- Email: [email protected]
Negative lifestyle is associated with a significant reduction in fecundity
FERTILITY AND STERILITY威 VOL. 81, NO. 2, FEBRUARY 2004 Copyright ©2004 American Society for Reproductive Medicine Published by Elsevier Inc. Printed on acid-free paper in U.S.A.
Negative lifestyle is associated with a significant reduction in fecundity Mohamed A. M. Hassan, M.Sc., and Stephen R. Killick, M.D. The University of Hull, Postgraduate Medical Institute, Hull and York Medical School, Academic Department of Obstetrics and Gynaecology, Women’s and Children’s Hospital, Hull Royal Infirmary, Hull, United Kingdom
Objective: To evaluate the association patterns and quantify the effects of lifestyle on time to pregnancy (TTP). Design: Observational study. Setting: Teaching hospitals in Hull, United Kingdom. Patient(s): Two thousand and one hundred twelve consecutive pregnant women. Intervention(s): A questionnaire inquiring about TTP, contraceptive use, pregnancy planning, previous subfertility/pregnancies, age, and lifestyle characteristics of either partner. Main Outcome Measure(s): We compared TTP, conception rates, and relative risk of subfecundity between subgroups with different lifestyle characteristics. Result(s): We found that TTP was significantly longer if the woman or partner smoked ⬎15 cigarettes/day (P⬍.001 and .04, respectively), the partner consumed ⬎20 alcohol units/week (P⬍.001), the woman’s body mass index was ⬎25 kg/m2 (P⬍.001), their coffee and/or tea intake was ⬎6 cups/day (P⫽.04), or if they were socially deprived (P⬍.001). Each of these effects remained unchanged after adjusting for the potential confounders. The relative-risks of subfecundity with each of these variables ranged between 1.4 to 1.9 (1.4 to 3.6 after adjustment). The effects of coital frequency and recreational drug use were insignificant. Couples who had ⬎4 negative lifestyle variables had a sevenfold longer TTP; their conception probabilities fell by 60%, and they were 7.3-fold more likely to be subfecund than those without negative variables. Conclusion(s): Lifestyle has a significant and cumulative impact on fecundity. Dose-dependent effects occur with smoking, alcohol, and tea/coffee consumption. Appropriate counseling could result in substantial reductions in the referrals for fertility investigations and treatments. (Fertil Steril威 2004;81:384 –92. ©2004 by American Society for Reproductive Medicine.) Key Words: Time to pregnancy, fecundity, fertility, lifestyle, age, obesity, smoking, alcohol, coffee, social deprivation
Received February 6, 2003; revised and accepted June 30, 2003. Presented at the XVII World Congress on Fertility and Sterility, Melbourne, Australia, November 25–30, 2001. Reprint requests: Mohamed A. M. Hassan, M.Sc., Women’s and Children’s Hospital, Hull Royal Infirmary, Anlaby Road, Hull HU3 2JZ, United Kingdom (FAX: 0044-1482-382781; E-mail: [email protected]). 0015-0282/04/$30.00 doi:10.1016/j.fertnstert.2003. 06.027
384
Half of the couples trying for a pregnancy succeed within 3 months, increasing to over 85% by end of the first year (1). An unsuccessful waiting time to pregnancy (TTP) despite frequent unprotected intercourse of ⬎12 months is usually used to define subfertility (2) and is commonly employed as an indication for commencing investigations (3). However, 30% of the subfertile couples have no identifiable medical cause, (4) and over 70% of these unexplained cases conceive within a further 24 months of trying without any medical intervention (5). Differences in the individual and lifestyle characteristics have been suggested to have a role, though poorly quantified, in the cause of subfertility (6 –11). If lifestyle variables could be modified, then this might assist
in the spontaneous achievement of pregnancy in cases of unexplained subfertility or in the success of fertility treatments (12, 13). Public expectation that medical treatment is increasingly possible and available leads to an ever increasing demand for the use of medical resources (14). Prevention, a main goal of the primary health care system, remains the most attractive and cost-effective approach to the majority of medical problems. Subfertility is no exception. Sound evidence-based advice given by general practitioners and through family planning clinics to couples planning for pregnancy could result, if the magnitude of the effects were great enough, in a substantial reduction in the referrals for medical investigation and in a consequent savings in resources.
The aim of this study was to evaluate the association patterns and to quantify the absolute and relative effects of lifestyle variables—including obesity, smoking, alcohol consumption, coffee and tea intake, recreational drug use, coital frequency, and standard of living— on fecundity, measured by the time interval of exposure to unprotected intercourse from the discontinuation of contraception until pregnancy (TTP).
MATERIALS AND METHODS A survey was conducted in Hull and East Yorkshire (September 2000 to May 2001). Consecutive women attending the antenatal clinics were asked to self-complete a questionnaire inquiring about TTP (the interval of exposure to unprotected intercourse from discontinuing birth control methods until conception), contraceptive use, pregnancy planning, previous fertility problems/pregnancies, gynecologic disease, and individual and lifestyle characteristics of either partner including their age, weight, height, smoking, alcohol consumption, coffee and tea intake, recreational drug use, and the couple’s coital frequency. Using the electoral ward, the postal code was linked to the Index of Multiple Deprivation (IMD), which was used as an indicator of the living standard. The IMD (15) is a compound index made up of six ward-level domain indices, each of which is composed of a number of indicators (33 in total) to describe aspects of this deprivation at a ward level as comprehensively as possible. These indices (contribution of each domain to the overall index) include: income (25%), employment (25%), education and training (15%), health deprivation and disability (15%), geographical access to services (10%), and housing (10%). The indicators measure deprivation independently of population size. The domain indices are also assigned a rank based on the electoral wards in England (8414), with the most deprived ward of each index given a rank of 1, and the least deprived ward given a rank of 8414. The IMD is ranked in the same way. The IMD score represents the combined sum of the weighted, exponentially transformed domain rank of the domain score. The bigger the IMD score, the more deprived the ward. The ranks show how a ward compares with all the other wards, whereas the scores indicate the distances between each rank position, as these will vary. Approval was obtained from the local research ethics committee (the UK equivalent of an institutional review board). There are no conflicts of interest. The response was over 99%, and the sample included 2112 completed questionnaires. Results of the component of the survey examining the effect of age on fecundity have already been published (16). Data analysis was carried out using a computer package (SPSS; SPSS, Inc., Chicago, IL). The outcome measures were the mean TTP, conception rates, and subfecundity FERTILITY & STERILITY威
TABLE 1 Differences in individual and lifestyle variables for fecund and subfecund couples. Variablea Women’s age (27.4 y) Men’s age (30.3 y) Women’s obesity: BMI (25.7 kg/m2) Women’s obesity: weight (69.1 kg) Women’s smokingb (11.1 cigarette/d) Men’s smokingb (15.6 cigarette/d) Women’s alcoholb (3.6 unit/wk) Men’s alcoholb (10.3 unit/wk) Women’s tea and coffee (3.7 cup/d) Coital frequency (1.9 times/wk) Previous pregnancies (1.5 pregnancies)
Fecund (CI)a
Subfecund (CI)a
P value
27.2 (26.9–27.4) 29.8 (29.5–30.1) 25.4 (25.2–25.7)
29.2 (28.6–29.7) 32.7 (32.0–33.4) 26.6 (26.1–27.1)
⬍.001 ⬍.001 ⬍.001
68.3 (67.6–69.0)
72.1 (70.6–73.6)
⬍.001
10.5 (10.0–11.0)
12.9 (11.6–14.3)
.002
15.3 (14.7–16.0)
16.7 (15.4–18.1)
.040
3.6 (3.4–3.8)
3.5 (3.1–4.0)
.600
9.8 (9.3–10.4)
11.5 (10.3–12.7)
.020
3.7 (3.5–3.8)
3.7 (3.4–4.0)
.900
1.9 (1.8–1.9)
1.9 (1.8–2.0)
.700
1.5 (1.4–1.6)
1.4 (1.4–1.6)
.200
Note: CI ⫽ 95% confidence interval; statistical test ⫽ Mann-Whitney. ⫽ Mean. b Excluding nonconsumers. a
Hassan. Lifestyle and fecundity. Fertil Steril 2004.
proportions of various subgroups for each of the lifestyle variables. Subfecund couples were those who had TTP ⬎12 months. Differences in the individual and lifestyle variables between fecund and subfecund couples were evaluated using the Mann-Whitney U-test. Each variable was correlated to TTP using Spearman’s correlation coefficient, then subgrouped. The mean TTP of subgroups of each variable were compared before and after adjustment for the potential confounders in a general linear model using univariate analysis. The conception rates of these subgroups were determined, and the relative risk (RR) of taking TTP ⬎12 or ⬎24 months was calculated before and after adjustment using binary logistic regression. The TTP, conception rates, and RR of subfecundity for groups with different numbers of negative lifestyle variables were compared to study the absolute effect of negative lifestyle on fecundity. Variables in the regression models included women’s age, weight, parity, smoking, alcohol consumption, coffee intake, menstrual pattern, contraceptive use, and also their partners’ age, smoking, alcohol consumption, and the couples’ coital frequency and living standard.
RESULTS Of the 2112 consecutive pregnant women surveyed, 136 women did not report TTP. Of the remaining 1976, 1128 385
TABLE 2 Effect of lifestyle variables on time to pregnancy (TTP). Unadjusted TTP (months) Variable Women’s smoking (cigarette/d)
Men’s smoking (cigarette/d)
Women’s alcohol (unit/wk)
Men’s alcohol (unit/wk)
Women’s tea and coffee (cup/d) Women’s obesity (BMI)
Living standard Recreational drug use Coital frequency
Number of negative lifestyle variables
Groups
(CI)a
None Light (ⱕ15) Heavy (⬎15) None Light (ⱕ15) Heavy (⬎15) None Mild (ⱕ20) Heavy (⬎20) None Mild (ⱕ20) Heavy (⬎20) Mild (⬍7) Heavy (ⱖ7) ⬍19 kg/m2 19–24 kg/m2 25–39 kg/m2 ⬎39 kg/m2 High standard Low standard Never Previous/current Once or less/week 2–4 times/week ⱖ5 times/week None One Two Three Four Five or more
9.3 (8.6–10.1) 9.8 (8.3–11.2) 17.4 (14.2–20.6) 9.6 (8.7–10.4) 9.0 (7.6–10.5) 11.7 (10.0–13.4) 8.7 (8.0–9.5) 7.6 (6.8–8.5) — 10.0 (8.5–11.4) 9.4 (8.6–10.2) 18.6 (15.7–21.3) 8.1 (7.5–8.7) 10.3 (8.3–12.2) 29.0 (18.5–39.5) 6.8 (5.5–8.1) 10.6 (9.8–11.4) 13.3 (8.3–18.4) 7.1 (5.6–8.7) 10.7 (9.8–11.5) 8.5 (7.9–9.1) 11.0 (3.6–18.4) 9.2 (8.0–10.4) 10.0 (9.2–10.9) 9.1 (7.1–11.0) 3.4 (0.2–6.6) 5.7 (4.4–7.1) 8.5 (7.2–9.8) 12.7 (10.9–14.4) 15.1 (12.4–17.8) 25.0 (16.3–33.7)
Statistical test F ⫽ 12.0 (P ⬍.001) F ⫽ 3.1 (P ⫽ .045) F ⫽ 3.4 (P ⫽ .07) F ⫽ 17.8 (P ⬍.001) F ⫽ 4.2 (P ⫽ .04) F ⫽ 13.1 (P ⬍.001) F ⫽ 14.6 (P ⬍.001) F ⫽ 0.4 (P ⫽ .5) F ⫽ 0.9 (P ⫽ .4) F ⫽ 17.0 (P ⬍.001)
Adjusted TTPb (months) (CI)a 9.1 (8.2–9.9) 11.1 (9.4–12.9) 18.7 (14.9–22.4) 9.2 (8.2–10.1) 11.2 (9.6–12.8) 10.8 (8.8–12.7) 9.3 (8.4–10.2) 7.6 (6.7–8.6) — 9.3 (7.7–11.0) 9.6 (8.8–10.5) 16.7 (13.2–20.2) 8.4 (7.7–9.1) 10.4 (8.1–12.8) 25.5 (15.1–35.9) 6.9 (5.5–8.4) 10.9 (10.0–11.7) 14.0 (8.8–19.3) 6.8 (5.0–8.5) 11.0 (10.0–11.9) 8.5 (7.9–9.2) 8.1 (0.3–15.9) 9.2 (7.9–10.6) 10.1 (9.1–11.0) 10.3 (8.2–12.5) 2.9 (0.0–6.3) 6.0 (4.4–7.6) 8.5 (7.2–9.7) 11.8 (9.9–13.7) 15.3 (11.8–18.7) 21.1 (12.0–30.3)
Statistical test F ⫽ 12.2 (P ⬍.001) F ⫽ 2.6 (P ⫽ .08) F ⫽ 2.3 (P ⫽ .08) F ⫽ 7.8 (P ⬍.001) F ⫽ 2.5 (P ⫽ .1) F ⫽ 10.5 (P ⬍.001) F ⫽ 16.5 (P ⬍.001) F ⫽ 0.1 (P ⫽ .9) F ⫽ 0.6 (P ⫽ .6) F ⫽ 6.5 (P ⬍.001)
Note: CI ⫽ 95% Confidence Interval; F ⫽ analysis of variance. a Mean. b Factors in the model: women’s age, weight, smoking, alcohol consumption, tea/coffee intake, drug abuse, parity, contraceptive use, and menstrual pattern, and men’s age, smoking, alcohol consumption, drug abuse, coital frequency, and living standard. Hassan. Lifestyle and fecundity. Fertil Steril 2004.
(57.1%) conceived within 3 months, a number that rose to 1604 (81.2%) by end of the first year. Of the 372 (18.8%) subfecund couples, 190 (9.6%) conceived in the second year. The subfecund women and their partners were significantly older (P ⬍.001), more obese (P ⬍.001), smoked more cigarettes (P ⫽ .002 and .04), consumed more alcohol (P ⫽.6 and .02), had longer contraceptive use (P ⬍.001); their recreational drug use and coital frequency were not significantly different when compared with fecund couples (Table 1).
Women and Men’s Smoking Of the couples surveyed, 72.6% of the women and 59.5% of the partners were nonsmokers, while 4.2% and 17.4%, respectively, used to smoke ⬎15 cigarettes/day. A statistically significant reduction in fecundity occurred with heavy but not with light smoking (Fig. 1A, B). Heavy smokers 386
Hassan et al.
Lifestyle and fecundity
(⬎15 cigarettes/day) among women had a twofold longer TTP (P ⬍.001), while the TTP of light smokers was not significantly different from that of nonsmokers. The effect of women’s heavy smoking remained statistically significant; men’s heavy smoking became insignificant after adjustment for the potential confounders (Table 2). Heavy smokers were more likely to be subfecund than nonsmokers; RR (95% CI) ⫽ 1.9 (1.4 –2.6) in women and 1.4 (1.1–1.8) in men (3.6 [1.9 –7.1], 1.4 [0.9 –2.1] after adjustment), while the conception rate within 12 months for light smokers was not different from that for nonsmokers (Table 3).
Women and Men’s Alcohol Consumption Of the survey participants, 58.2% of the women and 23.8% of their partners did not consume alcohol or had Vol. 81, No. 2, February 2004
FIGURE 1 Effect of each of the lifestyle variables on fecundity, expressed as time to pregnancy (TTP) in months. The values in each figure represent the mean TTP for each of the subgroups of the lifestyle variables, and the error bars represent the standard error of the mean. (A) Women’s smoking and (B) men’s smoking. The number of cigarettes/day smoked by women and their partners, respectively, were (I) nonsmokers, (II) ⱕ5, (III) 6 –10, (IV) 11–15, (V) 16 –20, and (VI) ⬎20. (P values are ⬍.001 and .05, respectively.) (C) Women’s alcohol consumption and (D) men’s alcohol consumption. The amounts of alcohol in units/week consumed by women and their partners, respectively, were: (I) nonconsumers, (II) ⱕ5, (III) 6 –10, (IV) 11–15, (V) 16 –20, and (VI) ⬎20. (P values are .05 and .009, respectively.) (E) Women’s coffee and tea intake. The amount of women’s coffee and tea per day in cups/day was: (I) nonconsumers, (II) ⱕ5, (III) 6 –10, (IV) 11–15, (V) 16 –20, and (VI) ⬎20. (P ⫽ .01.) (F) Women’s obesity presented by BMI. Women’s BMI in kg/m2 were: (I) ⬍19, (II) 19 –24, (III) 25–29, (IV) 30 –34, (V) 35–39, and (VI) ⬎39. (P ⬍ .001.)
Hassan. Lifestyle and fecundity. Fertil Steril 2004.
stopped drinking before trying for pregnancy; 12.0% of the partners but none of the women used to consume ⬎20 units/week. Heavy men’s alcohol consumption (⬎20 unit/ week) was associated with a significant reduction in fecundity (twofold longer TTP, P ⬍.001), but no similar effect was detected with women’s alcohol consumption as, in this sample, the amount they used to consume did not exceed 15 units/week (see Fig. 1C, D). Moderate alcohol consumption, FERTILITY & STERILITY威
neither in women nor in their partners, was found to have an effect on TTP compared with nonconsumers. Similar results were obtained after adjustment (see Table 2). Heavy men’s alcohol consumption was associated with a higher likelihood of subfecundity RR ⫽ 1.9 (1.3–2.7) (after adjustment ⫽ 2.2 [1.1– 4.4]). The pregnancy rates in association with moderate women or men’s alcohol consumption were not significantly different from the rates of nonconsumers (see Table 3). 387
TABLE 3 Relative risk of subfecundity for various subgroups of lifestyle variables. Relative risk of subfecundity (TTP ⬎12 months) Adjustedb
Unadjusted Variables Women’s smoking (cigarette/d)
Men’s smoking (cigarette/d)
Women’s alcohol (unit/wk)
Men’s alcohol (unit/wk)
Women’s coffee and tea (cup/d) Women’s BMI
Living standard Recreational drug use Coital frequency
Number of negative lifestyle variables
Groups
%
RR (CI)a
None Light (ⱕ15) Heavy (⬎15) None Light (ⱕ15) Heavy (⬎15) None Mild (ⱕ20) Heavy (⬎20) None Mild (ⱕ20) Heavy (⬎20) Mild (⬍7) Heavy (ⱕ7) ⬍19 kg/m2 19–24 kg/m2 25–39 kg/m2 ⬎39 kg/m2 High standard Low standard Never Previous/current ⱕ1/week 2–4 time/week ⱖ5 time/week None One Two Three Four Five or more
21.0 23.3 40.0 21.2 19.6 29.5 20.0 17.4 — 17.8 19.5 33.3 18.2 27.1 40.0 11.4 21.1 42.9 17.6 24.3 19.2 33.3 19.8 23.7 18.1 6.9 13.4 20.4 29.0 36.6 50.0
1.0 1.1 (0.9–1.4) 1.9 (1.4–2.6) 1.0 0.9 (0.7–1.2) 1.4 (1.1–1.8) 1.0 0.9 (0.7–1.1) — 1.0 1.1 (0.9–1.4) 1.9 (1.3–2.7) 1.0 1.5 (1.1–1.9) 3.5 (1.6–7.8) 1.0 1.9 (1.4–2.4) 3.8 (2.3–6.2) 1.0 1.4 (1.1–1.8) 1.0 1.7 (0.8–3.9) 1.0 1.2 (1.0–1.5) 0.9 (0.6–1.3) 1.0 1.9 (0.7–5.2) 3.0 (1.1–7.8) 4.2 (1.6–11.1) 5.3 (2.0–14.2) 7.3 (2.2–23.4)
P value
.400 .001 .600 .008 .200
.500 .001 .007 .020 ⬍.001 ⬍.001 .025 .300 .100 .700 .200 .010 ⬍.001 ⬍.001 .005
RR (CI)a 1.0 1.5 (1.1–2.2) 3.6 (1.9–7.1) 1.0 1.2 (0.8–1.7) 1.4 (0.9–2.1) 1.0 0.8 (0.6–1.0) — 1.0 1.3 (0.9–1.9) 2.2 (1.1–4.4) 1.0 1.7 (1.1–2.7) 4.8 (1.2–19.7) 1.0 2.2 (1.6–3.2) 6.9 (2.9–16.8) 1.0 1.6 (1.1–2.3) 1.0 1.6 (0.3–7.8) 1.0 1.2 (0.8–1.6) 1.0 (0.6–1.7) 1.0 2.2 (0.7–6.4) 3.3 (1.1–9.6) 4.4 (1.4–13.6) 6.5 (1.8–23.7) 7.2 (1.1–49.7)
P value
.0400 .0001 .4000 .0900 .0900
.2000 .0300 .0200 .0300 ⬍.0001 ⬍.0001 .0300 .6000 .4000 .9000 .2000 .0300 .0100 .0040 .0400
RR ⫽ relative risk; CI ⫽ 95% confidence interval; test ⫽ binary logistic regression. Factors in the model: women’s age, weight, smoking, alcohol consumption, tea/coffee intake, drug abuse, parity, contraceptive use, and menstrual pattern, and men’s age, smoking, alcohol consumption, drug abuse, coital frequency, and living standard.
a
b
Hassan. Lifestyle and fecundity. Fertil Steril 2004.
Women’s Tea and Coffee Intake Although 10.7% of the women did not drink tea or coffee, 19.1% consumed ⬎5 cups/day. A longer TTP with heavy coffee or tea intake (P ⫽.04) became insignificant after adjustment (see Fig. 1E, Table 1). Women who used to consume seven or more cups of tea or coffee/day were 1.5-fold (1.1–1.9) more likely to be subfecund (1.7 [1.1–2.7] after adjustment).
Women’s Obesity Among those surveyed, 2.6% of all women had a body mass index (BMI) ⬍19 kg/m2, and 17.9% had a BMI ⬎30 kg/m2 before pregnancy. The effect of body mass on fecundity appeared to be bimodal. Underweight women (BMI ⬍19 kg/m2) had a fourfold longer TTP than that of the 388
Hassan et al.
Lifestyle and fecundity
women who had a normal BMI (19 to 24 kg/m2). Women who had a prepregnancy weight ⬎80 kg or BMI ⬎25 kg/m2 took twofold longer TTP (P ⬍.001) (see Fig. 1F). The effects remained unchanged after adjustment for the other lifestyle variables, the woman’s age, and the menstrual pattern (see Table 2). Underweight women were 3.5-fold (1.6 – 7.8) and morbidly obese women were 3.8-fold (2.3– 6.2) more likely to be subfecund than those who had a normal BMI (4.8 [1.2–19.7] and 6.9 [2.9 –16.8] after adjustment, respectively) (see Table 3).
Living Standard The IMD score revealed that 22.1% of the couples had a deprivation score ⬍20 (high standard), and 21.2% had a score ⬎60 (low standard). Socially deprived couples took Vol. 81, No. 2, February 2004
significantly longer TTP (P ⬍.001) and were more likely to be subfecund (RR [CI] ⫽ 1.4 [1.1–1.8] before, and 1.6 [1.1–2.3] after adjustment) than those who had high living standard (see Tables 2 and 3).
Recreational Drug Use Only 3.0% of the women admitted previous or current drug use, and only 0.7% reported knowledge of their partner’s previous or current use. Recreational drug use, in this sample, was not found to be associated with a statistically significant effect on TTP or the subfecund proportions, compared with those of individuals who had never used recreational drugs (see Tables 2 and 3).
FIGURE 2 The absolute cumulative effect of increasing numbers of negative lifestyle variables on fecundity, expressed as time to pregnancy (TTP) in months. These variables include women’s smoking ⬎15 cigarettes/day, men’s smoking ⬎15 cigarettes/ day, men’s alcohol ⬎20 units/week, women’s coffee/tea intake ⱖ7 cups/day, women’s weight ⬎70 kg, social deprivation score ⬎60, women’s age ⬎35 years, and/or partners’ age ⬎45 years at the time of discontinuing contraception. The bold values represent the mean TTP for subgroups with increasing numbers of the negative lifestyle variables, and the error bars represent the standard error of the mean. The dashed lines point to the subgroups between which the shown P values were calculated.
Coital Frequency Infrequent intercourse was reported by 10.9% of the couples (less than once/week), and 12.2% reported frequent intercourse (five times or more/week). No statistically significant affect on TTP or conception rate was found for coital frequency in this sample (see Tables 2 and 3).
Absolute Effect of Negative Lifestyle The negative lifestyle variables were women’s heavy smoking, men’s heavy smoking (⬎15 cigarettes/day), heavy alcohol consumption (⬎20 units/week), heavy tea or coffee intake (⬎6 cups/day), prepregnancy BMI ⬎25 kg/m2, social deprivation (score ⬎60), and women’s age ⬎35 or men’s age ⬎45 years at the time of discontinuing contraception. Among those surveyed, 5.7% of the couples had none of these variables, 31.9% had one, 36.1% had two, 18.1% had three, and 8.2% had four or more variables. The increase in the number of the negative lifestyle variables was persistently associated with a significant and progressive reduction in fecundity. The mean TTP increased 2.5-fold with two variables, 3.7-fold with three variables, and 4.4-fold with four variables. Couples who had more than four negative variables had a 7.3-fold longer TTP than those who had no negative variables (Fig. 2; see Table 2). There was a statistically significant progressive decline in the conception rates within 6 and 12 months with the rise in numbers of negative lifestyle variables (Fig. 3). The conception probabilities, within 6 months, were found to fall from 0.9 with one variable to 0.77 with two, 0.48 with three down to 0.45 with four variables, and no pregnancies were achieved within 6 months in association with five or more variables. The conception probabilities within 12 months fell from 0.93 with one variable to 0.82 with two, 0.67 with three, down to 0.38 in association with four negative variables. Compared with the couples who had no negative variables, the RR (CI) of subfecundity rose from 1.9 (0.7–5.2) with one variable to 3.0 (1.1–7.8) with two, 4.2 (1.6 –11.1) with three, 5.3 (2.0 – 14.2) with four, up to 7.3 (2.2–23.4) in association with five or more negative variables (2.2 [0.7– 6.4], 3.3 [1.1–9.6], 4.4 [1.4 –13.6], 6.5 [1.8 –23.7], 7.2 [1.1– 49.7] after adjustment, respectively) (see Table 3). FERTILITY & STERILITY威
Hassan. Lifestyle and fecundity. Fertil Steril 2004.
DISCUSSION The methodology of this study has been previously discussed elsewhere (16). Using time to a current pregnancy excluded from the analysis those who had failed to conceive or had given up the pregnancy attempt (17–19). However, such selective sampling is not expected to have a significant effect on the results or conclusions, as lifestyle variables are not expected to lead to absolute sterility. In addition, an underestimation rather than overestimation of the negative effect, of the negative lifestyle, on fecundity would result from excluding the small minority who gave up the pregnancy attempt (20). The effect of negative lifestyle on fecundity was similar in planned and unplanned pregnancies. Furthermore, studies comparing the effects of exposures on TTP among pregnancy planners with those in current pregnancies have shown similar results (21). Data analysis aimed not only to detect but also to quantify the relative and absolute effects of lifestyle factors on fecundity. This was achieved in two ways; by comparing the mean TTP, then by comparing the conception rates and calculating the RR of subfecundity for various subgroups of each life389
FIGURE 3 The effect of increasing numbers of negative lifestyle variables on the cumulative conception rates within 1 year for a pregnant population. These variables include women’s smoking ⬎15 cigarettes/day, men’s smoking ⬎15 cigarettes/day, men’s alcohol ⬎20 units/week, women’s coffee or tea intake ⬎7 cups/day, women’s weight ⬎70 kg, social deprivation score ⬎60, women’s age ⬎35 years, and/or partners’ age ⬎45 years at the time of discontinuing contraception. The lines represent the cumulative conception rates for subgroups with different numbers of negative lifestyle variables as follows: E No negative variables; ■ One negative variable; ⫻ Two negative variables; ‚ Three negative variables; } Four or more negative variables.
Hassan. Lifestyle and fecundity. Fertil Steril 2004.
style factor and for groups with different numbers of the negative lifestyle factors. General linear and logistic regression models were used to control for confounders to assess the effect of each of the lifestyle variables independently. The harmful effects of smoking and heavy alcohol drinking on the general health are well accepted. Several studies have shown the negative effects of smoking (22–31) and alcohol consumption (32–34) on fertility. Smoking has been shown to affect gamete quality (35–39), impair fertilization (13, 40), or result in early miscarriage. The effect of alcohol consumption on fertility has been suggested to be related to hormonal and ovulatory abnormalities (41). Couples who are trying for pregnancy are usually advised to give up smoking and stop drinking, but this advice may be difficult or even impossible for some couples to follow, which may add more stress and strain to an already threatened relationship and further jeopardize their chances of conception (42– 44). It is 390
Hassan et al.
Lifestyle and fecundity
important, therefore, to quantify and base the advice given on clear evidence. Based on the above results, the effects of smoking and alcohol consumption on fecundity appear to be dosedependent. A significant negative effect was demonstrated only with heavy smoking (⬎15 cigarettes/day, women or men). Light smoking has not been found to affect TTP or the conception probabilities compared with nonsmoking. The effect of women’s alcohol consumption on fecundity in this sample was insignificant. This may be due to the relatively small amount they consumed. The effect of the male partner’s alcohol consumption on fecundity was only significant when the amount consumed exceeded 20 units/week; a smaller amount has not been shown to have a statistically significant effect. The absence of a statistically significant effect in association with moderate alcohol consumption is consistent with the results of other studies (45, 46). The Vol. 81, No. 2, February 2004
negative effect of heavy caffeine intake is also consistent with the results of other studies (47–50). The effect of body mass on fecundity was bimodal. Sporadic ovulation in underweight women is not unexpected, and this would explain the statistically significant reduction in fecundity of these women. A statistically significant negative effect of women’s obesity on fecundity was demonstrated. This effect was independent of other lifestyle variables, the women’s age, and the menstrual pattern, and was similar whether the absolute weight or BMI was used in the analysis. The effect of obesity on fertility might be a direct effect (51–53); be caused by disturbance in leptin (54 –57), an important factor for both body fat mass regulation and reproductive function; or be the result of polycystic ovary syndrome (58, 59), a prevalent condition among obese women. In these cases, weight loss has been shown to improve both the chances of spontaneous conception and the success of fertility treatments (60 – 63). In this sample, the statistically insignificant effect of recreational drug use on fecundity is probably a result of the tiny proportion that admitted having ever used drugs. Other studies have demonstrated a negative effect (64). Also, results from this study, in agreement with other studies (65, 66), are not supportive of the belief that frequent or timed intercourse enhances fecundity. These provide an evidencebased answer to a question commonly asked by couples striving for pregnancy. The detrimental effect on fecundity of social deprivation (as identified by using the IMD) could not be attributed to other lifestyle variables as it remained statistically significant after adjustment. Residence in more deprived areas is associated with personal disadvantage (67), but the mechanism by which social deprivation affects fertility is unclear. Further research is obviously needed. Increasingly in recent decades, couples, especially those with career ambitions, choose to delay having children until later age (68). Therefore, trying for a pregnancy at women’s age of 35 years or more and/or men’s age of 45 years or more was considered among the negative lifestyle factors. About two-thirds of the couples in this sample had two or more negative lifestyle variables, and the results of this study indicate that the detrimental effect of negative lifestyle factors on fecundity is cumulative. The TTP was progressively longer (2.4-fold with two, up to 7.3-fold with five or more variables) and the conception probabilities were persistently lower (0.82 with two, down to 0.38 with four variables) with increased numbers of negative lifestyle variables. Couples who had five or more negative variables were 7.3-fold more likely to be subfecund compared with those without any of these variables. Subfertile couples who are seeking medical intervention often disregard lifestyle factors as having adverse effects on fertility (69). Promoting a healthier lifestyle among the couFERTILITY & STERILITY威
ples planning or trying for pregnancy is important not only for their general health but also for prevention of subfertility, as evident from the data in our study. Primary health care providers are in a unique position to provide education, counseling, and support to these couples (70). Based on our results, should these couples lead a healthy lifestyle, a reduction in subfecundity by over half would result. This, in the long term, could lead to a substantial decline in the referrals for medical investigations and fertility treatments. References 1. Bongaarts J. A method for the estimation of fecundability. Demography 1975;12:645–60. 2. ESHRE Capri workshop. Guidelines to the prevalence, diagnosis, treatment and management of infertility. Hum Reprod 1996;11:1775–807. 3. Hull MGR, Glazener CMA, Kelly NJ, Conway DI, Foster PA, Hinton RA, et al. Population study of causes, treatment, and outcome of infertility. BMJ 1985;291:1693–7. 4. Templeton A. Infertility-epidemiology, aetiology and effective management. Health Bull 1995;53:294 –8. 5. Hull MGR. Infertility treatment: relative effectiveness of conventional and assisted conception methods. Hum Reprod 1992;7:785–96. 6. Van Noord-Zaadstra BM, Looman CW, Alsbach H, Habbema JD, te Velde ER, Karbaat J. Delaying childbearing: effect of age on fecundity and outcome of pregnancy. BMJ 1991;302:1361–5. 7. Kidd SA, Eskenazi B, Wyrobek AJ. Effects of male age on semen quality and fertility: a review of the literature. Fertil Steril 2001;75: 237–48. 8. Howe G, Westhoff C, Vessey M, Yeates D. Effects of age, cigarette smoking, and other factors on fertility: findings in a large prospective study. BMJ 1985;290:1697–700. 9. Feichtinger W. Environmental factors and fertility. Hum Reprod 1991; 6:1170 –5. 10. Bolumer F, Olsen J, Rebagliato M, Saez-Lloret I, Bisanti L. Body mass index and delayed conception: a European multicentre study on infertility and subfecundity. Am J Epidemiol 2000;151:1072–9. 11. Chia SE, Lim ST, Tay SK, Lim ST. Factors associated with male infertility: a case-control study of 218 infertile and 240 fertile men. Br J Obstet Gynaecol 2000;107:55–61. 12. Clark AM, Thornley B, Tomlinson L, Galletley C, Norman RJ. Weight loss in obese infertile women results in improvement in reproductive outcome for all forms of fertility treatment. Hum Reprod 1998;13: 1502–5. 13. Rosevear SK, Holt DW, Lee TD, Ford WC, Wardle PG, Hull MG. Smoking and decreased fertilisation rates in vitro. Lancet 1992;340: 1195–6. 14. Templeton A, Fraser C, Thompson B. Infertility-epidemiology and referral practice. Hum Reprod 1991;6:1391–4. 15. Noble M, Penhale B, Smith G, Wright G, Dibben C, Owen T, et al. Indices of deprivation 2000. London: Department of the Environment, Transport and the Regions (DETR), 2000. 16. Hassan MAM, Killick S. Evidence for the decline in male fertility with increasing age. Fertil Steril 2003;79(Suppl 3):1520 –7. 17. Basso O, Juul S, Olsen J. Time to pregnancy as a correlate of fecundity: differential persistence in trying to become pregnant as a source of bias. Int J Epidemiol 2000;29:856 –61. 18. Jensen TK, Scheike T, Keiding N, Schaumburg I, Grandjean P. Selection bias in determining the age dependence of waiting time to pregnancy. Am J Epidemiol 2000;152:565–72. 19. Juul S, Keiding N, Tvede M. Retrospectively sampled time to pregnancy data may make age-decreasing fecundity look increasing. European Infertility and Subfecundity Group. Epidemiology 2000;11:717–9. 20. Olsen J, Juul S, Basso O. Measuring time to pregnancy: methodological issues to consider. Hum Reprod 1998;13:1751–6. 21. Bolumar F, Olsen J, Boldsen J. Smoking reduces the biological capacity of conception. Results from a European multicenter study. The European Study Group on Infertility and Subfecundity. Ugeskr Laeger 1997;159:4526 –32. 22. Baird DD, Wilcox AJ. Cigarette smoking associated with delayed conception. JAMA 1985;253:2979 –83. 23. Weinberg CR, Wilcox AJ, Baird DD. Reduced fecundability in women with prenatal exposure to cigarette smoking. Am J Epidemiol 1989; 129:1072–8. 24. Suonio S, Saarikoski S, Kauhanen O, Metsapelto A, Terho J, Vohlonen I. Smoking does affect fecundity. Eur J Obstet Gynecol Reprod Biol 1990;34:89 –95.
391
25. Joesoef MR, Beral V, Aral SO, Rolfs RT, Cramer DW. Fertility and use of cigarettes, alcohol, marijuana, and cocaine. Ann Epidemiol 1994;4: 423. 26. Alderete E, Eskenazi B, Sholtz R. Effect of cigarette smoking and coffee drinking on time to conception. Epidemiology 1995;6:403–8. 27. Hughes EG, Brennan BG. Does cigarette smoking impair natural or assisted fecundity? Fertil Steril 1996;66:679 –89. 28. Vine MF. Smoking and male reproduction: a review. Int J Androl 1996;19:323–37. 29. Bolumar F, Olsen J, Boldsen J. Smoking reduces fecundity: a European multicenter study on infertility and subfecundity. The European Study Group on Infertility and Subfecundity. Am J Epidemiol 1996;143:578 – 87. 30. Curtis KM, Savitz DA, Arcbukle TE. Effects of cigarette smoking, caffeine consumption, and alcohol intake on fecundability. Am J Epidemiol 1997;146:32–41. 31. Augood C, Duckitt K, Templeton AA. Smoking and female infertility: a systematic review and meta-analysis. Hum Reprod 1998;13:1532–9. 32. Grodstein F, Goldman MB, Cramer DW. Infertility in women and moderate alcohol use. Am J Public Health 1994;84:1429 –32. 33. Hakim RB, Gray RH, Zacur H. Alcohol and caffeine consumption and decreased fertility. Fertil Steril 1998;70:632–7. 34. Jensen TK, Hjollund NH, Henriksen TB, Scheike T, Kolstad H, Giwercman A, et al. Does moderate alcohol consumption affect fertility? Follow up study among couples planning first pregnancy. BMJ 1998; 317:505–10. 35. Weisberg E. Smoking and reproductive health. Clin Reprod Fertil 1985;3:175–86. 36. Vine MF, Tse CK, Hu P, Truong KY. Cigarette smoking and semen quality. Fertil Steril 1996;65:835–42. 37. Rubes J, Lowe X, Moore D 2nd, Perreault S, Slott V, Evenson D, et al. Smoking cigarettes is associated with increased sperm disomy in teenage men. Fertil Steril 1998;70:715–23. 38. Wong WY, Thomas CM, Merkus HM, Zielhuis GA, Doesburg WH, Steegers-Theunissen RP. Cigarette smoking and the risk of male factor subfertility: minor association between cotinine in seminal plasma and semen morphology. Fertil Steril 2000;74:930 –5. 39. Zenzes MT, Wang P, Casper RF. Cigarette smoking may affect meiotic mutation of human oocytes. Hum Reprod 1995;10:3213–17. 40. Weigert M, Hofstetter G, Kaipl D, Gottlich H, Krischker U, Bichler K, et al. The effect of smoking on oocyte quality and hormonal parameters of patients undergoing in vitro fertilization-embryo transfer. J Assist Reprod Genet 1999;16:287–93. 41. Gill J. The effects of moderate alcohol consumption on female hormone levels and reproductive function. Alcohol Alcohol 2000;35:417–23. 42. Hjollund NH, Jensen TK, Bonde JP, Henriksen TB, Andersson AM, Kolstad HA, et al. Distress and reduced fertility: a follow up study of first-pregnancy planners. Fertil Steril 1999;72:47–53. 43. Stoleru S, Teglas JP, Fermanian J, Spira A. Psychological factors in the aetiology of infertility: a prospective cohort study. Hum Reprod 1993; 8:1039 –46. 44. Sanders KA, Bruce NW. A prospective study of psychological stress and fertility in women. Hum Reprod 1997;12:2324 –9. 45. Zaadstra B. M, Looman CW, te Velede ER, Habbema JD, Karbaat J. Moderate drinking: no impact on female fecundity. Fertil Steril 1994; 62:948 –54. 46. Folrack EI, Zielhuis GA, Rolland R. Cigarette smoking, alcohol consumption and caffeine intake and fecundability. Prev Med 1994;23: 175–80. 47. Wilcox A, Weinberg C, Baird D. Caffeinated beverages and decreased fertility. Lancet 1988;2:1453–6. 48. Olsen J. Cigarette smoking, tea and coffee drinking and subfecundity. Am J Epidemiol 1991;133:734 –9.
392
Hassan et al.
Lifestyle and fecundity
49. Bolumar F, Olsen J, Rebagliato M, Bisanti L. Caffeine intake and delayed conception: a European multicenter study on infertility and subfecundity. Am J Epidemiol 1997;145:324 –34. 50. Jensen TK, Henriksen TB, Hjollund NH, Scheike T, Kolstad H, Giwercman A, et al. Caffeine intake and fecundability: a follow up study among 430 Danish couples planning their first pregnancy. Reprod Toxicol 1998;12:289 –95. 51. Zaadstra BM, Seidell JC, Van Noord PA, te Velde ER, Habbema JD, Vrieswijk B, et al. Fat and female fecundity: prospective study of effect of body fat distribution on conception rates. BMJ 1993;306:484 –7. 52. Jarow JP, Kirkland J, Koritnik DR, Cefalu WT. Effect of obesity and fertility status on sex steroid levels in men. Urology 1993;42:171–4. 53. Foreyt JP, Poston WS 2nd. Obesity: a never-ending cycle? Int J Fertil Wom Med 1998;43:111–6. 54. Messinis IE, Milingos SD. Leptin in human reproduction. Hum Reprod Update 1999;5:52–63. 55. Magni P, Motta M, Martini L. Leptin: a possible link between food intake, energy expenditure, and reproductive function. Regul Pept 2000;92:51–6. 56. Alfer J, Muller-Schottle F, Classen-linke I, von Rango U, Happel L, Beier-Hellwig K, et al. The endometrium as a novel target for leptin: differences in fertility and subfertility. Mol Hum Reprod 2000;6:595– 601. 57. Imani B, Eijkemans MJ, de Jong FH, Payne NN, Bouchard P, Giudice LC, et al. Free androgen index and leptin are the most prominent endocrine predictors of ovarian response during clomiphene citrate induction of ovulation in normogonadotropic oligoamenorrheic infertility. J Clin Endocrinol Metab 2000;85:676 –82. 58. Franks S, Kiddy D, Sharp P, Singh A, Reed M, Seppala M, et al. Obesity and polycystic ovary syndrome. Ann NY Acad Sci 1991;626: 201–6. 59. Pettigrew R, Hamilton-Fairley D. Obesity and female reproductive function. Br Med Bull 1997;53:341–58. 60. Kiddy DS, Hamilton-Fairley D, Bush A, Short F, Anyaoku V, Reed MJ, et al. Improvement in endocrine and ovarian function during dietary treatment of obese women with polycystic ovary syndrome. Clin Endocrinol 1992;36:105–11. 61. Pasquali R, Casimirri F, Vicennati V. Weight control and its beneficial effect on fertility in women with obesity and polycystic ovary syndrome. Hum Reprod 1997;12:82–7. 62. Norman RJ, Clark AM. Obesity and reproductive disorders: a review. Reprod Fertil Dev 1998;10:55–63. 63. Kably-Ambe A, Barron-Vallejo J, Limon-Luque LM. Effect of body mass index and follicular synchrony in the ovarian response to ovulation induction with menotropins. Int J Fertil Wom Med 1999;44:156 –9. 64. Mueller BA, Daling JR, Weiss NS, Moore DE. Recreational drug use and the risk of primary infertility. Epidemiology 1990;1:189 –92. 65. Agarwal SK, Haney AF. Does recommending timed intercourse really help the infertile couple? Obstet Gynecol 1994;84:307–10. 66. Tur-Kaspa I, Maor Y, Levran D, Yonish M, Mashiach S, Dor J. How often should infertile men have intercourse? Fertil Steril 1994;62: 370 –5. 67. Sloggett A, Joshi H. Deprivation indicators as predictors of life events 1981–1992 based on the UK ONS Longitudinal Study. J Epidemiol Community Health 1998;52:228 –33. 68. Martin SP. Diverging fertility among U.S. women who delay childbearing past age 30. Demography 2000;37:523–33. 69. Olatunbosun OA, Edouard L, Pierson RA. How important is health promotion in the lifestyle of infertile couples? Clin Exp Obstet Gynecol 1997;24:183–6. 70. Whitman-Elia GF, Baxley EG. A primary care approach to the infertile couple. J Am Board Fam Pract 2001;14:33–45.
Vol. 81, No. 2, February 2004
Negative lifestyle is associated with a significant reduction in fecundity Mohamed A. M. Hassan, M.Sc., and Stephen R. Killick, M.D. The University of Hull, Postgraduate Medical Institute, Hull and York Medical School, Academic Department of Obstetrics and Gynaecology, Women’s and Children’s Hospital, Hull Royal Infirmary, Hull, United Kingdom
Objective: To evaluate the association patterns and quantify the effects of lifestyle on time to pregnancy (TTP). Design: Observational study. Setting: Teaching hospitals in Hull, United Kingdom. Patient(s): Two thousand and one hundred twelve consecutive pregnant women. Intervention(s): A questionnaire inquiring about TTP, contraceptive use, pregnancy planning, previous subfertility/pregnancies, age, and lifestyle characteristics of either partner. Main Outcome Measure(s): We compared TTP, conception rates, and relative risk of subfecundity between subgroups with different lifestyle characteristics. Result(s): We found that TTP was significantly longer if the woman or partner smoked ⬎15 cigarettes/day (P⬍.001 and .04, respectively), the partner consumed ⬎20 alcohol units/week (P⬍.001), the woman’s body mass index was ⬎25 kg/m2 (P⬍.001), their coffee and/or tea intake was ⬎6 cups/day (P⫽.04), or if they were socially deprived (P⬍.001). Each of these effects remained unchanged after adjusting for the potential confounders. The relative-risks of subfecundity with each of these variables ranged between 1.4 to 1.9 (1.4 to 3.6 after adjustment). The effects of coital frequency and recreational drug use were insignificant. Couples who had ⬎4 negative lifestyle variables had a sevenfold longer TTP; their conception probabilities fell by 60%, and they were 7.3-fold more likely to be subfecund than those without negative variables. Conclusion(s): Lifestyle has a significant and cumulative impact on fecundity. Dose-dependent effects occur with smoking, alcohol, and tea/coffee consumption. Appropriate counseling could result in substantial reductions in the referrals for fertility investigations and treatments. (Fertil Steril威 2004;81:384 –92. ©2004 by American Society for Reproductive Medicine.) Key Words: Time to pregnancy, fecundity, fertility, lifestyle, age, obesity, smoking, alcohol, coffee, social deprivation
Received February 6, 2003; revised and accepted June 30, 2003. Presented at the XVII World Congress on Fertility and Sterility, Melbourne, Australia, November 25–30, 2001. Reprint requests: Mohamed A. M. Hassan, M.Sc., Women’s and Children’s Hospital, Hull Royal Infirmary, Anlaby Road, Hull HU3 2JZ, United Kingdom (FAX: 0044-1482-382781; E-mail: [email protected]). 0015-0282/04/$30.00 doi:10.1016/j.fertnstert.2003. 06.027
384
Half of the couples trying for a pregnancy succeed within 3 months, increasing to over 85% by end of the first year (1). An unsuccessful waiting time to pregnancy (TTP) despite frequent unprotected intercourse of ⬎12 months is usually used to define subfertility (2) and is commonly employed as an indication for commencing investigations (3). However, 30% of the subfertile couples have no identifiable medical cause, (4) and over 70% of these unexplained cases conceive within a further 24 months of trying without any medical intervention (5). Differences in the individual and lifestyle characteristics have been suggested to have a role, though poorly quantified, in the cause of subfertility (6 –11). If lifestyle variables could be modified, then this might assist
in the spontaneous achievement of pregnancy in cases of unexplained subfertility or in the success of fertility treatments (12, 13). Public expectation that medical treatment is increasingly possible and available leads to an ever increasing demand for the use of medical resources (14). Prevention, a main goal of the primary health care system, remains the most attractive and cost-effective approach to the majority of medical problems. Subfertility is no exception. Sound evidence-based advice given by general practitioners and through family planning clinics to couples planning for pregnancy could result, if the magnitude of the effects were great enough, in a substantial reduction in the referrals for medical investigation and in a consequent savings in resources.
The aim of this study was to evaluate the association patterns and to quantify the absolute and relative effects of lifestyle variables—including obesity, smoking, alcohol consumption, coffee and tea intake, recreational drug use, coital frequency, and standard of living— on fecundity, measured by the time interval of exposure to unprotected intercourse from the discontinuation of contraception until pregnancy (TTP).
MATERIALS AND METHODS A survey was conducted in Hull and East Yorkshire (September 2000 to May 2001). Consecutive women attending the antenatal clinics were asked to self-complete a questionnaire inquiring about TTP (the interval of exposure to unprotected intercourse from discontinuing birth control methods until conception), contraceptive use, pregnancy planning, previous fertility problems/pregnancies, gynecologic disease, and individual and lifestyle characteristics of either partner including their age, weight, height, smoking, alcohol consumption, coffee and tea intake, recreational drug use, and the couple’s coital frequency. Using the electoral ward, the postal code was linked to the Index of Multiple Deprivation (IMD), which was used as an indicator of the living standard. The IMD (15) is a compound index made up of six ward-level domain indices, each of which is composed of a number of indicators (33 in total) to describe aspects of this deprivation at a ward level as comprehensively as possible. These indices (contribution of each domain to the overall index) include: income (25%), employment (25%), education and training (15%), health deprivation and disability (15%), geographical access to services (10%), and housing (10%). The indicators measure deprivation independently of population size. The domain indices are also assigned a rank based on the electoral wards in England (8414), with the most deprived ward of each index given a rank of 1, and the least deprived ward given a rank of 8414. The IMD is ranked in the same way. The IMD score represents the combined sum of the weighted, exponentially transformed domain rank of the domain score. The bigger the IMD score, the more deprived the ward. The ranks show how a ward compares with all the other wards, whereas the scores indicate the distances between each rank position, as these will vary. Approval was obtained from the local research ethics committee (the UK equivalent of an institutional review board). There are no conflicts of interest. The response was over 99%, and the sample included 2112 completed questionnaires. Results of the component of the survey examining the effect of age on fecundity have already been published (16). Data analysis was carried out using a computer package (SPSS; SPSS, Inc., Chicago, IL). The outcome measures were the mean TTP, conception rates, and subfecundity FERTILITY & STERILITY威
TABLE 1 Differences in individual and lifestyle variables for fecund and subfecund couples. Variablea Women’s age (27.4 y) Men’s age (30.3 y) Women’s obesity: BMI (25.7 kg/m2) Women’s obesity: weight (69.1 kg) Women’s smokingb (11.1 cigarette/d) Men’s smokingb (15.6 cigarette/d) Women’s alcoholb (3.6 unit/wk) Men’s alcoholb (10.3 unit/wk) Women’s tea and coffee (3.7 cup/d) Coital frequency (1.9 times/wk) Previous pregnancies (1.5 pregnancies)
Fecund (CI)a
Subfecund (CI)a
P value
27.2 (26.9–27.4) 29.8 (29.5–30.1) 25.4 (25.2–25.7)
29.2 (28.6–29.7) 32.7 (32.0–33.4) 26.6 (26.1–27.1)
⬍.001 ⬍.001 ⬍.001
68.3 (67.6–69.0)
72.1 (70.6–73.6)
⬍.001
10.5 (10.0–11.0)
12.9 (11.6–14.3)
.002
15.3 (14.7–16.0)
16.7 (15.4–18.1)
.040
3.6 (3.4–3.8)
3.5 (3.1–4.0)
.600
9.8 (9.3–10.4)
11.5 (10.3–12.7)
.020
3.7 (3.5–3.8)
3.7 (3.4–4.0)
.900
1.9 (1.8–1.9)
1.9 (1.8–2.0)
.700
1.5 (1.4–1.6)
1.4 (1.4–1.6)
.200
Note: CI ⫽ 95% confidence interval; statistical test ⫽ Mann-Whitney. ⫽ Mean. b Excluding nonconsumers. a
Hassan. Lifestyle and fecundity. Fertil Steril 2004.
proportions of various subgroups for each of the lifestyle variables. Subfecund couples were those who had TTP ⬎12 months. Differences in the individual and lifestyle variables between fecund and subfecund couples were evaluated using the Mann-Whitney U-test. Each variable was correlated to TTP using Spearman’s correlation coefficient, then subgrouped. The mean TTP of subgroups of each variable were compared before and after adjustment for the potential confounders in a general linear model using univariate analysis. The conception rates of these subgroups were determined, and the relative risk (RR) of taking TTP ⬎12 or ⬎24 months was calculated before and after adjustment using binary logistic regression. The TTP, conception rates, and RR of subfecundity for groups with different numbers of negative lifestyle variables were compared to study the absolute effect of negative lifestyle on fecundity. Variables in the regression models included women’s age, weight, parity, smoking, alcohol consumption, coffee intake, menstrual pattern, contraceptive use, and also their partners’ age, smoking, alcohol consumption, and the couples’ coital frequency and living standard.
RESULTS Of the 2112 consecutive pregnant women surveyed, 136 women did not report TTP. Of the remaining 1976, 1128 385
TABLE 2 Effect of lifestyle variables on time to pregnancy (TTP). Unadjusted TTP (months) Variable Women’s smoking (cigarette/d)
Men’s smoking (cigarette/d)
Women’s alcohol (unit/wk)
Men’s alcohol (unit/wk)
Women’s tea and coffee (cup/d) Women’s obesity (BMI)
Living standard Recreational drug use Coital frequency
Number of negative lifestyle variables
Groups
(CI)a
None Light (ⱕ15) Heavy (⬎15) None Light (ⱕ15) Heavy (⬎15) None Mild (ⱕ20) Heavy (⬎20) None Mild (ⱕ20) Heavy (⬎20) Mild (⬍7) Heavy (ⱖ7) ⬍19 kg/m2 19–24 kg/m2 25–39 kg/m2 ⬎39 kg/m2 High standard Low standard Never Previous/current Once or less/week 2–4 times/week ⱖ5 times/week None One Two Three Four Five or more
9.3 (8.6–10.1) 9.8 (8.3–11.2) 17.4 (14.2–20.6) 9.6 (8.7–10.4) 9.0 (7.6–10.5) 11.7 (10.0–13.4) 8.7 (8.0–9.5) 7.6 (6.8–8.5) — 10.0 (8.5–11.4) 9.4 (8.6–10.2) 18.6 (15.7–21.3) 8.1 (7.5–8.7) 10.3 (8.3–12.2) 29.0 (18.5–39.5) 6.8 (5.5–8.1) 10.6 (9.8–11.4) 13.3 (8.3–18.4) 7.1 (5.6–8.7) 10.7 (9.8–11.5) 8.5 (7.9–9.1) 11.0 (3.6–18.4) 9.2 (8.0–10.4) 10.0 (9.2–10.9) 9.1 (7.1–11.0) 3.4 (0.2–6.6) 5.7 (4.4–7.1) 8.5 (7.2–9.8) 12.7 (10.9–14.4) 15.1 (12.4–17.8) 25.0 (16.3–33.7)
Statistical test F ⫽ 12.0 (P ⬍.001) F ⫽ 3.1 (P ⫽ .045) F ⫽ 3.4 (P ⫽ .07) F ⫽ 17.8 (P ⬍.001) F ⫽ 4.2 (P ⫽ .04) F ⫽ 13.1 (P ⬍.001) F ⫽ 14.6 (P ⬍.001) F ⫽ 0.4 (P ⫽ .5) F ⫽ 0.9 (P ⫽ .4) F ⫽ 17.0 (P ⬍.001)
Adjusted TTPb (months) (CI)a 9.1 (8.2–9.9) 11.1 (9.4–12.9) 18.7 (14.9–22.4) 9.2 (8.2–10.1) 11.2 (9.6–12.8) 10.8 (8.8–12.7) 9.3 (8.4–10.2) 7.6 (6.7–8.6) — 9.3 (7.7–11.0) 9.6 (8.8–10.5) 16.7 (13.2–20.2) 8.4 (7.7–9.1) 10.4 (8.1–12.8) 25.5 (15.1–35.9) 6.9 (5.5–8.4) 10.9 (10.0–11.7) 14.0 (8.8–19.3) 6.8 (5.0–8.5) 11.0 (10.0–11.9) 8.5 (7.9–9.2) 8.1 (0.3–15.9) 9.2 (7.9–10.6) 10.1 (9.1–11.0) 10.3 (8.2–12.5) 2.9 (0.0–6.3) 6.0 (4.4–7.6) 8.5 (7.2–9.7) 11.8 (9.9–13.7) 15.3 (11.8–18.7) 21.1 (12.0–30.3)
Statistical test F ⫽ 12.2 (P ⬍.001) F ⫽ 2.6 (P ⫽ .08) F ⫽ 2.3 (P ⫽ .08) F ⫽ 7.8 (P ⬍.001) F ⫽ 2.5 (P ⫽ .1) F ⫽ 10.5 (P ⬍.001) F ⫽ 16.5 (P ⬍.001) F ⫽ 0.1 (P ⫽ .9) F ⫽ 0.6 (P ⫽ .6) F ⫽ 6.5 (P ⬍.001)
Note: CI ⫽ 95% Confidence Interval; F ⫽ analysis of variance. a Mean. b Factors in the model: women’s age, weight, smoking, alcohol consumption, tea/coffee intake, drug abuse, parity, contraceptive use, and menstrual pattern, and men’s age, smoking, alcohol consumption, drug abuse, coital frequency, and living standard. Hassan. Lifestyle and fecundity. Fertil Steril 2004.
(57.1%) conceived within 3 months, a number that rose to 1604 (81.2%) by end of the first year. Of the 372 (18.8%) subfecund couples, 190 (9.6%) conceived in the second year. The subfecund women and their partners were significantly older (P ⬍.001), more obese (P ⬍.001), smoked more cigarettes (P ⫽ .002 and .04), consumed more alcohol (P ⫽.6 and .02), had longer contraceptive use (P ⬍.001); their recreational drug use and coital frequency were not significantly different when compared with fecund couples (Table 1).
Women and Men’s Smoking Of the couples surveyed, 72.6% of the women and 59.5% of the partners were nonsmokers, while 4.2% and 17.4%, respectively, used to smoke ⬎15 cigarettes/day. A statistically significant reduction in fecundity occurred with heavy but not with light smoking (Fig. 1A, B). Heavy smokers 386
Hassan et al.
Lifestyle and fecundity
(⬎15 cigarettes/day) among women had a twofold longer TTP (P ⬍.001), while the TTP of light smokers was not significantly different from that of nonsmokers. The effect of women’s heavy smoking remained statistically significant; men’s heavy smoking became insignificant after adjustment for the potential confounders (Table 2). Heavy smokers were more likely to be subfecund than nonsmokers; RR (95% CI) ⫽ 1.9 (1.4 –2.6) in women and 1.4 (1.1–1.8) in men (3.6 [1.9 –7.1], 1.4 [0.9 –2.1] after adjustment), while the conception rate within 12 months for light smokers was not different from that for nonsmokers (Table 3).
Women and Men’s Alcohol Consumption Of the survey participants, 58.2% of the women and 23.8% of their partners did not consume alcohol or had Vol. 81, No. 2, February 2004
FIGURE 1 Effect of each of the lifestyle variables on fecundity, expressed as time to pregnancy (TTP) in months. The values in each figure represent the mean TTP for each of the subgroups of the lifestyle variables, and the error bars represent the standard error of the mean. (A) Women’s smoking and (B) men’s smoking. The number of cigarettes/day smoked by women and their partners, respectively, were (I) nonsmokers, (II) ⱕ5, (III) 6 –10, (IV) 11–15, (V) 16 –20, and (VI) ⬎20. (P values are ⬍.001 and .05, respectively.) (C) Women’s alcohol consumption and (D) men’s alcohol consumption. The amounts of alcohol in units/week consumed by women and their partners, respectively, were: (I) nonconsumers, (II) ⱕ5, (III) 6 –10, (IV) 11–15, (V) 16 –20, and (VI) ⬎20. (P values are .05 and .009, respectively.) (E) Women’s coffee and tea intake. The amount of women’s coffee and tea per day in cups/day was: (I) nonconsumers, (II) ⱕ5, (III) 6 –10, (IV) 11–15, (V) 16 –20, and (VI) ⬎20. (P ⫽ .01.) (F) Women’s obesity presented by BMI. Women’s BMI in kg/m2 were: (I) ⬍19, (II) 19 –24, (III) 25–29, (IV) 30 –34, (V) 35–39, and (VI) ⬎39. (P ⬍ .001.)
Hassan. Lifestyle and fecundity. Fertil Steril 2004.
stopped drinking before trying for pregnancy; 12.0% of the partners but none of the women used to consume ⬎20 units/week. Heavy men’s alcohol consumption (⬎20 unit/ week) was associated with a significant reduction in fecundity (twofold longer TTP, P ⬍.001), but no similar effect was detected with women’s alcohol consumption as, in this sample, the amount they used to consume did not exceed 15 units/week (see Fig. 1C, D). Moderate alcohol consumption, FERTILITY & STERILITY威
neither in women nor in their partners, was found to have an effect on TTP compared with nonconsumers. Similar results were obtained after adjustment (see Table 2). Heavy men’s alcohol consumption was associated with a higher likelihood of subfecundity RR ⫽ 1.9 (1.3–2.7) (after adjustment ⫽ 2.2 [1.1– 4.4]). The pregnancy rates in association with moderate women or men’s alcohol consumption were not significantly different from the rates of nonconsumers (see Table 3). 387
TABLE 3 Relative risk of subfecundity for various subgroups of lifestyle variables. Relative risk of subfecundity (TTP ⬎12 months) Adjustedb
Unadjusted Variables Women’s smoking (cigarette/d)
Men’s smoking (cigarette/d)
Women’s alcohol (unit/wk)
Men’s alcohol (unit/wk)
Women’s coffee and tea (cup/d) Women’s BMI
Living standard Recreational drug use Coital frequency
Number of negative lifestyle variables
Groups
%
RR (CI)a
None Light (ⱕ15) Heavy (⬎15) None Light (ⱕ15) Heavy (⬎15) None Mild (ⱕ20) Heavy (⬎20) None Mild (ⱕ20) Heavy (⬎20) Mild (⬍7) Heavy (ⱕ7) ⬍19 kg/m2 19–24 kg/m2 25–39 kg/m2 ⬎39 kg/m2 High standard Low standard Never Previous/current ⱕ1/week 2–4 time/week ⱖ5 time/week None One Two Three Four Five or more
21.0 23.3 40.0 21.2 19.6 29.5 20.0 17.4 — 17.8 19.5 33.3 18.2 27.1 40.0 11.4 21.1 42.9 17.6 24.3 19.2 33.3 19.8 23.7 18.1 6.9 13.4 20.4 29.0 36.6 50.0
1.0 1.1 (0.9–1.4) 1.9 (1.4–2.6) 1.0 0.9 (0.7–1.2) 1.4 (1.1–1.8) 1.0 0.9 (0.7–1.1) — 1.0 1.1 (0.9–1.4) 1.9 (1.3–2.7) 1.0 1.5 (1.1–1.9) 3.5 (1.6–7.8) 1.0 1.9 (1.4–2.4) 3.8 (2.3–6.2) 1.0 1.4 (1.1–1.8) 1.0 1.7 (0.8–3.9) 1.0 1.2 (1.0–1.5) 0.9 (0.6–1.3) 1.0 1.9 (0.7–5.2) 3.0 (1.1–7.8) 4.2 (1.6–11.1) 5.3 (2.0–14.2) 7.3 (2.2–23.4)
P value
.400 .001 .600 .008 .200
.500 .001 .007 .020 ⬍.001 ⬍.001 .025 .300 .100 .700 .200 .010 ⬍.001 ⬍.001 .005
RR (CI)a 1.0 1.5 (1.1–2.2) 3.6 (1.9–7.1) 1.0 1.2 (0.8–1.7) 1.4 (0.9–2.1) 1.0 0.8 (0.6–1.0) — 1.0 1.3 (0.9–1.9) 2.2 (1.1–4.4) 1.0 1.7 (1.1–2.7) 4.8 (1.2–19.7) 1.0 2.2 (1.6–3.2) 6.9 (2.9–16.8) 1.0 1.6 (1.1–2.3) 1.0 1.6 (0.3–7.8) 1.0 1.2 (0.8–1.6) 1.0 (0.6–1.7) 1.0 2.2 (0.7–6.4) 3.3 (1.1–9.6) 4.4 (1.4–13.6) 6.5 (1.8–23.7) 7.2 (1.1–49.7)
P value
.0400 .0001 .4000 .0900 .0900
.2000 .0300 .0200 .0300 ⬍.0001 ⬍.0001 .0300 .6000 .4000 .9000 .2000 .0300 .0100 .0040 .0400
RR ⫽ relative risk; CI ⫽ 95% confidence interval; test ⫽ binary logistic regression. Factors in the model: women’s age, weight, smoking, alcohol consumption, tea/coffee intake, drug abuse, parity, contraceptive use, and menstrual pattern, and men’s age, smoking, alcohol consumption, drug abuse, coital frequency, and living standard.
a
b
Hassan. Lifestyle and fecundity. Fertil Steril 2004.
Women’s Tea and Coffee Intake Although 10.7% of the women did not drink tea or coffee, 19.1% consumed ⬎5 cups/day. A longer TTP with heavy coffee or tea intake (P ⫽.04) became insignificant after adjustment (see Fig. 1E, Table 1). Women who used to consume seven or more cups of tea or coffee/day were 1.5-fold (1.1–1.9) more likely to be subfecund (1.7 [1.1–2.7] after adjustment).
Women’s Obesity Among those surveyed, 2.6% of all women had a body mass index (BMI) ⬍19 kg/m2, and 17.9% had a BMI ⬎30 kg/m2 before pregnancy. The effect of body mass on fecundity appeared to be bimodal. Underweight women (BMI ⬍19 kg/m2) had a fourfold longer TTP than that of the 388
Hassan et al.
Lifestyle and fecundity
women who had a normal BMI (19 to 24 kg/m2). Women who had a prepregnancy weight ⬎80 kg or BMI ⬎25 kg/m2 took twofold longer TTP (P ⬍.001) (see Fig. 1F). The effects remained unchanged after adjustment for the other lifestyle variables, the woman’s age, and the menstrual pattern (see Table 2). Underweight women were 3.5-fold (1.6 – 7.8) and morbidly obese women were 3.8-fold (2.3– 6.2) more likely to be subfecund than those who had a normal BMI (4.8 [1.2–19.7] and 6.9 [2.9 –16.8] after adjustment, respectively) (see Table 3).
Living Standard The IMD score revealed that 22.1% of the couples had a deprivation score ⬍20 (high standard), and 21.2% had a score ⬎60 (low standard). Socially deprived couples took Vol. 81, No. 2, February 2004
significantly longer TTP (P ⬍.001) and were more likely to be subfecund (RR [CI] ⫽ 1.4 [1.1–1.8] before, and 1.6 [1.1–2.3] after adjustment) than those who had high living standard (see Tables 2 and 3).
Recreational Drug Use Only 3.0% of the women admitted previous or current drug use, and only 0.7% reported knowledge of their partner’s previous or current use. Recreational drug use, in this sample, was not found to be associated with a statistically significant effect on TTP or the subfecund proportions, compared with those of individuals who had never used recreational drugs (see Tables 2 and 3).
FIGURE 2 The absolute cumulative effect of increasing numbers of negative lifestyle variables on fecundity, expressed as time to pregnancy (TTP) in months. These variables include women’s smoking ⬎15 cigarettes/day, men’s smoking ⬎15 cigarettes/ day, men’s alcohol ⬎20 units/week, women’s coffee/tea intake ⱖ7 cups/day, women’s weight ⬎70 kg, social deprivation score ⬎60, women’s age ⬎35 years, and/or partners’ age ⬎45 years at the time of discontinuing contraception. The bold values represent the mean TTP for subgroups with increasing numbers of the negative lifestyle variables, and the error bars represent the standard error of the mean. The dashed lines point to the subgroups between which the shown P values were calculated.
Coital Frequency Infrequent intercourse was reported by 10.9% of the couples (less than once/week), and 12.2% reported frequent intercourse (five times or more/week). No statistically significant affect on TTP or conception rate was found for coital frequency in this sample (see Tables 2 and 3).
Absolute Effect of Negative Lifestyle The negative lifestyle variables were women’s heavy smoking, men’s heavy smoking (⬎15 cigarettes/day), heavy alcohol consumption (⬎20 units/week), heavy tea or coffee intake (⬎6 cups/day), prepregnancy BMI ⬎25 kg/m2, social deprivation (score ⬎60), and women’s age ⬎35 or men’s age ⬎45 years at the time of discontinuing contraception. Among those surveyed, 5.7% of the couples had none of these variables, 31.9% had one, 36.1% had two, 18.1% had three, and 8.2% had four or more variables. The increase in the number of the negative lifestyle variables was persistently associated with a significant and progressive reduction in fecundity. The mean TTP increased 2.5-fold with two variables, 3.7-fold with three variables, and 4.4-fold with four variables. Couples who had more than four negative variables had a 7.3-fold longer TTP than those who had no negative variables (Fig. 2; see Table 2). There was a statistically significant progressive decline in the conception rates within 6 and 12 months with the rise in numbers of negative lifestyle variables (Fig. 3). The conception probabilities, within 6 months, were found to fall from 0.9 with one variable to 0.77 with two, 0.48 with three down to 0.45 with four variables, and no pregnancies were achieved within 6 months in association with five or more variables. The conception probabilities within 12 months fell from 0.93 with one variable to 0.82 with two, 0.67 with three, down to 0.38 in association with four negative variables. Compared with the couples who had no negative variables, the RR (CI) of subfecundity rose from 1.9 (0.7–5.2) with one variable to 3.0 (1.1–7.8) with two, 4.2 (1.6 –11.1) with three, 5.3 (2.0 – 14.2) with four, up to 7.3 (2.2–23.4) in association with five or more negative variables (2.2 [0.7– 6.4], 3.3 [1.1–9.6], 4.4 [1.4 –13.6], 6.5 [1.8 –23.7], 7.2 [1.1– 49.7] after adjustment, respectively) (see Table 3). FERTILITY & STERILITY威
Hassan. Lifestyle and fecundity. Fertil Steril 2004.
DISCUSSION The methodology of this study has been previously discussed elsewhere (16). Using time to a current pregnancy excluded from the analysis those who had failed to conceive or had given up the pregnancy attempt (17–19). However, such selective sampling is not expected to have a significant effect on the results or conclusions, as lifestyle variables are not expected to lead to absolute sterility. In addition, an underestimation rather than overestimation of the negative effect, of the negative lifestyle, on fecundity would result from excluding the small minority who gave up the pregnancy attempt (20). The effect of negative lifestyle on fecundity was similar in planned and unplanned pregnancies. Furthermore, studies comparing the effects of exposures on TTP among pregnancy planners with those in current pregnancies have shown similar results (21). Data analysis aimed not only to detect but also to quantify the relative and absolute effects of lifestyle factors on fecundity. This was achieved in two ways; by comparing the mean TTP, then by comparing the conception rates and calculating the RR of subfecundity for various subgroups of each life389
FIGURE 3 The effect of increasing numbers of negative lifestyle variables on the cumulative conception rates within 1 year for a pregnant population. These variables include women’s smoking ⬎15 cigarettes/day, men’s smoking ⬎15 cigarettes/day, men’s alcohol ⬎20 units/week, women’s coffee or tea intake ⬎7 cups/day, women’s weight ⬎70 kg, social deprivation score ⬎60, women’s age ⬎35 years, and/or partners’ age ⬎45 years at the time of discontinuing contraception. The lines represent the cumulative conception rates for subgroups with different numbers of negative lifestyle variables as follows: E No negative variables; ■ One negative variable; ⫻ Two negative variables; ‚ Three negative variables; } Four or more negative variables.
Hassan. Lifestyle and fecundity. Fertil Steril 2004.
style factor and for groups with different numbers of the negative lifestyle factors. General linear and logistic regression models were used to control for confounders to assess the effect of each of the lifestyle variables independently. The harmful effects of smoking and heavy alcohol drinking on the general health are well accepted. Several studies have shown the negative effects of smoking (22–31) and alcohol consumption (32–34) on fertility. Smoking has been shown to affect gamete quality (35–39), impair fertilization (13, 40), or result in early miscarriage. The effect of alcohol consumption on fertility has been suggested to be related to hormonal and ovulatory abnormalities (41). Couples who are trying for pregnancy are usually advised to give up smoking and stop drinking, but this advice may be difficult or even impossible for some couples to follow, which may add more stress and strain to an already threatened relationship and further jeopardize their chances of conception (42– 44). It is 390
Hassan et al.
Lifestyle and fecundity
important, therefore, to quantify and base the advice given on clear evidence. Based on the above results, the effects of smoking and alcohol consumption on fecundity appear to be dosedependent. A significant negative effect was demonstrated only with heavy smoking (⬎15 cigarettes/day, women or men). Light smoking has not been found to affect TTP or the conception probabilities compared with nonsmoking. The effect of women’s alcohol consumption on fecundity in this sample was insignificant. This may be due to the relatively small amount they consumed. The effect of the male partner’s alcohol consumption on fecundity was only significant when the amount consumed exceeded 20 units/week; a smaller amount has not been shown to have a statistically significant effect. The absence of a statistically significant effect in association with moderate alcohol consumption is consistent with the results of other studies (45, 46). The Vol. 81, No. 2, February 2004
negative effect of heavy caffeine intake is also consistent with the results of other studies (47–50). The effect of body mass on fecundity was bimodal. Sporadic ovulation in underweight women is not unexpected, and this would explain the statistically significant reduction in fecundity of these women. A statistically significant negative effect of women’s obesity on fecundity was demonstrated. This effect was independent of other lifestyle variables, the women’s age, and the menstrual pattern, and was similar whether the absolute weight or BMI was used in the analysis. The effect of obesity on fertility might be a direct effect (51–53); be caused by disturbance in leptin (54 –57), an important factor for both body fat mass regulation and reproductive function; or be the result of polycystic ovary syndrome (58, 59), a prevalent condition among obese women. In these cases, weight loss has been shown to improve both the chances of spontaneous conception and the success of fertility treatments (60 – 63). In this sample, the statistically insignificant effect of recreational drug use on fecundity is probably a result of the tiny proportion that admitted having ever used drugs. Other studies have demonstrated a negative effect (64). Also, results from this study, in agreement with other studies (65, 66), are not supportive of the belief that frequent or timed intercourse enhances fecundity. These provide an evidencebased answer to a question commonly asked by couples striving for pregnancy. The detrimental effect on fecundity of social deprivation (as identified by using the IMD) could not be attributed to other lifestyle variables as it remained statistically significant after adjustment. Residence in more deprived areas is associated with personal disadvantage (67), but the mechanism by which social deprivation affects fertility is unclear. Further research is obviously needed. Increasingly in recent decades, couples, especially those with career ambitions, choose to delay having children until later age (68). Therefore, trying for a pregnancy at women’s age of 35 years or more and/or men’s age of 45 years or more was considered among the negative lifestyle factors. About two-thirds of the couples in this sample had two or more negative lifestyle variables, and the results of this study indicate that the detrimental effect of negative lifestyle factors on fecundity is cumulative. The TTP was progressively longer (2.4-fold with two, up to 7.3-fold with five or more variables) and the conception probabilities were persistently lower (0.82 with two, down to 0.38 with four variables) with increased numbers of negative lifestyle variables. Couples who had five or more negative variables were 7.3-fold more likely to be subfecund compared with those without any of these variables. Subfertile couples who are seeking medical intervention often disregard lifestyle factors as having adverse effects on fertility (69). Promoting a healthier lifestyle among the couFERTILITY & STERILITY威
ples planning or trying for pregnancy is important not only for their general health but also for prevention of subfertility, as evident from the data in our study. Primary health care providers are in a unique position to provide education, counseling, and support to these couples (70). Based on our results, should these couples lead a healthy lifestyle, a reduction in subfecundity by over half would result. This, in the long term, could lead to a substantial decline in the referrals for medical investigations and fertility treatments. References 1. Bongaarts J. A method for the estimation of fecundability. Demography 1975;12:645–60. 2. ESHRE Capri workshop. Guidelines to the prevalence, diagnosis, treatment and management of infertility. Hum Reprod 1996;11:1775–807. 3. Hull MGR, Glazener CMA, Kelly NJ, Conway DI, Foster PA, Hinton RA, et al. Population study of causes, treatment, and outcome of infertility. BMJ 1985;291:1693–7. 4. Templeton A. Infertility-epidemiology, aetiology and effective management. Health Bull 1995;53:294 –8. 5. Hull MGR. Infertility treatment: relative effectiveness of conventional and assisted conception methods. Hum Reprod 1992;7:785–96. 6. Van Noord-Zaadstra BM, Looman CW, Alsbach H, Habbema JD, te Velde ER, Karbaat J. Delaying childbearing: effect of age on fecundity and outcome of pregnancy. BMJ 1991;302:1361–5. 7. Kidd SA, Eskenazi B, Wyrobek AJ. Effects of male age on semen quality and fertility: a review of the literature. Fertil Steril 2001;75: 237–48. 8. Howe G, Westhoff C, Vessey M, Yeates D. Effects of age, cigarette smoking, and other factors on fertility: findings in a large prospective study. BMJ 1985;290:1697–700. 9. Feichtinger W. Environmental factors and fertility. Hum Reprod 1991; 6:1170 –5. 10. Bolumer F, Olsen J, Rebagliato M, Saez-Lloret I, Bisanti L. Body mass index and delayed conception: a European multicentre study on infertility and subfecundity. Am J Epidemiol 2000;151:1072–9. 11. Chia SE, Lim ST, Tay SK, Lim ST. Factors associated with male infertility: a case-control study of 218 infertile and 240 fertile men. Br J Obstet Gynaecol 2000;107:55–61. 12. Clark AM, Thornley B, Tomlinson L, Galletley C, Norman RJ. Weight loss in obese infertile women results in improvement in reproductive outcome for all forms of fertility treatment. Hum Reprod 1998;13: 1502–5. 13. Rosevear SK, Holt DW, Lee TD, Ford WC, Wardle PG, Hull MG. Smoking and decreased fertilisation rates in vitro. Lancet 1992;340: 1195–6. 14. Templeton A, Fraser C, Thompson B. Infertility-epidemiology and referral practice. Hum Reprod 1991;6:1391–4. 15. Noble M, Penhale B, Smith G, Wright G, Dibben C, Owen T, et al. Indices of deprivation 2000. London: Department of the Environment, Transport and the Regions (DETR), 2000. 16. Hassan MAM, Killick S. Evidence for the decline in male fertility with increasing age. Fertil Steril 2003;79(Suppl 3):1520 –7. 17. Basso O, Juul S, Olsen J. Time to pregnancy as a correlate of fecundity: differential persistence in trying to become pregnant as a source of bias. Int J Epidemiol 2000;29:856 –61. 18. Jensen TK, Scheike T, Keiding N, Schaumburg I, Grandjean P. Selection bias in determining the age dependence of waiting time to pregnancy. Am J Epidemiol 2000;152:565–72. 19. Juul S, Keiding N, Tvede M. Retrospectively sampled time to pregnancy data may make age-decreasing fecundity look increasing. European Infertility and Subfecundity Group. Epidemiology 2000;11:717–9. 20. Olsen J, Juul S, Basso O. Measuring time to pregnancy: methodological issues to consider. Hum Reprod 1998;13:1751–6. 21. Bolumar F, Olsen J, Boldsen J. Smoking reduces the biological capacity of conception. Results from a European multicenter study. The European Study Group on Infertility and Subfecundity. Ugeskr Laeger 1997;159:4526 –32. 22. Baird DD, Wilcox AJ. Cigarette smoking associated with delayed conception. JAMA 1985;253:2979 –83. 23. Weinberg CR, Wilcox AJ, Baird DD. Reduced fecundability in women with prenatal exposure to cigarette smoking. Am J Epidemiol 1989; 129:1072–8. 24. Suonio S, Saarikoski S, Kauhanen O, Metsapelto A, Terho J, Vohlonen I. Smoking does affect fecundity. Eur J Obstet Gynecol Reprod Biol 1990;34:89 –95.
391
25. Joesoef MR, Beral V, Aral SO, Rolfs RT, Cramer DW. Fertility and use of cigarettes, alcohol, marijuana, and cocaine. Ann Epidemiol 1994;4: 423. 26. Alderete E, Eskenazi B, Sholtz R. Effect of cigarette smoking and coffee drinking on time to conception. Epidemiology 1995;6:403–8. 27. Hughes EG, Brennan BG. Does cigarette smoking impair natural or assisted fecundity? Fertil Steril 1996;66:679 –89. 28. Vine MF. Smoking and male reproduction: a review. Int J Androl 1996;19:323–37. 29. Bolumar F, Olsen J, Boldsen J. Smoking reduces fecundity: a European multicenter study on infertility and subfecundity. The European Study Group on Infertility and Subfecundity. Am J Epidemiol 1996;143:578 – 87. 30. Curtis KM, Savitz DA, Arcbukle TE. Effects of cigarette smoking, caffeine consumption, and alcohol intake on fecundability. Am J Epidemiol 1997;146:32–41. 31. Augood C, Duckitt K, Templeton AA. Smoking and female infertility: a systematic review and meta-analysis. Hum Reprod 1998;13:1532–9. 32. Grodstein F, Goldman MB, Cramer DW. Infertility in women and moderate alcohol use. Am J Public Health 1994;84:1429 –32. 33. Hakim RB, Gray RH, Zacur H. Alcohol and caffeine consumption and decreased fertility. Fertil Steril 1998;70:632–7. 34. Jensen TK, Hjollund NH, Henriksen TB, Scheike T, Kolstad H, Giwercman A, et al. Does moderate alcohol consumption affect fertility? Follow up study among couples planning first pregnancy. BMJ 1998; 317:505–10. 35. Weisberg E. Smoking and reproductive health. Clin Reprod Fertil 1985;3:175–86. 36. Vine MF, Tse CK, Hu P, Truong KY. Cigarette smoking and semen quality. Fertil Steril 1996;65:835–42. 37. Rubes J, Lowe X, Moore D 2nd, Perreault S, Slott V, Evenson D, et al. Smoking cigarettes is associated with increased sperm disomy in teenage men. Fertil Steril 1998;70:715–23. 38. Wong WY, Thomas CM, Merkus HM, Zielhuis GA, Doesburg WH, Steegers-Theunissen RP. Cigarette smoking and the risk of male factor subfertility: minor association between cotinine in seminal plasma and semen morphology. Fertil Steril 2000;74:930 –5. 39. Zenzes MT, Wang P, Casper RF. Cigarette smoking may affect meiotic mutation of human oocytes. Hum Reprod 1995;10:3213–17. 40. Weigert M, Hofstetter G, Kaipl D, Gottlich H, Krischker U, Bichler K, et al. The effect of smoking on oocyte quality and hormonal parameters of patients undergoing in vitro fertilization-embryo transfer. J Assist Reprod Genet 1999;16:287–93. 41. Gill J. The effects of moderate alcohol consumption on female hormone levels and reproductive function. Alcohol Alcohol 2000;35:417–23. 42. Hjollund NH, Jensen TK, Bonde JP, Henriksen TB, Andersson AM, Kolstad HA, et al. Distress and reduced fertility: a follow up study of first-pregnancy planners. Fertil Steril 1999;72:47–53. 43. Stoleru S, Teglas JP, Fermanian J, Spira A. Psychological factors in the aetiology of infertility: a prospective cohort study. Hum Reprod 1993; 8:1039 –46. 44. Sanders KA, Bruce NW. A prospective study of psychological stress and fertility in women. Hum Reprod 1997;12:2324 –9. 45. Zaadstra B. M, Looman CW, te Velede ER, Habbema JD, Karbaat J. Moderate drinking: no impact on female fecundity. Fertil Steril 1994; 62:948 –54. 46. Folrack EI, Zielhuis GA, Rolland R. Cigarette smoking, alcohol consumption and caffeine intake and fecundability. Prev Med 1994;23: 175–80. 47. Wilcox A, Weinberg C, Baird D. Caffeinated beverages and decreased fertility. Lancet 1988;2:1453–6. 48. Olsen J. Cigarette smoking, tea and coffee drinking and subfecundity. Am J Epidemiol 1991;133:734 –9.
392
Hassan et al.
Lifestyle and fecundity
49. Bolumar F, Olsen J, Rebagliato M, Bisanti L. Caffeine intake and delayed conception: a European multicenter study on infertility and subfecundity. Am J Epidemiol 1997;145:324 –34. 50. Jensen TK, Henriksen TB, Hjollund NH, Scheike T, Kolstad H, Giwercman A, et al. Caffeine intake and fecundability: a follow up study among 430 Danish couples planning their first pregnancy. Reprod Toxicol 1998;12:289 –95. 51. Zaadstra BM, Seidell JC, Van Noord PA, te Velde ER, Habbema JD, Vrieswijk B, et al. Fat and female fecundity: prospective study of effect of body fat distribution on conception rates. BMJ 1993;306:484 –7. 52. Jarow JP, Kirkland J, Koritnik DR, Cefalu WT. Effect of obesity and fertility status on sex steroid levels in men. Urology 1993;42:171–4. 53. Foreyt JP, Poston WS 2nd. Obesity: a never-ending cycle? Int J Fertil Wom Med 1998;43:111–6. 54. Messinis IE, Milingos SD. Leptin in human reproduction. Hum Reprod Update 1999;5:52–63. 55. Magni P, Motta M, Martini L. Leptin: a possible link between food intake, energy expenditure, and reproductive function. Regul Pept 2000;92:51–6. 56. Alfer J, Muller-Schottle F, Classen-linke I, von Rango U, Happel L, Beier-Hellwig K, et al. The endometrium as a novel target for leptin: differences in fertility and subfertility. Mol Hum Reprod 2000;6:595– 601. 57. Imani B, Eijkemans MJ, de Jong FH, Payne NN, Bouchard P, Giudice LC, et al. Free androgen index and leptin are the most prominent endocrine predictors of ovarian response during clomiphene citrate induction of ovulation in normogonadotropic oligoamenorrheic infertility. J Clin Endocrinol Metab 2000;85:676 –82. 58. Franks S, Kiddy D, Sharp P, Singh A, Reed M, Seppala M, et al. Obesity and polycystic ovary syndrome. Ann NY Acad Sci 1991;626: 201–6. 59. Pettigrew R, Hamilton-Fairley D. Obesity and female reproductive function. Br Med Bull 1997;53:341–58. 60. Kiddy DS, Hamilton-Fairley D, Bush A, Short F, Anyaoku V, Reed MJ, et al. Improvement in endocrine and ovarian function during dietary treatment of obese women with polycystic ovary syndrome. Clin Endocrinol 1992;36:105–11. 61. Pasquali R, Casimirri F, Vicennati V. Weight control and its beneficial effect on fertility in women with obesity and polycystic ovary syndrome. Hum Reprod 1997;12:82–7. 62. Norman RJ, Clark AM. Obesity and reproductive disorders: a review. Reprod Fertil Dev 1998;10:55–63. 63. Kably-Ambe A, Barron-Vallejo J, Limon-Luque LM. Effect of body mass index and follicular synchrony in the ovarian response to ovulation induction with menotropins. Int J Fertil Wom Med 1999;44:156 –9. 64. Mueller BA, Daling JR, Weiss NS, Moore DE. Recreational drug use and the risk of primary infertility. Epidemiology 1990;1:189 –92. 65. Agarwal SK, Haney AF. Does recommending timed intercourse really help the infertile couple? Obstet Gynecol 1994;84:307–10. 66. Tur-Kaspa I, Maor Y, Levran D, Yonish M, Mashiach S, Dor J. How often should infertile men have intercourse? Fertil Steril 1994;62: 370 –5. 67. Sloggett A, Joshi H. Deprivation indicators as predictors of life events 1981–1992 based on the UK ONS Longitudinal Study. J Epidemiol Community Health 1998;52:228 –33. 68. Martin SP. Diverging fertility among U.S. women who delay childbearing past age 30. Demography 2000;37:523–33. 69. Olatunbosun OA, Edouard L, Pierson RA. How important is health promotion in the lifestyle of infertile couples? Clin Exp Obstet Gynecol 1997;24:183–6. 70. Whitman-Elia GF, Baxley EG. A primary care approach to the infertile couple. J Am Board Fam Pract 2001;14:33–45.
Vol. 81, No. 2, February 2004