Studies on bladder dysfunction (BD), more specifically functional‐urodynamic changes in the bladder as a result of bladder outlet obstruction (BOO) have been summarized for this TT. Based on available, but limited evidence from human studies a three‐stage model can be hypothesized to characterize BOO‐induced bladder remodeling: hypertrophy, compensation  followed by the phase of decompensation [detrusor underactivity]. The time between the start of compensation and eventual decompensation seems to be determined by age of onset, severity, and type of obstruction and clinical mitigating factors such as vascular and metabolic problems. Understanding the relative contributions of these factors may allow the development of personalized timelines and probabilities for these obstructed patients. Other prevalent causes of BOO include bladder neck obstruction (BNO), posterior urethral valves (PUV), and urethral strictures (US). Conceptually, bladder dysfunction (BD) might be induced by BOO but alternatively could be pre‐existing; also, a combination of these factors might be possible. BPO‐ or BOO‐associated BD has been classified as follows: (a) detrusor overactivity (DO) with or without reduced bladder compliance, (b) detrusor underactivity (DU) or (c) mixed pattern.1.How might BOO lead to BD and more particularly what is its structural, histological and biochemical background?2.Is BD reversible after treatment of BOO and if so, is this always the case? In other words, can the detrusor recover after treatment?3.If detrusor function does not recover, why is this? Is there a certain period of exposure to BOO that predisposes to nonrecovery or decompensation of the bladder? And if so, how can this point of no return be characterized? Or is decompensation mainly related to acute or acute on chronic retention?This leads to several questions as follows:Is age of onset of BOO relevant? Are any clinical mitigating factors involved?Do functional changes occur in the bladder due to bladder outlet obstruction?” from the 2018 International Consultation on Incontinence‐Research Society (ICI‐RS) meeting.These are the proceedings of the Think Tank: “2Although in this Think Tank we focused on potential changes in humans, it is almost imperative to summarize biochemical and histological findings from animal research.2.1In the detrusor, BOO leads to initial inflammatory response and ischemia which eventually results in progression to smooth muscle hypertrophy.Increased formation of reactive oxygen species and/or decreased antioxidant defense are associated with increased OS; this, in turn, may cause cell damage through apoptosis. Studies in rats have suggested the possibility to improve detrusor blood flow with the medical therapy,2.2Galvin et al2.3P < .001).Animal models support the hypothesis that bladder smooth muscle (detrusor) does not adapt to chronic BOO in the same way skeletal muscle tissue adapts to overloads. In the latter, there is organized and functional hypertrophy. In the detrusor, hypertrophy leads to changes in the expression of the myosin heavy chain isoformIt is known that bladder wall elasticity changes with the relative content of connective tissue, collagen, and muscle.2.4Thickening of the bladder wall as a result of BOO has been attributed mainly to smooth muscle cell hypertrophy and collagen deposition. Ultrasound noninvasively estimates bladder wall thickness (BWT), and its correlation with BOO. Some investigators have proposed detrusor wall thickness (DWT) as a more reliable parameter, although data from BWT and DWT have shown consistent results with good accuracy of both techniques in predicting BOO.3Increased bladder pressure is the only urodynamic parameter that can be improved clinically. Although multiple treatment options exist for LUTS/BPO, mainly surgery, and to some extent α‐1 adrenergic antagonists and 5‐α reductase inhibitors, have been reported to improve BOO.Studies on human tissues indicate that BOO induces molecular and morphological‐structural alterations in multiple bladder compartments, namely urothelium, suburothelium, detrusor SMCs, detrusor ECM, and neurons. Cyclic stretch increased pressure, and hypoxia has been shown to modulate multiple signaling pathways involved in these alterations. The initial inflammatory response and ischemia are followed by progression to smooth muscle hypertrophy.A three‐stage model can be hypothesized to characterize BOO‐induced bladder remodeling in humans: hypertrophy, compensation  followed by the phase of decompensation (detrusor underactivity).4P = .024). Diabetes mellitus type 2 was also associated with DU (P = .015). Furthermore, reduced compliance (P = .042) and increased postvoid residual urine  were associated with higher collagen to smooth muscle ratio. These outcomes provide further insights in the origin of diabetes‐related BD.Averbeck et al5max decreased with 1.1% per year. Pmax (condom) increased longitudinally, that is, during the 5‐year follow‐up, but not cross‐sectionally. This could imply that compensation is a relatively fast process taking place in approximately 5 years.In 1020 healthy male volunteers, De Zeeuw et al6Although it is well established that BOO results in BD, it is not well established which factors influence the timeline to result in significant BD as well as the time to return to normal function following deobstruction. Cohorts of young boys with PUV demonstrate how variable both these timelines are. Due to prenatal scanning protocols, PUVs are typically diagnosed and treated in the first few months of life.2O) in all of the 16 boys studied.In perhaps the only study with prevalve ablation urodynamic studies during infancy, PUVs were associated with high detrusor overactivity  but the others had persisting bladder dysfunction. Of the relatively late presenters, presenting around the age of 6, 6/9 were overactive at follow‐up but half of these resolved after a 3‐year follow up. So, the urodynamic pattern of obstruction‐induced detrusor overactivity during the filling phase, that is generally found soon after valve ablation, gradually changes to detrusor underactivity in many boys and this seems to be the rule after puberty. This series supports the hypothesis that long‐term filling phase detrusor overactivity in boys with PUV is associated with voiding phase detrusor underactivity/hypocontractility when the initial presentation is not within the first 6 months after birth. However, longitudinal 15‐year follow‐up from birth to puberty is needed to validate this concept.Another group was predicting the timeline to bladder dysfunction secondary to BOO would be very useful are the relatively young men with BNO. BNO is the cause in 40% to 50% of men under the age of 50 years, with obstruction. Predicting the timeline of potential BD might allow for the safe deferral of BNI, which is relevant for the preservation of fertility. In four studies, reporting on a combined total of 362 men, the mean symptomatic duration before clinical analysis was approximately 4 years. In 30% of 110 men, DO was found. This gives some insight into the possible timeline of the compensatory phase. However, since obstruction is often nonspecific in its symptomatic presentation it is uncertain how much we can rely on this possible timeline; it seems however that it took less than 4 years in about one‐third of these men to develop obstruction‐induced compensatory increased contractility.Some observations in relatively young men before and after surgery for urethral stricture disease are noteworthy. Before urethroplasty, some of these men have a very large bladder capacity >900‐1000 mL) ?–Are there any noninvasive biomarkers for oxidative stress in humans?–Could noninvasive techniques  identify which patients are at increased risk of BOO‐related bladder dysfunction? (*prospective studies are still needed)–What is the role of urodynamics to define the management strategy  in high‐risk patients?How do histological and biochemical changes in the bladder function correlate with urodynamic findings?–What are the roles of HIFs as predictors in the early phase of changes?–BWT measurements by US in cohorts such as men with urethral stricture disease before and after urethroplasty, with a correlation of the findings with duration and severity of urethral stricture disease.–Can elastography measure collagen content of the bladder wall in vivo?.What is the role of clinical mitigating factors? What is the role of comorbidities  in the development of BOO‐related bladder dysfunction?Effects of bariatric surgery on detrusor in terms of histology, biochemistry, and serial urodynamics.What is the role of (BOO) exposure time? How much time does it take before the bladder decompensates?This may be investigated by correlating bladder wall thickness and elasticity measurements with storage/voiding pressures in men with urethral stricture when BOO onset is known.What is the possible role of age at onset of BOO on the effect of exposure time? Does it take longer for a young bladder to decompensate? Are there groups of PUV patients with different outcome after valve ablation? Is there a tipping point between young and old age?Urodynamically compares cohorts of men that were older and younger at the onset of BOO.What is the role of aging as a mitigating factor?Study functional changes in the bladder in older women [without “confounder” of progressive obstruction].Is recovery possible after treatment of BOO? When and under which circumstances? In other words: if BOO is treated before decompensation, can the compensation phase be reversed?Cohorts after urethroplasty (with known stricture exposure time) that do and do not show initial superflow and subsequent normalization?Role of PVR as a marker for decompensation.10Studies in humans and in animal models suggest a relationship between chronic BOO and both increased oxidative stress and increased collagen content in the bladder wall, which have been regarded as factors that trigger detrusor dysfunction.


Individuals with hypertrophic cardiomyopathy (HCM), even when asymptomatic, are at‐risk for sudden cardiac death and stroke from arrhythmias, making it imperative to identify individuals affected by this familial disorder. Consensus guidelines recommend that first‐degree relatives (FDRs) of a person with HCM undergo serial cardiovascular evaluations.We determined the uptake of family screening in patients with HCM and developed an online video intervention to facilitate family communication and screening. Family screening and genetic testing data were collected through a prospective quality improvement initiative, a standardized clinical assessment and management plan (SCAMP), utilized in an established cardiovascular genetics clinic. Patients were prescribed an online video if screening of their FDRs was incomplete and a pilot study on video utilization and family communication was conducted.Two‐hundred and sixteen probands with HCM were enrolled in SCAMP Phase I and 190 were enrolled in SCAMP Phase II. In both phases, probands reported that 51% of FDRs had been screened . Twenty patients participated in a pilot study on video utilization and family communication. Nine participants reported watching the video and six participants reported sharing the video with relatives; however only one participant reported sharing the video with relatives who were not yet aware of the diagnosis of HCM in the family.Despite care in a specialized cardiovascular genetics clinic, approximately one half of FDRs of patients with HCM remained unscreened. Online interventions and videos may serve as supplemental tools for patients communicating genetic risk information to relatives. All procedures involving human participants were in accordance with the 1964 Helsinki declaration and its later amendments or comparable ethical standards. Informed consent was obtained from all participants prior to inclusion the study.2.2Family screening and genetic testing data were collected through a prospective quality improvement (QI) initiative, a standardized clinical assessment and management plan (SCAMP), that has been reported as an effective tool for improving care practices among patients with rare diseases . First‐degree at‐risk relatives were considered unscreened if they had not pursued cardiovascular evaluation (including electrocardiogram and echocardiogram) or cascade genetic testing, when appropriate; or if they had previously pursued cardiovascular evaluation but their evaluation was outdated per consensus guidelines  to any proband where the uptake of evaluations in FDRs was incomplete.2.3Online educational videos were created in the Brigham and Women's Cardiovascular Genetics Clinic in April 2015. Two videos were created, namely one video was intended for families with a disease‐causing variant where cascade genetic testing was available to at‐risk relatives; the second video was intended for families where genetic testing had not been performed or was uninformative Appendix . The vidA pilot study investigating patients’ utilization of the video and family communication preferences was conducted from August 2017 to November 2017. Patients were eligible for participation in the study if they met the following criteria: 18 years of age or older, had a clinical diagnosis of HCM, were prescribed a video by their provider, and were English‐speaking. Patients were not required to be enrolled in the SCAMP to be eligible for the study . Eligible patients were recruited at the time of clinic visits or by telephone. Surveys were administered by a research assistant or genetic counselor in person or over the telephone; alternatively, participants could complete the survey online via a link through their email. Participants who opted to complete the survey online were sent a reminder 2 weeks later if the survey had not yet been completed.Participants completed a non‐anonymous survey consisting of multiple‐choice questions, Likert scales, and free response questions    of their FDRs had been appropriately screened. In comparison, in the 81 probands who did not pursue genetic testing, only 125 of 315 (40%) of their FDRs had been screened (p = .89). Additionally, there was no significant association between proband age and uptake of family screening . However, there was a significant, positive linear association between the number of visits a patient had in the cardiovascular genetics clinic and the uptake of family screening. .In Phase II, other factors that may influence the uptake of family screening were investigated. There was no significant difference between proband gender and the mean uptake of family screening  participated in the survey, four of 43 (9.3%) declined participation, and 19 of 43 (44.2%) patients did not respond. Nine of 20 participants reported watching the video, three of 20 did not watch the video, and eight of 20 were unsure if they had watched it. Participants who watched the video were asked to complete 5‐point Likert scales to rate whether the video improved their understanding of HCM inheritance and family screening recommendations. Approximately half of the participants reported the video did not increase their understanding of risk to family members (1/7), or that they did not learn new information, but it was a helpful review (3/7); whereas two participants reported it increased their understanding “a little” and 1 reported it increased understanding “a lot.” Similarly, over half of participants reported the video did not increase their understanding of family screening recommendations (2/7) or that they did not learn new information, but it was a helpful review (3/7); whereas two participants reported they learned “a little.” Not all participants completed the 5‐point Likert scales.Six of 20 participants reported sharing the video with relatives; 12 of 20 did not share the video, and 2 of 20 were unsure if they had shared the video , a short brochure (5/19), a personalized letter (4/19), a detailed packet of information (2/19), other (5/19), none of these (4/19). Eight of nineteen participants were interested in receiving additional guidance from their health‐care provider to help communicate their diagnosis. Participant preferences were varied when hypothetically asked about having their health‐care provider contact their family members directly, but with their permission. Three participants were willing to have their provider contact all at‐risk relatives versus some at‐risk relatives (1/19), all at‐risk relatives after they had a chance to speak with them (7/19), some at‐risk relatives after they had a chance to speak with them (4/19), and none of their relatives (4/19).4The aim of our study was to systematically assess the uptake of family screening in a cohort of patients with HCM and to conduct a pilot study of an online video intervention to facilitate family communication and screening. Data from a SCAMP study determined that approximately half of the FDRs in our cohort of patients with HCM remained unscreened. This is consistent with the uptake of screening reported in other cohorts with inherited cardiomyopathies, inherited arrhythmias, and inherited cancer syndromes  reported that they had not communicated genetic risk and screening recommendations to their family members, and this was similar for probands who did and did not pursue genetic testing. The clear majority of probands (69%) stated that their relatives were aware of the recommendation for screening but were simply uninterested. Taken together, these results suggest that most probands communicate genetic risk information and screening recommendations to their relatives, but many family members choose not to act on this information. However, a positive genetic test result in the proband may serve as a significant motivator for relatives to seek evaluation.BRCA1/2 genetic testing. In this study, only 31.5% of relatives reported intention to pursue genetic counseling and 35% reported intention to pursue genetic testing, and intention was higher for relatives of probands with informative test results. Additionally, 10% of relatives in the study reported that the proband told them the result but they could no longer remember it; and 14% of relatives found the information was very or somewhat difficult to understand (Daly, Montgomery, Bingler, & Ruth, These results echo the findings of a study where researchers, with proband permission, directly contacted FDRs of probands who had undergone Our results did not find a significant difference in proband gender on the uptake of screening, whereas female gender has been shown in multiple studies to be associated with increased family communication and screening (Batte et al., Due to ethical and privacy concerns, the standard that has emerged in most countries is for the proband to communicate with their relatives, rather than health‐care providers contacting at‐risk relatives directly (Forrest et al., Acknowledging the large portion of relatives who remain unscreened, there has been a call to consider novel ways to facilitate family communication and promote screening (Burns, James, & Ingles, Although we utilized the robust methodology of the SCAMP for obtaining family screening data, a major limitation of our study is that family screening uptake was reported by the proband and not verified with at‐risk relatives or through medical records. One study demonstrated that 22% of the FDRs a proband reported having disclosed results to did not actually recall receiving this information (Daly et al., Another limitation is the small sample size for our pilot study on utilization of an educational video. A randomized‐controlled trial of the video was not conducted, rather the video was prescribed to patients with incomplete family screening and video recipients were retroactively contacted and asked to participate in a survey. Providers could deviate from the SCAMP recommendation to prescribe the video; therefore, not all probands with incomplete family screening necessarily received the video. Additionally, some patients who were not enrolled in the SCAMP were prescribed the video and considered eligible for the pilot study. Only 20 of the 82 eligible video recipients participated in the survey and eight of the 20 could not recall watching the video, suggesting there might be recall bias due to the time that elapsed between video prescription and survey administration. Additionally, our cohort consisted of patients who were predominately white and had private insurance. The utilization of online technologies may be different in other populations.In conclusion, approximately half of relatives fail to pursue the potentially life‐saving screening that is recommended when HCM is diagnosed in a family, significantly diminishing the benefit of genetic diagnosis. Our research suggests that most probands share genetic risk information with their relatives, but many at‐risk relatives do not to act on this information. A positive genetic test result in the proband may serve as a significant motivator for relatives to seek evaluation. Participants identified multiple motivators and few barriers to sharing an educational video with their relatives to facilitate family communication; however, participants who shared the video typically sent it to relatives who were already aware of the diagnosis in the family. Therefore, online interventions may serve as helpful supplementary tools for disseminating genetic risk information in a family. As the use of genetic testing expands, it will be imperative to develop novel mechanisms for facilitating family communication and screening to achieve the greatest benefit of genetic diagnosis in a family.None declared. Click here for additional data file. Click here for additional data file. Click here for additional data file. Click here for additional data file. Click here for additional data file.


A 2010 World Health Assembly resolution called on member states to intensify efforts to address alcohol‐related harm. Progress has been slow. This study aims to determine the magnitude of public support for 12 alcohol policies and whether it differs by country, demographic factors and drinking risk (volume consumed).Data are drawn from seven countries participating in the International Alcohol Control Study which used country‐specific sampling methods designed to obtain random, representative samples. The weighted total sample comprised 11 494 drinkers aged 16–65 years.Drinking risk was substantial (24% ‘increased’ risk and 16% ‘high’ risk) and was particularly high in South Africa. Support varied by alcohol policy, ranging from 12% to 96%, but was above 50% for 79% of the possible country/policy combinations. Across countries, policy support was generally higher for policies addressing drink driving and increasing the alcohol purchase age. There was less support for policies increasing the price of alcohol, especially when funds were not earmarked. Policy support differed by country, and was generally higher in the five middle‐income countries than in New Zealand. It also differed by age, gender, education, quantity/frequency of drinking, risk category and country income level.We found a trend in policy support, generally being highest in the low–middle‐income countries, followed by high–middle‐income countries and then high‐income countries. Support from drinkers for a range of alcohol policies is extensive across all countries and could be used as a catalyst for further policy action. Alcohol was the ninth leading risk factor for death and disability globally in 2015 Global Strategy to Reduce the Harmful Use of Alcohol was approved by Member States Since 2010 the World Health Organization has been active in prompting member states to take more action to address harmful use of alcohol. In that year its Global Strategy. From assessments undertaken in Canada, Finland and South Africa it appears that some progress is being made, but despite the growing evidence base regarding what works, there remains much to be done There have been few evaluations of the extent to which individual countries or regions have progressed in implementing policies in line with the It has now been well established that support for more restrictive alcohol policies tends to be highest among light or non‐drinkers In most other studies looking at public support for alcohol policies the views of drinkers and non‐drinkers have been canvassed Generally, support for policies increasing the legal alcohol purchase age and increasing drink‐driving counter measures have received more support than those limiting availability or aimed at increasing the price of alcohol Data for this study come from the multi‐country International Alcohol Control (IAC) Study Policysum’) yields for each study participant a score from 12 (strong support) to 60 (strong opposition) which is a crude measure of their support for the various policy variables as a whole.Countries adapted the English IAC questionnaire and translated and back‐translated it into local languages  and piloted it before use. It comprised various domains, including demographic factors , alcohol consumption and support for 12 alcohol policies. The latter was obtained on a 5‐point Likert scale ranging from ‘strongly support’ (1) to ‘strongly oppose’ (5) with ‘do not know’ and ‘refuse’ options. Strongly support (1) and support (2) were combined to indicate support, and neutral (3), oppose (4) and strongly oppose (5) were combined to indicate lack of support. Persons who answered ‘do not know’ or refused to answer the question were excluded for that policy. For Thailand, three policies  and one for Vietnam (policy 8) were not included. We created a summary index which is the sum of the scores on the 12 individual policy support variables. This total policy support variable , ‘medium’ (4–6 drinks), ‘medium‐high’ (6 to ≤ 8 drinks) and ‘high’ (>8 drinks). Respondents reported their consumption of different beverages specific to their country in their own terms and interviewers coded these by using common containers and glass sizes in which alcohol is commonly served and sold in that country. We therefore had interviewers code what study participants said they consumed and we then afterwards recorded this into the number of drinks of 15 mL (12 g). ‘Risk category’ (drinking risk) was categorised into three levels: ‘low’ (up to four drinks on an occasion or four to six drinks on an occasion less than once per week), ‘increased’ (four to six drinks on an occasion at least once per week or more than six drinks on an occasion less than once per week) and ‘higher’ (more than six drinks on an occasion at least once per week). The risk categories were therefore derived based on the original location‐based occasion . Where participants did not provide complete data on quantity and frequency of drinking in all locations their data were omitted.Using the data on frequency of drinking in different locations over the past 6 months and quantity consumed on a typical occasion in each location, new variables were derived at the analysis stage. ‘Frequency of drinking’ is the sum of all drinking occasions at all locations over the past 6 months. The ‘typical occasion quantity’ is the weighted average of all the typical occasion quantities at each location, taking into account how often the person drank at that location. In this way, a location that a person only drank at once a year had minimal influence compared with a location that a person drank at daily. It was categorised into Some of the countries used telephone surveys  whereas others interviewed participants in their homes . Computer‐assisted surveys were used in all countries due to the complexity of the survey with numerous skip patterns. This involved using android tablets in Mongolia, Peru, South Africa, St Kitts and Nevis, Thailand and Vietnam, and an in‐house computer‐assisted telephone interviewing system in New Zealand. Once a household was contacted, a screening interview established eligibility for participation in the study (drinking in the last 6 months and age 16–65 years). Eligible individuals were enumerated, and one respondent was selected at random by the computer/tablet. Informed consent was then sought from the person identified before proceeding. Interviews took on an average about 30 minutes to complete. In many of the countries  participants received a small gift (e.g. a modest shopping or a cellular telephone recharge voucher or a Polo shirt) to acknowledge their participation. The studies were approved by their local ethics committees. Response rates varied from 60% in New Zealand and St Kitts and Nevis to 99% in Vietnam.It is important to account for the sampling design during analysis to make sure that the standard errors are not underestimated . This was not able to be done simply due to each of the countries in our study having different sampling designs, ranging from a simple random to a stratified multistage sample. The process used to adjust for cross‐country sampling design was based on Kaminska and Lynn 2017 P values less than 0.05 were considered statistically significant. A second (post‐hoc) multiple regression was undertaken to assess the association between the policy support variables and a newly constituted variable, country‐income level  adjusted for age, gender education and drinking risk.A statistical process was used to deal with outliers whereby the right‐skewed distributions of consumption‐related variables were transformed to normalise them. The transforming function was logarithmic  and power function (for frequency of drinking). The transformed series was then centred and scaled by subtracting the mean and dividing by the standard deviation and the 99th percentile of respondents were then removed. Using Stata The weighted sample of drinkers included 11 494 respondents aged 16 to 65 years  of the possible 80 country/policy combinations  as compared to New Zealand for the following policies: earlier closing times for bars and nightclubs, earlier closing times for buying alcohol from bottle stores and supermarkets, restricting marketing, increasing the price of alcohol, increasing alcohol taxes to pay for alcohol treatment, increasing alcohol taxes to lower other taxes, increasing alcohol taxes to pay for any government purpose (seven of the 12 policies) and also on the ‘policysum’ variable.Support was 16–52% higher for the other 11 policies among females than males with the exception of increasing alcohol taxes to pay for alcohol treatment (Table Support for various policies was associated with participants’ quantity and frequency of drinking and category of drinking risk. Persons who drank more frequently (or in some cases only those who drank the most frequently) were less likely to support various policies  as compared to participants in the lowest category of frequency of drinking. For Policy 1  and Policy 6 (restricting marketing) levels of support did not differ by frequency of drinking. With regard to drinking quantity, while in the same direction, fewer significant differences were found. Support for restricting the number of outlets in the community was found to be less for persons who typically drank four to six drinks per occasion (mid‐level drinkers) as compared to persons typically drinking fewer than four drinks, but no differences were found on these items for persons typically drinking more. Persons drinking four or more drinks per occasion were less supportive of earlier closing times for bars and nightclubs and mid‐level and mid‐high (six to less than eight drinks) level drinkers were less likely to be supportive of earlier closing times for buying alcohol from bottle stores and supermarkets and having more random breath testing of drivers. With regard to drinking risk, for some of the policies , the higher (or in some cases the highest) level of risk categories were significantly less supportive of these policies than persons who were in the lowest category of risk.P < 0.05) in high‐income countries compared to high–middle‐income countries, and in five instances was significantly higher (P < 0.05) in low–middle‐income countries compared to high–middle‐income countries after adjusting for age, gender, education and drinking risk  may have biased findings towards under reporting in the face‐to‐face interviews. The high reporting of heavy drinking in South Africa suggest that this was not the case.Some might consider it to be a limitation not to have included non‐drinkers in the study. However, given the finding from previous research that non‐drinkers are likely to be more supportive of alcohol policy controls Building on the core findings of this study that policy support seems to differ by the income level of country, with policy support being higher in less affluent societies, there is a need to replicate this research with a broader range of countries, including low‐income countries and high‐income countries and to increase the number of countries in each income group. Recognising that policy support changes over time future research should also include an assessment of where countries are at in their own policy development trajectory as well as indicators of the level of perceived harm to others associated with alcohol use.This study has shown that it is possible to conduct alcohol policy research using similar methodologies among countries varying in income level, language, education and drinking behaviour. The findings demonstrate substantial support by drinkers for increasing controls on alcohol in a number of areas. As such, they could give impetus to policy makers to move forward on strengthening alcohol control policies. We found a trend in policy support, generally being the highest in the low–middle‐income countries, followed by the high–middle‐income countries and then lowest in the high‐income countries. Further research is needed to replicate and expand on these findings.The authors have no conflicts of interest.


To assess the effectiveness of educational and/or psychological diabetes self‐management education (DSME) intervention for people with type 2 diabetes (T2DM) in the Asian Western Pacific (AWP) region.Translational research indicates that DSME is effective; therefore, it is important to look at the AWP region to see what has been implemented and what the potential barriers are for the low integration of DSME. The need for DSME is present, and programmes are being developed. Therefore, focusing a systematic review of DSME research in the AWP region would give a better understanding of which intervention approaches are associated with better clinical outcomes and are culturally acceptable.A systematic review.A review of randomized controlled trials (RCTs) and comparative studies to evaluate the effectiveness of face‐to‐face delivery reporting educational and/or psychological interventions for people with T2DM was implemented. We conducted searches using MEDLINE, EMBASE, CINAHL, PubMed and ASSIA databases between January 1990–June 2018. Studies published in English and non‐English were included. Two reviewers independently extracted data on participant and intervention characteristics. The quality of evidence was rated on predetermined criteria. Main outcomes included glycaemic control (reduction in HbA1c level).We included 21 DSME programmes (17 RCTs), while 15 were group‐based approaches. Twelve studies (60%) were categorized as high quality. Three studies (25%) had a moderate (good) effect. Eight trials were effective in improving glycaemic control and reported statistically significant improvements in HbA1c levels. 50% of these were high‐intensity group‐based programmes. Around 387 million people live with DM worldwide, and type 2 diabetes mellitus (T2DM) is the most common comprising 90% of those with diabetes  provides information and skills needed by people with T2DM to effectively self‐manage their diabetes, in addition to medical management, to achieve optimum glycaemic control  global diabetes scorecard reported that less than 1% of countries in AWP region integrate DSME in their health services  framework Davies,  and were3.2This systematic review included comparative studies. This is defined as RCTs, non‐RCTs and observational studies that used a comparison group. The broad inclusion criteria ensured all studies measuring effectiveness of DSME in adults aged 18 and over with T2DM in different healthcare settings were included. No limit was made on the language of publication. Eligible papers that were written in a different language were translated. Studies where participants were diagnosed with type 1 diabetes mellitus (T1DM), gestational diabetes and a mixture of T2DM with T1DM or other chronic conditions were excluded. Furthermore, studies solely investigating pharmacological or medication adherence, diet, exercise, physical activity, web‐based or peer support or telephone counselling were excluded to reduce confounding bias  defines DSME as “the ongoing process of facilitating the knowledge, skill and ability necessary for prediabetes and diabetes self‐care”  screened all titles from the searches to exclude studies that were irrelevant. Following this, three reviewers  independently screened the title and abstracts using an eligibility checklist. The full texts of the potentially eligible studies were retrieved for full review and final selection. Studies written in a language other than English were translated by native speakers: a nurse practitioner (Chinese articles) and a pharmacist (Japanese article). Data for the studies were extracted by the first reviewer and verified by the second and third reviewers, (KW and ES) and finally, the fourth reviewer Khalida Ismail (KI) for accuracy and completeness. Any discrepancies in the extracted data were discussed by all 4 reviewers for a 100% consensus.Data were extracted based on the following: (a) general information ; (b) study characteristics ; (c) intervention and setting (setting where intervention delivered and description of it); and (d) outcome data (baseline and follow‐up measure).3.4The quality of the studies was assessed using the Jadad score , cholesterol level (mmol/L), fasting plasma glucose level (mmol/L) and blood pressure (mmHg), as well as psychosocial variables such as self‐reported quality of life, self‐efficacy and level of depression.Overview and characteristics of included studies are presented in summary table Table . Meta‐an4A total of 1,744 non‐duplicated publications were screened, 151 abstracts were assessed for eligibility, and 43 publications required full‐text review before a decision could be made. Twenty‐one studies fulfilled the inclusion criteria, and the search processes are illustrated in Figure 4.1Twenty‐one studies were analysed in this systematic review. Sixteen studies  of studies having a mean population age of 55 years and above.The duration of interventions ranged from 6 weeks–18 months. Eight studies were conducted in China  assessed glycated haemoglobin  as the primary outcome with the effect size (Cohen's d) ranging from 0.1–0.6 and psychosocial well‐being or quality of life as the secondary outcome. Two studies were translated into English from the original Chinese article ; (d) 7 (33%) were implemented among people with T2DM with sub‐optimal diabetes control; and the remaining 7 (33%) did not specify a clinical sub‐group.Of the 21 studies, there were several clinical subgroups among the populations studied: (a) 2 studies (10%) were conducted among elderly people; (b) 4 (19%) included people with less than 5 years duration of T2DM; (c) 1 (5%) was conducted among overweight people with T2DM  of the reviews scored three and above against the Jadad score, which were then categorized as high in quality. Table In general, most of the studies included were of reasonable methodological quality and the abstract of the included studies was able to provide adequate information particularly on the aims, methods and findings of each study. Of twenty‐one studies, 12  where the studies were relatively balanced; four studies were implemented in a clinical setting   reported statistically significant improvements in glycaemic control, for both educational and psychological interventions. Four out of 8 studies   were of individual intervention studies    as an outcome to measure the impact of DSME  interventions. Eight studies  studies  . Interventions that integrated practical sessions reported an exceptional clinical improvement in glycaemic control (moderate effect size Cohen's d > 0.5). There was a trend from 2007 onwards towards multidimensional interventions  rather than on didactic teaching alone. There is little evidence to recommend a specific theoretical model as the most effective for DSME from the available analysis; however, self‐efficacy theory was widely used. Hence, we have little understanding of how intervention components promote behavioural modification or lifestyle change which may help improve clinical outcomes as only one‐third of our included studies measured at least one aspect of diabetes self‐management. Despite the small proportion of studies, they generally reported positive effects for glycaemic control.No direct comparison can be made between the present systematic review and any other review conducted in the AWP region as there are none. However, the results from this review are consistent with the review by Chrvala, Sherr, and Lipman  who repoIt is worth noting that multidisciplinary teams of DSME which involve more than one member of health professionals may contribute to effectiveness, though this has yet to be confirmed in RCTs and observational studies according to a review by Chrvala et al. . It was 5.1There is a possibility of publication bias as only published data were included. Fourteen studies (64%) included in the analysis had less than 12 months of follow‐up data; therefore, long‐term outcomes could not be assessed. In addition, the assessment of psychosocial outcomes in all studies was based on self‐report questionnaires which may introduce some bias. This review included non‐randomized study designs and was carried out using a discursive analysis rather than meta‐analysis, due to the heterogeneity in both the interventions and outcome measures, as well as the difference in populations and settings. In terms of outcomes, this review mainly focuses on glycaemic control (HbA1c), due to the issue of extracting or calculating the effect size when the secondary outcomes were made using different measures, such as for diabetes knowledge, quality of life, self‐efficacy, adherence and physical activity. Positive psychology is a relatively new approach that has been increasingly used as a promising technique to promote health; however, we did not encounter this approach in our search. In future searches, it might be useful to define this in the search strategy to see whether this changes the inclusion of positive psychology approaches.Despite the Jadad scoring system being simple and easy to use with known reliability and external validity, there are some flaws in the scale. It should be noted that the scoring system does not address the appropriateness of data analysis or allocation concealment (which is one of the parameters to avoid bias in research), or the assessment of intention‐to‐treat analysis. It also focuses on blinding, which is challenging in RCTs with complex interventions.Although blinding is gold standard in research design, blinding in most complex intervention RCTs is often not feasible. Complex intervention research such as DSME intervention trials is mainly conducted to determine effectiveness rather than efficacy in the traditional RCTs and often measure complex outcomes as well as consisting of multiple interactive elements that make it challenging to blind . Although randomization was implemented, there is still a potential of confounding bias, either consciously or unconsciously, which may have a negative impact on the integrity of the complex intervention trials.6This review identified and summarized the available evidence in the AWP region from the 21 studies regarding the effectiveness of DSME to improve diabetes self‐management. The results suggest that overall group‐based DSME is associated with improved clinical and psychosocial outcomes and interventions underpinned by behavioural theory with longer contact hours and the inclusion of active, hands‐on participatory sessions may maximize the potential benefit of these programmes. Likewise, involving the participation of the multidisciplinary team may also be important. However, what we do not yet know is how to target DSME in this region so that it is culturally appropriate and whether beliefs and attitudes towards diabetes in ethnically diverse AWP communities are being addressed and how this is achieved, which suggests more research is needed. We can conclude that standardized DSME programmes or specific guidelines in this region were limited; therefore, there is an urgent need to develop DSME and make it accessible to people with T2DM among AWP countries.7This review may guide healthcare providers or policymakers in designing future culturally tailored programmes for people with T2DM in the AWP region. Successful programmes are likely to be group based, include active participation and longer contact hours, but more research is needed to determine how to address specific cultural beliefs and attitudes towards diabetes. For example, the small feast culture appears to be one of the biggest barriers to maintaining the desired glucose level in Asian cultures. This happens infrequently in Western cultures, where meals are only offered to close friends and family Douglas, . Our resNone.


H2) and Pagel's λ, we find that analytical tooth wear data are not independent of phylogeny and failing to account for such nonindependence leads to overestimation of discriminability among species with different dietary preferences. We suggest that morphological traits inherited from ancestral clades  influence the ways in which the teeth wear during mastication and constrain the foods individuals of a species can effectively exploit. We do not suggest that tooth wear is simply phylogeny in disguise; the tooth wear of individuals and species likely varies within some range that is set by morphological constraints. We therefore recommend the use of phylogenetic comparative methods in studies of mammalian tooth wear, whenever possible.In the absence of independent observational data, ecologists and paleoecologists use proxies for the Eltonian niches of species . Some dietary proxies exploit the fact that mammalian teeth experience wear during mastication, due to both tooth‐on‐tooth and food‐on‐tooth interactions. The distribution and types of wear detectible at micro‐ and macroscales are highly correlated with the resource preferences of individuals and, in turn, species. Because methods that quantify the distribution of tooth wear  do so by direct observation of facets and marks on the teeth of individual animals, dietary inferences derived from them are thought to be independent of the clade to which individuals belong. However, an assumption of clade or phylogenetic independence when making species‐level dietary inferences may be misleading if phylogenetic niche conservatism is widespread among mammals. Herein, we test for phylogenetic signal in data from numerous analytical tooth wear studies, incorporating macrowear  and microwear . Using two measures of phylogenetic signal, heritability ( The course volume is then subtracted from the fine volume, yielding only the volume of the textural features and canceling out any overall shape or curve of the broader scanned area   on z‐scores  are arbitrary and thus uninformative for our analyses.We used two measures of phylogenetic signal: (1) phylogenetic heritability or u Lynch,  and (2) u Lynch, , 1999. WH2 is a measure of the phylogenetic heritability of a trait because it is an estimate of the degree to which phylogenetically related species can be used to predict the phenotype of each other  and σ^T2 is the estimated total variance of the trait mean . We calculated H2 using a phylogenetic generalized linear mixed‐effects modeling in the MCMCglmm R package  by the sum of the covariance matrices for the random and fixed (tooth wear) effects. We report the mean and upper and lower 95% confidence limits.r Lynch, . H2 is We also estimated Pagel's  λ using 2.2To demonstrate the impact of using phylogenetic comparative methods on discriminability among species with differing dietary niches, we used phylogenetic discriminant function analysis (PDFA) and quadratic discriminant function analysis (QDFA). We chose to analyze the LMM dataset for this purpose because microwear is comparable among a large set of taxa . Dietary categorization was based on the Elton Traits 1.0 database . QDFA identifies the combination of variables (quadratic functions) that achieves maximum separation among the defined groups in the training dataset  is equivalent to canonical correlation analysis and thus reduces to a multiresponse linear regression  and second PC2) principal components of mammal diet explain a cumulative 50.8% of the variance in the data. PC1 most strongly delineates insectivores and carnivores from species that feed primarily on plant materials. PC2 reflects separation of the frugivores and nectar specialists from other species Figure . Diet PC and seco principaH2 and λ  shows very high values for  λ Table –S3. LMM  λ Table .epLsar) and high‐scale fractal complexity (Asfc) as well as textural fill volume (Tfv). PC2 largely reflects the separation of species with high textural fill volume from the others  explain a cumulative 79.2% of the data variance. PC1 reflects separation of species with high anisotropy  cheek teeth (premolars and molars) that require constant wear, which is acquired through the introduction of exogenous grit into the mouth during grazing    .In a similar vein, hypercarnivores such as felids require powerful jaw‐closing muscles for capturing and dispatching prey  and p‐values or exploratory methods such as discriminant function analysis are used to test for significant differences among trophic groups .Mammal diets and tooth wear show significant phylogenetic signal when using Pagel's λ and phylogenetic heritability (We suggest that phylogenetic conservation of functional traits related to feeding explains phylogenetic signal in mammal diet and tooth wear.The ways in which teeth wear are determined, in part, by dietary constraints placed on animals by their morphology and the influence of morphology on the ways in which the teeth occlude.Tooth wear is not merely phylogeny in disguise; it can vary among individuals and time periods, but the degree of variation is constrained by morphology and thus phylogeny.Application of common, well‐documented phylogenetic comparative methods can circumvent statistical issues related to nonindependence among tooth wear data points due to PNC.Restriction of tooth wear comparisons to closely related species with similar dental morphologies will reduce the need for phylogenetic comparative methods but limit within‐guild comparison of distantly related taxa.None declared.Danielle Fraser conceived and designed the study, compiled published data from the literature, carried out the statistical analyses, interpreted the statistical analyses, and wrote the manuscript. Ryan J. Haupt compiled published data from the literature and wrote the manuscript. W. Andrew Barr helped conceive and design the study, helped design figures, interpreted the statistical results, and wrote the manuscript. Click here for additional data file. Click here for additional data file. Click here for additional data file. Click here for additional data file. Click here for additional data file. Click here for additional data file. Click here for additional data file. Click here for additional data file.


Synthesis. The ability to influence the soil microbial community by plants may be an important trait that trades off with growth, flowering, and seed size for promoting plant establishment, reproduction, and invasion.Soil microbial communities affect species demographic rates of plants. In turn, plants influence the composition and function of the soil microbiome, potentially resulting in beneficial feedbacks that alter their fitness and establishment. For example, differences in the ability to stimulate soil enzyme activity among plant lineages may affect plant growth and reproduction. We used a common garden study to test differences in plant‐stimulated soil enzyme activity between lineages of the same species across developmental stages. Lineages employed different strategies whereby growth, days to flowering and seed size traded‐off with plant‐stimulated soil enzyme activity. Specifically, the smaller seeded lineage stimulated more enzyme activity at the early stage of development and flowered earlier while the larger seeded lineage sustained lower but consistent enzyme activity through development. We suggest that these lineages, which are both successful invaders, employ distinct strategies (a colonizer and a competitor) and differ in their influence on soil microbial activity.  Meimberg et al.  at the Donald and Sylvia McLaughlin Natural Reserve of University of California, Davis in Lower Lake, California, USA. The soils were from Great Valley Sequence parent material and are classified as thermic Typic Haploxeralfs. Soil was ground to break up large pieces of clay‐loam, then sieved through a 3‐mm sieve, and homogenized using a cement mixer. The soil was poured into 164‐ml pots  until two‐thirds full. The final one‐third was filled with soil passed through a 1.5‐mm sieve to allow better germination and root penetration of the topsoil. Two seeds from the same seed family  within a population of a lineage were seeded into each pot in May 2012 (2 lineages × 3 populations × 10 seed families per population × 6 replicates = 360 pots). An additional 18 pots were filled with soil and left unplanted to act as controls for the enzymatic activity of the soil community in the absence of plants. Pots were placed on a mist bench at planting and were thinned to a single individual per pot after germination . The pots were moved to a growth chamber after germination to control the day length and temperature conditions, which were kept similar to their invasive range in California (Supporting Information Table 2.3n = 65), during the flowering stage when spikelets were fully formed but still green  and at post‐senescence . Number of replicates differed at harvest stage due to mortality and exclusion of individuals that had not reached the development stage . Post‐senescence harvests allowed all individuals to senesce ; at which point, all pots were watered to soil saturation  then left with standing biomass for three weeks in the growth chamber before plants were harvested.We destructively harvested individuals during development to measure enzyme activity in the rhizosphere with fluorometric enzyme assays. Plants were harvested during the tillering stage when production was mostly vegetative  and chitin  were assayed using standard fluorometric techniques  were sampled and assayed within 24 hr of harvest. Rhizosphere soil was collected by removing plants from the pots, and soil that remained attached to the roots after shaking was homogenized to produce a single sample per pot. Two hydrolytic soil enzymes involved in the degradation of N‐degrading enzyme activity in the soil was calculated by the sum of the enzyme activities of LAP and NAG. The stimulation of N‐degrading enzyme activities by each plant (plant‐stimulated enzyme activity) at each harvest stage was calculated as the ratio of the total N‐degrading enzyme activity of the rhizosphere soil for each sample over the mean N‐degrading enzyme activity of the control soils with no plants. The activity of the two enzymes was significantly correlated , and the ratio of NAG to LAP activity was consistent across lineages and control .Total 2.5We used two sets of analyses to assess both general differences in biomass, plant‐stimulated enzyme activity, time to flowering, and seed characteristics of the two lineages. We then examined covariance among plant‐stimulated enzyme activity and biomass production, time to flowering, and mean seed size.Biomass and plant‐stimulated enzyme activity were analyzed as a function of development stage , lineage , and their interaction to assess response through time for each lineage (see ANOVA in Supporting Information Table n = 62). Combined, these three correlations provided tests of the trade‐offs between plant‐stimulated enzyme activity and growth, flowering phenology, and seed size variables. All analyses were performed with the asreml‐R package  in the R statistical software .To examine trade‐offs, we assessed the correlation between plant‐stimulated enzyme activity at the tillering stage and biomass production, time to flowering, and average seed weight. We estimated biomass production as a function of day with a random slope for seed family per day , produced fewer seeds , larger seeds , and more total seed biomass  than the West lineage , which also correlated with later flowering and production of fewer and larger seeds. Our results support previous work on this invasive species, which found that the East lineage is less affected by interspecific plant competition than the West (Gomola et al., We used two distinct invasive lineages of the species 4.1N‐rich organic compounds—the rate‐limiting step in N mineralization (Schimel & Bennett, While it is well known that individuals within species vary in their ability to acquire, utilize, and compete for available nitrogen (Ahmad, Khan, Abrol, & Iqbal, 4.2Aegilops triuncialis showed similar growth patterns but distinct strategies of stimulating soil enzyme activity and reproduction. The East lineage consistently grew faster and achieved a larger size than the West despite similar growth patterns. The larger seed size of the East lineage likely influenced the faster growth. Furthermore, individuals with larger seeds and faster aboveground biomass accumulation allocated less resources to stimulating soil enzyme activity at the tillering stage. This suggests stimulating enzyme activity comes at a cost of allocation to aboveground growth. The ability to establish and grow with greater seed reserves would reduce dependency on soil microbes to provide nutrients. This supports similar results from another system that found larger, and less mycorrhizal‐dependent species were less dependent on the cooperativeness of the mycorrhizal species in the soil (Arguello et al., The two lineages of 4.3Aegilops triuncialis can invade soils ranging from nutrient‐limited serpentine communities to more resource‐rich loam soil with the West establishing with greater success in serpentine sites (Meimberg et al., Differences in the ability of the East and West lineages to acquire N and influence N mineralization suggests that multiple positive plant–soil linkages throughout the growing season lead to a positive feedback on establishment. We observed a negative correlation between enzyme activity at tillering and the average seed weight produced Figure . This re5We observed a novel relationship between plant‐stimulated enzyme activity and growth, flowering, and seed size that has the potential to influence the evolution of populations and mediate the type of sites a population will invade. Our results emphasize the importance of studying the interactions of individuals with their soil microbial communities, lending insights into the mechanisms promoting population distributions within the range of a species. Our findings also highlight the role of soil microbial communities for plant invasion strategies and suggest that the ability to stimulate enzyme activity of soil microbes may be a trait that influences where a plant establishes in new systems. Our results have implications for invasion ecology, the effects of climate change on the distribution of species, and community assembly.None declared.CEG, JKM, and MDW conceived, designed, and carried out the experiment. CEG wrote an initial version of the manuscript. CW contributed to the writing and revisions. MJO analyzed the data, wrote the manuscript, and led the revisions. All authors contributed to the revision process.https://doi.org/10.5061/dryad.1h268g3.Data are available in Dryad  Click here for additional data file.


Integr Environ Assess Manag 2019;15:278–291. © 2018 The Authors. Integrated Environmental Assessment and Management published by Wiley Periodicals, Inc. on behalf of Society of Environmental Toxicology & Chemistry (SETAC)The European Commission intends to protect vertebrate wildlife populations by regulating plant protection product (PPP) active substances that have endocrine‐disrupting properties with a hazard‐based approach. In this paper we consider how the Commission's hazard‐based regulation and accompanying guidance can be operationalized to ensure that a technically robust process is used to distinguish between substances with adverse population‐level effects and those for which it can be demonstrated that adverse effects observed  do not translate into adverse effects at the population level. Our approach is to use population models within the adverse outcome pathway framework to link the nonlinear relationship between adverse effects at the individual and population levels in the following way: (1) use specific protection goals for focal wildlife populations within an ecosystem services framework; (2) model the effects of changes in population‐related inputs on focal species populations with individual‐based population models to determine thresholds between negligible and nonnegligible  population‐level effects; (3) compare these thresholds with the relevant endpoints from laboratory toxicity tests to determine whether they are likely to be exceeded at hazard‐based limits or the maximum tolerated dose/concentration from the experimental studies. If the population threshold is not exceeded, then the substance should not be classified as an endocrine disruptor with population‐relevant adversity unless there are other lines of evidence within a weight‐of‐evidence approach to challenge this. We believe this approach is scientifically robust and still addresses the political and legal requirement for a hazard‐based assessment.  In this paper we consider how the European Commission's hazard‐based Plant Protection Product Regulation can be operationalized to distinguish between substances with adverse population‐level effects and those for which observed adverse effects do not translate into adverse population‐level effects.Our approach is to use population models within the adverse outcome pathways framework to link the nonlinear relationship between adverse effects at the individual and population levels.Only if the population threshold is exceeded should the active substance be classified as an endocrine disruptor with population‐relevant adversity, unless this classification is challenged by other lines of evidence  within a weight‐of‐evidence approach.We believe this approach is scientifically robust and addresses the political and legal requirement for a hazard‐based assessment. The potential effects of endocrine‐disrupting chemicals (EDCs) on wildlife have been a concern for many years (Campbell and Hutchinson Rutilus rutilus) from different southern English rivers and assessed the genetic structure of the populations at each location. Despite widespread feminization of male roach in effluent‐contaminated rivers, there was no evidence of a correlation between effective population size and predicted exposure to estrogens. In another study with fish, Harris et al.  to low concentrations (5–6 ng  ·  L−1) of the potent estrogen 17α‐ethynylestradiol (EE2) led to feminization and intersex in males and altered oogenesis in females, leading to near extinction of the population in the lake. However, in a follow‐up study, Blanchfield et al.  to the effects of endocrine‐disrupting substances, even when adverse effects of these substances are observed in laboratory tests. It is therefore important to establish a biologically causal link between endocrine‐disrupting effects measured in laboratory toxicity tests and adverse population‐level effects on vertebrate wildlife in the field, because this is necessary to meet the requirements of the definition of an endocrine disruptor for regulatory purposes , we discuss recent European Union (EU) regulation EC  and guidThe European Food Safety Authority (EFSA) benefits from many expert opinions provided by their Scientific Committee (EFSA SC) and Panel on Plant Protection Products and their Residues (EFSA PPR). We draw upon these opinions here to assist in mapping out a coherent and conservative hazard‐based approach Figure  for demoThe approach depends on clear identification of specific protection goals for focal wildlife populations within the EFSA's ecosystem services framework. The magnitude of relevant effects in toxicity tests performed at hazard‐based thresholds  is compared to population‐relevant thresholds derived from population modeling. The relevance of specific endpoints is taken from an understanding of the adverse outcome pathway (AOP) concept , ideally by use of transect or field survey methods across a range of representative fields, although literature and census data might also be useful EFSA . The sur1)Triturus cristatus), the natterjack toad , the common treefrog (Hyla arborea), the Hermann's tortoise (Testudo hermanni), the sand lizard (Lacerta agilis), and the smooth snake (Coronella austriaca). At least one relevant (generic) focal species should be selected for each regulatory exposure scenario . Examples of generic focal bird and mammal species are provided in EFSA , and Ibr2) Each of the selected focal species should, as a priority, be potentially ecologically susceptible to adverse effects caused by exposure to endocrine disruptors . “Susceptibility” here does not mean that the species has a proven toxicological sensitivity to the substance of interest . Instead it means that the ecology and demographic structure of the population make it vulnerable to the adverse endocrine‐mediated effects from the substance of interest. In this sense, the focal species acts as a surrogate for all other species in its taxonomic group because it has life history and other ecological traits at the more susceptible end of the spectrum for that taxon. Similar thinking led EFSA  to sugge3) The role of the selected species as a keystone, umbrella, or flagship species is of secondary importance to its ability to act as an indicator.Selection of focal species when assessing the potential population relevance of endocrine disruptors should therefore include the following considerations:The PPP regulation EC  uses theWe therefore also use the term “population” subsequently in this paper as an operational description of any group of individuals from the same species that occurs in a particular space during a particular time, as defined by a regulatory authority.Nontarget vertebrate wildlife populations provide a wide variety of ecosystem services including food (for human consumption), genetic resources (biodiversity), education and inspiration, aesthetic values, pest and disease regulation , seed and propagule dispersal, and recreation and ecotourism  EFSA . The EFSEFSA PPR  makes thTable 1) There is no alteration in the general function of the test organism or affected organ or tissue;2) It is an adaptive response;3) It is transient;4) The severity is limited and below thresholds of concern;5) The effect is isolated or independent;6) The effect is not a precursor to adverse effects;7) It is secondary to other adverse effect(s); or8) It is a consequence of the experimental model.The concept and definition of an “adverse effect” has received considerable attention in toxicology  Population recruitment;2) Population size; and3) Population stability.EFSA SC  identifiThey also state that adverse consequences on reproduction, growth and development, disease incidence, and survival in one or more species should be addressed “as these are the effects most likely to impact on population recruitment and stability”, although we note that survival is not an endpoint of relevance to endocrine disruption and, to the best of our knowledge, disease incidence is rarely considered explicitly in chemical risk assessment.In order to determine the biological relevance of an effect it should be considered whether the effect could lead to a functional deficit later on in the study, e.g. if a reduction in the weight of pups at birth leads to a decrease in level of survival. If not, then the effect may not be biologically relevant, however if there is a carry‐over of effects into the number of survivors, it can be considered biologically relevant.The EFSA  guidanceFor example, in 2‐generation mammalian reproduction studies, a body‐weight reduction in pups would not be considered relevant if normal development was observed in the F1 generation, especially if F1 fertility and reproduction were comparable to the control EFSA . SimilarThe EFSA SC opinion on the hazard assessment of endocrine disruptors EFSA SC  argues tof focal species could be used to determine endpoints corresponding to cut‐off values set by specific protection goals (SPG). These models can be used for calculating critical effect levels for certain types of effect, for instance for egg cracking, number of surviving chicks or the size of litters, above which the population of the focal species will be negatively affected to such an extent that the population will decline over time.EFSA SC  suggestsEFSA SC  also sugThis definition is related to the EFSA SC  view thaWe propose, in agreement with EFSA SC , that poThere are established methods to demonstrate the relevance of effects with population models to extrapolate from the laboratory to the field  substances. Both substances were investigated under acute (10‐day) and chronic (1‐year) exposure regimes. Acute exposures to the test substances had little effect on population‐level endpoints at any of the concentrations tested. Chronic exposures decreased population abundance at higher concentrations for both substances and most strongly with DHT, owing to the sex ratio shift to fewer females, which lowered population reproductive output. However, these concentrations considerably exceeded environmentally realistic levels. The model predicted that a substance‐induced change in sex ratio from 50:50 to approximately 40:60 in favor of males (DHT) or females (4‐tOP) would have limited effects on population abundance after chronic exposure but that a large reduction in abundance would occur if the ratio changed to approximately 20:80 in favor of either sex. This study suggests that an SPG for fish population abundance would be met at a benchmark concentration that did not skew sex ratios to more than approximately 40:60.Hazlerigg et al.  developeHamilton et al.  considerUncertainty analysis reported with the results of population modeling helps identify and prioritize the uncertainties associated with the assessment inputs and methodology used EFSA SC . However•–They focus on the direct measurement of the effects of concern under realistic field conditions, so can take account of all routes of exposure and all relevant sources of variation.–They avoid uncertainties associated with extrapolation from models or laboratory studies to the field.–They reduce uncertainties associated with extrapolating sensitivity (toxicity) from studied species to those exposed in the field.Field studies of mortality and reproductive effects are neither simple nor inexpensive, but they have some important advantages over other study types:• Design of a study of appropriate power requires knowledge of the levels of effects that are considered acceptable and the degree of certainty that is required to prevent the acceptable limit being exceeded.• “Extensive” approaches across a large number of sites to cover a broad spectrum of use conditions are preferable to “intensive” studies across a small number of sites, because they account for natural variability in exposure and effects.•–Capture‐mark‐release‐recapture studies to monitor population changes, which include changes in age structure, especially in small mammals.–Monitoring of sublethal effects with biomarkers . Repeated sampling from the same individuals may be desirable to control for high natural variability in biomarker levels, although this approach must be balanced against the risk that repeated capture will alter the behavior of the animals and hence will bias the results.–Visual observations to monitor populations and activity of birds and large mammals. Interpretation of results is difficult if the animals are not individually marked.–Monitoring of reproductive performance of birds.The choice of methods should be driven by the study objectives and might include:EFSA/ECHA (2018) guidance states that field studies cannot be used to override or dismiss evidence of adversity found in laboratory studies. However, this contrasts with previous EFSA  guidanceEFSA  guidanceIn the absence of such data , regulators must be confident of being able to extrapolate from laboratory data on endpoints such as growth and reproduction to potential effects on populations, ideally but not necessarily through the use of population modeling.In support of this, EFSA SC  states tField monitoring is probably the most powerful tool in establishing impacts at the population‐level .And,We agree with the EFSA SC opinion that, when available, the use of field studies, including field monitoring, should form an important line of evidence for assessing the population relevance of an endocrine disruptor, especially when used in combination with population modeling. Field studies can also provide invaluable inputs to modeling either for parameterization or validation, and models can add to field studies by extrapolating to untested conditions. If adequate, reliable, and representative population models and field studies show that there is no evidence for an adverse population‐level effect from an endocrine disruptor then this should override laboratory data, which is a position consistent with the PPP regulation.Results from laboratory tests can currently be linked to potential adverse effects at the population level either quantitatively by use of a population model, or qualitatively by use of expert judgment to bring together different lines of evidence  in an overall weight‐of‐evidence approach, as described by EFSA SC .The population modeling for focal species described earlier, potentially complemented by data from field studies, would provide a set of simulations that show what percentage effect on an input parameter leads to a nonnegligible effect on population recruitment, size, or stability. These values from population models then provide benchmarks against which an assessor can compare the results for specific laboratory test endpoints such as eggshell cracking in a bird toxicity test. This is likely to be a doubly conservative approach if the focal species chosen for modeling is ecologically sensitive and the laboratory species chosen for testing over a prolonged chronic duration is toxicologically sensitive.A wide range of potentially endocrine‐related endpoints are routinely measured in laboratory tests to support the registration of PPPs  across Danish agricultural landscapes in a study explicitly designed to show how the results of population modeling might be used to establish SPGs for this focal species. An IBM for skylarks was used to examine several scenarios that represented the range of agricultural landscapes across Denmark. In this section we describe the way in which the information in Topping and Luttik . Individual birds were categorized into 5 life stages: clutch, nestlings, prefledglings, males, and females. Available insect food biomass was determined by vegetation structure in the landscape and by its availability to birds foraging within a home range. Insect biomass was updated daily in the model and was affected by vegetation growth and human management, such as PPP application. During the breeding period the model considered the energetic balance of the adults, food requirements for maintenance, requirements of the young, and weather constraints both as a limit to foraging success and as increased energetic costs for cold weather. Initiation of breeding depended upon a bird finding a suitable territory and vegetation suitable for nesting. Breeding success depended on the habitat being able to fulfil the energetic requirements of the birds during the breeding period and the survival of eggs and nestlings, which was determined by food resource quantity and availability .Topping and Luttik  used theTen model landscapes were selected to be used in the simulation runs, representing the range of agricultural practices in Denmark, from intensive to extensive. A wide range of different PPP application timing scenarios and levels of effect on different life stages were simulated.These simulations showed that in the most sensitive of the 10 modeled landscapes a reduction in skylark eggshell thickness, which was associated with a 10% or less probability of clutch loss, led to negligible effects on population recruitment, size, and stability after a period of 20‐30 years.The model used by Topping and Luttik  has beenBird eggs begin to crack in the laboratory when shell thickness is reduced by 18% EFSA . ToppingThe results for eggshell thinning and cracking from laboratory‐based avian reproduction tests can be directly linked to effects on skylark population recruitment, size, and stability, with this benchmark response indicating an inflection point below which no adverse population effects would be expected. If avian testing is performed at the hazard‐based dietary limit of 1000 ppm and the benchmark response is not exceeded, then the tested substance is unlikely to cause adverse population effects in birds.1) Use SPGs for focal wildlife populations within EFSA's ecosystem services framework. The SPGs for vertebrate wildlife can be summarized as (i) ecological entity: populations of vertebrate focal species; (ii) attribute: population recruitment, size, and stability; (iii) effect magnitude: negligible; (iv) temporal scale: species life cycle, life span, or breeding period and an exposure frequency or duration agreed with regulatory authorities; (v) spatial scale: likely to be a watershed or landscape, but this element needs to be agreed upon with regulators; and (vi) degree of certainty: high .2) Model the effects of changes in population‐related inputs on focal species populations with IBMs to determine thresholds between negligible population effects and nonnegligible  population effects.3) Compare these thresholds with the relevant endpoints from laboratory toxicity tests to determine whether they are likely to be exceeded at the hazard‐based limits or the MTD/C from the experimental studies.4) If the population threshold is not exceeded, then the substance should not be classified as an endocrine disruptor with adverse population effects unless there are other lines of evidence within a weight‐of‐evidence approach to challenge this.In this paper we have suggested how to implement the new endocrine disruptor criteria in the PPP regulation in a way that builds upon ECHA/EFSA  guidanceIf the proposals in this paper are accepted by stakeholders, then it is likely that future technical work will need to concentrate on 4 main areas: (i) Selection of a small number of ecologically sensitive focal species for each taxonomic group. This task has already been performed by EFSA for birds and mammals EFSA , and Ibrhttps://setac.onlinelibrary.wiley.com/doi/10.1002/ieam.4116). The approach to identify adverse endocrine‐disrupting population‐level effects that we recommend in this paper is hazard based to comply with the PPP regulation, but uncertainty would be significantly reduced and assessment relevance improved if exposure was also explicitly considered during the process. For example, models are available at the organism level to predict whether an endocrine‐disrupting effect would be transient under realistic patterns of exposure . Use of such models might negate the need to move along an AOP to the population level by showing that an adverse endocrine‐disrupting effect had not occurred at the organism level. However, use of exposure duration and profiles information in these models implies a risk‐based approach, which is not currently allowed under the PPP regulation. We believe that further discussion of this issue between all stakeholders would help to reduce regulatory uncertainty and provide a more robust and science‐based solution to the problem of detecting and preventing adverse endocrine disruptor effects in the environment. Regardless, all substances shown to be non–endocrine disrupting and potentially endocrine disrupting, but without population‐relevant adverse effects, will still undergo risk assessment, thus ensuring a high level of protection for the environment.The identification of endocrine disruptors in PPPs under the regulation is primarily a hazard‐based and not a risk‐based methodology, which is an approach to regulation that has been strongly criticized in the past  to research and write this paper. All other co‐authors work for agrochemical companies as indicated by their affiliations.