Personal exposure to particulate matter-bound toxic elements and ovarian reserve hormone levels – SpringerOpen

 

Report on Environmental Pollutants and Women’s Reproductive Health in the Context of Sustainable Development Goals

Study Population Demographics and Alignment with SDGs

This report analyzes data from a study population of 2,350 women to assess the impact of environmental pollutants on reproductive health, a critical issue for Sustainable Development Goal 3 (Good Health and Well-being) and SDG 5 (Gender Equality). The demographic profile highlights diverse socioeconomic backgrounds, underscoring the importance of SDG 10 (Reduced Inequalities) in understanding health vulnerabilities.

• Total Participants: 2,350 women
• Median Age: 26 years
• Median BMI: 23.8 kg/m²
• Educational Status:
  • Elementary or Illiterate: 29.36%
  • High School: 47.09%
  • University: 23.55%
• Employment Status:
  • Housewives: 36.29%
  • Employees: 38.00%
  • Self-employed: 25.71%
• Health Indicators:
  • Regular Menstrual Cycle: 54%
  • Exposure to Environmental Tobacco Smoke: 20.93%
  • Median FSH Level: 23.32 mIU/mL
  • Median AMH Level: 8.20 ng/mL

Assessment of Environmental Pollutant Exposure and Its Implications for Sustainable Development

The measurement of airborne pollutants provides direct evidence of environmental hazards that challenge the objectives of SDG 11 (Sustainable Cities and Communities) and SDG 3 (Good Health and Well-being). The presence of these potentially toxic elements (PTEs) in the environment necessitates action towards SDG 12 (Responsible Consumption and Production) to control pollution at its source.

Concentration of Particulate Matter-Bound Potentially Toxic Elements (PM-bound PTEs)

Median concentrations of various PM-bound PTEs were recorded as follows:

• Aluminum (Al): 12.10 ng/m³
• Vanadium (Va): 0.27 ng/m³
• Chromium (Cr): 3.64 ng/m³
• Manganese (Mn): 0.85 ng/m³
• Cobalt (Co): 0.26 ng/m³
• Nickel (Ni): 1.07 ng/m³
• Copper (Cu): 21.16 ng/m³
• Zinc (Zn): 406.15 ng/m³
• Arsenic (As): 0.33 ng/m³
• Selenium (Se): 0.57 ng/m³
• Cadmium (Cd): 0.26 ng/m³
• Mercury (Hg): 0.95 ng/m³
• Lead (Pb): 0.94 ng/m³

Inter-Pollutant Correlations and Source Implications

Correlations between specific PTEs suggest common industrial or environmental sources, highlighting the need for targeted regulatory action under SDG 12.

• Strong positive correlation between Arsenic (As) and Cobalt (Co) (r = 0.48), and Arsenic (As) and Selenium (Se) (r = 0.57).
• Moderate positive correlation between Mercury (Hg) and Lead (Pb) (r = 0.35).
• Moderate negative correlation between Copper (Cu) and Manganese (Mn) (r = -0.42).

Health Impact Analysis: The Threat to Ovarian Reserve and SDG 3

The study’s core findings reveal a direct threat to female reproductive health, a key target within SDG 3. The specific impact on women’s ovarian reserve hormones underscores a gender-specific health vulnerability, making this a crucial concern for SDG 5.

Association between PM-bound PTEs and Follicle-Stimulating Hormone (FSH)

Regression analysis indicated a limited direct impact on FSH levels from most individual PTEs. A marginally significant positive association was noted for Aluminum (Al) (β = 3.77, P = 0.05) in the adjusted model. After Bonferroni correction, no associations remained statistically significant, suggesting that FSH may be less sensitive to these specific exposures compared to other hormonal markers.

Association between PM-bound PTEs and Anti-Müllerian Hormone (AMH)

In contrast to FSH, AMH levels showed significant negative associations with several PTEs, indicating a detrimental effect on ovarian reserve. These findings are a direct challenge to ensuring healthy lives (SDG 3).

1. Chromium (Cr): Showed a strong negative association with AMH (β = -1.16, P < 0.01).
2. Arsenic (As): Demonstrated a significant negative association with AMH (β = -15.42, P < 0.01).
3. Cadmium (Cd): Exhibited a significant negative association with AMH (β = -18.65, P < 0.01).
4. Mercury (Hg): Showed a significant negative association with AMH (β = -4.96, P < 0.01).
5. Lead (Pb): Showed a significant negative association with AMH (β = -4.59, P < 0.01).

These associations for Cr, As, Cd, and Hg remained statistically significant even after Bonferroni correction, confirming their robust negative impact on this key marker of female fertility.

Impact of Combined Pollutant Exposure

Mixture analysis revealed that simultaneous exposure to multiple PTEs has a significant cumulative negative effect on ovarian reserve. This finding reinforces the need for holistic environmental policies under SDG 11 and SDG 12.

• Effect on AMH: A significant negative association was found between the PTE mixture and AMH levels (β = -1.98, P < 0.01).
• Effect on FSH: The association with FSH levels was not statistically significant.

Within the mixture, Cadmium (Cd) and Chromium (Cr) had the most substantial negative effects on AMH levels, while Nickel (Ni) showed a positive effect.

Identifying Vulnerable Populations: A Stratified Analysis for SDG 10

The stratified analysis demonstrates that the health burdens of pollution are not distributed equally, which is a central concern of SDG 10 (Reduced Inequalities). Factors such as education, occupation, and health status modify the impact of PTE exposure.

The Role of Education in Mitigating Harm (SDG 4)

A significant interaction was found between education level and exposure to certain pollutants, linking SDG 4 (Quality Education) to health outcomes. Stronger negative associations between PTEs and AMH were observed among participants with lower education levels for:

• Aluminum (Al)
• Cobalt (Co)
• Cadmium (Cd)

This suggests that education may play a protective role, potentially through higher health literacy or different lifestyle and occupational choices.

Occupational and Domestic Exposure Risks (SDG 8)

The analysis stratified by job type points to varying exposure risks related to work and domestic environments, a key consideration for SDG 8 (Decent Work and Economic Growth) and SDG 5 (Gender Equality).

• Self-employed participants showed potentially stronger associations between Al, Co, and Ni exposure and lower AMH.
• Housewives showed a potential trend of stronger associations between Cd and Pb exposure and lower AMH, highlighting the health risks associated with domestic environments.

Compounding Risk Factors: Environmental Tobacco Smoke and BMI (SDG 3)

The analysis reveals that pre-existing conditions and co-exposures worsen health outcomes, demonstrating the need for integrated public health strategies under SDG 3 that address inequalities (SDG 10).

• Environmental Tobacco Exposure: Participants exposed to secondhand smoke showed stronger negative associations between As and Cd exposure and AMH levels.
• Body Mass Index (BMI): A significant interaction was observed for As and Pb. Women with a BMI ≥ 25 experienced significantly greater reductions in AMH from exposure to As and Pb compared to women with a lower BMI. This indicates that women with higher BMI are a particularly vulnerable subgroup.

Analysis of Sustainable Development Goals (SDGs) in the Article

1. Which SDGs are addressed or connected to the issues highlighted in the article?

• SDG 3: Good Health and Well-being: The article’s primary focus is on the health impacts of environmental pollution. It investigates how exposure to Potentially Toxic Elements (PTEs) in particulate matter affects women’s reproductive health, specifically their ovarian reserve, which is a key aspect of well-being and non-communicable disease prevention.
• SDG 4: Quality Education: The study uses educational status as a critical variable, finding that the negative health impacts of certain pollutants are more pronounced in women with lower education. This connects the goal of quality education to health resilience and environmental justice.
• SDG 5: Gender Equality: By focusing exclusively on women’s reproductive health, the article addresses a specific vulnerability that affects women. The analysis stratified by job type, including “housewives,” acknowledges how different life circumstances and roles can impact health outcomes for women, which is central to gender equality.
• SDG 8: Decent Work and Economic Growth: The research stratifies its analysis by employment status (housewives, employees, self-employed), revealing different levels of exposure and health impacts among these groups. This links environmental health risks to occupational and domestic settings.
• SDG 11: Sustainable Cities and Communities: The core issue is exposure to air pollution (PM-bound PTEs), a major challenge in urban and industrial areas. The study’s findings on the health consequences of poor air quality directly relate to the goal of making human settlements safe and sustainable.
• SDG 12: Responsible Consumption and Production: The pollutants studied (e.g., Lead, Mercury, Cadmium, Arsenic) are often by-products of industrial processes and waste. The article underscores the human health consequences of releasing these hazardous chemicals into the environment, highlighting the need for their sound management.

2. What specific targets under those SDGs can be identified based on the article’s content?

• Target 3.9: “By 2030, substantially reduce the number of deaths and illnesses from hazardous chemicals and air, water and soil pollution and contamination.” The article directly supports this target by identifying and quantifying illnesses (disrupted ovarian endocrine function, reduced ovarian reserve) resulting from exposure to hazardous chemicals (PTEs) in the air.
• Target 3.a: “Strengthen the implementation of the World Health Organization Framework Convention on Tobacco Control in all countries, as appropriate.” The study explicitly considers “exposure to environmental tobacco smoke” as a variable and finds it modifies the health effects of other pollutants, reinforcing the importance of controlling tobacco exposure.
• Target 4.5: “By 2030, eliminate gender disparities in education and ensure equal access to all levels of education…” The article demonstrates that women with lower education experience stronger negative health associations from pollutant exposure (e.g., “stronger associations among participants with lower education” for Al, Co, and Cd), highlighting education’s role in mitigating environmental health risks.
• Target 11.6: “By 2030, reduce the adverse per capita environmental impact of cities, including by paying special attention to air quality…” The research is centered on the adverse health impacts of poor air quality, providing evidence for the urgency of this target.
• Target 12.4: “By 2020, achieve the environmentally sound management of chemicals and all wastes…and significantly reduce their release to air…to minimize their adverse impacts on human health…” The study’s findings on the negative associations between PTEs like Cr, As, Cd, Hg, and Pb and AMH levels serve as a direct measure of the adverse human health impacts from chemical releases.

3. Are there any indicators mentioned or implied in the article that can be used to measure progress towards the identified targets?

• Indicator 11.6.2: Annual mean levels of fine particulate matter (e.g. PM2.5 and PM10) in cities. The article provides direct measurements for the components of particulate matter. It states, “The median concentrations of PM-bound PTEs were as follows: Al 12.10 ng/m³, … As 0.33 ng/m³, … Cd 0.26 ng/m³, … Hg 0.95 ng/m³, and Pb 0.94 ng/m³.” These measurements are a specific form of monitoring air quality.
• Indicator 3.9.1: Mortality rate attributed to household and ambient air pollution. While the article does not measure mortality, it measures morbidity (illness) through biological markers. The “significant negative association between mixture exposure to PM-bound PTEs and AMH levels (β = − 1.98)” and the changes in FSH levels are quantifiable health outcomes that serve as indicators of illness attributable to air pollution.
• Proportion of population with exposure to environmental tobacco smoke. The article provides a precise figure that can be used as an indicator for Target 3.a. It states that “492 individuals (20.93%) reported exposure to environmental tobacco smoke.”
• Indicators of educational attainment and employment status. The article provides demographic data that can be used to track disparities, relevant to Targets 4.5 and 5.4. For instance, “29.36% participants had elementary or were illiterate” and “853 (36.29%) were housewives.” The stratified analysis uses this data to show how health outcomes differ across these groups, making these statistics useful indicators for assessing equity.

4. Summary Table of SDGs, Targets, and Indicators

SDGs	Targets	Indicators
SDG 3: Good Health and Well-being	3.9: Reduce illnesses from hazardous chemicals and air pollution. 3.a: Strengthen implementation of tobacco control.	– Changes in ovarian reserve hormone levels (FSH, AMH) associated with PTE exposure (e.g., “Cr shows a strong negative association with AMH levels… β = − 1.16”). – Percentage of population exposed to environmental tobacco smoke (“20.93% reported exposure”).
SDG 4: Quality Education	4.5: Ensure equal access to all levels of education for the vulnerable.	– Disaggregation of health impacts by educational attainment (e.g., “stronger associations among participants with lower education” for Al, Co, and Cd exposure). – Percentage of participants by education level (“29.36% elementary or illiterate”).
SDG 5: Gender Equality	5.4: Recognize and value unpaid care and domestic work.	– Disaggregation of health impacts by job status, including “housewives” (e.g., “stronger associations with AMH levels among housewives” for Cd and Pb).
SDG 11: Sustainable Cities and Communities	11.6: Reduce the adverse environmental impact of cities, focusing on air quality.	– Annual mean levels of fine particulate matter, measured via specific PTE concentrations (e.g., “Pb 0.94 ng/m³”).
SDG 12: Responsible Consumption and Production	12.4: Achieve environmentally sound management of chemicals and wastes to minimize adverse impacts on human health.	– Evidence of adverse health impacts from chemical exposure (e.g., “significant negative associations” between As, Cd, Hg, Pb and AMH levels).

Source: enveurope.springeropen.com