Women's empowerment, locus of contraceptive decision-making, and modern contraceptive use in Peru

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We examined how distinct empowerment dimensions relate to the locus of contraceptive decision (female-controlled vs couple-controlled methods) and to modern method use among partnered Peruvian women. Methods: We conducted an analytic cross-sectional study using nationally representative ENDES/DHS microdata (2015–2018) for women aged 15–49 in union (N=27 440; pregnant women and those desiring pregnancy were excluded). Four empowerment indicators were analyzed: (1) decision over household resources, (2) freedom of movement, (3) partner’s respect for the woman’s opinions/desires/rights, and (4) decision over own health. The first three indices were built via PCA, standardized, and split into terciles; “health decision” was a three-level item (partner alone / joint / woman alone). Survey-weighted logistic models reported average marginal effects (percentage points), adjusting for individual and household characteristics, sexual and reproductive health supply conditions (e.g., service density, perceived distance, availability of female staff), and year and department fixed effects. Results: Decision over one’s own health shows consistent associations: medium and high levels increase modern method use by approximately 5–8 p.p. and woman-controlled methods by approximately 5–7 p.p. Partner’s respect is especially associated with jointly controlled methods (approximately 4–5 p.p.) and, to a lesser extent, with modern methods overall (approximately 3 p.p.). Freedom of movement exhibits small, positive associations concentrated at intermediate levels. The household-resources indicator is weak and unstable. Supply-side coefficients display expected directions: better availability and shorter perceived distance are associated with greater contraceptive use. Conclusions: Empowerment domains map onto specific contraceptive margins: clinical autonomy shifts use toward female-controlled methods, while partner respect favors couple-controlled choices. Counseling and service organization should incorporate women’s empowerment profiles, expand self-administered options, and strengthen couple communication to support informed, preferred method use. Women’s empowerment Contraception Decision-making Reproductive health services DHS Peru Background Universal access to contraception is central to sexual and reproductive health and rights (SRHR) and to global commitments such as the Sustainable Development Goals. Yet, modern contraceptive prevalence, method mix, and unmet need remain uneven across settings, even where service coverage has improved [9,15]. Contemporary SRHR guidance increasingly emphasizes self-care interventions and person-centered counseling approaches that can reduce barriers and strengthen women’s ability to enact their fertility preferences [14,15]. Peru illustrates this implementation gap. According to ENDES, around 85% of partnered women report wanting to stop childbearing or postpone pregnancy for two or more years, but only about 55% use modern contraceptive methods; additionally, roughly 6% have unmet need for family planning [13]. This mismatch highlights that effective contraceptive use depends not only on supply, but also on intra-household processes that shape decision-making and the feasibility of adopting specific methods. From the perspective of collective household models, women’s empowerment can be interpreted as shifts in bargaining weights that influence desired fertility and contraceptive choices [1–3]. Importantly, contraceptive adoption is not only about “use vs non-use”: it may depend on method attributes (such as observability to the partner and the degree of coordination required) so that the same empowerment domain can plausibly shift women toward methods that are primarily under their own control versus methods that typically require couple agreement [2,3]. Empirically, DHS-based empowerment measures (including SWPER and related indices) have been associated with higher modern contraceptive use in multiple contexts, and prior work also highlights the roles of autonomy and couple communication [4–8,10,16–19]. However, most evidence focuses on overall modern contraceptive use and seldom distinguishes explicitly between methods that are predominantly woman-controlled and those that are typically couple-controlled, potentially masking heterogeneous relationships by decision locus. In addition, relatively few applications incorporate supply-side conditions systematically (availability, distance, provider characteristics), which may confound associations between empowerment and contraceptive outcomes [9,20–22]. This study addresses these gaps using ENDES 2015–2018. We examine modern contraceptive use and further classify methods into two groups (those predominantly controlled by the woman and those typically requiring couple coordination) while linking four empowerment domains (household resources, freedom of movement, partner’s respect for opinions/desires/rights, and decision-making over one’s own health) to each contraceptive outcome. We account for survey design, individual and household covariates, fixed effects, and contextual supply measures. By mapping empowerment dimensions onto distinct contraceptive decision margins, our findings aim to inform targeted SRHR counseling and service organization in Peru and comparable settings [4–6,9,14–16]. Methods Data and data processing We conducted an analytical cross-sectional study using nationally representative Demographic and Health Survey microdata for Peru (DHS/ENDES), pooled for 2015–2018. We additionally incorporated SRH service availability indicators from administrative sources: health facility supply and health workforce counts from the Ministry of Health, and public health expenditure from the Ministry of Economy and Finance. ENDES/DHS provides sampling weights and the complex survey design variables (strata and primary sampling units), which were retained for analysis. The target population comprised partnered women aged 15–49 years (married or cohabiting). For the contraceptive outcomes, we excluded women who were pregnant at interview and those reporting a current desire to become pregnant. After applying these criteria and harmonizing variables across survey years, the analytical sample for contraceptive outcomes included 27,440 observations. We defined three binary outcomes of current contraceptive use. First, any modern method, following the standard classification (e.g., female and male sterilization, pill, IUD, injectables, implants, condoms, emergency contraception, lactational amenorrhea method, and other modern methods as applicable in ENDES). Second, woman-controlled methods, defined as methods whose initiation and continuation primarily depend on the woman (pill, injectables, IUD, implant, emergency contraception, and female sterilization). Third, couple-controlled methods, defined as methods that typically require coordination or agreement with the partner, including male/female condoms and male sterilization, and (consistent with the locus-of-control concept) traditional co-managed methods such as periodic abstinence and withdrawal. The full list of methods included in each category is reported in Table 1. We constructed four empowerment indicators: (1) decision-making over household resources, (2) freedom of movement, (3) partner respect for the woman’s opinions/desires/rights, and (4) decision-making over the woman’s own healthcare. The first three indicators were derived from ENDES items commonly used in DHS-based empowerment measurement. Specifically, household-resources decision-making combines items on participation in major household purchases, relative earnings within the couple, and who decides on the partner’s earnings; freedom of movement combines who decides on visits to relatives and partner control/restriction items; and partner respect captures the reported degree of respect for the woman’s opinions, desires, and rights. For these three domains, we applied principal component analysis (PCA) to the ordinal items, standardized the resulting scores (mean 0, SD 1), and categorized them into terciles (low/medium/high). Internal consistency and variance explained were assessed and are reported in Table 4. The healthcare decision indicator was based on a single item and recoded into three levels: low (partner decides alone), medium (joint decision), and high (woman decides alone). We adjusted for individual and household characteristics: age (and squared term), parity, woman’s and partner’s education, woman’s employment, household wealth quintile, health insurance coverage, urban/rural residence, natural region, and department of residence. We also included SRH supply measures combining administrative and survey-based proxies: facility density, physician density, and nursing/midwifery density per 1,000 population at the province level; the maximum facility level available in the province; and ENDES self-reported access barriers (perceived distance to a facility and perceived lack of female health personnel). Public health expenditure per capita was measured at the department level and assigned to respondents based on department of residence. Administrative indicators were converted to per-capita or per-1,000 population metrics using official population denominators and linked to ENDES respondents by their reported province and department of residence. Operational definitions and sources for all variables are summarized in Table 1. Statistical analysis We estimated the association between women’s empowerment and contraceptive use using survey-weighted logistic regression models. Three binary outcomes were analyzed separately: (i) current use of any modern contraceptive method, (ii) current use of woman-controlled methods, and (iii) current use of couple-controlled methods (definitions in Table 1). For each outcome, we fitted models that included the four empowerment indicators as the main exposures. Empowerment indicators derived from PCA were entered as terciles (medium and high), using the low tercile as the reference category; the healthcare decision indicator (single item) was also modeled in three levels with “low” (partner decides alone) as the reference. All models were estimated accounting for the ENDES/DHS complex sampling design (sampling weights, strata, and primary sampling units). We used robust variance estimation clustered at the primary sampling unit level. To facilitate interpretation, we report average marginal effects (AMEs) expressed in percentage points, alongside 95% confidence intervals. Statistical significance was assessed using two-sided tests with conventional thresholds (p<0.10, p<0.05, p<0.01). The main specification adjusted for a common set of covariates capturing individual and household characteristics (age and age-squared, parity, woman’s education, partner’s education, woman’s employment status, household wealth quintile, health insurance category, urban/rural residence, and additional geographic controls). To reduce confounding from access constraints, we additionally controlled for SRH supply and access measures: province-level densities of facilities and health personnel, the maximum facility level available in the province, and survey-based barriers (perceived distance to a facility and perceived lack of female personnel). We included fixed effects for survey year and department to absorb common time shocks and time-invariant differences across departments. Models were estimated on complete cases for the outcome and the covariates included in each specification; final analytical sample sizes are reported in the tables. We conducted robustness checks to evaluate the stability of the main associations. These included alternative specifications of the empowerment indicators (e.g., using standardized continuous scores instead of terciles for the PCA-based indices), and alternative sets of controls for SRH supply and geographic factors. Results were considered robust when the direction of effects and the approximate magnitude of the AMEs were stable across specifications. All analyses adhered to DHS/ENDES methodological guidance for pooled multi-year analyses and to standard reporting practices for observational studies using complex survey data. Results The pooled ENDES 2015–2018 analytic sample included 27,440 women aged 15–49 years who were married or cohabiting, after excluding women who were pregnant at the time of interview or who reported a current desire to become pregnant. In this population, 60% reported using any modern contraceptive method, 44% reported using methods classified as woman-controlled, and 39% reported using couple-controlled methods (Table 2). Prevalence patterns followed expected gradients by sociodemographic characteristics: modern method use was higher among younger women, those with secondary or higher education, women in higher wealth quintiles, and urban residents. Women self-identifying as Indigenous presented lower prevalence of modern method use (42%) and lower use of woman-controlled methods (37%). The gap between woman-controlled and couple-controlled methods was particularly pronounced among women aged 15–24 years (54% vs 35%), suggesting heterogeneity in the locus of contraceptive decision-making across the life course. Table 3 reports average marginal effects (percentage points) from survey-weighted logistic models adjusting for individual and household covariates, SRH supply and access measures, and year and department fixed effects. The empowerment domain most consistently associated with contraceptive outcomes was decision-making over one’s own health. Relative to the low category (partner decides alone), the medium and high levels were associated with higher probability of using modern methods (approximately 5.4 p.p. and 7.9 p.p., respectively; p<0.01) and higher probability of using woman-controlled methods (approximately 4.6 p.p. and 6.7 p.p.; p<0.01). By contrast, this indicator showed no positive association with couple-controlled methods, with small and non-significant coefficients, consistent with a shift toward methods under women’s direct control when clinical agency increases. The partner respect domain (respect for the woman’s opinions, desires, and rights) was positively associated with modern method use at the medium level (approximately 3.1 p.p.; p<0.01) and showed the clearest association with couple-controlled methods (approximately 4.1–4.9 p.p. for medium/high; statistically significant), indicating that improved communication and valuation of women’s preferences may facilitate coordinated methods. Freedom of movement exhibited a non-linear pattern: the medium level was positively associated with modern use and with woman-controlled methods (around 1.3 p.p.), whereas the high level was associated with lower use of couple-controlled methods (around −5.8 p.p.; statistically significant), consistent with substitution away from coordinated methods as autonomy increases. The household resources indicator displayed weak and unstable associations: the high category was negatively associated with modern method use (around −2.2 p.p.; statistically significant), while the medium category was positively associated with woman-controlled methods (around 2.6 p.p.; marginally significant) and negatively associated with couple-controlled methods (around −3.8 p.p.; statistically significant), again suggesting substitution toward woman-controlled options as economic agency increases. Access constraints behaved as expected. Reporting distance as a barrier was associated with lower use of modern and woman-controlled methods (negative, statistically significant), and reporting lack of female personnel as a barrier was likewise negatively associated with modern and woman-controlled use. Province-level supply measures (densities of facilities and health personnel and maximum facility level) were less consistent in the fully adjusted models, though the overall direction supported the relevance of access conditions. Psychometric results for the composite empowerment indices are summarized in Table 4. The partner respect index showed high internal consistency (Cronbach’s α=0.84) and high explained variance (=0.76), supporting its interpretation as a coherent scale. In contrast, the household resources (α=0.29; explained variance=0.42) and freedom of movement (α=0.34; =0.44) indices showed low internal consistency, consistent with more heterogeneous constructs and motivating interpretation as relative position measures derived from PCA rather than highly homogeneous scales. Overall, the results indicate that empowerment domains map onto distinct margins of contraceptive choice: greater clinical autonomy is most strongly associated with increased use of woman-controlled methods, whereas partner respect is most strongly associated with increased use of couple-controlled methods; aggregating modern methods can partially mask these differentiated patterns. Discussion This study shows that women’s empowerment is not uniformly associated with “modern contraceptive use” as an aggregate outcome; instead, distinct empowerment domains map onto different margins of contraceptive decision-making once methods are classified by locus of control. The most consistent and policy-relevant pattern is that greater clinical autonomy, captured by decision-making over one’s own health, is associated with higher use of modern methods overall and, specifically, higher use of methods predominantly controlled by the woman, with no corresponding increase in couple-controlled methods. In contrast, partner respect for the woman’s opinions, desires, and rights is most strongly associated with couple-controlled method use, consistent with the idea that interpersonal dynamics and communication facilitate methods that typically require coordination. These differentiated patterns help explain why some empowerment measures can appear weak, unstable, or ambiguous when the outcome is limited to “any modern method,” where opposing movements between woman-controlled and couple-controlled choices may partially offset each other. From an intra-household bargaining perspective, the results align with collective models in which empowerment shifts bargaining weights and therefore the household’s reproductive choices, conditional on preferences and constraints [1–3]. Importantly, our classification by decision locus highlights the role of method attributes (particularly the need for coordination, observability, and the extent to which initiation and continuation can be executed by the woman alone) in shaping how empowerment translates into behavior [2–3]. When women’s agency is higher in clinical decisions, the household equilibrium may shift toward methods that the woman can adopt and sustain without requiring ongoing partner agreement (e.g., injectables, IUD, implant, pill), whereas improvements in relationship quality and respect may increase the feasibility and acceptability of methods whose consistent use typically depends on couple cooperation (e.g., condoms) or shared practices. Our findings also speak to a broader empirical literature that links empowerment to contraceptive outcomes using DHS-based measures, including SWPER and related indices. Multi-country work has documented positive associations between empowerment and modern contraceptive use and emphasized autonomy and couple communication as key pathways [4–7,16–19]. Within Peru, recent ENDES-based evidence using SWPER similarly reports that lower empowerment is associated with lower modern contraceptive use [10], and related epidemiological work identifies correlates of highly effective method use in the Peruvian context [11]. The contribution of the present analysis is to unpack the aggregate modern-method association by showing that different empowerment domains align with different contraceptive margins: clinical autonomy is most predictive of woman-controlled method use, while partner respect is most predictive of couple-controlled method use. This distinction is directly relevant for counseling and program design because it informs not only whether modern contraceptive use might rise, but which methods are more likely to be taken up under different empowerment profiles. A second implication is that supply-side barriers remain consequential even after adjusting for empowerment and socioeconomic characteristics. Self-reported barriers related to distance and lack of female personnel were negatively associated with contraceptive use outcomes, consistent with the notion that agency is exercised within a constraint set shaped by service accessibility and acceptability. This is consistent with global guidance emphasizing person-centered counseling, reduction of access barriers, and self-care approaches that can lower transaction costs and improve continuity of use [14–15]. In practical terms, programs aiming to promote self-administered or less partner-dependent methods must still ensure that women can obtain methods reliably, receive appropriate counseling, and manage side effects and discontinuation risks, especially for long-acting methods where discontinuation dynamics can be substantial [20]. The combination of empowerment-sensitive counseling with concrete service delivery improvements is therefore central to moving from stated fertility preferences to effective use. Measurement considerations are important for interpreting domain-specific results. The “partner respect” index exhibited strong psychometric performance, supporting its interpretation as a coherent relational construct. By contrast, “resources decision-making” and “freedom of movement” showed low internal consistency, suggesting these indices capture more heterogeneous behaviors and norms and should be interpreted as relative position measures rather than tightly unified scales. This heterogeneity likely contributes to the weaker and less stable associations observed for these domains. In addition, the “decision over own health” indicator is a single item and is conceptually close to contraceptive behavior; it plausibly captures a particularly relevant facet of agency for SRH decisions, but its proximity also raises the possibility that it partially reflects unobserved couple dynamics or service interactions tightly linked to contraception. The strong association observed for this domain should therefore be read as a robust empirical relationship, while recognizing that the underlying mechanisms may combine empowerment, negotiation, and health-system contact. Several limitations should be acknowledged. First, the analysis is cross-sectional (pooled across years) and observational; residual confounding and reverse causality remain possible. Women who adopt certain methods may experience changes in perceived agency or relationship dynamics, and unobserved factors, such as partner preferences, fertility intentions beyond the exclusion criteria, or community norms, could influence both empowerment measures and contraceptive outcomes. Second, the locus-of-control classification, while substantively motivated, inevitably simplifies real-world decision-making; some methods may be jointly discussed yet practically controlled by one partner, and reporting may reflect social desirability or recall issues. Third, while we incorporated multiple supply proxies, administrative measures are aggregated and may not fully capture quality, stockouts, provider behavior, or method availability at the point of care; such mismeasurement can attenuate estimated associations. Despite these limitations, the study has notable strengths: nationally representative DHS/ENDES microdata across multiple years; explicit correction for complex survey design; a multidimensional empowerment framework; incorporation of both administrative and self-reported supply/access measures; and a conceptually grounded decomposition of contraceptive outcomes by decision locus. Together, these elements provide a clearer interpretation of how empowerment may translate into contraceptive behavior. The policy implications follow directly from the differentiated patterns. First, counseling and service organization should incorporate empowerment profiles: when clinical autonomy is low, interventions that strengthen women’s decision-making capacity and reduce barriers to confidential access may be especially relevant for woman-controlled methods; when relationship respect and communication are low, strategies that address couple dynamics, respectful partner engagement, and communication may be critical for methods requiring coordination [4–7,16–19]. Second, expanding access to self-administered options and ensuring person-centered counseling can help translate agency into sustained use, but these efforts must be paired with improvements in access and acceptability, including female personnel availability and reduced travel burdens [14–15]. Finally, future research should leverage quasi-experimental variation in method availability, counseling intensity, or service expansions to better identify causal effects and to understand how empowerment interacts with supply-side changes in shaping contraceptive trajectories. Conclusions In Peru, women’s empowerment is associated with contraceptive use in ways that depend on the locus of decision. Decision-making autonomy over one’s own health is consistently linked to higher use of modern contraception, driven primarily by increased uptake of woman-controlled methods. In contrast, partner respect for women’s opinions, desires, and rights is most strongly associated with couple-controlled methods, suggesting that relational dynamics and communication facilitate choices requiring coordination. These findings imply that treating “modern contraceptive use” as a single outcome can mask meaningful heterogeneity across method types. Sexual and reproductive health programs should align counseling and service organization with women’s empowerment profiles: expand and support access to woman-controlled and self-administered options for women with greater clinical autonomy, while strengthening couple communication and respectful partner engagement to support coordinated methods. Reducing access barriers, especially perceived distance and lack of female personnel, remains important to translate preferences into effective use. Abbreviations DHS: Demographic and Health Surveys; ENDES: Encuesta Demográfica y de Salud Familiar; SRH: Sexual and Reproductive Health; LAM: Lactational Amenorrhea Method; PCA: Principal Components Analysis; PSU: Primary Sampling Unit; CI: Confidence Interval Declarations Ethics approval and consent to participate ENDES/DHS protocols and tools were approved by the ICF Institutional Review Board and relevant national ethics boards in Peru. The authors analyzed de-identified, publicly available microdata under data-use agreements; no additional approval was required by PUCP. All respondents provided informed consent at the time of the surveys. Consent for publication Not applicable. Availability of data and materials ENDES microdata and documentation are publicly available from INEI (https://www.inei.gob.pe/) and the DHS Program (https://dhsprogram.com/). Administrative supply-side data were obtained from MINSA (https://www.gob.pe/minsa) and MEF (https://www.mef.gob.pe/). Competing interests The authors declare no competing interests. Funding No external funding. Authors’ contributions PF and DQ contributed equally. PF: conceptualization; methodology; data acquisition/curation (ENDES, administrative sources); empowerment indicators; model specification; statistical analysis and assumption checks; interpretation; tables/figures; writing—Introduction/Methods/Discussion; critical revision and editing; project administration. DQ: conceptualization; methodology; integration of supply variables (MINSA/MEF) and linkage to microdata; coding, reproducibility, and code audit; main estimation and robustness checks; psychometric verification (Cronbach’s α, PCA); literature review and reference normalization; writing—Abstract/Results/Conclusions; submission materials and compliance with journal policies. Both authors approved the final manuscript and are accountable for the work. Acknowledgements ------- References Browning M, Chiappori PA. Efficient intra-household allocations: a general characterization and empirical tests. Econometrica. 1998;66(6):1241–1278. Rasul I. 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Soc Sci Med. 2014;115:111–120. Staveteig S, Mallick L, Winter R. Uptake and discontinuation of long-acting reversible contraceptives (LARCs) in low-income countries. DHS Analytical Studies. 2015;54:1–64. Darroch JE, Sedgh G, Ball H. Contraceptive technologies: responding to women’s needs. Guttmacher Institute; 2011. Sedgh G, Ashford LS, Hussain R. Unmet need for contraception in developing countries: examining women’s reasons for not using. Guttmacher Institute; 2016. Tables Table 1. Study variables: operational definitions and data sources (ENDES/DHS Peru 2015–2018) VARIABLES Description Source Dependent variables Modern contraceptive use¹ Indicates whether the respondent is currently using any modern contraceptive method² (women aged 15–49 years). Binary: 1=yes, 0=no. ENDES Woman-controlled contraceptive use¹ Indicates whether the respondent is currently using a contraceptive method primarily under the woman’s control: pill, injectable, IUD, implant, female sterilization, and emergency contraception (women aged 15–49 years). Binary: 1=yes, 0=no. ENDES Couple-controlled contraceptive use¹ Indicates whether the respondent is currently using a contraceptive method typically decided by the woman and her partner: condom, male sterilization, periodic abstinence, and withdrawal (women aged 15–49 years). Binary: 1=yes, 0=no. ENDES Empowerment independent variables Indicator 1 Decision-making over household resources³. Three-level categorical variable: 1=low, 2=medium, 3=high empowerment. ENDES Indicator 2 Freedom of movement³. Three-level categorical variable: 1=low, 2=medium, 3=high empowerment. ENDES Indicator 3 Partner respect for the woman’s opinions, desires, and rights³. Three-level categorical variable: 1=low, 2=medium, 3=high empowerment. ENDES Indicator 4 Decision-making over one’s own health³. Three-level categorical variable: 1=low, 2=medium, 3=high empowerment. ENDES Control variables Woman-level variables Age Age of the woman (years). ENDES Age × Age Age of the woman squared. ENDES Education Highest educational level completed by the woman. Four categories: 1=no education, 2=primary, 3=secondary, 4=higher. ENDES Marital status Marital status of the woman. Binary: 1=married, 0=cohabiting. ENDES Employment Whether the woman was working at the time of interview. Binary: 1=yes, 0=no. ENDES Ethnicity Whether the woman self-identifies as of Indigenous origin⁴. Binary: 1=yes, 0=no. ENDES Disability Whether the woman reports any permanent disability⁵. Binary: 1=yes, 0=no. ENDES Health insurance Health insurance coverage. Three categories: 0=no insurance, 1=SIS, 2=private insurance/EsSalud/other. ENDES Health status Whether the woman sought care in the last 12 months due to a health problem. Binary: 1=yes, 0=no. ENDES No knowledge Whether the woman does not know where to go when she gets sick and wants advice/treatment. Binary: 1=yes, 0=no. ENDES Household-level variables Wealth quintile Household wealth index quintile. Five categories: 1=poorest, 2=poor, 3=middle, 4=rich, 5=richest. ENDES Household size Total number of household members. ENDES Partner’s age Age of the partner (years). ENDES Partner’s education Highest educational level completed by the partner. Four categories: 1=no education, 2=primary, 3=secondary, 4=higher. ENDES Partner lives in the household Whether the partner lives in the same household as the woman. Binary: 1=yes, 0=no. ENDES Health services variables Public health expenditure⁶ Department-level public health expenditure per capita (PEN). MEF Physicians⁶ Number of physicians per 1,000 inhabitants at the province level. MINSA Nurses⁶ Number of nurses per 1,000 inhabitants at the province level. MINSA Health facilities⁶ Number of health facilities per 1,000 inhabitants at the province level. MINSA Maximum facility level Highest facility level available in the province. Three categories: 1=health center/health post, 2=Type I–II hospital, 3=specialized institute/Type III hospital. MINSA Lack of female staff (barrier) Whether the woman reports lack of female staff in the facility as a problem. Binary: 1=yes, 0=no. ENDES Distance (barrier) Whether the woman reports distance to the facility as a problem. Binary: 1=yes, 0=no. ENDES Geographic variables Area Area of residence. Binary: 1=urban, 0=rural. ENDES Natural region Natural region. Four categories: 1=Metropolitan Lima, 2=rest of the Coast, 3=Highlands, 4=Jungle. ENDES Department⁷ Department of residence (24 categories). ENDES Year Survey year: 2015–2018. ENDES Notes: ¹ Women who at the time of interview were pregnant or reported wanting to become pregnant are excluded from the analytic sample. ² Modern methods include: pill, IUD, injection, implant, male condom, vaginal methods (foam, jelly, suppository), lactational amenorrhea method, emergency contraception, female condom, female sterilization, and male sterilization. ³ For details on empowerment index construction, see the Methods section. ⁴ Ethnicity is defined by self-identification; “Indigenous” refers to identifying with a pre-Hispanic Indigenous people. Those identifying as Black/Afro-descendant, moreno, zambo, White, or mestizo are classified as non-Indigenous; this group represents a small share (<1%) and their health indicators more closely resemble the non-Indigenous category. ⁵ Permanent limitations include difficulties in: mobility, seeing, hearing, speaking, understanding, and relating to others. ⁶ Variables were transformed to per-capita or per-1,000 population terms using INEI population denominators. ⁷ The Department of Lima includes the Province of Callao. Peru has 24 departments/regions (first-level subnational unit) and 196 provinces (second-level subnational unit). Source: Authors’ elaboration. Table 2. Prevalence of contraceptive use among partnered women (ENDES/DHS Peru 2015–2018): modern methods, woman-controlled methods, and couple-controlled methods (%) Modern methods (%) Woman-controlled (%) Couple-controlled (%) Total 60% 44% 39% Age 15-24 70% 54% 35% 25-34 67% 50% 39% 35-49 51% 37% 39% Education (woman) No education 40% 36% 32% Primary 52% 46% 34% Secondary 63% 46% 39% Higher 65% 41% 43% Woman employed No 63% 48% 36% Yes 58% 42% 40% Partner’s education No education 47% 44% 22% Primary 53% 46% 34% Secondary 62% 46% 39% Higher 63% 39% 44% Partner lives in household No 45% 34% 31% Yes 62% 45% 39% Wealth quintile Quintile 1 52% 46% 34% Quintile 2 61% 47% 38% Quintile 3 62% 45% 40% Quintile 4 64% 41% 42% Quintile 5 64% 41% 42% Area Urban 63% 44% 40% Rural 54% 46% 35% Indigenous No 62% 45% 39% Yes 42% 37% 37% Source: Authors’ elaboration using ENDES (2015–2018). Table 3. Average marginal effects of women’s empowerment on contraceptive use (ENDES/DHS Peru 2015–2018): survey-weighted logistic models VARIABLES Modern methods Woman-controlled Couple-controlled Sig. EM (%) Sig. EM (%) Sig. EM (%) Indicator 1: Medium 0.20 * 2.60 ** -3.80 Indicator 1: High ** -2.20 -1.30 -1.40 Indicator 2: Medium * 1.30 ** 1.30 ** -2.10 Indicator 2: High -0.40 1.20 *** -5.80 Indicator 3: Medium *** 3.10 0.40 ** 4.10 Indicator 3: High 1.30 -1.60 *** 4.90 Indicator 4: Medium *** 5.40 *** 4.60 -0.50 Indicator 4: High *** 7.90 *** 6.70 -1.40 Age *** 2.00 *** 1.60 *** 4.00 Age × Age *** 0.00 *** 0.00 *** -0.10 Education: Primary (ref: none) ** 6.10 ** 6.90 -1.10 Education: Secondary (ref: none) *** 8.00 4.20 1.70 Education: Higher (ref: none) *** 9.10 3.20 1.90 Marital status (married) 0.70 -0.20 0.30 Employment ** -1.30 ** -1.70 *** 3.10 Indigenous 3.80 0.20 1.20 Disability *** 11.30 * 7.10 0.20 Insurance: SIS (ref: none) *** 7.30 *** 7.70 *** -5.40 Insurance: Other (ref: none) ** 4.30 *** 3.20 ** -3.70 Health status 1.10 0.70 ** -2.60 No knowledge * 1.40 0.50 -0.40 Wealth quintile 2 (ref: 1) *** 5.60 ** 3.20 0.30 Wealth quintile 3 (ref: 1) ** 5.20 * 3.40 0.50 Wealth quintile 4 (ref: 1) *** 6.40 2.20 1.20 Wealth quintile 5 (ref: 1) * 5.60 ** 5.40 -0.50 Household size *** 1.80 *** 2.20 *** -1.40 Partner’s age 1.70 1.50 2.20 Partner’s education: Primary (ref: none) - - - Partner’s education: Secondary (ref: none) - - - Partner’s education: Higher (ref: none) - - - Partner lives in household *** 12.90 *** 8.60 *** 11.40 Public health expenditure 0.00 0.00 0.00 Physicians -3.30 0.00 -6.30 Nurses 1.00 -1.20 3.10 Health facilities -0.20 -0.10 0.50 Max facility level II (ref: I) 3.90 3.30 -0.80 Max facility level III (ref: I) 2.20 -1.70 3.40 Lack of female staff (barrier) ** -2.60 ** -3.00 * 1.60 Distance (barrier) ** -2.80 ** -2.10 0.10 Urban area -0.60 ** -3.50 2.90 Natural region FE Yes Yes Yes Department FE Yes Yes Yes Year FE Yes Yes Yes AME = average marginal effect (percentage points). *** p<0.01, ** p<0.05, * p<0.10. Table 4. Psychometric properties of empowerment indices (ENDES/DHS Peru 2015–2018): Cronbach’s alpha and variance explained (PCA) Indicator 1: Decision-making over household resources 2015 2016 2017 2018 2015-2018 Mean 0.00 0.02 0.02 0.03 0.02 Standard deviation 1.04 1.02 1.01 0.96 1.02 Minimum -2.01 -2.01 -2.01 -2.01 -2.01 Maximum 2.69 2.69 2.69 2.69 2.69 Observations 8440 8286 8545 4183 29454 Cronbach’s alpha 0.30 0.31 0.28 0.24 0.29 Variance explained 0.42 Indicator 2: Freedom of movement 2015 2016 2017 2018 2015-2018 Mean -0.08 -0.01 -0.01 0.13 -0.01 Standard deviation 1.04 0.99 1.01 0.94 1.00 Minimum -3.34 -3.34 -3.34 -3.34 -3.34 Maximum 0.59 0.59 0.59 0.59 0.59 Observations 8440 8286 8545 4183 29454 Cronbach’s alpha 0.34 0.34 0.34 0.32 0.34 Variance explained 0.44 Indicator 3: Partner respect for opinions, desires, and rights 2015 2016 2017 2018 2015-2018 Mean 0.02 0.04 0.05 -0.01 0.03 Standard deviation 0.98 0.98 0.97 1.01 0.98 Minimum -3.68 -3.68 -3.68 -3.68 -3.68 Maximum 0.68 0.68 0.68 0.68 0.68 Observations 8440 8286 8545 4183 29454 Cronbach’s alpha 0.83 0.83 0.84 0.85 0.84 Variance explained 0.76 Source: Authors’ elaboration. Additional Declarations No competing interests reported. Cite Share Download PDF Status: Posted Version 1 posted You are reading this latest preprint version Research Square lets you share your work early, gain feedback from the community, and start making changes to your manuscript prior to peer review in a journal. As a division of Research Square Company, we’re committed to making research communication faster, fairer, and more useful. We do this by developing innovative software and high quality services for the global research community. Our growing team is made up of researchers and industry professionals working together to solve the most critical problems facing scientific publishing. Also discoverable on Platform About Our Team In Review Editorial Policies Advisory Board Help Center Resources Author Services Accessibility API Access RSS feed Manage Cookie Preferences © Research Square 2026 | ISSN 2693-5015 (online) Privacy Policy Terms of Service Do Not Sell My Personal Information {"props":{"pageProps":{"initialData":{"identity":"rs-8818438","acceptedTermsAndConditions":true,"allowDirectSubmit":true,"archivedVersions":[],"articleType":"Research Article","associatedPublications":[],"authors":[{"id":588957378,"identity":"6425d4ed-e878-41cb-b0d8-474efbd18df5","order_by":0,"name":"Pedro Francke","email":"","orcid":"","institution":"Pontifical Catholic University of Peru","correspondingAuthor":false,"prefix":"","firstName":"Pedro","middleName":"","lastName":"Francke","suffix":""},{"id":588957379,"identity":"d429a1a3-c1c0-4a7a-abcb-a188eeac251a","order_by":1,"name":"Diego Quispe","email":"data:image/png;base64,iVBORw0KGgoAAAANSUhEUgAAAZAAAAAyAQMAAABI0h/eAAAABlBMVEX///8AAABVwtN+AAAACXBIWXMAAA7EAAAOxAGVKw4bAAAA7klEQVRIiWNgGAWjYDCCA0CcAGKwNyCJEKeF5wCSCEEtYCCRQKQWvgPM2yQe/Lkjxy/59pjEzx0Mcnw3EtgefMCjRfIAW5lEYtszY8nZeWmSvWcYjCVvJLAbzsCjxeAAj5lEYsPhxA23c8ykGdsYEjcAbZHmIaQl4c/h+g03z4C11IO1/CGohe1wgsENHrAWIAOoBZ/3JQ+zFVsA/WI4sycv2bL3jIThzDMP2w178GjhO9688eaPP3fk+dnPHrzxc4eNPN/x5GMPfuCzhpnBgAESF0AvMzZIABlA5xEAKFrAImyEtIyCUTAKRsHIAgDPMVGm7uN6cAAAAABJRU5ErkJggg==","orcid":"","institution":"Pontifical Catholic University of Peru","correspondingAuthor":true,"prefix":"","firstName":"Diego","middleName":"","lastName":"Quispe","suffix":""}],"badges":[],"createdAt":"2026-02-08 00:38:14","currentVersionCode":1,"declarations":"","doi":"10.21203/rs.3.rs-8818438/v1","doiUrl":"https://doi.org/10.21203/rs.3.rs-8818438/v1","draftVersion":[],"editorialEvents":[],"editorialNote":"","failedWorkflow":false,"files":[],"financialInterests":"No competing interests reported.","formattedTitle":"Women's empowerment, locus of contraceptive decision-making, and modern contraceptive use in Peru","fulltext":[{"header":"Background","content":"\u003cp\u003eUniversal access to contraception is central to sexual and reproductive health and rights (SRHR) and to global commitments such as the Sustainable Development Goals. Yet, modern contraceptive prevalence, method mix, and unmet need remain uneven across settings, even where service coverage has improved [9,15]. Contemporary SRHR guidance increasingly emphasizes self-care interventions and person-centered counseling approaches that can reduce barriers and strengthen women’s ability to enact their fertility preferences [14,15].\u003c/p\u003e\n\u003cp\u003ePeru illustrates this implementation gap. According to ENDES, around 85% of partnered women report wanting to stop childbearing or postpone pregnancy for two or more years, but only about 55% use modern contraceptive methods; additionally, roughly 6% have unmet need for family planning [13]. This mismatch highlights that effective contraceptive use depends not only on supply, but also on intra-household processes that shape decision-making and the feasibility of adopting specific methods.\u003c/p\u003e\n\u003cp\u003eFrom the perspective of collective household models, women’s empowerment can be interpreted as shifts in bargaining weights that influence desired fertility and contraceptive choices [1–3]. Importantly, contraceptive adoption is not only about “use vs non-use”: it may depend on method attributes (such as observability to the partner and the degree of coordination required) so that the same empowerment domain can plausibly shift women toward methods that are primarily under their own control versus methods that typically require couple agreement [2,3]. Empirically, DHS-based empowerment measures (including SWPER and related indices) have been associated with higher modern contraceptive use in multiple contexts, and prior work also highlights the roles of autonomy and couple communication [4–8,10,16–19]. However, most evidence focuses on overall modern contraceptive use and seldom distinguishes explicitly between methods that are predominantly woman-controlled and those that are typically couple-controlled, potentially masking heterogeneous relationships by decision locus. In addition, relatively few applications incorporate supply-side conditions systematically (availability, distance, provider characteristics), which may confound associations between empowerment and contraceptive outcomes [9,20–22].\u003c/p\u003e\n\u003cp\u003eThis study addresses these gaps using ENDES 2015–2018. We examine modern contraceptive use and further classify methods into two groups \u0026nbsp; (those predominantly controlled by the woman and those typically requiring couple coordination) while linking four empowerment domains (household resources, freedom of movement, partner’s respect for opinions/desires/rights, and decision-making over one’s own health) to each contraceptive outcome. We account for survey design, individual and household covariates, fixed effects, and contextual supply measures. By mapping empowerment dimensions onto distinct contraceptive decision margins, our findings aim to inform targeted SRHR counseling and service organization in Peru and comparable settings [4–6,9,14–16].\u003c/p\u003e"},{"header":"Methods","content":"\u003cp\u003e\u003cstrong\u003eData and data processing\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eWe conducted an analytical cross-sectional study using nationally representative Demographic and Health Survey microdata for Peru (DHS/ENDES), pooled for 2015–2018. We additionally incorporated SRH service availability indicators from administrative sources: health facility supply and health workforce counts from the Ministry of Health, and public health expenditure from the Ministry of Economy and Finance. ENDES/DHS provides sampling weights and the complex survey design variables (strata and primary sampling units), which were retained for analysis.\u003c/p\u003e\n\u003cp\u003eThe target population comprised partnered women aged 15–49 years (married or cohabiting). For the contraceptive outcomes, we excluded women who were pregnant at interview and those reporting a current desire to become pregnant. After applying these criteria and harmonizing variables across survey years, the analytical sample for contraceptive outcomes included 27,440 observations.\u003c/p\u003e\n\u003cp\u003eWe defined three binary outcomes of current contraceptive use. First, any modern method, following the standard classification (e.g., female and male sterilization, pill, IUD, injectables, implants, condoms, emergency contraception, lactational amenorrhea method, and other modern methods as applicable in ENDES). Second, woman-controlled methods, defined as methods whose initiation and continuation primarily depend on the woman (pill, injectables, IUD, implant, emergency contraception, and female sterilization). Third, couple-controlled methods, defined as methods that typically require coordination or agreement with the partner, including male/female condoms and male sterilization, and (consistent with the locus-of-control concept) traditional co-managed methods such as periodic abstinence and withdrawal. The full list of methods included in each category is reported in Table 1.\u003c/p\u003e\n\u003cp\u003eWe constructed four empowerment indicators: (1) decision-making over household resources, (2) freedom of movement, (3) partner respect for the woman’s opinions/desires/rights, and (4) decision-making over the woman’s own healthcare. The first three indicators were derived from ENDES items commonly used in DHS-based empowerment measurement. Specifically, household-resources decision-making combines items on participation in major household purchases, relative earnings within the couple, and who decides on the partner’s earnings; freedom of movement combines who decides on visits to relatives and partner control/restriction items; and partner respect captures the reported degree of respect for the woman’s opinions, desires, and rights. For these three domains, we applied principal component analysis (PCA) to the ordinal items, standardized the resulting scores (mean 0, SD 1), and categorized them into terciles (low/medium/high). Internal consistency and variance explained were assessed and are reported in Table 4. The healthcare decision indicator was based on a single item and recoded into three levels: low (partner decides alone), medium (joint decision), and high (woman decides alone).\u003c/p\u003e\n\u003cp\u003eWe adjusted for individual and household characteristics: age (and squared term), parity, woman’s and partner’s education, woman’s employment, household wealth quintile, health insurance coverage, urban/rural residence, natural region, and department of residence. We also included SRH supply measures combining administrative and survey-based proxies: facility density, physician density, and nursing/midwifery density per 1,000 population at the province level; the maximum facility level available in the province; and ENDES self-reported access barriers (perceived distance to a facility and perceived lack of female health personnel). Public health expenditure per capita was measured at the department level and assigned to respondents based on department of residence. Administrative indicators were converted to per-capita or per-1,000 population metrics using official population denominators and linked to ENDES respondents by their reported province and department of residence. Operational definitions and sources for all variables are summarized in Table 1.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eStatistical analysis\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eWe estimated the association between women’s empowerment and contraceptive use using survey-weighted logistic regression models. Three binary outcomes were analyzed separately: (i) current use of any modern contraceptive method, (ii) current use of woman-controlled methods, and (iii) current use of couple-controlled methods (definitions in Table 1). For each outcome, we fitted models that included the four empowerment indicators as the main exposures. Empowerment indicators derived from PCA were entered as terciles (medium and high), using the low tercile as the reference category; the healthcare decision indicator (single item) was also modeled in three levels with “low” (partner decides alone) as the reference.\u003c/p\u003e\n\u003cp\u003eAll models were estimated accounting for the ENDES/DHS complex sampling design (sampling weights, strata, and primary sampling units). We used robust variance estimation clustered at the primary sampling unit level. To facilitate interpretation, we report average marginal effects (AMEs) expressed in percentage points, alongside 95% confidence intervals. Statistical significance was assessed using two-sided tests with conventional thresholds (p\u0026lt;0.10, p\u0026lt;0.05, p\u0026lt;0.01).\u003c/p\u003e\n\u003cp\u003eThe main specification adjusted for a common set of covariates capturing individual and household characteristics (age and age-squared, parity, woman’s education, partner’s education, woman’s employment status, household wealth quintile, health insurance category, urban/rural residence, and additional geographic controls). To reduce confounding from access constraints, we additionally controlled for SRH supply and access measures: province-level densities of facilities and health personnel, the maximum facility level available in the province, and survey-based barriers (perceived distance to a facility and perceived lack of female personnel). We included fixed effects for survey year and department to absorb common time shocks and time-invariant differences across departments. Models were estimated on complete cases for the outcome and the covariates included in each specification; final analytical sample sizes are reported in the tables.\u003c/p\u003e\n\u003cp\u003eWe conducted robustness checks to evaluate the stability of the main associations. These included alternative specifications of the empowerment indicators (e.g., using standardized continuous scores instead of terciles for the PCA-based indices), and alternative sets of controls for SRH supply and geographic factors. Results were considered robust when the direction of effects and the approximate magnitude of the AMEs were stable across specifications. All analyses adhered to DHS/ENDES methodological guidance for pooled multi-year analyses and to standard reporting practices for observational studies using complex survey data.\u003c/p\u003e"},{"header":"Results","content":"\u003cp\u003eThe pooled ENDES 2015–2018 analytic sample included 27,440 women aged 15–49 years who were married or cohabiting, after excluding women who were pregnant at the time of interview or who reported a current desire to become pregnant. In this population, 60% reported using any modern contraceptive method, 44% reported using methods classified as woman-controlled, and 39% reported using couple-controlled methods (Table 2). Prevalence patterns followed expected gradients by sociodemographic characteristics: modern method use was higher among younger women, those with secondary or higher education, women in higher wealth quintiles, and urban residents. Women self-identifying as Indigenous presented lower prevalence of modern method use (42%) and lower use of woman-controlled methods (37%). The gap between woman-controlled and couple-controlled methods was particularly pronounced among women aged 15–24 years (54% vs 35%), suggesting heterogeneity in the locus of contraceptive decision-making across the life course.\u003c/p\u003e\n\u003cp\u003eTable 3 reports average marginal effects (percentage points) from survey-weighted logistic models adjusting for individual and household covariates, SRH supply and access measures, and year and department fixed effects. The empowerment domain most consistently associated with contraceptive outcomes was decision-making over one’s own health. Relative to the low category (partner decides alone), the medium and high levels were associated with higher probability of using modern methods (approximately 5.4 p.p. and 7.9 p.p., respectively; p\u0026lt;0.01) and higher probability of using woman-controlled methods (approximately 4.6 p.p. and 6.7 p.p.; p\u0026lt;0.01). By contrast, this indicator showed no positive association with couple-controlled methods, with small and non-significant coefficients, consistent with a shift toward methods under women’s direct control when clinical agency increases. The partner respect domain (respect for the woman’s opinions, desires, and rights) was positively associated with modern method use at the medium level (approximately 3.1 p.p.; p\u0026lt;0.01) and showed the clearest association with couple-controlled methods (approximately 4.1–4.9 p.p. for medium/high; statistically significant), indicating that improved communication and valuation of women’s preferences may facilitate coordinated methods. Freedom of movement exhibited a non-linear pattern: the medium level was positively associated with modern use and with woman-controlled methods (around 1.3 p.p.), whereas the high level was associated with lower use of couple-controlled methods (around −5.8 p.p.; statistically significant), consistent with substitution away from coordinated methods as autonomy increases. The household resources indicator displayed weak and unstable associations: the high category was negatively associated with modern method use (around −2.2 p.p.; statistically significant), while the medium category was positively associated with woman-controlled methods (around 2.6 p.p.; marginally significant) and negatively associated with couple-controlled methods (around −3.8 p.p.; statistically significant), again suggesting substitution toward woman-controlled options as economic agency increases.\u003c/p\u003e\n\u003cp\u003eAccess constraints behaved as expected. Reporting distance as a barrier was associated with lower use of modern and woman-controlled methods (negative, statistically significant), and reporting lack of female personnel as a barrier was likewise negatively associated with modern and woman-controlled use. Province-level supply measures (densities of facilities and health personnel and maximum facility level) were less consistent in the fully adjusted models, though the overall direction supported the relevance of access conditions. Psychometric results for the composite empowerment indices are summarized in Table 4. The partner respect index showed high internal consistency (Cronbach’s α=0.84) and high explained variance (=0.76), supporting its interpretation as a coherent scale. In contrast, the household resources (α=0.29; explained variance=0.42) and freedom of movement (α=0.34; =0.44) indices showed low internal consistency, consistent with more heterogeneous constructs and motivating interpretation as relative position measures derived from PCA rather than highly homogeneous scales. Overall, the results indicate that empowerment domains map onto distinct margins of contraceptive choice: greater clinical autonomy is most strongly associated with increased use of woman-controlled methods, whereas partner respect is most strongly associated with increased use of couple-controlled methods; aggregating modern methods can partially mask these differentiated patterns.\u003c/p\u003e"},{"header":"Discussion","content":"\u003cp\u003eThis study shows that women’s empowerment is not uniformly associated with “modern contraceptive use” as an aggregate outcome; instead, distinct empowerment domains map onto different margins of contraceptive decision-making once methods are classified by locus of control. The most consistent and policy-relevant pattern is that greater clinical autonomy, captured by decision-making over one’s own health, is associated with higher use of modern methods overall and, specifically, higher use of methods predominantly controlled by the woman, with no corresponding increase in couple-controlled methods. In contrast, partner respect for the woman’s opinions, desires, and rights is most strongly associated with couple-controlled method use, consistent with the idea that interpersonal dynamics and communication facilitate methods that typically require coordination. These differentiated patterns help explain why some empowerment measures can appear weak, unstable, or ambiguous when the outcome is limited to “any modern method,” where opposing movements between woman-controlled and couple-controlled choices may partially offset each other.\u003c/p\u003e\n\u003cp\u003eFrom an intra-household bargaining perspective, the results align with collective models in which empowerment shifts bargaining weights and therefore the household’s reproductive choices, conditional on preferences and constraints [1–3]. Importantly, our classification by decision locus highlights the role of method attributes (particularly the need for coordination, observability, and the extent to which initiation and continuation can be executed by the woman alone) in shaping how empowerment translates into behavior [2–3]. When women’s agency is higher in clinical decisions, the household equilibrium may shift toward methods that the woman can adopt and sustain without requiring ongoing partner agreement (e.g., injectables, IUD, implant, pill), whereas improvements in relationship quality and respect may increase the feasibility and acceptability of methods whose consistent use typically depends on couple cooperation (e.g., condoms) or shared practices.\u003c/p\u003e\n\u003cp\u003eOur findings also speak to a broader empirical literature that links empowerment to contraceptive outcomes using DHS-based measures, including SWPER and related indices. Multi-country work has documented positive associations between empowerment and modern contraceptive use and emphasized autonomy and couple communication as key pathways [4–7,16–19]. Within Peru, recent ENDES-based evidence using SWPER similarly reports that lower empowerment is associated with lower modern contraceptive use [10], and related epidemiological work identifies correlates of highly effective method use in the Peruvian context [11]. The contribution of the present analysis is to unpack the aggregate modern-method association by showing that different empowerment domains align with different contraceptive margins: clinical autonomy is most predictive of woman-controlled method use, while partner respect is most predictive of couple-controlled method use. This distinction is directly relevant for counseling and program design because it informs not only whether modern contraceptive use might rise, but which methods are more likely to be taken up under different empowerment profiles.\u003c/p\u003e\n\u003cp\u003eA second implication is that supply-side barriers remain consequential even after adjusting for empowerment and socioeconomic characteristics. Self-reported barriers related to distance and lack of female personnel were negatively associated with contraceptive use outcomes, consistent with the notion that agency is exercised within a constraint set shaped by service accessibility and acceptability. This is consistent with global guidance emphasizing person-centered counseling, reduction of access barriers, and self-care approaches that can lower transaction costs and improve continuity of use [14–15]. In practical terms, programs aiming to promote self-administered or less partner-dependent methods must still ensure that women can obtain methods reliably, receive appropriate counseling, and manage side effects and discontinuation risks, especially for long-acting methods where discontinuation dynamics can be substantial [20]. The combination of empowerment-sensitive counseling with concrete service delivery improvements is therefore central to moving from stated fertility preferences to effective use.\u003c/p\u003e\n\u003cp\u003eMeasurement considerations are important for interpreting domain-specific results. The “partner respect” index exhibited strong psychometric performance, supporting its interpretation as a coherent relational construct. By contrast, “resources decision-making” and “freedom of movement” showed low internal consistency, suggesting these indices capture more heterogeneous behaviors and norms and should be interpreted as relative position measures rather than tightly unified scales. This heterogeneity likely contributes to the weaker and less stable associations observed for these domains. In addition, the “decision over own health” indicator is a single item and is conceptually close to contraceptive behavior; it plausibly captures a particularly relevant facet of agency for SRH decisions, but its proximity also raises the possibility that it partially reflects unobserved couple dynamics or service interactions tightly linked to contraception. The strong association observed for this domain should therefore be read as a robust empirical relationship, while recognizing that the underlying mechanisms may combine empowerment, negotiation, and health-system contact.\u003c/p\u003e\n\u003cp\u003eSeveral limitations should be acknowledged. First, the analysis is cross-sectional (pooled across years) and observational; residual confounding and reverse causality remain possible. Women who adopt certain methods may experience changes in perceived agency or relationship dynamics, and unobserved factors, such as partner preferences, fertility intentions beyond the exclusion criteria, or community norms, could influence both empowerment measures and contraceptive outcomes. Second, the locus-of-control classification, while substantively motivated, inevitably simplifies real-world decision-making; some methods may be jointly discussed yet practically controlled by one partner, and reporting may reflect social desirability or recall issues. Third, while we incorporated multiple supply proxies, administrative measures are aggregated and may not fully capture quality, stockouts, provider behavior, or method availability at the point of care; such mismeasurement can attenuate estimated associations.\u003c/p\u003e\n\u003cp\u003eDespite these limitations, the study has notable strengths: nationally representative DHS/ENDES microdata across multiple years; explicit correction for complex survey design; a multidimensional empowerment framework; incorporation of both administrative and self-reported supply/access measures; and a conceptually grounded decomposition of contraceptive outcomes by decision locus. Together, these elements provide a clearer interpretation of how empowerment may translate into contraceptive behavior.\u003c/p\u003e\n\u003cp\u003eThe policy implications follow directly from the differentiated patterns. First, counseling and service organization should incorporate empowerment profiles: when clinical autonomy is low, interventions that strengthen women’s decision-making capacity and reduce barriers to confidential access may be especially relevant for woman-controlled methods; when relationship respect and communication are low, strategies that address couple dynamics, respectful partner engagement, and communication may be critical for methods requiring coordination [4–7,16–19]. Second, expanding access to self-administered options and ensuring person-centered counseling can help translate agency into sustained use, but these efforts must be paired with improvements in access and acceptability, including female personnel availability and reduced travel burdens [14–15]. Finally, future research should leverage quasi-experimental variation in method availability, counseling intensity, or service expansions to better identify causal effects and to understand how empowerment interacts with supply-side changes in shaping contraceptive trajectories.\u003c/p\u003e"},{"header":"Conclusions","content":"\u003cp\u003eIn Peru, women’s empowerment is associated with contraceptive use in ways that depend on the locus of decision. Decision-making autonomy over one’s own health is consistently linked to higher use of modern contraception, driven primarily by increased uptake of woman-controlled methods. In contrast, partner respect for women’s opinions, desires, and rights is most strongly associated with couple-controlled methods, suggesting that relational dynamics and communication facilitate choices requiring coordination.\u003c/p\u003e\n\u003cp\u003eThese findings imply that treating “modern contraceptive use” as a single outcome can mask meaningful heterogeneity across method types. Sexual and reproductive health programs should align counseling and service organization with women’s empowerment profiles: expand and support access to woman-controlled and self-administered options for women with greater clinical autonomy, while strengthening couple communication and respectful partner engagement to support coordinated methods. Reducing access barriers, especially perceived distance and lack of female personnel, remains important to translate preferences into effective use.\u003c/p\u003e"},{"header":"Abbreviations","content":"\u003cp\u003eDHS: Demographic and Health Surveys; ENDES: Encuesta Demogr\u0026aacute;fica y de Salud Familiar; SRH: Sexual and Reproductive Health; LAM: Lactational Amenorrhea Method; PCA: Principal Components Analysis; PSU: Primary Sampling Unit; CI: Confidence Interval\u003c/p\u003e"},{"header":"Declarations","content":"\u003cp\u003e\u003cstrong\u003eEthics approval and consent to participate\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eENDES/DHS protocols and tools were approved by the ICF Institutional Review Board and relevant national ethics boards in Peru. The authors analyzed de-identified, publicly available microdata under data-use agreements; no additional approval was required by PUCP. All respondents provided informed consent at the time of the surveys.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eConsent for publication\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eNot applicable.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eAvailability of data and materials\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003e\u0026nbsp;ENDES microdata and documentation are publicly available from INEI (https://www.inei.gob.pe/) and the DHS Program (https://dhsprogram.com/). Administrative supply-side data were obtained from MINSA (https://www.gob.pe/minsa) and MEF (https://www.mef.gob.pe/).\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eCompeting interests\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eThe authors declare no competing interests.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eFunding\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eNo external funding.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eAuthors’ contributions\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003ePF and DQ contributed equally. PF: conceptualization; methodology; data acquisition/curation (ENDES, administrative sources); empowerment indicators; model specification; statistical analysis and assumption checks; interpretation; tables/figures; writing—Introduction/Methods/Discussion; critical revision and editing; project administration. DQ: conceptualization; methodology; integration of supply variables (MINSA/MEF) and linkage to microdata; coding, reproducibility, and code audit; main estimation and robustness checks; psychometric verification (Cronbach’s α, PCA); literature review and reference normalization; writing—Abstract/Results/Conclusions; submission materials and compliance with journal policies. Both authors approved the final manuscript and are accountable for the work.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eAcknowledgements\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003e-------\u003c/p\u003e"},{"header":"References","content":"\u003col\u003e\n\u003cli\u003eBrowning M, Chiappori PA. Efficient intra-household allocations: a general characterization and empirical tests. Econometrica. 1998;66(6):1241\u0026ndash;1278.\u003c/li\u003e\n\u003cli\u003eRasul I. Household bargaining over fertility: theory and evidence from Malaysia. J Dev Econ. 2008;86(2):215\u0026ndash;241.\u003c/li\u003e\n\u003cli\u003eAshraf N, Field E, Lee J. Household bargaining and excess fertility: an experimental study in Zambia. Am Econ Rev. 2014;104(7):2210\u0026ndash;2237.\u003c/li\u003e\n\u003cli\u003eEwerling F, Lynch JW, Victora CG, van Eerdewijk A, Tyszler M, Barros AJD. The SWPER Global index: a multi-country measure of women\u0026rsquo;s empowerment based on DHS data. J Glob Health. 2020;10(1):010121.\u003c/li\u003e\n\u003cli\u003eEwerling F, Barros AJD, Hussain Z, et al. Women\u0026rsquo;s empowerment and fertility and contraception in sub-Saharan Africa: development and validation of a DHS-based index. Lancet Glob Health. 2017;5(12):e1226\u0026ndash;e1237.\u003c/li\u003e\n\u003cli\u003eEfendi F, Hadisuyatmana S, Kuswanto H, et al. Women\u0026rsquo;s empowerment and modern contraceptive use in Southeast Asia: a multi-country analysis. PLoS One. 2023;18(7):e0288517.\u003c/li\u003e\n\u003cli\u003eChalla S, Manu A, Morhe E, Dalton VK, Loll D, Dozier J, et al. Women\u0026rsquo;s autonomy, communication with partners, and modern contraceptive use: a cross-sectional analysis across 33 countries. PLoS One. 2020;15(3):e0226522.\u003c/li\u003e\n\u003cli\u003eBhushan NL, Khan ME, Verma R. Couple communication and contraceptive behaviours among adolescents and young women: evidence from LMICs. Front Reprod Health. 2021;3:669500.\u003c/li\u003e\n\u003cli\u003eHaakenstad A, Moses M, Tao T, et al. Modern contraceptive prevalence and method mix, 1990\u0026ndash;2019: a systematic analysis. Lancet. 2022;399(10331):1643\u0026ndash;1660.\u003c/li\u003e\n\u003cli\u003eChuman S\u0026aacute;nchez M, Huam\u0026aacute;n Rodr\u0026iacute;guez N, Vel\u0026aacute;squez Huam\u0026aacute;n V, et al. Women\u0026rsquo;s empowerment and modern contraceptive use in Peru: analysis of the 2022 ENDES using SWPER Global. SSM Popul Health. 2024;25:101631.\u003c/li\u003e\n\u003cli\u003eSoriano Moreno DR, Nivela Correa R, Hidalgo Lozada NA, et al. Factors associated with highly effective contraceptive methods among Peruvian women of reproductive age. Eur J Obstet Gynecol Reprod Biol. 2020;254:210\u0026ndash;216.\u003c/li\u003e\n\u003cli\u003eThe DHS Program. Demographic and Health Surveys: model questionnaires and methodology. Rockville (MD): ICF; 2019.\u003c/li\u003e\n\u003cli\u003eInstituto Nacional de Estad\u0026iacute;stica e Inform\u0026aacute;tica (INEI). ENDES 2015\u0026ndash;2018: microdata and documentation. Lima: INEI; 2016\u0026ndash;2019.\u003c/li\u003e\n\u003cli\u003eWorld Health Organization. WHO consolidated guideline on self-care interventions for health: sexual and reproductive health and rights. Geneva: WHO; 2022.\u003c/li\u003e\n\u003cli\u003eWHO, Johns Hopkins Bloomberg School of Public Health. Family planning: a global handbook for providers. 4th ed. Baltimore and Geneva: CCP and WHO; 2022.\u003c/li\u003e\n\u003cli\u003eJejeebhoy SJ. Women\u0026rsquo;s empowerment and reproductive health: pathways and evidence. Popul Dev Rev. 2024;50(2):381\u0026ndash;404.\u003c/li\u003e\n\u003cli\u003eDo M, Kurimoto N. Women\u0026rsquo;s empowerment and choice of contraceptive methods in developing countries. BMC Womens Health. 2012;12:13.\u003c/li\u003e\n\u003cli\u003ePrata N, Fraser A, Huchko MJ, Gipson JD, Withers M, Lewis S, et al. Women\u0026rsquo;s empowerment and family planning: a review of the literature. J Biosoc Sci. 2017;49(6):713\u0026ndash;743.\u003c/li\u003e\n\u003cli\u003eUpadhyay UD, Gipson JD, Withers M, et al. Women\u0026rsquo;s empowerment and fertility: a review of the literature. Soc Sci Med. 2014;115:111\u0026ndash;120.\u003c/li\u003e\n\u003cli\u003eStaveteig S, Mallick L, Winter R. Uptake and discontinuation of long-acting reversible contraceptives (LARCs) in low-income countries. DHS Analytical Studies. 2015;54:1\u0026ndash;64.\u003c/li\u003e\n\u003cli\u003eDarroch JE, Sedgh G, Ball H. Contraceptive technologies: responding to women\u0026rsquo;s needs. Guttmacher Institute; 2011.\u003c/li\u003e\n\u003cli\u003eSedgh G, Ashford LS, Hussain R. Unmet need for contraception in developing countries: examining women\u0026rsquo;s reasons for not using. Guttmacher Institute; 2016.\u003c/li\u003e\n\u003c/ol\u003e"},{"header":"Tables","content":"\u003cp\u003e\u003cstrong\u003eTable 1. Study variables: operational definitions and data sources (ENDES/DHS Peru 2015\u0026ndash;2018)\u003c/strong\u003e\u003c/p\u003e\n\u003ctable border=\"1\" cellspacing=\"0\" cellpadding=\"0\" width=\"577\"\u003e\n \u003ctbody\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 16.3493%;\"\u003e\n \u003cp\u003e\u003cstrong\u003eVARIABLES\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 46.7317%;\"\u003e\n \u003cp\u003e\u003cstrong\u003eDescription\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 14.4419%;\"\u003e\n \u003cp\u003e\u003cstrong\u003eSource\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd colspan=\"3\" valign=\"top\" style=\"width: 78.4765%;\"\u003e\n \u003cp\u003e\u003cstrong\u003eDependent variables\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 16.3493%;\"\u003e\n \u003cp\u003eModern contraceptive use\u0026sup1;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 46.7317%;\"\u003e\n \u003cp\u003eIndicates whether the respondent is currently using any modern contraceptive method\u0026sup2; (women aged 15\u0026ndash;49 years). Binary: 1=yes, 0=no.\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 14.4419%;\"\u003e\n \u003cp\u003eENDES\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 16.3493%;\"\u003e\n \u003cp\u003eWoman-controlled contraceptive use\u0026sup1;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 46.7317%;\"\u003e\n \u003cp\u003eIndicates whether the respondent is currently using a contraceptive method primarily under the woman\u0026rsquo;s control: pill, injectable, IUD, implant, female sterilization, and emergency contraception (women aged 15\u0026ndash;49 years). Binary: 1=yes, 0=no.\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 14.4419%;\"\u003e\n \u003cp\u003eENDES\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 16.3493%;\"\u003e\n \u003cp\u003eCouple-controlled contraceptive use\u0026sup1;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 46.7317%;\"\u003e\n \u003cp\u003eIndicates whether the respondent is currently using a contraceptive method typically decided by the woman and her partner: condom, male sterilization, periodic abstinence, and withdrawal (women aged 15\u0026ndash;49 years). Binary: 1=yes, 0=no.\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 14.4419%;\"\u003e\n \u003cp\u003eENDES\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd colspan=\"2\" valign=\"top\" style=\"width: 63.0809%;\"\u003e\n \u003cp\u003e\u003cstrong\u003eEmpowerment independent variables\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 15.3956%;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 16.3493%;\"\u003e\n \u003cp\u003eIndicator 1\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 46.7317%;\"\u003e\n \u003cp\u003eDecision-making over household resources\u0026sup3;. Three-level categorical variable: 1=low, 2=medium, 3=high empowerment.\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 14.4419%;\"\u003e\n \u003cp\u003eENDES\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 16.3493%;\"\u003e\n \u003cp\u003eIndicator 2\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 46.7317%;\"\u003e\n \u003cp\u003eFreedom of movement\u0026sup3;. Three-level categorical variable: 1=low, 2=medium, 3=high empowerment.\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 14.4419%;\"\u003e\n \u003cp\u003eENDES\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 16.3493%;\"\u003e\n \u003cp\u003eIndicator 3\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 46.7317%;\"\u003e\n \u003cp\u003ePartner respect for the woman\u0026rsquo;s opinions, desires, and rights\u0026sup3;. Three-level categorical variable: 1=low, 2=medium, 3=high empowerment.\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 14.4419%;\"\u003e\n \u003cp\u003eENDES\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 16.3493%;\"\u003e\n \u003cp\u003eIndicator 4\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 46.7317%;\"\u003e\n \u003cp\u003eDecision-making over one\u0026rsquo;s own health\u0026sup3;. Three-level categorical variable: 1=low, 2=medium, 3=high empowerment.\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 14.4419%;\"\u003e\n \u003cp\u003eENDES\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd colspan=\"3\" valign=\"bottom\" style=\"width: 78.4765%;\"\u003e\n \u003cp\u003e\u003cstrong\u003eControl variables \u0026nbsp; \u0026nbsp; \u0026nbsp;\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd colspan=\"3\" valign=\"top\" style=\"width: 78.4765%;\"\u003e\n \u003cp\u003e\u003cem\u003eWoman-level variables\u003c/em\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 16.3493%;\"\u003e\n \u003cp\u003eAge\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 46.7317%;\"\u003e\n \u003cp\u003eAge of the woman (years).\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 14.4419%;\"\u003e\n \u003cp\u003eENDES\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 16.3493%;\"\u003e\n \u003cp\u003eAge \u0026times; Age\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 46.7317%;\"\u003e\n \u003cp\u003eAge of the woman squared.\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 14.4419%;\"\u003e\n \u003cp\u003eENDES\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 16.3493%;\"\u003e\n \u003cp\u003eEducation\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 46.7317%;\"\u003e\n \u003cp\u003eHighest educational level completed by the woman. Four categories: 1=no education, 2=primary, 3=secondary, 4=higher.\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 14.4419%;\"\u003e\n \u003cp\u003eENDES\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 16.3493%;\"\u003e\n \u003cp\u003eMarital status\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 46.7317%;\"\u003e\n \u003cp\u003eMarital status of the woman. Binary: 1=married, 0=cohabiting.\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 14.4419%;\"\u003e\n \u003cp\u003eENDES\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 16.3493%;\"\u003e\n \u003cp\u003eEmployment\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 46.7317%;\"\u003e\n \u003cp\u003eWhether the woman was working at the time of interview. Binary: 1=yes, 0=no.\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 14.4419%;\"\u003e\n \u003cp\u003eENDES\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 16.3493%;\"\u003e\n \u003cp\u003eEthnicity\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 46.7317%;\"\u003e\n \u003cp\u003eWhether the woman self-identifies as of Indigenous origin⁴. Binary: 1=yes, 0=no.\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 14.4419%;\"\u003e\n \u003cp\u003eENDES\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 16.3493%;\"\u003e\n \u003cp\u003eDisability\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 46.7317%;\"\u003e\n \u003cp\u003eWhether the woman reports any permanent disability⁵. Binary: 1=yes, 0=no.\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 14.4419%;\"\u003e\n \u003cp\u003eENDES\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 16.3493%;\"\u003e\n \u003cp\u003eHealth insurance\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 46.7317%;\"\u003e\n \u003cp\u003eHealth insurance coverage. Three categories: 0=no insurance, 1=SIS, 2=private insurance/EsSalud/other.\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 14.4419%;\"\u003e\n \u003cp\u003eENDES\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 16.3493%;\"\u003e\n \u003cp\u003eHealth status\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 46.7317%;\"\u003e\n \u003cp\u003eWhether the woman sought care in the last 12 months due to a health problem. Binary: 1=yes, 0=no.\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 14.4419%;\"\u003e\n \u003cp\u003eENDES\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 16.3493%;\"\u003e\n \u003cp\u003eNo knowledge\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 46.7317%;\"\u003e\n \u003cp\u003eWhether the woman does not know where to go when she gets sick and wants advice/treatment. Binary: 1=yes, 0=no.\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 14.4419%;\"\u003e\n \u003cp\u003eENDES\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 16.3493%;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 46.7317%;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 14.4419%;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd colspan=\"3\" valign=\"top\" style=\"width: 78.4765%;\"\u003e\n \u003cp\u003e\u003cem\u003eHousehold-level variables\u003c/em\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 16.3493%;\"\u003e\n \u003cp\u003eWealth quintile\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 46.7317%;\"\u003e\n \u003cp\u003eHousehold wealth index quintile. Five categories: 1=poorest, 2=poor, 3=middle, 4=rich, 5=richest.\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 14.4419%;\"\u003e\n \u003cp\u003eENDES\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 16.3493%;\"\u003e\n \u003cp\u003eHousehold size\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 46.7317%;\"\u003e\n \u003cp\u003eTotal number of household members.\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 14.4419%;\"\u003e\n \u003cp\u003eENDES\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 16.3493%;\"\u003e\n \u003cp\u003ePartner\u0026rsquo;s age\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 46.7317%;\"\u003e\n \u003cp\u003eAge of the partner (years).\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 14.4419%;\"\u003e\n \u003cp\u003eENDES\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 16.3493%;\"\u003e\n \u003cp\u003ePartner\u0026rsquo;s education\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 46.7317%;\"\u003e\n \u003cp\u003eHighest educational level completed by the partner. Four categories: 1=no education, 2=primary, 3=secondary, 4=higher.\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 14.4419%;\"\u003e\n \u003cp\u003eENDES\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 16.3493%;\"\u003e\n \u003cp\u003ePartner lives in the household\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 46.7317%;\"\u003e\n \u003cp\u003eWhether the partner lives in the same household as the woman. Binary: 1=yes, 0=no.\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 14.4419%;\"\u003e\n \u003cp\u003eENDES\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 16.3493%;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 46.7317%;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 14.4419%;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd colspan=\"3\" valign=\"top\" style=\"width: 78.4765%;\"\u003e\n \u003cp\u003e\u003cem\u003eHealth services variables\u003c/em\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 16.3493%;\"\u003e\n \u003cp\u003ePublic health expenditure⁶\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 46.7317%;\"\u003e\n \u003cp\u003eDepartment-level public health expenditure per capita (PEN).\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 14.4419%;\"\u003e\n \u003cp\u003eMEF\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 16.3493%;\"\u003e\n \u003cp\u003ePhysicians⁶\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 46.7317%;\"\u003e\n \u003cp\u003eNumber of physicians per 1,000 inhabitants at the province level.\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 14.4419%;\"\u003e\n \u003cp\u003eMINSA\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 16.3493%;\"\u003e\n \u003cp\u003eNurses⁶\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 46.7317%;\"\u003e\n \u003cp\u003eNumber of nurses per 1,000 inhabitants at the province level.\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 14.4419%;\"\u003e\n \u003cp\u003eMINSA\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 16.3493%;\"\u003e\n \u003cp\u003eHealth facilities⁶\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 46.7317%;\"\u003e\n \u003cp\u003eNumber of health facilities per 1,000 inhabitants at the province level.\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 14.4419%;\"\u003e\n \u003cp\u003eMINSA\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 16.3493%;\"\u003e\n \u003cp\u003eMaximum facility level\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 46.7317%;\"\u003e\n \u003cp\u003eHighest facility level available in the province. Three categories: 1=health center/health post, 2=Type I\u0026ndash;II hospital, 3=specialized institute/Type III hospital.\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 14.4419%;\"\u003e\n \u003cp\u003eMINSA\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 16.3493%;\"\u003e\n \u003cp\u003eLack of female staff (barrier)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 46.7317%;\"\u003e\n \u003cp\u003eWhether the woman reports lack of female staff in the facility as a problem. Binary: 1=yes, 0=no.\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 14.4419%;\"\u003e\n \u003cp\u003eENDES\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 16.3493%;\"\u003e\n \u003cp\u003eDistance (barrier)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 46.7317%;\"\u003e\n \u003cp\u003eWhether the woman reports distance to the facility as a problem. Binary: 1=yes, 0=no.\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 14.4419%;\"\u003e\n \u003cp\u003eENDES\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 16.3493%;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 46.7317%;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 14.4419%;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd colspan=\"3\" valign=\"top\" style=\"width: 78.4765%;\"\u003e\n \u003cp\u003e\u003cem\u003eGeographic variables\u003c/em\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 16.3493%;\"\u003e\n \u003cp\u003eArea\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 46.7317%;\"\u003e\n \u003cp\u003eArea of residence. Binary: 1=urban, 0=rural.\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 14.4419%;\"\u003e\n \u003cp\u003eENDES\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 16.3493%;\"\u003e\n \u003cp\u003eNatural region\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 46.7317%;\"\u003e\n \u003cp\u003eNatural region. Four categories: 1=Metropolitan Lima, 2=rest of the Coast, 3=Highlands, 4=Jungle.\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 14.4419%;\"\u003e\n \u003cp\u003eENDES\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 16.3493%;\"\u003e\n \u003cp\u003eDepartment⁷\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 46.7317%;\"\u003e\n \u003cp\u003eDepartment of residence (24 categories).\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 14.4419%;\"\u003e\n \u003cp\u003eENDES\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 16.3493%;\"\u003e\n \u003cp\u003eYear\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 46.7317%;\"\u003e\n \u003cp\u003eSurvey year: 2015\u0026ndash;2018.\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 14.4419%;\"\u003e\n \u003cp\u003eENDES\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003c/tbody\u003e\n\u003c/table\u003e\n\u003cp\u003eNotes:\u003c/p\u003e\n\u003cp\u003e\u0026sup1; Women who at the time of interview were pregnant or reported wanting to become pregnant are excluded from the analytic sample.\u003c/p\u003e\n\u003cp\u003e\u0026sup2; Modern methods include: pill, IUD, injection, implant, male condom, vaginal methods (foam, jelly, suppository), lactational amenorrhea method, emergency contraception, female condom, female sterilization, and male sterilization.\u003c/p\u003e\n\u003cp\u003e\u0026sup3; For details on empowerment index construction, see the Methods section.\u003c/p\u003e\n\u003cp\u003e⁴ Ethnicity is defined by self-identification; \u0026ldquo;Indigenous\u0026rdquo; refers to identifying with a pre-Hispanic Indigenous people. Those identifying as Black/Afro-descendant, moreno, zambo, White, or mestizo are classified as non-Indigenous; this group represents a small share (\u0026lt;1%) and their health indicators more closely resemble the non-Indigenous category.\u003c/p\u003e\n\u003cp\u003e⁵ Permanent limitations include difficulties in: mobility, seeing, hearing, speaking, understanding, and relating to others.\u003c/p\u003e\n\u003cp\u003e⁶ Variables were transformed to per-capita or per-1,000 population terms using INEI population denominators.\u003c/p\u003e\n\u003cp\u003e⁷ The Department of Lima includes the Province of Callao. Peru has 24 departments/regions (first-level subnational unit) and 196 provinces (second-level subnational unit).\u003c/p\u003e\n\u003cp\u003eSource: Authors\u0026rsquo; elaboration.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eTable 2. Prevalence of contraceptive use among partnered women (ENDES/DHS Peru 2015\u0026ndash;2018): modern methods, woman-controlled methods, and couple-controlled methods (%)\u003c/strong\u003e\u003c/p\u003e\n\u003ctable border=\"1\" cellspacing=\"0\" cellpadding=\"0\"\u003e\n \u003ctbody\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\"\u003e\u003cbr\u003e\u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003e\u003cstrong\u003eModern methods (%)\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003e\u003cstrong\u003eWoman-controlled (%)\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003e\u003cstrong\u003eCouple-controlled (%)\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003e\u003cstrong\u003eTotal\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003e60%\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003e44%\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003e39%\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\"\u003e\u003cbr\u003e\u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\u003cbr\u003e\u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\u003cbr\u003e\u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\u003cbr\u003e\u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003e\u003cstrong\u003eAge\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\u003cbr\u003e\u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\u003cbr\u003e\u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\u003cbr\u003e\u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003e15-24\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003e70%\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003e54%\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003e35%\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003e25-34\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003e67%\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003e50%\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003e39%\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003e35-49\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003e51%\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003e37%\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003e39%\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd colspan=\"4\" valign=\"top\"\u003e\n \u003cp\u003e\u003cstrong\u003eEducation (woman)\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003eNo education\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003e40%\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003e36%\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003e32%\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003ePrimary\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003e52%\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003e46%\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003e34%\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003eSecondary\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003e63%\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003e46%\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003e39%\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003eHigher\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003e65%\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003e41%\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003e43%\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd colspan=\"4\" valign=\"top\"\u003e\n \u003cp\u003e\u003cstrong\u003eWoman employed\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003eNo\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003e63%\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003e48%\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003e36%\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003eYes\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003e58%\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003e42%\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003e40%\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd colspan=\"4\" valign=\"top\"\u003e\n \u003cp\u003e\u003cstrong\u003ePartner\u0026rsquo;s education\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003eNo education\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003e47%\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003e44%\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003e22%\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003ePrimary\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003e53%\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003e46%\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003e34%\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003eSecondary\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003e62%\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003e46%\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003e39%\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003eHigher\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003e63%\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003e39%\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003e44%\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd colspan=\"2\" valign=\"top\"\u003e\n \u003cp\u003e\u003cstrong\u003ePartner lives in household\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\u003cbr\u003e\u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\u003cbr\u003e\u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003eNo\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003e45%\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003e34%\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003e31%\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003eYes\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003e62%\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003e45%\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003e39%\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd colspan=\"2\" valign=\"top\"\u003e\n \u003cp\u003e\u003cstrong\u003eWealth quintile\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\u003cbr\u003e\u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\u003cbr\u003e\u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003eQuintile 1\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003e52%\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003e46%\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003e34%\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003eQuintile 2\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003e61%\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003e47%\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003e38%\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003eQuintile 3\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003e62%\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003e45%\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003e40%\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003eQuintile 4\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003e64%\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003e41%\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003e42%\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003eQuintile 5\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003e64%\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003e41%\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003e42%\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003e\u003cstrong\u003eArea\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\u003cbr\u003e\u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\u003cbr\u003e\u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\u003cbr\u003e\u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003eUrban\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003e63%\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003e44%\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003e40%\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003eRural\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003e54%\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003e46%\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003e35%\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003e\u003cstrong\u003eIndigenous\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\u003cbr\u003e\u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\u003cbr\u003e\u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\u003cbr\u003e\u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003eNo\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003e62%\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003e45%\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003e39%\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003eYes\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003e42%\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003e37%\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003e37%\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003c/tbody\u003e\n\u003c/table\u003e\n\u003cp\u003eSource: Authors\u0026rsquo; elaboration using ENDES (2015\u0026ndash;2018).\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eTable 3. Average marginal effects of women\u0026rsquo;s empowerment on contraceptive use (ENDES/DHS Peru 2015\u0026ndash;2018): survey-weighted logistic models\u003c/strong\u003e\u003c/p\u003e\n\u003ctable border=\"1\" cellspacing=\"0\" cellpadding=\"0\"\u003e\n \u003ctbody\u003e\n \u003ctr\u003e\n \u003ctd style=\"width: 280px;\"\u003e\n \u003cp\u003e\u003cstrong\u003eVARIABLES\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd colspan=\"2\" style=\"width: 102px;\"\u003e\n \u003cp\u003e\u003cstrong\u003eModern methods\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd colspan=\"2\" style=\"width: 110px;\"\u003e\n \u003cp\u003e\u003cstrong\u003eWoman-controlled\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd colspan=\"2\" style=\"width: 114px;\"\u003e\n \u003cp\u003e\u003cstrong\u003eCouple-controlled\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 280px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 44px;\"\u003e\n \u003cp\u003e\u003cstrong\u003eSig.\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 58px;\"\u003e\n \u003cp\u003e\u003cstrong\u003eEM (%)\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 50px;\"\u003e\n \u003cp\u003e\u003cstrong\u003eSig.\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 60px;\"\u003e\n \u003cp\u003e\u003cstrong\u003eEM (%)\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 49px;\"\u003e\n \u003cp\u003e\u003cstrong\u003eSig.\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 65px;\"\u003e\n \u003cp\u003e\u003cstrong\u003eEM (%)\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 280px;\"\u003e\n \u003cp\u003eIndicator 1: Medium\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 44px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 58px;\"\u003e\n \u003cp\u003e0.20\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 50px;\"\u003e\n \u003cp\u003e*\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 60px;\"\u003e\n \u003cp\u003e2.60\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 49px;\"\u003e\n \u003cp\u003e**\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 65px;\"\u003e\n \u003cp\u003e-3.80\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 280px;\"\u003e\n \u003cp\u003eIndicator 1: High\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 44px;\"\u003e\n \u003cp\u003e**\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 58px;\"\u003e\n \u003cp\u003e-2.20\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 50px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 60px;\"\u003e\n \u003cp\u003e-1.30\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 49px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 65px;\"\u003e\n \u003cp\u003e-1.40\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 280px;\"\u003e\n \u003cp\u003eIndicator 2: Medium\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 44px;\"\u003e\n \u003cp\u003e*\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 58px;\"\u003e\n \u003cp\u003e1.30\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 50px;\"\u003e\n \u003cp\u003e**\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 60px;\"\u003e\n \u003cp\u003e1.30\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 49px;\"\u003e\n \u003cp\u003e**\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 65px;\"\u003e\n \u003cp\u003e-2.10\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 280px;\"\u003e\n \u003cp\u003eIndicator 2: High\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 44px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 58px;\"\u003e\n \u003cp\u003e-0.40\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 50px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 60px;\"\u003e\n \u003cp\u003e1.20\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 49px;\"\u003e\n \u003cp\u003e***\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 65px;\"\u003e\n \u003cp\u003e-5.80\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 280px;\"\u003e\n \u003cp\u003eIndicator 3: Medium\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 44px;\"\u003e\n \u003cp\u003e***\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 58px;\"\u003e\n \u003cp\u003e3.10\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 50px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 60px;\"\u003e\n \u003cp\u003e0.40\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 49px;\"\u003e\n \u003cp\u003e**\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 65px;\"\u003e\n \u003cp\u003e4.10\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 280px;\"\u003e\n \u003cp\u003eIndicator 3: High\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 44px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 58px;\"\u003e\n \u003cp\u003e1.30\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 50px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 60px;\"\u003e\n \u003cp\u003e-1.60\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 49px;\"\u003e\n \u003cp\u003e***\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 65px;\"\u003e\n \u003cp\u003e4.90\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 280px;\"\u003e\n \u003cp\u003eIndicator 4: Medium\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 44px;\"\u003e\n \u003cp\u003e***\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 58px;\"\u003e\n \u003cp\u003e5.40\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 50px;\"\u003e\n \u003cp\u003e***\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 60px;\"\u003e\n \u003cp\u003e4.60\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 49px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 65px;\"\u003e\n \u003cp\u003e-0.50\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 280px;\"\u003e\n \u003cp\u003eIndicator 4: High\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 44px;\"\u003e\n \u003cp\u003e***\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 58px;\"\u003e\n \u003cp\u003e7.90\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 50px;\"\u003e\n \u003cp\u003e***\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 60px;\"\u003e\n \u003cp\u003e6.70\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 49px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 65px;\"\u003e\n \u003cp\u003e-1.40\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 280px;\"\u003e\n \u003cp\u003eAge\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 44px;\"\u003e\n \u003cp\u003e***\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 58px;\"\u003e\n \u003cp\u003e2.00\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 50px;\"\u003e\n \u003cp\u003e***\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 60px;\"\u003e\n \u003cp\u003e1.60\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 49px;\"\u003e\n \u003cp\u003e***\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 65px;\"\u003e\n \u003cp\u003e4.00\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 280px;\"\u003e\n \u003cp\u003eAge \u0026times; Age\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 44px;\"\u003e\n \u003cp\u003e***\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 58px;\"\u003e\n \u003cp\u003e0.00\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 50px;\"\u003e\n \u003cp\u003e***\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 60px;\"\u003e\n \u003cp\u003e0.00\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 49px;\"\u003e\n \u003cp\u003e***\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 65px;\"\u003e\n \u003cp\u003e-0.10\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 280px;\"\u003e\n \u003cp\u003eEducation: Primary (ref: none)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 44px;\"\u003e\n \u003cp\u003e**\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 58px;\"\u003e\n \u003cp\u003e6.10\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 50px;\"\u003e\n \u003cp\u003e**\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 60px;\"\u003e\n \u003cp\u003e6.90\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 49px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 65px;\"\u003e\n \u003cp\u003e-1.10\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 280px;\"\u003e\n \u003cp\u003eEducation: Secondary (ref: none)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 44px;\"\u003e\n \u003cp\u003e***\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 58px;\"\u003e\n \u003cp\u003e8.00\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 50px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 60px;\"\u003e\n \u003cp\u003e4.20\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 49px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 65px;\"\u003e\n \u003cp\u003e1.70\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 280px;\"\u003e\n \u003cp\u003eEducation: Higher (ref: none)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 44px;\"\u003e\n \u003cp\u003e***\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 58px;\"\u003e\n \u003cp\u003e9.10\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 50px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 60px;\"\u003e\n \u003cp\u003e3.20\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 49px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 65px;\"\u003e\n \u003cp\u003e1.90\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 280px;\"\u003e\n \u003cp\u003eMarital status (married)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 44px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 58px;\"\u003e\n \u003cp\u003e0.70\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 50px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 60px;\"\u003e\n \u003cp\u003e-0.20\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 49px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 65px;\"\u003e\n \u003cp\u003e0.30\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 280px;\"\u003e\n \u003cp\u003eEmployment\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 44px;\"\u003e\n \u003cp\u003e**\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 58px;\"\u003e\n \u003cp\u003e-1.30\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 50px;\"\u003e\n \u003cp\u003e**\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 60px;\"\u003e\n \u003cp\u003e-1.70\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 49px;\"\u003e\n \u003cp\u003e***\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 65px;\"\u003e\n \u003cp\u003e3.10\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 280px;\"\u003e\n \u003cp\u003eIndigenous\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 44px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 58px;\"\u003e\n \u003cp\u003e3.80\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 50px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 60px;\"\u003e\n \u003cp\u003e0.20\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 49px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 65px;\"\u003e\n \u003cp\u003e1.20\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 280px;\"\u003e\n \u003cp\u003eDisability\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 44px;\"\u003e\n \u003cp\u003e***\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 58px;\"\u003e\n \u003cp\u003e11.30\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 50px;\"\u003e\n \u003cp\u003e*\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 60px;\"\u003e\n \u003cp\u003e7.10\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 49px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 65px;\"\u003e\n \u003cp\u003e0.20\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 280px;\"\u003e\n \u003cp\u003eInsurance: SIS (ref: none)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 44px;\"\u003e\n \u003cp\u003e***\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 58px;\"\u003e\n \u003cp\u003e7.30\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 50px;\"\u003e\n \u003cp\u003e***\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 60px;\"\u003e\n \u003cp\u003e7.70\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 49px;\"\u003e\n \u003cp\u003e***\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 65px;\"\u003e\n \u003cp\u003e-5.40\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 280px;\"\u003e\n \u003cp\u003eInsurance: Other (ref: none)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 44px;\"\u003e\n \u003cp\u003e**\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 58px;\"\u003e\n \u003cp\u003e4.30\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 50px;\"\u003e\n \u003cp\u003e***\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 60px;\"\u003e\n \u003cp\u003e3.20\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 49px;\"\u003e\n \u003cp\u003e**\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 65px;\"\u003e\n \u003cp\u003e-3.70\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 280px;\"\u003e\n \u003cp\u003eHealth status\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 44px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 58px;\"\u003e\n \u003cp\u003e1.10\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 50px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 60px;\"\u003e\n \u003cp\u003e0.70\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 49px;\"\u003e\n \u003cp\u003e**\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 65px;\"\u003e\n \u003cp\u003e-2.60\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 280px;\"\u003e\n \u003cp\u003eNo knowledge\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 44px;\"\u003e\n \u003cp\u003e*\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 58px;\"\u003e\n \u003cp\u003e1.40\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 50px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 60px;\"\u003e\n \u003cp\u003e0.50\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 49px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 65px;\"\u003e\n \u003cp\u003e-0.40\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 280px;\"\u003e\n \u003cp\u003eWealth quintile 2 (ref: 1)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 44px;\"\u003e\n \u003cp\u003e***\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 58px;\"\u003e\n \u003cp\u003e5.60\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 50px;\"\u003e\n \u003cp\u003e**\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 60px;\"\u003e\n \u003cp\u003e3.20\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 49px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 65px;\"\u003e\n \u003cp\u003e0.30\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 280px;\"\u003e\n \u003cp\u003eWealth quintile 3 (ref: 1)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 44px;\"\u003e\n \u003cp\u003e**\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 58px;\"\u003e\n \u003cp\u003e5.20\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 50px;\"\u003e\n \u003cp\u003e*\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 60px;\"\u003e\n \u003cp\u003e3.40\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 49px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 65px;\"\u003e\n \u003cp\u003e0.50\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 280px;\"\u003e\n \u003cp\u003eWealth quintile 4 (ref: 1)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 44px;\"\u003e\n \u003cp\u003e***\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 58px;\"\u003e\n \u003cp\u003e6.40\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 50px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 60px;\"\u003e\n \u003cp\u003e2.20\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 49px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 65px;\"\u003e\n \u003cp\u003e1.20\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 280px;\"\u003e\n \u003cp\u003eWealth quintile 5 (ref: 1)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 44px;\"\u003e\n \u003cp\u003e*\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 58px;\"\u003e\n \u003cp\u003e5.60\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 50px;\"\u003e\n \u003cp\u003e**\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 60px;\"\u003e\n \u003cp\u003e5.40\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 49px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 65px;\"\u003e\n \u003cp\u003e-0.50\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 280px;\"\u003e\n \u003cp\u003eHousehold size\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 44px;\"\u003e\n \u003cp\u003e***\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 58px;\"\u003e\n \u003cp\u003e1.80\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 50px;\"\u003e\n \u003cp\u003e***\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 60px;\"\u003e\n \u003cp\u003e2.20\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 49px;\"\u003e\n \u003cp\u003e***\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 65px;\"\u003e\n \u003cp\u003e-1.40\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 280px;\"\u003e\n \u003cp\u003ePartner\u0026rsquo;s age\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 44px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 58px;\"\u003e\n \u003cp\u003e1.70\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 50px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 60px;\"\u003e\n \u003cp\u003e1.50\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 49px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 65px;\"\u003e\n \u003cp\u003e2.20\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 280px;\"\u003e\n \u003cp\u003ePartner\u0026rsquo;s education: Primary (ref: none)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 44px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 58px;\"\u003e\n \u003cp\u003e-\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 50px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 60px;\"\u003e\n \u003cp\u003e-\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 49px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 65px;\"\u003e\n \u003cp\u003e-\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 280px;\"\u003e\n \u003cp\u003ePartner\u0026rsquo;s education: Secondary (ref: none)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 44px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 58px;\"\u003e\n \u003cp\u003e-\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 50px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 60px;\"\u003e\n \u003cp\u003e-\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 49px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 65px;\"\u003e\n \u003cp\u003e-\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 280px;\"\u003e\n \u003cp\u003ePartner\u0026rsquo;s education: Higher (ref: none)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 44px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 58px;\"\u003e\n \u003cp\u003e-\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 50px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 60px;\"\u003e\n \u003cp\u003e-\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 49px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 65px;\"\u003e\n \u003cp\u003e-\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 280px;\"\u003e\n \u003cp\u003ePartner lives in household\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 44px;\"\u003e\n \u003cp\u003e***\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 58px;\"\u003e\n \u003cp\u003e12.90\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 50px;\"\u003e\n \u003cp\u003e***\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 60px;\"\u003e\n \u003cp\u003e8.60\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 49px;\"\u003e\n \u003cp\u003e***\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 65px;\"\u003e\n \u003cp\u003e11.40\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 280px;\"\u003e\n \u003cp\u003ePublic health expenditure\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 44px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 58px;\"\u003e\n \u003cp\u003e0.00\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 50px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 60px;\"\u003e\n \u003cp\u003e0.00\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 49px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 65px;\"\u003e\n \u003cp\u003e0.00\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 280px;\"\u003e\n \u003cp\u003ePhysicians\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 44px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 58px;\"\u003e\n \u003cp\u003e-3.30\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 50px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 60px;\"\u003e\n \u003cp\u003e0.00\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 49px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 65px;\"\u003e\n \u003cp\u003e-6.30\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 280px;\"\u003e\n \u003cp\u003eNurses\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 44px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 58px;\"\u003e\n \u003cp\u003e1.00\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 50px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 60px;\"\u003e\n \u003cp\u003e-1.20\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 49px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 65px;\"\u003e\n \u003cp\u003e3.10\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 280px;\"\u003e\n \u003cp\u003eHealth facilities\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 44px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 58px;\"\u003e\n \u003cp\u003e-0.20\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 50px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 60px;\"\u003e\n \u003cp\u003e-0.10\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 49px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 65px;\"\u003e\n \u003cp\u003e0.50\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 280px;\"\u003e\n \u003cp\u003eMax facility level II (ref: I)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 44px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 58px;\"\u003e\n \u003cp\u003e3.90\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 50px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 60px;\"\u003e\n \u003cp\u003e3.30\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 49px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 65px;\"\u003e\n \u003cp\u003e-0.80\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 280px;\"\u003e\n \u003cp\u003eMax facility level III (ref: I)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 44px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 58px;\"\u003e\n \u003cp\u003e2.20\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 50px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 60px;\"\u003e\n \u003cp\u003e-1.70\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 49px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 65px;\"\u003e\n \u003cp\u003e3.40\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 280px;\"\u003e\n \u003cp\u003eLack of female staff (barrier)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 44px;\"\u003e\n \u003cp\u003e**\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 58px;\"\u003e\n \u003cp\u003e-2.60\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 50px;\"\u003e\n \u003cp\u003e**\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 60px;\"\u003e\n \u003cp\u003e-3.00\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 49px;\"\u003e\n \u003cp\u003e*\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 65px;\"\u003e\n \u003cp\u003e1.60\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 280px;\"\u003e\n \u003cp\u003eDistance (barrier)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 44px;\"\u003e\n \u003cp\u003e**\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 58px;\"\u003e\n \u003cp\u003e-2.80\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 50px;\"\u003e\n \u003cp\u003e**\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 60px;\"\u003e\n \u003cp\u003e-2.10\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 49px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 65px;\"\u003e\n \u003cp\u003e0.10\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 280px;\"\u003e\n \u003cp\u003eUrban area\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 44px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 58px;\"\u003e\n \u003cp\u003e-0.60\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 50px;\"\u003e\n \u003cp\u003e**\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 60px;\"\u003e\n \u003cp\u003e-3.50\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 49px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 65px;\"\u003e\n \u003cp\u003e2.90\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 280px;\"\u003e\n \u003cp\u003eNatural region FE\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 44px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 58px;\"\u003e\n \u003cp\u003eYes\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 50px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 60px;\"\u003e\n \u003cp\u003eYes\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 49px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 65px;\"\u003e\n \u003cp\u003eYes\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 280px;\"\u003e\n \u003cp\u003eDepartment FE\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 44px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 58px;\"\u003e\n \u003cp\u003eYes\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 50px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 60px;\"\u003e\n \u003cp\u003eYes\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 49px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 65px;\"\u003e\n \u003cp\u003eYes\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 280px;\"\u003e\n \u003cp\u003eYear FE\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 44px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 58px;\"\u003e\n \u003cp\u003eYes\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 50px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 60px;\"\u003e\n \u003cp\u003eYes\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 49px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 65px;\"\u003e\n \u003cp\u003eYes\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 280px;\"\u003e\n \u003cp\u003eAME = average marginal effect (percentage points).\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 44px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 58px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 50px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 60px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 49px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 65px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 280px;\"\u003e\n \u003cp\u003e*** p\u0026lt;0.01, ** p\u0026lt;0.05, * p\u0026lt;0.10.\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\" style=\"width: 44px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 58px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 50px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 60px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 49px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 65px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003c/tbody\u003e\n\u003c/table\u003e\n\u003cp\u003e\u003cstrong\u003eTable 4. Psychometric properties of empowerment indices (ENDES/DHS Peru 2015\u0026ndash;2018): Cronbach\u0026rsquo;s alpha and variance explained (PCA)\u003c/strong\u003e\u003c/p\u003e\n\u003ctable border=\"1\" cellspacing=\"0\" cellpadding=\"0\" width=\"100%\" class=\"fr-table-selection-hover\"\u003e\n \u003ctbody\u003e\n \u003ctr\u003e\n \u003ctd colspan=\"6\" valign=\"top\" style=\"width: 100px;\"\u003e\n \u003cp\u003e\u003cstrong\u003eIndicator 1: Decision-making over household resources\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 36px;\"\u003e\u003cbr\u003e\u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 11px;\"\u003e\n \u003cp\u003e\u003cstrong\u003e2015\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 11px;\"\u003e\n \u003cp\u003e\u003cstrong\u003e2016\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 11px;\"\u003e\n \u003cp\u003e\u003cstrong\u003e2017\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 12px;\"\u003e\n \u003cp\u003e\u003cstrong\u003e2018\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 15px;\"\u003e\n \u003cp\u003e\u003cstrong\u003e2015-2018\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 36px;\"\u003e\n \u003cp\u003eMean\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 11px;\"\u003e\n \u003cp\u003e0.00\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 11px;\"\u003e\n \u003cp\u003e0.02\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 11px;\"\u003e\n \u003cp\u003e0.02\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 12px;\"\u003e\n \u003cp\u003e0.03\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 15px;\"\u003e\n \u003cp\u003e0.02\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 36px;\"\u003e\n \u003cp\u003eStandard deviation\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 11px;\"\u003e\n \u003cp\u003e1.04\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 11px;\"\u003e\n \u003cp\u003e1.02\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 11px;\"\u003e\n \u003cp\u003e1.01\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 12px;\"\u003e\n \u003cp\u003e0.96\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 15px;\"\u003e\n \u003cp\u003e1.02\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 36px;\"\u003e\n \u003cp\u003eMinimum\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 11px;\"\u003e\n \u003cp\u003e-2.01\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 11px;\"\u003e\n \u003cp\u003e-2.01\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 11px;\"\u003e\n \u003cp\u003e-2.01\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 12px;\"\u003e\n \u003cp\u003e-2.01\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 15px;\"\u003e\n \u003cp\u003e-2.01\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 36px;\"\u003e\n \u003cp\u003eMaximum\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 11px;\"\u003e\n \u003cp\u003e2.69\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 11px;\"\u003e\n \u003cp\u003e2.69\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 11px;\"\u003e\n \u003cp\u003e2.69\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 12px;\"\u003e\n \u003cp\u003e2.69\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 15px;\"\u003e\n \u003cp\u003e2.69\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 36px;\"\u003e\n \u003cp\u003eObservations\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\" style=\"width: 11px;\"\u003e\n \u003cp\u003e8440\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\" style=\"width: 11px;\"\u003e\n \u003cp\u003e8286\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\" style=\"width: 11px;\"\u003e\n \u003cp\u003e8545\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\" style=\"width: 12px;\"\u003e\n \u003cp\u003e4183\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\" style=\"width: 15px;\"\u003e\n \u003cp\u003e29454\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 36px;\"\u003e\n \u003cp\u003eCronbach\u0026rsquo;s alpha\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\" style=\"width: 11px;\"\u003e\n \u003cp\u003e0.30\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\" style=\"width: 11px;\"\u003e\n \u003cp\u003e0.31\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\" style=\"width: 11px;\"\u003e\n \u003cp\u003e0.28\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\" style=\"width: 12px;\"\u003e\n \u003cp\u003e0.24\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\" style=\"width: 15px;\"\u003e\n \u003cp\u003e0.29\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd colspan=\"2\" valign=\"top\" style=\"width: 48px;\"\u003e\n \u003cp\u003eVariance explained\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 11px;\"\u003e\u003cbr\u003e\u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 11px;\"\u003e\u003cbr\u003e\u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 12px;\"\u003e\u003cbr\u003e\u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 15px;\"\u003e\n \u003cp\u003e0.42\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 36px;\"\u003e\u003cbr\u003e\u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 11px;\"\u003e\u003cbr\u003e\u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 11px;\"\u003e\u003cbr\u003e\u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 11px;\"\u003e\u003cbr\u003e\u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 12px;\"\u003e\u003cbr\u003e\u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 15px;\"\u003e\u003cbr\u003e\u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd colspan=\"3\" valign=\"top\" style=\"width: 60px;\"\u003e\n \u003cp\u003e\u003cstrong\u003eIndicator 2: Freedom of movement\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 11px;\"\u003e\u003cbr\u003e\u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 12px;\"\u003e\u003cbr\u003e\u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 15px;\"\u003e\u003cbr\u003e\u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 36px;\"\u003e\u003cbr\u003e\u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 11px;\"\u003e\n \u003cp\u003e\u003cstrong\u003e2015\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 11px;\"\u003e\n \u003cp\u003e\u003cstrong\u003e2016\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 11px;\"\u003e\n \u003cp\u003e\u003cstrong\u003e2017\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 12px;\"\u003e\n \u003cp\u003e\u003cstrong\u003e2018\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 15px;\"\u003e\n \u003cp\u003e\u003cstrong\u003e2015-2018\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 36px;\"\u003e\n \u003cp\u003eMean\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\" style=\"width: 11px;\"\u003e\n \u003cp\u003e-0.08\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\" style=\"width: 11px;\"\u003e\n \u003cp\u003e-0.01\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\" style=\"width: 11px;\"\u003e\n \u003cp\u003e-0.01\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\" style=\"width: 12px;\"\u003e\n \u003cp\u003e0.13\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\" style=\"width: 15px;\"\u003e\n \u003cp\u003e-0.01\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 36px;\"\u003e\n \u003cp\u003eStandard deviation\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\" style=\"width: 11px;\"\u003e\n \u003cp\u003e1.04\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\" style=\"width: 11px;\"\u003e\n \u003cp\u003e0.99\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\" style=\"width: 11px;\"\u003e\n \u003cp\u003e1.01\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\" style=\"width: 12px;\"\u003e\n \u003cp\u003e0.94\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\" style=\"width: 15px;\"\u003e\n \u003cp\u003e1.00\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 36px;\"\u003e\n \u003cp\u003eMinimum\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\" style=\"width: 11px;\"\u003e\n \u003cp\u003e-3.34\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\" style=\"width: 11px;\"\u003e\n \u003cp\u003e-3.34\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\" style=\"width: 11px;\"\u003e\n \u003cp\u003e-3.34\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\" style=\"width: 12px;\"\u003e\n \u003cp\u003e-3.34\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\" style=\"width: 15px;\"\u003e\n \u003cp\u003e-3.34\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 36px;\"\u003e\n \u003cp\u003eMaximum\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\" style=\"width: 11px;\"\u003e\n \u003cp\u003e0.59\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\" style=\"width: 11px;\"\u003e\n \u003cp\u003e0.59\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\" style=\"width: 11px;\"\u003e\n \u003cp\u003e0.59\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\" style=\"width: 12px;\"\u003e\n \u003cp\u003e0.59\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\" style=\"width: 15px;\"\u003e\n \u003cp\u003e0.59\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 36px;\"\u003e\n \u003cp\u003eObservations\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\" style=\"width: 11px;\"\u003e\n \u003cp\u003e8440\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\" style=\"width: 11px;\"\u003e\n \u003cp\u003e8286\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\" style=\"width: 11px;\"\u003e\n \u003cp\u003e8545\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\" style=\"width: 12px;\"\u003e\n \u003cp\u003e4183\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\" style=\"width: 15px;\"\u003e\n \u003cp\u003e29454\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 36px;\"\u003e\n \u003cp\u003eCronbach\u0026rsquo;s alpha\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\" style=\"width: 11px;\"\u003e\n \u003cp\u003e0.34\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\" style=\"width: 11px;\"\u003e\n \u003cp\u003e0.34\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\" style=\"width: 11px;\"\u003e\n \u003cp\u003e0.34\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\" style=\"width: 12px;\"\u003e\n \u003cp\u003e0.32\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\" style=\"width: 15px;\"\u003e\n \u003cp\u003e0.34\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd colspan=\"2\" valign=\"top\" style=\"width: 48px;\"\u003e\n \u003cp\u003eVariance explained\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 11px;\"\u003e\u003cbr\u003e\u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 11px;\"\u003e\u003cbr\u003e\u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 12px;\"\u003e\u003cbr\u003e\u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 15px;\"\u003e\n \u003cp\u003e0.44\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 36px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 11px;\"\u003e\u003cbr\u003e\u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 11px;\"\u003e\u003cbr\u003e\u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 11px;\"\u003e\u003cbr\u003e\u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 12px;\"\u003e\u003cbr\u003e\u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 15px;\"\u003e\u003cbr\u003e\u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd colspan=\"5\" valign=\"top\" style=\"width: 85px;\"\u003e\n \u003cp\u003e\u003cstrong\u003eIndicator 3: Partner respect for opinions, desires, and rights\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 15px;\"\u003e\u003cbr\u003e\u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 36px;\"\u003e\u003cbr\u003e\u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 11px;\"\u003e\n \u003cp\u003e\u003cstrong\u003e2015\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 11px;\"\u003e\n \u003cp\u003e\u003cstrong\u003e2016\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 11px;\"\u003e\n \u003cp\u003e\u003cstrong\u003e2017\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 12px;\"\u003e\n \u003cp\u003e\u003cstrong\u003e2018\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 15px;\"\u003e\n \u003cp\u003e\u003cstrong\u003e2015-2018\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 36px;\"\u003e\n \u003cp\u003eMean\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\" style=\"width: 11px;\"\u003e\n \u003cp\u003e0.02\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\" style=\"width: 11px;\"\u003e\n \u003cp\u003e0.04\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\" style=\"width: 11px;\"\u003e\n \u003cp\u003e0.05\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\" style=\"width: 12px;\"\u003e\n \u003cp\u003e-0.01\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\" style=\"width: 15px;\"\u003e\n \u003cp\u003e0.03\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 36px;\"\u003e\n \u003cp\u003eStandard deviation\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\" style=\"width: 11px;\"\u003e\n \u003cp\u003e0.98\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\" style=\"width: 11px;\"\u003e\n \u003cp\u003e0.98\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\" style=\"width: 11px;\"\u003e\n \u003cp\u003e0.97\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\" style=\"width: 12px;\"\u003e\n \u003cp\u003e1.01\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\" style=\"width: 15px;\"\u003e\n \u003cp\u003e0.98\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 36px;\"\u003e\n \u003cp\u003eMinimum\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\" style=\"width: 11px;\"\u003e\n \u003cp\u003e-3.68\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\" style=\"width: 11px;\"\u003e\n \u003cp\u003e-3.68\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\" style=\"width: 11px;\"\u003e\n \u003cp\u003e-3.68\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\" style=\"width: 12px;\"\u003e\n \u003cp\u003e-3.68\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\" style=\"width: 15px;\"\u003e\n \u003cp\u003e-3.68\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 36px;\"\u003e\n \u003cp\u003eMaximum\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\" style=\"width: 11px;\"\u003e\n \u003cp\u003e0.68\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\" style=\"width: 11px;\"\u003e\n \u003cp\u003e0.68\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\" style=\"width: 11px;\"\u003e\n \u003cp\u003e0.68\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\" style=\"width: 12px;\"\u003e\n \u003cp\u003e0.68\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\" style=\"width: 15px;\"\u003e\n \u003cp\u003e0.68\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 36px;\"\u003e\n \u003cp\u003eObservations\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\" style=\"width: 11px;\"\u003e\n \u003cp\u003e8440\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\" style=\"width: 11px;\"\u003e\n \u003cp\u003e8286\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\" style=\"width: 11px;\"\u003e\n \u003cp\u003e8545\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\" style=\"width: 12px;\"\u003e\n \u003cp\u003e4183\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\" style=\"width: 15px;\"\u003e\n \u003cp\u003e29454\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 36px;\"\u003e\n \u003cp\u003eCronbach\u0026rsquo;s alpha\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\" style=\"width: 11px;\"\u003e\n \u003cp\u003e0.83\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\" style=\"width: 11px;\"\u003e\n \u003cp\u003e0.83\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\" style=\"width: 11px;\"\u003e\n \u003cp\u003e0.84\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\" style=\"width: 12px;\"\u003e\n \u003cp\u003e0.85\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\" style=\"width: 15px;\"\u003e\n \u003cp\u003e0.84\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd colspan=\"2\" valign=\"top\" style=\"width: 48px;\"\u003e\n \u003cp\u003eVariance explained\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 11px;\"\u003e\u003cbr\u003e\u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 11px;\"\u003e\u003cbr\u003e\u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 12px;\"\u003e\u003cbr\u003e\u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 15px;\"\u003e\n \u003cp\u003e0.76\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003c/tbody\u003e\n\u003c/table\u003e\n\u003cp\u003eSource: Authors\u0026rsquo; elaboration.\u003c/p\u003e"}],"fulltextSource":"","fullText":"","funders":[],"hasAdminPriorityOnWorkflow":false,"hasManuscriptDocX":true,"hasOptedInToPreprint":true,"hasPassedJournalQc":"","hasAnyPriority":true,"hideJournal":true,"highlight":"","institution":"","isAcceptedByJournal":false,"isAuthorSuppliedPdf":false,"isDeskRejected":"","isHiddenFromSearch":false,"isInQc":false,"isInWorkflow":false,"isPdf":false,"isPdfUpToDate":true,"isWithdrawnOrRetracted":false,"journal":{"display":true,"email":"[email protected]","identity":"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":"Women’s empowerment, Contraception, Decision-making, Reproductive health services, DHS, Peru","lastPublishedDoi":"10.21203/rs.3.rs-8818438/v1","lastPublishedDoiUrl":"https://doi.org/10.21203/rs.3.rs-8818438/v1","license":{"name":"CC BY 4.0","url":"https://creativecommons.org/licenses/by/4.0/"},"manuscriptAbstract":"\u003cp\u003e\u003cstrong\u003eBackground: \u003c/strong\u003eWomen’s empowerment may shape contraceptive choices through intra-household bargaining and the degree of coordination a method requires. We examined how distinct empowerment dimensions relate to the locus of contraceptive decision (female-controlled vs couple-controlled methods) and to modern method use among partnered Peruvian women.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eMethods: \u003c/strong\u003eWe conducted an analytic cross-sectional study using nationally representative ENDES/DHS microdata (2015–2018) for women aged 15–49 in union (N=27 440; pregnant women and those desiring pregnancy were excluded). Four empowerment indicators were analyzed: (1) decision over household resources, (2) freedom of movement, (3) partner’s respect for the woman’s opinions/desires/rights, and (4) decision over own health. The first three indices were built via PCA, standardized, and split into terciles; “health decision” was a three-level item (partner alone / joint / woman alone). Survey-weighted logistic models reported average marginal effects (percentage points), adjusting for individual and household characteristics, sexual and reproductive health supply conditions (e.g., service density, perceived distance, availability of female staff), and year and department fixed effects.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eResults: \u003c/strong\u003eDecision over one’s own health shows consistent associations: medium and high levels increase modern method use by approximately 5–8 p.p. and woman-controlled methods by approximately 5–7 p.p. Partner’s respect is especially associated with jointly controlled methods (approximately 4–5 p.p.) and, to a lesser extent, with modern methods overall (approximately 3 p.p.). Freedom of movement exhibits small, positive associations concentrated at intermediate levels. The household-resources indicator is weak and unstable. Supply-side coefficients display expected directions: better availability and shorter perceived distance are associated with greater contraceptive use.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eConclusions: \u003c/strong\u003eEmpowerment domains map onto specific contraceptive margins: clinical autonomy shifts use toward female-controlled methods, while partner respect favors couple-controlled choices. Counseling and service organization should incorporate women’s empowerment profiles, expand self-administered options, and strengthen couple communication to support informed, preferred method use.\u003c/p\u003e","manuscriptTitle":"Women's empowerment, locus of contraceptive decision-making, and modern contraceptive use in Peru","msid":"","msnumber":"","nonDraftVersions":[{"code":1,"date":"2026-02-16 09:21:11","doi":"10.21203/rs.3.rs-8818438/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":"57372257-6bb3-43bb-a454-e96eed7e02cf","owner":[],"postedDate":"February 16th, 2026","published":true,"recentEditorialEvents":[],"rejectedJournal":[],"revision":"","amendment":"","status":"posted","subjectAreas":[],"tags":[],"updatedAt":"2026-03-17T11:24:48+00:00","versionOfRecord":[],"versionCreatedAt":"2026-02-16 09:21:11","video":"","vorDoi":"","vorDoiUrl":"","workflowStages":[]},"version":"v1","identity":"rs-8818438","journalConfig":"researchsquare"},"__N_SSP":true},"page":"/article/[identity]/[[...version]]","query":{"redirect":"/article/rs-8818438","identity":"rs-8818438","version":["v1"]},"buildId":"XKTyCvWXoU3ODBz1xrDgd","isFallback":false,"isExperimentalCompile":false,"dynamicIds":[84888],"gssp":true,"scriptLoader":[]}