Schools are the most frequent target for intervention programs aimed at preventing child obesity; however, the overall effectiveness of these programs has been limited. It has therefore been recommended that interventions target multiple ecological levels  to have greater success in changing risk behaviors for obesity. This study examined the immediate and short-term, sustained effects of the Switch program, which targeted three behaviors  at three ecological levels .Participants were 1,323 children and their parents from 10 schools in two states. Schools were matched and randomly assigned to treatment and control. Measures of the key behaviors and body mass index were collected at baseline, immediately post-intervention, and 6 months post-intervention.d = 0.15 for body mass index at 6 months post-intervention) to large , controlling for baseline levels. There was a significant difference in parent-reported screen time at post-intervention in the experimental group, and this effect was maintained at 6 months post-intervention (a difference of about 2 hours/week). The experimental group also showed a significant increase in parent-reported fruit and vegetable consumption while child-reported fruit and vegetable consumption was marginally significant. At the 6-month follow-up, parent-reported screen time was significantly lower, and parent and child-reported fruit and vegetable consumption was significantly increased. There were no significant effects on pedometer measures of physical activity or body mass index in the experimental group. The intervention effects were moderated by child sex , family involvement (for fruit and vegetable consumption), and child body mass index (for screen time). The perception of change among the experimental group was generally positive with 23% to 62% indicating positive changes in behaviors.The effect sizes of the differences between treatment and control groups ranged between small (Cohen's The results indicate that the Switch program yielded small-to-modest treatment effects for promoting children's fruit and vegetable consumption and minimizing screen time. The Switch program offers promise for use in youth obesity prevention. Pediatric obesity continues to be a serious public health issue with trends indicating that the prevalence of childhood obesity will reach 24% in the USA by 2015 -6. Many Family components are critical for youth obesity prevention programs because parents directly and indirectly influence children's PA and nutrition behaviors at home and also dictate the physical and social environments that are available to their children . SeveralSocial ecological models that target multiple levels of influence have been recommended to address the obesity epidemic ,17. AlthAn established social ecological framework was used to guide the development of the Switch intervention ,27. DetaAll 10 elementary schools in Lakeville, MN and Cedar Rapids, IA, USA, participated in the study. These two school districts were approached due to the requirements of funding agencies. Schools were matched within district by enrollment and percent free/reduced-cost lunch and then randomly assigned to the experimental (three in Cedar Rapids and two in Lakeville) or control (three in Cedar Rapids and two in Lakeville) condition. Prior to participation, parents provided active written consent, and children provided assent.N = 430), fourth (N = 446), and fifth (N = 423) grade children returned consent forms . Participation rates were similar between the experimental and control schools . Forty-seven percent were male  and most (90%) were White, which is representative of their communities. Figure A sample of 1,323 third (Data were collected prior to implementation (baseline), immediately following the intervention (post-intervention), and 6 months post-intervention. Out of 1,323 consented families, 1,288 children (97%) provided data. Of those, 1,196 (93%) provided data at baseline, 1,156 (90%) at post-intervention, and 1,110 (86%) children at 6 months post-intervention. Data were provided by 1,076 children (84%) at both baseline and post-intervention, 1,029 (80%) at both baseline and 6-months post-intervention, and 992 (77%) at all three time points. A total of 1,150 (87%) parents provided data. Of those, 980 (74%) provided data at baseline, 916 (69%) at post-intervention, and 811 (61%) at 6 months post-intervention. Data were provided by 778 parents  at both baseline and post-intervention, 694 (52%) at baseline and 6 months post-intervention, and 631 (48%) at all three time points. Although the percentages varied between waves of data collection, over 80% of parent surveys were completed by mothers, between 7% and 11% were completed by fathers, and the rest were completed by both parents together.The study was approved by the University of Minnesota Institutional Review Board in accordance with the Declaration of Helsinki and the 'Ethical Principles of Psychologists and Code of Conduct' . It is rThe Switch program promoted healthy active lifestyles by encouraging students to 'Switch what you Do, Chew, and View'. The specific DO, VIEW, and CHEW goals were to be active for 60 minutes or more per day, to limit total ST to 2 hours or fewer per day, and to eat five fruits/vegetables or more per day. The intervention utilized overlapping behavioral and environmental strategies employed at multiple ecological levels, and is described in detail elsewhere .The community component was designed to promote awareness of the importance of healthy lifestyles and the prevention of childhood obesity in the targeted communities, and included paid advertising  and unpaid media emphasizing the key messages. Note that both experimental and control participants may have been exposed to the community component. The school component was designed to reinforce the Switch messages and facilitate the family component of the intervention. Teachers were provided with materials and ways to integrate key concepts into their existing curricula. Teachers were not required to participate, since the study was not designed as a school-based (curricular) intervention. Control schools did not receive any school materials. The family component was designed to provide parents (and children) with materials and resources to facilitate the adoption of the healthy target behaviors. Monthly packets containing behavioral tools were provided to assist parents and children in modifying their behaviors. Control families were recruited similarly to experimental families, but received no materials other than the surveys .Data were collected from multiple informants. Baseline assessments (October 2005) included children wearing pedometers for 1 week, completing surveys in classrooms, and having anthropometric measurements taken by school nurses. Parents and teachers also completed surveys. The same measures were conducted immediately post-intervention (May 2006). To measure the maintenance of effects, data were collected approximately 6 months after the end of the intervention (November 2006).Habitual PA was assessed by a pedometer . Accuracy was assessed by having participants walk 10 steps and pedometers that were off by more than 1 step were replaced. Children were instructed to wear the pedometer for 7 consecutive days and to record the time they put the monitor on and off as well as the number of steps accumulated each day. At least 4 days' of data (3 weekdays and 1 day at the weekend) with at least 10 hours/day were required to be considered compliant . The classification of meeting physical activity goals was determined using two published recommendations. The Vincent and Pangrazi  recommenStanding height and weight were measured by trained school nurses using standardized procedures . Body maTime spent viewing TV and playing video games was assessed (independently) by both parents and children, using methods that have been used reliably with parents  and chilParents and children reported on children's FV consumption with items adapted from the National Youth Risk Behavior Survey . The iteAt the conclusion of the program, children and parents in the experimental group were surveyed about noticeable effects of the program on ST, FV, and PA. For each behavior measured, participants reported on a five-point verbally anchored scale the degree to which they perceived their family changed behaviors (ranging from 'a lot more' to 'a lot less').r = 0.47); we therefore standardized scores on each measure and a family involvement score was calculated by averaging parent and child ratings. This composite measure of family involvement allowed for testing whether involvement modified the effect of the intervention, as it could be hypothesized that the effect of the program would be greatest for families who were most involved. High and low involvement groups were created by a median split.Parents and children also reported how much they had participated in the various aspects of the program at post-intervention . Reports of parents and children were found to be significantly correlated  units. Cohen's d is computed by subtracting the average score for the control group (MC) from the average score for the treatment group (MT), and then dividing the difference by the SD on the outcome measure for the sample. We used the standard criteria for ES of small (d = 0.20), medium (d = 0.50), and large effects (d = 0.80) [The primary tests examining differences between baseline and post-intervention and baseline and 6 months post-intervention were conducted using hierarchical multilevel regression analyses to take into account the nested nature of the data (families are nested within schools). An analysis of variance was conducted to test for differences between the schools on the outcome measures at baseline. School had a significant effect for all six outcome variables, explaining from 1% to 11% of the variance in each. Because schools explained a significant amount of variance hierarchical analyses were required and, therefore, subsequent analyses of differences between the treatment and control groups employ variance due to school as the error term in the analyses. This adjustment reduces the degrees of freedom (df) from over 1,300 to 9, but is necessary due to the variability by school and the fact that participants were randomized at the school level. Baseline values were used as covariates to control for any differences between participants on these variables prior to the intervention. This also controls for the observed difference between groups for the child reporting of FV. Further analyses were conducted to provide a more comprehensive evaluation of the intervention. One set of analyses examined whether or not the child's sex moderated the effectiveness of the intervention. These analyses examined whether the intervention had a greater impact for boys or girls. Another set of analyses examined whether family involvement in the programming moderated treatment effects. These analyses specifically examined whether effects were stronger for participants that were highly involved in the program. A final set of analyses tested for moderation of treatment effects by weight status. These analyses specifically examined whether the effects were stronger for overweight or obese youth compared with normal weight youth. As we had directional hypotheses, all reported tests are one-tailed. Effect sizes (ES) were also calculated using Cohen's  = 0.80) . We empl2 . Overall, 19% of children were classified as overweight and 8% were obese. There were significant differences between boys and girls on child-reported and parent-reported weekly ST  = 6.35, P < 0.001, and t (976) = 5.69, P < 0.001, respectively). This was due primarily to video game play. By child report, boys and girls were not significantly different on the number of fruits and/or vegetables they had eaten the previous day. Based on national guidelines (five servings of fruits and vegetables per day) approximately 44% of the children met the recommended guidelines. By parent report, girls ate almost two more servings of fruits and vegetables per week compared with boys  = 2.22, P < 0.05). Only 17% of children met the recommended guidelines of at least five servings a day. As expected, boys tended to have greater step counts than girls (t (823) = 9.01, P < 0.001). Depending on the recommendation used, between 28% and 43% of children achieved the recommended level of PA. Boys and girls were not significantly different on meeting the Vincent and Pangrazi recommendation , but were significantly different on meeting the stricter Tudor-Locke recommendation .Characteristics of the sample at baseline are shown in Table d = 0.15 for BMI at 6 months post-intervention) to large . There was a significant difference in parent-reported ST at post-intervention, and this effect was maintained at 6 months post-intervention (a difference of about 2 hours/week). Child-reported ST was also lower in treatment groups at 6 months post-intervention, but the effect was not significant . There were significant increases in parent-reported FV consumption at post-intervention and 6 months post-intervention. The increase for child-reported consumption was marginally significant at post-intervention and was significant at 6 months post-intervention. PA, as measured by pedometer, at post-intervention and 6 months post-intervention was not statistically significant, although the students in the treatment schools accumulated an average of about 350 more steps per day . Despite a lack of statistical significance, these differences are in the expected direction. At both post-intervention and 6 months post-intervention, the mean BMI values were not significantly different between the treatment and control groups.Tables t (961) = 2.84, P < 0.01) and 6 months post-intervention (t (907) = 1.99, P < 0.05). At both times, the interaction was due to girls in the treatment group reporting greater FV consumption  than girls in the control group . For PA, boys had higher step counts than girls at both post-intervention and 6 months post-intervention, but the interaction with treatment was significant at post-intervention, t (717) = 2.48, P < 0.05, with the program having a significant effect on girls . For BMI, there was a significant sex by treatment interaction at 6 months post-intervention, t (1083) = 2.19, P < 0.05, with boys in the treatment group having a lower BMI (M = 19.1 kg/m2) than boys in the control program (M = 19.4 kg/m2).We examined whether the treatment effects were modified by child sex. These analyses examined the effect of treatment program, sex, and the program by sex interaction on the outcome measures, controlling for baseline values. Although boys had higher total ST than girls (due to more video game play), the interactions between sex and treatment were non-significant. In contrast, the sex by treatment interaction on child-reported FV was significant at post-intervention (t (460) = 4.61, P < 0.001) and at 6 months post-intervention (t (423) = 2.37, P < 0.05), and for parent-reported FV at post-intervention (t (340) = 3.05, P < 0.01), controlling for baseline values. Greater consumption of FV was reported by children who were highly involved (defined by median split) in the treatment program  than for children who were less involved in the treatment program .We examined whether the treatment effects were modified by level of involvement, hypothesizing that the effects of the Switch program would be largest for families who were most highly involved. Significant interactions were found with child-reported FV consumption at post-intervention  than overweight (M = 30.9) or normal weight (M = 29.6) participants, t (1005) = 2.54, P < 0.05. This relation was moderated by a statistically significant interaction, t (1003) = -2.47, P < 0.05, with obese children showing the largest difference in ST between the treatment (M = 30.2) and control (M = 40.8) groups. Thus, the positive effect on child-reported ST was greatest for obese children.We examined whether the treatment effects were modified by child weight, hypothesizing that children who were classified as obese might benefit more from the program. Obese children reported higher ST at post-intervention . Furthermore, these community-based messages were available to both experimental and control families and, therefore, may have minimized differences between the groups.Although over 1,300 families participated in the study, a major limitation of this study was the sample size. Statistical analysis of treatment effects was at the school level due to families being nested within schools and randomization at the school level, resulting in low power to detect differences. Future studies should randomize at the classroom or family level to have greater degrees of freedom . Another limitation is the potential for social desirability to influence the results. It seems unlikely, however, that only the experimental group would be subject to such desirability biases. To reduce the potential effects of bias and method variance, we used multiple informants. An additional limitation was reliance on pedometers to measure PA. Although it seems preferable to have an objective measure, compliance with the requirements was lower than anticipated. Furthermore, the pedometer captures the total amount of PA and does not provide information on the intensity of PA. It is unknown if the amount of time spent in moderate-to-vigorous PA was altered by the intervention. IHere, it is possible that the total number of steps/day was unchanged yet the time spent in moderate-to-vigorous PA increased. Future studies should use PA monitoring tools that capture both the volume and intensity of PA.In conclusion, the results indicate that the Switch program produced modest treatment effects for children's FV and ST. It is noteworthy that the effects remained significant in the 6-month follow-up evaluation as this indicates maintenance of these differences over time. Although levels of BMI were not statistically different between groups, the maintenance of behaviors over time may contribute to reduced risks for overweight in the future. The Switch program which targets multiple behaviors through multiple channels offers promise for use in youth obesity prevention.ADA: American Dietetics Association; BMI: body mass index; ES: effect sizes; FV: fruit and vegetable consumption; PA: physical activity; SD: standard deviation; ST: screen time.The authors declare that they have no competing interests.The Switch program is a program of the National Institute on Media and the Family, a non-profit organization. Several of the authors were employed by the Institute to create the program or to conduct the research , or consulted with the Institute on the design (JCE) or analysis (DWR and RAR).DAG, JCE, DAW, RC, MW, SS, and KF designed the study, established methods and questionnaires, and participated in the coordination of the study. GW provided insight into the conceptual framework of the study. DWR, DAG, and RAR conducted the statistical analyses. All authors read and approved the final manuscript.The pre-publication history for this paper can be accessed here:


Excessive gestational weight gain and postpartum weight retention may predispose women to long-term overweight and other health problems. Intervention studies aiming at preventing excessive pregnancy-related weight gain are needed. The feasibility of implementing such a study protocol in primary health care setting was evaluated in this pilot study.A non-randomized controlled trial was conducted in three intervention and three control maternity and child health clinics in primary health care in Finland. Altogether, 132 pregnant and 92 postpartum women and 23 public health nurses (PHN) participated in the study. The intervention consisted of individual counselling on physical activity and diet at five routine visits to a PHN and of an option for supervised group exercise until 37 weeks' gestation or ten months postpartum. The control clinics continued their usual care. The components of the feasibility evaluation were 1) recruitment and participation, 2) completion of data collection, 3) realization of the intervention and 4) the public health nurses' experiences.1) The recruitment rate was slower than expected and the recruitment period had to be prolonged from the initially planned three months to six months. The average participation rate of eligible women at study enrolment was 77% and the drop-out rate 15%. 2) In total, 99% of the data on weight, physical activity and diet and 96% of the blood samples were obtained. 3) In the intervention clinics, 98% of the counselling sessions were realized, their contents and average durations were as intended, 87% of participants regularly completed the weekly records for physical activity and diet, and the average participation percentage in the group exercise sessions was 45%. 4) The PHNs regarded the extra training as a major advantage and the high additional workload as a disadvantage of the study.The study protocol was mostly feasible to implement, which encourages conducting large trials in comparable settings.Current Controlled Trials ISRCTN21512277 Obesity has become an epidemic throughout the world and increases the risk of several diseases such as type 2 diabetes, cardiovascular disease and certain cancers . For womThe effect of dietary and physical activity habits on gestational weight gain and postpartum weight retention is still unclear . TherefoThe study was conducted in six MCs and CCs in the city of Tampere and the town of Hämeenlinna. The selection of the clinics was based on the clinics' administrative personnel's suggestion for suitable clinics. In the larger trial, a larger number of other clinics will be randomized to intervention and control clinics. The most important reason for randomizing the clinics instead of individuals – i.e. public health nurses (PHN) or pregnant and postpartum women – is the likelihood of contamination of the PHNs' counselling practices. In this pilot study, three MCs and CCs volunteered to be intervention clinics and the remaining clinics were treated as control clinics. Feasibility of the study protocol was evaluated separately in the MCs and the CCs, because the larger trial was meant to begin in early pregnancy and continue after delivery.In Finland, women with no earlier deliveries are recommended to make 11–15 visits to a PHN and three visits to a physician during pregnancy . In the Fourteen PHNs from the intervention clinics and nine PHNs from the control clinics participated in the study. The PHNs recruited pregnant and postpartum women with no previous deliveries for the study. The exclusion criteria were age under 18 years, type 1 or 2 diabetes mellitus, twin pregnancy, physical disability preventing exercise, substance abuse, treatment or clinical history of any psychiatric illness, otherwise problematic pregnancy (defined by a doctor), inadequate language skills in Finnish and intention to change residence within three months. The PHNs recruited the pregnant women by phone when making an appointment for the first MC visit. The postpartum women were recruited when the PHN visited the participant's home after delivery or on the participant's first visit to the CC. As this was a pilot study, the sample size was not based on power calculations. Instead, the aim was to recruit at least 40 pregnant and 40 postpartum women from the intervention and the control clinics . All participants provided written informed consent to participation. The study was approved by the Ethics Committee of the Pirkanmaa Hospital District.Data collection was similar in the intervention and the control clinics Table . The PHNIn the control clinics, the PHNs continued their usual physical activity and dietary counselling practices. In the intervention clinics, the intervention included individual counselling on physical activity and diet and an option to attend supervised group exercise sessions once a week at a location close to the clinic Figure . The conBefore the study began, the PHNs of the intervention clinics were trained in the counselling procedures and the study arrangements  and the PHNs of the control clinics for the study arrangements  by the research group. All PHNs received a handbook in which the tasks related to each visit were explained. One or two researchers visited each clinic monthly during the study. One supportive meeting was held for the PHNs of the intervention and the control clinics separately. The exercise instructors (n = 10) were trained for the group exercise sessions by the research group .The location of the clinics should not have any effect on the services the clinics provide, because all clinics are supposed to follow the national guidelines for maternity and child health care ,18. In tInformation on the background characteristics and the usual counselling practices of the PHNs was collected by a questionnaire (n = 21) before the PHNs were trained for the study. The responses varied between the six MCs and CCs, but the numbers of PHNs in each clinic were too small to test the statistical significance of the between-clinic differences. Concerning all clinics, 15 (71%) PHNs were aged 40 years or more. The PHNs had either the official degree of PHN (n = 15), midwife (n = 1) or both (n = 5). Of those PHNs who had worked in a MC, the median time of working in a MC was 3.5 (range 1 to 30) years. Likewise, of those PHNs who had worked in a CC, the median time of working in a CC was 13.0 (range 1 to 26) years. The counselling practices varied remarkably between the PHNs, but not between the PHNs of the intervention and the control clinics ,20.In Finland, the clinic attended by each pregnant and postpartum woman is determined by her place of residence. The socioeconomic background of the residents varies between these areas, which may also have affected the characteristics of the participants. There was some variation in the participants' mean age, mean pre-pregnancy BMI, education level, smoking status and the baseline dietary and physical activity habits between the six clinics (results not shown), but the statistical significance of the differences could not be tested due to the small number of participants in each clinic. Information on these variables has been reported earlier in the intervention and the control clinics ,20.The feasibility assessment of the study protocol comprises the following four components. The main indicators and data collection for each component are described below.Information on the achievement of the recruitment aim  within three months, the participation rate of the eligible women and the drop-out rate of participants were obtained from the standardized recruitment forms used by each PHN.The proportion of data obtained on weight development, diet and physical activity was assessed from the number of completed and returned baseline and follow-up questionnaires, maternity cards and postpartum weight measurement forms. Information on the proportion of blood samples obtained was collected from the laboratory records.Concerning the intervention clinics, the realization rate, content and duration of counselling sessions was assessed from the PHNs' counselling cards. Each counselling session was regarded to have been implemented as intended if all essential parts of the counselling card were filled in for the session. The proportion of women completing ≥ 75% of the weekly records for physical activity and diet was obtained from the participants' follow-up notebooks. The mean participation percentage in the group exercise sessions was determined by calculating first the participation percentage of each woman separately from the number of sessions available for her and then averaging the individual participation percentages. Information on participation was obtained from the participant lists kept by the exercise instructors.Information on the PHNs' opinions of the appropriateness of the training for the study was collected using a questionnaire three months after the initiation of the study. The PHNs assessed the training on the Osgood scale (1 = very poor ... 5 = excellent). Additionally, the advantages and the disadvantages of the study for the PHNs were inquired from them by a semi-structured interview within two weeks each PHN's last participant had finished the study.As only 113 participants were enrolled within the three months allocated, the recruitment period was prolonged to six months Table . FinallyThe proportions of data obtained on weight, physical activity and diet were 96–100% and the proportions of blood samples obtained were 95–98% Table . The bloIn the intervention clinics, 98% of the counselling sessions were realized as intended and the mean durations of the sessions were as intended Table . All priUsing the 5-point scale, the PHNs of the intervention clinics scored the training for study arrangements 3.4 (sd 1.2), physical activity counselling 3.9 (sd 1.1) and dietary counselling 3.6 (sd 1.1) on average. The PHNs of the control clinics scored the training for study arrangements 3.9 (sd 0.7) on average. Nearly all PHNs regarded the training and the support during the study as sufficient and the researchers' visits to the clinics as useful.The PHNs of the intervention clinics considered the increased knowledge on physical activity and diet and the improved counselling skills to be the major advantages of the study for them. The PHNs of the control clinics appreciated the training they were promised after the study. The major disadvantage reported by the PHNs was that implementation of the study protocol took too much time. The extra time needed for the visits was 40–60 min/visit in the intervention clinics and 10–20 min/visit in the control clinics on average.We evaluated whether a study protocol aiming at preventing excessive gestational weight gain and postpartum weight retention could be feasibly implemented in the Finnish maternity and child health care system. Integrating a study protocol into the routine functions of primary health care is a demanding task, but we managed to implement the protocol mostly as intended.The overall participation rate was high (77%) and the drop-out rate low (15%). Data on weight development, diet and physical activity was collected very successfully. The proportion of blood samples obtained was extremely high, indicating that collection of this kind of material is possible in studies conducted in real health care settings. In the intervention clinics, almost all counselling sessions were realized as intended and most participants recorded their adherence to the physical activity and dietary plans regularly to their follow-up notebook. This success reflects the PHNs' and the participants' strong commitment to the study, possibly because they were able to see the importance of the study and to see some personal benefits compensating the burden.Although the main experiences were positive, some problems were encountered. The recruitment time needed to be prolonged because the recruitment of the participants was slower than expected. The experience helps in estimating the realistic time needed for recruitment in further studies. The participation rate was slightly lower in the intervention clinics than in the control clinics, which may be related to the participants' background characteristics, to their reluctance to improve or monitor their dietary and physical activity habits or to the PHNs' motivation to recruit participants. In further studies, the way in which study is introduced to the participants and how they are motivated to participate in it will be especially important.The drop-out rate was higher in the intervention MCs than in the other clinics, but the reasons for drop-out seemed quite plausible in all clinics. Pregnancy is often associated with changing residence and, consequently, clinics. For some women who changed residence, we managed to collect the follow-up questionnaires and the maternity cards by mail, thus preventing them dropping out of the study. Some women withdrew for reasons related their pregnancy (such as twin pregnancy or risk for premature delivery) or a stressful life situation. Additionally, as postpartum weight retention was the main outcome for postpartum participants in the effectiveness analyses, we had to exclude women who were pregnant again 10 months after their first delivery. On the other hand, the drop-outs related to the missing blood samples actually occurred due to misunderstanding because the participants would have been allowed to continue the study despite not giving the blood samples. Some participants in the intervention clinics withdrew because they found the data collection too burdensome. Therefore, the amount of data collection should be paid more attention in further studies. For this pilot study, we collected feasibility information, which may not be necessary in further studies.Although the other data collection was successful, NAF samples were obtained from only 41% of the postpartum participants. The sample could not be obtained from women who were still breastfeeding when the collection of the samples was finished. Further studies should allocate a longer time period for collection of NAF samples. As NAF samples are not routinely collected in health care, some women may have been suspicious or afraid of giving them. To minimize the number of women refusing to give the sample, the methods of collecting NAF sample should be described in detail to the participants beforehand. However, the most frequent reason for a missing NAF sample was that no NAF could be obtained from the breast despite attempts. Other studies have also reported difficulties in obtaining NAF . TherefoThe average participation percentage in the group exercise sessions was relatively low, especially among the pregnant participants. No information is available on the reasons why the women did not participate more often. The reasons have been discussed earlier  and theyThe quality and adequacy of training of the PHNs will be of crucial importance in future studies, since the PHNs regarded the increased knowledge about physical activity and diet as well as improved counselling skills as the major advantage of participating in the study. However, as the PHNs found that the implementation of the study protocol was time-consuming, the time spent on study arrangements and all paper flow should be kept to a minimum in further studies. A risk group approach should also be considered to limit the PHNs' workload and to better target counselling at those in need. Allocating shorter times for counselling may impair the effectiveness of the intervention.A major strength of the study was that the counselling was implemented during routine visits to primary health care instead of using extra study personnel. Using this approach, we also aimed at developing counselling practices, which could be incorporated into real health care situations. Safety issues are especially important when implementing interventions among pregnant and postpartum women. Therefore, another major strength of the study was that no statistically significant differences were observed in the incidence of selected adverse events between the intervention and the control groups . Nor werOne limitation of the pilot study was that we were not able to randomize the clinics, which may have caused some baseline differences between the participants of the intervention and the control clinics ,20. HoweImplementation of the study protocol proved to be feasible in this setting, which encourages the undertaking of a large study in Finland and possibly also in other countries with maternity and child health care services funded by public taxation . Such beThe authors declare that they have no competing interests.TIK participated in the development of the study design and the intervention protocols  and in the acquisition and analysis of the data. MA participated in the development of the study design and the intervention protocols  and in the acquisition of data. PK and EW were involved in the development of the study design. KO participated in the development of the intervention protocols (group exercise sessions) and in the acquisition of the data. KM participated in the development of the intervention protocols (laboratory issues) and in the acquisition of the data. MF was involved in the development of the study design and the intervention protocols. RL was the principal researcher and responsible for the study concept and design and she participated in the development of the intervention protocols. All authors participated in the interpretation of the data and preparation of the manuscript. Additionally, all authors have read and approved the final manuscript.The pre-publication history for this paper can be accessed here:


Obesity is a major cause of preventable death in Australia with prevalence increasing at an alarming rate. Of particular concern is that approximately 68% of men are overweight/obese, yet are notoriously difficult to engage in weight loss programs, despite being more susceptible than women to adverse weight-related outcomes. There is a need to develop and evaluate obesity treatment programs that target and appeal to men. The primary aim of this study is to evaluate the efficacy of two relatively low intensity weight loss programs developed specifically for men.2); no participation in other weight loss programs during the study; pass a health-screening questionnaire and pre-exercise risk assessment; available for assessment sessions; access to a computer with e-mail and Internet facilities; and own a mobile phone. Men were recruited to the SHED-IT  study via the media and emails sent to male dominated workplaces. Men were stratified by BMI category  and randomised to one of three groups: (1) SHED-IT Resources - provision of materials  with embedded behaviour change strategies to support weight loss; (2) SHED-IT Online - same materials as SHED-IT Resources plus access to and instruction on how to use the study website; (3) Wait-list Control. The intervention programs are three months long with outcome measures taken by assessors blinded to group allocation at baseline, and 3- and 6-months post baseline. Outcome measures include: weight (primary outcome), % body fat, waist circumference, blood pressure, resting heart rate, objectively measured physical activity, self-reported dietary intake, sedentary behaviour, physical activity and dietary cognitions, sleepiness, quality of life, and perceived sexual health. Generalised linear mixed models will be used to assess all outcomes for the impact of group , time  and the group-by-time interaction. These three terms will form the base model. 'Intention-to-treat' analysis will include all randomised participants.The study design is an assessor blinded, parallel-group randomised controlled trial that recruited 159 overweight and obese men in Newcastle, Australia. Inclusion criteria included: BMI 25-40  Obesity is a major cause of preventable death and is associated with a range of negative physiological and psychological consequences . In addiGut-Buster study was unique when published 14 years ago /height[m]Waist circumference was measured at two points: (i) level with the umbilicus, and (ii) at the largest circumference between the lower costal border and the umbilicus. Two measures were taken at each site, with accepted values within 0.5 cm. Further measures were taken if measurements were outside the acceptable range. The average of the two acceptable measures will be reported. To ensure follow up measurements were taken from the same location, the distances between the sternal notch and both waist circumference points were recorded. Each measurement was recorded with a non-extensible steel tape . This measure will be taken at each time point by one of two assessors with Level 1 Anthropometry qualifications to improve reliability.Blood pressure and resting heart rate were measured using NISSEI/DS-105E digital electronic blood pressure monitors  under standardised procedures. Participants were seated for five minutes before the first blood pressure measurement and a rest period of two minutes between measures was used. Blood pressure was measured three times. Further measurements were taken if the blood pressure or resting heart rate values fell outside of the acceptable ranges i.e. Systolic within 10 mmHg, diastolic within 10 mmHg (preferably 5 mmHg) and resting heart rate within 5 bpm. The mean of the two closest systolic pressures and the diastolic pressure paired to them will be reported. The mean of the two lowest resting pulse pressures will be used.Bioimpedance was used for the assessment of body composition, including fat mass, fat free mass and total body water. Body composition was assessed by the InBody720 , a multi-frequency bioimpedance device featuring an eight-point tactile electrode system. This device has been shown to be a valid and reliable device for body composition assessment ,36.Physical activity was objectively measured using pedometers . Participants were sent pedometers in the mail 1-2 weeks prior to the baseline assessment and will be provided with the pedometer at follow-up assessments. Participants were instructed on how to attach the pedometers (at the waist on the right hand side) and asked to remove the pedometers only when sleeping, when the pedometer might get wet  or during contact sports. Participants were asked to wear the pedometers for seven consecutive days and keep to their normal routine. At the end of the day participants were instructed to record their steps on a pedometer record sheet and reset their pedometers to zero. Participants were instructed to note down if they did an activity like cycling, swimming, contact sports or another activity that does not involve stepping and include details (type of activity and duration), or if they forgot to wear their pedometer. Participants will be included in all analyses if they have completed at least four weekdays of pedometer monitoring. The average of existing days will be imputed for participants who have included at least four days of data.Dietary intake was assessed using the Australian Eating Survey (AES). AES is a 120-item semi-quantitative Food Frequency Questionnaire (FFQ), used previously in Australian youth up to 16 years  and currNutrient intakes from the AES will be computed from the most current food composition database of Australian foods available, the Australian AusNut 1999 database (All Foods) Revision 17 and AusFoods (Brands) Revision 5  to generate individual mean daily macro-and micro-nutrient intakes. The AES includes questions about the total number of daily serves of fruit, vegetables, bread, dairy products, eggs, fat spreads, sweetened beverages and snack foods, as well as asking the type of bread, dairy products and fat spreads used. Twelve questions relate to food-related behaviours, including items on frequency of take-away food consumption and eating while watching television.Portion size was assessed using portion size photographs from the Dietary Questionnaire for Epidemiological Studies Version 2 (DQES v2), FFQ from the Cancer Council Victoria . These pAlcohol consumption was measured using an adaptation of the Australian Government Department of Veteran Affairs, Alcohol Use Disorders Identification Test (AUDIT) 2009 . This inPhysical activity and nutrition beliefs were assessed using a number of validated instruments: physical activity self efficacy , physicaSedentary behaviours were assessed using an adaptation of the Sitting Questionnaire, which has been shown to be both a valid and reliable measure of sitting time in various domains ,52.Quality of Life and general health was assessed using the UK short form 12 (SF-12) questionnaire ,54.Daytime Sleepiness was assessed using the Epworth sleepiness scale which is a valid measure of general daytime sleepiness .Sexual Function was assessed using the International Index of Erectile Function-5 (IIEF-5) questionnaire which has been shown to be a valid measure of erectile function .Adherence to self-monitoring  will be calculated from diaries for both treatment arms. In addition to this, men will hand in their SHED-IT support booklet at the 3- and 6-month time points, to be photocopied and posted back. We will also administer a detailed process questionnaire to examine men's perceptions of the SHED-IT program. This will include scales, individual items and open-ended questions that require men to describe the strengths and weaknesses of the program along with their suggestions for improvement. The process evaluation will cover issues such as the study feasibility, opinion of the allocated study group, use and appraisal of components of each intervention and their levels of overall satisfaction. We will also ask how much participants would be willing to pay for the offered intervention. The process evaluation will be administered at the 6-month time point.The sample size calculation is based on the primary outcome of weight loss at 6 months, which we have assumed will have a standard deviation of 5 kg ,57. ThirParticipants were randomised at an individual level by the trial statistician who will not have any contact with participants during the trial. Allocation was stratified by BMI category calculated at the baseline assessment  and the allocation sequence within strata was generated by a computer-based random number-producing algorithm in block lengths of six. Randomisation codes are stored in a restricted computer folder, which is not accessible by those assessing participants, those involved in group allocating participants or those participating in data entry for the study. Complete separation was achieved between the statistician who generated the randomisation sequence and those who concealed allocation from those involved in implementation of assignments.Study information for the three different groups was pre-packed into identical black plastic opaque envelopes and consecutively numbered within the three BMI categories and ordered according to the randomisation schedule. The packing and sequencing of these envelopes was completed by a research assistant who was not involved in enrolment, assessment or allocation of participants. Study participants completed all baseline assessments before proceeding to a separate room to meet with a research assistant who was not involved with the baseline assessments. The allocation sequence was concealed during this process. Participants' BMI category was calculated from the baseline measurements and the participant was allocated the next available number in that BMI category before being provided with their information pack. At this point the envelope was opened by the research assistant and details of the particular information pack were provided to the participant using a standardised protocol.Randomisation was undertaken by the trial statistician and measures will be taken by trained staff at all times points. In order to ensure accurate and consistent measurements, the study weight scale was professionally calibrated and the height scale checked and recalibrated daily before measurements commenced. All assessments were completed by staff blinded to treatment allocation. When men are contacted (via phone and email) to book in for follow-up assessments they will be asked not to inform data collection personnel of their group allocation. Data will be entered by research assistants blind to group allocation and a program of plausibility checks will be used to identify unrealistic values. The primary outcome measure (weight) will be double entered to ensure accuracy and a random 20% sample of all other measures will also be double entered.t tests for continuous variables and chi-squared (χ2) tests for categorical variables. The significance level for the comparison of baseline characteristics will be set at 0.05.Analyses will be performed using Stata Version 11 or later. All variables will be checked for plausibility and missing values. Data will be presented as mean (sd) for continuous variables and counts (percentages) for categorical variables. Differences between groups at randomisation and characteristics of completers versus dropouts will be tested using independent Resources vs. Control; Online vs. Control; and Resources vs. Online). The independent variables in the model will include a variable for treatment group, time  and the group-by-time interaction. The model will also include a term for the stratifying variable of BMI group at baseline. The coefficient and p-value for the group-by-6 month interaction term will be used to determine the efficacy of the interventions. Similar models will be used to examine differences in change in other outcome measures.A series of Generalised Linear Mixed Models (GLMMs) with a random intercept for individual will be used to test for differences between treatment groups in the mean level of weight after treatment. Separate models will be fit for each of the pair-wise comparisons  and of interest will be the 3 way interaction of treatment group by time by SES. We will also examine a range of secondary outcomes to support the primary outcome . Additional exploratory models will be fitted to examine if the men who have the greatest reduction in weight are also those who have the greatest improvements in the secondary outcomes.Statistical significance of the primary efficacy analysis (3 pair-wise comparisons) will be based on Hochberg's multiple testing procedure with the family wise error rate held at 5%. All secondary hypothesis tests will be performed using a 2-sided 5% significance level. In addition, linear regression and GLMMs will be used to describe relationships among the various dependent and independent variables.Online and Resources component. Men who complied well with the assigned treatment, defined as completion of requested daily eating and exercise diaries (n >40) over the 3-month period and weekly check-ins (n >10). Results of the per-protocol group will be compared with non-compliers in each group i.e. those who did not meet the above adherence recommendations.A per protocol analysis will also be conducted and include men who complied with treatment from the The aim of this study is to evaluate the efficacy of two 'low dose' weight loss programs developed specifically for men that could be widely and inexpensively implemented throughout Australia. We will determine whether these innovative approaches to obesity treatment will result in greater initial weight loss and improvements in cardiovascular risk factors compared to a Control group in a community sample of overweight men. There is an urgent need to develop and evaluate novel approaches to weight loss that attract and engage large numbers of men. We will also determine whether web-based support is more effective than resources alone. This study is designed to address the gap in service provision of community-based programs for overweight and obese men. There is limited evidence to guide the design of effective obesity treatment programs for overweight men that would be sustainable in most health care settings that do not require multiple visits to treatment centres.Our trial targets a national health priority in Australia and focuses on a high-risk under studied population. To successfully combat the obesity epidemic, clinicians and health care systems require feasible, effective and evidence-based treatment options that can be provided to large numbers of men. This randomised controlled trial will test alternative, evidence-based and theoretically driven, easily disseminated strategies specifically for weight loss in men. The interventions are all designed so they could serve as prototypes for rapid translation of research findings into widely available practical applications and widespread implementation in both the public health and medical care sectors. If successful, this project will reduce the negative health, economic and social consequences of obesity through clinically meaningful risk reduction in large numbers of overweight men.The authors declare that they have no competing interests.The study chief investigators PJM, RC, CEC, PM, RCP and Associate Investigator JMW were responsible for identifying the research question, design of the study, obtaining ethics approval, the acquisition of funding and overseeing study implementation. Associate Investigator TB and research assistants NB, MDY, EJA and KLS have contributed to development of intervention materials, recruiting participants and/or study implementation. All authors were responsible for the drafting of this manuscript and have read and approved the final version.The pre-publication history for this paper can be accessed here:http://www.biomedcentral.com/1471-2458/10/701/prepub


A 36-year-old man presented with headache and right upper and lower limb weakness for 10 days. MRI revealed absence of the odontoid process of the C2 vertebral body, with resultant atlantoaxial dislocation along with myelomalacic changes involving the cervicomedullary junction. Developmental anomalies of the odontoid are uncommon. The clinical importance lies in their potential to cause serious neurological complications due to atlantoaxial instability.We report a case of congenital absence of the dens, with resultant atlantoaxial dislocation and partial fusion of the C2 and C3 vertebrae.A 36-year-old man presented with a history of minor trauma to the head following a sudden jerk while traveling in a bus. He complained of headache and right upper and lower limb weakness. On examination, power in the right upper and lower limbs was 4/5. The right plantar reflex was extensor. No sensory deficit or bladder/bowel involvement was seen.MRI of the brain and the cervical spine was performed, which revealed absence of the odontoid process of the C2 vertebra , with reCongenital anomalies involving the craniovertebral junction are clinically important because of their potential for producing serious neurological deficits. The clinical features are chiefly because of the associated atlantoaxial dislocation and include persistent neck pain, headache, and transient/permanent paresis. Often, pCongenital anomalies involving the odontoid process are rare. They can be classified into os odontoideum, ossiculum terminale, aplasia-hypoplasia, and duplThe development of the axis is complex . Four osIn our case, the dens itself, as well as the part of the dens assimilated by the body of C2, was absent , the latAnomalies of the odontoid can usually be diagnosed on a standard series of radiographs, plus flexion and extension lateral films. With the increasing importance of CT scan and MRI in the study of the craniovertebral junction, a detailed evaluation of such congenital anomalies is now possible, as demonstrated in our case.The first case of odontoid hypoplasia was reported by Roberts in 1933. Since th


Henipavirus, are zoonotic paramyxoviruses that have been associated with sporadic outbreaks of severe disease and mortality in humans since their emergence in the late 1990s. Similar to other paramyxoviruses, their ability to evade the host interferon (IFN) response is conferred by the P gene. The henipavirus P gene encodes four proteins; the P, V, W and C proteins, which have all been described to inhibit the antiviral response. Further studies have revealed that these proteins have overlapping but unique properties which enable the virus to block multiple signaling pathways in the IFN response. The best characterized of these is the JAK-STAT signaling pathway which is targeted by the P, V and W proteins via an interaction with the transcription factor STAT1. In addition the V and W proteins can both limit virus-induced induction of IFN but they appear to do this via distinct mechanisms that rely on unique sequences in their C-terminal domains. The ability to generate recombinant Nipah viruses now gives us the opportunity to determine the precise role for each of these proteins and address their contribution to pathogenicity. Additionally, the question of whether these multiple anti-IFN strategies are all active in the different mammalian hosts for henipaviruses, particularly the fruit bat reservoir, warrants further exploration.Hendra and Nipah virus, which constitute the genus  HeV wasus (NiV) . Humans us (NiV) . In humaus (NiV) . HeV andaviruses ,6. In Baaviruses . In addi2.2.1.Paramyxovirinae subfamily, extend the coding capacity of their genome via an mRNA editing mechanism that gives rise to multiple proteins from the P gene. During transcription of the P gene the polymerase stutters at a run of A and G residues referred to as the editing site and this results in the addition of non-templated G residues into the nascent mRNA. An unedited henipavirus P mRNA encodes the phosphoprotein (P), which participates in viral RNA synthesis as a cofactor for the polymerase. The insertion of one extra G residue shifts the frame and this mRNA encodes the V protein  and NiV P (Ser-240 and Ser-472) . It is n2.3.The fourth protein encoded by the henipavirus P gene is the C protein, which is expressed from an alternate ORF present in P, V and W transcripts. This 18 kDa protein localizes to the cytoplasm in a punctate pattern and it can be detected at low levels in NiV virions . Interes3.Cellular detection of virus infection is the trigger for initiating synthesis of IFN-β, and the molecules described to serve as cytoplasmic sensors for RNA viruses are RIG-I and mda-5 ,24. The 3.1.Paramyxovirus V proteins limit the synthesis of type I IFN via a highly conserved mechanism . A studyThe V proteins are notably unable to interact with or inhibit signaling from the related RNA helicase, RIG-I . Due to 3.2.Like the V protein, the W protein of NiV can also prevent activation of the IFN-β promoter that is triggered by virus or intracellular dsRNA . As W ha4.Both type I (α/β) and type II (γ) interferons (IFN) mediate their effects on cells by binding to receptors on the cell surface and activating the JAK-STAT signaling pathway . STAT S. The act4.1.In the presence of either NiV P, V or W proteins, there are reduced levels of tyrosine 701 phosphorylated STAT1 in IFN-α/β-treated cells ,18. ThisIn an unstimulated cell STAT1 shuttles between the cytoplasm and nucleus but upon IFN treatment, the phosphorylated and dimerized form translocates to the nucleus. In cells that are expressing P and V proteins, STAT1 is retained exclusively in the cytoplasm in its inactive, non-phosphorylated form even in the presence of IFN-α/β or IFN-γ ,16,18. T4.2.As suggested by the strong co-localization data, the P, V and W proteins can all interact with STAT1 ,15–18. Tet al. [The STAT1 binding domain lies within the N-terminal portion of P, V and W ,15,17. Fet al.  examinedet al. . Mutatioet al. . Intereset al. . For botet al. .KO and CKO/G121E viruses display identical growth properties in both 293T and Vero cells, although interestingly both are attenuated relative to the wild-type NiV. Crucially, infection with the CKO/G121E virus induces STAT1 phosphorylation in response to IFN-β whereas WT and CKO viruses do not [KO/G121E infected cells in response to IFN. In contrast the inactive form of STAT1 remains sequestered in the nuclei of NiV WT and CKO infected cells. As mentioned earlier, these data suggest that the nuclear W protein is functioning as the main obstacle to IFN signaling and that this is abolished by the G121E mutation, which eliminates the STAT1 interaction. The finding that the recombinant NiV lacking STAT1-binding has identical growth properties to its CKO parent virus, even in 293T cells , indicates that the lack of STAT1 inhibition is not detrimental to the virus. This suggests that additional anti-IFN mechanisms encoded by NiV are probably still intact. These could be either V-mediated inhibition of mda-5, W-mediated inhibition of IRF3 activity in the nucleus, or both acting in concert.In order to verify the importance of the residues conferring STAT1-binding within the context of the whole virus, it was necessary to determine whether they were also required for the polymerase co-factor function of the P protein. Using a NiV mini-genome assay to assess polymerase function, it was shown that the critical region for RNA synthesis lies within amino acids 81–113 of the P protein and that substitutions that affect STAT1 binding do not interfere with polymerase activity ,21. Thiss do not . Also, net al. [To date, only the V protein has been reported to interact with STAT2 ,18,36. Tet al.  also demCurrently, there is limited information regarding the region of STAT1 that interacts with the NiV proteins. The domain structure of STAT1 can be broadly divided into an N-terminal domain, a coiled-coiled region, a DNA-binding domain, a linker domain, an SH2 domain and a transactivation domain . Using a5.KO virus which has attenuated growth properties relative to the wild-type virus [Of all the henipavirus P gene products, we know the least about the C protein. Plasmid-based expression of the NiV C protein has been shown to prevent the induction of a robust antiviral response  but the pe virus . The facpe virus .6.In conclusion, through their unique coding strategy, henipaviruses produce multiple proteins that antagonize the antiviral response at multiple levels. While the shared N-terminal domains of the P, V and W proteins direct inhibition of STAT signaling, the C-terminal domains of the V and W proteins confer unique properties on these proteins that extend their antagonist function. For V this involves mda-5-binding and for W this involves nuclear localization and the ability to block a late stage of the IFN induction pathway. The question of whether all these mechanisms are active in an infected cell is something that still needs to be explored. Unfortunately the need for biosafety level 4 conditions has limited this work but the description of a reverse genetics system for NiV opens the door to addressing the contribution of each protein and/or mechanism. Another factor to consider is that the presence of multiple anti-IFN mechanisms may relate to the zoonotic nature of these viruses. Even though it has already been shown that the NiV V protein can prevent IFN signaling in cells from multiple species , some of


Intimate partner violence (IPV) is a significant public health problem. There is a lack of data on IPV risk factors from longitudinal studies and from low and middle income countries. Identifying risk factors is needed to inform the design of appropriate IPV interventions.Data were from the Rakai Community Cohort Study annual surveys between 2000 and 2009. Female participants who had at least one sexual partner during this period and had data on IPV over the study period were included in analyses (N = 15081). Factors from childhood and early adulthood as well as contemporary factors were considered in separate models. Logistic regression was used to assess early risk factors for IPV during the study period. Longitudinal data analysis was used to assess contemporary risk factors in the past year for IPV in the current year, using a population-averaged multivariable logistic regression model.Risk factors for IPV from childhood and early adulthood included sexual abuse in childhood or adolescence, earlier age at first sex, lower levels of education, and forced first sex. Contemporary risk factors included younger age, being married, relationships of shorter duration, having a partner who is the same age or younger, alcohol use before sex by women and by their partners, and thinking that violence is acceptable. HIV infection and pregnancy were not associated with an increased odds of IPV.Using longitudinal data, this study identified a number of risk factors for IPV. These findings are useful for the development of prevention strategies to prevent and mitigate IPV in women. Violence against women is a serious and common human rights and public health problem, which causes significant morbidity and mortality worldwide . IntimatKnowledge of context-specific risk factors for IPV is important to be able to appropriately focus prevention efforts. A recent World Health Organization (WHO) review noted the lack of data on IPV risk factors from longitudinal studies and from low and middle income countries . This bri.e. communities which lack legal sanctions and where women lack access to shelters and family support, and in which there is less moral pressure for neighbours to intervene if a woman is beaten). Societal level factors are divorce regulations, a lack of legislation on IPV within marriage, protective marriage laws, and traditional gender and social norms [The WHO review identified risk factors for IPV and classified them into the four levels of an ecological framework: individual, relationship, community and societal levels factors . Individal norms .i.e. not legally or formally married) compared to being married, being married compared to having a boyfriend or other casual partner, having a partner who consumed alcohol before sex, and a woman perceiving her partner to have a higher risk of HIV infection were risk factors for IPV [Recent cross-sectional studies of women in sub-Saharan Africa have identified some of these same risk factors for IPV -6, as we for IPV ,8.In this study, we aimed to identify risk factors for IPV in women of reproductive age in Rakai District, Uganda, using longitudinal data from seven survey rounds of the Rakai Community Cohort Study between 2000 and 2009. We assessed characteristics shown to be risk factors in other settings -6.Since 1994, the Rakai Health Sciences Program has followed an open cohort of about 12,000 participants aged 15 to 49 years in 50 communities in the Rakai district of southwestern Uganda. The cohort has been described in detail elsewhere . In brieWomen who participated in the study between 2000 and 2009 were included in analyses if they reported at least one sexual partner during the study period and if they had provided any data on whether they experienced IPV during the study period.Intimate partner violence (IPV) was defined as any physical, sexual, or verbal violence by a partner in an intimate relationship. Questions on IPV were modified from the Revised Conflict Tactics Scales (CTS2), and, in some analyses, type of IPV was classified as minor or severe as per the CTS2 ,12. Minoi.e. in childhood or in early adulthood) and contemporary factors defined as variables that may affect women in their current lives. These two groups of variables were analysed separately.Potential risk factors for IPV were determined based on the literature and on which data were collected for the RCCS between 2000 and 2009. Since characteristics and experiences in early life may cause some of the characteristics and experiences in adulthood, and specifically, risk factors for IPV in adulthood may be on the causal pathway from early factors to IPV , risk vai.e. from the first round of participation during the period under study.Early factors included sexual abuse in childhood or adolescence , age at Contemporary factors included demographic variables such as age -21,23-25For participants who reported multiple partners in the past year, data about the partner with whom the participant reported having had sex most recently was used for the variables type of relationship with partner, alcohol use by partner, length of sexual partnership, and difference in age with partner; it was not possible to determine which specific partner (if any) had perpetrated violence.The prevalence of IPV and of potential IPV risk factors was assessed. To identify early factors, logistic regression was used to estimate the bivariate and multivariable odds ratios (OR) and 95% confidence intervals (95% CI) associated with violence during the period of study participation. For contemporary factors, population-averaged logistic regression models were used to look at bivariate and multivariable associations , which aa priori as being of greater importance on the basis of known associations with violence, including sexual abuse in childhood or adolescence, coerced first sex, and education for early factors, and age, marital status, pregnancy status, difference in age with partner, use of alcohol, number of partners in past year, and attitudes toward violence for contemporary factors [i.e. age at first sex for early factors and beginning with relationship type for contemporary factors, until the first variable was encountered with a p value of p < 0.1, either by Wald test or by likelihood ratio test, depending on whether the variable was continuous, binary, or categorical.For each of early factors and contemporary factors, since there were multiple predictors of interest and to minimize the risk of Type I error of conventional backward selection models, an Allen-Cady modified backward selection procedure was used for the multivariable models . Candida factors ,27,32. ASeparate models were run to look at the associations between contemporary factors and risk of violence in the same year, in consideration of the fact that certain associations, such as the temporal association between pregnancy and violence, might not be adequately captured when looking at exposure and outcome data from sequential years. Analyses were done using Stata 12.During the period under study, the Rakai Community Cohort Study was approved by institutional review boards at the Scientific and Ethics Committee of the Uganda Virus Research Institute, the Uganda National Council of Science and Technology, Columbia University, Johns Hopkins University, Johns Hopkins Bloomberg School of Public Health, and the Western. Ethics approval was obtained for this analysis from the University of Toronto.Of the 20584 women who participated in the study over this period, 15081 (73.3%) were included in these analyses. One hundred twenty women were excluded because they were younger than 15 or older than 49 during the entire period under study, four women were excluded because they had a positive HIV test result and subsequent negative tests, 3228 women were excluded because they were not sexually active during the study period, and 2151 were excluded because they did not have any data on IPV during the study period.IPV was common in this population, as shown in Table Most women (66%) who experienced any violence experienced more than one form of violence concurrently. In the most recent survey round of participation for the 4367 women who reported any IPV, 1064 women (24.4%) reported experiencing verbal violence only, 322 (7.4%) reported sexual violence only, and 94 (2.2%) reported physical violence only. Six hundred eighty-three women (15.6%) experienced verbal and physical violence only, 218 (5.0%) women reported verbal and sexual violence only, and 443 (10.1%) reported physical and sexual violence only, while 1289 women (29.5%) reported all three forms of violence.Women commonly experienced violence early in life, with 31.3% of 1784 women reporting sexual abuse in childhood or adolescence and 17.5% of 11607 reporting coerced first sex, as shown in Table In bivariate analyses, as shown in Table The frequency of characteristics and behaviours was examined, as shown in Table Table Multivariable models of the association between contemporary factors in the current year and IPV in the current year revealed qualitatively similar associations (data not shown). Of note, pregnancy was not a risk factor for violence in the same year, and in fact was associated with a lower risk of IPV with an odds ratio of 0.91 .As found in diverse international studies, IPV is prevalent in this population and most women who experienced IPV reported experiencing more than one form of violence concurrently. Several of the risk factors identified in this longitudinal study are consistent with existing evidence , includie.g. which types of IPV were measured, may affect estimates of association. In this study, data on physical, verbal, and sexual IPV were included, however, there were no data collected on controlling behaviours, which could affect the magnitude of association identified if controlling behaviours were associated with pregnancy independently of other forms of IPV. Finally, the finding of a lack of association could reflect effect modification on the basis of geographical or cultural contexts, i.e. that the association between pregnancy and IPV may only exist in certain contexts.In contrast with much of the literature on risk factors for IPV , but coni.e. that prevalent and incident cases of HIV and IPV were included in the exposure and outcome, respectively, the types of IPV included as noted above, or the period in which the exposure and outcome were measured (i.e. one year), which may not reflect the relevant period of exposure for this association; the inclusion and control of relevant confounders; or that HIV leading to IPV is not a significant pathway in this population.Another notable finding of this study is that HIV infection was not associated with IPV in the subsequent year, with an unadjusted odds ratio of 1.02  and an adjusted odds ratio of 1.03 . In other population-based studies from East Africa, one cross-sectional study  and one The strengths of this study are its large size, high participation rates, prospective design, the inclusion of several important variables as potential predictors, the separation of early and contemporary factors in analyses, and the focus on a low income country. There are several limitations to this study. Some risk factors which may be relevant were not included in the analyses because data were not available, such as number of children, income level, and the gap in income and education between partners, which may result in residual confounding of the associations between examined variables and IPV. Some variables may not specifically identify risky behaviour, for example the use of any alcohol before sex as opposed to heavy alcohol use or more general problematic alcohol consumption, which may dilute any association and bias the estimate of the effects of problematic alcohol use toward the null. The questions on IPV were modified from the CTS2, however, this version of the scale has not been validated in this population, which could contribute to measurement error. Also, as noted earlier, no data were collected on controlling behaviours as part of the definition of IPV, which could lead to an underestimate of associations. For contemporary factors, the exposure period was assumed to be the year prior to IPV, and for early factors, only IPV during the period under study was examined. In fact, the relevant exposure period for contemporary factors may be longer or shorter than a year, and for both early and contemporary factors, may take place closer to or further from any IPV incidents; these temporal relationships have not yet been well defined. Since we did not assess the role of early and contemporary factors together in one model, we are unable to determine whether contemporary factors are on the causal pathway between early factors and IPV, as hypothesized, or, in the event that contemporary factors are not in the causal pathway between early factors and IPV, whether early or contemporary factors are more strongly associated with experiencing IPV. Finally, it was not possible to discern whether data on violence were relevant to a specific partner for women who had more than one partner, however, this would not likely affect the validity of the results since consistently fewer than seven percent of women had more than one sexual partner in each survey round.i.e. sexual abuse in childhood or adolescence, lower levels of education, forced first sex, younger age, alcohol use by women and their partners, being in a relationship of shorter duration and thinking that violence is acceptable. The data also suggest that several hypothesized risk factors may not be associated with IPV, i.e. pregnancy and HIV positivity. Finally, the analysis also identifies novel risk factors for IPV in this setting, i.e. younger age at first sex, coerced first sex, and having a partner the same age or younger. These findings are likely generalizable to other rural areas in sub-Saharan Africa and potentially elsewhere, and have direct implications for public health action in terms of the primary and secondary prevention of IPV.In summary, this analysis confirms that certain established risk factors from other settings are associated with IPV in this setting, There are diverse approaches to addressing violence against women , and theThe authors declare that they have no competing interests.FK developed the research question and protocol, conducted analyses, and drafted the manuscript. LC, SB, and PO contributed to the analysis and interpretation of data. RG and JK were involved in the conception and design of the study, acquisition of data, and analysis and interpretation of data. DS, FN, GK, and MW were involved in conception and design of the study, and acquisition of data. All authors revised the manuscript and approved the final draft.The pre-publication history for this paper can be accessed here:http://www.biomedcentral.com/1471-2458/13/566/prepub


About 50% of patients in substance abuse treatment with a partner perpetrated and/or experienced intimate partner violence in the past year. To date, there are no screeners to identify both perpetrators and victims of partner intimate violence in a substance abusing population. We developed a 4 item screening instrument for this purpose, the Jellinek Inventory for assessing Partner Violence (J-IPV). Important strengths of the J-IPV are that it takes only 2 minutes to administer and is easy to use and to score.To investigate the validity of the J-IPV, two independent studies were conducted including 98 and 99 participants, respectively. Aim of the second study was to cross-validate findings from the first study. Psychometric properties of the J-IPV were determined by calculating sensitivity, specificity, positive and negative predictive value, and positive and negative likelihood ratio’s by comparing J-IPV outcomes to outcomes on the Revised Conflict Tactics Scales (‘gold standard’). Also, receiver operator characteristics (ROC)-curves were determined to weight sensitivity and specificity as a result of different J-IPV cutoffs, and the area under the curve (AUC) was calculated.any as well as severe intimate partner violence. Results from the second study replicated findings from the first study.Results of the first study demonstrated that the J-IPV possesses good psychometric properties to detect perpetrators and victims of We recommend administering the J-IPV to patients entering substance abuse treatment. If perpetrators and victims of partner violence are identified, action can be taken to stop IPV perpetration and arrange help for victims, for example by offering perpetrators treatment or by providing safety planning or advocacy interventions to victims. Consequences of physical IPV can be severe for victims and may result in injuries, chronic pain, depression, posttraumatic stress disorder, suicidality, and substance use disorders ar e.g., .Because of the serious consequences of IPV and its high prevalence among patients in substance abuse treatment, it is important to assess IPV perpetration among these individuals. Ideally, IPV perpetrators should be identified at intake in order to prevent further assault of victims victimization of IPV in the past year; the latter two questions address perpetration of IPV in the past year  On the basis of the criteria described above we developed the 4 items counting Jellinek Inventory for assessing Partner Violence (J-IPV), a screener that takes only 2 minutes to administer, and is simple to use and score. The first two questions of the J-IPV address year see . The itell e.g., , it was To determine psychometric properties of the J-IPV for detecting 1) any IPV perpetration, 2) severe IPV perpetration, 3) any IPV victimization, and 4) severe IPV victimization, the following values were determined: 1) sensitivity , 2) specificity , 3) positive predictive value , and 4) negative predictive value  were computed. In addition, positive likelihood ratio  and negative likelihood ratio  were calculated as suggested, for example, by There are no universal criteria to determine the minimum standards of a screening instrument, since it depends on the situation whether greater value is attached to sensitivity or specificity The study was approved by the ethical committee of the University of Amsterdam (reference number 2010-kp-1350). Written informed consent was obtained from all participants.th 2011 and April 22nd 2011 in Amsterdam or between December 28th 2011 and October 17th 2012 in Hilversum. Patients were included if they 1) fulfilled DSM-IV-TR criteria for substance abuse or dependence (with the exclusion of nicotine dependence as the sole substance use disorder diagnosis), 2) had a partner for at least 3 months in the past year, 3) had sufficient knowledge of the Dutch language , and 4) were at least 18 years old. Patients were excluded in case of 1) severe withdrawal or intoxication symptoms during the intake, 2) severe mental illness , and 3) severe cognitive disorders, such as Korsakoff’s syndrome or dementia.The two studies were conducted at two different locations of Jellinek, a large substance abuse treatment facility, in Amsterdam (study 1) and Hilversum (study 2), the Netherlands. Patients were included if they had an intake between February 28The J-IPV is a 4 item-screening device that was developed to assess IPV perpetration in patients entering substance abuse treatment. FK formulated the items of the J-IPV and EV, AS, and PE independently reviewed the items; the final items were based on consensus. The questions are administered as a structured interview and questions are answered with ‘yes’ or ‘no’. Two native English speakers translated the J-IPV from Dutch into English. Translations were compared with one another and led to the final English version of the J-IPV see .physical IPV, we only used item pairs assessing physical violence (2×12 items). To make the transition to the physical violence items more gradual, firstly 3 items pairs addressing verbal violence were administered . Subsequently, the physical violence items of the CTS2 were administered in the same order in which they appear in the CTS2. The other CTS2 items were not used in this study. The physical violence items of the CTS2 were used to categorize participants as perpetrator and/or victim of any/severe physical IPV. Participants were rated as perpetrator of any IPV when answering ‘yes’ to at least one physical IPV perpetration item and were rated as victim of any IPV after at least one ‘yes’ to any of the physical IPV victimization items. Further, participants were classified as having perpetrated severe physical IPV or being victimized by severe physical IPV if at least one of the severe physical violence perpetration or victimization items was answered with “yes”. The adapted version of the CTS2 was administered as a structured interview, a method that was supported by The CTS2 The MATE During the intake, psychologists from the treatment staff who regularly conducted the intakes and were not involved in the factual studies administered the MATE. Subsequently, patients were informed about the study. If they agreed to participate, informed consent was obtained. Hereafter, the J-IPV and CTS2 were administered successively as structured interview. Since the aim of the study was to investigate whether the J-IPV predicted the outcome on the CTS2, we did not counterbalance administration of the J-IPV and CTS2. To help participants remember the 7-point rating scale of the CTS2, they were given a form with response categories written out. The first study was conducted at Jellinek Amsterdam; the second study at Jellinek Hilversum in order to cross-validate findings from the first study.Demographics of participants of the 2 studies were compared using chi-square tests for categorical variables ; an independent samples t-test for normally distributed continuous variables (age); and a Mann-Whitney test for nonnormally distributed continuous variables (relationship length). To determine psychometric properties of the J-IPV, sensitivity, specificity, PPV, NPV, LR+, LR−, and AUC were calculated for the J-IPV compared to the CTS2 as ‘gold standard’  only both J-IPV perpetration items were used (items 3 and 4) and 3) the separate items addressing IPV perpetration (items 3 and 4) were used. Psychometric properties of the J-IPV to detect any/severe IPV victimization were determined when 1) all J-IPV items were used, 2) only both J-IPV victimization items were used (items 1 and 2) and 3) the separate items addressing IPV victimization (items 1 and 2) were used. After determining psychometric properties for these different options, the optimal cutoff or scoring method was selected to classify participants as 1) perpetrator of any IPV, 2) perpetrator of severe IPV, 3) victim of any IPV, and 4) victim of severe IPV. As mentioned in the introduction, we valued high sensitivity and NPV the most important psychometric properties the J-IPV should possess because it might be harmful to overlook perpetrators and victims of IPV. Therefore, the following steps were taken to decide on the optimal cutoff or scoring method. First, it was examined which cutoff or scoring method resulted in highest sensitivity and NPV. Then, it was observed whether this scoring method also yielded the highest AUC, and finally it was examined whether specificity and PPV were still acceptable.Prior to the start of this study, the J-IPV had been used in clinical practice for 20 months. Clinical observations taught that some patients who had committed physical IPV but saw themselves primarily as victim (and not perpetrator), did answer positively to one or both victimization items, but not to any of the perpetrator items. This demonstrates that people tend to underreport IPV perpetration e.g.,  but alsoA total of 115 participants met inclusion criteria. Seventeen participants (14.8%) were excluded: 7 participants (6.1%) refused participation, 5 (4.3%) suffered from severe mental illness, 4 (3.5%) dropped-out because of logistic reasons, and 1 (0.9%) suffered from a severe cognitive disorder see . The finOn the basis of the CTS2, participants were classified as 1) no perpetrator, no victim, 2) perpetrator only, 3) victim only, and 4) both perpetrator and victim of physical IPV see . About hA total of 158 participants met inclusion criteria. Fifty-nine participants (37.3%) were excluded: 8 participants (5.1%) refused participation, 11 (7.0%) suffered from severe mental problems, 4 (2.5%) suffered from a severe cognitive disorder; 2 (1.3%) were severely intoxicated, 3 (1.9%) dropped-out because the intaker was not yet trained in administering the J-IPV and CTS2, and 31 (19.6%) dropped-out because of logistic reasons see . The finIn addition, as in study 1, participants were classified as (non) perpetrator and/or victim of IPV see . Again, 2 (2) = 6.21; p<.05). Standardized residuals indicated that more participants of study 1 had a non-European nationality than participants in study 2. In addition, participants of study 1 and 2 differed significantly form one another regarding relationship length (F (186) = 4.52; p<.05); participants of study 2 had significantly longer relationships than participants of study 1. Participants of study 1 and 2 did not differ significantly regarding gender, age, living together, relationship at the time of the intake, children under 18, treatment intensity, and primary substance use disorder diagnosis. In addition, there were no differences between the 2 studies regarding prevalence rates of any/severe past year IPV perpetration/victimization. Also, there were no differences in rates of reciprocality of IPV  psychometric properties of both J-IPV perpetration items (items 3 and 4) were calculated, and 3), diagnostic efficiency was calculated for items 3 and 4, separately (see any of the J-IPV items) resulted in highest sensitivity (.80) and NPV (.85) (the indicators that were decided to be most important to the J-IPV). Also, the largest AUC (.80) was obtained when all 4 J-IPV items were used. In addition, specificity (.80) and PPV (.75) were still acceptable for this option, as well as LR+ (4.17), and an LR− (.24). For study 2, similar results were found   see . For illTo detect severe IPV perpetration, using a cutoff of 2 resulted in optimal psychometric properties in study 1  psychometric properties of both J-IPV victimization items (items 1 and 2) were calculated, and 3) diagnostic efficiency fore detecting IPV victimization was calculated for the separate victimization items (1 or 2). A cutoff of 1 resulted in the most favorable psychometric properties . Similar results were obtained in study 2 . ROC-curves are displayed in Psychometric properties for detecting any physical IPV victimization using CTS2 victimization items as ‘gold standard’ are displayed in severe physical IPV victimization were determined  and NPV . In other words, 80/84% of IPV perpetrators screened positive for IPV perpetration on the J-IPV; after screening negative, 85/82% of the participants had indeed not committed IPV. 2) To detect severe IPV perpetration, optimal results were found for a cutoff of 2, which resulted in sensitivity and NPV of 1.00 in both studies. 3) To detect any IPV victimization, we recommend using a cutoff of 1, which resulted in highest sensitivity (.83 and.80) and NPV (.87 and.86). It is noticeable that the same cutoff was suggested for detecting any IPV perpetration; this could be explained by the fact that in about 70% of the cases IPV was reciprocal .The aim of the present study was to validate and cross-validate the J-IPV by determining its sensitivity, NPV, AUC, specificity, PPV, LR+, and LR−. It was decided that sensitivity and NPV, which we considered the most important properties of the J-IPV, should be at least ≥.80. Based on the results of the two studies, it is suggested to use the following cutoffs for the different purposes of the J-IPV. 1) To detect ocal see . 4) To dnot factually involved in severe IPV is preferred above missing patients who are indeed involved in severe IPV. Moreover, patients who screened positive for severe IPV but were in fact not involved in severe IPV, were likely involved in non-severe IPV. Finally, likelihood ratios, ranging from 4.17–8.33 (LR+) and from 0–.25 (LR−), demonstrated that participants who screened positive were 4–8 times more likely than patients who screened negative to have perpetrated/experienced any/severe IPV, and that after screening negative, the odds were 0–25% to have perpetrated/experienced any/severe IPV. In sum, two independent studies demonstrated that the J-IPV is a valid screener with sensitivities and NPV’s ≥.80 to detect IPV in patients in substance abuse treatment. The second study replicated results from the first study, despite differences in population , and despite the fact that the first study was conducted in a large city and the second in a smaller town. Although it was expected that the second study would perform less than the first study For the other psychometric properties, the following results were found for the different cutoffs. AUCs that varied between.84 and.94 indicated that there was an 84–94% chance that a randomly selected perpetrator/victim of any/severe IPV scored higher on the J-IPV than a randomly selected patient that did not perpetrate/experience any/severe IPV. Further, specificities ranged from.79–.88, indicating that 79–88% of factual non-IPV perpetrators screened indeed negative. PPV’s were found between.45–.80, indicating that 45–80% of all positive screening participants actually committed/experienced any/severe IPV in the past year. PPV’s of the J-IPV to detect severe IPV perpetration and victimization were on the low side . However, we do not consider this problematic. The J-IPV is developed to screen for IPV and to identify patients in whom IPV should be further assessed. We argue that additional assessment of IPV in patients who are not to study the predictive validity of the CTS2 and the J-IPV. Further, it is noticeable that more men than women participated in the two studies. However, men are overrepresented in substance abuse treatment and this does not reflect a selection bias. Finally, in the second study, 31 patients (19.1%) were excluded from the study because of logistic reasons, such as that the intaker had forgotten to administer the J-IPV or that there was not sufficient time in the intake to administer the J-IPV and CTS2.There were several limitations to the study. In the first place, both the J-IPV and the CTS2 rely on self-report of participants, which implies that the results do not automatically reflect the physical violence that actually took place. Participants may deny or minimize the violence they have committed or were victimized by. On the other hand, although people tend to underreport violence in their relationship when completing the CTS In addition, there are several issues that should be addressed in future research. First, although the J-IPV demonstrated good psychometric properties in two different substance abuse treatment centers, these finding do not necessarily generalize to other settings , since psychometric properties depend on the prevalence of a ‘disease’ in a population severe IPV perpetration and/or victimization if limited time or resources are available. Second, using the J-IPV would help overcome personal barriers  to screening for IPV; the J-IPV is conducted as structured interview, which makes it easier for intakers to address this sensitive topic. Finally, also patient-related barriers  can be disputed on the basis of the present study. These problems are prevalent among patients in substance abuse treatment and no problems in administering the J-IPV have been encountered. An additional comment is that since Since the J-IPV demonstrated good psychometric properties, it is recommended to routinely administer the J-IPV, which is available in the public domain, during intakes in substance abuse treatment facilities. If patients answer ‘yes’ to one or more of four J-IPV questions, IPV should be further assessed (stepped assessment), for instance, by administering the CTS2. Also, when using the J-IPV, various barriers on screening for IPV as reported by not to screen for IPV in substance abuse treatment facilities.After a positive J-IPV score and careful subsequent assessment, appropriate treatment for IPV perpetrators and/or victims should be arranged. However, to date, no evidence-based treatments addressing IPV perpetration exist Appendix S1.(DOCX)Click here for additional data file.Charts S1Receiver operator characteristics (ROC)-curves to detect any and severe IPV perpetration and victimization for optimal scoring methods.(DOCX)Click here for additional data file.