Evaluations asked about their interval drinking status and problems, including each of what became the 11 DSM-IV AUD criteria using questions derived from the Semi-Structured Assessment for the Genetics of Alcoholism instrument . Subsequently, over 90% of probands were evaluated every 5 years where data were gathered regarding their own drinking practices and problems, and where the probands and their spouses offered information regarding the proband’s biological offspring. Note that the proband’s AUD diagnoses used in the current analysis were based on personal interviews with that proband father. For the current data, beginning at offspring age 18, an interview was carried out with these second-generation sons and daughters using a set of questions similar those asked during proband followups. Offspring were also followed with personal interviews about every 5 years regarding changes in demography, substance use and problems, and development of major psychiatric disorders. Followup evaluations also included filling out the Impulsiveness Sub-scale of the Karolinska Scales of Personality and the Zuckerman Sensation Seeking Scale . The offspring interviews contained items extracted from the Family History Assessment Module used in conjunction with the SSAGA in Collaborative Study of the Genetics of Alcoholism research . As part of the FH section of their interview, offspring were asked: “Have any of your parents or siblings had any of the these [following] experiences because of their own drinking?”. The items included the 11 DSM-IV AUD criteria plus a question about craving. In our offspring protocol,cannabis growing supplies before exiting the FH section interviewers also asked about alcohol quantities and frequencies for each first degree relative along with a re-review of the alcohol problems.

For these analyses, if the son or daughter endorsed 2 or more of the alcohol problem items for their father, the report was considered a positive indication of the proband’s alcohol problem. This relatively liberal FH interpretation of alcohol problems was used considering the advice against invoking excessively restrictive criteria when identifying a FH of AUDs , as described in the Introduction. At the time the current analyses were carried out, there were 447 probands’ sons and daughters age 18+, of whom 352 had been interviewed. Of these 352, 135 were offspring who were eligible for the analyses because they were drinking offspring of the 73 probands who had developed DSM-IV AUDs in the interval since entering the study. The major analyses focus on whether the offspring recognized the presence of their father’s DSM-IV alcohol problems that had been identified from the father’s own semi-structured interview. The proband’s AUD FH listed in Table 1 was based on the proband’s report of his mother’s and father’s alcohol problem history, but, using the FHM approach at study entry, the proband’s parents were not directly interviewed. Among those AUD probands, 21 had only one relevant offspring, 44 had 2 offspring, and 8 reported 3 or more drinking offspring age 18+. The Design Effect related to the possible skew of results caused by the number of children per family ranged from 0.08 to 1.37 across the FH alcohol questions, where 2.0 or higher would indicate a potential meaningful effect of multiple off- spring per family . In addition to SSAGA interviews and personality questionnaires, all probands and drinking offspring also reported their usual intensity of response to alcohol using the retrospective Self-Report of the Effects of Alcohol questionnaire , which is the only LR to alcohol measure available in both generations. This 12-item instrument records the average number of standard drinks required for up to 4 effects during the approximate first 5 times of drinking , their period of heaviest alcohol intake, and the 3 most recent drinking months.

The 4 possible effects included drinks required to: actually experience first alcohol effects, slurring speech, develop unsteadiness of walking, and unwanted falling asleep, with the greater the number of drinks for effects the lower the level of response, or sensitivity, per drink .The data were based on personal interviews with 135 SDPS drinking offspring who were age 18 or older and whose fathers developed DSM-IV alcohol abuse or dependence since entering the study as non-AUD drinkers at about age 20. To be included in analyses, the probands had to have at least one drinking biological offspring who was at least age 18 at the time of their most recent follow-up in 2018 or 2019 . While not the focus of this report, additional data indicated that 97.2% of the offspring of non-AUD probands correctly identified their father’s status . As shown in the first data column of Table 1, the average father in the proband–offspring pairs was 55 years old, European American, had ever been married, 25% ever divorced, and reported 18 years of education. Reflecting the criteria used to select the original SDPS probands, 64% had a parent with an AUD. During the 35 years of their followups, 61% of these AUD probands met criteria for alcohol dependence and 39% for alcohol abuse. During the followup, these men reported a lifetime average maximum of 17 standard drinks per occasion and endorsed an average of 5.5of the 11 DSM-IV criterion items. The lifetime rate of endorsement for each AUD criterion ranged from 87% for often using alcohol in higher quantities or for longer periods than intended to 21% for recurrent alcohol-related legal problems. During the 35 years of follow-up, about half of these probands had used tobacco products, over 90% had used cannabis, 73% had used other illegal drugs, 16% ever met criteria for a cannabis use disorder, and 21% met criteria for a SUD on another illicit drug. Although the numbers for variables in Table 1 were generated by considering all 135 proband–offspring pairs, no values were significantly different from those in Table 1 if data were limited to the 73 individual AUD probands involved in these analyses.

Data columns 2 through 4 in Table 1 indicate 11 signififi- cant differences across the 22% of probands for whom at least 1 offspring reported knowing about their father’s alcohol problems and the 78% of probands for whom no son or daughter recognized their father’s condition . Two of these 11 differences did not survive the Holm–Bonferroni procedure . The 9 differences that did survive included a slight but significantly lower ages for Group 1 probands, but there were no other significant demographic differences, including similarities for the proportions who were divorced from the off- spring’s mothers. Group 1 also reported higher values for the proband having a parent with an AUD, a proband diagnosis of alcohol dependence, the need for more drinks for effects the first 5 times of drinking, and reporting a higher number of the 11 lifetime DSM-IV AUD items. The latter included noting higher proportions of probands who endorsed spending a great deal of time involved with alcohol, decreasing other important activities in order to drink, continuing to use alcohol despite medical or psychological problems caused by alcohol, and drinking despite social or interpersonal problems related to alcohol. Although not shown in Table 1, if the analyses were limited to counting each proband only once and selecting only the oldest son or daughter when data from multiple offspring were available, significant differences remained for criterion items of a great deal of time spent regarding alcohol,cannabis indoor growing giving up important activities to drink, continuing to drink despite medical and psychological problems caused by alcohol and continuing despite interpersonal or social problems. In that smaller sample, group differences similar to those in Table 1 remained at a trend for a proband’s AUD FH, his alcohol dependence diagnosis and for his maximum drinks. Table 2 focuses on data from the 135 interviewed offspring of the probands who had developed an AUD during the 35 years of follow-up. Overall, these sons and daughters were 25 years old, European American, and had 15 years of education, with about 20% having ever been married and a third who identified with a religion. Two thirds of these offspring ever met criteria for an AUD , their average lifetime maximum drinks per occasion was 11, and they reported experiencing an average of 3 of the 11 AUD criteria in their lives, ranging from 60% for spending a great deal of time involved with alcohol to 3% who ever fulfilled criteria for alcohol withdrawal. About 32% had used tobacco products, 71% had ever used cannabis , and 6% ever met criteria for a SUD related to another illegal drug. Among these 135 sons and daughters, 8 variables were significantly different across Group 1 offspring who correctly identified their proband father as having an alcohol problem and those who did not . Four of these variables did not survive the Holm–Bonferroni procedure . Focusing on the 4 variables that survived the Bonferroni step, Group 1 offspring were more likely to have ever fulfilled criteria for an AUD, including higher rates than Group 2 for alcohol dependence.

Overall, offspring in Group 1 reported experiencing a higher number of alcohol criterion items, including higher proportions who endorsed spending a great deal of time centered on alcohol. In Table 2, however, the 2 groups were similar on demography , use of tobacco products or illicit drugs, and had similar scores on impulsivity. The major findings in this report relate to Table 3, and data from Tables 1 and 2 are offered to describe the populations overall and characterize how the group differences in Table 3 relate to the original data. Table 1 had 11 significant effects, and Table 2 had 8, for a total of 19 such effects across the 2 tables. Using the Lowry VassarStats binomial program , the exact binomial likelihood for 19 significant out of 60 tests is <0.0001, indicating that that number of significant findings would only occur by chance one in less than 10,000 times. Also, the Holm–Bonferroni sequential correction was conducted to take into account multiple testing effects and adjusting for family-wise error in Tables 1 and 2, using the Gaetano EXCEL calculator. This yielded 13 variables that remained significant with adjusted p-values from 0.0143 to 0.044. These included 9 proband variables as well as total number of DSM items, alcohol dependence, parent AUD, SRE-T, and age. Also included were 4 offspring items . It is important to note that of the 6 variables that remained in the backward elimination logistic regression , 5 are among those that were still significant after correcting for multiple testing. Only the item “identify with religion” that remained in the final regression model was not on the list of those that were significant after the Holm–Bonferroni sequential correction. The key step in these analyses, as shown in Table 3, simultaneously evaluated both fathers and offspring characteristics that related to Group 1 membership. Recognizing that many of the variables in Tables 1 and 2 were likely to correlate with each other, regression analyses were constructed to determine which characteristics remained robust when considered in the context of all other characteristics used in relevant analyses. To ensure that all father–offspring pairs were considered, the analyses used a bootstrap approach. In Table 3, all variables from Tables 1 and 2 were evaluated except for items that overlapped greatly with another variable or when the item was endorsed similarly by the large majority of participants in both groups.Table 3 presents the results from this bootstrapping approach for variables that added significantly to at least 200 iterations of the 1,000 bootstrap analyses. Here, for each relevant variable data column 1 presents the number of bootstrap regression analyses to which the variable added significantly, data column 2 presents the average odds ratio regarding correct identification that the AUD proband father had problems with alcohol, and the average significance level of that OR is presented in data column 3. With a mean McFadden pseudo R2 of 0.36, 5 variables from the probands and one from the offspring significantly entered at least 200 bootstrap analyses. Significant items for probands that related to the offspring correctly indicating their father had alcohol problems included the father’s self-report of spending a lot of time using alcohol or recovering from its effects, being more likely to identify with a religion , the proband was more likely to report that he continued to drink despite social/interpersonal problems or despite physical/ psychological problems and that the proband had a parent who met criteria for an AUD.