Welfare of the elderly in rural communities in central and northern Nigeria, sub Saharan Africa
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https://www.eduzhai.net Public Health Research 2012, 2(4): 92-101 DOI: 10.5923/j.phr.20120204.05 Elderly Well-being in a Rural Community in North Central Nigeria, sub-Saharan Africa Adebowale S. A.*, Atte O., Ayeni. O. Department of Epidemiology and M edical Statistics, Faculty of Public Health, College of M edicine, University of Ibadan, Ibadan, Nigeria Abstract Globally, the population of elderly is increasing and their well-being is becoming a public health concern. In Nigeria, poverty is widespread and elderly persons are at higher risk. Unfo rtunately, Nigerian Govern ment does not provide social security to elderly and the supports fro m the family are fading out. Therefore, the well-being of elderly is co mpromised. This study was designed to determine the prevalence and identify predictors of elderly well-being in a rural co mmunity in Nigeria. The study was cross-sectional in design and adopted mu lti-stage sampling procedures to select 1217 elderly aged 65+. Well-being was captured using scores from four do mains; social, psychological, physical and environmental. Data were analysed using descriptive statistics, Chi-square and logistic regression models. Mean age of the elderly was 72.3±8.4years and 65.2% were females. About 49.1% of the respondents have poor well-being. Poor well-being increases with age, but reduces as level of education increases. The identified pred ictors of poor well-being were; age (β=0.208;S.E= 0.056), ch ildren ever born (β= 0.672;S.E= 0.079), children alive (β =-0.596;S.E=0.275), marital status (β=0.260;S.E= 0.112), financial support from children (β= 0.208;S.E= 0.056), children visit by gender (CV) (β=-0.545;S.E= 0.095), ch ildren liv ing with elderly (β=-0.508; S.E=0.169) and having enough money to meet daily needs (HDHN) (-1.357;S.E= 0.179). Elderly who; do not receive any financial assistance from their children (FA C) (OR= 2.4; C.I=1.7-3.2) and those who were separated (OR=6.2; C.I=1.3-30.0) were more likely to experience poor well-being than those who receive and those who never married respectively. The likelihood of poor well-being was lower among elderly who HDHN (OR= 0.2; C.I=0.1-0.3) and those who don’t have any of their children liv ing with them (OR= 0.7; C.I=0.5-0.9). Mu ltiple logistic regression models were generated at 8th iterations. High proportion of the elderly in the commun ity has poor well-being. While developing policies aim at improving elderly well-being in Nigeria, government should include; age, marital status, FAC, CV, ch ild ren living with elderly and HDHN as part of their key variables. Keywords Elderly Well-Being, Rural Co mmunity, Elderly Care, Rural Co mmunity 1. Introduction Well-being is a positive physical, social and mental state; it is not just the absence of pain, discomfort, and incapacity. It arises fro m not only the action of an individual, but fro m a host of collect ive goods and relationships with other people. It requires that basic needs are met, that indiv iduals have a sense of purpose, and that they feel able to achieve important personal goals and participate in societal activ ities. Globally, the population is aging rapidly. Both the number and proportion of people aged 65 years and above are increasing, although at different rates in different parts of the wo rld. The nu mber of o lder adults has risen mo re than threefold since 1950, fro m appro ximately 130 million to 419 million in 2000, with the elderly share of the population increasing fro m 4 percent to 7 percent during that period. * Corresponding author: Adesteve2006@yahoo.com (Adebowale, A.S) Published online at https://www.eduzhai.net Copyright © 2012 Scientific & Academic Publishing. All Rights Reserved In Nigeria, those aged 65 years and above make up about 4.3 percent of the total population which was put at 140,431,790 million according to 2006 population exercise. The population of elderly (age 65+) in Nigeria is on the increase as the crude mortality rates are gradually reducing[4-7]. Aging in Nigeria is occurring against the background of socio-economic hardship, wide spread poverty, the HIV/AIDS pandemic, and the rapid transformation of the traditional e xtended family structure. The roles of e lderly in nation building at the various stages of their life cannot be over-emphasized. They are the custodians of culture and tradition, med iators during conflict resolution and contributors in enforcing peace in their various communit ies. The younger generation will no little or nothing about culture and tradition if the elderly who are to educate them are not been properly preserved. The elderly have served their motherland when they were young and active. Many elderly reach retirement age after a lifetime of poverty and deprivation, poor access to health care and poor dietary intake. These situations leave them with insufficient personal savings to meet their daily needs[10,11]. 93 Public Health Research 2012, 2(4): 92-101 They are most at times denied of their right to receive their pension resulting on their poor we ll-being due to poverty and poor medical attention. Therefore, well-being of the elderly is of paramount importance. Nigeria govern ment devotes few resources to health care and primary health care concentrates more on maternal and child health and contagious diseases. The problems of an aging population have not been seen as important in Nigeria because the aged are such a small part of the population. In most developing countries, formal social security systems have only limited coverage and inadequate benefit payments[12,13]. As a result, the majo rity of o lder people depend on family support networks, a reality that is well appreciated in most parts of sub-Saharan Africa in the past[14-16]. However, it is recognized that tradit ional social security systems are evolving, attenuating and rapidly disappearing due to pressures fro m urbanization and industrializat ion. Youths mig rate to cities while the elderly move back to the rural areas. Elderly persons in Nigeria reside more in ru ral co mmun ities, particularly those who have retired fro m their place of work. The health care system spends a small fraction of the budget on treating older adult illness and access to care is limited and not a policy priority in most developing countries[18,19]. The attitude of health care p roviders towards older people makes their situation even more difficult. Many older people do not access health services due to inability to prove their age, aggravated by the limited availability of health services, equipment and expert ise. In Nigeria, poverty is rife and elderly persons are more at risk since most of them are no longer in the economically active phase of life and there is no national social security to provide economic support in old age. Access to health care is severely limited both by paucity of health facilities and manpower and by out-of-pocket payment arrangement. Social network is dwindling and traditional fa mily support is decreasing as urbanization and migrat ion take young me mbers of the family away. A lso, social changes are affecting the position of the elderly in the society and leading to a reduction in their social status and influence in the community. The pattern of seeing elderly people’s welfare as the responsibility of the family had made the government of Nigeria to do litt le or nothing to provide for their welfare. In many cases, when they are entitled to pension, this regrettably is not often paid on time. This is because of poor planning and management coupled with lack of interest in the general we lfare of aged persons. Also, those who engaged in private sectors that do not have retirement benefits for their workers suffer after their retirement. In Nigeria, poverty and poor infrastructural development which perpetrated ru ral co mmunit ies where most elderly people reside constraint them fro m achiev ing good wellbeing. Tradit ionally , the elderly are expected to rely p rimarily on their fa milies for economic and e motional support. At times if family support mechanism fails, co mmunity help may be availab le. However, the collapse in family t ies and structure also have negative effect on elders who are used to enjoy supports fro m extended jo int families where traditionally the elders are respected and properly catered for[9,22]. Due to the youthful nature of Nigeria age structure, government believes that the health problems that manifest among children and youths need mo re attention than that of the elderly. As a result, very litt le consideration is given to elderly in Nigeria by both the research community and policy makers. Average household sizes are large and a substantial proportion of o lder adults live alone. The econo mies of the elderly (65 years and above) in Iju mu co mmunity where the current study was conducted are predominantly supported by subsistence agriculture, wh ich provides little or no pension coverage and limited health care services. Nigerians age 65 and over are an important and growing segment of Nigeria population, there remains a gap in knowledge. In Nigeria, there has been limited research on wellbeing of elderly, especially in rural settings where people are most beset by poverty and poor health conditions. This study was aimed at p roviding a better understanding of the well-being of older people in Iju mu co mmunity, a rural setting in North-Central Nigeria. The resulting information provides an insight into the mechanism for examin ing the relationship between socio-demographic factors and well-being of elderly. There is also dearth of info rmation on determinants of elderly well-being in the rural co mmunities in Nigeria. Therefore, this study was designed to fill these g aps . The objectives of this study were to; examine socio-demographic differential in elderly well-being, determine the prevalence and identify the predictors of poor well-being among the elderly residence in the study area. The first objective was designed with the view to knowing the socio-demographic factors that are associated with elderly well-being. The prevalence and predictors of poor well-being among the elderly will assist the populace in knowing the true state of health of elderly in the commun ity. The vision to advance the well-being of elderly informed the choice of the study objectives. Studying the differential in well-being of the elderly is obligatory, as this will provide decisive in formation for planning and evaluating success of health services and interventions. It will help the planners and policy makers in their decisions and uphold existing framework on elderly care and supports in Nigeria. 2. Methods Study Area The study area was Ijumu, a rural co mmunity in North- Central Nigeria with a population figure of 119,929. The community is made up of three ad min istrative districts that is, Gbede district in the North, Iju mu-central and Ogidi/ Iju muOke district in the south. There are 15 political wards in the area with 5 in Gbede district, 4 in Iju mu -central district and 6 in Iju mu Oke district. There are also 740 enumeration areas Adebowale S. A. et al.: Elderly Well-being in a Rural Community in North Central Nigeria, sub- Sahar an Africa 94 (EAs) with 247 in Gbede district, 197 in Iju mu-Central and 296 in Iju mu-Oke. The elderly in the commun ity are predominantly farmers who practice agricu lture on subsistence scale. There are few health facilities in the area most of which a re not we ll equipped to meet health ca re needs of its citizen s . Study Design The study was descriptive cross-sectional in design and focused main ly on elderly people (65 years and above) residing in the a rea for at least a year. The reason for limiting to a year is to reduce bias that could occur as a result of people who are visitors or who have enjoyed facilities in the c ity and just migrated to the co mmunity. A mu lti-stage sampling technique was used to select the elig ible respondents. EAs were chosen proportionately fro m each of the districts. Thereafter, the households with at least one elderly person in each EAs were listed to constitute a sampling frame. Moreover, households were rando mly picked fro m each of the selected EAs using systematic random sampling technique. Ho wever, in a household having more than one eligible respondent, the respondent was picked using lottery method. Quantitative method of data collection was used to elicit research information. The questionnaire contained relevant questions that cover all the objectives of the study. Data were collected by trained interviewers after obtaining an informed consent from the respondents. The train ing of interviewers and translation of the contents of the questionnaire to local language provided opportunities for proper understanding, easy interpretation and admin istration of the questionnaire. Meas ures The dependent variable that was measured was well-being of respondents. Well-being was assessed using World Health Organization quality of life brief (WHOQOL-Bref) questionnaire. The likert scale which measures well-being in the past few weeks prior the survey was used. The questionnaire contains a total of 24 questions based on a 4-do main structure. The 4 do mains are physical, psychological, social re lationship, and environment. These domains consisted of 7, 6, 3, and 8 questions respectively. The questions were assessed on a five point scale ranging fro m 1 to 5. The domain scores were scaled in a positive direct ion. The overall well-being was dichotomized into poor or good based on WHO standard procedures. The WHOQOL-Bref questionnaire has been shown to be a valid measure of Qo L in the elderly. The instrument was adapted by Gureje and colleagues in 2008 and showed that it has an excellent internal reliability (Cronbach alpha = 0.86). It was designed as a self-rating instrument that could also be interviewer-ad ministered. Descriptive statistics was used to describe the wellbeing domains, these are; physical, psychological, social relat ionship and environmental. Cross-tabulations were used in presenting frequency distribution of socio-demographic variables and well-being. Chi-square statistics was used to assess association between these factors and elderly well-being. Thereafter, significant variables fro m Chi-square statistics were only considered for ordinary logistic regres- sion. This was used to identify the socio-demographic vari- ables that contribute to well-being. The logistic regression model is defined as; ???????? ???????????????????????? � 1 − � ???????? = ????????0 + ????????1 ???????? 1 + ????????2 ???????? 2 + ????????3 ???????? 3 + ⋯+ ???????????????? ???????????????? Where z is the outcome measure which is we llbe ing; z = 1 for poor wellbeing; z = 0 fo r good wellbeing. β1, β2, β3, and so on, are the regression coefficients to be estimated, xi’s are covariates such as gender, marital status, age of respondent, level o f education, religion, current work status, occupation, family type, children ever born e.t.c. The identified variables relating to well-being were further considered for mu ltip le regression analysis. These same set of variables were also used in generating eight different models based on their Wald statistics values beginning fro m the variab le with highest value to the least. This was done for variab les that were significantly related with well-being. % of Domain Classification 3. Results Figure 1 shows the mult iple bar chart of the percentage of domain classification (physical, psychological, social relationship and environmental) by well-being status of the respondents. Majority 59.0% of the respondents have physical well-being classified as good. The percentage of elderly who’s psychological, social relat ionship and environmental well-being do main was good were 53.3%, 48.9% and 47.1% respectively. Good Poor 70 60 50 40 30 20 10 0 Physical Psychological Social Environmental Relationship Well-Being Domains Figure 1. The Multiple Bar Chart of the percentage of Domain Classificat ion Table 1 shows the frequency distribution of the respondents’ well-being status by demographic variables. The data show that the mean age o f the respondents was 72.3±8.4 years and 65.2% were females. About 51.9% of the respondents have good well-being. The state of well-being does not show any association with gender as no variation existed between the females and males elderly well-being (p=0.905). There was a strong association between the age classified in group and well-being (p =0.000). The prevalence of poor well-being was more pronounced among elderly eighty years and above (72.0%) than any other age intervals, 95 Public Health Research 2012, 2(4): 92-101 whereas it was least among those aged 65-69 years (40.9%). In Table 1, the percentage of elderly classified as having poor well-being reduces with the increasing levels of education. It falls consistently fro m 54.1% among those with no education to 35.8% for those with higher level of education. The number of children previously born alive does not show a significant relat ionship with well-being (p=0.056), however, the pattern shows an indication that higher children previously life born can inh ibit good well-being of elderly. Also, variation of well-being existed among the subgroup of the respondents in terms of their marital status and this variation was statistically significant (p=0.001). The elderly who were separated (76.2%) experienced higher poor well-being than those in any other marital groups. Poor well-being was also pronounced among divorced and separated elderly, 57.5% and 50.2% respectively. Table 2 shows the frequency distribution of the respondents’ well-being status by social variables. The data depict that there was a significant association between religion and well-being of elderly in the study area (p=0.044) with respondents who belong to Islamic sect having higher p roportion of poor well-being (53.4%) than the Christians (47.1%). No significant association existed between family type (p=0.250) work history (p=0.742) currently financing children needs (p=0.863) and elderly well-being. However, the current work status shows significant association with well-being, the proportion of poor well-being elderly among those who were not working (56.9%) was higher than their counterparts who were working (44.0%). Respondents who claimed that both males and females children visit more regularly had lower proportion of poor well-being (35.8%) elderly as against those who mentioned their males (62.3%) or females (62.9%) children respectively. Elderly who were supported financially by both of their males and females children had a lower percentage of poor well-being (39.7%) as compared with those who were only supported by either their males (60.7%) or female (62.0%) children. There was significant association between well-being of elderly and those having children liv ing together with them at their ho mes (p=0.006). Those having their children living with them (52.8%) having higher proportion of poor well-being elders than those with no children living with them (44.8%). The percentage of elderly who have enough money to meet h is or daily and health needs (20.5%) were experiencing lower poor well-being than those who do not (57.1%). Table 3 shows ordinary logistic regression analysis of poor well-being by background characteristics. At this stage some of the variables such as education, relig ion and current work status who were significantly associated with elderly well-being using Chi-square test were not significantly related to poor well-being. Therefore, these set of variables were eliminated fro m further analysis. In Table 3, nu mber of children alive (β=-0.596), which of your children visit you more regularly (β=-0.545), are any of your children living with you (β=-0.508), do you have enough money to meet your daily and health needs (β=-1.357), were negatively significantly related to poor well-be ing. Table 1. Frequency Distribution of the Respondents Well-being Status by Demographic variables Demographic Ch aract erist ics WELLBEING GOOD P OOR TOTAL TOTAL 50.9(620) 49.1(597) Male Gender; χ2=0.0142 51.2(217) 48.8(207) Female 50.8(403) 49.2(390) 65-69 Age Group*; χ2=49.072 59.1(358) 40.9(248) 70-74 75-79 46.9(114) 39.8(41) 53.1(129) 60.2(62) 80-84 51.4(72) 48.6(68) 85+ 28.0(35) 72.0(90) Levels of Educat ion*; χ2=17.845 None Primary 45.9(294) 53.5(190) 54.1(347) 46.5(165) Secondary 60.0(84) 40.0(56) Higher 64.2(52) 35.8(29) Children Ever Born; χ2=7.563 1-2 64.9(48) 35.1(26) 3-4 53.3(152) 46.7(133) 5-6 50.0(214) 50.0(214) 7+ 48.5(205) 51.5(218) Marital Status**; χ2=18.818 Never married Currently married 55.0(11) 54.4(472) 45.0(9) 45.6(396) Widowed 42.5(124) 57.5(168) Divorced Sep arat ed 50.0(8) 23.8(5) 50.0(8) 76.2(16) *Significant at 0.1%; **Significant at 1% 100.0(1217) 100.0(424) 100.0(793) 100.0(606) 100.0(243) 100.0(103) 100.0(140) 100.0(125) 100.0(641) 100.0(355) 100.0(140) 100.0(81) 100.0(74) 100.0(285) 100.0(428) 100.0(423) 100.0(20) 100.0(868) 100.0(292) 100.0(16) 100.0(21) However, respondents’ age (β=+0.208), children ever born (β=+0.672), marital status (β=+0.260), financial support fro m children (β =+0.931) were positively significantly related with poor well-being. The data further show that having enough money to meet daily and health needs (OR=0.26,C.I=0.18-0.37), ch ild ren regular v isit (OR=0.58, C.I=0.48-0.69) and financial support from children (OR=2.54,C.I=1.84-3.49), each contributed more to the strength of poor well-being of elderly than any other variables considered in the analysis. Table 4 shows the mult iple log istic regression analysis of poor well-being by background characteristics. The data show that the older elderly people were more at risk of poor well-being than the younger elderly. Elderly who were Adebowale S. A. et al.: Elderly Well-being in a Rural Community in North Central Nigeria, sub- Sahar an Africa 96 within the age bracket 70-74, 75-79 and 85+ were 1.4 (C.I=1.0-2.0), 2.2 (C.I=1.3-3.5) and 4.9 (C.I=3.0-8.0) mo re likely to experience poor well-being than their counterparts in age group 65-69 years respectively. Elderly people who were no more in relationship with their spouses (separated) were 6.3 (C.I=1.3-30.0) mo re likely to have poor well-being than the unmarried elderly. The higher risk of poor well-being was more pronounced among elderly who were only visited regularly by their male children than those often visited by both of their males and females children (OR=0.4, C.I=0.3-0.6). Receiving financial assistance from ch ildren was found to reduce the risk of poor well-being as those who do not receive any financial assistance from their children were twice (OR=2.4, C.I=1.7-3.2) more likely to experience poor well-being than those who receive. Children living with elderly inhibit poor well being. The likelihood of poor well-being was lower among Elderly who have enough money to meet their daily and health needs (OR=0.2, C.I=0.1-0.3) than those who do not. Table 5 shows multip le logistic regression models of poor well-being according to background characteristics. The analysis that generated the results in table 5 was based on the strength of relationship of the variables with the poor well-being as shown by ordinary logistic regression in Table 3. The introduction of these variables which generated eight different models was based on the value of Wald statistic (WS). It is known that the higher the value of WS the more the strength of relationship, this could be seen in the generated probability value. The eight analytical models of the regression analysis show in Table 5 point to the interaction effects of well-being and the variables such as having enough money to meet daily and health needs, children v isit, financial support from children, age, ch ild ren liv ing with elderly, number of children ever born, marital status and number of children surviving. When the logistic regression analysis was restricted to only the variable; financial ab ility to meet daily and health needs, elderly who do not have such ability were five times (p<0.001) more likely to experience poor well-being than those who have (Model 1). The e xtent of the risk was statistically significant and reduces as different variables were introduced into the logistic regression analysis. Children visit (added in the second model) reduces the effect of having enough money to meet daily and health needs. Receiving financial assistance from children (Model 3) does not change the effects of having enough money to meet daily and health needs or children v isit. Age does not affect the influence of the other variables considered (Model 4). Elderly having child ren living with them slightly reduces the effect of receiving financial support fro m children, children v isit and having enough money to meet daily and health needs, but it is an important factor affecting the influence of age (Model 5). Nu mber of children ever born, marital status and number of children surviving added as control individually do not change the effects of variables considered in the previous models (Models 6, 7 and 8). The apparent significant relat ionship of well-being and given birth to seven or more children (7+), children living with the respondents, age group 80-84 disappeared when controlling for the effect of number of children surviving (Model 8). Table 2. Frequency Distribution of the Respondents Well-being Status by Social variables Social Characte ristics W ELLB EING GOOD POOR TO TAL Ch rist ian ity Islam Religion***; χ2=4.068 52.9(446) 47.1(397) 46.6(172) 53.4(197) Type of Family; χ2=1.326 100.0(843) 100.0(369) Monogamy Polygamy 52.3(370) 48.9(239) 47.7(338) 51.1(250) Work History; χ2=0.109 100.0(708) 100.0(489) Ever Worked 50.8(583) 49.2(564) 100.0(1147) Never Worked 52.9(37) 47.1(33) 100.0(70) Currently Work Status*; χ2=19.395 Working 56.0(413) 44.0(324) 100.0(737) Not Working 43.1(207) 56.9(273) 100.0(480) Which of your children visit you more regularly?*; χ2=87.496 Male 37.7(66) 62.3(109) 100.0(175) Female 37.1(152) 62.9(258) 100.0(410) Bot h 64.2(401) 35.8(224) 100.0(625) Financial support from children*; χ2=56.704 Male 39.3(72) 60.7(111) 100.0(183) Female 38.0(128) 62.0(209) 100.0(337) Bot h 60.3(420) 39.7(277) 100.0(697) Do you still spend for any of your chil dren?; χ2=0.030 Yes 50.9(330) 49.1(318) 100.0(648) No 51.4(289) 48.6(273) 100.0(562) Are any of your children living with you?**; χ2=7.658 Yes 47.2(288) 52.8(322) 100.0(610) No 55.2(331) 44.8(269) 100.0(600) Do you receive financial assistance from your children*; χ2=57.422 Yes 57.3(526) 42.7(392) 100.0(918) No 31.8(93) 68.2(199) 100.0(292) Do you have Enough Money to meet your Dail y and He alth needs?*; χ2=111.959 Yes 79.5(213) 20.5(55) 100.0(268) No 42.9(407) 57.1(542) 100.0(949) *Significant at 0.1%; **Significant at 1% ;*** Significant at 5% 97 Public Health Research 2012, 2(4): 92-101 Table 3. Ordinary Logistic Regression Analysis of Poor Well-being according to Background Characteristics Background Characte risti cs Age Educat ion Children Ever Born Children Alive Marital Status Religion Current Work Status Which of your CV you more regularly? Do you receive FAfrom your children Are any of your children living with you? Do you have EM to meet your DHN? Cons tan t β 0.208 -0.134 0.672 -0.596 0.260 0.264 0.278 -0.545 0.931 -0.508 -1.357 0.411 S.E 0.056 0.079 0.276 0.275 0.112 0.145 0.147 0.092 0.163 0.169 0.179 0.669 Wald Sig. Exp(β) 13.957 2.869 5.930 4.682 5.361 3.312 3.571 35.035 32.647 9.029 57.635 0.379 0.000 0.090 0.015 0.030 0.021 0.069 0.059 0.000 0.000 0.003 0.000 0.538 1.231* 0.874 1.958*** 0.551*** 1.296*** 1.301 1.321 0.580* 2.537* 0.602** 0.257* 1.509 95%C.I for Exp(β) Lowe r Uppe r 1.104 1.372 0.748 1.021 1.140 3.363 0.321 0.945 1.041 1.615 0.980 1.729 0.990 1.763 0.484 0.694 1.844 3.492 0.432 0.838 0.181 0.365 * Significant at 0.1%, ** Significant at 1% ; ***Significant at 5% ;CV: Child visit; FA: Financial Assistance; EM: Enough Money; DHN: Daily and Health Needs Table 4. Multiple Logistic Regression Analysis of Poor Well-being according to Background Characteristics Ba ckg roun d Characte ristics 65-69(R.F) 70-74 75-79 80-84 85+ 1-2(R.F) 3-4 5-6 7+ 1-2(R.F) 3-4 5-6 7+ Never married Currently married Widowed Divorced Sep arat ed Male Female Bot h Yes No Yes No Yes No Cons tan t 95%C.I for Exp(β) β S.E Wal d Sig. Exp(β) Lowe r Uppe r Age Group (R.F) (R.F) (R.F) (R.F) 1.000 (R.F) (R.F) 0.345 0.172 4.016 0.045 1.413*** 1.008 1.980 0.770 0.247 9.742 0.002 2.159** 1.332 3.502 0.408 0.217 3.531 0.060 1.503 0.983 2.300 1.590 0.248 41.091 0.000 4.906* 3.016 7.977 Children Eve r Born (R.F) (R.F) (R.F) (R.F) 1.000 (R.F) (R.F) 0.124 0.707 0.031 0.861 1.132 0.283 4.524 0.643 0.829 0.602 0.438 1.903 0.375 9.667 1.564 0.879 3.165 0.075 4.780 0.853 26.791 Chil dren Survi ving (R.F) (R.F) (R.F) (R.F) 1.000 (R.F) (R.F) 0.309 0.659 0.220 0.639 1.362 0.374 4.960 -0.136 0.787 0.030 0.863 0.873 0.187 4.084 -1.093 0.844 1.679 0.195 0.335 0.064 1.752 Marital Status (R.F) (R.F) (R.F) (R.F) 1.000 (R.F) (R.F) 0.450 0.579 0.605 0.437 1.568 0.505 4.875 0.570 0.592 0.929 0.335 1.769 0.555 5.642 0.866 0.794 1.192 0.275 2.378 0.502 11.268 1.830 0.803 5.192 0.023 6.232*** 1.292 30.065 Which of your children visit you more regularly? (R.F) (R.F) (R.F) (R.F) 1.000 (R.F) (R.F) 0.122 0.202 0.363 0.547 1.130 0.760 1.680 -0.867 0.194 20.015 0.000 0.420* 0.287 0.614 Do you receive financial assistance from your children (R.F) (R.F) (R.F) (R.F) 1.000 (R.F) (R.F) 0.856 0.161 28.159 0.000 2.354* 1.716 3.229 Are any of your children living with you? (R.F) (R.F) (R.F) (R.F) 1.000 (R.F) (R.F) -0.359 0.140 6.534 0.011 0.699*** 0.531 0.920 Do you have Enough Money to meet your Dail y and He alth needs? -1.440 0.182 62.427 0.000 0.237* 0.166 0.339 (R.F) (R.F) (R.F) (R.F) 1.000 (R.F) (R.F) -0.720 0.674 1.140 0.286 0.487 * Significant at 0.1% ;**Significant at 1% ;***Significant at 5% Adebowale S. A. et al.: Elderly Well-being in a Rural Community in North Central Nigeria, sub- Sahar an Africa 98 Table 5. Multiple Logistic Regression Models of Poor Well-being according to Background Characteristics B AC KGROUND Model1 Model2 Model3 Model4 VARIABLES N=1217 N=1210 N=1210 N=1210 Do you have Enough Money to meet your Dail y and He alth needs? Yes 1.000 1.000 1.000 1.000 No 5.157* 4.700* 4.342* 4.177* Which of your children visit you more regularly? Male 1.000 1.000 1.000 Female 1.095 1.101 1.154 Bot h 0.381* 0.417* 0.441* Do you receive financial assistance from your children Yes 1.000 1.000 No 2.101* 2.568* Age Group 65-69(R.F) 1.000 70-74 1.449** 75-79 1.988** 80-84 1.400 85+ 4.710* Are any of your children living with you? Yes No Children Eve r Born 1-2(R.F) 3-4 5-6 7+ Marital Status Never Married Currently Married Widowed Divorced Sep arat ed Chil dren Survi ving 1-2(R.F) 3-4 5-6 7+ Cons tan t -1.354* 0.439* 0.374* 0.252* -2 Log likelihood Cox & Snell R2 Nagelkerke R2 1568.4 0.093 0.124 1490.7 0.143 0.190 1465.7 0.160 0.213 1415.1 0.194 0.259 * Significant at 0.1%, **Significant at 5% Model5 N=1210 1.000 4.111* 1.000 1.153 0.433* 1.000 2.412* 1.000 1.477** 2.191** 1.542** 5.192* 1.000 0.708** 0.299* 1408.7 0.199 0.265 Model6 N=1210 1.000 4.086* 1.000 1.135 0.423* 1.000 2.455* 1.000 1.440** 2.162** 1.520** 5.120* 1.000 0.736** 1.000 1.659 1.766 1.839** 0.177* 1404.4 0.202 0.269 Model7 N=1210 1.000 4.106* 1.000 1.105 0.422* 1.000 2.452* 1.000 1.429** 2.156** 1.474 4.961* 1.000 0.717** 1.000 1.631 1.786 1.868** 1.000 1.508 1.811 2.238 5.926** 0.112** 1395.6 0.207 0.277 Model8 N=1206 1.000 4.219* 1.000 1.130 0.420* 1.000 2.354* 1.000 1.413** 2.159** 1.503 4.906* 1.000 0.699 1.000 1.132 1.903 4.780 1.000 1.568 1.769 2.378 6.232** 1.000 1.362 0.873 0.335 0.115** 1382.1 0.213 0.284 4. Discussion This study was informed as a result of poor attitudes of government to elderly which are totally neglected thereby not bothered about their health and financial needs. In Nigeria, no policy or social security systemhas ever been put in place to care for people at their o ld age. Also, the primary health care system has no special provision for providing health care for the elderly, and even the overall hea lth policy show no special concern for the elderly. The retirees who served in public or private organization at their younger ages are often given gratuity and pension which were deducted fro m their monthly salary while in active service. Most at times, the dues are not received prior the death of the beneficiaries as a result of bureaucratic system in the organizations where they serviced. Due to poverty and poor infrastructural develop ment, elderly people living in Nigeria not only face lower life expectancies but also live a higher proportion of their lives in poor health. Govern ments have lackadaisical stance to the health of the aged and family structure which have been known to give care to elderly are on the verge of collapse. All these have adverse effect on the health of elderly which transform to their well-being status[9, 26]. In the current study, our data show that majority of the respondents have good physical and psychological well-being. This is an indication that good well-being transition is beginning in Nigeria even among the non-privileged sectors of the population fro m wh ich our samp le was drawn. Therefore, it is worthwhile to know that the transition is beginning to appear among the remote rural population involved in our research. Approximately the same proportion of the respondents had good and poor well-being. The mean age of the respondents was seventy two years and higher proportion of the elderly was females. Higher proportion of elderly females reflects the age structure of Nigeria popula- 99 Public Health Research 2012, 2(4): 92-101 tion which has more wo men at its upper tail end. The state of well-being does not show any association with gender. This is contrary to previous researches which show that women have longer life expectancy and spend a greater total number of years in good health than men; however, wo men spend a greater proportion of the older years in poor health than men[27, 28]. Another study found that elderly married males enjoy better health than the elderly females. The study concluded that the traditional role that wo men play as the primary care givers, coupled with the lower status leave them with access to limited financial resources and health care for themselves. Variables such as the age classified in group, education, marital status were associated with elderly well-being. The percentage of elderly classified as having poor well-being reduces with the increasing level of schooling attained. The difference is particu larly marked among wo men with higher level of education. Education has a lot of positive influence on well-being; educated elderly are likely to receive higher monthly pension, more knowledgeable on means of preventing and treatment of diseases, live in a clean environment. Kabir and colleagues studied the relationship between incidence of disease and the socio-economic characteristics of the elderly respondents and found that education was inversely related to the incidence of disease among the elderly. Their findings and that of another study further revealed that educational attain ment influences socioeconomic status, which plays a ro le in well-being at o lder ages. Higher levels of education are usually associated with higher incomes, higher standards of living and above average health[9, 30]. The current study show that variation of well-being existed among the subgroup of women in terms of their marital status. This is consistent with the result of s tudies from other parts of the world. For instance, a study found marital status to be associated with health and survival outcomes among elderly. The elderly who were separated experienced higher poor well-being than those in any other marital groups. In any rural part of Nigeria, either wo men or men who are separated and live alone do not accord respect and are often stigmatized and marginalized on things that can benefit their health. As a result, they go through psychological stress which can have serious effect on their well-being[21,22]. Unlike those who are married which tend to benefit fro m spousal supports and the widows/widowers do enjoy the concern, sympathy and support of the family and the community. Marital status can strongly affect one’s emotional and economic well-being as it influences living provisions and the availability of caregivers for elderly with an illness or d is ab ility [ 32 ]. Significant association also existed between religion and well-being of elderly in the study area with Islamic sect having higher proportion of poor well-being elderly than the Christians. Often, the Muslims engage in polygamous, marry new wives at older ages, and bear many children thus the financial means of the family are spread across its members. The family resources that ought to be used to meeting the daily and health needs of the elderly are concentrated on the care for younger children’s needs and education. The finding is in accordance with the result fro m previous studies[20, 32-34]. The study further found that no significant association existed between family type, work history and elderly well-being. So me older people wo rk as a result of economic necessity. Others may be attracted by the social contact, intellectual challenges, or sense of value that work often provides. The current wo rk status shows significant association with well-being, the proportion of poor well-being elderly among those who are not working was higher than their counterparts who were working. The association disappeared when the variab le was entered into ord inary logistic regression model. Elderly who were only visited regularly by their male children have higher risk of poor well-being than those often visited by both males and females ch ildren. Studies have established that daughters give more care to their aged parents than the males[35,36]. Males get occupied with their job and their immediate family needs. Also, elderly who usually receive financial support fro m their children have better well-being than those who do not. This is because most elderly people do not have the strength to work; therefore any financial assistance from the children will go a long way at allev iating their health and financial needs. Children living with elderly appear to bring greater vulnerability to poor well-being than those liv ing alone. Such elderly can be those who still have young children or grandchildren to cater for. The diversion of care to meeting the needs of their young children can have negative impact on the health of the elderly. 5. Conclusions Well-being considered to be poor is very co mmon among the elderly in the study area. The identified major socio-demographic factors that are predictors of elderly poor well-being were; older age, being separated after marriage, visits by only male children, not receiving financial support fro m children, ch ildren living with elderly and not having enough money to meet daily and health needs. While developing policies aim at imp roving elderly well-being in Nigeria, government should include; age, marital status, financial assistance from children, children visit by gender, children living with elderly and having enough money to meet daily needs as part of their key variables. Though Govern ments and individuals are not oblivious of the necessity for committed care for the elderly in Nigeria, however, not much has been done to ensure better well-being for the elderly. Govern ment should develop health and financial policies aim at improving well-being of elderly in the study community. 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