Association of Health Literacy and Socioeconomic Status with Oral Health Among Older Adults in Ghana: A Moderation Analysis of Social Capital

Abstract

We examined the moderating role of social capital (SC) in the association of socioeconomic status (SES) and health literacy (HL) with oral health (OH) status and the intentions to use OH services (IUOHS) among older Ghanaians. Data were derived from a cross-sectional survey (n = 522) and analyzed using ordinal and binary logistic regressions. Bridging SC moderated the relationship between HL and oral health status (B = 0. 0.117, p < .05) and the association of SES with IUOHS (adjusted odds ratio [AOR] = 1.144; 95% confidence interval [CI] = [1.027, 3.599]). Trust modified the association between HL and IUOHS (AOR = 1.051; 95% CI = [1.014, 3.789]). Bonding SC moderated the association between SES and oral health status (B = 0.180, p < .05). However, bonding SC negatively modified the association between SES and IUOHS (AOR = 0.961; 95% CI = [0.727, 0.997]). Cognitive and structural SC modify the associations of SES and HL with OH and IUOHS.

Keywords

oral health oral health services social capital socioeconomic status health literacy older persons Ghana

Introduction

The rise in noncommunicable diseases (NCDs) among older persons in low- and middle-income countries (LMICs), such as Ghana, is considered a major public health challenge (Gyasi & Phillips, 2020; World Health Organization [WHO], 2015). While attention is given to NCDs such as cardiovascular diseases, respiratory diseases, cancers, and diabetes, very little is known about conditions relating to oral health in LMICS. Yet, oral health causes ill-health and disability among more than 400 million people in Africa (WHO, 2021). Oral health describes the “state of being free from mouth and facial pain, tooth infection and decay, tooth loss, and other diseases and disorders that limit an individual’s capacity in biting, chewing, smiling, speaking, and psychosocial wellbeing”(WHO, 2021). Poor oral health, such as dental caries and periodontal disease, negatively affects the cognitive and physical functioning of affected people (Everaars et al., 2021; WHO, 2021). Crucially, oral health problems are common among older persons because of a lifetime of exposure to socioenvironmental health determinants (Petersen & Ogawa, 2018; WHO, 2021). Older persons are more likely to have periodontal disease and are less likely to use dental health services than the general population, which leads to poor oral health outcomes (Petersen et al., 2010; Petersen & Ogawa, 2018; WHO, 2021). Hence, a study of older Ghanaians identified oral health problems as a leading cause of morbidity (Ayernor, 2012).

Ecological and micro-level factors such as low access to oral health services and materials, health knowledge, social support, and personal hygiene signal inequalities in oral health outcomes (Marmot & Bell, 2011; Petersen & Ogawa, 2018). Correspondingly, factors such as socioeconomic status (SES) and health literacy (HL) are considered fundamental determinants of oral health outcomes and behaviors (Petersen & Kwan, 2011; Silva-Junior et al., 2020). SES is characterized by people’s income, social standing, employment, and educational attainment (Adler & Newman, 2002). The relationship between SES and health can be explained by Fundamental Cause Theory, which posits that higher SES—usually with superior access to tangible and intangible resources—enables people to avoid diseases and preventable deaths in a variety of ways (Phelan et al., 2010). People of high SES can access information and services that are necessary to improve their oral health (Petersen & Kwan, 2011; Sisson, 2007).

Likewise, sufficient HL has a positive effect on oral health outcomes and behavior of older persons (Silva-Junior et al., 2020; Ueno et al., 2013). HL refers to “the cognitive and social skills which determine the motivation and ability of individuals to gain access to, understand, and use information in ways which promote and maintain good health” (Nutbeam, 1998, p. 357). Paasche-Orlow and Wolf (2007) theorize a causal relation between HL and health outcomes. Sufficient HL is associated with an increased likelihood of better oral hygiene, such as tooth brushing and regular dental checkups, which lead to better oral health status (Ueno et al., 2013).

Despite the important role of SES and HL on oral health outcomes and behaviors, extant research in LMICs has not adequately explored the influence of other sociophysical factors (e.g., social support and access to health care) on the roles played by SES and HL (Aida et al., 2011; Rouxel et al., 2015). Therefore, this study examines the moderating role of structural (bonding and bridging) and cognitive (trust) social capital (SC) in the association of SES and HL with oral health status and the intention to use preventive oral health services among older persons in Ghana.

Social Capital, Socioeconomic Status, Health Literacy, and Oral Health

SC refers to various kinds of support such as information, instrumental support (e.g., money), and emotional support that people derive from different social and organizational relationships and have consequences for individuals and the groups involved (Putnam, 2000). SC has two primary components: one is structural and the other is cognitive. The structural component represents the resources from observable social relationships, such as bonding SC (e.g., families and close friends) and bridging SC (i.e., weak relationships such as a friend of a friend, neighbors, and people in other communities/towns) (Harpham et al., 2002; Putnam, 2000). The cognitive component of SC captures critical but unobservable aspects, such as trust—mutual faithfulness and obligation, which are the foundation of social relationships (Lewis & Weigert, 1985; Putnam, 2000). Overall, SC possesses the capacity to modify health outcomes directly and indirectly (Amoah, 2017; Rouxel et al., 2015).

Existing evidence indicates that bonding SC is associated with fewer dental caries, less edentulism (loss of teeth), a lower incidence of periodontal diseases, and increased use of curative and preventive oral health services among older persons by boosting their SES and health-related knowledge (Burr & Lee, 2013; Sabbah et al., 2011). Bonding SC can attenuate the negative effect of SES on health status (Uphoff et al., 2013). However, bridging SC may be more influential for health as it introduces new resources relative to those provided by bonding SC. Research among older persons in Japan shows that bridging SC has beneficial effects on dental health even among disadvantaged groups (Aida et al., 2009). Notwithstanding, SC does not always affect the impact of SES on older persons’ dental health (Aida et al., 2011), which is why cross-context evidence is critical to understanding the effect of SES on oral health.

Moreover, both bonding and bridging SC may buffer the effects of low HL on access to dental care (Patrick et al., 2006). Illiterate people (including many older persons) habitually rely on both their strong and weak social ties to access and apply relevant health information (Amoah, 2017; Amoah & Phillips, 2017), although evidence of oral health outcomes derived from this dependence in LMICs is almost nonexistent. However, the extent to which bonding and bridging SC affect health-related knowledge, decisions, and behaviors depend on the level of trust (Amoah et al., 2018; Amoah & Phillips, 2017). Trust is positively associated with the oral health of older persons (Aida et al., 2011). Therefore, SC can affect oral health by minimizing the undesirable effects of low SES and HL through increased access to health services and diffusion of essential health-related knowledge (Aida et al., 2011; Paasche-Orlow & Wolf, 2007; Rouxel et al., 2015). Correspondingly, this study hypothesizes that SES and HL have a positive effect on oral health and the intention to use preventive oral health services, and these relations will be positively modified by the trust, bonding, and bridging forms of SC.

Aging and Conditions of Older Persons in Ghana

The proportion of older persons in Ghana’s population is one of the highest in sub-Saharan Africa, primarily because of rising life expectancy (64 as of 2018) and declining fertility rates (Gyasi et al., 2020; Kpessa-Whyte, 2018). By 2050, about 12% of Ghana’s population will be 60 years and older, up from 6.9% in 2015 (Gyasi et al., 2020). While Ghana has witnessed some improvements in economic circumstances in the past two decades, most older persons remain in abject poverty, experience inadequate access to social services, and are less literate (Kpessa-Whyte, 2018). Despite numerous health challenges (e.g., functional limitations and multi-morbidities) that befall older persons in Ghana (see Gyasi et al., 2020), health interventions such as the National Health Insurance Scheme (NHIS), which is meant to reduce financial barriers to health care, have coverage limitations that exclude many older persons based on age (those younger than 70 years) and disease types (e.g., heart diseases and dental aids are not covered; Wang et al., 2017). In addition, recent financial and administrative challenges with the NHIS have meant that out-of-pocket payments for health care remain high in Ghana, leaving many older persons at the margins of the health system (Kpessa-Whyte, 2018; Wang et al., 2017). Consequently, most older persons rely on their families and other social ties to get by, which substantiates the relevance of investigating the role that SC plays in health outcomes (Gyasi et al., 2020).

Method

Data were drawn from an original cross-sectional survey that explored the relations between social environment and health-related well-being of adults aged 15 years and older in Ghana. The survey was conducted from July to December 2018, and it covered 5 of the then 10 regions in Ghana using a multistage sampling approach for a balanced sample. The regions included Ashanti, Greater Accra, Eastern, Brong Ahafo, and Northern regions. Data were gathered from 29 districts and 128 communities (51 rural and 77 urban areas) across the regions. The regions, districts, and communities were purposively selected to provide a fair representation in terms of socioeconomic, sex, geographical, religious, and ethnic compositions. A systematic sampling technique was used to select participants at household levels.

The sample size was determined for each region using the formula: Ns = (Np)(p)(1 − p) / (Np − 1)(B/C)² +(p)(1 − p), with 95% confidence level, sample error of 0.05, and assumption that 50% of participants will adequately respond to questions (Monette et al., 2008). The Ns = total sample size needed; Np = size of the population; p = proportion expected to answer a certain way; B = acceptable level of sampling error; and C = Z statistic associated with confidence interval. The sample was selected from 3.6 million households (comprising approximately a projected figure of 12.2 million people) across the five regions based on the most recent Ghana Statistical Service report (GSS, 2012). The study included 2,097 participants (representing approximately 0.06% and 0.017% of households and householders), although 1,925 would have sufficed statistically. The sampling process is shown in a flowchart in Supplemental Appendix I.

Following the approaches adopted in previous studies in Ghana (Gyasi et al., 2020), a person from every fifth house in urban areas was interviewed. Due to sparsity and small population sizes of rural areas, a person from every second house was used (and all houses were surveyed in very small villages). The house was used as a basis for selecting participants because households in the same house shared very similar characteristics (see Gyasi et al., 2020). Trained interviewers took various directions in every community to interview people who agreed to participate in the survey from the selected houses.

The questionnaires were distributed proportionally among communities based on the size of the sample frame (i.e., population aged 15 years and older). This case analyzed a subsample of 522 from the broader study involving participants aged 50 years and older. As the WHO (2015) has argued and applied elsewhere (Gyasi et al., 2020), reasons including low life expectancy and early onset of frailty in LMICs make adopting universal chronological age criteria for defining older persons less relevant for LMICs contexts, such as Ghana. The Research Ethics Committee of Lingnan University approved the study protocol (EC-043/1718) and the Council for Scientific and Industrial Research (CSIR), Ghana, provided in-country approval (RPN 005/CSIR-IRB/2018).

Measures

Dependent variables

Oral health status was measured using the one-item global self-rated health question: “How would you rate your oral health in the past 12 months?” The question was accompanied by five Likert-type response options (1 = very poor to 5 = very good). The definition of oral health (see WHO, 2021) was appended to this question to ensure consistent interpretation among participants. This instrument has been used elsewhere (Sanders et al., 2006). Its validity is demonstrated in a recent study whose results suggest a consistency between self-assessed and clinically diagnosed oral health problems among older persons (Everaars et al., 2021).

Intention to use preventive oral health services: Participants were asked “Do you intend to visit the dental clinic within the next 12 months for preventive oral health care including check-up, cleaning, or both?” An affirmative response to this question indicated an intention to access oral health services (ISSP Research Group, 2015).

Independent variables

SES: The MacArthur one-item scale of subjective social status (Adler et al., 1994) was employed to measure SES. Participants rated the state of their social and economic conditions compared to others in their social circles from 1 = low to 10 = high. The construct validity of this instrument has been well-established (Cundiff et al., 2013) and widely applied in previous related studies (Sanders et al., 2006). To ensure the robustness of the analyses in this study, objective indicators of SES such as education, income, and employment status were controlled as was done elsewhere (Nobles et al., 2013).

HL: The study used the Swedish Functional Health Literacy scale to measure HL. The scale ascertains a person’s ability to read and understand health information/instructions (Wångdahl & Mårtensson, 2015). The instrument comprises five items, each rated on a 5-point Likert-type scale (always, often, sometimes, not often, and never). The full instrument is shown in Supplemental Appendix II. The study derived three categories of HL from the responses. Responses to “always” and “often” were categorized as inadequate HL. Also, responses to “sometimes” were categorized as problematic HL; those of “not often” and “never” were merged and treated as sufficient HL (Wångdahl & Mårtensson, 2015). However, in the inferential analysis, a continuous variable derived from the mean score of all responses was used. The scale had a Cronbach’s alpha of .92, indicating high reliability. This instrument has been previously used among young and older populations in Ghana (Amoah, 2019) and produces similar results as other HL instruments such as the comprehensive HL scale (Wangdahl et al., 2014).

Moderator: SC

The three SC proxies (bonding, bridging and trust) were measured using aspects of the Adapted SC Assessment Tool (S-ASCAT; Harpham et al., 2002). For bonding and bridging SC, participants were given several options of relevant social networks for each kind. They were asked to indicate whether they had received support (instrumental, information, and/or emotional) from any of such networks in the past 12 months. The responses were summed to have a score for each SC indicator. Trust was measured with one item; “generally speaking, would you say that people in your communities/neighborhood could be trusted?” The response options were either “yes” or “no” The S-ASCAT instrument is considered one the most appropriate for measuring SC in developing countries (Agampodi et al., 2015).

Covariates

The study controlled several sociodemographic, health, and behavioral variables based on past literature to ensure robust results (Nobles et al., 2013; Petersen & Ogawa, 2018; Sanders et al., 2006). The variables included age, sex, marital status, area of residence, educational attainment, employment status, household size (absolute number), the region of residence, and monthly income (in Ghana Cedi). Health behaviors included health insurance subscription (NHIS) and self-initiated medical examination in the past 2 years. Others included smoking and alcohol consumption frequency (never, once a month, several times a month, several times a week, and daily). Finally, participants rated their overall health status in the past month as “poor,” “fair,” “good,” “very good,” or “excellent.” Supplemental Appendix III provides details of the characteristics of the covariates.

Data Analysis

Descriptive analysis was carried out to summarize the data. This was followed by a Spearman’s rank correlation analysis (Supplemental Appendix IV) to identify potential sociodemographic, health, and behavioral predictors of oral health and the use of preventive oral health services. Two predictive models, each with three steps, were constructed. The first was an ordinal logistic regression model to ascertain the role of SC in the relations between SES, HL, and oral health status. The second model used a binary logistic regression to analyze the relationships between SC, SES, HL, and intention to use oral health services. The first step of the models comprised sociodemographic correlates of oral health and intention to use oral health services, and the second step included the first steps in addition to the behavioral correlates, SC proxies, HL, and SES variables. The third step included the first two steps and the interaction terms of each of the SC proxies with SES and HL. The formula, 50 + 8m (where m is the number of predictor variables), was used to assess whether the models were overfitted (Tabachnick & Fidell, 1996). With 16 predictors in each model, a sample of 178 was considered adequate, but the analyses included 522 cases. Missing values (predominantly among five variables with an average of 2% missing responses) were replaced with the mean of the respective variables. Analyses were performed by SPSS v.25 with statistical significance set at p < .05.

Results

The participants were mainly males (52.7%) with an average age of 61.23 years (Standard deviation, SD =8.81). The majority (41.6%) had never been to school and were married (72.6%). Detailed demographic information is shown in Supplemental Appendix III. From Table 1, approximately 43.6% of older persons considered their oral health as “poor” but about 29.5% of these planned to use preventive oral health care. Only 17.2% had sufficient HL compared to 82.8% with limited HL (inadequate and problematic HL). Supplemental Appendix II shows that most participants indicated “always” or “often” in their response to the HL items. Bonding SC (M = 2.56, SD = 1.19) was higher among the participants compared to bridging SC (M= 1.86, SD = 1.09). The majority (57.9%) perceived their neighbors as trustworthy.

Table 1.

Descriptive Statistics of Variables Included in the Study.

Variable	Mean/valid n (N = 522)	SD/%	Range
SES	4.82	1.98	1–10
Bonding SC	2.56	1.19	0–5
Bridging SC	1.86	1.09	0–5
Trust
Yes	302	57.9	—
No	220	42.1	—
HL
Inadequate	242	46.2	—
Problematic	191	36.6	—
Sufficient	89	17.2	—
Intention to use of preventive oral health services
Yes	154	29.5	—
No	368	70.5	—
Oral health status
Very poor	18	3.5	—
Poor	75	14.3	—
Neither poor nor good	135	25.8	—
Good	217	41.6	—
Very good	77	14.8	—

Note. The full table with other variables is shown in Supplemental Appendix III. HL = Health literacy; SC = social capital; SD = Standard deviation; SES = Socioeconomic Status.

Table 2 shows that SES (B = 0.461, p < .05), HL (B = 0.461, p < .05), and bridging SC (B = 0.234, p < .05) were consistently associated with oral health status in Steps 2 and 3. However, bonding SC was not associated with oral health status. Further analysis showed that the association between HL and oral health status was substantially influenced by bridging SC (B = 0.117, p < .05) and bonding SC positively (B = 0.180, p < .05) moderated the relation between SES and oral health status after adjusting for sociodemographic and behavioral factors (Table 2). Moreover, age, having health insurance, overall health status, and sex were associated with oral health status (Table 2).

Table 2.

The Role of SC in the Relations Between HL, SES, and Oral Health Status by Ordinal Logistic Regression.

Variable	Step 2 (Main effects)		Step 3 (Interaction effects)
Variable	B (95% CI)	Standard error	B (95% CI)	Standard error
Use of preventive oral health	−0.765 [–1.156, −0.373]***	0.200	−0.696 [–1.093, −0.298]***	0.203
Socioeconomic status (SES)	0.237 [0.044, 0.519]*	0.082	0.165 [0.030, 0.539]*	0.049
Health literacy	0.326 [0.166, 0.485]***	0.061	0.461 [0.156, 0.977]*	0.140
Bonding SC	0.318 [–1.014, 0.159]	0.277	0.661 [0.238, 1.215]**	0.267
Bridging SC	0.270 [0.105, 0.435]***	0.086	0.234 [0.049, 0.625]*	0.097
Trust	0.180 [−0.157, 0.517]	0.172	0.507 [−0.070, 1.084]	0.294
Overall health status	0.565 [0.341, 0.789]***	0.114	0.772 [0.535, 1.009]***	0.121
SES × Bonding SC			0.180 [0.045, 0.415]*	0.063
SES × Bridging SC			0.069 [−0.026, 0.165]	0.049
SES × Trust			−0.051 [−0.162, 0.059]	0.057
Health literacy × Bonding SC			−0.009 [−0.037, .018]	0.014
Health literacy × Bridging SC			0.117 [0.039, 0.372]*	0.037
Health literacy × Trust			0.029 [−0.024, 0.082]
Nagelkerke Pseudo R ²	.229		.264

Note. The full table (comprising all three steps) with control variables is shown in Supplemental Appendix V. CI = confidence interval; SC = social capital; SES = Socioeconomic Status.

p < .05. **p < .01. ***p < .001.

In Table 3 (Step 3), SES (adjusted odds ratio, [AOR] = 1.311, 95% confidence interval [CI] = [1.100, 1.563]) and trust (AOR = 1.540, 95% CI = [1.115, 2.741]) were associated with intention to use preventive oral health services. Trust significantly moderated the relations between HL and intention to use preventive oral health services (AOR = 1.051, 95% CI= [1.014, 3.789]). Also, bridging SC enhanced the relations between SES and the intention to use preventive oral health services (AOR = 1.444, 95% CI = [1.027, 3.599]). Bonding SC (AOR = 0.961, 95% CI = [0.727, 0.997]) negatively modified the influenced the association of SES on the intention to use preventive oral health services.

Table 3.

The Role of SC in the Relationships Between Health Literacy, SES, and Use of Preventive Oral Health Service by Binary Logistic Regression.

Variable	Step 2 (Main effects)	Step 3 (Interaction effects)
Variable	Adjusted odds ratio (95% CI)	Adjusted odds ratio (95% CI)
Socioeconomic status (SES)	1.173 [1.026, 1.341]*	1.311 [1.100, 1.563]**
Health literacy	1.035 [0.923, 1.103]	1.088 [1.020, 2.905]*
Bonding SC	0.487 [0.764, 1.137]	1.092 [1.019, 2.052]*
Bridging SC	0.273 [0.714, 1.100]	1.143 [0.938, 1.535]
Trust	1.333 [1.081, 2.392]*	1.540 [1.115, 2.741]*
SES × Bonding SC		0.961 [0.727, 0.997]*
SES × Bridging SC		1.144 [1.027, 3.599]*
SES × Trust		0.996 [0.931, 1.066]
Health literacy × Bonding SC		1.030 [0.949, 1.119]
Health literacy × Bridging SC		1.032 [0.911, 1.169]
Health literacy × Trust		1.051 [1.014, 3.789]*
Nagelkerke Pseudo R ²	.183	.260

Note. The full table (comprising all three steps) with control variables is shown in Supplemental Appendix VI. CI = confidence interval; SES = Socioeconomic Status; SC = social capital.

p < .05. **p < .01.

Discussion

Empirical research on the multidimensional factors associated with older adults’ oral health in LMICs, including Ghana, is scarce. Therefore, this study has filled an important gap in the literature and has significant implications for public health and social policy. The study examined the moderating effect of structural (bonding and bridging) and cognitive (trust) SC on the effect that SES and HL individually have on oral health and the intention to seek preventive oral health services among older persons. To the best of our knowledge, this is the first study to investigate the multidimensional aspects of social determinants of older persons’ oral health outcomes and related behaviors in Ghana by considering their personal resources and elements of their social environment. In support of our hypothesis, both SES and HL were found to have a positive association with oral health and the intention to seek presentive oral health services. These findings are consistent with studies on SES and oral health (Petersen & Kwan, 2011; Sisson, 2007) and HL and oral health and related behaviors (Silva-Junior et al., 2020; Ueno et al., 2013). The findings help to explain the observed poor oral health status and low intention to use preventive oral health services among the participants. Our hypothesis that all types of SC will moderate the individual effect of SES and HL on oral health and the intention to use preventive oral health services was largely supported, albeit with some degree of inconsistency.

First, trust positively moderated the influence of HL on intention to use preventive oral health services. This implies that it is unlikely for the influence of HL to be felt in situations where older persons distrust the health system or communities of support that relay useful health information. This may explain why people with a high sense of trust were more likely to use preventive oral health services in our analysis. Previous research indicates that the public, particularly older persons in Ghana, rely on their informal networks in seeking health care, including decisions about services or facilities to use, and this can often be imputed to high trust in their social networks (Amoah & Phillips, 2017; Gyasi et al., 2020). Indeed, trust is considered a critical element in the functioning of health systems in sub-Saharan Africa, as people take to all sorts of measures to avoid “distrustful” and “poor quality” services (Østergaard, 2015). Many older persons in Ghana are poorly educated (Kpessa-Whyte, 2018). Improving their HL as part of oral health promotion must, therefore, take cognizance of the level of trust in their social environments as such resources can be supportive in achieving planned goals, according to our study. However, even with such understanding, a critical question remains: how to tap into such a resource pool to improve HL? Future research may benefit from understanding the mechanism of trust cultivation regarding health knowledge at community/neighborhood levels and understanding how public health officials can apply similar principles in oral health education in later life.

Second, our study showed that bridging SC had a positive effect on the influence of HL on oral health status. This result answered a primary question raised in the conceptual causal model of HL and health regarding the nature of the effects that elements of SC can have on the association between HL and health outcomes (Paasche-Orlow & Wolf, 2007). Concerning HL, older persons who are well connected with others outside their primary social networks can obtain knowledge from wider sources to explore and apply relevant information to improve oral health due to the diversity of resources offered by bridging SC (Amoah & Phillips, 2017; Putnam, 2000). These opportunities to seek diversified health information partly make up for the deficiencies in older persons’ cognitive functions and illiteracy (Reisi et al., 2012). The moderating role of bridging SC on the relationship between SES and the intention to use preventive oral health services complement the abovementioned explanations, and the finding is consistent with research on general health of older persons (Aida et al., 2011). In Ghana, like many other LMICs, bridging SC helps people to connect with health professionals and other resourceful persons, which can encourage positive oral health behavior (Amoah, 2017, 2018; Petersen et al., 2010). For instance, given the high level of poverty among older persons in Ghana (Kpessa-Whyte, 2018), bridging SC can be a source of instrumental support, such as transport and pecuniary support, which can encourage them to seek preventive care, although this is not always the case (Burr & Lee, 2013). However, as argued elsewhere (Rouxel et al., 2015), the benefits of “weak” social ties may mainly be available to people who already have high SES, which then reinforces class differences in oral health outcomes. The phenomenon of social contagion can also explain the influence of bridging SC. As bridging SC is sometimes located at community/neighborhood levels (Aida et al., 2011), some older persons are likely to at least plan to seek preventive oral care if the practice is common in their wider social environment. This explanation needs to be explored further in future research.

Third, the study found that bonding SC had an inconsistent role in the specified relations that contradicted our hypotheses. It positively modified the association between SES and oral health status but negatively moderated the effect of SES on the intention to use preventive oral health services. This inconsistency amplifies conclusions about the possible downside of SC (Amoah, 2017; Putnam, 2000). On the positive side, Putnam (2000) has argued that egalitarian social ties can be a platform for healthy norms and the spread of proper health information, which can improve health outcomes. From this perspective, our results increased the value of strong social ties as a resource for achieving desired behavioral change, even among those with high SES. The negative effect, while contradictory to our hypothesis, is not surprising; and research in the United States has found similar results among older persons (Sabbah et al., 2011). The negative effect of bonding SC is often located in the context of distressful social relationships, which cause people to take to detrimental health behaviors such as smoking and consumption of confectionaries known to cause dental problems (Sisson, 2007). It is possible that the bonding SC of older persons in this study consisted of individuals who shared similar or low levels of HL. Given the strong influence of bonding SC, such collective low HL can transmit misinformation and misapplication of even proper health information leading to poor decisions. However, this explanation is contrary to positions elsewhere (Burr & Lee, 2013). The inconsistent results provide conceptual clarity to the fundamental cause theory (Phelan et al., 2010). While SES shapes health outcomes, the characteristics of other resources accrued through some social networks can negate expected benefits by encouraging undesirable behaviors. The significant role of SC calls for regular contextual analyses to understand its influence on oral health.

Limitations

The results must be interpreted with some limitations. The analysis is based on cross-sectional data, which implies that causal inferences cannot be drawn. For instance, it would be problematic to draw conclusions from the negative effect of bonding SC on the association between SES and oral health. Similarly, due to poor house numbering in most parts of the study areas, it was challenging to implement an absolute probability sampling method for a household-based survey. Therefore, the sampling was based on an eclectic approach aimed at achieving a balanced instead of a representative sample. Also, the data were entirely based on retrospective self-reports, which could have been infused with socially desirable responses and recall problems among the participants. Because of these limitations, the results cannot be generalized to the entire older population of Ghana. However, these limitations do not undermine the veracity of our study, since the results are largely consistent with many previous studies applying similar methodological approaches in different settings, as discussed earlier.

Conclusion

Our results demonstrate that SC modifies the effect that SES and HL each have on oral health status and the intention to use preventive oral health services. In particular, bridging SC moderated the influence of HL on oral health status and the influence of SES on the intention to use preventive oral health services. Bonding SC had a positive effect on the influence of SES on oral health but weakened the effect of SES on the intention to use oral health services. The cognitive component (trust) significantly influenced the extent to which HL affected attitudes toward preventive oral health care. These results suggest the need to consider older persons’ oral health in the broader context of the observable and non-observable aspects of their social environments. Health promotion activities regarding older persons’ oral health and related behaviors must take cognizance of SES and HL and the social environments in which information is dispensed, and interventions are implemented to achieve set goals. Future research should utilize both longitudinal survey data and qualitative approaches to understand possible proximate causal effects and to unravel the in-depth mechanisms of their effects.

Supplemental Material

sj-pdf-1-jag-10.1177_07334648211028391 – Supplemental material for Association of Health Literacy and Socioeconomic Status with Oral Health Among Older Adults in Ghana: A Moderation Analysis of Social Capital

Supplemental material, sj-pdf-1-jag-10.1177_07334648211028391 for Association of Health Literacy and Socioeconomic Status with Oral Health Among Older Adults in Ghana: A Moderation Analysis of Social Capital by Padmore Adusei Amoah, Adwoa Owusuaa Koduah, Razak M. Gyasi, Kingsley Atta Nyamekye and David R. Phillips in Journal of Applied Gerontology

Footnotes

Declaration of Conflicting Interests

The authors declared no potential conflicts of interest with respect to the research, authorship, and/or publication of this article.

Funding

The authors disclosed receipt of the following financial support for the research, authorship, and/or publication of this article: The Lingnan University Faculty Research Grant (Grant code: 102159) funded this study. The study also received funding support from Lingnan University through the Lam Woo Research Fund-Individual Grant (Grant code: LWI20014) in the preparation of the manuscript. The funders did not have any role in the design of the study, preparation of manuscript or in the decision to publish.

ORCID iDs

Padmore Adusei Amoah

Adwoa Owusuaa Koduah

Supplemental Material

Supplemental material for this article is available online.

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