Study of anaemia in pregnancy and low birth weight in fluoride endemic area of Western Rajasthan: a cohort study

Introduction

Maternal and neonatal mortality rates are high in developing countries (Beck et al., 2010). Low birth weight (LBW) is the most common cause of neonatal mortality (Eshete et al., 2019; Watkins et al., 2016). The birth weight of newborn babies is a significant indicator of a child’s vulnerability to the risk of childhood diseases and chances of existence (Alemayehu et al., 2020). The World Health Organization (WHO) defines LBW as weight at birth less than 2.5 kg (“WHA Global Nutrition Targets 2025: Low Birth Weight Policy Brief,” n.d.). LBW may be an outcome of either preterm birth or retarded fetal growth. According to a report by UNICEF on “The State of the World’s Children 2008”, the highest percentage (43%) of LBW babies below five years of age are in India. The prevalence of LBW babies in South Asia is 42%, in developed countries 35%, in developing countries 26% and 25% in the rest of the world (Sachdev, 2001).

India has been documenting the serious problem of anaemia in pregnancy, resulting in LBW (Batista Filho et al., 2008; Rahman et al., 2016; World Health Organization, 2015). The Ministry of Health and Family Welfare, Government of India, has launched the National Anaemia Prophylaxis Programme to combat anaemia. The decision to supplement iron along with folic acid (iron (60 mg) and folic acid (500 μg) orally for 90 days) to pregnant women visiting antenatal clinics (ANCs) during the first and second trimesters was implemented across the country. The Indian Council of Medical Research (ICMR) conducted a study in 11 Indian states in 1985–86 and discovered that the intervention did not affect pregnant women’s haemoglobin (Hb) levels. This resulted in the power of iron and folic acid tablets increasing to 100 mg and 500 mg, respectively, which has been popular since 1992 (Susheela et al., 2010).

However, despite so many interventions to reduce anaemia during pregnancy, expected results have not so far been obtained (Beard, 2000; Kapil et al., 2019; Vijayaraghavan et al., 1990). So, another factor needs to be investigated, and one such factor is fluoride intake. Fluorosis, an underestimated and sometimes debilitating condition, is being caused by high levels of fluoride in food and contaminated groundwater in India (Bello, 2020). Fluoride causes serious destruction to the gastrointestinal mucosa by destroying microvilli resulting in non-absorption of nutrients from the regimen (Das et al., 1994; Dhar and Bhatnagar, 2009; Susheela et al., 2018). Fluoride also destroys erythrocytes, thereby contributing to the loss of Hb and anaemia. Interestingly, fluoride exposure during pregnancy was not significantly associated with fertility or birth outcomes, especially among women living in areas with levels of fluoride consistent with water fluoridation (Goodman et al., 2022). A study conducted in the United States discovered that greater water fluoride concentrations were connected with a 3.3-month earlier age of menarche (Malin et al., 2022). Further, cognitive skills in older adults living in high fluoride drinking water locations may be compromised (Ren et al., 2021). A south Indian researcher discovered that nutritional status has an effect on the severity of fluorosis, with impoverished children being more affected by severe fluorosis (Mahantesha et al., 2016).

Fagin’s report on fluoride’s second thoughts in 2008 is a warning to all concerned, as he exposed the possibility of fluoride-producing diseases in the teeth, bone, brain, and thyroid gland (Fagin, 2008). Fluoride is a toxic substance that promotes thyroid hormone production in children when it is consumed during the intrauterine growth stage (Gedalia et al., 1964). As a result, the thyroid hormone status of married women before conception may need to be examined (McNeil and Stanford, n.d.).

Fluorides, like other elements, have both good and harmful properties that have a substantial impact on public health. Even though it is noted that an optimal dose of 1mg of fluoride per litre in drinking water is beneficial for the prevention of tooth decay, extended exposure to greater concentrations can lead to adverse effects on teeth and bones (Azami-Aghdash et al., 2013). A concentration of fluoride higher than 2 mg/l causes teeth corrosion to increase with fluoride intake, and this can occur in conjunction with other conditions or might increase certain risks (Susheela, 2013). In pregnant women, placental carriage of fluorides happens as early as the 19^th week of gestation (Gedalia et al., 1964). Studies in a few countries have demonstrated linkages between dental fluorosis and LBW. Contrastingly, other literatures have found increased risk of adverse birth outcomes in areas where fluoride levels in drinking water are high (> 1.5 mg/L) (Goyal et al., 2020). However, there is a paucity of studies in the Indian context correlating exposure to fluoride and anaemia in mothers resulting in LBW infants (Guth et al., 2020). Therefore, this study was planned to find linkages between fluorosis, anaemia during pregnancy, and outcome regarding the birth weight of newborn babies.

Methods

Results

Out of 1440 pregnant women enrolled, 50% (n = 720) were from the Jodhpur district, and 50% (n = 720) were from the Nagaur district of western Rajasthan (Patil, 2023c, 2023d). The mean age of women from Jodhpur was 25.51 (±3.87) years, and from Nagaur were, 23.74 (±3.85) years. The mean Hb (gm%) level in pregnant women in the Jodhpur district was 10.4 gm% as compared to the Nagaur district (9.1 gm%).

Fluoride content in water and urine samples of Nagaur and Jodhpur district

Mean fluoride values in water samples were measured to be 0.57 (range from 0.0 to 2.7 PPM) in Jodhpur and 0.7 (range from 0.0 to 3.4 PPM) in Nagaur.

The excretion of mean fluoride value in the urine of pregnant females was found to be 1.4 (range from 0.0 to 12.7 mg/L) in the Jodhpur district and 2.2 (range from 0.1 to 13.7 mg/L) in the Nagaur district. Figure 1 depicts the urinary fluoride content in the Nagaur district, which is very high on the northern side. Figure 2 describes the level of urinary fluoride in the Jodhpur district. The level of fluoride is low compared to the Nagaur district. However, in the district’s central and southern regions, fluoride content is high in the urine as it is excessive in the groundwater.

Figure 1. Fluoride content in urine samples of Nagaur District.

Figure 2. Fluoride content in urine samples of Jodhpur District.

Low birth weight babies in Nagaur and Jodhpur district

The mean weight of newborns from the Jodhpur district was 2.8 kg (±0.56), and from Nagaur was 2.8 kg (±0.44). Around 19% of the newborns in Jodhpur and around 22% in Nagaur had LBW. However, there was no significant difference in LBW babies in both districts (p=0.151).

As shown in Figure 3, the LBW babies were seen in the regions of the Nagaur district where the groundwater fluoride level was very high. However, in the context of the Jodhpur district (Figure 4), the low weight babies were seen in the southern part of the district where the groundwater fluoride level is low. This might be because of the consumption of the fluoride from the other sources.

Figure 3. Low birth weight babies in Nagaur District.

Figure 4. Low birth weight babies in Jodhpur District.

Table 1 illustrates the socio-demographic characteristics of western Rajasthan’s Jodhpur and Nagaur fluoride endemic districts. A significant association was seen between fluoride level in the water (p = 0.00001), Body Mass Index (BMI) (p = 0.00001), anaemia (p = 0.00001), and dental fluorosis (p = 0.00001). Table 2 illustrate the association of fluoride in water with BMI, anaemia and dental fluorosis among pregnant women.

Table 1. Socio-demographic and selected characteristics of fluoride endemic districts.

Characteristics	Jodhpur District	Nagaur District
	(n = 720)	(n = 720)
Mean age of pregnant women (years)	25.51 (+3.87)	23.74 (+3.85)
Mean weight of pregnant women (kg)	62.7 (+11.53)	58.6 (+10)
Mean height of pregnant women (cm)	161.9 (+7.52)	163.1 (+3.62)
Socio-economic Status (%)
Upper Class	17.92	0.69
Upper Middle Class	55.56	1.67
Middle Class	12.22	4.87
Lower Middle Class	11.94	87.64
Lower Class	2.36	5.13
Literacy Status (%)
No Schooling	2.8	16.4
Primary Education	27.5	58.2
Secondary Education	21.1	19.4
Graduation	28.2	5.6
Post-Graduation	20.4	0.4
Birth Weight (%)
Low Birth Weight	18.89	22.08
Normal Birth Weight	81.11	77.92
Water Fluoride (%)	1.67	7.08
Dental Fluorosis (%)	9.02	23.33
Chin Test (%)	5.13	12.63
Stretch Test (%)	4.16	7.5
Muscular Weakness (%)	20.14	38.33
Tingling Sensation (%)	12.5	37.22

Table 2. Association of fluoride level in water with BMI, anemia, and dental fluorosis.

Variables		Water Fluorosis			χ2	p-value
		Optimal n = 939 (%)	Sub-Optimal n = 438 (%)	High n = 63 (%)
Birth Weight	Low	207	80	8	5.0727	0.07915
	Normal	732	358	55
Anaemia	No	191	152	9	37.0404	0.00001
	Yes	748	286	54
Dental Fluorosis	No	417	247	17	28.1077	0.00001
	Yes	522	191	46
Chin Test	No	860	401	51	8.3956	0.01502
	Yes	79	37	12

A significant association was also seen in dental fluorosis with birth weight and anaemia (p < 0.005). Table 3 illustrates dental fluorosis’s association with baby birth weight (normal birth weight (NBW) and LBW) and anaemia in pregnant women (no anaemia and anaemia). The excretion of fluoride in pregnant women’s urine and haemoglobin (Hb) has a statistically significant linear relationship. The direction of the relationship is negative, i.e., urine fluorosis and haemoglobin of pregnant women are negatively correlated. This illustrated that greater fluoride excretion is associated with lower haemoglobin levels (r = -0.2).

Table 3. Association of dental fluorosis across baby birth weight and anemia status of pregnant women.

Variables		Dental Fluorosis		χ2	p-value	Relative Risk (RR)
		No Fluorosis (%)	Fluorosis (%)
Birth Weight	Normal Birth Weight	754 (46.31)	874 (53.69)	19.1402	0.000012	RR = 1.63 (CI 1.27-2.09)
	Low Birth Weight	46 (28.40)	116 (71.60)
Anaemia	No anemia	160 (34.26)	307 (65.74)	74.1282	0.00001	RR = 2.2 (CI 1.84-2.63)
	Anaemia	206 (15.57)	1117 (84.43)

Urine fluoride and newborn birth weight have a statistically significant linear relationship. The direction of the relationship is negative, i.e., urinary fluoride and newborn birth weight are negatively correlated. This illustrated that greater urinary fluoride is associated with birth weight (r = -0.01). The relative risk of LBW was 1.63 times more in high fluorosis cases. Also, the relative risk of anaemia among pregnant women was 2.2 times in high fluoride endemic areas.

Tea consumption was high in both districts, whereas tobacco/areca nut usage was high (55%) in the Nagaur district. It was observed that the consumption of black salt was around 38% in Nagaur and 28% in the Jodhpur district, and the consumption of churan/chat masala was 35.4% and 14.6% in Nagaur and Jodhpur districts, respectively. Table 4 shows drug consumption and selected dietary habits of pregnant women.

Table 4. Drug consumption and dietary habits of pregnant women.

Drug/Diet	Nagaur (%)	Jodhpur (%)
Drugs
Anti-Depressant	3 (0.4)	28 (3.9)
Anti-infective	16 (2.2)	37 (5.1)
NSAID	23 (2.2)	25 (3.5)
Corticosteroids	1 (0.1)	0 (0)
Sedative	6 (0.8)	10 (1.4)
Ani-Emetic	159 (22.1)	54 (7.5)
Other like thyroid, DM	51 (7.1)	42 (5.8)
Iron tab	376 (52.2)	134 (18.6)
Calcium	376 (52.2)	131 (18.2)
Multivitamin	37 (5.1)	48 (6.7)
Homoeopathic	13 (1.8)	38 (5.3)
Ayurvedic	4 (0.6)	38 (5.3)
Albendazole	6 (0.8)	38 (5.3)
Vaccine T1 T2	376 (52.2)	40 (5.6)
Others Drugs	28 (3.9)	76 (10.6)
Diet
Black salt	204 (28.3)	273 (37.9)
Churan/chat masala	105 (14.6)	255 (35.4)
Tea	495 (68.8)	628 (87.2)
Coca/coffee	39 (5.4)	40 (5.6)
Preserved fruits juice	48 (6.7)	48 (6.7)
Meat/canned fish	38 (5.3)	207 (28.7)
Dry fruits/walnut	61 (8.5)	41 (5.7)
Tobacco/Arecanut	43 (6)	396 (55.0)
Milk product	663 (92.1)	305 (42.4)
Eggs	46 (6.4)	90 (12.5)
Pickle	126 (17.5)	199 (27.6)
Fruits	622 (86.4)	427 (59.3)
Vegetable	699 (97.1)	676 (93.9)
Cereals	704 (97.8)	688 (95.6)
Pulses	688 (95.6)	677 (94.0)
Fat oils	692 (96.1)	667 (92.6)
Sugar/honey/Jaggery	664 (92.2)	77 (10.7)

Discussion

Fluorosis is an endemic disease caused by excessive fluoride exposure from various sources. The element fluorine is a potent enzyme inhibitor, hormone disruptor, and neurotoxic, making it a double-edged sword that causes metabolic derangements (Susheela et al., 2018). Fluorosis manifests as a “linked disease” in many emerging Asian and African countries (Susheela and Toteja, 2018). In many countries throughout the world, high fluoride level in groundwater has become one of the most serious health-related geo-environmental challenges (Demelash et al., 2019; Johnston and Strobel, 2020). Fluorosis has affected 21 Indian states. The Fluorosis Research and Rural Development Foundation, India survey mentioned that more than 66 million people are affected by fluorosis in India (Susheela and Toteja, 2018).

The Bureau of Indian Standards (BIS) has specified fluoride levels in drinking water standards, with a maximum acceptable limit of 1.0 mg/L and an allowed limit of 1.5 mg/L in the absence of an alternative source (Puri and Kumar, 2012). In some areas of Rajasthan, people drink water with fluoride levels as high as 24 mg/l (Department of Environmental Engineering, Delhi Technological University, India et al., 2014). In our study, mean fluoride values in water samples were 0.57 (range 0.0 to 2.7 PPM) in Jodhpur and 0.7 (range 0.0 to 3.4 PPM) in Nagaur. A similar study was carried out in the Punjab district of Faridkot, India. The mean value of water fluoride content was discovered to be 2.4 mg/L, which was higher than the allowable limits (Goyal et al., 2020). Hence, this region’s exposure to fluoride from drinking water is of considerable concern.

Even though low haemoglobin levels are frequently detected in clinical settings, they are rarely considered significant unless they are associated with the detection of a serious blood disease (Andezhath, 2010). The greatest concern is that ingesting fluoride (F–) through water and food could result in serious health consequences. In our research, there was a significant association between fluoride levels in water and anaemia (p = 0.00001). The highly detrimental F– damages the lining of the intestine and hinders nutritional absorption when it enters the body through food, water, habit-forming chemicals, and dental products (Susheela et al., 2018). Hillman et al. discovered anaemia in cattle due to F– poisoning and fluorosis in the 1980s (Hillman et al., 1979). Excessive fluoride may affect brain development in utero and lead to neurological abnormalities, according to evidence from several human studies (Grandjean, 2019; Guth et al., 2020).

Urine has long been recognized as a significant diagnostic marker for fluoride intake since it is widely used, relatively easy to collect, and non-invasive (Idowu et al., 2019; Kumar et al., 2017). In our study, pregnant women’s excretion of fluoride in urine and haemoglobin (Hb) had a statistically significant linear relationship. The direction of the relationship is negative, i.e., urine fluorosis and haemoglobin of pregnant women are negatively correlated. Excretion of mean fluoride value in the urine of pregnant females was found to be 1.4 (range from 0.0 to 12.7 mg/L) in Jodhpur district and 2.2 (range from 0.1 to 13.7 mg/L) in Nagaur district. Females with high urine fluoride levels have a higher risk of pregnancy difficulties such as anaemia and poor fetal outcomes, according to a study by Goyal et al. (2020).

According to AK Susheela et al., drinking fluoride-free water and eating fluoride-free food reduced preterm births by four times and LBW babies by two times (Susheela and Toteja, 2018).

In industrialized and developing countries, the burden of poor pregnancy outcomes (APOs), including preterm deliveries and LBWs, is significant (Blencowe et al., 2012; Lawn et al., 2006; Lee et al., 2013). Maternal anaemia was identified as a risk factor for low/insufficient birth weight in the current study, which was similar to findings from a prior study by Räisänen et al. (2014).

In India, anaemia affects 55.3 per cent of women aged 15 to 49 years old (Kulasekaran, 2012). Anaemia in women during pregnancy has been linked to underweight children. Mother and newborn mortality rates in India are still high due to poor haemoglobin levels. Furthermore, anaemic mothers frequently give birth to low-weight newborns (as low as 1.0 to 1.2 kg), with a high risk of developmental problems or infant mortality later in life (Andezhath, 2010).

A study finds that maternal haemoglobin (Hb > 110 g/l) protects against the risk of APOs in the study populations, which is consistent with prior findings (Padhi et al., 2015). With anaemia in the first or second trimester, a recent systematic review and meta-analysis found a significantly greater risk of LBW (OR: 1.29; 95 percent CI: 1.09–1.53) and preterm birth (OR: 1.21; 95 percent CI: 1.13–1.30) (Haider et al., 2013). Preterm delivery and LBW are important factors of child survival, impairments, stunting, and long-term negative implications for the beginning of non-communicable diseases later in life. They necessitate effective public health interventions.

The precise mechanism that links maternal anaemia to LBW remains unknown. Only a few prospective cohort studies have examined the relationships between maternal anaemia and LBW (Bakacak et al., 2015; Figueiredo et al., 2019; Haider et al., 2013; Rahman et al., 2016). In Jodhpur, around 19 percent of newborns had a LBW, whereas, in Nagaur, nearly 22 percent had a LBW. According to another study, the relative risk of giving birth to LBW babies is 37% among the women with low haemoglobin levels (Figueiredo et al., 2019).

According to other studies, factors such as diet, excessive tea consumption, other associated nutritional deficiencies, and the use of fluoridated toothpaste have also been linked to the occurrence and severity of fluorosis (Rao and Mahajan, 1990; Shruthi and Anil, 2018). The participants in our study mostly ate locally grown vegetarian cuisine daily and had a history of drinking tea and brushing their teeth with fluoridated toothpaste. In our study, there was a significant link between dental fluorosis and birth weight and anaemia (p > 0.005). Tea consumption was high in both districts, whereas tobacco/areca nut consumption was high (55 percent) in Nagaur. Black salt consumption was found to be roughly 38 percent in Nagaur and 28 percent in the Jodhpur district. In comparison, churan/chat masala consumption was found to be 35.4 percent and 14.6 percent in Nagaur and Jodhpur districts, respectively.

The prevalence of dental fluorosis was 13.17 percent in the study by Shruti et al., with a high fluoride level (Shruthi and Anil, 2018). Fluorosis is irreversible and only develops when the enamel is growing and exposed to fluoride. Fluoridated enamel is porous (objectionable secondary staining is common) and opaque rather than being a standard creamy-white translucent tint (Mahantesha et al., 2016). In our study, a significant association was also seen between fluoride level in the water and dental fluorosis (p = 0.00001) and baby birth weight (p = 0.000012) and LBW (p = 0.00001).

The presence of more than eight ppm of fluoride in drinking water over a long period might cause skeletal fluorosis (Reddy, 2009). As a result of the persistent poisoning, bone density gradually increases, and joints stiffen and become painful.

Susheela et al.’s findings support the notion that iron and folic acid at current levels is beneficial in reducing the risk of LBW when combined with proper nutrition and reduced F– intake (Susheela et al., 2010). According to one study, efforts to raise Hb by iron and folic acid (IFA) supplementation through State and National Programs have yet to provide desired outcomes (Beard, 2000; Vijayaraghavan et al., 1990).

The use of validated instruments by previously trained researchers strengthens the internal validity of this study. A large sample size aids in extrapolating study findings to populations with similar geographies. In terms of the study’s weaknesses, the self-reported data may have resulted in calibration bias. Also, sample losses owing to missed follow-ups are a possibility.

With a coordinated effort to implement proper rules and procedures, the Millennium Development Goal of reducing early childhood mortality by two-thirds will be easier to attain (“Global nutrition targets 2025,” n.d.). Here are a few solutions that have been presented for better implementation.

In every policy design, Behavior Change Communication (BCC) intervention must be an integral part that focuses on each stakeholder (“tagged_ifas_participants_manual_for_healthcare_providers.pdf,” n.d.). Information, Education and Communication (IEC) initiatives must include educating pregnant women on the role of Hb and LBW children, as well as the do’s and don’ts of fluoride consumption in the diet, through media campaigns (“Dietary guidelines for Indians.pdf,” n.d.; Goyal et al., 2020). The role of dieticians and nutritionists must be escalated during ANC visits (Kominiarek and Rajan, 2016). Ascorbic acid improves iron absorption (vitamin C). This should be stressed throughout the diet counselling session, which includes a list of vital fruits and vegetables that contain vitamin C that should be consumed (Hallberg et al., 1989). Iron absorption is inhibited by phytic acid/sodium phytate in brown bread and tannin in tea. The resulting vitamin B12 and folic acid deficiencies may cause anaemias. Vitamin B12 is not often investigated but is a key constituent for Hb biosynthesis (Delimont et al., 2017). Withdrawing fluoride from the diet may have repaired damage to the gastrointestinal mucosa/loss of microvilli, allowing nutrients to be absorbed, resulting in increased Hb and correction of anaemias (Johnston and Strobel, 2020). This calls for assessing the effectiveness of de-fluoridation activities along with the most common food practices leading to high fluoride levels in pregnant women.

Fluoride assessment in body fluids is the primary criterion to know how much fluoride has entered the body. Regular monitoring of 24-hour urine samples and plasma samples may help researchers better understand the harmful effects of excessive fluoride exposure during pregnancy (Goyal et al., 2020). Thus, a monitoring and impact assessment must be part and parcel of future research related to fluoride and anaemic mothers.

In addressing the potential impact of various risk factors on anemia in the studied areas, we took measures to mitigate bias. Although the mean fluoride levels were not exceptionally high in both regions, we conducted a comprehensive assessment of potential contributors to anemia in pregnant women. This included the measurement of fluoride levels in both water and urine, acknowledging their role as risk factors.

Additionally, we investigated other factors such as dietary patterns, excessive consumption of tea and black salt, concomitant nutritional deficiencies, and the use of fluoridated toothpaste. We also considered the source of drinking water, aiming to account for any potential effects on hemoglobin levels in pregnant women. The study also delved into iron and folate supplementation for pregnant women, exploring the correlation with the risk of low birth weight in both districts. However, there was no significant difference in LBW babies in both districts (p=0.151).

It’s important to note that the study has its limitations, and while we addressed a few risk factors, there may be several area-specific that were not thoroughly explored, contributing to potential bias in the assessment of anemia in pregnant women.

Limitations

The confounding factors included the exposure time to fluoride in drinking water, as well as the exposure to fluoride in age, obstetric history, supplements, diet, air, medication, water sources, cooking vessel etc. To minimize the confounding factors, we could have applied regression analysis to observe the impact of fluoride on maternal and child health. Further, recruitment of larger sample participants in a randomized manner could help in getting the impact of Fluoride on pregnant women.

However, we have collected data on variables like 24-hr diet recall to track nutrition aspects, past obstetric history, cooking vessels, medication, water sources and other co-morbidity like blood pressure, diabetes etc. But we could not perform analysis to see their impact on MCH in fluoride endemic areas.

Conclusion

In fluoride endemic areas, other factors should be included besides iron and folic acid supplementation for improving anaemia in pregnant women. This calls for an assessment of the effectiveness of de-fluoridation activities along with the most common indigenous food practices in the area. In India, the role of fluoride as a risk factor in pregnancy has not been documented. In this context, the current study has added a significant body of knowledge that can be further scaled up.