1CHAPTER ONE 1.1 INTRODUCTION The concept of informed choice in family planning can be applied to a wide range of sexual and reproductive health decisions. It focuses on whether to seek to avoid pregnancy, whether to space and time one‘s childbearing, whether to use contraception, what family method to use, and whether and when to continue or switch methods. The term family planning choice could also refer to a family decision-making, Diaz, Jasis, Pachauri, Pine, Planta, Ruminjo, Steele, Tabbut- Henry and Widyantoro (1999). The principle of informed choice focuses on the individual. Yet most people‘s family planning decisions also reflect a range of outside influences. Social and cultural norms, gender roles, social networks, religion, and local beliefs influence peoples‘ choices (Bosveld, 1998). To a large extent, these community norms determine individual childbearing preferences and sexual and reproductive behaviour. Community and culture affect a person‘s attitude towards family planning, desired sex of children, preferences about family size, family pressures to have children and whether family planning accords with customs and religious beliefs, Dixon-Meuller (1999); Greenwell (1999) and Vickers (1974). Community norms also prescribe how much autonomy individuals have in making family planning decisions. The larger the differences in 2 reproductive intentions within a community, the more likely that community norms support individual choices Bosveld (1998) and Dixon-Mueller (1999). Household and community influences can be so powerful that they can obscure the line between individual desires and community norms. For instance, in some culture, many women reject contraception because bearing and raising children is the path to respect and dignity in the society; International Planned Parenthood Federation (1996); Cherkaovi (2000); and Barnett (2001). In either countries most women use contraception because having small families is the norm, Mkangi (2001); and Lutz (2003). People are often unaware that such norms influences their choices. In other cases they are particularly aware. For example, young people often decide not to seek family planning because they do not want their parents or other adults to know that they are sexually active. Many fear ridicule, disapproval and hostile attitude from service providers and others, Jejebhoy (2004). A person‘s social environment usually has more influence on family planning decisions than do the attributes of specific contraceptives. In Kenya, for example, when new clients were asked to give a single reason for their choice of a specific family planning method, most cited the attitudes of their spouse or their peers, or their religion or value, Kim, Kols, Mucheka (1998). In many countries family planning programs are part of national economic and social development efforts. Efforts to foster equity in decision-making and raise awareness about reproductive right of the family, 3 community, and society also promote informed choice of family planning, Jacobnson (2000). As women gain more autonomy, they are better able to claim their rights as individuals, including the right to act to protect their own reproductive health, Heise, Ellsberg and Gottemeller (1999). Everybody belongs to informal social networks that influence their behaviour to some degree, Montgometry (2000); Panel on Population Projections, Committee on Population and National Research Council (2000); Roger (1999); and Valente (1995). Social networks include the extended family, friends, neighbours, political groups, church group, youth groups, and other formal and informal associations. During the course of the day, women often speak to other women about family planning and experience with contraceptive use. For many women, informal communication is a primary source of family planning information, Rutenberg and Watkins (2002). The influence of social networks is crucial to informed choice. Most people seek the approval of others and modify their own behaviour to please others or to meet others‘ expectations, Bongaarts (1996), Stash (2000); and Valente, Watkins, Jato, Vanderstraten and Tsitsol (2000). Individual health behaviour is influenced by how a person thinks that others view their behaviour, Rutenberg and Watkins (2000). In Nigeria and other West African Countries for example, some women said that, it was difficult for them to use family planning because their relatives or friends were not using it. These women were reluctant to be the first in their social group to use 4 family planning, Stash (2000). People choose contraceptive methods that are commonly used in their community because they know that it is socially acceptable to do so, and they tend to know more about these methods, Rogers and Kincaid (2004); and Valente, Watkins, Jato, Vanderstraten and Tsitsol (2000). Many women use the same family planning method that others in their social networks use, Godley (2001). A 1998 study in urban Nigeria found that the more widely used a method was, the more attractive it became to others in the cities and villages - Entuisle, Rindfuss, Guilkey, Chamrathrithirong, Curran and Sawangdee (1999). Entire communities may encourage one type of contraceptive based on the choices of early contraceptive users, rather than individual needs - Potter (1999). Even when people are aware of the side effects or failures experienced by other users of a method, sometimes they still prefer it because it is familiar, Entwisle, Rindfuss, Guikey, Chamtratrithirong, Curran and Sawangdee (1999). While social networks exerts a strong influence on more people‘s reproductive attitudes and behaviour, family planning programs themselves influence social norms through the diffusion of new ideas about contraceptive use - Cleland, and Mauldin (2001). Based on a review of studies over the previous two decades, research in 1996 found that programs have helped convert people‘s interest in having fewer children into a definite demand for contraception. They have done so largely by making 5 contraceptive use more accessible, common and acceptable in many communities - Freedman (1997). Family planning programs are often the deciding factor for people who want to avoid pregnancy but who feel uncertain about using family planning - Jainn (1999); and Magnani, Hotchkiss, Florence and Shafer (1999). The role of social networks in the diffusion of new ideas about family planning has been recognized for several decades - Retherford and Palmore (1999). As more and more people decide to use family planning, it has become increasingly acceptable for others to choose to do so as well, Cleland and Wilson (2004). In Nigeria, most research on family planning choices have been based exclusively on family planning methods, scarcely do we have studies linking family planning choices to socio-cultural and norms factors. It is therefore not to the knowledge of the researcher that studies linking family planning choices to couples socio-cultural norms have been carried out. It is against this background that this study becomes relevant in filling such missing gaps in our knowledge in the issue of socio-cultural and norm factors and family planning choices among couples in Ibadan metropolis, in Nigeria. When studying families, women's fertility is one of those topics that is sort of a constant drumbeat in the background. Sociologists around the world have fretted about this for decades; they want us to care. We read things like the fact that the 6 current fertility rate around the world is so low, that the United Nations has decided it is "unprecedented in human history." And while we were impressed by how as dramatic a statement that was, still, falling total fertility rates and replacement rates just seemed too abstract for us to get all that worked up about. The fertility rates are at or under the replacement rate in every developed nation in the world, and fall as those in less-developed nations increase the literacy and educational attainment of their populations. However, education and literacy alone do not appear to be the sole determinant of fertility rates. For example, educational attainment has dramatically risen in some Arab and Asian nations, but the fertility rates of those nations have not changed as much as was expected. So there must be other cultural, social and economic factors may diminish or even outweigh the education factor. Similarly, the general theory is that a rise of women's educational attainment will delay the women's age at first childbirth. The women will put off starting a family because they are in school or in work, or perhaps it is just because the education included lessons about contraception. But literacy rates in Cuba are some of the highest in the world. And while Cuba's fertility rate is one of the lowest in the world, the increased literacy hasn't seemed to have any other effect. Conversely, the age at which women are having children is declining, when it would usually be expected to be rising. In a study of employed Cuban women, 7 all of whom had easily available birth control and abortions, 50 percent of them had had a child before the age of 20. Actually, in many countries, women's actual fertility rate is consistently below their average desired number of children. Meaning women have less children than the number they consider to be ideal. And often, no matter what size of family the woman has, she always thinks that a larger number of children is actually the ideal. And that holds true the bigger the family she has. 1.2 SCOPE AND LIMITATION This study is delimited to the adults in the three Local Governments considered. Mushin is a suburb of Lagos, located in Lagos State, Nigeria, and is one of Nigeria's 774 Local Government Areas. It is located 10 km north of the Lagos city core, adjacent to the main road toIkeja, and is a largely a congested residential area with inadequate sanitation and low-quality housing. It had 633,009 inhabitants at the 2006 Census. Amuwo Odofin is one of the 57 Local Government Councils that make up Lagos State , which was created out of the old Amuwo Odofin Local Government on 27 October 2003. It covers land mass of 100q.km, divided into two distinct geographical spheres of Upland and Riverine areas. For political expediency, the Local Government is divided into three geo-political zones, that is, 8 the Riverine, the Middle Belt and the Upper Belt. The Riverine area comprises Towns and Villages such as Tomaro, Ilado, Okun Glass, Sankey, Igbo Alejo, Igbologun etc. The middle belt begins with the Local Government boundary adjacent to Apapa Local Government through the Tincan Coconut area, Beach- land Estate. The Upper belt comprises Amuwo Odofin Estate, Raji Rasaki Estate, Amuwo Odofin New Town, Festac Town , Abule Ado, Trade-fair Complex among others. The Local Government, with a population of over 1,500,000 according to the 2006 Census shares its boundaries with Ajeromi and Ifelodun Local Government in the East, Oriade Local Government in the West, the Badagry Creek to the South and Isolo/Igando Local Government to the North. Ikeja is an outer-ring suburb of the city of Lagos and capital of Lagos State. It is also one of Nigeria's 774 Local Government Areas (LGAs). The Murtala Mohammed International Airportis located there. Prior to the emergence of military rule in the early 1980s, Ikeja was a well planned, clean and quiet residential environment with shopping malls, pharmacies and government reservation areas. Ikeja is also home to the Femi Kuti's Africa Shrine andLagbaja's Motherlan', both live music venues. 9 1.3 AIMS and OBJECTIVES 1. To identify the family planning practice in the study area. 2. To determine the relationship between family practices and size of the family 3. To determine whether the family planning practices depends on occupation. 4. To determine whether family planning practices depends on religion. 1.5 LITERATURE REVIEW Ware (1974) revealed that there is no measure that provides an equal effective index of the potential for change in family size in developing countries. Reflection of norms and culture of a place, particularly those that are related to the value of children affect decisions of people on family size, (Kent & Larson 1982). Ware (1975) in his article on the limits of acceptable family size in western Nigeria drew data from interviews with a stratified probability sample of 2996 Yoruba men and women aged 17 or above living in Lagos and Western States in June–July 1973. Although drawing upon other material from the 1 ½-hour interviews the discussion concentrates upon the family size ideals of these individuals. In addition to the customary measures of ideal family size, new measures of the limits of 10 acceptable family size are described, together with the reactions of the whole sample to a wide range of statements relating to family size and the value of children. It is shown that the smallest family which would be acceptable to any appreciable proportion of the population is four children, which would be acceptable to 18% of all respondents. Comparative data from elsewhere in the developing world are presented to show that African family size ideals are amongst the highest in the world. Age, educational and occupational differentials in perceptions of different family sizes are also discussed. Lucas and Ukaegbu (1977) in their paper on other limits of acceptable family size in Sourthern Nigeria compared the results of questions about the best number of children and the desire for more children from three Nigerian sample surveys of adult females: in the Lagos metropolis (1973), in West Nigeria (1973), and among the Ngwa Ibo in the East Central State (1974). In Lagos and West Nigeria support for the ‗small‘ family (of four children or, rarely, less) is more prevalent amongst the younger, urban bred and educated women: when these achieve their preferred family size a decline in fertility may be implemented. Among the Ngwa Ibo four children are seen as too few and the desire to stop childbearing only receives majority support from wives with seven or more surviving children. Economic constraints on family size have less impact on the Ngwa Ibo but glimmerings of 11 interest in family limitation, albeit at high parities, are apparent among the educated Ngwa wives. Adams (1981) in his presentation on family size and the quality of children in a Presidential address to the population association of America noted that if couples decide to have fewer children in order to achieve higher ―quality‖ offspring, are they correct in assuming that the quality of children bears an important and inverse relation to family size? If they are correct, how does number of children operate to affect individual quality? This research (using U.S. whites primarily) takes educational attainment (among adults) and college plans (among youngsters) as the principal indicators of quality, but also directs some attention to measures of intelligence. The analysis supports the ―dilution model‖ (on average, the more children the lower the quality of each child) and indicates that only children do not suffer from lack of siblings, and that other last-borns are not handicapped by a ―teaching deficit.‖ Number of siblings (relative to other background variables) is found to have an important detrimental impact on child quality-an impact compounded by the fact that, when couples are at a stage in life to make family- size decisions, most background factors (however important to the quality of their children) are no longer readily manipulatable. A special path analysis of college plans among boys uses a modification of Sewell‘s Wisconsin Model as its base. The results show that number of siblings is a negative influence on intervening 12 variables affecting college plans. In general, the research documents the unfavorable consequences for individual siblings of high fertility, even in a country that is (at least for whites) as socially, economically, and politically advantaged as the United States. Oyewole et al (1983) in their write-up on desired family size and sex of children in Nigeria stated that in 1981, sex ratio data and preferences for family size and for combinations and permutations of children were provided by 333 Nigerian students at the University of ilorli, liorin, Nigeria. For the present and parental generations cornblned, the seconcia, sex ratio was estimated to be 95.8 males:100 females. In the projected families, preferences for family sizes resulted in an average of 4.88 children per family. The most preferred family consisted of fot, children-a 2m2f combination in a mimi order, whereas the second most perferred family consisted of five children-a 3m2f combination In a mfmfm order. Also expressed was a strong preference for permutations of sexes, resulting In a male child as first-born followed by an alternation of sexes. A eater preference for male children was indicated by the combined sex ratio of 167 males:100 females for the preferred families. 13 Axinn and Thornton (1984) in a journal on family and household investigate the influence of parents‘ marital dissolutions on their children‘s attitudes toward several dimensions of family formation. Hypotheses focus on the role of parents‘ attitudes as a mechanism linking parents‘ behavior to their children‘s attitudes. We test these hypotheses using intergenerational panel data that include measures of parents‘ attitudes taken directly from parents and measures of children‘s attitudes taken directly from children. Results demonstrate strong effects of parental divorce, remarriage, and widowhood on children‘s attitudes toward premarital sex, cohabitation, marriage. childbearing, and divorce. The results also show that parents‘ own attitudes link their behavior to their children‘s attitudes, although substantial effects of parental behavior remain after controlling for parents‘ attitudes. An earlier version of this paper was presented at the 1994 annual meetings of the American Sociological Association, held in Los Angeles. The authors wish to thank the National Science Foundation (Grant SES-9257724) and the National Institute of Child Health and Human Development (Grant UO1 HD30928-01) for their financial support of this research. We wish to thank Jennifer Barber for her assistance with analyses reported here and her helpful comments on the manuscript. We also thank Kazuo Yamaguchi for his helpful answers to statistical questions. Finally, we would like to thank the anonymous 14 reviewers for their helpful comments and suggestions. Any errors or omissions remain the responsibility of the authors alone. Ascadi and Ascadi (1990) revealed that in societies where fertility is controlled by lineage, ancestors and gods‘ agents who do not recognize individual desire in fertility decision making, and where fertility controls are not widespread; their response to ideal family size will be altered by the variables mentioned. Belmont and Marolla (1990) in his article on Birth Order, Family Size, and Intelligence, the relation of birth order and family size to intellectual performance, as measured by the Raven Progressive Matrices, was examined among nearly all of 400,000 19-year-old males born in the Netherlands in 1944 through 1947. It was found that birth order and family size had independent effects on intellectual performance. Effects of family size were not present in all social classes, but effects of birth order were consistent across social class. Victor (1992) in a journal on Chance, Child Traits, and Choice of Family Size Uses a model of maximization of expected utility, where utility depends on the number and traits of children, as well as consumption. The model is applied to the case when the sex of children is the relevant trait of children to explore questions of family size. The model generates qualitative predictions linking sex composition of children to the propensity to have more children. It is expected that families with 15 either a larger or smaller proportion of boys than they desire or expect in the next birth tend toward larger families than those whose experience conforms more closely to the desired and expected composition. In cases where families modify the expected sex of children in light of the sex composition of their own children, this result depends on the assumption that the demand for children has a price elasticity lower than unity. Data for the United States and East Pakistan are consistent with these predictions. The same theoretical framework is applied to infant survival. Zick and Xiang (1994) explained that the relationship between income and demand for children is not necessarily linear; and an increase in income may not necessarily lead to an increase in demand for children because individuals may choose to invest in the quality of surviving children. NDHS (2003) summits that most families based their family size on their economic status especially wealth. For instance, most opulent men, irrespective of their residence, married wives and even deviate from tamable family size because of their level of opulence. But most highly rich families have the lowest family size. Meanwhile, the lowest wealth quintile has high family mean. Filtop (1998) in his article on Family size and the quality of children noted If couples decide to have fewer children in order to achieve higher ―quality‖ 16 offspring, are they correct in assuming that the quality of children bears an important and inverse relation to family size? If they are correct, how does number of children operate to affect individual quality? This research (using U.S. whites primarily) takes educational attainment (among adults) and college plans (among youngsters) as the principal indicators of quality, but also directs some attention to measures of intelligence. The analysis supports the ―dilution model‖ (on average, the more children the lower the quality of each child) and indicates that only children do not suffer from lack of siblings, and that other last-borns are not handicapped by a ―teaching deficit.‖ Number of siblings (relative to other background variables) is found to have an important detrimental impact on child quality—an impact compounded by the fact that, when couples are at a stage in life to make family-size decisions, most background factors (however important to the quality of their children) are no longer readily manipulable. A special path analysis of college plans among boys uses a modification of Sewell‘s Wisconsin Model as its base. The results show that number of siblings is a negative influence on intervening variables affecting college plans. In general, the research documents the unfavorable consequences for individual siblings of high fertility, even in a country that is (at least for whites) as socially, economically, and politically advantaged as the United States. 17 Family size limitation and birth spacing considered Two models of fertility change in the initial stages of decline are explored: (1) fertility changes occur among older women in response to changes in long-term family-size targets (stopping effects); (2) family-size changes reflect decisions at each parity level to delay or prevent the birth of the next child (spacing effects). The "stopping" and "spacing" effects are examined among Asian and African immigrants in Israel. The data show important spacing effects among these immigrants that relate mainly to socioeconomic change rather than cultural factors. Comparisons with other subpopulations suggest that there are no general, universal rules of spacing or stopping patterns in the transition to lower fertility. Psacharopoulos et al (2000) in their paper on family size, schooling and child labour in Peru analyzes the effects of being indigenous, number of siblings, sibling activities and sibling age structure on child schooling progress and child non- school activity. The analysis is based on the Peru 1991 Living Standards Survey. The analysis shows that family size is important. However, the analysis also demonstrates the importance of taking into consideration the activities of siblings. The number of siblings not entrolled in school proves to be an important control variable in at least one specification of the empirical model. However, more research is needed on the interactions between siblings, their activities and their age structure. In other words, an attempt must be made to find ways of taking into 18 account the ―life cycle effects‖ of one‗s siblings on their schooling performance and labor force activity. The analysis also shows that the age structure of siblings is important, but in conjunction with their activities. That is, having a greater number of younger siblings implies less schooling, more age-grade distortion in the classroom and more child labor. Keep and Dewilde (2002) in their article on Contraceptive choice in the completed family used a 2-page questionnaire; the 1st part was self-administered while the 2nd half of the questionnaire allowed for the physician to interview the respondents. The survey studied the demographic characteristics of the respondents and the relationship of these characteristics to contraceptive choice, family size and possible future choice in contraception. Demographic information assayed included age and occupation and religion of the respondent and the number of unplanned children. 235 of the 359 respondents (2/3) considered their family complete. 70% of those surveyed used some form of contraception with oral contraceptives and female sterilization being the most popular currently used methods and oral contraceptives and condoms being the most popular ever used method. Motivations for contraceptive choice were also evaluated (family health, age, socioeconomic conditions, etc). Although a large number of unplanned pregnancies were reported, they were not necessarily unwanted. The failure a contraceptive method may account for this. Over 80% of those surveyed had used 19 oral contraceptives at some time. Although the couples agreed on family size, the reasoning behind their decision was obtuse and not well planned. Sterilization created mixed emotions among both partners. Its popularity stems from the standard recommendation of discontinued use of oral contraceptives after age 35. However, doctors need to be considerate of the ambivalent feelings of their patients and recommend choices that leave options open without presenting health risks. Vopel et al (2004) in their article on citation, family size, opposition and the value of patent rights combined estimates of the value of patent rights from a survey of patent-holders with a set of indicator variables in order to model the value of patents. Our results suggest that the number of references to the patent literature as well as the citations a patent receives are positively related to its value. References to the non-patent literature are informative about the value of pharmaceutical and chemical patents, but not in other technical fields. Patents which are upheld in opposition and annulment procedures and patents representing large international patent families are particularly valuable. Singarepore (2005) paper and analysis statistical snippet revealed that family size is becoming smaller in the average number of children born to the ever married females, and that there was a negative correlation between family size and 20 educational attainment of the mother. Graduate mothers had on average 1.3 - 1.4 children, while those with below secondary education had 3.3 - 3.4 children. Singarepore identified two factors which contribute to the phenomenon. These are: 1. Delay child bearing of graduates 2. Termination of smaller size by graduate mother The fertility deferential between graduate mothers with those below secondary education is larger at younger age groups but narrowed with age. This shows both the delay in child bearing of graduate mothers‘ vis-à-vis below secondary education mothers, and the catching up time progresses. Though, there is a catch- up process by graduate mothers, the eventual family size [with reference to another aged 50 and above] below secondary mothers is still much higher than graduate mothers. This supports the McCarthy and Oni (1987) that the number of surviving children, women‘s education, and sex preferences significantly affect desired family size. Meanwhile, young people in Kenya revealed significant negative effect of age, education, mass media exposure, and modern orientation, on ideal family size; of these variables education and age have the strongest effect, (Musyok, 1983). Men in Nigeria want more children than women. Ideal family size among urban men is lower than that of rural men with 6.6 and 9.8 respectively. 21 Regional difference is also high because men in the northwest versus south west revealed 12.8 & 4.8 respectively, (NDHS 2003). Park (2005) submitted that poverty, unemployment, and social isolation are features of family in which children are abused. When family well-being is hampered, violence comes into such families. Generally, family violence refers to any rough and illegitimate use of physical force, aggression, or verbal abuse by one family member towards another. Kalesanwo and Emmanuel (2009) in their article on Assessment of Adults` Opinion On The Ideal Family Size And Family Well-being In Ogun State, Nigeria noted that family can be taken to mean a unit consisting of husband and wife, and their children, (Moses and Adewale 2002). Moses, Patric and Olarenwaju (2001) quoting Otite and Ogion (1981) reported that family as a bio-social group, meaning that family has both biological and social aspects. Moses and Adewale (2002) quoting Murdrock (1965) defines family as a social group characterized by common residence, economic, cooperation, and reproduction. They reported that family is a group of persons united by ties of marriage, blood, or adoption constituting a single house hold; interacting and communicating with each other in their respective social role of husband and wife, mother and father, brother and sister, as well as maintaining a common culture. Moses, Patrick, and Olarenwaju 22 (2001) classified family into extended and nuclear family based on the kinship system; this system is based on blood relation and marriage. Based on Lifecycle family, they also grouped family into family of orientation and family of procreation. While on the basis of modernization, they further grouped family into traditional family, modern family, and post-modern family. It is basically a microcosm of larger society, so any tension in family creates tension in the society at large. Yeatman and Trinitapoli (2010) in their write-up on the relationship between religion and family planning in rural Malawi noted that despite the centrality of religion and fertility to life in rural Africa, the relationship between the two remains poorly understood. The study presented here uses unique integrated individual- and congregational-level data from rural Malawi to examine religious influences on contraceptive use. In this religiously diverse population, we find evidence that the particular characteristics of a congregation-leader‘s positive attitudes toward family planning and discussion of sexual morality, which do not fall along broad denominational lines-are more relevant than denominational categories for predicting women‘s contraceptive use. They further find evidence for a relationship between religious socialization and contraceptive behavior. 23 Olajide (2010) in his article on Socio-Cultural and Norms Factors Influencing Family Planning Choices among Couples in Ibadan Metropolis, Nigeria established the influence of socio-cultural and norms factors on couples‘ family planning choices. Couples involved in the study were randomly selected from five different professions in Ibadan constituted the sample for the study. The two instruments used were author-constructed questionnaires with 0.62 and o.69 reliability co-efficient respectively. The data obtained were analyzed using chi- square statistics and multiple regression analysis. The results indicated that significant relationship existed between social and cultural factors (252.959); gender roles (176.849); social networks (95.424); religion (125.742); and local belief factors (205.196). The results further indicated that a combination of the five independent variables significantly predicted couples family planning choices yielding a co-efficient multiple regression (R) of 0.467 and F-ratio of 57.241. The results further revealed that significant relationship existed between each of the independent variables except local belief factors. Based on the results of this finding, it was recommended that those in the helping professions should take cognizance of those variables that have been found to influence family planning choices among couples. 24 Fayehun et al (2011) in his article on sex of preceding child and birth spacing among Nigerian ethnic groups was of the view that in seeking for more effective ways of fertility control and improvement of maternal and child health through birth spacing in a predominantly patrilineal society like Nigeria, this study explores how the sex of a previous child affects birth interval among ethnic groups, controlling for demographic and socioeconomic variables. The study utilized birth history data from the 2008 Nigeria Demographic and Health Survey. The findings showed that the effect of sex of prior births on the birth interval is slightly significant among the Igbo and the Southern minorities, who tend to desire to have a male child sooner if preceding births were female. Among all the ethnic groups, women who are yet to meet their ideal sex preference have a shorter birth interval than those who have. Apart from the evident sex preferences, these results suggest that Nigerian parents also undertake sex balancing among their children. There is a consistent and strong relationship between the survival of a child and subsequent birth interval, which suggest that women have a short birth interval, and hence a large family size, because they are not certain that their children would survive. 25 CHAPTER TWO 2.0 DATA COLLECTION The instrument for this study is a self-structured questionnaire that covers 3 items (finance, religion and literacy) that serve as the basis for choice on family size and child spacing was used to collect data to test the hypotheses raised for this study (see appendix A for questionnaire). Mushin has a population of 1,121,697 people, Amuwo-Odofin has a population of 956,543 people and Ikeja has a population of 786,178 people (Nigeria news- Nigeria Population 2006). Two hundred respondents were randomly chosen from each Local Government (cluster) using simple random sampling techniques summing to 600 respondents. The sampling covered both the rural and urban segment of the locality with interest on the adults. The data obtained were collated and analyzed using inferential statistics of chi- square to test the acceptance and non-acceptance of the hypotheses. 26 CHAPTER THREE 3.0 DATA ANALYSIS The data obtained were analyzed using inferential statistics of chi-square. In probability theory and statistics, the chi-squared distribution (also chi- square or χ²-distribution) with k degrees of freedom is the distribution of a sum of the squares of k independent standard normal random variables. It is one of the most widely used probability distributions in inferential statistics, e.g., in hypothesis testing or in construction of confidence intervals. When there is a need to contrast it with the non-central chi-squared distribution, this distribution is sometimes called the central chi-squared distribution. The chi-squared distribution is used in the common chi-squared tests for goodness of fit of an observed distribution to a theoretical one, the independence of two criteria of classification of qualitative data, and in confidence interval estimation for a population standard deviation of a normal distribution from a sample standard deviation. Many other statistical tests also use this distribution, like Friedman's analysis of variance by ranks. 27 The procedure of the chi-square test is as follows: 1. Formulate the null hypothesis 2. Compute the expected frequencies of the cells 3. Expected frequency C ij = R i * C J N r c r c N =∑R i = ∑C j = ∑∑ = O ij 1 1 1 1 Where R i = ith row‘s marginal frequencies C j = jth column‘s marginal frequencies N = total number of observation 28 4. Compute the test statistic r c χ 2 = ∑ ∑ (o ij – e ij ) 2 1 1 e ij Where o ij = observed frequency e ij = expected frequency 4. Decide the α-level of significance and read from table χ 2(α ) df Where df = (r-1)(c-1) 5. Decision rule: reject Ho if χ 2 > χ 2(α) df and accept if otherwise. 6. Conclude appropriately. 29 3.1.1 Test on Family Size Family Size Entry 1 1 2 2 3 3 4 4 ≥ 5 5 H o = There‘s a statistical significant association between Child spacing and family size. i.e the years for child spacing considered do not equally affect the family sizes. H 1 = There‘s no statistical significant association between Child spacing and family size. i.e the years for child spacing considered equally affect the family sizes. 30 Case Processing Summary Cases Valid Missing Total N Percent N Percent N Percent Child_Spacing * Family_Size 1800 100.0% 0 .0% 1800 100.0% D.R: Accept H 0 if ρ (Asymp. Sig. (2-sided)) is ≤ 0.05 and reject otherwise. Chi-Square Tests Value df Asymp. Sig. (2- sided) Pearson Chi-Square 649.964 a 16 .000 Likelihood Ratio 692.749 16 .000 Linear-by-Linear Association 21.662 1 .000 N of Valid Cases 1800 a. 0 cells (.0%) have expected count less than 5. The minimum expected count is 15.68. Conclusion: Since ρ = .000 < .005, we accept H 0 that there‘s a statistical significant association between Child spacing and family size. i.e the years for child spacing considered do not equally affect the family sizes. 31 Symmetric Measures Value Approx. Sig. Nominal by Nominal Phi .601 .000 Cramer's V .300 .000 N of Valid Cases 1800 Phi and Cramer's V are both tests of the strength of association. At ρ = .601, the strength of association between the variables is not very strong. Post-Hoc Analysis When there is a difference in the performance of samples from the same population, the post-hoc test in SPSS points out the different variable. This is done using the standardized residual it has approximately a standard normal distribution. Values of the standardized residual outside the range -2 ≤ S.R ≤ 2, shows a really big difference with the observed value. 32 Child_Spacing * Family_Size Crosstabulation Family_Size Total 1.00 2.00 3.00 4.00 5.00 Child_Spacing 1.00 Count 123 68 41 9 1 242 Std. Residual 13.6 -2.2 -1.4 -4.5 -5.1 2.00 Count 82 191 128 202 169 772 Std. Residual -3.7 -5.4 -2.7 8.1 8.4 3.00 Count 9 209 98 55 39 410 Std. Residual -7.0 4.9 1.3 -.8 -1.2 4.00 Count 45 106 87 3 0 241 Std. Residual 1.1 1.9 5.1 -5.5 -5.3 5.00 Count 27 83 25 0 0 135 Std. Residual 1.2 4.8 -.6 -4.5 -4.0 Total Count 286 657 379 269 209 1800 Results Parents with three (3) children who choose to space their children with a year led to the unequal choice of family size. Equal choices was observed by Parents planning 2 years child spacing. 33 Parents with three (3) and five (5) children respectively who choose to space their children with 3 years led to the unequal choice of family size. Parents with one (1) and two (2) children respectively who choose to space their children with 4 years led to the unequal choice of family size. Parents with one (1) child who choose to space their children with a year led to the unequal choice of family size. 34 3.1.2 Test on Income Income Entry ≤ #50,000 1 #51,000 - #80,000 2 #81,000 - #100,000 3 #100,000 < 4 H o = There‘s a statistical significant association between Child spacing and income. i.e the years for child spacing considered do not equally affect the income. H 1 = There‘s no statistical significant association between Child spacing and income. i.e the years for child spacing considered equally affect the income. 35 Case Processing Summary Cases Valid Missing Total N Percent N Percent N Percent Child_Spacing_3 * Income 1767 98.2% 33 1.8% 1800 100.0% D.R: Accept H 0 if ρ (Asymp. Sig. (2-sided)) is ≤ 0.05 and reject otherwise. Chi-Square Tests Value df Asymp. Sig. (2- sided) Pearson Chi-Square 192.793 a 12 .000 Likelihood Ratio 202.810 12 .000 Linear-by-Linear Association 9.358 1 .002 N of Valid Cases 1767 a. 0 cells (.0%) have expected count less than 5. The minimum expected count is 15.10. Conclusion: Since ρ = .000 < .005, we accept H 0 that there‘s a statistical significant association between Child spacing and income. i.e the years for child spacing considered do not equally affect the income. 36 Symmetric Measures Value Approx. Sig. Nominal by Nominal Phi .330 .000 Cramer's V .191 .000 N of Valid Cases 1767 Phi and Cramer's V are both tests of the strength of association. At ρ = .330, the strength of association between the variables is not very weak. Post-Hoc Analysis When there is a difference in the performance of samples from the same population, the post-hoc test in SPSS points out the different variable. This is done using the standardized residual it has approximately a standard normal distribution. Values of the standardized residual outside the range -2 ≤ S.R ≤ 2, shows a really big difference with the observed value. 37 Child_Spacing_3 * Income Crosstabulation Income Total 1.00 2.00 3.00 4.00 Child_Spacing_3 1.00 Count 109 96 85 23 313 Std. Residual -1.7 1.5 1.3 -.9 2.00 Count 221 124 71 93 509 Std. Residual .8 -.9 -4.5 7.1 3.00 Count 76 67 20 7 170 Std. Residual .7 3.3 -3.2 -2.1 4.00 Count 112 80 140 31 363 Std. Residual -3.0 -1.6 5.8 -.2 5.00 Count 208 98 103 3 412 Std. Residual 3.0 -1.0 .5 -5.6 Total Count 726 465 419 157 1767 Results Parents choose to space their children with a year irrespective of their income Parents whose income is below #80,000 prefer a 2 years spacing period leading to unequal choice of the 3 years spacing period. 38 Parents whose income is below #50,000 prefer a 3 years spacing period leading to unequal choice of the 3 years spacing period. Parents whose income is below #80,000 and above #100,000 prefer a 4 years spacing period leading to unequal choice of the 3 years spacing period. Parents whose income is between #50,000 and #100,000 prefer a 5 years spacing period leading to unequal choice of the 3 years spacing period. 39 3.1.3 Test on Religion Religion Entry Christian 1 Muslim 2 Traditional 3 Others 4 H o = There‘s a statistical significant association between Child spacing and Religion. i.e the years for child spacing considered do not equally affect the Religion. H 1 = There‘s no statistical significant association between Child spacing and Religion. i.e the years for child spacing considered equally affect the Religion. 40 Case Processing Summary Cases Valid Missing Total N Percent N Percent N Percent Child_Spacing_2 * Religion 1800 100.0% 0 .0% 1800 100.0% D.R: Accept H 0 if ρ (Asymp. Sig. (2-sided)) is ≤ 0.05 and reject otherwise. Chi-Square Tests Value df Asymp. Sig. (2- sided) Pearson Chi-Square 187.254 a 12 .000 Likelihood Ratio 186.457 12 .000 Linear-by-Linear Association 31.079 1 .000 N of Valid Cases 1800 a. 0 cells (.0%) have expected count less than 5. The minimum expected count is 11.80. Conclusion: Since ρ = .000 < .005, we accept H 0 that there‘s a statistical significant association between Child spacing and religion. i.e the years for child spacing considered do not equally affect the religion. 41 Symmetric Measures Value Approx. Sig. Nominal by Nominal Phi .323 .000 Cramer's V .186 .000 N of Valid Cases 1800 Phi and Cramer's V are both tests of the strength of association. At ρ = .323, the strength of association between the variables is very weak. Post-Hoc Analysis When there is a difference in the performance of samples from the same population, the post-hoc test in SPSS points out the different variable. This is done using the standardized residual it has approximately a standard normal distribution. Values of the standardized residual outside the range -2 ≤ S.R ≤ 2, shows a really big difference with the observed value. 42 Child_Spacing_2 * Religion Crosstabulation Religion Total 1.00 2.00 3.00 4.00 Child_Spacing_2 1.00 Count 28 146 98 64 336 Std. Residual -2.2 -1.6 .4 5.4 2.00 Count 40 201 138 44 423 Std. Residual -1.9 -.6 1.8 .4 3.00 Count 113 350 98 54 615 Std. Residual 4.0 2.6 -5.6 -.8 4.00 Count 26 123 150 7 306 Std. Residual -2.0 -2.3 7.0 -4.2 5.00 Count 21 72 19 8 120 Std. Residual 1.5 1.6 -2.5 -1.1 Total Count 228 892 503 177 1800 Results Muslim and traditional believers of the respondents who choose to space their children with a year led to the unequal choice of child spacing. Traditional believers and the respondents of other religion who choose to space their children with 2 years led to the unequal choice of child spacing. 43 Respondents of other religion who choose to space their children with 3 years led to the unequal choice of child spacing. Religion did not affect the response of parents with 4 years child spacing plan. Traditional believers of the respondents who choose to space their children with 5 years led to the unequal choice of child spacing. 44 3.1.4 Test on Literacy Literacy Entry FSLC 1 SSCE 2 Diploma/OND/NCE 3 BSC/BED 4 Masters 5 PHD 6 H o = There‘s a statistical significant association between Child spacing and literacy. i.e the years for child spacing considered do not equally affect the literacy. H 1 = There‘s no statistical significant association between Child spacing and literacy. i.e the years for child spacing considered equally affect the literacy. 45 Case Processing Summary Cases Valid Missing Total N Percent N Percent N Percent Child_Spacing_1 * Literacy 1800 100.0% 0 .0% 1800 100.0% D.R: Accept H 0 if ρ (Asymp. Sig. (2-sided)) is ≤ 0.05 and reject otherwise. Chi-Square Tests Value df Asymp. Sig. (2- sided) Pearson Chi-Square 2251.899 a 30 .000 Likelihood Ratio 1175.120 30 .000 Linear-by-Linear Association 95.511 1 .000 N of Valid Cases 1800 a. 3 cells (7.1%) have expected count less than 5. The minimum expected count is 3.83. Conclusion: Since ρ = .000 < .005, we accept H 0 that there‘s a statistical significant association between Child spacing and family size. i.e the years for child spacing considered do not equally affect the family sizes. 46 Symmetric Measures Value Approx. Sig. Nominal by Nominal Phi 1.119 .000 Cramer's V .500 .000 N of Valid Cases 1800 Phi and Cramer's V are both tests of the strength of association. At ρ = 1.119, the strength of association between the variables is very strong. Post-Hoc Analysis When there is a difference in the performance of samples from the same population, the post-hoc test in SPSS points out the different variable. This is done using the standardized residual it has approximately a standard normal distribution. Values of the standardized residual outside the range -2 ≤ S.R ≤ 2, shows a really big difference with the observed value. 47 Child_Spacing_1 * Literacy Crosstabulation Literacy Total .00 1.00 2.00 3.00 4.00 5.00 6.00 Child_Spacing_1 .00 Count 92 0 0 0 0 0 0 92 Std. Residual 40.3 -6.0 -4.5 -3.8 -2.8 -2.3 -2.0 1.00 Count 0 41 43 21 9 14 0 128 Std. Residual -2.6 -1.4 2.9 .3 -.6 2.5 -2.3 2.00 Count 0 108 87 65 53 0 0 313 Std. Residual -4.0 -1.4 2.4 2.4 5.1 -4.2 -3.6 3.00 Count 0 411 131 81 34 15 75 747 Std. Residual -6.2 6.7 -2.4 -3.2 -3.7 -4.2 7.9 4.00 Count 0 99 106 70 52 74 0 401 Std. Residual -4.5 -4.7 2.1 1.1 3.1 10.7 -4.1 5.00 Count 0 53 21 40 5 0 0 119 Std. Residual -2.5 .9 -.9 5.1 -1.6 -2.6 -2.2 Total Count 92 712 388 277 153 103 75 1800 Results Parents with FSLC, Diploma, OND, NCE, BSC and BED who choose to space their children with a year led to the unequal choice of child spacing. 48 Parents with FSLC who choose to space their children with 2 years led to the unequal choice of child spacing. Parents who choose to space their children with a 3 years are not affected by their educational level or background. Parents with SSCE, Diploma, OND and NCE who choose to space their children with 4 years led to the unequal choice of child spacing. . Parents with FSLC and SSCE who choose to space their children with 5 years led to the unequal choice of child spacing. 49 CHAPTER FOUR 4.0 Summary, Conclusion and Recommendations 4.1 Summary This study looked into the role of child spacing as it is affected by family size, income, religion and literacy level in Mushin, Amuwo-Odofin and Ikeja all in Lagos State. For this purpose, a well-structured questionnaire (see appendix 5) was constructed and distributed to 600 respondents (Parents) in each cluster. Analysis was done using SPSS17. 4.2 Conclusion Four hypotheses were tested and in all of which the null hypothesis was accepted indicating that the various family sizes, income groups, religion, and literacy levels influences parent choice on appropriate child spacing in most cases unequally as shown below: 50 Results from Family size Parents with three (3) children who choose to space their children with a year led to the unequal choice of family size. Equal choices was observed by Parents planning 2 years child spacing. Parents with three (3) and five (5) children respectively who choose to space their children with 3 years led to the unequal choice of family size. Parents with one (1) and two (2) children respectively who choose to space their children with 4 years led to the unequal choice of family size. Parents with one (1) child who choose to space their children with a year led to the unequal choice of family size. 51 Results from Income Parents choose to space their children with a year irrespective of their income Parents whose income is below #80,000 prefer a 2 years spacing period leading to unequal choice of the 3 years spacing period. Parents whose income is below #50,000 prefer a 3 years spacing period leading to unequal choice of the 3 years spacing period. Parents whose income is below #80,000 and above #100,000 prefer a 4 years spacing period leading to unequal choice of the 3 years spacing period. Parents whose income is between #50,000 and #100,000 prefer a 5 years spacing period leading to unequal choice of the 3 years spacing period. 52 Results from Religion Muslim and traditional believers of the respondents who choose to space their children with a year led to the unequal choice of child spacing. Traditional believers and the respondents of other religion who choose to space their children with 2 years led to the unequal choice of child spacing. Respondents of other religion who choose to space their children with 3 years led to the unequal choice of child spacing. Religion did not affect the response of parents with 4 years child spacing plan. Traditional believers of the respondents who choose to space their children with 5 years led to the unequal choice of child spacing. 53 Results from Literacy level Parents with FSLC, Diploma, OND, NCE, BSC and BED who choose to space their children with a year led to the unequal choice of child spacing. Parents with FSLC who choose to space their children with 2 years led to the unequal choice of child spacing. Parents who choose to space their children with a 3 years are not affected by their educational level or background. Parents with SSCE, Diploma, OND and NCE who choose to space their children with 4 years led to the unequal choice of child spacing. . Parents with FSLC and SSCE who choose to space their children with 5 years led to the unequal choice of child spacing. 54 4.3 Recommendation Based on the findings and conclusion above, the following are recommended: 1. Teaching of Family life education must continue in every home and community through qualified personnel. 2. Government and private bodies should collaborate to provide family planning facilities in all parts of the state and encourage their utilization. 3. Family planning facilities should be made available and easily accessible to the rural dwellers. 4. Family life education must be extended to all areas to enhance their birth control awareness.