The paper uses data from the Millennium Cohort Study (MCS), a UK longitudinal cohort study of around 19,000 children who were born in the UK between September 2000 and January 2002. The sample was selected from a random sample of electoral wards with a stratified sampling strategy to ensure a sufficient number of observations from all four UK countries and from disadvantaged and ethnically diverse areas (Hansen 2012). For this reason, the analyses used sample weights to adjust for the unequal probability of being sampled and the stratified and clustered sample design. The first sweep of data was collected when the cohort members were around nine months old, and subsequent sweeps of data were collected when the children were around three, five, seven and 11 years old. During home visits, interviewers collected information about a range of factors, including demographic characteristics (the relationship status was recorded at each sweep of data collection), socio-economic circumstances, different measures of child well-being and the parent’s behaviours.

Sample

Our sample is made up of two groups: children whose mother was neither married nor cohabiting with a partner at the time of birth and all children who were born into a household where their biological parents lived together and remained together for the first seven years of life of the child. The first group is our population of interest; the second group is considered to provide context.

To identify children of lone mothers, we consider information from the first sweep of the MCS. In the first sweep of the MCS, the main respondent was asked: “What was your relationship with (the child’s name)’s father at the time (he/she) was born?”. Mothers could answer one of the following: married and living together, cohabiting/living as married, separated, divorced, closely involved, just friends, not in any relationship. We select the group of mothers who answered one of the following: closely involved, just friends, not in any relationship. We call this group “lone mothers at birth”. It is worth noting that these women might have been romantically involved with the father of the child or with someone else when the child was born; however, they were neither married nor cohabiting with a partner. Thus, the definition of lone mother is based on residency with a father figure. We then follow the children of these mothers until sweep 4, that is, when they were around seven years old. Partnership status at subsequent waves is constructed through information provided in the household grid and on a survey question about the relationship between the main and (if present) partner respondent. We retain only those observations for which we have a valid interview at every sweep of data collection.

The total number of children born to a lone mother in the MCS is 3285. Using population weights, we estimate that in the UK population in 2000, about 14.7% of children were born to lone mothers, according to our definition, which is close to the figure from official statistics. We lose 1718 children because of attrition and are left with 1567 children. From this figure, we had to exclude 278 cases because of rare or unclassifiable trajectories, leading to a sample size of 1289. Lastly, we had to drop 120 observations because of missing outcomes. The final number of children in this group is 1169. This figure corresponds to 11.4% of all the MCS children.

One striking finding is the high rate of attrition in this subset of the population. More than half of children born to a lone mother who participated in the MCS at sweep 1 had dropped out by sweep 4. A more careful analysis showed that the largest rate of attrition occurs between Sweeps 1 and 2 when 29.3% of the observations are lost. Between Sweeps 2 and 3 and between 3 and 4, the attrition rate remains constant at about 17%. This should be compared with the overall attrition rate for MCS that is 39.1%. This finding confirms that we are dealing with a hard to reach population. To account for the attrition, we used non-response weights although we cannot exclude the possibility that the results may have been subject to bias.

To provide context and as a comparison, we include the group of children whose biological parents were together at the time of birth of the child and did not separate at any point before the collection of Sweep 4. After considering attrition, and availability of outcome variables, we end up with a subsample of 6161 children who fall into this group. Thus, the total analytical sample consists of 7330 children.

Finally, it is important to note that the US literature on family resources across family types makes a clear distinction between cohabitation and marriage. Nonetheless, in this study we group cohabitation and marriage together. We have done this in order to maximise our sample size and because in the UK unmarried cohabitations have been consistently found to be more stable and marriage-like than cohabitations in the USA (Kiernan et al. 2011).

Family Trajectories

From the sample of children born to lone mothers, we construct mothers’ union trajectories in the first seven years of life of the child (Table 1). We base the construction of the trajectories on two criteria. First, the trajectories need to be theoretically relevant. We are interested in examining the mothers’ partnership experiences, and in doing so we distinguish biological fathers from stepfathers and between stable and unstable unions. Second, because the trajectories need to provide an adequate sample size, we have to exclude rare and unclassifiable trajectories.Footnote 4

Table 1 Family trajectories from birth until age 7 for children born to lone mothers. Full size table

The trajectories included in the analysis are the following: children who live with a lone mother for the first seven years of their life, which we refer to as trajectory L; children who are born to lone mothers but then live with their biological father and do not experience the dissolution of the parents’ relationship at any time until they are 7, which we refer to as trajectory L-B (from the pattern Lone-Bio); children who are born to lone mothers and then transition to a stepfamily and later experience the dissolution of the partnership, which we refer to as trajectory L-S (from Lone-Step); at last, children who are born to a lone mother, then live with their biological father and experience the dissolution of the partnership, so that the mother is again single when they are 7 years old; we refer to this group with the acronym L-B-L (from the sequence Lone-Bio-Lone). The largest trajectory is L; 5.2% of all the MCS children live continuously with a lone mother from birth until age 7. Although the main focus of the paper is the comparison of outcomes among children born to a lone mother (L, L-B, L-S, L-B-L), we also compare each of these trajectories with a more traditional household type in which the child lives continuously with both biological parents until age seven hereafter referred to as B (Bio).

Analytical Strategy

The analytical strategy is divided into two sections. The first section aims to investigate the heterogeneity of family backgrounds among children who were born to lone mothers. The goal of the second section is to investigate the association between a range of child outcomes and the four trajectories. Children who were living with a mother who formed a union with a father (trajectories L-B, L-S and L-B-L) are compared to children who were living continuously with a lone mother until age seven (the reference trajectory L). To provide context, in both sections, we also compare each of the trajectories with a more traditional household type in which the child lives continuously with both biological parents until age seven (trajectory B).

The formation or dissolution of a union is related to a number of factors, including maternal and household attributes that potentially are also relevant for child well-being. In the multivariate models, we include a set of background characteristics of the mother that account for some of these attributes. Thus, we are interested in identifying the association between the family trajectories and child outcomes after the confounding effect of background characteristics is taken into account. It is important to note that our results represent descriptions of the associations rather than the causal effects of those transitions; even in this already selected group of children there may be further selection processes associated with the mothers’ characteristics and with the well-being of their children that may make them more likely to experience one type of transition than another. Because our interest lies in accounting for factors that determine selection into different trajectories, we want to control for background variables that are measured as early as possible. Thus, we include variables that are measured at birth (and asked retrospectively at Sweep 1)—whenever possible—or at the first sweep, when the children were nine months old. In section 4.2, we provide detailed descriptions of the variables included and the time at which they are measured. To allow comparison of effect sizes across outcomes, we compute partial correlation coefficients. We computed them in a three-step process. First, we regressed each outcome on all explanatory variables apart from the variable of interest and took residuals. Second, we regressed the variable of interest on all explanatory variables and took the residuals. Third, we regressed the residuals from step 1 on the residuals from step 2. The R squared of this last regression corresponds to the partial correlation coefficient. We apply survey weights to all the regressions.