Socio-Environmental Variation in Menopause Experiences of Subsaharan African women: A LMIC-HIC comparative perspective

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Adedipe, Joseph S. Hundeyin, Olu A. Adedipe, Sylvia N Kama-Kieghe This is a preprint; it has not been peer reviewed by a journal. https://doi.org/ 10.21203/rs.3.rs-8239685/v1 This work is licensed under a CC BY 4.0 License Status: Published Journal Publication published 26 Dec, 2025 Read the published version in Journal of Advances in Medicine and Medical Research → Version 1 posted You are reading this latest preprint version Abstract Objectives : to identify menopause age, symptom-prevalence and severity, knowledge and treatment-gap specific to residence of the Sub-Saharan women. Methods : An electronic mixed-methods cross-sectional community survey administered in June 2024, of Sub-Saharan women >40yrs who had reached menopause across the world. Data analysis was via Microsoft Excel©. Results : 87 of the 124 responses met inclusion criteria. Average menopause age of 47.59 yrs ± 4.56 (HIC) vs 49.78yrs ±3.26 (LMIC) P= 0.013 95%CI (0.479 -3.9). There were no statistical differences in demographics though a small cohort of HIC women with early menopause occurrence after 5-8yrs of emigration with an average of 6.8 yrs ± 3.4 yrs, was observed. Symptom-prevalence was 93.5%(HIC) vs 92.7%(LMIC). Global significant symptom-severity at 17%: Genitourinary symptoms- GUS (58%) was most common in LMIC cohort followed by Vasomotor symptoms (42%) and Insomnia (21%). Vasomotor symptoms were equipoised with GUS in the HIC (58%). Hypertension prevalence was 15.2% (HIC) vs 21.4% (LMIC). Knowledge deficit : Appropriate definition by >78% globally with the HIC cohort largely by symptomatology. There was poorer symptom-recognition in the LMIC (46.3%) as compared to the HIC (26.1%). Some harm from poor symptom-recognition due to disease-severity was seen in LMIC (16%) as only 13% with significant symptom-severity, mostly Vasomotor and GUS, were on MHT (Menopause hormone treatment). Global MHT use was 8%: largely in HIC (15.2%) vs LMIC (0%) P=0.009: and within the well-educated (67%) vs those with high household incomes (37%) P=0.004. Conclusions : In this small study, HIC-residence woman undergoes Menopause 26.4 months ahead of her LMIC-counterpart. There is a knowledge and treatment-deficit with associated disease morbidity. This highlights the need for tailored health-awareness programmes supported by timely-treatment given possible cardio-protection benefits. Endocrinology & Metabolism Domicile Hypertension LMICs Menopause Sub-Saharan Residence Introduction There is limited awareness of the wide range of menopausal symptoms in the sub-Saharan African woman in the low- to medium income country (LMIC) as compared to High income countries (HIC) due to the socio-cultural construct of Menopause being natural and a rite of passage to elevated social role changes. Menopause is the complete cessation of menstrual periods: defined as 12 consecutive months of amenorrhea for which there is no other obvious pathological or physiological cause, a diagnosis made in retrospect. The Perimenopause is the period before the menopause and the 1st year after the menopause¹. This is a transition period which may be uneventful for as many as 20% of women; but could result in one or more troubling symptoms with varying severity. The commonest menopause symptoms are the vasomotor symptoms followed by sexual symptoms – lack of desire/ arousal/ lubrication following genitourinary symptoms; sleep disorders, mood disturbances- (mood lability swings/ anxiety/ depression) and musculoskeletal symptoms². There is research paucity as to the prevalence and distribution of these symptoms amongst SSA women: and much less on the possible impact of different residences/ domiciles. Limited data have been incidental findings indicating a variable prevalence, noted during large population studies on Human Immunodeficiency virus (HIV) research largely in the South and Southeastern areas of Africa. As HIV alters the menopause experience, these findings may not be totally representative³ alongside other confounders such as prevailing national health systems and climatic variations. There are few studies within the West African setting, with fewer Nigerian studies reflecting a wide variation of Menopause age from 49yrs to 57yrs depending on geographical location⁴ˉ⁵. Currently, a lot of available data, has been extrapolated from studies on African American women which may not be entirely representative due to differences in geographical location, health awareness, sunlight exposure, variable systemic health inequity and social deprivation, systemic geopolitical and individual barriers to medication use, dietary and exercise regimes. Systemic barriers Over 80% of African nations fall within the LMIC category⁶ often characterised by an inadequate healthcare sector, poor infrastructure, few healthcare personnel and lack of affordable drugs within inadequate health programs: all products of limited budgetary expenditure. Access to menopause care is complicated by limited understanding of the perimenopause by both healthcare professionals and women alike, a dismissive attitude to symptoms given the sociocultural construct -that assumes it is a western disease- underpinned by economic factors⁷. These factors cause delays in identification and subsequent management, and are not helped by the prevailing poor literacy, life experiences, financial constraints, healthcare accessibility constraints reinforcing a heavy reliance on traditional knowledge and community wisdom. With a limited life expectancy and a focus on other chronic diseases with significant mortality or morbidity alongside health concerns arising from social deprivation and other parameters of poverty and health inequality such as maternal and infant mortality, menopause symptoms are often ignored and left to fester in the background. However, it is difficult to lay it all on culture and health inequality as a similar pattern of reduced access and treatment has been observed in the HIC setting study which examined some General practitioner surgeries in the United Kingdom, identifying literacy, poor communication, social deprivation and cultural bias, as the distinct confounders⁸ˉ⁹. Symptom presentation Vasomotor symptoms can sometimes be mistaken as climate/ weather effects in tropical countries: and are often ignored or tolerated. Genitourinary symptoms can present with vaginal symptoms and psychosexual sequelae which are often difficult to manage, given confounders such as relationship difficulties and background social construct. As marital relations are sometimes not in the forefront in this age group particularly in the LMIC setting, with most women having completed childbearing, any genitourinary symptoms or sexual symptoms and associated marital disharmony are either not recognised or not considered a major concern⁴ˉ⁵. In the event of distressing symptomatology, the prevalent cultural or religious bias sometimes leads to or creates embarrassment when seeking help, resulting in a desire to avoid or reluctantly engage with formal healthcare provision. This with community wisdom leads to an observed reliance on herbs and exercise, limiting a drive for formal treatment¹º. Materials and methods This electronic cross-sectional community study survey with a qualitative arm was administered securely in June 2024 over a 6-week period, following stakeholder questionnaire validation, to women of West, East and Southern African origin over the age of 40yrs who had reached menopause. Recruitment was via several sources which include social media, family and friends, word of mouth and clinical networks. Primary objective was to identify age of menopause with population characteristics, knowledge of menopausal symptoms and associated cultural nuances. The secondary objectives assessed symptom prevalence and quality of life impact alongside knowledge and treatment gap specific to domiciles. Inclusion criteria included age over 40 yrs, self-reported last menstrual period occurring over 12 months ago or biochemically proven menopause-state. Individual data correlated with device IP details inclusive, were reviewed for repetitions and presence of exclusion criteria. The use of repeat focused open questions helped to limit missing data. After an in-depth focus group + community engagement through semi-structured interviews to identify culturally sensitive tools and words, an online peer-reviewed e-survey was created and administered following introductory email links. Implied consent was obtained with anonymised data in line with the principles outlined in the Declaration of Helsinki regarding research ethics involving human subjects. No formal board review was obtained as this survey was primarily carried out to identify baseline data and deficits preceding a Menopause society service provision roll-out. An iterative approach was utilised with concurrent data analysis following data collection which included free texting with in-depth telephone interviews that fed into the qualitative arm, to further explore some of the nuances. A thematic data analysis with methodical triangulation was performed Individual data included general demographics- current age, age of menopause, past medical and surgical histories, country of and time of presence in current residence. Domiciles were differentiated into LMIC or HIC, using the World bank data. Following preliminary data analysis through Microsoft Excel, a multivariate logistic regression with MedCalc© and further analysis by Anthropic©, was performed. Results 124 women responded to the survey with 30% dropping out. Of the 88 that completed the survey, 87 met the inclusion criteria. Demographics The LMIC cohort were predominantly domiciled in West Africa-( mostly Nigeria; 3 responders from Southeast Africa) made up 47.6% of the responders whilst the HIC cohort were 1 st generation migrants who relocated to current domiciles, 5-30 years ago, largely in North America, and Europe, a respondent in the Middle East and Australia each. An average menopause age of 47.59years ± 4.56 in the HIC setting: 49.78yrs ±3.26 in the LMIC setting was observed. The LMIC cohort reached menopause 26.4 months later than their HIC cohorts with a higher number of women with early menopause in the HIC cohort (6 vs 3): a possible contributory factor. Menopause had occurred in the premature menopause HIC cohort shortly after migration as determined by their responses of achieving menopause mostly within 5-8 years of migration, an average of 6.8 yrs ± 3.4 yrs, raising the question of a subtle acquired migration-related health morbidity from inherent increased stressors resulting in significant accelerated nativity advantage erosion as no co-existing medical pathologies were reported. LMIC cohort had more children (2.76 vs 2.4) and were unlikely to report symptoms as compared to their HIC counterparts, largely due to poor symptom awareness, variable symptom impact given their use of over-the-counter medication, dietary changes and some herbal remedies. HIC cohort had more knowledge of cultural or alternative menopause therapies (21.7% vs 12.2%); defined menopause appropriately, though largely based on symptoms: a reflection of the widely available information on menopause: increasing the risk of medicalising a natural phenomenon. See table 1. For statistically significant associations Though both cohorts had similar job profiles mostly professional jobs (80%), with a minimum of university-level educational attainment: LMIC's yearly household mean income was equivalent to 33% of their HIC counterparts. This in addition to larger households as 81% of LMIC vs 65% HIC had a >3person-household, in a fee-based healthcare system; led to comparatively reduced purchasing power; with a preference for alternative treatment strategies such as herbs, over-the-counter medication, as provided in the thematic analysis of qualitative arm feedback. This was also complicated by lack of healthcare access or medication availability within the LMIC cohort. However, HIC cohort did not engage with MHT use due to several factors: lack of symptom recognition, poor healthcare-seeking behaviours, concerns over poor symptom control, MHT side effects and treatment and investigation-related morbidity, impact of MHT on fibroids and cancer risk. This might explain why MHT was used only by 7, all HIC women: whilst 75% of those within the HIC cohort who reported significant symptom-severity, were not on hormone therapy. In addition to the disease morbidity, antihypertensive medication use was reported in 15.2% of HIC vs 21.4% in the LMIC cohort, raising the concern about missed cardio-protection opportunities. Symptomatology: Symptom reporting: Missed opportunities with symptom-recognition discordance was seen in ~80% globally, worse in the LMIC cohort. Only 15.8% (LMIC) versus 25%(HIC) of those who previously self-reported no symptoms, had no symptoms. In the symptomatic group within the HIC cohort, there was equal prevalence of Vasomotor symptoms (58%) and Genitourinary symptoms (58%) as their most frequent symptoms with a QOL impact/ severity scale of 1-2 suggesting occasional-mild impact in 75%. This may explain why there were no initial self-reported symptoms prior to going through specific symptom questionnaire section in the survey. In the LMIC cohort, 15.8% of those who reported no symptoms were confirmed symptom-less: in the 84.2% symptomatic women, the frequently occurring symptoms were genitourinary symptoms (58%) with accompanying psychosexual impact, vasomotor symptoms (42%), mood lability (37%) and insomnia (21%). Here, the QOL impact was significant, with significant- moderate impact in 16%: occasional-mild impact in 68%, suggesting more women in the LMIC cohort suffered some degree of harm from poor symptom recognition. Symptom severity scale was determined by a 6 point-Likert scale with significant impact tagged at 3 and above. Globally 15 women reported varying symptoms with a significant -moderate QOL impact. In the HIC cohort, the most common symptom were genitourinary problems (87.5%) vasomotor (50%) Memory problems (50%) and labile moods (50%). Genitourinary symptoms (100%) were the most common, followed by vasomotor symptoms (71.4%) and insomnia (42.8%) in the LMIC cohort. Following the use of repeated question re-phrase, 6.9% (6/87) reported no symptoms consistently. Thematic analysis of Qualitative survey findings 1 — Structural and Environmental Determinants of Health Subtheme 1.1 : Geographical Factors and Biological Implications Respondents highlighted the role of sunlight exposure as a differentiating health factor between LMICs and HICs. Limited sunlight in non-tropical HICs was believed to contribute to vitamin D insufficiency, which some respondents linked to more severe menopause symptoms. Meaning: - Environmental context shapes biological vulnerability and symptom perception. Subtheme 1.2 : Food Quality and Environmental Health Benefits LMIC environments were perceived to provide easier access to fresh, organic, unprocessed foods, whereas food systems in HICs were viewed as more processed, expensive, and less nutritious. Meaning: - Environmental resources indirectly influence metabolic health, symptom burden, and perceptions of wellbeing. 2 — Socioeconomic Inequity and Stressors Subtheme 2.1: Social Deprivation Among First-Generation Immigrants Respondents consistently linked immigration to financial strain, stress, reduced disposable income, and housing and healthcare inequities. This was connected to a loss of nativity advantage, mirroring findings from studies like SWAN. Meaning: - Migration-related stress erodes protective factors, increasing vulnerability during midlife and menopause. Subtheme 2.2: Financial and Family Burden (“Black Tax”) Ethnic minority women in HICs described heavy familial responsibilities, financial obligations to extended families, and pressure to “provide,” all of which intensified stress. Meaning: - Economic and cultural expectations intersect with health access and stress-induced symptom worsening. 3 — Health System Inequities and Poor Menopause Literacy Subtheme 3.1: Limited Access and Disparate Treatment Experiences Ethnic minority women, particularly migrants, described unequal access to treatment, under-recognition of symptoms, and poorer clinical engagement. Meaning: -Systemic bias and unequal access amplify disease burden. Subtheme 3.2: Pandemic as a Revealer of Inequities COVID-19 was repeatedly cited as a time where ethnic minority groups experienced disproportionate morbidity and mortality due to chronic disease burdens, social deprivation, and delayed healthcare access. Meaning: - Crises magnify structural inequalities that already affect menopausal health. Subtheme 3.3: Persisting Low Menopause Literacy Despite policies and awareness campaigns, respondents noted poor menopause literacy among both patients and healthcare professionals in HICs. Meaning: -Knowledge gaps impede informed decision-making and worsen underdiagnosis and undertreatment. 4 — Cultural Norms, Gender Roles, and Health Beliefs Subtheme 4.1: Stigma and Ideologies Around Weight and “Good Living” In some LMIC contexts, weight gain is viewed as culturally desirable, symbolising prosperity and protection from menopause symptoms. This obscures recognition of associated risks such as hypertension. Meaning: - Cultural beliefs shape symptom interpretation and delay health-seeking behaviour. Subtheme 4.2: Menopause Normalisation and Symptom Endurance Menopause was often regarded as a natural, brief transition requiring endurance rather than treatment. Meaning: - Sociocultural norms minimise women’s discomfort and discourage healthcare utilisation. Subtheme 4.3: Sexual Health Stigma and Dissociation from the Genital Tract Women described low awareness and recognition of vaginal atrophy, dyspareunia, and genitourinary syndrome of menopause. Post-childbearing, many reported psychological dissociation from the genital area or discomfort discussing symptoms. Relationship dissatisfaction and concerns about partner infidelity further complicated this domain. Meaning: -Sociocultural silence around sexuality hinders early recognition of menopausal genitourinary conditions. 5 — Limited and Fear-Based Use of Treatments Subtheme 5.1: Reluctance to Use Menopausal Hormone Therapy or Herbal Therapies Respondents reported poor MHT or herbal treatment uptake due to the following factors which include fear of side effects, uncertainty around dosage, insufficient information about risks/benefits, concerns about worsening conditions like fibroids, influence of prior sensationalised media coverage. Meaning: - Mistrust, misinformation, and diagnostic uncertainty result in low engagement with treatment options. Sub-theme 5.2: Mitigating bleeding side effects Respondents reported poor accessibility to diagnostic and treatment modalities in the event of Breakthrough bleeding whilst on MHT, especially with women with fibroids. Meaning: - poor accessibility or affordability of diagnostic or treatment modalities is a recognised barrier to MHT use. Once synthesized, the 4 overarching themes are: 1. Intersection of Environment, Migration, and Inequality: Geographic environments and socioeconomic disruptions (migration stress, poverty, systemic inequality) collectively shape menopausal experience. 2. Cultural Silence and Gendered Expectations: Norms around stoicism, weight, and sexuality reinforce underdiagnosis and limited support. 3. Healthcare System Gaps and Misinformation: Poor menopause literacy, treatment fears, and accessibility barriers hinder effective care. 4. Psychosocial Stress as a Mediator of Symptom Severity: Chronic stress—economic, relational, or cultural—emerges as a cross-cutting factor influencing symptom perception and severity. Discussion This is the 1st study identifying differences in Menopause experience, symptom awareness and treatment in sub-Saharan women of similar ethnicities located in different residences /domiciles. Demographics The HIC women were largely 1st generation immigrants located in their current domiciles for an average of 15 years with a range of 5–30 years. It is recognised that black American women (with African ancestry) reach Menopause at 49yrs¹¹ ˉ ¹², undergoing the menopause transition earlier, and longer than her Caucasian counterpart. Due to research paucity, there are few African studies demonstrating significant variation, with women in SW Nigeria reaching menopause at age 57yrs⁴ as compared to 49yrs seen in SE Nigeria⁵. The statistically significant difference in age of menopause across domiciles is thought to be due to a higher number of women with early menopause in the HIC cohort with no other observed contributory significant pathology. Thematic analysis suggests a subtle acquired-migration-related health morbidity with accelerated nativity advantage erosion which had been previously identified in different South American cohorts residing in the United States by the Swan study¹¹, may have facilitated an earlier menopause transition. Qualitative data suggests the Menopause change occurred a few years after completion of their immigration journeys. These time periods were described as eventful with significant stressors such as temporary relative social deprivation whilst actively seeking better job opportunities, professional examination huddle stresses, childcare stress with no readily available family support alongside financial stresses from family expectations aka black tax. These factors align with findings noted by Bromberger et al.¹³ Menopause knowledge was quite high in both cohorts, a reflection of their high educational status and environmental awareness, specific to the HIC cohort as HIC governments are increasingly raising Menopause and midlife health awareness with appropriate treatment, to tackle endemic systemic inequalities associated with HRT management as highlighted by a 2020 study by Hillman et al⁸ which had identified a large unmet need in terms of menopause care in areas of deprivation. Awareness of Cultural nuances – alternative treatment interventions, was higher in HIC as compared to LMIC; and nuances were found to be like practices described by Rasweswe and Mulaudzi¹º with dietary changes being the most common treatment alternative, followed by herbs, exercise and weight gain. Symptom definition and perception Though the 79% of the LMIC cohort defined menopause appropriately, with definition by symptomatology comparatively less, as compared to the HIC cohort (26% vs 72%): a reflection of the increasing health awareness programmes and policy changes within HIC settings which runs the risk of medicalising a natural phenomenon in the asymptomatic women, creating undue health anxiety. This knowledge gap was also evident as there was poor symptom self-recognition and reporting in 46.3% (LMIC) vs 26.1% (HIC). The difference in symptom awareness and impact with corresponding treatment deficit, as detailed above, may be additionally environmentally modulated with ethnocultural influence¹⁴. Though menopause age was earlier in the HIC setting as compared to LMIC domiciled women, an observation not in keeping with previous studies, similar trends in differences in symptomatology, health-seeking behaviours as reported over 4 countries in a previous study (DAMES) and society tool kit were observed¹⁴ˉ¹⁵. Acculturation which has been described but effects difficult to predict, as it’s a result of many factors, previously identified by the SWAN study¹¹, played a role here. It is noted that GUS is more prevalent than vasomotor symptoms in the LMIC cohort sometimes presenting with mild to moderate psychosexual morbidity. This may be due to a higher prevalence of younger women, higher educational attainment with high professional/skilled job in the cohort; demographics which are not representative of the average Subsaharan woman with 38% completing lower secondary school education¹⁶. Treatment acceptability/ availability was low in this study, like an observation in the SWAN study regarding black women. Poor acceptability was thought to be due to poor symptom control from MHT particularly Selective Serotonin Reuptake Inhibitors (SSRIs). Addressing these concerns, will facilitate an uptake on MHT particularly for those with severe symptoms. The concern about treatment interactions with fibroids raised in the qualitative arm is noted. Particularly if there are no medical facilities to optimally investigate and treat breakthrough bleeding whilst on MHT. Cardiometabolic risks There is a reported rising prevalence of high blood pressure in the background African population, currently at 20–48% dependent on geographical location, age and other factors, with a significant mortality of 300–600 deaths per 100,000 population: contributing significantly to two-thirds of the worldwide cardiovascular deaths occurring in LMIC settings ¹⁷ˉ²º. As multiple studies have identified increased cardiovascular mortality with development of type 2 diabetes, in women who reached Menopause < 45yrs the beneficial role of commencing MHT use within 10 years of menopause or below the age of 60yrs, should be considered ²¹ˉ²². whilst sleep equity should be formally facilitated given links between insomnia and Hypertension²³. The qualitative data reveal a complex interplay of environmental, socioeconomic, structural, and cultural factors shaping menopausal experiences among ethnic minority women across LMIC and HIC contexts, most of which have been discussed earlier: and highlights the need for intersectional, culturally competent, and structurally informed healthcare policies and menopause support pathways Limitations This was a small cross-sectional snapshot study, with a possible reduced power, presenting self-reported awareness/ knowledge, symptoms and treatment. The results should be interpreted cautiously due to a potential strong non-response selection bias as the respondents were largely well educated, with higher digital literacy and household income earnings in addition to relatively higher purchasing power. Though the findings here may not be representative of the average Sub-Saharan woman, the observed correlations of MHT use with high educational attainment is in keeping with current evidence. Other correlations which might have occurred by chance, still needs further exploration. Conclusion There is a domiciliary impact on menopause symptom prevalence, recognition and severity, with a significant knowledge-gap and treatment-deficit regardless of financial status in the SSA woman, worse in the LMIC setting. Postgraduate education reduces the deficit globally. There is an observed earlier age of menopause in the HIC cohort which requires further scrutiny. The significant symptom severity and prevalence of hypertensive diseases in these women alongside the qualitative data synthesis highlight the need for increasing awareness and treatment. An area that needs more research. Declarations No funding to declare Disclosure of conflicts of interest The authors have no disclosures to make Acknowledgements We wish to express our gratitude to the following people for their help: questionnaire validation steering group, facilitating with active iterative feedback and thematic analysis, and increasing visibility namely: Adetutu Ogunsanwo, Bimpe Ige, Taiwo Ogunba, Kofoworola Sanni-Sule, Foka Ngam, Halima Aliyu, Daniel Alli. Lauren Ashley Djissi and Amonia Gasper and Tonye Wokoma. References Utian WH (1999) The International Menopause menopause-related terminology definitions. Climacteric 2(4):284–286 Santoro N, Epperson CN, Mathews SB (2015) Menopausal symptoms and their management. 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Menopause 14(4):788–797 Tables Table 1 HIC (46) LMIC(41) comments General Demographics Menopause age (yrs)(nos) 47.59 ± 4.6 (46) 49.78 ± 3.3 (41) SE = 0.861 P = 0.013 Country distribution Europe/ North America West, South East Africa Educational level >/= university 67.4% 57.1% 62.5%- HRT use P = 0.325 Parity 2.4 2.76 Household size>/=3 65% 81% P = 0.097 95%CI (-2.86% to33.09%) Knowledge Definition: 1.Actual 2.Symptom-related 85% 13% 72% 79% 43% 26% P = 0.486 P = 0.001 P = 0.0001 Cultural practice Awareness Cultural practice awareness % (nos) Diet Herbs Exercise Weight gain 21.7% ( 10 ) 60% 40% 10% 10% 12.2% ( 5 ) 60% 40% -- -- P = 0.244 Symptoms Symptom prevalence (2ry survey) 43 (93.5%) 38 (92.7%) Initial symptom report 34 22 31 initially reported no symptoms HIC:12 LMIC:19 Reporting discordance symptom reporting discordance deficit 43 vs 34 26.1% 9 (19.5%) 38 vs 22 46.3% 16(39.02%) P = 0.045 95%CI (0.45%-37.18%) Symptom severity (QOL impact) > 3 no/(%) HRT use 8 (17.4%) 25% 7(17%) 0% Global HRT use HRT use HIC VS LMIC 15.2% 0% P = 0.009 95%CI (3.72%-28.2%) Co-morbidities Hypertension prevalence 15.2%/46 21.4%/41 P = 0.456 95%CI (-10.1% to 22.76%) Other factors High educational attainment -University-level and higher High earnings >£50,000 equivalent annual household income HRT use Educational vs high earnings 0.625 (67%) 0.304 (37%) P = 0.004; 95%CI (10.01% to 47.59%) Table 2 SUMMARY TABLE (Themes + Representative content) Theme Description Illustrative Respondent Ideas Geographical & Environmental Factors Climate and environment influence biological wellbeing (e.g., vitamin D, food quality). “Readily available sunlight in LMICs may reduce symptom severity.” / “Processed foods in HICs worsen metabolic health.” Immigration, Deprivation & Stress Migrants face reduced income, discrimination, and health inequities. “Nativity advantage declines after migration.” / “Financial pressures increase stress.” Health System Inequalities Minority women report poorer access and care quality. “Ethnic minorities in the UK received less menopause support.” / “COVID highlighted chronic inequities.” Menopause Literacy Gaps Low awareness among patients and clinicians hinders care. “Even with policies, menopause literacy was poor.” Cultural Norms & Sociocultural Roles Cultural beliefs shape symptom expectations and responses. “Weight gain is seen as protective.” / “Menopause is something to endure.” Sexual Health Silence & Stigma Vaginal atrophy and sexual symptoms under-recognised due to cultural taboos. “Women disengaged from genital health after childbirth.”/ “no need for sexual activity after childbirth completion or after menopause” Fear of MHT & Alternative Treatments Mistrust driven by side-effect fears, media, and misinformation. “Concerns over fibroid growth and sensationalised press reduce uptake.”/ “no readily available/ affordable highly sensitive diagnostic test in women with fibroids” Additional Declarations The authors declare no competing interests. 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Adedipe","email":"data:image/png;base64,iVBORw0KGgoAAAANSUhEUgAAAZAAAAAyAQMAAABI0h/eAAAABlBMVEX///8AAABVwtN+AAAACXBIWXMAAA7EAAAOxAGVKw4bAAAAz0lEQVRIiWNgGAWjYBACAxDxgIGZgR/ESCggVksCUItkA4hhQIoWgwNwLgFgLpH+8EFCjbWc8fnViR8eGDDI84sdwK/FckaOsUHCsXRjsxtvN0sAHWY4c3YCAYfdyGGTSGA7nLjtxtkNIC0JBrcJakl/JpHw73D95hlnN/8gUkuCmURi2+EEA/7ebcTZYtnzxtggsS/dcMYN3m0WCQYShP1izg4MsQ/frOX5+89uvvmjwkaeX5qAFgSQAKuUIFY5CPAfIEX1KBgFo2AUjCQAAO81RdmQVExnAAAAAElFTkSuQmCC","orcid":"","institution":"Hull Royal Infirmary, UK","correspondingAuthor":true,"prefix":"","firstName":"Tolu","middleName":"O.","lastName":"Adedipe","suffix":""},{"id":552817698,"identity":"32900bab-4dfb-47c1-8464-f316f604bea1","order_by":1,"name":"Joseph S. Hundeyin","email":"","orcid":"","institution":"Hull Royal Infirmary, UK","correspondingAuthor":false,"prefix":"","firstName":"Joseph","middleName":"S.","lastName":"Hundeyin","suffix":""},{"id":552817699,"identity":"861ac982-79ad-473b-8e0a-c81eea83919d","order_by":2,"name":"Olu A. 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The Perimenopause is the period before the menopause and the 1st year after the menopause\u0026sup1;.\u003c/p\u003e\u003cp\u003eThis is a transition period which may be uneventful for as many as 20% of women; but could result in one or more troubling symptoms with varying severity.\u003c/p\u003e\u003cp\u003eThe commonest menopause symptoms are the vasomotor symptoms followed by sexual symptoms \u0026ndash; lack of desire/ arousal/ lubrication following genitourinary symptoms; sleep disorders, mood disturbances- (mood lability swings/ anxiety/ depression) and musculoskeletal symptoms\u0026sup2;.\u003c/p\u003e\u003cp\u003eThere is research paucity as to the prevalence and distribution of these symptoms amongst SSA women: and much less on the possible impact of different residences/ domiciles.\u003c/p\u003e\u003cp\u003eLimited data have been incidental findings indicating a variable prevalence, noted during large population studies on Human Immunodeficiency virus (HIV) research largely in the South and Southeastern areas of Africa. As HIV alters the menopause experience, these findings may not be totally representative\u0026sup3; alongside other confounders such as prevailing national health systems and climatic variations. There are few studies within the West African setting, with fewer Nigerian studies reflecting a wide variation of Menopause age from 49yrs to 57yrs depending on geographical location⁴ˉ⁵.\u003c/p\u003e\u003cp\u003eCurrently, a lot of available data, has been extrapolated from studies on African American women which may not be entirely representative due to differences in geographical location, health awareness, sunlight exposure, variable systemic health inequity and social deprivation, systemic geopolitical and individual barriers to medication use, dietary and exercise regimes.\u003c/p\u003e\u003cp\u003eSystemic barriers\u003c/p\u003e\u003cp\u003eOver 80% of African nations fall within the LMIC category⁶ often characterised by an inadequate healthcare sector, poor infrastructure, few healthcare personnel and lack of affordable drugs within inadequate health programs: all products of limited budgetary expenditure.\u003c/p\u003e\u003cp\u003eAccess to menopause care is complicated by limited understanding of the perimenopause by both healthcare professionals and women alike, a dismissive attitude to symptoms given the sociocultural construct -that assumes it is a western disease- underpinned by economic factors⁷. These factors cause delays in identification and subsequent management, and are not helped by the prevailing poor literacy, life experiences, financial constraints, healthcare accessibility constraints reinforcing a heavy reliance on traditional knowledge and community wisdom.\u003c/p\u003e\u003cp\u003eWith a limited life expectancy and a focus on other chronic diseases with significant mortality or morbidity alongside health concerns arising from social deprivation and other parameters of poverty and health inequality such as maternal and infant mortality, menopause symptoms are often ignored and left to fester in the background.\u003c/p\u003e\u003cp\u003eHowever, it is difficult to lay it all on culture and health inequality as a similar pattern of reduced access and treatment has been observed in the HIC setting study which examined some General practitioner surgeries in the United Kingdom, identifying literacy, poor communication, social deprivation and cultural bias, as the distinct confounders⁸ˉ⁹.\u003c/p\u003e\u003cp\u003eSymptom presentation\u003c/p\u003e\u003cp\u003eVasomotor symptoms can sometimes be mistaken as climate/ weather effects in tropical countries: and are often ignored or tolerated. Genitourinary symptoms can present with vaginal symptoms and psychosexual sequelae which are often difficult to manage, given confounders such as relationship difficulties and background social construct. As marital relations are sometimes not in the forefront in this age group particularly in the LMIC setting, with most women having completed childbearing, any genitourinary symptoms or sexual symptoms and associated marital disharmony are either not recognised or not considered a major concern⁴ˉ⁵. In the event of distressing symptomatology, the prevalent cultural or religious bias sometimes leads to or creates embarrassment when seeking help, resulting in a desire to avoid or reluctantly engage with formal healthcare provision. This with community wisdom leads to an observed reliance on herbs and exercise, limiting a drive for formal treatment\u0026sup1;\u0026ordm;.\u003c/p\u003e"},{"header":"Materials and methods","content":"\u003cp\u003eThis electronic cross-sectional community study survey with a qualitative arm was administered securely in June 2024 over a 6-week period, following stakeholder questionnaire validation, to women of West, East and Southern African origin over the age of 40yrs who had reached menopause. Recruitment was via several sources which include social media, family and friends, word of mouth and clinical networks.\u003c/p\u003e\u003cp\u003ePrimary objective was to identify age of menopause with population characteristics, knowledge of menopausal symptoms and associated cultural nuances. The secondary objectives assessed symptom prevalence and quality of life impact alongside knowledge and treatment gap specific to domiciles.\u003c/p\u003e\u003cp\u003eInclusion criteria included age over 40 yrs, self-reported last menstrual period occurring over 12 months ago or biochemically proven menopause-state. Individual data correlated with device IP details inclusive, were reviewed for repetitions and presence of exclusion criteria. The use of repeat focused open questions helped to limit missing data.\u003c/p\u003e\u003cp\u003eAfter an in-depth focus group\u0026thinsp;+\u0026thinsp;community engagement through semi-structured interviews to identify culturally sensitive tools and words, an online peer-reviewed e-survey was created and administered following introductory email links. Implied consent was obtained with anonymised data in line with the principles outlined in the Declaration of Helsinki regarding research ethics involving human subjects. No formal board review was obtained as this survey was primarily carried out to identify baseline data and deficits preceding a Menopause society service provision roll-out.\u003c/p\u003e\u003cp\u003eAn iterative approach was utilised with concurrent data analysis following data collection which included free texting with in-depth telephone interviews that fed into the qualitative arm, to further explore some of the nuances. A thematic data analysis with methodical triangulation was performed\u003c/p\u003e\u003cp\u003eIndividual data included general demographics- current age, age of menopause, past medical and surgical histories, country of and time of presence in current residence. Domiciles were differentiated into LMIC or HIC, using the World bank data. Following preliminary data analysis through Microsoft Excel, a multivariate logistic regression with MedCalc\u0026copy; and further analysis by Anthropic\u0026copy;, was performed.\u003c/p\u003e"},{"header":"Results","content":"\u003cp\u003e124 women responded to the survey with 30% dropping out. Of the 88 that completed the survey, 87 met the inclusion criteria.\u003c/p\u003e\n\u003cp\u003eDemographics\u003c/p\u003e\n\u003cp\u003eThe LMIC cohort were predominantly domiciled in West Africa-( mostly Nigeria; 3 responders from Southeast Africa) made up 47.6% of the responders whilst the HIC cohort were 1\u003csup\u003est\u003c/sup\u003e generation migrants who relocated to current domiciles, 5-30 years ago, largely in North America, and Europe, a respondent in the Middle East and Australia each.\u0026nbsp;\u003c/p\u003e\n\u003cp\u003eAn average menopause age of 47.59years \u0026plusmn; 4.56 in the HIC setting: 49.78yrs \u0026plusmn;3.26 in the LMIC setting was observed. The LMIC cohort reached menopause 26.4 months later than their HIC cohorts with a higher number of women with early menopause in the HIC cohort (6 vs 3): a possible contributory factor.\u0026nbsp;\u003c/p\u003e\n\u003cp\u003eMenopause had occurred in the premature menopause HIC cohort shortly after migration as determined by their responses of achieving menopause mostly within 5-8 years of migration, an average of 6.8 yrs \u0026plusmn; 3.4 yrs, raising the question of a subtle acquired migration-related health morbidity from inherent increased stressors resulting in significant accelerated nativity advantage erosion as no co-existing medical pathologies were reported.\u003c/p\u003e\n\u003cp\u003eLMIC cohort had more children (2.76 vs 2.4) and were unlikely to report symptoms as compared to their HIC counterparts, largely due to poor symptom awareness, variable symptom impact given their use of over-the-counter medication, dietary changes and some herbal remedies.\u003c/p\u003e\n\u003cp\u003eHIC cohort had more knowledge of cultural or alternative menopause therapies (21.7% vs 12.2%); defined menopause appropriately, though largely based on symptoms: a reflection of the widely available information on menopause: increasing the risk of medicalising a natural phenomenon.\u003c/p\u003e\n\u003cp\u003e\u003cem\u003eSee table 1. For statistically significant associations\u0026nbsp;\u003c/em\u003e\u003c/p\u003e\n\u003cp\u003eThough both cohorts had similar job profiles mostly professional jobs (80%), with a minimum of university-level educational attainment: LMIC\u0026apos;s yearly household mean income was equivalent to 33% of their HIC counterparts. This in addition to larger households as 81% of LMIC vs 65% HIC had a \u0026gt;3person-household, in a fee-based healthcare system; led to comparatively reduced purchasing power; with a preference for alternative treatment strategies such as herbs, over-the-counter medication, as provided in the thematic analysis of qualitative arm feedback. This was also complicated by lack of healthcare access or medication availability within the LMIC cohort.\u0026nbsp;\u003c/p\u003e\n\u003cp\u003eHowever, HIC cohort did not engage with MHT use due to several factors: lack of symptom recognition, poor healthcare-seeking behaviours, concerns over poor symptom control, MHT side effects and treatment and investigation-related morbidity, impact of MHT on fibroids and cancer risk. This might explain why MHT was used only by 7, all HIC women: whilst 75% of those within the HIC cohort who reported significant symptom-severity, were not on hormone therapy.\u0026nbsp;\u003c/p\u003e\n\u003cp\u003eIn addition to the disease morbidity, antihypertensive medication use was reported in 15.2% of HIC vs 21.4% in the LMIC cohort, raising the concern about missed cardio-protection opportunities.\u0026nbsp;\u003c/p\u003e\n\u003cp\u003eSymptomatology:\u003c/p\u003e\n\u003cp\u003eSymptom reporting:\u003c/p\u003e\n\u003cp\u003eMissed opportunities with symptom-recognition discordance was seen in ~80% globally, worse in the LMIC cohort. Only 15.8% (LMIC) versus 25%(HIC) of those who previously self-reported no symptoms, had no symptoms.\u0026nbsp;\u003c/p\u003e\n\u003cp\u003eIn the symptomatic group within the HIC cohort, there was equal prevalence of Vasomotor symptoms (58%) and Genitourinary symptoms (58%) as their most frequent symptoms with a QOL impact/ severity scale of 1-2 suggesting occasional-mild impact in 75%. This may explain why there were no initial self-reported symptoms prior to going through specific symptom questionnaire section in the survey.\u003c/p\u003e\n\u003cp\u003eIn the LMIC cohort, 15.8% of those who reported no symptoms were confirmed symptom-less: in the 84.2% symptomatic women, the frequently occurring symptoms were genitourinary symptoms (58%) with accompanying psychosexual impact, vasomotor symptoms (42%), mood lability (37%) and insomnia (21%). Here, the QOL impact was significant, with significant- moderate impact in 16%: occasional-mild impact in 68%, suggesting more women in the LMIC cohort suffered some degree of harm from poor symptom recognition.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eSymptom severity scale\u003c/strong\u003e was determined by a 6 point-Likert scale with significant impact tagged at 3 and above.\u003c/p\u003e\n\u003cp\u003eGlobally 15 women reported varying symptoms with a significant -moderate QOL impact. In the HIC cohort, the most common symptom were genitourinary problems (87.5%) vasomotor (50%) Memory problems (50%) and labile moods (50%). Genitourinary symptoms (100%) were the most common, followed by vasomotor symptoms (71.4%) and insomnia (42.8%) in the LMIC cohort.\u003c/p\u003e\n\u003cp\u003eFollowing the use of repeated question re-phrase, 6.9% (6/87) reported no symptoms consistently.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eThematic analysis of Qualitative survey findings\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003e1 \u0026mdash; Structural and Environmental Determinants of Health\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003e\u003cem\u003eSubtheme 1.1\u003c/em\u003e: Geographical Factors and Biological Implications\u003c/p\u003e\n\u003cp\u003eRespondents highlighted the role of sunlight exposure as a differentiating health factor between LMICs and HICs. Limited sunlight in non-tropical HICs was believed to contribute to vitamin D insufficiency, which some respondents linked to more severe menopause symptoms.\u003c/p\u003e\n\u003cp\u003eMeaning: - Environmental context shapes biological vulnerability and symptom perception.\u003c/p\u003e\n\u003cp\u003e\u003cem\u003eSubtheme 1.2\u003c/em\u003e: Food Quality and Environmental Health Benefits\u003c/p\u003e\n\u003cp\u003eLMIC environments were perceived to provide easier access to fresh, organic, unprocessed foods, whereas food systems in HICs were viewed as more processed, expensive, and less nutritious.\u003c/p\u003e\n\u003cp\u003eMeaning: - Environmental resources indirectly influence metabolic health, symptom burden, and perceptions of wellbeing.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003e2 \u0026mdash; Socioeconomic Inequity and Stressors\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003e\u003cem\u003eSubtheme 2.1:\u003c/em\u003e Social Deprivation Among First-Generation Immigrants\u003c/p\u003e\n\u003cp\u003eRespondents consistently linked immigration to financial strain, stress, reduced disposable income, and housing and healthcare inequities. This was connected to a loss of nativity advantage, mirroring findings from studies like SWAN.\u003c/p\u003e\n\u003cp\u003eMeaning: - Migration-related stress erodes protective factors, increasing vulnerability during midlife and menopause.\u003c/p\u003e\n\u003cp\u003e\u003cem\u003eSubtheme 2.2:\u003c/em\u003e Financial and Family Burden (\u0026ldquo;Black Tax\u0026rdquo;)\u003c/p\u003e\n\u003cp\u003eEthnic minority women in HICs described heavy familial responsibilities, financial obligations to extended families, and pressure to \u0026ldquo;provide,\u0026rdquo; all of which intensified stress.\u003c/p\u003e\n\u003cp\u003eMeaning: - Economic and cultural expectations intersect with health access and stress-induced symptom worsening.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003e3 \u0026mdash; Health System Inequities and Poor Menopause Literacy\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003e\u003cem\u003eSubtheme 3.1: Limited Access and Disparate Treatment Experiences\u003c/em\u003e\u003c/p\u003e\n\u003cp\u003eEthnic minority women, particularly migrants, described unequal access to treatment, under-recognition of symptoms, and poorer clinical engagement.\u0026nbsp;\u003c/p\u003e\n\u003cp\u003eMeaning: -Systemic bias and unequal access amplify disease burden.\u003c/p\u003e\n\u003cp\u003e\u003cem\u003eSubtheme 3.2: Pandemic as a Revealer of Inequities\u003c/em\u003e\u003c/p\u003e\n\u003cp\u003eCOVID-19 was repeatedly cited as a time where ethnic minority groups experienced disproportionate morbidity and mortality due to chronic disease burdens, social deprivation, and delayed healthcare access.\u003c/p\u003e\n\u003cp\u003eMeaning: - Crises magnify structural inequalities that already affect menopausal health.\u003c/p\u003e\n\u003cp\u003e\u003cem\u003eSubtheme 3.3: Persisting Low Menopause Literacy\u003c/em\u003e\u003c/p\u003e\n\u003cp\u003eDespite policies and awareness campaigns, respondents noted poor menopause literacy among both patients and healthcare professionals in HICs.\u003c/p\u003e\n\u003cp\u003eMeaning: -Knowledge gaps impede informed decision-making and worsen underdiagnosis and undertreatment.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003e4 \u0026mdash; Cultural Norms, Gender Roles, and Health Beliefs\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003e\u003cem\u003eSubtheme 4.1: Stigma and Ideologies Around Weight and \u0026ldquo;Good Living\u0026rdquo;\u003c/em\u003e\u003c/p\u003e\n\u003cp\u003eIn some LMIC contexts, weight gain is viewed as culturally desirable, symbolising prosperity and protection from menopause symptoms. This obscures recognition of associated risks such as hypertension.\u003c/p\u003e\n\u003cp\u003eMeaning: - Cultural beliefs shape symptom interpretation and delay health-seeking behaviour.\u003c/p\u003e\n\u003cp\u003e\u003cem\u003eSubtheme 4.2: Menopause Normalisation and Symptom Endurance\u003c/em\u003e\u003c/p\u003e\n\u003cp\u003eMenopause was often regarded as a natural, brief transition requiring endurance rather than treatment.\u003c/p\u003e\n\u003cp\u003eMeaning: - Sociocultural norms minimise women\u0026rsquo;s discomfort and discourage healthcare utilisation.\u003c/p\u003e\n\u003cp\u003e\u003cem\u003eSubtheme 4.3: Sexual Health Stigma and Dissociation from the Genital Tract\u003c/em\u003e\u003c/p\u003e\n\u003cp\u003eWomen described low awareness and recognition of vaginal atrophy, dyspareunia, and genitourinary syndrome of menopause. Post-childbearing, many reported psychological dissociation from the genital area or discomfort discussing symptoms.\u003c/p\u003e\n\u003cp\u003eRelationship dissatisfaction and concerns about partner infidelity further complicated this domain.\u003c/p\u003e\n\u003cp\u003eMeaning: -Sociocultural silence around sexuality hinders early recognition of menopausal genitourinary conditions.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003e5 \u0026mdash; Limited and Fear-Based Use of Treatments\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003e\u003cem\u003eSubtheme 5.1: Reluctance to Use Menopausal Hormone Therapy or Herbal Therapies\u003c/em\u003e\u003c/p\u003e\n\u003cp\u003eRespondents reported poor MHT or herbal treatment uptake due to the following factors which include fear of side effects, uncertainty around dosage, insufficient information about risks/benefits, concerns about worsening conditions like fibroids, influence of prior sensationalised media coverage.\u003c/p\u003e\n\u003cp\u003eMeaning: - Mistrust, misinformation, and diagnostic uncertainty result in low engagement with treatment options.\u003c/p\u003e\n\u003cp\u003e\u003cem\u003eSub-theme 5.2: Mitigating bleeding side effects\u003c/em\u003e\u003c/p\u003e\n\u003cp\u003eRespondents reported poor accessibility to diagnostic and treatment modalities in the event of Breakthrough bleeding whilst on MHT, especially with women with fibroids.\u003c/p\u003e\n\u003cp\u003eMeaning: \u0026nbsp;- poor accessibility or affordability of diagnostic or treatment modalities is a recognised barrier to MHT use.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eOnce synthesized, the 4 overarching themes are:\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003e1. Intersection of Environment, Migration, and Inequality: \u0026nbsp;Geographic environments and socioeconomic disruptions (migration stress, poverty, systemic inequality) collectively shape menopausal experience.\u003c/p\u003e\n\u003cp\u003e2. Cultural Silence and Gendered Expectations: Norms around stoicism, weight, and sexuality reinforce underdiagnosis and limited support.\u003c/p\u003e\n\u003cp\u003e3. Healthcare System Gaps and Misinformation: Poor menopause literacy, treatment fears, and accessibility barriers hinder effective care.\u003c/p\u003e\n\u003cp\u003e4. Psychosocial Stress as a Mediator of Symptom Severity: Chronic stress\u0026mdash;economic, relational, or cultural\u0026mdash;emerges as a cross-cutting factor influencing symptom perception and severity.\u003c/p\u003e"},{"header":"Discussion","content":"\u003cp\u003eThis is the 1st study identifying differences in Menopause experience, symptom awareness and treatment in sub-Saharan women of similar ethnicities located in different residences /domiciles.\u003c/p\u003e\u003cdiv id=\"Sec17\" class=\"Section2\"\u003e\u003ch2\u003eDemographics\u003c/h2\u003e\u003cp\u003eThe HIC women were largely 1st generation immigrants located in their current domiciles for an average of 15 years with a range of 5\u0026ndash;30 years. It is recognised that black American women (with African ancestry) reach Menopause at 49yrs\u0026sup1;\u0026sup1; ˉ \u0026sup1;\u0026sup2;, undergoing the menopause transition earlier, and longer than her Caucasian counterpart. Due to research paucity, there are few African studies demonstrating significant variation, with women in SW Nigeria reaching menopause at age 57yrs⁴ as compared to 49yrs seen in SE Nigeria⁵.\u003c/p\u003e\u003cp\u003eThe statistically significant difference in age of menopause across domiciles is thought to be due to a higher number of women with early menopause in the HIC cohort with no other observed contributory significant pathology. Thematic analysis suggests a subtle acquired-migration-related health morbidity with accelerated nativity advantage erosion which had been previously identified in different South American cohorts residing in the United States by the Swan study\u0026sup1;\u0026sup1;, may have facilitated an earlier menopause transition. Qualitative data suggests the Menopause change occurred a few years after completion of their immigration journeys. These time periods were described as eventful with significant stressors such as temporary relative social deprivation whilst actively seeking better job opportunities, professional examination huddle stresses, childcare stress with no readily available family support alongside financial stresses from family expectations aka black tax. These factors align with findings noted by Bromberger et al.\u0026sup1;\u0026sup3;\u003c/p\u003e\u003cp\u003eMenopause knowledge was quite high in both cohorts, a reflection of their high educational status and environmental awareness, specific to the HIC cohort as HIC governments are increasingly raising Menopause and midlife health awareness with appropriate treatment, to tackle endemic systemic inequalities associated with HRT management as highlighted by a 2020 study by Hillman et al⁸ which had identified a large unmet need in terms of menopause care in areas of deprivation.\u003c/p\u003e\u003cp\u003eAwareness of Cultural nuances \u0026ndash; alternative treatment interventions, was higher in HIC as compared to LMIC; and nuances were found to be like practices described by Rasweswe and Mulaudzi\u0026sup1;\u0026ordm; with dietary changes being the most common treatment alternative, followed by herbs, exercise and weight gain.\u003c/p\u003e\u003c/div\u003e\u003cdiv id=\"Sec18\" class=\"Section2\"\u003e\u003ch2\u003eSymptom definition and perception\u003c/h2\u003e\u003cp\u003eThough the 79% of the LMIC cohort defined menopause appropriately, with definition by symptomatology comparatively less, as compared to the HIC cohort (26% vs 72%): a reflection of the increasing health awareness programmes and policy changes within HIC settings which runs the risk of medicalising a natural phenomenon in the asymptomatic women, creating undue health anxiety. This knowledge gap was also evident as there was poor symptom self-recognition and reporting in 46.3% (LMIC) vs 26.1% (HIC).\u003c/p\u003e\u003cp\u003eThe difference in symptom awareness and impact with corresponding treatment deficit, as detailed above, may be additionally environmentally modulated with ethnocultural influence\u0026sup1;⁴.\u003c/p\u003e\u003cp\u003eThough menopause age was earlier in the HIC setting as compared to LMIC domiciled women, an observation not in keeping with previous studies, similar trends in differences in symptomatology, health-seeking behaviours as reported over 4 countries in a previous study (DAMES) and society tool kit were observed\u0026sup1;⁴ˉ\u0026sup1;⁵.\u003c/p\u003e\u003cp\u003eAcculturation which has been described but effects difficult to predict, as it\u0026rsquo;s a result of many factors, previously identified by the SWAN study\u0026sup1;\u0026sup1;, played a role here.\u003c/p\u003e\u003cp\u003eIt is noted that GUS is more prevalent than vasomotor symptoms in the LMIC cohort sometimes presenting with mild to moderate psychosexual morbidity. This may be due to a higher prevalence of younger women, higher educational attainment with high professional/skilled job in the cohort; demographics which are not representative of the average Subsaharan woman with 38% completing lower secondary school education\u0026sup1;⁶.\u003c/p\u003e\u003cp\u003eTreatment acceptability/ availability was low in this study, like an observation in the SWAN study regarding black women. Poor acceptability was thought to be due to poor symptom control from MHT particularly Selective Serotonin Reuptake Inhibitors (SSRIs). Addressing these concerns, will facilitate an uptake on MHT particularly for those with severe symptoms. The concern about treatment interactions with fibroids raised in the qualitative arm is noted. Particularly if there are no medical facilities to optimally investigate and treat breakthrough bleeding whilst on MHT.\u003c/p\u003e\u003c/div\u003e\u003cdiv id=\"Sec19\" class=\"Section2\"\u003e\u003ch2\u003eCardiometabolic risks\u003c/h2\u003e\u003cp\u003eThere is a reported rising prevalence of high blood pressure in the background African population, currently at 20\u0026ndash;48% dependent on geographical location, age and other factors, with a significant mortality of 300\u0026ndash;600 deaths per 100,000 population: contributing significantly to two-thirds of the worldwide cardiovascular deaths occurring in LMIC settings \u0026sup1;⁷ˉ\u0026sup2;\u0026ordm;. As multiple studies have identified increased cardiovascular mortality with development of type 2 diabetes, in women who reached Menopause\u0026thinsp;\u0026lt;\u0026thinsp;45yrs the beneficial role of commencing MHT use within 10 years of menopause or below the age of 60yrs, should be considered \u0026sup2;\u0026sup1;ˉ\u0026sup2;\u0026sup2;. whilst sleep equity should be formally facilitated given links between insomnia and Hypertension\u0026sup2;\u0026sup3;.\u003c/p\u003e\u003cp\u003eThe qualitative data reveal a complex interplay of environmental, socioeconomic, structural, and cultural factors shaping menopausal experiences among ethnic minority women across LMIC and HIC contexts, most of which have been discussed earlier: and highlights the need for intersectional, culturally competent, and structurally informed healthcare policies and menopause support pathways\u003c/p\u003e\u003c/div\u003e\u003cdiv id=\"Sec20\" class=\"Section2\"\u003e\u003ch2\u003eLimitations\u003c/h2\u003e\u003cp\u003eThis was a small cross-sectional snapshot study, with a possible reduced power, presenting self-reported awareness/ knowledge, symptoms and treatment. The results should be interpreted cautiously due to a potential strong non-response selection bias as the respondents were largely well educated, with higher digital literacy and household income earnings in addition to relatively higher purchasing power. Though the findings here may not be representative of the average Sub-Saharan woman, the observed correlations of MHT use with high educational attainment is in keeping with current evidence. Other correlations which might have occurred by chance, still needs further exploration.\u003c/p\u003e\u003c/div\u003e"},{"header":"Conclusion","content":"\u003cp\u003eThere is a domiciliary impact on menopause symptom prevalence, recognition and severity, with a significant knowledge-gap and treatment-deficit regardless of financial status in the SSA woman, worse in the LMIC setting. Postgraduate education reduces the deficit globally. There is an observed earlier age of menopause in the HIC cohort which requires further scrutiny. The significant symptom severity and prevalence of hypertensive diseases in these women alongside the qualitative data synthesis highlight the need for increasing awareness and treatment. An area that needs more research.\u003c/p\u003e"},{"header":"Declarations","content":"\u003cp\u003e\u003cstrong\u003eNo funding to declare\u003c/strong\u003e\u003c/p\u003e\n\u003ch2\u003eDisclosure of conflicts of interest\u003c/h2\u003e\u003cp\u003eThe authors have no disclosures to make\u003c/p\u003e\u003ch2\u003eAcknowledgements\u003c/h2\u003e\u003cp\u003eWe wish to express our gratitude to the following people for their help: questionnaire validation steering group, facilitating with active iterative feedback and thematic analysis, and increasing visibility namely: Adetutu Ogunsanwo, Bimpe Ige, Taiwo Ogunba, Kofoworola Sanni-Sule, Foka Ngam, Halima Aliyu, Daniel Alli. Lauren Ashley Djissi and Amonia Gasper and Tonye Wokoma.\u003c/p\u003e"},{"header":"References","content":"\u003col\u003e\u003cli\u003e\u003cspan\u003eUtian WH (1999) The International Menopause menopause-related terminology definitions. Climacteric 2(4):284\u0026ndash;286\u003c/span\u003e\u003c/li\u003e\u003cli\u003e\u003cspan\u003eSantoro N, Epperson CN, Mathews SB (2015) Menopausal symptoms and their management. Endocrinol Metabolism Clin 44(3):497\u0026ndash;515\u003c/span\u003e\u003c/li\u003e\u003cli\u003e\u003cspan\u003eVan Ommen CE, King EM, Murray MC (2021) Age at menopause in women living with HIV: a systematic review. Menopause 28(12):1428\u0026ndash;1436\u003c/span\u003e\u003c/li\u003e\u003cli\u003e\u003cspan\u003eAkindele RA, Omopariola SO, Adeyemo AT, Adeyemo AT, Afolabi BA, Folami EO, Omisakin AO, Bello NO (2023) Prevalence of Menopausal Symptoms in Osogbo, South-West, Nigeria. Niger J Med 32(2):155\u0026ndash;160\u003c/span\u003e\u003c/li\u003e\u003cli\u003e\u003cspan\u003eAgwu UM, Umeora OU, Ejikeme BN (2008) Patterns of menopausal symptoms and adaptive ability in a rural population in South-east Nigeria. J Obstet Gynaecol 28(2):217\u0026ndash;221\u003c/span\u003e\u003c/li\u003e\u003cli\u003e\u003cspan\u003ehttps://\u003cspan class=\"ExternalRef\"\u003e\u003cspan class=\"RefSource\"\u003edatahelpdesk.worldbank.org/knowledgebase/articles/906519-world-bank-country and-lending-groups\u003c/span\u003e\u003cspan address=\"http://datahelpdesk.worldbank.org/knowledgebase/articles/906519-world-bank-country and-lending-groups\" targettype=\"URL\" class=\"RefTarget\"\u003e\u003c/span\u003e\u003c/span\u003e accessed on 31/5/25\u003c/span\u003e\u003c/li\u003e\u003cli\u003e\u003cspan\u003eBaber RJ (2014) East is east and West is west: perspectives on the menopause in Asia and The West. Climacteric 17(1):23\u0026ndash;28\u003c/span\u003e\u003c/li\u003e\u003cli\u003e\u003cspan\u003eHillman S, Shantikumar S, Ridha A, Todkill D, Dale J (2020) Socioeconomic status and HRT prescribing: a study of practice-level data in England. Br J Gen Pract 70(700):e772\u0026ndash;e777\u003c/span\u003e\u003c/li\u003e\u003cli\u003e\u003cspan\u003eMacLellan J, Dixon S, Bi S, Toye F, McNiven A (2023) Perimenopause and/or menopause help-seeking among women from ethnic minorities: a qualitative study of primary care practitioners\u0026rsquo; experiences. Br J Gen Pract 73(732):e511\u0026ndash;e518\u003c/span\u003e\u003c/li\u003e\u003cli\u003e\u003cspan\u003eRasweswe MM, Mulaudzi FM (2022) Indigenous knowledge, beliefs, practices and treatments of menopause among females of African descent. Working with indigenous knowledge: Strategies for health professionals [Internet]\u003c/span\u003e\u003c/li\u003e\u003cli\u003e\u003cspan\u003eGreen R, Santoro N (2009) Menopausal symptoms and ethnicity: the Study of Women's Health Across the Nation. Women\u0026rsquo;s Health 5(2):127\u0026ndash;133\u003c/span\u003e\u003c/li\u003e\u003cli\u003e\u003cspan\u003ePalmer JR, Rosenberg L, Wise LA, Horton NJ, Adams-Campbell LL (2003) Onset of natural menopause in African American women. Am J Public Health 93(2):299\u0026ndash;306\u003c/span\u003e\u003c/li\u003e\u003cli\u003e\u003cspan\u003eBromberger JT, Matthews KA, Kullerr LH et al (1997) Prospective study of the determinants of age at menopause. Am J Epidemiol 145:124\u0026ndash;133\u003c/span\u003e\u003c/li\u003e\u003cli\u003e\u003cspan\u003ePrasad S (2023) Menopause in ethnic minority women. Post Reproductive Health 29(4):236\u0026ndash;239\u003c/span\u003e\u003c/li\u003e\u003cli\u003e\u003cspan\u003eObermeyer CM, Reher D, Saliba M (2007) Symptoms, menopause status, and country differences: a comparative analysis from DAMES. Menopause 14(4):788\u0026ndash;797\u003c/span\u003e\u003c/li\u003e\u003c/ol\u003e"},{"header":"Tables","content":"\u003cdiv class=\"gridtable\"\u003e\n \u003ctable id=\"Tab1\" border=\"1\"\u003e\n \u003ccaption language=\"En\"\u003e\n \u003cdiv class=\"CaptionNumber\"\u003eTable 1\u003c/div\u003e\n \u003cdiv class=\"CaptionContent\"\u003e\u003cbr\u003e\u003c/div\u003e\n \u003c/caption\u003e\n \u003cthead\u003e\n \u003ctr\u003e\n \u003cth align=\"left\" style=\"width: 16.9435%;\"\u003e\u0026nbsp;\u003c/th\u003e\n \u003cth align=\"left\" style=\"width: 17.608%;\"\u003e\u0026nbsp;\u003c/th\u003e\n \u003cth align=\"left\" style=\"width: 14.6179%;\"\u003e\n \u003cp\u003eHIC (46)\u003c/p\u003e\n \u003c/th\u003e\n \u003cth align=\"left\" style=\"width: 18.6047%;\"\u003e\n \u003cp\u003eLMIC(41)\u003c/p\u003e\n \u003c/th\u003e\n \u003cth align=\"left\" style=\"width: 9.3023%;\"\u003e\u0026nbsp;\u003c/th\u003e\n \u003cth align=\"left\" style=\"width: 22.9236%;\"\u003e\n \u003cp\u003ecomments\u003c/p\u003e\n \u003c/th\u003e\n \u003c/tr\u003e\n \u003c/thead\u003e\n \u003ctbody\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\" style=\"width: 16.9435%;\"\u003e\n \u003cp\u003eGeneral Demographics\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\" style=\"width: 17.608%;\"\u003e\n \u003cp\u003eMenopause age (yrs)(nos)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\" style=\"width: 14.6179%;\"\u003e\n \u003cp\u003e47.59\u0026thinsp;\u0026plusmn;\u0026thinsp;4.6\u003c/p\u003e\n \u003cp\u003e(46)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\" style=\"width: 18.6047%;\"\u003e\n \u003cp\u003e49.78\u0026thinsp;\u0026plusmn;\u0026thinsp;3.3\u003c/p\u003e\n \u003cp\u003e(41)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\" style=\"width: 9.3023%;\"\u003e\n \u003cp\u003eSE\u0026thinsp;=\u0026thinsp;0.861\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\" style=\"width: 22.9236%;\"\u003e\n \u003cp\u003e\u003cstrong\u003eP\u0026thinsp;=\u0026thinsp;0.013\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\" style=\"width: 16.9435%;\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003ctd align=\"left\" style=\"width: 17.608%;\"\u003e\n \u003cp\u003eCountry distribution\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\" style=\"width: 14.6179%;\"\u003e\n \u003cp\u003eEurope/ North America\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\" style=\"width: 18.6047%;\"\u003e\n \u003cp\u003eWest, South East Africa\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\" style=\"width: 9.3023%;\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003ctd align=\"left\" style=\"width: 22.9236%;\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\" style=\"width: 16.9435%;\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003ctd align=\"left\" style=\"width: 17.608%;\"\u003e\n \u003cp\u003eEducational level \u0026gt;/= university\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\" style=\"width: 14.6179%;\"\u003e\n \u003cp\u003e67.4%\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\" style=\"width: 18.6047%;\"\u003e\n \u003cp\u003e57.1%\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\" style=\"width: 9.3023%;\"\u003e\n \u003cp\u003e62.5%- HRT use\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\" style=\"width: 22.9236%;\"\u003e\n \u003cp\u003eP\u0026thinsp;=\u0026thinsp;0.325\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\" style=\"width: 16.9435%;\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003ctd align=\"left\" style=\"width: 17.608%;\"\u003e\n \u003cp\u003eParity\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\" style=\"width: 14.6179%;\"\u003e\n \u003cp\u003e2.4\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\" style=\"width: 18.6047%;\"\u003e\n \u003cp\u003e2.76\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\" style=\"width: 9.3023%;\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003ctd align=\"left\" style=\"width: 22.9236%;\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\" style=\"width: 16.9435%;\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003ctd align=\"left\" style=\"width: 17.608%;\"\u003e\n \u003cp\u003eHousehold size\u0026gt;/=3\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\" style=\"width: 14.6179%;\"\u003e\n \u003cp\u003e65%\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\" style=\"width: 18.6047%;\"\u003e\n \u003cp\u003e81%\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\" style=\"width: 9.3023%;\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003ctd align=\"left\" style=\"width: 22.9236%;\"\u003e\n \u003cp\u003e\u003cstrong\u003eP\u0026thinsp;=\u0026thinsp;0.097\u003c/strong\u003e\u003c/p\u003e\n \u003cp\u003e95%CI (-2.86% to33.09%)\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\" style=\"width: 16.9435%;\"\u003e\n \u003cp\u003eKnowledge\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\" style=\"width: 17.608%;\"\u003e\n \u003cp\u003eDefinition:\u003c/p\u003e\n \u003cp\u003e1.Actual\u003c/p\u003e\n \u003cp\u003e2.Symptom-related\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\" style=\"width: 14.6179%;\"\u003e\n \u003cp\u003e85%\u003c/p\u003e\n \u003cp\u003e13%\u003c/p\u003e\n \u003cp\u003e72%\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\" style=\"width: 18.6047%;\"\u003e\n \u003cp\u003e79%\u003c/p\u003e\n \u003cp\u003e43%\u003c/p\u003e\n \u003cp\u003e26%\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\" style=\"width: 9.3023%;\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003ctd align=\"left\" style=\"width: 22.9236%;\"\u003e\n \u003cp\u003eP\u0026thinsp;=\u0026thinsp;0.486\u003c/p\u003e\n \u003cp\u003e\u003cstrong\u003eP\u0026thinsp;=\u0026thinsp;0.001\u003c/strong\u003e\u003c/p\u003e\n \u003cp\u003e\u003cstrong\u003eP\u0026thinsp;=\u0026thinsp;0.0001\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\" style=\"width: 16.9435%;\"\u003e\n \u003cp\u003eCultural practice\u003c/p\u003e\n \u003cp\u003eAwareness\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\" style=\"width: 17.608%;\"\u003e\n \u003cp\u003eCultural practice awareness % (nos)\u003c/p\u003e\n \u003cp\u003eDiet\u003c/p\u003e\n \u003cp\u003eHerbs\u003c/p\u003e\n \u003cp\u003eExercise\u003c/p\u003e\n \u003cp\u003eWeight gain\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\" style=\"width: 14.6179%;\"\u003e\n \u003cp\u003e21.7% (\u003cspan class=\"CitationRef\"\u003e10\u003c/span\u003e)\u003c/p\u003e\n \u003cp\u003e60%\u003c/p\u003e\n \u003cp\u003e40%\u003c/p\u003e\n \u003cp\u003e10%\u003c/p\u003e\n \u003cp\u003e10%\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\" style=\"width: 18.6047%;\"\u003e\n \u003cp\u003e12.2% (\u003cspan class=\"CitationRef\"\u003e5\u003c/span\u003e)\u003c/p\u003e\n \u003cp\u003e60%\u003c/p\u003e\n \u003cp\u003e40%\u003c/p\u003e\n \u003cp\u003e--\u003c/p\u003e\n \u003cp\u003e--\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\" style=\"width: 9.3023%;\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003ctd align=\"left\" style=\"width: 22.9236%;\"\u003e\n \u003cp\u003eP\u0026thinsp;=\u0026thinsp;0.244\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\" style=\"width: 16.9435%;\"\u003e\n \u003cp\u003eSymptoms\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\" style=\"width: 17.608%;\"\u003e\n \u003cp\u003eSymptom prevalence\u003c/p\u003e\n \u003cp\u003e(2ry survey)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\" style=\"width: 14.6179%;\"\u003e\n \u003cp\u003e43 (93.5%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\" style=\"width: 18.6047%;\"\u003e\n \u003cp\u003e38 (92.7%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\" style=\"width: 9.3023%;\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003ctd align=\"left\" style=\"width: 22.9236%;\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\" style=\"width: 16.9435%;\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003ctd align=\"left\" style=\"width: 17.608%;\"\u003e\n \u003cp\u003eInitial symptom report\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\" style=\"width: 14.6179%;\"\u003e\n \u003cp\u003e34\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\" style=\"width: 18.6047%;\"\u003e\n \u003cp\u003e22\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\" style=\"width: 9.3023%;\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003ctd align=\"left\" style=\"width: 22.9236%;\"\u003e\n \u003cp\u003e31 initially reported no symptoms HIC:12 LMIC:19\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\" style=\"width: 16.9435%;\"\u003e\n \u003cp\u003eReporting discordance\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\" style=\"width: 17.608%;\"\u003e\n \u003cp\u003esymptom reporting discordance\u003c/p\u003e\n \u003cp\u003edeficit\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\" style=\"width: 14.6179%;\"\u003e\n \u003cp\u003e43 vs 34\u003c/p\u003e\n \u003cp\u003e26.1%\u003c/p\u003e\n \u003cp\u003e9 (19.5%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\" style=\"width: 18.6047%;\"\u003e\n \u003cp\u003e38 vs 22\u003c/p\u003e\n \u003cp\u003e46.3%\u003c/p\u003e\n \u003cp\u003e16(39.02%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\" style=\"width: 9.3023%;\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003ctd align=\"left\" style=\"width: 22.9236%;\"\u003e\n \u003cp\u003e\u003cstrong\u003eP\u0026thinsp;=\u0026thinsp;0.045 95%CI (0.45%-37.18%)\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\" style=\"width: 16.9435%;\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003ctd align=\"left\" style=\"width: 17.608%;\"\u003e\n \u003cp\u003eSymptom severity\u003c/p\u003e\n \u003cp\u003e(QOL impact)\u0026thinsp;\u0026gt;\u0026thinsp;3 no/(%)\u003c/p\u003e\n \u003cp\u003eHRT use\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\" style=\"width: 14.6179%;\"\u003e\n \u003cp\u003e8 (17.4%)\u003c/p\u003e\n \u003cp\u003e25%\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\" style=\"width: 18.6047%;\"\u003e\n \u003cp\u003e7(17%)\u003c/p\u003e\n \u003cp\u003e0%\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\" style=\"width: 9.3023%;\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003ctd align=\"left\" style=\"width: 22.9236%;\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\" style=\"width: 16.9435%;\"\u003e\n \u003cp\u003eGlobal HRT use\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\" style=\"width: 17.608%;\"\u003e\n \u003cp\u003eHRT use\u003c/p\u003e\n \u003cp\u003eHIC VS LMIC\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\" style=\"width: 14.6179%;\"\u003e\n \u003cp\u003e15.2%\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\" style=\"width: 18.6047%;\"\u003e\n \u003cp\u003e0%\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\" style=\"width: 9.3023%;\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003ctd align=\"left\" style=\"width: 22.9236%;\"\u003e\n \u003cp\u003e\u003cstrong\u003eP\u0026thinsp;=\u0026thinsp;0.009 95%CI (3.72%-28.2%)\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\" style=\"width: 16.9435%;\"\u003e\n \u003cp\u003eCo-morbidities\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\" style=\"width: 17.608%;\"\u003e\n \u003cp\u003eHypertension prevalence\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\" style=\"width: 14.6179%;\"\u003e\n \u003cp\u003e15.2%/46\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\" style=\"width: 18.6047%;\"\u003e\n \u003cp\u003e21.4%/41\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\" style=\"width: 9.3023%;\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003ctd align=\"left\" style=\"width: 22.9236%;\"\u003e\n \u003cp\u003eP\u0026thinsp;=\u0026thinsp;0.456\u003c/p\u003e\n \u003cp\u003e95%CI (-10.1% to 22.76%)\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\" style=\"width: 16.9435%;\"\u003e\n \u003cp\u003eOther factors\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\" style=\"width: 17.608%;\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003ctd align=\"left\" style=\"width: 14.6179%;\"\u003e\n \u003cp\u003eHigh educational attainment\u003c/p\u003e\n \u003cp\u003e-University-level and higher\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\" style=\"width: 18.6047%;\"\u003e\n \u003cp\u003eHigh earnings \u0026gt;\u0026pound;50,000 equivalent annual household income\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\" style=\"width: 9.3023%;\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003ctd align=\"left\" style=\"width: 22.9236%;\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\" style=\"width: 16.9435%;\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003ctd align=\"left\" style=\"width: 17.608%;\"\u003e\n \u003cp\u003eHRT use Educational vs high earnings\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\" style=\"width: 14.6179%;\"\u003e\n \u003cp\u003e0.625 (67%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\" style=\"width: 18.6047%;\"\u003e\n \u003cp\u003e0.304\u003c/p\u003e\n \u003cp\u003e(37%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\" style=\"width: 9.3023%;\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003ctd align=\"left\" style=\"width: 22.9236%;\"\u003e\n \u003cp\u003e\u003cstrong\u003eP\u0026thinsp;=\u0026thinsp;0.004;\u003c/strong\u003e\u003c/p\u003e\n \u003cp\u003e\u003cstrong\u003e95%CI (10.01% to 47.59%)\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003c/tbody\u003e\n \u003c/table\u003e\n\u003c/div\u003e\n\u003cdiv class=\"gridtable\"\u003e\n \u003cdiv align=\"left\" class=\"colspec\"\u003e\u003cbr\u003e\u003c/div\u003e\n \u003cdiv align=\"left\" class=\"colspec\"\u003e\u003cbr\u003e\u003c/div\u003e\n \u003cdiv align=\"left\" class=\"colspec\"\u003e\u003cbr\u003e\u003c/div\u003e\n \u003ctable id=\"Tab2\" border=\"1\"\u003e\n \u003ccaption language=\"En\"\u003e\n \u003cdiv class=\"CaptionNumber\"\u003eTable 2\u003c/div\u003e\n \u003cdiv class=\"CaptionContent\"\u003e\n \u003cp\u003eSUMMARY TABLE (Themes\u0026thinsp;+\u0026thinsp;Representative content)\u003c/p\u003e\n \u003c/div\u003e\n \u003c/caption\u003e\n \u003cthead\u003e\n \u003ctr\u003e\n \u003cth align=\"left\"\u003e\n \u003cp\u003eTheme\u003c/p\u003e\n \u003c/th\u003e\n \u003cth align=\"left\"\u003e\n \u003cp\u003eDescription\u003c/p\u003e\n \u003c/th\u003e\n \u003cth align=\"left\"\u003e\n \u003cp\u003eIllustrative Respondent Ideas\u003c/p\u003e\n \u003c/th\u003e\n \u003c/tr\u003e\n \u003c/thead\u003e\n \u003ctbody\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e\u003cstrong\u003eGeographical \u0026amp; Environmental Factors\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eClimate and environment influence biological wellbeing (e.g., vitamin D, food quality).\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e\u0026ldquo;Readily available sunlight in LMICs may reduce symptom severity.\u0026rdquo; / \u0026ldquo;Processed foods in HICs worsen metabolic health.\u0026rdquo;\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e\u003cstrong\u003eImmigration, Deprivation \u0026amp; Stress\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eMigrants face reduced income, discrimination, and health inequities.\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e\u0026ldquo;Nativity advantage declines after migration.\u0026rdquo; / \u0026ldquo;Financial pressures increase stress.\u0026rdquo;\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e\u003cstrong\u003eHealth System Inequalities\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eMinority women report poorer access and care quality.\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e\u0026ldquo;Ethnic minorities in the UK received less menopause support.\u0026rdquo; / \u0026ldquo;COVID highlighted chronic inequities.\u0026rdquo;\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e\u003cstrong\u003eMenopause Literacy Gaps\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eLow awareness among patients and clinicians hinders care.\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e\u0026ldquo;Even with policies, menopause literacy was poor.\u0026rdquo;\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e\u003cstrong\u003eCultural Norms \u0026amp; Sociocultural Roles\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eCultural beliefs shape symptom expectations and responses.\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e\u0026ldquo;Weight gain is seen as protective.\u0026rdquo; / \u0026ldquo;Menopause is something to endure.\u0026rdquo;\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e\u003cstrong\u003eSexual Health Silence \u0026amp; Stigma\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eVaginal atrophy and sexual symptoms under-recognised due to cultural taboos.\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e\u0026ldquo;Women disengaged from genital health after childbirth.\u0026rdquo;/ \u0026ldquo;no need for sexual activity after childbirth completion or after menopause\u0026rdquo;\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e\u003cstrong\u003eFear of MHT \u0026amp; Alternative Treatments\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eMistrust driven by side-effect fears, media, and misinformation.\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e\u0026ldquo;Concerns over fibroid growth and sensationalised press reduce uptake.\u0026rdquo;/ \u0026ldquo;no readily available/ affordable highly sensitive diagnostic test in women with fibroids\u0026rdquo;\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003c/tbody\u003e\n \u003c/table\u003e\n\u003c/div\u003e"}],"fulltextSource":"","fullText":"","funders":[],"hasAdminPriorityOnWorkflow":false,"hasManuscriptDocX":true,"hasOptedInToPreprint":true,"hasPassedJournalQc":"","hasAnyPriority":true,"hideJournal":false,"highlight":"","institution":"Hull and East Yorkshire Hospitals NHS Trust","isAcceptedByJournal":true,"isAuthorSuppliedPdf":false,"isDeskRejected":"","isHiddenFromSearch":false,"isInQc":false,"isInWorkflow":false,"isPdf":false,"isPdfUpToDate":true,"isWithdrawnOrRetracted":false,"journal":{"display":true,"email":"[email protected]","identity":"researchsquare","isNatureJournal":false,"hasQc":true,"allowDirectSubmit":true,"externalIdentity":"","sideBox":"","snPcode":"","submissionUrl":"/submission","title":"Research Square","twitterHandle":"researchsquare","acdcEnabled":true,"dfaEnabled":false,"editorialSystem":"","reportingPortfolio":"","inReviewEnabled":false,"inReviewRevisionsEnabled":true},"keywords":"Domicile, Hypertension, LMICs, Menopause, Sub-Saharan, Residence","lastPublishedDoi":"10.21203/rs.3.rs-8239685/v1","lastPublishedDoiUrl":"https://doi.org/10.21203/rs.3.rs-8239685/v1","license":{"name":"CC BY 4.0","url":"https://creativecommons.org/licenses/by/4.0/"},"manuscriptAbstract":"\u003cp\u003e\u003cstrong\u003eObjectives\u003c/strong\u003e: to identify menopause age, symptom-prevalence and severity, knowledge and treatment-gap specific to residence of the Sub-Saharan women.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eMethods\u003c/strong\u003e: An electronic mixed-methods cross-sectional community survey administered in June 2024, of Sub-Saharan women \u0026gt;40yrs who had reached menopause across the world. Data analysis was via Microsoft Excel©.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eResults\u003c/strong\u003e: 87 of the 124 responses met inclusion criteria. Average menopause age of 47.59 yrs ± 4.56 (HIC) vs 49.78yrs ±3.26 (LMIC)\u003cstrong\u003e P= 0.013 \u003c/strong\u003e95%CI (0.479 -3.9). There were no statistical differences in demographics though a small cohort of HIC women with early menopause occurrence after 5-8yrs of emigration with an average of 6.8 yrs ± 3.4 yrs, was observed.\u0026nbsp;\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eSymptom-prevalence\u003c/strong\u003e was 93.5%(HIC) vs 92.7%(LMIC). Global significant symptom-severity at 17%: Genitourinary symptoms- GUS (58%) was most common in LMIC cohort followed by Vasomotor symptoms (42%) and Insomnia (21%). Vasomotor symptoms were equipoised with GUS in the HIC (58%). Hypertension prevalence was 15.2% (HIC) vs 21.4% (LMIC).\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eKnowledge deficit\u003c/strong\u003e: Appropriate definition by \u0026gt;78% globally with the HIC cohort largely by symptomatology. There was poorer symptom-recognition in the LMIC (46.3%) as compared to the HIC (26.1%). Some harm from poor symptom-recognition due to disease-severity was seen in LMIC (16%) as only 13% with significant symptom-severity, mostly Vasomotor and GUS, were on MHT (Menopause hormone treatment).\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eGlobal MHT use\u003c/strong\u003e was 8%: largely in HIC (15.2%) vs LMIC (0%) \u003cstrong\u003eP=0.009: \u003c/strong\u003eand within the well-educated (67%) vs those with high household incomes (37%) \u003cstrong\u003eP=0.004.\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eConclusions\u003c/strong\u003e: In this small study, HIC-residence woman undergoes Menopause 26.4 months ahead of her LMIC-counterpart. There is a knowledge and treatment-deficit with associated disease morbidity. This highlights the need for tailored health-awareness programmes supported by timely-treatment given possible cardio-protection benefits.\u003c/p\u003e","manuscriptTitle":"Socio-Environmental Variation in Menopause Experiences of Subsaharan African women: A LMIC-HIC comparative perspective","msid":"","msnumber":"","nonDraftVersions":[{"code":1,"date":"2025-12-02 07:18:38","doi":"10.21203/rs.3.rs-8239685/v1","editorialEvents":[{"type":"communityComments","content":0}],"status":"published","journal":{"display":true,"email":"[email protected]","identity":"researchsquare","isNatureJournal":false,"hasQc":true,"allowDirectSubmit":true,"externalIdentity":"","sideBox":"","snPcode":"","submissionUrl":"/submission","title":"Research Square","twitterHandle":"researchsquare","acdcEnabled":true,"dfaEnabled":false,"editorialSystem":"","reportingPortfolio":"","inReviewEnabled":false,"inReviewRevisionsEnabled":true}}],"origin":"","ownerIdentity":"9225f848-891a-4526-abd6-7296b103aab9","owner":[],"postedDate":"December 2nd, 2025","published":true,"recentEditorialEvents":[],"rejectedJournal":[],"revision":"","amendment":"","status":"published-in-journal","subjectAreas":[{"id":58829528,"name":"Endocrinology \u0026 Metabolism"}],"tags":[],"updatedAt":"2026-01-05T15:23:47+00:00","versionOfRecord":{"articleIdentity":"rs-8239685","link":"https://doi.org/10.9734/jammr/2025/v37i126033","journal":{"identity":"journal-of-advances-in-medicine-and-medical-research","isVorOnly":true,"title":"Journal of Advances in Medicine and Medical Research"},"publishedOn":"2025-12-27 00:00:00","publishedOnDateReadable":"December 27th, 2025"},"versionCreatedAt":"2025-12-02 07:18:38","video":"","vorDoi":"10.9734/jammr/2025/v37i126033","vorDoiUrl":"https://doi.org/10.9734/jammr/2025/v37i126033","workflowStages":[]},"version":"v1","identity":"rs-8239685","journalConfig":"researchsquare"},"__N_SSP":true},"page":"/article/[identity]/[[...version]]","query":{"redirect":"/article/rs-8239685","identity":"rs-8239685","version":["v1"]},"buildId":"8U1c8b4HqxoKbykW_rLl7","isFallback":false,"isExperimentalCompile":false,"dynamicIds":[84888],"gssp":true,"scriptLoader":[]}