Hyperglycemia in pregnancy: A sensitivity analysis study of two recommended screening tests in Tanzania.

Hyperglycemia in pregnancy: A sensitivity analysis study of two recommended screening tests in Tanzania | medRxiv /* */ /* */ <!-- <!-- /*! * yepnope1.5.4 * (c) WTFPL, GPLv2 */ (function(a,b,c){function d(a){return"[object Function]"==o.call(a)}function e(a){return"string"==typeof a}function f(){}function g(a){return!a||"loaded"==a||"complete"==a||"uninitialized"==a}function h(){var a=p.shift();q=1,a?a.t?m(function(){("c"==a.t?B.injectCss:B.injectJs)(a.s,0,a.a,a.x,a.e,1)},0):(a(),h()):q=0}function i(a,c,d,e,f,i,j){function k(b){if(!o&&g(l.readyState)&&(u.r=o=1,!q&&h(),l.onload=l.onreadystatechange=null,b)){"img"!=a&&m(function(){t.removeChild(l)},50);for(var d in y[c])y[c].hasOwnProperty(d)&&y[c][d].onload()}}var j=j||B.errorTimeout,l=b.createElement(a),o=0,r=0,u={t:d,s:c,e:f,a:i,x:j};1===y[c]&&(r=1,y[c]=[]),"object"==a?l.data=c:(l.src=c,l.type=a),l.width=l.height="0",l.onerror=l.onload=l.onreadystatechange=function(){k.call(this,r)},p.splice(e,0,u),"img"!=a&&(r||2===y[c]?(t.insertBefore(l,s?null:n),m(k,j)):y[c].push(l))}function j(a,b,c,d,f){return q=0,b=b||"j",e(a)?i("c"==b?v:u,a,b,this.i++,c,d,f):(p.splice(this.i++,0,a),1==p.length&&h()),this}function k(){var a=B;return a.loader={load:j,i:0},a}var l=b.documentElement,m=a.setTimeout,n=b.getElementsByTagName("script")[0],o={}.toString,p=[],q=0,r="MozAppearance"in l.style,s=r&&!!b.createRange().compareNode,t=s?l:n.parentNode,l=a.opera&&"[object Opera]"==o.call(a.opera),l=!!b.attachEvent&&!l,u=r?"object":l?"script":"img",v=l?"script":u,w=Array.isArray||function(a){return"[object Array]"==o.call(a)},x=[],y={},z={timeout:function(a,b){return b.length&&(a.timeout=b[0]),a}},A,B;B=function(a){function b(a){var a=a.split("!"),b=x.length,c=a.pop(),d=a.length,c={url:c,origUrl:c,prefixes:a},e,f,g;for(f=0;f<d;f++)g=a[f].split("="),(e=z[g.shift()])&&(c=e(c,g));for(f=0;f<b;f++)c=x[f](c);return c}function g(a,e,f,g,h){var i=b(a),j=i.autoCallback;i.url.split(".").pop().split("?").shift(),i.bypass||(e&&(e=d(e)?e:e[a]||e[g]||e[a.split("/").pop().split("?")[0]]),i.instead?i.instead(a,e,f,g,h):(y[i.url]?i.noexec=!0:y[i.url]=1,f.load(i.url,i.forceCSS||!i.forceJS&&"css"==i.url.split(".").pop().split("?").shift()?"c":c,i.noexec,i.attrs,i.timeout),(d(e)||d(j))&&f.load(function(){k(),e&&e(i.origUrl,h,g),j&&j(i.origUrl,h,g),y[i.url]=2})))}function h(a,b){function c(a,c){if(a){if(e(a))c||(j=function(){var a=[].slice.call(arguments);k.apply(this,a),l()}),g(a,j,b,0,h);else if(Object(a)===a)for(n in m=function(){var b=0,c;for(c in a)a.hasOwnProperty(c)&&b++;return b}(),a)a.hasOwnProperty(n)&&(!c&&!--m&&(d(j)?j=function(){var a=[].slice.call(arguments);k.apply(this,a),l()}:j[n]=function(a){return function(){var b=[].slice.call(arguments);a&&a.apply(this,b),l()}}(k[n])),g(a[n],j,b,n,h))}else!c&&l()}var h=!!a.test,i=a.load||a.both,j=a.callback||f,k=j,l=a.complete||f,m,n;c(h?a.yep:a.nope,!!i),i&&c(i)}var i,j,l=this.yepnope.loader;if(e(a))g(a,0,l,0);else if(w(a))for(i=0;i (function(w,d,s,l,i){w[l]=w[l]||[];w[l].push({'gtm.start':new Date().getTime(),event:'gtm.js'});var f=d.getElementsByTagName(s)[0];var j=d.createElement(s);var dl=l!='dataLayer'?'&l='+l:'';j.src='//www.googletagmanager.com/gtm.js?id='+i+dl;j.type='text/javascript';j.async=true;f.parentNode.insertBefore(j,f);})(window,document,'script','dataLayer','GTM-P4HH5NV'); Skip to main content Home About Submit ALERTS / RSS Search for this keyword Advanced Search Hyperglycemia in pregnancy: A sensitivity analysis study of two recommended screening tests in Tanzania View ORCID Profile Amani Kikula , View ORCID Profile Kaushik Ramaiya , View ORCID Profile Nathanael Sirili , View ORCID Profile Matilda Mkonyi , Rukia Msumi , John Macha , View ORCID Profile Andrea B. Pembe , View ORCID Profile José L. Peñalvo , View ORCID Profile Lenka Beňová doi: https://doi.org/10.1101/2025.05.08.25327275 Amani Kikula 1 Department of Obstetrics and Gynaecology, Muhimbili University of Health and Allied Sciences , Dar es Salaam, Tanzania 2 Department of Family Medicine and Population Health, University of Antwerp , Antwerp, Belgium 3 Department of Public Health, Institute of Tropical Medicine , Antwerp, Belgium Find this author on Google Scholar Find this author on PubMed Search for this author on this site ORCID record for Amani Kikula For correspondence: amanikikula{at}live.com Kaushik Ramaiya 4 Department of Internal Medicine, Shree Hindu Mandal Hospital , Dar es salaam, Tanzania Find this author on Google Scholar Find this author on PubMed Search for this author on this site ORCID record for Kaushik Ramaiya Nathanael Sirili 5 Department of Development Studies, Muhimbili University of Health and Allied Sciences , Dar es Salaam, Tanzania Find this author on Google Scholar Find this author on PubMed Search for this author on this site ORCID record for Nathanael Sirili Matilda Mkonyi 1 Department of Obstetrics and Gynaecology, Muhimbili University of Health and Allied Sciences , Dar es Salaam, Tanzania Find this author on Google Scholar Find this author on PubMed Search for this author on this site ORCID record for Matilda Mkonyi Rukia Msumi 6 Department of Obstetrics and Gynaecology, Mbagala Rangi Tatu Hospital , Dar es salaam, Tanzania Find this author on Google Scholar Find this author on PubMed Search for this author on this site John Macha 7 Department of Obstetrics and Gynaecology, Kisarawe District Hospital , Coast, Tanzania Find this author on Google Scholar Find this author on PubMed Search for this author on this site Andrea B. Pembe 1 Department of Obstetrics and Gynaecology, Muhimbili University of Health and Allied Sciences , Dar es Salaam, Tanzania Find this author on Google Scholar Find this author on PubMed Search for this author on this site ORCID record for Andrea B. Pembe José L. Peñalvo 2 Department of Family Medicine and Population Health, University of Antwerp , Antwerp, Belgium 8 Instituto de Salud Carlos III , Madrid, Spain Find this author on Google Scholar Find this author on PubMed Search for this author on this site ORCID record for José L. Peñalvo Lenka Beňová 3 Department of Public Health, Institute of Tropical Medicine , Antwerp, Belgium Find this author on Google Scholar Find this author on PubMed Search for this author on this site ORCID record for Lenka Beňová Abstract Full Text Info/History Metrics Data/Code Preview PDF Abstract Screening for hyperglycaemia in pregnancy (HIP) is an entry point to a healthy pregnancy and childbirth for both the woman and child, and offers a window of opportunity for the prevention of cardio-metabolic complications over the life-course of the woman and newborn. In Tanzania, two different screening algorithms to identify women with HIP are recommended, with no clear understanding of which performs better. We aimed to determine the prevalence of hyperglycemia in pregnancy (HIP) among antenatal care (ANC) attendees and the accuracy of HIP screening tests. A cross-sectional study design involving 970 women attending ANC clinic was done in two district hospitals (Mbagala Rangi Tatu and Kisarawe) of Tanzania between June and October 2024. Socio-demographic, obstetric characteristics, and anthropometric parameters were obtained from study participants. A checklist screening test (CST) for gestational diabetes mellitus (GDM), defined by the Tanzanian standard treatment guideline, was used. We tested for glycosuria and two-hour 75-gram oral glucose tolerance test (OGTT) on every study participant. We conducted descriptive statistics and sensitivity analysis to determine the prevalence of HIP and assess the screening performance of CST and glycosuria test against OGTT using World Health Organization 2013 diagnostic criteria for GDM. The prevalence of HIP was 10% (7.9% GDM and 2.1% diabetes in pregnancy). Glycosuria test missed all women with GDM and could identify only 20% with diabetes in pregnancy. The CST had a sensitivity and specificity of 72.2% and 32.4%, respectively, while the glycosuria test had 4.1% and 97.1%. The area under the receiver operator characteristic curve for both the CST 0.523 (0.48-0.57,95%CI) and glycosuria test 0.506 (0.49-0.53,95%CI) was low, indicating their poor discriminatory performance for HIP. One in every ten women had HIP. The CST is a better first-step screening test than the glycosuria test based on sensitivity. 1 Introduction In 2020 , approximately 800 women died globally every day due to pregnancy-related complications with 70% of these deaths occurred in sub-Saharan Africa (SSA) ( 1 ). Complicating the efforts to reduce maternal deaths is the increasing contribution of indirect causes to overall maternal mortality, known as the obstetric transition ( 2 – 4 ). It is in part caused by the growing epidemic of overweight and obesity, particularly among women of SSA ( 5 – 7 ). In Tanzania, like in most other SSA countries, the prevalence of high body mass index (BMI) among adults is increasing ( 8 , 9 ) and over a quarter of women who intend to conceive were either overweight or obese ( 10 ). Overweight and obesity during pregnancy are risk factors for gestational diabetes mellitus (GDM) ( 11 ). GDM increases the risk for complications during pregnancy, childbirth, and beyond, including pre-eclampsia and intra-uterine fetal death; traumatic or operative delivery ( 12 ). Following delivery, the risk for infection and thromboembolism is higher among women with GDM ( 12 ). The risk for developing type 2 diabetes mellitus and other cardiometabolic conditions later in life is also higher for the newborn and woman who had unmanaged GDM ( 13 ). Thus, screening for GDM as an entry point to successful timely management of the condition is an important predictor of a healthy pregnancy and childbirth for both the woman and child, and offers a window of opportunity for the prevention of these complications over the life-course ( 14 ). In 2013, the World Health Organization (WHO) adopted the International Association of Diabetes and Pregnancy Study Groups recommendation for universal screening using a one-step, 75-grams, two-hour oral glucose tolerance test (OGTT) ( 15 ). Alternatively, a two-step approach involves an initial screening based on one or more risk factors to identify women who require an OGTT. This method is favored in settings where universal OGTT-based screening is not economically feasible. The International Federation of Gynecology and Obstetrics (FIGO) advocates for context-specific screening strategies that align with the healthcare system realities of different countries ( 12 ). In Tanzania, the two-step approach has been adopted. However, two different screening algorithms to identify women for the second step co-exist in national guidelines. The Tanzania antenatal care (ANC) guideline uses glycosuria as the initial screening step for those who would require a random blood glucose test ( 16 ). The Tanzania standard treatment guideline (STG) relies on a checklist of risk factors ( Table 1 ) to identify those who should be further tested using OGTT ( 17 ). In the Tanzanian context, there is no evidence about which one of these screening modalities performs better. Therefore, this study aimed to assess the prevalence of GDM and evaluate the accuracy of both screening algorithms among women attending ANC in two district hospitals in Tanzania. View this table: View inline View popup Download powerpoint Table 1: Source and information obtained from the woman during data collection 2 Materials and methods We conducted a cross-sectional study to assess screening accuracy for hyperglycemia in pregnancy (HIP) with a focus on sensitivity of the screening tests ( 18 ). The index screening tests were a checklist screening test (CST) and a urine dipstick glycosuria test. The diagnostic gold standard test was the two-hour 75-gram non-fasting OGTT. 2.1 Study sites We collected data in ANC clinics of two primary-level district hospitals in Tanzania between June 19 and October 31, 2024. Firstly, Kisarawe hospital is located in a rural district of the Coast region and Mbagala Rangi Tatu hospital is in an urban district of Dar es salaam region. More details about study sites are provided elsewhere ( 19 ). In Tanzania, ANC service is offered from the dispensary level to the national level hospital, with 90% of women receiving ANC services from skilled providers ( 20 ). More women (55%) are receiving ANC at district hospitals compared to any other level ( 21 ). 2.2 ANC services related to GDM care During ANC, women’s height is measured at the first visit; their weight and blood pressure are measured every visit. The two study hospitals had laboratory departments that served the whole hospital, including the ANC clinic. Routinely, point-of-care capillary blood glucose tests to check for glucose levels were used and either a urine dipstick or analyzer machine for urinalysis was done. All care provided and any results were documented in the hospital registers and the woman-held ANC record. Services provided at the ANC clinic are guided by the Tanzanian ANC guideline ( 16 ) and supplemented by the Tanzanian STG ( 17 ). 2.3 Sample size and eligibility We used a standard sample size formula for sensitivity studies ( 22 ). A minimum sample size of 946 women was deemed necessary considering a 19.5% prevalence of GDM ( 23 ) and expected level of sensitivity for glycosuria test of 4.7% and 69% for CST ( 24 , 25 ). The desired precision estimate of 7% at a 95% level of confidence, and a 10% refusal rate. All women attending ANC clinics in the study hospitals at gestation age of 24 to 28 weeks were approached and those who provided informed written consent were enrolled for a structured interview and other measurements ( Table 1 ). We excluded women who were known diabetes mellitus patients through medical records or self-report, who were on steroid treatment for any medical condition, or who had a self-reported active diagnosed infectious disease (e.g. malaria) on day of the visit. We consecutively included all eligible women in both hospitals until the sample size was reached. For the glycosuria test, women were provided with urine collecting containers (60ml) and instructed to collect a minimum of 10ml of urine within dedicated hospital toilets. They immediately submitted the urine sample to the trained laboratory research assistants (RAs) for processing. Following collection of the urine sample, study participants were provided with a rapillose 75gram OGTT solution ( 26 ) and we supervised their consumption in 15-20 minutes. RAs documented the participants’ study ID and time of intake of the OGTT solution in the laboratory study request form and attached it to the woman’s ANC record. Women then received their routine ANC while awaiting the two-hour time mark for a blood glucose test. Fig 1 shows the sequence of study procedures that recruited women in the study followed. Laboratory RAs were selected laboratory personnel from each hospital who received and processed the urine for glycosuria and POC capillary blood glucose tests. Calibration was done after every 20 th test using calibration strips and a control solution provided by the manufacturer. Download figure Open in new tab Fig 1: Description of recruitment of study participants and study procedures The results of the glycosuria test and the blood glucose test were documented in the study request form and the ANC record. A member of the research team also communicated the test results to the woman and the ANC clinic staff. Women with blood glucose of ≥8.5 mmol/dl were referred to the hospital obstetrician and continued with further care as per hospital protocol. Table 2 describes all the measured parameters that were done to recruited women. View this table: View inline View popup Table 2: Description of the measured parameters for study participants 2.4 Data collection and analysis We collected all the data using kobo toolbox electronic software, extracted and cleaned in Excel spreadsheet then exported for analysis into STATA SE software (V.18.5). All entries with a missing blood glucose value were excluded from the analysis. We conducted pooled descriptive and sensitivity analysis of participant characteristics from both hospitals. For each screening test and the diagnostic test, we categorized results as either positive or negative. The BMI was extrapolated from the MUAC with a consideration that MUAC has a negligible increase during pregnancy (0.05 cm) and a MUAC of ≥ 28 cm was considered to correlate to pre-pregnancy BMI of ≥ 25kg/m 2 ( 23 , 27 ). In Tanzania, only 34% of women have their first ANC clinic visit in the first trimester ( 20 ), this limited using the documented body weight on the ANC record for BMI calculation. We used a ≥8.5mmol/L cut-off value for the diagncostic test to determine the true positive, false positive, true negative, and false negative values. The performance of the screening tests was measured using sensitivity, specificity, negative and positive predictive values, with a 95% confidence interval (CI). Hyperglycemia in pregnancy includes GDM and diabetes in pregnancy (DIP). We classified blood glucose levels of 8.5-11.0 mmol/L as GDM, and >11.0 mmol/L as DIP ( 12 ). We compared the performance of the two screening tests using the receiver operator characteristics (ROC) curves against the diagnostic OGTT test. The diagnostic test result was dichotomized to hyperglycemia and normal blood glucose value (<8.5 mmol/L). 2.5 Ethical approvals The study received ethical approval from the Institutional Ethics Committee at the Institute of Tropical Medicine, Antwerp 1687/23, Muhimbili University of Health and Allied Sciences Research and Ethics committee MUHAS-REC-07-2023-1834 and the National Health Research Ethics Review Committee NIMR/HQ/R.8a/Vol.IX/4457. 3. Results We recruited a total of 975 women for screening at the two hospitals. Out of these, five were excluded; two were unavailable for the two-hour blood glucose test, and three requested withdrawal from the study ( Fig 2 ). Download figure Open in new tab Fig 2: Study flowchart for inclusion of study participants for analysis Out of the 970 women included in the final analysis sample, 68.7% (666 women) were recruited at Mbagala Rangi Tatu Hospital ( Table 3 ). Just half (52.2%) of the study participants were in the 20–29-years age group. A total of 40.2% had attained secondary school-level education and the majority (91.6%) were either married or living with a partner. About two-thirds (56.4%) had a BMI of ≥25kg/m 2 and 4.1% were HIV-positive. View this table: View inline View popup Table 3: Sociodemographic characteristics, HIV status, and body mass index of the study participants by hospital (n=970) The prevalence of GDM was 7.9%, and of DIP 2.1%, with a combined 10.0% prevalence of HIP. The glycosuria test was negative for all women diagnosed with GDM and identified only 20% of women with DIP. The CST identified over two-thirds (67.5%) of women with GDM and 90.0% of women with DIP ( Table 4 ). View this table: View inline View popup Table 4: Prevalence of gestational diabetes mellitus and diabetes in pregnancy among women from the study hospitals (n=970) The CST had a higher sensitivity than glycosuria test (72.2% vs 4.1%), making the CST a better first-step screening test as compared to the glycosuria test. The glycosuria test had a better specificity of 97.1% than 32.4% of the CST. Both tests had comparable positive predictive values (10.6% CST,13.8% glycosuria) and negative predictive values (91.3% checklist and 90.1% glycosuria) ( Table 5 ). Overall, both tests performed poorly as diagnostic tests for HIP with area under the ROCs of 0.52 (0.48-0.57, 95%CI) and 0.51 (0.49-0.53, 95%CI) respectively, indicating poor discrimination ( Figure 3 ). View this table: View inline View popup Download powerpoint Table 5: Sensitivity analysis for Hyperglycemia in pregnancy of checklist screening test and glycosuria test against 2-hours OGTT (n=970) Download figure Open in new tab Fig 3: Receiver observer characteristics curve comparing checklist screening test and glycosuria tests for Hyperglycemia in pregnancy. 4 Discussion In the two study hospitals, one in every ten women presenting for antenatal care at 24 to 28 weeks of pregnancy had hyperglycemia in pregnancy. The glycosuria test could not identify any woman with GDM and missed more than three-quarters of those who tested positive for DIP. The CST had better sensitivity than the glycosuria test making it a better first-step screening test than the glycosuria test in identifying women with hyperglycemia during pregnancy for diagnostic tests. Both CST and glycosuria tests cannot be used as stand-alone diagnostic tests for Hyperglycemia in pregnancy. At a global level, multiple guidelines with different algorithms exist for GDM screening ( 28 ). Screening algorithms and diagnostic thresholds differ across different available guidelines and have evolved affecting GDM prevalence estimation and its standardization ( 29 – 32 ). The FIGO recommended standardized algorithms and tests for GDM screening to suit different contexts, including having the OGTT as the gold standard test for GDM diagnosis, however, its cost has limited its universal usage, particularly in low-resource countries ( 12 , 33 ). Tanzania faces a unique situation of having two co-existing algorithms with a glycosuria test and CST recommended independently for GDM screening in the two available national guidelines ( 16 , 17 ). The healthcare workers using these guidelines work within a health system with limited supplies, training opportunities, and monitoring frameworks ( 21 ). These challenges are known to limit the implementation of multiple clinical guideline recommendations ( 34 ) with low levels of optimal adherence to available treatment guidelines ( 35 – 37 ). Having two guidelines in Tanzania, with two algorithms and different types of tests for screening, further complicates efforts to mainstream GDM care within the ANC setting. This underscores the need for the Ministry of Health to have a single algorithm for GDM screening in its guidelines. This should go hand-in-hand with efforts to improve the health system capacity to manage those who will test positive for GDM ( 38 ). For the study participants, the glycosuria test missed all women who screened positive for GDM and was positive for only one-fifth of those with DIP. The urine multi-stick used for glycosuria test is routinely used in most primary healthcare facilities for assessing other clinical parameters in urine as part of ANC check ( 20 ), however, it lacks the required sensitivity as a GDM first-step screening test. The CST demonstrated better sensitivity compared to glycosuria test. The items on the checklist could be further adapted to the Tanzanian context to improve its sensitivity and specificity as a first-step screening test ( 24 , 39 ). Studies have reported that using additional characteristics such as body fat content, history of macrosomic birth, MUAC, and family history of diabetes improved the CST’s screening accuracy ( 39 ). However, it requires a good medical records system to report such characteristics ( 40 ). Given the low sensitivity of the glycosuria test shown in this study and other studies ( 12 , 25 ), it should no longer be used as a GDM screening tool in Tanzania. Globally, about one in every ten pregnancies are affected by GDM, ( 41 ) in line with the findings from this study. In North Africa, over a quarter of pregnant women have GDM, which is the highest in Africa ( 42 ). Overall, there is no significant difference in the prevalence of GDM between low-income and high-income countries ( 42 ). In Tanzania, while there was no GDM detected in the early 1990s ( 43 ), GDM prevalence since the 2000s have ranged from 4.3% to 39% ( 23 , 44 , 45 ). These variations could be attributed to differences in the studies’ cut-off values and tests used for diagnosis, the population studied, but are also sounding an alarm about the rise of GDM in the country. Without routine screening during ANC, pregnant women will miss the opportunity for early detection and timely intervention to prevent potential GDM-related complications during pregnancy and cardiometabolic complications after childbirth ( 46 ). The high prevalence and known morbidities that result from GDM underscore the need for universal screening of GDM to achieve targeted reductions in maternal mortality in the global south. We acknowledge using a non-fasting two-hour OGTT as a diagnostic test for GDM which is evidenced to have similar diagnostic accuracy to the fasting two-hour OGTT ( 12 , 47 , 48 ). The blood sample used was a capillary blood sample which has slight lower glucose levels to the plasma blood samples. Despite these limitations, to our knowledge, this is the first study of its kind in Tanzania to compare the screening potential of two nationally recommended screening tests for GDM. Additionally, our use of standardized 75-gram OGTT solutions maintained consistent glucose loads to all participants. We believe that these findings highlight the need to urgently revise the GDM screening guidelines and consistently implement one well-performing screening algorithm. 5 Conclusions Hyperglycemia in pregnancy was found in 10% of the pregnant women in the study hospitals. The CST performed better as a first-step screening tool. Glycosuria test performed poorly and should not be used as a screening tool for GDM. We recommend further studies to be done to inform the revision of the GDM screening tests to have one with an optimally acceptable discriminatory potential during screening for further diagnostic confirmation of hyperglycemia in pregnancy in Tanzania. Data Availability Data will be available upon reasonable request through the National Institute of Medical Research, Tanzania - National Health Research Ethics Review Sub-committee - publications{at}nimr.or.tz www.nimr.or.tz https://www.nimr.or.tz Authors’ contributions Conceptualization, data curation, formal analysis, investigation, methodology, project administration, resources, validation, visualization, writing original draft and reviews – AK; investigation, methodology, reviewing and editing the manuscript – MM, RM, and JM; conceptualization, supervision, methodology, review and editing of manuscript, and validation KR,NS, ABP, JLP, and LB. Declaration of interest None. Acknowledgments We thank the women who agreed to participate in this study. We also acknowledge Judith Banyenza, Karama Ogillo and Joyce Kaswamila who assisted in data collection, Davis Mlay for managing the electronic database. We are also thankful to the health care workers and health managers in the two districts that the work was done. Footnotes ↵ α Senior author References 1. ↵ Trends in maternal mortality 2000 to 2020: estimates by WHO, UNICEF, UNFPA, World Bank Group and UNDESA/Population Division [Internet] . [cited 2025 Jan 7 ]. Available from: https://www.who.int/publications/i/item/9789240068759 2. ↵ Chaves S da C , Cecatti JG , Carroli G , Lumbiganon P , Hogue CJ , Mori R , et al. Obstetric transition in the World Health Organization Multicountry Survey on Maternal and Newborn Health: exploring pathways for maternal mortality reduction . Rev Panam Salud Publica . 2015 May ; 37 ( 4–5 ): 203 – 10 . OpenUrl PubMed 3. Souza J , Tunçalp Ö, Vogel J , Bohren M , Widmer M , Oladapo O , et al. Obstetric transition: the pathway towards ending preventable maternal deaths . BJOG: An International Journal of Obstetrics & Gynaecology . 2014 ; 121 ( 1 ): 1 – 4 . OpenUrl 4. ↵ Cresswell JA , Alexander M , Chong MYC , Link HM , Pejchinovska M , Gazeley U , et al. Global and regional causes of maternal deaths 2009-20: a WHO systematic analysis . Lancet Glob Health . 2025 Apr ; 13 ( 4 ): e626 – 34 . OpenUrl 5. ↵ Vasileva LV , Marchev AS , Georgiev MI . Causes and solutions to “globesity”: The new fa(s)t alarming global epidemic . Food and Chemical Toxicology . 2018 Nov 1; 121 : 173 – 93 . OpenUrl PubMed 6. Obesity and overweight [Internet] . [cited 2025 Jan 7 ]. Available from: https://www.who.int/news-room/fact-sheets/detail/obesity-and-overweight 7. ↵ World Obesity Federation Global Obesity Observatory [Internet] . [cited 2025 Feb 26 ]. World Obesity Day Atlases | Obesity Atlas 2024 . Available from: https://data.worldobesity.org/publications/?cat=22 8. ↵ Pallangyo P , Mkojera ZS , Hemed NR , Swai HJ , Misidai N , Mgopa L , et al. Obesity epidemic in urban Tanzania: a public health calamity in an already overwhelmed and fragmented health system . BMC Endocrine Disorders . 2020 Sep 29; 20 ( 1 ): 147 . OpenUrl PubMed 9. ↵ Msollo SS , Shausi GL , Mwanri AW . Prevalence, knowledge and practices on prevention and management of overweight and obesity among adults in Dodoma City, Tanzania . PLoS One . 2024 ; 19 ( 1 ): e0297665 . OpenUrl CrossRef PubMed 10. ↵ Kikula AI , Semaan A , Balandya B , Makoko NK , Pembe AB , Peñalvo JL , et al. Increasing prevalence of overweight and obesity among Tanzanian women of reproductive age intending to conceive: evidence from three Demographic Health Surveys, 2004–2016 . Journal of Global Health Reports . 2023 Oct 4; 7 : e2023062 . OpenUrl 11. ↵ Maternal Obesity and Risk of Gestational Diabetes Mellitus | Diabetes Care | American Diabetes Association [Internet] . [cited 2025 Feb 26 ]. Available from: https://diabetesjournals.org/care/article/30/8/2070/28574/Maternal-Obesity-and-Risk-of-Gestational-Diabetes 12. ↵ Moshe H , Kapur A , Sacks DA , Hadar E , Agarwal M , Di Renzo GC , et al. The International Federation of Gynecology and Obstetrics (FIGO) Initiative on gestational diabetes mellitus: A pragmatic guide for diagnosis, management, and care . 2015 ; 131 ( S3 ). Available from: https://obgyn.onlinelibrary.wiley.com/doi/10.1016/S0020-7292%2815%2930033-3 13. ↵ Hivert MF , Backman H , Benhalima K , Catalano P , Desoye G , Immanuel J , et al. Pathophysiology from preconception, during pregnancy, and beyond . The Lancet . 2024 Jul 13; 404 ( 10448 ): 158 – 74 . OpenUrl 14. ↵ Simmons D , Gupta Y , Hernandez TL , Levitt N , van Poppel M , Yang X , et al. Call to action for a life course approach . Lancet . 2024 Jul 13; 404 ( 10448 ): 193 – 214 . OpenUrl PubMed 15. ↵ WHO Diagnostic Criteria and Classification of Hyperglycaemia First Detected in Pregnancy; 2013 [Internet] . [cited 2025 Jan 7 ]. Available from: https://iris.who.int/bitstream/handle/10665/85975/WHO_NMH_MND_13.2_eng.pdf?sequence=1 16. ↵ Antenatal care Guideline 2018 , Tanzania Mainland . 17. ↵ Standard Treatment Guidelines and National Essential Medicines List For Tanzania Mainland ; 2021 ; Sixth edition. 18. ↵ Bossuyt PM , Reitsma JB , Bruns DE , Gatsonis CA , Glasziou PP , Irwig L , et al. STARD 2015: an updated list of essential items for reporting diagnostic accuracy studies . BMJ . 2015 Oct 28; 351 : h5527 . OpenUrl FREE Full Text 19. ↵ Kikula A , Sirili N , Ramaiya K , Peñalvo JL , Pembe AB , Beňová L. Optimizing screening practice for gestational diabetes mellitus in primary healthcare facilities in Tanzania: research protocol . Reprod Health . 2024 Dec 20; 21 ( 1 ): 193 . OpenUrl PubMed 20. ↵ Mainland M of H [Tanzania, Health [Zanzibar M of, Statistics (NBS) NB of, Statistician (OCGS) O of the CG, ICF . Tanzania demographic and health survey 2022 . 2023 Oct 15; Available from: https://www.dhsprogram.com/publications/publication-FR382-DHS-Final-Reports.cfm 21. ↵ Ramaiya KL , Swai AM , Mutabingwa TK , Mwanri AW , Kagaruki GB . Capacity and capability of Tanzania health facilities to diagnose and manage diabetes mellitus in pregnancy . Diabetes Res Clin Pract . 2018 Nov ; 145 : 119 – 29 . OpenUrl PubMed 22. ↵ Hajian-Tilaki K. Sample size estimation in diagnostic test studies of biomedical informatics . Journal of Biomedical Informatics . 2014 Apr 1; 48 : 193 – 204 . OpenUrl CrossRef PubMed 23. ↵ Njete HI , John B , Mlay P , Mahande MJ , Msuya SE . Prevalence, predictors and challenges of gestational diabetes mellitus screening among pregnant women in northern Tanzania . Trop Med Int Health . 2018 Feb ; 23 ( 2 ): 236 – 42 . OpenUrl PubMed 24. ↵ Nombo AP , Mwanri AW , Brouwer-Brolsma EM , Ramaiya KL , Feskens EJM . Gestational diabetes mellitus risk score: A practical tool to predict gestational diabetes mellitus risk in Tanzania . Diabetes Res Clin Pract . 2018 Nov ; 145 : 130 – 7 . OpenUrl PubMed 25. ↵ Agbozo F , Abubakari A , Narh C , Jahn A. Accuracy of glycosuria, random blood glucose and risk factors as selective screening tools for gestational diabetes mellitus in comparison with universal diagnosing . BMJ Open Diabetes Res Care . 2018 ; 6 ( 1 ): e000493 . OpenUrl Abstract / FREE Full Text 26. ↵ Rapilose-OGTT-Product-Data-Sheet-v1.5-20231212-1.pdf [Internet] . [cited 2024 Dec 11 ]. Available from: https://www.penlanhealthcare.com/wp-content/uploads/2024/04/Rapilose-OGTT-Product-Data-Sheet-v1.5-20231212-1.pdf 27. ↵ Khadivzadeh T. Mid upper arm and calf circumferences as indicators of nutritional status in women of reproductive age . East Mediterr Health J . 2002 ; 8 ( 4–5 ): 612 – 8 . OpenUrl PubMed 28. ↵ Zhang M , Zhou Y , Zhong J , Wang K , Ding Y , Li L. Current guidelines on the management of gestational diabetes mellitus: a content analysis and appraisal . BMC Pregnancy Childbirth . 2019 Dec ; 19 ( 1 ): 1 – 15 . OpenUrl CrossRef PubMed 29. ↵ Simmons D , Sweeting A. Defining gestational diabetes: not just about cutoffs . The Lancet Diabetes & Endocrinology . 2023 May 1; 11 ( 5 ): 303 – 4 . OpenUrl PubMed 30. Desoye G , Poppel M van . Is a new discussion about diagnosis of gestational diabetes needed? The Lancet Diabetes & Endocrinology . 2024 Jan 1; 12 ( 1 ): 11 – 2 . OpenUrl PubMed 31. Rani PR , Begum J. Screening and Diagnosis of Gestational Diabetes Mellitus, Where Do We Stand . J Clin Diagn Res . 2016 Apr ; 10 ( 4 ): QE01 – 4 . OpenUrl 32. ↵ Bakshi RK , Kumar A , Gupta V , Radhika AG , Misra P , Bhardwaj P. Review of the Screening Guidelines for Gestational Diabetes Mellitus: How to Choose Wisely . Indian Journal of Community Medicine . 2023 Dec ; 48 ( 6 ): 828 . OpenUrl PubMed 33. ↵ Jagannathan R , Neves JS , Dorcely B , Chung ST , Tamura K , Rhee M , et al. The Oral Glucose Tolerance Test: 100 Years Later . Diabetes Metab Syndr Obes . 2020 Oct 19; 13 : 3787 – 805 . OpenUrl PubMed 34. ↵ Gandolfi S , Bellè N , Nuti S. Please mind the gap between guidelines & behavior change: A systematic review and a consideration on effectiveness in healthcare . Health Policy . 2025 Jan ; 151 : 105191 . OpenUrl PubMed 35. ↵ Mwakasungura F , Mkumbwa R , Sunguya B. Facilitators and barriers for healthcare workers’ adherence to the national nutritional guidelines for people living with HIV in Dar-es-Salaam: A mixed-method study . PLOS Global Public Health . 2025 Feb 25; 5 ( 2 ): e0003664 . OpenUrl 36. Budimu A , Emidi B , Mkumbaye S , Kajeguka DC . Adherence, Awareness, Access, and Use of Standard Diagnosis and Treatment Guideline for Malaria Case Management among Healthcare Workers in Meatu, Tanzania . J Trop Med . 2020 Feb 18; 2020 : 1918583 . OpenUrl CrossRef PubMed 37. ↵ Wiedenmayer K , Ombaka E , Kabudi B , Canavan R , Rajkumar S , Chilunda F , et al. Adherence to standard treatment guidelines among prescribers in primary healthcare facilities in the Dodoma region of Tanzania . BMC Health Services Research . 2021 Mar 24; 21 ( 1 ): 272 . OpenUrl PubMed 38. ↵ Utz B , De Brouwere V. “Why screen if we cannot follow-up and manage?” Challenges for gestational diabetes screening and management in low and lower-middle income countries: results of a cross-sectional survey . BMC Pregnancy Childbirth . 2016 Nov 8; 16 ( 1 ): 341 . OpenUrl PubMed 39. ↵ Msollo SS , Martin HD , Mwanri AW , Petrucka P. Simple method for identification of women at risk of gestational diabetes mellitus in Arusha urban, Tanzania . BMC Pregnancy Childbirth . 2022 Jul 6; 22 : 545 . OpenUrl PubMed 40. ↵ Natural language processing of electronic health records for early detection of cognitive decline: a systematic review | npj Digital Medicine [Internet] . [cited 2025 Mar 11 ]. Available from: https://www.nature.com/articles/s41746-025-01527-z 41. ↵ Sweeting A , Hannah W , Backman H , Catalano P , Feghali M , Herman WH , et al. Epidemiology and management of gestational diabetes . The Lancet . 2024 Jul 13; 404 ( 10448 ): 175 – 92 . OpenUrl 42. ↵ Wang H , Li N , Chivese T , Werfalli M , Sun H , Yuen L , et al. IDF Diabetes Atlas: Estimation of Global and Regional Gestational Diabetes Mellitus Prevalence for 2021 by International Association of Diabetes in Pregnancy Study Group’s Criteria . Diabetes Research and Clinical Practice [Internet] . 2022 Jan 1 [cited 2025 Feb 7 ]; 183 . Available from: https://www.diabetesresearchclinicalpractice.com/article/S0168-8227(21)00409-5/fulltext 43. ↵ Swai AB , Kitange HM , McLarty DG , Kilima PM , Masuki G , Mtinangi BL , et al. No deterioration of oral glucose tolerance during pregnancy in rural Tanzania . Diabet Med . 1991 Apr ; 8 ( 3 ): 254 – 7 . OpenUrl PubMed 44. ↵ Grunnet LG , Hjort L , Minja DT , Msemo OA , Møller SL , Prasad RB , et al. High Prevalence of Gestational Diabetes Mellitus in Rural Tanzania—Diagnosis Mainly Based on Fasting Blood Glucose from Oral Glucose Tolerance Test . IJERPH [Internet] . 2020 [cited 2025 Feb 27 ]; 17 ( 9 ). Available from: https://www.mdpi.com/1660-4601/17/9/3109 45. ↵ Mghanga FP , Maduhu EA , Nyawale HA . Prevalence and associated factors of gestational diabetes mellitus among rural pregnant women in southern Tanzania . Ghana Med J . 2020 Jun ; 54 ( 2 ): 82 – 7 . OpenUrl PubMed 46. ↵ Fu J , Retnakaran R. The life course perspective of gestational diabetes: An opportunity for the prevention of diabetes and heart disease in women . eClinicalMedicine [Internet] . 2022 Mar 1;45. Available from: https://www.thelancet.com/journals/eclinm/article/PIIS2589-5370(22)00024-4/fulltext 47. ↵ Seshiah V , Balaji V , Shah SN , Joshi S , Das AK , Sahay BK , et al. Diagnosis of gestational diabetes mellitus in the community . J Assoc Physicians India . 2012 Aug ; 60 : 15 – 7 . OpenUrl PubMed 48. ↵ Anjalakshi C , Balaji V , Balaji MS , Ashalata S , Suganthi S , Arthi T , et al. A single test procedure to diagnose gestational diabetes mellitus . Acta Diabetol . 2009 Mar 1; 46 ( 1 ): 51 – 4 . OpenUrl CrossRef PubMed View the discussion thread. Back to top Previous Next Posted May 09, 2025. Download PDF Data/Code Email Thank you for your interest in spreading the word about medRxiv. NOTE: Your email address is requested solely to identify you as the sender of this article. 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