Abstract
Metabolic syndrome is more prevalent in women than in men in Vietnam, although data among women of reproductive age remain limited. A cross-sectional study was conducted in Bac Giang Province, Vietnam, in 2019 to estimate the prevalence of metabolic syndrome and its components, and to determine associations with sociodemographic and health factors in 194 overweight and obese women aged 20–45 years. Anthropometric indicators, plasma glucose and lipid concentrations, blood pressure, sociodemographic characteristics, medical status, medication/supplement use, and energy intake were measured. The prevalence of metabolic syndrome was 47.4% (95% CI: 40.5, 54.5%). Metabolic syndrome was significantly associated with obesity (OR: 4.14; 95% CI: 1.45, 11.85), and hypertension (OR: 25.40; 95% CI: 3.18, 202.89). Dyslipidemia, high plasma glucose concentrations, and hypertension were common. High parity was associated with higher plasma glucose and lower total cholesterol concentrations. Unemployment and higher plasma triglyceride concentrations were associated with higher total cholesterol concentrations. Increased systolic blood pressure and medical status were associated with higher triglyceride concentrations. Obesity was associated with high plasma glucose. These findings highlight the need for targeted interventions, including lifestyle modifications, routine clinical screening, and socioeconomic support for vulnerable groups, to prevent and manage metabolic syndrome in overweight and obese women of reproductive age.
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Introduction
Non-communicable diseases, primarily cardiovascular and chronic respiratory diseases, cancers, and diabetes, pose a significant threat to global health. Collectively, these diseases account for 41 million deaths annually, which is equivalent to over 70% of all worldwide deaths1, with a projected annual global cost of treatment of US$13 trillion and a forecasted loss of US$47 trillion in gross domestic product by 20302.
Overweight and obesity increase the risk of major non-communicable diseases3,4,5,6. Overweight/obese individuals have a higher risk of developing type 2 diabetes mellitus, dyslipidemia, and hypertension than those with a body mass index within the normal range3,7. In turn, obese individuals who are affected by diabetes, dyslipidemia, or hypertension have been reported to have a higher risk of cardiovascular disease or acute cardiovascular events compared with those without diabetes, dyslipidemia, or hypertension8,9,10,11. Abdominal obesity, in combination with dyslipidemia, hypertension, and hyperglycemia, also leads to the development of metabolic syndrome12,13, which is associated with an increased risk of cardiovascular disease and type 2 diabetes mellitus7,14,15.
In Vietnam, overweight and obesity have rapidly become pressing public health issues5,16,17,18, particularly in low- and middle-income settings undergoing rapid socioeconomic change5,19,20,21. Between 2000 and 2015, the prevalence of overweight and obesity among Vietnamese adults increased from 3.7%22 to 15.6%23, alongside a near doubling of type 2 diabetes mellitus and notable increases in hypertension23 and dyslipidemia24. National surveys consistently show a higher prevalence of overweight and obesity, dyslipidemia16,23,25 and metabolic syndrome among women compared with men26,27,28,29. However, limited evidence exists for women under 50 years of age26,27, even though the risk of cardiovascular disease associated with metabolic syndrome is reported to be greater in women than in men30.
Focusing on women of reproductive age, defined as 20 to 45 years, is therefore crucial, as this period is central to women’s health, productivity, and fertility, while also having intergenerational implications. This group is particularly vulnerable to lifestyle and dietary changes associated with economic transition, which may amplify metabolic risk. Despite this, research examining metabolic syndrome and its determinants among overweight and obese women of reproductive age in Vietnam remains scarce.
Bac Giang Province, located in the Northern midland of Vietnam, is ranked 24th among the 63 provinces in Vietnam for economic development13,31,32. The rapid economic transition in the province has led to changes in nutrition practices among women33; whether these changes have been paralleled by an increase in overweight and obesity or metabolic syndrome in this population has not been investigated. Therefore, this study aimed to estimate the prevalence of high plasma glucose concentrations, dyslipidemia, hypertension, and metabolic syndrome; and to determine associations between metabolic syndrome and its components and sociodemographic and health factors among overweight and obese women of reproductive age in Bac Giang Province, Vietnam.
Methods
Study design
This cross-sectional study used screening data from a randomized controlled trial that investigated the effects of medium-chain triglyceride oil for improving nutritional status and plasma lipid profiles in overweight and obese women (trial registered on 19/08/2019 at clinicaltrials.gov as NCT04067323). Data for this study were collected between July and September 2019. The study was approved by the Ethics Council in Biomedical Research at the National Institute of Nutrition, Ministry of Health, Vietnam (152/VDD-QLKH). The study was performed in accordance with the ethical standards laid down in the Declaration of Helsinki and its later amendments. All participants provided written informed consent prior to participation. Participation was voluntary and participants were free to withdraw from the study at any stage.
Participants
Women were eligible to participate if they were aged 20 to 45 years, resided in the selected areas described below, had a body mass index (BMI in kg/m2) ranging from 25.0 to < 40.0, and voluntarily agreed to take part in the study. Exclusion criteria included current pregnancy or breastfeeding.
Location and sampling
This research was conducted in Bac Giang Province, a region characterized by mixed agriculture and industrial development, located 50 km east of Hanoi, the capital of Vietnam. Bac Giang province is divided into 10 district-level subdivisions: 9 districts and 1 city (Bac Giang City). Participants were selected through a multistage sampling approach. Initially, Bac Giang City was chosen for the recruitment of eligible women. However, due to an insufficient number of overweight and obese women in Bac Giang City, 2 additional districts, Viet Yen and Lang Giang, which offered social and economic conditions similar to those of Bac Giang City, were included. In total, 228,873 women aged 20–45 years resided in the selected areas34, with an estimated prevalence of overweight and obesity in women of 3.1%35, equivalent to 7,096 women. Once the 3 areas were selected, the study was promoted to potential participants by health workers and village health collaborators through the commune/ward loudspeaker system commonly used for community announcements. Information flyers were also distributed to homes. Four hundred sixty-eight women aged 20–45, who self-assessed themselves as overweight/obese, expressed interest in the study. These women were then weighed and had their height measured by research staff, and eligibility was confirmed for 234 women (i.e., BMI between 25.0 and < 40.0 kg/m2). Of the 234 eligible women, 194 agreed to participate in the study.
Sociodemographic indicators, medical status, and medication/supplement use
Sociodemographic, medical status, and medication/supplement use data were collected from all participants via a researcher-administered questionnaire. Sociodemographic data included participant age, employment status, education level, place of residence, and parity. The medical status questionnaire included questions about conditions known to affect plasma glucose concentrations or shown to be associated with weight gain such as thyroid diseases, growth hormone disorders, Cushing’s syndrome, polycystic ovary syndrome, pancreatic gland diseases, adrenal hyperplasia, hyperparathyroidism, or depression. The medication/supplement use questionnaire asked about current use of mediation/supplements likely to affect the biochemical indicators examined in this study.
Dietary data
A 24-hour food recall was used to collect dietary intake data from each participant. Participants were asked by trained research staff to list all foods and beverages consumed in the previous 24 h. Photographs of commonly used measures (e.g., bowls, spoons) and food portion sizes (e.g., slices) were used to facilitate the estimation of portion sizes. The food recall data were used to estimate energy intake with the 2019 Vietnamese food composition tables36.
Anthropometric data
Anthropometric measurements were taken once according to standard procedures37. Body weight was measured using a digital scale (TANITA SC-330) to the nearest 0.1 kg, with participants dressed in light clothing. Height was measured using a UNICEF wooden wall-mounted stadiometer to the nearest 0.1 cm, with participants standing without shoes. Waist circumference was measured with a nonstretchable tape to the nearest 0.1 cm in the horizontal plane midway between the lowest rib and the top of the hipbone37.
BMI was calculated by dividing body weight in kg by the height in meters squared (kg/m2). Overweight was defined as a BMI between 25.0 and < 30.0 kg/m2, and obesity as a BMI between 30.0 and < 40.0 kg/m212. Abdominal obesity was defined as a waist circumference of ≥ 80 cm12.
Biochemical indicators
Qualified and experienced technicians performed blood sampling using approved materials and procedures. Venous blood (2 mL) was collected in the morning into heparin tubes, after at least 8–12 h of fasting and at least 24 h of alcohol abstinence. Blood samples were centrifuged within 30 min of sampling at 2,500 rpm for 15 min, and plasma was transferred into Eppendorf tubes. Plasma was kept at 2–8 °C during transport to the National Institute of Nutrition in Hanoi on the day of sampling where it was stored at -20 °C until analysis.
All biochemical indicators were measured using the enzymatic colour method with a Beckman Coulter AU480 Chemistry Analyzer38,39 and commercial kits (Beckman Coulter, Co. Clare, Ireland). Plasma glucose, total cholesterol, triglyceride, and HDL cholesterol measurements were validated through participation in the Randox International Quality Assessment Scheme (RIQAS, Randox Laboratories Ltd, United Kingdom). To assess accuracy of the analytical methods, the Human Assayed Multi-sera Level 2 (Lot No. 1291UN, Randox, United Kingdom) was used in plasma glucose, total cholesterol, triglyceride, and HDL cholesterol analyses, and HDL/LDL Cholesterol Control Serum Level 1 (Beckman Coulter, Co. Clare, Ireland) was used in the analysis of plasma LDL cholesterol. Plasma glucose concentration was determined with the use of Hexokinase enzyme kits. The analysed mean value for the quality control serum was 5.99 mmol/L (SD: 0.22 mmol/L; CV%: 3.66%), compared to the manufacturer’s target value of 6.29 mmol/L and a reference range of 5.35–7.23 mmol/L. Plasma total cholesterol concentration was measured using cholesterol dehydrogenase enzyme kits. The analysed mean value for the quality control serum was 4.17 mmol/L (SD: 0.10 mmol/L; CV%: 2.34%), compared to the manufacturer’s target value of 4.16 mmol/L and a reference range of 3.62–4.70 mmol/L. Plasma triglyceride concentration was determined with Lipase/glycerol phosphate oxidase - peroxidase (CHO/PAP) enzyme kits. The analysed mean value for the quality control serum was 1.04 mmol/L (SD: 0.05 mmol/L; CV%: 4.36%), compared to the manufacturer’s target value of 1.10 mmol/L and a reference range of 0.92–1.28 mmol/L. HDL cholesterol and LDL cholesterol concentrations were analysed with Direct HDL Immunoseparation kits and CHO/PAP enzyme kits, respectively. The analysed mean value for the quality control serum for HDL cholesterol was 1.34 mmol/L (SD: 0.04 mmol/L; CV%: 3.05%), compared to the manufacturer’s target value of 1.25 mmol/L and a reference range of 1.06–1.44 mmol/L. The analysed mean value for the quality control serum for LDL cholesterol was 1.91 mmol/L (SD: 0.06 mmol/L; CV%: 2.91%), compared to the manufacturer’s target value of 1.99 mmol/L and a reference range of 1.73–2.25 mmol/L.
High plasma glucose concentration was defined as ≥ 5.60 mmol/L12. High plasma total cholesterol concentration was defined as ≥ 5.2 mmol/L40. High plasma triglyceride concentration was defined as ≥ 1.7 mmol/L40. Low plasma HDL cholesterol concentration was defined as < 1.03 mmol/L. High plasma LDL cholesterol concentration was defined as ≥ 2.6 mmol/L40. Dyslipidemia was defined if at least one of the following factors was present: high plasma total cholesterol concentration, high plasma triglyceride concentration, low plasma HDL cholesterol concentration, high plasma LDL cholesterol concentration, or current use of medication to lower serum lipid concentrations.
Blood pressure
Blood pressure was measured once using a sphygmomanometer (Omron HEM-8712, Japan) on the left arm, with participants in the sitting position after at least 10 min of rest and no consumption of alcohol or tobacco in the previous 24 h. Hypertension was defined as systolic blood pressure ≥ 140 mmHg or diastolic blood pressure ≥ 90 mmHg41.
Metabolic syndrome
Metabolic syndrome was defined according to the International Diabetes Federation criteria as a waist circumference ≥ 80 cm and at least two of the following four factors: plasma triglyceride concentration ≥ 1.7 mmol/L, plasma HDL cholesterol concentration < 1.29 mmol/L, systolic blood pressure ≥ 130 mmHg or diastolic blood pressure ≥ 85 mmHg, and plasma glucose concentration ≥ 5.60 mmol/L12.
Statistical analysis
There were no missing data. Age was classified into tertiles (20 to < 35 years, 35 to < 42 years, and 42 to ≤ 45 years). Employment status was categorized as employed or unemployed. Education level was categorized as below high school or high school and above. Place of residence was categorized as rural or urban. In Vietnam, couples are recommended to have no more than two children42 therefore parity was classified as ≤ 2 or > 2 children. Responses to the medical status and medication/supplement use questionnaires were coded as ‘yes’ or ‘no’.
Generalized linear mixed models were used to estimate the prevalence of high plasma glucose concentration, hypertension, high plasma total cholesterol concentration, high plasma triglyceride concentration, low plasma HDL cholesterol concentration, high plasma LDL cholesterol concentration, dyslipidemia, and metabolic syndrome. Generalized linear mixed models were also used to estimate the association between binary outcomes (high plasma glucose concentration and metabolic syndrome) and sociodemographic variables (age, employment status, education level, place of residence, and parity), medical status, medication/supplement use, anthropometric status (overweight, obesity), and hypertension. Univariable associations considered only one factor at a time and multivariable models included all factors (sociodemographic factors, medical status, medication/supplement use, anthropometric status, and hypertension). All models included district/city as a random effect to account for clustering.
Linear mixed models were used to estimate the association between continuous outcomes (plasma glucose concentration, plasma total cholesterol concentration, and plasma triglyceride concentration) and sociodemographic factors, anthropometric factors (BMI and waist circumference), medical status, medication/supplement use, blood pressure, energy intake, and plasma lipid concentrations (total cholesterol, triglyceride, LDL cholesterol, and HDL cholesterol concentrations). We report univariable and multivariable models. The plasma lipid concentrations used in multivariable models were different in each adjusted model: total cholesterol, triglyceride, LDL cholesterol, and HDL cholesterol concentrations were used in the model assessing the associations between plasma glucose concentration and the other defined factors; triglyceride concentration was used in the model that assessed the associations between total cholesterol and other defined factors; and the model assessing the associations between plasma triglyceride concentration and other defined factors included no biochemical indicators. We did not include weight or height data in these analyses because we used BMI in the models. All models included district/city as a random effect to account for clustering.
The baseline screening dataset used for this study was complete; participants with missing data were excluded. Before proceeding with the analysis, all variables were examined for multicollinearity, and any variable that showed evidence of multicollinearity was removed from the analytical model.
We also estimated the intracluster correlation coefficients for plasma glucose concentration, plasma total cholesterol concentration, plasma triglyceride concentration, high plasma glucose concentration, and metabolic syndrome under a model with district/city as a random effect and no covariates. The intracluster correlation coefficient is a measure of similarity of outcomes among women residing in the same district/city. All estimates are reported along with 95% CIs. Analyses were performed with Stata (version 14.0; Stata Corp LP, TX, USA).
Results
Participants
The majority of women (71%) were aged 35 to ≤ 45 years, 80% were currently employed, and 70% were educated to a high school level or above (Table 1). The majority of women had ≤ 2 children; had no medical conditions likely to affect plasma glucose concentration or shown to be associated with weight gain; and did not currently take any medications/supplements likely to affect plasma glucose or lipid concentrations. Nearly all participants had abdominal obesity (Table 1).
Prevalence of high plasma glucose concentrations, hypertension, dyslipidemia, and metabolic syndrome
After accounting for clustering, nearly half of the women were estimated to have low plasma HDL cholesterol concentrations and metabolic syndrome (Table 2). High plasma triglyceride and LDL cholesterol concentrations were estimated to be present in over a third of all women, whereas 1 in 5 women were estimated to have high plasma glucose concentrations. The overall estimated prevalence of dyslipidemia was 75.3% (95% CI: 68.7, 80.8%) (data not presented in Table 2).
Associations between metabolic syndrome and its components and sociodemographic and health factors
Mean plasma glucose concentrations were significantly associated with anthropometric measurements, blood pressure, and plasma total cholesterol and triglyceride concentrations in univariable analyses (Table 3). In the multivariable analysis, mean plasma glucose concentrations were 0.28 mmol/L (95% CI: 0.01, 0.54 mmol/L; p = 0.038) higher in women who gave birth to more than 2 children compared with women who gave birth to ≤ 2 children.
In univariable analyses, parity, medical status, BMI, waist circumference, blood pressure, and plasma triglyceride concentrations were significantly associated with mean plasma total cholesterol concentrations (Table 4). However, employment status, parity and plasma triglyceride concentrations were significantly associated with mean plasma total cholesterol concentrations in the multivariable analysis. Plasma total cholesterol concentrations were: 0.29 mmol/L (95% CI: 0.004, 0.57 mmol/L; p = 0.047) higher in women who were unemployed compared with women who were employed; 0.37 mmol/L (95% CI: -0.69, -0.06 mmol/L; p = 0.020) lower in women who gave birth to more than 2 children compared with women who gave birth to ≤ 2 children; and they increased by 0.20 mmol/L (95% CI: 0.10, 0.31 mmol/L; p < 0.001) for each additional 1 mmol/L in plasma triglyceride concentrations.
There was evidence of significant associations between mean plasma triglyceride concentrations and medical status, waist circumference, and blood pressure in univariable models (Table 5) but only medical status and systolic blood pressure were significantly associated with mean plasma triglyceride concentrations in the multivariable analysis. Plasma triglyceride concentrations were 0.98 mmol/L (95% CI: 0.44, 1.51 mmol/L; p < 0.001) higher in women with conditions known to affect plasma glucose concentration or shown to be associated with weight gain compared to women without these conditions, and they were associated with an increase of 0.02 mmol/L (95% CI: 0.01, 0.04; p = 0.009) for every 1 mmHg increase in systolic blood pressure.
The prevalence of high plasma glucose concentrations was higher in obese women than overweight women (44.0% vs. 20.1%; p = 0.011;) and in women with hypertension than in women not affected by hypertension (50.0% vs. 20.1%; p = 0.005; Table 6). In the multivariable analysis, high plasma glucose concentrations were significantly associated only with anthropometric status. Women who were obese were 3.3 times more likely to have high plasma glucose concentrations compared to women who were overweight (OR: 3.30; 95% CI: 1.26, 8.65; p = 0.015).
Age, medical status, anthropometric status, and hypertension were significantly associated with metabolic syndrome in univariable analyses (Table 7). In the multivariable analysis, anthropometric status and hypertension were significantly associated with metabolic syndrome. Women who were obese were 4.14 times more likely (OR: 4.14; 95% CI: 1.45, 11.85; p = 0.008) and those who had hypertension were 25.4 times more likely (OR: 25.40; 95% CI: 3.18, 202.89; p = 0.002) to have metabolic syndrome compared to overweight women and those not affected by hypertension, respectively.
The intracluster correlation coefficients for plasma glucose concentration, plasma total cholesterol concentration, plasma triglyceride concentration, high plasma glucose concentration, and metabolic syndrome are reported in Table 8. These estimates may inform the design and sample size calculations in future studies targeting the same outcomes in overweight and obese Vietnamese women of reproductive age.
Discussion
This study provides evidence that dyslipidemia is common among overweight and obese women in Vietnam, particularly in the study site of Bac Giang Province, affecting three-quarters of individuals in this population group. Our findings are in line with previous research in Vietnam, which showed that although dyslipidemia affected 35.9% of all women in a study conducted in Hanoi City (n = 209)43, 38.3% of women in a study conducted in Hue Province (n = 242)44, and 55.7% of women in a study conducted in Thai Binh Province (n = 975)45, a similar proportion of overweight or obese women in these studies had dyslipidemia compared with our results: 70.4%43, 66%44, 70.5%45, respectively. Our results are also in agreement with international research demonstrating that overweight and obesity are independent risk factors for dyslipidemia46. Although the reproductive age span is often defined as 15–49 years in previous studies, this study focused on women aged 20–45 years. This narrower range was selected to minimize potential bias by excluding younger women (15–19 years), who may be biologically immature, and older women (46–49 years), who are approaching menopause and are more likely to have chronic comorbidities that could affect study outcomes.
Metabolic syndrome has previously been associated with overweight and obesity47,48 and is generally thought to more likely affect middle-aged and older individuals26,49,50. Recent estimates show that approximately 50% of middle-aged women are affected by metabolic syndrome50,51,52,53. Alarmingly, although participants in our study were younger compared to women in previous studies50,51,52,53, we found that nearly half of the women in our study had metabolic syndrome. This suggests that metabolic syndrome may be a common complication of excess body fat in women well before middle age.
High plasma glucose concentrations (≥ 5.60 mmol/L12) were estimated to affect 1 in 5 women in our study, which is similar to previous findings in Vietnam54. To facilitate comparisons with other studies, we also estimated the proportion of prediabetes (fasting plasma glucose concentrations between 5.6 mmol/L and < 7 mmol/L55,56,57), which was 19.6% (data not presented in Tables). This estimate is higher than previously reported in North America and the Caribbean (15.4%), Central and South America (10%)58, Nepal (9.2%)59, and other countries in South Asia (3.0%-11.5%)60. The difference compared to previous international reports could be a result of a higher BMI in participants in our study, as the finding is in line with the well-established association between overweight/obesity and an increased risk of impaired fasting glucose, which increases the likelihood of developing diabetes61. We acknowledge that the association between glucose and lipid concentrations reflects correlation rather than causality, and that potential multicollinearity or endogeneity among these biomarkers limits causal interpretation.
The prevalence of hypertension is higher among overweight/obese populations compared to non-overweight/non-obese individuals62. The mechanisms through which obesity can lead to elevated arterial blood pressure are complex and appear to be modulated by environmental factors (lifestyle, including diet and exercise), genetic factors62, and age63. Although the prevalence of hypertension in our research (10.4%) was similar to that found in < 40 year old overweight/obese women previously64, it was considerably lower than the 16.6% found in the general population of 23,555 18–69 year old Vietnamese women, as reported in a recent meta-analysis65, or the 2019 prevalence of 32% and > 25% found in 30–79 year old women globally and in Vietnam, respectively66; this difference in prevalence is most likely related to age.
Our results showed significant relationships between metabolic syndrome and anthropometric status and hypertension. Higher BMI and hypertension are well known to be positively associated with metabolic syndrome52,53,67,68,69,70,71. These findings reinforce the need to monitor weight and blood pressure as part of metabolic syndrome screening and management. Although the associations between obesity, hypertension, and metabolic syndrome are partly expected due to definitional overlap, the exceptionally high odds ratio for hypertension (OR 25.40; 95% CI: 3.18–202.89) underscores its clinical and practical importance for identifying high-risk women and guiding targeted interventions. At the public health level, integrating obesity and hypertension screening into community programs for women of reproductive age may support early detection and prevention of metabolic syndrome and its complications, particularly in contexts where prior data are limited.
In this study, plasma glucose and total cholesterol concentrations were associated with parity. The positive association between parity and plasma glucose concentrations found in our study confirmed previous findings72. Our results on the negative relationship between total cholesterol concentrations and parity were also similar to other work in the region, such as in China73. Parity can be used as a proxy indicator of the socioeconomic status of the household where families with more than two children often belong to a lower socioeconomic group74,75. However, a recent change to the population health policy in Vietnam has allowed couples to now have more than two children76. This change has led to an increase in the number of children in wealthier urban families77. The relationship between plasma glucose and total cholesterol concentrations and parity is therefore unclear and requires further investigation in overweight and obese women in Vietnam.
We found that plasma total cholesterol concentrations were higher in unemployed women compared with employed women. It is possible that this relationship may be mediated by eating behaviours, where a high intake of saturated and trans fats resulted in increased plasma cholesterol concentrations78. However, the relationship between employment status and eating behaviours is still poorly understood and requires further clarification. These findings emphasize the relevance of socioeconomic determinants, such as parity and employment status, in tailoring interventions to local populations.
Our research also found positive correlations between plasma triglyceride concentrations and plasma total cholesterol concentrations, systolic blood pressure, and medical status. Not surprisingly, women affected by conditions known to affect plasma glucose concentrations or those associated with weight gain had higher plasma triglyceride concentrations than those not affected by these conditions. The positive relationship between the amount of visceral fat and free fatty acid concentrations was identified as the cause of fat accumulation in the liver, which is common in abdominal obesity79. Elevated free fatty acid concentrations may induce insulin resistance in skeletal muscle by inhibiting insulin-mediated glucose uptake, whereas increased free fatty acid concentrations in the long term may affect the function of pancreatic beta cells80 and lead to high plasma glucose concentrations. In addition, insulin resistance also induces lipid disorders by increasing lipolysis, leading to an excess of free fatty acids. In the liver, free fatty acids are the substrate for the synthesis of triglycerides. This results in high plasma triglycerides and is accompanied by high plasma glucose concentrations through the insulin resistance mechanism in abdominal obesity or general obesity. The relationship between plasma triglyceride concentrations and systolic blood pressure found in our study was consistent with two Japanese studies that showed a significantly positive association between triglycerides and both systolic and diastolic blood pressure81,82. Hence, blood pressure and medical status checks should be recommended practices in clinical and community settings, particularly in overweight and obese women. The former could be a proxy, and the latter is an associated factor of raised triglyceride concentrations. Collecting information on these factors could help identify relevant health issues or medical implications in overweight and obese women.
To date, our study is among the first to evaluate the prevalence of metabolic syndrome, dyslipidemia, hyperglycemia, and hypertension in 20–45 year old overweight and obese women in Vietnam. However, the limitations of this research should be acknowledged. First, as this was a cross-sectional study, causality cannot be assumed. Second, endogeneity among metabolic syndrome components and correlated biomarkers further limits causal interpretation. Third, the relatively small sample size should be noted, as reflected in some wide confidence intervals. Lastly, as energy intakes appeared low for this population, it is likely that the 24-hour dietary recall underestimated energy intake, a common issue in overweight and obese participants83 and women84. This study was also restricted to overweight and obese women of reproductive age, which allowed us to focus on a high-risk group but limits the generalizability of the findings to the broader female population. In addition, based on the sampling strategy, the reported prevalence estimates should be interpreted as representative of the study site only, rather than the entire province or national population. Despite these limitations, the study makes an important contribution and helps close a crucial gap in the current literature in Vietnam.
In summary, dyslipidemia, metabolic syndrome, high plasma glucose concentrations, and hypertension were common in overweight and obese child-bearing women in Bac Giang Province, Vietnam. High parity was positively associated with plasma glucose concentrations and negatively with plasma total cholesterol concentrations, while unemployment and plasma triglyceride concentrations were positively associated with plasma total cholesterol concentrations. Increased systolic blood pressure and conditions known to affect plasma glucose concentrations or shown to be associated with weight gain were risk factors for increased triglyceride concentrations. Obesity and hypertension were risk factors for metabolic syndrome, while obesity was also associated with high plasma glucose concentrations. Taken together, these findings highlight both biological and socioeconomic factors relevant to local health programs. Prospective interventions, education, and communication activities aimed at reducing the risk of metabolic syndrome and its components should therefore consider socioeconomic indicators (e.g., parity, employment) alongside clinical risk factors (e.g., obesity, hypertension) identified in this study.
Data availability
All data generated and analysed for this study are summarised in this published article. The datasets are available from Dr Tuyet Thi Anh Doan (anhtuyetdoanthi@gmail.com) upon reasonable request and with the permission of the National Institute of Nutrition in Vietnam.
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Acknowledgements
The authors thank the study participants and those who conducted the fieldwork (supervisors, interviewers, phlebotomists, anthropometrists, and drivers). We also thank the Directors of the Bac Giang Province Center for Disease Control and the health stations in wards and communes for facilitating the study.
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Study design: TSN, VKT, TDL, TTAD. Data collection: TTAD, TSN, VKT, ATDN, THN, HHL, LNPH, ATN. Statistical analyses: TTAD, NTDH, TSN, TDL, NTT, ATDN, HHL, LNPH, THN, HDN. Data interpretation: TTAD, NTDH, TSN, EAS-G, TDL, NTT, HDN. Writing - original draft: TTAD, NTDH, TSN, EAS-G, TDL. Writing - review & editing: TTAD, NTDH, EAS-G, TSN, TDL. Primary responsibility for final content: TTAD, NTDH, EAS-G, TSN, TDL. All authors provided a critical review of the manuscript and read and approved the final version.
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Doan, T.T.A., Nguyen, T.S., Tran, V.K. et al. Prevalence and factors associated with metabolic syndrome and its components among overweight and obese reproductive-age women in Bac Giang, Vietnam. Sci Rep 15, 42765 (2025). https://doi.org/10.1038/s41598-025-27095-6
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DOI: https://doi.org/10.1038/s41598-025-27095-6
