Characteristics of Sexual Abuse in Childhood and Adolescence Influence Sexual Risk Behavior in Adulthood

Childhood and adolescent sexual abuse has been associated with subsequent (adult) sexual risk behavior, but the effects of force and type of sexual abuse on sexual behavior outcomes have been less well-studied. The present study investigated the associations between sexual abuse characteristics and later sexual risk behavior, and explored whether gender of the child/adolescent moderated these relations. Patients attending an STD clinic completed a computerized survey that assessed history of sexual abuse as well as lifetime and current sexual behavior. Participants were considered sexually abused if they reported a sexual experience (1) before age 13 with someone 5 or more years older, (2) between the ages of 13 and 16 with someone 10 or more years older, or (3) before the age of 17 involving force or coercion. Participants who were sexually abused were further categorized based on two abuse characteristics, namely, use of penetration and force. Analyses included 1177 participants (n=534 women; n=643 men). Those who reported sexual abuse involving penetration and/or force reported more adult sexual risk behavior, including the number of lifetime partners and number of previous STD diagnoses, than those who were not sexually abused and those who were abused without force or penetration. There were no significant differences in sexual risk behavior between nonabused participants and those who reported sexual abuse without force and without penetration. Gender of the child/adolescent moderated the association between sexual abuse characteristics and adult sexual risk behavior; for men, sexual abuse with force and penetration was associated with the greatest number of episodes of sex trading, whereas for women, those who were abused with penetration, regardless of whether the abuse involved force, reported the most episodes of sex trading. These findings indicate that more severe sexual abuse is associated with riskier adult sexual behavior.
Introduction
Childhood and adolescent sexual abuse has been associated with a wide variety of adverse mental and physical health outcomes. Research also suggests that the greater the severity of the sexual abuse, the worse the health outcomes. Thus, more severe sexual abuse (e.g., sexual abuse involving force, more intimate sexual acts, a close relative, or repeated sexual abuse) has been associated with poorer social adjustment, less life satisfaction, and more severe psychological symptoms (Callahan, Price, & Hilsenroth, 2003; Carlson, McNutt, & Choi, 2003; Fassler, Amodeo, Griffin, Clay, & Ellis, 2005; Feinauer, Mitchell, Harper, & Dane, 1996). In a meta-analysis on the effects of child sexual abuse, Rind, Tromovitch, and Bauserman (1998) found that force was associated with more negative reactions but not with later psychological symptoms, whereas penetration was unrelated to these outcomes.
Sexual abuse severity also has been associated with subsequent sexual risk behavior, including more sexual partners (Merrill, Guimond, Thomsen, & Milner, 2003) and greater likelihood of sex with someone just met, earlier age at first intercourse, and a higher frequency of STD diagnoses (Walser & Kern, 1996). Although these studies suggest that more severe sexual abuse is associated with more sexual risk behavior, they provide only limited information regarding whether specific aspects of the abuse predict such outcomes. Needed is more fine-grained research to determine whether characteristics of the abuse experience (e.g., whether physical force was used during the abuse and the type of sexual act that occurred during the abuse) are associated with sexual health outcomes.
Two studies have examined the association between sexual abuse with force and later sexual risk behavior. Cinq-Mars, Wright, Cyr, and McDuff (2003) found that adolescent girls who experienced childhood or adolescent sexual abuse with force were more likely than girls who were sexually abused without force to have engaged in subsequent consensual sex during adolescence, to have more than one partner per year, and to have been pregnant. In a sample of men who have sex with men (MSM), Jinich et al. (1998) reported that sexual abuse perceived as moderately or strongly coerced was associated with higher frequency of unprotected anal sex and higher HIV seroprevalence rates, relative to MSM who perceived the sexual abuse as voluntary or mildly coerced. Thus, in these two studies, sexual abuse involving force has been associated with greater sexual risk behavior.
Investigations of the effects of penetrative (vs. non-penetrative) sexual abuse have yielded mixed results. Cinq-Mars et al. (2003) found that adolescent girls who experienced sexual abuse involving penetration were more likely to have engaged in consensual sex and experienced an unplanned pregnancy, compared to girls who experienced non-penetrative sexual abuse. Fergusson, Horwood, and Lynskey (1997) found that, compared to participants reporting no sexual abuse, those who experienced non-penetrative sexual abuse reported higher rates of unprotected sex. However, those who experienced penetrative sexual abuse reported the worst outcomes; compared to participants who were not sexually abused, those who reported penetrative sexual abuse were more likely to have been pregnant, to report more than five sexual partners by age 18, to have had unprotected sex, and to have had an STD.
In contrast, in a meta-analysis, Arriola, Louden, Doldren, and Fortenberry (2005) found that the effect size for the relation between sexual abuse and later sexual behavior (i.e., unprotected sex, sex with multiple partners, and sex work) did not differ for studies including non-contact abuse, studies including contact abuse only, and studies including penetration abuse only; their findings suggest that type of sexual act during sexual abuse was not associated with later sexual behavior. However, some of these categories included very few studies (e.g., there were only three studies that included penetration abuse only). Furthermore, effects may have been obscured if studies with less restrictive definitions of sexual abuse included a large number of participants who had exper- ienced more severe (i.e., contact or penetrative) sexual abuse.
In sum, evidence from a small number of studies suggests that force and penetration may be associated with adult sexual risk behavior. An important limitation of previous research is that few studies have investigated the differential effects of sexual abuse for men and women. Because women in heterosexual relationships often have less control or power over sexual encounters compared to men (see the Theory of Gender and Power, Connell, 1987, for an explanation of the power imbalance between men and women), it is important to study gender in relation to sexual health behaviors. Indeed, the limited research on this topic suggests that the association between sexual abuse and adult sexual behavior differs by gender (e.g., Futterman, Hein, Reuben, Dell, & Shaffer, 1993; Mason, Zimmerman, & Evans, 1998; Zierler et al., 1991). It is possible that gender interacts with abuse characteristics to lead to different outcomes for males and females, an idea which is supported by research on the psychological sequelae of sexual abuse. For example, in a meta-analysis, Rind et al. (1998) found that whether or not the sexual abuse experience was consensual was associated with later psychological adjustment for men, but not for women. Few studies have investigated the effects of the interaction of gender and abuse characteristic on later sexual behavior. Overall, previous studies investigating the association between abuse characteristics and later sexual behavior have tended to use small samples, or included only males or only females, thus precluding gender comparisons.
The primary purpose of this study was to determine whether use of force and type of sexual act was associated with sexual risk behavior in a group of patients receiving outpatient care from a sexually transmitted disease (STD) clinic. Based on previous research, we hypothesized that: (1) the use of force; and (2) sexual abuse involving penetration would be associated with greater sexual risk behavior. The secondary purpose of this study was to determine whether the effects of abuse characteristics on adult sexual behavior differed by gender.
Method
Participants
Participants were men and women attending a public STD clinic in upstate New York. All had been screened for possible inclusion in a randomized controlled trial (RCT) evaluating several different sexual risk reduction programs. Screening criteria for the RCT included: age 18 or older; not HIV positive; and sexual behavior (e.g., unprotected sex, multiple partners) that put them at risk for contracting an STD in the past 3 months. This study used baseline data from the RCT, prior to the receipt of the interventions. Baseline data were available from 1265 eligible participants. Data from participants who refused to answer sexual abuse (n=12) or demographic (n=1) questions, were inconsistent in reporting their sexual behavior (n=5), were outliers on sexual behavior data (n=30; defined as having a studentized deleted residual >4), or were recruited in error (n=1) were eliminated. Outliers on sexual behavior data were excluded because these individuals likely were members of an extremely high-risk population that merits separate investigation (Wegener & Fabrigar, 2000).
Overall, the sample was 46% female (n=557), 65% African American (n=785), and 24% Caucasian (n=294). The majority of participants were unemployed (n=620; 51%), had a high school education or less (n=762; 63%), and had a household income of less than $15,000 per year (n=686; 57%). Most participants were single (never married; n=958; 79%); 75 participants (6%) were married, and 183 (15%) were divorced, separated, or widowed. Participants were, on average, 29.2 years of age (SD=9.7). Among women, 504 (90%) reported having sex with only men in the past 3 months; 53 (10%) reported having sex with both men and women. Among men, 612 (93%) reported having sex with only women in the past 3 months; 31 (5%) reported having sex with only men; and 15 (2%) reported having sex with both men and women in the past 3 months.
Procedure
Patients who registered for a clinic visit were invited to a private exam room by a trained research assistant (RA), and were asked to answer a series of brief screening questions. The RA explained the study to patients who met eligibility criteria and obtained informed consent. Participants then completed a 45-minute, Audio Computer-Assisted Self-Interview (ACASI) that included measures of demographic characteristics, health behaviors and beliefs, and psychosocial functioning, as well as questions about childhood sexual experiences and current sexual behavior. ACASI was used because it optimizes participant privacy (improving data quality) while allowing low-literacy persons to participate (Schroder, Carey, & Vanable, 2003). For the present study, we used data from measures of childhood/adolescent sexual abuse and sexual behavior. After their clinic exam and counseling, participants were paid $20 to compensate them for their time. All procedures were approved by the IRBs of the participating institutions.
Measures
Childhood/adolescent sexual abuse
Three items, adapted from Finkelhor’s (1979) longer survey of childhood sexual experiences, were used to assess sexual abuse (see Appendix A).1 Participants who reported any contact sexual experiences (including kissing, fondling, giving oral sex, receiving oral sex, vaginal sex, or anal sex) (1) before age 13 with someone 5 or more years older or (2) between ages 13 and 16 with someone 10 or more years older, and those who reported (3) any contact sexual experience before age 17 involving force or coercion, were classified as sexually abused; all other participants were classified as not sexually abused. Those who were sexually abused were further categorized according to whether the abuse involved force and/or penetration. Participants who reported a sexual experience before age 17 involving force or coercion were considered to have experienced sexual abuse with force. Sexually abused participants who reported any oral, vaginal, or anal sex were considered to have experienced sexual abuse with penetration. A single, four level categorical variable was created to examine the impact of different abuse characteristics on sexual risk behavior: (1) no sexual abuse; (2) sexual abuse without force or penetration; (3) sexual abuse with penetration but without force; and (4) sexual abuse with both force and penetration. Too few participants reported sexual abuse with force and without penetration (n=39, 5%) to include a sexual abuse with force only category.
Current sexual behavior
The sexual risk behavior items were developed and tested in previous studies (Carey et al., 1997, 2000, 2004). Participants were asked to report: the number of male and female sexual partners they had in their lifetime and in the past 3 months; the number of times they exchanged sex for money or drugs (lifetime); and the number of times they had been treated for an STD (lifetime).
The frequency of unprotected sex was also investigated. Participants were asked to report the number of times in the past 3 months that they had vaginal and anal sex with and without a condom with their: (1) steady partner; (2) other male partners; and (3) other female partners. Responses to these items were used to calculate the absolute number and the proportion (number of unprotected sex episodes/number of protected and unprotected sex episodes) of unprotected sex episodes in the past 3 months.
Table 1Sexual abuse characteristics by genderMen (n=643)Women (n=534)Total (n=1177)n% of menn% of womenn% of totalNo sexual abuse227351823440935Sexual abuse without force and without penetration10016591115914Sexual abuse with penetration only (no force)208321052031327Sexual abuse with both force and penetration108171883529625Table 2Demographic characteristics of sexual abuse groups formed by force and penetrationNo Sexual Abusea (n=409)Sexual Abuse (no force or penetration)b (n=159)Sexual Abuse (penetration)c (n=313)Sexual Abuse (force and penetration)d (n=296)n%n%n%n%Sex (male)227c,d56100d63208a,d66108a,b,c36Race (minority)269b,c,d66120a,c75279a,b,d89228a,c77Education (high school or less)212b,c,d52100a,c63244a,b,d78191a,c65MSDMSDMSDMSDAge (in years)28.4d9.628.79.529.29.830.5a9.7ap < .05, compared to No Sexual Abuse.bp < .05, compared to Sexual Abuse, No Force, No Penetration.cp < .05, compared to Sexual Abuse, No Force, Penetration.dp < .05, compared to Sexual Abuse, Force, Penetration.
Statistical analyses
Analyses of variance (ANOVAs) were used to determine whether the four categories of sexual abuse (no sexual abuse; sexual abuse without force or penetration; sexual abuse with penetration; and sexual abuse with both force and penetration) were associated with later risky sexual behavior. If there was a significant overall effect of sexual abuse, Tukey tests were conducted to determine specifically which groups differed. Demographic variables that differed between groups were controlled for in these analyses. Thus, the ANOVAs included: (1) demographic covariates and (2) a main effect of sexual abuse. Continuous outcome variables that were not normally distributed (i.e., the number of lifetime partners, the number of partners in the past 3 months, the number of episodes of unprotected sex in the past 3 months, the number of times participants exchanged sex for money or drugs, and the number of previous STD diagnoses) were transformed using a log10 of (x+1) transformation (Tabachnick & Fidell, 2001). Unless otherwise stated, analyses associated with these variables used the log transformation.
Exploratory analyses were conducted to investigate whether gender moderated the relations between the sexual abuse characteristics and later sexual behavior. ANOVAs were conducted including demographic covariates, a main effect of abuse, and the interaction of abuse and gender.
Results
Of the 1216 patients who completed the survey, 66% reported childhood/adolescent sexual abuse (n=807). Of these 807 participants who met criteria for sexual abuse, 159 (20%) reported sexual abuse without force and without penetration, 313 (39%) reported sexual abuse with penetration, 39 (5%) reported sexual abuse with force and without penetration, and 296 (37%) reported sexual abuse with both force and penetration. Because few participants reported sexual abuse with force but without penetration, those participants were excluded from the analyses, leaving a final sample size of N=1177. Sexual abuse characteristics by gender are reported in Table 1.
Table 3Sexual risk behaviors of participants who reported sexual abuse with force, sexual abuse without force, and no sexual abuse (raw data)No Sexual Abusea (n=409)Sexual Abuse (no force or penetration)b (n=159)Sexual Abuse (penetration)c (n=313)Sexual Abuse (force and penetration)d (n=296)MSDMSDMSDMSDSexual partners (number, lifetime)31.7c,d80.927.6c,d28.260.1a,b211.564.2a,b172.4Sexual partners (number, past 3 months)2.5c,d2.12.72.23.2a2.73.5a4.0Unprotected sex (number of events, past 3 months)15.3c,d24.317.026.820.7a30.122.8a38.2Unprotected sex (proportion, past 3 months)0.680.320.640.330.700.300.670.33Exchanged sex for money or drugs (number, lifetime)4.9c,d55.95.6d42.06.5a,d42.417.6a,b,c89.6STD diagnoses (number, lifetime)2.4c,d3.02.6c,d3.23.4a,b3.64.0a,b4.1ap < .05, compared to No Sexual Abuse.bp < .05, compared to Sexual Abuse, No Force, No Penetration.cp < .05, compared to Sexual Abuse, No Force, Penetration.dp < .05, compared to Sexual Abuse, Force, Penetration.
Demographic differences
Preliminary analyses examined whether any demographic variables were associated with the sexual abuse characteristics (see Table 2). Sexual abuse was significantly associated with sex, race, education, and current age. Thus, for example, participants reporting a history of sexual abuse were more likely to be less well-educated and more likely to report a minority racial/ethnic identity than nonabused participants. Importantly, sexual abuse involving force and penetration was more likely to be reported by women than by men. All pairwise comparisons for the demographic characteristics are presented in Table 2. Because of these associations, sex, race, education, and current age were used as covariates in subsequent analyses.
Relation between sexual abuse characteristics and sexual behavior
After controlling for relevant demographic covariates, sexual abuse was significantly associated with the number of lifetime partners, F(3, 1160)=21.08, p < .0001, the number of episodes of unprotected sex in the past 3 months, F(3, 1169)=3.97, p < .01, the number of partners in the past 3 months, F(3, 1169)=7.28, p < .0001, the number of times sex was traded, F(3, 1153)=14.23, p < .0001, and the number of previous STD diagnoses, F(3, 1169)=8.01, p < .0001 (see Table 3). Sexual abuse was not significantly associated with the proportion of unprotected sex episodes in the past 3 months.
Follow-up Tukey tests showed that, compared to those who were sexually abused with penetration, those who were not sexually abused had significantly fewer: (1) lifetime sexual partners (Cohen’s d=.40); (2) partners in the past 3 months (d=.23); (3) episodes of unprotected sex in the past 3 months (d=.19); (4) episodes of sex trading (d=.31); and (5) previous STD diagnoses (d=.22; all ps < .05). Similarly, compared to those who were sexually abused with both force and penetration, those who were not sexually abused had significantly fewer: (1) lifetime sexual partners (d=.49); (2) partners in the past 3 months (d=.29); (3) episodes of unprotected sex in the past 3 months (d=.21); (4) episodes of sex trading (d=.46); and (5) previous STD diagnoses (d=.34; all ps < .05).
In addition, compared to those who were sexually abused with penetration, those who experienced sexual abuse without force and without penetration had significantly fewer lifetime sexual partners (d=.32) and fewer previous STD diagnoses (d=.17; both ps < .05). Similarly, compared to those who were sexually abused with both force and penetration, those who experienced sexual abuse without force and without penetration had significantly fewer: (1) lifetime sexual partners (d=.34); (2) episodes of sex trading (d=.29); and (3) previous STD diagnoses (d=.30; all ps < .05). Finally, those who were sexually abused with both force and penetration reported significantly more episodes of sex trading than those who were sexually abused with penetration (d=.29; p < .05).
Because sex trading likely leads to a greater number of sexual partners, episodes of unprotected sex, and STD diagnoses, follow-up analyses were conducted to determine whether penetration was still associated with the sexual behavior outcomes after controlling for sex trading. All effects remained significant after controlling for sex trading (all ps < .05).
Gender as a moderator of the relation between sexual abuse characteristics and sexual behavior
To determine whether gender moderated the relation between sexual abuse characteristics and sexual behavior, gender-by-sexual abuse interactions were included in the ANOVAs. Relevant demographic covariates were included.
The gender-by-sexual abuse interaction was significantly associated with the number of episodes of sex trading, F(3, 1150)=3.56, p < .05. Analyses of simple main effects revealed that, for both women and men, those who were sexually abused with force and penetration reported significantly more episodes of sex trading than those who were not abused, or than those who were abused without force and without penetration. However, for women only, those who were sexually abused with penetration reported significantly more episodes of sex trading than those who were not abused (all ps < .05; see Fig. 1).Fig. 1The effect of the interaction of gender and sexual abuse status on the number of episodes of sex trading
Discussion
This study investigated whether characteristics of childhood and adolescent sexual abuse (i.e., force and type of sexual activity) were related to adult sexual risk behavior, and whether these associations differed by gender. This research benefited from several methodologic strengths. For example, we sampled a large group of both men and women who reported sexual abuse; this large and diverse sample allowed exploration of two sexual abuse characteristics and gender differences. We also used psychometrically sound measures and a computer-administered survey, known to result in higher, and presumably more candid, rates of socially stigmatized and sensitive behaviors (Schroder et al., 2003). These strengths increase confidence in the validity and generalizability of the results.
A key set of findings was that (1) sexual abuse with penetration as well as (2) sexual abuse with force and penetration were both related to higher rates of adult sexual behavior compared to (3) sexual abuse without force and without penetration and (4) no sexual abuse. This pattern of findings corroborates results from research investigating the mental health sequelae of sexual abuse, which indicate that force (e.g., Bulik, Prescott, & Kendler, 2001; Rind et al., 1998; Rodriguez, Ryan, Kemp, & Foy, 1997) and penetration (e.g., Briere & Elliott, 2003; Bulik et al., 2001) are associated with worse psychological outcomes; the current research also adds to the limited body of research suggesting a relation between force and penetration, and later sexual behavior (e.g., Cinq-Mars et al., 2003; Fergusson et al., 1997). The effect sizes for the association between sexual abuse and later sexual behavior were small to medium, indicating that other variables besides sexual abuse account for a large portion of the variance in adult sexual behavior. The latter finding is consistent with the idea that adult sexual behavior is influenced by multiple environmental as well as individual factors (Smith & Subramanian, 2006).
Penetration by itself (i.e., without force) and penetration in combination with force were associated with increased sexual risk behavior relative to those who were abused without force and without penetration, and those who were not abused. The sole difference between the penetration only and the penetration plus force groups involved sex trading, where those who experienced sexual abuse with force and penetration reported engaging in a greater frequency of sex trading, relative to those who experienced sexual abuse with penetration and no force. However, this finding was qualified by a significant gender-by-abuse interaction. Because only a very small number of participants reported sexual abuse with force but without penetration (i.e., forced kissing or fondling), we were unable to investigate the impact of force only.
A somewhat unexpected finding was that the group that reported sexual abuse without force and without penetration did not differ significantly from the nonabused group on any of the sexual behavior outcomes. Future investigation of the relation between sexual abuse and adult sexual behavior might find it fruitful to conduct more fine-grained assessments of the sexual experiences that involve only large age differentials to determine how these experiences are perceived by both men and women, and whether such experiences influence subsequent sexual behavior.
It may seem counter-intuitive that individuals who experienced more severe sexual abuse (i.e., sexual abuse with force or penetration) would engage in more sexual experiences than those who experienced less severe sexual abuse; that is, one might expect individuals who experienced severe sexual abuse to avoid sex because of the negative consequences. However, relative to individuals who experienced less severe sexual abuse, individuals who experienced more severe sexual abuse may use different strategies to cope with their sexual abuse experience(s). Thus, for both men and women, those who experienced more severe forms of sexual abuse may use alcohol or drugs to cope with the sexual abuse, which, in turn, may lead to the exchange of sex for money or drugs, and/or to a greater number of sexual partners and episodes of unprotected sex. In addition, alcohol and other drug use may lead to a greater number of sexual partners and episodes of unprotected sex due to decreased ability to attend to distal concerns, such as acquiring an STD when intoxicated or high (cf. alcohol myopia; Steele & Josephs, 1990). Indeed, we have reported previously that substance use is an important mediator of the relation between sexual abuse and risky sexual behavior (Senn, Carey, Vanable, Coury-Doniger, & Urban, 2006); future research should explore whether substance use and other potential mediators operate differently for those who experienced different severity levels of sexual abuse.
An alternative explanation for the association between more severe sexual abuse and greater adult sexual risk behavior is Finkelhor and Browne’s (1985) traumagenic dynamics model. This model proposes that one consequence of sexual abuse is traumatic sexualization, in which a child develops maladaptive scripts for sexual behavior, when rewarded for sexual behavior by affection. More severe sexual abuse, such as sexual abuse involving force or penetration, may lead to greater traumatic sexualization. As adults, those who experienced traumatic sexualization may believe sex is necessary to obtain affection from others. Thus, traumatic sexualization may lead to, for example, earlier consensual sex or a greater number of sexual partners (e.g., Cinq-Mars et al., 2003; Fergusson et al., 1997).
Another consequence of sexual abuse, according to Finkelhor and Browne (1985), is powerlessness, in which a child learns that his or her needs or requests are ignored by others; the child thus fails to develop self-efficacy to stop unwanted sexual advances. More severe sexual abuse, particularly sexual abuse involving force or penetration, may lead to greater feelings of powerlessness. Perhaps because they lack the interpersonal skills or the self-efficacy to stop unwanted sexual advances, these individuals may be less likely to refuse intercourse with aggressive partners, resulting in more sexual partners. Powerlessness could help explain findings linking more severe sexual abuse to more adult sexual risk behavior (e.g., Cinq-Mars et al., 2003; Fergussion et al., 1997). In this regard, Kallstrom-Fuqua, Weston, and Marshall (2004) found that sexual abuse severity had an indirect effect on maladaptive relationships, mediated through powerlessness; thus, having many sexual partners could be a consequence of difficulty forming close relationships. Further research is needed to examine whether the sexual abuse characteristics investigated in this study are associated with Finkelhor and Browne’s (1985) traumagenic dynamics.
Another finding yielded by this study is that abuse characteristics were associated with different outcomes for men and women. For men, only abuse with both force and penetration was associated with a greater frequency of sex trading, whereas for women, abuse with penetration, regardless of whether or not force was involved, was associated with more sex trading. In the current cultural context, young males may view sex with an older woman as masculine and mature, rather than abusive. Males, therefore, may tend to view only experiences involving force or coercion as abusive. Women, on the other hand, may be more likely to view intercourse with an older individual as abusive, regardless of whether or not force was involved. This idea is supported by meta-analytic findings that boys’ reactions to sexual abuse were less negative than were girls’ reactions (Rind et al., 1998). Different perceptions of whether or not the experience was abusive may lead to the use of different coping strategies.
These results should be interpreted mindful of the limitations of the study. One limitation involved the brevity of the sexual abuse assessment. Use of a brief survey allowed us to obtain a large and diverse sample, but limited the richness of the data collected. The survey did not assess other aspects of sexual abuse, such as duration, frequency, and relationship to the perpetrator, which may be important correlates of later outcomes (e.g., Banyard & Williams, 1996; Briere & Elliott, 2003). In addition, these brief questions did not allow for assessment of reactions to the sexual experience; many participants, especially those who did not report force or coercion, may not have considered themselves sexually abused, but may have viewed these sexual experiences as inconsequential or even consensual. Future research, involving mixed qualitative and quantitative methods, might help to elucidate the empirical relations observed in the current sample.
A second limitation involves the correlational nature of the data. Clearly, such data limit causal inferences, although given the temporal sequence of childhood/adolescent sexual abuse and adult sexual behavior, the limits may be less concerning in this context. Nonetheless, we acknowledge that unexplored variables that are related to both sexual abuse and greater sexual risk behavior (e.g., more adverse childhood experiences; Dong, Anda, Dube, Giles, & Felitti, 2003) should be included in future investigations of the sexual abuse–risky sex relation.
It is important to recognize that participants in this study were recruited from a sexually transmitted disease clinic, and were included because they were currently engaging in sexual behavior that conferred risk for contracting an STD. The rates of sexual abuse reported in this sample were considerably higher than rates (i.e., 15% for men and 30% for women) reported in national samples (Briere & Elliott, 2003; Finkelhor, Hotaling, Lewis, & Smith, 1990; Vogeltanz et al., 1999). In addition to engaging in sexual risk behavior, patients attending STD clinics may differ from the general population in other important ways as well; for example, patients attending STD clinics often report extremely high rates of alcohol and drug use (Cook et al., 2006). Due to the nature of the sample, these results of the present study may not generalize to other populations.
These results have implications for both practice and research. Regarding public health and clinical practice, they suggest that a thorough sexual health assessment should include inquiry about the nature of the sexual abuse, particularly whether force was involved and what type of sexual act occurred. Given the likely impact of sexual abuse on sexual risk behavior (as well as other health outcomes), we recommend a more comprehensive approach to sexual health assessment, education, counseling, and/or therapy. Indeed, these findings highlight the need to develop interventions tailored to the unique needs of persons with a history of sexual abuse to promote (and restore) sexual health and reduce sexual risk. With respect to research, these findings raise many questions about the conditions under which sexual abuse impairs healthy sexual development and expression, and about the mechanisms by which sexual abuse influences sexual development, behavior, and adjustment. This work will require sophisticated methods and analyses to overcome the limitations of what is inherently retrospective and correlational research.

sexual behavior
hiv
sexually transmitted disease
child/adolescent sexual abuse


Digestibility of resistant starch containing preparations using two in vitro models

Background Resistant starch (RS) is known for potential health benefits in the human colon. To investigate these positive effects it is important to be able to predict the amount, and the structure of starch reaching the large intestine.
Introduction
Resistant Starch (RS) is defined as starch that is not absorbed in the small intestine of humans. Three different types of RS were defined by Englyst et al. [1]. Type 1 is defined as physically inaccessible starch, type 2 (RS2) as native starch granules and type 3 (RS3) as retrograded starch. More recently, a fourth type of RS has been classified, comprising chemically modified starches [2, 3]. RS is claimed to be a good substrate for colonic fermentation and to be beneficial because of its high ratio of butyrate production, which may play a major role in the prevention of colon cancer, as shown in several studies on animal models [4, 5]. The fermentation products from RS are known to lower the pH in the colon which leads to less production, and/or accumulation of potentially harmful by-products of protein fermentation, for example, ammonia or phenols which may promote tumorigenesis [6]. To estimate potential health benefits of RS it is important to be able to predict its behavior in the human gastrointestinal tract, in particular the amount and the structure of starch reaching the large intestine. The digestion of food and absorption of nutrients are spatiotemporal and dynamic processes involving complex enzymatic systems and transport reactions. Thus, the simulation of all these biochemical and physiological events in a single model is illusive. Nevertheless, several in vitro digestion methods, from basic batch systems to sophisticated dynamic models have been developed in order to quantify digestibility of food [7–9]. A realistic approach implies a well-defined system that takes into account the specific contributions of oral, gastric and intestinal digestion. Advantages of using in vitro instead of in vivo models are low costs, relatively easy performance, no limitations by ethical constraints, and the possibility to compare different substrates when applying standardized conditions. Therefore, the aim of this study was to compare a rather simple and a more sophisticated in vitro model as well as the Megazyme RS method to determine the indigestible fractions of two RS preparations containing RS2 and RS3. The digestion residues obtained by the two models were compared and characterized. Furthermore, the RS3 fractions were compared with ileostomy effluents obtained in an in vivo study [10].
Materials and methods
Substrates
The RS3 containing carbohydrate source, C⋆Actistar®, is a retrograded long chain maltodextrin product obtained after partial enzymatic hydrolysis, and subsequent retrogradation of tapioca starch (RTmd), produced according to United States Patent 6 043 229 [11] and obtained from Cerestar-Cargill (Vilvoorde, Belgium). Physico-chemical characteristics of RTmd were described recently by Pohu [12]. The RS2 containing carbohydrate source is native high amylose maize (HAM) starch and was obtained from Cerestar International (Neuilly-sur-Seine, France).
Batch in vitro digestion model
The batch model used is a three step incubation at 37°C simulating the digestion in mouth, stomach and small intestine. The method was carried out as described by Lebet et al. [7] and modified by Jörger [13]. A sample of 30 g substrate was suspended in 500 ml phosphate buffer (20 mM, pH 6.9, Na2HPO4 1.42 g/l, KH2PO4 1.36 g/l, NaCl 0.58 g/l), and incubated stepwise with (a) 0.5 ml human salivary α-amylase solution (Sigma A1031, Buchs, CH, 10 mg/ml in CaCl2 1 mM) at pH 6.9 for 15 min, (b) 1.25 ml porcine pepsin suspension (Sigma P7012, 1 mg/ml in NaCl 9 g/l) at pH 2.0 for 30 min and (c) 10 ml porcine pancreatin (Sigma P7545, 0.5 mg/ml in CaCl2 25 mM) at pH 6.9 for 3 h in the presence of 12 g bovine bile (Sigma B8381). Degradation products were removed by dialysis (Servapor 44146, Serva Feinbiochemica GmbH & Co., Heidelberg, Germany; cut-off 12–14 kDa) overnight under continuous movements against running deionized water <20°C. The retentate was freeze-dried. Based on total starch (TS) determinations in the starting materials and digestion residues, the amount of indigestible starch was calculated.
Dynamic in vitro digestion model (TIM-1)
The dynamic model used in this study has been described by Minekus et al. [8]. The model comprises four serial compartments simulating stomach, duodenum, jejunum and ileum. The in vitro digestion was performed for 6 h at 37°C. A mixture of 60 g substrate, 180 g electrolyte solution (NaCl 5 g/l, KCl 0.6 g/l, CaCl2·2H2O 0.3 g/l, NaHCO3 0.6 g/l), 60 g water, 5 g pepsin solution (Sigma P7012, 0.28 g/l in solution A: NaCl 3.1 g/l, KCl 1.1 g/l, CaCl2·2H2O 0.15 g/l, NaHCO3 7.1 g/l) and 5 g lipase solution (Rhizopus lipase, Amano Pharmaceutical Co. F-AP 15, Ltd. Japan, 0.25 g/l in solution A) were introduced into the gastric compartment. Computer controlled peristaltic valve pumps controlled meal transit through the individual compartments. The pH value was computer monitored by adding HCl (1 M) or NaHCO3 (1 M), respectively. In the stomach the values were preset to pH 4.5, 2.8, 1.8, 1.7 and 1.5 at 0, 20, 40, 60 and 90 min, respectively. In the small intestine, the pH was maintained at 6.5, 6.8 and 7.2 in the duodenum, jejunum and ileum, respectively. About 1 ml trypsin solution (Sigma T4665, 2 g/l in solution A) was added to the duodenum at the beginning of the experiment. Secretions of porcine bile 4 g/100 g in water (Sigma B8631) and pancreatic solution 7 g/100 g in water (Pancrex-V powder, Paines & Byrne, Greenford, UK) entered the duodenal compartment at 0.5 and 0.25 ml/min, respectively. The absorption of water and digestive products from the jejunal and ileal compartments was simulated using hollow-fiber devices (cut-off 5–10 kDa). Ileal effluents (indigestible fraction) were collected after 2, 4 and 6 h, pooled and freeze-dried. Substrate remaining in the jejunum and ileum at the end of the experiment was considered to be indigestible as well and was therefore mixed with the ileal effluent pool. TS determinations of the starting materials, the digestion residues and the remaining substrate in the model after the experiment were carried out. Starch degradation products (up to DP 7) were quantified in dialysates by high-performance anion-exchange chromatography with pulsed amperometric detection (HPAEC-PAD) in a BioLC System (Dionex Corp., Sunnyvale CA, USA) using a Carbo-Pac PA1 column and applying a sodium acetate gradient (unpublished, internal method). TS and oligosaccharide quantifications were recalculated as glucose content. The recovered glucose after the experiment (in the digestible and indigestible residues) was assumed as 100%, of which the indigestible fraction is expressed as a fraction.
Characterization
Both RS preparations were characterized before and after digestion. Additionally, freeze dried RTmd fractions from an ileostomy study feeding RTmd were pooled (7 subjects) and used for characterization analyses [10].
TS was determined using the Megazyme TS assay kit (Megazyme, Co. Wicklow, Ireland) [14]. In brief, starch was hydrolyzed in two phases. In phase 1, starch was pre-treated with dimethyl-sulfoxide (DMSO), totally solubilized and partially hydrolyzed with α-amylase. In phase 2, dextrins were quantitatively hydrolyzed to glucose with amyloglucosidase (AMG). Glucose was subsequently determined enzymatically using the Hexokinase/Glucose-6-phosphate-dehydrogenase assay according to Boehringer [15].
The RS fraction was determined using the Megazyme RS assay kit (Megazyme, Co. Wicklow, Ireland) [16]. The samples were incubated in a shaking water bath with pancreatic α-amylase and AMG at 37°C for 16 h, during which time non-resistant starch was solubilized and hydrolyzed to glucose. RS was recovered as a pellet after centrifugation, which was dissolved by stirring in KOH 2 M and quantitatively hydrolyzed to glucose with AMG [16]. Glucose was determined as described above.
Protein was determined as sum of amino acids after acid hydrolysis and ion-exchange chromatography with post-column ninhydrin detection [17].
Wide-angle X-Ray powder diffraction (X-Ray) measurements were performed using a Scintag PADX Diffractometer (PANAlytical, Almelo, NL) operating at 45 mA and 40 kV at an angular range of 2θ from 1 to 40° with a step size of 0.03°. Counting time was 5 s on each step.
Differential scanning calorimetry (DSC) measurements were performed using the Thermal Analyst system 2000 (DSC 2910, TA Instument Ltd, Newcastle, UK). Samples at a starch:water ratio of 1:4 were prepared and heated from 4°C to 200°C at 10°C/min, thereafter the samples were cooled at 20°C/min to 4°C and heated again at the same heating rate. All the DSC results were evaluated from the mean of three separate determinations for each sample, unless stated otherwise.
Statistical analysis
Statistical analyses were carried out using SPSS, version 12.0.1 for Windows (one-way ANOVA and Post-Hoc Tukey). Differences were considered to be significant at P < 0.05.
Results
Composition and digestibility of RS containing preparations
In Table 1 the average TS contents and indigestible starch fractions of RTmd and HAM are shown. All data are mean values of at least five repetitions. Data resulting from the dynamic and the batch model are based on the TS content before and after digestion. Both preparations contain identical amounts of TS. The two in vitro digestion models as well as the Megazyme RS method which is accepted as the official AOAC method for RS determination, led to similar amounts of indigestible RS3 fractions. Digestibility of RS2 was similar using the dynamic model, and the Megazyme RS method, whereas the batch model led to a lower digestibility. Expressing the RS results obtained by the Megayzme RS method based on substrate fresh weight (instead of g/100 g TS as shown in Table 1) yielded to 50.2 ± 2.6, and 45.3 ± 4.1 g/100 g for RTmd and HAM, respectively. This is very well in accordance with respectively, 48.3 ± 2.8 and 46.3 ± 3.9 g/100 g found in a collaborative study published earlier by McCleary et al. [16]. Standard deviations after HAM digestion were found to be higher compared to RTmd digestion. The batch system showed a better reproducibility than the dynamic model and Megazyme RS method for both substrates.
Table 1Average total starch (TS) content of retrograded tapioca maltodextrins (RTmd) and high amylose maize starch (HAM) and their indigestible starch fractions obtained by dynamic digestion, batch digestion and the Megazyme resistant starch (RS) method (mean values ± SD)SampleTS (g/100 g dm)Digestion methodIndigestible starch fraction (g/100 g TS dm)RTmd94.3 ± 1.8 (n = 17)Dynamic59.6 ± 2.1 (n = 6)a,bBatch60.6 ± 0.9 (n = 5)aMegazyme57.7 ± 2.9 (n = 12)bHAM94.3 ± 1.1 (n = 7)Dynamic57.5 ± 4.7 (n = 5)dBatch65.8 ± 3.5 (n = 10)cMegazyme54.8 ± 5.0 (n = 17)dMeans with the same letters are not significantly different (Tukey P < 0.05)
Composition of digestion residues
In Table 2 the average TS and RS contents of RTmd and HAM digestion residues are shown. TS quantifications of in vitro digestion residues were carried out after each single experiment in duplicate. In contrast, RS contents as well as TS in ileostomy effluents were measured in the pooled fractions only. TS contents in digestion residues turned out to be lower than in corresponding starting materials (Table 1), which are due to additional enzymes and bile added during digestion. Moreover, residues obtained from the batch digestion contained more starch than those from the dynamic model. The digestion residues of RTmd and HAM obtained from the dynamic model contained 1.5 g protein/100 g dm and 1.8 g protein/100 g dm, respectively, whereas in the batch digestion residues only 0.6 g protein/100 g dm and 1.2 g protein/100 g dm were determined. Bile contains large amounts of glycine that was correspondingly found in higher amounts in the dynamically digested residues (0.2 and 0.3 g/100 g dm for RTmd and HAM, respectively) compared to the batch digested residues (0.3 and 0.4 g/100 g dm for RTmd and HAM, respectively). Also other amino acids like asparagine, glutamine, alanine, proline, and leucine were found in higher amounts in dynamically digested preparations. The lower amount of TS found in the ileal effluent pool compared to the in vitro digested samples is due to the dilution by additional endogenous and exogenous material such as diet derived protein, dietary fiber and fat.
Table 2Total starch (TS) and resistant starch (RS) contents of in vitro and in vivo digestion residues of retrograded tapioca maltodextrins (RTmd) and high amylose maize starch (HAM) (mean values ± SD)SampleTS (g/100 g dm)RS (g/100 g dm)RTmd dynamic72.4 ± 3.7 (n = 12)36.4 ± 1.0 (n = 2)RTmd batch88.6 ± 0.6 (n = 10)61.4 ± 1.2 (n = 3)RTmd in vivo48.4 ± 0.0 (n = 2)31.3 ± 1.1 (n = 2)HAM dynamic74.9 ± 1.7 (n = 10)27.6 ± 2.0 (n = 2)HAM batch80.9 ± 2.6 (n = 12)35.7 ± 0.7 (n = 3)
It is expected that RS values close to 100% are found in the in vivo as well as the in vitro digestion residues. As shown in Table 2 lower amounts of RS (28–62%) were found in the digestion residues. This can be explained by the fact that the digestion method carried out prior to the analytical RS determination has an influence on the starch structures leading to less resistant starch. Therefore, analysing RS in digestion residues may be interpreted as characterization method, indicating the highly resistant fraction. Different amounts of RS were found because of additional non-starch material present in the samples as described above. Calculating RS recoveries based on TS led to 50 g/100 g TS for the dynamically digested RTmd fractions, whereas after batch and in vivo digestion similar amounts (69 and 65 g/100 g TS, respectively) were found. In contrast, clearly lower RS amounts were found in both HAM digestion residues (37 and 44 g/100 g) after dynamic and batch digestion, respectively.
In Fig. 1 the absorption of digestion products from the jejunum and ileum compartments during the dynamic experiment can be followed. The main digestion products found were maltose and maltotriose despite the fact that larger molecules are able to pass the hollow fiber devices as well. Starch digestion products up to DP3 were found when RTmd was being digested, whereas after HAM digestion minor amounts of maltotetraose (less than 0.1% of total digestible glucose) were detected as well. The kinetics of RTmd and HAM digestion differed considerably. The digestible fraction of RTmd was degraded completely after 4 h, whereas degradation of HAM still continued after 4 h. The lower amounts of degradation products collected during the first 4 h from HAM digestion, and the higher total amounts separated from the ileum compartment show that HAM under these experimental conditions is being digested more slowly compared to RTmd. The enzyme used for starch digestion in the dynamic model is a α-amylase, therefore maltose is theoretically expected to be the smallest degradation product. As can be seen in Fig. 1, glucose was found as well. Glucose could originate from added compounds during the dynamic digestion experiment, such as bile and enzymes. Moreover, a small contamination of α-amylase by AMG or α-amylase containing small amounts of side-activity cannot be excluded. The total amount of starch degradation products absorbed during the dynamic in vitro digestion experiment is slightly higher for HAM compared to RTmd. This is in accordance with a somewhat lower non-significant indigestible residue of HAM compared to RTmd as shown in Table 1.
Fig. 1Digestible starch degradation products (up to DP3) of retrograded tapioca maltodextrins (RTmd), and high amylose maize starch (HAM) recovered from the jejunum (a) and the ileum (b) compartments
Characterization of digestion residues
X-ray diffraction
X-ray diffraction patterns of RTmd and its dynamic, batch and in vivo digestion residues are presented in Fig. 2. RTmd and indigestible RTmd fractions all led to a typical A-type pattern. However, the diffraction patterns, with exception of RTmd dynamically digested, exhibited an additional peak at θ2 = 20° which can be interpreted as V-form due to the presence of amylose–lipid complexes. RTmd and RTmd batch digested residues were very similar concerning their crystallinity. The only differences were the peaks at 2θ = 20°, and 2θ = 23°, which were slightly lower and higher, respectively in the batch digested sample. In contrast to RTmd and its batch digested fraction, dynamically digested RTmd showed no peak at 2θ = 27°C and no pronounced double peak at 2θ = 17° and 2θ = 18° (both typical for A-type structure), which indicate a loss in crystallinity due to digestion. The in vivo digestion residue showed an additional peak at 2θ = 29°; this peak could be due to additional structures of proteins or lipids present in this sample.
Fig. 2X-ray diffraction patterns of retrograded tapioca maltodextrins (RTmd) and their digestion residues
HAM containing samples led to lower crystallinity compared to RTmd (Fig. 3), which correspond to Gerard et al. [18], showing that high amylose maize starches have low crystallinity. HAM and its digestion residues led to B-type pattern, although the peak at 2θ = 20° observed in HAM and batch digested HAM indicated a mixture between B- and V-type which was described by Shi et al. [19] as well. Due to in vitro digestion of HAM and dynamically digestion of RTmd the peak θ2 = 26° disappeared which points to a loss in crystallinity. Similar as for RTmd (Fig. 2) the dynamic digestion led to higher changes in crystallinity compared to batch digestion.
Fig. 3X-ray diffraction patterns of high amylose maize starch (HAM) and their digestion residues
DSC
The thermal behavior of the substrate melting was studied using DSC measurements. The results from the first and second heating are shown in Table 3. During the first heating, endothermic peak temperatures (Tp) turned out to be slightly lower for RS2 compared to RS3. The peak ranges within the RTmd and HAM containing preparations were found to be similar with exception of a slightly narrower peak of in vivo digested RTmd. Enthalpies were found to be lower for HAM containing preparations compared to RTmd containing preparations. The melting transition of RTmd was separated by an exothermic effect (not shown). Such a melting characteristic can be interpreted as partial melting (endothermic), followed by recrystallization (exothermic) and final melting (endothermic) [20, 21]. This exothermic peak was not visible in the digestion residues, which indicates that due to digestion the fractions responsible for these rearrangements were removed. Within the RS3 fractions, in vivo digestion led to significantly lower enthalpies. Dynamic digestion of both preparations led to an exothermic peak when the sample was reheated (Table 3). This indicates that the reorganization of the crystalline structures takes place during the second heating. RTmd and its batch and in vivo digested fractions did not show any heat flow during the second heating (therefore not shown in Table 3), it can be interpreted that recrystallization was completed during cooling in these samples already. HAM containing samples, excluding the dynamically digested fraction, all led to an endothermic peak during reheating which indicates a reversible reconstruction of the amylose–lipid complexes [20].
Table 3Average results (n = 3) from differential scanning calorimetry (DSC) for retrograded tapioca maltodextrins (RTmd) and high amylose maize starch (HAM) and their digestion residues. T0: onset temperatures (°C), Tp: peak temperatures (°C), Tc: completion temperatures (°C), ΔH: transition enthalpy ± SD (J/g) (endothermic if nothing else stated)SampleT0(°C)Tp (°C)Tc (°C)ΔH (J/g)First heatingRTmd (n = 2)60.7112.8140.49.0 ± 1.1aRTmd dynamic58.4108.6132.49.1 ± 0.2aRTmd batch61.8109.1136.410.8 ± 2.0aRTmd in vivo58.4105.0123.55.2 ± 1.1bHAM61.896.9110.02.6 ± 0.3cHAM dynamic55.598.7127.04.2 ± 2.2cHAM batch (n = 2)59.991.5110.53.6 ± 0.7cSecond heatingRTmd dynamic79.787.9144.0*2.4 ± 0.4HAM60.088.2109.62.7 ± 0.9dHAM dynamic84.994.2146.1*2.8 ± 0.2dHAM batch59.883.2101.90.9 ± 0.0e*Exothermic, means with the same letters are not significantly different (Tukey P < 0.05)
Discussion
Digestibility of RS preparations
In vitro digestion models use a strictly standardized procedure based on an average human digestibility. Therefore standard deviations of in vitro experiments are expected to be low. In vitro obtained HAM fractions showed higher standard deviations compared to in vitro digested RTmd fractions. Possibly the molecular structures of HAM have been more sensitive to small differences in experimental conditions such as mechanical stress, temperature or pH between experiments.
RTmd in vitro digestion residues result in quantitatively similar RS fractions (Table 1) which are very well in accordance with 59 g/100 g found in vivo after feeding RTmd to ileostomy patients [10]. In contrast, in vitro digestion using HAM as a substrate led to different amounts of RS. These differences may be explained by methodological variations in the in vitro models used, suggesting that HAM was more affected by the experimental conditions. During the dynamic digestion experiment the substrate is exposed to the movements of the flexible walls [8], in the batch model the slurry is stirred [7], and in the Megazyme RS method the sample is shaken [16]. An effect of mechanical treatment on starch degradation of HAM but not of RTmd was shown by McCleary and Monaghan [22] before. They performed the Megazyme RS method comparing shaking and stirring. Stirring led to a higher digestibility of HAM, whereas RTmd did not show any differences. In the present study however, stirring applied in the batch model led to a lower digestibility compared to shaking as used in the Megazyme RS method. This shows that apart from mechanical forces, also other factors may have a significant impact on starch degradation. For example, different amounts and types of enzymes, their accessibilities to the substrate as well as the formation of the enzyme–substrate complexes could have a larger influence on starch degradation of HAM compared to RTmd using in vitro digestion models. Furthermore, the incubation time during the dynamic digestion is nearly twice as long compared to the batch digestion and over four times as long in the Megazyme RS method. As pointed out in Fig. 1, 99% of in vitro digestible RTmd fractions were degraded after 4 h, whereas only 86% of those of HAM were digested at this stage. If the dynamic digestion experiment would have been stopped after 4 h (the duration of the batch digestion experiment is 3.75 h), the remaining indigestible fraction of HAM would be identical to that obtained by the batch in vitro digestion. Whether a prolongation of the batch incubation would lead to HAM fractions similar to those obtained with the dynamic model, remains to be elucidated.
The analytical RS contents found in the dynamically digested residues was lower in both preparations when compared to the batch digested fractions (Table 2). This leads to the assumption that in the dynamic approach starch structures are attacked to a higher extent compared to the batch model. Nevertheless, the amount of TS recovered after digestion of RTmd was not affected, whereas the TS recovery of HAM possibly was influenced by the different amount of analytical RS present in the sample; the results strongly indicate that structural features play an important role in digestibility.
Structural aspects of the RS preparations
X-Ray diffraction
A mixture between A- and V-type structures for RTmd, and its in vivo digestion residues (Fig. 2) was found by Pohu [12] as well. The tightly packed A-type structure is known to be very heat stable. Shamai et al. [23] investigated RS3 fractions from high amylose maize, maize flour and wheat starch, respectively. They found that RS3 produced at low retrogradation temperatures of 40°C lead to B-type patterns, whereas incubation at 95°C produced a mixture of A- and V-type polymorphs. This is in contrast to the present study, where RS3 produced from long chain tapioca maltodextrins was found to consist of a mixture between A- and V-type crystal structures, even though rather low retrogradation temperatures of 52–54°C were applied [11]. This shows that the structural behavior of RS3 cannot be predicted without knowing the exact process parameters and these parameters are rarely disclosed, particularly in patents.
HAM led to a mixture of B- and V-type polymorphs, which is characteristic for native high amylose maize starch, as shown by several research groups [23–25]. The dynamically digested fraction did not show the V-type characteristic peak at 2θ = 20°. This peak is known to represent amylose–lipid complexes. It is possible that the extra-addition of lipase in the dynamic digestion model was able to degrade lipids present in HAM and RTmd to an extent where no complexation was possible anymore. During batch digestion no additional lipase was used since this enzyme is present in the pancreatin preparation. In earlier experiments it has been shown that the pH-optimum of the pancreatic lipase is approximatively 9 [26]. Therefore, the incubation at pH 6.9 in the batch model is expected to lead to a small lipid degradation only. This could explain that the peak at 2θ = 20° was only reduced during batch procedure, but disappeared using the dynamic digestion model. In vivo digested RTmd showed amylose–lipid complexes (Fig. 2) as well. However, it can not be stated whether the lipid degradation in the dynamic model was more efficient compared to in vivo digestion because diet-derived lipids led to a much higher lipid content before in vivo digestion (results not shown). The X-ray patterns of RTmd and HAM samples indicate that the molecules within the crystals are not packed in the same way which leads to different functional properties of HAM, and RTmd. Batch digestion of both preparations did not lead to a distinct change in crystallinity. However, in vivo digestion caused slightly broader, and dynamic digestion distinctly broader diffraction peaks, which indicate the presence of either imperfect or relatively small crystallites [27]. The latter could have occurred due to the mechanical stress which underlines that the dynamic model attacks the starch structures more strongly.
DSC
Endothermic transitions of the investigated samples took place at temperatures which are known to destroy the amylose–lipid complexes. At lower temperatures (45–60°C) no peak was detected indicating that amylopectin is neither present in RTmd nor in HAM [20]. RTmd in vivo digested showed the lowest peak maximum and enthalpy of all the digestion residues. This may be due to the higher amount of non-starch material in the sample (Table 1) which may compete for water binding and thus reduce the starch swelling.
Dynamically digested HAM showed a slightly broader endothermic peak compared to the other samples which indicates a broader polydispersity [28]. This observation coincides well with the statement that starch is degraded differently, and probably more strongly in the dynamic model. In vitro digestion of HAM led to slightly but not significantly higher enthalpies, especially when dynamically digested. Cooke et al. [27] suggested that the enthalpy of gelatinization primarily reflects the loss of the double helical order which could occur to a higher extent during dynamic digestion.
Conclusions
The results of this study show that both, a simple and a more sophisticated in vitro digestion model and the ileostomy study led to similar amounts of starch escaping digestion when using a RS3 containing carbohydrate source as substrate. In contrast, when the two in vitro digestion models were compared with a RS2 containing preparation, different amounts of indigestible starch were found. It is not possible to predict which model simulated the in vivo RS2 fraction more precisely. The more sophisticated in vitro digestion model attacked starch probably more strongly compared to the batch in vitro digestion model using an RS2 and an RS3 containing substrate. This was confirmed by differences in crystalline fractions and structural rearrangements as measured by X-ray and DSC measurements. These structural differences, caused by different experimental parameters influenced starch digestibility of HAM but not of RTmd. The behavior of other RS preparations in the two in vitro models described here can not be deduced from the obtained results and has to be examined case by case.

in vitro digestion
x-ray
dsc
resistant starch type 2
resistant starch type 3


Can Examination of WWW Usage Statistics and other Indirect Quality Indicators Help to Distinguish the Relative Quality of Medical websites?

Background The Internet offers a great amount of health related websites, but concern has been raised about their reliability. Several subjective evaluation criteria and websites rating systems have been proposed as a help for the Internet users to distinguish among web resources with different quality, but their efficacy has not been proven.
Introduction
After the early enthusiasm generated by the potential use of the Internet in Medicine [1,2,3], concern has been raised about the quality of the resources available on the Internet compared to more academic media. It is technically very easy to publish on the Internet [4]. The lack of a review process of the documents on the Net, and the power of this media in transmitting the data has the risk of misinforming both lay people [5,6,7] and health care professionals [8]. However, only a few studies have tried to measure this risk of misinformation [9,10,11]. Nothing yet is known about the users' ability to discriminate between low and high quality resources.
Several initiatives have been proposed which could be applied at different levels to improve the average quality of medical websites. For instance, we could apply certain basic methods for the websites to be correctly designed. In this sense, some academic organizations have proposed a set of basic information that every medical web site should provide about the author and sources of the web site contents, their potential conflicts of interest and funding, and the currency of the information [12]. But many of the available medical websites have been created without any quality control by a third party. How can Internet health care visitors distinguish between such different resources?
Internet users can find health and medical related websites in several ways. World Wide Web search engines (e.g., AltaVista, Excite, Infoseek and many others) provide the users with a list of websites that match a given topic, with the results ordered by syntactic similarity with the query [13]. Unfortunately, the quality of contents is not guaranteed.
On the other hand, certain websites indexes and review services, such as Medical Matrix (http://www.medmatrix.org/) and HealthAtoZ (http://www.HealthAtoZ.com/), offer systematic evaluations of medical resources on the Web [14], as a post publication editorial process. These rating systems could be an useful tool for guiding the visitors of medical websites [12]. However, authors who have reviewed these Internet resources, point out the variability of their evaluation criteria and their doubtful efficacy [14].
The quality of a given medical article on the Internet could be measured by the users opinion about it, for example by counting the number of times it is retrieved [15]. However, this idea has been criticized because it would replace the scientific peer review process with the opinion of the Internet users, whatever their qualification [6].
Despite the differences between the printed medical information and the Internet, several evaluation tools from the former could be useful if applied on the "Net." Similarly to printed medical journals, medical documents on the Internet could be ranked by their citation analysis [15,16], but no methods have been proven for use with medical websites. When an article is quoted in a paper, certain agreement among the authors may be supposed. Similarly, when a webmaster makes a link from his web site to another, certain credibility is given to the latter. In fact, the International Committee of Medical Journals Editors recommend caution when a link is made from a peer reviewed journal site to other sites [17]. If linking on the web can be equivalent to quoting in printed medical articles, a citation analysis on the web could be performed by the quantification of the links to a given medical web site.
The ideal method for assessing the quality of medical websites should provide a means of rating great amounts of medical web resources while respecting the World Wide Web peculiarities, such as its multimedia capabilities and changing contents. At the same time, it should at least be as reliable as systematic reviews of those resources by editorial boards. In summary, it should be a method born in the Internet but with the efficacy of those used in the printed media.
In this study, we evaluated the reliability of four websites characteristics as medical websites quality indicators. The four characteristis used: their authors' impact factor, their grade of updating, their daily visits and inbound links. The evaluations of a sample of pediatric websites by a number of Internet rating systems was the gold standard with which these websites characteristics were compared.
Methods
During March 1998 a subset of websites rating systems were compiled. From these, we selected a sample of websites that were studied during the first week of April 1998.
Eight web rating systems, whose evaluations were offered as figures, were compiled from previous studies [13,14] (Table 1). One half of the selected rating systems gave the results of their evaluations by means of graphic analog scales, and the other half by numeric scales. Every web site evaluated by these rating systems that provided information about child health, whether for lay people or health professionals, was included in the study. Some of these rating systems (e.g., Lycos Top 5%) provides the visitors with a search tool by keyword. In these cases, the websites were selected using the keywords "Pediatrics", "Infancy", "Child health", and "Child Care." For the remaining rating systems, the pediatric websites were compiled manually. Those websites not accessible twice during the study period were excluded.
Only three rating systems (Medical Matrix, Physician Choice, and Six Senses) gave information about their editorial boards. Most of their members were physicians. Two of the web rating systems only gave a global result of their websites evaluation (Medical Matrix and Magellan), while the rest (HealthAtoZ, Argus Clearinghouse, Lycos Top 5%, Sympatico Health, Physician Choice, and Six Senses) gave a result for each considered criterion. Content was a common criterion to all the eight ranking systems. Therefore, the results of the evaluation of each web site were divided in two categories, content and non-content (design) aspects. In order to make comparisons, the results of the evaluations of the websites supplied by each rating system were transformed to a one hundred scale.
Table 1
Compiled web sites ranking systems. The results of evaluations are showed as two possible types of scales, graphic analog (A) or numeric (N)
Rating systems (Included/excluded web sites)
Uniform Resource Locator
Type of scale
Argus Clearinghouse Seal of Approval (16/1)
http://www.clearinghouse.net/cgi-bin/chadmin/viewcat/Health___Medicine?kywd++
A
HealthAtoZ (241/66)
http://www.healthatoz.com
*
Lycos Top 5% (8/3)
http://point.lycos.com/topics/Health_Overall.html
N
Magellan Internet Guide (40/11)
http://www.mckinley.com/magellan/Reviews/Health_and_Medicine/index.magellan.html
A
Medical Matrix (75/11)
http://www.medmatrix.org/SPages/Pediatrics.asp
A
Physician's choice (4/0)
http://www.mdchoice.com/pcsites.htm
N
Six Senses Seal of Approval (4/0)
http://www.sixsenses.com/winners.html
N
Sympatico Health (8/1)
http://www1.sympatico.ca/Contents/Health/LISTS/D3-C03_all1.html
A
* Graphic analog scale developed in numeric
When provided, the daily visits registered by the websites visits counters were recorded. In some websites the date from which the counter was started was not available. Thus, their webmasters were asked for this information by electronic mail, and it was included in the statistical study if provided before the end of the observation period, 15th April 1998.
The websites authors and editors' names were searched in 1997 MEDLINE [18], and their articles were registered. Their impact factors of the journals wherein they were published were obtained by using the 1996 Science Citation Index (Institute for Scientific Information, Philadelphia, PA). The impact factor of a given web site author was the sum of the impact factors of his or her articles. For institutional websites only the name of the web editor was considered.
When provided, the time since the last update was also recorded.
Finally, by means of the Web search engine Infoseek [19], we calculated how many websites on the Internet linked to each web site of our sample. The searching strategy by syntax of this engine allows to know the websites that are linked to a given web site [20]. As a web site may be linked not only from external websites but also from websites of its own organization, we only considered external links. Although other search engines such as AltaVista, Excite or HotBot offer similar searching options, we chose Infoseek because it provided the results of the queries grouped by web site, which makes the exclusion of the internal links easier.
Comparison of means was performed by Mann-Whitney U test, and correlation analysis by means of Spearman's correlation coefficient ( rS). P values equal or less than .05 were considered significant. All computations were made with SPSS for Windows 7.0 (SPSS Inc., Chicago, IL) statistical package.
Results
After excluding 93 non-accessible websites, a total of 363 pediatric websites were compiled.
Table 2
Correlations among the number of daily visits to the web sites, the impact factor of their authors or editors, the grade of update, and the number of links that receive. NS means not significant
Number of inbound links rS p
Visits/day rS p
Author's impact factor rS p
Visits/day
.46 .005
Author impact factor
NS
NS
Weeks since the last update
-.36 <.001
NS
NS
Table 3
Correlation among the number of links and visits to the web sites, the impact factor of their authors, and the time since the last update, and the results of their evaluation by HealthAtoZ and Medical Matrix. No significant correlations were demonstrated with the other systems. Medical Matrix only provides total results, does not specify results by contents and non-contents aspects
Number of Inbound Links
Visits/day
Author impact factor
Weeks since the last update
rS
p
rS
p
rS
p
rS
p
HealthAtoZ
Total Contents Non contents
.29 <.001 .30 <.001 .24 <.001
NS
NS
-.19 .04 -.23 .00 NS
Medical Matrix
Total
NS
.79 .03
NS
NS
On average, the websites of our sample received links from 470 other sites on the Internet (range, 0 to 3574). In 48% of the websites, information on their last update was given. On average, they had been updated 47.5 weeks before (range, 0 to 395). Only 10% of the websites had a visit counter, and the average daily visits were 470 (range, 1.2 to 3145). Seven visit counters did not distinguish among different visitors, that is, they registered any visit to their websites. In 137 websites (38%) the editor/author's name was given, but only 60 of them had published at least one article since January 1997 in the journals included in MEDLINE database. Their average impact factor was 2.14.
Figure 1
Weeks since the last update for the total of the sample, n=363, and for the websites evaluated at least by two rating systems, n=25 (median, 25th and 75th percentiles)
Figure 2
Number of inbound links to websites for the total of the sample, n=363, and for the websites evaluated at least by two rating systems, n=25 (median, 25th and 75th percentiles)
Table 4
Top 50 pediatric web sites of the sample (N= 363) by the number of their inbound links. The weeks since the last update, the number of daily visits to the web sites and their editor/author's impact factor are also provided. In parenthesis, the place that each web site would obtain if ranked by the two latter criteria. In italics, those web sites indexed at least by two rating systems. Missing values are due to the lack of visits counter, editor's name, or information about the last update, for many web sites
Uniform Resource Locator
Number of inbound links
Daily visits to web sites
Web site editor/author's impact factor
Weeks since the last update
1
http://www.merck.com
3574
-
-
13
2
http://www.ucalgary.ca/~dkbrown/index.html
2355
1620 (3º)
0 ( 360º)
-
3
http://KidsHealth.org
1109
-
-
-
4
http://www.psych.med.umich.edu/web/aacap
927
-
-
3
5
http://www.aap.org
896
-
-
1
6
http://www.chadd.org
785
-
-
4
7
http://www.castleweb.com/diabetes
767
-
-
-
8
http://www.medconnect.com
714
-
-
-
9
http://www.aaaai.org
677
-
-
-
10
http://www.aacap.org/web/aacap
612
-
-
4
11
http://www.nas.com/downsyn
572
-
0 ( 360º)
1
12
http://www.childbirth.org
534
-
-
-
13
http://web.syr.edu/~jmwobus/autism
502
-
0 ( 360º)
-
14
http://oncolink.upenn.edu/disease
487
-
10.1 (8º)
9
15
http://www.jdfcure.com/index.html
428
-
-
-
16
http://www.mic.ki.se/Diseases/index.html
423
1412 (5º)
-
-
17
http://www.asf.org
365
940 (6º)
-
1
18
http://www.mdcc.com
365
-
-
1
19
http://www.mc.vanderbilt.edu/peds
357
-
-
-
20
http://www.ama-assn.org/journals/standing/jama/jamahome.htm
330
-
-
-
21
http://www.med.jhu.edu/peds/neonatology/poi.html
322
253 (10º)
9.3 (13º)
2
22
http://www.wish.org
317
-
-
-
23
http://education.indiana.edu/cas/adol/adol.html
312
-
0 ( 360º)
52
24
http://www.kidsdoctor.com
297
-
0 ( 360º)
-
25
http://www.xmission.com/~gastown/safe
297
94 (20º)
-
-
26
http://www.childquest.org
287
-
-
6
27
http://www.uab.edu/pedinfo
284
-
-
-
28
http://www.childsecure.com
255
-
-
-
29
http://www.mc.vanderbilt.edu/peds/pidl
254
-
0 ( 360º)
1
30
http://www.stjude.org
251
-
-
-
31
http://www.nccf.org
249
70 (25º)
-
8
32
http://www.mda.org.au
238
-
0 ( 360º)
12
33
http://www.peds.umn.edu
235
-
0 ( 360º)
2
34
http://www.csmc.edu/neonatology
232
117 (15º)
-
1
35
http://med-aapos.bu.edu
225
-
0.4 (51º)
3
36
http://www.jhbmc.jhu.edu
220
-
-
3
37
http://sids-network.org
214
3145 (1º)
0.3 (54º)
1
38
http://www.diabetes.com
212
-
-
-
39
http://sids-network.org/index.htm
208
3145 (1º)
0.3 (55º)
1
40
http://www.oneworld.org/scf
205
-
-
-
41
http://www.childmmc.edu
204
-
-
13
42
http://www.os.dhhs.gov/hrsa/mchb
197
-
-
7
43
http://www.wp.com/pedsrheum
197
81 (23º)
11.7 (6º)
-
44
http://dem0nmac.mgh.harvard.edu/neurowebforum/neurowebforum.html
188
2441 (2º)
0 ( 360º)
-
45
http://pedsccm.wustl.edu
179
145 (13º)
1.0 (39º)
2
46
http://www.drgreene.com
179
-
-
-
47
http://www.medsch.wisc.edu
162
-
-
-
48
http://www.blindcntr.org/bcc
150
-
-
-
49
http://home.coqui.net/titolugo
144
68 (26º)
0.2 (56º)
1
50
http://www.chmcc.org
141
-
-
1
Only 25 websites of the sample were indexed and evaluated at least by two rating systems, and none by the eight. This subset of websites showed significantly better results of the evaluation of their contents and design by HealthAtoZ, and higher grade of updating (Figure 1) and higher number of inbound links (Figure 2). When the evaluations of these 25 websites by the different rating systems were compared, no significant correlations were found. Changes regarding the average impact factor of the authors of the websites or the number of daily visits could not be demonstrated in this subset of websites.
Some interesting correlations between the results of the evaluations of the websites and the rest of study variables were found. The number of links received by the websites significantly correlated with their daily visits and with the time since the last update (Table 2). The number of inbound links also correlated with the results of the websites evaluation by HealthAtoZ (Table 3).
The number of daily visits significantly correlated with the results of the websites evaluation made by Medical Matrix, and the grade of updating significantly correlated with the results of the contents and designs evaluation made by HealthAtoZ (Table 3).
Finally, no correlation was demonstrated between the average impact factor of the websites authors and the other variables.
The top fifty pediatric websites of the sample are shown in Table 4, ordered by the number of their inbound links according to the Infoseek indexing engine. More than a half of the 25 websites indexed by at least two rating systems may be found among these top fifty websites.
Discussion
In this study, certain websites characteristics that depend on the users' preferences have been compared with evaluations of pediatric resources on the Web by third parties. Although rating systems have been previously criticized because their editorial boards frequently do not employ uniform criteria [13], we have considered them as the standard method because it somewhat represents a post-publication review process.
Some aspects of our method are open to discussion. Firstly, the reliability of the data regarding the daily visits and the updating frequency depends on the accuracy of the information that the websites editors offer in their sites. In this sense, we considered the grade of updating of the websites by the dates of their last changes. Clearly these changes could involve very different aspects and in different grades, and not necessarily provide more current contents. However, we believe that it could demonstrate the editor's efforts in maintaining or increasing the interest of his web site for the visitors.
The results regarding the number of daily visits to the websites must be considered with caution when comparing one web site to another, because some visit counters were set to register every visit, instead of every distinct visitor. Nevertheless, both can be considered usage indexes of a given web site.
On the other hand, quantification of links to the websites clearly depends on the power of the search engine we employ. By no means our results show the total number of links to the websites in our sample. In fact, a previous article states that it would be necessary to combine the databases from at least five large search engines to cover the most of the web [21].
Although all bibliometric indexes have limitations [22,23], we employed the impact factor as a measure of the webmasters' publishing capacity because it is a classical indicator of the quality of biomedical articles. Recently, it has been suggested that every medical web site should be evaluated following some basic criteria [24]. One of the more accepted criteria is that the authorship must be clearly stated, as a basic means for assessing the reliability of the web site contents. However, we could not demonstrate that the more highly evaluated, the most updated, or the most linked or visited pediatric websites, had the authors with the highest publishing capacity measured by their impact factor. In other words, some web quality standards do not correlate with classical quality standards from the printed media such as the impact factor of a given author's articles.
We could not find statically significant correlations among the evaluations of the websites by the different rating systems. This is probably due to the small size of the subset of websites indexed and evaluated by all the systems, and their different evaluation criteria. However, some interesting data were found when we considered the correlations among the four websites characteristics and the evaluations. We found that the best websites for HealthAtoZ, the largest analyzed rating system, were the most updated and the most linked ones. On the other hand, the most valuable websites for Medical Matrix, the second rating system by size, were the most visited ones. In any case, both the number of daily visits and the time since the last update highly correlated with the number of inbound links. The lack of correlation among the four variables and the evaluations by the other rating systems could be due to their little contribution to our sample.
Many efforts to establish quality criteria will have limited efficacy due to the dynamic behaviour of the Internet as a publishing medium. In fact, a recent article demonstrates the lack of consensus among the editorial boards of a large sample of evaluation and rating systems regarding the evaluation criteria they employ. The same authors pointed out that "... it may be difficult or even inappropriate to develop a static tool or system for assessing health related websites." [25] Therefore, the question could be to provide context to this issue. That is, to know how good a given medical web site is in comparison with the rest of medical websites. A democratic and feasible method for reaching this objective could be let the Internet community say which medical websites are the best ones, that is, which they usually visit or which they usually recommend by linking to them. Moreover, we believe that the fact that these usage indexes correlate with the evaluations by third parties, qualifies them as quality markers.
Eysenbach and Diepgen [16] have recently proposed that an ideal quality control system for medical resources on the Internet should take in account the users opinion, and not only their evaluation by a third party, that is, a "downstream filtering" and not only an "upstream filtering" approach. More interestingly, our study demonstrates certain agreement among both approaches in identifying high quality resources.
LaPorte et al [15] proposed an electronic publishing system in which the impact of a given resource on the Internet could be measured by counting how many times the document was retrieved or quoted. The introduction of the citation analysis of the medical resources on the web as a method to assess their quality has been recently proposed [16]. On the other hand, a very promising software system is being developed by Kleinberg [26,27]. This system would provide the users with a way of knowing the very best of the web on a given topic in a faster and more complete way than commercial human compiled directories. This system is based in the identification of two subsets of websites when a query on a given topic is made, those websites containing a lot of information about the topic (authoritative websites) and those which contain large amounts of links to the former (hub sites). Our work demonstrates that those authoritative websites, that is the more linked ones, are indeed the best ones regarding the evaluation of its contents and design by the editorial boards of some large web rating systems.
The citation analysis of biomedical journals has been a classic tool in assessing their relative quality [28]. Similarly, medical web resources could be ranked by a "webcite index" [16], which is not yet defined. Linking in the World Wide Web could be equivalent to quoting in printed publications, and its quantification could be useful for measuring the relative quality of medical websites. Some indexes could be created to make more rational comparisons among websites with different sizes. For example, in the same way that the calculation of the impact factor of a given medical journal takes into account the number of articles published by that journal yearly, the size of a given domain could be considered to obtain some indexes that would express more accurately the grade of linkage of a medical web site. Moreover, Platform for Internet Content Selection (PICS) [29], an infrastructure that could be applied as a filtering system of the medical information on the Net [16], could incorporate these indexes as one of the meta- data assigned to every medical document as electronic labels. Then, these electronic labels could be checked automatically by an user's browser, bypassing those documents with a "webcite index" not high enough. A problem could be how to avoid false "self-labelling" by dishonest webmasters. In any case, more work is needed to give answers to these and other technical questions on the emerging field of Webometrics [30].
An evaluation system based on this quantification would bring advantages and risks. Rankings could be generated very quickly and in an objective way, because the Internet community by itself would evaluate great amounts of medical websites. However, this evaluation process would be made a posteriori, and the potential harmful effects of the diffusion of documents without enough quality could not be avoided. Therefore, this method could not replace previous editorial effort that warrants a minimal quality for each resource.
Our work demonstrates that the visitors of pediatric websites and the editors of websites on the "Net," so called webmasters, show certain maturity when they have to identify the pediatric resources with high quality. We believe that the key point is how to augment the proportion of these resources. An important issue could be to establish a citation style not only for articles from peer reviewed electronic journals [31], but also for any medical document on the Net. The prestige that citation in a printed journal represents will stimulate high quality publishing on the Internet, and web site editors will employ enough review processes to obtain the necessary quality. A web site's ranking system based on the citation analysis on the web by the quantification of links would be an additional incentive. The more valuable resources will attract the Internet users' visits and the webmasters' links, and very likely the best funding and financial supports.
In summary, although the Internet provides a very different publishing medium, traditional means borrowed from printed journals could also be used with this electronic media for achieving minimal levels of quality. These include certain peer review processes, that enhance the rigor of the documents submitted for publication taking in account the peculiarities of this media, and linking analysis as a measure of the citation on the World Wide Web.

internet
bibliometrics
webometrics
health education
information systems
computer communication networks
cybermetrics
web metrics