Associação entre bebidas adoçadas e consumo calórico em refeições na população brasileira.

Nas últimas décadas, tem sido observado o aumento da oferta de bebidas com elevado conteúdo calórico e com grandes quantidades de açúcar de rápida absorção. Essas bebidas adoçadas, cujo consumo tem aumentado no Brasil assim como em outras partes do mundo, são consideradas fatores de risco para obesidade e diabetes. O consumo de bebidas adoçadas pode levar ao balanço energético positivo e consequentemente ao ganho de peso. Essa associação pode ser explicada pelo mecanismo regulatório de compensação de calorias líquidas. Compensação calórica ocorre quando há redução no consumo de calorias provenientes de alimentos sólidos para compensar as calorias líquidas adicionadas à refeição ou dieta. No entanto, não há consenso em relação a evidências da compensação calórica, dificultando a elaboração de recomendações sobre essas bebidas em saúde pública. Razões para a falta de consenso incluem a diversidade de desenhos de estudos, experimentos realizados em ambientes controlados e não reais em relação ao consumo de alimentos e bebidas, e estudos com amostras pequenas ou de conveniência. Esta dissertação estudou a associação entre bebidas adoçadas e consumo calórico, verificando se calorias de bebidas adoçadas são compensadas em refeições realizadas em um ambiente pragmático. Os dados de consumo calórico de 34.003 indivíduos, com idade igual ou superior a dez anos, foram obtidos pelo Inquérito Nacional de Alimentação 2008-2009, em todo território nacional. Os participantes completaram dois registros alimentares, em dias não consecutivos da mesma semana. Foram selecionadas as refeições dos períodos café da manhã, almoço e jantar de cada indivíduo em cada um dos dias. Para cada refeição, foi calculado o valor calórico de alimentos e de bebidas adoçadas consumidos. Para testar a compensação calórica, um modelo de regressão linear multinível com efeitos mistos foi ajustado para analisar cada período. A variável reposta utilizada foi consumo calórico proveniente de alimentos e a variável explicativa foi consumo calórico de bebida adoçada na refeição. Os efeitos intra-indivíduo da bebida adoçada no consumo calórico foram estimados e interpretados. Esses efeitos são considerados não-enviesados pois são controlados pelas características constantes dos indivíduos, tendo assim o indivíduo atuando como seu próprio controle na análise. Covariadas incluídas no modelo foram variáveis da refeição: local, dia da semana, horário, consumo calórico na refeição anterior e intervalo de tempo desde a última refeição; e do indivíduo: sexo, faixa etária, categoria de Índice de Massa Corpórea e quartos de renda per capita. Efeitos aleatórios dos indivíduos e dos domicílios foram incluídos no modelo para melhor estimar a estrutura de erros de dados correlacionados. A compensação calórica foi de 42% para o café da manhã, não houve compensação no almoço e para o jantar, compensação variou de 0 a 22%, tendo interação com quartos de renda per capita. A conclusão desta dissertação é que as bebidas adoçadas não são completamente compensadas em refeições realizadas em ambiente pragmático. Assim, a redução do consumo de bebidas adoçadas em refeições pode ajudar a diminuir o consumo calórico excessivo e levar a um melhor controle do peso em indivíduos.

Enfoque da estatística espacial em modelos dinâmicos de mudança do uso do solo.

O atual nível das mudanças uso do solo causa impactos nas mudanças ambientais globais. Os processos de mudanças do uso e cobertura do solo são processos complexos e não acontecem ao acaso sobre uma região. Geralmente estas mudanças são determinadas localmente, regionalmente ou globalmente por fatores geográficos, ambientais, sociais, econômicos e políticos interagindo em diversas escalas temporais e espaciais. Parte desta complexidade é capturada por modelos de simulação de mudanças do uso e cobertura do solo. Uma etapa do processo de simulação do modelo CLUE-S é a quantificação da influência local dos impulsores de mudança sobre a probabilidade de ocorrência de uma classe de uso do solo. Esta influência local é obtida ajustando um modelo de regressão logística. Um modelo de regressão espacial é proposto como alternativa para selecionar os impulsores de mudanças. Este modelo incorpora a informação da vizinhança espacial existente nos dados que não é considerada na regressão logística. Baseado em um cenário de tendência linear para a demanda agregada do uso do solo, simulações da mudança do uso do solo para a microbacia do Coxim, Mato Grosso do Sul, foram geradas, comparadas e analisadas usando o modelo CLUE-S sob os enfoques da regressão logística e espacial para o período de 2001 a 2011. Ambos os enfoques apresentaram simulações com muito boa concordância, medidas de acurácia global e Kappa altos, com o uso do solo para o ano de referência de 2004. A diferença entre os enfoques foi observada na distribuição espacial da simulação do uso do solo para o ano 2011, sendo o enfoque da regressão espacial que teve a simulação com menor discrepância com a demanda do uso do solo para esse ano.

Linear regression under fixed-rank constraints: A Riemannian approach

In this paper, we tackle the problem of learning a linear regression model whose parameter is a fixed-rank matrix. We study the Riemannian manifold geometry of the set of fixed-rank matrices and develop efficient line-search algorithms. The proposed algorithms have many applications, scale to high-dimensional problems, enjoy local convergence properties and confer a geometric basis to recent contributions on learning fixed-rank matrices. Numerical experiments on benchmarks suggest that the proposed algorithms compete with the state-of-the-art, and that manifold optimization offers a versatile framework for the design of rank-constrained machine learning algorithms. Copyright 2011 by the author(s)/owner(s).

Regression on fixed-rank positive semidefinite matrices: A Riemannian approach

The paper addresses the problem of learning a regression model parameterized by a fixed-rank positive semidefinite matrix. The focus is on the nonlinear nature of the search space and on scalability to high-dimensional problems. The mathematical developments rely on the theory of gradient descent algorithms adapted to the Riemannian geometry that underlies the set of fixedrank positive semidefinite matrices. In contrast with previous contributions in the literature, no restrictions are imposed on the range space of the learned matrix. The resulting algorithms maintain a linear complexity in the problem size and enjoy important invariance properties. We apply the proposed algorithms to the problem of learning a distance function parameterized by a positive semidefinite matrix. Good performance is observed on classical benchmarks. © 2011 Gilles Meyer, Silvere Bonnabel and Rodolphe Sepulchre.

地理信息系统支持下的滑坡灾害空间分析预测-以云南小江流域为例

As a typical geological and environmental hazard, landslide has been causing more and more property and life losses. However, to predict its accurate occurring time is very difficult or even impossible due to landslide's complex nature. It has been realized that it is not a good solution to spend a lot of money to treat with and prevent landslide. The research trend is to study landslide's spatial distribution and predict its potential hazard zone under certain region and certain conditions. GIS(Geographical Information System) is a power tools for data management, spatial analysis based on reasonable spatial models and visualization. It is new and potential study field to do landslide hazard analysis and prediction based on GIS. This paper systematically studies the theory and methods for GIS based landslide hazard analysis. On the basis of project "Mountainous hazard study-landslide and debris flows" supported by Chinese Academy of Sciences and the former study foundation, this paper carries out model research, application, verification and model result analysis. The occurrence of landslide has its triggering factors. Landslide has its special landform and topographical feature which can be identify from field work and remote sensing image (aerial photo). Historical record of landslide is the key to predict the future behaviors of landslide. These are bases for landslide spatial data base construction. Based on the plenty of literatures reviews, the concept framework of model integration and unit combinations is formed. Two types of model, CF multiple regression model and landslide stability and hydrological distribution coupled model are bought forward. CF multiple regression model comes form statistics and possibility theory based on data. Data itself contains the uncertainty and random nature of landslide hazard, so it can be seen as a good method to study and understand landslide's complex feature and mechanics. CF multiple regression model integrates CF (landslide Certainty Factor) and multiple regression prediction model. CF can easily treat with the problems of data quantifying and combination of heteroecious data types. The combination of CF can assist to determine key landslide triggering factors which are then inputted into multiple regression model. CF regression model can provide better prediction results than traditional model. The process of landslide can be described and modeled by suitable physical and mechanical model. Landslide stability and hydrological distribution coupled model is such a physical deterministic model that can be easily used for landslide hazard analysis and prediction. It couples the general limit equilibrium method and hydrological distribution model based on DEM, and can be used as a effective approach to predict the occurrence of landslide under different precipitation conditions as well as landslide mechanics research. It can not only explain pre-existed landslides, but also predict the potential hazard region with environmental conditions changes. Finally, this paper carries out landslide hazard analysis and prediction in Yunnan Xiaojiang watershed, including landslide hazard sensitivity analysis and regression prediction model based on selected key factors, determining the relationship between landslide occurrence possibility and triggering factors. The result of landslide hazard analysis and prediction by coupled model is discussed in details. On the basis of model verification and validation, the modeling results are showing high accuracy and good applying potential in landslide research.

Weighted and two-stage least squares estimation of semiparametric truncated regression models

This paper provides a root-n consistent, asymptotically normal weighted least squares estimator of the coefficients in a truncated regression model. The distribution of the errors is unknown and permits general forms of unknown heteroskedasticity. Also provided is an instrumental variables based two-stage least squares estimator for this model, which can be used when some regressors are endogenous, mismeasured, or otherwise correlated with the errors. A simulation study indicates that the new estimators perform well in finite samples. Our limiting distribution theory includes a new asymptotic trimming result addressing the boundary bias in first-stage density estimation without knowledge of the support boundary. © 2007 Cambridge University Press.

Structured Illumination Microscopy and a Quantitative Image Analysis for the Detection of Positive Margins in a Pre-Clinical Genetically Engineered Mouse Model of Sarcoma.

Intraoperative assessment of surgical margins is critical to ensuring residual tumor does not remain in a patient. Previously, we developed a fluorescence structured illumination microscope (SIM) system with a single-shot field of view (FOV) of 2.1 × 1.6 mm (3.4 mm2) and sub-cellular resolution (4.4 μm). The goal of this study was to test the utility of this technology for the detection of residual disease in a genetically engineered mouse model of sarcoma. Primary soft tissue sarcomas were generated in the hindlimb and after the tumor was surgically removed, the relevant margin was stained with acridine orange (AO), a vital stain that brightly stains cell nuclei and fibrous tissues. The tissues were imaged with the SIM system with the primary goal of visualizing fluorescent features from tumor nuclei. Given the heterogeneity of the background tissue (presence of adipose tissue and muscle), an algorithm known as maximally stable extremal regions (MSER) was optimized and applied to the images to specifically segment nuclear features. A logistic regression model was used to classify a tissue site as positive or negative by calculating area fraction and shape of the segmented features that were present and the resulting receiver operator curve (ROC) was generated by varying the probability threshold. Based on the ROC curves, the model was able to classify tumor and normal tissue with 77% sensitivity and 81% specificity (Youden's index). For an unbiased measure of the model performance, it was applied to a separate validation dataset that resulted in 73% sensitivity and 80% specificity. When this approach was applied to representative whole margins, for a tumor probability threshold of 50%, only 1.2% of all regions from the negative margin exceeded this threshold, while over 14.8% of all regions from the positive margin exceeded this threshold.

Are Fast Responses More Random? Testing the Effect of Response Time on Scale in an Online Choice Experiment

Scepticism over stated preference surveys conducted online revolves around the concerns over “professional respondents” who might rush through the questionnaire without sufficiently considering the information provided. To gain insight on the validity of this phenomenon and test the effect of response time on choice randomness, this study makes use of a recently conducted choice experiment survey on ecological and amenity effects of an offshore windfarm in the UK. The positive relationship between self-rated and inferred attribute attendance and response time is taken as evidence for a link between response time and cognitive effort. Subsequently, the generalised multinomial logit model is employed to test the effect of response time on scale, which indicates the weight of the deterministic relative to the error component in the random utility model. Results show that longer response time increases scale, i.e. decreases choice randomness. This positive scale effect of response time is further found to be non-linear and wear off at some point beyond which extreme response time decreases scale. While response time does not systematically affect welfare estimates, higher response time increases the precision of such estimates. These effects persist when self-reported choice certainty is controlled for. Implications of the results for online stated preference surveys and further research are discussed.

Methods to increase response to postal and electronic questionnaires

Background: Postal and electronic questionnaires are widely used for data collection in epidemiological studies but non-response reduces the effective sample size and can introduce bias. Finding ways to increase response to postal and electronic questionnaires would improve the quality of health research. Objectives: To identify effective strategies to increase response to postal and electronic questionnaires. Search strategy: We searched 14 electronic databases to February 2008 and manually searched the reference lists of relevant trials and reviews, and all issues of two journals. We contacted the authors of all trials or reviews to ask about unpublished trials. Where necessary, we also contacted authors to confirm methods of allocation used and to clarify results presented. We assessed the eligibility of each trial using pre-defined criteria. Selection criteria: Randomised controlled trials of methods to increase response to postal or electronic questionnaires. Data collection and analysis: We extracted data on the trial participants, the intervention, the number randomised to intervention and comparison groups and allocation concealment. For each strategy, we estimated pooled odds ratios (OR) and 95% confidence intervals (CI) in a random-effects model. We assessed evidence for selection bias using Egger's weighted regression method and Begg's rank correlation test and funnel plot. We assessed heterogeneity among trial odds ratios using a Chi 2 test and the degree of inconsistency between trial results was quantified using the I 2 statistic. Main results: Postal We found 481 eligible trials.The trials evaluated 110 different ways of increasing response to postal questionnaires.We found substantial heterogeneity among trial results in half of the strategies. The odds of response were at least doubled using monetary incentives (odds ratio 1.87; 95% CI 1.73 to 2.04; heterogeneity P < 0.00001, I 2 = 84%), recorded delivery (1.76; 95% CI 1.43 to 2.18; P = 0.0001, I 2 = 71%), a teaser on the envelope - e.g. a comment suggesting to participants that they may benefit if they open it (3.08; 95% CI 1.27 to 7.44) and a more interesting questionnaire topic (2.00; 95% CI 1.32 to 3.04; P = 0.06, I 2 = 80%). The odds of response were substantially higher with pre-notification (1.45; 95% CI 1.29 to 1.63; P < 0.00001, I 2 = 89%), follow-up contact (1.35; 95% CI 1.18 to 1.55; P < 0.00001, I 2 = 76%), unconditional incentives (1.61; 1.36 to 1.89; P < 0.00001, I 2 = 88%), shorter questionnaires (1.64; 95%CI 1.43 to 1.87; P < 0.00001, I 2 = 91%), providing a second copy of the questionnaire at follow up (1.46; 95% CI 1.13 to 1.90; P < 0.00001, I 2 = 82%), mentioning an obligation to respond (1.61; 95% CI 1.16 to 2.22; P = 0.98, I 2 = 0%) and university sponsorship (1.32; 95% CI 1.13 to 1.54; P < 0.00001, I 2 = 83%). The odds of response were also increased with non-monetary incentives (1.15; 95% CI 1.08 to 1.22; P < 0.00001, I 2 = 79%), personalised questionnaires (1.14; 95% CI 1.07 to 1.22; P < 0.00001, I 2 = 63%), use of hand-written addresses (1.25; 95% CI 1.08 to 1.45; P = 0.32, I 2 = 14%), use of stamped return envelopes as opposed to franked return envelopes (1.24; 95% CI 1.14 to 1.35; P < 0.00001, I 2 = 69%), an assurance of confidentiality (1.33; 95% CI 1.24 to 1.42) and first class outward mailing (1.11; 95% CI 1.02 to 1.21; P = 0.78, I 2 = 0%). The odds of response were reduced when the questionnaire included questions of a sensitive nature (0.94; 95% CI 0.88 to 1.00; P = 0.51, I 2 = 0%). Electronic: We found 32 eligible trials. The trials evaluated 27 different ways of increasing response to electronic questionnaires. We found substantial heterogeneity among trial results in half of the strategies. The odds of response were increased by more than a half using non-monetary incentives (1.72; 95% CI 1.09 to 2.72; heterogeneity P < 0.00001, I 2 = 95%), shorter e-questionnaires (1.73; 1.40 to 2.13; P = 0.08, I 2 = 68%), including a statement that others had responded (1.52; 95% CI 1.36 to 1.70), and a more interesting topic (1.85; 95% CI 1.52 to 2.26). The odds of response increased by a third using a lottery with immediate notification of results (1.37; 95% CI 1.13 to 1.65), an offer of survey results (1.36; 95% CI 1.15 to 1.61), and using a white background (1.31; 95% CI 1.10 to 1.56). The odds of response were also increased with personalised e-questionnaires (1.24; 95% CI 1.17 to 1.32; P = 0.07, I 2 = 41%), using a simple header (1.23; 95% CI 1.03 to 1.48), using textual representation of response categories (1.19; 95% CI 1.05 to 1.36), and giving a deadline (1.18; 95% CI 1.03 to 1.34). The odds of response tripled when a picture was included in an e-mail (3.05; 95% CI 1.84 to 5.06; P = 0.27, I 2 = 19%). The odds of response were reduced when "Survey" was mentioned in the e-mail subject line (0.81; 95% CI 0.67 to 0.97; P = 0.33, I 2 = 0%), and when the e-mail included a male signature (0.55; 95% CI 0.38 to 0.80; P = 0.96, I 2 = 0%). Authors' conclusions: Health researchers using postal and electronic questionnaires can increase response using the strategies shown to be effective in this systematic review. Copyright © 2009 The Cochrane Collaboration. Published by John Wiley & Sons, Ltd.


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Review and meta-analysis of the short-term effects of a vegetable oil emulsion on food intake

Several short-term studies have investigated the effects of a vegetable oil emulsion on subsequent food intake, although findings have been inconsistent. This work aimed to review all studies, and investigate differences in study outcomes based on methodology. All known studies were identified. Data were abstracted from published studies (n = 7). Details of unpublished studies were gained from investigators/sponsors (n = 5), or were unavailable for reasons of confidentiality (n = 4). Available data were combined using meta-analyses. A combined appetite suppressant effect of the emulsion compared with control was found for test meal intake at approximately 4, 12 and 36 h post-treatment: smallest combined mean difference (random effects model) = 0.53 MJ (95% confidence interval 0.20, 0.86), P < 0.01. However, considerable heterogeneity (variability) between study results was also found (smallest I2 = 94%, P < 0.01), questioning the predictive validity of the above findings. Meta-regression suggested this heterogeneity to be related to differences in the processed nature of the product, treatment dose and in particular year of study (smallest B = 0.54, 95% confidence interval 0.06, 1.03, P = 0.04), although again heterogeneity was found. The only consistent finding was a lack of effect on food intake 4 h post-preload in studies conducted after 2003. These results suggest a small but inconsistent appetite suppressant effect of the vegetable oil emulsion. However, due to the large heterogeneity, no definitive conclusions can be drawn.

Coxiella burnetii (Q fever) seroprevalence in cattle

Human cases of Q fever appear to be common in Northern Ireland compared to the rest of the British Isles. The purpose of this study was to describe the seroepidemiology of Coxiella burnetii infection in cattle in Northern Ireland in terms of seroprevalence and determinants of infection. A total of 5182 animals (from a stratified systematic random sample of 273 herds) were tested with a commercial C. burnetii phase 2 IgG ELISA. A total of 6.2% of animals and 48.4% of herds tested positively. Results from a multilevel logistic regression model indicated that the odds of cattle being infected with Q fever increased with age, Friesian breed, being from large herds and from dairy herds. Large dairy herd animal prevalence was 12.5% compared to 2.1% for small beef herds. Preliminary seroprevalence in sheep (12.3%), goats (9.3%), pigs (0%) rats (9.7%) and mice (3.2%) using indirect immunofluorescence is reported.

DNA double-strand break distributions in X-ray and alpha-particle irradiated V79 cells: Evidence for non-random breakage

Many studies have shown that with increasing LET of ionizing radiation the RBE (relative biological effectiveness) for dsb (double strand breaks) induction remains around 1.0 despite the increase in the RBE for cell killing. This has been attributed to an increase in the complexity of lesions, classified as dsb with current techniques, at multiply damaged sites. This study determines the molecular weight distributions of DNA from Chinese hamster V79 cells irradiated with X-rays or 110 keV/mu m alpha-particles. Two running conditions for pulsed-field gel-electrophoresis were chosen to give optimal separation of fragments either in the 225 kbp-5.7 Mbp range or the 0.3 kbp to 225 kbp range. Taking the total fraction of DNA migrating into the gel as a measure of fragmentation, the RBE for dsb induction was less than 1.0 for both molecular weight regions studied. The total yields of dsb were 8.2 x 10(-9) dsb/Gy/bp for X-rays and 7.8 x 10(-9) dsb/Gy/bp for a-particles, measured using a random breakage model. Analysis of the RBE of alpha-particles versus molecular weight gave a different response. In the 0.4 Mbp-57 Mbp region the RBE was less than 1.0; however, below 0.4 Mbp the RBE increased above 1.0. The frequency distributions of fragment sizes were found to differ from those predicted by a model assuming random breakage along the length of the DNA and the differences were greater for alpha-particles than for X-rays. An excess of fragments induced by a single-hit mechanism was found in the 8-300 kbp region and for X-rays and alpha-particles these corresponded to an extra 0.8 x 10(-9) and 3.4 x 10(-9) dsb/bp/Gy, respectively. Thus for every alpha-particle track that induces a dsb there is a 44% probability of inducing a second break within 300 kbp and for electron tracks the probability is 10%. This study shows that the distribution of damage from a high LET alpha-particle track is significantly different from that observed with low LET X-rays. In particular, it suggests that the fragmentation patterns of irradiated DNA may be related to the higher-order chromatin repealing structures found in intact cells.

A Monte Carlo model of DNA double-strand break clustering and rejoining kinetics for the analysis of pulsed-field gel electrophoresis data

In studies of radiation-induced DNA fragmentation and repair, analytical models may provide rapid and easy-to-use methods to test simple hypotheses regarding the breakage and rejoining mechanisms involved. The random breakage model, according to which lesions are distributed uniformly and independently of each other along the DNA, has been the model most used to describe spatial distribution of radiation-induced DNA damage. Recently several mechanistic approaches have been proposed that model clustered damage to DNA. In general, such approaches focus on the study of initial radiation-induced DNA damage and repair, without considering the effects of additional (unwanted and unavoidable) fragmentation that may take place during the experimental procedures. While most approaches, including measurement of total DNA mass below a specified value, allow for the occurrence of background experimental damage by means of simple subtractive procedures, a more detailed analysis of DNA fragmentation necessitates a more accurate treatment. We have developed a new, relatively simple model of DNA breakage and the resulting rejoining kinetics of broken fragments. Initial radiation-induced DNA damage is simulated using a clustered breakage approach, with three free parameters: the number of independently located clusters, each containing several DNA double-strand breaks (DSBs), the average number of DSBs within a cluster (multiplicity of the cluster), and the maximum allowed radius within which DSBs belonging to the same cluster are distributed. Random breakage is simulated as a special case of the DSB clustering procedure. When the model is applied to the analysis of DNA fragmentation as measured with pulsed-field gel electrophoresis (PFGE), the hypothesis that DSBs in proximity rejoin at a different rate from that of sparse isolated breaks can be tested, since the kinetics of rejoining of fragments of varying size may be followed by means of computer simulations. The problem of how to account for background damage from experimental handling is also carefully considered. We have shown that the conventional procedure of subtracting the background damage from the experimental data may lead to erroneous conclusions during the analysis of both initial fragmentation and DSB rejoining. Despite its relative simplicity, the method presented allows both the quantitative and qualitative description of radiation-induced DNA fragmentation and subsequent rejoining of double-stranded DNA fragments. (C) 2004 by Radiation Research Society.

Self-reported teamwork in family health team practices in Ontario:Organizational and cultural predictors of team climate

Objective: To determine the organizational predictors of higher scores on team climate measures as an indicator of the functioning of a family health team (FHT). Design: Cross-sectional study using a mailed survey. Setting: Family health teams in Ontario. Participants: Twenty-one of 144 consecutively approached FHTs; 628 team members were surveyed. Main outcome measures: Scores on the team climate inventory, which assessed organizational culture type (group, developmental, rational, or hierarchical); leadership perceptions; and organizational factors, such as use of electronic medical records (EMRs), team composition, governance of the FHT, location, meetings, and time since FHT initiation. All analyses were adjusted for clustering of respondents within the FHT using a mixed random-intercepts model. Results: The response rate was 65.8% (413 of 628); 2 were excluded from analysis, for a total of 411 participants. At the time of survey completion, there was a median of 4 physicians, 11 other health professionals, and 4 management and clerical staff per FHT. The average team climate score was 3.8 out of a possible 5. In multivariable regression analysis, leadership score, group and developmental culture types, and use of more EMR capabilities were associated with higher team climate scores. Other organizational factors, such as number of sites and size of group, were not associated with the team climate score. Conclusion: Culture, leadership, and EMR functionality, rather than organizational composition of the teams (eg, number of professionals on staff, practice size), were the most important factors in predicting climate in primary care teams.

Determinants of WTP for Prosecco wine: A latent class regression with attitudinal responses

Purpose – Under investigation is Prosecco wine, a sparkling white wine from North-East Italy.
Information collection on consumer perceptions is particularly relevant when developing market
strategies for wine, especially so when local production and certification of origin play an important
role in the wine market of a given district, as in the case at hand. Investigating and characterizing the
structure of preference heterogeneity become crucial steps in every successful marketing strategy. The
purpose of this paper is to investigate the sources of systematic differences in consumer preferences.
Design/methodology/approach – The paper explores the effect of inclusion of answers to
attitudinal questions in a latent class regression model of stated willingness to pay (WTP) for this
specialty wine. These additional variables were included in the membership equations to investigate
whether they could be of help in the identification of latent classes. The individual specific WTPs from
the sampled respondents were then derived from the best fitting model and examined for consistency.
Findings – The use of answers to attitudinal question in the latent class regression model is found to
improve model fit, thereby helping in the identification of latent classes. The best performing model
obtained makes use of both attitudinal scores and socio-economic covariates identifying five latent
classes. A reasonable pattern of differences in WTP for Prosecco between CDO and TGI types were
derived from this model.
Originality/value – The approach appears informative and promising: attitudes emerge as
important ancillary indicators of taste differences for specialty wines. This might be of interest per se
and of practical use in market segmentation. If future research shows that these variables can be of use
in other contexts, it is quite possible that more attitudinal questions will be routinely incorporated in
structural latent class hedonic models.