Vulnerability to Sex Trafficking: Adult Women’s Experiences While They Were Adolescents

Abstract

The concept of vulnerability to sex trafficking has been the subject of intense academic debate. It is well documented in the literature that child sex trafficking is facilitated by the abuse of a position of vulnerability, though limited research has focused on children’s order of birth as an element of vulnerability to sex trafficking. The objective of this article, based on a sample of 112 Central American women smuggled to the United States for the sex trade before they had attained the age of eighteen years, is to examine whether the order of birth constitutes an element of vulnerability to sex trafficking. Trafficked minors had vulnerabilities linked to structural-level and individual-level factors. We conclude that sisters occupying the first place in the order of birth are the most susceptible to being recruited by an international network that smuggles women for prostitution. On the contrary, the youngest and middle sisters are less at risk due to the protection and guidance of the other sisters.

1. Introduction

The concept of vulnerability was included in the UN Trafficking Protocol to protect disadvantaged populations who were unable to consent to certain forms of migration. Although, as Lima de Pérez [1] has pointed out, a misuse of the concept of vulnerability may mean the classification of certain cases as sex trafficking instead of human smuggling or migrant sex work. Vulnerability to sex trafficking is the set of circumstances that make it easier for a person to become a victim of sex trafficking. Therefore, vulnerability is viewed as a greater susceptibility to being trafficked.

According to ‘vulnerability theory’, vulnerability is a constant and universal aspect of the human condition. All human beings are ontologically vulnerable; however, ‘situational vulnerability’ is greater for some people, for social and economic reasons, than for others [2]. The risk of specific harms that a person is exposed to is determined by the features of a person’s situation.

The situations in which a person would experience heightened risks of harm have been linked to (1) structural factors, such as poverty, inequality, lack of economic opportunities, gender inequality, illiteracy, and lack of formal education, among others; and (2) individual factors, such as pregnancy during adolescence, family dysfunctions, among others [3,4,5].

On the one hand, in relation to circumstances that appear to be linked to structural factors, sex trafficking has been described as one of the consequences of neoliberal economic policies, global capitalism, and the process of economic globalization characterized by defunding the welfare state [3], deepening rural poverty, increasing economic exploitation of the poor, and the net transfer of wealth from poor to rich economies [6] (p. 27). Numerous studies conclude that material inequalities drive people to migrate through risky means that expose them to sex trafficking. The reasoning goes as follows: poverty plays in favor of sex trafficking networks, which exploit the economic vulnerabilities of the poorest to lure them with false promises of a better life and greater economic opportunities [7,8,9,10].

The feminization of poverty and gender violence and inequality have been associated with the sale of women and children for sex trafficking [7,11,12]. Likewise, the lack of formal education has been considered one of the elements that places victims at a higher risk of being trafficked due to their greater economic needs and fewer employment opportunities [13,14,15]. In this sense, formal education has been considered one of the main factors that allow victims to increase their economic opportunities and escape the risk of sexual exploitation [16,17,18].

On the other hand, in relation to circumstances that appear linked to individual factors, pregnancy during adolescence has been associated with scenarios of family rejection, residential instability, school failure, and financial insecurity [19] (p. 274). In a qualitative study conducted in Tijuana and Ciudad Juárez on the factors leading to underage entry into prostitution, the authors found that in half of the cases studied, teens entered the sex trade because when they became pregnant, they lost any social support. They were thrown out of their homes because of their pregnancy [20] (p. 7).

Many studies conclude that dysfunctional family environments characterized by drug addiction, gender-based violence, physical or sexual abuse, and neglectful behaviors favor sex trafficking through two mechanisms: (1) the exploitation of minors by a family member [4] and (2) the abandonment of the home by the minor to escape family problems [5,21,22]. In relation to the first mechanism, the family itself is the one who exploits and obtains an economic benefit from sex trafficking. Some studies highlight that minors exploited by a family member are younger than those exploited by pimps. In rural environments, these cases go more unnoticed and are more difficult to detect [4,23].

Other studies point out that when a family member is the perpetrator, sexual exploitation appears related to economic needs derived from the former’s addiction [24,25]. In relation to the second mechanism, family circumstances give rise to vulnerabilities that facilitate sex trafficking. Street youth are particularly vulnerable to sex trafficking [5,26,27]. This is because the helplessness caused by homelessness makes minors vulnerable to the affection and security provided by traffickers who profit financially from sexual exploitation [22,24].

The association between runaways, survival sex, and exploitation of the prostitution of others has been documented in numerous investigations, which conclude that runaway minors are vulnerable to sexual exploitation as a bargaining chip for money, food, and shelter [9,22,24]. In these cases, the victims do not recognize themselves as such because the treatment the minors receive from perpetrators is no worse than that received at home [28,29]. This makes the trafficker not be perceived as a victimizer but as a protector of the minor [22,24,26]. On the contrary, mistrust in police officers, justice professionals, and human service providers derives from scenarios of re-traumatization and abuse of power [28] (p. 19).

This paper explores the hypothesis that situations linked to structural and individual factors in which a minor would experience a greater susceptibility to being trafficked are amplified by the birth order among female siblings. While structural and individual factors leading minor victims into sexual exploitation have been extensively analyzed, the relevance of birth order has been neglected in most studies on the vulnerability to minor sex trafficking.

Only a few qualitative studies carried out in Mexico and India have examined birth order as a vulnerability to child sex trafficking. Some studies conducted in Mexico have pointed out that birth order constitutes a feature of a person’s situation that heightens its vulnerability to sex trafficking [30,31]. Also, some studies on Bedia girls engaged in the commercial sex industry in India have examined the birth order among female siblings as a situation in which a person would experience heightened risks of being trafficked.

The commercial sexual exploitation of children (CSEC) is a socially accepted form of prostitution by numerous Indian castes. Girls as young as 12 are selected to enter the sex industry to generate family income [32,33,34]. By making their own lives worse, Bedia girls engaged in prostitution improve the lives of their siblings and parents [32]. Many cases have been reported where Bedia girls have been rescued from a sex trafficking situation, handed over to their parents, and compelled again to go into sex work [35]. While some studies on vulnerabilities to sex trafficking among Bedia youth concluded that birth order did not predict commercial sex industry entry among female siblings [33], other studies concluded that the eldest daughter was often the one selected to enter the commercial sex trade. Rana et al. [34] concluded that “The queerness of the Bedia community is that they themselves train their girls to be prostitutes. Traditionally, the elder daughter must participate in prostitution” (p. 4). In another study, Rana [36] explains that “Community-constituted norms take for granted that their elder daughter would join prostitution for family survival” (p. 263). Likewise, Dalla et al. [32] pointed out that the eldest daughter had the responsibility to enter the commercial sex industry “so that her younger siblings could marry” (p. 319). The problem this paper aims to tackle is to fill this gap in existing literature by quantifying the effect of birth order on minors’ susceptibility to being trafficked.

The objective of this article, based on a sample of 112 Central American women trafficked to the United States for the purpose of prostitution when they were minors, is to analyze whether birth order constitutes an element of vulnerability to sex trafficking in minors and, if so, to quantify its effect. First, the methodology used is reviewed, and the sample is described. Next, the vulnerabilities of the women interviewed are analyzed. Finally, the relationship between birth order and vulnerability to sex trafficking, both through deception and abuse of a situation of vulnerability, is analyzed.

2. Materials and Methods

2.1. Sampling Procedure and Ethical Aspects

The migration process to the US is risky and increases women’s vulnerability. Therefore, interviewing marginalized populations at a pivotal time of migrating to the US presents an ethical dilemma. However, restricting studies involving women migrating to the US would silence women’s accounts of their experiences and limit the pursuit of disciplinary knowledge. Vulnerable populations are more likely to be mistreated or taken advantage of. To avoid our participants being harmed in some ways and to prevent any effect the interview could have on migrant women’s life post-interview, we advised interviewees not to answer any question they did not feel comfortable with and not to mention any names of persons or places. Before the interview began, we reassured our interviewees about the value of their lived experiences and how what they had to say would be helpful for others.

To avoid interviewees feeling interrogated, we used a memorized, not a written, guide. Likewise, to avoid any power imbalance between researchers and migrant women, the interview format was an ordinary conversation. Interviews started by addressing less important topics and continued on to discussing more sensitive topics in a way that was meaningful for interviewees. In many cases, the outcome of the interview was therapeutic. Interviewees were pleased to share their thoughts with a researcher that valued, always validated, and never rejected what they had to say.

In a typical fieldwork trip, the first and third authors stayed a few days at a low-cost hotel near a bus station used by migrants. In many cases, when a few migrants (six or seven) gather some money, one of them hires a room for one day. This room can be used only for two people. Therefore, only two of them will stay at night, while the other four or five will stay outside. However, the latter will use the room to take a shower. The initial contact usually was established with one or several migrants staying in the hotel. After getting to know each other, we explained the purpose of our study to them and asked them to help us recruit, from among their acquaintances, those who fit the research criteria. When we were lucky, we could conduct a few interviews. The interviews were recorded and transcribed.

Due to the difficulty in locating and accessing the population under study, the only possible approach was using non-probabilistic sampling, so purposive sampling was used. The procedure used to select the sample was chain sampling. The interviews were conducted with Central American migrant women in transit to the United States in different locations in eight Mexican states (Chiapas, Tabasco, Mexico City, Veracruz, Tamaulipas, Nuevo León, Coahuila, and Chihuahua) during the years 2012 to 2023.

Four criteria were followed to select the sample:

(1)

Being of legal age at the time of the interview.

(2)

Having been trafficked to the United States and prostituted before the age of 18.

(3)

Suffering from situations of vulnerability linked to structural factors, such as extreme poverty characterized by a lack of access to essential goods and services.

(4)

Suffering from situations of vulnerability linked to individual factors, such as teenage pregnancy, absence of one or both parents, or coming from a dysfunctional home with domestic violence, alcoholism, drug addiction, or parental abuse.

During the fieldwork, the guidelines proposed by the World Health Organization [37] were followed. The methodological design was approved by the Ethics Committee of the Academic Research Body ‘Migration, Development, and Human Rights’ of Tamaulipas Autonomous University. Consent for voluntary participation in the study was obtained orally. The purpose of the study, the institution conducting the study, and the voluntary nature of participants’ involvement in the research were explained to each participant. Likewise, those who agreed to take part in this research were informed of the confidentiality and anonymity of all the information collected.

2.2. Participants

More than two-fifths (43.7%) of the respondents were Guatemalan; more than a quarter (26.8%) were Salvadoran; a quarter were Honduran; and five were Nicaraguan (see

Table 1. Country of origin of the women interviewed.

Statistics	Guatemala	El Salvador	Honduras	Nicaragua	Total
n	49	30	28	5	112
%	43.7	26.8	25.0	4.5	100

Source: Elaborated by the authors based on the data collected during the interviews.

). The ages of the respondents ranged from 18 to 32 years old. Due to the poor environment in which they grew up, they had an average of 3.3 years of education. The average number of siblings was 5.7. The interviewees were trafficked to the United States between the ages of 12 and 17 and remained in prostitution for an average of 81.3 months until they were repatriated to their countries of origin because they could not prove their legal stay in the United States (see

Table 2. Characteristics of the women interviewed.

Characteristics	m	mo	mdn	min	max	sd
Age	23.2	25	23	18	32	3.07
Years of education	3.3	0	4	0	9	2.94
Number of siblings	5.7	5	6	1	11	1.81
Age when trafficked to the United States	15.2	16	15	12	17	1.34
Months in prostitution in the United States	81.3	95	75.5	24	185	30.22

Note. Sample size: n = 112. Descriptive statistics: m = arithmetic mean. mo = mode, mdn = median, min = minimum, max = maximum, sd = standard deviation. Source: Elaborated by the authors based on the data collected during the interviews.

).

2.3. Data Analysis: Qualitative Aspects

The data analysis process for the qualitative portion of the project covered three technical stages: (1) Simplification of information; (2) Categorization of information; and (3) The analysis of results. The first stage consisted of the reduction and simplification of the data collected under the criterion of interpretative relevance [38] (p. 287). Once all the core thematic lines had been delimited, the reverse process was carried out: a categorization of the information. This is an inductive process of conceptual classification of units under the same criterion [38] (p. 290). After this stage, in which the qualitative material was categorized, the phase of analysis of results began [39] (p. 52).

2.4. Data Analysis: Quantitative Aspects

The statistical significance of the effect of birth order (youngest, middle, and older sister) on the general situation or the two specific situations was tested using the likelihood ratio test or G-test with Williams’ continuity correction [40] at a 5% significance level. The type II error, or probability β (the probability of retaining the null hypothesis given that the alternative hypothesis is true), in the significance test was calculated using the cumulative probability distribution function of a non-central chi-squared distribution. The complement of β provides the statistical power, or the probability of rejecting the null hypothesis given that the alternative is true: ϕ = 1 − β. Simultaneous confidence intervals (CIs) for these multinomial proportions at 95% were calculated using Wilson’s method [41,42]. The effect size of birth order was estimated using Cohen’s w statistic [43]. Post hoc pairwise comparisons were executed using the binomial exact test with Benjamini–Hochberg’s correction [44]. The calculations were performed using SPSS 29 [45] and Real Statistics using Excel [46] (see File S1 for raw data).

3. Results

3.1. Vulnerabilities of Central American Women Trafficked to the United States

All the interviewees presented vulnerabilities linked to both structural and individual factors that made them susceptible to being trafficked for sexual exploitation. In terms of vulnerabilities linked to structural factors, all the interviewees experienced extreme poverty during their childhood. Extreme poverty has been identified as an element that dehumanizes and commodifies women and children, who are perceived as objects of little value [47]. Moreover, the lack of economic resources compels victims to take great risks, such as migrating to the United States under unfavorable conditions [48] (p. 123).

The term most frequently mentioned by the interviewees to describe their family situations was poverty, which was associated with unemployment, poorly paid employment, and a lack of economic opportunities. The interviewees recalled with sadness the hunger they experienced in their childhood, the scarcity of food at home, and having to sleep on an empty stomach.

Dionisia, a 26-year-old Guatemalan woman, the fourth of seven siblings, was born into a peasant family. She never went to school because her family could not afford the costs. When she was 12 years old, due to a drought, they ran out of money. (See Appendix A).

Esperanza, a 19-year-old Guatemalan woman, the eldest of four siblings, started working at the age of 10. She dropped out of school because her father did not earn enough money to support the family. In her childhood, she never thought about having new clothes or shoes. Her only thought was about having enough food. She endured without eating, but her younger siblings did not stop crying because there was no food on the table.

Gabriela, a 20-year-old Guatemalan woman, was the third of five siblings. She was 13 years old when her mother died. Because her father was unemployed, she left home because there was no food. But she joined bad acquaintances and fell into drugs.

Inés, a 24-year-old Guatemalan woman, was the fifth of seven siblings. Her family migrated from a rural area to San Marcos to be better. However, they suffered from underemployment. Although all members of the family worked, all their income was spent on food.

Jacinta, a 25-year-old Salvadoran woman, the youngest of seven siblings, started working at the age of 9 to help her father. At the age of 14, she went to live with her partner. But he was murdered, and she was widowed at the age of 16.

Patricia, a 21-year-old Salvadoran woman, the eldest of four siblings, was abandoned by her parents and left in the care of a 15-year-old aunt.

Trinidad, a 23-year-old Salvadoran woman, was the youngest of four siblings. Her father was a merchant, but there were days when he did not sell anything, and they did not have enough to eat.

Likewise, the lack of education intensifies the vulnerability created by poverty because it deprives the person of the benefits associated with school attendance [48] (p. 124). As seen in

Table 3. Vulnerabilities linked to structural factors and individual factors.

Type of Vulnerability	Specific Vulnerability Factor	n	%
Linked to structural factors	Poverty	112	100
	Illiteracy	44	39.3
Linked to individual factors	Teenage pregnancy	46	41.1
	Absence of the father	24	21.4
	Absence of the mother	6	5.4
	Absence of both parents	13	11.6
	Disabled father	4	3.6
	Alcoholic and unemployed father	9	8.0
	Raped and/or prostituted by a relative	10	8.9
	Mother prostitute	11	9.8
	Some family member is involved in organized crime	14	12.5

Note. n = absolute frequency and % percentage = (n/112) × 100. The sum of vulnerabilities is greater than 112, since several vulnerabilities per participant are included. Source: Elaborated by the authors from data collected during the interviews.

, almost two-fifths (39.3%) of the interviewees had not attended school due to a lack of economic resources.

On the other hand, vulnerabilities associated with individual factors are linked to teenage pregnancy, the absence of one or both parents, and the violence stemming from alcoholism, drug use, and involvement in illegal markets (organized crime, drug trafficking, and pimping). More than two-fifths (41.1%) of those interviewed experienced a pregnancy during their adolescence. Adolescent pregnancy leaves a trail of social, economic, and health vulnerabilities, which facilitates sex trafficking [49] (p. 1050). This scenario places minors in a borderline situation that forces them to accept any source of income to support their children.

Pilar, a 26-year-old Honduran woman, was the youngest of seven siblings. Her parents were sick, and there was no money in the house. She never had new clothes, and some days, she did not eat at all. Therefore, she started working at the age of 9. At the age of fifteen, she became pregnant and had to prostitute herself to support her child.

Two-fifths of the respondents grew up in households where one or both parents were missing because they died, were murdered, disappeared, were incarcerated, or left home. The father was absent in more than a quarter (21.4%) of the cases, the mother in 5.4%, and both father and mother in 11.6% of the cases studied. Teresa, a 26-year-old Honduran woman, was the second of five siblings. Her parents consumed the entire family budget on alcohol and drugs. Therefore, they barely had enough to eat. But her situation worsened when her mother killed her father in self-defense.

Six were raped or prostituted by a relative. Rosa, a 22-year-old Honduran woman, was the eldest of six siblings. From the time she was born, her father despised her for not being a boy, and from a very young age, she was raped by him.

Eight of the interviewees indicated that their father did not make any contribution to the family economy, either because he was sick and disabled or because he was an alcoholic and unemployed. In eleven of the cases studied, the mother made a living from the sex trade, which led her daughters to become involved in this environment. In some cases, the interviewees were not forced by their mothers to enter the sex trade.

Dorotea, a 26-year-old Nicaraguan woman, was the eldest of three siblings. Her mother was a sex worker and earned enough money to support her. But, when her twin sisters were born, she became depressed and stopped working. Then, the family economy collapsed. Her mother never forced her to work, but, at the age of 13, she started working in cleaning activities to support her mother and sisters, and when she was fifteen, she decided to work in prostitution.

However, in other cases, they were forced. Silvia, a 22-year-old Salvadoran woman, was the eldest of three siblings. Her younger sisters lived with an aunt, but she always accompanied her mother, who was a sex worker. Due to alcohol and drug use, her mother acquired such a high debt that she sold her daughter to pay it off.

On the other hand, in 12.5% of the cases, some member of the family was a member of a criminal organization involved in drug trafficking, human trafficking, or extortion. These households were characterized by high levels of gender-based violence, which mainly affected underage daughters.

Paulina, a 27-yea-old Salvadoran woman, was the youngest of eight siblings. She grew up in a family of delinquents. His father and brothers were criminals. Drugs were used regularly in her home, and both she and her mother were abused by both her father and siblings. One of her brothers was killed and another imprisoned.

All these vulnerabilities pave the way for minors to be recruited by sex trafficking networks, either through fraud, deception, or coercion, or by abusing a position of vulnerability. Underage girls recruited by these networks often find themselves in a situation where their only option is to emigrate to solve their problems.

Abigail, a 26-year-old Salvadoran woman, was the fifth of eleven siblings. She was born into a peasant family, but they did not suffer economic hardship. Her problem started at the age of 14, when she married a criminal. Her husband was killed because of a drug trafficking problem, and she was going to be killed.

Sandra, a 20-year-old Honduran woman, was the second of four siblings. Their parents were always drunk and did not care about their children. That is why she decided to emigrate to the United States when she was 15 years old. She wanted to live alone and get away from her family.

Susana, a 27-year-old Honduran woman, was also the second of four siblings. Their parents drank, took drugs, and usually forgot to feed their daughters. She ran away from home when she was thirteen due to domestic violence. She went to live with her partner, but her situation worsened. He always was high and beat her. Therefore, when she was sixteen, she decided to emigrate to the United States for fear of being killed.

3.2. Situation Experienced in Relation to Sex Trafficking Networks

The 112 women who make up the total sample were victims of sex trafficking when they were minors, that is, they were recruited by an international human smuggling network involved in the sex trade before they were 18 years old, which is called the general situation for the purposes of analysis. While some women recruited and transported by traffickers are unaware that they will be prostituted, others are aware that they will be compelled to prostitute themselves [49,50].

Of these 112 women, 36 (32.1%) were victims of sex trafficking through deception, which is called specific situation 1. They were deceived and coerced. On the other hand, 76 (67.9%) of the 112 women were victims of sex trafficking through abuse of a situation of vulnerability (extreme poverty, pregnancy during adolescence, absence of a father figure, among the main reasons), which is called specific situation 2. They were aware of the activity they had to perform, but they did not know about the working conditions.

3.2.1. Effect of Birth Order on Overall Sex Trafficking Status as a Minor

We examined whether birth order influences the likelihood of being trafficked as a minor by assessing the deviation of its empirical distribution from the expected distribution under the assumption of independence. The significance test was conducted using the G-test with Williams’ continuity correction [40].

We counted the absolute frequencies of the number of siblings (NH) in the sample (n_i). Three birth order categories were established: 1 = youngest, 2 = middle sister (neither older nor younger), and 3 = only daughter or oldest sister. The absolute frequencies (n_o) and relative frequencies or proportions (f_o) of these three ordered categories in the sample were obtained. Simultaneous confidence intervals (CIs) for these multinomial proportions at 95% were calculated using Wilson’s method [41,42].

The observed proportion (f_o) of youngest sisters was 0.116, 95% CI [0.069, 0.189]; for middle sisters, it was 0.5, 95% CI [0.409, 0.591]; and for oldest sisters, it was 0.384, 95% CI [0.299, 0.476]. Refer to

Table 4. Observed and expected frequency of the number of siblings in the general situation of sex trafficking while underage.

N. of Siblings and Statistics	ni	P (NS|Birth Order)			Expected Frequency			∑
		Youngest	Middle	Oldest	Youngest	Middle	Oldest
1	3	0	0	1	0	0	3	3
2	2	0.5	0	0.5	1	0	1	2
3	5	0.333	0.333	0.333	1.667	1.667	1.667	5
4	16	0.25	0.5	0.25	4	8	4	16
5	27	0.2	0.6	0.2	5.4	16.2	5.4	27
6	28	0.167	0.667	0.167	4.667	18.667	4.667	28
7	15	0.143	0.714	0.143	2.143	10.714	2.143	15
8	10	0.125	0.75	0.125	1.25	7.5	1.25	10
9	5	0.111	0.778	0.111	0.556	3.889	0.556	5
11	1	0.091	0.818	0.091	0.091	0.818	0.091	1
ne					20.773	67.455	23.773
fe					0.185	0.602	0.212	112
LLfe					0.124	0.510	0.147	1
ULfe					0.267	0.688	0.297
no					13	56	43	112
fo					0.116	0.5	0.384	1
LLfo					0.069	0.409	0.299
ULfo					0.189	0.591	0.476
no × ln(no/ne)					−6.093	−10.422	25.485	8.970
(fo − fe)2/fe					0.026	0.017	0.139	0.182

Note. n_i = absolute frequency of the number of siblings (NS), P(NS|birth order) = probability of the number of siblings conditional on the birth order category under an assumption of equiprobability or independence, Expected frequency (under the assumption of independence) = n_i × P(ns_i/bo_ij), where ns represents number of siblings (i = {1, 2, …, 11}) and bo denotes order of birth (j = {1 = youngest sister, 2 = middle sister, 3 = oldest or only sister}), and ∑ = row sum of the last three columns. n_e = expected absolute frequency or column sum of the joint frequencies, f_e = expected relative frequency with 95% confidence interval by Wilson’s method for simultaneous intervals of multinomial proportions (LL = lower limit and UL = upper limit), n_o = observed absolute frequency, f_o = observed relative frequency with 95% confidence interval by Wilson’s method for simultaneous intervals of multinomial proportions, n_o × ln(n_o/n_e) = summands of the G statistic, and (f_o − f_e)²/f_e = summands of the Cohen’s W effect size statistic. Source: Own elaboration from data collected during the interviews.

for details.

The probabilities of the number of siblings (NS) conditional on the three categories of birth order were calculated under the assumption of independence, P(NS|birth order). The product of the observed frequency of the number of siblings and the conditional probability yields the joint expected frequency. The marginal frequency or sum of the joint expected frequencies per column gives the absolute expected frequency per category under the assumption of independence.

The difference between observed and expected frequencies in the general situation was significant by G-test at 5% significance level (g = 2 × 8.970 = 17.940, Williams’ continuity correction: q = 1.006, g_c = g/q = 17.940/1.006 = 17.833, p-value = 0.00013 < α = 0.05). The observed frequency of the number of oldest sisters (f_o = 0.384, 95% CI [0.299, 0.476]) was above the expected (f_e = 0.212, 95% CI [0.147, 0.297]); thus, the interval of the observed and expected proportion did not overlap. Refer to Table 4 for details.

The post hoc power of the test statistic was calculated as the complement of the cumulative distribution function of a non-central chi-squared distribution with two degrees of freedom. Its non-centrality parameter is the value of the test statistic (NCP = g_c). The argument of the function is the critical value of the chi-square test: ϕ = 1 − NCχ²_{[gl = 2, PNC = 17.833]} (0.95χ²_[2] = 5.991) = 1 − 0.027 = 0.973. With a value greater than 0.9, a very high statistical power was achieved. The effect size of birth order was estimated using Cohen’s [43] W statistic: W = √[∑(f_o − f_e)²/f_e]. Values of W less than 0.1 indicate a trivial effect size, between 0.1 and 0.249, a small effect, between 0.25 and 0.499, a medium effect, and greater than or equal to 0.5, a large effect. In this case, a medium effect size resulted (0.25 < w = √0.182 = 0.427 < 0.5).

When performing post hoc goodness-of-fit tests between pairs of categories using the binomial exact test with Benjamini–Hochberg’s correction [44] for a 5% significance level, it was observed that the number of oldest sisters was significantly higher, while the number of youngest sisters was significantly lower than expected (p_(one-tailed) = 0.0001 < α_c = 0.017). Additionally, the number of oldest sisters was significantly higher, while the number of middle sisters was significantly lower than expected (p_(one-tailed) = 0.0003 < α_c = 0.033). See

Table 5. Pairwise goodness of fit assessed by the exact binomial test with Benjamini–Hochberg correction for the false discovery rate in the general situation of sex trafficking while a minor.

i	j	no(i)	njo(i)	n	pe(ij)	ne(i)	ne(j)	p(1-tailed)	i	αc	sig.
1	2	13	56	69	0.235	16.246	52.754	0.2210	3	0.050	no
1	3	13	43	56	0.466	26.114	29.886	0.0003	2	0.033	yes
2	3	56	43	99	0.739	73.202	25.798	0.0001	1	0.017	yes

Note. i, j = birth order category (1 = youngest, 2 = middle, 3 = oldest), n_o = observed absolute frequency, p_e = expected probability = p_e(ij) = n_e(i)/(n_e(i) + n_e(j)): p_e(12) = 20.773/(20.773 + 67.455) = 0.235, p_e(13) = 20.773/(20.773 + 23.773) = 0.466, and p_e(23) = 67.455/(67.455 + 23.773) = 0.739, n_e(i) = n × p_e(ij), n_e(j) = n × (1 − p_e(ij)), p_(1-tailed) = P[X ≤ n_o(i)|n, p_e(ij)], where X~B(n, p_e(ij)), i = ascending order of probability, α_c = (i/3) × α = significance level corrected by the Benjamini–Hochberg procedure for an α of 0.05, sig. = the test is not significant, if p_(1-tailed) ≥ α_c; and is significant, if p_(1-tailed) < α_c. Source: Own elaboration from the data collected during the interviews.

.

3.2.2. Effect of Birth Order on Specific Situation 1 (of Sex Trafficking through Deception)

Deception is a strategy used with some frequency by sex traffickers that recruit minors in Central America and take them to the United States. Underage girls from families living in poverty and financial instability are easily lured by recruiters who offer them attractive, high-paying jobs in the fashion, beauty, or modeling sectors. The minors quickly agree to leave behind a life of suffering to live a supposed life of luxury in the United States. However, when they arrive in the country of destination, the activity they are to perform is very different from what they were told. In the destination country, they realize that they were not brought to be models but to be exploited in the sex trade.

Being minors, having no English language or literacy skills, and having no economic resources blocks trafficked children from seeking assistance. Accepting the traffickers’ proposal would mean that they would be able to pay off the debt they incurred when they were taken to the north, and they can send remittances to their families. On the contrary, rejecting the traffickers’ proposal would mean their deportation and the accumulation of a debt that neither they nor their families could afford. As a result, victims had to accept what the traffickers proposed to them: to engage in the sex trade in exchange for financial remuneration. As the following excerpts reflect, the interviewees indicated that they did not wish to engage in prostitution but had to do so.

“They told me about having a job, but they didn’t tell me what the job was going to be. With the desire and need to work, I said yes. I was going to work, and I came without knowing that this job was. Once there, I had to do it, what else could you do when you are in economic trouble; there is nothing else to do but to work”

(Consuelo. 20 years old woman from Honduras interviewed in Coahuila in March 2015).

“I did not want to do it, but they forced me. I was in the north far from my family and I didn’t know anyone, so I had to do it”

(Daniela. 21 years old woman from Honduras interviewed in Tabasco in July 2015).

“Arriving to the north they asked me that if I had had sex, and I told them that I didn’t; then, it was when they put a price on me (…) When I arrived, they told me what I had to do. I didn’t know that I had to do it; but, once there, they told me that and I had to do it because I had to repay the expenses, they had incurred for me”

(Fernanda. 23 years old woman from Guatemala interviewed in Mexico City in June 2018).

“They didn’t tell me that I had to work in prostitution. They told me that when I was in the north. When I was already there, they told me, and I had to do it”

(Mariana. 25 years old woman from Honduras interviewed in Veracruz in December 2020).

Regarding the quantitative data, the observed relative frequency or proportion (f_o) of youngest sisters in specific situation 1 (of sex trafficking through deception) was 0.056, with a 95% confidence interval (CI) of [0.015, 0.181]. For middle sisters, the proportion was 0.444, 95% CI [0.295, 0.604], while for oldest sisters, it was 0.5, 95% CI [0.345, 0.655]. The difference between the observed and expected frequency was significant (g = 18.534, Williams’ continuity correction: q = 1.019, g_c = g/q = 18.534/1.019 = 18.197, p-value = 0.0001). The frequency of oldest sisters was higher than expected (f_e = 0.197, 95% CI [0.099, 0.353]), and the interval of the observed and expected proportion did not overlap. The post hoc statistical power was very high (ϕ = 1 − NCχ²_{[gl = 2, PNC = 18.197]} (0.95χ²_[2] = 5.991)) = 1 − 0.024 = 0.976, which is greater than 0.9). The effect size of birth order by Cohen’s [43] W statistic was large (w = √0.610 = 0.781, exceeding 0.5). Refer to

Table 6. Observed and expected frequency of the number of siblings in the specific situation 1 of sex trafficking through deception.

Number of Siblings	ni	P (NS|Birth Order)			Expected Frequency			∑
		Youngest	Middle	Oldest	Youngest	Middle	Oldest
2	1	0.5	0	0.5	0.5	0	0.5	1
3	4	0.333	0.333	0.333	1.333	1.333	1.333	4
4	3	0.25	0.5	0.25	0.75	1.5	0.75	3
5	7	0.2	0.6	0.2	1.4	4.2	1.4	7
6	11	0.167	0.667	0.167	1.833	7.333	1.833	11
7	4	0.143	0.714	0.143	0.571	2.857	0.571	4
8	3	0.125	0.75	0.125	0.375	2.25	0.375	3
9	3	0.111	0.778	0.111	0.333	2.333	0.333	3
ne					7.096	21.807	7.096	36
fe					0.197	0.606	0.197	1
LLfe					0.099	0.443	0.099
ULfe					0.353	0.748	0.353
no					2	16	18	36
fo					0.056	0.444	0.500	1
LLfo					0.015	0.295	0.345
ULfo					0.181	0.604	0.655
no × ln(no/ne)					−2.533	−4.954	16.754	9.267
(fo − fe)2/fe					0.102	0.043	0.465	0.610

Note. n_i = absolute frequency of the number of siblings (NH), P (NS|birth order) = probability of the number of siblings conditional on the birth order category under an assumption of equiprobability or independence, Expected frequency (under the assumption of independence) = n_i × P(ns_i/bo_ij), where ns represents number of siblings (i = {1, 2, …, 11}) and bo denotes order of birth (j = {1 = youngest sister, 2 = middle sister, 3 = oldest or only sister}), and ∑ = row sum of the last three columns. n_e = expected absolute frequency or column sum of the joint frequencies, f_e = expected relative frequency with 95% confidence interval by Wilson’s method for simultaneous intervals of multinomial proportions (LL = lower limit and UL = upper limit), n_o = observed absolute frequency, f_o = observed relative frequency with 95% confidence interval by Wilson’s method for simultaneous intervals of multinomial proportions, n_o × ln(n_o/n_e) = summands of G statistic and (f_o − f_e)²/f_e = summand of the Cohen’s W effect size statistic. Source: Own elaboration from data collected during the interviews.

for more details.

When conducting post hoc pairwise goodness-of-fit comparisons using the binomial exact test with Benjamini and Hochberg [44] correction at a 5% significance level, the count of oldest sisters was significantly higher, while the count of youngest sisters was significantly lower than expected (p_(one-tailed) = 0.0002 < α_c = 0.017). Similarly, the count of oldest sisters was significantly higher, while the count of middle sisters was significantly lower than expected (p_(one-tailed) = 0.0003 < α_c = 0.033). Refer to

Table 7. Pairwise goodness of fit assessed by exact binomial test with Benjamini–Hochberg correction in the specific situation 1 of sex trafficking through deception.

i	j	no(i)	njo(i)	n	pe(ij)	ne(i)	ne(j)	p(1-tailed)	i	αc	sig.
1	2	2	16	18	0.246	4.419	13.581	0.1447	3	0.050	no
1	3	2	18	20	0.5	10	10	0.0002	1	0.017	yes
2	3	16	18	34	0.754	25.652	8.348	0.0003	2	0.033	yes

Note. i, j = birth order category (1 = youngest, 2 = middle, 3 = oldest), n_o = observed absolute frequency, p_e = expected probability = p_e(ij) = n_e(i)/(n_e(i) + n_e(j)): p_e(12) = 7.096/(7.096 + 21.807) = 0.246, p_e(13) = 7.096/(7.096 + 7.596) = 0.5 y p_e(23) = 21.807/(21.807 + 7.096) = 0.754, n_e(i) = n × p_e(ij), n_e(j) = n × (1 − p_e(ij)), p_(1-tailed) = P[X ≤ n_o(i)|n, p_e(ij)], where X~B(n, p_e(ij)), i = ascending order of probability, α_c = (i/3) × α = significance level corrected by Benjamini–Hochberg procedure for an α of 0.05, sig = the test is not significant, if p_(1-tailed) ≥ α_c; and it is significant, if p_(1-tailed) < α_c. Source: Own elaboration from data collected during the interviews.

for details.

3.2.3. Effect of Birth Order on Specific Situation 2 (of Sex Trafficking through Abuse of a Situation of Vulnerability)

The abuse of a situation of vulnerability is the strategy most frequently used by networks smuggling women from Central America to the United States for the purpose of prostitution. Extreme poverty, teenage pregnancies, the absence of parental figures, the inability of the head of the household to play the role of provider, or the family’s involvement in illegal markets facilitates the recruitment of Central American minors by human smuggling networks involved in the sex trade. The traffickers do not deceive the minors. The former explain to the latter the nature of the work they will be doing in the United States. This does not prevent underage girls from refusing to migrate north. The multiple vulnerabilities they have faced since their early childhood predispose them to accept any type of activity in exchange for economic remuneration.

Schwartz et al. [48] (p. 123) point out that the vulnerability associated with poverty causes many people to allow themselves to be put into slavery to obtain financial security. Therefore, when human smugglers tell underage girls that they will only take them to the United States if they agree to work in the sex trade, the minors do not hesitate to accept the smugglers’ invitation. As Patricia (21 years old woman from El Salvador interviewed in Veracruz in April 2021) said, “When I went north, I already knew about the job I would do”, or as Paulina (27 years old woman from El Salvador interviewed in Veracruz in April 2021) pointed out, “I already knew, I knew what I was going to do and that the job was good because they paid me well”. Likewise, Sandra (20 years old woman from Guatemala interviewed in Mexico City in July 2022) affirmed, “When I went to the north, the smuggler told me: ‘I’ll help you, but your job will be in a bar serving men’, and I said: ‘yes’”.

Regarding the quantitative data, the observed relative frequency or proportion (f_o) of youngest sisters in specific situation 2 (of sex trafficking through the abuse of a vulnerable situation) was 0.145, with a 95% CI [0.083, 0.241]. For middle sisters, the proportion was 0.526, 95% CI [0.416, 0.635], and for oldest sisters, it was 0.329, 95% CI [0.234, 0.441]. The difference between observed and expected frequencies was not significant (g = 4.888, Williams’ continuity correction: q = 1.009, g_c = g/q = 4.888/1.009 = 4.846, p-value = 0.0887 > α = 0.05). The type II error was greater than 0.5: β = NCχ²_{[gl = 2, PNC = 4.846]} (0.95χ²_[2] = 5.991) = 0.509, and the post hoc statistical power was less than 0.5 (ϕ = 1 − 0.509 = 1 − 0.042 = 0.491 > 0.9). These last two statistics are consistent with the retention of the null hypothesis, indicating that rejecting the null hypothesis would be an error. However, the effect size of birth order by Cohen’s [43] W statistic was not trivial, but small (0.2 < w = √0.071 = 0.266 < 0.5). Refer to

Table 8. Observed and expected frequency of the number of siblings in the specific situation 2 of sex trafficking through abuse of a situation of vulnerability.

Number of Siblings	ni	P (NS|Birth Order)			Expected Frequency			∑
		Youngest	Middle	Oldest	Youngest	Middle	Oldest
1	3	0	0	1	0	0	3	3
2	1	0.5	0	0.5	0.5	0	0.5	1
3	1	0.333	0.333	0.333	0.333	0.333	0.333	1
4	13	0.25	0.5	0.25	3.25	6.5	3.25	13
5	20	0.2	0.6	0.2	4	12	4	20
6	17	0.167	0.667	0.167	2.833	11.333	2.833	17
7	11	0.143	0.714	0.143	1.571	7.857	1.571	11
8	7	0.125	0.75	0.125	0.875	5.25	0.875	7
9	2	0.111	0.778	0.111	0.222	1.556	0.222	2
11	1	0.091	0.818	0.091	0.091	0.818	0.091	1
ne	76				13.676	45.648	16.676	76
fe					0.180	0.601	0.219	0.180
LIfe					0.110	0.488	0.141	0.110
LSfe					0.281	0.703	0.325	0.281
no					11	40	25	11
fo					0.145	0.526	0.329	0.145
LLfo					0.083	0.416	0.234	0.083
USfo					0.241	0.635	0.441	0.241
no × ln(no/ne)					−2.395	−5.283	10.122	2.444
(fo − fe)2/fe					0.007	0.009	0.055	0.071

Note. n_i = absolute frequency of the number of siblings (NS), P (NS|birth order) = probability of the number of siblings conditional on the birth order category under an assumption of equiprobability or independence, expected frequency under the assumption of independence = n_i × P(ns_i/bo_ij), where ns represents number of siblings (i = {1, 2, …, 11}) and bo denotes order of birth (j = {1 = youngest sister, 2 = middle sister, 3 = oldest or only sister}), and ∑ = row sum of the last three columns. n_e = expected absolute frequency or column sum of the joint frequencies, f_e = expected relative frequency with 95% confidence interval by Wilson’s method for simultaneous intervals of multinomial proportions (LL = lower limit and UL = upper limit), n_e = observed absolute frequency, f_o = observed relative frequency with 95% confidence interval by Wilson’s method for simultaneous intervals of multinomial proportions, n_o × ln(n_o/n_e) = summands of the G statistic and (f_o − f_e)²/f_e = summand of the Cohen’s W effect size statistic. Source: Own elaboration from data collected during the interviews.

for details.

Pairwise goodness-of-fit comparisons using the binomial exact test with Benjamini–Hochberg [44] correction for a 5% significance level also showed no significant difference. However, without the correction, the count of oldest sisters was significantly higher, and the count of middle sisters was significantly lower than expected (p_(one-tailed) = 0.026 < α = 0.05). Refer to

Table 9. Pairwise goodness of fit assessed by the exact binomial test with Benjamini–Hochberg correction for specific situation 2 of sex trafficking through abuse of a vulnerable situation.

i	j	no(i)	njo(i)	n	pe(ij)	ne(i)	ne(j)	p(1-tailed)	i	αc	sig.
1	2	11	40	51	0.231	11.757	39.243	0.653	3	0.050	no
1	3	11	25	36	0.451	16.221	19.779	0.055	2	0.033	no
2	3	40	25	65	0.732	47.608	17.392	0.026	1	0.017	no

Note. i, j = birth order category (1 = youngest, 2 = middle, 3 = oldest), n_o = observed absolute frequency, p_e = expected probability = p_e(ij) = n_e(i)/(n_e(i) + n_e(j)): p_e(12) = 13.676/(13.676 + 45.648) = 0.231, p_e(13) = 13.676/(13.676 + 16.676) = 0.451 y p_e(23) = 45.648/(45.648 + 16.676) = 0.732, n_e(i) = n × p_e(ij), n_e(j) = n × (1 − p_e(ij)), p_(1-tailed) = P[X ≤ n_o(i)|n, p_e(ij)], where X~B(n, p_e(ij)), i = ascending order of probability, α_c = (i/3) × α = significance level corrected by Benjamini–Hochberg procedure for an α of 0.05, sig = the test is not significant, if p_(1-tailed) ≥ α_c; and it is significant if p_(1-tailed) < α_c. Source: Own elaboration from data collected during the interviews.

for details.

4. Discussion

Human smuggling networks who recruit women for the purpose of sexual exploitation target and take advantage of the desperate situation of vulnerable underage victims who, compelled by severe economic problems, make a constrained choice to migrate north. Minors trafficked through deception consented under conditions of fraud, while minors trafficked through abuse of a situation of vulnerability made a difficult choice and consented to a sex trafficking situation.

The 112 women interviewed, who were trafficked when they had not attained the age of eighteen years, exhibited two types of vulnerabilities: those associated with social structures and those associated with individual behaviors. The interviewees grew up in households characterized by extreme poverty and other vulnerabilities.

On one hand, factors such as family financial instability, economic insecurity, unemployment, and a lack of economic opportunities in their countries of origin makes underage girls susceptible to the enticing narratives of traffickers promising economic prospects in the United States. Poverty creates desperate conditions that restrict the options of underage sex trafficking victims and increases their risk of sexual exploitation. The children’s desire to escape poverty makes sex trafficking possible.

On the other hand, problems such as teenage pregnancy and the pervasive climate of violence resulting from family dysfunctions, as well as the involvement of parents or siblings in illegal markets, creates an environment conducive to minors seeking migration to change the trajectory of their lives. Parents, especially foster parents, who are substance dependent should be screened for putting their daughters at risk of being exploited in prostitution.

Sisters who occupy the first position in the birth order (oldest sisters) are the most susceptible to being recruited by an international human smuggling network involved in prostitution (general situation) and to being tricked by traffickers into migrating to the United States to enter the sex trade market, compared to youngest sisters (specific situation 1). Even considering that the oldest sisters studied in this research were minors (average age of 15), their position in the birth order made them more vulnerable to sacrifice themselves for the sake of their youngest brothers and sisters, especially when one or both parents were absent.

On the contrary, youngest and middle sisters are at a lower risk due to the protection and guidance provided by their oldest siblings. As a result, their frequency is lower than expected in both the general situation and the specific situation 1 (of sexual trafficking through deception) when compared to oldest sisters in the pairwise comparisons. No differences are observed between the youngest and middle sisters. In the specific situation 2 (of sexual trafficking through the abuse of a vulnerable situation), the effect of birth order is not significant in the omnibus test; however, it is observed that older sisters have a higher risk than middle sisters in the reduced comparison to these two categories using the exact probability.

Statistical significance in a statistical test indicates the presence of an effect in a study. As a good practice in analysis, this information should be complemented by the effect size, which indicates the potential practical significance of the finding [51]. It should be noted that a large effect size suggests that the research finding has practical significance, a medium effect size indicates potential application or consideration, while a small effect size shows limited practical applications [52]. It is noteworthy that the effect size of birth order is large in sex trafficking through deception and medium in the general situation. Consequently, these findings have practical implications and should be considered relevant.

For whom do these results have significant implications? Given that this pertains to a violation of human rights, it is crucial for school authorities, law enforcement officers, advocacy organizations working with at-risk populations, and persons involved in local anti-trafficking coalitions, especially in sex trafficking prevention programs, in societies characterized by high levels of poverty, social inequality, and family disintegration. To help potentially vulnerable individuals before they become exploited, special attention and assistance should be given to girls who hold the first position in the birth order, as they show significantly higher numbers of cases in the studied population.

An only daughter or oldest sister facing an unwanted pregnancy within an impoverished family, particularly in cases where one parent is absent and within a context of organized crime presence, demands heightened attention for protection from both schools and social services. To disregard these cases would constitute a serious negligence on the part of the competent authorities.

As Schwarz et al. [3] have pointed out, anti-trafficking efforts should be framed from a human rights position, finding upstream, structural solutions to vulnerability. Current anti-trafficking policies are not designed to help potentially vulnerable individuals before they become trafficked. The well-funded anti-trafficking movement is focused on prosecution, not on changing social structures, which are the root causes of trafficking.

5. Conclusions

The problem of minor sex trafficking from Central America to the United States is rooted in vulnerabilities associated with structural and individual factors, which are amplified by the birth order among female siblings. Sisters occupying the first place in the birth order are the most susceptible to being recruited by an international network involved in smuggling women for the sex trade. By contrast, the youngest and middle sisters are less at risk of being trafficked for the purpose of sexual exploitation due to the protection and guidance of the older sisters.

The difference manifests in both the general context of trafficking for the purpose of sexual exploitation and the specific scenario of trafficking through deception. In instances of sex trafficking resulting from the exploitation of vulnerability, typically associated with factors such as teenage pregnancy or paternal absence, compounded by poverty and minimal education, the difference is less evident. This is mainly between the middle and oldest sisters, with the latter being more at risk.

We conclude that the approach to combating sex trafficking should be proactive, focusing on the factors that compel victims into trafficking, rather than reactive, after the harm has occurred. We agree with Schwarz et al. [3] that reactive measures are expensive and ineffective, while proactive measures (such as poverty alleviation programs and funding for abused and neglected children) reduce push factors for trafficking.