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Adolescent Smoking, Weight Changes, and Binge-Purge Behavior: Associations with Secondary Amenorrhea

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I

Jim Johnson, PhD, and Agnes H. Whitaker, MD

Introduction Therc is a striking paucity of data on the epidemiology and correlates of amenorrhea among adolescent females. The few studies that have examined menstruation among community-based samples of adolescent females have restricted their focus to age at menarche'1' and to other menstrual characteristics, such as oligomenorrheal and dysmenorrhea." 5 In recent ycars, clinical research on amenorrhea has also focused on nonpregnant clinical samples with high rates of amenorrhea. In addition to patients with welldefined medical disorders,6,7 thcsc samples include patients with eating disorders, such as anorexia nervosa8- "I and bulimia,' 1-16 and substance abuse disorders, such as alcoholism.17 High rates of amenorrhca have also been found in carecr ballet dancers'8" 9 and athletes.24V22 The association of amenorrhea with extreme forms of weight control, substance use, and exercise in these highly nonreprcsentative samples raises the question of whether adolescents in the general population who engage in these behaviors are at increased risk for secondary amenorrhea. The importance of the question is underscored by two sets of findings: (1) the high rates at which adolescent girls experiment with weight control,23 cigarettes,2425 and alcohol;'9'26 and (2) the association of amenorrhea in sclected samples with increased rates of infertility,27 increased rates of osteoporosis,28,29 scoliosis and stress fractures,3013' and lower lifetime occurrence of breast cancer and cancers of the reproductive system32-all conditions of major concem to women.

Amcnorrhea is classified for clinical purposes as either pnrmary or secondary. Primary amenorrhea is defined as the fail-

urc to achieve menarche by age 16.6.7 Sccondary amenorrhea refcrs to the prolonged absence (usually defined as 3 months) of menstrual bleeding any time after menarche.67 These age and duration guidelines for the clinical investigation of adolescent amenorrhea take into account the normal variation in age of menarche (11 to 15 years)2 and the physiological occurrcnce of irregular intermenstrual intervals (oligomenorrhca) due to anovulatory cycles in the first years after menarche." 3->35 Amenorrhea is properly regarded as a symptom that may reflect quite different etiologies and endocrine profiles. This study focuses on the prevalence and behavioral correlates of secondary amenorrhea in an unselected population of adolescent females.

Methods Study Sample and Measures The study sample was a county-wide population of high school students (n = 5596) who participated in a survey of selected psychiatric disorders in 1985.23 Students were surveyed during classroom hours in the eight high schools in the county (five general public schools, one vocational public school, one indepcndent Jim Johnson is with the Clinical and Genetic Epidemiology Unit of Columbia University College of Physicians and Surgeons. Agnes H. Whitaker is with the New York State Psychiatric Institute, Division of Child Psychiatry at the Columbia University College of Physicians and Surgeons. Requests for reprints should be sent to Agnes H. Whitaker, MD, Box 78, New York State Psychiatric Institute, 722 West 168th Street, New York, NY 10032. This paper was submitted to the journal September 24, 1990, and accepted with revisions May 7, 1991.

American Journal of Public Health

47

J_hnsn and Whiaker

Test38 identified cases of anorexia nervosa and bulimia with a sensitivity of 86.7 and a specificity of 72.9.39 Level of exercise was assessed by listing nine types of activities and asking how many days per week in the past month the student engaged in those activities. Cigarette use and beer and wine consumption were assessed with items drawn from Kandel.40 Other studies have found that adolescent self-reports on cigarette4l and alcohol use are valid.42'43 To our knowledge, the validity of adolescent reports on exercise has not been studied. As for background characteristics, social class was defined according to Hollingshead,44 relative body weight was defined by body mass index (BMI) (weight in kg/height in an2 x 10 000),45.46 and gynecologic age was defined as the difference in years between chronological age and age at menarche.4748 Accuracy of students' reports of height and weight were assessed with a validity study.23 Reports for height were found to be accurate and unbiased whereas heavy girls tended to underestimate their weight; however, the bias was minimal (-2.5 kg). By definition, premenarchal girls were not considered to be at risk for secondary amenorrhea.

Statistical Analysis

day and boarding school, and one parochial day school). The study protocol included provision for surveying absentees. Of the county-wide enrollment, 91% (2564 boys and 2544 girls) returned valid questionnaires. The population was primarily White (94 percent) and was evenly distributed across ages 14 to 17; 2.5% were 13 years old or younger, and 5.5% were 18 years old or older. The girls' version of the survey questionnaire asked whether menstrual periods had begun and, if so, the year and month of menarche. Postmenarchal girls were asked, "Have you missed three of your expected periods in a row since this time last year?" Other menstrual questions, with the exception of the item concerning amenorrhea, were pattemed after the questionnaire items of Widholm and Kantero.' Other investigators have found that adolescents report age at menarche with a high degree of accuracy.26 48 American Journal of Public Health

Weight control practices, binge-eating, andweight historywere assessedwith the Eating Symptoms Inventory.23 This instrument contains 24 sets of questions that operationalize the symptoms of anorexia nervosa and bulimia as defined by the American Psychiatric Association in the Diagnostic and Statistical Manual of Mental Disorders (3rd ed.) (DSM-III).37 Binge-eating behaviors included large binges, recurrent binges, and binge discomfort (termination of binges for abdominal pain, sleep, social interruption, or feeling the urge to throw up), as detailed in an earlier report.3 Dieting, fasting, purging (self-induced vomiting and laxative use), and use of diet pills and diuretics were also assessed. From a review of semistructured clinical interviews with a subsample of356 students who participated in the survey, a screen for eating disorders based on items in the inventory and on the Diet Factor from the Eating Attitudes

Risks are framed in terms of relative risk (RR).49 Problems related to interpretation of risk factors in a cross-sectional study are reserved for the discussion. We also report 95% confidence intervals (CIs) based on the limits of risk. Most of the putative risk factors (weight history, weight control practices, substance abuse, and exercise) were to some extent correlated; any statement about independent contributions to the risk of secondary amenorrhea had to include evaluation of these potential risk factors in a multivariate logistic regression model in conjunction with careful examination of the cross-classified risks. The RRs of amenorrhea reported in Tables 1 and 2 are the ratios (proportions) of the risk in those exposed to the risk factor to the risk in those unexposed. CIs are from the limits of the probabilities of a logistic regression estimate in both the unadjusted (Table 1) and adjusted (Table 2) case. In Table 2, the estimated risk for an individual is given by

1/{1 + exp[ - 1*(constant blXl + .. brXr)]}.5°

+

January 1992, Vol. 82, No. 1

Adolescent Smoking, Weight Changes, and Binge-Purge Behavior

We have avoided reporting adjusted odds ratios in this cross-sectional study, given that the risk in some of the exposed strata (e.g., severe binge-purge) violates the "rare disease" assumption.49 If one is concerned about statistical significance, the CIs reported in Tables 1 and 2 exclude one only when the odds ratio would also. To the extent that the risk in a number of the exposed groups exceeds 10%, the relative risks, as reported in Tables 1 and 2, is the superior point estimates of risk when compared with the odds ratio. As an estimate of the adjusted population excess fraction (population attributable risk), we also use

p(exposure)*(1 - RRa)I

{[p(exposure)*(RRa - 1)]

+

1}.

Because there is some controversy over the use of this estimate,51,52,53 we stratified the data as far as feasible and reestimated using (1) Greenland's "exact method"52

equation 2, and (2) Miettinen's multivariate confounder score method; the latter allowed us to do what we did in (1) while retaining more information with respect to dosage.54 In each case, the estimates ob tained by these three alternative methods were consistent within rounding error. Convergence of solutions suggests that the estimates of adjusted excess fractions (Table 2) are reasonable.

Results Prevalence ofPrimary and SecondaryAmenorrhea. Among girls aged 16 and older, the prevalence of primary amenorrhea (premenarchal status) was 2.0%. The 1-year prevalence of secondary amenorJanuary 1992, Vol. 82, No. 1

rhea in postmenarcheal girls was 8.5%. Only 1 out of the 245 girls subsequently interviewed by clinicians in the second stage of the study had ever been pregnant, suggesting that pregnancy at most accounted for one or two reports of secondary amenorrhea in these data. Among the 2544 girls surveyed in this semirural county, 36 reported using birth control pills, and the prevalence of secondary amenorrhea among them was 5.6% (vs 8.5% for the remainder of the population). Relationships with Social Class, Age, and BMI. The proportion of girls who reported secondary amenorrhea in the past year appears in Table 3 by social class," chronological age, gynecological age, and BMI quartile. Secondary amenorrhea was not significantly related to social class (by chi-square statistic). A post hoc grouping of the lowest two social classes (suggested by the data in Table 3) also failed to yield a significant difference. Risk of secondary amenorrhea was highest among girls whose gynecologic age was 2 years or less, and it was lower in the older gynecologic age groups. There was no relationship between secondary amenorrhea and BMI quartile. More restricted divisions of BMI, including deciles, were also unrelated to secondary amenorrhea, as was percent below ideal weight at lowest weight for previous year.

Weight Control Bulimic Behaviors, and Weight Changes. Girls who had dieted, even for longer than 28 consecutive days, were not at increased risk for secondary amenorrhea when compared with girls who had not. However, girls who had fasted for extended periods (3 or more days) were at some increased risk (RR = 1.84, 95% CI = 1.20-2.71) (Table

1). Duration of dieting and fasting were evaluated independently of kilograms lost on a diet or fast because many girls reported that they had dieted (or fasted) for extended periods without weight loss.23 In contrast to simple duration of dieting, other methods of weight control

American Joumal of Public Health

49

Johnson and Whitaker

35

%

Purgers

(20/66)

30 25

RiskFactorsforSecondaryAmenor-

A m

*

20-

n 0 r

r

h

(43/302)

15-

S

c

were related to age, with older girls more likely to both smoke and drink. Neither variable was related to social class. In contrast to adults, smoking here was not related to BMI: smokers in this adolescent sample were not of lighter relative weight than nonsmokers.

10 _ (94/119)

0

Non-purgers (6/160)

U

0 0

1

2or3

DSM-III Binge-Eating Behaviors

FIGURE 1-BInge eating, sef-lnduced vomiting, or laxabte use and secondary amenorrhea. Amenorhea Is defined as three consect missed menstrual perods In tm past year In a p narchal girl. "Purgers" report use of self-induced vomiting or laxtve for weght control. Binge-eating behaviors consist of large binges, frequent binges, and binge dscomfort (se

texl).

associated with higher risk for secondary amenorrhea. Self-induced vomiting, use of laxatives, and use of diet pills (mainly nonprescription) were each associated with one and one-half to threefold increases in risk for secondary amenorrhea (Table 1). The use of diuretics (nonprescription) was not significantly associated with increased risk (RR = 1.64, 95% CI = n.s.); however, the number of girls who used diuretics was small (n = 22), and thus our statistical power to detect such an increase in risk was minimal. As we have reported elsewhere,23 weight control behaviors were more common in girls who were older and heavier (by BMI) and were minimally related to social class. Reports of binge-eating consistent with the DSM-IIP7 definition of this behavior were associated with a twofold increase in the risk of secondary amenorrhea. With respect to weight change in the past year, girls who had gained at least 4.5 kg, or 10 lb, and girls whose weight had fluctuated (a gain of 4.5 kg or more combined with a loss of 4.5 kg or more) in the pastyearwere at higher risk for secondary amenorrhea (RR = 1.93, 95% CI = 1.362.67; RR = 2.82,95% CI = 1.61-4.60, respectively) when compared with girls who had not gained or lost 4.5 kg in the previous year (Table 1). Girls who reported a simple loss of at least 4.5 kg in the previous were

50 American Joumal of Public Health

also at some increased risk for secondary amenorrhea (RR = 1.54, 95% CI = 1.05-2.23). However, a weight loss of 4.5 kg or more appeared to be a greater risk factor in girls in the lowest BMI quartile (RR = 3.00, 95% CI = 1.44-5.53, not shown on Table 1). For these analyses, a cutoff of 4.5 kg or more was used to evaluate weight change as a risk factor. Parallel analyses using number of kilograms lost, percent of body weight lost, or various transformations (e.g., log (kg)) produced similar results. Exercise Regimens. Girls who exercised daily were not at greater risk for premenarchal status or secondary amenorrhea than those who did not. Gymnasts and dancers who exercised daily also failed to show an elevated risk (RR = 0.99, 95% CI = 0.54-1.77, not shown on Table 1). Cigarette Smoking andAlkohol Use. The risks associated with cigarette smoking and alcohol also appear on Table 1. Both risk factors show evidence of a doseresponse relationship with twofold increases in secondary amenorrhea at the higher dose (one pack of cigarettes or more per day; alcohol use more than several times per week). Cigarette smoking and alcohol use in this sample were related: girls who smoked were twice as likely to drink, and girls who drank were twice as likely to smoke. Both variables

year were

rhea: MultivaniateAnalysis. Table 2 presents the final model from successive logistic regression and cross-classification analyses.55-56 It reports the probability of exposure (percent of girls with the characteristic), the RRa, the excess fraction for the population, and the attributable risk in those exposed to a risk factor.50 Of particular importance to clinicians is binge-purge behavior. As Figure 1 shows, the risk associated with bingeeating behavior was modified by the level of purging (laxative use or self-induced vomiting). The statistical interaction suggested by Figure 1 was significant (P < .001). Because laxative use in combination with binge-eating rarely occurred in the absence of self-induced vomiting (n = 69), laxative use was combined with self-induced vomiting for the purposes of these analyses. Binge eating was a risk factor for secondary amenorrhea only when it occurred in combination with purging (and vice versa). Given the striking pattern of results in Figure 1, bingepurge behavior was modeled with two variables: partial binge-purge behavior, defined as self-induced vomiting or laxative use in conjunction with a singleDSMIII binge-eating behavior (RRa = 1.99, 95% CI = 1.39-2.81), and complete binge-purge behavior, defined as self-induced vomiting or laxative use in conjunction with two or three DSM-III bingeeating behaviors (RRa = 4.17, 95% CI = 2.54-6.52) (Table 2). Girls who smoked a pack of cigarettes or more per day were at excess risk for secondary amenorrhea, even with statistical control for other variables in the model. The variable representing lower levels of exposure to cigarettes (less than a pack per day) was not statistically significant in the final multivariate model, but the point estimate of the effect (RRa = 1.35, 95% CI = 0.90-1.72) (Table 2) was intermediate, consistent with a dose-response relationship. To the extent that there were age differences in the association between smoking and secondary amenorrhea, there was a nonsignificant tendency for the association to be stronger in older girls. Unfortunately, no information was available as to how long the girls had been smoking.


Adolescent Smoking, Weight Changes, and Binge-Purge Behavior

A number of variables contributed little to the model after adjustment for other associated variables. To the extent that diet pills, diuretics, or simple duration of dieting or fasting was associated with increased rates of amenorrhea, it appeared to be due to the association of these variables with other risk factors (i.e., weight fluctuation and binge-purge behavior). The decision to drop alcohol from the final model was made only after exaiining the effects of alcohol consumption across levels of other risk factors. No excess risk was apparent above and beyond the effects of confounding variables. Focusing on the population excess fractions in the fourth column of Table 2, it is apparent that many of the cases of secondary amenorrhea in the population were associated with behavior: 12% with smoking and 21% with binge-purge behavior. The direction of effect was less compelling with respect to the fraction associated with weight gain, loss, and fluctuation. However, most weight fluctuation in the population coincided with some form of weight control behavior (85%). The final column of Table 2 provides adjusted estimates of attributable risk in girls actually exposed to the model risk factors. It was not possible to confirm the results of the model presented in Table 2 with a complete cross-classification of risk factors because the number of possible combinations is unwieldy (8640, if BMI is categorized). As an alternative, the data of primary interest are presented in Figure 2, cross-classifying and collapsing dose categories across smoking, binge-purge behavior, and type of weight change.

Discussion The prevalence of secondary amenorrhea in an unselected adolescent population has not been previously reported. The most methodologically satisfactory study of secondary amenorrhea among adult women (excluding instances attributable to pregnancy and surgical treatment) found a 1-year prevalence of 4.4% for women aged 18 to 45, with a 6.3% prevalence in the age group 18 to 2457somewhat lower than the rate of 8.5% found in this study. Lower rates among adult women may be due to a number of factors, such as maturation of the reproductive cycle47 or lower rates of the types of behavior examined here. Certainly, secondary amenorrhea may be due to other underlying medical causes, which must be systematically exJanuary 1992, Vol. 82, No. 1

30

(18/64)

Wgt.Change & Binge-Purge

25 (19/8 7)

20

A m e

Wgt.Change

(14/166) No Binge-Purge

15

o

r

(29/294)

r

h e0

0 c

x0 NoC3ns

~~~No Chaknge (23/123)

(12/94)

Binge-Purge

5

23 *

X No Change (47/914) No Binge-Purge

0

v

smokers non-smokers FIGURE 2-Smoking, weight changes, binge-purge behavior, and secondary amenorrhea.Weightchanges refersto the gain, loss, orfiucthuon of at least4.5 kgs (10 lb) In the previous year. "Binge-purge behavior" refers to the combination of binge eating with purging (laative use or self-Induced vomiting). "Smokers" refers to any ongoing cigarette smoking.

cluded in a thorough diagnostic workup of each case.6,7,58 However, such unmeasured risk factors would have to be strongly associated with the risk factors identified by this observational study to render these results spurious. We find an explanation pointing to spurious associations unlikely, given the biologic plausibility of the risk factors nominated. Binge-eating behaviors were associated with a markedly increased risk for secondary amenorrhea. An association between binge-purge behavior and amenorrhea and/or menstrual irregularity among high school girls was noted by Johnson et al.,59 but rates and risks for amenorrhea were not fully explored. With respect to the risk for secondary amenorrhea associated with binge-purge behavior, it is likely that purging (self-induced vomiting or laxative use) rather than binge eating is the causal agent. Little, if any, increased risk was evident in the large number of girls who binged but did not purge. The fact that the combination of binge eating and purging carries increased risk is likely to indicate the (unmeasured) increased frequency of purging accompanying the full binge-purge behavioral syndrome. The mechanism by which bingepurge behavior may affect the hypotha-

lamic-pituitary-ovarian axis is not clear. At least three separate studies60-62 find evidence in adult bulimic patients of dis-

turbed hypothalamic-pituitary function that is not attributable to emaciation. Possible etiologic factors include nutritional deficiencies,6364 insufficient body fat content,65 intermittent dieting,66 stress,'6067,68 exercise,21 and adaptation to semistarvation at a weight that is considered "normal" by population standards but is below the physiological setpoint for the individual.62

Weight changes resulting from weight control practices were associated with secondary amenorrhea above and beyond the specific methods used (Table 2). In particular, weight fluctuation over the past year was associated with the greatest risk for secondary amenorrhea. This epidemiologic study confirms the importance of weight control in the pathogenesis of amenorrhea in "normal weight" women, a phenomenon long noted in gynecologic case reports69'70 and recently cited as an underrecognized contributor to infertility.7' The episodic loss and regain of weight that is so common among adolescent

girls23 may be far from

benign. In these data, the excess risk associated with weight fluctuation in conjunction with binge-purge behaviors may be a proxy for the most severe forms of binge purging or for extremely rapid weight loss. We have controlled statistically for significant weight loss (4.5 kg) in the past year, American Journal of Public Health 51

36


but these data did not allow us to take into consideration how rapidly these weight changes occurred. Several clinical studies have also found a relationship between weight fluctuation and amenorrhea. Copeland and Herzog16 found that, among normal weight bulimic patients without a history of anorexia nervosa, those who had gained weight from a previously lower weight had a much higher occurrence of amenorrhea than those who had not. Kreipe et al.72 found a similar association between weight fluctuation and menstrual irregularity in women with subclinical eating disorders. They suggested two possible explanations: (1) these women have a natural weight setpoint that is higher than the weight considered normal on standardized tables; and (2) these women embark on unrealistic "crash" diets in which rapid weight loss (which is only to be regained) disrupts the menstrual cycle. A third possibility, proposed by Devlin et al.,62 is that weight fluctuation per se may influence hypothalamic-pituitary-ovarian axis functioning. The risk associated with a simple gain of 4.5 kg or more may reflect weight "rebound" in girls who attempted weight control. This possibility is suggested by the observation that a gain of 4.5 kg was more than would be expected from normal growth tables for girls aged 13 to 18. In addition, girls who had gained weight but had not engaged in any weight control behaviors were at a low risk for secondary amenorrhea (5/103 = 4.9%). A simple weight loss of 4.5 kg or more in the absence of regain or binge-purge behavior was not a strong risk factor for secondary amenorrhea, except among girls at very low relative body weight. In this adolescent population, cigarette smoking was associated with secondary amenorrhea. Previous studies in adults have found cigarette smoking to be associated with higher rates of physician-attended menstrual disorders,73 infertility,74 low birth weight in offspring,75 spontaneous abortion,76 and early menopause.77 78 Several biologic mechanisms have been proposed, such as actions on the hypothalamic-pituitary-ovarian axis, a direct toxic effect on the ovary, and alteration of pe-

ripheral estrogen.79 The results reported here suggest that as much as 50% of cases of secondary amenorrhea among adolescent girls may be related to behaviors that could be modified. Measures of attributable risk should not be interpreted as implying causality in the absence of other evidence for causal52 American Journal of Public Health

ity.50 Nonetheless, these estimates, if cautiously interpreted, can identify the risk groups within a population. Adjusted estimates are also informative even if simple additivity of individual estimates is fallacious. We have interpreted these associations as risks from cross-sectional data on the basis of consistency with clinical studies and biologic plausibility. Finally, a number of caveats are in order. First, it must be emphasized that underlying medical conditions could have been responsible for both weight fluctuations and the comorbid amenorrhea. A medical workup may thus be warranted, depending on the age of the adolescent and other factors.6'7 At the population level, however, 85% of the adolescent girls who report weight changes greater than 4.5 kg also engage in some form of weight control, suggesting that the workup should include a careful review of weight control practices as well as smoking. Second, the failure to find an association between exercise and amenorrhea could be a question of exposure level. Although we examined the risk of secondary amenorrhea in the most extreme exercisers in this population, it is likely that they are not comparable to the career dancers and athletes who have often been the focus of other reports.18,19',2 However, Wilson et al.80 also found no relation between exercise levels and menstrual characteristics in healthy adolescent girls. In addition, a number of reports have suggested that a significant amount of amenorrhea in athletes is related to binging and purg-

ing.19,81 Third, in contrast to clinical studies of menstrual disturbance in women with alcoholism,17 these data did not implicate alcohol as a risk factor after adjustment for confounding variables (e.g., smoking). There are at least two alternative explanations for this lack of association in these data: (1) the exposure to alcohol was not severe enough or long enough to induce secondary amenorrhea in this young population, or (2) purging and smoking were measured more accurately than alcohol consumption in this study. Because either scenario would produce no association, alcohol cannot be exonerated as a risk factor for amenorrhea. Fourth, these data are from self-report questionnaires, which doubtless have limitations. However, other investigators have validated adolescent self-reports of menstruation.36 Our own clinical follow-up of 245 of these girls39 suggests excellent agreement between the question-

naire data and the clinical interview with respect to both amenorrhea and high-risk eating behaviors. Furthermore, any misreporting of the presence of either secondary amenorrhea or high-risk behaviors would most likely bias against finding associations. In summary, girls who engaged in binge-purge behavior were at risk for secondary amenorrhea. Second, weight changes, especially weight fluctuation, also appeared to disrupt menstruation. Finally, cigarette smoking was associated with secondary amenorrhea. These data suggest that evaluation of the adolescent with secondary amenorrhea, in both clinical and research settings, should include a careftl history to assess these potentially modifiable contributory factors. []

Acknowledgments This research was supported in part by National Institute of Mental Health (NIMH) grant 1-RO3-MH40527-01 ("Eating Disorders in Adolescents: An Epidemiologic Study") and Biomedical Research Support Grant (New York State Psychiatric Institute); NIMH grant ST32 MH 16434 and NIMH Clinical Research Center grant 306-07. We thank David Shaffer FRCP (Lond), FRC Psych (Lond), Mark Davies, MPH, and Helen Myers for their invaluable earlier contributions to the study presented here; and Bruce Link, PhD, Diane E. McLean, PhD, Richard Neugebauer, PhD, Steve Ng, MD, Mervyn Susser, MB, BCh, FRCP(E), DPH, and B. Timothy Walsh, MD, for their helpful suggestions with the manuscript.

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Adolescent Smoldng, Weight Changes, and Binge-Purge Behavior

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