Burden of preconception morbidity in women of reproductive age from an urban setting in North India.

BACKGROUND: There is a growing interest in the life course approach for the prevention, early detection and subsequent management of morbidity in women of reproductive age to ensure optimal health and nutrition when they enter pregnancy. Reliable estimates of such morbidities are lacking. We report the prevalence of health or nutrition-related morbidities, specifically, anemia, undernutrition, overweight and obesity, sexually transmitted infections (STIs) or reproductive tract infections (RTIs), diabetes or prediabetes, hypothyroidism, hypertension, and depressive symptoms, during the preconception period among women aged 18 to 30 years.
METHODS: A cross-sectional study was conducted among 2000 nonpregnant married women aged 18 to 30 years with no or one child who wished to have more children in two low- to middle-income urban neighborhoods in Delhi, India, in the context of a randomized controlled trial. STIs and RTIs were measured by symptoms and signs, blood pressure by a digital device, height by stadiometer and weight by a digital weighing scale. A blood specimen was taken to screen for anemia, diabetes, thyroid disorders and syphilis. Maternal depressive symptoms were assessed using the Patient Health Questionnaire-9 (PHQ-9). Multivariable logistic regression analysis was performed to identify sociodemographic factors associated with individual morbidity.
RESULTS: Overall, 58.7% of women were anemic; 16.5%, undernourished; 26%, overweight or obese; 13.2%, hypothyroid; and 10.5% with both symptoms and signs of STIs/RTIs. There was an increased risk of RTI/STI symptoms and signs in undernourished women and an increased risk of diabetes or prediabetes in overweight or obese women. An increased risk of undernutrition was also observed in women from lower categories of wealth quintiles. A decreased risk of moderate to severe anemia was seen in overweight women and those who completed at least secondary education.
CONCLUSIONS: Our findings show a high burden of undernutrition, anemia, RTIs, hypothyroidism and prediabetes among women in the study. This information will aid policymakers in planning special programs for women of reproductive age.

Introduction

Optimal health and nutritional status are essential for women of reproductive age. Early screening and treatment of morbidities are important to enable women to be prepared for future pregnancy [1, 2]. Anemia, under- or overnutrition, sexually transmitted infections (STIs) or reproductive tract infections (RTIs), hypothyroidism, diabetes and hypertension have been shown to be associated with an increased risk of adverse birth outcomes such as prematurity or small for gestational age (SGA) [3-5]. Specifically, anemia has been associated with the likelihood of having a baby born with low birth weight (LBW); underweight has been associated with LBW and preterm birth; smoking has been associated with preterm birth; and hypothyroidism has been associated with preterm birth, intrauterine growth restriction and LBW [3-5].

These associations have been largely based on observational studies. More recently, interventions delivered during prepregnancy and pregnancy, including additional food supplements for pregnant women with undernutrition, has been reported to increase birth weight and reduce SGA births [6]. The lack of planning for pregnancy and low rates of contraception use are of concern, as women are underprepared to enter pregnancy [7]. Detection and management of these morbidities through evidence-based intervention packages before pregnancy is important, as pregnancy is often reported several weeks post conception. Furthermore, some measures can be effective only when applied prior to conception, such as folic acid for the prevention of neural tube defects and adequate management of hypothyroidism [8, 9].

Reliable estimates of these morbidities in women of reproductive age are lacking in India.

We report the prevalence of anemia, undernutrition, overweight and obesity, STIs/RTIs, chronic diseases such as diabetes, prediabetes, hypothyroidism, and hypertension, and depressive symptoms among women aged 18 to 30 years residing in two urban neighborhoods in South Delhi, India. We also present associations of these morbidities with sociodemographic and economic factors.

Materials and methods

Subjects

A cross-sectional study among 2000 nonpregnant married women aged 18 to 30 years with no or one child who wished to have more children was conducted in two low- to middle-income urban neighborhoods in Delhi in the context of a randomized controlled trial (CTRI/2017/06/008908). In this trial, we conducted a door-to-door survey from July 1, 2017 to December 31, 2017 covering all households in Sangam Vihar and Dakshinpuri to identify 18- to 30-year-old married nonpregnant women living with their husbands who had no or one child and wished to have more children. The poorest households (~20%) were excluded, as these households were without concrete roofing, toilets, water connection and legal electricity. Based on the population included, the results will be generalizable to most of the low- to middle-income population in urban India [10]. Women who did not give consent were excluded.

Study procedures

Trained study workers assessed symptoms of STIs/RTIs. They measured blood pressure (Omron HBP 1300 digital blood pressure device; Omron Healthcare India), height (Seca-213 stadiometer) and clothed weight (Salter 9509 weighing scale) [11-13]. A nonfasting blood specimen was obtained from women who were allocated to the intervention group of the randomized controlled trial to screen for anemia (hemoglobin), diabetes (HbA1c), thyroid disorder [thyroid-stimulating hormone (TSH) and free thyroxine (FT4)] and syphilis (rapid plasma reagin; RPR).

Three milliliters of blood was collected in an evacuated tube containing ethylenediamine tetraacetic acid (EDTA; Becton Dickinson) to estimate the complete blood count (CBC) and HbA1c level, and 7 ml was collected in trace element-free serum-separating tubes. The sample was centrifuged at ~450 × g at room temperature for 10 minutes. The separated serum was transported in a cold box (4° to 8° C) to the Strand-Quest Diagnostics laboratory for TSH, ferritin, FT4 and RPR analyses [14].

The CBC parameters were measured on an LH 750 analyzer using AccuCount technology, an advanced analytical technique combining the Coulter principle of impedance counting and sizing with new sophisticated mathematical algorithms [15]. Serum ferritin was assessed using chemiluminescence in a Siemens Advia Centaur XP [16]. TSH and free T4 assays were performed using competitive immunoassay with direct chemiluminescence using acridinium ester technology [17]. HbA1c was assessed using the high-performance liquid chromatography technique in TOSOH-G8 [18]. The RPR test was performed by the flocculation technique [19].

Definitions used

Anemia was defined as severe (hemoglobin: <8 g/dl), moderate (hemoglobin: 8–10.99 g/dl) or mild (hemoglobin: 11–11.99 g/dl) [20]. Low serum ferritin was defined by a cutoff of <30 ng/ml [21]. Undernutrition (BMI: <18.5 kg/m2) was categorized as severe (BMI: <16 kg/m2) or moderate (BMI: 16 to 18.49 kg/m2). Overweight was defined as a BMI of 25 to 29.99 kg/m2, and obesity was defined as a BMI ≥30 kg/m2 [22]. Prediabetes was defined as HbA1c between 5.7% and 6.4%, and diabetes was defined as HbA1c ≥6.5% [23]. Women were treated with thyroxine if TSH levels were >5.5 IU/mL or if TSH levels were between 4.0 and 5.5 IU/mL and FT4 levels were <0.89 ng/dL [24]. Women were defined as stunted if their height was <150 cm [< -2 standard deviations (SDs) of the World Health Organization (WHO) standards; https://www.who.int/childgrowth/en/].

The symptoms of STIs/RTIs were assessed by trained study workers. An STI/RTI was considered if any one of the following symptoms were reported: swelling in the groin, dysuria, genital ulcer or sore, itching or burning sensation in the genital region, vaginal discharge, and pain in the lower abdomen. All women reporting one or more symptoms were examined by a physician, and an RTI was confirmed if any of the following signs were present: sores, blisters or ulcers in the genital area; foul-smelling, greenish or curdy white vaginal discharge; cervical erosion or mucopurulent pus at the cervical os; vaginal erythema with discharge; vulvar erythema, edema or induration; palpable lymph nodes in the inguinal area; and painful or palpable adnexa on bimanual examination, lower abdominal tenderness, or cervical motion tenderness [25]. Syphilis was diagnosed by the RPR test [25].

Depressive symptoms were assessed using the PHQ-9 questionnaire validated for the Indian population [26]. Severe depressive symptoms were defined as PHQ-9 scores ≥15, and moderate depressive symptoms were defined as PHQ-9 scores between 10 and 14 [27].

Hypertension was based on physician confirmation of a systolic blood pressure ≥140 mm Hg and/or diastolic blood pressure ≥90 mm Hg [28]. If an initial blood pressure reading of ≥140/90 mm Hg was detected, a repeat measurement was taken after two days had passed. If the reading was still ≥140/90 mm Hg, the woman was referred to a tertiary care hospital (Safdarjung Hospital) for further assessment by a physician.

The wealth index was calculated for each participant by performing a principal component analysis based on all assets owned by the household, as done in national surveys [29]. The variables used were the source of drinking water; source of electricity; type of sanitation facility; type of cooking fuel used; construction material of the roof, floor and walls of the house; ownership of items such as a mattress, a pressure cooker, a chair, a cot/bed, a table, an electric fan, a radio/transistor, a black and white television, a color television, a sewing machine, a mobile telephone, any other telephone, a computer, a refrigerator, a watch or clock, a bicycle, a motorcycle or scooter, an animal-drawn cart, a car, a water pump, a thresher, a tractor and a house; number of household members sleeping in a room; and ownership of a bank or post-office account [29]. The total scores were used to divide the population into five equal wealth quintiles: the poorest, very poor, poor, less poor and the least poor.

Ethical approvals

The ongoing trial is being conducted according to the guidelines outlined in the Declaration of Helsinki and is approved by the ethics committees of the Society for Applied Studies, New Delhi (SAS/ERC/LG/2017); Vardhman Mahavir Medical College and Safdarjung Hospital (IEC/SJH/VMMC/PROJECT-2017/694), New Delhi; and WHO, Geneva (ERC.0002934).

Written individual informed consent in the local language was obtained from the participants prior to enrollment. For those who were unable to read, the form was read aloud, and in those who were unable to sign, a thumb imprint was taken as witnessed by an impartial literate witness.

Sample size

Sample size calculations were based on confidence interval using single proportion with relative precision. A sample size of 2000 women would enable us to measure the prevalence of specific morbidity (anemia, undernutrition, STIs/RTIs, hypothyroidism, overweight or obesity) with a relative precision ranging between 10% and 30%, at 5% alpha level and a nonresponse rate of 20%. Sample sizes table is provided in S1 Table.

Statistical analysis

We used STATA version 15.1 (Stata Corporation, College Station, TX) for statistical analyses. Proportions and 95% confidence intervals (CI)) were calculated for categorical variables by binomial exact method, and means (SDs) or medians (interquartile ranges; IQRs) were calculated for continuous variables. One-way ANOVA was used to compare the mean serum ferritin values across anemia groups.

Multivariable logistic regression analysis was performed to identify baseline covariates (women’s age, education, occupation and BMI; religion of the head of the family; wealth quintile; and family structure) independently associated with each morbidity (moderate to severe anemia, hypothyroidism, undernutrition, overweight or obesity, prediabetes or diabetes, and symptoms and signs of RTI/STI). We included all baseline variables in each of the multivariable regression models. The multivariable logistic regression models were assessed for independence of observations, specification error, goodness-of-fit, multicollinearity, and influential observations [30]. We also used the “margins” command to calculate the predicted probability of each baseline variable holding all the other explanatory variables constant for each morbidity (S2 Table).

Results

The baseline characteristics of the 2000 women included in this study are shown in Table 1. Approximately 35% of the women (692/2000) were stunted (height <150 cm). Nearly 80% (1632/1985) were Hindu by religion, and 45% (887/1985) belonged to the bottom two quintiles of the wealth index. The median (IQR) family income per year was 3333.3 (2500, 4300) USD, 90% of the households had bank accounts, and all enrolled households had concrete roofs and toilets, water connections within the house premises and legal electricity connections.

Table 1

Baseline characteristics of surveyed participants.

Participant and Family/Household Characteristics
	n = 2000
Age in years, mean (SD)	24.1 (2.9)
Height in cm, mean (SD)	152.3 (5.6)
Proportion of women with height
<150 cm	692 (34.6)
≥150 cm	1308 (65.4)
Years of schooling	n = 1985
Median (IQR)	10 (8, 12)
Occupation	n = 1985
Housewife	1872 (94.3)
Working	113 (5.7)
Religion of the head of the household
Hindu	1632 (82.2)
Muslim	336 (16.9)
Others	17 (0.9)
Family structure*
Nuclear	792 (39.9)
Extended or joint	1194 (60.1)
Total family income per year (in USD)
Median (IQR)	3333.3 (2500, 4300)
Wealth quintiles
Poorest	382 (19.2)
Very poor	505 (25.4)
Poor	481 (24.2)
Less poor	390 (19.7)
Least poor	226 (11.4)
Any member of the household covered by a health scheme/health insurance	226 (11.5)

All values are number (percentages) unless stated otherwise

*Extended family: Family unit living with parents, their children and other dependent blood relatives; Joint family: parents and their male children with their families living together in a household.

Prevalence of morbidities

The prevalence of morbidities in the women who participated in the survey is summarized in Fig 1. Of the total women, 16% (95% CI: 14.4–17.7) did not have any previously listed morbidity, 84% (95% CI: 82.2–85.5) had one morbidity, 25% (95% CI: 23.1–27.0) had two morbidities and 5% (95% CI: 4.1–6.1) had 3 or more morbidities. Of the 2000 women, hemoglobin, TSH and HbA1c levels were ascertained in 98.9%; BMI, in all; symptoms of STIs/RTIs, in 99.9%; hypertension, in 99.3%; and PHQ-9 scores, in 96.1%.

Fig 1

Prevalence of morbidity among nonpregnant married women aged 18 to 30 years residing in low- to middle-income urban communities in Delhi.

Overall, 58.7% (95%CI: 56.5–60.9) of the women (1162/1979) had anemia, 16.5% (95%CI: 14.9–18.2) (330 women) were undernourished, and 26% (95%CI: 24.3–28.2) (525 women) were overweight or obese. In the 1979 women assessed, 13.2% (95%CI: 11.7–14.7) (261 women) were eligible for treatment with thyroxine. Prediabetes was detected in 10.8% (95%CI: 9.4–12.2) of participants, and only 0.7% (95%CI: 0.4–1.2) (14 women) had diabetes. Approximately one-tenth of the participants had both symptoms and signs of STIs/RTIs. In 29.9% (95%CI: 27.8–31.9) of the women, anemia was moderate to severe.

The prevalence of morbidities that would require treatment under medical supervision in a hospital or at the primary care level is shown in Table 2. The former category included severe anemia, hypothyroidism, diabetes, hypertension, STIs/RTIs by syndromic diagnosis, undernutrition, obesity and severe depressive symptoms; this comprised 32.3% of the study participants. Nearly half of the women had a morbidity that could be managed at the primary care level.

Table 2

Prevalence of morbidities by severity and appropriate level for care among women aged 18 to 30 years residing in low- to middle-income urban communities in Delhi.

Morbidity	Prevalence n (%)	95% CI
Women with any severe morbidity requiring specialized medical supervision and follow-up	624 (32.3)	30.2–34.4
[met criteria for treatment with thyroxine (hypothyroidism) or had symptoms and signs of STIs/RTIs, severe anemia (Hb<8 g/dl), severe undernutrition (BMI <16 kg/m2), severe depressive symptoms (PHQ-9 score ≥15), diabetes (HbA1c ≥6.5%), confirmed hypertension, or obesity (BMI ≥30 kg/m2)]
Women with conditions that could be treated at primary level care	1139 (60.5)	58.2–62.7
[moderate anemia (Hb 8 to 10.99 g/dl), moderate undernutrition (BMI: 16 to 18.49 kg/m2), prediabetes (HbA1c: 5.7 to 6.4%), moderate depressive symptoms (PHQ-9 score: 10–14), or overweight (BMI: 25 to 29.99 kg/m2)]

Table 3 shows serum ferritin levels according to the severity of anemia. Notably, nearly all severely anemic women and over two-thirds of moderately anemic women had low serum ferritin levels. The proportion of anemic women with low serum ferritin levels was significantly higher among those with severe (98.5%; 64/65) and moderate (87.3%, 453/519) anemia than in those with mild anemia (69.3%, 389/561). There was a significant difference in the mean serum ferritin levels between the mild, moderate and severe anemia categories (ANOVA; p<0.001).

Table 3

Proportion of anemic women with low serum ferritin levels (<30 ng/ml).

Anemia	Serum ferritin		Prevalence of low serum ferritin n (%)	95% CI
	Mean (SD)	Median (IQR)
Severe anemia, n = 65	4.3 (4)	4 (2–5)	64 (98.5)	91.7–99.9
Moderate anemia, n = 519	16.3 (20.5)	9 (6–18)	453 (87.3)	84.1–90.0
Mild anemia, n = 561	28.1 (42.7)	19 (10–33)	389 (69.3)	65.3–73.1

ANOVA; p<0.001

Table 4 shows the association between individual morbidity and baseline characteristics from the multivariable logistic regression analysis. Increasing levels of schooling were protective against moderate to severe anemia; the odds of having moderate or severe anemia were 40% and 60% lower, respectively, among women who had completed secondary or higher levels of education than among those who had never been to school. The odds of having moderate to severe anemia were 35% lower in overweight women than in women with normal BMI. The odds of having hypothyroidism increased 5% with each year increase in the age of the women. There was a significant association between undernutrition and wealth quintiles with a dose response in the relationship. The odds of being overweight or obese increased 24% with each year increase in the age of the women. The odds of being overweight or obese were 85% and 60% higher among women who were in the top two wealth quintiles than among those who were in the lowest wealth quintile.

Table 4

Multivariable analysis showing the association between baseline sociodemographic and anthropometry variables and individual morbidities.

	Adjusted OR (95% CI)*
	Moderate to Severe Anemia	Hypothyroidism	Undernutrition	Overweight or Obesity	Prediabetes or Diabetes	Symptoms and Signs of STIs/RTIs
Women’s age	0.97 (0.93–1.01)	1.05 (1.01–1.11)	0.91 (0.87–0.95)	1.24 (1.19–1.29)	1.12 (1.06–1.18)	1.01 (0.95–1.06)
Women’s years of schooling
None (0)	Ref	Ref	Ref	Ref	Ref	Ref
Primary (1–5)	0.78 (0.48–1.27)	0.65 (0.35–1.24)	1.13 (0.63–2.04)	0.16 (0.64–2.10)	1.20 (0.49–2.94)	2.32 (0.98–5.50)
Secondary (6–12)	0.58 (0.38–0.90)	0.55 (0.32–0.94)	0.92 (0.55–1.55)	1.10 (0.64–1.80)	1.09 (0.49–2.43)	1.70 (0.76–3.80)
Higher than secondary (>12)	0.40 (0.25–0.65)	0.63 (0.35–1.14)	0.81 (0.45–1.48)	1.11 (0.64–1.92)	1.31 (0.57–3.00)	1.31 (0.56–3.09)
Women’s occupation
Working	Ref	Ref	Ref	Ref	Ref	Ref
Housewife	0.90 (0.58–1.37)	0.71 (0.42–1.19)	0.94 (0.55–1.63)	0.79 (0.51–1.23)	0.76 (0.43–1.34)	0.56 (0.33–0.97)
Religion of head of the household
Others	Ref	Ref	Ref	Ref	Ref	Ref
Hindu	1.30 (0.99–1.70)	0.79 (0.56–1.11)	1.14 (0.82–1.57)	0.62 (0.47–0.82)	1.02 (0.67–1.54)	0.76 (0.53–1.09)
Wealth quintiles
Poorest	Ref	Ref	Ref	Ref	Ref	Ref
Very Poor	0.93 (0.69–1.25)	1.35 (0.89–2.07)	0.67 (0.48–0.93)	1.16 (0.82–1.65)	1.15 (0.68–1.95)	0.97 (0.62–1.52)
Poor	1.05 (0.77–1.42)	1.16 (0.74–1.81)	0.64 (0.44–0.91)	1.21 (0.85–1.72)	1.37 (0.81–2.32)	1.04 (0.66–1.66)
Less Poor	0.90 (0.63–1.26)	1.22 (0.76–1.99)	0.49 (0.32–0.75)	1.85 (1.28–2.69)	1.78 (1.03–3.05)	1.08 (0.65–1.79)
Least Poor	0.98 (0.66–1.47)	0.98 (0.55–1.73)	0.40 (0.24–0.70)	1.59 (1.04–2.43)	1.74 (0.95–3.20)	1.23 (0.69–2.20)
Family structure
Nuclear	Ref	Ref	Ref	Ref	Ref	Ref
Extended/Joint	0.92 (0.74–1.14)	1.04 (0.77–1.40)	0.95 (0.73–1.24)	0.84 (0.66–1.06)	0.89 (0.64–1.23)	1.20 (0.87–1.66)
Women’s BMI
18.5 to 24.99 kg/m2	Ref	Ref			Ref	Ref
<18.5 kg/m2	1.29 (0.99–1.67)	0.70 (0.46–1.07)			0.76 (0.44–1.33)	1.80 (1.24–2.60)
25 to 29.99 kg/m2	0.65 (0.49–0.86)	0.99 (0.71–1.40)			2.43 (1.72–3.45)	1.09 (0.73–1.61)
≥ 30 kg/m2	0.67 (0.42–1.07)	1.05 (0.60–1.84)			9.29 (5.93–14.56)	1.24 (0.66–2.31)

*Estimates (OR) are shown for the variables included in the multivariable logistic regression model. For each condition, the comparator group was all women.

The risk of prediabetes or diabetes increased with overweight and obesity compared to normal weight. The odds of having prediabetes or diabetes increased by 12% with each year increase in the age of the women.

The odds of women having positive symptoms and signs of STIs/RTIs were 80% higher among women with BMI <18.5 kg/m2 than among women with normal BMI (18.5 to 24.99 kg/m2).

All multivariable logistic regression models were assessed for specification error, goodness-of-fit, multicollinearity and influential observations. We did not find any significant specification error and influential observations for any of the multivariable logistic regression models. Hosmer and Lemeshow goodness-of-fit statistics show that all models fit the data well. Variables included in the models did not show any collinearity. Details of the diagnostics for each model are provided in S3 Table.

Discussion

The salient finding of the study is that nearly half of the women of reproductive age in the study had a morbidity that could be managed within the primary health care system. Furthermore, in nearly one-third of the women, the nature of the morbidity was such that it would require management under careful medical supervision in a hospital setting. We observed an increased risk of RTI/STI symptoms and signs in undernourished women, diabetes or prediabetes in overweight or obese women and a decreased risk of moderate to severe anemia in overweight women. The relevance of these findings needs to be viewed in the context of the high burden of adverse birth outcomes such as preterm births and SGA babies in India and other low- and middle-income countries [31].

In our study, the high prevalence of hypothyroidism is of serious concern [24]. In human studies, hypothyroidism during early pregnancy has been associated with an increased risk of neurocognitive deficits in offspring, pregnancy loss and placental abruption [32]. Considering the high prevalence of hypothyroidism among women in the preconception period and its adverse impact on pregnancy and fetal outcomes, timely screening of hypothyroidism before the planning of pregnancy and adequate management is critical. The observed prevalence of RTIs in ~10% of the women using the syndromic approach was lower than that observed in previous studies [33]. A previous study in a similar north Indian setting reported a 40% prevalence of RTIs in women aged 14–70 years [33]. Furthermore, etiological agents of RTI were detected in 12.5% of women with no symptoms [33]. The significance of asymptomatic colonization in the occurrence of adverse birth outcomes is unclear. We observed an increased risk of symptoms and signs of RTIs in undernourished women. Undernutrition may lower immune function and increase susceptibility to infection. The prevalence of prediabetes was similar to the findings from another study in India [34]. The link between maternal hyperglycemia and metabolic disease risk in offspring has been suggested in experimental models [35]. The clinical significance of a maternal prediabetic state on birth outcomes is uncertain and needs more research. Using a depressive symptom assessment tool to assess mental health status, 1.5% of women were classified as having moderate to severe depressive symptoms and in need of medical care. This was similar to the findings from the National Mental Health Survey (2015–16) in India, where the overall weighted prevalence of current depressive disorders in females older than 18 years was 2.97%, and in the age group of 18–29 years, it was 1.61% [36]. A national population-based survey showed that poor preconception mental health was associated with increased odds of experiencing any pregnancy complication and having LBW infants [37]. The data linking preconception mental health status and adverse birth outcome are limited.

In this study, the prevalence of anemia was similar to the national average reported in the National Family Health Survey; the prevalence of moderate to severe anemia was approximately 30% [29]. The serum ferritin findings in the anemic women in this study indicated that the vast majority of the moderately to severely anemic women had low serum ferritin and likely iron deficiency [38]. In the mildly anemic women, only half had low serum ferritin, indicating that other conditions may also account for anemia. In India, most anemic women receive weekly prophylaxis as a part of the national program rather than therapeutic doses of iron; this may be a cause of a persistence of high levels of anemia [39]. The risk of moderate to severe anemia was decreased in overweight women. Previous studies have also shown a decreased risk of anemia in overweight or obese women of reproductive age [40, 41]. Despite adiposity being protective against anemia, pregnant women who are overweight may have an increased risk of numerous other complications, including gestational diabetes, preeclampsia, pregnancy-induced hypertension, stillbirths, and preterm births [42]. Our study showed the dual burden of nutrition: 16.5% undernutrition and 25% overweight or obesity, which is similar to the national averages [29]. Prepregnancy underweight significantly increases the risk of preterm birth and SGA babies [4, 43]. Overweight, in particular obesity, may carry a higher risk of gestational diabetes and preterm birth [44]. Correction of aberrant nutritional status before conception seems important to reduce adverse birth outcomes and other consequences rather than initiation of corrective action only when pregnancy is confirmed.

Animal studies have shown that undernutrition or deficiency of specific nutrients and overnutrition can affect the embryo with a potential for future disease risk over their lifetime [2, 45–47]. Maternal overnutrition may cause defects in the mitochondrial phenotype, increased concentrations of inflammatory markers and chromosomal alterations in oocytes [2, 45–47]. Maternal undernutrition may reduce the concentration of circulating insulin and amino acids, which can lead to an altered growth trajectory of the fetus from before implantation [2, 45–47]. Disturbances in epigenetic mechanisms during early pregnancy may lead to an altered embryonic gene expression profile that persists through subsequent cell cycles and drives a modified developmental program [48].

The main strength of the current study was the careful ascertainment of morbidity using standard definitions and laboratory investigations performed in an internationally accredited laboratory. Our findings may be generalizable to 80% of similar populations of India [10]. Our estimate of women with both symptoms and signs of RTI was most likely an underestimate, as only 75% of those reporting symptoms agreed to a clinical examination.

There are several implications of the study findings. In countries such as India, special programs for adolescent health and nutrition have been initiated; however, their coverage and quality need improvement [49]. The adolescent health program ceases at 18 years of age, and consideration needs to be given to extend such a program to women up to 30 years of age. More research is required to estimate the prevalence of relevant health and nutrition disorders among women of reproductive age in India and the region. Health and nutrition disorders need to be managed prior to becoming pregnant and from early pregnancy to maximize the impact on birth outcomes. Improving primary health care, referral, and care at secondary and tertiary care hospitals are all important for the effective implementation of prepregnancy and pregnancy care in low- and middle-income countries.

Conclusions

The present study demonstrates a high burden of several noncommunicable diseases, nutritional problems and infectious diseases in women of reproductive age during the preconception period, which have serious adverse effects on pregnancy and birth outcomes. For women to enter pregnancy anemia free, nutritionally replete and infection free, a preconception health program is of utmost importance.

Sample sizes.

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Predicted probabilities of baseline socio-demographic and anthropometry variables for Individual morbidities.

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Diagnostics of multivariable logistic regression models.

(DOCX)

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27 Nov 2019

PONE-D-19-26942

Burden of preconception morbidity in women of reproductive age from an urban setting in North India

PLOS ONE

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Reviewers' comments:

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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

**********

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

Reviewer #1: Yes

Reviewer #2: Yes

**********

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: No

**********

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.

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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: This paper uses cross sectional data on 2,000 married women 18 to 30 years of age selected from two low-med socioeconomic urban neighborhoods in Delhi, India to study health and nutrition related morbidities that are related to poor birth outcomes. The descriptive results show high rates of undernutrition, anemia, reproductive tract infections, hypothyroidism, and prediabetes. Multivariate results using logistic regression demonstrate associations of these morbidities to a basic set of variables such as age, education, and wealth.

On the whole, this is a well done study and I only have minor comments:

1. Women who did not give consent were excluded. It would be good to know the how many women were excluded and any information on how they may differ from the analysis sample.

2. In the multivariate analysis, the authors only included baseline variables that had a p value less than .20 in bivariate analyses. This is typically not a good idea since the baseline variables are likely correlated and omitting variables could lead to biased effects for the included variables. A better strategy would be to use the complete set of baseline variables in all regressions.

3. The coefficients in a logistic regression are scaled by an unknown factor. As a result, marginal effects which are not scale dependent are also often reported. Marginal effects are straightforward to calculate using the STATA statistical software that the authors used.

Reviewer #2: Preconception health and nutrition are recognised to impact on maternal and birth outcomes and an understanding of the prevalence of maternal health conditions and sociodemographic correlates is therefore important and understudied in this setting. This is a generally well designed, conducted and written study. Please perform a thorough proof-read to improve readability and punctuation. For example ‘planning special programs for the women’, ‘was such that it would require to be managed ‘ etc. There is some inconsistency in reporting of outcomes (eg variable inclusion or exclusion of overnutrition) and I would clarify this throughout the manuscript. The discussion is somewhat simplistic and would benefit from restructuring.

Line 23- I would reword the abstract of ‘We report prevalence of health and nutrition-related morbidities specifically, anemia, undernutrition, overweight and obesity, sexually transmitted infections (STI) or reproductive tract infections (RTI), diabetes or prediabetes, hypothyroidism, hypertension, and depressive symptoms during the preconception period, among women aged 18 to 30 years’ to health OR nutrition-related as I’m unclear how STI and RTI’s are nutrition related?

Line 30 - As this is a subset of a randomised controlled trial, the generalisability of the population needs to be commented on as these women would have volunteered for recruitment to a much more intensive research study and hence would be assumed to be more motivated.

Line 39 - ‘Significant associations were observed for RTI/STI and undernutrition, hypothyroidism and diabetes or prediabetes with increasing age, low body mass index (BMI) and lower wealth quintiles. Anemia was inversely

associated with women’s years of schooling.’ Please format appropriately to make the dependent and independent variables clearer.

Line 53 – This is worded a little clumsily (eg ‘health-related morbidity’). Suggest rephrase

Line 54-57 – I would provide further detail here about exactly what morbidities are associated with exactly what outcomes.

Line 58-60 – I would distinguish here between the need for interventions during pregnancy to both manage under and over nutrition.

Line 66 – ‘Reliable estimates of these morbidities in women of reproductive age are lacking in India.’ Is this the main research gap of this study? I would state this more clearly in the introduction and discussion.

Line 81 – Provide data to support this in the results (eg Table 1).

Line 85 – Provide more detail on the signs and symptoms of STI/RTI assessed and how (eg clinical checklist based on what)?.

Line 86 – State if weight measured clothed/unclothed or fasting/non-fasting and if blood sample non-fasting.

Line 150 – Not all the morbidities mentioned in the abstract are in the sample size calculations (eg over nutrition). Please specify primary versus secondary outcomes (ideally a priori). Overnutrition is also mentioned in the discussion as an important morbidity despite lack of inclusion in these sample size calculations and regression models.

Line 159-160/Table 4- Again, not all outcomes are mentioned (eg over nutrition).

Line 161 – Please provide details of how the models were assessed for standard assumptions.

Line 167 – Provide definition of stunting in the methods.

Line 188 – From this sentence it sounds like overweight/obesity don’t warrant medical treatment, is this the case?

Provide data on the proportion of women who responded from the total eligible.

Figure 1 – Suggest provide in greyscale and 2D

Table 4 – Not all significant results are reported in the text (eg BMI and anaemia), I would clearly state all significant relationships and then explain these in more detail.

There are no line numbers in the discussion so it is difficult to make comments. The formatting of the discussion also makes it difficult to review as it’s difficult to see where new paragraphs sometimes commence. The discussion appears to be written in a way where there are numerous very short paragraphs without consistent description of the consistency of findings to prior research and potential mechanisms/implications of the findings. I would suggest restructuring to 5-6 larger paragraphs

‘Animal studies have shown that undernutrition or deficiency of specific nutrients and

physiological status including hyperglycemia can affect the embryo with a potential for their

future disease risk over their lifetime [2, 32-34]’ Please clarify mechanistically how different physiological states affect the embryo in different ways.

**********

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Reviewer #1: No

Reviewer #2: No

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9 Jan 2020

RESPONSES TO REVIEWERS

1. We note that you have indicated that data from this study are available upon request. PLOS only allows data to be available upon request if there are legal or ethical restrictions on sharing data publicly. For information on unacceptable data access restrictions, please see http://journals.plos.org/plosone/s/data-availability#loc-unacceptable-data-access-restrictions.

In your revised cover letter, please address the following prompts:

a) If there are ethical or legal restrictions on sharing a de-identified data set, please explain them in detail (e.g., data contain potentially identifying or sensitive patient information) and who has imposed them (e.g., an ethics committee). Please also provide contact information for a data access committee, ethics committee, or other institutional body to which data requests may be sent.

We have shared the dataset.

b) If there are no restrictions, please upload the minimal anonymized data set necessary to replicate your study findings as either Supporting Information files or to a stable, public repository and provide us with the relevant URLs, DOIs, or accession numbers. Please see http://www.bmj.com/content/340/bmj.c181.long for guidelines on how to de-identify and prepare clinical data for publication. For a list of acceptable repositories, please see http://journals.plos.org/plosone/s/data-availability#loc-recommended-repositories.

We will update your Data Availability statement on your behalf to reflect the information you provide.

We have uploaded the anonymized data set.

REVIEWER #1

This paper uses cross sectional data on 2,000 married women 18 to 30 years of age selected from two low-med socioeconomic urban neighborhoods in Delhi, India to study health and nutrition related morbidities that are related to poor birth outcomes. The descriptive results show high rates of undernutrition, anemia, reproductive tract infections, hypothyroidism, and prediabetes. Multivariate results using logistic regression demonstrate associations of these morbidities to a basic set of variables such as age, education, and wealth.

On the whole, this is a well done study and I only have minor comments:

1. Women who did not give consent were excluded. It would be good to know the how many women were excluded and any information on how they may differ from the analysis sample.

Of the women who had no other exclusion criteria, 13% did not consent to participate in the study. Some characteristics of the enrolled and non-enrolled women are given below.

Baseline characteristics of enrolled and non-enrolled women

Characteristics Enrolled women

(n=2000) Non-enrolled women

(n=869)

Height <150 cm, n (%) 34.6% 34.7%

Height (cm), Mean (SD) 152.3 (5.6) 151.7 (6.2)

Body Mass Index (kg/m2), Mean (SD) 22.6 (4.3) 22.9 (3.9)

Mid Upper Arm Circumference (cm), Mean (SD) 25.7 (3.7) 25.3 (3.1)

Women years of schooling, Median (IQR) 10 (8, 13) 10 (8, 12)

Total family income per year (INR), Median (IQR) 200000 (144000, 264000) 180000 (120000, 240000)

2. In the multivariate analysis, the authors only included baseline variables that had a p value less than .20 in bivariate analyses. This is typically not a good idea since the baseline variables are likely correlated and omitting variables could lead to biased effects for the included variables. A better strategy would be to use the complete set of baseline variables in all regressions.

We have rerun the multivariable regression models using all the baseline variables namely women’s age, years of schooling, occupation, religion, household wealth quintile, family structure, women’s BMI. We have updated Table 4 accordingly. No major changes were observed in the effect size and its 95% CI. (Table 4; Pages 16-17).

3. The coefficients in a logistic regression are scaled by an unknown factor. As a result, marginal effects which are not scale dependent are also often reported. Marginal effects are straightforward to calculate using the STATA statistical software that the authors used.

We agree that the coefficients in a logistic regression are scaled by an unknown factor specifically for categorical variables. We have used the following command in STATA “margins, dydx(*)” to calculate the predicted probability of each baseline variable holding all the other explanatory variables constant. We have provided the predicted probability of each baseline variable with each morbidity (moderate to severe anemia, hypothyroidism, undernutrition, overweight or obesity, prediabetes or diabetes and symptoms and signs of RTI/STI) in the Supplement Table 1. The inference from logistic regression models and margins model is the same.

We have accordingly modified the Statistical analysis section (Lines 189-194).

REVIEWER #2

Preconception health and nutrition are recognised to impact on maternal and birth outcomes and an understanding of the prevalence of maternal health conditions and sociodemographic correlates is therefore important and understudied in this setting. This is a generally well designed, conducted and written study.

Please perform a thorough proof-read to improve readability and punctuation. For example ‘planning special programs for the women’, ‘was such that it would require to be managed ‘ etc.

Thank you this suggestion. We hope that the manuscript reads better now.

There is some inconsistency in reporting of outcomes (eg variable inclusion or exclusion of overnutrition) and I would clarify this throughout the manuscript. The discussion is somewhat simplistic and would benefit from restructuring.

We have now included overnutrition (overweight or obesity) as an outcome. We have also restructured the Discussion section and hope that it provides better clarity now.

Line 23- I would reword the abstract of ‘We report prevalence of health and nutrition-related morbidities specifically, anemia, undernutrition, overweight and obesity, sexually transmitted infections (STI) or reproductive tract infections (RTI), diabetes or prediabetes, hypothyroidism, hypertension, and depressive symptoms during the preconception period, among women aged 18 to 30 years’ to health OR nutrition-related as I’m unclear how STI and RTI’s are nutrition related?

Thank you. We have rephrased the sentence as “We report the prevalence of health or nutrition-related morbidities, specifically, anemia, undernutrition, overweight and obesity, sexually transmitted infections (STIs) or reproductive tract infections (RTIs), diabetes or prediabetes, hypothyroidism, hypertension, and depressive symptoms, during the preconception period among women aged 18 to 30 years” (Lines 63-67).

Line 30 - As this is a subset of a randomised controlled trial, the generalisability of the population needs to be commented on as these women would have volunteered for recruitment to a much more intensive research study and hence would be assumed to be more motivated.

We excluded women living in temporary housing as they are likely to be relocated by the government in the near future. However, height, BMI, MUAC, years of schooling, total family income per year between enrolled and excluded women were not very different (see the table on Baseline characteristics of enrolled and non-enrolled women under Reviewer 1, Point 1). We have commented on the generalizability of the population in the Discussion section (Lines 365).

Line 39 - ‘Significant associations were observed for RTI/STI and undernutrition, hypothyroidism and diabetes or prediabetes with increasing age, low body mass index (BMI) and lower wealth quintiles. Anemia was inversely associated with women’s years of schooling.’ Please format appropriately to make the dependent and independent variables clearer.

We have rephrased the statement (see below) to clearly indicate dependent and independent variables (Lines 40-45). We hope that the dependent and independent variables are clearer now.

“There was an increased risk of RTI/STI symptoms and signs in undernourished women and an increased risk of diabetes or prediabetes in overweight or obese women. An increased risk of undernutrition was also observed in women from lower categories of wealth quintiles. A decreased risk of moderate to severe anemia was seen in overweight women and those who completed at least secondary education.

Line 53 – This is worded a little clumsily (eg ‘health-related morbidity’). Suggest rephrase

We have now rephrased this as:

“Optimal health and nutritional status are essential for women of reproductive age. Early screening and treatment of morbidities are important to enable women to be prepared for future pregnancy” (Lines 60-63).

Line 54-57 – I would provide further detail here about exactly what morbidities are associated with exactly what outcomes.

We have provided details on the outcomes and the associated morbidities (Lines 66-70).

“Specifically, anemia has been associated with the likelihood of having a baby born with low birth weight (LBW); underweight has been associated with LBW and preterm birth; smoking has been associated with preterm birth; and hypothyroidism has been associated with preterm birth, intrauterine growth restriction and LBW.”

Line 58-60 – I would distinguish here between the need for interventions during pregnancy to both manage under and over nutrition.

We have specified that interventions during pregnancy that are needed to manage undernutrition (Lines71-74).

Line 66 – ‘Reliable estimates of these morbidities in women of reproductive age are lacking in India.’ Is this the main research gap of this study? I would state this more clearly in the introduction and discussion.

The main research gap in India is lack of reliable estimates of health or nutrition related morbidities specifically, anemia, undernutrition, overweight and obesity, sexually transmitted infections (STIs) or reproductive tract infections (RTIs), diabetes or prediabetes, hypothyroidism, hypertension, and depressive symptoms among women of reproductive age.

Line 81 – Provide data to support this in the results (eg Table 1).

We have provided the following information in the Results section (Lines 203-206).

The median (IQR) family income per year was 3333.3 (2500, 4300) USD, 90% of the households had bank accounts, and all enrolled households had concrete roofs and toilets, water connections within the house premises and legal electricity connections.

Line 85 – Provide more detail on the signs and symptoms of STI/RTI assessed and how (eg clinical checklist based on what)?.

We are following “National Guidelines on Prevention, Management and Control of Reproductive Tract Infections including Sexually Transmitted Infections”, Ministry of Health and Family Welfare, Government of India (http://naco.gov.in/sites/default/files/National_Guidelines_on_PMC_of_RTI_Including_STI%201.pdf) for assessing symptoms and signs of STI/RTI. The symptoms and signs of STI/RTI are described in the Definition section; these are also summarized below. (Lines 134-144).

“The symptoms of STIs/RTIs were assessed by trained study workers. An STI/RTI was considered if any one of the following symptoms were reported: swelling in the groin, dysuria, genital ulcer or sore, itching or burning sensation in the genital region, vaginal discharge, and pain in the lower abdomen. All women reporting one or more symptoms were examined by a physician, and an RTI was confirmed if any of the following signs were present: sores, blisters or ulcers in the genital area; foul-smelling, greenish or curdy white vaginal discharge; cervical erosion or mucopurulent pus at the cervical os; vaginal erythema with discharge; vulvar erythema, edema or induration; palpable lymph nodes in the inguinal area; and painful or palpable adnexa on bimanual examination, lower abdominal tenderness, or cervical motion tenderness [25]. Syphilis was diagnosed by the RPR test.”

Line 86 – State if weight measured clothed/unclothed or fasting/non-fasting and if blood sample non-fasting.

The weight was measured with clothes on and non-fasting blood sample was drawn. These have been specified in the manuscript (Line 104).

Line 150 – Not all the morbidities mentioned in the abstract are in the sample size calculations (eg over nutrition). Please specify primary versus secondary outcomes (ideally a priori). Overnutrition is also mentioned in the discussion as an important morbidity despite lack of inclusion in these sample size calculations and regression models.

We have now calculated the sample size for prevalence of overweight or obesity. Assuming, prevalence of overweight or obesity as ~25%, with 15% relative precision and 95% confidence level, 512 women of reproductive age group are required.

We did multivariable logistic regression to examine the association between baseline covariates (women’s age, education, occupation and BMI; religion of the head of the family; wealth quintiles; family structure) with overweight or obesity. We have now included these estimates in Table 4 (Pages 16-17).

Line 159-160/Table 4- Again, not all outcomes are mentioned (eg over nutrition).

We have now included overnutrition (overweight or obesity) in Table 4 (Pages 16-17).

Line 161 – Please provide details of how the models were assessed for standard assumptions.

The multivariable logistic regression models were assessed for independency, specification error (“linktest” command in STATA to calculate linear predicted value (_hat) and linear predicted value squared (_hatsq) , goodness-of-fit (we used Hosmer and Lemeshow’s goodness-of-fit test), multicollinearity ( “collin” command in STATA), influential observations ( “predict” command in STATA).

Line 167 – Provide definition of stunting in the methods.

We have provided the definition of stunting [height <150 cm (< -2 standard deviations of the World Health Organization standards; https://www.who.int/childgrowth/en/] in the Methods section (Lines 131-134).

Line 188 – From this sentence it sounds like overweight/obesity don’t warrant medical treatment, is this the case?

We have now included overweight in the definition of women with conditions that could be treated at primary level care and obesity in definition of women with any severe morbidity requiring specialized medical supervision and follow up. Accordingly, we have revised Table 2 (Table 2; Page 13).

Provide data on the proportion of women who responded from the total eligible.

Of the total eligible women who met the inclusion criteria, 3604 (85%) women were enrolled and 675 (13%) did not give consent.

Figure 1 – Suggest provide in greyscale and 2D

We have modified Figure 1 as requested.

Table 4 – Not all significant results are reported in the text (e.g. BMI and anaemia), I would clearly state all significant relationships and then explain these in more detail.

We have now reported all significant results in the text (Lines 250-261) and explained these in greater details in the Discussion section (Lines 292-293; Lines 300-302; and Lines 322-327).

There are no line numbers in the discussion so it is difficult to make comments. The formatting of the discussion also makes it difficult to review as it’s difficult to see where new paragraphs sometimes commence. The discussion appears to be written in a way where there are numerous very short paragraphs without consistent description of the consistency of findings to prior research and potential mechanisms/implications of the findings. I would suggest restructuring to 5-6 larger paragraphs

We have restructured the Discussion into 6 paragraphs and added line numbers.

‘Animal studies have shown that undernutrition or deficiency of specific nutrients and

physiological status including hyperglycemia can affect the embryo with a potential for their future disease risk over their lifetime [2, 32-34]’ Please clarify mechanistically how different physiological states affect the embryo in different ways.

We have now clarified the mechanisms how different physiological status affect the embryo in different ways (Line 352-360).

Submitted filename: Responses to reviewers.docx

Click here for additional data file.

19 Mar 2020

PONE-D-19-26942R1

Burden of preconception morbidity in women of reproductive age from an urban setting in North India

PLOS ONE

Dear Dr. Bhandari,

Thank you for re-submitting your manuscript to PLOS ONE. We feel that it has greatly improved, but would like to ask you to make some minor changes to the manuscript, to meet PLOS ONE’s publication criteria. Therefore, we invite you to submit a revised version of the manuscript that addresses the minor points raised below.

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We look forward to receiving your revised manuscript.

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Frank Wieringa, M.D., Ph.D.

Academic Editor

PLOS ONE

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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 #3: (No Response)

**********

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 #3: Yes

**********

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

Reviewer #1: Yes

Reviewer #3: 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 #3: 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 #3: 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: (No Response)

Reviewer #3: A cross-sectional study was conducted to report the prevalence of health or nutrition-related morbidities during the preconception period among women from North India. The study also aimed to predict health and nutrition-related outcomes. The prevalence of health and nutrition-related morbidities ranged from 10 to nearly 60%.

Minor revisions:

1- Indicate the date range women participated in the study.

2- Line 164: Provide a more comprehensive sample size calculation.

State and justify the study’s target sample size with a pre-study statistical power calculation. The power calculation should include: sample size, alpha level (indicating one or two-sided), minimal detectable difference and statistical testing method.

3- Line 170: State the method used to estimate the 95% CIs.

4- Table 1: Indicate when frequency (%) are represented.

5- Line 203-8 : Provide 95% confidence intervals associated with the incidence percentages.

6- Table 3: Clarify that the 95% CIs are associated with the prevalence.

7- Include labeling that clearly identifies the morbidity factors.

8- The method section indicates that "multivariable logistic regression models were assessed for independence of observations, specification error, goodness-of-fit, multicollinearity and influential observations." Provide a summary of these indicators for each of the multivariate logistic models. Include a general statement about the fit in the results section, and include the full details as supplemental material.

**********

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 #3: No

[NOTE: If reviewer comments were submitted as an attachment file, they will be attached to this email and accessible via the submission site. Please log into your account, locate the manuscript record, and check for the action link "View Attachments". If this link does not appear, there are no attachment files to be viewed.]

While revising your submission, please upload your figure files to the Preflight Analysis and Conversion Engine (PACE) digital diagnostic tool, https://pacev2.apexcovantage.com/. PACE helps ensure that figures meet PLOS requirements. To use PACE, you must first register as a user. Registration is free. Then, login and navigate to the UPLOAD tab, where you will find detailed instructions on how to use the tool. If you encounter any issues or have any questions when using PACE, please email us at figures@plos.org. Please note that Supporting Information files do not need this step.

29 Apr 2020

RESPONSES TO REVIEWERS COMMENTS

REVIEWER #3:

A cross-sectional study was conducted to report the prevalence of health or nutrition-related morbidities during the preconception period among women from North India. The study also aimed to predict health and nutrition-related outcomes. The prevalence of health and nutrition-related morbidities ranged from 10 to nearly 60%.

Minor revisions

1- Indicate the date range women participated in the study.

The women were enrolled from July 1, 2017 to December 31, 2017 (Lines 86-87).

2- Line 164: Provide a more comprehensive sample size calculation.

State and justify the study’s target sample size with a pre-study statistical power calculation. The power calculation should include: sample size, alpha level (indicating one or two-sided), minimal detectable difference and statistical testing method.

Sample size calculations were based on confidence interval using single proportion with relative precision. We calculated sample size assuming a relative precision ranging between 10 and 30%, at 5% alpha level and assuming a non-response rate of 20% (Table below). These details have now been added under the section on sample size (Page 8). The table of sample sizes has been provided as Supplemental Table 1.

3- Line 170: State the method used to estimate the 95% CIs.

We used binomial exact method to estimate the 95% CIs.

4- Table 1: Indicate when frequency (%) are represented

Apologies, we have now indicated when frequencies (%) are represented (Page 10; Line 193)

5- Line 203-8: Provide 95% confidence intervals associated with the incidence percentages.

We have now provided 95% confidence intervals associated with the incidence percentages. (Pages 10-11)

6- Table 3: Clarify that the 95% CIs are associated with the prevalence.

We agree. The 95% CIs are associated with the prevalence.

7- Include labeling that clearly identifies the morbidity factors.

The following labeling was used for categorizing morbidities:

• Anemia: Reference category: No or mild anemia; other category: Moderate to severe anemia

• Hypothyroidism : Reference category: hypothyroidism absent ;other category: hypothyroidism present

• Undernutrition: Reference category: BMI � 18.5 kg/m2 ;other category: BMI <18.5 kg/m2

• Overweight and obesity : Reference category: BMI < 25 kg/m2 ; other category: BMI �25 kg/m2

• Prediabetes or Diabetes : Reference category: HbA1c <5.7%; other category: HbA1c �5.7%

• Symptoms and Signs of STIs/RTIs : Reference category: women who had either symptoms and no signs present or no symptoms present ;other category: women who had both symptoms and signs present

The baseline variables were labelled as;

• Women’s age : continuous variable

• Women’s education : Reference category :None; category 1: primary (1-5 years);category 2: secondary (6-12 years);category 3: higher than secondary (>12 years)

• Women’s occupation : Reference category: working outside home ; other category :not working (housewife)

• Women’s BMI : Reference category: BMI 18.5 to 24.99 kg/m2 ;category 1: BMI <18.5 kg/m2; category 2: BMI 25 to 29.99 kg/m2 and category 3: BMI� 30 kg/m2

• Religion of the head of the family : Reference category :others (religions than Hindu );other category Hindu

• Wealth quintiles: Reference category: poorest; category 1: very poor; category 2: poor; category 3: less poor; category 4: least poor

• Family structure : Reference category :nuclear families; other category extended/joint families

8- The method section indicates that "multivariable logistic regression models were assessed for independence of observations, specification error, goodness-of-fit, multicollinearity and influential observations." Provide a summary of these indicators for each of the multivariate logistic models. Include a general statement about the fit in the results section, and include the full details as supplemental material.

We have described the fit of the models in the results section (Lines 248-253). This is reproduced below

All multivariable logistic regression models were assessed for specification error, goodness-of-fit, multicollinearity and influential observations. We did not find any significant specification error and influential observations for any of the multivariable logistic regression models. Hosmer and Lemeshow goodness-of-fit statistics showed that all models fit the data well. Variables included in the models did not show any collinearity. Details of the diagnostics for each model are provided in Supplemental Table 2.

Submitted filename: Responses to reviewers comments_21042020.docx

Click here for additional data file.

3 Jun 2020

Burden of preconception morbidity in women of reproductive age from an urban setting in North India

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9 Jun 2020

PONE-D-19-26942R2

Burden of preconception morbidity in women of reproductive age from an urban setting in North India

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