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10
Multilevel Modeling of Influences on Transitions to Adulthood in Developing Countries with Special Reference to Cameroon

Barthélémy Kuate-Defo




Adolescence is a critical period in an individual’s life. During this time many key social, economic, biological, developmental, and demographic events occur that set the stage for adult life. Not surprisingly, therefore, adolescents are widely recognized as a critical target group for reproductive health and other social policies and programs. Yet the growing interest in adolescents in the policy and programming arenas has drawn attention to the gaps in research regarding the status and situation of adolescents in developing countries and the transitions to adulthood that individuals experience.

One of the chronic methodological problems that has hampered a deep understanding of the transition from childhood to adulthood is the inadequacy of traditional statistical techniques for modeling hierarchy. Such techniques estimate models without taking into account the clustered structure of data. As a result they have fostered an impoverished conceptualization of relationships between exposure and response variables and have often discouraged the formulation of explicit multilevel models with hypotheses about effects occurring at each level and across levels. They have caused concerns about aggregation bias, misestimated precision, and the “unit of analysis” and “level of measurement” problems, concerns that are better addressed with multilevel approaches (Bryk and Raudenbush, 1992; Goldstein, 2003; Kuate-Defo, 2005a; Searle, Casella, and McCulloch, 1992; Snijders and Bosker, 1999). Building on a theoretical framework developed by the National Research Council (NRC)’s Panel on Transitions to Adulthood in Developing Countries, this chapter formulates and estimates multilevel models that identify the fixed and random effects of covariates at the



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The Changing Transitions to Adulthood in Developing Countries: Selected Studies 10 Multilevel Modeling of Influences on Transitions to Adulthood in Developing Countries with Special Reference to Cameroon Barthélémy Kuate-Defo Adolescence is a critical period in an individual’s life. During this time many key social, economic, biological, developmental, and demographic events occur that set the stage for adult life. Not surprisingly, therefore, adolescents are widely recognized as a critical target group for reproductive health and other social policies and programs. Yet the growing interest in adolescents in the policy and programming arenas has drawn attention to the gaps in research regarding the status and situation of adolescents in developing countries and the transitions to adulthood that individuals experience. One of the chronic methodological problems that has hampered a deep understanding of the transition from childhood to adulthood is the inadequacy of traditional statistical techniques for modeling hierarchy. Such techniques estimate models without taking into account the clustered structure of data. As a result they have fostered an impoverished conceptualization of relationships between exposure and response variables and have often discouraged the formulation of explicit multilevel models with hypotheses about effects occurring at each level and across levels. They have caused concerns about aggregation bias, misestimated precision, and the “unit of analysis” and “level of measurement” problems, concerns that are better addressed with multilevel approaches (Bryk and Raudenbush, 1992; Goldstein, 2003; Kuate-Defo, 2005a; Searle, Casella, and McCulloch, 1992; Snijders and Bosker, 1999). Building on a theoretical framework developed by the National Research Council (NRC)’s Panel on Transitions to Adulthood in Developing Countries, this chapter formulates and estimates multilevel models that identify the fixed and random effects of covariates at the

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The Changing Transitions to Adulthood in Developing Countries: Selected Studies appropriate units of analysis, level-specific contextual effects, and nested random influences in estimating the influences of competing factors on various transitional events. Data from Cameroon are used to illustrate the features of this methodology and to test several assumptions of the theoretical framework of the NRC’s Panel on Transitions to Adulthood in Developing Countries. Cameroon has special appeal because it is generally considered a microcosmic representation of tropical Africa due to its diversity. We use a multilevel modeling framework because individuals are bound by family, neighborhood, community, regional, national, and international factors that influence their individual or collective behaviors, so that treating these individuals as independent observations within a study may be quite misleading. Indeed, there is potentially some correlation among individuals interacting and behaving like others within their various contexts of life, which may remain even after all measured variables are taken into account in analyses. This study posits that this correlation is a consequence of developmental, normative or behavioral, structural or contextual factors that are related to various transitions to adulthood and are common to groups of individuals but that are unmeasured or unmeasurable. Correlated observations violate a standard assumption of independence in statistical analyses, resulting in understated standard errors and a greater likelihood of committing Type I errors and, in the case of nonlinear models such as survival models, estimated parameters that are both biased and inconsistent (Kuate-Defo, 2001). The next section of this chapter considers the meaning of successful and healthy transitions to adulthood in the context of a developing country. The following section presents the logic and assumptions of multilevel modeling as well as data requirements. The data set, main relations considered and statistical methods are then described. The two final sections present the main empirical findings and discuss their implications. SUCCESSFUL AND HEALTHY TRANSITIONS TO ADULTHOOD Half of the population worldwide is now under age 25, with the largest ever generation of adolescents—1.2 billion people between the ages of 10 and 19—representing one fifth of the world’s population (UNFPA, 2003a). Such growth puts untimely pressure on the limited and/or scarce resources that can prepare these young people for a better future. This is because more than 87 percent of them live in a developing world with changing and diverse socioeconomic, cultural, and epidemiological circumstances often made harsh by poverty. The impact of these circumstances on the options of adolescents and youth is apparent as they move through the lifecycle and are expected to assume adult roles. On the other hand, this large number of

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The Changing Transitions to Adulthood in Developing Countries: Selected Studies young people presents a unique opportunity for development and social growth in the developing world, notwithstanding variability in levels and areas of investment, fertility levels, dependency ratios, opportunity structures within the economy, socioeconomic situations of families, and level of development of communities and nations. Adolescence is a critical stage in the development of gender roles and responsibilities. Individuals in this transitory period attempt to cope with many life options and choices, including those related to friendship, courtship, marriage, education, employment, reproductive life and health, family formation and childbearing, lifestyles, and nutrition. Within any society, these options and choices influence and determine the timing, sequencing, and readiness to experience events marking the passage from adolescence to adulthood as well as the well-being and quality of life at later ages. Adulthood is characterized by a number of roles expected from people treated as adults. Role is a behavioral concept well established in social science and has special appeal within the multilevel framework, owing to the unique quality of the role concept as a link between the social and individual levels, because communities, households, families/extended families, and social groups are all structural contexts where individuals live and exercise their roles and responsibilities. The sequential pattern of those roles over the life cycle defines to some extent the adult life course. Adult life in all societies is more compartmentalized than the life of children because it is dominated to a greater extent by formalized expectations and obligations as expressed in the legal, social, cultural, and moral codes of conduct and behavior. These aspects of adult life are well captured by the concept of role and adult behavior. To pinpoint the extent to which transitions are successful/unsuccessful or healthy/unhealthy for an adolescent within a given social context, one must come up with some role properties. Role properties, both positive and negative according to the legal, social, cultural, and moral codes of conduct and behavior, have relevance for understanding the changes in status of individuals as they experience events portraying specific transitions through their life course. As the life of an individual at any moment can be thought of as the array of roles that he or she enacts, so can the person’s life course be conceptualized as a sequence of roles enacted. Throughout the life course, each person occupies a variety of roles involving opportunities and resource constraints as well as expectations and demands. Some of these roles are age dependent (e.g., being enrolled in school), while others are both age and sex dependent (e.g., being pregnant). During the life course, attachment in the relatively uncompartmentalized life of the infant is seen as analogous to more diverse forms of social support in various adult role settings. The constructive aspects of adult roles embedded in experienced states are features of successful transitions,

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The Changing Transitions to Adulthood in Developing Countries: Selected Studies but have not been studied much in developing countries in part because the research emphasis has been on the demand and expectational attributes and therefore, the literature on successful transitions from adolescence to adulthood remains scarce. The constructive aspects of roles imply roles that offer opportunities to acquire new skills and abilities and use those already acquired. In this study, roles or events with positive properties will characterize successful transitions, in contrast to roles or events with negative properties. Furthermore, successful transitions can be associated with unhealthy events or health problems and in such cases, we treat the transition as unhealthy, whether it is successful or not. For example, in Cameroon, the legal age at marriage is 15 for girls and 18 for boys and the legal age at entry into the labor force is 15 for both sexes. This means that from a sociolegal point of view, transitions to employment, marriage, household headship, and marital childbearing are legal transitions in the Cameroon context if they occurred at or after age 15, except for marriage and fatherhood, which should occur only at or after age 18 for boys. MULTILEVEL FRAMEWORK FOR THE STUDY OF TRANSITIONS TO ADULTHOOD: LOGIC, ASSUMPTIONS, AND DATA REQUIREMENTS Many kinds of data in the social, biological, behavioral, biomedical and clinical sciences have a multilevel (or hierarchical, clustered or nested) structure and many designed surveys on human subjects also create data hierarchies. Young people from the same families (or households), communities, or higher level groupings tend to be more alike in terms of factors that are likely to be positively or negatively associated with their transition to adulthood than their peers chosen at random from the general population. We argue that multilevel modeling is the most appropriate methodology for testing the theoretical framework developed by the NRC’s Panel on Transitions to Adulthood in Developing Countries. From a multilevel perspective, the panel’s framework considers five units of analysis or levels of operation of influences for the study of changing transitions to adulthood: the global context, the national context, the community context, the individual, and the within-individual changes in the transition to adulthood. The panel’s framework highlights the interlinkages and influences between context and individual behavior and is based on the main assumption that much of what happens to young people in developing countries and what constitutes their daily experience, are shaped by the contexts in which their lives are embedded. This chapter uses the multilevel framework to explicit test this panel’s assumption that contexts matter in young people’s transition to adulthood. We do so by separating the net influences of individual attributes from the fixed and random context-dependent effects using avail-

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The Changing Transitions to Adulthood in Developing Countries: Selected Studies able data from Cameroon to document the significance of the fixed effects and random effects of both community context and province context, net of the fixed and random effects of individual-level and household-level covariates. Although not made explicit in the panel’s framework, it is understood that how the effects of the global context, the national context and the community context operate will have different implications for young males and young females as well as for young people from different family backgrounds defined by such characteristics as socioeconomic status and ethnicity. We explicitly test this panel’s conjecture by estimating separate models for young males and young females and by estimating the effects of ethnicity and the index of socioeconomic status at the household and community levels using illustrative data from Cameroon renown for its ethnic diversity. In order words, the panel’s framework implicitly considers that young people differ for reasons that may be associated with the contexts they have been exposed to and this necessary differentiation may also be influenced by the characteristics of individuals so that once contexts are established and fixed for individuals, even if their establishment were effectively random, they will tend to become differentiated and this differentiation or variability implies that the context and those living in it both influence and are influenced by the context membership. There is nothing methodologically and substantively wrong with aggregate analysis when the study focuses only on macro-level propositions once proper account is taken of the fact the reliability of an aggregated variable depends on the number of micro-level units in a macro-level unit and thus will be larger for the larger macro-units than for the smaller ones (Kuate-Defo, 2005a). In cases where the interest of the study centers on macro-micro propositions as articulated in the theoretical framework developed by the NRC panel, however, aggregation may result in gross errors and wrong conclusions. Such conclusions may be either due to the ‘shift of meaning’ in that a variable aggregated to the macro level refers to the macro-units and not directly to the micro-units (Snijders and Bosker, 1999), the ecological fallacy in that a correlation between macro-level variables cannot be used to make assertions about micro-level relationships (Robinson, 1950), the neglect of the original data structure especially when some kind of analysis of covariance is used (e.g., in a study of transition to adulthood, we may be interested among other things in assessing between-community differences in young people’s transition to adulthood after correcting for innate individual differences), or due to the fact that aggregation prevents from examination the net effects of micro-level variables in the presence of other influential variables and nested random influences or the potential cross-level interaction effects of a specified micro-level variable (e.g., ethnic affiliation or gender) with a macro-level variable (e.g., urban place of residence). Multilevel statistical models are always needed if a multistage sampling design has been employed,

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The Changing Transitions to Adulthood in Developing Countries: Selected Studies and are used to examine the macro-micro relationships between variables at different levels of hierarchy. With multistage samples typical of most surveys, the population of interest usually consists of sub-populations from which selection occurs. A common mistake in research is to ignore this sampling scheme and to overlook the fact that lower-level units were not sampled independently from each other but that instead they are dependent and nested observations: having selected a primary unit (e.g., a community) increases the chances of selection of secondary units (e.g., individuals or households) from that community. In multilevel analysis, such nested dependency of lower-level units within higher-level units is of focal interest and the underlying assumption is that units within an entity at a given level of observation share the same environment and resources. To ignore this relationship or the “unit of analysis” problem in testing the theoretical framework of the NRC panel—e.g., by using aggregate analysis or traditional regression techniques which recognize only the individual youth as the units of analysis and ignore their groupings within the community or other higher-level contexts nested in the national context for instance—amounts to overlooking the importance of context effects which are at its heart. For instance, young people within any one community share the same characteristics and may tend to be similar so that they provide rather less information than would have been the case if the same number of young people were drawn from different communities. Hence, for a meaningful study of transitions to adulthood and depending on available data, it is important to understand the factors associated with such variations from one young person to another within a family or household, from household to household within a community, and from community to community within a country, for example. One may draw wrong conclusions if either of these sources of variability is ignored. That is why it is illuminating to explicitly model the variability associated with each level of nesting, as documented in this study. One could then investigate the extent to which any of the explanatory variables at the individual/household level say, could explain between-community variation, or assess whether transition to adulthood rate differences between young males and young females vary from community to community within a province or from province to province within a country such as Cameroon. One central issue in specifying context effects is the definition of an individual’s geographical area which in turn is contingent upon the context being considered and the data requirements. There are no existing data or statistical methods that can fully test all the five levels of the theoretical framework of the NRC Panel on Transitions to Adulthood in Developing Countries, which we view as a generic framework from that standpoint,

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The Changing Transitions to Adulthood in Developing Countries: Selected Studies since past surveys including the Demographic and Health Surveys (DHS) have not been designed for doing such multilevel analysis. Nonetheless, because the most widely available and comparable data sources for developing countries remain the DHS-type surveys, which have multistage sampling designs, multilevel modeling is the most appropriate methodology for the analysis of such data to study transition to adulthood, given their complex patterns of variability. One cannot use such data without taking into account the clustering in complex sample design where the first-stage sampling unit is often a well-defined geographical unit and further stages of random selection are carried out until the eligible households are selected and individual respondents interviewed. Such sampling procedures only provide for clustered data and preclude the possibility that units are cross-classified (i.e., a young person belonging simultaneously to two or more contexts at the same level of observation, each of which being potentially an influential variable in that young person’s life). Hence, we can articulate the multilevel models for clustered data, with a focus on nested/multilevel sources of variability. We do so by stacking DHS-type data from the individual (e.g., background information and individual characteristics), household (e.g., relationships to head of household, household amenities), and community (e.g., socioeconomic infrastructure and community endowment) questionnaires as well as macro-level data considered at higher levels (e.g., physical environment and climate), to create a clustered or hierarchical data file with appropriate units of analysis as illustrated in Kuate-Defo (2001), and that fully exploit information from these questionnaires that are relevant to a study of transition to adulthood. In order to stack these files together to build a clustered data file for multilevel modeling, a given individual must belong to one and only one household which in turn must belong to one and only one community which must belong to one and only one province, and so forth, in order to isolate “pure” context effects uncovered in our study. This stacking imposes that the hierarchical contexts (household, community, province) within which the life of an individual is embedded are invariant over the observation period in order for a given unit of analysis and level of observation to be valid for an individual in clustered data and for rigorous multilevel analysis to be doable since well-defined contextual units are required, otherwise the basic assumption of multilevel theory is violated. The identification of “pure” context effects necessary imposes that migrant respondents must be excluded from analyses because their inclusion would have as a prerequisite the availability of cross-classified data on the different age-specific contexts of residence and explanatory variables that may be time-varying in the life course of each individual; in this case, multilevel modeling of jointly clustered and cross-classified data would have to be available.

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The Changing Transitions to Adulthood in Developing Countries: Selected Studies DATA AND RELATIONSHIPS BETWEEN EXPOSURE AND RESPSPONSE VARIABLES Data Source The data set used for application in this chapter comes from the 1998 Cameroon Demographic and Health Survey (or CDHS-98; Central Bureau of Population Studies, 1998) that collected cross-sectional and nationally representative information at the individual, household, community, and regional or provincial levels. The special feature of the CDHS-98 data most relevant for this study is the availability of duration data on mutually exclusive, cause-specific school termination reported by women ages 15 to 49 at the time of the survey. These data were retrieved from questions S111a (“Age stopped attending school”) and V154 (“Reason stopped attending school”), which were asked to female respondents who attended school and obviously not to those with no schooling. We also adopt a gender perspective in this study by assessing the likelihood of investment in education on the transition opportunities of both female and male youth to adulthood within the socioeconomic context of Cameroon where statistically significant gender gaps in educational attainment still persists. The analyses therefore concern both female and male youths’ experiences with specific events before their 25th birthday and characterizing their change of status to adult roles and responsibilities. Indeed, in the CDHS-98, 14.3 percent of female youth ages 15 to 19 years had no schooling, and 17.7 percent of female youth ages 20 to 24 years never started school; in contrast, only 5.6 percent of male youth ages 15 to 19 years had no schooling, and 4.5 percent of those ages 20 to 24 years never attended school. These data have been found to be of good quality (Fotso et al., 1999; Kuate-Defo, 2000). The theoretical framework of the NRC’s Panel on Transitions to Adulthood in Developing Countries assumes that the timing and sequencing of events and transitions experienced by young people during their life course are produced by the contexts in which they live. Thus, its main thrust is a nested structure of interlinkages of context effects in the presence of other explanatory and random influences on transition to adulthood. Dealing with cross-classified data on contexts for the same individual (which lends itself to viewing migration as a truly endogenous behavior), requires at least three things: (1) migration histories on the different places of residences of each individual and on changing individual, household, community, and national characteristics inherent in the life experiences of that individual; (2) relevant clustered and cross-classified multilevel data; and (3) multilevel models for clustered and cross-classified data with potentially endogenous variables. This implies

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The Changing Transitions to Adulthood in Developing Countries: Selected Studies that one would need for a study of transition within the nested contexts, both cross-classified contextual information on each individual and time-dependent-context-dependent explanatory variables in the life course of that individual. That would give rise to clustered cross-classified data and a multilevel modeling of such data could be undertaken. Given the limitations of existing data and the shortcomings of DHS-type data in particular regarding context-dependent migration histories and time-dependent-context-dependent explanatory variables, one cannot investigate transition to adulthood with the aim of testing the context effects without identifying one and only one context at each higher level per Level 1 (individual) unit. The identification of context is essential for clustered data used in multilevel modeling because the main premise of multilevel theories is that a context is well-defined and identifiable. Thus, analyses are based on all respondents irrespective of migration/residence history for relevant descriptive analyses, and migrant respondents are excluded from multilevel analyses because the CDHS-98, like other DHS surveys, only collect information on childhood place of residence, current residence, and lifetime place of residence. Clearly, we have adopted a more rigorous and conservative strategy to preserve our study from committing Type I errors or other inferential errors often encountered in aggregate and single-level studies and to detect “pure” contextual effects (e.g., associated with urban versus rural residence for community context), net of fixed and random influences of other measured and unmeasured factors. The data are therefore restricted to respondents who never migrated, for whom the childhood place of residence and current place of residence are the same, and to cases with no missing data on the dependent variables. In the CDHS-98, 47.2 percent and 63.8 percent of young males ages 15 to 19 years and 20 to 24 years ever migrated, respectively; 58.6 percent and 69.5 percent of young females ages 15 to 19 years and 20 to 24 years ever migrated—with the vast majority of girls migrating for marriage as shown in Kuate-Defo (2000), respectively. After all necessary exclusions, the samples used in various analyses are indicated in the respective tables of results (see Tables 10-2 to 10-6). Table 10-1 specifying selected explanatory and response variables used in this study, is self-explanatory. Response Variables The Three Dichotomous Response Variables In order to test the panel’s conceptual framework, we identified measures of successful or unsuccessful transitions to adulthood that are avail-

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The Changing Transitions to Adulthood in Developing Countries: Selected Studies TABLE 10-1 Definitions and Specifications of Variables Utilized in Analyses: CDHS-98 Names Dichotomous response variables Head of the household before age 25 (both male and female samples) Had sexually transmitted diseases during the last 12 months and before age 25 (both male and female samples) Had worked during the last 12 months and before age 25 (both male and female samples) Polychotomous response variable Cause-specific school attrition before age 25 due to pregnancy and work The woman is still employed and married The woman is still married and school failure (females only) Explanatory variables measured at the individual level or household level Age cohort (in years) Times to school attrition (duration in years) Gender Religion Ethnic affiliation Household wealth index Family structure Explanatory variables measured at the community level Community development index Place of residence Explanatory variables measured at the province level Main regions SOURCE: Cameroon Demographic and Health Survey (1998).

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The Changing Transitions to Adulthood in Developing Countries: Selected Studies Specifications Dichotomous variable coded 1 if a respondent headed a household at the survey date and by the 25th birthday, 0 otherwise. Dichotomous variable coded 1 if a respondent age 24 or younger had a sexually transmitted infection during the last 12 months, 0 otherwise. Dichotomous variable coded 1 if a respondent age 24 or younger had reported being employed during the last 12 months, 0 otherwise. These causes of school dropout by the 25th birthday of women are modeled within a competing risks framework. A series of multistate life tables are constructed, followed by multilevel models for competing events. The dependent variable is a categorical measure of the six states (types of exits) of the female respondent: 1 if left school due to work, 2 if left school due to marriage, 3 if left school due to unwed pregnancy, 4 if left school due to failure, 5 if left school for all other reasons, and 6 if still enrolled in school. The detailed causes are listed in Table 10-2. Coded 1 if 15-19, 0 if 20-24. A series of 11 dummies for failure time <15, 15 to 24. Coded 1 if male, 0 otherwise. Coded 1 if Catholic, 2 if Protestant, 3 if Muslim or others. Coded 1 if Pahouin-Beti, 2 if Douala-Bassa, 3 if Fulfulde-Fulani, and 4 if other ethnic groups. Constructed using principal component analysis (PCA) on a set of over 15 wealth items, and aggregating the deciles into three groups coded 1 for the lowest 40%, 2 for the middle 40%, and 3 for the highest 20%. Coded 1 if respondent lives with biological or own parents, 0 otherwise. Constructed employing PCA using more than 10 items capturing various aspects of development per community and deciles aggregated into three groups, and coded 1 for the lowest 40%, 2 for the middle 40%, and 3 for the highest 20%. Coded 1 if urban, 0 otherwise. Coded 1 if forest, 2 if highlands, and 3 if Sudano-Sahelian.

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The Changing Transitions to Adulthood in Developing Countries: Selected Studies CONCLUSION: KEY ISSUES Implications for Analysis Several major findings emerge from this study and lend support to the main assumptions underlying the theoretical framework developed by the NRC’s Panel on Transitions to Adulthood in Developing Countries. More specifically, as that framework had conjectured, we found that there are similarities and differences that young people face in different contexts and regions of Cameroon, as well as differences between men and women and among different socioeconomic and cultural groups of young people as characterized by household or community socioeconomic status, religion and ethnicity, as they make their transition to adulthood. First, more than half of young people who leave school in Cameroon do so because they cannot pay school fees; only about 1 in 10 women under age 25 stop school because of marriage or childbearing; and poor health is reported as the main reason for leaving school by 5 percent of young females. Second, young people who live with their parents or in urban areas are most likely to pursue their studies and least likely to leave school. Third, this study provides compelling evidence that a meaningful study of biodemographic processes and transitions to adult roles cannot ignore ethnic and regional influences, which also covary with gender. Young people from the Douala-Bassa and Pahouin-Beti ethnic groups have substantially lower odds of being head of the household than their Bamileke counterparts; the likelihood of reporting being employed is substantially lower among Douala-Bassa and Pahouin-Beti youths than their Bamileke counterparts; young people from the Douala-Bassa ethnic groups and from the Sudano-Sahelian or the highland regions are most unlikely to report having had an STI; young females from the Sudano-Sahelian regions are most likely to stop school due to marriage and least likely to report pregnancy as a reason for leaving school; and young girls from the Pahouin-Beti ethnic groups are three times as likely to stop school due to pregnancy as Bamileke girls. The former are at significantly lower risks of stopping school to transition to work or marriage than the latter. As hypothesized, ethnic influences operate differently by gender. Interaction parameters of ethnicity and place/region of residence with gender demonstrate that their effects are also gender dependent: Young men of Pahouin-Beti descent or from the Sudano-Sahelian regions are 2.5 times and 3.8 times as likely to be head of household as their counterparts of Bamileke descent or from the forest regions, while young females with a Douala-Bassa background are more than four times as likely to live as a household dependent as their counterparts from Bamileke ethnic groups. Young males are more than four times as likely to report having contracted a reproductive health STI as young females, and young males living in

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The Changing Transitions to Adulthood in Developing Countries: Selected Studies worse-off communities are five times as likely to report an STI as their peers from the richest communities. Our finding that the prevalence of STIs is significantly higher among boys than girls is also consistent with a recent multicountry study which found that more boys than girls have experienced STI symptoms in Argentina, Botswana, Peru, the Philippines, the Republic of Korea, and Thailand (Brown et al., 2001). Studies of effects of parental structure on life course events during adolescence in developing countries remain scarce. Yet the proportion of children living in structures other than parental ones has increased in recent decades due to increased educational opportunities far away from the parental home and, to some extent, emergence of separation/divorce, greater prevalence of nonmarital childbearing, changing family relations, and economic crisis. Because of these changes, living conditions for some young people have changed substantially from the traditional parents-centered childrearing regime to a diversity of living arrangements in childhood, pre-adolescence, and adolescence. As a result, most young people in alternative situations live with one biological parent, a biological parent and a stepparent, grandparents, relatives, or unrelated guardians, or live independently. Social scientists and biomedical researchers have been concerned about the implications of the increase in the proportion of children living in these alternative situations. One focus of research has been the long-range effects of such experiences on the health, education, behavior, and well-being of children. Our study finds that young people who are not living with their own parents are twice as likely to drop out of school as children who live with their biological parents (p < 0.01), are more than eight times as likely to marry earlier than their counterparts living in the parental home (p < 0.01), and to some extent have higher risks of stopping school due to a pregnancy than young people living with their parents. Our findings are consistent with those reported in various U.S. studies, which have shown that young people in alternative living arrangements without their own parents attain lower levels of education, have less chance of graduating from high school, marry earlier, become parents earlier, have sexual intercourse earlier, are more likely to have premarital births, and are more likely to divorce (for a review, see National Research Council and Institute of Medicine, 1999). Scarr and Weinberg (1994) also show that educational and occupational skills achievements of adolescents and young adults are greatly influenced by the social and familial environments. One of the distinctive, prevailing features of the African family is that individuals are encouraged to stay and live with parents and/or family members until they experience specific events marking a successful transition to adulthood, notably graduating from school and securing employment. Our findings here lend support to this African tradition, which is of great importance as long as it fosters successful transitions to adult roles among young people.

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The Changing Transitions to Adulthood in Developing Countries: Selected Studies One of the most intriguing findings of this study is that more than half the girls who left school before age 25 reported they could not pay their school fees, and the situation tends to be worsening over time. Younger people tend to be more affected by the financial difficulties of their families at keeping them in school than their older counterparts, with almost 53 percent of females ages 15 to 19 years stopping school because their school fees was not paid, compared with only 49 percent of females ages 20 to 24 years and 46 percent for these ages 25 to 49 years; adolescent boys and girls ages 15-19 years are also 2.6 times and 2.1 times as likely to be employed in the recent past as their older counterparts ages 20-24 years. These findings may suggest an emerging phenomenon whereby parents may be attempting to rationalize their investment by selecting their children to remain in school given their scare financial resources on the basis of what they have already spent on their education and the likelihood of graduation for seeking employment so as to support the extended family, while keeping younger progeny out of school so that they can participate in the family’s efforts to generate income through petit commerce and the like which often requires that young people walk along the roads and station at police checkpoints to sell handy cooked meals, fruits, and other consumable farm products in order to raise the family income needed to keep the most advanced and promising older child in schools. In addition, it is worth noting that in the total samples of young women and men in the CDHS-98, fully over 14 percent of females ages 15-19 years and 18 percent of females ages 20-24 years have never been to school, and over 5 percent of males ages 15-19 years and 4 percent of young males ages 20-24 years have no schooling. Obviously, if the main reason for stopping school is financial hardship among young respondents who ever attend school, it is most likely that those with no schooling are even more inclined because their parents could not afford to send them to school. In the 1980s and early 1990s, wages, the main source of income for most civil servants and their relatives, were slashed by nearly 70 percent by the government of Cameroon, part of a series of stern measures designed to deal with the rampant economic crisis. A series of social measures also were implemented, including charging fees to attend all public schools, some of which are now more expensive to attend than private schools. The combined effects of these measures and the enduring economic crisis in Cameroon, as in many African countries, may explain this situation, which has major implications for the development of Cameroon. Jensen and Nielsen (1997) also found that in Zimbabwe, inability to afford school fees ranked second (18 percent of cases) as the main reason for leaving school. Put together, these findings clearly call for an urgent need to invest in young people’s future in Africa through education, particularly for girls. The international community should join efforts together at all levels focusing on the overall goal of the UN Millennium

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The Changing Transitions to Adulthood in Developing Countries: Selected Studies Development Goals of overcoming poverty, especially in Africa where poverty lurks. Indeed, the UN Millennium Declaration stressed the special needs of Africa requiring that actions take place at the global and country levels. Our study also shows that while the link between the socioeconomic conditions of families and school attendance is consistent with the standard human capital framework (Becker, 1964), other influential variables in the context of Cameroon are also important, such as ethnic groups, type of place of residence, region of the country, family structure, and child age. These findings imply that ethnic capital and social capital are important predictors of school attendance and transitions to adulthood in African settings, especially given the diversity of Cameroon, which has more than 200 ethnic groups. In addition, further research is needed to deepen our understanding of these other forms of capital on young people’s transitions to adulthood because some evidence exists on these influential factors in other areas of the life course (e.g., Borjas, 1992). This study’s finding that more than half of girls stop schooling because they cannot pay school fees while barely 1 in 10 left school due to marriage is generalized across generations and place of residence. Furthermore, none of our multilevel analyses demonstrates statistically significant differences in school leaving due to marriage by place of residence. Put together, these findings call into question the widespread belief that in most African countries, girls stop going to school because of early marriage. Our proposition is that they often find that the only life option for securing their future is marriage, which has childbearing as one of its benefits. There is an urgent need to pay attention to these economics of schooling, marriage, and childbearing in order to clarify whether delayed marriage and/or childbearing has usually been concomitant with or followed by increased educational opportunities for girls, independent of other influential factors. Clearly, our findings indicate that the linkages between female schooling, marriage, and childbearing in Africa should be revisited, as pursued in Kuate-Defo (2005c). Sexual initiation and relations and reproductive events free of infection are a genuine preoccupation in any reproductive health promotion program. Intervention programs targeted at adolescents and young people must assess the prevalence and biosocial determinants of STIs frequently encountered in the sites where the intervention is to be delivered. Yet the attention given to the health problems of adolescents and young people in designing and implementing national and/or large-scale intervention programs is still meager, in part because so little is known about the magnitude and patterns of health problems during these periods of life. The few studies that exist in a variety of settings in the developing world have documented high rates of morbidity among young people in both rural and urban populations (Bang et al., 1989; Brown et al., 2001; Fleming and Wasserheit, 1999; Holmes, 1994; Narayan et al., 2001).

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The Changing Transitions to Adulthood in Developing Countries: Selected Studies In an effort to ensure healthy transitions of young people to adulthood in developing countries, it is crucial to have a deeper understanding of the socioepidemiological risk and protective factors of STIs among young people. Information concerning STI rates, including those for HIV, in the early years of sexual activity is of paramount importance in developing effective interventions to improve adolescent reproductive health and contribute to safe and healthy transitions to young adulthood. STIs, including HIV/AIDS, present a major public health problem in developing countries, and their drastic impact on morbidity and mortality across the lifespan has been widely recognized. Our study has documented important age, gender, ethnic, socioeconomic, and contextual differences in the prevalence of STI symptoms among young people in Cameroon. The data at hand indicate that the prevalence of STIs is four times higher among boys than girls. Infection rates are highest among young people from rural areas, worse-off communities, and forest regions, where the prevalence of sterility remains notoriously high in the country (Kuate-Defo, 1997). However, the evidence regarding the accuracy of self-reported symptoms versus medical diagnoses is inconclusive in developing countries. Some studies have shown that women’s self-reported symptoms understate the prevalent conditions compared with the medical diagnoses (Liu et al., 2003). This discrepancy has been ascribed to factors such as the fact that reproductive tract infections are sometimes asymptomatic and even when symptomatic, women’s perceptions of the symptoms may not prompt her to seek treatment. Because of these cautionary notes and the possibility of misclassification, this study has focused analyses on all symptoms together as signs of STIs. Thus, although these estimates may understate or distort the scope and/or patterns of the problem of STIs among young people in Cameroon, the substantive finding that young males are significantly more likely to be infected with an STI than young girls is consistent with a recent multinational study conducted in developing countries by the World Health Organization (Brown, 2001). These findings provide a good yardstick that future research can use to deepen our understanding and improve the measurement of young people’s perceptions of reproductive health problems, including STIs. Our field experience shows that information about these issues is generally poor among young people because their limited knowledge is often based on a mixture of facts, fictions, myths, and rumors. Implications for Methodology This study has situated the estimated influences on transitions to adulthood within a multilevel framework as the most appropriate and logical approach to formally test the theoretical framework of the NRC’s Panel on

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The Changing Transitions to Adulthood in Developing Countries: Selected Studies Transitions to Adulthood in Developing Countries. It has allowed a rigorous assessment of the robustness of estimated fixed effects and random effects at the individual, community, and province levels and helped to isolate the net effects of measured factors which are of primary interest in most applications and for engaging a decision-making dialogue with policy makers and planners concerned with young people’s life experiences including the events charting their transitions to adulthood. We paid close attention to the assumptions required by multilevel models and theories and investigated the tenability of those assumptions in light of the available data and our best judgments based on accumulated data analytic experiences on a variety of topics for which data have clustered structures, so that specification assumptions must apply at each level of observation. While our general multilevel model formulated above allowed for the effects of covariates to be fixed or random at each level of hierarchy and for cross-level interactions, after trial runs and given the nature of the data, we were able to retrieve stable estimates for models that could only fit level-specific fixed and random effects of measured and unmeasured factors as shown in Tables 10-5 and 10-6. We found that these random effects are statistically significant in some models: significantly positive random community (for females) and regional (for both sexes) influences associated with females heading a household account for 20 percent and 14 percent, respectively, of the total nested variation, even after controlling for the influences of nested explanatory factors of other levels; community random influences on school dropout due to pregnancy account for 11 percent of the total variation across levels over and above the fixed and random effects of other influential factors. In particular, the between-individual variance is statistically significant in all models (p < 0.01), the between-community variance is statistically significant for girls only (p < 0.05) and for the transition out of school due to childbearing (p < 0.10), and the between-province variance is statistically significant for boys only (p < 0.10) in the model predicting being head of household. Notwithstanding their importance, the effects of several exposure variables considered in this study remain robust, including individual-level characteristics such as age, sex, ethnic affiliation, and contextual factors such as level of development of the community and region of residence. The multilevel approach employed here clearly shows significant correlations among individuals interacting and behaving likewise within their nested contexts of life and are robust to controls for all measured variables, and substantiates the shortcomings of aggregate analysis and single-level analysis that inherently ignore such nested correlations and often commit ecological fallacy for the former or Type I errors for the latter, among other inferential problems. Overall, the presence of fixed and random effects of community-level and province-level factors identified does not change substantially the val-

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The Changing Transitions to Adulthood in Developing Countries: Selected Studies ues for the individual-level parameters with the battery of multilevel nonlinear models applied here to explicitly handle the hierarchical or clustered structure of our data, while single-level modeling, which ignores the three levels of hierarchy (e.g., in the individual, household, community questionnaires of the DHS-type surveys), would have led us to commit the Type I errors by falsely rejecting the null hypothesis for some variables (results for single-level models not shown) because the standard errors of the associated parameters were underestimated. The estimated parameters suggest, for instance, that there may be more variation across communities and provinces in the likelihood of young males versus young females being head of household than standard single-level analyses would have implied. This study also demonstrates the significance of influential unmeasured variables affecting the various transitions of young people during their life course, independently of the significance of individual/household-level and contextual community-level and province-level covariates. A number of these unobserved influences may be unmeasurable in conventional qualitative or quantitative methods of inquiry, and often require triangulation research methodologies that combine qualitative and quantitative approaches to study biosocial events generally defining transitions during the life course. Most past surveys including the DHS-type surveys have not been designed with the goal of handling multilevel theories and sophisticated statistical models and therefore are not fully equipped to confront all methodological problems associated with causal inference. This study has employed a multilevel framework that locates the household, community, and provincial contexts that are invariant during the exposure length to the likelihood of making a transition to adulthood for a given individual given its characteristics, thereby illuminating some fundamental obstacles in the identification, specification, explanation, and insightfulness of multilevel contextual effect studies. A full implementation of the models formulated above, which will allow us to deal with all components of the theoretical framework developed by the NRC’s Panel on Transitions to Adulthood in Developing Countries, will depend on the extent to which a multilevel survey design is used in collecting clustered data at the individual-level, including measures nested within individuals and higher levels of hierarchy (e.g., household, community, region, country). Our findings of significant variances at the individual, community, and province levels suggest that future efforts for data collection and investigation on influences on transitions to adulthood should go beyond existing research approaches in order to deepen our understanding of various nuances and manifestations of transitions to adulthood in developing countries. Greater effort needs to be made to design surveys that actually measure some of the factors that we suggest might be important but at present are only inferred. For example, important changes have occurred in the last 15

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The Changing Transitions to Adulthood in Developing Countries: Selected Studies years in the political and economic landscapes of many African countries. Introduction of political capital and social capital into such analyses may prove insightful in understanding some of these unobserved variations. Although a number of theoretical perspectives are well advanced by now and the basic and advanced statistical methods for multilevel modeling in the literature are well known by methodologists, an area where much progress is needed concerns the design of multilevel surveys and data needs for empirical specification of models and testing of underlying theories and assumptions. Most past surveys have not been designed with the explicit aim of supporting multilevel modeling, and existing textbooks on multilevel modeling provide only scanty guidance as to the design of multilevel surveys, for instance, of children, families, and communities that are at the heart of most population investigations and policies. This makes it difficult to address the most important yet unresolved research issue in this area, namely the development of an understanding of the causal effects of postulated risk/protective factors of outcomes under investigation so that more effective intervention programs targeted at young people can be designed, implemented and evaluated. Our hope is for much progress in the near future. ACKNOWLEDGMENTS This work was supported by the Rockefeller Foundation’s Intervention Research Grant RF 97045 #90 to the author; supplemental support was provided by the National Academies (Washington, DC) and the PRONUSTIC Research Laboratory at the Université de Montréal (Canada). We thank Barney Cohen, Jere Behrman, Nelly Stromquist, Cynthia Lloyd, and two anonymous referees for their discussions, suggestions, and comments. REFERENCES Agresti, A. (1990). Categorical data analysis. New York: Wiley. Arnold, B.C., and Brockett, P.L. (1983). Identifiability for dependent multiple decrement/competing risks model. Scandinavian Actuarial Journal, 31, 117-127. Baltagi, B.H. (1995). Econometric analysis of panel data. Chichester, England: Wiley. Bang, R.A., Bang, A.T., Baitule, M., Chaudhary, Y., Sarmukaddam, S., and Tale, O. (1989). High prevalence of gynecological diseases in rural Indian women. Lancet, 8(29), 85-88. Becker, G. (1964). Human capital: A theoretical and empirical analysis, with special reference to education. New York: National Bureau of Economic Research. Binder, M., and Woodruff, C. (2002). Inequality and intergenerational mobility in schooling: The case of Mexico. Economic Development and Cultural Change, 50(2), 249-267.

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