Gender disparities on food consumption patterns among coastal community with climate change experience in Sabak Bernam, Selangor

This study explores gender-related differences in food consumption across eight food categories: (1) carbohydrates (cereals, grains, roots, and tubers), (2) legumes, pulses, nuts, and seeds, (3) dairy, (4) protein sources (meat, fish, and eggs), (5) vegetables and leaves, (6) fruits, (7) oils, fats, and butter, and (8) sugar and sweets. The analysis is based on three demographic variables: the gender of the respondent, the gender of the household head, and the gender composition of household members. The study also aims to identify significant predictors of poor female-headed households based on food consumption patterns. Data were collected through purposive sampling from 274 households in Sabak Bernam, a coastal district in Malaysia known for its active fisheries and aquaculture activities. The district contributes significantly to Malaysia’s coastal economy, with the locals engaged throughout the fisheries value chain. This study focuses on 226 valid responses from individuals who reported experiencing climate change-related events. Independent samples t-tests and one-way ANOVA were used to assess mean differences in Food Consumption Scores (FCS) across the gender-related variables. Significant differences were found in the consumption of vegetables, fruits, and oils. Females consumed more vegetables (FCS = 6.17) and oil (FCS = 3.08) than males (FCS = 5.25 and 2.68, respectively). Conversely, fruit consumption was lower among males (FCS = 3.27) than females (FCS = 4.10). Significant differences were also found in the consumption of legumes, nuts, and seeds based on household headship. Female-headed households reported lower consumption (FCS = 0.98) than male-headed households (FCS = 3.78). For other food categories, including meat, fish, and eggs, no significant differences were observed, suggesting a level of dietary homogeneity across households regardless of gender possibly influenced by affordability, availability, or cultural food norms. A binary logistic regression model was used to predict the likelihood of a household being poor and female-headed. The model was statistically significant (p < 0.05), explaining 19.6% of the variance. Two significant predictors emerged: the FCS for legumes, nuts, and seeds (OR = 0.711) and the number of male household members (OR = 0.577). Each unit increase in legume consumption reduced the odds of being poor and female-headed by 29%, suggesting these foods may be markers of economic well-being. Additionally, each additional male household member reduced the odds by 42%, implying that male presence may support income generation and contribute to improved food security. These findings underscore the intersection of gender, diet, and economic status, highlighting the need for gender-responsive nutrition and social protection policies in climate-affected coastal communities.

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