Gender, self-rated health and functional decline among community-dwelling older adults

Archives of Gerontology and Geriatrics 77 (2018) 174–183

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Archives of Gerontology and Geriatrics journal homepage: www.elsevier.com/locate/archger

Gender, self-rated health and functional decline among community-dwelling older adults

T

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Razak M. Gyasi , David R. Phillips Department of Sociology and Social Policy, Lingnan University, Hong Kong

A R T I C LE I N FO

A B S T R A C T

Keywords: Gender Functional declines Instrumental activities of daily living Marital status Self-rated health Health- and social-care policy

Objective: This paper examines the association between self-rated health (SRH) and functional decline (FD) in older Ghanaian cohorts and investigates whether the effect differs by gender and also modified by marital status. Methods: The study used cross-sectional survey data (N = 1200) from an Aging, Health, Psychological Wellbeing and Health-seeking Behavior Study (AHPWHB) study conducted in between August 2016 and January 2017. A four-level gendered-stratified logit modeling estimated the SRH-FD association and the interaction terms. Results: Overall, 23% of male respondents and 34% of women revealed significant FD (p < 0.001). The fullyadjusted model showed that SRH status was a strong predictor of FD across genders but the effect was most pronounced among men. Compared with excellent/very good SRH, fair and poor SRH (β = 0.160; p < 0.05) and (β = 1.700; p < 0.001) for women and (β = 2.202; p < 0.001) and (β= 2.356; p < 0.001) for men respectively were significantly associated with increased FD. However, good (β = − 1.760; p < 0.001), fair (β = − 2.800; p < 0.001) and poor SRH (β = −2.088; p < 0.001) decreased FD if an older woman was married compared with unmarried women with excellent/very good SRH. Conclusion: The strength of SRH-FDs association largely differed with gender and also moderated by marital status for women. Improving the SRH and marital quality could be protective of functional abilities, independence and quality of life for older people.

1. Introduction Life expectancy at birth worldwide has increased by more than 30 years over the last 9 decades and there has been a rapid growth in numbers of people aged 60 years or older (United Nations, 2015; Phillips & Feng, 2018). Disproportionately, low- and middle-income countries (LAMICs) are the home for more than 67% of older cohorts and this proportion will increase to about 85% by 2050 (United Nations DESA Population Division (UNDESA, 2017). Ghana, as an example of LAMICs, has one of the largest and fastest growing older populations in the sub-Saharan African region. Whilst a great achievement, demographic aging can perhaps compromise health and wellbeing particularly in the context of LAMICs where aging occurs almost always some way ahead of social and economic development and especially healthand social-care services. Older people in LAMICs tend to suffer from a wide range of health challenges, infectious and chronic conditions, including functional declines (FD) and cognitive impairment often with gendered dimensions. Estimates show that about 40% of non-institutionalized older people globally report difficulty with some physical functions and/or have

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Corresponding author. E-mail address: [email protected] (R.M. Gyasi).

https://doi.org/10.1016/j.archger.2018.05.010 Received 9 February 2018; Received in revised form 10 May 2018; Accepted 11 May 2018 Available online 16 May 2018 0167-4943/ © 2018 Elsevier B.V. All rights reserved.

disabilities (UNDESA, 2017). Increases in old age poverty through difficulty in carrying out basic and instrumental activities of daily living may also increase dependence in poorer countries, with multiple negative effects on health and safety and the need for support and family care (Jin et al., 2017; Hajek, Brettschneider, Mallon, Van Der Leeden, & Mamone, 2017; La Fleur & Salthouse, 2017). These, in turn, may increase psychological distress, poorer quality of life and the associated higher healthcare demand, sometimes leading to institutionalization, higher rates of morbidity and also mortality (Chou, Hwang, & Wu, 2012). A clear understanding of strong predictors of FD among older persons in LAMICs could provide important guidance for policymakers and health services development towards improving functional independence and quality of life in late life. As a reliable subjective indicator of health through a single psychometric or clinical item, SRH broadly captures not only the overall current health status but also historical and future hospital records especially old age health outcomes (Nielsen, 2015). SRH generally reflects the physical, emotional and personal components of health and frequently been adopted in national level surveys globally. A growing number of cross-sectional and longitudinal studies especially among

Archives of Gerontology and Geriatrics 77 (2018) 174–183

R.M. Gyasi, D.R. Phillips

2. Methods

older people have linked SRH to many health outcomes including functional limitations (Shinkai et al., 2013; Fujiwara et al., 2008), mental/cognitive impairments (Lachytova, Katreniakova, Mikula, Jendrichovsky, & Nagyova, 2017; La Fleur & Salthouse, 2017), chronic non-communicable conditions (Chan et al., 2015), mortality (DeSalvo, Bloser, Reynolds, He, & Muntner, 2006; Falconer, Quesnel-Vallée, & Taylor, 2015) and overall quality of life (OECD, 2014). More specifically, studies in more advanced settings have found that respondents with poor SRH have functional ability risks many times greater than those with better SRH (Idler, Russell, & Davis, 1992; Tomioka, Kurumatani, & Hosoi, 2017). In this regard, our major expectation, therefore, is that a poorer self-perceived health status will lead to FD among older persons. Although there is a distinct contextual framework within which traditional socio-cultural structures interpret the meaning of health and healthcare in sub-Saharan Africa (Gyasi, Buor, Adu-Gyamfi, Adjei, & Amoah, 2018), only very limited evidence exists in this context regarding the relationships between SRH and FD in later life (Debpuur, Welaga, Wak, & Hodgson, 2010). Moreover, some studies in richer countries have historically established associations between SRH and instrumental activities of daily living (Debpuur et al., 2010; Idler et al., 1992), these studies unfortunately have generally failed to isolate SRH as the major explanatory variable in order to measure its precise effect. Previous studies on this topic have, therefore, provided somewhat mixed results and the evidence is often confounding (Shinkai et al., 2013). More importantly, most studies also fail to account for the important role of respondent characteristics such as gender differences and marital status in the relationship between SRH and FD for a more critical conclusion. Indeed, very few studies have moved beyond examining the direct effects of, or relationships of, SRH and FD of older people. Our study contributes to the understanding of these relationships between SRH and FD among community-residing older persons in a lower middle-income country, Ghana, and suggests their implications for policy and public health planning in several ways. First, we introduce specificity in the relationship between SRH and FD by controlling for important respondents’ sociodemographic and health-related conditions rather than treating SRH as a component of the potential predictors. Second, previous studies do suggest that older persons’ perceived health status and their health outcomes may be influenced by gender (DeSalvo et al., 2006; Tomioka et al., 2017). This may be subject to stimulus-response and health-illness perception differentials between the gendered sub-groups (Gyasi et al., 2018). Providing gendered-stratification in the SRH-FD analysis may improve existing understanding. Moreover, although sparse evidence exists (Bulanda, Brown, & Yamashita, 2016; Zhang & Hayward, 2006), the effect of marital status on physical health is experienced by men and women differently especially in later life, when marital dissolution and various forms of marital destruction often prevail, including widowhood, divorce and prolonged separation. Therefore, this paper provides gender-based evidence to evaluate potential gender differences in the effect of SRH on FD. In addition, studies underscore that marital status has a robust buffering effect on deteriorating health and wellbeing of the general population but especially in late life (Liu, 2012; Whisman, Robustelli, & Sbarra, 2016; Zhang & Hayward, 2006). Marital disruption (i.e. divorce, separation and widowhood) has strongly been linked to an increased risk for multiple health challenges including FD and mortality (Shor, Roelfs, Bugyi, & Schwartz, 2012; Sbarra & Law, 2011). However, older persons who are continuously or currently married have a greater chance of reporting better status (Dupre, George, Liu, & Peterson, 2015). Based on the review of previous studies, we were particularly interested in investigating the moderating role of marital status in the association between SRH and FD in later life.

2.1. Sample and data The empirical analysis of the present study used data from an Ageing, Health, Psychological Wellbeing and Health-seeking Behavior Study (AHPWHB). It involved a retrospective population-based, crosssectional survey conducted between August 2016 and January 2017. The study was designed to investigate general health and health services use among community-dwelling household older persons aged 50 years and older. One thousand two-hundred participants were randomly selected and interviewed from individuals nested in 6 districts in the Ashanti region of Ghana through a multi-stage stratified sampling procedure. In the initial sampling stage, three sub-regional areas were defined as primary sampling units based on their distinctive demographic, sociocultural and geographic characteristics. Two districts in each sub-region were randomly selected, with equal chances of selection given to all districts. Urban and rural sectors of each selected district were identified based on the classification of Ghana Statistical Service (GSS, 2012). Data were collected through successful household interviews with the eligible participants. The survey questionnaire was developed in English and translated into Twi (the major local dialect) following WHO translation guidelines for assessment of instruments (Üstun et al., 2005). Sampling weights for the individual older persons were generated to account for the survey design employed and to allow representativeness and generalizability of the findings to the eligible population (Moussavi et al., 2007). This study was approved by the Committee on Human Research Publication and Ethics (CHRPE), School of Medical Sciences, Kwame Nkrumah University of Science and Technology and Komfo Anokye Teaching Hospital, Kumasi, Ghana (Ref: CHRPE/AP/507/16). Ethics approval was also granted by the Research Ethics Sub-Committee of Lingnan University, Hong Kong. Study participants were fully briefed on the research and they provided written and/or oral informed consent based on their preferences. 2.2. Measures 2.2.1. Functional decline (FD) Self-report of difficulty in conducting activities of daily living (ADL) and instrumental activities in daily living (IADL) among older persons were obtained and used as proxies for FD. Difficulty with ADL and IADLs are commonly used to gauge older people’s daily performance (WHODAS-II; WHO, 2012). ADLs were measured on a nine-item scale that reflected performance at four levels: (1) not limited at all (2) less limited (3) somewhat limited and (4) much limited: eating, dressing and/or undressing, grooming, getting in and out of bed, bathing, moving tables/chairs, washing, lifting/carrying groceries and walking more than a kilometer. The total score ranged from 9 to 36 and was divided into two groups: 9–18 was considered 1 = “not declined” and 19–36 as 2 = “declined”. IADLs were addressed based on seven items relevant to the local circumstances: using the telephone/mobile phone, using public transport, shopping, preparing meals/kitchen chores, washing of clothes/doing laundry, taking medicine and management of finances. The overall score ranged from 7 to 21 with 7–14 representing 1 = “not impaired” and 15–21 representing 2 = “impaired”. 2.2.2. Self-rated health (SRH) The key independent variable is SRH and studies propose that it is a sensitive and reliable indicator of an individual’s current health status (Wu & Schimmele, 2006). SRH was determined by the item “In general, how would you rate your overall health at the present time?” This was assessed via five-response categories: “excellent”, “very good”, “good”, “fair” and “poor” (Rand health, 2007). As we obtained a small proportion (fewer than 2%) of the total sample in the “excellent” category, “excellent” and “very good” were combined and used as the reference 175

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R.M. Gyasi, D.R. Phillips

category, compared with “good”, “fair” and “poor” in our analysis.

representing the age groups 50–69, 70–79 and 80 or more years, respectively. Education reflected two schooling levels: up to basic = 1, secondary or higher = 2. Gender (men = 0, women = 1), residential status (rural living = 0, urban living = 2) and income level (lower (less than 500 Cedis) = 0, higher (500+ Cedis) = 2) were dummy variables.

2.2.3. Moderator 2.2.3.1. Marital status. was used as a moderating variable in this analysis. Marital status was collected using a four-level measure comprising of currently married = 1, widowed = 2, divorced/ separated = 3 and never married = 4. These were later collapsed and dichotomised into married/partnered = 0 and not married/not partnered = 1 for analytical purposes. The reason being that participants who were not married as of data collection period including widowed, divorced/separated and never married in the context of this study shared similar characteristics of not receiving any spousal support for health and healthcare. These categories were therefore treated as singles.

2.2.4.6. Social support. Two important social support variables were used. Frequency of contact with family/close friends and social participation. Participation in social events involved four activities: attendance at religious services, a social club at a senior center, regular sports or cultural clubs, and civic or political organizations. The responses to the two items were given on a five-point scale ranging from 1 = never, 2 = less frequently, 3 = frequently, 4 = very frequently, to 5 = almost every day, which were later averaged to create an index score for social support.

2.2.4. Covariates Despite the view that the attention of this article is on the association of SRH and FD, it was significant to control for other theoretically relevant demographic, socioeconomic and health-related and lifestyle variables to assure reliability of the findings.

2.3. Analytical plan First, bivariate comparisons of data between selected sociodemographic characteristics and health-related variables by gender, SRH and respondents’ FD status were examined with χ2 and Fisher’s exact tests, given the categorical nature of variables. Second, a series of multivariate logistic regression models were built in which FD levels as outcome variable was regressed upon the exposure variables. In Model 1, we calculated the crude odds ratio (OR) entering SRH only as an independent variable. In Model 2, we estimated adjusted OR by entering sociodemographic and health-related variables to investigate whether SRH statuses explain differences in FD entirely. Whilst Model 3 added social support variable, the interaction term (SRH × marital status) was added in the full model (Model 4) to test whether the effects of SRH on FD varied significantly by marital status. Separate genderedstratified analyses were conducted to examine the role of gender in the SRH and FD association. Analyses were conducted using IBM-SPSS for Windows application (version 21.0; IBM SPSS Inc., Chicago, USA) Software and the level of significance was p ˂ 0.05 (two-tailed). Regression diagnostic statistic judged the goodness-of-fit of the model via the Nagelkerke R2 and Hosmer-Lemeshow model fit test.

2.2.4.1. Psychological distress. This was assessed by composite sevenitem questions measuring the psychological health and depressive symptomatology of the participants on a range of health complaints adapted from the Kessler Psychological Distress Scale (KPDS)-(K6) (Kessler et al., 2002). Sample items included “In the last 30 days about how often did you feel…‘happy’, “sad or depressed”, “nervous or uneasy”, “restless or fidget”, “bored”, “hopeless”, “lonely” and “worthless” or “having no value”. Respondents rated the items on a four-point response scale, 1 = “None of the time”, 4 = “All of the time”. Cronbach’s alpha of the scale was 0.88. Being happy was included and the response categories were then reverse-coded. All items were summed to create an index score for psychological distress with total score 7–28. A score of 7–14 was considered 1 = “not distressed” and 14–28 as 2 = “distressed”. 2.2.4.2. Comorbid conditions and multi-morbidity. Self-reports of diagnosis of ten (10) chronic diseases by a health professional was considered for comorbidity/multi-morbidity. These included hypertension, diabetes, respiratory diseases, cancers, stroke, chronic kidney diseases, asthma, arthritis, depression and insomnia. Also, sleep problems were assessed with one item: ’overall in the last 30 days, how much of a problem did you have with sleeping such as falling asleep unintendedly, waking up frequently during the night or waking up too early in the morning?’ A four-point response scale was used: 1 = “None”, 4 = “Extreme”. A summary measure was created by averaging the responses.

3. Results Table 1 shows the baseline characteristics of the respondents. Compared with men, women were less likely to have socio-cultural and economic resources, such as being married, being educated and having higher incomes respectively, and also being physically active. In terms of health, overall, men rated their health better compared with women (Fisher’s exact test, p < 0.001): 29% of men evaluated their SRH as very good, 31% as good, 26% as fair and 15% as poor. By contrast, women’s responses were 15%, 31%, 31% and 24% respectively. More women than men reported comorbidity/multi-morbidity (57% vs 46%, p < 0.001), extreme sleep problems (31% vs 23%, p < 0.005) and psychological distress (50% vs 38%, p < 0.001). Of interest, 101 (23%) men and 261 (34%) women revealed significant levels of FD (p < 0.001). Table 2 represents participants’ characteristics by SRH categories. Participants who reported poor SRH tended to be older, women, were not married, generally of lower socioeconomic status, and also receiving lower social support. Moreover, this group suffered from higher number of chronic diseases, had extreme sleep problem, reported FD, and were psychologically distressed, with p < 0.001 for all associations. Table 3 shows that the distribution of FD is significantly and directly related to health-related variables and this trend was similar across males and females. However, certain key gender disparities were found. Compared with men, women who experienced FD reported poorer health status generally. For example, poor SRH (42% vs 40%), chronic conditions (77% vs 69%), psychological distress (61% vs 55%), extreme sleep problems (38% vs 36%) and physically inactivity (84% vs 68%)

2.2.4.3. Physical activity. was assessed with items: ‘how often do you engage in activities that require a moderate level of energy such as gardening, cleaning the car, or doing a walk?’, ‘What type and amount of physical activity you do in your daily life’ and ‘How often do you engage in vigorous physical activity, such as sports, heavy housework, or a job that involves physical labor?’ These questions had as possible responses: ‘More than once a week’, ‘once a week’, ‘One to three times a month’ and ‘hardly ever, or never’. Physical inactivity was defined as never or almost never engaging in moderate or vigorous physical activity through the response of ‘One to three times a month’ and ‘Hardly ever, or never’ to both questions. 2.2.4.4. Alcohol intake. Respondents were asked to indicate on a no/ yes response scale if they consumed any drink that contains alcohol such as beer, hard wine, spirit, over the past 30 days. 2.2.4.5. Sociodemographic variables. Older age was categorised into three groups: younger olds, older-olds, and oldest-old persons, 176

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intervals are reported. For women (Table 5), the unadjusted model (Model 1) indicates that the odds of reporting FD among good, fair and poor SRH were 117%, 284% and 1027% respectively, compared with participants reporting very good/excellent SRH. The results in Model 2 suggest that the risk of becoming functionally impaired among women who reported fair and poor SRH reduced to 16% and 432% respectively but remained statistically significant after adjusting for socioeconomic and health-related variables. Entering the social network variable in Model 3, the odds of FD for fair and poor SRH women were statistically robust and increased slightly to 17% and 448% respectively. Finally, Model 4 shows significant interactions between SRH and marital status. Married women reporting good, fair and poor SRH were (83%, 94% and 88% respectively) were less likely to report FD compared with unmarried who reported excellent/very good SRH. Being married reduces the strength of the positive association between sub-optimal SRH and FD (see Figs. 1–3). Table 6 reveals broadly similar patterns of SRH status and FD relationships for older men. However, importantly, older men had a higher likelihood to report FD than women. For example, after controlling for all covariates in Model 3 (similar to results from Models 1 and 2), men with fair and poor SRH were 804% and 955% more likely to be functionally impaired compared with those reporting excellent/ very good SRH. Our results in the full model (Model 4) somewhat showed insignificant interactions between SRH and marital status for men.

Table 1 Baseline characteristics of the sample by gender (n = 1200). Total

Female

Male

N

(%)

n

(%)

n

(%)

χ2

769 253 178 660 521 166

(64.1) (21.1) (14.8) (55.0) (43.4) (13.8)

480 160 119 430 218 62

(63.2) (21.1) (15.7) (56.7) (28.7) (8.2)

289 93 59 230 303 104

(65.5) (21.1) (13.4) (52.2) (68.7) (23.6)

1.223

2.281 181.534*** 55.599***

264 377 606 729

(25.3) (31.4) (50.5) (60.8)

123 142 336 464

(19.0) (18.7) (44.3) (61.1)

141 235 270 265

(35.4) (53.3) (61.2) (60.1)

35.003*** 154.792*** 32.080*** 0.127

636 544

(53.0) (45.3)

435 378

(57.3) (49.8)

201 166

(45.6) (37.6)

15.418*** 16.645***

336

(28.0)

234

(30.8)

102

(23.1)

8.205**

239 369 348 244

(19.9) (30.8) (29.0) (20.3)

113 234 233 179

(14.9) (30.8) (30.7) (23.6)

126 135 115 65

(28.6) (30.6) (26.1) (14.7)

39.011***

Functional decline status Not decline 838 Decline 362

(69.8) (30.2)

498 261

(65.6) (34.4)

340 101

(77.1) (22.9)

17.465***

Age (years) Younger olds Older olds Oldest olds Urban residence Married/partnered Schooling above basic Higher incomes Current alcohol use Physically active Social support networks Chronic conditions Psychologically distressed Extreme sleep problems Self-rated health Very good Good Fair Poor

4. Discussion and conclusions This study provides novel insights into gender differentials in the relationship between SRH and FD among community-dwelling older cohorts in Ghana and considers whether the effect is moderated by marital status. This is the first sub-Saharan African study we can find to present a gender-based investigation of the association between SRH and FD, utilizing a representative sample of older people with diverse demographic and socioeconomic characteristics. Overall, our study found an FD prevalence of 30.2% with significant gender differences. Over 11% older women than men reported FD in our sample. This finding is not entirely surprising owing to the view, that public health researchers and epidemiologists have long noted that women live longer on average and therefore may suffer greater health challenges generally and FD outcomes specifically than their men counterparts (McCracken & Phillips, 2017; WHO, 2015) since old age positively

***p < 0.001; **p < 0.005. Younger olds = 50–69 years; Older olds = 70–79 years; Oldest old = 80 + years.

were significantly reported by women and men respectively. Conversely, women with FD were less likely to report alcohol intake, spousal cohabitation and higher socioeconomic conditions than their men counterparts. Correlations between variables are presented in Table 4. Multivariate logistic models of FD estimating the independent contribution of the exposure variables are presented in Table 5 (older women) and Table 6 (for older men). The estimates were stratified by gender to investigate how gender and SRH status might combine to influence the incidence of FD in late life. The unstandardized logistic coefficients, odds ratios and the lower-upper bound 95% confidence Table 2 Baseline characteristic by categories of SRH among study participants (n = 1200). Total

Very good

Good

Fair

Poor

N

(%)

n

(%)

n

(%)

n

(%)

n

(%)

χ2

Age (years) Younger olds Older olds Oldest olds Female gender Urban residence Married/partnered Schooling above basic Higher incomes Current alcohol use Physically active Chronic conditions Psychologically distressed Extreme sleep problems Social support networks

769 253 178 759 660 521 599 264 377 606 636 544 336 887

(64.1) (21.1) (14.8) (63.3) (55.0) (43.4) (49.9) (25.3) (31.4) (50.5) (53.0) (45.3) (28.0) (73.9)

193 30 16 113 113 142 167 87 116 174 80 84 39 181

(80.8) (12.6) (6.7) (47.3) (47.3) (59.4) (69.9) (40.1) (48.5) (72.8) (33.5) (35.1) (16.3) (75.7)

233 85 51 234 218 170 174 84 86 208 196 122 71 292

(63.1) (23.0) (13.8) (63.4) (59.1) (46.1) (47.2) (26.1) (23.3) (56.4) (53.1) (33.1) (19.2) (79.1)

224 75 49 233 193 125 170 53 94 163 211 172 107 258

(64.4) (21.6) (14.1) (67.0) (55.5) (35.9) (48.9) (17.2) (27.0) (46.8) (60.6) (49.4) (30.7) (74.1)

119 63 62 179 136 84 88 40 81 61 149 166 119 156

(48.8) (25.8) (25.4) (73.4) (55.7) (34.4) (36.1) (20.3) (33.2) (25.0) (61.1) (68.0) (48.8) (63.9)

60.358***

Functional decline status Not decline Decline

838 362

(69.8) (30.2)

218 21

(91.2) (8.8)

300 69

(81.3) (18.7)

226 122

(64.9) (35.1)

94 150

(38.5) (61.5)

***p < 0.001; **p < 0.005; *p < 0.05. Younger olds = 50–69 years; Older olds = 70–79 years; Oldest old = 80 + years. 177

39.011*** 8.318* 41.946*** 58.088*** 38.515*** 47.265*** 117.980*** 51.097*** 85.511*** 83.738*** 18.236*** 192.380***

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R.M. Gyasi, D.R. Phillips

Table 3 Baseline characteristics of the sample with functional decline status (N = 1200). Total

Not decline

N

(%)

n

Decline (%)

n

(%)

χ2

For Females (n = 759) Age (years) Younger olds Older olds Oldest olds Urban residence Married/partnered Schooling above basic Higher incomes Current alcohol use Physically active Chronic conditions Psychologically distressed Extreme sleep problems Social support networks

480 160 119 430 218 278 123 142 336 435 378 234 573

(63.2) (21.1) (15.7) (56.7) (28.7) (36.6) (19.0) (18.7) (44.3) (57.3) (49.8) (30.8) (75.5)

366 89 43 281 169 220 96 107 295 233 220 134 399

(73.5) (17.9) (8.6) (56.4) (33.9) (44.2) (22.6) (21.5) (59.2) (46.8) (44.2) (26.9) (80.1)

114 71 76 149 49 58 27 35 41 202 158 100 174

(43.7) (27.2) (29.1) (57.1) (18.8) (22.2) (12.2) (13.4) (15.7) (77.4) (60.5) (38.3) (66.7)

76.978***

Self-rated health Very good Good Fair Poor

113 234 233 179

(14.9) (30.8) (30.7) (23.6) For Males (n = 441)

99 179 151 69

(19.9) (35.9) (30.3) (13.9)

14 55 82 110

(5.4) (21.1) (31.4) (42.1)

94.702***

Age (years) Younger olds Older olds Oldest olds Urban residence Married/partnered Schooling above basic Higher incomes Current alcohol use Physically active Chronic conditions Psychologically distressed Extreme sleep problems Social support networks

289 93 59 230 303 321 141 235 270 201 166 102 314

(65.5) (21.1) (13.4) (52.2) (68.7) (72.8) (35.4) (53.3) (61.2) (45.6) (37.6) (23.1) (71.2)

251 56 33 178 248 265 115 182 238 131 110 66 258

(73.8) (16.5) (9.7) (52.4) (72.9) (77.9) (36.7) (53.5) (70.0) (38.5) (32.4) (19.4) (75.9)

38 37 26 52 55 56 26 53 32 70 56 36 56

(37.6) (36.6) (25.7) (51.5) (54.5) (55.4) (30.6) (52.5) (31.7) (69.3) (55.4) (35.6) (55.4)

45.551***

Self-rated health Excellent/Very good Good Fair Poor

126 135 115 65

(28.6) (30.6) (26.1) (14.7)

119 121 75 25

(35.0) (35.6) (22.1) (7.4)

7 14 40 40

(6.9) (13.9) (39.6) (39.6)

97.624***

0.031 19.229*** 35.561*** 10.145*** 7.344** 131.514*** 65.574*** 18.333*** 10.448*** 16.755***

0.023 12.376*** 19.895*** 1.106 0.035 48.157*** 29.737*** 17.691*** 11.539*** 15.861***

***p < 0.001; **p < 0.005. Younger olds = 50–69 years; Older olds = 70–79 years; Oldest old = 80 + years. Table 4 Correlation matrix for study variables.

1. Functional decline status 2. Self-rated health 3. Age 4. Gender 5. Residence 6. Marital status 7. Education 8. Income 9. Alcohol use 10. Physical activity levels 11.Chronic diseases 12. Psychological distress 13. Sleep problems 14. Social support network

M ± SD

1

2

3

4

5

6

7

8

9

10

0.30

–

2.49 1.51 0.39 0.55 1.43 1.51 1.25 0.31 0.51

0.39** 0.32** −0.12** 0.07 −0.20** −0.24** −.12** −0.10** −0.40**

– 0.20** −0.17** 0.04 −0.18** −0.19** −.17** −0.08** −0.31**

– −0.30 −0.07* −0.22** −0.34** −.23** −0.10** −0.27**

– −0.04 0.39** 0.35** 0.18** 0.36** 0.16**

– 0.07* 0.03 0.19** −0.02 −0.08**

– 0.25** 0.18** 0.08** 0.26**

– 0.20** 0.22** 0.12**

– 0.4 1.3**

– −0.01

–

0.53 0.55

0.29** −0.18**

0.18** −0.24**

0.10** −0.05

−0.11** 0.12**

0.06* 0.03

−0.09** 0.19**

−0.09** 0.11**

−0.02** 0.05

−0.07* 0.01

1.28 0.74

0.14** −0.16**

0.25** −0.10**

0.05 −0.07*

−0.08** −0.05

−0.02 0.05

−0.10** 0.08**

−0.10** 0.02

−0.13** 0.03

−0.05 −0.04

**p < 0.005; *p < 0.05. Younger olds = 50–69 years; Older olds = 70–79 years; Oldest old = 80 + years.

178

11

12

−0.19** 0.16**

– −0.10**

–

−0.17** 0.19**

0.05 −0.07*

−0.14** 0.11**

13

– −0.04

179

−440.399 1.000 (0.961) 0.295

0.776* 1.346*** 2.422***

2.173 3.840 11.273

1.150−4.104 2.064−7.145 5.971−21.282 1.582 4.165 1.027 0.956 0.457 0.661 0.608 0.153 5.096 1.330 1.036

0.459 1.427*** 0.027 −0.045 −0.782** −0.414 −0.497 −1.877*** 1.629*** 0.285 0.035

−266.264 8.511(.385) 0.510

0.833 1.160 5.322

OR

−0.183 0.148* 1.672***

β

95%C.I

β OR

Model 2c

Model 1

0.918−2.729 2.246−7.725 0.655−1.610 0.574−1.592 0.278−0.752 0.360−1.215 0.344−1.075 0.093−0.251 3.103−8.370 0.856−2.067 0.643−1.668

0.382−1.816 1.547−2.462 2.435−11.629

95%C.I

−265.789 10.290(0.245) 0.511

0.472 1.432*** 0.047 −0.030 −0.777** −0.415 −0.480 −1.845*** 1.626*** 0.254 0.033 −0.242

−0.141 0.160* 1.700***

β

Model 3d

1.604 4.187 1.048 0.970 0.460 0.660 0.619 0.158 5.081 1.289 1.034 0.785

0.869 1.173 5.476

OR

0.928−2.773 2.257−7.768 0.667−1.646 0.582−1.616 0.279−.757 0.359−1.213 0.350−1.094 0.096−0.260 3.086−8.367 0.826−2.013 0.642−1.666 0.483−1.276

0.396−1.903 1.552−2.495 2.498−12.005

95%C.I

0.172 0.061 0.124

−1.760* −2.800*** −2.088* −259.965 4.903(0.768) 0.527

1.562 4.214 1.112 1.233 0.460 0.542 0.590 0.143 5.546 1.285 0.962 0.781

0.673 0.649 4.033

OR

0.446 1.438*** 0.107 0.209 −0.776** −0.612† −0.527† −1.942*** 1.713*** 0.251 −0.038 −0.248

−0.396 −0.432 1.395***

β

Model 4e

***p < 0.001; **p < 0.005; *p ˂ 0.05; † p ˂ 0.1. a Excellent/very good is the reference category for the SRH variable. b Younger olds is the reference category for age variable. c Adjusted for age, residence, marital status, schooling level, income level, alcohol consumption, physical activity levels, chronic conditions, psychological distress and sleep problems. d All variables in Model 2 plus social support network variable. e All variables in Model 3 plus the interaction term (SRH × Marital status).

Self-rated health (SRH) Gooda Fair Poor Age (years) Older oldsb Oldest olds Urban residence Married/partnered Schooling above basic Higher incomes Current alcohol use Physically active Chronic conditions Psychologically distressed Extreme sleep problems Social support networks SRH × Marital status Good × Married Fair × Married Poor × Married Model fitting information Log-likelihood Hosmer-Lemeshow χ2 Nagelkerke Pseudo-R2

Variables

Table 5 Logistic regression (ORs and 95% CI) for the association of functional decline among older women

0.035−0.840 0.012−0.312 0.025−0.616

0.891−2.739 2.237−7.936 0.701−1.766 0.722−2.105 0.278−0.763 0.289−1.018 0.332−1.050 0.086−0.239 3.330−9.238 0.811−2.036 0.589−1.572 0.474−1.286

0.303−1.498 0.282−1.494 1.805−9.012

95%C.I

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180 −129.310 5.626(0.689) 0.498

4.685 1.603 0.618 0.709 0.325 2.025 0.747 0.282 2.914 1.811 0.878 0.346

1.036 9.041 10.549 2.120–10.356 0.556–4.620 0.303–1.262 0.352–1.429 0.145–0.729 1.939–4.365 0.373–1.498 0.142–0.561 1.491–5.693 0.920–3.564 0.428–1.800 0.167–0.717

0.352−3.046 3.148−25.961 3.604−30.875

−0.116 2.159*** 2.359***

***p ˂ 0.001; **p ˂ 0.005; *p ˂ 0.05; † p ˂ 0.1. a Excellent/very good is the reference category for the SRH variable. b Younger olds is the reference category for age variable. c Adjusted for age, residence, marital status, schooling level, income level, alcohol consumption, physical activity levels, chronic conditions, psychological distress and sleep problems. d All variables in Model 2 plus social support network variable. e All variables in Model 3 plus the interaction term (SRH × Marital status).

−133.431 6.420(0.600) 0.476

1.544*** 0.472 −0.481 −0.344 −1.124** 0.705* −0.291 −1.266*** 1.069** 0.594 −0.130 −1.061**

0.035 2.202*** 2.356***

β

0.891 8.659 10.575

OR

−127.574 4.903(0.768) 0.507

−189.618 2.100 (0.730) 0.295

1.754–7.817 0.539–4.108 0.322–1.294 0.343–1.366 0.151–0.722 0.887–4.004 0.414–1.605 0.113–0.433 1.402–5.120 0.890–3.293 0.407–1.672

0.417−3.583 3.245−26.250 4.619−38.174

95%C.I

Model fitting information Log-likelihood Hosmer-Lemeshow χ2 Nagelkerke Pseudo-R2

3.703 1.488 0.645 0.685 0.330 1.884 0.815 0.221 2.679 1.712 0.825

1.222 9.229 13.278

OR

4.502 1.503 0.782

1.309*** 0.398 −0.438 −0.379 −1.108** 0.634 −0.204 −1.510*** 0.986** 0.538 −0.192

0.200 2.222*** 2.586***

β

1.505 0.407 −0.246

0.767−5.045 3.862−21.285 10.933−67.672

95%C.I

Model 4e

4.614 1.606 0.626 0.701 0.336 2.053 0.748 0.243 2.845 1.820 0.865 0.375

1.967 9.067 27.200

OR

Model 3d

1.529*** 0.474 −0.469 −0.355 −1.091** 0.719* −0.291 −1.416*** 1.046 0.599 −0.145 −0.982**

0.676 2.205*** 3.303***

β

95%C.I

β OR

Model 2c

Model 1

Age (years) Older oldsb Oldest olds Urban residence Married/partnered Schooling above basic Higher incomes Current alcohol use Physically active Chronic conditions Psychologically distressed Extreme sleep problems Social support networks SRH × Marital status Good × Married Fair × Married Poor × Married

Self-rated health (SRH) Gooda Fair Poor

Variables

Table 6 Logistic regression (ORs and 95% CI) for the association of functional decline among older men.

0.500–40.556 0.200–11.297 0.087–6.991

2.095–10.161 0.535–4.823 0.306–1.280 0.335–1.465 0.148–0.761 1.945–4.463 0.369–1.514 0.119–0.496 1.435–5.643 0.909–3.646 0.411–1.820 0.179–0.786

0.293−2.713 2.983−25.134 3.478−32.154

95%C.I

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men than women. These gender differences seem to be in line with the social epidemiologic thesis which proposes that men more frequently report fatal and functionally-related disabilities which often warrant hospitalization, specialty care and emergency services use compared with women (Cameron, Song, Manheim, & Dunlop, 2010; Wang, Hunt, Nazareth, Freemantle, & Petersen, 2013). The implications are that health- and social-care systems should be strengthened and provide a more specialized care for especially older men in order to maintain their functional independence. Like many other sub-Saharan African communities, meaningful intergenerational informal social support which is culturally known to offer instrumental and emotional support to older people in Ghana could also be relied upon to provide the needed support and social care for older persons (Apt, 2013, 2002; van der Geest, 2016). Moreover, our results showed a reduction in the association between SRH and FD among older women, taking into account the sociodemographic and health-related covariates. The indication is that becoming functionally impaired among older women with fair and poor SRH is partly linked with the background and other health characteristics including chronic diseases and psychological distress level. Unlike women, among older men, social support also influenced the association between SRH and FD. We found that the adjustment for our measure of social support in Model 3 significantly reduced the risk of FD by 2.04% and 20.55% for older men who reported fair and poor SRH respectively. This observation relates well with our bivariate findings in which participants who indicated better SRH were more likely to receive social support, as reported in some earlier studies (Tomioka et al., 2017; van der Geest, 2016). Studies have also noted that various social support networks may potentially alleviate FD (Stoeckel & Litwin, 2016) and therefore the effect of SRH on FD may be mediated by social support, possibly in a manner similar to the role of informal social support on older adults psychological wellbeing (Phillips, Siu, Yeh, & Cheng, 2008) One key finding of our analysis revealed among women (but not men) the significant role of marital status when considering the SRH and FD associations. Older people’s marital status significantly interacted with SRH: being married dampens the positive associations between poor and fair SRH statuses and FD among women. Married older women who perceived deteriorating health status correspondingly had lower odds of reporting FD in relation to their unmarried counterparts, even among those with excellent/very good SRH. These findings suggest that marriage, which may provide a sense of cohesion, security and coping resource for women, could potentially offset stress in later life and moderate the incidence of FD among non-institutionalized older women. Generally, stress factors do have a substantial effect on SRH (Lee, Song, Yang, & Kang, 2015; Zhang & Hayward, 2006). This implies that various stressful life events such as marital loss, which could occur through death of spouse, divorce or prolonged marital separation (Bulanda et al., 2016; Unger, Johnson, & Marks, 1997), and the associated psychological distress (Saevareid, Thygesen, Nygaard, & Lindstrom, 2007) can lead to or perhaps precipitate FD in older women. Moreover, the fact that no significant interactions were found between SRH and marital status for older men points to the view that whilst marital quality provides considerable protection for older women against the incidence of FD, it offers only a limited mechanism to link SRH and FD for older men. However, further research employing qualitative approaches is needed to explain these relationships as they may seem counter-intuitive in terms of the often-cited view of the positive role of marriage on older men’s health (Bulanda et al., 2016; Lee et al., 2015). We note several limitations of this study. First, the cross-sectional data gathering design may limit our findings to correlational inferences as opposed to cause-and-effect statements and limits our ability to draw generalizations. Moreover, long-term accounts of the effect of SRH on FD among older cohorts cannot be established. However, the findings of the present study are not only consistent with those found in previous

Fig. 1. Being married dampens the positive relationship between poor SRH and FD compared with excellent/very good SRH in women.

Fig. 2. Being married dampens the positive relationship between fair SRH and FD compared with excellent/very good SRH in women.

Fig. 3. Being married dampens the positive relationship between good SRH and FD compared with excellent/very good SRH in women.

correlates with poor health. Older women in Ghana appear to be no exception. This finding suggests several social and public health implications for viable strategies to ensure gendered equity rather than equality in healthcare provision and the engagement in moderate levels of physical activity among older people particularly women in LAMICs. This potentially may prevent increased levels of disability and mortality (DiPietro, 2001; Whisman et al., 2016). The relationship between SRH and FD was clearly established by our evidence showing that older persons who perceived suboptimal health status, including poor and fair SRH levels, were significantly more likely to report FD compared with those reporting excellent/very good SRH, in both crude and fully-controlled models. The odds of reporting FD increased with reports of deteriorating SRH. This finding is consistent with some older observations and also more recent reports in more advanced settings including Japan (Tomioka et al., 2017) and in selected European countries (Stoeckel & Litwin, 2016) on the associations between SRH and FD decline. Although this relationship was seen across both genders, the effect was substantially greater among older 181

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longitudinal studies but could also potentially be repeated over time. Finally, the use of self-reported assessments of SRH, FD and the healthrelated variables could potentially expose our result to the risk of a number of social and subjective biases which could, in turn, affect the accuracy of the responses either through underestimation, overestimation or generally faulty recall. Despite these limitations, efforts were made to minimize potential measurement errors in the assessment of outcome and exposure variables through quality control mechanisms. In addition, the data for this study drew on a large, representative sample drawn through a careful multi-stage sampling approach which also included rural and urban characteristics and therefore allowed for more confident interpretation of the findings. Finally, the four-stage gender-based multivariate modeling recognized and hopefully helped to avoid confounding conditions which could potentially distort study inferences. Our findings are interesting and novel in a lower-income country. They underscore the importance of SRH for functional status and the likelihood of FD in later life. Although the findings provide some evidence to suggest that SRH is a strong and independent predictor of FD among non-institutionalized older cohorts, the associations have some gender differences and also show some influence of marital status for women in particular. Thus, respondents with poor or fair SRH who were married reported lower levels of FD than the unmarried with even excellent/very good SRH status. Overall, we propose that the SRH of older people has a critical effect on FD and thereby on the extent of later life functional independence and wellbeing. An important practical and policy implication is that improving SRH in older age could effectively maintain, or perhaps slow decline in functional abilities and quality of life of often vulnerable older men and women. Moreover, marital status has demonstrated a buffering effect in the relationships between SRH and FD, especially for older women.

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