Maturitas 56 (2007) 263–272
A prospective analysis of alcohol consumption and onset of perimenopause Ghasi S. Phillips a,∗ , Lauren A. Wise b , Bernard L. Harlow c a
Harvard School of Public Health, Epidemiology, Kresge Building, 9th Floor, 677 Huntington Avenue, Boston, MA 02115, United States b Slone Epidemiology Center, Boston University, 1010 Commonwealth Avenue, Boston, MA 02215, United States c Epidemiology and Community Health, University of Minnesota School of Public Health, 1300 South Second Street, Suite 300, Minneapolis, MN 55454, United States Received 7 March 2006; received in revised form 22 August 2006; accepted 25 August 2006
Abstract Objectives: We prospectively assessed the association between alcohol consumption and onset of perimenopause in women of late reproductive age using data from the Harvard Study of Moods and Cycles. Specific types of alcoholic beverages – red wine, white wine, beer, and liquor – were evaluated. Methods: Among 502 women aged 36–45 years residing in seven Boston communities, we assessed self-reported perimenopausal symptoms over a 5-year period. The onset of perimenopause was defined using changes in menstrual characteristics. We administered a semiquantitative food frequency questionnaire at enrollment to measure regular alcohol consumption during the past year. Hazard ratios (HRs) and 95% confidence intervals were derived from Cox regression models. Results: No association was found between total alcohol consumption and time to perimenopause. Compared with women consuming <1 alcoholic drink per month, HRs for those drinking red wine in quantities of 1–3 glasses per month, 1 glass per week, or ≥2 glasses per week were all below 1.0, after accounting for other sources of alcohol. Among never smokers, the inverse association with red wine was stronger and a positive association was observed with liquor consumption although numbers were small. No associations were observed with white wine or beer. Conclusion: While there was no association between total alcohol consumption and onset of perimenopause, there was some suggestion of an inverse association between red wine and risk of perimenopause, particularly among never smokers. © 2006 Elsevier Ireland Ltd. All rights reserved. Keywords: Perimenopause; Menopause; Climateric; Alcohol; Red wine; White wine; Beer; Liquor; Women’s health; Resveratrol
1. Introduction
∗
Corresponding author. Tel.: +1 347 267 4558. E-mail addresses:
[email protected],
[email protected] (G.S. Phillips).
The World Health Organization (WHO) defines perimenopause as the period beginning with the endocrinological, biological, and clinical features associated with the menopausal transition and ending
0378-5122/$ – see front matter © 2006 Elsevier Ireland Ltd. All rights reserved. doi:10.1016/j.maturitas.2006.08.008
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1 year after the development of the menopause [1]. During this time, women begin to live with low levels of estrogen which may increase the risk of osteoporosis [2], cardiovascular disease [3], and related mortality [4]. In contrast, longer exposure to estrogenic activity has been linked with a higher incidence of breast cancer [5]. It is estimated that the median age when women commence perimenopause is 47.5 years with the median length lasting 3.5 years [6]. Besides age, cigarette smoking is a well recognized risk factor that accelerates the age of menopause by approximately 1–3 years [6–11]. There is some evidence that nulliparity [11–13], major depression [14], low socioeconomic position [11,15], and African-American or Hispanic ethnicity [7,8,10,12] may increase the risk of an early inception of perimenopause. The relation between alcohol intake and the onset of menopause has also been examined [7,11,12,16,17]. Alcohol (specifically ethyl alcohol) may affect certain reproductive processes directly [18,19] or through the phytoestrogen resveratrol [20–22]. Three crosssectional studies [7,11,12] and one case-control study [16] have examined the association between total alcohol consumption and the menopausal transition. One recent longitudinal study found evidence of a later age of menopause associated with alcohol consumption, but the authors did not examine the type of alcoholic beverage [17]. The present study addresses the possible heterogeneity of alcohol effects by conducting separate analyses on red wine, white wine, liquor, and beer in a prospective fashion.
2. Materials and methods 2.1. Study population The Harvard Study of Moods and Cycles is a longitudinal study derived from a population-based sample of women aged 36–45 years between 1995 and 1997. The main purpose of the study was to assess the influence of major depression on ovarian function in late reproductive-aged women. Women were randomly selected from seven Boston communities listed in Massachusetts Town Books, which annually post residents by name, age, and address. A short questionnaire was mailed to 6228 women to assess menopausal
status and past depression. The Center for Epidemiologic Studies Depression Scale (CES-D) was also sent to measure current depressive symptoms [23]. After the questionnaires were completed by 73.5% (n = 4569) of women contacted, a representative cohort of 332 depressed and 644 non-depressed women were formally enrolled in the study after providing written consent. In-person interviews were conducted at study enrollment and every 6 months over a 3-year period to collect data on medical, reproductive and psychiatric histories. A subsequent follow-up questionnaire was mailed 2 years later to capture additional events, yielding a total follow-up period of 5 years (60 months). Further details pertaining to the data collection methods and exclusionary criteria have been published elsewhere [24,25]. 2.2. Dietary assessments A 131-item semiquantitative food frequency questionnaire (SFFQ) was administered to the study participants at baseline [26]. The women provided information on their average use of beer (1 glass, bottle, can), red wine (4 oz glass), white wine (4 oz glass), and liquor (1 drink or shot) during the previous year. Frequency of beverage intake was specified in nine categories: “never or less than 1 per month”, “1–3 per month”, “1 per week”, “2–4 per week”, “5–6 per week”, “1 per day”, “2–3 per day”, “4–5 per day”, and “6+ per day”. Total alcohol consumption was computed by adding the weighted contributions to alcohol (ethanol) from the above-mentioned serving sizes of beer, wine, and liquor. The weights were as follows: 12.8 g for beer, 11.0 g for wine, and 14.0 g for liquor [27]. The questions on alcohol consumption have been validated in a similar cohort where the correlation coefficient was 0.90 between the 1-week diet records and the questionnaire [28,29]. We categorized total alcohol intake into five 5-unit categories ranging from 0 g of alcohol per day to at least 15 g per day. To address the notion that the effect of a specific alcoholic drink might have been masked in the composite alcohol variable, we examined associations between the onset of perimenopause and red wine, white wine, liquor, and beer. To increase statistical power we collapsed the nine aforementioned frequency categories into five levels of alcohol consumption: non-drinkers or <1 drink per month, <1 drink
G.S. Phillips et al. / Maturitas 56 (2007) 263–272
per month, 1–3 drinks per month, 1 drink per week, and ≥2 drinks per week. 2.3. Assessment of the outcome Onset of perimenopause was defined as: (1) an absolute change of at least 7 days in menstrual cycle length relative to length at baseline; (2) a change in menstrual flow amount by two flow categories or more (e.g. light or moderately light to moderately heavy or heavy) or an absolute change in duration lasting at least 2 days relative to that observed at baseline; or (3) periods of amenorrhea ensuing for 3 months or more [30–33]. 2.4. Baseline covariates At study enrollment, we conducted in-person interviews to obtain demographic, lifestyle, reproductive, and medical information [14]. We coded baseline covariates in the manner shown in Table 1 while using the World Health Organization classification for body mass index [34]. 2.5. Restriction criteria for prospective analyses Of the original 976 women enrolled in the Harvard Study of Moods and Cycles, we excluded participants who were lost to follow-up within the first 6 months after study enrollment (n = 17) and those who already experienced perimenopausal symptoms at baseline (n = 91). To avoid misclassification of time to perimenopause, we also excluded women who were pregnant, breastfeeding, or using exogenous hormones at baseline (n = 140). Of the remaining 728 subjects, 502 women provided information on their alcohol drinking habits as well as covariates relevant to the present analysis. 2.6. Statistical analyses All analyses were performed with SAS statistical software (Version 9.1) [35]. We used the chi-square test to compare the overall frequency of risk factors for perimenopause in relation to total alcohol intake. In the context of a prospective study, these comparisons allowed for the identification of potential confounding variables.
265
Crude and multivariate Cox proportional hazards regression models [36] were used to estimate hazard ratios (HRs) and 95% confidence intervals (CIs) for the onset of perimenopause in association with alcohol consumption. Time to perimenopause, in months, was calculated from the date of entry into the study (baseline) until the onset of perimenopause, the occurrence of a censoring event (i.e., loss to follow-up, use of exogenous hormones, pregnancy, breastfeeding, or medical menopause), or the end of observation (60 months), whichever came first. We censored women who reported the commencement of both hormone therapy and perimenopause during the same follow-up interval because we could not determine whether the use of hormones preceded the occurrence of perimenopausal symptoms or vice versa. We used the “exact” option to handle numerous ties since most data on time to perimenopause were collected in 6 months intervals and were relatively imprecise. We controlled for age, BMI, education, depression, smoking, caloric intake, and monthly household income in multivariate models. In each alcohol-specific analysis, the multivariate models also adjusted for the three other alcoholic drinks, which were coded in continuous form. Adding the other beverages allowed us to estimate the independent effect of each alcoholic beverage on the onset of perimenopause. As the original study design involved the assessment of depression on ovarian function, we conducted subgroup analyses among depressed and non-depressed groups to assess the presence of effect modification by depression on the association between alcohol (total and specific beverage) and perimenopause. Since cigarette smoking is an established risk factor for onset of perimenopause and menopause [6–11], we examined the association between alcohol and perimenopause separately among never and ever smokers. Our main rationale for examining the alcohol-perimenopause association among never smokers was to minimize concern about residual confounding by smoking. To test for effect modification by smoking status, we compared models with and without interaction terms of alcohol consumption and smoking. To test for violation of the proportional hazards assumption, we compared models with and without interaction terms of alcohol consumption and time. A p-value <0.05 was used to denote evidence of departure from proportional hazards.
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Table 1 Frequency (percentage) of baseline covariates according to total alcohol consumption among 502 women Characteristic
Alcohol consumption <0.1 (g/day)
Age at baseline 36–37 38–39 40–41 42–43 44–45
0.1–4.9 (g/day)
5.0–9.9 (g/day)
10.0–14.9 (g/day)
≥15.0 (g/day)
p-Valuea
0.18
16 (12.6) 26 (20.5) 33 (26.0) 37 (29.1) 15 (11.8)
33 (17.7) 54 (29.0) 44 (23.7) 38 (20.4) 17 (9.1)
12 (12.4) 28 (28.9) 20 (20.6) 30 (30.9) 7 (7.2)
12 (20.3) 12 (20.3) 9 (15.3) 14 (23.7) 12 (20.3)
5 (15.2) 7 (21.2) 11 (33.3) 7 (21.2) 3 (9.1)
116 (91.3)
177 (95.2)
96 (99.0)
56 (94.9)
31 (93.9)
11 (8.7)
9 (4.8)
1 (1.0)
3 (5.1)
2 (6.1)
12 (9.5) 29 (22.8)
15 (8.1) 33 (17.7)
4 (4.1) 12 (12.4)
1 (1.7) 5 (8.5)
0 (0.0) 6 (18.2)
38 (29.9) 48 (37.8)
60 (32.3) 78(41.9)
42 (43.3) 39 (40.2)
20 (33.9) 33 (55.9)
7 (21.2) 20 (60.6)
0.02
17 (13.4) 110 (86.6)
27 (14.5) 159 (85.5)
16 (16.5) 81 (83.5)
11 (18.6) 48 (81.4)
4 (12.1) 29 (87.9)
0.86
History of major depression No 86 (67.7) Yes 41 (32.3)
124 (66.7) 62 (33.3)
75 (77.3) 22 (22.7)
41 (69.5) 18 (30.5)
19 (57.6) 14 (42.4)
0.22
Age at menarche ≤11 12–14 ≥15
20 (15.8) 96 (75.6) 11 (8.7)
32 (17.2) 131 (70.4) 23 (12.4)
18 (18.6) 66 (68.0) 13 (13.4)
8 (13.6) 47 (79.7) 4 (6.8)
9 (27.3) 20 (60.6) 4 (12.1)
0.57
Smoking status Never Past Current
66 (52.0) 49 (38.6) 12 (9.5)
113 (60.8) 58 (31.2) 15 (8.1)
53 (54.6) 32 (33.0) 12 (12.4)
30 (50.9) 23 (39.0) 6 (10.2)
14 (42.4) 13 (39.4) 6 (18.2)
0.46
Monthly household take-home pay
5 (2.7) 17 (9.1) 25 (13.4) 28 (15.1) 54 (29.0) 33 (17.7) 24 (12.9)
2 (2.1) 7 (7.2) 16 (16.5) 14 (14.4) 21 (21.7) 20 (20.6) 17 (17.5)
0 (0.0) 4 (6.8) 7 (11.9) 9 (15.3) 17 (28.8) 11 (18.6) 11 (18.6)
0 (0.0) 2 (6.1) 5 (15.2) 6 (18.2) 11 (33.3) 5 (15.2) 4 (12.1)
0.38
Parity Nulliparous 1 live birth 2 live births 3 live births ≥4 live births
39 (21.0) 25 (13.4) 39 (21.0) 43 (23.1) 40 (21.5)
22 (22.7) 14 (14.4) 19 (19.6) 24 (24.7) 18 (18.6)
17 (28.8) 5 (8.5) 16 (27.1) 8 (13.6) 13 (22.0)
7 (21.2) 9 (27.3) 7 (21.2) 5 (15.2) 5 (15.2)
0.55
Ethnicity White, Non-Hispanic Non-White Education HS grad Some college or vocational/technical school College Graduate Graduate School Married No Yes
34 (26.8) 16 (12.6) 33 (26.0) 24 (18.9) 20 (15.8)
0.16
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Table 1 (Continued ) Characteristic
Alcohol consumption 0.1–4.9 (g/day)
5.0–9.9 (g/day)
10.0–14.9 (g/day)
≥15.0 (g/day)
p-Valuea
8 (6.3) 59 (46.5) 34 (26.8) 26 (20.5)
21 (11.3) 107 (57.5) 36 (19.4) 22 (11.8)
15 (15.5) 53 (54.6) 19 (19.6) 10 (10.3)
14 (23.7) 30 (50.9) 14 (23.7) 1 (1.7)
6 (18.2) 19 (57.6) 6 (18.2) 2 (6.1)
0.003
76 (59.8) 51 (40.2)
108 (58.1) 78 (41.9)
41 (42.3) 56 (57.7)
28 (47.5) 31 (52.5)
7 (21.2) 26 (78.8)
<0.001
<0.1 (g/day) Body mass index <20.0 20.0–24.9 25.0–29.9 ≥30.0
(kg/m2 )
Total calories (kcal) <1800 ≥1800
Abbreviations: g, grams. a p-Value for the overall association between each baseline variable and total alcohol consumption.
3. Results Table 1 illustrates that alcohol consumption was more common among women with higher levels of education, women considered to be of average weight with respect to their height, and women with energy intake more than 1800 kcal/day. In our study, the prevalence of regular alcohol consumption in the year prior to baseline was 75%. Of the total alcohol consumed by all women (in grams), 27% was contributed by red wine, 28% by white wine, 12% by liquor, and 33% by beer. There was no evidence of an association between total alcohol consumption and onset of perimenopause in the crude or adjusted models (Table 2). However, there was some suggestion that women who consumed moderate amounts of red wine had a reduced rate of entry into perimenopause, after adjustment for potential confounders. Multivariate HRs for the inception of perimenopause for red wine drinkers were all below one relative to non-drinkers, but there was no visual evidence of a monotonic dose-response relation. No associations were observed between white wine, beer, or liquor consumption and risk of perimenopause. The inverse association between red wine consumption and onset of perimenopause was more apparent among never smokers (Table 3). In this subgroup, a positive association was also observed with liquor consumption although the number of liquor drinkers was small. No associations were observed for white wine or beer in either never or ever smokers. Likelihood ratio tests showed no statistical difference in the main effects by smoking status (p-values, test for interaction: 0.19 (red wine) and 0.17 (liquor)). The association between
alcohol consumption and onset of perimenopause did not vary appreciably by history of depression (data not shown). Furthermore, there was no evidence of departure from the proportional hazards assumption (pvalue = 0.13).
4. Discussion In this prospective study, we saw no evidence that higher levels of total alcohol consumption delayed the onset of perimenopause. However, there was some suggestion of an inverse association between red wine consumption and onset of perimenopause. The overall lack of association supports the results of some studies [7,12,16] but not all [11,17]. Torgerson et al. [11] conducted a cross-sectional study that found a striking reduction in risk of early menopause as alcohol intake increased from none to 1 drink per day. Moreover, a recent longitudinal study by Kinney et al. [17], showed a later median age at menopause for women who drank alcohol 5–7 days per week compared with women who did not drink alcohol. In our analyses of specific alcohol beverages, we observed an inverse association for onset of perimenopause with increasing consumption of red wine, particularly among never smokers. Several studies have reported that ethanol (alcohol) possesses estrogenic properties and thus could modulate certain reproductive functions [18,19]. Despite this finding, our observed association between the inception of perimenopause and red wine, if real, must act through another pathway since no associations were seen with white wine or beer.
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Table 2 Crude and multivariate hazard ratios for onset of perimenopause in relation to alcohol intake among 502 women Alcohol intake
Number
Person-months
Crude HR (95% CI)
Multivariate HR (95% CI)a
Total alcohol (g/day) <0.1 0.1–4.9 5.0–9.9 10.0–14.9 ≥15.0
127 186 97 59 33
4566 7104 3864 1842 1248
1.00 0.85 (0.64, 1.12) 0.84 (0.60, 1.17) 1.12 (0.77, 1.63) 0.84 (0.51, 1.37)
1.00 0.94 (0.70, 1.26) 0.95 (0.67, 1.34) 1.29 (0.86, 1.93) 0.93 (0.56, 1.56)
Total alcohol (drinks) None or <1 per month 1–3 per month 1 per week ≥2 per week
127 159 68 148
4566 6024 2610 5424
1.00b 0.89 (0.66, 1.18) 0.91 (0.64, 1.31) 0.86 (0.64, 1.16)
1.00b 0.97 (0.72, 1.31) 0.97 (0.67, 1.42) 1.00 (0.72, 1.38)
Red wine (4 oz glass)c <1 per month 1–3 per month 1 per week ≥2 per week
145 97 52 81
4896 4002 2022 3138
1.14 (0.86, 1.52) 0.67 (0.48, 0.95) 0.87 (0.58, 1.29) 0.76 (0.53, 1.09)
1.03 (0.61, 1.74) 0.58 (0.33, 1.03) 0.73 (0.37, 1.44) 0.67 (0.34, 1.31)
White wine (4 oz glass) <1 per month 1–3 per month 1 per week ≥2 per week
102 129 64 80
3606 5160 2556 2736
1.05 (0.76, 1.44) 0.78 (0.57, 1.06) 0.76 (0.52, 1.12) 0.96 (0.68, 1.36)
1.31 (0.79, 2.21) 1.00 (0.62, 1.61) 1.16 (0.64, 2.12) 1.52 (0.87, 2.66)
Liquor (1 drink or shot) <1 per month 1–3 per month 1 per week ≥2 per week
252 70 29 24
9438 2622 1092 906
0.84 (0.64, 1.09) 0.99 (0.69, 1.41) 0.91 (0.55, 1.50) 0.99 (0.59, 1.67)
1.07 (0.65, 1.74) 1.35 (0.78, 2.33) 1.28 (0.64, 2.56) 1.29 (0.66, 2.50)
Beer (1 glass, bottle, can) <1 per month 1–3 per month 1 per week ≥2 per week
152 78 65 80
5424 3048 2646 2940
0.96 (0.72, 1.28) 0.77 (0.54, 1.10) 0.77 (0.53, 1.12) 0.96 (0.68, 1.35)
1.06 (0.64, 1.76) 0.92 (0.53, 1.60) 0.99 (0.55, 1.80) 1.13 (0.65, 1.97)
Abbreviations: HR, hazard ratio; CI, confidence interval. a Adjusted for age, BMI, caloric intake, depression, education, cigarette smoking, and monthly household income. Each model also included the three other alcoholic drinks coded as continuous variables. b Referent group for all beverage-specific comparisons. c p-Value for the multivariate analysis trend test was 0.01. Test for trend excludes non-drinkers or <1 per month of any alcohol.
A possible mechanism could exist through resveratrol, which is a phytoestrogen that can act on ovarian cells and human breast tissue [20–22]. Resveratrol (3,5,4 -trihyrodxystilbene) has a polyphenolic structure similar to that of diethylstilbestrol (DES) [37,38]. During fungal attacks or injuries, grape vines (Vitis vinifera) concentrate resveratrol in grape skins [39] however red grape skins, which are used to make red wines (e.g. Pinot, Noir, and Merlot), contain more resveratrol than white grape skins, which are needed
for white wines (e.g. Chardonnay) [38,40]. Resveratrol has many beneficial biological roles including anticancer effects [21,22,41–43], antioxidant activity [38], and estrogenic functions [20–22,38,41,44,45]. Since resveratrol can act as an estradiol agonist on ovarian estrogen receptors [21,46,47], it seems feasible that regular consumption of moderate amounts of red wine could increase ovarian exposure to resveratrol which in turn could stimulate the production of ovarian hormones necessary for usual ovarian function.
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Table 3 Adjusted hazard ratios for onset of perimenopause in relation to alcohol intake among never and ever cigarette smokers Alcohol intake
Never smokers
Ever smokers CI)a
Number
Person-months
Multivariate HR (95% CI)a
1.00 1.06 (0.70, 1.59) 1.03 (0.63, 1.68) 1.04 (0.57, 1.91) 1.36 (0.63, 2.92)
61 73 44 29 19
2136 2712 1776 852 708
1.00 1.00 (0.62, 1.59) 0.84 (0.51, 1.40) 1.44 (0.81, 2.56) 0.73 (0.36, 1.48)
2430 3690 1536 2784
1.00b 1.16 (0.76, 1.77) 0.99 (0.59, 1.67) 0.98 (0.61, 1.57)
61 63 27 75
2136 2334 1074 2640
1.00b 0.97 (0.59, 1.57) 0.89 (0.50, 1.60) 1.00 (0.62, 1.59)
79 54 34 43
2670 2208 1284 1848
0.88 (0.40, 1.93) 0.53 (0.23, 1.22) 0.56 (0.21, 1.47) 0.34 (0.12, 0.97)
66 43 18 38
2226 1794 738 1290
1.19 (0.54, 2.60) 0.60 (0.25, 1.47) 0.95 (0.32, 2.77) 0.85 (0.34, 2.17)
White wine (4 oz glass) <1 per month 1–3 per month 1 per week ≥2 per week
51 79 34 46
1842 3234 1374 1560
1.38 (0.65, 2.92) 1.15 (0.59, 2.26) 1.15 (0.49, 2.71) 1.65 (0.75, 3.66)
51 50 30 34
1764 1926 1182 1176
1.55 (0.70, 3.47) 0.91 (0.43, 1.95) 1.26 (0.49, 3.25) 1.62 (0.70, 3.73)
Liquor (1 drink or shot)c <1 per month 1–3 per month 1 per week ≥2 per week
157 30 13 10
6126 1068 486 330
1.45 (0.70, 2.98) 2.01 (0.89, 4.53) 2.25 (0.81, 6.25) 3.36 (1.15, 9.84)
95 40 16 14
3312 1554 606 576
1.09 (0.51, 2.35) 1.35 (0.60, 3.06) 1.26 (0.44, 3.61) 0.92 (0.37, 2.29)
Beer (1 glass, bottle, can) <1 per month 1–3 per month 1 per week ≥2 per week
81 48 40 41
2910 1824 1728 1548
1.22 (0.60, 2.48) 1.02 (0.49, 2.16) 1.17 (0.51, 2.69) 1.40 (0.67, 2.92)
71 30 25 39
2514 1224 918 1392
1.15 (0.53, 2.49) 1.05 (0.44, 2.49) 1.07 (0.43, 2.66) 1.19 (0.49, 2.90)
Number
Person-months
Multivariate HR (95%
66 113 53 30 14
2430 4392 2088 990 540
Total alcohol (drinks) None or <1 per month 1–3 per month 1 per week ≥2 per week
66 96 41 73
Red wine (4 oz glass)c <1 per month 1–3 per month 1 per week ≥2 per week
Total alcohol (g/day) <0.1 0.1–4.9 5.0–9.9 10.0–14.9 ≥15.0
Abbreviations: HR, hazard ratio; CI, confidence interval. a Adjusted for age, BMI, caloric intake, depression, education, and monthly household income. Except for total alcohol, each model included the three other alcoholic drinks coded as continuous variables. b Referent group for all beverage-specific comparisons. c Among never smokers, p-value for linear test for trend was 0.001 and 0.004 for the red wine and liquor analyses, respectively. Test for trend excludes non-drinkers or <1 per month of any alcohol.
We cannot rule out the possibility that the inverse association seen with red wine might be due to residual confounding or uncontrolled factors. However, our final models adjusted for several established risk factors for perimenopause as well as variables that might decrease the amount of unexplained variability. It is unclear why we observed a positive association between liquor intake and onset of
perimenopause among never smokers only, while the overall analyses did not show an association. Given that the number of liquor drinkers was small, we believe these results should be interpreted with caution. Selection bias, in the form of differential loss to follow-up, might be a concern for our study. Women who did not drink any alcohol spent, on average,
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3 months longer in the study compared to women who consumed any form of alcohol (33.6 months versus 30.6 months). Although the difference was small, if the alcohol drinkers who dropped out were more likely to experience early perimenopause, the observed associations would be underestimates of the true alcohol-perimenopause association. Misclassification of alcohol consumption might bias our findings due to the difficulty in estimating serving sizes and recalling average intake over the past year. Dietary recall is more problematic for items that vary on a day-by-day basis but not for items that are components of a usual diet. Thus, the semiquantitative food frequency questionnaire is a good tool to quantify usual intake as it measures the average consumption of foods and nutrients within the past year [26]. It is doubtful that the manner in which women reported their usual intake of alcohol would depend on their menstrual cycle events, therefore any random misclassification introduced in our analysis would bias effect estimates towards the null. The assessment of alcohol intake would have been more efficient if measurements were taken at each follow-up period [26]. However, by only taking one measure of average alcohol consumption it was assumed that alcohol intake did not vary appreciably over the course of the study period. Daily recall of menstrual changes would give rise to a near optimal assessment of the inception of perimenopause. However, we based the assessment on self-reports given within the previous 6 months of each follow-up period. Consequently, the outcome variable might be subject to measurement errors independent of alcohol consumption. Since the participants were unaware of the study hypothesis, it is unlikely that reports of menstrual irregularities would be related to alcohol intake. Any non-differential misclassification of the outcome would bias our estimates toward the null. Our study has several strengths. We used a prospective study design to examine the association between time to perimenopause and regular alcohol consumption unlike the three other studies that investigated this relation among a cross-sectional sample of women [7,11,12]. Since the exposure was measured before the occurrence of perimenopause, it is unlikely that the reporting of alcohol would have been influenced by perimenopausal status.
We addressed the possible heterogeneity of alcohol effects by conducting separate analyses on red wine, white wine, liquor, and beer. Our analysis provided evidence that there might be a component to red wine that differentiates its relation with perimenopause from that of other beverages. This possible heterogeneity in effects could explain why other studies reported null findings [7,10,12,16]. It is unknown what proportion of alcohol drinkers in the Kinney study were red wine drinkers because they only examined total alcohol consumption. If large, this could explain why they found an inverse association with total alcohol [17]. Interestingly, Torgerson et al. [11] found a striking decreased risk of early menopause with increasing alcohol consumption. However, unlike our study, they classified one drink equal to “0.5 pint of lager/beer, or 1 measure of spirit, or one glass of wine, port, or sherry”. In summary, we found no association between the inception of perimenopause and total alcohol consumption, but there was some suggestion that red wine might delay the onset of perimenopause, particularly among never smokers. Our results are consistent with the hypothesis that red wine has antioxidant and pro-estrogenic effects. Further studies are needed to confirm these results in other populations of women. References [1] World Health Organization Scientific Group. Research on the menopause. Geneva: World Health Organization; 1981. [2] Kritz-Silverstein D, Barrett-Connor E. Early menopause, number of reproductive years, and bone mineral density in postmenopausal women. Am J Public Health 1993;83(7): 983–8. [3] Snowdon DA, Kane RL, Beeson WL, et al. Is early natural menopause a biologic marker of health and aging? Am J Public Health 1989;79(6):709–14. [4] van der Schouw YT, van der Graaf Y, Steyerberg EW, Eijkemans JC, Banga JD. Age at menopause as a risk factor for cardiovascular mortality. Lancet 1996;347(9003):714–8. [5] Medina D. Mammary developmental fate and breast cancer risk. Endocr Relat Cancer 2005;12(3):483–95. [6] McKinlay SM, Brambilla DJ, Posner JG. The normal menopause transition. Maturitas 1992;14(2):103–15. [7] Brett KM, Cooper GS. Associations with menopause and menopausal transition in a nationally representative US sample. Maturitas 2003;45(2):89–97. [8] Bromberger JT, Matthews KA, Kuller LH, Wing RR, Meilahn EN, Plantinga P. Prospective study of the determinants of age at menopause. Am J Epidemiol 1997;145(2):124–33.
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