3 Data and Methods
3.1. Data
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立 政 治 大 學
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N a tio na
l C h engchi U ni ve rs it y
For the breastfeeding-pregnancy overlap, most studies argue for an effect of early cessation of breastfeeding, weaning, as a result of a closely spaced conception (Hobcraft, et al.,1983, Sweemer, 1984; Forste, 1994; DaVanzo, et al., 2008). Despite medical literature assessing the impact in breast milk nutrients and child weight, there’s little direct evidence of these quality effects affecting child mortality through a shorter birth interval (Marquis, et al., 2002; Marquis, et al., 2003).
Research that aims to untangle the relationship between child spacing and child mortality is very broad, expands through disciplines and deals with complex multilateral relationships between variables and mechanisms. Experts fail to agree on the existence of certain effects and channels, as the discussion grows into different realities. In fact, human fertility is subject to many unmeasurable variables –culture, religiousness– and fundamental differences –developed and developing countries, health care systems– than unanimity upon the subject is not expected.
3 Data and Methods
3.1. Data
To study the impact of the interbirth interval on infant mortality among Nicaraguan families and the mechanism by which it affects, data from the Demographic and Health Surveys (DHS) were used. The DHS started in 1984, building on the experience of its predecessors the World Fertility Surveys and the Contraceptive Prevalence Surveys. To date, it has become a widely spread, nationally representative, and comparable household data source, allowing to document demographic dynamics, such as fertility, family planning, maternal and child health in intervals of approximately five years (Fabic, Choi & Bird, 2012).
Nicaragua first enrolled in the DHS program in 1997, after years of battling the economic downfall inherited from the Sandinista government and a decade of civil conflicts, during its third phase primarily financed by the United States Agency for International Development (USAID). Thereafter, the country has continuously teamed up with different international organizations to gather the data until the last DHS developed in 2011-2012 (see Table 1). No more data has been available ever since, possibly due to ambiguous and hostile policies of the Ortega government towards foreign aid agencies – that led to the departure of the United Nations Development Program (UNDP) in 2016–
and the halting of funds due to the 2018 sociopolitical crisis (Martí, 2019).
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Table 1: Nicaraguan DHS (1998-2011) general description
Data Period Primary
donor Source Selection criteria Sample size Households Women
1 United Nations Fund for Population Activities
2 National Institute of Information for Development (Nicaragua, Spanish acronym)
Data on each DHS is cross-sectional; thus, the datasets were pooled to have a more comprehensive sample. The main dependent variable, infant mortality, is defined as a binary variable that depicts the occurrence of under-one-year old death. The DHS only gathers important nutritional and live outcomes variables from alive children under five at the time of the interview but reports the history of age at death for each woman’s offspring. Therefore, in this study, all chosen variables that report on child-specific aspects will be those that cover the full record of offspring and not those later expanded in the dataset. On the contrary, the main independent variable will be defined as the interbirth interval (IBI), i.e. the time measured in months from the childbirth of the preceding child to the birth of the index child. This is mainly because there is no information on each pregnancy’s duration, thus, other time measures such as birth-to-pregnancy (recommended by the WHO (2007)) cannot be obtained; nor there’s data on the outcome of each pregnancy besides live birth, thus, neither the inter-outcome intervals can be found (used by DaVanzo, et al. (2008)).
To be included in the empirical model, the IBI was coded into 4 categories:
firstborn, index children born first (inapplicable for the calculation of IBI); and IBI groups of: less than 18 months, between 18 to 35 months, and more than 36 months. These categories reflect on previous literature findings regarding the deleterious effects of short (less than 18 months) intervals (WHO, 2007).
Additionally, the selection of covariates serves two purposes: (1) control for confounding factors that may also explain infant mortality; and (2) address the objectives of assessing the existence and direction of effects of the causal mechanisms described in Section 2.3.1., such as: maternal depletion and sibling competition for Nicaraguan
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families. Nonetheless, one of the causal mechanisms that it’s not possible to discuss due to the scope of the DHS data is the breastfeeding-pregnancy overlap. As mentioned above, DHS data only follows children that are reported alive, living at the household and younger than 5 years old at the time of the interview. Thus, information on breastfeeding practices, nutrition, immunization and pregnancy durations are not available for the main interest group.
Covariates are split into: a) index child-specific and referenced variable: interbirth intervals, gender of index child, singleton birth (single or multiple), birth order, and death of the preceding child; b) mother specific variables, such as: the highest level of education reached, mother’s age, whether or not the mother has experienced a miscarriage; and c) household variables: a measure of the wealth of the household, number of adults living in the household and distance to health services. Additionally, by-groups specifications on: mortality of previous child, mother’s age, birth order, household wealth and area of residence will be used to explore and discuss the empirical evidence of causal mechanisms and assess which effect prevails over the other possible channels.
These variables can be grouped by the mechanism each address, in this sense, variables such as IBI<18 months and the death of preceding child could reflect on the mother’s depletion; and the sibling competition can be evidenced in variables such as birth order and multiple births. Lastly, to account for the effect of previous miscarriages or interruptions, binary variables for mothers that have had each of these occurrences were created. Although it is not possible to link these events to each child record, it still provides valuable information on the maternal reproductive and health history.
For the most part, the selection of these variables responds to a synthesis of the previous empirical literature and the viability of finding them in the DHS datasets.
Primarily, the models followed are DaVanzo, et al. (2008), Fotso, et al. (2013) and Becher, et al. (2004). All variables are described in detail in Table 2 below.
Table 2: Description of variables used in the empirical model
Variable Reference Levels Description
Index child-level variables
Difference in months from the day of birth of the preceding child to the birth date of the index child
Infant mortality of
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Table 2: Description of variables used in the empirical model
Variable Reference Levels Description
Index child-level variables
Singleton birth Binary; 0= singleton
birth, 1= multiple birth
Whether the birth was singleton or multiple
Birth order Becher, et al.
(2004)
First born, 2nd to 4th, ≥5th Categories that group children by the order in which they were born Mother-level variables the index child measured in years
Miscarriages Proxy to the
Whether the mother has had a pregnancy interruption (DHS 1998-2001) or a miscarriage (DHS 2006-2011)
Household-level variables
Wealth index Proxy to the
one used by with the mother in the household.
Remoteness to health Area of residence Fotso, et al.
(2014)
Binary; 0= urban, 1=
rural
Whether the household is located in an urban or rural area
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國立 政 治 大 學
‧
N a tio na
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3.2. Empirical methods