17 research outputs found

    Sitting time (minutes/day) trend among adults aged 20–69 years in Mexico City.

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    <p>Mexican Nutrition and Health Survey 2006 and Mexico City Diabetes Representative Survey 2015.</p

    Crude and adjusted odds ratios (OR) of being in the highest sitting category (≥ 420 minutes/day), MCDRS, Mexico City, 2015.

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    <p>Crude and adjusted odds ratios (OR) of being in the highest sitting category (≥ 420 minutes/day), MCDRS, Mexico City, 2015.</p

    Sitting time (minutes/day) trends among adults aged 20–69 years in Mexico City by sociodemographic factors<sup>♦</sup>.

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    <p>Sitting time (minutes/day) trends among adults aged 20–69 years in Mexico City by sociodemographic factors<a href="http://www.plosone.org/article/info:doi/10.1371/journal.pone.0188518#t002fn002" target="_blank"><sup>♦</sup></a>.</p

    Non-communicable diseases standardized mortality rate per 100,000 Mexican adults from 2005 to 2021.

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    Estimates from binomial regression model adjusted by municipal structure of age, sex, and quintiles of the distribution of male proportion, indigeneity, illiteracy, poverty, population density, density of ultra-processed food, alcohol & tobacco retail stores, households with television, density of hospitals, affiliated with Mexican Institute of Social Security, unaffiliated with health services, mortality rate from causes other than non-communicable diseases, year, and state of the country. Predicted mortality rate was standardized by using the structure of age of 2015 for Mexican adults aged 20 years, from CONAPO.</p

    Mortality rate ratios of municipal factors per 100,000 Mexican adults and their association with the standardized mortality rate of non-communicable diseases from 2005 to 2021.

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    Q: quintile. Q1: reference category. IMSS: Mexican Institute of Social Security. NCDs: non-communicable diseases. Estimates from binomial regression model adjusted by municipal structure of age, sex, and quintiles of the distribution of male proportion, indigeneity, illiteracy, poverty, population density, *density of ultra-processed food, alcohol & tobacco retail stores, households with television, density of hospitals, affiliated with IMSS, unaffiliated with health services, mortality rate from causes other than NCDs, year and state of the country. Predicted mortality rate was standardized by using the structure of age of 2015 for Mexican adults aged 20 years, from CONAPO.</p

    S1 Data -

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    BackgroundNon-communicable diseases (NCDs) are the leading causes of mortality in Mexico. Factors contributing to NCDs-related deaths may vary across small geographic areas such as municipalities. We aimed to predict municipal-level factors associated with NCD mortality in Mexican adults from 2005 to 2021 using the small-area analysis (SSA) approach.MethodsWe gathered data on population sociodemographic, access to healthcare services, and mortality records at the municipal-level from census and public institutions from 2005 to 2021. We identified municipal predictors of NCDs mortality rates (MR) using negative binomial regression models.ResultsA total of 584,052 observations of Mexican adults were analyzed. The national expected NCDs MR per 100,000 inhabitants was 210.7 (95%CI: 196.1–226.7) in 2005 and increased to 322.4 (95%CI: 300.3–346.4) by 2021. Predictors of NCDs mortality (quintile 5 vs. quintile 1) included; indigeneity (IRR = 1.15, 95%CI: 1.12–1.19), poverty (IRR = 1.14, 95%CI: 1.13–1.15), affiliation with Mexican Social Security Institute (IRR = 1.11, 95%CI: 1.09–1.14), households with television (IRR = 1.14, 95%CI: 1.11–1.17), and high density of ultra-processed food, alcohol & tobacco retail stores (IRR = 1.15, 95%CI: 1.13–1.17). The greatest increases in MR were observed in municipalities from Oaxaca (>200% increments).ConclusionThere was an overall increase in NCDs MR from 2005 to 2021, with a significant geographic variation among Mexican municipalities. The results of this study highlight the importance of identifying priority areas in the country that urgently require public policies focused on local factors associated with deaths from NCDs, such as the regulation of the ultra-processed food, alcohol & tobacco retail stores, and efforts to reduce social inequalities.</div

    S2 Data -

    No full text
    BackgroundNon-communicable diseases (NCDs) are the leading causes of mortality in Mexico. Factors contributing to NCDs-related deaths may vary across small geographic areas such as municipalities. We aimed to predict municipal-level factors associated with NCD mortality in Mexican adults from 2005 to 2021 using the small-area analysis (SSA) approach.MethodsWe gathered data on population sociodemographic, access to healthcare services, and mortality records at the municipal-level from census and public institutions from 2005 to 2021. We identified municipal predictors of NCDs mortality rates (MR) using negative binomial regression models.ResultsA total of 584,052 observations of Mexican adults were analyzed. The national expected NCDs MR per 100,000 inhabitants was 210.7 (95%CI: 196.1–226.7) in 2005 and increased to 322.4 (95%CI: 300.3–346.4) by 2021. Predictors of NCDs mortality (quintile 5 vs. quintile 1) included; indigeneity (IRR = 1.15, 95%CI: 1.12–1.19), poverty (IRR = 1.14, 95%CI: 1.13–1.15), affiliation with Mexican Social Security Institute (IRR = 1.11, 95%CI: 1.09–1.14), households with television (IRR = 1.14, 95%CI: 1.11–1.17), and high density of ultra-processed food, alcohol & tobacco retail stores (IRR = 1.15, 95%CI: 1.13–1.17). The greatest increases in MR were observed in municipalities from Oaxaca (>200% increments).ConclusionThere was an overall increase in NCDs MR from 2005 to 2021, with a significant geographic variation among Mexican municipalities. The results of this study highlight the importance of identifying priority areas in the country that urgently require public policies focused on local factors associated with deaths from NCDs, such as the regulation of the ultra-processed food, alcohol & tobacco retail stores, and efforts to reduce social inequalities.</div
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