Utilization of field health services among women with pre-pregnancy excess weight in Gampaha District, Sri Lanka: a lower middle-income country

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This is a preprint; it has not been peer reviewed by a journal. https://doi.org/ 10.21203/rs.3.rs-9507553/v1 This work is licensed under a CC BY 4.0 License Status: Under Review Version 1 posted 4 You are reading this latest preprint version Abstract Background The rising prevalence of pre-pregnancy excess weight represents a major challenge to achieving optimal maternal and neonatal health outcomes. Excess maternal weight is associated with increased pregnancy-related complications and greater health service utilization. Despite this growing burden, evidence on the utilization of maternal field health services for excess weight in Sri Lanka remains limited. Methods A descriptive cross-sectional study with an analytical component was conducted. Women identified as overweight or obese at the first antenatal clinic visit were recruited. The calculated sample size was 482, and data were collected using a two-stage sampling technique. Data collection tools included a judgmentally validated, interviewer-administered questionnaire and a structured data extraction sheet. Statistical analysis was performed using the Statistical Package for Social Sciences version 25. Descriptive statistics were used to summarize findings, while the Chi-square test and Mann–Whitney U test were applied at a 5% level of significance. Results A total of 427 pregnant women participated in the study with a response rate of 88.6%. The majority of participants were aged 20–39 years (95%), with an approximate overweight-to-obese ratio of 2:1. In the antenatal period, all received advice from Public Health Midwives (PHMs) regarding their elevated body mass index and associated pregnancy risks. Routine antenatal monitoring, including blood pressure and symphysio-fundal height measurement, was done on all participants. Most participants (93.7%) received regular domiciliary visits from PHMs. The primary source (78,6%) of information on BMI and weight management was MOH staff, including PHMs. Provision of personalized interventions was limited. Only 10.5% received individualized dietary plans, 4.9% were offered tailored physical activity plans, and 6.3% underwent dietary assessment using a 24-hour dietary recall. Referral to dietitians was rare, with only 3.0% of participants receiving such referrals. Conclusions Although routine antenatal and domiciliary services show high coverage among excess-weight women, gaps were identified in the delivery of individualized nutritional and lifestyle interventions. Strengthening multidisciplinary involvement and enhancing personalized maternal care strategies are essential to address the specific needs of overweight and obese pregnant women. Further studies incorporating multivariable analyses are warranted to determine independent predictors of service utilization gaps. Overweight in pregnancy Obesity in pregnancy Maternal BMI Antenatal care utilization Field health services Public Health Midwives Sri Lanka Gampaha District Figures Figure 1 Figure 2 Background Pregnancy is a critical phase in a woman’s life, involving profound changes that affect the mother, the family, and society. Ensuring a safe and healthy pregnancy while minimizing preventable pregnancy-related risks remains a public health priority. One of the most prominent risk factors for poor outcomes in pregnancy is pre-pregnancy excess weight. The global obesity epidemic transcends geographic boundaries and poses a major health system challenge, with poor weight management contributing to more deaths than smoking, alcohol consumption, and physical inactivity combined, accounting for approximately 12% of all deaths in the United Kingdom ( 1 ). Maternal overweight and obesity are associated with pregnancy complications and unfavorable long-term outcomes for both the mother and the child, including hypertensive disorders, cesarean sections, and gestational diabetes ( 2 – 8 ). Importantly, excess weight in pregnant women is a considerable burden on the health care system due to increased service utilization and pregnancy-related complications ( 9 ). Developing a comprehensive understanding of these factors is essential for achieving the targets of the United Nations Sustainable Development Goals ( 10 ). A woman’s pre-pregnancy Body Mass Index (BMI) is considered to be reflected from her BMI measured at the first clinic visit, referred to as the “Booking Visit”, which should take place before 12 weeks of amenorrhea. The term "excess weight" typically refers to both overweight and obesity. The Ministry of Health's (MoH) Nutrition Division divides Sri Lankan adults' BMI into five categories. “Underweight (BMI 30 kg/m 2 )”. Similar parameters are used to interpret pre-pregnancy BMI in pregnant women as well. Sri Lanka, a lower-middle-income country in South Asia, has historically had strong maternal and child health indicators and an extensive public health infrastructure. Public Health Midwives (PHMs) are the frontline grassroots health workers who provide domiciliary and clinic-based antenatal care, health education, and follow-up for women and children ( 11 ). A few of the PHM areas bond together and form into Medical Officer of Health (MOH) areas ( 12 ). First established in Kalutara in 1926, the MOH system now covers the entire country and represents the smallest administrative unit of public health in Sri Lanka ( 13 ). In Sri Lanka, the prevalence of pre-pregnancy excess weight has grown rapidly from 15% in 2017 to nearly 30% in 2019, according to the Family Health Bureau ( 14 ). Gampaha District, one of the most populous districts in Sri Lanka, has a population of 2,304,833 and a high population density of 1,802 persons per square kilometer ( 15 ). It is a multicultural and multireligious district with both urban and rural communities and ranks third nationally for the proportion of overweight and obese women. Given this context, the utilization of field health services for pre-pregnancy excess-weight women is crucial to improving maternal and neonatal outcomes. Sri Lanka’s field health services, PHMs, routinely record anthropometric measurements, provide individualized dietary counseling based on dietary recall, promote healthy lifestyle practices, and facilitate referrals to MOH services for further care. Evidence from international studies highlights gaps in personalized care for overweight women, suggesting that service contact alone is insufficient without tailored, high-quality interventions. With such targeted strategies, the Sri Lankan health system targeted to reduce the percentage of high BMI pregnant women at registration from 21.3% in 2015 to less than 10% by 2025 ( 16 ). In Sri Lanka, the extent of this care gap at the community level remains underexplored. Therefore, this study aimed to assess the utilization of available field health services among pre-pregnancy excess-weight women in selected MOH areas of Gampaha District, to identify service gaps and opportunities for improvement. Methodology Present study utilized a community-based descriptive cross-sectional design with an analytical component. Four Medical Officer of Health (MOH) areas in the Gampaha District, namely Biyagama, Mahara, Negombo, and Wattala were selected using random sampling. Out of all registered pregnant mothers in Gampaha district, 31.7% belong to these four MOH areas. The data collection period spanned from March 2022 to February 2023. These women were recruited based on specific eligibility criteria. They had a pre-pregnancy BMI of 25.0 kg/m² or higher, their children were less than one year old but beyond the neonatal period (older than 28 days), and they were over 18 years old at the time of booking their pregnancy. Exclusion criteria included not having accurate documentation of their pregnancy and postpartum periods, and those not consistently attending the selected MOH areas for antenatal care. The sample size was calculated using the formula for estimating a single population proportion described by Lwanga et al. (1991). After adjusting for a 20% non-response rate, the final required sample size was 482 pregnant women. The final sample consisted of 427 mothers aged 18–46 years, representing diverse ethnic and educational backgrounds. A two-step sampling method was used, first selecting four MOH areas using simple random sampling, followed by consecutive recruitment of eligible women attending Child Welfare Clinics (CWCs). The data collection methods involved a combination of structured, interviewer-administered questionnaires and cross-verification with maternal and neonatal health records. The structured questionnaire was reviewed by three public health experts for content validity and pre-tested at the Kiribathgoda Maternal and Child Health clinic to assess clarity and feasibility. Researchers visited clinics across the study setting areas for data collection. The same structured questionnaire was administered across all modes, with training provided to interviewers to ensure consistency. Data were analyzed using Statistical Package for Social Sciences version 26. Descriptive statistics were used to summarize variables. Primary outcome variables included receipt of individualized dietary advice, exercise plans, 24-hour dietary recalls, and referrals to dietitians. The main exposure variable was pre-pregnancy BMI, classified into overweight (25.0–29.9) and obese (≥ 30.0). Predictors included health services and interventions provided during the pregnancy period, while confounding factors such as maternal age, family income, and pre-existing medical conditions were also taken into account. Chi-square test and Mann–Whitney U tests were used at the significance level at 5%. Results Sociodemographic Characteristics A total of 427 participants were enrolled in the study, with ages ranging from 18 to 46 years and they all were excess weight (Table 1 ). With nearly half (n = 213; 49.9%) aged between 20 and 29 years. The mean (SD) age was 30.1 (5.05) years. Ethnically, most participants were Sinhalese (n = 336; 78.7%), followed by Sri Lankan Moors (13.6%) and Sri Lankan Tamils (6.6%). Educational attainment was relatively high, with 39.1% (n = 167) having passed the General Certificate of Education Advanced Level (GCE A/L or equivalent), while 38.9% (n = 166) had passed the Ordinary Level (GCE O/L or equivalent). Only 4.0% had a tertiary education. Less than one tenth (8.2%) had completed only primary education up to Grade 5. Most of the women were not working (n = 357; 83.6%). Of the 70 women who were employed, the most common occupation category was “Professionals” (n = 22; 31.43%) followed by “Clerical support workers” (14.3%) and “Craft-related trade workers” (12.9%), based on the International Standard Classification of Occupations (ISCO-08). Household income ranged from LKR 10,000 to LKR 500,000, with a median income of LKR 45,000 (IQR: 30,000–75,000). Around 67% of the women earned below LKR 60,000 per month, and only 6.6% had incomes above LKR 120,000. Three respondents could not provide income information. (1 USD = 300 LKR). Among employed participants, daily working hours ranged from 3 to 12 hours, with a mean (SD) of 8.88 (2.21) hours. Most worked between 5 and 10 hours per day (77.1%). Table 1 Sociodemographic Data of Participants Category Frequency Percentage (%) Age categories (n = 427) 19 years or less 10 2.3 20 to 29 years 213 49.9 30 to 39 years 195 45.7 39 years or more 9 2.1 Registered in the eligible family register before booking visit (n = 427) Registered 341 79.9 Not registered 86 20.1 Ethnicity (n = 427) Sinhalese 336 78.7 Sri Lankan Moor 58 13.6 Sri Lankan Tamil 28 6.6 Burgher 3 0.7 Indian Tamil 2 0.5 Employment status (n = 427) Employed 70 16.4 Non employed 357 83.6 Educational level (n = 427) Primary education – Grade five 35 8.2 Grade six – eleven 42 9.8 Studied up to passing GCE O/L only 166 38.9 Passed GCE A/L 167 39.1 Tertiary education 17 4.0 Maternal Anthropometric and Obstetric Characteristics The mean (SD) period of amenorrhea (POA) at booking was 7.0 weeks (1 week 4 days), with registration occurring as early as 4 weeks and 1 day and as late as 11 weeks and 6 days of gestation. Participants registering after 12 weeks were excluded. Of the total participants, 134 (31.4%) were primigravida, while 293 (68.6%) were multigravida, including four grand multigravidas (Fig. 1 ). A history of pregnancy loss was reported by 109 participants (25.5%), including miscarriages (23.2%), intrauterine deaths (0.9%), neonatal deaths (0.7%), and ectopic pregnancies (0.7%) (Fig. 1 ). Subfertility was reported by 100 participants (23.4%). Pre-existing diabetes mellitus prior to the last pregnancy was present in 27 participants (6.3%), while 19 participants (4.4%) had pre-existing hypertension. Based on pre-pregnancy BMI, the overweight percentage is 63.5% (n = 271), and Obese is 36.5% (n = 156) (Table 2 ). The mean (SD) pre-pregnancy BMI of participants was 29.26 (3.55) kg/m², with values ranging up to 44.3 kg/m². All women were informed by the PHM about their BMI status and the associated pregnancy risks. A family history of excess weight was reported by 115 participants (27.0%). Most participants (n = 388; 90.9%) reported low levels of physical activity prior to pregnancy. Moderate and vigorous physical activity levels were reported by 35 (8.2%) and 4 (0.9%) participants, respectively. Gestational weight gain ranged from 0 to 23.0 kg, with a mean (SD) gain of 7.16 (4.25) kg. Mean weight gain was higher among overweight participants (7.53 kg) compared to obese participants (6.52 kg) (Table 2 ). Only one-third of participants achieved the recommended gestational weight gain. Among overweight women, 32.8% achieved the expected weight gain, while 39.1% gained below and 28.0% gained above the recommended range. Among obese women, 36.5% achieved the expected weight gain, with 43.6% gaining below and 19.9% gaining above the recommended range (Table 2 ). Table 2 Pre-pregnancy BMI distribution and gestational weight gain characteristics among participants. Variable Overweight Obese Total BMI Distribution (n = 427) Number of Participants 271 156 427 Percentage (%) 63.5 36.5 100.0 Gestational weight gain (n = 427) Mean 7.5 kg 6.5 kg 7.1 kg Standard Deviation 4.3 kg 4.2 kg 4.2 kg Minimum 0.0 kg 0.1 kg 0.0 kg Maximum 23.0 kg 22.0 kg 23.0 kg Range 23.0 kg 21.9 kg 23.0 kg Achievement of the recommended weight gain Below recommendation, n (%) 106 (39.1) 68 (43.6) 174 (40.7) Within recommendation, n (%) 89 (32.8) 57 (36.5) 146 (34.2) Above recommendation, n (%) 76 (28.0) 31 (19.9) 107 (25.1) Registration and Coverage of Routine Field Health Services Most participants (n = 341; 79.9%) had been registered in the Eligible Family Register before their pregnancy booking visit. In Sri Lanka, PHM is supposed to do regular domestic visits and register eligible women in the Eligible Family Register, so that the services that are offered by PHM will not be missed. Body weight was recorded at all subsequent antenatal visits. Blood pressure and symphysio-fundal height (SFH) measurements were conducted and documented for all participants (n = 427, 100%) at every clinic visit, which reflects 100% service compliance for this critical initial step. A large majority (n = 400; 93.7%) received regular monthly domiciliary visits from PHMs, with no cases of loss to follow-up reported. Despite these strengths in routine care, several significant service gaps were identified in personalized care for overweight and obese women. Utilization of Pre-Conceptional, Antenatal Preventive Services Pre-conceptional care by the PHM was reported by 277 participants (64.6%), while 150 (35.1%) had not received or followed up pre-conceptional services. Pre-conceptional folic acid supplementation for at least three months before conception was reported by 248 participants (58.1%). Utilization of Personalized Weight-Related Interventions Although general dietary and physical activity advice was provided during antenatal health education sessions, issuing individualized management plans was limited. Only 22% of women were given dedicated time for BMI-related discussion. Just 10.5% (n = 45) received individualized diet plans. Only 5% (n = 21) were offered personalized physical activity plans. Referrals to dietitians were rare, with only 13 participants (3.0%) receiving such a referral. All 13 women (100%) referred to a dietitian followed through with the clinic visit, reflecting good adherence when referrals were made. This emphasizes the potential for improvement if referral pathways are strengthened. Dietary assessment through 24-hour dietary recall was conducted in only 27 women (6.3%). Among these, dietary adequacy assessments were used to provide targeted nutrition guidance. The vast majority (93.7%) did not receive this service. Difficulties with blood pressure cuffing due to upper arm circumference are often a challenge in obese individuals. This was reported in 2.3% of the cases (n = 10) (Fig. 2 ). Sources of Information on BMI and Weight Management Pregnant women in the study identified various sources from which they received information regarding Body Mass Index (BMI) and weight management during pregnancy. As shown in Table 3 , the majority (79%, n = 336) cited staff from the Medical Officer of Health (MOH) office, including PHMs and the Medical Officer of Health, as their primary source of information. Visiting Obstetricians and Gynecologists were mentioned by 9.8% (n = 42) of participants, while 2.1% (n = 9) received guidance from dietitians. Nutrition clinics and general practitioners (family doctors) each accounted for 1.9% (n = 8) of the information sources. Notably, 4.9% of mothers (n = 21) reported that they had not received any information regarding BMI or weight control from any healthcare provider. This highlights the central role of PHMs in health education, but also reveals gaps in multidisciplinary involvement. Table 3 Sources of Information on High BMI and Weight Control Source of Information Number Percentage PHM 218 51.0 MOH 118 27.6 VOG 42 9.8 Dietitian 9 2.1 Nutrition Clinic 8 1.9 Family medical officer 8 1.9 Ward nurse 3 0.7 No information received by the health sector 21 4.9 These results indicate that while frontline workers (Medical Officers of Health and PHMs) are the dominant source of BMI-related education, involvement from dietitians and specialized maternal care clinics is limited. The data show that although foundational antenatal practices like BMI screening and BP monitoring were universally implemented, personalized interventions such as individualized diet plans, exercise prescriptions, and nutritional referrals were not consistently offered. Only 3% of mothers were referred to a dietitian despite the known risks associated with pre-pregnancy obesity. Likewise, despite national maternal health guidelines encouraging tailored counseling for excess weight, only 22% of participants were provided an extended time by PHMs to discuss BMI concerns. This highlights a key area where frontline service delivery could be further strengthened. Discussion This study is among the first to describe field-level service utilization patterns for overweight and obese pregnant mothers in Sri Lanka. The study used a service “cascade” perspective that distinguishes routine antenatal contact from the content and personalization of care. Study findings revealed that routine maternal health services showed high coverage, with about 80% registered in the Eligible Family Register, 93.7% receiving PHM home visits, and 100% receiving standard antenatal monitoring. However, personalized weight-management care was limited. In the study, 64.6% reported pre-conception care, only 10.5% received individualized diet plans, 5% physical activity guidance, 3% dietitian referrals, and 6.3% dietary assessments, and only one-third achieved the recommended gestational weight gain. PHMs and MOH staff were the main sources of BMI-related information, highlighting a gap between high antenatal service coverage and limited individualized obesity-related care. Present study of 427 overweight or obese pregnant women indicated near-universal engagement with ANC care, virtually all women attended ANC and received standard services, reflecting Sri Lanka’s strong maternal health system. This aligns with many settings globally. For instance, in high-income countries (e.g., Australia and Canada), ANC coverage is also essentially universal, and women are typically weighed and have their BMI recorded at their first visit. In Australia, 59–62% of women reported being weighed or offered weight measurement at their initial visit (and 44% had height measured to calculate BMI) ( 17 ). Low- and middle-income countries (LMICs) have seen rising ANC utilization rates in recent years, though timely first-trimester booking can be lower in some regions ( 18 ). In middle- and low-income countries, pre-conception care is limited by low awareness, stigma, and poor healthcare access. In Sri Lanka, weight and nutrition counselling gaps, and COVID-19 disruptions have left many overweight women entering pregnancy without proper pre-pregnancy optimization during the study period. Even with these limitations, about two-thirds of overweight/obese women in Sri Lanka accessed pre-conception care. It is a higher rate than in many countries, but the guidance, especially on weight management, was insufficient. Globally, pre-conception care for obesity is underused, with many women in high-income countries entering pregnancy overweight and without adequate dietary or lifestyle counseling. In Australia, over 50% of women begin pregnancy overweight or obese, and many do not meet recommended diet and activity guidelines, reflecting poor pre-conception diet quality and weight optimization common in high-income countries. One report noted that 80% of Australian women fail to consume the recommended servings of vegetables, and 44% fall short on fruit intake, in the pre-conception period ( 22 ). These statistics underscore insufficient diet quality and weight optimization before pregnancy. The juxtaposition of high coverage and poor quality of care for managing maternal overweight is a consistent finding across countries of all income levels. In Sri Lanka, virtually every pregnant woman attends ANC (high coverage), yet, specifically with respect to quality, personalized dietary or weight-management support was lacking. Only 10.5% received an individualized diet plan, 5% got physical activity guidance, 3% were referred to a dietitian, and 6.3% had a 24-hour dietary recall. This limited utilization of tailored interventions is echoed in many other countries, indicating a global gap in translating obesity guidelines into practice. In high-income countries, personalized weight management in pregnancy is limited. Research in the United States and Canada shows that only about 28–30% of women receive specific weight-gain advice and about 12% receive guideline-consistent counseling, while lifestyle interventions remain poorly implemented in routine care ( 19 ). In an Australian survey (2018–2019), only about one-third of Australian women received advice on gestational weight gain, diet, or exercise at their first ANC visit, and fewer than 7% received complete weight-related care ( 20 ). Middle-income countries show a similar pattern of inadequate personalization as well. Studies in Thailand and Ethiopia report little to no individualized gestational weight gain counseling due to a lack of programs, training, and guideline awareness ( 18 , 21 ). Several limitations should be acknowledged in this study. First, the cross-sectional nature of the study restricts the ability to establish causality between excess maternal weight and service utilization patterns. Longitudinal or case-control designs would be more appropriate to explore temporal relationships and health outcomes. Second, the exclusion of adverse outcomes such as miscarriages, stillbirths, and neonatal deaths limits the comprehensiveness of the study. These complications, often associated with maternal overweight and obesity, are crucial indicators of care effectiveness and should be addressed in future studies. Third, selection bias cannot be ruled out, as only mothers who continued antenatal follow-up at selected CWCs and who had access to phone communication were included. This may underrepresent those with poorer service access or those experiencing the most severe complications. Fourth, the absence of multivariable analysis limits our ability to control for confounders such as maternal education, parity, and socioeconomic status. Conclusions and Recommendations Routine antenatal and domiciliary maternal health services demonstrated high coverage as reflected with all getting clinic-based services, more than 90% receiving and more than three fourth getting eligibility registrations among excess-weight womenThese findings indicate strong implementation and coverage of routine antenatal and field maternal health services among women with excess weight. However, customized care opportunities were not utilized by the majority for diet and physical activity-related services. Strengthening multidisciplinary services for managing issues on diet and physical activity must be promoted. Similarly, the enhancement of personalized maternal care strategies must be facilitated to address the specific needs of overweight and obese pregnant women. Further studies incorporating multivariable analyses are warranted to identify independent predictors of service utilization gaps and to address potential confounding. Leverage digital tools and community-based interventions to deliver weight management advice, including video-based education and text-based reminders. Ensure the availability of appropriate medical equipment, such as larger cuff sizes for blood pressure monitoring, to support high-BMI patient needs. Future research should include multivariable and longitudinal analyses to better understand predictors of poor service utilization and test interventions aimed at improving care equity and effectiveness in similar LMIC contexts. Abbreviations BMI Body Mass Index CWC / CWCs Child Welfare Clinic / Child Welfare Clinics FHB Family Health Bureau IQR Interquartile Range ISCO-08 International Standard Classification of Occupations 2008 kg/m² kilograms per square meter LMIC Low- and middle-income countries MOH Medical Officer of Health MoH Ministry of Health PHM / PHMs Public Health Midwife / Public Health Midwives POA Period of Amenorrhea SD Standard Deviation SDG / SDG 3 Sustainable Development Goal / Sustainable Development Goal 3 SFH Symphysio-fundal height SPSS Statistical Package for the Social Sciences UK United Kingdom Z Z value / Z-score Declarations Ethical Approval Ethical approval for this study was obtained from the Ethics Review Committee of the Postgraduate Institute of Medicine, University of Colombo. The study was conducted in accordance with ethical guidelines to ensure the rights, safety, and well-being of all participants. (Registration no.- ERC/PGIM/2022/080). Written informed consent was obtained from all participants before data collection. Participation was voluntary, and confidentiality and anonymity of the participants were strictly maintained throughout the study. Availability of data and materials The datasets generated and analyzed in the current study are not publicly available due to ethical and confidentiality considerations, but are available from the corresponding author on reasonable request. Competing Interest All authors declare that there are no competing interests in relation to this study. The authors have no financial, personal, or professional interests that could have influenced the conduct or outcomes of the research. Funding This research did not receive any specific grant from funding agencies in the public, commercial, or not-for-profit sectors. Authors’ contributions MLPKSM conceived the study, developed the study design, conducted data collection, performed data analysis, and drafted the manuscript. VK contributed to the study design, provided methodological guidance, critically reviewed the manuscript, and supervised the research process. Both authors read and approved the final manuscript. Acknowledgements The authors wish to acknowledge the Medical Officers of Health, Public Health Midwives, and clinic staff in the selected MOH areas of Gampaha District for their support during data collection. We are also grateful to all pregnant women who participated in the study for their time and cooperation. Authors’ information MLPKSM is a medical officer affiliated with the Office of the Provincial Director of Health Services, Western Province, Sri Lanka, with research interests in maternal health, public health services, occupational health, and health systems strengthening. He is a postgraduate candidate in MD in Community Medicine. He holds an undergraduate degree in Bachelor of Medicine and Bachelor of Surgery (MBBS), a Diploma in Occupational Health, and a Master of Science in Community Medicine. He is currently pursuing a Master of Business Administration (MBA). VK is a board-certified Specialist in Community Medicine and currently serves as Director, Non-Communicable Diseases, Ministry of Health, Sri Lanka. She holds an MBBS, MSc, and MD in Community Medicine, and has undertaken post-doctoral and research fellowships at Harvard School of Public Health, University of Melbourne, and Monash University. She has received multiple President’s Awards for scientific publications and has contributed to WHO expert groups and national NCD policy development. References Strauss A. Obesity in pregnant women: maternal, fetal, and transgenerational consequences. Eur J Clin Nutr. 2021;75(12):1681–3. Santos S, Voerman E, Amiano P, Barros H, Beilin LJ, Bergström A, et al. 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Antenatal care addressing gestational weight gain (GWG): a cross sectional study of pregnant women ’ s reported receipt and acceptability of recommended GWG care and associated characteristics. BMC Pregnancy Childbirth. 2024;24(111):1–15. Chairat T, Ratinthorn A, Limruangrong P, Boriboonhirunsarn D. Prevalence and related factors of inappropriate gestational weight gain among pregnant women with overweight / obesity in Thailand. BMC Pregnancy Childbirth [Internet]. 2023;1–15. Available from: https://doi.org/10.1186/s12884-023-05635-0 Mdietst HOC, Willcox JC, Mdietst CW, Wilkinson SA. Digital preconception interventions targeting weight, diet and physical activity : A systematic review. Nutr Diet. 2024;81(3):244–60. Additional Declarations No competing interests reported. Cite Share Download PDF Status: Under Review Version 1 posted Editorial decision: Revision requested 30 Apr, 2026 Editor assigned by journal 28 Apr, 2026 Submission checks completed at journal 28 Apr, 2026 First submitted to journal 23 Apr, 2026 You are reading this latest preprint version Research Square lets you share your work early, gain feedback from the community, and start making changes to your manuscript prior to peer review in a journal. As a division of Research Square Company, we’re committed to making research communication faster, fairer, and more useful. We do this by developing innovative software and high quality services for the global research community. Our growing team is made up of researchers and industry professionals working together to solve the most critical problems facing scientific publishing. Also discoverable on Platform About Our Team In Review Editorial Policies Advisory Board Help Center Resources Author Services Accessibility API Access RSS feed Manage Cookie Preferences © Research Square 2026 | ISSN 2693-5015 (online) Privacy Policy Terms of Service Do Not Sell My Personal Information {"props":{"pageProps":{"initialData":{"identity":"rs-9507553","acceptedTermsAndConditions":true,"allowDirectSubmit":false,"archivedVersions":[],"articleType":"Research Article","associatedPublications":[],"authors":[{"id":628421073,"identity":"7a6c6460-1db0-46b2-8703-bb251fc10dfc","order_by":0,"name":"Mahanama L.P.K.S.M.","email":"data:image/png;base64,iVBORw0KGgoAAAANSUhEUgAAAZAAAAAyAQMAAABI0h/eAAAABlBMVEX///8AAABVwtN+AAAACXBIWXMAAA7EAAAOxAGVKw4bAAAAuElEQVRIiWNgGAWjYFAC/u8/GBhsGBgkSNBjAFScRrqWwyRokW8/kGDwc8f5xP7ZzQcfMNTYRBO24kzCgcTeM7cTZ9w5lmzAcCwtt4GgFobEhgO8bbcTG27kmEkwNhwmrEW+/zFj49+2c4nzidbCcCONmZm37UDiBqK1GNx4w8Ys25ZsvPFGWrJBAjF+ke/PYWN822YnO+9G8sEHH2psiHAYFDiCVSYQqxwE7ElRPApGwSgYBSMMAADTy0JwuDcXRQAAAABJRU5ErkJggg==","orcid":"","institution":"University of Colombo","correspondingAuthor":true,"prefix":"","firstName":"Mahanama","middleName":"","lastName":"L.P.K.S.M.","suffix":""},{"id":628421074,"identity":"accd93ff-f1f0-4404-af5a-f69dc059d8ea","order_by":1,"name":"Kumarapeli V.","email":"","orcid":"","institution":"Ministry of Health","correspondingAuthor":false,"prefix":"","firstName":"Kumarapeli","middleName":"","lastName":"V.","suffix":""}],"badges":[],"createdAt":"2026-04-23 13:53:09","currentVersionCode":1,"declarations":"","doi":"10.21203/rs.3.rs-9507553/v1","doiUrl":"https://doi.org/10.21203/rs.3.rs-9507553/v1","draftVersion":[],"editorialEvents":[],"editorialNote":"","failedWorkflow":false,"files":[{"id":107839515,"identity":"0b9d712d-6e56-4640-860f-9d05358baf5a","added_by":"auto","created_at":"2026-04-26 17:22:47","extension":"png","order_by":1,"title":"Figure 1","display":"","copyAsset":false,"role":"figure","size":70149,"visible":true,"origin":"","legend":"\u003cp\u003e\u003cstrong\u003eParity and Pregnancy Loss Before the Last Pregnancy of the Participants of the Study.\u003c/strong\u003e\u003c/p\u003e","description":"","filename":"floatimage1.png","url":"https://assets-eu.researchsquare.com/files/rs-9507553/v1/a51dc0cde6b41bcfd9ff5514.png"},{"id":107839516,"identity":"29f136c5-ac78-49e4-97b0-1888159e1a1c","added_by":"auto","created_at":"2026-04-26 17:22:47","extension":"png","order_by":2,"title":"Figure 2","display":"","copyAsset":false,"role":"figure","size":51381,"visible":true,"origin":"","legend":"\u003cp\u003e\u003cstrong\u003eUtilization of Personalized Weight-Related Interventions\u003c/strong\u003e\u003c/p\u003e","description":"","filename":"floatimage2.png","url":"https://assets-eu.researchsquare.com/files/rs-9507553/v1/ec82650ef3128398411bce11.png"},{"id":107869609,"identity":"1280195a-fe16-459b-87ad-2bc6c4fc391c","added_by":"auto","created_at":"2026-04-27 07:37:33","extension":"pdf","order_by":0,"title":"","display":"","copyAsset":false,"role":"manuscript-pdf","size":378301,"visible":true,"origin":"","legend":"","description":"","filename":"manuscript.pdf","url":"https://assets-eu.researchsquare.com/files/rs-9507553/v1/08f1f23e-edda-4371-a40d-2b8bbf720a10.pdf"}],"financialInterests":"No competing interests reported.","formattedTitle":"Utilization of field health services among women with pre-pregnancy excess weight in Gampaha District, Sri Lanka: a lower middle-income country","fulltext":[{"header":"Background","content":"\u003cp\u003ePregnancy is a critical phase in a woman\u0026rsquo;s life, involving profound changes that affect the mother, the family, and society. Ensuring a safe and healthy pregnancy while minimizing preventable pregnancy-related risks remains a public health priority. One of the most prominent risk factors for poor outcomes in pregnancy is pre-pregnancy excess weight. The global obesity epidemic transcends geographic boundaries and poses a major health system challenge, with poor weight management contributing to more deaths than smoking, alcohol consumption, and physical inactivity combined, accounting for approximately 12% of all deaths in the United Kingdom (\u003cspan citationid=\"CR1\" class=\"CitationRef\"\u003e1\u003c/span\u003e). Maternal overweight and obesity are associated with pregnancy complications and unfavorable long-term outcomes for both the mother and the child, including hypertensive disorders, cesarean sections, and gestational diabetes (\u003cspan additionalcitationids=\"CR3 CR4 CR5 CR6 CR7\" citationid=\"CR2\" class=\"CitationRef\"\u003e2\u003c/span\u003e\u0026ndash;\u003cspan citationid=\"CR8\" class=\"CitationRef\"\u003e8\u003c/span\u003e). Importantly, excess weight in pregnant women is a considerable burden on the health care system due to increased service utilization and pregnancy-related complications (\u003cspan citationid=\"CR9\" class=\"CitationRef\"\u003e9\u003c/span\u003e). Developing a comprehensive understanding of these factors is essential for achieving the targets of the United Nations Sustainable Development Goals (\u003cspan citationid=\"CR10\" class=\"CitationRef\"\u003e10\u003c/span\u003e).\u003c/p\u003e \u003cp\u003eA woman\u0026rsquo;s pre-pregnancy Body Mass Index (BMI) is considered to be reflected from her BMI measured at the first clinic visit, referred to as the \u0026ldquo;Booking Visit\u0026rdquo;, which should take place before 12 weeks of amenorrhea. The term \"excess weight\" typically refers to both overweight and obesity. The Ministry of Health's (MoH) Nutrition Division divides Sri Lankan adults' BMI into five categories. \u0026ldquo;Underweight (BMI\u0026thinsp;\u0026lt;\u0026thinsp;18.5 kg/m\u003csup\u003e2\u003c/sup\u003e), normal weight (BMI 18.5\u0026ndash;22.9 kg/m\u003csup\u003e2\u003c/sup\u003e), risk of overweight (BMI 23.0\u0026ndash;24.9 kg/m\u003csup\u003e2\u003c/sup\u003e), overweight (BMI 25.0-29.9 kg/m\u003csup\u003e2\u003c/sup\u003e), and obesity (BMI\u0026thinsp;\u0026gt;\u0026thinsp;30 kg/m\u003csup\u003e2\u003c/sup\u003e)\u0026rdquo;. Similar parameters are used to interpret pre-pregnancy BMI in pregnant women as well.\u003c/p\u003e \u003cp\u003eSri Lanka, a lower-middle-income country in South Asia, has historically had strong maternal and child health indicators and an extensive public health infrastructure. Public Health Midwives (PHMs) are the frontline grassroots health workers who provide domiciliary and clinic-based antenatal care, health education, and follow-up for women and children (\u003cspan citationid=\"CR11\" class=\"CitationRef\"\u003e11\u003c/span\u003e). A few of the PHM areas bond together and form into Medical Officer of Health (MOH) areas (\u003cspan citationid=\"CR12\" class=\"CitationRef\"\u003e12\u003c/span\u003e). First established in Kalutara in 1926, the MOH system now covers the entire country and represents the smallest administrative unit of public health in Sri Lanka (\u003cspan citationid=\"CR13\" class=\"CitationRef\"\u003e13\u003c/span\u003e). In Sri Lanka, the prevalence of pre-pregnancy excess weight has grown rapidly from 15% in 2017 to nearly 30% in 2019, according to the Family Health Bureau (\u003cspan citationid=\"CR14\" class=\"CitationRef\"\u003e14\u003c/span\u003e).\u003c/p\u003e \u003cp\u003eGampaha District, one of the most populous districts in Sri Lanka, has a population of 2,304,833 and a high population density of 1,802 persons per square kilometer (\u003cspan citationid=\"CR15\" class=\"CitationRef\"\u003e15\u003c/span\u003e). It is a multicultural and multireligious district with both urban and rural communities and ranks third nationally for the proportion of overweight and obese women. Given this context, the utilization of field health services for pre-pregnancy excess-weight women is crucial to improving maternal and neonatal outcomes. Sri Lanka\u0026rsquo;s field health services, PHMs, routinely record anthropometric measurements, provide individualized dietary counseling based on dietary recall, promote healthy lifestyle practices, and facilitate referrals to MOH services for further care.\u003c/p\u003e \u003cp\u003eEvidence from international studies highlights gaps in personalized care for overweight women, suggesting that service contact alone is insufficient without tailored, high-quality interventions. With such targeted strategies, the Sri Lankan health system targeted to reduce the percentage of high BMI pregnant women at registration from 21.3% in 2015 to less than 10% by 2025 (\u003cspan citationid=\"CR16\" class=\"CitationRef\"\u003e16\u003c/span\u003e). In Sri Lanka, the extent of this care gap at the community level remains underexplored. Therefore, this study aimed to assess the utilization of available field health services among pre-pregnancy excess-weight women in selected MOH areas of Gampaha District, to identify service gaps and opportunities for improvement.\u003c/p\u003e"},{"header":"Methodology","content":"\u003cp\u003ePresent study utilized a community-based descriptive cross-sectional design with an analytical component. Four Medical Officer of Health (MOH) areas in the Gampaha District, namely Biyagama, Mahara, Negombo, and Wattala were selected using random sampling. Out of all registered pregnant mothers in Gampaha district, 31.7% belong to these four MOH areas. The data collection period spanned from March 2022 to February 2023. These women were recruited based on specific eligibility criteria. They had a pre-pregnancy BMI of 25.0 kg/m\u0026sup2; or higher, their children were less than one year old but beyond the neonatal period (older than 28 days), and they were over 18 years old at the time of booking their pregnancy. Exclusion criteria included not having accurate documentation of their pregnancy and postpartum periods, and those not consistently attending the selected MOH areas for antenatal care. The sample size was calculated using the formula for estimating a single population proportion described by Lwanga et al. (1991). After adjusting for a 20% non-response rate, the final required sample size was 482 pregnant women. The final sample consisted of 427 mothers aged 18\u0026ndash;46 years, representing diverse ethnic and educational backgrounds. A two-step sampling method was used, first selecting four MOH areas using simple random sampling, followed by consecutive recruitment of eligible women attending Child Welfare Clinics (CWCs).\u003c/p\u003e \u003cp\u003eThe data collection methods involved a combination of structured, interviewer-administered questionnaires and cross-verification with maternal and neonatal health records. The structured questionnaire was reviewed by three public health experts for content validity and pre-tested at the Kiribathgoda Maternal and Child Health clinic to assess clarity and feasibility. Researchers visited clinics across the study setting areas for data collection. The same structured questionnaire was administered across all modes, with training provided to interviewers to ensure consistency.\u003c/p\u003e \u003cp\u003eData were analyzed using Statistical Package for Social Sciences version 26. Descriptive statistics were used to summarize variables. Primary outcome variables included receipt of individualized dietary advice, exercise plans, 24-hour dietary recalls, and referrals to dietitians. The main exposure variable was pre-pregnancy BMI, classified into overweight (25.0\u0026ndash;29.9) and obese (\u0026ge;\u0026thinsp;30.0). Predictors included health services and interventions provided during the pregnancy period, while confounding factors such as maternal age, family income, and pre-existing medical conditions were also taken into account. Chi-square test and Mann\u0026ndash;Whitney U tests were used at the significance level at 5%.\u003c/p\u003e"},{"header":"Results","content":"\u003cdiv id=\"Sec4\" class=\"Section2\"\u003e \u003ch2\u003eSociodemographic Characteristics\u003c/h2\u003e \u003cp\u003eA total of 427 participants were enrolled in the study, with ages ranging from 18 to 46 years and they all were excess weight (Table\u0026nbsp;\u003cspan refid=\"Tab1\" class=\"InternalRef\"\u003e1\u003c/span\u003e). With nearly half (n\u0026thinsp;=\u0026thinsp;213; 49.9%) aged between 20 and 29 years. The mean (SD) age was 30.1 (5.05) years. Ethnically, most participants were Sinhalese (n\u0026thinsp;=\u0026thinsp;336; 78.7%), followed by Sri Lankan Moors (13.6%) and Sri Lankan Tamils (6.6%). Educational attainment was relatively high, with 39.1% (n\u0026thinsp;=\u0026thinsp;167) having passed the General Certificate of Education Advanced Level (GCE A/L or equivalent), while 38.9% (n\u0026thinsp;=\u0026thinsp;166) had passed the Ordinary Level (GCE O/L or equivalent). Only 4.0% had a tertiary education. Less than one tenth (8.2%) had completed only primary education up to Grade 5.\u003c/p\u003e \u003cp\u003eMost of the women were not working (n\u0026thinsp;=\u0026thinsp;357; 83.6%). Of the 70 women who were employed, the most common occupation category was \u0026ldquo;Professionals\u0026rdquo; (n\u0026thinsp;=\u0026thinsp;22; 31.43%) followed by \u0026ldquo;Clerical support workers\u0026rdquo; (14.3%) and \u0026ldquo;Craft-related trade workers\u0026rdquo; (12.9%), based on the International Standard Classification of Occupations (ISCO-08). Household income ranged from LKR 10,000 to LKR 500,000, with a median income of LKR 45,000 (IQR: 30,000\u0026ndash;75,000). Around 67% of the women earned below LKR 60,000 per month, and only 6.6% had incomes above LKR 120,000. Three respondents could not provide income information. (1 USD\u0026thinsp;=\u0026thinsp;300 LKR). Among employed participants, daily working hours ranged from 3 to 12 hours, with a mean (SD) of 8.88 (2.21) hours. Most worked between 5 and 10 hours per day (77.1%).\u003c/p\u003e \u003cp\u003e \u003cdiv class=\"gridtable\"\u003e\u003ctable float=\"Yes\" id=\"Tab1\" border=\"1\"\u003e \u003ccaption language=\"En\"\u003e \u003cdiv class=\"CaptionNumber\"\u003eTable 1\u003c/div\u003e \u003cdiv class=\"CaptionContent\"\u003e \u003cp\u003eSociodemographic Data of Participants\u003c/p\u003e \u003c/div\u003e \u003c/caption\u003e \u003ccolgroup cols=\"3\"\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c1\" colnum=\"1\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c2\" colnum=\"2\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c3\" colnum=\"3\"\u003e\u003c/div\u003e \u003cthead\u003e \u003ctr\u003e \u003cth align=\"left\" colname=\"c1\"\u003e \u003cp\u003eCategory\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c2\"\u003e \u003cp\u003eFrequency\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c3\"\u003e \u003cp\u003ePercentage (%)\u003c/p\u003e \u003c/th\u003e \u003c/tr\u003e \u003c/thead\u003e \u003ctbody\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eAge categories (n\u0026thinsp;=\u0026thinsp;427)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e19 years or less\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e10\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e2.3\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e20 to 29 years\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e213\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e49.9\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e30 to 39 years\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e195\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e45.7\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e39 years or more\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e9\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e2.1\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colspan=\"3\" nameend=\"c3\" namest=\"c1\"\u003e \u003cp\u003eRegistered in the eligible family register before booking visit (n\u0026thinsp;=\u0026thinsp;427)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eRegistered\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e341\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e79.9\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eNot registered\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e86\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e20.1\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eEthnicity (n\u0026thinsp;=\u0026thinsp;427)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eSinhalese\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e336\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e78.7\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eSri Lankan Moor\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e58\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e13.6\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eSri Lankan Tamil\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e28\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e6.6\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eBurgher\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e3\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e0.7\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eIndian Tamil\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e2\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e0.5\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eEmployment status (n\u0026thinsp;=\u0026thinsp;427)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eEmployed\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e70\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e16.4\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eNon employed\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e357\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e83.6\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eEducational level (n\u0026thinsp;=\u0026thinsp;427)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003ePrimary education \u0026ndash; Grade five\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e35\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e8.2\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eGrade six \u0026ndash; eleven\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e42\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e9.8\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eStudied up to passing GCE O/L only\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e166\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e38.9\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003ePassed GCE A/L\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e167\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e39.1\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eTertiary education\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e17\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e4.0\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003c/tbody\u003e \u003c/colgroup\u003e \u003c/table\u003e\u003c/div\u003e \u003c/p\u003e \u003c/div\u003e\n\u003ch3\u003eMaternal Anthropometric and Obstetric Characteristics\u003c/h3\u003e\n\u003cp\u003eThe mean (SD) period of amenorrhea (POA) at booking was 7.0 weeks (1 week 4 days), with registration occurring as early as 4 weeks and 1 day and as late as 11 weeks and 6 days of gestation. Participants registering after 12 weeks were excluded. Of the total participants, 134 (31.4%) were primigravida, while 293 (68.6%) were multigravida, including four grand multigravidas (Fig.\u0026nbsp;\u003cspan refid=\"Fig1\" class=\"InternalRef\"\u003e1\u003c/span\u003e). A history of pregnancy loss was reported by 109 participants (25.5%), including miscarriages (23.2%), intrauterine deaths (0.9%), neonatal deaths (0.7%), and ectopic pregnancies (0.7%) (Fig.\u0026nbsp;\u003cspan refid=\"Fig1\" class=\"InternalRef\"\u003e1\u003c/span\u003e). Subfertility was reported by 100 participants (23.4%). Pre-existing diabetes mellitus prior to the last pregnancy was present in 27 participants (6.3%), while 19 participants (4.4%) had pre-existing hypertension.\u003c/p\u003e \u003cp\u003e \u003c/p\u003e \u003cp\u003eBased on pre-pregnancy BMI, the overweight percentage is 63.5% (n\u0026thinsp;=\u0026thinsp;271), and Obese is 36.5% (n\u0026thinsp;=\u0026thinsp;156) (Table\u0026nbsp;\u003cspan refid=\"Tab2\" class=\"InternalRef\"\u003e2\u003c/span\u003e). The mean (SD) pre-pregnancy BMI of participants was 29.26 (3.55) kg/m\u0026sup2;, with values ranging up to 44.3 kg/m\u0026sup2;. All women were informed by the PHM about their BMI status and the associated pregnancy risks. A family history of excess weight was reported by 115 participants (27.0%). Most participants (n\u0026thinsp;=\u0026thinsp;388; 90.9%) reported low levels of physical activity prior to pregnancy.\u003c/p\u003e \u003cp\u003eModerate and vigorous physical activity levels were reported by 35 (8.2%) and 4 (0.9%) participants, respectively. Gestational weight gain ranged from 0 to 23.0 kg, with a mean (SD) gain of 7.16 (4.25) kg. Mean weight gain was higher among overweight participants (7.53 kg) compared to obese participants (6.52 kg) (Table\u0026nbsp;\u003cspan refid=\"Tab2\" class=\"InternalRef\"\u003e2\u003c/span\u003e). Only one-third of participants achieved the recommended gestational weight gain. Among overweight women, 32.8% achieved the expected weight gain, while 39.1% gained below and 28.0% gained above the recommended range. Among obese women, 36.5% achieved the expected weight gain, with 43.6% gaining below and 19.9% gaining above the recommended range (Table\u0026nbsp;\u003cspan refid=\"Tab2\" class=\"InternalRef\"\u003e2\u003c/span\u003e).\u003c/p\u003e \u003cp\u003e \u003cdiv class=\"gridtable\"\u003e\u003ctable float=\"Yes\" id=\"Tab2\" border=\"1\"\u003e \u003ccaption language=\"En\"\u003e \u003cdiv class=\"CaptionNumber\"\u003eTable 2\u003c/div\u003e \u003cdiv class=\"CaptionContent\"\u003e \u003cp\u003ePre-pregnancy BMI distribution and gestational weight gain characteristics among participants.\u003c/p\u003e \u003c/div\u003e \u003c/caption\u003e \u003ccolgroup cols=\"4\"\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c1\" colnum=\"1\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c2\" colnum=\"2\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c3\" colnum=\"3\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c4\" colnum=\"4\"\u003e\u003c/div\u003e \u003cthead\u003e \u003ctr\u003e \u003cth align=\"left\" colname=\"c1\"\u003e \u003cp\u003eVariable\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c2\"\u003e \u003cp\u003eOverweight\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c3\"\u003e \u003cp\u003eObese\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c4\"\u003e \u003cp\u003eTotal\u003c/p\u003e \u003c/th\u003e \u003c/tr\u003e \u003c/thead\u003e \u003ctbody\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eBMI Distribution (n\u0026thinsp;=\u0026thinsp;427)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eNumber of Participants\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e271\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e156\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e427\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003ePercentage (%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e63.5\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e36.5\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e100.0\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eGestational weight gain (n\u0026thinsp;=\u0026thinsp;427)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eMean\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e7.5 kg\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e6.5 kg\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e7.1 kg\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eStandard Deviation\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e4.3 kg\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e4.2 kg\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e4.2 kg\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eMinimum\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e0.0 kg\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e0.1 kg\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e0.0 kg\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eMaximum\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e23.0 kg\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e22.0 kg\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e23.0 kg\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eRange\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e23.0 kg\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e21.9 kg\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e23.0 kg\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colspan=\"2\" nameend=\"c2\" namest=\"c1\"\u003e \u003cp\u003eAchievement of the recommended weight gain\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eBelow recommendation, n (%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e106 (39.1)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e68 (43.6)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e174 (40.7)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eWithin recommendation, n (%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e89 (32.8)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e57 (36.5)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e146 (34.2)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eAbove recommendation, n (%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e76 (28.0)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e31 (19.9)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e107 (25.1)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003c/tbody\u003e \u003c/colgroup\u003e \u003c/table\u003e\u003c/div\u003e \u003c/p\u003e\n\u003ch3\u003eRegistration and Coverage of Routine Field Health Services\u003c/h3\u003e\n\u003cp\u003e Most participants (n\u0026thinsp;=\u0026thinsp;341; 79.9%) had been registered in the Eligible Family Register before their pregnancy booking visit. In Sri Lanka, PHM is supposed to do regular domestic visits and register eligible women in the Eligible Family Register, so that the services that are offered by PHM will not be missed. Body weight was recorded at all subsequent antenatal visits. Blood pressure and symphysio-fundal height (SFH) measurements were conducted and documented for all participants (n\u0026thinsp;=\u0026thinsp;427, 100%) at every clinic visit, which reflects 100% service compliance for this critical initial step. A large majority (n\u0026thinsp;=\u0026thinsp;400; 93.7%) received regular monthly domiciliary visits from PHMs, with no cases of loss to follow-up reported. Despite these strengths in routine care, several significant service gaps were identified in personalized care for overweight and obese women.\u003c/p\u003e\n\u003ch3\u003eUtilization of Pre-Conceptional, Antenatal Preventive Services\u003c/h3\u003e\n\u003cp\u003ePre-conceptional care by the PHM was reported by 277 participants (64.6%), while 150 (35.1%) had not received or followed up pre-conceptional services. Pre-conceptional folic acid supplementation for at least three months before conception was reported by 248 participants (58.1%).\u003c/p\u003e \u003cdiv id=\"Sec8\" class=\"Section2\"\u003e \u003ch2\u003eUtilization of Personalized Weight-Related Interventions\u003c/h2\u003e \u003cp\u003eAlthough general dietary and physical activity advice was provided during antenatal health education sessions, issuing individualized management plans was limited. Only 22% of women were given dedicated time for BMI-related discussion. Just 10.5% (n\u0026thinsp;=\u0026thinsp;45) received individualized diet plans. Only 5% (n\u0026thinsp;=\u0026thinsp;21) were offered personalized physical activity plans. Referrals to dietitians were rare, with only 13 participants (3.0%) receiving such a referral. All 13 women (100%) referred to a dietitian followed through with the clinic visit, reflecting good adherence when referrals were made. This emphasizes the potential for improvement if referral pathways are strengthened.\u003c/p\u003e \u003cp\u003eDietary assessment through 24-hour dietary recall was conducted in only 27 women (6.3%). Among these, dietary adequacy assessments were used to provide targeted nutrition guidance. The vast majority (93.7%) did not receive this service. Difficulties with blood pressure cuffing due to upper arm circumference are often a challenge in obese individuals. This was reported in 2.3% of the cases (n\u0026thinsp;=\u0026thinsp;10) (Fig.\u0026nbsp;\u003cspan refid=\"Fig2\" class=\"InternalRef\"\u003e2\u003c/span\u003e).\u003c/p\u003e \u003cp\u003e \u003c/p\u003e \u003c/div\u003e\n\u003ch3\u003eSources of Information on BMI and Weight Management\u003c/h3\u003e\n\u003cp\u003ePregnant women in the study identified various sources from which they received information regarding Body Mass Index (BMI) and weight management during pregnancy. As shown in Table\u0026nbsp;\u003cspan refid=\"Tab3\" class=\"InternalRef\"\u003e3\u003c/span\u003e, the majority (79%, n\u0026thinsp;=\u0026thinsp;336) cited staff from the Medical Officer of Health (MOH) office, including PHMs and the Medical Officer of Health, as their primary source of information. Visiting Obstetricians and Gynecologists were mentioned by 9.8% (n\u0026thinsp;=\u0026thinsp;42) of participants, while 2.1% (n\u0026thinsp;=\u0026thinsp;9) received guidance from dietitians. Nutrition clinics and general practitioners (family doctors) each accounted for 1.9% (n\u0026thinsp;=\u0026thinsp;8) of the information sources. Notably, 4.9% of mothers (n\u0026thinsp;=\u0026thinsp;21) reported that they had not received any information regarding BMI or weight control from any healthcare provider. This highlights the central role of PHMs in health education, but also reveals gaps in multidisciplinary involvement.\u003c/p\u003e \u003cp\u003e \u003cdiv class=\"gridtable\"\u003e\u003ctable float=\"Yes\" id=\"Tab3\" border=\"1\"\u003e \u003ccaption language=\"En\"\u003e \u003cdiv class=\"CaptionNumber\"\u003eTable 3\u003c/div\u003e \u003cdiv class=\"CaptionContent\"\u003e \u003cp\u003eSources of Information on High BMI and Weight Control\u003c/p\u003e \u003c/div\u003e \u003c/caption\u003e \u003ccolgroup cols=\"3\"\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c1\" colnum=\"1\"\u003e\u003c/div\u003e \u003cdiv align=\"char\" char=\".\" class=\"colspec\" colname=\"c2\" colnum=\"2\"\u003e\u003c/div\u003e \u003cdiv align=\"char\" char=\".\" class=\"colspec\" colname=\"c3\" colnum=\"3\"\u003e\u003c/div\u003e \u003cthead\u003e \u003ctr\u003e \u003cth align=\"left\" colname=\"c1\"\u003e \u003cp\u003eSource of Information\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c2\"\u003e \u003cp\u003eNumber\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c3\"\u003e \u003cp\u003ePercentage\u003c/p\u003e \u003c/th\u003e \u003c/tr\u003e \u003c/thead\u003e \u003ctbody\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003ePHM\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e218\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e51.0\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eMOH\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e118\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e27.6\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eVOG\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e42\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e9.8\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eDietitian\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e9\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e2.1\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eNutrition Clinic\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e8\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e1.9\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eFamily medical officer\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e8\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e1.9\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eWard nurse\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e3\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e0.7\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eNo information received by the health sector\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e21\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e4.9\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003c/tbody\u003e \u003c/colgroup\u003e \u003c/table\u003e\u003c/div\u003e \u003c/p\u003e \u003cp\u003eThese results indicate that while frontline workers (Medical Officers of Health and PHMs) are the dominant source of BMI-related education, involvement from dietitians and specialized maternal care clinics is limited. The data show that although foundational antenatal practices like BMI screening and BP monitoring were universally implemented, personalized interventions such as individualized diet plans, exercise prescriptions, and nutritional referrals were not consistently offered. Only 3% of mothers were referred to a dietitian despite the known risks associated with pre-pregnancy obesity. Likewise, despite national maternal health guidelines encouraging tailored counseling for excess weight, only 22% of participants were provided an extended time by PHMs to discuss BMI concerns. This highlights a key area where frontline service delivery could be further strengthened.\u003c/p\u003e"},{"header":"Discussion","content":"\u003cp\u003eThis study is among the first to describe field-level service utilization patterns for overweight and obese pregnant mothers in Sri Lanka. The study used a service “cascade” perspective that distinguishes routine antenatal contact from the content and personalization of care. Study findings revealed that routine maternal health services showed high coverage, with about 80% registered in the Eligible Family Register, 93.7% receiving PHM home visits, and 100% receiving standard antenatal monitoring. However, personalized weight-management care was limited. In the study, 64.6% reported pre-conception care, only 10.5% received individualized diet plans, 5% physical activity guidance, 3% dietitian referrals, and 6.3% dietary assessments, and only one-third achieved the recommended gestational weight gain. PHMs and MOH staff were the main sources of BMI-related information, highlighting a gap between high antenatal service coverage and limited individualized obesity-related care.\u003c/p\u003e \u003cp\u003ePresent study of 427 overweight or obese pregnant women indicated near-universal engagement with ANC care, virtually all women attended ANC and received standard services, reflecting Sri Lanka’s strong maternal health system. This aligns with many settings globally. For instance, in high-income countries (e.g., Australia and Canada), ANC coverage is also essentially universal, and women are typically weighed and have their BMI recorded at their first visit. In Australia, 59–62% of women reported being weighed or offered weight measurement at their initial visit (and 44% had height measured to calculate BMI) (\u003cspan class=\"CitationRef\"\u003e17\u003c/span\u003e). Low- and middle-income countries (LMICs) have seen rising ANC utilization rates in recent years, though timely first-trimester booking can be lower in some regions (\u003cspan class=\"CitationRef\"\u003e18\u003c/span\u003e).\u003c/p\u003e \u003cp\u003eIn middle- and low-income countries, pre-conception care is limited by low awareness, stigma, and poor healthcare access. In Sri Lanka, weight and nutrition counselling gaps, and COVID-19 disruptions have left many overweight women entering pregnancy without proper pre-pregnancy optimization during the study period. Even with these limitations, about two-thirds of overweight/obese women in Sri Lanka accessed pre-conception care. It is a higher rate than in many countries, but the guidance, especially on weight management, was insufficient. Globally, pre-conception care for obesity is underused, with many women in high-income countries entering pregnancy overweight and without adequate dietary or lifestyle counseling. In Australia, over 50% of women begin pregnancy overweight or obese, and many do not meet recommended diet and activity guidelines, reflecting poor pre-conception diet quality and weight optimization common in high-income countries. One report noted that 80% of Australian women fail to consume the recommended servings of vegetables, and 44% fall short on fruit intake, in the pre-conception period (\u003cspan class=\"CitationRef\"\u003e22\u003c/span\u003e). These statistics underscore insufficient diet quality and weight optimization before pregnancy.\u003c/p\u003e \u003cp\u003eThe juxtaposition of high coverage and poor quality of care for managing maternal overweight is a consistent finding across countries of all income levels. In Sri Lanka, virtually every pregnant woman attends ANC (high coverage), yet, specifically with respect to quality, personalized dietary or weight-management support was lacking. Only 10.5% received an individualized diet plan, 5% got physical activity guidance, 3% were referred to a dietitian, and 6.3% had a 24-hour dietary recall. This limited utilization of tailored interventions is echoed in many other countries, indicating a global gap in translating obesity guidelines into practice. In high-income countries, personalized weight management in pregnancy is limited. Research in the United States and Canada shows that only about 28–30% of women receive specific weight-gain advice and about 12% receive guideline-consistent counseling, while lifestyle interventions remain poorly implemented in routine care (\u003cspan class=\"CitationRef\"\u003e19\u003c/span\u003e). In an Australian survey (2018–2019), only about one-third of Australian women received advice on gestational weight gain, diet, or exercise at their first ANC visit, and fewer than 7% received complete weight-related care (\u003cspan class=\"CitationRef\"\u003e20\u003c/span\u003e). Middle-income countries show a similar pattern of inadequate personalization as well. Studies in Thailand and Ethiopia report little to no individualized gestational weight gain counseling due to a lack of programs, training, and guideline awareness (\u003cspan class=\"CitationRef\"\u003e18\u003c/span\u003e, \u003cspan class=\"CitationRef\"\u003e21\u003c/span\u003e).\u003c/p\u003e \u003cp\u003eSeveral limitations should be acknowledged in this study. First, the cross-sectional nature of the study restricts the ability to establish causality between excess maternal weight and service utilization patterns. Longitudinal or case-control designs would be more appropriate to explore temporal relationships and health outcomes. Second, the exclusion of adverse outcomes such as miscarriages, stillbirths, and neonatal deaths limits the comprehensiveness of the study. These complications, often associated with maternal overweight and obesity, are crucial indicators of care effectiveness and should be addressed in future studies. Third, selection bias cannot be ruled out, as only mothers who continued antenatal follow-up at selected CWCs and who had access to phone communication were included. This may underrepresent those with poorer service access or those experiencing the most severe complications. Fourth, the absence of multivariable analysis limits our ability to control for confounders such as maternal education, parity, and socioeconomic status.\u003c/p\u003e "},{"header":"Conclusions and Recommendations","content":"\u003cp\u003eRoutine antenatal and domiciliary maternal health services demonstrated high coverage as reflected with all getting clinic-based services, more than 90% receiving and more than three fourth getting eligibility registrations among excess-weight womenThese findings indicate strong implementation and coverage of routine antenatal and field maternal health services among women with excess weight. However, customized care opportunities were not utilized by the majority for diet and physical activity-related services.\u003c/p\u003e\u003cp\u003eStrengthening multidisciplinary services for managing issues on diet and physical activity must be promoted. Similarly, the enhancement of personalized maternal care strategies must be facilitated to address the specific needs of overweight and obese pregnant women. Further studies incorporating multivariable analyses are warranted to identify independent predictors of service utilization gaps and to address potential confounding.\u003c/p\u003e\u003cp\u003eLeverage digital tools and community-based interventions to deliver weight management advice, including video-based education and text-based reminders. Ensure the availability of appropriate medical equipment, such as larger cuff sizes for blood pressure monitoring, to support high-BMI patient needs.\u003c/p\u003e\u003cp\u003eFuture research should include multivariable and longitudinal analyses to better understand predictors of poor service utilization and test interventions aimed at improving care equity and effectiveness in similar LMIC contexts.\u003c/p\u003e"},{"header":"Abbreviations","content":"\u003cdiv class=\"DefinitionList\"\u003e \u003cdiv class=\"DefinitionListEntry\"\u003e \u003cdiv class=\"Term\"\u003e\u003cb\u003eBMI\u003c/b\u003e\u003c/div\u003e \u003cdiv class=\"Description\"\u003e \u003cp\u003eBody Mass Index\u003c/p\u003e \u003c/div\u003e \u003c/div\u003e \u003cdiv class=\"DefinitionListEntry\"\u003e \u003cdiv class=\"Term\"\u003e\u003cb\u003eCWC / CWCs\u003c/b\u003e\u003c/div\u003e \u003cdiv class=\"Description\"\u003e \u003cp\u003eChild Welfare Clinic / Child Welfare Clinics\u003c/p\u003e \u003c/div\u003e \u003c/div\u003e \u003cdiv class=\"DefinitionListEntry\"\u003e \u003cdiv class=\"Term\"\u003e\u003cb\u003eFHB\u003c/b\u003e\u003c/div\u003e \u003cdiv class=\"Description\"\u003e \u003cp\u003eFamily Health Bureau\u003c/p\u003e \u003c/div\u003e \u003c/div\u003e \u003cdiv class=\"DefinitionListEntry\"\u003e \u003cdiv class=\"Term\"\u003e\u003cb\u003eIQR\u003c/b\u003e\u003c/div\u003e \u003cdiv class=\"Description\"\u003e \u003cp\u003eInterquartile Range\u003c/p\u003e \u003c/div\u003e \u003c/div\u003e \u003cdiv class=\"DefinitionListEntry\"\u003e \u003cdiv class=\"Term\"\u003e\u003cb\u003eISCO-08\u003c/b\u003e\u003c/div\u003e \u003cdiv class=\"Description\"\u003e \u003cp\u003eInternational Standard Classification of Occupations 2008\u003c/p\u003e \u003c/div\u003e \u003c/div\u003e \u003cdiv class=\"DefinitionListEntry\"\u003e \u003cdiv class=\"Term\"\u003e\u003cb\u003ekg/m\u0026sup2;\u003c/b\u003e\u003c/div\u003e \u003cdiv class=\"Description\"\u003e \u003cp\u003ekilograms per square meter\u003c/p\u003e \u003c/div\u003e \u003c/div\u003e \u003cdiv class=\"DefinitionListEntry\"\u003e \u003cdiv class=\"Term\"\u003e\u003cb\u003eLMIC\u003c/b\u003e\u003c/div\u003e \u003cdiv class=\"Description\"\u003e \u003cp\u003eLow- and middle-income countries\u003c/p\u003e \u003c/div\u003e \u003c/div\u003e \u003cdiv class=\"DefinitionListEntry\"\u003e \u003cdiv class=\"Term\"\u003e\u003cb\u003eMOH\u003c/b\u003e\u003c/div\u003e \u003cdiv class=\"Description\"\u003e \u003cp\u003eMedical Officer of Health\u003c/p\u003e \u003c/div\u003e \u003c/div\u003e \u003cdiv class=\"DefinitionListEntry\"\u003e \u003cdiv class=\"Term\"\u003e\u003cb\u003eMoH\u003c/b\u003e\u003c/div\u003e \u003cdiv class=\"Description\"\u003e \u003cp\u003eMinistry of Health\u003c/p\u003e \u003c/div\u003e \u003c/div\u003e \u003cdiv class=\"DefinitionListEntry\"\u003e \u003cdiv class=\"Term\"\u003e\u003cb\u003ePHM / PHMs\u003c/b\u003e\u003c/div\u003e \u003cdiv class=\"Description\"\u003e \u003cp\u003ePublic Health Midwife / Public Health Midwives\u003c/p\u003e \u003c/div\u003e \u003c/div\u003e \u003cdiv class=\"DefinitionListEntry\"\u003e \u003cdiv class=\"Term\"\u003e\u003cb\u003ePOA\u003c/b\u003e\u003c/div\u003e \u003cdiv class=\"Description\"\u003e \u003cp\u003ePeriod of Amenorrhea\u003c/p\u003e \u003c/div\u003e \u003c/div\u003e \u003cdiv class=\"DefinitionListEntry\"\u003e \u003cdiv class=\"Term\"\u003e\u003cb\u003eSD\u003c/b\u003e\u003c/div\u003e \u003cdiv class=\"Description\"\u003e \u003cp\u003eStandard Deviation\u003c/p\u003e \u003c/div\u003e \u003c/div\u003e \u003cdiv class=\"DefinitionListEntry\"\u003e \u003cdiv class=\"Term\"\u003e\u003cb\u003eSDG / SDG 3\u003c/b\u003e\u003c/div\u003e \u003cdiv class=\"Description\"\u003e \u003cp\u003eSustainable Development Goal / Sustainable Development Goal 3\u003c/p\u003e \u003c/div\u003e \u003c/div\u003e \u003cdiv class=\"DefinitionListEntry\"\u003e \u003cdiv class=\"Term\"\u003e\u003cb\u003eSFH\u003c/b\u003e\u003c/div\u003e \u003cdiv class=\"Description\"\u003e \u003cp\u003eSymphysio-fundal height\u003c/p\u003e \u003c/div\u003e \u003c/div\u003e \u003cdiv class=\"DefinitionListEntry\"\u003e \u003cdiv class=\"Term\"\u003e\u003cb\u003eSPSS\u003c/b\u003e\u003c/div\u003e \u003cdiv class=\"Description\"\u003e \u003cp\u003eStatistical Package for the Social Sciences\u003c/p\u003e \u003c/div\u003e \u003c/div\u003e \u003cdiv class=\"DefinitionListEntry\"\u003e \u003cdiv class=\"Term\"\u003e\u003cb\u003eUK\u003c/b\u003e\u003c/div\u003e \u003cdiv class=\"Description\"\u003e \u003cp\u003eUnited Kingdom\u003c/p\u003e \u003c/div\u003e \u003c/div\u003e \u003cdiv class=\"DefinitionListEntry\"\u003e \u003cdiv class=\"Term\"\u003e\u003cb\u003eZ\u003c/b\u003e\u003c/div\u003e \u003cdiv class=\"Description\"\u003e \u003cp\u003eZ value / Z-score\u003c/p\u003e \u003c/div\u003e \u003c/div\u003e \u003c/div\u003e"},{"header":"Declarations","content":"\u003cp\u003e\u003cstrong\u003eEthical Approval\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eEthical approval for this study was obtained from the Ethics Review Committee of the Postgraduate Institute of Medicine, University of Colombo. The study was conducted in accordance with ethical guidelines to ensure the rights, safety, and well-being of all participants. (Registration no.- ERC/PGIM/2022/080). Written informed consent was obtained from all participants before data collection. Participation was voluntary, and confidentiality and anonymity of the participants were strictly maintained throughout the study.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eAvailability of data and materials\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eThe datasets generated and analyzed in the current study are not publicly available due to ethical and confidentiality considerations, but are available from the corresponding author on reasonable request.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eCompeting Interest\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eAll authors declare that there are no competing interests in relation to this study. The authors have no financial, personal, or professional interests that could have influenced the conduct or outcomes of the research.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eFunding\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eThis research did not receive any specific grant from funding agencies in the public, commercial, or not-for-profit sectors.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eAuthors\u0026rsquo; contributions\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eMLPKSM conceived the study, developed the study design, conducted data collection, performed data analysis, and drafted the manuscript. VK contributed to the study design, provided methodological guidance, critically reviewed the manuscript, and supervised the research process. Both authors read and approved the final manuscript.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eAcknowledgements\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eThe authors wish to acknowledge the Medical Officers of Health, Public Health Midwives, and clinic staff in the selected MOH areas of Gampaha District for their support during data collection. We are also grateful to all pregnant women who participated in the study for their time and cooperation.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eAuthors\u0026rsquo; information\u0026nbsp;\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eMLPKSM is a medical officer affiliated with the Office of the Provincial Director of Health Services, Western Province, Sri Lanka, with research interests in maternal health, public health services, occupational health, and health systems strengthening. He is a postgraduate candidate in MD in Community Medicine. He holds an undergraduate degree in Bachelor of Medicine and Bachelor of Surgery (MBBS), a Diploma in Occupational Health, and a Master of Science in Community Medicine. He is currently pursuing a Master of Business Administration (MBA).\u003c/p\u003e\n\u003cp\u003eVK is a board-certified Specialist in Community Medicine and currently serves as Director, Non-Communicable Diseases, Ministry of Health, Sri Lanka. She holds an MBBS, MSc, and MD in Community Medicine, and has undertaken post-doctoral and research fellowships at Harvard School of Public Health, University of Melbourne, and Monash University. She has received multiple President\u0026rsquo;s Awards for scientific publications and has contributed to WHO expert groups and national NCD policy development.\u003c/p\u003e"},{"header":"References","content":"\u003col\u003e\u003cli\u003e\u003cspan\u003eStrauss A. Obesity in pregnant women: maternal, fetal, and transgenerational consequences. 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Nutr Diet. 2024;81(3):244\u0026ndash;60.\u003c/span\u003e\u003c/li\u003e\u003c/ol\u003e"}],"fulltextSource":"","fullText":"","funders":[],"hasAdminPriorityOnWorkflow":false,"hasManuscriptDocX":false,"hasOptedInToPreprint":true,"hasPassedJournalQc":"","hasAnyPriority":true,"hideJournal":false,"highlight":"","institution":"","isAcceptedByJournal":false,"isAuthorSuppliedPdf":false,"isDeskRejected":"","isHiddenFromSearch":false,"isInQc":false,"isInWorkflow":false,"isPdf":false,"isPdfUpToDate":true,"isWithdrawnOrRetracted":false,"journal":{"display":true,"email":"[email protected]","identity":"bmc-health-services-research","isNatureJournal":false,"hasQc":true,"allowDirectSubmit":false,"externalIdentity":"bhsr","sideBox":"Learn more about [BMC Health Services Research](http://bmchealthservres.biomedcentral.com/)","snPcode":"","submissionUrl":"https://www.editorialmanager.com/BHSR/default.aspx","title":"BMC Health Services Research","twitterHandle":"BMC_series","acdcEnabled":true,"dfaEnabled":false,"editorialSystem":"em","reportingPortfolio":"BMC Series","inReviewEnabled":true,"inReviewRevisionsEnabled":true},"keywords":"Overweight in pregnancy, Obesity in pregnancy, Maternal BMI, Antenatal care utilization, Field health services, Public Health Midwives, Sri Lanka, Gampaha District","lastPublishedDoi":"10.21203/rs.3.rs-9507553/v1","lastPublishedDoiUrl":"https://doi.org/10.21203/rs.3.rs-9507553/v1","license":{"name":"CC BY 4.0","url":"https://creativecommons.org/licenses/by/4.0/"},"manuscriptAbstract":"\u003ch2\u003eBackground\u003c/h2\u003e \u003cp\u003eThe rising prevalence of pre-pregnancy excess weight represents a major challenge to achieving optimal maternal and neonatal health outcomes. Excess maternal weight is associated with increased pregnancy-related complications and greater health service utilization. Despite this growing burden, evidence on the utilization of maternal field health services for excess weight in Sri Lanka remains limited.\u003c/p\u003e\u003ch2\u003eMethods\u003c/h2\u003e \u003cp\u003eA descriptive cross-sectional study with an analytical component was conducted. Women identified as overweight or obese at the first antenatal clinic visit were recruited. The calculated sample size was 482, and data were collected using a two-stage sampling technique. Data collection tools included a judgmentally validated, interviewer-administered questionnaire and a structured data extraction sheet. Statistical analysis was performed using the Statistical Package for Social Sciences version 25. Descriptive statistics were used to summarize findings, while the Chi-square test and Mann\u0026ndash;Whitney U test were applied at a 5% level of significance.\u003c/p\u003e\u003ch2\u003eResults\u003c/h2\u003e \u003cp\u003eA total of 427 pregnant women participated in the study with a response rate of 88.6%. The majority of participants were aged 20\u0026ndash;39 years (95%), with an approximate overweight-to-obese ratio of 2:1. In the antenatal period, all received advice from Public Health Midwives (PHMs) regarding their elevated body mass index and associated pregnancy risks. Routine antenatal monitoring, including blood pressure and symphysio-fundal height measurement, was done on all participants. Most participants (93.7%) received regular domiciliary visits from PHMs. The primary source (78,6%) of information on BMI and weight management was MOH staff, including PHMs. Provision of personalized interventions was limited. Only 10.5% received individualized dietary plans, 4.9% were offered tailored physical activity plans, and 6.3% underwent dietary assessment using a 24-hour dietary recall. Referral to dietitians was rare, with only 3.0% of participants receiving such referrals.\u003c/p\u003e\u003ch2\u003eConclusions\u003c/h2\u003e \u003cp\u003eAlthough routine antenatal and domiciliary services show high coverage among excess-weight women, gaps were identified in the delivery of individualized nutritional and lifestyle interventions. Strengthening multidisciplinary involvement and enhancing personalized maternal care strategies are essential to address the specific needs of overweight and obese pregnant women. Further studies incorporating multivariable analyses are warranted to determine independent predictors of service utilization gaps.\u003c/p\u003e","manuscriptTitle":"Utilization of field health services among women with pre-pregnancy excess weight in Gampaha District, Sri Lanka: a lower middle-income country","msid":"","msnumber":"","nonDraftVersions":[{"code":1,"date":"2026-04-26 17:22:44","doi":"10.21203/rs.3.rs-9507553/v1","editorialEvents":[{"type":"communityComments","content":0},{"type":"decision","content":"Revision requested","date":"2026-04-30T07:39:28+00:00","index":"","fulltext":""},{"type":"editorAssigned","content":"","date":"2026-04-28T15:29:29+00:00","index":"","fulltext":""},{"type":"checksComplete","content":"","date":"2026-04-28T15:29:27+00:00","index":"","fulltext":""},{"type":"submitted","content":"BMC Health Services Research","date":"2026-04-23T13:37:04+00:00","index":"","fulltext":""}],"status":"published","journal":{"display":true,"email":"[email protected]","identity":"bmc-health-services-research","isNatureJournal":false,"hasQc":true,"allowDirectSubmit":false,"externalIdentity":"bhsr","sideBox":"Learn more about [BMC Health Services Research](http://bmchealthservres.biomedcentral.com/)","snPcode":"","submissionUrl":"https://www.editorialmanager.com/BHSR/default.aspx","title":"BMC Health Services Research","twitterHandle":"BMC_series","acdcEnabled":true,"dfaEnabled":false,"editorialSystem":"em","reportingPortfolio":"BMC Series","inReviewEnabled":true,"inReviewRevisionsEnabled":true}}],"origin":"","ownerIdentity":"20d10b36-56c2-4a11-bf59-2ad231b13951","owner":[],"postedDate":"April 26th, 2026","published":true,"recentEditorialEvents":[{"type":"decision","content":"Revision requested","date":"2026-04-30T07:39:28+00:00","index":"","fulltext":""}],"rejectedJournal":[],"revision":"","amendment":"","status":"under-review","subjectAreas":[],"tags":[],"updatedAt":"2026-05-01T18:08:12+00:00","versionOfRecord":[],"versionCreatedAt":"2026-04-26 17:22:44","video":"","vorDoi":"","vorDoiUrl":"","workflowStages":[]},"version":"v1","identity":"rs-9507553","journalConfig":"researchsquare"},"__N_SSP":true},"page":"/article/[identity]/[[...version]]","query":{"redirect":"/article/rs-9507553","identity":"rs-9507553","version":["v1"]},"buildId":"XKTyCvWXoU3ODBz1xrDgd","isFallback":false,"isExperimentalCompile":false,"dynamicIds":[84888],"gssp":true,"scriptLoader":[]}