Introduction

Alcohol use disorders (alcohol abuse and/or dependence, hereafter, AUD) are among the mental disorders with the highest prevalence rates worldwide [1]. The health risks associated with alcohol consumption increase in older people because their physical tolerance for alcohol decreases while the prevalence of some of the main risk factors for AUD (e.g., life stressors, solitude, social exclusion, physical illness and slower metabolism) is increasing [2,3]. Despite these data, few studies of people over 65 years of age have been conducted [3–6]. The available data indicate that approximately 60% of older people in Western countries have consumed alcohol during the past 12 months [3,4,7], but less than 20% report drinking excessively [6,8,9], and lower levels of alcohol consumption have been identified among those over the age of 65 years compared with younger adults. Thus, the research results on the lifetime prevalence of AUD are very heterogeneous. Reported lifetime prevalence rates include the 7.1% reported by Hanson et al. [10], the 8.9% prevalence of “heavy drinkers” identified by DiBari et al. [8] using biological and psychological screening methods, and the 17.8% prevalence of abuse and 12.5% prevalence of dependence reported by Hasin et al. [11]. The differences observed in studies with representative samples in the United States may be particularly relevant: The National Comorbidity Survey Replication (NCS-R) found prevalence rates of 8.4% [9], whereas NESARC reported 16.1% [12]. Regarding the AUD 12-month prevalence, variation was also observed; reported results vary from 0.1% in the ESEMeD studies [6] to 3% in the National Survey on Drug Use and Health in the United States [7] and from 0.7% in the study by Helmchen in Germany [13] to 0.9% in the Finnish population [14] or 1.5% in the NESARC study conducted in the United States [12]. In a recent meta-analysis of data from 25 epidemiological studies of mental health in older people conducted by Volkert and colleagues [5], only 7 studies included AUD information. Major variations in AUD prevalence were observed across these studies, with a standardized mean of 0.96% (95% CI [0.84–1.07]) and a lifetime AUD prevalence of 11.7% (95% CI [11.08–12.34]). It seems, that recent studies indicate potential biases in the estimation of alcohol use by older people measured through usual epidemiological study approaches [15]. Various factors may explain the differences identified in the reported AUD prevalence among older adults [5]. The definitions of ‘drinker’ or ‘heavy drinker’ vary [16], the sampling methods were not adapted to the cultural context of this population, and the instruments employed were designed for the general population and not for the unique characteristics of older people [17].

Aims of the study

We established the following study objectives: a) to collect descriptive information on the patterns of alcohol use; b) to identify the current, 12-month and lifetime prevalences of abuse, dependence and AUD; and c) to identify major factors associated with alcohol use and AUD in the population aged between 65 and 84 years residing in six cities in European and European-associated countries.

Materials and methods

The MentDis_ICF65+ study was a stepwise, cross-sectional, multi-center survey conducted in six European and Europe-associated cities (Hamburg, Germany; Ferrara, Italy; London-Canterbury, England; Madrid, Spain; Geneva, Switzerland; and Jerusalem, Israel). This work was supported by a grant from the European Commission (Grant No: 223105) within the 7^th Framework Research Program of the EU. A detailed description of the methodology has been provided elsewhere [18].

Results

The mean age of the participants was 73.7 years, and 50.6% of the participants were female. Additional sociodemographic characteristics are shown in Table 1.

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Table 1. Sociodemographic characteristics of the overall sample and the subsample of lifetime drinkers (people who reported drinking any type of alcoholic beverage at least 12 times during their lifetime).

https://doi.org/10.1371/journal.pone.0196574.t001

Regarding the alcohol use patterns observed in the overall sample, 67.8% [62.0;73.7] of the sample had consumed alcohol during the past 12 months, and 81.4% [75.3;87.5] had consumed alcohol at least once over the course of their lives. The indices for alcohol intake on a standard day during the past 12 months and over the course of the participants’ lifetime were calculated, and similar values were obtained for both periods (12-Month: 3.0 [2.7;3.4]; lifetime: 3.3 [2.2;4.5]) (see Table 2).

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Table 2. Past 12-month and lifetime alcohol use patterns (use of alcohol, and consumption indicator: Index^*) in the overall sample and the subsample of lifetime drinkers (people who reported drinking any type of alcoholic beverage at least 12 times during their lifetime).

https://doi.org/10.1371/journal.pone.0196574.t002

Table 3 presents the following estimated prevalence rates: current, 12-month and lifetime for abuse, dependence and AUD.

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Table 3. Current (last month), 12-month and lifetime prevalence of alcohol abuse, alcohol dependence and alcohol abuse and/or dependence disorders (AUD) by cities.

https://doi.org/10.1371/journal.pone.0196574.t003

As shown in Table 3, AUD had the highest overall prevalence, at 8.8% [4.5;13.2]; its lifetime prevalence was 5.3% [2.3;8.2], and it had the lowest prevalence during the past year (12-month) and the last month (current) at 1.1% [0.5;1.7]. Similar trends were identified in the prevalence of alcohol abuse (current: 1.2% [0.6;1.8]; 12-month: 5.0% [2.0;7.9]; lifetime: 8.4% [4.0;12.7]) and dependence (current: not estimable; 12-month: 1.2% [0.4;2.1]; lifetime: 2.3% [1.2;3.4]). In relation to the different cities participating in the study, a trend towards higher prevalence rates for all categories (abuse, dependence and AUD) and all reference periods was observed. The prevalence was higher in Hamburg, London-Canterbury and Geneva and lower in Ferrara, Madrid and Jerusalem (lowest in all categories). At the 12-month timepoint, differences of up to 5 times more AUD were observed in Hamburg, London and Geneva compared to Madrid, Ferrara and Jerusalem. The differences followed the same sense in the Abuse category and, although the same pattern was maintained, the differences in the Dependency category were minor. The results showed similar values for the current and lifetime prevalence.

The major factors associated with alcohol consumption (lifetime drinkers) and past 12-month and lifetime AUD were identified. Table 4 shows the ORs associated with the main sociodemographic and psychopathological variables, including the city in which the interview was performed. A significant gender*city interaction was identified for lifetime drinking and past 12-month AUD, and Fig 1 displays the adjusted prevalence for both genders within the cities.

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Table 4. Odds ratios for the associations between alcohol use disorders and sociodemographic characteristics and other mental disorders in the sample of lifetime drinkers and the sample of people who reported alcohol abuse and/or dependence disorders (AUD).

https://doi.org/10.1371/journal.pone.0196574.t004

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Fig 1. Marginal means (adjusted prevalence) for significant gender*city interactions in lifetime drinkers and people with AUD in the past 12 months.

Note: No women in Madrid met the criteria for past 12-month AUD.

https://doi.org/10.1371/journal.pone.0196574.g001

Regarding lifetime AUD prevalence, males had a 5-times-greater odds of AUD than women (OR = 5.3 [4.1;6.9]). Differences between cities were also identified: residents of Hamburg (OR = 5.4 [2.9;10.0]; p = 0.001), London-Canterbury (OR = 5.1 [2.5;10.2]; p = 0.001) and Geneva (OR = 5.4 [2.7;10.8]; p = 0.001) had a 5-times-greater odds of lifetime AUD than did residents of Madrid, whereas the odds of AUD in Ferrara (OR = 0.5 [0.3;1.0]; p = 0.059) and Jerusalem (OR = 0.9 [0.5;1.6]; p = 0.694) did not differ significantly from those in Madrid. Regarding lifetime drinking and 12-month AUD, we identified a significant gender*city interaction, indicating that the observed gender differences were not the same in all countries. Fig 1 shows that the prevalence of lifetime drinking was the lowest in Jerusalem. Moreover, the odds of lifetime drinking in Madrid, Ferrara, Geneva and Jerusalem were 3–4 times higher in males than females, whereas in London and Hamburg, the odds were 5–6 times higher in males than females. No significant gender difference was identified in the prevalence of 12-month AUD in Jerusalem (prevalence in both genders: 0.01, with an OR of 1.5 [0.4;4.9] for males; p = 0.532), whereas in all other cities, significant gender differences were observed, with the greatest difference identified in London (OR = 11.2 [8.4;15.0]) and the smallest difference identified in Ferrara (OR = 4.1 [1.6;10.2]). No women in Madrid met the criteria for past 12-month AUD (see Table 4, Fig 1).

The prevalence of lifetime alcohol consumption and 12-month and lifetime AUD tended to be lower in the older age groups. There were no significant differences in terms of marital status. The residence situation (living alone) was significantly associated with 12-month AUD only, and living alone was associated with a 2-fold increase in the odds of AUD (OR = 2.0 [1.0;3.8]). Financial situation was significantly and inversely associated with AUD (past 12-month and lifetime: p = 0.016, p = 0.005). Similarly, religious affiliation demonstrated an inverse association with lifetime drinking and past 12-month and lifetime AUD (p = 0.005; p = 0.015; p = 0.047). The odds of lifetime drinking increased by 10% with every additional year of schooling (OR 1.1 [1.1;1.2]) (see Table 4); however, no significant association was identified between schooling and AUD.

Past 12-month and lifetime AUD were associated with nicotine dependence (OR = 4.6 [2.6;8.0]; p = 0.001 and OR = 3.9 [2.5;6.0]; p = 0.001, respectively). There were also significant associations between having any depressive disorder (Major Depressive Disorder, Dysthymia) (OR = 0.1 [0.0;0.3]; p = 0.001) or any affective disorder (Major Depressive Disorder, Dysthymia, Any Bipolar Disorder) (OR = 4.3 [1.8;10.1]; p = 0.002) in the past year and alcohol abuse or dependence during the past 12 months (past 12-month AUD; see Table 4).

Discussion

This study found higher alcohol consumption and prevalence rates (current, 12-month and lifetime) of abuse, dependence and AUD than previous studies. Significant differences were also identified by gender and city.

The relative novelty of these results can be interpreted from two complementary viewpoints. On the one hand, the sampling strategy employed herein allowed us to include people over 80 years of age. Additionally, the instrument developed and employed in the study (CIDI65+) has shown good reliability in older people [20] for identifying different patterns of use, abuse, and dependence. We detected rates similar to those of previous studies in terms of lifetime consumption and prevalence using these strategies; however, we also identified noteworthy differences between our findings and the results of prior studies in terms of current (past month) and past 12-month prevalence. The higher prevalence rates identified herein may have occurred because non-age-adjusted instruments might produce biases (i.e., lower estimates) in older people [20,17].

Approximately 80% of the participants reported a lifetime consumption of alcohol, and over 65% reported 12-month consumption [4,7]. The following gender and age differences were identified: consumption was higher in males and lower in the older age groups. The odds of reporting alcohol consumption were almost twice as high in the 65- to 70-year age group than in the 80- to 84-year age group. For the recent timepoints (12 months and 1 month), this finding may be due to illnesses (and medications) that are incompatible with alcohol, greater diet control, slower metabolism, etc. However, for the lifetime prevalence, this phenomenon could be explained better by a cohort effect or some type or recall bias in the older population.

Moreover, many people who abuse alcohol may die before reaching old age (80 to 84 years) due to alcohol-induced illnesses. In contrast with the results of prior studies [7], the odds of consumption were only slightly higher in people with more years of schooling, but this association had no impact on past 12-month or lifetime AUD prevalence. The restricted age range for years of schooling variable (cut-off: 13 years) used in the present study may have contributed to the observed differences.

The prevalence of lifetime AUD in the sample is consistent with the results of the NCS-R [9] and DiBari et al. [8] studies, which were conducted using biological and behavioral markers in European samples, but were somewhat below the mean values obtained in the meta-analysis performed by Volkert et al. (11.71%) [5] and much lower than the values reported for the NESARC study [12]. Again, the oldest groups (80–84 years old) presented the lowest AUD prevalence. Moreover, gender differences in lifetime prevalence were found to be relevant. Similar to consumption, alcohol-related deaths, diseases and medications may explain the observed decrease in prevalence rates.

One of our most striking findings was that the 12-month prevalence data indicate relatively high levels of alcohol abuse, levels that were higher than those observed in previous studies. This level of abuse was far higher than the 0.96% reported by Volkert et al. (2013) [5] in their meta-analysis, the 0.1% identified in the ESEMeD [6] studies, the 0.7% identified by Pirkola et al. [14) and the 0.9% observed by Helmchen et al. [13], all of which included European samples. The results also deviate from North American studies, which have indicated prevalence rates ranging from 1.5% in the NESARC study [12] to 2.98% in the NSDUH study [7]. However, the results of this study were consistent with those of Waern et al. [23], who, in a recent cohort study conducted in Sweden, found that alcohol consumption in 75-year-olds had increased from 1975 to 2005 in both genders and all the categories studied (e.g., beer, wine, spirits, total grams of alcohol and times per week). These authors reported that the prevalence rates of at-risk drinking (this rate did not include diagnoses) were 19.3% in men and 0.6% in women for the earlier-born cohort (1901) and 27.4% in men and 10.4% in women for the later-born cohort (1930).

In general, these results were in accordance with previous studies that reported positive associations between AUD and affective and other substance use disorders (nicotine) in general population samples [24, 25]. More recent work has also revealed strong relationships between these factors and alcohol dependence [26, 27].

The differences in consumption and AUD prevalence observed among study cities may be particularly relevant. These differences (more consumption, abuse and AUD in Hamburg, London-Canterbury and Geneva) may be related to cultural patterns of alcohol consumption, as some European studies have suggested. The Food in Later Life Project [28] seems to identify different social patterns of alcohol use in Mediterranean countries versus central European and Nordic countries, and the IAS [29] suggested similar results. From a more international perspective, the WHO [30] has reported the existence of different alcohol consumption patterns in different cultural settings, showing that alcohol consumption may be culturally mediated (e.g., Mediterranean countries with a culture of wine production and consumption vs. central European countries and Great Britain, which have a higher consumption of distilled alcohol or beer). However, our findings should be interpreted with caution as we also observed a strong interaction between city and gender, which precludes simple interpretations of consumption and past 12-month prevalence. Both genders exhibited greater odds of alcohol consumption in Hamburg, London/Canterbury and Geneva than in Madrid. The past 12-month prevalence rates showed similar differences, but they were only significant for males.

To increase life expectancy and improve the health and quality of life of older people, it is essential to attend to their physical and mental health [31]. Despite the significant presence of mental health problems in the elderly, the evidence reveals a dual reality. On the one hand, there is a lack of specialized mental health services and interventions designed for the elderly [32, 33], and on the other hand, elderly adults in some countries have difficulty accessing specialized services [34, 35, 36].

A special point about the use of DSM-IV-TR criteria as a measure of psychological disorders among older adults should be noted. The DSM criteria probably underestimate the prevalence of depression and anxiety among older adults [17, 37]. This point could be related to the risk of having to respond to the difficulty to remember the symptoms or the difficulty to associate the symptoms with the psychological distress, among others [20]. Considering the previous facts and despite the limitations of the study (e.g., a relatively low sample size by city, resulting in a low test power; inclusion of a community-dwelling population only; possible recall bias related to lifetime consumption) the evidence suggests that action should be taken to ensure that older people with mental problems receive the best possible care. In this sense, different complementary pathways of action are proposed:

• Designing specialized health care services and interventions for older people that include comprehensive care strategies to address comorbidities and the specifics of physical and psychological disorders in this population. According to the NICE guidelines, the best treatment options for mental health problems in the elderly combine medical and psychological treatments [38]. Older people show motivation to change (including abstain) and they respond well to brief advice and motivational therapy [33]. Furthermore, recent studies suggest that intensive interventions with personalized feedback, physician advice, educational materials plus follow-up could be effective [39].
• Implementing psychological awareness programs in the primary care setting to identify possible psychological and mental disorders and offer stepped interventions that can be adapted to individual needs [40]. In some cases, simple interventions (e.g., brief interventions combined with advice to reduce drinking) could also have a positive effect [39] and could be used in a stepped intervention model.
• Optimizing this population’s access to existing specialized mental health services in each city.

These efforts may include supporting social transformation processes that strive to eliminate the social exclusion of older people with mental disorders and designing a new generation of social and health services that recognize the specific needs of the older population from a holistic and inclusive perspective.