The Changing Transitions to Adulthood in Developing Countries Selected Studies (2005) / Chapter Skim
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10 Multilevel Modeling of Influences on Transitions to Adulthood in Developing Countries with Special Reference to Cameroon--Barthélémy Kuate-Defo
10 Multilevel Modeling of Influences on Transitions to Adulthood in Developing Countries with Special Reference to Cameroon--Barthélémy Kuate-Defo
Pages 367-423
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From page 367... ...
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)
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From page 368... ...
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.
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From page 369... ...
The constructive aspects of adult roles embedded in experienced states are features of successful transitions,
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From page 370... ...
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.
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From page 371... ...
, 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)
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From page 372... ...
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.
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From page 373... ...
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 welldefined 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 crossclassified data would have to be available.
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From page 374... ...
. 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.
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From page 375... ...
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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From page 376... ...
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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From page 377... ...
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.
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From page 378... ...
For reproductive health problems, two questions were asked about sexually transmitted infections (STI)
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From page 379... ...
. Leaving school to work or to get married is considered a successful transition to adult roles and responsibilities, whereas dropping out of school due to a pregnancy or grade failure is an unsuccessful transition.
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From page 380... ...
Physiological Influences Several physiological factors have been implicated in explanations of behaviors, risks, and events experienced during the life course. During childhood and adolescence, innate or acquired immunity or healthiness, menarche, and coinfection have been the most studied in relation to positive and negative behaviors and life events (Evans, Barer, and Marmor, 1994; Gray, Leridon, and Spira, 1993; National Research Council, 2001)
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From page 381... ...
Such individual-specific unmeasured random influences will be captured in all fitted multilevel models at the individual level. Demographic, Socioeconomic, and Cultural Influences A number of studies have found that transitions to adulthood covary with age, gender, ethnicity and religion, family structure, and social class.
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From page 382... ...
Gender Gender differences in exposure to and experience of various socioeconomic and demographic events across the life course are well established. In general, females are at a disadvantage compared to males in terms of educational attainment and employment opportunities, especially in developing countries (Jejeebhoy, 1995; UNFPA, 2003a)
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From page 383... ...
Family Structure In all societies, family is the most important setting for ensuring successful transitions to adulthood. Although not all adolescents growing up in poor or divorced families are destined to have problems, an extensive literature suggests that adolescents living in families experiencing economic hardship, divorce, or both are at increased risk for a range of health and behavioral problems, including school failure and high-risk behaviors (Binder and Woodruff, 2002; Bledsoe, 1994; Scarr and Weinberg, 1994)
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From page 384... ...
Socioeconomic Indexes at the Household and Community Levels Among the many factors that influence young people's health, behaviors, development, and well-being are household wealth and amenities as well as socioeconomic conditions of the community (Binder and Woodruff, 2002; Bolin et al., 2003; Jensen and Nielsen, 1997)
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From page 385... ...
Lack of access to such services often translates into lack of access to barrier contraceptive methods such as condoms or school-learned skills needed in the labor market. We assess these potential influences of socioeconomic conditions by constructing socioeconomic indices (a household wealth index and a community development index)
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From page 386... ...
. For the earliest part of the life course, life is relatively uncompartmentalized, and under normal circumstances, childhood place of residence is shared with biological parents.
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From page 387... ...
; Yijk the value of a young person i from community j belonging to province k, on individual-level vector of predictors Z1; b1 the vector of fixed and random effects of individual-level predictors Z1; b2 the vector of fixed and random effects of community-level predictors Z2; and b3 the vector of fixed and random effects of province-level predictors Z3. This model also specifies nested sources of variability or nested random influences, denoted hk, Jjk, and eijk for the province level, community level, and individual level, respectively.
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From page 388... ...
Multilevel Competing Risks Model for the Risk of Stopping School One of the features of survival analysis is its ability to take into account censoring of exposure in the specification and estimation of effects of covariates on the response variable. The end of exposure to the risk of stopping school can occur for different censoring reasons.
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From page 389... ...
is the instantaneous rate of school leaving due to cause r at time t given, and in the presence of the other causes of school dropout. Because leaving school due to cause r must be a unique element of {1,2,...,m}, the overall hazard rate of school leaving is: (3)
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From page 390... ...
Likewise, because the hazard is fully parametric, it is possible to extrapolate beyond the range of observations, although the usual caveats apply. The overall hazard function from equation 4 is the sum of all the causespecific hazard functions.
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From page 391... ...
The relevant reduced-form multilevel competing risks models posit that the transition probability mr(t) -- that stopping school due to cause r occurs to the i-th individual from the j-th community of the k-th province at duration t-is a linear combination of the levelspecific covariates, where the logit of a probability mr is the log-odds, defined as logit(mr)
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From page 392... ...
For the multilevel logistic regression models formulated for each dichotomous response variable, models were fitted separately for males and females as well as a pooled model for both sexes. An important question in this study is whether the effects of explanatory variables, structural contexts and random influences, vary by sex.
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From page 393... ...
capturing the duration structure of school attrition. Like in the case involving multilevel logit models above, the multilevel survival analysis formulated here is designed to test the hypothesis of the theoretical framework of the NRC's Panel that contexts matter even after controlling for other influential measured and unmeasured factors of transitions to adulthood.
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From page 394... ...
3.29 + + Cameroon; The advantage of partitioning nested random contextual influences using this definition is that it can be directly extended to define the residual intraclass correlation coefficient that controls for the effects of explanatory variables (e.g., covariates at the individual/household or community levels, environment at the province level) , which has special appeal in this study as we investigate the net multilevel effects of both fixed and random influences on transitions to adulthood (see Tables 10-5 and 10-6, Panel C)
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From page 395... ...
The age pattern of school attrition indicates that the vast majority of young people leave school between 7 and 18 years of age. The inability to pay school fees is the main cause of leaving school among women in Cameroon.
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From page 396... ...
Hence, although "could not pay school fees" is not a specific category of the polychotomous response variable in this study, the findings reported here highlight the urgency with which investment in youth in Africa must start with investment in their education to complete at least the elementary school. This investment should include government subsidies to public and private schools in order to meet the second goal of the United Nations Millennium Development Goals (MDG)
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From page 397... ...
There is also a consistent cohort-dependent pattern in the timing of leaving school due to pregnancy and marriage by age 25. Nearly 13 percent of women ages 25 to 49 dropped out of school due to a pregnancy or marriage; 12.3 percent of women ages 20 to 24 who left school did so because of a pregnancy, and only 7.1 percent because of marriage.
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From page 398... ...
. Only 2 percent of women ages 15 to 49 left school because they had graduated, an indication of dramatic unmet needs in school attendance and grade completion for women that is generalized in Cameroon and most likely in other African countries.
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From page 399... ...
15-19 61.1 58.2 20-24 38.9 41.8 Religion Catholic 36.7 36.6 Protestant 33.3 25.7 Muslim 22.6 25.4 Others 7.4 12.3 Ethnic affiliation Bamileke related 39.2 31.5 Pahouin-Beti related 15.9 18.6 Fulfulde-Fulani 33.9 41.1 Douala-Bassa 10.9 8.8 Respondent's education Some 76.8 88.4 None 23.2 11.6 Household wealth index Poorest 40% 33.7 43.3 Middle 40% 50.8 43.0 Richest 20% 15.5 13.7 Family structure Live with biological parents 50.3 56.6 Live alone with other people 49.7 43.4 Community development index Poorest 40% 29.2 41.0 Middle 40% 35.3 29.3 Richest 20% 35.4 29.7 Place of residence Rural 56.2 65.2 Urban 43.8 34.8 Main regions Forest 41.9 40.5 Highlands 25.2 19.4 Sudano-Sahelian 32.9 40.1 Events with undefined transitions to adult roles Times to school attrition 48.6 - continued
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From page 400... ...
15-24 (N = 849) Event marking successful transitions to adult roles Worked during the last 12 months 54.1 59.4 Head of household 6.4 18.6 Times to school attrition for 3.2 - work and still working Times to school attrition for 3.0 - marriage and still married Event marking unsuccessful transitions to adult roles Had an STI during the last 12 months 1.4 5.7 Times to school attrition due to 4.0 - unwed pregnancy Times to school attrition due to failure 5.5 - SOURCE: Cameroon Demographic and Health Survey (1998)
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From page 401... ...
Girls who live with their biological parents have lower probabilities of stopping school earlier than their counterparts living with other people. There are also statistically significant differences in the likelihood of school attrition according to the socioeconomic conditions of young people's families and the level of development of their communities.
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From page 402... ...
402 for Failure 0.0001 0.2132 0.0118 0.0001 0.0834 < < < < < Attrition Grade p 1.00 2.81 p 1.00 1.43 1.20 1.15 p 1.00 0.76 0.88 0.63 p 1.00 0.80 0.39 p 0.48 1.00 Roles School Adult to 0.0002 0.7261 0.0045 0.0002 0.0226 < < < < < Unwed Pregnancy p 1.00 2.63 p 1.00 0.73 0.96 1.03 p 1.00 2.28 0.35 1.48 p 1.00 1.25 0.72 p 0.70 1.00 Transition Cause-Specific CDHS-98 with of and Data, Married 0.0001 0.0001 0.0001 0.0019 0.0001 Attrition < < < < < Marriage Still p 1.00 3.09 p 1.00 2.05 0.74 3.80 p 1.00 0.35 3.27 0.48 p 1.00 0.70 0.58 p 0.06 1.00 School Probabilities Weighted and Tables Working 0.0178 0.5439 0.0001 0.0005 0.0751 < < < < < Cause-Specific Work Still p 1.00 2.30 p 1.00 1.18 1.28 1.02 p 1.00 0.59 2.28 0.67 p 1.00 0.67 0.47 p 0.77 1.00 Life Variables: Decrement 0.0001 0.0001 0.0001 0.0001 0.0001 Explanatory < < < < < School Attrition p 1.00 1.78 p 1.00 1.07 1.23 1.06 p 1.00 0.91 1.12 0.83 p 1.00 0.90 0.62 p 0.67 1.00 Multiple Selected by from variables variables people Risks Females parents other Relative Young explanatory years) related explanatory with (in related biological or 40% 40% 20% 10-4 affiliation structure with alone cohort 15-19 20-24 Catholic Protestant Muslim Others Bamileke Pahouin-Beti Fulfulde-Fulani Douala-Bassa Poorest Middle Richest Live Live TABLE Cameroonian Individual-level Age Religion Ethnic Household-level HWI Family
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From page 404... ...
Finally, the place and region of residence have statistically significant impacts on school attrition. As expected, girls who live in rural areas have the highest probabilities of leaving school early during their life course; they are 1.4 times as likely to stop school earlier than their counterparts from urban areas.
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From page 405... ...
Predictors of the Likelihood of Being Head of the Household, Employed, and Having an STI Table 10-5 shows the estimated coefficients and standard errors (in parentheses) of the most parsimonious three-level logistic regression models for the dichotomous response variables considered in this study, namely whether the young person was head of the household at the time of the interview, was employed, or was infected with an STI during the 12 months preceding the survey date.
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From page 406... ...
(0.316) Panel C: Partitioning the nested contextual random influences Proportion of variance 0.196 0.001 0.039 among communities within provinces (r2)
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From page 407... ...
MULTILEVEL MODELING OF INFLUENCES ON TRANSITIONS 407 Being Employed Being Infected with an STI Female Male Both Sexes Female Male Both Sexes 0.400 1.155b 0.474 4.808a 2.587b 3.202a (0.387)
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From page 408... ...
and regional (for both sexes) influences are positively associated with females heading a household, controlling for the effects of nested explanatory factors and random influences at other levels, and account for 20 percent and 14 percent of the total variation across levels over and above significant ethnic differences, respectively.
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From page 409... ...
In essence, cohort membership, religious and ethnic affiliations, familial living arrangements, contextual community and regional factors, and community random influences (for pregnancy) , are the main predictors of young people's hazards of leaving school as they transition to adult roles and responsibilities through employment, marriage, or childbearing.
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From page 410... ...
+0.377 (0.485) 0.082 Risks Women a a a a Competing Young School Attrition +3.564 (0.461)
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From page 412... ...
. Significant contextual community and regional influences that vary by reason for leaving school are noticeable, so are community random influences on school dropout due to pregnancy, which account for 11 percent of the total variation across levels over and above significant influences of other covariates.
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From page 413... ...
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 DoualaBassa 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 DoualaBassa 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.
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From page 414... ...
, 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.
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From page 415... ...
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.
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From page 416... ...
. 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.
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From page 417... ...
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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From page 418... ...
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)
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From page 419... ...
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)
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From page 420... ...
. Identifiability for dependent multiple decrement/ competing risks model.
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From page 421... ...
. From epidemiological synergy to public health policy and practice: The contribution of other sexually transmitted diseases to sexual transmission of HIV infection.
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From page 422... ...
. The identifiability of the competing risks model.
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From page 423... ...
. Sexually transmitted infections: Policies and principles for prevention and care.
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