Association of coincident self-reported mental health problems and alcohol intake with all-cause and cardiovascular disease mortality: A Norwegian pooled population analysis.

BACKGROUND: The disease burden attributable to mental health problems and to excess or harmful alcohol use is considerable. Despite a strong relationship between these 2 important factors in population health, there are few studies quantifying the mortality risk associated with their co-occurrence in the general population. The aim of this study was therefore to investigate cardiovascular disease (CVD) and all-cause mortality according to self-reported mental health problems and alcohol intake in the general population. METHODS AND
FINDINGS: We followed 243,372 participants in Norwegian health surveys (1994-2002) through 2014 for all-cause and CVD mortality by data linkage to national registries. The mean (SD) age at the time of participation in the survey was 43.9 (10.6) years, and 47.8% were men. During a mean (SD) follow-up period of 16.7 (3.2) years, 6,587 participants died from CVD, and 21,376 died from all causes. Cox models estimated hazard ratios (HRs) with 95% CIs according to a mental health index (low, 1.00-1.50; high, 2.01-4.00; low score is favourable) based on the General Health Questionnaire and the Hopkins Symptom Checklist, and according to self-reported alcohol intake (low, <2; light, 2-11.99; moderate, 12-23.99; high, ≥24 grams/day). HRs were adjusted for age, sex, educational level, marital status, and CVD risk factors. Compared to a reference group with low mental health index score and low alcohol intake, HRs (95% CIs) for all-cause mortality were 0.93 (0.89, 0.97; p = 0.001), 1.00 (0.92, 1.09; p = 0.926), and 1.14 (0.96, 1.35; p = 0.119) for low index score combined with light, moderate, and high alcohol intake, respectively. HRs (95% CIs) were 1.22 (1.14, 1.31; p < 0.001), 1.24 (1.15, 1.33; p < 0.001), 1.43 (1.23, 1.66; p < 0.001), and 2.29 (1.87, 2.80; p < 0.001) for high index score combined with low, light, moderate, and high alcohol intake, respectively. For CVD mortality, HRs (95% CIs) were 0.93 (0.86, 1.00; p = 0.058), 0.90 (0.76, 1.07; p = 0.225), and 0.95 (0.67, 1.33; p = 0.760) for a low index score combined with light, moderate, and high alcohol intake, respectively, and 1.11 (0.98, 1.25; p = 0.102), 0.97 (0.83, 1.13; p = 0.689), 1.01 (0.71, 1.44; p = 0.956), and 1.78 (1.14, 2.78; p = 0.011) for high index score combined with low, light, moderate, and high alcohol intake, respectively. HRs for the combination of a high index score and high alcohol intake (HRs: 2.29 for all-cause and 1.78 for CVD mortality) were 64% (95% CI 53%, 74%; p < 0.001) and 69% (95% CI 42%, 97%; p < 0.001) higher than expected for all-cause mortality and CVD mortality, respectively, under the assumption of a multiplicative interaction structure. A limitation of our study is that the findings were based on average reported intake of alcohol without accounting for the drinking pattern.
CONCLUSIONS: In the general population, the mortality rates associated with more mental health problems and a high alcohol intake were increased when the risk factors occurred together.

Introduction

Excessive and harmful alcohol consumption is associated with violence and accidents and chronic diseases such as cancer and cardiovascular disease (CVD), and is a leading contributor to the disease burden in many countries [1]. Alcohol drinking guidelines inform the public about levels and patterns of drinking that are less harmful, as judged by estimates of average risk in the general population [2,3]. They also give reasons to avoid alcohol, such as in specific groups where the health consequences of alcohol could be worse than in the general population [4,5].

Guidelines in both Canada and the UK mention mental health problems as a reason to avoid alcohol [2,3]. The recommendation is based on evidence of a positive association between alcohol intake or alcohol use disorder and mental health problems [6-9], and there is a possibility that mental health problems could worsen because of drinking. The disease burden attributed to mental health problems is considerable [10-14]. Excess or harmful alcohol use could have a negative influence on mental health by interfering with social relationships and environments that underlie mental well-being, such as family relations and employment [6], or through direct biological mechanisms that reduce grey and white matter brain volume or interfere with neurotransmitter functioning [15]. On the other hand, there is evidence suggesting that acute or chronic symptoms of mental distress might lead to an increase in alcohol intake [16,17], supporting the ‘self-medication theory’. In addition, a positive association between alcohol use and mental health problems could also arise or be explained in part by genetic or environmental factors influencing both alcohol use and mental health [18,19].

A bi-directional relationship between mental health and alcohol intake, or shared genetic or environmental factors, could lead to negative feedback cycles [8] that over time contribute to more mental health problems, heavier alcohol or psychotropic drug use, poor diet, physical inactivity, and a less protective social and socioeconomic environment. The consequence could be an increased mortality risk among individuals in the general population who both experience mental health problems and drink alcohol, but few studies have quantified this relationship [20]. We provide relevant data from a large pooled sample of population-based cardiovascular health surveys in Norway, focusing on the quantity of alcohol intake and intensity of mental health problems reported by people in the general population. The first objective was to estimate the risk of mortality from all causes and CVD according to self-reported alcohol intake and according to self-reported mental health problems separately. The second objective was to investigate whether risks of all-cause and CVD-related mortality are increased in persons who report mental health problems and alcohol intake in combination, which would suggest an interaction between mental health problems and alcohol intake.

Methods

Study population selection, data linkage, and ethical approval

The Age 40 Program is a collection of cardiovascular health surveys that invited all men and women aged 40–42 years living in 13 out of 19 counties in Norway to participate. The Cohort of Norway (CONOR) is a collection of population-based cardiovascular health surveys from different geographical areas in Norway, both rural and urban, where various age groups were invited [21]. To conduct this study, we identified surveys within the Age 40 Program and CONOR that measured both alcohol intake and mental health problems. The identified surveys were performed between 1994 and 2002, had a response rate ranging from 38% to 78%, and constitute a source population of 307,541 visits, where both sexes are rather equally represented and where approximately 73% were in the age range 35 to 50 years at the time of participation in the survey (S1 Table). Use of the term ‘visits’ reflects the fact that a small proportion of individuals attended more than 1 survey. The vast majority, however, attended only a single survey and were represented by a single visit. The overlap was coincidental, with the exception of 2 surveys from the Tromsø study, where a large proportion of the participants in the fifth survey were previous participants in the fourth survey.

When selecting the study population, we only allowed each individual to be represented by a single visit. For the small proportion with multiple visits, we choose the first for individuals who attended the fourth and fifth survey of the Tromsø study (n = 7,017). For individuals who coincidentally attended a survey in CONOR and in the Age 40 Program, we placed an arbitrary priority on CONOR, but chose the visit from the Age 40 Program if data on drinking status were missing in CONOR. Individuals with missing or inconsistent survey data on alcohol, mental health, or covariates were excluded, as well as individuals missing covariate or outcome data obtained by registry linkage (S1 Fig).

This study is based on person-level data from health surveys and national registries. The personal identification number (PIN) that is unique to each Norwegian resident ensures nearly complete linkage. Statistics Norway received data from the data sources, replaced the PIN with a dummy ID number, and sent the data to the authors. The authors could then link the data. The Regional Committee for Medical and Health Research Ethics South-East (11/1676) approved the study and gave exemption regarding consent in the surveys where this was not obtained. This study is reported as per the Reporting of Studies Conducted Using Observational Routinely-Collected Health Data (RECORD) guideline, which is an extension of the Strengthening the Reporting of Observational Studies in Epidemiology (STROBE) guideline (S1 Checklist). The study is part of a larger research project with a prospective protocol (S1 Protocol). In S1 Text, we provide an overview of differences between the conducted study and the planned study as described in the protocol. Data cleaning, harmonisation of survey data, selection of the study population, and statistical analyses were performed using R statistical software (S2 Text).

Mental health index

A mental health index modified from the General Health Questionnaire [22] and the Hopkins Symptom Checklist [23] assessed self-reported mental health in the surveys (S3 Text). The index correlates with the Hopkins Symptom Checklist and the Hospital Anxiety and Depression Scale [24]. It is based on 7 questions that inquire whether the person in the past 2 weeks ever felt ‘nervous and unsettled’, ‘troubled by anxiety’, ‘secure and calm’, ‘irritable’, ‘happy and optimistic’, ‘sad/depressed’, or ‘lonely’. We scored the 4 possible answers (‘no’ = 1, ‘a little’ = 2, ‘quite a bit’ = 3, and ‘very’ = 4), and, by reversing the scores for the questions ‘secure and calm’ and ‘happy and optimistic’, we obtained for each individual a sum score (range 7–28) and a mean score per question (1–4), in which higher scores indicate more problems. To increase sample size, we replaced a single missing value by the sample mean value for that question. Participants missing 2 or more values were excluded. The index was categorised as follows based on the mean score per question: low, 1.00–1.50; medium, 1.51–2.00; and high, 2.01–4.00.

Alcohol consumption

Questions relevant to alcohol intake differed between surveys (S1 Table). Only a few surveys provided data on lifetime abstaining, and we therefore defined lifetime and current abstainers collectively as current abstainers. We estimated the average intake of alcohol (grams/day) among current drinkers using 2 methods depending on the data available in each survey. The first method used the question ‘How many glasses of beer, wine, or spirits do you usually drink during a two-week period?’, which was answered separately for each beverage type (range 0–50, higher values truncated). For individuals with data on at least 1 beverage type, the number of glasses were added together and the sum divided by 14. Conversion from glasses to grams of alcohol was performed using the following definitions: 1 litre of pure alcohol is 789 grams, a glass of beer is 33.3 cl and 4.5% alcohol (11.8 grams), a glass of wine is 15 cl and 12% alcohol (14 grams), and a glass of liquor is 4 cl and 40% alcohol (12.6 grams). The second method combined drinking frequency obtained from the question ‘Approximately how often during the past year have you consumed alcohol?’ (‘A few times last year’ = 6 times/year, ‘Approximately 1 time a month’ = 12 times/year, ‘2–3 times a month’ = 30 times/year, ‘Approximately 1 time a week’ = 52 times/year, ‘2–3 times a week’ = 130 times/year, and ‘4–7 times a week’ = 286 times/year), with the reported number of glasses consumed per occasion (0–20, higher values truncated) obtained from the question ‘When you drank alcohol, how many glasses did you usually drink?’ The calculated number of glasses per year was divided by 365 and converted to grams of alcohol (1 glass = 12.8 grams of pure alcohol). Alcohol intake was categorised as follows: current abstainers; low, <2 grams/day; light, 2–11.99 grams/day; moderate, 12–23.99 grams/day; and high, ≥24 grams/day.

Covariates

Marital status at survey participation (married, divorced, separated/widowed, never married) was ascertained using the National Registry. The National Education Database provided data on the highest level of attained education (range 1–8; 1 = primary school and 8 = master’s degree or higher). Questionnaires provided data on smoking status, level of physical activity (range 1–4), history of diabetes, history of CVD, and family history of coronary heart disease. In some surveys, questionnaires also provide data on the use of antidepressants and tranquillizers in the last 4 weeks (yes/no) and whether the person has ever sought help for psychological problems (yes/no). Smoking status was defined as never, light former, heavy former, light current, and heavy current smoker (light and heavy defined by ≤20 and >20 pack years). We obtained systolic blood pressure (mm Hg), resting heart rate (bpm), and body mass index (BMI, kg/m2) from objective measurements performed by survey personnel. Serum triglycerides (mmol/l), total cholesterol, and high-density lipoprotein cholesterol (HDL-C) were obtained using biochemical measurements in non-fasting blood samples taken by study personnel.

Outcome

Participants were followed until emigration (until December 31, 2012), death, or December 31, 2014. Emigration status was obtained from the National Registry, and mortality data from the Norwegian Cause of Death Registry. Cause of death is based on certificates filled out by on-site medical doctors, and occasionally (4.3% in 2015) on autopsies [25]. The 9th (1994–95) and 10th (1996–2014) revision of the International Classification of Diseases (ICD) were used to identify deaths from all causes and from CVD (ICD–9: 390–459; ICD–10: I00–I99).

Statistical analysis

We first described the distribution of covariate values according to categories of the mental health index and alcohol intake. Analysis of variance and the chi-squared test were used to assess differences between groups. Next, we visualised the crude association of alcohol intake with the mental health index, and assessed the age- and sex-adjusted association using ordinary linear regression. The first objective was to assess the separate associations of mental health problems and of alcohol intake with all-cause and CVD mortality. To address this, we used Cox proportional hazard models to estimate hazard ratios (HRs), 95% CIs, and p-values according to the mental health index and according to alcohol intake (separate analysis). Time on study was used as the timescale. To address the second objective of a potential interaction between mental health and alcohol intake, we present HRs for their association within strata of each other (stratified analysis) and for their joint association by using a common reference category (joint analysis). This setup provides the information required to interpret the interaction from different perspectives, to assess the influence from covariates, and to perform recalculations [26,27]. For the separate, joint, and stratified analyses, we fitted an unadjusted Cox model, a model adjusted for age and sex, and a model further adjusted for smoking status, education, marital status, history of CVD, BMI, heart rate, physical activity, diabetes, family history of coronary heart disease, serum cholesterol, and serum triglycerides. Age, BMI, serum cholesterol, and serum triglycerides were fitted as linear variables, and the other variables were fitted as categorical variables. These covariates were included because they could confound associations involving alcohol intake and mental health. We left out HDL-C (only available for a smaller sample) and blood pressure because they were more likely to play a mediating role in associations involving alcohol intake. The decision to exclude blood pressure did not materially alter risk estimates in analyses involving mental health.

In the separate, stratified, and joint analyses, we estimated HRs using categorical exposure variables, with a low mean score on the mental health index (1.00–1.50) and a low alcohol intake (<2 grams/day) as the single or combined reference category, where applicable. Based on HRs from the joint analysis, we tested for interaction by assessing whether the observed joint HR differed from the expected joint HR using a multiplicative interaction structure. We did this for all possible combinations of the exposure categories. Specifically, we divided the observed joint HR for a given combination (e.g., moderate index score + moderate alcohol intake) by the expected joint HR (e.g., the product of the HRs from moderate index score + low alcohol intake and low index score + moderate alcohol intake). Standard errors and 95% CIs were obtained using the Delta method. In the separate and stratified analyses, we also estimated HRs per unit increase of the exposure variables on a continuous scale (for average alcohol intake among current drinkers only), used interaction terms (to test for a difference in slope) as a complementary test for interaction, and present the associations graphically to support the interpretation of the associations. The functional form of the associations was obtained by including the continuous exposure variables as penalised smoothed splines in Cox models adjusted for age and sex. The regression terms (log HR) were plotted as a function of the mental health index and alcohol intake. The function is centred (log HR = 0) at the mean value of the predictors.

Lastly, we used ordinary linear regression to assess whether self-reporting of alcohol intake was consistent with alcohol intake as judged by HDL-C [28]. HDL-C was regressed on age, sex, and average alcohol intake (current drinkers only), and the results are presented as regression coefficients with 95% CIs. Analyses were repeated among men and women with different scores on the mental health index to assess the possibility of differential bias in self-reporting, together with interaction terms to test for a difference in slope.

Results

Study population

The source population comprised 295,126 participants, of whom 12,415 had participated in more than 1 of the health surveys. Among these individuals with overlapping participation, we selected 1 visit. Next, we excluded in total 51,754 (17.5%) participants for missing values: Participants were excluded for missing drinking status (n = 6,655), leaving 288,471 individuals with current drinking status, and for missing values on the mental health index (n = 28,278), alcohol intake among current drinkers (n = 8,713), follow-up data (n = 21), or covariate data (n = 8,087). The number of participants available for statistical analyses was 243,372 (S1 Fig).

Potentially eligible individuals excluded for missing values were on average older, more likely to be male, and more likely to have died from any cause and CVD during follow-up than individuals in the source population (S2 Table). As a result, the proportion of people dying among complete cases in the study population was somewhat lower than in the source population.

Participant characteristics

Participant characteristics (Tables 1 and S3) were unevenly distributed according to the mental health index and alcohol intake. Participants with higher scores on the mental health index were more often women, had less education on average, and were more likely to have ever been married and to have a history of diabetes and CVD. They also had less favourable levels of CVD risk factors including more drinking and current smoking, less physical activity, higher heart rate, and higher serum triglycerides. Participants with a higher score on the mental health index were more likely to have used antidepressants and tranquillizers in the last 4 weeks, as well as to have sought help for psychological problems, within the subsets where this information was assessed. Participants who drank more alcohol were more often male, more likely to have ever been married, had higher serum HDL-C and triglycerides on average, and to a large extent had also attained more education and reported more physical activity on average. Current abstainers were less likely to be a current or previous smoker than current drinkers. Among current drinkers, alcohol intake was positively associated with current light and with current and previous heavy smoking. We observed a non-linear distribution pattern for age, systolic blood pressure, diabetes, and history of CVD. Drinkers reporting light (2–11.99 grams/day) and moderate (12–23.99 grams/day) alcohol intake were younger and had lower blood pressure, less diabetes, and less previous CVD in comparison with current abstainers and drinkers with low intake (<2 grams/day) and high intake (≥24 grams/day). Current abstainers and drinkers with a high alcohol intake were more likely to have used antidepressants or tranquillizers during the past 4 weeks, as well as more likely to have ever sought help for psychological problems, than drinkers reporting low, light, and moderate intake of alcohol.

Table 1

Descriptive statistics according to self-reported mental health problems and alcohol intake in the study population.

Characteristic	Mental health index(mean score)	n	All participants(n = 243,372)	Current abstainers(n = 22,496)	Average intake of alcohol (grams/day)				p-Value
					Low(<2 grams/day)(n = 85,961)	Light(2–11.99 grams/day)(n = 116,170)	Moderate(12–23.99 grams/day)(n = 15,944)	High(≥24 grams/day)(n = 2,801)
Sex (male)	All	243,372	116,218 (47.8%)	7,942 (35.3%)	32,930 (38.3%)	60,847 (52.4%)	12,110 (76.0%)	2,389 (85.3%)	<0.001
	1.00–1.50	148,428	73,888 (49.8%)	4,917 (37.3%)	21,336 (40.7%)	39,375 (54.4%)	7,088 (77.4%)	1,172 (87.0%)	<0.001
	1.51–2.00	71,546	32,759 (45.8%)	2,164 (33.5%)	8,889 (35.6%)	17,120 (50.1%)	3,799 (75.4%)	787 (84.7%)	<0.001
	2.01–4.00	23,398	9,571 (40.9%)	861 (30.0%)	2,705 (31.6%)	4,352 (44.9%)	1,223 (69.8%)	430 (81.9%)	<0.001
	p-Value		<0.001	<0.001	<0.001	<0.001	<0.001	0.016
Age	All	243,372	43.9 (10.6)	49.0 (14.2)	44.6 (11.4)	42.6 (9.0)	42.8 (9.1)	43.9 (10.4)	<0.001
	1.00–1.50	148,428	43.9 (10.5)	48.8 (14.0)	44.5 (11.4)	42.6 (8.9)	43.0 (9.3)	44.3 (10.6)	<0.001
	1.51–2.00	71,546	43.9 (10.7)	49.3 (14.3)	44.7 (11.5)	42.5 (8.9)	42.6 (8.9)	44.0 (10.5)	<0.001
	2.01–4.00	23,398	44.4 (11.1)	49.8 (14.6)	44.9 (11.6)	42.9 (9.3)	42.7 (8.8)	42.8 (9.2)	<0.001
	p-Value		<0.001	<0.001	<0.001	0.442	0.032	0.007
Mental health index (1–4)	All	243,372	1.51 (0.42)	1.54 (0.48)	1.51 (0.43)	1.49 (0.40)	1.54 (0.44)	1.67 (0.55)	0.012
	1.00–1.50	148,428	1.25 (0.15)	1.24 (0.15)	1.25 (0.15)	1.25 (0.15)	1.26 (0.15)	1.26 (0.15)	<0.001
	1.51–2.00	71,546	1.72 (0.15)	1.73 (0.15)	1.72 (0.15)	1.71 (0.15)	1.72 (0.15)	1.73 (0.15)	0.002
	2.01–4.00	23,398	2.48 (0.37)	2.53 (0.40)	2.49 (0.37)	2.46 (0.35)	2.49 (0.36)	2.61 (0.44)	0.007
	p-Value		<0.001	<0.001	<0.001	<0.001	<0.001	<0.001
Average alcohol intake (grams/day)	All	220,876	4.64 (5.81)	—	0.57 (0.71)	5.38 (2.57)	15.9 (3.12)	34.6 (12.8)	<0.001
	1.00–1.50	135,254	4.48 (5.34)	—	0.58 (0.71)	5.34 (2.55)	15.8 (3.09)	32.9 (10.8)	<0.001
	1.51–2.00	65,091	4.79 (5.94)	—	0.57 (0.70)	5.44 (2.59)	15.9 (3.11)	34.2 (11.5)	<0.001
	2.01–4.00	20,531	5.20 (7.90)	—	0.51 (0.68)	5.48 (2.64)	16.2 (3.23)	39.9 (17.6)	<0.001
	p-Value		<0.001	—	<0.001	<0.001	<0.001	<0.001
Education (1–8)	All	243,372	4.05 (1.64)	3.67 (1.66)	3.82 (1.58)	4.23 (1.63)	4.44 (1.68)	4.31 (1.75)	<0.001
	1.00–1.50	148,428	4.08 (1.63)	3.78 (1.67)	3.84 (1.57)	4.25 (1.62)	4.49 (1.66)	4.49 (1.71)	<0.001
	1.51–2.00	71,546	4.08 (1.66)	3.64 (1.68)	3.85 (1.60)	4.26 (1.65)	4.45 (1.69)	4.35 (1.77)	<0.001
	2.01–4.00	23,398	3.75 (1.64)	3.21 (1.54)	3.60 (1.58)	3.98 (1.64)	4.13 (1.74)	3.78 (1.74)	<0.001
	p-Value		<0.001	<0.001	<0.001	<0.001	<0.001	<0.001
Ever married	All	243,372	47,686 (19.6%)	3,353 (14.9%)	15,899 (18.5%)	23,310 (20.1%)	4,216 (26.4%)	908 (32.4%)	<0.001
	1.00–1.50	148,428	27,161 (18.3%)	1,782 (13.5%)	9,230 (17.6%)	13,579 (18.8%)	2,185 (23.9%)	385 (28.6%)	<0.001
	1.51–2.00	71,546	15,061 (21.1%)	1,033 (16.0%)	4,900 (19.6%)	7,399 (21.7%)	1,420 (28.2%)	309 (33.3%)	<0.001
	2.01–4.00	23,398	5,464 (23.4%)	538 (18.8%)	1,769 (20.7%)	2,332 (24.1%)	611 (34.9%)	214 (40.8%)	<0.001
	p-Value		<0.001	<0.001	<0.001	<0.001	<0.001	<0.001
Current smoker	All	243,372	83,359 (34.3%)	3,635 (16.2%)	28,425 (33.1%)	42,698 (36.8%)	7,153 (44.9%)	1,448 (51.7%)	<0.001
	1.00–1.50	148,428	47,112 (31.7%)	1,696 (12.9%)	16,216 (30.9%)	24,854 (34.4%)	3,735 (40.8%)	611 (45.4%)	<0.001
	1.51–2.00	71,546	25,426 (35.5%)	1,070 (16.6%)	8,473 (34.0%)	13,018 (38.1%)	2,388 (47.4%)	477 (51.3%)	<0.001
	2.01–4.00	23,398	10,821 (46.2%)	869 (30.3%)	3,736 (43.6%)	4,826 (49.8%)	1,030 (58.8%)	360 (68.6%)	<0.001
	p-Value		<0.001	<0.001	<0.001	<0.001	<0.001	<0.001
Physical activity (1–4)	All	243,372	2.04 (0.94)	1.80 (0.92)	1.95 (0.93)	2.13 (0.94)	2.19 (0.96)	2.08 (0.96)	<0.001
	1.00–1.50	148,428	2.09 (0.95)	1.87 (0.94)	2.00 (0.95)	2.18 (0.95)	2.25 (0.96)	2.16 (0.98)	<0.001
	1.51–2.00	71,546	2.00 (0.92)	1.74 (0.89)	1.91 (0.91)	2.08 (0.92)	2.14 (0.94)	2.07 (0.94)	<0.001
	2.01–4.00	23,398	1.85 (0.91)	1.62 (0.87)	1.77 (0.88)	1.96 (0.91)	2.01 (0.96)	1.87 (0.93)	<0.001
	p-Value		<0.001	<0.001	<0.001	<0.001	<0.001	<0.001
BMI (kg/m2)	All	243,372	25.7 (3.90)	26.3 (4.52)	25.8 (4.18)	25.4 (3.59)	25.8 (3.50)	26.0 (3.70)	<0.001
	1.00–1.50	148,428	25.7 (3.81)	26.3 (4.40)	25.8 (4.06)	25.5 (3.52)	25.9 (3.47)	26.2 (3.58)	<0.001
	1.51–2.00	71,546	25.6 (3.95)	26.3 (4.55)	25.8 (4.25)	25.3 (3.64)	25.7 (3.47)	26.1 (3.77)	<0.001
	2.01–4.00	23,398	25.8 (4.33)	26.7 (4.92)	26.0 (4.62)	25.4 (3.93)	25.6 (3.75)	25.5 (3.83)	<0.001
	p-Value		0.590	<0.001	0.055	<0.001	<0.001	<0.001
Systolic blood pressure (mm Hg)	All	243,372	130.1 (17.4)	134.4 (21.7)	130.1 (18.1)	128.9 (16.1)	132.2 (15.7)	134.4 (16.1)	<0.001
	1.00–1.50	148,428	130.5 (17.4)	134.6 (21.4)	130.6 (18.0)	129.3 (16.1)	132.6 (15.8)	135.1 (16.1)	<0.001
	1.51–2.00	71,546	129.6 (17.5)	134.3 (22.0)	129.6 (18.3)	128.3 (16.0)	131.7 (15.7)	133.9 (16.1)	<0.001
	2.01–4.00	23,398	129.2 (17.8)	134.4 (22.4)	128.7 (17.9)	127.6 (16.3)	131.2 (15.3)	133.8 (15.8)	<0.001
	p-Value		<0.001	<0.001	<0.001	<0.001	<0.001	0.063
Use of antidepressants in the last 4 weeks (yes)	All	27,028	1,008 (3.7%)	78 (7.4%)	385 (4.1%)	401 (3.0%)	96 (3.8%)	48 (7.4%)	<0.001
	1.00–1.50	14,785	189 (1.3%)	12 (2.2%)	73 (1.4%)	86 (1.1%)	12 (0.9%)	6 (2.0%)	0.072
	1.51–2.00	8,956	333 (3.7%)	19 (6.1%)	137 (4.4%)	128 (2.8%)	32 (3.8%)	17 (7.9%)	<0.001
	2.01–4.00	3,287	486 (14.8%)	47 (23.5%)	175 (15.3%)	187 (12.8%)	52 (15.4%)	25 (17.9%)	0.001
	p-Value		<0.001	<0.001	<0.001	<0.001	<0.001	<0.001
Use of tranquillizers in the last 4 weeks (yes)	All	27,069	1,206 (4.5%)	100 (9.4%)	441 (4.7%)	486 (3.6%)	119 (4.7%)	60 (9.3%)	<0.001
	1.00–1.50	14,785	212 (1.4%)	22 (4.1%)	83 (1.6%)	81 (1.1%)	20 (1.5%)	6 (2.0%)	<0.001
	1.51–2.00	8,975	402 (4.5%)	26 (8.3%)	150 (4.9%)	171 (3.8%)	37 (4.4%)	18 (8.4%)	<0.001
	2.01–4.00	3,309	592 (17.9%)	52 (25.9%)	208 (17.9%)	234 (15.9%)	62 (18.1%)	36 (26.7%)	0.001
	p-Value		<0.001	<0.001	<0.001	<0.001	<0.001	<0.001
Ever sought help for a psychological problem (yes)	All	108,744	12,531 (11.5%)	1,443 (15.6%)	4,737 (11.8%)	5,249 (10.2%)	847 (12.4%)	255 (18.9%)	<0.001
	1.00–1.50	65,292	3,384 (5.2%)	360 (6.7%)	1,328 (5.5%)	1,467 (4.7%)	182 (4.8%)	47 (7.3%)	<0.001
	1.51–2.00	32,362	4,674 (14.4%)	485 (18.2%)	1,746 (14.9%)	2,039 (13.3%)	329 (14.9%)	75 (17.3%)	<0.001
	2.01–4.00	11,090	4,473 (40.3%)	598 (47.3%)	1,663 (40.2%)	1,743 (37.9%)	336 (41.3%)	133 (47.8%)	<0.001
	p-Value		<0.001	<0.001	<0.001	<0.001	<0.001	<0.001

Values are presented as mean (standard deviation) or count (percentage). Group differences were assessed with analysis of variance and the chi-squared test. Mental health index is presented as the mean score per question (range 1–4) on the 7 questions that constitute the mental health index, where a high score indicates a greater number of self-reported mental health issues. We present attained education and physical activity at the mean values of 8 and 4 ordinal categories, respectively, where a higher mean value indicates higher education and higher activity level.

Alcohol intake and the mental health index

The crude relationship between alcohol intake and the mental health index appeared non-linear (S2 Fig; Table 1). The analysis adjusted for age and sex showed that the mean score on the mental health index was, in comparison with people drinking <2 grams/day, slightly lower and thus more favourable among participants with a light alcohol intake, slightly higher among current abstainers and participants with a moderate intake, and considerably higher among participants with a high intake. The regression coefficients (95% CIs) were 0.033 (0.027, 0.039; p < 0.001) among current abstainers and −0.011 (−0.015, −0.007; p < 0.001), 0.051 (0.044, 0.059; p < 0.001), and 0.187 (0.171, 0.202; p < 0.001) among participants with light, moderate, and high average alcohol intake, respectively, in comparison with a low intake.

Mental health and the risk of all-cause and CVD mortality

The mean (SD) follow-up time in the study population was 16.7 (3.2) years, with a minimum of 0 days and a maximum of 20.3 years. In total, 21,376 participants died and 6,587 died from CVD in this period. The visualisation of the associations between the mental health index and all-cause and CVD mortality supported a linear relationship with both outcomes (Fig 1). In formal analyses (S4 Table), the age- and sex-adjusted HRs (95% CIs) per unit increase in the mean score per question on the mental health index were 1.35 (1.32, 1.39; p < 0.001) for all-cause mortality and 1.29 (1.22, 1.36; p < 0.001) for CVD mortality. These estimates were attenuated to 1.17 (1.14, 1.21; p < 0.001) and 1.07 (1.01, 1.13; p = 0.020) in multivariable adjusted analysis, respectively.

Fig 1

Visualisation of the association between mental health problems (mental health index, mean score per question, range 1–4) and all-cause and cardiovascular disease mortality among all participants (n = 243,372).

The mental health index was fitted as a continuous variable using penalised smoothed splines in a Cox model adjusted for age and sex. The vertical axis shows the log hazard ratio (the exponential value is equivalent to the hazard ratio). The solid line depicts the spline and the dashed curves depict twice the standard error (as plotted by the termplot function in R statistical software, which was used for visualisation). Twice the standard error is a close approximation of a 95% confidence interval, as 95% of the values fall within 1.96 × standard error of the mean if the values are normally distributed. The curve is centred (log hazard ratio = 0) at the mean value of the predictors (mean score: 1.51). The y-axis is fixed between −0.5 and 1.5.

Alcohol intake and the risk of all-cause and CVD mortality

In comparison with drinkers with a low alcohol intake, the multivariable adjusted HRs (95% CIs) for all-cause mortality were 1.19 (1.15, 1.24; p < 0.001) among current abstainers, and 0.93 (0.90, 0.96; p < 0.001), 1.03 (0.97, 1.09; p = 0.386), and 1.33 (1.19, 1.48; p < 0.001), respectively, among drinkers reporting light, moderate, and high alcohol intake (S5 Table). Multivariable adjusted HRs (95% CIs) for CVD mortality were, in comparison with drinkers with a low alcohol intake, 1.25 (1.18, 1.34; p < 0.001) among current abstainers and 0.90 (0.85, 0.96; p = 0.001), 0.93 (0.82, 1.05; p = 0.257), and 1.04 (0.83, 1.31; p = 0.724), respectively, among drinkers reporting light, moderate, and high alcohol intake.

Interaction between mental health problems and alcohol intake regarding all-cause and CVD mortality

To assess the joint association of mental health problems and alcohol intake with all-cause (Table 2) and CVD (Table 3) mortality, we used the participants with a low mental health index score (1.00–1.50 mean score) and low alcohol intake (<2 grams/day) as a common reference category. The observed HRs (95% CIs) for all-cause mortality in categories combining a low score on the mental health index (1.00–1.50) with light, moderate, and high alcohol intake were 0.93 (0.89, 0.97; p = 0.001), 1.00 (0.92, 1.09; p = 0.926), and 1.14 (0.96, 1.35; p = 0.119), respectively. We then multiplied each of the abovementioned HRs by the HR for the category combining a high score on the mental health index (2.01–4.00) with a low alcohol intake, which was 1.22 (95% CI 1.14, 1.31; p < 0.001). This provides the expected joint HRs (1.13, 1.22, and 1.39, respectively) for the categories combining a high score on the mental health index with light, moderate, and high alcohol intake, assuming no interaction on the multiplicative scale. The observed joint HRs for these categories, however, were 1.24 (95% CI 1.15, 1.33; p < 0.001), 1.43 (95% CI 1.23, 1.66; p < 0.001), and 2.29 (95% CI 1.87, 2.80; p < 0.001), respectively, which were 1.09 (95% CI 1.03, 1.15; p = 0.002), 1.17 (95% CI 1.06, 1.27; p = 0.001), and 1.64 (95% CI 1.53, 1.74; p < 0.001) higher than the expected joint HRs, suggesting interaction. In addition, for the combined category of high alcohol intake and a medium score on the mental health index (1.51–2.00), the observed joint HR for all-cause mortality was 1.33 (95% CI 1.11, 1.60; p = 0.003), which was 1.13 (95% CI 1.00, 1.36; p = 0.019) higher than the expected HR of 1.17 (derived from 1.14 × 1.03). The observed joint HR for CVD mortality was also higher than expected for a high alcohol intake combined with a high mean score on the mental health index, but not for other combinations. Observed and expected joint HRs were 1.78 (95% CI 1.14, 2.78; p = 0.011) and 1.05 (derived from 0.95 × 1.11), respectively, while the HR for interaction was 1.69 (95% CI 1.42, 1.97; p < 0.001).

Table 2

All-cause mortality according to mental health problems and alcohol intake using a joint reference category.

Measure	Mental health index (range 1–4)	Current abstainers	Average alcohol intake (grams/day)
			Low(<2 grams/day)	Light(2–11.99 grams/day)	Moderate(12–23.99 grams/day)	High(≥24 grams/day)
Event/no event (n)	1.00–1.50	2,319/10,855	4,959/47,480	4,223/68,092	634/8,519	142/1,205
	1.51–2.00	1,298/5,157	2,513/22,443	1,954/32,214	360/4,678	117/812
	2.01–4.00	695/2,172	1,050/7,516	835/8,852	180/1,573	97/428
Unadjusted
HR (95% CI)	1.00–1.50	1.92 (1.83, 2.02), p < 0.001	Referent	0.62 (0.59, 0.64), p < 0.001	0.76 (0.70, 0.82), p < 0.001	1.20 (1.02, 1.42), p = 0.030
	1.51–2.00	2.24 (2.11, 2.38), p < 0.001	1.08 (1.03, 1.13), p = 0.001	0.61 (0.58, 0.64), p < 0.001	0.79 (0.71, 0.88), p < 0.001	1.47 (1.22, 1.76), p < 0.001
	2.01–4.00	2.83 (2.61, 3.06), p < 0.001	1.35 (1.26, 1.44), p < 0.001	0.95 (0.88, 1.02), p = 0.138	1.17 (1.01, 1.35), p = 0.042	2.24 (1.83, 2.73), p < 0.001
HR for interaction (95% CI)	1.00–1.50	—	Referent	—	—	—
	1.51–2.00	1.08 (1.01, 1.14), p = 0.013	—	0.91 (0.85, 0.98), p = 0.009	0.96 (0.84, 1.09), p = 0.550	1.13 (0.94, 1.32), p = 0.159
	2.01–4.00	1.09 (1.04, 1.15), p = 0.001	—	1.14 (1.09, 1.19), p < 0.001	1.14 (1.06, 1.23), p = 0.001	1.38 (1.27, 1.48), p < 0.001
Adjusted for age and sex
HR (95% CIs)	1.00–1.50	1.13 (1.07, 1.18), p < 0.001	Referent	0.90 (0.86, 0.93), p < 0.001	0.99 (0.91, 1.07), p = 0.740	1.20 (1.02, 1.42), p = 0.029
	1.51–2.00	1.29 (1.22, 1.38), p < 0.001	1.10 (1.04, 1.15), p < 0.001	0.94 (0.89, 0.99), p = 0.013	1.14 (1.02, 1.27), p = 0.020	1.56 (1.30, 1.88), p < 0.001
	2.01–4.00	1.70 (1.56, 1.84), p < 0.001	1.42 (1.33, 1.52), p < 0.001	1.43 (1.33, 1.54), p < 0.001	1.80 (1.55, 2.09), p < 0.001	3.68 (3.01, 4.51), p < 0.001
HR for interaction (95% CI)	1.00–1.50	—	Referent	—	—	—
	1.51–2.00	1.04 (0.99, 1.12), p = 0.215	—	0.95 (0.89, 1.02), p = 0.141	1.05 (0.94, 1.16), p = 0.369	1.18 (1.00, 1.36), p = 0.035
	2.01–4.00	1.06 (1.01, 1.11), p = 0.015	—	1.11 (1.08, 1.17), p < 0.001	1.28 (1.22, 1.35), p < 0.001	2.16 (2.09, 2.21), p < 0.001
Multivariable adjusted
HR (95% CI)	1.00–1.50	1.19 (1.13, 1.25), p < 0.001	Referent	0.93 (0.89, 0.97), p = 0.001	1.00 (0.92, 1.09), p = 0.926	1.14 (0.96, 1.35), p = 0.119
	1.51–2.00	1.27 (1.19, 1.35), p < 0.001	1.03 (0.98, 1.08), p = 0.200	0.93 (0.88, 0.98), p = 0.005	1.04 (0.94, 1.16), p = 0.440	1.33 (1.11, 1.60), p = 0.003
	2.01–4.00	1.39 (1.28, 1.51), p < 0.001	1.22 (1.14, 1.31), p < 0.001	1.24 (1.15, 1.33), p < 0.001	1.43 (1.23, 1.66), p < 0.001	2.29 (1.87, 2.80), p < 0.001
HR for interaction (95% CI)	1.00–1.50	—	Referent	—	—	—
	1.51–2.00	1.03 (0.99, 1.12), p = 0.353	—	0.97 (0.89, 1.01), p = 0.351	1.01 (0.94, 1.16), p = 0.863	1.13 (1.00, 1.36), p = 0.119
	2.01–4.00	0.95 (0.88, 1.03), p = 0.203	—	1.09 (1.03, 1.15), p = 0.002	1.17 (1.06, 1.27), p = 0.001	1.64 (1.53, 1.74), p < 0.001

HRs, 95% CIs, and p-values derived from Cox models. The multivariable model was adjusted for age, sex, education, marital status, smoking, physical activity, body mass index, resting heart rate, total cholesterol concentration, triglyceride concentration, diabetes, family history of coronary heart disease, and history of CVD. The HR for interaction assesses whether the observed joint HR differed from the expected joint HR derived using a multiplicative interaction structure, calculated by dividing the observed joint HR for a given combination (e.g., moderate index score + moderate alcohol intake) by the expected joint HR (e.g., the product of the HRs from moderate index score + low alcohol intake and low index score + moderate alcohol intake). Standard errors and 95% CIs were obtained using the Delta method.

CI, confidence interval; HR, hazard ratio.

Table 3

CVD mortality according to mental health problems and alcohol intake using a joint reference category.

Measure	Mental health index (range 1–4)	Current abstainers	Average alcohol intake (grams/day)
			Low(<2 grams/day)	Light(2–11.99 grams/day)	Moderate(12–23.99 grams/day)	High(≥24 grams/day)
Event/no event (n)	1.00–1.50	898/12,276	1,606/50,833	1,148/71,167	153/9,000	34/1,313
	1.51–2.00	499/5,956	822/24,134	506/33,662	96/4,942	25/904
	2.01–4.00	256/2,611	308/8,258	184/9,503	32/1,721	20/505
Unadjusted
HR (95% CI)	1.00–1.50	2.30 (2.12, 2.49), p < 0.001	Referent	0.52 (0.48, 0.56), p < 0.001	0.56 (0.48, 0.66), p < 0.001	0.88 (0.63, 1.24), p = 0.465
	1.51–2.00	2.66 (2.40, 2.94), p < 0.001	1.09 (1.00, 1.19), p = 0.043	0.49 (0.44, 0.54), p < 0.001	0.65 (0.53, 0.79), p < 0.001	0.96 (0.65, 1.42), p = 0.830
	2.01–4.00	3.20 (2.80, 3.65), p < 0.001	1.22 (1.08, 1.38), p = 0.002	0.64 (0.55, 0.75), p < 0.001	0.63 (0.45, 0.90), p = 0.011	1.40 (0.90, 2.18), p = 0.131
HR for interaction (95% CI)	1.00–1.50	—	Referent	—	—	—
	1.51–2.00	1.06 (0.95, 1.17), p = 0.276	—	0.86 (0.73, 0.99), p = 0.052	1.06 (0.84, 1.27), p = 0.593	1.00 (0.56, 1.44), p = 1.000
	2.01–4.00	1.14 (1.04, 1.25), p = 0.005	—	1.01 (0.89, 1.15), p = 0.888	0.92 (0.64, 1.22), p = 0.625	1.30 (1.02, 1.60), p = 0.022
Adjusted for age and sex
HR (95% CIs)	1.00–1.50	1.25 (1.15, 1.36), p < 0.001	Referent	0.84 (0.78, 0.91), p < 0.001	0.79 (0.67, 0.94), p = 0.006	0.89 (0.63, 1.25), p = 0.516
	1.51–2.00	1.43 (1.29, 1.58), p < 0.001	1.11 (1.02, 1.21), p = 0.013	0.85 (0.77, 0.94), p = 0.002	1.03 (0.84, 1.27), p = 0.742	1.04 (0.70, 1.54), p = 0.875
	2.01–4.00	1.79 (1.57, 2.04), p < 0.001	1.31 (1.16, 1.48), p < 0.001	1.10 (0.95, 1.29), p = 0.210	1.16 (0.81, 1.64), p = 0.418	2.75 (1.77, 4.28), p < 0.001
HR for interaction (95% CI)	1.00–1.50	—	Referent	—	—	—
	1.51–2.00	1.03 (0.92, 1.14), p = 0.601	—	0.91 (0.79, 1.03), p = 0.164	1.17 (0.99, 1.36), p = 0.052	1.05 (0.63, 1.45), p = 0.830
	2.01–4.00	1.09 (0.99, 1.19), p = 0.066	—	1.09 (0.89, 1.12), p = 0.142	1.12 (0.91, 1.33), p = 0.244	2.36 (2.21, 2.49), p < 0.001
Multivariable adjusted
HR (95% CI)	1.00–1.50	1.25 (1.15, 1.36), p < 0.001	Referent	0.93 (0.86, 1.00), p = 0.058	0.90 (0.76, 1.07), p = 0.225	0.95 (0.67, 1.33), p = 0.760
	1.51–2.00	1.32 (1.19, 1.46), p < 0.001	1.04 (0.96, 1.13), p = 0.340	0.89 (0.80, 0.98), p = 0.019	1.02 (0.83, 1.26), p = 0.814	0.95 (0.64, 1.42), p = 0.765
	2.01–4.00	1.36 (1.19, 1.56), p < 0.001	1.11 (0.98, 1.25), p = 0.102	0.97 (0.83, 1.13), p = 0.689	1.01 (0.71, 1.44), p = 0.956	1.78 (1.14, 2.78), p = 0.011
HR for interaction (95% CI)	1.00–1.50	—	Referent	—	—	—
	1.51–2.00	1.02 (0.89, 1.14), p = 0.767	—	0.92 (0.78, 1.05), p = 0.275	1.09 (0.87, 1.32), p = 0.426	0.96 (0.45, 1.46), p = 0.900
	2.01–4.00	0.98 (0.83, 1.14), p = 0.815	—	0.94 (0.77, 1.12), p = 0.528	1.01 (0.69, 1.33), p = 0.957	1.69 (1.42, 1.97), p < 0.001

HRs, 95% CIs, and p-values derived from Cox models. The multivariable model was adjusted for age, sex, education, marital status, smoking, physical activity, body mass index, resting heart rate, total cholesterol concentration, triglyceride concentration, diabetes, family history of coronary heart disease, and history of CVD. The HR for interaction assesses whether the observed joint HR differed from the expected joint HR derived using a multiplicative interaction structure, calculated by dividing the observed joint HR for a given combination (e.g., moderate index score + moderate alcohol intake) by the expected joint HR (e.g., the product of the HRs from moderate index score + low alcohol intake and low index score + moderate alcohol intake). Standard errors and 95% CIs were obtained using the Delta method.

CI, confidence interval; HR, hazard ratio.

In stratified analyses adjusted for age and sex, a 1-unit increase in mean score per question on the mental health index was consistently associated with a higher HR for both mortality outcomes at all alcohol intake levels, but only for all-cause mortality in multivariable adjusted analyses (S4 Table). The point estimates and test for slope difference indicated a more pronounced change in HRs for all-cause mortality among people reporting moderate and high alcohol intake versus low intake. Multivariable adjusted HRs for all-cause mortality per unit change in the mental health index in the low, moderate, and high alcohol intake strata were 1.15 (95% CI 1.10, 1.21; p < 0.001), 1.32 (95% CI 1.17, 1.48; p < 0.001), and 1.32 (95% CI 1.17, 1.48; p < 0.001), respectively. HRs for the tests for slope differences were 1.22 (95% CI 1.08, 1.38; p = 0.002) for moderate versus low intake and 1.38 (95% CI 1.16, 1.63; p < 0.001) for high versus low intake. In stratified analysis of alcohol intake, HRs for both mortality outcomes were consistently higher among current abstainers in comparison with current drinkers with a low intake. In analysis of current drinkers only, the visualisation of the associations of average alcohol intake with all-cause mortality and CVD mortality (Fig 2) indicated a more adverse association among people with more mental health problems at higher alcohol intake levels, albeit with wide CIs. HRs per unit increase in average alcohol intake were 1.06 (95% CI 1.04, 1.08; p < 0.001) for all-cause mortality and 1.07 (95% CI 1.02, 1.11; p = 0.003) for CVD mortality among people with a high mental health index score, but not different from 1 among people with a low or medium score (S5 Table). HRs derived from the tests for slope difference were 1.07 (95% CI 1.04, 1.10; p < 0.001) for all-cause and 1.10 (95% CI 1.04, 1.16; p = 0.001) for CVD mortality, indicating a more pronounced change in HR per unit change in alcohol intake among people with a high versus low score on the mental health index.

Fig 2

Visualisation of the associations of alcohol intake (grams per day) with all-cause mortality and cardiovascular disease mortality among current drinkers (n = 220,876) in strata of the mental health index.

(A) All-cause mortality; (B) cardiovascular disease mortality. Average alcohol consumption was fitted as a continuous variable using penalised smoothed splines in a Cox model adjusted for age and sex. The vertical axis shows the log hazard ratio (the exponential value is equivalent to the hazard ratio). The solid line depicts the spline and the dashed curves depict twice the standard error (as plotted by the termplot function in R statistical software, which was used for visualisation). Twice the standard error is a close approximation of a 95% confidence interval, as 95% of the values fall within 1.96 × standard error of the mean if the values are normally distributed. The curve was centred (log hazard ratio = 0) at the mean value of alcohol intake in each mental health index stratum (1.00–1.50, 4.48 grams/day; 1.51–2.00, 4.79 grams/day; 2.01–4.00, 5.20 grams/day). The curves were plotted individually using a fixed y-axis between −0.5 and 3 and then superimposed.

Additional analyses

Crude distributions of HDL-C according to sex, alcohol intake, and the mental health index are presented in S3 Table. In analyses adjusted for age, the regression coefficient (95% CI) per unit increase in alcohol (1 gram/day) was 0.013 (0.013, 0.014) and 0.007 (0.006, 0.007) mmol/l among women and men, respectively. Regression coefficient (95% CI) values for low, medium, and high mental health index scores respectively were 0.014 (0.013, 0.015), 0.013 (0.012, 0.014), and 0.012 (0.010, 0.013) for women (p for difference in slope with low score as reference: 0.051 and 0.001), and 0.007 (0.007, 0.007), 0.006 (0.006, 0.007), and 0.006 (0.005, 0.007) for men (p for difference: 0.017 and 0.046).

Discussion

Brief summary

In this study of adults from the general Norwegian population, we observe that those who report more mental health problems, as judged by a high score on a mental health index, had a 26% and 10% higher risk of all-cause and CVD mortality, respectively, in comparison with people who report fewer problems. Furthermore, we find non-linear associations involving alcohol intake, with a 7% and 10% lower risk of all-cause and CVD mortality, respectively, with light intake (2–11.99 grams/day), and a 33% higher risk of all-cause mortality with high intake (≥24 grams/day), in comparison with low intake (<2 grams/day). In joint analyses, we observed a 129% and 78% higher risk of all-cause and CVD mortality, respectively, for the combination of high alcohol intake and high mean score on the mental health index (compared with low alcohol intake and a low index score). These estimates were 64%–69% higher than expected under the assumption of a multiplicative interaction structure.

Mental health and mortality

A higher score on the mental health index was associated with higher all-cause and CVD mortality. This is in agreement with existing research on the health consequences of mental health problems [10-14]. A considerable part of the age- and sex-adjusted association was accounted for by multivariable adjustment, which is in line with the interpretation that mental health may impact mortality via changes in health behaviour. An alternative and more conservative interpretation is that the association was confounded by the risk factors in the multivariable model. Support for either interpretation would require a temporal sequence, but as mental health and other risk factors were measured at the same time, the study was limited in this regard.

Alcohol intake and mortality

Previous studies have reported a J- or U-shaped risk pattern between alcohol intake and all-cause mortality or CVD [29,30]. A recent consortium-based individual-level analysis of current drinkers found that an intake of 14 grams/day was associated with the lowest risk of both outcomes [31]. Our data are in support of lower CVD and all-cause mortality at light alcohol intake (2–11.99 grams/day), and also numerically lower CVD mortality at moderate intake (12–23.99 grams/day), in comparison with a low intake (<2 grams/day). The data also support higher all-cause mortality for high intake (≥24 grams/day). The difference in HR between current abstainers and current drinkers with a low intake of alcohol is less likely to be the result of a difference in the reported alcohol intake, and more likely to reflect unmeasured confounding or reverse causation as suggested by genetically informed studies [32].

Joint analysis of mental health and alcohol intake and mortality

HRs for all-cause mortality for the joint association of mental health problems and alcohol intake were 9%–64% higher than expected under an assumption of a multiplicative interaction structure. For CVD mortality, the associations were in line with a potential interaction among participants reporting the highest alcohol intake level and the most mental health problems, but this interaction did not manifest as a gradient starting at lower intake or index levels. Data in support of an interaction involving alcohol intake and mental health problems with all-cause mortality were observed in a previous study by Greenfield et al., in which 18% of the participants were defined with high levels of depression using a 20-item Centre for Epidemiological Studies Depression Scale [20]. We performed our study in a larger sample, allowing us to categorise people with mental health problems into more finely graded groups. A medium score on the mental health index (1.51–2.00) can be interpreted as subclinical or subthreshold levels of depression or anxiety disorders, and a high score (2.01–4.00) as a value that may approximate clinical levels. We make this argument because approximately 7% of the participants would be defined as having mental distress if we applied a previously suggested cutoff value (≥2.15) [24], which converges with Norwegian health registry (6.9%) and clinical interview (8.1%) data for depression diagnosis in the general population [33].

Methodological considerations

A major limitation was the use of a single measurement to assess alcohol intake and mental health problems. Most participants attended the baseline survey in midlife (mean age: 44 years) and a long follow-up period was needed to power the analyses. Changes in alcohol intake or mental health during the follow-up period might have diluted the observed associations. Changes in alcohol intake before a survey, especially ‘sick quitters’, can give rise to reverse causation through an inflated risk if abstainers are used as the reference category [32]. A predominantly midlife sample, however, might be preferable to an older sample in this regard [34]. We also used low-level drinking as the referent category, and not current abstainers, in order to reduce bias from residual confounding or reverse causation [35]. Previous studies showed more mental distress among abstainers [36], and in a subset we found a higher use of antidepressants and tranquillizers among current abstainers, as well as among people reporting high intake of alcohol and people with higher scores on the mental health index. Systematic underreporting of alcohol intake was indicated by the higher increase in HDL-C per unit (1 gram/day) increase in self-reported alcohol intake among women (0.013 mmol/l) and men (0.007 mmol/l) in comparison with short-term experimental studies (1 gram/day, approximately 0.0035 mmol/l) [28]. A small difference in slope according to mental health was observed, which seems too small to cause differential bias.

Norway is a country with rather low per capita alcohol consumption [37], a free healthcare system, and a high life expectancy. We argue that the findings in this study can be generalised to a large segment of the general Norwegian population, but there are important limitations. Because of the sampling profile of the health surveys, and the Age 40 Program in particular, the vast majority of the participants in the study population attended a health survey in midlife (73% were between 35 and 50 years of age). A study performed exclusively in younger or older populations, where the nature of non-CVD deaths could differ, may return somewhat different results. A related issue is the possibility that individuals who were the most vulnerable or susceptible to the negative effects of alcohol or mental health problems could have been more likely to have died prior to the health surveys, which could result in underestimation of the risk associated with alcohol intake and mental health problems [38]. The study population also deviated from the general population for 2 reasons. First, the response rate in the health surveys that constituted the source population ranged from 37.5% to 78%. Self-selection into survey attendance likely resulted in a slightly healthier source population than the general population. People with more severe types of mental health problems or more extreme alcohol intake could be underrepresented. Second, the participants excluded for missing values (mostly data on mental health and alcohol intake) were older and more likely to have died during follow-up than the average participant, suggesting that they might have been more frail. The associations could be different, and possibly more pronounced, in more frail or extreme subpopulations, or in countries where average alcohol intake is higher, the drinking pattern different, or mental healthcare less available.

Implications and future research

This study was performed in a large sample of the general population. The findings suggest that mortality risk is increased in people who report both more mental health problems and a higher alcohol intake, raising the possibility of interaction between risks associated with mental health problems and higher alcohol intake. An implication of this finding might be that the disease burden attributable to mental health problems could be higher in subpopulations that drink more alcohol, and vice versa. Co-addressing mental health and alcohol intake in primary healthcare, perhaps even before problems reach clinical level, may help reduce disease burden attributable to both risk factors by improving quality of life and reducing mortality. The study also provides additional observational data that are in line with the current low-risk drinking guidelines, in which people with mental health problems are advised to consider avoiding or limiting their intake of alcohol. Unfortunately, the study design does not enable us to indicate mechanisms that could be underlying the suggested interaction. A longitudinal study design could provide more answers, especially if it includes repeated measurements over the life course for mental health problems, average alcohol intake (preferably also drinking patterns), and health data related to risk factors, health behaviour, dietary factors, and the use of psychotropic drugs. Such a study could follow the consequences associated with different sequences of events (a high alcohol intake preceding mental health problems or vice versa), both in terms of the risk factors and the mortality risk. Genotyping of large cohorts harbouring relevant information could reveal the role of genetic variants predisposing individuals to both alcohol use and mental health problems over time.

Conclusions

Our study found that the mortality rates associated with more mental health problems and a high alcohol intake were increased when these risk factors occurred together among people in the general population. Current low-risk drinking guidelines targeted at the general population state that mental health problems are a reason to consider avoiding or limiting alcohol. The study findings are in line with this advice. Clinicians may consider advising patients about the additional harm implicated by this combination even if alcohol intake and mental health problems jointly or alone do not reach clinical levels of severity.

The Reporting of studies conducted using observational routinely-collected health data (RECORD) guideline, which is an extension of the strengthening the reporting of observational studies in epidemiology (STROBE) guideline.

(DOCX)

Click here for additional data file.

Flowchart showing the selection of study participants from the source health surveys and into the study sample.

(TIF)

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Crude relationship between alcohol intake and mental health problems as measured by the mean score per question on the mental health index.

The boxplot depicts the mean value of the mental health index with 95% confidence intervals among current abstainers. The curve depicts the smoothed mean of the mental health index according to the average alcohol intake (grams/day) among current drinkers. The grey shading depicts the 95% confidence intervals. The vertical axis has been truncated.

(TIF)

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This study is part of a larger research project with a protocol containing information about the planned project, including background, research questions, most of the data sources, main variables, and pre-planned data analysis and study samples.

(PDF)

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The cardiovascular health surveys constituting the source population (n = 307,541 visits).

(DOCX)

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Descriptive statistics of individuals excluded because of missing values.

(DOCX)

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Descriptive statistics according to mental health problems and alcohol intake in the study population (Table 1 continued).

(DOCX)

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All-cause and CVD mortality according to mental health index in the study population overall and stratified by alcohol intake.

(DOCX)

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All-cause and CVD mortality according to alcohol intake in the study population overall and stratified by mental health index.

(DOCX)

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Overview of the differences between the study planned per protocol and the study performed.

(DOCX)

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Programming code for R statistical software: Data cleaning, harmonisation of survey data, and selection of study population.

(TXT)

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The mental health index.

(DOCX)

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29 Aug 2019

Dear Dr. Degerud,

Thank you very much for submitting your manuscript "Combination of self-reported mental health problems and alcohol intake and the risk of all-cause and cardiovascular disease mortality - A pooled analysis of Norwegian cardiovascular health surveys." (PMEDICINE-D-19-02500) for consideration at PLOS Medicine.

Your paper was evaluated by a senior editor and discussed among all the editors here. It was also discussed with an academic editor with relevant expertise, and sent to three independent reviewers, including a statistical reviewer. The reviews are appended at the bottom of this email and any accompanying reviewer attachments can be seen via the link below:

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In light of these reviews, I am afraid that we will not be able to accept the manuscript for publication in the journal in its current form, but we would like to consider a revised version that addresses the reviewers' and editors' comments. Obviously we cannot make any decision about publication until we have seen the revised manuscript and your response, and we plan to seek re-review by one or more of the reviewers.

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In addition, please note that an author cannot serve as primary contact for obtaining the data.

3. Abstract: Please include number of participants included in the study.

4. Abstract and throughout: Please include p-values along with 95% CIs.

5. Abstract: At Line 51 There is a grammatical issue: “less” should be “fewer”.

6. Abstract: Please move the limitation sentence (last sentence of abstract’s Conclusion section) to be the last sentence of the abstract’s Methods and Findings section.

7. Author Summary: At this stage, we ask that you include a short, non-technical Author Summary of your research to make findings accessible to a wide audience that includes both scientists and non-scientists. The Author Summary should immediately follow the Abstract in your revised manuscript. This text is subject to editorial change and should be distinct from the scientific abstract. Please see our author guidelines for more information: https://journals.plos.org/plosmedicine/s/revising-your-manuscript#loc-author-summary

8. Methods and Results: A table describing cohort demographics (such as table S1) should be found in the main text.

9. Methods and Results: Please add the following statement, or similar, to the Methods: "This study is reported as per the Strengthening the Reporting of Observational Studies in Epidemiology (STROBE) guideline (S1 Checklist)."

10. Methods and Results: Survey response rates were not included. Please include survey response rates.

11. Methods and Results: Line 96-98: There appears to be a typo “The Regional Ethics Committee South-East (11/1676) approved the study and gave exemption regarding consent in surveys were this was not obtained.” (were should be where)

12. Methods and Results: Please provide p-values for HRs and CIs reported in Table 1 and Table 2.

13. Methods and Results: Results from models adjusted for age and sex are presented, as well as multivariable models. Please also present results from unadjusted models.

14. Methods and Results (and supplemental data): Line 332: “Gender” is used, while “sex” is used elsewhere. Both terms are used in the supplemental information. The terms gender and sex are not interchangeable (as discussed in http://www.who.int/gender/whatisgender/en/ ); please use the appropriate term.

15. Discussion: Between the limitations section and conclusions section, please add a brief discussion of implications and next steps for research, clinical practice, and/or public policy.

16. Figures 1, 2, and 3: It is difficult to see the difference between the blue and black dashed lines. Please make this difference more clear (e.g. change the colors, line weights, etc.).

17. Figure S3: For the Kaplan-Meier curve, please provide the number at risk for each time interval.

18. Figure S2, and S3: Please show the axis beginning at zero. If this is not possible, please show a break in the axis.

19. For Figure S3: Please indicate in the figure caption the meaning of the dotted lines vs. solid lines. In the legend of figure S3, p-value = 0 should be p-value < 0.001.

20. For Figure S3: Panel B legend has “Alcohol intake” at the top- remove for consistency, or add a description of different plotted series to graphs in panels A, C, and D.

21. Table S4: The legend has a typo- a period is missing at the end of “HR and 95% CI and p-value derived from Cox models”.

22. References: Please use the "Vancouver" style for reference formatting, and see our website for other reference guidelines: https://journals.plos.org/plosmedicine/s/submission-guidelines#loc-references

23. Thank you for submitting the STROBE checklist. Please confirm that STROBE is the most appropriate reporting guideline, rather than RECORD. Please report your study according to the relevant guideline, which can be found here: http://www.equator-network.org/

Comments from the reviewers:

Reviewer #1: This paper reports findings from an analysis of combined national survey data linked to mortality in which the authors investigated the association between self-reported level of alcohol intake and mortality and the extent to which this varied according to concurrent reported mental health status. The methodological approach is robust, in my opinion, the paper is well-written, and the authors draw appropriate conclusions. My comments are as follows:

1. Although unlikely in an unselected community sample, I suppose it is possible that the modifying effect is of psychotropic medication rather than mental health status. It would have been helpful to have had some indication of the level of psychotropic medication use in people within the different mental health status groups, even if this couldn't be considered as a covariate. If this is not possible then I feel it needs to be highlighted as a potential limitation.

2. I found the text a little confusing on what was done about people who had participated in more than one survey. On p10 it is implied that they were included, but it is not clear (beyond data availability) how one survey point was chosen over another. And then on p15 it is implied that participants in multiple surveys were excluded, which seems to contradict the earlier statement. Some clarification of text is needed.

3. On P16, lines 231-234, it would be helpful if the authors coud clarify for readers what's meant by 'index score' (I assume it is the mental health measure - if so, could it be referred to as this?).

4. The labelling of different models for rows in Table 1 (p23, lines 315-316) seems to be missing. The same issue applies to Table 2.

Reviewer #2: This manuscript describes associations of measures of mental health and alcohol consumption with both all-cause mortality and CVD mortality using pooled data from Norwegian health surveys conducted between 1994 and 2002. Linkage to death registration covered mortality up to the end of 2014. The total source population for the study was over 300,000 individuals and over 21,000 had died by 2014 (6,587 from CVD). Cox Proportional Hazards Models were used for the main analyses to describe the independent associations of mental health and alcohol consumption with mortality, and the interaction terms between mental health and alcohol consumption, adjusted first for age and sex only, and then for age, sex, education, marital status, smoking, physical activity, body mass index, resting heart rate, and total cholesterol. The pattern of findings indicated higher mortality at higher bands of mental health index score (all-cause and CVD but less so for the latter); higher mortality for other groups than for the low average alcohol daily intake group (<2 g/day) with increasing mortality at higher levels of current drinking; and an interaction whereby increasing alcohol intake was more strongly associated with increased mortality in groups scoring more highly on the mental health index. This was most evident for the subgroup with high mental health score and high alcohol intake (>=24 g/day) that had very high mortality rates. The patterns were similar when additional covariates were included in the models but the magnitude of differences was attenuated. The pattern of interaction was also shown by expressing the HR per 5g/day increase in consumption within strata of mental health index score, where the HR for the highest stratum was greater than for the two lower mental health strata.

The paper has strengths, especially in terms of the available data and size of population. This facilitates the quantification of the identified interaction. The manuscript also acknowledges limitations, especially the cross-sectional nature of the risk factor data. However, it also presents and discusses the findings in terms of a model of "susceptibility" to the health risks of drinking, where those with more mental health problems have increased susceptibility. This interpretation is the greatest weakness of the manuscript and it evolves from a narrative that is very sparse in terms of providing an account of what mechanisms might underlie the key observations. There are glimpses of what the authors might be thinking, such as the mention in the abstract that mental health problems "might become worse from drinking" but this does not constitute a coherent explanation or hypothesis for future investigation. There is also a statement at lines 172-173 that HDL-C and systolic blood pressure "are likely to play a mediating rather than a confounding role" but it isn't explicit what association/pattern they are mediating. Further, there is a mention of "genetic risk for alcohol addiction" (line 395) in the Discussion. There could well be other plausible accounts of the reported interactions and one possible explanation is that groups with high mental health scores and high current drinking have a longer history of heavy use. Overall, the paper presents an intriguing and potentially useful empirical finding but sheds too little light on what might be going on to bring it about.

In addition to this main point there a number of more specific points for the authors to consider.

1) The mention in the introduction (lines 63-64) of a positive association between alcohol intake and mental health gets into an unnecessary debate. There are a number of studies (not cited) that find poorer mental health in abstainers compared with light drinkers. However, this has very little to do with the ingestion of ethanol* and such J or U shapes (including this study's findings in Table S2) are not a threat to the core analyses of the present research. I note, too, that reference 7 appears to be cited to support both sides of the above debate. (I haven't checked to see whether it does have ambiguous results.)

2) I think more information is needed in the Methods (lines 87-88) about the surveys other than the Age 40 Program rather than readers having to look elsewhere (ref. 16). What age ranges are included? I would be uncomfortable if these other data sets included younger adults where the nature of non-CVD deaths could be very different from those found at older ages. I'm looking for some reassurance here.

3) There were times in the descriptions of the analyses where a particular analysis appeared to be limited to current drinkers but I couldn't always follow why this was so and under what circumstances it was necessary. Current abstainers are included in the tables, and the figures showing the Kaplan-Meier risk curves (Figs. 2 and 3) have lines starting at 0g/day. Can it be made clearer which analyses excluded current abstainers and why?

4) The early parts of the Discussion are quite vague in expressing the quantification of effects. "Increased risk", "more susceptible", "higher" and "considerable" are descriptions which give little idea of whether the differences found are large or small. The Discussion also suffers particularly from the main weakness of the paper as outlined above.

5) The number of participants for the HUBRO Cohort is reported incorrectly in Table S1.

* Lucas, N., Windsor, T. D., Caldwell, T. M. & Rodgers, B. (2010). Psychological distress in non-drinkers: Associations with previous heavy drinking and current social relationships. Alcohol and Alcoholism 45 (1), 95-102.

Bryan Rodgers

Reviewer #3: This paper addresses the important topic of interaction between alcohol use and mental health status on all-cause and CVD-related mortality. However, the paper has several issues that limit the interpretability of the findings:

1. Presentation of methods and results: The statistical methods and results sections were poorly organized and difficult to follow. The authors present stratified smoothed hazard functions (in the figures), hazard ratios for the joint effects of alcohol use and mental health status, Kaplan Meier plots, and log rank tests. It is unclear in the methods and results sections why all of these different types of results are presented (e.g., which hypothesis is addressed by each set of results).

2. Interaction vs effect modification: In the main text, the paper presents joint hazard ratios, which indicate that the authors are interested in interaction between alcohol use and mental health. However, the primary conclusion seems to be that alcohol is worse for people with worse mental health, which seems to indicate that they are interested in describing the different effects of alcohol within strata of mental health status. (in the former case, joint hazard ratios (with a common referent group, are logical to estimate joint effects; in the latter case, one would present hazard ratios for alcohol use within strata of mental health status). The wording of the conclusion should be consistent with the methods and results.

3. Use of nonstandard language: throughout, the papers uses somewhat nonstandard language (e.g., referring to "risks" and "risk differences" to discuss smoothed hazard plots). I recommend staying away from these terms in this context.

Minor comments:

1. Abstract: were expected HRs under interaction based on an assumption of multiplicative or additive interaction

2. Line 82: a figure would be helpful to understand this complex design. As written, it is a bit unclear who the target population is and who the study generalizes to. Are any important groups excluded or overrepresented?

3. Line 113: was the categorization of the index based on the mean score per question?

4. Line 168: Here, or early in the statistical analysis section, I recommend stating clearly which hazard ratios were estimated and why.

5. Line 168: What was the timescale for the hazard ratios?

6. Line 170: Is there a conceptual model or causal diagram that informs which variables are considered mediators vs confounders? I would have expected biomarkers and current health indicators (heart rate, diabetes, serum cholesterol and serum triglycerides) to be on the causal path (ie play a mediating role) as well.

7. Line 175: The paragraph that starts at this line should clearly state which hazard ratios were estimated to address which scientific hypotheses. As written, it is unclear to me why so many different types of results were presented. For example, why present both the interaction terms with the continuous variables and the joint reference category HRs?

8. Line 181: Please define a, b, and c in this equation.

9. Line 181: it appears that the authors are evaluating whether the joint HR differs from the expected joint HR under a multiplicative interaction structure. Why was this structure chosen rather than an additive interaction structure? (The authors could have evaluated a departure from additivity using the RERI (see Li R, Chambless L. Test for additive interaction in proportional hazards models. Annals of epidemiology. 2007 Mar 1;17(3):227-36 for details)

10. Line 194: Was any of the missing data described in this paragraph likely to be informative? Seems like those missing alcohol data may have been systematically different from those with alcohol data.

11. Line 199: what proportion of participants were excluded due to missing data?

12. Line 203: Including a traditional "table 1" with participant characteristics would help readers follow the paper.

13. Line 225: In this section, I recommend interpreting the beta coefficients to guide the reader through the analysis.

14. Line 230: is the mean presented here the average time of follow-up among those who died or overall? This should be better labeled.

15. Line 234: How were expected numbers of deaths computed from Kaplan-Meier curves and log rank tests? This was not described in the methods section and is not a familiar approach.

16. Line 237: the number of CVD deaths was fewer than what? This sentence should be rephrased.

17. Line 241 and throughout: These figures present the smoothed hazard function, which is different from the "risk curve."

18. Figure 1: Methods for producing these figures should be included in the Methods section. In addition, the rationale for producing these figures is not obvious. What hypothesis is being addressed? What do these figures add?

19. Line 245 and throughout: This line and below lines refer to the "risk difference" but it is unclear where this is coming from. It appears authors are referring to the Figures, but these figures depict a hazard function. Terms like "risk" and "risk difference" have specific definitions in epidemiology and should be avoided in other contexts to avoid confusion.

20. Line 307: what is this measure of interaction and how is it defined? Is this the departure from the expected HR under perfect multiplicativity?

21. Tables: Labels in the first column of tables are unclear

Any attachments provided with reviews can be seen via the following link:

[LINK]

16 Oct 2019

Submitted filename: Response to reviewers.docx

Click here for additional data file.

8 Nov 2019

Dear Dr. Degerud,

Thank you very much for submitting your revised manuscript "Combination of self-reported mental health problems and alcohol intake and the risk of all-cause and cardiovascular disease mortality - A pooled analysis of Norwegian cardiovascular health surveys." (PMEDICINE-D-19-02500R1) for consideration at PLOS Medicine.

Your revised paper was evaluated and discussed among all the editors here, and was sent for re-evaluation by two independent reviewers, including a statistical reviewer (Reviewers 2 and 3). Their reviews are appended at the bottom of this email, and the accompanying reviewer attachment from Reviewer 3 can be seen via the link below:

[LINK]

In light of the review of Reviewer 3, I am afraid that we will not be able to accept the manuscript for publication in the journal in its current form, but we would like to consider a further revised version that addresses the reviewers' and editors' comments. Obviously we cannot make any decision about publication until we have seen the revised manuscript and your response, and we plan to seek re-review by one or more of the reviewers.

In revising the manuscript for further consideration, your revisions should address the specific points made by each reviewer and the editors. Please also check the guidelines for revised papers at http://journals.plos.org/plosmedicine/s/revising-your-manuscript for any that apply to your paper. In your rebuttal letter you should indicate your response to the reviewers' and editors' comments, the changes you have made in the manuscript, and include either an excerpt of the revised text or the location (eg: page and line number) where each change can be found. Please submit a clean version of the paper as the main article file; a version with changes marked should be uploaded as a marked up manuscript.

In addition, we request that you upload any figures associated with your paper as individual TIF or EPS files with 300dpi resolution at resubmission; please read our figure guidelines for more information on our requirements: http://journals.plos.org/plosmedicine/s/figures. While revising your submission, please upload your figure files to the PACE digital diagnostic tool, https://pacev2.apexcovantage.com/. PACE helps ensure that figures meet PLOS requirements. To use PACE, you must first register as a user. Then, login and navigate to the UPLOAD tab, where you will find detailed instructions on how to use the tool. If you encounter any issues or have any questions when using PACE, please email us at PLOSMedicine@plos.org.

We expect to receive your revised manuscript by Nov 15 2019 11:59PM. Please email us (plosmedicine@plos.org) if you have any questions or concerns.

***Please note while forming your response, if your article is accepted, you may have the opportunity to make the peer review history publicly available. The record will include editor decision letters (with reviews) and your responses to reviewer comments. If eligible, we will contact you to opt in or out.***

We ask every co-author listed on the manuscript to fill in a contributing author statement, making sure to declare all competing interests. If any of the co-authors have not filled in the statement, we will remind them to do so when the paper is revised. If all statements are not completed in a timely fashion this could hold up the re-review process. If new competing interests are declared later in the revision process, this may also hold up the submission. Should there be a problem getting one of your co-authors to fill in a statement we will be in contact. YOU MUST NOT ADD OR REMOVE AUTHORS UNLESS YOU HAVE ALERTED THE EDITOR HANDLING THE MANUSCRIPT TO THE CHANGE AND THEY SPECIFICALLY HAVE AGREED TO IT. You can see our competing interests policy here: http://journals.plos.org/plosmedicine/s/competing-interests.

Please use the following link to submit the revised manuscript:

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Your article can be found in the "Submissions Needing Revision" folder.

To enhance the reproducibility of your results, we recommend that you deposit your laboratory protocols in protocols.io, where a protocol can be assigned its own identifier (DOI) such that it can be cited independently in the future. For instructions see http://journals.plos.org/plosmedicine/s/submission-guidelines#loc-methods.

Please ensure that the paper adheres to the PLOS Data Availability Policy (see http://journals.plos.org/plosmedicine/s/data-availability), which requires that all data underlying the study's findings be provided in a repository or as Supporting Information. For data residing with a third party, authors are required to provide instructions with contact information for obtaining the data. PLOS journals do not allow statements supported by "data not shown" or "unpublished results." For such statements, authors must provide supporting data or cite public sources that include it.

We look forward to receiving your revised manuscript.

Sincerely,

Caitlin Moyer, Ph.D.

Associate Editor

PLOS Medicine

plosmedicine.org

-----------------------------------------------------------

Requests from the editors:

Abstract: Methods and Findings: Lines 44-48: Please revise this sentence to: “For CVD mortality, HRs were 0.93 (0.86, 1.00, p = 0.058), 0.90 (0.76, 1.07, p = 0.225), and 0.95 (0.67, 1.33, p = 0.760) for a low index score combined with light, moderate, and high alcohol intakes, and 1.11 (0.98, 1.25, p = 0.102), 0.97 (0.83, 1.13, p = 0.689), 1.01 (0.71, 1.44, p = 0.956), and 1.78 (1.14, 2.78, p =0.011) for high index score combined with light, moderate, and high alcohol intakes, respectively.” to further clarify which analyses correspond to which values.

Abstract: Background: Lines 27-30: In the final sentence of this section, please add the term “self-reported” (so that it reads “...according to self-reported mental health problems and alcohol intake…”

Abstract: Methods and Findings: Lines 48-51: Please revise this sentence to: “HRs for the combination of a high index score and high intakes (HRs: 2.29 for all-cause and 1.78 for CVD) were 64% (95% CI: 53 – 74%) and 69% (42 – 97%) higher than expected for all-cause mortality and CVD mortality, respectively, under the assumption of a multiplicative interaction structure.” to clarify which analyses correspond to which data values.

Abstract: Methods and Findings: Lines 51-52: Please revise this sentence to: “A limitation of our study is that the findings were based on average reported intakes of alcohol without accounting for the drinking pattern.” or similar to clarify the main limitation of the study for the reader.

Results: Lines 326-328: Please specify which beta-coefficient values correspond to which analyses. Also, please provide a reference to the table where the data are presented showing the relationship between mean mental health index score and alcohol intakes (e.g. Table 1).

Results: Lines 355-357: Please specify which values correspond to which analyses for abstainers, and light, moderate and heavy drinkers.

Discussion: Conclusion: Please expand on your conclusion sentence. (For example, you could also speak to the result of your objective to look at the association between alcohol consumption and CVD/all cause mortality broken down by mental health index, and briefly touch on any important clinical implication.)

S2 Table: Please define the abbreviation “CVD” in the table footnote.

S3 Table: Please define the abbreviations “CVD” and “IHD” in the table footnote.

Figures 1 and 2: Please explain why twice the SD used rather than 95% CIs.

Supporting Information: S1 protocol: Please provide a descriptive title for this item.

Comments from the reviewers:

Reviewer #2: The authors have provided a detailed and clear account of the revisions made to this manuscript in their rebuttal. I have focussed on the general comments I made on the initial submission and the responses to my five specific points. Overall, I will leave the other reviewers to address the revisions made in response to their points but I have checked specific things they raised that were related to my own initial concerns, particularly Reviewers 1's point about psychotropic medication and Reviewer 3's first two points. I am very happy with the responses made by the authors to my original review and find the manuscript to be considerably improved. For the second of my specific points, I agree that little purpose would be served by including the sensitivity analysis with a limited age range in the final manuscript. The proportion of the sample aged under 40 at initial attendance is too small to make a notable difference.

There are some minor issues with the language of the manuscript. Some examples I remember were:

line 283 - "and died more often from all-causes and CVD" would read better as "and more likely to have died from all-causes and CVD";

line 449 - "However, the study design prevent further investigation" should be "However, the study design prevents further investigation";

line 537 - "Such as study" should be "Such a study".

Reviewer #3: Please see attached file.

Any attachments provided with reviews can be seen via the following link:

[LINK]

Submitted filename: degerund.pdf

Click here for additional data file.

28 Nov 2019

Submitted filename: Response to reviewers.docx

Click here for additional data file.

18 Dec 2019

Dear Dr. Degerud,

Thank you very much for re-submitting your manuscript "Combination of self-reported mental health problems and alcohol intake and the risk of all-cause and cardiovascular disease mortality - A pooled analysis of Norwegian cardiovascular health surveys." (PMEDICINE-D-19-02500R2) for review by PLOS Medicine.

I have discussed the paper with my colleagues and the academic editor and it was also seen again by one reviewer. I am pleased to say that provided the remaining editorial and production issues are dealt with we are planning to accept the paper for publication in the journal.

The remaining issues that need to be addressed are listed at the end of this email. Any accompanying reviewer attachments can be seen via the link below. Please take these into account before resubmitting your manuscript:

[LINK]

Our publications team (plosmedicine@plos.org) will be in touch shortly about the production requirements for your paper, and the link and deadline for resubmission. DO NOT RESUBMIT BEFORE YOU'VE RECEIVED THE PRODUCTION REQUIREMENTS.

***Please note while forming your response, if your article is accepted, you may have the opportunity to make the peer review history publicly available. The record will include editor decision letters (with reviews) and your responses to reviewer comments. If eligible, we will contact you to opt in or out.***

In revising the manuscript for further consideration here, please ensure you address the specific points made by each reviewer and the editors. In your rebuttal letter you should indicate your response to the reviewers' and editors' comments and the changes you have made in the manuscript. Please submit a clean version of the paper as the main article file. A version with changes marked must also be uploaded as a marked up manuscript file.

Please also check the guidelines for revised papers at http://journals.plos.org/plosmedicine/s/revising-your-manuscript for any that apply to your paper. If you haven't already, we ask that you provide a short, non-technical Author Summary of your research to make findings accessible to a wide audience that includes both scientists and non-scientists. The Author Summary should immediately follow the Abstract in your revised manuscript. This text is subject to editorial change and should be distinct from the scientific abstract.

We expect to receive your revised manuscript within 1 week. Please email us (plosmedicine@plos.org) if you have any questions or concerns.

We ask every co-author listed on the manuscript to fill in a contributing author statement. If any of the co-authors have not filled in the statement, we will remind them to do so when the paper is revised. If all statements are not completed in a timely fashion this could hold up the re-review process. Should there be a problem getting one of your co-authors to fill in a statement we will be in contact. YOU MUST NOT ADD OR REMOVE AUTHORS UNLESS YOU HAVE ALERTED THE EDITOR HANDLING THE MANUSCRIPT TO THE CHANGE AND THEY SPECIFICALLY HAVE AGREED TO IT.

Please ensure that the paper adheres to the PLOS Data Availability Policy (see http://journals.plos.org/plosmedicine/s/data-availability), which requires that all data underlying the study's findings be provided in a repository or as Supporting Information. For data residing with a third party, authors are required to provide instructions with contact information for obtaining the data. PLOS journals do not allow statements supported by "data not shown" or "unpublished results." For such statements, authors must provide supporting data or cite public sources that include it.

If you have any questions in the meantime, please contact me or the journal staff on plosmedicine@plos.org.

We look forward to receiving the revised manuscript by Dec 23 2019 11:59PM.

Sincerely,

Caitlin Moyer, Ph.D.

Associate Editor

PLOS Medicine

plosmedicine.org

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Requests from Editors:

1. Data Availability Statement: Thank you for providing your data availability statement and the contact information for access to your study’s data. Please remove the following text from the statement, as this detail is not needed: “The reason why the data are not made publicly available in a public repository or as a supporting information is because of local legal restrictions as well as ethical restrictions related to privacy. The participants have not consented to their data becoming publicly available and they might lose control of their data, such as their right to have their data deleted.”

2. Title: Please revise your title according to PLOS Medicine's style. Your title must be nondeclarative and not a question. Please place the study design in the subtitle, after a colon rather than a hyphen. When you revise your title, please update the text of the manuscript as well as the manuscript submission form with your revised title. We suggest, “Association of coincident self-reported mental health problems and alcohol intake with all-cause and cardiovascular disease mortality: A Norwegian pooled population analysis” or similar.

3. Abstract: Methods and Findings: Line 36: Please indicate here that alcohol intake was “self-reported”.

4. Abstract: Methods and Findings: Please provide some summary demographic information for the study participants, e.g. prevalence information, mortality, etc.

5. Abstract: Methods and Findings: Line 42: Please revise to “...light, moderate, and high intakes, respectively.”

6. Abstract: Conclusions: Please revise this sentence to clarify “they” in “...were increased when they occurred together.”

7. Author summary: Please use bullets rather than dashes for separate points.

8. Author Summary: Why was this study done?: Please revise the second point to clarify, we suggest: “Many people both drink alcohol and experience mental health problems, but we do not have much data showing whether the combination of drinking alcohol and mental health problems is associated with additional negative health consequences.”

9. Author Summary: What did the researchers do and find?: Please clarify the second point, we suggest: “The risk of all-cause and cardiovascular disease mortality was higher among people defined with more mental health problems and a high alcohol intake (“>24 g/day”) than would be expected for the linear combination of high alcohol intake and high mental health index.”

10. Author Summary: What do these findings mean?: Please clarify the bullet points and remove causal language, similar to this, according to your intended meaning:

- The findings suggest that co-occurring alcohol intake and mental health problems are associated with increased negative health effects including all-cause and cardiovascular disease-related mortality.

- Our findings may help to inform clinical recommendations regarding potential risks of alcohol use by individuals with mental health problems.

- The findings warrant future studies with longitudinal data that can shed more light on the mechanisms underlying the interaction between alcohol intake, mental health, and mortality.

11. Introduction: Line 104: Please change “relation” to “relationship”.

12. Introduction: Lines 106-108: The meaning of the word “trait” is not clear, please clarify these sentences.

13. Introduction: Lines 104-111: Please replace “relation” with “relationship”.

14. Introduction: Line 118: Please change “interaction” to “an interaction between mental health problems and alcohol intake.” or similar, according to your meaning.

15. Introduction: Final sentence: Please revise to reduce causal language: “The second objective was to investigate whether risks of all-cause or CVD-related mortality are increased in persons who report mental health problems and alcohol intake in combination, suggesting an interaction between mental health problems and alcohol intake.” or similar

16. Methods: Line 131: Please clarify if by “when attending” you mean “at the time of participation in the survey”

17. Results: Lines 282-289: Please clarify that the 51,754 participants excluded is the total excluded, and you then discuss the breakdown of that number by type of missing data.

18. Results: Lines 342-343: Please give the minimum follow up time, as well as the maximum.

19. Results: Lines 366-372: Please provide p values for analyses of alcohol intake and the risk of all-cause and CVD mortality.

20. Results: Lines 380-386: Please clarify what is meant when you say “higher” or “higher than expected” by providing the reader with information on what would be “expected” and also describing the HRs you observed, and demonstrating how they differ (with 95% CIs and p values).

21. Results: Lines 406-410: Please provide the 95% CIs and p values for the relationships described here. In the sentence at line 406 please clarify that this describes the relationship for all-cause mortality.

22. Results: Lines 418-420: Please clarify what is meant when you say “test for a difference in slope was positive”.

23. Discussion: Line 540: Please clarify the term “frailer”.

24. Discussion: Line 546-548: Please revise this sentence to avoid causal language, we suggest: “This study suggests that in a large sample of the general population that mortality risk is increased in people who report more mental health problems and a higher alcohol intake, raising the possibility of interaction between risks associated with mental health problems and higher alcohol intake.” or similar.

25. Discussion: Lines 548 and Line 572 (and throughout): Please revise to avoid the use of causal language (“evidence”) as your study is observational and causality cannot be suggested.

26. Discussion: Conclusions: First sentence: Please add “Our study found…” or similar to the sentence.

27. Discussion: Conclusions: Line 572-574: This sentence is not clear, please revise: “This potentially involves wide population groups extending beyond diagnosed patients with disorders related to alcohol use or mental health.”

28. Figure 2 legend: Please clarify what is meant by “functional forms” in the title.

29. Table 1 Legend: Rather than saying a high score is unfavorable, please clarify specifically what a high score indicates (e.g. indicates greater numbers of self reported mental health issues).

30. Table 2 and Table 3: Please present both the 95% CIs and p values for the interaction effects.

31. S2 Figure: Please clarify in the legend the gray shading represents the 95% CIs.

32. S1 Checklist: Thank you for including the STROBE Checklist.

33. Please remove the sections (lines 770 and beyond) on Transparency, Competing Interests, Funding, Ethics Approval, and Data Sharing, as this information is automatically pulled together via the manuscript submission system.

Comments from Reviewers:

Reviewer #3: The authors have been very responsive to my previous comments and have now addressed all issues raised. No additional comments.

Any attachments provided with reviews can be seen via the following link:

[LINK]

22 Dec 2019

Submitted filename: Response to reviewers.docx

Click here for additional data file.

6 Jan 2020

Dear Mr Degerud,

On behalf of my colleagues and the academic editor, Dr. Charlotte Hanlon, I am delighted to inform you that your manuscript entitled "Association of coincident self-reported mental health problems and alcohol intake with all-cause and cardiovascular disease mortality: A Norwegian pooled population analysis" (PMEDICINE-D-19-02500R3) has been accepted for publication in PLOS Medicine.

PRODUCTION PROCESS

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If you are likely to be away when either this document or the proof is sent, please ensure we have contact information of a second person, as we will need you to respond quickly at each point.

PRESS

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PROFILE INFORMATION

Now that your manuscript has been accepted, please log into EM and update your profile. Go to https://www.editorialmanager.com/pmedicine, log in, and click on the "Update My Information" link at the top of the page. Please update your user information to ensure an efficient production and billing process.

Thank you again for submitting the manuscript to PLOS Medicine. We look forward to publishing it.

Best wishes,

Caitlin Moyer, Ph.D.

Associate Editor

PLOS Medicine

plosmedicine.org