The rural-urban divide of the relationship between polygynous marriage structures, multiple marriage unions, and self-rated happiness among currently married Ghanaian women

doi:10.21203/rs.3.rs-1853526/v1

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The rural-urban divide of the relationship between polygynous marriage structures, multiple marriage unions, and self-rated happiness among currently married Ghanaian women

https://doi.org/10.21203/rs.3.rs-1853526/v1

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Polygyny and multiple marital unions are generally associated with overall happiness deficits, yet the rural-urban differentials of these associations are not thoroughly interrogated. This study uses a nationally representative dataset of 7785 married and in-union Ghanaian women aged 15–49 years to investigate the rural-urban differences in the relationship between polygyny, multiple marital unions, and happiness. Findings show that rural married and in-union women in polygynous relationships [APOR = 0.760, 95% CI:0.60, 0.96] and were married more than once [APOR = 0.79, 95% CI:0.66, 0.94] were less likely to be happy. Age, education, household wealth, and region of residence were significantly associated with happiness only among rural married women. Both rural and urban married and in-union women in the Upper West and Upper East Regions were more likely to be happy than married women in the Greater Accra Region. Policies should enable rural women in polygyny and those in their second or more marital unions with happiness-enabling resources.

Happiness

Polygyny

Multiple marriage unions

reproductive-aged women

Ghana.

Marriage is regarded as a close personal relationship and a social institution that has an impact on people's lives and wellbeing [1]. Marriage improves physical and subjective well-being by providing additional sources of self-esteem and supportive intimate relationships [1–3]. It also regulates sexual relations and encourages commitment between spouses while providing basic insurance against adverse life events [1]. Despite the numerous benefits of marriage, several researchers have reported some problems associated with marriage [4–7]. Some of the common problems indicated are lack of commitment, infidelity [5], communication difficulties, money, household management [7], and time spent together among others [4]. Many of these issues reportedly have a deleterious impact on spouses and children, especially in the event of separation and divorce. The problem that leads to divorce, may be evident from the start of the relationship or they may arise and then worsen over time [7].

Marriage, in several contexts, is formed by ordinance and customary [8]. One type of marriage, polygamous unions, which allows a partner to have multiple spouses, is widely practised in sub-Saharan Africa [9, 10]. While prohibited under civil legislation, several tribes and religious groups (e.g., Muslims) in Ghana recognize polygamous marriages and Ghana’s customary marriage laws promote it [11]. Many men are motivated to form polygamous marriages because of the pride associated with having many children and its association with the socioeconomic security and stability of a family [9, 10]. Also, children from these unions were viewed as a source of labour, emotional support, and financial security for their parents in old age [9]. Although previous studies report the endorsement of polygyny by some women, most women disapprove of it [12]. A study found that despite their dislike of polygyny, women in Ghana who had fertility problems allowed their partners to have other spouses to protect their marriage from ending in divorce or separation [10].

Regardless of the supposed positive benefits of polygyny, women involved in this family structure experience problems which undermine their self-reported happiness. Many women in polygynous unions deal with grief, solitude, rivalry, and lack of intimacy [10, 13, 14]. These experiences are consistent with studies reporting poor mental health and higher psychological distress among women in polygamous marriages compared to their monogamous counterparts [15–17]. Women in polygamous marriages are, thus, more likely to suffer sexual, physical, and emotional abuse at the hands of their husbands [18]. Nevertheless, some women in polygamous unions adopt multiple mechanisms such as reliance on religion, faith, and a strong sisterly bond formed with co-wives to cope with these undesirable experiences [10].

These positive and negative factors associated with marriages have contributed to the debatable question: “does marriage create happiness or does happiness promote marriage?” [1]. Scholars have questioned whether it is marriage per se or simply the act of union formation that is associated with happiness [2]. Scholars have also asserted that it is imperative to consider rural-urban trends when attempting to understand the relationship between polygyny and happiness [9, 19]. Rural and urban communities have their unique sub-cultures that may define how they perceive happiness and satisfaction with life in general and polygynous unions [19]. People who live in areas outside the city, suburbs, or rural areas are said to be slightly happier and satisfied with their place of residence compared to those in urban areas [19].

The rural and urban effects on happiness raise the question of whether the relationship between polygyny and self-reported happiness differs along the rural and urban dimensions. Also, although there are different studies conducted on marriage and polygyny in Ghana [10, 11, 20, 21], none have examined the relationships between polygyny and overall happiness. Therefore, this study focused on the rural-urban dimensions of the relationship between polygynous marriage structures, multiple marriage unions, and self-rated happiness among currently married Ghanaian women using the nationally representative 2017/2018 Ghana Multiple Indicator Cluster Survey.

Data source and collection procedure

The current study analyzed the women's dataset from the 2017/2018 Ghana Multiple Indicator Cluster Survey Six (GMICS 6). The MICS 6 is a cross-sectional survey conducted by the Ghana Statistical Service (GSS) in collaboration with other government agencies including the Ghana Health Service (GHS), the Ministry of Health (MOH), and the Ministry of Education [22]. The United Nations International Children's Emergency Fund (UNICEF) and other international donors provided funding and technical support for the survey [22]. The MICS Programme collects internationally comparable household data on a variety of indicators from children and women to be used by countries for national development plans, policies, and programmes, as well as to assess progress towards SDGs and other agreements signed internationally [22].

Trained field officials collected the data on behalf of the GSS and UNICEF beginning from 15 October 2017 and ending on 15 January 2018. A multi-stage, stratified cluster sampling approach was used for the data collection. This approach ensured national surveying of women in urban and rural areas from the previous 10 administrative regions in Ghana namely, Western, Central, Greater Accra, Volta, Eastern, Ashanti, Brong Ahafo, Northern, Upper East, and Upper West. The GSS based the sampling frame for the data collection on the 2010 Population and Housing Census (PHC) of Ghana. Enumeration areas (EAs) were identified within this sampling frame and selected as the primary sampling units (PSUs) and thus completing the first stage of the data collection. In the second stage, a list of households was created, and sampled systematic random sampling from each selected EA. In the end, participants were recruited from a total of 13202 households. In this study, data of 7785 married or in-union women between the ages of 15 to 49 years were analyzed.

Measures

Outcome variables

The outcome variable used in this study was happiness. Happiness was measured using a self-report single-item question. Participants were asked, “First, taking all things together, would you say you are very happy, somewhat happy, neither happy nor unhappy, somewhat unhappy or very unhappy”. Participants responded to the question on a 5-point response scale (“1 = very happy”, “2 = somewhat happy”, “3 = neither happy nor unhappy”, “4 = somewhat unhappy” and “5 = very unhappy”) with the aid of a response card displaying smiling faces (and not so smiling faces) which corresponded to the response categories. Per the research aim, the response categories were reverse coded by assigning “0” to very unhappy, “1” to somewhat happy”, “2” to neither happy nor unhappy, “3” to somewhat happy, and “4” to very happy.

Predictor variables

Polygyny relationships and multiple marriage union statuses were treated as the main independent variables in this study. Both variables were derived from single-item questions. For polygyny, women were asked, “Besides yourself, does your (husband/partner) have any other wives or partners or does he live with other women as if married?” Women responded by answering “Yes = 1” or “No = 2” to the question. For multiple marriage unions, women were asked “Have you been married or lived with someone only once or more than once?” and responded by using the response format, “Only Once = 0” and “More than once = 1”.

Control variables

Woman’s age, woman’s education, health insurance status, household wealth index, rural-urban residence, and region of residence were selected as control variables for this study. The choice of control variables was informed by availability in the dataset and findings from previous studies [23, 24].

Data Preparation And Analysis

Statistical analyses began with data cleaning in Stata version 14. Univariate analyses computing frequencies and percentages were conducted next with weighted data (see Table 1). Weights were applied to correct the biases in the dataset. Next, bivariate and multivariable analyses were conducted in chi-square and ordered logistic regression on the full sample and rural-urban stratified sample. Before performing these analyses, the clusters, stratification, and sample weights within the dataset were corrected by activating the complex survey mode command “svyset”. According to West et al, such corrections are important for secondary datasets collected with complex survey designs to account for possible analytical errors and make proper inferences about the population [25]. After achieving this correction, the main bivariate analyses in chi-square were performed on the full sample by examining the relationship between the predictor variables, control variables, and outcome variable as shown in Table 1. This was followed by multivariable analyses in ordered logistic regression. Three models were tested in the multivariable analyses. The first comprised of the individual regression of both predictor variables and control variables onto the outcome variable (see Model 1 column on Table 2). The second involved regressing only the predictor variables onto the outcome (see Model 2 on Table 2). Lastly, both predictor and control variables were simultaneously regressed onto the outcome variable (see Model 3 on Table 2). These three steps were applied to both the full sample and rural-urban stratified samples. The proportional ratios and the adjusted proportional ratios are reported.

Ethics Approval And Data Availability

The study was conducted in accordance with the Declaration of Helsinki and adhered to good practice. Ethical approval was sought by the United Nations International Children's Emergency Fund (UNICEF) from relevant authorities including the Ghana Statistical Service, Ghana Health Service, the Ministry of Health (MOH), and the Ministry of Education. Enumerators obtained child assent and parental/adult informed consent from participants before primary data collection occurred. Aside from that, participants were assured of anonymity and confidentiality. To access the dataset, permission was sought and granted by UNICEF at https://mics.unicef.org/surveys.

Summary statistics of the study variables

Overall, about 39.62% of the respondents indicated that they were very happy in life. Approximately 1460 out of 7785 of the respondents reported that they were co-wives. Out of this number, 39.60% of the respondents indicated that they were very happy in life. About 21.53% of the respondents had married more than once (1676/7785). Out of this number, 33.49% reported being very happy in life. It was further noted that a total of 3647 out of 7785 of the respondents were from urban areas. Out of this number, 41.94% of the urban dwellers reported being very happy in life. Detailed information on the study variables is presented in Table 1.

Table 1

summary statistics of study variable
	n	VU	SU	N	SH	VH
Self-rated happiness	7785 (100%)	5.35	5.53	15.42	34.08	39.62
Independent variable
Co-wife status	p ≤ 0.001
No	6325 (81.24)	4.63	5.12	15.43	35.21	39.60
Yes	1460 (18.76)	8.45	7.30	15.37	29.16	39.72
Control variables
Married more than once	p ≤ 0.001
Once	6109 (78.47)	4.51	5.26	15.23	33.69	41.30
More than once	1676 (21.53)	8.40	6.51	16.11	35.49	33.49
Age	p ≤ 0.05
15–19	197 (2.53)	5.08	5.81	10.69	38.72	39.69
20–24	782 (10.05)	3.50	7.28	15.01	33.82	40.39
25–29	1360 (17.47)	4.15	5.68	14.39	34.06	41.72
30–34	1694 (21.77)	5.64	3.78	13.59	33.96	43.04
35–39	1470 (18.88)	4.31	5.30	15.67	34.23	40.49
40–44	1307 (16.78)	8.02	6.98	18.71	32.77	33.53
45–49	975 (12.52)	6.06	5.32	16.54	35.12	36.96
Education	p ≤ 0.001
None or pre-primary	2095 (26.90)	6.39	6.94	14.23	30.49	41.94
Primary	1546 (19.86)	7.18	6.67	17.58	32.85	35.72
Junior secondary	2869 (36.85)	4.60	5.26	16.20	37.34	36.60
Senior secondary	840 (10.79)	4.20	3.30	14.67	35.33	42.50
Post-secondary	435 (5.59)	0.97	0.81	9.81	31.75	56.66
Health insurance	p ≤ 0.001
Insured	4497 (57.77)	4.38	5.35	14.65	33.50	42.12
Uninsured	3287 (42.23)	6.67	5.78	16.47	34.87	36.21
Household wealth	p ≤ 0.001
Poorest	1479 (19.0)	6.88	7.14	15.13	32.62	38.23
Second Quintile	1455 (18.69)	7.33	6.77	16.94	32.90	36.05
Third Quintile	1431(18.69)	5.97	6.04	14.88	34.60	38.51
Fourth Quintile	1618 (18.38)	4.26	5.41	16.95	35.23	38.16
Richest	1802 (23.14)	2.98	2.92	13.49	34.79	45.83
Rural-urban	p ≤ 0.001
Urban	3647 (46.85)	4.70	4.69	14.25	34.41	41.94
Rural	4138 (53.15)	5.92	6.27	16.46	33.78	37.57
Region	p ≤ 0.001
Greater Accra	900 (11.56)	4.64	4.15	12.05	36.44	42.73
Western	778 (10.00)	6.57	8.62	14.60	35.49	34.71
Central	752 (9.66)	2.95	6.71	14.67	38.46	37.21
Volta	620 (7.97)	6.30	3.58	11.19	31.67	47.25
Eastern	930 (11.94)	4.35	6.23	18.99	34.94	35.49
Ashanti	1769 (22.72)	6.25	5.64	19.75	34.07	34.29
Brong-Ahafo	682 (8.76)	8.18	4.44	10.72	34.82	41.84
Northern	889 (11.42)	3.52	5.52	18.81	32.56	39.58
Upper East	259 (3.33)	5.50	4.06	4.54	23.53	62.36
Upper West	205 (2.64)	4.84	2.89	10.05	23.16	59.06
VU: Very Unhappy
SU: Somewhat Unhappy
N: Neither Happy nor Unhappy
SH: Somewhat Happy
VH: Very Happy

Associated factors of happiness in a stratified rural-urban bivariate and multivariable model.

Separate ordered logistic regression models were used to assess the relationship between polygyny, multiple union/marriages, covariates (age, education, household wealth index, rural-urban residence, and region of residence), and happiness in stratified rural-urban samples. As shown in Table 2, bivariate and multivariable analyses were reported for overall happiness in life. Though the multivariable analyses are of the main interest in this study, we found some significant associations in the bivariate analyses that need to be highlighted. Thus, in terms of rural married women, we found a significant association between polygyny and happiness. Similarly, a significant association was found between multiple unions and happiness among rural married women. Also, age, education, household wealth, and region of residence were significantly associated with happiness among rural married women only. The only region of residence was significantly associated with happiness among both rural and urban married women.

The results from the multivariable analyses indicated that there is a significant association between rural women in polygynous relationships and happiness. Specifically, rural women in polygynous relationships were less happy than those not in polygynous relationships [APOR = 0.760, 95% CI: 0.60, 0.96]. There was no significant relationship between polygyny and overall happiness among urban married women. Rural married women that were married more than once were less happy than their counterparts who were in their first marriage unions [APOR = 0.79, 95% CI:0.66, 0.94].

Rural married women between the ages of 40 to 44 years were less likely to be happy in life compared to their 15 to 19 years counterparts [APOR = 0.58, 95% CI: 0.35, 0.94]. Rural married women who have attained senior secondary education were less likely to be happy compared to those with only pre-primary or no education [APOR = 0.68, 95% CI: 0.48, 0.96]. Rural married women who dwelt in households with the highest wealth quintile were positively associated with a higher self-rating of overall happiness compared to those in the lowest wealth quintile households [APOR = 1.56, 95% CI: 1.11, 2.19].

Differences also exist in the effect of region of residence on happiness among women in rural and urban areas. Rural and urban married women in the Upper East and Upper West Regions were associated with a higher likelihood of self-rated overall happiness compared to the Greater Accra Region. Results are summarized in Table 2.

Table 2

Ordered regression of independent and control variables on self-rated happiness for the full sample and Rural-urban divide
	Full Sample			Rural			Urban
	Model 1: POR	Model 2: APOR	Model 3: APOR	Model 1: POR	Model 2: APOR	Model 3: APOR	Model 1: POR	Model 2: APOR	Model 3: APOR
Independent variables
Co-wife status
No	Ref.	Ref.	Ref.	Ref.	Ref.	Ref.	Ref.	Ref.	Ref.
Yes	0.85 [0.71, 1.02]	0.87 [0.72, 1.04]	0.81* [0.68,0.97]	0.94 [0.74,1.20]	0.93 [0.73,1.19]	0.76* [0.60, 0.96]	0.79* [0.62, 0.99]	0.82 [0.65, 1.03]	0.86 [0.67, 1.11]
Control variables
Married more than once
Once	Ref.	Ref.	Ref.	Ref.	Ref.	Ref.	Ref.	Ref.	Ref.
More than once	0.71*** [0.62, 0.82]	0.71*** [0.62, 0.82]	0.82** [0.71,0.94]	0.68*** [0.57,0.81]	0.67*** [0.57,0.80]	0.79** [0.66, 0.94]	0.78* [0.62, 0.97]	0.79* [0.63, 0.99]	0.87 [0.69, 1.10]
Age
15–19	Ref.	Ref.	Ref.	Ref.	Ref.	Ref.	Ref.	Ref.	Ref.
20–24	0.96 [0.67, 1.37]		0.88 [0.61, 1.28]			0.96 [0.60, 1.52]			0.80 [0.42, 1.52]
25–29	1.02 [0.720,1.441]		0.87 [0.60, 1.26]			0.75 [0.47, 1.18]			1.12 [0.61, 2.07]
30–34	1.07 [0.77, 1.50]		0.93 [0.65, 1.35]			0.76 [0.48, 1.21]			1.20 [0.66, 2.18]
35–39	0.97 [0.69, 1.38]		0.87 [0.60, 1.26]			0.95 [0.60, 1.51]			0.83 [0.44, 1.55]
40–44	0.67* [0.47,0.96]		0.60** [0.41, 0.89]			0.58* [0.35, 0.94]			0.69 [0.37, 1.26]
45–49	0.837 [0.59,1.20]		0.76 [0.52, 1.13]			0.64 [0.39, 1.05]			0.99 [0.53, 1.84]
Education
None or pre-primary	Ref.	Ref.	Ref.	Ref.	Ref.	Ref.	Ref.	Ref.	Ref.
Primary	0.80* [0.65,0.98]		0.83 [0.65, 1.04]			0.73* [0.58, 0.93]			0.99 [0.58, 1.69]
Junior secondary	0.93 [0.80,1.08]		0.88 [0.73, 1.06]			0.70** [0.54, 0.90]			1.20 [0.85, 1.69]
Senior secondary	1.16 [0.89, 1.51]		0.91 [0.66, 1.27]			0.68* [0.48, 0.96]			1.28 [0.72, 2.30]
Post-secondary	2.11*** [1.46, 3.06]		1.46 [0.93, 2.29]			1.15 [0.64, 2.04]			1.92 [0.92, 3.99]
Health insurance
Insured	Ref.	Ref.	Ref.	Ref.	Ref.	Ref.	Ref.	Ref.	Ref.
Uninsured	0.78*** [0.69, 0.88]		0.90 [0.79, 1.02]			0.91 [0.76, 1.08]			0.91 [0.76, 1.10]
Household wealth
Poorest	Ref.	Ref.	Ref.	Ref.	Ref.	Ref.	Ref.	Ref.	Ref.
Second Quintile	0.92 [0.75, 1.12]		1.12 [0.91, 1.37]			1.20 [0.96, 1.51]			0.87 [0.50, 1.54]
Third Quintile	1.07 [0.88,1.30]		1.32* [1.05, 1.65]			1.41** [1.09, 1.83]			1.10 [0.61, 1.98]
Fourth Quintile	1.09 [0.89, 1.32]		1.39** [1.12, 1.72]			1.97*** [1.50, 2.59]			0.95 [0.54, 1.67]
Richest	1.53*** [1.27, 1.83]		1.78*** [1.40, 2.26]			1.56** [1.11, 2.19]			1.39 [0.78, 2.50]
Rural-urban
Urban	Ref.	Ref.	Ref.	Ref.	Ref.	Ref.	Ref.	Ref.	Ref.
Rural	0.81** [0.70, 0.93]		0.94 [0.80, 1.10]	—	—	—	—	—	—
Region
Greater Accra	Ref.	Ref.	Ref.	Ref.	Ref.	Ref.	Ref.	Ref.	Ref.
Western	0.67** [0.51, 0.88]		0.81 [0.62, 1.07]			0.75 [0.35, 1.61]			0.98 [0.75, 1.29]
Central	0.82 [0.63, 1.07]		1.03 [0.79, 1.34]			1.06 [0.50, 2.22]			1.03 [0.74, 1.45]
Volta	1.11 [0.80, 1.54]		1.58** [1.12, 2.23]			1.71 [0.78, 3.73]			1.30 [0.85, 1.97]
Eastern	0.72* [0.55, 0.94]		0.88 [0.66, 1.18]			0.92 [0.43,1.98]			0.83 [0.59, 1.18]
Ashanti	0.66** [0.51, 0.85]		0.77* [0.60, 0.99]			0.80 [0.38,1.69]			0.77 [0.58, 1.01]
Brong-Ahafo	0.91 [0.69, 1.18]		1.15 [0.87, 1.54]			1.22 [0.56, 2.67]			1.09 [0.79, 1.52]
Northern	0.83 [0.62, 1.09]		1.23 [0.89, 1.70]			1.21 [0.55, 2.66]			1.27 [0.83, 1.96]
Upper East	2.01*** [1.53, 2.64]		2.94*** [2.16, 4.01]			2.72* [1.26,5.89]			4.14*** [2.91, 5.90]
Upper West	1.71** [1.18, 2.49]		2.49*** [1.67, 3.70]			2.66* [1.16, 6.11]			1.89* [1.04, 3.45]
Model details
Strata			20			11			10
PSUs			660			421			319
Pop. number of observations			7785			4456			3329
Pop. Size			8066.98			4287.9			3779.1
Design df			640			410			309
F stats			9.75			F (26, 385) = 5.70			F (26, 284) = 7.48
Prob > F			0.0000			0.000			0.000
Note. JHS: PSU: Primary sampling units; POR: proportional odds ratio; APOR: adjusted proportional odds ratio. ^* p < 0.05, ^ p < 0.01, ^* p < 0.001

This study investigated the urban-rural differences in the relationship between polygynous marriage structures, multiple marriage unions, and self-reported happiness of women in Ghana, after adjusting for control variables.

Rural co-wives had a lower likelihood of self-rated overall happiness. However, polygyny was not significantly associated with self-rated happiness among urban married women. These results have rural-urban differential implications. Generally, most polygynous relationships are characterized by rivalry, lack of cooperation, competition for scarce economic resources, and conjugal attention from the husband among co-wives [10]. These specific polygyny characteristics sometimes result in adverse consequences for the members of this union, especially the women and their children [10]. Given that these polygyny-related conflicts and rivalries are more pronounced in rural areas [13], rural women might be more prone to rate themselves unhappy. Another characteristic, which is often prevalent in rural areas, which can affect happiness is co-wives living together in the same house [14]. This proximity creates tension and rivalry among the co-wives in terms of conjugal visits and sharing of resources [14]. However, in many cases, co-wives in urban homes live in separate houses [26]. Co-wives having little clue about the amount of attention provided to their rivals by the husband reduces the tension and rivalry. Also, most African cultures especially in rural areas are driven by patriarchal social norms [27]. The patriarchal nature of polygyny to a large extent leads to sexual, physical, and emotional abuse of women by their husbands [27]. These abuses, because they are more pronounced in rural areas, can disable the resources that promote overall happiness among rural co-wives [28]. The absence of a significant effect of polygyny on urban co-wives’ overall happiness may be attributable to several factors. First, urban women are generally more economically empowered and well informed about their rights and privileges than their rural counterparts [29], and have access to resources to demand and enjoy equal rights and status with men in many aspects of life [29]. That is, urban women have significant access to employment, asset ownership, housing, and education compared to their rural counterparts. With these socioeconomic safety nets, which are substantial drivers of overall happiness and wellbeing, the effect of polygyny among urban co-wives may have little to no significant effect on overall happiness.

Furthermore, there is a rural-urban disparity in the influence of multiple marriages on overall happiness among currently married women in Ghana. In our study, we found that women who were in their second or more marriage unions had significantly lower self-rated happiness, but this association is non-significant among urban married women. Generally, our findings are comparable to others who reported that multiple marital unions affect overall happiness in a current marital union [30]. The authors explained that forming a new marital union after the dissolution of the previous one increased the risk of mental health problems such as depression, binge drinking, and substance abuse [30]. Forming a new partnership is quite stressful particularly when children are present as mediating influences [31]. The urban-rural dichotomy of the relationship between multiple unions and self-rated happiness can be explained as follows. It is common knowledge that divorce, separation, and the death of a spouse are the drivers of women forming marital unions with new partners [32]. These drivers are equally risk factors for unhappiness, depression, and other mental health challenges [33, 34]. The significant effect of multiple unions on the overall happiness of rural women but not with urban women could be that the negative effects of the dissolution of previous marriages are more pronounced in rural areas where social safety nets of happiness are in scarcity [29, 35].

Age was significantly related to self-rated overall happiness in rural married women but not among urban married women. Specifically, married women within the age group of 40 to 44 were less likely to rate themselves happy compared to teenage married women in rural areas. This was unexpected since one would have expected that self-rated happiness among teenage mothers would have been lower, making the coefficient of the other age categories positive. However, a convincing explanation for this association is that since teenage marriage is predominantly a rural phenomenon [28], early marriage may be acceptable to rural adolescent girls and its impact on their happiness may be lessened. The age group in question (40 to 44 years) is identified in the literature as middle age and this period is characterized by changes in family and job roles [36]. Women in this period may be encumbered with the coordination of multiple roles and experiences of several unpredictable stressful life events that can potentially affect the way rural married women will rate their overall marital satisfaction, wellbeing, and overall happiness [37, 38].

Urban-rural differences exist in the effect of education on overall happiness, as it was significantly related to self-rated happiness among rural married women only. For married rural women, having a primary or secondary school level education was unexpectedly negatively associated with self-rated overall happiness compared to those without education. Women in rural areas might have thought that their access to higher education will give them access to livelihood-enabling resources. This expectation, when crashed within the context of limited access to employment opportunities and social amenities [39, 40], could rather become a source of unhappiness. In a nutshell, employment opportunities may not be available for educated women in rural areas and their inability to secure employment may decrease their happiness levels [41]. Also, due to inadequate healthcare services in rural areas, educated married women may not meet their health needs and this could impact their happiness levels. For urban married women, education has no significance on overall happiness. The lack of effect of education on overall happiness among urban women in Ghana can be attributable to the high literacy rate among the urban population, which probably reduces its effect on overall happiness.

Household wealth was significantly associated with overall happiness in rural areas but not in urban areas among currently married Ghanaian women. The finding of a positive effect of household wealth on happiness among rural married women is in agreement with a report on this association in another study [42]. Household wealth may have enabled rural married women to improve their social functioning and psychological wellbeing [43]. The lack of significant association between household wealth and overall happiness among urban married women may be attributable to the distinction between household wealth and individual wealth. Probably, urban married women may not perceive household assets as their assets—this perception could be widespread in urban areas—resulting in the lack of effect of household wealth on overall happiness.

Finally, rural and urban married women in the Upper East and Upper West Regions were more likely to report higher overall happiness compared to married women in both rural and urban married women in the Greater Accra Region. The simplicity of life is more prominent among rural and urban married women in both the Upper East and Upper West Regions than Greater Accra Region. Generally, the Upper East and West Regions have the following characteristics that are identified in the literature as enablers of happiness: subsistence agriculture, high levels of connectedness, and religiosity [44, 45]. Living-related stress levels in the Greater Accra Region, the political capital region of Ghana, are higher compared to other regions due to the high standards of living [46]. Therefore, married women in Greater Accra may have to contend with the effect of “keeping up with the Joneses” where they have to emulate the lifestyle of other rich neighbours [47].

One strength of this study is its ability to unearth the urban-rural differentials in the relationship between sociodemographic factors and happiness. Another strength is in the use of a nationally representative sample and robust data collection procedures which increases generalizability and lessens the effects of potential errors associated with self-reported measures. However, the use of a cross-sectional study makes it difficult to establish any causal inferences between the predictors and the outcome variable. Additionally, the sample consisted of only married women within 15–49 years; thus, the results cannot be generalized to older married women.

This paper examined the association between polygyny, multiple marriages or unions, and the happiness of married or in-union women, specifically in Ghana. Polygyny and multiple union/marriages were found to be significantly negatively associated with self-rated overall happiness in rural married women but not among urban women. Rural-urban differentials were observed in the association between sociodemographic factors and self-rated overall happiness. Policies should enable women in polygynous marital unions and those in their second or more marital unions with happiness-enabling resources given that severe unhappiness is an early sign of general mental health problems.

Ethics approval and consent to participate

Consent for publication

Not Applicable

Availability of data and materials

The datasets generated and/or analysed during the current study are available in UNICEF repository https://mics.unicef.org/surveys

Competing interest

The authors have no relevant financial or non-financial interests to disclose.

Funding

No funding was received to assist with the preparation of this manuscript.

Author Contributions

Kenneth Owusu Ansah contributed to the data curation, analysis, and interpretation as well as the writing of the main manuscript text.

Emmanuel Dziwornu contributed to the write-up of the main manuscript text.

Kwabena Frimpong-Manso reviewed and edited the manuscript

Nutifafa Eugene Yaw Dey contributed to the data curation, analysis, and interpretation as well as the writing of the main manuscript text

Precious Adade Duodu contributed to the writing of the main manuscript text

Pascal Agbadi contributed to the study's data curation, analysis, and interpretation, as well as reviewing and editing the manuscript.

Acknowledgement

We would like to appreciate the necessary stakeholders involved in conducting the Multiple Indicator Cluster Survey six. We are also grateful to UNICEF for permitting us to use the 2017/2018 Ghana Multiple Indicator Cluster Survey. The authors also appreciate the training in academic writing and data management provided by Research Empowerment Network (REN).

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No competing interests reported.

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The rural-urban divide of the relationship between polygynous marriage structures, multiple marriage unions, and self-rated happiness among currently married Ghanaian women

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