Factors associated with early pregnancy anemia in rural Sri Lanka: Does being 'under care' iron out socioeconomic disparities?

Globally, more than a third of pregnant women are anemic, and progress in its prevention and control is slow. Sri Lanka is a lower-middle-income country with a unique public health infrastructure that provides multiple interventions across the lifecycle for anemia prevention, despite which anemia in pregnancy remains a challenge. Studying the factors associated with maternal anemia in this context would provide unique information on challenges and opportunities encountered as low-and-middle-income countries attempt to control anemia by improving health care coverage. All first-trimester pregnant women registered for antenatal care in the Anuradhapura district between July 2019 to September 2019 were invited to participate in the baseline of a cohort study. Interviewer-administered and self-completed questionnaires were used. Anemia was defined using a full blood count. A hierarchical logistic regression model was built to identify factors associated with anemia. Out of 3127 participants, 451 (14.4%) were anemic. According to the regression model (Chi-square = 139.3, p<0.001, n = 2692), the odds of being anemic increased with the Period of gestation (PoG) (OR = 1.07, 95% CI = 1.01-1.13). While controlling for PoG, age and parity, history of anemia (OR = 3.22, 95%CI = 2.51-4.13), being underweight (OR = 1.64, 95%CI = 1.24-2.18), having the last pregnancy five or more years back (OR = 1.57,95%CI = 1.15-2.15) and having used intrauterine devices for one year or more (OR = 1.63, 95%CI = 1.16-2.30) increased the odds of anemia. Breast feeding during the last year (OR = 0.66, 95%CI = 0.49-0.90) and having used contraceptive injections for one year or more (OR = 0.61,95%CI = 0.45-0.83) reduced the risk of anemia. Proxy indicators of being in frequent contact with the national family health program have a protective effect over the socioeconomic disparities in preventing early pregnancy anemia. Maintaining the continuum of care through the lifecycle, especially through optimizing pre and inter-pregnancy care provision should be the way forward for anemia control.

Introduction

Anemia results from inadequate red cell or hemoglobin concentration to maintain the optimum oxygen supply for tissues [1]. Anemia in pregnant women could result in significant transgenerational morbidity, mortality, and productivity loss [2-10]. Pregnant women are especially vulnerable to anemia for several reasons, including physiological changes, socioeconomic or cultural restrictions to achieve optimal nutrition, and increased nutritional demand during pregnancy [11]. In fact, 37% of pregnant women worldwide are anemic [12]. A significant proportion of them, especially those identified as anemic during the early stages of pregnancy, would have already had anemia or marginal hemoglobin values before pregnancy. Therefore, prevention of anemia in pregnancy is essentially linked with anemia control in reproductive-age women.

Global progress in reducing anemia prevalence among pregnant women has been plodding [13]. Why a significant proportion of pregnant women would remain vulnerable to anemia despite multiple interventions at different stages of the lifecycle is a question that needs answers. Identifying factors associated with anemia is as crucial as identifying the underlying etiologies for anemia when answering this question.

Studies have shown that healthcare utilization during pregnancy, including the reception of antenatal care [13, 14], nutrient supplements [15-17], deworming [18, 19], and utilization of general healthcare services such as family planning [20-23] significantly reduced anemia in pregnant or non-pregnant reproductive-age females. Individual dietary patterns such as increased meat, fish and egg consumption, and community-level food fortification programs are also associated with anemia prevention [13, 14]. The odds of being anemic decreases with increased maternal age, increased gap between pregnancies, and lower parity [13, 14, 24]. Across geographical regions, underweight women have an increased risk of anemia compared to normal or overweight women [13, 20, 25]. Education level, wealth, employment status, hygiene, and sanitary facilities are also associated with anemia [25-31].

Sri Lanka is a lower-middle-income country providing well-structured family health services free of charge at the point of delivery with an island-wide coverage [32]. Public health provision has a strong orientation towards the continuum of care across the life cycle [33]. Despite the country’s continuous efforts, nearly a third of pregnant women are anemic, and anemia prevalence among first-trimesters women is 18.4% [33]. Early studies in Sri Lanka have shown that anemia was more prevalent among pregnant women with a high parity [34]. However, perhaps due to the success of the family planning programme, this association was not reflected in later studies(8). Pregnant women at either extremity of reproductive age have reported a higher prevalence of anemia and iron deficiency [35]. Iron folate supplementation prior to the booking visit did not prevent anemia [35]. Iron folate supplementation during pregnancy, incorporated into the national maternal care package reduced the risk of anemia [32, 36]. Dietary habits such as milk, tea, and red meat consumption failed to show an association with anemia in pregnancy, but higher consumption of green leaves and eggs was associated with a lower risk for anemia [37]. An association between anemia and income level also has been shown [37]. Studies on non-pregnant reproductive age females have shown that anemia was not associated with economic status or dietary habits such as vegetarianism, consuming tea within an hour of a meal, and consuming meat, fish, and eggs [38]. Age, parity, and educational level were associated with anemia [39, 40]. Local studies reporting data on factors associated with anemia have employed heterogeneous study samples impairing the ability to generate an in-depth understanding of the determinants of maternal anemia, which would be invaluable to design further anemia control strategies. Therefore, we conducted this study to identify the factors associated with early pregnancy anemia in a large community-based sample of pregnant women from a single geographical area in the country. Identifying associated factors enabled recognizing gaps in the current preventive strategies, alerting stakeholders to refine them to achieve better outcomes.

Materials and methods

We carried out this descriptive cross-sectional study as a component of the baseline assessment of the Rajarata pregnancy cohort [41]. All the first trimester (Period of gestation less than 13 weeks) pregnant women registered in the pregnant mothers’ registers of public health midwives in Anuradhapura district between July and September 2019 were invited to participate in the study. Anuradhapura is the geographically largest of the 25 administrative districts in the country. For the participant recruitment, special clinics were conducted weekly or fortnightly in each of the 22 medical officers of health (MOH) areas in the district. Anemia prevalence in the recruited sample of first trimester women (n = 3127) was 14.4% (n = 451), and iron deficiency, minor hemoglobinopathies, and vitamin B12 deficiency were identified as the major etiological contributors to anemia [42].

An interviewer-administered questionnaire was used to obtain demographic and health-related data. Menstrual blood loss was assessed using a pictogram. Health records, including the current and previous pregnancy records, and high-performance liquid chromatography (HPLC) for thalassemia screening were checked to verify the information. Socioeconomic data and data on dietary habits were obtained using self-completed questionnaires. All the tools were developed specifically for the study and were translated into the local languages (Sinhala and Tamil). They were validated by a panel of multidisciplinary experts including a consultant community physician, social epidemiologist, hematologist, physicians and public health midwives working in the area where study is conducted. Tools were pretested among 20 pregnant women with the same eligibility criteria but registered in the maternal care program prior to the study period. The questions were amended according to the results of pretesting in order to make sure they were comprehendible by participants. An interviewer guide was followed when administrating the questionnaire. Anthropometric measurements of participants were obtained following a standard protocol. A full blood count was performed on all the participants from a public health research laboratory with external and internal quality control methods [43]. A standardized protocol was followed when collecting, transporting and storing blood samples. A detailed account of the study is presented elsewhere [44]. All the questionnaires and protocols for anthropometric measurements and sample collection are available online [43].

Measures

Anemia was defined as a hemoglobin level less than 11 g/dl. Minor hemoglobinopathies were identified based on the red cell index (microcytic anemia with a high red cell count), which showed a 100% positive predictive value in the HPLC tested subsample [42]. Independent variables included demographic factors, reproductive and gynecological factors, uptake of health services, diet, nutritional status, current health status and socio-economic conditions. During the completion of the interviewer-administered questionnaire, the expected date of delivery was verified with ultrasound confirmation whenever possible, and this was reassessed during the follow-up of the cohort. PoG was calculated using the date of the last menstrual period (LRMP) reported by the woman, and ultrasound confirmed date of delivery. Obtained values were triangulated to decide the most appropriate value. Maternal age was calculated using the date of birth. Education level of the participant and her husband, number of family members living with the participant (family size), parity, number of children, gap between the previous and current pregnancy and duration of using different contraceptive methods were recorded as ordinal values and categorized later. Among women with regular menstrual cycles, who use sanitary pads, menstrual blood loss per cycle was calculated using a scoring system on the data obtained from the pictogram [45]. This pictogram has been used in previous studies conducted in the same setting [46]. A score of 1, 5 and 20 given when each used sanitary pad was lightly, moderately or completely stained when changed, respectively and an additional score of 5 was added if clots are passed [45]. Average blood loss per year was calculated based on the cycle length. This variable was binned into three equal percentiles categorizing the blood loss as low, medium and high. A score out of five was allocated to the frequency of consuming food items given in the questionnaire (ranging from1 for never consuming to 5 for consuming daily). Scores were added up as necessary (e.g.: scores for consuming chicken, other meat, freshwater fish, sea fish, canned fish, sprats, and dry fish were combined for the variable ‘Frequency of consuming meat/fish’). The combined score was binned into three based on equal percentiles to determine low, moderate, and high consumption levels. BMI below 18.5 kg/m2 was considered underweight and BMI of 25 kg/m2 was considered overweight/ obese category [47]. Monthly income was also binned into four based on equal percentiles. Proxy indicators; using a water sealed toilet, having electricity at home, having a mobile phone, using biomass fuel for cooking, drinking water filtered using Reverse Osmosis, having a vehicle at home were used to represent socio-economic status.

Data analysis

Data were analyzed using SPSS version 22. The data set used for the analysis is attached as S1 File. Chi square tests were performed to identify variables significantly associated with anemia. Based on the results of this bivariate analysis a two-step hierarchical logistic regression was performed to identify factors associated with anemia among first-trimester pregnant women. The PoG in weeks, maternal age (years), and parity (primy or multi) were added in block one. Having been breastfeeding within the past one year, ever having had anemia, BMI (those who were not underweight as reference category), having a vehicle at home, the gap between last and current pregnancies (reference category was being a primy or having the last pregnancy within five years), having used contraceptive injections for one year or more and having used intrauterine contraceptive devices for one year or more were added to the model as the block two. The final model was statistically significant (Chi-square = 139.3, p<0.001, n = 2692), which could explain 5.0% (Cox and Snell R square) and 9.2% (Nagaelkerke R squared) of the variance and correctly classified 86.2% of cases.

Ethical clearance

This study was approved by the ethics review committee of the Faculty of Medicine and Allied Sciences, Rajarata University of Sri Lanka. Informed written consent was obtained from all participants. Proxy consent of guardians and ascent of participants were also obtained when the participant was below 18 years of age.

Results

Out of the 3127 first trimester pregnant women recruited, 215 (7.5%) were teenage (below 20 years of age) and majority were ethnic Sinhalese (n = 2730, 87.1%), followed by Moor (n = 358, 11.4%) and Tamil (n = 39,1.2%), respectively. The majority (N = 1873, 60.3%) were educated up to the GCE ordinary level. Of the participants, 1071 (34.3%) were primi gravid, and 1158 (37.1%) had one child. Monthly family income varied between 2000 rupees (9.9 USD) to 0.5 million rupees (2469 USD). The median was 40,000 rupees (197.6 USD). Underweight, normal, overweight and obesity were seen in 504 (16.6%), 993 (32.7%), 485 (16.0%) and 1053 (34.7%) respectively. The mean period of gestation (PoG) was eight weeks, and hemoglobin distribution according to the gestation revealed a reducing trend after ten weeks PoGs (Fig 1).

Fig 1

Haemoglobin level of first-trimester pregnant women by the period of gestation.

Five hundred sixty-one participants (18%) had a history of anemia, of whom 36.2% (n = 161) were anemic currently. Eighty-two out of the 561 had undergone HPLC testing, and 38 (5.9%) were confirmed as thalassemia trait. Only 32 out of the confirmed thalassemia trait participants were anemic during the first-trimester assessment. A quarter (n = 40) of anemic pregnant women with a history of anemia had a high Red Cell Index suggestive of minor hemoglobinopathy. Among the anemic pregnant women, one-third of ethnic Moore women (n = 19) had a high red cell index compared to only 18.2% (n = 72) of other women. Respectively 198, 360, 39, and 52 women with anemia had received dietary advice, oral iron, intravenous iron, and other vitamins as treatment for anemia at the time of the previous diagnosis. Seventeen had received blood transfusions, of which 11 were during the antenatal period of a previous pregnancy. Only 156 had evidence of normalized hemoglobin levels after initial treatments.

Chi-square tests showed that the anemia prevalence were statistically significantly different between groups categorized according to the gap between current and last pregnancy, body mass index (BMI) category, history of anemia, having used an intrauterine contraceptive device (IUCD) for one year or more, having used depo-medroxyprogesterone acetate injection (DMPA) for a year or more, breastfeeding during the past year and frequency of consuming dairy products (Table 1). Among studied socioeconomic factors, having a vehicle at home was significantly associated with anemia (Table 2).

Table 1

Demographic and health factors associated with anemia among first-trimester pregnant women in the Anuradhapura district.

Variable		Anemic		Non-anaemic
		N	%	N	%	Χ2	p
Demographic factors
Age	<20	36	7.9	169	6.3
	20–29	248	54.2	1459	54.5
	30–39	158	34.6	1000	37.3	5.88	0.12
	≤40	15	3.3	51	1.9
Education level	Up to O/L	274	61.3	1587	59.9	0.31	0.58
	Beyond O/L	173	38.7	1062	40.1
Partner’s education level	Up to O/L	307	68.2	1800	68.2	0.00	0.99
	Beyond O/L	143	31.8	840	31.8
Family size	<5	294	65.6	1811	68.3	1.30	0.25
	≥5	154	34.4	839	31.7
Ethnicity	Sinhala	393	86.0	2331	87.2	0.97	0.60
	Moore	58	12.7	300	11.2
	Other (Malay, Burger and other)	6	1.3	42	1.6
Reproductive and gynaecological factors
Number of children	Non	143	31.2	817	30.5	0.34	0.84
	One	147	32.5	849	31.8
	Two or more	164	36.3	1007	37.7
Planned pregnancy (current)	Yes	326	72.3	1950	73.9	0.55	0.46
	No	125	27.7	687	26.1
The gap between current and last pregnancy	<5 years	147	32.7	1084	40.8	13.29	0.001
	≥5 years	160	35.6	754	28.4
	Primiparous	143	31.8	817	30.8
Breast feeding currently/within last one year	No	301	69.8	1590	62.4	8.85	0.003
	Yes	130	30.2	959	37.6
Have had miscarriages ever	No	230	74.4	1343	72.8	0.36	0.55
	Yes	79	25.6	502	27.2
Has regular menstrual cycles	Yes	388	85.5	2229	83.5	1.12	0.29
	No	66	14.5	441	16.5
Average menstrual blood loss (before pregnancy)	Low	138	32.5	865	33.7	0.96	0.62
	Moderate	138	32.5	864	33.7
	High	149	35.1	838	32.6
Health Service Uptake
Has used injectable contraceptives for ≥1year	No	369	80.7	1997	74.5	8.17	0.004
	Yes	88	19.3	683	25.5
Has used intrauterine contraceptive devices for ≥1year	No	389	85.1	2422	90.4	11.57	0.001
	Yes	68	14.9	258	9.6
Had taken anthelminthic drugs within last 6 months	Yes	195	43.6	1151	43.5	0.00	0.96
	No	252	56.4	1495	56.5
Attended pre pregnancy sessions	Yes	71	22.5	431	23.1	0.05	0.82
	No	244	77.5	1434	76.9
Has consumed iron supplements during last pregnancy	Yes	269	91.5	1625	92.9	0.69	0.41
	No	25	8.5	125	7.1
Has consumed iron supplements during postpartum period of last pregnancy	Yes, regularly	178	61.6	1067	61.6	0.00	1.00
	Yes, not regularly	28	9.7	168	9.7
	No	83	28.7	496	28.7
Consumed folic acid supplements before pregnancy	Yes	266	81.8	1559	80.4	0.37	0.54
	No	59	18.2	380	19.6
Consuming folic acid supplements currently	Yes	421	93.3	2521	94.7	1.36	0.24
	No	30	6.7	141	5.3
Diet
Frequency of consuming meat/fish	Low	64	35.2	466	42.4	3.38	0.18
	Moderate	67	36.8	366	33.3
	High	51	28.0	268	24.4
Frequency of consuming milk/dairy products	Low	85	46.7	378	34.5	10.27	0.006
	Moderate	59	32.4	452	41.2
	High	38	20.9	267	24.3
Nutritional status
History of anemia	No	284	63.8	2210	83.9	104.52	0.001
	Yes, during a past pregnancy/postpartum	109	24.5	319	12.1
	Yes, not during a past pregnancy	52	11.7	106	4.0
Waist-to-hip ratio	≥88 cm	282	66.2	1707	67.4	0.25	0.62
	<88 cm	144	33.8	825	32.6
BMI	Underweight	101	23.0	403	15.5	20.22	0.001
	Normal	152	34.6	841	32.4
	Overweight/obese	186	42.4	1352	52.1
Current health status
Had blood in stools within last 6 months	Yes	15	3.4	111	4.2	0.64	0.42
	No	428	96.6	2534	95.8
Had melena within last 6 months	Yes	9	2.0	45	1.7	0.22	0.64
	No	438	98.0	2600	98.3

Table 2

Social and economic conditions associated with anemia among first-trimester pregnant women in the Anuradhapura district.

		Anemic		Non-anaemic
		N	%	N	%	Χ2	p
Alcohol and tobacco use
Have/had the habit of smoking tobacco products	Yes	2	0.5	7	0.3	0.43	0.512
	No	398	99.5	2347	99.7
Have/ Had the habit of betel (Piper betle) chewing (ever)	Yes	13	3.2	43	1.8	3.46	0.06
	No	388	96.8	2313	98.2
Has someone who smokes at home	Yes	79	19.8	413	17.8	0.91	0.34
	No	321	80.3	1912	82.2
Have/ever had the habit of consuming alcoholic beverages	Yes	3	0.8	17	0.8	0.01	0.920
	No	362	99.2	2185	99.2
Self-reported abuse
Have you been emotionally or physically abused ever	Yes	18	4.5	80	3.4	1.35	0.25
	No	379	95.5	2293	96.6
Proxy indicators of socio-economic status
Uses a water sealed toilet	Yes	401	89.5	2438	92.1	3.30	0.07
	No	47	10.5	210	7.9
Has electricity at home	Yes	435	97.3	2605	98.4	2.69	0.10
	No	12	2.7	42	1.6
Has a mobile phone	Yes	438	97.8	2613	98.7	2.46	0.12
	No	10	2.2	34	1.3
Uses biomass fuel for cooking	Yes	201	44.9	1314	49.6	3.44	0.06
	No	247	55.1	1335	50.4
Drinks water filtered using Reverse Osmosis	Yes	312	69.8	1872	70.7	0.14	0.71
	No	135	30.2	777	29.3
Has a vehicle at home	Yes	391	89.1	2401	92.0	4.28	0.038
	No	48	10.9	208	8.0
Income
Monthly family income category	1 (Lowest)	50	28.4	280	26.4	1.55	0.67
	2	37	21.0	263	24.8
	3	41	23.3	255	24.1
	4(Highest)	48	27.3	262	24.7

Hierarchical logistic regression was performed to assess the impact of several factors on the likelihood of anemia in the first trimester of pregnancy (Table 3). After controlling for PoG at hemoglobin measurement, maternal age, and parity, the greatest contribution to the model was from having a history of anemia. Those with a history of anemia were 3.2 (P<0.001) times more likely to have anemia during the first trimester of pregnancy. Odds of having anemia increased with increasing PoG. Using IUCD for one year or more also increased the odds of having anemia by 1.6 times compared to those who had not used IUCD for a year or more. Having used DMPA injections for one year or more was protective against anemia. Those who were breastfeeding or had breastfed within the past year were less likely to be anemic than those who had never breastfed/had stopped breastfeeding more than a year ago. Underweight pregnant women were 1.6 times more likely to be anemic than pregnant women with normal BMI, overweight, or obese. Pregnant women who had had their last pregnancy five or more years back were 1.6 times more likely to have anemia compared to primiparous women and those who had their last pregnancy within five years.

Table 3

Hierarchical logistic regression explaining anemia in first-trimester pregnant women in Anuradhapura district.

	B	S.E.	Sig.	Odds ratio	95% CI for OR
					Lower	Upper
Period of gestation (weeks)	0.07	0.03	0.018	1.07	1.01	1.13
Maternal age (years)	-0.01	0.01	0.408	0.41	0.97	1.02
Parity (primy or multi)	-0.06	0.20	0.782	0.95	0.64	1.41
Having breast fed within one year	-0.41	0.16	0.009	0.66	0.49	0.90
History of anaemia	1.17	0.13	0.001	3.22	2.51	4.13
Underweight (reference group- Normal/ overweight/ obese)	0.5	0.15	0.001	1.64	1.24	2.18
No vehicle at home	0.32	0.19	0.099	1.37	0.95	2.00
Used DMPA one year or more	-0.49	0.18	0.002	0.61	0.45	0.83
Used IUCD one year or more	0.49	0.18	0.005	1.63	1.16	2.30
Last pregnancy 5 or more years back (reference group–primy/ last pregnancy within 5 years)	0.45	0.16	0.005	1.57	1.15	2.15

Discussion

This large community-based study provides a detailed analysis of probable associations of early pregnancy anemia in Sri Lanka, including demographic, nutritional, reproductive, and socioeconomic factors. In contrast to many studies in global literature, we have adopted a demarcation between these underlying associations and etiological causes for anemia, latter being described in detail elsewhere [42]. This analysis shows that PoG, history of anemia, being underweight, having the last pregnancy five or more years back, having used IUCD or DMPA, and breastfeeding during the last year were associated with anemia in early pregnancy. The study reflects that anemia during the first trimester of pregnancy represents the impact of pre-pregnancy determinants, including lifestyle, nutrition, and reproductive choices on the health of pregnant women. Strengthening the lifecycle approach in providing care for reproductive and other health issues would successfully address many factors associated with early pregnancy anemia in this community.

Review of global literature shows that factors associated with anemia in pregnancy are diverse and depend on the context [14]. Health and social inequities play a central role in the occurrence of anemia [13, 48]. Sri Lanka is unique in the global health landscape as it has a good public health infrastructure, well-established, accessible and affordable maternal care services with high coverage, and better gender equity compared to countries with similar economic characteristics [49, 50]. Studying the factors associated with maternal anemia in this context would provide unique information on opportunities and challenges that could be anticipated as low- and middle-income countries move forward with anemia reduction goals by improving health care coverage.

Anemia increased with PoG (OR = 1.07, 95% CI 1.01 to 1.13). This observation can at least partly be explained through hemodilution, which starts as early as six weeks of PoG [51]. Looking at this pattern, we could argue that using 11g/dl as the hemoglobin cutoff until 13 weeks of PoG may classify some pregnant women with a lower hemoglobin level purely due to physiological changes in pregnancy, as anemic. This claim could be further supported by having a number of normal peripheral blood film reports in anemic women of this sample and common symptoms of anemia having a low sensitivity [42, 52]. Such mothers will undergo unnecessary interventions such as additional investigations, increased iron dose, and other nutritional supplements and dietary modifications that may lead to increased psychological and economic burden. Therefore, the harms and benefits of redefining the anemia cutoff for early pregnancy should be studied further through prospective studies.

Controlling for PoG, maternal age, and parity, the strongest predictor of first-trimester anemia, was having had anemia earlier in life. Non-modifiable etiologies such as thalassemia trait and membrane disorders contribute to a significant proportion of anemia in Sri Lankan communities [42, 53, 54]. On the other hand, treating anemia without a proper follow-up and etiological diagnosis may also lead to unresolved or recurrent anemia in women, which may be carried on to the pregnancy. More than two-thirds of the women with a history of anemia had been diagnosed during a previous pregnancy. Hence paying attention to ascertain the etiology of anemia identified in pregnant women and following them up during the postnatal period would be beneficial in view of providing a continuum of care.

Compared to primiparous women and women who had a pregnancy within the last five years, having had the last pregnancy five or more years back was associated with an increased risk for anemia. A study among non-pregnant women has also shown a similar trend of increased prevalence of anemia with the increased pregnancy gap [55]. Similarly, having breastfed a baby within the last year is also protective of anemia after controlling for age and pregnancy gap. These findings contrast with previous global literature showing that breastfeeding and lower pregnancy gaps increase the risk for anemia in women [13, 14]. A possible contextual explanation for this would be that recent contact with the public health system could be beneficial for maintaining the nutritional status of women in this community. Newly married women can attend the periconceptional clinics and receive nutritional supplementations and advice. Nutritional supplements are continued from the antenatal period to six months postpartum. Having a child under five years of age also brings the family to frequent close contact with the public health system. Attention given to women and children during the first few years of delivery through domiciliary and clinic care provided by the primary health care personnel is high in Sri Lanka. In the context where interpregnancy care is not strong or well structured, women who do not have frequent contact with the public health system may be at a disadvantage [33].

Contraceptive choices were associated with anemia, probably through alterations to menstrual blood loss. Hormonal contraceptives like DMPA have been shown to reduce anemia risk [23]. DMPA can cause temporary cessation of menstruation in many users [56]. Reduced menstrual loss may allow women to maintain their hemoglobin and iron levels. Copper IUCD provided by the national family planning program is the commonly used type of IUCD, which is known to increase menstrual blood loss and reduce iron stores in women [57, 58]. This may predispose women to develop anemia in the first trimester of pregnancy, especially when it occurs on top of already depleted nutritional stores or minor hemoglobinopathy variants. As IUCD is considered an ethnically appropriate modern method due to the absence of hormonal effects and is used by 10% of reproductive-age females in the country, it would be valuable to investigate the above observation further [59]. Providing adequate follow-up for contraceptive users and prompt treatment of excessive menstrual bleeding associated with contraceptive methods could help reduce anemia in reproductive-age females leading to a reduction of anemia in early pregnancy.

Comparable to global evidence [13], underweight pregnant women had 1.64 (95% CI 1.24–2.18) times more risk of being anemic than pregnant women with normal BMI. This signifies the association between anemia and nutrition during pre-pregnancy periods. A study among primary school children from the same setting has also shown an association between BMI and anemia, indicating that anemia and macro-nutrient deficiencies may be linked through common causative factors [60]. However, the income level or assets such as vehicles were not statistically significantly associated with anemia in the current study.

The study was conducted in a rural district of the country. The study’s internal validity is high as the total study population was invited to participate, and the participation rate was high (86%). However, inter-district variations in the epidemiological patterns of anemia should be considered when generalizing the results to the country or beyond.

Conclusion

Looking at the reproductive and nutrition-related associations to early pregnancy anemia in the current study results, we hypothesize that being in frequent contact with the national family health program succeeds over socioeconomic disparities in preventing anemia in early pregnancy. Therefore, quantitative and qualitative improvement of already implemented nutritional interventions is important, and attention should be paid to maintaining them even during crises like the SARS Covid-19 pandemic. Even though the national program focuses on a continuum of care across the life cycle, interpregnancy care and care for eligible couples are still not strong. Strategies to mend this gap will reduce the burden of anemia in pregnancy through assessment and optimization of the macro and micronutrient status of women prior to pregnancy.

Data used for the analysis.

(XLS)

Click here for additional data file.

8 Jun 2022

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Comments to the Author

1. Is the manuscript technically sound, and do the data support the conclusions?

The manuscript must describe a technically sound piece of scientific research with data that supports the conclusions. Experiments must have been conducted rigorously, with appropriate controls, replication, and sample sizes. The conclusions must be drawn appropriately based on the data presented.

Reviewer #1: Yes

Reviewer #2: Yes

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2. Has the statistical analysis been performed appropriately and rigorously?

Reviewer #1: Yes

Reviewer #2: Yes

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3. Have the authors made all data underlying the findings in their manuscript fully available?

The PLOS Data policy requires authors to make all data underlying the findings described in their manuscript fully available without restriction, with rare exception (please refer to the Data Availability Statement in the manuscript PDF file). The data should be provided as part of the manuscript or its supporting information, or deposited to a public repository. For example, in addition to summary statistics, the data points behind means, medians and variance measures should be available. If there are restrictions on publicly sharing data—e.g. participant privacy or use of data from a third party—those must be specified.

Reviewer #1: Yes

Reviewer #2: Yes

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4. Is the manuscript presented in an intelligible fashion and written in standard English?

PLOS ONE does not copyedit accepted manuscripts, so the language in submitted articles must be clear, correct, and unambiguous. Any typographical or grammatical errors should be corrected at revision, so please note any specific errors here.

Reviewer #1: Yes

Reviewer #2: Yes

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5. Review Comments to the Author

Please use the space provided to explain your answers to the questions above. You may also include additional comments for the author, including concerns about dual publication, research ethics, or publication ethics. (Please upload your review as an attachment if it exceeds 20,000 characters)

Reviewer #1: Although the manuscript has merit, unfortunately there is abundance of literature published since 2018 on this topic and in similar settings. There is very little that this study adds to existing knowledge base. Examples of similar recent published studies include:

Amarasinghe GS, Agampodi TC, Mendis V, Malawanage K, Kappagoda C, Agampodi SB. Prevalence and aetiologies of anaemia among first trimester pregnant women in Sri Lanka; the need for revisiting the current control strategies. BMC pregnancy and childbirth. 2022 Dec;22(1):1-2.

Andersen CT, Cain JS, Chaudhery DN, Ghimire M, Higashi H, Tandon A. Assessing public financing for nutrition in Bhutan, Nepal and Sri Lanka. Maternal & Child Nutrition. 2022 Mar 21:e13320.

Abeywickrama HM, Koyama Y, Uchiyama M, Shimizu U, Iwasa Y, Yamada E, Ohashi K, Mitobe Y. Micronutrient status in Sri Lanka: a review. Nutrients. 2018 Nov;10(11):1583.

Reviewer #2: Dear author/s,

I have tried to assess your paper and it is a kind of problem-solving research and sounds good. But there are still some unclear issues in the paper and you are expected to work on them. The journal guidelines should be followed and you can find other comments and suggestions in the main text of your paper.

Regards,

Fufa

**********

6. PLOS authors have the option to publish the peer review history of their article (what does this mean?). If published, this will include your full peer review and any attached files.

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Do you want your identity to be public for this peer review? For information about this choice, including consent withdrawal, please see our Privacy Policy.

Reviewer #1: No

Reviewer #2: Yes: FUFA ABUNNA

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Submitted filename: plos one.docx

Click here for additional data file.

27 Jun 2022

Reviewer #2: Dear author/s,

I have tried to assess your paper and it is a kind of problem-solving research and sounds good. But there are still some unclear issues in the paper and you are expected to work on them. The journal guidelines should be followed and you can find other comments and suggestions in the main text of your paper.

Thank you very much for the comments. I have addressed all the concerns raised in the manuscript and a point-by-point reference to them are added below.

How is it possible to deal with a self-administered questionnaire? Are they professionals? I think it should have been made via interview.

Thank you for raising this concern. This community has a high (95%) level of literacy level[1]. In addition to that, participants who found it difficult to read and write were helped by data collectors. The self-administered questionnaire was simple and short with minimum writing and involvement. It was used to obtain data on mainly diet. Before administering we pilot tested the questionnaire and necessary amendments were made while it was made sure that it could be read and understood by participants. We included this in the manuscript LN-112- 113

“All the tools were developed specifically for the study and were translated into the local languages (Sinhala and Tamil). They were validated by a panel of multidisciplinary experts including a consultant community physician, social epidemiologist, hematologist, and physicians and public health midwives working in the area where the study is conducted. Tools were pretested among 20 pregnant women with the same eligibility criteria but registered in the maternal care program prior to the study period. The questions were amended according to the results of pretesting in order to make sure they were comprehendible by participants.”

(Having a vehicle at home)- Is it important for this research?

Thank you for this point. Yes, having a vehicle at home and other indicators resembling household assets and housing conditions were used as proxy indicators for socio-economic status. We have experienced that asking about household income is not that reliable in studies conducted in this location possibly as many residents are full-time or part-time farmers with variable income over the months. So, assets are more reliable as a measure of economic status over time. It was included in the multivariate analysis as this variable showed a statistically significant association with anemia in the bivariable analysis. The table 1 was r splitted into two and reclassified to make this point clear. The point was mentioned in the newly added paragraph on measures LN-153-156

“Proxy indicators; using a water sealed toilet, having electricity at home, having a mobile phone, using biomass fuel for cooking, drinking water filtered using Reverse Osmosis, having a vehicle at home were used to represent socio-economic status.”

Which model?

Thank you. We meant the Regression model. This was clarified in the text. LN- 32

Keywords

Thank you for pointing this out. Keywords were inserted

Did u translate the questionnaire to the local language? Otherwise very difficult to understand some technical terminologies

Thank you very much. Yes. All the tools were translated into the two local languages, Sinhala and Tamil, and pretested. A clarification was added in the text. LN-112

“ All the tools were developed specifically for the study and were translated into the local languages (Sinhala and Tamil).”

A reference to tools available online was also added to the manuscript.

Full blood count - Is it done manually or using a machine?

It was done with a machine (Beckman 03 part hematological analyzer )

Teenage - define

Thank you for pointing this out. We added a clarification to the text. We considered below 20 years as teenage. LN - 179

Not clear – Fig 1 Hemoglobin distribution of first-trimester pregnant women by the period of gestation

Thank you. The figure caption was changed as follows.

“Fig 1 Haemoglobin level of first trimester pregnant women by the period of gestation”

Which statistical software did u use?

We used SPSS version 22. This has been mentioned in the Methods section of the manuscript. LN-158

It is very difficult to understand this table, either divide the table into separate descriptions or reduce its contents. Above all, it lacks clarity, cut-off points, and definitions. It is better to use graphs, pie charts, and other methods of data presentations

Thank you very much for the suggestion. I have added a paragraph under the Measures to clarify the variables and definitions that have been used in this table. LN 128 - 156

“ Measures

Anemia was defined as a hemoglobin level less than 11 g/dl. Minor hemoglobinopathies were identified based on the red cell index (microcytic anemia with a high red cell count), which showed a 100% positive predictive value in the HPLC tested subsample(15). Independent variables included demographic factors, reproductive and gynecological factors, uptake of health services, diet, nutritional status, current health status and socio-economic conditions. During the completion of the interviewer-administered questionnaire, the expected date of delivery was verified with ultrasound confirmation whenever possible, and this was reassessed during the follow-up of the cohort. PoG was calculated using the date of last menstrual period (LRMP) reported by the woman, and ultrasound confirmed date of delivery and data were triangulated decide the most appropriate value. Maternal age was calculated using the date of birth. Education level of the participant and her husband, number of family members living with the participant (family size), parity, number of children, gap between the previous and current pregnancy and duration of using different contraceptive methods were recorded as ordinal values and categorized later. Among women with regular menstrual cycles, who use sanitary pads, menstrual blood loss per cycle was calculated using a scoring system on the data obtained from the pictogram (score of 1, 5 and 20 given when each used sanitary pad was lightly, moderately or completely stained when changed, respectively and 5 was added if clots are passed) (18). Average blood loss per year was calculated based on the cycle length. This variable was binned into three equal percentiles. A score out of five was allocated to the frequency of consuming food items given in the questionnaire (1 for never, 5 for daily). Scores were added up as necessary (e.g.: scores for consuming chicken, other meat, freshwater fish, sea fish, canned fish, sprats, and dry fish were combined for the variable ‘Frequency of consuming meat/fish’). The combined score was binned into three based on equal percentiles to determine low, moderate, and high consumption levels). BMI below 18.5 kg/m2 was considered underweight and BMI of 25 kg/m2 was considered overweight/ obese category(19). Monthly income was also binned into four based on equal percentiles. Proxy indicators; using a water sealed toilet, having electricity at home, having a mobile phone, using biomass fuel for cooking, drinking water filtered using Reverse Osmosis, having a vehicle at home were used to represent socio-economic status.”

The table was split into two for clarity. The first one includes demographic and health related variables whereas the second one includes social and economic variables.

How is age defined? From their ID of birth certificate? Better to reduce the categories

Thank you for raising this issue. We collected the birth date of the participants and calculated the age for the date of data collection. This clarification was added to the methods section (see above). We also reduced the number of age categories in Table 1 and updated the statistics as suggested.

Why you mix these two ethnicities? Either make correction in the methods part otherwise it looks as if it is ethnic ‘cleansing’

Thank you pointing this out. We mixed it as the percentage having a minor hemoglobinopathy was higher among the Moore/ Malay ethnicity. Since it does not seem to be appropriate, I changed the categories as Sinhala, Moore, and other (Burgher, Malay, other). (Table 1)

Has regular menstrual cycles- Is it not difficult to explain this.? How is irregularity defined? Do women have the experience of registering their menstrual cycle? I think this is more subjective. Either you have to set a cutoff point to define irregularity!

We assumed that women would have an understanding of their menstrual cycle is generally regular or irregular. These are women still in their first-trimester. So, they will remember their menstrual periods. This was not found problematic during the pretesting or data collection. Further it’s a routine question asked from pregnant women in getting the history in Sri lanka by both the Public Health Midwives and Medical Officers. Hence the question is well understood by the community and well received.

Average menstrual blood loss before pregnancy - Again this is more of subjective! What is it? The number of days or volume of blood?

Thank you for raising this issue. We used a pictogram to identify the extent of filling and the number of pads in the amount of filling. Then a calculation was made about the blood loss based on a previous publication[2]. This was multiplied by the number of periods over a year based on the cycle length. The calculation was made only for women with regular cycles and using sanitary pads. This was clarified in the measures section (please see above). This method is used in previous studies in the same population[3].

Dietary intake - Still these are more subjective. What is low, moderate or high or low? Please set a kind of cut-off Points.

Thank you for pointing out this deficiency. A detailed explanation of the variable was added to the paragraph on measures (please see above).

Folic acid supplements - How do they know these supplements?

Thank you for raising this concern. Folic acid supplements are provided free of charge through the public health midwife. Since health education is provided on this at preconception care and at the registration of pregnancy (participants are those registered for the maternal care program) and the supplement is given to mothers with the registration, they are more aware of it even by name. We also used the term “small white pill” to recognize the pill during the interview as it is the appearance of the tablet distributed by the medical supplies department at that time.

Have/ Had the habit of betel chewing (ever) - what is it

Thank you for pointing this out. Betel leaves (piper betle) are chewed often with areca nuts, Lyme, tobacco and sometimes different herbs. I added the scientific nomenclature for clarity (Table 2).

Monthly family income – cutoff

Thank you for pointing this out. The description was added in the paragraph on measures.

It is not well discussed. It is better to focus on very important findings. What is new in this study? What makes this study special and different from other studies conducted elsewhere in the globe.

Thank you for pointing this out. I have revised the discussion section to focus more on important findings. I added the following component to highlight the usefulness of the study. LN- 237 - 252

“Review of global literature shows that factors associated with anemia in pregnancy are diverse and depend on the context(20). Health and social inequities play a central role in occurrence of anemia(21,22). Sri Lanka is unique in the global health landscape as it has a good public health infrastructure, well established, accessible and affordable maternal care services with high coverage and better gender equity compared to countries with similar economic characteristics(23,24). Studying the factors associated with maternal anemia in this context would provide unique information on opportunities and challenges that could be anticipated as low- and middle-income countries move forward with anemia reduction goals by improving health care coverage.”

Reviewer #1: Although the manuscript has merit, unfortunately there is abundance of literature published since 2018 on this topic and in similar settings. There is very little that this study adds to existing knowledge base. Examples of similar recent published studies include:

Amarasinghe GS, Agampodi TC, Mendis V, Malawanage K, Kappagoda C, Agampodi SB. Prevalence and aetiologies of anaemia among first trimester pregnant women in Sri Lanka; the need for revisiting the current control strategies. BMC pregnancy and childbirth. 2022 Dec;22(1):1-2.

Andersen CT, Cain JS, Chaudhery DN, Ghimire M, Higashi H, Tandon A. Assessing public financing for nutrition in Bhutan, Nepal and Sri Lanka. Maternal & Child Nutrition. 2022 Mar 21:e13320.

Abeywickrama HM, Koyama Y, Uchiyama M, Shimizu U, Iwasa Y, Yamada E, Ohashi K, Mitobe Y. Micronutrient status in Sri Lanka: a review. Nutrients. 2018 Nov;10(11):1583.

Thank you for the comment. However, it seems that the reviewer has mistakenly assumed the content in this manuscript describe etiological factors (such as micronutrient deficiencies) which are commonly described in global literature under associated factors’. In fact, one of the papers given as example of similar literature describe the etiologies related to anemia in the same sample of women, published separately due to the clear distinction of two entities we adopted in conducting the research (as well as due to the scope being too large to be published as a single paper). This study describes an explanatory model for anemia in early pregnancy.

Studies looking at associated factors have clearly shown how diverse and context-specific they could be. We believe that a similar study has not been conducted in a lower-middle income setting where anemia prevalence remains relatively high despite a multitude of targeted interventions (please see reply to previous reviewer comment). Such a study will reflect the gaps of current strategies and points towards potential remedial actions, which is the uniqueness of the study.

“Local studies reporting data on factors associated with anemia have employed heterogeneous study samples impairing the ability to generate an in-depth understanding of the determinants of maternal anemia, which would be invaluable to design further anemia control strategies. Therefore, we conducted this study to identify the factors associated with early pregnancy anemia in a large community-based sample of pregnant women from a single geographical area in the country.” LN 88-95

Review of global literature shows that factors associated with anemia in pregnancy are diverse and depend on the context(30). Health and social inequities play a central role in the occurrence of anemia(31,32). Sri Lanka is unique in the global health landscape as it has a good public health infrastructure, well-established, accessible, and affordable maternal care services with high coverage and better gender equity compared to countries with similar economic characteristics(33,34). Findings of this study provides unique information on opportunities and challenges that could be anticipated as low- and middle-income countries move forward with anemia reduction goals by improving health care coverage.” LN 249

Reference

1. Department of Census and Statistics Ministry of National Policies and Economic Affairs. Sri Lanka Demographic and Health Survey 2016. Colombo; 2017.

2. HIGHAM JM, O’BRIEN PMS, SHAW RW. Assessment of menstrual blood loss using a pictorial chart. Br J Obstet Gynaecol. 1990;97:734–9.

3. Chathurani U, Dharshika I, Galgamuwa D, Wickramasinghe N, Agampodi T, Nugegoda D, et al. Association between menstrual blood loss before pregnancy and microcytic hypochromic anemia during pregnancy among currently pregnant women in Anuradhapura district. 2014.

Submitted filename: Responce to reviewers.docx

Click here for additional data file.

1 Sep 2022

Factors associated with early pregnancy anemia in rural Sri Lanka: Does being 'under care' iron out socioeconomic disparities?

PONE-D-22-01123R1

Dear Dr. Agampodi,

We’re pleased to inform you that your manuscript has been judged scientifically suitable for publication and will be formally accepted for publication once it meets all outstanding technical requirements.

Within one week, you’ll receive an e-mail detailing the required amendments. When these have been addressed, you’ll receive a formal acceptance letter and your manuscript will be scheduled for publication.

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If your institution or institutions have a press office, please notify them about your upcoming paper to help maximize its impact. If they’ll be preparing press materials, please inform our press team as soon as possible -- no later than 48 hours after receiving the formal acceptance. Your manuscript will remain under strict press embargo until 2 pm Eastern Time on the date of publication. For more information, please contact onepress@plos.org.

Kind regards,

Rubeena Zakar, Ph.D

Section Editor

PLOS ONE

Additional Editor Comments (optional):

Reviewers' comments:

Reviewer's Responses to Questions

Comments to the Author

1. If the authors have adequately addressed your comments raised in a previous round of review and you feel that this manuscript is now acceptable for publication, you may indicate that here to bypass the “Comments to the Author” section, enter your conflict of interest statement in the “Confidential to Editor” section, and submit your "Accept" recommendation.

Reviewer #1: All comments have been addressed

Reviewer #2: All comments have been addressed

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2. Is the manuscript technically sound, and do the data support the conclusions?

The manuscript must describe a technically sound piece of scientific research with data that supports the conclusions. Experiments must have been conducted rigorously, with appropriate controls, replication, and sample sizes. The conclusions must be drawn appropriately based on the data presented.

Reviewer #1: Yes

Reviewer #2: Yes

**********

3. Has the statistical analysis been performed appropriately and rigorously?

Reviewer #1: Yes

Reviewer #2: Yes

**********

4. Have the authors made all data underlying the findings in their manuscript fully available?

The PLOS Data policy requires authors to make all data underlying the findings described in their manuscript fully available without restriction, with rare exception (please refer to the Data Availability Statement in the manuscript PDF file). The data should be provided as part of the manuscript or its supporting information, or deposited to a public repository. For example, in addition to summary statistics, the data points behind means, medians and variance measures should be available. If there are restrictions on publicly sharing data—e.g. participant privacy or use of data from a third party—those must be specified.

Reviewer #1: Yes

Reviewer #2: Yes

**********

5. Is the manuscript presented in an intelligible fashion and written in standard English?

PLOS ONE does not copyedit accepted manuscripts, so the language in submitted articles must be clear, correct, and unambiguous. Any typographical or grammatical errors should be corrected at revision, so please note any specific errors here.

Reviewer #1: Yes

Reviewer #2: Yes

**********

6. Review Comments to the Author

Please use the space provided to explain your answers to the questions above. You may also include additional comments for the author, including concerns about dual publication, research ethics, or publication ethics. (Please upload your review as an attachment if it exceeds 20,000 characters)

Reviewer #1: Thank you for addressing the comments highlighted in the previous review. The manuscript is now suitable for publication in the journal. This article will add to the existing knowledge base in this area within a LMIC settings.

Reviewer #2: (No Response)

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7. PLOS authors have the option to publish the peer review history of their article (what does this mean?). If published, this will include your full peer review and any attached files.

If you choose “no”, your identity will remain anonymous but your review may still be made public.

Do you want your identity to be public for this peer review? For information about this choice, including consent withdrawal, please see our Privacy Policy.

Reviewer #1: No

Reviewer #2: Yes: FUFA ABUNNA

**********

26 Sep 2022

PONE-D-22-01123R1

Factors associated with early pregnancy anemia in rural Sri Lanka: Does being ‘under care’ iron out socioeconomic disparities?

Dear Dr. Agampodi:

I'm pleased to inform you that your manuscript has been deemed suitable for publication in PLOS ONE. Congratulations! Your manuscript is now with our production department.

If your institution or institutions have a press office, please let them know about your upcoming paper now to help maximize its impact. If they'll be preparing press materials, please inform our press team within the next 48 hours. Your manuscript will remain under strict press embargo until 2 pm Eastern Time on the date of publication. For more information please contact onepress@plos.org.

If we can help with anything else, please email us at plosone@plos.org.

Thank you for submitting your work to PLOS ONE and supporting open access.

Kind regards,

PLOS ONE Editorial Office Staff

on behalf of

Dr. Rubeena Zakar

Section Editor

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