Effect of women access to land on household nutritional outcomes in smallholder production system: application of heterogeneous treatment effects

PurposeLand is an emotive issue for women in Kenya, majority of who still suffer the consequences of not having access to land, leading to economic insecurity. This paper aims at examining the effects of women access to land on household nutritional outcomes among smallholder farmers in Kenya.Design/methodology/approachThe study uses primary data collected from a sample of 384 small-scale women farmers selected using multi-stage sampling technique. For data analysis, household nutritional outcomes were measured using Households Dietary Diversity Scores (HDDS) and Household Hunger Scale Scores (HHS). Stratification multilevel and matching-smoothing approach that controls for pre-treatment heterogeneity bias and treatment effect heterogeneity bias was used in estimating heterogeneous effects of women access to land.FindingsThe analysis reveals that women access to land has a significant positive effect on household nutritional outcomes. All households across all propensity scores strata benefited significantly but differently from women access to land in terms of nutritional outcomes.Research limitations/implicationsEconometrically, propensity matching technique used in computing heterogeneity effects captures selection bias due to observable characteristics but it fails to capture selection bias due to unobservable factors. However, robust strategies were employed to ensure minimal estimation bias.Originality/valueThe paper provides insights on the determinants of women access to land and the influence women access to land has on household nutritional outcomes. In addition, by employing one of the conventional impact evaluation techniques, the paper contributes to knowledge by taking into accounts the heterogeneity in the effects of women access to land on household nutritional outcomes.

Aesthetic Parameters and Patient-Perspective Tools for Maxillary Anterior Single Implants’ Assessment

Background. This review aimed to concisely describe the current aesthetic objective indices for a single-implant maxillary anterior crown. The secondary aim was to propose introducing a unified, standardized questionnaire for adequately collecting patient-reported outcome measures (PROMs) in implant dentistry. Materials and Methods. A literature review was conducted using both EMBASE/Ovid and MEDLINE/PubMed databases by combining keywords and Emtree/Mesh terms related to “Esthetics,” “Self-Assessment or Surveys and Questionnaires,” and “Single-Tooth Dental Implants.” Results. The most meaningful aesthetic objective indices for single implants in the literature are the Pink Esthetic Score (PES), the Papilla Presence Index (PPI), Peri‐Implant and Crown Index (PICI), PES/White Esthetic Score (PES/WES), the Implant Crown Aesthetic Index (ICAI), and a modified version of the ICAI (mod-ICAI) index. Clearly, PES/WES is still the most widely accepted tool. It is encouraging to observe that there is an increasing tendency in recent years to report PROMs more frequently in the implant dentistry literature. We proposed the implementation of a unified, standardized questionnaire using a self-administered visual analogue scale (VAS) scoring system, which evaluates overall satisfaction, comfort, tooth appearance, gingival appearance, function, and hygiene complexity. This tool should be validated in the oral implantology research context for its regular implementation or further development. Conclusions. Conducting qualitative studies among dental implant patients who received few implants or single-tooth implant reconstructions in the aesthetic zone may help dental researchers understand better how to efficiently develop and validate a quantitative instrument. This standard tool would reduce heterogeneity bias by providing comparable data between studies.

Global assessment of how averaging over spatial heterogeneity in precipitation and potential evapotranspiration affects modeled evapotranspiration rates

Accurately estimating large-scale evapotranspiration (ET) rates is essential to understanding and predicting global change. Evapotranspiration models that are applied at a continental scale typically operate on relatively large spatial grids, with the result that the heterogeneity in land surface properties and processes at smaller spatial scales cannot be explicitly represented. Averaging over this spatial heterogeneity may lead to biased estimates of energy and water fluxes. Here we estimate how averaging over spatial heterogeneity in precipitation (P) and potential evapotranspiration (PET) may affect grid-cell-averaged evapotranspiration rates, as seen from the atmosphere over heterogeneous landscapes across the globe. Our goal is to identify where, under what conditions, and at what scales this “heterogeneity bias” could be most important but not to quantify its absolute magnitude. We use Budyko curves as simple functions that relate ET to precipitation and potential evapotranspiration. Because the relationships driving ET are nonlinear, averaging over subgrid heterogeneity in P and PET will lead to biased estimates of average ET. We examine the global distribution of this bias, its scale dependence, and its sensitivity to variations in P vs. PET. Our analysis shows that this heterogeneity bias is more pronounced in mountainous terrain, in landscapes where spatial variations in P and PET are inversely correlated, and in regions with temperate climates and dry summers. We also show that this heterogeneity bias increases on average, and expands over larger areas, as the grid cell size increases.

Global assessment of how averaging over land-surface heterogeneity affects modeled evapotranspiration rates

The major goal of large-scale Earth System Models (ESMs) is to understand and predict global change. However, computational constraints require ESMs to operate on relatively large spatial grids (typically ~1 degree or ~100 km in size) with the result that the heterogeneity in land surface properties and processes at smaller spatial scales cannot be explicitly represented. Averaging over this spatial heterogeneity may lead to biased estimates of energy and water fluxes in ESMs. For example, evapotranspiration rates and the properties that regulate them are spatially heterogeneous at scales orders of magnitude smaller than typical ESM grid cells. Here we quantify the effects of spatial heterogeneity on grid-cell-averaged evapotranspiration (ET) rates, as seen from the atmosphere over heterogeneous landscapes across the globe. In an earlier study, we used a Budyko framework to functionally relate ET to precipitation (P) and potential evapotranspiration (PET), and used a sub-grid closure relation to quantify the effects of sub-grid heterogeneity on average ET at 1° by 1° grid cells- the scale of typical ESM. We showed that because the relationships driving ET are nonlinear, averaging over sub-grid heterogeneity in P and PET leads to overestimation of average ET. In this study, we extend that work to the globe and examine the global distribution of this bias, its scale dependence, and the underlying mechanisms. Our analysis shows that this heterogeneity bias is more pronounced in mountainous terrain, in landscapes where P is inversely correlated with PET, and in regions with temperate climates and dry summers. We also show that the magnitude of this heterogeneity bias grows on average, and expands over larger areas, as the size of the grid cell increases. Correcting for this overestimation of ET in ESMs is important for modeling the water cycle, as well as for future temperature predictions, since current overestimations of ET rates imply smaller sensible heat fluxes, and potential underestimation of dry and warm conditions in the context of climate change. Our work provides a basis for translating the heterogeneity bias into correction factors in large-scale ESMs, and highlights the regions where more detailed mechanistic modeling is needed.