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European Journal of Sport Studies Publish Ahead of Print DOI: 10.12863/ejssbx3x2-2015x2

Section B doi: 10.12863/ejssbx3x2-2015x2

Age at menarche in Congolese women: relative importance of determinants linked to physical activity and family structure

Lounana Joseph1, Medelli Jean1, Sozina Katuli2, Chukwueke Ihuoma3, W Lawrence Beeson3,4, Zaida Cordero-MacIntyre3,4. 1Exercise Biology and Sport Medicine Unit, University-Hospital-Centre, 80054 AMIENS Cedex 1, France. 2Andrews University. Department of Physical Therapy, Berrien Springs, MI 3Center for Nutrition, Healthy Lifestyle and Disease Prevention, School of Public Health, Loma Linda University, Loma Linda, CA 4 Center for Health Disparities and Molecular Medicine, School of Medicine, Loma Linda University, Loma Linda, CA

Abstract

Objective: To assess the effects of family structure and physical activity on late menarche. Research Methods and Procedures: Retrospectively ages at menarche, family sizes, birth orders and other variables were studied in 238 Congolese women including 90 pre-menarche-trained athletes, 18 post-menarche- trained athletes and 130 non-athletes.

Results: Mean age at menarche was later (p<0.001) in pre-menarche (15.36 + 1.04 yrs) compared to post- menarche athletes (13.93 + 1.03 yrs) or to non-athletes (14.03 + 1.22 yrs), but similar (p>0.4) between these two last groups. Mean birth order or birth order within a family size was higher (p<0.01) in athletes than in non-athletes. Mean family size or sex ratio did not differ between groups. Controlling for the effect of duration of training before menarche abolished family size or birth order slight effect (p<0.05) on age at menarche, while the duration of training substantial effect (p<0.001) on age at menarche persisted after controlling for family size and birth order effects. Regression analysis confirmed that duration of training was a better predictor of age at menarche than family size or birth order in pre-menarche athletes.

Conclusion: Physical activity before puberty seems to be a more important determinant of late menarche than family structure.

Key words: puberty, athletes, Africa, family size, populations.

EJSS Journal 3(2):68-85 - ISSN 2282-5673 Lounana Joseph et al. Age at menarche in ...

Corresponding Author: Zaida R. Cordero- MacIntyre, PhD. Center for Health Disparities and Molecular Medicine, Loma Linda School of medicine. School of Public Health, Loma Linda University, Loma Linda, CA 92350. Phone: (909) 558-1000 Ext: 47172; email: zcordero-macintyre@llu.edu Received: march 2013 - Accepted june 2013

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1. Introduction Compared to non-athletes and the general population, female athletes present a later menarche (Malina et al.,1979; Frisch et al., 1980; Sudhi and Grewal, 1980; Mathur and Toriola 1982; Mesaki et al., 1984; Sharma and Shukla, 1992; Baxterjones et al., 1994, Lounana et al., 2002). Late age at menarche in athletes is generally associated with bone age retardation (Warren, 1980, Weimann et al., 2000) and delay in pubertal elevation of the luteinizing hormone : follicle-stimulating hormone (LH:FSH) ratio (Weimann et al., 2000). Several factors related to genetics, physical training, body composition, hormonal profile, nutritional or socio- economic status, geographical or socio- cultural environment as well as family and psychosocial environment have been implicated in the onset of menarche. Studies of mother/daughter or sister/sister pairs has shown significant correlation with the onset of menarche (Stager et al., 1984; Brooksgun and Warren, 1988; Malina et al., 1994). Regression analysis indicated an association between age at menarche and family size, birth order (Malina et al., 1997) or various conditions of social environment ( Lounana et al., 2002). The explanation of the late menarche among female athletes remains unclear for some authors (Malina, 1983) while other authors (Weimann et al, 2000) implicate intensive physical training, stress due to training and competition, weight loss leading to a low fat mass, hormonal disorders, and high-energy expenditure coupled with inadequate dietary intake. To date few studies have separately evaluated the effects of training and family structure (Mota and Silva, 1999, Bagley et al., 2006). In addition, most of the population studies were Caucasian (European or American), showing exclusive family and specific socio-

cultural characteristics (Wronka and Pawlińska-Chmara, 2005, Anh et al. 2013, Mota and Silva 1999). Our study focused at examining various determinants of age at menarche in a Black African population from Congo-Brazzaville and to evaluate the effects of factors linked to the presence or absence of a regular physical activity and its duration before menarche, simultaneously with the family structure or composition.

2. Materials and methods

Participants. This survey was carried out in May/June 1998 with 238 premenopausal African women (mean age 23.9 ± 4.5 years) from Congo-Brazzaville. All participants were students or young workers whose birth, childhood and puberty occurred during a relatively peaceful period of the country’s history, i.e. without war, starvation and migrations that could influence the onset of menarche (Prebeg and Bralic, 2000). The sample included 90 female athletes who started their physical training before menarche (pre-menarche athletes), 18 athletes who started their physical training after menarche (post-menarche athletes) and 130 subjects having no regular physical activity or athletic training (non-athletes). The recruited 108 athletes came from six sports: 50% from handball (HB), 18% from running (RUN), 15% from soccer (FB), 8% from volleyball (VB), 7% from basketball (BB) and 2% from gymnastics For eighty percent of the individuals (HB, BB, FB and VB), training often included warm-up exercises, endurance and power exercises, interval training, jumps, stretching and specific resistance exercises. However, most of the training time was dedicated to specific exercises (i.e. ball control, dribbling, passing, shooting, defence, placement, etc.) and above all to a match lasting about 2 hours per training session. All the RUN athletes were

EJSS Journal 3(2):68-85 - ISSN 2282-5673 Lounana Joseph et al. Age at menarche in ...

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middle-distance or distance runners. All athletes trained about 20 to 30 hours per week with at least five out of seven days of training. The gymnasts complied with Olympic gymnastics program. The study was undertaken with the personal consent of all the participants. This survey was approved by the administrative authorities of the “Permanent Research Institutions” of the “Higher Institute of Physical Education and Sport” (ISEPS) and under the care of Marien Ngouabi University (UNMG), of the Ministry of Education and the Ministry of Youth and Sports of Congo- Brazzaville. Inclusion criteria. Participants had to be: “Bantu” ethnic or cultural origin, with childhood and teenage years in Brazzaville or its surroundings, from a non-broken monogamous family structure notably with the father at home, and satisfying physical and mental health criteria. To avoid a possible bias in the counting of non-pubescent girls, the individuals were selected at the date of the study with a civil age of over 18.5 years, which is the maximum age at menarche generally observed among the Congolese population (Louisiana et al., 2002). Other criteria were the possession of a sport licence, an intensive training of 20 to 30 hours per week with at least 5 out of 7 days of training, a high level of national or international competition certified by an individual’s list of achievements or by a competition program of a sport club. To avoid any bias linked to a possible concomitance between date of entry into sport and date at menarche, and to increase the separation between groups of participants, we selected only the pre- menarche athletes who started training at least 1.0 year before menarche and the post- menarche athletes who started training at least 1.0 year after menarche. Non-athletes were those with total absence of regular physical training of any nature and duration. Exclusion criteria. Not satisfying the inclusion requirements, detection of a serious pathological, nutritional or familial medical history, inability to memorize dates or miscellaneous events of family and personal

life, use of contraceptives, belonging to a polygamous family or to an ethnic group practising traditional rites of puberty initiation and having less than 1.0 year of training from the date of menarche. Variables and measurements. Retrospective method with direct interviews based on a pre- tested questionnaire with an estimate of 90 % of exactitude of recall (Lounana et al. 2002). Each participant was requested to give information as precise as possible concerning: date of birth, date of menarche, date of beginning of regular sport training, number of children in the family (family size), number of boys and girls in the family, birth order among siblings, family’ standard of living and participant’ school level. The sex-ratio was calculated in each family as number of boys divided by number of girls. The family size was examined either as a continuous variable or was divided into five classic groups: size A (1-2 children), size B (3-4 children), size C (5-6 children), size D (7-8 children) and size E (over 8 children). The subject’s school level was taken into account to minimize a possible bias in the ability of understanding questions or memorizing dates and events. Six stages described this parameter: school non- attendance (stage 1), half and end of primary school (stages 2 and 3), half and end of secondary school (stages 4 and 5), at least one year at university (stage 6). To control any bias related to the social status, the family’s standard of living was especially focused on the childhood and teenage years of the individuals and then assessed by a classification drawn from the Warner socio- metric scale (DeLandsheere, 1972). This classification was based on the examination of parameters obtained during the interview (father’s and mother’s occupations, type and location of dwelling place, living comforts, type of school, means of travel, neighbourhood). These data were classified into six levels as; the relatively rich and prosperous class (levels 5 and 6), the middle class (levels 3 and 4) and the lower class (levels 1 and 2). Civilian age, age at menarche and age at

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beginning of regular sport training were calculated from the reported dates. An exact date of menarche was reported by 59% of the participants. For 30% of the participants in whom the date was not precise within a quarter, the middle of the period was considered as the annual fraction. In the particular case whose age at menarche was only reported between two consecutive birthday dates (11% of the individuals), it was put at the date of the 1st birthday plus 0.5 years (Livson, 1962). Individual, free, recreational sport is not popular yet among women of Congo-Brazzaville. Though the recruiting criteria to clubs are not known, it is observed that the first selection of a sport is generally definitive. “Age at beginning of regular sport participation” means “age at which formal and specialized athletic training is initiated”. The reported dates at beginning of regular sport training were easily checked against sport licences and clubs registrations. These dates were obtained with 100% accuracy in all athletic participants (athletes without sport licence have been excluded as indicated above). For analysis purpose, the “duration of training before menarche” variable included values observed in pre- menarche athletes whereas a value of zero was attributed to the post-menarche athletes and the non-athletes. Statistical analysis. Analysis of variance (ANOVA) was used for the comparison of more than two group means after testing for normality assumptions using Kolmogorov- Smirnov test and Wald-Wolfowitz test respectively. Binary comparisons were made using the Games-Howel post-hoc test. Multiple and binary non-parametric comparisons of the means of the non-paired groups were performed with the Kruskall- Wallis H and Mann-Whitney U tests. To study the effect of the variables, we carried out simple or multiple regression and covariance (ANCOVA) analyses based on the General Linear Modelling procedures, as well as an analysis of logistic regression. Correlations were evaluated using a Pearson classical or a Spearman non-parametric test. All analyses were carried out with statistical

analysis software packages (SPSS for Windows, v23, SPSS Inc., and STATVIEW 5, SAS Institute Inc. USA). Statistical significance was set at p < 0.05.

3. Results Figure 1 shows the age at menarche distributions. Table 1 summarizes the subsamples characteristics. The 3 groups of subjects did not differ for any of the variables studied except for age at menarche, birth order and birth order within a family size. The mean birth order or birth order within a family size was lower (p < 0.01) for the non- athletes compared to the two groups of athletes who were statistically similar on this point. The mean age at menarche reported by the 90 pre-menarche athletes (15.36 + 1.04 years) was significantly later (p<0.001) compared to the 18 post-menarche athletes (13.93 + 1.03 years) or the 130 non-athletes (14.03 + 1.22 years), while no difference (p > 0.4) was observed between these two last groups (Table 1). Using an ANCOVA model and introducing duration of training variable significantly lowered the difference between groups for age at menarche (F=1.98 vs. 38.7) at a non- significant level (p > 0.1 vs. p < 0.001), whereas no effect was observed by introducing any other variable in the model. In pre-menarche athletes, there was no relation between duration of training before menarche and age at beginning of regular sport training (p > 0.9). In addition, the duration of training significant effect on age at menarche did not change even if duration of training was adjusted for age at beginning of regular sport training. Tables 2 and 3 summarize the correlation analysis. Age at menarche was strongly (p<0.001) correlated with duration of training in pre-menarche athletes (r = 0.38). Birth order was significantly correlated with family size in pre-menarche athletes (r = 0.53), post- menarche athletes (r = 0.85) and non-athletes (r = 0.47). Table 4 summarizes the results of linear regression analysis for the prediction of age at menarche. The main effect of duration of training on age at menarche was significant

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(p<0.001) in the pre-menarche athletes (slope β = 0.24) and in the total sample (β = 0.38). The coefficient of 0.38, which takes into account the 0 value of duration of training in the general population, indicates that menarche is late by 4.56 months for each year of training before the menarche. The individual regression effect of family size or birth order on age at menarche was not significant. However, there was a slight but significant effect (p<0.05) of family size when controlling statistically for birth order (β = -0.08), and also a slight effect of birth order when controlling for family size (β = 0.10) with similar magnitudes in pre- menarche athletes and in the total sample. There was a significant effect (p<0.001) of duration of training on age at menarche when controlling for family size or/and birth order with similar magnitudes in the pre-menarche athletes (β = 0.27) as well as in the total sample (β = 0.38). In the population studied, the upper limit of variation including 95% of confidence interval for the average age at menarche was calculated as 14.73 years. Table 5 shows the subjects distribution according to this threshold value: 73% of pre-menarche athletes, 39% of post-menarche athletes and 35% of non-athletes had a late menarche (>14.73 years). The logistic regression analysis indicated that “presence” (but not “absence”) of training before menarche is linked to a higher risk of late menarche (Odds-ratio = 0.228; p<0.001).

4. Discussion Menarche is an event that is generally well remembered by women. Its recall precision frequently goes beyond 80% in developed countries (Koprowski et al., 2001; Must et al., 2002). It remains unproven if a similar level of recall can be observed in less developed countries. We therefore recognize that there is an important limit in the retrospective nature of the information used in this study. However, several potential bias factors were taken into consideration in the analysis of the results (tables 2 and 3) as well as in the methodological approach.

Variability of age at menarche in African Black populations Black Africa is constituted of about forty countries still subjected to several calamities (famine, war, poverty, malnutrition) as well as endemic diseases such as malaria or sickle cell illness, which are possible factors interfering with the normal growth and maturation, and then with the occurring of the menarche in female teenagers. The menarcheal age in Black populations of Africa has been studied in relatively large samples (see Table 6), which unfortunately have been seldom exploited for a simultaneous analysis of determinants. Compared to Western Caucasian populations (Frisch et al., 1980; Baxterjones et al., 1994; Malina et al., 1994; Malina et al., 1997), the mean menarcheal age in African Black populations generally appears higher by 1.5 to 2 years. This difference is linked to the conditions of life and nutrition, and to the socio-economical and cultural status of the populations (Morabia et al., 1998; Thomas et al., 2001). In most of Black African countries, the menarche occurs at a mean age varying between 13 and 16 years. The lowest values of this range are generally found in countries that are relatively more industrialized (i.e. South Africa, Nigeria), while higher values are found in less developed countries (see table 6). A trend towards lower values has been described in some countries but this trend seems to be totally undetectable in the poorest countries (Padez, 2003). In African populations the mean menarchal age is higher for rural or suburban compared to urban communities (+0.6 to +1.5 years) (Pasquet et al. 1999; Pawloski 2002; Oduntan et al. 1976), for the poorest socio-economic strata compared to richest (~ +0.8 years) (Attallah, et al. 1983), for certain ethnic groups (Adadevoh et al., 1989), especially for Black compared to White South Africans (~ +1.0 year) (Henneberg and Luow,1995; Cameron and Getz, 1997), and for girls suffering from homozygous sickle cell disease compared to controls (~ +1.2 year) (Modebe, 1987; Frisch et al. 1981; M’Pemba-Loufoua et al. 2001). The relation between physical

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activity and menarche has not been extensively studied in Sub-Saharan Africa. The mean menarcheal age value observed in the current study in the non-athletes population of Congo-Brazzaville (14.0 ± 1.2 years) is similar to a previously reported value (13.92 ± 1.4 years) from the same population Lounana et al., 2002). It is also comparable to data of general populations from Black African countries of similar living standards (see table 6). Late menarche in athletes and non athletes Our first finding is that a later menarche commonly characterise female athletes in comparison with non-athletes. This phenomenon is particularly observed in female athletes who started training before puberty, while female athletes who started training after puberty exhibit a pubertal chronology identical to the non-athletes or the general population. This result is in total agreement with many other studies (Malina et al., 1979; Frisch et al., 1980; Mesaki et al., 1984; Sharma and Shukla, 1992; Baxterjones et al., 1994; Lounana et al., 2002; Frisch et al., 1981; Vadocz et al., 2002). Since it is not known whether menarche is delayed or just late the term “late menarche” is suitable to use (Stager et al, 1984. This pubertal dysfunction has been noted in individual sports as well as in team sports. Female swimmers are also vulnerable to a later puberty associated with exercise training (Baxterjones et al., 1994; Frisch 1981; Constantini and Warren, 1995; Astrand et al, 1963). In the Congolese population, each group is affected by cases of late menarche (>14.73 years). We can consider that the general population normally include about 1/3 of cases of late menarche (table 5). It is also suggested that they could be a result of combination of these two factors since the effect of thinness on late menarche doesn’t appear alone, only together with the effect of intensive physical activity (Vandenbrouke, 1982). The effect of selection would be associated with the nature of sport (Malina 1983). Girls with similar morphology and physical abilities have a tendency to converge to the

same type of sport. In some sports like gymnastics or ballet dance, recruitment at an early age could favor girls with physical characteristics, such as thinness or low body mass and fat, associated with late menarche (Beunen et al., 1994). Attempting to minimize an effect possibly due to the nature of sport on age at menarche, our samples of athletes were taken from sports whose initial recruitment methods were well defined and not suspect of bias (Lounana et al., 2002; Lounana et al., 2000). Our results did not show any difference for the mean age at menarche according to the nature of sport (p>0.17). Effect of duration of training before menarche In the current study, the effect of training duration on age at menarche appeared to be unaffected by the effect of age at beginning of regular sport training. Notably, the estimation of a 4.56 months late menarche for each training year before menarche is in agreement with the 5 months late previously reported both for Congolese population (Lounana, 2002) and American population (Frisch et al., 1981). In addition, we noted that 1/3 of the pre-menarche athletes who did not have a late menarche (>14.73 years) displayed a mean training time significantly lower compared to the 2/3 of the individuals whose menarche was late (2.3 + 0.93 vs. 3.5 + 1.8 years; p<0.01). This is in agreement with another study (Mesaki et al, 1984) which found that intensive physical activity (and not moderate) is commonly associated with a late menarche in girls who started training before puberty. These results suggest a dose-response characteristic of the training effect associated with late menarche. Hard physical exercise and high level of competition result in training stress that is generally associated with changes in fat/leanness ratio and disturbances in metabolic and hormonal levels (Weimann et al., 2000; Toriola, 1988; Loucks, 1990). In female gymnasts, a close relationship has been found between the “entry age” into high intensity training and alterations in peri- pubertal development, such as a delay of LH:FSH ratio of 2.3 years, a bone age retardation of 2.5 years, as well as a lateness

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in age at menarche of 2.5 years (Weimann et al., 2000). Birth order and family size values In the Congolese as well as in the American population (Malina et al., 1997) women atheletes exhibit a higher average birth order compared to non-athletes. However in the Congolese population, the average birth order does not differ between pre-menarche and post-menarche athletes. Furthermore, birth order is positively correlated to duration of training (table 4). Thus in the Congolese population, birth order would appear as a selection factor for sports activity independent of puberty maturation. The higher birth order among siblings might increase chances of a girl to be more independent and free in the family, since a particularly important barrier against physical activity for women is time constraints (Tappe et al., 1989). Time dedicated to family chores by young African girls seems to be significant. The mean values of family size in Congo- Brazzaville population are in agreement with the official statistics between 1965 and 1998 (United Nations, 2002). Congolese population and Western reference populations display, for family size, several points of divergence which could explain the differences seen in the effect of this variable on age at menarche. We observed higher family size among Congolese population compared to European or American populations. Family size values were identical between athletes and non- athletes in Congolese population.

Family size and birth order effects on age at menarche The effect on age at menarche of birth order adjusted for family size appeared relatively null (β = 0.01 to 0.04) in the American non- athlete university students (Malina et al., 1997; Wellens et al., 1992). This is also observed in the Congolese non-athletes and Post-menarche athletes (β = -0.02 to 0.02; tables 1 and 4). On the contrary in athletes, this effect is significant and almost of similar (Pillai, 1995) magnitude among the different populations. However, in Congolese Pre- menarche athletes this effect is positive (β =

0.10), whereas it is mostly negative (β = -0.07 to –0.19) in English university athletes (Malina et al., 1979) or American athletes (Malina et al., 1997). There was a weaker inverse relationship between family size and age at menarche adjusted for birth order in the Congolese pre- menarche athletes and the total sample (β = - 0.05 to –0.08) compared to American university student and Olympic athletes (β = 0.16 to 0.22; (Malina et al. 1997; Wellens, 1992). The family size effect observed more often is generally in a positive direction, and its magnitude turns out to be weaker for the non-athletes (β = 0.08 to 0.15) than for athletes (β = 0.12 to 0.22) from America, Belgium (Malina et al., 1994; Wellens et al., 1992), Romania (Stukovsk et al., 1967), Italy (Gallo, 1977) or United Kingdom (Malina et al., 1979). How family size and birth order may generate positive or negative effects on age at menarche remain to be elucidated. One typical hypothesis of the probable mechanism of the positive effect of family size leading to a late menarche is based on nutrition, health, and the assumption that the more the family size increases, the larger the number of mouths to feed, and thus the higher the risk of disease and malnutrition possibly leading a girl to remain below the physique necessary for the onset of menarche. Another hypothesis (Malina et al., 1997) is that the effect of increase in family size can show-up earlier, related to the frequency of births, the reduction and repetition of which would have unfavourable cumulative effects on the mother/fetus relationship as well as on the conditions of fetal development. These processes can affect the initial programming of maturation during the sensitive period of fetal development. The inverse relation of family size and age at menarche could be linked to specificities of the Congolese population family structure and socio-cultural context and could be considered as an indirect negative effect generated in the family life by an increase in family size associated with an amplification of family stress factors, such as family

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conflicts or unstable home environments, which are capable of generating an early menarche (Graber et al, 1995; Malina, 1983).

Duration of training and family size - birth order relationships Duration of training appears to be a confounding factor for the effects of family size and birth order on age at menarche (tables 2 and 4). However, when controlled for duration of training, the effect of family size or birth order on age at menarche was removed (table 4, figure 2), while the duration of training effect on age at menarche persisted after controlling for family size and birth order effects (table 4). Furthermore, in agreement with other reports (Malina et al, 1997), this study reveals that the effects of family size and birth order, once mutually adjusted, are systematically present in athletes but neither in non-athletes nor in the general population. These facts suggest that family size and birth order effects would be associated with sports activity, which seems to be itself a prime factor. The maximum level of age at menarche variability predicted by duration of training effect (R² = 0.25) is around 8 times higher than the negligible one by family size or birth order (R² = 0.03). A longitudinal survey of genetic behaviour carried out with 1,338 American parental couples (Doughty and Rodgers, 2000) indicated that around half of the variability of the age at menarche could be attributed to genetic factors (R² = 0.54) and almost half to non-shared environmental influences. However in this study the 25 % rate of prediction due to duration of training would account for around half of the age at menarche variability predicted by environmental factors. Thus the effect of physical activity before menarche appears to be significant.

The relationship observed between duration of training and family size-birth order complex is a new finding. This relation is consistent with the hypothesis that freedom of action allowing a girl to escape more often from family chores for personal activities could increase as the family size increases, the elder daughter belonging to a larger family having possibly the highest freedom. Study Limitations Due to limitations during enrolment the study ended up with uneven sample size for the two groups compared. This may pose some problems as these may end up with unequal variance which violates some of the assumptions of the tests used, particularly the regression analysis. However for the t-test the uneven variance is accounted for in the SPSS since there is an option for equal variance not assumed.

Conclusion. This study showed that, in Congolese female athletes, late age at menarche is associated with intensive physical activity initiated before puberty. The effects of family size and birth order on age at menarche appear to be unsteady, unlike the clearly apparent effect of duration of physical activity. Family size and birth order are not good predictors of the menarche in the Congolese population. Surprisingly, these two variables appear to be associated with the sports activity variables. It is suggested that the effect of physical activity should be taken into account when examining the relative contribution of familial and environmental factors implicated in the late menarche of female athletes.

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Acknowledgements.

The authors would like to thank all the Congolese women who kindly participated in this study. Special thanks for help in data collection go to Lambert Bakala, Bernard Batambika, Pierre Bazolo and François Mbemba, lecturers at ISEPS (Marien Ngouabi University of Congo–Brazzaville), Frederic Campion for his assistance and Emmanuel Ojo for editing.

Table 1. Ages at menarche (AMC), family sizes (FS), birth orders (BO), duration of training before menarche (DTBM) and possible bias variables § in groups of participants

Mean age at menarche (AMC, years) differed between pre-menarche and post-menarche athletes or non-athletes (ANOVA p<0.001), but not between post-menarche athletes and non-athletes (p>0.4). Mean birth order (BO) or birth order within a family size (BO/FS) differed between each group of athletes and the aon-athletes (Kruskall-Wallis and Mann-Whitney p<0.01). No difference (p>0.05) was observed between groups for mean family size, civilian age (CVA, yrs), sex ratio, school level (SL) or family-economic level (FEL). DTBM is duration of training before menarche (years).

Group N Mean SD Min Max Median

AMC Pre-menarche athletes 90 15.3 1.04 13.7 18.2 15.2 Post-menarche athletes 18 13.9 1.03 11.5 15.5 13.9 Non-Athletes 130 14.0 1.2 10.0 16.5 14.1

FS Pre-menarche athletes 90 6.7 2.4 2 14 6 Post-menarche athletes 18 7.4 3.8 2 17 7 Non-Athletes 130 6.7 2.5 1 14 7

BO Pre-menarche athletes 90 4.0 2.4 1 10 4 Post-menarche athletes 18 5.1 2.8 1 11 5 Non-Athletes 130 3.0 2.0 1 9 3 §BO/FS Pre-menarche athletes 90 0.6 0.3 0.1 1 0.6

Post-menarche athletes 18 0.7 0.2 0.4 1 0.7 Non-Athletes 130 0.5 0.3 0.1 1 0.5

DTBM. Pre-menarche athletes 90 3.2 1.7 1.2 9.7 2.8 §CVA Pre-menarche athletes 90 24.3 4.7 19.0 36.7 23.5

Post-menarche athletes 18 23.6 4.8 19.1 36.7 22.0 Non-Athletes 130 23.7 4.3 19.0 38.1 23.0 §Sex ratio Pre-menarche athletes 90 1.1 0.7 0.2 4 1

Post-menarche athletes 18 1.1 0.5 0.5 2 1 Non-Athletes 130 1.2 1.4 0.3 7 1 §SL Pre-menarche athletes 90 4.1 1.3 2 6 4

Post-menarche athletes 18 4.7 1.0 3 6 5 Non-Athletes 130 4.3 1.3 1 6 4 §FEL Pre-menarche athletes 90 2.6 0.4 1.5 3 2.5

Post-menarche athletes 18 2.5 0.4 1.5 3 2.5 Non-Athletes 130 2.6 0.4 1 3 2.5

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Table 2. Pearson correlations between age at menarche (AMC), family size (FS), birth order (BO) and duration of training before menarche (DTBM)

N

AMC

FS

FS ctrl BO

BO ctrl FS

AMC. Pre-menarche athletes 90 -0.11 0.20* Post-menarche athletes 18 -0.21 -0.03 Non-Athletes 130 -0.05 0.04

FS. Pre-menarche athletes 90 -0.01

Post-menarche athletes 18 -0.41

Non-Athletes 130 -0.30

BO. Pre-menarche athletes 90 0.14 0.53 **

Post-menarche athletes 18 -0.04 0.85 **

Non-Athletes 130 0.05 0.47 **

DTBM. Pre-menarche athletes 90 0.38 ** 0.07 -0.03 0.08

N AMC FS BO DTBM

CVA Pre-menarche athletes 90 0.21 0.20 -0.18 0.05 Post-menarche athletes 18 -022 0.11 0.15

Non-Athletes 130 -0.06 -0.06 -0.15

Sex ratio Pre-menarche athletes 90 -0.25 0.03 0.05 0.22 Post-menarche athletes 18 -0.65 0.65 0.88

Non-Athletes 130 0.06 0.04 -0.07

SL Pre-menarche athletes 90 0.15 0.24 0.01 0.03 Post-menarche athletes 18 0.21 0.44 0.18

Non-Athletes 130 0.002 0.15 -0.04

FEL Pre-menarche athletes 90 0.25 0.02 0.22 0.04 Post-menarche athletes 18 0.07 0.09 0.37

Non-Athletes 130 0.004 0.03 0.19 No significant correlation was observed. CVA is civilian age; sex ratio is number of boys divided by number of girls; SL is school level; FEL is family socio-economic level.

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Table 4. Standard error of estimate (SEE) and coefficients of simple and partial linear regressions (GLM procedures) performed for the prediction of age at menarche

Pre-menarche athletes (N = 90)

Total sample (N = 238)

AMC predictors Coef. SEE R2 Coef. SEE R2

Family size (FS) 0.00 0.05 0.00 -0.03 0.03 0.00

Birth order (BO)

Duration of training before

0.06 0.05 0.02 0.05 0.04 0.01

menarche (DTBM) 0.24 ** 0.07 0.15 0.38 * 0.04 0.25

FS / BO -0.08 * 0.06 0.03 -0.08 * 0.04 0.02

BO / FS 0.10 * 0.06 0.03 0.10 * 0.04 0.02

FS / DTBM 0.01 0.05 0.17 -0.03 0.03 0.27

DTBM / FS 0.27 * 0.07 0.17 0.38 ** 0.04 0.27

BO / DTBM 0.08 0.05 0.20 0.02 0.03 0.26

DTBM / BO 0.26 ** 0.07 0.20 0.38 ** 0.04 0.26

DTBM / FS / BO 0.26 ** 0.07 0.21 0.38 ** 0.04 0.27

FS / BO / DTBM -0.05 0.06 0.21 -0.05 0.04 0.27

BO / FS / DTBM 0.11 0.06 0.21 0.05 0.04 0.27 The dependant variable in the model was age at menarche (AMC). The independent variables were family size (FS), birth order (BO) or/and duration of training before menarche (DTBM) analysed by simple (i.e. FS) or multiple regression test (i.e. FS / BO). Significant effects: *p<0.05; **p<0.001.

Table 5. Logistic regression between training option and the occurrence of late menarche in each group of subjects

Training before menarche

Late menarche (>14.73 years)

Not late (≤ 14.73 years)

Total

option N ( %) N ( %) N ( %)

Pre-menarche athletes Yes 66 (73) 24 (27) 90 (100)

Post-menarche athletes No 7 (39) 11 (61) 18 (100)

Non-athletes No 46 (35) 84 (65) 13 (100) Pre-menarche athletes exhibit about twofold more cases of late menarche (p<0.001) than Post-menarche athletes or Non-athletes. Presence (Yes) and not absence (No) of training before menarche is associated to a higher risk of late menarche (Coefficient = -1.478 ; Standard Error = 0.286 ; Odds-ratio = 0.228 ; Confidence interval of 95% = 0.130-0.400 ; p<0.001).

79

Table 6. Mean (± SD) or median* age at menarche in some Sub-Saharan countries of Africa Country Reference Sample N Method Age at menarche (yrs) Cameroon Pasquet et al. 1999

Urban schoolgirls

205

Status quo

13.18 ± 1.08

Suburban schoolgirls 505 Status quo 13.98 ± 1.55 Rural schoolgirls 201 Status quo 14.27 ± 1.65

Congo-Brazzaville Lounana et al. 2002

Elite Handball athletes

50

Recall by interview

15.36

± 1.57

High-school Handball athletes 61 Recall by interview 14.74 ± 1.06 M’Pemba-Louufoua

Non-athletes (controls) 214 Recall, random sampling 13.92 ± 1.4

et al. 2001 Patients with sickle cell disease 72 Prospective 15.2 ± 1.6

Ghana Adadevoh et al. 1989

Suburban schoolgirls

2087

Status quo

13.98

± 1.42

Kenya Rogo et al. 1987

Urban female students

452

Recall by questionnaire

14.4

± 0.7

Leenstra et al. 2005 Rural schoolgirls 928 Status quo, random way 15.0 *

Mali Pawloski 2002

Urban adolescent girls

323

Status quo

14.1

± 0.61

Rural adolescent girls 407 Status quo 14.7 ± 0.59

Mozambique Padez 2003

Urban schoolgirls

396

Recall by interview

13.91

± 1.29

Urban schoolgirls 357 Status quo 13.20 ± 1.18

Nigeria Oduntan et al. 1976

Urban schoolgirls

2029

Status quo

13.70

± 0.03

Mathur & Toriola 1982

Rural schoolgirls Pre-menarche athletes

328 272

Status quo

Recall by questionnaire

14.50 14.41

± 0.09 ± 1.67

Post-menarche athletes 146 Recall by questionnaire 13.53 ± 1.63 Elite Athletes (combined sample) 418 Recall by questionnaire 14.13 ± 1.59 Non-athletes (controls) 512 Recall by questionnaire 13.57 ± 1.52 Modebe 1987 Patients with sickle cell disease 30 Status quo 14.5 ± 1.13 Urban schoolgirls (controls) 2174 Status quo 13.3 ± 1.09 Thomas et al. 1990 Female students 768 Recall by questionnaire 13.4 ± 1.4

Ihekwaba 1994 Abioye-Kuteyi et al. 1997

Rural adolescents and adults Urban schoolgirls

435 352

Prospective

Recall, random sampling

14.2 13.94

± 2.5 ± 1.31

80

Table 6. Mean (± SD) or median* age at menarche in some Sub-Saharan countries of Africa (cont’d)

Country Reference Sample N Method Age at menarche (yrs) Senegal Simondon et al. 1997

Rural adolescent girls

1126

Status quo

16.1

± 1.2

Garnier et al. 2003 Rural adolescent girls 331 Status quo 15.5 ± 0.5

Somalia Gallo 1975

Adolescent girls from all regions

524

Recall by questionnaire

14.78

± 0.07

South Africa Henneberg 1995

Urban Coloured girls

258

Recall by interview

13.30

± 1.32

Cameron & Getz 1997 Rural Black schoolgirls

190

Status quo

14.03

± 1.25

Sudan Attallah et al. 1983

Urban schoolgirls from rich strata

457

Status quo

13.35

± 0.14

Urban “ from median strata 458 Status quo 13.85 ± 0.15 Urban “ from poor strata 457 Status quo 14.06 ± 0.18

Zambia Pillai 1995

Urban schoolgirls

525

Status quo

14.2

± 1.4

Gillet et al. 2004 Suburban schoolgirls 774 Status quo 14.8 ± 1.2

Zimbabwe Mbizvo et al. 1995

Suburban adolescent pupils

872

Recall by questionnaire

13.5

± 1

Nilses et al. 1997 Rural adolescents and adults 1213 Recall by interview 15.0 *

Figure 1. Percentages of participants per group of age at menarche in pre-menarche (Pre-M) athletes, post-menarche (Post-M) athletes and non-athletes.

81

82

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