Mining leachate contamination and subfecundity among women living near the United States-Mexico border

Published: 6 December 2022| Version 2 | DOI: 10.17632/gc9fcwtjvn.2
Contributors:
,
,

Description

Design and sample We conducted a retrospective cohort study on pregnancy cases of women living across the watershed area of the Sonora River, in those municipalities directly affected by the environmental disaster: Arizpe, Banámichi, Huépac, San Felipe de Jesús, Aconchi, Baviácora, Ures, and some villages belonging to the state capital Hermosillo (Molino de Camou, Topahue, San Francisco de Batuc, El Tronconal and San Pedro El Saucito) (Lammers., 2014). In addition, we included Magdalena de Kino as a non-exposed community, whose water supply source is different from the resting municipalities, but shares common climate and ecological characteristics (Figure 1). Participants were first identified by the local health centers and then visited at home, where they were asked to participate before signing the informed consent. Inclusion criteria were women being older than 18 years, planned pregnancy, conception of pregnancy in municipalities considered as exposed and non-exposed in this study after the disaster or before up to 10 years prior, with the possibility of including more than one pregnancy for each participant. Among the criteria for exclusion were having a physical or mental disability to adequately respond the questionnaire or refused to sign the consent. The study sample size had enough statistical power according to the Freedman table (Freedman., 1982), taking into account that previous studies exploring fecundity and metal exposure worked with samples between 41 and 300 pregnancies (Snijders., 2012). The study was approved by either ethical review board of the University of Sonora, Mexico, and the Industrial University of Santander, Colombia. Statistical methods Univariate and bivariate descriptive analysis were made after completing the database, using chi-square, Student’s t, and Mann-Whitney U to test for differences between variables. Fecundability odds ratios (fOR) obtained from discrete time analogue of Cox’s proportional hazard models were used to estimate associations with logistic regression models using the macro dthaz (Dinno., 2011). For multiple analysis, variables included in the model had p<0.25 in the bivariate Wald-test or had effect changes > 20%. Models were adjusted for age at pregnancy, age at first pregnancy, pregnancy order, maternal occupation, father’s occupation, father’s age, and father history of hyperthyroidism. Finally, for each approach to measure exposure (acute, acute plus non-affected zone, and pollution gradient), we developed three models: model 1 included all pregnancies with TTP up to 12 months; model 2 excluded pregnancies with TTP = 1; whereas model 3 only included first time pregnancies in order to control for obstetric history of participants (Idrovo et al., 2005; Weinberg et al., 1994 ). All assumptions and adjustments were evaluated, and Stata 14 was the statistical software used to carry out all the analysis (Stata Corporation, College Station, USA).

Files

Steps to reproduce

Data collection A team of trained senior year medical students from the University of Sonora administered questionnaires to participants from June 8th to 23rd, 2016, which allowed collecting information on sociodemographic data (marital status, ethnicity, migration, education, and time of residence), eating habits (beef, chicken, fish, pork or goat consumption of animals drinking water from the contaminated river), drinking water characteristics (source, availability, and water use for cooking, consuming, recreation, bathing, fishing, crop irrigation and animal watering); occupational exposures to pesticides, solvents, heavy metals, arsenic and other chemical substances, personal history of hypertension, diabetes, hypothyroidism, renal insufficiency, lupus, depressive or psychiatric disorders; coffee drinking habit, smoking and alcohol consumption, and a surrogate approximation of the body mass index at the time of pregnancy (Osuna et al., 2006). Data on gynecologic and obstetric history (menarche age, menstrual characteristics, contraceptive methods use, previous surgeries, sexual transmitted diseases) and father-related information (age, eating habits, occupational and disease history, coffee, smoking and alcohol consumption) was also collected. TTP was ascertained by asking How long did you try having sexual relationships until you get pregnant (in months)? Exposure To deal with the difficulty of measuring exposure to the toxic mixture of the leachate discharge into the river, three different approaches were taken. The first compared pregnancies from women living along the Sonora River occurring in the aftermath of the disaster (exposed to disaster), with those pregnancies that have occurred before the onset of the disaster (non-exposed to disaster) and those of women from Magdalena de Kino (non-exposed zone). This approach allowed to explore for potential acute effects and expected prevalence by including a non-exposed zone, since other toxic releases have occurred in the past contaminating the Sonora River, but never have raised public concerns (Gomez., 2011), we called this approach “acute plus non-affected zone”. In the second approach, in order to analyze acute effects attributed exclusively to the disaster, only pregnancies from resident women along the Sonora River were included, marked as exposed those pregnancies occurred after August 6th, 2014, and unexposed those that have occurred before, we called this approach “acute”. Finally, the third approach classified the exposure concentration-level gradient along the river flow according to the data provided by the official website run by the government (Díaz et al., 2016), where localities at the mid and downstream the watershed reported the highest levels of contaminants, we called this approach “pollution gradient” (Figure 1).

Institutions

Universidad de Sonora, Universidad de Santander, Universidad Industrial de Santander

Categories

River Chemistry, Mining, Contamination

Licence