Background: An estimated 863 million people-a third of the world's urban population-live in slums, yet there is little information on the disease burden in these settings, particularly regarding chronic preventable diseases.
Methods: From March to May 2012, we conducted a cluster randomized survey to estimate the prevalence of noncommunicable diseases (NCDs) and associated risk factors in a peri-urban shantytown north of Lima, Peru. Field workers administered a questionnaire that included items from the WHO World Health Survey and the WHO STEPS survey of chronic disease risk factors. We used logistic regression to assess the associations of NCDs and related risk factors with age and gender. We accounted for sampling weights and the clustered sampling design using statistical survey methods.
Results: A total of 142 adults were surveyed and had a weighted mean age of 36 years (range 18-81). The most prevalent diseases were depression (12%) and chronic respiratory disease (8%), while lifetime prevalence of cancer, arthritis, myocardial infarction, and diabetes were all less than 5%. Fifteen percent of respondents were hypertensive and the majority (67%) was unaware of their condition. Being overweight or obese was common for both genders (53%), but abdominal obesity was more prevalent in women (54% vs. 10% in men, p < 0.001). Thirty-five percent of men binge drank and 34% reported current smoking; these behaviors were less common among women (4% binge drank, p < 0.001; 8% smoked, p = 0.002). Increasing age was associated with an increased risk of abdominal obesity (Odds Ratio (OR) = 1.04, 95% CI = 1.01, 1.07, p = 0.02), hypertension (OR = 1.06, 95% CI = 1.02, 1.10, p = 0.006), arthritis (OR = 1.07, 95% CI = 1.03, 1.11, p < 0.001) and cancer (OR = 1.13, 95% CI = 1.07, 1.20, p < 0.001) in adjusted models. The prevalences of other NCDs and related risk factors were similar when stratified by age or gender.
Conclusions: This study underlines the important burden of noncommunicable disease in informal settlements in Peru and suggests that prevention and treatment interventions could be optimized according to age and gender.