less social support.9e12 Moreover, a number of studies suggest that loneliness (conceptualized as a converse of social support, i.e. the gap between one's desired and actual ties to others2) is associated with depressive symptoms and depression.13e15 However, there has been limited research on whether there is variation in the relationship between social support and mental health by age or gender. Given the research cited previously, it is highly plausible that such differences exist. We investigated this possibility using a general population cohort and hypothesized that younger people and women may benefit more from social support than older people and males.
Methods Data source The Household, Income and Labour Dynamics in Australia (HILDA) survey is a longitudinal, nationally representative study of Australian households established in 2001. It collects detailed information annually from over 13,000 individuals within over 7000 households.16 The response rate to wave 1 was 66%.16 The survey covers a range of dimensions including social, demographic, health and economic conditions using a combination of face-to-face interviews with trained interviewers and a self-completion questionnaire. Although data are collected on each member of participating households, interviews are only conducted with those older than 15 years of age. The initial wave of the survey began with a large national probability sample of Australian households occupying private dwellings.16 Interviews were sought in later waves with all persons in sample households who turned 15 years of age. Additional persons have been added to the sample as a result of changes in household composition. For example, if a household member left his or her original household (e.g. children left home, or a couple separated), he/she formed an entirely new household including all persons living with the original sample member. Inclusion of these new households is the main way in which the HILDA survey maintains sample
representativeness. A top-up sample of 2000 people was added to the cohort in 2011 to allow better representation of the Australian population using the same methodology as the original sample (i.e. a three-stage area-based design).17 The response rates for the HILDA survey are above 90% for respondents who have continued in the survey and above 70% for new respondents being invited into the study.16 The main variables examined in this study were available in all annual waves of HILDA (2001e2013).
Analytic considerations and approach Research on social support has also been subject to the concern that perceived-support measures may be confounded with either personality factors or depression,18,19 thus there may be the possibility that people with poorer mental health attract less social support. However, past prospective studies have evidenced functional differences between social support, loneliness and mental health problems.18 For example, social support and loneliness predict subsequent depression longitudinally, even after controlling for initial depression levels,14,15,20e23 which provides some empirical support for this causal pathway. Further, a number of other studies have found that common mental illnesses, such as depressive symptoms, represent clearly different statistical constructs from loneliness and social support.14,24,25 Regardless, this emphasizes the importance of controlling for person-related characteristics that could influence the relationship between social support and mental health. In this study, we will use longitudinal linear fixed-effects regression models to estimate an association between social support and mental health score within individuals. We will use fixed-effects regression models to assess mean differences in mental health associated with medium or high social support compared with that individual's mean mental health score when they reported low social support. These models provide an indication of within-person effects, where each individual acts as their own control and estimates are not confounded by time-invariant personal, demographic and environmental factors.26 Fixed-effects models are particularly useful where timeinvariant confounding is likely to create bias in causal estimates. For example, mental health may be affected by withinperson factors such as personality (e.g. negative affect). We controlled for time-varying factors by including a number of relevant confounders into the fixed-effects models. Including these in fixed-effects models accounted for individual change in these variables that might influence the relationship between social support and mental health. We tested the hypothesis that the association between social support and mental health differed depending on the age and gender of a person using an interaction term in fixed-effects models, and examined this using the likelihood ratio test and inspection of significance values of interaction terms in the model. Where interactions were significant, models were then stratified by age and gender.
Outcome variable Mental health was assessed using the five-item Mental Health Inventory (MHI-5), a subscale from the Short Form-36 (SF-36) general health measure. The MHI-5 assesses symptoms of
Please cite this article in press as: Milner A, et al., Age and gender differences in the influence of social support on mental health: a longitudinal fixed-effects analysis using 13 annual waves of the HILDA cohort, Public Health (2016), http://dx.doi.org/10.1016/ j.puhe.2016.06.029
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depression and anxiety (nervousness, depressed affect) and positive aspects of mental health (feeling calm, happy) in the past 4 weeks. The MHI-5 has reasonable validity and is an effective screening instrument for mood disorders or severe depressive symptomatology in the general population27e29 and has been validated as a measure for depression using clinical interviews as the gold standard.27,30,31 The current analyses uses the continuous MHI-5 score (scales 1e100), with higher scores representing better mental health. Although there is no universally accepted translation of MHI-5 score difference to clinical meaningfulness, a difference of three points on the norm based scale (T-score) has been suggested to reflect a minimally important difference,32 and a difference of four or more on the unstandardized scale has been characterized as indicating a moderate clinically significant effect.33
Exposure variable The social support measure was designed to assess an individual's perception of the social support they receive. Perceived social support has been recognized as having a more important effect on mental health34 and mortality35 than received social support. The HILDA social support measure has been used in previous studies.36,37 This measure primarily taps into emotional support (items 3, 4, 5, 7, 8) and practical support (items 1, 6, 9). It also measures loneliness (item 2), which we would conceptualize as the converse of social support. The 10item scale included the following items: 1. I have no one to lean on in times of trouble (reverse coded); 2. I often feel very lonely (reverse coded); 3. I enjoy the time I spend with the people that are important to me; 4. I seem to have a lot of friends; 5. People don't come and visit as much as I would like (reverse coded); 6. I often need help from other people but can't get it (reverse coded); 7. I don't have anyone that I can confide in (reverse coded); 8. There is someone who can always cheer me up when I am down; 9. When I need someone to help me out, I can usually find someone; and 10. When something is on my mind, just talking with the people I know can make me feel better. Items are rated on a Likert scale ranging from strongly disagree (1) to strongly agree (7) and the Cronbach's alpha, for the current data, was 0.84 across all waves. The social support scale was created by averaging the 10 items in the scale, with lower scores representing lower social support and higher scores representing higher social support (the items we reverse coded previously). In its original form, the scale was strongly positively skewed. Hence, we tested the analytic relationships of interest with social support coded in three levels (low [1e4.69], medium [4.70e5.59], high [5.6e7]) based on the observed distribution of the variable across all waves of HILDA. As a sensitivity test, we also tested social support as a linear variable.
3
Other covariates We included gender and age group (under 30, 31e44, 45e60, 61þ years) in the main models to test for interaction effects. The models also included a number of likely time-varying potential confounders. These included household structure (couple or lone adult residing with dependants, couple without dependants, lone person without dependants, and a group or multiple person household) and marital status (married, separated, divorced, widowed, de facto, single), recognizing that the perceptions of social support may differ according to whether someone is in a relationship or not (i.e. differences between received and perceived social support).38 We also controlled for employment status (permanent, casual or labour hire, fixed term, not in the labour force, unemployed), recognizing the people who are employed may have access to a wider range of sources for social support than those who are not employed. Other time-varying potential confounders controlled for included education (postgraduate, bachelor degree, diploma or certificate, year 12, not completed year 12) and long term health condition (yes or no).
Analytic sample and missing data Fig. 1 describes how the analytic sample was obtained. About 7% of people in HILDA had missing information on the MHI-5 or social support and were thus excluded. From here, approximately 5% of people were excluded due to missing information on other covariates. The final analytic sample was comprised 24,799 people, 88.9% of the original number of people included in the cohort. Those not included in the analysis were more likely to be single, and to have attained less education than those included in the analytic sample. However, these differences were non-significant and only represented a small proportion of persons.
Results Characteristics of the analytic sample The characteristics of the analytic sample can be seen in Table 1. The minimum number of observations for respondents included in the study was 2 and the maximum was 12; on average respondents contributed 5.8 waves of data.
Overall description of mental health and social support in the analytic sample Across the whole sample, the mean (SD) MHI-5 scores for men and women was 75.5 (16.6) and 73.2 (17.4) respectively (Table 2). In terms of age differences, the MHI-5 score of people over 61 years of age (mean 76.8, standard deviation 16.8) was about 4 points higher than that of the youngest age group (mean 72.9, standard deviation 16.9). As can be seen, females and youngest age groups more often reported the highest category of social support compared to males and the youngest age group (Table 2). Within-person regression results can be seen in Table 3 which shows the adjusted main effects model (1), the
Please cite this article in press as: Milner A, et al., Age and gender differences in the influence of social support on mental health: a longitudinal fixed-effects analysis using 13 annual waves of the HILDA cohort, Public Health (2016), http://dx.doi.org/10.1016/ j.puhe.2016.06.029
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Table 1 e Sample characteristics (n ¼ 24,799; obs 144,848) on first and last contributed waves to the analysis. Exposure and other covariates
Fig. 1 e Sample selection.
adjusted age interaction model (2), and the adjusted gender interaction model (3). There was a strong direct relationship between social support and mental health (model 1). Compared to when a person had lower support, an increase to ‘medium’ social support was associated with approximately a 5.2-point improvement in mental health (95% CI 5.0e5.4). There was over a 9-point increase in mental health when a person changed from being in the low social support category to the high social support category (95% CI 9.10e9.5). These results were confirmed when the social support was measured as a linear variable (5.13, 95% CI 5.04e5.23, P < 0.001). Model 2 indicates that there was a significant interaction between age and social support. In essence, this shows that the effect of social support on mental health decreases with age. Model 3 shows the interaction between social support and gender and suggests that the effect of social support on mental health is greater for females than males. Likelihood ratio tests were highly significant (P < 0.001) when comparing both model 2 and model 3 to model 1. Supplementary Table 1 shows results of the relationship between social support and mental health by age, for male and females (with 95% confidence intervals). Younger males had the lowest levels of mental health while those aged 45e60 years had the highest levels of mental health. It appears that
First observed wave (%)
Last observed wave (%)
73.6
73.1
26.2 27.1 46.7
26.8 26.3 46.9
48.0 52.0
48.0 52.0
41.3 23.9 20.5 14.3
32.6 21.9 23.9 21.6
39.5 3.3 7.6 3.8 13.0 32.7
43.6 3.1 8.8 5.6 12.0 26.9
31.5 16.2 4.8 8.8 32.9 5.8
35.2 12.9 5.0 8.9 33.4 4.6
22.2 77.8
29.7 70.3
6.8 11.8 25.1 13.9 42.5
8.8 13.3 29.6 15.8 32.5
27.6 43.2 10.6 10.4 8.3
29.3 38.4 9.4 14.7 8.3
MHI-5 (continuous) Social support Low (1e4) Medium (4e5) High (5e6) Gender Male Female Age group Under 30 years 31e44 years 45e60 years 61þ years Marital status Married Separated but not divorced Divorced Widowed De facto Single Employment status Permanent Casual or labour hire Fixed term Self employed Not in the labour force Unemployed Long term health conditions Yes No Education Postgraduate Bachelor degree Diploma or certificate Year 12 Less than year 12 Household structure Couple with no children Couple with children Lone with children Lone person Other
Table 2 e Mental health and social support in the analytic sample, pooled observations 2001e2013. Exposure and other covariates Gender Male Female Age group Under 30 years 31e44 years 45e60 years 61þ years
MHI-5 mean (std. dev.)
Social support (%) in low (L), medium (M), and high (H) categories
75.5 (16.6) 73.2 (17.4)
28.3 (L), 30.0 (M), 41.7 (H) 22.6 (L), 25.5 (M), 51.9 (H)
72.9 (16.9) 73.6 (16.9) 74.2 (17.5) 76.8 (16.8)
20.8 26.1 27.9 26.6
(L), 25.8 (L), 29.1 (L), 28.4 (L), 27.4
(M), (M), (M), (M),
53.4 (H) 44.8 (H) 43.7 (H) 46.0 (H)
MHI-5 ¼ Mental Health Inventory (MHI-5), std. dev. ¼ standard deviation.
Please cite this article in press as: Milner A, et al., Age and gender differences in the influence of social support on mental health: a longitudinal fixed-effects analysis using 13 annual waves of the HILDA cohort, Public Health (2016), http://dx.doi.org/10.1016/ j.puhe.2016.06.029
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Table 3 e Fixed-effect regression results, the effect of social support on mental health by age and gender, HILDA, 2001e2013, 24,799 persons. Exposure and other covariates
(Model 1) adjusted main effects model Coef
Social support Low Medium High Age group Under 30 years 31e44 years 45e60 years 60+ years Age*social support Under 30*low 31e44*medium 45e60*medium 60 plus*medium 31e44*high 45e60*high 60 plus*high Gender*social support Male*low Female*medium Female*high Constant
95% CI
(Model 2) adjusted age interaction model
P-value
Coef
95% CI
(Model 3) adjusted gender interaction model
P-value
Coef
95% CI
P-value
Ref 5.2 9.3
5.0e5.4 9.1e9.5
<0.001 <0.001
Ref 7.4 12.9
6.9e7.8 12.5e13.3
<0.001 <0.001
Ref 4.9 8.7
4.7e5.2 8.4e8.9
<0.001 <0.001
Ref 0.3 0.4 1.6
0.0 to 0.7 0.0 to 0.9 0.9e2.2
0.079 0.070 <0.001
Ref 2.3 3.5 6.3
1.8e2.9 2.9e4.1 5.6e7.1
<0.001 <0.001 <0.001
Ref 0.3 0.4 1.6
0.0 to 0.7 0.0 to 0.9 0.9e2.2
0.078 0.070 <0.001
Ref 1.6 2.6 4.4 2.9 4.8 7.1
2.1 to 3.1 to 4.9 to 3.5 to 5.3 to 7.6 to
Ref 0.5 1.2 64.1
0.2e0.9 0.7e1.6 64.1e65.9
0.006 <0.001 <0.001
65.0
64.1e65.9
<0.001
62.6
1.1 2.1 3.8 2.4 4.2 6.5
61.6e63.5
<0.001 <0.001 <0.001 <0.001 <0.001 <0.001
<0.001
The MHI-5 runs from 0 (low) to 100 (high). Coef ¼ model coefficient; 95% CIs ¼ 95% confidence intervals, significance value at 95%. Adjusted models include age group, marital status, long term health conditions, education, household structure. Reference categories in the interaction models represent young people with low social support (model 2) and males with low social support (model 3). Coefficients for gender are dropped from the fixed-effects model as these are fixed variables.
receiving medium or high levels of social support was associated with the greatest improvement in mental health among the youngest age group. Social support was also associated with a substantial improvement in mental health among those aged 31e44 years. The mental health of males over 61 years and over was least affected by moving from low to medium or high social support. Results for females suggest substantially greater differences in mental health between the oldest age group (61 years and over) and the other age groups. Apart from this age group, the overall levels of mental health by age group were similar between women and men. There were also similar age gradients in the effect of social support on mental health as in males, i.e. the effect of social support on mental health was most apparent in younger rather than older age groups.
Discussion This study has demonstrated that the relationship between social support and mental health is modified by age and gender. Specifically, the provision of higher levels of social support is associated with greater differences in mental health among people under 30 years than older age groups (particularly those persons 45 years and older). The mental health of females appeared to benefit slightly more from higher levels of social support than males. These findings must be tempered with some caveats. First of all, we would acknowledge that our outcome and exposure
measures were self-reported, and hence there is the possibility of dependent misclassification. In saying this, the MHI-5 subscale has been validated against gold standard clinical measures in numerous previous studies and shown to have good sensitivity and specificity.27,30,31,39 We would also point out that we explicitly assessed within-person changes in social support in relation to changes in mental health. To the extent that personal characteristics that might confound the examined associations are time invariant (e.g. negative affect), these would be controlled for by the fixed-effects analysis. Further, we would note that subjective accounts of social support are in fact appropriate, considering that perceived social support has stronger effects on measures of mental health than received social support.40 There is also a need to consider factors connected to the HILDA study which might impact generalizability, including the greater retention of persons of higher vs lower socio-economic status. We would argue that these limitations are offset by the strengths of the study, particularly its longitudinal design, which enabled us to examine the relationship between social support and mental health over 13 annual waves using a large representative national sample. Further, the fixed-effects analytical approach allowed us to examine causally-robust within-person associations controlling for time-invariant confounders that may have otherwise biased results. Our study suggests that the mental health of both females and males both benefited from the provision of social support, although females appeared to benefit slightly more than males. Past research in this area has been mixed, as reviewed
Please cite this article in press as: Milner A, et al., Age and gender differences in the influence of social support on mental health: a longitudinal fixed-effects analysis using 13 annual waves of the HILDA cohort, Public Health (2016), http://dx.doi.org/10.1016/ j.puhe.2016.06.029
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by Fuhrer et al.41 In their own investigation of this topic, Fuhrer et al.41 found greater effects of emotional social support on the mental health of males rather than females, while the effects of social support at work were slightly more beneficial for females. In contrast, other studies suggest few gender differences in the effects of social support on health.42,43 These mixed findings are likely to reflect differences in the measurement of social support, as the conceptualization and scales used to measure the construct varied considerably between studies. For these reasons, we would highlight that the results of these past studies are not strictly comparable to our study as we used an omnibus measure of social support. Further, there are considerable differences in study designs, as some studies have used cross-sectional designs44 while others have used a longitudinal approach,41 as well as the specific sample examined, e.g. older persons44 vs a working age cohort.41 Younger age groups appeared to derive the greatest benefit from social support. There is some evidence that younger people experience a considerable transition in their sources of social support, shifting from valuing familial networks to friend networks in older adolescents and early adulthood.3,45 There is also evidence that as younger people move into adolescence and young adulthood, they begin to rely on relationships other than their immediate primary family network, and derive self-definition from these other relationships to an increasing degree.46,47 Hence, wider peer and friendship networks may be more important for overall mental health among young people. It is also worth note that the youngest age group also has the lowest levels of mental health comparative to other age groups. This finding is consistent with past national surveys showing that young people consistently report worse mental health than older age groups (and are also least likely to seek help for these problems).48 Most past research in the area has assessed between person differences only. Our study adds uniquely to past research in that it uses a within-person analytic approach, which means that we were able to rule out stable personrelated characteristics associated with both mental health and social support (time-invariant confounders). In conclusion, our study across 13 waves of annual panel data suggests that there are considerable age differences in the relationship between social support and mental health. There is, to a lesser extent, evidence of gender differences. These results have considerable implications in terms of prevention and promotion of mental health. There is already evidence that social support intervention may be beneficial in reducing depression and depressive symptoms.49 The results of this study suggest that social support interventions that promote emotional support and reduce loneliness may particularly benefit younger Australians.
Author statements Acknowledgements This paper uses unit record data from the Household, Income and Labour Dynamics in Australia (HILDA) Survey. The HILDA Project was initiated and is funded by the Australian
Government Department of Social Services (DSS) and is managed by the Melbourne Institute of Applied Economic and Social Research Melbourne Institute. The findings and views reported in this paper, however, are those of the author and should not be attributed to either DSS or the Melbourne Institute. The data used in this paper was extracted using the Add-On Package PanelWhiz for Stata. PanelWhiz (http://www. PanelWhiz.eu) was written by Dr. John P. Haisken-DeNew ([email protected]).
Ethical approval The authors assert that all procedures contributing to this work comply with the ethical standards of the relevant national and institutional committees on human experimentation and with the Helsinki Declaration of 1075, as revised in 2008. Data are available for approved users from the Department of Social Services.
Funding This work was supported by beyondblue and the Movember Foundation. This study also received centre grant funding (#15732) from the Victorian Health Promotion Foundation Melbourne, Victoria (Australia).
Competing interests None declared.
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32. Ware Jr JE. SF-36 health survey update. Spine 2000;25:3130e9. 33. Contopoulos-Ioannidis DG, Karvouni A, Kouri I, Ioannidis JPA. Reporting and interpretation of SF-36 outcomes in randomised trials: systematic review. BMJ Br Med J 2009;338:a3006. 34. McDowell TL, Serovich JM. The effect of perceived and actual social support on the mental health of HIV-positive persons. AIDS Care 2007;19:1223e9. 35. Lyyra T-M, Heikkinen R-L. Perceived social support and mortality in older people. J Gerontol B Psychol Sci Soc Sci 2006;61:S147e52. 36. Crosier T, Butterworth P, Rodgers B. Mental health problems among single and partnered mothers. The role of financial hardship and social support. Soc Psychiatry Psychiatr Epidemiol 2007;42:6e13. 37. Hewitt B, Turrell G, Giskes K. Marital loss, mental health and the role of perceived social support: findings from six waves of an Australian population based panel study. J Epidemiol Community Health 2012;66:308e14. 38. Haber MG, Cohen JL, Lucas T, Baltes BB. The relationship between self-reported received and perceived social support: a meta-analytic review. Am J Community Psychol 2007;39:133e44. 39. Bech P, Rasmussen NA, Olsen LR, Noerholm V, Abildgaard W. The sensitivity and specificity of the Major Depression Inventory, using the Present State Examination as the index of diagnostic validity. J Affect Disord 2001;66:159e64. 40. Helgeson VS. Two important distinctions in social support: kind of support and perceived versus received. J Appl Soc Psychol 1993;23:825e45. 41. Fuhrer R, Stansfeld SA, Chemali J, Shipley MJ. Gender, social relations and mental health: prospective findings from an occupational cohort (Whitehall II study). Soc Sci Med 1999;48:77e87. 42. Fusilier MR, Ganster DC, Mayes BT. The social support and health relationship: is there a gender difference? J Occup Psychol 1986;59:145e53. 43. Zhang B, Li J. Gender and marital status differences in depressive symptoms among elderly adults: the roles of family support and friend support. Aging Ment Health 2011;15:844e54. 44. Caetano SC, Silva CM, Vettore MV. Gender differences in the association of perceived social support and social network with self-rated health status among older adults: a population-based study in Brazil. BMC Geriatr 2013;13:122. pez M. Parents and peers as providers 45. del Valle JF, Bravo A, Lo of support in adolescents' social network: a developmental perspective. J Community Psychol 2010;38:16e27. 46. Meeus WM. Identity development, parental and peer support in adolescence: results of a national Dutch survey. Adolescence 1995;30:931. 47. Meeus W, Iedema J, Maassen G, Engels R. Separationeindividuation revisited: on the interplay of parenteadolescent relations, identity and emotional adjustment in adolescence. J Adolesc 2005;28:89e106. 48. Slade T, Johnston A, Oakley Browne MA, Andrews G, Whiteford H. 2007 National survey of mental health and wellbeing: methods and key findings. Aust N Z J Psychiatry 2009;43:594e605. -Llopis e, Hosman C, Jenkins R, Anderson P. Predictors of 49. Jane efficacy in depression prevention programmes. Meta-analysis 2003;183:384e97.
Appendix A. Supplementary data Supplementary data related to this article can be found at http://dx.doi.org/10.1016/j.puhe.2016.06.029.
Please cite this article in press as: Milner A, et al., Age and gender differences in the influence of social support on mental health: a longitudinal fixed-effects analysis using 13 annual waves of the HILDA cohort, Public Health (2016), http://dx.doi.org/10.1016/ j.puhe.2016.06.029
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Original Research
Age and gender differences in the influence of social support on mental health: a longitudinal fixed-effects analysis using 13 annual waves of the HILDA cohort A. Milner a,b,*,c, L. Krnjacki b, A.D. LaMontagne a,b a Work, Health and Wellbeing Unit, Centre for Population Health Research, School of Health & Social Development, Deakin University, Melbourne, Australia b Centre for Health Equity, Melbourne School of Population and Global Health, The University of Melbourne, Victoria 3010, Australia
article info
abstract
Article history:
Objectives: Perceived social support is associated with better mental health. There has been
Received 11 March 2016
limited attention to how these relationships are modified by age and gender. We assessed
Received in revised form
this topic using 13 years of cohort data.
23 May 2016
Study design: Prospective cohort study.
Accepted 28 June 2016
Methods: The outcome was the Mental Health Inventory-5 (MHI-5), a reliable and valid
Available online xxx
screening instrument for mood disorders. The main exposure was a social support scale composed of 10 items. We used longitudinal fixed-effects regression modelling to investigate
Keywords:
within-person changes in mental health. Analytic models controlled for within-person sour-
Social support
ces of bias. We controlled for time-related factors by including them into regression modelling.
Mental health
Results: The provision of higher levels of social support was associated with greater im-
MHI-5
provements in mental health for people aged under 30 years than for older age groups. The
Gender
mental health of females appeared to benefit slightly more from higher levels of social
Age
support than males. Improvements in the MHI-5 were on a scale that could be considered
Longitudinal analysis
clinically significant. Conclusions: The benefits of social support for young people may be connected to agerelated transitions in self-identity and peer friendship networks. Results for females may reflect their tendency to place greater emphasis on social networks than males. © 2016 The Royal Society for Public Health. Published by Elsevier Ltd. All rights reserved.
Abbreviations: MHI-5, Mental Health Inventory-5. * Corresponding author. Work, Health & Wellbeing, Population Health Strategic Research Centre, Building BC3.213, School of Health & Social Development, Deakin University, Burwood, VIC 3125 Australia. Fax: þ61 03 9244 6624. E-mail address: [email protected] (A. Milner). c www.deakin.edu.au. http://dx.doi.org/10.1016/j.puhe.2016.06.029 0033-3506/© 2016 The Royal Society for Public Health. Published by Elsevier Ltd. All rights reserved. Please cite this article in press as: Milner A, et al., Age and gender differences in the influence of social support on mental health: a longitudinal fixed-effects analysis using 13 annual waves of the HILDA cohort, Public Health (2016), http://dx.doi.org/10.1016/ j.puhe.2016.06.029
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Introduction Social support (defined as the social resources that persons perceive to be available or that are actually provided to them by non-professionals1) is provided through people's connections or contacts with others.2 The degree to which an individual may rely on these social resources differs depending on a variety of factors, including age3,4 and gender.5e7 Past research suggests that women are more likely to give and receive emotional support than males.6 As women have a greater number of female friends than men, they may have a greater range of people to call on for emotional support should they need it.6 There is also some evidence that reliance on different social groups changes as people grow older; e.g. adolescents appear to draw more on peer networks as they age.3 In contrast, older adults tend to have smaller social networks, are less close to network members, and have fewer nonprimary group ties than younger persons.8 There is substantial evidence that those with greater social support have better mental health than those with less social support.9e12 Moreover, a number of studies suggest that loneliness (conceptualized as a converse of social support, i.e. the gap between one's desired and actual ties to others2) is associated with depressive symptoms and depression.13e15 However, there has been limited research on whether there is variation in the relationship between social support and mental health by age or gender. Given the research cited previously, it is highly plausible that such differences exist. We investigated this possibility using a general population cohort and hypothesized that younger people and women may benefit more from social support than older people and males.
Methods Data source The Household, Income and Labour Dynamics in Australia (HILDA) survey is a longitudinal, nationally representative study of Australian households established in 2001. It collects detailed information annually from over 13,000 individuals within over 7000 households.16 The response rate to wave 1 was 66%.16 The survey covers a range of dimensions including social, demographic, health and economic conditions using a combination of face-to-face interviews with trained interviewers and a self-completion questionnaire. Although data are collected on each member of participating households, interviews are only conducted with those older than 15 years of age. The initial wave of the survey began with a large national probability sample of Australian households occupying private dwellings.16 Interviews were sought in later waves with all persons in sample households who turned 15 years of age. Additional persons have been added to the sample as a result of changes in household composition. For example, if a household member left his or her original household (e.g. children left home, or a couple separated), he/she formed an entirely new household including all persons living with the original sample member. Inclusion of these new households is the main way in which the HILDA survey maintains sample
representativeness. A top-up sample of 2000 people was added to the cohort in 2011 to allow better representation of the Australian population using the same methodology as the original sample (i.e. a three-stage area-based design).17 The response rates for the HILDA survey are above 90% for respondents who have continued in the survey and above 70% for new respondents being invited into the study.16 The main variables examined in this study were available in all annual waves of HILDA (2001e2013).
Analytic considerations and approach Research on social support has also been subject to the concern that perceived-support measures may be confounded with either personality factors or depression,18,19 thus there may be the possibility that people with poorer mental health attract less social support. However, past prospective studies have evidenced functional differences between social support, loneliness and mental health problems.18 For example, social support and loneliness predict subsequent depression longitudinally, even after controlling for initial depression levels,14,15,20e23 which provides some empirical support for this causal pathway. Further, a number of other studies have found that common mental illnesses, such as depressive symptoms, represent clearly different statistical constructs from loneliness and social support.14,24,25 Regardless, this emphasizes the importance of controlling for person-related characteristics that could influence the relationship between social support and mental health. In this study, we will use longitudinal linear fixed-effects regression models to estimate an association between social support and mental health score within individuals. We will use fixed-effects regression models to assess mean differences in mental health associated with medium or high social support compared with that individual's mean mental health score when they reported low social support. These models provide an indication of within-person effects, where each individual acts as their own control and estimates are not confounded by time-invariant personal, demographic and environmental factors.26 Fixed-effects models are particularly useful where timeinvariant confounding is likely to create bias in causal estimates. For example, mental health may be affected by withinperson factors such as personality (e.g. negative affect). We controlled for time-varying factors by including a number of relevant confounders into the fixed-effects models. Including these in fixed-effects models accounted for individual change in these variables that might influence the relationship between social support and mental health. We tested the hypothesis that the association between social support and mental health differed depending on the age and gender of a person using an interaction term in fixed-effects models, and examined this using the likelihood ratio test and inspection of significance values of interaction terms in the model. Where interactions were significant, models were then stratified by age and gender.
Outcome variable Mental health was assessed using the five-item Mental Health Inventory (MHI-5), a subscale from the Short Form-36 (SF-36) general health measure. The MHI-5 assesses symptoms of
Please cite this article in press as: Milner A, et al., Age and gender differences in the influence of social support on mental health: a longitudinal fixed-effects analysis using 13 annual waves of the HILDA cohort, Public Health (2016), http://dx.doi.org/10.1016/ j.puhe.2016.06.029
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depression and anxiety (nervousness, depressed affect) and positive aspects of mental health (feeling calm, happy) in the past 4 weeks. The MHI-5 has reasonable validity and is an effective screening instrument for mood disorders or severe depressive symptomatology in the general population27e29 and has been validated as a measure for depression using clinical interviews as the gold standard.27,30,31 The current analyses uses the continuous MHI-5 score (scales 1e100), with higher scores representing better mental health. Although there is no universally accepted translation of MHI-5 score difference to clinical meaningfulness, a difference of three points on the norm based scale (T-score) has been suggested to reflect a minimally important difference,32 and a difference of four or more on the unstandardized scale has been characterized as indicating a moderate clinically significant effect.33
Exposure variable The social support measure was designed to assess an individual's perception of the social support they receive. Perceived social support has been recognized as having a more important effect on mental health34 and mortality35 than received social support. The HILDA social support measure has been used in previous studies.36,37 This measure primarily taps into emotional support (items 3, 4, 5, 7, 8) and practical support (items 1, 6, 9). It also measures loneliness (item 2), which we would conceptualize as the converse of social support. The 10item scale included the following items: 1. I have no one to lean on in times of trouble (reverse coded); 2. I often feel very lonely (reverse coded); 3. I enjoy the time I spend with the people that are important to me; 4. I seem to have a lot of friends; 5. People don't come and visit as much as I would like (reverse coded); 6. I often need help from other people but can't get it (reverse coded); 7. I don't have anyone that I can confide in (reverse coded); 8. There is someone who can always cheer me up when I am down; 9. When I need someone to help me out, I can usually find someone; and 10. When something is on my mind, just talking with the people I know can make me feel better. Items are rated on a Likert scale ranging from strongly disagree (1) to strongly agree (7) and the Cronbach's alpha, for the current data, was 0.84 across all waves. The social support scale was created by averaging the 10 items in the scale, with lower scores representing lower social support and higher scores representing higher social support (the items we reverse coded previously). In its original form, the scale was strongly positively skewed. Hence, we tested the analytic relationships of interest with social support coded in three levels (low [1e4.69], medium [4.70e5.59], high [5.6e7]) based on the observed distribution of the variable across all waves of HILDA. As a sensitivity test, we also tested social support as a linear variable.
3
Other covariates We included gender and age group (under 30, 31e44, 45e60, 61þ years) in the main models to test for interaction effects. The models also included a number of likely time-varying potential confounders. These included household structure (couple or lone adult residing with dependants, couple without dependants, lone person without dependants, and a group or multiple person household) and marital status (married, separated, divorced, widowed, de facto, single), recognizing that the perceptions of social support may differ according to whether someone is in a relationship or not (i.e. differences between received and perceived social support).38 We also controlled for employment status (permanent, casual or labour hire, fixed term, not in the labour force, unemployed), recognizing the people who are employed may have access to a wider range of sources for social support than those who are not employed. Other time-varying potential confounders controlled for included education (postgraduate, bachelor degree, diploma or certificate, year 12, not completed year 12) and long term health condition (yes or no).
Analytic sample and missing data Fig. 1 describes how the analytic sample was obtained. About 7% of people in HILDA had missing information on the MHI-5 or social support and were thus excluded. From here, approximately 5% of people were excluded due to missing information on other covariates. The final analytic sample was comprised 24,799 people, 88.9% of the original number of people included in the cohort. Those not included in the analysis were more likely to be single, and to have attained less education than those included in the analytic sample. However, these differences were non-significant and only represented a small proportion of persons.
Results Characteristics of the analytic sample The characteristics of the analytic sample can be seen in Table 1. The minimum number of observations for respondents included in the study was 2 and the maximum was 12; on average respondents contributed 5.8 waves of data.
Overall description of mental health and social support in the analytic sample Across the whole sample, the mean (SD) MHI-5 scores for men and women was 75.5 (16.6) and 73.2 (17.4) respectively (Table 2). In terms of age differences, the MHI-5 score of people over 61 years of age (mean 76.8, standard deviation 16.8) was about 4 points higher than that of the youngest age group (mean 72.9, standard deviation 16.9). As can be seen, females and youngest age groups more often reported the highest category of social support compared to males and the youngest age group (Table 2). Within-person regression results can be seen in Table 3 which shows the adjusted main effects model (1), the
Please cite this article in press as: Milner A, et al., Age and gender differences in the influence of social support on mental health: a longitudinal fixed-effects analysis using 13 annual waves of the HILDA cohort, Public Health (2016), http://dx.doi.org/10.1016/ j.puhe.2016.06.029
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Table 1 e Sample characteristics (n ¼ 24,799; obs 144,848) on first and last contributed waves to the analysis. Exposure and other covariates
Fig. 1 e Sample selection.
adjusted age interaction model (2), and the adjusted gender interaction model (3). There was a strong direct relationship between social support and mental health (model 1). Compared to when a person had lower support, an increase to ‘medium’ social support was associated with approximately a 5.2-point improvement in mental health (95% CI 5.0e5.4). There was over a 9-point increase in mental health when a person changed from being in the low social support category to the high social support category (95% CI 9.10e9.5). These results were confirmed when the social support was measured as a linear variable (5.13, 95% CI 5.04e5.23, P < 0.001). Model 2 indicates that there was a significant interaction between age and social support. In essence, this shows that the effect of social support on mental health decreases with age. Model 3 shows the interaction between social support and gender and suggests that the effect of social support on mental health is greater for females than males. Likelihood ratio tests were highly significant (P < 0.001) when comparing both model 2 and model 3 to model 1. Supplementary Table 1 shows results of the relationship between social support and mental health by age, for male and females (with 95% confidence intervals). Younger males had the lowest levels of mental health while those aged 45e60 years had the highest levels of mental health. It appears that
First observed wave (%)
Last observed wave (%)
73.6
73.1
26.2 27.1 46.7
26.8 26.3 46.9
48.0 52.0
48.0 52.0
41.3 23.9 20.5 14.3
32.6 21.9 23.9 21.6
39.5 3.3 7.6 3.8 13.0 32.7
43.6 3.1 8.8 5.6 12.0 26.9
31.5 16.2 4.8 8.8 32.9 5.8
35.2 12.9 5.0 8.9 33.4 4.6
22.2 77.8
29.7 70.3
6.8 11.8 25.1 13.9 42.5
8.8 13.3 29.6 15.8 32.5
27.6 43.2 10.6 10.4 8.3
29.3 38.4 9.4 14.7 8.3
MHI-5 (continuous) Social support Low (1e4) Medium (4e5) High (5e6) Gender Male Female Age group Under 30 years 31e44 years 45e60 years 61þ years Marital status Married Separated but not divorced Divorced Widowed De facto Single Employment status Permanent Casual or labour hire Fixed term Self employed Not in the labour force Unemployed Long term health conditions Yes No Education Postgraduate Bachelor degree Diploma or certificate Year 12 Less than year 12 Household structure Couple with no children Couple with children Lone with children Lone person Other
Table 2 e Mental health and social support in the analytic sample, pooled observations 2001e2013. Exposure and other covariates Gender Male Female Age group Under 30 years 31e44 years 45e60 years 61þ years
MHI-5 mean (std. dev.)
Social support (%) in low (L), medium (M), and high (H) categories
75.5 (16.6) 73.2 (17.4)
28.3 (L), 30.0 (M), 41.7 (H) 22.6 (L), 25.5 (M), 51.9 (H)
72.9 (16.9) 73.6 (16.9) 74.2 (17.5) 76.8 (16.8)
20.8 26.1 27.9 26.6
(L), 25.8 (L), 29.1 (L), 28.4 (L), 27.4
(M), (M), (M), (M),
53.4 (H) 44.8 (H) 43.7 (H) 46.0 (H)
MHI-5 ¼ Mental Health Inventory (MHI-5), std. dev. ¼ standard deviation.
Please cite this article in press as: Milner A, et al., Age and gender differences in the influence of social support on mental health: a longitudinal fixed-effects analysis using 13 annual waves of the HILDA cohort, Public Health (2016), http://dx.doi.org/10.1016/ j.puhe.2016.06.029
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Table 3 e Fixed-effect regression results, the effect of social support on mental health by age and gender, HILDA, 2001e2013, 24,799 persons. Exposure and other covariates
(Model 1) adjusted main effects model Coef
Social support Low Medium High Age group Under 30 years 31e44 years 45e60 years 60+ years Age*social support Under 30*low 31e44*medium 45e60*medium 60 plus*medium 31e44*high 45e60*high 60 plus*high Gender*social support Male*low Female*medium Female*high Constant
95% CI
(Model 2) adjusted age interaction model
P-value
Coef
95% CI
(Model 3) adjusted gender interaction model
P-value
Coef
95% CI
P-value
Ref 5.2 9.3
5.0e5.4 9.1e9.5
<0.001 <0.001
Ref 7.4 12.9
6.9e7.8 12.5e13.3
<0.001 <0.001
Ref 4.9 8.7
4.7e5.2 8.4e8.9
<0.001 <0.001
Ref 0.3 0.4 1.6
0.0 to 0.7 0.0 to 0.9 0.9e2.2
0.079 0.070 <0.001
Ref 2.3 3.5 6.3
1.8e2.9 2.9e4.1 5.6e7.1
<0.001 <0.001 <0.001
Ref 0.3 0.4 1.6
0.0 to 0.7 0.0 to 0.9 0.9e2.2
0.078 0.070 <0.001
Ref 1.6 2.6 4.4 2.9 4.8 7.1
2.1 to 3.1 to 4.9 to 3.5 to 5.3 to 7.6 to
Ref 0.5 1.2 64.1
0.2e0.9 0.7e1.6 64.1e65.9
0.006 <0.001 <0.001
65.0
64.1e65.9
<0.001
62.6
1.1 2.1 3.8 2.4 4.2 6.5
61.6e63.5
<0.001 <0.001 <0.001 <0.001 <0.001 <0.001
<0.001
The MHI-5 runs from 0 (low) to 100 (high). Coef ¼ model coefficient; 95% CIs ¼ 95% confidence intervals, significance value at 95%. Adjusted models include age group, marital status, long term health conditions, education, household structure. Reference categories in the interaction models represent young people with low social support (model 2) and males with low social support (model 3). Coefficients for gender are dropped from the fixed-effects model as these are fixed variables.
receiving medium or high levels of social support was associated with the greatest improvement in mental health among the youngest age group. Social support was also associated with a substantial improvement in mental health among those aged 31e44 years. The mental health of males over 61 years and over was least affected by moving from low to medium or high social support. Results for females suggest substantially greater differences in mental health between the oldest age group (61 years and over) and the other age groups. Apart from this age group, the overall levels of mental health by age group were similar between women and men. There were also similar age gradients in the effect of social support on mental health as in males, i.e. the effect of social support on mental health was most apparent in younger rather than older age groups.
Discussion This study has demonstrated that the relationship between social support and mental health is modified by age and gender. Specifically, the provision of higher levels of social support is associated with greater differences in mental health among people under 30 years than older age groups (particularly those persons 45 years and older). The mental health of females appeared to benefit slightly more from higher levels of social support than males. These findings must be tempered with some caveats. First of all, we would acknowledge that our outcome and exposure
measures were self-reported, and hence there is the possibility of dependent misclassification. In saying this, the MHI-5 subscale has been validated against gold standard clinical measures in numerous previous studies and shown to have good sensitivity and specificity.27,30,31,39 We would also point out that we explicitly assessed within-person changes in social support in relation to changes in mental health. To the extent that personal characteristics that might confound the examined associations are time invariant (e.g. negative affect), these would be controlled for by the fixed-effects analysis. Further, we would note that subjective accounts of social support are in fact appropriate, considering that perceived social support has stronger effects on measures of mental health than received social support.40 There is also a need to consider factors connected to the HILDA study which might impact generalizability, including the greater retention of persons of higher vs lower socio-economic status. We would argue that these limitations are offset by the strengths of the study, particularly its longitudinal design, which enabled us to examine the relationship between social support and mental health over 13 annual waves using a large representative national sample. Further, the fixed-effects analytical approach allowed us to examine causally-robust within-person associations controlling for time-invariant confounders that may have otherwise biased results. Our study suggests that the mental health of both females and males both benefited from the provision of social support, although females appeared to benefit slightly more than males. Past research in this area has been mixed, as reviewed
Please cite this article in press as: Milner A, et al., Age and gender differences in the influence of social support on mental health: a longitudinal fixed-effects analysis using 13 annual waves of the HILDA cohort, Public Health (2016), http://dx.doi.org/10.1016/ j.puhe.2016.06.029
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by Fuhrer et al.41 In their own investigation of this topic, Fuhrer et al.41 found greater effects of emotional social support on the mental health of males rather than females, while the effects of social support at work were slightly more beneficial for females. In contrast, other studies suggest few gender differences in the effects of social support on health.42,43 These mixed findings are likely to reflect differences in the measurement of social support, as the conceptualization and scales used to measure the construct varied considerably between studies. For these reasons, we would highlight that the results of these past studies are not strictly comparable to our study as we used an omnibus measure of social support. Further, there are considerable differences in study designs, as some studies have used cross-sectional designs44 while others have used a longitudinal approach,41 as well as the specific sample examined, e.g. older persons44 vs a working age cohort.41 Younger age groups appeared to derive the greatest benefit from social support. There is some evidence that younger people experience a considerable transition in their sources of social support, shifting from valuing familial networks to friend networks in older adolescents and early adulthood.3,45 There is also evidence that as younger people move into adolescence and young adulthood, they begin to rely on relationships other than their immediate primary family network, and derive self-definition from these other relationships to an increasing degree.46,47 Hence, wider peer and friendship networks may be more important for overall mental health among young people. It is also worth note that the youngest age group also has the lowest levels of mental health comparative to other age groups. This finding is consistent with past national surveys showing that young people consistently report worse mental health than older age groups (and are also least likely to seek help for these problems).48 Most past research in the area has assessed between person differences only. Our study adds uniquely to past research in that it uses a within-person analytic approach, which means that we were able to rule out stable personrelated characteristics associated with both mental health and social support (time-invariant confounders). In conclusion, our study across 13 waves of annual panel data suggests that there are considerable age differences in the relationship between social support and mental health. There is, to a lesser extent, evidence of gender differences. These results have considerable implications in terms of prevention and promotion of mental health. There is already evidence that social support intervention may be beneficial in reducing depression and depressive symptoms.49 The results of this study suggest that social support interventions that promote emotional support and reduce loneliness may particularly benefit younger Australians.
Author statements Acknowledgements This paper uses unit record data from the Household, Income and Labour Dynamics in Australia (HILDA) Survey. The HILDA Project was initiated and is funded by the Australian
Government Department of Social Services (DSS) and is managed by the Melbourne Institute of Applied Economic and Social Research Melbourne Institute. The findings and views reported in this paper, however, are those of the author and should not be attributed to either DSS or the Melbourne Institute. The data used in this paper was extracted using the Add-On Package PanelWhiz for Stata. PanelWhiz (http://www. PanelWhiz.eu) was written by Dr. John P. Haisken-DeNew ([email protected]).
Ethical approval The authors assert that all procedures contributing to this work comply with the ethical standards of the relevant national and institutional committees on human experimentation and with the Helsinki Declaration of 1075, as revised in 2008. Data are available for approved users from the Department of Social Services.
Funding This work was supported by beyondblue and the Movember Foundation. This study also received centre grant funding (#15732) from the Victorian Health Promotion Foundation Melbourne, Victoria (Australia).
Competing interests None declared.
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Appendix A. Supplementary data Supplementary data related to this article can be found at http://dx.doi.org/10.1016/j.puhe.2016.06.029.
Please cite this article in press as: Milner A, et al., Age and gender differences in the influence of social support on mental health: a longitudinal fixed-effects analysis using 13 annual waves of the HILDA cohort, Public Health (2016), http://dx.doi.org/10.1016/ j.puhe.2016.06.029